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Understanding the dynamics of fish ecology and movements: implications for management of a temperate estuarine marine park Daniel Edward Yeoh BSc (Hons) Murdoch University This thesis is presented for the degree of Doctor of Philosophy of Murdoch University, Western Australia 2018

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Page 1: Understanding the dynamics of fish ecology and movements ...Understanding the dynamics of fish ecology and movements: implications for management of a temperate estuarine marine park

Understanding the dynamics of fish ecology

and movements: implications for management

of a temperate estuarine marine park

Daniel Edward Yeoh

BSc (Hons) Murdoch University

This thesis is presented for the degree of Doctor of Philosophy of

Murdoch University, Western Australia

2018

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Declaration

I declare that this thesis is my own account of my research and contains as its main

content work which has not previously been submitted for a degree at any tertiary

education institution.

Daniel Edward Yeoh

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I

Abstract

The overarching aim of this study was to provide a detailed ecological understanding of

the fish fauna of a temperate microtidal estuary in south-western Australia (SWA), the

Walpole-Nornalup Marine Park. Located in a global climate change hotspot, this largely

unmodified and permanently-open system is the only marine park on the south coast of

WA. Despite its small size, it has the highest recreational fishing activity in the bioregion,

yet managers lack contemporary understanding of its fish fauna and the ability to detect

limits of acceptable change. A multi-faceted monitoring approach combining surveys of

fish assemblages and acoustic telemetry was used to address the following key objectives:

(1) quantify spatio-temporal shifts in fish faunal composition, (2) assess changes in fish

communities, populations and a fish-based index of ecosystem health since the last

studies in the 1990s, and (3) track the detailed movements of key fishery species. This

study is one of the few globally to characterise fish responses to natural and anthropogenic

drivers at the individual, population, community and ecosystem levels.

Various structural and functional attributes of fish assemblages were examined

throughout the system between day and night, seasons and years from July 2014–May

2016. Forty-seven species from 29 families were recorded, placing this estuary among

the most diverse in the region. Marine-associated species, many of fishery importance,

dominated the composition. Most ichthyofaunal attributes differed between estuarine

regions, day–night, seasons and years, reflecting mainly habitat preferences or, in the case

of diel patterns, changes in fish activity and predator–prey interactions.

Since the 1990s, marine and warmer-water species have increased in abundance, while

larger benthic species have decreased. Size declines in fishery species were also detected.

Ecological health of the deeper waters has deteriorated over time, while the reverse

occurred in the shallows. These findings likely reflect the effects of accelerated warming

and drying of the climate, combined with increased fishing activity.

Acoustic tracking of Acanthopagrus butcheri, Chrysophrys auratus, Rhabdosargus sarba

(Sparidae) and Platycephalus speculator (Platycephalidae) revealed marked differences

in their estuarine-marine connectivity, intra-estuarine use and mobility. Drivers of these

patterns, which were mixed among species, principally reflected spawning behaviours,

habitat preferences, feeding modes and responses to water temperature and freshwater

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flow. This is the first multi-species tracking study in a SWA estuary, and highlights their

divergent estuarine use, vulnerability to fishing and shifts in niche overlap likely to occur

with further climate change.

The multiple fish assessment techniques at a range of organisational levels presented here

provide a major contribution towards the refinement of robust faunal monitoring regimes,

which are currently lacking in Australian estuarine management. Such regimes, combined

with sound data on the environmental and social pressures on estuaries, are imperative

for the effective management of estuarine ecosystems and their fisheries.

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Contents

ABSTRACT ..................................................................................................................... I

CONTENTS .................................................................................................................. III

LIST OF FIGURES ..................................................................................................... VI

LIST OF TABLES .................................................................................................... XIII

ACKNOWLEDGEMENTS ....................................................................................... XVI

CHAPTER 1: GENERAL INTRODUCTION ............................................................. 1

1.1 THE ESTUARINE ENVIRONMENT ................................................................................ 1 1.2 FISHES IN ESTUARIES ................................................................................................ 2

1.3 ESTUARIES AND HUMANS: USES AND IMPACTS ......................................................... 3 1.4 MANAGEMENT OF ESTUARIES AND THEIR FISH STOCKS ............................................ 5 1.4 ESTUARIES OF SOUTH-WESTERN AUSTRALIA ............................................................ 7 1.5 WALPOLE-NORNALUP ESTUARY ............................................................................ 10

1.6 STUDY RATIONALE, OBJECTIVES AND THESIS STRUCTURE ...................................... 11

CHAPTER 2: HIERARCHICAL ENVIRONMENTAL FILTERS SHAPING THE

FISH FAUNA OF THE WALPOLE-NORNALUP ESTUARY ............................... 13

2.1 INTRODUCTION ....................................................................................................... 13

2.2 METHODS ............................................................................................................... 17 2.2.1 Study area ...................................................................................................... 17 2.2.2 Fish faunal sampling ...................................................................................... 18

2.2.3 Measurement of water quality parameters .................................................... 20 2.2.4 Data analyses ................................................................................................. 20

2.3 RESULTS ................................................................................................................. 23 2.3.1 Physico-chemical water variables ................................................................. 23 2.3.2 Overall fish species abundances and guilds .................................................. 25

2.3.3 Regional, seasonal and interannual differences in nearshore fish

communities ............................................................................................................ 31

2.3.4 Regional, seasonal and interannual differences in offshore fish communities

................................................................................................................................. 39

2.4 DISCUSSION ............................................................................................................ 44 2.4.1 How does the fish faunal diversity of the Walpole-Nornalup compare with

that of other south-western Australian estuaries in different bioregions and with

different mouth states? ............................................................................................ 44 2.4.2 How do intra-estuarine habitat filters shape the fish fauna of the Walpole-

Nornalup Estuary? .................................................................................................. 51 2.4.3 How do environmental influences drive seasonal and interannual changes in

the fish fauna of the Walpole-Nornalup Estuary? .................................................. 54 2.4.4 The importance of the estuary as a nursery for marine species, and

particularly those of fishery importance ................................................................. 57

2.4.5 Conclusions .................................................................................................... 58

CHAPTER 3: DIEL SHIFTS IN THE STRUCTURE AND FUNCTION OF

NEARSHORE FISH COMMUNITIES ...................................................................... 60

3.1 INTRODUCTION ....................................................................................................... 60

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3.2 METHODS ............................................................................................................... 65 3.2.1 Study area ...................................................................................................... 65 3.2.2 Field sampling ................................................................................................ 65 3.2.3 Data analyses ................................................................................................. 66

3.3 RESULTS ................................................................................................................. 69 3.3.1 Diel changes in water quality parameters ..................................................... 69 3.3.2 Diel changes in total species abundances ...................................................... 69 3.3.3 Diel changes in fish abundance, species richness and taxonomic distinctness

................................................................................................................................. 71

3.3.4 Diel changes in species, guild and size composition ..................................... 72 3.4 DISCUSSION ............................................................................................................ 76

3.4.1 Diel changes in fish abundance, species richness and taxonomic distinctness

................................................................................................................................. 78 3.4.2 Diel shifts in species composition .................................................................. 79 3.4.3 Diel shifts in functional guild and size composition ...................................... 80 3.4.4 Further work and recommendations .............................................................. 81

CHAPTER 4: INTERDECADAL CHANGES IN THE FISH FAUNA AND

ECOSYSTEM HEALTH OF THE WALPOLE-NORNALUP ESTUARY, AND

THEIR POTENTIAL ENVIRONMENTAL AND SOCIAL DRIVERS ................. 84

4.1 INTRODUCTION ....................................................................................................... 84

4.2 METHODS ............................................................................................................... 88 4.2.1 Collection of fish community data ................................................................. 88

4.2.2 Collection of environmental data ................................................................... 89

4.2.3 Data analyses ................................................................................................. 90

4.3 RESULTS ................................................................................................................. 97 4.3.1 Interdecadal changes in climatic conditions and estuarine water quality .... 97 4.3.2 Interdecadal changes in fish faunal composition ........................................ 102

4.3.3 Interdecadal changes in ecosystem health ................................................... 114 4.3.4 Interdecadal changes in the length composition of fishery important species

............................................................................................................................... 118 4.4 DISCUSSION .......................................................................................................... 123

4.4.1 Has marinisation and tropicalisation of the Walpole-Nornalup Estuary

occurred since the early 1990s? ........................................................................... 123

4.4.2 Has the ecological health of the Walpole-Nornalup Estuary declined over the

past 25 years? ....................................................................................................... 125

4.4.3 Have changes in the abundance and population size structure of key fishery

species occurred since the 1990s? ........................................................................ 128 4.4.4 Summary, implications and recommendations ............................................ 131

CHAPTER 5: RESIDENCY AND MOVEMENT PATTERNS OF FOUR KEY

FISHERY SPECIES IN THE WALPOLE-NORNALUP ESTUARY ................... 134

5.1 INTRODUCTION ..................................................................................................... 134 5.2 METHODS ............................................................................................................. 137

5.2.1 Acoustic array design ................................................................................... 137 5.2.2 Fish collection and tagging .......................................................................... 139 5.2.3 Range testing of acoustic telemetry equipment ............................................ 140

5.2.4 Collation of environmental and habitat data ............................................... 140

5.2.5 Data analyses ............................................................................................... 141

5.3 RESULTS ............................................................................................................... 145

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5.3.1 Summary of all individuals tracked ............................................................. 145 5.3.2 Estuarine-marine connectivity ..................................................................... 147 5.3.3 Intra-estuarine area use ............................................................................... 148 5.3.3 Level of movement throughout the estuary .................................................. 159

5.3.4 Influences of environmental and biological factors on temporal changes in

residency and intra-estuarine distribution ............................................................ 160 5.4 DISCUSSION .......................................................................................................... 171

5.4.1 Estuarine dependence and connectivity with the marine environment ........ 172 5.4.2 Intra-estuarine habitat use and drivers of distribution ................................ 174

5.4.3 Site fidelity and mobility .............................................................................. 178 5.4.4 Niche overlap and potential future shifts ..................................................... 179 5.4.5 Implications for fisheries management ........................................................ 180

5.4.6 Limitations and recommendations ............................................................... 181

CHAPTER 6: GENERAL DISCUSSION ................................................................. 182

6.1 INDIVIDUAL TO ECOSYSTEM-LEVEL APPROACHES FOR MONITORING ESTUARINE FISH

FAUNA ........................................................................................................................ 184

6.2 IMPLICATIONS AND FUTURE DIRECTIONS FOR MANAGEMENT OF THE WALPOLE-

NORNALUP INLETS MARINE PARK ............................................................................. 187 6.2.1 Ecological and social values, their threats and potential future changes ... 187 6.2.2 Management recommendations ................................................................... 189

6.2.3 Future monitoring plan ................................................................................ 190 6.3 CONCLUDING REMARKS ....................................................................................... 195

APPENDICES ............................................................................................................. 196

REFERENCES ............................................................................................................ 219

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List of Figures

Figure 1.1 (a) Map of south-western Australia showing the location of estuaries and their

major tributaries (adapted with permission from Hallett et al., 2018). Estuary

types are designated on the basis of their connectivity with the sea. (b) Satellite

image of the Walpole-Nornalup Estuary (denoted by bold text in [a]). ............. 8

Figure 2.1 Conceptual model of the major environmental filters that shape local estuarine

fish composition from the global species pool. Blue shaded area represents the

relative number of species at each spatial scale. Natural environmental

influences on these filters are represented in green boxes and arrows, and

anthropogenic influences are denoted by red boxes and arrows. ...................... 14

Figure 2.2 Location of each nearshore and offshore fish sampling site throughout the five

study regions of the Walpole-Nornalup Estuary. .............................................. 19

Figure 2.3 Mean ± SE (a) temperature (°C) recorded in the nearshore waters of each

region during each sampling season, and (b) mean salinity and (c) dissolved

oxygen content (mg L−1) recorded during each season and year. Regions; Deep

River (◼) Frankland River (◼), Walpole Inlet (◼), Upper Nornalup (◼) and

Lower Nornalup (◼). Seasons; winter (W), spring (Sp) summer (S) and autumn

(A). NB, no measurements recorded during Sp2, and also A2 in the case of

dissolved oxygen. .............................................................................................. 26

Figure 2.4 Mean ± SE (a) temperature (°C) recorded in the offshore waters in each region

during summer (S) and winter (W), and (b) salinity, and (c) dissolved oxygen

concentration (mg L−1), recorded at the surface () and bottom (◼) of the water

column in those waters during summer and winter of each sampling year (1, 2).

Regions, LN; Lower Nornalup, UN; Upper Nornalup, WI; Walpole Inlet, FR;

Frankland River. ............................................................................................... 27

Figure 2.5 Proportion of species in the nearshore (NS) and offshore (OS) waters in each

estuarine usage guild (a), feeding mode guild (b) and habitat guild (c). Guild

abbreviations are given in Table 2.1. ................................................................ 30

Figure 2.6 Mean number (± SE) of (a) individuals and (b) species recorded on each

sampling occasion within each season of the first (◼) and second () year of

sampling, and the mean (± SE) (c) number of species and (d) average taxonomic

distinctness recorded on each sampling occasion within each region. Regions;

Deep River (DR) Frankland River (FR), Walpole Inlet (WI), Upper Nornalup

(UN) and Lower Nornalup (LN). Seasons; winter (W), spring (Sp) summer (S)

and autumn (A). ................................................................................................ 31

Figure 2.7 nMDS ordination plot constructed from the centroids of the nearshore species

composition recorded in (a) each region × season combination and (b) each

season in each year. Trajectories indicate the temporal order of sampling.

Regions; Deep River () Frankland River (), Walpole Inlet (), Upper

Nornalup (◆) and Lower Nornalup (◼). Seasons; winter (W), spring (Sp)

summer (S) and autumn (A). Years; 2014–15 (solid); 2015–16 (dashed). ....... 33

Figure 2.8 Shade plot of the pre-treated abundances of the most prevalent nearshore fish

species in each estuarine region, season and sampling year of sampling. Regions;

Deep River (DR) Frankland River (FR), Walpole Inlet (WI), Upper Nornalup

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(UN) and Lower Nornalup (LN). Seasons; winter (W), spring (Sp) summer (S)

and autumn (A). Years; 2014–15 (black); 2015–16 (magenta). Spawning

locations; marine (marine stragglers and marine estuarine-opportunists; ),

estuarine (estuarine & marine and solely estuarine species; ) and freshwater

(freshwater migrants; ). ................................................................................. 33

Figure 2.9 Proportions of (a) each estuarine usage guild recorded in each region and

season, and (b) year, (c) each feeding mode guild recorded in each region and

season, and (d) year, and (e) each habitat guild recorded in each region and

season, and (f) season and year. Estuarine usage guilds; freshwater migrant

(FM), estuarine species (ES), estuarine & marine (EM), marine estuarine-

opportunist (MEO) and marine straggler (MS). Feeding mode guilds;

zooplanktivore (ZP), zoobenthivore (ZB), piscivore (PV), omnivore (OV),

opportunist (OP) and detritivore (DV). Habitat guilds; small pelagic (SP), small

benthic (SB), pelagic (P), demersal (D) and bentho-pelagic (BP). ................... 37

Figure 2.10 Mean number (± SE) of fish h−1 recorded in the offshore waters of each

region of the Walpole-Nornalup Estuary (Lower Nornalup; LN, Upper

Nornalup; UN, Walpole Inlet; WI and Frankland River; FR). ......................... 39

Figure 2.11 Shade plot of the pre-treated abundances of each fish species recorded within

the offshore waters of each region, i.e. Lower Nornalup (LN), Upper Nornalup

(UN), Walpole Inlet (WI) and Frankland River (FR). ...................................... 41

Figure 2.12 Proportions of (a) each estuarine usage guild recorded in each region and

season, and (b) year, (c) each feeding mode guild recorded in each region and

season, and (d) season and year, and (e) each habitat guild recorded in each

region. Estuarine usage guilds; estuarine species (ES), estuarine & marine

(EM), marine estuarine-opportunist (MEO) and marine straggler (MS). Feeding

mode guilds; zooplanktivore (ZP), zoobenthivore (ZB), piscivore (PV),

omnivore (OV), opportunist (OP) and detritivore (DV). Habitat guilds; small

pelagic (SP), pelagic (P), demersal (D) and bentho-pelagic (BP). .................. 43

Figure 2.13 Average taxonomic distinctness (Δ+) of the fish fauna recorded in the

Leschenault (L), Peel-Harvey (PH) and Swan-Canning (S) estuaries on the

lower-west coast of WA (open symbols), and in the Broke (BR), Wilson (WS),

Irwin (IW), Oyster Harbour (OY), Walpole-Nornalup (WN) and Wellstead

(WE) estuaries on the south coast of WA (closed symbols). Mouth-states; (◆)

permanently open, (◆) seasonally open, (◆) normally closed. Data sources for

estuaries other than the Walpole-Nornalup are given in Table 2.4................... 47

Figure 2.14 Proportion of species in each estuarine usage guild in the nearshore and

offshore waters of Walpole-Nornalup Estuary (WN), Oyster Harbour (OY),

Broke Inlet (BR), Irwin Inlet (IW), Wilson Inlet (WS) and Wellstead Estuary

(WE) on the south coast of Western Australia. Estuarine usage guilds; freshwater

migrant (FM), estuarine species (ES), estuarine and marine (EM), marine

estuarine-opportunist (MEO), marine straggler (MS). Data for estuaries other

than WN were obtained from Chuwen et al. (2009b) and Hoeksema et al. (2009).

........................................................................................................................... 47

Figure 2.15 Monthly mean (±SE) (a) maximum and (b) minimum air temperatures and

(c) total monthly rainfall recorded in the Walpole region, and (d) total monthly

river flow recorded in the upper Frankland River, during the first year of

sampling (May 2014 to April 2015; ◼) and the second (May 2015 to April 2016;

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). Temperature and rainfall data recorded at Bureau of Meteorology stations

009998 and 009611, respectively (http://www.bom.gov.au/climate/data/), and

flow data recorded at the Department of Water Mount Frankland flow station

(ID 605012; www.kumina.water.wa.gov.au).................................................... 56

Figure 3.1 Location of the four study regions in the Walpole-Nornalup Estuary. ,

sampling sites. ................................................................................................... 65

Figure 3.2 Relative proportions of each species recorded during the day (light grey) and

night (dark grey) and the total number of individuals caught. Only species where

≥10 individuals were recorded are shown. ....................................................... 71

Figure 3.3 (a) Mean number of individuals recorded during the day and night in each

season, and (b) mean number of species and (c) mean taxonomic distinctness

recorded during the day and night. Standard errors bars are provided for all

means. ............................................................................................................... 72

Figure 3.4 Centroid nMDS ordination plots constructed from Bray-Curtis similarity

matrices of pre-treated mean (a) species abundances and (b) feeding mode guilds

during the day () and night () in each season. ........................................... 73

Figure 3.5 Shade plot illustrating the pre-treated abundances of the most prevalent fish

species during the day and night in each season, with shading intensity being

proportional to abundance. Species are ordered by a hierarchical cluster analysis

of their mutual associations across dielseason groups. Dashed lines in the

dendrogram indicate species with significantly similar patterns of abundance, as

detected by SIMPROF. Habitat guilds H, i.e. small pelagic (SP), small benthic

(SB), pelagic (P), demersal (D), bentho-pelagic (BP) and feeding guilds F, i.e.

zooplanktivore (ZP), zoobenthivore (ZB), piscivore (PV), omnivore (OV),

opportunist (OP), detritivore (DV), are given for each species. ....................... 73

Figure 3.6 Proportions of each feeding guild during the day (light grey) and night (dark

grey) in (a) spring, (b) summer, (c) autumn and (d) winter. Zooplanktivore (ZP),

zoobenthivore (ZB), piscivore (PV), omnivore (OV), opportunist (OP),

detritivore (DV). Proportions are based on pre-treated data, and the total number

of individuals in each guild and season is also provided. ................................. 74

Figure 3.7 Proportions of each habitat guild during the day (light grey) and night (dark

grey) based on pre-treated data. Small pelagic (SP), small benthic (SB), pelagic

(P), demersal (D), bentho-pelagic (BP). The total number of individuals in each

guild is also provided. ....................................................................................... 75

Figure 3.8 Proportions of each size class recorded during the day (light grey) and night

(dark grey), (a) across all seasons and regions, and in (b) spring, (c) summer, (d)

autumn and (e) winter. The total number of individuals in each size class is also

provided. ........................................................................................................... 76

Figure 3.9 Conceptual diagram of major day-night shifts in the fish, benthic invertebrate

and bird faunas of the Walpole-Nornalup Estuary. White text indicates attributes

of the fish assemblages that typically increased in the nearshore waters in each

diel period (Images courtesy of the Integration and Application Network,

University of Maryland Center for Environmental Science

[ian.umces.edu/symbols/]). ............................................................................... 77

Figure 4.1 Location of each nearshore and offshore site at which fish were sampled in

the Walpole-Nornalup Estuary in 1989─90 (Potter & Hyndes, 1994) and

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2013─17. Abbreviations for each sampling region as used in the text are given

in parentheses. ................................................................................................... 89

Figure 4.2 Long-term trends in (a) total annual rainfall in Walpole, (b) total annual flow

in the Frankland River, (c) total annual flow in the Deep River, (d) mean monthly

maximum air temperatures at Cape Leeuwin and (e) mean monthly minimum air

temperatures at Cape Leeuwin. Horizontal green line represents the long-term

average of each variable (i.e. from 1952 to 2015 for plots a, b, d, e; 1976 to 2015

for plot c) and grey bars show annual anomalies. Blue line indicates a 10 year

average of each climate variable (across years prior). Light blue shading

corresponds to the interdecadal fish sampling period. ...................................... 99

Figure 4.3 Rolling average across ten years prior of (a) total annual rainfall in Walpole,

(b) total annual flow in the Frankland River, (c) total annual flow in the Deep

River, (d) mean monthly maximum air temperatures at Cape Leeuwin and (e)

mean monthly minimum air temperatures at Cape Leeuwin, in each season from

1988 to 2015. .................................................................................................. 100

Figure 4.4 (a) Mean (±SE) temperature (°C) recorded in the shallow nearshore waters of

the Walpole-Nornalup Estuary seasonally during 1989–90 and 2014–16. (b)

Mean (±SE) salinity recorded seasonally in those waters during 1989–90, 2014–

15 and 2015–16. Seasons; winter (W), spring (Sp), summer (S) and autumn (A).

......................................................................................................................... 101

Figure 4.5 Mean (±SE) (a) temperature (°C) and (b) salinity recorded in the deeper

offshore waters of the Walpole-Nornalup Estuary during winter (W), spring

(Sp), summer (S) and autumn (A) of 1989–90 and 2013–17. ........................ 101

Figure 4.6 Average taxonomic distinctness (∆+) of the nearshore fish fauna in the

Walpole–Nornalup Estuary during 1989–90 (open symbols) and 2014–16

(closed symbols) within: (a) each region (averaged over seasons) and (b) each

season (averaged over regions). Contours represent limits within which 95% of

simulated ∆+ values lie, and dashed lines indicate mean ∆+. .......................... 106

Figure 4.7 nMDS ordination plot constructed from the Bray-Curtis resemblance matrix

of nearshore species composition of the Walpole-Nornalup Estuary (a)

bootstrapped to create averages for each region and (b) employing the distance

among centroid averages of each season, during 1989–90 (), 2014–15 () and

2015–16 (). Regions; Walpole Inlet (WI; ◼), Upper Nornalup (UN; ◼) and

Lower Nornalup (LN; ◼). Seasons; winter (W), spring (Sp) summer (S) and

autumn (A). Trajectories show temporal order of sampling and shaded areas on

Fig. 4.7a represent approximate 95% confidence boundaries. (c) Shade plot of

the pre-treated abundances of each species during 1989–90 and 2014–16 in each

region and season, with shading intensity being proportional to abundance.

Species in Fig. 4.7c are ordered by a hierarchical cluster analysis of their mutual

associations across groups and dashed lines in the dendrogram indicate species

with significantly similar patterns of abundance, as detected by SIMPROF. 107

Figure 4.8 Proportions of each (a) estuarine usage, (b) habitat and (c) feeding mode guild

recorded in the nearshore waters of the Walpole-Nornalup Estuary during 1989–

90 and 2014–16 in each region (across all seasons) and each season (across all

regions). Regions; Lower Nornalup (LN), Upper Nornalup (UN) and Walpole

Inlet (WI). Seasons; winter (W), spring (Sp) summer (S) and autumn (A). See

Table 4.4 for guild abbreviations. ................................................................... 109

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Figure 4.9 (a) Average taxonomic distinctness (∆+) of the fish fauna in the offshore

waters of each region of the Walpole–Nornalup Estuary during 1989–90 (open

symbols) and 2013–17 (closed symbols). Contours represent limits within which

95% of simulated ∆+ values lie, and dashed lines indicate mean ∆+. (b) nMDS

ordination plot constructed from the (Bray-Curtis) bootstrapped averages of

offshore species composition in each region of the estuary during 1989–90 and

2013–17. Shaded areas represent approximate 95% confidence boundaries and

trajectories show temporal order of sampling. Regions; Frankland River (),

Walpole Inlet (◆), Upper Nornalup (◼), Lower Nornalup (). ................... 111

Figure 4.10 Shade plot of the pre-treated abundances of fish species recorded in the

offshore waters of each region of the Walpole-Nornalup Estuary during 1989–

90 and 2013–17, with shading intensity being proportional to abundance. Only

species are ordered by a hierarchical cluster analysis of their mutual associations

across groups. Dashed lines in the dendrogram indicate species with

significantly similar patterns of abundance, as detected by SIMPROF.......... 112

Figure 4.11 Proportions of each (a) estuarine usage guild and (b) feeding mode guild

recorded in the offshore waters during 1989–90 and 2013–17. (c) Proportions of

each habitat guild recorded in each region during 1989–90 and 2013–17.

Regions; Lower Nornalup (LN), Upper Nornalup (UN), Walpole Inlet (WI) and

Frankland River (FR). See Table 4.4 for guild abbreviations......................... 113

Figure 4.12 Mean (±SE) Fish Community Index (FCI) scores and grades (shading)

recorded in the nearshore waters of the Walpole-Nornalup Estuary during the

historical (1989–90) and contemporary (2014‒16) sampling periods within (a)

each region and (b) each season...................................................................... 116

Figure 4.13 Average scores of each FCI metric recorded throughout the nearshore waters

of the Walpole-Nornalup Estuary during the historical (1989–90) and

contemporary (2014‒16) sampling periods within (a) each region and (b) each

season. See Table 4.2 for full metric names. .................................................. 116

Figure 4.14 Mean (±SE) Fish Community Index (FCI) scores and grades (shading)

recorded in the offshore waters of the Walpole-Nornalup Estuary during the

historical (1989–90) and contemporary (2013‒17) sampling periods within (a)

each region and (b) each season...................................................................... 117

Figure 4.15 Average scores of each FCI metric recorded throughout the offshore waters

of the Walpole-Nornalup Estuary during the historical (1989–90) and

contemporary (2013‒17) sampling periods within (a) each region and (b) each

season. See Table 4.2 for full metric names. .................................................. 117

Figure 4.16 Mean (±SE) Fish Community Index (FCI) scores recorded in each the

nearshore and offshore waters of the Walpole-Nornalup Estuary across all

regions and seasons during the historical (1989–90) and contemporary (2014–

16/2013–17) sampling periods. ....................................................................... 118

Figure 4.17 (a) Length-frequency (total length; TL) plots of Acanthopagrus butcheri from

both the nearshore and offshore waters of the Walpole-Nornalup Estuary during

the historical (1989–96) and contemporary (2013–16) sampling periods. (b)

kernel density estimates (KDEs) of the lengths of A. butcheri caught in the

nearshore waters and (c) the offshore waters during each period. Light blue

shaded area represents the null model of the average length-distribution from

both periods (±SE), and indicates no significant difference in density. Dashed

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vertical lines indicate the minimum legal length for capture and retention of this

species in Western Australia. .......................................................................... 120

Figure 4.18 (a) Length-frequency (total length; TL) plots and (b) kernel density estimates

(KDEs) of Arripis georgianus recorded during the historical (1989–90) and

contemporary (2013–16) sampling periods. Light blue shaded area represents

the null model of the average length-distribution from both periods (±SE), and

indicates no significant difference in density.................................................. 121

Figure 4.19 (a) Length-frequency (total length; TL) plots and (b) kernel density estimates

(KDEs) of Sillaginodes punctatus recorded during the historical (1989–90) and

contemporary (2013–16) sampling periods. Light blue shaded area represents

the null model of the average length-distribution from both periods (±SE), and

indicates no significant difference in density. Dashed vertical line indicates the

minimum legal length for capture and retention of this species in Western

Australia. ......................................................................................................... 122

Figure 4.20 Shade plot of the (square-root transformed) abundances of each fish species

in catches from gill nets set overnight in the offshore waters of each region of

the Walpole-Nornalup Estuary during autumn in 1990 and 2017. ................. 128

Figure 4.21 Conceptual diagram of climate-related changes in the environment and fish

fauna of the Walpole-Nornalup Estuary between the early 1990s and mid-2010s.

......................................................................................................................... 131

Figure 5.1 Location of acoustic receiver stations ( ) deployed in the Walpole-Nornalup

Estuary. See Table 5.1 for station characteristics. .......................................... 138

Figure 5.2 (a) Daily presence of tagged (a) Acanthopagrus butcheri, (b) Platycephalus

speculator, (c) Chrysophrys auratus and (d) Rhabdosargus sarba at receivers in

the basin (◼) and riverine (◼) reaches of the Walpole-Nornalup Estuary for all

or some of the period between July 2014 and February 2017. (◼) denotes

detections at the mouth of the estuary, () denotes fish reported as caught by

recreational fishers and ( ) denotes fish likely to have been caught based upon

visual examination of tracking data. ............................................................... 153

Figure 5.3 Total proportion of time that individuals of (a) Acanthopagrus butcheri, (b)

Platycephalus speculator, (c) Chrysophrys auratus and (d) Rhabdosargus sarba

spent in the Upper Frankland River (UFR), Lower Frankland River (LFR),

Walpole Inlet (WI), Nornalup Inlet (NI) and the marine environment. (e) Mean

(±SE) proportion of time that each species spent in each region and the total

proportion of individuals that visited each region .......................................... 154

Figure 5.4 Average residency of Acanthopagrus butcheri, Platycephalus speculator,

Chrysophrys auratus and Rhabdosargus sarba at each acoustic receiver station

() throughout the Walpole-Nornalup Estuary over the monitoring period.

Station names are given in Fig. 5.1 (section 5.2). ........................................... 155

Figure 5.5 Mean (±SE) residency of each study species in deep and shallow waters (≥1.5

m or <1.5 m average depth, respectively), areas with prominent rock or reef

present or absent, and in areas with prominent wooden structure present or

absent. ............................................................................................................. 155

Figure 5.6 Station residency of each of the 22 tagged Acanthopagrus butcheri. Yellow

triangles denote the nearest station to the location at which each individual was

released. Station names are given in Fig. 5.1 (section 5.2) ............................. 156

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Figure 5.7 Station residency of each of the 19 tagged Platycephalus speculator. Yellow

triangles denote the nearest station to the location at which each individual was

released. Station names are given in Fig. 5.1 (section 5.2). ............................ 157

Figure 5.8 Station residency of (a) each of the 9 tagged Chrysophrys auratus and (b) each

of the 8 tagged Rhabdosargus sarba. Yellow triangles denote the nearest station

to the location at which each individual was released. Station names are given in

Fig. 5.1 (section 5.2). ...................................................................................... 158

Figure 5.9 Mean (±SE) monthly (a) number of stations visited and (b) minimum linear

distance travelled by individuals of each study species from August 2015 to

January 2016. .................................................................................................. 159

Figure 5.10 Relationship between the total length (mm) and average daily linear distance

travelled by individuals of each study species. ............................................... 160

Figure 5.11 (a) Mean weekly water temperature throughout the Walpole-Nornalup

Estuary and mean freshwater flow in the upper Frankland River between August

2014 and August 2016. Average weekly (b) station residency indices (RI) and

(c) location upstream from the estuary mouth (±SE; blue shading) of

Acanthopagrus butcheri. Note, station LFR1 was missing for part of April and

May 2016. ....................................................................................................... 161

Figure 5.12 Predicted weekly residency of Acanthopagrus butcheri as estimated by the

best two mixed effects models (#1 and 2) in Table 5.4. Shaded areas represent

confidence limits. ............................................................................................ 162

Figure 5.13 Predicted (a) daily and (b) weekly distance upstream of Acanthopagrus

butcheri in each month and under various environmental conditions as estimated

by the best models in Table 5.5. Error bars and shaded areas represent SE. .. 164

Figure 5.14 Average weekly (a) station residency indices (RI) and (b) location upstream

from the estuary mouth (±SE; blue shading) of Platycephalus speculator

between December 2014 and August 2016. ................................................... 165

Figure 5.15 Average weekly (a) station residency indices (RI) and (b) location upstream

from the estuary mouth (±SE; blue shading) of Chrysophrys auratus between

August 2015 and April 2016. .......................................................................... 167

Figure 5.16 The predicted weekly distance upstream of individuals of Chrysophrys

auratus (a) during each month of the year from August to January, and (b) in

relation to weeks since tagging, as estimated by the best fit mixed effects models,

#1 and #2, respectively, in Table 5.8. Error bars and shaded areas represent SE.

......................................................................................................................... 169

Figure 5.17 Average weekly (a) station residency indices (RI) and (b) location upstream

from the estuary mouth (±SE; blue shading) of Rhabdosargus sarba between

August 2015 and April 2016. .......................................................................... 170

Figure 5.18 The predicted weekly distance upstream of individuals of Rhabdosargus

sarba (a) during each month of the year from August to April, and (b) under

various temperature and flow conditions, as estimated by the best fit mixed

effects models, #1 and #2, respectively, in Table 5.10. Error bars and shaded

areas represent SE. .......................................................................................... 171

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List of Tables

Table 2.1 Percentage contribution (%) and rank based on total abundance of each fish

species recorded in the nearshore and offshore waters of the Walpole-Nornalup

Estuary between July 2014 and May 2016. Total length ranges (TL; mm) and

functional guilds (E, estuarine usage; F, feeding mode; H, habitat) are given for

each species. Guild abbreviations are described in the footnote. J Juveniles, A

Adults. ............................................................................................................... 28

Table 2.2 Global P and R values, as well as pairwise R values, from three-way crossed

(region × season × year) ANOSIM tests of the nearshore species composition

and guild composition (estuarine usage, feeding mode and habitat) data.

Significant (P < 0.05) pairwise test results are in bold..................................... 32

Table 2.3 Global P and R values, as well as pairwise R values, from three-way crossed

(region × season × year) ANOSIM tests of the offshore species and guild

composition (estuarine usage, feeding mode and habitat) data. Significant (P <

0.05) pairwise test results in bold. .................................................................... 40

Table 2.4 Summary of the biogeographical, geomorphological and environmental

characteristics of various estuaries in south-western Australia and their fish

species richness and most abundant taxa. All fish composition data obtained

using a 21.5 m seine net (3 and 9 mm mesh) and multi–mesh gill nets (8 × 20m

panels, 38–127 mm mesh) to sample nearshore and offshore waters,

respectively. Physico–chemical water quality variables; temperature (T), salinity

(S) and dissolved oxygen (DO)......................................................................... 45

Table 3.1 Summary of selected previous studies investigating diel variation of estuarine

fish faunas. The diel period in which the number of fish species/diversity and

abundance/biomass was highest is provided for each study, as are the key

families and/or size classes (total length, TL) that were considerably more

abundant in each diel period. Secondary meta-analysis of published literature

was used to determine the most abundant families/size classes in cases where

they were not explicitly given. Significant diel differences detected only during

a certain season, month or tide are indicated by (*), while those detected only in

certain habitats are indicated by (^). ................................................................. 62

Table 3.2 Total number of individuals (n) and percentage contribution (%) of each fish

species caught during the day and night in the Walpole-Nornalup Estuary.

Habitat guilds H, i.e. small pelagic (SP), small benthic (SB), pelagic (P),

demersal (D), bentho-pelagic (BP), and feeding guilds F, i.e. zooplanktivore

(ZP), zoobenthivore (ZB), piscivore (PV), omnivore (OV), opportunist (OP),

detritivore (DV), are given for each species. .................................................... 70

Table 4.1 Sources of fish species and length composition data analysed in this Chapter.

........................................................................................................................... 89

Table 4.2 Fish metrics employed for the nearshore and offshore Fish Community Indices

(Hallett et al., 2012b). ....................................................................................... 95

Table 4.3 Threshold scores for each Fish Community Index estuarine health grade (as

derived from unpublished analyses by C. Hallett, Murdoch University, using all

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available historical fish community data from permanently-open south coast

estuaries and following the approach of Hallett, 2014). ................................... 95

Table 4.4 Percentage contribution (%) and rank based on total abundance/catch rate (R)

of each fish species recorded in the nearshore and offshore waters of the

Walpole-Nornalup Estuary during the historical (1989–90) and contemporary

(2014–16/2013–17) sampling periods. Functional guilds (E, estuarine usage; F,

feeding mode; H, habitat) are given for each species (guild abbreviations

described in the footnote). Abundant species (contributing ≥5%) are in bold.

......................................................................................................................... 104

Table 4.5 R-statistic and/or P values for global and pairwise comparisons from ANOSIM

tests on nearshore fish (a) species composition, and (b) estuarine usage, (c)

feeding mode and (d) habitat guild composition. Significant (P < 0.05) pairwise

R comparisons are in bold. .............................................................................. 106

Table 5.1 Depth and habitat within detection range of each acoustic receiver station

deployed in the Walpole-Nornalup Estuary. Station locations are shown in

Figure 5.1. See section 5.2.4 for derivation of habitat characteristics. Regions;

Upper Frankland River (UFR), Lower Frankland River (LFR), Walpole Inlet

(WI), Upper Nornalup (UN) and Lower Nornalup (LN). ............................... 138

Table 5.2 Metrics calculated for each species to assess their use of the Walpole-Nornalup

Estuary. ........................................................................................................... 141

Table 5.3 Transmitter ID (ID), total length (TL; mm), tagging details, tracking period

(days), total number of times detected, number of receiver stations visited,

detection index (DI) and minimum linear distance travelled by each individual

of (a) Acanthopagrus butcheri, (b) Platycephalus speculator, (c) Chrysophrys

auratus and (d) Rhabdosargus sarba and tagged in the Walpole-Nornalup

Estuary from July 2014 to February 2016. A sea trip refers to a fish leaving the

estuary for ≥ 6hours. ....................................................................................... 146

Table 5.4 Mixed effects models examining the influence of freshwater flow (flow), water

temperature (temp), month, weeks since tagging (WST), fish length (TL) and

linear distance upstream (dist_up) on the weekly residency (RI) of

Acanthopagrus butcheri at the station nearest to their tagging location. Models

are ranked by ΔAICC and were compared to the null model ‘RI ~ 1 + (1|ID) +

(1|station)’. ...................................................................................................... 162

Table 5.5 Mixed effects models examining the influence of freshwater flow, water

temperature, tidal height (tide), lunar illumination (lunar), month and fish length

(TL) on the (a) daily and (b) weekly distance of Acanthopagrus butcheri

upstream (km from estuary mouth). The top 10 models (ranked by ΔAICC) from

a full set of 39 candidate models are shown. All models were compared to the

null model ‘distance ~ 1 + (1|ID) + (1|year) + (1|tagging.group)’. ................. 164

Table 5.6 (a) Mixed effects models examining the influence of freshwater flow (flow),

water temperature (temp), month of the year, weeks since tagging (WST), fish

length (TL) and distance upstream (dist_up) on the weekly residency (RI) of

individuals of Platycephalus speculator at the station nearest to their tagging

location. Models are ranked by ΔAICC and were compared to the null model ‘RI

~ 1 + (1|ID) + (1|station)’. (b) Model summaries for the two best fit (lowest

AICC) models. Positive coefficients indicate an increase in residency and

negative coefficients indicate a decrease in residency. ................................... 166

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Table 5.7 (a) Mixed effects models examining the influence of freshwater flow (flow),

water temperature (temp), month of the year, weeks since tagging (WST) and

fish length (TL) on the weekly residency (RI) of individuals of Chrysophrys

auratus at station LFR2 where they were released. Models are ranked by ΔAICC

and were compared to the null model ‘RI ~ 1 + (1|ID)’. (b) Model summary of

the two best fit models (lowest AICC). Positive coefficients indicate an increase

in residency and negative coefficients indicate a decrease in residency. ....... 168

Table 5.8 Mixed effects models examining the influence of freshwater flow (flow), water

temperature (temp), tidal height (tide), lunar illumination (lunar), month of the

year, weeks since tagging (WST) and fish length (TL) on the weekly distance

upstream of individuals of Chrysophrys auratus. The top 5 models (ranked by

ΔAICC) from a full set of 26 candidate models are shown. All models were

compared to the null model ‘distance ~ 1 + (1|ID)’. ....................................... 168

Table 5.9 (a) Mixed effects models examining the influence of freshwater flow (flow),

water temperature (temp), month of the year, weeks since tagging (WST), fish

length (TL) and distance upstream (dist_up) on the weekly residency (RI) of

individuals of Rhabdosargus sarba at the station nearest to their tagging

location. Models are ranked by ΔAICC and were compared to the null model ‘RI

~ 1 + (1|ID) + (1|station)’. (b) Model summaries for the two best fit (lowest

AICC) models. Positive coefficients indicate an increase in residency and

negative coefficients indicate a decrease in residency. ................................... 170

Table 5.10 Mixed effects models examining the influence of freshwater flow (flow),

water temperature (temp), tidal height (tide), lunar illumination (lunar), month

of the year, weeks since tagging (WST) and fish length (TL) on the weekly

distance upstream of individuals of Rhabdosargus sarba. The top 5 models

(ranked by ΔAICC) from a full set of 26 candidate models are shown. All models

were compared to the null model ‘distance ~ 1 + (1|ID)’. .............................. 171

Table 6.1 A comparison of the key benefits and limitations of various approaches

employed to monitor fish in estuaries. These consider sampling aspects, data

requirements, interpretation of findings and breadth of knowledge provided.

......................................................................................................................... 186

Table 6.2 Proposed monitoring regime of fish communities in the Walpole and Nornalup

Inlets Marine Park to facilitate measurement of ecosystem health via the Fish

Community Index. .......................................................................................... 191

Table 6.3 Potential species for future tracking with acoustic telemetry within the Walpole

and Nornalup Inlets Marine Park, listed in order of priority based on current

knowledge gaps and tagging feasibility. Key areas for future research specific to

each are also listed. ......................................................................................... 193

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Acknowledgements

First and foremost, I would like to thank my supervisors. To my principal supervisor

Fiona Valesini, I am extremely grateful for your tireless dedication on all aspects of the

project. Your enthusiasm and advice was invaluable, and thank you for all the time spent

meticulously editing Chapters. To Chris Hallett, many thanks for all the time and effort

you have dedicated, both in the field and office. Your encouragement, guidance and

assistance, particularly in the final stages of the write up of this thesis, is greatly

appreciated. To Dave Abdo, many thanks for all your help and advice in the planning and

design of this project, for your assistance in the field, and for editing various Chapters.

To Joel Williams, I greatly appreciate the encouragement and advice you have given me

throughout my candidature, and your knowledge and dedication on many estuarine

sampling trips was invaluable.

I must also thank the many dedicated friends and colleagues who provided valuable

assistance in the field. Special thanks to Sian Glazier, Tom Bateman, Michael Tropiano,

Vincent Smythe, Max Wellington, Sam Robinson and Sam Moyle.

I would also like to thank Ian Potter for his support and guidance when I initially joined

the Murdoch fish group, which provided me with the opportunity to undertake this PhD.

Thanks also to James Tweedley, with whom I have had numerous helpful discussions

over the years. Many thanks to Alan Cottingham for your assistance with various aspects

of data analyses, and for providing unpublished biological data for Black Bream. Thanks

to Steve Beatty for the helpful discussions regarding fish tracking, and for the loan of

surgery gear. Thanks also to Steeg Hoeksema for providing water quality data for several

south coast estuaries. Unpublished data from recreational creel surveys was kindly

provided by the Department of Biodiversity, Conservation and Attractions WA. I am also

grateful for helpful statistical advice provided by Bob Clarke.

A big thanks also to Tahryn Thompson, Kylie Outhwaite, Justin Ettridge and Shaun

Ossinger for their help with various aspects of the project. Valuable advice and assistance

catching fish was also provided by local recreational fishers from the Walpole region.

On a personal level, I must give sincere thanks to my parents Paul and Andrea for their

constant support and encouragement. Finally, a big thanks to Sian for all your support

over the past years, your assistance with proof reading, and for putting up with me during

this journey.

Financial support was provided by the Department of Fisheries Western Australia,

Murdoch University and Recfishwest. Work was performed under Murdoch University

Animal Ethics permit number RW2676/14 and scientific permits granted by the

Department of Fisheries and Department of Parks and Wildlife.

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Chapter 1: General Introduction

1.1 THE ESTUARINE ENVIRONMENT

Estuaries are transitional waters that lie at the interface between marine, freshwater and

terrestrial environments. They are highly dynamic systems whose geomorphology,

hydrology and physico-chemistry are shaped by a host of marine and land-derived inputs,

as well as climatic influences (McLusky & Elliott, 2004; Jennerjahn & Mitchell, 2013;

Little et al., 2017) including air and sea temperatures, rainfall, streamflow, tidal amplitude

and wave energy (Chícharo & Barbosa, 2011; Wolanski & Elliott, 2015; Raimonet &

Cloern, 2017). Morphologically, these diverse environments range from extensive

riverine systems to large coastal basins, as well as small tidal creeks and shallow lagoons

(Elliott & McLusky, 2002; Whitfield & Elliott, 2011; Tweedley et al., 2016b). Some are

permanently open to the ocean, whereas others close intermittently due to sand bars

forming at their mouths (Hodgkin & Hesp, 1998; Roy et al., 2001; McSweeney et al.,

2017). Water quality parameters (e.g. temperature, salinity, dissolved oxygen, turbidity)

often reach greater extremes and are far more variable in estuaries than coastal or riverine

environments, fluctuating over daily, seasonal and interannual timescales (Tyler et al.,

2009; Haraguchi et al., 2015; Potter et al., 2015b). In systems periodically isolated from

the sea, seasonal transitions in salinity will commonly range from fresh to hypersaline

(Chuwen et al., 2009a; Potter et al., 2010). Environmental conditions also vary markedly

over both horizontal and vertical spatial gradients, with clear differences in water and

substratum attributes typically occurring between upstream and downstream areas, as

well as deeper and shallower waters (Roy et al., 2001; Whitfield & Elliott, 2011; Potter

et al., 2015b).

Despite their environmental extremes and variability, estuaries play many important

ecological roles and are among the most productive of all ecosystems (Heip et al., 1995;

Costanza et al., 2007; Elliott & Whitfield, 2011). They are crucial in nutrient recycling

and the filtration and transformation of organic material, particularly from land-derived

sources (Roy et al., 2001; Barbier et al., 2011; Bauer & Bianchi, 2011). Nutrients are then

either flushed into the ocean, or stored in the estuarine sediment. As nutrient-rich and also

characteristically shallow and warmer environments, estuaries support high rates of

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primary productivity (Cloern et al., 2014; Whitfield, 2016), which in turn provide an

abundance of habitats and food for aquatic biota (Potter et al., 2015b).

1.2 FISHES IN ESTUARIES

Estuaries globally are well recognised as nurseries for many marine fish species (Blaber

& Blaber, 1980; Beck et al., 2001; Sheaves et al., 2015). Their productivity allows

juveniles to rapidly reach sizes where they are less vulnerable to predation, a threat which

may also be lower in the confines of estuaries compared to exposed coastal and oceanic

waters (Potter & Hyndes, 1999). These ecosystems also support freshwater species to

varying degrees (Whitfield, 2015) and serve as pathways for fishes moving between

marine and freshwater environments (Elliott & Hemingway, 2002; Vasconcelos et al.,

2011). Additionally, some species complete their whole life cycle within the estuarine

environment.

There are several published schemes for classifying the ways in which fish use estuaries

(e.g. Potter et al., 1990; Whitfield, 1999; Elliott et al., 2007). Most recently, Potter et al.

(2015a) proposed four main categories; marine, estuarine, freshwater and diadromous,

each of which comprises multiple guilds based on shared life-cycle characteristics. The

marine and freshwater categories consist of species which spawn at sea and in freshwater

areas, respectively, but use estuaries at one or more stages in their life cycle. Among

guilds in these categories, estuarine usage ranges from facultative to obligatory, with

some species ‘accidently’ or opportunistically entering estuaries, while others are

dependent upon them during one or more life stages. The estuarine category comprises

solely estuarine species that complete their whole life cycle within estuaries, as well as

species which can complete their life cycle in either estuaries or marine/freshwater

environments. Finally, diadromous fishes are those that migrate between freshwater and

the sea and vice versa, for which estuaries provide a crucial link.

The fish composition of an estuary, including the contribution of various life cycle guilds,

reflects hierarchical environmental drivers which can be considered to sequentially

exclude or ‘filter’ species from a global pool (Mouchet et al., 2013; Henriques et al.,

2016). Most broadly, continental divides and oceanographic patterns drive biogeographic

distributions of species (Pasquaud et al., 2015; Henriques et al., 2017). Within a

bioregion, estuarine geomorphology is a key determinant of the diversity and composition

of species found within a system (Whitfield et al., 2017b). For example, the ability of

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marine species to enter an estuary primarily depends on its level of connectivity with the

sea (i.e. permanently vs intermittently open, and its mouth depth and width; Harrison &

Whitfield, 2006b; James et al., 2007; Pasquaud et al., 2015). At this and finer intra-

estuarine scales, the availability of certain benthic habitats, such as seagrass, macroalgae,

salt marsh, woody debris, rock or biogenic reef, acts as a further filter of fish composition

given the differing shelter and food requirements among species (Gray et al., 1996; Pihl

et al., 2002; Loureiro et al., 2016; Amorim et al., 2017; Whitfield, 2017). Water quality

properties including salinity, temperature, dissolved oxygen and turbidity also shape fish

fauna based on the physiological tolerances and preferences of different species

(Whitfield et al., 1981; Cyrus & Blaber, 1992; Harrison & Whitfield, 2006c).

For example, permanently-open systems typically exhibit longitudinal environmental

gradients, with marine influences in the lower reaches and freshwater/terrestrial

influences in the upper reaches (Elliott & McLusky, 2002; Chuwen et al., 2009a;

Whitfield et al., 2012a). Resultantly, lower estuary fish faunas generally comprise a

diversity of marine and often stenohaline species, with a transition towards oligohaline

and freshwater species further upstream (Akin et al., 2005; Barletta et al., 2005; Whitfield

et al., 2012a; Teichert et al., 2017). Temporal changes in environmental conditions also

influence estuarine fish assemblages over diel (Hagan & Able, 2008; Bailey & James,

2013; Krumme et al., 2015), seasonal (Claridge et al., 1986; Marshall & Elliott, 1998;

Jaureguizar et al., 2016; Pichler et al., 2017), interannual (Martinho et al., 2009; Eick &

Thiel, 2014; Veale et al., 2014) and multidecadal timescales (Henderson et al., 2011;

Baptista et al., 2015; Valesini et al., 2017).

1.3 ESTUARIES AND HUMANS: USES AND IMPACTS

Estuaries are centres of attraction for human populations, with most of the world’s major

cities built around estuarine systems (Valle-Levinson, 2010). Their sheltered waters serve

as harbours and shipping routes, and they provide an abundance of easily accessible

resources, including water and food (Blaber, 2000; McLusky & Elliott, 2004; Wolanski

& Elliott, 2015). Aside from providing goods and facilitating transport, estuaries offer a

multitude of other ecosystem services, including nutrient cycling, water purification,

flood mitigation and power generation (Barbier et al., 2011; Temmerman et al., 2013;

Hallett et al., 2016a). A host of recreational and tourism activities such as boating,

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swimming, sailing and nature watching are also undertaken within estuarine regions

(McLusky & Elliott, 2004; Barbier et al., 2011).

A major service provision from estuaries is through fishery harvest, and throughout the

world, commercial, recreational and artisanal fishers depend on these aquatic systems.

The productivity and accessibility of estuaries facilitates substantial catches of fish

(Lenanton & Potter, 1987; Blaber, 2000; Beckley & Ayvazian, 2007; Whitfield, 2016),

and more broadly they are crucial for supporting many marine fisheries through their

nursery role (Gillanders et al., 2003; Able, 2005; Vasconcelos et al., 2008; Sheaves et al.,

2015). In the United States, estuarine-associated fish were estimated to comprise 46% of

the total commercial fishery landings from 2000–04, and up to 80% of recreational

landings (Lellis-Dibble et al., 2008). Similarly, Lamberth and Turpie (2003) showed that

estuarine-dependent species accounted for 83% of catches in several inshore marine

fisheries in South Africa. It has also been estimated that more than 75% of the national

Australian commercial fishery catch spends at least part of their life cycle within estuaries

(Creighton et al., 2015). Moreover, 35% of all recreational fishing effort in Australia

occurs in estuaries, which in 2000–01 resulted in an estimated total annual catch of 17

million fish, 2.6 million crabs and 15 million prawns (Henry & Lyle, 2003).

However, this high degree of human activity in estuaries and their surrounding

catchments poses severe threats to their ecological health (Kennish, 2002; Sheaves et al.,

2012; Jennerjahn & Mitchell, 2013; Cloern et al., 2016). As global populations increase,

the impacts of threats including catchment development and infrastructure, pollution and

habitat loss are becoming more apparent. For example, an increase in shipping traffic and

the size of vessels has resulted in the dredging and development of many estuaries to

accommodate them (McLusky & Elliott, 2004; Elliott et al., 2016). Large-scale industry

and agriculture are changing the hydrology of systems and causing habitat destruction,

pollution and excessive nutrient loading (Kennish, 2002; Paerl, 2006; Cloern et al., 2016).

In recent decades, degradation has been exacerbated by the impacts of anthropogenically-

induced climate changes. The high sensitivity of estuaries to climate influences means

that slight changes in temperature, rainfall and sea level may have drastic ecological

impacts (Scavia et al., 2002; Cloern et al., 2011; Gillanders et al., 2011a; Feyrer et al.,

2015).

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Global increases in fishing effort are placing further direct stress on fish populations

(Jackson et al., 2001; Elliott, 2002; Lotze et al., 2006; Whitfield & Cowley, 2010).

Overfishing in estuaries has been widely linked to reductions in the abundance of targeted

species, changes in their size and age structure, and decreased productivity and value of

fisheries (Laë, 1997; Poulsen et al., 2007; James et al., 2008a; Chuwen et al., 2011;

Cowley et al., 2013; Whitfield et al., 2017a). Unsustainable fishing practices can also

impact entire fish communities and ecosystems through bycatch, habitat destruction and

trophic changes (Blaber et al., 2000; Blaber, 2011; Cloern et al., 2016).

1.4 MANAGEMENT OF ESTUARIES AND THEIR FISH STOCKS

As among the most ecologically important yet heavily exploited ecosystems, it is

imperative that robust approaches are developed to manage estuaries and their associated

fish stocks. In general, estuarine management aims to sustain the human uses, goods and

services these systems provide, without compromising their ecological integrity (or

‘health’; Boerema & Meire, 2017). Given that assessing estuarine integrity fundamentally

requires detailed information on ecosystem structure and function, including its physical,

chemical and biological components (Rapport et al., 1998), it follows that effective

management requires appropriate monitoring of these components to understand how

they respond to natural and anthropogenic drivers (Borja et al., 2016).

Typical structural measures of estuarine fish fauna include total abundance and/or

biomass, species richness, diversity/evenness and taxonomic composition (Fausch et al.,

1990; Warwick & Clarke, 2001; Tweedley et al., 2017). Functional responses are often

assessed through grouping fish into guilds on the basis of their use of estuaries (see section

1.2), affinity for particular habitats, reproductive strategy or feeding mode (Mouillot et

al., 2006; Franco et al., 2008; Nicolas et al., 2010a). Examinations at this level explicitly

link fish community structure to ecosystem functioning, helping to elucidate the

ecological drivers of spatio-temporal changes (Mouillot et al., 2006; Villéger et al., 2010;

Baptista et al., 2015; Lefcheck et al., 2015), as well as facilitate global comparisons

irrespective of species identity (Elliott et al., 2007).

The above structural and functional measures (‘metrics’) of fish or other biotic

communities can be integrated into single, easily interpretable indices termed multimetric

indices of ecosystem health (Whitfield & Elliott, 2002; Harrison & Whitfield, 2004; Borja

et al., 2011; Sheaves et al., 2012). These indices synthesise the ecological responses of

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fish communities to a wide array of environmental factors, and can be used to track the

health of an estuary in response to both short- and long-term stressors (Whitfield & Elliott,

2002; Harrison & Whitfield, 2004; Hallett et al., 2016c). They have been used extensively

to assess the ecological health of estuaries throughout Europe (e.g. Uriarte and Borja,

2009; Hering et al., 2010), North America (e.g. Gibson et al., 2000) and South Africa

(e.g. Harrison & Whitfield, 2004; Harrison & Whitfield, 2006a). Their usefulness is

reflected by the fact that they now form an integral part of the environmental legislation

in these regions (i.e. EU Water Framework Directive, US Clean Water Act, South African

National Water Act 1998; Hallett et al., 2016a). They have, however, only recently been

developed and applied in Australian estuaries (e.g. Fish Community Index – Hallett et al.,

2012b), and currently they have not been adopted into legislation (Hallett et al., 2016a).

In addition to holistic knowledge of ecosystem integrity, effective ecosystem-based

fisheries management also requires detailed data on how targeted species respond to

environmental drivers and fishing activity (Fletcher et al., 2010). Monitoring of targeted

species has traditionally focused on assessments of abundance/catch rates, size and age

composition, growth and reproductive biology (e.g. Blaber, 1974; Sarre & Potter, 1999;

Radebe et al., 2002; Chuwen et al., 2011; Walsh et al., 2011; Ferguson et al., 2014),

information essential for undertaking stock assessments and determining harvest controls

(e.g. size and bag limits). However, such monitoring does not provide detailed data on

fish movements and behaviour, which are crucial for understanding area use, ecosystem

connectivity, direct responses to environmental stressors and complex biological

interactions (Hindell et al., 2008; Gillanders et al., 2011b; Lee et al., 2017).

Observation-based fish monitoring techniques, including diver observations (Methven et

al., 2001), remote underwater video (Gibson et al., 1998; Becker et al., 2010) and high

definition sonar (Becker et al., 2011; Becker et al., 2015; Rieucau et al., 2015), allow

very fine-scale movements and behaviours of key species or assemblages to be studied.

However, such methods require intensive human effort, may be biased or inhibited under

certain environmental conditions, and are generally only practical for short time periods

and over relatively small spatial scales (Gillanders et al., 2011b; Taylor et al., 2013; Tušer

et al., 2014). Broader scale and more continuous fish movement patterns are thus typically

studied either with natural markers (e.g. parasites, stable isotopes and micro- and trace

elements from otoliths; Gillanders, 2009) or by tagging fish; including with physical tags,

stains/dyes (e.g. otolith staining) or fin-clipping (McFarlane et al., 1990).

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Electronic tags have been developed and refined over recent decades, and now allow fish

to be tracked over spatial scales from metres to thousands of kilometres, and with far

greater continuity and accuracy than previously (Voegeli et al., 2001). One of the most

versatile and widely-used applications of these tags is in acoustic telemetry (Hussey et

al., 2015; Crossin et al., 2017; Taylor et al., 2017), whereby uniquely coded transmitters

(‘acoustic tags’) are attached to fishes, and can be detected using either active tracking

technology or fixed location receivers in arrays (Heupel et al., 2006). Deployment of

acoustic arrays can be tailored to address key questions such as estuarine-ocean

connectivity (Able et al., 2014; Childs et al., 2015), habitat use (Francis, 2013; Furey et

al., 2013; Le Pichon et al., 2017), attraction to artificial structures (Hindell, 2007; Lowry

et al., 2017), homing ability of translocated fishes (Marcotte, 2014; Taylor et al., 2016)

and responses to environmental changes (Grothues et al., 2012; Grant et al., 2017a;

Williams et al., 2017). Acoustic tags can also be fitted with sensors to measure variables

such as fish swimming depth, metabolic activity and predation (Cooke et al., 2016; Payne

et al., 2016; Halfyard et al., 2017).

1.4 ESTUARIES OF SOUTH-WESTERN AUSTRALIA

The estuaries of south-western Australia (SWA) are distinct in their morphology,

hydrology and ecology from those in many other regions of the world, including northern

Australia and the northern hemisphere (Potter & Hyndes, 1999; Potter et al., 2010;

Tweedley et al., 2016b). Primarily, this is due to the microtidal conditions in SWA (tidal

amplitude <2 m), compared to the latter macrotidal (>2 m) regions. Morphologically,

SWA estuaries generally have a short, narrow entrance channel and a relatively large,

shallow basin or basins, fed by one or more tributary rivers (Hodgkin & Hesp, 1998;

Chuwen et al., 2009a). Unlike macrotidal systems, many SWA estuaries become isolated

from the sea due to sand deposition at their entrance (Hodgkin & Hesp, 1998; Potter &

Hyndes, 1999). Of the approximately 50 estuaries along 2,400 km of SWA coast, only

seven remain permanently open to the sea (Fig. 1.1a), with the remainder either seasonally

or intermittently open (typically opening annually), normally-closed (opening every

several years) or permanently-closed (very rarely or never opening; Hodgkin & Hesp,

1998; Brearley, 2005; Fig. 1.1a).

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Figure 1.1 (a) Map of south-western Australia showing the location of estuaries and their

major tributaries (adapted with permission from Hallett et al., 2018). Estuary types are

designated on the basis of their connectivity with the sea. (b) Satellite image of the

Walpole-Nornalup Estuary (denoted by bold text in [a]).

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Compared to the high energy systems of macrotidal regions, the estuaries of SWA are

generally less turbulent and turbid (Potter et al., 2015b; 2016; Tweedley et al., 2016b).

This provides more favourable conditions for the larval development of numerous fish

species, and consequently a far greater number of species and individuals complete their

life cycles within these estuaries (Potter & Hyndes, 1999; Potter et al., 2016; Tweedley

et al., 2016b). For example, estuarine-spawning fishes contribute only 0.6 and 3.8% to

the total number of individuals and species, respectively, in the macrotidal Severn Estuary

(UK), compared with 27–55 and 33–99%, respectively, in estuaries throughout SWA

(Potter & Hyndes, 1999).

The shallow estuaries of SWA are also greatly influenced by marked seasonality of

temperature and rainfall. Summer months are warm and dry, with average maximum

temperatures ranging 24–33 °C (Hope et al., 2015). In contrast, winter months are mild

and wet, with average minimum temperatures of only 3–12 °C, and up to 80% of the total

annual rainfall occurs from May to October (Silberstein et al., 2012; Hope et al., 2015).

This drives seasonal variation in key estuarine water quality characteristics

(Kanandjembo et al., 2001; Hoeksema & Potter, 2006). For example, salinity and

temperature are typically at their minimum during winter and spring, rising sharply in late

spring and early summer, before reaching their maximum in late summer/early autumn

(Loneragan et al., 1989; Kanandjembo et al., 2001; Chuwen et al., 2009a). Rainfall also

drives the opening of seasonally- and normally-closed systems. Sand bars form at the

mouths of estuaries during low river flow periods (typically in summer) until sufficient

freshwater discharge causes erosion and breaking of these bars (typically in late-

winter/spring; Hodgkin & Hesp, 1998; Potter & Hyndes, 1999).

During recent decades, unprecedented rates of warming and drying of the regional climate

have led to substantial effects on estuarine environments and their fish faunas (Hallett et

al., 2018). Since the 1970s, mean air temperatures have risen by c. 1 °C, while rainfall

has declined by 15–20% and freshwater flows throughout much of the region have more

than halved (Petrone et al., 2010; Barron et al., 2012; Silberstein et al., 2012; Hope et al.,

2015). Estuaries are thus becoming increasingly saline, with marine conditions occurring

further upstream and for longer periods of the year (Hallett et al., 2018). Extended bar

closures may also occur, preventing immigration/emigration of marine species and

potentially resulting in extreme hypersalinity and fish kills (Hoeksema et al., 2006).

Reduced estuarine flushing and warmer temperatures, combined with higher nutrient

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loads from growing catchment developments (especially urbanised areas) and recycled

stores from sediment deposits, have led to growing eutrophication and algal blooms

(Davis & Koop, 2006; Brearley, 2013; Potter et al., 2016). Vertical stratification of the

water column has also become more pronounced, leading to oxygen depletion of the

bottom waters and physiological stress and/or mortality among fishes (Cottingham et al.,

2014; 2016; Hallett et al., 2016c; Potter et al., 2016; Tweedley et al., 2016a). Towards

the end of this century it is predicted that winter rainfall will have further declined by up

to 45%, while air temperatures will be up to 2–4 °C warmer (Hope et al., 2015). Coupled

with continued population growth, the above environmental shifts in the estuaries of this

region will become more notable and widespread (Hallett et al., 2018).

1.5 WALPOLE-NORNALUP ESTUARY

The Walpole-Nornalup Estuary on the south coast of SWA (35.005° S, 116.725° E; Fig.

1.1a), is unlike many other estuaries in the region in several respects. Firstly, it is one of

the very few along this coastline that is permanently open to the sea. This is due to its

large catchment (5,785 km2; second largest on the south-coast of WA), situation in the

wettest part of the region (c. 1300 mm annual rainfall), and unique mouth morphology

whereby a rocky headland shelters the entrance from marine sand deposition (Hodgkin &

Hesp, 1998; Brearley, 2005; Semeniuk et al., 2011). Secondly, the estuary is considered

to be largely unmodified from a pristine state (NLWRA, 2002), being surrounded by

dense native vegetation protected by National Parks (Brearley, 2005; DEC, 2009) and

having a local population of only c. 400 residents (ABS, 2016). Lastly, the system is the

only marine park on the south coast of WA, and one of only two estuarine marine parks

in SWA. Gazetted in 2009, the Walpole and Nornalup Inlets Marine Park aims to preserve

the unique ecological, social and cultural values of the system (DEC, 2009).

The estuary has a narrow entrance channel, two basins (the Walpole and Nornalup Inlets)

and three tributaries (the Frankland, Deep and Walpole Rivers; Fig. 1.1b). The basins are

highly marine influenced, with salinities in the deeper waters remaining close to that of

sea water (i.e. 35) for much of the year (Hodgkin & Clark, 1988; Semeniuk et al., 2011).

Of the tributaries, the Frankland River is by far the largest and longest (c. 400 km in

length), and accounts for approximately 60% of annual freshwater flow to the estuary.

The smaller Deep and Walpole Rivers (120 and 15 km long) contribute a further 30 and

5%, respectively (Hodgkin & Clark, 1988; Brearley, 2005; Semeniuk et al., 2011). During

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summer, tidal incursions and salinities of >30 often occur at least 6 km upstream in the

Deep River and 12 km upstream in the Frankland River (Hodgkin & Clark, 1988;

Brearley, 2005). In winter, substantial flows typically cause these tributaries to become

essentially fresh throughout their length (Hodgkin & Clark, 1988).

A permanent connection with the sea provides favourable conditions for marine flora and

fauna, resulting in considerably higher aquatic biodiversity in the Walpole-Nornalup than

nearby seasonally-open or normally-closed estuaries (Brearley, 2005; Huisman et al.,

2011; Kendrick & Rule, 2013). Previous studies of its fish fauna have shown that the

system is an important nursery for a number of key marine fishery species and supports

juveniles and adults of several elasmobranch species (Hodgkin & Clark, 1988; Potter &

Hyndes, 1994). Since the early 1900s, commercial fishing and the use of nets has been

prohibited to preserve the estuary as a recreational angling haven (Christensen, 2009).

Indeed, recreational fishing effort in the estuary is the highest of any system along the

south coast due to vast numbers of tourists visiting from intra- and inter-state (Smallwood

& Sumner, 2007).

1.6 STUDY RATIONALE, OBJECTIVES AND THESIS STRUCTURE

Despite the clear ecological, social and cultural significance of the Walpole-Nornalup

Estuary, no quantitative studies of its fish communities have been undertaken for over 25

years, since the work of Potter and Hyndes (1994). Ecosystem managers thus lack

contemporary data on this key ecological component, and so have little evidence on which

to base management decisions and establish limits of acceptable change. Moreover, given

the high degree of fishing activity within the system, there is a clear need to identify those

areas of the estuary that are of greatest importance for sustaining various species,

including their nursery, spawning and aggregation sites. From a broader bioregional and

national perspective, robust quantitative data on the fish fauna and their responses to

changes in the estuarine environment are essential for benchmarking the Walpole-

Nornalup relative to other comparable systems. Such broader-scale comparisons are

necessary for understanding whether any longer-term shifts in the fish ecology and

ecosystem health of this estuary are system-specific, or more reflective of wider trends,

particularly given the rate at which climate change is occurring in SWA and other

Mediterranean climate regions.

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Given the above, the purpose of this thesis is to combine a suite of complementary

monitoring techniques to gather sound, quantitative data on the spatio-temporal

characteristics of the ichthyofauna throughout the Walpole Nornalup Estuary over

multiple years, and assess fish responses to environmental and anthropogenic changes

over both space (mainly intra-estuarine) and time (day vs night, seasons, years and

decades). The broad aims of the four subsequent data chapters in this thesis are as follows,

with more specific objectives and hypotheses given in each chapter.

Chapter 2: Quantify the structure and function of the fish communities throughout

the Walpole-Nornalup Estuary, and how they are shaped by environmental

mechanisms acting at broad (i.e. inter-estuarine) to local (i.e. intra-estuarine) spatial

scales, as well as seasonal to interannual temporal scales.

Chapter 3: Examine finer-scale temporal (diel) changes in the fish assemblages of

this system, and their environmental and biological drivers.

Chapter 4: Determine the nature, extent and potential causes of any significant

changes in the populations of key fishery species, fish communities and ecosystem

health of the Walpole-Nornalup Estuary since the last quantitative studies in the

1990s.

Chapter 5: Explore the estuarine–ocean connectivity and intra-estuarine

distributions of four major fishery species using contemporary acoustic telemetry,

and investigate their relationships with key environmental factors (e.g. water

temperature, river flow, moon phase, tidal amplitude), biological drivers (e.g. fish

size and reproductive phase) and intra-estuarine habitats (e.g. depth, physical

structure and substrate type).

The outcomes from these investigations will be used to tailor a fish faunal monitoring

regime for the Walpole and Nornalup Inlets Marine Park to support its future

management. This, in turn, will provide a basis for comparisons with other temperate

estuaries throughout Australia and globally.

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Chapter 2: Hierarchical environmental filters shaping the fish fauna of the Walpole-Nornalup Estuary

2.1 INTRODUCTION

Estuarine fish faunas are shaped by a complex hierarchy of environmental mechanisms

operating from global to local scales (Pasquaud et al., 2015; Vasconcelos et al., 2015;

Henriques et al., 2016; Sheaves, 2016). At a global level, biogeographic differences in

species distributions largely reflect the effects of broad-scale factors such as

oceanographic patterns and sea temperatures (e.g. Harrison & Whitfield, 2006c), which

structure species pools via pathways such as dispersal limitation and species tolerances

(Wiens, 2011; Henriques et al., 2016). Within a bioregion, environmental factors such as

estuarine connectivity with the ocean (i.e. open vs closed mouth states), estuary

geomorphology (e.g. depth, shape and size), tidal exchange, coastal currents, climatic

patterns and extent of anthropogenic modifications, further refine species pools by

influencing the potential of marine species to migrate between the estuary and ocean

(Harrison & Whitfield, 2006b; James et al., 2007; Hoeksema et al., 2009; Pasquaud et

al., 2015) and/or shaping the core features of the estuarine environment, e.g. hydrological

regimes, water quality and sedimentology (Roy et al., 2001; Chuwen et al., 2009a;

Whitfield et al., 2012a; Wolanski & Elliott, 2015). At an intra-estuarine scale, habitat

diversity, extent and quality further influence ichthyofaunal composition through the

specific requirements and preferences of individual species (Whitfield, 1983; 1999;

Sheaves & Johnston, 2009; França et al., 2011; Loureiro et al., 2016).

In recent years, the concept of environmental filtering, whereby species are sequentially

removed from the species pool as their physiological tolerances are exceeded, has been

used to help explain spatial patterns in biotic community structure (Laliberté et al., 2014;

Kraft et al., 2015). An extension of this idea could include hierarchical environmental

filters ranging from global to local scales, as conceptualised in Figure 2.1 for estuarine

species pools. Major filters act at each spatial scale, and within each, a complexity of sub-

filters lead to multiple and often interacting effects. For example, at the localised habitat

scale, water physcio-chemistry and physical structure may each exert differing effects on

individual species (Cyrus & Blaber, 1992; Barletta et al., 2005; Eick & Thiel, 2014).

Biological interactions among species (Fig. 2.1), while not environmental filters per se,

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further shape fish fauna through resource competition (Islam & Tanaka, 2005; Platell et

al., 2006) and predation (Heimbuch, 2008; Baker & Sheaves, 2009).

Figure 2.1 Conceptual model of the major environmental filters that shape local estuarine

fish composition from the global species pool. Blue shaded area represents the relative

number of species at each spatial scale. Natural environmental influences on these filters

are represented in green boxes and arrows, and anthropogenic influences are denoted by

red boxes and arrows.

Alongside the above spatial filters, temporal influences such as climatic conditions and

lunar cycles drive changes in estuarine environments over time scales ranging from

interdecadal to diurnal (Elliott & McLusky, 2002; Tyler et al., 2009; Haraguchi et al.,

2015; Cloern et al., 2017), and are widely implicated in corresponding shifts in estuarine

fish communities (Claridge et al., 1986; Thiel et al., 1995; Potter et al., 2001; Barletta et

al., 2005; Rountree & Able, 2007; Rieucau et al., 2015). These temporal drivers often act

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at multiple spatial levels, thereby influencing broad to local scale environmental filters

(Fig. 2.1). For example, in temperate microtidal regions, the marked decrease in rainfall

from winter to summer often results in sand bars forming at the mouths of estuaries in the

latter season (Hodgkin & Hesp, 1998; Roy et al., 2001), removing connectivity with the

sea and altering the within-estuary habitats through subsequent shifts in water physico-

chemistry (e.g. salinity and dissolved oxygen and nutrient concentrations; Gobler et al.,

2005; Chuwen et al., 2009a; Potter et al., 2010). These environmental changes are often

accompanied by reduced fish diversity as marine immigration ceases and highly tolerant

euryhaline species become more dominant (James et al., 2007; Hoeksema et al., 2009;

Whitfield et al., 2012c). If low rainfall persists for several years, extended mouth closure

may cause even more dramatic environmental changes (e.g. prolonged hypersalinity;

Young & Potter, 2002; Chuwen et al., 2009a), resulting in highly depauperate fish faunas

(Whitfield, 1999; Young & Potter, 2002; Hoeksema et al., 2006). Alternatively, periods

of exceptionally high rainfall may also hamper fish recruitment and diversity by reducing

larval/juvenile immigration from the sea (Martinho et al., 2009; Pattrick & Strydom,

2014), and marine fishes within the system may emigrate due to fresher and thus less

favourable conditions (Loneragan & Potter, 1990; Thiel et al., 1995; Sheaves et al., 2007;

Whitfield et al., 2012a; Jaureguizar et al., 2016).

Superimposed on the above natural spatial and temporal environmental influences,

anthropogenic pressures acting at global (e.g. climate change; Kennish, 2002; Gillanders

et al., 2011; James et al., 2013) through to local scales (e.g. modified freshwater flows

through damming and diversion of rivers, land reclamation and habitat loss, fishing and

pollution; Blaber et al., 2000; McLusky & Elliott, 2004; Sheaves et al., 2012; Blaber &

Barletta, 2016) further influence the structure of estuarine fish assemblages. Indeed, the

cumulative effects of these anthropogenic influences have resulted in estuaries becoming

among the most degraded of all aquatic ecosystems (Jackson et al., 2001; Cloern et al.,

2016).

Despite their dynamic nature and the growing anthropogenic pressures they face,

estuaries globally are recognised as highly important nursery areas for marine fish (e.g.

Blaber & Blaber, 1980; Beck et al., 2001; Able, 2005; Whitfield, 1999; Sheaves et al.,

2015). Furthermore, the importance of this role may be heightened in exposed coastal

areas where nearshore marine environments do not provide good alternative nursery areas

(Lasiak, 1986), such as along the south coast of Western Australia (WA) (Ayvazian &

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Hyndes, 1995; Coulson et al., 2017). While many estuaries along this temperate

microtidal coastline are naturally predisposed to closing to the sea (Hodgkin & Hesp,

1998), climate change throughout the region during the past half century has caused rapid

and unprecedented warming and decreased rainfall (Silberstein et al., 2012; Hope et al.,

2015), resulting in the extended closure of many systems and thus limiting their

accessibility for marine species (Hallett et al., 2018). These extended closures also

magnify the effects of eutrophication, hypoxia and hypersalinity, which impact many

estuaries in the region (e.g. Brearley, 2013; Hallett et al., 2018), and further reduce their

fish diversity.

The Walpole-Nornalup Estuary, located in the highest rainfall area on the south coast of

WA, is fed by a large catchment (i.e. 5,785 km2; Brearley, 2005) and has a unique mouth

morphology which shelters its entrance from marine sand deposition (Hodgkin & Hesp,

1998). It is thus one of the few estuaries along this coastline that remain permanently-

open to the ocean, unlike along the lower west coast of WA where most remain open to

the sea, due to both lower coastal wave energy and anthropogenic modification of their

mouths. Given the extended mouth closures of several other south coast estuaries over

recent decades, it is likely that the ecological importance of the Walpole-Nornalup to

marine fish species will have increased, and will continue to do so into the future.

However, as the last quantitative studies of the fish assemblage in this system were

undertaken over two decades ago (Neira & Potter, 1994; Potter & Hyndes, 1994), little is

known of its current fish fauna, their main environmental drivers or how they compare to

those of other systems. Evidence-based management of estuarine fish faunas

fundamentally requires current and sound knowledge of their structural and functional

attributes, and how they respond to key environmental and anthropogenic drivers. In light

of the above-described climate change effects, and those of other anthropogenic stressors

linked to increasing coastal populations in the region (Hirst, 2008), information on the

fish fauna of the Walpole-Nornalup from previous decades is unlikely to be relevant for

setting reliable resource management targets (Kopf et al., 2015).

The overarching aim of this component of the study is therefore to provide comprehensive

quantitative data on the ichthyofaunal composition of the Walpole-Nornalup Estuary and

examine how it is shaped by environmental filters acting from bioregional to local scales,

as well as temporal effects at interannual and seasonal scales. These data will further be

used to test the following hypotheses.

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1. Reflecting well established global patterns in marine diversity, particularly a poleward

decline in species richness, the fish fauna of the Walpole Nornalup will be less diverse

than that of permanently open estuaries situated at lower latitudes on the west coast of

WA. However, at a regional level, the system will be more diverse and comprise a greater

contribution of marine-spawning species than estuaries of similar latitude which

intermittently close to the sea.

2. At an intra-estuary scale, the environmental characteristics of the Walpole-Nornalup,

and thus its fish faunal composition, will follow a longitudinal gradient from the estuary

mouth to its upstream extent, as occurs in many permanently-open systems. Specifically,

fish species and guild diversity will be highest in the lower estuary due to a prevalence of

marine-spawning species with specialist feeding modes, while the upper estuary will be

least diverse and dominated by generalist-feeding estuarine and/or freshwater-spawning

species.

3. The ichthyofaunal composition of the Walpole-Nornalup will vary significantly among

seasons (especially summer vs winter) and consecutive years in response to changing

physico-chemical conditions. Temporal variation will be greatest in the upper estuary

where environmental conditions are typically most dynamic. Moreover, temporal changes

in the Walpole-Nornalup will be less pronounced than in seasonally-closed south-western

Australian estuaries where more distinct hydrological shifts often occur.

2.2 METHODS

2.2.1 Study area

The Walpole-Nornalup Estuary is situated at 35.005°S, 116.725°E on the south coast of

WA. The region has a temperate climate, is microtidal (<0.9 m tidal range) and receives

c. 1300 mm in rainfall per year (Hodgkin & Hesp, 1998; Semeniuk et al., 2011). Under

the Integrated Marine and Coastal Regionalisation of Australia framework (IMCRA v4.0;

Department of the Environment and Heritage, 2006), the estuary is located within the WA

South Coast bioregion, as distinct from those on the lower west coast of WA, which are

in the Leeuwin-Naturaliste bioregion. The estuary has two basins and three main

tributaries (Fig. 2.2). The larger of the two basins, the Nornalup Inlet, is approximately 5

× 3.5 km (12.6 km2 surface area), has extensive shallow (<1.5 m deep) sand flats which

fringe its deeper (3–6 m) central waters, and is fed by the Frankland and Deep rivers. The

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smaller Walpole Inlet basin is approximately 1 × 2 km (1.3 km2 surface area), <1.5 m

deep, and is fed by the Walpole River. The benthic habitat of both basins has little

structural complexity, with only small areas of rocky reef, seagrass or vegetative cover,

while considerable amounts of large woody debris are present in the rivers (Huisman et

al., 2011; Semeniuk et al., 2011).

2.2.2 Fish faunal sampling

Fish communities in both the shallow nearshore (≤1.5 m deep) and deeper offshore

(typically ≥1.5 m deep) waters of the Walpole-Nornalup Estuary were sampled seasonally

in five regions of the estuary (Lower Nornalup, LN; Upper Nornalup, UN; Walpole Inlet,

WI, Frankland River, FR and Deep River, DR; Fig. 2.2) between July 2014 (Austral

winter) and May 2016 (Austral autumn).

Fish in the nearshore waters were collected at 23 sites (4–6 replicates in each region; Fig.

2.2) using a beach seine net that was 21.5 m long, had a vertical drop of 1.5 m, two 10 m

long wings (outer 6 m comprising 9 mm mesh and inner 4 m comprising 3 mm mesh), a

1.5 m long bunt (3 mm mesh) and swept an area of approximately 116 m2. This net type

was chosen as it is consistent with that used in numerous previous studies of estuarine

fish assemblages in south-western Australia (e.g. Young et al., 1997; Hoeksema & Potter,

2006; Hoeksema et al., 2009) and has several advantages over larger nets, including its

greater speed and ease of deployment, the wider range of habitats in which it can be used,

and the relatively lower overall fish mortality associated with its use (Hallett & Hall,

2012). The net was deployed parallel to the bank and then hauled ashore or onto a vessel

if no beach area was nearby.

Fish in the offshore waters were sampled using multi-mesh gill nets consisting of eight

20 m long panels, each with a different mesh size, i.e. 38, 51, 63, 76, 89, 102, 115 and

127 mm stretched internal diameter. To minimize the impact of this sampling method on

the fish communities of the estuary, gill netting was undertaken at only 12 sites

throughout the system (three replicates in each the LN, UN, WI and FR; Fig. 2.2) and

during summer and winter only. Nets were deployed from a vessel within an hour of

sunset and set for one hour.

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Figure 2.2 Location of each nearshore and offshore fish sampling site throughout the five

study regions of the Walpole-Nornalup Estuary.

All fish in each sample were identified to species, counted and measured to the nearest 1

mm (total length), except where a large number of a species was caught, in which case a

representative subsample of up to 50 individuals was measured. Wherever possible, fishes

were processed in the field and released alive. In cases where fishes could not be quickly

identified and measured in the field, they were immediately euthanised in an ice slurry

before being transported to a laboratory for processing.

Each fish species was allocated into (i) estuarine usage guilds (freshwater migrant, FM;

estuarine species, ES; estuarine and marine, EM; marine estuarine-opportunist, MEO;

marine straggler, MS), (ii) functional habitat guilds (small pelagic, SP; small benthic, SB;

pelagic, P; demersal, D; bentho-pelagic, BP) and (iii) feeding mode guilds

(zooplanktivore, ZP; zoobenthivore, ZB; detritivore, DV; omnivore, OV; piscivore, PV)

based on published literature (e.g. Potter & Hyndes, 1999; Elliott et al., 2007; Gomon et

al., 2008; Hallett et al., 2012a; Potter et al., 2015a) and information from FishBase

(Froese & Pauly, 2016). To ascertain whether fishes caught were juveniles or adults, the

length at 50% maturity (L50) for each species, where available, was again obtained from

relevant published literature and information from FishBase.

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2.2.3 Measurement of water quality parameters

Salinity, water temperature (°C) and dissolved oxygen concentration (DO; mg L−1) were

measured at each site on each sampling occasion using a multiparameter water quality

meter (HydroLab Quanta or Yellow Springs International 556). These parameters were

recorded in the middle of the water column at nearshore sites and at both the water surface

and bottom at the deeper offshore sites. Due to equipment malfunction, no water quality

variables were recorded in spring 2015 and limited data was collected during autumn

2016 (see Results, section 2.3.1).

2.2.4 Data analyses

The following statistical analyses were performed using the software packages PRIMER

v7 (Clarke & Gorley, 2015) with the PERMANOVA+ add-on module (Anderson et al.,

2008) or R (R Development Core Team, 2016; www.r-project.org).

Spatio-temporal differences in water quality

Salinity, water temperature and dissolved oxygen data collected simultaneously during

fish sampling was subject to Permutational Analysis of Variance tests (PERMANOVA;

Anderson, 2001) to quantify spatio-temporal differences in the physico-chemical

environment of the estuary. Prior to analyses, these data were initially examined to

determine if transformation was required to meet test assumptions of homogeneous

dispersion among a priori groups (Anderson, 2001) following the criteria of Clarke et al.

(2014a), and no transformations were deemed necessary. Separate Euclidean distance

matrices were constructed for each water quality variable collected in the nearshore

waters, which were then each subjected to a three-way crossed region × season × year

PERMANOVA test. Salinity, temperature and DO data collected in the deeper offshore

waters was similarly used to construct Euclidean distance matrices, but these were

subjected to four-way crossed region × season × year × depth PERMANOVA tests. All

factors were considered fixed and the null hypothesis of no significant difference among

groups was rejected if the significance level (P) was <0.05. The components of variation

value (COV) for each significant term was used to ascertain its relative importance. When

PERMANOVA detected significant differences, plots of the mean values (± standard

error) in each region, season, year and/or depth were used to elucidate the main causes of

those differences.

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Spatio-temporal differences in mean fish abundance, species richness and taxonomic

distinctness

The total number of individuals in each nearshore and offshore sample was initially

transformed (ln[x+1] and fourth-root, respectively) to approximate a homogeneous

dispersion among a priori groups (Anderson, 2001; Clarke et al., 2014a). These

transformed data were then used to create separate Euclidean distance matrices for the

nearshore and offshore waters. Euclidean distance matrices were similarly constructed

from the number of species recorded in each nearshore (no transformation required) and

offshore sample (square-root transformed).

Quantitative average taxonomic distinctness (∆*) was used to provide a robust measure

of species diversity (Warwick & Clarke, 1995). Prior to calculating this index, the species

abundances in each sample were dispersion weighted (Clarke et al., 2006) then square-

root transformed (Clarke et al., 2014b). ∆* was then calculated for each sample using the

DIVERSE routine, and the resultant data used to construct separate Euclidean distance

matrices for the nearshore and offshore waters.

Each of the above distance matrices were then subjected to a three-way crossed region ×

season × year PERMANOVA test. Interpretation of these tests was the same as that

outlined above for the water quality variables.

Spatio-temporal differences in species and functional guild composition

To test for any spatio-temporal differences in species composition, Bray-Curtis similarity

matrices constructed from the above pre-treated (dispersion-weighted and transformed)

species abundance data in each the nearshore and offshore waters were subjected to the

same three-way PERMANOVA test described above. These pre-treated data for each

water depth were then averaged separately on the basis of (i) estuarine usage, (ii) habitat

and (iii) feeding mode functional guilds, used to calculate Bray-Curtis resemblance

matrices, and subjected to PERMANOVA. Any significant differences in species or guild

composition were then further explored using Analysis of Similarity tests (ANOSIM;

Clarke & Green, 1988; Clarke, 1993). The design of the ANOSIM tests was tailored to

accommodate any significant interactions detected by PERMANOVA, and are provided

in detail in the Results. The criteria for rejecting the null hypothesis of no significant

compositional differences among groups was the same as that for PERMANOVA, and

the extent of any significant differences was gauged by the magnitude of the R-statistic.

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To illustrate any significant spatio-temporal differences detected by the above tests, the

distance among centroids of groups of replicate samples in each region, season and/or

year was calculated, and the resultant distance matrix subjected to non-metric

multidimensional scaling ordination (nMDS).

A shade plot (Clarke et al., 2014b) constructed from the pre-treated species abundance

data, averaged appropriately, was then used to determine the species most responsible for

driving any significant spatio-temporal differences in species composition. For the

nearshore data, only those species comprising >10% of the total abundance in at least one

averaged sample were included, while all species in the offshore waters were included.

Species (displayed on the y-axis) were ordered according to a group-average hierarchical

agglomerative cluster analysis of a resemblance matrix defined between species as

Whittaker’s index of association (Legendre & Legendre, 1998). A Similarity Profiles test

(SIMPROF Type 3; Somerfield & Clarke, 2013) was also applied to identify those points

in the clustering procedure at which no significant structure (difference in species

abundance patterns) could be detected. Samples, displayed on the x-axis, were ordered

according to the most influential spatial and/or temporal factor.

Any significant differences in functional guild composition were further explored by

calculating the proportion of each guild (based on pre-treated values) within each region,

season and/or year.

Spatio-temporal relationships between fish fauna and environmental parameters

To test for any significant correlations between the spatio-temporal patterns in fish

species composition and those in the measured suite of water quality parameters, both the

Biota and Environment matching (BIOENV; Clarke & Ainsworth, 1993) and Distance-

based Linear Modelling (DISTLM; McArdle & Anderson, 2001) routines were

employed. For these analyses, the Bray-Curtis resemblance matrices constructed from the

pre-treated species abundance data for the nearshore and offshore waters were each

matched to the normalised salinity, temperature and dissolved oxygen data collected in

situ while sampling fish. Tests were firstly undertaken using all samples (i.e. from all

regions, seasons and years) to explore any overall correlation, and then within levels of

particular factors based on the outcomes of PERMANOVA tests on fish species

composition (see Results) to remove any confounding influences.

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For the BIOENV tests, the Spearman rank correlation coefficient (ρ) was employed as

the matching coefficient, and Euclidean distance was used to define sample resemblances

for the water quality data. For all DISTLM tests, a step-wise selection procedure using a

modified version of the Akaike (1973) information criterion (AICC) was employed as the

selection criterion, and the R2 value was used to gauge the proportion of fish faunal

variability ‘explained’ by the ‘best’ water quality model. For both tests, the null

hypothesis of no significant correlation was rejected if P < 0.05. Significant matches

detected by BIOENV were illustrated by subjecting the relevant Bray-Curtis matrices

constructed from the fish data to nMDS ordination, then overlaying bubble plots of the

selected water quality data. When DISTLM detected significant results, a distance-based

redundancy analysis (dbRDA) was used to illustrate the modelled relationships.

2.3 RESULTS

2.3.1 Physico-chemical water variables

Temperature, salinity and dissolved oxygen concentration (DO) measured in the shallow

nearshore waters of the Walpole-Nornalup Estuary differed significantly among seasons

and, in the latter two cases, also among regions (Appendix 2.1). The region × season

interaction was also significant for all variables, as was the season × year interaction for

salinity and DO (Appendix 2.1). The COV values for these tests showed season was the

most influential factor in all cases, followed closely by the season × year interaction for

salinity and DO.

Mean water temperature was lowest during winter (c. 13–15 °C) and highest in summer

(c. 24–25 °C) in all regions (Fig. 2.3a). The region × season interaction was due mainly

to relatively small differences in the order of regions between some seasons, e.g. while

the warmest temperatures were found in the Lower Nornalup (LN) in winter and autumn,

this was the coolest region in summer. Mean salinity in all regions during the first year of

sampling (i.e. 2014–15) was also lowest in winter (c. 4 in the Frankland River; FR to c.

13 in the Upper Nornalup; UN), and highest in summer (c. 33 in FR to 37 in the Walpole

Inlet; WI), except in the Deep River (DR), which was not sampled during that winter and

was most saline during autumn (salinity c. 30; Fig. 2.3b). During the second year (2015–

16), salinities were highest in summer in all regions, but lowest in autumn in both the FR

and LN (Fig. 2.3b). Moreover, average salinities in the FR, WI, UN and LN during the

second winter (c. 17–30) were far higher than those of the first (c. 4–13). Among regions,

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salinity was considerably higher in the LN and UN than FR and DR throughout much of

the sampling period (Fig. 2.3b). Dissolved oxygen concentrations in all regions were

highest in winter (c. 8.8–10.8 mg L−1) and lowest in summer (c. 5.5–8.2 mg L−1) in both

years. They were also notably higher during the first winter than the second, while the

opposite was true, to a lesser extent, for summer in all regions except DR (Fig. 2.3c).

In the deeper offshore waters, significant regional, seasonal, interannual and depth

differences in water temperature were detected by PERMANOVA (Appendix 2.2), as

were all two-way interactions with season and the three-way region × season × year

interaction. Seasonal effects were by far the most influential, with temperatures

considerably warmer throughout the system during summer (23–25 °C) than in winter

(13–14 °C; Fig. 2.4a). During summer of both years the WI was the warmest region (25–

25.5 °C) and the LN was the coolest (22.7–23.3 °C), while during winter the FR had the

coolest water temperatures each year (Fig. 2.4a). The far less apparent interactions among

years and depths were due to only small temperature differences among the latter factors

within each season and/or region. Little difference occurred between years within

summer, while during the second winter temperatures throughout the system were slightly

warmer than during the first (12.5–14.3 vs 13.9–14.4 °C). Similarly, between water

depths, bottom temperatures within each season were in general warmer than those at the

surface, but only by <1 °C (Fig. 2.4a).

With respect to offshore salinity, all main effects and many interactions were significant,

but the effect of season, closely followed by the season × year interaction, were by far the

most influential terms (Appendix 2.2). Between seasons, salinities were highest in

summer and lowest in winter in each region, year and depth combination. However, mean

values during winter of the second year were considerably higher than those in the first

(c. 4–30 vs 18–30), while the opposite was true, to a lesser extent, during summer (c. 33–

37 vs 23–34; Fig. 2.4b). Among regions, salinity was generally highest in the LN and UN

and lowest in the FR, and more so during winter than summer. Surface salinities were

lower than bottom salinities in the winters of both years in all regions, but were very

similar between water depths and essentially marine (32–37) in both summers, except

during the second summer in the FR (Fig. 2.4b).

Dissolved oxygen content in the offshore waters varied significantly among the main

effects of season and depth, and with seasonal differences again the most influential of

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all model terms (Appendix 2.2). All two-way interactions involving season were also

significant, as was the season × year × depth interaction and the four-way interaction.

Mean values were higher in winter than summer in each region, year and depth

combination, except in the bottom waters of the UN during the first winter (Fig. 2.4c).

Bottom DO was generally lower than that of the surface which was most apparent in the

FR and UN, and particularly during the first winter of sampling where 5 mg L−1 difference

occurred between depths in the latter region (Fig. 2.4c).

2.3.2 Overall fish species abundances and guilds

A total of 151,499 fish representing 46 species and 29 families were recorded throughout

the nearshore and offshore waters of the Walpole Nornalup Estuary in 2014–16 (Table

2.1). In the shallows, the atherinid Leptatherina presbyteroides was by far the most

abundant (c. 80% of the total catch), followed by L. wallacei, the engraulid Engraulis

australis and the gobiids Favonigobius lateralis and Pseudogobius olorum (c. 1–8% of

the catch; Table 2.1). The sparid Acanthopagrus butcheri and the arripid Arripis

georgianus were most abundant in the offshore waters (c. 34–37% of the catch), followed

by another sparid, Rhabdosargus sarba, the terapontid Pelates octolineatus and the elopid

Elops machnata (c. 3–5%; Table 2.1).

Across both water depths, the vast majority of species were caught either as juveniles

only, or as both juvenile and adults (Table 2.1). Of the ten most abundant species in each

water depth, all were recorded as juveniles and adults, except Sillaginodes punctatus in

the nearshore waters, and Chrysophrys auratus and Pseudocaranx georgianus in the

offshore waters, which were recorded as juveniles only (Table 2.1). The few species

which were recorded solely as adults (i.e. Spratelloides robustus, Gambusia holbrooki

and Galaxias maculatus) were recorded only in relatively low numbers.

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Figure 2.3 Mean ± SE (a) temperature (°C) recorded in the nearshore waters of each

region during each sampling season, and (b) mean salinity and (c) dissolved oxygen

content (mg L−1) recorded during each season and year. Regions; Deep River (◼)

Frankland River (◼), Walpole Inlet (◼), Upper Nornalup (◼) and Lower Nornalup (◼).

Seasons; winter (W), spring (Sp) summer (S) and autumn (A). NB, no measurements

recorded during Sp2, and also A2 in the case of dissolved oxygen.

(a)

(b)

(c)

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Figure 2.4 Mean ± SE (a) temperature (°C) recorded in the offshore waters in each region

during summer (S) and winter (W), and (b) salinity, and (c) dissolved oxygen

concentration (mg L−1), recorded at the surface () and bottom (◼) of the water column

in those waters during summer and winter of each sampling year (1, 2). Regions, LN;

Lower Nornalup, UN; Upper Nornalup, WI; Walpole Inlet, FR; Frankland River.

(a)

(b)

(c)

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Table 2.1 Percentage contribution (%) and rank based on total abundance of each fish species recorded in the nearshore and offshore waters of the

Walpole-Nornalup Estuary between July 2014 and May 2016. Total length ranges (TL; mm) and functional guilds (E, estuarine usage; F, feeding mode;

H, habitat) are given for each species. Guild abbreviations are described in the footnote. J Juveniles, A Adults.

Family Species Common Name Guild

TL Nearshore Offshore

E, F, H % Rank % Rank

ATHERINIDAE Leptatherina presbyteroides Silver Fish EM, ZP, SP 18–78 J,A 80.38 1 ATHERINIDAE Leptatherina wallacei Western Hardyhead ES, ZB, SP 18–83

J,A 8.07 2 ENGRAULIDAE Engraulis australis Australian Anchovy EM, ZP, SP 32–102

J,A 5.06 3 0.48 16

GOBIIDAE Favonigobius lateralis Southern Longfin Goby MEO, ZB, SB 16–75 J,A 1.23 4

GOBIIDAE Pseudogobius olorum Bluespot Goby ES, OV, SB 18–46 J,A 1.23 5

ATHERINIDAE Atherinosoma elongata Elongate Hardyhead ES, ZB, SP 15–88 J,A 0.74 6

GOBIIDAE Afurcagobius suppositus Southwestern Goby ES, ZB, SB 16–65 J,A 0.67 7

SILLAGINIDAE Sillaginodes punctatus King George Whiting MEO, ZB, D 27–302 J 0.62 8 0.65 15

SPARIDAE Rhabdosargus sarba Tarwhine MEO, ZB, BP 16–332 J,A 0.51 9 5.01 3

MUGILIDAE Aldrichetta forsteri Yelloweye Mullet MEO, OV, P 28–355 J,A 0.44 10 0.16 18

MUGILIDAE Mugil cephalus Sea Mullet MEO, DV, P 25–427 J,A 0.38 11 2.42 7

SPARIDAE Acanthopagrus butcheri Black Bream ES, OP, BP 50–298 J,A 0.25 12 37 1

ARRIPIDAE Arripis truttaceus Western Australian Salmon MEO, PV, P 39–195 J 0.12 13 HEMIRAMPHIDAE Hyporhamphus melanochir Southern Sea Garfish MEO, ZB, SP 111–201 J,A 0.09 14 0.16 19

GOBIIDAE Arenigobius bifrenatus Bridled Goby ES, ZB, SB 23–141 J,A 0.07 15

CARANGIDAE Pseudocaranx georgianus Silver Trevally MEO, ZB, BP 92–286 J 0.03 16 1.62 9

TERAPONTIDAE Pelates octolineatus Western Striped Grunter MEO, OV, BP 20–253 J,A 0.03 17 4.2 4

PLEURONECTIDAE Ammotretis rostratus Longsnout Flounder MEO, ZB, D 24–183 J,A 0.02 18 0.16 20

SILLAGINIDAE Sillago schomburgkii Yellowfin Whiting MEO, ZB, D 125–340 J,A 0.01 19 0.32 17

SILLAGINIDAE Sillago burrus Western Trumpeter Whiting MEO, ZB, D 36–132 J 0.01 20 CLUPEIDAE Spratelloides robustus Blue Sprat MEO, ZP, SP 72–77 A 0.01 21 POECILIIDAE Gambusia holbrooki Eastern Gambusia FM, ZB, SP 27–35 A 0.01 22 CLUPEIDAE Hyperlophus vittatus Sandy Sprat MEO, ZP, SP 32–67 J <0.01 23 ARRIPIDAE Arripis georgianus Australian Herring MEO, PV, P 45–262 J,A <0.01 24 34.09 2

Table continued overleaf.

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Family Species Common Name Guild

TL Nearshore Offshore

E, F, H % Rank % Rank

LABRIDAE Notolabrus parilus Brownspotted Wrasse MS, ZB, D 23–60 J <0.01 25 PLEURONECTIDAE Ammotretis elongatus Elongate Flounder MEO, ZB, D 68–92 J <0.01 25

CYNOGLOSSIDAE Paraplagusia bilineata Lemon Tongue Sole MS, ZB, D 137–165 J <0.01 25

PLATYCEPHALIDAE Platycephalus speculator Southern Bluespotted Flathead EM, PV, D 165–430 J,A <0.01 26 0.97 12

PLOTOSIDAE Cnidoglanis macrocephalus Estuary Cobbler EM, ZB, D 37–660 J,A <0.01 27 0.97 13

SYNGNATHIDAE Pugnaso curtirostris Pugnose Pipefish MS, ZP, D 38 J <0.01 27

SILLAGINIDAE Sillago bassensis Southern School Whiting MS, ZB, D 141–154 J <0.01 27

ENOPLOSIDAE Enoplosus armatus Old Wife MS, ZB, D 18–28 J <0.01 27

BLENNIIDAE Parablennius postoculomaculatus False Tasmanian Blenny MS, OV, SB 20–44 J <0.01 27

CLINIDAE Cristiceps australis Southern Crested Weedfish MS, ZB, D 50–56 J <0.01 27

MYLIOBATIDAE Myliobatis tenuicaudatus Southern Eagle Ray MEO, ZB, D 700–1200 J,A <0.01 28 1.29 11

GALAXIIDAE Galaxias maculatus Common Galaxias FM, ZB, SB 72A <0.01 28

SYNGNATHIDAE Urocampus carinirostris Hairy Pipefish ES, ZP, D 46 J <0.01 28

CLINIDAE Heteroclinus sp. Weedfish MS, ZB, D 44 J <0.01 28

PARALICHTHYIDAE Pseudorhombus jenynsii Smalltooth Flounder MEO, ZB, D 185–185 J <0.01 28

MONACANTHIDAE Monacanthid sp. Leatherjacket MS, OV, D 66 J <0.01 28

ELOPIDAE Elops machnata Australian Giant Herring MS, PV, BP 397–750 3.07 5

POMATOMIDAE Pomatomus saltatrix Tailor MEO, PV, P 192–395 J,A 2.91 6

SPARIDAE Chrysophrys auratus Snapper MEO, ZB, BP 145–246 J 1.94 8

RHINOBATIDAE Aptychotrema vincentiana Western Shovelnose Ray MEO, ZB, D 220–880 J,A 1.62 10

TRIAKIDAE Mustelus antarcticus Gummy Shark MS, ZB, D 750–965 J 0.81 14

CARANGIDAE Trachurus novaezelandiae Yellowtail Scad MS, ZB, P 220 J 0.16 21

Total number of individuals 150,880

40

619

21 Total number of species

Estuarine usage, E; freshwater migrant (FM), estuarine species (ES), estuarine & marine (EM), marine estuarine-opportunist (MEO), marine

straggler (MS). Feeding mode, F; zooplanktivore (ZP), zoobenthivore (ZB), piscivore (PV), omnivore (OV), opportunist (OP), detritivore (DV).

Habitat, H; small pelagic (SP), small benthic (SB), pelagic (P), demersal (D), bentho-pelagic (BP).

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Marine spawning species (i.e. marine estuarine-opportunists and marine stragglers)

dominated the fish composition of both the shallow nearshore and deeper offshore waters,

accounting for 68–81% of species (Fig. 2.5a), while 19–28% of species were estuarine

spawners (i.e. estuarine & marine and estuarine species). Only two freshwater-spawning

species (freshwater migrants) were recorded (G. holbrooki and G. maculatus), both of

which were captured in the nearshore waters (Table 2.1; Fig. 2.5a). Zoobenthivores were

the most prevalent feeding guild, accounting for 57–60% of all species in each the

nearshore and offshore waters (Fig. 2.5b). In the former waters, zooplanktivores and

omnivores accounted for a further 12–15% of species, while few piscivores, detritivores

and opportunists were recorded (Fig. 2.5b). Comparatively, piscivores comprised c. 19%

of species in the offshore waters, while only one zooplanktivore (E. australis) was

recorded (Table 2.1; Fig. 2.5b). Demersal fishes dominated habitat guild composition

throughout the system, accounting for 38–45% of species in both the nearshore and

offshore waters (Fig 2.5c). Small pelagic and small benthic fishes collectively accounted

for 35% of species in the nearshore waters, while in the offshore waters, these guilds were

either not caught or represented only a small proportion of fish, with large pelagic and

bentho-pelagic species being considerably more abundant (Fig. 2.5c).

Figure 2.5 Proportion of species in the nearshore (NS) and offshore (OS) waters in each

estuarine usage guild (a), feeding mode guild (b) and habitat guild (c). Guild abbreviations

are given in Table 2.1.

(a) (b) (c)

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2.3.3 Regional, seasonal and interannual differences in nearshore fish communities

Mean fish abundance, species richness and diversity

The mean abundance of fish in the nearshore waters differed significantly between

seasons and years, with the latter being slightly more influential (Appendix 2.3). Fish

abundance was considerably higher during the second year of sampling, and was highest

in autumn and lowest in spring or summer (Fig. 2.6a). Mean species richness, differed

significantly between regions, seasons and years and also had a significant season × year

interaction (Appendix 2.3), with the latter having the greatest effect. This interaction was

largely due to mean values being greatest in the second year in all seasons except winter

(Fig. 2.6b), while the significant regional differences reflected the notably greater values

in the WI, DR and especially the FR (c. 4.8–5.2 species) compared to the two Nornalup

Inlet regions (i.e. LN and UN, 4.2–4.3 species; Fig. 2.6c). Average taxonomic distinctness

differed significantly only among regions (Appendix 2.3) and displayed directly opposing

trends to those in mean species richness, being greatest in the two Nornalup Inlet regions

and lowest in the two river regions (Fig. 2.6d).

Figure 2.6 Mean number (± SE) of (a) individuals and (b) species recorded on each

sampling occasion within each season of the first (◼) and second () year of sampling,

and the mean (± SE) (c) number of species and (d) average taxonomic distinctness

recorded on each sampling occasion within each region. Regions; Deep River (DR)

Frankland River (FR), Walpole Inlet (WI), Upper Nornalup (UN) and Lower Nornalup

(LN). Seasons; winter (W), spring (Sp) summer (S) and autumn (A).

(a)

(b)

(c)

(d)

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Species composition

Species composition of the nearshore fish community was shown by PERMANOVA to

differ significantly among regions, seasons and years, as well as for the region × season

and season × year interactions (Appendix 2.4). However, the region main effect was by

far the most important, followed by the first of the above interactions (Appendix 2.4).

Further investigation of these spatio-temporal differences using a region × season × year

ANOSIM also showed significant overall differences for each factor, and that the greatest

differences, although only moderate in their extent, occurred among regions (Global R =

0.333), followed by seasons (Global R = 0.200) then years (Global R = 0.153; Table 2.2).

All pairwise tests between regions were significant, with the greatest and moderately high

differences occurring between the Nornalup Inlet regions (LN and UN) and river regions

(DR and FR), i.e. R = 0.482–0.556 (Table 2.2). This was illustrated on the centroid nMDS

ordination plot in Fig. 2.7a, in which the points representing the latter regions lay on the

opposite side from the former. The main causes of the region × season interaction are also

evident from this plot, namely the far greater seasonal differences in the riverine regions

(longer trajectories) than all others (Fig. 2.7a).

Table 2.2 Global P and R values, as well as pairwise R values, from three-way crossed

(region × season × year) ANOSIM tests of the nearshore species composition and guild

composition (estuarine usage, feeding mode and habitat) data. Significant (P < 0.05)

pairwise test results are in bold.

Species composition Estuarine usage guilds Years (Global R = 0.153, P = 0.001) Years (Global R = 0.100, P = 0.011) Seasons (Global R = 0.200, P = 0.001) Seasons (Global R = 0.063, P = 0.016) W Sp S W Sp S Sp 0.242 Sp 0.076 S 0.153 0.173 S 0.094 0.057 A 0.205 0.292 0.176 A 0.082 0.077 0.032 Regions (Global R = 0.333, P = 0.001) Regions (Global R = 0.300, P = 0.001) DR FR WI UN DR FR WI UN FR 0.179 FR 0.003 WI 0.292 0.184 WI 0.089 0.220 UN 0.499 0.482 0.303 UN 0.367 0.459 0.149 LN 0.544 0.556 0.384 0.085 LN 0.674 0.679 0.455 0.043 Feeding mode guilds Habitat guilds Years (Global R = 0.077, P = 0.028) Years (Global R = 0.140, P = 0.001) Seasons (Global R = 0.111, P = 0.001) Seasons (Global R = 0.159, P = 0.001) W Sp S W Sp S Sp 0.207 Sp 0.186 S 0.071 0.057 S 0.088 0.210 A 0.108 0.230 0.014 A 0.162 0.220 0.122 Regions (Global R = 0.178, P = 0.001) Regions (Global R = 0.172, P = 0.001) DR FR WI UN DR FR WI UN FR 0.202 FR 0.164 WI 0.144 0.069 WI 0.207 0.042 UN 0.344 0.187 0.004 UN 0.218 0.192 0.115 LN 0.563 0.223 0.125 0.046 LN 0.131 0.365 0.238 0.115

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Figure 2.7 nMDS ordination plot constructed from the centroids of the nearshore species

composition recorded in (a) each region × season combination and (b) each season in each

year. Trajectories indicate the temporal order of sampling. Regions; Deep River ()

Frankland River (), Walpole Inlet (), Upper Nornalup (◆) and Lower Nornalup (◼).

Seasons; winter (W), spring (Sp) summer (S) and autumn (A). Years; 2014–15 (solid);

2015–16 (dashed).

Figure 2.8 Shade plot of the pre-treated abundances of the most prevalent nearshore fish

species in each estuarine region, season and sampling year of sampling. Regions; Deep

River (DR) Frankland River (FR), Walpole Inlet (WI), Upper Nornalup (UN) and Lower

Nornalup (LN). Seasons; winter (W), spring (Sp) summer (S) and autumn (A). Years;

2014–15 (black); 2015–16 (magenta). Spawning locations; marine (marine stragglers and

marine estuarine-opportunists; ), estuarine (estuarine & marine and solely estuarine

species; ) and freshwater (freshwater migrants; ).

(a) (b)

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Pairwise ANOSIM tests between seasons also detected significant differences in species

composition in each case, although their extent was generally low, ranging from R =

0.292 for spring vs autumn to R = 0.153 for winter vs summer (Table 2.2). An nMDS

ordination plot of the centroids in each season and year (Fig. 2.7b) showed that each

sampling occasion was clearly separated, with no overlap between the first year of

sampling (left side of the plot) and the second (right side). Moreover, the seasonal trends

in each year were notably different, illustrating the underlying causes of the season × year

interaction. For example, spring was most distinct from both winter and autumn in the

first year, whereas more uniform and sequential seasonal shifts occurred in the second

year (Fig. 2.7b).

The shade plot in Fig. 2.8 reveals the species that contributed most to the above regional

and temporal differences in fish species composition. From a regional perspective, the

LN and UN were characterised by a considerably greater number of relatively abundant

species (26–28) than the FR and especially DR (16–18). In the former regions, moderate

to high abundances of marine spawning species, e.g. F. lateralis, L. presbyteroides, S.

punctatus and Aldrichetta forsteri, were recorded during most or several sampling

occasions, while estuarine spawning species including L. wallacei, Afurcagobius

suppositus, P. olorum, A. butcheri and Arenigobius bifrenatus were far more abundant in

the FR and DR. The WI contained a mix of estuarine and marine spawning species and,

interestingly, was the only region where the estuarine and marine E. australis was caught

regularly and, during the second autumn, in substantial numbers (Fig. 2.8). While the

highly abundant F. lateralis, L. presbyteroides and L. wallacei were found consistently

throughout the estuary on most sampling occasions, they exhibited regional preferences

as outlined above, and also showed marked seasonality. Leptatherina presbyteroides was

generally more abundant during autumn and/or winter, particularly in the UN, while L.

wallacei was more abundant during summer and/or spring in the LN, UN and WI, but

typically most abundant during autumn in the FR and DR (Fig. 2.8). Favonigobius

lateralis was abundant during most seasons within the LN and UN, but in the FR and DR

was most abundant during summer and/or autumn. The three other gobiid species

recorded (A. suppositus, P. olorum and A. bifrenatus) were similarly far more abundant

during summer, and most evidently in the FR. Variability in the abundance of several

species was also observed between the two sampling years. Notably, F. lateralis was

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typically less abundant during the second year, while the opposite was often true for R.

sarba, L. presbyteroides and L. wallacei (Fig. 2.8).

Guild composition

Guild composition, based either on estuarine use, feeding mode or habitat, differed

significantly among regions, seasons and years in all cases (Appendix 2.4). The region ×

season interaction was also significant, as was the season × year interaction in the case of

habitat guilds. As with species composition, the region main effect most strongly

influenced both estuarine use and feeding mode guild composition, and was the second

most influential term for habitat guild composition behind the region × season interaction

(Appendix 2.4).

Three-way crossed ANOSIM tests for each of the above guild types similarly revealed

significant region, season and year differences, with the overall extent of regional

differences (Global R = 0.172–0.3) being greater than those for seasons (Global R =

0.063–0.159) and years (Global R = 0.077–0.14) in all cases (Table 2.2). Although overall

regional differences were only small to moderate, some pairwise comparisons revealed

moderately high differences, especially for the estuarine use guilds. For example, the

composition in the LN was clearly distinct from that in all other regions except the UN

(R = 0.455–0.679; Table 2.2), reflecting the notably higher proportion of marine-

spawning species (marine stragglers and marine estuarine-opportunists), especially

compared to the FR and DR where most individuals were estuarine residents. The latter

region was also the only one where freshwater migrants were recorded, and only during

spring (Fig. 2.9a). A far higher proportion of marine straggler species during summer in

LN, while estuarine & marine fishes were clearly most abundant in WI and UN during

autumn, and also winter in the latter region. ANOSIM did not, however, detect any

significant differences in estuarine usage composition between individual pairs of seasons

(Table 2.2), and the small interannual differences were mainly due to higher proportions

of estuarine species and estuarine & marine species, but lower proportions of marine

estuarine-opportunist species, in the second year (Fig. 2.9b).

Among feeding guilds, moderate to moderately high differences occurred between the

DR and both of the Nornalup basin regions (R = 0.344–0.563; Table 2.2), reflecting the

fact that opportunist species dominated catches in the DR, but were absent in the LN and

in relatively low proportions in the UN (Fig. 2.9c), while the reverse was generally true

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for zooplanktivores and zoobenthivores. During certain seasons, piscivores and

detritivores were also far more abundant in the latter two regions compared to the former,

further contributing to regional differences and the region × season interaction. Although

to a lesser extent, similar differences in guild composition also occurred between the

FR/WI and the LN (R = 0.125–0.223; Table 2.2), due to prevalence of opportunists in the

former regions within most seasons (Fig. 2.9c). When pairwise comparisons were made

between seasons (Table 2.2), ANOSIM detected only significant differences among

winter, spring and autumn (R = 0.108–0.23; Table 2.2), which was mainly due to

zooplanktivores being most abundant during autumn, while detritivores and piscivores

were most abundant during winter and spring, respectively (Fig. 2.9c). Differences

between the two sampling years were very small, and reflected higher proportions of

opportunistic fishes in the second year, while the reverse was true for zoobenthivores,

piscivores and detritivores (Fig. 2.9d).

Habitat guild composition differed significantly between all pairs of regions except WI

and FR, but the extent of these differences was low to moderate, with the greatest

occurring between FR and LN (R = 0.365; Table 2.2). Notably, higher proportions of

pelagic and/or demersal fishes were caught in the LN, UN and WI than the two riverine

regions, where small benthic, small pelagic and/or bentho-pelagic fishes comprised the

majority of catches (Fig. 2.9e). However, the regional differences in these guild

proportions varied seasonally, reflecting the relatively influential region × season

interaction. For example, pelagic fish were abundant in the LN during winter and summer

(33–43%) but contributed only 10–12% to catches during autumn and spring (Fig. 2.9e),

while small pelagic fish were abundant in the FR in autumn and winter (48–53% of fish)

but not in summer (11%; Fig. 2.9e). Pairwise differences between seasons were small,

with the greatest involving spring (R = 0.186–0.22; Table 2.2), which were generally due

to generally lower proportions of small benthic and small pelagic fish, and greater

proportions of pelagic and demersal fish in this season. Interannual differences broadly

reflected greater proportions of small benthic fish in the first year and bentho-pelagic fish

in the second (Fig. 2.9f), but the nature of these differences varied between seasons. For

example, in the second year, bentho-pelagic fish comprised 44% of the catch in autumn

but only 11% in spring (Fig. 2.9f).

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Figure 2.9 Proportions of (a) each estuarine usage guild recorded in each region and

season, and (b) year, (c) each feeding mode guild recorded in each region and season, and

(d) year, and (e) each habitat guild recorded in each region and season, and (f) season and

year. Estuarine usage guilds; freshwater migrant (FM), estuarine species (ES), estuarine

& marine (EM), marine estuarine-opportunist (MEO) and marine straggler (MS).

Feeding mode guilds; zooplanktivore (ZP), zoobenthivore (ZB), piscivore (PV),

omnivore (OV), opportunist (OP) and detritivore (DV). Habitat guilds; small pelagic

(SP), small benthic (SB), pelagic (P), demersal (D) and bentho-pelagic (BP).

(c) (d)

(a) (b)

(e) (f)

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Relationships between fish community composition and water quality parameters

Overall spatio-temporal patterns in the nearshore fish community were shown by

BIOENV to be significantly matched to those in a combination of salinity and temperature

(P = 0.02), but the extent of that correlation was very small (ρ = 0.074). Given the

relatively strong regional and region × season differences in fish composition detected by

PERMANOVA (Appendix 2.4), further BIOENV tests were then undertaken within each

season × year combination to compensate for any confounding temporal influences.

These tests detected a significant and far stronger correlation between the fish and salinity

and temperature data in spring of the first year of sampling (P = 0.01; ρ = 0.462) and

during winter of the second year (P = 0.01; ρ = 0.392), but did not find significant matches

on any other sampling occasion. An nMDS plot constructed with fish species composition

data and overlayed with corresponding salinity and temperature values (Appendix 2.5a),

displays a general pattern of samples from each region with similar salinity and or

temperature values being grouped closely together. When a similar plot from spring only

is examined (Appendix 2.5b), this pattern is more evident, with generally decreasing

salinity and temperature from the left to right of the plot (i.e. from the LN to the FR), with

the exception of samples from the DR. Note, that as no water quality variables were able

to be collected during the second spring of sampling (see previously), this plot and the

aforementioned analyses only contain fish samples from spring during the first sampling

year.

DistLM determined that a combination of all three water quality variables, i.e. salinity,

temperature and DO, best explained the overall patterns in fish species composition, but

again this provided only a relatively weak correlation (R = 0.10, P = 0.001). A dbRDA

plot corresponding this analysis (Appendix 2.6a) shows separation within each region of

samples from winter, when temperatures were coolest and salinities lowest, with those of

summer where the reverse was true, although patterns within other seasons are less clear.

Within individual seasons, the strongest correlation between the pattern of fish fauna and

that of water quality variables again occurred during spring, where salinity and

temperature cumulatively explained 27% of variation (P = 0.002). During summer, a

combination of salinity and DO explained 13% of variation (P = 0.001), while during

winter salinity alone provided the best fish (R = 0.10, P = 0.001), and no significant

matches were detected during autumn (P = 0.094). Examination of dbRDA plots

corresponding to these tests (Appendix 2.6b–d), shows that during spring and summer

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correlations with water quality variables and fish fauna were largely explained by spatial

(regional) separation, while in winter, differences between the two sampling years had

more influence than spatial effects.

2.3.4 Regional, seasonal and interannual differences in offshore fish communities

Mean abundance, species richness and diversity

Unlike in the nearshore waters, the mean abundance of fish in the offshore waters differed

significantly only among regions (Appendix 2.7), being far higher in the WI (c. 14 fish

h−1) than all other regions and lowest in the LN (c. 1 fish h−1; Fig. 2.10). Also in contrast

to the shallows, no significant regional, seasonal or interannual differences were detected

in the species richness or taxonomic distinctness of the fish fauna in the deeper waters

(Appendix 2.7).

Figure 2.10 Mean number (± SE) of fish h−1 recorded in the offshore waters of each

region of the Walpole-Nornalup Estuary (Lower Nornalup; LN, Upper Nornalup; UN,

Walpole Inlet; WI and Frankland River; FR).

Species composition

Significant differences in offshore fish species composition were detected only between

regions (P ≤ 0.002; Appendix 2.8, Table 2.3). Pairwise ANOSIM tests between regions

showed the WI and LN were clearly distinct (R = 0.556), followed by low to moderate

differences between WI/FR and LN/FR (R = 0.236–0.343), whereas the remaining

pairwise comparisons were not significant (Table 2.3). A shade plot (Fig. 2.11) revealed

markedly higher catches of A. georgianus and A. butcheri in the WI than LN, while more

consistent catches of Mugil cephalus, P. octolineatus and E. machnata, but lower

abundances of A. georgianus, were recorded in the FR than WI. Further contributing to

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regional differences were consistent catches of several other species including

Pomatomus saltatrix, Cnidoglanis macrocephalus and R. sarba in the FR and WI, but not

LN, which also resulted in a greater overall spread of species in the former regions, while

Mustelus antarcticus, S. punctatus, E. australis and Trachurus novaezelandiae were

recorded in the LN, but not the FR or WI.

Guild composition

PERMANOVA detected significant regional differences in estuarine usage, feeding mode

and habitat guild composition in the offshore waters (Appendix 2.8). Region × season

effects were also significant for the first two of the above guild types, as were region ×

year effects for estuarine usage and season × year effects for feeding mode composition.

Regional effects were, however, either the most important or close to the most important

in each case. As was the case with species composition, ANOSIM employing all estuarine

usage and feeding mode guild composition data detected the greatest regional difference

between LN and WI (R = 0.472–0.537; Table 2.3). In the case of habitat guilds, however,

ANSOIM did not detect significant regional differences (Global R = 0.075, P = 0.163;

Table 2.3), and thus, pairwise tests among regions were not examined for this guild.

Table 2.3 Global P and R values, as well as pairwise R values, from three-way crossed

(region × season × year) ANOSIM tests of the offshore species and guild composition

(estuarine usage, feeding mode and habitat) data. Significant (P < 0.05) pairwise test

results in bold.

Species composition Estuarine usage guilds

Years (Global R = 0.160, P = 0.050) Years (Global R = 0.139, P = 0.100)

Seasons (Global R = 0.109, P = 0.160) Seasons (Global R = 0.088, P = 0.184)

Regions (Global R = 0.234, P = 0.003) Regions (Global R = 0.172, P = 0.017)

FR WI UN FR WI UN

WI 0.343 WI 0.157

UN 0.046 0.120 UN 0.093 0.157

LN 0.236 0.556 0.019 LN 0.204 0.472 −0.093

Feeding mode guilds Habitat guilds

Years (Global R = 0.120, P = 0.089) Years (Global R = 0.060, P = 0.271)

Seasons (Global R = 0.116, P = 0.102) Seasons (Global R = 0.088, P = 0.145)

Regions (Global R = 0.176, P = 0.009) Regions (Global R = 0.075, P = 0.163)

FR WI UN

WI 0.231

UN 0.065 0.324

LN 0.185 0.537 −0.120

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Figure 2.11 Shade plot of the pre-treated abundances of each fish species recorded within

the offshore waters of each region, i.e. Lower Nornalup (LN), Upper Nornalup (UN),

Walpole Inlet (WI) and Frankland River (FR).

The proportion of marine spawning species (marine stragglers and marine estuarine-

opportunists) was by far the greatest in the LN and UN, while estuarine spawning species

(estuarine and estuarine & marine species) comprised most of the catches in the WI and

FR (Fig. 2.12a). Interestingly, no estuarine species were caught in the offshore waters of

the LN or UN, but marine estuarine-opportunists and estuarine & marine species were

recorded throughout all regions and seasons and marine straggler species were found in

the FR in both seasons. The region × season interaction reflected considerably greater

contributions of estuarine species during winter in both the WI and FR, plus a winter

decrease in the proportion of estuarine & marine species in those regions, but an increase

in the LN (Fig. 2.12a). Between the two sampling years, the proportion of marine

stragglers was highest in the LN and FR during the first year, while the reverse was true

in the WI, where estuarine and estuarine & marine species comprised the vast majority of

catches during the first year, but not the second (Fig. 2.12b). Contrastingly, in all other

regions the latter guild was proportionately more abundant during the second year than

the first. Among feeding guilds, catches in the LN were comprised entirely of

zooplanktivores, zoobenthivores and/or piscivores, and while these guilds similarly

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dominated catches in the UN, omnivorous fishes were also caught (Fig. 2.12c). In

contrast, opportunists comprised a large proportion of the catches in the WI and FR,

particularly during winter, with detritivores also being prevalent in the latter region but

only in summer. From a seasonal perspective, the proportion of opportunistic and

omnivorous species was noticeably higher in winter than summer, especially in the first

year (Fig. 2.12d), while the opposite was true for piscivores and detritivores. Lastly, the

significant regional differences in habitat guilds mainly reflected a progressive decline in

the proportion of demersal species from the lower (LN) to upper (FR) reaches of the

system (Fig. 2.12e), while the opposite was true for bentho-pelagic fishes. While pelagic

fish made considerable contributions to all regions, small pelagics were not recorded at

all in the FR and made only a small contribution to the WI.

Relationships between fish community composition and water quality parameters

As PERMANOVA tests of fish species composition only detected significant regional

differences, the following BIOENV and DistLM tests were undertaken on the full data

set. BIOENV demonstrated that a combination of surface and bottom salinity best

matched with the overall spatio-temporal patterns in the offshore fish community, but that

this correlation was moderately low (P = 0.01; ρ = 0.248). Examination of an nMDS plot

of species composition overlayed with salinity (Appendix 2.9a), however, displays that

fish samples were grouped far more closely by spatial region than salinity. In contrast,

DISTLM employing the above data indicated surface salinity and DO best explained

patterns in fish composition, although again the correlation was only weak (P = 0.028; R

= 0.11). A distance based redundancy analyses plot for this test (Appendix 2.9b) displays

fish samples recorded during the first winter of sampling when the lowest salinities were

recorded as being clearly separated from those of all other sampling occasions, with the

exception of one sample from FR sample during the second summer.

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Figure 2.12 Proportions of (a) each estuarine usage guild recorded in each region and

season, and (b) year, (c) each feeding mode guild recorded in each region and season, and

(d) season and year, and (e) each habitat guild recorded in each region. Estuarine usage

guilds; estuarine species (ES), estuarine & marine (EM), marine estuarine-opportunist

(MEO) and marine straggler (MS). Feeding mode guilds; zooplanktivore (ZP),

zoobenthivore (ZB), piscivore (PV), omnivore (OV), opportunist (OP) and detritivore

(DV). Habitat guilds; small pelagic (SP), pelagic (P), demersal (D) and bentho-pelagic

(BP).

(a) (b)

(c) (d)

(e)

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2.4 DISCUSSION

This component of the study has focussed on gaining a comprehensive understanding of

the current fish fauna throughout the Walpole-Nornalup Estuary, and investigating how

its species pool is shaped by environmental filters acting across different spatial

(biogeographical to local) and temporal (interannual to seasonal) scales. Forty-six species

from 29 families were recorded throughout the shallow and deeper waters of the estuary

from July 2014 to May 2016, with marine spawning fishes being the most abundant.

Juveniles of most species, including many that are recreationally and/or commercially

important, were also recorded. This highlights the nursery role of this estuary, which is

one of the few on the south coast of Western Australia that is permanently open to the

ocean. These data, together with those recorded by other workers in various south-western

Australian estuaries with divergent biogeographic, morphological and environmental

characteristics (Table 2.4), were used to test the set of hypotheses posed in section 2.1

regarding the influences of the above environmental filters.

2.4.1 How does the fish faunal diversity of the Walpole-Nornalup compare with that of other south-western Australian estuaries in different bioregions and with different mouth states?

There was mixed support for the first hypothesis posed in this study, namely that the fish

fauna of the Walpole-Nornalup will be less diverse than those of permanently-open

estuaries in the lower west coast bioregion, but more diverse and more influenced by

marine species than those of intermittently-open estuaries in the south coast bioregion. In

agreement with this hypothesis, the total fish species richness recorded in both the

nearshore and offshore waters of the Walpole-Nornalup (i.e. 40 and 21 species,

respectively) was lower than that of several permanently-open estuaries along the lower

west coast (nearshore 43–57 species; offshore 24–25 species; Table 2.4). The fish fauna

of the Walpole-Nornalup was also more taxonomically diverse than those of several

nearby seasonally-open or normally-closed estuaries on the south coast (Table 2.4; Fig.

2.13), and its nearshore waters contained a greater contribution of marine spawning

species (marine stragglers and marine estuarine-opportunists; Fig. 2.14). In contrast to the

above hypothesis, taxonomic distinctness was lower in west-coast estuaries than in the

Walpole-Nornalup (Fig. 2.13). Additionally, offshore species richness in this system was

substantially lower than previously recorded in nearby seasonally-closed south coast

estuaries, namely the Broke, Wilson and Irwin Inlets (i.e. 21 vs 27–31 species; Table 2.4).

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Table 2.4 Summary of the biogeographical, geomorphological and environmental characteristics of various estuaries in south-western Australia and their

fish species richness and most abundant taxa. All fish composition data obtained using a 21.5 m seine net (3 and 9 mm mesh) and multi–mesh gill nets

(8 × 20m panels, 38–127 mm mesh) to sample nearshore and offshore waters, respectively. Physico–chemical water quality variables; temperature (T),

salinity (S) and dissolved oxygen (DO).

Estuary Data source(s)

Geomorphology and habitat Physico–chemical water quality variables^

Fish species richness and most abundant species#

Nearshore waters Offshore waters

Swan–Canning Estuary 32.055°S, 115.735°E West coast Permanently-open (Hallett, 2010)

Area 55 km2 Linear length 60km Typically ≤5 m deep.

Coarse–fine sand, silt, mud and river gravels. Diverse physical structure. Seagrasses (mainly Halophila ovalis) in lower/middle estuary. Rushes in littoral of upper estuary. Various macroalgae species.

Nearshore T: 12–14 °C (W), 24–31 °C (S) S: 2–22 (W), 9–37 (S) DO: 5–7 mg L–1 (W), 5–9 mg L−1 (S) Offshore T: 13–17 °C (W), 23–29 °C (S) S: 3–23 (W), 10–36 (S) DO: 3–7 mg L–1 (W), 4–7mg L–1 (S)

57 spp. (60% marine*) L. wallacei P. olorum L. presbyteroides Papillogobius punctatus Torquigener pleurogramma

24 spp. (71% marine) Nematalosa vlaminghi Amniataba caudavittata A. butcheri M. cephalus E. australis

Peel–Harvey Estuary 32.526°S, 115.710°E West coast Permanently-open (Potter et al., 2016; C. Hallett unpubl. data)

Area 130km2 Linear length c. 35 km Typically ≤2 m deep.

Coarse–fine sands, silt, soft mud. Seagrasses (mainly H. ovalis) in basins and channel. Various macroalgae. Vegetation in littoral zones of basins/rivers.

Nearshore T: 13–17 °C (W), 22–28 °C (S) S: 20–32 (W), 33–42 (S) Offshore T: 11–15 °C (W), 17–29 °C (S) S: 4–33 (W), 2–53 (S) DO: 3–11 mg L−1 (W), 0–9 mg L−1 (S)

53 spp. (65% marine) H. vittatus Atherinosoma elongata L. wallacei A. forsteri Ostorhinchus rueppellii

24 spp. N. vlaminghi M. cephalus Gerres subfasciatus A. butcheri P. saltatrix

Leschenault Estuary 33.27°S, 115.70°E West coast Permanently-open (Veale et al. 2014)

Area 25km2 Linear length <15 km Typically ≤1 m deep.

Highly seasonal dense macroalgae throughout basin, various seagrass species.

Nearshore T: 15–16 °C (W), 26–36 °C (S) S: 23–32 (W), 30–49 (S)

43 spp. (70% marine) Not sampled A. elongata Craterocephalus mugiloides H. vittatus A. forsteri L. presbyteroides

Broke Inlet 34.937°S, 116.373°E South coast Seasonally-open (Chuwen et al., 2009b; Hoeksema et al., 2009; S. Hoeksema unpubl. data)

Area 48 km2 Linear length <20km Typically ≤2 m deep.

Coarse–fine sands, silt (OS waters). Some granite outcrops. Sparse Ruppia megacarpa and macroalgae.

Nearshore T: 13–15 °C (W), 22–27 °C (S) S: 6–18 (W), 8–38 (S) DO: 8–9 mg L–1 (W), 5–6 mg L–1 (S) Offshore T: 11–13 °C (W), 20–23 °C (S) S: 0–20 (W), 5–35 (S) DO: 8–10 mg L–1 (W), 3–5 mg L–1 (S)

11 spp. (36% marine) A. elongata L. wallacei L. presbyteroides F. lateralis P. olorum

31 spp. (81% marine)

Basin A. forsteri A. georgianus M. cephalus P. georgianus H. melanochir

Rivers M. cephalus A. butcheri A. georgianus

Walpole–Nornalup Estuary 35.005°S, 116.725°E South coast Permanently-open (Present study)

Area 15 km2 Linear length c. 17 km Typically ≤4 m deep.

Coarse–fine sands, silt/mud (OS waters). Areas of rock/gravel, isolated rocky reefs. Largely unvegetated, sparse seagrass and diverse macroalgae in lower estuary. Littoral vegetation in upper estuary.

Nearshore T: 13–15 °C (W), 23–25 °C (S) S: 3–31 (W), 24–37 (S) DO: 10–11 mg L–1 (W), 6–8 mg L–1 (S) Offshore T: 12–15 °C (W), 23–25 °C (S) S: 3–30 (W), 25–37 (S) DO: 5–11 mg L–1 (W), 5–7 mg L–1 (S)

40 spp. (65% marine) L. presbyteroides L. wallacei E. australis F. lateralis P. olorum

21 spp. (76% marine)

Basins A. georgianus A. butcheri R. sarba P. saltatrix A. vincentiana

Rivers A. butcheri P. octolineatus E. machnata

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Estuary Data source(s)

Geomorphology and habitat Physico–chemical water quality variables^

Fish species richness and most abundant species#

Nearshore waters Offshore waters

Irwin Inlet 34.99°S, 116.965°E South coast Seasonally-open (Chuwen et al., 2009b; Hoeksema et al., 2009; S. Hoeksema unpubl. data)

Area 10 km2 Linear length <10 km Typically <2 m deep.

Coarse–fine sands, silt (OS waters). Dense R. megacarpa and macroalgae throughout basin.

Nearshore T: 15–17 °C (W), 21–22 °C (S) S: 11 (W), 38–39 (S) DO: 7–8 mg L–1 (W), 4–6 mg L–1 (S) Offshore T: 12–15 °C (W), 22–24 °C (S) S: 1–25 (W), 32–38 (S) DO: 2–9 mg L–1 (W), 3–5 mg L–1 (S)

20 spp. (40% marine) A. elongata L. wallacei L. presbyteroides F. lateralis P. olorum

27 spp. (78% marine)

Basin A. forsteri A. georgianus C. macrocephalus P. georgianus A. truttaceus

Rivers M. cephalus A. butcheri A. truttaceus

Wilson Inlet 35.026°S, 117.333°E South coast Seasonally-open (Chuwen et al., 2009b; Hoeksema et al., 2009; S. Hoeksema unpubl. data)

Area 48 km2 Linear length <20 km2 Typically ≤2 m deep.

Coarse–fine sands, silt (OS waters). Some granite outcrops. Dense R. megacarpa and macroalgae throughout basin.

Nearshore T: 14–15 °C (W), 24–25 °C (S) S: 18–22 (W), 23–26 (S) DO: 7–9 mg L–1 (W), 4–7 mg L–1 (S)

Offshore T: 11–14 °C (W), 19–23 °C (S) S: 2–22 (W), 14–25 (S) DO: 5–9 mg L–1 (W), 2–6 mg L–1 (S)

19 spp. (47% marine) A. elongata L. wallacei P. olorum F. lateralis A. suppositus

27 spp. (78% marine)

Basin A. forsteri E. australis C. macrocephalus M. cephalus A. georgianus

Rivers A. butcheri M. cephalus A. forsteri

Oyster Harbour 34.97°S, 117.96°E Permanently-open (Chuwen et al., 2009b; Hoeksema et al., 2009; S. Hoeksema unpubl. data)

Area 15.6 km2 Linear length 15 km Typically <5 m deep, c. 12 m deep entrance channel.

Coarse–fine sands, silt in upper estuary. Some granite outcrops. Marine seagrasses (e.g. Posidonia) throughout basin.

Nearshore T: 15–16 °C (W), 24–27 °C (S) S: 7–18 (W),8–37 (S) DO: 8 mg L–1 (W), 3–6 mg L–1 (S)

Offshore T: 12–14 °C (W), 20–23 °C (S) S: 30–36 (W), 35–38 (S) DO: 5–9 mg L–1 (W), 2–5 mg L–1 (S)

34 spp. (68% marine) F. lateralis A. elongata L. wallacei L. presbyteroides A. suppositus

44 spp. (86% marine)

Basin P. octolineatus A. georgianus T. novaezelandiae P. georgianus A. georgianus

Rivers A. butcheri Argyrosomus japonicus M. cephalus

Wellstead Estuary 34.392°S, 119.399°E South coast Normally-closed (Chuwen et al., 2009b; Hoeksema et al., 2009; S. Hoeksema unpubl. data)

Area 2.5 km2 Linear length Typically ≤1 m deep.

Coarse–fine sands, mud. Low physical structure. Dense R. megacarpa in lower–middle estuary, dense samphire in littoral zones.

Nearshore T: 13–15 °C (W), 22–23 °C (S) S: 30–35 (W), 30–44 (S) DO: 7–8 mg L–1 (W), 5 mg L–1 (S)

Offshore T: 13–16 °C (W), 22–25 °C (S) S: 25–33 (W), 17–43 (S) DO: 6–9 mg L–1 (W), 2–7 mg L–1 (S)

17 spp. (41% marine) A. elongata P. olorum L. wallacei F. lateralis A. suppositus

17 spp. (59% marine)

Basin A. forsteri A. butcheri M. cephalus A. truttaceus Gymnapistes marmoratus

Rivers A. butcheri M. cephalus A. forsteri

^ Mean values during winter (W) and summer (S). # Full names of species which were also recorded in the Walpole-Nornalup are given previously in Table 2.1.

*A marine species refers to marine stragglers and marine estuarine-opportunists.

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Figure 2.13 Average taxonomic distinctness (Δ+) of the fish fauna recorded in the

Leschenault (L), Peel-Harvey (PH) and Swan-Canning (S) estuaries on the lower-west

coast of WA (open symbols), and in the Broke (BR), Wilson (WS), Irwin (IW), Oyster

Harbour (OY), Walpole-Nornalup (WN) and Wellstead (WE) estuaries on the south coast

of WA (closed symbols). Mouth-states; (◆) permanently open, (◆) seasonally open, (◆)

normally closed. Data sources for estuaries other than the Walpole-Nornalup are given in

Table 2.4.

Figure 2.14 Proportion of species in each estuarine usage guild in the nearshore and

offshore waters of Walpole-Nornalup Estuary (WN), Oyster Harbour (OY), Broke Inlet

(BR), Irwin Inlet (IW), Wilson Inlet (WS) and Wellstead Estuary (WE) on the south coast

of Western Australia. Estuarine usage guilds; freshwater migrant (FM), estuarine species

(ES), estuarine and marine (EM), marine estuarine-opportunist (MEO), marine straggler

(MS). Data for estuaries other than WN were obtained from Chuwen et al. (2009b) and

Hoeksema et al. (2009).

0 20 40 60 80

Number of species

60

70

80

90

100

De

lta

+

mouthcoastPOLWC

NCSC

POSC

SOSC

PHWE

OY

WSBR

IW

WN

S

Nearshore waters Offshore waters

Nearshore waters Offshore waters

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The observed bioregional differences in total fish species richness, with lower values

recorded in the Walpole-Nornalup as well as Oyster Harbour (also permanently-open and

located on WA’s south coast) compared to similarly open estuaries on the lower west

coast (Swan-Canning, Peel-Harvey and Leschenault), parallels declines with increasing

latitude globally (Edgar et al., 1999; Pease, 1999; Harrison & Whitfield, 2006c; Whitfield

et al., 2017b). As the majority of fish species in permanently-open estuaries in south-

western Australia (SWA) are marine spawning (e.g. Potter & Hyndes, 1999), this finding

at least partly reflects a sea temperature-driven decrease in marine species richness that

occurs southwards along the Western Australian coastline (e.g. Fox & Beckley, 2005). It

is also relevant that the poleward-flowing Leeuwin Current, which drives the dispersal of

eggs, larvae and juveniles of numerous inshore marine species and transports tropical

species into temperate waters in Western Australia (Hutchins & Pearce, 1994; Lenanton

et al., 2009), has a far greater effect along the west than south coast (Ayvazian & Hyndes,

1995). Given the combined effects of these biogeographical filters on the potential species

pool of the Walpole-Nornalup, it is thus unsurprising that its species richness is lower

than that of comparable systems on the west coast.

While species richness is a useful measure of biodiversity, it is well known to increase

with sampling effort. The potential influence of inconsistences in sampling methodology

between the various studies in Table 2.4 on the above-described species richness trends

is recognised. In this context, it should be noted that intensive nearshore sampling (480

seine net samples) of the seasonally closed Broke Inlet by Tweedley (2010) recorded just

27 fish species, compared to 40 in the permanently open Walpole-Nornalup (184

samples). Moreover, this sampling effort in both the Broke and Walpole-Nornalup was

comparable or greater than that employed by researchers in the Swan-Canning, Peel-

Harvey and Leschenault Estuaries (124–204 samples), yet the latter west coast estuaries

were notably more speciose as mentioned above. Average taxonomic distinctness, a

measure that is relatively independent of effort (Warwick & Clarke, 1995; 2001), was

also compared between estuaries (Fig. 2.13). Interestingly, the latter measure did not

display a clear relationship with biogeography. Given the sensitivity of taxonomic

distinctness to anthropogenic disturbances (Warwick & Clarke, 1995; Tweedley et al.,

2017), the lower taxonomic distinctness scores of the Swan-Canning, Peel-Harvey and

Leschenault Estuaries compared to those of the Walpole-Nornalup likely reflect the far

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more degraded environments of the former systems, masking any biogeographic

influences.

At a finer scale, the connectivity of an estuary with the ocean is well recognised as a major

filter of estuarine fish species pools, both through shaping environmental conditions

within a system and limiting accessibility for marine species (Harrison & Whitfield,

2006b; James et al., 2007; Harrison & Whitfield, 2008; Chuwen et al., 2009a; b; Nicolas

et al., 2010b; Potter et al., 2010; Whitfield et al., 2012c). When the influence of bioregion

is removed and only south coast estuaries are examined, the importance of estuarine

mouth state is clearly reflected by the far greater number and proportion of marine

spawning species in the nearshore waters of the permanently-open Walpole-Nornalup and

Oyster Harbour than nearby intermittently-open systems (i.e. 23–26 vs 4–9 species; Table

2.4; Fig. 2.13). Some examples of marine-spawning species caught in the nearshore

waters of the former estuaries but not the latter group include Ammotretis elongatus,

Arripis georgianus, Cristiceps australis and Enoplosus armatus (Table 2.1; Hoeksema et

al., 2009). The average taxonomic distinctness of the offshore fish fauna in the Walpole-

Nornalup was also far higher than in the above intermittently-open systems (Fig. 2.13),

and values in the nearshore waters were higher than in the Broke and Wellstead. As little

difference in the composition of freshwater and estuarine spawning species occurs among

these systems, these findings are likely to reflect the influence of various marine species

from different higher taxonomic levels such as order and family (e.g. elasmobranchs; see

below).

It should be noted, however, that unlike the Walpole-Nornalup, the nearshore fish faunas

of all other south coast systems presented in Fig. 2.13 were only sampled in the estuary

basins and not their tidal rivers (Hoeksema et al. 2009). Nonetheless, these sampling

differences had only a minor influence on the comparability of the species richness and

taxonomic distinctness trends presented here, given that only two of the species caught in

the Walpole-Nornalup were recorded solely in the rivers, namely the freshwater migrants

Gambusia holbrooki and Galaxias maculatus. Moreover, a reanalysis of the taxonomic

distinctness funnel plot using only data from the basin of the Walpole-Nornalup was

negligibly different from that in Fig. 2.13.

Like most estuaries throughout south-western Australia (Potter & Hyndes, 1999;

Hoeksema et al., 2009; Table 2.4), the shallow nearshore waters of the Walpole-Nornalup

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were overwhelmingly dominated by several highly abundant atherinid and gobiid species,

which are small-bodied, short-lived and recruit annually. In contrast to several other south

coast systems, however, the marine-associated atherinid Leptatherina presbyteroides was

by far the most abundant species in the Walpole-Nornalup (c. 80% of the catch) and was

widespread throughout the estuary on all sampling occasions. Such findings are likely

due to the estuary’s permanent connection with the ocean and thus greater marine

influences compared to other south coast systems that open intermittently. This atherinid

species has also been shown to be most abundant over bare sand habitat (Humphries &

Potter, 1993), which is more prevalent in the Walpole-Nornalup compared to several

other SWA estuaries (Table 2.4). Another marine-associated species, the engraulid

Engraulis australis (Dimmlich & Ward, 2006), was caught in high numbers (100–1000s

of individuals) in the shallows of Walpole-Nornalup on several occasions, particularly in

Walpole Inlet, and ranked third by abundance. This contribution was notably higher than

that previously recorded in the shallows of other SWA estuaries (e.g. Table 2.4; Potter &

Hyndes, 1999). While this finding is also likely related to the permanently-open nature of

the Walpole-Nornalup, a unique combination of intra-estuarine habitat characteristics,

namely the moderately saline, warm, shallow and nutrient rich Walpole Inlet (Deeley,

2001; Semeniuk et al., 2011), may make this estuary particularly favourable as a nursery

for E. australis (see next section).

In the deeper waters of the Walpole-Nornalup, Acanthopagrus butcheri and A.

georgianus were most abundant (c. 34–37% of the catch), followed by Rhabdosargus

sarba, Pelates octolineatus and Elops machnata (c. 3–5%). Acanthopagrus butcheri, a

euryhaline estuarine species, is abundant in the deeper waters of many estuaries of

southern Australia (Sarre & Potter, 1999; Table 2.4), particularly in their tidal rivers

(Chuwen et al., 2009b), and seemingly irrespective of estuary mouth-state. The marine-

spawning A. georgianus is abundant in the basins of many other south coast systems,

though not the normally-closed Wellstead Estuary (Table 2.4), reflecting the extended

isolation of the latter system from the marine environment. Similarly, R. sarba and P.

octolineatus were moderately to highly abundant in the offshore waters of several other

south coast estuaries (1–29% of the total catch; Chuwen et al., 2009b).

The regular occurrence of Elops machnata in the Walpole-Nornalup, and particularly in

the Frankland River where c. 90% of individuals were caught, contrasts with the findings

for other south coast estuaries where it has only been recorded in very low numbers

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(≤0.1% of the catch) and only in the basins (Chuwen et al., 2009b). The greater abundance

and upstream penetration of this pelagic, marine-spawning piscivore in the Walpole-

Nornalup is again likely to be attributed to its constant ocean connectivity. While E.

machnata is also regularly recorded in the permanently-open Swan-Canning and Peel-

Harvey estuaries on the lower west coast (Hallett & Tweedley, 2014; 2015; C. Hallett,

unpubl. data), it is proportionately less abundant (≤1% contribution). This may reflect

competition from other large predators in these latter systems such as Argyrosomus

japonicus, which were not recorded in the Walpole-Nornalup. It is also noteworthy that

two mugilid species, Aldrichetta forsteri and Mugil cephalus, were abundant throughout

the offshore waters of Broke, Irwin and Wilson Inlets and Wellstead Estuary, but not in

the Walpole-Nornalup or the basin of Oyster Harbour. Given the high contribution of

sediment, organic matter and small invertebrates to the diets of these species (Platell et

al., 2006), such findings may reflect the generally more eutrophic nature, reduced tidal

flushing and/or higher macrophyte biomass of these intermittently-open than

permanently-open south coast systems (Roy et al., 2001; Harrison & Whitfield, 2012).

2.4.2 How do intra-estuarine habitat filters shape the fish fauna of the Walpole-Nornalup Estuary?

In addition to the above broad-scale influences that shape estuarine fish faunas, intra-

estuarine habitat differences are also expected to have an influence, as proposed in the

second hypothesis for this study. In accordance with this hypothesis, the composition of

the nearshore fish fauna of the Walpole-Nornalup Estuary followed a longitudinal

estuarine gradient, exhibiting the greatest differences between the lower-most (Lower

Nornalup Inlet) and upper-most (Frankland and Deep Rivers) parts of the estuary. Species

diversity (total species richness and average taxonomic distinctness) also decreased with

distance upstream. Such ichthyofaunal patterns, which are typical of permanently-open

estuaries globally (e.g. Akin et al., 2005; Nicolas et al., 2010b; Whitfield et al., 2012a;

Teichert et al., 2017), generally reflect both proximity to the ocean and the often vastly

different habitats (including water physico-chemistry, substrate and/or structural

heterogeneity), that fish encounter along an estuary from its marine to freshwater extents.

Within the Walpole-Nornalup, the Lower Nornalup Inlet is characterised by typically

marine salinities (i.e. >30), coarse sediment (Semeniuk et al., 2011) and high algal and

seagrass diversity (Huisman et al., 2011). In contrast, the tidal rivers were often meso- to

oligohaline (mean salinities of c. 4–18 in winter/spring and 18–32 during

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autumn/summer) and contained fine sediment, few submerged macrophytes, dense

riparian vegetation and snags (Huisman et al., 2011; Semeniuk et al., 2011). As

hypothesised, numerous marine species, and particularly those with specialist feeding

modes (e.g. Favonigobius lateralis, Sillaginodes punctatus, Ammotretis rostratus,

Notolabrus parilus and Paraplagusia bilineata), were consistently more abundant in the

Lower Nornalup and contributed to its high diversity. Such findings undoubtedly reflect

the more suitable habitat and greater food availability for these species in the lower

estuary (Blaber & Blaber, 1980; Whitfield, 1983; Potter & Hyndes, 1999; Nicolas et al.,

2010a). For example, the gobiid F. lateralis has been shown in other estuaries to prefer

coarse sandy substrates (Gill & Potter, 1993; Humphries & Potter, 1993) and feed on

amphipods and small polychaetes (Humphries & Potter, 1993), whereas juvenile S.

punctatus are often associated with shallow seagrass beds and exhibit a clear feeding

preference for benthic copepods (Jenkins et al., 2011). Several estuarine and freshwater-

associated species, including L. wallacei, Afurcagobius suppositus, Pseudogobius

olorum, A. butcheri and Arenigobius bifrenatus, dominated the far less diverse fish faunas

in the Frankland and Deep rivers. The characteristics of these species, including fast

maturation, short life spans and/or generalist (i.e. opportunistic or omnivorous) feeding

modes, represent adaptations to highly variable environmental conditions (Teichert et al.,

2017), which were most evident in the upper estuary (see next section).

Interestingly, unlike the situation in the nearshore waters, a longitudinal diversity gradient

did not occur in the offshore fish fauna. Indeed, the greatest differences in species

composition occurred between the Lower Nornalup and Walpole Inlet, and total species

richness was lowest in the first of these regions, clearly contradicting hypothesis two.

These findings likely reflect the fact that while the shallows of the Lower Nornalup

contain coarse sediment, extensive macrophytes and high invertebrate diversity (Hodgkin

& Clark, 1988; Huisman et al., 2011), thereby providing suitable habitat and food for

many species, the benthic habitat in the deeper waters mostly comprises mud with little

vegetation and a depauperate invertebrate fauna (Hodgkin & Clark, 1988; Semeniuk et

al., 2011). The fish faunal differences between the Lower Nornalup and Walpole Inlet

were largely due to the consistently greater abundances of A. georgianus, A. butcheri and

Pomatomus saltatrix in the latter region, which may in part reflect greater prey

availability for these species, which are either piscivorous or omnivorous. As identified

in the previous subsection, the shallow Walpole Inlet was the only region of the estuary

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where the baitfish E. australis was abundant in the shallows, which would provide high

quality prey for piscivores. Compared to the larger Nornalup Inlet, the Walpole Inlet has

higher nutrient loadings (and can therefore support higher phytoplankton abundances;

Deeley, 2001), receives negligible freshwater input from its only tributary, the 15 km long

Walpole River (Brealey, 2005; Semeniuk et al., 2011), and is 1–2 °C warmer during

summer, the spawning period of E. australis (Dimmlich et al., 2004). All E. australis

caught in the Walpole Inlet were juveniles (<60 mm TL, far below the L50 of 99 mm for

this species [Dimmlich & Ward, 2006]), suggesting that the productive and saline waters

of the inlet serve as nursery for this planktivore prior to its migration into deeper coastal

areas, as occurs elsewhere in Australia (Dimmlich et al., 2004; Dimmlich & Ward, 2006).

While the above findings clearly suggest that the spatial differences in the fish

communities throughout the estuary relate to those in the environment, statistical

correlations between the fish and water quality (salinity, temperature and dissolved

oxygen concentration) data were generally weak or insignificant. This outcome may

partly reflect the numerous other intra-estuary habitat filters that shape the fish fauna (e.g.

benthic quality, physical structure, food availability) and which could not feasibly be

incorporated into the above analyses. Given the high environmental variability within

estuaries (e.g. Elliott & McLusky, 2002), it is also possible that the spot measurements

recorded were not entirely representative of the average physico-chemical conditions

occurring over an extended period (e.g. days to months), which may have further

contributed to a lack of correlation. To better compare such patterns in the future, it is

recommended that environmental parameters be more continuously monitored and

incorporated into hydrological models.

Finally, it is also noteworthy that spatial differences in the fish composition of the

Walpole-Nornalup were generally smaller than those documented in several other

permanently-open estuaries in SWA, such as the Swan-Canning (Loneragan et al., 1989;

Valesini et al., 2017) and Leschenault (Veale et al., 2014). As distance upstream is an

important determinant in shaping intra-estuary fish faunas (Martino & Able, 2003), it is

unsurprising that in the far longer Swan-Canning Estuary (i.e. 60 vs 17 km linear length),

more distinct ichthyofaunal differences occur between its upper and lower extents. For

example, ANOSIM tests employing nearshore species composition data in the latter

system revealed marked differences between the upper and lower estuary (R = 0.881–

0.989; Valesini et al., unpubl. data), while only moderate differences (R = 0.544–0.556)

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were observed in the Walpole-Nornalup. This likely reflects the penetration of several

marine-associated species such as L. presbyteroides, F. lateralis and R. sarba into the

upper regions of the Walpole-Nornalup, contrasting with the situation in the Swan-

Canning where these species are almost exclusively confined to the lower or middle

estuary (Prince et al., 1982; Gill & Potter, 1993; Valesini et al., 2017). While the

Leschenault is comparable in length to the Walpole-Nornalup (c. 15 km), it has a unique

geomorphology and vast areas of its basin receive no riverine inputs, resulting in extreme

salinity gradients and thus more pronounced spatial differences in fish species

composition (ANOSIM R between regions of up to 0.94; Veale et al., 2014).

2.4.3 How do environmental influences drive seasonal and interannual changes in the fish fauna of the Walpole-Nornalup Estuary?

Marked environmental changes within the Walpole-Nornalup Estuary occurred between

seasons and the two study years (2014–15 and 2015–16), which corresponded with

differences in climatic conditions as described below. As proposed in hypothesis three,

nearshore fish species and guild compositions, as well as species richness and mean

abundance, also differed significantly over the above temporal scales, and seemingly in

response to climatic drivers. Indeed, temporal changes in the latter two variables were

more pronounced than inter-regional differences. In further agreement with hypothesis

three, the extent of seasonal changes in nearshore species composition was greatest in the

upper estuary, reflecting the more variable environment of the tidal rivers (see below).

Additionally, changes in several structural attributes of the fish fauna were less

pronounced than those documented in many seasonally-open/normally-closed south coast

estuaries, which often undergo far greater environmental changes, both intra-annually and

interannually, due to their periodic isolation from the sea. Contradicting this hypothesis,

however, seasonal differences in species composition were greatest between spring and

both winter and autumn, not winter and summer as predicted. Furthermore, no significant

temporal differences were detected in any structural attribute of the offshore fish fauna.

While various water quality attributes in the shallows of the Walpole-Nornalup were most

different between winter and summer, which clearly corresponded with distinct

differences in rainfall and air temperature (Fig. 2.15a–c), this was not reflected in the

magnitude of seasonal differences in the fish fauna. These findings are likely due to the

influence of the recruitment of key species. Nearshore fish abundances were by far the

highest during autumn and winter, largely due to the vast numbers of L. presbyteroides

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(up to 21,576 individuals in a single sample), evidently following their recruitment from

spawning in spring/early summer of the previous year (Prince & Potter, 1983; Hoeksema

& Potter, 2006). This recruitment was clearly supported by seasonal length composition

plots for this species, which are presented in Appendix 2.10. These plots show the

appearance of juvenile (<40 mm TL) individuals during summer, with this cohort growing

in size during autumn and winter. The considerably higher mean species richness during

summer, and also autumn in the second year, was in part attributed to consistent catches

of three gobiid species, i.e. A. suppositus, P. olorum and A. bifrenatus. Length

composition plots of these species (Appendix 2.10, plot not shown for A. suppositus)

reveal the presence of numerous small individuals during summer, apparently following

a spring/early summer spawning period, which coincided with the optimal spawning

temperatures of 20–25 °C for these species (Gill & Potter, 1993; Gill et al., 1996; Wise,

2005). Various marine-associated species (e.g. S. punctatus, R. sarba, and N. parilus)

were also caught more frequently during summer, when nearshore salinities throughout

the estuary ranged from c. 25 to 36, further contributing to the high species richness.

The magnitude of seasonal changes in the nearshore fish species composition was far

greater in the Frankland and Deep Rivers than within the Nornalup Inlet. This presumably

reflects the more variable physio-chemical characteristics, and particularly salinity, of the

riverine reaches (Fig. 2.3; 2.4), a pattern typical of SWA estuaries (Kanandjembo et al.,

2001; Hoeksema & Potter, 2006; Chuwen et al., 2009a; b). Mean salinities in these

tributaries ranged from c. 4–18 in winter to 24–33 in summer, compared to those in the

Nornalup Inlet which ranged from c. 13–30 to 31–35. However, compared to findings in

several nearby intermittently-closed estuaries, i.e. the Broke, Irwin and Wilson Inlets and

the Wellstead Estuary (Hoeksema et al., 2009; Chuwen et al., 2009b), seasonal changes

in the fish composition of the Walpole-Nornalup Estuary were generally less marked. For

example, winter vs summer differences in the latter system were small (pairwise

ANOSIM, R = 0.153), compared to the far more distinct changes in the Wilson Inlet and

Wellstead Estuary (R = 0.633–0.714; Hoeksema et al., 2009). This likely reflects the

constant oceanic influences and thus greater environmental stability within the

permanently-open Walpole-Nornalup. This environmental stability was even more

pronounced in the deeper waters (Fig. 2.4), where no significant temporal changes in fish

species composition occurred. The above results are supported by similar findings from

temperate South Africa, where seasonal closure of estuaries has been shown to

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considerably reduce fish diversity and drive changes in species composition (e.g. Bennett,

1989; James et al., 2007; Whitfield et al., 2008).

Figure 2.15 Monthly mean (±SE) (a) maximum and (b) minimum air temperatures and

(c) total monthly rainfall recorded in the Walpole region, and (d) total monthly river flow

recorded in the upper Frankland River, during the first year of sampling (May 2014 to

April 2015; ◼) and the second (May 2015 to April 2016; ). Temperature and rainfall

data recorded at Bureau of Meteorology stations 009998 and 009611, respectively

(http://www.bom.gov.au/climate/data/), and flow data recorded at the Department of

Water Mount Frankland flow station (ID 605012; www.kumina.water.wa.gov.au).

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Markedly different rainfall patterns occurred between the two years of this study (Fig.

2.15c), resulting in notable changes in river flow regimes and thus the water quality

characteristics of the system. Winter and spring flows in the Frankland River, the tributary

which accounts for the majority of freshwater input to the estuary (Hodgkin & Clark,

1988; Semeniuk et al., 2011), were approximately twice as high during 2014–15 than

2015–16 (Fig. 2.15d). As a result, nearshore salinities during the second winter (c. 17–

30) were far higher than those in the first (c. 4–13). While salinity was not measured in

spring 2015–16 due to equipment malfunction, it is probable that a similar increase in

spring salinities also occurred between years. In contrast, summer and autumn flows,

although small compared to those of winter and spring, were both higher during 2015–16

than 2014–15 (Fig. 2.15d). Given the above, it is relevant that several marine-associated

species were substantially more abundant in the nearshore waters during the drier (2015–

16) than wetter (2014–15) sampling year, including L. presbyteroides (84,527 vs 36,747

total number of individuals), E. australis (7,419 vs 217) and R. sarba (721 vs 51), most

likely reflecting their preference for higher salinities. Interestingly, however, the

abundance of F. lateralis, a species typically associated with marine conditions (Gill &

Potter, 1993; Potter & Hyndes, 1999), decreased during the drier year, while three other

gobiid species (P. olorum, A. suppositus and A. bifrenatus), usually associated with

fresher–brackish conditions (Gill & Potter, 1993; Potter & Hyndes, 1999), were more

abundant. This could reflect the higher summer flows during 2015–16, which may have

favoured recruitment success among the latter three species and/or caused their

downstream displacement from upstream areas. Moreover, the poor recruitment of F.

lateralis during that year could also be attributable to the fresher summer conditions,

which may have hampered its spawning success (Wise, 2005).

2.4.4 The importance of the estuary as a nursery for marine species, and particularly those of fishery importance

More than 20 commercially and/or recreationally important species (e.g. Smallwood &

Sumner, 2007; Ryan et al., 2015; Fletcher & Santoro, 2015) were recorded in the

Walpole-Nornalup during the current study, including A. georgianus, A. truttaceus,

Chrysophrys auratus, Hyporhamphus melanochir, P. saltatrix, Cnidoglanis

macrocephalus, Platycephalus speculator, A. butcheri, Sillago schomburgkii, S.

punctatus and R. sarba. Most of these species, which are largely marine-spawning, were

caught either exclusively as juveniles or as both juveniles and adults, re-affirming that the

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Walpole-Nornalup clearly plays an important nursery role in supporting regional

fisheries. While most of these species are present in various other south coast estuaries

(e.g. Potter et al., 1990; Chuwen et al., 2009b; Hoeksema et al., 2009), juveniles of S.

punctatus, the most retained species by recreational fishers on the south coast (Smallwood

& Sumner, 2007; Ryan et al., 2015) and a highly valuable commercial species (Brown et

al., 2013), were notably more abundant in the nearshore waters of the Walpole-Nornalup.

Like many teleosts, several elasmobranch species depend on estuaries and sheltered

coastal areas as nursery environments, in part for their productivity but largely for

protection from predation (e.g. Heupel & Simpfendorfer, 2002; Heupel et al., 2007;

Cerutti-Pereyra et al., 2014). As most elasmobranchs cannot osmoregulate efficiently at

reduced salinities (Whitfield et al., 1981), highly marine-influenced systems such as the

Walpole-Nornalup are likely to provide the most favourable estuarine environments.

Indeed, in both this study and that by Potter and Hyndes (1994), five elasmobranch

species were recorded in the Walpole-Nornalup, i.e. Myliobatis tenuicaudatus,

Aptychotrema vincentiana, Mustelus antarcticus, Bathytoshia lata and Sphyrna zygaena,

which are largely absent from nearby intermittently-open estuaries (Chuwen et al.,

2009b). While elasmobranchs are traditionally regarded as marine stragglers in SWA

estuaries (Potter et al., 1990; Chuwen et al., 2009b; Tweedley, 2010; Potter et al., 2015a),

the regular presence of juvenile M. antarcticus within the Walpole-Nornalup, and also

juvenile and adult M. tenuicaudatus and A. vincentiana, suggests the importance of this

estuary as a nursery and, in the case of the latter two species, perhaps a primary nursery

in which adults give birth (Heupel et al., 2007). To better understand how these species

use the system throughout different life-cycle stages, further work using targeted

sampling and tracking techniques (e.g. acoustic telemetry) is recommended to determine

their population structure, movement patterns and residency.

2.4.5 Conclusions

Study findings have demonstrated how a hierarchy of environmental filters, from broad-

scale oceanographic patterns to local habitat features, can shape the species pool of an

estuary. The fish fauna of the Walpole-Nornalup was less speciose than those of

comparable permanently-open systems on the west coast of WA, but places it among the

most diverse estuaries in the south coast bioregion. Its permanently-open nature allows

constant ichthyofaunal exchange with the ocean, and results in a highly marine-influenced

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and relatively stable environment, which evidently provides a key nursery area for

numerous marine-spawning teleost and elasmobranch species. Within the estuary, finer-

scale habitat features (e.g. sediment type, physical structure and water quality variables)

vary markedly from the lower to upper reaches, influencing resource availability to

various species, and in turn, further shaping local fish communities. Moreover, the fish

faunal composition of this permanently open system changes significantly between

seasons and years, which reflects the influences of forcing climatic variables on the

physico-chemical environment of the system, and recruitment success among marine

migrants and short-lived estuarine species (e.g. atherinids and gobiids).

Given the prevalence of marine species in the Walpole-Nornalup compared to other

estuaries along the south coast of WA, and that the exposed coastal waters of the region

are typically unfavourable for juvenile fishes, this system is likely to be of considerable

importance for sustaining fish populations outside of the estuary. As climate change

throughout SWA is occurring at an unprecedented rate, winter flows are declining and

‘dry’ years (such as 2015–16 in the present study) are forecast to become more common.

In the face of these changes, many estuaries along the south coast are likely to close for

extended periods, becoming less accessible and hospitable for marine species. Under such

scenarios the Walpole-Nornalup, a system predisposed to remain open given its unique

geomorphology, may become of increased importance as a nursery.

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Chapter 3: Diel shifts in the structure and function of nearshore fish communities

This Chapter appears largely unmodified from its published version:

Yeoh, D. E., Valesini, F. J., Hallett, C. S., Abdo, D. A. & Williams, J. (2017). Diel shifts in the

structure and function of nearshore estuarine fish communities. Journal of Fish Biology 90, 1214-

1243.

3.1 INTRODUCTION

The highly productive and typically sheltered waters of estuaries provide an abundance

of potential food sources and habitats (Costanza et al., 1997; Beck et al., 2001; McLusky

& Elliott, 2004), making them of great importance to fish populations globally,

particularly as nursery and development areas (Blaber & Blaber, 1980; Rakocinski et al.,

1996; Able, 2005). Knowledge of the spatial and temporal variability of these fish faunas

is crucial for understanding and thus managing the ecological structure and function of

these important ecosystems. Spatial variability in estuarine fish assemblages has typically

has been studied in great detail worldwide and at multiple scales, including

intercontinentally (Potter et al., 1990; Barletta & Blaber, 2007; Tweedley et al., 2016b),

regionally (Elliott & Dewailly, 1995; Whitfield, 1999; Selleslagh et al., 2009), locally

between systems (Bennett, 1989; Strydom et al., 2003; Hoeksema et al., 2009) and locally

within systems (Loneragan et al., 1986; Akin et al., 2005; Barletta et al., 2005). The

majority of the above studies, and many more (e.g. Claridge et al., 1986; Marshall &

Elliott, 1998; Potter et al., 2001), have similarly documented the temporal variability of

estuarine fish communities over seasonal to inter-decadal timescales.

Comparatively, finer-scale temporal variability, and specifically diel changes, are less

understood, with much of the above knowledge based on sampling during either the day

or night. Environmental conditions within estuaries can fluctuate dramatically between

these diel periods (Tyler et al., 2009; Morse et al., 2014), which in turn influences the

behaviour and distribution of fishes (Neilson & Perry, 1990; Reebs, 2002; Henderson &

Fabrizio, 2014). Understanding this variability can reveal important ecological

interactions between species and/or guilds of species (Ley & Halliday, 2007), in turn

facilitating more comprehensive and effective ecosystem management. This knowledge

also highlights potential biases associated with sampling a single diel period and provides

a rationale for the design of future research studies.

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To provide a sound basis for understanding overarching trends and potential drivers in

the diel variation of estuarine fish fauna, a subset of relevant studies were reviewed from

a range of estuaries worldwide, throughout temperate to tropical and micro- to macro-

tidal regions, and encompassing a variety of sampling methods including observation-

based techniques and both passive and active netting (Table 3.1). Generally, day-night

shifts in fish assemblage characteristics were observed across all of these environments,

albeit to varying degrees. A higher total abundance and species richness of fish was

typically observed at night, particularly in shallow nearshore waters. In several studies,

the magnitude of day-night change was strongly influenced by habitat (e.g. Young et al.,

1997; Gray et al., 1998; Castellanos-Galindo & Krumme, 2013; 2015) and/or lunar, tidal

or seasonal conditions (e.g. Stoner, 1991; Griffiths, 2001; Hagan & Able, 2008).

While the above studies have well documented diel changes in (i) total fish abundance,

species richness and/or diversity (e.g. Stoner, 1991; Gray et al., 1998; Bailey & James,

2013), (ii) community composition (e.g. Young et al., 1997; Methven et al., 2001;

Hoeksema & Potter, 2006) and/or (iii) size structure (e.g. Becker et al., 2011; Becker &

Suthers, 2014), very few have examined day-night shifts in the functional composition of

estuarine fish communities. Functional approaches, which group fish into guilds based on

how they utilise estuaries (Elliott et al., 2007; Potter et al., 2015a), their affinity for

particular habitats, or their reproductive strategy or feeding mode (Franco et al., 2008;

Nicolas et al., 2010b; Hallett et al., 2012a), explicitly link community structure to

ecosystem functioning and can help elucidate ecological drivers of community change

(Mouillot et al., 2006; Villéger et al., 2010). Furthermore, no studies to our knowledge

have utilised all four of the above approaches to provide a more comprehensive and

holistic assessment of diel variations in nearshore estuarine fish ecology.

Given the above, the primary aims of this study are as follows.

1. Quantify the nature and extent of any day vs night shifts in the structural

(abundance, species richness, taxonomic diversity, species composition and size

composition) and functional (feeding and habitat guild composition) attributes of

the nearshore fish fauna in a temperate microtidal estuary.

2. Ascertain whether the magnitude of any such diel variation differs

between the main regions of the estuary and among seasons.

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Table 3.1 Summary of selected previous studies investigating diel variation of estuarine fish faunas. The diel period in which the number of fish

species/diversity and abundance/biomass was highest is provided for each study, as are the key families and/or size classes (total length, TL) that were

considerably more abundant in each diel period. Secondary meta-analysis of published literature was used to determine the most abundant families/size

classes in cases where they were not explicitly given. Significant diel differences detected only during a certain season, month or tide are indicated by

(*), while those detected only in certain habitats are indicated by (^).

Study Sampling area (Region) Description

Habitat sampled Method (frequency)

No. species/ diversity

Abundance/ biomass

Abundant during day

Abundant during night

MICROTIDAL Griffiths (2001)

Lake Illawarra (south-eastern Australia) Intermittently open, large basin (c. 3627 ha).

Nearshore waters, seagrass beds adjacent to deep channels.

Seine net (bi-monthly for five months).

Night Night* Gerreidae Girellidae

Gobiidae Teprapontidae Muglidae

Werri Lagoon (south-eastern Australia) Intermittently open, small basin (c. 14 ha).

Nearshore waters, seagrass meadows adjacent to shallow sand flats.

Seine net (bi-monthly for five months).

Night* Night* Gobiidae Atherinidae Eleotridae

Shellharbour Lagoon (south-eastern Australia) Intermittently open, small basin (<2 ha).

Nearshore waters, seagrass meadows, adjacent to shallow sand flats.

Seine net (bi-monthly for five months).

Night* No sig. var. Pseudomugilidae Gobiidae Ambassidae

Gray et al. (1998)

Richmond River Estuary (south-eastern Australia) Permanently open, riverine estuary (c. 1907 ha).

Nearshore waters (<1.2 m deep), bare sand and seagrass.

Seine net (one season). Night^

Night^ Sillaginidae^ Mugilidae^

Clupeidae^ Ambassidae^

Wooli Wooli River Estuary (south-eastern Australia) Permanently open, barrier lagoon estuary (c. 190 ha).

Nearshore waters (<1.2 m deep), bare sand and seagrass.

Seine net (one season). Night^ Night^ Sillaginidae^ Mugilidae^

Clupeidae^ Ambassidae^

Smith & Hindell (2005)

Barwon River Estuary (south-eastern Australia) Permanently open, drowned river valley system (c. 19 km in length).

Offshore waters in lower estuary, mangrove vegetated and unvegetated habitats.

Fyke and gill nets (one season).

Night

Night Gobiidae Tetraodontidae

Anguillidae Arripidae^ Sparidae Mugilidae

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Study Sampling area (Region) Description

Habitat sampled Method (frequency)

No. species/ diversity

Abundance/ biomass

Abundant during day

Abundant during night

Becker & Suthers (2014)

Smiths Lake (south-eastern Australia) Intermittently open estuary (c. 937 ha).

Nearshore (<1 m deep) and offshore (3–4 m deep) waters. Bare sand habitat.

DIDSON (one season, two years).

No species data collected

Day Baitfish (<100 mm TL)

301–500 and >500 mm TL in nearshore waters

Guest et al. (2003)

Gold Coast Broadwater (eastern Australia) Permanently open, shallow, sub-tropical barrier lagoon estuary (>1000 ha).

Shallow (<1 m) seagrass habitat in lower estuary.

Seine net and beam trawl (one season).

Night Night Ambassidae Terapontidae Gobiidae

Hoeksema & Potter (2006)

Swan River Estuary (south-western Australia) Permanently open, drowned river valley system (c. 60 km in length).

Nearshore waters (<1.5 m deep) in upper estuary. Sand/mud flats adjacent to snags and deep channels.

Seine net (monthly for one year).

Night Night Gobiidae Sparidae Atherinidae Poeciliidae

Young et al. (1997)

Moore River Estuary (south-western Australia) Seasonally open, shallow riverine system (c. 10 km in length).

Nearshore waters (<1 m deep), sand flats near snags.

Seine net (monthly for one year).

Night Night^ Gobiidae Atherinidae Muglidae Sparidae

Bailey & James (2013)

Kariega Estuary (South Africa) Permanently open, narrow riverine system (c. 18 km in length).

Offshore waters (<5 m deep). Low turbidity (<10 NTU) with little stratification.

Otter trawl (one season).

Night Night Sparidae Gobiidae Soleidae

Becker et al. (2011)

East Kleinemonde Estuary (South Africa) Intermittently open, shallow riverine system (12–36 ha).

Nearshore waters (<0.7 m deep) in the littoral zone.

DIDSON (one season). No species data collected

Not tested Baitfish (<100 mm TL)

101–300 and 301–500 mm TL

Stoner (1991)

Laguna Joyuda (Puerto Rico) Permanently-open, shallow lagoon (c. 121 ha).

Mangrove fringed basin, <1.6 m deep, highly turbid (~15 cm visibility), shelly/mud sediment with high organic content.

Otter trawl (one wet and dry season).

No sig. var.

Night Gerreidae Engraulidae

Methven et al. (2001)

Bellevue, Trinity Bay (Newfoundland) Permanently open estuarine embayment (<1000 ha).

Nearshore waters (<2 m deep), gravel/ small rock substrate.

Seine net and diver observations (monthly, two 16 month periods six years apart).

Night Night Pleuronectidae Osmeridae Gadidae

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Study Sampling area (Region) Description

Habitat sampled Method (frequency)

No. species/ diversity

Abundance/ biomass

Abundant during day

Abundant during night

MACROTIDAL Ley & Halliday (2007)

Cairns/Townsville region, north-eastern Australia Six large estuaries (>400 ha). Two wave and four tidal dominated. Semi-diurnal tides, >4 m on spring.

Offshore waters fringed by dense mangroves. Upstream and downstream regions.

Gill nets (bi-monthly for two years).

Night Night Mugilidae Engraulidae Clupeidae Latidae Polynemidae

Castellanos-Galindo & Krumme (2013)

Bahía Málaga (Tropical Eastern Pacific – South America) Large estuarine embayment (c. 13,000 ha), tidal range of >4.5 m.

Intertidal mangrove creeks.

Block nets (monthly for one year).

No sig. var.

Day^ Carangidae Atherinopsidae Tetraodontidae

Gobiidae Lutjanidae Centropomidae Arridae

Castellanos-Galindo & Krumme (2015)

Caeté Estuary (Western Atlantic —South America) Lower reaches of c. 100 km long riverine system. Humid tropical region, semi-diurnal (4–5 m tidal range).

Intertidal mangrove creeks.

Block nets (monthly for one year).

Not given Not given Tetraodontidae Gerreidae

Arridae Sciaenidae

Krumme et al. (2004)

Caeté Estuary (Western Atlantic — South America) Lower reaches of c. 100 km long riverine system. Humid tropical region, semi-diurnal (4–5 m tidal range).

Intertidal mangrove creeks and nearshore subtidal areas in adjacent channels.

Block and seine nets (wet season, spring and neap tides).

Night (block net). No sig. var. (seine net)

No sig. var. Tetraodontidae Engraulidae

Auchenipteridae Sciaenidae

Krumme et al. (2015)

Sikao Creek (south-west Thailand) Mangrove estuary with complex dendritic creek networks (<1000 ha total area). Semi-diurnal tides, 0.5–2 m neap, 2–3 m spring. 0.04 ha (neap) to 1.9 ha (spring).

Intertidal mangrove creeks and nearshore subtidal areas in adjacent channels.

Block and seine nets (three consecutive lunar cycles, spring and neap tides).

Day^ (intertidal). Night (subtidal)

Night Phallostethidae Adrianichthyidae

Ambassidae

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3.2 METHODS

3.2.1 Study area

The Walpole-Nornalup Estuary (otherwise known as Walpole and Nornalup Inlets

Marine Park) on the south coast of Western Australia (35.005°S, 116.725°E) has a

temperate climate, is microtidal (<0.9 m tidal range) and receives approximately 1,300

mm of rainfall per year (Hodgkin & Hesp, 1998; Semeniuk et al., 2011; BoM, 2016). The

estuary is permanently open to the sea via a narrow entrance channel, has two basins and

three main tributaries (Fig. 3.1). The larger of the two basins, Nornalup Inlet, has a surface

area of approximately 1260 ha, ranges 3–6 m deep through its centre, is fringed by

extensive shallow sand flats <1.5 m in depth and is fed by the Frankland and Deep rivers.

The smaller Walpole Inlet basin has a surface area of approximately 130 ha, is <2 m deep

and is fed by the Walpole River. The benthic habitat throughout much of the estuary is

sand and mud, with only small areas of seagrass, vegetative cover or rock in the basins

and small areas of submerged fallen trees in the rivers (Brearley, 2005; Huisman et al.,

2011; Semeniuk et al., 2011).

Figure 3.1 Location of the four study regions in the Walpole-Nornalup Estuary. ,

sampling sites.

3.2.2 Field sampling

Fish communities in the shallow nearshore waters (≤1.5 m deep) were sampled during

both the day and night at 19 sites across four regions of the estuary (Lower Nornalup, LN;

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Upper Nornalup, UN; Walpole Inlet, WI; Frankland River, FR; Fig. 3.1) in each season

between November 2014 (austral spring) and July 2015 (austral winter). Daytime

sampling was undertaken no earlier than one hour after sunrise and no later than one hour

before sunset, while night sampling occurred between one hour after sunset and one hour

before sunrise. Fish were collected using a 21.5 m long seine net with a vertical drop of

1.5 m, two 10 m long wings (outer 6 m comprising 9 mm mesh and inner 4 m comprising

3 mm mesh), a 1.5 m long bunt (3 mm mesh) and swept an area of approximately 116 m2.

This net is consistent with numerous previous studies of estuarine fish assemblages in

south-western Australia (e.g. Young et al., 1997; Hoeksema & Potter, 2006; Hoeksema

et al., 2009) and has several advantages over other assessment techniques including its

low species and size selectivity, rapid and simple deployment, efficacy over a wide range

of habitats, and the relatively lower fish mortality associated with its use (Pierce et al.,

1990; Hallett & Hall, 2012). The net was deployed parallel to the bank and then hauled

ashore or onto a vessel if no beach was nearby. Salinity, water temperature (°C) and

dissolved oxygen (DO) concentration (mg L−1) were measured in the middle of the water

column at each site on each sampling occasion using a multiparameter water quality meter

(HydroLab Quanta or Yellow Springs International 556).

All fish in each sample were identified to species, counted and measured to the nearest 1

mm (total length, TL), except where large numbers of a particular species were caught, in

which case a random subsample of 50 individuals was measured. Wherever possible, fish

were processed in the field and released, although in cases where identification and

measurement required greater time, fish were immediately euthanised in an ice slurry

before being transported to the laboratory for processing. Each species was allocated to

functional habitat guilds (small pelagic, SP; small benthic, SB; pelagic, P; demersal, D;

bentho-pelagic, BP) and feeding mode guilds (zooplanktivore, ZP; zoobenthivore, ZB;

detritivore, DV; omnivore, OV; opportunist, PV; piscivore, PV) based on published

literature (e.g. Potter & Hyndes, 1999; Elliott et al., 2007; Hallett et al., 2012a) and

information from FishBase (Froese & Pauly, 2016).

3.2.3 Data analyses

The following statistical analyses were performed using the software packages PRIMER

v7 (Clarke & Gorley, 2015) with the PERMANOVA+ add-on module (Anderson et al.,

2008) and R (R Development Core Team, 2014; www.r-project.org).

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Diel changes in fish abundance, species richness and taxonomic distinctness

The total number of species and individuals in each sample were initially transformed

(square-root and ln[x+1], respectively) to approximate homogenous dispersions among a

priori groups (Anderson, 2001), with the most appropriate transformations identified

using the methodology of Clarke et al. (2014a). These data were used to create separate

Euclidean distance matrices for each variable, which were then each subjected to a three-

way crossed (diel × region × season) Permutational Analysis of Variance test

(PERMANOVA; Anderson, 2001). Emphasis was placed only on interpreting any

significant (P < 0.05) day vs night differences, with the remaining factors included to

account for any confounding influences. In these and all subsequent PERMANOVA tests,

all factors were considered fixed and the components of variation (COV) values were

used to ascertain the relative importance of each significant term. Significant diel

differences were explored using plots of the mean values (± standard error) during both

the day and night, within each region and/or season as appropriate.

Quantitative average taxonomic distinctness (∆*) was used to provide a robust measure

of species diversity (Warwick & Clarke, 1995). Prior to calculating this index, the

numbers of each species in each sample were dispersion weighted (Clarke et al., 2006)

then square-root transformed (Clarke et al., 2014b). ∆* was then calculated for each

sample using the DIVERSE routine, and the resultant data used to construct a Euclidean

distance matrix, which was then subjected to the same PERMANOVA test described

above.

Diel changes in species and functional guild composition

The pre-treated species abundance data (above) was used to construct a Bray-Curtis

similarity matrix to provide the basis for testing for any diel variation in species

composition. These data were then averaged separately for both habitat and feeding mode

guilds, and similarly used to calculate Bray-Curtis resemblance matrices. Each of these

matrices was then subjected to PERMANOVA (see earlier) to ascertain any day vs night

differences. To illustrate any significant diel trends, distances among centroids of groups

of replicate samples were calculated for both the day and night (within each region and/or

season as appropriate), and the resultant distance matrix subjected to non-metric

multidimensional scaling ordination (nMDS).

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A shade plot (Clarke et al., 2014b) constructed from the pre-treated species abundance

data, averaged appropriately, was then used to determine the species most responsible for

driving any diel differences in species composition. Only those species comprising >5%

of the total abundance in at least one averaged sample were included. Species (displayed

on the y-axis) were ordered according to a group-average hierarchical agglomerative

cluster analysis of a resemblance matrix defined between species as Whittaker’s index of

association (Legendre & Legendre, 1998). A Similarity Profiles test (SIMPROF Type 3;

Somerfield & Clarke, 2013) was also applied to identify those points in the clustering

procedure at which no significant structure (difference in species abundance patterns)

could be detected. Samples, displayed on the x-axis, were ordered for diel period within

each level of any other influential factor(s).

Any significant diel variation in functional guild composition was explored by calculating

the proportion of each guild in both the day and night, within each region and/or season

as appropriate.

Diel changes in size composition

Fish were grouped into three classes based on their total length (TL), i.e. <100, 100–199

and ≥200 mm. When very large numbers of a species were caught in a sample, and thus

only a sub-sample of fish was measured, un-measured individuals were designated to a

size class based on the proportions in the measured component. The proportions of each

size class in both the day and night in each season were then calculated. Any significant

diel differences in TL for each of the 10 most abundant species were tested using t-tests,

with resultant P-values adjusted using a Bonferroni correction and compared to α = 0.05.

Diel changes in water quality parameters

Salinity, water temperature and DO data recorded at each site on each sampling occasion,

which did not require any prior transformation to approximate homogenous dispersions

among a priori groups (Anderson, 2001; Clarke et al., 2014a), were each subjected to the

same suite of analyses described above for fish species richness/abundance to explore any

significant diel differences.

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3.3 RESULTS

3.3.1 Diel changes in water quality parameters

Salinity, water temperature and DO concentration each varied significantly between day

and night, with the three-way interaction and/or the season × diel interaction also being

significant for the latter two variables (Appendix 3.1). However, the components of

variation values showed that, in each of these cases, the influence of the season main

effect was far greater than that of any significant term involving diel period. The relatively

small day vs night differences are further exemplified by the plots of the means for each

of these water quality parameters in each diel period, season and region (Appendix 3.2).

3.3.2 Diel changes in total species abundances

A total of 100,869 fish from 36 species and 21 families were recorded during this study

(Table 3.2). A far higher number of individuals was recorded during the day than at night,

i.e. 86,892 and 13,977 fish respectively.

During the day, the five most abundant species were the silver fish Leptatherina

presbyteroides (Richardson 1843), the western hardyhead Leptatherina wallacei (Prince,

Ivantsoff & Potter 1982), the southern longfin goby Favonigobius lateralis (Macleay

1881), the King George whiting Sillaginodes punctatus (Cuvier 1829) and the Australian

anchovy Engraulis australis (White 1790), while at night, L. presbyteroides, F. lateralis,

L. wallacei, the southwestern goby Afurcagobius suppositus (Sauvage 1880) and the

bluespot goby Pseudogobius olorum (Sauvage 1880) were most abundant (Table 3.2).

Although the atherinids L. presbyteroides and L. wallacei were prevalent during both diel

periods based on total abundances, they were proportionately far more abundant during

the day, when 74–90% of these individuals were caught (Fig. 3.2). In contrast, F. lateralis

was proportionately far more abundant at night, a trend that was similarly displayed by

the three other gobiid species recorded, i.e. A. suppositus, P. olorum and the bridled goby

Arenigobius bifrenatus (Kner 1865) (Fig. 3.2). Other species that were proportionately

far more abundant during the day than night included sea mullet Mugil cephalus (L.

1758), Western Australian salmon Arripis truttaceus (Cuvier 1829), S. punctatus, blue

sprat Spratelloides robustus (Ogilby 1897) and yellowfin whiting Sillago schomburgkii

(Peters 1864), while the opposite was true for Australian herring Arripis georgianus

(Valenciennes 1831), southern bluespotted flathead Platycephalus speculator

(Klunzinger 1872) and western striped grunter Pelates octolineatus (Jenyns 1840) (Fig.

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3.2). It is also interesting to note that, while the proportions of the catch recorded during

each diel period were similar for species within any one family, the two Arripidae species

had almost opposing contributions (Fig. 3.2).

Table 3.2 Total number of individuals (n) and percentage contribution (%) of each fish

species caught during the day and night in the Walpole-Nornalup Estuary. Habitat guilds

H, i.e. small pelagic (SP), small benthic (SB), pelagic (P), demersal (D), bentho-pelagic

(BP), and feeding guilds F, i.e. zooplanktivore (ZP), zoobenthivore (ZB), piscivore (PV),

omnivore (OV), opportunist (OP), detritivore (DV), are given for each species.

Family Species H, F Day Night Total

n % n %

ATHERINIDAE Leptatherina presbyteroides SP, ZP 79,254 91.21 8,317 59.50 87,571 ATHERINIDAE Leptatherina wallacei SP, ZB 4,064 4.68 1,443 10.32 5,507 GOBIIDAE Favonigobius lateralis SB, ZB 1,089 1.25 1,925 13.77 3,014 SILLAGINIDAE Sillaginodes punctatus D, ZB 437 0.50 84 0.60 521 ENGRAULIDAE Engraulis australis SP, ZP 338 0.39 310 2.22 648 MUGILIDAE Aldrichetta forsteri P, OV 314 0.36 157 1.12 471 ATHERINIDAE Atherinosoma elongata SP, ZB 299 0.34 143 1.02 442 GOBIIDAE Afurcagobius suppositus SB, ZB 283 0.33 706 5.05 989 MUGILIDAE Mugil cephalus P, DV 282 0.32 30 0.21 312 GOBIIDAE Pseudogobius olorum SB, OV 179 0.21 452 3.23 631 SPARIDAE Acanthopagrus butcheri BP, OP 166 0.19 96 0.69 262 SPARIDAE Rhabdosargus sarba BP, ZB 54 0.06 35 0.25 89 GOBIIDAE Arenigobius bifrenatus SB, ZB 33 0.04 161 1.15 194 SILLAGINIDAE Sillago schomburgkii D, ZB 18 0.02 5 0.04 23 ARRIPIDAE Arripis truttaceus P, PV 15 0.02 2 0.01 17 HEMIRAMPHIDAE Hyporhamphus melanochir SP, ZB 14 0.02 5 0.04 19 TERAPONTIDAE Pelates octolineatus BP, OV 10 0.01 34 0.24 44 CLUPEIDAE Spratelloides robustus SP, ZP 8 0.01 2 0.01 10 CARANGIDAE Pseudocaranx georgianus BP, ZB 7 0.01 0 - 7 CLUPEIDAE Hyperlophus vittatus SP, ZP 6 0.01 2 0.01 8 PLEURONECTIDAE Ammotretis elongatus D, ZB 3 <0.01 0 - 3 PLEURONECTIDAE Ammotretis rostratus D, ZB 2 <0.01 7 0.05 9 ARRIPIDAE Arripis georgianus P, PV 2 <0.01 32 0.23 34 PLOTOSIDAE Cnidoglanis macrocephalus D, ZB 2 <0.01 7 0.05 9 ENOPLOSIDAE Enoplosus armatus D, ZB 2 <0.01 0 - 2 LABRIDAE Notolabrus parilus D, ZB 2 <0.01 1 0.01 3 PLATYCEPHALIDAE Platycephalus speculator D, PV 2 <0.01 10 0.07 12 SILLAGINIDAE Sillago bassensis D, ZB 2 <0.01 2 0.01 4 CLINIDAE Cristiceps australis D, ZB 1 <0.01 1 0.01 2 CLINIDAE Heteroclinus heptaeolus D, ZB 1 <0.01 0 - 1 MYLIOBATIDAE Myliobatis tenuicaudatus D, ZB 1 <0.01 1 0.01 2 CYNOGLOSSIDAE Paraplagusia bilineata D, ZB 1 <0.01 2 0.01 3 SILLAGINIDAE Sillago burrus D, ZB 1 <0.01 2 0.01 3 RHINOBATIDAE Aptychotrema vincentiana D, ZB 0 - 1 0.01 1 PARALICHTHYIDAE Pseudorhombus jenynsii D, ZP 0 - 1 0.01 1 SYNGNATHIDAE Pugnaso curtirostris D, ZB 0 - 1 0.01 1 Total no. individuals 86,892 13,977 100,869 Total no. species 33 32 36

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Figure 3.2 Relative proportions of each species recorded during the day (light grey) and

night (dark grey) and the total number of individuals caught. Only species where ≥10

individuals were recorded are shown.

3.3.3 Diel changes in fish abundance, species richness and taxonomic distinctness

The mean abundance of individuals did not differ significantly between day and night

overall (P = 0.268; Appendix 3.3), but there was a significant (P < 0.001) season × diel

interaction that was far more influential than the other two significant terms, namely the

region and season main effects. Examination of the mean density of fish in each diel

period and season showed that values were highest at night during spring and summer,

while far more individuals were caught during the day in autumn and winter (Fig. 3.3a).

PERMANOVA detected significant (P < 0.001) diel differences overall for species

richness, and while regional and seasonal differences were also significant (P ≤ 0.002),

the first of these main effects was the most influential (Appendix 3.3). Taxonomic

distinctness (∆*) also varied significantly between day and night (P = 0.012), which was

the only significant term for this variable (Appendix 3.3). Both mean species richness and

∆* were significantly higher at night (Fig. 3.3b, c).

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Figure 3.3 (a) Mean number of individuals recorded during the day and night in each

season, and (b) mean number of species and (c) mean taxonomic distinctness recorded

during the day and night. Standard errors bars are provided for all means.

3.3.4 Diel changes in species, guild and size composition

Species composition

Three-way PERMANOVA demonstrated that species composition was significantly

influenced by diel period, region and season, and that the season × diel interaction was

also significant (Appendix 3.4). Unlike the situation for mean abundance, species richness

and ∆*, however, the influence of region was far greater than that of any significant diel

term (Appendix 3.4). The nMDS ordination plot of the centroids in each diel period and

season showed clear day vs night differences in species composition, with night-time

samples lying to the left of the corresponding daytime samples in each season (Fig. 3.4a).

Species composition in both diel periods followed a somewhat cyclic seasonal pattern,

although this was more evident at night (Fig. 3.4a).

The shade plot shown in Fig. 3.5 demonstrated that the fish species mainly responsible

for the above diel differences included the atherinids L. presbyteroides and L. wallacei,

which were most abundant during the day (and especially in autumn and winter for the

first of these species), and the Gobiids F. lateralis, A. suppositus and P. olorum, which

were generally more abundant at night (and especially in summer for the latter two

species). Several other species including A. georgianus, P. octolineatus, tarwhine

Rhabdosargus sarba (Forsskål 1775) and longsnout flounder Ammotretis rostratus

(Günther 1862) were also more abundant at night throughout most seasons (Fig. 3.5).

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Figure 3.4 Centroid nMDS ordination plots constructed from Bray-Curtis similarity

matrices of pre-treated mean (a) species abundances and (b) feeding mode guilds during

the day () and night () in each season.

Figure 3.5 Shade plot illustrating the pre-treated abundances of the most prevalent fish

species during the day and night in each season, with shading intensity being proportional

to abundance. Species are ordered by a hierarchical cluster analysis of their mutual

associations across dielseason groups. Dashed lines in the dendrogram indicate species

with significantly similar patterns of abundance, as detected by SIMPROF. Habitat guilds

H, i.e. small pelagic (SP), small benthic (SB), pelagic (P), demersal (D), bentho-pelagic

(BP) and feeding guilds F, i.e. zooplanktivore (ZP), zoobenthivore (ZB), piscivore (PV),

omnivore (OV), opportunist (OP), detritivore (DV), are given for each species.

Feeding guilds

Feeding guild composition, like species composition, also differed significantly among

diel periods, regions and seasons and had a significant season × diel interaction, with the

regional main effect being the most important (Appendix 3.4). Particularly clear day vs

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night differences were evident across all seasons on the nMDS ordination plot constructed

from group centroids, with no overlap at all between diel periods (Fig. 3.4b).

The proportions of each feeding guild recorded during the day and night varied

substantially between seasons. Notably, zooplanktivores (ZP) were far more prevalent

during the day than at night in autumn and winter, but the reverse was true in spring and

summer (Fig. 3.6). The proportion of piscivores (PV), however, was notably higher at

night during both summer and winter, but they were almost evenly spread throughout

both diel periods in spring and autumn. The proportions of omnivores (OV) and

opportunists (OP) were considerably higher at night in spring, summer and autumn, but

higher during the day in winter (Fig. 3.6). Zoobenthivores (ZB) were relatively evenly

distributed between both diel periods in all seasons, while the diel proportions of the

detritivorous guild (DV), which comprised only one species (M. cephalus), fluctuated

substantially between seasons (Fig. 3.6).

Figure 3.6 Proportions of each feeding guild during the day (light grey) and night (dark

grey) in (a) spring, (b) summer, (c) autumn and (d) winter. Zooplanktivore (ZP),

zoobenthivore (ZB), piscivore (PV), omnivore (OV), opportunist (OP), detritivore (DV).

Proportions are based on pre-treated data, and the total number of individuals in each

guild and season is also provided.

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Habitat guilds

Three-way PERMANOVA showed that habitat guild composition differed significantly

between day and night (P < 0.001; Appendix 3.4), with no significant interactions

involving diel period. The proportion of small pelagic (SP) fishes was highest during the

day, while fishes in all other habitat guilds were more abundant at night (Fig. 3.7).

Figure 3.7 Proportions of each habitat guild during the day (light grey) and night (dark

grey) based on pre-treated data. Small pelagic (SP), small benthic (SB), pelagic (P),

demersal (D), bentho-pelagic (BP). The total number of individuals in each guild is also

provided.

Size composition

The vast majority of fish caught were <100 mm in length, with those ≥100 mm

contributing <2% of the total catch by numbers of individuals (Fig. 3.8a). Notably larger

proportions of fish in the smallest and medium size classes were caught during the day,

while almost equal proportions of fish in the largest size class were recorded across both

diel periods (Fig. 3.8a). When fish size compositions were examined in each season (Fig.

3.8b–e), larger fish (≥200 mm) were proportionately more abundant at night than

medium-sized (100–199 mm) and small (<100 mm) fish in all cases except spring, when

small fish were most abundant at night (Fig. 3.8b). Additionally, far greater proportions

of fish in all size classes were caught during the day in winter (Fig. 3.8e), while the

opposite was true in summer (Fig. 3.8c).

The mean lengths of five of the ten most abundant species also varied significantly

between day and night. Larger individuals of three of these species, i.e. L. presbyteroides

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(T3664 = −4.50; P < 0.001), E. australis (T244 = −4.49; P < 0.001) and M. cephalus (T88 =

−5.90; P < 0.001), were caught at night, whilst the reverse was true for S. punctatus (T253

= 4.03; P < 0.001) and L. wallacei (T1639 = 12.44; P < 0.001). The length distribution of

M. cephalus, in particular, was far wider at night than during the day, i.e. 22–358 and 25–

82 mm, respectively.

Figure 3.8 Proportions of each size class recorded during the day (light grey) and night

(dark grey), (a) across all seasons and regions, and in (b) spring, (c) summer, (d) autumn

and (e) winter. The total number of individuals in each size class is also provided.

3.4 DISCUSSION

This study has assessed diel variability in a holistic suite of structural and functional

attributes of the nearshore fish fauna in a temperate microtidal estuary, at a breadth that

very few studies have investigated previously. As discussed below, examining these

attributes in combination provides greater insight into diel responses across the fish

community, and the likely consequences for broader ecosystem function.

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All measured attributes of the nearshore fish fauna throughout the Walpole-Nornalup

Estuary exhibited significant diel variation (Fig. 3.9). From a structural perspective, mean

species richness and diversity (taxonomic distinctness) were higher at night across all

regions and seasons, while the diel period in which mean abundance was higher varied

seasonally. Notably, the influence of diel period was greater than that of region or season

for each of these attributes. The extent and pattern of day vs night differences in species

composition also varied seasonally, but these differences were less important than those

among estuarine regions. Similarly, from a functional point of view, the significant diel

differences in habitat and feeding guild composition were not as influential as regional

and/or seasonal differences. Overall, smaller fish were more abundant during the day

while larger fish were more abundant at night, and the mean lengths of five of the ten

most abundant species differed significantly between diel periods.

Figure 3.9 Conceptual diagram of major day-night shifts in the fish, benthic invertebrate

and bird faunas of the Walpole-Nornalup Estuary. White text indicates attributes of the

fish assemblages that typically increased in the nearshore waters in each diel period

(Images courtesy of the Integration and Application Network, University of Maryland

Center for Environmental Science [ian.umces.edu/symbols/]).

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3.4.1 Diel changes in fish abundance, species richness and taxonomic distinctness

Previous studies of diel shifts in estuarine fish faunas have typically reported higher

abundance, species richness and diversity at night than during the day in the shallows

(Table 3.1). The findings in this study largely concurred with these global trends, with

the exception of mean abundance, which was only notably higher at night during summer.

Moreover, the total number of fish caught was far higher during the day, contrasting with

the findings of many previous studies (e.g. Guest et al., 2003; Hoeksema & Potter, 2006;

Miller & Skilleter, 2006). This was largely attributable to very high catches of two

atherinids (L. presbyteroides and L. wallacei) which form large, tight schools during the

day and were highly abundant in autumn and winter, reflecting their seasonal recruitment

(Prince & Potter, 1983; Hoeksema & Potter, 2006). In spring and summer, however, when

these species were less prevalent, mean abundance of all fish was higher at night. Strong

seasonal × diel interactions in mean fish abundances within estuaries have similarly been

observed by other workers (e.g. Young et al., 1997; Griffiths, 2001; Hagan & Able, 2008),

and the above influence of highly schooling species reaffirms the contention that

abundance measures alone, and particularly total abundance, are often poor indicators of

spatio-temporal changes in fish fauna due to their inherent stochasticity.

Greater mean fish species richness at night in the shallows of estuarine environments has

been attributed by many workers to nocturnal inshore migration (e.g. Methven et al.,

2001; Hoeksema & Potter, 2006; Miller & Skilleter, 2006). However, several studies in

deeper offshore estuarine waters have similarly found higher species richness at night

(Smith & Hindell, 2005; Ley & Halliday, 2007; Bailey & James, 2013), indicating that,

in a more general sense, such findings may simply reflect an increase nocturnally in fish

activity and/or catchability. During the day, many species burrow in sediment or shelter

in physical structure (Gray & Bell, 1986; Bailey & James, 2013), and nets may be more

readily evaded by visual and highly mobile fishes (Stoner, 1991; Gray et al., 1998; Guest

et al., 2003).

The consistently higher average taxonomic distinctness of the fish fauna at night during

this study reflected the greater prevalence of several species from higher taxonomic levels

(order), including A. rostratus (Pleuronectiformes), P. speculator (Scorpaeniformes) and

estuary cobbler Cnidoglanis macrocephalus (Valenciennes 1840; Siluriformes). In

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contrast, daytime samples were more consistently dominated by several highly abundant

species belonging to the same genus or family, e.g. Atherinidae.

3.4.2 Diel shifts in species composition

Diel variation in fish species composition throughout the Walpole-Nornalup Estuary was

largely driven by representatives from the Atherinidae (L. presbyteroides and L. wallacei)

and Gobiidae (F. lateralis, A. suppositus and P. olorum). However, species from these

families consistently exhibited opposing diel patterns, with those from the former being

far more abundant during the day and those from the latter being more abundant at night.

The consistency and strength of this trend throughout the estuary, albeit driven by

different atherinid and gobiid species in different regions, at least partly explained the

lack of any significant diel × region interaction in species composition.

The far higher abundances of gobiids at night in this study are consistent with the findings

of several other studies (e.g. Young et al., 1997; Griffiths, 2001; Hoeksema & Potter,

2006), and have been attributed to the increased nocturnal activity and daytime burrowing

or sheltering of these non-schooling species (Erős et al., 2005; Grabowska & Grabowski,

2005; Gaygusuz et al., 2010), including in deeper waters, to avoid avian predation (Young

et al., 1997; Hoeksema & Potter, 2006). The extremely high daytime abundances of

atherinids (up to 21,576 individuals in a sample vs ≤756 at night) may reflect an

alternative response to perceived danger from predation (Ryer & Olla, 1998), as previous

workers have observed these species forming large, tight schools in nearshore waters

during the day but being more sparsely dispersed at night (Becker et al., 2011; Becker &

Suthers, 2014). However, the roles of predation and other factors in influencing diel

changes in abundance of these small fish species are far from clear. For example, gobiids

have also been shown to be more abundant nocturnally in systems with low avian

presence (Griffiths, 2001) and in deeper waters (Bailey & James, 2013), highlighting

other potential drivers of their low daytime abundances in the shallows. Additionally,

benthic macroinvertebrates, a major prey item for gobiids (Gill & Potter, 1993;

Humphries & Potter, 1993), are often more active at night (Last & Peter, 2004; Forward

et al., 2007), suggesting a potential influence of food availability on the diel movements

of these fish. Furthermore, the diel trends in atherinid abundances in this study contrast

with those in two other studies in south-western Australian estuaries (Young et al., 1997;

Hoeksema & Potter, 2006), which found that species such as L. wallacei were more

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abundant at night in the nearshore waters and attributed this to a decreased threat of

nocturnal predation. However, various workers have shown that piscivorous fishes often

migrate inshore at night in estuaries (e.g. Rountree & Able, 1997; Becker & Suthers,

2014), and indeed, the abundance of medium to large fish, and especially piscivores,

similarly increased at night in the shallows during the present study (see following

subsection), indicating that predation pressure on these small pelagic fishes may not

decrease nocturnally.

In contrast to predation by fish, avian piscivory is largely reliant on sight (Safina &

Burger, 1985; Sheaves, 2001; Tweedley et al., 2016b) and so mostly occurs during the

day (Terörde, 2008). Although avian piscivory is typically low within more turbid

macrotidal estuaries (Baker & Sheaves, 2007; Tweedley et al., 2016b), it may exert

considerable influence, both directly and indirectly, on the structure of shallow water fish

assemblages in clearer microtidal systems (Gawlik, 2002; Steinmetz et al., 2003; Žydelis

& Kontautas, 2008). For example, waders and cormorants are abundant throughout the

Walpole-Nornalup and pose a considerable and direct threat to small benthic fish during

the day in shallow waters (Trayler et al., 1989; Crowder et al., 1997; Gawlik, 2002).

Indeed, gobies are known to constitute a large portion of cormorant diets in south-western

Australian estuaries (Trayler et al., 1989; Humphries et al., 1992). Raptors, which feed

on medium- and larger-bodied fish (Smith, 1985; McLean & Byrd, 1991; Lounsbury-

Billie et al., 2008), are also abundant throughout the system. In the face of such predation

during the day, these fish are more likely to inhabit deeper waters (Crowder et al., 1997),

thereby increasing the tendency for small-bodied, schooling fishes such as atherinids to

occupy the shallows during that diel period. The above highlights the numerous potential

influences on the diel movements of estuarine fish, and thus the difficulty of determining

causality without manipulative experimental approaches to test specifically for drivers of

interest.

3.4.3 Diel shifts in functional guild and size composition

Through grouping together species with similar behavioural traits, feeding modes and/or

habitat requirements, shifts in functional guild composition provide further detail about

biotic trends and support an understanding of ecosystem function rather than simply

structure (e.g. Franco et al., 2008; Villéger et al., 2010). Assessments at the guild level

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also allow for greater global comparability among relevant ecosystems, irrespective of

species type (Elliott et al., 2007; Nicolas et al., 2010a).

Habitat guild composition varied significantly between diel periods, with small pelagic

fishes being more abundant during the day and larger pelagic, small benthic, bentho-

pelagic and demersal fish being more prevalent at night. The higher daytime abundance

of small pelagics predominantly reflects the diel responses of atherinids (see preceding

subsections), as the only other abundant species in this guild (E. australis) showed little

diel variation. Similarly, the only small benthic species recorded were gobiids, and thus

diel shifts in this guild were attributed to the aforementioned feeding and predation

influences on these species.

In comparison, the demersal guild contained 17 species, most of which were recorded in

low numbers, e.g. P. speculator, C. macrocephalus and A. rostratus. The majority of

these fish, and the nocturnally-caught individuals in the bentho-pelagic and pelagic guilds

(e.g. A. georgianus, P. octolineatus, and R. sarba), were >100 mm TL, thereby accounting

for the proportional increase in medium- and larger-bodied fish at night in the size

composition analyses. From a feeding guild perspective, all fish in the above three habitat

guilds were carnivorous to some extent (i.e. piscivores, zoobenthivores or omnivores),

except for M. cephalus, which is a detritivore. Such trends may reflect greater food

availability for these species, given the increased activity of benthic invertebrates (Stoner,

1991; Wassenberg & Hill, 1994; Taylor & Ko, 2011) and certain smaller-bodied teleosts

(e.g. gobiids) at night. As avian predation is also far lower at night, these fish may migrate

from their daytime refuges and/or offshore waters into the more exposed but productive

shallows to feed (Fig. 3.9), as has been indicated in several other studies (e.g. Gray et al.,

1998; Nagelkerken et al., 2000).

3.4.4 Further work and recommendations

The consideration of structural and functional community characteristics within the

present study has provided additional support for discerning potential biotic and/or

environmental influences of the observed diel differences in the ichthyofauna of the

Walpole-Nornalup Estuary. However, it is not possible to clearly identify the dominant

drivers, or fully understand the effects of sampling bias, based solely on fish assemblage

data. Thus, while various reasonable inferences can be made based on available evidence,

ecological and behavioural interactions such as predation and feeding cannot be

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quantified. This limitation is shared by the majority of previous studies that have

examined diel variation in estuarine fish faunas (Reebs, 2002). Experimental approaches,

such as controlled feeding and predation manipulation experiments, are required to more

definitively ascertain the drivers of diel variation in estuarine fish assemblages.

From a fish sampling perspective, seine nets have many merits, such as the ability to

obtain detailed species and size composition data from a highly representative sample of

the fish fauna, including small cryptic species. Indeed, concurrent sampling using a larger

seine net and gill nets resulted in very few additional species being caught. This

information is difficult to obtain accurately using purely observation-based approaches

such as high definition acoustic cameras, e.g. the DIDSON (Becker & Suthers, 2014).

However, seine nets cannot be used to effectively sample deeper waters and thus enable

direct comparisons with shallow environments, as can gear types such as the DIDSON.

Sampling prominent physical structure (e.g. rocks and fallen timber) is also impractical

with seine nets, and thus it is possible that species inhabiting the small areas of structural

habitat in the Walpole-Nornalup (e.g. submerged tree branches) were not captured. Net

avoidance and escape, particularly during the day by visual, larger and faster swimming

fishes, has been recorded by various other workers in estuarine environments (Gray et al.,

1998; Guest et al., 2003; Pessanha et al., 2003), and thus potentially impacted the findings

of the present study. This may partly account for the fact that large M. cephalus were

caught only at night.

For future studies, the current findings indicate that combined day and night sampling is

required to gain the best representation of the fish fauna in an estuarine system.

Depending on project aims and resource availability, however, one diel period may

provide a more suitable selection over the other. For example, night-time sampling is

likely to encompass a greater number and diversity of species, but is frequently associated

with greater operational costs and safety risks. Alternatively, if targeting a specific guild,

species or size class, a single diel period is likely be more appropriate and cost effective.

In summary, the observed diel shifts in the structure of the nearshore fish community in

the Walpole-Nornalup Estuary were in general agreement with many other studies in

nearshore estuarine ecosystems worldwide. Unusually, far greater total abundances were

recorded during the day, attributable to the high daytime catches of two highly abundant

and schooling species, and particularly during autumn/winter. The use of a functional

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guild approach illustrated that benthic fishes were more abundant at night, as were

carnivorous and particularly piscivorous species, suggesting that piscivory on smaller fish

in the shallows at night does not necessarily decrease. There is also reasonable evidence

that in clear, shallow, microtidal systems such as the Walpole-Nornalup, avian piscivory

exerts a considerable influence on the diel patterns of the fish fauna.

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Chapter 4: Interdecadal changes in the fish fauna and ecosystem health of the Walpole-Nornalup Estuary, and

their potential environmental and social drivers

4.1 INTRODUCTION

The impacts of growing human populations on coastal zones worldwide have been

extensively documented, from habitat destruction and pollution to overfishing and the

introduction of alien species (e.g. Jackson et al., 2001; Lotze et al., 2006; Worm et al.,

2006). During recent decades these pressures have been further compounded by marked

changes in regional climates linked to global warming, which is driving rapid broad-scale

biological responses affecting entire ecosystems (Hoegh-Guldberg & Bruno, 2010;

Poloczanska et al., 2016; Hughes et al., 2017). Mean global surface temperatures during

2014–16 were the warmest since instrumental records began in 1880 (NASA/GISS,

2017), yet the extent of observed warming is only a fraction of that projected to occur

during this century. The resulting changes in both mean and extreme climatic conditions

are anticipated to have drastic ecological impacts, ranging from effects on individual

species through to loss of biodiversity, structure and function of ecosystems (Harley et

al., 2006; Halpern et al., 2007; 2008; Arnold et al., 2017).

Estuaries are environments predicted to experience some of the greatest changes, given

their susceptibility to pressures from marine, freshwater and terrestrial sources (Kennish,

2002; Gillanders et al., 2011a; Jennerjahn & Mitchell, 2013). These effects are already

clearly apparent in the temperate Mediterranean regions of Europe, southern Africa and

Australia, where warming and drying of the climate are occurring at unprecedented rates

(González-Ortegón et al., 2015; Potts et al., 2015; Hallett et al., 2018). Freshwater decline

and increased evaporation have led to progressive increases in the salinity of various

estuaries, along with a resultant contraction or upstream shift of freshwater and/or

estuarine biota and greater abundances of marine species (Pasquaud et al., 2012; James

et al., 2013; Marques et al., 2014; Whitfield et al., 2016; Hallett et al., 2018; Valesini et

al., 2017). As waters warm, poleward range expansions of (sub)tropical species and

greater abundances of warm temperate species have also been documented (James et al.,

2008b; Pasquaud et al., 2012; James et al., 2013; Veale et al., 2014; Whitfield et al.,

2016).

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Under dry conditions, estuaries may also become more susceptible to degradation due to

increased stratification and/or reduced flushing of estuarine water into the sea (Attrill &

Power, 2000; Tweedley et al., 2016a). This is particularly so in microtidal regions, where

oceanic water exchange is inherently minimal and often further reduced or inhibited

through sand-bar formation (Tweedley et al., 2016b; Hallett et al., 2018). Coupled with

warm temperatures, these environmental changes can lead to severe hypersalinity,

eutrophication, hypoxia and anoxia (Cyrus et al., 2010; Wetz & Yoskowitz, 2013; Collins

& Melack, 2014; Cloern et al., 2016). Such conditions have been well documented to

cause physiological stress and/or mortality among fishes (e.g. Burkholder et al., 1992;

Whitfield et al., 2006; Small et al., 2014), and prolonged and widespread effects have

been linked with detrimental changes in the abundance, growth and/or population

structure of species within a system (Ferguson et al., 2013; Cottingham et al., 2014;

Valesini et al., 2017). In a broader context, these changes at an individual or species level

may reflect loss of ecological structure and function, and ultimately, a decrease in

ecosystem health (Costanza & Mageau, 1999). Thus, to readily assess, track and report

estuarine degradation, various workers around the world have synthesised the responses

of fish fauna to stress into multimetric indices of ecological integrity (Whitfield & Elliott,

2002; Harrison & Whitfield, 2004; Hallett et al., 2012b; Fonseca et al., 2013).

Climatic changes in south-western Australia (SWA) have accelerated substantially over

the past two to three decades, with clear impacts on estuarine environments and their fish

faunas. Since the mid-1970s, rainfall in the region has declined by 15–20% (Petrone et

al., 2010; Silberstein et al., 2012), with total annual rainfall during 2010 the lowest on

record (Silberstein et al., 2012). In contrast, mean sea and air temperatures have risen by

c. 1 °C during the past century (BoM & CSIRO, 2016), and most rapidly since the mid-

1980s/early-1990s (Pearce & Feng, 2007; Hope et al., 2015). The combination of warmer

temperatures and reduced rainfall, coupled with extensive clearing of native vegetation,

ground water extraction and the damming and diversion of rivers and streams to support

growing human populations and resource demands, has resulted in freshwater flows more

than halving since the 1970s (Petrone et al., 2010; Barron et al., 2012; Silberstein et al.,

2012; Hope et al., 2015; BoM & CSIRO, 2016).

Reduced flushing, in combination with other direct and indirect impacts of agriculture

and development (e.g. increased nutrient inputs), has exacerbated the problems of

eutrophication, sedimentation, algal blooms and hypoxia in several extensively modified

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SWA estuaries during recent decades (Hugues-dit-Ciles et al., 2012; Brearley, 2013;

Elliott et al., 2016; Tweedley et al., 2016a). These environmental stressors have been

linked to both instantaneous effects on fish faunas, e.g. fish kill events (Hallett et al.,

2016c), and longer-term shifts in the biology of individual species (Cottingham et al.,

2014; Cottingham et al., 2016) and/or composition of communities (Veale et al., 2014;

Potter et al., 2016; Valesini et al., 2017). There is also substantial evidence that in several

commercially and recreationally fished systems (e.g. Swan-Canning, Peel-Harvey,

Wilson Inlet), fishing mortality may have caused decreases in the abundance and size of

targeted species (Beckley & Ayvazian, 2007; Chuwen et al., 2011; Valesini et al., 2017).

The focus of this study, the Walpole-Nornalup Estuary, is unique in comparison to most

other estuaries in SWA, in that it is largely unmodified from a pristine state (NLWRA,

2002) and fringed by only a small town of c. 400 residents (ABS, 2016). Given the

generally lower levels of physical degradation, development and pollution affecting the

Walpole-Nornalup compared to other SWA estuaries, any ecological changes that may

have occurred in the system over the past two to three decades, and particularly those

among its fish communities, could be considered to largely reflect the rapidly changing

climate of the region. When compared to recent findings in highly modified SWA

systems, such information could contribute to knowledge of how climate change effects

on estuarine ecosystems compare to localised anthropogenic stressors.

Commercial fishing and the use of nets has also been prohibited in the Walpole-Nornalup

for most of the past century (Christensen, 2009), which is also rare among not only SWA

estuaries, but those globally. Notably, however, recreational fishing effort, which is

mostly attributable to tourists, is the highest of any estuary on the south coast of WA

(Smallwood & Sumner, 2007). During the early 2000s total annual finfish harvest was

estimated to be more than double that of other estuaries in the region (i.e. 28 vs 0.4 – 12

tonnes), of which Black Bream Acanthopagrus butcheri accounted for c. 75% by weight

(14.8 t), comparable to that in the far larger and more heavily populated Swan-Canning

(i.e. 16 t; Smith 2006). Given that the number of recreational fishers state-wide has

doubled from the early-1990s to mid-2010s (315,000 vs 711,000 fishers; Ryan et al.,

2015), and the tendency for anglers to target larger fish (Blaber et al., 2000; Arlinghaus

et al., 2010), substantial changes in the size structure of key fishery species are expected

to have occurred in the Walpole-Nornalup since its fish fauna was last studied during the

early to mid-1990s (Potter & Hyndes, 1994; Sarre & Potter, 1999). Any such changes,

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particularly among species that are confined to the system, such as the solely estuarine A.

butcheri (Sarre & Potter, 1999), are likely to closely reflect the influence of recreational

rod and line fishing rather than those of netting or commercial fishing.

Thus, using data collected from the Walpole-Nornalup during 2013–17, and two and half

decades ago during the late 1980s and early- to mid-1990s, when the climate regime was

quite different and fishing activity was far lower, the overarching aim of this component

of the study is to explore the extent and potential drivers of any significant interdecadal

changes in the fish fauna and broader ecosystem health of the estuary. The more specific

aims and hypotheses are as follows.

1. Quantify if the fish faunal composition of the estuary has changed between 1989–

90 and 2013–17, and if so, relate any changes to potential shifts in the regional

climate and physico-chemical environment of the system. It is hypothesised that,

given recent marinisation and warming observed throughout other temperate

estuaries, the fish fauna of the Walpole-Nornalup Estuary in 2013–17 will be more

dominated by marine-spawning and warmer-water species than in 1989–90.

2. Determine whether fish compositions show any overall trend in declining

ecological health over time by application of a multimetric biotic index of

ecosystem integrity, the Fish Community Index (FCI; Hallett et al., 2012b).

Despite the relatively low level of physical anthropogenic impacts on the system,

it is hypothesised that decreases in freshwater flow would have caused

environmental degradation, and thus, a decline in the ecosystem health of the

estuary from 1989–90 to 2013–17.

3. Assess whether the population size structure of key fishery species (i.e. A.

butcheri, Australian Herring Arripis georgianus and King George Whiting

Sillaginodes punctatus, the most retained species by recreational fishers within

the estuary; Smallwood & Sumner, 2007) has changed significantly between

decades, and if any such changes are related to fishing activity and/or

environmental drivers. Given the comparatively high levels of recreational fishing

activity in the system, it is hypothesised that larger individuals of these key species

will be less abundant during 2013–17 compared to the 1990s.

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4.2 METHODS

4.2.1 Collection of fish community data

Fish communities in both the nearshore (<1.5 m deep) and offshore (typically >1.5 m

deep) waters of the Walpole-Nornalup Estuary were sampled every second month

between October 1989 (Austral spring) and August 1990 (Austral winter) by Potter and

Hyndes (1994), and seasonally (nearshore waters) or biannually (summer and winter,

offshore waters) between July 2014 and May 2016 as part of the current study (Table 4.1;

Fig. 4.1). In both studies, nearshore fish were sampled using a 41.5 m long beach seine

net (which had a vertical drop of 1.5 m, comprised 51 mm wing mesh and 9 mm bunt

mesh and swept an area of 274 m2), while offshore fish were sampled using multi-mesh

gill nets (160 m long, vertical drop of 2 m, with six to eight mesh sizes ranging from 38–

127 mm stretched internal diameter). Net deployment and retrieval was undertaken as

detailed in Chapter 2 (subsection 2.2.1), with the exception that Potter and Hyndes (1994)

set the gill nets overnight, whereas they were only deployed for one hour during 2014–

16 due to ethical considerations and management agency restrictions on fish mortality

associated with this sampling method. As gill netting during the latter sampling regime

was also restricted to bi-annually, additional data for the offshore waters were obtained

from sampling the above sites during spring 2013 (three hour sets; J. Williams et al.,

Murdoch University, unpubl. data) and autumn 2017 (one hour sets; WA Department of

Primary Industries and Regional Development [DPIRD] Fisheries, unpubl. data),

allowing for comparisons between historical and contemporary periods across all four

seasons (Table 4.1). Additionally, an opportunity arose in early 2017 to compare (a) one

hour and overnight set times and (b) overnight sets in contemporary and historical

periods, during a single sampling event at all sites sampled by Potter and Hyndes (1994),

which is described in the Discussion (subsection 4.4.2). In all cases, all fishes were

identified, counted, measured and allocated to estuarine usage guilds as described in

subsection 2.2.1. To maximise comparability of the data sets, gill net catches of each

species were standardised to fish h−1.

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Table 4.1 Sources of fish species and length composition data analysed in this Chapter.

Interdecadal analysis Data source

Year(s) Seasons sampled

Period

Nearshore fish communities and ecosystem health Potter & Hyndes (1994) 1989‒90 All Historical Current sampling regime 2014‒16 All Contemporary Offshore fish communities and ecosystem health Potter & Hyndes (1994) 1989‒90 All Historical Current sampling regime 2014‒16 W, S Contemporary J. Williams et al., Murdoch University (unpublished data)

2013 Sp Contemporary

WA Fisheries monitoring (DPIRD Fisheries, unpublished data)

2017 A Contemporary

Length composition of key recreational fishery species Potter & Hyndes (1994) 1989‒90 All Historical (Sarre, 1999)^ 1993‒96 All Historical Current sampling regime 2014‒16 All Contemporary J. Williams et al., Murdoch University (unpublished data)^

2013 Sp Contemporary

^Length composition data for Acanthopagrus butcheri only. Seasons; winter (W), spring (Sp) summer (S)

and autumn (A).

Figure 4.1 Location of each nearshore and offshore site at which fish were sampled in

the Walpole-Nornalup Estuary in 1989─90 (Potter & Hyndes, 1994) and 2013─17.

Abbreviations for each sampling region as used in the text are given in parentheses.

4.2.2 Collection of environmental data

Historical records of total monthly rainfall (mm) in Walpole, collected by the Australian

Bureau of Meteorology (BoM; station ID 009611), were collated for all years which they

were available, i.e. 1952 to 2015 (BoM, 2016; http://www.bom.gov.au/climate/data/).

Limited historical air temperature data exist for the Walpole region, thus mean monthly

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maximum and minimum values (°C) recorded at a nearby coastal weather station (BoM

station ID 009518; Cape Leeuwin) over the above period were instead used.

River flow data for the two major tributaries of the estuary, the Frankland and Deep rivers,

were obtained from the Department of Water (www.kumina.water.wa.gov.au). Total

monthly discharge (megalitres) was obtained for each year in which data were available,

i.e. 1952–2015 at the Frankland River station, Mount Frankland (ID 605012), and 1976–

2015 at the Deep River station, Teds Pool (ID 606001).

Salinity and water temperature (°C) were measured at each site on each occasion when

fish were sampled during 1989─90 and 2013─17 using a multiparameter water quality

meter (HydroLab or Yellow Springs International). These parameters were recorded in

the middle of the water column at nearshore sites, and at both the water surface and

bottom at the deeper offshore sites. Due to equipment malfunction, no water quality data

were recorded in spring 2015.

4.2.3 Data analyses

The following statistical analyses were performed using the software packages PRIMER

v7 (Clarke & Gorley, 2015) with the PERMANOVA+ add-on module (Anderson et al.,

2008) or R (R Development Core Team, 2016; www.r-project.org).

Longer-term changes in environmental conditions

To test whether total annual rainfall and river flow to the estuary had declined over time,

and if annual average monthly minimum and maximum air temperatures had increased,

Pearson’s product moment linear correlation was employed using a one-tailed t-test. To

account for curvilinearity of rainfall and flow data, total annual values were log-

transformed prior to analysis. All available data (i.e. 1952–2015 for temperature, rainfall

and discharge in the Frankland River, and 1976–2015 for discharge in the Deep River)

were firstly analysed, then focus was placed on examining changes coinciding with the

fish sampling regimes, i.e. employing data from January 1988 (preceding the 1989–90

fish sampling of Potter and Hyndes, 1994) to December 2015 (preceding the cessation of

fish sampling in the current study). Additionally, to test whether any longer-term changes

in total rainfall and river discharge, or average minimum and maximum air temperature

varied between seasons, the above tests were then undertaken separately for each season

of each year during the latter period. For all tests Pearson’s correlation coefficient r was

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used to determine the strength of the relationship between climate variables and years,

and significance rejected at a Bonferroni corrected P ≥ 0.05.

Water temperature (°C) and salinity data collected simultaneously with fish data during

1989–90 and 2013–17 were initially examined for homogeneous dispersion among a

priori groups (Anderson, 2001) following the criteria of Clarke et al. (2014a), and shown

to require no transformation prior to analysis. Separate Euclidean distance matrices were

constructed for each water quality variable in each of the nearshore and offshore waters,

which were then subjected to Permutational Analysis of Variance tests (PERMANOVA;

Anderson, 2001). For the nearshore waters a three-way crossed region × season × year

design was employed. For the offshore waters, depth was added as a fourth factor, and

the ‘year’ factor replaced with period, i.e. two levels, ‘historical’ and ‘contemporary’. All

factors were considered fixed, and the null hypothesis of no significant differences among

years was rejected if the significance level (P) was <0.05. The components of variation

value (COV) for each significant and relevant term was used to ascertain their relative

importance.

Interdecadal comparison of nearshore fish faunas

The total number of individual fish (square-root transformed) and counts of the number

of species (no transformation required) in each sample collected from the nearshore

waters were used to create separate Euclidean distance matrices. Average taxonomic

distinctness (∆+), a robust presence-absence measure of species diversity (Warwick &

Clarke, 1995), was calculated for each sample using the DIVERSE routine and the

resultant data also used to construct a Euclidean distance matrix.

The above three matrices were then each subjected to a three-way crossed region × season

× year PERMANOVA. While the main focus was to explore decadal differences, all three

periods (1989–90, 2014–15 and 2015–16) were treated as separate levels of that factor,

given that fish were only sampled for one year in the earlier period but two in the latter,

and that previous analyses in Chapter 2 demonstrated significant differences in nearshore

fish composition between 2014─15 and 2015─16 (subsection 2.3.3). Any significant

yearly differences were only treated as important when the main cause was between

1989–90 and one or both of the later years. Additionally, it should also be noted that any

significant terms not involving year were not examined further, with the former factors

only included to account for any confounding influences of region and/or season.

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Interpretation of these tests was the same as that outlined above for water quality

variables.

Any significant differences in taxonomic diversity between the historical and

contemporary period were further explored using funnel plots of the mean ∆+ vs number

of species, within each region and/or season as appropriate.

To test for any significant yearly differences in species composition, nearshore species

abundance data were first pre-treated via dispersion weighting (Clarke et al., 2006) and

square-root transformation (Clarke et al., 2014b). These data were then used to construct

a Bray-Curtis similarity matrix which was subject to the same PERMANOVA test

described above. To examine inter-period differences in functional guild composition, the

pre-treated data were then averaged separately on the basis of (i) estuarine usage,

(ii) habitat and (iii) feeding mode functional guilds (see subsection 2.2.2), used to

calculate separate Bray-Curtis resemblance matrices, then similarly subjected to

PERMANOVA. Any significant compositional differences among years were then

further explored using Analysis of Similarity (ANOSIM) tests (Clarke & Green, 1988;

Clarke, 1993) using a three-way crossed region × season × year design. The criterion for

rejecting the null hypothesis of no significant differences among years was the same as

that for PERMANOVA, and the extent of any significant differences was gauged by the

magnitude of the R-statistic.

Non-metric multidimensional scaling ordination (nMDS) was used to illustrate any

significant inter-period differences in species composition detected by the above tests,

with averages of each region and/or season during each year displayed and bootstrapping

used to provide 95% confidence intervals.

A shade plot (Clarke et al., 2014b) constructed from the pre-treated species abundance

data, averaged appropriately, was then used to determine the species most responsible for

driving any significant differences in historical (1989–90) and contemporary (2014–16)

fish composition. Species (displayed on the y-axis) were ordered according to a group-

average hierarchical agglomerative cluster analysis of a resemblance matrix defined

between species as Whittaker’s index of association (Legendre & Legendre, 1998). A

Similarity Profiles test (SIMPROF Type 3; Somerfield & Clarke, 2013) was also applied

to identify those points in the clustering procedure at which no significant structure (i.e.

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difference in species abundance patterns) could be detected. Samples, displayed on the x-

axis, were ordered by year, with region and/or season nested as appropriate.

To determine which guilds were most responsible for any significant interdecadal

differences in functional composition, the proportions of each guild (based on pre-treated

values) during each decadal period were calculated within each region and/or season as

appropriate.

Interdecadal comparison of offshore fish faunas

Pre-treatment and analysis of the offshore fish faunal data to test for any significant

decadal differences was the same as that described above for the nearshore fish data, with

the following exceptions. Firstly, as gill nets were set for considerably longer during

1989–90 than 2013–17, differences in species richness were not examined given the

susceptibility of this measure to sampling effort. Secondly, the design of the

PERMANOVA test differed slightly, in that the ‘year’ factor was replaced with ‘period’

(i.e. historical, 1989–90 and contemporary, 2013–17), with the winter and summer

samples collected in 2014–15 and 2015–16 pooled given that previous analyses in

Chapter 2 detected no interannual variability in their composition (subsection 2.3.4). It

should also be noted that as the data from 1989–90 were collected every second month

during a one year period, the two winter and summer samples at each site were collected

during the same year.

Relationships between fish communities and salinity and temperature

To test for significant correlations between any differences in fish species composition

from 1989–90 to 2013–17 and those in a range of potential environmental drivers, both

the Biota and Environment matching (BIOENV; Clarke & Ainsworth, 1993) and

Distance-based Linear Modelling (DISTLM; McArdle & Anderson, 2001) routines were

employed. For these analyses, subsets of the Bray-Curtis resemblance matrices

constructed from the pre-treated nearshore or offshore species composition data

(described above) were each matched with Euclidean distance matrices constructed from

the corresponding salinity and/or temperature data collected in situ at the time of fish

sampling. In the offshore waters, a stratification index (i.e. the difference in salinity

between the surface and bottom of the water column) was also included in the

environmental data suite. Prior to analysis, the environmental data were subjected to

Draftsman plots to determine the extent of any collinearity (Pearson’s correlation always

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<0.95) and the need for any transformation (none required), then normalised to place all

variables on the same (dimensionless) scale. For each of the nearshore and offshore data

sets, these tests were undertaken separately within each region (using data from all

seasons and both periods) and season (using data from all regions and both periods) to

reduce any confounding influences of region/season within decades.

For the BIOENV tests, the Spearman rank correlation coefficient (ρ) was employed as

the matching coefficient. For DISTLM tests, a step-wise selection procedure using a

modified version of the Akaike (1973) information criterion (AICC) was employed as the

selection criterion, and the R2 value was used to gauge the proportion of fish variability

‘explained’ by the ‘best’ water quality model. For both tests, the null hypothesis of no

significant correlation was rejected if P < 0.05. Significant matches detected by BIOENV

were illustrated by subjecting the relevant Bray-Curtis matrices constructed from the fish

data to nMDS ordination, then overlaying bubble plots of the selected water quality data.

When DISTLM detected significant results, a distance-based redundancy analysis

(dbRDA) was used to illustrate the modelled relationships.

Interdecadal changes in estuarine ecosystem health

A quantitative fish-based index of estuarine ecosystem health, the Fish Community Index

(FCI; Hallett et al., 2012b), was employed to assess the current ecological health of the

system and identify any change in its health status since 1989–90. The FCI was first

developed for the Swan-Canning Estuary on the lower west coast of WA and, since 2012,

has been implemented for annual monitoring and reporting of the condition of that

system. This multimetric index integrates information on a suite of biological variables

(‘metrics’; see Table 4.2), each of which quantifies an aspect of the structure and/or

function of the fish community, to quantify estuarine health status (Hallett et al., 2016c).

Separate indices have been constructed for nearshore and offshore waters given the

natural differences in their fish assemblages.

Scores for each metric in each fish sample were calculated by comparing the sample data

to ‘best-available’ historical reference conditions, which were tailored to each main

region of the estuary and season (see Hallett et al. [2012a] for full details). The metric

scores were then summed to provide a quantitative FCI score for each sample (scaled 0–

100). Finally, index scores were compared to statistically-derived thresholds (Hallett,

2014) to determine estuarine health grades, ranging from A (very good) to E (very poor).

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Note that, given the relative paucity of historical fish faunal data for the Walpole-

Nornalup Estuary, a modified version of the FCI was used in the current study. This

employed all available historical fish community data from permanently-open estuaries

on the south coast of WA to establish the reference conditions for each metric, and the

statistically-derived scoring thresholds used to determine estuarine health grades (Table

4.3). Final health index scores for the Walpole-Nornalup during historical and

contemporary periods were calculated using the nearshore and offshore fish species

composition data outlined in Table 4.1.

Table 4.2 Fish metrics employed for the nearshore and offshore Fish Community Indices

(Hallett et al., 2012b).

a A measure of the biodiversity of species b Species with specialist feeding requirements (e.g. those which only eat small invertebrates) c Species which are omnivorous or opportunistic feeders d Species which eat detritus (decomposing organic material) e Species which live on, or are closely associated with, the sea/river bed f The Blue-spot or Swan River goby, a tolerant, omnivorous species which often inhabits silty habitats and

is adapted to dealing with low dissolved oxygen conditions by undertaking aquatic surface respiration (Gee

& Gee, 1991)

Table 4.3 Threshold scores for each Fish Community Index estuarine health grade (as

derived from unpublished analyses by C. Hallett, Murdoch University, using all available

historical fish community data from permanently-open south coast estuaries and

following the approach of Hallett, 2014).

Grade Nearshore Offshore

A >72.52 >72.60

B 64.35–72.52 58.55–72.60

C 57.31–64.35 46.20–58.55

D 47.90–57.31 33.88–46.20

E <47.90 <33.88

Metric

Predicted

response to

degradation

Nearshore

Index

Offshore

Index

Number of species (no.spp) Decrease ✓ ✓

Shannon-Wiener diversity (sha.wie) a Decrease ✓

Proportion of trophic specialists (p.troph.spec) b Decrease ✓

Number of trophic specialist species (no.troph.spec) b Decrease ✓ ✓

Number of trophic generalist species (no.gen) c Increase ✓ ✓

Proportion of detritivores (p.detr) d Increase ✓ ✓

Proportion of benthic-associated individuals

(p.benth.indv) e

Decrease ✓ ✓

Number of benthic-associated species (no.benth.sp) e Decrease ✓

Proportion of estuarine spawning individuals (p.es.sp) Decrease ✓ ✓

Number of estuarine spawning species (no.es.sp) Decrease ✓

Proportion of Pseudogobius olorum (p.olorum) f Increase ✓

Total number of Pseudogobius olorum (tot.no.olorum) f Increase ✓

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Interdecadal differences in length composition of key recreational fishery species

Length-frequency plots and kernel density estimates (KDEs; Silverman, 1986) were used

to assess any changes in the length distribution of three abundant and highly targeted

recreational fishery species (Acanthopagrus butcheri, Sillaginodes punctatus and Arripis

georgianus) between the early-1990s and mid-2010s. To maximise sample sizes for A.

butcheri, additional historical length data were used (see Table 4.1), which had been

obtained from a biological study of this species during 1994–96 by Sarre (1999), using

the same 41.5 m seine nets and multimesh gill nets as described for the present sampling

regime.

KDEs were fitted using the R package ‘sm’ (Bowman & Azzalini, 2010), and the

probability density function f(𝑥) of the lengths determined using the following formula,

where K is the kernel, h is the smoothing parameter (bandwidth) and n is the number of

observations.

𝑓(𝑥) =1

𝑛ℎ∑ 𝐾 (

�̂� − 𝑥𝑖

ℎ )

𝑛

𝑖=1

The ‘sm.density.compare’ function in ‘sm’ was used to test for any significant

(Bonferroni adjusted P < 0.05) differences in the length composition of each species

between historical and contemporary periods. This test compared the KDEs of each

period against a null model created from the combined length-distribution during both

periods using a permutation test with 1000 iterations. When significant inter-period

differences were detected, a plot of the null model (±SE) was overlaid with the KDEs

from each period to determine which regions of the length-distribution had changed over

time (Langlois et al., 2012). As length data for A. butcheri was obtained opportunistically

from several studies, KDEs were fitted separately for seine and gill net data to account

for any inter-period differences in sampling effort with either gear type.

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4.3 RESULTS

4.3.1 Interdecadal changes in climatic conditions and estuarine water quality

Total annual rainfall in the Walpole region has declined significantly from 1952 to 2015

(P = 0.002, r = −0.35; Appendix 4.1; Fig. 4.2a). Rainfall decline was most apparent during

the early-mid 1970s, with ten-year average values prior to 1970 ranging 1400–1480 mm

and decreasing to 1187–1296 mm between 1976 and 2015 (Fig. 4.2a). Thus, during the

latter period, total annual rainfall was often >250 mm below the long-term average, and

rarely exceeded 200 mm above that average. No significant reduction in total annual or

seasonal rainfall occurred, however, over the 1988–2015 period of most interest to the

current study (Appendix 4.1; Fig. 4.2a; 4.3a).

While total annual discharge in both the Frankland and Deep rivers has similarly declined

over time, this was most apparent from 1988 to 2015 (i.e. Frankland, 1952–2015, r =

insignificant vs 1988–2015, r = −0.54; Deep 1976–2015, r = −0.42 vs 1988–2015, r =

−0.62; Appendix 4.1; Fig. 4.2b,c). During the period of 1988−2015, ten-year average

values for flow declined from 150 to 90 GL in the Frankland and from 35 to 17 GL in the

Deep (Fig. 4.2b,c). In the Deep River these declines were significant during winter, spring

and autumn, while in the Frankland River decreases were evident during winter and

spring only (Appendix 4.1; Fig. 4.3b,c). In both tributaries, the volume of decline was by

far the greatest in winter and accounted for c. 50–72% of the total flow reduction between

1988 and 2015.

In contrast, both mean monthly minimum and maximum surface air temperatures in the

Walpole region have increased significantly between 1952 and 2015 (r = 0.69 and 0.58,

respectively; Appendix 4.1; Fig. 4.2d,e). After 1988, annual means of both variables

regularly exceed the long term (1952–2015) average, and very few cooler (i.e. below

average) years were recorded (Fig 4.2d,e). Ten-year average maximum temperatures

steadily rose during this period (Fig. 4.2d), with two marked step-wise increases

occurring, firstly during 1980–85, and again even more noticeably during 2010–15 when

temperatures increased by c. 0.5 °C (Fig. 4.2d). Mean minimum monthly temperatures

cooled slightly from 1967 to 1973, after which they increased, most rapidly so during

2010–15 (Fig. 4.2e). Moreover, by 2015 ten-year average minimum air temperatures were

0.8 °C warmer than in 1988 (14.9 vs 14.1 °C; Fig. 4.2e). Within individual seasons, mean

minimum temperatures were 0.7–1.0 °C warmer during winter, spring and summer in

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2015 than 1988, and mean maximum values were 0.4–0.7 °C higher in the former two

seasons (Fig. 4.3d,e). No significant warming occurred in autumn.

Within the estuary, mean water temperature and salinity at the sites at which fish were

sampled were also markedly different between the historical (1989–90) and contemporary

(2013–17) periods. In the shallow nearshore waters, PERMANOVA detected significant

and relatively important season × year interactions for each water quality variable, and

while the region × season × year interaction was also significant for salinity, it was far

less influential (Appendix 4.2). Note, that while both contemporary sampling years

(2014–15, 2015–16) were included as separate factors in the above test design, further

ANOSIM tests (not shown) revealed that significant year interactions were primarily due

to differences between 1989–90 and one or both contemporary years, and that no

difference occurred in temperature between 2014–15 and 2015–16. Thus, mean nearshore

temperatures in each season were 1.8–5.7 °C warmer during contemporary sampling than

historically, except in autumn when they were c. 3 °C cooler (Fig. 4.4a). Mean salinities

also notably increased over time during both winter and spring (i.e. 2 vs 15–24 in winter

and 14 vs 28 in spring; Fig. 4.4b).

Similarly, in the deeper offshore waters a significant season × period interaction was

detected among both temperature and salinity, with the main effect of period also

significant for the latter variable (Appendix 4.3). Interdecadal temperature changes in

these waters mirrored those in the shallows, albeit to a slightly lesser extent, with winter,

spring and summer temperatures 0.6–1.8 °C warmer during 2013–17 than 1989–90, while

in autumn the water was c. 3 °C cooler (Fig. 4.5a). With respect to offshore salinity,

markedly higher means were recorded in both winter and autumn of 2013–17 than 1989–

90 (20 vs 12 and 35 vs 28, respectively), while little change occurred during summer and

spring (Fig. 4.5b).

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Figure 4.2 Long-term trends in (a) total annual rainfall in Walpole, (b) total annual flow

in the Frankland River, (c) total annual flow in the Deep River, (d) mean monthly

maximum air temperatures at Cape Leeuwin and (e) mean monthly minimum air

temperatures at Cape Leeuwin. Horizontal green line represents the long-term average of

each variable (i.e. from 1952 to 2015 for plots a, b, d, e; 1976 to 2015 for plot c) and grey

bars show annual anomalies. Blue line indicates a 10 year average of each climate variable

(across years prior). Light blue shading corresponds to the interdecadal fish sampling

period.

(a) Total annual rainfall

(b) Total annual flow (Frankland River)

(c) Total annual flow (Deep River)

(d) Mean monthly maximum air temperatures

(e) Mean monthly minimum air temperatures

Fish sampling period

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Figure 4.3 Rolling average across ten years prior of (a) total annual rainfall in Walpole,

(b) total annual flow in the Frankland River, (c) total annual flow in the Deep River, (d)

mean monthly maximum air temperatures at Cape Leeuwin and (e) mean monthly

minimum air temperatures at Cape Leeuwin, in each season from 1988 to 2015.

(a)

(b)

(c)

(d)

(e)

Winter

Spring

Summer

Autumn

Season

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Figure 4.4 (a) Mean (±SE) temperature (°C) recorded in the shallow nearshore waters of

the Walpole-Nornalup Estuary seasonally during 1989–90 and 2014–16. (b) Mean (±SE)

salinity recorded seasonally in those waters during 1989–90, 2014–15 and 2015–16.

Seasons; winter (W), spring (Sp), summer (S) and autumn (A).

Figure 4.5 Mean (±SE) (a) temperature (°C) and (b) salinity recorded in the deeper

offshore waters of the Walpole-Nornalup Estuary during winter (W), spring (Sp), summer

(S) and autumn (A) of 1989–90 and 2013–17.

(a) (b)

(a) (b)

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4.3.2 Interdecadal changes in fish faunal composition

Nearshore waters

At a broad level, comparison of the fish faunas throughout the nearshore waters of the

Walpole-Nornalup Estuary between the historical (1989–90) and contemporary (2014–

16) sampling periods revealed that the estuarine and marine Leptatherina presbyteroides

was the most abundant species in both periods, based on percentage contribution to the

overall catch (Table 4.4). However, while it comprised nearly half of the catch in the

earlier period, it represented c. 77% in the later period. Additionally, Favonigobius

lateralis and L. wallacei, which ranked second and third in 1989–90 (c. 17–27%), ranked

only seventh and ninth during contemporary sampling (c. 1–2%). Atherinosoma elongata

was relatively abundant in both periods (c. 3–5% of the catch), whereas the marine sparid

Rhabdosargus sarba and sillaginid Sillaginodes punctatus, which together represented c.

6% of the catch in 2014–16, comprised <1% of the catch in 1989–90. The total number

of species and taxonomic distinctness (∆+) recorded in 2014–16 was considerably higher

than in 1989–90 (i.e. 26 vs 11 species, and 73.8 vs 71.3 ∆+), due mainly to several species

with marine affinities that were not recorded in the earlier period (Table 4.4).

These findings were supported by PERMANOVA tests employing species richness and

∆+ data recorded in each region and on each sampling occasion, which detected

significant differences among both variables between years, and in the case of the latter

for all crossed interactions involving the term year (Appendix 4.4). Mean species richness

was significantly lower during 1989–90 than in 2014–15 and 2015–16 (3.3 ± 0.5 vs 4.9 ±

0.5 and 5.5 ± 0.7 species, respectively). Likewise, ∆+ generally increased between 1989–

90 and 2014–16, most notably in the regions LN and WI (Fig. 4.6a), and during winter

(Fig. 4.6b). It should also be noted that during 1989–90 all ∆+ values were below those of

the global mean of all samples. Contrastingly, no significant differences in fish

abundances were detected between years (Appendix 4.4).

Nearshore species composition differed significantly between years and for all interaction

terms involving years (Appendix 4.5). The year component of a subsequent three-way

crossed year × season × region ANOSIM test on the species composition data revealed

that significant interannual effects were due to substantial differences between 1989–90

and 2014–15/2015–16 (R = 0.75–1.0), while no significant difference occurred between

the latter two years (Table 4.5a). An nMDS ordination plot of the nearshore species

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composition in each region during each of the above years (Fig. 4.7a) shows that these

decadal differences were most apparent (longest trajectory) in the WI, and to a lesser

extent the LN. From a seasonal perspective, the most notable interdecadal changes

occurred during summer (Fig. 4.7b), with the magnitude of changes in other seasons less

clear due to variation among the two contemporary years. A complementary shade plot

analysis demonstrated that these longer-term shifts in nearshore fish fauna were due

mainly to notably higher and more consistent catches of various marine species in the

contemporary period, e.g. R. sarba, Sillago schomburgkii, L. presbyteroides, S. punctatus

and Aldrichetta forsteri, as well as numerous other relatively abundant marine species

which were not recorded during historical sampling, e.g. Hyperlophus vittatus,

Arenigobius bifrenatus, Engraulis australis, S. burrus and Hyporhamphus melanochir

(Table 4.4; Fig. 4.7c). The estuarine species A. butcheri and A. elongata were also notably

more abundant in 2014–16. In contrast, the gobiid F. lateralis and the estuarine and

freshwater species L. wallacei and Pseudogobius olorum were more prevalent in 1989–

90 (Fig. 4.7c). While all three regions of the estuary were characterised by a greater

diversity of species during 2014–16, this was especially the case in the Lower Nornalup

where an additional 11 species were recorded. Similarly, during summer far greater

abundances of several species, including R. sarba, S. punctatus, A. elongata and H.

vittatus, were recorded during 2014–16 compared to 1989–90 (Fig. 4.7c).

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Table 4.4 Percentage contribution (%) and rank based on total abundance/catch rate (R) of each fish species recorded in the nearshore and offshore

waters of the Walpole-Nornalup Estuary during the historical (1989–90) and contemporary (2014–16/2013–17) sampling periods. Functional guilds (E,

estuarine usage; F, feeding mode; H, habitat) are given for each species (guild abbreviations described in the footnote). Abundant species (contributing

≥5%) are in bold.

Nearshore waters Offshore waters

Guild 1989–90 2014–16 1989–90 2013–17

Family Species E, F, H % R % R % R % R RHINOBATIDAE Aptychotrema vincentiana MS, ZB, D 0.48 17 1.16 14

MYLIOBATIDAE Myliobatis tenuicaudatus MS, ZB, D 4.12 8 0.5 17

ELOPIDAE Elops machnata MS, PV, BP 0.05 20 4.46 5

CLUPEIDAE Spratelloides robustus MEO, ZP, SP 0.06 18 Hyperlophus vittatus MEO, ZP, SP 0.41 12

ENGRAULIDAE Engraulis australis EM, ZP, SP 1.58 8 0.83 15 0.99 15

GONORYNCHIDAE Gonorynchus greyi MS, ZB, D 0.05 20

TRIAKIDAE Mustelus antarcticus MS, ZB, D 2.46 12 1.49 12

SPHYRNIDAE Sphyrna zygaena MS, PV, P 0.08 19

PLOTOSIDAE Cnidoglanis macrocephalus EM, ZB, D 0.01 23 11.96 4 0.66 16

HEMIRAMPHIDAE Hyporhamphus melanochir MEO,ZB,SP 0.09 16 0.5 17

ATHERINIDAE Leptatherina presbyteroides EM, ZP, SP 47.27 1 77.08 1

Leptatherina wallacei ES, ZB, SP 16.52 3 1.50 9

Atherinosoma elongata ES, ZB, SP 4.78 4 3.24 3

PLATYCEPHALIDAE Platycephalus speculator EM, PV, D 7.17 5 1.32 13

TERAPONTIDAE Pelates octolineatus MEO, OV, BP 0.98 10 3.96 9 5.78 4

SILLAGINIDAE Sillago bassensis MS, ZB, D 1.91 13

Sillaginodes punctatus MEO, ZB, D 0.87 7 2.86 4 5.42 6 1.82 9

Sillago burrus MEO, ZB, D 0.03 22

Sillago schomburgkii MEO, ZB, D 0.21 14 1.82 9

POMATOMIDAE Pomatomus saltatrix MEO, PV, P 1.52 14 3.14 6

CARANGIDAE Trachurus novaezelandiae MS, ZB, P 0.5 17 Pseudocaranx georgianus MEO, ZB, BP 3.42 10 2.48 7

ARRIPIDAE Arripis georgianus MEO, PV, P 0.56 8 0.06 18 17.25 1 16.67 2

Table continued overleaf.

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Nearshore waters Offshore waters

Guild 1989–90 2014–16 1989–90 2013–17

Family Species E, F, H % R % R % R % R Arripis truttaceus MEO, PV, P 0.40 13

SPARIDAE Chrysophrys auratus MEO, ZB, BP 2.58 11 2.48 7

Acanthopagrus butcheri ES, OP, BP 1.12 5 2.27 6 13.81 3 43.07 1

Rhabdosargus sarba MEO, ZB, BP 0.06 10 3.39 2 0.05 20 9.41 3

MUGILIDAE Aldrichetta forsteri MEO, OV, P 1.06 6 2.82 5 5.08 7 Mugil cephalus MEO, DV, P 0.52 11 16.81 2 1.82 9

LABRIDAE Notolabrus parilus MS, ZB, D 0.08 17 Halichoeres brownfieldi MS, ZB, D 0.03 22

BLENNIIDAE Parablennius postoculomaculatus MS, OV, SB 0.04 21

GOBIIDAE Favonigobius lateralis MEO, ZB, SB 27.39 2 2.12 7

Arenigobius bifrenatus ES, ZB, SB 0.12 15

Pseudogobius olorum ES, ZB, SB 0.31 9

PARALICHTHYIDAE Pseudorhombus jenynsii MEO, ZB, D 0.01 23 0.37 18

PLEURONECTIDAE Ammotretis rostratus MEO, ZB, D 0.06 10 0.05 20 0.60 16

MONACANTHIDAE Monacanthid sp. MS, OV, D

0.01 23

Number of species 11 26 22 19

Number of families 8 14 18 15

Taxonomic distinctness (∆+)

71.3 73.8

82.42 79.77

Estuarine usage, E; estuarine species (ES), estuarine and marine (EM), marine estuarine-opportunist (MEO), marine straggler (MS). Feeding mode, F; zooplanktivore

(ZP), zoobenthivore (ZB), piscivore (PV), omnivore (OV), opportunist (OP), detritivore (DV). Habitat, H; small pelagic (SP), small benthic (SB), pelagic (P), demersal

(D), bentho-pelagic (BP).

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Table 4.5 R-statistic and/or P values for global and pairwise comparisons from ANOSIM

tests on nearshore fish (a) species composition, and (b) estuarine usage, (c) feeding mode

and (d) habitat guild composition. Significant (P < 0.05) pairwise R comparisons are in

bold.

(a) Species composition (b) Estuarine usage guilds Years (Global R = 0.750, P = 0.001) Years (Global R = 0.431, P = 0.005) 1989–90 2014–15 1989–90 2014–15 2014–15 1 2014–15 0.563 2015–16 0.75 0.375 2015–16 0.375 0.4375 Seasons (Global R = 0.701, P = 0.001) Seasons (Global R = 0.507, P = 0.001)

W Sp S W Sp S Sp 0.667^ Sp 0.417^ S 1.000^ 0.750^ S 0.333^ 0.583^ A 0.417^ 1.000^ 0.250^ A 0.667^ 0.500^ 0.417^ Regions (Global R = 0.758, P = 0.001) Regions (Global R = 0.654, P = 0.001) WI UN WI UN UN 0.917 UN 0.667 LN 0.545 LN 0.545

(c) Feeding mode guilds (d) Habitat guilds Years (Global R = 0.292, P = 0.063) Years (Global R = 0.458, P = 0.008) 1989–90 2014–15 1989–90 2014–15 2014–15 0.438 2014–15 0.563 2015–16 0.250 0.188 2015–16 0.688 -0.063 Seasons (Global R = 0.542, P = 0.002) Seasons (Global R = 0.551, P = 0.003) W Sp S W Sp S Sp 0.583^ Sp 0.000^ S 0.750^ 0.583^ S 0.500^ 0.167^ A 0.583^ 0.833^ 0.333^ A 0.500^ 0.583^ 0.083^ Regions (Global R = 0.516, P = 0.009) Regions (Global R = 0.447, P = 0.012) WI UN WI UN UN 0.667 UN 0.667 LN 0.182 LN 0.364

^Permutations for pairwise test <35 and thus not interpreted further irrespective of P value.

Figure 4.6 Average taxonomic distinctness (∆+) of the nearshore fish fauna in the

Walpole–Nornalup Estuary during 1989–90 (open symbols) and 2014–16 (closed

symbols) within: (a) each region (averaged over seasons) and (b) each season (averaged

over regions). Contours represent limits within which 95% of simulated ∆+ values lie, and

dashed lines indicate mean ∆+.

(a) (b)

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Figure 4.7 nMDS ordination plot constructed from the Bray-Curtis resemblance matrix

of nearshore species composition of the Walpole-Nornalup Estuary (a) bootstrapped to

create averages for each region and (b) employing the distance among centroid averages

of each season, during 1989–90 (), 2014–15 () and 2015–16 (). Regions; Walpole

Inlet (WI; ◼), Upper Nornalup (UN; ◼) and Lower Nornalup (LN; ◼). Seasons; winter

(W), spring (Sp) summer (S) and autumn (A). Trajectories show temporal order of

sampling and shaded areas on Fig. 4.7a represent approximate 95% confidence

boundaries. (c) Shade plot of the pre-treated abundances of each species during 1989–90

and 2014–16 in each region and season, with shading intensity being proportional to

abundance. Species in Fig. 4.7c are ordered by a hierarchical cluster analysis of their

mutual associations across groups and dashed lines in the dendrogram indicate species

with significantly similar patterns of abundance, as detected by SIMPROF.

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With respect to guild composition based on estuarine usage, feeding mode and habitats,

PERMANOVA detected significant year effects and various interactions involving year

in all three cases (Appendix 4.5). ANOSIM tests revealed that these significant yearly

differences were due solely to differences between the historical sampling period (1989–

90) and one or both of the contemporary sampling years (i.e. 2014–15/2015–16) in the

case of estuarine usage (R = 0.563) and habitats (R = 0.563–0.688; Table 4.5b,d).

However, no significant pairwise yearly differences in feeding guild composition were

detected (Table 4.5c).

The above interdecadal differences in estuarine usage composition were in part driven by

pronounced increases in marine stragglers in the LN and estuarine & marine species in

the UN over time. This latter guild type decreased, however, in the LN, as did the

proportion of estuarine species in the UN (Fig. 4.8a). In the WI solely estuary species

dominated catches during both periods, although during the contemporary period

estuarine & marine and marine estuarine-opportunist species were slightly more abundant

than historically (Fig. 4.8a). Within seasons, the proportion of solely estuarine species

was notably lower during winter, spring and summer of the contemporary period than

historically, with estuarine & marine or marine stragglers species proportionately more

abundant (Fig. 4.8a). Contrastingly, however, the proportion of solely estuarine species

increased over time during autumn, with marine-estuarine opportunists clearly less

abundant. Among habitat guilds, small benthic fishes often dominated the assemblages in

1989–90, particularly in the LN and in summer and autumn, whereas bentho-pelagic

fishes were often among the most abundant in 2014–16, especially in the WI and LN and

in winter and autumn (Fig. 4.8b). Additionally, there was a greater diversity of habitat

guilds in the later than earlier period, with all five guilds represented in each region and

season in 2014–16, whereas this was often not the case in 1989–90 (Fig. 4.8b). While

interdecadal trends in feeding mode were less clear, a greater diversity of guilds generally

occurred in 2014–16 than 1989–90 (Fig. 4.8c). In the LN for example, only

zoobenthivores and zooplanktivores were recorded during 1989–90, whereas omnivores

also made a notable contribution in 2014–16. Moreover, zoobenthivores dominated in

summer and autumn in 1989–90, whereas a greater spread of guilds dominated by

opportunists occurred in these seasons in 2014–16. Interestingly, detritivores were only

recorded during 2014–16 and only in the UN and WI during winter and spring (Fig. 4.8c).

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Figure 4.8 Proportions of each (a) estuarine usage, (b) habitat and (c) feeding mode guild

recorded in the nearshore waters of the Walpole-Nornalup Estuary during 1989–90 and

2014–16 in each region (across all seasons) and each season (across all regions). Regions;

Lower Nornalup (LN), Upper Nornalup (UN) and Walpole Inlet (WI). Seasons; winter

(W), spring (Sp) summer (S) and autumn (A). See Table 4.4 for guild abbreviations.

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Offshore waters

As in the nearshore waters, several notable differences in species contributions occurred

between 1989–90 and 2013–17 in the offshore waters (Table 4.4). For example, while A.

butcheri and A. georgianus ranked in the top three species in both periods, they together

comprised a far greater proportion of the overall catch in the contemporary period (c. 60

vs 31%). In contrast, the second most abundant species in 1989–90, Mugil cephalus (c.

17% of the catch), contributed <2% during 2013–17. Other species that were abundant in

the earlier but not the later period included Cnidoglanis macrocephalus and

Platycephalus speculator (c. 7–12% during 1989–90 vs 1% in 2013–17), while the

reverse was true for R. sarba and Elops machnata (<0.1 vs 4–9%; Table 4.4). The total

number of species and taxonomic distinctness (Δ+) recorded in the offshore waters (all

regions and seasons combined) decreased slightly over time (i.e. 22 vs 19 species, 82.4

vs 79.8 Δ+; Table 4.4). Within particular regions, both metrics were lower during 2013–

17 than 1989–90 in all except the WI, where the reverse was true for Δ+ (Fig. 4.9a).

Moreover, PERMANOVA employing replicate Δ+ data detected that inter-period

differences were the only significant term in a three-way crossed design (Appendix 4.6),

with mean Δ+ decreasing from 78.7±1.2 to 43.0±8.3 between decades. Contrastingly, no

significant differences in overall abundance (i.e. hourly catch rates) were detected

(Appendix 4.6).

With respect to species composition, PERMANOVA detected a significant difference

between sampling periods, which was the most influential term, as well a significant

region × period interaction (Appendix 4.7). A complementary nMDS plot (Fig. 4.9b)

illustrates all points representing 2013–17 clearly separated and laying to the right of

those from 1989–90, with the greatest interdecadal shifts (as evidenced by trajectory

length) occurring in the LN, UN and FR.

A shade plot (Fig. 4.10) revealed notably higher abundances of P. speculator, C.

macrocephalus, Myliobatis tenuicaudatus, M. cephalus, Pelates octolineatus and S.

punctatus in at least three regions during 1989–90 compared to 2013–17. In contrast, R.

sarba, E. machnata and Aptychotrema vincentiana were more abundant in 2013–17 than

in 1989–90. Additionally, Pseudorhombus jenynsii, A. forsteri and S. bassensis and

Gonorynchus greyi were relatively abundant in at least one region in 1989–90, but were

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not recorded at all in 2013–17, whilst the opposite was true for S. schomburgkii, H.

melanochir and Trachurus novaezelandiae.

Significant period differences were also detected by PERMANOVA in estuarine usage,

feeding mode and habitat guild composition, and also the region × period interaction for

the latter variable, which was the most influential term (Appendix 4.7). Plots of the

proportions of each guild type in 1989–90 and 2013–17 reveal that, in the case of

estuarine usage, estuarine & marine species have declined over time, while marine

estuarine-opportunist and solely estuarine species have increased (Fig. 4.11a). Among

feeding mode guilds, piscivores, opportunists and zooplanktivores were more abundant

in 2013–17, while the proportion of detritivores, omnivores and zoobenthivores declined

(Fig. 4.11b). Demersal fishes comprised a considerably lower proportion of the offshore

assemblage in 2013–17 than 1989–90 in all regions except the WI (Fig. 4.11c), while that

of pelagic fishes increased considerably in the LN and UN (Fig. 4.11c). Bentho-pelagic

species decreased in abundance over time in the LN, but became slightly more abundant

in the UN and WI, and even more so in the FR where they comprised c. 75% of catches

during 2013–17.

Figure 4.9 (a) Average taxonomic distinctness (∆+) of the fish fauna in the offshore

waters of each region of the Walpole–Nornalup Estuary during 1989–90 (open symbols)

and 2013–17 (closed symbols). Contours represent limits within which 95% of simulated

∆+ values lie, and dashed lines indicate mean ∆+. (b) nMDS ordination plot constructed

from the (Bray-Curtis) bootstrapped averages of offshore species composition in each

region of the estuary during 1989–90 and 2013–17. Shaded areas represent approximate

95% confidence boundaries and trajectories show temporal order of sampling. Regions;

Frankland River (), Walpole Inlet (◆), Upper Nornalup (◼), Lower Nornalup ().

2D Stress: 0.19

1989–90

2013–17 (a) (b)

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Figure 4.10 Shade plot of the pre-treated abundances of fish species recorded in the

offshore waters of each region of the Walpole-Nornalup Estuary during 1989–90 and

2013–17, with shading intensity being proportional to abundance. Only species are

ordered by a hierarchical cluster analysis of their mutual associations across groups.

Dashed lines in the dendrogram indicate species with significantly similar patterns of

abundance, as detected by SIMPROF.

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Figure 4.11 Proportions of each (a) estuarine usage guild and (b) feeding mode guild

recorded in the offshore waters during 1989–90 and 2013–17. (c) Proportions of each

habitat guild recorded in each region during 1989–90 and 2013–17. Regions; Lower

Nornalup (LN), Upper Nornalup (UN), Walpole Inlet (WI) and Frankland River (FR).

See Table 4.4 for guild abbreviations.

Relationships between fish species composition and environmental variables

Alignment in the patterns of fish species abundances and those of water quality variables

(i.e. salinity and/or temperature) were tested using BIOENV and DistLM. Correlations

were generally weak to moderate and significant only for nearshore waters in certain

regions and seasons.

In the UN, a significant correlation between both salinity and temperature and nearshore

fish faunal composition was detected by both BIOENV (P = 0.01) and DistLM (P =

0.011), although this provided only a weak fit in both tests, indicated by a Spearman rank

correlation (ρ) of 0.257 and an R2 of 0.23, respectively. nMDS and distance based

redundancy (dbRDA) plots (not shown) indicate that differences in fish composition were

(a)

1989–90 | 2013–17

1989–90 2013–17 1989–90 2013–17

1.00

0.75

0.50

0.25

0.00

(c)

(b)

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due to lower salinities and/or temperatures during one or more seasons in 1989–90 than

2014–16. No significant pattern was detected in the LN or WI.

Within particular seasons, BIOENV detected a moderate correlation between salinity and

nearshore species composition in autumn (P = 0.04, ρ = 0.415) and winter (P = 0.04, ρ =

0.29), but not summer or spring. DistLM similarly detected a significant correlation

between fish faunal composition and salinity in winter (P = 0.006; R2 = 0.21), and also

summer (P = 0.042, R2 = 0.17), but not in autumn or spring. Examination of

corresponding nMDS and dbRDA plots (not shown) revealed that again these patterns

among fish fauna reflected the generally less saline conditions in one or more regions

during 1989–90 than 2014–16.

4.3.3 Interdecadal changes in ecosystem health

In the nearshore waters, mean FCI scores were considerably higher during the

contemporary period than historically in the WI and especially LN (Fig. 4.12a). Within

the LN, scores improved from 39 (grade E) during 1989–90 to 56 (D/C) during 2014–16,

while in the WI scores increased from c. 54 (D) to 68 (B). In contrast, mean scores in the

UN were lower during the later than earlier period (i.e. 56 vs 64, corresponding to a fall

in grade from C/B to D/C; Fig. 4.12a). Within individual seasons, mean scores improved

during summer from 58 (C/D) to 69 (B), and in autumn from 42 to 58 (E to C/D grade),

while little change occurred between periods during winter and spring (Fig. 4.12b).

Shade plots constructed from the component metric scores revealed that the notably

higher mean values for the FCI in the LN and WI during 2014–16 than 1989–90 were

mainly due to increases in the total number of species, number of trophic specialist species

and number of benthic species, and decreases in the proportion of detritivores (the latter

being a negative metric with an inverse relationship to ecosystem condition; Fig. 4.13).

In the UN, where a slight decline in ecosystem health occurred over time, marginally

lower scores during 2014–16 than 1989–90 were recorded for the number of generalist

species, proportion of detritivores and proportion of benthic species and proportion of

estuarine species (Fig. 4.13a). During summer the greatest increases between 1989–90

and 2014–16 occurred among the total number of species, number of benthic species, and

number of trophic specialists, while in autumn metric scores increased for the proportion

of estuarine individuals, proportion of detritivores and total number of species. Across all

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samples from 2014–16 no P. olorum were recorded, which produced high scores (i.e. 10)

for these two metrics.

When applied to data from the offshore waters, the FCI scored the LN, UN and FR

considerably lower during the contemporary period than historically (i.e. means of 57–77

vs 26–43), resulting in a drop in grades from A, B or C, to D or E (Fig. 4.14a). Similarly,

average scores during each season (across all regions) were markedly lower during 2013–

17 than in 1989–90 (21–47 vs 56–65; Fig. 4.14b), with the greatest decline occurring

during autumn where grades fell from B/C to E. The metrics most contributing to the

above declines were the total number of species recorded, number of trophic specialists

and Shannon Weiner diversity (Fig. 4.15). Negligible differences in FCI scores occurred

between periods in the offshore waters of the WI (Fig. 4.14a).

Across the estuary as a whole (i.e. all regions and seasons combined), the mean nearshore

FCI score increased slightly between decadal periods from c. 56 to 60, marginally

increasing the corresponding grade from a C/D to a C (Fig. 4.16). In contrast, the mean

offshore FCI score was substantially higher historically than during the contemporary

sampling period (62 vs 39), with ecological condition falling from a grade B to D over

time (Fig. 4.16).

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Figure 4.12 Mean (±SE) Fish Community Index (FCI) scores and grades (shading)

recorded in the nearshore waters of the Walpole-Nornalup Estuary during the historical

(1989–90) and contemporary (2014‒16) sampling periods within (a) each region and (b)

each season.

Figure 4.13 Average scores of each FCI metric recorded throughout the nearshore waters

of the Walpole-Nornalup Estuary during the historical (1989–90) and contemporary

(2014‒16) sampling periods within (a) each region and (b) each season. See Table 4.2 for

full metric names.

(a)

(b)

1989–90 2014–16

A

B

C

D

E

Gra

de

(b) (a)

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Figure 4.14 Mean (±SE) Fish Community Index (FCI) scores and grades (shading)

recorded in the offshore waters of the Walpole-Nornalup Estuary during the historical

(1989–90) and contemporary (2013‒17) sampling periods within (a) each region and (b)

each season.

Figure 4.15 Average scores of each FCI metric recorded throughout the offshore waters

of the Walpole-Nornalup Estuary during the historical (1989–90) and contemporary

(2013‒17) sampling periods within (a) each region and (b) each season. See Table 4.2 for

full metric names.

(a) (b)

A

B

C

D

E

Gra

de

(a)

(b)

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Figure 4.16 Mean (±SE) Fish Community Index (FCI) scores recorded in each the

nearshore and offshore waters of the Walpole-Nornalup Estuary across all regions and

seasons during the historical (1989–90) and contemporary (2014–16/2013–17) sampling

periods.

4.3.4 Interdecadal changes in the length composition of fishery important species

Marked changes in the length composition of A. butcheri, A. georgianus and S. punctatus

occurred between the historical (1989–96) and contemporary (2013–16) periods

examined in this study. With respect to A. butcheri, while a slight increase in the modal

length of the population occurred between decadal periods (i.e. 170‒190 vs 210‒230 mm

TL), notably fewer fish above the minimum legal length for capture and retention (MLL;

250 mm) were present during 2013‒16 (Fig. 4.17a). Moreover, a 100 mm decrease in

maximum length class occurred over time, from 410–430 mm during 1989–96 to only

310–330 mm in 2013–16. In addition, proportionally fewer small individuals (i.e. <170

mm TL) were recorded during the later than earlier period (Fig. 4.17a).

Kernel density estimates (KDEs) of the length data for A. butcheri were used to test for

differences in size composition between periods. significant differences in size

distribution occurred in both the nearshore and offshore waters between 1989–96 and

2013–16 (P < 0.001; Fig. 4.17b,c). In the former shallower waters a clear increase in

modal size occurred over time from c. 100–130 mm during 1989–90 to 200–230 mm in

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2013–16 (Fig. 4.17b), with the shape of the distribution changing from right-skewed (i.e.

small fish most abundant) to left-skewed (i.e. large fish were most abundant). In the

offshore waters changes in modal size were less marked, although the length distribution

of fish from 2013–16 was clearly truncated above the mode, and significantly fewer

individuals at all lengths above c. 290 mm were recorded than in 1989–90 (Fig. 4.17c).

Among A. georgianus the modal length class has declined from 240–250 mm during

1989‒90 to 220–230 mm in 2013‒16 (Fig. 4.18a), although the shape of the distribution

has not notably changed. A KDE comparison test revealed significant differences in the

length distribution of this species between periods (P < 0.001), with fewer fish between

240 and 290 mm TL recorded during 2013–16 than 1989–90, while the reverse was true

among fish 170–230 mm TL (Fig. 4.18b). Very few individuals <150 mm were recorded

during either period.

With respect to the sillaginid S. punctatus, a clear shift in the shape of the length

distribution occurred over time, with small fish far more abundant during 2013–16 than

in 1989–90, while the reverse was true for larger individuals (Fig. 4.19). Notably, most

fish recorded during 1989–90 were 200‒400 mm, while during 2013–16 almost all were

<200 mm with only a very small proportion above the MLL of 280 mm (Fig. 4.19a). As

occurred among A. butcheri and A. georgianus, the KDEs of the length distributions of S.

punctatus were significantly different between periods (P < 0.001; Fig. 4.19b).

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Figure 4.17 (a) Length-frequency (total length; TL) plots of Acanthopagrus butcheri from

both the nearshore and offshore waters of the Walpole-Nornalup Estuary during the

historical (1989–96) and contemporary (2013–16) sampling periods. (b) kernel density

estimates (KDEs) of the lengths of A. butcheri caught in the nearshore waters and (c) the

offshore waters during each period. Light blue shaded area represents the null model of

the average length-distribution from both periods (±SE), and indicates no significant

difference in density. Dashed vertical lines indicate the minimum legal length for capture

and retention of this species in Western Australia.

1989–96 n = 651

2013–16 n = 457

1989–96 n = 225

2013–16 n = 88

1989–96 n = 607

2013–16 n = 369

(a)

Total Length (mm)

(b)

(c)

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Figure 4.18 (a) Length-frequency (total length; TL) plots and (b) kernel density estimates

(KDEs) of Arripis georgianus recorded during the historical (1989–90) and contemporary

(2013–16) sampling periods. Light blue shaded area represents the null model of the

average length-distribution from both periods (±SE), and indicates no significant

difference in density.

(a)

1989–90 n = 218

(b)

1989–90 n = 218

2013–16 n = 190

2013–16 n = 190

Total length (mm)

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Figure 4.19 (a) Length-frequency (total length; TL) plots and (b) kernel density estimates

(KDEs) of Sillaginodes punctatus recorded during the historical (1989–90) and

contemporary (2013–16) sampling periods. Light blue shaded area represents the null

model of the average length-distribution from both periods (±SE), and indicates no

significant difference in density. Dashed vertical line indicates the minimum legal length

for capture and retention of this species in Western Australia.

1989–90 n = 81

2013–16 n = 131

Total length (mm)

1989–90 n = 81

2013–16 n = 131

(a)

(b)

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4.4 DISCUSSION

4.4.1 Has marinisation and tropicalisation of the Walpole-Nornalup Estuary occurred since the early 1990s?

This study has demonstrated significant changes in the fish faunal composition and

abiotic environment of the Walpole-Nornalup Estuary over the past two and half decades,

including several that are consistent with climate change effects in SWA over this period.

These include an overall marinisation and tropicalisation of the fish fauna, as well as

corresponding increases in both temperature (mean values up to 5 °C warmer in winter,

spring and summer) and salinity (up to seven-fold higher in winter and spring) of the

system from 1989–90 to 2013–17. In agreement with the first hypothesis posed in this

study, significantly greater contributions of various warm-temperate, tropical and/or

marine species (e.g. Rhabdosargus sarba, Arripis truttaceus, Engraulis australis,

Aptychotrema vincentiana and Elops machnata), as well as lower contributions of species

with freshwater affinities (e.g. Mugil cephalus, Pseudogobius olorum and Leptatherina

wallacei), were generally recorded in the later than earlier period. Additionally, the

presence of numerous additional marine species in the shallows during the contemporary

period, including Sillago schomburgkii, S. burrus, Pelates octolineatus and

Hyporhamphus melanochir, resulted in a substantial increase in total species richness

from 11 to 26 species. This work is the first to examine such longer-term changes in the

fish and environmental characteristics of a south-coast WA estuary, although similar

changes have been observed over the last two to three decades in permanently-open

estuaries on the lower-west coast of WA. These include a greater prevalence of marine

species and a reduced contribution of freshwater-affiliated species in the Swan-Canning

(Valesini et al., 2017) and Peel-Harvey (Potter et al., 2016) estuaries, as well as increasing

abundances of (sub)tropical species through southward range extensions in the

Leschenault Estuary (Veale et al., 2014). Globally, similar trends have also been

documented during recent years in temperate estuaries of South Africa (James et al.,

2008b; James et al., 2013; Whitfield et al., 2016) and Europe (Pasquaud et al., 2012;

Baptista et al., 2015).

The predominant warming and marinisation of the Walpole-Nornalup Estuary since 1990

is almost certainly linked to broader-scale climate change impacts throughout SWA

(Barron et al., 2012; Silberstein et al., 2012). In addition to reductions in river flow and

increasing air temperatures, sea surface temperatures of SWA have also been warming at

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an unprecedented rate (Pearce & Feng, 2007; Hope et al., 2015; BoM & CSIRO, 2016).

Most notably, a severe marine heatwave in 2011 (Pearce & Feng, 2013) resulted in

widespread southwards range extensions of many species in the coastal environment (e.g.

Hyndes et al., 2016; Wernberg et al., 2016). It is thus noteworthy that in the present study,

several warm temperate or subtropical marine species (e.g. R. sarba, S. schomburgkii, E.

machnata and S. burrus; Ayvazian & Hyndes, 1995; Potter & Hyndes, 1999; Harrison &

Whitfield, 2006c), which were not recorded in Walpole-Nornalup during 1989–90 or

were found only in low numbers, comprised a substantial part of the catches during 2013–

17, suggesting that similar range extensions have occurred.

Providing further support to the fish faunal-environmental change relationships outlined

above, BIOENV and DistLM tests demonstrated that interdecadal shifts in fish species

composition in the nearshore waters were significantly related to those of salinity and/or

temperature in one or more seasons or regions. The strength of these relationships was,

however, only moderate to weak, which appears to largely reflect seasonal and regional

variability masking interdecadal changes. Ideally, these tests would have been undertaken

within each level of region and season, but given the low number of historical samples

available this was not possible.

Although warming and marinisation have clearly made the Walpole-Nornalup more

favourable for many marine species, there were also notable decreases in the abundances

of several species since the 1990s. These include the gobiid Favonigobius lateralis, which

parallels similar abundance declines over the past two to three decades in estuaries on the

lower west coast of WA (Veale et al., 2014; Valesini et al., 2017). Recruitment of this

species has been shown to be inhibited by water temperatures above 25 °C (Wise, 2005),

and given that nearshore water temperatures in the Walpole-Nornalup were often higher

than this in the mid-2010s (and reaching 32 °C on some occasions; data not shown), it is

possible that these findings reflect an exceedance of the thermal tolerance of this species.

Similarly, two marine estuarine-opportunist mullet (Mugilidae) species, i.e. Aldrichetta

forsteri and M. cephalus, were abundant in the offshore waters during the earlier sampling

period, but largely absent in 2013–17. James et al. (2016) have suggested that members

of Mugilidae may be among the first species to respond to climate changes as patterns in

their distribution and abundance closely reflect water temperature. Thus, while A. forsteri

and M. cephalus can tolerate temperatures up to 33 °C (Chubb et al., 1981; Whitfield et

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al., 2012b), both appear to have a far lower optimal maximum and have been documented

to avoid waters which exceed 20–27 °C (Chubb et al., 1981; Jones et al., 1996; Lan et

al., 2014). It has also been proposed that fresh or oligohaline waters provide optimal

conditions for growth of M. cephalus (Cardona, 2006; Whitfield et al., 2012b). As the

Walpole-Nornalup has become both warmer and more marine during recent years, larger

and more mobile individuals of these mullet species may be emigrating to more

favourable habitats, and thus, their abundances in gill net catches declined. In the case of

A. forsteri this would likely be to cooler marine waters, given the affinity of this species

for the marine environment (Chubb et al., 1981). While this may also be the case among

M. cephalus, concurrent sampling in the upper reaches of the Frankland River (3–5 km

upstream of the sites sampled for this Chapter) during 2013–17 resulted in regular catches

of this species, indicating that an upstream distribution shift has occurred.

4.4.2 Has the ecological health of the Walpole-Nornalup Estuary declined over the past 25 years?

Support for hypothesis two, namely that the ecological health of the Walpole-Nornalup

Estuary has declined from the early 1990s to mid-2010s, was mixed. Thus, while the Fish

Community Index (FCI) exhibited a substantial decrease over time in the offshore waters,

it increased in the shallows. The former trend was largely attributable to reductions in

species richness, Shannon-Weiner Diversity, the number of trophic specialists and

proportion of benthic individuals, the latter of which included several large species such

as Cnidoglanis macrocephalus, Pseudorhombus jenynsii, Mustelus australis,

Platycephalus speculator and S. bassensis. Further supporting these declines detected by

the FCI, mean taxonomic distinctness also showed a pronounced drop over time (i.e. 78.7

vs 43), highlighting a reduction in biodiversity of the deeper waters. In contrast, the

apparent increase in nearshore health reflected generally higher abundances, species

richness and trophic diversity recorded during the contemporary period, mostly attributed

to an influx of marine species as described in the previous section.

As the Walpole-Nornalup is surrounded by national parks and has not been extensively

urbanised (DEC, 2009), it is probable that the observed declines in ecosystem health of

the offshore waters largely reflect the effects of climate changes, and particularly reduced

flows. The degree to which estuaries are vulnerable to degradation from water quality

problems is heavily influenced by their rate of water and particulate exchange with the

ocean (Huang et al., 2011; Tweedley et al., 2016b). Under reduced river flow conditions,

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flushing is decreased and deposited nutrients and organic material are retained for longer,

effects which are particularly pertinent in microtidal systems which also received limited

tidal flushing (Tweedley et al., 2016b). Higher accumulations of organic material lead to

increased levels of bacterial decomposition and biological oxygen demand, which can

result in hypoxia and anoxia in the benthic zone (Pihl et al., 1991; Tyler et al., 2009).

Aside from causing mortality of fishes through suffocation, these conditions can

adversely affect growth and maturity rates (Whitfield, 1995; Pichavant et al., 2001; Small

et al., 2014; Hrycik et al., 2017), and can reduce food quality for demersal fishes through

declines in benthic macroinvertebrate abundances (Pihl, 1994; Powers et al., 2005;

Switzer et al., 2009). Similar declines in flows over the past two to three decades in the

Swan-Canning Estuary on the lower west coast of WA have induced prolonged and

widespread hypoxia (i.e. <2–3 mgL−1 dissolved oxygen) in the deeper waters of that

system (Cottingham et al., 2014; Tweedley et al., 2016a; Valesini et al., 2017;

Cottingham et al., 2018a). This has been linked with declining abundances of several

large benthic species (e.g. C. macrocephalus and the platycephalid P. westraliae; Valesini

et al., 2017), as well as the onshore movement of Acanthopagrus butcheri from deeper

waters to nearshore refuge areas (Cottingham et al., 2014; 2018a). Among the latter

sparid, a species of particular importance to recreational fisheries, reduced growth rates

and a decline in body condition also occurred over time, which is discussed in subsection

4.4.3 below.

Although in the Walpole-Nornalup hypoxic conditions were only occasionally recorded

in the water column (see Chapter 2), it is probable that the FCI has responded to longer

term environmental trends not detected through spot water quality measurements (Karr,

1993). Extensive diving while undertaking work for Chapter 5 revealed that the benthic

habitat of the deeper (2–4 m deep) waters was largely silt/mud which was anoxic below

a few millimetres, with little coarse sediment or vegetation evident. Such depauperate

habitat would clearly be unproductive and unfavourable for benthic associated fishes, as

was shown by the low offshore FCI scores. While limited historical data of benthic

condition and oxygen concentration from the system exist for comparison, the similarity

of observed trends with those in Swan-Canning, and evidence of increasing hypoxia in

the deeper waters of a nearby south-coast estuary (the Blackwood/Hardy; Brearley,

2013), provide strong circumstantial evidence that the offshore benthic habitat of the

Walpole-Nornalup may have declined over time. Providing further support, the only

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offshore region which did not decrease in ecological health was the shallow (c. 1 m deep)

Walpole Inlet, where benthic degradation from low oxygen would be far less likely due

to greater wind driven mixing (Diaz & Rosenberg, 1995; Kurup & Hamilton, 2002).

In addition to the likely effects that the above environmental changes have had on the fish

fauna and ecosystem health of the Walpole-Nornalup, it is also possible that the decadal

shifts in the offshore FCI scores were influenced by differences in sampling methodology

and gear efficiency between the two periods. Firstly, under the reduced flow conditions

of the contemporary period, turbidity may have been lower than historically, thus making

gill nets more visible and less efficient (Jester, 1977; Wardle et al., 1991), which may

have contributed to lower catch rates among several species. Furthermore, while fish

sampling in these waters during 1989–90 was undertaken using overnight gill net sets,

only one hour set times were permissible in the contemporary period to minimise fish

mortality and non-fish bycatch. This does, however, present several comparability issues.

As larger predatory fish and scavengers (e.g. elasmobranchs) are attracted to smaller fish

in gill nets and consequently become tangled (Engås et al., 2000), overnight sets will be

more likely to catch a higher proportion of those species. Additionally, longer set times

will naturally result in greater species richness and diversity; metrics employed by the

FCI which cannot be practically standardised for lower effort. However, evidence

obtained from a sampling opportunity in autumn 2017, which enabled the comparison of

fish catches from gill nets set overnight vs for one hour throughout the Walpole-Nornalup,

showed that at a broader regional level species composition was quite similar between

the two set times (data not shown). Moreover, when catches from overnight sets in

autumn 2017 were compared to those in the same season in 1989‒90, clear decreases in

abundance and species richness were observed (i.e. means of 11 ± 2 vs 52 ± 5 individuals

and 4 ± 0.8 vs 8 ± 1.2 species, respectively), as well as a considerable change in species

composition (Fig. 4.20). Several species, including the benthic associated C.

macrocephalus, P. speculator, Myliobatis tenuicaudatus and Sillaginodes punctatus,

were clearly less abundant in 2017 than 1989‒90, reflecting the same observations as

described above from the one hour set times. Thus, while unavoidably lower values of

certain metrics in the later period may have exaggerated the magnitude of degradation

detected by the FCI, these more recent findings validate that the observed decadal shifts

in fish composition and ecological health are not simply an artefact of sampling

differences.

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It should also be noted that the nearshore waters were sampled identically during both

periods and clear increases in fish abundances, diversity and FCI scores occurred over

time. As the deeper offshore waters of the system have degraded, fishes may be

increasingly using shallow and well-oxygenated nearshore habitats as refuges (Pihl et al.,

1991; Crowder & Eby, 2002; Bell & Eggleston, 2005). Thus, observed interdecadal

increases in nearshore ecosystem health could be considered to reflect the cumulative

effects of both an overall increase in diversity due to marinisation, and an inshore

movement of fishes from deep to shallower waters.

Figure 4.20 Shade plot of the (square-root transformed) abundances of each fish species

in catches from gill nets set overnight in the offshore waters of each region of the

Walpole-Nornalup Estuary during autumn in 1990 and 2017.

4.4.3 Have changes in the abundance and population size structure of key fishery species occurred since the 1990s?

The vast majority (c. 70%) of species recorded within the Walpole-Nornalup Estuary are

of commercial and/or recreational fishery importance. As outlined in preceding sections,

several of these species have increased in abundance since the early 1990s (e.g. R. sarba,

S. schomburgkii and E. australis), while several others have declined (e.g. C.

macrocephalus, P. speculator, P. jenynsii and M. cephalus). In agreement with

hypothesis three, populations of A. butcheri, S. punctatus and A. georgianus, the three

species contributing the most to fishery harvest from the system (Smallwood & Sumner,

2007), contained notably fewer larger fish in the later than earlier period. While the

probable drivers of these size shifts vary among species (see below), most are related

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more generally to climate change effects over recent decades, as well as fishing mortality

in the case of A. butcheri and A. georgianus.

Acanthopagrus butcheri is among the most retained estuarine species by recreational

fishers Australia-wide (Henry & Lyle, 2003; Ryan et al., 2015), and is the only solely

estuarine species commonly targeted in the Walpole-Nornalup (Smallwood & Sumner,

2007). Indeed, the latter authors showed that the recreational harvest of A. butcheri in the

Walpole-Nornalup was more than five-fold that of any other south-coast WA estuary (i.e.

14.8 vs <2.8 tonnes) and comparable to that of the far larger Swan-Canning Estuary on

the State’s lower-west coast (i.e. 16 tonnes; Smith, 2006). Comparison of the length

composition of this species between 1989–90 and 2013–17 revealed a substantial decline

in the proportion of large fish in the system. Furthermore, most individuals during the

contemporary period were just under the state minimum legal length (MLL) of 250 mm,

which could be reflective of high fishing mortality (Arlinghaus et al., 2010; Gwinn et al.,

2015). A similar decline in the prevalence of larger fish has also been recorded in the

recreational fisher catch, with a creel survey undertaken during 2002‒03 showing that the

average length of retained A. butcheri was 308 mm TL (Smallwood & Sumner, 2007),

whereas that in surveys conducted during 2013–16 was only 276 mm (Department of

Biodiversity, Conservation and Attractions WA; DBCA, unpubl. data). Moreover, during

the latter period, 85% of A. butcheri caught by recreational fishers were released due to

them being under MLL (DBCA, unpubl. data), compared to only 54% during 2002/03

(Smallwood & Sumner, 2007).

A concurrent tagging study of this species (Chapter 5) provides additional evidence of

high fishing mortality on A. butcheri above the MLL in the Walpole-Nornalup. Five of

the 23 individuals (c. 22%) that were tagged within the system were confirmed caught by

recreational anglers between July 2014 and August 2016, which is far higher than the

recapture rate of this species in the same period in two highly-populated and heavily

fished SWA estuaries, namely the Swan-Canning (2.4%) and Peel-Harvey (5.8%;

Murdoch University, unpubl. data). Visual inspection of the tracking data for A. butcheri

in the Walpole-Nornalup also indicates that a further four fish are likely to have been

caught but not reported, resulting in c. 39% of tagged fish being captured by recreational

anglers.

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Compounding the above fishing pressures, recent findings by Cottingham et al. (2018b)

reveal a marked decline in the growth rate and body condition of A. butcheri in the system

between the early 1990s and 2013–15. Thus, to reach MLL males and females of this

species now take 15.5 and 17.7 years, respectively, compared to only 6.2–6.6 years

previously (Cottingham et al., 2018b). Aside from the above-described climate change

effects on water and sediment quality and food availability in the system, it is also

possible that temperate estuarine species such as A. butcheri are under added competition

for resources from the increased abundance of numerous marine species in the system

over the past 25 years, which could contribute to its poorer growth performance (Byström

et al., 1998; Fullerton et al., 2000). This decline, in combination with a doubling of

recreational fishing effort state-wide since 1990 (Ryan et al., 2015), suggests that

management interventions are required to ensure the sustainability of this fishery.

With respect to changes in the size composition of S. punctatus, the far smaller modal

length during 2014–16 clearly reflects the increased abundances of juveniles <150 mm

TL, which are in their first year of life and utilise the shallow waters of estuaries and

sheltered coastal areas as nurseries (Hyndes et al., 1998). After attaining c. 250 mm TL

and 1.5 years of age, fish then move into slightly deeper (2–4 m) waters where they remain

until they reach c. 370 mm TL and 2.5 years, before migrating to offshore reefs as they

approach maturity (Hyndes et al., 1998; Fowler et al., 2002). While larger fish (i.e. 250–

370 mm TL) were abundant in the Walpole-Nornalup during 1989–90, they were almost

absent from catches during 2013–17. Again, this may reflect a decline in the condition of

deeper offshore habitats within the system, and also, the significant warming of those

waters from 1989–90 to 2014–16 (e.g. an increase in mean summer temperatures from c.

22 to 24 °C), given that the thermal tolerance of S. punctatus decreases with age. Thus,

Meakin et al. (2014) demonstrated that while fish less than a year old could withstand

temperatures of up to 30 °C, larger three-year old fish exhibited stress at 24 °C, and

suffered 50% mortality at 30 °C. Moreover, the optimum temperatures for the

development of juvenile S. punctatus is 22–26 °C (Jones et al., 1996; Ham & Hutchinson,

2003), and average nearshore water temperatures within the estuary now range from c.

22–24.5 °C during spring and summer when the new recruits arrive, compared to only

17–22.5 °C during 1989–90. Warming of these shallow waters, combined with the

increase in salinity of the estuary over the past two decades, has thus apparently led to a

more favourable nursery environment for the juveniles of this species.

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In contrast to the interdecadal changes in the size composition of A. butcheri and S.

punctatus, the observed declines in the modal length of A. georgianus, a highly migratory

species comprising a single stock throughout Australia (Ayvazian et al., 2004), are likely

to reflect broader-scale stock issues rather than local environmental and/or fishing

pressures in the Walpole-Nornalup. A recent stock assessment of this species (Smith &

Brown, 2014) has shown declines in both the age and size composition of this species

throughout south-western Australia, which has been linked to both climate-related

impacts on spawning success and high fishing mortality state-wide.

4.4.4 Summary, implications and recommendations

Several of the observed changes in the environmental and fish faunal characteristics of

the Walpole-Nornalup Estuary over the past 25 years are likely to reflect the broader-

scale influences of climate change occurring throughout south-western Australia, which

are conceptualised below in Figure 4.21.

Figure 4.21 Conceptual diagram of climate-related changes in the environment and fish

fauna of the Walpole-Nornalup Estuary between the early 1990s and mid-2010s.

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Estuaries in this region are becoming warmer and, in the case of those with a regular

connection to the sea, more marine. These conditions provide favourable environments

for temperate to tropical marine species, which are increasingly utilising estuaries as

observed in the present study and several others on the lower-west coast of WA (e.g.

Veale et al., 2014; Potter et al., 2016; Valesini et al. 2017). As discussed in Chapter 2,

estuaries are well recognised for their nursery role in supporting marine species and

fisheries. Increased utilisation of the Walpole-Nornalup by juveniles of numerous key

fishery species (e.g. S. punctatus, A. truttaceus) may have direct benefits to sustaining

regional fisheries, particularly given the exposed and thus unfavourable nursery habitat

provided by coastal waters of the region (Ayvazian & Hyndes, 1995). Moreover, given

that very few solely estuarine species in south-western Australia are targeted by fishers

(Lenanton & Potter, 1987), marinisation may also enhance local recreational fishing

within systems due to greater abundances of marine species that are also present as adults

(e.g. R. sabra, E. machnata, S. schomburgkii).

However, such increased colonisation by marine species can also place estuarine resident

species under increased stress through competition for resources where there is niche

overlap. As both sea surface and air temperatures rise, species with low thermal tolerances

must move southward, although the potential for this is limited for coastal species on the

south coast of WA, given that only oceanic waters lie further south. Degradation of deeper

benthic habitats in estuaries resulting from warmer waters and reduced river flushing may

also lead to fish mortality or detrimental changes in their growth and reproductive

capacity. In the Walpole-Nornalup, decreased abundances of numerous benthic species

and a decline in offshore ecosystem health have coincided with rapid warming and a

halving of freshwater flow since the early 1990s. Additionally, there is substantial

evidence that the impacts of recreational fishing, exacerbated by climate change effects

on growth, have caused changes in the size structure of the highly targeted A. butcheri.

Obtaining recreational catch and effort data is often challenging and costly (Post et al.,

2002; McCluskey & Lewison, 2008; Ryan et al., 2015), and thus, a lack of information

exists for many fisheries globally (McPhee et al., 2002; Cooke & Cowx, 2004; Beckley

& Ayvazian, 2007; Cowley et al., 2013). The observed population changes among A.

butcheri in the present study highlight a clear need to quantify the distribution and

intensity of recreational fishing activity, particularly in areas where targeted species may

be under increasing stress from external environmental influences.

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Finally, the comparability issues encountered when assessing long-term changes in the

ecological health of the offshore waters highlight the importance of standardising future

monitoring regimes for not only the Walpole-Nornalup, but also other estuaries state- and

nation-wide.

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Chapter 5: Residency and movement patterns of four key fishery species in the Walpole-Nornalup Estuary

5.1 INTRODUCTION

Estuaries provide highly productive and diverse habitats that support rapid growth and

development of not only estuarine-spawned species, but also species from marine and

freshwater environments (Whitfield, 1994; Elliott et al., 2007; Potter et al., 2015a). In

particular, estuaries are well recognised as nurseries for juveniles of marine species

(Blaber & Blaber, 1980; Beck et al., 2001; Sheaves et al., 2015) and have been shown to

be directly support major coastal fisheries (Gillanders, 2002; Gillanders et al., 2003; Able,

2005; Vasconcelos et al., 2008). Estuarine dependency among marine species, however,

is highly variable and ranges from opportunistic to obligatory (Whitfield, 1994; Elliott et

al., 2007; Potter et al., 2015a). As dynamic and spatially heterogeneous environments,

the suitability of estuarine habitats for both marine and solely estuarine species also

changes over space and time. For example, in temperate estuaries freshwater flows during

winter typically cause emigration of marine species and downstream shifts in estuarine

and freshwater-associated species (Marshall & Elliott, 1998; Kanandjembo et al., 2001;

Hagan & Able, 2003; Maes et al., 2004). Conversely, protracted drought may increase

estuarine salinities, resulting in greater colonisation by marine species and an upstream

shift in the distribution of many fish species (Martinho et al., 2007; Pasquaud et al., 2012;

González-Ortegón et al., 2015).

For fisheries managers, knowledge of the timing, duration and location of estuarine

habitation by targeted species is fundamental to understanding their estuarine dependence

and, in turn, developing appropriate management strategies (Able, 2005). At a fine scale,

the intra-estuarine distribution of fishes closely reflects food and habitat availability

(Thiel et al., 1995; Akin et al., 2005; Whitfield, 2017), knowledge of which can thus

identify areas of greatest importance to sustaining populations. Moreover, quantitative

data on how fish distribution may change temporally during different life stages and/or

in response to forcing environmental variables (e.g. salinity, temperature, dissolved

oxygen, tidal flow), is paramount to understanding ecosystem structure and function and

can provide insight as to how fish stocks may be affected by climate changes (Izzo et al.,

2016; Williams et al., 2017).

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Over the past two decades passive acoustic telemetry, whereby fixed hydrophones or

acoustic receivers are deployed to detect aquatic animals tagged with battery-powered

transmitters, has become an increasingly utilised tool in fisheries research (Heupel et al.,

2006; Hussey et al., 2015; Crossin et al., 2017; Taylor et al., 2017). This technology

allows fishes to be tracked for periods of months to years, over spatial scales ranging from

metres to 1000s of kilometres. Compared to the use of nets or other traditional fish

sampling techniques, acoustic telemetry is generally less labour intensive and destructive,

and importantly, allows far greater spatial and temporal continuity (Heupel et al., 2006;

Crossin et al., 2017; Taylor et al., 2017). Acoustic telemetry thus has a broad range of

applications for understanding how fish use estuaries during different life phases or

activities, their habitat preferences and responses to environmental changes.

Acoustic receivers can be deployed as ‘gates’ at estuary mouths to quantify estuarine-

marine connectivity by recording the timing, frequency and duration of fish immigration

or emigration (Cowley et al., 2008; Able et al., 2014; Harasti et al., 2017). They can also

be deployed in systematic arrangements within estuaries to examine finer-scale habitat

preferences and space use (Grothues & Able, 2007; Espinoza et al., 2011a; Grant et al.,

2017b), seasonal patterns in movement and direct responses to environmental changes

such as freshwater flows, temperature, lunar cycles, tidal movements, or time of day

(Childs et al., 2008; Taylor et al., 2014; Payne et al., 2016; Grant et al., 2017a). This

information can be used in turn to identify when and where targeted species may be most

vulnerable to fishing activities (e.g. during spawning periods) and highlight priority areas

for conservation (Bennett et al., 2012; Francis, 2013; Childs et al., 2015). Moreover,

tracking multiple species simultaneously can reveal ecological interactions and niche

partitioning patterns (Le Pichon et al., 2017; Matich et al., 2017; Williams et al., 2017),

which, in turn, can feed into multispecies based fisheries models and support ecosystem

based fisheries management.

Despite the usefulness of acoustic telemetry and its expanding use in estuaries globally,

this technology has been vastly underutilised in south-western Australia (SWA). Thus,

while the estuarine fish faunas of the region have been extensively studied over the past

40 years (e.g. Chubb et al., 1979; Potter et al., 1990; Potter & Hyndes, 1999; Chuwen et

al., 2009; Valesini et al., 2017), no published studies employing acoustic telemetry exist.

As described above, use of this technology can greatly expand upon traditional

knowledge of how fish use the estuaries of the region, and moreover, address areas of

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research where data are lacking. For example, Potter et al. (2015a) emphasized a need to

better understand marine-estuarine connectivity among populations of estuarine & marine

species, which may complete their life cycle in either environment. In systems with high

levels of localised fishing activity, such as the Walpole-Nornalup Estuary (Smallwood &

Sumner, 2007), managers also require knowledge of the habitats and areas of the estuary

that are of greatest importance to targeted species (e.g. nursery, spawning and aggregation

sites; DEC, 2009). This information, encompassing estimates of activity, space use and

seasonal movement patterns, can identify the vulnerability of various species to localised

fishing activity. Given the unprecedented rate at which climate change is occurring in

SWA (see Chapter 4), predictions of how warmer and more marine conditions will

influence fish populations are also required. Specifically, improved knowledge of habitat

overlap between estuarine residents and marine spawning species, which will likely

become more abundant in estuaries under a drier climate (Hallett et al., 2018), can provide

insight into the potential resource competition that may occur into the future.

The overarching aim of this component of the study is to utilise passive acoustic telemetry

to examine and compare estuarine-ocean connectivity and intra-estuarine distributions of

four key fishery species within the permanently-open Walpole-Nornalup Estuary.

Namely, Black Bream Acanthopagrus butcheri, Southern Bluespotted Flathead

Platycephalus speculator, Snapper Chrysophrys auratus and Tarwhine Rhabdosargus

sarba. Acanthopagrus butcheri, as the most targeted species in the system (Smallwood &

Sumner, 2007), are of particular focus. Extensive biological studies in SWA (Sarre &

Potter, 1999; Cottingham et al., 2014; Cottingham et al., 2016) and acoustic tracking on

the east-coast of Australia (Hindell, 2007; Hindell et al., 2008; Sakabe & Lyle, 2010;

Williams et al., 2017) have shown that while individuals of this species rarely leave

estuaries, their distribution typically shifts upstream during spawning and also markedly

in response to environmental drivers (e.g. downstream following freshwater flows). In

contrast, P. speculator (Platycephalidae) is an estuarine & marine species (Hyndes et al.,

1992), but thought to be almost solely estuarine on the south-coast (Coulson et al., 2017),

while C. auratus and R. sarba are two marine-spawning sparids that are considered to use

estuaries opportunistically and mostly as nurseries (Gillanders, 2002; Radebe et al., 2002;

Hesp et al., 2004; Wakefield et al., 2011).

The specific aims of the present tracking study are as follows:

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1. Determine the (i) estuarine-ocean connectivity, (ii) intra-estuarine residency

patterns and (iii) level of movement throughout the system of each species, examining

any inter-specific differences and changes through time.

2. Investigate how the above patterns in fish distribution may be related to

environmental factors (e.g. salinity, water temperature, river flow, moon phase, tidal

amplitude), biological drivers (e.g. body size, reproductive phase) and or intra-estuarine

habitat features (e.g. depth, physical structure, substrate).

Given the findings of acoustic tracking on the east coast of Australia and traditional

biological studies in SWA, it is hypothesised that A. butcheri and P. speculator will not

leave the estuary, however, the marine estuarine-opportunists R. sarba and C. auratus are

predicted to migrate to sea, especially following substantial freshwater flows.

It is further hypothesised that A. butcheri will use vast areas of the system, moving

upstream during spring and early summer for spawning, and downstream in winter in

response to freshwater flows. In contrast, C. auratus, R. sarba and P. speculator will be

largely confined to the lower/middle estuary where salinities remain closer to marine.

Thus, it is also predicted that the greatest distribution overlap among all four study species

will occur in the Nornalup Inlet and lower Frankland River.

As a benthic ambush predator, it is hypothesised that P. speculator will be far less mobile

and show greater site attachment than the bentho-pelagic A. butcheri, C. auratus and R.

sarba.

5.2 METHODS

5.2.1 Acoustic array design

A fixed acoustic array of 17 VEMCO VR2W omni-directional acoustic receivers

(VEMCO; https://vemco.com/) was deployed throughout the Walpole-Nornalup Estuary

in July 2014 (Table 5.1; Fig. 5.1). The array was designed to maximise spatial coverage

of the estuary and encompass a variety of habitats. Additionally, paired stations were

deployed as ‘gates’ at the junctions of major estuarine regions (Walpole Inlet, Nornalup

Inlet and the Frankland River) and at the estuary mouth to detect movement between

regions and between the estuary and the sea, respectively. Range testing (see section

5.2.3) was undertaken at these stations to ensure receivers had adequate coverage of these

choke points even under poorest detection conditions.

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Table 5.1 Depth and habitat within detection range of each acoustic receiver station

deployed in the Walpole-Nornalup Estuary. Station locations are shown in Figure 5.1.

See section 5.2.4 for derivation of habitat characteristics. Regions; Upper Frankland River

(UFR), Lower Frankland River (LFR), Walpole Inlet (WI), Upper Nornalup (UN) and

Lower Nornalup (LN).

Figure 5.1 Location of acoustic receiver stations ( ) deployed in the Walpole-Nornalup

Estuary. See Table 5.1 for station characteristics.

Region Station name

Depth (m)

Habitat

UFR UFR1 0–4 Upper river; Mud substrate, extensive snags and fallen timber. UFR UFR2 0–4 Upper river; Mud substrate, extensive snags and fallen timber.

UFR UFR3 0–4 Upper river; Mud substrate, moderate quantity of snags; Boat ramp/jetty.

LFR LFR1 0–2 Lower river; Shallow mud flats, moderate quantity of snags and rocks.

LFR LFR2 0–6 Lower river; Sand/mud substrate, shallow flats and deep drop offs, areas of complex rock and snags.

UN UN1 0–2.5 River mouth (Frankland R.); Sand/mud flats.

UN UN2 0–1.5 Basin; Shallow sand flats, small areas of rock and seagrass; Boat ramp/jetty.

UN UN3 0–1.5 Basin; Shallow sand flats. UN UN4 2–6 Basin; Mud substrate, areas of rock/oyster reef.

WI WI1 0–2 Basin; Mud substrate in deeper waters, sand, rocks and some snags along banks; Boat ramp/jetty.

UN UN5 0–3 Basin; Sand/mud substrate, sand flats and rocks on banks. UN UN6 4–6 Basin; Mud substrate. UN UN7 0–4 Basin; Mud substrate, small areas of deep sand and rock.

UN UN8 0–2 River mouth (Deep R.); Mud substrate, some areas of shallow and deep sand flats.

LN LN1 0–4 Basin, lower estuary; Shallow sand flats with areas of seagrass and algae, substrate in deeper waters is mud.

LN LN2 0–2 Basin, lower estuary/entrance channel; Shallow sand flats with dynamic channels, some algal/seagrass meadows.

LN LN3 0–5 Basin; entrance channel; Shallow sand flats with dynamic channels, several deep pools with rock/reef and marine algae.

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Sub-surface receiver moorings were constructed from a concrete block (c. 30–50 kg) with

a stainless steel anchor point imbedded, to which 1–1.5 m of 14 mm nylon rope and a 15

cm styrene buoy were attached. Receivers were fixed vertically to the moorings c. 30–50

cm above the substrate, with the hydrophone facing upward. Data were downloaded from

receivers typically every three months, with bio-fouling cleaned during the same

occasions to maximise detection probability.

5.2.2 Fish collection and tagging

Fish were caught with beach seine nets and rod and line (with the latter using soft plastic

lures and natural baits such as prawns and mullet) across a range of estuarine regions

between July 2014 and February 2016. A total of 23 Acanthopagrus butcheri, 21

Platycephalus speculator, 10 Chrysophrys auratus and 10 Rhabdosargus sarba were then

surgically implanted with either V8–4L (20.5 mm long, 8 mm in diameter and weighing

2 g in water) or V9–2L (29 mm, 9 mm and 2.9 g) VEMCO coded acoustic transmitters.

All transmitters were programmed with a 60–120 second random delay (nominal 90 s),

resulting in 204 and 656 days of battery life for the V8 and V9 transmitters, respectively.

The specific tag type, tagging date and capture/release location of each individual is given

in the Results (section 5.3.1; Table 5.3).

The surgical tagging procedure was as follows. After capture, fish were immediately

placed in either a holding pen (80 × 80 × 80 cm mesh cage submerged in water) or aerated

holding tanks. Fish were then individually anaesthetised in an aerated solution of 20 mg

Aqui-S: 1 L of estuary water. Once stage III anaesthesia was reached (identified by a total

loss of equilibrium and no reaction to touch stimuli), fish were measured and placed in a

V-shaped cradle, then a small longitudinal incision was made through the ventral body

wall and the appropriately-sized transmitter inserted into the peritoneal cavity. The

incision was closed with one to two simple interrupted stitches using absorbable sutures

(3–0 or 4–0 MONOCRYL®). A hard plastic external tag (TBF; Hallprint;

https://hallprint.com) c. 30 mm long with a unique fish identification code and researcher

contact details, was then attached to the fish approximately 20 mm below the base of the

dorsal fin to enable tagged fish to be identified if re-caught by anglers. All wound areas

were swabbed with diluted antiseptic (Betadine®) to minimise chances of infection. Post-

surgery, fish were monitored in a holding pen until fully recovered (swimming upright

and coherently), and then released within 50 m of their site of capture.

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As detailed in section 5.3.1, all tagged A. butcheri and R. sarba were substantially above

the lengths at maturity (L50) for those species (c. 160−180 mm; Sarre & Potter, 1999;

Hesp & Potter, 2003). All P. speculator were above the L50 for males (200 mm) and only

one (ID34097; 327 mm) was below the L50 for females (340 mm; Coulson et al., 2017).

In contrast, only juveniles of C. auratus were tagged (L50 = 586–600 mm; Wakefield et

al., 2015), as adults are not typically recorded in estuaries of the region (e.g. Potter et al.,

1993; Potter & Hyndes, 1994).

5.2.3 Range testing of acoustic telemetry equipment

Transmitter detection range was tested using fixed-delay (V9–2L; 5 s delay) range test

transmitters, with receivers moored at 50–100 m intervals along their line of sight (for up

to 900 m). This was conducted across a representative range of habitats in the basins and

Frankland River. As rough weather conditions (e.g. wind, waves) have been shown to

negatively impact detection probability (Kessel et al., 2014; Stocks et al., 2014), range

testing was undertaken during both calm (wind <10 kn) and rough (wind >25 kn)

conditions. The average detection range of V9–2L transmitters across a range of weather

conditions was c. 400 m at basin stations, except where obstructions occurred due to land

or very shallow sand flats. Riverine stations typically had a detection radius of 150–300

m. The detection range of V8-4L transmitters, which have a slightly lower power output

than V9-2L transmitters (i.e. 144 vs 146 dB re 1 µPa @ 1 metre), was considered to be

87–90% of that of the latter transmitter type (VEMCO, 2017).

5.2.4 Collation of environmental and habitat data

Odyssey temperature loggers (Dataflow Systems Ltd; http://odysseydatarecording. com/)

were attached to nine receiver moorings (all FR stations, UN1, UN8, WI1 and LN1) to

record water temperature at 30 minute intervals for the duration of the study. Daily river

flow data (total discharge; m3 s−1) for the major tributary of the estuary, the Frankland

River, was obtained from the Department of Water and Environmental Regulation

(www.kumina.water.wa.gov.au; station 605012). Lunar illumination (%) for each

tracking day was calculated using the ‘lunar’ package in R (Lazaridis, 2014), and daily

tidal amplitude was obtained from the nearest marine gauging station (Department of

Transport WA; −35.033750, −117.892583) and time-adjusted to match the location of the

estuary.

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The average depth within a normal detection range of each station was calculated in QGIS

(http://www.qgis.org) using bathymetric data provided by the WA Department of Primary

Industries and Regional Development (DPIRD) Fisheries. Benthic habitat characteristics

and the locations of prominent physical structures (rocks, snags, jetties, reef) were

obtained from published maps (DEC, 2009; Semeniuk et al., 2011), satellite imagery and

field observations.

5.2.5 Data analyses

Fish detection data were downloaded from the acoustic receivers using the VEMCO User

Environment (VUE) software, then visually examined to remove false detections (i.e.

erroneous tag codes) and those from predated fish (uncharacteristic movements, usually

followed by tags becoming sedentary), dead fish or dropped tags (constant tag detections

at a single receiver). Individuals detected for less than three weeks were also removed.

Fish were classified as caught by a fisher if either the capture was reported or visual

examination of the tracking data showed clear evidence of capture. Examples of the latter

scenarios are provided in section 5.3.2.

A detection index (DI) was calculated for each fish to quantify its presence within the

array, which was determined as the total number of days a fish was detected relative to

the maximum tracking period of a transmitter (determined by either battery life or the

cessation of the study; e.g. Williams et al., 2017). For each species, a range of metrics

were then calculated to assess (i) estuarine-marine connectivity, (ii) intra-estuarine area

use, (iii) levels of moment throughout the estuary and (iv) temporal patterns of

distribution (see Table 5.2). Unless otherwise stated, all analyses were undertaken in R

(R Core Development Team, 2016).

Table 5.2 Metrics calculated for each species to assess their use of the Walpole-Nornalup

Estuary.

Metric Estuarine-marine connectivity • No. sea trips

• No. one-way sea trips • Proportion of time in the ocean

Intra-estuarine area use • Proportion of time in each estuarine region • Station residency (total tracking period) • Habitat residency

Level of movement throughout the estuary

• No. stations visited • Minimum linear distances travelled within

estuary Temporal changes in residency and intra-estuarine distribution

• Weekly station residency • Weekly and daily fish position upstream

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Estuarine-marine connectivity and intra-estuarine area use

Estuarine−marine connectivity was quantified by determining the total number of sea

trips made by each individual of each species (successive detections at stations LN1

and/or LN2 then LN3, followed by an absence of detections for at least six hours), and

the total number of individuals making one-way migrations to sea (i.e. no return during

the study period). Fish were considered to have re-entered the estuary when they were

detected at two or more stations within the array. The proportion of time fish spent in the

ocean and each of the four major regions of the estuary (Nornalup Inlet, Walpole Inlet,

the Lower Frankland River and Upper Frankland River) was also calculated, with the

latter determined from the inter-region gate stations (UN1/UN5/LN3, WI1, LFR2 and

UFR3, respectively). If an individual left the estuary permanently, ocean time was

considered to be that from when they left the estuary until cessation of the transmitter

battery life or the study, whichever came first.

Finer-scale spatial use of the estuary was assessed by calculating a residency index (RI)

at each receiver station, i.e. the number days a fish was present at the station relative to

the total number of days that fish was monitored (date of tagging until date of last

detection). A fish was considered present at a station when two or more detections were

recorded within a 24 h period (e.g. Keller et al., 2017).

Permutational Analysis of Variance (PERMANOVA; Anderson, 2001), conducted in

PRIMER v7 (Clarke & Gorley, 2015) with the PERMANOVA+ add-on module

(Anderson et al., 2008), was used to test for inter-specific differences in (i) the proportion

of time spent in each region and (ii) station residency. For each of these tests, the

respective data sets for each individual fish were used to create a Bray-Curtis resemblance

matrix, which was then subjected to a one-way PERMANOVA test. The null hypothesis

of no significant differences among species was rejected at P < 0.05. For any significant

findings, pairwise differences between species were explored using one-way Analysis of

Similarity tests (ANOSIM; Clarke & Green, 1988; Clarke, 1993).

To explore if habitat attributes influenced the distribution of each study species, residency

was also calculated on the basis of (i) depth (i.e. deep or shallow; >1.5 m or <1.5 m

average depth within detection range, respectively), (ii) if prominent rock and/or reef was

present or absent within detection range, and (iii) if prominent wood structure (e.g. snags,

jetties) was present or absent within detection range. Individual habitat residency was

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calculated as the proportion of days that a fish was present at any station with the above

characteristics. For each species and for each of the above three habitat categories,

separate paired Wilcoxon tests were undertaken to test if residency differed significantly

(P < 0.05) between each level of the habitat category.

For those species where substantial numbers of fish were tagged in different estuarine

regions (A. butcheri, P. speculator), a one-way PERMANOVA was also used to test for

differences in station residency among groups of individuals which were tagged in

different estuarine regions.

Level of movement throughout the estuary

To quantify the level of movement of each species throughout the estuary, the total

number of stations and number of stations visited each month by each individual was

calculated. Linear distances travelled throughout the array were also calculated using the

package ‘Vtrack’ in R (Campbell et al., 2012; Dwyer et al., 2015). The latter distances,

which are the minimum distances travelled between stations, excluding the average

detection radius of the receiver, were determined from known coordinates of stations,

accounting for impassable boundaries of the estuary (e.g. curvature of the river,

headlands, islands). Under very calm conditions there was the possibility of ‘untrue’

movements, i.e. the perception that fish had travelled further than was true due to an

increase or overlap in station detection ranges. In these instances, distances travelled were

standardised to a maximum realistic distance based upon the duration of the non-

residence event and the maximum sustained swimming speed of each species (estimated

from published literature and using a subset of receivers with no possible overlap in

detection range). Total distances travelled by each individual were then also standardised

to an average daily distance based upon the number of days each fish was present in the

estuary. To test if movement was related to body size, daily distances travelled by

individuals of each species were correlated against TL using simple linear regression.

PERMANOVA was used to test for differences among species in station visits and

distances travelled during a six month period when sufficient numbers of all four species

were present (August 2015 to January 2016). The number of stations visited and total

distance travelled each month by each individual present during that period were first

transformed to meet the assumption of homogeneity of variances (fourth root and

log(x+1), respectively; Anderson, 2001). The transformed data were then used to create

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separate Euclidean distance matrices, which were tested employing a two-way species ×

month design to account for any confounding seasonal influences.

Temporal changes in fish distribution/residency and the influence of environmental and

biological factors

Weekly station residency was calculated for each individual fish to examine temporal

changes in residency. This metric reflected the proportion of days a fish was present at

each station each week. The daily and weekly location of fish upstream from the estuary

mouth was also calculated to examine longitudinal changes in distribution. The daily

location of each fish was firstly estimated using a mean-position algorithm

(Simpfendorfer et al., 2002) based on the linear distance upstream of each station

(Simpfendorfer et al., 2008). For each individual, a weekly average position was then

calculated, and for each species, a weekly mean location of the population. To account

for differences in the tracking periods of the study species, the following temporal periods

were examined for these and the below analyses; A. butcheri, August 2014 to August

2016, P. speculator, December 2014 to August 2016, R. sarba, August 2015 to April

2016 and C. auratus, August 2015 to January 2016.

Mixed effects models fitted by maximum likelihood estimation were used to examine the

influence of freshwater river flow, water temperature and fish size (TL) on the residency

patterns of each species. For these analyses, the response variable represented weekly

residency at the station nearest to where each individual was released. The number of

weeks since each individual was tagged was also included as a continuous predictor

variable. A categorical factor of ‘month’ was also tested for each species, except C.

auratus due to low sample sizes. Water temperature data from loggers nearest to the

release station of each individual (see section 5.2.4) and daily river flow data were

averaged for each study week to match residency data. To account for potentially

differing effects of temperature and flow on residency in the upper vs lower reaches of

the system, the distance of the station from the estuary mouth was also tested as an

interaction term with the latter variables. As residency data represent the proportion of

days a fish was detected each week, a binomial distribution was used (Espinoza et al.,

2015). Fish ID and station were included as random effects to account for a lack of spatial

and temporal independence among samples. Akaike information criterion with a small

sample-bias correction, AICC, was used to select the best models, with models compared

to a null model ‘RI ~ 1 + (1|ID) + (1|station)’ at α = 0.05 using likelihood ratio tests.

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Models were computed using the glmer function of the R package ‘lme4’ (Bates et al.,

2017).

The daily and weekly location of individuals relative to the estuary mouth, and their

potential relationships with a suite of environmental factors and fish size, were examined

for each species using linear mixed effects models (LMMs) run with the lmer function in

‘lme4’. River flow, water temperature, maximum tidal amplitude and lunar illumination

and fish TL were included as continuous predictor variables, and month was included as

a categorical factor. Note that for the daily model, a 48 hour time-lag was added to the

flow data (e.g. Grant et al., 2017a), and for weekly models, the environmental variables

were averaged for each study week. To account for a lack of spatial and temporal

independence among individuals, ‘tagID’ was also included as a random effect. For A.

butcheri and P. speculator, which were tagged in several batches tracked over a 1.5–2

year period, year (1, 2) and tagging batch (1–8) were also included as random factors to

account for differences between the two study years and the timing and location of tagged

fish, respectively. The AICC was again used to select the best models, and models were

compared against appropriate null models for each species.

5.3 RESULTS

5.3.1 Summary of all individuals tracked

A total of 23 Acanthopagrus butcheri, 21 Platycephalus speculator, 10 Rhabdosargus

sarba and 10 Chrysophrys auratus were caught and implanted with internal acoustic

transmitters between July 2014 and February 2016. Details of each fish tagged are given

in Table 5.3. Tagged individuals of the three sparid species (A. butcheri, R. sarba and C.

auratus) were similar in length and ranged from 230–308 mm TL, with means of 272,

252 and 257 mm, respectively. Platycephalus speculator ranged from 321–465 mm TL,

with a mean of 385 mm. The tracking period for individual fish ranged from two to 656

days, with fish detected by one to 15 stations (Table 5.3; Fig. 5.2). Detection indices

ranged from a mean of 0.42 for C. auratus to 0.25 for P. speculator. Fifty-eight of the 64

tagged fish were detected for at least three weeks, and were thus included in subsequent

analyses presented in the following sections.

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Table 5.3 Transmitter ID (ID), total length (TL; mm), tagging details, tracking period

(days), total number of times detected, number of receiver stations visited, detection index

(DI) and minimum linear distance travelled by each individual of (a) Acanthopagrus

butcheri, (b) Platycephalus speculator, (c) Chrysophrys auratus and (d) Rhabdosargus

sarba and tagged in the Walpole-Nornalup Estuary from July 2014 to February 2016. A

sea trip refers to a fish leaving the estuary for ≥ 6hours.

ID TL Tagging Region

Tag Date

Tagged Tracking

Period

Total no. Sea Trips

Distance (km)

Detect. Stations DI Total Daily

(a) Black Bream (Acanthopagrus butcheri)

18890 297 WI V9-2L 26/07/2014 656 47,670 15 0.84 0 609.91 0.93 18891 285 WI V9-2L 26/07/2014 514 8,835 10 0.32 0 131.3 0.26 18892 245 WI V9-2L 26/07/2014 63 138 1 0.03 0 0 0 18893 240 WI V9-2L 26/07/2014 27 926 5 0.04 0 1.95 0.07 18894 243 WI V9-2L 26/07/2014 124 3,082 10 0.11 0 35.39 0.29 18895 305 UN V9-2L 26/07/2014 94 3,559 8 0.07 0 19.01 0.2 18896 270 UN V9-2L 26/07/2014 24 1,037 8 0.03 0 6.34 0.26 18897 295 UN V9-2L 26/07/2014 655 9,663 14 0.34 0 295.79 0.45 18898 262 UN V9-2L 26/07/2014 33 1,679 7 0.03 0 9.46 0.29 18899^ 265 UN V9-2L 26/07/2014 2 35 1 - - - - 18900 308 LFR V9-2L 25/09/2014 654 2,9043 8 0.56 0 288.88 0.44 18901 265 LFR V9-2L 25/09/2014 656 108,613 10 0.86 0 746.91 1.14 18912 263 UFR V9-2L 6/05/2015 269 17,080 13 0.29 0 0 0 18913 290 UFR V9-2L 6/05/2015 555 70,843 12 0.67 0 148.91 0.5 18909 269 UFR V9-2L 7/05/2015 47 26,470 1 0.07 0 150.46 0.56 18911 249 UFR V9-2L 7/05/2015 300 33,928 13 0.41 0 232.22 0.42 18915 246 UFR V9-2L 7/05/2015 606 87,372 13 0.84 0 391.86 0.65 18916 276 UFR V9-2L 7/05/2015 169 994 4 0.02 0 14.06 0.08 18918 255 UFR V9-2L 7/05/2015 252 32,330 12 0.35 0 287.94 1.14 34091 280 LFR V9-2L 8/05/2015 133 11,997 9 0.10 0 105.17 0.79 34092 292 LFR V9-2L 8/05/2015 656 83,065 15 0.94 0 827.65 1.26 34093 275 LFR V9-2L 8/05/2015 621 57,475 10 0.75 0 534.29 0.86 34094 271 LFR V9-2L 8/05/2015 273 24,645 13 0.30 0 308.44 1.13

Mean 272 322 30,020 9.6 0.36 0 233.91 0.53 SE 4.2 53.8 6,931 0.87 0.07 0 53.62 0.09

(b) Southern Bluespotted Flathead (Platycephalus speculator)

18902 365 UN V9-2L 4/11/2014 656 121,367 4 0.81 0 42.45 0.065 18903^ 356 UN V9-2L 4/11/2014 1 44 1 - - - - 18904 442 UN V9-2L 4/11/2014 39 1,359 2 0.05 0 0.75 0.019 18905 465 UN V9-2L 2/11/2014 656 1,512 5 0.24 0 19.93 0.03 18906 362 UN V9-2L 2/11/2014 654 736 4 0.13 0 6.58 0.01 18907 380 UN V9-2L 2/11/2014 219 35,246 2 0.34 0 5.97 0.027 18908 432 UN V9-2L 5/11/2014 483 1,239 2 0.06 0 1.19 0.002 18910 383 UN V9-2L 6/11/2014 649 15,630 3 0.38 0 3.3 0.005 18914 380 UN V9-2L 6/11/2014 653 4,019 6 0.21 0 12.87 0.02 18917^ 351 UN V9-2L 5/11/2014 6 20 1 - - - - 18919 367 UN V9-2L 6/11/2014 556 349 2 0.03 0 0.5 0.001 34090 405 LFR V9-2L 8/05/2015 125 8,899 11 0.06 1 10.24 0.082 34095 402 UN V9-2L 9/05/2015 38 1,601 1 0.06 0 0 0 34096 373 UN V9-2L 9/05/2015 106 11,780 3 0.16 1 2.179 0.021 34097 321 UN V9-2L 9/05/2015 656 95,915 4 0.93 0 30.42 0.046 34098 345 UN V9-2L 9/05/2015 229 33,969 7 0.34 1 7.98 0.035 34101 374 LFR V9-2L 10/11/2015 38 22,209 1 0.06 0 0 0 34102 382 LFR V9-2L 10/11/2015 101 15,769 6 0.07 1 5.96 0.059 38202 418 LFR V9-2L 10/11/2015 123 3,426 9 0.11 1 21.32 0.173 38203 405 LFR V9-2L 10/11/2015 80 13,498 3 0.07 0 7.12 0.089 38205 378 LFR V9-2L 11/11/2015 475 87,367 3 0.66 0 2.11 0.004

Mean 385 344 25,047 4.11 0.25 0.26 9.52 0.036 SE 7.5 60.44 8,283 0.62 0.06 0.1 2.64 0.01

Table continued overleaf.

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(c) Snapper (Chrysophrys auratus)

34103 230 LFR V8-4L 23/07/2015 196 29,362 11 0.8 0 33.64 0.17 34104 268 LFR V8-4L 23/07/2015 128 3,384 11 0.41 0 69.69 0.54 34107 241 LFR V8-4L 23/07/2015 182 16,269 11 0.75 0 39.83 0.22 34111 252 LFR V8-4L 23/07/2015 20 285 8 0.07 1 4.02 0.2 34112 232 LFR V8-4L 23/07/2015 138 8,757 6 0.4 0 5.87 0.04 38208 266 LFR V8-4L 10/11/2015 70 2,318 8 0.28 1 18.24 0.26 38209 265 LFR V8-4L 10/11/2015 74 2,120 12 0.24 1 34.67 0.47 38211 246 LFR V8-4L 10/11/2015 150 33,303 12 0.74 1 20.14 0.13 38210^ 235 LFR V8-4L 10/11/2015 199 13,550 1 - - - - 34095.2 281 LFR V9-2L 14/02/2016 51 3,695 8 0.08 1 20.27 0.4

Mean 257 112.11 11,055 9.67 0.42 0.56 27.37 0.27 SE 3.7 20.32 4,163 0.73 0.09 0.18 6.7 0.06

(d) Tarwhine (Rhabdosargus sarba)

34099 273 WI V9-2L 24/07/2015 511 29,690 12 0.47 2 114.15 0.22 34100^ 256 WI V9-2L 24/07/2015 116 93,771 1 - - - - 34105 248 LFR V8-4L 23/07/2015 135 16,172 12 0.56 1 87.56 0.65 34106 259 LFR V8-4L 23/07/2015 65 13,781 8 0.31 0 50.32 0.77 34108 253 WI V8-4L 24/07/2015 200 11,636 8 0.68 1 10.86 0.05 34109^ 250 UN V8-4L 23/09/2015 11 630 1 - - - - 34110 265 UN V8-4L 23/09/2015 72 9,468 12 0.28 2 58.96 0.82 38204 268 LFR V9-2L 10/11/2015 453 61,824 14 0.59 3 410.63 0.91 38206 262 LFR V9-2L 14/02/2016 64 11,148 10 0.1 0 66.98 1.05 38207 232 UN V8-4L 23/09/2015 45 2,566 12 0.18 0 21.63 0.48

Mean 252 193.13 19,536 11 0.4 1.13 102.64 0.62 SE 5.6 65.7 6,625 0.76 0.07 0.4 45.54 0.12

^ fish not included in analyses due to insufficient movements and/or detections. Note, the mean

tracking period, number of detections and number of stations visited exclude these individuals.

5.3.2 Estuarine-marine connectivity

A total of 15 fish left the estuary during the study period, comprising five individuals each

of P. speculator, C. auratus and R. sarba (26, 55 and 63 %, respectively of tracked fish;

Table 5.3; Fig. 5.2; 5.3).

Platycephalus speculator left the estuary 101–229 days after tagging, with two fish

leaving during spring, one during summer and two in autumn (Fig. 5.2b). No fish that left

the estuary returned. Among C. auratus, excluding one fish presumed to have died or

been predated after 128 days (ID34104), only the three smallest individuals (ID34112,

34107 and 34103; 230‒241 mm TL) did not leave the estuary during the tracking period.

Of the five individuals that left the estuary, one emigrated during August 2015, two during

January 2016 and two in April 2016. As for P. speculator, no C. auratus which left the

system returned (Fig. 5.2c).

Among R. sarba, five individuals left the estuary during November/December of 2015,

but in contrast to the above two species, four returned after ≤40 days (Fig. 5.2d).

Interestingly, one individual (ID38204) left the system for two consecutive 10 hour

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periods on the 29/12/15 and 30/12/15. This fish and also ID34099, both of which were

tagged with V9–2L (656-day battery life) tags, remained in the system for c. 12 months

before leaving the estuary again in December 2016 (two days apart on the 12/12 and

14/12). The mean proportion of time spent in the marine environment by R. sarba was

thus notably less than C. auratus (i.e. 18% vs 37%; Fig. 5.3e).

5.3.3 Intra-estuarine area use

Acanthopagrus butcheri

Acanthopagrus butcheri were detected in all estuarine regions and at all stations except

LN3 situated at the mouth of the estuary (Fig. 5.3; 5.4). Additionally, with the exception

of fish ID18892 which was caught by a recreational fisher two months after release, all

individuals were recorded in the Frankland River and more than half (13/22) were

recorded at station UFR1, the most upstream receiver in the array (Fig. 5.2–5.4).

Thirteen fish spent the majority of time (54–100%) in either the Upper Frankland River

(UFR) or Lower Frankland River (LFR), and seven spent a considerable proportion of

time (30–100%) in the Walpole Inlet (WI; Fig. 5.3a). Apart from fish 18897 and 18890,

all individuals spent <50% of their time in the largest region of the estuary, the Nornalup

Inlet (NI; Fig. 5.3a).

At a finer scale, residency was highest at stations UFR3 and LFR2 in the lower to middle

Frankland River (mean residency index [RI] of 0.22 and 0.14, respectively) and at stations

UN1 and UN3 in the Upper Nornalup Inlet (UN) near the mouth of this tributary (RI =

0.11–0.16; Fig. 5.4). Residency at station WI1 at the entrance to the Walpole Inlet (WI)

was also relatively high (RI = 0.13). The lowest residency was recorded at stations UN6,

UN7 and UN8 in the central/western Nornalup Inlet (RI < 0.007) and at station UFR1 in

the uppermost reaches of the Frankland River (RI = 0.007; Fig. 5.4). Overall, residency

of A. butcheri was far higher in shallow than deep waters (mean RI = 0.56 vs 0.24; paired

Wilcoxon P < 0.001; Fig. 5.5), and also in areas where wooded structure was present (RI

= 0.54 vs 0.23; paired Wilcoxon P < 0.001; Fig. 5.5). The presence of rock, however, did

not have a significant influence on the residency of this species.

Significant residency differences were also detected among individuals tagged in

different regions of the estuary (PERMANOVA, P < 0.001; Appendix 5.1). Thus, with

the exception of two fish (ID18890 and ID18916), residency of A. butcheri was

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significantly higher either at the station closest to where they were initially caught and

released, or at one nearby (<1 km radius; Fig. 5.6).

Five A. butcheri were reported as caught by recreational fishers between 47 days and two

years after they were released (Fig. 5.2a), all of which were caught in the same region as

they were tagged, and two of which were <50 m from their site of initial release. Note,

the latter includes fish ID18899 which was not shown in Figure 5.2 due to insufficient

detections, but was reported as caught two years after tagging. Visual examination of

tracking data also revealed that several other fish may have been caught and kept by

fishers, but not reported (Fig. 5.2a). For example, A. butcheri ID34094 was tracked

moving around the estuary for 274 days, then was detected at station LN1 in the lower

estuary at 13:13 on 05/02/2015 and not detected again until 21:54 that day at station WI1

(c. 4 km upstream), where it was constantly detected for the remainder of the transmitter

battery life (>1 year). It is likely that a fisher caught that individual in the lower estuary,

transported it upstream and discarded the carcass and transmitter into the water in

detection range of the latter station, which is close to a boat ramp with a fish cleaning

area. Additionally, patterns in movement suggest that fish ID18893, 18895 and 18898

were likely caught near the mouth of the Frankland River (nearby to station LFR2), a

popular location for boat fishers and house boats, and fish ID18911 was likely caught

near station UFR3, which is in detection range of a popular fishing jetty.

Platycephalus speculator

Individuals of P. speculator were detected by one to 11 stations (mean 4.1 ± 0.4 SE) for

an average of 344 days (Table 5.3b). Most P. speculator (12/19) remained within the NI

for the majority of the study, with fish spending on average 67% of time in this region

(Fig. 5.2b; 5.3b). No fish tagged in the NI travelled into the Frankland River, and none

were detected in the UFR.

Residency was highest at station UN8 at the mouth of the Deep River (mean RI = 0.22;

Fig. 5.4). Moderate residency was also recorded at station LFR2 in the lower Frankland

River (RI = 0.11) and at stations UN5, UN6 and UN7 in the Nornalup Inlet (RI = 0.05–

0.08; Fig. 5.4). As occurred for A. butcheri, significant residency differences were

detected among P. speculator tagged in different regions of the estuary (P < 0.001;

Appendix 5.1). Most individuals were only detected by stations nearby to where they

were caught and released, with very high RI’s of up to 1 (Fig. 5.7). This was also the case

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for two of the five individuals which left the system (ID34096 and 34098), which showed

very high site attachment (RI = 0.69‒0.95) to the receiver where they were released before

migrating to sea.

Unlike A. butcheri, the residency of P. speculator was higher in deep than shallow waters

(RI = 0.44 vs 0.15; paired Wilcoxon P = 0.023), where rock and/or reef was present (RI

= 0.49 vs 0.09; paired Wilcoxon P < 0.001; Fig. 5.5) and where submerged wood/snags

were absent (RI = 0.14 vs 0.49; paired Wilcoxon P = 0.023).

One fish (ID34095) was reported as caught and kept by an angler 38 days post-release

(Fig. 5.2b) nearby to station UFR8 where it was tagged. This individual was detected only

at this station for the duration of its tracking period.

Chrysophrys auratus

Nine Chrysophrys auratus were tracked for 20–196 days, with fish detected by six to 12

stations (mean 9.7 ± 0.4 SE; Table 5.3c). Individuals spent the greatest proportion of time

within the NI and LFR (means of 42 and 21%, respectively; Fig. 5.3c). No fish visited the

UFR, and although four were detected in the WI, the proportion of time spent there was

minimal (<0.01%; Fig. 5.3c). Station residency for this sparid was highest at LFR2 in the

Lower Frankland River (RI = 0.31), and also UN2/4 in the north-eastern Nornalup Inlet

(RI = 0.22–0.24; Fig. 5.4). Moreover, residency was far higher at stations with rock/reef

present (RI = 0.72 vs 0.14; paired Wilcoxon P = 0.004; Fig. 5.5), although water depth

and the presence of submerged wooden structure had no significant influence.

Several individuals (ID34095.2, ID38211, ID34111 and ID38209) displayed high site

attachment close to the station where they were tagged and released (Fig. 5.8a). Notably,

however, all of these individuals left the estuary. For example, following release, fish ID

38211 was detected for 146 days at station LFR2, before migrating to sea over a period

of 4 days.

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Rhabdosargus sarba

Eight Rhabdosargus sarba were detected for 45–511 days at 10–14 stations (mean 11.0

± 0.7 SE; Table 5.3d). All tagged fish were detected in the NI and WI, and all but one

were recorded in the LFR (Fig. 5.3e; 5.8b). In contrast, only one individual was recorded

in the UFR (ID 38204; Fig. 5.3d; 5.8b). Individuals generally spent the greatest proportion

of time in the NI, i.e. 51% on average (Fig. 5.3d).

Residency for this species was highest at station UN1 (RI = 0.27) at the mouth of the

Frankland River and stations UN5/WI1 in the channel between the Nornalup and Walpole

inlets (RI = 0.22–0.23; Fig. 5.4). Residency at station LFR2 in the lower Frankland and

stations UN2/3 and LN1 in the Nornalup Inlet was also notable (RI = 0.11–0.14; Fig. 5.4).

With the exception of fish ID34099, which was highly resident at station WI1 where it

was released (RI = 0.5; Fig. 5.8b), residency of individual R. sarba was generally

moderate to high across several stations within the NI.

Paired Wilcoxon tests did not detect any significant difference in the residency of R. sarba

between different levels of each of the habitat attributes.

Interspecific differences

PERMANOVA detected significant differences among species in (i) the amount of time

spent in each broad estuarine region and (ii) station residency (P < 0.001; Appendices

5.2; 5.3). Among the former metric, ANOSIM also found significant species differences,

though the overall extent of the differences was low to moderate (R = 0.242, P < 0.001;

Appendix 5.2b). Pairwise tests revealed that these differences were greatest between A.

butcheri and both P. speculator and C. auratus (pairwise R = 0.395–0.372, P < 0.01;

Appendix 5.2b), followed by A. butcheri vs R. sarba (R = 0.213). No significant

differences occurred between either of the latter two sparids and P. speculator. Thus, A.

butcheri spent a far greater proportion of time in the UFR than P. speculator, R. sarba

and C. auratus (35 vs <0.01%; Fig. 5.3e), which all spent the most time in the NI (67, 51

and 42% of the tracking period, respectively). Acanthopagrus butcheri also spent far more

time in the WI than either P. speculator or C. auratus (26 vs 0–1.6%). The LFR was

occupied to greater extent by A. butcheri and C. auratus (19–22%) than R. sarba and P.

speculator (9–11%; Fig. 5.3e).

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Species differences in station residency were also shown by ANOSIM to be low to

moderate (R = 0.282, P < 0.001; Appendix 5.3b). Station residency of A. butcheri was

again shown to be significantly different from each of the other study species (pairwise R

= 0.171–0.455), and also between R. sarba and C. auratus (R = 0.451; Appendix 5.3b).

The relative distinctiveness of A. butcheri reflects the far higher residency of this species

at various Frankland River stations (LFR1 and UFR1–3) compared to the other three

study species (Fig. 5.4). Additionally, the residency of A. butcheri at stations UN6, UN7,

UN8 in central/western Nornalup Inlet was far lower than that of P. speculator, and to a

lesser extent, C. auratus and R. sarba. Differences among the latter two sparids reflect

the higher residency of R. sarba at stations WI1/UN5 (between the two inlets) and station

UN1 (near the Frankland River mouth), while C. auratus displayed higher residency at

station LFR2 and UN2/UN3 (lower river and north-eastern Nornalup Inlet, respectively;

Fig. 5.4).

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Figure 5.2 (a) Daily presence of tagged (a) Acanthopagrus butcheri, (b) Platycephalus

speculator, (c) Chrysophrys auratus and (d) Rhabdosargus sarba at receivers in the basin

(◼) and riverine (◼) reaches of the Walpole-Nornalup Estuary for all or some of the

period between July 2014 and February 2017. (◼) denotes detections at the mouth of the

estuary, () denotes fish reported as caught by recreational fishers and ( ) denotes fish

likely to have been caught based upon visual examination of tracking data.

(a)

(b)

(c)

(d)

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Figure 5.3 Total proportion of time that individuals of (a) Acanthopagrus butcheri, (b)

Platycephalus speculator, (c) Chrysophrys auratus and (d) Rhabdosargus sarba spent in

the Upper Frankland River (UFR), Lower Frankland River (LFR), Walpole Inlet (WI),

Nornalup Inlet (NI) and the marine environment. (e) Mean (±SE) proportion of time that

each species spent in each region and the total proportion of individuals that visited each

region

(a)

(b)

(c)

(d)

(e)

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Figure 5.4 Average residency of Acanthopagrus butcheri, Platycephalus speculator,

Chrysophrys auratus and Rhabdosargus sarba at each acoustic receiver station ()

throughout the Walpole-Nornalup Estuary over the monitoring period. Station names are

given in Fig. 5.1 (section 5.2).

Figure 5.5 Mean (±SE) residency of each study species in deep and shallow waters (≥1.5

m or <1.5 m average depth, respectively), areas with prominent rock or reef present or

absent, and in areas with prominent wooden structure present or absent.

A. butcheri

P. speculator

C. auratus

R. sarba

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Figure 5.6 Station residency of each of the 22 tagged Acanthopagrus butcheri. Yellow triangles denote the nearest station to the location at which each

individual was released. Station names are given in Fig. 5.1 (section 5.2)

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Figure 5.7 Station residency of each of the 19 tagged Platycephalus speculator. Yellow triangles denote the nearest station to the location at which each

individual was released. Station names are given in Fig. 5.1 (section 5.2).

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Figure 5.8 Station residency of (a) each of the 9 tagged Chrysophrys auratus and (b) each

of the 8 tagged Rhabdosargus sarba. Yellow triangles denote the nearest station to the

location at which each individual was released. Station names are given in Fig. 5.1

(section 5.2).

(a)

(b)

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5.3.3 Level of movement throughout the estuary

Acanthopagrus butcheri and R. sarba were the most mobile species and travelled an

average (± SE) minimum linear distance of 0.53 ± 0.09 and 0.62 ± 0.12 km day−1,

respectively (Table 5.3). Several individuals of the former species covered >500 km in

total, with A. butcheri ID34092 travelling at least 827.65 km. Fish ID38204 was the most

mobile individual of R. sarba, and was estimated to have travelled at least 410 km over

the 453 days for which it was tracked. Chrysophrys auratus travelled 4–70 km in total,

with an average rate of 0.27 ± 0.6 km day−1 (Table 5.3). In contrast, P. speculator

displayed little movement throughout the system, with fish travelling on average only

0.036 km day−1 (Table 5.3). Moreover, most individuals of this platycephalid (84%)

travelled less than 20 km in total over their tracking period, and the maximum cumulative

distance travelled in 656 days of tracking was only 42 km.

PERMANOVA detected significant inter-specific differences in both the number of

stations visited and the total distance travelled from August 2015 to January 2016 (P =

0.001; Appendix 5.4). Both metrics were far higher among the three sparid species than

P. speculator (c. 4.5 vs 1.8 stations month−1; 7–24 vs 0.15 km month−1; Fig. 5.9).

PERMANOVA did not detect significant differences in either metric between months, or

a species × month interaction. The daily distance travelled by individuals of C. auratus

increased significantly with fish length (R2 = 0.59, P = 0.01), but no such significant

relationship was detected for the other three study species (Fig. 5.10).

Figure 5.9 Mean (±SE) monthly (a) number of stations visited and (b) minimum linear

distance travelled by individuals of each study species from August 2015 to January 2016.

(a) (b)

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Figure 5.10 Relationship between the total length (mm) and average daily linear distance

travelled by individuals of each study species.

5.3.4 Influences of environmental and biological factors on temporal changes in residency and intra-estuarine distribution

Acanthopagrus butcheri

Between August 2014 and August 2016, mean weekly water temperatures throughout the

Walpole-Nornalup Estuary varied from 11–16 °C during winter (Jun–Aug) and 21–24°C

during summer (Dec–Feb; Fig. 5.11a). In contrast, weekly river flow to the system was

highest in winter and late spring (typically 5–17 m3 s−1) and lowest in summer and early

autumn (typically <0.5 m3 s−1; Fig. 5.11a). Notably, however, during the summer of 2016

(late January and early February) substantial flows of 2.1–5.6 m3 s−1 were recorded.

Marked seasonal changes in the intra-estuarine distribution of A. butcheri were observed,

with notable upstream shifts in residency and population location occurring during late

spring/early summer of both 2014–15 and 2015–16 (Fig. 5.11b,c). During late spring and

early summer (October–December) residency was greatest at stations in the UFR and

lowest (or non-existent) in the UN/LN (Fig. 5.11b). Comparatively, during August and

September, residency was highest at stations in the LFR/WI and/or UN. Between the two

study years, residency in the middle estuary (stations WI1/UN5) was notably lower

during 2015–16 than 2014–15, while in the Frankland River, and particularly at station

UFR3, the reverse was true (Fig. 5.11b). An upstream population shift of c. 6 km was also

apparent during late autumn/early winter of 2014–15, but not 2015–16 (Fig. 5.11c).

R2 = 0.59, P = 0.01

R2 = 0.04, P = 0.48

R2 = −0.12, P = 0.63

R2 = −0.03, P = 0.48

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Figure 5.11 (a) Mean weekly water temperature throughout the Walpole-Nornalup

Estuary and mean freshwater flow in the upper Frankland River between August 2014

and August 2016. Average weekly (b) station residency indices (RI) and (c) location

upstream from the estuary mouth (±SE; blue shading) of Acanthopagrus butcheri. Note,

station LFR1 was missing for part of April and May 2016.

Of the 11 candidate mixed effects models used to examine potential environmental and

biological influences on the weekly residency patterns of A. butcheri, five were

significantly better (P < 0.05 and lower AICC) than the null model, with the top two

(ΔAICC < 10) employing distance upstream and temperature and/or flow as factors (Table

5.4). The first of these models predicted that under increasing temperatures, residency of

A. butcheri would increase at stations in the upper estuary, but decrease at stations in the

lower estuary (Fig. 5.12a). The second model predicted that increased flows would result

in higher residency at downstream than upstream stations (Fig. 5.12b).

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Table 5.4 Mixed effects models examining the influence of freshwater flow (flow), water

temperature (temp), month, weeks since tagging (WST), fish length (TL) and linear

distance upstream (dist_up) on the weekly residency (RI) of Acanthopagrus butcheri at

the station nearest to their tagging location. Models are ranked by ΔAICC and were

compared to the null model ‘RI ~ 1 + (1|ID) + (1|station)’.

# model df logLik AICC ΔAICC weight P 1 RI ~ temp * dist_up 6 -397.91 807.91 0 0.97 <0.001 2 RI ~ flow * dist_up 6 -401.31 814.71 6.8 0.03 <0.001 3 RI ~ TL + WST 5 -458.85 927.77 119.86 0 0.004 4 RI ~ WST 4 -461.44 930.93 123.02 0 0.017 5 RI ~ TL 4 -462.3 932.64 124.73 0 0.046 6 RI ~ flow + WST 5 -461.4 932.88 124.97 0 0.055 7 RI ~ WST + temp 5 -461.44 932.95 125.04 0 0.058 8 NULL 3 -464.3 934.62 126.71 0 1 9 RI ~ flow 4 -464.13 936.3 128.39 0 0.558

10 RI ~ temp 4 -464.28 936.6 128.7 0 0.85 11 RI ~ flow + temp 5 -463.72 937.51 129.6 0 0.562 12 RI ~ month 14 -455.02 938.52 130.61 0 0.07

Figure 5.12 Predicted weekly residency of Acanthopagrus butcheri as estimated by the

best two mixed effects models (#1 and 2) in Table 5.4. Shaded areas represent confidence

limits.

With respect to distance upstream of the population (Fig. 5.11c), during August and early

September of 2014 and 2015 A. butcheri resided on average 4–5 km from the estuary

mouth. In late September of both years the population shifted upstream, remaining 8–

10.6 km from the estuary mouth for the majority of October–December (Fig. 5.11c).

Interestingly, in 2014, the population migrated downstream during the last week of

October (mean location 5.7 km upstream) and then back upstream for the following six

weeks (mean location 8.3–10 km upstream). In spring/summer 2015, the population

remained upstream for approximately twice as long as in the previous year, with a

downstream shift not occurring until late February. Similarly to the above model

outcomes for weekly station residency, the mean location upstream of A. butcheri

(a) Model 1 (RI ~ dist_up × temp) (b) Model 2 (RI ~ dist_up × flow) Lower estuary Upper estuary Lower estuary Upper estuary

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displayed an inverse correlation with flow, with mean river flows above 5 m3 s−1

corresponding with the population being <7.5 km upstream (Fig. 5.11c).

A set of 39 candidate models were used to test if either the weekly or daily distance

upstream of A. butcheri was influenced by various environmental factors, month and fish

size. All of the top ten models (lowest AICC) at both the daily and weekly scale included

month as a factor (Table 5.5). The best model for daily distance upstream also included

flow and maximum tide height as factors, and the best weekly model included flow and

water temperature. Both these models predicted A. butcheri to be furthest upstream during

October and November, and furthest downstream during August–September and

February–May (Fig. 5.13), and c. 7.5-8 km upstream under low flow conditions (<1 m3

s−1) but 5–6 km under high flow conditions (15 m3 s−1). With respect to the best daily

model, an increase in daily maximum tide height from 0.6 to 1.6 m was also predicted to

cause fish to move c. 2 km further upstream, while the weekly model further predicted

that temperature increases from 12.5 to 22.5 °C would be linked with an upstream shift

of fish from 5 to 9 km from the estuary mouth.

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Table 5.5 Mixed effects models examining the influence of freshwater flow, water

temperature, tidal height (tide), lunar illumination (lunar), month and fish length (TL) on

the (a) daily and (b) weekly distance of Acanthopagrus butcheri upstream (km from

estuary mouth). The top 10 models (ranked by ΔAICC) from a full set of 39 candidate

models are shown. All models were compared to the null model ‘distance ~ 1 + (1|ID) +

(1|year) + (1|tagging.group)’.

# Model df logLik AICC ΔAICC weight P (a) Daily distance upstream 1 distance ~ month + flow + tide 18 −10445.1 20926.28 0 1 <0.001 2 distance ~ month + flow + temp 18 −10470.5 20977.07 50.79 0 <0.001 3 distance ~ month + flow + lunar 18 −10478.6 20993.32 67.04 0 <0.001 4 distance ~ month + flow 17 −10479.9 20994.04 67.76 0 <0.001 5 distance ~ TL + flow + month 18 −10479.2 20994.48 68.2 0 <0.001 6 distance ~ month + temp + tide 18 −10481.7 20999.61 73.33 0 <0.001 7 distance ~ month + temp + lunar 18 −10499.7 21035.58 109.29 0 <0.001 8 distance ~ month + temp 17 −10503.6 21041.36 115.07 0 <0.001 9 distance ~ TL + temp + month 18 −10502.9 21042.04 115.76 0 <0.001

10 distance ~ month + tide + lunar 18 −10508.4 21052.91 126.62 0 <0.001 (b) Weekly distance upstream 1 distance ~ month + flow + temp 18 −1872.26 3781.34 0 0.73 <0.001 2 distance ~ month + temp 17 −1875.43 3785.59 4.25 0.09 <0.001 3 distance ~ month + temp + lunar 18 −1874.53 3785.88 4.54 0.08 <0.001 4 distance ~ month + temp + tide 18 −1874.66 3786.14 4.8 0.07 <0.001 5 distance ~ month + flow + tide 18 −1875.05 3786.92 5.58 0.04 <0.001 6 distance ~ TL + temp + month 18 −1879.06 3794.95 13.61 0.00 <0.001 7 distance ~ month + flow 17 −1880.89 3796.51 15.17 0.00 <0.001 8 distance ~ TL + flow + month 18 −1880.35 3797.53 16.18 0.00 <0.001 9 distance ~ month + flow + lunar 18 −1880.78 3798.39 17.05 0.00 <0.001

10 distance ~ month + tide 17 −1896.01 3826.75 45.41 0.00 <0.001

Figure 5.13 Predicted (a) daily and (b) weekly distance upstream of Acanthopagrus

butcheri in each month and under various environmental conditions as estimated by the

best models in Table 5.5. Error bars and shaded areas represent SE.

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Platycephalus speculator

Weekly residency of P. speculator remained relatively constant throughout the year and

was generally highest in the UN, particularly at stations UN5–8 (Fig. 5.14a). Notably

though, during December–March of 2015/16 a slight increase occurred at stations

LNFR1/2 in the Frankland River, and also UN1/2 near its mouth. Residency at station

LN1 in the lower estuary also increased between August 2015 and January 2016.

Residency of P. speculator at the station where they were tagged was shown by mixed

effects models to be most influenced by temperature and number of weeks since tagging

(WST; lowest AICC from 11 candidate models; Table 5.6a). Thus, under warmer water

temperatures and a longer time since tagging, the residency of P. speculator at their

tagging location decreased (Table 5.6b). The second best model was a combination of

temperature and flow, with residency predicted to decrease in response to increases in

both environmental variables. The linear distance upstream of P. speculator did not differ

significantly from the null model for any of the 39 candidate models, reflecting the

relatively constant location of the population throughout the duration of the study

(population mean ranging only from 3 to 4.7 km; Fig. 5.14b).

Figure 5.14 Average weekly (a) station residency indices (RI) and (b) location upstream

from the estuary mouth (±SE; blue shading) of Platycephalus speculator between

December 2014 and August 2016.

Riv

er

Mid

dle

Estu

ary

L

ow

er

Estu

ary

Station residency

Population location

(a)

(b)

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Table 5.6 (a) Mixed effects models examining the influence of freshwater flow (flow),

water temperature (temp), month of the year, weeks since tagging (WST), fish length (TL)

and distance upstream (dist_up) on the weekly residency (RI) of individuals of

Platycephalus speculator at the station nearest to their tagging location. Models are

ranked by ΔAICC and were compared to the null model ‘RI ~ 1 + (1|ID) + (1|station)’. (b)

Model summaries for the two best fit (lowest AICC) models. Positive coefficients indicate

an increase in residency and negative coefficients indicate a decrease in residency.

(a) # model df logLik AICC ΔAICC weight P

1 RI ~ WST + temp 5 −198.05 406.17 0 1 <0.001

2 RI ~ flow + temp 5 −208.07 426.22 20.05 0 <0.001

3 RI ~ temp * dist_up 6 −214.3 440.7 34.53 0 <0.001

4 RI ~ temp 4 −218.64 445.33 39.16 0 <0.001

5 RI ~ flow + WST 5 −219.92 449.92 43.75 0 <0.001

6 RI ~ TL + WST 5 −220.49 451.06 44.88 0 <0.001

7 RI ~ WST 4 −222.6 453.25 47.08 0 <0.001

8 RI ~ month 14 −213.92 456.35 50.18 0 <0.001

9 RI ~ flow * dist_up 6 −232.17 476.45 70.28 0 0.033

10 RI ~ TL 4 −234.41 476.87 70.7 0 0.039

11 NULL 3 −236.54 479.11 72.94 0 1

12 RI ~ flow 4 −236.53 481.11 74.94 0 0.879

Chrysophrys auratus

Weekly residency of C. auratus was moderate at station LFR2 and several stations

throughout the UN and LN during the first month of tracking (August 2015; Fig. 5.15a).

In September and early October 2015, residency decreased at LFR2 and increased notably

at station UN4, but in mid-October, residency at station LR2 again increased and then

remained relatively constant for the duration of the study. Nine models were tested to

determine whether the weekly residency of C. auratus was influenced by a suite

environmental factors, only two of which differed significantly from a null model. Both

of these models included WST, with temperature and river flow also included in the best

and second best models, respectively (Table 5.7a). These models predict a decrease in the

(b) Estimate SE Z P

Model

1 (Intercept) −1.98212 1.084365 −1.828 0.0676

WST −0.04759 0.008507 −5.595 <0.001

temp −0.35338 0.056686 −6.234 <0.001

Model

2 (Intercept) −3.48437 0.92813 −3.754 <0.001

flow −0.21199 0.0499 −4.248 <0.001

temp −0.46873 0.07025 −6.673 <0.001

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residency of C. auratus as the number of weeks since tagging increases (Table 5.7b).

Similarly, an increase in river flow has a negative effect on residency, while contrastingly

temperature has a positive effect.

The mean location upstream C. auratus ranged from 3.4–6.7 km (Fig. 5.15b), and again,

only two models to predict the latter response variable performed better than the null

model (Table 5.8), one of which included month and the other WST. Fish were predicted

to be the furthest downstream during September and January, and distance upstream also

decreased with time since tagging (Fig. 5.16b).

Figure 5.15 Average weekly (a) station residency indices (RI) and (b) location upstream

from the estuary mouth (±SE; blue shading) of Chrysophrys auratus between August

2015 and April 2016.

Riv

er

Mid

dle

Estu

ary

L

ow

er

Estu

ary

Station residency

Population location

(a)

(b)

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Table 5.7 (a) Mixed effects models examining the influence of freshwater flow (flow),

water temperature (temp), month of the year, weeks since tagging (WST) and fish length

(TL) on the weekly residency (RI) of individuals of Chrysophrys auratus at station LFR2

where they were released. Models are ranked by ΔAICC and were compared to the null

model ‘RI ~ 1 + (1|ID)’. (b) Model summary of the two best fit models (lowest AICC).

Positive coefficients indicate an increase in residency and negative coefficients indicate

a decrease in residency.

(a) # model df logLik AICC ΔAICC weight P

1 RI ~ temp + WST 4 −33.14 74.66 0 0.42 0.014

2 RI ~ flow + WST 4 −33.51 75.39 0.73 0.29 0.02

3 NULL 2 −37.4 78.92 4.26 0.05 1

4 RI ~ WST 3 −36.43 79.08 4.41 0.05 0.162

5 RI ~ temp 3 −36.53 79.29 4.63 0.04 0.187

6 RI ~ TL 3 −36.54 79.31 4.64 0.04 0.189

7 RI ~ flow + temp +TL 5 −34.5 79.57 4.9 0.04 0.121

8 RI ~ WST + TL 4 −35.75 79.89 5.22 0.03 0.192

9 RI ~ flow 3 −37.16 80.53 5.87 0.02 0.481

10 RI ~ flow + temp 4 −36.09 80.56 5.9 0.02 0.27

(b) Estimate Std. Error z value P

m1 (Intercept) −3.434 1.185 −2.898 0.004

WST −1.2623 0.6052 −2.086 0.037

temp 0.4377 0.2028 2.158 0.031

m2 (Intercept) −3.5656 1.2722 −2.803 0.005

flow −0.4722 0.2265 −2.085 0.037

WST −1.5371 0.7199 −2.135 0.038

Table 5.8 Mixed effects models examining the influence of freshwater flow (flow), water

temperature (temp), tidal height (tide), lunar illumination (lunar), month of the year,

weeks since tagging (WST) and fish length (TL) on the weekly distance upstream of

individuals of Chrysophrys auratus. The top 5 models (ranked by ΔAICC) from a full set

of 26 candidate models are shown. All models were compared to the null model ‘distance

~ 1 + (1|ID)’.

No model df logLik AICC ΔAICC P

1 distance ~ month 8 −176.94 371.22 0 0.001

2 distance ~ WST 4 −182.62 373.61 2.38 0.002

3 NULL 3 −187.14 380.49 9.27 1

4 distance ~ temp 4 −186.81 381.97 10.75 0.415

5 distance ~ tide 4 −186.85 382.06 10.84 0.448

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Figure 5.16 The predicted weekly distance upstream of individuals of Chrysophrys

auratus (a) during each month of the year from August to January, and (b) in relation to

weeks since tagging, as estimated by the best fit mixed effects models, #1 and #2,

respectively, in Table 5.8. Error bars and shaded areas represent SE.

Rhabdosargus sarba

Throughout most of the study period, the residency of R. sarba was moderate to high at

a number of stations in the UN and also LFR2 and WI1 (Fig. 5.17a). However, from late

November to early January, residency increased substantially in the lower estuary

(stations LN1–3) and generally decreased elsewhere throughout the system. Ten of the

11 candidate models that employed the weekly RI data for R. sarba were significantly

different from the null model, with an interaction between temperature and distance

upstream providing the best fit (Table 5.9a). Coefficients from this model predict that as

temperature increases, residency decreases (Table 5.9b), with this decline being more

apparent for fish tagged in downstream than upstream locations.

The mean distance upstream of the population of R. sarba showed a clear decrease during

late November 2015 to January 2016 (Fig. 5.18b). Of the 26 candidate models for the

mean weekly position of this species relative to the estuary mouth, month provided the

best fit (Table 5.10; Fig. 5.18a). River flow and temperature were also included in the

other four best models. Although lunar illumination, tide and fish TL were selected in

models 3–5, maximum likelihood tests showed no significant differences between these

and model 2, indicating that flow and temperature were by far the most influential

environmental variables. Predictions from model 2 indicate that both variables are linked

with a downstream shift in the population of R. sarba. Notably, temperature increases

from 12.5 to 22.5 °C are predicted to cause a downstream movement of the population by

c. 3 km (Fig. 5.18b), equivalent to a shift from the middle to lower estuary.

(a) Model 1 (distance ~ month) (b) Model 2 (distance ~ WST)

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Figure 5.17 Average weekly (a) station residency indices (RI) and (b) location upstream

from the estuary mouth (±SE; blue shading) of Rhabdosargus sarba between August

2015 and April 2016.

Table 5.9 (a) Mixed effects models examining the influence of freshwater flow (flow),

water temperature (temp), month of the year, weeks since tagging (WST), fish length (TL)

and distance upstream (dist_up) on the weekly residency (RI) of individuals of

Rhabdosargus sarba at the station nearest to their tagging location. Models are ranked by

ΔAICC and were compared to the null model ‘RI ~ 1 + (1|ID) + (1|station)’. (b) Model

summaries for the two best fit (lowest AICC) models. Positive coefficients indicate an

increase in residency and negative coefficients indicate a decrease in residency.

(a) # model Df logLik AICC ΔAICC weight P

1 RI ~ temp * dist_up 6 −34.99 82.68 0 1 <0.001

2 RI ~ TL + WST 5 −43.04 96.59 13.91 0 <0.001

3 RI ~ WST 4 −45.02 98.37 15.69 0 <0.001

4 RI ~ WST + temp 5 −44.42 99.33 16.66 0 <0.001

5 RI ~ flow + WST 5 −44.46 99.42 16.74 0 <0.001

6 RI ~ flow * dist_up 6 −46.7 106.11 23.43 0 <0.001

7 RI ~ temp 4 −50.62 109.58 26.9 0 <0.001

8 RI ~ month 11 −42.9 110.1 27.43 0 <0.001

9 RI ~ flow + temp 5 −50.52 111.54 28.87 0 <0.001

10 RI ~ flow 4 −54.83 118 35.32 0 <0.001

11 RI ~ TL 4 −63.6 135.53 52.85 0 0.098

12 NULL 3 −64.97 136.13 53.46 0 1

(b) Estimate SE Z P

m1 (Intercept) −2.0695 1.1003 −1.881 0.06

temp −0.7714 0.242 −3.188 0.001

dist_up 0.5653 1.1279 0.501 0.616

temp × dist_up 0.9387 0.2317 4.051 <0.001

m2 (Intercept) −2.7427 0.9619 −2.851 0.004

TL 1.9349 1.0084 1.919 0.055

WST −1.1993 0.2823 −4.249 <0.001

Riv

er

Mid

dle

Estu

ary

Lo

we

r E

stu

ary

Station residency

Population location

(a)

(b)

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Table 5.10 Mixed effects models examining the influence of freshwater flow (flow),

water temperature (temp), tidal height (tide), lunar illumination (lunar), month of the year,

weeks since tagging (WST) and fish length (TL) on the weekly distance upstream of

individuals of Rhabdosargus sarba. The top 5 models (ranked by ΔAICC) from a full set

of 26 candidate models are shown. All models were compared to the null model ‘distance

~ 1 + (1|ID)’.

# model df logLik AICC ΔAICC P 1 distance ~ month 11 −179.42 383.09 0 <0.001 2 distance ~ flow + temp 5 −199.59 409.67 26.58 <0.001 3 distance ~ flow + temp + lunar 6 −199.39 411.46 28.38 <0.001 4 distance ~ flow + temp + TL 6 −199.43 411.53 28.45 <0.001 5 distance ~ flow + temp + tide 6 −199.59 411.85 28.77 <0.001

Figure 5.18 The predicted weekly distance upstream of individuals of Rhabdosargus

sarba (a) during each month of the year from August to April, and (b) under various

temperature and flow conditions, as estimated by the best fit mixed effects models, #1

and #2, respectively, in Table 5.10. Error bars and shaded areas represent SE.

5.4 DISCUSSION

The tracking of Acanthopagrus butcheri, Platycephalus speculator, Rhabdosargus sarba

and Chrysophrys auratus using acoustic telemetry has provided detailed insight into the

ways in which these key fishery species use the Walpole-Nornalup Estuary, specifically

with respect to their estuarine dependency, intra-estuarine distribution patterns and levels

of mobility and site fidelity. Distribution patterns of the four study species differed

markedly, highlighting the divergent ways in which these species use estuaries. To my

knowledge, this is the first multispecies tracking study in an estuary on the south coast of

WA, and the first to use telemetry to quantify the movements of P. speculator. It is one

of only a few estuarine tracking studies of teleosts state-wide. The resulting tracking data

have enabled relationships between fish distributions and key environmental and

biological drivers to be assessed continuously for up to two years, providing a far greater

(a) Model 1 (distance ~ month) (b) Model 2 (distance ~ flow + temp)

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resolution of understanding than is achievable using traditional capture-based measures.

The study has further identified areas of the Walpole-Nornalup Estuary that may be of

greatest importance to each species, where and when fish could be most vulnerable to

fishing activity, and potential shifts in fish distribution that may occur under forecast

climate changes.

This work compliments a range of fish tracking studies in temperate estuaries from the

east coast of Australia (Hindell, 2007; Sackett et al., 2007; Hindell et al., 2008; Tracey et

al., 2011; Walsh et al., 2011; Taylor et al., 2014; Gannon et al., 2015; Payne et al., 2015;

Williams et al., 2017) and globally (Hartill et al., 2003; Grothues & Able, 2007; Childs

et al., 2008; Bennett et al., 2012; Able et al., 2014; Amorim et al., 2017; Grant et al.,

2017a; Grant et al., 2017b; Le Pichon et al., 2017).

5.4.1 Estuarine dependence and connectivity with the marine environment

Knowledge of how fish move between estuaries and marine environments is fundamental

to understanding their estuarine dependence and the degree of connectivity between

estuarine and marine populations (Able, 2005; Ray, 2005; Potter et al., 2015a). In the

present study, 26, 53 and 64% of tagged P. speculator, C. auratus and R. sarba,

respectively, emigrated to the sea, while no A. butcheri left the system and were thus

entirely estuarine dependent. Migrations were one-way for the first two of these species,

although several R. sarba which left the estuary returned. The migratory patterns for C.

auratus and R. sarba, and lack of migration for A. butcheri, were in line with the posed

hypotheses and, for the latter species, matched the outcomes of other comparable tracking

studies (Hindell, 2007; Hindell et al., 2008; Sakabe & Lyle, 2010; Williams et al., 2017).

However, the findings for P. speculator contrasted with the hypothesis that they would

not leave the system.

Platycephalus speculator is typically regarded as a marine and estuarine species (Potter

& Hyndes, 1999), although on the south coast of WA it was anticipated that it would be

more likely to complete its life cycle solely within estuaries due to the high wave exposure

of the coast (Coulson et al., 2017). Tracking showed that one quarter of tagged P.

speculator left the Walpole-Nornalup and did not return. Given that each emigrating fish

had more than one year of tag battery life remaining, these findings clearly demonstrate

the use of both estuarine and marine environments by this species on the south coast, and

moreover, population mixing between these areas. It is thus also relevant that while the

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majority of P. speculator displayed very little intra-estuarine movement (see section

5.4.3), three fish tagged in the Frankland River (ID34090, 38202 and 34102) were highly

mobile and left the system 3–4 months after tagging. Given their mobility and rapid

emigration, these may represent individuals from the marine population, which enter the

estuary opportunistically for short periods, possibly in an exploratory manner, before

returning to sea.

Rhabdosargus sarba and C. auratus are regarded as marine estuarine-opportunists in

south-western Australia (Potter & Hyndes, 1999), i.e. species that regularly use estuaries

but spawn in the marine environment (Potter et al., 2015a). All five R. sarba that left the

system did so during November/December 2015, and four fish returned to the estuary

shortly after (<12 hrs to 40 days). Two of the latter individuals (ID34099 and 38204),

which were tracked for over a year, also migrated to sea again during December 2016

(Fig. 5.2). While no data are available on the precise spawning time for this species on

the south coast of WA, peak spawning along the west coast occurs in late winter/spring

when marine water temperatures range 18–20 °C (Hesp, 2003; Hesp & Potter, 2003). Sea

surface temperatures adjacent to the Walpole-Nornalup fell within this range during

November/December (IMOS, 2017). As all R. sarba were considered mature based upon

their length at tagging, it is probable the observed movements were spawning migrations.

The return of several fish and the high abundances of both juveniles and adults in the

system (see Chapter 2), indicates that this species relies heavily upon the estuary at all

life stages except during spawning and very early development.

The five largest individuals of C. auratus made one-way migrations out of the estuary

within 150 days, and time since tagging was shown to have a negative effect on both

estuarine residency and fish location upstream. Unlike R. sarba, it appears that this sparid

only remains in the estuary for short periods before migrating to sea as they grow. This is

supported by findings from extensive netting in this system (Potter & Hyndes, 1994; and

see previous Chapters), during which very few C. auratus >300mm were recorded. Fish

migrate between habitats primarily for food, shelter or spawning (Bell & Worthington,

1993). Given that all the tagged individuals of C. auratus in the current study were still

several years from spawning (with maturity occurring at c. 586–600 mm, or

approximately seven years of age; Wakefield et al., 2015), it is likely that the observed

movements to the marine environment were for food and/or shelter. The diet of C. auratus

changes markedly with growth, shifting from smaller invertebrates to larger, harder-

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bodied prey (e.g. crabs and echinoderms; French et al., 2012; Usmar, 2012), which are

presumably more abundant in the marine environment. Moreover, larger individuals of

C. auratus have been shown to be closely associated with rocky reef habitat (Parsons et

al., 2003; Harasti et al., 2015; Fowler et al., 2017), which is far more complex and

extensive in the marine environment than in the estuaries of WA.

5.4.2 Intra-estuarine habitat use and drivers of distribution

In support of the proposed hypotheses, A. butcheri used extensive areas of the estuary,

with fish detected at all stations except LN3 at the estuary mouth. This species spent the

greatest proportion of time in the Frankland River and displayed moderate to high

residency at all riverine stations except the most upstream receiver. Platycephalus

speculator, C. auratus and R. sarba, in comparison, were predominantly recorded in the

basins of the estuary and the lower Frankland River, and essentially absent from the Upper

Frankland River. Given the marine affinities of the latter three species, these findings

align with the fact the lower to middle estuary is highly marine-influenced and less

environmentally variable than the upper reaches of the system (see Chapter 2). Finer-

scale habitat features, including water depth, structural complexity and/or sediment type,

were also shown to influence the species distributions and inter-regional residency

patterns (see below).

Based on the existing understanding of the growth and reproductive biology of A. butcheri

in south-western Australia (Sarre, 1999; Sarre & Potter, 1999), it was further

hypothesized that individuals of this species would migrate upstream during late spring

and early summer (October–December) to spawn. Tracking data provided clear evidence

of such migrations in the Walpole-Nornalup, and a general upstream shift into the Upper

Frankland River. Mixed effects models showed that these movements were closely

related to warming water temperatures, and that increases in river flow caused

downstream shifts in the distribution of A. butcheri. Freshwater flows also caused

downstream shifts of P. speculator, C. auratus and R. sarba, and may have triggered

emigrations to sea of the former two species.

Intra-estuarine habitat use

Habitat complexity is an important determinant of resource availability and has been

widely linked to the distribution of estuarine fishes (Whitfield, 1983; Martino & Able,

2003; Sheaves & Johnston, 2009; Loureiro et al., 2016; Amorim et al., 2017). In the

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present study, the residency of A. butcheri, C. auratus and P. speculator was significantly

higher in estuarine areas with greater structural complexity, and specifically wooden

structure/snags for A. butcheri and submerged rock/reef areas for the latter two species.

Such structures may provide shelter from predation and are hard stable surfaces on which

macroalgae, bivalves, crustaceans and other potential food sources can live (Gratwicke &

Speight, 2005; Schneider & Winemiller, 2008; Kovalenko et al., 2012). Other acoustic

tracking studies have reported similar associations with structure among A. butcheri on

the lower-west coast of WA (Watsham, 2016; S. Beatty, Murdoch University, unpubl.

data), and C. auratus in South Australia (Fowler et al., 2017). Differences in the structural

preferences of A. butcheri and C. auratus may reflect the diets of these species and

variation in the types of prey associated with rocky vs wooden substrates (McGuinness

& Underwood, 1986; McGuinness, 1989). Thus, juvenile C. auratus (150–300 mm TL)

are essentially carnivorous, feeding predominately on small crabs, shrimp, bivalves and

polychaetes (Usmar, 2012), while similar sized A. butcheri are highly omnivorous and

consume large volumes of plant material in this system (Sarre et al., 2000).

Unlike the above bentho-pelagic sparids, P. speculator is a benthic species that burrows

into and is well camouflaged against soft substrata (Gomon et al., 2008; Coulson et al.,

2015). For this platycephalid, it is thus unlikely that structurally complex habitat would

be advantageous for shelter, although the observed increases in residency may reflect

greater prey availability in the proximity of such structures. It should be noted, however,

that several rocky areas in the Nornalup Inlet were also immediately adjacent to some of

the only areas of the system with deeper (2–3 m) sand substrata, which is the preferred

habitat of P. speculator (Gomon et al., 2008; Chatfield et al., 2010). Unfortunately, the

spatial resolution of the acoustic array did not allow the location of tagged fish to be

distinguished between the above two habitat types.

Differences in water depth were also linked with the intra-estuarine distributional patterns

of particularly A. butcheri, with this species spending far more time in shallow than deep

habitats, and especially in the lower Frankland River and on sand flats near the mouth of

this tributary. Additionally, except for one individual of P. speculator, no fish of any

species spent any considerable period of time in the deeper waters (4–6 m) of central

Nornalup Inlet. Such findings may reflect the depauperate invertebrate communities in

these deeper unconsolidated sediments (see Chapter 4), or the propensity towards hypoxia

of these deeper bottom waters in microtidal estuaries (Crowder & Eby, 2002; Tyler et al.,

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2009; Tweedley et al., 2016a), which may further reduce prey availability and/or cause

mortality or physiological stress among fishes (Pihl et al., 1991; Pihl, 1994; Buzzelli et

al., 2002; Small et al., 2014).

Seasonal changes in fish distribution

Daily, weekly and monthly changes in residency patterns and/or upstream location were

detected for all four study species, reflecting the highly dynamic nature of estuarine

environments and the biology of those species. Thus, all tagged A. butcheri migrated

upstream into the Upper Frankland River during spring and early summer, which

coincided with the warming of estuarine waters following their minimum in late winter.

These migrations corresponded with the peak spawning period of A. butcheri in the

Walpole-Nornalup (i.e. October–December; A. Cottingham, Murdoch University,

unpubl. data), and were similar those observed on the east coast of Australia (Hindell et

al., 2008; Sakabe & Lyle, 2010; Tracey et al., 2011; Williams et al., 2017).

Freshwater flows, in contrast, caused A. butcheri to move downstream, which also

concurs with the above tracking studies from the east coast of Australia and circumstantial

evidence from south-western Australia (Sarre, 1999). While A. butcheri are highly

euryhaline and can tolerate fresh to hypersaline waters (Sarre & Potter, 1999; Hoeksema

et al., 2006; Chuwen, 2009), brackish waters with salinity of 10–25 appear optimal (Sarre,

1999; Hindell et al., 2008; Sakabe & Lyle, 2010). Thus, in winter and early spring when

river flow to the Walpole-Nornalup was high (i.e. >10 m3 s−1), salinity in the Upper

Frankland River ranged only from 0–10 (data not shown). These changes coincided with

an increase in the residency of A. butcheri in the lower river and basins of the system,

while the reverse was generally true once flows subsided. The notable upstream

movement during late autumn/early winter of 2015 (April–June), which followed a

prolonged summer dry period (four months with <0.3 m3 s−1 flow), may also reflect a

tendency towards brackish conditions and avoidance of highly marine downstream

waters. It should be noted, however, that a number of A. butcheri were tagged in the

middle/upper estuary during May, thereby enhancing the apparent magnitude of

population shift.

Tidal height also significantly influenced the distribution of A. butcheri, with fish located

further upstream during high tides. Close associations between tidal amplitude/direction

and the upstream migration of A. butcheri have also been documented in a south-eastern

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Australian estuary (Sakabe & Lyle, 2010), and also for several other species in microtidal

South African estuaries (Attwood et al., 2007; Childs et al., 2008; Næsje et al., 2012).

Sakabe and Lyle (2010) proposed that A. butcheri may be moving upstream to feed on

intertidal mud flats which are inaccessible during lower tides. Although there are few

intertidal flats in the Walpole-Nornalup, high spring tides (e.g. 1.2–1.6 m) cause

inundation of riparian vegetation (e.g. Juncus spp., Melaleuca spp.) in the upper riverine

reaches, which may provide rare feeding opportunities for A. butcheri. Moreover, fish

may also be following an incursion of saline water or ‘salt wedge’ that pushes further

upstream during higher tides (Næsje et al., 2012).

Seasonal patterns in the distribution of R. sarba were almost in complete contrast to those

of A. butcheri. As temperatures increased, this sparid moved downstream and/or migrated

to sea. As described earlier, these movements correlate closely with the spawning patterns

of this species. Freshwater flows were also linked with a downstream shift of R. sarba,

with fish moving from the Lower Frankland River into the Nornalup Inlet following

substantial flows in August 2015 and January 2016. Similar downstream movements in

response to both warming temperatures and increases in flow have been observed for

another species of Rhabdosargus, R. holubi, in a South African Estuary (Grant et al.,

2017a).

The distribution of C. auratus was less clearly aligned with environmental influences,

being more strongly related to time at liberty. Following tagging, fish typically remained

in the Lower Frankland River for several weeks to months, before moving downstream

into the Nornalup Inlet or migrating to sea. Upstream migrations were not evident,

although residency in the Lower Frankland was greater during warmer periods and

decreased after high flows. It is possible that the timing of C. auratus leaving the system

was related to increased freshwater fluxes, given that one fish emigrated during a high

flow (10–15 m3 s−1) event in August 2015, and two did so <7 days after heavy rainfall in

January 2016. Moreover, two C. auratus also emigrated immediately before a high

rainfall event in April 2016, possibly representing pre-emptive movements driven by

changes in barometric pressure, as has been proposed by various other researchers

(Heupel et al., 2003; Sackett et al., 2007; Henderson et al., 2014).

Model findings suggested that temperature, flow and time since tagging were the

predominant drivers of changes in the residency of P. speculator. Individuals tended to

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stay close (<1 km) to their release station (see next section), with the most notable changes

in residency reflecting emigration of fish from the estuary. Of the five P. speculator that

left, two did so in August/September 2015, coinciding with a prolonged high flow event

(flow rates of 5–15 m3 s−1 over a month; Fig. 5.11a), and three left between December

and March, the known spawning period of this species (Hyndes et al., 1992; Coulson et

al., 2017) and when water temperatures were at their maximum (20−25 °C).

5.4.3 Site fidelity and mobility

As hypothesised, P. speculator was generally far less mobile than the three sparid species,

typically spending the majority of time at one receiver station and travelling on average

<10 km over a tracking period of 344 days (0.036 km a day; Table 5.3). While five P.

speculator left the estuary, two showed very high intra-estuarine site fidelity (up to 150

days at a single station) prior to emigrating. Acoustic tracking of Eastern Bluespotted

Flathead Platycephalus caeruleopunctatus (Fetterplace et al., 2016) and Sand Flathead

P. bassensis (Tracey et al., 2011) has similarly shown high site attachment, with

infrequent long-distance migrations. Comparatively, the tagged sparids were regularly

detected at multiple receivers, moved between several or all regions of the estuary, and

travelled on average 0.27–0.62 km a day, equating to as much as 830 km over 656 days

in the case of A. butcheri. The far lower mobility of P. speculator compared to the three

sparids likely reflects the distinct ways in which these species obtain resources, with the

former being ambush predators (Humphries et al., 1992; Gomon et al., 2008; Coulson et

al., 2015), whereas A. butcheri, C. auratus and R. sarba actively search for food items

(Blaber, 1984; Sarre et al., 2000; Hindell et al., 2008; French et al., 2012; Usmar, 2012;

Williams et al., 2017).

Although generally mobile, a number of A. butcheri and several R. sarba and C. auratus

appeared to exhibit clear site preferences. Notably, individuals of A. butcheri and R. sarba

often travelled vast distances (several hundred km in total) but regularly returned to a

particular location. One fish, A. butcheri ID18912, despite travelling >150 km over 269

days, was caught by a fisher at the exact location it was initially released. Similarly, R.

sarba ID38204 and 34099 made several return trips to the lower estuary and to sea, but

spent the majority of time in the region where they were tagged (LFR and WI,

respectively). Interestingly, R. sarba on the east coast of Australia have shown little

homing ability (Taylor et al., 2016), yet the latter fish left the Walpole Inlet and spent 40

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days at sea, then returned to the Walpole Inlet within 12 hours of re-entering the estuary.

Site familiarity may be advantageous for accessing food and/or shelter (Grant et al.,

2017b) and clear site fidelity has previously been observed among A. butcheri and C.

auratus elsewhere in Australia and New Zealand (Hartill et al., 2003; Parsons et al., 2003;

Harasti et al., 2015; Williams et al., 2017), and among R. holubi in South Africa (Grant

et al., 2017b).

5.4.4 Niche overlap and potential future shifts

Knowledge of the spatial and temporal distribution of species with similar morphologies

and feeding modes can provide insight into resource partitioning and overlap (Matich et

al., 2017; Matley et al., 2017). Among the four study species, the greatest distributional

overlap throughout much of the year occurred in the Lower Frankland River and Nornalup

Inlet, and A. butcheri, R. sarba and C. auratus exhibited further, finer-scale spatial

overlap in these regions. As all three sparids are opportunistic feeders, bentho-pelagic and

abundant at lengths of 150–300 mm, there is potential for considerable food resource

competition.

As highlighted earlier, both R. sarba and C. auratus were displaced downstream when

freshwater flows occurred. Current climate predictions for SWA indicate a reduction of

winter rainfall by up to 45% towards the end of this century (Hope et al., 2015), which

will result in greater saline incursions further upstream and for longer throughout the year

(Hallett et al., 2018). Under such conditions, R. sarba and C. auratus may remain further

upstream for longer throughout the year, thus increasing their habitat overlap with A.

butcheri. As a species that is essentially confined to the system, increased competition

from marine immigrants may have considerable negative effects on the population of A.

butcheri, e.g. reduced growth and/or body condition (Byström et al., 1998; Fullerton et

al., 2000). Being the most targeted fishery species in the estuary (Smallwood & Sumner,

2007), this, in turn, may reduce the recreational fishing amenity of the system.

Climate predictions also suggest an increased frequency and intensity of severe weather

events, such as summer storms (Hope et al., 2015). Tracking showed that A. butcheri

moved into the upper estuary during their spawning period and downstream in response

to freshwater flows. High and unseasonal flows during summer thus may disrupt

spawning activity, and moreover, cause larvae and eggs to be flushed downstream before

they have developed (Williams et al., 2017). For marine species such as C. auratus, these

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flows may cause early emigration from the system, which, in turn, may reduce future

productivity of broader marine fisheries (see below).

5.4.5 Implications for fisheries management

The residency and movement data collected in this study provide valuable insights on the

vulnerability of the four study species to fishing activities, and which habitats are key to

sustaining their stocks. These findings have fundamental implications for local fisheries

management, and more broadly for promoting productive marine fisheries in the region.

The very high capture rate of tagged A. butcheri by recreational anglers (up to 39% during

the 2.5 year study period) provides evidence of high fishing mortality on this species.

Such vulnerability to capture may be due to their highly mobile nature, and therefore,

increased probability of encountering fishers (Rudstam et al., 1984; Millar & Fryer,

1999). Tracking showed that fish regularly migrate from the basins into the Frankland

River, particularly during their spawning period in late spring and early summer. As the

population is concentrated into a narrower area, their vulnerability to capture may further

increase, and it appears that several A. butcheri (ID18893, 18895 and 18898) were caught

making migrations upstream. Given these findings, as well as recent declines in the

growth rate of A. butcheri and the abundance of larger individuals (see Chapter 4),

changes to management may be required to ensure the sustainability and amenity of this

recreational fishery. Targeted spatio-temporal fishing restrictions which protect spawning

aggregations are effective fisheries management tools (e.g. Erisman et al., 2017) and the

movement data collected in this study provides a sound basis for such an approach to be

implemented for A. butcheri in the Walpole-Nornalup.

Species such as P. speculator which are highly site attached, or C. auratus which are

strongly associated with a select habitat type (i.e. rock/reef), may be more vulnerable to

localised habitat loss than fishing pressure. For the benthic P. speculator, any future

deterioration in sediment quality in deeper waters due to prolonged hypoxia associated

with climate changes and anthropogenic development (see Chapter 4) would clearly

reduce available habitat. Similarly, as only small areas of rock and biogenic reef exist

throughout the Nornalup Inlet (Semeniuk et al., 2011), their loss (e.g. through dredging

or sedimentation) may have significant consequences for the viability of the system as a

nursery for C. auratus. Studies on the east coast of Australia have shown that 89% of

adult snapper caught in a marine fishery originated from estuarine nursery habitats in the

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local region (Gillanders, 2002). Impacts on the populations of C. auratus within Walpole-

Nornalup could thus have major implications for south coast marine fisheries. In contrast,

there is potential for estuarine nursery habitat for this sparid to be enhanced through the

deployment of oyster racks or artificial reef (Folpp et al., 2011; Lowry et al., 2014).

5.4.6 Limitations and recommendations

Whilst this study has provided a substantial amount of new knowledge, it does have

several limitations. Firstly, it should be noted that tagged fish represented only a single

life stage of each species, i.e. adult or juvenile. Among C. auratus, tagging adults in the

system was not possible as they are only very rarely recorded in estuaries. With respect

to the other study species, only larger fish were targeted to allow questions around

spawning movements to be answered. To gain further ecological understanding of these

species the tagging of juveniles would clearly be beneficial. Given the site fidelity of

individuals, another limitation was the breadth at which fish were tagged. Attempts were

made to catch and tag fish throughout the estuary, but C. auratus were only able to be

caught and tagged in the LFR, which may have increased the apparent importance of this

region for this species.

It should also be noted that fish that left the estuary were deemed to be at sea until the

expiry of their transmitter battery life. Indeed, the possibility cannot be excluded that fish

either died or were predated in the marine environment, or entered a nearby estuary.

However, as all nearby estuaries (125 km east and 180 km west) are seasonally closed

(Brearley, 2005), immigration would be inhibited for much of the year. For future studies,

additional receiver stations would ideally be deployed in the marine waters adjacent to

the estuary and at the mouths of all neighbouring systems.

In summary, the use of acoustic tracking technology has significantly improved our

understanding of how key fishery species use the Walpole-Nornalup Estuary and respond

to environmental changes. The results highlight differing levels of estuarine dependency

and vulnerability to fishing activity and climate change, which may assist managers to

determine how best to sustain populations.

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Chapter 6: General discussion

This thesis has examined how the structural and functional characteristics of estuarine

fish fauna reflect environmental, biological and anthropogenic drivers operating from

bioregional to intra-estuarine scales, and change over diel to inter-decadal timeframes.

Multiple fish monitoring techniques were combined to assess change at individual (fish

movements; Chapter 5), population (length composition; Chapters 3 & 4), community

(e.g. diversity, species and guild composition; Chapters 2–4) and ecosystem (Fish

Community Index, FCI; Chapter 4) levels of biological organisation. This provided a

comprehensive understanding of the dynamics of the fish ecology in the Walpole-

Nornalup Estuary, a unique and socially valuable marine park, and enabled comparisons

with other estuaries throughout south-western Australia (SWA) and temperate microtidal

regions globally. A study of this breadth has not been previously undertaken in any other

SWA estuary. Moreover, while several studies globally have employed both fish

abundance and acoustic telemetry data to examine species-specific estuarine use and

responses to environmental change (e.g. Farrugia et al., 2011; Bennett et al., 2012; Stehlik

et al., 2017), this study is the first, to my knowledge, to concurrently examine responses

of the entire fish community. This is also the first multi-species tracking study in a SWA

estuary, and highlights the divergent estuarine use of several fishery important species

and their vulnerability to fishing activity and environmental change. When incorporated

into management and policy, such information has extensive benefits to sustaining fish

stocks (see section 6.2, and also Crossin et al. [2017] for a global review).

With regards to the main findings of this thesis, the permanently-open Walpole-Nornalup

was shown to have a more diverse and species rich fish fauna than nearby systems which

intermittently close to the sea (Chapter 2). This reflected a highly marine influenced

estuarine environment and the presence of numerous marine-associated fish species and

individuals. Nonetheless, the reverse was true when the Walpole-Nornalup was compared

to permanently-open systems on the lower west coast of the State, which reflected broad-

scale biogeographic patterns and a poleward decline in marine species diversity. Similar

patterns have been observed in other temperate estuaries on the east coast of Australia

and elsewhere globally (Pease, 1999; Nicolas et al., 2010b; Whitfield et al., 2017b).

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At an intra-estuarine scale, most structural and functional attributes of the fish fauna

differed between estuarine regions, and from a temporal perspective, also between day

and night, seasons and years. Regional, seasonal and inter-annual shifts closely reflected

habitat variation (e.g. sediment type, physical structure, salinity and water temperature),

several aspects of which were driven primarily by temperature, rainfall, river flow and

proximity to the estuary mouth (Chapter 2). In contrast, at a diel scale, patterns primarily

reflected nocturnal/diurnal changes in fish activity and predator–prey interactions

(Chapter 3).

Acoustic tracking of Acanthopagrus butcheri, Chrysophrys auratus, Rhabdosargus sarba

(Sparidae) and Platycephalus speculator (Platycephalidae) provided more detailed and

continuous data on the distributions of these recreationally and commercially important

species (Chapter 5). This revealed marked differences in their estuarine-marine

connectivity, intra-estuarine use and mobility. Acanthopagrus butcheri did not leave the

estuary, but were highly mobile and used vast areas of the system from the lower to upper

reaches. In contrast, the latter three species were essentially confined to the lower/middle

reaches, and marine emigration was detected among 26–63% of individuals. Drivers of

these patterns, which were mixed among species, principally reflected spawning

behaviours, habitat preferences, feeding modes and responses to water temperature and

freshwater flow.

Another key finding of this thesis was documenting how accelerated warming and drying

of the SWA climate over recent decades has affected the environmental and ichthyofaunal

characteristics of the Walpole-Nornalup (Chapter 4). Thus, since the 1990s, marine and

warm-water associated species have significantly increased in abundance, while the

reverse was true among large benthic, temperate and freshwater associated fishes,

including several of fishery importance. These changes were concurrent with rapid

warming of sea and air temperatures and halving of freshwater flows to the system,

resulting in a more marine and warmer estuarine environment. Long-term degradation of

the deeper offshore waters of the system, but not the shallows, was also suggestive of

increasing hypoxia in the benthic zone due to reduced flushing and nutrient accumulation.

Unfortunately, absence of historical dissolved oxygen data for the system prevented any

further conclusions. A lack of appropriate monitoring of biota and environmental drivers

is an ongoing problem in Australian estuarine management, which needs to be addressed

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to better understand ecological changes and predict future trends (section 6.2) (Hallett et

al., 2016b).

Observed fish faunal responses to short-term environmental fluctuations (e.g. fresh water

flow events, seasonal temperature change) at both the individual (Chapter 5) and

community levels (Chapter 2) have also provided insights into future shifts that are likely

to occur under continued warming and drying of the SWA climate. Marine-associated

species are likely to remain within the Walpole-Nornalup for longer throughout the year

and penetrate further upstream, while temperate species are likely to continue to decline

in abundance due to lower recruitment success and/or ocean emigration. Given that

anthropogenically-induced climate change is among the most widespread and intense

threat to estuaries worldwide (Feyrer et al., 2015; Cloern et al., 2016; Robins et al., 2016;

Gabler et al., 2017), and that similar environmental changes and fish faunal responses are

occurring in other Mediterranean regions (e.g. Europe [Pasquaud et al., 2012; Chevillot

et al., 2016], North America [Cloern et al., 2011] and South Africa [James et al., 2013;

Whitfield et al., 2016]), the current findings may also have broader implications for

understanding future changes in other temperate estuarine systems globally.

In the remainder of this discussion, I firstly evaluate the benefits and limitations of the

various monitoring approaches employed throughout this thesis, with recommendations

for their use in estuaries elsewhere (section 6.1). Finally, I reiterate key implications of

this research for the management of the Walpole and Nornalup Inlets Marine Park

(WNIMP) and propose a comprehensive and cost-effective fish monitoring regime

tailored for the system (section 6.2).

6.1 INDIVIDUAL TO ECOSYSTEM-LEVEL APPROACHES FOR

MONITORING ESTUARINE FISH FAUNA

All techniques for sampling or monitoring of fish have their own inherent advantages and

limitations. Estuaries present further challenges for the collection of robust spatio-

temporal data in that abundant species are often small and/or cryptic and estuarine

environments are highly heterogeneous and dynamic. The monitoring regime of the

present study, which combined several netting techniques and acoustic telemetry, allowed

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detailed examination of fish fauna at multiple levels of biological organisation including

an assessment of ecosystem health.

In general, the various approaches were complementary, although differed in their

breadth, sensitivity and continuity. For assessing the fish faunas of the WNIMP and

indeed those of any other estuary, the application of all available approaches would

clearly maximise data availability. However, in most cases this is unfeasible due to

resource and time restraints. Effective and cost-efficient monitoring should therefore

employ the approach or approaches that provide robust data and are best suited to the key

research questions and management objectives. On the basis of the findings of this thesis

and other studies which have employed multiple complementary approaches to assess

estuarine fish fauna (e.g. Richardson et al., 2011; Stehlik et al., 2017; Valesini et al.,

2017), Table 6.1 summarises the key benefits and limitations of monitoring at the

individual, population, community and ecosystem levels, with respect to both technical

aspects of data collection and the type of information provided.

For example, acoustic tracking of individuals provided the most detailed and continuous

data for understanding how fish used the estuary, including movements in responses to

temperature and flow, the timing and frequency of migrations between estuarine regions

and the ocean, and where fish spent the most time (Chapter 5). Such detail is imperative

for protecting key habitats and modelling fish responses to forecast climate changes. The

usefulness of acoustic tracking, however, is often limited by the number and type of fish

that can be tagged (e.g. an inability to tag juveniles of many species). In contrast,

community-level approaches (e.g. employing netting), while less spatio-temporally

continuous and more labour intensive, allow the entire composition to examined,

including very small and cryptic species. In the Walpole-Nornalup, community-level

assessments revealed shifts in the structure and function of fish fauna in response to both

short- (e.g. day vs night and seasonal changes) and long-term (interdecadal)

environmental drivers (Chapters 2–4).

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Table 6.1 A comparison of the key benefits and limitations of various approaches

employed to monitor fish in estuaries. These consider sampling aspects, data

requirements, interpretation of findings and breadth of knowledge provided.

Benefits Limitations

Tracking individual fish (e.g. acoustic telemetry)

• Provides detailed and spatio-temporally continuous movement data which can: o highlight behavioural patterns, o enable direct examination of fish

responses to environmental variables (e.g. flow, temperature, tide),

o detect changes in fish distribution at different life stages (e.g. fish size, spawning period).

• Monitoring is relatively non-invasive and requires little labour.

• Sample size limited due to feasibility and costs of tracking a large number of animals.

• Type and size of fish able to be tracked potentially limited by tracking equipment (e.g. tag size).

• Potential biases from the timing and location of tagged fish.

Assessing population dynamics (e.g. length and age composition, reproductive biology)

• Enables quantification of impacts (e.g. fishing, toxins, environmental change) that are often not detected by broader scale assessments.

• Can explore spatio-temporal patterns among a broad range of size classes including very small individuals.

• Multiple sampling approaches can be combined (e.g. nets, line fishing).

• Sampling is labour intensive and potentially destructive.

• Requires large numbers of fish to be caught and often euthanased.

• Generally limited to key species.

• May lack spatio-temporal continuity and detail.

Characterising community composition (e.g. species richness, diversity, species and guild composition)

• Provides information on entire fish assemblage, allowing trends from multiple species with different life cycle traits, feeding modes, habitat preferences and environmental tolerances to be simultaneously understood.

• Can identify key species driving changes and interactions among species.

• Fish can often be identified, counted and released in the field.

• Fundamental to ecosystem-based fisheries management.

• Sampling is labour intensive and potentially destructive.

• Requires standardised sampling gear (e.g. net type and size), regimes (e.g. time of day) and effort (e.g. number of replicates, net soak time) to enable reliable comparisons over space and time.

• Limited ability to detect subtle changes among a single species (e.g. size and growth rate declines).

• Difficult to tease apart responses to natural vs anthropogenic drivers of observed responses.

Application of multi-metric indices of ecosystem health (e.g. Fish Community Index; FCI).

• Encompasses responses of entire ecosystem to change.

• Report card results easy to communicate to a wider audience.

• May detect ecosystem changes not detected by traditional water quality indicators.

• Subject to the same limitations as the community level approach on which it is based.

• Requires robust baseline/reference conditions.

• Negative changes in some metrics can be offset by positive changes in others, resulting in no detectable change in overall condition.

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Similarly, the FCI, which simplifies the complex structural and functional components of

estuarine fish faunas into easily interpretable measures for tracking and reporting

ecosystem health (Hallett, 2014), detected changes in the health of the Walpole-Nornalup

between the historical (mid-1990s) and contemporary sampling periods. However, the

FCI is insensitive to more subtle changes in the fish fauna, such as size declines among

targeted species (e.g. A. butcheri and Arripis georgianus). Assessment only at the

ecosystem level is thus inappropriate if detailed knowledge of valuable fish stocks is

required. A further limitation of the FCI is the need to define appropriate reference

conditions for each component metric, which may require extensive and costly sampling

(Tweedley et al., 2017). To maximise the reliability and interpretability of these indices,

data should also be collected under uniform sampling effort (Pérez-Domínguez et al.,

2012). Despite best attempts to correct for sampling bias, this posed an issue in the present

study when comparing index scores from the contemporary period to those historically,

as sampling practices that were once widely accepted are no longer commonplace due to

ethical considerations (e.g. overnight gill net sets). For future application of the FCI in

the Walpole-Nornalup and other estuaries, a consistent fish community monitoring

sampling regime is thus crucial.

6.2 IMPLICATIONS AND FUTURE DIRECTIONS FOR MANAGEMENT OF

THE WALPOLE-NORNALUP INLETS MARINE PARK

6.2.1 Ecological and social values, their threats and potential future changes

The Walpole-Nornalup Estuary has a relatively diverse fish fauna compared to many

other estuaries on the south coast of Western Australia, likely reflecting its permanent

connectivity with the sea (Chapter 2). Numerous marine species were recorded, including

more than 20 of fishery importance (e.g. Sillaginodes punctatus, A. georgianus, C.

auratus, Pseudocaranx georgianus, A. truttaceus, Pomatomus saltatrix, P. speculator).

As most estuaries along this coast are seasonally- or normally-closed to the sea, the

Walpole-Nornalup is likely an important nursery for juveniles of these valuable species

in the region. In addition to marine fishery species, the solely estuarine Black Bream A.

butcheri, an iconic recreational species, was abundant throughout the system (Chapter 2).

Acoustic tracking of this sparid showed that although individuals used vast areas of the

system, most migrated upstream into the Frankland River during their spawning period

(Chapter 5). This highlights both the importance of this tributary as a key habitat, and also

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the vulnerability of A. butcheri to fishing activity in the upper tidal reaches of the river

during their spawning period. There is also evidence that the system may be a nursery for

several elasmobranch species including Mustelus antarcticus, Myliobatis tenuicaudatus

and Aptychotrema vincentiana (Chapter 2). Further highlighting the unique ecological

characteristics of the Walpole-Nornalup, day-night shifts among nearshore fish

communities (Chapter 3) differed from those in the nearby Wilson Inlet and estuaries on

the lower west coast of WA (Swan-Canning and Moore). Birds are well recognised

predators in shallow aquatic ecosystems globally (Steinmetz et al., 2003; Žydelis &

Kontautas, 2008; Cowley et al., 2017), and this suggested that in the Walpole-Nornalup,

a shallow, clear and relatively unmodified system surrounded by dense vegetation, top-

down effects from daytime avian piscivory may be exerting considerably greater

influences on estuarine fish fauna.

The accelerated warming and drying of the SWA climate over the past two to three

decades is forecast to continue throughout this century (Chapter 4). As a result,

permanently-open estuaries in the region are predicted to become progressively more

marine, whilst those that are naturally predisposed to isolation from the sea are likely to

close for extended periods (Hallett et al., 2018). Findings of the present study suggest that

marine-associated species will become increasingly abundant in the WNIMP, penetrating

further upstream and remaining in the system for longer throughout the year. As one of

the very few permanently-open estuaries on the south coast, it is thus also likely that the

contribution of juveniles recruiting from the WNIMP to marine fisheries will increase.

Warming and marinisation may also directly benefit fishing within the estuary as valuable

marine species become more abundant.

Despite these potential benefits to local fisheries, climate changes will undoubtedly also

have negative impacts on certain species and aspects of the estuarine environment.

Continued reductions in river flow are likely to induce further degradation of the deeper

waters and potentially cause prolonged and widespread hypoxia, as has occurred in other

SWA systems (Brearley, 2013; Valesini et al., 2017; Cottingham et al., 2018b). This,

coupled with increased salinities, would substantially reduce available habitat for

estuarine and freshwater-associated species. Habitat compression over the past two

decades has been linked to substantial declines in the growth and body condition of A.

butcheri in the Swan-Canning Estuary (Cottingham et al., 2014; 2016; 2018a). Marked

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declines in these biological parameters, and also the abundance of larger fish, have

similarly been documented in the Walpole-Nornalup during the same period (Chapter 4).

Further habitat contractions, in combination with potentially elevated competition from

marine species for resources, may therefore impact the viability of the WNIMP as a

fishery for A. butcheri. Direct impacts of human activities such as fishing and boating

(e.g. reductions in the size and abundance of targeted fish, litter and pollution, bank

erosion, boat noise) would also be expected to intensify as coastal populations and

tourism increase in the area.

Given the above threats to this highly valuable estuary, there is a clear need for effective

management of fish stocks, as well as ongoing monitoring of broader ecological

condition. Sound estuarine monitoring fundamentally requires regularly and consistently

collected data on ecological structure and function, coupled with information on likely

environmental (e.g. water quality parameters) and anthropogenic (e.g. fishing activity)

drivers. Outlined below are several key fisheries management recommendations (section

6.2.2) and a proposed ecological monitoring regime (section 6.2.3).

6.2.2 Management recommendations

Recent declines in the abundance of several key fishery species (Chapter 4) and evidence

of very high fishing mortality on large A. butcheri (Chapter 5) suggest that amendments

to fisheries management in WNIMP may be required. Under current regulations, no areas

of the marine park are closed to recreational rod and line fishing (DEC, 2009). When

appropriately designed, no take marine reserves are a proven conservation tool (Halpern

et al., 2010; Edgar et al., 2014; 2017; Harasti et al., 2018), and sanctuaries closed to all

forms of fishing have been gazetted within other marine parks throughout Western

Australia to sustain fish stocks and preserve biodiversity (e.g. Penn & Fletcher, 2010).

However, given the small physical size of the WNIMP and its highly dynamic fish fauna,

permanent sanctuary zones in the estuary are likely to be of little conservation merit

without substantially or entirely reducing recreational fishing amenity. Aside from

complete closures, targeted restrictions focused on areas and times when key species are

most vulnerable (e.g. during spawning aggregations) can be efficient and effective

management tools (Erisman et al., 2017), and may provide a greater balance between

conservation and recreation. As acoustic tracking in the present study showed that A.

butcheri migrate upstream in the Frankland River during their spawning period (late

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spring/early summer), a seasonal restriction on fishing for this species in this area may

reduce fishing mortality with minimal impact to overall fishery access.

In addition to spatio-temporal controls, changes to size limits may benefit fishery

productivity and amenity. Currently, minimum legal size limits (MML) are in place for a

number of fishery species, including A. butcheri, R. sarba, P. speculator and S. punctatus.

This is one of the oldest and most widely used controls in recreational fisheries

management, with the MLL typically set to allow fish to mature and reproduce at least

once before they can be harvested (Gwinn et al., 2015). With respect to A. butcheri in the

WNIMP, however, fish mature at 2–4 years of age and 150–170 mm TL (A50 and L50,

respectively; Cottingham et al., 2018b), but take a further decade to approach the MLL

of 250 mm, which is attained at 15.5–17.7 years. Thus, under current regulations most of

the population are unable to be harvested, and fishing mortality is focused solely on the

oldest and largest individuals. While many anglers aim to catch fish for consumption,

others achieve satisfaction purely from catch and release fishing and sportfishing for large

‘trophy fish’ (Arlinghaus et al., 2007; Gwinn et al., 2015; Cooke et al., 2018; Magee et

al., 2018). Harvest slots, where both a minimum and maximum legal length are enforced,

can therefore be effective controls in recreational fisheries — allowing a sustainable yield

of mature fish, but protecting the largest individuals (Arlinghaus et al., 2010; Gwinn et

al., 2015). Given the current population status of A. butcheri in the WNIMP, a reduction

of the MLL to 200 mm (which is still sufficiently above the L50 to allow spawning) and

the introduction of a maximum legal length (e.g. 300 mm), would allow a greater number

of fish to be harvested while protecting the few larger ‘trophy fish’ in the system for catch

and release fishing.

6.2.3 Future monitoring plan

Prior to the current study, managers had little to no contemporary, quantitative data on

the spatio-temporal characteristics of the fish fauna in the WNIMP, and no reliable

method for measuring, tracking and reporting change in the ecological health of the

system over time. This study has provided comprehensive details on current trends in the

fish fauna of this system and assessed changes at the population, community and

ecosystem levels since the last studies in the 1990s. Based on this improved

understanding, as well as key knowledge gaps identified through this thesis, I propose the

following plan for monitoring the fish faunas and ecosystem health of the WNIMP. The

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plan also considers potential environmental and social drivers (e.g. water quality, fishing

activity), as well as various marine park priority areas and research questions identified

by Kendrick et al. (2016).

Assessing, tracking and reporting estuarine ecosystem health

Objective: Provide regular quantitative data on the composition of the fish

fauna throughout the WNIMP to facilitate ongoing monitoring of estuarine

ecosystem health, as reflected through the Fish Community Index.

A sampling regime to meet the above objective is detailed in Table 6.2. It has been

designed to maximise efficiency and cost effectiveness, while providing robust data on

fish communities to enable comparisons with other SWA estuaries.

As most FCI metrics of the fish fauna did not differ significantly between the Lower and

Upper Nornalup Inlet (Chapter 2), it is recommended that these be combined into a single

monitoring region (‘Nornalup Inlet’). It is also recommended that an additional

monitoring site is included in the Upper Frankland River above the most upstream site in

the present study, given that climate change effects on the system will likely enable

marine species to penetrate further upriver in the future (Chapter 4). To minimise costs,

sampling is proposed only during autumn and spring to provide the best representation of

the estuary in ‘dry’ and ‘wet’ states, respectively. Seine netting should be undertaken

during the day and gill netting at night, for direct comparability with most previous studies

in the region and other concurrent sampling regimes being undertaken in SWA (e.g.

Hallett, 2017).

Table 6.2 Proposed monitoring regime of fish communities in the Walpole and Nornalup

Inlets Marine Park to facilitate measurement of ecosystem health via the Fish Community

Index.

Gear Regions (no. sites)* Sampling frequency

Nearshore waters 21.5m seine net

(3 mm & 9 mm mesh) Nornalup Inlet (6) Walpole Inlet (4) Frankland River (4)

Annually, autumn and spring (day)

Deep River (4) Offshore waters Multi-mesh gill nets

(38–127 mm meshes; one hour sets)

Nornalup Inlet (4) Walpole Inlet (4) Frankland River (4)

Annually, autumn and spring (night)

*All site locations are the same as those sampled in the current study, with the exception of one additional

site in the upper Frankland River.

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Understanding estuarine use by key species

Objective: Build on existing knowledge of fish movements in the WNIMP

to provide a fuller understanding of how key fishery species use the system

in relation to environmental and anthropogenic drivers.

Acoustic telemetry has proven a useful tool for studying the movements of important

fishery species in the system (Chapter 5) and it is proposed that further fish tracking be

undertaken within and just outside the estuary. A list of potential species, the rationale

for their investigation and specific areas for future research relevant to their management

is provided in Table 6.3.

It is further recommended that the current array of 17 VR2-W receivers (see section 5.2.1)

remain in place to maximise comparability with existing findings, but that several

additional receivers be deployed within the estuary and the adjacent marine environment

to address some knowledge gaps. These include receivers in the Deep and Walpole rivers

to address questions regarding the importance of these smaller tributaries compared to the

much larger Frankland River, as well as receivers in the marine environment adjacent to

the estuary mouth and also at the mouths of nearby estuaries, including the Broke, Irwin

and Wilson Inlets. The latter two groups of receivers would help quantify (i) the relative

importance of the estuary compared to inshore marine habitats, and (ii) the degree to

which fish travel between nearby systems. Resources permitting, there may also be scope

to gather further detail on the habitat preferences and spatial overlap of key species

through the deployment of a Vemco Positioning System (VPS), which enables finer-scale

tracking with an accuracy of several metres (Espinoza et al., 2011b). This may be

particularly beneficial for species such as the platycephalid P. speculator, which showed

highly localised movement patterns.

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Table 6.3 Potential species for future tracking with acoustic telemetry within the Walpole

and Nornalup Inlets Marine Park, listed in order of priority based on current knowledge

gaps and tagging feasibility. Key areas for future research specific to each are also listed.

Current knowledge and relevance Areas for future research Black Bream Acanthopagrus butcheri • Move extensively throughout inlets

and Frankland River. • Highly targeted in the system. • Evidence of size declines in recent

decades. • Slow growth (c. 12 years to reach

MLL of 250mm).

• Movements into Deep and Walpole Rivers.

• Fine-scale habitat use (e.g. avoidance of hypoxic zones).

• Adult vs juvenile movements. • Movements in relation to fishing effort. • Niche overlap and resource competition

with other species. Pink Snapper Chrysophrys auratus • Juveniles abundant in the estuary. • Largest tagged individuals left

estuary. • WNIMP likely an important nursery.

• Estuarine-marine connectivity • Fine-scale habitat use (e.g. association

with differing types of physical structures).

• Assess importance of WNIMP as a nursery in comparison to nearby estuaries and adjacent marine habitats.

Yellowfin Whiting Sillago schomburgkii • Adults & juveniles abundant in the

estuary. • Increasingly abundant in recent years,

corresponding with warming sea temperatures.

• Estuarine-marine connectivity. • Overlap/competition with other species

(e.g. S. punctatus, A. butcheri).

Southern Bluespotted Flathead Platycephalus speculator • High intra-estuarine site attachment. • Several fish left system.

• Estuarine-marine connectivity. • Fine-scale habitat use (e.g. sediment

type, diel shifts in depth). Elasmobranchs (various), e.g. Gummy Shark, Rays • WNIMP a likely nursery for several

species. Adults also reside in system. • Gummy Shark fishery important,

other species socially and ecologically important.

• Estuarine-marine connectivity. • Movements in relation to anthropogenic

activities (e.g. fish cleaning stations, boat ramps).

King George Whiting Sillaginodes punctatus • Juveniles abundant throughout

system. • WNIMP likely an important nursery. • Larger fish sensitive to temperature

increases; declines observed since the 1990s.

• Estuarine-marine connectivity. • Assess importance of WNIMP as a

nursery. • Responses to temperature changes.

Australian Herring Arripis georgianus • 1–2 yr old fish abundant, but older

fish declining. • State-wide stock issues (fishing and

environmental).

• Estuarine-marine connectivity. • Overlap/competition with other species. • Broader-scale migratory patterns along

SWA coast, entry to other estuaries.

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Monitoring of key water quality parameters

Objective: Provide detailed data of key water quality parameters throughout

the WNIMP to help elucidate drivers of change among fish fauna.

Monitoring of water quality is fundamental to understanding drivers of ecological change

and may assist with developing predictive ecosystem response models for this and other

SWA estuaries. Currently, WA government agencies (DBCA/DWER) monitor water

quality in the WNIMP seasonally at several sites throughout the basins. Given that the

physico-chemical properties of estuaries exhibit substantial spatial variability

(horizontally and vertically) and are highly dynamic (e.g. dissolved oxygen content,

which can change significantly within a diel period; Tyler et al. 2009; Dubuc et al., 2018),

data collected over the full extent of the system and on a more regular basis would enable

enhanced understanding of the system. It is therefore recommended that in situ loggers

recording key water quality parameters (e.g. temperature, salinity and dissolved oxygen)

c. hourly be deployed in both inlets, as well as regular intervals upstream into the

Frankland and Deep Rivers, ideally at multiple depths in the water column. Areas of

particular focus should be the deeper waters of the Nornalup Inlet and Frankland River,

which are likely to be most vulnerable to stratification and degradation from hypoxia.

Quantifying fishing activity

Objective: Quantify the spatio-temporal characteristics of fishing activity in the

WNMIP.

To better quantify the impacts of fishing on fish stocks and relate these to fish movement

patterns in the WNIMP, detailed recreational catch and effort data and information on the

spatio-temporal patterns of fishing activity are required. Techniques to collect such data

could include phone diary surveys, creel and boat-ramp surveys, field observations and

camera-based methods (e.g. Smallwood et al., 2011; Cowley et al., 2013; Ryan et al.,

2013). Ideally, these would build upon surveys undertaken in the WNIMP during 2013–

16 (DBCA, unpublished data) and State-wide surveys (e.g. Ryan et al., 2013; Ryan et al.,

2015). Data from these previous surveys, field observations and personal communications

with recreational fishers during this study suggest that fishing effort is widely distributed

through the system. Given this, a roving creel survey of fishers conducted from a vessel

may be required to gather detailed spatial data of their catch and effort.

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6.3 CONCLUDING REMARKS

Estuaries globally are under increasing threat from anthropogenically-induced climate

change and growing disturbances from human activities. To develop effective

management strategies to preserve the integrity of estuaries while sustaining the many

ecosystem services they provide, there is a fundamental need to understand the dynamics

of these systems and their ecological structure and function. This will, in turn, better allow

their inherent natural variability to be disentangled from anthropogenically-induced

shifts. This thesis has provided comprehensive and detailed knowledge of numerous

aspects of the fish ecology in the temperate Walpole-Nornalup Estuary, and the drivers

which influence these fauna over various spatial and temporal scales. Monitoring at the

individual, population, community and ecosystem levels has provided comprehensive

information on how fish in this, and other SWA systems, are likely respond to ongoing

warming and drying of the climate. Similar climatic shifts are occurring in temperate

regions throughout the world (e.g. South Africa, Mediterranean Europe) and these

findings have direct relevance for understanding changes in estuarine ichthyofauna that

may occur. Moreover, this study provides a major contribution towards the refinement of

fish monitoring regimes for comparable estuarine systems. Such regimes, combined with

sound data on the environmental and social pressures on estuaries, are imperative for the

effective management of estuarine ecosystems and their fisheries.

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Appendices

Chapter 2

Appendix 2.1 Mean squares (MS), Pseudo-F (F) values, significance levels (P) and

components of variation values (COV) for three-way crossed PERMANOVA of water

temperature (°C), salinity and dissolved oxygen concentration (mg L−1) recorded in the

nearshore waters of the estuary. Significant results in bold.

Main effects d.f. MS F P COV

Water temperature

Region 4 6.273 1.692 0.178 0.334

Season 3 804.79 217.01 0.001 5.500

Year 1 3.341 0.901 0.320 −0.101

Region × Season 12 9.066 2.445 0.012 0.920

Region × Year 4 2.200 0.593 0.688 −0.387

Season × Year 2 2.711 0.731 0.479 −0.252

Region × Season × Year 5 8.424 2.271 0.054 1.016

Residuals 113 3.709 1.926

Salinity

Region 4 714.88 36.034 0.001 5.504

Season 3 1801.1 90.785 0.001 8.202

Year 1 11.592 0.584 0.443 −0.478

Region × Season 12 86.152 4.343 0.001 3.237

Region × Year 4 25.233 1.272 0.278 0.731

Season × Year 2 970.21 48.904 0.001 7.792

Region × Season × Year 5 21.599 1.089 0.364 0.621

Residuals 113 19.839 4.454

Dissolved oxygen

Region 4 3.0129 8.071 0.001 0.385

Season 3 52.729 141.25 0.001 1.449

Year 1 0.6072 1.627 0.208 0.083

Region × Season 12 1.5291 4.096 0.001 0.458

Region × Year 4 1.2803 3.43 0.010 0.340

Season × Year 1 26.068 69.829 0.001 1.202

Region × Season × Year 3 0.8863 2.374 0.065 0.336

Residuals 101 0.37331 0.611

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Appendix 2.2 Mean squares (MS), Pseudo-F (F) values, significance levels (P) and

components of variation values (COV) for three-way crossed PERMANOVA of water

temperature (°C), salinity and dissolved oxygen concentration (mg L−1) recorded in the

offshore waters of the estuary. Significant results in bold.

Main effects d.f. MS F P COV

Water temperature Region 3 6.067 12.163 0.001 0.482 Season 1 2498.6 5008.9 0.001 7.214 Year 1 4.018 8.055 0.004 0.271 Depth 1 4.691 9.403 0.003 0.296 Region × Season 3 6.342 12.714 0.001 0.698 Region × Year 3 0.442 0.887 0.434 −0.069 Region × Depth 3 1.088 2.181 0.089 0.222 Season × Year 1 2.587 5.187 0.026 0.295 Season × Depth 1 2.095 4.199 0.039 0.258 Year × Depth 1 0.803 1.61 0.205 0.113 Region × Season × Year 3 2.05 4.11 0.009 0.508 Region × Season × Depth 3 0.328 0.657 0.581 −0.169 Region × Year × Depth 3 0.385 0.771 0.505 −0.138 Season × Year × Depth 1 0.072 0.143 0.708 −0.189 Region × Season × Year × Depth 3 1.172 2.349 0.080 0.474 Residuals 64 0.499 0.706 Salinity Region 3 197.33 22.319 0.001 2.802 Season 1 4088.8 462.48 0.001 9.22 Year 1 408.71 46.228 0.001 2.886 Depth 1 429.09 48.533 0.001 2.959 Region × Season 3 77.669 8.785 0.001 2.395 Region × Year 3 21.114 2.388 0.077 1.011 Region × Depth 3 31.706 3.586 0.013 1.38 Season × Year 1 1430.1 161.75 0.001 7.695 Season × Depth 1 216.12 24.445 0.001 2.939 Year × Depth 1 7.348 0.831 0.388 −0.249 Region × Season × Year 3 49.802 5.633 0.003 2.613 Region × Season × Depth 3 17.728 2.005 0.109 1.217 Region × Year × Depth 3 25.269 2.858 0.040 1.655 Season × Year × Depth 1 57.103 6.459 0.013 2.006 Region × Season × Year × Depth 3 8.444 0.955 0.408 −0.364 Residuals 64 8.841 2.973 Dissolved oxygen Region 3 0.711 0.987 0.386 −0.02 Season 1 85.221 118.23 0.001 1.327 Year 1 2.115 2.935 0.076 0.17 Depth 1 38.367 53.23 0.001 0.886 Region × Season 3 2.204 3.058 0.023 0.352 Region × Year 3 0.366 0.507 0.695 −0.172 Region × Depth 3 3.457 4.796 0.005 0.477 Season × Year 1 9.837 13.647 0.001 0.616 Season × Depth 1 11.392 15.805 0.001 0.667 Year × Depth 1 0.946 1.313 0.256 0.097 Region × Season × Year 3 1.384 1.921 0.142 0.333 Region × Season × Depth 3 1.76 2.441 0.069 0.416 Region × Year × Depth 3 1.369 1.899 0.123 0.329 Season × Year × Depth 1 7.211 10.004 0.002 0.735 Region × Season × Year × Depth 3 1.845 2.559 0.055 0.612 Residuals 64 0.721 0.849

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Appendix 2.3 Mean squares (MS), Pseudo-F (F) values, significance levels (P) and

components of variation values (COV) for three-way crossed PERMANOVA of

nearshore fish abundance data (log(x+1) transformed), species richness and average

taxonomic distinctness (∆*). Significant results in bold.

Main effects d.f. MS F P COV

Abundance Region 4 5.027 1.93 0.099 0.265 Season 3 12.96 4.976 0.002 0.499 Year 1 34.2 13.131 0.002 0.62 Region × Season 12 2.664 1.023 0.419 0.082 Region × Year 4 2.139 0.821 0.502 −0.164 Season × Year 3 2.115 0.812 0.483 −0.152 Region × Season × Year 11 1.761 0.676 0.756 −0.428 Residuals 141 2.604 1.614

Species richness Region 4 7.16 2.365 0.042 0.346 Season 3 18.633 6.155 0.001 0.613 Year 1 17.458 5.767 0.023 0.419 Region × Season 12 3.048 1.007 0.463 0.049 Region × Year 4 3.53 1.166 0.330 0.171 Season × Year 3 20.288 6.702 0.001 0.905 Region × Season × Year 11 3.36 1.11 0.351 0.269 Residuals 141 3.027 1.74

Taxonomic distinctness (∆*) Region 4 1043.3 4.415 0.002 4.841 Season 3 438.73 1.857 0.133 2.206 Year 1 25.914 0.11 0.733 −1.601 Region × Season 12 244.18 1.033 0.434 0.946 Region × Year 4 193.65 0.819 0.512 −1.574 Season × Year 3 557.37 2.359 0.071 3.903 Region × Season × Year 11 249.18 1.054 0.392 1.671 Residuals 141 236.32 15.373

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Appendix 2.4 Mean squares (MS), Pseudo-F (F) values, significance levels (P) and

components of variation values (COV) for three-way crossed PERMANOVA of

nearshore fish species composition and estuarine usage, feeding mode and habitat guild

composition. Significant results in bold.

Main effects d.f. MS F P COV

Species composition Region 4 19258 8.859 0.001 22.273 Season 3 7421.9 3.414 0.001 11.234 Year 1 13446 6.185 0.001 11.717 Region × Season 12 4468.1 2.055 0.001 16.162 Region × Year 4 1901.9 0.875 0.712 −3.975 Season × Year 3 5572.9 2.564 0.001 12.698 Region × Season × Year 11 2275.2 1.047 0.344 4.692 Residuals 141 2173.9 46.625

Estuarine use guild composition Region 4 24007 16.765 0.001 25.604 Season 3 3002.4 2.097 0.020 6.146 Year 1 9961.8 6.957 0.001 10.193 Region × Season 12 1956 1.366 0.042 7.724 Region × Year 4 1492.8 1.043 0.393 1.88 Season × Year 3 1915.2 1.338 0.170 4.788 Region × Season × Year 11 1362.8 0.952 0.561 −3.876 Residuals 142 1432 37.841

Feeding mode guild composition Region 4 11734 5.353 0.001 16.646 Season 3 5519.9 2.518 0.003 8.946 Year 1 6348.3 2.896 0.008 7.115 Region × Season 12 3766.3 1.718 0.004 13.388 Region × Year 4 2006.6 0.915 0.576 −3.281 Season × Year 3 3316.2 1.513 0.081 7.303 Region × Season × Year 11 2252.4 1.028 0.426 3.624 Residuals 141 2191.9 46.818 Habitat guild composition Region 4 6902.7 4.171 0.001 12.345 Season 3 6404.5 3.87 0.001 10.688 Year 1 11502 6.951 0.001 10.952 Region × Season 12 3405.4 2.058 0.001 14.117 Region × Year 4 1738.1 1.05 0.402 2.198 Season × Year 3 4000.7 2.418 0.003 10.549 Region × Season × Year 11 2018.2 1.22 0.129 8.885 Residuals 141 1654.9 40.68

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Appendix 2.5 (a) nMDS ordination plots of nearshore fish species composition data

overlayed with corresponding water temperature (°C) and salinity values, constructed

from (a) the centroids in each region × season × year combination, and (b) species

composition at each site during only spring of the first year of sampling and (c) winter of

the second.

(a)

(b)

(c)

(b)

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Appendix 2.6 Distance based redundancy analyses (dbRDA) plots correlating nearshore

fish species composition data with that of (a) water temperature (temp), salinity (sal) and

dissolved oxygen concentration (do) recorded during all regions, seasons and years, (b)

salinity and temperature during summer, (c) salinity and temperature during spring, (d)

salinity during winter, (e) temperature during winter 2014 and (f) salinity during winter

2015.

(e)

(f)

(a)

(b)

(d)

(c)

(e)

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Appendix 2.7 Mean squares (MS), Pseudo-F (F) values, significance levels (P) and

components of variation values (COV) for three-way crossed PERMANOVA of offshore

fish abundance data (fourth-root transformed), species richness (square-root transformed)

and average taxonomic distinctness (∆*). Significant results in bold.

Main effects d.f. MS F P COV

Abundance Region 3 1.6309 4.412 0.010 0.324 Season 1 0.3410 0.923 0.348 −0.034 Year 1 1.4404 3.897 0.081 0.211 Region × Season 3 1.0306 2.788 0.053 0.332 Region × Year 3 0.50464 1.365 0.266 0.15 Season × Year 1 0.47664 1.290 0.284 0.094 Region × Season × Year 3 0.26523 0.718 0.568 −0.187 Residuals 32 0.36963 0.608

Species richness Region 3 0.68691 1.288 0.294 0.113 Season 1 0.23713 0.445 0.520 −0.111 Year 1 1.0794 2.024 0.179 0.151 Region × Season 3 0.10442 0.196 0.903 −0.267 Region × Year 3 0.38285 0.718 0.556 −0.158 Season × Year 1 0.03118 0.058 0.820 −0.205 Region × Season × Year 3 0.27429 0.514 0.659 −0.294 Residuals 32 0.53335 0.73

Taxonomic distinctness (∆*) Region 3 1781.5 0.881 0.465 −4.469 Season 1 576.09 0.285 0.607 −7.759 Year 1 3145 1.556 0.229 6.843 Region × Season 3 85.768 0.042 0.987 −17.96 Region × Year 3 74.91 0.037 0.991 −18.01 Season × Year 1 104.55 0.052 0.834 −12.638 Region × Season × Year 3 568.58 0.281 0.857 −22.004 Residuals 32 2021.1 44.957

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Appendix 2.8 Mean squares (MS), Pseudo-F (F) values, significance levels (P) and

components of variation (COV) for three-way crossed PERMANOVA of offshore species

composition data, and estuarine usage, feeding mode and habitat guild composition.

Significant results in bold.

Main effects d.f. MS F P COV

Species composition Region 3 4369.2 2.887 0.002 15.427 Season 1 2356.6 1.557 0.139 5.928 Year 1 3069.8 2.029 0.065 8.053 Region × Season 3 1573.5 1.040 0.425 3.167 Region × Year 3 1801 1.190 0.287 6.924 Season × Year 1 1513.9 1.000 0.430 0.225 Region × Season × Year 3 2269 1.499 0.087 15.872 Residuals 32 1513.3 38.901

Estuarine use guild composition Region 3 921 3.467 0.002 7.39 Season 1 767.9 2.891 0.046 4.575 Year 1 715.99 2.695 0.065 4.332 Region × Season 3 588.56 2.216 0.044 7.336 Region × Year 3 661.61 2.491 0.025 8.124 Season × Year 1 621.52 2.34 0.098 5.446 Region × Season × Year 3 453.7 1.708 0.127 7.918 Residuals 32 265.64 16.298

Feeding mode guild composition Region 3 1690.6 4.198 0.001 10.36 Season 1 847.8 2.105 0.066 4.306 Year 1 824.3 2.047 0.117 4.191 Region × Season 3 920.73 2.286 0.014 9.292 Region × Year 3 669.79 1.663 0.100 6.672 Season × Year 1 1223.9 3.039 0.033 8.273 Region × Season × Year 3 466.4 1.158 0.324 4.607 Residuals 32 402.73 20.068 Habitat guild composition Region 3 615.25 2.634 0.013 5.640 Season 1 286.26 1.226 0.302 1.482 Year 1 517.76 2.217 0.100 3.441 Region × Season 3 407.5 1.745 0.091 5.385 Region × Year 3 247.88 1.061 0.426 1.546 Season × Year 1 400.76 1.716 0.185 3.733 Region × Season × Year 3 203.24 0.87 0.568 −3.179 Residuals 32 233.54 15.282

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Appendix 2.9 (a) nMDS plot of offshore fish species composition data (averaged by

region × season × year) overlayed with corresponding salinity data collected at the surface

(salS) and bottom (salB) of the water column, and (b) a distance based redundancy

analyses (dbRDA) plot correlating offshore fish species composition data with that of

surface salinity and dissolved oxygen concentration recorded in those waters.

(a)

(b)

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Appendix 2.10 Length composition (kernel density estimates) of Leptatherina

presbyteroides, Favonigobius lateralis, Pseudogobius olorum and L. wallacei on each

sampling occasion from winter 2014 (W1) to autumn 2016 (A2). Seasons; winter (W),

spring (Sp) summer (S) and autumn (A), years; 2014–15 (1), 2015–16 (2). Blue lines trace

potential spawning cohorts.

Total length (mm)

Den

sity

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Chapter 3

Appendix 3.1 Mean squares (MS), Pseudo-F values (F), significance levels (P) and

components of variation values (COV) for three-way crossed diel × region × season

PERMANOVAs of salinity, water temperature and dissolved oxygen concentration

throughout the Walpole-Nornalup Estuary. Significant results are in bold text, df, degrees

of freedom.

df MS F P COV

Salinity

Region 3 977.88 62.270 0.001 5.253

Season 3 1485.80 94.616 0.001 6.570

Diel 1 67.42 4.293 0.035 0.872

Region × Season 9 153.73 9.789 0.001 3.968

Region × Diel 3 21.25 1.353 0.290 0.564

Season × Diel 3 14.80 0.942 0.433 −0.230

Region × Season × Diel 9 20.81 1.325 0.246 1.080

Residual 112 15.70 3.963

Water Temperature

Region 3 3.32 0.915 0.448 −0.094

Season 3 731.99 201.800 0.001 4.624

Diel 1 53.95 14.873 0.001 0.860

Region × Season 9 3.98 1.096 0.395 0.200

Region × Diel 3 1.50 0.414 0.769 −0.349

Season × Diel 3 6.08 1.675 0.188 0.379

Region × Season × Diel 9 12.04 3.319 0.003 1.385

Residual 112 3.63 1.905

Dissolved oxygen

Region 3 0.88 3.159 0.025 0.131

Season 3 74.58 268.560 0.001 1.477

Diel 1 2.18 7.848 0.006 0.167

Region × Season 9 1.60 5.776 0.001 0.389

Region × Diel 3 0.55 1.987 0.113 0.125

Season × Diel 3 1.63 5.871 0.001 0.282

Region × Season × Diel 9 0.87 3.151 0.003 0.369

Residual 112 0.28 0.527

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Appendix 3.2 Mean salinity (), water temperature () and dissolved oxygen () values

during the day (open symbols) and night (solid symbols) in each season in the (a)

Frankland River, (b) Walpole Inlet, (c) Upper Nornalup and (d) Lower Nornalup.

Standard errors bars are provided for all means.

Frankland River Walpole Inlet

Upper Nornalup Lower Nornalup

Frankland River Walpole Inlet

Upper Nornalup Lower Nornalup

Frankland River Walpole Inlet

Upper Nornalup Lower Nornalup

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Appendix 3.3 Mean squares (MS), Pseudo-F values (F), significance levels (P) and

components of variation values (COV) for three-way crossed diel × region × season

PERMANOVAs of the abundance, species richness and average taxonomic distinctness

of the fish fauna throughout the Walpole-Nornalup Estuary. Significant results are in bold

text, df, degrees of freedom.

df MS F P COV

Abundance of individuals Region 3 11.05 5.190 0.003 0.493 Season 3 8.00 3.757 0.016 0.405 Diel 1 2.47 1.163 0.268 0.070 Region × Season 9 1.92 0.900 0.510 −0.152 Region × Diel 3 0.37 0.175 0.918 −0.309 Season × Diel 3 13.22 6.209 0.001 0.787 Region × Season × Diel 9 2.11 0.991 0.486 −0.065 Residual 119 2.13 1.459

Species richness Region 3 1.27 7.454 0.001 0.173 Season 3 1.26 7.408 0.002 0.175 Diel 1 5.84 34.28 0.001 0.282 Region × Season 9 0.27 1.571 0.129 0.103 Region × Diel 3 0.35 2.032 0.122 0.098 Season × Diel 3 0.09 0.505 0.686 −0.069 Region × Season × Diel 9 0.07 0.401 0.939 −0.149 Residual 119 0.17 0.413

Taxonomic distinctness Region 3 324.32 1.206 0.327 1.230 Season 3 402.74 1.498 0.202 1.935 Diel 1 1764.00 6.562 0.012 4.573 Region × Season 9 306.57 1.140 0.343 2.028 Region × Diel 3 70.26 0.261 0.845 −3.290 Season × Diel 3 174.68 0.650 0.579 −2.294 Region × Season × Diel 9 141.71 0.527 0.847 −5.263 Residual 119 268.83 16.400

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Appendix 3.4 Mean squares (MS), Pseudo-F values (F), significance levels (P) and

components of variation values (COV) for three-way crossed diel × region × season

PERMANOVAs of the species composition and feeding and habitat guild composition of

the fish fauna throughout the Walpole-Nornalup Estuary. Significant results are in bold

text, df, degrees of freedom.

d. MS F P COV

Species composition

Region 3 19898.0 8.544 0.001 21.884

Season 3 8939.9 3.839 0.001 13.594

Diel 1 9780.9 4.200 0.001 10.208

Region × Season 9 4489.2 1.928 0.001 15.341

Region × Diel 3 2578.6 1.107 0.296 3.690

Season × Diel 3 3826.3 1.643 0.004 9.150

Region × Season × Diel 9 2318.1 0.995 0.495 −1.530

Residual 119 2328.8 48.258

Feeding guild composition

Region 3 11876 5.240 0.001 16.184

Season 3 9148.2 4.036 0.001 13.87

Diel 1 10034 4.427 0.001 10.422

Region × Season 9 3495.5 1.542 0.014 11.571

Region × Diel 3 1495.8 0.660 0.867 −6.482

Season × Diel 3 4230.3 1.867 0.024 10.478

Region × Season × Diel 9 2367.4 1.045 0.394 4.688

Residual 119 2207.2 46.981

Habitat guild composition

Region 3 8277.5 4.911 0.001 13.404

Season 3 7246.0 4.299 0.001 12.468

Diel 1 9174.7 5.443 0.001 10.234

Region × Season 9 4236.0 2.513 0.001 16.668

Region × Diel 3 756.9 0.449 0.968 −7.115

Season × Diel 3 1694.6 1.005 0.449 0.715

Region × Season × Diel 9 1301.8 0.772 0.867 −9.142

Residual 119 1685.5 41.055

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Chapter 4

Appendix 4.1 Results of Pearson’s product moment correlation tests employing total

annual and total seasonal rainfall and river flow data collected between 1952 and 2015.

Pearson’s correlation coefficient (r), Bonferroni-corrected significance values (P), test

statistics (t) and degrees of freedom (d.f.) are given for each test.

d.f. t P r

Rainfall

1952 to 2015 Annual 62 −2.941 0.002 −0.35

1988 to 2015 Annual 26 −1.447 0.080 −0.27

Winter 26 −1.348 0.379 −0.26

Spring 26 −0.605 1.000 −0.12

Summer 26 −0.747 0.924 −0.14

Autumn 26 −0.696 0.986 −0.14

Flow (Frankland River)

1952 to 2015 Annual 62 −1.250 0.108 −0.16

1988 to 2015 Annual 26 −3.266 0.002 −0.54

Winter 26 −3.406 0.004 −0.56

Spring 26 −2.491 0.039 −0.44

Summer 26 −1.403 0.345 −0.27

Autumn 26 −1.407 0.342 −0.27

Flow (Deep River)

1976 to 2015 Annual 39 −2.87 0.003 −0.42

1988 to 2015 Annual 26 −4.041 0.001 −0.62

Winter 26 −4.379 0.001 −0.65

Spring 26 −2.71 0.024 −0.47

Summer 26 −2.381 0.052 −0.42

Autumn 26 −5.320 0.001 −0.72

Mean minimum air temperature (Cape Leeuwin)

1952 to 2015 Annual 62 7.485 0.001 0.69

1988 to 2015 Annual 26 4.338 0.001 0.65

Winter 26 3.747 0.002 0.59

Spring 26 3.469 0.004 0.56

Summer 26 3.521 0.003 0.57

Autumn 26 0.988 0.665 0.19

Mean maximum air temperature (Cape Leeuwin)

1952 to 2015 Annual 62 5.538 0.001 0.58

1988 to 2015 Annual 26 2.305 0.015 0.41

Winter 26 4.084 0.001 0.63

Spring 26 2.442 0.043 0.43

Summer 26 0.837 0.821 0.16

Autumn 26 0.750 0.920 0.15

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Appendix 4.2 Mean squares (MS), Pseudo-F (F) values, significance levels (P) and

components of variation values (COV) for three-way crossed PERMANOVA employing

nearshore water temperature and salinity data collected seasonally throughout the

Walpole-Nornalup Estuary in 1989–90, 2014–15 and 2015-16.

Main effects d.f. MS F P COV

Temperature

Region 2 0.466 0.455 0.65 −0.221

Season 3 228.33 222.7 0.001 5.076

Year 2 12.602 12.291 0.005 1.006

Region × Season 6 2.316 2.259 0.129 0.642

Region × Year 4 1.015 0.99 0.461 −0.05

Season × Year* 5 19.014 18.546 0.002 2.296

Region × Season × Year* 9 0.734 0.716 0.661 −0.481

Residuals 11 1.025 1.013

Salinity

Region 2 29.467 22.244 0.002 1.565

Season 3 802.02 605.41 0.001 9.526

Year 2 311.22 234.93 0.001 5.206

Region × Season 6 7.664 5.785 0.004 1.422

Region × Year 4 2.885 2.178 0.156 0.619

Season × Year* 5 149.15 112.59 0.001 6.581

Region × Season × Year* 9 8.53 6.439 0.001 2.392

Residuals 11 1.325 1.151

* term has one or more empty cells in a balanced design.

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Appendix 4.3 Mean squares (MS), Pseudo-F (F) values, significance levels (P) and

components of variation values (COV) for four-way crossed PERMANOVA employing

offshore water temperature and salinity data collected at the surface and bottom of the

water column seasonally throughout the Walpole-Nornalup Estuary in 1989–90 and

2013–17.

Main effects d.f. MS F P COV

Water temperature

Region 3 0.689 0.197 0.899 −0.382

Season 3 452.16 129.32 0.001 4.56

Depth 1 0.033 0.009 0.906 −0.304

Period 1 1.063 0.304 0.597 −0.255

Region × Season 9 2.36 0.675 0.723 −0.454

Region × Depth 3 0.205 0.059 0.972 −0.584

Region × Period 3 0.574 0.164 0.920 −0.538

Season × Depth 3 0.556 0.159 0.916 −0.522

Season × Period 3 21.782 6.230 0.003 1.302

Depth × Period 1 0.02 0.006 0.947 −0.43

Region × Season × Depth 9 0.369 0.106 0.997 −1.064

Region × Season × Period 8 0.912 0.261 0.970 −0.933

Region × Depth × Period 3 0.319 0.091 0.968 −0.793

Season × Depth × Period 3 0.533 0.152 0.934 −0.741

Region × Season × Depth × Period 8 0.468 0.134 0.998 −1.429

Residuals 32 3.496 1.87

Salinity

Region 3 241.09 5.539 0.003 3.202

Season 3 2532.8 58.192 0.001 10.74

Depth 1 259.21 5.955 0.021 2.396

Period 1 199.8 4.590 0.043 2.040

Region × Season 9 65.2 1.498 0.213 1.981

Region × Depth 3 19.785 0.455 0.702 −1.570

Region × Period 3 40.292 0.926 0.465 −0.566

Season × Depth 3 74.814 1.719 0.200 1.703

Season × Period 3 130.26 2.993 0.041 2.835

Depth × Period 1 1.35 0.031 0.871 −1.499

Region × Season × Depth 9 20.634 0.474 0.875 −2.879

Region × Season × Period 8 21.688 0.498 0.855 −2.713

Region × Depth × Period 3 19.872 0.457 0.705 −2.163

Season × Depth × Period 3 3.264 0.075 0.98 −2.732

Region × Season × Depth × Period 8 32.718 0.752 0.655 −2.699

Residuals 32 43.526 6.597

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Appendix 4.4 Mean squares (MS), Pseudo-F (F) values, significance levels (P) and

components of variation values (COV) for a three-way crossed PERMANOVA of

nearshore fish abundance (sqrt transformed), species richness and average taxonomic

distinctness (∆+) data recorded seasonally throughout the Walpole-Nornalup Estuary in

1989–90, 2014–15 and 2015–16. Significant results in bold.

Main effects d.f. MS F P COV

Abundance

Region 2 271.16 4.281 0.065 3.857

Season 3 10.273 0.162 0.918 −2.301

Year 2 157.07 2.480 0.172 2.656

Region × Season 6 57.542 0.909 0.520 −1.277

Region × Year 4 20.713 0.327 0.808 −3.011

Season × Year 6 58.845 0.929 0.506 −1.142

Region × Season × Year 11 15.135 0.239 0.966 −6.191

Residuals 12 63.334 7.958

Species richness

Region 2 10.601 3.741 0.050 0.746

Season 3 10.695 3.775 0.049 0.886

Year 2 23.936 8.448 0.003 1.260

Region × Season 6 0.213 0.075 0.996 −0.859

Region × Year 4 4.756 1.679 0.223 0.64

Season × Year 6 7.383 2.606 0.050 1.149

Region × Season × Year 11 3.692 1.303 0.315 0.826

Residuals 12 2.833 1.683

Taxonomic distinctness (∆+)

Region 2 384.34 3.207 0.107 4.351

Season 3 689.96 5.757 0.004 7.542

Year 2 2138.2 17.84 0.002 12.326

Region × Season 6 398.39 3.324 0.033 8.856

Region × Year 4 476.27 3.974 0.031 8.707

Season × Year 6 817.77 6.823 0.002 14.234

Region × Season × Year 11 325.33 2.714 0.041 12.782

Residuals 12 119.86 10.948

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Appendix 4.5 Mean squares (MS), Pseudo-F (F) values, significance levels (P) and

components of variation values (COV) for a three-way crossed PERMANOVA test of the

nearshore fish species composition and guild composition (estuarine usage, feeding mode

and habitat) data recorded seasonally throughout the Walpole-Nornalup Estuary in 1989–

90, 2014–15 and 2015–16. Significant results in bold.

Main effects d.f. MS F P COV

Species composition

Region 2 12754 10.142 0.001 28.683

Season 3 3295.2 2.62 0.006 14.258

Year 2 6485.1 5.157 0.001 19.837

Region × Season 6 2450.6 1.949 0.001 18.329

Region × Year 4 3095.3 2.462 0.002 19.771

Season × Year 6 3804 3.025 0.001 27.19

Region × Season × Year* 11 2485.3 1.976 0.001 31.246

Residuals 12 1257.5 35.461

Estuarine use guild composition

Region 2 12407 19.385 0.001 29.019

Season 3 1741.9 2.722 0.011 10.485

Year 2 4671.8 7.299 0.001 17.421

Region × Season 6 1332.3 2.082 0.021 13.961

Region × Year 4 2119.9 3.312 0.003 17.741

Season × Year 6 2253.5 3.521 0.001 21.643

Region × Season × Year* 11 1283.6 2.006 0.015 22.623

Residuals 12 114.48 10.7

Feeding mode guild composition

Region 2 13481 12.711 0.001 29.813

Season 3 2698.4 2.544 0.008 12.783

Year 2 4580.5 4.319 0.002 16.278

Region × Season 6 2129.2 2.008 0.014 17.346

Region × Year 4 2769.8 2.612 0.002 19.067

Season × Year 6 3259.8 3.074 0.001 25.268

Region × Season × Year* 11 2253.6 2.125 0.002 30.8

Residuals 12 1060.6 32.567

Habitat guild composition

Region 2 9794.2 11.219 0.001 25.267

Season 3 2483.2 2.845 0.011 12.674

Year 2 5822 6.669 0.001 19.301

Region × Season 6 2214.7 2.537 0.002 19.437

Region × Year 4 2221.2 2.544 0.006 16.934

Season × Year 6 2921.8 3.347 0.001 24.389

Region × Season × Year* 11 2003.6 2.295 0.002 29.983

Residuals 12 872.99 29.546

* term has one or more empty cells in a balanced design.

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Appendix 4.6 Mean squares (MS), Pseudo-F (F) values, significance levels (P) and

components of variation values (COV) for a three-way crossed PERMANOVA of

offshore total fish abundance (i.e. catch rates, fish hr−1; fourth root transformed) and

average taxonomic distinctness (∆+) data recorded seasonally throughout the Walpole-

Nornalup Estuary in 1989–90 and 2013–17. Significant results in bold.

Main effects d.f. MS F P COV

Abundances

Region 3 0.675 2.778 0.096 0.212

Season 3 0.187 0.769 0.543 −0.072

Period 1 0.013 0.054 0.84 −0.111

Region × Season 9 0.136 0.558 0.783 −0.197

Region × Period 3 0.244 1.004 0.434 0.013

Season × Period 3 0.351 1.444 0.279 0.141

Region × Season × Period 8 0.135 0.554 0.817 −0.27

Residuals 16 0.243 0.493

Taxonomic distinctness

Region 3 1.7 1.609 0.215 0.258

Season 3 0.856 0.811 0.507 −0.136

Period 1 11.784 11.158 0.006 0.756

Region × Season 9 0.755 0.715 0.692 −0.33

Region × Period 3 1.819 1.722 0.198 0.388

Season × Period 3 0.923 0.874 0.484 −0.157

Region × Season × Period 8 0.88 0.833 0.606 −0.345

Residuals 16 1.056 1.028

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Appendix 4.7 Mean squares (MS), Pseudo-F (F) values, significance levels (P) and

components of variation values (COV) for a three-way crossed PERMANOVA test of the

offshore fish species composition and guild composition (estuarine usage, feeding mode

and habitat) data recorded seasonally throughout the Walpole-Nornalup Estuary in 1989–

90 and 2013–17. Significant results in bold.

Main effects d.f. MS F P COV

Species composition

Region 3 7250.7 3.168 0.001 22.69

Season 3 3444.2 1.505 0.072 10.347

Period 1 11805 5.157 0.001 22.508

Region × Season 9 1706.3 0.745 0.934 −14.525

Region × Period 3 3996.7 1.746 0.016 18.379

Season × Period 3 2403.4 1.05 0.420 4.605

Region × Season × Period 8 1682 0.735 0.923 −20.228

Residuals 16 2289 47.843

Estuarine usage guilds

Region 3 3134.1 2.246 0.025 13.432

Season 3 1801.1 1.291 0.253 6.133

Period 1 10348 7.417 0.001 21.833

Region × Season 9 735.47 0.527 0.973 −15.456

Region × Period 3 1556.6 1.116 0.375 5.649

Season × Period 3 1780.7 1.276 0.267 8.452

Region × Season × Period 8 331.22 0.237 1 −26.783

Residuals 16 1395.3 37.353

Feeding mode guilds

Region 3 5134.4 3.883 0.001 19.888

Season 3 1927.6 1.458 0.175 7.49

Period 1 5358.4 4.052 0.003 14.659

Region × Season 9 1062.8 0.804 0.766 −9.694

Region × Period 3 2007.6 1.518 0.133 11.643

Season × Period 3 2619 1.981 0.052 15.504

Region × Season × Period 8 1135.4 0.859 0.701 −11.225

Residuals 16 1322.3 36.363

Habitat guilds

Region 3 3621.9 3.586 0.002 16.462

Season 3 1028.3 1.018 0.450 1.301

Period 1 3923.7 3.885 0.024 12.455

Region × Season 9 929.47 0.92 0.553 −5.402

Region × Period 3 2488 2.463 0.020 17.098

Season × Period 3 1416.2 1.402 0.213 8.677

Region × Season × Period 8 628.69 0.622 0.878 −16.034

Residuals 16 1010.1 31.781

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Chapter 5

Appendix 5.1 Mean squares (MS), Pseudo-F (F) values, significance levels (P) and

components of variation values (COV) for one-way PERMANOVA tests to explore

differences in the station residency of each A. butcheri and P. speculator which were

tagged in different regions of the estuary.

Species df MS F P COV

A. butcheri 3 5357.9 4.603 0.001 27.806

P. speculator 1 19233 7.501 0.001 45.057

Appendix 5.2 (a) Mean squares (MS), Pseudo-F (F) values, significance levels (P) and

components of variation values (COV) for one-way PERMANOVA and (b) R-statistic

and/or P values for global and pairwise comparisons from one-way ANOSIM, exploring

differences in the proportion of time each of the four study species spent in each estuarine

region and the ocean. Significant (P < 0.05) pairwise R comparisons are in bold.

(a) df MS F P COV

3 13086 6.233 0.001 28.377

(b) Global R = 0.242, P = 0.001

A. butcheri P. speculator R. sarba

P. speculator 0.395

R. sarba 0.213 0.055

C. auratus 0.372 0.092 0.082

Appendix 5.3 (a) Mean squares (MS), Pseudo-F (F) values, significance levels (P) and

components of variation values (COV) for one-way PERMANOVA and (b) R-statistic

and/or P values for global and pairwise comparisons from one-way ANOSIM, exploring

differences in the station residency of each of the four study species. Significant (P <

0.05) pairwise R comparisons are in bold.

(a) df MS F P COV

3 15742 7.507 0.001 31.624

(b) Global R = 0.282, P = 0.001

A. butcheri P. speculator R. sarba

P. speculator 0.455

R. sarba 0.171 0.016

C. auratus 0.351 0.036 0.451

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Appendix 5.4 Mean squares (MS), Pseudo-F (F) values, significance levels (P) and

components of variation values (COV) for two-way crossed PERMANOVA exploring

differences in the (a) total distance travelled and (b) number of stations visited each month

by individuals of each study species between August 2015 and January 2016.

Main Effect df MS F P COV

(a) Distance travelled month−1

Species 3 55.31 40.97 0.001 1.09

Month 5 0.97 0.72 0.625 −0.12

Species × Month 15 0.87 0.65 0.835 −0.25 Residuals 177 1.35 1.16

(b) Stations visited month−1 Species 3 1.26 11.58 0.001 0.16 Month 5 0.07 0.68 0.643 −0.04 Species × Month 15 0.15 1.41 0.139 0.08 Residuals 171 0.11 0.33

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