A long-term study of a small rocky reef

Bill Ballantine

Leigh Marine LaboratoryNew Zealand

This study aims to determine the variations over TIME in a NATURAL marine benthic community

i.e. where there is no exploitation, no serious disturbance and no driving force for change.

To make this valid, practical and generally meaningful requires a large number of decisions, choices, stratifications, etc. including -

Theoretical points:

1. For spatial comparisons the observations need to be made at the same time.

Similarly, comparisons over time need observations at the same place.

The study needs a fixed site.

2. Comparisons in space need to be separated by sufficient distance to avoid auto-correlation (pseudo-replication).

Similarly, replicates in time need sufficient separation in time. The study must extend over multiple generations.

Practical considerations:

• No human interference : in a marine reserve• No major natural disturbances (e.g. erosion) • Easily accessible for frequent observations• Simple topography – uniform, gentle, bedrock slope• Reduced secondary factors (e.g. rock type)• Low diversity – only ~15 significant species• Short generation times – < 1 - 5 years• Comprehensive – all significant species monitored• Small enough to allow census of most species

• Large enough to provide multiple patch dynamics

The locality: Goat Island Bay, Leigh

Standard Reef

Standard Reef: total area 5m x 4m

Standard Reef: 1–20 @ 1m2, A-L @ 0.1 m2

Most data that will be shown comes from 1-10 m2

Square 2 : open rock and crevices

The Standard Reef biological community

Trophic level

Carnivorous whelk

Grazing molluscs 4 species

Phytoplankton Benthic microflora Ralfsia

3

2

1

Some data: infrequent sampling

Good data: regular census

Barnacles Mussels Cellana radiansSypharochiton pelliserpentisMelagraphia aethiopsTurbo smaragda

Grazing molluscs:

• RESIDENTS

• A chiton• Sypharochiton pelliserpentis

A patellid limpet• Cellana radians

• VISITORS

– A turbinid snail • Turbo smaragda

– A trochid snail• Melagraphia aethiops

Sypharochiton pelliserpentis

Homing to crevices (< 30 cm)

Slow growing and long-lived (>3 years)

Small changes (<10% per month and <50% per year)

No seasonality

Range of biomass over time ~ 4x

Sypharochiton pelliserpentis biomass in 1-10 m2 (all data)Standard Reef, Echinoderm Reef

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Bio

mas

s (g

)

0

100

200

300

400

500

Mean

Graph: Sigmaplot Sypharo biom 1-1- 1997 on Graph page 1Data: Excel SigplotSy1-1097on Sheet 1

*

* Total wet weight

Cellana radians

Home-ranging (< 1 m)

Fast growing and short-lived (< 2 years)

Rapid changes (up to 50% per month)

Strong seasonality (summer peaks)

Range of biomass over time >20x

Cellana radians biomass (g) 1-10 m2

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Cel

lana

rad

ians

bio

mas

s (g

)

0

100

200

300

400

500

Cellana radians biomass (g) 1-10 m2 (all data)Standard Reef, Echinoderm Reef

Turbo smaragdus

Wide-ranging (up and back to lower zone)Moderate growth rate and longevity Very rapid short term changes (>50% per month) and

rapid changes per year >70%)Weak seasonality

Range of biomass over time >20x

Turbo biomass (g) 1-10 m2

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Tur

bo b

iom

ass

(g)

0

100

200

300

400

500

Turbo biomass (g) 1-10 m2 (all data)Standard Reef, Echinoderm Reef

Melagraphia aethiops

Very wide-ranging (at this level)Moderate growth rate and longevity Long periods of low (< 30) or high (> 50) abundanceNo seasonality

Range of biomass over time >20x

Melagraphia aethiops biomass in 1-10 sq m (all data)Standard Reef, Echinoderm Reef

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Mel

agra

ph

ia b

iom

ass

(g)

0

100

200

300

400

500

Conclusions for grazing molluscs:

1. The variations of biomass over time are LARGE and important.

2. The variations are NOT PREDICTABLE (beyond very short time frames).

3. The variations are NOT RANDOM and the patterns are distinctive for each species.

4. The variations show no persistent patterns of competition.

None of these conclusions were expected, and they do not match well with existing theory on food web models.

Sypharochiton

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Bio

mas

s (g

)

0

100

200

300

400

500

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Cella

na

ra

dia

ns b

iom

as (

g)

0

100

200

300

400

500

Turbo

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Tur

bo s

mar

agd

us

bio

ma

ss (

g)

0

100

200

300

400

500

Melagraphia biomass in 10 m2 (standard months)

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Mela

gra

phia

bio

mass (g

)

0

100

200

300

400

500

Comparison of 4 grazing molluscs

Melagraphia

Cellana

Sessile species:

• A small sheet-forming barnacle

– Chamaesipho columna

• A black encrusting alga

– Ralfsia (cf confusa)

• A small mussel

– Xenostrobus pulex

– Despite only 3 species, the patch dynamics are complex

Barnacles: Chamaesipho columna

Clean barnacle % cover 1-10 m2 Standard Reef, Echinoderm Reef

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Cle

an b

arn

acle

% c

ove

r (n

o R

alfs

ia o

r m

uss

els)

0

20

40

60

80

100

Ralfsia covered barnacles

Ralfsia % cover 1-10 m2 (std motnhs) Standard Reef, Echinoderm Reef

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Ral

fsia

% c

ove

r

0

20

40

60

80

100

months)

Mussels % cover in photonodes A-E (std motnhs) Standard Reef, Echinoderm Reef

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Mu

ssel

% c

ove

r

0

20

40

60

80

100

Conclusions for sessile species are the same as for the grazing molluscs –

(a) large variations over time(b) unpredictable(c) different patterns for each species(d) low correlations between species

Sessile species dynamics

• Barnacles settle only on bare rock• Ralfsia only grows well on or between barnacles• Mussels settle on Ralfsia, barnacles or themselves, but not on

bare rock

Settlement (all species) occurs as strong pulses, but is only weakly seasonal.

Ralfsia grows over barnacles but does not harm themMussels grow over and smother barnacles and RalfsiaRalfsia dies back after ~ 12 months

There is no equilibrium state.

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Mu

sse

ls %

co

ve

r

0

10

20

30

40

50

60

70

80

90

100

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Cle

an

ba

rna

cle

% c

ove

r (n

o R

alfsia

or

Mu

sse

ls)

0

10

20

30

40

50

60

70

80

90

100

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Ra

lfsia

% c

ove

r

0

10

20

30

40

50

60

70

80

90

100

Barnacles

Ralfsia

Mussels

Variations with time

Barnacles Ralfsia Bare

Barnacles Ralfsia Mussels

Barnacles Bare Mussels

1999

2001

2003

Correlation coefficients (r) for 1-10 m2 on Standard Reef 1997 onwards

CHITON CELLANA TURBO TROCHID BARNACLES RALFSIA MUSSELS

CHITON 0.60 0.41 0.59 0.19 -0.09 -0.32

CELLANA 0.25 0.57 0.22 -0.12 -0.25

TURBO 0.48 0.23 -0.16 -0.09

TROCHID 0.31 -0.08 -0.46

BARNACLES -0.61 -0.33

RALFSIA -0.18

MUSSELS

Extra time

A further 9 years of data is available but includes a 2 year gap.

Conclusions from extra time confirm and reinforce previous conclusions especially:

(a) The range of variation(b) The specifically distinct patterns

Sypharochiton biomass (g) 1-10 m2

1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009

Syp

har

och

ito

n b

iom

ass

(g)

0

100

200

300

400

500

600

Cellana radians biomass (g) 1-10 m2

1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009

Cel

lan

a ra

dia

ns

bio

mas

s (g

)

0

100

200

300

400

500

80010001200

*

* Three lines of evidence indicate a similar event occurred in 1981

Turbo smaragdus (g) 1-10 m2

1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009

Tu

rbo

bio

mas

s (g

)

0

100

200

300

400

500

Turbo smaragdus biomass (g) 1-10 m2

Melagraphia aethiops biomass (g) 1-10 m2

1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009

Mel

agra

phia

bio

mas

s (g

)

0

50

100

150

200

250

300

Discussion:

1. All species in this natural and undisturbed community show variations over time which are:

(a) Large and ‘ecologically important’(b) Unpredictable (except for very short periods)(c) Non-random and distinctive in their patterns(d) Largely independent

Given (a) and (d), it follows that the interactions between species are varying over time.

2. There is little or no comparable data because

(a) these are very difficult to obtain even if time is available and undisturbed sites exist

(b) the topic does not seem interesting to most workers(c) career paths and grant agency policies tend to

prevent their collection.

3. Existing knowledge is mainly from studies that are:

(a) short-term(b) detailed and precise(c) focused on active processes and limiting factors

Such studies are necessary and important, but are effectively just short clips from a movie.

Cellana radians biomass 10 m2

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Ce

llan

a r

ad

ian

s b

iom

as

(g)

0

100

200

300

400

500

The conclusions from the 3 periods would be quite different.

Cellana radians biomass 10m2

4. Existing theory on temporal variation in biological communities consists mainly of implicit and untested assumptions that such variation is

(a) small, except when disturbed from outside(b) and /or periodic (e.g. seasonal)

(c) and /or random(d) and /or unimportant

5. Existing models of biological community dynamicsimplicitly assume that

(a) the community is maintained by active processes(b) these processes can be recognized and estimated(c) the estimates can be used to make a useful model(d) it is not necessary to include any temporal variation

(other than that produced by external factors)

e.g. Branch (2008) Trophic interactions in sub-tidal rocky reefs on the west coast of South Africa

6. Such models are useful as descriptions, but they cannot be made predictive in any precise way because they are equilibrium models and are unable to cope with continuous or complex temporal changes.

Conclusions

1. In a simple undisturbed rocky shore community the main species showed large changes in abundance over time- scales that included multiple generations.

2. These changes were not predictable, except over very short time frames but were not random. Each species had a distinctive pattern but the details never repeated precisely.

3. Despite all the changes and the absence of any equilibrium state, the community persisted through time as frequently recurring similar structures and patterns.

4. There is little comparable data (spatially-explicit, multi-generational), and no clear theory on what temporal changes should be expected in an undisturbed community.

5. It is not known if the kind of changes found in this study would occur in other communities, but it seems likely.

6. It is well-known that even simple physical systems can show complex intrinsic dynamics, if the system is externally forced and governed by non-linear processes.

7. Biological communities are such systems and consequently are likely to show similar intrinsic dynamics.

8. Furthermore, although these intrinsic dynamics will be overlaid by ‘external’ disturbances (such as exploitation,

severe storms, pollution, etc.) they are likely to continue to operate.

A useful analogy ?

In the 1960s, weather forecasters were confident that with better data and analysis, their forecasts would improve indefinitely.

Edward Lorentz proved that this is not true.

“Complex systems” are completely deterministic and show recognizable types of order, but do not reach equilibrium and never repeat exactly the same state.

Consequently, detailed predictions are not possible (except for short periods), no matter how much is known about the present situation or the governing processes.

Biological communities are likely to be “complex systems” of this type.

If ecologists considered the component species of a community analogous to the weather at a locality and the entire community analogous to the climate, I believe considerable practical and theoretical advances could be made with existing data.

Community predictability will become a matter of pattern and probability not precision.

The climate of an area is composed entirely of ‘weather events’ none of which can be precisely predicted, but we know that the climate of an area has real and useful levels of predictability, indeed most of our activities depend on this (e.g. successful farming is possible).

Three problems with this study

1. No spatial replication2. Very small area3. Simple community (low biodiversity)

I could only manage a single, small, simple area for a long period.

Better data would not only require large amounts of work and finance, it would also require a long time. Consequently it seems sensible to extract as much information as possible from the present study.

A recent relevant paper

Beninca et al (2008) Chaos in a long-term experiment with a plankton community. Nature: 451, 822-826.

They maintained a closed mesocosm under constant conditions for 8 years and showed:

1. A complex biological community can persist despite large, unpredictable changes in all its component trophic groups. Stability is not required.2. These changes were due to intrinsic dynamics and long-term prediction can be fundamentally impossible.

Help!

Some of this team (expert mathematicians with high-powered computers) have offered to analyse the Standard Reef and associated climate data and these are being sent to them by John Atkins and Agnès Le Port.

I would very much appreciate:(i) Any suggestions for forms of analysis (e.g. correlation with

SOI, lag times, etc.(ii) References to any comparable data sets (i.e. long-term,

fixed site(s), undisturbed, and multi-species).

My email is b.ballantine@auckland.ac.nz

Acknowledgements

Over the years, many people assisted with the very tedious task of recording the data in this study.Many others helped with studies of particular species, with analysis and with discussion.Although they are too numerous to list, I am very grateful to them all.

Neil Barr and Agnès Le Port helped prepare this presentation.