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Interactions between timber harvesting and swamp wallabies

(Wallabia bicolor): Space use, density and browsing impact

Julian Di Stefano a,b,*, Jacob A. Anson b,1, Alan York a, Andrew Greenfield b,Graeme Coulson b, Ann Berman c, Michael Bladen c

a University of Melbourne, School of Forest and Ecosystem Science, Water St, Creswick, 3363 Victoria, Australiab University of Melbourne, Department of Zoology, 3010 Victoria, Australia

c 7 Laver St, Kew, 3101 Victoria, Australia

Received 8 May 2007; received in revised form 10 July 2007; accepted 10 July 2007

bstract

Timber harvesting in native Eucalyptus forests was used as an experimental treatment to study its effect on the space use and density of the

wamp wallaby (Wallabia bicolor), and on the impact of herbivorous mammals on postharvest tree regeneration. The space use and density studies

sed a Multiple Before–After Control-Impact (MBACI) design to compare changes before and after (and in some cases before and during)

arvesting between unharvested control and harvested impact locations. The impact of harvesting on wallaby space use was quantified separately at

wo harvested sites in terms of home range size, core range size and overlap (95 and 50% fixed kernels), and the shift in geographic centre of

ocation (GCL). The most obvious response to harvesting was a substantial shift in core range position and, in some cases, a large (>100%) increase

n home range size. Relative to unharvested controls, GCLs shifted substantially farther at one harvested site but not at the other. Home range

verlap tended to be similar at control and harvested sites indicating that harvesting had a minimal impact on the overall use of space. One year

fter harvesting, wallaby density was about five times greater at harvested sites than at control sites. This overall increase was characterised by an

lmost complete abandonment of harvested areas for the first 8–10 months and then a rapid influx of animals after this time. Browsing impact on

2-month-old Eucalyptus seedlings (% biomass removed) ranged from 1.0 to 11.2% but was insubstantial for coppice (0.4–0.9%). The percentage

f severely damaged seedlings ranged from 0 to 12.9%. The reduction in stocking attributable to severe browsing ranged from 0 to 3% indicating

hat browsing impact had little effect on regeneration success. The results are discussed with reference to effective monitoring of browsing impact

n commercially harvested native forests.

2007 Elsevier B.V. All rights reserved.

eywords: Commercial forestry; Herbivory; Home range; Land management; Macropod; Mammals; Relative density

www.elsevier.com/locate/foreco

Forest Ecology and Management 253 (2007) 128–137

1. Introduction

Sustainable management of forests used for commercial

timber production requires, amongst other things, an under-

standing of harvesting impacts on forest wildlife (Linden-

mayer, 1994; Simberloff, 1999). An important group of forest

fauna are herbivorous ground-dwelling mammals who often

from timber harvesting in the short to medium term. Although

effects can be mediated by silvicultural practices (Reimoser

* Corresponding author. Tel.: +61 3 5321 4259; fax: +61 3 5321 4166.

E-mail address: [email protected] (J. Di Stefano).1 Current address: 2808 19th Street NW, Calgary, Alberta, TM2 3V8,

anada.

378-1127/$ – see front matter # 2007 Elsevier B.V. All rights reserved.

oi:10.1016/j.foreco.2007.07.010

and Gossow, 1996), harvesting generally creates patches of

early successional forest adjacent to mature stands, providing

high quality foraging and shelter environments for many

species (Bobek et al., 1984; Fuller and Gill, 2001; le Mar and

McArthur, 2005). Cote et al. (2004) suggested that habitat

enhancement resulting from commercial timber production is

one of the reasons for overabundant deer populations around

the world.

A corollary of the enhanced habitat quality afforded by

harvesting is that mammalian herbivores often consume

regenerating tree seedlings. From a commercial perspective,

this can have adverse effects on the survival, growth rates and

form of regenerating trees in both commercial and non-

commercial forests (Gill, 1992; Welch et al., 1992; Reimoser

and Gossow, 1996; Bulinski, 1999; Bulinski and McArthur,

mailto:[email protected]

http://dx.doi.org/10.1016/j.foreco.2007.07.010

Fig. 1. Map of Australia showing the general location of study forests within

the State of Victoria (shaded). Density and browsing data were collected in all

forests, while space use data were collected only in the Pyrenees.

J. Di Stefano et al. / Forest Ecology and Management 253 (2007) 128–137 129

1999; Rooney, 2001; Zamora et al., 2001; Bulinski and

McArthur, 2003; Di Stefano, 2005). In addition, browsing by

herbivores may alter plant community composition (Horsley

et al., 2003), can have secondary impacts on other groups of

organisms (Moser and Witmer, 2000; Flowerdew and Ellwood,

2001) and can influence ecosystem processes through inputs of

dung and urine (Hobbs, 1996), or through interactions between

selective foliage consumption, litter quality, below-ground

plant responses and the abundance of soil micro-organisms

(Bardgett et al., 1998; Wardle et al., 2002).

Although retrospective studies of harvesting impacts on

herbivores are common (e.g. Chubbs et al., 1993; St-Louis

et al., 2000; le Mar and McArthur, 2005), we are aware of only

one study containing pre-, during- and postharvest data at both

control and impact locations (Campbell et al., 2004), although

several others used similar designs to quantify the impact of

other disturbances on herbivore behaviour (Newell, 1999;

Cimino and Lovari, 2003). Collecting data before, during and

after harvesting enables the study of immediate behavioural

responses to habitat alteration, and the fate of individuals to be

quantified (Newell, 1999). In addition, the use of Before–After

Control-Impact (BACI, MBACI, etc.) designs provides a better

basis for inferring impacts than the traditional retrospective

approach (Keough and Mapstone, 1995; Downes et al., 2002).

Despite their strength, BACI designs are infrequently used in

studies of harvesting impacts on vertebrates.

In this study, our objective was to investigate interactions

between commercial timber production and the swamp wallaby

(Wallabia bicolor), a medium-sized ground-dwelling generalist

herbivore that is widely distributed throughout the native

forests of southern and eastern Australia. Past research on

harvesting impacts in these forests have focused on arboreal

mammals (Tyndale-Biscoe and Smith, 1969; Lindenmayer

et al., 1991; Gibbons and Lindenmayer, 1996; Lindenmayer

and Franklin, 1997; Kavanagh, 2000), and little information on

ground dwelling species is available. In addition, swamp

wallabies contribute to locally severe browsing damage

(Sebire, 2001) and appear to favour 1–2 year old densely

regenerating areas over surrounding unharvested forest (Di

Stefano, 2005). Quantifying the interactions between herbivor-

ous mammals and both their pre- and postharvest environment

may facilitate the development of browsing reduction plans

(Reimoser and Gossow, 1996; Partl et al., 2002).

Specifically, we make two predictions related to the

impact of harvesting on wallabies. As was the case for other

mobile generalist herbivores (e.g. Linnell and Andersen,

1995; Campbell et al., 2004), we expect harvesting to have

little immediate impact on space use (prediction 1), but

expect that wallaby density will increase in the first year after

harvesting due to increased food and shelter resources on

regenerating areas (prediction 2). In addition, we relate

browsing impact to the success of regenerating Eucalyptus

seedlings using a local regeneration standard (Dignan and

Fagg, 1997). Assessing browsing impact in relation to

regeneration standards enables forest managers to judge if

browsing impact is acceptable, or if management interven-

tion is needed (Reimoser et al., 1999).

2. Methods

2.1. Study sites

We collected data from the Pyrenees, Mt. Disappointment

and Black Range State Forests in Victoria, Australia (Fig. 1).

Wallaby density and browsing data were collected from all

three forests, while space use data were only collected from the

Pyrenees. All are relatively open, dry sclerophyll forests

dominated by Eucalyptus spp. The Pyrenees is the driest, most

open and least productive and has a seasonally abundant forb

community, while Mt. Disappointment and the Black Range

contain taller trees and a denser shrub layer facilitated by higher

rainfall and more fertile soils. Additional details regarding the

dominant plant species and physical geography of the study

areas within these forests are given in Table 1.

All three forests had been subjected to selective timber

harvesting throughout the nineteenth century, but since about

1970 the seed tree silvicultural system (Lutze et al., 1999) had

been predominantly used. Seed tree silviculture involves the

harvest of 10–30 ha patches while retaining four to nine mature

trees per hectare to provide seed for the next crop and habitat for

arboreal animals. Operations generally take place between late

spring and autumn (October to April) after which logging

debris is burnt to prepare a seedbed and stimulate seed fall.

Additional seed is added by hand or from the air if necessary,

and only in exceptional circumstances are nursery grown

seedlings planted. Over the years, this harvesting system has

produced a matrix of differentially aged patches of regenerating

forest surrounded by mature stands that show signs of historical

logging operations (usually single tree selection) to a greater or

lesser degree.

2.2. Study species

Swamp wallabies are 10–25 kg macropodid marsupials that

have been classified as browsers on the basis of dental

morphology (Sanson, 1980) and diet (Hollis et al., 1986). They

are solitary, non territorial and polygynous (Croft, 1989), and

Table 1

Vegetation, climate and physical geography of the study sites (LCC, 1973, 1978; BOM, 2006; DSE, 2006)

Site characteristics Forest structure Dominant understorey plants

Pyrenees State Forest, west-central Victoria

Rainfall: 600–700 mm/year Dry, open forest dominated

by messmate (Eucalyptus

obliqua)/blue gum

(E. globulus bicostata) or blue

gum/messmate associations.

Red ironbark (E. tricarpa),

red stringybark

(E. macrorhyncha) yellow box

(E. melliodora) and

candlebark (E. rubida)

occasionally present

Virtually absent middlestorey except for silver wattle (Acacia

dealbata) and cherry ballart (Exocarpos cupressiformis). Sparse

shrub layer includes common heath (Epacris impressa), gorse

bitter-pea (Davisia ulicifolia), common cassinia (Cassinia

aculeata) and prickly wattle (A. paradoxa). Ground layer

dominated by austral bracken (Pteridium esculentum) and grasses

including common tussock grass (Poa labillarderi) and silvertop

wallaby grass (Joycea pallida). Supports a seasonally abundant

forb community including soft crane’s bill (Geranium

potentilloides), kidney weed (Dichondra repens), creeping oxalis

(Oxalis corniculata) and bidgee-widgee (Acaena novae-zelandiae).

Soils: Stony red duplex

Overstorey Ht: 15–28 m

Crown cover: 70–84%

Elevation: 500–700 m a.s.l.

Mt. Disappointment State Forest, central Victora

Rainfall: >1000 mm/year Dry forest dominated by

messmate/mountain grey

gum (E. cephellocarpa)

associations

Virtually absent middlestorey except for silver wattle. Moderate

shrub layer includes common cassinia, prickly current bush

(Coprosma quadrifida), hop goodenia (Goodenia ovata). Tree

ferns (Dicksonia spp.) found in wet gullies. Ground layer includes

austral bracken, grasses and a sparse forb community

Soils: Red friable earths


Crown cover: 70–84%


Black Range State Forest, northeast Victoria

Rainfall: >1000 mm/year Dry forest dominated by

pure messmate and

messmate/peppermint

(E. radiata) associations

Middlestorey occasionally present including silver wattle, blanket

leaf (Bedfordia arborescens) and hazel pomaderris (Pomaderris

aspera). Moderate shrub layer includes musk daisy-bush (Olearia

argophylla), common cassinia, prickly current bush and hop

goodenia. Tree ferns found in wet gullies. Ground layer includes

austral bracken, grasses and a sparse forb community

Soils: Red friable/shallow stony earths


Crown cover 70–84%


J. Di Stefano et al. / Forest Ecology and Management 253 (2007) 128–137130

young are conceived and born throughout the year (Paplinska

et al., 2006). Swamp wallabies select densely vegetated habitats

during the day (Troy et al., 1992) but move into more open

habitats to forage at night (Swan et al., unpublished manu-

script). Home ranges are relatively small (15–40 ha) and

temporally stable (Troy and Coulson, 1993; Wood, 2002), and

range size has been correlated with the availability of important

resources (Di Stefano et al., unpublished manuscript). The

dispersal of young males has been observed, but the age of

dispersal never quantified. In the context of native forest timber

harvesting, the species responds positively to densely vegetated

one to two year old regenerating areas (Di Stefano, 2005), but

the effect has never been quantified or examined in relation to

regenerating sites of other ages.

2.3. Wallaby capture and radio-tracking

Wallaby movement data were collected in the Pyrenees State

Forest (Fig. 1). We collected data before, after and in some

cases during harvesting and analysed them within the frame-

work of a Multiple Before–After Control-Impact (MBACI)

design with a single before and after sample (Downes et al.,

2002).

To increase the likelihood of spatial independence,

unharvested control locations were defined as stands of

unharvested forest at least 1.5 km from each other and from

other disturbed areas. We randomly selected six control

locations from a pool of 15 potential sites identified within the

area used for timber harvesting (above approximately 500 m

a.s.l.). Two sites originally intended for use as replicate

impact location were harvested during the study period.

However, the forest adjacent to one of these was subjected to

a fuel reduction burn about 12 months prior to harvest and the

postharvest slash burn at this site was also used to reduce fuel

in another adjacent unharvested patch. These factors resulted

in substantial differences between the two impact locations,

so in the final analysis we compared them to control sites

separately.

Wallabies were trapped from March to October 2004 using

double-layered traps designed for the purpose (Di Stefano et al.,

2005). We free-fed with carrots up to 4 weeks prior to trapping,

then used carrots and occasionally peanut butter as bait, setting

traps in the late afternoon and checking them early the

following morning. Once caught, wallabies were sedated with

an intra-muscular injection of Zoletil 100 (Virbac Australia

Ltd.) at 0.05 mg/kg and fitted with a Sirtrack radio-collar

(approximately 30 g) and two Allflex ear tags. We glued

reflective tape to both collar and tags to facilitate identification,

and at the point of capture recorded the weight, crus (leg) and

pes (foot) length of adults and the pes length of pouch young.

We initially caught and radio-collared 27 adult wallabies but

due to death (n = 1), battery failure (n = 2), and collar loss

(n = 9), the final analysis consisted of data from 15. Seven (two

male, five female) were from five control sites while the two

impact sites had six (three male, three female) and two (female)

wallabies, respectively. Due to the losses, the final sample was

relatively small, particularly with respect to males, and the data

should be interpreted with this in mind.


Wallabies were radio-tracked between April 2004 and August

2005 by homing-in on foot using a hand-held Yagi antenna

(Telonics RA-14) and a Telonics TR2 portable receiver and

positions were recorded using a Garmin 12 GPS unit, which

reported an estimated error of <15 m in 96.3% of cases. We

tracked in all weather and at all times of the day and night

(defined as completely dark), and tracking was scheduled so that

nocturnal and diurnal locations for each wallaby were spread

approximately evenly throughout these periods. In order to

minimize disturbance to individuals we left at least 6 h between

tracking events and obtained no more than two fixes per

individual in a 24 h period. On average (�95% CI), wallabies

were tracked for 101.9 � 36.0, 100.8 � 20.5 and 88.0 � 6.4

days in the pre-, during- and postharvest periods, respectively.

Because we did not always see wallabies before disturbing

them, we used a 1–5 rating system to quantify location

accuracy: (1) within 5 m of exact location, (2) 5–25 m, (3) 25–

100 m, (4) 100–200 m and (5) >200 m, or when a signal could

not be detected. Due to their relative inaccuracy, a GPS reading

was not taken for rating 5s. In cases where we saw or heard the

wallaby (rating 1, 2 and most 3), locations were based on visual

and aural cues. In cases when the wallaby moved before it was

observed, (some 3 and all 4), we estimated its pre-disturbed

location on the basis of aural feedback from the tracking

equipment in relation to the local terrain. The mean (�95% CI)

percentage of locations that corresponded to each rating was (1)

49.8% � 11.7, (2) 19.6% � 5.7, (3) 23.7% � 7.3, (4)

4.7% � 2.4 and (5) 2.2% � 1.6. Prior to analysis we removed

a single rating 4 location from four individuals as they resulted

in large range size increases, which we defined as �10%.

Due to the time required to catch animals at multiple sites,

different harvest start dates for each impact site, time delays in

the harvesting process and the need to cull a number of control

wallabies for another study, the before and after periods at each

site did not completely overlap. This introduced time as a

potential confounding factor, although we do not believe its

effect was likely to be large. Two control animals were tracked

for extended periods and showed no temporal change in their use

of space, and other wallabies monitored for>12 months (data not

shown) demonstrated strong fidelity to their home range over a

number of seasons. Consequently, any effects observed in this

study are most likely attributable to the harvesting treatment.

The final data set contained 1379 positions with 79.7% � 1.0

(mean � 95% CI) collected during the day. The mean number of

positions per individual within each monitoring period (before,

during and after) was 32.3 � 0.9 (max = 34, min = 30) and

31.2 � 0.8 (max = 36, min = 26) for control and impacted

locations, respectively. We collected about 30 locations for each

animal in each time period as 30 is considered a minimum for

kernel based home range estimation (Seaman et al., 1999), and

similar sample sizes reduces bias from comparisons (Kenward,

2001).

2.4. Wallaby density

Wallaby density data were obtained at 10 sites (five control,

five impact) established across the three study forests (Fig. 1).

Four sites (two impact, two control) were established in each of

the Pyrenees and the Black Range, and two sites (one impact,

one control) at Mt. Disappointment. The design conformed to a

traditional MBACI with data collected at multiple control and

impact sites a number of times before and after harvesting

(Downes et al., 2002).

Because the Black Range State Forest had been intensively

harvested during the last half century, it was difficult to find

potential unharvested control locations far enough away from

previously harvested sites to be spatially independent of them.

We therefore defined control locations in all forests as

potentially harvestable stands regardless of their position

relative to previously harvested areas, which differs from the

spatially isolated controls used to test prediction 1. As a

consequence, the two control locations in the Pyrenees were

selected in addition to those already chosen to collect wallaby

movement data (see Section 2.3), although wallabies were

radio-tracked at the two impact locations in this forest. The final

control locations were selected at random from a larger pool of

potential sites, and were at least 1.5 km from impact locations.

The population of impact sites was limited by harvesting plans

and we used sites that were available within the study’s

timeframe.

At each of the 10 sites we defined an approximately square

10-ha area and used a randomly positioned grid to locate about

30 (min = 25) 15 m2 permanent circular plots. Beginning in

March 2004 we counted wallaby faecal pellets in these plots

(Southwell, 1989) every month for 3 months and then every 2

months thereafter until July 2006. We assumed that pellet

numbers reflected wallaby density (Johnson and Jarman, 1987),

although they may also be related to changes in activity. On

virtually all occasions we were able to differentiate between

swamp wallaby pellets and the pellets of other macropods

(mainly eastern grey kangaroos, Macropus giganteus) on the

basis of size, shape, colour and internal texture (Triggs, 2004).

A small number of unidentified pellets (2.6% of the sample)

were excluded from subsequent analysis.

Data were collected on five occasions before harvesting and

on seven occasions afterwards, although due to the onset of

harvesting operations only three of the impacted sites

contributed to all five pre-harvest counts. Postharvest burning

was conducted at all impacted sites during April or May 2005

and plots were re-established at this time. Postharvest plots

were not in exactly the same position as pre-harvest plots, but

were systematically spread over the same (or very similar)

10 ha area. At each site the number of pellets on each plot was

converted to pellets/ha/day and then averaged to generate a

measure of relative density at each site for each monitoring

time. These site means were used in the analysis described

below.

2.5. Browsing impact

A browsing assessment was conducted on all five

regenerating areas during April 2006, approximately 12

months after the postharvest, burn and shortly after a major

increase in scat numbers at these sites. We used the previously


established scat counting plots as a sampling frame to assess

browsing damage and density of regenerating Eucalyptus

seedlings, although new 15 m2 plots were established in

adjacent positions to remove any effect of repeated visits on

regeneration success, and in one case we used smaller plots

(4.37 m2) due to high seedling density. In the Pyrenees,

predominant tree species included messmate (E. obliqua) and

blue gum (E. globulus bicostata) at site 1 and messmate, blue

gum and a mix of candle bark (E. rubida) and red stringybark

(E. macrorhyncha) at site 2, and were regenerating as both

seedlings and coppice. Eucalypt regeneration at Mt. Dis-

appointment and the Black Range consisted almost completely

of messmate seedlings. Because both seedlings and coppice

were present in the Pyrenees, we conducted assessments for

both types of regeneration at these sites.

We assessed between 108 and 140 seedlings per site for

browsing by selecting the five (occasionally fewer in sparsely

regenerating patches) seedlings closest to plot centres and

estimating the amount of biomass removed to the nearest 5%.

The type of damage (side leaves, growing tip, whole crown,

etc.) was also recorded. At the two Pyrenees sites, coppice was

assessed in the same way except that the five stems were

randomly selected from one or two multi-stemmed coppicing

stumps. Browsing impact was averaged for seedlings (or

coppice stems) within plots, and then the site value expressed as

an average of the plot means.

To be operationally relevant, browsing impact should be

linked to regeneration standards (Reimoser et al., 1999), which

in southeastern Australia are defined by stocking, the

proportion of 16 m2 plots containing a viable seedling (e.g.

Dignan and Fagg, 1997). Although stocking surveys are usually

conducted 18–30 months after harvesting, results as early as 12

months postharvest are still acceptable (Dignan and Fagg,

1997).

We related browsing impact to stocking by defining

browsing impact, BI, as the reduction in stocking due to

browsing:

BI ¼ ST � SA

where ST is the total stocking and SA is the stocking adjusted for

browsing impact. While BI is a measure of browsing impact,

regeneration is unacceptable if SA falls below a minimum

standard, which for the sites used in this study was 65%.

Normally, ST would be calculated as the percentage of 16 m2

plots containing at least one seedling, regardless of browsing

damage, while SA would be the percentage of plots containing

at least one undamaged or substantially undamaged seedling,

where substantial damage is defined as the removal of the whole

crown (Wilkinson and Neilsen, 1995). Due to different sized

plots (15 and 4.37 m2) used in this study, however, we estimated

16 m2 stocking from an h-factor graph (Lutze, 2003), which

represents the relationship between seedling density, hetero-

geneity (Mount, 1961) and 16 m2 stocking. ST and SA were

estimated using total and adjusted seedling density, respec-

tively, where for each plot adjusted density = total densi-

ty � (1 � PSD), and PSD was the proportion of seedlings

substantially damaged.

2.6. Data analysis

Conventional analysis, bootstrapping procedures and home

range calculations were performed in GenStat 8, Pop Tools

(Hood, 2005) and Ranges VI (Anatrack Ltd.), respectively. We

generated home range (95% fixed kernel) and core range (50%

fixed kernel) estimates for pre-harvest, postharvest and, where

applicable, during-harvest periods, and calculated the percen-

tage overlap of postharvest and during-harvest ranges on pre-

harvest ranges. Distances between before/during and before/

after geographic centres of location (GCLs) were also

calculated. At control sites, range size data from before and

after harvesting were converted to a single variable by

calculating the before/after difference and expressing it as a

percentage of the pre-harvest value. At impact sites, the same

procedure was followed but the before/during differences were

also calculated, resulting in a before/during and a before/after

contrast.

Because male and female mammals may have substantially

different ranging behaviour (Clutton-Brock, 1989), we initially

analysed the data for each variable (95% range size, 50% range

size, 95% range overlap, 50% range overlap and distance

between GCLs) using both combined male and female and

females only data sets. The results were very similar, so the

combined data set was used in the final analysis. Inferences

about harvesting impacts on the five variables were made by

comparing the single value from each impact site to the mean

and associated 95% confidence interval derived from the

control sites. Due to the presence of outliers, we used 10,000

bootstrap iterations to calculate 95% confidence intervals

around the mean control values.

To determine an appropriate smoothing factor for the home

range estimates we initially used the median multiplier from the

sample of least squares cross validated results (Kenward, 2001)

but this value (0.6) resulted in some home range outlines that

were fractured into multiple segments and biologically

nonsensical. Results were reported based on a multiplier of

0.8 as the home range outlines generated were most consistent

with the perception of space use acquired throughout the

tracking regime.

We used a four factor repeated measures ANOVA to assess

the impact of harvesting on wallaby density. The factors were

State Forest (Pyrenees, Black Range and Mt. Disappointment;

used as a blocking factor), Treatment (control and impact), BA

Period (before and after) and Monitoring Time nested within

BA Period. Although this analysis tests multiple statistical

hypotheses, the two of primary interest are the Treatment � BA

Period and Treatment �Monitoring Time (BA Period) inter-

actions. This type of analysis is described in detail by Downes

et al. (2002).

We calculated the Greenhouse–Geisser epsilon to assess

the assumption of equal correlation between the monitoring

times (G–G epsilon = 0.26), and ultimately used it to adjust

the outputs of the analysis. The assumptions of normality

and homogeneity of variance were tested with a half-normal

plot and a fitted-value plot, respectively, and a log10(x + 0.1)

transformation was deemed necessary. As logarithmic


transformations reduce the effect of large values, they may

result in the loss of biologically important patterns (Keough

and Mapstone, 1995). In addition, interpreting effects on the

transformed scale can sometimes be difficult (Stewart-Oaten

et al., 1992; Jaccard and Guilamo-Ramos, 2002). Therefore,

to examine this potential effect on the Treatment � BA

Period interaction using the raw data, we generated 95%

confidence intervals around the mean before/after diffe-

rences at control and impact sites using 10000 bootstrap

iterations.

3. Results

3.1. Space use

The percentage of pre-harvest wallaby locations in areas that

were subsequently harvested or disturbed by the harvesting

process ranged from 3.0 to 94.4%. Wallabies with a small

percentage of their pre-harvest locations in subsequently

disturbed areas were not attracted into them during harvesting

or up to 3 months after. Wallabies that spent more time in

disturbed areas before harvesting moved away when harvesting

began, but still used the disturbed area to some extent

throughout the during-harvest and postharvest periods

(Table 2).

The effect of harvesting (Fig. 2) was most clearly shown by

changes in home range overlap. In most cases, 95% home range

overlap was less at impact sites than controls (Fig. 2C), and,

with the exception of the before/after contrast at Impact Site 1,

this effect was accentuated when 50% overlap was measured

(Fig. 2D). In general, this demonstrated an almost complete

shift away from pre-harvest core use areas in the during- and

postharvest periods.

The effect of harvesting on home range size (Fig. 2A and B)

differed markedly between the two impact sites. Relative to

controls, 95% range size (Fig. 2A) decreased at Impact Site 1

but tended to increase at Impact Site 2, particularly for the

before/after contrast. Nevertheless, the large before/after

Table 2

Percentage of wallaby locations within the area disturbed by the harvesting

operation

Impact site ID Locations in disturbed area (%)

Before During After

1 F1 3.3 0 3.1

1 F2 9.1 13.8 0

2 F1 3.1 (6.3) 0 3.2 (3.2)

2 F2 3.0 (30.0) 0 0 (3.1)

2 F3 41.7 (94.4) 3.1 0 (30.3)

2 M1 25.8 (45.2) 12.9 11.8 (29.4)

2 M2 9.7 (34.2) 15.2 0 (10.7)

2 M3 22.6 (48.4) 3.0 0 (3.3)

Before: before harvest; During: between harvest onset and burning of logging

debris; After: after burning. F: female; M: male. On average (�95% CI),

wallabies were tracked for 101.9 � 36.0, 100.8 � 20.5 and 88.0 � 6.4 days in

the pre-, during- and postharvest periods, respectively. At Impact Site 2, a

substantial area was burnt but not harvested so numbers in parenthesis refer to

locations in either harvested or burnt areas.

contrast values at Impact Site 2 represented the mean response

of a number of individuals and hides substantial within-site

variation. While the mean change in home range size was

116%, the 95% confidence interval was 3 to 229%, and was

generated on the basis of three large range increases and two

moderate range reductions. Results from the 50% range size

analysis (Fig. 2B) were variable at both control and impact

sites, and no clear patterns were evident.

At control sites the mean (95% CI) distance between the

before and after geographic centre of location (GCL) was

65.5 m (31.9–124.4 m). At Impact Site 1 the distances

between both the before/during (100.5 m) and before/after

(39.0 m) GCLs were within the control site confidence

interval, although the latter value was close to the lower

bound. At Impact Site 2 the distances between both the

before/during (151.7 m) and before/after (204.4 m) GCLs

were outside the control site confidence interval. The largest

distance moved was by M3 (Table 2) whose postharvest GCL

was 340 m from his pre-harvest one. Even so, his postharvest

95% home range overlapped his pre-harvest home range

by 20.5%.

3.2. Wallaby density

There was a clear effect of harvesting on relative wallaby

density. The raw data (Fig. 3) suggested a substantial

Treatment � BA Period interaction, and although not

detected statistically by the analysis using transformed data

(df = 1, F = 0.02, P = 0.9), analysis of the raw data showed

a substantial effect. Based on 10000 bootstrapped samples,

the mean (95% CI) before/after difference between control

and impact locations was 21.5 (12.3–30.4) pellets/ha/day.

The mean before/after difference is equivalent to the

Treatment � BA Period interaction, and an effect is implied

as the lower confidence bound is substantially larger than

zero.

In addition, the analysis of transformed data provide strong

statistical evidence for the Treatment � Time (BA Period)

interaction (df = 10, F = 10.97, P = < 0.001), which was

driven by the contrast between the first three and last four

postharvest measurements (Fig. 3). During the first three

postharvest measurements, wallaby density at controls was

substantially more than at impact sites (e.g. control minus

impact difference (�CI of difference) at July 2005 was

6.9 � 3.1 pellets/ha/day) but this pattern was reversed at

subsequent monitoring times. At impact sites, there was a

clear trend of increasing density with time after harvest,

although the shape of the trend beyond July 2006 is unknown.


Mean biomass loss from eucalyptus seedlings ranged from

1.0 to 11.2% with both sites in the Pyrenees and one in the

Black Range experiencing the highest browsing impact. In

contrast, biomass loss from coppice stems was 0.9 and 0.4%

at the two Pyrenees sites. The percentage of seedlings

with missing crowns (considered to be seriously damaged;

Fig. 2. The effect of harvesting on (A) 95% range size, (B), 50% range size, (C) 95% range overlap and (D) 50% range overlap in the Pyrenees State Forest. Overlap is

calculated as the percentage of the during- or postharvest home range overlapping the pre-harvest home range. Error bars are bootstrapped 95% confidence intervals.


Wilkinson and Neilsen, 1995) ranged from 0 to 12.9%. In order

of increasing effect, browsing impact (BI, the reduction in

stocking due to browsing) at the five sites was 0, 0, 1, 2 and 3%,

indicating that mammalian herbivory had an insubstantial

effect on Eucalypt regeneration success.

Fig. 3. Effect of harvesting on relative wallaby density. Pre-harvest data March

to September 2004, postharvest data July 2005 to July 2006. Error bars are 95%

confidence intervals.

4. Discussion

4.1. Impact of harvesting on swamp wallabies

Consistent with prediction 1, immediate and short term (3

months postharvest) effects of harvesting on space use were

minor. Although most wallabies shifted the location of their

core range in response to harvesting and some appeared to

greatly increase the size of their home range, individuals were

relatively unperturbed by the harvesting process, even when

logging machinery was operating. The wallabies most affected

were at Impact Site 2 (e.g. F3, M1 and M3 in Table 2). While

these individuals modified their movements slightly to avoid

the harvesting operation, all continued to use parts of their pre-

harvest range within the during- and postharvest periods.

Mobile animals like wallabies have the ability to avoid

harvesting and other disturbances while still using familiar

areas. Results from other BACI-type studies investigating the

effects of harvesting on medium to large generalist herbivores

have shown that indices of home range size and overlap differed

little between individuals that occupied harvested sites and

those that did not (Edge et al., 1985; Linnell and Andersen,

1995; Campbell et al., 2004). Although we did not collect these

data, the observed changes in space use reported here appeared

to have little effect on the availability of important resources in

the short term, although for other species this may depend on


factors such as population density and territoriality. This is in

contrast to the immediate and short-term effect of harvesting

and other similar disturbances on arboreal animals (Tyndale-

Biscoe and Smith, 1969; Lindenmayer et al., 1991; Gibbons

and Lindenmayer, 1996; Lindenmayer and Franklin, 1997;

Newell, 1999; Kavanagh, 2000), which suffer a direct reduction

of important resources, and may die as a result.

Reduced use of the disturbed areas in the first 3 months after

harvesting by radio-tracked individuals is consistent with

results from the faecal pellet survey. Relative to the pre-harvest

baseline, postharvest density was initially very low but, in

support of prediction 2, began to increase about 8–10 months

after the postharvest burn, and by the end of the monitoring

period was at least five times pre-harvest levels. Although it is

possible that a postharvest differential in pellet detectibility

developed due to rapid vegetation growth at impact sites, any

associated bias was likely to be minor relative to the size of the

observed effect.

Similar increases in the density of other mammalian

herbivores within 12 months of harvesting have been found

in both native forests (St-Louis et al., 2000) and plantations (le

Mar and McArthur, 2005), and elevated moose (Alces alces)

and mule deer (Odocoileus hemionus) density were positively

correlated with increased forage availability resulting from pre-

commercial thinning (Sullivan et al., 2007). Although it was not

an objective of this study to quantify the reasons for the

observed density effect, qualitative observations suggest that

the presence of shelter was important. During this and a

previous study (Di Stefano, 2005), we observed wallabies on

harvested areas only after regenerating vegetation (mainly

eucalypt seedlings, eucalypt coppice and austral bracken,

Pteridium esculentum) had grown to wallaby height. On a

number of occasions we disturbed individuals sheltering next to

1–2 m tall coppice regrowth and pellet numbers close to re-

sprouting vegetation appeared relatively high. Whatever the

causal factors, it is clear that swamp wallabies perceived

harvested areas to be a favourable habitat less than one year

after the postharvest burn, and that this effect was consistent

across the landscape.


We assumed that the majority of browsing damage was

caused by swamp wallabies, although other herbivorous

mammals (e.g. eastern grey kangaroos, European rabbits,

Oryctolagus cuniculus, sambar and fallow deer, Cervus

unicolour and Dama dama, and brushtail possums, Tricho-

saurus vulpecular) were also present. On the basis of observed

faecal pellet numbers, the abundance of deer and possums

appeared to be very low relative to swamp wallabies.

Kangaroos and rabbits were relatively abundant, but kangaroos

are predominantly grazers (Sanson, 1980), and thus are unlikely

to eat tree seedlings, while rabbits often leave bitten-off shoots

lying on the ground which we did not observe.

In addition to mammalian browsing, the success of

postharvest eucalypt regeneration is influenced by factors

including seed supply, seedbed condition, overwood competition

and local climate (Squire et al., 1991), and final regeneration

outcomes are likely to result from some combination of these

effects. However, the development of an efficient strategy to

reduce browsing requires the effect of browsing on regeneration

success to be separated from other factors, and the index of

browsing impact (BI) presented in this study enables this to be

achieved. By directly linking herbivore impact to an operational

measure of regeneration success, the effect of browsing on

regeneration standards can be quantified.

For regeneration to be deemed acceptable for the harvested

areas assessed in this study, stocking must be�65%. Of the five

monitored sites, two were well below this level and three well

above it, so regeneration standards were either met or not

regardless of the small browsing impact (max. BI value = 3%).

In situations where total stocking levels are just above the

standard, small reductions attributable to browsing could be

important. Thus the importance of browsing impact not only

depends on browsing severity, but on the total stocking level as

well.

BI is a useful measure only if herbivory does not reduce the

ability to identify seedlings (e.g. by killing them or making

them difficult to find by removing almost all the biomass). If

this occurred, total stocking, ST, would be underestimated,

resulting in the underestimation of BI. Available evidence from

southeastern Australia indicates that although browsing can

substantially damage seedlings, it does not kill them in the short

term (Bulinski, 1999; Bulinski and McArthur, 1999; Di

Stefano, 2005). Nevertheless, careful monitoring may be

required to identify live seedlings with missing crowns and

generate an accurate estimate of ST.

4.3. Management implications

Harvesting had little impact on the space use of swamp

wallabies. It did, however, result in regenerating patches that

became highly attractive to this species 8–10 months after the

postharvest burn, and supported relatively large numbers of

individuals after this time. As high densities of mammalian

herbivores can have adverse effects on plant community

composition (Horsley et al., 2003), and may also affect other

aspects of ecosystem function (Bardgett et al., 1998; Wardle

et al., 2001) it would seem prudent for forest managers to

monitor such potential effects in south eastern Australian

harvested landscapes.

From a management perspective, browsing impact is only

important if it causes measures of regeneration success to fall

below established standards. Thus the variable of interest is the

reduction in regeneration success attributable to browsing,

defined here as BI. In the context of southeastern Australia,

browsing impact that causes stocking values to fall below the

minimum standard (65% for the sites used in this study) should

be deemed unacceptable. Currently, operational assessment of

browsing impact is made by measuring height loss and

recording the amount of biomass removed (Dignan and Fagg,

1997; Forestry Tasmania, 1999), and these measures may not

reflect the degree to which browsing mammals alter regenera-

tion success. Using BI as an index of browsing impact will


provide forest managers with the information to decide whether

browsing impact is acceptable, or a problem requiring action.

Finally, it seems that in areas where the practice is

acceptable, the promotion of coppice stems may reduce the

effect of browsing on regeneration success.

Acknowledgments

We thank Graham Hepworth for statistical advice and Merv

Flett, Bruce McTavish, Lachlan Spencer and Bob McPhail for

facilitating field work. The comments of two referees helped to

improve the manuscript. Funding was provided by the

Holsworth Wildlife Research Endowment, the Victorian

Department of Sustainability and Environment (DSE) and

the University of Melbourne (School of Forest and Ecosystem

Science and Department of Zoology). J.D. was supported by an

Australian Postgraduate Award. This research was conducted in

conjunction with DSE permit No. 10002779 and Melbourne

University Faculty of Science Animal Experimentation

Committee permit No. 03249.

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