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Journal of Mammalogy, 89(2): 398–407, 2008
Responses of a carnivorous marsupial (Antechinus flavipes) to local habitat factors in two
types of forests in south-eastern Australia
Hania Lada, Ralph Mac Nally*, and Andrea C. Taylor
Australian Centre for Biodiversity: Analysis, Policy and Management, School of Biological
Sciences, Monash University, Victoria, 3800, Australia
*Correspondent:
Running head: Response of antechinus to habitat
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ABSTRACT
Ecosystems around the world have been degraded or destroyed by human activities, including
regulation of river flows, clearance of vegetation and removal of fallen timber. In
southeastern Australia much of the original vegetation was converted to farmland. Remaining
forests such as hilly box-ironbark and floodplain river red gum (Eucalyptus camaldulensis)
are mostly re-growth. The yellow-footed antechinus (Antechinus flavipes) inhabits both types
of forests and is the only small, native, carnivorous mammal on most floodplains in
southeastern Australia. In this region, frequency of flooding has been reduced by regulation of
river flows, which has led to decline in conditions favourable for flood-adapted terrestrial and
aquatic organisms. Here, we compared numbers of A. flavipes in box-ironbark forests, and in
river red gum forests that were deprived of floods; partially inundated with environmental
flows; flooded naturally; and watered in large, artificial floods. We found that abundance of
A. flavipes on floodplains and in box-ironbark forests increased with larger volumes of fallen
timber and with greater numbers of large, old trees. In river red gum forests, numbers of 2nd-
year females increased with proximity to flood locations. For conservation purposes, we
recommend preservation of large trees, restoration of fallen-timber on forest floor, and spring
flooding of floodplains.
Key words: Antechinus flavipes, box-ironbark, Eucalyptus camaldulensis, fallen timber,
flood, hollow, logging, Murray River, river red gum, woodload
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INTRODUCTION
Ecosystems around the world have been degraded through anthropogenic actions (Sala
et al. 2000). Habitats have been lost due to activities such as clearance of vegetation, logging,
removal of fallen timber, and regulation of river flows (e.g., Cunningham et al. 2007; Maser
and Sedell 1994; Micklin 1988). These actions have led to decline or extinction of many
species (Sala et al. 2000; Wilcove et al. 1998). In Australia during the last 200 years, 18
species of endemic mammals have become extinct most likely because of human-induced
changes to environment (Johnson 2006). These changes principally involved introduction of
alien species, whose detrimental effects were exacerbated by degradation and loss of habitats
(Johnson 2006). Most of the native vegetation in the southeastern part of the continent has
been cleared for farming; for example, only 6% of the original tree cover remains in the
Murray Fans and Victorian Riverina bioregions (Bennett et al. 1998; Department of
Sustainability and Environment 2004). Remaining forests have been or are extensively
logged, and abundance of large, old trees has been reduced substantially (Environment
Conservation Council 1997). Many organisms rely on mature, hollow-bearing trees for shelter
and for foraging opportunities (e.g., Cameron 2006; Erickson and West 2003; Gibbons et al.
2002; Holloway and Malcolm 2007). Fallen timber also provides important ecological
resources (Harmon et al. 1986), but has been removed extensively for firewood over much of
southeastern Australia (Laven and Mac Nally 1998; Mac Nally et al. 2002a). Stripping fallen
timber from the forest floor simplifies habitat structure, which reduces shelter and foraging
opportunities (Harmon et al. 1986). Dependence on fallen timber has been shown for many
organisms (e.g., Gibb et al. 2006; Lindhe et al. 2004; Sippola et al. 2005; Waldien et al.
2006), including Australian saproxylic invertebrates (Grove 2002), and vertebrates such as the
brown treecreeper (Climacteris picumnus) (Mac Nally 2006; Mac Nally et al. 2002b) and the
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yellow-footed antechinus (Antechinus flavipes) (Lada et al. 2007b; Mac Nally and Horrocks
2002).
In Victoria, despite massive losses of habitats through logging and fallen-timber
removal, box-ironbark forests still support some native fauna, including A. flavipes
(Environment Conservation Council 1997). A. flavipes has a 2-week, synchronized, winter
mating season followed by obligatory die-off of males, and weaning of offspring in summer
(McAllan et al. 2006; McDonald et al. 1981; Woolley 1966). The species also inhabits river
red gum (Eucalyptus camaldulensis) forests of floodplains, where in most cases, it is the only
small, native, carnivorous mammal (Menkhorst and Knight 2001). These 2 types of forests are
markedly different. Box-ironbark forests grow on dry, upland areas, whereas river red gum
forests grow on floodplains and have evolved reliance on inundations. River red gum forests
along the Murray River have been subjected to clearance of vegetation, removal of fallen
timber, and regulation of river flows causing changes in flooding regimes (Close 1990). In
160 years since the beginning of European impacts on the floodplains, frequency of floods
has been reduced, especially in the last 50 years (Close 1990; Murray-Darling Basin
Commission 2005), and much of the native vegetation has been removed (Fahey 1988;
Walker et al. 1993). There is a scarcity of large, old trees in box-ironbark forests, which were
nearly completely cleared during the 19th century gold rush (Environment Conservation
Council 1997). These forests have been logged several times since and large trees were
deliberately removed in the 1930s and 1950s for silviculture (Muir et al. 1995), so that
virtually no old-growth box-ironbark forests remain in Victoria (Environment Conservation
Council 1997).
Lada et al. (2007b) showed that on the Murray River floodplains (in 3 river red gum
forests studied each year from 2003 to 2005) abundance of A. flavipes increased with
proximity to floods, higher fallen-timber loads and the number of large trees. These findings
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agreed with earlier studies reporting positive effects of fallen-timber loads on the abundance
of A. flavipes in 2 river red gum forests (Mac Nally and Horrocks 2002; Mac Nally et al.
2001). However, similar studies of A. flavipes have not been conducted in box-ironbark
forests, where effects of flooding are not relevant, fallen-timber loads are lower and there are
fewer large trees. Also, the responses of A. flavipes inhabiting river red gum forests on
floodplains of unregulated rivers, such as the Ovens River, remain undocumented. Mac Nally
et al. (2001) attempted to address this in relation to fallen-timber loads only, but failed to trap
A. flavipes on the Ovens floodplain in either 1998 or 1999.
Studies of abundance of mammals other than A. flavipes, before and after floods have
reported either declines or no changes (Andersen et al. 2000; Granjon et al. 2005; Jacob 2003;
Redhead 1979; Williams et al. 2001). Here, we investigated whether evidence for the positive
effects of proximity to floods on numbers of A. flavipes (Lada et al. 2007b) also are found on
floodplains experiencing natural flooding regimes as well as on floodplains inundated more
extensively than those in the study of Lada et al. (2007a). We test whether capture rates of all
individuals, males, females and 2nd-year females of A. flavipes in box-ironbark and in river
red gum forests are related to habitat variables that are of major management concern: fallen-
timber volumes, densities of large trees, and distance from floods (in river red gum forests
only). Capture rates are used here as a relative measure of animal abundances and, in the case
of 2nd-year females, survival of females beyond 1 year. We compare capture rates of A.
flavipes between nearby box-ironbark and river red gum forests, among river red gum forests
differing in current flooding regimes, and among box-ironbark forests.
MATERIALS AND METHODS
Study sites and captures of animals.—Individuals of A. flavipes were trapped once a
year in the austral autumn and winter in 2004 and 2005 at 0.25-ha sites, randomly selected from
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100 sites within 500 m × 500 m squares, in 7 river red gum forests and in 3 box-ironbark
forests. Minimum distances between sites were 0–150 m. Box-ironbark forests are dominated
by grey box (Eucalyptus microcarpa) and red ironbark (E. sideroxylon) in northern Victoria (E.
tricarpa in central Victoria), with some red box (E. polyanthemos) and red stringybark (E.
macrorhyncha), and with herbs, shrubs, leaves and fallen timber providing groundcover. River
red gum sites (denoted RRG) were in GuttrumRRG (centred on 35°35’S, 144°04’E; n = 32),
KoondrookRRG (35°43’S, 144°15’E; n = 27), GunbowerRRG (35°43’S, 144°13’E; n = 102),
BarmahRRG (35°52’S, 145°01’E; n = 29), MillewaRRG (35°50’S, 145°00’E; n = 30), OvensRRG
(36°13’S, 146°15’E; n = 13) and Reedy LakeRRG (36°42’S, 145°05’E; n = 23) (Fig. 1).
Groundcover is provided by fallen timber and bark in all river red gum forests, along with tall
grass in OvensRRG, and shrubs and reeds in Reedy LakeRRG. Box-ironbark sites (denoted BI)
were in ChilternBI (part of Chiltern-Mt Pilot National Park) (36°08’S, 146°36’E; n = 62), in
RushworthBI (36°39’S, 145°01’E; n = 40) and in the Killawarra section of Warby RangeBI State
Park (36°13’S, 146°11’E; n = 27) (Fig. 1). There were 385 sites in total. Relative and absolute
spatial distributions of sites are available from the corresponding author. GunbowerRRG,
BarmahRRG, MillewaRRG and OvensRRG forests were partially flooded in spring 2003 and 2004,
with the only natural flood occurring in the OvensRRG forest (Ovens River is unregulated).
Management agencies inundated the other forests with environmental flows, which are floods
used to stimulate ecological processes. BarmahRRG, MillewaRRG, GunbowerRRG and
KoondrookRRG are Ramsar-listed wetlands of international importance (Murray-Darling Basin
Commission 2005), yet KoondrookRRG has not been flooded since 1996. The Reedy LakeRRG
Wildlife Reserve is a small forest (730 ha) that fringes a swamp on the Goulburn River
floodplain, so that it has a different character to the other river red gum forests (Fig. 1).
At each 0.25 ha site, 5 or 6 small-mammal Elliott traps (33 × 10 × 9 cm; Elliott
Scientific Co., Upwey, Victoria, Australia), were placed on the ground in a straight line, 12 m
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apart. This number of traps was considered to be sufficient for sampling most animals in a
0.25 ha area because individuals moved so extensively across whole sites that they were
unlikely to miss locations of all traps (H. Lada, pers. obs.), recapture rates were high from
both the same and other sites, and traps on the same site were never saturated with individuals
of A. flavipes. Traps contained polyester bedding and bait (peanut butter, quick oats and
honey), were wrapped in plastic bags covered with bark and set for 1–5 nights, and checked at
dawn and dusk. Variation in trapping effort was due to early trap collection at sites that were
about to be logged or where individuals were repeatedly recaptured and further trapping was
deemed likely to be detrimental to the welfare of the animals. This variation in effort was
accounted for statistically. Animals were treated in a humane manner, research was
authorized by Monash University Biological Sciences Animal Ethics Committee, and
guidelines approved by the American Society of Mammalogists (Gannon et al. 2007) were
followed.
Recaptured individuals were identified by unique positions of ear-biopsy holes (2
mm), which had been taken for genetic analysis (Lada et al. 2007a). For statistical analysis,
we defined the total number of traps per site for each trapping period as the number of traps
on a site less the number of recaptures from the same site. This accounted for recaptures that
had rendered traps unavailable to new individuals. Red marsupia (pouches) and visible teats
identified 2nd-year females (teats of 1st-year females are not visible until the breeding
season).
Site measurements.—Site measurements for GuttrumRRG, KoondrookRRG and
GunbowerRRG forests were obtained from Lada et al. (2007b) and we followed methods
described therein to characterize each 0.25 ha site in MillewaRRG, BarmahRRG, RushworthBI,
Reedy LakeRRG, Warby RangeBI, OvensRRG and ChilternBI. Volumes of fallen timber (“vol”)
were estimated on each site by measuring length and diameter of each log with a diameter
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≥0.1 m. The numbers of dead and live large trees with diameter at breast height (DBH) ≥ 60
cm were counted for each site as the “Ltrees” variable. In BarmahRRG, MillewaRRG, OvensRRG
and Reedy LakeRRG forests, Euclidean distances between sites and flood fronts (“FloodDist”)
were obtained from field observations and flood maps (K. Ward, Goulburn-Broken
Catchment Management Authority, pers. comm.). In Reedy LakeRRG, FloodDist was the
Euclidean distance from each site to the exposed edge of the swamp, which had been covered
with water in the spring of 2003 and 2004 (H. Lada, pers. obs.). FloodDist for GunbowerRRG,
KoondrookRRG and GuttrumRRG sites were the same as in Lada et al. (2007a). All flooded
areas were covered with water for at least 1 week. We used 2003 and 2004 annual rainfall for
2004 and 2005 trapping data, respectively (Bureau of Meteorology 2003, 2004) as the
previous-year rainfall variable (“rain”). Given the antechinus life history, unfavourable
conditions for rearing offspring in the previous year would affect abundances of animals in
the following year.
Statistical analysis.—We used logistic regression in WinBUGS 1.4 (Spiegelhalter et
al. 2003) to determine the influence of local habitat factors on antechinus capture rates (of all
individuals, of males, of females and of 2nd-year females) in river red gum and box-ironbark
forests. Capture rate was the proportion of traps at a site that captured a unique individual or,
equivalently, the probability of success for a single trap at a given site in a given year. To
allow for differences in trapping effort, the binomial distribution was used for the response
variable, capture rate. The number of unique individuals rij caught at site i in year j was
treated as the result of nij Bernoulli trials with probability of trapping success pij, where nij was
the number of available traps. Survey year was treated as a categorical factor, with volume of
fallen timber (vol), number of large trees (Ltree) and distance to flood locations (FloodDist)
as linear covariates. For box-ironbark sites, the FloodDist variable was not applicable and was
not included. We added type-level fixed effects to account for possible habitat-type-related
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differences between river red gum sites and box-ironbark sites, site-level random effects to
account for possible temporal autocorrelations in repeated sampling, and forest-level random
effects to account for possible spatial correlations among sites within forests. The model was:
rij ~ binomial (pij, nij)
logit(pij) = α + yearj + βvol .volij + βLtree .Ltreeij + βflooddist .flooddistij + sitei + foresti + typei,
(1)
where βvol is the volume of fallen timber effect, βLtree is the number of large trees effect, and
βflooddist is the FloodDist effect, and sitei, and foresti are random effects, and typei is a fixed
effect.
To reduce correlation among model parameters and to speed model convergence, all
predictor variables were standardized before model fitting (Spiegelhalter et al. 2003):
X’mk = (Xmk −
€
X k)/sk, where
€
X k and sk are the mean and standard deviation of variable k and
Xmk is the mth value of that variable. We set year2004 = 0, so the intercept α is the mean capture
rate in 2004 and the year effects are deviations from that mean for year 2005. We set typeRRG
to zero. Year effects and all covariate coefficients were assigned uninformative normal prior
distributions, with means 0 and high variances (10,000). The random effects terms sitei, and
foresti, and the fixed effect term typei had normal prior distributions with means 0 and
common variances, σsite2, σforest
2 and σtype2, respectively. We gave uniform priors (0,50) to the
standard deviations of the random effects terms, σsite, σforest and σtype (Gelman 2005).
We sampled posterior distributions for 60,000 Markov Chain Monte Carlo (MCMC)
iterations after a 60,000 burn-in. Three different chains were run and the Gelman-Ruben
statistic was monitored to check for MCMC convergence (Brooks and Gelman 1998).
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We calculated the posterior probability and hence, posterior odds, that each
regression coefficient or fixed effect was either positive or negative, depending on the sign
of the parameter. The prior odds were set at 1:1 (i.e., the parameter was equally likely a
priori to be negative or positive) because we used an uninformative, normal prior
distribution. This means that the posterior odds are equivalent to Bayes factors (Jaynes
2003). Given the data, the Bayes factor is an odds ratio of superiority of one model or
hypothesis (A) over an alternative (B). In this case, HA is that the model parameter differs
from zero and HB is that the parameter does not differ from zero. Bayes factors > 10
provide strong evidence for one hypothesis over another, while 3 < Bayes factors < 10 are
moderate evidence (Jeffreys 1961), and Bayes factors < 3 are “hardly worth reporting”
(Kass and Raftery 1995).
We ran models with additional terms that potentially might affect capture rates,
namely rainfall, and year × FloodDist interaction. The latter allowed for different FloodDist
effects in 2004 and 2005 (see Lada et al. 2007b). We considered that flooding of river red
gum forests reduced the relevance of rainfall effects, so we added previous-year rainfall
variable (rain) to model (1) for box-ironbark forests only. All models were assessed with
Deviance Information Criterion (DIC, Spiegelhalter et al. 2002) for both sexes, males,
females and 2nd-year females. Models with the smallest DIC are most efficacious, but models
that differ by less than two DIC units are regarded as indistinguishable (Burnham and
Anderson 1998). In such cases we chose the simplest model (fewest parameters). Otherwise,
models with the lowest DIC were accepted as the most parsimonious representations.
When no FloodDist effect was observed, we repeated analyses with values of the
FloodDist variable excluded for one forest (BarmahRRG, MillewaRRG, OvensRRG or Reedy
LakeRRG). This allowed us to determine whether results reported by Lada et al. (2007a) were
unique to the GuttrumRRG-KoondrookRRG-GunbowerRRG area, or whether a particular forest
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was responsible for a lack of effect. If FloodDist effect is present when a particular forest is
excluded from the analysis, it indicates that the inclusion of the forest had caused
disappearance of the effect.
We compared capture rates among select pairs of forests using equation1. Within any
WinBUGS MCMC run, one can compute probability distributions for any function of model
parameters that are estimated. The pij values are the estimates of capture rates in forest i in
year j, which can be averaged over years to produce pi, the forest i-specific rate. We then
compute the difference between, say, pOvens and pWarby Range as (pOvens – pWarby Range) and
monitor its value in the MCMC run. We can use the same inferential method (Bayes factors)
as described above. Capture rates were compared between closely located pairs of river red
gum and box-ironbark forests: OvensRRG and Warby RangeBI (6 km); and Reedy LakeRRG and
RushworthBI (4 km). We compared all pairs of box-ironbark forests, and pairs of river red
gum forests with different, recent flooding history: KoondrookRRG (not flooded since 1996)
was compared with MillewaRRG (controlled floods in 2003 and 2004). Both are forests
growing on the New South Wales (northern) Murray River floodplains. We also compared
OvensRRG and BarmahRRG, both Victorian forests flooded in 2003 and 2004 by the
unregulated Ovens River and the regulated Murray River, respectively. OvensRRG was
compared also to MillewaRRG.
RESULTS
Site measurements and captures of animals.—In 2004 and 2005 (9,754 trap nights,
excluding traps with recaptures on the same site), 62 individual females were captured on 77
sites, and 90 different males on 130 sites in box-ironbark forests. Over the same period, 205
individual females were trapped on 232 sites and 265 different males on 310 sites in river red
gum forests (numbers of females and males in each forest are available from the
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corresponding author). Second-year females were not trapped in either Warby RangeBI or
GuttrumRRG forests.
Fallen-timber volumes were very low in box-ironbark forests, but higher in river red
gum forests (Table 1). Numbers of large trees per site were 0–18 in river red gum forests and
0–5 in box-ironbark forests (Table 1). All 0.25-ha sites in Reedy LakeRRG, OvensRRG and
BarmahRRG had at least 1 large tree. Large trees were absent from 3% of sites in both
MillewaRRG and GuttrumRRG , 12% of sites in GunbowerRRG, 15% in KoondrookRRG, 32% in
RushworthBI, 46% in Warby RangeBI and 69% in ChilternBI.
Effects of local habitat factors in box-ironbark and river red gum forests on capture
rates.—Deviance Information Criterion (DIC) values were much smaller for model 1 (3
covariates) than for the model with rainfall (4 covariates), for females, second-year females,
males and all animals. Adding year × FloodDist interaction to model 1 improved the fit only
for males. Therefore, the model with the interaction was chosen for males, and model 1 for
the other classes of animals.
We found strong evidence that capture rates increased with greater volumes of fallen
timber for females, 2nd-year females, males and all individuals (Table 2, Fig. 2). There was
moderate evidence for positive effects of abundance of large trees on survival of females to a
2nd year, which was suggested by the increase in capture rates of this class of animal with the
greater number of large trees (Table 2). Large trees also had a positive effect on capture rates
of females and all animals (Table 2, Fig. 2). There was moderate evidence that capture rates
decreased with the distance to flood locations (the FloodDist effect) for males in 2004 and for
second-year females (Table 2, Fig. 2).
There was no evidence for a flood-distance effect for females. However, a negative
response (i.e., a decrease in numbers of females with distance from inundations) was observed
after FloodDist variables for BarmahRRG were removed. In their absence, the evidence for the
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negative effects of FloodDist on animal abundance was moderate for females, and strong for
2nd-year females and moderate for all individuals (data not shown). Removing FloodDist
variables for one of OvensRRG, MillewaRRG or ReedyRRG reduced evidence for FloodDist
effects because of the influence of BarmahRRG.
Comparisons of capture rates among forests.—We found strong evidence that capture
rates of all animals, females, 2nd-year females and males were higher in Reedy LakeRRG
forest than in nearby RushworthBI forest (Table 3). Capture rates of females were substantially
higher in OvensRRG (natural flood) than in nearby Warby RangeBI (flood irrelevant), in
GuttrumRRG (no flood since 1996), BarmahRRG (controlled large flood), and MillewaRRG
(controlled large flood) (Table 3). In contrast, males were substantially more abundant in each
of GuttrumRRG and BarmahRRG than in OvensRRG forests (Table 3). We found strong evidence
that capture rates of all individuals, females, males and 2nd-year females were higher in
ChilternBI than in either RushworthBI or in Warby RangeBI forests, and were higher for males
in RushworthBI than in Warby RangeBI (Table 3).
DISCUSSION
Our hierarchical analysis of the effects of local habitat factors in box-ironbark and
river red gum forests on capture rates of A. flavipes in 2004–2005 gave partly similar results
to those reported by Lada et al. (2007b) for flood-deprived and partially inundated river red
gum floodplains along Murray River, visited between 2003 and 2005. Data from Lada et al.
(2007a) for 2004 and 2005 were part of both studies. In both studies, there was strong
evidence for an increase in number of females with higher fallen-timber volumes and greater
number of large trees. We found that abundance of males increased with larger fallen-timber
volumes and proximity to floods, whereas Lada et al. (2007a) also found positive effects of
large trees. Here, evidence was moderate rather than strong for increased survival of females
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to a 2nd year with proximity to floods. In both studies evidence was moderate and strong for
positive effects of large trees and of fallen-timber on 2nd-year female numbers, respectively.
From comparisons between the 2 studies, we infer that the most consistent evidence was for
increases in animal abundances with larger fallen-timber volumes.
Fallen timber is likely to provide shelter and may be particularly important in habitats
with little vegetative groundcover, such as in river red gum forests along the Murray River.
Stokes et al. (2004) showed that foraging activities of A. flavipes and common dunnarts
(Sminthopsis murina) increased when refuges (wire netting on the ground) from predators
were provided. Hollow logs provided den sites for spot-tailed quolls (Dasyurus maculatus)
more often than did any other features (Glen and Dickman 2006). In addition to structural
complexity, fallen timber offers foraging opportunities. Pouncing birds most frequently
swooped on prey from logs (Antos and Bennett 2006). Mac Nally (2006) showed that, in river
red gum forests, the vulnerable brown treecreeper Climacteris picumnus preferred fallen-
timber volumes of ≥ 67 m3 /ha (reported as woodloads of ≥ 40 Mg /ha). It is unknown
whether similar volumes are required for the positive response of the treecreeper in box-
ironbark forests. In the current study, individuals of A. flavipes were observed foraging on and
inside, sheltering in, and sunning on, logs and trees. Also for antechinus, hollows in trees
(including coppiced ones) provided communal nesting sites, while logs served as highways,
providing routes for movement.
Box-ironbark forests in this study are depleted of fallen timber (only 4 of 129 sites had
volumes ≥ 20 m3 /ha), and the range was narrower (0.3–33.7 m3 ha-1) than in river red gum
forests (5.6–212.3 m3 /ha). Only ChilternBI has no ongoing logging/timber removal. Pre-
European volumes of fallen timber in box-ironbark forests are unknown, but most likely were
much higher than the current volumes. This is because logs and large trees (which would
have contributed fallen timber) have been removed systematically from the forests for the last
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160 years. In the absence of old-growth box-ironbark remnants, the maximum volume of
fallen timber estimated for a site in this study (i.e., 33.7 m3 /ha in much changed RushworthBI
forest) may offer some guidance for pre-European volumes. Given repeated degradation of
box-ironbark forests, the volume of 33.7 m3 /ha is more likely to be an underestimate than an
overestimate of historic volumes. Laven and Mac Nally (1998) suggested that because of
infertility of Australian soils (Muir et al. 1995), pre-European fallen-timber volumes were
likely lower than the volume estimates in North America of 30–1421 m3 /ha and 46–132 m3
/ha for coniferous and deciduous forests, respectively (Harmon et al. 1986). In the current
guidelines for vegetation quality assessment of box-ironbark forests, 0.1 ha sites are assigned
the highest possible value for logs criterion if there are ≥ 10 m of logs (diameter ≥ 0.1 m) of
which ≥ 5 m are large logs (diameter ≥ 0.35 m) (Department of Sustainability and
Environment 2004). Only 10% of the 129 box-ironbark sites in our study fitted this criterion.
This benchmark is equivalent to the minimum fallen-timber volume of 5.2 m3 /ha, which is
6.4 and 12.8 times lower than the minimum amounts to which floodplainRRG A. flavipes and
C. picumnus respectively, responded positively (Mac Nally 2006; Mac Nally and Horrocks
2002; Mac Nally et al. 2002b). To achieve best outcomes for biodiversity and to reach a
compromise between faunal requirements and the massive amounts needed to replenish
fallen-timber, Mac Nally et al. (2001) recommended that heterogeneity in fallen-timber
volumes be considered in habitat restoration, that is, some areas are provided with very high
volumes of fallen timber. Our study supports these recommendations.
Evidence for flood-distance effects on capture rates of A. flavipes were less
pronounced than that reported by Lada et al. (2007a) and seemed to be due to the inclusion of
data for BarmahRRG. The reasons for the exceptional (negative rather than positive) response
to floods in BarmahRRG are currently unclear. If a similar response had been observed in
MillewaRRG (which lies across river from BarmahRRG), then we may have concluded that large
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controlled floods were less beneficial to antechinus than small, controlled floods. However,
responses of A. flavipes in MillewaRRG differed from BarmahRRG and were similar to those on
other floodplains, where abundances increased with proximity to floods. The numbers of
males and 2nd-year females increased with the proximity to flood locations, as did the
number of females and all individuals after BarmahRRG FloodDist variables were removed
from analyses. These increases in numbers were not due to philopatry. Through genetic
analyses Lada et al. (2007a) inferred that females were not absolutely philopatric, and that
some females in GunbowerRRG forest dispersed towards flooded areas. Males, the
predominant dispersing gender (Coates 1995; Marchesan and Carthew 2004), moved
throughout the whole forest. Emergence of macroinvertebrates on flooded sites following
water recession (Ballinger and Mac Nally 2005; Ballinger et al. 2005) may be beneficial to
the survival of the carnivorous A. flavipes (Lada et al. 2007b). Considering that the increased
abundance of beetles lasted for more than 2 years after the BarmahRRG flood (Ballinger et al.
2005), some antechinus females may have increased their chances of survival to the mating
season and past weaning by residing in areas that had been flooded the previous year.
Complete die-off of antechinus males after a mating season means that persistence of a
population depends on at least some females being able to wean male offspring each year
(and female offspring if all mothers perish). Therefore, the evidence for the positive effects of
larger fallen-timber volumes, number of large trees and proximity to floods on the abundance
of females are critical when conservation decisions are made.
Females were substantially more abundant in OvensRRG forest (natural flooding
regimes) than in BarmahRRG, MillewaRRG (large, controlled flooding) or GuttrumRRG (no flood
since 1996). This result does not necessarily indicate superiority of natural flooding regimes
over environmental flows because only 13 sites were sampled in OvensRRG forest, all near to
inundations, because the floodplain is relatively narrow. Opportunities to study responses to
17
natural flooding regimes are limited because most river red gum floodplains inhabited by A.
flavipes are along rivers with substantial regulation. Given this, we recommend that the Ovens
River remains unregulated in order to maintain the relatively high abundance of A. flavipes in
OvensRRG forest. A substantially higher abundance of females in Reedy LakeRRG forest than in
nearby RushworthBI forest suggested that the former was a better habitat than the latter, at
least over the 2 years sampled. This may be due to the combination of greater availability of
fallen timber, large, hollow-bearing trees and proximity to “inundated areas” in Reedy
LakeRRG forest. However, this forest is relatively small and, even though designated as a
wildlife reserve, is being degraded by illegal removal of trees and logs (H. Lada, pers. obs.).
We were unable to determine which factors make ChilternBI forest particularly suitable for A.
flavipes compared to WarbyBI and RushworthBI forests, both in animal abundances and
survival of females to a 2nd breeding season. Although not measured for each site, ChilternBI
harboured a huge abundance of golden orb-weaving spiders (Nephila species; H. Lada, pers.
obs.), which are possibly a food source for A. flavipes. A. agilis and A. swainsonii, which are
closely related to A. flavipes, mostly ate Araneae (spiders), Coleoptera and Hymenoptera
(ants), in a study at Mumbulla State Forest (Lunney et al. 2001). Future studies should include
assessment of prey availability and identification of dietary components of A. flavipes from
scats in each of the 3 box-ironbark forests.
We have shown the effects of local habitat factors on the abundances of A. flavipes in
river red gum and box-ironbark forests in the bioregions of Victorian Riverina, Murray Fans,
Inland Slopes and Goldfields in Victoria and Riverina in New South Wales. Despite being
much degraded, these forests are of great importance for conservation (Bennett et al. 1998;
Environment Conservation Council 1997). They support native fauna, and together with black
box (E. largiflorens) woodlands, roadside strips, linear riparian zones and some small isolated
patches are the only native vegetation left in the area, which now consists mostly of
18
production land-uses. Preserving, if not improving, the quality of remaining habitats will
likely benefit many native species, including A. flavipes. The shortages of hollow-bearing
large trees may be partially mitigated by, for example, installing nest boxes for wildlife
shelter in the short-term, and allowing medium-sized trees to grow large in the long-term.
Fallen-timber volumes should be restored in at least some parts of forests, and floodplains
need to be flooded more regularly in spring. It is possible that these three factors also play
important roles on animal abundances in floodplain ecosystems around the world and may
need to be considered together for restoration of habitats.
ACKNOWLEDGEMENTS
The work was partially supported by a grant from the Monash Research Fund: New
Research Areas scheme. Thanks to Anna Lada, Peter Lada and Quentin Lang for assistance
with fieldwork, to Jon Cuddy, Greg Horrocks and Keith Ward for information, to James
Thomson for discussions about data analyses and to two anonymous reviewers for comments
how to improve the manuscript. This work was carried out under Monash University
Biological Sciences Animal Ethics Committee permit BSCI/2003/02, Department of
Sustainability and Environment permit 10002325, Animal Care and Ethics Committee of the
Director-General of New South Wales (NSW) Agriculture Certificate of Approval, Animal
Research Authority issued by the Director-General of NSW Department of Primary
Industries, Forestry Commission of NSW permit XX23517 and NSW National Parks and
Wildlife Service research permit S10252. This is publication number 110 from the Australian
Centre for Biodiversity: Analysis, Policy and Management.
19
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Figure Legends
FIG. 1.—Location of study sites in river red gum forests (RRG) and box-ironbark forests (BI)
in southeastern Australia. R=river.
FIG. 2.—Fitted relationships between capture rates of yellow-footed antechinus (Antechinus
flavipes) A) females and fallen-timber volumes (vol), B) females and number of large trees
(Ltree), C) males and distances to 2003 floods (FloodDist), D) all individuals and fallen-
timber volumes, E) all individuals and number of large trees, and F) 2nd-year females and
distances to floods. Capture rate is the probability of success (catching a unique individual)
for a single trap at a given site in a given year. Plotted probabilities (capture rates) were
calculated from the posterior distributions of model parameters while holding all covariates,
other than the variable of interest, constant at their means (standardized value = 0). Values at
mean for 2004 were used for all plots. Solid lines show posterior probabilities (capture rates),
broken lines are upper and lower 95% credible intervals.
27
TABLE 1.—Habitat variables in three box-ironbark (BI) and seven river red gum (RRG) forests:
mean fallen-timber volumes (m3 ha-1), numbers of large trees, and distance (km) to flood in
2003 (FloodDist04) and in 2004 (FloodDist05). There were no floods in box-ironbark forests
(N/A).
0.25-ha Fallen-timber large trees
sites volume per 0.25-ha site FloodDist04 FloodDist05
Forest sampled Mean ± SD Mean ± SD Mean ± SD Mean ±SD
ChilternBI 62 4.6 ± 3.2 0.4 ± 0.6 NA NA
Warby RangeBI 27 6.7 ± 5.3 0.6 ± 0.6 NA NA
RushworthBI 40 9.0 ± 7.1 1.4 ± 1.5 NA NA
Reedy LakeRRG 23 24.4 ± 12.6 5.5 ± 2.7 0.8 ± 0.2 0.7 ± 0.2
OvensRRG 13 51.2 ± 20.0 3.6 ± 1.6 0.1 ± 0.1 0.0 ± 0.0
GunbowerRRG 102 59.2 ± 33.5 2.5 ± 2.1 2.1 ± 1.2 1.9 ± 1.3
BarmahRRG 29 68.6 ± 43.4 4.1 ± 3.0 0.9 ± 1.1 2.2 ± 2.5
KoondrookRRG 27 71.1 ± 33.9 2.4 ± 2.1 3.5 ± 0.2 3.3 ± 0.5
GuttrumRRG 32 75.1 ± 39.8 4.5 ± 3.4 14.3 ± 0.2 14.3 ± 0.2
MillewaRRG 30 88.4 ± 31.2 3.6 ± 2.1 0.1 ± 0.1 0.1 ± 0.1
28
TABLE 2.—Bayesian regression analyses of capture rates of the yellow-footed antechinus (Antechinus flavipes) with respect to fallen-timber
volume, number of large trees, and distance from flood locations at sampled sites in river red gum and box-ironbark forests in southeastern
Australia.
Capture ratea — fallen-timber volume Capture ratea — large/very large trees Capture ratea — distance to floods
Posterior Posterior Posterior
mean mean mean
probability probability probability
Direction of Bayesb Direction of Bayesb Direction of Bayesb
Coefficient for Mean ± SD of response response factor Mean ± SD of response response factor Mean ± SD of response response factor
Both sexes 0.31 ± 0.08 positive 1.000 Infinity 0.10 ± 0.06 positive 0.926 12.51 –0.03 ± 0.22 negative 0.567 1.31
Females 0.33 ± 0.10 positive 1.000 Infinity 0.21 ± 0.08 positive 0.994 166 0.08 ± 0.32 positive 0.567 1.31
2nd-yr females 0.26 ± 0.20 positive 0.913 10.5 0.20 ± 0.18 positive 0.860 6.14 –0.37 ± 0.21 negative 0.918 3.76
Males 0.24 ± 0.08 positive 0.997 332 0.01 ± 0.08 positive 0.556 1.25
Males in 2004 –0.19 ± 0.19 negative 0.831 4.92
Males in 2005 –0.02 ± 0.16 negative 0.559 1.27
Capture ratea — interaction between year and distance to flood
Males 0.17 ± 0.16 positive 0.854 5.85
a Data as natural log of odds b Bayes factors: > 10 indicates very high support for hypothesis; > 3 indicates support for hypothesis
29
TABLE 3.—Mean capture rates of the yellow-footed antechinus (Antechinus flavipes) in box-
ironbark (BI) and river red gum (RRG) forests in southeastern Australia for 2004 and 2005.
Pairwise comparisons of capture rates between forests are shown in lower part of table.
Both sexes Males Females Second-year Females
Forest Mean ±SD Mean ± SD Mean ± SD Mean ± SD
ChilternBI 0.085 ± 0.036 0.045 ± 0.026 0.048 ± 0.042 0.016 ± 0.049
WarbyBI 0.024 ± 0.011 0.012 ± 0.008 0.015 ± 0.014 0.001 ± 0.001
RushworthBI 0.025 ± 0.012 0.018 ± 0.011 0.007 ± 0.006 0.001 ± 0.003
Reedy LakeRRG 0.053 ± 0.012 0.030 ± 0.008 0.023 ± 0.008 0.003 ± 0.002
OvensRRG 0.033 ± 0.009 0.010 ± 0.003 0.025 ± 0.009 0.001 ± 0.001
GunbowerRRG 0.049 ± 0.006 0.028 ± 0.004 0.020 ± 0.003 0.002 ± 0.001
BarmahRRG 0.026 ± 0.007 0.016 ± 0.004 0.011 ± 0.004 0.001 ± 0.001
KoondrookRRG 0.035 ± 0.006 0.020 ± 0.004 0.015 ± 0.004 0.001 ± 0.001
GuttrumRRG 0.030 ± 0.015 0.023 ± 0.010 0.006 ± 0.005 0.001 ± 0.001
MillewaRRG 0.031 ± 0.007 0.019 ± 0.005 0.013 ± 0.004 0.001 ± 0.001
Comparison Probabilitya Probabilitya Probabilitya Probabilitya
ChilternBI, WarbyBI 1.000 C 1.000 C 1.000 C 0.999 C
ChilternBI, RushworthBI 1.000 C 1.000 C 1.00 0 C 0.999 C
WarbyBI, RushworthBI 0.585 0.909 Rus 0.058 0.731
ReedyRRG, RushworthBI 0.965 RL 0.895 RL 0.975 RL 0.914 RL
OvensRRG, WarbyBI 0.797 Ov 0.568 0.866 Ov 0.798 Ov
OvensRRG, BarmahRRG 0.770 Ov 0.869 B 0.974 Ov 0.548
OvensRRG, MillewaRRG 0.573 0.952 M 0.969 Ov 0.700
OvensRRG, GuttrumRRG 0.588 0.911 GT 0.963 Ov 0.745 Ov
KoondrookRRG, MillewaRRG 0.696 0.577 0.686 0.510
a Posterior probability of higher capture rate in: Chiltern (C), Ovens (Ov), Reedy Lake (RL), Rushworth (Rus),
Barmah (B), Millew (M) and Guttrum GT). Difference considered substantial if probability > 0.75 (Bayes factor
> 3).