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Landsc Ecol (2024) 39:138
https://doi.org/10.1007/s10980-024-01927-8
ORIGINAL PAPER
Fragments maintain similar herpetofauna andsmall
mammal richness anddiversity tocontinuous habitat,
butcommunity composition andtraits differ
DylanM.Westaway· ChrisJ.Jolly· DavidM.Watson· TimS.Jessop· DamianR.Michael·
GrantD.Linley· AnnaAristova· BenHolmes· JodiN.Price· EuanG.Ritchie· WilliamL.Geary·
AnneBuchan· EllaLoeffler· DaleG.Nimmo
Received: 27 February 2024 / Accepted: 18 June 2024 / Published online: 29 July 2024
© The Author(s) 2024
habitat breadth, and litter size in moderating species
responses to land modification.
Methods We established 100 sampling sites to sur-
vey herpetofauna and small mammals in 11 fragments
in an agricultural landscape compared to 11 eco-
logically equivalent ‘pseudo-fragments’ in a nearby
national park in south-eastern Australia. We selected
pairs of fragments and pseudo-fragments of the same
size and vegetation type, and used identical survey
methods to sample pairs simultaneously, thereby con-
trolling for numerous confounding factors, such as
differing vegetation type, weather, and survey effort.
Results Species richness and diversity were similar
between fragments and pseudo-fragments. Despite
this, we found community composition differed mark-
edly—driven by the varying responses of individual
species—indicating a shift in fauna communities
Abstract
Context Human disturbance has transformed eco-
systems globally, yet studies of the ecological impact
of landscape modification are often confounded. Non-
random patterns of land clearing cause differing veg-
etation types and soil productivity between fragments
in modified landscapes and reference areas—like
national parks—with which they are compared.
Objectives We sought to explore the influence of
land modification on herpetofauna and small mam-
mal communities using multiple biodiversity meas-
ures—species richness and diversity, individual spe-
cies abundance, and community composition. We
also aimed to investigate the role of traits such as diet,
Supplementary Information The online version
contains supplementary material available at https:// doi.
org/ 10. 1007/ s10980- 024- 01927-8.
D.M.Westaway(*)· D.M.Watson· D.R.Michael·
G.D.Linley· J.N.Price· D.G.Nimmo
School ofAgricultural, Environmental andVeterinary
Sciences, Gulbali Institute, Charles Sturt University,
Thurgoona, NSW2640, Australia
e-mail: dwestaway93@gmail.com
C.J.Jolly
School ofNatural Sciences, Macquarie University,
MacquariePark, NSW2109, Australia
T.S.Jessop
Science, Economics andInsights Division, Department
ofPlanning andEnvironment, Conservation
andRestoration Science, Parramatta, NSW2150, Australia
A.Aristova
School ofExercise andNutrition Sciences, Deakin
University, Geelong, VIC3220, Australia
B.Holmes
Wimmera Catchment Management Authority, Horsham,
VIC3400, Australia
E.G.Ritchie· W.L.Geary
School ofLife andEnvironmental Sciences, Deakin
University, Burwood, VIC3125, Australia
W.L.Geary· A.Buchan· E.Loeffler
Biodiversity Strategy & Planning, Biodiversity Division,
Department ofEnvironment, Energy & Climate Action,
EastMelbourne, VIC3002, Australia
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associated with land modification. Fossorial habit,
omnivorous diet, and broad habitat requirements led
to higher abundance in fragments whilst arboreality,
carnivorous diet, and narrow habitat requirements led
to higher abundance in pseudo-fragments.
Conclusions Although fragments hold similar num-
bers of species to continuous areas, they contain dis-
tinct and novel communities, and sustain high abun-
dances of some species. These diverse communities
are dominated by native species, including threatened
species, and their distinctive composition is shaped
by traits conducive to persistence amidst land modi-
fication. These novel communities may provide a
reservoir of resilience in the face of environmental
change and should be viewed as complementary to
conservation areas.
Keywords Community composition· Habitat
fragmentation· Habitat loss· Patch dynamics·
Species assemblages· Traits
Introduction
Habitat loss is the most pervasive threat to global
biodiversity, driven primarily by the conversion of
natural landscapes for agriculture and urbanisation
(Powers and Jetz 2019). With over half of all ice-
free land on Earth converted for agriculture (Hooke
etal. 2013), conservation must occur within modified
landscapes if we are to address the present ‘extinction
crisis’ (Dirzo etal. 2022). Critical to informing con-
servation actions in these landscapes is the identifica-
tion and quantification of the impacts of land modi-
fication. Overwhelmingly, native species richness is
the response metric through which the effect of land
modification on fauna is measured, with a common
pattern of reduced richness in modified landscapes
(Newbold etal. 2015; Thompson etal. 2016; Cordier
etal. 2021). However, species richness is not always a
reliable indicator of biodiversity (Fischer and Linden-
mayer 2007). For example, richness might remain the
same after land modification due to the immigration
of overabundant generalist species, masking the loss
of rare, endemic species (Matthews etal. 2014).
The ‘habitat amount hypothesis’ contends that spe-
cies richness in fragments is driven by the ‘sample
area effect’, where richness is primarily determined
by the area of habitat in the local landscape (i.e., the
sample area represented by the total habitat surround-
ing a sample site; Fahrig 2013). Fahrig (2013) advo-
cates for the comparison of fragments with equal-
sized areas but within a region of continuous habitat
(hereon referred to as ‘pseudo-fragments’; sensu Mac-
Nally and Bennett 1997). Though it has since been
conceded that such comparisons do not directly test
the habitat amount hypothesis (Fahrig 2021), these
comparisons are nevertheless valuable in exploring
the biodiversity value of fragments. Due to the sam-
ple area effect, species richness is expected to decline
proportionally to reduction in fragment size purely as
a function of habitat loss, rather than fragmentation.
In contrast, the ‘island biogeography theory’ contends
that individual fragment size and isolation determine
species richness through demographic effects such as
reduced immigration, increased inbreeding depres-
sion and elevated extinction in small, isolated frag-
ments (Macarthur and Wilson 1967). This theory pre-
dicts a disproportionate reduction in species richness
as fragment size decreases. Therefore, the mechanism
driving richness patterns can be tested by comparing
the slopes of the species-area curve between frag-
ments and pseudo-fragments. “The sample area effect
alone predicts that the species–area relationship for
habitat patches should be lower, but have the same
slope, as the relationship for sample areas within con-
tinuous habitat” (Fahrig 2013). Whereas, under island
biogeography theory “the species–area relationship
for habitat patches should be steeper than for sample
areas within continuous habitat” (Fahrig 2013).
Community composition, which incorporates the
relative abundances of all species detected at a site,
provides another lens through which the effect of
landscape modification can be viewed. Composi-
tional differences can occur despite similar richness,
providing insight into subtle changes in the structure
of a community (Kay etal. 2018). Community com-
position is driven by individual species responses to
modification which are, at least partly, mediated by
ecological and life history traits (Henle etal. 2004;
Keinath etal. 2017). Under the ‘landscape-moderated
functional trait selection hypothesis’ (Tscharntke
etal. 2012), species trait selection shapes the trajec-
tory of community assembly. Traits such as general-
ist dietary and habitat requirements, high dispersal
ability, and high fecundity are thought to be advan-
tageous whilst large body size, specialist dietary and
habitat requirements, and complex social structure are
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disadvantageous in fragments (Henle etal. 2004; Car-
dillo etal. 2005; Michael etal. 2015; Keinath etal.
2017).
While the management emphasis in modified land-
scapes typically prioritises protecting large sections
of remnant vegetation, growing evidence demon-
strates the value of small fragments for wildlife con-
servation (Tulloch etal. 2016; Riva and Fahrig 2022).
Indeed, a global meta-analysis revealed that small,
isolated fragments tended to have higher conservation
value than similarly sized areas in continuous tracts
of vegetation (Wintle etal. 2019). Similarly, an analy-
sis of 32 datasets comparing species richness across
small and large fragments found small outperformed
large in 25 of 32 instances, and no instance of large
fragments outperforming small (Riva and Fahrig
2022).
The disproportionate importance of small frag-
ments is likely due to several factors. In agricultural
landscapes, remnant fragments often occur in flat, fer-
tile landscapes that have been selectively cleared due
to their high productivity (Watson 2011; Maron etal.
2012; Simmonds etal. 2017). Consequently, their host
biota are quite distinct from sites with steep terrain or
poor soils, where larger areas set aside for conserva-
tion (e.g., conservation reserves) tend to exist, due
to their low value to agriculture (Watson etal. 2014;
Venter et al. 2018; Engert et al. 2023). Thus, small
fragments may be all that remains of heavily cleared,
but highly productive, ecosystem types. This creates
problems when comparing ecological communities
between fragments and nearby ‘reference areas’ set
aside for conservation, as such comparisons are often
confounded by factors, such as vegetation type, that
differ between fragments and reference areas because
of non-random land clearing (Maron etal. 2012; Sim-
monds et al. 2017). Furthermore, land modification
alters ecological processes in remnant fragments. For
example, fire is typically excluded from fragments
and many fragments are exposed to livestock grazing,
both of which alter fragment vegetation. Additionally,
species detectability can vary according to circadian
rhythms, seasonality, weather conditions, and survey
method, potentially further confounding compari-
sons (Boulinier etal. 1998). Therefore, to make fair
comparison between fragmented and non-fragmented
communities requires standardized survey design,
methods and sampling effort to limit temporal and
spatial confounds from influencing inference.
We investigated the occurrence of herpetofauna
and small mammals, as well as the activity of intro-
duced predators, in woodland fragments within an
agricultural matrix compared to ecologically equiva-
lent pseudo-fragments in a nearby national park in
south-eastern Australia. We endeavoured to con-
trol for external factors that typically vary in frag-
mentation studies (e.g., vegetation type), to capture
the effect of land modification alone. We sought to
answer the overarching question: do fauna communi-
ties differ between isolated fragments and continuous
pseudo-fragments of habitat? Our approach consid-
ered multiple biodiversity measures—species rich-
ness and diversity, community composition and indi-
vidual species abundance—along with trait data to
explore the effect of land modification. In accordance
with both the habitat amount hypothesis and island
biogeography theory, we expected lower species rich-
ness and diversity in fragments compared to pseudo-
fragments. Consistent with the ‘landscape-moderated
functional trait selection hypothesis’, we predicted
communities in fragments and pseudo-fragments to
differ in composition owing to the varying response
of individual species, mediated by traits. We predict
generalist species to show increased abundance in
response to modification whilst specialist species will
show decreased abundance.
Materials andmethods
Study area
The study was undertaken within the Little Desert
National Park and surrounding agricultural land
in western Victoria, Australia (Fig. 1A). The area
receives an average of 449mm annual rainfall with
mean maximum temperature of 31.3 °C in January,
14.0 °C in July and mean minimum temperature of
13.9 °C and 4.5 °C, respectively (Bureau of Mete-
orology, http:// www. bom. gov. au/ clima te/ data/). The
landscape is characterised by sandy soils and contains
a series of undulating dunes and swales, and expan-
sive plains. Three vegetation communities dominate
the landscape—Lowan Sands Mallee, occurring on
light sandy soil, dominated by desert stringybark
(Eucalyptus arenacea), reaching 5–10 m, with a
dense heathy understory usually containing grass
trees (Xanthorrhoea australis). Sandstone Ridge
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Shrubland, occurring on sandy sandstone outcrops,
contain sparse multi-stemmed eucalypts (predomi-
nantly ridge-fruited mallee, E. costata, and slender-
leaf mallee, E. leptophylla) reaching < 5m high, and
abundant mid-storey shrubs (broom honey-myrtle,
Melaleuca uncinata, violet honey-myrtle, M. wilsonii,
and broom baeckea, Hysterobaeckea behrii). Yellow
Gum Woodland exists over clay soils, with yellow
gum (E. leucoxylon) the main tree species reach-
ing > 10m, and a variety of shrubs and grasses creat-
ing a relatively open understory.
Outside the national park, agriculture (predomi-
nantly sheep grazing and cropping) is widespread
in the region. Early clearing by European colonists
began in the late 1800s removing much of the native
vegetation, particularly on the more productive ‘Wim-
mera black soils’ (Landt 1961). As has happened
across the world (Watson etal. 2014; Simmonds etal.
2017; Venter et al. 2018), vegetation communities
on fertile soils were selectively cleared, leaving the
majority of native vegetation remaining on less fer-
tile, sandy soils. From the 1960s onwards, agriculture
expanded into less fertile, sandy soils abutting the
Little Desert National Park (Landt 1961). Small frag-
ments of vegetation were left uncleared to provide
shelter for livestock, so that farms comprise a mosaic
of patches of remnant vegetation of differing shape
and size, surrounded by pasture or cropland. These
Nhill
Little Desert
National Park
Kaniva
C
A
B
Grazed
pasture
Fragment
Pseudo-fragment
Little Desert
National Park
Fig. 1 A National scale: study area location within Australia,
B regional scale: study fragments (solid triangles) and pseudo-
fragments (hollow triangles) across the Little Desert National
Park and surrounds, and Clandscape scale: study fragments in
the agricultural landscape and paired pseudo-fragments (con-
nected with arrows) in the adjacent national park showing pro-
portional sampling. Continuous vegetation of the national park
is shaded grey, whilst fragments of remnant native vegetation
in the agricultural landscape are hashed grey
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fragments support the same soils and vegetation types
to the adjacent national park, providing an opportu-
nity to test for the effect of land modification without
the confounding effects of vegetation type and varia-
tion in resource availability and productivity. Increas-
ingly, intensification of agricultural practices in the
region has diminished remnant vegetation in farming
landscapes (Maron and Fitzsimons 2007).
Experimental design
We sampled 11 matching pairs of fragments (n = 11)
and pseudo-fragments (n = 11), 1–10ha in size. Each
fragment is a patch of remnant vegetation (isolated
11–60years ago) surrounded by cleared grazing land.
Using geographic information systems and ground-
truthing, each fragment was paired with a pseudo-
fragment—an area of the same size as the fragment,
comprised of the same vegetation type, but embed-
ded within the continuous habitat of the national park
(MacNally and Bennett 1997; Deacon and Mac Nally
1998; Johnstone etal. 2010, 2012, 2014).
Each paired fragment and pseudo-fragment were
selected to be as similar as possible, differing only in
landscape context (i.e., isolated fragment vs. continu-
ous pseudo-fragment) and land-use (Fig. 1C). Fire
history was considered in pair selection to account for
the effect of post-fire succession on biotic communi-
ties (Nimmo etal. 2013; Haslem etal. 2011). No fire
had occurred in any of the fragments since the time
of clearing according to the landholders. For pseudo-
fragments, we used the “Fire History Records of Fires
across Victoria” dataset (DEECA 2023). The region
has experienced numerous large wildfires and fre-
quent planned burns in recent years. Therefore, we
focussed on the longest unburnt areas available to
locate pseudo-fragments (9/11 last burnt > 40 years
ago, the remaining two burnt 25 and 28 years ago
respectively), so that fire history of pseudo-fragments
matched fragments (all last burnt > 40 years ago) as
closely as possible. Fragments were periodically
exposed to sheep grazing, although two of the 11
fragments were fenced off excluding sheep (but sub-
ject to historic grazing) but not impeding the move-
ment of the herpetofauna and small mammals studied.
The relatively small size of the fragments and
pseudo-fragments (< 10 ha) allowed us to sur-
vey them intensively (each surveyed ~ 30 times),
reducing the likelihood of false negatives. An
area-proportionate sampling approach was under-
taken in which the survey effort (the number of trap
lines) was dependent on fragment size. Specifically,
for every hectare, each fragment contained one pit-
fall line, a 30-m-long aluminium flywire drift fence
running through three 20-L buckets and two double-
ended funnel traps. In addition, two artificial refuge
stations were established adjacent to each trap line,
each composed of a double-stack of 1 m2 sheets of
corrugated tin, and two terracotta roof tiles placed on
the ground. This multi-method capture design was
used to reduce method-related capture bias for differ-
ent species, maximizing the detection of target spe-
cies. Trap lines were separated by at least 50m, mak-
ing it unlikely for most target species to visit multiple
trap lines (Pulsford etal. 2018).
Our paired design allowed sampling in fragments
and pseudo-fragments to be almost identical, thereby
controlling for sampling bias and detectability.
Between November 2021 and January 2022, all traps
were open for three blocks (one per month) of five
consecutive days and nights except when temperature
exceeded 35°C or predicted daily rainfall exceeded
5mm. Trap nights (calculated as the total number of
24-h periods each pitfall and funnel trap was open
for plus the number of times artificial refuges were
checked) ranged from 101 in the smallest fragments
to 960 in the largest. Traps were checked twice a day,
at dawn and dusk, and refuge stations checked twice
each trapping block. Paired fragments were always
trapped on the same days at approximately the same
time by two separate teams.
Vegetation surveys
To assess habitat structure, vegetation surveys were
conducted at each of the 100 trap lines. Habitat struc-
ture was measured using vertical structure poles at
1-m intervals along a 30-m transect run parallel to the
drift fence, 5m away. At each metre along the tran-
sect, leaf litter depth was given a rating between 0
(bare ground) and 4 (5 cm +), and the incidence of
vegetation touching the structure pole was recorded
for low (0–0.5m), mid (0.5–1.0m), high (1–2m) and
canopy (2m +) strata. Coarse woody debris volume
was recorded by measuring length and diameter of
logs that fell within 5m either side of the transect.
The closest six trees of the dominant species in the
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area were measured for diameter at breast height
(Fig.2).
Camera trapping
Camera traps were deployed at each fragment and
pseudo-fragment to provide an index of activity for
two introduced predators prominent in the region:
the red fox (Vulpes vulpes) and feral cat (Felis
catus). Small fragments (0–3 ha) contained one
camera, medium fragments (4–6 ha) two cameras
and large fragments (7–10ha) three cameras which
collected images semi-continuously throughout the
duration of the study. Cameras used were all of the
same model (Swift Enduro), were set to medium
sensitivity, and to capture five images after each
trigger with no delay. Cameras were placed at
waist height, facing downwards to a focus point on
the ground 1.5–2 m from the tree the camera was
placed on. Cameras were initially baited (with a
punctured tin of sardines) whilst traps were inac-
tive and unbaited during trapping to avoid attracting
predators to vulnerable animals in traps.
Fig. 2 Vegetation
similarity between paired
fragments and pseudo-
fragments: ALowan Sands
Mallee fragment, B Lowan
Sands Mallee pseudo-frag-
ment, C Sandstone Ridge
Shrubland fragment, and D
Sandstone Ridge Shrubland
pseudo-fragment
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Statistical analyses
All analyses were performed in R (R Core Team
2023).
Does vegetation structure differ betweenfragments
andpseudo‑fragments?
We used generalised linear mixed effect models
(GLMMs) using the “lme4” package (Bates etal.
2015) to compare vegetation structure between frag-
ments and pseudo-fragments. The data was divided
into vegetation types to enable a comparison
between the attributes of vegetation in fragments
and those in pseudo-fragments, controlling for veg-
etation type. Structural complexity at low, mid, high
and canopy strata were modelled as the proportion
of times along the transect that vegetation touched
the vertical structure pole for each stratum, assum-
ing a binomial error distribution. Leaf litter depth,
coarse woody debris volume, largest tree (diameter
at breast height) and mean tree size (diameter at
breast height) were modelled assuming a Gaussian
distribution. Each of these vegetation metrics men-
tioned above were modelled in turn as the response
variable, whilst fragment type was specified as a
categorical fixed effect with two levels (fragment,
pseudo-fragment) and fragment ID specified as a
random effect to account for non-independence of
sites (transects) within fragments.
Does species richness anddiversity differ
betweenfragments andpseudo‑fragments?
Species richness (total number of species) and Shan-
non’s diversity index (a measure of diversity incorpo-
rating species richness and evenness) were calculated
for each fragment and pseudo-fragment. We used raw
rather than standardised values because: (1) our study
design ensured almost identical survey effort across
paired fragments and pseudo-fragments, (2) low sam-
ple sizes resulting from lower survey effort at smaller
fragments and pseudo-fragments resulted in standard-
ised estimates with high levels of uncertainty. Cross-
sample singletons and doubletons (i.e., species that
were recorded only once or twice across all sampling)
were excluded from all analyses as their removal has
shown to decrease error rate and improve accuracy of
diversity metrics (Allen etal. 2016).
Species richness and diversity values were mod-
elled against the predictor variables fragment type
(fragment vs. pseudo-fragment), fragment size
(1–10 ha), and their interaction term, using gener-
alised linear models (GLMs) assuming a Gaussian
error distribution. Here, we define ‘fragment size’
as the area of the fragment and the equivalent area
sampled for their paired pseudo-fragments. Models
were ranked according to Akaike’s Information Cri-
terion adjusted for small sample sizes (AICc) and
coefficients (and 85% CIs; Arnold 2010) reported for
all supported models (delta AICc < 2; Burnham and
Anderson 2004).
Does community composition differ
betweenfragments andpseudo‑fragments?
To examine how land modification affects community
composition, we used Permutation Multivariate Anal-
ysis of Variance (PERMANOVA) from the “vegan”
package (Dixon 2003). Species abundances were
used to calculate Bray–Curtis dissimilarity measures
for each of the fragments and pseudo-fragments. Sig-
nificance values were calculated based on 999 unre-
stricted permutations of the raw data. Differences in
community structure between fragment types were
visualised through non-metric multi-dimensional
scaling (nMDS). Indicator species analysis was con-
ducted using the “indicspecies” package (Cáceres and
Legendre 2009) to identify species characteristic of
fragments and pseudo-fragments respectively.
To explore herpetofauna and small mammal com-
munity compositional differences further, we mod-
elled species abundance (total number of individuals
of each species captured in each fragment/pseudo-
fragment) and incidence (proportion of trap lines
occupied per fragment/pseudo-fragment) in relation
to fragment type and fragment size. Generalised lin-
ear models were performed for species which were
captured 11 or more times (equal to half the total
number of fragments/pseudo-fragments; Williams
etal. 2012). Abundances were modelled assuming a
Poisson error distribution and with a log link func-
tion. Species’ incidence was modelled as the num-
ber of success (trap lines occupied per fragment) and
failures (trap lines unoccupied per fragment) within a
fixed number of Bernoulli trials (total number of trap
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lines per fragment), assuming a binomial error dis-
tribution and with a logit link function. Four models
including the variables fragment type, fragment size,
and the interaction term were fit. Due to evidence of
overdispersion in global models for some species,
model selection was performed according to QAICc,
thereby accounting for potential overdispersion. Sup-
ported models (delta QAICc < 2) were fit specifying
a quasipoisson or quasibinomial error distribution
(Burnham and Anderson 2004).
Do traits mediate species abundance
betweenfragments andpseudo‑fragments?
Traits were considered for only our most abundant
class—reptiles—as we recorded too few amphibian
and mammal species (2 and 5 species respectively)
to warrant their inclusion. Trait data (TableS7) was
collated from a global trait database (Meiri 2018),
complemented by a comprehensive field guide to the
region (Robertson and Coventry 2014), and included
litter size, mass, snout-vent length, taxonomic fam-
ily, diet, habit, activity period, leg development, and
temperature regulation. Additionally, habitat breadth
was calculated as a measure of habitat specialisation
following established methods (Ducatez etal. 2014;
Lettoof etal. 2023) using the IUCN Red List database
(IUCN 2023).
Cohen’s d effect sizes were calculated for each spe-
cies, with 95% confidence intervals from 1000 boot-
strap samples, to estimate the magnitude of difference
in abundance between fragments and pseudo-frag-
ments. A multiple regression analysis was then per-
formed to investigate the relationship between spe-
cies traits and calculated effect sizes. We fit models
including all combinations (without interactions) of
the traits previously listed. The confidence intervals
of effect sizes were included in the model via inverse
variance weighting using the “weights” argument.
Models were ranked according to AICc and coeffi-
cients (and 85% CIs) reported for supported models
(delta AICc < 2).
Does introduced predator activity differ
betweenfragments andpseudo‑fragments?
Site-specific relative abundance indices were calcu-
lated for the introduced predators, red fox and feral
cat. We considered detections > 30min apart to be a
separate event to account for the same animal being
detected multiple times in the same visit (Cunning-
ham etal. 2018). We used generalised linear models
(GLMs) using the “lme4” package (Bates etal. 2015)
with relative abundance indices for each fragment/
pseudo-fragment as the response variable and frag-
ment type (fragment vs. pseudo-fragment) as the pre-
dictor variable to determine the influence of fragment
type on predator activity.
Results
Does vegetation structure differ between fragments
and pseudo-fragments?
Vegetation structure was similar between paired
fragments and pseudo-fragments with 10 out of 14
metrics measured showing no significant difference
between fragment types. Structural complexity at low
(< 0.5 m) and medium (0.5–1 m) strata were simi-
lar across fragment types (TableS1, Fig.3C and D).
However, despite selecting pseudo-fragments to be
as similar as possible to fragments, the latter showed
higher structural complexity within the high (1–2m)
and canopy (> 2m) strata (TableS1, Fig.3E and F),
and deeper leaf litter (TableS1, Fig. 3B). The vol-
ume of coarse woody debris (TableS1, Fig.3A) and
tree size (TableS1) were similar between treatments,
except for one species of tree, E. leptophylla, which
were larger in fragments.
Does species richness and diversity differ between
fragments and pseudo-fragments?
Across 9,618 trap nights, a total of 1,736 individu-
als from 19 reptile species, five mammal species, and
two amphibian species (there were likely three but
due to the difficulty of distinguishing between Neo‑
batrachus pictus and N. sudellae, these two species
were combined) were recorded. In total, 867 indi-
viduals were sampled from 25 species in fragments
and 869 individuals from 23 species in pseudo-frag-
ments (Table 1). Three species were found exclu-
sively in fragments (Echiopsis curta, Notechis scuta‑
tus, Sminthopsis crassicaudata) whilst one species
was found exclusively in pseudo-fragments (Varanus
rosenbergi). The most abundant species were More‑
thia obscura (383 captures, 22.06% of total captures),
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Ctenotus robustus (197, 11.35%), Ctenotus orientalis
(193, 11.12%), and Pseudomys apodemoides (175,
10.08%). Pitfall traps were the most successful survey
method recording 1,191 animals (0.33 animals/trap
night). Funnel traps captured 501 animals (0.21 ani-
mals/trap night), whereas tin stacks (39 captures, 0.03
animals/trap night) and roof tiles (5 captures, 0.002
animals/trap night) accounted for far fewer animals.
Species richness ranged from four to 20 species
per fragment/pseudo-fragment. The most parsimoni-
ous model included only fragment size (TableS2),
while the null model was also supported. Parameter
estimates showed that species richness increased with
fragment size (TableS3). We observed no evidence
of an ‘island effect’ on species richness where the
species-area curve for fragments would be steeper
compared to pseudo-fragments (Fig.4).
Shannon’s diversity estimates in fragments and
pseudo-fragments ranged from 0.75 to 2.39. Two
models received substantial support: the null model,
and the model including fragment size (Table S2).
Parameter estimates suggest there was a small posi-
tive effect of fragment size on diversity (TableS3).
Does community composition differ between
fragments and pseudo-fragments?
Community composition differed significantly across
fragment types (PERMANOVA: R2 = 0.217, d.f. = 1,
p < 0.001). The ordination showed a clear separation
Fig. 3 Vegetation metrics across fragment type and Ecological
Vegetation Class (EVC) categories: A volume of coarse woody
debris (log(cm3)), B leaf litter depth rating, and structural com-
plexity of low (0–0.5m; C), mid (0.5–1.0m; D), high (1–2m;
E) and canopy (> 2m; F) strata. Black dots represent data val-
ues from each transect
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between communities in fragments compared to
pseudo-fragments (Fig. 5). Indicator species analy-
sis found three lizard species (C. robustus, Tiliqua
rugosa, Lerista bougainvilli), one frog species (Lim‑
nodynastes dumerilii) and one rodent species (Mus
musculus) to be strongly associated with fragments.
Conversely, one species of lizard (Amphibolurus nor‑
risi), and one marsupial species (Cercartetus lepi‑
dus) were strongly associated with pseudo-fragments
(Table 2). Abundance showed a significant associa-
tion (85% CIs did not overlap zero) with fragment
type for nine of the 18 species for which modelling
Table 1 Total abundance (number of fragments/pseudo-fragments detected at) for each species recorded in the study
Common name Scientific name Code Pseudo-fragment Fragment Total
Agamidae
Mallee Tree Dragon Amphibolurus norrisi AmpNor 23 (9) 2 (2) 25 (11)
Painted Dragon Ctenophorus pictus CtePic 35 (7) 22 (4) 57 (11)
Eastern Bearded Dragon Pogona barbata PogBar 4 (3) 1 (1) 5 (4)
Diplodactylidae
Eastern Stone Gecko Diplodactylus vitattus DipVit 4 (2) 5 (1) 9 (3)
Elapidae
Bardick Echiopsis curta EchCur 0 (0) 1 (1) 1 (1)
Tiger Snake Notechis scutatus NotScu 0 (0) 1 (1) 1 (1)
Eastern Brown Snake Pseudonaja textilis PseTex 1 (1) 4 (4) 5 (5)
Mitchell’s Short-tailed Snake Suta nigriceps SutNig 5 (5) 3 (3) 8 (8)
Gekkonidae
Marbled Gecko Christinus marmoratus ChrMar 83 (10) 45 (7) 128 (17)
Pygopodidae
Lined Worm-lizard Aprasia striolata AprStr 3 (3) 9 (5) 12 (8)
Common Scaly-foot Pygopus lepidopodus PygLep 9 (4) 2 (2) 11 (6)
Scincidae
Spotted Ctenotus Ctenotus orientalis CteOri 90 (11) 103 (11) 193 (22)
Robust Ctenotus Ctenotus robustus CteRob 38 (2) 159 (10) 197 (12)
Delicate Skink Lampropholis delicata LamDel 71 (9) 68 (8) 139 (17)
South-eastern Slider Lerista bougainvilli LerBou 9 (5) 38 (10) 47 (15)
Common Dwarf Skink Menetia greyii MenGre 17 (6) 21 (6) 38 (12)
Shrubland Morethia Morethia obscura MorObs 210 (11) 173 (11) 383 (22)
Shingleback Lizard Tiliqua rugosa TilRug 1 (1) 11 (7) 12 (8)
Varanidae
Heath Goanna Varanus rosenbergi VarRos 5 (3) 0 (0) 5 (3)
Burramyidae
Western Pygmy-possum Cercartetus concinnus CerCon 19 (6) 28 (8) 47 (14)
Little Pygmy-possum Cercartetus lepidus CerLep 62 (10) 15 (5) 77 (15)
Dasyuridae
Fat-tailed Dunnart Sminthopsis crassicaudata SmiCra 0 (0) 2 (1) 2 (1)
Muridae
House Mouse Mus musculus MusMus 2 (2) 24 (7) 26 (9)
Silky Mouse Pseudomys apodemoides PseApo 134 (7) 41 (1) 175 (8)
Limnodynastidae
Eastern Banjo Frog Limnodynastes dumerilii LimDum 21 (4) 77 (11) 98 (15)
Neobatrachus sp. Neobatrachus sp. NeoSp 23 (5) 12 (5) 35 (10)
Total 869 (11) 867 (11) 1736 (22)
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was performed. Eleven of 18 species showed an asso-
ciation with fragment size whilst the interaction term
between fragment type and fragment size influenced
abundance for three of 18 species (Table3).
For individual species abundances, model param-
eters identified the same five species as in indica-
tor species analysis, and an additional legless lizard
species (Aprasia striolata) to be positively associ-
ated with fragments (Table4; Fig.6A–C). The same
two species identified by indicator species analysis
as well as one legless lizard species (Pygopus lepi‑
dopodus) showed a significant negative associa-
tion with fragments and, thus, a positive association
with pseudo-fragments (Table4; Fig.6D, E). All 11
associations with fragment size were positive (abun-
dance increased with fragment size). Findings were
similar when using the proportion of survey lines
(sites) occupied per fragment/pseudo-fragment as the
response variable (TablesS4 and S5, Fig S1).
Do traits mediate species abundance in fragments and
pseudo-fragments?
The only supported model explained the data well
(R2 = 0.799) and included three traits as predictor
variables: diet, habit and habitat breadth (Table 5).
Species with a carnivorous diet or semi-arboreal habit
were more abundant in pseudo-fragments, whereas
those with an omnivorous diet or fossorial habit were
more abundant in fragments (Fig.7; Table6). Habitat
specialists were more abundant in pseudo-fragments
compared to habitat generalists which were more
abundant in fragments.
Does introduced predator activity differ between
fragments and pseudo-fragments?
Over 8,994 trap days, 310 fox detection events (271
in fragments and 39 in pseudo-fragments) and four
cat detection events (one in a fragment and three in
pseudo-fragments) occurred. Modelling was only per-
formed for foxes due to low overall detection of cats.
Fox activity was significantly higher in fragments
Fig. 4 The relationship between species richness and fragment
size for fragments (blue) and pseudo-fragments (red). Dashed
lines represent regression lines for fragments and pseudo-frag-
ments individually, whilst the solid black line shows the overall
regression line
Fig. 5 The nMDS ordination showing: A the separation of
community composition between fragments (blue) and pseudo-
fragments (red). Each point represents a fragment/pseudo-frag-
ment plotted on unobserved variables (NMDS1 and NMDS2)
used to visualise dissimilarity between points. Ellipses show
95% confidence intervals. B Individual species’ position
according to the fragments/pseudo-fragments they occurred
in (first 3 letters of genus and species; see Table1 for species
list). ‘Indicator species’ are shown in bold
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compared to pseudo-fragments (Coefficient ± 85%
CI = 1.16 [0.45–1.87], R2 = 0.23; TableS6).
Discussion
Land clearing has transformed ecological communi-
ties worldwide, yet studies of the impact of landscape
modification are often confounded by non-random
patterns of land clearing. We compared communities
of herpetofauna and small mammals of remnant frag-
ments in modified landscapes to similar pseudo-frag-
ments in continuous habitat. Total number of animals,
species richness, and species diversity were similar
between fragments and pseudo-fragments. Despite
this, community composition differed between frag-
ment types indicating a shift in fauna communities
associated with land modification. Relative abun-
dances of individual species show there are ‘winners
and losers’ in modified landscapes as some species
proliferate in fragments whilst others decline. We
explore the influence of traits in determining a spe-
cies’ response to land modification.
Does vegetation structure differ between fragments
and pseudo-fragments?
Despite intentionally matching similar habitat across
fragments and pseudo-fragments, vegetation surveys
showed some significant differences between frag-
ment types, including deeper leaf litter and more
complex vegetation structure at higher strata for frag-
ments. Abiotic factors, such as soil quality, typically
differ between fragmented habitat and continuous
habitat due to non-random land clearing (Simmonds
et al. 2017; Maron et al. 2012), likely contributing
to differing vegetation structure. Additionally, land
clearing alters ecological processes by increasing
edge effects, promoting weed invasion, encouraging
grazing by domestic and native herbivores, and alter-
ing fire regimes. These effects combined mean that
fragmented and continuous habitat are unlikely to be
truly equivalent, despite their regular comparison in
ecological research.
One possible explanation for the differences
observed in our study, is that the absence of fire in
fragments allowed leaf litter to accumulate and taller
growth of large shrubs and trees. Fire, both planned
burns and wildfire, is a widespread and common
occurrence in the Little Desert National Park result-
ing in very few remaining tracts of long-unburnt
vegetation there. Previous work in similar habi-
tat has shown leaf litter and canopy cover may take
20–40years to return to pre-fire levels (Haslem etal.
2011). Nevertheless, overall vegetation structure was
similar between fragment types (10 of 14 metrics
were similar), vegetation type the same and time-
since-fire matched as close as possible given the high
frequency of fire in the region.
Does species richness and diversity differ between
fragments and pseudo-fragments?
Species richness and diversity estimates were simi-
lar between paired fragments and pseudo-fragments.
Thus, our results do not support the trend of reduced
Table 2 Results of indicator analysis showing species associ-
ated with fragments and pseudo-fragments. Significant (95%)
associations are shown in bold
IndVal p
Fragment-associated species
Limnodynastes dumerilii 0.886 0.009
Lerista bougainvilli 0.857 0.014
Ctenotus robustus 0.857 0.001
Mus musculus 0.766 0.048
Tiliqua rugosa 0.764 0.01
Ctenotus orientalis 0.731 0.802
Cercartetus concinnus 0.658 0.404
Aprasia striolata 0.584 0.26
Menetia greyii 0.549 0.855
Pseudonaja textilis 0.539 0.324
Pseudo-fragment-associated species
Amphibolurus norrisi 0.868 0.002
Cercartetus lepidus 0.856 0.003
Christinus marmoratus 0.768 0.128
Morethia obscura 0.74 0.651
Pseudomys apodemoides 0.698 0.08
Lampropholis delicata 0.646 0.812
Ctenophorus pictus 0.625 0.35
Neobatrachus sp. 0.547 0.622
Pygopus lepidopodus 0.545 0.218
Suta nigriceps 0.533 0.648
Varanus rosenbergi 0.522 0.219
Pogona barbata 0.467 0.469
Diplodactylus vitattus 0.284 1.000
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species richness in modified landscapes predicted by
both the habitat amount hypothesis and island bioge-
ography theory, and supported by several comprehen-
sive meta-analyses (Newbold etal. 2015; Thompson
etal. 2016; Cordier etal. 2021).
Declines in species richness after land modification
are primarily driven by two processes. First, species
are lost as habitat area decreases via the sample area
effect (Fahrig 2013). Second, ecosystem decay alters
the demography of remaining species in fragmented
habitats over time, leading to increased extinction
risk (Chase etal. 2020). Despite the negative effect of
these processes, similar richness (Schutz and Driscoll
2008), and in some instances, higher richness in mod-
ified landscapes (Suazo-Ortuno etal. 2008) have been
reported. Modified habitats, such as fragments, may
offer additional resources (resource subsidies) for
some taxa including increased food availability and
altered thermoregulatory conditions (Nowakowski
etal. 2018; Doherty etal. 2019), potentially increas-
ing available niches and counterbalancing the nega-
tive effect on species richness of ecosystem decay.
Fragment size was an important predictor for
species richness and diversity, with larger fragments
Table 3 Model selection for generalised linear models exploring how fragment type and size influence individual species abundance
(only models with delta AICc < 2 are shown)
Species Model terms df QAICc Delta QAICc R2
Lerista bougainvillii Fragment type + size 3 52.8 0 0.753
Fragment type + size + fragment type:size 4 53.5 0.70 0.804
Lampropholis delicata Size 2 33.3 0 0.834
Ctenotus robustus Fragment type + size + fragment type:size 4 36.7 0 0.999
Fragment type 2 37.2 0.54 0.974
Fragment type + size 3 37.5 0.83 0.993
Ctenotus orientalis Size 2 39.8 0 0.922
Menetia greyii Size 2 40.6 0 0.510
Christinus marmoratus Size 2 38.1 0 0.745
Fragment type + size 3 39.1 0.98 0.848
Amphibolurus norrisi Fragment type + size 3 53.1 0 0.718
Morethia obscura Size 2 36.4 0 0.992
Ctenophorus pictus Null 1 29.9 0 0.000
Size 2 31.4 1.41 0.316
Cercartetus lepidus Fragment type + size + fragment type:size 4 54.6 0 0.928
Cercartetus concinnus Null 1 36.4 0 0.000
Size 2 37.8 1.37 0.184
Pseudomys apodemoides Size 2 31.4 0 0.984
Fragment type + size 3 31.6 0.23 0.999
Limnodynastes dumerilii Fragment type + size 3 36.2 0 0.944
Fragment type 2 37.9 1.66 0.787
Tiliqua rugosa Fragment type 2 39.8 0 0.358
Fragment type + size 3 41.7 1.9 0.381
Aprasia striolata Fragment type + size 3 43.3 0 0.333
Size 2 43.8 0.44 0.231
Neobatrachus sp. Null 1 31.9 0 0.000
Size 2 32.7 0.81 0.303
Fragment type 2 33.8 1.87 0.148
Mus musculus Fragment type + size 3 40.0 0 0.911
Pygopus lepidopodus Fragment type + size 3 40.4 0 0.454
Fragment type + size + fragment type:size 4 41.4 0.98 0.502
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Table 4 Estimated model
coefficients for generalised
linear models exploring
how fragment type and size
influence individual species
abundance (only models
with delta AICc < 2 are
shown). Significant effects
(85%) are shown in bold
Species Predictors Estimate CI (85%)
Lerista bougainvillii (Intercept) −0.34 −1.09 to 0.41
Fragment type [Fragment] 1.44 0.63–2.25
Size 0.56 0.18–0.95
(Intercept) −0.21 −0.88 to 0.46
Fragment type [Fragment] 1.19 0.40–1.98
Size −0.13 −0.80 to 0.54
Fragment type [Fragment] × size 0.92 0.13–1.72
Lampropholis delicata (Intercept) 1.68 1.29–2.07
Size 0.61 0.20–1.02
Ctenotus robustus (Intercept) −0.41 −2.69 to 1.86
Fragment type [Fragment] 3.07 0.75–5.38
Size 2.36 0.35–4.37
Fragment type [Fragment] × size −2.15 −4.20 to −0.10
(Intercept) 1.24 0.16–2.32
Fragment type [Fragment] 1.43 0.23–2.64
(Intercept) 1.16 0.20–2.12
Fragment type [Fragment] 1.43 0.38–2.48
Size 0.42 −0.06 to 0.90
Ctenotus orientalis (Intercept) 2.01 1.71–2.30
Size 0.62 0.31–0.93
Menetia greyii (Intercept) 0.30 −0.15 to 0.75
Size 0.77 0.30–1.24
Christinus marmoratus (Intercept) 1.63 1.29–1.97
Size 0.55 0.19–0.91
(Intercept) 1.89 1.48–2.30
Fragment Type [Fragment] −0.61 −1.25 to 0.02
Size 0.55 0.18–0.92
Amphibolurus norrisi (Intercept) 0.58 0.25–0.90
Fragment type [Fragment] −2.44 −3.44 to −1.45
Size 0.61 0.28–0.95
Morethia obscura (Intercept) 2.70 2.44–2.96
Size 0.61 0.33–0.88
Ctenophorus pictus (Intercept) 0.95 0.38–1.52
(Intercept) 0.87 0.31–1.44
Size 0.42 −0.18 to 1.03
Cercartetus lepidus (Intercept) 1.69 1.41–1.98
Fragment type [Fragment] −2.74 −4.26 to −1.22
Size 0.27 −0.03 to 0.58
Fragment type [Fragment] × size 1.80 0.42–3.18
Cercartetus concinnus (Intercept) 0.76 0.37–1.15
(Intercept) 0.71 0.32–1.09
Size 0.33 −0.08 to 0.74
Pseudomys apodemoides (Intercept) 1.75 1.02–2.49
Size 0.89 0.13–1.65
(Intercept) 2.18 1.41–2.94
Fragment type [Fragment] −1.18 −2.42 to 0.05
Size 0.89 0.16–1.62
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having higher species richness and slightly higher
diversity. This is congruent with both the sample
area effect and island biogeography theory. Whilst
a large fragment is predicted to hold higher richness
than a small one, when comparing an equal amount
of habitat between single large and several small
fragments (SLOSS approach), island biogeogra-
phy theory predicts lower richness in several small
fragments, whereas the habitat amount hypoth-
esis is “equally compatible with either outcome of
SLOSS” (Fahrig 2021). Recent evidence contradicts
the island biogeography theory, finding small frag-
ments often outperform large ones (Wintle et al.
2019; Riva and Fahrig 2022). The mechanisms
driving this pattern are not fully understood but may
include: increased functional connectivity, spread-
ing of extinction risk, and landscape complementa-
tion (Fahrig 2003). Our data showed no evidence
of an island effect (Macarthur and Wilson 1967),
where species area curves are steeper for fragments
compared to pseudo-fragments, indicating small
fragments studied here were not depauperate of her-
petofauna and small mammal species studied, pro-
viding support for the high value of small fragments
(Fahrig 2013). Additionally, two threatened species
were only detected in fragments (E. curta and S.
crassicaudata) compared to one threatened species
only detected in pseudo-fragments (V. rosenbergi)
suggesting fragments provide habitat for rare spe-
cies as well as common ones.
Table 4 (continued) Species Predictors Estimate CI (85%)
Limnodynastes dumerilii (Intercept) 0.47 −0.36 to 1.31
Fragment type [Fragment] 1.30 0.39–2.21
Size 0.63 0.17–1.10
(Intercept) 0.65 −0.33 to 1.63
Fragment type [Fragment] 1.30 0.19–2.40
Tiliqua rugosa (Intercept) −2.4 −3.89 to −0.90
Fragment type [Fragment] 2.40 0.83–3.96
(Intercept) −2.43 −3.86 to −1.01
Fragment type [Fragment] 2.40 0.92–3.88
Size 0.28 −0.17 to 0.73
Aprasia striolata (Intercept) −1.59 −2.56 to −0.63
Fragment type [Fragment] 1.10 0.08–2.12
Size 0.84 0.24–1.45
(Intercept) −0.90 −1.51 to −0.29
Size 0.84 0.22–1.47
Neobatrachus sp. (Intercept) 0.46 −0.15 to 1.08
(Intercept) 0.34 −0.34 to 1.01
Size 0.54 −0.18 to 1.25
Mus musculus (Intercept) −2.64 −4.61 to −0.67
Fragment type [Fragment] 2.48 0.66–4.31
Size 1.65 0.68–2.61
Pygopus lepidopodus (Intercept) −0.72 −1.45 to 0.01
Fragment type [Fragment] −1.5 −2.64 to −0.37
Size 1.16 0.46–1.86
(Intercept) −0.55 −1.20 to 0.10
Fragment type [Fragment] −4.92 −10.32 to 0.49
Size 0.93 0.27–1.60
Fragment type [Fragment] × size 3.25 −1.10 to 7.59
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Does community composition differ between
fragments and pseudo-fragments?
We found a significant difference in species com-
position between fragments and pseudo-fragments.
Despite 22 of 26 species being detected in both
fragment types, the ordination showed a clear sepa-
ration between the community composition of frag-
ments and pseudo-fragments. Similarly, Kay etal.
(2018) found modified sites differed in composition
but not richness, compared with intact sites. There-
fore, remnant fragments can host novel communi-
ties (Morse etal. 2014), containing combinations of
Fig. 6 Predicted abundances of: A Lerista bougainvilli, B
Limnodynastes dumerilii, C Tiliqua rugosa, D Amphibolurus
norrisi, E Cercartetus lepidus, F Morethia obscura in frag-
ments and pseudo-fragments of sizes 1, 5 and 10 hectares.
Plots are derived from the highest performing model for each
species (Table3). Plots B, C and D relate to additive models
whilst the models for A, E and F contain an interaction term
(Table4)
Table 5 Model selection for multiple regression models
exploring how traits influence species response to fragmenta-
tion (top five performing models shown)
Model terms df AICc Delta AICc R2
Diet + habit + habitat breadth 7 38.2 0 0.799
Diet + habit 6 40.7 2.52 0.668
Habit + habitat breadth 5 41.5 3.37 0.533
Habit 4 41.9 3.70 0.393
Activity time + habitat
breadth + temperature
regulation
6 42.7 4.47 0.627
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fauna species that did not co-occur in the study area
prior to land modification.
One lizard (A. norrisi) and one marsupial (C. lepi‑
dus) were deemed ‘indicator’ species characteristic
of pseudo-fragment species assemblages. Several
characteristics of remnant fragments may lead to spe-
cies decline and contraction toward continuous habi-
tat. First, livestock grazing in fragments can reduce
habitat quality, limiting food and shelter resources
for some species (Driscoll 2004; Cordier etal. 2021).
However, in some cases, grazing has shown neg-
ligible effects on fauna communities (Read 2002;
Michael etal. 2018) indicating grazing context (i.e.,
stock density, grazing duration) may be important.
Second, edge effects may have a negative effect on
some species. For example, high edge:area ratio can
result in more intense visitation by introduced preda-
tors and, thus, higher predation pressure on species
vulnerable to such predators (Didham et al. 2007;
Graham etal. 2012). Indeed, in our study, fox activ-
ity was significantly higher in fragments compared
to pseudo-fragments. Third, fragment isolation can
reduce immigration and emigration, interrupting pop-
ulation dynamics (Fischer and Lindenmayer 2007).
Williams et al. (2012) found reptile species more
likely to occur in a fragment when in close proximity
to a large section of continuous habitat, implying dis-
persal is critical to ‘rescue’ or recolonise fragments.
Both pseudo-fragment indicator species are arboreal,
likely reducing their dispersal ability across the tree-
less agricultural matrix (Hansen etal. 2020), and con-
tributing to their reduced abundance in fragments.
Here, we see an ‘island effect’ where these species
are most abundant on the ‘mainland’, in this case the
continuous habitat of the reserve, and show reduced
abundance as fragment size decreases.
Despite the widespread negative consequences
of land modification, some native species are more
abundant in modified landscapes. We identified five
indicator species characteristic of fragments and con-
sider several possible explanations for their higher
abundance in fragments. First, agricultural landscapes
may offer increased resources (Doherty etal. 2019)
for species able to access them facilitating increased
survival and reproductive success. For instance, farm
dams and drainage lines inadvertently create breed-
ing habitat for water-dependent species (Knutson
et al. 2004) like the frog, L. dumerilii, which was
abundant in fragments. Second, altered exposure to
Fig. 7 Effect of species traits—diet (A), habit (B) and habi-
tat breadth (C)—on abundance. Positive effect size indicates
higher abundance in pseudo-fragments, negative effect size
indicates higher abundance in fragments
Table 6 Estimated model coefficients from the only supported
model (delta AICc < 2) showing the influence of species traits
on effect size (Cohen’s d)
Positive values indicate higher abundance in pseudo-fragments
whilst negative values indicate higher abundance in fragments
Predictors Estimate 85% CIs
Intercept 0.69 0.22 to 1.15
Diet (Carnivorous) 0.67 0.31 to 1.02
Diet (Omnivorous) −0.74 −1.32 to −0.16
Habit (Fossorial) −1.03 −1.47 to −0.59
Habit (Semi−arboreal) 1.17 0.71 to 1.63
Habitat breadth −0.22 −0.35 to −0.10
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disturbances, such as fire, may increase habitat suit-
ability for some species (Nimmo et al. 2012). The
absence of fire in fragments may benefit species that
prefer long-unburnt habitat (Haslem etal. 2011), like
the leaf-litter-dwelling lizard, L. bougainvilii, which
showed higher abundance in fragments. Indeed, vege-
tation surveys in our study showed that fragments had
significantly deeper leaf litter, and more structural
complexity at high and canopy strata, possibly a result
of fire exclusion from fragments. Third, ‘hard’ frag-
ment edges discourage emigration which can lead to a
‘crowding’ or ‘concentration’ effect (Grez etal. 2004;
Tscharntke etal. 2012), increasing a species’ popu-
lation density. This effect is likely strongest for spe-
cies with low dispersal ability, like the pygopodid, A.
striolata, which had higher abundance in fragments.
Importantly, factors driving a species’ response can
operate in tandem. For example, after fragmentation,
L. bougainvilli might increase in number due to the
concentration effect. Then, over time, leaf litter may
accumulate in the absence of fire, and the cultivation
of crops in the surrounding matrix cause a spillover
of agricultural pest insects resulting in better habitat
and more food resources for the skink, increasing the
carrying capacity of the population in the fragment.
Do traits mediate species abundance in fragments and
pseudo-fragments?
Ecological traits influence a species’ response to frag-
mentation, where some species are better equipped
to withstand disturbance compared to others (Henle
et al. 2004; Keinath et al. 2017; Doherty et al.
2020). We found three traits—diet, habitat breadth
and habit—affect species abundance between frag-
ments and pseudo-fragments. An omnivorous diet
provides a wider range of food items to exploit post-
disturbance when food resources may be altered,
whereas carnivorous species must continue to hunt
prey animals to survive, even when prey numbers
are reduced. Similarly, species with broad habitat
requirements can find refuge in a variety of habitats
compared to those with narrow habitat requirements
which are reliant on a select few habitat types, mak-
ing them vulnerable to extinction when these habitats
are altered (Lettoof et al. 2023). These traits—diet
and habitat breadth—are often assessed on a con-
tinuum of generalist to specialist. Our results support
existing evidence that generalists are more abundant
in fragmented agricultural landscapes compared to
specialists which are more likely to be rare or locally
extinct (Driscoll 2004; Michael etal. 2015; Keinath
etal. 2017; Simpson etal. 2023).
Compared to terrestrial species, semi-arboreal spe-
cies were more abundant in pseudo-fragments and
fossorial species more abundant in fragments. It is
possible that, for both groups, reduced dispersal influ-
ences species’ responses but in opposite directions.
After fragmentation, fossorial species may increase
in density through a concentration effect where indi-
viduals are no longer dispersing due to hard fragment
edges (Grez etal. 2004; Tscharntke etal. 2012). Fos-
sorial species may be buffered from negative effects
of fragmentation, such as grazing and increased pre-
dation by introduced predators, by their ability to
take refuge underground. Additionally, fossorial spe-
cies included in our study have small body size and
home ranges meaning small fragments can support
large populations. In contrast, the two semi-arboreal
reptiles in our study are comparatively large-bodied
with larger home ranges resulting in fewer individuals
occupying an equivalent area. As arboreal species are
presumably less likely to cross the treeless agricul-
tural matrix, reduced immigration from nearby pop-
ulations in large tracts of habitat may leave arboreal
species vulnerable to decline in fragments (Hoehn
etal. 2007; Munguia-Vega etal. 2013). On the other
hand, one study found arboreality to increase resist-
ance to land modification (Neilly et al. 2018), and
the abundance of one semi-arboreal mammal spe-
cies in our study, Cercartetus concinnus, was similar
between fragments and pseudo-fragments. Further
research is needed to disentangle the relative effects
of traits driving species’ responses to fragmentation.
Conservation implications
We show that fragments can contain novel commu-
nities, including threatened species, not present in
continuous habitat. These distinct communities are
shaped by traits advantageous to survival in altered
landscapes and may provide an important source of
adaptability to maintain ecosystem function in the
face of continued human disturbance. Furthermore,
fragments may provide ‘insurance populations’, safe-
guarded against large disturbances like wildfire and
disease which have the capacity to spread through
continuous habitat, decimating populations. Thus,
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Landsc Ecol (2024) 39:138 Page 19 of 21 138
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small fragments may be highly complementary to
large conservation reserves, and we support the grow-
ing body of evidence emphasising the importance of
preserving small habitat patches.
Acknowledgements We pay respects to the Wotjobaluk peo-
ple, traditional custodians of the land on which this research
was conducted. We are deeply grateful to landholders who
allowed us access to their property: Bim and Ben Nash, Rommi
Crouch, Mick Shoulders, Alan Bennett, Shane Dodson and
their respective families. Your welcoming nature and ongo-
ing support are greatly appreciated. We thank the many field
assistants for their contributions. This study was approved by
CSU ACEC (Protocol No. A21056) under the DEECA wild-
life permit (10010008) and Parks VIC access agreement
(AA-0000016).
Author contributions Project conception (DMW, DGN,
DMW, TSJ, CJJ, BH, DRM, EGR, WLG, AB, EL), data col-
lection (DMW, GDL, CJJ, AA, DGN), analysis (DMW, DGN),
writing, review and editing (all).
Funding Open Access funding enabled and organized by
CAUL and its Member Institutions. Funding for this work was
provided by the Department of Energy, Environment and Cli-
mate Action (DEECA), the Gulbali Institute GAPS program,
and the Bill Borthwick Scholarship from the Victorian Envi-
ronmental Assessment Council.
Data availability Data will be publicly available from the
Dryad digital repository.
Declarations
Competing interests The authors declare no conflict of inter-
est.
Open Access This article is licensed under a Creative Com-
mons Attribution 4.0 International License, which permits
use, sharing, adaptation, distribution and reproduction in any
medium or format, as long as you give appropriate credit to the
original author(s) and the source, provide a link to the Crea-
tive Commons licence, and indicate if changes were made. The
images or other third party material in this article are included
in the article’s Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not
included in the article’s Creative Commons licence and your
intended use is not permitted by statutory regulation or exceeds
the permitted use, you will need to obtain permission directly
from the copyright holder. To view a copy of this licence, visit
http://creativecommons.org/licenses/by/4.0/.
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