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Austral Ecology. 2024;49 :e13530.
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https://doi.org/10.1111/aec.13530
wileyonlinelibrary.com/journal/aec
INTRODUCTION
Vegetation structures play a critical role in mediating predation risk in
ecosystems worldwide (Janssen et al., 2007). Spinifex grass (Triodia
sp.), characterized by its tough, spiky texture, dominates more than a
third of Australia's immense arid and semi- arid interior. Spinifex is an
essential habitat for various small vertebrates due to its comparatively
cooler microclimate, rich invertebrate composition, and spiky structure
that provides protection from predators (Bell etal.,2021; Pianka,1989).
However, spinifex is highly flammable, rendering the associated vegeta-
tion communities susceptible to fire. As such, the abundance and cover
of spinifex in a given location often reflects the area's fire history (Haslem
etal., 2 0 11), which in turn influences animal species whose abundance
RESEARCH NOTE
The red fox (Vulpes vulpes) is the dominant predator of
lizard models in a semi- arid landscape, and predation risk
is reduced by vegetation cover
ShannonBraun1,2 | Euan G.Ritchie1 | Tim S.Doherty3 | Dale G.Nimmo4
Received: 6 July 2023
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Revised: 25 A pril 2024
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Accepted: 28 April 2024
DO I: 1 0.1111 /a ec.13 5 30
This is an open acces s artic le under th e terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium,
provided the original work is properly cited.
© 2024 The Authors. Austral Ecology published by John Wiley & S ons Austra lia, Ltd on be half of Ecol ogical S ociety of Australi a.
1School of Li fe and Environmental
Scienc es, Deakin University, Burwood,
Victoria, Australia
2Department of Ecology Evolution and
Environme nt, La Trobe Univer sity,
Bundoora, Victoria, Australia
3School of Life and Environmental
Scienc es, The University of Sydney,
Camperdown, New South Wales, Australia
4Gulbali Institute, Charles Sturt University,
Albury, NSW, Australia
Correspondence
Dale G. Nimmo, Gulbali Institute, Charles
Sturt University, Thurgoona, NSW 2640,
Australia.
Email: dnimmo@csu.edu.au
Present address
Tim S. Doherty, Biodiversity and
Conservation Science, Department
of Biodiversity, Conservation and
Attractions, Woodvale, WA, Australia
Funding information
Department of Energy, Environment and
Climate Action
Abstract
Vegetation structure affects predation risk in ecosystems around the world.
Spinifex (Triodia spp.) is a foundation species in fire- prone grasslands and wood-
lands that cover more than a third of Australia's land surface. Spinifex habitats
are known for their high reptile diversity, and it has long been hypothesized that
the spiky structure of spinifex dissuades predators, thereby providing a haven
for prey. We investigated predation risk to small lizards in semi- arid Australia
by identifying teeth marks on replica model plasticine lizards, in combination
with remote camera surveillance, to quantify and verify predation risk across
several microhabitats, including spinifex. The introduced red fox (Vulpes vulpes)
was identified as the main predator of lizard models, constituting 43.9% of all
predation attempts. Lizard models placed at the base of spinifex plants (Triodia
scariosa) were significantly less likely to be attacked than all other microhabitat
types (bare ground, leaf litter, burrows), confirming the hypothesis that spinifex
reduces predation risk. Our results support recent work that has highlighted
foxes as a significant predator of Australian reptiles. Given that fire is a driver of
spinifex cover in arid ecosystems, our findings have implications for interactions
between fire and invasive predators in Australian ecosystems.
KEYWORDS
hunting, mammalian predators, microhabitat, squamate, vegetation cover, wildfire
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varies in response to changes in spinifex structure, such as cover or
height (Verdon etal.,2020).
Invasive predators are a major driver of global biodiversity loss
(Doherty et al., 2016). Often, native species are naïve to the risks
posed by invasive predators, leading to increased mortality rates (Sih
et al., 2010). As a result, invasive predators tend to exert a stronger
suppressive effect on native prey compared with native predators (Salo
etal.,2007). Recent studies have emphasized the predatory pressure
exerted by invasive predators on Australian reptiles. For instance, red
foxes (Vulpes vulpes) and feral cats (Felis catus) are known to prey on
263 and 108 reptile species, respectively, including 15 and 20 threat-
ened species (Stobo- Wilson etal.,2021). However, beyond theirdietary
habits, little is known about the fine- scale behaviours of foxes and cats
when hunting reptiles, including what triggers their detection of prey and
decisions on whether or not to launch an attack.
We conducted a field experiment using model plasticine lizards to
assess which predators most frequently attack lizards, and to test the
influence of spinifex on attack rates. Plasticine models provide a sur-
rogate measure of predation pressure on stationary prey in instances
where studying real animals is not feasible or ethically permissible.
Their use allows for an approximation of predation risk, but does not in-
corporate some important elements of real predator–prey encounters;
namely, prey in real encounters have the option to flee an approach-
ing predator. Nonetheless, plasticine models have been successfully
used to study lizard predation in a variety of contexts, including driv-
ers of niche divergence (Daly et al.,2008), the influence of colour on
predation risk (Stuart- Fox etal.,2003), and the impact of vegetation
structure on predation rates (Bradley et al., 2022; Sato etal., 2014).
We were particularly interested in predation pressure exerted by the
red fox (Vulpes vulpes), after a previous study revealed it to be the
most widespread invasive predator within the study region (Payne
etal.,2014). We conducted this study in the semi- arid mallee region of
Victoria, Australia, which is home to many reptile species closely asso-
ciated with spinifex grass (Bell etal.,2021; Cogger,1989). We hypoth-
esized that red foxes would be frequent predators of the model lizards.
Additionally, we predicted that the model lizards situated in areas with
simpler vegetation structures would be more susceptible to predation
compared with those positioned within densely vegetated areas, like
those containing spinifex grass.
MATERIALS AND METHODS
Study area
We conducted this study in Murray- Sunset National Park in the semi- arid
northwest region of Victoria, Australia (coordinates: 34.81° S, 141.64°
E). The research focused on the predominant vegetation type in the
park, known as ‘triodia mallee’. This vegetation is characterized by a
canopy of multi- stemmed Eucalyptus dumosa and E. socialis, under-
lain by spinifex grass (Triodia scariosa) and interspersed with shrubs
(Haslem et al., 2010). The area is vulnerable to wildfires, which typi-
cally result in the consumption of most vegetation biomass at a site,
including the vast majority of spinifex. As the time elapsed since the last
fire increases, vegetation, including spinifex, progressively regenerates
(Haslem etal.,2011).
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Study design
Replica lizard models
We hand- crafted 280 plasticine lizards (Rainbow modelling clay, S & S
Wholesale Pty Ltd, Thornleigh, New South Wales, Australia; see Daly
etal.,2008). Each model had an approximate 80 mm snout- vent length, a
tail of equal length, and weighed around 90 g. They were painted to match
the mallee dragon's (Ctenophorus fordi) colour—an agamid lizard (i.e.,
Family Agamidae) that is locally abundant and influenced by fire and veg-
etation structure (Nimmo et al.,2 012)— using colour- matching scanners
(Bunnings Warehouse Pty Ltd, Thomastown, Victoria, Australia) from a
photograph of a mallee dragon. To simulate movement and attract preda-
tors, we attached each model to a platform connected to a spring, allowing
them to sway in the wind.
Experimental design
The lizard replicas were spread across 40 sites that were 20 × 20 m in
size and separated by at least 300 m. Within each plot, seven plasticine
lizard models were arranged (280 models total). In each of the 40 sites,
six lizard models were placed in the three dominant microhabitats: (1) bare
ground, (2) leaf litter, and (3) spinifex, with allocation to each microhabitat
being relative to proportional coverage, which was visually estimated by SB
using a Braun- Blanquet cover scale. Additionally, a seventh lizard model
was situated within a small hole in the sandy substrate, simulating a lizard
emerging from its burrow. Models set in spinifex were positioned so that
they were partially emerging from the base of the spinifex clump, which imi-
tates the behaviour of spinifex specialist lizards that use this anti- predator
tactic during the initial stages of basking (Cogger,19 74). At each site, a
motion- sensing camera (ScoutGuard 550) was installed 1 m in front of one
of the lizard models placed on bare ground at a height of 50 cm to monitor
for any predation events.
Monitoring predation events
Models were deployed for 47 days in summer (December 2012 to January
2013) when reptile activity in the region is at its highest. Following retrieval,
models were inspected for bite marks to identify instances of predation
and the likely predator involved (e.g., fox, varanid lizard, other lizards, bird,
cat, or unknown). This approach has been successfully employed in previ-
ous studies to both recognize predators and to measure predation rates
(Bateman etal.,2017; Daly etal.,2008). To ensure the accuracy of preda-
tor identification based on bite marks, the data were corroborated using
known predation events captured by the remote cameras. The relatively
long period between deployment and retrieval means that predators may
have learned that lizard models were not real prey during the deployment
period, but we are unable to verify this with our data.
Statistical analysis
We employed generalized linear mixed models (GLMMs) with a bino-
mial error distribution using the lme4 package in R (Bates et al.,2015).
We included ‘site’ as a random effect because the models were spatially
14429993, 2024, 5, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/aec.13530 by National Health And Medical Research Council, Wiley Online Library on [11/07/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License
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clustered within sites. The response variable in our analysis was a binary
variable with 0 indicating no predation on a model and 1 indicating any
predation. Total predation was chosen over predation by specific predators
due to the relatively low sample size of predation events for each group.
To evaluate whether the cameras' presence influenced the likelihood of
predation, we first constructed a GLMM to compare the lizard models that
were positioned in front of cameras with those situated in the same micro-
habitat (i.e., bare ground) but not in front of cameras. Next, we modelled
the probability of predation in relation to the type of microhabitat, which
was treated as a single predictor variable with four categories. ‘Spinifex’
was designated as the reference category, and it was compared against
‘bare ground’, ‘leaf litter’, and ‘burrow’. GLMMs were used to calculate odds
ratios which measure the odds that a predation event will occur under one
treatment in relation to the reference category.
RESULTS
During the 47- day sampling period, attacks were recorded on 57 of the
280 lizard models (20.4% of all models). Foxes were the primary preda-
tors, accounting for the largest number of predation attempts (25 instances,
or 43.9% of the attacks) (Figure1). They were followed by birds (12 in-
stances; 21.1%), other reptiles (10 instances; 17.5%), unidentified predators
(9 instances; 15.7%), and lastly, a single predation event by a feral cat (1
instance; 1.8%). The footage from the motion- sensing cameras captured
foxes exhibiting strong behavioural responses indicative of predation at-
tempts. They were seen carefully approaching the models and then chew-
ing and pulling at them for several seconds, leaving behind characteristic
stretching on the devices and chew marks on the models (Figure2). In
most cases, the evidence for identifying the predators was clear, as distin-
guishable teeth marks were left on the models. Moreover, tracks and scat
found near the models often aided in predator identification. Out of the
25 instances involving foxes, cameras recorded 28%, with each recording
confirming the correct field identification of fox predation. The placement of
models in front of cameras did not have an impact on the overall predation
rates (GLMM coefficient = −0.50, S.E. = ±0.86).
The microhabitat where a lizard model was positioned significantly im-
pacted the likelihood of predation overall (Figure3, Table1). In terms of
total predation, models placed on bare ground, in leaf litter, and in burrows
were 3.58, 3.44, and 6.03 times respectively more likely to be preyed upon
compared with those placed in spinifex (Figure3, Table1). Microhabitat
accounted for ~10% of the variation in the data (Table1).
DISCUSSION
Our study has demonstrated that foxes are a dominant predator of liz-
ards in the study region, accounting for more than 40% of all recorded
attacks. It is increasingly evident that red foxes play a significant role as
predators of reptiles, particularly lizards, in Australian ecosystems. Stobo-
Wilson etal.(2022) estimated that foxes are responsible for the predation
of ~88 million reptiles annually across Australia, including 95 squamate
(i.e., lizards and snakes) species. Fleming etal.(2021) noted that reptiles
are frequently found in the scats and stomachs of foxes, especially in arid
and semi- arid regions. Our study corroborates this by demonstrating that
foxes were the dominant predator of lizards during the summer months in a
semi- arid region. More generally, our findings are consistent with previous
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studies of plasticine model reptiles that have found mammals to be domi-
nant predators (Duchesne etal.,2022; Purger etal.,2017 ).
Stobo- Wilson et al. (2022) observed that reptiles are more frequently
found in the diets of foxes in areas with sparse vegetation and higher tem-
peratures. This finding is complemented by other research underscor-
ing the role of vegetation structure in moderating reptile predation risk
(Duchesne etal.,2022; Hansen etal.,2019; Sato etal. 2014). Our research
FIGURE 1 The proportion of predator attacks made by foxes, birds, and reptiles out of 280 lizard models placed throughout mallee
habitats in south- eastern Australia. The total number of attacks by each predator type is provided in parenthesis.
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contributes to this discussion, revealing that lizards placed near the base of
spinifex clumps are less likely to fall prey, indicating that denser vegetation
like spinifex serves as a refuge for small vertebrates. The protective role
of spinifex can be attributed to two primary factors: its physical protection
and its impact on prey detection by predators. Spinifex's dense and spiky
nature provides a physical barrier that would likely be uncomfortable for
predators to penetrate during hunting (Cogger,1974; Pianka,1989). This
deterrent may discourage predators from pursuing prey within spinifex
clumps. Additionally, our positioning of lizard models—designed to imi-
tate lizards partially covered by spinifex while basking at the base of the
clump—could obscure predators' visual detection from behind or above.
Therefore, the lower predation rates on lizard models under spinifex may
also be due to reduced prey visibility to predators. We believe that these
two factors, protection and reduced detection, jointly contribute to the ob-
served decrease in predation rates on our lizard models, and real lizards.
Spinifex is a crucial resource for numerous lizards throughout much of
arid and semi- arid Australia, and its cover and structure significantly influ-
ence the presence of spinifex specialist species (Nimmo etal.,2014; Verdon
etal.,2020). Besides offering refuge from predators, spinifex also provides
shelter from temperature extremes by moderating the microclimate (Bell
et al., 2021; Cogger, 19 74) and supports termite populations, which are
essential prey for many spinifex specialists (Morton & James,1988). Our
study suggests that protection from predation is likely to account for at least
part of the association between reptiles and spinifex (Pianka,1989).
The pace of spinifex recovery after a fire is closely tied to the rate at
which fauna dependent on spinifex can re- colonize burnt landscapes. In
our study system, spinifex is very rare in the years after fire, comprising
about 2% of ground cover immediately after fire, and taking ~30 years to
reach peak cover of ~20% (Haslem etal.,2011). Fire regimes that result in
large amounts of recently burnt vegetation are likely to heighten predation
risk for a variety of spinifex- dependent species by removing the protection
from predation that is afforded by spinifex. This predation pressure could be
FIGURE 2 Screen shots of predation at tempts on lizard models. Top row: red foxes (Vulpes vulpes); bottom row: red fox, white winged
chough (Corcorax melanorphamphos) and central bearded dragon (Pogona vitticeps).
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magnified if red foxes and cats are drawn into recently burnt areas, which
has recently been demonstrated in the Murray mallee (Senior etal.,2023).
Retaining patches of unburnt spinifex within the fire boundary could be
one way of maintaining reptile species diversity during prescribed burning.
In support of this, Senior etal.(2023) found three species of reptile and
reptile richness was higher in areas near large unburnt refuges following a
prescribed fire in the mallee.
Our study does have limitations. First, employing a more realistic model,
perhaps created from 3D prints of scanned lizards and equipped with life-
like movements, might yield more ecologically meaningful predation rates
FIGURE 3 Predictions from generalized linear mixed models of the probability of a model being attacked by any predator over the
47 days deployment period according to the microhabitat within which the lizard model was placed. Error bars represent 95% confidence
intervals. The number above each error bar represents the total count of models attacked, while the number below indicates the count of
models not attacked, within each microhabitat type.
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compared with what was observed in the current study. Second, introduc-
ing novel objects into the environment, even if they are designed to re-
semble real animals, might prompt predators to investigate the objects for
reasons other than predation. Some studies have employed control models
constructed from the same materials as the animal replicas but without
mimicking the shape of an animal (e.g., Bell etal.,2021). Although rela-
tively few studies deploy such controls, this approach can be instrumental
in distinguishing genuine predation from other behaviours that might be
misconstrued as predation events (e.g., predators investigating or attempt-
ing to remove the unfamiliar object). It can also help differentiate the cues
that predators rely on to locate prey (i.e., visual versus olfactory) (Bateman
etal.,2017). It would be beneficial for future studies to compare predation
rates in other types of low vegetation, such as small shrubs that lack spiky
features, to better differentiate between the protection and detection fac-
tors mentioned earlier. Future research could also examine how varying
environmental conditions affect predation rates. Our study was conducted
after 2 years of very high rainfall (2010–2011) relative to the long- term av-
erage, which likely inflated predator populations through increased prey
abundance. In contrast, Bell etal. (2021) conducted a similar experiment
during a drought, but recorded almost no predator attacks on their lizard
models.
Our study has confirmed that spinifex protects prey animals from pre-
dation by an invasive predator, the red fox. Fire management should seek
to maintain unburnt patches of spinifex during prescribed burning to create
predator refuges that facilitate the persistence and recovery of prey ani-
mals following fire.
AUTHOR CONTRIBUTIONS
Shannon Braun: Conceptualization (equal); formal analysis (equal); inves-
tigation (equal); methodology (equal). Euan G. Ritchie: Conceptualization
(lead); funding acquisition (equal); investigation (equal); methodology
(equal); project administration (equal); resources (equal); supervision
(equal); writing – review and editing (equal). Tim S. Doherty: Formal
analysis (equal); writing – review and editing (equal). Dale G. Nimmo:
Conceptualization (lead); formal analysis (lead); funding acquisition (equal);
methodology (equal); project administration (equal); resources (equal); su-
pervision (equal); visualization (equal); writing – review and editing (equal).
ACKNOWLEDGEMENTS
Thanks to Andrew Bennett and Mike Clarke for agreeing that this study was
worth doing, and facilitating its support. Thanks to Christopher Gordon for
his helpful insights into the joys of model plasticine lizard- making. Many
thanks to Mackenzie Kwak, Nathan Litjens, Ryan Davis, David De Angelis,
TAB LE 1 Generalized linear mixed model results depicting the odds of replica lizard
models being attacked in different microhabitats, with ‘Spinifex’ as the reference category.
Predictors Odds ratios CI p
Intercept (Spinifex) 0.08 0.03– 0.20 <0.001
Bare ground 3.58 1.3 0 –9.85 0.013
Burrow 6.03 1.92–18.95 0.002
Leaf Litter 3.44 1.0 7–11.0 3 0.038
Observations 280
Marginal R2/conditional R20.096/0.137
Note: The table presents the odds ratios, confidence intervals (CI), and p- values for each predictor
(Bare ground, Burrow, Leaf Litter). Rand om effects, Intraclass Correlation Coefficient (ICC), and R-
squared values (Marginal R2 and Conditional R2) are also displ ayed.
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Connie Warren, Megan Ouyang, and Bronwyn who were all valuable field
volunteers. Finally, thanks to Jessica Hodgson and Luke O'Loughlin for
helpful comments that improved this manuscript. Funding was supplied
by the Department of Energy, Environment and Climate Action under the
Mallee Hawkeye project. Open access publishing facilitated by Charles
Sturt University, as part of the Wiley - Charles Sturt University agreement
via the Council of Australian University Librarians.
DATA AVAILABILITY STATEMENT
Data available on request from the authors.
ORCID
Euan G. Ritchie https://orcid.org/0000-0003-4410-8868
Dale G. Nimmo https://orcid.org/0000-0002-9814-1009
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How to cite this article:
Braun, S., Ritchie, E.G.,
Doherty, T.S. & Nimmo, D.G.
(2024) The red fox (Vulpes
vulpes) is the dominant
predator of lizard models in a
semi- arid landscape, and
predation risk is reduced by
vegetation cover. Austral
Ecology, 49, e13530. Available
from: h t tp s : // d o i .o r g / 10 .1111/
aec.13 5 30
14429993, 2024, 5, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/aec.13530 by National Health And Medical Research Council, Wiley Online Library on [11/07/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License