Educating the enemy: Harnessing learned avoidance behavior in wild predators to increase survival of reintroduced southern corroboree frogs

Abstract

After decades of near‐complete extirpation, the yellow‐and‐black‐striped Southern Corroboree Frog (Pseudophryne corroboree) is being reintroduced into field enclosures that exclude all but avian predators. The frog's long absence means avian attack risk to reintroduced individuals is unknown, so we asked: does corroboree frog coloration make them vulnerable to predators? First, using painted clay frog models and humans as proxy predators, we found that, surprisingly, striped models were as difficult to detect as control black models, and were far less detectable than yellow models. Second, to quantify attack probabilities, we deployed 2,304 models twice in the species' former range. Of our recovered models, 18% of the striped models were attacked by birds, suggesting they are a significant threat. In our second deployment, we saw a significant reduction in attacks on all model colors with only 10% of striped models attacked. If predators generalize their avoidance learning to real corroboree frogs, strategically timed model deployment near release sites may enhance the probability of survival of reintroduced frogs. Our study suggests that model deployment could be an effective low‐cost technique to increase the survival of reintroduced prey species, including, but not limited to, those potentially conspicuous to their natural enemies.

Full text

CONTRIBUTED PAPER
Educating the enemy: Harnessing learned avoidance
behavior in wild predators to increase survival of
reintroduced southern corroboree frogs
Kate D. L. Umbers
1,2
| Julia L. Riley
3
| Michael B. J. Kelly
1,2
|
Griffin Taylor-Dalton
1
| Justin P. Lawrence
4
| Phillip G. Byrne
5
1
School of Science and Health, Western
Sydney University, Richmond, New South
Wales, Australia
2
Hawkesbury Institute for the
Environment, Western Sydney University,
Richmond, New South Wales, Australia
3
Department of Botany & Zoology,
Stellenbosch University, Stellenbosch,
South Africa
4
Department of Biology, University of
Mississippi, Oxford, Mississippi
5
School of Biology, University of
Wollongong, Wollongong, New South
Wales, Australia
Correspondence
Kate Umbers, School of Science and
Health, Western Sydney University,
Richmond, NSW, Australia.
Email: k.umbers@westernsydney.edu.au
Funding information
University of Wollongong, Grant/Award
Number: VC's Fellowship; Australian
Research Council, Linkage Program,
Grant/Award Number: LP170100351
Abstract
After decades of near-complete extirpation, the yellow-and-black-striped
Southern Corroboree Frog (Pseudophryne corroboree) is being reintroduced
into field enclosures that exclude all but avian predators. The frog's long
absence means avian attack risk to reintroduced individuals is unknown, so
we asked: does corroboree frog coloration make them vulnerable to predators?
First, using painted clay frog models and humans as proxy predators, we found
that, surprisingly, striped models were as difficult to detect as control black
models, and were far less detectable than yellow models. Second, to quantify
attack probabilities, we deployed 2,304 models twice in the species' former
range. Of our recovered models, 18% of the striped models were attacked by
birds, suggesting they are a significant threat. In our second deployment, we
saw a significant reduction in attacks on all model colors with only 10% of
striped models attacked. If predators generalize their avoidance learning to
real corroboree frogs, strategically timed model deployment near release sites
may enhance the probability of survival of reintroduced frogs. Our study sug-
gests that model deployment could be an effective low-cost technique to
increase the survival of reintroduced prey species, including, but not limited
to, those potentially conspicuous to their natural enemies.
KEYWORDS
alpine, antipredator, aposematism, Australian Alps, chytrid, clay models, conservation,
reintroduction
1|INTRODUCTION
The success of reintroduction programs can depend on
the depth of scientific knowledge on species' natural his-
tory (Berger-Tal et al., 2011). Understanding predator–
prey dynamics and directly measuring the potential
impact of predation on postrelease survival can therefore
help optimize reintroductions (Armstrong & Seddon,
2008). Species' vulnerability to predation largely depends
on the experience predators have with the profitability of
Received: 21 May 2019 Revised: 29 October 2019 Accepted: 6 November 2019
DOI: 10.1111/csp2.139
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided
the original work is properly cited.
© 2019 The Authors. Conservation Science and Practice published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology
Conservation Science and Practice. 2020;2:e139. wileyonlinelibrary.com/journal/csp2 1of15
https://doi.org/10.1111/csp2.139

potential prey in combination with the experience prey
have in successfully avoiding their predators. Captive
and/or isolated prey populations can lose protective traits
that are maintained in their wild counterparts through
natural selection (Jolly, Webb, & Phillips, 2018). For
example, over just 13 generations, northern quolls
(Dasyurus hallucatus) descended from populations on a
predator-free island lost protective traits that their main-
land counterparts retained (Jolly et al., 2018). Predator
awareness can be reinstated using conditioning tech-
niques with model predators (Griffin, Blumstein, &
Evans, 2000). For example, captive-raised tammar wal-
labies (Macropus eugenii) that do not exhibit natural
predator-avoidance behaviors can be successfully trained
to avoid foxes (Vulpes vulpes) before release by exposing
them to taxidermy foxes as model predators. Similar con-
ditioning techniques have also been used on El Hierro
giant lizards (Gallotia simonyi) who subsequently change
their behavior when in the presence of cats and kestrels
(Burunat-Pérez, Suárez-Rancel, & Molina-Borja, 2018).
Yet, the outcome of training is not always successful. For
example, similar training techniques have also been used
on greater bilbies (Macrotis lagotis), but whether training
enhances survival in the wild is currently equivocal
(Moseby et al., 2011; Moseby, Cameron, & Crisp, 2012).
An alternative approach to manipulating predation rates
in conservation strategies is to teach the predator population
to avoid prey. In their classic experiment, Nicolaus, Cassel,
Carlson, and Gustavson (1983) showed that crows (Corvus
brachyrhynchos) can be taught to avoid colored eggs con-
taining a toxin, and then generalize to avoid eggs of the
same color in other locations. Learned avoidance condition-
ing has also been a successful technique for teaching some
Australian native predators to avoid eating the invasive cane
toad (Bufo marinus), whose chemical defense is highly toxic
to many Australian species (Ujvari, Mun, et al., 2013;
Ujvari, Oakwood, & Madsen, 2013). For example, survival
of the northern quoll (D. hallucatus) is enhanced when indi-
viduals are trained to avoid eating cane toads by feeding
them toad-flavored sausages laced with thiabendazole
which induces nausea (Indigo, Smith, Webb, & Phillips,
2018). When the prey species is the focus of conservation,
generating or enhancing learned avoidance in the wild
predator population is a logical extension of the learned-
aversion methods so far applied to conservation. Brightly
colored prey species may be particularly susceptible to pred-
ators upon reintroduction, so teaching predators to avoid
them warrants investigation as a powerful tool in their
recovery program.
Understanding the role an imperilled species' colora-
tion plays in protecting them from predation is an impor-
tant aspect of their natural history that should be
incorporated into conservation plans. Predators can be
deterred by prey via protective coloration, a broad term
that includes camouflage (concealing) and aposematism
(warning). Camouflage includes background matching
(crypsis/disruptive coloration), and individuals appearing
to be something they are not (masquerade; Ruxton,
Sherratt, & Speed, 2004). The protective value of camou-
flage lies in predators either failing to detect prey, or
detecting them but misclassifying prey as something
inedible (Guilford & Dawkins, 1991; Skelhorn, Rowland,
Speed, & Ruxton, 2010). Upon reintroduction, extirpated
species that rely on camouflage may experience the same
level of protection as their ancestors if the environment
has not changed in a way that now renders them conspic-
uous. However, this may be less likely for animals with
warning colors (one type of aposematism).
Aposematic animals that use coloration as their signal
are often conspicuous and easy to detect (Mappes,
Marples, & Endler, 2005), but the protective value of
aposematism comes from predators coupling the signal with
unprofitability. Often it is essential that predators learn to
associate a signal with unprofitability through experience
interacting with the prey, sometimes killing the prey in the
process (Endler & Mappes, 2004). Extirpated aposematic
species that require predator learning for effective protection
face a challenge upon reintroduction; if they are conspicu-
ous, they may be fatally attacked if the current generation of
predators is naïve to the meaning of their signal. Thus,
reintroduced aposematic prey may experience high preda-
tion rates as predators learn to avoid them, potentially dev-
astating conservation efforts. However, learned avoidance is
not always required. Predators may have innate aversion to
certain color patterns—like black and yellow stripes
(Lindström, Alvtalo, Mappes, Rilpi, & Vertainen, 1999)—
and preferentially avoid them in a neophobic response
(Exnerováetal.,2007;Mappesetal.,2005).Inaddition,
avoidance can be socially learned as individual predators
observe each other attempting to subdue prey (Thorogood,
Kokko, & Mappes, 2018). Reintroduced aposematic prey
may thus be protected without predators having to learn
avoidance, or in other cases face high levels of predation as
predators learn about the prey's unprofitability. Thus, the
effect of coloration on prey vulnerability cannot be assumed
and ought to be measured when possible.
The IUCN Global Amphibian Assessment identified
26 Australian frog species needing ex situ intervention
(McFadden et al., 2013). Of these species, several exhibit
striking coloration, including the black-and-yellow striped
southern and Northern Corroboree Frogs (Pseudophryne
corroboree and P. pengellyi, respectively). Their coloration
and the ability of Pseudophyrne sp. frogs' to both acquire
toxins from their diet and generate them de novo
(Pseudaphryinanime, see below) has led to the widely held
assumption that the corroboree frogs are aposematic, though
2of15 UMBERS ET AL.

this hypothesis has not been formally tested. Both species are
threatened, and the Southern Corroboree Frog is critically
endangered. For 40 years, Southern Corroboree Frogs have
experienced a catastrophic population decline due, primarily,
to living in sympatry with a chytridiomycosis reservoir spe-
cies (Crinia signifera; Hunter, Marantelli, et al., 2010; Hunter,
Speare, et al., 2010; Scheele et al., 2017). Southern Corrobo-
ree Frogs are now functionally extinct (Brannelly, Roberts,
Skerratt, & Berger, 2017). Only a small number of individuals
remain in the wild at translocated and reintroduced sites
(McFadden, personal communication). Their survival is
dependent on ex situ breeding and reintroduction (Berger
et al., 2016). Reintroduction enclosures exclude mammalian
and reptilian predators, but do not exclude birds, primarily
visual hunters that have tetrachromatic vision (full color
vision including sensitivity in the ultraviolet; Bennett,
Cuthill, & Norris, 1994; Hart, Partridge, Cuthill, & Bennett,
2000; Brannelly et al., 2015). So, does Southern Corroboree
Frog coloration make them vulnerable to bird attack?
We aimed to understand predation risk faced by
reintroduced Southern Corroboree Frogs through two
experiments using clay models to quantify the probability
that frogs are detected and attacked by birds. We chose clay
models because (a) real frogs are highly valuable for conser-
vation, and (b) naturally occurring predation events are sel-
dom witnessed in nature (Noonan & Comeault, 2009). In
all experiments we used black, yellow, and black-and-
yellow striped clay frog models. By including plain black
and yellow models we controlled for the relative extremes
of detectability, and the colors themselves influencing
detectability and attack independent of the pattern.
The aim of the first experiment was to measure the
detectability (sensu Guilford & Dawkins, 1991) of our
three types of clay models (Endler, 1991; Guilford &
Dawkins, 1991). When using clay models to measure pre-
dation rates in free-ranging wild predators, it is impossi-
ble to determine when models are detected but ignored
by predators (Rößler, Pröhl, & Lötters, 2018). We thus
used humans as a proxy for predators to measure detect-
ability, as is commonplace in sensory ecology, because
unlike wild bird predators humans can tell us when they
see a model (Bergeron & Fuller, 2017; Mappes, Kokko,
Ojala, & Lindström, 2014; Seddon, Tobias, Eaton, &
Ödeen, 2010). Although human vision differs from bird
vision in that we do not detect ultraviolet, Southern Cor-
roboree Frogs do not reflect in the ultraviolet, so humans
can see the complete reflectance of Corroboree Frog col-
oration (Figure 1, Umbers, Silla, Bailey, Shaw, & Byrne,
2016). Our hypothesis was that the model types differed
in their detectability. We predicted that (a) if stripes cam-
ouflage frogs, then striped models would be detected at a
similar rate to black models, and (b) if stripes make frogs
conspicuous, striped models would be detected at a simi-
lar rate to yellow models.
FIGURE 1 Reflectance of the
yellow coloration of live Southern
Corroboree Frogs (a), the yellow paint
on our clay frog models (b), the black
paint used on the black frog models (c),
and the black stripes on the yellow-and-
black striped frog models (d)
UMBERS ET AL.3of15

The aim of the second experiment was to understand
how coloration influences the avian predation risk to
reintroduced Southern Corroboree Frogs. We deployed
clay models within parts of the Southern Corroboree Frog's
former range and quantified avian attacks. Our hypothesis
was that the model types differed in their probability of
bird attack. We predicted that if corroboree frog coloration
makes them vulnerable, and frogs are attacked by preda-
tors (because they have lost learned avoidance, lost innate
avoidance, or never had innate avoidance), we would see
similarly high attack rates on striped and yellow models,
and low attacks on black models. However, if corroboree
frog stripes are protective through concealing them from
predators (camouflage), or if predators avoid their stripes,
we expected similarly low attack rates on striped and black
models, and higher attack rates on yellow models.
Finally, we aimed to determine whether the unprofit-
able experience of mistaking a clay model for food could
deter predators in future encounters. We deployed our
models a second time and tested for differences in attacks
between the first and second deployments in the same
locations 5 weeks apart. We predicted that predators
would exhibit learned avoidance and be less likely to
attack models in the second deployment after having had
an initial unprofitable experience attacking a clay frog.
2|METHODS
2.1 |Natural history
P. corroboree is a small toadlet endemic to alpine habitats
above 1,200 m elevation in Australia with striking longitudi-
nal black-and-yellow stripes (Figure 2). To people of the
Wolgalu Aboriginal Nation the Southern Corroboree Frog
is known as Gyack (Connolly, Williams, & Williams, 2017).
For Wolgalu people, Gyack's breeding calls herald prepara-
tion for travel to the Australian high country for important
spring seasonal ceremonies and sacred business (Connolly
et al., 2017). Corroboree frog breeding season is a signal of
spring in the Australian Alps because it is triggered by the
snow melt during which males gather in peat bogs to con-
struct a small, dry chamber withinvegetationandsoiland
call to attract females to mate. Females lay their eggs within
the chamber, and the male remains inside it throughout the
breeding season (January and February annually) (Byrne &
Silla, 2017). Embryos develop within the egg until they
reach an advanced stage, at which point they undergo dia-
pause until winter rains stimulate hatching (Anstis, 2014).
After hatching, tadpoles remain in winter pools and meta-
morphose in the following summer (about a year of devel-
opment from egg deposition until metamorphosis) (Anstis,
2014). The frogs become sexually mature around 4 years old
(Hunter, Osborne, Smith, & McDougall, 2009; McFadden
et al., 2013). In general, Pseudophryne frogs possess defen-
sive chemical compounds in the skin (Daly et al., 1990)
derived both from their diet and de novo but it is unclear as
to whether the corroboree frogs possess these toxins (Smith
et al., 2002). Candidate avian predators in the frog's range
probably include: Australian Magpie, Cracticus tibicens;Lit-
tle Raven, Corvus mellori; Pied Currawong, Strepera
graculina; and Laughing Kookaburra, Dacelo novaeguinea.
2.2 |Clay model approach and
construction
The clay model experimental approach uses models to
assess predation risk as an alternative to natural observa-
tion when predation is rarely observed, or individuals are
FIGURE 2 Photographs of
(a) real Southern Corroboree Frog,
and (b) black, (c) black-and-yellow
striped, and (d) yellow frog models
with bird attack impressions
4of15 UMBERS ET AL.

rare. Our clay models were approximately 27 mm in
snout-to-vent (SVL) length, comparable to a mature spec-
imen of P. corroboree (25–33 mm SVL) (Anstis, 2014). To
construct models, we heated clay and then poured it into
silicone molds and allowed it to set. We used Monster
Clay, which is an oil-based plasticine clay that sets firm
but does not harden, ensuring the clay remains soft and
can retain evidence of predation attempts (i.e., tooth or
beak impressions). Three color patterns were selected for
model coloration, “black,”“yellow,”and “striped”
(Figure 2). Visual comparison with spectrophotometric
measurements using a Jaz spectrophotometer (Ocean
Optics, Dunedin) of live specimens of P. corroboree
viewed at Taronga Zoo, and on eight individuals from a
research colony at the University of Wollongong (see
Umbers et al., 2016), allowed for accurate color matching
of paints used to color over the brown clay used to make
all models (Figure 1). The black treatment (N= 768;
black paint: Derivan Matisse “Raw Umber,”Series 1) had
a dual function, controlling for the black stripes in the
corroboree pattern and resembling a palatable, compara-
tively sized camouflaged species (e.g., C. signifera) found
sympatrically with P. corroboree. The plain yellow treat-
ment acted as a control for conspicuousness of the yellow
in the corroboree frog pattern (N= 768; yellow paint:
Resene “Bird Flower”). Black stripes were added to
models painted with the same yellow as above to create
the striped models (N= 768; yellow paint: Resene “Bird
Flower”; black stripes: Black Uniball Posca PC-3M,
Tokyo). Once the paint dried, clear acrylic gloss spray
(MTN Montana Colors, Barcelona) was applied to all the
models to give them a wet appearance, simulating the
appearance of live frogs.
2.3 |Model detectability
We created a 10 m ×25 m grid of 30 models (10 per treat-
ment) in a grassy field at the Hawkesbury Campus of
Western Sydney University, similar to alpine sites where
the models were deployed. Models were placed on both
sides of a 1 m wide midline that spanned the 25 m length
of the grid. Models were placed at intervals 1–5 m perpen-
dicular to the midline on a wooden golf tee in the ground
to stabilize them. Models were spaced haphazardly along
the 25 m axis of the grid to ensure observers did not
expect models at particular intervals. Before the trial,
34 observers were independently shown an unpainted
model and were told that models similar to, but not the
same as, the model they were shown could be found per-
pendicular to the midline between 1 and 5 m away. Land-
marks were pointed out to observers to ensure boundaries
of the grid were clear. Observers then followed an
experimenter that walked at a standardized pace (~1 m/s),
and noted each model detected.
We used a generalized linear mixed effect model
(GLMM using the lme4 R package; Bates, Mächler,
Bolker, & Walker, 2015) with a binomial distribution
(logit link) to statistically analyze our data in R version
3.4.0 (R Core Team, 2017). We compared whether a
model was detected (binary response variable: seen = 1,
not seen = 0) between treatments (categorical fixed effect:
black, yellow, or striped), while controlling for distance
the model was from the pathway (continuous fixed effect)
and differences between human subjects (random effect).
Post hoc, to examine comparisons between all treatment
types, we used the R function lsmeans from the lsmeans
R package, and corrected p-values using Tukey's HSD
multiplicity adjustment (Lenth & Lenth, 2018).
2.4 |Model attacks
To assess attack rate by avian predators, we deployed
2,304 frog models (all three colors; N= 768 of each) on
two separate occasions during the 2015/2016 summer in
Kosciuszko National Park, New South Wales, Australia
within the historic range of the Southern Corroboree
Frog. Models were deployed first between December
28, 2015 and January 2, 2016 and, second, February 8–12,
2016. This was during the Southern Corroboree Frog's
breeding season when predators would most likely
encounter adult frogs gathered together (Hunter et al.,
2009). To measure changes in predator behavior, the
same transects were used in both deployments. Transects
were at four locations >2 km apart each containing
576 models. Transect starting locations were
(a) 3631029.5300S, 14815050.3100E, (b) 3624021.8100 S,
14818046.8400E, (c) 3622036.0000S, 14822012.0000 E, and
(d) 3622036.8100S, 1482901.3100 E. These locations are
more than 30 km from the nearest current Southern Cor-
roboree Frog reintroduction site. To be clear, we are not
providing location information on the current locations
of Southern Corroboree Frogs (only our study's transect
locations) in order to keep the locations of this critically
endangered species secret.
We deployed models in 24 rows of 24 frogs (8 models
of each color in a randomized order 1 m apart) with each
row approximately 100 m apart to maximize the likeli-
hood of independent attacks (that different individual
birds attack the models), which can be a common prob-
lem with clay model experiments (Noonan & Comeault,
2009) (Figure 3). We selected this “clumped”design
because (a) as predator encounter rate increases, preda-
tors are more likely to learn when prey are clumped
(Endler & Rojas, 2009; Gamberale & Tullberg, 1996; Riipi,
UMBERS ET AL.5of15

Alatalo, Lindström, & Mappes, 2001), and (b) because
Southern Corroboree Frogs had a patchy distribution dur-
ing their breeding season when they were abundant
(Hunter et al., 2009). We pressed models onto golf tees to
minimize the risk that they would be dislodged by forces
other than predators (wind, rain, etc.). Models were not
retrieved until after 96 hr in the field to avoid disturbing
predators in the area while the models were present. We
did not recover all the models that we deployed, as is the
expectation in field-based model experiments of this mag-
nitude (Table 1; Rößler et al., 2018). We excluded all
missing models from our analysis because it is impossible
to know the fate of the missing models, and because their
missing status is not reliable evidence of predation
(Rößler et al., 2018). Therefore, attack marks and subse-
quent statistical analyses were on recovered models only.
Following Low, Sam, McArthur, Posa, and Hochuli
(2014), we categorized the attacks on recovered models as
avian, mammalian, or unidentified. We attributed models
showing deep U- or V-shaped marks to birds, whereas
models exhibiting teeth impressions, such as incisor marks,
were attributed to mammals (McElroy, 2016). Models that
could not be confidently categorized by three independent
observers were excluded from analysis (N= 80), and statis-
tical analysis focused exclusively on avian attacks because
they are motivated by visual cues, and because other preda-
tors are excluded from reintroduction enclosures.
We used G-tests to examine differences in the propor-
tion of models recovered for each treatment. We used a
GLMM with a binomial distribution (logit link; Bates
et al., 2015) to statistically compare whether or not a
model was attacked (binary response variable;
attacked = 1, no attack = 0) between the first and second
deployments. This model included the fixed effects of
model treatment (categorical fixed effect: black, yellow,
or striped), deployment (categorical fixed effect: first or
second), and the interaction between these two variables.
It also included the random effect of location and row, to
control for dependencies in our data due to the specific
positions of deployment. We conducted post hoc compar-
isons between deployments and all treatment types using
the same method as detailed in our analysis of the detect-
ability study above (Lenth & Lenth, 2018).
3|RESULTS
3.1 |Model detectability
Out of a possible 1,020 observations, our observers
detected models 75 times (10 black, 3 striped, 62 yellow;
Figure 4). Yellow models were more likely to be detected
than black or striped models, and there was no difference
in detectability between black and striped models
(Table 2). As predicted by our GLMM, the mean proba-
bility of detection was 0.148 (SE = 0.027) for yellow
models, 0.022 (SE = 0.008) for black models, and 0.006
(SE = 0.004) for striped models.
3.2 |Model attacks
3.2.1 |Comparing attacks between
deployments
The proportion of models attacked by birds (of those
recovered) was higher in the first deployment (21.7%,
314/1445) than the second (9.4%; 211/2236). As a propor-
tion of recovered models for each treatment in the first
deployment, birds attacked 27.9% (123/440) of black,
17.6% (86/489) of striped, and 20.3% (105/516) of yellow
models (Figure 5). In the second deployment birds
attacked 12.2% of black (88/723), 9.9% of striped (75/759),
and 6.4% of yellow (48/754) recovered models (Figure 5).
FIGURE 3 Experimental
setup of each transect within
Kosciuszko National Park
(KNP), New South Wales
(NSW), Australia. Models were
placed 1 m apart separated into
24 per row, with 24 rows per
transect that were separated
by ~100 m
6of15 UMBERS ET AL.

TABLE 1 A summary of 13, haphazardly chosen, clay model studies completed since 2000 to provide rough guidelines on the number
of models and treatments typical for clay model design, and on which to base expectations of the percentage of models attacked. This is not
intended to be a complete summary of all clay model studies. It is presented with the aim that it can put our study (Row 1) in context, as
well as direct experimental design of future studies
Citation Species Treatments
Number of
models
deployed
Number of
recovered
models
Method for
dealing with
unrecovered
models
Number of
models
attacked
Percentage
of models
attacked
Present study Southern Corroboree
Frog
Pseudophryne
corrboree
3 4,608 3,681 Excluded from
analysis
525 14.3
McLean, Moussalli,
and Stuart-Fox
(2010)
Lake Eyre dragon
Ctenophorus
maculosus
4 2,800 2,400 Not reported 20 0.8
Richards-Zawacki,
Yeager, and Bart
(2013)
Strawberry poison
frog
Oophaga pumilio
4 1,600 <1,600 Excluded from
analysis
202 12.6
Comeault and
Noonan (2011)
Dyeing poison frog
Dendrobates
tinctorius
3 1,891 1874 Excluded from
analysis
49 2.6
Howe, Lövei, and
Nachman (2009)
Cotton bollworm
Helicoverpa armigera
1 1,802 Unclear Unclear Not reported 3.9
Stuart, Dappen, and
Losin (2012)
Strawberry poison
frog
Oophaga pumilio
4 2,400 2,335 Excluded from
analysis
108 5.0
Vignieri, Larson,
and Hoekstra
(2010)
Deer mice
Peromyscus sp.
4 250 238 Excluded from
analysis
28 8.5
Bittner (2003) Common garter
snake
Thammophis sirtalis
4 480 480 Not applicable 50 10.4
Noonan and
Comeault (2009)
Dyeing poison frog
Dendrobates
tinctorius
3 1,260 1,260 Not applicable 139 11.0
Stuart-Fox,
Moussalli,
Marshall, and
Owens (2003)
Tawny dragon and
red-barred dragon
Ctenophorus decressii
and C. vadnappa
4 2,200 2,200 Not applicable 113 5.0
Saporito, Zuercher,
Roberts, Gerow,
and Donnelly
(2007)
Strawberry poison
frog
Oophaga pumilia
4 800 776 Analyzed twice,
assuming attacked
and not attacked
99 12.4
Chouteau and
Angers (2011)
Mimic poison frog
Ranitomeya imitator
3 1,800 1,580 Excluded from
analysis
229 14.5
Amézquita, Castro,
Arias, González,
and Esquivel
(2013)
Harlequin poison
frog
Oophaga histrionica
4 800 679 Excluded from
analysis
150 22.0
Watson, Roelke,
Pasichnyk, and
Cox (2012)
Juvenile skinks with
blue tails
(multiple species)
4 180 Unclear Unclear Not reported 70.6
UMBERS ET AL.7of15

For all model treatments there was a significant reduc-
tion in probability of attack between the first and second
deployments (Table 3). As summarized from raw data, the
reduction in proportion of models attacked relative to
those recovered was 15.7% for black (Tukey HSD compari-
son: β= 1.308, SE = 0.190, z= 6.898, p
corr
< .001), 7.7%
for striped (β= 0.501, SE = 0.204, z= 2.449, p
corr
= .014),
and 13.9% for yellow models (β= 1.344, SE = 0.214,
z= 6.279, p
corr
< .001).
3.2.2 |Summary of attacks from the first
deployment
From the first deployment, 1,445 (62.7%) models were
recovered. The recovery rate of this deployment was
likely affected by an unexpected rainstorm that occurred
on the last day of our model deployment. However, the
proportion of models recovered did not significantly differ
among treatments (57.3% black, 67.2% yellow, and 63.6%
striped models; G
2
= 3.83, p= .15). Of the recovered
models, a total of 383 (26.5%) models were attacked, and
the majority of attacks (82%) were from birds (4% mam-
mals and 14% unknown). Bird attacks (N= 314, 21.7% of
recovered models) were split between 123 (39.2%) on
black, 105 (33.4%) on yellow, and 86 (27.4%) on striped
models (Figure 5).
Within the first deployment the mean probability of
attack, as predicted from our GLMM, was 0.220
0
20
40
60
Black Striped Yellow
Treatment
Number Seen
FIGURE 4 The number of models seen in each treatment by
humans during our detectability experiment
TABLE 2 (a) Outcome of the generalized linear mixed effect model examining differences in the probability of detection by a human
between model colors. Model estimates (β) of fixed effects presented are on the latent (logit link) scale with their corresponding SEs, variance
estimates (σ
2
) are supplied for residuals and random effects, and all significant values (p< .05) are presented in bold. (b) We also present
comparisons of detection probability between all model colors, and in this case, p-values (p
corr
) were corrected using Tukey's HSD
multiplicity adjustment
(a) Output from the GLMM
Variable names
Fixed effects βSE z p
Intercept (black) −2.786 0.430 −6.475 <.001
Treatment (striped) −1.303 0.667 −1.954 .051
Treatment (yellow) 2.053 0.360 5.697 <.001
Distance −0.327 0.094 −3.468 .001
Random effects σ
2
Observer 0.512
Residuals 1.000
(b) Multiple comparisons between model colors
Model colors βSE t p
corr
Black vs. yellow −2.053 0.360 −5.697 <.001
Striped vs. yellow −3.356 0.603 −5.561 <.001
Black vs. striped 1.303 0.667 1.954 .124
8of15 UMBERS ET AL.

(SE = 0.125) for black, 0.104 (SE = 0.068) for yellow, and
0.088 (SE = 0.059) for striped models. The probability of
bird attack was significantly higher for black models than
yellow (β= 0.887, SE = 0.181, z= 4.890, p
corr
< .001) and
striped models (β= 1.076, SE = 0.190, z= 5.667,
p
corr
< .001; Figure 5). There was no difference in the
probability of bird attack between yellow and striped
models (β=−0.188, SE = 0.186, z=−1.012, p
corr
= .569;
Figure 5).
3.2.3 |Summary of attacks from the
second deployment
Thirty-seven days later, we deployed a further 2,304
models. During this second deployment the weather was
mild, and we recovered 2,236 models (97%). The propor-
tion recovered did not significantly differ among colors
(G
2
= 0.52, p= .77); we recovered 94% of black, 98% of
yellow, and 99% of striped models. In total 239 (11%)
models were attacked, and the majority of attacks (88%)
were from birds (5% were from mammals and 7% were
unknown). Bird attacks (N= 211 or 9% of recovered
models) were on 88 (41.7%) black, 75 (35.5%) striped, and
48 (22.8%) yellow models.
Within the second deployment the mean probability
of attack, as predicted from our GLMM, was 0.071
(SE = 0.048) for black, 0.055 (SE = 0.038) for striped, and
0.029 (SE = 0.021) for yellow models. Probability of
attack was not different between striped and black
models (β= 0.269, SE = 0.182, z= 1.480, p
corr
= .301),
but was significantly higher for black (β= 0.923,
SE = 0.203, z= 4.551, p
corr
< .001) and striped
(β= 0.655, SE = 0.206, z= 3.181, p
corr
= .004) than yel-
low models (Figure 5).
4|DISCUSSION
We aimed to understand the predation risk facing
reintroduced Southern Corroboree Frogs and explore the
application of clay model deployment as a conservation
tool that exploits learned predator aversion to increase the
likelihood of survival in reintroduced prey species. We
0.0
0.1
0.2
0.3
Black Striped Yellow
Treatment
Proportion Attacked by Birds
0.00
0.25
0.50
0.75
1.00
Black Striped Yellow
Treatment
Probability of Bird Attack
0.0
0.1
0.2
0.3
Black Striped Yellow
Treatment
Proportion Attacked by Birds
0.00
0.25
0.50
0.75
1.00
Black Striped Yellow
Treatment
Probability of Bird Attack
FIGURE 5 The proportion of recovered models that were attacked by birds (left panels), and the predicted probability of bird attack
(right panels) for each model treatment from the first (top) and second deployments (bottom). The predicted probability of bird attack is
depicted with a split violin plot, dot plot, and a simplified boxplot showing the mean and 95% confidence intervals. Lines connecting the
model treatments with an asterisk above them indicate significant differences
UMBERS ET AL.9of15

found that Southern Corroboree Frog black-and-yellow
striped coloration does not make them conspicuous, but
instead makes them as difficult to detect as black cryptic
models (by humans). This suggests that from a distance at
least, corroboree frogs are camouflaged by their stripes.
We also found that although similar in detectability,
striped models were less likely to be attacked than black
models in the wild when avian predators first encountered
them. Consistent with other clay model studies, the char-
acteristic V- and U-shaped impressions on our models
indicated that birds were the most common predators
(Chouteau & Angers, 2011; Comeault & Noonan, 2011;
Hegna, Saporito, & Donnelly, 2012; Rößler et al., 2018).
Birds attacked about 18% of striped models in our first
deployment, and when we deployed the models a second
time, around 5 weeks later, about 10% of striped models
were attacked. Our interpretation of this result is that
corroboree frog coloration has some protective value
against avian predators, but that birds are still a signifi-
cant threat if 1 in 5 reintroduced individuals are vulnera-
ble to attack and that a reduction to a 1 in 10 chance of
attack is a worthwhile improvement. A similar significant
reduction in avian attack rate was seen in the other
model colors, specifically 16% fewer black and 14% fewer
yellow models were attacked in the second deployment.
The drop in attack rates between deployments is consis-
tent with aposematism theory, which posits that encoun-
ters with unprofitable prey—conspicuous or not—are
efficiently learned and remembered and subsequently,
similar prey are avoided in the future (Roper & Redston,
1987). Our results thus suggest that birds learned to avoid
unprofitable clay models in repeat encounters (Dell'aglio,
Stevens, & Jiggins, 2016). If birds generalize from models
to real frogs, it should be possible to condition birds to
avoid real frogs based on a previous unprofitable experi-
ence with clay models.
4.1 |The disparity between detectability
and attack rates for model types
The detectability of our frog models to humans did not
match their likelihood of being attacked by birds in the
first deployment. The first deployment in our study is
most likely to represent the predator population's natural
response to Southern Corroboree Frogs upon their
reintroduction (i.e., their behavior without any prior
interaction with our clay models). Black models were dif-
ficult for humans to detect, but, in the first deployment,
the most likely to be attacked by birds. Striped models
were also difficult for humans to detect, but had a lower
probability of bird attack than black models. On the other
hand, yellow models were highly detectable by humans,
but were less likely to be attacked than black models.
It is impossible to know whether birds detected but
ignored models, as opposed to not detecting them at all.
Yet, if we assume that humans are suitable proxies for
bird vision (given the lack of UV in the coloration of
Southern Corroboree Frogs), then we can generate a few
hypotheses for further testing: (a) the disparity between
low detectability and relatively higher attack rates on
black models may reflect bird preference for a similar-
sized frog species sympatric to Southern Corroboree
Frogs, the common eastern froglet (C. signifera); (b) the
high detectability of yellow models, but subsequent low
attack rate may suggests that yellow frogs were detected
TABLE 3 Outcome of the
generalized linear mixed effect model
examining differences between
deployments and model colors in the
probability of bird attack. Model
estimates (β) of fixed effects presented
are on the latent (logit link) scale with
their corresponding SEs, variance
estimates (σ
2
) are supplied for residuals
and random effects, and all significant
values (p< .05) are presented in bold.
Post hoc multiple comparisons between
model treatments across and between
deployments can be found in the
Results section
Variable names Model output
Fixed effects βSE z p
Intercept (black, 1) −1.263 0.727 −1.737 .082
Treatment (striped) −1.076 0.190 −5.667 <.001
Treatment (yellow) −0.887 0.181 −4.890 <.001
Deployment (2) −1.308 0.190 −6.898 <.001
Treatment (striped): deployment (2) 0.807 0.263 3.067 .002
Treatment (yellow): deployment (2) −0.036 0.271 −0.133 .894
Random effects σ
2
Row 1.007
Location 1.868
Residuals 1.000
10 of 15 UMBERS ET AL.

but avoided, which may shed some light on why some
frog species turn yellow in the breeding season
(i.e., Lesuer's frog, Ranoidea lesueuri; Bell & Zamudio,
2012); and (c) if birds detect striped models as frequently
as black models, that striped models are less likely to be
attacked after detection than black models.
4.2 |The protective mechanism of
Southern Corroboree Frog coloration
Striped and black models were similarly detectable to
humans, and both these color patterns were less detect-
able than yellow models. During the first deployment,
black models had a higher probability of bird attack than
both striped and yellow models. Our data invoke two
nonmutually exclusive hypotheses to explain the mecha-
nism by which corroboree frog coloration influences
predator behavior: (a) that the Southern Corroboree Frog
color pattern may hinder predator detection by disruptive
camouflage or (b) that birds may detect, but preferen-
tially avoid the striped pattern on first encounter because
innately they associate the coloration with unprofitability
(i.e., aposematism) (Lindström et al., 1999; Mappes et al.,
2005; Rojas, 2017). Future experiments should test
whether the stripes have a deterring function at close dis-
tance, but a concealing effect at long distance (Tullberg,
Merilaita, & Wiklund, 2005). Our detectability study sug-
gests that at a long distance, to a human viewer, South-
ern Corroboree Frog coloration is camouflaging. Yet, we
advise careful interpretation of our detection experiment
results, and stress that they be viewed independently
from the results of the field deployment. We present
them as indirect evidence toward understanding how
Southern Corroboree Frog coloration influences predator
behavior. To definitively test detectability of Southern
Corroboree Frog coloration, future studies should iden-
tify bird predators and train captive birds to indicate
detection in experiments with real corroboree frogs.
Given the critically endangered status of these frogs, this
approach would need to take place using animals in cap-
tive colonies.
4.3 |Could seasonal changes have
affected our results?
We cannot rule out that a time-in-season effect explains
the difference in attacks between deployments. Perhaps,
for example, predators avoid frogs later in the season
because insects provide more palatable alternative prey
(Mappes et al., 2014). However, this is unlikely to influ-
ence our results because insect prey is abundant from
November to April, and our entire study occurred in the
middle of this period. Also, we cannot be sure that the
same individual predators attacked models in both
deployments, though overlap is likely because many local
predator species have stable territories and small home
ranges (i.e., 2 km
2
in Australian Magpies, C. tibicen).
Finally, although unlikely, local avian predators may
have experience with Southern Corroboree Frog colora-
tion through traveling to areas where Southern Corrobo-
ree Frog (about 30 km away), or its sister species,
Northern Corroboree Frog, still persist (about 200 km
away). For example, Little Ravens travel great distances
(>50 km per day; Whisson, Weston, & Shannon, 2015).
Even if predators do have experience with corroboree
frogs through the above mechanisms, or others like social
learning (Thorogood et al., 2018), the reduction in attack
rates in the second deployment suggests model decoys
promote learned avoidance.
4.4 |Clay model deployment in species
reintroduction and recovery plans
An important part of the Southern Corroboree Frog
recovery plan is to consider the behavior of local preda-
tors and minimize the risk they pose during
reintroduction (Moseby et al., 2011). Including model
deployment as a predator aversion technique in the
reintroduction program may enhance the success of
Southern Corroboree Frogs reintroduction in the
Australian Alps. Habitats are constantly in flux and when
long-extirpated species are reintroduced they may
encounter changes in the behavior, like the loss of aver-
sive behaviors, or a seasonal change in demography of
the predator population, like a higher proportion of naïve
fledgling predators (Armstrong & Seddon, 2008; Mappes
et al., 2005, 2014; Thorogood et al., 2018). Our data sug-
gest that Southern Corroboree Frog coloration provides
some protection against current local avian predators,
but that birds still pose a risk worth mitigating. One such
mitigation technique could include strategically timed
deployment of clay models near reintroduction sites—we
suggest timing the deployment so that it would train
predators that are most likely to encounter real frogs, but
not so similar in time to the release of reintroduced frogs
as to attract predators to field enclosures (see below).
Additionally, deployment of models with particularly dis-
tasteful substances may be considered to expedite preda-
tor avoidance learning, although, our study seems to
suggest that unprofitable interactions with clay models
alone is enough to deter predators (Rößler et al., 2018).
More generally, we suggest that clay models could
also be used across the world in reintroductions of other
UMBERS ET AL.11 of 15

imperilled, potentially conspicuous prey species. There
are two obvious applications. First, clay model studies
can be used to understand how a reintroduced species'
coloration affects their predation rate in the wild. This is
important knowledge about the predation risk that pre-
cious individuals from breeding programs may face once
reintroduced. Second, predator conditioning via clay
model deployment could be used to reduce predation risk
from visual predators. Other bright-colored frogs, like the
Panamanian golden frog (Atelopus zeteki) and the red-
banded poison frog (Oophaga lehmanni), that are cur-
rently under-going ex situ breeding programs, may be
good candidates. We recommend a case-by-case approach
in model and deployment design (for review see Rößler
et al., 2018). Briefly, there are six main considerations:
1. Number and design of models—The number of models
should be large enough to ensure predators encounter
and attack a sufficient number. Most clay model
experiments receive attacks on between 5 and 30% of
recovered models (Table 1). Depending on the
research question, the number of treatments should
be as small as possible (commonly four; Table 1) to
ensure statistical power. Inclusion of a negative con-
trol should be considered—which would comprise all
the model materials in a nonvisually similar presenta-
tion to control for attacks driven by novelty or non-
visual senses. Consideration should be made as to the
addition of a distasteful compound to the models
(such as quinine), which may expedite any learning
but is a trade-off as an additional factor to account for
in the experimental design. The size, shape, and colors
used for making the models require close quantitative
scrutiny to ensure they match those of the real
animals.
2. Proximity to the threatened populations—In the
absence of direct evidence about the effect of models
on predator behavior, models should not initially be
deployed close to the threatened population in case
they attract predators to the area. However, under-
standing the natural history of possible predators is
important (i.e., home range size, seasonal movement
patterns, spatial ecology, etc.) because predators may
be highly localized and any learned response to the
clay could break down with distance (Comeault &
Noonan, 2011).
3. Deployment duration—Models should be deployed for
a period long enough to ensure a sufficient number of
attacks are recorded. Some studies check models each
day for attacks to determine when to retrieve models,
yet this may affect the presence of predators within
the study area. Models should therefore be deployed
long enough to be detected but not checked too often.
4. Deployment timing—Seasonal timing should be con-
sidered. One aspect to consider is that it would be ben-
eficial to minimize encounters with adverse weather
events. In the case of protecting species set to be
reintroduced, models should obviously be deployed
before reintroduction. More subtly, though, it is
important to consider the life cycle of the predator.
For example, fledglings may pose a big threat to spe-
cies every spring. Longitudinal clay model studies that
are repeated throughout a target species' active season
may be able to give insight into the diversity of preda-
tor species over time, however, as our data show, mul-
tiple deployments can also affect predator behavior.
Regardless, longitudinal clay model studies could
yield data that would be useful information for timing
of deployments to afford protection for species.
5. Human resources—The main costs of this approach
are in making and deploying the models. Clay model
studies often aim to identify attacking predators, so
models are made of soft clay. In this approach 3D
printing is often not appropriate, so models are often
made by pouring soft-set clay into molds and then
painting them by hand. This process can be laborious.
Placing the models in the field one-by-one and retriev-
ing them is also laborious but unavoidable.
6. Molecular techniques—Recently molecular techniques
have been applied to clay model studies to identify
predators by sampling saliva from the clay model,
extracting DNA, and using this to identify predator
species (Rößler et al. unpublished data). While the
addition of this approach would add time and cost, it
may also provide novel and critical data about the
predator species targeting prey species during
reintroductions.
5|CONCLUSION
Habitats are constantly in flux and long-extirpated spe-
cies may encounter changes in predators when
reintroduced (Armstrong & Seddon, 2008). Our data sug-
gest that corroboree frog coloration provides some protec-
tion against current local avian predators, but that birds
still pose a risk worth mitigating. Contrary to expecta-
tions for a black-and-yellow striped frog, our data suggest
that corroboree frog coloration makes them difficult to
detect. Perhaps they are camouflaged and toxic—or per-
haps they are camouflaged at a distance, but the yellow
and black coloration renders them aposematic when
viewed up close (Rojas, 2017). Such hypotheses are for
future work in sensory ecology. For applied conservation
research, our findings suggest that a strategically timed
and strategically placed deployment of clay models could
12 of 15 UMBERS ET AL.

be an effective predator mitigation technique. Deploy-
ment of models with particularly distasteful substances
may be considered to expedite predator avoidance learn-
ing. Application of this technique into reintroduction
programs might enhance the success of corroboree frog
reintroduction within the Australian Alps and could also
be applied to imperilled prey animals globally.
ACKNOWLEDGMENTS
We thank J. O'Hanlon, S. Knox, M. Duncan, S. Samuel,
M. Humphries, and F. Andrews for help with model con-
struction, G. Bourke, T. Kahlke, J. Ryeland, and
E. Drinkwater for assistance during fieldwork. Taronga
Zoo for access to specimens for photos and J. Van Dyke,
B. Rojas, and J. Mappes for manuscript reviews. We also
thank all anonymous reviewers for their helpful sugges-
tions on our earlier manuscript drafts. Data in KU's
GitHub Repository. Study approved by University of Wol-
longong Animal Ethics Committee (permit 14/08), and
NSW National Parks and Wildlife Service (License
SL101674).
CONFLICT OF INTEREST
The authors declare no conflict of interest.
AUTHOR CONTRIBUTIONS
K.D.L.U. and P.G.B. conceived the study, M.B.J.K., G.T-
D., and K.D.L.U. constructed models, M.B.J.K., G.T-D.,
and J.P.L. conducted the field work in Kosciuszko,
K.D.L.U. and J.L.R. conducted the field work in Sydney,
M.B.J.K. wrote the first draft, J.L.R. and
K.D.L.U. conducted the statistical analyses, and K.D.L.U.,
J.L.R., and P.G.B. honed the manuscript for publication
with input from all authors.
ORCID
Kate D. L. Umbers https://orcid.org/0000-0002-9375-
4527
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SUPPORTING INFORMATION
Additional supporting information may be found online
in the Supporting Information section at the end of this
article.
How to cite this article: Umbers KDL, Riley JL,
Kelly MBJ, Taylor-Dalton G, Lawrence JP,
Byrne PG. Educating the enemy: Harnessing
learned avoidance behavior in wild predators to
increase survival of reintroduced southern
corroboree frogs. Conservation Science and Practice.
2020;2:e139. https://doi.org/10.1111/csp2.139
UMBERS ET AL.15 of 15