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Multiple-model mimicry, whereby different morphs of an aposematic species each resemble another defended species sharing the costs of predator education, has been proposed as a mechanism allowing colour polymorphisms in aposematic species. Male wood tiger moths, Arctia plantaginis (Linnaeus, 1758), are chemically defended and polymorphic (yellow, white) for hindwing coloration. We selected four potentially aposematic moth species and studied whether Müllerian mimicry exists between them and A. plantaginis morphs. We tested the moths' relative palatability to natural predators with and without visual cues, their phenotypic similarity under a bird visual system, and whether trials with a potential moth model influence a predator's willingness to attack A. plantaginis. Our results show that (1) three of the four tested species were not sufficiently unpalatable and thus not potential models for A. plantaginis, and (2) birds confused the unpalatable yellow model Arichanna melanaria with yellow A. plantaginis, although their overall appearance is distinguishable. This indicates imperfect mimicry based on shared colour cues. Multiple-model mimicry is thus a potential contributor to the maintenance of multiple morphs, although no unpalatable model was found for the white morph. Our findings highlight the importance of accounting for both prey coloration and palatability, which in concert affect predator behaviour, the ultimate driver of mimicry evolution.
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© 2018 The Linnean Society of London, Biological Journal of the Linnean Society, 2018, XX, 1–8 1
Biological Journal of the Linnean Society, 2018, XX, 1–24. With 7 figures.
Can multiple-model mimicry explain warning signal
polymorphism in the wood tiger moth, Arctia plantaginis
(Lepidoptera: Erebidae)?
K. RÖNKÄ1*, J. MAPPES1, C. MICHALIS2, R. KIVIÖ1, J. SALOKANNAS1 and B. ROJAS1
1Centre of Excellence in Biological Interactions, Department of Biological and Environmental Science,
University of Jyväskylä, PO Box 35, FI-40014, Finland
2School of Biological Sciences, University of Bristol, Bristol BS8 1TQ, UK
Received 26 November 2017; revised 28 March 2018; accepted for publication 28 March 2018
Multiple-model mimicry, whereby different morphs of an aposematic species each resemble another defended
species sharing the costs of predator education, has been proposed as a mechanism allowing colour polymorphisms
in aposematic species. Male wood tiger moths, Arctia plantaginis (Linnaeus, 1758), are chemically defended and
polymorphic (yellow, white) for hindwing coloration. We selected four potentially aposematic moth species and
studied whether Müllerian mimicry exists between them and A. plantaginis morphs. We tested the moths’ relative
palatability to natural predators with and without visual cues, their phenotypic similarity under a bird visual
system, and whether trials with a potential moth model influence a predator’s willingness to attack A. plantaginis.
Our results show that (1) three of the four tested species were not sufficiently unpalatable and thus not potential
models for A. plantaginis, and (2) birds confused the unpalatable yellow model Arichanna melanaria with yellow
A. plantaginis, although their overall appearance is distinguishable. This indicates imperfect mimicry based on
shared colour cues. Multiple-model mimicry is thus a potential contributor to the maintenance of multiple morphs,
although no unpalatable model was found for the white morph. Our findings highlight the importance of accounting
for both prey coloration and palatability, which in concert affect predator behaviour, the ultimate driver of mimicry
evolution.
ADDITIONAL KEYWORDS: aposematism – Geometridae – imperfect mimicry – palatability – predator–prey
interactions – signal-detection theory.
INTRODUCTION
Local variation in warning signals is evolutionarily
puzzling because prey that have warning colours
are expected to be under positive frequency-
dependent selection by local predators, leading to
signal monomorphism (Müller, 1879; Fisher, 1958;
Ruxton, Sherratt & Speed, 2004). To avoid the costs
of unnecessary pursuit or toxic load, predators learn
to avoid unprofitable prey by associating it with
prey coloration. Learned avoidance is expected to be
generalized to other prey sharing a similar warning
signal. This allows predators to optimize their fitness
by attacking only profitable prey items in the prey
community, while prey individuals with a similar
appearance share the costs of predator education.
Hence, local predators provide strong selection for
qualities that make them associate warning signals
with prey defence, for example signal conspicuousness,
colour, pattern or uniformity.
Signal sharing can occur between species when
two or more defended species resemble each other in
a Müllerian mimicry ring (e.g. Müller, 1879; Benson,
1972; Kapan, 2001; Marek & Bond, 2009; Stuckert
et al., 2014). However, the system is prone to cheating.
Less defended intra- or interspecific individuals with
a similar warning signal can parasitize the defended
model species, obtaining the benefits of predator
avoidance without incurring the costs associated with
the defence (e.g. Bates, 1862; Kunte, 2009; Kraemer,
Serb & Adams, 2015; Jones et al., 2017; Katoh, Tatsuta
& Tsuji, 2017). Thus, mimetic systems between species
varying in their level of palatability can be thought
of as a continuum from equally defended Müllerian
*Corresponding author. E-mail: katja.ronka@helsinki.fi
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2 K. RÖNKÄ ET AL.
© 2018 The Linnean Society of London, Biological Journal of the Linnean Society, 2018, XX, 1–24
mimics benefiting each other to Batesian mimicry, in
which a palatable mimetic species gains protection
from a defended model, while the model suffers from
increased predation as the proportion of non-defended
prey increases (Huheey, 1976; Rowland et al., 2010).
Predators trade-off between the costs of attacking a
defended model and not attacking a palatable mimic
(Speed, 1999; Johnstone, 2002; Skelhorn & Rowe,
2007). The strength of selection for signal similarity
in a given predator–prey community thus depends
on the predator’s tendency to generalize and the
rates of discrimination error (Lindström, Alatalo &
Mappes, 1997; Mappes & Alatalo, 1997; MacDougall
& Dawkins, 1998; Ihalainen, Lindström & Mappes,
2007; Aronsson & Gamberale-Stille, 2012; Ihalainen
et al., 2012). This is, in turn, influenced by predators’
hungriness (i.e. motivation to attack; Sandre et al.,
2010), which is affected by prey availability (Kokko,
Mappes & Lindström, 2003; Lindström et al., 2004),
as well as by the relative palatability of the prey
(Ihalainen et al., 2007).
Although the concept of Müllerian mimicry was
proposed in 1879, and several theoretical as well as
experimental approaches have contributed to a better
understanding of its underpinnings, it remains of
debate how mimetic relationships affect selection on
warning coloration and how polymorphism among
defended co-mimics is maintained (Joron & Mallet,
1998; Speed, 1999; Rowland et al., 2007). Lepidoptera
have some of the best known examples of mimetic
systems (e.g. Bates, 1862; Müller, 1879; Benson, 1972;
Mallet & Barton, 1989; Kapan, 2001; Katoh et al.,
2017), but, in general, empirical approaches with real
prey and their relevant predators are scarce (Ruxton
et al., 2004). Moreover, surprisingly little is known
about the palatability of species, for example what
kind of chemical defences the species possess, and how
they affect different predators (Marsh & Rothschild,
1974; but see Arias et al., 2016a for a study where
inter-species palatability was addressed as a possible
explanation for polymorphism in a mimetic species).
Another factor hindering mimicry studies has been
the lack of an objective way of measuring colour and
pattern similarity. However, the development of image
analysis methods (e.g. Endler & Mielke, 2005; Endler,
2012; Le Poul et al., 2014; Kemp et al., 2015; Troscianko
& Stevens, 2015; Taylor, Reader & Gilbert, 2016; Van
Belleghem et al., 2018) and increasing knowledge of
predator visual systems (e.g. Vorobyev & Osorio, 1998;
Kelber, Vorobyev & Osorio, 2003; Renoult, Kelber &
Schaefer, 2017) are beginning to overcome this issue.
In addition to detailed knowledge of predator vision,
however, it is necessary to understand the cognitive
processes involved in prey recognition and predator
attack decisions, more specifically, how predators use
the information they gather from prey palatability
and associated cues (Skelhorn, Halpin & Rowe,
2016). This is because predator behaviour, whether
or not it sees the difference between co-mimics or
confuses them, and correspondingly attacks (or not)
a particular prey, is the ultimate selective force on
both the warning signal and the chemical defence(s)
variation. Local predator communities consist of both
inexperienced and experienced individuals (Mappes
et al., 2014), the latter of which may choose to consume
defended prey (Ihalainen et al., 2008b) according to
their physiological state, i.e. toxic burden (Johnstone,
2002; Barnett, Bateson & Rowe, 2007; Skelhorn &
Rowe, 2007). Studying the behaviour of relevant
natural predators is thus key in assessing selection on
aposematic species (see also Merilaita, 2016).
Although many previous studies have provided
insight into how a single aposematic prey species can
exhibit multiple morphs within a given population
(e.g. Ueno, Sato & Tsuchida, 1998; Nokelainen et al.,
2012, 2014; Hegna et al., 2013; Rojas, Devillechabrolle
& Endler, 2014), the relative importance of different
mechanisms remains poorly understood. A possible
explanation for this counterintuitive phenomenon
is multiple-model mimicry. Examples of multiple-
model mimicry are described for both Batesian
(Papilio dardanus: Nijhout, 2003; Papilio memnon:
Clarke, Sheppard & Thornton, 1968) and Müllerian
mimics (Heliconius numata: Brown & Benson, 1974;
Joron et al., 1999; Appalachian millipedes: Marek &
Bond, 2009; Ranitomeya imitator: Symula, Schulte &
Summers, 2001; but see Chouteau et al., 2011 for a
study that challenges the multiple-model hypothesis
in R. imitator).
The benefits of polymorphism are easily explained
for Batesian mimics, which gain most selective
advantage when they are rare compared to their
models. Mimicking several sympatric models instead
of one can thus sustain larger population sizes of the
Batesian mimic (Edmunds, 1974). The same could
apply to quasi-Batesian systems, where a defended
model is mimicked by a less-defended co-mimic (Speed,
1999; Rowland et al., 2010). Müllerian polymorphism,
however, is somewhat more complex: although each
morph can benefit from sharing the signal with
a defended model, frequency-dependent selection
should still favour local monomorphism. One well-
known example of multiple-model Müllerian mimicry
is the remarkable case of Heliconius numata, where
polymorphism is thought to be maintained via spatial
differences in local selection and dispersal (Joron et al.,
1999) and selection against intermediate phenotypes
(Arias et al., 2016b).
The wood tiger moth, Arctia plantaginis (formerly
Parasemia plantaginis Rönkä et al., 2016), is an
aposematic species with remarkable variation in
hindwing coloration across its Holarctic range.
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MULTIPLE-MODEL MIMICRY IN A. PLANTAGINIS 3
© 2018 The Linnean Society of London, Biological Journal of the Linnean Society, 2018, XX, 1–24
Males in some populations are polymorphic, with
co-occurring yellow and white morphs. Here, we
hypothesize that this local polymorphism could be
maintained because each morph gains protection from
a different defended species (i.e. a quasi-Batesian or
Müllerian co-mimic, referred to hereafter as a model).
For multiple-model mimicry to explain the maintenance
of local polymorphism, the putative models need to (1)
be sufficiently unpalatable to facilitate the avoidance
of the co-mimic (A. plantaginis) and (2) share their
warning colours with the corresponding morphs in the
eyes of would-be predators. Two black-and-yellow and
two black-and-white diurnal sympatric moths were
selected as potential models for the yellow and white
wood tiger moth morphs, respectively (Table 1). To test
whether mimetic relationships could exist between the
species, we carried out bioassays with relevant wild-
caught predators aiming to test (1) the relative degree
of palatability of each putatively mimetic pair in both
the presence and the absence of visual cues, and (2)
if experience with a putative model changes bird
reactions towards the putative mimic (yellow or white
A. plantaginis morph) and vice versa. In other words,
we tested whether there is potential for generalized
avoidance between unpalatable prey sharing a similar
warning colour. We complemented these bioassays
with detailed image analyses comparing both the
overall appearance and hindwing warning colour of
A. plantaginis and its putative co-mimics. The image
analyses were used to provide an objective measure
of similarity among species, and to determine whether
the birds could use hindwing colour as a cue for
unpalatability.
MATERIAL AND METHODS
Study SpecieS
Adult A. plantaginis (Erebidae: Arctiinae) are diurnal
(Rojas, Gordon & Mappes, 2015), and aposematic,
as they are chemically defended (Rojas et al., 2017)
and conspicuously coloured (Nokelainen et al., 2012).
Their chemical defence contains pyrazine compounds,
which are deterrent to avian predators (Rojas et al.,
2017) and synthesized de novo (Burdfield-Steel et al.,
2018). In Europe, the coloration of adult males consists
of a contrasted black-and-white forewing pattern
and either white or yellow hindwing warning colour
combined with variable degree of black patterning
(Hegna, Galarza & Mappes, 2015). Male hindwing
warning coloration is determined by one autosomal
locus with at least three alleles (J. Galarza et al., unpubl.
data), resulting in distinct white and yellow hindwing
morphs, whereas female hindwing colours vary
continuously from orange to red. Local polymorphism
is common across the Holarctic distribution range,
and in Finland both white and yellow males co-occur.
Morph frequencies in A. plantaginis are monitored
yearly using pheromone traps and netting. The peak
flight season is at the beginning of July, where males
fly in search for females. Based on species phenology,
co-occurrence with A. plantaginis and coloration, four
geometrid moth species were selected as potential
mimetic models (Table 1). The black-and-yellow
Arichanna melanaria and Pseudopanthera macularia
resemble the yellow morph, while the black-and-
white Lomaspilis marginata and Rheumaptera
hastata resemble the white morph of A. plantaginis.
Species occurrence was inferred from distribution,
habitat and timing of flight data from updated
databases (FinBIF), books (Silvonen, Top-Jensen &
Fibiger, 2014), and 30 transect counts in wood tiger
moth habitats during its flight season in 2014 (K.
Rönkä, unpubl. data). In addition to having a similar
appearance to A. plantaginis, Arichannamelanaria is
known to be capable of sequestering low quantities
of grayanotoxins, which are known to deter at least
lizards (Nishida, 1994). To our knowledge, none of the
adult putative model species in this study has ever
been directly tested for palatability.
Wild-caught and freeze-killed specimens of
Autographa gamma and Zygaena sp. were used for
positive and negative palatability controls, respectively,
while Tenebrio molitor larvae (hereafter referred to as
mealworms) were used to control for bird motivation
to attack and consume insect prey. The silver Y moth,
Autographa gamma, is common, polyphagous and
cryptically coloured, and thus is likely to be palatable
to most predators. Burnet moths, Zygaena spp., by
contrast, are known to possess hydrocyanic acid (Jones,
Parsons & Rothschild, 1962; Davis & Nahrstedt, 1982),
and to be unpalatable to birds (Turner, 1970, and
references therein).
Moth samples were collected by netting (netting
and light for Arichanna melanaria) from their natural
habitats (Table 1). To obtain enough samples for all the
experiments, field-collected L. marginata, R. hastata
and P. macularia were mated and F1 generation
was reared in a glasshouse in Central Finland, using
natural food plants, and overwintered as pupae.
Arctia plantaginis were obtained from a laboratory
stock originating and reinforced with field-collected
individuals from Finland. Only male A. plantaginis
were used in experiments. All the other species are
sexually monomorphic in coloration, and thus a random
selection of both sexes was used in experiments. As we
were unable to rear Arichanna melanaria in sufficient
numbers, all the samples of this species were collected
from the wild in Central Finland during their flight
season in August 2015. To reduce the effect of intensive
sampling on natural populations, only male Arichanna
melanaria were selectively collected and used in
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4 K. RÖNKÄ ET AL.
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Table 1. Selected moth species and comparative information on size, timing of flight, abundance and collection of samples. Photos taken by KR.
Key Species Wingspan
(mm)
Flight period
(day.month)
Abundance in Finland Food plant reared on Origin of samples
Apy = yellow morph
Apw = white morph
Putative mimics
Arctia plantaginis
(Linnaeus, 1758)
29–37 9.6.-20.7. locally common Taraxacum ssp.,
Plantago major
Laboratory stock
(with Finnish
origin)
Am
Putative model for
yellow morph
Arichanna melanaria
(Linnaeus, 1758)
28–41 6.7.-19.8. common, sometimes
outbreaks in Asia
Vaccinium uligino-
sum, Rhododendron
tomentosum
Central Finland
Pm
Putative model for
the yellow morph
Pseudopanthera macularia
(Linnaeus, 1758)
23–27 24.5.-4.7. EN in Finland, common
in Estonia
Lamium album
(natural food plant
Teucrium scordium)
Reared from indi-
viduals caught in
Pärnu, Estonia
Rh
Putative model for
the white morph
Rheumaptera hastata
(Linnaeus, 1758)
26–34 22.5.-7.7. common, outbreaks
in northern North
America
Betula, Salix Southern & Central
Finland, reared
Lm
Putative model for
the white morph
Lomaspilis marginata
(Linnaeus, 1758)
21–27 5.5.-8.9. common, with several
generations
Salix, Populus Southern & Central
Finland, reared
C+ Positive (palat-
able) control
Autographa gamma
(Linnaeus, 1758)
36–34 1st generation 30.5.-
28.7., 2nd gener-
ation 27.7.-20.10.
common migrant Central Finland
C- Negative (unpalat-
able) control
Zygaena sp. 30–39 1.7.-18.8. local, in Georgia common Georgia
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MULTIPLE-MODEL MIMICRY IN A. PLANTAGINIS 5
© 2018 The Linnean Society of London, Biological Journal of the Linnean Society, 2018, XX, 1–24
experiments. All samples were killed by freezing
after collection or eclosion, and stored at −20 °C for a
maximum of 18 months. Most samples were stored for
less than 6 months before feeding them to birds.
palatability experimentS without viSual cueS
A first step to address the question of whether a
species is a potential model for a mimic in a presumed
Müllerian complex is to test how palatable it is in
relation to its putative mimic. We thus tested the
relative palatability between potential co-mimics with
two feeding assays (Table 2), where moths were offered
to a relevant predator (great tit, Parus major) without
any visual cues. The proportion eaten was used as a
proxy for palatability. To transform the frozen moths
into a homogenous paste, we first dried them in a
freeze-dryer at −20 °C. The dried samples were stored
at room temperature for a maximum of 8 weeks before
the experiments. Three individuals of each species were
pooled in one Eppendorf tube to minimize the effect
of potential inter-individual variation in palatability,
leaving the left side fore- and hindwings of every
third individual aside for subsequent image analysis.
The tube contents were crushed into powder using a
TissueLyser II for 5 s (at 30 rounds per second) with a
5-mm steel ball in the tube. We weighed the resulting
powder to the nearest 0.01 mg and added water to
each sample in a ratio of 6:1 for the A. plantaginis,
Autographa gamma and Zygaena sp., and 9:1 for the
other moths. These amounts of water were used to
create a smooth paste of uniform consistency for all
samples. Once water was added, the paste was used
immediately or stored in a fridge (+3 °C) or freezer
(−20 °C) between bird assays, to prevent spoilage and
microbial growth.
In the first assay, we used dead T. molitor larvae
mixed with 397 µL/g of either water (positive control,
palatable) or a 10% quinine solution (negative control,
unpalatable). Mealworms were killed by freezing them
and subsequently crushed in a mortar. Mealworms
were not freeze-dried because their high body fat
content made the dried samples colour yellowish,
unlike the moth samples. Instead, we used non-dried
samples, whose natural brown colour was similar to
that of the moth samples. On average 40 mg (14–70 mg)
of each species/control was taken for the first trial. The
uneaten proportion was then reused in a subsequent
second trial, supplemented with fresh samples to gain
a starting weight between 14.7 and 61.7 mg.
Numbered cups (lids of 2-mLEppendorf tubes) and
small pieces of parafilm (to seal the cup) were weighed
to the nearest 0.0001 g, and a well-mixed paste of
each species and controls was added to the cups. Each
cup was then placed in a randomized position in an
eight-spot platform made of a Styrofoam bottom and a
plastic carpet with 10-mm holes that kept the sealed
cups in place during bird assays (Fig. 1). A parafilm
seal was used before the beginning of each trial to
avoid both water evaporation and the spread of any
potential odours of the different species before the bird
had the chance to taste them. Birds were pre-trained
to open the parafilm-sealed cups using an edible paste
made of shell-less sunflower seeds crushed with a
mortar and coloured brown (1 mL of yellow/red/blue
mixture of dr. Oetker food dyes added to 6.359 mg of
seeds). Every bird had to complete five pre-training
steps before starting the trial, to ensure they mastered
the technique to open the parafilm seals and to
motivate them to open all eight cups in search of
food during the experiment. In the first pre-training
step, the birds were given sunflower seeds from open
cups. Once the bird had consumed all seeds, they were
offered the pre-training paste in open cups. After the
birds had consumed the paste and emptied all cups,
they were given the next round with sealed cups, but
Figure 1. Schematic diagram of the platform and a cup made of an Eppendorf lid containing moth paste used in Assays
1 and 2 without visual cues. Each cup contained paste made of one moth species or the palatable (C+) or unpalatable (C-)
control positioned in a randomized order on the platform. See text for a description of the positive (C+) and negative (C-)
controls used in each assay.
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6 K. RÖNKÄ ET AL.
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with pre-made holes in the parafilm. Finally, the birds
were presented with two rounds of platforms with
sealed cups with no holes in them. The latter round
was given immediately before the experiment, and the
experiment was started 1 h after the bird had finished
eating the last pre-training round. The second assay
followed the same protocol, except that Autographa
gamma was used as the positive and Zygaena sp. as
the negative control, instead of mealworms (Table 2).
To ensure that we had enough moth and moth control
samples for 15 birds in the second experiment, the
sample weight was reduced to 20.5–29.6 mg (on
average 24.7 mg), and only one trial was run per bird.
In both assays, the opened cups were weighed again
immediately after the trial ended, and the proportion
of paste eaten was calculated as the difference in cup
weights before and after the trial, divided by the cup
weight before the trial. To ensure accurate measures
of the proportions eaten, we recorded cases where
the bird spilled cup contents out of the cup during
the trials to be taken into account in the analysis. In
the second experiment, we also recorded the order in
which the cups were opened, to account for potential
effects of bird saturation or learning during the trial.
Furthermore, we measured the time taken by the bird
from opening the cup until the end of the trial. This
was done to account for water evaporation, which was
assumed to reduce sample weight in an approximately
linear manner after opening the cup lid. Each trial
ended 2 min after the bird had opened the last cup to
provide time for the bird to finish eating all the cup
contents at will. If the trial continued for longer than
1 h, seed crumbs were added on top of all unopened
cups, to prevent bird starvation and to motivate the
bird to continue the trial.
To test the relative palatability of the potential
model species, we built generalized linear mixed
models (GLMs) with proportion eaten as the dependent
variable, modelled with a beta distribution and a logit
link function. Proportion eaten varies between 0 and
1, and is thus best fit with a beta distribution, which
allows for heteroskedasticity and asymmetry of the
dependent variable distribution. Proportions eaten
marked to be exactly 0 or 1 due to measurement
inaccuracy were modified to 0.001 and 0.999,
respectively, to match the model assumptions. The
models were fitted using the R package glmmADMB
(v.0.8.3.3; Fournier et al., 2012; Skaug et al., 2013) to
account for random structures in the experimental
setup. In the first assay with two trials (Assay 1) Bird
ID was added as a random factor and in the second
assay (Assay 2), which consisted of only one trial, we
added cup position on the tray as a random variable to
account for any spatial bias in bird feeding behaviour
caused by the experimental setup. Prey species
(including the palatable and unpalatable controls)
was used as the explanatory variable and whether
cup contents were spilled on the floor was included as
a fixed factor, to account for cases where some of the
reduced weight was left potentially uneaten, in both
models (Assay 1 and 2). In addition, opening order
and the time that each cup was open within the trial
were used as covariates in the analysis of the second
experiment (Assay 2). Planned contrasts were used to
test for all relevant differences in palatability of the
putative models against A. plantaginis morphs and
the controls, and between A. plantaginis morphs, to
avoid multiple testing. This was done using a design
matrix, where the average amount eaten was set as
the intercept and contrasts were set according to the
study questions (see Fig. 2, Table 2).
image analySiS
While coloration is commonly measured using
spectrometry, analysing images makes it possible to
consider the whole animal and its patterns instead of
point measures only (Stevens et al., 2007). Here image
analysis was used to assess the discriminability of
the wood tiger moth morphs (yellow and white) from
their putative models (yellow: Arichanna melanaria,
P. macularia; white: R. hastata, L. marginata) based
on (1) their overall appearance (colour and pattern
on both wings) and (b) hindwing colour only modelled
with an avian visual system (Table 2). A total of 94 dry
moth samples, together with a scale and a 93% white
and 7% grey calibration standard, were photographed
with a Samsung NX1000 camera customized to full
spectrum length with a Nikon EL-80mm lens. Images
were taken in raw format with a fixed aperture
setting, using filters for UV (Baader U 300–400 nm)
and visible light (Baader UV/IR cut filter 400–700 nm)
imaging. The grey standards were essential for the
calibration to ensure an accurate representation of the
moths’ natural colours. Calibration was done using the
Image Calibration and Analysis Toolbox (Troscianko &
Stevens, 2015) in ImageJ (Schneider, Rasband &
Eliceiri, 2012), where raw pictures of each moth were
aligned manually, normalized and assembled into a
multispectral image stack, converted to 32 bits per
channel and saved as .tif for further analysis.
The area of interest containing the moth in these
calibrated and normalized pictures (including also
information from the UV-channels when saved as 32-bit
per channel) was then specified using a custom-made
Matlab program. The RGB values of each pixel within
the area of interest (either both of the left side wings or
the hindwing only) were then transformed to relative
photon catches of the blue tit’s (Cyanistes caeruleus)
cones under a D65 standard daylight illuminant (Hart,
2001), to describe the moth wings as seen by their
avian predators (similar to Stevens & Cuthill, 2006).
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Table 2. Synthesis of all experiments, study questions, statistical tests, sample sizes, main results and conclusions
Experiment Experimental procedure Study questions Measured variables and
tested comparisons
Statistical test
method
Sample size Main results and
conclusions
Assay 1
palatability with
no visual cues
Figure 1
2 trials with mealworm
controls
(1) Are the putative
models Am, Pm,
Rh & Lm less
palatable than the
putative mimics
Apy/Apw?
(2) Are the
putative models
less palatable
than good/
bad mealworm
controls?
(3) Is Apw less
palatable than
Apy?
Figure 2, Figure 4A,
Table 2A
Proportions eaten in two
trials of
(a) putative models vs. Ap
morph
(b) putative models vs.
controls
(c) white vs. yellow Ap
GLMM with a beta
distribution and a
logit link function
Figure 2, Assay 1
[number of moth
paste samples
not spilled (used
in Figure 4A)/
number of all
moth samples
(used in
analysis])
(1) No significant
difference Am vs. Apy
and Pm vs. Apy; Rh and
Lm are eaten more than
Apw
(2) Putative models are
eaten less than both
controls
(3) No significant
difference between Apy
and Apw
Pm and Am are
putative Müllerian
models; Rh and Lm are
putative quasi-
Batesian mimics
Assay 2
palatability with
no visual cues
Figure 1
1 trial with Autographa
gamma and Zygaena
sp. controls
(1) and (3) same as
above
(2) Are the putative
models less pal-
atable than a pu-
tatively palatable
moth (Autographa
gamma) or an un-
palatable moth
(Zygaena sp.)?
Figure 2, Figure 4B,
Table 2B
Proportions eaten of
(a) putative models vs. Ap
morph
(b) putative models vs.
controls
(c) white vs. yellow Ap
GLMM with a beta
distribution and a
logit link function
Figure 2, Assay
2 [number of
of moth paste
samples not
spilled (used in
Figure 4B)/
number of of
all moth
samples (used in
analysis])
(1) No significant differ-
ence Am vs. Apy and Pm
vs. Apy; Rh and Lm are
eaten more than Apw
(2) Putative models
are eaten less than
Autographa gamma but
more than Zygaena
(3) No significant differ-
ence. between Apy and
Apw
Pm and Am are puta-
tive Müllerian models;
Rh and Lm are putative
quasi-Batesian mimics
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Table 2. Continued
Experiment Experimental procedure Study questions Measured variables and
tested comparisons
Statistical test
method
Sample size Main results and
conclusions
Assay 3
palatability with
visual cues:
proportions
eaten
Figure 3
Data from all trials (see
Table S4 for a version
with data from first
trials only)
(1) Are the putative
models Am, Pm,
Rh & Lm less
palatable than the
putative mimics
Apy/Apw?
(2) Does the pres-
ence of visual
cues change moth
acceptability to
birds?
(3) Is Apw less palat-
able than Apy?
Figure 2, Figure 4C,
Table 3C
Proportions eaten of
(a) putative models vs. Ap
morph
(b) white vs. yellow Ap
GLMM with a beta
distribution and a
logit link function
Figure 2, Assay 3
Great tits:
Pm = 20
Am = 20
Apy = 39
Apw = 18
Rh = 10
Lm = 8
Proportion eaten:
(1) Pm eaten more than
Apy, other differences
non-significant
(2) All moths eaten more
than without visual cues
Once attacked, most
species eaten at similar
levels (different from
without visual cues,
indicating that birds can
handle their prey)
Assay 3
palatability
with visual
cues: beak
cleaning
Figure 3
Data from all trials
(1) Do the putative
models Am, Pm,
Rh & Lm induce
more disgust be-
haviour than
the putative
mimics Apy/Apw?
(2) Is there a dif-
ference in bird
disgust behaviour
between Apw and
Apy?
Figure 5, Table 4
Amount of beak clean-
ing of
(a) putative
models vs. Ap morph
(b) white vs. yellow Ap
GLMM with a
negative binomial
distribution and a
logit link function
Figure 2, Assay 3
Great tits:
Pm = 20
Am = 20
Apy = 39
Apw = 18
Rh = 10
Lm = 8
Beak cleaning (BC):
(1) Less BC to Pm than
Apy, no diff. Am vs. Apy,
less BC to Rh and Lm
than Apw
Pm, Rh and Lm seem
to be less defended than
Ap
(2) Less BC to Apy than
Apw
difference between
morph defences
Assay 3
palatability
with visual
cues: learning
in Supporting
Information
Figure 3
4 trials with species
X as a ‘model’
(last trial not used)
Palatability in se-
quential
presentations –
are there signs
of increased
or decreased
avoidance?
Table S1, Figure S1
The effects of
(a) moth species,
(b) bird species and
(c) their interaction on
changes in survival (cu-
mulative risk of being
attacked during a trial)
during four sequential
presentations
Cox proportional
hazards model
for survival
Figure S1
Blue tits:
Apy = 11
Am = 11
Great tits:
Apy = 20
Am = 10
The proportional risk of
being attacked by blue
and great tits changes
differently depending
on moth species great
tits showed increasing
avoidance towards Am
but blue tits did not
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Table 2. Continued
Experiment Experimental procedure Study questions Measured variables and
tested comparisons
Statistical test
method
Sample size Main results and
conclusions
Image analysis
visual cues only
pictures of all species
colour and pattern
value extraction using
blue tit vision model
model to assess
discriminability
(1) How easy it is for
the predators to
tell apart the pu-
tative models and
Apy/
Apw?
(2) Could they be
using hindwing
colour only as a
common cue?
Modelled
discriminability of a pu-
tative model vs. a puta-
tively mimetic
Ap morph and the
other Ap morph
based on
(a) overall appearance
(colour and texture)
(b) hindwing colour
(Figure 6)
Logistic regression
model AUC
(a measure from
signal detection
theory)
Apy vs.
Am = 14
Pm = 12
Rh = 9
Lm = 16
Apw vs.
Am = 14
Pm = 12
Rh = 9
Lm = 17
(1) All species distinguish-
able based on overall
appearance
(2) Am vs. Apy and Rh vs.
Apw are less easy to
discriminate based on
hindwing colour
hindwing colour could
be used as a common
cue
Assay 3
mimicry
Figure 3
1st trial of species
X as a ‘model’ vs.
5th trial of species
X as a ‘mimic’ (from an-
other group of birds)
(1) Does experience
with the
putative model in-
crease
hesitation
towards the
putative mimic?
(2) Does experience
with the putative
mimic decrease
hesitation
towards the
putative model?
Figure 7
Attack latency without re-
cent experience
(1st trial) with a puta-
tive model vs. after re-
cent experience with a
putative model (5th
trial)
(a) towards a putative
mimic (Apy)
(b) towards a putative
model (Am) with both
bird species
unpaired two-sample
Wilcoxon test
Blue tits:
Apy first = 11
Apy last = 10
Am first = 11
Am last = 11
Great tits:
Apy first = 20
Apy last = 9
Am first = 10
Am last = 10
(1) Great tits show a non-
significant tendency to
hesitate more towards
Apy after experience
with Am, but blue tits
do not
(2) Experience with Apy
decreased hesitation
towards Am, although
the effect is only signifi-
cant in great tits the
compared species affect
each other’s survival,
suggesting that birds
confuse the putatively
mimetic moth species
with each other
Relevant figures and tables to each experiment are referred to in the table. The arrows are used to indicate conclusions made based on the main results. Species names are abbreviated: Ap = Arctia
plantaginis, Apy = yellow morph, Apw = white morph are used for the putative mimics, and Am = Arichanna melanaria, Pm = Pseudopanthera macularia, Rh = Rheumaptera hastata and
Lm = Lomaspilis marginata for the putative models.
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For the extraction of wing pattern values, 8000 pixels
were extracted from each area of interest and those
pixels were convolved with log-Gabor (Gabor, 1946)
filters of six orientations (0 to 150° in 30° increments)
and four spatial frequencies (the pattern analysis
is similar to those of Xiao & Cuthill, 2016; Michalis
et al., 2017). Log-Gabor filters can quantify a pattern
by detecting changes in luminance at specified spatial
scales and orientations.
Using the extracted values, we compared the
putative models (Arichanna melanaria, P. macularia,
R. hastata, L. marginata) against each of the
A. plantaginis morphs, first based on pattern and
colour of both wings (left fore- and hindwing), and
then based on hindwing colour only (i.e. the warning
signal). To achieve this we used Signal Detection
Theory measures, which were calculated based on
logistic regression analyses. Comparisons were done
via a logistic regression model, which evaluated how
easy it is to determine if a random pixel is part of
species A or species B in terms of colour and pattern
using the R package lme4 (v.1.1.13; Bates et al., 2015).
To avoid overfitting, we used a method called ‘leave-
one-out cross-validation’ (Lantz, 2013). This method fits
(or ‘trains’) the model created by the logistic regression
analysis on all of the individuals of the two species to
be compared, except one individual of species A and
one individual of species B. Next, we tested (validated)
this model on those individuals of species A and B that
were left out. In each comparison the individuals of
one of the putative models were compared with the
individuals of one of the A. plantaginis morphs. This
process was repeated so that each individual of the two
species was left out once (Lantz, 2013).
To determine how easily two species are discriminated
from each other, the widely used statistical methods
based on null hypothesis testing (statistical
significance) cannot be used. The question is how
different the two species are from each other rather
than whether the two species are different. Thus, we
employed several measures used in Signal Detection
Theory to determine how well or badly classification
works for each species (Wickens, 2002; the analysis
is similar to that of Michalis, 2017). These measures
were as follows: ‘sensitivity’, which is the proportion
of individuals of species A correctly classified;
‘specificity’, which is the proportion of individuals of
species B correctly classified; ‘precision’, which is the
proportion of pixels classified as species A that were
actually individuals of species A; ‘prevalence’, which
is the proportion of all the pixels of species A (0.5 in
our case as the same number of individuals from each
species was used); the ‘Area Under the Curve (AUC)’,
which is the probability that a randomly selected
individual of species A can be differentiated from a
randomly selected individual of species B); and, finally,
the ‘Receiver Operating Characteristic’ (ROC) curve,
a plot of sensitivity against specificity (Robin et al.,
2011). The AUC values range from 0.5 (performance
is no better than a random allocation of individuals as
species A or B) to 1 (all individuals of species A can be
perfectly discriminated from those of species B), and
were interpreted in accordance with a standard scale
where values of 0.9–1 imply excellent discrimination,
0.8–0.9 imply good discrimination, 0.7–0.8 imply fair
discrimination, 0.6–0.7 imply poor discrimination
and 0.5–0.6 imply that the putative co-mimics are
indistinguishable from each other, i.e. the model is no
better than chance (Lantz, 2013).
experiment with viSual cueS
Visual cues can be associated with prey unpalatability
in subsequent encounters with individuals of either
the same species or a different species with similar
appearance. Based on this, we ran a third assay, this
time with freeze-killed moths, to test bird responses to
taste and visual cues combined (Table 2). To measure
the consistency of bird behaviour, and determine
whether they would learn to associate the moth’s
appearance with its taste, we offered four individuals of
the potential model species in four subsequent trials to
each bird (see Supporting Information for methods and
results concerning changes in bird behaviour during
the four trials). To further test if recent experience
with a potential model would affect a bird’s reactions
towards another species, the four trials were followed
by a fifth trial with the potential mimic (Fig. 3). As the
Japanese populations of Arichanna melanaria were
known to possess an intermediate level of defence
(Nishida, 1994), we wanted to test its palatability in
relation to yellow A. plantaginis in more detail, using
two different relevant predators, great and blue tits.
Tests for differences between bird species are reported
in the Supporting Information. The other species
combinations were offered to great tits only, as in the
assays without visual cues.
Birds were pre-trained to fetch food from a Petri dish
attached to a green cardboard platform, to provide a
controlled green background for all moths. Each bird was
given three sunflower seeds on the Petri dish, and once
it had consumed the seeds, it was starved for 1 h. The
bird was then offered a small live mealworm and, if it
attacked the mealworm within 2 min, it was considered
ready to begin the experiment. Pieces of freshly killed
mealworm (one piece ~40 mg, one-third the weight of a
final instar larva) were given before, after and between
the moth trials to control for bird motivation to forage
on insect prey, and rule out satiation where the bird
refused to attack the moth. If the bird did not attack the
mealworm within 2 min, it was given a 10-min break
and tested again. If the bird did not attack a moth and
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the subsequent mealworm, the moth trial was dismissed
and the moth was offered again after the 10-min break.
However, if the bird did not attack the moth but did
attack the mealworm, the experiment was continued to
the next trial. Mealworm trials were continued for 3 min
from when the bird first saw the prey.
Frozen moths were thawed in airtight boxes lined
with moist paper at +3 °C to keep them fresh and easy
to manipulate. Before the experiment, the flight muscles
of each thawed moth were broken with tweezers to
enable manipulating their posture and the moth was
then placed on a Petri dish in a natural resting position,
with wing pattern and colours of the dorsal side visible.
Moths were presented to birds for 5 min (starting from
when the bird first saw the prey) in each trial. This
was done to allow the birds plenty of time to decide
whether to attack the moth, and to show potential
disgust behaviours (such as beak cleaning) after tasting
the moth. In each trial, we recorded whether the bird
attacked the moth (an attack was a peck or grabbing
the moth from the Petri dish), the latency to attack,
the proportion of the moth eaten at the end of the trial
(%) and the number of times the bird cleaned its beak
(a known sign of disgust; Evans & Waldbauer, 1982;
Rowland et al., 2015) within 1 min of the attack.
To test for palatability in the assay with visual cues
(Assay 3), we used data from all trials in which each
bird attacked and thus tasted the moth (see Supporting
Information for another approach using data from
first encounters only). Similar to the assays without
visual cues, the proportion of the attacked moths eaten
was used as the dependent variable, modelled with a
beta distribution and logit link function using the R
package glmmADMB (v 0.8.3.3). Values of 0 and 1
were again modified to 0.001 and 0.999, respectively,
to match model assumptions. Moth species was used
as the explanatory variable and Bird ID as a random
factor to account for repeated measures in the four
subsequent trials. Furthermore, the frequency with
which birds cleaned their beak during 1 min after
attack (number of beak wipes) was included as the
response variable modelled with a negative binomial
distribution and a logit link function in a GLM using
the R package lme4 (v.1.1.13), where prey species
was included as the explanatory variable. Planned
contrasts were again used to compare the palatability
of each putative model and its mimic (Fig. 2A–D), and
between the A. plantaginis morphs (Fig. 2G).
Finally, we tested whether the birds’ behaviour
towards the A. plantaginis morphs was affected by
recent experience with a potential model species (here
only Arichanna melanaria compared with the yellow
morph, see results below). This was done by comparing
attack latencies of birds that received A. plantaginis
in the first trial to the attack latencies of birds that
received A. plantaginis after having four trials with
Figure 2. Planned contrasts used in statistical analyses to compare bird responses between (A) Pseudopanthera macularia
and yellow Arctia plantaginis, (B) Arichanna melanaria and yellow A. plantaginis, (C) Rheumaptera hastata and white
A. plantaginis, (D) Lomaspilis marginata and white A. plantaginis, (E) putative models and the unpalatable control, (F)
putative models and the palatable control, and (G) A. plantaginis morphs. The numbers given in each column under the
moth species represent the number of samples not spilled on the floor/all samples tested in Assay 1 (first row), the number
of samples not spilled on the floor/all samples tested in Assay 2 (second row) and the number of moths attacked during a
trial/number of moths tested during Assay 3 (third row). All samples were used in analysing the proportions eaten in Assays
1 and 2, whereas in Assay 3 only the samples attacked and thus tasted were included in palatability analyses (proportions
eaten, beak cleaning). See Table 2 for a comprehensive presentation of sample sizes in each analysis.
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the potential model Arichanna melanaria with an
unpaired two-sample Wilcoxon test (Table 2). To
further test whether experience with A. plantaginis
would affect bird reactions towards the putative
co-mimic Arichanna melanaria, we compared attack
latencies of birds that received Arichanna melanaria
in the first trial to the attack latencies of birds that
received Arichanna melanaria after having four trials
with A. plantaginis (Fig. 3) with unpaired two-sample
Wilcoxon tests. All analyses were done in Rstudio
(RStudio, 2015) with R v.3.3.3 (R CoreTeam, 2013).
animal welfare
All the assays were carried out in custom-built plywood
aviaries equipped with a perch, fresh water available ad
libitum and lit with a daylight lamp (Exo Terra Repti Glo
10.0 UVB). Great tits were observed through a one-way
plexiglass wall in front of a 50 × 50 × × 70 cm cage whereas
the blue tits, which are more sensitive to the observer’s
presence, were observed through a small mesh-covered
window at the side of a 50 × 45 × 65 cm cage. The cages
for both species were placed in a dark room to avoid any
disturbance caused by the observer. All experiments were
filmed to record the observed behaviours in more detail.
Birds were wild-caught at Konnevesi research station
using peanut-filled feeding traps, and at Jyväskylä using
traps and mist-netting at winter-feeding sites. Each bird
was weighed upon capture and kept singly in a plywood
cage with food and water available ad libitum and
12:12-h light/dark cycle. After the experiment each bird
was sexed, weighed, ringed and released at the original
capture site. Permits for the capture and use of birds in
experiments were granted by the Central Finland Centre
for Economic Development, Transport and Environment
and licensed from the National Animal Experiment Board
(ESAVI/9114/04.10.07/2014) and the Central Finland
Regional Environment Centre (VARELY/294/2015). All
procedures complied with the Association for the Study
of Animal Behavious’s Guidelines for the treatment
of animals in behavioural research and teaching. The
experiments were conducted at Konnevesi research
station in Central Finland in February–March 2016,
October–November 2016 and February–March 2017.
RESULTS
palatability with and without viSual cueS
All yellow and white putative models were found to
be less palatable than the positive controls (mealworm
and Autographa gamma), but more palatable than
Figure 3. Examples of sequences of trials in Assay 3 with visual cues: to a bird that received Arichanna melanaria as
a putative model and yellow Arctia plantaginis as a mimic (above) and to a bird that received yellow A. plantaginis as a
putative model and Arichanna melanaria as a mimic (below). Data from the first and fifth trials (in colour) were used to
compare attack latencies with and without experience with a putative model (Fig. 7).
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MULTIPLE-MODEL MIMICRY IN A. PLANTAGINIS 13
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Zygaena sp. when offered without visual cues (Table 3,
Fig. 4A, B). When provided with visual cues birds ate
higher proportions of the attacked moths (Fig. 4C).
The proportions eaten of the yellow putative models
did not differ significantly from the proportions eaten
of the yellow A. plantaginis without visual cues, except
for P. macularia, which were eaten significantly more
by great tits in the assay with visual cues (Table 3C,
Fig. 4C). The yellow A. plantaginis also elicited
significantly more beak cleaning behaviour than
P. macularia (Table 4, Fig. 5).
Without visual cues, L. marginata was eaten
significantly more and R. hastata marginally
significantly more than white A. plantaginis in the
first assay (Table 3A), and R. hastata was eaten
significantly more and L. marginata marginally
significantly more than white A. plantaginis in
the second assay (Table 3B), indicating that both
species were relatively more palatable than their
putative mimic. Correspondingly, with visual cues,
white A. plantaginis elicited significantly more beak
cleaning than its putative mimics (Table 4, Fig. 5).
Table 3. GLMM estimates for palatability in three assays: (A) with mealworm controls, (B) with moth controls and (C)
with visual cues
(A) Assay 1 with mealworm controls
Random effects Variance SD
Bird ID 0.3699 0.6082
Fixed effects Estimate SE Z-value P-value
(Intercept): [mean proportion eaten] −0.918 0.155 −5.93 <0.001*
P. macularia vs. yellow A. plantaginis 0.315 0.241 1.31 0.1915
Arichanna melanaria vs. yellow A. plantaginis 0.395 0.240 1.64 0.1001
R. hastata vs. white A. plantaginis 0.427 0.242 1.77 0.0775
L. marginata vs. white A. plantaginis 0.613 0.240 2.55 0.0108*
C- vs. putative models 0.353 0.194 1.82 0.0684
C+ vs. putative models 1.522 0.193 7.88 < 0.001*
yellow vs. white A. plantaginis −0.017 0.242 −0.07 0.9426
spilled on floor 0.462 0.160 2.88 0.0039*
(B) Assay 2 with moth controls
Random effects Variance SD
Bird ID 0.627 0.792
Cup position 0.000000455 0.00067
Fixed effects Estimate SE Z-value P-value
(Intercept): [mean proportion eaten] −0.405 0.343 −1.18 0.23745
P. macularia vs. yellow A. plantaginis 0.423 0.340 1.24 0.21315
Arichanna melanaria vs. yellow A. plantaginis 0.327 0.342 0.96 0.33875
R. hastata vs. white A. plantaginis 0.903 0.357 2.53 0.01153*
L. marginata vs. white A. plantaginis 0.651 0.361 1.80 0.07144
Zygaena vs. putative models −1.08 0.293 −3.69 0.00022*
Autographa gamma vs. putative models 0.673 0.293 2.30 0.02164*
yellow vs. white A. plantaginis 0.333 0.344 0.97 0.33309
time open <0.001 <0.001 0.88 0.37941
eating order −0.162 0.046 −3.51 0.00044*
spilled on floor 0.801 0.284 2.82 0.00480*
(C) Assay 3 with visual cues
Random effects Variance SD
Bird ID 0.851 0.923
Fixed effects Estimate SE Z-value P-value
(Intercept): [mean proportion eaten] 0.597 0.161 3.70 < 0.001*
P. macularia vs. yellow A. plantaginis 0.665 0.275 2.41 0.0158*
Arichanna melanaria vs. yellow A. plantaginis −0.146 0.297 −0.49 0.622
R. hastata vs. white A. plantaginis −0.203 0.419 −0.48 0.628
L. marginata vs. white A. plantaginis 0.287 0.446 0.64 0.520
yellow vs. white A. plantaginis 0.326 0.364 0.89 0.371
Statistical significance of the planned contrasts at P < 0.05 is marked with an asterisk (*). The planned contrasts are shown in Figure 3 for Assays 1
and 2. In Assay 3 no controls were used, and thus contrasts were only made between putative models and their mimics and between A. plantaginis
morphs.
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Despite apparent differences in proportions eaten of the
putative white model species and white A. plantaginis
morphs with visual cues (Fig. 4C), there was no
significant difference in proportions eaten of R. hastata
and the white A. plantaginis (Table 3C), perhaps due
to relatively small sample sizes and thus low power
of the test (Table 2, Fig. 3). Great tits, however, ate all
R. hastata offered with visual cues after very short
attack latencies (Supporting Information, Figs S1, S2).
White A. plantaginis were eaten significantly less
when tasted for the first time (Table S3) and elicited
significantly more beak cleaning (Table 4) than
the yellow A. plantaginis, although no significant
differences between morphs were found in the
Figure 4. Proportions of the potentially aposematic moth species eaten by great tits in the absence of visual cues (A)
compared to mealworm controls (Assay 1) and (B) compared to moth controls (Assay 2). (C) The proportions of moths eaten
when visual cues were presented (Assay 3). Only samples not spilled outside of the cups and those birds that did attack the
moths offered are considered (see Fig. 3 for sample sizes). The statistical significance of each planned contrast between the
moth species is given in Table 3. The box plots represent the middle 50% of the original data, upper (lower) limit is the first
(third) quartile and thick line the median. Whiskers extend up to 1.5 times the interquartile range from top (bottom) of the
box to the furthest data point within the distance. ‘Outlier’ data points beyond the whiskers are illustrated as open circles.
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MULTIPLE-MODEL MIMICRY IN A. PLANTAGINIS 15
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proportions eaten without visual cues or taking into
account all trials with visual cues (Table 3). Changes
in bird responses during the four subsequent trials
with visual cues are examined in more detail in the
Supporting Information.
diScriminability of the putative modelS from
the wood tiger moth morphS
The putative models are easily distinguished from
A. plantaginis when considering both colour and
pattern of the whole moth (AUC values for all
comparisons > 0.93). However, when considering
only the hindwing warning colour, the putatively
mimetic pairs Arichanna melanaria (Am) – yellow
A. plantaginis (Apy) and R. hastata (Rh)– white
A. plantaginis (Apw) become more difficult to
discriminate (Am-Apy: AUC = 0.79, Rh-Apw:
AUC = 0.67; Fig. 6), whereas L. marginata (Lm) and
P. macularia (Pm) are easily distinguished from both
A. plantaginis morphs based on hindwing colour too
(all comparisons AUC = 1; Fig. 6).
bird reSponSeS towardS the moSt likely model
after experience with the other
As all putative models except Arichanna melanaria
were found to be more palatable than A. plantaginis,
Table 4. GLM estimates of the amounts of beak cleaning for the planned comparisons between putative models and
A. plantaginis morphs in Assay 3; the amounts of beak cleaning are shown in Figure 5
Fixed effects Estimate SE Z-value P-value
(Intercept): [mean amount of BC] 1.037 0.129 8.045 < 0.001*
P. macularia vs. yellow A. plantaginis −0.956 0.211 −4.534 < 0.001*
Arichanna melanaria vs. yellow A. plantaginis −0.303 0.215 −1.407 0.1596
R. hastata vs. white A. plantaginis −1.429 0.306 −4.667 < 0.001*
L. marginata vs. white A. plantaginis −1.509 0.319 −4.725 < 0.001*
yellow vs. white A. plantaginis −0.538 0.263 −2.047 0.0406*
Statistical significance of the planned contrasts at P < 0.05 is marked with an asterisk (*).
Figure 5. Beak cleaning induced by different moth species over 1 min, starting from when the bird (great tit) first pecked
or grabbed the prey in its beak in Assay 3. The statistical significance of planned contrasts between the putative models
and Arctia plantaginis morphs for the amount of beak cleaning at the P < 0.05 level is marked with an asterisk (*) and
model estimates given in Table 4. The box plots represent the middle 50% of the original data, upper (lower) limit is the first
(third) quartile and the thick line the median. Whiskers extend up to 1.5 times the interquartile range from top (bottom) of
the box to the furthest data point within the distance. ‘Outlier’ data points beyond the whiskers are illustrated as open circles.
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16 K. RÖNKÄ ET AL.
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and L. marginata and P. macularia were found to be
easily distinguished from their putative co-mimics
based on the image analysis, they are unlikely to act
as Müllerian models for the wood tiger moth morphs.
We therefore tested changes in bird responses towards
Arichanna melanaria and the yellow wood tiger moth
morph only.
There was no significant change in the birds’ attack
latency towards the yellow A. plantaginis with or
without recent experience with the putative model
Arichanna melanaria by blue or great tits, although the
latter did on average hesitate longer before attacking
the yellow A. plantaginis after having experience with
Arichanna melanaria (unpaired two-sample Wilcoxon
Figure 6. Discrimination of putative models from both Arctia plantaginis morphs (Apy and Apw) based on hindwing
colour according to bird visual system. The putative models are (A) Arichanna melanaria (Am), (B) Pseudopanthera
macularia (Pm), (C) Rheumaptera hastata (Rh) and (D) Lomaspilis marginata (Lm). Birds can discriminate P. macularia
and L. marginata from both A. plantaginis morphs, but the discrimination is more difficult between Arichanna melanaria
and the yellow A. plantaginis and between R. hastata and the white A. plantaginis.
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MULTIPLE-MODEL MIMICRY IN A. PLANTAGINIS 17
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tests, W = 76, P = 0.145 for blue tits, and W = 54.5,
P = 0.097 for great tits; Fig. 7A, B). Experience with
yellow A. plantaginis, however, significantly decreased
the great tits’ attack latencies towards Arichanna
melanaria (W = 80, P = 0.026; Fig. 7D), and the
trend was similar but not significant in the blue tits
(W = 78.5, P = 0.245; Fig. 7C).
DISCUSSION
The existence and maintenance of warning colour
polymorphisms has raised interest among evolutionary
biologists for decades because of their paradoxical
nature. Here, we studied whether multiple-model
mimicry could contribute to the maintenance of a
Figure 7. Attack latencies of (A) blue and (B) great tits towards the yellow Arctia plantaginis before and after experience
with Arichanna melanaria (Am), and attack latencies of (C) blue and (D) great tits towards Arichanna melanaria after
experience with yellow A. plantaginis (Apy). Statistically significant differences at P < 0.05 are marked with an asterisk
(Wilcoxon test). The box plots represent the middle 50% of the original data, upper (lower) limit is the first (third) quartile and
the thick line the median. Whiskers extend up to 1.5 times the interquartile range from top (bottom) of the box to the
furthest data point within the distance. ‘Outlier’ data points beyond the whiskers are illustrated as open circles. Sample size
is illustrated with orange dots on top of the box plots using R package beeswarm (v.0.2.3; Eklund, 2016).
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18 K. RÖNKÄ ET AL.
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warning signal polymorphism in the aposematic
moth A. plantaginis. Our results provide partial
support for this hypothesis, as Arichanna melanaria
was found to be a potential Müllerian model for the
yellow A. plantaginis, whereas R. hastata was a quasi-
Batesian mimic rather than a Müllerian model for
the white A. plantaginis. However, it is possible that
a Müllerian model for the white morph exists among
the species not considered in this study or that even
less defended co-mimics benefit the white morph
under some circumstances (see, for example, Rowland
et al., 2007, 2010). Based on the relative palatability
of the moths with and without visual cues, Arichanna
melanaria is as (un)palatable to the birds as the yellow
A. plantaginis. Although the image analysis with avian
vision model indicates that birds are able to distinguish
the species based on the moths’ overall appearance, the
model suggests that the hindwing colours of Arichanna
melanaria and the yellow A. plantaginis, and
R. hastata and the white A. plantaginis are relatively
similar. Knowing that birds pay more attention to
coloration than to pattern (Exnerová et al., 2006; Ham
et al., 2006; Aronsson & Gamberale-Stille, 2012; Rönkä
et al., 2018), and that moth hindwing coloration indeed
is an important signal for birds (e.g. Nokelainen et al.,
2102, 2014), we can safely assume that signal sharing
between these species is possible. All other putative
co-mimics tested here were found to be visually distinct
and/or more palatable than the wood tiger moths, and
could therefore not be Müllerian models for them. We
discuss the implications of these findings below.
palatable or unpalatable: it iS all relative
Studies on mimicry have predominantly focused
on the appearance of the mimetic complex, i.e. their
shared visual signal (e.g. Benson, 1972; Mallet &
Barton, 1989; Yeager et al., 2012). However, chemical
defences are also prone to variation (Nishida, 1994;
Speed et al., 2012), both within and between species,
adding another important dimension to mimetic
relationships (Skelhorn & Rowe, 2006; Ihalainen
et al., 2007; Stuckert et al., 2014; Arias et al., 2016a).
Of all the species tested in this study, Autographa
gamma was the most palatable, with birds eating
on average about half of each sample of this species
presented. In contrast, all the species tested as models/
co-mimics exhibited a certain degree of unpalatability,
although not to the extent of Zygaena sp., a species
in a group well known for their chemical defences
containing cyanide compounds (Davis & Nahrstedt,
1982). These results suggest that there is potential for
mimetic relationships between A. plantaginis and the
candidate mimics considered here, and that there is
no such thing as a fully palatable or fully unpalatable
prey species (Brower et al., 1968; Speed, 1999).
Moth toxicity can vary in relation to sex, diet and
drying of the specimen (Marsh & Rothschild, 1974).
Here, we tested only male moths of Arichanna
melanaria, which may bias the results towards higher
palatability (Marsh & Rothschild, 1974). All specimens
were either wild-caught or reared on natural food
plants, except for P. macularia, which was reared
on Lamium album, potentially affecting its relative
palatability. We are not aware of how freezing or
freeze-drying affects the palatability of these moths,
but our observations of tit responses towards living
A. plantaginis and P. macularia are largely similar to
those observed towards the freeze-killed individuals (K.
Rönkä, pers. observ.). However, it is important to note
that the differences reported by Marsh & Rothschild
(1974) are based on injections of moth extracts into
mice, which are likely to confound reactions to the
chemical defences with those to foreign insect protein,
present especially in non-dried samples (Ley & Watt,
1989). Thus, injections trigger different responses than
ingestion, which is the way in which predators come
into contact with a prey animal’s chemical defences in
the wild. In fact, it is known that predators can learn
about the degree of toxicity of different prey based on
prey unpalatability (Skelhorn & Rowe, 2010).
taSte and viSual cueS combined
Interestingly, in the third assay, in which birds were
offered real moths, the proportion eaten of the attacked
moths was considerably higher than when the same
moth species were offered as a paste in the absence of
visual cues. This could mean that the visual cues were
essential for prey recognition (e.g. Veselý et al., 2013).
Additionally, when moths were offered whole, birds
could handle them and selectively consume only the
most nutritious, palatable parts, leaving parts such as
the wings and the prothoracic glands containing the
defensive fluid of A. plantaginis uneaten. By contrast,
when mixed in the paste birds would need to consume
all moth parts including defensive compounds, which
may also have been stronger, as they were pooled from
three individuals. Moreover, encountering several
unpalatable prey in a row may have reduced the birds’
motivation to forage out of the cups in the assays
without visual cues, which is reflected in the significant
negative effect of eating order on the proportion eaten
in Assay 2 (Table 3B). In the first two assays, only one
of the eight samples (the positive control) was known
to be palatable. In contrast, the birds’ motivation to
attack and consume insect prey was ensured in the
third assay by offering them pieces of palatable freshly
killed mealworms between every trial.
Previous studies have demonstrated that prey
palatability can influence predator learning of a
particular warning signal, with signals associated
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MULTIPLE-MODEL MIMICRY IN A. PLANTAGINIS 19
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with higher unpalatability being easier to learn and
more memorable (Duncan & Sheppard, 1965; Skelhorn
& Rowe, 2006; Rowland et al., 2007). Our third assay
shows that birds do not increase their avoidance
towards the yellow morph of A. plantaginis over time,
as opposed to Arichanna melanaria, which is attacked
less by great tits as trials proceed (Fig. S1). In fact, the
attack risk towards Arichanna melanaria was overall
lower than towards A. plantaginis. The latency to
attack A. plantaginis by great tits after being exposed
to Arichanna melanaria showed a non-significant
increase compared to when the birds were presented
A. plantaginis first (Fig. 7B). However, the experience
with yellow A. plantaginis reduced the attack latency
towards Arichanna melanaria (Fig. 7C, D), indicating
that birds generalized their response towards
A. plantaginis to Arichanna melanaria based on
their similar hindwing colour. The reduction in attack
latency may have been caused by birds becoming more
experienced in handling yellow A. plantaginis during
the four trials, leaving unpalatable parts uneaten
(see Supporting Information). Altogether, our findings
suggest that Arichanna melanaria could indeed be a
Müllerian model for yellow A. plantaginis.
One aspect to be cautious about with regard to this
possible mimetic relationship is that A. plantaginis
usually starts its flight season earlier than Arichanna
melanaria. However, their flight seasons largely
overlap and, if birds can remember their experiences
over the winter, the yellow morph of A. plantaginis
can still benefit from signal sharing with Arichanna
melanaria. In addition, predators in the wild are likely
to make their decision to attack in a few seconds.
Thus, live A. plantaginis may be better protected
in the eyes of natural predators in the wild than in
the lab, rendering the relationship between yellow
A. plantaginis and Arichanna melanaria beneficial
for both species, i.e. truly Müllerian. This, however,
remains to be explicitly tested.
Live wood tiger moths are capable of surviving a
bird attack (Rönkä et al., unpubl. data). Thus, moth
palatability might not directly translate to differences
in survival, and the different morphs may be relying
on different lines of defence. Nokelainen et al. (2012)
found that blue tits hesitated significantly longer before
attacking live yellow versus white A. plantaginis. Here,
we found no significant difference in the first trial
hesitation times by great tits, although most of the longer
hesitation times were towards the yellow morph. Black-
and-yellow is a common warning colour combination,
and might thus induce wariness in both inexperienced
and experienced predators (Lindström, Alatalo &
Mappes, 1999; Exnerová et al., 2006). However, after
attacking, the great tits found the white A. plantaginis to
be less palatable than the yellow ones, as per the higher
frequency of beak cleaning (Fig. 5), lower proportions
eaten (Table S3, Fig. S2) and a decreasing probability of
attacks in the third assay compared to the yellow morph
(Table S1). We thus hypothesize that the yellow morph
relies on not being attacked and hence benefits from
signal sharing with other similarly coloured aposematic
prey, whereas the white morph relies more heavily on
taste-rejection by birds once attacked.
Although we found a potential Müllerian model
for the yellow morph only, we cannot exclude the
possibility that the white morph benefits from mimicry
too. According to the image analysis, birds have trouble
distinguishing between the more palatable black-and-
white R. hastata and the white A. plantaginis morph
based on hindwing colour. The colours and patterns of
the moths blur when on the move, which further reduces
the need for perfection in pattern similarity (Edmunds,
2000). If birds generalize between the two species, this
might increase the chances of the white A. plantaginis
being taste-rejected. This is because variation in prey
chemical defences can be aversive to avian predators
(Barnett, Bateson & Rowe, 2014) and, furthermore,
because variation in co-mimic defences could enforce
the surprise effect of the A. plantaginis defence: they
release their aversive defensive fluid when grabbed
by the bird in its beak, potentially causing the bird to
release the prey relatively unharmed.
predator StrategieS
In the present study, we report signs of difference in the
response of blue and great tits to the same type of prey,
which have also been addressed in previous studies
(Exnerová et al., 2003, 2006; Turini, Veselý & Fuchs,
2016). These differences are expressed, for example,
in the way in which prey are handled: the great tits
decreased their attacks towards Arichanna melanaria,
whereas the blue tits did not (Fig. S1). However, the blue
tits did decrease the amounts they ate of the attacked
Arichanna melanaria during the four trials, suggesting
that they were using taste-rejection (Skelhorn & Rowe,
2006; Halpin & Rowe, 2010, 2016), whereas the more
cautious behaviour of great tits, which are known to
discriminate prey both before and during handling
(Exnerová et al., 2003, 2006), matches better a ‘go-slow’
strategy (Guilford, 1994). This is in agreement with
previous research showing how the composition
of predator communities can have an effect on the
success of one morph over the other (Nokelainen et al.,
2014). Although beyond the scope of the present study,
we highlight these potential differences in predator
behaviour as a promising research avenue.
imperfect mimicry and generalized avoidance
Inaccurate mimicry can arise when predators
generalize widely among signals (Rowe, Lindström
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20 K. RÖNKÄ ET AL.
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& Lyytinen, 2004; Ihalainen et al., 2012; Mappes
et al., 2014) or use one cue and discard the rest
(Bain et al., 2007; Chittka & Osorio, 2007; Kikuchi
& Pfennig, 2010, 2013; Kikuchi et al., 2016). Here,
we found support for the latter: (1) according to our
image analysis, the birds’ visual system is capable
of discerning between Arichanna melanaria and
yellow A. plantaginis, and between R. hastata and
the white A. plantaginis, but the hindwing colours of
the two species-pairs are not easily distinguishable
for the birds, and could thus be used as a cue that is
generalized between them; and (2) the experience
with yellow A. plantaginis changed great tits’
reaction towards Arichanna melanaria, indicating
that the birds used the hindwing warning colour
as their primary cue for moth palatability instead
of wing pattern, size or shape. Indeed, previous
experimental evidence has demonstrated that
warning colour might be of foremost importance
in recognizing aposematic prey (Morrell & Turner,
1970; Terhune, 1977; Exnerová et al., 2006; Ham
et al., 2006; Aronsson & Gamberale-Stille, 2012;
Cibulková, Veselý & Fuchs, 2014; Rönkä et al. ,
2018). For example, the area of warning colour on
the wings has been shown to be a more important
cue for predators than prey body size (Remmel &
Tammaru, 2011; Hegna et al., 2013), and colour
to be more important than pattern (Aronsson &
Gamberale-Stille, 2008; Finkbeiner, Briscoe &
Reed, 2014).
Overall, our results imply a complex interplay
between warning signals and chemical defences
influencing predator attacks on prey that look alike
(see also Ihalainen et al., 2008a), reinforcing the idea
that both taste and visual appearance are important
in predator avoidance learning (Lindström et al.,
2006). We suggest that imperfect mimics can benefit
from their coexistence (because birds generalize
between similar colours). However, concluding that
multiple-model mimicry explains warning signal
polymorphism in A. plantaginis would require one
more step of inquiry, namely testing how predation
pressure towards A. plantaginis morphs is affected
by the frequency of models and mimics of the
yellow and white morphs in the field, in natural
communities of predators and prey. Furthermore,
experiments on mimicry are customarily done
using dead or stationary prey, ignoring the fact
that birds may use flying behaviour as a cue for
unpalatability (Chai & Srygley, 1990), and that the
resemblance of moving prey does not need to be as
accurate as between non-moving prey (Edmunds,
2000). Our results highlight the importance of
taking the predator’s perspective into account in the
evolution of mimicry. Visual resemblance alone, even
if investigated using objective image analyses and
vision models, is not sufficient to prove a mimetic
relationship, let alone mutualism. Indeed, predator
behaviour – in particular, which cues predators pay
attention to and whether they use this information of
prey characteristics in decision-making – ultimately
determines whether two focal species will benefit
each other.
ACKNOWLEDGEMENTS
We are grateful to all the people working on this project:
Kari Kulmala caught and reared moths with us from
Central Finland; Helinä Nisu took care of the birds
and pre-trained them for the palatability experiment
and caught birds from feeders; Heikki Helle helped
with bird catching; and Johannes Braunisch, Chiara de
Pasqual and Tuuli Salmi helped with mimicry trials and
watching the video-recorded behaviours. We are grate-
ful to Janne Valkonen, Sebastiano de Bona and Andrés
López-Sepulcre for statistical advice; Ossi Nokelainen
for borrowing his customized camera and introducing
ImageJ to us; Innes Cuthill who wrote the original sig-
nal detection analysis program; and to Emily Burdfield-
Steel for helpful discussion and language checking
that improved the manuscript. Brice Noonan, Mathieu
Joron and Chris Jiggins gave their thoughtful com-
ments on an earlier version of this paper as part of KR’s
PhD thesis. We also thank three anonymous reviewers
for their dedication and valuable feedback. Funding for
this study was provided by the Centre of Excellence in
Biological Interactions (Academy of Finland, project no.
284666 to JM).
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SUPPORTING INFORMATION
Additional Supporting Information may be found in the online version of this article at the publisher’s web-site.
Table S1. Cox survival regression estimates for Arichanna melanaria and yellow A. plantaginis [Apy] in the four
trials with blue and great tits (C. caeruleus and P. major, respectively). Hazard ratio is calculated as the risk of
event (attack) for groups in the numerator (given in parentheses) as compared to the risk of event (attack) for
groups in the denominator.
Table S2. Cox survival regression estimates for R. hastata and white A. plantaginis in the four trials with great
tits. Hazard ratio is calculated as the risk of event (attack) for R. hastata as compared to the risk of event (attack)
for A. plantaginis.
Table S3. Cox survival regression estimates for white and yellow A. plantaginis (Apy) in the four trials with great
tits. Hazard ratio is calculated as the risk of event (attack) for white A. plantaginis as compared to the risk of
event (attack) for yellow A. plantaginis.
Table S4. Proportions eaten in Assay 3 considering only the first presentations with each species (i.e. in the first
trial or the fifth trial).
Figure S1. Cox regression survival model estimates for moths attacked by blue (A, B) and great tits (C–F) in the
four trials (line colours darken towards the later trials 1–4) where yellow A. plantaginis (A, C), Arichanna mela-
naria (B, D), white A. plantaginis (E) or R. hastata (F) was offered as a potential model; n refers to the number of
birds tested in each case.
Figure S2. Proportions eaten in the four subsequent trials in Assay 3 of the moths that were attacked: (A) of yel-
low A. plantaginis and (B) of Arichanna melanaria by blue tits compared to (C) of yellow A. plantaginis and (D)
Arichanna melanaria by great tits, and (E) white A. plantaginis and (F) R. hastata by great tits.
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... Second, both yellow and white N. lecontei larvae have melanin-based black spots across their body, which predators could use as an additional signal of unprofitability together with the bright pigmentation (but see Aronsson and Gamberale-Stille 2008). This similarity in one aspect of the aposematic pattern could have decreased initial costs of rarity for a white larval form, thereby facilitating the shift from yellow to white pigmentation via generalization (Balogh et al. 2010;Lawrence et al. 2019; but see Rönkä et al. 2018b). Third, and perhaps most importantly, the costs of being a low frequency color morph could be mitigated by gregariousness in chemically defended prey. ...
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... We used the Wood tiger moth (Arctia plantaginis, Erebidae: Arctiinae) as our model prey. This species has distinctive wing color morphs that its bird predators can detect (Henze et al. 2018), it produces defensive chemicals eliciting predator avoidance, which justifies its status as an aposematic organism (Nokelainen et al. 2012;Hegna et al. 2013;Burdfield-Steel et al. 2018;Rönkä et al. 2018a). We focused on males, which are polymorphic regarding their hind-wing coloration: their hind wings may be yellow (chroma-rich) or white (luminance-rich). ...
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Despite decades of study, mimicry continues to inspire and challenge evolutionary biologists. This essay aims to assess recent conceptual frameworks for the study of mimicry and to examine the links between mimicry and related phenomena. Mimicry is defined here as similarity in appearance and/or behavior between a mimic and a model that provides a selective advantage to the mimic because it affects the behavior of a receiver causing it to misidentify the mimic, and that evolved (or is maintained by selection) because of those effects. Mimics copy cues or signals that are already in use as part of a stable communication system, but offer misleading information to receivers. Mimicry overlaps, both conceptually and evolutionarily, with camouflage and perceptual exploitation but the overlap is only partial, which may create some confusion. Certain types of camouflage (e.g. masquerade) conform to the definition of mimicry, while others (e.g. background matching) are not considered mimicry because they prevent detection rather than recognition of the camouflaged animal. Mimicry, on the other hand, works by exploiting peculiarities of the receiver at higher stages of sensory processing involving recognition and classification of stimuli. Perceptual exploitation models of trait evolution are also closely related to mimicry, and sensory traps in particular may act as a precursor for true mimicry to evolve. The common thread through these diverse phenomena is deception of a receiver by a mimic. Thus receiver deception (i.e. perceptual error) emerges as a key characteristic of mimicry shared with some types of camouflage and perceptual exploitation.
... Our results from females align well with previous work on the male defensive fluids in this species, showing that the fluids are clearly distasteful to birds (Nokelainen et al. 2012, Rojas et al. 2017, Rönkä et al. 2018. Wood tiger moths can survive attacks by birds such as blue tits (K. ...
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