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EVOLUTION OF MIMICRY AND APOSEMATISM EXPLAINED: SALIENT TRAITS AND PREDATOR PSYCHOLOGY

Baharan Kazemi

Evolution of Mimicry and Aposematism Explained: Salient Traits and Predator Psychology

Baharan Kazemi ©Baharan Kazemi, Stockholm University 2017

ISBN print 978-91-7797-037-8 ISBN PDF 978-91-7797-038-5

Printed in Sweden by Universitetsservice US-AB, Stockholm 2017 Distributor: Department of Zoology, Stockholm University “We are just an advanced breed of monkeys on a minor planet of a very average star. But we can understand the Universe. That makes us something very special.”

Stephen Hawking

“The more we know the immutable laws of nature, the more in- credible miracles become for us.”

Charles Darwin

“Man selects only for his own good. Nature only for that of the being which she tends.”

Charles Darwin

“It seems to me that the natural world is the greatest source of excitement; the greatest source of visual beauty; the greatest source of intellectual interest. It is the greatest source of so much in life that makes life worth living.”

David Attenborough

Till min sol, Enya Linnea

Contents

List of papers ...... 7

Introduction Imperfect mimicry ...... 9 Evolution of mimicry ...... 15 Evolution of aposematism ...... 16 Predator psychology ...... 17 Aims of the thesis ...... 21

Methods Predators ...... 22 Experimental setup ...... 22 Pre-training ...... 24 Experimental procedures ...... 24

Results & Discussion Initial step of mimicry evolution ...... 29 Variation in the degree of mimic-model similarity ...... 33 Persistence of imperfect mimicry ...... 37 Evolution of conspicuous warning signals ...... 39 Summary ...... 43

References ...... 44

Svensk sammanfattning ...... 53

Acknowledgements ...... 56

5

6

List of papers

I Kazemi, B., Gamberale-Stille, G., Tullberg, B. S., Leimar, O. (2014). Stimulus salience as an explanation for imperfect mimicry. Curr. Biol. 24:965-969.

II Kazemi, B., Gamberale-Stille, G., Leimar, O. (2015). Multi-trait mimicry and the relative salience of individual traits. Proc. R. Soc. B 282: 20152127.

III Kazemi, B., Gamberale-Stille, G., Wåtz, T., Wiklund, C., Leimar, O. (2017). Learning of salient prey traits explains Batesian mimicry evolution. Accepted for publication in Evolution.

IV Gamberale-Stille, G., Kazemi, B., Balogh, A., Leimar, O. Biased generalization of salient traits drives the evolution of warning signals. Manuscript under review.

Reprints were made with permission from the journal publishers.

Candidate contributions to thesis articles*

I II III IV

Conceived the study Minor Substantial Significant Minor

Designed the study Significant Substantial Substantial Significant

Collected the data Substantial Substantial Substantial Substantial

Analyzed the data Substantial Substantial Substantial Minor

Manuscript preparation Substantial Substantial Substantial Significant

* Contribution Explanation Minor: contributed in some way, but contribution was limited. Significant: provided a significant contribution to the work. Substantial: took the lead role and performed the majority of the work.

7

8

Introduction

Imperfect Mimicry

Naturalists of the mid 1800s explored the forests of the southern hemisphere and in 1858 Charles Darwin (spurred by A. R. Wallace) presented the theory of natural selection. Shortly after, H. W. Bates (1862) introduced the concept of mimicry, stating that some animal species elude predatory attacks by mimicking the appearance of co- existing noxious prey, who signal their unprofitability through for example conspicuous color patterns (Poulton 1887, 1890). Batesian mimicry (named after him) refers specifically to cases where an un- palatable model species is mimicked by harmless and edible species (Poulton 1890; Wickler 1968; Ruxton et al 2004). In general, this type of relationship benefits only the mimetic species and has an adverse effect on predator avoidance when too many edible mimics are at- tacked (Edmunds 1974; Turner 1987). In 1879, F. Müller explained another type of mimicry that had puzzled Bates among others – Mül- lerian mimicry, where the mimics also have some degree of protec- tion. This relationship is in general considered to benefit all involved parties, i.e. being mutualistic, in the way that two or more species can share the loss of individuals to predators that are learning to dis- criminate between prey (Müller 1879; Turner 1987; Sherratt 2008). Mimicry rings can involve several aposematic species that converge to a common appearance, and due to the mutual benefit, they can be considered as co-mimics rather than models and mimics (Mallet & Gilbert 1995; Rowland et al 2007). There are also many examples of mimicry rings involving both Batesian and Müllerian mimics/co- mimics (Franks & Noble 2004). However, the divide between Batesi- an and Müllerian mimicry is not so clear-cut. In some cases it is more complicated to define a species as being the one or the other, due to for example varying distastefulness of the involved species, where a less distasteful Müllerian mimic may cause a diluting effect on the predator aversion (Turner 1984; Speed 1993, 99; Balogh et al 2008).

9 It can also vary with how differently predators perceive and evaluate the varying distastefulness of the prey (Lindström et al 2004; Skel- horn and Rowe 2010). It has been suggested that there may be a spectrum between Batesian and Müllerian mimicry (Turner 1984; Speed 1993, 1999; Balogh et al. 2008). There are other forms of less common mimicry as well, but I will not go further into the different types of mimicry per se but focus on the matter that is relevant for all types – the occurrence of imperfect mimicry.

Mimicry is a remarkable example of evolutionary adaptation through natural selection and has received much attention (Poulton 1913; Wallace 1867, Holling 1965; Wickler 1968, Edmunds 1974, Sheppard 1975, Endler 1981; Turner 1987, Mallet & Joron 1999; Ruxton et al 2004; Gilbert 2005; Kikuchi & Pfennig 2013). In contrast, the occur- rence of imperfect mimicry did not elicit much attention (Poulton 1913; Goldschmidt 1945) until the past few decades (Sheppard 1975; Huheey 1988; Dittrich et al 1993; Lindström et al 1997; Edmunds 2000; Sherratt 2002; Johnstone 2002; Gilbert 2005; Leimar et al. 2012; Penney et al 2012; Gamberale-Stille et al 2012), and has been regarded as a challenge to genetics, mimicry theory, and to evolu- tionary theory in general (Sheppard 1959; Edmunds 2000; Sherratt 2002; Ruxton et al. 2004 [pp. 159–161]; Chittka and Osorio 2007; Kikuchi and Pfennig 2013).

Considering the principles of natural selection, the belief for mimicry evolution is that a beneficial resemblance to a model species should evolve towards high or perfect similarity to achieve high protection (Fisher 1930; Turner 1970, p.232; Schmidt 58, 60; Ruxton et al 2004), yet there are many examples of persistent imperfect mimicry across different animal groups (Brower 1958; Savage and Slovinski 1992; Dittrich et al 1993, Edmunds 2000, Sherratt 2002, Ruxton et al 2004, Gilbert 2005, Chittka and Osorio 2007; Kikuchi & Pfennig 2010; Win- ter 2017). There is also a great variation in the degree of mimic- model similarity (fig. 1), some appear so incomplete to us that it is surprising how such a crude disguise can fool predators. Several hy- potheses have been put forward to explain the occurrence of imper- fect mimicry (Poulton 1904; Marshall 1908; Punnett 1915; Nicholson

10

1927; Fisher 1927; Edmunds 2000; Sherratt 2002; Ruxton et al 2004; Gilbert 2005; Kikuchi and Pfennig 2013).

One suggestion is that the accuracy of a mimicry is in “the eye of the beholder”, referring to that what humans perceive as imperfect mim- icry may well be perceived as high similarity by the targeted signal receivers (Cuthill and Bennett 1993; Dittrich et al. 1993; Edmunds 2000). The belief here is that we have different perceptual and cogni- tive abilities than the natural signal receivers, who are not able to detect the differences in question (Kikuchi and Pfennig 2010). In con- trast, similarities have been found between human and for example bird perception of mimic accuracy (Penney et al. 2012; Sherratt et al. 2015). It has also been suggested that predators may pay attention to some specific aspects of the prey when they rank mimic accuracy (Dittrich et al. 1993; Bain et al. 2007; Kikuchi & Pfennig 2010). How- ever, these ideas do not offer an explanation as to why signal receiv- ers would assess prey differently, and why they would only pay atten- tion to certain prey aspects. Is it in fact due to a perceptual or cogni- tive limitation or is it a result of conscious decision-making affected by a particular factor?

Another suggested explanation is the theory of developmental or genetic constraint (Smith et al. 1985; Holen & Johnstone 2004). This idea states that imperfect mimics may not be highly protected by their mimicry but are prevented from improving further by counter- acting forces such as genetic limitation, phylogenetic constraints on the anatomy, sexual selection (Wickler 1968; Turner 1978; Wiernasz 1989; Estrada & Jiggins 2008), or trade-offs such as thermoregulation (Brakefield 1985) and camouflage (Holen & Johnstone 2004; Stevens 2007; Stuart-Fox & Moussalli 2009; Barnett et al. 2016). The assump- tion of this idea is that the benefit of a partial similarity to a model species is higher than the benefit of the original appearance (e.g. camouflage). However, it is not specified what could enable this, i.e. what would cause an imperfect similarity to be successful enough to persist in a population under counteracting forces.

The multi-model hypothesis suggests that a mimic adopts an inter- mediate appearance with partial resemblance to several models that

11 exist in adjacent areas (Edmunds 1974, 2000; Sbordoni et al. 1979; Savage & Slovinsky 1996; Sherratt 2002; Gilbert 2005). In this way, the geographic range of the mimic can span over several model population areas because it will protected to some extent in each area, or border areas, as a kind of “jack-of-all-trades” (Sherratt 2002). This idea might for example be applicable to ant-mimicking spiders (Edmunds 1978, 2000). There are however contrasting examples where the appearance of the mimetic species is not intermediate but locally adapted to several model appearances (i.e. polymorphic mim- ic) in adjacent areas (Brown & Benson 1974). Penney et al (2012) found no evidence for intermediate similarity between imperfect hoverfly mimics and wasp and bee models. In a study with poison frogs it was suggested that when two model species in adjacent are- as have different toxicities, a better mimicry of the less toxic model could be more advantageous (Darst and Cummings 2006). The idea is that predators that learn to avoid the highly toxic model generalize more widely, including the less similar mimic. Though, a more accu- rate mimicry of the less toxic model is required for protection against the predators that learn to avoid the less toxic model, due to narrow generalization. The multi-model hypothesis is thus not widely appli- cable to different mimicry systems, and also, the underlying factor that would cause predators to generalize between the imperfect mimic and the model to some extent is not addressed.

A widespread idea is the hypothesis of relaxed selection pressure, which was initially investigated by Duncan and Sheppard (1965), who showed that selection pressure decreased as the mimic-model simi- larity increased (Alcock 1970; Ford 1971; Sherratt 2002; Lynn et al. 2005; Penney et al. 2012). A frequently discussed factor is the cost of attacking the model species. Predators that experience a more aver- sive model (e.g. highly toxic or with very painful sting) are presumed to generalize more widely to be sure to avoid any mistakes, resulting in weak selection pressure on imperfect mimics to improve further (Duncan and Sheppard 1965; Goodale & Sneddon 1977; Lindström 1997). Although, a highly toxic model can have both less and more accurate mimics simultaneously (Darst & Cummings 2006), which is contradictory to the idea of wide generalization. In a study of coral snake mimicry (Kikuchi et al. 2010), it was also shown that predators

12 only generalized and avoided one of the two investigated imperfect mimics, instead of wide generalization and avoidance of both, which also contradicted this hypothesis. Very few studies have investigated the averseness of a natural model prey in relation to the mimic accu- racies in a mimicry system (e.g. ladybugs – Marples et al. 1989; Marples 1993; butterflies – Brower 1958; poison frogs - Darst & Cummings 2006). Other suggested factors are the mimic-model ratio (Brower & Brower 1962; Huheey 1964; Lindström et al. 1997; Harper & Pfennig 2007) and the abundance of alternative prey (Lindström et al. 2004). Relaxed selection models usually consider prey as one- dimensional, whereas warning signals are generally multi- dimensional.

In conclusion, it has been complicated to explain the occurrence of imperfect mimicry with regards to natural selection. Existing hypoth- eses are not widely applicable to the variety of mimicry examples and lack an explanation as to what the essential psychological pro- cess is that causes predators to generalize between models and im- perfect mimics.

13

9 1 8

2 3 10 11

4 5 12 13

6 7 14 15

16 17 18 19 20

1)
Vespula germanica (model) 8) Coccinella septempunctata (model) 16) Battus philenor (model) 2)
Sericomyia silentis 9) Adalia bipunctata 17) Papilio polyxenes 3)
Xanthogramma pedissequum 10) Clytra quadripuncta 18) Papilio troilus 4)
Helophilus pendulus 11) Gonioctena decemnotata 19)
Papilio glaucus 5)
Episyrphus balteatus 12) Charidotella sexpunctata 20)
Limenitis astyanax 6)
Synanthedon vespiformi 13) Paraplectana tsushimensis 7)
Clytus arietis 14) Mylabris quadripunctata 15) Tetraopes tetrophthalmus

Figure 1. Variation in the degree of similarity between models and mimics. Both Batesian and Müllerian mimics are included.

14

Evolution of mimicry

The most accepted view of mimicry evolution is the two-step hy- pothesis (Nicholson 1927; Turner 1984; Joron 2003; Ruxton et al. 2004; Balogh et al. 2010). The evolutionary process is described as an initial major mutational change in the appearance of a non- mimetic species, producing a crude resemblance to the model spe- cies (Punnett 1915; Goldschmidt 1945), which causes predator gen- eralization and avoidance. Subsequently, gradual mutational changes enhance the similarity over time. A preceding belief was that the mutant should acquire high similarity instantly to escape extinction, based on the assumption that all or many aspects of the prey have similar importance for the predator (Turner 1981; Dittrich et al. 1993; Ruxton et al. 2004; Bain et al. 2007). A simultaneous change in mul- tiple traits, which can be in different modalities (e.g. visual, audial, and olfactory), seems highly unlikely. The more recent idea that is gaining ground postulates that predators only pay attention to a few traits in their prey assessment, and these specific traits are most im- portant for mimic success (Chittka & Osorio 2007; Franks & Sherratt 2007; Kikuchi & Pfennig 2010; Balogh et al. 2010; Gamberale-Stille et al. 2012). The feature theory states that a single similarity to the model species can be sufficient to be generalized with the model and avoided, provided that the similarity occurs in a feature with high salience. It also implies a wide generalization over the other traits, allowing the survival of a crude mimic that can initiate mimicry evolu- tion (Balogh et al. 2010; Gamberale-Stille et al. 2012).

The work in this thesis is based on these latter ideas that one or a few specific aspects of the prey have particular significance to preda- tors and that they use such traits before others when they learn and make decisions about prey. Visual predators impose a significant selective pressure on prey appearances. It is therefore important to understand how they perceive and process visual signals if we aim to explain the evolution of conspicuous warning signals and imperfect mimicry.

15 Evolution of aposematism

Aposematism was first described by the naturalist A. R. Wallace (1867) and refers to prey species that signal their unprofitability (e.g. toxicity, distastefulness, or sting) to predators through striking ap- pearances (Poulton 1890; Cott 1940; Edmunds 1974; Ruxton et al. 2004). The evolution of warning signals has been much discussed in the literature. The frequent arguments are that signals evolve to be- come easily detectable, memorable, and induce fast learning (Wal- lace 1867; Roper & Redston 1987; Guilford & Dawkins 1991; Endler 1992; Speed 2000; Ruxton et al. 2004). In most cases this is achieved through conspicuousness, such as bright colors, black contrast pat- terns, and background contrast. The benefit of aposematism is posi- tively correlated to the number of similarly signaling individuals. However, it is not clear how a species initially evolves from a more cryptic appearance to being conspicuous. The paradox lies in that an initial emergence of an individual with a more noticeable trait would inevitably attract attention, and it would be sampled and most likely killed by the predators.

One main theory is that aposematism could evolve through gradual changes. The idea is that predator generalization bias could select for increased intensity of a trait through peak shifts (Leimar et al. 1986; Mallet & Singer 1987; Gamberale & Tullberg 1996, 1999; Yachi & Higashi 1998, 1999; Lindström et al 1999; Lynn et al 2005). The generalization of a learnt stimulus discrimination is proposed to be a gradient with maximum and minimum peak responses around the positive and negative stimuli (fig. 2). A biased generalization of a stimulus component leads to a “shift” away from the response peaks (Hanson 1959; Purtle 1973). Accordingly, predators that have learned to avoid prey with a specific trait would generalize and avoid prey specimens with a more intense version of the trait more, and in this way drive the evolution of conspicuous traits. The selective ad- vantage of the more pronounced version of the trait would balance the visibility risk and avoid extinction in the initial stage of the evolu- tion.

16

avoidance avoidance

Trait A Trait A+

intensity

Figure 2. Illustration of generalization bias leading to a peak shift in response to a trait appearance. In this figure, “trait A” has been learnt to be avoided. “Trait A+” is a slightly more intense version of “trait A” and elicits slightly higher avoidance due to generalization bias, leading to a peak-shift in avoidance. The star symbols at the top symbolize the original trait appearance and the more intense version of it after gradual selection, or “shifts”, toward increased intensity.

Predator psychology

The importance of predator psychology for imperfect mimicry has been emphasized in the past decades (Dittrich et al. 1993; Rowe & Guilford 1999; Sherratt 2002; Gilbert 2005; Chittka & Osorio 2007; Kikuchi & Pfennig 2010; Balogh et al. 2010). Studies have shown that predators use some traits before others when they learn and make decisions about the un-/profitability of multi-trait prey (Schmidt 1958, 1960; Exnerova et al. 2006; Bain et al. 2007; Aronsson & Gamberale- Stille 2007; Cheney et al. 2013; Sherratt et al. 2015; Winters et al. 2017). Schmidt (1958, 1960), for example, demonstrated that butter- fly prey stimuli with just partial color similarities with the model prey were avoided. Several other studies have found that avian predators assess prey based on the color trait primarily when it was combined with traits such as a black pattern or size (Terhune 1977; Osorio et al. 1999; Exnerova et al. 2006; Aronsson & Gamberale-Stille 2008, 2012). In a study by Aronsson and Gamberale-Stille (2007), chicks avoided stimuli with the same color as the avoided model stimulus, but not stimuli with the same pattern. The use of a prime trait in prey

17 assessment has been observed in other animal groups as well. Fish, for example, that prey on nudibranch molluscs, have been shown to generalize between the prey based on one of the color components – a yellow rim around the body, and did not discriminate or general- ize based on the other color component – a red spot (Winters et al. 2017). Experiments with artificial prey also showed that fish used the color component over a black pattern (Cheney et al. 2013).

Our main hypothesis in this thesis is based on this recent notion that certain prey traits are more important to predators and therefore used firsthand in prey assessment (Dittrich et al. 1993; Gamberale- Stille 2003; Chittka & Osorio 2007; Franks & Sherratt 2007; Kikuchi & Pfennig 2010; Balogh et al. 2010; Gamberale
Stille et al. 2012), mak- ing them most relevant in the evolution of aposematism and mimicry. We incorporated concepts derived from animal learning psychology and proposed that traits have different salience to the predators. Some are perceived as highly salient and are used primarily to dis- criminate and generalize between prey, while other traits with lower salience are overshadowed and seemingly not used in the prey as- sessment. We predicted that mimicry of just one salient trait should elicit a significant amount of avoidance due to some degree of gen- eralization with the model prey, despite dissimilarities in other traits. Additionally, in a situation where multiple traits have similar salience, multi-trait mimicry could be required to achieve higher protection, because the predator attention and association will be shared be- tween them. These hypotheses offer an explanation to the initial step of mimicry evolution, the varying degrees of mimic-model similarity, and the persistence of imperfect mimicry.

To explain the evolution of conspicuous warning signals, we elabo- rated the earlier idea of a gradual evolution through biased predator generalization by proposing that the biased generalization should be of traits with high salience. Our prediction is that the predators would develop a stronger association to the salient trait and there- fore generalize and avoid a more pronounced version of it, which would imply that predators could gradually select for an increase in the intensity of a salient trait, leading to the evolution of striking warning signals.

18

The psychological concept of salience denotes that a stimulus that is more striking or distinguishable in a situation (fig. 3) will attract the major share of the signal receiver’s attention. The receiver (e.g. a predator) will thus develop a strong association between the salient stimulus (e.g. a certain prey trait) and the outcome it predicts (e.g. reward or punishment). In the presence of a high-salience stimulus, other stimuli with lower salience are overshadowed and will therefore attract little or no attention and association (fig. 4). However, when presented in the absence of a more salient trait, they will be learned and associated with the outcome (Pavlov 1927; Mackintosh 1975, 76). The salience and overshadowing of traits can increase or de- crease with an increase or decrease in the intensities of the involved traits, i.e. an increase in the intensity of a salient trait will increase its salience and the overshadowing of other traits (Miles & Jenkins, 1973; Mackintosh 1976). Salient traits are assumed to elicit higher learning rates, thus, the rate of discrimination learning of a stimulus can be used as a measure of its salience (Pavlov 1927; Pearce & Hall 1980; Mitchell & Pelley 2010).

A B C D E

Figure 3. Illustrative example of stimulus salience due to conspicuousness and discriminability. The salient stimuli are the (A) magenta color, (B) black pattern, (C) circle shape, (D) double stripes, and (E) plain orange front wings.

19 High salience

Low salience Proportion of attention

Figure 4. Illustration of the relationship between stimulus salience and associability. The high-salience stimulus attracts the major share of the perceiver’s attention and overshadows the less salient stimulus. An association is developed between the salient stimulus and the outcome.

Rescorla and Wagner (1972) presented a model of Pavlovian condi- tioning which included the assumption that differences in the associ- ative strength of a stimulus depends on the total associative strength evoked by the compound stimuli (Miller et al. 1995). Therefore, if several stimulus components have similar salience, the attention and consequently the learned association will be shared between them, whereas if one component has higher salience it will gain higher as- sociative strength than the other. Overshadowing, and the associat- ed phenomenon of blocking, are direct consequences of this (Kamin 1967; Mackintosh 1975, 76). The factors that influence the perceived salience of traits will affect the required mimic-model similarity, and also which traits that evolve to striking warning signals. The salience of a trait can vary with the context in which it is present. It can be perceived as more salient if it is more striking than other traits (e.g. a brighter color or louder sound), or if it stands out to the background, or is an easily discrimi- nated trait between profitable and unprofitable prey. The initial sali- ence of a trait may change as a result of predator experience. Previ- ous experience with the signal can lead to an increase or decrease of the salience due to learned irrelevance or predictiveness of the trait (Mackintosh 1975; Pearce & Bouton 2001; Dopson et al. 2010). For example, a trait that initially is perceived as highly salient, such as a color, can decrease in salience if the predator learns that it is not a very reliable predictor of the outcome (e.g. reward or punishment). Inversely, a trait with lower salience that is initially overshadowed and

20 not used in the prey assessment can become more salient if it is a more reliable predictor of the outcome (Schmidt 1958; Sutherland & Mackintosh 1971; Aronsson & Gamberale-Stille 2012). The latter prediction is partially overlapping with the discriminability factor. The trait/-s that are most discriminable between profitable and unprofita- ble prey will have high salience.

Traits that are not particularly striking, easily detected or contrasting against the background (fig. 3) can also be, or become, salient if they are the particular trait that facilitates discrimination learning. This notion is particularly relevant for the initial phase of warning signal evolution, when the discrimination learning involves prey species without any striking attributes. A generalization bias of such a trait could drive it toward becoming more striking.

The ideas in this thesis, including the psychological concepts of sali- ence and overshadowing as an explanation for the occurrence of imperfect mimicry, and salience-driven generalization bias as an ex- planation for warning signal evolution, have not been described be- fore but are widely applicable to any situation involving learning and generalization.

We tested our hypotheses through discrimination learning trials, fol- lowed by generalization tests, and discrimination trials measuring salience.

Aims of the thesis

To explain following central issues of mimicry and aposematism:

How mimicry evolution can be initiated in a non-mimetic species
Why and how imperfect mimicry persists instead of evolving into more accurate mimicry
Why and how more accurate mimicry evolves
How evolution of conspicuous warning signals can occur

21 Methods

Predators

Insect-eating birds as a predatory group impose a significant selec- tion pressure on prey. This makes them a relevant study species when investigating mimicry and signal evolution. In papers I, II, and III we used wild-caught blue tits (Cyanistes caeruleus) as predators. The attributes of blue tits that make them so suitable for our studies are that they have a very good color vision (tetrachromatic), they are highly food motivated during the winter season, and they are nu- merous here in Sweden. They are feisty little creatures that protest vigorously when they are caught (in trapping cages) through noise and painful pecking on hands but habituate rather quickly to being handled and caged indoors when they realize that the bird hotel of- fers a private room with good food, shelter and water ad lib during cold winter time.

In paper IV we used domestic chickens of the species Gallus gallus domesticus that are kept under semi-natural conditions. The chickens are behaviorally similar to the red jungle fowl (Gallus gallus) that is the wild ancestor. They too have a very good color vision (tetrachro- matic), and are highly food motivated during winter. The hens were used to being handled by people and were not noticeably stressed by the experimental procedures, in fact, most of them insisted on going back to the “chicken hotel” after returning to their original housing.

Experimental setup

The advantage of doing experiments in the lab is that we can control the environment and easily keep track of individual progresses. As we wanted to give the blue tits space to fly around and investigate the prey stimuli during the trials, we used a cubical room as the are-

22 na. It was equipped with a tall bird stand with perches all the way up for sitting and observing, and the background boards on which the prey were presented were situated on the floor (fig. 5). We chose the colors of the background boards in a way to minimize influence on the appearances of the prey stimuli. In paper I the background was black, in paper II it was natural MDF wood color, and in paper III a gray shade.

The hens in paper IV performed trials in a Skinner-Box-like setup. The arena was a cuboid box with no roof. The hens were placed in- side the box and the stimuli were presented one at a time through a slot in one of the walls (fig. 5).

A "
 
  
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Figure 5. (Left) The experimental arena in paper I, II, and III shown from above. The image shows three gray background boards with white pre-training prey items on top of wells. The “zoom-in” shows a lifted prey item, revealing the mealworm re- ward in the well beneath. (Right) The Skinner-box-like setup in paper IV shown from the side. The “zoom-in” shows an inserted stimulus box with a prey stimulus on top of a closed the lid (C) and an opened lid that reveals the reward in the box (D).

In paper I, II, and IV we used artificial prey stimuli that consisted of printed paper items. In paper III we tested a real mimicry scenario and used real butterfly wings as semi-natural prey stimuli.

23

The prey stimuli in paper I, II, and III were presented flat on top of small wells in the background boards. The profitable prey stimuli had a piece of mealworm (Tenebrio molitor) in the well underneath as a reward (fig. 5), and the unprofitable stimuli had empty wells as nega- tive reinforcement. In the Skinner-box-like setup of paper IV the prey stimuli were presented flat on top of the lid of stimuli boxes that were maneuvered in and out of the experimental box. The lid was opened to offer a reward (risoni) when the hen pecked on a profita- ble prey stimulus, and as negative reinforcement for the unprofitable prey the lid remained closed and stayed in the slot for an additional time.

Pre-training

In paper I, II, and III, the purpose of the pre-training was to train the blue tits to lift (“attack”) the paper items to access the reward, and to habituate them to the experimental arena. They were trained with smaller boards with pre-training stimuli (white square items) in their home cages, and also with pre-training stimuli in the experi- mental arena, before starting experimental trials. In paper IV, the hens were habituated to the “Skinner-box” and trained to access a reward by pecking on (“attacking”) the pre-experimental stimulus presented on top of a stimulus box (fig. 5). The pre-training stimulus was a black cross on white background.

Experimental procedures

General approach

All papers in the thesis consisted of a two-parted experiment includ- ing a discrimination learning task followed by a generalization test, and a second part that tested salience through a discrimination learning task.

24

During the discrimination learning the predators successively learned to distinguish between rewarded and unrewarded prey stimuli and avoid the unrewarded prey by the end of the training. Subsequently, we tested how the birds generalized their learned avoidance to new “mimic” prey stimuli.

In paper I, II, and III, the birds performed a one-trial generalization test. In paper IV, the generalization test consisted of 10 probing trials in which the test stimuli (probes) were presented in intervals amidst the discrimination learning prey stimuli. The salience test in all papers was a discrimination learning task between rewarded and unrewarded prey stimuli, to measure how fast a discrimination task was learnt.

Paper I

In order to test how bird predators perceive and assess imperfect mimics we used multi-trait prey stimuli with three traits that in the literature have been considered to be of importance to visual preda- tors for prey recognition
color, pattern and shape. To control for any pre-existing biases or avoidance of certain aspects we used three variants of each trait: cyan, magenta, and yellow as colors; two black dots, two black stripes, and no pattern (plain) as patterns; circle, square, and triangle as shapes. We created three different model types: a magenta-circle-stripes, a cyan-triangle-dots, and a yellow- square-plain. In the discrimination learning part of the experiment the birds learned to recognize and avoid the assigned unrewarded model prey and attack the rewarded prey, which were dissimilar to the associated model in all traits. Subsequently, we investigated which of the prey traits the birds had learned to discriminate and thus used in their generalization of different mimics. In the generali- zation trial, each bird was presented with four mimic types that all had the same one trait (color, pattern, or shape) in common with the assigned model, and the other two traits were similar to the reward- ed prey types (paper I, fig S1). This single trait similarity to the model corresponded to imperfect mimicry. Finally, to confirm that our find- ings could be explained by how salient the traits were perceived by

25 the birds, we performed discrimination trials measuring how quickly the birds learned to discriminate between unrewarded and rewarded prey stimuli based on the three individual traits.

Paper II

In this study we investigated the relative salience of traits. We ma- nipulated the salience of the blue and the black trait of a model prey stimulus by presenting it in two different setups. In one of the setups, the model was presented together with a single type of rewarded prey appearance, and in the second setup it was presented together with multiple types of rewarded prey appearances. In the second part of the experiment we tested how the context (rewarded prey composition) affected the learning and generalization of the model prey traits. The birds from the two discrimination setups each per- formed a generalization trial with a mimic of the black or the blue model trait, in the given setup.

The relative salience of the black and blue traits was measured in a salience test. We tested how quickly the birds learned to avoid a prey stimulus with one of these traits in the two setups (fig 1, paper II).

Paper III

To examine the proposed evolutionary scenario of mimicry between Papilio polyxenes asterius and its noxious model Battus philenor (fig. 1), we used real butterfly wings of B. philenor (Bph), P. p. asterius (Ppo), Papilio machaon (Pma), a hybrid (Hyb) between the mimic (Ppo) and the non-mimic (Pma), and entirely black wings (Bla).

During the discrimination learning the birds learned to avoid the un- rewarded Bph model and attack the rewarded Pma wings. We then tested how the birds generalized their learned avoidance of Bph to three mimic types – Ppo, Hyb, and Bla wings. The hybrid form was used to test the effect of partial melanization, representing the pos- sible initial crude mutant. The black wings were used to test the ef-

26 fect of black coloration. In the salience test we measured how quickly the birds learned to discriminate between the model and the three mimic types, including a discrimination between black wings and Pma.

Paper IV

The prey stimuli in paper IV consisted of two traits, similar to paper II. One trait varied in the color dimension, ranging from a green to blue hue, and the other varied in gray scale from light to dark gray shade. The unrewarded prey stimulus was a medium blue-gray combination. One group of birds received a discrimination learning task with a big difference in the color component between the unrewarded (S-) and rewarded (S+) prey stimuli, and a small difference in the gray com- ponent. The second group learned the reverse component differ- ences. We then initiated a 10-trial generalization test by inserting test stimuli amidst the regular discrimination stimuli presentations. The “probing” procedure has the advantage that we can collect the nec- essary amount of data without risking extinction.

We performed two generalization tests: first we examined generaliza- tion bias of the color and gray components of the S- stimulus; sec- ondly, we tested generalization of the individual S+ components. In order to examine generalization bias of the color component of S- we used two probe stimuli with more intense blue shades than the S- and an identical gray component. A third probe had a less intense blue (i.e. more green) than the S- as a counter control. The gray di- mension was tested in the same way – two probes with darker shades of gray, and a third probe with a lighter gray shade, with the color component (blue) identical to S-.

The generalization of the S+ components was examined by cross- combining the two components with the S- components, generating two possible combinations for the probes: S+col/S-gray and S- col/S+gray. The generalization probes differed in accordance with the assigned discrimination task beforehand.

27 Finally, we tested the salience of a large and a small difference in the color and gray components between S- and S+ (fig S2, paper IV) respectively. Only one of the two components differed between S+ and S-.

28

Results & Discussion

Our main hypothesis in this thesis is that traits have different salience to predators and that the most salient traits are used primarily in the discrimination and generalization of prey, while other traits with low salience are overshadowed and not used in the prey assessment. Our findings demonstrate that our hypothesis can be applied to ex- plain the initiation (first step) of mimicry evolution that involves a crude mimic (ppaper I and III), the persistence of imperfect mimicry (ppaper I, II, III), the varying degrees of mimic-model similarity (ppa- per II), and furthermore, the evolution of conspicuous warning sig- nals (ppaper IV).

Initial step of mimicry evolution

The two-step hypothesis is currently the most accepted view for mimicry evolution. It states that the evolutionary process is initiated by a major mutational change in a non-mimetic species that produc- es a rough resemblance to the model species, causing predators to generalize between the model and the crude mimic and avoid it. The initial gained protection would allow the crude mimic to persist and evolve more refined mimicry through gradual changes over time. We propose that if the initial change produces similarity in a trait that is of high salience to the predators, the crude mimic could be general- ized with the model to some extent, despite other trait differences, and initiate mimicry evolution.

Our investigations of how bird predators learn to discriminate and subsequently generalize between multi-trait prey stimuli showed that the birds only used one of three traits in their prey stimuli assessment (ppaper I). We found that mimicry of the color trait was highly effec- tive, eliciting as high avoidance as the model stimulus, even though the mimics differed in both pattern and shape. Mimicry of either the pattern or shape of the model did not offer any protection; the mim- ics were attacked as much as the rewarded prey stimuli (fig. 6). This

29 result demonstrates that predators can use one particular trait to discriminate and generalize between prey stimuli. To find out if this could be explained by the relative salience of the three traits, we tested how quickly the birds learned to discriminate each of them. As expected, the learning rate of the color discrimination was the high- est, confirming that the birds perceived it as the most salient trait, whereas pattern and shape discriminations were learned at an inter- mediate rate (fig. 6).

B

1.0 1.0



a a

0.5 0.5

b b
color Avoidance of mimic Avoidance Avoidance of model Avoidance pattern shape

0.0 0.0 perfect color pattern shape 123456 Mimic variant Trial

Figure 6. (Left) Generalization test of imperfect mimic prey stimuli. The single trait that is mimicked is given on the x-axis. Data are pooled over the three model vari- ants that are mimicked. (Right) Salience discrimination test of the color, pattern and shape traits individually. The learning curves are fitted logistic regressions to the data. The proportion of attacks directed away from, i.e. avoidance of, the mimics and models is shown with 95% bootstrap confidence intervals. Statistically significant differences are between “a” and “b”.

The findings in paper I show that predators perceive certain prey traits as particularly important and use these firsthand in their as- sessment of prey quality (profitable/unprofitable). Such psychologi- cally “higher ranked” traits that elicit higher learning rate and associ- ative strength than other traits, are considered to be high-salience traits (Pavlov 1927; Mackintosh 1975). In the first step of mimicry evo- lution, similarity in a single trait can thus generate enough generali- zation with the model to avoid attacks, providing that the similarity occurs in a trait that is of high salience to the predators. This is in line

30 with the earlier idea of a saltation in a trait of high importance, com- bined with wide generalization over the less important traits (Balogh et al. 2010; Gamberale-Stille et al. 2012). Schmidt (1960) also sug- gested that an initial single similarity in a color component (e.g. black wing color) could be enough to elicit generalization and avoidance as a first step in the evolution. Several other experimental studies have shown that predators use one of several stimulus components in their prey assessment (Sexton 1960; Terhune 1977; Aronsson & Gamberale-Stille 2007; Exnerova et al. 2006; Winters et al. 2017), all of which can be explained by our hypothesis of predator perception of trait salience.

The results in paper II also support this idea and further show that in situations where multiple traits are perceived as similarly salient, mimicry of one of the traits will elicit intermediate avoidance, while mimicry of both offers highest protection. This implies that an initial partial resemblance can be enough to avoid attacks, but further im- provement will be required for higher protection, which corresponds to the gradual changes of the second step of mimicry evolution. A more detailed discussion of these findings follows in the next section.

In paper III, we explored a proposed scenario for the initial step of mimicry evolution in the eastern black swallowtail butterfly, Papilio polyxenes asterius, to its noxious model the pipevine swallowtail, Battus philenor (fig. 1). Clarke & Sheppard (1955) proposed that the black wing color of P. p. asterius was controlled by a single dominant gene, and argued that mimicry in P. p. asterius could have been initi- ated by a single mutation in the gene that produces black, resulting in a passable mimic (Clarke & Sheppard 1959). Our purpose was to investigate if we could confirm and further explain the proposed sce- nario by applying our hypothesis of salient traits, with the expecta- tion that the black wing color would be the most salient trait. The generalization test, which followed an avoidance learning of the B. philenor model prey, showed that the partial melanization of the hy- brid prey resulted in intermediate avoidance, in comparison to the very high avoidance of the natural P. p. asterius mimic (fig. 7). In the salience test, the difference between the model and the hybrid was learned at an intermediate rate, while the difference between the

31 model and the natural mimic was not learned at all during the course of our trials (fig. 7). Additionally, discrimination between plain black wings and yellow non-mimetic wings (P. machaon) was learned very quickly. In conclusion, these results demonstrated that the black col- or had high salience and a similarity to the model in the black trait resulted in intermediate protection from attacks. The differences in the other traits between the hybrid and the model had intermediate salience, which shows that there would be scope for gradual evolu- tion toward higher similarity to achieve ultimate protection, as seen in the natural mimic.

A B 1.0

* *

0.5 ** Avoidance

Bla
Pma Bph
Ppo

Bph
Hyb Bph
Bla 0 Bph Ppo Hyb Bla 123456 Mimic type Tr ial

Figure 7. (Left) Generalization test of imperfect mimic prey stimuli. The mimic type is given on the x-axis. (Right) Salience discrimination test of four discrimination treatments. The learning curves are fitted logistic regressions to the data. The pro- portion of attacks directed away from, i.e. avoidance of, the mimics and models is shown with 95% bootstrap confidence intervals. Statistically significant differences are marked with stars.

In paper I and II we can see that traits with lower salience can be learned when the most salient trait is excluded, which indicates that they have the potential to become more salient and be used in the prey assessment. Such an effect could be generated by for example predator experience, which is discussed in more detail in the next section.

32

Our findings verified our hypothesis and supported the previously suggested idea for mimicry evolution in the eastern black swallowtail. It seems feasible to assume that mimicry evolution in P. p. asterius started through a mutation that produced melanization in an original- ly yellow non-mimetic ancestor. The attained similarity in the salient black trait would have caused generalization between the melanic mutant and the B. philenor model to the extent that it could persist. In the second part of the evolutionary process, gradual changes would have refined the mimicry to obtain higher protection.

Variation in the degree of mimic-model similarity

Similarity in a few traits is regarded as poor or imperfect mimicry (Dit- trich et al. 1993; Bain et al. 2007), leading to the assumption that similarity in a high number of traits is good mimicry. It has been sug- gested that the more traits a mimic has in common with its model, the higher is the avoidance by the predators (Schmidt 1958, 1960). Considering that there is a wide range of persistent imperfect mimic- ry, some with very few trait similarities to the model, this leads to the question of what essentially determines the required level off similari- ty, or number of trait similarities, for successful mimicry?

We investigated this issue in paper II by manipulating the salience of two model traits (black and blue) by presenting them in two differ- ent setups. The difference between the setups was the composition of the rewarded prey stimuli. The setup (context) in which the model was presented affected the salience of its color traits differently. In the setup with a single type of rewarded prey, both the blue and the black component were quite distinguishable, and the birds used both of them to discriminate and generalize between prey stimuli. This was shown in that mimics of either the blue or the black trait were intermediately avoided due to their single trait similarity to the model, in comparison to the highly avoided “perfect” mimic (blue and black). In the setup with multiple rewarded prey appearances, the blue trait was more distinguishable than the black, which resulted

33 in that mimicry of just the blue trait produced significantly higher avoidance than mimicry of the black trait (fig. 8).

1.0

0.5

Single Multiple Avoidance of mimic Avoidance

0.0 Black Blue Perfect Black Blue Perfect Mimic type

Figure 8. Generalization test of imperfect mimic prey stimuli. The trait that is mim- icked is given on the x-axis. ‘Single’ and ‘Multiple’ denote the composition of the rewarded prey appearances. The proportion of attacks directed away from, i.e. avoidance of, the mimics is shown with 95% bootstrap confidence intervals. The dashed lines indicate the final two contrasts given in table 1 in paper II (i.e. the dif- ference between black and blue mimics in the two discrimination learning treat- ments).

The following salience test confirmed that the birds perceived the blue trait similarly salient in the two setups. The black trait on the other hand, was perceived as less salient in the setup with multiple types of rewarded prey, presumably due to the decreased discrimi- nability in comparison to the rewarded prey traits (fig. 9). Schmidt (1960) made similar observations with artificial prey stimuli, showing that a partial similarity with the model stimulus in a single trait (black) could offer protection, while similarity in two traits may be slightly more effective. Aronsson and Gamberale-Stille (2012) found that birds primarily learned the color component of the model stimulus, which overshadowed the pattern component. However, with in- creased experience, the predators could start using the pattern as well to a lower degree.

34

(a) (b)

1.0 1.0

0.5 0.5

Single
Single Avoidance of Blue Avoidance Avoidance of Black Avoidance Multiple Multiple

0.0 0.0 123456 123456 Tr ial Trial

Figure 9. Salience discrimination test of the two model traits individually, in two different contexts. (Left) black trait, (right) blue trait. “Single” and “Multiple” denote the composition of rewarded prey appearances. The learning curves are fitted lo- gistic regressions to the data. The proportion of attacks directed away from, i.e. avoidance of, the mimics and models is shown with 95% bootstrap confidence inter- vals.

In conclusion, our findings showed that individual model traits can have different salience to the predators depending on the context in which they are present. In a context where multiple traits have similar salience to the predators, mimicry of a single trait can offer partial or considerable protection, though, to achieve higher protection, mim- icry in a higher number of traits will be required.

Presuming that the successfulness of mimicry depends on similarity in salient traits, it is important to reflect on the factors that could af- fect salience. How discriminable or distinct certain model traits are from the profitable prey traits, or from the background, are two fac- tors that have been emphasized in hypotheses about conspicuous warning signal evolution, and both can influence salience and facili- tate fast avoidance learning (Getty 1985; review in Ruxton et al. 2004 - Table 7). As shown in paper II, in a context where a trait was more discriminable in comparison to the rewarded prey traits, it had higher salience, and when the trait was less discriminable, it had lower sali- ence. Conspicuous traits are expected to have high salience and be important for mimicry success, while more general traits (e.g. body shape or size) that are more similar to, or less discriminable from, the

35 profitable prey traits, are expected to have low salience. A partially overlapping explanation is the idea of detectability, which means that a trait, or signal, is easily detected during foraging. For example, color is a good candidate to be a high-salience trait for birds that are visual predators with a good color vision. They can easily detect col- ors from a distance and this could contribute to quicker, cost- effective, decision-making without closer inspection.

Another important influence on trait salience can be predator expe- rience. With greater experience, predators could start learning that a high-salience trait is not a sufficiently reliable predictor of the out- come, for example when exploited by mimics. At this point, a trait with lower salience that was previously overshadowed and not used in the prey assessment could gain salience and be incorporated in the prey assessment, provided that it is a reliable predictor of the outcome (Schmidt 1958; Sutherland & Mackintosh 1971; Aronsson & Gamberale-Stille 2012). A successive incorporation of traits that ini- tially had lower salience could gradually select for more accurate mimicry. This process may require long-lived predators that can ac- quire extensive experience with the prey community, low time con- straint during foraging due to possible speed-accuracy trade-offs (Chittka & Osorio 2007; Chittka et al. 2009), and relatively tolerable consequences of sampling models. Such an effect has been ob- served within the time frame of some studies (Schmidt 1958; Ar- onsson & Gamberale-Stille 2012). We also need to consider the pos- sibility that predators may treat natural prey differently in comparison to some artificial stimuli.

Multi-trait mimicry could also be selected for by a variety of preda- tors (Carter 1946; Schmidt 1960). For example, different bird families have been found to impose dissimilar predation pressures on two different color morphs of a moth species (Nokelainen et al. 2014). Human “predators” perform similar to bird predators in some as- pects, but a study that replicated the experiments in paper I found that humans used two out of three traits in a context where birds used one trait (Sherratt et al. 2015). There are areas with high num- bers of insectivores such as spiders, ants, amphibians, robber flies, and preying mantises that feed on for example mimetic flies, beetles,

36 spiders, moths and butterflies. Different sensory and cognitive abili- ties, and different hunting methods (e.g. initiate attack from a dis- tance or get very close, opportunity to inspect prey), means that dif- ferent traits of a species will be perceived as salient. In such cases, mimicry in multiple traits could be required to gain protection against different predators.

In summary, the relative salience of traits, which can be context de- pendent, could explain why there is variability in mimetic resem- blance in nature, ranging from crude mimicry in a few traits to very accurate mimicry. The suggested factors that could influence trait salience and lead to selection for mimicry in a higher number of traits, exemplify how and when more accurate mimicry evolves.

Persistence of imperfect mimicry

Several theories have been proposed to explain the persistence of imperfect mimicry (see introduction). Yet, no explanation is given for how the predators generalize between the model and an imperfect mimic, i.e. what leads them to use certain traits as main cues in their prey assessment, while “overlooking” other dissimilarities. We sug- gest that predators use traits that they perceive as highly salient pri- marily in their prey assessment, while other traits with lower salience are overshadowed and consequently not used in the prey assess- ment. If the mimic-model differences are in traits with low salience, there will be no, or very low, selection pressure for them to change, allowing imperfect mimicry to persist.

In paper I we found that the salient color trait overshadowed both the black pattern and shape traits. Mimics of the color trait were highly avoided, despite their dissimilarities to the model in both pat- tern and shape. Even though the birds could learn to discriminate between prey based on either the pattern or the shape, mimicry of these traits did not elicit any attack avoidance, due to overshadowing in the presence of the more salient color trait (fig. 6).

37 The generalization test of paper II further confirmed this by show- ing that in a context where one of the model traits is perceived as more salient, the accompanying trait with lower salience is overshad- owed and has little effect on the prey assessment (fig. 8). Thus, simi- larity in the most salient trait will be sufficient for high protection.

The mimicry case that we examined in paper III is a good example of persistent imperfect mimicry. The natural Batesian mimic P. p. as- terius, has clear differences to the model B. philenor in its color pat- tern, such as the number of orange spots, their placement, their size, and the area coverage of iridescent blue. Even so, our experiments showed that the natural mimics were avoided as much as the model prey (fig. 7), indicating that it was equally effective despite the dis- similarities. The differences had no noticeable salience to the birds, seen in that they did not learn to discriminate between the two dur- ing our experiment (fig. 7). These findings verified our idea that the selection for more accurate mimicry will level off when the remaining trait differences have very low salience to the predators.

In an outdoor experiment with wild birds and artificial prey stimuli, partial color mimicry resulted in considerable avoidance, despite an additional dissimilarity (Ford 1971). A study of coral snake mimicry by Kikuchi et al. (2010) showed that imperfect mimicry was highly effec- tive even though the mimicked color stripes had a different width and order than the model. The same was found in for example a case of ladybird mimicry where the non-toxic 2-spotted ladybird mimics the highly toxic 7-spotted ladybird (Marples et al. 1989). The smaller mimic has the red color of the model but a different number of spots as the name indicates. The most familiar example is the vast number of species (e.g. hoverflies, beetles and moths) that mimic wasps in the yellow and black color components but with great variability in their resemblance to the model (Dittrich et al. 1993; Edmunds 2000; Weller et al. 2000; Gilbert 2005). The imperfect mimics can differ in a number of traits, sometimes so much that it is remarkable that they can pass as mimics (fig. 1).

In all the mentioned examples, a specific color, or color combination, are perceived as highly salient, overshadowing other trait dissimilari-

38 ties. The low salience traits are consequently not used in the prey assessment. Accordingly, even a crude mimicry can be effective and persist, provided that the most salient trait/-s of the model are mim- icked.

Evolution of conspicuous warning signals

Warning signals are frequently suggested to have evolved to be- come easily detectable (e.g. contrast and conspicuousness), memo- rable, and induce high learning rate (Guilford 1990; Guilford & Daw- kins 1991; Speed 2000; Ruxton et al. 2004; Hauglund et al. 2006). Essentially, such factors are either a product of, or affect, the trait salience. In fact, all factors that are positively correlated with the ef- fects of aposematism can be explained through the concept of sali- ence. Other examples are discriminability from profitable prey (dis- cussed above) and neophobia. Additionally, it has been suggested that biases in predator learning and generalization can drive the evo- lution of warning signals (Leimar et al. 1986; Mallet & Singer 1987; Gamberale-Stille & Tullberg 1999; Yachi & Higashi 1999; Lynn et al. 2005). Based on these ideas, we suggest that predators could have a biased generalization of salient traits, toward a more pronounced version of them, leading to peak-shifts in the response gradient. Such a selection for an increase in the intensity of a trait would lead to the evolution of a conspicuous warning signal.

The generalization probe trials in paper IV showed that birds had learned to discriminate between the rewarded and unrewarded stim- uli based on the component in which they differed the most (blue or gray). This was seen in that they generalized and avoided probe stimuli that had a slightly more intense version of the avoided stimu- lus component, i.e. more blue or darker gray. In the visual sensory dimension, the extent of generalization around a given stimulus component usually has a Gaussian distribution centered on that stimulus value (Ghirlanda & Enquist 2003; Chittka & Osorio 2007; Ruxton et al. 2008). In our analysis of how birds generalized their learned avoidance of the unrewarded stimulus component, fitted

39 Gaussian curves showed that there was a slight shift, or bias, in the direction of the more intense version (fig. 10).

a 1.0 *** 1.0 *

0.8
0.8

0.6 0.6
0.4 0.4

Proportion attacks 0.2 0.2

0.0 0.0 C4 C5(S
)C6C7 G4 G5(S
)G6G7 Colour variation around S
Grey variation around S

Figure 10. Generalization test of the color (left) and the gray (right) stimulus com- ponents, with a big difference (high salience) between rewarded and unrewarded prey stimuli. The intensity of the test stimuli goes from lower to higher, from left to right, on the x-axis. The learnt unrewarded stimulus (S-) component is C5 and G5. The proportion of attacks is shown with 95% bootstrap confidence intervals. Statisti- cal significance is marked with stars and is based on table S1 in paper IV. Fitted Gaussian curves show the generalization gradients. The line between the peak of the curve and the x-axis shows the “shift” away from the S- stimulus component.

The additional salience test verified our belief that a large difference between rewarded and unrewarded stimuli in a stimulus component should have high salience, whereas a small difference should have lower salience. The measured learning rates confirmed that a large difference was learned significantly faster than a small difference and thus had higher salience (fig. 11).

40

1.0

Large difference in blue

Large difference in gray 0.5

Small difference in gray

Small difference in blue

Proportion avoidance of S Proportion avoidance





0.0 1 10 Trial

Figure 11. Salience discrimination test of a large and small difference in the color (blue) and gray component between the rewarded and unrewarded prey. The pro- portion of unrewarded stimulus presentations that did not elicit an attack (i.e. avoid- ance) is shown with 95% confidence intervals.

In conclusion, the stimulus component that was most discriminable between the rewarded and unrewarded stimuli had high salience to the birds and was used to discriminate and generalize between the stimuli. Subsequently, the birds showed a generalization bias in the way that they avoided a more intense version of the salient stimulus component, leading to a peak-shift in the response gradient around the unrewarded salient stimulus component. Thus, our idea seems valid, that biased generalization of high-salience traits can gradually select for increased intensity and drive the evolution of striking warn- ing signals such as bright colors and color patterns.

In paper III, we used a plain black wing type as one of the test mim- ic prey in the generalization test, following an avoidance learning of the B. philenor model. Surprisingly, we found that the birds avoided the black mimics as much as the model prey in the single test trial, indicating that they did not differentiate between them (fig. 7). How- ever, the salience test revealed that the birds easily discriminated between them. The high avoidance of the black wings might there- fore have been due to an initial bias toward the more exaggerated version of the salient black trait of the model. However, in the ab- sence of alternative rewarded prey (i.e. discrimination between mim-

41 ic and model only), and with more interaction with the prey, the birds easily learned to discriminate between the two. A similar result was found by Schmidt (1960), who found that birds that learned to avoid a tri-colored model, avoided wholly black mimics greatly (Schmidt 1960 p.154), indicating a generalization bias. Gamberale-Stille & Tullberg (1999) showed that chickens that learned to avoid a red colored seed bug prey, avoided specimens that were more red to a higher degree. The same was found with chickens pecking on a computer screen, gradually selecting for a stronger color hue (Jans- son & Enquist 2003).

The salience of a stimulus component can increase with an increase in its intensity (Kamin1969; Miles & Jenkins 1973; Mackintosh 1976). Thus, a trait that is initially perceived as salient and used in for exam- ple prey assessment, could be perceived as more salient if the inten- sity increases. A different side of the coin would be that when the intensity of the trait increases in the unprofitable stimulus, the dis- criminability between profitable and unprofitable stimuli is increased, which results in an increased salience of the trait. The evolution of a conspicuous warning signal could therefore begin in an inconspicu- ous trait that is readily discriminable between profitable and unprof- itable prey and therefore perceived as salient and used in the prey assessment. Individuals that attain a more intense version of the spe- cific trait would be effectively avoided due to a bias in predator gen- eralization, leading to a gradual selection for higher intensity of the trait.

42

SUMMARY

In this thesis we have presented and empirically tested a general hypothesis, involving trait salience and predator psychology, which could explain the central issues of mimicry and aposematism.

i) We suggest that predators perceive certain traits as highly salient and therefore use these primarily in their discrimination and generali- zation of prey. Traits with low salience will be overshadowed by the high-salience traits and therefore not used in the prey assessment. This hypothesis can explain the initial step of mimicry evolution in- volving a crude mimic, and the persistence of imperfect mimicry.

ii) When several model traits have similar salience, mimicry of one or a few traits could offer some protection, whereas mimicry of multiple traits will be required for ultimate protection. This can explain the variation in mimetic similarity in different mimicry systems, and why more accurate mimicry can be required.

iii) Mimicry evolution will level off when the remaining mimic-model differences are in traits with very low salience.

iv) Predators can have a biased generalization of salient traits. A more striking or intense version of the learned model trait will be generalized and avoided. Thus, predator bias can select for a gradual intensification of an initially inconspicuous trait. This could explain how a conspicuous warning signal evolves.

43 References

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52

Svensk sammanfattning

Aposematiska arter är oätliga på grund av t ex giftighet, osmaklighet eller sting, och har utvecklat slående egenskaper såsom starka färger och färgmönster för att signalera sin oätlighet till predatorer. En del ofarliga och ätliga arter utnyttjar den avskräckande effekt som apo- sematiska arter (modeller) har genom att härma deras utseende. Det finns även härmning, s.k. mimikry, som involverar flera oätliga arter som har utvecklat en gemensam likhet för att på så sätt reducera förlusten av individer per art till predatorer som ska lära sig diskrimi- nera mellan ätliga och oätliga arter. Oavsett typ av mimikry så före- kommer det stor variation i likheten mellan härmare och deras mo- deller. En del härmare har utvecklat stor likhet till sin modellart för att uppnå ett effektivt skydd, medan andra kan vara väl skyddade av en ungefärlig likhet.

Förekomsten av ofullständiga härmare har varit svårt att förklara med hänsyn till naturlig selektion. Tidigare teorier har inte kunnat ge en genomgripande förklaring till detta fenomen. I denna avhandling presenterar jag våra hypoteser som ger ett nytt perspektiv på hur man kan lösa de centrala frågeställningarna gällande ofullständig mimikry: hur kan en icke-härmare som förvärvar endast en grov likhet med en modellart initiera evolution av mimikry, utan att istället selek- teras bort? Varför, och hur, kan ofullständig härmning bestå istället för att utvecklas till bättre likhet med modellen? Dessutom presente- rar vi en möjlig förklaring till evolutionen av aposematism genom vår grundläggande hypotes.

Genom att tillämpa etablerade inlärningspsykologiska teorier och begrepp har vi utvecklat och testat en hypotes som kan tillämpas brett. Våra idéer baseras på insikten att predatorer endast använder sig av ett fåtal specifika egenskaper i utseendet, vilka de uppfattar som viktigare än andra egenskaper, när de lär sig diskriminera och generalisera mellan bytesdjur. Vår övergripande hypotes är att olika egenskaper är olika utmärkande, d.v.s. har olika salience, för preda- torerna. De egenskaper som uppfattas vara mycket utmärkande, och

53 därmed har hög salience, används i första hand för att diskriminera och generalisera mellan byten, medan egenskaper som är mindre framträdande, d.v.s. har låg salience, blir överskuggade och används inte i bedömningsprocessen. En egenskaps salience kan bero på exempelvis hur iögonfallande eller särskiljbar den är i sitt samman- hang. Det kan även påverkas av predatorernas tidigare erfarenheter, samt hur värdefullt det är för dem att lära sig känna igen en egen- skap baserat på t ex belöningens eller bestraffningens omfattning. Överskuggning av egenskaper med lägre salience är en konsekvens av att den största andelen av predatorns uppmärksamhet dras mot den egenskap som har högst salience. Predatorn lär sig därmed as- sociera just den egenskapen med påföljden (associativ inlärning), och följaktligen generalisera mellan bytesdjur baserat på den inlärda egenskapen. Till exempel, om röda ränder associeras med bytesdju- rets giftighet och undviks, kommer andra djur med någon form av röda ränder också att undvikas i viss mån på grund av generalisering av färgmönstret.

Vi testade vår hypotes genom experiment med vilda blåmesar och höns som predatorer, samt konstgjorda och semi-naturliga (fjä- rilsvingar) stimuli som byten. Våra resultat visade att fåglarna an- vände sig av den egenskap som de uppfattade som mest salient för att diskriminera och generalisera mellan stimuli. Efter att ha lärt sig undvika en modell med ett visst utseende, undvek de härmare av den specifika egenskapen så gott som lika mycket som modellen, trots att de andra egenskaperna skiljde sig åt. Vi visade även att sali- ence är relativt och kan påverkas av sammanhanget. I vissa situation- er kan flera egenskaper uppfattas ha hög salience, vilket leder till att härmning av en enskild sådan egenskap är relativt fördelaktigt, men inte lika fördelaktigt som härmning av flera. Vidare undersökte vi ett möjligt händelseförlopp för det första evolutionära steget hos en existerande mimikry mellan den nordamerikanska ätliga fjärilsarten Papilio polyxenes asterius och dess oätliga modell Battus philenor. Resultaten bekräftade att en likhet med modellen i den egenskap som uppfattades som mest salient (svart vingfärg) ledde till delvist skydd mot attacker, trots en i övrigt ofullständig likhet. För att kom- plettera helhetsbilden testade vi även om vår idé om egenskapers salience, kombinerat med hypotesen om att predatorer kan ha en

54 bias i sin generalisering, skulle kunna förklara evolutionen av de slå- ende egenskaper som aposematiska arter har. Våra experiment vi- sade att fåglarna generaliserade och undvek en mer förstärkt variant av den egenskap som de uppfattade som mest salient och lärde sig undvika.

Experimentresultaten bekräftar våra idéer och visar följande: i) Evolution av mimikry kan initieras genom en mutation hos en icke-härmare, som resulterar i likhet med en modellart i en egen- skap med hög salience. Detta leder till att predatorerna genera- liserar mellan icke-härmaren och modellen i tillräckligt hög grad för att den nya mutanten ska överleva och initiera den evolution- ära processen. ii) Ofullständig mimikry kan bli bestående då de kvarvarande skill- naderna är i egenskaper som har låg salience för predatorerna, och därmed inte har någon större inverkan på diskrimineringen av byten. Således är de under lågt, eller inget, selektionstryck för att förändras. iii) Variationer mellan mimikrysystem, i graden av likhet mellan här- mare och modeller, kan förklaras genom att flera egenskaper kan ha likvärdig salience i vissa förhållanden, varpå härmning av flera egenskaper kan vara nödvändigt för att uppnå maximalt skydd. iv) En egenskap med hög salience kan gradvis drivas mot att bli mer och mer förstärkt, som en följd av predatorers generali- serings-bias, och leda till evolution av iögonfallande utseenden.

Sammanfattningsvis kan vår teori om egenskapers salience och överskuggning tillämpas för att förklara hur ofullständig härmning uppkommer, förblir ofullständig, och varför det finns variationer i likhet. Dessutom förklarar vi hur salience kan påverka evolutionen av varningssignaler. Det är första gången dessa begrepp från inlär- ningspsykologin tillämpas för att förklara ofullständig härmning och aposematism.

55 Acknowledgements

The last chapter of this monumental period of my life...

I could not have asked for a better power-duo than Olle and Gabriel- la as supervisors. Your different personalities and expertise complet- ed each-other, and I learned so much about so many different things. You have always been there for me. I never felt that I didn’t get enough time or attention from you. I will miss our meetings in Olle’s office, chatting about this and the other, including anecdotes, the great ideas in this thesis, and annoying reviewers that just didn’t get it. I will miss Gabriella’s humor and Olle’s characteristic comments. Thank you for your support and everything that you have done for me.

I want to thank Sven for pointing my in the right direction when I was going to do my master thesis, which was the beginning of all this. Thank you for your support and advice also as a member in my fol- low-up committee, and all the nice chats at Tovetorp where I did all the experiments. I would also like to thank somebody that we all miss...Birgitta. It is with great sorrow I write this, but with nice memo- ries. Thank you Birgitta for the advice and support during my master thesis, which later became paper I, and for your support as a mem- ber in my follow-up committee. You, and Gabriella, made me feel welcome from the very beginning. It was always nice chatting to you, and I admired you for your achievements.

Thank you all at Tovetorp! Specially Nisse and Thomas that helped me whenever I needed something. I just wish I could have been there during spring or summer instead of six winters in darkness... I shared one winter with Therese, who helped me with some experi- ments. Thank you for your help and nice company Therese. Also thanks to Robert who helped me in the very beginning with experi- ments. Christer, our butterfly expert, your ambitious butterfly breed- ing was very valuable for the third paper, and it ended up being

56 even better than we thought. Thank you for contributing with your knowledge, kindness, and humor.

There are so many people that have made my time at Zootis enjoya- ble! So many great people in one place, I’m going to miss that a lot. I specially want to thank Anna, Martin, and Sandra S, for all the fun times, support, advice, discussions about life, and conference travel memories. A special thanks goes also to Marianne A, for being such a great person to be around from the very beginning when I helped you with experiment, and your support ever since, even though you finished at Zootis just when I started. Alexandra B, Kristin, Johanna, Alexander, and Sandra G, thank you for all the laughs and sharing this time with me. Bertil, thank you for the nice experiences at Tjärnö, your humor, and trusting me with your camera equipment. I also need to thank Siw and Annette who have put up with me when I was a scatterbrain, and fixing stuff no matter what.

I’m very grateful to my friends and family who have followed my pro- gress and given me pep-talks when needed, listened to my com- plaints, put up with me during stressful times, and been proud of me for achievements. My husband Jonathan has been part of this even by helping at Tovetorp. Thank you for feeding me all the time, and taking care of Enya during the time I’ve needed to work on my the- sis. I specially want to thank my mum, who has been there for me always. Merci maman! My dad has followed my work with great in- terest, merci baba, for your support. I’m very grateful to mum and Olle (mum’s husband) for lending me their only car during all those winters when I needed to go to Tovetorp for weeks, for feeding me, and spending time with Enya during my thesis writing.

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