UC Irvine UC Irvine Electronic Theses and Dissertations
Title Deconstructing visual signals in social butterflies
Permalink https://escholarship.org/uc/item/0jd725qm
Author Finkbeiner, Susan Diane
Publication Date 2015
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UNIVERSITY OF CALIFORNIA, IRVINE
Deconstructing visual signals in social butterflies
DISSERTATION
Submitted in partial satisfaction of the requirements for the degree of
DOCTOR OF PHILOSOPHY
in Ecology and Evolutionary Biology
by
Susan Diane Finkbeiner
Dissertation Committee: Professor Adriana D. Briscoe, Co-chair Professor Robert D. Reed, Co-chair Professor Nancy T. Burley Professor Kailen A. Mooney
2015
Chapter 1 © 2012 The Royal Society Chapter 2 © 2014 John Wiley and Sons All other materials © 2015 Susan D. Finkbeiner
DEDICATION
To
My parents: Mary and David Finkbeiner, for their unconditional support throughout my lifelong endeavors to become an entomologist and study tropical butterflies;
My sisters: Brenda Finkbeiner and Karla DeFazio,
for their patience enduring my obsession with insects;
And to the late Dr. Thomas Eisner:
who encouraged me to never loose curiosity for the fascinating insects and butterflies that I love.
“No one changes the world who isn’t obsessed.” -Billie Jean King
“In Wildness is the preservation of the world” - Henry David Thoreau
ii TABLE OF CONTENTS
Page
LIST OF FIGURES……………………………………………………………… iv LIST OF TABLES………………………………………………………………. vi ACKNOWLEDGEMENTS……………………………………………………… vii CURRICULUM VITAE...………………………………………………………. ix ABSTRACT OF THE DISSERTATION……………………………………….. xi INTRODUCTION………………………………………………………………. 1
CHAPTER 1: Anti-predator benefits of communal roosting behavior in Heliconius butterflies Introduction……………………………………………………………… 14 Methods………………………………………………………………….. 17 Results…………………………………………………………………… 22 Discussion……………………………………………………………….. 25 Literature Cited………………………………………………………….. 29
CHAPTER 2: Relative contributions of color versus pattern to predator avoidance and mate attraction in Heliconius butterflies Introduction……………………………………………………………… 39 Methods………………………………………………………………….. 41 Results…………………………………………………………………… 50 Discussion……………………………………………………………….. 53 Literature Cited………………………………………………………….. 59
CHAPTER 3: Adaptive function of ultraviolet (UV) and fluorescence in Heliconius butterflies Introduction……………………………………………………………… 70 Methods………………………………………………………………….. 71 Results…………………………………………………………………… 74 Discussion……………………………………………………………….. 77 Literature Cited…………………………………………………….……. 79
CHAPTER 4: True UV color vision in a butterfly with two UV opsins Introduction……………………………………………………………… 92 Methods………………………………………………………………….. 94 Results…………………………………………………………………… 99 Discussion……………………………………………………………….. 104 Literature Cited………………………………………………………….. 107
SUMMARY OF DISSERTATION CONCLUSIONS …………………………. 116
iii LIST OF FIGURES
Page
Figure 1.1 Natural and artificial roosts of Heliconius erato with examples of bird attacks………………………………………………….…. 36
Figure 1.2 Reflectance spectra of natural and artificial butterfly wings used in discriminability calculations……………………………….…… 37
Figure 2.1 Color- and pattern-manipulated wing models experience different predation rates and different probabilities of inducing pre-mating approach behavior in male butterflies ……………………………. 66
Figure 2.2 Reflectance spectra of the natural and artificial model dorsal wing colors used in mate preference studies…………………..… 67
Figure 2.3 Evidence of predation attempts on butterfly models……………. 68
Figure 2.4 Graphical model of approach and courtship behavior…………… 69
Figure 3.1 Natural and artificial Heliconius butterfly wings and excitation and emission spectra of 3-hydroxy-DL-kynurenine (3-OHK)…… 83
Figure 3.2 Reflectance spectra of artificial H. erato butterfly models with and without UV…………………………………………………… 84
Figure 3.3 Reflectance spectra of artificial H. erato butterfly models with and without fluorescence…………………………………………. 85
Figure 3.4 Reflectance spectra of Eueides isabella non-fluorescing yellow wing pigment, and non-fluorescing H. erato butterfly models…… 86
Figure 3.5 Irradiance spectra of open sunlight and cloud cover, and the experimental cage under open sunlight and cloud cover…………. 87
Figure 3.6 Male and female H. erato butterflies approach and court UV- and fluorescence-manipulated butterfly models at varying rates……… 88
Figure 3.7 Specific male and female H. erato approach and courtship behaviors toward UV- and fluorescent-manipulated artificial butterfly models…………………………………………………… 89
Figure 3.8 Artificial butterfly models with and without UV and fluorescence experience similar predation rates in field studies………………… 91
iv
Figure 4.1 A male H. erato butterfly is shown on the light source apparatus during a trial………………………………………………………. 111
Figure 4.2 Proportion of correct choices to the trained wavelength stimulus of 390 nm for H. erato and E. isabella butterflies under varying light intensities……………………………………………………. 112
Figure 4.3 Proportion of correct choices to the trained wavelength stimulus of 380 nm for H. erato and E. isabella butterflies under varying light intensities……………………………………………………. 113
Figure 4.4 Proportion of correct choices to the trained wavelength stimulus of 400 nm for H. erato and E. isabella butterflies under varying light intensities……………………………………………………. 114
Figure 4.5 Proportion of correct choices to the trained wavelength stimulus of 436 nm for H. erato and E. isabella butterflies under varying light intensities……………………………………………………. 115
v LIST OF TABLES
Page
Table 1.1 Results from discriminability calculations for butterfly models using low light intensity and open habitat irradiance……………… 34
Table 1.2 Data representing attacks on butterfly models at field sites in Costa Rica and Panama, categorized by aggregation size…………. 35
Table 2.1 Achromatic contrasts for both the natural wing spectra and artificial wing gray spectra…………………………………………………… 64
Table 2.2 The ratios of approach and courtship occurrences are for male butterflies during paired mate choice trials………………………… 65
vi ACKNOWLEDGEMENTS
First and foremost I thank my graduate advisors, Dr. Adriana Briscoe and Dr. Robert Reed, for unparalleled guidance and support throughout my graduate career, and for recognizing my potential as a researcher. I admire their intelligence, accomplishments, and dedication, and I am grateful for their time and effort teaching me valuable skills that I will use throughout the rest of my career. This dissertation, along with my other academic achievements and successes as a graduate student, truly reflects their superior advising capabilities. This work would not have been possible without their contributions.
I am also very grateful to my advising committee members, Dr. Nancy Burley and Dr. Kailen Mooney, for their suggestions and helpful discussions about my research project ideas. They provided invaluable knowledge, especially with respect to project design and statistical analyses, for ecology and behavior-based assays. Thank you for pushing me to broaden my background in those disciplines.
A sincere thank you to my friends and family for helping me through this journey. I deeply thank my parents, Mary and David Finkbeiner, for their endless love and support throughout my lifetime preparing for a career as a scientist. They never once hesitated to help me reach my lifelong dream of becoming and entomologist and studying tropical butterflies, from taking me on collecting trips when I was five years old to letting me study abroad in Costa Rica. Thank you to my sisters, Karla and Brenda, for being patient with my insect obsession since I was two years old. And thank you to Santiago Meneses Ospina, the other bug-loving half of me, who has not only helped me with field work, statistics, and project ideas, but also provided mental and emotional support when I needed it most, even from the time applied to graduate school. Thanks for being there for me.
Many thanks to those who have provided additional research advice and aided in project development, including Dr. W. Owen McMillan with the Smithsonian Tropical Research Institute (STRI), and other STRI personnel and researchers in Panama, including Adriana Tapia, Megan Supple, Elizabeth Evans, Brett Seymoure, Barbara Huber, Moises Abanto, and Oscar Paneso; and to those with the Organization for Tropical Studies (OTS) at the La Selva Biological Station that helped make my field seasons a success. It goes without saying that I thank everyone who has assisted with butterfly model assembly and field work, and endured hot, humid days in the rainforest and greenhouses, rain or shine: Angela Oh, Nina Chiu, Ella Yuen, Maggie McDuffee, Jimena Golcher Benavides, Talia Gustafson, Micki Kellinger, and Jasmine Velez – a big thank you to all you for toughing it out in the field!
I am also grateful to Daniel Osorio for his ideas and recommendations, as well as Larry Gilbert, Jim Mallet, Chris Jiggins, Richard Merrill, Patricio Salazar, Johannes Spaethe, and Christian Salcedo for giving tips on making artificial butterfly models and/or advice working with Heliconius in the field. Thank you also to Michael D. Lee for contributing our hierarchical Bayesian analysis for Chapter 2, and to Michael Phelan, Kameryn Denaro, and Fabio Macciardi who have helped with statistical analyses; and thanks to Georg Striedter for his time and input as a member of my advancement to candidacy committee.
vii An exceptional thank you to Dave Krueger with UCI ImageWorks for aid in designing and printing artificial butterfly models, and for taking the time to show me how to work with Adobe Illustrator. Without his patience and expertise, three of my four dissertation chapters would not have been possible. I also thank Dmitry Fishman at the UCI Laser Spectroscopy Facility, and Milka Stakic and Suman Ranjit at the UCI Lab of Fluorescence Dynamics for help with measuring excitation and emission spectra for Chapter 3.
I also thank OTS and STRI for providing outstanding research facilities in some of the most diverse rainforests of the world, and to La Autoridad Nacional del Ambiente (ANAM, Panama) and El Ministerio del Ambiente, Energía, y Telecomunicaciones (MINAET, Costa Rica) for research permit approval. Thank you also to Paola Vargas with the Costa Rica Entomological Supply for providing happy, healthy butterflies for in-cage experiments at UC- Irvine, and to the USDA for approving our permits for butterfly importation.
Many thanks to both Briscoe Lab and Reed Lab members (Arnaud Martin, Emily Daniels, Kyle McCulloch, Aide Macias, Gil Smith, James Lewis) for providing feedback on manuscripts, presentations, and project ideas, as well as providing advice and suggestions regarding research and non-research-related challenges. I thank my fellow cohort members and other graduate students with the EEB department at UCI for making my time at the University enjoyable, and thanks for all the interesting conversations we have had throughout the years. I also thank my roommates Kim Makuch and Elena Liang for putting up with my crazy schedules and frequent traveling, and for listening when I needed advice. A big thanks to the furry friends in my life: Ruby, Max, and Meeko, for always being attentive, happy, entertaining pets to be around.
Thank you to The Royal Society for permission to include Chapter 1 of my dissertation, which was originally published in Proceedings of the Royal Society London B. Likewise, I thank John Wiley and Sons for permission to include Chapter 2 of my dissertation, originally published in Evolution.
And finally I thank my many funding sources; without them my dissertation (and especially field work) would not have been achieved: The National Science Foundation (NSF) Graduate Research Fellowship award no. DGE-0808392; NSF grant no. IOS-1025106 to A.D.B. and R.D.R.; National Geographic Society Young Explorer’s Grant (two grants); Smithsonian Tropical Research Institute Fellowship (five years); U. S. Department of Education GAANN Fellowship (two years); Organization for Tropical Studies Short-Term Fellowship; Sigma Xi Grants-in-Aid of Research (GIAR); and the University of California, Irvine (UCI).
viii CURRICULUM VITAE
Susan Diane Finkbeiner
EDUCATION
2015 University of California, Irvine (UCI) Ph.D. Ecology and Evolutionary Biology
2009 Cornell University, Ithaca, New York B.Sc. Entomology with honors distinction in research
APPOINTMENTS
(2015) Postdoctoral Research Associate, Boston University Teaching Assistant, University of California, Irvine (2009-2011) Teaching Assistant, University of California, Irvine (2009) Field Assistant, Smithsonian Tropical Research Institute, Panama (2006-2009) Research and Field Assistant, Entomology Department, Cornell University Undergraduate Teaching Assistant, Cornell University (2007-2008) Entomology Teacher, Rockford College Learning Center
FELLOWSHIPS AND GRANTS
(2014-2015) U.S. Department of Education GAANN Fellow (2010-2015) Smithsonian Tropical Research Institute (STRI) Fellow (2011-2014) National Science Foundation (NSF) Graduate Research Fellow (2014) National Geographic Young Explorer’s Grant (2012) Sigma Xi Grants-in-Aid of Research (GIAR) Grant International Society for Behavioral Ecology Travel Grant Smithsonian Institution Travel Award (2011) National Geographic Young Explorer’s Grant Organization for Tropical Studies (OTS) Short-Term Fellow (2010-2011) U.S. Department of Education GAANN Fellow
RELEVANT HONORS
(2014) UCI Ayala School of Biological Sciences Dr. William F. Holcomb Scholarship First place in student talk competition - Southwest Organismal Biology (SWOB) Conference (2011) President’s Prize Winner - Entomological Society of America (ESA) Conference (2010) OTS Ruggles Scholarship (2009) Honors Distinction in Research awarded from Cornell University (2005) U.S. Army Scholar Athlete (2005) Illinois State Scholar
ix PUBLICATIONS
Finkbeiner, S. D., and A. D. Briscoe. In prep. Butterflies use fluorescent signals in cloudy weather.
Finkbeiner, S. D., A. D. Briscoe, and R. D. Reed. 2014. Warning signals are seductive: Relative contributions of color and pattern to predator avoidance and mate attraction in Heliconius butterflies. Evolution. 68(12):3410–3420.
Finkbeiner, S. D. 2014. Communal roosting in Heliconius butterflies (Nymphalidae): Roost recruitment, establishment, fidelity, and resource use trends based on age and sex. Journal of the Lepidopterists’ Society. 68(1): 10-16.
Finkbeiner, S. D., A. D. Briscoe, and R. D. Reed. 2012. The benefit of being a social butterfly: communal roosting deters predation. Proceedings of the Royal Society London B. 279(1739): 2769-2776.
Finkbeiner, S. D., R. D. Reed, R. Dirig, and J. E. Losey. 2011. The role of environmental factors in the northeastern range expansion of Papilio cresphontes Cramer (Papilionidae). Journal of the Lepidopterists’ Society. 65(2): 119-125.
NON-PEER REVIEWED PUBLICATIONS
Finkbeiner, S. D. and L. Paulson. 2008. Prey manipulation in Centruroides margaritatus (Scorpiones: Buthidae). OTS database. Vol. USAP 2008.
Finkbeiner, S. D., A. Santana, and A. Corrales. 2008. Proboscis length affects handling time in butterflies foraging on Asclepias (Apocynaceae). OTS database. Vol. USAP 2008.
Corrales, A., S. D. Finkbeiner, A. Moran, L. Paulson, and H. Pollock. 2008. Water quality of aquatic ecosystems affected by agriculture as indicated by benthic macroinvertebrates. OTS database. Vol. USAP 2008.
x ABSTRACT OF THE DISSERTATION
Deconstructing visual signals in social butterflies
By
Susan Diane Finkbeiner
Doctor of Philosophy in Ecology and Evolutionary Biology
University of California, Irvine, 2015
Professor Adriana D. Briscoe, Co-chair
Professor Robert D. Reed, Co-chair
Visual signals represent one of the most common forms of communication in animals. It has long been known that visual signals play an important role in predator and mate recognition in many animal species. Visual signals can be expressed in terms of color (chromatic cues), brightness (achromatic cues), context (patterns), magnitude, ultraviolet (UV) reflectance, as well as fluorescence, and often times animal visual systems are specialized to discriminate between particular visual features that are more biologically relevant. My dissertation work examines these aspects using Heliconius butterflies. First I tested whether Heliconius erato communal roosting behavior confers a selective benefit in terms of predator avoidance through collective warning signaling, and explored how roost size influences predator behavior (Chapter 1). I found that magnitude, by means of roost size, plays a role in the effectiveness of roosts as anti-predator signals.
H. erato butterflies that convene in medium-sized groups are best protected from predation. Following roosting studies, I identified the relative importance of color versus
xi pattern signals for both predator avoidance and mate attraction by these butterflies
(Chapter 2). My results showed that color appears to be a more effective repel signal than pattern, and the same signals selected for by predators are most preferred by mates. This interaction between warning coloration (aposematism) and mate choice indicates cooperation between the visual signals that influence individual fitness. For my next project I investigated the adaptive function of UV and fluorescent signals in H. erato
(Chapter 3). I found that both signals are important for intraspecific signaling in
Heliconius and are likely maintained through sexual selection, but under cloudy weather conditions, UV signals become ineffective whereas fluorescence persists as a reliable signal. Finally, I used behavioral tests to determine whether Heliconius have true color vision in the UV range as a consequence of UV opsin duplication (Chapter 4). I found that butterflies were capable of discriminating between more than one UV wavelength under varying light intensities, supporting that they have true UV color vision, which may aid in the detection of their genus-specific UV and fluorescent wing pigment. This dissertation
(i) demonstrates how aposematic signaling may drive the evolution of social behavior in the context of visual ecology, (ii) shows how natural and sexual selection can work together to favor the evolution of specific animal phenotypes, and (iii) connects the evolution of specialized visual systems to specialized visual signals.
xii INTRODUCTION
Visual signals are among the most diverse and prevalent forms of communication in animals. They can serve multiple functions, including mate attraction and protection from predators (Endler 1992). Signals are variable and may be expressed in terms of color
(chromatic cues), brightness (achromatic cues), context (patterns), magnitude (i.e. signal repetition), ultraviolet (UV) reflectance, as well as fluorescence; and signals are commonly enhanced when animals spend time in close proximity with one another or in groups to communicate the same signal simultaneously. Visual signals can be directed toward one or multiple receivers, and are perceived best when the receiver’s visual system favors the detection of specific signals. Therefore, animal visual systems are often specialized to discriminate between particular visual features that are more biologically relevant.
Aposematism, commonly known as warning coloration, functions to provide a warning signal associated with unprofitability to predators, such as toxicity, unpalatability, or capture costs (Cott 1957; Guilford 1990; Ruxton et al. 2004). It represents a major theme in the evolution of animal phenotypes, and is a widespread trait found in many invertebrate taxa
-- often communicated visually through bright and conspicuous color patterns. Collective aposematism is a phenomenon in which multiple aposematic prey form aggregations to enhance the effects of warning coloration (Gamberale & Tullberg 1996; Riipi et al. 2001).
This is compelling because it serves as a nexus point between social behavior, the visual ecology of predator-prey interactions, and adaptation. It is often observed in insects and is considered a form of social behavior.
1 Communal roosting behavior in butterflies
Nearly half of all insect orders display some social cooperation, from informal sub- social interactions to intricate eusocial colonies. Thus, the evolution of insect social behavior has been a widely researched topic for over a century (Costa 2006). The vast majority of insect sociality research has focused on eusocial insects. Much less work has been done on sociality in non- colonial insects, and there is an especially conspicuous knowledge gap for the highly diverse order Lepidoptera (butterflies and moths). Although some research has been done with communal behaviors in lepidopteran larvae, much less is known regarding social behaviors in adults. Of interest here is a unique gregarious behavior exhibited by the non- migratory Heliconius passion-vine butterflies. Adults of many species of this genus form communal roosts in which they repeatedly gather at a particular location in their home range to roost for the night. This behavior has been hypothesized to confer two adaptive functions: anti-predator defense and/or information-sharing (Waller & Gilbert 1982; Mallet 1986). This cooperative behavior is also exceptional because the butterflies likely rely on visual cues and memory to locate roosts (Jones 1930; Mallet 1986; Salcedo 2010), rather than scent-marking and aggregate pheromones as seen in most other communal insects (Costa 2006). Published reports of roosting in Heliconius have been mostly descriptive (Waller & Gilbert 1982; Mallet
1986; Mallet & Gilbert 1995; Salcedo 2010), and few experimental projects have been undertaken to assess the evolutionary and ecological aspects of this behavior.
Heliconius butterflies are perhaps best known for their dramatic aposematic wing patterns and are a popular model system for studies of Müllerian mimicry, behavior, genetics, development, ecology, and evolution. The butterflies are chemically defended by consuming toxic Passiflora (passion-vine) host plants as larvae, and are thus considered model exemplars
2 of visually-mediated aposematism (Nahrstedt & Davis 1983, 1985; Engler-Chaouat & Gilbert
2007). A large literature related to this genus exists, with many studies examining the behavioral ecology of adults from this genus. In general, adult social behavior is uncommon in butterflies, yet the genus Heliconius boasts several unique behavioral adaptations: pupal mating, gregarious roosting, pollen-feeding for longevity, communal egg laying, and acoustic signaling (Boggs et al.1981; Mallet 1986; Deinert et al. 1994; Reed 2003; Hay-Roe & Mankin
2004). Despite the substantial amount that is known about Heliconius natural history, surprisingly little is known about their gregarious roosting behavior and its possible relationship to visual signaling and collective aposematism.
Diversity of warning signal elements in butterfly wing patterns
Predation is a key selective pressure maintaining aposematic color patterns in animals, often selecting against novel or rare phenotypes (Lindström et al. 2001; Comeault & Noonan
2011). This is especially apparent in butterfly mimicry systems since predators learn to avoid specific wing patterns (Benson 1972; Mallet & Barton 1989; Kapan 2001; Langham 2004;
Merrill et al. 2012). The vibrant wing patterns of Heliconius butterflies are highly characteristic and are composed of vivid colors (often red, black, and yellow), contrasting patterns, UV-reflective elements (Briscoe et al. 2010), fluorescence (Cockayne 1924), iridescence, and polarized reflectance patterns (Sweeney et al. 2003; Douglas et al. 2007). In other butterfly genera that do not employ such bright, aposematic colors, predator avoidance can be achieved through visual signals such as eyespots (Lyytinen et al. 2004; Stevens et al.
2007; Oliver et al. 2009; De Bona et al. 2015) and possibly iridescence (Doucet & Meadows
2009).
3 Although aposematism is a significant force driving the evolution of innumerable animal species, the magnitude and variety of the specific signals that contribute to aposematism remain poorly understood (Stevens 2007; Stevens & Ruxton 2012). Warning signals are often expressed visually, but are perceived in different ways by predators (Osorio et al. 1999). Therefore it is useful to know exactly which elements of an aposematic animal’s phenotype are being recognized and assessed by potential predators. Little work has been done focusing on specific visual signals that lend protection to aposematic animals. More rigorous work on this topic could very well steer the existing concept of visually-mediated aposematism from warning coloration to a broader notion of warning syndromes, which would include multimodal signals determined by obvious factors -- color and pattern -- as well as features less commonly considered such as UV signals and fluorescence. In order to understand the selective pressures driving the evolution of many colorful aposematic animal phenotypes, it is necessary to dissect the specific visual signals recognized by would-be predators.
Butterfly wing patterns and mate signaling
The visual signals displayed by animals can serve other functions in addition to predator avoidance, such as mate signaling, which can be an equally important selective pressure. However signals that aid in mate attraction might also result in increased detection by predators (Promislow et al. 1992), and (on the contrary) visual signals used to deter predators could interfere with intraspecific communication (Burns 1966; Estrada & Jiggins
2008). Predator detection, though, is less risky for aposematic animals whose appearance is recognized as unprofitable. Therefore it is important to examine any cooperation or conflict
4 between visual signals used in both predator avoidance and mate preference, which can help identify how natural and sexual selection work together to favor the evolution of particular phenotypes.
In Heliconius, we expect that the same visual signals used to attract mates are also effective in deterring predators. Mate recognition in butterflies can be attributed to visual signals such as iridescence and UV reflectance (Silberglied & Taylor 1978; Rutowski et al.
2005, Kemp 2007), polarized light (Sweeney et al. 2003), and attractive color patterns, which are similar to signals likely used by predators to recognize unprofitable prey. A number of behavioral studies demonstrate color-based mate preference in butterflies (Fordyce et al.
2002; Ellers & Boggs 2003; Robertson & Monteiro 2005). Assortative mating, or a nonrandom mating pattern where individuals prefer to mate with others of their own genotype and/or phenotype, occurs frequently in Heliconius and appears to be heavily influenced by color (Jiggins et al. 2001; Jiggins et al. 2004; Kronforst et al. 2007; Chamberlain et al. 2009;
Melo et al. 2009). Heliconius butterflies are known to use color vision in the context of feeding in the long-wavelength and other parts of the visible light spectrum (Swihart 1971;
Zaccardi et al. 2006), but color discrimination in the long-wavelength range with respect to mate recognition has yet to be confirmed. Evidence suggests that male Heliconius butterflies have a strong attraction toward the color found on the forewing band (Kronforst et al. 2006;
Merrill et al. 2011), but the importance of pattern alone (in the absence of colors) in assortative mate preference has not been examined.
Fluorescent signals in butterflies
It is also unknown to what extent fluorescence may play a role for predator and mate
5 recognition in butterflies, and how important UV acts as a signal specifically for Heliconius.
In insects, fluorescence has been reported in at least five orders and over 100 species (Welch et al. 2012). Although the first discovery of fluorescence in any insect was that of butterfly fluorescence in 1924 (Cockayne 1924), the question of whether butterflies use fluorescence for communication via signaling remains unresolved despite numerous studies investigating the physical properties of butterfly fluorescence (Kumazawa et al. 1996; Vukusic & Hooper
2005; Vigneron et al. 2008; Wilts et al. 2012). Fluorescent pigments absorb short wavelengths
(UV or blue) and re-emit them at longer wavelengths that trigger photoreception, creating a glowing effect (Hausmann et al. 2003). Under changing terrestrial habitat spectral environments (forest or open), fluorescence may function as a more reliable signal than other color signals, as it has shown to be effective under various aquatic light environments and at different water depths for mantis shrimp (Mazel et al. 2004). Other animals such as birds use fluorescence to enhance mate signaling (Arnold et al. 2002), and fluorescence affects male- male interactions in reef fish (Gerlach et al. 2014). Because so many different groups of butterflies (including Heliconiine) contain fluorescent wing elements (Cockayne 1924;
Kumazawa et al. 1996; Vukusic & Hooper 2005), some of which are sexually dimorphic
(Phillips 1959), it is likely butterflies are capable of detecting fluorescent signals. However the adaptive function of fluorescence in butterflies has yet to be determined, along with whether or not fluorescence is important as an anti-predatory signal.
Specialized visual system for UV discrimination
Finally, given recent research on the visual system in Heliconius butterflies, the implication is that the butterflies are capable of discriminating between multiple color
6 wavelengths in the UV range (300-400 nm). Butterflies typically have only one UV opsin
(Vanhoutte et al. 2002; Briscoe et al. 2003; Sauman et al. 2005; Koshitaka et al. 2008), however in Heliconius, an opsin duplication event has occurred in the UV range based on molecular evidence (Briscoe et al. 2010). Because of this second UV opsin, the butterflies are expected to detect differences between more than one UV wavelength regardless of wavelength intensity. This opsin duplication event occurred in conjunction with the evolution of a unique yellow UV and fluorescent pigment in the wings, 3-hydroxy-DL-kynurenine (3-
OHK), suggesting that it may play a role in conspecific recognition (Bybee et al. 2012).
Heliconius are part of a large mimicry complex that includes both within-genus mimics that are unpalatable (Müllerian mimics), as well as non-Heliconius mimics, some of which may be palatable (Batesian mimics). Non-Heliconius mimics do not contain 3-OHK pigment, and therefore it would be favorable to have two UV opsins for discrimination between yellow pigments on mimics versus conspecifics. Whether or not Heliconius are capable of true color vision UV range has yet to be confirmed experimentally, and will show how these butterflies use UV vision in the context of foraging and possibly intraspecific communication, providing insight on the adaptive function of UV opsin duplication in animals.
Dissertation overview
The goal of my dissertation is to investigate the nature of aposematic signaling in a group of butterflies that show a rare type of gregarious roosting behavior, dissect the visual signals associated with predator and mate signaling in these animals, and provide experimental evidence for UV wavelength discrimination in a butterfly with a specialized visual system and special wing pigmentation. First I tested whether Heliconius roosting
7 behavior confers a selective benefit in terms of predator avoidance through collective aposematism, and explored how roost size influences predator behavior (Chapter 1).
Following roosting studies, I identified the relative importance of color versus pattern
(Chapter 2), then UV reflectance and fluorescence (Chapter 3), for both predator avoidance and mate recognition in Heliconius butterflies. Finally, I determined whether Heliconius have true color vision in the UV range as a consequence of UV opsin duplication, which may aid in the detection of their genus-specific UV and fluorescent wing pigment (Chapter 4). This work
(i) provides insight on the types of ecological and evolutionary pressures that contribute to social behavior in historically solitary animals, (ii) allows us to understand how aposematic signaling may drive the evolution of social behavior in the context of visual ecology, (iii) presents information on the relative contributions of specific visual signals that result in predator avoidance and mate attraction, (iv) shows how both natural and sexual selection can work together to favor the evolution of specific animal phenotypes, and (v) demonstrates the adaptive significance of UV opsin duplication in animals, connecting the evolution of specialized visual systems to specialized visual signals.
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13 CHAPTER 1: Anti-predator benefits of communal roosting behavior in Heliconius butterflies
INTRODUCTION
In 1867 the naturalist J. A. Allen first described the spectacular aggregations of migratory monarchs, and was thus the first to report the phenomenon of communal roosting in butterflies (Scudder & Allen 1869; Brower 1995). Shortly thereafter William Henry Edwards, the entomologist who inspired Bates and Wallace to visit the Amazon, reported communal roosting in the tropical Heliconius passion-vine butterflies (Edwards 1881). Since the mid- nineteenth century this unusual behavior has generated a great deal of scientific and popular interest. After 140 years of work on butterfly roosting, however, it still remains unclear what the benefit of being a social butterfly is. Here we test the major hypotheses for why
Heliconius passion vine butterflies roost communally, and present experimental data assessing the adaptive function of this behavior.
Communal roosting is observed in many types of animals, including birds, bats, and primates (Ward 1965; Soini 1987; Lewis 1995; Merkel & Mosbech 2008), and is especially widespread in insects, having been observed in bees, wasps, beetles, dragonflies, butterflies, and moths (Pearson & Anderson 1985; DeVries et al. 1987; Salcedo 2010). In butterflies, communal roosting is described as “a behavior in which individuals aggregate quiescently in close proximity to each other at a site for more than a few hours” (DeVries et al. 1987). This behavior is known primarily from the heliconiines, acraeines, ithomiines, and danaiines
(Benson & Emmel 1973; Turner 1975). Many species of Heliconius in particular have been observed to form communal roosts in which adults repeatedly gather in a particular location in their home range to roost for the night (Figure 1.1a). Butterflies arrive at their roost sites as
14 early as three hours before sunset, and depart from roosts within the first two hours after sunrise. Roost-mates are generally conspecifics, but sometimes different species – often
Müllerian co-mimics – roost together (Mallet 1986a). The evolution of communal roosting behavior in Heliconius is believed to be facilitated by unpalatability, slow reproductive rate
(Erlich & Gilbert 1973), limited learned home range (Turner 1975; Mallet 1986b), and long lifespan due to pollen consumption (Gilbert 1972; Boggs et al. 1981).
Heliconius butterflies are well known for their brightly colored wing patterns and their unpalatability due to cyanogenic glycosides (Engler-Chaouat & Gilbert 2007). Because of these features, Heliconius butterflies serve as a textbook example of warning signaling – also known as aposematism. Aposematism is a major theme in the evolution of animal phenotypes where its principle function is to provide warning signals associated with unprofitability to predators, such as toxicity, unpalatability, or capture costs (Cott 1957; Guilford 1990; Santos et al. 2003). Aposematism is widespread in invertebrates and is often achieved through visual signaling via conspicuous color patterns. Collective aposematism is a phenomenon in which aposematic prey form aggregations to enhance the effects of warning signals (Gamberale &
Tullberg 1998; Riipi et al. 2001). Despite the substantial amount that is known about
Heliconius natural history, little is known about their communal roosting behavior and its possible relationship to collective aposematism.
There is a substantial literature on Heliconius roosting (Jones 1930; Turner 1975;
Young & Thomason 1975; Mallet 1980; Waller & Gilbert 1982; Mallet 1986a; Mallet &
Gilbert 1995; Salcedo 2011), however relatively few experimental studies have been done to address the function of this behavior. Although the adaptive consequences of roosting remain unclear, it is unlikely that aggregations are involved with thermoregulation (Salcedo 2010),
15 kin selection (Mallet 1986a), or mating (females usually mate once in their lifetime, within hours or days after eclosion; Gilbert 1976; Schulz et al. 2008). The favored explanations have been narrowed to two major hypotheses: information-sharing and/or anti-predator defense.
The information-sharing hypothesis proposes that new roost-mates, presumably related individuals, follow experienced members to food sources from the roost (Gilbert 1975; Waller
& Gilbert 1982). This form of information sharing is a common behavior in other communal animals such as birds (Ward & Zahavi 1973; Dall 2002). Conversely, the anti-predator hypothesis suggests predators avoid Heliconius aggregations as a result of collective aposematism or predator confusion (Turner 1975; Gillett et al. 1979; Mallet 1986a). In other aposematic insects, gregarious behavior contributes to collective enhancement of warning signaling, resulting in more effective predator deterrence (Benson 1971; Edmunds 1974;
Vulinek 1990; Gamberale & Tullberg 1998). Another potential anti-predator mechanism is the dilution effect, often known as “safety in numbers”, which posits that the probability of a single individual being attacked in a group is lower with increasing density (Hamilton 1971;
Bertram 1978; Turner & Pitcher 1986; Sillén-Tullberg & Leimar 1988).
In field studies in Panama and Costa Rica we tested these hypotheses to determine why Heliconius passion-vine butterflies assemble in communal roosts. To test whether
Heliconius butterflies rely on roosts as information-sharing centers, we examined following behavior by butterflies during departures from natural aggregations. The anti-predator defense hypothesis was tested using avian-indiscriminable artificial butterfly models placed singly and in aggregations in the forest. Following the predation study, we investigated whether naturally occurring roost size corresponds with optimal roost sizes inferred from experimental data.
16 METHODS
Field Sites
All data collection was completed in Costa Rica and Panama. Field sites for this work were chosen based on the abundance and accessibility of Heliconius butterflies and communal roosts. The Panama sites were part of the Smithsonian Tropical Research Institute; we used areas in Gamboa and Soberanía National Park along Pipeline Road. Data were collected in
Panama from June through September of 2010 and 2011 during the rainy season. The 2010 visit resulted in natural roost data collected from H. erato, and the 2011 visit resulted in the predation experiment data. In Costa Rica we worked at the Organization for Tropical Studies’
La Selva Tropical Biological Station in Sarapiquí. La Selva was visited in April and May of
2011, during the end of the dry season into the beginning of the rainy season. This site was used for collecting natural roost data from H. sara and model predation experiments.
Natural roost observations
To assess the information-sharing hypothesis, which predicts that butterflies use roosts to learn the locations of foraging sites from other roost-mates, we observed following behavior of H. erato and H. sara individuals departing natural roosting aggregations.
Following was confirmed only if a butterfly was observed departing the roost with another roost-mate to subsequently arrive at a flowering plant with that same roost-mate. The roosts were within 30 meters of the first visited flowering plant, and it was feasible to follow butterflies to these plants. We began all observations approximately 30 minutes before sunrise, before butterflies left to forage, and stayed until only one individual remained. All H. erato roost members were given unique identification numbers using a Sharpie® marker, and
17 were sexed and age determined based on wing wear (Karlsson 1987). Butterflies were captured and marked after departing their roosts to prevent them from associating the roost with danger (Mallet et al. 1987). Average roost sizes were determined by recording the number of individuals in each roost nightly.
Models
We used artificial butterfly models to test the hypothesis that Heliconius roosts provide an anti-predatory benefit. Wing images were designed in Adobe Illustrator using high-resolution scans of ventral H. erato petiverana wings as a reference. Model butterfly wings were printed on Whatman filter paper, which produces reflectance spectra close in brightness to actual wings, using an Epson Stylus Pro 4880 printer with UltraChrome K3 ink.
A 3-hydroxy-DL-kynurenine (3-OHK) pigment solution of 1.0 mg 3-OHK dissolved in 100
µl of methanol was applied to the yellow bands on the hindwing to provide accurate UV reflectance, since printed yellows do not accurately mimic Heliconius yellow in the shape of their reflectance spectra. 3-OHK is the same yellow wing pigment as found in the wings of the butterflies themselves (Reed et al. 2008; Briscoe et al. 2010). Portions of the artificial wings were dipped in clear wax to allow imprints of beak and bite marks, then KRYLON® matte finishing spray was applied lightly (before spectra measurements were taken) to coat the 3-OHK with a waterproofing element. Model abdomens were made of Newplast® plasticine.
Birds, in particular jacamars, flycatchers, and tanagers, are major Heliconius predators
(Benson 1971; Waller & Gilbert 1982; Chai 1986; Pinheiro 2003; Langham 2004; Pinheiro
2011). Therefore, artificial butterfly models were designed and assessed using tetrachromatic
18 bird color-vision models in order to ensure that avian predators would find color stimuli presented by the models indiscriminable from actual butterflies. Reflectance spectra of yellow, pink, and black from the models and the ventral surface of natural H. erato petiverana wings were measured using an Ocean Optics USB2000 fiber optic spectrometer. A deuterium- halogen tungsten lamp (DH-2000, Ocean Optics) was used as a standardized light source, and measurements were taken using a bifurcating fiber cable (R400-7-UV/VIS, Ocean Optics).
The axis of the illuminating and detecting fiber was at an elevation of 45° to the plane of the wing and pointed left with respect to the body axis for every measurement. A white spectralon standard (WS-1-SL, Labsphere) was used to calibrate the spectrometer. Spectra measurements from the fiber optic spectrometer were processed using MatLab Software (see Briscoe et al.
2010). The quantum catches for stimuli (Kelber et al. 2003) were calculated and discriminability between artificial models and natural wing reflectance spectra was determined using tetrachromatic bird-vision models from Vorobyev & Osorio (Vorobyev &
Osorio 1998). The comparisons were made using the blue tit (Parus caeruleus) and chicken
(Gallus gallus) cone sensitivities, which represent the UV- and violet-type avian visual systems respectively. Low light intensity and open habitat irradiance spectra were used
(Bybee et al. 2012). All spectral comparisons represented by an average of wing measurements (n=12) fell below the threshold of one Just Noticeable Difference (JND)
(Figure 1.2, Table 1.1), therefore the reflectance spectra of models and actual butterfly wings were inferred to be indiscriminable to birds.
Predation Experiments
Butterfly models were tied to branches with thread in appropriate roosting habitats and
19 in natural roosting postures (Mallet 1986a; Salcedo 2010; Figure 1.1b). At our Costa Rica field site a total of 320 aggregations containing five butterflies each and 320 single butterflies were used for the first predation experiment. The models were placed in 80 different forest sites each containing four roosts and four single individuals. All 80 sites were at least 250 m apart to control for the home range territories of primary Heliconius avian predators. Predator home range sizes vary between 100-250 m and have been determined by other researchers through radio-tracking and minimum convex polygon (MCP) modeling (flycatchers, Ning et al. 2007); harmonic distance method and core area use (tanagers, Samuel et al. 1985); and observation (tanagers, Buskirk et al. 1972; jacamars, Pinheiro et al. 2003, C. E. G. Pinheiro, pers. comm., L. E. Gilbert, pers. comm). Tree Tanglefoot® was applied to the base of plant stems containing artificial butterflies to avoid removal or attack of the models by ants and other small arthropods, and it was also effective in preventing small vertebrates such as lizards from reaching the butterfly models (Dial & Roughgarden 1995).
The models were left at their sites for a total of 96 hours (four days), and each model was examined daily for predation evidence and replaced if attacked. None of the 80 sites were used twice in the study because predator forgetting time varies between bird species, and is affected by prey conspicuousness and distastefulness (Servedio 2000; Speed 2000; Ruxton et al. 2004), both difficult to measure for this project. A butterfly was considered attacked if damage to the abdomen and wings appeared in the form of beak marks and/or large indentations in the abdomen (Figure 1.1c-d; see also Brodie 1993, Stobbe & Schaefer 2008).
Small chew-like marks, likely from mandibular insects such as grasshoppers, were not considered in the data analyses. If a model was attacked twice on two separate days it was only counted as a single attack. If multiple butterflies in a roost were attacked, this was also
20 counted as a single attack (i.e. each roost was treated as a unit), because in nature when a roost is disturbed most or all individuals depart from the roosting site (Mallet 1986a; Salcedo
20011; pers. obs.), thereby reducing the probability of further predation attempts on individual roost-mates. Predation differences were analyzed using a Wilcoxon signed-rank test with continuity correction, using each site as a sample.
To assess the per capita attack risk of individual butterflies, single (focal) individuals were randomly selected from each roost to compare attack rates under the conservative assumption that one attack leads to the dispersal of the other roosting butterflies. For roosts of one, this single individual was the focal individual. The binomial response of attack (yes, no) was modeled as dependent upon roost size using generalized linear models. In these analyses, site was included as a random effect to account for potential non-independence among replicate roosts within sites.
As a control for our models, we compared the attack rate on models with real wings
(and plasticine abdomens) to the attack rate on models with artificial wings, using five forest sites separated 250 meters apart, each with four models with real wings and four models with artificial wings. They were left for 96 hours and checked daily for attacks. We found no difference in attacks between real-wing models and artificial models (Wilcoxon signed-rank test W = 249.5, p = 0.836, n = 20).
The second predation study, conducted in Panama, investigated the association between roost size and predation frequency. This was tested using the same artificial butterfly models described above. One hundred forest sites were chosen, approximately 250 meters apart, and each of these sites contained two roosts of two, five, and ten butterflies. This totaled 600 artificial roosts: 200 roosts for each treatment. Roosts were removed after four
21 days, each of the 100 sites were used only once, and attacked models were replaced when necessary. If a roost was attacked more than once or if more than one butterfly in the roost was attacked, it was only counted as one attack, thus each roost was considered as a single unit in the analysis. These predation data were analyzed using a Kruskal-Wallis multiple comparison test with a post hoc Bonferroni correction, using each site as a sample. Individual per capita attack risk was determined by comparing attack rates between randomly selected single (focal) individuals in each roost treatment, and the binomial response of attack was modeled as dependent upon roost size using generalized linear models, with site included as a random effect. The post hoc tests for the significance of pairwise comparisons were made using a Tukey test.
We determined at what time of day roosts are most susceptible to attack to gain further information about the roost predators. This study was conducted with 100 artificial roosts in
Panama: 52 roosts of two placed randomly along two trails in Soberanía National Park, and the remaining 48 roosts were already being observed for predation data (16 more roosts of two, five, and ten each). The artificial roosts were checked for attacks every three hours from
6:00 a.m. (15 minutes prior to sunrise) to 6:00 p.m. (just before sunset) for nine days.
RESULTS
Observations of roost departure following
To assess whether Heliconius butterflies rely on communal roosts as information- sharing centers, we observed following behavior during morning roost departures. Of 256 H. erato departures by at least 66 unique individuals from nine different roosts, only one instance of following from the roost to a flowering plant was observed (Wilcoxon signed-rank test W =
22 256, p < 0.0001, n = 256, based on the null hypothesis that there is no difference between the number of butterflies that do and do not follow). Additionally, out of 74 H. sara butterfly departures from at least 25 unique individuals and three different roosts, we observed no incidence of following. When butterflies departed roosts in the morning occasionally more than one individual would leave at the same time, but they were never observed to follow one another. Most of the time the butterflies left individually, even when there was a disturbance event.
Lantana and Psychotria plants, considered to be key Heliconius resources, were common at our study sites, and it is important to note that spatial distribution and density of nectar and pollen sources may influence whether following happens. We observed that many roosting butterflies shared the same flower resources and followed each other between flowering plants, as previously described by Waller and Gilbert (1982). As well, on multiple occasions we observed a new recruit following an established roost member to the aggregation, suggesting following behavior may play a role in roost recruitment.
Observations on roost size and proximity
The average roost size in H. erato was observed to be 4.3 individuals (SD = 1.6, n =
233 observations across nine natural roosts) from roosts in Gamboa, Panama. It was common to find multiple roosts within fifteen meters of each other, some as close as three meters apart, and in line-of-sight from one another in a given part of the home range. We observed this in both H. erato and H. sara. When butterflies of H. erato were exercising pre-roosting behavior, the butterflies often interacted with one another before convening at their preferred roosts.
23 Effect of roost size on predation frequency
To determine whether communal roosts provide an anti-predatory benefit, we first tested whether there is a difference in predation between single butterfly models or models placed in aggregations of five. We observed a very strong difference in attack frequencies between roosting and solitary butterflies. Of 320 artificial H. erato roosts, only 25 were attacked compared to 68 attacks on 320 single individuals (Wilcoxon signed-rank test W =
4141.5, p = 0.000262, n = 80 sites; Table 1.2). Individual attack risk also differed significantly between roosts of one (single butterflies) and roosts of five (F1,559 = 36.85, p <
0.0001, n = 640 roosts total), with 21.3% of focal individuals being attacked in roosts of one but only 3.4% of focal individuals being attacked in roosts of five (Table 1.2).
Considering the difference we found in predation between single butterflies and roosts, we decided to investigate whether the predator deterrence effect was similar across roosts of different sizes (Table 1.2). We found significantly higher predation on roosts of two and ten than on roosts of five (Kruskal-Wallis test x2 = 8.7356, p = 0.0127, n = 100 sites). The post hoc Bonferroni correction showed that roosts of ten were attacked more than roosts of five (p = 0.016), and roosts of two were attacked more than roosts of five (p = 0.028). There was no significant difference in predation frequency between roosts of two and ten (p =
1.000). Individual attack rate also differed significantly between the three roost sizes (F2,498 =
5.51, p = 0.0043, n = 600 roosts total), with attack rates of focal individuals in roosts of two, five, and ten being 9.5%, 1.5%, and 4.5% respectively (Table 1.2). Adjusting significance levels to account for multiple comparisons, Tukey tests showed that a single butterfly in a roost of two has a higher attack risk than a single butterfly in a roost of five (p = 0.00064) but
24 there is no difference in individual attack risk between roosts of five and ten butterflies (p =
0.22), or between roosts of two and ten butterflies (p = 0.13).
Timing and nature of predation
We sought to determine at which time of day roosts are most susceptible to attack.
We found that all attacks occurred during the morning hours, also observed in natural roosts by Mallet (1986a). Ten out of twelve attacks, from 100 different artificial roosts, occurred between the hours of 6:00 a.m. and 9:00 a.m., and two attacks occurred between the hours of
9:00 a.m. and 12:00 p.m. Triangular beak marks observed in the model abdomens supports previous findings (Pinheiro 2003; Langham 2004; Pinheiro 2011) that birds are the primary predators of Heliconius. This is further supported since all attacks on models occurred between the hours of 6:00 a.m.-12:00 p.m. when birds are most active (Buskirk et al. 1972;
DesLauriers & Francis 1991).
DISCUSSION
In this study we assessed the two major hypotheses for explaining why Heliconius butterflies participate in communal roosting behavior. We found no support for the information-sharing hypothesis because there was little evidence of roost-mates following each other to resources upon departure from roosts. These findings are in agreement with
Mallet (1986a), who observed a similar lack of following and even a predictable tendency for roost-mates to visit different flowers.
In contrast, we found very strong support for the anti-predator defense hypothesis. Our field experiments in Costa Rica using avian-indiscriminable butterfly models showed
25 predation attempts on singly placed models were nearly three times higher than predation attempts on roosts of five models, and the predation risk for a single butterfly is over six times the per capita predation risk for an individual butterfly in a roost of five (Table 1.2). A second field experiment in Panama showed the same trend, with attack rates more than twice as high on roosts of two versus five, and individual risk over six times higher in a roost of two than a roost of five (Table 1.2). Surprisingly, however, the Panama experiment also showed that attacks on roosts of ten were three times as high as on roosts of five (Table 1.2), thus suggesting the predator deterrence effect may be weak or non-existent in large aggregations.
In the Panama experiment the greatest individual fitness benefit was seen in roosts of five, with an individual predation risk of 1.5%, however individuals in roosts of ten benefited only slightly less (not significant) than those in roosts of five (individual risk of 4.5% in roosts of ten). Therefore, even though roosts of ten did not enjoy a significantly decreased predation rate compared to roosts of two or five, a simple dilution effect (Bertram 1978) would still favor large roost sizes.
Our field studies suggest that the most beneficial minimum roost size, with respect to group advantage, may be around five individuals. This is because our experimental aggregations of five models experienced the lowest overall attack rates and also offered the lowest per capita attack risk for individuals. Interestingly, this experimentally determined minimum roost size corresponds closely to naturally observed H. erato roost sizes (4.3). This correspondence implies that predator deterrence, coupled with the dilution effect, could help explain roost sizes observed in natural populations. An optimal or minimum roost size may be important for predator deterrence when butterfly densities are too low for assembling in larger
26 aggregations, however roost sizes are probably influenced by foraging and resource availability as well.
Since medium-sized roosts provide an anti-predatory benefit through collective aposematism, it is unclear why larger aggregations appear to lose their ability to deter predators. It is possible that solitary individuals or very small roosts are too small to communicate an effective warning signal, while very large roosts may be conspicuous enough to attract naïve predators. In support of this idea Salcedo (2011) noted that the most frequent predator disturbances on H. sara roosts occurred on the largest aggregation studied (10-16 individuals) suggesting that oversized aggregations of Heliconius may increase the frequency of predator attacks. Although there is much evidence that predator wariness and aggregation- induced phobias increase with the size of aposematic prey aggregations (Ruxton et al. 2004), greater aggregation distinctiveness increases detectability costs and, in some cases, larger aggregation sizes of defended animals results in higher predation (Riipi et al. 2001; Lindstedt et al. 2011). There may be other costs to forming larger groups such that small movements made by other butterflies could produce incidental disturbances or “false alarms” causing unexpected or premature roost departures, but this would not explain higher predation on larger roosts from our experimental data.
We propose that it is no coincidence that multiple roosts are found in the same location in a home range and often in line-of-sight from one another. We have observed this in H. erato, H. sara, H. melpomene, and H. charithonia, with some roosts neighboring the roosts of heterospecifics (in Costa Rica). Others have observed this Heliconius behavior of preferentially forming smaller aggregations as well (Mallet 1986a; Salcedo 2006; C. Boggs,
Pers. Comm). Salcedo (2011) proposes these may be early-stage aggregations made up of
27 individuals who have not yet located a larger roost. In contrast, however, our field observations of pre-roosting interactions between butterflies from different roosts suggests the butterflies are aware of other roosts in their home range yet still choose to join smaller aggregations, despite plenty of substrate (i.e. dry branches and twigs) to sustain much larger aggregations. Based on the assumption that individual fitness should increase with larger aggregations due to a reduced per capita predation risk, again it is unclear why local butterflies do not simply choose to form very large roosts. There is the possibility that an interaction among roosts is introduced so that if individuals in one group are attacked the predator is inhibited from attacking individuals in other groups (Sillén-Tullberg & Leimar
1988). This repeated warning display could therefore facilitate rapid learning in naïve birds whose feeding areas may include multiple Heliconius roosting sites (Poulton 1931; Tuskes &
Brower 1978). It is also possible that very large roosts could attract high enough levels of predation to cancel out the dilution benefit, although experimental work is required to test this idea.
Here we show that Heliconius butterflies do not rely on communal roosts as information-sharing centers. Instead, our field studies indicate that this behavior confers an anti-predatory benefit at both the individual level (predator dilution) and group level
(collective aposematism), and attack risks vary between individuals in different aggregation sizes. This correspondence suggests that predation may be the key selective pressure maintaining communal roosting in Heliconius, thus providing insight into the types of ecological pressures that contribute to the evolution of social behavior in historically solitary animals.
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33 Table 1.1. Results from discriminability calculations using low light intensity and open habitat irradiance. Comparisons were made using the blue tit (Parus caeruleus) and chicken
(Gallus gallus) cone sensitivities and are based on average values (n=12). Spectra comparisons fell below the threshold of one Just Noticeable Difference (JND). FV=Forewing ventral, HV=Hindwing ventral; L=Light, D=Dark.
Comparisons FV-L pink FV-D pink vs. HV yellow vs. FV black vs. HV black vs. vs. model model pink model yellow model black model black pink JNDs P. caeruleus 0.597 0.374 0.736 0.336 0.440 JNDs G. gallus 0.556 0.424 0.858 0.315 0.533
34 Table 1.2. Data representing attacks on butterfly models at field sites in Costa Rica and
Panama, categorized by aggregation size. Roost attack risk was calculated by dividing attacked roosts by the overall number of roosts used in that treatment. Individual attack risk was determined by comparing attack rates between randomly selected single (focal) individuals in each roost treatment, based on the assumption that one attack leads to the dispersal of the other roosting butterflies. Probability values indicated by asterisk: *p < 0.05,
**p < 0.001, ***p < 0.0005.
Aggregation size Total Roosts Attack risk Attack risk observations attacked (per roost) (per individual)
Single individuals 320 68 21.3% 21.3% }*** }*** Roosts of five 320 25 7.8% 3.4%
RicaCosta
Roost of two 200 21 10.5% 9.5%
}* }** Roost of five 200 8 4.0% 1.5% * Panama } Roost of ten 200 24 12.0% 4.5%
35
Figure 1.1. Natural (a) and artificial (b) roosts of Heliconius erato. (c) Beak pinch at end of model abdomen, and triangular beak mark imprint on wax wing (indicated by arrowhead). (d) Dorsal view of abdominal beak pinch.
36
Figure 1.2. Reflectance spectra of natural and artificial butterfly wings used in discriminability calculations. Shown are the mean values and standard errors (each n =
37 12). Graphs include a ventral image of Heliconius erato petiverana with circled regions indicating where wing reflectance measurements were taken. (a) Yellow reflectance spectra. (b) Pink reflectance spectra, comparisons made using lightest (A) and darkest (B) pink regions on the wing. (c) Black reflectance spectra, comparisons made using both fore- (A) and hindwing (B) regions.
38 CHAPTER 2: Relative contributions of color versus pattern to predator avoidance and mate attraction in Heliconius butterflies
INTRODUCTION
Animals display a variety of visual signals that serve multiple functions, including predator avoidance and mate signaling (Endler 1992). Sometimes, however, there may be interference between these signals. For instance, signals that aid in mate attraction frequently cause a higher risk of detection by predators (Promislow et al. 1992), while visual signals used to deter predation may also interfere with intraspecific communication (Burns 1966;
Estrada & Jiggins 2008). Warning signaling – often referred to as aposematism – is a recurring phenomenon in the evolution of animal phenotypes where its principal function is to provide a signal advertising unprofitability to predators (Cott 1957; Guilford 1990; Ruxton et al. 2004). Warning signals are often communicated visually through conspicuous colors and patterns, and although these signals are a significant force driving the evolution of many species, the relative importance of specific visual features contributing to aposematism remains little explored (Stevens 2007; Stevens & Ruxton 2012). Likewise, the evolutionary interplay between selection for warning signals and selection for other types of signals, specifically mating signals, also needs to be addressed in more depth. If the same visual signals have similar influence on predator avoidance and mate attraction, then there would be support for an honest signaling model (especially in the context of sexual signals) where information conveyed by an animal is useful to the receiver and can in turn increase its fitness
(Zahavi 1975).
Neotropical passion-vine butterflies of the genus Heliconius have highly characteristic wing markings composed of vivid colors and contrasting patterns. The butterflies are
39 chemically defended by cyanogenic glycosides (Engler-Chaouat & Gilbert 2007), and thus represent a case of visually-mediated aposematism. Previous studies have demonstrated the tendency of avian predators to attack unrecognized Heliconius morphs (Benson 1972; Mallet
& Barton 1989; Kapan 2001; Langham 2004; Merrill et al. 2012), but it remains unknown what specific coloration features the predators use for prey recognition and how these features interact with the butterflies’ mating signals. Heliconius butterflies have been shown to demonstrate assortative mating, or a nonrandom mating pattern where males and females prefer to mate with others of their own genotype and/or phenotype. Across the genus, assortative mating appears to be heavily influenced by wing color (Jiggins et al. 2001; Jiggins et al. 2004; Kronforst et al. 2007; Chamberlain et al. 2009; Melo et al. 2009). For butterflies and other animals, chromatic features (i.e., hue and saturation) are generally used for object identification and detection, whereas achromatic features (i.e., brightness, not hue and saturation) may play a significant role in detection under low-light conditions (Maier 1992;
Vorobyev & Osorio 1998; Osorio et al. 1999; Kelber et al. 2003).
To determine to what extent warning signaling covaries with intraspecific signaling, we assessed the importance of color and pattern for both predation and mate selection in
Heliconius erato butterflies. We define colors as consisting of hue, saturation, and brightness, and pattern as the size, shape, and location of patches (which can be chromatic, achromatic, or both), that are displayed on the wing. Here we aim to answer four questions: 1) What role does color play in recognition of H. erato by experienced predators and conspecific males? 2)
What role does pattern play in recognition of this species by experienced predators and conspecific males? 3) Is color more effective than pattern in recognition by experienced predators and conspecific males? 4) To what extent might color and pattern features have
40 interfering, or parallel, effects on aposematism and mate attraction? We used color- and pattern-manipulated Heliconius erato petiverana models in field studies to address these questions. We accounted for both chromatic and achromatic features by including achromatic models that lack color, making this one of the first studies to explicitly control for color alone.
By exploring the contributions color and pattern for both mate and predator recognition, we were able to identify the significance of these visual features in the context of both natural and sexual selection.
METHODS
Field sites
All predation experiments were conducted at the Organization for Tropical Studies’ La
Selva Tropical Biological Station in Sarapiquí, Costa Rica. This work occurred in April and
May of 2012, during the end of the dry season into the beginning of the rainy season. All mate choice experiments were conducted in Panama at the Smithsonian Tropical Research
Institute’s insectary facilities in Gamboa. Butterflies were collected along Pipeline Road in the adjacent Soberanía National Park. Mate choice data were collected from June through
October of 2012 during the rainy season. H. erato petiverana butterflies in our Costa Rica and
Panama field sites share the same wing phenotype.
Production of artificial butterflies
We used artificial butterfly models to test the relative influence of color and pattern composition on mate choice and warning signaling, and to what degree the effects of these overlap. Artificial models were constructed according to Finkbeiner et al. (2012). Four model
41 types were developed: a local phenotype model, a color-switched model (where the colors on the forewing and hindwing band were switched with one another), an achromatic model (no color: black, white, and grays only), and a non-local model which resembled Heliconius erato emma but contained the same reds and yellows as H. erato petiverana (Figure 2.1). H. erato emma is a South American morph that does not occur in the same geographic range as H. erato petiverana and therefore predators and other Heliconius should not have had prior exposure to this phenotype, although the ventral hindwing of H. erato emma may slightly resemble faint rays seen in certain morphs of Heliconius doris. Black pattern elements likely play an important role in receiver detection of species because black can provide high contrast against a foliage background (Stevens & Ruxton 2012). Because of this black regions of model wings were kept black and not switched with any colored regions in order to promote equal rates of model detection by predators. While our study would have benefitted from using an achromatic non-local model type, we limited the number of prey options to four treatments to avoid confusing predators with too many choices, which has been suggested to be a problem in other predation studies (Chris Jiggins, pers. comm.). As a follow-up experiment, however, we recorded predation on just two treatment types: achromatic models with the local pattern and achromatic models with a non-local pattern to confirm the importance of pattern composition alone, in the absence of color.
For predation studies, butterfly models were created to display the ventral side of H. erato petiverana wings since this area of the wing is exposed during rest. Models were designed to accommodate the avian visual system in order to minimize the ability of birds, the major predators of Heliconius, to distinguish between the color pattern stimuli presented by real butterflies versus experimental models. Tetrachromatic bird color-vision models, from
42 two birds that differ in the spectral sensitivities of their short-wavelength-sensitive cone visual pigments, were used for discriminability modeling of color models – the UV-type (blue tit,
Parus caeruleus) and violet-type (chicken, Gallus gallus) visual systems (Vorobyev & Osorio
1998; Kelber et al. 2003). Previous quantitative models and experimental field studies suggest that the colors found on the artificial models and on the ventral side of H. erato petiverana are indiscriminable to avian predators of both visual types (Finkbeiner et al. 2012). For our achromatic models, we calculated the achromatic contrasts of their double-cones for both the natural wing spectra and artificial gray spectra and selected the most similar grays for the artificial models (Bybee et al. 2012, equation 2; Table 2.1).
For mate choice trials, the butterfly models presented both dorsal and ventral wing surfaces. Colors were selected for the ventral side of the artificial models as described above.
To find appropriate dorsal colors to use for the models, spectral measurements were taken from the dorsal side of H. erato petiverana which consists of three major wing colors: red, yellow, and black. Measurements were taken using an Ocean Optics USB2000 fiber optic spectrometer (bifurcating fiber cable R400-7-UV–vis, Ocean Optics) with a deuterium– halogen tungsten lamp (DH-2000, Ocean Optics) used as a standardized light source. For every measurement, the axis of the illuminating and detecting fiber was placed in a probe holder at an elevation of 45 degrees to the plane of the wing, and pointed left with respect to the body axis. The spectrometer was calibrated during each use with a white spectralon standard (WS-1-SL, Labsphere). We printed the artificial butterfly model wings on Whatman filter paper, which yields reflectance spectra close in brightness to actual butterfly wings, using an Epson Stylus Pro 4880 printer with UltraChrome K3 ink. A yellow pigment solution of 0.010 mg / µL 3-hydroxy-DL-kynurenine (3-OHK) in methanol was applied to the yellow
43 bands on the ventral side, and a solution of 0.015 mg / µL 3-OHK in methanol was applied to the bands on the dorsal side to provide accurate UV reflectance. Since chromatic models contained methanol from the 3-OHK solutions, as a control methanol was applied to the area where the “yellow” band is located on achromatic models in case butterfly or predator response varied due to methanol odor. Appropriate colors were selected for models based on overall similarity to reflectance spectra of natural butterfly wings (Figure 2.2). As an additional test to ensure the visual accuracy of the models, five-minute trials comparing approaches by randomly selected wild-caught H. erato males to H. erato models with artificial wings and H. erato models with real wings were conducted weekly, totaling 12 trials.
Using a Wilcoxon signed-rank test with continuity correction, no difference was detected in approaches between real-wing models and artificial-wing models (W = 27.5, P = 0.649).
When considering possible differences between dorsal and ventral wing colors in H. erato, it is important to note that the shape of reflectance spectra for reds on both surfaces are nearly identical and show only slight variations in brightness. For yellows, the dorsal surface is brighter than the ventral surface. Nonetheless, we assume that this difference in brightness has little or no effect on a bird’s, or potential mate’s, ability to detect differences between colors, because chromatic features are more reliable signals under the variant illumination conditions of our experiment than are brightness features. Regardless of whether dorsal or ventral wings are displayed, avian predators and potential mates should have already learned both. Because the predation study focuses on the ventral wing side, and the mate choice study on the dorsal side, we interpret our results as assessing the potential for selection on both dorsal and ventral visual features.
44 Predation experiments
To test the relative influence of color and pattern composition on predator avoidance, we recorded predation attempts on models placed in the field. The models were fitted with plasticine abdomens and tied to branches with thread to represent natural resting postures. We chose to use butterflies at rest since birds often attack butterflies in the morning hours while still at rest before foraging (Finkbeiner et al. 2012), and in other butterflies ventral wing characters appear to play a more important role in predator avoidance than do dorsal wing patterns (Oliver et al. 2009). Other studies investigating Heliconius predation have successfully used artificial models that display dorsal wing surfaces (Merrill et al. 2012), however we have observed that virtually all H. erato butterflies at rest in natural habitats hold their wings closed, thus exposing the ventral surface of the wing. We acknowledge that the actual butterflies’ ventral wing bands appear slightly narrower than dorsal bands, and there is some evidence that the colored band elements on male H. erato are larger than those on females (Klein & Araújo 2013). In our artificial butterfly models, the dorsal and ventral wing bands are the same size.
Four individuals of each model type were randomly placed in 100 forest sites at our
Costa Rica field location, totaling 1600 models used: 400 of each type (local, color-switched, achromatic, and non-local). Models were placed far enough apart so they were not within humanly visible range from one another (on average 5-10 meters separated), and were positioned approximately 1.5 meters above the ground, which is consistent with natural roosting heights of H. erato (Mallet & Gilbert 1995). Each forest site was at least 250 meters apart to avoid overlap between predator home ranges (home range estimates are summarized in Finkbeiner et al. 2012) and no sites were used twice in the study to control for predator
45 learning. Tree Tanglefoot® was applied to the base of plant stems containing artificial butterflies to prevent removal or attack of the models by small mandibulate arthropods. The models remained at their sites for a total of 96 h (4 days), and each model was examined daily for evidence of predation. When a model was attacked, a substitute was placed in the same location, but any attacks on the substitutes were not included in the analysis. A model was determined attacked if the wings and abdomen had apparent beak marks and/or large indentations in the abdomen (Figure 2.3). If a model had more than one beak mark on it, this was counted only as a single attack. The binomial response of attack (i.e., yes or no) was modeled as dependent upon butterfly model type using a zero-inflated Poisson regression model, including sites as a random effect, with the ‘pscl’ package (Zeileis et al. 2008;
Jackman 2011) in R statistical software (R Development Core Team 2010). We later conducted a follow-up experiment in which we recorded predation on just two treatment types: 100 achromatic models with a non-local pattern, and 100 achromatic models with the local pattern, as a control for pattern in the absence of color. The models were placed in forest sites using the same methods described above, and data were analyzed using the aforementioned techniques.
Mate choice experiments
To identify the relative contributions of color and pattern components in mate preference, we carried out mate choice experiments with wild-caught H. erato petiverana males using insectary facilities in Gamboa, Panama. We used males in this study because they are often more active than females in insectary-based studies, and in nature females cannot accept a male until he has initially been attracted to and courted her. Although males and
46 females of H. erato are sexually monomorphic in their color patterns, we do not rule out the possibility that males may have a biased selection toward a certain model type that could differ from female preference (see Kemp & Macedonia 2007). Prior to experimental use, the males were acclimated to the insectary environment for at least five days. Males were introduced individually into experimental cages (2m × 2m × 2m) and presented with one of three pairs of the artificial butterfly models: local versus color-switched, local versus achromatic, and local versus non-local pattern. The local model represented the male’s own color pattern. The artificial models, placed ~1 m apart, were fixed onto the ends of zip-ties attached to a PVC pipe suspended between two metal bars with monofilament. By tugging on the monofilament attached to another zip-tie in the center of the PVC pipe, the models could be manipulated to simulate the movement of butterflies in flight (see Supporting Information
Video 1 in Finkbeiner et al. 2014). The models imitated active flight behavior in order to appear realistic to males. In nature, males patrol for females in the home range and often approach to court females while females are in flight. Although the wing movements of the artificial models may vary from that of natural butterflies, our mechanical design made it possible to implement the most important control of having paired models displaying identical wing movements within trials.
Each individual male was presented with each of the three model pairs, in random order, three times. No males were presented with the same pair twice in one day. Mate choice trials with each pair lasted five minutes, beginning at the first sign of activity by the male. We randomized which models were placed on the north or south end of the flight simulator, and to control for males approaching models based on preference for a particular region of the cage, the models’ placement was switched at 2.5 minutes. Individual males experienced nine
47 five-minute trials – three five-minute trials with each pair. During trials two variables were recorded: 1) approaches, which consisted of flight directed toward the model, and in which the male came within 20 cm of the model (see Supporting Information Video 2 in Finkbeiner et al. 2014); and 2) courting attempts, which were classified as sustained hovering or circling behavior (lasting > 1 second) around the model (see Supporting Information Video 3 in
Finkbeiner et al. 2014). Approach and courtship in H. erato are discrete, highly characteristic behaviors that are easy to identify and previous studies have used ‘approach’ and ‘courtship’ movements as a way to classify and measure butterfly response to artificial mates (Jiggins et al. 2001; Jiggins et al. 2004; Kronforst et al. 2006). All courting attempts were also counted as approaches since a courting attempt is first initiated by an approach.
Mate preference data were analyzed using a hierarchical random effects Bayesian model for count data, which accounts for variation in both individual-level and population-level preferences, as well as trial-by-trial variability. This statistical approach has been used in other recent studies to analyze count data in ecological and behavioral processes (e.g., Shiffrin et al. 2008; Fordyce et al. 2011; Lee 2011; Merrill et al. 2011a; Lee & Wagenmakers 2013).
!,! In our model, we denote by �!"# the count of approaches to the local model type for the �th
!,! butterfly on their �th trial in the �th condition, and �!"# for the count of approaches to the
!,! !,! novel model type (color-switched, achromatic, or non-local). Similarly, there are �!"#and �!"# for the counts of courting attempts toward the local and novel model types, respectively. We assume there is an overall preference � of choosing the local model type over any alternative novel model type. Each of the three novel model type conditions is then assumed to have a preference for the local type that comes from a distribution centered around �. These preferences are �!", �!" and �!" for the specific color-switched, achromatic, and non-local
48 conditions. Since �! is the preference for the local model type, 1 − �! is the preference for the novel model type. Specifically, 1 − �!" is the preference for the color-switched type over the local type, 1 − �!" is the preference for the achromatic type over the local type, and 1 − �!" is the preference for the non-local type over the local type. There are assumed to be between- butterfly individual differences, drawn from a distribution with mean �!, so that the �th butterfly on the �th condition has a latent preference given �!". There is also assumed to be between-trial variability for the same butterfly across the repeated trials, so that �!"# denotes the latent preference of choosing the local model type for the �th butterfly on the �th trial in the �th condition. Finally, it is assumed that �!"# is constant throughout trials, so the number
! of times the local model type was chosen �!"# = �!"# follows a binomial distribution with
! ! this preference out of a total of �!"# = �!"# + �!"# events. The overall preference � and the condition-specific �! preferences are the key parameters of interest.
We use beta distributions to model: 1) the condition-level variability that gives preferences of choosing the local model type over the three novel model types, 2) the group- level (population-level) variability that allows for individual differences between the butterflies within a condition, and 3) the trial-to-trial variability for each butterfly in each condition. The model is precisely illustrated by the graphical model shown in Figure 2.4, and additional details about the analysis are presented as Supporting Information in Finkbeiner et al. (2014). The population preference of choosing the local model type �! for the �th condition is drawn from a beta distribution centered on the overall preference of choosing the local
! ! ! model type �, with a precision λ , so that �! ~ Beta �λ , 1 − � λ . The preference for the
�th butterfly in the �th condition is assumed to be drawn from a beta distribution with mean �!
49 ! ! ! and precision λ! , so that �!" ~ Beta �!λ! , 1 − �! λ! . And finally, the preference and variability for the �th butterfly on its �th trial in the �th condition is assumed to be drawn from
! ! ! a beta distribution with mean �!" and precision λ , so that �!"# ~ Beta �!"λ , 1 − �!" λ .
The model was implemented in JAGS software (Plummer 2003; for script see
Supporting Information in Finkbeiner et al. 2014). The same model was applied independently to both the approach and courtship data. All of the analyses reported are based on six independent Markov chain Monte Carlo chains, each with 20,000 collected samples and 20,000 discarded burn-in samples. We evaluated standard measures of convergence and auto-correlation, including the � statistic (Gelman 1996), to verify the samples as good approximations to the posterior distribution. To address whether pairs of the group mean preferences are the same or different, we used Bayes factors (Kass & Raftery 1995) estimated by the Savage-Dickey approximation method (Wagenmakers et al. 2010) to compare the prior and posterior density of the parameters. Details about robustness checks to examine the sensitivity of our results to quantitatively different ways of formalizing modeling assumptions are also presented as Supporting Information in Finkbeiner et al. (2014).
RESULTS
Predation study
To determine the relative influence of color and pattern composition on predator avoidance, we placed the different model types of H. erato petiverana in forest sites. We observed the highest frequency of attacks on the achromatic model type, and the lowest frequency of attacks on the local model type (Figure 2.1). Of 1600 artificial butterfly models, a total of 102 had evidence of bird attacks: nine local, 24 color-switched, 38 achromatic, and
50 31 non-local model types. Despite a low frequency of attacks overall, we found clear differences in attacks across all four model types. Visual inspection of the frequency of attacks along with our analysis indicates the largest difference in attacks was observed between the local and achromatic types (z value = 3.975, P < 0.0001), then between the local and non-local types (z value = 3.094, P = 0.00197), and finally between the local and color- switched types (z value = 2.500, P = 0.0124). We also found a difference in attacks between the color-switched and achromatic model types (z value = 2.266, P = 0.0234; Figure 2.1). No statistically significant differences were detected in predation between the color-switched and non-local types, or between the achromatic and non-local types. For our follow-up experiment, which compared predation between achromatic models with a non-local pattern and achromatic models with the local pattern, we recorded 9 attacks on the non-local pattern and 3 attacks on the local pattern, out of 100 models of each type. No statistically significant difference was detected (z value = -1.642, P = 0.101).
Mate choice study
To assess the roles of color and pattern components in inducing mating-related behaviors, we recorded the responses of wild-caught H. erato petiverana males when presented with a series of different artificial butterfly models. Overall, we recorded 2224 approaches and 772 courtship attempts from 51 unique males during 438 five-minute trials.
47 out of the 51 males completed all nine five-minute trials (three trials with each pair), whereas three males only completed one set of three trials and one male completed two sets of the three trials. The data from those males were included in the analysis since each set of these trials still consisted of a test with all three pairs. The posterior means of the probability,
51 or preferences, of males approaching and directing courtship attempts at the local model type
(overall � preference), and at the color-switched, achromatic, and non-local model types
(condition-specific 1 − �! preferences: 1 − �!", 1 − �!", and 1 − �!"), are presented in Table
2.2, along with their corresponding 95% credible intervals. Violin plots (Hintze & Nelson
1998) representing the posterior distributions of approach and courtship data, as well as figures showing the Savage-Dickey estimates, are presented as Supporting Information in
Finkbeiner et al. (2014).
Our results show that males preferentially approached and courted conspecific (local- pattern) models more than any other model type (Figure 2.1, Table 2.2). In addition, the evidence strongly suggests that approach and courtship preference means differ between the three novel model types. This evidence is based on extremely high Bayes factors and non- overlapping posterior distributions in the estimation (see Supporting Information in
Finkbeiner et al. 2014 for interpretation details). Males showed a higher preference for approaching the non-local type than the color-switched type (Bayes factor = 2.01x104 in favor of the two preferences being different). Males also showed a higher preference for approaching the non-local model type than the achromatic type (Bayes factor = 1.75x104 in favor of the two preferences being different), and the color-switched model types were preferred and approached more than the achromatic ones (Bayes factor = 1.09x104 in favor of the two preferences being different). The Bayes factor of 1.09x104, for instance, indicates that the data are 1.09x104 times more likely to have arisen if the group means for the color- switched and achromatic model types are different, rather than if they are the same. We found similar results with respect to courting attempts: males showed a higher preference for courting models of the non-local type than the color-switched type (Bayes factor = 1.67x104).
52 They also preferred to court models of the non-local type more than the achromatic type
(Bayes factor = 2.69x104), and the color-switched model types were preferred and courted more than the achromatic model types (Bayes factor = 1.02x104). In summary, males predominantly preferred to approach and court their own type, followed by (in consecutive order) the non-local type, color-switched type, and finally the achromatic type.
DISCUSSION
Relative effects of color and pattern on predation rates
In this study, we tested the relative influence of color and pattern features in both predator avoidance and mate preference. We found that wing color and pattern composition appear to play roles in both cases, although color likely has a greater influence than pattern on predator and conspecific recognition. From our predation results we conclude that color alone acts as a successful aposematic signal in Heliconius butterflies because achromatic models
(possessing the same pattern, but no color) were attacked significantly more than the local model (Figure 2.1).
We also found that pattern appears to play some role in aposematic signaling in H. erato
– although the evidence for this in our own study has some weakness. Specifically, we found that non-local models possessing a novel pattern, but the same colors as the local model type, were attacked significantly more often than the local model. However, since the placement of colors (e.g., red vs. yellow on the forewing) is not the same between these two models, hue and brightness differences between yellow and red could also account for the differences in attack rate. A more informative comparison for the possible effect of pattern is the comparison between the color-switched and the non-local model because in this case the
53 placement of colors on the wing is similar so there are no brightness or hue differences. In this controlled comparison for pattern, no significant difference was detected in attacks between the color-switched model and non-local model. Furthermore, our follow-up experiment detected no significant difference in attacks between achromatic local and achromatic non- local patterned models, suggesting that in the absence of color, particular patterns by themselves appear to have little specific effect as warning signals. Nonetheless, a combination of the appropriate colors and patterns is likely important for optimal predator deterrence in
Heliconius.
Our findings are consistent with previous work by Aronsson and Gamberale-Stille
(2008) that found avian predators primarily attend to color, rather than pattern, when learning aposematic visual signals. Studies focusing on the importance of visual signals in predator avoidance of other aposematic animals provide evidence that a bright color alone provides protection (Ruxton et al. 2004), but in some snakes, the correct combination of colors is fundamental for predator recognition and avoidance (Brodie 1993). Similar studies have shown that dragonflies are more likely to avoid wasp-like stripes rather than uniform black or yellow, indicating the influence of pattern on their foraging decisions (Kauppinen & Mappes
2003), and with inexperienced chicks, striped patterns can increase avoidance when coupled with colors that are not typically associated with a cost (Hauglund et al. 2006). Evidence that predators avoid aposematic colors more readily than a particular aposematic pattern could be due to the fact that predators who target fast-moving prey may have difficulty identifying precise patterns during prey movement, whereas detecting colors would be much easier.
Perhaps this is why aposematic prey often have markings comprised of repeated pattern elements which could improve the likelihood of detection (Stevens & Ruxton 2012).
54 Relative effects of color and pattern on inducing mating behavior
Our mate preference experiments had similar outcomes to the predation study with respect to color. We found that all colored models were considerably more successful at triggering mating-associated behaviors than the achromatic model. This evidence that males are highly responsive to chromatic features is consistent with previous findings that H. erato have excellent color vision in the long-wavelength range in the context of feeding (Zaccardi et al. 2006). Our new results provide evidence that color discrimination in the long-wavelength range also matters for mating behavior, although further experiments would be required to confirm this.
With respect to pattern, we found that the local model type was the most effective at inducing mating behavior in males. Unlike the predation experiments, however, we found strong evidence for a difference in the preference means of approach and courtship between the non-local and color-switched models. The non-local pattern was preferred more, suggesting that pattern may play a more significant role in mate preference than in predation.
Although both the color-switched and non-local model types presented yellow bands on the forewing, the non-local model had a greater surface area of red on the hindwing than the color-switched model. Previous studies have shown that male Heliconius butterflies are strongly attracted to the color found on the forewing band (Kronforst et al. 2006; Merrill et al.
2011b), which in this case is red, so it is possible this preference is in part due to a greater area of red on the wings. An alternative explanation could be that there is some inherent preference for the rayed pattern in the non-local model that is shared across different H. erato races.
55 It is important to note that while we provide evidence that color plays a proximate role in conspecific recognition and mate preference, it does not necessarily mean that it is a product of sexual selection (for a discussion of these issues, see Mendelson & Shaw 2012); although we do speculate that this is the case. When considering the evolution of coloration, a key question (also raised by Kemp & Macedonia 2007 and Kunte 2009) is whether male preference leads to significant variation in female mating success, which would in turn lead to selection on female coloration. Nielson and Watt (2000) proposed that females who are approached less frequently by males suffer a reduction in fitness because they spend more of their time in a non-fertile state. This effect could be additionally amplified in H. erato because older females – virgin or not – attract fewer courtship attempts by males (Klein & Araújo
2010), so the longer a female waits to mate, the lower her chance of mating becomes. It has also been proposed that females who settle to mate with fewer, older, and/or smaller males should receive reduced nutritional benefits from poorer quality spermatophores (e.g.
Rutowski et al. 1987). Again, this effect could be amplified in H. erato due to the limited number of matings wild females experience owing to their postmating male “antiaphrodisiac” pheromones (Gilbert 1976; Estrada et al. 2011). In addition to these fitness effects, genetic work has shown that genes causing wing pattern variation have the same effects on both sexes
(Papa et al. 2013). Thus, selection on wing patterns in one sex would be expected to affect the wing patterns of both sexes. In sum, while little work has been done to empirically determine the fitness effects of male bias in Heliconius, precedents in other butterfly systems make it reasonable to speculate that male preference should lead to selection on coloration in females.
Many Heliconius mate preference studies have focused on species from the polyandrous “adult mating” melpomene-cydno clade, however our study presents some of the
56 first mate preference data using H. erato as the study species. We have shown here that males exhibit strong color pattern-based preferences toward conspecific phenotypes (suggesting assortative mating in this species), and they actively approach and court artificial models despite being members of the Heliconius “pupal mating” clade, in which females are typically monandrous and males are not expected to be vigorous courters, (Gilbert 1976; Gilbert 1991;
Deinert et al. 1994; McMillan et al. 1997; Estrada et al. 2011; Walters et al. 2012). The observation of these behaviors also suggest that H. erato may commonly mate as adults, although more rigorous field studies need to be done to confirm this (but see Klein & Araújo
2010 for information about adult courtship behavior in H. erato).
Color features are better predictors of fitness-related effects than pattern features
As described above, our predation and mate preference studies suggest that color is a more broadly effective visual signal than pattern. Namely, the achromatic model was attacked by predators more than any other model, and also had the lowest probability of inducing mating behavior in male butterflies. Even further, the fact that males responded more to the non-local type than to the color-switched type shows that for any given pattern, color matters for mate preference. A similar study by Kronforst et al. (2006) showed that yellow male H. cydno have a higher probability of courting their own yellow type than the white type, even when pattern remains the same. With respect to pattern, we found some evidence that pattern matters for male preference as have previous studies (Chamberlain et al. 2009). In the lycaenid butterfly Lycaeides idas, females with reduced ventral wing pattern features were less preferred than females with unmanipulated patterns (Fordyce et al. 2002). Although a combination of the correct colors and pattern is important for both warning coloration and
57 mate attraction in H. erato, we conclude that color likely contributes more to overall signal effectiveness in both circumstances.
Warning coloration and mate choice signals work in parallel
One of the most interesting findings from our study is that visual features used for both predator avoidance and mate attraction produce similar effects on fitness-related traits.
The results from both sets of experiments show consistent overlap between the model treatments attacked most by predators and those least effective at inducing male mating behavior (Figure 2.1). We acknowledge, however, that while our results suggest mate choice and predation will produce selection for similar colors and patterns, we have not evaluated in detail the relative strength of selection by each of these two pressures. It is possible one selective force may influence evolution by the other if substantial imbalance exists between them (for a review on this topic see Kunte 2009); but confirming this will require further work within this system.
In H. erato, the phenotype most effective in preventing predator attack is selected most by males, suggesting its appearance provides a signal to potential mates demonstrating greater survival probability for both itself and offspring. This implies an honest signaling model where information communicated by an animal is useful to the receiver and can in turn increase its fitness (Zahavi 1975). Therefore, males should invest greater energy in courting females that display their same phenotype. A similar situation has also been described in the poison-dart frog Oophaga pumilio where aposematic coloration also serves as an attractive signal to mates (Maan & Cummings 2008). This positive interaction between aposematism and mate choice indicates cooperation between visual signals that benefit individual fitness.
58 By identifying the contributions of color versus pattern in predation and mate preference studies, we have shown how both natural and sexual selection may work together to reinforce the evolution of coordinated suites of visual signals.
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63 Table 2.1. Achromatic contrasts (using double-cones) for both the natural wing spectra and artificial wing gray spectra. The most similar contrasts are in red and were used as grays
(indicated by asterisk) for the red and yellow regions in achromatic models.
(Q_s_doublecone - Q_b_doublecone)/ (Q_s_doublecone + Q_b_doublecone) Chicken Blue tit grey_1 0.951998445 0.952402091
grey_2 * 0.946373699 0.946933885
grey_3 0.936370454 0.937098626 grey_4 0.926315677 0.92725889 HD_yellow_9 0.947829769 0.946323561
Chicken Blue tit grey_5 0.915925064 0.916911137 grey_6 0.900671394 0.90189849
grey_7 0.894357989 0.895620412
grey_8 0.878907188 0.880256263 grey_9 0.849848602 0.851479745 grey_10 0.845209583 0.846880214 grey_11 0.838664102 0.840570118 grey_12 * 0.816946245 0.81907446 grey_13 0.799482315 0.801828135 grey_14 0.794789556 0.797015887 grey_15 0.784709385 0.786692445
grey_16 0.759613762 0.761707831
grey_17 0.750918501 0.753078146 FD_red_8 0.820312926 0.790705733
64 Table 2.2. The ratios of approach and courtship occurrences are shown for male H. erato petiverana butterflies during paired trials with the local model type and the color-switched, achromatic, and non-local type, respectively. Probabilities of approach and courtship, estimated using a hierarchical Bayesian framework, represent the overall preference � of choosing the local model type over all other novel model types, and the group preferences
1 − �! of choosing the novel model types. The 95% credible intervals (Bayesian confidence intervals) are shown in parentheses. The probabilities and credible intervals are graphed in
Figure 2.1.
______Occurrences and probabilities of approach and courtship between model types ______Male display Color-switched : Local Achromatic : Local Non-local : Local ………………………………………………………………..……………………………………...…... Ratios of H. 181 : 558 51 : 566 369 : 499 erato approach
Ratios of H. 46 : 216 6 : 221 94 : 189 erato courtship
______Male display Local Color-switched Achromatic Non-local � 1 − �!" 1 − �!" 1 − �!" ……………………………………………………………………………………………………………
Probability of 0.739 0.243 0.086 0.422 H. erato approach (0.541, 0.881) (0.212, 0.276) (0.063, 0.110) (0.387, 0.457)
Probability of 0.814 0.173 0.034 0.324 H. erato courtship (0.606, 0.944) (0.128, 0.223) (0.010, 0.062) (0.270, 0.382) ………………………………………………………………………….………………………….……
65
Figure 2.1. Color- and pattern-manipulated wing models experience different predation rates
(left axis) and different probabilities of inducing pre-mating approach behavior in male butterflies (right axis). There are four model types: a local H. erato petiverana type, a color- switched type, an achromatic type, and a non-local type. Error bars for the predation data include 95% CIs based on exact binomial distribution (Brown et al. 2002), and error bars for the mate preference data represent 95% credible intervals (Bayesian confidence intervals).
Asterisks represent the p-values from pairwise comparisons between predation on the local model type and the three other model types, where *P < 0.05, **P < 0.005, ***P < 0.0001.
All Bayes factors from approach probability comparisons show overwhelming evidence that the preference means differ between the model types (Bayes factors > 1.00x104).
66 100 Butter ly wing yellow (n=12)
80 Paper wing yellow
60
40
percent percent reflectance
20
0 300 400 500 600 700
100
Butter ly wing red (n=12) 80 Paper wing red
60
40
percent percent reflectance
20
0 300 400 500 600 700 wavelength (nm)
Figure 2.2. Reflectance spectra of the natural and artificial (paper) model dorsal wing colors used in mate preference studies.
67
Figure 2.3. Evidence of predation attempts on a color-switched (upper) and non-local (lower) butterfly model. Triangular beak marks are visible on the upper area of the abdomen akin to the location of the butterfly head.
68
µ λc
π b j λj
pij µ Uniform(0, 1) ∼ λc Uniform(1, 200) ∼ π Beta(µλc, (1 µ) λc) qijk λt j ∼ − λb Uniform(1, 200) j ∼ b b pij Beta(πjλj , (1 πj) λj ) yijk ∼ − λt Uniform(1, 200) ∼ q Beta(p λt, (1 p ) λt) ijk ∼ ij − ij nijk y Binomial(q ,n ) ijk ∼ ijk ijk k trials
i butterflies j conditions
Figure 2.4. Graphical model of approach and courtship behavior across conditions (model type), assuming different mean preferences for each condition, and trial-by-trial variability for each butterfly in each condition. Continuous variables are shown as circular nodes, and discrete variables as square nodes. Observed variables are shaded whereas unobserved variables are not shaded. Plates are square boundaries that enclose subsets of the graph, to indicate the subset has independent replications in the model. See Supporting Information in
Finkbeiner et al. (2014) for details.
69 CHAPTER 3: Adaptive function of ultraviolet (UV) and fluorescence in Heliconius butterflies.
INTRODUCTION
Animal visual signals are incredibly diverse and serve multiple functions, including mate attraction and protection from predators (Endler 1992). Signals can be directed toward one or multiple receivers, and signal consistency is important for effective communication. In nature, however, spectral environments change throughout the day and are predicted to affect signal detectability (Endler 1993, Endler & Théry 1996, Heindl & Winkler 2003, Stevens
2007, Stevens & Ruxton 2012, Rojas et al. 2014). Environmental factors, particularly weather, can quickly alter ambient lighting. This impacts animal foraging, courtship, and predator avoidance, and species that rely on signaling for communication will benefit most from signals that remain functional under variable environmental conditions.
In butterflies, many species advertise conspicuous colors and patterns. Several butterfly groups have fluorescent components in their wings (Cockayne 1924, Kumazawa et al. 1996, Vukusic & Hooper 2005, Vigneron et al. 2008, Wilts et al. 2012), as well as UV elements (Silberglied and Taylor 1978, Meyer-Rochow 1991, Robertson and Monteiro 2005,
Rutowski et al. 2005, Kemp 2008, Briscoe et al. 2010). Fluorescent pigments absorb short wavelengths (UV or blue) and re-emit them at longer wavelengths that trigger photoreception, producing a glowing effect (Hausmann et al. 2003). In insects, fluorescence has been reported in at least five orders and over 100 species (Welch et al. 2012). Although the first discovery of fluorescence in any insect was that of butterfly fluorescence in 1924 (Cockayne 1924), the question of whether butterflies use fluorescence for communication remains unresolved despite numerous studies investigating the physical properties of butterfly fluorescence
(Kumazawa et al. 1996, Vukusic & Hooper 2005, Vigneron et al. 2008, Wilts et al. 2012).
70 Likewise, it is unclear how fluorescence and other visual signals such as UV are effective under variable light environments.
Here we use fluorescent- and UV-manipulated artificial butterfly models in field studies to determine the adaptive function of fluorescence and UV in butterflies in the context of both natural and sexual selection, and to identify how cloudy conditions affect fluorescent and UV signaling toward conspecifics. We use the toxic passion-vine butterfly Heliconius erato because its wings contain a yellow pigment, 3-hydroxy-DL-kynurenine (3-OHK), which has fluorescent properties and reflects UV light (Briscoe et al. 2010, Figure 3.1). This pigment has been hypothesized to serve as a private channel of communication among Heliconius butterflies since the yellow pigments of mimics in related genera neither fluoresce nor reflect
UV (Bybee et al. 2012).
METHODS
Butterfly Models
We used artificial butterfly models to test whether fluorescence and UV serve as visual signals for H. erato butterflies. Butterfly models were designed using a fiber optic spectrometer (Ocean Optics USB 2000) as described in Finkbeiner et al. 2012. We developed four model types: models with (F+) and without (F-) fluorescence, and models with (UV+) and without (UV-) ultraviolet. For the UV+ models, an odorless UV-reflective yellow paint
(Fish Vision™) was added to the dorsal yellow band of the model wings to provide sufficient
UV reflectance (Figure 3.2a). To eliminate UV reflectance altogether (for UV- models), a thin film UV filter (Edmund Optics, Item No. 39-426) was placed over both the yellow and red/pink UV-reflective portions on the wings. The UV filter prevents any light reflectance up
71 to 400 nm, and UV reflects from 300-400 nm (Figure 3.2a-d). As a control, Mylar film was added to the yellow and red/pink portions of models used for the UV+ treatment. Mylar film acts as a neutral-density filter and has the same clear texture and appearance as the UV filter.
The models used in fluorescence studies for the F+ treatment contained a 3-OHK solution applied to the yellow band to provide natural fluorescence on the models (Figure
3.1c, see Finkbeiner et al. 2014 for 3-OHK concentrations). Fluorescence can be confirmed by shining a hand-held 365 nm LED light over the natural and artificial butterfly models in a darkroom (Figure 3.1b-c). Fluorescent regions are classified by any area which, when illuminated with a UV-only light, emits light wavelengths longer than 400 nm (Hausmann et al. 2003). Excitation and emission spectra for 3-OHK fluorescence (taken from a solution of
1.0 mg 3-OHK dissolved in 2.0 ml methanol) were measured using a Varian Cary Eclipse
Spectrofluorometer, which revealed two excitation peaks at 307 nm and 441 nm, and one emission peak at 486 nm (Figure 3.1d). To our knowledge, this represents the lowest known natural fluorescence excitation peak (307 nm) reported in any insect; insect fluorescence records to date indicate excitation peaks ranging from around 340 nm to 480 nm (Welch et al.
2012). The non-fluorescent models (F-) were covered with strips of yellow Manila paper
(Creatology® Manila Drawing Paper, Item No. 410590) pasted to the yellow portion of model wings. The Manila paper has a reflectance spectra that closely resembles reflectance of non-3-
OHK yellows found in butterfly taxa that are close relatives to Heliconius, which are also
Heliconius mimics, for example Eueides (Bybee et al. 2012; Figures 3.3 and 3.4).
Mate Preference Experiments
To determine whether butterflies use fluorescence and UV as visual signals, mate
72 preference experiments were carried out at the insectary facilities in Gamboa, Panama from
September 2013 through February 2014. Data were collected from 80 wild-caught H. erato petiverana butterflies: 40 males and 40 females. Each butterfly was introduced individually into experimental cages (2 m × 2 m × 2 m) and presented with one of two pairs of the artificial models: F+ versus F-, or UV+ versus UV-. The models were separated by 1 m and attached to an apparatus used to simulate flight (for information on flight simulator construction see Finkbeiner et al. 2014). Individual butterflies experienced six five-minute trials – three five-minute trials with each of the two pairs. During trials two variables were recorded: 1) approaches, which consisted of flight directed toward the model, and in which the butterfly came within 20 cm of the model and 2) courtship events, which were classified as sustained hovering or circling behavior around the model (for examples of these specific behaviors see videos 2 and 3 in Finkbeiner et al. 2014). Mate preference data were analyzed using a two-way ANOVA to examine the effects of model type and sex on butterfly behavior.
Cloud coverage was also documented, and spectral irradiance measurements were taken to provide quantitative information for cloudy and sunny conditions. Data from trials that were completely cloudy throughout the trial were analyzed separately, to determine whether butterfly response differed based on available sunlight. Weather conditions were recorded either as sunny (no clouds covering the sun at all during the trial), cloudy (clouds covering the sun during the entire trial), and variable (trials had partial sunlight, for instance if a cloud passed over the sun during part of the trial this was considered variable weather).
Most trials were distinctly sunny or cloudy. Irradiance spectra graphs of open sunlight, the experimental cage during open sunlight, as well as open cloud cover and cage conditions under cloud cover, are shown in Figure 3.5.
73 Predation Experiments
To assess whether fluorescence and UV serve as potential aposematic signals, we conducted field predation experiments using artificial butterfly models. Predation experiments were completed in Panama at the Smithsonian Tropical Research Institute
Gamboa field station and at selected forest sites in Soberanía National Park, from June through September in 2013. Models were fitted with plasticine abdomens and tied to branches with thread to represent natural resting postures. For the fluorescence study, five artificial models of each treatment (F+ and F-) were randomly placed in 100 forest sites
(Finkbeiner et al. 2014), each site separated ~250 meters to account for avian predator home range (home ranges described in Finkbeiner et al. 2012). This totaled 1,000 models: 500 of each F+ and F- type. The same methods were used for the UV study, using 500 each of UV+ and UV- model treatments in non-overlapping sites from the fluorescent models. The models remained at their sites for four days, and each model was examined for evidence of predation.
A butterfly was considered attacked if damage to the abdomen and wings appeared in the form of beak marks and/or large indentations in the abdomen (for examples of attacked models see Finkbeiner et al. 2012, Finkbeiner et al. 2014). The binomial response of attack
(yes or no) was modeled as dependent upon butterfly model type using a zero-inflated
Poisson regression model, including sites as a random effect, in R statistical software with the ‘pscl’ package (Zeileis et al. 2008, R Development Core Team 2010, Jackman 2011).
RESULTS
Mate preference experiments
To test whether fluorescence and UV serve as visual signals for H. erato butterflies,
74 we used fluorescent- and UV-manipulated artificial butterfly models in mate preference studies with wild caught male and female H. erato butterflies. We found a strong model type effect on the number of butterfly approaches toward fluorescent and UV models under all light conditions. There were significantly more approaches toward F+ than F- models (Two- way ANOVA, F=16.287, p=8.507x10-5, n=80; Figure 3.6a), and toward UV+ than UV- models (F=10.469, p=0.00149, n=80). There was no apparent effect of sex on butterfly approach behavior (F=2.738, p=0.0999, n=80 for fluorescence; F=0.0493, p=0.952, n=80 for
UV), providing evidence that males and females approach the models at equal rates. This shows that females are in fact ‘active’ during such preference studies, at least with respect to approaches, and how females and males share the same preference for fluorescence and UV in conspecifics. In nature, females may use approach behavior in non-mating related interactions, such as following between pollen resources or to new roosting locations (Waller and Gilbert 1982, Finkbeiner 2014). Specific male and female behaviors for all comparisons are graphed in Figure 3.7. Regarding courtship behavior, we found a strong model type effect where F+ models were courted much more than F- models (F=11.731, p=0.000788, n=80;
Figure 3.6b). The test for the main effect of sex shows that males court fluorescent models at a significantly higher rate than females (F=9.211, p=0.000167, n=80). However, we found no significant model type effect on the number of courtship events directed toward UV+ and
UV- models (F=2.304, p=0.131, n=80), which suggest UV may be a less important short- range signal than fluorescence. There was also no effect of sex on butterfly courtship behavior toward the UV models (F=0.701, p=0.498, n=80). Overall these results provide clear evidence that fluorescence and UV both function as visual signals for H. erato butterflies.
75 Mate preference under variable weather conditions
To identify how cloudy weather conditions affect fluorescence and UV signaling in butterflies, we isolated and analyzed data collected only during trials that experienced overcast weather conditions (cloudy throughout the entire trial). Under such light settings there continued to be a strong model type effect on the number of approaches toward the fluorescent models (F=7.929, p=0.00636, n=36; Figure 3.6c), and a slight effect of butterfly sex on approach behavior where males approached models at a higher rate than females
(F=5.006, p=0.0285, n=36). For courtship behavior, there was still a significant model type effect on the number of courtship events under cloudy conditions directed toward the fluorescent models (F=6.396, p=0.0138, n=36, Figure 3.6d), and under these conditions males also courted the models at a significantly higher rate than females (F=5.588, p=0.0210, n=36). However, under cloudy conditions we no longer found a model type effect on the number of approaches toward the UV models (F=0.711, p=0.402, n=36), and no effect of butterfly sex (F=1.926, p=0.170, n=36). There was also no effect of model type (F=0.238, p=0.628, n=36) or sex (F=0.167, p=0.684, n=36) on courtship events toward the UV models.
Our results imply that butterflies experience difficulty discerning between UV presence and absence under cloudy skies, possibly due to lower available light throughout the spectrum including in the UV (Figure 3.5; but see Obara et al. 2008 for butterfly mating preferences in different UV environments), yet the butterflies continued to be able to detect fluorescence regardless of weather condition. This shows how fluorescence persists as a signal during variable conditions under which UV signals are no longer effective.
76 Predation experiments
In an additional study we tested whether fluorescence and UV might serve as aposematic signals toward avian predators. We used 2000 artificial butterfly models (500 of each model type) in field predation studies and measured predation as the frequency of avian attacks on models in the forest. Using a zero-inflated Poisson regression model, we detected no difference in predation between F+ and F- models: (z-value=-0.014, p=0.989, n=1000;
Figure 3.8), and no difference in predation between UV+ and UV- models: (z-value=-0.536, p=0.592, n=1000). These results indicate that fluorescence and UV are not used for aposematic signaling.
DISCUSSION
This work introduces 1) a new function for fluorescence in terrestrial animals by showing that this signal is successful for conspecific recognition in variable terrestrial light environments, and 2) represents the first study to show that naturally occurring fluorescence in an insect acts as a visual signal. Our findings provide evidence that fluorescent butterfly wing pigments are as biologically relevant as any other pigment, and could suggest that the sexually dimorphic fluorescent markings noted in several butterfly groups (Cockayne 1924,
Phillips 1959) are associated with mate attraction. Fluorescent pigments may also act as honest indicators of butterfly age, because the intensity of fluorescence decreases over time in response to UV exposure (Welch et al. 2012) and male H. erato are typically restricted to mating with only young, virgin females (Gilbert 1976, Walters et al. 2012). Other animals such as birds use fluorescence to enhance mate signaling (Arnold et al. 2002), fluorescence affects male-male interactions in reef fish (Gerlach et al. 2014), and mantis shrimp use
77 fluorescence to increase signal brightness, particularly at greater water depths (Mazel et al.
2004).
The fluorescent properties of 3-OHK indicate two excitation peaks at 307 and 441 nm
(Figure 3.1); having two peaks potentially allows for maximum emission under variable spectral environments. Both excitation peaks create one emission peak at 486 nm. This emission spectrum corresponds well with the photoreceptor spectral class that has been tuned to middle-wavelength detection in H. erato butterflies, which has peak sensitivity at 470 nm
(Briscoe et al. 2010). In Heliconius, 3-OHK is unique in that it co-occurred with the evolution of the genus and is accompanied by the butterfly’s specialized visual system, which includes duplicated UV opsins in the eye (Briscoe et al. 2010). These opsin duplicates are expected to enhance UV discrimination, implying that the reflectance spectra of 3-OHK may serve as a private signal between Heliconius butterflies to identify conspecifics (Bybee et al. 2012), especially in the presence of mimics whose yellow wing colors lack UV reflectance. Our results support this hypothesis by demonstrating that Heliconius butterflies prefer yellow wing colors that are UV(+) rather than UV(-).
Results from our predation study show that fluorescence and UV do not affect avian predator detection, despite studies showing that birds use fluorescence and UV for mate recognition (Bennet et al. 1996, Arnold et al. 2002), and UV for foraging (Siitari et al. 1999,
Lyytinen et al. 2004). Our results coincide with Lyytinen et al. (2000), who also found no support for UV as an aposematic signal for bird predators. Our work provides experimental evidence that in natural conditions, the mimicry between fluorescent/UV coloration and non- fluorescent/non-UV coloration in butterflies is successful for deterring birds as predicted by modeling of bird vision (Bybee et al. 2012). Given we found no indication that butterfly
78 fluorescence and UV function as aposematic signals toward avian predators, this reinforces the notion that these signals are exclusively used for intraspecific communication.
In summary, we demonstrate for the first time that butterflies use fluorescence as a reliable visual signal under cloudy conditions to enhance conspecific signaling, which presents a novel mechanism for how visual signals can function in highly variable terrestrial light environments. Both male and female butterflies had difficulty discerning UV signals during cloudy weather, but remained competent in detecting fluorescence regardless of ambient lighting. We provide field evidence that butterfly fluorescence and UV are impactful visual signals maintained by sexual selection rather than natural selection, while altogether solving the mystery of insect fluorescence that has perplexed biologists and physicists for decades.
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82
Figure 3.1. Natural and artificial Heliconius butterfly wings and excitation and emission spectra of 3-hydroxy-DL-kynurenine (3-OHK). Heliconius erato (a) under broad spectrum white light and (b) under 365 nm LED light showing fluorescing 3-OHK bands. (c) Artificial
H. erato model under 365 nm LED light, also with fluorescing bands from applied 3-OHK solution. (d) Fluorescence excitation and emission spectra of 3-OHK. There are two excitation peaks, at 307 nm and 441 nm, and an emission peak at 486 nm (from both excitation spectra).
The peak at 478 nm is not true excitation but instead a result of Rayleigh light scattering, and the additional peak at 617 nm is from 2nd order diffraction Rayleigh scattering.
83
Figure 3.2. Reflectance spectra of artificial H. erato butterfly models with and without UV on the (a) dorsal yellow band, (b) ventral yellow band, (c) dorsal red band, and (d) ventral red/pink band. UV reflects from 300-400 nm and can be eliminated altogether using a thin film UV filter.
84
Figure 3.3. Reflectance spectra of artificial H. erato butterfly models with and without fluorescence on the (a) dorsal yellow band and (b) ventral yellow band. Fluorescing models were painted with a 3-OHK pigment solution on the band whereas non-fluorescing models have their yellow band made with a strip of Manila paper.
85
Figure 3.4. Reflectance spectra of (a) Eueides isabella dorsal and ventral non-fluorescing yellow wing pigment, and (b) non-fluorescing Manila paper on F- H. erato butterfly models. The reflectance spectra are very similar.
86
Figure 3.5. Irradiance spectra of (a) open sunlight and the experimental cage during open sunlight conditions, and (b) cloud cover and the experimental cage under cloud cover. Each graph represents the average from five measurements in each condition.
87
Figure 3.6. Male and female H. erato butterflies approach and court UV- and fluorescence- manipulated butterfly models at varying rates. Approaches (a) and courtship events (b) under all light conditions are on the left, and approaches (c) and courtship events (d) under only cloudy conditions are on the right. Shown are the mean approach and courtship values with standard errors (each n = 80 butterflies: 40 males and 40 females for all light conditions; and n = 36: 20 males and 16 females for cloudy conditions only). Asterisks represent the p-values from pairwise comparisons where *p < 0.05, **p < 0.01, ***p < 0.001.
88
Figure 3.7. Male and female H. erato butterflies approach and court UV- and fluorescent- manipulated artificial butterfly models at varying rates, under all light conditions (a-d) and
89 under only cloudy conditions (e-h). All behaviors directed toward UV models are in the left column, and behaviors directed toward fluorescence models are in the right column. Shown are the mean approach and courtship values with standard errors (n = 80 butterflies: 40 males and 40 females for all light conditions; and n = 36: 20 males and 16 females for cloudy conditions only).
90
Figure 3.8. Artificial butterfly models with (UV+) and without (UV-) UV and with (F+) and without (F-) fluorescence experience similar predation rates in field studies. Shown are the proportions of models attacked (total n = 2000: 500 of each model type) and error bars include 95% CIs. The p-values from pairwise comparisons between UV+ and UV-, and F+ and F-, are above 0.05.
91 CHAPTER 4: True UV color vision in a butterfly with two UV opsins
INTRODUCTION
Animals employ a variety of visual signals that are used for intraspecific communication. These signals are best perceived by conspecifics when their visual systems have evolved to accommodate signal detection. True color vision in animals is characterized by wavelength discrimination based on chromatic content and spectral composition of the stimuli, independent of their intensities (Menzel 1979; Goldsmith 1990; Kelber & Pfaff
1999). Animals that have true color vision must use at least two types of photoreceptors, with different spectral sensitivities, to successfully discriminate between multiple wavelengths where the sensitivity curves overlap.
Insects use color vision for multiple tasks, including foraging, host plant detection, and conspecific recognition. Most insects have a short wavelength (S) receptor sensitive in the ultraviolet (UV) and blue ranges, a medium wavelength (M) receptor sensitive in the green range, and a long wavelength (L) receptor sensitive in the yellow-red range, though many insects lack red receptors. In Heliconius passion-vine butterflies, adults have proportionately large heads (relative to body mass) with notable investment in the visual neuropile (Gilbert
1975), which implies selective pressures for increased visual sensitivity. Work has been shown that they can perceive colors across a wide range, from UV wavelengths (300-400 nm), up to as long as 700 nm in the red range (Crane 1955; Swihart 1967, 1972; Zaccardi et al. 2006). There is also evidence that butterflies, including Heliconius, have true color vision
(Kelber & Pfaff 1999; Kinoshita et al. 1999; Zaccardi et al. 2006).
Butterflies typically have only one UV opsin (Vanhoutte et al. 2002; Briscoe et al.
2003; Sauman et al. 2005; Koshitaka et al. 2008), however in Heliconius, an opsin duplication
92 event has occurred in the UV range based on molecular evidence (Briscoe et al. 2010). The two UV-absorbing rhodopsins have λmax absorption at ~355 and ~398 nm, and Heliconius erato specifically has been shown to have spectral sensitivity at 370 nm as indicated by electroretinogram measurements (Struwe 1972). Although present throughout the genus, the duplicated UV opsin is sex-specific in H. erato where females express both opsins but males only express the second opsin with sensitivity at 398 nm (McCulloch et al. in prep).
Heliconius butterflies also have a genus-specific pigment, 3-hydroxy-DL-kynurenine
(3-OHK), found in the yellow scales of the wings. Together, the pigment and the wing ultrastructure reflect UV light in the 300-400 nm range. This wing pigment has evolved in
Heliconius in conjunction with their duplicated UV opsin in the butterfly eye (Briscoe et al.
2010), yet close relatives to this genus lack both the opsin duplication and 3-OHK. It has been predicted that the second UV opsin would allow for better discrimination of conspecifics with respect to the yellow coloration on the wings (particularly in the presence of non-Heliconius mimics, Bybee et al. 2012), and especially with respect to UV wavelengths, but this has no experimental support. Here we test whether Heliconius are capable of discriminating between color wavelengths within in the UV range in the context of foraging, to provide the first direct behavioral evidence that this new UV opsin gene functions in UV color discrimination. We use H. erato male and female butterflies, as well as butterflies from a closely related outgroup,
E. isabella (that lack both the second UV opsin and 3-OHK) as a control. Given evidence that the duplicated UV opsin is only expressed in female H. erato butterflies (McCulloch et al. in prep), we separately tested male and female H. erato to account for this sex-limited adaptation.
We expect that: 1) female H. erato will successfully discriminate between two different UV wavelengths under different light intensity combinations, by using both UV-sensitive
93 photoreceptors, 2) male H. erato and E. isabella will not be able to discriminate between two
UV wavelengths, because they have or express only one UV-sensitive photoreceptor, and 3)
H. erato and E. isabella males and females will be able to discriminate between colors in the blue range to support that they still have intact color vision in the longer wavelength range, using one UV-sensitive photoreceptor and one blue (short wavelength) photoreceptor. By confirming UV color discrimination in H. erato butterflies, we are able to demonstrate the functional significance of UV opsin duplication in animals, connecting the evolution of specialized visual systems to specialized visual signals.
METHODS
Animals
To test butterfly discrimination ability between different UV wavelengths, individual butterflies were first trained to associate a particular wavelength of light with a food source.
H. erato and E. isabella butterflies were purchased as pupae from the Costa Rica
Entomological Supply (La Guácima, Costa Rica). The pupae were kept in a humidified chamber and hung on pieces of cardboard until they emerged as adults. Once their wings had dried, butterflies were removed from the pupal chamber and were individually sexed and marked with a unique number. Butterflies were kept in glassine envelopes in a moist container when they were not being used for experiments. The butterflies were fed using a 10% honey solution with one bee pollen granule dissolved for each 2 ml of solution because in nature,
Heliconius diet consists of both nectar and supplemental protein obtained from flower pollen
(Gilbert 1972; Boggs et al. 1981). Butterflies were only fed on the positive stimulus during the training and testing, so that they only associate a single light wavelength with food. A
94 total of 241 butterflies were used in the study, of which 120 were successfully trained and used in complete trials: 40 H. erato females, 40 H. erato males, and 40 E. isabella (20 females, 20 males).
Behavioral experiments and apparatus
The experiments and training took place indoors in a mesh enclosure constructed from
PVC pipes, measuring 1 m ✕ 70 cm ✕ 90 cm, and the room temperature was fixed at 24° C.
The top of the enclosure was lined with 8 fluorescent tubes (Philips TLD 965 18 W;
Eindhoven, The Netherlands) to provide natural lighting (Zaccardi et al. 2006). Three sides of the enclosure were draped with large white plastic bags so that butterflies were not distracted by other objects in the room. The fourth side of the enclosure, where experimental apparatus was placed, had a large black plastic bag draped behind the mesh to provide highest contrast between the light stimuli and the background.
Our apparatus for training and experiments was previously constructed and used by
Zaccardi et al. (2006). It consists of two stimuli presented side-by-side, separated by 6 cm on two black platforms set on a larger black plate, measuring a total of 20 cm ✕ 10 cm (see
Figure 4.1 for a frontal view photograph of our apparatus). The apparatus was positioned vertically in the center of the black side of the enclosure. The wavelength stimuli were presented to the butterflies (two stimuli at a time) using 10 nm narrow band-pass filters
(Edmund Optics; Barrington, NJ, USA) and emitted through the filters from a KL2500 Schott cold light source (Mainx, Germany) with two light guides connecting the light sources to the stimuli. The light beams, held stable with a light guide holder, passed first through a diffusor and interference filter, then through a transparent Plexiglass feeder disk (see Figure 3 in
95 Zaccardi et al. 2006 for a diagram of the apparatus). For our experiments we used four different wavelengths of light as stimuli separated into paired choice tests: 380 nm versus 390 nm, and 400 nm versus 436 nm. We use 380 and 390 nm as the UV stimuli because this is an area where the sensitivity curves of the two UV photoreceptors are estimated to overlap. We also chose 400 nm and 436 nm, to support intact color vision using one UV photoreceptor and a blue photoreceptor. The light intensities for each wavelength could be adjusted using a dial on the light source that changed the energy delivered to the light bulb. Between these four wavelengths of light, the intensities for the experiments ranged from 9.56 ✕ 1015 to 1.71 ✕
1017; quanta s-1 steradian-1 cm-2.
Butterfly training
Butterflies were trained and fed for the first time within 15 hours of eclosion. They were first allowed to acclimate to the experimental cage environment up to one minute before training, and only one butterfly was trained at a time. A droplet of food solution was placed in a small trough attached to the front of the feeder disk for the trained stimulus (+), and the untrained stimulus (-) feeder trough remained empty. Each butterfly was trained by having its wings held together with forceps, and then manually, but slowly, moved from the rear of the enclosure (opposite end of the apparatus) toward the apparatus to simulate a flying motion.
The butterfly was then slowly waved in front of both the trained and untrained stimulus, and finally held in front of the trained stimulus where its proboscis was uncoiled until it came into contact with the food solution. At this moment the butterfly began to drink. After the proboscis was manually uncoiled 2-3 times, the butterfly was able to uncoil the proboscis on its own at the sight of the stimuli. The procedure of carrying the butterfly with forceps from
96 the rear of the cage to the light sources to feed was repeated 5 times per training session, with two training sessions per day separated by approximately 6 hours. Each time the butterfly fed from the trained stimulus, it was allowed to drink for 10 seconds, except for the very last training segment of the day where it was allowed to drink for several minutes. During training and between training sessions, the placement of the trained and untrained stimuli (left or right side of the apparatus) was randomly switched so that the butterfly did not simply learn to associate the left or right light with a food source. The apparatus was also cleaned thoroughly after each training session to minimize any association of pheromone cues to the stimulus.
After about 4-5 days of training, butterflies were capable of independently flying toward the apparatus when released from the rear of the cage, at which they were able to make a choice to fly to one of the two light stimuli. At this point, the trained butterflies were starved for 20-
24 hours then their choice trials began.
Experimental trials
During trials, butterflies were individually released from the rear of the enclosure and given the opportunity to fly to one of the two light stimuli presented on the feeder apparatus.
A droplet of food solution remained on the positive, trained stimulus feeder, and a droplet of water was placed in the untrained stimulus feeder as a control. Only one butterfly was used at a time during experiments. Each time a butterfly approached and touched the feeder within 2 cm of the light stimulus (on that corresponding light’s platform, Figure 4.1), with either its proboscis or tarsus, this was counted as a choice. Most butterflies flew directly to the light stimulus. If a butterfly touched the feeder more than once during an approach, only the first point of contact was counted. Allowing the butterflies to independently fly to one light
97 stimulus or the other is a reliable, non-trivial way to measure a choice that was made. Each butterfly was allowed 15 choices with each wavelength pair, at one of three intensity combinations listed below, making a total of 45 choices made per butterfly. Not all choice experiments were recorded in one day for each butterfly, and depended on individual behavior.
Choice experiments with each butterfly spanned 1-3 days.
A separate cohort of butterflies was trained with each wavelength pair, because the butterflies did not survive long enough to be trained multiple times. Ten individuals each of H. erato females, H. erato males, and E. isabella (five males, five females) were first trained to
390 nm (+), and then tested for UV discrimination ability between 390 nm (+) and 380 nm. A new cohort with the same number of individuals was trained to 380 nm (+) and given the choice between the two UV stimuli. Two new cohorts of butterflies, of the same sample sizes described above, were used for training to 400 nm (+) (to discriminate between 400 nm and
436 nm using both a UV and blue photoreceptor) and to 436 nm (+) (also to discriminate between 400 nm and 436 nm). During experiments, butterflies were allowed to drink for only
1-2 seconds then gently carried back to the rear of the cage again with forceps. Between choices, the placement of the trained stimulus (left or right) was randomly switched, as during training, in order to prevent a learning association with one side of the apparatus. Three different approximate ratios of the physical intensities, or brightness, of the +/-
(trained/untrained) stimuli were used: 0.067, 1.0, and 15.0 (or 1:15, 1:1, and 15:1). The actual calculated ratios are 0.062, 1.0, 16.213 for 380 vs. 390 nm; and 0.0635, 1.0, 15.741 for 400 vs.
436 nm. These intensity ratios are described throughout the rest of this study as 1:15, 1:1, and
15:1, i.e. the trained stimulus (+) at 15 times less bright than the untrained stimulus (-), equal intensities for both stimuli, and the trained stimulus (+) at 15 times brighter than untrained
98 stimulus (-). Butterflies first completed trials at an intensity combination of 1:1 (15 choices each), to indicate discrimination ability between the wavelengths at equal intensities.
Following this test they were given random choices between intensities of 1:15 or 15:1
(trained:untrained) until they had completed 15 choices with each intensity combination.
Allowing butterflies to make choices to approach each stimulus under multiple intensity combinations will allow us to determine whether a butterfly chooses a wavelength due to actual color discrimination, or due to preference for the trained brightness rather than the trained wavelength.
The number of correct versus incorrect choices each butterfly made at different intensity combinations was modeled as dependent upon wavelength using general linear models, with Poisson distribution, in R statistical software (R Development Core Team 2010).
We compared the ability of each butterfly type (H. erato females, H. erato males, and E. isabella) to discriminate between the wavelength combinations at the different intensities, as well as examined how discrimination abilities differed between all three butterfly types used in the study.
RESULTS
UV discrimination
To test UV wavelength discrimination in butterflies, we trained H. erato and E. isabella butterflies to a particular wavelength of UV light, and then presented the butterflies with both the rewarded (trained) and an unrewarded (untrained) UV light stimulus at different intensity combinations. Butterflies were first trained to 390 nm, then offered a choice between
390 nm and 380 nm, and then new butterflies were trained to 380 nm and offered a choice
99 between the same two UV wavelength pairs. For each trained cohort of butterflies, we used 10 female H. erato, 10 male H. erato, and 10 E. isabella (5 females and 5 males).
At the trained intensity of 1:1 (equal intensities) for 390 and 380 nm, female H. erato chose the trained light stimulus, 390 nm, significantly more than the untrained stimulus, 380 nm (z-value = 6.791, p < 0.0001, Figure 4.2a). This indicates their ability to distinguish between the two UV wavelengths. The females continued to choose the correct, trained stimulus under varying light intensity combinations. At an intensity ratio of 1:15 (rewarded : unrewarded), females significantly chose 390 nm over 380 nm (z-value = 5.19, p < 0.0001,
Figure 4.2a); and at an intensity of 15:1 (rewarded : unrewarded), females also chose 390 nm over 380 nm (z-value = 7.35, p < 0.0001, Figure 4.2a). There was no difference between female preference for the correct stimulus with a 1:1 and 1:15 light ratio (z-value = -0.794, p
= 0.427), or with a 1:1 and 15:1 light ratio (z-value = 0.319, p = 0.749), meaning that females chose the correct light stimulus (390 nm) equally across all light intensity combinations.
With respect to male behavior, at the trained intensity of 1:1 for 390 and 380 nm, male
H. erato chose both the trained (390 nm) and untrained (380 nm) light stimuli equally (z- value = -0.49, p = 0.624, Figure 4.2b). This suggests they cannot distinguish between the two
UV wavelengths. However, the males significantly preferred the correct, trained stimulus
(390 nm) when it was presented 15x brighter than the untrained stimulus (ratio 15:1 for rewarded : unrewarded; z-value = 6.421, p < 0.0001, Figure 4.2b); and they significantly preferred the incorrect, untrained (unrewarded) stimulus, 380 nm, at the intensity of 1:15
(rewarded : unrewarded; z-value = -6.671, p < 0.0001, Figure 4.2b). These results suggest that males prefer the brighter stimulus regardless of light wavelength, and further support their inability to discriminate between 390 and 380 nm. Comparing male and female performance,
100 females significantly prefer the correct stimulus (390 nm) more than males when 390 vs. 380 nm are at intensities of 1:1 (z-value = -3.427, p = 0.0006), and at intensities of 1:15 (z-value
= -6.126, p < 0.0001), respectively. However, males and females equally choose the correct stimulus, 390 nm, when the intensity of trained : untrained ratio is at 15:1 (z-value = -0.514, p
= 0.607).
With E. isabella, at the trained intensity of 1:1 for 390 and 380 nm, individuals had similar behavior to male H. erato in that they chose both the trained (390 nm) and untrained
(380 nm) light stimuli equally (z-value = 0.327, p = 0.744, Figure 4.2c). They were able to significantly choose the correct stimulus (390 nm) only when it was 15x brighter than the untrained stimulus (z-value = 6.791, p < 0.0001, Figure 4.2c), and they chose the untrained stimulus (380 nm) significantly more when it was 15x brighter than the trained, correct stimulus (z-value = -6.293, p < 0.0001, Figure 4.2c).
The same series of tests were repeated with a new cohort of butterflies, 10 female H. erato, 10 male H. erato, and 10 E. isabella, and this time individuals were trained to 380 nm and then given the choice experiment of 380 nm or 390 nm under varying intensity ratios:
1:15, 1:1 (trained ratio), and 15:1. Female butterflies were again consistent in discriminating between the trained (380 nm) and untrained (390 nm) stimuli when intensities were the same
(z-value = -6.671, p < 0.0001, Figure 4.3a), when the trained stimulus was 15x brighter (z- value = -7.793, p < 0.0001, Figure 4.3a), and when the trained stimulus was 15x less bright
(z-value = -5.194, p < 0.0001, Figure 4.3a). Male H. erato butterflies were incapable of discriminating between the different wavelengths when presented at equal intensities (z-value
= -0.327, p = 0.744, Figure 4.3b), and chose the incorrect stimulus when it was 15x brighter than the correct, trained stimulus (z-value = 6.162, p < 0.0001, Figure 4.3b). Males did,
101 however, choose the correct stimulus when it was presented at an intensity ratio of 15x brighter than the untrained stimulus (z-value = -5.194, p < 0.0001, Figure 4.3b). Similar to male behavior, E. isabella could not distinguish between the two wavelengths presented at a
1:1 intensity ratio (z-value = 0.327, p = 0.744, Figure 4.3c). They significantly preferred the trained stimulus only when 15x brighter (z-value = -7.024, p < 0.0001, Figure 4.3c), and preferred the untrained stimulus also only when 15x brighter (z-value = 7.346, p < 0.0001,
Figure 4.3c). In sum, female H. erato can always discriminate between 380 and 390 nm, consistently preferring the correct, trained stimulus, whereas males and E. isabella struggle with discrimination and only choose the correct stimulus when it is at a brighter intensity than the incorrect, untrained stimulus.
Short wavelength discrimination
To provide evidence for intact non-UV color vision for male H. erato and male and female E. isabella, we repeated the series of discrimination tests using 400 nm and 436 nm narrow bandpass filters which would allow short wavelength discrimination using one UV photoreceptor and a blue photoreceptor. These tests were carried out with new cohorts of butterflies, 10 female H. erato, 10 male H. erato, and 10 E. isabella. Individuals were first trained to 400 nm and then given choice tests between 400 nm and 436 nm under intensity ratios of 1:15, 1:1 (trained ratio), and 15:1. As expected, when trained to 400 nm, female H. erato chose the correct stimulus when offered both light wavelengths at equal intensities (z- value = -7.93, p < 0.0001, Figure 4.4a), at an intensity of 1:15 for trained : untrained (z-value
= -7.54, p < 0.0001, Figure 4.4a), and at an intensity of 15:1 of trained : untrained (z-value = -
8.099, p < 0.0001, Figure 4.4a). Male H. erato behavior and E. isabella behavior paralleled
102 female discrimination behavior between the two longer wavelengths, with male H. erato choosing the correct wavelength at intensity combinations of 1:1 (z-value = -7.93, p < 0.0001,
Figure 4.4b), 1:15 (z-value = -7.54, p < 0.0001, Figure 4.4b), and 15:1 (z-value = -7.987, p <
0.0001, Figure 4.4b); and E. isabella also choosing the correct, trained wavelengths at intensity ratios of 1:1 (z-value = -7.63, p < 0.0001, Figure 4.4c), 1:15 (z-value = -6.671, p <
0.0001, Figure 4.4c), and 15:1 (z-value = -7.445, p < 0.0001, Figure 4.4c).
When trained to 436 nm, all butterflies continued to show a significant preference for the correct wavelength stimulus regardless of intensity combination. Female and male H. erato preferred the trained stimulus at equal intensities (z-value = 7.930, p < 0.0001 for females, Figure 4.5a; z-value = 7.714, p < 0.0001 for males, Figure 4.5b), at an intensity combination of 1:15 (z-value = 7.242, p < 0.0001 for females, Figure 4.5a; z-value = 6.909, p
< 0.0001 for males, Figure 4.5b), and at 15:1 intensity (z-value = 7.987, p < 0.0001 for females, Figure 4.5a; z-value = 7.865, p < 0.0001 for males, Figure 4.5b). E. isabella followed the same trend and significantly preferred the correct wavelength (436 nm) at an intensity combination of 1:1 (z-value = 7.793, p < 0.0001, Figure 4.5c), 1:15 (z-value = 6.293, p < 0.0001, Figure 4.5c), and 15:1 (z = 7.930, p < 0.0001, Figure 4.5c). There was no statistically detected difference between H. erato male and female behavior, or between E. isabella and H. erato behavior (all p > 0.05), for selecting the correct light wavelength when trained to either 400 nm or 436 nm. All butterflies expressed the same discrimination abilities between 400 nm and 436 nm across all three intensity combinations.
103 DISCUSSION
We conclude that H. erato has true color vision in the UV range, at least between 380 nm and 390 nm, and that this is a female-limited behavior. This represents one of the first studies to show that an animal can discriminate between more than one UV color using two
UV photoreceptors, providing the first direct behavioral evidence that this new UV opsin gene in Heliconius is used in the context of UV color discrimination. We also show that H. erato and E. isabella have color vision in the blue range between 400 nm and 436 nm, using both a
UV and blue photoreceptor. Butterflies were capable of color discrimination regardless of their light intensities, supporting that this is true color vision and not simply wavelength- specific behavior.
True UV color discrimination is made possible in H. erato as a result of their second
UV-sensitive photoreceptor, which has been present in the genus since it originated (Briscoe et al. 2010). Opsin duplication events, as well as spectral tuning (where peak wavelengths shift to a more biologically relevant spectral region to accommodate an organism’s visual recognition needs), are not uncommon in butterflies. For example, a species of lycaenid butterfly uses its duplicated blue opsin to see green, perhaps for discrimination of oviposition sites or mate detection (Sison-Mangus et al. 2008), and the pierid butterfly Pieris rapae has both spectrally tuned blue-absorbing pigments and a duplicated blue opsin, which may be crucial for mate recognition and driven by female-specific UV wing reflection (Wakakuwa et al. 2010).
In Heliconius erato, two UV opsins allow for UV color discrimination, although the diversity of duplicated opsin expression between sexes is thought-provoking. It is unclear why females would benefit from UV color discrimination whereas males do not have this
104 discrimination ability (McCulloch et al. in prep). Perhaps the adaptive function of UV color discrimination in butterflies stems beyond intraspecific communication, and has implications for host plant recognition or specific pollen plant detection. Within Heliconius, different species are specialists on Passiflora host plants for oviposition, and many of these Passiflora species contain extrafloral nectaries that resemble yellow Heliconius eggs (Williams &
Gilbert 1981). Many species of Heliconius avoid ovipositing on host plants that already have eggs because larvae have cannibalistic tendencies (Brown 1982; De Nardin & de Araújo
2011), and fresh, new shoots that are most edible for larvae can be of limited quantity (Gilbert
1982). It is possible that the egg mimic structures differ spectrally from actual eggs in their
UV reflectance, thus allowing the additional UV opsin to provide discrimination between natural and mimic eggs. There is also the possibility that the host plant leaves, or even specific pollen plants for foraging (such as Psychotria, Lantana, and Psiguria), have unique spectral properties in the UV range that would make a second UV opsin advantageous to females but not as relevant for males. Further research is welcomed to test these concepts.
It makes logical sense that the unique Heliconius yellow wing pigment 3-OHK, that co-evolved with the duplicated UV opsin, would be easier to detect for butterflies that have two UV opsins than those that only have one UV opsin (thus promoting the idea that this pigment acts as a private channel for communication between butterflies in this genus, Bybee et al. 2012). The pigment has special spectral properties that result in a distinct reflectance slope between 300-400 nm (see Figure 3 in Briscoe et al. 2010), and having photoreceptor sensitivities at ~355 nm and ~398 nm should allow for discrimination of this particular pigment compared to other yellow pigments (Bybee et al. 2012). Heliconius are part of a large mimicry complex that includes both within-genus mimics that are unpalatable (Müllerian
105 mimics), as well as non-Heliconius mimics, some of which may be palatable (Batesian mimics). Non-Heliconius mimics do not contain 3-OHK pigment, and therefore it would be favorable to have two UV opsins for discrimination between yellow pigments on mimics versus conspecifics. This pigment is also fluorescent and acts as a reliable visual signal under variable environmental conditions (Finkbeiner & Briscoe, in prep), with strong implications that it functions for conspecific signaling. Therefore, any additional aid in signal detection would be crucial for these butterflies at both short and long ranges.
Although a second UV opsin would still not allow for discrimination between H. erato males and females, it could potentially allow for discrimination between H. erato and its co- mimic Heliconius melpomene. This is based on evidence by Bybee et al. (2012) that
Heliconius 3-OHK yellows between the two mimetic species are discriminable from each other (for individual yellow wing reflectance spectra see Supporting Information Figure 2 in
Briscoe et al. 2010). H. melpomene has an identical wing pattern to H. erato and is found in the same geographic area (and often in the same forest habitat) as H. erato, so any ability for the butterflies to distinguish between the two species would be useful. Both H. erato and H. melpomene may also interact together by forming communal roosts in the same home range, which would help provide added anti-predatory benefits (Finkbeiner et al. 2012). Heliconius co-mimics have been observed foraging together (pers. obs) and roosting together (although uncommon; Mallet 1986, Finkbeiner et al. 2014), and this could represent another instance where identifying a Heliconius individual (whether or not co-species) would be beneficial.
Although other animals have photoreceptor spectral sensitivity in the UV range, it has not yet been demonstrated that they have true UV color discrimination. Perhaps the closest example is seen in the hummingbird hawkmoth Macroglossum stellatarum, where individuals
106 learned to discriminate between 365 nm and 380 nm, but it was not possible to determine whether they were able to do so by means of true color vision or an achromatic cue (Kelber &
Henique 1999). Many insects have UV vision (Briscoe & Chittka 2001) and several hymenopteran groups with UV sensitivity have shown fine color discrimination in longer wavelengths (Backhaus & Menzel 1987; Camlitepe & Akosy 2010), but still lack evidence for color discrimination between UV wavelengths. In the case of the mantis shrimp and similar stomatopods, whose compound eyes possess the largest number of photoreceptor types known in any animal (including four UV-sensitive photoreceptors, Marshall & Oberwinkler 1999), there is little indication that their photoreceptors function with respect to true color vision at all (Thoen et al. 2014). However our study provides clear evidence that, despite variations in light intensity, butterflies have the ability to finely discriminate between two UV wavelengths.
This represents the first direct behavioral result that any animal can see multiple UV wavelengths using true color vision, supporting that the new UV opsin gene in Heliconius functions in the context of UV color discrimination. Our work demonstrates an adaptive significance for UV opsin duplication in animals – and given that the duplicated UV opsin in
Heliconius has co-evolved with a unique UV pigment found exclusively in this genus – we are able to build a connection between the evolution of specialized visual systems to specialized visual signals.
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107 Briscoe, A. D., G. D. Bernard, A. S. Szeto, L. M. Nagy, and R. H. White. 2003. Not all butterfly eyes are created equal: Rhodopsin absorption spectra, molecular identification and localization of ultraviolet-, blue-, and green-sensitive rhodopsin-encoding mRNAs in the retina of Vanessa cardui. J. Comp. Neurol. 458:334-349. Briscoe, A. D., S. M. Bybee, G. D. Bernard, F. Yuan, M. P. Sison-Mangus, R. D. Reed, A. D. Warren, J. Llorente-Bousquets, and C.-C. Chiao. 2010. Positive selection of a duplicated UV- sensitive visual pigment coincides with wing pigment evolution in Heliconius butterflies. Proc. Natl. Acad. Sci. USA. 107:3628-3633. Briscoe, A. D., and L. Chittka. 2001. The evolution of color vision in insects. Ann. Rev. Entomol. 46:471-510. Brown, K. S. Jr.1981. The biology of Heliconius and related genera. Annu. Rev. Entomol. 26:427-456. Bybee S. M., F. Yuan, M. D. Ramstetter, J. Llorente-Bousquets, R. D. Reed, D. Osorio, and A. D. Briscoe. 2012. UV photoreceptors and UV-yellow wing pigments in Heliconius butterflies allow a color signal to serve both mimicry and intraspecific communication. Am. Nat. 179:38-51. Camlitepe, Y., and V. Akosy. 2010. First evidence of fine colour discrimination ability in ants (Hymenoptera, Formicidae). J. Exp. Biol. 213:72-77. Crane, J. 1955. Imaginal behaviour of a Trinidad butterfly, Heliconius erato hydara Hewitson, with special reference to the social use of color. Zoologica. 40: 167–196.
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Figure 4.1. A male H. erato butterfly that has just landed on the light source apparatus during a trial. The light wavelengths presented are 390 nm (left) and 380 nm (right) at equal intensities.
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Figure 4.2. Proportion of correct choices to the trained wavelength, 390 nm, for female
(a) and male (b) H. erato and E. isabella (c) butterflies under varying light intensities.
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Figure 4.3. Proportion of correct choices to the trained wavelength, 380 nm, for female
(a) and male (b) H. erato and E. isabella (c) butterflies under varying light intensities.
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Figure 4.4. Proportion of correct choices to the trained wavelength, 400 nm, for female
(a) and male (b) H. erato and E. isabella (c) butterflies under varying light intensities.
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Figure 4.5. Proportion of correct choices to the trained wavelength, 436 nm, for female
(a) and male (b) H. erato and E. isabella (c) butterflies under varying light intensities.
115 SUMMARY OF DISSERTATION CONCLUSIONS
Visual signals represent one of the most common forms of communication in animals. It has long been known that visual signals play an important role in predator and mate recognition in many animal species. Visual signals can be expressed in terms of color (chromatic cues), brightness (achromatic cues), context (patterns), magnitude, UV reflectance, as well as fluorescence, and often times animal visual systems are specialized to discriminate between particular visual features that are more biologically relevant. My dissertation work touches on all these aspects.
My first dissertation chapter, which investigated the adaptive function of communal roosting behavior in aposematic Heliconius butterflies, concludes that magnitude – or repetition of a particular pattern (in this case butterfly wings) – plays a role in the effectiveness of roosts as anti-predator signals. Heliconius erato butterflies that convene in medium-sized groups are best protected from predation, and my data suggest that groups too large or too small are not as effective in deterring predators.
Experimentally optimal group sizes corresponded closely with the average number of H. erato butterflies found in wild roosts, reinforcing the apparent anti-predatory benefits of forming medium-sized groups. These results imply a strong visual signal communicated to predators through communal roosting behavior, and based on results from other roosting studies, there is also a strong visual component associated with roost assembly and conspecific recognition during roost formation.
Although communal roosts themselves act as an aposematic signal, for my second chapter I decided to dissect the specific visual signals used by predators to detect and avoid Heliconius, as well as which of these signals the butterflies might be using to
116 identify conspecifics. To do this, I determined the relative contributions of color versus pattern for predator avoidance and mate attraction in H. erato using artificial butterfly models that represented variations of the natural butterfly phenotype. My results showed that color signals are most important, based on the highest predation frequency and lowest mate preference for achromatic (colorless) models. I found that the same signals selected for by predators are most preferred by mates. This interaction between aposematism and mate choice indicates cooperation between the visual signals that influence individual fitness, and implies that these cooperative visual signals are used as honest signals to communicate unprofitability to predators and high survival success to mates.
Based on my results from the second study, and because the visual stimuli in an animal’s appearance can be quite diverse, for my third chapter I decided to investigate other visual features communicated through butterfly wings that are less commonly considered such as ultraviolet (UV) and fluorescence. An aposematic animal will benefit most if the visual signals it relies on to deter predators (such as color, pattern, UV, and fluorescence) are also effective at attracting mates, thus reinforcing the evolution of its color patterns. I found that UV and fluorescence play a minimal role (if any) in anti- predator defense. However, these visual signals are important for intraspecific signaling in
Heliconius and are likely maintained through sexual selection, and fluorescence is a more persistent signal than UV in cloudy weather. This represents the first study to demonstrate that naturally occurring fluorescence in butterflies, or any insect, acts as a visual signal.
For my fourth and final chapter, to complement the results I found with respect to
UV and fluorescent signaling in Heliconius, I carried out in-cage experiments to show how H. erato can discriminate between two wavelengths within the UV range under
117 different light intensities. Heliconius have a specialized visual system that includes a duplicated UV-sensitive photoreceptor in the eye. This opsin duplication event occurred in conjunction with the evolution of a unique yellow UV and fluorescent pigment in the wings, 3-hydroxy-DL-kynurenine (3-OHK). The coevolution of the additional UV photoreceptor with the special wing pigment suggests that the second UV opsin may play a role in conspecific recognition. This represents the first study to show true UV color vision in animals, and provides the first direct behavioral evidence that this new UV opsin in Heliconius is used for UV color discrimination. This confirms the importance of multiple UV visual stimuli to invertebrate perception in the context of foraging, which could have implications with respect to conspecific recognition for animals with specialized UV signals and UV vision.
My dissertation projects show an example of how some color pattern signals can be used together to communicate information to both predators and conspecifics, as well as how specialized color signals can be tailored into separate roles according to a receiver’s ability to discriminate and classify colors. My dissertation work (i) provides insight on the types of ecological and evolutionary pressures that contribute to social behavior in historically solitary animals, (ii) allows us to understand how aposematic signaling may drive the evolution of social behavior in the context of visual ecology, (iii) presents information on the relative contributions of specific visual signals that result in predator avoidance and mate attraction, (iv) shows how both natural and sexual selection can work together to favor the evolution of specific animal phenotypes, and (v) demonstrates the adaptive significance of UV opsin duplication in animals, connecting the evolution of specialized visual systems to specialized visual signals.
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