UNIVERSITY OF CALIFORNIA, IRVINE
Insights into butterfly ecology and evolution
DISSERTATION
submitted in partial satisfaction of the requirements for the degree of
DOCTOR OF PHILOSOPHY
in Biological Sciences
by
Nélida Beatriz Mercedes Pohl Pohl
Dissertation Committee: Associate Professor Adriana D. Briscoe, Chair Professor Diane R. Campbell, co-Chair Professor Timothy J. Bradley
2009
1
© 2009 Nélida Beatriz Mercedes Pohl Pohl
2
The dissertation of Nélida Beatriz Mercedes Pohl Pohl is approved and is acceptable in quality and form for publication on microfilm and in digital formats:
______
______Committee Chair
______Committee co-Chair
University of California, Irvine 2009
3 TABLE OF CONTENTS
Page
LIST OF FIGURES iv
LIST OF TABLES v
ACKNOWLEDGMENTS vi
CURRICULUM VITAE vii
ABSTRACT OF THE DISSERTATION ix
INTRODUCTION 1
CHAPTER 1: Impact of duplicate gene copies on phylogenetic analysis and divergence time estimates in butterflies 6
Abstract 7 Introduction 9 Materials and Methods 13 Results and Discussion 20 Conclusions 34
CHAPTER 2: Butterflies show flower preferences but not constancy 36
Abstract 37 Introduction 39 Materials and Methods 43 Results 52 Discussion 58
TABLES AND FIGURES 64
REFERENCES 118
4 LIST OF FIGURES
Page
Figure 1.1 Alignments of UVRh, BRh, LWRh, EF-1α, and COI 64
Figure 1.2 Maximum Parsimony tree 86
Figure 1.3 Maximum Likelihood trees 88
Figure 1.4 Bayesian trees 90
Figure 1.5 Maximum parsimony, maximum likelihood and Bayesian faster trees 92
Figure 1.6 Bayesian estimates of rate multiplier parameter (m) by gene partition 93
Figure 1.7 Bayesian divergence time estimates with slower evolving genes 94
Figure 1.8 Bayesian divergence time estimates with faster evolving genes 95
Figure 2.1 Flower reflectance spectra 110
Figure 2.2 Spontaneous flower preferences 112
Figure 2.3 Spontaneous color preferences 113
Figure 2.4 Spontaneous morphology preferences 114
Figure 2.5 Spontaneous display size preferences 115
Figure 2.6 Seed production 116
5 LIST OF TABLES
Page
Table 1.1 List of primers 96
Table 1.2 Taxa and genes 98
Table 1.3 Tajima relative rates tests 100
Table 1.4 Partitioned Bremer support values 101
Table 1.5 Penalized likelihood age estimates 102
Table 1.6 Bayesian age estimates 103
Table 1.7 Bayesian age estimates using slower evolving gene copies 104
Table 1.8 Bayesian age estimates using faster evolving gene copies 107
Table 2.1 Tests of butterfly flower constancy behavior 117
6 ACKNOWLEDGEMENTS
I would like to thank my committee; Adriana Briscoe, Diane Campbell and Tim Bradley for the support and criticism provided over the years. I’m also grateful to Art Weis for his help during the earlier stages of this dissertation. Stimulating discussions with Francesca Frentiu, Nick Waser and Mary Price generated ideas that improved this work. I thank Jennifer Van Wyk and Zac Davies for their participation in field work, and Marilou Sison-Mangus, Emily Yee and Saif Liswi for their contribution to the laboratory work. Jeffrey Thorne provided helpful assistance with data analyses. Support and funding came from Fulbright-CONICYT, UCI Edward A. Steinhaus Annual Memorial Award, Sigma Xi GIAR, the Lee R. G. Snyder Memorial Fund at RMBL, Southern California Phi Beta Kappa International Student Scholarship, UCI Miguel Velez Fellowship Award, site NSF REU grant DBI 0242960 to RMBL, NSF DEB-9806547, IOS-0646060 and IOS-0819936, and grants from the UCI Undergraduate Research Program. I am also indebted to my family and friends in Chile, and to the new friends I have made in these past five years, for the unconditional love that made me who I am today.
7 CURRICULUM VITAE
Nélida Pohl
EDUCATION
2009 PhD. Biological Sciences, Department of Ecology and Evolutionary Biology, University of California, Irvine, USA. 2003 MSc. Ecology and Evolutionary Biology, Universidad de Chile 2001 Photography Diploma, Universidad Católica de Chile 2000 BSc. Biological Sciences, Universidad de Chile
GRANTS AND FELLOWSHIPS
2007-2008 UCI Miguel Velez Fellowship Award 2007-2008 Southern California Phi Beta Kappa International Student Scholarship 2007 Rocky Mountain Biological Laboratory Snyder grant 2006 Sigma Xi Grants in Aid of Research 2005-2006 UCI Edward A. Steinhaus Annual Memorial Award 2005 Rocky Mountain Biological Laboratory Snyder grant 2003-2007 Government of Chile (CONICYT) fellowship. 2003-2007 Fulbright fellowship. 2002-2003 Graduate Fellowship from the Millenium Center for Advanced studies in Ecology and Biodiversity, Chile. 2002-2003 University of Chile Graduate Thesis Support Grant.
PROFESSIONAL APPOINTMENTS
2003-2008 Teaching assistant, Department of Ecology and Evolutionary Biology, University of California, Irvine. 2000-2002 Teaching assistant, Facultad de Ciencias, Universidad de Chile. 2000-2001 Research assistant, Laboratorio de Neurobiología y Biología del Conocer, Departamento de Biología, Universidad de Chile.
PRESENTATIONS AT SCIENTIFIC MEETINGS
2008 Conference on the Ecology and Evolution of Plant-Pollinator Interactions, Milwaukee, Wisconsin. 2007 Invited speaker 9th International Pollination Symposium, Ames, Iowa. 2006 7th International Workshop on Molecular Biology and Genetics of the Lepidoptera, Crete, Greece 2006 IX Congreso Latinoamericano de Botánica, Santo Domingo, Republica Dominicana. 2005 NAS Sackler Colloquium on Tapestry of Life, Irvine, CA. 2005 Evolution Conference, Fairbanks, Alaska USA
8 2004 15th Science Conference of Sigma Chapter - Graduate Women in Science. California State University, Fullerton, CA. 2004 Southern California Animal Behavior conference, University of California, Los Angeles, CA. 2003 CalPEG (California Population and Evolutionary Genetics Meeting) University of California, Irvine, CA. 2002 Congreso anual de la Sociedad de Biología de Chile, Puyehue, Chile 2002 VIII Congreso Latinoamericano de Botánica, Cartagena de Indias, Colombia. 2001 Society of Neuroscience Meeting, San Diego, CA. 2001 Congreso anual de la Sociedad de Biología de Chile, Pucón, Chile.
PUBLICATIONS
Pohl, N, J. Van Wyk, and D.R. Campbell. Butterflies show flower preferences but not constancy. In preparation for Oecologia.
Pohl, N, M.P. Sison-Mangus, E.N. Yee, S.W. Liswi and A.D. Briscoe. Impact of duplicate gene copies on phylogenetic analysis and divergence time estimates in butterflies. Submitted to BMC Evolutionary Biology.
Medel, R., A. Valiente, C. Botto-Mahan, G. Carvallo, F. Perez, and N. Pohl. & Navarro, L. 2007. The influence of insects and hummingbirds on the geographical variation of the flower phenotype in Mimulus luteus. Ecography 30: 812-818.
Pohl, N, G. Carvallo, C. Botto-Mahan, and R. Medel. 2006. Non-additive effects of flower damage and hummingbird pollination on the fecundity of Mimulus luteus. Oecologia 149: 648-655.
Botto-Mahan, C., N. Pohl, and R. Medel. 2004. Nectar guide fluctuating asymmetry does not relate to female fitness in Mimulus luteus. Plant Ecology 174: 347 - 352.
Herrera, G., M.J. Fernandez, N. Pohl, M. Diaz, F. Bozinovic, and A. Palacios. 2004. Sistema visual en el colibri austral (Sephanoides sephaniodes) y el picaflor cordillerano (Oreotrochilus leucopleurus): electrorretinografia y coloracion. Ornitologia Neotropical 15 (Suppl.): 215-222.
Marín, G., J.C. Letelier, P. Henny, E. Sentis, G. Farfán, F. Fredes, N. Pohl, H. Karten, and J. Mpodozis. 2003. Spatial organization of the pigeon tectorotundal pathway: an interdigitating topographic arrangement. The Journal of Comparative Neurology 458: 361-380.
9 ABSTRACT OF THE DISSERTATION
Insights into butterfly ecology and evolution
By
Nélida Beatriz Mercedes Pohl Pohl
Doctor of Philosophy in Biological Sciences
University of California, Irvine, 2009
Associate Professor Adriana D. Briscoe, Chair
Professor Diane R. Campbell, co-Chair
This dissertation examined features of the butterfly visual system. The first part
used opsin genes, which code for the visual pigment proteins, in reconstruction of
butterfly phylogenies. The second part examined butterfly behavioral responses to flower
color visual cues. The first goal was to examine the effect of incorporating duplicate
opsin gene copies on tree reconstruction and divergence time estimation. Sequences from
5 genes, including 3 opsins, were obtained from 27 taxa. Regardless of the phylogenetic
reconstruction method, combined data sets analyses using either slower or faster evolving
copies of duplicate genes, as well as individual analyses of blue and long-wavelength opsin genes, which are present in multiple copies in some lineages, resulted in a single topology in agreement with our current understanding of family relationships. Two methods resulted in similar divergence time estimates regardless of whether faster or slower evolving copies were used. Family-level results were congruent with other recent estimates, indicating an age of at least 150 MY for the first familial divergence. These results are consistent with overlapping timeframes for the diversification of butterfly
10 families and angiosperms and suggest the use of duplicate gene copies for phylogenetic
reconstruction and divergence time estimation.
The second goal was to explore the role of color in flower visiting behavior. This
study represented the first field-based attempt with butterflies to phenotypically manipulate flower color and decouple its effect from that of other traits. In order to assess if butterflies possess spontaneous color preferences and if they behave as constant flower visitors, all visits to artificial arrays of Asteraceae flowers were recorded. Natural arrays contained unmanipulated flowers of two species. Flowers in ‘color’ arrays differed only in color, while ‘morphology’ arrays had the effect of color eliminated. Different combinations of color and morphology preferences were found in the species examined.
P. campestris and C. oetus had color but no ‘morphology’ preferences. S. mormonia and
L. heteronea had color and morphology preferences. The behavior of L. heteronea suggests a potential to exert correlational selection on associations of flower traits. In this first field experimental test of butterfly flower constancy, no species showed constancy.
11 INTRODUCTION
The beauty of butterflies, and their incredible morphological and ecological diversity, have always captured our interest and imagination. Butterfly enthusiasts have amassed impressive amounts of natural history information that constitute a rich source from which professional scientists have often drawn questions about the mechanisms responsible for that diversity. This seminal wealth of knowledge is partly responsible for the increasing use of butterflies as model organisms for the study of ecology and evolution (Boggs et al., 2003). Both the traits that unify butterflies and those that differentiate butterflies contribute to this status. Butterflies as a whole are relatively easy to find and track and their major phylogenetic relationships are reasonably well resolved.
By providing a plethora of diverse solutions to ecological conundrums, they constitute an excellent system for comparative ecological and evolutionary biology studies.
The systematic study of the ecology and evolution of particular butterfly taxa has already shed light on numerous biological phenomena, including hybridization and speciation (Mavarez et al., 2006; Mullen et al. 2008), mimicry (Brower, 1996; Mullen et al. 2008), coevolution with host plants (Ehrlich and Raven, 1964; Janz and Nylin, 1998), development of wing patterns (Beldade and Brakefield, 2002; McMillan et al., 2002), and long distance migration (Froy et al., 2003; Bingman and Cheng, 2005). Moreover, the blossoming of butterfly genomics is opening a myriad of new doors for addressing both old and new questions (Beldade et al., 2008). For example, one recent finding that can be
12 explored in depth with the newly developed tools of genomics is the existence of retrotransposon mediated horizontal transfer in butterflies (Novikova et al., 2007).
Butterflies are also proving to be useful model organisms in predicting the impact of global warming (Parmesan et al., 1999; Hoyle and James, 2005; Wallisdevries and
Van Swaay, 2006), and conservation efforts have benefited from the utility of butterflies as biodiversity indicators (Mac Nally and Fleishman, 2002). Butterflies, being phytophagous organisms, are engaged in a variety of ecological interactions with the plant species they feed from, such that dwindling butterfly populations can threaten the viability of the communities they belong to (Bloch et al., 2006). For these reasons, the study of butterfly ecology and evolution is not only of interest to basic science, but becomes fundamental to understand the proximal causes and ways to deter the potential consequences of the current environmental crisis.
The appeal of butterflies as model organisms for comparative studies relies partly on the ample phylogenetic information existing for particular taxa, and the clarity of its familial relationships, unparalleled among the major insect orders (Grimaldi and Engel,
2005). Despite this wealth of information, many groups still lack the type of phylogenetically comprehensive analysis needed to make full use of their potential for comparative research (Boggs et al., 2003). The study of butterfly evolutionary history dates back to Forbes (1932), but really took wing with Ehrlich’s phenetic classification
(Ehrlich, 1958), which introduced many new characters and a rigorous comparative morphology approach to classification (Vane-Wright, 2003). The next step was taken by
Kristensen (1976), who was the first to employ a cladistic methodology on butterfly phylogenetics (Vane-Wright, 2003). Major butterfly family and subfamily relationships
13 were still contentious by the time Scott published his cladistic study, which agreed with
most relationships supported by Ehrlich (Scott, 1985). Our current understanding of
familial relationships is based on Wahlberg and collaborators’ phylogeny, which
recovered with ample support the relationships among 57 taxa, including skippers
(Hesperiidae) and Hedylid moths, believed to be the moth taxon closest to the butterfly
superfamily Papilionoidea (Wahlberg et al., 2005). These authors proposed the following
classification: (Hesperidae + (Papilionidae + (Pieridae + (Nymphalidae + (Lycaenidae +
Riodinidae))))). Among the many relationships that remain unclear are: the positioning of
genera within the tribe Troidini, the monophyly of the subfamily Parnassiinae and
location of the monotypic Baroniinae, all in the Papilionidae; the relationships within
Pierinae and between Coliadinae and other Pierid subfamilies; the position of Theclinae in the Lycaenidae; and within the Nymphalidae, the status of the Limenitinae and
Satyrinae, and the sister group to Nymphalinae. To solve these mysteries, the insect phylogenetics community is in dire need of new molecular markers to increase the number of characters available for analyses, and thus increase the robustness of phylogenetic inference (Wahlberg and Wheat, 2008). The visual system of butterflies may provide a source for such markers. As rhodopsins, the visual pigment molecules responsible for light sensitivity in the arthropod compound eye, are partly composed of opsin proteins, which are encoded by a family of genes previously employed with success in Hymenopteran phylogenetics (Pilgrim et al., 2008, and references therein). The first part of this dissertation makes use of opsin genes in construction of a butterfly phylogeny and determination of some key timepoints of divergence.
14 The second part examines behavioral responses of adult butterflies to food plants.
There is no doubt that the striking diversity of insects is to a large extent a product of
their phytophagous habits, with many researchers advocating for coevolution between
angiosperms and insects as responsible for the incredible radiations of both groups
(Labandeira et al., 1994; Crane et al., 1995). The concept of coevolution was in fact first
introduced using butterflies and their larval host plants as an example (Ehrlich and
Raven, 1964), and since then much has been learned about this particular interaction. We
now possess extensive knowledge on oviposition preferences and underlying chemical
factors (Singer, 2003; Wheat et al., 2007), and about the mechanisms determining host
plant shifts (Janz and Nylin, 1998). The looser nature of the relationship between adult
butterflies and their nectaring plants, compared to the strict dependence of lesser mobile
larvae on the plants they eclose and feed on, may be responsible for the little attention butterfly pollination has attracted to date. Moreover, butterflies have historically been considered lesser pollinators due to a purposely erratic flight behavior compared to bees.
Also in comparison with bees, butterflies pollinate fewer crop species, are less frequent pollinators in the well studied northern hemisphere temperate zones and, being solitary, are harder to manipulate under laboratory conditions (Weiss, 2001). These factors contribute to the little understanding we possess of their pollination behavior. For example, despite a wealth of information on color vision (all Lepidoptera species examined possess it), how this perceptual capability translates into flower color preferences and in general the use of color as a cue while foraging for nectar has seldom been studied under field conditions in butterflies (Weiss, 1995; Borges et al., 2003;
Neumayer and Spaethe, 2007).
15 The present work elaborates on two aspects of the butterflies’ visual system
(opsin genes and color preferences) to fill into some of the existing gaps in our knowledge of their ecology and evolution, exploring issues in phylogenetic reconstruction and examining their flower visiting behaviors. Specifically, the goals of this dissertation are to: 1) Reconstruct the phylogenetic history of butterflies, timing their main divergence events; 2) Assess the utility of opsin genes as molecular markers for butterfly phylogenetics; 3) Determine the relative strength of color as a visual cue responsible for butterfly flower preferences, and; 4) Find if butterflies behave as flower constant visitors.
16 Chapter 1
Impact of duplicate gene copies on phylogenetic analysis and divergence
time estimates in butterflies
17 ABSTRACT
The increase in availability of genomic sequences for a wide range of organisms
has revealed gene duplication to be a relatively common event. Encounters with duplicate
gene copies have consequently become almost unavoidable in the context of using gene
sequences for inferring species trees. Here we explicitly examine the effect of
incorporating duplicate gene copies evolving at different rates on tree reconstruction and
time estimation of recent and deep divergences in butterflies.
Sequences from ultraviolet-sensitive (UVRh), blue-sensitive (BRh), and long-
wavelength sensitive (LWRh) opsins, EF-1α and COI, were obtained from 27 taxa
representing the five major butterfly families (5535 bp total). Both BRh and LWRh are
present in multiple copies in some butterfly lineages and the different copies evolve at
different rates. Regardless of the phylogenetic reconstruction method used, we found that
analyses of combined data sets using either slower or faster evolving copies of duplicate
genes resulted in a single topology in agreement with our current understanding of
butterfly family relationships based on morphology and molecules. Interestingly,
individual analyses of BRh and LWRh sequences also recovered these family-level relationships. Two different relaxed clock methods resulted in similar divergence time estimates at the shallower nodes in the tree, regardless of whether faster or slower evolving copies were used, with larger discrepancies observed at deeper nodes in the phylogeny. The time of divergence between the monarch butterfly Danaus plexippus and
the queen D. plexippus (15.3-35.6 MYA) was found to be much older than the time of
divergence between monarch mimic Limenitis archippus and red-spotted purple L.
18 arthemis (4.7-13.6 MYA), and overlapping with the time of divergence of the mimetic
passionflower butterflies Heliconius erato and H. melpomene (13.5-26.1 MYA). Our
family-level results are congruent with recent estimates found in the literature and indicate an age of at least 150 MY for the divergence of all butterfly families except the split which separated the riodinids from the lycaenids.
These results are consistent with diversification of butterfly families in the age of angiosperms and suggest that duplicate gene copies may be employed for both phylogenetic reconstruction and divergence time estimation.
19 INTRODUCTION
Gene duplication has long been recognized as a major source of evolutionary innovation (Ohno, 1970). It is a pervasive evolutionary process, with 50% of all genes in any given genome expected to duplicate and proliferate at least once in time scales ranging from 35 to 350 MY (Lynch and Conery, 2000). In molecular phylogenetics, gene duplication is a process that can lead to discordance between gene and species trees at deep phylogenetic levels, much as coalescence can obscure the reconstruction of recent speciation events (Maddison, 1997). The consensus has been to avoid the use of paralogous genes until methods are developed to handle their potential confounding effects (Wahlberg and Wheat, 2008). However, given the high likelihood of gene duplication under neutral evolutionary processes, as the size of molecular data sets gets larger (in number of genes and taxa used) the inclusion of duplicated genes becomes almost unavoidable. Within the butterflies, for instance, duplicate copies of opsin genes have been found both within and between families (Briscoe, 2008) but the effect of explicitly including multiple duplicate gene copies on phylogenetic reconstruction and divergence time estimation in butterflies has not yet been examined.
Historically opsin genes have been advocated as phylogenetic markers, due to the amount of information we possess about their molecular evolution relative to other nuclear genes, and the wealth of cloned sequences available for a wide array of organisms (Chang and Campbell, 2000). In fact, the long wavelength-sensitive opsin gene (LWRh) has routinely been used for the past 10 years in bee, bumblebee and wasp phylogenetic studies (Cameron and Mardulyn, 2003; Danforth et al., 2003; Banks and
20 Whitfield, 2006; Danforth et al., 2006; Pilgrim et al., 2008), and has proven useful at both
shallow (Ascher et al., 2001) and deep phylogenetic levels, suggesting their utility at
resolving family level, Cretaceous age insect divergences (Danforth et al., 2004; Hines,
2008). Currently there is little information about the potential use of other opsin genes in
reconstructing insect phylogenies (Spaethe and Briscoe, 2004), yet almost all insects that
have been studied including butterflies have three clades of opsins that encode spectrally
distinct visual pigments present in the adult compound eye that are ultraviolet- (UVRh),
blue- (BRh) and long wavelength (LWRh)-sensitive (Briscoe and Chittka, 2001). This suggests that other clades of opsins may also be useful for phylogenetic reconstruction over a similar range of divergence times.
Butterflies are some of the best known organisms, possessing remarkable life histories and an uncanny beauty, but yet their most basal relationships have been until recently still obscure (Grimaldi and Engel, 2005). In the early days of butterfly evolution research, the study of the oldest butterfly lineages was intertwined with speculations about timing of their origins (Forbes, 1932; Shields, 1976; Tindale, 1980; Scott, 1985). In more recent studies, the complexity of simply finding the most plausible topologies, and the difficulty of disentangling molecular evolutionary rates and divergence times, resulted in few studies directly concerned with timing the divergence of butterfly clades.
Concerns about the applicability of a molecular clock (Britten, 1986), and the scarcity of butterfly fossils with which to calibrate it (Scott et al., 1985; Hall et al., 2004; Peñalver and Grimaldi, 2006) have also undoubtedly contributed to this paucity in the literature. In recent years the advent of both non-parametric and parametric Bayesian (Sanderson,
2002; Thorne and Kishino, 2002) methods that free the estimations of divergence times
21 from the restrictions of a molecular clock and permit the incorporation of flexible fossil
or biogeographical calibration points, has rekindled efforts to date the different
diversification events within butterflies, and in the process sparked a controversy about
when and where butterflies originated (Sanderson, 2002; Vane-Wright, 2004). A
generally young and scant record comprised of about 50 Rhopaloceran fossils, a group
which includes the skippers (Hesperioidea), nocturnal butterflies (Hedyloidea) and true
dayflying butterflies (Papilionoidea), all found within the Cenozoic Era (65.5-0 million
years ago, MYA) and not older than 52 MY (million years, a skipper) and 48 MY (a
papilionid), respectively (Kristensen and Skalski, 1999; Durden and Rose, 1978), has in
of itself not been particularly useful in the direct estimation of the earliest butterfly
divergences; and is considered by some researchers as a veritable indicator of a recent
butterfly origin, dating back to the last epoch of the late Cretaceous (70.6 ± 0.6 – 65.8 ±
0.3 MYA) or early Cenozoic (65.5 - 0.0 MYA) no earlier than 70 MY ago (Grimaldi and
Engel, 2005; Vane-Wright, 2004). On the other hand, molecular phylogenetic methods have produced much older divergence time estimates for several butterfly families, prompting many to ascribe the origin of butterflies to the diversification of angiosperms, between 100 and 140 MYA (Braby et al., 2005; Braby et al., 2006; Wahlberg, 2006;
Nazari et al., 2007; Wheat et al., 2007; Peña and Wahlberg, 2008).
Another group of insects thought to have evolved concordantly with the early diversification of angiosperms are the ants (Moreau et al., 2006), but despite thorough sampling and an ample fossil record, disagreements concerning basal relationships and timing of the earliest divergences still exist (Brady et al., 2006; Crozier, 2006; but see
Rabeling et al., 2008). In contrast, the basal relationships of butterflies are for the most
22 part resolved, with our current understanding of relationships at the familial level being based on the study of Wahlberg and collaborators, which employed both molecular and morphological data to resolve deep nodes in the phylogeny of butterflies (Wahlberg et al.,
2005). Therefore, with a known phylogeny, butterflies are a useful group of organisms for examining the impact of duplicate genes on phylogenetic reconstruction and divergence time estimation.
In this study, we examine the effect of including duplicated opsin genes evolving at different rates on phylogenetic reconstruction and divergence time estimates. We find that individual and combined analyses of the BRh and LWRh genes are able to recover butterfly family-level relationships where previously morphological characters were required in addition to molecular (Wahlberg et al., 2005). We estimate divergence times for clades of high interest to the ecology and evolutionary biology communities, such as for the co-mimics Heliconius erato and H. melpomene (Papa et al., 2008), the migratory monarch Danaus plexippus and the non-migratory queen D. gilippus (Zhu et al., 2008) and their mimics in the genus Limenitis (Prudic and Oliver, 2008). We find our estimates of family-level times of divergence with either slower or faster evolving gene duplicates to be mostly in agreement with other recent estimates found in the literature, but we push back the minimum edge of divergence for the most basal butterfly families to 150 MY.
Our results suggest the potential utility of the opsins for resolving even older and more complex group relationships such as the moths.
23 MATERIALS AND METHODS
Tissue Collection
Most butterflies were included based on initial studies, which indicated the
potential utility of the LWRh gene for reconstructing family and subfamily-level relationships (Frentiu et al., 2007), and the availability of fossil and/or biogeographical calibration points (See discussion). These butterfly taxa were resampled (this study) for their UVRh, BRh, EF-1α and COI sequences. Other species were included because they
are currently being developed as model systems in butterfly ecology and evolutionary
biology. All specimens were collected as adults in the field and immediately placed in
RNALater (Applied BioSystems/Ambion, Austin, TX) or freshly frozen (Euphydryas
chalcedona, Speyeria mormonia, Satyrium behrii and Agriades glandon, Mono County,
CA; Agraulis vanillae, Huntington Beach, CA; Coenonympha tullia and Oeneis chryxus,
Boulder, CO; Lycaena heteronea, L. helloides and L. nivalis, Gunnison County, CO).
The remaining specimens were kindly provided as gifts (Nymphalis antiopa, Irvine, CA,
Peter Bryant; Limenitis arthemis astyanax, Baltimore County, MD, Austin Platt; L.
archippus archippus, Franklin County, MA, Fred Gagnon; Danaus plexippus, Bradford
County, FL, Edith Smith; D. gilippus, Collier County, FL; Heliconius erato and H.
melpomene, Costa Rica, Larry Gilbert; Neominois ridingsii, Montrose County, CO,
Matthew Garhart; Lycaena rubidus and Colias philodice, Gunnison County, CO, Ward
Watt and Carol Boggs; Polyommatus icarus, Germany, Almut Kelber and Apodemia
mormo, Hemet, CA, John Emmel).
24 PCR, Cloning, and Sequencing
For E. chalcedona, N. antiopa, H. erato, A. vanillae, S. mormonia, C. tullia, N.
ridingsii, L. heteronea, L. helloides, L. nivalis, A. mormo, L. arthemis astyanax, L.
archippus archippus, D. gilippus, H. melpomene, O. chryxus, S. behrii, A. glandon and C.
philodice, total RNA was extracted from one head with Trizol (GibcoBRL), and cDNA
synthesized using the Marathon cDNA Amplification Kit (BD Biosciences Clontech,
Mountain View, CA). The cDNA was then utilized in 3’ RACE (rapid amplification of
cDNA ends) PCR (BD Adv 2 Polymerase Mix) with, in the case of opsin genes, the
adaptor primer AP1 and an arthropod opsin-specific degenerate primer (80, 5’-GAA
CAR GCW AAR AAR ATG A -3’). PCR products were gel purified (Geneclean kit,
QBioGene), incubated for 10 min at 72°C with 0.5 µl Taq DNA polymerase (Promega) to
add A-overhangs, cloned into pGem T-easy vector systems (Promega, Madison WI) and
sequenced (BigDye® Terminator v3.1 Cycle Sequencing Kit, Applied Biosystems) at the
University of California, Irvine DNA core sequencing facilities. Duplicate gene
transcripts were obtained by performing multi-plex PCR on additional clones to identify
templates that did not amplify with the opsins picked up in this initial procedure. To
obtain complete UVRh, BRh and LWRh opsin sequences, gene specific reverse primers
were designed from the fragments and used to amplify the 5’ RACE products (Table 1.1).
From these cDNAs we also amplified fragments of the mitochondrial cytochrome
oxidase subunit I (COI) gene from H. erato and S. mormonia and the nuclear elongation
factor 1 alpha (EF-1α) gene from H. erato, S. mormonia, O. chryxus, S. behrii, A.
glandon and A. mormo using the primers mRon (5’- GGR GCH CCH GAT ATA GCH
25 TTY CC -3’) and mHobbes (5’-AAA TGT TGD GGN AAA AAD GTT A-3’) for COI modified from Monteiro and Pierce (2001), and EF44(f) (5’-GCY GAR CGY GAR CGT
GGT ATY AC-3’) and EFrcM4(r) (5’-ACA GCV ACK GTY TGY CTC ATR TC-3’) for
EF-1α (Monteiro and Pierce, 2001).
Standard phenol:chlorophorm extraction of genomic DNA was performed on one
individual adult per species from L. arthemis astyanax, L. archippus archippus, D.
plexippus, D. gilippus, H. melpomene, O. chryxus, L. rubidus, S. behrii, A. glandon, P.
icarus, and C. philodice. From these pools of genomic DNA we obtained the COI and
EF-1α genes from D. plexippus, D. gilippus, H. melpomene, L. rubidus, and C. philodice;
the COI gene from O. chryxus, S. behrii, A. glandon and P. icarus; and the EF-1α gene
from L. arthemis astyanax and L. archippus archippus using the primers described above.
Phylogenetic Reconstruction
For each gene we aligned our sequences and others obtained from GenBank
(Table 1.2) using MEGA 3.1 (Kumar et al., 2004) and by hand. Besides the 5 individual
gene data sets, we constructed 3 concatenated data sets combining all 3 opsin genes
(UVRh + BRh + LWRh), all 4 nuclear genes (UVRh + BRh + LWRh + EF-1α) and all 5 genes (UVRh + BRh + LWRh + EF-1α + COI), respectively. Because not all sampled
taxa possess the same duplications, to prepare these concatenated data sets we first chose
which copies of the duplicated genes to use in the alignments (Fig. 1.1). We chose by
comparing the rate of evolution of different paralogous gene pairs using the relative rate
tests as implemented in MEGA 3.1 and selecting for a first round of analyses the slowest
26 evolving copy for inclusion (except in the case of the pierid blue opsin gene duplication, in which we chose for all analyses the V gene, due to the absence of C. philodice B gene from our data set). The resulting nucleotide alignments were used to reconstruct phylogenetic relationships by maximum-parsimony (MP), maximum-likelihood (ML) and
Bayesian methods. We then repeated all 3 concatenated analyses on a second set of alignments, this time including the faster evolving paralogous copies of duplicated genes.
We rooted our trees with two moth species, the sphingid Manduca sexta and the bombycid silkworm Bombyx mori. See Table 1.2 for GenBank numbers of sequences included in slow vs. fast data sets.
The incongruence length difference (ILD) test (Farris et al., 1994) implemented as partition homogeneity test in PAUP 4.0 for assessing incongruence between character sets showed that the three opsin gene partitions are congruent regardless of whether slower (P = 0.057) or faster (P=0.191) evolving copies are used, but the addition of EF-
1α and EF-1α + COI to the opsin data results in incongruent data sets in which the different partitions are evolving non-homogeneously (P < 0.001 for both slower/faster data sets for both combinations). Since the utility of the ILD test has been challenged
(Darlu and Lecointre, 2002), however, we analyzed the data partitioned (by gene) and un- partitioned. Maximum parsimony analyses were run using heuristic searches, tree bisection-reconnection (TBR) branch swapping algorithm with gaps treated as missing data and all characters equally weighted in PAUP 4.0 (Swofford, 2000). Clade robustness was evaluated using decay indexes (Bremer support values) using PAUP 4.0 and TreeRot
(Sorenson, 1999). Partitioned Bremer support (PBS) values were also calculated to
27 determine the relative contribution of the 5 gene partitions to the total Bremer support of the combined, un-partitioned analysis.
The optimal DNA substitution model for each data set was determined by nested likelihood ratio tests as implemented in Modeltest 3.7 (Posada and Crandall, 1998). The
GTR + I + G (general time reversible plus proportion of invariant sites and gamma- distributed rates for sites) substitution model was selected for all data sets, including for individual and concatenated gene sequences. Proportion of invariant sites and gamma shape parameters were estimated in PAUP 4.0. Maximum likelihood analyses were conducted in PHYML online web server (Guindon and Gascuel, 2003; Guindon et al.,
2005) for all 8 data sets and the reliability of the trees obtained was tested by 500 bootstrap replicates.
As for the Bayesian phylogenetic reconstruction method, we chose the GTR + I +
G model of nucleotide evolution for all 8 data sets, where the proportion of invariant sites and the shape of the gamma parameter were estimated for each gene or partition employed. Bayesian analyses were performed using MrBayes 3.1.2 (Ronquist and
Huelsenbeck, 2003) on all 8 unpartitioned data sets, and repeated with the all genes data set under 2 partitioning schemes: by gene (5 partitions) and by gene and codon position
(5 genes X 3 positions = 15 partitions) under the same model selected for ML analyses
(GTR+I+G). In a partitioned analysis the model parameters (in this case, I and G) are calculated separately for each partition. For each data set, 4 chains, 3 heated and 1 cold, were run simultaneously for 4 X 106 generations sampled every 100th generation. The first 20000 trees were discarded as burn-in samples. The remaining trees were used to
28 generate a majority rule consensus tree, in which the percentage of samples recovering a
particular clade represents its support measured as posterior probabilities.
Divergence Time Estimation
We performed two analyses on the combined data set of 5 genes, first using the
slower evolving copies of duplicated genes, as determined by relative rate tests, and
second using the faster evolving copies. Initial results for the semi-parametric penalized likelihood method were obtained with the default settings of the software r8s using cross-
validation to find the smoothing parameter resulting in the lowest cross validation scores.
We found this smoothing parameter to be 3.2 for both slow and fast data sets. Using this
value we repeated the analysis and estimated divergence ages.
For the Bayesian analysis, the rate of evolution prior was selected based on the
root to tip median branch length of our slow and fast trees, a proxy advocated by Thorne
and Kishino (2002) and explained in detail by Wiegmann et al. (2003). These branch
lengths were calculated using the GTR + I + G ML model of evolution in PAUP 4.0. For
both slow and fast data sets the median branch length, divided by the prior of root age
resulted in a value between 0.003 and 0.005 depending on the root age prior; therefore we
utilized a prior of 0.002 ± 0.002 (standard deviation). The prior for the variation in the
rate of evolution over time (brownmean) was set to 0.02 ± 0.02 based on the empirical
suggestion of Thorne and Kishino (2002) and Wiegmann et al. (2003), which states that a
preferred brownmean multiplied by the root age prior should result in a number between
1 and 2. Large standard deviations were chosen for all priors to increase the flexibility of
29 our analyses considering the lack of detailed information about the actual divergence
times and rates of evolution of butterflies.
Under the Bayesian framework, and for both slower and faster data sets we
performed analyses using all 18 permutations of prior values, which included a prior
distribution for age of the ingroup node of either 70 (±70) or 100 (±100) MYA, a prior
for the rate of molecular evolution of either 0.02± 0.02, 0.002± 0.002 or 0.0002± 0.0002,
and a prior for the variation of the rate of evolution over time (brownmean) of either
0.02± 0.02, 0.002±0.002 or 0.0002± 0.0002. Parameters were sampled after a burnin
period of 100,000 cycles, for an additional 1,000,000 cycles sampled every 100.
Divergence time estimates were calculated from these 10,000 samples.
List of abbreviations
MY = million years
MYA = million years ago
UVRh = ultraviolet-sensitive rhodopsin
BRh = blue-sensitive rhodopsin
LWRh = long wavelength-sensitive rhodopsin
EF-1α = elongation factor 1-alpha
COI = cytochrome oxidase I
30 RESULTS AND DISCUSSION
Relative rates tests classify duplicate BRh and LWRh opsins functionally
As mentioned previously, most insects including butterflies have adult
compound eyes that contain at least three classes of opsin genes (UVRh, BRh and LWRh)
that encode visual pigments with wavelengths of peak absorbance, λmax, that fall roughly into the UV (300-400 nm), blue (400-500 nm) and long wavelength (500-600 nm) portions of the light spectrum. Within these broad partitions of the spectrum, the visual pigments of butterflies typically cluster in narrower ranges (i.e., 345-380 nm, 437-470 nm and 514-565) (Reviewed in Frentiu and Briscoe, 2008). There are, however, additional opsins that evolved from these three basic classes in some butterfly eyes, which encode visual pigments with λmax values outside of these typical ranges (see below).
All three basic classes of opsin (UVRh, BRh and LWRh) were present in all 27
butterfly species included in this study, except in the two closely-related satyrines,
Neominois ridingsii and Oeneis chryxus, in which no BRh gene could be found after exhaustive screening of head-specific cDNAs. We think that these species probably do have blue-sensitive visual pigments in the eye based on physiological studies (Gary
Bernard, pers. comm.) but we were simply unsuccessful in retrieving them. Similarly, we also think that besides the BRh opsin we found in the pierid Colias philodice this species likely has a violet-sensitive visual pigment in the eye based on old electrophysiological studies of a related species (Eguchi et al., 1982) but we did not find it. Full-length coding regions were otherwise obtained for the opsin cDNAs, including both start and stop
31 codons. The size of these transcripts, including 3’ and 5’ UTR regions ranged from 1137-
1575 bp (UVRh), 996-1590 bp (BRh), and 1143-1743 bp (LWRh). Besides the three basic opsin classes, all lycaenid butterflies (this study and Sison-Mangus et al., 2006) and the pierid Pieris rapae (Arikawa et al., 2005) have duplicated blue opsins, representing two independent BRh duplications, while the papilionids Papilio xuthus and P. glaucus, the riodinid Apodemia mormo and the moth Bombyx mori possess duplicated LWRh opsins
(Kitamoto et al., 1998; Briscoe, 2000; Frentiu et al., 2007) representing four independent
gene duplications (gene names for the long-wavelength pigments have been renamed here for simplicity).
Relative rates test showed that of the lycaenid blue opsin duplicates, BRh1 evolved slower than BRh2 in every one of the 7 lycaenid species sampled, although not significantly so (Table 1.3). The slower rate of evolution of the BRh1 opsin is consistent with our observation that this gene encodes the 437 nm visual pigment in Lycaena rubidus, which is a wavelength of peak absorbance that is more typical of the “blue- sensitive” visual pigments in butterflies, than the duplicate BRh2 gene in L. rubidus which encodes the unusually red-shifted 500 nm visual pigment (Sison-Mangus et al.,
2006). Similarly, in the pierid Pieris rapae, the blue opsin copy (B), which encodes a 450 nm visual pigment (Arikawa et al., 2005) evolved slower than the violet copy (V), which encodes a more unusual 425 nm pigment, but this result was not significant either.
Among the duplicated LWRh genes, significantly different rates of evolution were observed where Bombyx mori LWRh2 evolved slower than B. mori LWRh1, and Papilio
LWRh2 evolved slower than both Papilio LWRh1 and Papilio LWRh3, and Apodemia
mormo LWRh1 evolved slower than A. mormo LWRh2 (Table 1.3). Here too, the slowest
32 evolving Papilio LWRh2, encodes a pigment that with a λmax at 520 nm is functionally
more similar to other butterfly long-wavelength sensitive visual pigments in its
wavelength of peak absorbance than the pigment encoded by LWRh3 (λmax=575 nm), and
the slower evolving Apodemia LWRh1 encodes a pigment that with a slightly blue-shifted
λmax at 505 nm is much more typical of other butterfly pigments than its faster evolving
LWRh2 copy that encodes a pigment with the highly atypical λmax at 600 nm (Frentiu et
al., 2007). Given that the relative rates tests seem able to classify the slowest and fastest evolving gene copies in a way that also roughly reflected their function, with the slowest evolving copies having spectral properties falling in a more narrow, similar and presumably ancestral range than the fastest evolving copies, we decided to divide our data for further analysis (see Materials and Methods) into alignments which included the slowest or fastest evolving copies.
For phylogenetic analysis and divergence time estimation, we also obtained EF-
1 α and COI for individual taxa where such sequences were not already available in
GenBank. A total of 66 new gene sequences, including 38 opsin genes, 15 EF-1α and 13
COI sequences, are reported in this study (Fig. 1.1). Accession numbers for all new sequences and those downloaded from GenBank are shown in Table 1.2. The combined data set consisted of a total of 5523 bp, of which 1158, 1156, 1164, 1066 and 982 bp, belonged to the UVRh, BRh, LWRh, EF-1α and COI genes respectively.
33 Maximum parsimony analysis recovers a single well-resolved tree for butterflies
Maximum parsimony (MP) analysis of all five genes using the slowest evolving
opsin duplicates identified by the relative rates test resulted in a single tree (Fig. 1.2) with a topology congruent with that inferred in a previous study from molecular and morphological data (Wahlberg et al., 2005). Re-running this analysis using the faster evolving gene copies also revealed the same topology (Fig. 1.5). As traditionally recognized, Papilionidae is placed as sister to (Pieridae + (Nymphalidae + (Lycaenidae +
Riodinidae))). The relationships recovered within Nymphalidae also correspond to the current consensus, which groups Limenitinae with Heliconiinae and Nymphalinae as sister to the previous two, Satyrinae as sister to (Nymphalinae + (Limenitinae +
Heliconiinae)) and Danainae as the basal subfamily, sister to (Satyrinae + (Nymphalinae
+ (Limenitinae + Heliconiinae))). Within Lycaenidae, the Theclinae clade, represented by the hairstreak Satyrium behrii, groups together with the Lycaeninae, and these two clades are sister to the Polyommatinae.
Dissecting the contribution of different genes to this topological hypothesis through partitioned analysis reveals that the LWRh gene provides the strongest support to the topology, followed by the BRh, UVRh, EF-1α and COI genes (Table 1.4). This holds
true for both combined analyses which included slower and faster gene copies of
duplicate genes. Using the slower evolving copies we can see that both LWRh and BRh
support all nodes, as shown by positive partitioned Bremer support values, whereas the
information provided by UVRh, EF-1α and COI conflicts with one or more nodes. The
UV opsin data strongly renders the grouping of both (Lycaenidae + Riodinidae), and
34 (Nymphalidae + (Lycaenidae + Riodinidae)) spurious, and also does not support the
monophyly of Satyrinae. EF-1α does not recover the (Lycaeninae + Theclinae) clade, but
it does not take many steps to retrieve it (partitioned Bremer support -2, Table 1.4). COI
conflicts with 10 out of the 26 total nodes, resulting in many negative support values
(Table 1.4). This is not surprising since it has long been recognized that its fast rate of evolution renders COI of limited use when reconstructing phylogenetic history at levels deeper than species (Braby et al., 2006; Roe and Sperling, 2007).
The Bremer support values rendered by the analysis of the combined data set using faster evolving gene copies are qualitatively and quantitatively similar to the values of the slower evolving copies in most cases (Table 1.4). A few exceptions occur at basal nodes in the tree, where using the faster evolving copy of duplicated genes eliminates the support of the UVRh and COI genes for Danainae as the most basal of the Nymphalidae
(node 23, Fig. 1.2 and Table 1.4), the support of the BRh gene for Pieridae as sister group
to (Nymphalidae + (Lycaenidae + Riodinidae))(node 25), the support of COI for the node
consisting of Vanessa + Nymphalis (node 19), and adds the positive support of COI to
Papilionidae as sister to (Pieridae + (Nymphalidae + (Lycaenidae + Riodinidae))) (node
26). However, these qualitative differences are not quantitatively important since the
individual Bremer support values for these gene partitions approach zero in both slow
and fast gene copy analyses of these nodes.
One possible reason for the poor performance of the UVRh gene in our data set is
that there may be duplicate copies, especially at deeper nodes in the phylogeny, which we
have not yet identified in these species that are missing from our analysis. When
searching for opsins by screening cDNAs as we have done in the current study, it is
35 difficult to know when to stop because there is far less functional data on the UV class of
photoreceptor than either the blue or the long wavelength. This apparently messy result is
interesting because it suggests we should continue to look harder. By contrast, for the
BRh and LWRh genes, we think we have identified all but one of the duplicates in the
species represented and so this may have contributed to their striking performance.
Maximum likelihood and Bayesian phylogenetic analyses concur
To ensure that that the good performance of the BRh and LWRh opsins and the
poorer performance of the UVRh opsin was not an artifact of tree reconstruction method
we also performed maximum likelihood (ML) and Bayesian analysis of the data.
Maximum likelihood and Bayesian analysis of the LWRh data set as well as the all opsins, all nuclear, all genes data sets using slower and faster evolving opsin copies resulted in identical, strongly supported topologies (Fig. 1.3A and 1.3D, Fig. 1.4A and
1.4D, Fig. 1.5B and 1.5C) congruent with that obtained in our combined MP analyses
(Fig. 1.2), and with the inferred phylogenetic hypothesis of Wahlberg et al. (2005). The
BRh gene rendered a nearly identical topology, with the only exception being an unresolved node joining the nymphalid subfamilies Satyrinae, Nymphalinae and
Limenitinae + Heliconiinae (Fig. 1.3C, 1.4C). In contrast, the UVRh, EF-1α and COI
genes rendered non-traditional groupings with various degrees of bootstrap support (Fig.
1.3B, 1.3E, 1.3F, Fig. 1.4B, 1.4E, 1.4F).
We also calculated using MrBayes a rate multiplier parameter (m) that reports
relative substitution rate differences between partitions (Nylander et al., 2004; Wahlberg
36 and Wheat, 2008), which can vary widely between genes. As shown in Fig. 1.6, rates of
change for opsin genes are intermediate between fast evolving COI and comparatively
slow evolving EF-1α, which can account for the strong phylogenetic signal contained by
the LWRh and BRh genes at the hierarchical levels under examination in this study. On
the other hand, the relatively lower performance of the UVRh is somewhat puzzling
because its m falls in between that of the two other opsins.
Interestingly, of all 6 gene duplications included in our data sets (independent
BRh duplications in Lycaenidae and Pieridae, two LWRh duplications in Papilio plus one
LWRh duplication in Bombyx mori and one in Apodemia mormo), only one results in different groupings depending on which copy is utilized. Including BRh1 in the analysis resulted in the grouping of Satyrium behrii with the Lycaeninae under both maximum likelihood (93% bootstrap support, Fig. 1.3C) and Bayesian analysis (Fig. 1.4C), whereas using BRh2 creates either a polytomy of the three lycaenid subfamilies when employing
ML (Fig. 1.3C), or the grouping of Theclinae with Polyommatinae under a Bayesian
framework (Fig. 1.4C).
Wahlberg and Wheat (2008) included a heat shock protein gene HSP70 in their
analyses, and the resulting highly supported polyphyly of major lineages was blamed on
the paralogy of heat shock protein genes. As we have suggested above, it is possible that
a hypothetical early duplication of the UVRh gene in butterflies, which we have failed to
identify may have contributed to its relatively poor performance. On the other hand, our
results suggest that if one has access to more complete gene family data sets, such as
through comprehensive screening of cDNAs or high quality genomic sequences, at least
at the evolutionary scale under examination in this study, the effect of gene duplications
37 on phylogenetic reconstruction as exemplified by LWRh and BRh is not necessarily disruptive.
Regardless of the phylogenetic reconstruction method used, we found overwhelming support of a single phylogenetic hypothesis. Both the LWRh and BRh
genes, as well as combined analyses of all opsin genes, all nuclear genes and all 5 genes
rendered essentially the same tree topology, which also mirrors the current phylogenetic
hypothesis for butterflies proposed by Wahlberg et al. (2005) based on three genes (COI,
EF-1α and wingless) and 99 morphological characters. Of the genes used in the above-
mentioned study, EF-1α provided the strongest support to the topology, while COI the
weakest (Table 1.4; Wahlberg et al., 2005). In their case, the addition of morphological
data was crucial to elucidate many higher-level nodes, whereas in our study LWRh and
BRh individually and in combination with other genes was sufficient to achieve this goal.
Divergence time estimates using duplicate gene copies are similar at shallow nodes
To estimate divergence times we used two different relaxed clock methods and the same calibration points on the phylogenetic hypothesis shown in Fig. 1.2. First we employed a semi-parametric rate smoothing penalized likelihood method (Sanderson,
2002), and second, we used a Bayesian approach (Thorne and Kishino, 2002). We note that this is the first study of butterfly divergence times employing both methods. For calibration we used two fossils as well as a biogeographic event to constrain three nodes.
The most recent common ancestors of Vanessa cardui and Nymphalis antiopa (node 19,
Fig. 1.2), and of Pieris rapae and Colias philodice (node 2) were constrained to a
38 minimum age of 34 mya based on the Florissant fossils Vanessa amerindica (Miller and
Brown, 1989; Wahlberg, 2006) and Stolopsyche libytheoides (Scudder, 1889; Braby et
al., 2006), respectively, whereas the split between the Neartic Papilio glaucus and the
Paleartic P. xuthus (node 1) was constrained between 35 and 65 mya, based on the
breakage of the super continent Laurasia (Dietz and Holden, 1970; Noonan, 1988;
Zakharov et al., 2004).
Under the Bayesian approach, three priors also need to be established, namely, the age of the root (node 26, Fig. 1.2), the rate of evolution in substitutions per site per
million years, and the variation of the rate of evolution over time, also called brownmean
(Thorne and Kishino, 2002). We selected 70 and 100 MY as priors for the age of the
ingroup node to reflect recent competing hypotheses for the origin of butterflies. Our 70
MY prior follows the hypothesis of early butterfly diversification following the
Cretaceous/Tertiary boundary (K/T, 65 MYA, Vane-Wright, 2004), and the 100 MY
prior reflects a conservative approach to a second hypothesis locating this event
sometime in the Cretaceous, roughly following the diversification of angiosperms 140
MYA (Bell et al., 2005). Both the mass extinction of terrestrial vertebrates following the
impact of a large meteor off the Yucatan Peninsula in Mexico defining the K/T boundary,
and the rise of the angiosperms as dominant terrestrial plants had enormous evolutionary
consequences, providing likely scenarios for the origin and diversification of insect taxa.
In general, penalized likelihood (Table 1.5) reported older estimates than
Bayesian analyses (Table 1.6, tables 1.7 and 1.8) (slow/fast datasets, penalized likelihood
reported estimates on average 17.98/7.10 MY older than estimates obtained by Bayesian
analyses, respectively), and the older the node the larger the difference between estimates
39 obtained through the two methods and between estimates calculated using the slower and
faster copies of duplicated genes. This is especially dramatic when we compare the
estimates for when the oldest butterfly family, Papilionidae, is inferred to have first
appeared (node 26). The penalized likelihood estimate using the slower evolving gene
duplicates is much older (240.44 MYA) than the penalized likelihood estimate using the
fast evolving gene copy (210.88 MYA) (Table 1.5), and both estimates are together older
than those obtained using the Bayesian method, 154.7 MYA (112.8-197.9, 95%
confidence intervals) for the slower evolving copies vs. 175.4 MYA (134.4-218.9) for the faster evolving copies. It is important to note that the use of the three shallow level calibration points available under the restrictions of our data set constitutes a likely source of variation in our divergence time estimates, especially at deep nodes very distant in time from the calibrated nodes (Hedges and Kumar, 2004), so all of these estimates
should be viewed with some caution.
The Bayesian analyses performed on combined data sets containing slower evolving copies of duplicated genes rendered younger estimates, and therefore more conservative estimates than the analyses of combined data sets including faster evolving gene copies or the analyses using penalized likelihood (Fig. 1.7 and 1.8). Since the effect
of the priors employed in the analyses is small, and the choice of a root age of 70 and 100
MY did not seem to have much of an impact on divergence dates (Table 1.6, tables 1.7
and 1.8) the rest of this discussion will be based on the divergence times estimated using
our preferred rate and brownmean priors (0.002, 0.02, respectively) and our most
conservative root age prior of 70 MY (see Materials and Methods).
40 Our results indicate that the Papilionidae diverged from the ancestor of all the
other butterfly families combined sometime between 153.7 (95% confidence interval
between 113.1-197.4) and 173.6 (132.5-216.2) MY ago, depending on whether the
slowest or fastest evolving copies of duplicated genes are being included (node 26, Table
1.6). These results are compatible with other studies focused on divergences of younger
lineages within the family. Zakharov and collaborators suggest for instance the ancestor
of Papilio diverged from the Tribe Troidini up to 100 MY ago (Zakharov et al., 2004)
while Braby et al., (2005) propose a minimum age of 90 MY for the first diversification
within Troidini. We also note that two other studies (Zakharov et al., 2004; Nazari et al.,
2007), using similar calibration constraints as our study, timed the major divergences
within the papilionid genus Papilio as occurring around 57.9 (37.8-78.0) and 57.9 (43.0-
72.8) MY ago, respectively, which is comparable with our estimated divergence of P.
glaucus from P. xuthus between 58.0 (45.4-64.8) and 59.2 (47.2-64.8) MY ago (node 1,
Table 1.6).
We estimate the split of Pieridae, the next oldest butterfly lineage to have evolved, from the ancestor of (Nymphalidae + (Lycaenidae + Riodinidae)) to be situated between 133.9 (101.1-170.0) and 153.4 (118.5-190.0) MY ago (node 25, Table 1.6), a result consistent with Wheat et al., (2007), who estimated this split to have occurred between 79 and 166 MY ago. Similarly, Braby et al., (2006) estimated the subtribes
Pierina and Aporiina to have diverged 58 MY ago, and from this result extrapolate an average age for the crown group of the Pieridae of 95 MY (99.9% confidence interval between 82 and 112 MY ago). Despite this estimate being younger than ours, their confidence interval partly overlaps ours when using slower evolving gene copies. At the
41 subfamily level, our results situate the split between Pierinae and Coliadinae (node 2,
Table 1.6) in the Pieridae between 74.4 (56.4-94.1) and 91.7 (70.6-115.0) MY ago, which
is consistent with the results of Wheat et al., (2007), who, using distance methods on the
EF-1α and COI genes alone, estimate this divergence is between 62 and 96 MY ago.
For the youngest butterfly families, the most recent common ancestor of
Nymphalidae and (Lycaenidae + Riodinidae) (node 24, Table 1.6), is located by our
analyses at a minimum age between 121.8 (93.3-152.7) and 140.3 (109.1-173.2) MY, and
the split between Lycaenidae and Riodinidae (node 9, Table 1.6) at 108.0 (83.6-135.1)
and 120.0 (93.6-148.1) MY ago. Estimates for the origins of subfamilies within the
Lycaenidae (Theclinae, Lycaeninae and Polyommatinae) and Nymphalidae (Danainae,
Limenitinae, Nymphalinae, Heliconiinae, and Satyrinae) are shown in Table 1.6.
Wahlberg (2006) suggests that the nymphalid subfamily Nymphalinae was already
present at the Cretaceous/Tertiary boundary, 65 MYA. In our data set, the first split
within Nymphalinae (node 20, Table 1.6) occurs between 62.0 (52.2-75.3) and 66.5
(55.7-80.6) MY ago, which is concordant with Wahlberg’s estimate. We note too that
Peña and Wahlberg (2008) estimated the split between Satyrinae and the closely related
subfamily Calinaginae (missing from our data set), to have occurred 80.5 ± 4.9 MY ago.
Though not directly comparable, this result is compatible with our estimated age 100.2
MYA (78.8-123.8) for the divergence of Satyrinae from its more distantly related
subfamilies (Nymphalinae + (Limenitinae + Heliconiinae)) (node 22).
On the other hand, Monteiro and Pierce (2001), using a mitochondrial gene
molecular clock estimated the origin of the Satyrine genus Bicyclus between 15 and 20
MYA, and the split of the subtribe to which it belongs (Mycalesina: Satyrini) from the
42 subtribe to which Coenonympha belongs (Coenonymphina: Satyrini) at roughly 35 MYA
(extrapolated from Figure 1, Peña and Wahlberg, 2008). This last estimate is much younger than our estimation for the split between Bicyclus and (Coenonympha +
(Neominois + Oeneis)) which we find between 74.5 (58.6-93.3) and 81.6 (64.4-101.6)
MYA (node 13, Table 1.6). This discrepancy may be partly due to the currently
unresolved polytomies that plague the Satyrini tribe (Peña et al., 2006).
The only divergence time estimate existent for species in the widely studied
nymphalid genus Danaus, to which the famed monarch butterfly belongs (D. plexippus),
corresponds to the divergence between the sister species D. plexippus and D. erippus,
which based on molecular clock estimates are suggested to have split about 2 MY ago
(Brower and Jeansonne, 2004). Our analyses situate the split between the less closely
related D. plexippus and the queen butterfly D. gilippus, between 23 (15-35) and 26 (18-
36) MY ago, depending on the copy of duplicated genes used (slow and fast
respectively). As expected based on its position in the butterfly phylogeny, the
scientifically conspicuous Danainae originated prior to the Limenitinae (Table 1.6),
which contains the palatable species Limenitis archippus, mimic of both the monarch and
queen butterflies. We estimated the divergence between the North American L. archippus
archippus and L. arthemis astyanax (the red spotted purple, which is a palatable mimic of the papilionid Battus philenor), to have occurred between 7.9 (4.7-13.6) and 8.1 (5.2-
12.1) MYA. This result conflicts with a previous estimate of the colonization of the
Nearctic by the genus Limenitis, situated at about 4 MYA by a molecular clock
calculation but recognized by the author to be based on a crude divergence rate
percentage (Mullen, 2006), but is compatible with the postulated Laurasian origin of the
43 genus Limenitis and the Bering land bridges that connected Asia with North America in the late Miocene (11.61 ± 0.01 to 5.33 ± 0.01 MYA, Hopkins, 1959).
Another taxon famous for its astounding mimicry complexes is the nymphalid genus Heliconius, for which, surprisingly, only two estimates of divergence times exist in the literature, for intraspecific or more-closely related species in Heliconius than those included in our study. Based on arthropod mitochondrial gene evolution rates, Brower found the first split within H. erato and H. melpomene to have occurred between 1.5 and
2 MYA (Brower, 1996), whereas Kronforst (2008), using the same method, dated the split between the closely related Heliconius melpomene/cydno and silvaniform clades, which excludes H. erato, at 2.5 MYA. Our study includes H. melpomene and H. erato, members of branches representative of the first divergence within the genus, and estimates their split between 18 (12-25) and 19 (14-26) MYA.
44 CONCLUSIONS
Our results suggest the use of the LWRh and BRh (but not UVRh) opsins in resolving both lower and higher level phylogenetic relationships in butterflies and suggest they may help to resolve relationships and divergence times estimates between even larger and more complex groups such as the moths. One possible reason for the unusually good performance of LWRh and BRh opsins may be due to the fact that some of the individual opsin duplicates included in this study appear to demarcate family level synapomorphies (i.e., family-specific gene duplications) and this may in some
unexpected way, also be reflected in the pattern of molecular evolution of the individual
genes. It is tempting to speculate that these unique opsin gene duplication events may in
fact represent true molecular traits that fundamentally distinguish one butterfly family
from another.
Another possibility is in the way we have handled this data. We propose that
phylogenomic studies might usefully include duplicate gene copies for phylogenetic
analysis if relative rates tests are first used to identify slow and fast evolving copies. In
our data set where the spectral properties of some of the visual pigments encoded by
duplicate copies are known, this simple procedure brought together a collection of genes
in the slow category whose ancestral function has been retained and whose patterns of molecular evolution may have been conducive to phylogenetic reconstruction and divergence times estimation. Even for genes where no functional information is known a similar procedure may help.
45 As several previous studies on butterfly family and subfamily divergence times have suggested, so too do our results support an origin of butterflies older than the 70
MY advocated by Vane-Wright (2004) and others, regardless of the absence of butterfly fossils older than Eocene ages. The present study, using a set of genes that includes opsins, which have not been used previously in butterfly divergence time estimations
(and two different methodological frameworks), reaches the same conclusion: the origin of butterflies surpasses with ample margin the Cretaceous/Tertiary boundary by at least
90 MY.
46 Chapter 2
Butterflies show flower preferences but not constancy
47 ABSTRACT
The flower visiting behavior of butterflies is poorly understood compared with that of other insect groups. For example, the extent to which flower color and other visual cues influence butterfly flower choice is unknown. In this study we phenotypically manipulated flower color in order to decouple it from other flower traits such as morphology or nectar, asking if Lycaena heteronea, Speyeria mormonia, Cercyonis oetus and Phyciodes campestris possess spontaneous preferences for particular colors or other traits, and if they behave as constant flower visitors. This study is the first attempt with butterflies to tease apart the effect of color on preference, and to test for flower constancy, using experimental trait manipulations under field conditions.
We measured flower preference and constancy by recording all visits to artificial flower arrays of either Erigeron speciosus/Achillea alpicola, or Dugaldia hoopesii/Wyethia amplexicaulis. Natural arrays contained unmanipulated flowers of two species. In ‘color’ arrays, manipulated flowers differed only in color, while in
‘morphology’ arrays the effect of color was eliminated. Additional experiments examined the roles of flower size and nectar reward.
Over the course of three field seasons, we recorded a total of 4935 individual visits in 1236 foraging bouts, finding different combinations of color and morphology preferences in the species examined. P. campestris and C. oetus have color but no
‘morphology’ preferences, whereas S. mormonia and L. heteronea have color and morphology preferences. The behavior of L. heteronea also suggests a potential to exert correlational selection on associations of flower traits. Strikingly, in this first
48 experimental test of butterfly flower constancy in the field, no butterfly species showed constancy in any of the arrays employed.
49 INTRODUCTION
Plants and their animal pollinators possess traits that have allowed them to
interact throughout their evolutionary history. Pollinators display behaviors that influence
pollen dispersal, such as flower choice, time spent foraging at a nectar source, and number of flowers visited in a foraging bout. A pollinator’s choice of flowers depends
initially on how flowers are perceived by its sensory system. Visual signals such as flower color, shape and size can play an important role in flower detection and choice
(Levin, 1968; Waser and Price, 1983; Campbell et al., 1997; Schemske and Bradshaw,
1999). Floral traits other than visual, such as the presence of fragrances and the volume
and components of nectar, can also be involved in pollinator attraction (Sutherland and
Vickery, 1993; Andersson and Dobson, 2003; Galizia et al., 2005; Petanidou et al.,
2006; Afik et al., 2006; Schlumpberger and Raguso, 2008).
Flower visitation behavior has been extensively studied in hymenopteran
pollinators and to a lesser extent in hummingbirds (Bleiweiss, 1990; Dukas and Real,
1993; Melendez-Ackerman et al., 1997; Irwin, 2000). Much less is known about the
flower-feeding behavior and perceptual capabilities of flies, beetles and butterflies
(Weiss, 2001), which can constitute the main pollinator fauna in some ecological
communities (Arroyo et al., 1982). This study focuses on the visual cues that attract adult
foraging butterflies to flowers.
Striking life history differences between Lepidoptera and Hymenoptera preclude
the extrapolation of butterfly flower visiting behavior from the behavior of the much
better studied bees (Chittka and Thomson, 2001; Weiss and Papaj, 2003). For example,
50 whereas worker honeybees are engaged primarily in foraging, butterflies not only are feeding but also looking for potential mates or oviposition sites (Goulson et al., 1997a), and therefore will be attracted to a different set of cues. Also, in terms of visual physiology, bees possess a much smaller diversity of photoreceptor spectral sensitivity types than most butterflies (Peitsch et al., 1992; Briscoe, 2008), suggesting differences in the perception of flower colors that could initiate distinct behavioral responses.
Many studies have shown the ability of butterflies to respond to color and learn new associations between color and nectar rewards (Crane, 1955; Swihart and Swihart,
1970; Swihart, 1971; Scherer and Kolb, 1987; Lewis and Lipani, 1990; Goulson and
Cory, 1993; Kandori and Ohsaki, 1996; 1998; Kelber, 1996; 1997; 2003; Kelber and
Pfaff, 1997; 1999; Weiss, 1997; Weiss and Papaj, 2003; Kinoshita et al., 1999), most of them using artificial flowers (but see Weiss, 1995; Borges et al., 2003; Neumayer and
Spaethe, 2007). Despite this relative wealth of information, the behavioral consequences of color vision while foraging on real flowers under field conditions are poorly understood. In field studies, demonstrating that color is the trait butterflies are responding to would require that color phenotype be phenotypically or genetically manipulated. To our knowledge, only a handful of studies have decoupled the effect of color from other floral traits through trait manipulations in the field, and none of them involved butterflies
(Waser and Price, 1983; 1985; Melendez-Ackerman and Campbell, 1998; for review see
Rausher, 2008).
Other floral traits to which pollinators may respond visually include flower size, floral display size, and flower shape. Preferences for larger flowers and floral displays are well known in bees but few, and conflicting, data are available for Lepidoptera (Ilse,
51 1928; Kelber, 1997; Vaughton and Ramsey, 1998; Thompson, 2001). In the only study
focused solely on butterfly flower display size preferences in the field, butterflies
preferred larger display sizes (Arroyo et al. 2007). In Lepidoptera, the recognition of
shapes is important for choosing the right mates and oviposition plants (Rutowski and
Warrant, 2002). Pattern recognition and preferences, albeit weaker than size and color
preferences, have been demonstrated using artificial stimuli in laboratory experiments
with hawkmoths (Kelber 1997, 2002).
Butterflies could also be choosing which flowers to visit based on their nectar
volume and concentration. The study of butterfly nectars has focused on models that
predict optimal volume and concentrations required to meet their energetic demands
(Watts et al., 1974; May, 1985; 1988; Pivnick and McNeil, 1985; Boggs, 1988; Daniel et al. 1989; Hainsworth et al., 1991), and on determining specific sugar and amino acid
composition preferences (Erhardt 1991, 1992; Erhardt et al. 1998). No experiments have
teased apart the effects of reward and visual cues on attraction of butterflies to flowers in
the field.
Pollinators can exert selection on plant traits through both, flower preference, the
net over-visitation of one flower type over another, and flower constancy. Flower
constancy is the restriction of flower visits to fewer flower types or species than available
due to intrinsic limitations in memory (Waser, 1986), or learning abilities (Chittka et al.,
1999). Flower constant visitors show a propensity to sequentially visit flower types previously visited, bypassing alternative, equally rewarding types. While flower preference increases overall visitation, and with it pollen deposition and removal, flower constancy increases assortative pollination, which can be beneficial if fitness costs related
52 to pollen loss, stigma interference and hybridization exist (Waser 1986). Flower
constancy has been examined in few Lepidoptera species, namely, Pieris rapae, P. napi,
and the skipper Thymelicus flavus (Lewis, 1986; Goulson and Cory, 1993; Goulson et al.,
1997a, b). These studies found high fidelity in the butterflies’ choice of flowers, but
conflicting results concerning the existence of costs associated with switching from one
flower type to another. Moreover, there is little evidence supporting the existence of the
memory constraints needed for constancy to occur (Lewis, 1989; Kandori and Ohsaki,
1996). None of these studies, however, evaluated constancy using experimental arrays of
real flowers in the field, as necessary to measure its strength (Waser 1986).
We used arrays of phenotypically manipulated flowers to determine if free flying
Lycaena heteronea, L. rubidus (Lepidoptera: Lycaenidae), Speyeria mormonia,
Cercyonis oetus and Phyciodes campestris (Lepidoptera: Nymphalidae) butterflies show flower preferences and/or constancy. Using experimental manipulations to tease apart the effects of color and other floral traits under field conditions, we asked the following questions: 1) Do these butterflies show spontaneous preferences for flower color and/or for other floral features? 2) Are these butterflies behaving as constant flower visitors, and
does the degree of constancy depend on the choice of traits presented?
53 MATERIALS AND METHODS
Study System
We studied the flower visiting behavior of two lycaenid and three nymphalid
butterfly species near the Rocky Mountain Biological Laboratory (RMBL), located in
Gunnison Co., CO. The ruddy copper (Lycaena rubidus Behr) and the blue copper (L. heteronea Boisduval) butterflies live in high elevation habitats from British Columbia to
North Dakota, and from central California to northern New Mexico. Ruddy copper males
have a bright red-orange upper side, whereas blue copper males have bright blue upper
sides with darker veins. The larval host plants of these species are Polygonaceae from the
genus Rumex in the case of L. rubida and Eriogonum in L. heteronea (Glassberg, 2001).
The mormon fritillary (Speyeria mormonia Boisduval), the field crescent
(Phyciodes campestris Boisduval) and the small wood nymph (Cercyonis oetus
Boisduval) are nymphalid butterflies, also widely distributed in mountainous western north America. Both sexes of the mormon fritillary display an orange/brown coloration on the upper wing. Their larvae feed on species of Viola. Males of the field crescent have
orange/black upper sides and their larval host plants are Aster and Machaeranthera
(Asteraceae). The small wood nymph presents light to dark brown upper sides with one
or two eyespots. Their larvae feed on different species of grasses (Glassberg, 2001).
Adult butterflies feed on the nectar of many different species in the Asteraceae
(personal observation, Glassberg, 2001), four of which we used in this study. To assess
flower color independently from the human visual system, we measured the reflectance
54 spectra of unmanipulated and painted flowers with a S2000 Miniature Fiber Optic
Spectrometer (Ocean Optics). Figure 2.1 shows average reflectance spectra measured
from 3 to 4 flowers taken from different plants. The mountain yarrow (Achillea alpicola
Nuttall) has clusters of white florets that evenly reflect wavelengths above 400 nm and
lack a strong ultraviolet reflectance (Fig. 2.1), whereas the flower heads of the showy
fleabane (Erigeron speciosus Lindall) have yellow disk flowers and purple/blue ray flowers with a peak reflectance at 450 nm and a steady increase in reflectance above 650 nm, also without an ultraviolet component (Fig. 2.1). Both ray and disk flowers of mule's ear (Wyethia amplexicaulis Nuttall) are yellow, reflecting wavelengths above 500 nm
(Fig. 2.1) and all flowers of Hoope's sneezeweed (Dugaldia hoopesii Rydberg) are orange, with reflectance rising above 550 nm (Fig. 2.1). These latter two species do possess ultraviolet reflectance, expressed as a 20% reflectance peak at 350 nm (Fig 2.1).
Spontaneous Flower Preferences and Constancy
In this study we used two different flower arrays. On 2006 and 2007 we observed flower visitation patterns of L. heteronea and L. rubidus in arrays consisting of A. alpicola and E. speciosus, their preferred species in our study sites. In the summer of
2007 and 2008 we added arrays of W. amplexicaulis and D. hoopesii, species in high abundance during those seasons and avidly visited by many butterfly species. We used whole flower heads of E. speciosus, W. amplexicaulis and D. hoopesii and whole or portions of A. alpicola floret clusters as units in the arrays. We will refer to these clusters of florets as ‘flowers’. Each array contained 48, 10-12 cm long, plastic vases (flower
55 picks) spaced every 20 centimeters. Twenty-four flowers from each plant species were
randomly assigned to these vases. For each butterfly entering the array, movements
between flowers were recorded. Flower preference was assessed by treating such a
foraging bout by an individual butterfly as a replicate, and comparing the proportion of
visits butterflies made to each of the flower species with the null expectation of 1/2 using
a one sample t-test.
In the course of these three field seasons (2006-8) we recorded a total of 906
individual flower visits, distributed in 433 foraging bouts to natural, un-manipulated
arrays. In 2006 and 2007, natural arrays of A. alpicola and E. speciosus flowers were
observed from July 13- August 7 for a total of 57 hours. In 2007 and 2008, natural arrays of D. hoopesii and W. amplexicaulis were presented to populations of L. heteronea, C.
oetus, P. campestris and S. mormonia, and observed from July 11-13 for 16 hours. All
observations in all experiments, including those described in later sections, were made
between 8:30 and 17:00.
To test for flower constancy we recorded the particular sequence of visits in each
array, calculated the frequencies of all four possible flight transitions among the two
flower types and constructed a 2 X 2 table to perform a G test of independence for each
array (Melendez-Ackerman et al. 1997). This allowed us to determine if the probability
of moving to a particular flower type depends or not on the previously visited type.
Arrays with less than 40 total transitions recorded were analyzed using Fisher’s exact
test.
We also estimated constancy using Bateman’s constancy index (CI, Bateman
1951), calculated with the following equation:
56
In which A and D represent transitions between flowers of the same type, and B and C
represent transitions between different flower types. Bateman’s index has the advantage
of distinguishing between complete constancy (CI ≅ 1), random transitions (CI ≅ 0), and
complete inconstancy (CI ≅ -1), in which most transitions are between unlike flowers
(Waser 1986).
Spontaneous Color Preferences
To test if any detected flower preferences are due to color (in the broad sense
including hue and brightness) we repeated the experiments using manipulated flower
arrays. In the experiments involving E. speciosus/A. alpicola, one array contained only A.
alpicola flowers, half of them painted with water-based acrylic paint to match the natural
color of the species (white), and half of them painted to match E. speciosus natural color.
The accuracy of the match was tested with a spectrometer (Fig. 2.1). Water-based acrylic
paints have been used previously (Waser and Price 1985, Meléndez-Ackerman and
Campbell 1998) and do not damage flowers. A second array contained only E. speciosus flowers. In 2007 white morphs of E. speciosus flower were abundant, so color arrays contained all unpainted flowers, half of each color morph. In 2008 white E. speciosus flowers were not common, so we applied the painting treatments described above; half of the flowers were painted white, and the other half painted to match their natural purplish
57 blue hue. The same strategy of painting treatments was applied to the W.
amplexicaulis/D. hoopesii arrays. We analyzed the data as explained above.
During the 2006 and 2007 field seasons we recorded a total of 1124 individual visits to color arrays, distributed across 287 foraging bouts. Color arrays of E. speciosus and A. alpicola were presented to populations of L. heteronea and L. rubidus in both years. These arrays were observed from July 17 to August 2 for a total of 50 hours. Color arrays of D. hoopesii and W. amplexicaulis were presented to populations of L. heteronea, C. oetus, P. campestris and S. mormonia in 2007 for 9 hours, from July 25th to
July 27th.
Spontaneous Morphology Preferences
To test if any detected flower preferences are due to preferences for the particular
flower characteristics of a species, aside from corolla color, we constructed arrays of two
plant species, both painted the same color. Any preference seen in such an array could be
due to differences in floral morphology and size, floral nectar, and/or floral scents. For
simplicity, we refer to these arrays hereafter as “morphology” arrays, recognizing that
other cues could be involved. Additional experiments (see below) were used to
investigate possible confounding effects of nectar rewards and display size. In the E.
speciosus/A. alpicola experiments, one array contained only white painted flowers, half
from A. alpicola, and half from E. speciosus. A second array contained only purple
painted flowers, half from A. alpicola, and half from E. speciosus. We constructed similar
58 arrays to study the morphological preference of butterflies visiting W. amplexicaulis/D.
hoopesii.
During the 2007 and 2008 field seasons we recorded a total of 780 individual
visits to morphology arrays, distributed across 264 foraging bouts. In 2007, morphology
arrays of A. alpicola and E. speciosus flowers were observed from August 1st to August
10th for a total of 29 hours. On four out of the five days of observation, the blue and white
arrays were set approximately 4 meters apart, and observed simultaneously. These
simultaneous observations allowed us to extract additional information from comparing
the number of foraging bouts to both arrays on each of the four days using a paired two
sample t-test on log transformed data. In 2007 and 2008, morphology arrays of W.
amplexicaulis and D. hoopesii were observed for 22 hours from July 18th to August 2nd.
The data were analyzed as explained above.
Effect of Paint
A set of experiments was designed as a control for the effects of acrylic paint. In
principle, the paint itself could change other features of the flower traits in a way that
alters the behavior of the butterflies. In addition, minor mismatches between the
reflectance spectra of paint and natural colors also justify this control (Fig. 2.1). Most
importantly, these paints absorbed UV, so that we could not match the reflectance in the
UV that occurs naturally in flowers of D. hoopesii and W. amplexicaulis. In these control arrays, flowers from only one species were employed, half left unpainted and half painted their natural color in the visible range, under the expectation that butterflies would not be
59 able to recognize the difference between these two flower types and therefore should
show no preferences. For each array and butterfly species we compared the proportion of
visits to painted and unpainted flowers using χ2 tests. Combining the 2007 and 2008 field
seasons we recorded a total of 861 visits to the D. hoopesii paint control array, 277 to the
W. amplexicaulis array and 64 to A. alpicola. These arrays were observed for a total of
29.5 hours between July 11-16, 2007 and July 19-31, 2008.
Potential Influence of Other Floral Traits
Spontaneous display size preferences: The size of the floral display can influence flower
visitation, potentially explaining any observed “morphology” preferences. For example,
in morphology arrays containing D. hoopesii and W. amplexicaulis, a putative preference for W. amplexicaulis could be due to a preference for its particular shape or, alternatively, a preference for the larger flowers of W. amplexicaulis larger flowers (diameters of W. amplexicaulis and D. hoopesii range from 8 to 13 cm and 5 to 9 cm, respectively). To
examine the possibility of size preferences, we manipulated the size of the flower unit
used in each array. We manipulated arrays in different ways for each flower species,
depending on its natural morphology and size. In arrays consisting of D. hoopesii, we cut
the ray petals of 24 flowers to half their original length, keeping the remaining 24 intact.
Flowers of A. alpicola were manipulated by plucking florets until 24 of them were half
the size of the other 24 flower clusters. We manipulated E. speciosus arrays by presenting
either single flower heads, or groups of 3 in a single flower pick. In this case flower
preference was assessed by comparing the proportion of visits made by individual
60 butterflies to ‘large’ (multiple flower heads per flower pick) versus ‘small’ (single flower
head per flower pick) flowers.
We recorded a total of 923 flower visits to size arrays during the summer of 2008,
distributed over 252 foraging bouts. Size arrays of A. alpicola and E. speciosus flowers were observed from August 12th to August 22nd for a total of 21.5 hours. Due to low
visitation rates, on four out of five days of observation, the A. alpicola and E. speciosus
size arrays were set approximately 4 meters apart, and observed simultaneously. Size
arrays of D. hoopesii were observed for 5 hours from August 14th to August 15th.
Nectar rewards: Flower preferences could also result from attraction to non-visual
signals. Factors such as scent and/or association with reward can account for flower
preferences and could be the cause of any observed “morphology” preferences. To
account for differences in flower rewards that could underlie flower preferences, we
measured the standing crop of nectar and its sugar concentration in all four plant species
studied. In 2007 and 2008, we measured the nectar standing crop of 39 E. speciosus, 44
A. alpicola, 47 W. amplexicaulis and 50 D. hoopesii flower heads or flower clusters,
bagged for 24 hours. Since the small size of individual florets prevents the use of micro-
capillaries to collect nectar, we measured the nectar produced by whole flower heads or
flower clusters by spinning them for five minutes in a micro-centrifuge using 1.5 ml
micro-centrifuge tubes equipped with a fine mesh to contain the flowers from reaching
the bottom of the tube where nectar was collected. The minute amounts of nectar
collected in the bottom of the micro-centrifuge tubes were then extracted using micro-
capillary tubes. A portable refractometer was used to determine the sugar concentration
61 of the nectar. We used two-sample t-tests to asses if the nectar volume and concentration
differed between the two species used in a particular array.
Reproductive System
Flower visitation does not necessarily imply effective pollination. To determine if
the plant species used in this study need a pollen vector to achieve successful
reproduction, we studied their reproductive systems, performing three different crossing
treatments during the 2007 and 2008 field seasons. Thirty individual flower heads or
flower clusters per species were bagged before opening using bridal veil netting of mesh
size < 1 mm2, and one of three treatments was applied to each of them after anthesis. Ten
flower clusters remained bagged with no further manipulation, ten were manually self- crossed with other bagged flowers of the same plant, and ten were manually out-crossed.
Since the individual flowers of composite flower heads open in a temporal and spatial sequence, we applied the treatments on five consecutive days to ensure that as many as possible of the individual flowers had been receptive. Bagged flowers were collected 3 weeks after the original bagging, and viable seeds were counted with the help of an optical microscope. We used a one-way ANOVA and Tukey a posteriori comparisons to assess which treatments, if any, had an effect on the number of seeds produced per flower head or cluster.
62 RESULTS
Spontaneous Flower and Color Preferences
At natural arrays of unpainted flowers, L. heteronea preferred to visit A. alpicola
over E. speciosus (t = 4.51, df=67, p<0.0001, Fig. 2.2). In color preference arrays, L, heteronea preferred white over purple E. speciosus (t = 2.05, df=29, p<0.05, Fig. 2.3) and while there were no statistically significant preferences for white or purple A. alpicola (t
= 0.72, df=21, p=0.24), on average L. heteronea over-visited white flowers (average proportion of white flowers visited = 0.56, Fig. 2.3). These results suggest that the preference of L. heteronea for the normally white-flowered A. alpicola is based, at least in part, on a preference for white over purple.
In contrast to L. heteronea, its congener L. rubidus preferred to visit E. speciosus over A. alpicola in both 2006 and 2007 (combined data for both years: average proportion of visits to A. alpicola = 0.26, t =4.64, df=52, p<0.0001, Fig. 2.2).
Unfortunately we could not get enough visits to the painted arrays (total of 20 visits to both color arrays in two seasons) to robustly determine which particular visual cue is driving their feeding decisions.
In the 2007 season, when presented with an array containing unpainted D. hoopesii and W. amplexicaulis. L. heteronea, S. mormonia, and P. campestris all preferred the orange flowers of D. hoopesii over the yellow W. amplexicaulis (t =10.27, df=187, p<0.0001; t = 3.27, df=32, p<0.01; t = 28.95, df=35, p<0.0001, respectively, Fig.
2.2). Visits from S. mormonia and P. campestris to the natural arrays were scarce in the
63 2008 field season; we were able to collect visitation data only for C. oetus and L.
heteronea. Both species preferred W. amplexicaulis over D. hoopesii (t = 2.87, df=34, p<0.01; t = 2.27, df=19, p<0.05, respectively, Fig. 2.2), with L. heteronea reversing the preference for D. hoopesii observed in 2007.
In terms of color, P. campestris and S. mormonia preferred orange over yellow D. hoopesii (t =2.50, df=20, p<0.05; t =4.07, df=79, p<0.0001, Fig. 2.3), but showed no color preferences when choosing between orange and yellow W. amplexicaulis (t =0.84, df=3, p=0.24; t =1.07, df=20, p<0.15, Fig. 2.3). The situation was reversed for L. heteronea and C. oetus. Both species preferred yellow over orange W. amplexicaulis (L. heteronea: t =6.93, df=24, p<0.0001; C. oetus: t =21.44, df=43, p<0.0001, Fig. 2.3), but showed no color preferences when choosing between orange and yellow D. hoopesii (L.
heteronea: t =1.69, df=8, p<0.07; C. oetus: t =1.24, df=18, p<0.12, Fig. 2.3).
Spontaneous Morphology Preferences
When analyzing color and morphological preferences separately, we found that
different butterfly species utilize these visual cues in diverse ways. When all offered
flowers were white, L. heteronea preferred A. alpicola over E. speciosus (t = 2.58, df=66,
p<0.05, Fig. 2.4), suggesting that a preference for flower morphology exists
independently of color. Nevertheless, the fact that the purple array had a total of only 7
visitation bouts (contrasted with the white array, which was observed simultaneously and
visited by 67 individuals; two sample paired t-test: t =7.04, df=3, p<0.01) suggests that
64 the preference for the color white is stronger than the preference for other particular
flower characteristics (Fig. 2.4).
Neither P. campestris nor C. oetus showed any preferences based on morphology
When all flowers presented were painted orange, visits to D. hoopesii and W. amplexicaulis were not significantly different (P. campestris: t =0.39, df=4, p=0.36; C. oetus: t =1.24, df=23, p<0.23, Fig. 2.4). Similarly, when all flowers presented were painted yellow, C. oetus visits to D. hoopesii and W. amplexicaulis were not significantly different (t =0.12, df=18, p=0.46, Fig. 2.4). In contrast to those two butterfly species, both
L. heteronea and S. mormonia had strong morphology preferences. L. heteronea preferred W. amplexicaulis irrespective of the color used for the array (orange array: t
=3.20, df=16, p<0.006; yellow array: t =2.97, df=11, p<0.05, Fig. 2.4), whereas S. mormonia preferred D. hoopesii irrespective of color (orange array: t =3.00, df=59, p<0.005; yellow array: t =3.52, df=25, p<0.005, Fig. 2.4). L. heteronea also preferred yellow W. amplexicaulis over yellow D. hoopesii in 2008 (t =1.76, df=33, p<0.05).
Flower Constancy
During the 2006-2008 field seasons we recorded a total of 2111 flight transitions among flowers in our natural, color, morphology and size arrays. Despite the fact that different butterfly species showed different color and morphological preferences, none of them displayed a flower constant behavior while foraging for nectar in any of the arrays employed (Table 2.1). The probability of moving to a particular flower type (species, color, morphology, size) was independent from the previous flower type visited (G test of
65 independence, Fisher’s exact test, Table 2.1), and Bateman’s indexes show that most transitions were random and not likely to be either between like or unlike flowers (Table
2.1). No constancy was detected even for experiments with sample sizes as large as 361 transitions.
Effect of Paint
The acrylic paint applied to flower corollas did not affect visitation behavior by
D. hoopesii, W. amplexicaulis or A. alpicola. For the 8 combinations of butterfly species and flower species tested, none showed a preference for painted versus unpainted flowers of the same color (proportion of visits to painted flowers ranged from 0.45 to 0.55, all χ2 tests: p>0.10).
Spontaneous Display Size Preferences
In arrays consisting of cut/unmanipulated D. hoopesii ray petals we found no size preferences for any of the three butterfly species that visited these arrays (C. oetus: t
=0.64, df=14, p=0.53; P. campestris: t =0.66, df=5, p=0.54; S. mormonia: t =1.33, df=15, p=0.20; Fig. 2.5). On the other hand, large A. alpicola flower clusters were preferred over small ones by both C. oetus and L. heteronea (C. oetus: t =11.34, df=54, p<0.0001; L. heteronea: t =8.72, df=101, p<0.0001; Fig. 2.5). C. oetus and L. heteronea also showed a preference for large (3 flower heads) versus small (single flower heads) E. speciosus flowers (C. oetus: t =6.40, df=5, p<0.002; L. heteronea: t =3.01, df=38, p<0.05; Fig.
66 2.5), whereas P. campestris, and S. mormonia showed only marginally significant preferences (P. campestris: t =2.34, df=5, p=0.07; S. mormonia: t =2.17, df=6, p=0.07,
Fig. 2.5).
Nectar Rewards
The nectar volume and concentration of A. alpicola flower clusters (average of 30
individual flowers per cluster) did not differ from those of E. speciosus flower heads
(volume: t=0.66, df=81, p=0.51; concentration: t=0.71, df=16, p=0.49). An A. alpicola
cluster produced an average of 0.39 ± 0.96 μl of nectar whereas an E. speciosus flower
head produced an average of 0.50 ± 0.61 μl of nectar. The average nectar concentration
was 19.80 ± 7.43 % in A. alpicola and 21.69 ± 4.03% in E. speciosus. Individual florets
of W. amplexicaulis produced larger amounts of nectar than D. hoopesii florets (W.
amplexicaulis: 0.09 ± 0.08 μl; D. hoopesii: 0.02 ± 0.02 μl; t=5.38, df=80, p<0.0001) but
entire flower heads of these two species did not differ in either total nectar volume (W.
amplexicaulis: 2.42 ± 2.18 μl; D. hoopesii: 3.42 ± 4.55 μl; t=1.37, df=95, p=0. 17) or concentration (W. amplexicaulis: 56.75 ± 15.25 %; D. hoopesii: 53.14 ± 12.00 %; t=1.00, df=57, p=0.32).
67 Reproductive System
In both 2007 and 2008, E. speciosus produced more seeds when out-crossed than when self-crossed or bagged without manipulation (data combined for both field seasons:
ANOVA: F2,50=10.53, p<0.0002, Fig. 2.6), suggesting both the need of a pollen vector
and the presence of self-incompatibility and/or early acting inbreeding depression (Post-
hoc Tukey test: bagged v/s outcrossed, p<0.004; selfed v/s outcrossed, p<0.0006). The same was true for A. alpicola (ANOVA: F2,16=13.07, p<0.001; post-hoc Tukey test:
bagged v/s outcrossed, p<0.002; selfed v/s outcrossed, p<0.002, Fig. 2.6). We detected no
effects of crossing treatment on the number of seeds produced by D. hoopesii, (combined
data from 2007-08: ANOVA: F2,54=0.36, p=0.70) or W. amplexicaulis (ANOVA:
F2,27=0.72, p=0.50, Fig. 2.6).
68 DISCUSSION
Preferences
The four butterfly species Lycaena heteronea, Speyeria mormonia, Cercyonis oetus and Phyciodes campestris utilized different combinations of visual cues while foraging for nectar. Both P. campestris and C. oetus possessed color, but no morphology/rewards preferences. These two species seemed to be choosing familiar combinations of visual cues. For example P. campestris, which preferred the naturally orange flowers of D. hoopesii, significantly over-visited orange over yellow D. hoopesii as expected, but when exposed to an array consisting of only W. amplexicaulis flowers
(whose natural color is yellow), it over-visited yellow compared to orange flowers, although not significantly so. Even though C. oetus did not display significant morphology/rewards preferences, it behaved similarly, over-visiting D. hoopesii when all flowers were painted orange, and W. amplexicaulis when all flowers were painted yellow.
S. mormonia chose flowers based on both color and morphology. It strongly preferred flowers from D. hoopesii, both because of a preference for the color orange, and for other flower characteristics.
The phenotypic manipulation of flower color allows us to explore the nature of the association between this and other floral traits. These experiments provide one of the few cases demonstrating that pollinators have color preferences under field conditions
(Rausher 2008). In addition, the use of both color arrays and “morphology” arrays allows consideration of whether butterflies respond to the two kinds of traits in the way that is
69 predicted from responses to each alone. Floral trait associations could arise from genetic
or developmental mechanisms, or alternatively from adaptive pollinator-mediated correlational selection, in which a particular combination of traits is favored at the expense of others (Endler, 1995). Surprisingly, the putative existence of correlational evolution of flower traits has seldom been explored experimentally (Herrera, 2001), despite having been suggested as potentially the commonest mode of natural selection
(Schluter and Nychka, 1994). In our study, the behavior displayed by L. heteronea provides the strongest evidence that butterfly visitation could impose correlational selection on flower traits. In simultaneously observed white and purple morphology arrays of A. alpicola and E. speciosus, it significantly preferred A. alpicola over E. speciosus when both were painted white, but made the reverse choice when both were painted purple. Since E. speciosus and A. alpicola require a pollen vector to set seed, this behavior has the potential to exert selection on floral traits, although estimates of effects on male or female fitness would be required to demonstrate selection. The behavior of P. campestris also suggests a potential for correlational selection, since it significantly preferred orange in D. hoopesii arrays, while showing no significant color preferences in
W. amplexicaulis arrays. To confirm this possibility a larger sample size of P. campestris visits to W. amplexicaulis color arrays is needed.
In 2007, the behavior displayed by L. heteronea was puzzling. It chose flowers based on both color and morphology/rewards, but its preferences were not coherent. It preferred D. hoopesii, but when color and morphology/rewards were decoupled, it seemed to prefer the color yellow and the morphology/rewards of W. amplexicaulis.
These results can be understood if the flower preferences of L. heteronea shifted
70 throughout the season. The arrays with unpainted flowers of both species were utilized only at the beginning of the field season, followed by the painted arrays, and therefore L. heteronea butterflies could have learnt to avoid its originally preferred species, switching to a diet consisting primarily of W. amplexicaulis flowers, and concurrently switching its color preference to yellow and its morphology preference to W. amplexicaulis.
Considering that the resources of both species were not significantly different in terms of quality and quantity of nectar, such switching behavior could be beneficial for L. heteronea only if the demand for W. amplexicaulis was lower than for the heavily used flowers of D. hoopesii. In this scenario, if W. amplexicaulis flowers possess characteristics unattractive to some butterfly species other than L. heteronea (e.g. a particular scent), visits to D. hoopesii could offer less and less reward compared to W. amplexicaulis as the season progresses.
Lycaena rubidus shares the geographical range and habitats of the closely related
L. heteronea (Glassberg, 2001; Pratt and Wright, 2002), and possesses the same combination of four visual pigments in the ventral half of the compound eye (Bernard and Remington, 1991; Sison-Mangus et al., 2006). Flying over two-dimensional landscapes such as the mountain meadows where we conducted this study, these butterflies are presumably detecting flowers with these ventral ommatidia, implying that in principle the two species can detect the same flower colors. In this light, it is interesting that L. heteronea and L. rubidus preferred different flower species (and presumably colors). The display of different spontaneous flower preferences could be due not to dissimilar perceptual capabilities but to ecological factors such as aggressive competition for floral resources, as was observed in two Brazilian Heliconius species
71 (Duarte and Duarte, 2001). Different reward quantity/quality preferences are not likely
causes for this partition of resources, since the flower units of A. alpicola and E.
speciosus did not differ in either nectar volume or concentration.
Nectar volume and concentration were also similar between D. hoopesii and W.
amplexicaulis flowers, ruling out the role of rewards in producing the apparent
morphology preferences encountered in this study. Conversely, larger flower display
sizes were generally chosen over smaller ones, though only C. oetus and L. heteronea
preferences were significant. These size preferences could have confounded our results
from arrays consisting of combinations of D. hoopesii and W. amplexicaulis, since the
latter’s flower heads are generally larger than D. hoopesii’s (personal observation, see above). However, no butterfly species showed size preferences in D. hoopesii arrays; moreover, three of the butterfly species showed a consistent preference for the smaller- flowered D. hoopesii, which clearly cannot be explained by a preference for large size.
With the present information we can not rule out the role of size as a trait partly responsible for the preference of C. oetus for W. amplexicaulis flowers. Larger flower and flower display sizes preferences have been previously described in Lepidoptera (Ilse,
1928; Vaughton and Ramsey, 1998; Thompson, 2001; Arroyo et al., 2007, but see Kelber
1997).
72 Constancy
The striking absence of flower constancy found in this study in the face of distinct flower preferences contrasts with the scarce literature advocating for the existence of flower constancy in butterflies (Lewis, 1986; 1989; Goulson and Cory, 1993; Goulson et al., 1997a, b; but see Kandori and Ohsaki, 1996). However, none of those studies used experimental manipulations of real flowers to approach the question of constancy under field conditions, but instead either utilized natural or artificial flowers in artificial settings, or followed free flying butterflies recording all flowers visited in a certain area.
The drawback of the latter approach is that the percent of conspecific transitions is a function not just of constancy, as in an experiment with randomly arranged flowers, but also of the natural spatial arrangement of the flowers. Furthermore, several of these studies did not test constancy per se but measured handling and/or searching times, behaviors that influence the advantage of constancy to the visitor.
The absence of constancy, as observed in the current study, could be disadvantageous for plant species that rely mostly on butterflies for pollen transfer.
Nonetheless, successful butterfly pollination has been unequivocally shown in many occasions (Levin, 1968; Schmitt, 1980; Courtney et al., 1982; Arroyo et al., 1982; Bloch and Erhardt 2008). Flower inconstancy can decrease plant reproductive success by lowering visitation by more constant visitors (Feinsinger, 1987), pollen loss to foreign stigmas (Campbell and Motten, 1985), stigma clogging and interference with foreign pollen (Thomson et al., 1981), and production of unviable hybrids (Levin, 1972). The magnitude of these fitness costs is little understood, and potentially they could often be
73 offset by the advantage of having more visitors, regardless of their degree of constancy
(Chittka et al., 1999). For example, some species may suffer low costs from the deposition of foreign pollen by inconstant visitors (Feinsinger et al., 1987), and species that share inconstant pollinators may forego these costs by placing their pollen loads on different body parts of their visitors (Armbruster and Herzig, 1984). To explore these possibilities, future experiments could be designed to: examine how much pollen is transported on the body of a butterfly to a long series of visits (pollen carryover); test if the flowering species they visit are pollen-limited; and investigate which flower traits are most likely to induce constancy/inconstancy in butterfly pollinated species.
74 Figure 1.1. Alignment of 29 lepidopteran UVRh complete coding sequences
V. cardui MIP-VLNMDNKTENYNIYGAYFAPLSSSDGIKMLVDGLEGEDLAAVPEHWFSYAAPPASAHTALALLYCFFTAAALIGNG 80 E. chalcedona ...-S.T.E....D...... V...... SI...... S...... 80 N. antiopa ...-...... S...... V...... VI...... L...... 80 L. arthemis ...-..K...E...N.V...... V....E..NS..M.VM....L..T...... 80 L. archippus ...-..K...E...N.V...... V....E..NS..M.VM....L..T...... 80 D. plexippus ...-TIT...D.D.I.V...... E.T...M...T...... HT.PS...... 80 D. gilippus ...-TIT...E.D.F.V...... M...M...T...... HT.T...... T...... 80 H. erato ------.E.E.Q...V...F...... V...... DSV...VM....L..TS...... S...... 80 H. melpomene ------.E.E.Q...V...... V...... DSA...V.....L..P...... 80 A. vanillae .M.NT.K.E.D.Q...V...... V...... DS....VM....L..T...... S...... 80 S. mormonia ...-.MK.E.D.D..SA...... V...... DSD...VM....L..T...... M... 80 C. tullia .L.-TAT...D.HDF.T...... -G.M...... M...... T.E...... 80 B. anynana .M.-T.....D.Q.F.T...... V..S....E.....A...I.D..M...S...... 80 N. ridingsii ...-TI.V..D.Q.F.T...... TA...... M...... 80 O. chryxus ...-T.....D.H.F.T...... T...... M...... 80 L. rubidus ...-S.S..T.N.S.HL...... EPE...... T....E...... L..T...... I...... 80 L. helloides ...-S.V..I.N.S.HL...... SE..G...T....E...... L..P...... I...... 80 L. heteronea ...-S.V....N.S.HL...... SE..G...T....E...... L..P...... I.L...... 80 L. nivalis ...-S.V....N.S.HL...... SE..G...T....E...... L..P...... I...... 80 S. behrii .V.-S.D..SHN.T.HL...... SE..G...T...... L..P...... M.L...... 80 A. glandon ...-PMD..-.N.T.HL...... AVV..GE..T.....Q.....L..P...... M...... T...... 80 P. icarus ...-PMD..-.N.T.HL...... AME..GE..T.....Q.....L..P...... T...... 80 A. mormo ...-S.S.E.S..S.SM...... -.ETE..G...T...... L..H...... S...V...V... 80 C. philodice ...-TQD...S..Y...... -G.ER..GE..T.....MM.....K.PE...... C...... 80 P. rapae ...-TQD...S..Y...... -G.E...GE..T....EMM.....K.PE...... C...... 80 P. glaucus ..A-PAA...H...NYN...... Y..DEPVE..GA..T.A....I....LA.P...... M...V.V...... 80 P. xuthus ...-AAV...H...NYN...... Y.LEG-VEL.GA..T...... I....L..P...... M...V.V...... 80 M. sexta ------.N.QS...Y-H..Q.EA.K.AGA.E..G...T.D....M....L..P...... I...F...V... 80 B. mori ------AGAVE..G...S.D...... LTFP...... I...... L... 80
V. cardui LVVFMFATTKSLRTSSNLLILNLAIFDFIMMAKAPLFIYNSAMRGFATGALGCQIFAVMGSYSGIGAGMTNACIAYDSHS 160 E. chalcedona ..IY...... L..M...... I...... Y...VM.....S...... A...... 160 N. antiopa ..M...S...... L..M...... M...... L...... 160 L. arthemis ..M.V...... L..M...... I...... L...... 160 L. archippus ..M.V...... L..M...... I...... L...... 160 D. plexippus M.M.I.L...... S...... I.M....L....A.PV...M.S...A...... S...... 160 D. gilippus M.M.I.M...... MS...... M....L....A.D....M..L...... V.S...... 160 H. erato ..I.....SS..S...... I...... S...... S...... 160 H. melpomene ..I.V...... F...... S...... 160
75 A. vanillae ..I...... S...... M...... I...... S...... S...... 160 S. mormonia ..I.I.....I.S...... I...... S...A...... AT...... 160 C. tullia ..M...S...C.S...... ML..M..L...V....A.N....S.V....M..L...... 160 B. anynana ..M...S...... ML..L...... I...... N....S.V....M..L...... 160 N. ridingsii ..M...?.....S...... ML..M...... I.....VNS.....?....M..L...... 160 O. chryxus ..M...... S...... ML..M...... I.....INK...A...... M...... 160 L. rubidus ..M...... Q..ML..M...... M...... V....M..L...... M...... 160 L. helloides ..M...... Q..ML..M...... M...... M..L...... M...... 160 L. heteronea ..M...... Q..ML..M...... M...... M..L...... M...... 160 L. nivalis ..M...... Q..ML..M...... M...... M..L...... M...... 160 S. behrii ..IYI...... Q...L...... M...... M..L...... M...... 160 A. glandon ..M.I...... Q..ML..M...... I.....M...... M..KM..L...... 160 P. icarus ..M.I...... Q..ML..M...... I.....M...... M..KM.GL...... 160 A. mormo ..I...... Q..ML..M..L...M...... ?M...M.G...... 160 C. philodice M.I....S...... A...... M...... L...M.M...... A...W.KM...... M..A...... 160 P. rapae M.M.I..S...... A...... M...... L...M...... K...A..MW..M...... 160 P. glaucus ..M.I.SAS.....P....VVQ...L..L..L...M.....MK....A.VM...M..F...V..TA..L....M...... 160 P. xuthus ..M...SAS.....P....VVQ..VL..L..L...M.....MK....S.VI...M..F...V..TA..L....M...... 160 M. sexta M.M...S...... F.V....ML..M...... M...... V.TV...M..L..A...... M...... 160 B. mori ..I.V.S.....S...... Q..ML..M...... M...... TI.....S...A...M...... R.. 160
V. cardui TMTRPLDGRLSRGKALLMMALVWIYATPWSLMPLFKVWGRFVPEGYLTSCTFDYLSNTFDTKLFVACMFVCSYVFPMSFI 240 E. chalcedona ...... V.IM.M...... Q....Y...... T...... P..?.I...... M 240 N. antiopa ...... IM...... 240 L. arthemis .I...... S...... C...... T...... V.T...... 240 L. archippus .I...... S...... C...... T...... V.T...... 240 D. plexippus .I...... Q...... F..M...... L...... S...... T...... TM. 240 D. gilippus .I...... Q...... C..M...... L...... S...... S...... T...... M. 240 H. erato .I...... S...... C...... A.....N...... G.I.T...L...C.. 240 H. melpomene .I...... S...... C...... N...... T...... G.I.T...L...G.. 240 A. vanillae .I.S....S...... C...... N...... T...... G.I.L....L..... 240 S. mormonia .I...... S...... C...... A.....S...... T...... G.I...... LL. 240 C. tullia ...... C...... L....I....A...... T...... G...... C...... 240 B. anynana ...... I.CI.M...... ML..L.I..S...... S....T.S...... G...... C...F.M 240 N. ridingsii ...... V.....CM...... L...... T....N....G...... M 240 O. chryxus ...... CM...... I..S...... T...... G...... M 240 L. rubidus ...... VM....CM...... L...... Y...... TD...... I...... M. 240 L. helloides ...... VM...TFM...... L...... Y...... T...... I...... M. 240 L. heteronea ...... VM....CM...... L...... Y...... T...... I...... M. 240 L. nivalis ...... VM....CM...... L...... Y...... T...... I...... M. 240 S. behrii ...S...... VM....CM...... L....I...Y...... T.S...... G.I...... L. 240 A. glandon ...... Q...I..V.CM...... E....Y...... G.I.L...... TM. 240
76 P. icarus ...... Q...I..V.FM...... E....Y...... G.I.L...... TM. 240 A. mormo ...... S.....VMM...FI.M...... L...... Y...... T...... 240 C. philodice .I.S...... S..V....ICM.M.T...... S...S...... T.S..N....G...T...... LC. 240 P. rapae ...S...... S..V.....FM...T...... S...... F...... TT...N...... C. 240 P. glaucus .I...... V....VC..V.TA..AIL.QLQI...Y....F...... TT...N.....S....V.....LA. 240 P. xuthus .I...... V....VC..L.TA..AIL.QLQI...Y....F...... TT...N.....S....V.M...IA. 240 M. sexta .I...... S..E..V...V.F..M.S...A.L..L.I..SY...... S....T...... T...... LM 240 B. mori .I...... S..K..V.....F..M.C...A.L..L.I..SY...... T...... I...... MM 240
V. cardui MYFYSGIVKQVFAHEAALSEQAKKMNVESLSSNQNASAESAEIRIAKAALTVCFLFVASWTPYGVMSLMGAFGDQQLLTP 320 E. chalcedona I...... R...... R.... 320 N. antiopa I...... M...... R.... 320 L. arthemis I...... R.....A.....V.M...... R.... 320 L. archippus I...... R.....A.....V.M...... R.... 320 D. plexippus ...... R...... M...... A...... R.... 320 D. gilippus ...... R...... M...... S...... A...... R.... 320 H. erato ...... R...... M...... 320 H. melpomene ...... R...... M...... 320 A. vanillae ...... S...... R...... M...... 320 S. mormonia ...... R...... M...... R.... 320 C. tullia ...... S...... D...... M.M...... TA.I...... S.... 320 B. anynana L...... R.....A...... SM...... A....Y...N.... 320 N. ridingsii L...... R...... SM...... S.... 320 O. chryxus L...... R...... SM...... S.... 320 L. rubidus I.....M...... D..R.....A...... M...... A.I...... S.... 320 L. helloides I.....M...... D..R.....A...... M...... A.I...... S.... 320 L. heteronea I.....M...... D..R.....A...... M...... A.I...... S.... 320 L. nivalis I.....M...... D..R.....A...... M...... A.I...... S.... 320 S. behrii I...... D..R.....A...... M...... A.I...... S.... 320 A. glandon ...... R...... D..R.....G...... SM...... A...... N.... 320 P. icarus ...... R...... D..R.....G...... SM...... A...... N.... 320 A. mormo I.....M...... G...... M...... S...... A...... N.... 320 C. philodice I...... R.....G.....M...... I...... E.... 320 P. rapae I...... R...... R.....A...... S...... T...... N.... 320 P. glaucus ...... D...... Y...... I...... N.... 320 P. xuthus L...... D...... A...... Y...... I...... N.... 320 M. sexta ...... A..GG.S.....SM...... A...... N...... 320 B. mori I...... RA..SGASQ...MSM...... A...... 320
V. cardui GVTMIPAVTCKLVACIDPWVYAISHPKYSQELQSRMPWLQINEPDDNASTGTNNTANSS-APA-TA 386 E. chalcedona ...... A..T...... K...... -...AS. 386 N. antiopa ...... V...... -...-.. 386
77 L. arthemis ...... A..A...M...... R...... M...... T...-.T.AS. 386 L. archippus ...... A..A...... P.R..S...M...... T...-.T.AS. 386 D. plexippus ....M...A..T...... R...... V.NT..G.T..TA..--.. 386 D. gilippus ...... A..A...M...... R...... V.NT..G.T..TA..--.. 386 H. erato ...... A..T...... RS.....MS...... T..T-...AS. 386 H. melpomene ...... A..T...... RS.....MS...... T..T-...A.. 386 A. vanillae ...... A...... R...... MR.....V...... T..T-...A.. 386 S. mormonia ...... A..A...... R...... M...... T...-...AS. 386 C. tullia ...... L...A...... R...... V...... T..-A..--.. 386 B. anynana ...... A...M...... R...... M...... T..T..T-T.--.. 386 N. ridingsii ...... R...... S..V....T..-.K.A..--.. 386 O. chryxus ...... A...... R...... T..T...-..--.. 386 L. rubidus ....M...A..A...... R...... M...S.T.....T..T..T-...AS. 386 L. helloides ....M...A..A...... R...... M...S.T.....T..T..T-...AS. 386 L. heteronea ....M...A..A...... R...... M...S.T.....T..T..T-...AS. 386 L. nivalis ....M...A..A...... R...... M...S.T.....T..T..T-...AS. 386 S. behrii ....M...A..A...... R...... M...S.T.....T..T..T-...AS. 386 A. glandon ....M...... A...... R...... M...S.T.....TA.-..-A...-S. 386 P. icarus ....M...... A...... R...... M...S.S.....TA....-A...-S. 386 A. mormo ...... A...... K...... T.NAS.A....-A..PAS. 386 C. philodice ...... M...A...M...... RS...... S...... NTS.T.T..-A...-W- 386 P. rapae ...... M...A...... M...... S...... T..TS.T.T..-A...-W- 386 P. glaucus ....M..LA..G...... K...... D.....V.NT...... -...--- 386 P. xuthus ....M..LA..G...... K...... D...... NT.S...... -...--- 386 M. sexta ...... A..A....S...... M...... R...... D....TV..A.S..T..-AP..A.. 386 B. mori ....M...A..A...M...... R...... TT..A.S..VS.-AP..AP. 386
78 Figure 1.1. Alignment of 35 lepidopteran BRh complete coding sequences
V. cardui -MATNYTDDIG---PVAYPLKMVTQEVVEHMLGWNIPEDHQDLVHEHWSNFPAVSKYWHYGLAFIYTILMLASVSGNGIV 80 E. chalcedona -...... ---.A...... S...... E...... R...... F...C..S....T.L....M. 80 N. antiopa -...... ?..---...... M...?.L...... 80 L. arthemis -...... ---...... SK....N...... E..E...... IC..L...... V..M...... 80 L. archippus -...... ---...... S....QN...... E..E...... N....IC..L..S...I..M...... 80 D. plexippus -....F.E...---.M...M...S...... E...... R...... F...... L.....MT..... 80 D. gilippus -....F.E...---.M...... S...... E...... R...... L.....MT..... 80 H. erato -...... ---.M...... S...... E..G...... S....A.FV..L...C.....L...... 80 H. melpomene -...... ---...... S...... E...... A.FV..L..SF...... 80 A. vanillae -..A...... ---...... S...... E..E...... A.FT...... L..I...... 80 S. mormonia MA.S...E...---...H...L.S...... E...... I...L..SL..I..M...... 80 C. tullia -....F.....---...W...... E...... E..A...... RD...... M...V..I..CL..... 80 B. anynana -...... E...---...W.....S...... E...... D...D...... F...L...V..F..M...... 80 L. rubidus1 -..Y.F...F.---...H.....SS.AE...... EY.YF...... M..L..C..CL..... 80 L. rubidus2 -.EG.F..NM.---.L...FQ..SK.TE..V....Y..EY.FM.QD...SY..I...... M.F....T..... 80 L. helloides1 ------...... C..CL..... 80 L. helloides2 -.EG.F..NM.---.L...FQ..SK.TD..V....Y..EY.FM.QD...SY..I...... M.F...IT..... 80 L. heteronea1 -..Y.F...F.---...H.....SS.AE...... EY.YF...... M..L..C..CL..... 80 L. heteronea2 -.EG.F..NM.---.L...FQ..SK.TD..V....Y..EY.FM.QD...SY..I...... M.F...IT..... 80 L. nivalis1 -..Y.F...F.---...H.....SS.AE...... DEY.YF...... M.....C..CL..... 80 L. nivalis2 -.EG.F..NM.---.L...FQ..SK.AD..V....Y..EY.FM.QD...SY..I...... M.F...IT..... 80 S. behrii1 -..Y.L.E.F.---..G...... SS.TE...... DEY.YF...... Y...... M..M..C..CL..... 80 S. behrii2 -..G.F..NL.---.L...FQ...K.TD..V....Y..EY.FM.Q...RSY..I...... M.F...IT..... 80 A. glandon1 -..Y.L...F.---...-A....SD.AE...... V..EY.YF..D..RAY.....W...... M..M..FC.CL...M. 80 A. glandon2 -.D-.S.EN..---.T..AFQ.IEE.TK.NI..Y.Y..EY.FM.QD...SY..IN.....S..L...M.FI..IT..... 80 P. icarus1 -..F.L...F.---...-A....SD.AE...... V..EY.YF..D..RAY.....W...... M..M..FC.CL...M. 80 P. icarus2 -.D-.S.GN..---.M..AFQ..EE.TK..I..Y.Y..EY.FM.QD...SY..IN.....S..L...M.FI..IT..... 80 A. mormo -..M.F..G..---.L.L..Q.MA..AE...... M..E..H..Q....SY...... CM.AL.W....T..... 80 C. philodiceV -..E.F.ENE----.I.F.Y...SH.IQK...... M..E..H...... RQ..D.DRSS..L..LM....TMS..T...L. 80 P. rapaeB -DTV.A.A.G.---AI..AF...SS..Q.N...F...PE...... R.....D.F...M..L...M..VS.LC..... 80 P. rapaeV -.EL...AGD----.I.F.F...SG..QQ...... AE..G...... RQ....D.FS..L..L..F...IF..T..SL. 80 P. glaucus -..A..S....---.M...M.L.SS.I....M...... E..AM..A..RS...... Y.FI..L...M..VT.LI..... 80 P. xuthus -..A..S....---.M...M.L.SS.M....M...... E..AM..A..RS...... Y.FI..L...M..VT.LV..... 80 M. sexta -....F.QELYEIG.M...... MSKD.A...... E...... D..R...... V..LM..M..VT.LT..... 80 B. mori -..L.F.QEMSDIG.M...... SS.M...... E...... S...... C..LM.AM..VT.LV..... 80
V. cardui MWIFSTSKSLRSASNMFVINLAVFDLMMMLEMPMLVVNSFYQRLLGYQLGCDMYAVLGSLSGIGGAMTNAIIAFDRYKTM160 E. chalcedona ...... IS...... P...... Y....G...... 160 N. antiopa ...... L..T...... 160 L. arthemis I.M...... I..M...... M...... V...... V...... 160 L. archippus I.M...... I..M...... M...... V...... F...... V...... 160 D. plexippus I.M...... P...... I..F...... L..L...H.S...... I...V...... I160 D. gilippus I.M...... P...... M..F...F...L..L...H.S...... I...V...... I160 H. erato I.M...... M...... M...... L..L...... V...... G...... I...V..Y.....I160 H. melpomene I.M...... T...... M...... M...M...... L...... V...... F...... I...V..Y.....I160
79 A. vanillae I...... A..V...... L.II.....HPI.F...... G...... I..VV..Y.....I160 S. mormonia I.M...... Y...... R....L.G.F...... SI...... 160 C. tullia ..M...... T...... L..I...H..PV...... G...... I..V...Y...... 160 B. anynana I.M...... M...... I...L..I...H.S.V...... I..V...Y...... 160 L. rubidus1 I...... S.P...... L..TL..F...L.I...... KM.....S..I..SF.AM...... I160 L. rubidus2 I...... A...P...... V...... FIL...HH.IV...TV..I..T...M..F...I...V..Y.....I160 L. helloides1 I...... S.P...... L..TL..F...L.I...... KM.....S..I..S..AM...... I160 L. helloides2 I...... A...P...... V...... FIL...HH.II...TV..I..T...M..F...I...V..Y.....I160 L. heteronea1 I...... S.P...... L..TL..F...L.I...... KM.....S..I..SF.AM...... I160 L. heteronea2 I...... A...P...... V...... FIL...HH.II...TV..I..S...M..F...I...V..Y.....I160 L. nivalis1 I...... S.P...... L..TL...... L.I...... KM.....N..I..S...M...... I160 L. nivalis2 I...... A...P...... V...... FIL...HH.II...TV..I..T...M..F...I...V..Y.....I160 S. behrii1 I...... P...... I..TL..F.....IA.....KM.....S..I..SF.A...M...... I160 S. behrii2 I...... P...... V...I...IF.L...H.HII...AV.NV..T...I..F...I...VM.Y.....I160 A. glandon1 I...... P..F..M...M..TL..F.....I...... TM.....S.....AF.AM..M....Q...M...... 160 A. glandon2 ...... A...P.....M...... V...... IF.L..YHHHMV...VV.NV..T...M..F...I...V..Y.....I160 P. icarus1 I...... P..F..M...M..TL..F.....M...... TM.....S.....AF.AM..M....Q...M...... 160 P. icarus2 ...... A...P...... V...... IF.L..YHHHMI...AV.NV..T...M..F...I...V..Y.....I160 A. mormo I...... P...... L..T..A...... H..MV..ET..II.G...... V...... 160 C. philodiceV ..M...... TP...... L...A..G...H.IL.....SM...E....I...... VM.Y...... 160 P. rapaeB V...... IV...L...V..M...H.IM...F.KM...... T...V....A.I...V..Y.....I160 P. rapaeV I...... IV...I...T...... H.M...... TMI.N.M...I...F.A...... I...V..Y.....I160 P. glaucus I.M...... I...L.IA.....HPI.F.....I...... M...... I...V...... I160 P. xuthus I.M...... S...... I...L.MA.....HPI.F.....V...... M...... I...V...... I160 M. sexta I.M...... M...... L.IM...... V...... V...... I...V...... I160 B. mori I.M.G...... M...... L.II...... V...... I...V...... I160
V. cardui SSPLDGSLNRVQASLLILFSWLWALPFTFLPAFSVWGRYVPEGFLTTCSFDYMTDDQDTKIFVMCIFVWSYVIPMTFICC240 E. chalcedona ...... KI...F...... L.E.....M.T....I...L..LM...F240 N. antiopa ...... K....F...... M..I.M.I...... V...F240 L. arthemis ...... A...A.T.F...... I....K...... LTTLPE.....V....M...... V..L...F240 L. archippus ...... A...A.T.F...... K...... LTTL.E....SV....M.I...... L...F240 D. plexippus ...... R..HT..A.....T.V..T..S...... K...... FL.E.E..RV...... CC..Y240 D. gilippus ...... R...T..A.....T.V..T..S...... K...... FL.E.E..RV....M...... CC..Y240 H. erato ...... T...... I.....I...F...... F.E.....V....M.T...C...LL?.Y240 H. melpomene ...... S...... T...... IM....I...F...... F.E.....V....M.A...C...LLL.Y240 A. vanillae ...... T.T...... T....V...... F...... F.E.....V..L.M.A...... L...Y240 S. mormonia ...... T...... T.M...... L...... F...... I.E....SL....M.I...... L.M.Y240 C. tullia ...... T.M..Y....LT.I...... QI..K...... F....T..SV....M.M...... M.M.F240 B. anynana ...... T...... M..T...... I..KF...... F.E.T...L....M.I...A...LSM.F240 L. rubidus1 .C....RITK...LI..A...V.SM...... K....FM...... L...P...L...... C...M...I.L.F240 L. rubidus2 .C.....VTKT..L.....T.V...... I....KL.SKF...... L.E.S...V...SCC....F..VIIL.Y240 L. helloides1 .C....RITK...LI..A...V.S...... K....FM...... L..EP...L...... C...M...I.L.F240 L. helloides2 .C.....VTKT..L.....T.V...... I....KL.SKF...... L.E.S...... LSCC....F..VIIL.Y240 L. heteronea1 .C....RITK...LI..A...V.SM...... K....FM...... L...... L...... C...M...I.L.F240 L. heteronea2 .C.....VTKT..L.....T.V...... I.....L.SKF...... L.E.S...V..LSCC....F..VIIL.Y240 L. nivalis1 .C....RITK...LI..A...V.S...... K..S.FM...... L..EP...L...... C...L...I.L.F240 L. nivalis2 .C....RVTKT..L.....T.V...... I....KL.SKF...... L.E.S...... LSCC....F..VIIL.Y240
80 S. behrii1 .C.....ITK...LI.MA...V.S....L...... FM...... L..HP...L...... C....M..I.L.F240 S. behrii2 .C.....VTKT..L..M..T.V...... V....QL.SKF...... L...N...... LSCC....F..I.IL.Y240 A. glandon1 ...... RITN...MI..V.T.I.T...... I...FM...... L.E.T...V...... L...AT..M.L.F240 A. glandon2 .C....RVTKS..LA.MMMT.M.S....M....R...KF...... L.E.SA.RM..LVCCM.D.FL.IFML.Y240 P. icarus1 ...... RITN...MI..V.T.I.T...... F.R....FM...... L.E.T...V...... L....T....L.F240 P. icarus2 .C....RVTKS..LA.MVMT.V.S....M...IQ...KF...... L.E.YA.RM..LVCCM.N.FL.VFML.Y240 A. mormo .C.....M.K...I..CV.T....M...... LD....F...... L...T.I.V...... M....M..L.L.T240 C. philodiceV ...I..RI.SA..T..VM.T..Y.M...VF.LTKT..SF.T...... FLS..VS.--..L.MSI...... L..T240 P. rapaeB .C.I...I.K...II..V.T.F.T....I..LTR...KF...... SF...S..RV..A...... VL..F240 P. rapaeV .C.I..RI.K....I..AVT.M...... I..WTR...Q.TT...... FLSE.....A..A.M.C...... LM.T240 P. glaucus .C.....M.K...... V.T.F.S....M...LK....F...... F...... V..A...... A...AL..Y240 P. xuthus .C.....I.K...... A.T.F.SM...I...LK....F...... F...... V..A...... A...AL..Y240 M. sexta ...... M.T...G...A.T.F...... I.....M..SF...... F.E....EV..A...... CM..AL..Y240 B. mori .C.....I.K...... MA.T.F...... I.....M...... F...... V..A...... C....LM.Y240
V. cardui FYSKLFGAVRLHERMLKEQAKKMNVKSLAANKEDSGKSIEMSIAKVAFTIFFLFLYSWTPYAFVTMTGAFGDSGLLTPVA320 E. chalcedona ...... S...... A...V.I...... VCA...... S...... S.....T320 N. antiopa ...... G...A...V...... C...... 320 L. arthemis ...... G...A...V.I...... VC...... E..SI...LT320 L. archippus ...... G...A...V.I...... VC...... A...... SI...LT320 D. plexippus ...... S...... D.....V.IR...... M....VCA...... A...... SI..... 320 D. gilippus ...... S...... D.A...V.IR...... M....ICA...... A...... SI..... 320 H. erato ...... A...V...... VC...... SI..... 320 H. melpomene ...... A...... VC...... A.V...... SI....T320 A. vanillae ...... A...V...... VC...... 320 S. mormonia ...... A...... VC...... A...... 320 C. tullia ...... S...... G...A...V.I...... VC...... A.M...... S...... 320 B. anynana ...... S...... G...A...V.I...... VC...... A.I...... SM..... 320 L. rubidus1 ...... S...M..K..R...... S..D.A...V.I...... VC...... NI..... 320 L. rubidus2 Y.FQ...... T..K..R...... S....G...V.I...... ICA...... LV...... SI.S... 320 L. helloides1 ...... S...M..K..R...... S..D.A...V.I...... VC...... NI..... 320 L. helloides2 Y.FQ...... T..K..R...... S....G...V.I.M...... ICA...... LV...... SI.S... 320 L. heteronea1 ...... S...M..K..R...... S..D.A.T.V.I...... VC...... NI..... 320 L. heteronea2 Y.FQP.....T..K..R...... S....G...V.I.M...... ICA...... LV...... SI.S... 320 L. nivalis1 ...... S...M..K..R...... S..D.A...V.I...... VC...... NI..... 320 L. nivalis2 Y.FQ...... T..K..R...... S....G...V.I.M...... ICA...... LV...... SI.S... 320 S. behrii1 ...... S...M..K..R...... S..D.A...V.I...... VC...... NM.S... 320 S. behrii2 Y.FQ...... N..K..R...... SS....G...V.I...... ICA...... LV...... SI..... 320 A. glandon1 ...... N...A..S..R...... S..DEA.T.V.IR...... M....VC...... K.I..... 320 A. glandon2 Y..R...... T..K..R...... -S..D.G.A.V..RM...... VCA...... LV...... SI..... 320 P. icarus1 ...... N...A..S..R...... S..DEA.T.V.IR...... M....VC...... K.I..... 320 P. icarus2 Y.AL...... T..K..R...... -S..D.G.A.V..RM...... M.VCA...... LV...... SI..... 320 A. mormo ...... ?...... N...... S....A...V.I...... VC...... N...... SI..... 320 C. philodiceV ..L...... H..K...... S....A...V.I...... IC.....GI.A.I...... S.....V320 P. rapaeB ...... S...... K..R...... S..D.A...V.I...... VCA.....V...I.T....N....HV320 P. rapaeV ...... V...H..S...... S....A...V.I.M...... IC.....GV...I...... S.....V320 P. glaucus ...Q.....S...K..Q...... S....AS..V...... M.VCG.....I...... Y...S..S... 320 P. xuthus ...Q...... S..Q...... S....AS..V.I...... M.VCG...... Y...S...... 320
81 M. sexta ...Q...... Q...... S....NSR.V.I.M...... ICA...... T....M. 320 B. mori ...Q...... Q...... ASS.V.I.M...... M....VCA...... N....M. 320
V. cardui TMVPAVCAKIVSCIDPWVYAINHPSYSAELQKSLPWMGVREADPDSVSSA-SGATAQTQNPTAE- 385 E. chalcedona ...... K...... RV...... NS.T..TS-...... A 385 N. antiopa ...... -...... S....A 385 L. arthemis ...... V....R...... T-...... HAA..A 385 L. archippus ...... V....R...... T-...... HAA..- 385 D. plexippus ..M...... V...L...... RV...... NT.NV-...... -NP..A 385 D. gilippus ..M...... V...L...... RV...... NT.NV-...... -NP..A 385 H. erato ..M...... R...... TS-...... A 385 H. melpomene ..M...... R...... T..TS-...... A 385 A. vanillae ...... R...... TS-.A...... HAN..A 385 S. mormonia ...... V...... RV...... T..TS-...... AA..A 385 C. tullia ...... M...... R.....RV...... P...... N.-....TH..H.S.DA 385 B. anynana ...... M...... R...E.RV...... P...... TS-...... -NA..A 385 L. rubidus1 ...... M...... E.RVS.L..K.PN..T..TS-.T..S.---AP.DA 385 L. rubidus2 ...... T...M...... T.R...L....S...TA..S-.T..S...HH...A 385 L. helloides1 ...... M...... E.RVS.L..K.PN..T..TS-.T..S.---AP..A 385 L. helloides2 ...... T...M...... T.R...L....S...TA..S-.T..S...HH...A 385 L. heteronea1 ...... M...... E.RVS.L..K.PN..T..TS-.T..S.---AP..A 385 L. heteronea2 ...... T...M...... T.R...L....S...TA..S-.T..S...HQ...A 385 L. nivalis1 ...... M...... E.RVS.L..K.PN..T..TS-.T..S.---AP..A 385 L. nivalis2 ...... T...M...... T.R...L....S...TA..S-.T..S...HH...A 385 S. behrii1 ...... L...... E.RVS.L..K.PN..T..TS-.T..S.....Q..A 385 S. behrii2 ..M...... T...M...... T.R...L....Q...TA..S-.T...... HQ...A 385 A. glandon1 ...... A...... E.RVS.L..K.PS..T..QS-.T..S.---VPQ.A 385 A. glandon2 ...... T...... K.....T.R...L....K...TA..S-.T..S...H....A 385 P. icarus1 ...... A...... M...... E.RVS.L..K.PS..T..QS-.T..S.---VPQ.A 385 P. icarus2 ...... T...... K.....T.R...L....K...TA..S-.T..S..HH....A 385 A. mormo ...... E.RI...... PNH.T..TS-.T..S...HAAT.A 385 C. philodiceV ..I...FC.A...L...... F.V..E.RV.....S.P...AQ..T-GS.VTN----S..A 385 P. rapaeB ..I...F..S...... E...... I..PSAETQ.TN-ASTAT.S--AS.DA 385 P. rapaeV ..I...FC.A...... FR...ESRV...... P...AT.TN-ASTSTT----P.DA 385 P. glaucus ..I....C.....M...... R...... R...L....Q...... TSN.VT.T.SHT.N..T 385 P. xuthus ..I....C.....M...... R...L....Q...T..NSN.VT.T.SHT....A 385 M. sexta ..I....C.V...M...... R...... Q...A..TTT.V...GF.P.A..A 385 B. mori ...... C.V...M...... T.R...L....S...A..TTT.VG...S.-A...A 385
82 Figure 1.1. Alignment of 35 lepidopteran LWRh complete coding sequences
V. cardui MAITSLD--PGAAALQAWGGQMAAFG-SNETVVDKVLPDMLHLVDPHWYQFPPMNPLWHGLLGFVIGILGFISITGNGMV 80 E. chalcedona ...... LG...... Y.-.....?..AP.E....I...... ?...M.Y.....FM.?...?.V...... 80 N. antiopa ...... --...... -...... E...... 80 L. arthemis ...... PG...... Y.-...... L...V...V..A..... 80 L. archippus ...... PG...... Y.-...... D...... L.M.V...?..?..... 80 D. plexippus .....M.PG...... -...... I...... M...... M.V...M...... 80 D. gilippus .....M.PG...T...... E.....-...... I...... M...... M.V.S...V...... 80 H. erato ...... PG...... ?...... -...... I....H...... V.....V...... 80 H. melpomene ...... PG...... -...... I.A..H...... V.....V...... 80 A. vanillae ...... AG...... V...-...... I...... V.....V...... 80 S. mormonia ...... PG...... -...... I...... V.....V...... 80 C. tullia ....NM.PG..V....G.E..AM.Y.-..M..L..AT...... M..Y...... Y...... MVV.AV...C..... 80 B. anynana .....M.PG..I...... HA.?Y.-...... V...V...... 80 N. ridingsii .....M.PG..V..M...... AMP..-...?...... Y...... S.....M.V...... A..... 80 O. chryxus .....M.PG..V..M...... AM.Y.-...... I...... Y...... L.M.V.....FA..... 80 L. rubidus .S.....PA..V..M....P.AM.Y.-G....I.....E...KI.A...... A...SMICI.AT...... 80 L. helloides .S.....AA..V..M....P.AM.Y.-G....I.....E...KI.A...... Y...A..MS.ICV.AT...... 80 L. heteronea .S.....PA..V..M....P.AM.Y.-G....I.....E...KI...... A...S.ICL.AT...... 80 L. nivalis .S.....PA..V..M.G..PRAM.Y.-G....I.....E...KI.A...... A...STICL.AS...... 80 S. behrii .T.A...PA..V..M...... AL...-...... E...KI...... I.A.I.SVV.I.AT...A.. 80 A. glandon .T.MN..PA..V....S..P.AS.LF-N...... E...SI...... I.A.ITSVILM.AS...... 80 P. icarus .T.MN..PA..V....S..PRAS.LF-N...G.....SE...SI....D...... AI.A.ITSVILM.AS...... 80 A. mormo1 .T..N..PG.RF.PIE.-----L...-...... E....I.....E...... FMACITI.AFA..... 80 A. mormo2 ....N..PG..V....S..P.TM..S-N.M...... E...KI.K...... D..Y..V.?.MAWICMTAFS..A.. 80 C. philodice .....M.PA..V..M.....HAE.YS-..Q...... E....I.A...... Y.....T.S..A...V...... 80 P. rapae ....N..PA..V..M.SF.IHAE...-..Q..M.....E.M..I...... L.....A....T.SV.A...M...... 80 P. glaucus1 ..LD...PAAT--FGH..A.K.E.Y.-..Q..I.Q...E.M..I...... AV...M.LS..... 80 P. glaucus2 ...AN..PGL..-.AEV....A...S-..Q...... S...M..I...... M...... T..V...M...... 80 P. glaucus3 ..LDY.NTGAA--KMGT.N...S.Y.-A.Q...... E....I...... Y.....T.AC.AIT.....A.. 80 P. xuthus1 ..MD...PGAA--SAP..A.KIE.Y.-..H..I.Q...E....I...... AV...M.LS..... 80 P. xuthus2 ...AN.EPGM.--.SE.....A....-..Q...... T...M..I...... M...... T..V...M...... 80 P. xuthus3 ..LNY.NTGAA--KMDT.N...S.Y.-A.Q...... E....I...... Y.....T.TC.AIT.....A.. 80 M. sexta .-----.PG..L...... AAKSP.Y.AA.Q...... P...M.MI...... A....T..V...V.MS..... 80 B. mori1 .-SM.M.AG..F....S.SS.V....N..Q....S.S.E....I.AY...... A....T..V.....MM..... 80 B. mori2 .--I...PG..M...... V..Y.AA.Q...... P.....M...... A....T..V...M..S..... 80
V. cardui IYIFTTTKSLKTPSNILVVNLAFSDFLMMCVMSPPMVVNCYTETWVFGPLACQLYACAGSLFGCASIWTMTMIAFDRYNV160 E. chalcedona V...... F...... ?LLGL.A...... Y...... V...... 160 N. antiopa V...... T...... N...... V...... 160 L. arthemis V...... T...... C..LF.A...... Y...... 160 L. archippus V...... T...... C..L...... MS..Y...?...?G...... T...... 160 D. plexippus V...... T...... C..AI.A...LI...N...... G...... 160 D. gilippus V...... AL.A...MI...N...... F...... V...... 160 H. erato V...... T...... FM.A....M...N...... Y..V...... 160 H. melpomene V...... FM.A....M...N...... Y..V...... 160
83 A. vanillae V...... FM.A....M...H...... Y..V...... 160 S. mormonia V...... T...... AM.A...... Y...... Y..V...... 160 C. tullia V...... T...... AL.A...... Y...... L...... 160 B. anynana V...... M...... L...... N...... T...... M...... 160 N. ridingsii V...... T...... V.?...... T...... Y...... ?L..V...... 160 O. chryxus V....?...... T....A.....FY...... 160 L. rubidus ....S...... L...... L....IITT....V...T.Y...M...... DI...C...... V...... 160 L. helloides ....S...... L...... L....IITT....A...T.Y...M...... DI...C...... V...... 160 L. heteronea ....S...... L...... L....IITT....V...T.Y...M...... DI...C...... V...... 160 L. nivalis ....S...... L...... L....IITT....L...T.Y...M...... DT...C...... V...... 160 S. behrii ?...C...T...... L...... L....IITT....V...T.Y...M...... DI...C...... V...... 160 A. glandon ...... T...... LFI....L....IITT....V...T.Y...I...... DI...C...... V...S...... 160 P. icarus ...... T...... LFI....L....II?T....V...T.Y...I...... DI...C...... V...S...... 160 A. mormo1 L...... L..M...... C.IV..G...L.S..Y...... E...... G...S...... 160 A. mormo2 L...NS....S....LF...... A.I..LA..VL..S.YQ...... F.DI...C...... V...... 160 C. philodice ...... L...... AM.A..LCI.S.YQ...... V...F...F...... V...... A...... 160 P. rapae V...... L...... AM.A..L...S.N...... T...F...F...... V...... A...... 160 P. glaucus1 ..M.....T...... L..L...V...... TC.A..L...S.H...... A...A...... TI...... 160 P. glaucus2 V....S...... L...... LC.A...... Y...... E...... SM...... 160 P. glaucus3 ...... N...... L...... V...... AC.A..LII.S.N...... F.AI...G...Y.TV...... A...... 160 P. xuthus1 ...... T...... L..L...V...... TC.A..L...S.H...... A...A...... TI...... M...... 160 P. xuthus2 V....S...... L...... LC.A...LI...Y...... E...... SM...... 160 P. xuthus3 ...... N...... L...... V...... AC.A..LII.S.N...... F.AI...G...Y.TV...... A...... 160 M. sexta ....MS...... L...... A...A...... Y....W..F..E...... M...... 160 B. mori1 ....M...N...... L...... A...A..I...N...... F..E..G...... 160 B. mori2 ....MS...... L...... A...A...... N...... F..E...... 160
V. cardui IVKGIAAKPLTINGAMLRVLGIWVFSLAWTVAPLFGWGRYVPEGNMTACGTDYLDKSWFNRSYILIYSIFCYFSPLFLII240 E. chalcedona ...... V...L...FA..M...L.....ML...... L...... F..G.L...... L..V....L...... 240 N. antiopa ...... M...... M...... M...... V....M...... 240 L. arthemis ...... M.....L...... A...S..I...... F..T.G...... F...A..YM...... 240 L. archippus ...... M.....L...... A.A.?..I...... F..T.V...... V...A..YT...... 240 D. plexippus ....L....M.....L...... A...... M...... F...FA.....V...V....A...... 240 D. gilippus ....M....M.....L...... A...... L...... F...VA.IT..VT...A...A...... 240 H. erato ...... M.....L...F...A...... I...... F.Q.FS...... L...A..YA...... 240 H. melpomene ...... M.....L...FF..A...... F.Q.IS.MT...L...A..YA...... 240 A. vanillae ...... M.....L...FF..A...G..L...... F...LS..T...L...A..YA...... 240 S. mormonia ...... M.....L.S.F...L...... F....S..T..ML..VA..YL....M. 240 C. tullia ...... L...F...M...I.....M....S...... VH.....V..V...YA...... 240 B. anynana ...... G...... L...FA..L...... I...... S...... F....Q...... F...... Y...L..C240 N. ridingsii ...... M.....L...... L...G.....MM...S...... L...... V..L...Y...L... 240 O. chryxus ...... M.....L...... L...... M....S...... L...... V..V...Y...L... 240 L. rubidus ...... L..I....L...... IT...... K.A.....CV...... VH....IL..VA...A?.L... 240 L. helloides ...... L..I....L...... IT...... K.A.....CV...... VH....IL..VA...A...... 240 L. heteronea ...... L..I....L...... IT...... K.A.....CV...... VH....IL..VA...A...... 240 L. nivalis ...... L.QI....L...... IT...... K.A.....CV...... VH....IL..VA...A...... 240 S. behrii ...... M.N...L..I....L...... LT...... K.A.....CV...... VH....IL...A...A...... 240 A. glandon ...... NG..L..I..V.L...... T...... K.A.....CV...... VH.?..IL..FA...M...... 240
84 P. icarus ...... NG..L..I....L...... IT...... K.A.....CV...... VH....IL..FAY..M...... 240 A. mormo1 ...... M.....L.SIF.M.L...... CS...... LS.....V....V..A..?... 240 A. mormo2 ....M...... L..I....L.?....L..M....K.A...... NS..QALD?V?..WL..VA...L..G..C240 C. philodice ...... L.QIFAV.A...... L..I...SS...... S.DLLSQI..IT...A...L..A..V240 P. rapae ...... M...S.L.SI..V.L...... L..I...S...... S.D.AS....IL.A.A...L.....V240 P. glaucus1 ...... M.N...L..I.A...S...... M...NS...... N.D..S....VA.A.....T..A... 240 P. glaucus2 ...... M.....L..I....L...... I..I...NS...... N...LS.....V....V.YM..L... 240 P. glaucus3 ...... MS....L..I.A..LS...... I...NS...... V...... S.DMLS....IA.AV....L..G... 240 P. xuthus1 ...... M.N...L..I.A...S...... M...NS...... N.D..S....VA.A.....T..A... 240 P. xuthus2 ...... M.....L..I....L...... I..ML..NS...... S...LS.....V....V.YT..L... 240 P. xuthus3 ...... MS....L..I.A..LS...... I...NS...... V...... S.D.LS....IA.AV....L..G..V240 M. sexta ....M....M.S...L..M...... LL.F...NS...... S...VS...... V.V..L..L... 240 B. mori1 ...... M.N...L..I....A...... F...NS...... T.D..S....VV..V.V..A..L..V240 B. mori2 ...... M.N...L..I....A...... L..F...NS...... S.D..S...... V.V..A..L..M240
V. cardui YSYFFIVQAVAAHEKAMSEQAKKMNVASLS--SSDAANTSAECKLAKVALMTISLWFMAWTPYLVINYAGIFETATITPL320 E. chalcedona ...... ?.....S...... --...... F....D.I.L... 320 N. antiopa ...... --...... 320 L. arthemis ...... --...Q...... M...M..S.. 320 L. archippus ...... I...... --...QG...... M..S.. 320 D. plexippus ...... I...... --...Q...... FC...DG.P.S.. 320 D. gilippus ...... I...... --...Q...... FC...DG.P.S.. 320 H. erato ....?...... --...... K.M..S.I320 H. melpomene ...... --...Q...... K.M..S.I320 A. vanillae ...... --...... D.M..S.I320 S. mormonia ...... --...Q...... M..S.. 320 C. tullia ...T...... ?...... QQ.DADK...... M.MS.I320 B. anynana ...... I...... --..EN...... M..S.. 320 N. ridingsii ...... M...... --...Q...... S.....MQ.S.. 320 O. chryxus ...... --...Q...... S.....MQ.S.. 320 L. rubidus ...W..I...S...... R--...... I..W....K.SL.S.. 320 L. helloides ...W..I...S...... R--...... I..W....K.SL.S.. 320 L. heteronea ...W..I...S...... R--...... I..W....K.SL.S.. 320 L. nivalis ...W..I...S...... R--...... I..W....K.SL.S.. 320 S. behrii ...W..I...S...... R--...G.DK...... I..W....K.SM.S.. 320 A. glandon ...W..I...S...... R--...Q...... I..F....K.EL.S.. 320 P. icarus ...W..I...S...... R--...Q...... I..F....K.ER.S.. 320 A. mormo1 ...... I...S...... --...QS...... FT.V....K.... 320 A. mormo2 ...... L...S...... R...... R--...Q...... I.....T...... I..MS..-HG.GL... 320 C. philodice ...... --..EQS...... ?..F..V....P.S.. 320 P. rapae ...W...... S...... --..EQ...... F..V...SP.S.. 320 P. glaucus1 ...... I...... S...... --..E...... M...... FT...... S.. 320 P. glaucus2 ...... S...... R--..E...... T.V....A.S.. 320 P. glaucus3 ...W..I...... --...... F..V....P.S.V320 P. xuthus1 ...... I...... --..E...... FT...... S.. 320 P. xuthus2 ...... R--..E...... T.V....P.S.. 320 P. xuthus3 ...W..I...... --...... F..V....P.S.V320 M. sexta ...... --..E...... T.V..S.P.S.. 320
85 B. mori1 ...YY.....S...... --..E.....T...... T.ML.S.P.S.. 320 B. mori2 ...... --..E...... M..T.V..S.P.S.. 320
V. cardui ATIWGSVFAKANAVYNPIVYGISHPKYRAALYASFPALACQPSP--EDNASVAS-AATA-TEEKPSA 387 E. chalcedona ...... --...... -....-...... 387 N. antiopa ...... --...... -....-...... 387 L. arthemis V...... A.E.--Q..T....-S...-...... 387 L. archippus V...... A.E.--Q..T....-S...-.?..... 387 D. plexippus ...... S..A.S--D..V.A..-....C...... 387 D. gilippus ...... A--D..V.A..-....C...... 387 H. erato V...... G....SA.--...G....-....-...?... 387 H. melpomene V...... S..TA.--..TG....-....-...... 387 A. vanillae V...... G....SA.--...G....-....-...... 387 S. mormonia V...... G.....AA--.E.G....-....-...... 387 C. tullia V....A...... R...... GDS..T.T..-...H-...... 387 B. anynana V...... R..G....AAA--...G....-....-...... 387 N. ridingsii V...... R...... A--..T.....-....-....A.. 387 O. chryxus V.M...... C...... R...... KA--D.T.....-....-...... 387 L. rubidus V.....I.....SI?...... ?.....S...... --DESG....-TG..VQ...... 387 L. helloides V.....I.....SI...... ?...S...... --DETG....-?G..IQ...... 387 L. heteronea V.....I.....SI...... S...... S--DETG....-TG..IQ...... 387 L. nivalis V.....I.....SL...... S...... S--DETG....-TG..IQ...... 387 S. behrii V.....I.....SI...... R...... A--DESG....-S...VQ...... 387 A. glandon ...... I...... M...... R...... A--DESG....-SG..VQ...... 387 P. icarus ...... I...... DM...... R...... A--DESG....-SG..VQ...... 387 A. mormo1 F...... TI...... S....?..--DESG....S.T..VQ...Q.. 387 A. mormo2 S.....L....STI...... K...... ES--DESG.I..T.?..---...A. 387 C. philodice S...... Q...... S-.ETG....-....C...... 387 P. rapae S...... Q...... A-.ETG....-....C...... 387 P. glaucus1 G...... S....Q...S.....AA--D..T.Q..-GK.TVC...... 387 P. glaucus2 ...... QK..S...... --.ETG....-G..TAC...... 387 P. glaucus3 S...... S....QR..S...... --DESG....-GN..VC....P. 387 P. xuthus1 G...... S....Q...S.....AA--D..T.QV.-GK..VC...... 387 P. xuthus2 ...... QK..S...... A--.ETG....-G..TAC...... 387 P. xuthus3 S...... S....QR..S...... --DESG....-GN..VC...AP. 387 M. sexta ...... L...... Q.....K..S.Q..SA.--..AG....-GT..VS....A. 387 B. mori1 ...... L...... Q....K...V.Q.HSTTT-DEAS....-G-.TVM....T- 387 B. mori2 ...... L...... Q...... S.Q..SA.P-D.GG....-G...VS....A. 387
86
87 Figure 1.1. Alignment of 29 lepidopteran EF1α partial coding sequences
V. cardui IDIALWKFETAKYYVTIIDAPGHRDFIKNMITGTSQADCAVLIVAAGTGEFEAGISKNGQTREHALLAFTLGVKQLIVGV 80 E. chalcedona ...... 80 N. antiopa ...... 80 L. arthemis ...... 80 L. archippus ...... 80 D. plexippus ...... F...... 80 D. gilippus ...... S.F...... 80 H. erato ...... 80 H. melpomene ...... 80 A. vanillae ...... 80 S. mormonia ...... N...... 80 C. tullia ...... 80 B. anynana ...... 80 N. ridingsii ...... 80 O. chryxus ------...... 80 L. rubidus ...... 80 L. helloides ...... 80 L. heteronea ...... 80 L. nivalis ...... R...... 80 S. behrii ...... 80 A. glandon ...... 80 P. icarus ...... 80 A. mormo ...... 80 C. philodice ...... S...... 80 P. rapae ...... G...... 80 P. glaucus ...... S...... 80 P. xuthus ...... S...... 80 M. sexta ...... S...... 80 B. mori ...... S...... 80
V. cardui NKMDSTEPPYNEGRFEEIKKEVSSYIKKIGYNPAAVAFVPISGWHGDNMLEASTKMPWFKGWQVERKEGKAEGKCLIEAL 160 E. chalcedona ...... S.S...... D...... 160 N. antiopa ...... 160 L. arthemis ...... S.S...... A...... D...... 160 L. archippus ...... S.S...... A...... D...... 160 D. plexippus ...... S.S...... Q...... I...... 160 D. gilippus ...... T.S.S...... Q...... I..R...... 160 H. erato ...... A...... D...... 160 H. melpomene ...... A...... D...... 160
88 A. vanillae ...... S.S...... P...... D...... 160 S. mormonia ...... S.S...... P...... D...... 160 C. tullia ...... S.P...... P...... 160 B. anynana ...... S.S...... D...... 160 N. ridingsii ...... S.P...... P...... 160 O. chryxus ...... S.P...... P...... 160 L. rubidus ...... S.S...... 160 L. helloides ...... S.P...... 160 L. heteronea ...... S.P...... P...... 160 L. nivalis ...... S.P...... 160 S. behrii ...... S...... D...... 160 A. glandon ...... S.S...... 160 P. icarus ...... S.S...... 160 A. mormo ...... S.P...... P...... 160 C. philodice ...... S.S...... P...... L...... 160 P. rapae ...... S...... P...... N...... 160 P. glaucus ...... S.S...... P...... N...... 160 P. xuthus ...... S.S...... P...... N...... 160 M. sexta ...... S.S...... P...... L...... 160 B. mori ...... S.P...... P...... D..S..... 160
V. cardui DAILPPARPTDKALRLPLQDVYKIGGIGTVPVGRVETGVLKPGTIVVFAPANITTEVKSVEMHHEALQEAVPGDNVGFNV 240 E. chalcedona ...... 240 N. antiopa ...... 240 L. arthemis ...... V...... 240 L. archippus ...... V...... 240 D. plexippus ...... 240 D. gilippus ...... 240 H. erato ...... 240 H. melpomene ...... 240 A. vanillae ...... 240 S. mormonia ...... P...... 240 C. tullia ...... P...... S...... 240 B. anynana ...... 240 N. ridingsii ...... S...... 240 O. chryxus ...... I...... S...... 240 L. rubidus ...... I...... 240 L. helloides ...... 240 L. heteronea ...... 240 L. nivalis ...... 240 S. behrii ...... 240 A. glandon ...... S...... 240
89 P. icarus ...... S...... 240 A. mormo ...... P...... V...... 240 C. philodice ...... P...... 240 P. rapae ...... 240 P. glaucus ...... 240 P. xuthus ...... 240 M. sexta ...... P...... 240 B. mori ...... P...... 240
V. cardui KNVSVKELRRGYVAGDSKNNPPKGAADFTAQVIVLNHPGQISNGYTPVLDCHTAHIACKFAEIKEKVDRRSGKSTEDNPK 320 E. chalcedona ...... T.....E... 320 N. antiopa ...... 320 L. arthemis ...... E... 320 L. archippus ...... E... 320 D. plexippus ...... E... 320 D. gilippus ...... E... 320 H. erato ...... S...... L...... 320 H. melpomene ...... 320 A. vanillae ...... E... 320 S. mormonia ...... R...... 320 C. tullia ...... E... 320 B. anynana ...... T...... I 320 N. ridingsii ...... 320 O. chryxus ...... T...... 320 L. rubidus ...... T...... 320 L. helloides ...... E... 320 L. heteronea ..G...... E... 320 L. nivalis ...... E... 320 S. behrii ...... T...... 320 A. glandon ...... R...... E... 320 P. icarus ...... 320 A. mormo ...... F...... R...... E... 320 C. philodice ...... T...... 320 P. rapae ...... S...... T...... 320 P. glaucus ...... R...... T...... 320 P. xuthus ...... T...... 320 M. sexta ...... T...... 320 B. mori ...... T.....V... 320
V. cardui SIKSGDAAIVNLVPSKPLCVEAFQEFPPLG----- 355 E. chalcedona ...... S...... ------355 N. antiopa .....E...... L..----- 355
90 L. arthemis ...... Q...... RFAVR 355 L. archippus ...... Q...... RFAVR 355 D. plexippus ...... RFAVR 355 D. gilippus ...... RFAVR 355 H. erato ...... Q...... RFAVR 355 H. melpomene ...... Q...... RFAVR 355 A. vanillae ...... Q...... RFAVR 355 S. mormonia ...... I.Q...... RFAVR 355 C. tullia ...... RFAV- 355 B. anynana ...... S....------355 N. ridingsii ...... ------355 O. chryxus ...... RFAVR 355 L. rubidus ...... S...... RFAVR 355 L. helloides ...... S...... RFAVR 355 L. heteronea ...... S...... RFAVR 355 L. nivalis ...... S...... RFAVR 355 S. behrii ...... S...... RFAVR 355 A. glandon ...... S...... RFAVR 355 P. icarus ...... S...... RFAVR 355 A. mormo ...... S...... RFAVR 355 C. philodice ...... S...... RFAVR 355 P. rapae ...... S...... RFAVR 355 P. glaucus ...... S...... RFAVR 355 P. xuthus ...... S...... RFAVR 355 M. sexta ...... M...S...... RFAVR 355 B. mori ...... S...... RFAVR 355
91 Figure 1.1. Alignment of 29 lepidopteran COI partial coding sequences
V. cardui RMNNMSFWLLPPSLMLLISSSIVENGAGTGWTVYPPLSSNIAHSGSSVDLAIFSLHLAGISSILGAINFITTIINMRVNS 80 E. chalcedona ...... N 80 N. antiopa ...... I...... A...... I.N 80 L. arthemis ------A...... G 80 L. archippus ------A...... I.G 80 D. plexippus ...... I...... L...I.N 80 D. gilippus ...... L...I.N 80 H. erato .L...L...... I...... G...... I.N 80 H. melpomene ...... I...... G...... I.N 80 A. vanillae ...... I...... G...... I.N 80 S. mormonia ...... I...... G...... I.K 80 C. tullia ...... I...... G...... S...... G 80 B. anynana ...... V.....N...... G.A....T...... S...... TIG 80 N. ridingsii ...... I.N 80 O. chryxus ...... V...... I.N 80 L. rubidus ...... L...... P...... I.N 80 L. helloides ...... L...... I.N 80 L. heteronea ...... F...... I.N 80 L. nivalis ...... L...... I.N 80 S. behrii ...... N 80 A. glandon ...... V...... G...... N 80 P. icarus --...G...... I...... G...... N 80 A. mormo ...... F...... G.A...... N 80 C. philodice ...... T...... I.N 80 P. rapae ...... T...... ISN 80 P. glaucus ...... T.....M...S...... GS.....V...... I.N 80 P. xuthus ...... T.....M...... GS.....V...... I.N 80 M. sexta ...... I.N 80 B. mori ...... M...... M....L.N 80
V. cardui MSFDQMPLFVWAVGITALLLLLSLPVLAGAITMLLTDRNINTSFFDPAGGGDPISYQHLFWFFG?????????PGFGMIT 160 E. chalcedona ...... L...... H?EVYILIL...... S 160 N. antiopa ...... L...... ????YILIL...... S 160 L. arthemis ...... S..I.S...... L...... L...... HPEVYILIL...... S 160 L. archippus ...... S..I.S...... L...... L...... HPEVYILIL...... S 160 D. plexippus .T...... L...... L...... HPEVYILIL...... S 160 D. gilippus .L...... I...... V...... L...... L...... HPEVYILIL...... S 160 H. erato .....L...... L...... L...... HPEVYILIL...... S 160 H. melpomene .....L...... L...... L...... HPEVYILIL...... S 160
92 A. vanillae .....L...... L...... L...... HPEVYILIL...... S 160 S. mormonia ...... L...... L...... HPEVYILIL...... S 160 C. tullia ..Y...... L...... L...... HPEVYILIL...... S 160 B. anynana ..YS...... S...... L...... L...... V??????LIL...... S 160 N. ridingsii .TY...... L...... L...... HPEVYILIL...... S 160 O. chryxus .TY...... L...... L...... HPEVYILIL...... S 160 L. rubidus L.....S..I...... L...... L...... HPEVYILIL....I.S 160 L. helloides L.....S..I...... L...... L...... HPEVYILIL....I.S 160 L. heteronea L.....S..I...... L...... L...... HPEVYILIL....I.S 160 L. nivalis L.....S..I...... L...... L...... HPEVYILIL....I.S 160 S. behrii L.....S..I...... L...... L...... HPEVYILIL....I.S 160 A. glandon L.....S..I...... L...... L...... HPEVYILIL....I.S 160 P. icarus L.....S..I...... L...... L...... HPEVYILIL....I.S 160 A. mormo ...... S...... L...... L...... HPEVYILIL....I.S 160 C. philodice ...... L...... L...... HPEVYILIL...... S 160 P. rapae ...... L...... L...... HPEVYILIL...... S 160 P. glaucus ...... L...... L...... HPEVYILIL...... S 160 P. xuthus ...... L...... N..L...... HPEVYILIL...... S 160 M. sexta ...... F...... L...... L...... HPEVYILIL...... S 160 B. mori .....L...... F...... L...... L...... HPEVYILIL...... S 160
V. cardui HIISQESGKKETFGCLGMIYAMMAIGLLGFIVWAHHMFTVGMDIDTRAYFTSATMIIAVPTGIKIFSWLATLHGTQINYS 240 E. chalcedona ...... Y...... 240 N. antiopa ...... 240 L. arthemis .M...... Y...... I...... 240 L. archippus .M...... Y...... I...... 240 D. plexippus ...... S...... I...... 240 D. gilippus ...... S...... M...... 240 H. erato ...... 240 H. melpomene ...... 240 A. vanillae ...... 240 S. mormonia ...... 240 C. tullia ...... L...... N 240 B. anynana ...... Y...... L...... 240 N. ridingsii ...... L...... 240 O. chryxus ...... L...... 240 L. rubidus ...... S...... L...... I...... I...... 240 L. helloides ...... S...... L...... T.I...... 240 L. heteronea ...... S...... L...... I...... 240 L. nivalis ...... S...... L...... I...... 240 S. behrii ...... S...... L...... IY...... 240 A. glandon ...... V...... L...... IY....I.. 240
93 P. icarus ...... A...... L...... IY...... 240 A. mormo ...... S...... I...... SLN 240 C. philodice ...... S...... Y...... 240 P. rapae ...... S...... Y...... 240 P. glaucus ...... T...... 240 P. xuthus ...... T...... F...... 240 M. sexta ...... T...... I...... N 240 B. mori ...... L...... M...... N 240
V. cardui PSMLWSLGFIFLFTVGGLTGVILANSSIDITLHDTYYVVAHFHYVLSMGAVFAILGGFIHWYPLFTGLMMNNYLLKIQFI 320 E. chalcedona ...... V...... M...... 320 N. antiopa ...... V...... 320 L. arthemis ...... V...... F...... A..P...... 320 L. archippus ...... V...... F...... T..P...... 320 D. plexippus ..I...... V...... V...... TL.P...... 320 D. gilippus ..I...... V...... V...... TL.P...... 320 H. erato ...... V...... V...S...... L.P...... 320 H. melpomene ...... V...... V...S.....LL.P...... 320 A. vanillae ...... V...... V...... L.P...... 320 S. mormonia ...... TLSP...... 320 C. tullia ...... A...... V...... IL.P...... 320 B. anynana ...... A...... I...... TL.PF...... 320 N. ridingsii ...... L..A...... F...V...... VL.P...... 320 O. chryxus ...... L..A...... F...V...... L.P...... 320 L. rubidus ...... F....F...... FL.P...... 320 L. helloides ...... F....F...... YL.P...... 320 L. heteronea ...... V...... F....F...S....YL.P...... 320 L. nivalis ...M...... F....F...... YL.P...... 320 S. behrii ...... F...... L..P.Y...... 320 A. glandon ...... F...... CL...... 320 P. icarus ...... F...... YL...... 320 A. mormo .P...... V...... FA...... SL.SFY...... 320 C. philodice ...... V...... I...... L.PFY...... 320 P. rapae ...... V...... I...... SL...Y...... 320 P. glaucus ..I...... V...... V...... M.S...... SL.P...... F 320 P. xuthus ..I...... V...... V...... M.S...... S..P...... F 320 M. sexta ..I...... V...... M...... L..NL.P...... F 320 B. mori .NI...... V...... I....N...... SL.S.M.....F 320
V. cardui SMFIGVN 327 E. chalcedona ...... 327 N. antiopa ...... 327
94 L. arthemis ...L... 327 L. archippus ...L... 327 D. plexippus ...L... 327 D. gilippus ...L... 327 H. erato ...... 327 H. melpomene ...... 327 A. vanillae ...... 327 S. mormonia T...... 327 C. tullia ...... 327 B. anynana ...... 327 N. ridingsii ...... 327 O. chryxus ...... 327 L. rubidus I...... 327 L. helloides I..MA.. 327 L. heteronea I...... 327 L. nivalis I...... 327 S. behrii I...... 327 A. glandon I...... 327 P. icarus I...... 327 A. mormo ...... 327 C. philodice T...... 327 P. rapae V...... 327 P. glaucus T..F... 327 P. xuthus T..F... 327 M. sexta I..L... 327 B. mori T...... 327
95
96 Figure 1.2. Maximum parsimony tree from 5 genes and combined equally weighted 2388 parsimony informative sites. Numbers correspond to un-partitioned decay indexes (Bremer support values) for the data set containing the slower evolving gene copies of duplicated genes. Circled numbers label individual nodes. Members of each sampled subfamily are represented on the right side, wing sizes are not to scale.
97
98 Figure 1.3. Topologies obtained from maximum likelihood (ML) analyses of combined and individual gene data. Numbers above and below branches represent clade support as proportion of 500 bootstrap samples. (a) An identical topology was obtained with all three combined data sets using the slower evolving copies of duplicated genes with numbers corresponding to proportion of bootstrap samples obtained from all opsins / all nuclear / all genes datasets, respectively. Only one bootstrap support is shown for clades in which all three data sets result in the same value. Traditional butterfly families are represented by the following colors: Papilionidae (green), Pieridae (yellow), Nymphalidae (red), Riodinidae (purple) and Lycaenidae (blue). (b-f) ML topologies obtained for individual genes: b) UVRh, c) BRh, d) LWRh, e) EF1α, f) COI. Displayed in the lower left corner of each panel are the shape of the gamma parameter (γ) and proportion of invariant sites (I) used in maximum likelihood analyses. Nodes with bootstrap support under 0.50 are showed as polytomies. The six gene duplication events that generated the duplicated genes included in this study are displayed as black arrows along the topology: the duplication of BRh in Pieridae, the duplication of BRh in Lycaeninae (c), the duplication of Bombyx mori LWRh, the duplication of A. mormo LWRh and the two duplications of LWRh in the genus Papilio (d).
99
100 Figure 1.4. Topologies obtained from Bayesian analyses of combined and individual gene data. Numbers above and below branches represent clade support as posterior probabilities. A. An identical topology was obtained using the slower evolving copies of duplicated genes with numbers corresponding to posterior probabilities obtained from the all opsins / all nuclear / all genes datasets respectively. Only one support value is shown for clades in which all three data sets result in the same value. Traditional butterfly families are represented by the following colors: Papilionidae (green), Pieridae (yellow), Nymphalidae (red), Riodinidae (purple) and Lycaenidae (blue). (b-f) Bayesian topologies obtained for individual genes: b) UVRh, c) BRh, d) LWRh, e) EF-1α, f) COI. S. behrii is marked light green in the BRh gene tree to show how the two gene copies group with different lycaenid subfamilies. Nodes with posterior probabilities below 0.5 are showed as polytomies. Branch lengths are shown as average substitutions per site.
101
Figure 1.5 - Identical topologies obtained from maximum parsimony (MP), maximum likelihood (ML) and Bayesian analyses of combined data sets using faster evolving copies of duplicated genes.
102
3
2.5
2
m 1.5
1
0.5
0 UVRh BRh LWRh EF1a COI
Figure 1.6. Bayesian estimates of rate multiplier parameter (m) by gene partition.
103
Figure 1.7. Divergence time estimates using the Bayesian method. Estimations were performed using the combined five gene data set with the slowest copy of duplicated genes using priors of age of ingroup node = 70 MY, rtrate = 0.002 and brownmean = 0.02. For each estimate 95% confidence intervals are shown.
104
Figure 1.8. Divergence time estimates using the Bayesian method. Estimations were performed using the combined five gene data set with the fastest copy of duplicated genes using priors of age of ingroup node = 70 MY, rtrate = 0.002 and brownmean = 0.02. For each estimate 95% confidence intervals are shown.
105 Table 1.1. Primers used in 5’RACE of opsin cDNAs.
Species UVRh Sequence BRh Sequence LWRh Sequence E. chalcedona ECALUVRD2 AGGATCGATACACGCTACA ECALBRD1 CACAGACGAACAGGAAGAAGATT ECALLWRD1† AGTAGCTAGAGGCGTGAGTG GTCTT G TGAT N. antiopa NANUVRD1 AAAGCTCCTATTAACGACA * * NANLWRD1† GCAGTTTCGAAG TCACG ATACCAGCATAG L. arthemis LARASUVRD1 CAAGAAGCAACGAAGAGG * * N/A N/A AAACAC L. archippus LastUVSalIRD GGCGGGTCGACGCTGATGC LastBlueSalIRD GGCGGGTCGACGCTTCTGCGGCTG N/A N/A TGCTGTTGCAGAAGA CGTGTTGC D. gilippus DPUVRD1 AACGACGAACAATGCGAA DPBRD1 CATTCAACCTTACTACCATCACAA DPLRD3 TTCTGCCAATGCGATGTTCTT ACC TAT H. melpomene HMPUVRD1 ACGCAACAAAGAGGAAGC * * HMPLWRD1 GTTTTGAAGATTCCGGCATA ACAC GTTG A. vanillae AVANUVRD1 ATGGCATGCGTCGTTGTAG AVANBRD1 TCTGGAGTTCCGCCCTGTATCTA AVANLWRD1† GGTCACAATAGGGCTAATCG TT TCAT S. mormonia SMORUVRD1 GACGCAACAAAGAGGAAG SMORBRD1 ATGGATCAATGCAGGAGACGAC SMORLWRD1 TTCGAAGATTCCGGCATAGT CACAC † TGAT C. tullia CTULUVRD1 CTCTTGCCTGTACTTGGGA CTULBRD1 CCTGTCACCAAAAGCTCCTATCAT CTULLWRD1† GATGGCGCTCGTCTATGTGT TGACT C N. ridingsii NRIDUVRD1 TCGCTGAAGTTCTTGTCTGT N/A N/A NRIDLWRD1† TCGAAGATGCCGGAGTAGTT ATTT GA O. chryxus OXUSUVRD1 GGAATCATTGTTACGCCTG N/A N/A OXUSLWRD1† GAAGATGCCGGA GTGT GTAGTTGATGAC L. helloides NLyNBRD1 GGTGTCCAGGCGCAGATGA NLyOBRD1 RTCCTYTATCCGGTTGTCGTTCGT NLyLWRD1 GTCCAAGCACGGTCGGTCAG AGAGG NLyNBRD1 GGTGTCCAGGCGCAGATGAAGAG TT G L. heteronea LyUVRD1 AATGTAGATGTAGAAATGC LyBRD2 GTGACGATGACTGGAGCCTTC LyLWRD1 CATCTGGGGTTCAATCTTCG TTGCA LyNBRD1 GGTGTCCAGGCGCAGATGAAGAG C G L. nivalis LynivUVRD04/06 GAGAGGCCGTGTTATTGTT NLyOBRD1 RTCCTYTATCCGGTTGTCGTTCGT NLyLWRD1 GTCCAAGCACGGTCGGTCAG GAGTG LyNBRD1 TTCACGGATTCGATGTAACTTTAG TT S. behrii SATYUVRD1 CTACAGCCTTACAAGCCAC * * SATYLWRD1 ACGCCATGAACCAGAGTGAG AGC AT A. glandon AGLAUVRD1 AGGTGTCAACAAGTTCTGG * * AGLALWRD1 CTCGGTACTTAGGATGGCTT
106 TCTCC ATGC A. mormo APOUVRD1 GAAGAAACGAACAGGAAA * * APOLW1RD1† AAGTGGAGTGATTTTCGCTG CAAACT APOLW2RD1† TCT AGATGGTTGACAGTGGAGTT AGAC C. philodice COUVRD1 AGCGACAAATAGGAAACA * * COLW1RD1 CGAATACACCAGCGAAGTTG GACAGT AT *See Supplementary Table S1 in Sison-Mangus et al. (2006). Journal of Experimental Biology. 209: 3079-3090. †Primers not previously published along with sequences reported in Frentiu et al. (2007). Molecular Biology and Evolution. 24:2016-2028.
107 Table 1.2. Taxa and genes used in this study. In bold are sequences added by this study. Slower and faster evolving gene copies used in combined analyses are marked by * and & respectively. Parentheses indicate duplicate gene names (e.g. BRh1 or BRh2).
Family Subfamily Species UVRh BRh LWRh EF1α COI Locality/collector Nymphalidae Nymphalinae Vanessa cardui AF414074 AY613987 AF385333 AY248807 AY248782 Nymphalinae Euphydryas EU449014 EU358776 DQ924373 AY788744 AF187752 California: Mono Co. chalcedona Nymphalinae Nymphalis AY918892 AY918893 AY740907 AY218266 AY218246 California: Irvine, Peter Bryant antiopa Limenitinae Limenitis AY918901 AY918902 AY918903 DQ157895 DQ205131 Maryland: Baltimore Co. Austin Platt arthemis astyanax Limenitinae Limenitis EU449016 EU358777 partial DQ208217 DQ205114 Massachusetts: Franklin Co. Fred Gagnon archippus archippus Danainae Danaus AY605546 AY605544 AY605545 DQ157894 EU330440 Florida: Bradford Co., Edith Smith plexippus Danainae Danaus EU449017 EU358779 EU352197 EU326286 EU330435 Florida: Collier Co. Gulf Coast Butterflies gilippus Heliconiinae Heliconius AY918904 AY918906 AY918907 DQ157892 EU330441 Costa Rica Larry Gilbert erato Heliconiinae Heliconius AY918896 AY918897 EU480690 DQ448447 EU449025 Costa Rica Larry Gilbert melpomene Heliconiinae Agraulis EU449018 EU358780 DQ924367 DQ922873 DQ922841 California: Huntington Beach. vanillae Heliconiinae Speyeria EU449019 EU358781 DQ924366 EU326287 EU330436 California: Mono Co. mormonia Satyrinae Coenonympha EU449020 EU358782 DQ924374 AF173399 AF170860 Colorado: Boulder. tullia Satyrinae Bicyclus AF484248 AY918894 AY918895 AY218258 AY218238 anynana Satyrinae Neominois EU449021 DQ924377 DQ339026 DQ338870 Colorado: Montrose Co. Matthew Garhart ridingsii Satyrinae Oeneis chryxus EU449022 DQ924378 EU326283 EU330437 Colorado: Boulder. Lycaenidae Lycaeninae Lycaena AY587904 AY587902(1)* AY587901 DQ157891 EU330442 Colorado: Gunnison Co. Carol Boggs rubidus AY587903(2)&
108 Lycaeninae Lycaena DQ517940 DQ517943(1)* DQ517949 AY954622 AY954562 Colorado: Gunnison Co. helloides DQ517946(2)& Lycaeninae Lycaena DQ517941 DQ517944(1)* DQ517950 EU326289 EU330432 Colorado: Gunnison Co. heteronea DQ517947(2)& Lycaeninae Lycaena nivalis DQ517942 DQ517945(1)* DQ517951 EU326288 EU330433 Colorado: Gunnison Co. DQ517948(2)& Theclinae Satyrium behrii EU449023 DQ402498(1)* EU352198 EU326284 EU330438 California: Mono Co. DQ402499(2)& Polyommatinae Agriades EU449024 DQ402502(1)* EU352199 EU326285 EU330439 California: Mono Co. glandon DQ402503(2)& Polyommatinae Polyommatus EU088115 DQ402500(1)* EU088114 AY496846 EU330434 Germany: Almut Kelber icarus DQ402501(2)& Riodinidae Riodininae Apodemia AY587905 AY587906 AY587907(1) * EU520324 AF170863 California: Hemet John Emmel mormo AY587908(2)& Pieridae Coliadinae Colias AY918898 AY918899 (V) AY918900 DQ157890 EU330443 Colorado: Gunnison Co. Ward Watt & Carol Boggs philodice Pierinae Pieris rapae AB208673 AB208675 (B) AB177984 AY870550 AY954581 AB208674 (V) Papilionidae Papilioninae Papilio glaucus AF077191 AF077192 AF077189(1)& EU136675 AF044013 AF077190(2)* AF098283(3) Papilio xuthus AB028218 AB028217 AB007423(1)& AF044838 AF043999 AB007424(2)* AB007425(3) Sphingidae Manduca sexta L78081 AD001674 L78080 AF234571 U09843 Bombycidae Bombyx mori AADK01002 AADK01014448 AADK01025811 D13338 AF149768 778 AADK01025594
109 Table 1.3. Tajima relative rates tests between duplicated copies of BRh and LWRh genes.
Species L. rubidus L. heteronea L. helloides L. nivalis P. icarus A. glandon S. behrii P. rapae Gene copies (seq A/B) BRh1/2 BRh1/2 BRh1/2 BRh1/2 BRh1/2 BRh1/2 BRh1/2 BRhV/B Outgroup (seq C) A. mormo A. mormo A. mormo A. mormo A. mormo A. mormo A. mormo P. xuthus N sites 1127 1126 994 1129 1115 1117 1139 1125 Unique differences seq A 101 98 80 90 112 113 97 125 Unique differences seq B 106 119 103 115 140 138 113 120 Unique differences seq C 122 125 109 123 110 112 135 115 χ2 (1 d.f.) 0.12 2.03 2.89 3.05 3.11 2.49 1.22 0.10 P 0.728 0.154 0.089 0.081 0.078 0.115 0.270 0.750
Species B. mori A. mormo P. xuthus P. xuthus P. xuthus P. glaucus P. glaucus P. glaucus Gene copies (seq A/B) LWRh1/2 LWRh1/2 LWRh1/2 LWRh1/3 LWRh2/3 LWRh1/2 LWRh1/3 LWRh2/3 D. Outgroup (seq C) M. sexta P. rapae P. rapae P. rapae P. rapae P. rapae P. rapae plexippus N sites 1128 1109 1137 1137 1137 1137 1137 1137 Unique differences seq A 107 97 145 114 97 156 117 90 Unique differences seq B 67 135 88 103 143 88 103 144 Unique differences seq C 114 123 116 141 105 104 145 106 χ2 (1 d.f.) 9.20 6.22 13.94 0.56 8.82 18.95 0.89 12.46 P 0.002 0.0126 0.0002 0.455 0.003 0.00001 0.345 0.0004
110
Table 1.4. Partitioned Bremer support values for nodes shown in Fig. 1. Values represent support as calculated using data sets containing slower/faster evolving gene copies. Only one number is displayed when both analyses rendered the same value.
Node Node name UV B LW EF-1α COI Total 1 Papilio 69 39/43 49/72 12 12 181/208 2 Colias + Pieris 45/26 36/26 19/37 13/7 8 123/104 3 Agriades + Polyommatus 47 60/74 63/58 57 15 242/251 4 L. helloides + L. nivalis 13 11/9 7 0 4 35/33 5 (L. helloides + L. nivalis) 14 4/6 11 7/6 1/2 37/39 L. heteronea 6 ((L. helloides + L. 32 43/31 55/49 12/13 -9/-10 133/115 nivalis) L. heteronea) L. rubidus 7 Lycaeninae + Satyrium 6 3/11 15/20 -2/-1 -11/-12 11/24 8 (Lycaeninae + 17 35/40 37/30 3 6 98/96 Satyrium)( Agriades + Polyommatus) 9 Lycaenidae + Apodemia -20 14/7 20/22 7 -6 15/10 10 Danaus 60/67 63/75 83/62 36/28 14/24 256 11 Neominois + Oeneis 24/23 0 36/34 27/28.5 8/6.5 95/92 12 (N. ridingsii + O. 2 0 12/6 6 -2 18/12 chryxus) C. tullia 13 ((N. ridingsii + O. 22 12/10 8/10 4 7 53 chryxus) C. tullia) Bicyclus 14 Heliconius 22 19 13 12 -5 61 15 Heliconius + Agraulis 28 16 21 3 4 72 16 ((Heliconius) Agraulis) 12 10 12/13 10 -1 43/44 Speyeria 17 Limenitis 48 67/68 46/47 44 29 234/236 18 Limenitis + node 16 9 15/17 10/7 6 3 43/42 19 Vanessa + Nymphalis 20/16 23/27 23/27 14/17 4/-1 84/86 20 (Vanessa + Nymphalis) 9.5 23 13/14 6.5 8 60/61 Euphydryas 21 Node 18 + node 20 12 1/4 7/1 2 -1 21/18 22 Node 21 + node 13 -4 8/11 8/9 4 -1 15/19 23 Node 22 + node 10 2/-4 2/3 4/5 0/4 1/-1 9/7 24 Node 23 + node 9 -20/-4 14/3 20/5 7/4 -6/-1 15/7 25 Node 24 + node 2 4 0/-2 8/5 0 6 18/13 26 Node 25 + node 1 18/13 14/9 35/9 0/6 -2/2 65/39 Total 491.5/47 532/540 635/594 290.5/28 88/95.5 2037/ 9.5 9 1998 Percentage 24 26/27 31/29.7 14/14.5 4.3/4.8 100
111 Table 1.5. Penalized likelihood age estimates in millions of years of nodes shown in Fig. 1. Shown are divergence time estimates calculated using the combined data sets including the slow and fast evolving copies of duplicated genes.
Node Node name Slow Fast 1 Papilio 65.00* 62.28 2 Colias + Pieris 98.85 107.17 3 Agriades + Polyommatus 9.98 12.53 4 L. helloides + L. nivalis 3.96 6.72 5 (L. helloides + L. nivalis) L. heteronea 8.54 12.39 6 ((L. helloides + L. nivalis) L. heteronea) L. rubidus 17.91 23.37 7 Lycaeninae + Satyrium 70.34 66.75 8 (Lycaeninae + Satyrium)( Agriades + Polyommatus) 90.25 87.41 9 Lycaenidae + Apodemia 151.61 138.67 10 Danaus 22.33 24.45 11 Neominois + Oeneis 24.29 27.69 12 (N. ridingsii + O. chryxus) C. tullia 75.43 73.07 13 ((N. ridingsii + O. chryxus) C. tullia) Bicyclus 94.12 87.12 14 Heliconius 16.98 19.31 15 Heliconius + Agraulis 35.12 36.23 16 ((Heliconius) Agraulis) Speyeria 61.68 60.22 17 Limenitis 7.70 7.93 18 Limenitis + node 16 88.30 79.88 19 Vanessa + Nymphalis 34.00* 34.64 20 (Vanessa + Nymphalis) Euphydryas 69.60 68.62 21 Node 18 + node 20 117.02 106.22 22 Node 21 + node 13 141.18 125.76 23 Node 22 + node 10 156.04 146.12 24 Node 23 + node 9 176.26 164.34 25 Node 24 + node 2 197.19 182.80 26 Node 25 + node 1 240.44 210.88
112 Table 1.6. Bayesian age estimates and 95% confidence intervals in millions of years of nodes shown in Fig. 1. Estimates were calculated using combined data sets including slow and fast evolving gene copies. These results were obtained using a prior distribution for the age of the ingroup node of either 70 (±70) or 100 (±100) MY, a rate of evolution of 0.002 substitutions per site per million years and brownmean value of 0.02.
Node Node name Slow (root age 70) Fast (root age 70) Slow (root age 100) Fast (root age 100) 1 Papilio 59.2 (47.2-64.8) 58.0 (45.4-64.8) 59.3 (47.8-64.8) 58.2 (45.8-64.7)
113 2 Colias + Pieris 74.4 (56.4-94.1) 91.7 (70.6-115.0) 74.9 (56.6-94.7) 92.4 (70.7-115.3) 3 Agriades + Polyommatus 12.4 (7.6-20.5) 11.7 (7.7-17.4) 12.6 (7.6-21.8) 11.7 (7.8-17.3) 4 L. helloides + L. nivalis 6.5 (3.8-10.00) 8.5 (5.4-12.8) 6.5 (3.8-10.3) 8.6 (5.5-12.7) 5 (L. helloides + L. nivalis) L. heteronea 12.1 (7.5-18.4) 14.5 (9.5-21.3) 12.2 (7.6-18.8) 14.5 (9.6-21.0) 6 ((L. helloides + L. nivalis) L. heteronea) L. rubidus 20.9 (13.5-31.2) 24.8 (16.9-35.3) 21.2 (13.6-31.8) 24.8 (17.0-35.3) 7 Lycaeninae + Satyrium 59.9 (45.0-77.4) 62.3 (46.8-80.2) 60.5 (45.3-79.0) 62.6 (47.3-80.9) 8 (Lycaeninae + Satyrium)( Agriades + Polyommatus) 73.1 (56.3-93.0) 80.0 (61.0-100.7) 73.7 (56.4-94.2) 80.5 (61.7-101.6) 9 Lycaenidae + Apodemia 108.0 (83.6-135.1) 120.0 (93.6-148.1) 108.7 (83.4-136.2) 121.0 (94.6-149.6) 10 Danaus 23.1 (15.1-34.7) 25.5 (17.6-35.8) 23.2 (15.3-35.6) 25.6 (17.9-35.6) Node 11 Node name Neominois70, 0.02, 0.02+ Oeneis 70, 0.02,26.6 0.002 (17.9 -38.0)70, 0.02, 0.000228.0 (19.770,- 38.6)0.002, 0.02 * 26.8 70,(17.7 0.002,-38.2) 0.002 28.370, 0.002, (19.8 0.0002-39.5) 1 12 (N. ridingsiiPapilio + O. chryxus)58.9 (46.8 -C.64.8) tullia 60.1 (49.864.3-64.8) (49.7 -81.7)61.3 (53.4-70.064.9) (54.1-59.288.2) (47.2 -64.8)64.7 (49.760.1 -(50.182.0)-64.8) 70.661.5 (54.7 (53.8--89.5)64.9) 13 ((N. ridingsii + O. chryxus) C. tullia) Bicyclus 74.5 (58.6-93.3) 81.6 (64.4-101.6) 74.9 (58.4-93.6) 82.4 (64.8-102.9) 14 Heliconius 18.1 (12.3-25.3) 19.1 (13.6-25.9) 18.2 (12.4-25.6) 19.2 (13.5-26.1) 15 Heliconius + Agraulis 32.8 (24.0-43.4) 35.2 (26.2-45.8) 33.0 (24.1-43.6) 35.3 (26.3-45.8) 16 ((Heliconius) Agraulis) Speyeria 52.9 (41.2-66.8) 57.5 (44.8-72.1) 53.1 (41.4-67.1) 57.8 (45.3-72.6) 17 Limenitis 7.9 (4.7-13.6) 8.1 (5.2-12.1) 7.9 (4.7-13.5) 8.1 (5.3-12.1) 18 Limenitis + node 16 68.3 (55.0-84.8) 75.4 (60.1-93.1) 68.6 (54.8-85.0) 75.9 (60.7-94.0) 19 Vanessa + Nymphalis 37.1 (34.1-45.1) 37.4 (34.1-45.5) 37.2 (34.1-45.5) 37.6 (34.1-45.9) 20 (Vanessa + Nymphalis) Euphydryas 62.0 (52.2-75.3) 66.5 (55.7-80.6) 62.3 (52.0-75.4) 66.9 (55.9-81.6) 21 Node 18 + node 20 87.4 (70.0-107.3) 97.5 (78.3-119.1) 87.8 (69.8-108.1) 98.3 (78.9-120.3) 22 Node 21 + node 13 100.2 (78.8-123.8) 113.0 (89.6-138.1) 100.7 (78.5-124.8) 113.9 (90.4-139.5) 23 Node 22 + node 10 110.8 (86.1-138.2) 127.5 (100.1-156.7) 111.4 (85.6-138.5) 128.6 (101.3-158.3) 24 Node 23 + node 9 121.8 (93.3-152.7) 140.3 (109.1-173.2) 122.5 (92.9-153.6) 141.6 (110.3-175.2) 25 Node 24 + node 2 133.9 (101.1-170.0) 153.4 (118.5-190.0) 134.7 (100.6-170.1) 154.8 (119.7-192.0) 26 Node 25 + node 1 153.7 (113.1-197.4) 173.6 (132.5-216.2) 154.7 (112.8-197.9) 175.4 (134.0-218.9)
Table 1.7. Age estimates in millions of years of internal nodes of the topology shown in Fig. 1. Age estimates calculated through MCMC Bayesian analyses in PAML/Multidivtime. These results were obtained using different combinations of prior values, reported at the top of each column, which respectively represent the age of the ingroup node, the rate of evolution and the variation of the rate of evolution over time (brownmean). Shown are divergence time estimates and 95% confidence intervals calculated using all 5 genes including the slower evolving copies of duplicated genes. An asterisk marks the combination of prior values which estimates are shown in figure 5.
114 2 Colias + Pieris 73.1 (54.7-92.9) 77.2 (60.0-95.5) 83.7 (68.4-100.9) 74.4 (56.4-94.1) 77.7 (60.4-96.6) 84.3 (68.8-102.1) 3 Agriades + Polyommatus 12.3 (7.3-20.8) 11.7 (7.6-18.2) 11.5 (8.3-15.7) 12.4 (7.6-20.5) 11.9 (7.8-18.2) 11.5 (8.3-15.6) 4 L. helloides + L. nivalis 6.3 (3.7-9.8) 6.6 (4.1-9.9) 7.0 (4.9-9.8) 6.5 (3.8-10.00) 6.7 (4.1-9.9) 7.1 (4.9-9.9) 5 (L. helloides + L. nivalis) L. heteronea 11.9 (7.4-18.2) 11.9 (7.8-17.4) 11.8 (8.5-16.1) 12.1 (7.5-18.4) 12.0 (7.9-17.6) 11.9 (8.5-16.1) 6 ((L. helloides + L. nivalis) L. heteronea) L. 20.8 (13.3-31.1) 20.0 (13.5-28.8) 18.9 (13.9-25.3) 20.9 (13.5-31.2) 20.2 (13.7-29.3) 19.0 (13.9-25.4) rubidus Node7 NodeLycaeninae name + Satyrium 70,58.9 0.0002, (43.8 -0.0276.6) 70,59.9 0.0002, (46.0 0.002-76.0) 70,60.9 0.0002, (49.1 0.0002-74.4) 100,59.9 0.02, (45.0 0.02-77.4) 100,60.5 0. (46.7 02, 0.002-76.6) 100,61.2 0. (49.302, 0.0002-75.0) 8 (Lycaeninae + Satyrium)( Agriades + 71.6 (54.0-91.4) 74.1 (58.1-92.5) 77.6 (63.7-93.3) 73.1 (56.3-93.0) 75.0 (59.2-93.0) 78.0 (63.7-94.1) 1 Papilio 59.9 (48.4-64.9) 60.7 (51.3-64.9) 61.7 (54.3-64.9) 59.1 (47.1-64.8) 60.2 (49.8-64.8) 61.4 (53.6-64.9) Polyommatus) 2 Colias + Pieris 80.2 (60.3-102.6) 82.2 (64.0-102.7) 87.1 (71.3-105.1) 73.8 (55.4-93.9) 77.5 (60.3-96.5) 84.3 (69.1-101.0) 9 Lycaenidae + Apodemia 105.3 (79.5-132.9) 112.7 (90.5-137.3) 122.8 (103.4-144.3) 108.0 (83.6-135.1) 113.8 (92.0-138.1) 123.7 (104.5-146.0) 3 Agriades + Polyommatus 13.1 (8.1-21.9) 12.4 (8.1-19.3) 11.9 (8.6-16.1) 12.5 (7.4-21.0) 11.9 (7.7-18.5) 11.6 (8.3-15.5) 10 Danaus 23.0 (14.9-35.3) 22.5 (17.7-32.2) 22.3 (16.8-29.1) 23.1 (15.1-34.7) 22.6 (15.7-32.4) 22.4 (17.0-29.1) 4 L. helloides + L. nivalis 7.0 (4.2-10.8) 7.1 (4.5-10.6) 7.4 (5.1-10.2) 6.4 (3.7-10.1) 6.6 (4.2-9.9) 7.1 (4.9-9.9) 11 Neominois + Oeneis 26.3 (17.3-37.8) 26.4 (18.5-36.5) 26.5 (20.0-34.2) 26.6 (17.9-38.0) 26.5 (18.5-36.2) 26.6 (20.1-34.8) 5 (L. helloides + L. nivalis) L. heteronea 13.0 (8.2-19.8) 12.7 (8.3-18.8) 12.3 (8.8-16.9) 12.1 (7.4-18.6) 12.0 (7.8-17.7) 11.9 (8.6-16.2) 12 (N. ridingsii + O. chryxus) C. tullia 63.1 (47.7-80.7) 65.8 (52.2-81.9) 69.7 (57.2-84.3) 64.3 (49.7-81.7) 66.3 (52.2-82.3) 70.1 (57.8-84.6) 6 ((L. helloides + L. nivalis) L. heteronea) L. 22.3 (14.4-34.0) 21.2 (14.3-31.5) 19.7 (14.5-26.3) 21.0 (13.4-31.5) 20.3 (13.7-29.7) 19.0 (14.0-25.2) 13 ((N. ridingsii + O. chryxus) C. tullia) 73.0 (56.3-92.3) 76.5 (61.9-93.8) 81.5 (68.1-97.3) 74.5 (58.6-93.3) 77.2 (62.5-94.5) 82.0 (68.5-97.6) rubidus Bicyclus 7 Lycaeninae + Satyrium 65.0 (48.7-86.1) 64.3 (49.1-82.9) 63.5 (50.9-78.3) 59.5 (44.6-77.1) 60.4 (46.8-77.3) 61.3 (49.5-74.9) 14 Heliconius 17.9 (12.1-25.1) 18.0 (12.7-24.4) 18.7 (14.2-24.0) 18.1 (12.3-25.3) 18.1 (13.0-24.7) 18.7 (14.2-24.2) 8 (Lycaeninae + Satyrium)( Agriades + 79.9 (61.3-102.7) 80.0 (62.7-100.3) 81.0 (66.2-98.3) 72.5 (55.0-92.0) 74.7 (58.8-93.4) 78.2 (64.3-94.0) 15 Heliconius + Agraulis 32.4 (23.4-42.7) 33.0 (24.8-42.5) 34.7 (27.5-42.9) 32.8 (24.0-43.4) 33.2 (25.1-42.9) 34.8 (27.6-43.2) 16 ((Heliconius) Agraulis) Speyeria 52.0 (40.4-65.8) 53.6 (42.7-66.6) 56.4 (46.6-67.6) 52.9 (41.2-66.8) 53.9 (42.9-66.7) 56.7 (46.9-68.3) 17 Limenitis 7.9 (4.6-14.0) 7.6 (4.9-11.8) 7.4 (5.2-10.1) 7.9 (4.7-13.6) 7.6 (4.9-11.6) 7.4 (5.3-10.2) 18 Limenitis + node 16 67.0 (53.3-82.9) 69.8 (57.1-85.1) 74.0 (62.5-87.5) 68.3 (55.0-84.8) 70.2 (57.4-85.4) 74.4 (62.5-88.3) 19 Vanessa + Nymphalis 37.0 (34.1-44.9) 36.7 (34.1-43.6) 36.2 (34.1-41.6) 37.1 (34.1-45.1) 36.7 (34.1-43.7) 36.2 (34.1-41.8) 20 (Vanessa + Nymphalis) Euphydryas 61.1 (50.7-73.8) 63.1 (53.8-75.4) 65.7 (57.3-76.6) 62.0 (52.2-75.3) 63.3 (54.0-75.3) 66.0 (57.4-76.8) 21 Node 18 + node 20 85.5 (67.0-105.7) 90.5 (74.6-109.1) 97.4 (83.8-113.8) 87.4 (70.0-107.3) 91.1 (75.5-109.4) 98.0 (84.0-114.5) 22 Node 21 + node 13 97.6 (74.9-122.4) 104.2 (85.2-125.7) 113.2 (97.0-132.2) 100.2 (78.8-123.8) 105.1 (86.0-127.0) 114.0 (97.5-132.9) 23 Node 22 + node 10 107.8 (81.4-135.8) 115.7 (93.4-140.2) 126.5 (107.8-147.7) 110.8 (86.1-138.2) 116.8 (94.9-141.4) 127.4 (108.6-149.1) 24 Node 23 + node 9 118.3 (88.0-150.3) 127.8 (102.4-155.7) 140.7 (119.7-164.4) 121.8 (93.3-152.7) 129.1 (103.9-157.2) 141.8 (120.4-166.2) 25 Node 24 + node 2 129.7 (94.5-166.8) 140.9 (111.1-173.2) 155.8 (131.9-182.6) 133.9 (101.1-170.0) 142.6 (113.4-174.9) 157.1 (132.9-184.6) 26 Node 25 + node 1 148.2 (104.6-193.9) 161.7 (125.4-200.4) 178.3 (151.0-208.8) 153.7 (113.1-197.4) 163.8 (128.4-203.0) 179.8 (152.0-211.2) Butterflies + M. sexta
Continuation Table 1.7.
115 Polyommatus) 9 Lycaenidae + Apodemia 120.6 (95.9-149.2) 123.1 (100.4-148.8) 128.8 (108.9-151.8) 106.8 (80.9-133.7) 113.4 (91.1-138.4) 123.8 (104.7-145.2) 10 Danaus 23.7 (16.0-35.0) 23.4 (16.5-33.2) 23.0 (17.4-30.2) 23.0 (15.0-34.7) 22.6 (15.7-32.4) 22.4 (16.9-29.1) 11 Neominois + Oeneis 28.6 (19.4-41.2) 28.1 (19.8-39.3) 27.5 (20.7-36.0) 26.5 (17.6-38.0) 26.6 (18.6-36.8) 26.6 (20.1-34.4) 100, 0. 0002, Node12 (N. ridingsiiNode +name O. chryxus) C. tullia 100,70.1 0.002, (54.2 0.02-89.7) * 100,70.7 0.002, (55.9 0.002-89.1) 100,72.6 0.002, (59.4 0.0002-87.9) 100,63.9 0.0002, (48.7 0.02-81.0) 100,66.2 0. 0002, (52.3 0.002-82.6) 70.1 (57.5-84.3) 13 ((N. ridingsii + O. chryxus) C. tullia) 81.5 (64.4-102.5) 82.4 (66.8-102.0) 85.0 (71.0-101.5) 73.9 (57.7-92.8) 77.0 (61.8-94.7) 82.00.0002 (68.8 -97.2) 1 BicyclusPapilio 59.3 (47.8-64.8) 60.2 (59.0-64.8) 61.5 (53.8-64.9) 59.9 (48.5-64.8) 60.7 (51.2-64.9) 61.8 (54.5-64.9) 142 ColiasHeliconius + Pieris 74.919.2 (56.6(13.4--94.7)27.3) 78.019.1 (61.1(13.8--96.5)26.0) 84.719.3 (69.3 (14.7-102.2)-25.1) 81.118.0 (60.4 (12.2-104.0)-25.4) 83.118.1 (64.8 (13.0-103.8)-24.6) 87.318.8 (71.3 (14.3-105.8)-24.3) 153 AgriadesHeliconius + Polyommatus + Agraulis 35.112.6 (25.9 (7.6--21.8)47.2) 35.011.9 (26.7 (7.7--18.6)45.5) 36.011.6 (28.4 (8.4--15.8)44.9) 32.613.3 (23.8 (8.2--22.6)43.3) 33.212.6 (25.1 (8.2--19.9)43.0) 34.812.0 (27.6 (8.7--16.4)43.2) 164 ((Heliconius)L. helloides Agraulis) + L. Speyeria nivalis 56.96.5 (44.5 (3.8--10.3)72.3) 57.26.7 (45.6 (4.2--10.1)71.7) 58.57.1 (48.1 (4.9--70.5)9.9) 52.57.2 (40.9 (4.3--11.2)66.5) 53.97.2 (43.0 (4.5--10.7)67.3) 56.77.4 (46.9 (5.1--10.4)68.2) 175 (L. helloides + L. nivalis) L. heteroneaLimenitis 12.28.2 (7.6(5.1--18.8)13.4) 12.17.9 (7.9(5.1--17.8)12.1) 12.07.7 (8.6(5.4--16.3)10.6) 13.27.9 (8.3(4.7--20.6)13.9) 12.97.6 (8.4(4.9--19.2)11.7) 12.47.4 (8.8(5.3--16.9)10.1) 186 ((L. helloides + L. nivalis)Limenitis L. heteronea) + node L.16 21.274.0 (13.6(59.4--31.8)92.1) 20.474.7 (13.7(61.1--29.9)92.0) 19.176.9 (14.0(64.6--25.3)91.4) 22.767.7 (14.5(53.9--35.5)84.2) 21.670.2 (14.5(57.5--32.2)85.9) 19.774.4 (14.4(62.8--26.5)88.1) 19 Vanessa + Nymphalisrubidus 38.0 (34.1-47.9) 37.4 (34.1-46.0) 36.7 (34.1-43.1) 37.0 (34.1-44.9) 36.7 (34.1-43.8) 36.2 (34.1-41.6) 207 (Vanessa + Nymphalis)Lycaeninae Euphydryas+ Satyrium 60.566.2 (45.3(55.2--79.0)81.4) 60.766.5 (46.6(56.4--77.6)80.9) 61.667.8 (49.8(58.7--75.4)79.3) 65.861.6 (49.2(51.4--87.6)74.7) 65.063.3 (49.8(53.9--84.9)75.9) 63.766.0 (51.4(57.4--78.6)76.5) 21 Node 18 + node 20 95.8 (77.8-117.2) 97.4 (81.4-117.9) 101.3 (86.8-118.2) 86.5 (68.3-106.6) 91.0 (74.9-109.7) 98.0 (84.1-113.7) 22 Node 21 + node 13 110.9 (89.2-136.1) 113.2 (93.7-136.4) 118.2 (101.0-138.0) 99.0 (76.5-123.3) 104.9 (85.3-127.1) 114.0 (97.9-132.5) 23 Node 22 + node 10 123.7 (98.8-151.5) 126.5 (104.3-152.3) 132.5 (113.1-154.9) 109.4 (83.2-137.0) 116.5 (93.7-141.5) 127.4 (108.9-148.3) 24 Node 23 + node 9 137.3 (109.5-169.0) 140.7 (115.6-169.3) 147.9 (126.1-173.2) 120.2 (89.9-151.3) 128.7 (102.7-156.6) 141.8 (120.9-165.6) 25 Node 24 + node 2 153.6 (121.4-190.0) 157.2 (128.4-190.3) 164.9 (139.9-193.8) 132.0 (96.7-168.7) 141.9 (111.7-174.3) 157.0 (133.2-184.2) 26 Node 25 + node 1 180.6 (142.9-226.1) 183.5 (149.8-223.8) 189.5 (161.1-222.5) 151.0 (108.2-196.3) 162.9 (126.3-201.6) 179.7 (152.2-210.1) Butterflies + M. sexta
Continuation Table 1.7
116 8 (Lycaeninae + Satyrium)( Agriades + 73.7 (56.4-94.2) 75.2 (59.5-94.4) 78.4 (64.3-94.9) 80.8 (62.2-104.6) 80.8 (63.5-102.8) 81.3 (66.6-98.4) Polyommatus) 9 Lycaenidae + Apodemia 108.7 (83.4-136.2) 114.5 (92.2-139.7) 124.2 (105.2-146.1) 121.6 (96.3-151.1) 124.2 (101.5-151.9) 129.1 (108.7-152.1) 10 Danaus 23.2 (15.3-35.6) 22.7 (15.9-32.6) 22.5 (17.1-29.3) 24.0 (16.0-36.5) 23.5 (16.3-33.3) 23.1 (17.5-30.4) 11 Neominois + Oeneis 26.8 (17.7-38.2) 26.7 (18.9-36.6) 26.7 (20.0-34.6) 28.8 (19.5-41.7) 28.5 (19.9-39.9) 27.6 (20.9-36.0) 12 (N. ridingsii + O. chryxus) C. tullia 64.7 (49.7-82.0) 66.6 (52.5-82.5) 70.4 (58.0-84.6) 70.7 (54.6-90.7) 71.3 (56.4-90.2) 72.8 (59.9-87.5) 13 ((N. ridingsii + O. chryxus) C. tullia) 74.9 (58.4-93.6) 77.6 (62.4-94.8) 82.3 (68.8-97.9) 82.2 (64.7-103.4) 83.2 (67.1-103.5) 85.1 (71.1-101.5) Bicyclus 14 Heliconius 18.2 (12.4-25.6) 18.2 (12.9-24.8) 18.8 (14.4-24.3) 19.5 (13.5-28.0) 19.3 (13.8-26.5) 19.4 (14.8-25.0) 15 Heliconius + Agraulis 33.0 (24.1-43.6) 33.3 (25.0-43.1) 34.9 (27.9-43.2) 35.5 (26.1-47.9) 35.4 (26.8-46.2) 36.1 (28.6-44.8) Node16 ((Heliconius)Node name Agraulis) Speyeria 70,53.1 0.02, (41.4 0.02-67.1) 70,54.2 0.02, (43.2 0.002-67.3) 70,56.8 0.02, (47.0 0.0002-68.3) 70,57.5 0.002, (44.9 0.02-74.2) * 70,57.6 0.002, (45.8 0.002-72.7) 70,58.7 0.002, (48.1 0.0002-70.9) 171 LimenitisPapilio 57.97.9 (45.3 (4.7-13.5)64.7) 58.47.6 (46.6 (5.0-11.8)64.8) 59.87.5 (49.9 (5.3-10.2)64.8) 58.08.3 (45.4 (5.1-14.1)64.8) 58.47.9 (46.8 (5.2-12.3)64.8) 59.97.7 (49.9 (5.5-10.4)64.8) 182 LimenitisColias + +node Pieris 16 91.068.6 (70.1 (54.8-113.8)-85.0) 92.870.7 (73.1 (57.9-114.9)-86.0) 98.474.6 (79.8 (62.8-119.1)-88.2) 91.774.7 (70.6 (59.8-115.0)-94.0) 93.375.3 (73.2 (61.4-115.7)-93.0) 98.777.1 (80.1 (64.6-120.1)-91.6) 19 Vanessa + Nymphalis 37.2 (34.1-45.5) 36.8 (34.1-43.9) 36.3 (34.1-41.7) 38.3 (34.1-44.5) 37.6 (34.1-46.7) 36.7 (34.1-43.0) 20 (Vanessa + Nymphalis) Euphydryas 62.3 (52.0-75.4) 63.6 (54.3-75.9) 66.2 (57.6-76.9) 66.7 (55.4-83.4) 66.9 (56.5-81.2) 67.9 (58.8-79.6) 21 Node 18 + node 20 87.8 (69.8-108.1) 91.6 (75.5-110.1) 98.3 (84.5-114.3) 96.6 (78.3-118.9) 98.2 (81.4-119.4) 101.6 (87.1-118.7) 22 Node 21 + node 13 100.7 (78.5-124.8) 105.7 (86.1-127.8) 114.4 (97.9-133.2) 111.8 (89.8-137.7) 114.1 (94.3-138.7) 118.5 (101.6-138.3) 23 Node 22 + node 10 111.4 (85.6-138.5) 117.6 (95.0-143.0) 127.8 (109.1-149.1) 124.7 (99.6-153.6) 127.6 (105.1-154.5) 132.9 (113.1-155.0) 24 Node 23 + node 9 122.5 (92.9-153.6) 130.0 (103.7-158.4) 142.3 (121.4-166.2) 138.5 (109.8-170.5) 142.1 (116.2-172.8) 148.3 (126.0-173.7) 25 Node 24 + node 2 134.7 (100.6-170.1) 143.5 (112.9-176.1) 157.8 (134.0-185.4) 155.1 (122.5-192.2) 158.9 (129.8-194.2) 165.4 (139.9-194.6) 26 Node 25 + node 1 154.7 (112.8-197.9) 165.1 (128.9-204.3) 180.6 (153.4-211.6) 182.3 (143.9-229.0) 185.7 (150.8-228.1) 190.2 (161.3-223.2) Butterflies + M. sexta
Table 1.8. Age estimates in millions of years of internal nodes of the topology shown in Fig. 1. Age estimates calculated through MCMC Bayesian analyses in PAML/Multidivtime. These results were obtained using different combinations of prior values, reported at the top of each column, which respectively represent the age of the ingroup node, the rate of evolution and the variation of the rate of evolution over time (brownmean). Shown are divergence time estimates and 95% confidence intervals calculated using all 5 genes including the faster evolving copies of duplicated genes. An asterisk marks the combination of prior values which estimates are shown in supplementary figure 4.
117 3 Agriades + Polyommatus 11.7 (7.7-17.3) 11.7 (7.8-17.0) 12.1 (8.7-16.5) 11.7 (7.7-17.4) 11.8 (8.0-17.3) 12.2 (8.7-16.6) 4 L. helloides + L. nivalis 8.5 (5.4-12.7) 8.5 (5.5-12.5) 8.9 (6.2-12.3) 8.5 (5.4-12.8) 8.7 (5.6-12.7) 8.9 (6.1-12.4) 5 (L. helloides + L. nivalis) L. heteronea 14.4 (9.5-21.1) 14.4 (9.6-20.6) 14.5 (10.3-19.8) 14.5 (9.5-21.3) 14.6 (9.8-20.9) 14.6 (10.4-19.9) 6 ((L. helloides + L. nivalis) L. heteronea) L. 24.7 (16.9-34.9) 24.4 (17.0-34.3) 23.8 (17.4-31.8) 24.8 (16.9-35.3) 24.6 (17.0-34.8) 23.9 (17.5-31.9) rubidus Node7 NodeLycaeninae name + Satyrium 70,61.8 0.0002, (46.7 -0.0279.3) 70,62.2 0.0002, (47.5 0.002-79.2) 70,63.9 0.0002, (51.0 0.0002-79.3) 100,62.3 0.02, (46.8 0.02-80.2) 100,62.8 0. (48.0 02, 0.002-80.4) 100,64.2 0. (50.902, 0.0002-79.3) 8 (Lycaeninae + Satyrium)( Agriades + 79.3 (61.0-99.7) 80.4 (62.7-100.4) 84.3 (68.2-102.7) 80.0 (61.0-100.7) 81.1 (63.3-101.7) 84.6 (68.2-103.0) 1 Polyommatus)Papilio 59.2 (47.9-64.8) 59.6 (48.7-64.8) 60.6 (51.2-64.9) 58.1 (45.8-64.7) 58.6 (46.9-64.8) 59.9 (50.2-64.8) 92 LycaenidaeColias + Apodemia + Pieris 118.798.1 (92.5(76.5--146.9)122.6) 121.599.1 (97.6(78.0--148.4)123.0) 129.6102.9 (108.0 (83.6--154.5)125.3) 120.091.3 (93.6(70.5--148.1)113.8) 122.593.5 (97.9(73.7--150.0)115.7) 130.298.9 (107.9 (80.6--155.6)119.5) 103 Agriades + PolyommatusDanaus 25.412.5 (17.7 (8.3--35.7)18.4) 25.412.5 (18.0 (8.5--35.0)17.8) 25.612.7 (19.1 (9.1--33.7)17.3) 25.511.7 (17.6 (7.7--35.8)17.6) 25.511.7 (18.1 (7.9--35.4)17.0) 25.612.2 (19.2 (8.7--33.8)16.5) 114 L. helloidesNeominois + +L. Oeneis nivalis 28.09.2 (19.4 (5.9--38.4)13.4) 28.09.2 (20.2 (6.0--38.0)13.4) 28.39.3 (21.0 (6.4--37.4)13.2) 28.08.5 (19.7 (5.3--38.6)12.6) 28.28.6 (20.2 (5.6--38.5)12.6) 28.49.0 (20.9 (6.2--37.2)12.5) 125 (L.(N. helloides ridingsii + L.+ O.nivalis) chryxus) L. heteronea C. tullia 69.515.5 (53.7(10.3--86.9)22.4) 70.515.5 (55.1(10.5--87.9)22.0) 73.815.2 (59.6(10.8--90.6)20.9) 70.014.5 (54.1 (9.4--88.2)21.0) 71.014.5 (56.0 (9.8--88.9)20.7) 74.114.6 (59.8(10.4--91.1)20.0) 136 ((L. helloides((N. ridingsii + L. nivalis)+ O. chryxus) L. heteronea) C. tullia) L. 81.026.3 (63.8 (18.1-100.5)-37.7) 82.326.1 (65.5 (18.2-101.7)-36.5) 86.425.0 (71.0 (18.2-104.7)-33.7) 81.624.7 (64.4 (16.9-101.6)-35.4) 82.924.5 (66.4 (17.2-102.3)-34.1) 86.723.9 (71.1 (17.5-105.1)-32.1) Bicyclusrubidus 147 Lycaeninae Heliconius+ Satyrium 19.066.7 (13.6(50.9--25.9)86.0) 19.166.9 (13.8(51.4--25.7)85.4) 19.967.1 (15.1(53.1--25.8)83.5) 19.162.1 (13.6(46.6--25.9)79.7) 19.362.7 (14.1(48.2--26.1)79.6) 20.064.3 (15.0(51.0--26.0)80.0) 158 (Lycaeninae + HeliconiusSatyrium)( Agriades+ Agraulis + 86.034.9 (67.0 (26.2--108.2)45.2) 86.735.2 (67.8 (26.6--108.0)45.6) 88.537.0 (71.5 (29.1--108.3)46.4) 79.735.2 (60.9 (26.2--100.4)45.8) 81.035.5 (63.9 (27.1--100.9)46.1) 84.737.1 (68.5 (29.2--103.5)46.8) Polyommatus) 16 ((Heliconius) Agraulis) Speyeria 57.1 (45.0-71.7) 57.7 (45.6-72.0) 60.5 (49.3-73.8) 57.5 (44.8-72.1) 58.2 (46.2-72.7) 60.6 (49.2-74.2) 17 Limenitis 8.0 (5.3-12.1) 8.0 (5.3-11.8) 8.0 (5.7-11.1) 8.1 (5.2-12.1) 8.1 (5.4-11.8) 8.0 (5.7-11.2) 18 Limenitis + node 16 74.8 (59.9-92.4) 75.8 (61.3-92.9) 79.7 (66.1-95.9) 75.4 (60.1-93.1) 76.5 (62.0-94.0) 79.9 (66.2-96.5) 19 Vanessa + Nymphalis 37.4 (34.1-45.4) 37.3 (34.1-45.4) 37.2 (34.1-44.4) 37.4 (34.1-45.5) 37.4 (34.1-45.6) 37.2 (34.1-44.8) 20 (Vanessa + Nymphalis) Euphydryas 66.1 (55.4-80.3) 66.9 (56.4-80.9) 69.3 (59.2-82.6) 66.5 (55.7-80.6) 67.3 (56.6-81.2) 69.5 (59.5-82.8) 21 Node 18 + node 20 96.7 (78.0-117.8) 98.5 (80.7-119.0) 104.1 (88.1-123.8) 97.5 (78.3-119.1) 99.2 (81.5-120.6) 104.4 (87.8-124.3) 22 Node 21 + node 13 111.9 (89.1-136.7) 114.3 (92.9-138.4) 121.3 (102.2-143.9) 113.0 (89.6-138.1) 115.1 (93.7-139.3) 121.8 (102.3-144.9) 23 Node 22 + node 10 126.1 (98.9-154.7) 129.1 (104.4-156.7) 137.6 (115.6-162.9) 127.5 (100.1-156.7) 130.2 (105.0-158.2) 138.1 (115.2-164.1) 24 Node 23 + node 9 138.7 (107.9-171.1) 142.2 (114.2-172.9) 152.4 (127.6-180.9) 140.3 (109.1-173.2) 143.5 (115.1-175.0) 153.1 (127.7-181.8) 25 Node 24 + node 2 151.4 (117.0-187.8) 155.5 (123.8-189.9) 166.9 (139.3-198.6) 153.4 (118.5-190.0) 157.0 (125.0-193.1) 167.7 (139.7-199.4) 26 Node 25 + node 1 171.0 (130.9-213.4) 175.9 (139.2-216.7) 188.6 (157.0-224.2) 173.6 (132.5-216.2) 177.7 (140.5-219.7) 189.6 (158.0-225.5) Butterflies + M. sexta
Continuation Table 1.8
118 9 Lycaenidae + Apodemia 130.3 (104.3-159.4) 131.8 (106.8-160.2) 136.6 (113.7-162.7) 119.4 (93.5-147.4) 122.5 (98.5-149.0) 130.2 (107.7-155.6) 10 Danaus 26.5 (18.8-37.1) 26.6 (19.0-36.6) 26.6 (19.9-35.1) 25.5 (17.7-36.1) 25.5 (18.2-35.3) 25.8 (19.4-34.0) 11 Neominois + Oeneis 29.9 (21.1-41.5) 29.9 (21.3-40.7) 29.6 (21.9-39.0) 28.0 (19.4-38.7) 28.1 (19.9-38.7) 28.5 (21.1-37.5) 12 (N. ridingsii + O. chryxus) C. tullia 75.0 (58.6-95.0) 75.6 (59.3-94.3) 77.4 (62.3-95.0) 69.6 (53.9-87.7) 70.9 (55.5-89.0) 74.2 (59.9-91.2) 13 ((N. ridingsii + O. chryxus) C. tullia) 87.6 (69.7-108.9) 88.4 (70.7-109.2) 90.7 (74.4-109.9) 81.2 (64.0-100.7) 82.9 (66.2-102.7) 86.8 (71.3-104.9) 100, 0. 0002, Node Node name Bicyclus 100, 0.002, 0.02 * 100, 0.002, 0.002 100, 0.002, 0.0002 100, 0.0002, 0.02 100, 0. 0002, 0.002 14 Heliconius 20.3 (14.5-27.7) 20.5 (14.8-27.6) 20.8 (15.7-27.0) 19.1 (13.5-26.1) 19.3 (14.0-25.8) 20.00.0002 (15.1 -26.2) 151 Heliconius + AgraulisPapilio 37.458.2 (28.1(45.8-49.1)64.7) 37.758.7 (28.7(47.2-48.8)64.8) 38.760.1 (30.2(50.6-49.0)64.8) 35.059.4 (26.1(48.2-45.8)64.8) 35.559.7 (27.1(49.0-45.8)64.8) 37.160.7 (29.1(51.9-46.7)64.9) 162 ((Heliconius) Agraulis)Colias Speyeria+ Pieris 92.461.3 (70.7 (48.1-115.3)-77.5) 94.161.7 (74.0 (49.1-116.7)-77.5) 99.463.2 (80.9 (51.1-120.4)-77.8) 98.857.3 (76.6 (44.9-122.9)-71.9) 99.558.2 (78.5 (46.1-123.1)-72.8) 103.460.7 (84.0 (49.2-125.7)-74.4) 173 Agriades + PolyommatusLimenitis 11.78.5 (5.6(7.8-12.6)17.3) 11.98.4 (5.6(8.0-12.4)17.0) 12.38.4 (5.9(8.8-11.7)16.7) 12.68.0 (5.2(8.4-12.2)18.6) 12.68.0 (5.3(8.7-11.7)18.2) 12.88.1 (5.8(9.2-11.2)17.4) 184 L. helloidesLimenitis + + L. node nivalis 16 80.68.6 (64.9 (5.5-12.7)99.7) 81.28.7 (65.6 (5.7-100.0)-12.7) 83.39.0 (68.7 (6.2-101.1)-12.6) 75.19.2 (60.1 (6.0-13.6)92.7) 76.49.3 (62.0 (6.1-13.5)94.0) 80.09.4 (66.2 (6.5-13.1)96.7) 195 (L. helloides + L.Vanessa nivalis) +L. Nymphalis heteronea 38.514.5 (34.2 (9.6-21.0)48.7) 38.414.7 (34.1 (9.9-21.0)48.3) 38.014.7 (34.1(10.4-46.5)20.0) 37.415.6 (34.1(10.4-45.8)22.6) 37.415.5 (34.1(10.5-45.4)22.3) 37.215.3 (34.1(10.9-44.5)21.0) 206 ((L. helloides(Vanessa + L.+ nivalis)Nymphalis) L. heteronea) Euphydryas L. 70.324.8 (58.6(17.0-86.7)35.3) 70.724.8 (58.9(17.3-86.6)34.6) 72.024.1 (61.2(17.6-86.6)32.4) 66.326.4 (55.5(18.2-80.7)37.9) 67.226.1 (18.3(56.5-81.3)36.9) 69.525.1 (59.7(18.4-83.0)33.6) rubidus 21 Node 18 + node 20 104.7 (85.7-127.7) 105.8 (87.2-128.2) 109.0 (92.0-130.0) 97.1 (78.4-118.8) 99.3 (81.5-120.3) 104.5 (88.2-124.0) 7 Lycaeninae + Satyrium 62.6 (47.3-80.9) 63.3 (48.6-80.5) 64.8 (51.3-80.5) 67.2 (51.1-86.8) 67.2 (51.9-85.6) 67.5 (53.7-83.9) 22 Node 21 + node 13 122.1 (99.4-148.7) 123.4 (101.2-148.7) 127.5 (107.3-152.0) 112.4 (89.5-137.6) 115.2 (93.8-140.1) 121.9 (102.7-144.5) 238 (Lycaeninae + Satyrium)(Node 22 Agriades + node 10 + 138.680.5 (112.6 (61.7-168.2)101.6) 140.281.8 (114.6 (64.2-168.8)102.0) 145.185.3 (121.9 (69.0-172.3)104.2) 126.886.7 (67.6(99.7-156.3)109.6) 130.287.0 (105.4 (68.7-158.1)108.3) 138.389.1 (116.0 (72.0-164.1)108.7) Polyommatus) 24 Node 23 + node 9 153.5 (123.9-187.1) 155.4 (126.4-187.3) 161.2 (135.8-191.4) 139.5 (108.5-172.2) 143.6 (115.4-174.7) 153.2 (128.1-181.1) 9 Lycaenidae + Apodemia 121.0 (94.6-149.6) 123.6 (99.7-150.7) 131.2 (108.7-156.8) 131.5 (105.5-160.7) 132.5 (107.8-160.6) 137.4 (113.7-164.1) 25 Node 24 + node 2 169.4 (136.9-206.6) 171.3 (139.4-207.4) 177.4 (148.9-210.7) 152.3 (117.1-189.0) 157.0 (124.8-192.2) 167.9 (139.8-199.7) 26 Node 25 + node 1 194.0 (156.1-237.3) 195.9 (158.7-238.3) 201.3 (169.3-238.4) 172.3 (130.6-215.2) 177.7 (140.3-219.0) 189.7 (157.8-225.0) Butterflies + M. sexta
Continuation Table 1.8
119 10 Danaus 25.6 (17.9-35.6) 25.6 (18.1-35.5) 25.8 (19.2-34.3) 26.7 (18.7-37.4) 26.7 (19.0-37.0) 26.7 (19.8-35.2) 11 Neominois + Oeneis 28.3 (19.8-39.5) 28.3 (20.3-38.6) 28.6 (21.3-37.6) 30.1 (21.3-41.5) 30.0 (21.6-41.0) 29.8 (22.2-39.5) 12 (N. ridingsii + O. chryxus) C. tullia 70.6 (54.7-89.5) 71.5 (56.5-89.1) 74.6 (60.3-91.4) 75.6 (59.2-94.8) 75.9 (59.8-95.4) 77.8 (63.1-95.2) 13 ((N. ridingsii + O. chryxus) C. tullia) 82.4 (64.8-102.9) 83.4 (67.0-103.1) 87.3 (71.5-105.6) 88.3 (70.5-109.5) 88.8 (71.5-110.1) 91.0 (74.6-110.1) Bicyclus 14 Heliconius 19.2 (13.5-26.1) 19.4 (14.1-26.2) 20.1 (15.2-26.2) 20.5 (14.7-27.9) 20.5 (15.0-27.7) 20.9 (15.6-27.2) 15 Heliconius + Agraulis 35.3 (26.3-45.8) 35.8 (27.2-46.4) 37.3 (29.3-47.0) 37.7 (28.5-49.1) 37.8 (28.7-49.2) 38.8 (30.4-49.0) 16 ((Heliconius) Agraulis) Speyeria 57.8 (45.3-72.6) 58.6 (46.5-73.0) 61.0 (49.6-74.9) 61.8 (48.6-77.6) 61.9 (48.9-77.7) 63.4 (51.4-77.8) 17 Limenitis 8.1 (5.3-12.1) 8.1 (5.5-11.8) 8.1 (5.7-11.2) 8.5 (5.7-12.8) 8.5 (5.7-12.4) 8.4 (5.9-11.7) 18 Limenitis + node 16 75.9 (60.7-94.0) 77.0 (62.7-94.7) 80.3 (66.5-97.2) 81.2 (65.5-100.2) 81.5 (65.7-101.1) 83.7 (69.3-101.2) 19 Vanessa + Nymphalis 37.6 (34.1-45.9) 37.5 (34.1-46.0) 37.3 (34.1-44.7) 38.7 (34.1-49.1) 38.5 (34.1-48.6) 38.2 (34.1-46.8) 20 (Vanessa + Nymphalis) Euphydryas 66.9 (55.9-81.6) 67.6 (57.0-82.1) 69.8 (59.8-83.1) 70.7 (58.8-87.1) 70.9 (59.5-87.2) 72.2 (61.4-86.6) 21 Node 18 + node 20 98.3 (78.9-120.3) 99.9 (82.5-121.0) 105.0 (88.7-124.8) 105.5 (86.6-128.2) 106.2 (87.5-129.2) 109.4 (92.5-130.4) 22 Node 21 + node 13 113.9 (90.4-139.5) 116.0 (94.6-140.4) 122.6 (103.2-145.6) 123.1 (100.2-149.4) 124.0 (102.1-150.2) 128.1 (107.9-152.3) 23 Node 22 + node 10 128.6 (101.3-158.3) 131.3 (106.6-159.3) 139.2 (116.7-165.0) 139.8 (113.8-169.8) 140.9 (115.5-170.4) 145.8 (122.6-172.8) 24 Node 23 + node 9 141.6 (110.3-175.2) 144.9 (117.0-176.3) 154.3 (128.9-183.1) 154.9 (125.3-188.1) 156.2 (127.2-188.4) 162.1 (135.7-192.2) 25 Node 24 + node 2 154.8 (119.7-192.0) 158.5 (127.0-193.4) 169.1 (141.4-200.6) 170.9 (138.0-208.7) 172.3 (140.3-208.9) 178.4 (149.5-211.7) 26 Node 25 + node 1 175.4 (134.0-218.9) 179.6 (142.5-219.8) 191.2 (159.5-226.9) 195.8 (158.1-240.3) 197.2 (160.3-239.3) 202.5 (170.1-239.3) Butterflies + M. sexta
120 ----- E. speciosus 100 100
80 80
60 60
40
40 % Reflectance Reflectance % Reflectance ----- A. alpicola ----- A. alpicola painted white
20 20
0 0 300 400 500 600 700 300 400 500 600 700 Wavelength (nm) Wavelength (nm)
----- W. amplexicaulis ----- D. hoopesii 100 100 - - - W. amplexicaulis painted yellow - - - D. hoopesii painted orange
80 80
60 60
40 40 % Reflectance Reflectance % Reflectance
20 20
0 0 300 400 500 600 700 300 400 500 600 700 Wavelength (nm) Wavelength (nm)
121 Fig. 2.1. Average reflectance spectra of unpainted and painted A. alpicola, E. speciosus, W. amplexicaulis and D. hoopesii flowers.
122
Fig. 2.2. Spontaneous preferences in arrays of unpainted flowers. Displayed are proportions of visits ± 95% confidence intervals.
123
Fig. 2.3. Spontaneous color preferences. Arrays were composed of flowers from one species, half of them painted to match its original color, and half to resemble a second flower species. Displayed are proportions of visits ± 95% confidence intervals.
124
Fig. 2.4. Spontaneous morphology preferences. Arrays contained all same colored flowers from two different species. Displayed are proportions of visits ± 95% confidence intervals.
125
Fig. 2.5. Spontaneous display size preferences. Arrays contained flowers from one species only. Half of the flower picks presented displays of double the size of the remaining picks. ‘Large’ D. hoopesii’s flower heads had ray flowers left uncut, whereas ‘small’ flowers had their ray flowers cut in half. ‘Large’ A. alpicola flower clusters were double the diameter of ‘small’ clusters. ‘Large’ E. speciosus displays included three individual flower heads whereas ‘small’ displays included only one. Displayed are proportions of visits ± 95% confidence intervals.
126
Fig. 2.6. Number of seeds produced by three different crossing treatments. Displayed are average seed numbers; error bars represent ± 1 standard error.
127 Table 2.1: Tests of butterfly flower constancy behavior. G tests of independence were used in arrays of 40 or more flight transitions. Fisher’s exact test was employed otherwise. BI denotes Bateman’s constancy index.
Species Natural arrays Color arrays Morphology arrays Orange D. hoopesii/W. Yellow D. hoopesii/W. D. hoopesii/W. amplexicaulis D. hoopesii orange/yellow W. amplexicaulis orange/yellow amplexicaulis amplexicaulis G* N P BI G N P BI G N P BI G N P BI G N P BI C. oetus --- 21 0.66 -0.17 --- 35 0.39 -0.34 0.63 229 0.43 -0.14 0.13 106 0.72 -0.06 0.09 44 0.76 0.09 P. campestris --- 57 1.00 # --- 37 0.07 0.40 ------12 1.00 -0.17 ------L. heteronea 1.62 251& 0.20 0.10 --- 12 1.00 0.13 ------13 0.53 # ------S. mormonia 0.00 44& 1.00 0.00 2.34 361 0.13 -0.09 0.12 42 0.73 -0.10 0.30 190 0.58 0.05 --- 35& 0.39 -0.34
E. speciosus/A. alpicola E. speciosus white/purple A. alpicola white/purple Purple E. speciosus/A. alpicola White E. speciosus/A. alpicola G N P BI G N P BI G N P BI G N P BI G N P BI L. heteronea --- 20 0.64 0.17 ------0.03 118 0.85 0.02 ------0.26 76 0.61 0.09 L. rubidus 1.68 78 0.20 0.18 ------
Species Size arrays D. hoopesii A. alpicola E. speciosus G N P BI G N P BI G N P BI C. oetus 0.00 44 0.99 0.00 --- 28 0.29 # --- 19 1.00 -0.02 P. campestris --- 22 0.67 -0.13 ------21 0.35 0.29 L. heteronea ------23 0.14 0.39 --- 28 1.00 0.07 S. mormonia 1.46 108 0.23 -0.14 ------
* G: G-test of independence. Fisher’s exact tests were used with sample sizes (number of flower transitions recorded) below 40. # Bateman’s index could not be calculated when there were no records of one or more types of flight transitions. & Combined data from 2007-8 seasons.
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