Variation in Female Mating Preferences in Swordtail Fishes: the Importance of Social

Home , Green swordtail, Kevin de Queiroz, Xiphophorus, Xiphophorus birchmanni, Xiphophorus malinche, Xiphophorus montezumae

Experience, Male Aggression and Genetic Variation

A dissertation presented to

the faculty of

the College of Arts and Sciences of Ohio University

In partial fulfillment

of the requirements for the degree

Doctor of Philosophy

Donelle M. Robinson

August 2011

This dissertation titled

Variation in Female Mating Preferences in Swordtail Fishes: the Importance of Social

Experience, Male Aggression and Genetic Variation

DONELLE M. ROBINSON

has been approved for

the Department of Biological Sciences

and the College of Arts and Sciences by

Molly R. Morris

Professor of Biological Sciences

Howard Dewald

Interim Dean, College of Arts and Sciences

ABSTRACT

ROBINSON, DONELLE M., Ph.D., August 2011, (Select Program Name from list:)

Variation in Female Mating Preferences in Swordtail Fishes: the Importance of Social

Experience, Male Aggression and Genetic Variation

Director of Dissertation: Molly R. Morris

Identifying the different factors that influence female preference is essential to our understanding of the evolution of female preferences. Plastic mate preferences can be

favored by natural selection in varying environments, including social environments. In

this dissertation, I addressed the following questions in Xiphophorus birchmanni, X.

cortezi and X. malinche: 1) What factors affect variation in female preference for vertical

bars; 2) Does experience with different male phenotypes affect female preferences for

vertical bars; 3) Does female preference contribute to the evolution of the exaggerated

dorsal fin; 4) Did the exaggerated dorsal fin evolve to enhance courtship displays; 5)

What are the phylogenetic relationships within and across these species?

Female preferences for vertical bars in X. cortezi varied with female bar state,

female size, and population in wild-caught females. By further examining differences

using lab-reared fish, I found that preferences varied by social experience with barred and

barless males, and this relationship varied across populations. These results indicated a

combination of both genetic (population, bar state) and environmental (female size) on

female preferences. I also found that barless males were more aggressive toward females,

and suggest that these behavioral differences could explain how experience influences

female preferences.

Xiphophorus birchmanni females preferred dorsal fins that were larger than

expected given the male’s size, and during male–female interactions, males raised their

dorsal fins as part of their courtship display directed towards females. I suggest that

female preference selected for enlarged dorsal fins in male X. birchmanni, and that female preferences are potentially disruptive for dorsal fin size. I also found that raising the dorsal fin is a signal directed at females in several species of Xiphophorus. However, sexual dimorphism in dorsal fin size evolved prior to increased use of the dorsal fin during courtship. It is possible that either female preferences or male competition led to initial exaggeration of the dorsal fin.

In the three species phylogeography, haplotypes of X. malinche and X. cortezi

were paraphyletic with respect to each other, while X. birchmanni haplotypes formed a

monophyletic group. However, microsatellite analyses uncovered three genetic groups

corresponding to the three species. Populations of X. malinche and X. cortezi clustered

within their respective species, suggesting that these are separate species.

Approved: ______

Molly R. Morris

Professor of Biological Sciences

ACKNOWLEDGMENTS

I would like to thank my advisor, Molly Morris, for her support and guidance throughout my dissertation. Her support has contributed to the success of this research and increased the quantity of research that I could produce during the past five years. I

thank members of the Morris lab past and present: Lisa Bono, Peter Braun, Jason Brewer,

Andre Fernandez, Susan Lyons and Scarlett Tudor for their support and friendship. I

thank my committee members Harvey Ballard, Oscar Rios-Cardenas and Matthew White

for their comments on this dissertation. I thank Natalie Dubois for teaching me PCR

reactions and David Cannatella for letting me work with his lab while I learned molecular

techniques. I thank Kevin de Quieroz and Carla Gutierrez Rodriguez for their comments

and suggestions for Chapter 5. There are several students who also helped with parts of

this research: Elise Baron, Julie Bauerschmidt, Theresa Beham, Shawn Conaster, Dan

Glaser, Sarah Klim, Katy Kovar, Andrew Morris, Britanny Tarselli. For assistance

collecting fish, I thank the Morris lab, Jeff Baker, Angela Horner and Charles Nevill. I

thank my advisors from Texas State University, Caitlin Gabor and Andrea Aspbury, for

training me well as a graduate student so that I easily transitioned to doctoral student. I

also thank Floyd Weckerly at Texas State University for making statistics approachable.

There were several funding sources for my dissertation that I thank. Parts of this

dissertation were funded by grants from the Animal Behavior Society and the Graduate

Student Senate to D.M. Robinson, as well as a National Science Foundation grant to

M.R. Morris and O. Rios-Cardenas. During my research, I was also support by

fellowships from the Ohio Center for Ecology and Evolutionary Studies, research

assistantships in the Morris lab, and teaching assistantships in the Department of

Biological Sciences. Travel to scientific conferences to present the first four chapters of

this dissertation was provided by the Department of Biological Sciences, Graduate

Student Senate, and the Animal Behavior Society. I also thank Christiane Meyer for

providing Xiphophorus helleri for Chapter 4.

Finally, I thank my friends and family for their constant support during these past

five years. I especially thank my husband, Charles Nevill, for listening to me constantly

discuss my research and for assisting with parts of my dissertation, including building the

transparency machine for Chapter 3 and writing applets that helped analyses for Chapter

5. I thank my parents for raising me so that I believed I could pursue anything. I also

thank my purr-fection support team, Cookie and Mac, who ensured that I was never lonely when I worked late.

TABLE OF CONTENTS

Page

Abstract...... 3

Acknowledgments...... 5

List of Tables ...... 12

List of Figures...... 13

General Introduction...... 15

Study System and Research Directions ...... 19

References...... 24

Chapter 1: Unraveling the Complexities of Variation in Female Mate Preference for

Vertical Bars in the Swordtail, Xiphophorus cortezi ...... 31

Abstract...... 31

Introduction...... 32

Methods ...... 35

Statistical Analyses ...... 38

Results...... 40

Discussion...... 42

Acknowledgements...... 50

References...... 50

Chapter 2: Female Preference Plasticity in Xiphophorus cortezi ...... 60

Abstract...... 60

Introduction...... 61

Methods ...... 66

Experiment 1-Manipulating Female Social Environment ...... 67

Fish Collection and Maintenance...... 67

Experience Treatments...... 68

Female Growth...... 70

Female Preference Tests ...... 70

Analysis of Strength of Preference ...... 72

Experiment 2-Differences in Mating Behaviors between Barred and Barless

Males...... 74

Results...... 76

Experiment 1-Manipulating Female Experience ...... 76

Female Growth...... 76

Female Preferences ...... 76

Experiment 2- Differences in Male Courtship and Coercive Behaviors ...... 78

Discussion...... 78

Acknowledgements...... 84

References...... 84

Chapter 3: Female Preference and the Evolution of an Exaggerated Male Ornament: the Shape of the Preference Function Matters ...... 95

Abstract...... 95

Introduction...... 96

Methods ...... 99

Female Preferences ...... 100

Dorsal Fin Size...... 103

Male–Female Interactions...... 104

Results...... 107

Female Preferences ...... 107

Dorsal Fin Size...... 107

Male–Female Interactions...... 108

Discussion...... 109

Acknowledgments ...... 116

References...... 116

Chapter 4: Role of the Dorsal Fin During Courtship in Xiphophorus ...... 128

Abstract...... 128

Introduction...... 129

Materials and Methods...... 132

Morphology...... 133

Male-Female Interactions ...... 134

Phylogenetic Comparisons...... 136

Results...... 137

Morphology...... 137

Male-Female Interactions ...... 137

Phylogenetic Comparisons...... 139

Discussion...... 139

Acknowledgements...... 145

References...... 145

Chapter 5: Genetic Variation and Phylogeography of the Swordtail Fishes

X. birchmanni, X. cortezi, and X. malinche (Cyprinodontiformes: Poeciliidae) ...... 154

Abstract...... 154

Introduction...... 155

Methods ...... 158

Sample Collection...... 158

Molecular Analyses ...... 160

Statistical Analyses ...... 162

Mitochondrial Control Region...... 162

Microsatellite Analyses...... 165

Results...... 167

Mitochondrial Control Region...... 167

Relationships Among Haplotypes...... 167

Population Genetic Analyses ...... 169

Microsatellite Analyses...... 171

STRUCTURE ...... 172

Discussion...... 176

Genetic and Geographic Diversity within Species ...... 176

Ancestral Haplotypes and Biogeographic Origin ...... 180

Deviations from Hardy Weinberg Equilibrium ...... 182

Microsatellite Admixture ...... 183

Species Status...... 185

Conclusions...... 186

Acknowledgements...... 187

References...... 187

LIST OF TABLES

Page

Table 1.1 Populations of Xiphophorus cortezi tested from female SOP for vertical bars...... 55

Table 1.2 Models for female SOP...... 56

Table 2.1. Models for female strength of preference for vertical bars. Models are ranked in order of support by Akaike’s Information Criterion...... 91

Table 2.2. ANOVA Table for female strength of preference for vertical bars...... 92

Table 3.1. Models of courtship behaviour for male Xiphophorus birchmanni...... 122

Table 4.1. Range of sizes and the slope representing the relationship between (log transformed) standard length and dorsal fin area, and the 95% confidence intervals surrounding the slope...... 149

Table 4.2. Unpaired t-test results for sexual dimorphism in dorsal fin size...... 150

Table 5.1. Populations and measures of the genetic diversity of the mitochondrial DNA control region ...... 194

Table 5.2. Hierarchical analysis of molecular variance (AMOVA) ...... 196

Table 5.3. Estimates of pairwise FST for control region (below diagonal) and RST for microsatellites (above diagonal) among populations of X. cortezi...... 197

Table 5.4. Estimates of pairwise FST for control region (below diagonal) and RST for microsatellites (above diagonal) among populations of X. birchmanni ...... 198

Table 5.5. Estimates of pairwise FST for control region (below diagonal) and RST for microsatellites (above diagonal) among populations of X. malinche ...... 199

Table 5.6. Estimates of demographic and neutrality tests within each species and drainage...... 200

Table 5.7. Population genetic variability of microsatellites ...... 201

Table 5.8. Inbreeding coefficients (FIS) of microsatellite loci...... 202

Table 5.9. Wright’s F-statistics for microsatellite loci within each species ...... 204

LIST OF FIGURES

Page

Figure I.1. Reconstruction of ancestral states using maximum parsimony and maximum likelihood for the COMPLEX character scorings using the Rauchenberger et al. (1990) phylogeny...... 30

Figure 1.1. Male and female Xiphophorus cortezi are polymorphic for the pigment pattern vertical body bars: (a) Barless male, (b) barred male, (c) barless female and (d) barred female...... 57

Figure 1.2. Parameters selected by candidate models for female SOP for vertical bars in Xiphophorus cortezi...... 58

Figure 2.1. Correlation between female population and experience treatment on female SOP ...... 93

Figure 2.2. Correlation between female growth and experience treatment (a. mixed treatment, b. barred treatment) on female SOP...... 94

Figure 3.1. Models of male X. birchmanni used to examine female preferences for large dorsal fin size ...... 123

Figure 3.2. Mean + SE time that female Xiphophorus birchmanni spent associating with each transparency...... 124

Figure 3.3. Isometry of the dorsal fin size (mm2) and body size (standard length) in Xiphophorus birchmanni ...... 125

Figure 3.4. Mean + SE time that male Xiphophorus birchmanni spent raising the dorsal fin when a female was present or absent...... 126

Figure 3.5. Total number of courtship behaviours by male Xiphophorus birchmanni relative to (a) strength of response to females and (b) dorsal fin size ...... 127

Figure 4.1. Mean time males of five swordtail species raised their dorsal fins alone (grey bars) and with females present (white bars) during a 10 min observation...... 151

Figure 4.2. Partial regression plots for strength of response in Xiphophorus nezahualcoyotl ...... 152

Figure 4.3. Maximum parsimony reconstruction of the ancestral states of the male dorsal fin morphology and use of the dorsal fin during courtship...... 153

Figure 5.1. Map showing collection localities for X. birchmanni (squares), X. cortezi (circles), and X. malinche (triangles)...... 205

Figure 5.2. Genetic relationships for X. birchmanni (squares), X. cortezi (circles), and X. malinche (triangles): (a) Maximum likelihood bootstrap tree and Bayesian posterior probabilities for haplotypes of the mitochondrial DNA control region haplotypes ...... 206

Figure 5.3. Parsimony analyses based on sequences of the mitochondrial DNA control region: (a) Parsimony networks for X. birchmanni (squares), X. cortezi (circles), and X. malinche (triangles) ...... 208

Figure 5.4 Observed mismatch distribution (histogram) under population expansion model for drainages of a) Xiphophorus cortezi, b) X. birchmanni and c) X. malinche mtDNA control region sequences...... 211

Figure 5.5. Isolation by distance for plots using Nei & Li (1979) genetic distance for mtDNA and Cavalli Svorza chord distance for microsatellite loci for all possible pairs of populations: mtDNA compared to (a) river distance and (b) straight-line distances, and microsatellites compared to c) river and d) straight- line distances...... 212

Figure 5.6. Genetic groups across species for two, three and four genetic groups (K) based on STRUCTURE analysis of microsatellite loci...... 214

Figure 5.7. Genetic groups in X. birchmanni for two, three and four genetic groups (K) based on STRUCTURE analysis of microsatellite loci...... 215

Figure 5.8. Genetic groups in X. cortezi for two, three and four genetic groups (K) based on STRUCTURE analysis of microsatellite loci ...... 216

Figure 5.9. Genetic groups in X. malinche for two, three and four genetic groups (K) based on STRUCTURE analysis of microsatellite loci...... 217

GENERAL INTRODUCTION

Studies of the evolution of female mate preferences and the male traits that evolve due to mate preferences have recently expanded to include the more complex contexts in which female preferences act. Many sexually selected male traits are affected by both male-male competition and female mate choice (Tinbergen 1953; Ord et al. 2001), and often function as signals with dual audiences: females assessing males as potential mates and males assessing males as competitors (see review in Andersson 1994). Sexual selection on a trait can be determined by correlating the trait to mating success (reviewed in Andersson 1994). Variation in male morphology can also be correlated with variation in mating behaviors that may influence male mating success. This has been studied extensively in systems with distinct male morphs that use alternative reproductive tactics

(Gross 1996; Lee 2005). However, continuous variation in male morphology also can correspond to behavioral differences. For example, in many systems, large body size is associated with more aggressive behaviors during male-male competition (reviewed in

Arnott & Elwood 2009). Thus, male morphological characters may be a cue that conveys the male behavioral phenotype to males and females, as well as potentially indicating male genetic quality to females.

Historically, sexual selection theory has predicted that female mate choice will select for male traits that are favored during male-male competition (Arnqvist & Rowe

2005). Female mate choice should reinforce (select in the same direction as) male-male

competition if male traits favored by male-male competition are correlated to direct

benefits (resources that increase female fitness) or indirect benefits (genetic quality) that

females receive from those males. For example, females may prefer males with better

resources (better territories), which may be related to the competitive ability of males to

obtain those resources. Females also may prefer competitively superior mates if these

males have better genes to pass on to their offspring, or if these males produce sons that

also are competitively superior.

Female preferences may vary adaptively across females on several levels, and

within a female during different stages of life history. Different populations within a

species will have both genetic and environmental differences that can produce divergent

selection on traits and preferences between environments (e.g., Endler & Houde 1995;

Boughman 2001). Variation in female preferences can also occur within a population

across females that differ phenotypically. For example, females in poor condition, who may not be able to withstand the costs of searching for mates, may be less choosy than females in good condition (Jennions & Petrie 1997; Cotton et al. 2006). The costs of female mate choice may vary during different stages of life history. For example, fecundity may vary at different life stages. In many species, females continue to grow after reaching sexual maturity, and older, larger females are also more fecund (Andersson

1994). Older females are often more choosy, and two different hypotheses for this pattern have been suggested. In species where older females are larger, the younger smaller females may be more likely to divert resources to growth rather than choice to maximize

their reproductive potential (Jennions & Petrie 1997; Cotton et al. 2006). In addition,

older females may have more experience with the different male phenotypes than

younger females and thus better able to discriminate among phenotypes.

Sexual conflict also influences female preferences, and occurs during intersexual

interactions when the evolutionary interests of males and females differ (Parker 1979), such as when males are selected to mate multiple times using coercive mating behaviors that can harm females. In general, mating with males that are aggressive can carry costs for females. Aggressive males may not only coerce females to mate more often than is optimal, but can also increase predation risk, reduce foraging time, or even inflict

physical injury on females (e.g. Chapman et al. 1995; Martin & Hosken 2003; Linder &

Rice 2005; Sakurai & Kasua 2008). When traits favored in males carry costs to females,

there are two possible, nonmutually exclusive, effects to female mate choice. First, the amount of stimulation that females require to respond to male traits may shift through a change in the intercept of the female preference function (Rosenthal & Servedio 1999;

Gavrilets et al. 2001; Rowe et al. 2004). For example, female preference for large males

may increase so that females only respond to large males in the population. In this

situation, a coevolutionary arms race between female preferences and male traits may

occur, and females may prefer more exaggerated male traits. Female preferences for

exaggerated male traits may become so extreme that no existing male traits are

exaggerated enough to be preferred by females. Second, female sensitivity to male traits

may be reduced through a change in the slope of the female preference function

(Rosenthal & Servedio 1999; Rowe et al. 2004). In this situation, females may evolve a preference that allows them to avoid males with the aggressive behaviors (Rowe et al.

2004). A number of studies have found that females prefer less aggressive males (e.g.,

Moore et al. 2003; Ophir & Galef 2003; Spritzer et al. 2006; Poschadel et al. 2007) and one model suggests that this outcome is more likely than a coevolutionary arms race between male trait and female preference for the male trait (Rowe et al. 2004).

A better understanding of the genetic and environmental factors influencing female preference will allow us to better understand the role that plasticity in preference plays in the evolution of preference as well as its influence on the evolution of male traits. Swordtail fishes (genus Xiphophorus) are an ideal system for studying variation in mating preferences for several reasons. This is a model system in behavioral ecology

(Ryan & Rosenthal 2001). Sexual ornaments have been studied extensively in the swordtail fishes. The swordtail is an extension of the lower rays of the caudal fin found in several species of Xiphophorus and is preferred by females in many species (e.g., Basolo

1990; Basolo & Trainor 1992; Rosenthal & Evans 1998; Rosenthal et al. 2002). Several melanin pigmentations also exist in Xiphophorus that may increase conspicuousness.

Female preferences have been found for the pigmentations vertical bars (Morris et al.

1995, 2007) and spotted caudal (Fernandez & Morris 2008). The prevalence of sexual ornaments varies widely across species, with some species (X. continens, X. pygmaeus) lacking sexual ornaments such as the swordtail (Morris et al. 1995, 2005), and other species (X. multilineatus, X. nigrensis) having males of multiple size classes with the

smallest size classes having lost or reduced ornament expression and using alternative mating strategies (Ryan & Causey 1989; Zimmerer & Kallman 1989; Ryan et al. 1990).

Finally, measures of mate preference in the lab have been found to reflect mate choice decisions, as measured by paternity, in the field for closely related X. multilineatus

(Morris et al. 2010) and in captivity for X. helleri (Walling et al. 2010).

Study System and Research Directions

Swordtails (Genus: Xiphophorus) are livebearing fish belonging to the family

Poeciliidae and have internal fertilization. Both males and females mate multiply, and females are capable of storing sperm for several months (Constantz 1989). Cryptic female mate choice has been documented in livebearing fish and is a mechanism whereby females may reduce costs associated with sampling mates by biasing paternity after mating (Poecilia reticulata: Evans et al. 2003; Pilastro et al. 2004; Evans & Rutstein

2008). Male harassment of females also occurs in livebearers, including swordtails, and is costly to females by reducing foraging time (e.g., Magurran & Seghers 1994; Schlupp et al. 2001; Plath et al. 2007) and by reducing female fitness (Ojanguref & Magurran 2007).

Male harassment may not affect all females equally; female growth is indeterminate

(Kallman 1989; Marcus & McCune 1999) and male harassment may not be as costly to older, larger females. In addition, as females are more fecund as they grow larger and older, growth could be optimized over mate choice when females are young. Therefore, adaptive variation in female mate preference is predicted in this system.

In Xiphophorus, the pigment pattern vertical body bars is a signal used both in

male-male competition and female mate choice (Morris et al. 1995, 2007; Moretz &

Morris 2006). The genetic basis of vertical bars has been examined in Xiphophorus

multilineatus and in hybrid crosses (Atz 1962; Zimmerer & Kallman 1988). Vertical bar

expression can vary among species. Variation in female mate choice for vertical bars has

high repeatability and was found to correlate with whether females had the pigment

pattern vertical bars, which may indicate that this variation in female mate choice also

has a genetic basis (Morris et al. 2003). Female mate choice for vertical bars varies

among species in the Northern clade of swordtails (Fig. I.1; Morris et al. 2007). The ancestral state of female mate choice in Northern swordtails is a response to vertical bars

(Morris et al. 2007). However, female responses vary extensively across species: some species prefer barred males, some species prefer barless males, some species have polymorphic preferences, and some species do not respond to vertical bars (Morris et al.

1995, 2003, 2005, 2007; Morris & Ryan 1996; Hankison & Morris 2002). Vertical bar expression in males also varies by species. In some species all males have vertical bars, in some species all males are barless, and in other species males are polymorphic for vertical bars (Morris et al. 2007). Male response to vertical bars also varies among species of Northern swordtails (Fig. I.1; Moretz & Morris 2006). At the base of the clade of Northern swordtails, vertical bars were used in male-male competition, but were not an honest signal of aggressive intent (vertical bars were not expressed prior to biting, Moretz

& Morris 2006). The response of males to vertical bars did not evolve until after vertical bars were used in male-male competition (Moretz & Morris 2006). Male responses to

vertical bars vary among species: males may increase aggression, decrease aggression, be

polymorphic in their response, or not respond to aggression (Fig. I.1; Moretz & Morris

2003, 2006). Vertical bars are an honest signal of aggressive intent in species where

males respond to vertical bars (Moretz & Morris 2006). The female response to vertical bars evolved before the male response to vertical bars (Fig. I.1; Morris et al. 2007).

In X. cortezi, both males and females are polymorphic for vertical bars

(Rauchenberger 1990). Male aggression and female preferences in X. cortezi have been tested in fish originating from Arroyo La Conchita, Mexico. Male competitive ability in this population is correlated with vertical bars: barless males are more aggression and more likely to win male-male contests than barred males when controlling for male body size (Moretz 2005). Males also vary in their response to vertical bars: barred males respond to bars with decreased aggression, whereas barless males do not respond to bars during male-male competition (Moretz & Morris 2003). Females also exhibit variation in preference for vertical bars, with barred females preferring barred males (Morris et al.

2003). Female mate choice has a high repeatability and is correlated with females having bars, suggesting that variation in female preferences may be heritable (Morris et al.

2003). A phylogeographic study of X. cortezi found a high degree of genetic differentiation among populations, with a positive relationship between genetic and geographic (river) distance (Gutiérrez-Rodríguez et al. 2007).

In Chapter 1 (Robinson & Morris 2010), I examined variation in female preferences for the pigment pattern vertical bars across five populations of the swordtail,

Xiphophorus cortezi that were genetically differentiated and varied in the frequency of males and females with bars. I also assessed how within-individual variation affected female preferences. This study indicated a combination of both genetic (bar state) and environmental (female size) influences on how females responded to male phenotypes in this species. In addition, population-level differences could be interpreted as the result of genetic differences or differences in experience with barred and barless individuals. In

Chapter 2, I examined whether there were behavioral differences between male phenotypes that could influence female preferences. I also further investigated variation in female preferences for vertical bars by examining how social experience affected mating preferences of females from two genetically diverged populations of X. cortezi.

The dorsal fin is another sexually selected ornament in swordtail species, although there has been less work investigating the role of this ornament in female mate preference than the vertical bar pigment pattern. The dorsal fin is raised during courtship displays and during male-male contests in some species (Zimmerer & Kallman 1989; Rosenthal et al. 2003), and males that lose contests will lower the dorsal fin (e.g. Moretz 2003; Lyons

& Morris 2008). The dorsal fin is an important sexual ornament in other poeciliid species.

In sailfin mollies, Poecilia latipinna, females prefer males with larger dorsal fins, which may be due to female preferences for larger males in this system (MacLaren et al. 2004).

There is also evidence that the relationship between dorsal fin size and body size across

species of sailfin mollies correlates with male mating behavior (Hankison & Ptacek

2007). In Chapter 3 (Robinson et al. 2011), I investigated the role of the dorsal fin during male and female interactions in X. birchmanni. Xiphophorus birchmanni males have large dorsal fins that are strongly correlated with body size: large males have larger dorsal fins than small males (Fisher et al. 2009), although this study did not include the exact relationship between dorsal fin size and body size (i.e. the regression statistics).

Previous work has suggested that the dorsal fin is a trait females could use to identify aggressive males in this species, and that females prefer males with smaller dorsal fins as a means of avoiding aggressive males (Fisher & Rosenthal 2007). I re-examined the role of female preference in the evolution of the enlarged dorsal fins in this species by testing for preferences on the other end of the preference function (larger dorsal fins), the use of the dorsal fin during courtship, and the aggressive behavior of these males towards females during male-female interactions. In Chapter 4, I expand the description of the dorsal fin as a sexual ornament by describing this trait and its use during courtship in four additional species of swordtails. This comparative study allows me to examine the relative evolution of the size of the dorsal fin in relation to its use during courtship in the

Northern swordtail clade.

While in Chapters 1-4 I have focused on sexual selection in the Northern swordtails, in Chapter 5 I examine genetic variation and the evolutionary relationship among populations of three species of Northern swordtails, hypothesized by

Rauchenberger et al. (1990) to form a clade: X. birchmanni, X. cortezi, and X. malinche.

Examining the phylogeny of the three species of the Cortezi clade is important for

understanding the variation in mating behavior in the prior chapters, which compare

mating preference behaviors across populations of X. cortezi (Chapters 1, 2) and

courtship behavior across species (Chapter 4). Prior studies investigating genetic

variation in these species have disagreed over their evolutionary relationships. Most

recently, a phylogeography of X. cortezi suggested that some populations of X. cortezi might be X. malinche or another unidentified species (Gutiérrez-Rodríguez et al. 2007).

In this chapter, I assessed phylogeographic variation in these species using mitochondrial

DNA data from additional populations as well as eight microsatellites. The microsatellite data allowed me to include interbreeding as additional criteria for assessing the species status of X. malinche, as well as to re-examine the relationships among the populations of

X. cortezi with nuclear markers.

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Figure I.1. Reconstruction of ancestral states using maximum parsimony and maximum likelihood for the COMPLEX character scorings using the Rauchenberger et al. (1990) phylogeny. Branches are colored based on maximum parsimony reconstruction. Areas of pies indicate relative support for the different ancestor states using maximum likelihood. Likelihood decision threshold was T=2. Asterisk next to pie indicates one or more significant states. ( Ancestral states for female preference for bars: no preference (white), preference for bars (yellow), preference for no bars (red), polymorphism (black), equivocal between polymorphism and preference for bars (hatched). (b) Ancestral states for male response to bars: no response (white), increased aggression towards bars (yellow), decreased aggression towards bars (red), polymorphism of no response and decreased aggression towards bars (black), equivocal (hatched). Figure from Morris et al. (2007).

a b

CHAPTER 1: UNRAVELING THE COMPLEXITIES OF VARIATION IN FEMALE

MATE PREFERENCE FOR VERTICAL BARS IN THE SWORDTAIL,

XIPHOPHORUS CORTEZI

Abstract

Investigations into the nature of mate choice suggest that variation in female mate

preferences is often context-dependent, varying in response to genetic and environmental influences on female condition as well as to external environmental stimuli. Determining whether variation in female mate preference is adaptive requires understanding the variables involved that produce this variation and how they interact. Comparative, multivariate studies of wild-caught adult females can be used as initial assessments of variation in female mate preferences, providing valuable insights into the parameters that influence female preferences under natural conditions. I examined variation in female preferences for the pigment pattern vertical bars across five populations of the swordtail,

Xiphophorus cortezi. The populations I examined are genetically differentiated and varied in the frequency of males and females with bars. I also considered a variable indicative of within-individual variation (size, as influenced by age) and a variable that varies across individuals (genotype for vertical bars: barred or barless). Using Akaike information criterion (AIC), all candidate models explaining variation in strength of preference included female bar state, female size, and population. I suggest that a combination of genetic (bar state) and environmental (female size) conditions influenced

32 how they responded to experience with both male phenotypes in X. cortezi. Future studies should examine the possibility that barred and barless females respond differently over an environmental gradient.

Introduction

Recent research in sexual selection emphasizes the complex nature of female mate preference for male traits (Jennions & Petrie 1997; Widemo & Sæther 1999).

Female preference may vary within a species at the population level (Endler & Houde

1995; Boughman 2001; Simmons et al. 2001; Klappert et al. 2007) and also among and within individuals in a population (Kodric-Brown & Nicoletto 1996, 1997; Cotton et al.

2006b; Parrott et al. 2007). Some studies have been able to identify adaptive advantages to variation in mate preference as well. For example, the cost/benefit ratio of female mate preference may vary with age, as seen in the cockroach, Nauphoeta cinerea. Young females are more fecund than older females, and female choosiness is positively correlated to fecundity (Moore & Moore 2001). In addition, changes in the traits females prefer in the lark bunting, Calamospiza melanocorys, were shown to parallel changes in male traits that best predict female reproductive success across years (Chaine & Lyon

2008). Therefore, to understand the evolution of female preference, variation must be considered to be more than random deviation from optimal preferences.

Models of the evolution of female preference, as well as those that seek to

understand the role of female preference in speciation, depend on assumptions about the

underlying mechanisms behind variation in female mate choice. Using multivariate

analyses to examine several different factors that influence female preference across

different populations makes it possible to identify individual aspects of a female’s

phenotype and/or the environment that explain variation in female preference

(Schlichting & Pigliucci 1998, West-Eberhard 2003). We still know little about the

genetic influences on mate choice (Kokko et al. 2003), which could be due to the lack of

consideration of the nature of context-dependent aspects of mate preference (Cotton et al.

2006b). The heritable aspects of preference variation may remain cryptic if genotypes

respond differently to environmental effects. For example, in Drosophila pseudoobscura,

bristle number is affected by both genotype and temperature (Gupta & Lewontin 1982).

However, bristle number only varies at intermediate temperatures, so an experiment

conducted at an extreme temperature would fail to observe any genetic differences.

Comparative, multivariate studies of the preferences of wild-caught females can identify

traits on which selection may act. These studies can provide the framework for future

controlled laboratory studies designed to study the heritability and evolution of female

preference as a phenotypically plastic trait.

In this study I examined variation in female mate preferences for a pigment

pattern, vertical body bars, across five genetically diverged populations of the swordtail fish, Xiphophorus cortezi (Gutiérrez-Rodríguez et al. 2007). Vertical body bars is a

melanin-based pigment pattern found in many swordtail fish (Rosen 1979;

Rauchenberger et al. 1990), that has been shown to be sexually selected in X. cortezi

(Morris et al. 2003; Moretz 2005). Evidence of a genetic influence on vertical bars in

Xiphophorus species, including X. cortezi, comes from hybrid crosses in which barred X.

cortezi individuals were crossed with barless individuals of another species, producing

primarily intermediate offspring (Atz 1962). In X. cortezi, both males and females are polymorphic for vertical bars (Rauchenberger et al.1990, Fig. 1.1). In addition, as in all northern swordtail species with vertical bars, the barred males and females in X. cortezi can facultatively express their bars by changing the concentration of the melanin within the cell (Zimmerman & Kallman 1988). Barless X. cortezi males are more aggressive and more likely to win male-male contests than barred males when controlling for male body size (Moretz 2005), and both male and female responses to vertical bars has been shown to correlate with an individual’s bar state in the La Conchita population (Moretz &

Morris 2003; Morris et al. 2003). In the current study, I investigated the hypothesis that the two types of females (barred and barless) have similar mating preferences for vertical bars. To determine how variation in female preferences varied, I used an information- theoretical approach (Anderson 2008) which ranks a set of hypotheses in terms of their probability given the data. I considered the parameters female bar state, population (a factor that reflects several differences across the five populations) and female size, and assessed all possible models incorporating subsets of these three variables and their interactions to determine which models best explained variation in female preference for vertical bars.

Methods

Adult males and females were collected using seines and minnow traps in

December 2005 and April 2006 from five populations in the Pánuco River system in

Mexico (Table 1.1). These populations were chosen to represent the full range of genetic

diversity previously identified for this species (Gutiérrez-Rodríguez et al. 2007). Males

from each population were scored for the presence/absence of vertical bars (Fig. 1.1).

Fish were transported to Ohio University and maintained in 208.2-liter communal aquaria

by population on a 12-h light: dark cycle and fed Tetramin flakes daily until satiation.

Females were isolated for at least one week prior to testing in 18.9-liter aquaria and were

all likely pregnant during testing. Swordtails store sperm that remains viable for many

months, so mating and fertilization need not be coordinated (Farr 1989).

Female mate preference for vertical bars was assessed for five populations (see

Table 1.1 for sample sizes and mean SL of females tested). For Arroyo La Conchita, I combined the data for nine females collected in the current study with the data for 10 females from the same locality tested by Morris et al. (2003). I assessed female association preferences from September 2006-June 2007 with video animations created using Lightwave 3D version 5.6 (Newtek). The animations were created from a scanned image of one male X. cortezi with eight vertical bars on each side. The number of bars on each side of barred males can range from 1-12 in these populations. A previous study of

Arroyo La Conchita found an average of 6.8 bars on each side, with a range from 1-9

bars on each side of a male (Morris et al. 2001). The barless animation was created by

removing the bars from the same image using the rubber stamp tool in Photoshop 5.0

(Adobe Systems, Inc.) by replacing the bars with the fish’s skin adjacent to each bar (see

Morris et al. 2003 for more information on animation design). Previous experiments examining female preferences in Xiphophorus have used video animations successfully

(e.g., Rosenthal et al. 1996; Trainor & Basolo 2000; Morris et al. 2003, 2007; Fisher &

Rosenthal 2007). Using video animations as stimuli is beneficial in that I can control for

other morphological and behavioral differences between males other than vertical bars. A

previous study demonstrated a preference for vertical bars in X. cortezi using numerous

different pairs of live males as stimuli (Morris et al. 2001). However, as I was interested in examining variation in this preference both across and within populations in this study, rather than demonstrating the existence of the preference, I used only one pair of video animations to provide a more consistent stimulus. Animations have been previously shown to produce the same preferences as live males in X. cortezi (Morris et al. 2003). In addition, association times as a measure of preferences have been evaluated and found to be a good predictor of mate choice in nature for X. multilineatus (Morris et al. 2010) and have been used to assess mate choice in other swordtails and livebearing fishes (e.g.,

Bisazza et al. 2001; Cummings & Mollaghan 2006).

Females (N=73, for population information see Table 1.1) were allowed to simultaneously choose between an animation of a barless male and an animation of a male with eight bars on both sides. The video animations show the male swimming in a

normal manner. Preference tests were conducted between 0800 and 1400 in a 37.9-liter

aquarium that was divided by two lines into three equal compartments. The length of the aquarium was covered by cardboard to reduce reflection. On each end of the aquarium, a white plastic divider was placed between the high definition video monitor and aquarium.

Each video monitor was attached to a separate DVD player. The animations were randomly assigned to a video monitor. A mirror placed above the aquarium was used to observe the female. The female was placed in a clear Plexiglas tube in the center compartment to acclimate for 10 min prior to testing. After 10 min, I removed the white plastic dividers and played the animations. The female first observed the monitors without the males for 180 s and then observed the monitors with the animations for 60 s prior to being released from the acclimation chamber. Upon release from the acclimation chamber, the female’s association preference for the animations was assessed for 510 s.

The preference test was repeated with the animations switched (end to end) to control for side bias. Strength of preference (SOP) was measured as the difference between the amounts of time a female spent with each animation. A female was scored as having a side bias when she spent less than 10 s on each side of the testing aquarium when added across the two trials. Females with side biases were retested after 7-14 days. Females that had two side biased tests (N = 4) were not included in the analysis.

All females included in the analysis were tested twice using the same stimuli (7-

14 days between tests). The difference between the amounts of time a female spent with each animation (barred versus barless) was used as an indicator of her strength of

preference (SOP), with positive values indicating an overall preference for the barred animation. Total association time for the combined stimuli (barred + barless) was not significantly different across populations (F4,68=0.945, P=0.444), suggesting that strength

of response was not influencing this measure of preference. As SOP was not significantly

different between the first and second preference tests (Paired t-test: Chapulhuacanito:

t20=0.213, P=0.834, San Martin: t11=-0.178, P=0.862, Tanute: t7=-0.532, P=0.611,

Tecolutlo: t12=-0.009, P=0.993), the amount of time the female spent with each video across both tests was summed to obtain a better estimate of female preferences. Given that I did not expect all of the females to have a preference, I did not examine repeatability; individuals that lack preferences will not be consistent in the time they associate with a stimulus across time (Gabor & Aspbury 2008). Vertical bars are facultatively expressed in both males and females. When vertical bars are not expressed,

they are still visible on males, but rarely remain visible on females. Therefore, females

were anaesthetized with tricaine methane sulfoanate (MS222) to assess female bar state

by inducing bar expression and to measure standard length (SL) after completion of the

second preference test. Females were scored as either barred or barless.

Statistical Analyses

I used Akaike’s Information Criterion (AIC) to determine the most parsimonious

model for explaining variation in female SOP (Akaike 1974). AIC selects models by

weighting residual error of each model against the number of factors in the model. This is

39 especially powerful for factor reduction given that more factors often explain more variation. While its use in behavioral ecology has so far been limited (but see Garamszegi et al. 2009), the use of AIC in biological studies is widespread (Anderson 2008). I assessed the parameters female bar state (barred/barless), population and female SL

(covariate), as well as all interaction terms. I treated population as a fixed factor because I was interested in any potential influences on SOP due to differences across populations.

Because all models could be biologically relevant, I tested all possible models as well as the null model. To calculate AIC, I obtained the residual sums of squares (SSE) using general linear models. Since some models included many parameters (K), relative to sample size (n), I calculated AIC corrected for small sample sizes (Anderson et al. 2000):

AICc= n(ln(SSE/n)+ 2K(n/n-K-1)

The model with the minimum AIC was considered to have the highest probability given the data (Anderson et al. 2000). Models were ranked using AICc, ∆AICc, and AIC weights (wi); (Anderson et al. 2000). Models with ∆AICc<2 are presented since models with a lower ∆AICc are more likely to be biologically significant and therefore are considered competing models. In addition, models with a higher wi are more likely to be biologically significant relative to other models considered (Anderson et al. 2000).

Competing models are models that include parameters that should be considered for explaining the variation in preference (Anderson et al. 2000). Further analyses of the parameters that were selected by the models were conducted to provide insights into their

specific influences on SOP. I used a one-paired t-test to assess female preferences in

barred and barless females. I used ANOVA to assess whether female SL differed across

populations and bar states. Given the possible interactions with female SL, I used linear

regression to explore how female SL and SOP varies within each group. I used chi-square

goodness of fit test to examine whether the frequency of barred males varied across

populations. I used Spearman rank correlation to examine the relationship between mean

female SOP and the frequency of barred males. Alpha was set at 0.05 and all tests were

two-tailed. These analyses were performed using SPSS 14.0 (SPSS Inc., Chicago, IL,

U.S.A.). The assumptions for each test were met.

Results

There are three competing models with ∆AICc<2 and high wi. All three models

included the parameters female bar state, population, and SL (Table 1.2). The model that

best explained variation in female SOP (highest wi) only included these three parameters.

The other two competing models also included interactions between female SL and population, and one competing model included an interaction between female SL and bar

state (Table 1.2). The interaction between female bar state and population would have

been difficult to detect in my dataset as I did not have barless females from one of the populations to test.

The influence of the individual parameters on SOP can be visualized in Fig. 1.2.

However, given that it is a multivariate analysis, this figure is a simplification of how

these parameters influenced female preference. Barred females had a stronger SOP than

barless females for the barred male (Fig. 1.2a). The SOP of barred females was

significantly different from zero (One sample t-test: t47=3.75, P<0.001). Barless females

did not have a significant SOP for vertical bars (One sample t-test: t24=1.49, P=0.151). Of the populations tested, females from Tecolutlo had the lowest strength of preference (Fig.

1.2b). Female SL did not differ by population (ANOVA: F4,64=1.66, P=0.171, Table 1.1) or female bar state (ANOVA: F1,64=2.27, P=0.137). However, in two populations there

was a negative relationship between female SL and SOP for bars (linear regression: La

Conchita: F1,17=10.35, P=0.005; Tecolutlo: F1,11=9.72, P=0.010, Fig. 1.2c). There was

also a negative relationship between female SL and SOP in barred females (linear

regression: F1,46=3.84, P=0.056, Fig. 1.2d), but this relationship was not significant in

barless females (linear regression: F1,23=1.57, P=0.223,Fig. 1.2d).

The frequency of barred males varied across populations (Chi-square test:

X2=10.150, P<0.025; Table 1.1). However, I detected no significant relationship between

female SOP and the frequency of barred males (Spearman correlation: Rho=0.400,

Z=0.800, P=0.424).

Discussion

Female mate preference for vertical bars in Xiphophorus cortezi is quite complex, varying over the lifetime of females (as indicated by female size), across individuals within a population (bar state), and across populations. All of the candidate AIC models included female bar state, female size, and population, and two of the competing models also included interactions between female size and female bar state as well as female size and population. Examining the preferences of wild-caught females in the context of information theory has provided us with a more realistic model of the complexity of this preference. I hypothesize that variation in female preference for barred males is explained in part by variation in female experience with and responses to the more aggressive barless males (Moretz 2005). The influence of female bar state and, to some extent female size, on female preference for the bars support this hypothesis. The effect of population on this preference could reflect the genetic differentiation of the Tecolutlo population (weaker preference for bars) although female preference is also likely affected by environmental differences such as reduced prior experience with barless males (no barless adult males were collected at this site). Below, I discuss how this hypothesis could be explained by each of the parameters in the candidate models, as well the experiments that will be necessary to rule out alternative hypotheses.

I detected a significant preference for males with vertical bars by barred females but not by barless females. The relationship between bar state and response to the bars I detected in females is similar to the response that has been detected in X. cortezi males:

barred males have a response to the bars while barless males do not (Moretz & Morris

2003). I hypothesize that the proximate mechanism for the relationship between an

individual’s bar genotype and their response to bars has to do with the association

between bar state and aggression. Barless males are more aggressive than barred males

during male contests and in response to their own mirror image. Barred males also respond to barred males with reduced aggression, while barless males are equally

aggressive towards both barred and barless males and are more likely to win male contests (Moretz 2005). Specifically I hypothesize that the female preference for barred males by barred females may reflect a general preference for less aggressive males.

While the animations did not differ in behavior, females that have interacted with both types of males may associate the two male phenotypes with differences in aggression. If female aggressive behavior also is correlated with bar state (as is true for males), the weaker preference for barred males by barless females could suggest that interacting with barless males may be less costly for barless females. The lower mating costs would suggest that barless females would not need to discriminate as much as barred females in their mating preferences. A relationship between female preference for a trait and female expression of that trait was also detected in stalk-eyed flies, Diasemopsis meigenii, where female SOP for male eyespan varies with female eyespan (Hingle et al. 2001; Cotton et al. 2006a). It has been hypothesized that the proximate mechanism for this relationship is the association between female eyespan and visual acuity: females with larger eyespans are better able to distinguish between differences in male eyespan (Hingle et al. 2001;

Cotton et al. 2006a). While our knowledge of the X. cortezi system indicates that the

relationship between male aggression and vertical bar state may explain this preference,

other factors may also result in the difference in preference between barred and barless

females.

Even though the overall relationship between female bar state and preference

suggests that barred females have a stronger preference than barless females, the SOP for

vertical bars was weakest in the Tecolutlo population in which all wild-caught adults

(both males and females) possessed vertical bars. While I did not collect barless

individuals at Tecolutlo, barless individuals could occur at a low frequency in this

population. Therefore, one possible explanation for the weak preference for bars at

Tecolutlo (even though all females tested had bars) is that females need to experience

sufficient variation in male ornament expression to efficiently use that ornament as a cue

(reviewed in Candolin 2003). For example, female guppies, Poecilia reticulata, do not discriminate between differences in orange coloration when reared with males that vary little in coloration (Rosenqvist & Houde 1997). However, when reared with males with greater differences in orange coloration, females prefer males with more orange. Even though I did not detect an interaction between female bar state and population, I wouldn’t expect to find this interaction as there were no barless females to test from this population. If experience differentially affects female preferences, then I would predict this interaction if there were both barred and barless females, but only barred males, in the Tecolutlo population. The population from Tecolutlo is more genetically diverged than the other populations of X. cortezi tested in this study (Gutiérrez-Rodríguez et al.

2007). Therefore, female preferences in the Tecolutlo population also could be more

genetically diverged than the other populations.

A future study could test the hypothesis that the frequency of barless males

influences SOP through the experience with both types of males by testing the preference

of these populations over time, as the frequency of barred males is likely to vary over

time as well as across populations. While I did not detect a relationship between the

frequency of bars and female SOP across populations, my sample only included five

populations and of those populations, only the Tecolutlo population had a low frequency

of barless males. Examining this relationship within a population over time could better

elucidate this relationship, given the other environmental and genetic differences across

populations. Differences in the frequency of barred males across populations may result

from ecological factors selecting against different male phenotypes (e.g. predation),

although these ecological factors have not been assessed. In the poeciliid Phalloceros

caudimaculatus, vertical bars are associated with emergent vegetation and may conceal fish (Endler 1982). While this study suggests that vertical bars may function in crypticity,

bars may not consistently function in crypsis across species and environments. Given the

clear blue waters in which many swordtail species are found and the use of vertical bars

in communication, it has been hypothesized that the original function of the bars in swordtails was to increase conspicuousness (Morris et al. 2007).

Preference for less aggressive males could also explain the relationship between

female size and preference for bars, as well as the interaction between female size and bar

state that was included in one of the competing AIC models. Interacting with barless males may be less costly to larger females. Females continue to grow after they reach maturity (Kallman 1989; Marcus & McCune 1999), and larger, older females may be more experienced as well as better able to deal with aggressive males than smaller females. The relationship between SOP and female size may differ depending on female bar state, as suggested by the inclusion of an interaction term between female size and bar state in one of the candidate models. Many other studies have found that females prefer less aggressive male phenotypes (Arnqvist & Rowe 2005). For example in the newt,

Euproctus asper, females prefer smaller males (Poschadel et al. 2007), and larger male newts are more aggressive and exhibit coercive mating behavior. In addition to costs of mating with aggressive males, different preferences by larger females could suggest that these females gain benefits by mating with barless males. For example, females that mate with aggressive barless males may produce male offspring that are more aggressive and therefore more likely to win male-male contests (Moretz 2005). Laboratory studies which examine whether female aggression varies by size and bar state, as well as whether the behaviors of barless versus barred males differ when interacting with females, will help to elucidate how these variables interact to produce variation in female preferences for vertical bars.

An interaction between female size and population in some models suggests that the relationship between female size and SOP for barred males may not be consistent across populations. Indeed a significant negative relationship between female SOP for barred males and female size was only detected in two populations, one population with both barred and barless individuals (La Conchita) as well as in the population where I found no barless individuals (Tecolutlo). Therefore, extensive experience with barless males does not seem to be necessary to produce this relationship. At this time I can only speculate on why I detected a relationship between female size and SOP in some populations and not others. On the one hand, this result suggests that the hypothesis about the need for experience with barless males to develop a preference for barred males may be incorrect. However, another possibility is that the relationship between female size and the SOP for barred males is due to two preferences: one for less aggressive barred males

(which requires experience with both types of males) and one for more “visible” males

(which does not require experience with both types of males). In both cases, stronger selection on smaller females to reduce mating costs could produce the relationship between SOP and preference for barred males, but the strength of the overall preference would be stronger when both preferences were present. A relationship between female size and SOP for other male traits has been detected in swordtail fishes (male size, Rios-

Cardenas et al. 2007, bar number symmetry, Morris et al. 2006), and suggests that this relationship may reflect a component to SOP that is based on general preferences for more “detectable” males based on female size, in addition to preferences for males with specific traits. Environmental differences across populations that influence female

condition could explain why the relationship between size and SOP was not detected in

all the populations. There is a clear link between female condition and female preferences in many systems (reviewed in Jennions & Petrie 1997; Cotton et al. 2006b). Selection

pressures on body size may also vary across populations based on predation, temperature,

competition with other species, and food availability (e.g., Trexler & Travis 1990;

Trexler et al. 1990; Basolo & Wagner 2004; Rios-Cardenas et al. 2007; Basolo 2008).

Clearly further study of the relationship between size and preference across conditions

are needed to understand why size produces variation in female mate preference.

Based on the factors I examined in this study, I propose that female X. cortezi

have context-dependent mating preferences for the pigment pattern vertical bars. Whether or not a female has bars influences the degree to which her size and experience with barless males influences her preference for males with bars. In this study, females were collected from natural populations where their previous social and sexual experiences were unknown, but which I assume reflects experiences common to females in these contexts. Future studies may uncover additional genetic or environmental influences that explain more of the variation in female preferences. Finally, as the context-dependent nature of the female response can make detecting a genetic component to variation difficult (West-Eberhard 2003), studies of the heritability of female preferences must follow the same caveats as heritability studies of other plastic traits by considering

heritability as a context specific measure. Failure to detect heritability of preferences

within specific contexts does not exclude a genetic influence on female preference. To

49 examine the heritability of response to the bars, it will be important to test SOP across a range of environmental contexts, including social contexts such as aggression.

When examining female mate preference, it is now clear that variation within a species and even within females cannot be ignored. Identifying the different factors that influence female preference is essential to our understanding of the evolution of female preferences. I suggest that aspects of a female’s phenotype influenced how she responded to vertical bars. Future studies should investigate the prospect that different genotypes respond differently to environmental conditions (including social environments) using controlled laboratory studies. If different female genotypes produce different female preferences across environments, the hypothesis about the variation in female preference for vertical bars fits with the concept of different reaction norms for barred and barless females (West-Eberhard 2003) and provides a framework in which to study the evolution of this preference. I propose that studies such as this one which examine a combination of differences across wild-caught females and natural environments in the context an information-theoretical analysis make it possible not only to uncover the best models for explaining the complexities of adaptive variation in female mate preference, but will help us gain a better understanding of how female preferences evolve.

Acknowledgements

I would like to thank A.A. Fernandez, M.S. Tudor and O. Rios-Cardenas for

collecting fish, S. Lyons for fish maintenance, T.R. Beham, J. Bauerschmidt, S. Conaster

and K. Kovar for assistance with choice tests and L.M. Bono, J. Brewer, and M.S.

Lattanzio for constructive comments on the manuscript. I thank the Republic of Mexico

for collection permits. All experiments comply with current laws and with the Animal

Care Guidelines of Ohio University (Animal Care and Use Protocol No. L01-01).

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Table 1.1. Populations of Xiphophorus cortezi tested from female SOP for vertical bars Location Males collected Females tested

SL (mm) % SL (mm) % SOP (seconds) Population Drainage N W N (mean + SE) barred N (mean + SE) barred mean +SE) Chapulhuacanito Tempoal 21.20607 98.66922 23 38.7 + 0.81 78 21 42.3 + 0.63 52 448.19 + 168.77 La Conchita Moctezuma 21.55833 98.98867 62 39.3 + 0.17 48 19 42.7 + 0.81 47 380.79 + 233.33 San Martín Tempoal 21.36955 98.65905 37 37.7 + 0.58 54 12 44.7 + 0.86 83 658.08 + 221.83 Tanute Tampaón 21.6520599.03545 44 35.0 + 0.81 64 8 43.8 + 1.11 63 567.38 + 202.19 Tecolutlo Tempoal 21.1211798.46792 20 39.3 + 0.80 100 13 42.1 + 0.63 100 -64.54 + 167.28 SL=standard length SOP=strength of preference

Table 1.2. Models for female SOP. Models are ranked in order of support by Akaike’s Information Criterion. Only the first three models have ∆AICc < 2 and are candidate models. Additional models and the null model are shown for comparison.

Model SSE K AICc ∆AICc wi Bars + population + female SL 36360730 8 975.90 0.00 0.26

Bars +population + female SL + population x SL 31454697 12 976.27 0.37 0.22

Bars + population + female SL + population x SL + 30360851 13 976.66 0.76 0.18 bars x SL Bars + population + female SL + bars x SL 36100250 9 977.99 2.08 0.09

Population + female SL + population x SL 34185172 11 979.48 3.57 0.04

Population + female SL 39875044 7 980.11 4.21 0.03

Intercept (null model) 47604786 2 981.49 5.59 0.02

∆AICc= model AICc - AICmin SSE Residual sums of squares from general linear model K Number of parameters included in model

AICc Akaike’s Information Criterion corrected for small sample size

wi AIC weights

a b

c d

Figure 1.1. Male and female Xiphophorus cortezi are polymorphic for the pigment pattern vertical body bars: (a) Barless male, (b) barred male, (c) barless female and (d) barred female.

Figure 1.2. Parameters selected by candidate models for female SOP for vertical bars in Xiphophorus cortezi. (a) Mean SOP by female bar state (barred females N=48, barless females N=25). (b) Mean SOP by population. Error bars indicate standard error. Relationship between female size and SOP by (c) population and (d) female bar state.

CHAPTER 2: FEMALE PREFERENCE PLASTICITY IN XIPHOPHORUS CORTEZI

Abstract

Historically, variation in mating preference was assumed to be non-adaptive or without genetic basis, and therefore often a factor to be controlled. However, natural selection can select for plastic mate preferences in response to varying environments, including social environments. In this study, I examined the influence of social experience on the mating preferences of females from two genetically diverged populations of the swordtail Xiphophorus cortezi. In one population, males are polymorphic for the pigment pattern vertical bars and females prefer males with bars, while in the other population, barless males are rare and females do not have a preference based on this pigment pattern. I also examined whether barred and barless males differed in the behaviors they directed towards females. Previous studies indicate that barless males are more aggressive than barred males during male-male contests. In this study, I found that barless males were also more aggressive toward females, and suggest that these behavioral differences could explain how experience influenced female preferences.

Female preferences for vertical bars differed significantly with experience (barred males only, or both barred and barless males), and the effect of experience varied by population, suggesting a genetic component to variation in this preference. There was also a significant influence of female growth on female preferences. Female strength of preference for vertical bars decreased with growth when females experienced both types

of males, the social situation when barred males are the less aggressive phenotype.

However, female strength of preferences increased with growth when females

experienced only barred males, and males with bars turned off more often are the less

aggressive of the barred males in this social situation. The difference between the populations in their response to experience cannot easily be explained by maternal

effects, and suggests that there has been selection in the population with the more

aggressive barless males to have a more plastic female preference in relation to cues that

indicate aggressive males.

Introduction

Phenotypic plasticity has been widely investigated as a mechanism for adaptive

responses to variable stimuli in the fields of gene expression, developmental biology,

morphology and life history (e.g., Schlichting & Smith 2002; West-Eberhard 2003;

Jackson & Chen 2010; Pfennig et al. 2010). Less studied is the potential for adaptive phenotypic plasticity in female mate preferences (but see Godwin 2010; Stillwell et al.

2010). Female preferences can respond to environmental variables (Jennions & Petrie

1997; Cotton et al. 2006). Environmental effects on development, such as food availability, have been demonstrated to affect mate preference (e.g. Burley & Foster

2006; Fisher & Rosenthal 2006; Hebets et al. 2008; Fox & Moya-Lorano 2009; reviewed in Hunt et al. 2005). Light environment, predation, and parasitism also significantly

affect female mate preferences (e.g., Hamilton & Zuk 1982; Endler & Houde 1995;

Cornwallis & Uller 2010; Fuller & Noa 2010).

Sexual selection theory will benefit from additional studies investigating adaptive

variation in mate preferences in response to different social environments (Jennions &

Petrie 1997; Cotton et al. 2006). If females adopt different strategies for choosing mates

depending on the male phenotypes available (e.g., Real 1990; Wiegmann et al. 1996;

Alonzo & Sinervo 2001), then preferences are likely to vary depending on available males as well. Several studies indicate that learning familiar male phenotypes within a population can prevent mismatings with heterospecific males, reduce the likelihood of aggressive encounters with unfamiliar males, and increase offspring success in cooperative mating systems (e.g., Endler & Houde 1995; Parker et al. 2001; Randall et al.

2002; White et al. 2007). For example, early experience with males has been shown to imprint preferences for familiar male phenotypes (e.g., Freeberg 1996; Plenge et al. 2000;

Riebel 2009; Arnold & Taborsky 2010). However, sometimes females prefer novel or rare males, which could function to increase the genetic diversity of their offspring (e.g.,

Kokko et al. 2007; Zajitschek & Brooks 2008; Gershman 2009; Rutledge et al. 2010). If male relative fitness also varies based on the phenotypic composition of the social environment, and females are incorporating indirect benefits into mate choice decisions, then females should use context-dependent mate choice strategies to choose the fittest males in a particular social environment.

The direct costs and benefits of interacting with a potential mate could also vary

relative to phenotypic composition of the social environment. Winners of male-male

contests will depend on the phenotypes of the males present, and yet females prefer

winners in several species as it could indicate good genes or high quality territories

(reviewed in Andersson 1994; Berglund et al. 1996). Females have also been shown to avoid winners of male-male contests when the direct costs of interacting with aggressive

males outweigh the potential benefits of mating with competitively superior males

(reviewed in Qvarstrom & Forsgren 1998; Arnqvist & Rowe 2005). For example, in

Japanese quail, Coturnix japonica, sexually inexperienced females prefer more

aggressive males while experienced females switch their preferences to less aggressive

male phenotypes. The switch in preferences suggests that interacting with these males

may be harmful to females and females learn to avoid them (Ophir & Galef 2004). Males with costly traits can reduce female fitness by increasing female mating rate beyond

optimum, reducing foraging time, increasing conspicuousness to predators and causing

physical injury to females (reviewed in Arnqvist & Rowe 2005).

The effects of social environment on female preference can be difficult to

quantify. Female experiences within a population can vary with age, but experiences also

can vary with other differences in female phenotype (Jennions & Petrie 1997; Cotton et al. 2006). For example, females with higher fecundity may have increased male attention and therefore gain more private information about potential mates. Females also gain public information for mate preferences by observing other individuals’ behaviors,

64 especially male-male interactions and the mate choice decisions of older females (Dall et al. 2005; Kendal et al. 2005; Gruter et al. 2010). Different female phenotypes may incorporate the same information differently for mate choice decisions. For example, females with access to higher quality mates should be choosier in their preferences (Sih et al. 2009). To correctly assess effects of social environment on female preferences, both the social environment and variation in female phenotypes must be carefully considered.

Female preferences differ across populations for the pigment pattern vertical body bars in the swordtail fish, Xiphophorus cortezi. Population level preferences could be the result of differences in female experience due to variation in the frequency of barred to barless males (Robinson & Morris 2010, Chapter 1) and genetic differences across populations (Gutiérrez-Rodriguez et al. 2007, Chapter 5). Male behavioral differences may affect female preferences within populations: barless X. cortezi males are more aggressive and more likely to win male-male contests than barred males when controlling for male body size (Moretz 2005) and both male and female responses to vertical bars have been shown to correlate with an individual’s bar state (Moretz & Morris 2003;

Morris et al. 2003; Robinson & Morris 2010 (Chapter 1)). Female preferences vary in some populations by female size, a phenotype that changes throughout the lifetime of a female as females continue to grow (Robinson & Morris 2010 (Chapter 1)). Larger, older females may be more experienced as well as better able to deal with aggressive males than smaller females.

Vertical body bars is a melanin-based pigment pattern found in many swordtail fish (Rauchenberger et al. 1990; Rosen 1979), that has been shown to be sexually selected in X. cortezi (Moretz 2005; Morris et al. 2003). Evidence of a genetic influence on vertical bars in Xiphophorus species, including X. cortezi, comes from hybrid crosses in which barred X. cortezi individuals were crossed with barless individuals of another

species, producing primarily intermediate offspring (Atz 1962). In X. cortezi, both males

and females are polymorphic for vertical bars (Rauchenberger et al.1990). In addition, as

in all northern swordtail species with vertical bars, the barred males and females in X. cortezi can facultatively express their bars by changing the concentration of the melanin within the cell (Zimmerman & Kallman 1988).

In this study, I tested whether experience affects female mate preferences for the pigment pattern vertical body bars in the swordtail, Xiphophorus cortezi. I manipulated

the experience of virgin females from two populations, San Martin and Tecolutlo, from

the Sierra Madres in Mexico. I chose to examine these populations because they are

genetically different (Gutiérrez-Rodriguez et al. 2007), and because wild-caught females

from these populations differ in the frequency of barred to barless males they have

experienced (Robinson & Morris 2010 (Chapter 1)). While most populations of X. cortezi

have both barred and barless males, the Tecolutlo population either does not have barless

males or has them at a very low frequency (Robinson & Morris 2010 (Chapter 1)). Wild-

caught females from these populations also vary in female preferences: females from San

Martin have an overall preference for barred males, while females from Tecolutlo have

no overall preference (Robinson & Morris 2010 (Chapter 1)). Females may need

experience with both phenotypes to have a preference for vertical bars. Since barless males are more aggressive than barred males, it is possible that female X. cortezi avoid

aggressive males and prefer barred males only when experiencing both phenotypes. I was

also interested in quantifying the potential costs to females of interacting with barred

versus barless males. To quantify the potential costs, I measured female growth during

the experience treatments. Since female swordtails continue to grow after sexual

maturity, slower growth rates could reflect reduced foraging as well as increased energy

expenditure toward social interactions and reproduction. Although differences in male

aggression between barred and barless males have been previously quantified (Moretz

2005; Moretz & Morris 2003), I further investigated variation in male behavior during

male-female interactions.

Methods

After collection, fish were transported to Ohio University and maintained in 38-

liter communal tanks by population on a 13:11-h light: dark cycle, fed Tetramin flakes

daily until satiation and supplemented twice weekly with brine shrimp or bloodworms.

Analyses were performed using SPSS 17.0 (SPSS Inc., Chicago, IL, U.S.A.) and JMP

version 8.0 (SAS Institute Inc., Cary, NC, U.S.A.). All tests were two-tailed and alpha set

to 0.05. The assumptions for each test were met.

Experiment 1-Manipulating Female Social Environment

Fish Collection and Maintenance

Adult females were collected using seines and minnow traps in April 2006 and

December 2008 from the San Martin (21.36955oN, 98.65905oW) and Tecolutlo

(21.12117oN, 98.46792oW) populations in the Pánuco River system in Mexico. Tanks contained either dividers or the aquarium plant Vesicularia dubyana for fry to hide. Each tank was checked daily for fry. When fry were discovered, adults were moved to another tank.

Fry were never moved in the first month, as young fry can be harmed by nets and can be easily missed. After 1 month, fry were spaced out among tanks (1-4 per tank) to promote growth. Fry tanks were checked once a week for maturing fish, and juvenile males were removed at the first visible stages of gonopodium development (i.e., a visible concentration of anal fin rays). Females were also removed once they reached sexual maturity (indicated by the formation of a brood spot, Meffe & Snelson 1989; Morris &

Ryan 1992) and placed in single-sex communal tanks by population. Fry and virgin tanks were visually isolated from adult tanks to prevent observations of adult interactions.

Therefore, virgin females used in this study had no experience with adult sexual interactions.

Male X. cortezi were collected from La Cebolla, Mexico (21.39120oN,

98.99808oW) in March 2009 for use as stimulus males. I used males from La Cebolla to standardize experience with a foreign male population across the populations of females.

Males from the Tecolutlo population could not be used as stimuli in this study since there are no/few barless males at Tecolutlo.

Experience Treatments

Communal tanks of six females and six males were used to examine how experience with different frequency of barred and barless males influenced female mate preference for this trait. Using communal tanks (rather than one on one interaction with males) is a more natural setting to test effects of experience on female preferences, providing females not only experience with males, but also the opportunity to eavesdrop on male competitive interactions and on male courtship behaviors with other females.

Experience treatments occurred from January 2009-March 2010. Females from each population (San Martin and Tecolutlo) experienced one of two treatments for 30 days. Due to the number of maturing females available, I was limited to two treatments.

In the first treatment (“barred treatment”), females experienced only barred male X. cortezi, which is similar to the experience of wild-caught females from Tecolutlo (100% of males collected were barred (Robinson & Morris 2010 (Chapter 1)). In the second treatment (“mixed treatment”), females experienced both barred (N = 3) and barless (N =

3) males. This frequency of barred to barless males is similar to what of wild-caught

females from San Martin experience (54% of males collected were barred, Robinson &

Morris 2010 (Chapter 1)). Stimulus males were sometimes reused across tanks, but the

same six males from one tank were never reused together.

Except for male bar state, other aspects of the tank environment were consistent

between the two treatments. These tanks were 208 l, visually isolated from other tanks,

and contained several plastic plants and the aquarium plant Vesicularia dubyana to

produce spatial heterogeneity in the tank. There were three replicate tanks per population

for each treatment for a total of six tanks per population and twelve tanks total (N = 72 females). Female size (standard length, SL) was measured at the beginning and end of the

30 day experience treatment. Females were approximately the same age and had reached sexual maturity for each treatment. Prior to experience, females from San Martin were larger than females from Tecolutlo (X + SE: San Martin: 30.51 + 0.11, Tecolutlo 27.66 +

0.39; ANOVA: F1,69 = 13.93, P<0.001). However, averaged across populations, female

size did not differ across experience treatments (X + SE: barred: 30.09 + 0.54, mixed:

28.72 + 0.62; ANOVA: F1,69 = 0.911, P = 0.343). The size of the stimulus males did not

differ for the two different populations of female tested, by experience treatments, or by

male bar state (X + SE, range: 37.68 + 0.61, 29.48 - 49.38; ANOVA: female population:

F1,68 < 0.001, P = 0.996, experience treatment: F1,68 = 0.712, P = 0.402, male bar state:

F1,68 = 0.342, P = 0.561).

Female Growth

Female growth during the experience treatments may be an indicator of costs to females of associating with different types of males. Female growth was calculated from the residuals of the log-log regression of female SL before experience and female SL after experience. Thus, females with positive residuals grew more relative to their body size and females with negative residuals grew less relative to their body size. Variation in female growth was analyzed using ANOVA with female population and experience treatment as fixed factors, an interaction between female population and experience treatment, and tank nested in treatment as a random factor.

Female Preference Tests

After the 30 day experience treatment, females were isolated into 19-l tanks for 7-

14 days before being tested for preferences for vertical bars. I assessed female mate preferences by measuring the time females associated with two different video animations created using Lightwave 3D version 5.6 (Newtek). The animations were created from a scanned image of one male X. cortezi with eight vertical bars on each side.

The number of bars on barred males can range from 1-12 on each side in these populations. A previous study of Arroyo La Conchita found an average of 6.8 bars on each side, with a range from 1-9 bars on each side of a male (Morris et al. 2001). The video animations used in this study are the same animations that have been used

successfully in previous studies of Xiphophorus cortezi (Morris et al. 2003, Robinson &

Morris 2010 (Chapter 1)). Using video animations as stimuli is beneficial in that I can

control for other morphological and behavioral differences between males other than

vertical bars.

Females were allowed to simultaneously choose between an animation of a barless male and an animation of a male with eight bars on both sides. The video

animations show the male swimming in a normal manner. Preference tests were

conducted between 0800 and 1400 in a 38-liter aquarium that was divided by two lines

into three equal compartments. The length of the aquarium was covered by cardboard to reduce reflection. On each end of the aquarium, a white plastic divider was placed between the high definition video monitor and aquarium. Each video monitor was attached to a separate DVD player. The animations were randomly assigned to a video monitor. A mirror placed above the aquarium was used to observe the female. The female was placed in a clear Plexiglas tube in the center compartment to acclimate for 10 min prior to testing. After 10 min, I removed the white plastic dividers and played the animations. The female first observed the monitors without the males for 180 s and then observed the monitors with the animations for 60 s prior to being released from the acclimation chamber. Upon release from the acclimation chamber, the female’s mate preference for the animations was assessed for 510 s. The preference test was repeated with the animations switched (end to end) to control for side bias. Strength of preference

(SOP) was measured as the difference between the amounts of time a female spent with

each animation. A female was scored as having a side bias when she spent less than 10 s

on each side of the testing aquarium when added across the two trials. Females with side

biases were retested after 7-14 days. Females that had two side biased tests (N = 3) were

not included in the analysis. All females included in the analysis were tested twice using

the same stimuli (7-14 days between tests).

Analysis of Strength of Preference

Total association time for the combined stimuli (barred + barless) was not

significantly different across populations or treatments (ANOVA: female population:

F1,66 = 0.15, P = 0.697, experience treatment: F1,66 = 0.01, P = 0.907), suggesting that

strength of response was not influencing our measure of preference. As SOP was not

significantly different between the first and second preference tests (paired t test: t68 =

0.67, P = 0.503), the amount of time the female spent with each video across both tests was summed to obtain a better estimate of female preferences. Association times as a measure of preferences have been evaluated and found to be a good predictor of mate choice in nature for X. multilineatus (Morris et al. 2010) and has been used to assess mate choice in other swordtails and livebearing fishes (e.g., Bisazza et al. 2001; Cummings &

Mollaghan 2006). Given that I did not expect all of the females to have a preference, I did not examine repeatability; individuals that lack preferences will not be consistent in the time they associate with a stimulus across time (Gabor & Aspbury 2008).

I used Akaike information Criterion (AIC) to find the best model to explain

variation in female strength of preference for vertical body bars. Previous studies have indicated that female population and size can affect female SOP for vertical bars

(Robinson & Morris 2010 (Chapter 1)). Therefore, in addition to the effects of experience, I considered female population and size when examining female SOP. I was also interested in determining whether female growth during the treatments would affect female preferences. And finally, since females within tanks had experienced the same group of males, I also considered tank as a random factor nested in treatment. I also used

Akaike information Criterion (AIC) to compare different measures of female size to

include in the analysis (female SL before experience, female SL after experience, female

growth, or no measure of size) and to determine whether I should include tank nested in

treatment as a random factor (Akaike 1974).

AIC selects models by weighting residual error of each model against the number

of parameters in the model. This is especially powerful for model comparison and variable reduction given that more variables often explain more variation. While its use in behavioral ecology has so far been limited (but see Garamszegi et al. 2009), the use of

AIC in biological studies is widespread (Anderson 2008). All models included experience

treatment (barred or mixed) and female population (Tecolutlo or San Martin). All

possible interaction terms were included in each model, with the exception of tank nested in treatment (interactions with this variable would be redundant since each tank had only

one experience treatment and female population). The intercept (null model) was also

included for comparison. Since some models included many parameters (K), relative to

sample size (N), I used AIC corrected for small sample sizes (Anderson et al. 2000): AICc

= 2k – 2 ln (likelihood) + (2k (k+1)) / (N -k – 1). The model with the minimum AIC was considered to have the highest probability given the data (Anderson et al. 2000). Models

were ranked using AICc, ∆AICc, and AIC weights (wi) (Anderson et al. 2000). Models with ∆AICc < 2 are presented since models with a lower ∆AICc are more likely to be

biologically significant and therefore are considered competing models. In addition,

models with a higher wi are more likely to be biologically significant relative to other

models considered (Anderson et al. 2000). Competing models are models that include

parameters that should be considered for explaining the variation in preference (Anderson

et al. 2000). For the model with ∆AICc = 0, I also present the ANOVA table. For significant interactions I use post hoc tests and linear regression to further quantify those effects.

Experiment 2-Differences in Mating Behaviors between Barred and Barless Males

Males and females were collected from San Martin (N=14 pairs) in December

2008 and Cebolla (N=19 pairs) in March 2009. I examined the mating behaviors of both barred and barless males (N = 23 barred, N = 10 barless) interacting with wild caught

females from the same population. Males and females were isolated for at least one week

prior to testing in 18-liter aquaria. Male-female pairs were tested in a 78-liter aquarium.

Pairs acclimated for 10 min with the female in an opaque chamber. The chamber was

removed and the pair interacted for 10 minutes, starting with the first interaction. The

male behaviors I recorded included those that coax females to mate (displays, headstands,

gonopore nibbling) and those that are more coercive (chases, attempted copulations,

backing, bites). Copulation attempts are considered a coercive mating behavior in

livebearing fishes (e.g., Pilastro et al. 1997; Plath et al. 2007; Morris et al. 2008) and can

cause physical injury to females (R. Deaton et al. personal communication). I compared

differences between the coaxing and coercive mating behaviors of barred and barless

males using MANOVA. Due to the low number of males performing chases (N = 2),

nibbling (N = 2), and circles (N = 3), these behaviors were not included in the analyses.

There was no significant difference between the barred males from San Martin and

Cebolla in either coercive behaviors (F3,19 = 1.22, P = 0.329) or coaxing behaviors (F2,20 =

2.99, P = 0.073). Therefore, I did not consider the populations separately when I compared the behaviors of barred and barless males. Due to the small number of barless males from San Martin (N = 1), I did not test for population differences in barless males.

Results

Experiment 1-Manipulating Female Experience

Female Growth

Female growth was not significantly affected by tank nested in experience treatment (Wald Z = 1.84, P = 0.066), experience treatment (F1,8 = 0.88, P = 0.375),

female population (F1,8 = 0.266, P = 0.620) or the interaction between female population

and experience treatment (F1,8 = 4.09, P = 0.078).

Female Preferences

The model with the lowest AICc included female growth and did not include tank nested in treatment (Table 2.1). This was the only model that met the criterion as a candidate model (∆AICc < 2). This model significantly explained variation in female

2 SOP (ANCOVA: adjusted r = 0.18, F7,61 = 3.12, P = 0.006). In this model, the only main

effect that was significant was experience treatment (Table 2.2). However, there were

two significant interactions with experience, and therefore experience is only considered

in the context of the interactions.

There were two significant interaction effects in this model (Table 2.2). First,

there was a significant interaction between experience treatment and female population

(Table 2.2, Fig. 2.1). Females from the San Martin population from the mixed treatment

had a significantly stronger preference for vertical bars than females from both

populations in the barred treatment (Tukey HSD: P<0.02). The SOP of females in the

mixed treatment was not significantly different between females from San Martin and

Tecolutlo (Tukey HSD: P = 0.097). SOP for barred males in San Martin females from the mixed treatment was significantly greater than zero (mean + SE: 548.1 + 145.5 s, one

group t test: t17 = 4.4, P < 0.001). Female SOP among the other groups (San Martin

barred treatment and all Tecolutlo females) were not significantly different from each

other (Tukey’s HSD: P > 0.599). SOP in these groups was not significantly different

from zero (mean + SE, one group t test: Tecolutlo mixed: 30.1 + 125.9 s, t17 = 0.239, P =

0.814; San Martin barred: 22.4 + 158.0 s, t16 = 0.14, P = 0.889, Tecolutlo barred: -26.1 +

119.6 s, t15 = -0.22, P = 0.831).

Second, there was a significant interaction between experience treatment and female growth on SOP (Table 2.2, Fig. 2.2). When females had experienced both barred and barless males, SOP for vertical bars decreased with growth (linear regression: F1,34 =

4.41, P = 0.043 , Fig. 2.2a). When females had experienced only barred males, SOP for vertical bars increased with growth (linear regression: F1,31 = 5.65, P = 0.024 , Fig. 2.2b).

This effect on female SOP did not vary by female population (i.e. no significant

interaction between female population and female growth, and no significant three-way

interaction between experience treatment, female population and female growth interaction, Table 2.2).

Experiment 2- Differences in Male Courtship and Coercive Behaviors

Barless males performed significantly more coercive behaviors than barred males

(F3,29 = 5.55, P = 0.004), and this result was driven by the barless males biting the

females more than barred males (mean + SE, barred = 1.6 + 1.2, barless = 10.6 + 4.8,

F1,31 = 6.24, P=0.018) and copulating more with females (barred = 3.2 + 0.9, barless 7.1 +

2.2, F1,31 = 4.16, P=0.050). Backing did not differ between barred and barless males

(mean + SE, barred = 1.0 + 0.3, barless 0.3 + 0.2, F1,31 = 2.51, P = 0.123). Barred and barless males also differed in the number of coaxing behaviors performed (MANOVA:

F2,30 = 3.82, P = 0.033), and this result was driven by barless males performing more

headstands than barred males (mean + SE, barred = 0.9 + 0.4, barless = 3.3 + 1.1, F1,31 =

7.331, P = 0.011). Displays did not differ between barred and barless males (mean + SE,

barred = 2.5 + 1.3, barless = 0.5 + 0.2, F1,31 = 1.112, P=0.300).

Discussion

The results of this study demonstrate that female preference for vertical body bars

in the swordtail X. cortezi is phenotypically plastic in response to social environment.

Population differences in female preferences most likely represent differences in a

genetically influenced response threshold, where the preferences of females from the

population that had more aggressive males (barless males) were more sensitive to the

aggressive behaviors of the barless males (Schlichting & Pigliucci 1998; West-Eberhard

2003). While this study did not examine a direct effect of the aggressive behaviors of

males in the experience treatments on female preferences, I demonstrated that the barless

males were on average more aggressive towards females than barred males. Additional

evidence suggesting that females may adjust their preferences for the bars based on making an association between male bar state and aggressive behaviors is discussed below.

It has been hypothesized that X. cortezi females can associate behavioral differences between males based on the vertical bars pattern (Robinson & Morris 2010

(Chapter 1)). This study demonstrated that barless males are more aggressive toward females, in addition to being more aggressive during male-male contests (Moretz 2005).

Higher levels of aggressive behaviors, in addition to the higher courtship rate by barless males, could indicate male quality to females. However, the negative effects of aggression on females could negate any perceived indirect benefits of barless males.

Female poeciliids continue to grow after sexual maturity and larger females are more fecund (Kallman 1989; Marcus & McCune 1999). In several poeciliids, including

Xiphophorus cortezi, male harassment of females has been demonstrated to reduce female foraging time (Plath et al. 2007), which could reduce female growth. A reduction in female growth may represent a significant cost to females by reducing fecundity.

While growth didn’t vary significantly by treatment, it did influence female preferences.

Females that grew the least when exposed to both male phenotypes had the strongest

preferences for vertical bars, suggesting that these females’ preferences may be an

avoidance response to aggressive barless males. Growing more may be an indication that

females are not as affected by male aggression, and therefore females that grow more

may not need to avoid aggressive males (prefer less aggressive males). This hypothesis is further supported by the fact that females that only experienced barred males and grew the most, had the stronger preferences for vertical bars. Male aggression occurred in both treatments, and X. cortezi males facultatively express their bars in male-male contests

(Moretz & Morris 2003, 2006; Moretz 2005). Therefore, in the barred treatment, the males that had their bars expressed more often would be the more aggressive males.

Females that grew less in this treatment used the information available to avoid the most aggressive males (i.e. had a preference for no bars, or avoided barred males). These results indicate that experience influenced the preferences of females in both populations, but the degree to which experience with barless males influenced the San Martin population appears to be much greater than the Tecolutlo population. Females with slower growth rates were more likely to avoid the more aggressive males in both treatments (males with bars expressed in the barred treatment, barless males in the mixed treatment), but overall the San Martin females were more influenced by the aggressive barless in the mixed treatment and therefore had a stronger preference for barred males. I hypothesize that there are genetically influenced differences across these populations in the degree to which male aggression influences their preferences.

Although genetically different reaction norms is one hypothesis to explain the

differences in plasticity I detected, maternal effects due to external environmental

conditions that differed across populations could also influence female development and

preferences. Studies of maternal influence on mate preference have focused on sexual

imprinting (Qvarstrom & Price 2001). However, maternal effects that affect female

condition could influence female preference, given the amount of evidence linking

female preferences to condition (Jennions & Petrie 1997; Cotton et al. 2006). Because

San Martin females in this study were initially larger than Tecolutlo females (3 mm larger

on average), this could have had some influence on female preferences. While I

controlled for female size by including growth in the analysis, growth did have a

significant influence on preference, suggesting the possibility of maternal effects.

However, I suggest that the difference in the strength of the response to aggressive barless males is not likely to be due to maternal effects, as the size difference in the

females at the beginning of the experiment was the opposite of what would be predicted

to give the Tecolutlo females an advantage at dealing with aggressive males.

The effect of growth on female preference I detected also suggests that there were

important differences across females within the same treatment. Within each treatment,

females that grew less preferred the less aggressive males. Even though the same public

information was available within tanks, females may have incorporated public

information differently into mate preferences. For example, in three-spined sticklebacks,

Gasterosteus aculeatus, females varied their use of public and private information based

82 on the age of information and on the reliability of private information relative to public information (van Bergen et al. 2004). The social networks within small groups of poeciliid females can vary because some females are preferred by males (e.g., Parzefall

1973; Farr & Travis 1986; Bisazza et al. 1989; Ptacek & Travis 1997; Aspbury & Gabor

2004). Preferred females would have different private information and should be choosier in relation to mate preferences (Sih et al. 2009). The interaction between the treatment

(barred versus mixed) and female growth suggests that females used a combination of public and private information for mate choice decisions in X. cortezi.

Previous studies of swordtails have found that female size (SL) varies with female preferences. Because female size is indeterminate (Kallman 1989; Marcus & McCune

1999), the size of wild-caught females can indicate female age, experience and growth rate. Larger, older females may be better able to deal with aggressive males than smaller females. In the current study, female growth was favored by model selection as a better indicator of female preference than female size. For future studies of female preferences, the measure of female size should depend on the experimental design. Size in this study did not indicate female experience, since females were all given 30 days of sexual experience with males. For studies that give females limited access to males, growth may be a better indicator of female response to male aggression than size. Growth is also a better variable to measure for female responsiveness, since size will differ little in short- term lab studies and is influenced by initial female size. However, in wild-caught

83 females, where female growth would not be easily measured, female size is still a good indicator of sexual experience with males and ability to respond to aggressive males.

The strength of change in female preferences for vertical bars in response to experience varied across populations as a result of different reaction norms (West-

Eberhard 2003). The implication of these differences for selection on the male trait would be stronger positive selection for barred males due to female mate preference in the population that had barless males than the population with all barred males. There is also evidence that females that had lower growth rates were responding in both social environments (barred males only and mixed barred and barless males) to cues that indicated which males were more aggressive, so that these males could be avoided. If female growth indicates female condition, then there could be adaptive reasons for these females to prefer less aggressive males. Future studies should be designed to tease apart the effects of male aggression and male pigmentation on female preferences. Since freeze-branding temporarily removes the vertical bars (Raleigh et al. 1973; Hert 1986), this technique can be used to separate the behavioral phenotype from the pigment pattern.

For example, the different male phenotypes may be more or less conspicuous across environments, or females may prefer other differences between barred and barless males.

Even if male behavioral differences are not necessary for females to discriminate between barred and barless males, the differences in male aggression indicate that direct costs to females are an important selection force on female preferences.

Acknowledgements

I would like to thank Molly R. Morris for financial support and comments

throughout this project. I thank Lisa Bono, Jason Brewer, Charles Nevill, and Oscar Rios-

Cardenas for help collecting fish, Andrew Fernandez and Marina Latiker for help rearing fry, and Susan Lyons for comments on the manuscript. I also thank the Mexican government for collection permits. This research was supported by an Animal Behavior

Society Research Grant and an Ohio Center for Ecology and Evolutionary Studies

Fellowship to D.M. Robinson, and an NSF grant to M.R. Morris. All experiments comply with current laws of the United States and with the Animal Care Guidelines of Ohio

University (Animal Care and Use approval L01-01).

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Table 2.1. Models for female strength of preference for vertical bars. Models are ranked in order of support by Akaike’s Information Criterion. Only the first model is a candidate model with ∆AICc < 2. Variables that differed across models are listed. The null model is included for comparison.

Model K AICc ∆AICc wi Female growth 9 929.204 0 0.745

Female growth, tank 10 931.343 2.139 0.255

Female SL after experience 9 977.201 47.997 <0.001

Female SL after experience, tank 10 979.091 49.887 <0.001

Female SL before experience 9 978.598 49.394 <0.001

Female SL before experience, tank 10 980.632 51.428 <0.001

Size not included 6 1018.705 89.501 <0.001

Size not included, tank 7 1020.211 91.007 <0.001

Intercept (null model) 2 1067.047 137.843 <0.001

∆AICc = model AICc - AICmin; K = number of parameters included in model; AICc = Akaike’s information criterion corrected for small sample size; wi = AIC weights.

Table 2.2. ANOVA Table for female strength of preference for vertical bars. Adjusted r2=0.184 for the model. Effect df Sum of Squares FP Experience treatment 1 2316424 8.14 0.006 Female population 1 432614 1.52 0.222 Female growth 1 781908 2.75 0.102 Experience treatment x female population 1 1455617 5.12 0.027 Experience treatment x female growth 1 1351355 4.75 0.033 Female population x female growth 1 379839 1.34 0.252 Experience treatment x female population x female growth 1 105143 0.37 0.545 Error 61 284508

700

Barless 500

300 San Martin Tecolutlo

100

Strength of preference (s) -100

-300 3/3 mixed 6 barred Barless Mixed Barred

Experience treatment

Figure 2.1. Correlation between female population and experience treatment on female SOP. Mean and standard error by groups, lines indicate groups that are not significantly different using Tukey HSD. Light gray denotes San Martin females, dark grey denotes Tecolutlo females.

d 1600 a. Mixed 1200

Barre 800 400

0 -400

-800

Strength of preference (s) -1200 Barless -.05 -.03 -.01 .01 .03

d 1600 b. Barred 1200 Barre 800

400 0

-400 -800

Strength of preference (s)

Barless -1200 -.05 -.03 -.01 .01 .03

Female growth (residual)

Figure 2.2. Correlation between female growth and experience treatment (a. mixed treatment, b. barred treatment) on female SOP. Female growth was estimated as the residuals of female size before and after experience. Positive numbers indicate that females grew more relative to their body size. Open diamonds denote San Martin females, grey circles denote Tecolutlo females.

CHAPTER 3: FEMALE PREFERENCE AND THE EVOLUTION OF AN

EXAGGERATED MALE ORNAMENT: THE SHAPE OF THE PREFERENCE

FUNCTION MATTERS

Abstract

Sexual selection theory often predicts that female preferences will produce directional selection for male traits that either reinforces or opposes male–male competition. However, without considering the complexity of preference functions and the potential for adaptive variation in female mate preferences, the direction of selection due to female preference can be misidentified. Previous studies have suggested that female preference opposed male–male competition in the evolution of the large, sexually dimorphic dorsal fin in the swordtail fish, Xiphophorus birchmanni. I present two lines of evidence to suggest that female preference selects for enlarged dorsal fins in male X. birchmanni, and therefore female preferences are not directional for small dorsal fins, but instead are potentially disruptive. Xiphophorus birchmanni females prefer dorsal fins that are larger than expected given the male’s size, and during male–female interactions, males raise their dorsal fins as part of their courtship display directed towards females. I argue that selection due to female preference is likely to be much more complex than is often considered.

Introduction

Historically, sexual selection theory predicted that female mate choice and male–

male competition select for the same male traits (Arnqvist & Rowe 2005). Female mate

choice should reinforce male–male competition when male traits favoured by male–male competition are correlated with direct or indirect benefits that females receive from those

males. However, traits used in male–male competition may not benefit females

(Qvarnström & Forsgren 1998), and mating with males that have these traits may be costly to females (e.g. coercion to mate), suggesting that these two components of sexual

selection may oppose one another in some cases (Arnqvist & Rowe 2005). In addition,

there is empirical evidence for traits being favoured by male–male competition but not by

female mate choice (e.g. cockroaches, Nauphoeta cinera: Moore & Moore 1999; meadow

voles, Microtus pennsylvanicus: Spritzer et al. 2005; killifish, Lucania goodei: McGhee

et al. 2007; reviewed in Arnqvist & Rowe 2005). Determining whether the two

components of sexual selection are congruent or antagonistic in the evolution of a

particular trait requires an accurate assessment of the shape of the female mate preference

function.

Several studies have determined that female preference functions can be complex

(reviewed in: Jennions & Petrie 1997; Widemo & Sæther 1999; Candolin 2003).

Distinguishing between preference functions that produce directional selection as

compared to stabilizing or disruptive selection requires that preferences be tested in both

directions (for traits that are both larger and smaller than average) (Wagner 1998). For example, female red bishops, Euplectes orix, prefer males with long tails over short tails.

However, additional tests determined that females also discriminate against longer tails that resemble tails of closely related species (Pryke & Andersson 2008), suggesting stabilizing rather than directional selection. In some populations of sailfin mollies,

Poecilia latipinna, males prefer females that are the average size in the population (Gabor et al. 2010). The mode of selection can also differ from trait to trait (e.g. treefrogs, Hyla

versicolor: Gerhardt & Brooks 2009). While more complete examinations of preference

functions suggest that some studies have correctly reported directional selection due to

female mate preference (e.g. birds, Taeniopygia guttata: Clayton & Prove 1989;

grasshoppers, Chorthippus biguttulus: Klappert & Reinhold 2003; frogs, Oophaga

pumilio: Maan & Cummings 2009), the prevalence of research reporting directional

selection may be overestimated both by study design and publication bias. Studies cannot

conclude directional selection on traits without eliminating alternative types of selection

using multiple female preference tests.

Swordtails (genus: Xiphophorus) are livebearing fish belonging to the family

Poeciliidae and have internal fertilization. Northern swordtails are found in streams and

rivers of the Rio Pánuco River basin in Mexico (Rosen & Bailey 1963). Both males and

females mate multiply, and females are capable of storing sperm for several months

(Constantz 1989). Xiphophorus birchmanni is the only species of northern swordtails that

has large males that do not develop swords. However, males develop large dorsal fins

that are strongly correlated with male body size: large males have larger dorsal fins than

small males (Fisher et al. 2009).

Males in several species of swordtails raise the dorsal fin during male–male

competition (e.g. Zimmerer & Kallman 1989; Rosenthal et al. 2003). Xiphophorus

birchmanni males are more aggressive towards models of males with smaller dorsal fins

and less aggressive towards models with larger dorsal fins (Fisher & Rosenthal 2007).

However, the relationship between a male’s own dorsal fin size and his aggression level

has not yet been determined. It has been hypothesized that males with larger dorsal fins

are more aggressive, and that females avoid them for that reason (Fisher & Rosenthal

2007). In support of this idea, Fisher & Rosenthal (2007) found that females prefer males

with smaller dorsal fins to males with dorsal fins of average size. Females also preferred

live males with relatively smaller dorsal fins for their body size (Fisher et al. 2009). One

interpretation of these results is that female preferences exert directional selection for

small dorsal fin size. To test this hypothesis fully, however, it is necessary to explore the

other half of the preference function: to test female preferences for larger relative to

average fin sizes. This is one of the goals of the present study. If female preference is

producing directional selection against larger dorsal fins, then I would predict a female

preference for average dorsal fins when given a choice between average and larger dorsal

fins. In addition, I examined the use of the dorsal fin by males during courtship and the

relationship between dorsal fin size and the use of aggressive and coercive mating

behaviours. Previous research compared males raising their dorsal fins across different

social conditions to suggest that this signal is directed towards males but not females

(Fisher & Rosenthal 2007). In the present study, I explore the use of the dorsal fin during courtship by adding another social condition to those previously studied. If raising the dorsal fin is a signal directed towards females, I predicted that males would raise the dorsal fin more when they were with a female than when alone. If males use the dorsal fin during courtship, I also predicted that males that raised the dorsal fin more would perform more courtship behaviours. Finally, if females prefer males with smaller dorsal fins as a means to avoid more aggressive large-finned males, I predicted that males with larger dorsal fins would be more aggressive towards females or use more coercive mating behaviours.

Methods

I collected X. birchmanni males and females from the Rio Garces (20°56'24"N,

98°16'53"W), and males from the Rio Santa Maria (21°3'30"N, 98°21'12"W) in Mexico.

Fish were isolated into 19-litre aquaria on a 12:12 h light:dark cycle and fed Tetramin

flakes (Tetra, Blacksburg, VA, U.S.A.). Behavioural tests (male–female interactions and

female preference) occurred between 0800 and 1400 hours. All experiments complied

with current laws and with the Animal Care Guidelines of Ohio University (Animal Care

and Use Protocol No. L01-01). All statistical tests were parametric and two tailed.

Analyses were performed using JMP 8.0 (SAS Institute, Cary, NC, U.S.A.) and R (R

Project for Statistical Computing, Vienna, Austria).

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Female Preferences

While a previous study found a preference for males with dorsal fins reduced by

55% area (33% decrease in length x width; Fisher & Rosenthal 2007), I further explored

the preference function by examining female preference for average as compared to larger dorsal fins. Females (N = 17) were tested in a 39-litre aquarium divided into three equal compartments. Females were tested with pairs of transparencies consisting of one unaltered image (‘average’) and one image with dorsal fin area increased by 200%

(‘larger’, 73% increase in length x width; Fig. 3.1). Increased dorsal fin sizes were larger than the absolute dorsal fin size and the relative dorsal fin size (i.e. relative to standard length; see Dorsal Fin Size below) of all males measured (453–748 mm2), but the

absolute size was not outside of the range of X. birchmanni from other populations (M. R.

Morris, unpublished data). Pairs of transparencies (3 pairs created from 3 males) were created using digital photographs of the same male with dorsal fin area altered in

Tektronix 7760 printer (Xerox Corporation, Wilsonville, OR, U.S.A.).White paper in the shape of the fish’s body (excluding fins) was placed between the mirror images. I cut the photographs from the transparencies and fastened both photographs and the white paper together using clear double-sided tape, creating a two-dimensional model with an opaque body and transparent fins. Transparencies have been used successfully to test female

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preferences in poeciliids (e.g. MacLaren et al. 2004; Gumm et al. 2006; MacLaren &

Daniska 2008).

The transparency apparatus was reproduced from MacLaren et al. (2004) to fit a

37.9-litre aquarium. The apparatus was modified to stand on metal legs without touching

the aquarium, and foam insulation was used to prevent vibrations from transferring from

the apparatus to the floor and testing aquarium. A motorized pulley system was created

using a Planetary Gear Box (Tamiya America, Inc., Aliso Viejo, CA, U.S.A.) to move

each transparency parallel to its respective side of the aquarium. Fishing line attached

transparencies to a rectangular motorized belt with rounded corners (33 cm long x 2 cm

wide) placed on both sides above the testing aquarium. Transparencies moved clockwise

5 cm and 7 cm from each end of the aquarium so they appeared to swim. The top and

back wall of the aquarium were covered with white plastic to obscure the view of the

apparatus.

For preference tests, the aquarium was divided by two lines into three equal compartments. On each end of the aquarium, I placed a transparency onto the motorized belt out of view of the focal female. I randomly assigned the transparencies to the sides of the aquarium. Females acclimated in a clear tube in the centre compartment for 10 min. I then started the motor so the transparencies moved into view and ‘swam’ parallel to the aquarium. Females observed transparencies for 2 min. After the 2 min observation, females were released from the clear tube and could interact with the transparencies for 8

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min. During the 8 min interaction, I recorded the time females spent in the compartment adjacent to each transparency. I re-acclimated and retested females after switching transparencies between sides to control for side bias. A female was scored as having a side bias when she spent less than 10 s on one of the two sides of the testing aquarium when added across the two trials. Females with side biases were retested after 7–14 days.

All females were tested again after 7 days with the same stimulus pair. After the final trial, females were measured for standard length. During each trial, I recorded the amount of time the female spent in the compartment adjacent to each transparency to measure her preference for each transparency. The difference between the time females spent with each transparency across both tests indicated strength of preference. In closely related X. nigrensis, association time is the most consistent receptive behavioural measure within females (measured as a low coefficient of variation over consecutive tests; Cummings &

Mollaghan 2006). Association times have been found to be a good predictor of mate choices made in nature. For example, association times reflected mate choice decisions, as measured by paternity, in the field for closely related X. multilineatus (Morris et al.

2010) and in captivity for X. helleri (Walling et al. 2010). As strength of preference was not significantly different between the first and second preference tests (paired t test: t16 =

0.74, P = 0.472), the amount of time the female spent with each transparency across both tests was summed to obtain a better estimate of female preferences. I used a paired t test to assess female preferences for larger versus average transparencies. I used linear regression to determine whether female strength of preference differed with female standard length. I used ANOVA to assess whether different transparencies affected the

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female strength of preference and total association time (measured as total time spent

with both the large and average transparencies).

Dorsal Fin Size

I assessed dorsal fin size in X. birchmanni to (1) relate female preference tests to

natural variation in male dorsal fin size and (2) evaluate any correlation between male

courtship behaviour and dorsal fin size (see Male–Female Interactions below). The dorsal

fin sizes of both males (N = 14) and females (N = 10) were measured and compared to

body size and mating behaviours. Live fish were digitally photographed with their dorsal

fins raised and then were measured for standard length with callipers. I measured

standard length again with the straight line selections tool in ImageJ (1997–2009,

National Institutes of Health, Bethesda, MD, U.S.A.) to convert from pixels to

millimetres for digital photographs. Dorsal fin area was measured with the polygon

selections tool and converted from pixels to mm2. Each picture was measured three times

and the average measurements used for the analyses. I assessed whether there is an

isometric relationship between dorsal fin area and standard length. An isometric

relationship indicates that dorsal fin area changes proportionally with standard length

across the range of measurements. Since dorsal fin area (a two-dimensional measure) was

compared to standard length (a one-dimensional measure), the slope of the log–log regression should be 2.0 for isometry (Warton & Weber 2002; Warton et al. 2006). From the equation of the log–log regression between male standard length and dorsal fin size, I

104 also calculated the residuals for dorsal fin size for each male (residuals = observed - expected dorsal fin size), which provided a measure of dorsal fin size relative to male size

(hereafter ‘relative’ dorsal fin size). Males with positive residuals had dorsal fins larger than expected for their body size, while males with negative residuals had dorsal fins smaller than expected for their body size. I used both of these measurements (absolute dorsal fin size and relative dorsal fin size) to examine the relationship between dorsal fin size and male behaviours in the male–female interactions.

Male–Female Interactions

I examined the interactions between males and females to determine whether either the absolute or relative dorsal fin size was correlated with male aggression and coercive mating behaviours or courtship behaviours. Male–female pairs (N = 16) were tested in a 78-litre aquarium. Pairs acclimated for 10 min with the female in an opaque chamber. The chamber was removed and the time the male raised his dorsal fin was recorded for 10 min. Copulation attempts and male courtship behaviours (displays, headstands, gonopore nibbling) were also recorded. Whereas I detected no aggression

(e.g. chases, bites), copulation attempts are considered a coercive mating behaviour in livebearing fishes (e.g. Houde 1997; Pilastro et al. 1997; Plath et al. 2007; Morris et al.

2008) and can cause physical injury to females (R. Deaton personal communication).

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I compared the time a male raised his dorsal fin when he was with a female to the time he raised it when alone to determine whether raising the dorsal fin is a signal directed towards females. Fourteen of the 16 males were also tested without females

(sample sizes varied because of the death of two males). To obtain a baseline estimate for each male, the time a male raised his dorsal fin when alone was recorded using the same procedure (10 min acclimation, 10 min observation). The order of the two tests (with and without a female) was randomized. I compared male use of the dorsal fin with and without a female using a paired t test. The difference between the amounts of time a male raised his dorsal fin in each test (with and without a female) was used as an indicator of his strength of response to females, with positive values indicating that a male spent more time with his dorsal fin raised when females were present.

Finally, I examined the relationships between the behaviours males used when interacting with a female and the size of his dorsal fin to determine whether female preference for smaller dorsal fins could be explained by females avoiding more aggressive or coercive males. I used Akaike’s (1974) Information Criterion (AIC) to determine the most parsimonious model for explaining the strength of response, total number of courtship behaviours (coaxing) and number of attempted copulations

(coercive). AIC selects models by weighting the residual error of each model against the number of parameters in the model. This is especially powerful for parameter reduction given that more parameters often explain more variation. While its use in behavioural ecology has so far been limited (but see Garamszegi et al. 2009), the use of AIC in

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biological studies is widespread (Anderson 2008). For strength of response, I assessed

male standard length (covariate), female standard length (covariate), male absolute dorsal

fin size (covariate), relative male dorsal fin size (covariate) and population (Santa Maria or Garces, factor). For number of copulations, I assessed number of courtship behaviours

(covariate), male standard length (covariate), female standard length (covariate), absolute male dorsal fin size (covariate), relative male dorsal fin size (covariate), population

(Santa Maria or Garces, factor) and strength of response (covariate). For total number of courtship behaviours, I assessed number of copulations (covariate), male standard length

(covariate), female standard length (covariate), absolute male dorsal fin size (covariate), relative male dorsal fin size (covariate), population (Santa Maria or Garces, factor) and strength of response (covariate). All morphometrics were log transformed for the analyses. I included all possible models with up to seven parameters (five assessed parameters plus the intercept and error terms), as well as the null model (includes only the intercept and error term). I did not include the parameter male dorsal fin size in the same model as relative male dorsal fin size. Since some models included many parameters (K), relative to sample size (N), I used AIC corrected for small sample sizes

(Anderson et al. 2000): AICc = 2k – 2 ln (likelihood) + (2k (k+1))/(N – k – 1). The model with the minimum AIC was considered to have the highest probability given the data

(Anderson et al. 2000). Models were ranked using AICc, ∆AICc, and AIC weights (wi)

(Anderson et al. 2000). Models with ∆AICc less than 2 are presented since models with a lower ∆AICc are more likely to be biologically significant and therefore are considered competing models. In addition, models with a higher wi are more likely to be biologically

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significant relative to other models considered (Anderson et al. 2000). Competing models are models that include parameters that should be considered for explaining the variation in preference (Anderson et al. 2000). For the model with ∆AICc equal to 0, I also present

the ANOVA table when the null model was rejected.

Results

Female Preferences

Females spent significantly more time near males with the larger dorsal fin (mean

+ SE: larger = 724.82 + 50.65 s, average = 547.77 + 39.38 s; paired t test: t16 = 2.47, P =

0.03; Fig. 3.2). Female size (standard length) was not correlated with strength of

preference (linear regression: F1,15 = 0.29, P = 0.60). Female strength of preference did

not differ significantly across male transparencies (F2,14 = 1.03, P = 0.383), nor did total

association time differ (F2,14 = 1.28, P = 0.309).

Dorsal Fin Size

Dorsal fin area scaled to standard length did not differ significantly from isometry for males (slope test: r = -0.02, N = 14, P = 0.95; log–log regression: dorsal fin area

2 2 (mm ) = -1.10 + (2.06 x standard length (mm)); r = 0.68, F1,12 = 25.75, P < 0.01) or females (slope test: r = 0.39, N = 10, P = 0.26; log–log regression: dorsal fin area (mm2)

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2 = -1.91 + (2.29 x standard length (mm)); r = 0.92, F1,8 = 91.00, P < 0.01) (Fig. 3.2).

Therefore, although larger individuals have larger dorsal fins, the geometric relationship between dorsal fin size and body size is maintained within each sex of this species. Males always had larger dorsal fins than females (mean + SE: males: 247.7 + 14.0 mm2, range

163.9–347.6 mm2, N = 14; females: 64.9 + 6.2 mm2, 32.2–90.2 mm2, N = 10).

Male–Female Interactions

Males raised their dorsal fin significantly more when a female was present than

when no other fish was present (paired t test: t14 = 4.00, P = 0.001; Fig. 3.4), suggesting that raising the dorsal fin is a signal directed at females. The model that best explained variation in male strength of response to females (strength of response = time dorsal fin raised with female – time dorsal fin raised without female) was the null model (intercept), indicating that none of the assessed parameters, including either of the measures of dorsal fin size, explained variation in strength of response. The null model also best explained variation in the number of copulations (coercive behaviour). The model that best explained variation in the total number of male courtship behaviours (coaxing behaviours) included strength of response and absolute dorsal fin size (Table 3.1). This was the only candidate model (∆AICc < 2) for male courtship behaviours. This model

significantly explained variation in the total number of courtship behaviours (ANCOVA:

2 r = 0.53, F2,11 = 6.30, P = 0.015). Males with a greater strength of response courted more

(ANCOVA: β = 0.023, F1,11 = 6.90, P = 0.024; Fig. 3.5a) as did males with smaller dorsal

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fins (β = -45.2, F1,11 = 6.05, P = 0.032; Fig. 3.5b). These results suggest that males that court more raise their dorsal fin more, and that smaller males with smaller absolute dorsal

fins court more. Because of the tight correlation between male size and dorsal fin size, it

was not possible to determine whether body size or dorsal fin size was more important in

this case. Therefore, I performed an additional ANCOVA to investigate these effects

separately by separating absolute dorsal fin size into the variables male standard length

and relative dorsal fin size (based on residuals). This model explained a similar amount

of variation in the total number of courtship behaviours as the prior model (ANCOVA: r2

= 0.54, F3,10 = 3.89, P = 0.044), although with the additional parameter, the df decreased

and P increased for the overall model. Males with a greater strength of response still

significantly courted more (ANCOVA: β = 0.024, F1,10 = 6.16, P = 0.032). However, with

the separation of absolute dorsal fin size into its two components, I found no significant

relationship between male standard length and the number of courtship behaviours

(ANCOVA: β = -81.49, F1,10 = 3.26, P = 0.101) or between relative dorsal fin size and

the number of courtship behaviours (β = -54.12, F1,10 = 2.55, P = 0.141).

Discussion

The evolution of the sexually dimorphic dorsal fin of X. birchmanni has been described as an example of selection due to female preference opposing selection due to male–male competition (Fisher & Rosenthal 2007; Fisher et al. 2009). However, I present evidence to suggest that female preference was involved in the evolution of the enlarged dorsal fins in males of this species. Given a choice between average and larger dorsal fin

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sizes, females preferred the model male with the larger dorsal fin. A preference for larger

dorsal fins suggests that at one end of the preference function female preferences would

reinforce male competition, which selects for larger dorsal fins, while at the other end of

the preference function females prefer smaller dorsal fins (Fisher & Rosenthal 2007).

Together, these studies suggest that females may prefer dorsal fin sizes that deviate in

either direction from average (disruptive selection). I also demonstrated that males raise

the dorsal fin as part of courtship behaviour even when other males are not present, and

that the propensity to raise the dorsal fin in the presence of females is correlated with the

use of other coaxing behaviours during courtship. Therefore, the results of the male–

female interaction study suggest that raising the dorsal fin is a signal directed towards

females, and that the dorsal fin plays a key role in courtship.

Several hypotheses could explain female preference for larger dorsal fins.

However, the empirical data I currently have is insufficient to distinguish between these possibilities. First, an advantage of mating with males with larger dorsal fins could have driven the female preference beyond its natural selection optimum (Fisher 1930). Second, as dorsal fins are assessed in male–male competition, dorsal fin size may have indicated male genetic or phenotypic quality and females may use the dorsal fin as a means of detecting superior fathers for their offspring. Third, female preferences for larger male traits can evolve as mechanisms to reinforce species barriers (Gerhardt 1991; Servedio &

Noor 2003). The preference for larger dorsal fins I detected could have evolved as a species-specific cue in X. birchmanni, as this species has larger dorsal fins relative to

111 body size than any of the other species of northern swordtails (Rauchenberger et al. 1990;

D. M. Robinson, unpublished data). The populations of X. birchmanni I examined are currently sympatric with only one other species of Xiphophorus (X. variatus), in which males have much smaller dorsal fins than X. birchmanni males. Fourth, a pre-existing preference for large males could have led to the large dorsal fins in X. birchmanni, as they make the males appear larger. A pre-existing preference for large males has been suggested as a mechanism for the origin of the swordtail in Xiphophorus (Basolo 1990;

Rosenthal & Evans 1998). A sensory bias for large male body size also has been proposed as the mechanism involved in the origin of the preference for enlarged dorsal fins in the sailfin males of Poecilia latipinna (MacLaren et al. 2004) and for preferences for large male traits in general (Endler 1992; Ryan & Keddy-Hector 1992; Arnqvist

2006). To determine whether the preference I detected for enlarged dorsal fins originated from sensory bias, historical inferences would be useful to demonstrate the preference for larger dorsal fins evolved before the enlarged dorsal fins in males. Finally, a preference for a large male trait could be the outcome of antagonistic coevolution. When there are costs to mating with males with particular traits, the amount of stimulation required for females to respond to male traits may increase (Rosenthal & Servedio 1999; Gavrilets et al. 2001). In this situation, a coevolutionary arms race between female preferences and male traits may occur, and female preferences may become so extreme that no existing male traits are exaggerated enough to be preferred. Considering the lack of aggression and the positive relationship between courtship behaviours and raising the dorsal fin, I

112

have no evidence that sexual conflict by overt aggression is currently influencing female

preference for dorsal fin size.

Fisher and colleagues (Fisher & Rosenthal 2007; Fisher et al. 2009) explained the

evolution of a preference for smaller dorsal fins in X. birchmanni as evidence of

antagonistic coevolution (Arnqvist & Rowe 2005). While the preference I detected for

large dorsal fins does not necessarily rule out this hypothesis, there are several other lines

of evidence suggesting that it is unlikely. A relationship between dorsal fin size and

aggression in male–female interactions has not been demonstrated. I detected no evidence

of a relationship between either the absolute or relative dorsal fin size and male aggressive behaviours towards females (no aggressive behaviours observed) or the use of coercive mating behaviours such as attempted copulations (e.g. Houde 1997; Pilastro et al. 1997; Plath et al. 2007; Morris et al. 2008). The only behaviour correlated with dorsal fin size was courtship behaviours: males with absolutely smaller dorsal fins courted more. Males with smaller dorsal fins are smaller males that could be compensating for being less attractive to females. Finally, female X. birchmanni preferred larger males

(Fisher et al. 2009), even though large body size is commonly associated with more aggression during male–male competition (poeciliids: Hughes 1985; Riesch et al. 2006; reviewed in Arnott & Elwood 2009). Therefore, if females are avoiding aggressive males

(whether or not the aggression is directed at females or other males), a preference for smaller males, not larger males, would be predicted for the same females that preferred smaller dorsal fins. More evidence that females incur a cost to mating with males with

113 larger dorsal fins is needed to conclude that antagonistic coevolution can explain a preference for males with smaller dorsal fins.

The study that detected a preference for smaller dorsal fins as compared to average dorsal fins (Fisher & Rosenthal 2007) used video animations as stimuli, while the current study, which detected a preference for larger dorsal fins as compared to average dorsal fins, used transparencies. While courtship behaviour was controlled for in both studies, the potentially more active male in the video animations may have produced a stronger preference than the males in my experiments (Rosenthal et al. 1996). The differences in methodologies would not explain, however, why I detected a preference for a larger dorsal fin over the average size fin, while Fisher & Rosenthal (2007) detected a preference for a smaller dorsal fin as compared to an average size fin. Therefore, given preferences for both smaller and larger dorsal fins, hypotheses for why the preference function may be bimodal need to be examined. One possible explanation for this pattern within females would be preferences for novel traits (Kokko et al. 2007). Alternatively, preference for dorsal fin size could be plastic, varying either across or within females such that females sometimes prefer larger dorsal fins and sometimes prefer smaller dorsal fins. Female preferences are known to vary in both strength and direction due to several variables, including age, condition and temporal variables (reviewed in: Jennions &

Petrie 1997; Widemo & Sæther 1999; Cotton et al. 2006). As the same females were not tested in both preference tests, it is not possible to know whether the disruptive selection is driven by preferences within or across different females.

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Regardless of how female preference selects for dorsal fin size, it is clear that the behaviour of raising the dorsal fin is part of the X. birchmanni courtship display. Recently it has been suggested that ornaments most often arise secondarily as a way to enhance behavioural displays (Byers et al. 2010). Given the widespread use of raising the dorsal fin during courtship in Poeciliidae (e.g. Ptacek 1998; Rosenthal et al. 2003), the enlarged dorsal fin in male X. birchmanni may have evolved to visually enhance the motor display of raising the dorsal fin during courtship. The difference between my conclusion and the conclusion of previous studies, which suggested that raising the dorsal fin functions to deter male competitors, but not to attract females, arises from examining this behaviour in different contexts. Fisher & Rosenthal (2007) always tested males with an observer female present (i.e. male with female, male with female and stimulus female, male with female and competitor male), and found that the males displayed more in the last social condition, with a male competitor and female observer. I examined the time the dorsal fin was raised when X. birchmanni males were alone as compared to being with a female.

Several studies have reported that males display more to females when rival males are present (e.g. Bosch & Marquez 1996; Wilson et al. 2009; Davie et al. 2010), which is the same pattern found in X. birchmanni (Fisher & Rosenthal 2007). However, this study found that X. birchmanni males display to females in the absence of rival males, suggesting that these displays are not directed exclusively towards males.

It will be important to untangle the interactions between male mating behaviours and dorsal fin morphologies, as well as the potential for multiple, interacting female

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preference in X. birchmanni, before the evolution of the preference for dorsal fin size can be fully understood. For example, no study of X. birchmanni has investigated how the preferences for body size and dorsal fin size interact. Given that dorsal fin size is isometric, experimentally manipulating dorsal fin size will result in a geometric relationship between dorsal fin size and body size different from what females encounter in natural males. Using live males, Fisher et al. (2009) found a preference for males with negative residuals from the correlation between dorsal fin and body size, suggesting that relative dorsal fin size may be the key trait females assessed (i.e. a male with a negative residual could have an absolutely larger dorsal fin than a male with a positive residual).

An inappropriate definition of a male trait can lead to inappropriate conclusions about its evolution in relation to female preference (Wiens & Morris 1996). It would also be worth assessing whether females have additional preferences for dorsal fin shape (e.g. morphometrics of height to width) in addition to size, as males may vary in these aspects of the dorsal fin as well. Just as we need to have a better description of the preference function, we need to have a clear understanding of the aspects of the traits females are assessing, so that it is clear when we may be measuring multiple, independently evolving preferences as compared to one preference based on multiple facets of the male trait.

In conclusion, detecting female preferences for both smaller dorsal fins (Fisher &

Rosenthal 2007) and larger dorsal fins (current study) suggests that the evolution of female preference functions are likely to be much more complex than previously appreciated, requiring more complex models to understand their evolution (Rowe et al.

116

2005). In addition, it is clear that the validity of my conclusions about the relative roles of

female preference and male–male competition in selecting for an exaggerated male trait

rely on a more complete evaluation of the range of female preferences given a range of

male trait values. Determining whether female preferences vary across time or

environments, as well as examining how multiple preferences interact, is essential in

describing the type of selection female mate preference is producing.

Acknowledgments

I thank Julie Bauerschmidt, Theresa Beham, Shawn Conaster and Sarah Klim for

assistance with trials, Geoff Baker, Kevin de Queiroz and Oscar Rios-Cardenas for

assistance in the field, and the Mexican government for collection permits. Funding was

provided by grants from the National Science Foundation (IBN 9983561) and Ohio

University (Research Incentive) to M.R.M., and by an Ohio Center for Ecology and

Evolutionary Studies fellowship to D.M.R.

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Table 3.1. Models of courtship behaviour for male Xiphophorus birchmanni. Models are ranked in order of support by Akaike’s Information Criterion (AIC).

Model K AICc ∆AICc wi Log (dorsal fin area), strength of response 4 98.52 0 0.251

Strength of response 3 100.60 2.09 0.088

Log (dorsal fin area) 3 101.29 2.77 0.063

Log (standard length), strength of response 4 101.56 3.04 0.055

Log (standard length) 3 101.77 3.26 0.049

Intercept (null model) 2 101.84 3.33 0.047

K = number of parameters included in model; AICc = Akaike’s Information Criterion corrected for small sample size; ∆AICc = model AICc - AICmin; wi = AIC weights. Only the first model was a candidate model with ∆AICc < 2. Additional models and the null model are shown for comparison.

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I.I. II.II.

(a)a

(b) b

(c)c

Figure 3.1. Models of male X. birchmanni used to examine female preferences for large dorsal fin size. For female preference tests, females observed pairs of model males, either (a), (b), or (c). Female preferences were tested between models (I) normal dorsal fin size and (II) dorsal fin size increased by 200% area.

124

800

600

400

Association time (s) 200

0 Average Large

Transparency

Figure 3.2. Mean + SE time that female Xiphophorus birchmanni spent associating with each transparency.

125

2.6 )) 2 2.4

2.2

1.8

fin area (mm Log (dorsal 1.6

1.4 1.4 1.5 1.6 1.7 1.8

Log (standard length (mm))

Figure 3.3. Isometry of the dorsal fin size (mm2) and body size (standard length) in Xiphophorus birchmanni. Open circles: females; closed circles: males.

126

400

300

200

Time raised (s) 100

0 None Female Fish present

Figure 3.4. Mean + SE time that male Xiphophorus birchmanni spent raising the dorsal fin when a female was present or absent.

127

(a) (b)

30 30

20 20

10 10

Total courtship behaviours Total courtship behaviours 0 0 -300 -100 100 300 500 2.2 2.3 2.4 2.5

Strength of response (s) Log (dorsal fin area (mm2))

Figure 3.5. Total number of courtship behaviours by male Xiphophorus birchmanni relative to (a) strength of response to females and (b) dorsal fin size.

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CHAPTER 4: ROLE OF THE DORSAL FIN DURING COURTSHIP IN

XIPHOPHORUS

Abstract

Recent reviews have suggested that many sexual ornaments evolve to enhance

male behavioral displays. This study is a preliminary investigation into the evolution of the use of the dorsal fin during courtship in relation to dorsal fin size in the Northern swordtails (Xiphophorus). Previous work has found that the dorsal fin is used during male-male contests, but the role of the dorsal fin in courtship had only been assessed in one species. I determined whether raising the dorsal fin is a signal directed towards females across the Northern swordtails, and whether the size of the dorsal fin increased to enhance the behavior of raising the dorsal fin during courtship. The results from this study suggest that raising the dorsal fin is a signal directed at females in several species of Xiphophorus, although ancestral state reconstruction was unable to determine whether this signal was present at the base of the Northern swordtail clade. Dorsal fin use during courtship varied with dorsal fin size both within and across species: use of the dorsal fin during courtship in X. nezahualcoytl depended on the size of the dorsal fin and size of the female, and males from the species with the smallest dorsal fins for their size (X. helleri) had their dorsal fins up when alone as often as when with a female. It does not appear that enlarged dorsal fins evolved primarily to enhance the use of the dorsal fin during courtship, as sexual dimorphism in dorsal fin size evolved prior to an increase use of the

129 dorsal fin during courtship. However, it is possible that either female preferences or male competition led to exaggeration of the dorsal fin, which resulted in costs associated with raising the larger dorsal fin.

Introduction

Males in promiscuous mating systems often evolve elaborate ornaments that function in female courtship and male-male contests (Andersson 1994). A recent review suggests that many male ornaments evolve to enhance male performance of energetically expensive behaviors (Byers et al. 2010). However, since many sexual ornaments result from elaborations on morphological characters that originally evolved for another function, assessing the role of the evolution of sexual ornaments in enhancing the performance of a behavior can be difficult. Phylogenetic comparative studies can be used to determine the relationship between the evolution of ornament elaboration and ornament use in courtship. If a sexually selected male trait has evolved to enhance a particular male behavior, the behavior should have evolved prior to the elaboration of the male trait. For example, if use of the trait during courtship evolved prior to the elaboration of the trait, then selection on preference for the trait could select for elaboration of the trait.

One way of identifying elaborated male ornaments is by looking for traits that are sexually dimorphic. Although sexual dimorphism can indicate sexual selection on a

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morphological trait, other types of natural selection can influence sexual dimorphism if males and females have different ecological niches or behaviors (Darwin 1871).

Allometry, which is a predictable change in the geometric relationship of two traits across a range of measurements, has also been observed in many sexual ornaments (Kodric-

Brown et al. 2006; Bonduriansky 2007) and is considered to be an indicator of sexual selection. While allometry may indicate sexual selection on an ornament, sexual ornaments can also scale isometrically (i.e. proportionally with body size). A recent review suggested that the prevalence of allometry in sexual ornaments may be minimal and that its prevalence in the literature is a result of sampling bias focusing on extreme traits (Bonduriansky 2007). Ornaments should scale allometrically when the fitness benefits of investing in ornaments differ across males of different sizes (Kodric-Brown et al. 2006), and may be an additional indicator of alternative mating tactics in smaller

males which evolve under strong sexual selection (Gross 1996; Lee 2005). Such tactics

often use coercive rather than coaxing mating behaviors, and produce antagonistic

selection on male traits found in both types of males.

In the current study, I examined the evolution of the dorsal fin across the Northern

swordtail fishes (genus Xiphophorus) in relation to the use of this trait during courtship.

My goal was to determine the extent to which this trait has become elaborated across this group of fishes as a means of enhancing the behavioral display in which males raise their dorsal fin when courting females. Evidence suggests that the dorsal fin may be an important sexually selected signal in swordtail species. Courtship displays involve a male

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orienting in front of a female and then quivering the body in a “C” shape. This behavior occurs in most species, often with a raised dorsal fin (Rosenthal et al. 2003). Males also display by raising their dorsal fins during male-male contests (e.g., Zimmerer & Kallman

1989; Rosenthal et al. 2003) and lowering the dorsal fin when a contest is lost (e.g.

Moretz 2003; Lyons & Morris 2008). The dorsal fin as a sexual ornament has been studied primarily in X. birchmanni (Fisher & Rosenthal 2007; Fisher et al. 2009;

Robinson et al. 2011 (Chapter 3)). Males of this species have lost the swordtail, but have

large dorsal fins that they use during courtship (Robinson et al. 2011 (Chapter 3)). In this

study, I expand the description of the dorsal fin as a sexual ornament by describing this

trait and its use during courtship in four additional species of swordtails. In this study, I

examine morphology and courtship behaviors in a phylogenetic context to examine their

evolution in the Northern swordtails. My first objective was to determine if raising the

dorsal fin is a signal directed towards females across the Northern swordtails, and is

therefore the ancestral state in this clade. The increased use of the dorsal fin during

courtship interactions was detected in X. birchmanni (Robinson et al. 2011 (Chapter 3))

but has not been specifically examined in other swordtail species. If raising the dorsal fin

is a signal directed towards females, I predict that males will raise the dorsal fin more

when they are with a female than when alone. My second objective was to evaluate the

evolutionary relationship between the use of the dorsal fin during courtship and male

morphology. If the dorsal fin evolved to enhance the behavioral display, then I would

predict that ornament size should correlate to its importance during courtship, and that

132 large sexually dimorphic dorsal fins will have evolved after the use the dorsal fin during courtship.

Materials and Methods

I used laboratory stocks of three Northern swordtail species from the Río Pánuco

Drainage, Mexico, a member of each of the three putative clades (see Rauchenberger et al. 1990, Morris et al. 2001), and one Southern swordtail species from Belize (Table 4.1) to examine male use of the dorsal fin during courtship. In addition, data from X. birchmanni collected for a previous study (Robinson et al. 2011 (Chapter 3)) are included here for comparison. Fish were isolated into 19-litre aquaria on a 12:12 h light:dark cycle and fed Tetramin flakes (Tetra, Blacksburg, VA, U.S.A.). All experiments complied with current laws and with the Animal Care Guidelines of Ohio University (Animal Care and

Use Protocol No. L01-01). Analyses were performed using JMP 8.0 (SAS Institute, Cary,

NC, U.S.A.), SPSS 17.0 (IBM, Chicago, IL, U.S.A.), RMA (Bohonak 2004), R 2.13 (R

Project for Statistical Computing, Vienna, Austria) and Mesquite 2.73 (Maddison &

Maddison 2010). Size variables (standard length, dorsal fin area, sword size) were log transformed for all analyses. Analyses were performed within each species unless noted.

133

Morphology

I assessed male morphology to evaluate correlations between male traits and male

use of the dorsal fin during courtship. I also assessed female morphology to quantify

sexual dimorphism in the dorsal fin. The morphological traits I examined included dorsal

fin size (area) and body size (standard length, SL). In the analyses, I compare 95 males

and 62 females from five species (Table 4.1). Live fish were digitally photographed with

their dorsal fins raised and then were measured for standard length (mm) with callipers. I

measured standard length again with the straight line selection tool in ImageJ (1997–

2009, National Institutes of Health, Bethesda, MD, U.S.A.) to convert from pixels to

millimetres for digital photographs. Dorsal fin area was measured with the polygon

selections tool and converted from pixels to mm2.

I used reduced major axis regression (RMA) to assess the relationship within each

species between standard length and dorsal fin area for each sex. RMA regression is

commonly used for studying allometric relationships and is more appropriate than

ordinary least squares regression when both variables in the analysis may have

measurement error (McArdle 1988; LaBarbera 1989; Blob 2000). Since dorsal fin area (a two-dimensional measure) was compared to standard length (a one-dimensional measure), the slope of the log–log regression should be 2.0 for isometry (Warton &

Weber 2002; Warton et al. 2006). I tested for an allometric relationship by calculating the

95% confidence interval of the slope of the regression. An isometric relationship would

134 indicate that dorsal fin size changes proportionally with standard length across the range of measurements. Differences from isometry (i.e. allometry) could suggest that there is selection on the size of the dorsal fin in addition to selection on overall size of an individual.

I tested for sexual dimorphism in dorsal fin size by performing another RMA regression to obtain the residuals for dorsal fin area relative to SL across the sexes. I then performed an unpaired t-test on the residuals of the RMA regression to test differences between males and females. To examine the relationship between dorsal fin size and male behaviors in the male–female interactions (below), I calculated residuals within species for dorsal fin area relative to SL.

Male-Female Interactions

The behaviors of male-female pairs across all species (N = 16 for X. multilineatus;

N = 20 for X. cortezi; N = 20 for X. nezahualcoyotl; N = 13 for X. helleri) were observed in a 78-litre aquarium. Pairs acclimated for 10 min with the female in an opaque chamber. Once the chamber was removed, I recorded the time the male raised his dorsal fin over a period of 10 min starting with the first interaction. Each male was also tested alone to provide a baseline estimate for how often a male raises his dorsal fin when he is not interacting with another fish. The time a male raised his dorsal fin when alone was recorded using the same procedure (10 min acclimation, 10 min observation). The order

135

of the two tests (with and without a female) was randomized, and the time the dorsal fin

was raised with and without a female was compared using a paired t test. The difference

between the amounts of time a male raised his dorsal fin in each test (with and without a

female) was the measure of a male’s “strength of response” to females, with positive

values indicating that a male spent more time with his dorsal fin raised when females

were present.

I examined whether the male’s strength of response to females varied with female

and male morphology. I used Akaike’s (1974) Information Criterion (AIC) to determine

the most parsimonious model for explaining the strength of response within each species.

AIC selects models by weighting the residual error of each model against the number of

parameters in the model. The parameters I assessed were male SL (covariate), female SL

(covariate), male absolute dorsal fin area (covariate) and residual male dorsal fin area

(covariate). I included all possible models with up to five parameters (three assessed

parameters plus the intercept and error terms), as well as the null model (includes only

the intercept and error term). I did not include the parameters absolute male dorsal fin

area and relative male dorsal fin area in the same models. Since some models included

many parameters (K) relative to sample size (N), I used AIC corrected for small sample

sizes (Anderson et al. 2000): AICc = 2k – 2 ln (likelihood) + (2k (k+1))/(N – k – 1). The model with the minimum AIC was considered to have the highest probability given the data (Anderson et al. 2000). Models with ∆AICc less than 2 are presented since models

with a lower ∆AICc are more likely to be biologically significant and therefore are

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considered competing models. For the model with ∆AICc equal to 0, I also present the

ANOVA table when the null model was rejected.

Phylogenetic Comparisons

I compared dorsal fin area across species by performing a regression correction for phylogenetic relationship in R (Revell 2009) using the phylogeny proposed by

Rauchenberger et al. (1990) to obtain the residuals for dorsal fin area relative to SL across species. Because some species have allometric dorsal fins, suggesting the potential for antagonistic selection on dorsal fin size between large and small males, I performed this analysis twice. In one analysis I used the average measurements across all males in each species, and in the other analysis I used the average measurements of the five largest males in each species. To assess the ancestral state of male dorsal fin size in the Northern swordtail clade, I reconstructed the character history using parsimony in Mesquite

(Maddison & Maddison 2010) using the dorsal fin residuals obtained in the analysis above.

To assess the ancestral state of use of the dorsal fin in the Northern swordtail clade, I reconstructed the ancestral state of courtship behavior in Mesquite (Maddison &

Maddison 2010). After assessing the variation in use across the species tested, use of the dorsal fin during courtship was scored as one of three states: increasing use of the dorsal fin during courtship, no increase use of dorsal fin during courtship, or polymorphism in

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use of the dorsal fin during courtship. Finally, to determine if there was a relationship

between use of the dorsal fin and exaggeration of the dorsal fin I used independent

contrasts to compare the difference in time dorsal fin was raised when courting as

compared to alone to the residuals of the dorsal fin area in relation to body size.

Results

Morphology

The slope for the relationship between dorsal fin area and standard length in males was significantly different from isometry in X. cortezi, X. multilineatus and X. nezahualcoyotl according to the 95% confidence intervals (slope=2 for isometry, Table

4.1). In these species, larger males had larger dorsal fins for their SL, suggesting different selection on dorsal fin size in large as compared to small males in these three species.

Female dorsal fin area was not significantly different from isometry in any species (Table

4.1). The dorsal fin was sexually dimorphic in every species; males had significantly larger dorsal fins than females relative to SL (Table 4.2).

Male-Female Interactions

Males in X. birchmanni, X. cortezi, and X. multilineatus increased use of the dorsal fin in the presence of females (X. birchmanni: t14=4.00, P=0.001, X. cortezi:

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t19=2.41, P=0.026, X. multilineatus: t17=2.84, P=0.011, Fig. 4.1). Male X. nezahualcoyotl

decreased the amount of time the dorsal fin was raised in the presence of females (t19=-

2.12, P=0.048, Fig. 4.1). Male X. helleri did not change the amount of time that the

dorsal fin was raised in the presence of females (t15=-0.95, P=0.357, Fig. 4.1). The lack of a significant difference for male X. helleri was due to the fact that males had their dorsal fins raised during most of the time they were alone, as well as the time they were interacting with females.

In considering the influence of male and female morphology on the use of the dorsal fin during courtship, the null model best explained strength of response (strength

of response = time dorsal fin raised with female – time dorsal fin raised without female)

in X. birchmanni, X. cortezi, X. multilineatus, and X. helleri, indicating that none of the morphological variables included in the analysis explained additional variation in strength of response. In X. nezahualcoyotl, there were two models that best explained variation in strength of response. One model included male SL, female SL, and the

2 residuals for male dorsal fin area (K=5, AICc=176.33, r =0.654, F3,15=11.919, P<0.001).

The second model for strength of response and its associated statistics were identical except that dorsal fin area was included instead of residual dorsal fin area. Therefore, I

have only presented the first model. Smaller male X. nezahualcoyotl raised their dorsal

fins more than larger male X. nezahualcoyotl (B = -1059.75, F1,15=5.25, P=0.037 Fig.

4.2a). Male X. nezahualcoyotl with larger dorsal fins relative to their SL raised their dorsal fins more than males with smaller dorsal fins for their SL (B = 2267.28,

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F1,15=34.86, P<0.001 Fig. 4.2b). Finally, males in this species raised their dorsal fins less

when interacting with larger females (B = -1951.83, F1,15=13.53, P=0.002 Fig. 4.2c).

Phylogenetic Comparisons

After controlling for phylogenetic relationships, X. helleri had the smallest dorsal

fins for their SL, followed by X. multilineatus and X. nezahualcoyotl. Xiphophorus

birchmanni and X. cortezi had the largest dorsal fins for their SL (Fig. 4.3). The ancestral

state reconstruction found that the dorsal fin increased in size at the base of the Northern

swordtails, as well as at the clade giving rise to X. cortezi and X. birchmanni. The

ancestral state reconstruction for the dorsal fin as a signal during courtship was

ambiguous at the base of the Northern swordtail clade, but the signal was clearly present

at the base of the clade shared by X. cortezi, X. birchmanni, and X. multilineatus (Fig.

4.3). Sexual dimorphism for the size of the dorsal fin is the ancestral state for the

Northern swordtails (results not shown). The relationship between the residuals for dorsal fin size and strength of response was not significant (P = 0.12).

Discussion

This study found extensive variation in the degree of allometry of dorsal fin size and use of the dorsal fin during courtship across the species of swordtail fishes examined.

The main patterns that emerged support the hypothesis that the dorsal fin is an important

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signal during courtship in the Northern swordtails. In addition, there was evidence to

suggest that the size of the dorsal fin influences its use during courtship, a pattern that was detected both within and across species. However, it is not clear if increased dorsal fin size evolved to enhance the use of the dorsal fin during courtship, as the dorsal fin was sexually dimorphic even in the species that did not raise the dorsal fin as a signal directed toward females. In addition, determining where use of the dorsal fin during

courtship evolved depends on how this behavior is assessed. Finally, dorsal fin size was

not always allometric in relation to male size across the species that did raise their dorsal

fin more during courtship. Together these results suggest that while the evolution of an enlarged dorsal fin in males may be influenced by the importance of raising the dorsal fin during courtship, several other factors are also involved in the evolution of this trait.

The ancestral state reconstruction could not determine whether the dorsal fin was a signal directed toward females at the base of the Northern swordtail clade. The ancestral state is ambiguous due to the polymorphism in male behavior in X. nezahualcoyotl. However, the use of the dorsal fin during courtship by some male X. nezahualcoyotl could be inferred as the signal being present in this species, even though males were polymorphic for using the dorsal fin during courtship. This definition of the dorsal fin as a courtship signal changes the analysis so that the use of the dorsal fin during courtship is present at the base of the Northern swordtail clade. While phylogenetic comparative methods can be powerful for understanding the evolution of characters, there are limitations to their use. For the independent contrasts comparing

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dorsal fin size and male strength of response, a single value (the mean) was included for each species, which can be misleading in the case of polymorphisms within species. Even

though X. nezahualcoyotl was polymorphic for dorsal fin use, the mean strength of

response in this species was negative and therefore was included in the analysis as a

decrease in dorsal fin use.

Because male X. helleri have smaller dorsal fins, raising the dorsal fin may be less

energetically costly than in other species. Male X. helleri raised their dorsal fins

throughout most of the trials, regardless of whether a female was present or absent, and

the time the dorsal fin was raised when alone was greather than in other species.

Lowering the dorsal fin when females are absent could reduce energetic costs, suggesting

that the larger dorsal fins in the Northern swordtails could be an honest signal to females

of male courtship effort (Zahavi 1975). The idea that X. helleri males with smaller dorsal

fins for their size can keep the dorsal fin raised during courtship as well as when alone

could be investigated more thoroughly by examining the use of the dorsal fin across more

species. Xiphophorus helleri was the only Southern swordtail included in this study, and

there may be evolutionary differences beyond the smaller dorsal fin size that are affecting

use of the dorsal fin in this species.

Males had larger dorsal fins than females for their body size in every species. The

use of the dorsal fin as a signal directed toward females during courtship indicates a role

of sexual selection in the evolution of larger dorsal fins in males. However, past selection

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for dorsal fin size could produce sexual dimorphism even though sexual selection may not be currently selecting on dorsal fin size. Sailfin mollies (genus: Poecilia) are another

poeciliid with large, sexually dimorphic dorsal fins that are used during courtship

(Hankison & Ptacek 2007), so it is possible that the sexually dimorphic dorsal fin is the

ancestral state for poeciliids. In addition to sexual selection, ecological factors could

produce sexual dimorphism in dorsal fin size, in particular if there is an optimal

relationship between dorsal fin size and body size in certain habitats and selection for

differences in body size between the sexes. A more extensive analysis of sexual

dimorphism in body size and dorsal fin size could uncover such correlations (reviewed in

Andersson 1994).

While sexual dimorphism in the dorsal fin was found in each Northern swordtail,

allometry in dorsal fin size was not. The presence of allometry in ornament size can indicate sexual selection; however, allometry is not a necessary requirement for sexual selection (Kodric-Brown et al. 2006; Bonduriansky 2007). In X. birchmanni, a species that has large sexually dimorphic dorsal fins, dorsal fin size was isometric. This is a species with all large males, suggesting that there may not be differential selection on males of different body sizes. Allometry may be more prevalent in species with a wide range of male sizes, which could also increase differential selection pressures on males.

One example of this would be X. multilineatus, a species with alternative mating strategies that select for different traits in large courter and small sneaker males

(Zimmerer & Kallman 1989). Due to the behaviors of the sneaker males, which use

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coercive mating in addition to courtship, selection on the dorsal fin size between courters

and sneakers could be antagonistic.

In every species, there was a strong correlation between male dorsal fin size and

body size, suggesting that the dorsal fin may provide redundant information about body size (Møller & Pomiankowski 1993; Johnstone 1997). The use of the dorsal fin during courtship could emphasize larger male body size, which is known to be preferred by females in several different species of swordtails (Ryan et al. 1990; Rios-Cardenas et al.

2007; Fisher et al. 2009). Studies varying sword and body size in X. helleri found that females had no preference between males of similar total length (sword size + body size) when sword size and body size varied, suggesting that female preferences for swords is

actually due to female preferences for larger body size (Rosenthal & Evans 1998). A

similar study found that dorsal fin size may reflect female preference for body size in

sailfin mollies, Poecilia latipinna (MacLaren et al. 2004). However, preferences in

Xiphophorus for dorsal fin size appear more complicated. In X. birchmanni, females have

a preference for both large (Robinson et al. 2011 (Chapter 3)) and small (Fisher &

Rosenthal 2007; Fisher et al. 2009) dorsal fins, suggesting disruptive selection on dorsal

fin size. In X. helleri, females have a preference for the dorsal fin to body size ratio that is natural in this species, suggesting stabilizing selection that may reflect species recognition cues (MacLaren & Daniska 2008). However, when the dorsal fin to body size ratio was constant in X. helleri, females preferred larger males over smaller males, indicating that this species still has a preference for larger body size (MacLaren &

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Daniska 2008). Since male body size does not change significantly after sexual maturity

(Kallman 1989), body size is more likely to provide females with a combination of

genetic and long-term developmental information.

The results of this study highlight the importance of the dorsal fin as a sexual

ornament in several species of Xiphophorus. Future studies should investigate the

relationship between use of the dorsal fin during courtship and dorsal fin size in more species in each clade of Northern and Southern swordtails to tease apart whether the

difference detected in use of the dorsal fin between X. helleri and the other species represents the evolution of a morphological trait to enhance a behavior during courtship.

Although the dorsal fin was not a signal directed toward females in X. helleri, since males always have the dorsal fin raised, females assess dorsal fin size as a cue in this species.

This could suggest that female preference led the initial exaggeration of dorsal fin size.

The correlation between the exaggerated dorsal fin and reduced use of the dorsal fin when males are alone may reduce the costs of a larger trait, leading to evolution of the dorsal fin as a courtship-specific signal. Finally, variation I detected here provides the

necessary context in which to describe the states of the traits of interest, so that an investigation of the evolution of the sexually dimorphic dorsal fin using phylogenetic comparative methods in a broader survey of poeciliids can be conducted.

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Acknowledgements

I thank Christiane Meyer for providing X. helleri, Elise Baron, Dan Glaser, and

Sarah Klim for assistance with courtship trials, Brittany Tarselli for assistance scoring

photographs, Molly Morris for insightful comments throughout the project and

manuscript and for use of her fish stocks, and Debora Goedert for comments on the

manuscript. D.M.R. was supported by an Ohio Center for Ecology and Evolutionary

Studies fellowship.

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Table 4.1. Range of sizes and the slope representing the relationship between (log transformed) standard length and dorsal fin area, and the 95% confidence intervals surrounding the slope. Standard length in mm Dorsal fin area in mm2 Species N (mean , range) (mean, range) r2 Slope CI slope Females X. birchmannia 10 42.00, 30.72-49.48 64.86, 32.25-90.20 0.92 2.39 1.84-2.94 X. cortezi 16 39.03, 35.20-41.96 50.08, 39.59-75.47 0.05 4.04 1.87-6.22 X. helleri 15 53.27, 47.44-58.31 104.56, 74.70-128.39 0.41 2.57 1.38-3.75 X. multilineatus 11 33.11, 30.02-39.58 39.62, 29.48-49.79 0.59 0.56 1.18-3.39 X. nezahualcoyotl 10 30.76, 24.24-44.70 30.22, 18.09-57.50 0.94 1.90 1.50-2.29 Males X. birchmannia 17 49.14, 41.72-57.48 244.52, 163.92-347.59 0.63 2.48 1.65-3.32 X. cortezi 22 36.51, 29.86-41.78 96.61, 27.92-155.66 0.58 4.41* 3.04-5.77 X. helleri 17 50.13, 42.20-53.42 117.65, 62.47-154.80 0.61 2.97 1.94-3.99 X. multilineatus 18 29.54, 25.70-37.50 35.75, 20.43-67.99 0.56 5.05* 3.29-6.82 X. nezahualcoyotl 21 28.84, 21.96-37.59 39.92, 19.21-103.43 0.83 3.37* 2.70-4.04 a Data from Robinson et al. 2011 *Slope is significantly different from isometry.

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Table 4.2. Unpaired t-test results for sexual dimorphism in dorsal fin size. Dorsal fin residuals Species DF Mean Confidence interval t P X. birchmannia 25 0.207 0.065-0.349 3.29 0.003 X. cortezi 36 0.341 0.221-0.461 8.09 <0.001 X. helleri 30 0.116 0.052-0.180 5.09 <0.001 X. multilineatus 27 0.110 0.018-0.202 3.15 0.004 X. nezahualcoyotl 29 0.170 0.082-0.258 5.73 <0.001 a Data from Robinson et al. 2011

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P =0.357

P =0.011 P =0.048 P =0.026 P =0.001

Time dorsal fin raised (s) Time dorsal fin raised

X. birchmanni X. cortezi X. helleri X. multilineatus X. nezahualcoyotl

Species Figure 4.1. Mean time males of five swordtail species raised their dorsal fins alone (grey bars) and with females present (white bars) during a 10 min observation. Significance was calculated from paired t-tests and rounded to the nearest one-thousandth. Error bars indicate standard deviation.

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) a b c s Raised more Raised more (

onse p

th of res

Stren

Male standard length Male dorsal fin residuals Female standard length Raised less

Figure 4.2. Partial regression plots for strength of response in Xiphophorus nezahualcoyotl. Strength of response varied with (a) male standard length, (b) residuals for male dorsal fin area and (c) female standard length.

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Figure 4.3. Maximum parsimony reconstruction of the ancestral states of the male dorsal fin morphology and use of the dorsal fin during courtship. The first number for each node represents the residuals for male dorsal fin area averaging all males in each species. The second number represents the residuals for dorsal fin size averaging only the five largest males in each species. Residuals were calculated using methods by Revell (2009). Areas of pie indicate relative support for different ancestral states of courtship. White is not using the dorsal fin during courtship, black is increased use of the dorsal fin during courtship, and grey is a polymorphism in use of the dorsal fin during courtship. Northern swordtail phylogeny from Rauchenberger et al. (1990).

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CHAPTER 5: GENETIC VARIATION AND PHYLOGEOGRAPHY OF THE

SWORDTAIL FISHES X. BIRCHMANNI, X. CORTEZI, AND X. MALINCHE

(CYPRINODONTIFORMES: POECILIIDAE)

Abstract

In this study I used the mitochondrial control region and eight microsatellite loci to examine the phylogeography of Xiphophorus malinche and expand on previous studies of

X. cortezi and X. birchmanni, the three species in the hypothesized Cortezi clade of swordtails. Previous studies using mitochondrial DNA have found that haplotypes of X. cortezi are paraphyletic to X. malinche, questioning whether these are separate species.

The results of the mitochondrial DNA are consistent with prior studies questioning the species status of X. cortezi and X. malinche; haplotypes of both species were paraphyletic with respect to each other. However, microsatellite analyses uncovered three genetic groups corresponding to the three species. Populations of X. malinche and X. cortezi that had mitochondrial haplotypes that differed by one base pair did not cluster together on the microsatellite minimum evolution trees. Instead, in the STRUCTURE analysis as well as the minimum evolution trees for the microsatellites, all populations of X. malinche and

X. cortezi clustered within their respective species. Within species, the microsatellite and mitochondrial data generally agreed. I found a pattern of isolation by distance in both the mitochondrial and microsatellite markers. In X. cortezi and X. birchmanni, isolation by distance was better explained by river distances. Straight line distances better explained

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genetic variation in X. malinche, indicating that stream capture is affecting gene flow in this species. The pattern of isolation by distance in X. malinche also indicates that this

species has historically existed at higher elevations, rather than moving to higher

elevations as a result of climate change.

Introduction

Studying phylogeographic variation within species is an important part of understanding the processes that produce biodiversity (Moritz 2002). Most studies of

phylogeographic variation continue to use single markers (dominantly mitochondrial

DNA), even though multiple markers are necessary to accurately reconstruct genetic

relationships due to frequent discordance between gene and species trees (e.g., Brito &

Edwards 2009; Wiens et al. 2010; Zink 2010). Mitochondrial DNA remains the preferred

marker in animals for several reasons, including its relatively higher mutation rate

relative to nuclear genes, the availability of universal primers, and the ability to create

phylogenetic relationships over other highly variable markers that rely on gene frequency

data (reviewed in Avise 2000; Brito & Edwards 2009). For studies attempting to

reconcile the pitfalls of single marker studies with the lack of informative nuclear

sequence data available, microsatellites also have become an important tool (e.g. Suk &

Neff 2009; Earl et al. 2010; Marchetto et al, 2010). Their high genetic diversity and

evolution rates make it possible to find existing spatial patterns at fine geographic and

temporal scales (Estoup et al. 1998; Ellegren 2004).

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This study assesses phylogeographic variation in Xiphophorus birchmanni, X. cortezi, and X. malinche. These species belong to the Northern swordtails and are found in several rivers in the in the Río Pánuco basin in the Sierra Madre Oriental (Fig. 5.1).

Hybrid zones have been found between X. birchmanni and X. malinche (Rosenthal et al.

2003; Culumber et al. 2011) and between X. birchmanni and X. cortezi (Gutiérrez-

Rodríguez et al. in prep). There is no evidence of X. malinche and X. cortezi occurring sympatrically. Xiphophorus malinche only occurs at high elevations in streams with sandy bottoms, X. cortezi occurs at variable elevations in small streams with rocky bottoms, and X. birchmanni occurs at mid and low elevations in streams with rocky bottoms (Rauchenberger et al. 1990).

These three species share several morphological similarities which have been used to describe their relationships (Rauchenberger et al. 1990; Gutiérrez-Rodríguez et al.

2008). Xiphophorus malinche was first described by Rauchenberger et al. (1990) as a sister species to X. birchmanni, and in a clade with X. cortezi. Rauchenberger et al.

(1990) also used allozymes to examine the relationships among the Northern swordtails, although at the time only one population was included for the newly described X. malinche. Other studies based on different genetic markers have reached conflicting conclusions regarding the relatedness of these three species. Studies using RAPDs identified X. malinche and X. birchmanni as sister species (Borowsky et al. 1995), while studies using allozymes (Morris et al. 2001) and analyzing nuclear genes separately from mitochondrial (Meyer et al. 2006) were inconclusive on the relationships of these three

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species. Studies using mitochondrial markers consistently show X. malinche and X. cortezi as more closely related than X. malinche and X. birchmanni, and in some cases evidence suggested X. birchmanni as being more closely related to other Northern swordtails (i.e. not part of the Cortezi clade) (Meyer et al. 2006; Gutiérrez-Rodríguez et al. 2007, 2008). A phylogeographic study of X. cortezi suggested that some populations of X. malinche might be X. cortezi (Gutiérrez-Rodríguez et al. 2007). However, the evidence could also suggests that X. malinche evolved from within X. cortezi as X. cortezi was shown to be paraphyletic, with three haplotypes of X. cortezi and X. malinche included in one of the X. cortezi clades (Gutiérrez-Rodríguez et al. 2007). Finally, a study that combined mitochondrial DNA, nuclear DNA and phenotypic data suggested X. malinche could be the sister species of X. birchmanni or X. cortezi, depending on the analysis used (Marcus & McCune 1999).

The present study aims to further examine the phylogeographic variation within

X. birchmanni, X. cortezi and X. malinche using mitochondrial DNA and microsatellites.

Both types of markers have been successful at describing genetic variation in poeciliids

(e.g., mitochondrial DNA: Mateos et al. 2002; Mateos 2005; Doadrio et al. 2009; Jones &

Johnson 2009; microsatellites: Soucy & Travis 2003; Hankison & Ptacek 2008; Barson et al. 2009; Tatarenkov et al. 2010). I will add new populations for each species, and present the first comprehensive study of phylogeographic variation in X. malinche. Several

populations of X. malinche exhibit physical isolation in headwater streams. Similar to

previous mitochondrial phylogeographies of X. birchmanni and X. cortezi (Gutiérrez-

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Rodríguez et al. 2007, 2008), I predict that populations of X. malinche will exhibit

significant genetic differentiation. By using microsatellite markers on the same dataset, I

will assess whether microsatellite variation reflects variation seen in mitochondrial DNA

across the species. Specifically, I would like to reassess the species status of X. malinche

and X. cortezi based on the overwhelming similarity detected in the mitochondrial

haplotypes, and the lack of support for X. cortezi as a monophyletic species in previous

studies (Gutiérrez-Rodríguez et al. 2007, 2008). I also will be able to assess genetic

substructure within each species. Population structure within drainages cannot be

assessed with mitochondrial DNA exclusively. The previous phylogeographies of X.

birchmanni and X. cortezi each found that some drainages contained a single haplotype

(Gutiérrez-Rodríguez et al. 2007, 2008). I predict genetic structure will follow an

isolation by distance model, and that populations within drainages will be more genetically similar than across drainages.

Methods

Sample Collection

Xiphophorus birchmanni, X. cortezi, and X. malinche were collected from 35 sites

in Mexico (Fig. 5.1, Table 5.1). Specimens of X. malinche (N = 94) were collected during

two collection trips: from Tepeyiza, Amajac, Tamala, and Culhuacán in October 2007;

from Río Claro, Soyatla, Otlazintla and Zontecomatlán in December 2004. Specimens of

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X. cortezi (N=129) were added to those collected for a previously published phylogeography study of this species (N=65, Gutiérrez-Rodríguez et al. 2007). The new

specimens of X. cortezi were collected in April 2004 from Conchita and Tecolutlo, in

January 2007 from Tanute and Cebolla, in March 2008 from Río Huichihuayán, Oxitipa,

Tambaque, Tampamolon, and Tancuilin, and in December 2008 from Tecolutlo.

Specimens of X. birchmanni (N= 43) were added to those collected for a previously

published phylogeography study of this species (N=122, Gutiérrez-Rodríguez et al.

2008). New specimens of X. birchmanni were collected in October 2007 from Río

Amajac, Contzintla, Garces II and San Pedro, in January 2007 and March 2008 from Río

Claro II. Specimens were collected using electroshockers, seines, and minnow traps. Fish

were anesthetized with tricaine methane sulphonate (MS222). Specimens for other

Northern swordtails and the Southern swordtail X. helleri were also used: X. helleri from

Río Sarabia-Palomares, X. pygmaeus from Huichihuayán, X. multilineatus from

Tambaque, X. continens from Dos Rios, X. nigrensis from Río Coy, and X. nezahualcoyotl from Dos Rios.

A fin clip from each specimen was stored in salt-saturated 20% dimethyl sulphoxide solution (Seutin et al. 1991) and the rest of the specimen was preserved in

95% ethanol. Specimens from Cebolla, Conchita, Tanute and Tecolutlo were preserved in

95% ethanol and a fin clip taken immediately prior to DNA extraction.

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Molecular Analyses

DNA was extracted from fin clips of the new collected specimens from all three species (N = 342) using the DNeasy tissue kit (Qiagen Inc.) following the manufacturer instructions. A portion of the mitochondrial control region was amplified using standard protocols for polymerase chain reaction (PCR) with master mixes from Apex (Apex Life

Sciences Co.) and Bioline (Bioline USA Inc.) on a MJ Research PTC-100 thermocycler

(MJ Research Inc.). Samples were amplified using either forward primers K (5′-

AGCTCAGCGCCAGAGCGCCGGTCTTGTAAA-3′, Lee et al. 1995), L15995n (5′-

AACCTCCRCCYCTAACTCCCAAAG-3′), Gutiérrez-Rodríguez et al. 2008), or

L16378n1 (5′-ATGYAGTAAGARACCA-3′, Gutiérrez-Rodríguez et al. 2008) and reverse primers G (5′-CGTCGGATCCCATCTTCAGTGTTATGCTT-3′, Lee et al. 1995) or H16498n (5′-GGGTAAYGAGGAGTATG-3′, Gutiérrez-Rodríguez et al. 2008). PCR products were purified with QIAquick PCR Purification Kit (Qiagen Inc.) and sequenced using BigDye terminator cycle sequencing kit and read on a 3730 automated sequencer

(Applied Biosystems) at Ohio State University Plant Microbe Genomics Facility.

Forward and reverse control region sequences were aligned using the default settings in

Geneious 5.0.2 (Biomatters Ltd.) followed by manual alignment in SE-AL 2.0a11 (A.

Rambaut 2007). A large indel of 24 bp that occurred in two haplotypes (M5, M7) was coded as a single evolutionary event.

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Samples were genotyped for eight microsatellite loci (D6, D15, D21, D29, T30,

T38, MSD23, mATG61) with primers developed for Xiphophorus by Seckinger et al.

(2002) and Walter et al. (2004) for 454 individuals (Table 5.2). When a large number of specimens were available, more individuals were sequenced for microsatellites than for mitochondrial DNA, since few haplotypes had previously been found. Forward primers were labeled with fluorescent markers, either 6FAM (loci T30, mATG61), VIC (loci D6,

D21), NED (loci D15, MSD23), or PET (loci D29, T30) (Applied Biosystems). Ninety- two of the samples were amplified for loci D6, D15, D21, D29 and T38 in another study

(Gutiérrez-Rodríguez et al. in prep) using the forward primers labeled with HEX for D6 and D21, and 6FAM for D29. To standardize sizes for using different fluorescent dyes, 3 samples per repeat length were amplified with each dye. Microsatellites were amplified using standard protocols for polymerase chain reaction (PCR) with master mixes from

Apex (Apex Life Sciences Co.) and Bioline (Bioline USA Inc.) on an MJ Research PTC-

100 thermocycler (MJ Research Inc.). PCR products were diluted in distilled water between 1:10 and 1:200 depending on the concentration of the PCR product, and combined into two multiplexes, one including D6, D15, D29 and T38, and the other including the remaining loci. PCR products were sent to Ohio State University Plant

Microbe Genomics Facility and read on a 3730 automated sequencer (Applied

Biosystems). Samples were standardized with -500 LIZ size standard (Applied

Biosystems) and analyzed with GeneMapper 4.0 (Applied Biosystems). Microsatellite bins were adjusted to standardize bin size across runs using Microsoft Excel 2003.

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Statistical Analyses

Mitochondrial Control Region

Relationships Among Haplotypes

I examined the phylogenetic relationships among distinct mtDNA haplotypes with maximum likelihood, Bayesian analyses and maximum parsimony. Models of molecular evolution were selected based on Akaike information criterion corrected for small sample size (AICc) for maximum likelihood and Bayesian information criterion (BIC) for

Bayesian analysis using jModeltest 0.1.1 (Posada 2008). I included sequences from the

six other species of Northern swordtails to help determine relationships within the putative cortezi clade. The Southern swordtail X. helleri was used as an outgroup.

The maximum likelihood analysis was performed with PhyML 3.0 (Guindon et al.

2010) on the ATGC bioinformatics platform (atgc-montpellier.fr) using the substitution model supported by jModeltest (TrN + G, gamma shape parameter= 0.011) with 1000 bootstrap replicates. Tree topologies were found using subtree pruning and regrafting.

Bayesian analysis was carried out using the MrBayes plugin (Huelsenbeck & Ronquist

2001) in Geneious 5.0.2. The substitution model selected by jModeltest (TrN + G) is not included in MrBayes, thus I used the GTR + G (gamma shape parameter= 0.011), which is the closest model to TrN + G available in MrBayes. Four heated Markov chains

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(temperature = 0.2) were run 10,000,000 generations with a burnin of 500,000

generations. Trees were sampled every 2,000 generations for a total of 9,500 post burn-in trees and a consensus topology was created using the consensus tree builder in Geneious

5.0.2. Gaps were treated as missing data in both analyses. Bayesian posterior probabilities

for specific phylogenetic hypotheses were calculated by using the proportion of post

burn-in trees from MrBayes that supported each hypothesis (Lewis 2001). The specific

hypotheses tested were 1) the monophyly of X. malinche and X. cortezi, and 2) the

Cortezi clade of Rauchenberger et al. (1990), including X. birchmanni, X. cortezi and X.

malinche. A nexus file of the resulting trees from the Bayesian analysis was exported

from Geneious 5.0.2 and loaded into a nexus tree applet that was created with C#

(Microsoft Co.). The applet calculates the number of trees that include specified taxa as a

monophyletic group.

The statistical parsimony method by Templeton et al. (1992) was also used to

infer the relationship among haplotypes using TCS 1.21 (Clement et al. 2000). The

parsimony network was constructed with the default 0.95 probability connection limit

and treated gaps as a fifth state. The ancestral haplotypes inferred from the statistical

parsimony network were compared to the ancestral haplotypes inferred by the parsimony

tree created in Mega 5.05 (Tamura et al. 2011). The maximum parsimony tree was

constructed using the close neighbor interchange method using 100 initial random trees,

with 1000 bootstraps. Gaps were included in the analysis.

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Population Genetic Analyses

All population genetic analyses were performed for each of the species. I assessed

genetic variation within locality by calculating gene diversity (h) and nucleotide diversity

(π). Analyses of molecular variance (AMOVA) were performed using the TrN + G model

to calculate genetic distances with the gamma shape parameter= 0.011 as obtained from

MODELTEST. A total of 16,000 permutations were calculated to assess the significance

of each AMOVA. One AMOVA for each species used groups that corresponded to the

drainages where collection sites are located. I calculated the degree of genetic

differentiation between the sampled localities with pairwise FST and the significance was

assessed with 1000 permutations.

To test for a relationship between geographic and genetic distance, I performed

two Mantel tests, each one with 10,000 permutations using IBD 1.52 (Bohonak 2002). I

used Nei’s average number of pairwise differences between localities as the genetic

distance (Nei & Li 1979) and used river distances (the paths along water courses

connecting two localities) as well as straight-line distances (minimum great circle distance between two localities) as geographical distances. Each Mantel test used log genetic and log geographic distances.

I estimated demographic range expansion of haplotypes through a mismatch distribution analysis using the sum of squared differences (SSD) as a test statistic

(Schneider & Excoffier 1999). I also used Tajima’s D and Fu’s FS neutrality statistics to

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examine whether samples were at demographic equilibrium with respect to the

mitochondrial sequences. Each test was performed for each drainage, since most genetic

variation was structured within drainages based on AMOVA results, using 10,000

permutations in Arlequin 3.5.1.2 (Excoffier & Lischer 2010).

Microsatellite Analyses

I performed Bayesian genetic clustering on the microsatellite loci with

STRUCTURE 2.2.3 (Pritchard et al. 2000). STRUCTURE infers genetic clusters (K) using multilocus data. I used the admixture model of evolution with independent allele frequencies. Twenty five chains were run for each K, from K=1 to K=7. The length of the

burnin was 100,000 and the number of Markov chain Monte Carlo (MCMC) replications

after the burn-in was 100,000. Each run was checked for convergence. To determine the

most likely value of K, I averaged the log-likehoods across the runs for each K and

calculated the statistic ΔK based on the rate of change in the log probability of data

between successive K values (Evanno et al. 2005). First I used STRUCTURE to assess

the number of genetic groups across species. To examine genetic substructures, I repeated

the analysis within each group identified by STRUCTURE (i.e. species). Runs with the highest log likelihoods are presented for K=2 to K=4.

The genetic relationship among the collection sites of the three species was assessed by calculating Cavalli-Sforza and Edwards (1967) chord distances with Gendist

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in PHYLIP version 3.69 (Felsenstein 2005). Based on the mtDNA phylogenetic results, I

constructed a separate tree for X. birchmanni while X. malinche and X. cortezi were included in the same tree. I generated 1000 data sets by bootstrapping across loci using

Seqboot in PHYLIP. Minimum evolution trees were estimated with Fitch and a strict majority consensus tree was created using Consensus in PHYLIP and visualized with

TreeView 1.6.6 (R Page 2001).

For each locality and species, I used Arlequin to calculate allelic diversity, observed heterozygosity (HO), expected heterozygosity (HE), and genotypic linkage

disequilibrium between all pairs of loci using a Markov chain length of 10,000. In

addition I calculated allelic richness (AR) and inbreeding within localities (FIS) testing for

its significance with 1000 permutations in FSTAT 2.9.3 (Goudet 2001).

I assessed population structure among localities by calculating Weir and Cockerham’s

(1984) estimators of Wright’s (1978) F-statistics in the computer program FSTAT 2.9.3.

The estimators F and θ correspond to FIT (total inbreeding coefficient) and FST

(subdivision among sampled populations), respectively. I also calculated pairwise RST between localities in Arlequin. The significance of the estimators was determined by jackknifing and bootstrapping with 10,000 permutations. To test for a relationship between geographic and genetic distance, I performed two Mantel tests as described for the control region, using as genetic distance chord distances (Cavalli-Sforza & Edwards

1967), which were calculated in the computer program Populations 1.2.32 (O. Langella

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1999 http://bioinformatics.org/~tryphon/populations/).The locality Xiliatl (X. cortezi) was

not included in microsatellite analyses because there was not enough DNA left from the

previous study for this sample (Gutiérrez-Rodríguez et al. 2007).

Results

Mitochondrial Control Region

Relationships Among Haplotypes

Across the mitochondrial sequences for all three species there were 112 variable

sites out of the 816 bp analyzed (13.73%). Within species, there were 7 variable sites for

X. birchmanni (0.86%), 20 for X. cortezi (2.45%), and 17 for X. malinche (2.08%).

Haplotypes B1-6 for X. birchmanni and M1-2 for X. malinche are identical to haplotypes

of the same name in Gutiérrez-Rodríguez et al. (2008). However, because the sequences used in the current study were shorter than those of the previous ones, the 1 bp difference between haplotypes B2 and B3 was lost and these haplotypes were specified as a single

haplotype B2/B3. Haplotypes C1-9 for X. cortezi are identical to haplotypes H1-H9 in

Gutiérrez-Rodríguez et al. (2007). Haplotypes B7, M3-7, and C10-11 are unique to this

study (Table 5.1). Most haplotypes were restricted to each drainage except for B1, which

individuals sampled in Calabozo and Hules shared this haplotype. The same is true for

haplotypes C1 and C6 that were found in both Tampaón and Moctezuma drainages, and

168 for haplotype M2 that was shared by individuals form the Hules and Calabozo drainages.

In X. malinche, haplotype M1 was found in Moctezuma and Hules drainages and haplotype M2 was found in the Hules and Calabozo drainages. None of the mitochondrial haplotypes were shared across species.

The consensus trees obtained from Bayesian inference and maximum likelihood were generally similar, although the consensus of the Bayesian tree had stronger support for some clades (Fig. 5.2a). A single disagreement occurred between consensus tree topologies, with the Bayesian consensus tree forming a clade with M3 and M4 that was not supported by the maximum likelihood consensus tree. Both trees clustered haplotypes of X. birchmanni into a well supported clade (bootstrap 0.93, posterior probability 1.0,

Fig. 5.2a), and haplotypes of X. malinche and X. cortezi into another clade that also included X. multilineatus and X. nigrensis (bootstrap 0.93, posterior probability 1.0, Fig.

5.2a). There was little support for the two hypotheses tested using Bayesian posterior probabilities of the post burn-in trees: the monophyly of X. malinche and X. cortezi each had a low posterior probability (X. malinche=0, X. cortezi=0); the Cortezi clade

(Rauchenberger et al. 1990) containing X. birchmanni, X. cortezi, and X. malinche also had a low posterior probability (0). The haplotypes of X. cortezi and X. malinche formed a statistical parsimony network that was separate (i.e. unconnected) from X. birchmanni

(Fig. 5.3a), indicating that these haplotypes are separated by enough mutational steps

(more than the connection limit of 12) that the number is likely to be underestimated by parsimony. In X. birchmanni, differences between haplotypes ranged from one to four

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mutations. A single mutational step separated haplotypes of X. cortezi and X. malinche

(C1 and M4, C9 and M1). Fifteen mutations in X. cortezi and 18 mutations in X. malinche separated the most distantly related haplotypes. Across the two species, 25 mutations separated the most distantly related haplotypes. Haplotypes B1 and C1 were inferred to be ancestral according to outgroup weights (Castelloe & Templeton 1994), which are based on haplotype frequencies and position (interior vs. tip) in the network. The parsimony tree indicated that the ancestral haplotype is between B4 and the other haplotypes for X. birchmanni and between M3 and M4 and the other haplotypes for X. malinche (Fig. 5.3b). The ancestral haplotype for X. cortezi is between C6 and C10 and the other haplotypes.

Population Genetic Analyses

Haplotype and nucleotide diversity are summarized in Table 5.1. Several localities contained just one haplotype. Few localities had gene diversity over 0.50 (X. cortezi: Tampamolon, Huichihuayán, Conchita; X. birchmanni: Amajac, Sasaltitla; X. malinche: Tamala, Otlazintla). Nucleotide diversity was also low (π <0.005), indicating little variation in sequences within localities. The results of the AMOVA revealed significant genetic differentiation at every hierarchical level (Table 5.2). The AMOVAs

found that river drainages explained most of the variation in each species (80.17% X.

cortezi, 82.56% X. birchmanni, 91.74% X. malinche). Differences among localities

within each drainage explained much less variation (7.45% X. cortezi, 8.20% X.

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birchmanni, 4.67% X. malinche), differences within localities also did not explain much variation (12.38% X. cortezi, 9.24% X. birchmanni, 3.59% X. malinche).

Genetic differentiation between pairs of localities within each species is presented

in Tables 3-5. For X. cortezi, most localities within each drainage were significantly

different from most localities from other drainages (Table 5.3). However, Oxitipa and

Caldera from the Tampaón drainage were not significantly different from Tampamolon

that is in the Moctezuma drainage. For X. birchmanni, localities within each drainage were also significantly different from most localities from other drainages (Table 5.4).

However, most localities located in the Calabozo were not significantly different to those in Zontecomatlán. The Amajac locality was not significantly different from Xiliatl II, San

Pedro, Atlapexco, Pezmatlan, Contzintla, Otlazintla and Zontecomatlán. For X. malinche,

localities in the Zontecomatlán drainage were significantly different from localities in

other drainages (Table 5.5). The drainage differences were not as pronounced in X.

malinche as in the other species. Only the localities within the Zontecomatlán drainage

were significantly different from all localities in the other drainages.

In the mismatch distribution analysis, the null model of population expansion was

not rejected for most genetic groups. The exceptions were the drainages with a single

haplotype (X. cortezi Hules, X. birchmanni Moctezuma and Acamaluco, X. malinche

Calabozo, Table 5.6, Fig. 5.4). Tajima’s D and Fu’s Fs were not significant for any drainage, indicating that there has not been recent population expansion (Table 5.6).

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Mantel tests revealed significant and positive correlations between genetic

distance and both river distance and straight-line distance for each species (Fig. 5.5a, b,

P<0.05). The Mantel test using straight-line distances explained more variation

(r2=0.326) than river distances for X. malinche (r2=0.170, Fig. 5.5a, b), suggesting that

stream capture may have influenced gene flow in this species. For X. birchmanni, river

distances explained more genetic variation (r2=0.445) than straight-line distances

(r2=0.333, Fig. 5.5a, b). For X. cortezi, river distances and straight-line distances

explained similar amounts of genetic variation (river: r2=0.133, straight line: r2=0.196).

Microsatellite Analyses

In X. cortezi, a total of 189 alleles were found across all loci. The number of

alleles per locus varied from 7 to 93, and within localities across all loci this number

varied from 11 to 56 (mean alleles/locus, 1.375-8.875, Table 5.7). In X. birchmanni, a

total of 128 alleles were found across the loci. The number of alleles per locus varied

from 4 to 32, and within localities across all loci this number varied from 12 to 73 (mean

alleles/locus, 1.500-9.125, Table 5.7). In X. malinche, a total of 85 alleles were found

across the loci. The number of alleles per locus varied from 2 to 30, and within localities

across all loci this number varied from 13 to 40 (mean alleles/locus, 1.625-5.000, Table

5.7). Values of inbreeding coefficients within localities (FIS) were positive and deviated

significantly from zero in several localities of X. cortezi (Caldera, Oxitipa, Tanute,

Huichihuayán, San Martín and Tecolutlo) although they were only significant in one

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locality of X. malinche (Culhuacán) and three localities of X. birchmanni (Garces, Chila

and Otlazintla), indicating heterozygote deficiencies (Table 5.8). The sample sizes of some localities of X. birchmanni may have prevented detection of significant deviations from Hardy Weinberg equilibrium despite high FIS (Xiliatl II FIS =0.787, Amajac

FIS=0.389). No significant linkage disequilibrium was detected in any of the population- loci comparisons after Bonferonni corrections. The FIS(f) values when all populations

were combined differed significantly from zero when all loci were combined for X.

cortezi and X. malinche (Table 5.9). Loci mATG61, D21, MSD23 and T30 were

significantly different from Hardy-Weinberg equilibrium for X. cortezi, and locus D15

was significantly different Hardy-Weinberg equilibrium for X. malinche.

STRUCTURE

For cross-species comparison, the highest ΔK was K=3, and therefore three

groups best explains the genetic structure (Fig. 5.6). At K=3, the groups corresponded to

each species, with low admixture between groups (alpha=0.0370). However, the

Zontecomatlán population of X. malinche (Zontecomatlán drainage) was part of the

genetic group containing X. birchmanni. At K=2, one group corresponded to X. cortezi

and the second corresponded to X. malinche and X. birchmanni, with low admixture

(alpha=0.0365). At K=4, X. cortezi split into two genetic groups, one corresponding to

the Tampaón and San Pedro drainages, and the other roughly corresponding to the

Moctezuma and Hules drainages with low admixture between groups (alpha=0.0332).

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The Tecolutlo population of X. cortezi (Hules drainage), was admixed between X. cortezi

and X. malinche at K=3 but not at K=4. The Chapulhuacanito population of X. cortezi

(San Pedro drainage) was admixed between X. cortezi and X. birchmanni at K=3, but at

K=6 the genetic differences in this population became part of a different genetic group

within X. cortezi (not shown).

For X. birchmanni, ΔK selected K=2 as best explaining genetic structure (Fig.

5.7), roughly corresponding to the Acamaluco-Moctezuma-Hules, and Calabozo-

Zontecomatlán drainages with low admixture between genetic groups (alpha=0.0546).

However, there was admixture between some localities in the Calabozo and Hules

drainages. For X. cortezi, ΔK selected K=3 as best explaining genetic structure (Fig. 5.8),

corresponding to the Tampaón, Moctezuma, and Hules-San Pedro drainages, with some

admixture occurring mostly between the Tampaón and Moctezuma populations. In general there was low admixture between genetic groups (alpha=0.1084). For X.

malinche, ΔK selected K=2 as best explaining genetic structure (Fig. 5.9). At K=2, the

Zontecomatlán drainage split from the other drainages, with low admixture between

genetic groups (alpha=0.0313).

The minimum evolution tree had low support for drainage structure within X.

birchmanni (Fig. 5.2b). However, drainage structure was supported by the minimum

evolution trees in X. malinche and X. cortezi (Fig. 5.2c). In X. malinche, the Moctezuma

and Calabozo localities had high bootstrap support (97% and 92%, respectively). The

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Zontecomatlán drainage clustered together, while the remaining drainages formed a

second cluster. In X. cortezi, the Tampaón drainage had high bootstrap support (90%).

Localities in the San Pedro drainage grouped together and there was modest bootstrap

support for this clade (77%). Most of the localities of the Moctezuma drainage clustered

together; however, Tampamolon clustered with the localities in the Tampaón. Within the

Moctezuma drainage, the Tancuilin, Cebolla and Conchita localities formed a well-

supported cluster (91% bootstrap support). Tecolutlo, the only X. cortezi locality in the

Hules drainage, did not cluster with any other drainage, but did cluster at the same node

as other X. cortezi drainages. All X. malinche populations also clustered together at a

node with modest bootstrap support (69%). Thus, X. cortezi and X. malinche populations

from the same drainages (Moctezuma, Hules) did not cluster together across species.

FIT(F) was significantly positive for most loci, as well as across loci for all three

species (Table 5.8), indicating a species-wide deficit in heterozygotes. FST(θ ) also was significantly positive for most loci, as well as across loci for all three species, indicating genotypic subdivision within each species. Estimates of population genetic differentiation

(RST) between pairs of localities within each species are presented in Tables 3-5. For X.

cortezi, localities within each drainage were significantly differentiated from most

localities from other drainages (Table 5.3), suggesting little recent gene flow between

drainages. However, some populations in different drainages were not significantly

different. The San Pedro localities (San Martín, Chapulhuacanito) were not significantly

different from some localities in each of the other drainages (Tampaón: Caldera;

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Moctezuma: Tampamolon, Huichihuayán; Hules: Tecolutlo). The Tecolutlo locality

(Hules) was not significantly different from the Tampamolon and Huichihuayán localities

(Moctezuma). For X. birchmanni, localities in the Zontecomatlán drainage were different from localities in most other drainages, with the exception of Calabozo. This indicates that X. birchmanni in the Zontecomatlán drainage may have less gene flow than other drainages. The Sasaltitla and Zontecomatlán localities also were not different from

Atlapexco (Hules). The Moctezuma and Acamaluco drainages were different from most other drainages, suggesting low gene flow between these drainages, with the exception of some populations within the Calabozo drainage. The Atlapexco population (Hules) was not significantly different than Xiliatl II (Acamaluco). For X. malinche, the Otlatzintla and Tepeyiza localities in the Zontecomatlán drainage were significantly different from most other localities, indicating little gene flow between this drainage and other drainages. However, the Zontecomatlán locality was not significantly different from other localities, most likely due to low sample size. For each species, there were also localities within drainages that were significantly different, suggesting there may be additional barriers to gene flow within some drainages.

Mantel tests revealed significant and positive correlations between genetic distance and river distance for both river distance and straight-line distance for each species (Fig. 5.5c, d, P<0.05). Straight-line distances explained more genetic variation

(r2=0.527) than river distances (r2=0.446) for X. malinche, indicating that stream capture has affected gene flow in this species. For X. birchmanni, river distance explained more

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genetic variation (r2=0.178) than straight-line distances (r2=0.083). For X. cortezi, river distances explained more genetic variation (r2=0.484) than straight-line distances

(r2=0.393). More genetic variation was explained in X. cortezi by geographic distance than in the other species.

Discussion

Genetic and Geographic Diversity within Species

This study corroborated prior findings that the mitochondrial control region had low to moderate gene diversity and low nucleotide diversity within populations, as well as high genetic diversity across populations (Gutiérrez-Rodríguez et al. 2007, 2008). Low levels of genetic diversity have been found in freshwater fishes (e.g., Carvalho et al.

1991; Shaw et al. 1994; Hänfling & Brandl 1998a, b; Mesquita et al. 2001) and in general, it tends to be lower in freshwater fishes than marine fishes and is thought to be due to the relatively few barriers to dispersal in the marine environment (Ward et al.

1994). Although it is possible that sample sizes in some populations restricted finding additional haplotypes, overall the additional sampling of the current study discovered few new haplotypes (X. cortezi, N=2, X. birchmanni, N=1). In X. malinche, five new haplotypes were found across the seven populations sampled. There were also few haplotypes per drainage within species (X. birchmanni 1-2/drainage, X. cortezi 1-

5/drainage, X. malinche 1-3/drainage). This study also found low nucleotide and

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haplotype diversity, which could be associated with a population expansion after a

bottleneck which was supported by the mismatch distribution in some river drainages.

However, the Tajima’s D and Fu’s FS results do not support population expansion.

Within each species there was evidence for isolation by distance, with similar results for the microsatellites and mitochondrial control region. River distances explain

more of the genetic variation than straight-line distances for X. cortezi, and this

relationship was stronger for the microsatellites than for the mitochondrial DNA. This

result for the mitochondrial contrasts the previous study (Gutiérrez-Rodríguez et al.

2007), which suggested that straight-line distances explained more of the genetic

variation in X. cortezi. While both measures of geographic distance explained genetic

variation in the previous and present study, outlier points were only found with the river

distance in the prior study, suggesting stream capture events affecting gene flow between

some populations. In X. cortezi, the relationship for isolation by distance was stronger

with microsatellite variation than with mitochondrial variation. The stronger signal in the

microsatellite markers may indicate that recent gene flow has been predominantly within

rivers, while historical gene flow may have been affected by both gene flow within rivers

and stream capture events. The AMOVA and STRUCTURE results both indicate that

genetic variation was explained by the river drainages in X. cortezi. The haplotypes were often found within a single drainage, similar to the prior phylogeography (Gutiérrez-

Rodríguez et al. 2007), with a few exceptions. The Oxitipa population in the Tampaón and the Tampamolon population in the Moctezuma share haplotypes (C1, C6) that are

178 otherwise specific to each drainage (C1 Moctezuma, C6 Tampaón), and microsatellite minimum evolution tree also places the Tampamolon population as more similar to populations in the Tampaón drainage. The Tampamolon population exists in a floodplain that spans part of the Tampaón and Moctezuma drainages, making more recent connections likely between these two drainages. The Oxitipa also comes close to the

Moctezuma in some areas. While the C1 haplotype was not sampled in the Tanute locality, it may have been undetected in this study due small sample size. The co- occurrence of the C3 haplotype in the San Pedro and Moctezuma is also likely due to a floodplain near the San Martín and Amacuzac populations. However, the Amacuzac microsatellite data indicates it is more similar to other populations in the Moctezuma. The genetic similarity of the Cebolla, Conchita and Tancuilin, and their distance from the

Huichihuayán population on the minimum evolution tree may be a result of dispersal barriers between these populations and those at the lower elevations in this drainage. For example, the Conchita population is present above waterfalls that would prevent upstream dispersal (Rauchenberger et al. 1990).

In X. birchmanni, the AMOVA and STRUCTURE results both indicate that genetic variation was explained by the river drainages. However, the STRUCTURE results also indicated admixture between drainages (Hules and Calabozo), suggesting recent gene flow between drainages, and haplotype B1 was found in both the Calabozo and Hules drainages, also supporting gene flow. While river distances explained mitochondrial variation and microsatellite variation better than straight-line distances, the

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relationship with river distance was much stronger with the variation in the mitochondrial

DNA than with variation in the microsatellites. While a stronger genetic variation by

distance relationship could suggest sex-biased dispersal, there is no evidence of this in

swordtails (X. helleri, Tatarenkov et al. 2010). The evidence from other poeciliids is

mixed, with Poecilia reticulata, P. gillii, and Gambusia affinis having male-biased

dispersal (Brown 1985; Chapman & Kramer 1991; Croft et al. 2003), while G. holbrooki

has female-biased dispersal (Congdon 1994). Males in some swordtails do maintain

territories (Morris et al. 1995), and therefore may be less likely to migrate than females. It

is interesting that the Claro II and San Pedro localities group together in the microsatellite

minimum evolution tree, which indicates a role of stream capture affecting the

distribution of X. birchmanni, since the Xiliatl II, Candelaria, and Atlapexco populations

are all closer by river distance. The lack of signal in the minimum evolution tree and the lack of private microsatellite alleles in several populations of X. birchmanni suggest recent gene flow among populations. Gene flow may be higher in X. birchmanni due to flooding at lower elevations and the relatively larger streams it inhabits, which generally are less subdivided by barriers to fish movement than smaller streams (Gutiérrez-

Rodríguez et al. 2007).

The river drainages in the AMOVA explained most of the genetic variation in X. malinche, although the pattern of isolation by distance in X. malinche was better explained by straight distances than by river distances. Since X. malinche is only found at higher elevations, this pattern suggests this species has been subject to stream capture

180 events (Rauchenberger et al. 1990). The headwaters of most drainages where X. malinche exists are geographically close to the headwaters of the Río Claro, while the headwaters of the Zontecomatlán are adjacent to headwaters of the Río Tuxpan system and less prone to stream capture with the other localities of X. malinche. This separation between the

Zontecomatlán drainage and the other drainages is supported both by the STRUCTURE results and the high mitochondrial FST values between the Zontecomatlán populations and other drainages. The mitochondrial haplotype M1 was found in the Moctezuma-

Hules, and M2 was found in the Hules-Calabozo, while all haplotypes found in the

Zontecomatlán drainage were private to this drainage. An alternative hypothesis by

Culumber et al. (2011) suggested that X. malinche has recently been pushed into higher elevations by climate change. This hypothesis seems unlikely given the degree of genetic isolation of X. malinche localities in the Zontecomatlán drainage and the low genetic distances between the other drainages. I would expect the pattern seen in X. birchmanni, with the Calabozo and Zontecomatlán populations more genetically similar to each other than other populations of X. malinche, if X. malinche had previously occupied lower elevations.

Ancestral Haplotypes and Biogeographic Origin

The statistical parsimony networks indicate that the ancestral haplotype for X. birchmanni is B1, which is found in the Hules and Calabozo drainages, while all three rooted trees infer B4, which is found in the Acamaluco drainage, as the ancestral

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haplotype. The result of the statistical parsimony network differs from Gutiérrez-

Rodríguez et al. (2008), which suggested that B2 was the ancestral haplotype. This

discrepancy is likely due to the methods used by statistical parsimony, which use haplotype frequencies and network position to identify ancestral haplotypes. The addition of the B7 haplotype to the parsimony network, as well as combining B2 and B3 into a single haplotype in the present study, could account for these differences. Rauchenberger et al. (1990) hypothesized that the ancestral form of X. birchmanni originated upstream in the Moctezuma drainage and spread via stream capture. The results of this study do not support this hypothesis, since the haplotype found in the Moctezuma drainage (B7), or a similar unsampled haplotype, was not inferred as ancestral in any of the analyses.

Gutiérrez-Rodríguez et al. (2008) hypothesized that X. birchmanni arose near the

Acamaluco drainage (described as San Pedro) and spread southeast, which is supported by the inference of an unsampled haplotype between B4 and the rest of the haplotypes as ancestral in rooted trees.

The statistical parsimony network infers C1 as ancestral for X. cortezi and X.

malinche, while the rooted phylogenetic trees infer an unsampled haplotype between C6

and C10 and the rest of the haplotypes as ancestral for X. cortezi, and an unsampled

haplotype between M3 and M4 and the rest of the haplotypes as ancestral for X.

malinche. The inferred ancestral haplotype for X. cortezi from the statistical parsimony network differs from Gutiérrez-Rodríguez et al. (2007), which inferred C4 (named H4 in the prior study) as ancestral when treating gaps as a 5th state. The difference is likely due

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to the increased sampling of X. cortezi and X. malinche in the current study, which

detected seven new haplotypes for these species. Some evidence suggests that genetic

diversity tends to be higher in ancestral populations (e.g., Schlötterer & Harr 2002;

Tinshkoff et al. 2009). The number of haplotypes present is greatest in the Moctezuma

drainage, which would lend further support to the hypothesis that the biogeographical

origin of X. cortezi is in the Moctezuma drainage. However, the greater number of populations present in the Moctezuma drainage is the more likely reason for the increased genetic diversity in this drainage. Alternatively, the rooted phylogenetic trees indicate an origin in the Tampaón drainage for X. cortezi, and in the Moctezuma drainage for X. malinche.

Deviations from Hardy Weinberg Equilibrium

Some populations in this study were not in Hardy-Weinberg equilibrium (HWE).

There are several reasons why this can occur, including linkage disequilibrium, the presence of null alleles, selection and subpopulation structure (e.g., due to spatial structure or assortative mating). Linkage disequilibrium was not significant between pairs of loci after Bonferonni corrections. In the present study, the large number of alleles found for some loci could produce a heterozygote deficiency. Deviations from Hardy

Weinberg equilibrium have been found in other studies of Xiphophorus (Tatarenkov et al.

2010; Culumber et al. 2011). In X. helleri, deviations from HWE were attributed to null alleles in two microsatellite loci (Tatarenkov et al. 2010). Null alleles are common in

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microsatellites since the flanking regions where primers anneal are also subject to higher rates of mutation (e.g., Angers & Bernatchez 1997; Grimaldi & Crouau-Roy 1997) and could produce heterozygote deficiency. In some populations, deviations in HWE were found across all loci but were not significant for any of the individual loci. Although microsatellites are considered a neutral marker, nonneutrality sometimes has been found with neutral markers (e.g., Ballard & Kreitman 1995, Selkoe & Toonen 2006). Finally, assortative mating could produce heterozygote deficiencies. This system is considered a model system for behavioral ecology (Ryan & Rosenthal 2001) and sexual selection could be producing assortative mating that is causing the observed deviations from HWE.

Microsatellite Admixture

The microsatellite data could potentially be used to investigate hybridization,

although that was not a focus of this study. I did not include samples from a hybrid zone

between X. birchmanni and X. cortezi in the Rio Xiliatl (Gutiérrez-Rodríguez et al.

unpublished data) or from the hybrid zone between X. birchmanni and X. malinche in the

Rio Calnalí (Rosenthal et al. 2003). However, Culumber et al (2011) suggest that hybrids

between X. malinche and X. birchmanni are common throughout their ranges.

Unfortunately, coordinates were not provided in the Culumber et al. (2011) study, and

therefore I cannot be certain if I sampled any of the same localities. Of the sites sampled,

additional hybrid zones were not indicated, as levels of admixture were low (alpha=0.03

for K=3, alpha below 1.0 indicates most individuals fall into a single group). However,

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the STRUCTURE analysis that grouped X. malinche with X. birchmanni together when K

was set to two groups suggests that hybrid individuals may have been present in the

analysis. Low levels of admixture were found in the Tamala population of X. malinche

with X. birchmanni, and X. birchmanni from the Claro II showed low levels of admixture with X. cortezi and X. malinche. In the Cebolla, Xiliatl II and Amajac, what appears as admixture is more likely due to missing data for loci that would not amplify for a few individuals (N=5). While K=2 through K=4 show the Chapulhuacanito population of X.

cortezi and a single individual from San Martín as being admixed with X. birchmanni, at

K=6 (not shown) only a single individual in Chapulhuacanito remained admixed with X.

birchmanni, suggesting most differences at lower K are a result of genetic differences

within X. cortezi rather than admixture. Although I did not collect X. birchmanni in the

San Pedro drainage, they have been reported there (Rauchenberger et al. 1990). Results

suggesting admixture in the Hules drainage are puzzling. The single X. birchmanni from

the Pezmatlan showed admixture with X. cortezi. While hybrid zones have been found on

the Calnalí (Culumber et al. 2011; Gutiérrez-Rodríguez et al. in prep), potential admixture with X. cortezi is surprising given no records of X. cortezi in the Hules beyond the Tecolutlo locality. Three individuals in the Culhuacán population of X. malinche also

appear to be admixed with X. cortezi. In addition, the Tecolutlo population of X. cortezi

appears admixed with X. malinche for K=3, but for K=4 and higher this locality is primarily admixed between the genetic groups that split X. cortezi. Given that K is specified in advance, STRUCTURE must assign loci even though genetic differences

could result in individuals not cleanly fitting into the assigned groups. In addition, given

185

the rapid evolution of microsatellites, some low level admixture could indicate homoplasy (Estoup et al. 2002). While there are several potential indications of

hybridization, the strong signal across species and overall low levels of admixture

suggest that there were relatively few individuals that may be hybrids in this study.

Species Status

The mitochondrial results of this study were similar to prior studies that also used

mitochondrial DNA (Meyer et al. 1994, 2006; Gutiérrez-Rodríguez et al. 2007, 2008) in

suggesting that X. malinche is more closely related to X. cortezi than X. birchmanni. The

current study found that haplotypes of X. cortezi and X. malinche formed a clade, and

differed by as little as 1 bp, while haplotypes of X. birchmanni were not included in the same clade as X. malinche and X. cortezi. Because X. malinche populations were placed within the X. cortezi clade, the species status of X. malinche had been questioned.

However, the microsatellite data indicates that X. cortezi and X. malinche might be distinct species with genetic substructure. The pattern of paraphyly for X. cortezi with X. malinche can be explained by the evolution of X. malinche from X. cortezi where gene sorting is not yet complete (Neigel & Avise 1986). This seems like the most likely hypothesis given the morphological similarities between the species (Rauchenberger et al. 1990) and their geographical distributions. However, paraphyly could also be the result of gene flow; although this was not reflected in the microsatellite results. Another possibility is that gene duplication events have led to gene transfer between the

186

mitochondrial and nuclear genome (Zhang & Hewitt 1996), which could lead to slower

mutation of the sequences. However, this seems unlikely based on the concordance of

these results with other studies including the mitochondrial DNA of these species (Meyer et al. 2006; Culumber et al. 2011).

Evidence for the relationships between the species of Northern swordtail fishes

has differed between mitochondrial DNA data sets and other molecular markers.

Rauchenberger et al. (1990) proposed a three species clade of X. pygmaeus, X. nigrensis

and X. multilineatus, which was later supported by RAPDs (Borowsky et al. 1995) and

allozymes (Morris et al. 2001). However, the placement of X. pygmaeus was inconclusive

in an analysis that used nuclear sequence data (Meyer et al. 2006). Mitochondrial DNA studies, including the present study, did not find support for placing X. pygmaeus with X. nigrensis and X. multilineatus (Meyer et al. 1994, 2006). In the Southern swordtails, mitochondrial DNA grouped X. clemenciae with platyfish, while nuclear genes placed X. clemenciae within the Southern swordtails (Meyer et al. 2006). Because of the differences in markers, X. clemenciae has been suggested as a species of hybrid origin

(Meyer et al. 2006).

Conclusions

There are several important findings of this study. First, I found genetic divergence across populations of each of the species sampled, consistent with a pattern of

187

isolation by distance. Second, while I found general agreement between patterns in

microsatellite and mitochondrial data within species, across species, the mitochondrial

DNA alone could not confirm that X. cortezi and X. malinche were separate species.

Third, based on the microsatellite data, it is clear that X. cortezi and X. malinche are

genetically distinct species.

Acknowledgements

I would like to thank Andre Fernandez, Angela Horner, Jeff Baker, and Kevin de

Quieroz for help collecting fish, Natalie Dubois for communicating her knowledge of

informative microsatellites, Andrew Morris for performing PCR reactions, Charles Nevill

for creating the nexus tree viewer, and Kevin de Quieroz for insightful comments on the

manuscript. I would also like to thank the Cannatella lab at the University of Texas for training in molecular protocols for D. M. Robinson, and the Mexican government for

collection permits. D. M. Robinson was supported by a fellowship from the Ohio Center

for Ecology and Evolutionary studies during this research. All protocols were approved by Ohio University IACUC (L01-01).

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Table 5.1. Populations and measures of the genetic diversity of the mitochondrial DNA control region. No. Species Drainage Locality N Haplotypes (n) h π 1 X. cortezi Tampaón Caldera 5 C6 (5) 0.0000 0.0000 2 Tambaque 16 C6 (13), C10 (3) 0.3250 0.0004 3 Oxitipa 12 C1 (3), C6 (9) 0.4091 0.0035 4 Tanute 8 C6 (8) 0.0000 0.0000 5 Moctezuma Tampamolon 6 C1 (4), C6 (2) 0.5333 0.0046 6 Huichihuayán 11 C1 (7), C11(4) 0.5091 0.0006 7 Cebolla 6 C1 (1), C2 (5) 0.3333 0.0004 8 Conchita 12 C1 (5), C2 (7) 0.5303 0.0007 9 Tancuilin 7 C1 (7) 0.0000 0.0000 10 Amacuzac 1 C3 (1) 0.0000 0.0000 14 San Pedro San Martín 10 C3 (10) 0.0000 0.0000 15 Chapulhuacanito 11 C4 (7), C5 (3) 0.4667 0.0006 16 Acamaluco Xiliatl II 7 C8 (5), C9 (2) 0.4762 0.0018 18 Hules Tecolutlo 7 C7 (7) 0.0000 0.0000 11 X. birchmanni Moctezuma Claro II 8 B7 (8) 0.0000 0.0000 17 Acamaluco Xiliatl II 5 B4 (5) 0.0000 0.0000 19 Hules Candelaria 14 B1 (14) 0.0000 0.0000 20 Huazalingo 16 B1 (11), B6 (5) 0.4583 0.0006 21 San Pedro 9 B1 (9) 0.0000 0.0000 22 Atlapexco 8 B1 (8) 0.0000 0.0000 23 Pezmatlan 2 B1 (2) 0.0000 0.0000 25 Contzintla 3 B1 (3) 0.0000 0.0000 26 Calabozo Garces 14 B2/B3 (14) 0.0000 0.0000

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Table 5.1 (continued) No. Species Drainage Locality N Haplotypes (n) h π 27 X. birchmanni Calabozo Tlalteatla 13 B2/B3 (13) 0.0000 0.0000 28 Amajac 4 B1 (2), B2/B3 (2) 0.6667 0.0008 30 Garces II 10 B2/B3 (10) 0.0000 0.0000 31 Zontecomatlán Sasaltitla 16 B2/B3 (10), B5 (6) 0.5000 0.0006 32 Chila 16 B2/B3 (16) 0.0000 0.0000 33 Otlatzintla 7 B2/B3 (7) 0.0000 0.0000 34 Zontecomatlán 11 B2/B3 (11) 0.0000 0.0000 12 X. malinche Moctezuma Tamala 10 M1 (4), M3 (3), M4 (3) 0.7333 0.0032 13 Claro 10 M1 (10) 0.0000 0.0000 24 Hules Culhuacán 10 M1 (2), M2 (8) 0.3556 0.0004 28 Calabozo Amajac 3 M2 (3) 0.0000 0.0000 29 Soyatla 7 M2 (7) 0.0000 0.0000 33 Zontecomatlán Otlatzintla 8 M5(5), M6 (3) 0.5357 0.0013 34 Zontecomatlán 2 M5 (2) 0.0000 0.0000 35 Tepeyiza 17 M5 (15), M6 (1), M7 (1) 0.2279 0.0004 N,n, number sequenced; h, mean gene diversity; π, nucleotide diversity

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Table 5.2. Hierarchical analysis of molecular variance (AMOVA). Sum of Variance Percentage of Species Source of variation d.f. squares components variation X. cortezi Among drainages 4 222.717 2.53858 Va 80.17* Among populations within drainages 9 20.769 0.23592 Vb 7.45* Within populations 104 40.784 0.39215 Vc 12.38* Total 117 284.27 3.16666 X. birchmanni Among drainages 4 72.14 0.65272 Va 82.56* Among populations within drainages 11 7.24 0.06480 Vb 8.20* Within populations 133 9.719 0.07307 Vc 9.24* Total 148 64.859 0.7096 X. malinche Among drainages 3 452.236 9.28174 Va 91.74* Among populations within drainages 4 14.658 0.47199 Vb 4.67* Within populations 59 21.427 0.36318 Vc 3.59* Total 66 488.322 * Significant at P<0.05

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Table 5.3. Estimates of pairwise FST for control region (below diagonal) and RST for microsatellites (above diagonal) among populations of X. cortezi. Tampaón Moctezuma San Pedro Hules

Caldera Tambaque Oxitipa Tanute Tampamolon Huichihuayán Cebolla Conchita Tancuilin Amacuzac San Martín Chapulhuacanito Tecolutlo Caldera - 0.120* 0.144* 0.010 0.262* 0.358* 0.714** 0.666** 0.707** 0.441 0.050 0.093 0.171* Tambaque 0.007 - 0.059* -0.008 0.578** 0.609** 0.831** 0.807** 0.832** 0.761 0.329** 0.401** 0.472** Oxitipa 0.063 0.250* - -0.040 0.534** 0.552** 0.765** 0.748** 0.765** 0.659 0.336* 0.401** 0.453** Tanute 0 0.061 0.127 - 0.349* 0.357** 0.598** 0.585** 0.602** 0.406 0.211* 0.244* 0.293** Tampamolon 0.568 0.752* 0.208 0.650* - -0.040 0.211* 0.153* 0.246* -0.154 0.012 0.053 0.012 Huichihuayán 0.978** 0.976** 0.718** 0.982** 0.354* - 0.406** 0.336** 0.405** 0.125 -0.053 0.045 0.011 Cebolla 0.990* 0.981** 0.694** 0.992** 0.344* 0.648** - -0.010 0.073 -0.154 0.316** 0.431** 0.317** Conchita 0.978** 0.976** 0.738** 0.981** 0.414* 0.474* 0.008 - 0.101* -0.213 0.283** 0.378** 0.269** Tancuilin 0.971* 0.973** 0.678* 0.978** 0.271 0.176 0.536* 0.358* - -0.168 0.333** 0.454** 0.342** Amacuzac 1.000 0.973 0.363 1.000 -0.662 0.646 0.833 0.688 0.432 - -0.012 0.118 0.024 San Martín 1.000** 0.983** 0.658* 1.000** 0.278* 0.815** 0.939** 0.831** 0.763** 0 - -0.026 -0.029 Chapulhuacanito 0.982** 0.979** 0.741** 0.986** 0.498** 0.796** 0.861** 0.813** 0.764** 0.685 0.843** - -0.007 Tecolutlo 1.000* 0.995** 0.898** 1.000** 0.861* 0.983** 0.992** 0.982** 0.981* 1.000 1.000** 0.991** - Xiliatl 0.977* 0.982** 0.860** 0.982** 0.832** 0.966** 0.965* 0.966** 0.960** 0.948 0.979** 0.979** 0.394* *P<0.05; **P<0.00050 (significance after Bonferonni corrections); no significance calculated for Amacuzac due to sample size

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Table 5.4. Estimates of pairwise FST for control region (below diagonal) and RST for microsatellites (above diagonal) among populations of X. birchmanni. Moctezuma Acamaluco Hules Calabozo Zontecomatlán

Claro II Xiliatl II Candelaria Huazalingo San Pedro Atlapexco Pezmatlan Contzintla Garces Tlatleatla Amajac II Garces Sasaltitla Chila Otlazintla Zontecomatlán Claro II - 0.185* 0.079* 0.119* 0.082* 0.094* 0.010 -0.003 0.279** 0.381** 0.361* 0.113 0.194* 0.297** 0.339** 0.276** Xiliatl II 1.000* - 0.314** 0.132* 0.169* 0.059 0.663 0.228* 0.073 0.219* 0.386* 0.044 0.162* 0.193* 0.206 0.154 Candelaria 1.000** 1.000** - 0.193** 0.041 0.066 0.199 0.011 0.253** 0.358** 0.461** 0.175* 0.145* 0.289** 0.358** 0.269** Huazalingo 0.869** 0.850** 0.249* - 0.039 0.012 0.438 0.021 0.168* 0.325** 0.431** 0.015 0.110* 0.201** 0.291** 0.161* San Pedro 1.000** 1.000* 0.000 0.193 - -0.022 0.253 -0.070 0.205** 0.319** 0.432** 0.075 0.120* 0.223** 0.301** 0.191** Atlapexco 1.000** 1.000* 0.000 0.179 0.000 - 0.247 -0.031 0.093* 0.198* 0.297* -0.020 0.058 0.106* 0.169* 0.077* Pezmatlan 1.000* 1.000* 0.000 -0.057 0.000 0.000 - 0.090 0.352 0.442 0.560 0.370 0.287 0.551 0.417 0.525 Contzintla 1.000* 1.000* 0.000 0.042 0.000 0.000 0.000 - 0.214* 0.334** 0.448* 0.082 0.121 0.290* 0.306* 0.251* Garces 1.000** 1.000** 1.000** 0.815** 1.000** 1.000** 1.000* 1.000* - 0.028 -0.019 0.012 0.065 -0.012 0.012 -0.006 Tlatleatla 1.000** 1.000** 1.000** 0.809** 1.000** 1.000** 1.000* 1.000* 0.000 - -0.004 0.165* 0.166* 0.097* -0.030 0.108* Amajac 0.917* 0.884 0.648* 0.354* 0.544 0.515 0.111 0.250 0.648* 0.631* - 0.214* 0.190* 0.157* 0.017 0.170* Garces II 1.000* 1.000* 1.000* 0.716* 1.000* 1.000* 1.000* 1.000* 0.000 0.000 0.250 - 0.019 0.015 0.136* -0.005 Sasaltitla 0.901** 0.887** 0.807** 0.716** 0.773** 0.765** 0.683* 0.705* 0.314* 0.304* 0.369* 0.108 - 0.028 0.126* 0.025 Chila 1.000** 1.000** 1.000** 0.825** 1.000** 1.000** 1.000* 1.000* 0.000 0.000 0.677* 0.000 0.333* - 0.075 -0.028 Otlazintla 1.000** 1.000* 1.000** 0.765** 1.000** 1.000** 1.000* 1.000* 0.000 0.000 0.481 0.000 0.225 0.000 - 0.082* Zontecomatlán 1.000** 1.000** 1.000** 0.797** 1.000** 1.000** 1.000* 1.000* 0.000 0.000 0.593 0.000 0.282 0.000 0.000 -

*P<0.05; **P<0.00039 (significance after Bonferonni corrections); no signficance calculated for Pezmatlan RST due to sample size

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Table 5.5. Estimates of pairwise FST for control region (below diagonal) and RST for microsatellites (above diagonal) among populations of X. malinche. Moctezuma Hules Calabozo Zontecomatlán Tamala Claro CulhuacánAmajac Soyatla Otlatzintla Zontecomatlán Tepeyiza Tamala - 0.094* 0.062 0.128 0.038 0.236* 0.059 0.342** Claro 0.531* - 0.089* 0.263* 0.094 0.273* 0.172 0.526** Culhuacán 0.532* 0 - 0.115 0.017 0.235* 0.067 0.126* Amajac 0.35 0 0 - 0.020 0.348* 0.305 0.729** Soyatla 0.476* 0 0 0 - 0.282** 0.182 0.474** Otlatzintla 0.923** 1.000** 1.000** 1.000* 1.000* - -0.085 0.632** Zontecomatlán 0.950* 1.000* 1.000** 1.000* 1.000** 0 - 0.616** Tepeyiza 0.950** 1.000**1.000** 1.000**1.000** 0 0 - *P<0.05; **P<0.00140 (significant after Bonferonni corrections

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Table 5.6. Estimates of demographic and neutrality tests within each species and drainage. Species Drainage N SSD P D P FS P X. cortezi Tampaón 41 0.022 0.191 -1.150 0.119 2.227 0.875 Moctezuma 43 0.012 0.140 -1.397 0.065 -0.194 0.475 San Pedro 20 0.013 0.223 0.961 0.841 0.709 0.625 Acamaluco 7 0.244 0.079 0.687 0.802 2.508 0.874 Hules 7 0.000 0.000* 0.000 1.000 0.000 - X. birchmanni Moctezuma 8 0.000 0.000* 0.000 1.000 0.000 - Acamaluco 5 0.000 0.000* 0.000 1.000 0.000 - Hules 53 0.326 0.115 -0.094 0.332 0.374 0.338 Calabozo 41 <0.001 0.265 -0.841 0.193 -0.710 0.115 Zontecomatlán 50 0.314 0.117 -0.047 0.352 0.430 0.334 X. malinche Moctezuma 20 0.340 <0.001* 1.362 0.914 3.282 0.939 Hules 10 0.004 0.454 0.000 1.000 0.417 0.373 Calabozo 10 0.000 0.000* 0.000 1.000 0.000 - Zontecomatlán 32 0.120 0.138 0.000 1.000 0.352 0.525 SSD, sum of squared deviation for demographic expansion; D, Tajima's D; FS, Fu's FS test; P values for FS=0 were not calculated

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Table 5.7. Population genetic variability of microsatellites. Private Species Drainage Location N A AR Alleles HO HE X. cortezi Tampaón Caldera 7 3.500 1.469 4 0.330 0.553 Tambaque 25 7.125 1.485 6 0.424 0.485 Oxitipa 25 8.875 1.519 8 0.382 0.519 Tanute 21 6.625 1.502 6 0.404 0.502 Moctezuma Tampamolon 8 5.125 1.687 5 0.674 0.687 Huichihuayán 20 8.125 1.697 7 0.559 0.696 Cebolla 14 3.000 1.376 2 0.345 0.430 Conchita 15 3.750 1.300 0 0.374 0.400 Tancuilin 12 4.875 1.537 3 0.470 0.537 Amacuzac 1 1.375 1.375 1 1.000 1.000 San Pedro San Martín 14 5.625 1.544 5 0.420 0.544 Chapulhuacanito 13 7.625 1.701 7 0.606 0.701 Hules Tecolutlo 19 5.750 1.562 7 0.445 0.563 X. birchmanni Moctezuma Claro II 12 6.250 1.630 3 0.521 0.630 Acamaluco Xiliatl II 4 1.625 1.214 0 0.100 0.428 Hules Candelaria 14 6.250 1.560 1 0.563 0.560 Huazalingo 10 6.250 1.545 1 0.557 0.623 San Pedro 15 7.625 1.523 2 0.458 0.522 Atlapexco 8 6.125 1.618 0 0.578 0.618 Pezmatlan 1 1.500 1.500 4 1.000 1.000 Contzintla 4 3.500 1.616 0 0.643 0.704 Calabozo Garces 20 9.125 1.567 4 0.536 0.648 Tlalteatla 12 5.625 1.515 0 0.556 0.687 Amajac 3 2.875 1.533 0 0.393 0.609 Garces II 6 4.125 1.554 0 0.486 0.633 Zontecomatlán Sasaltitla 16 6.625 1.658 3 0.594 0.658 Chila 16 6.500 1.258 1 0.617 0.612 Otlatzintla 7 4.625 1.627 1 0.455 0.634 Zontecomatlán 16 7.375 1.638 0 0.578 0.600 X. malinche Moctezuma Tamala 10 5.000 1.571 8 0.600 0.653 Claro 17 4.375 1.396 3 0.497 0.452 Hules Culhuacán 23 2.875 1.203 10 0.096 0.324 Calabozo Amajac 3 1.625 1.242 1 0.583 0.483 Soyatla 9 1.875 1.225 1 0.410 0.449 Zontecomatlán Otlatzintla 9 3.500 1.563 4 0.533 0.541 Zontecomatlán 2 2.250 1.750 0 0.571 0.643 Tepeyiza 22 2.500 1.135 1 0.239 0.271 A, mean alleles/locus; AR, allelic richness for N=1; HO, mean observed heterozygosity; HE, mean expected heterozygosity

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Table 5.8. Inbreeding coefficients (FIS) of microsatellite loci. Species Drainage Location N mATG61 D15 D21 D29 D6 MSD23 T30 T38 all X. cortezi Tampaón Caldera 7 0.80 0.44 0.31 NA 1.00 0.25 0.43 -0.09 0.42* Tambaque 25 0.73* -0.02 0.55 -0.05 0.03 0.13 0.38 0.28 0.14 Oxitipa 25 0 0.01 0.08 -0.02 -0.10 0.11 0.63 0 0.27* Tanute 21 0 0.52 0.50 -0.04 0.17 0.07 0.50 -0.06 0.20* Moctezuma Tampamolon 8 0.65 -0.06 -0.03 -0.21 -0.78 -0.07 0.79 0.02 0.02 Huichihuayán 20 0.74* 0.10 0.20 -0.24 0.31 0.15 0.44 0.12 0.20* Cebolla 14 1.00 -0.27 0.29 NA 1.00 0.01 1.00 0.07 0.20 Conchita 15 0.32 -0.08 -0.07 NA -0.03 0.36 NA -0.12 0.07 Tancuilin 12 -0.17 0.65 0.29 0 -0.17 0.02 0.85* -0.23 0.13 Amacuzac 1 NA NA NA NA NA NA NA NA NA San Pedro San Martín 14 0.22 0.23 0.23 1.00 0.07 0.04 0.14 -0.03 0.25* Chapulhuacanito 13 0.51 0.18 0.62 0.46 0.24 -0.06 0.55 -0.11 0.14 Hules Tecolutlo 19 0.069 1.00 -0.102 0.325 -0.029 0.079 0.535 0.033 0.21* X. birchmanni Moctezuma Claro II 12 0.616 0.5 0.034 0.476 0 0.04 -0.111 0.06 0.18 Acamaluco Xiliatl II 4 NA 1.00 NA 1.00 1.00 0.41 NA NA 0.79 Hules Candelaria 14 -0.19 0.16 0.08 0 0 -0.06 0.07 -0.07 0 Huazalingo 10 -0.13 -0.06 0.12 NA -0.13 0.05 0.13 0.33 0.11 San Pedro 15 1.00 0.66 0.16 -0.04 0.66 0.07 0 -0.05 0.13 Atlapexco 8 -0.17 0.63 0.06 -0.11 -0.08 0.08 -0.08 0.18 0.07 Pezmatlan 1 NA NA NA NA NA NA NA NA NA Contzintla 4 -0.50 NA 0.46 0 0.33 -0.09 0.37 -0.14 0.10 Calabozo Garces 20 -0.05 0.49 0.17 0.25 NA 0.07 0.06 0.19 0.18* Tlalteatla 12 NA 1.00 0.29 0 NA 0 -0.05 0.11 0.20

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Table 5.8 (continued) Species Drainage Location N mATG61 D15 D21 D29 D6 MSD23 T30 T38 all X. birchmanni Calabozo Amajac 3 1.00 0.50 0.57 NA 1.00 -0.09 0.50 -0.20 0.39 Garces II 6 0.64 NA 0.12 -0.14 1.00 0.074 0 0.25 0.25 Zontecomatlán Sasaltitla 16 -0.05 0.53 0.16 -0.30 0.05 -0.06 0.60* -0.17 0.10 Chila 16 NA -1.00* -1.00* NA NA -1.00* NA -1.00* -1.00* Otlatzintla 7 0.07 0.80 0.25 0.28 1.00 0.12 0.12 0.25 0.29* Zontecomatlán 16 0.15 0.33 0.02 -0.02 0.66 -0.03 0.14 0.12 0.12 X. malinche Moctezuma Tamala 10 0.04 NA 0.20 -0.08 0.438 0.053 0.122 -0.118 0.085 Claro 17 -0.107 NA 0 -0.067 -0.524 0.079 0 -0.088 -0.101 Hules Culhuacán 23 1* NA 0.743* NA NA 0.435* 1* 0.656 0.709* Calabozo Amajac 3 NA NA 0 -0.333 NA -0.5 NA 0 -0.273 Soyatla 9 NA 0.571 NA -0.455 NA 0.138 NA -0.032 0.108 Zontecomatlán Otlatzintla 9 0.19 NA -0.067 -0.032 NA -0.032 NA -0.016 0.015 Zontecomatlán 2 0 0 NA 0 1 -0.333 0 0 0.158 Tepeyiza 22 0 NA NA NA NA 0.049 1 -0.024 0.121 *significant after Bonferonni corrections P<0.0018

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Table 5.9. Wright’s F-statistics for microsatellite loci within each species. X. birchmanni X. cortezi X. malinche

Locus FIT FST FIS FIT FST FIS FIT FST FIS mATG61 0.385* 0.252* 0.175 0.718* 0.544* 0.381* 0.415* 0.345* 0.155 D15 0.505* 0.236* 0.365* 0.540* 0.446* 0.164 1.118 0.750* 0.586 D21 0.256* 0.205* 0.067 0.590* 0.440* 0.269* 0.853* 0.700* 0.598 D29 0.514* 0.455* 0.109 0.589* 0.574* 0.026 0.803* 0.842* -0.248* D6 0.478* 0.210* 0.347* 0.300* 0.218* 0.103 0.279 0.348* -0.237 MSD23 0.046 0.075 -0.029 0.158* 0.071* 0.093* 0.273* 0.182* 0.104 T30 0.285* 0.206* 0.099 0.670* 0.316* 0.517* 0.518 0.127 0.489 T38 0.123* 0.101* 0.027 0.234* 0.214* 0.027 0.542* 0.554* -0.04

All loci 0.285* 0.206* 0.099 0.458* 0.335* 0.182* 0.536* 0.467* 0.126* *P<0.05

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22° A

2 1 3

4 B 5 6

7 14 8 C 9 10 D 11 E 16 15 18 17 19 26 21° 20 12 21 22 G 31 23 F 13 27 24 25 30 32 33 28 34

29 35

Figure 5.1. Map showing collection localities for X. birchmanni (squares), X. cortezi (circles), and X. malinche (triangles). Numbers correspond to localities in Table 5.1. Letters correspond to drainages: A Tampaón, B Moctezuma, C San Pedro, D Acamaluco, E Hules, F Calabozo, G Zontecomatlán.

206

a.a

207

c b

Figure 5.2. Genetic relationships for X. birchmanni (squares), X. cortezi (circles), and X. malinche (triangles): a) Maximum likelihood bootstrap tree and Bayesian posterior probabilities for haplotypes of the mitochondrial DNA control region haplotypes. Branch lengths are proportional to the number of substitutions per site. Numbers below branches indicate bootstrap support (left) and posterior probability (right) when either value was greater than 50%. A single disagreement between the maximum likelihood and Bayesian tree is denoted by *, where the consensus tree from the maximum likelihood analysis did not support a clade. Names of other species and drainage names for X. birchmanni, X. cortezi, and X. malinche haplotypes are indicated. Populations where each haplotype is found are in Table 5.1. Tree is rooted with the Southern swordtail X. helleri. b) Unrooted minimum evolution bootstrap tree for microsatellites based on Cavalli-Svorza and Edwards (1967) distances for X. birchmanni and c) X. cortezi and X. malinche. Numbers indicate bootstrap support when greater than 50%.

208

209

Figure 5.3. Parsimony analyses based on sequences of the mitochondrial DNA control region: a) Parsimony networks for X. birchmanni (squares), X. cortezi (circles), and X. malinche (triangles). Gaps were treated as a 5th state. Each line corresponds to one mutational change. The size of the ellipse for each haplotype corresponds to the haplotype’s frequency. Squares represent ancestral haplotypes inferred by TC.

210

Unobserved haplotypes are represented by a small circle. b) Maximum parsimony tree with gaps treated as informative characters. Tree is rooted with X. helleri. Numbers indicate bootstrap support when greater than 50%.

211

a 1 Tampaon 0.8 Moctezuma San Pedro 0.6 Acamaluco Hules 0.4 Frequency

0.2

0 0123456789 Number of differences b

1 Moctezuma Acamaluco 0.8 Hules 0.6 Calabozo 0.4 Zontecomatlan Frequency 0.2 0 01 Number of differences c 1 Moctezuma 0.8 Hules Calabozo 0.6 Zontecomatlan 0.4 Frequency 0.2 0 012345

Number of differences

Figure 5.4. Observed mismatch distribution (histogram) under population expansion model for drainages of a) Xiphophorus cortezi, b) X. birchmanni and c) X. malinche mtDNA control region sequences.

212

a b

213

c d

Figure 5.5. Isolation by distance for plots using Nei & Li (1979) genetic distance for mtDNA and Cavalli Svorza chord distance for microsatellite loci for all possible pairs of populations: mtDNA compared to a) river distance and b) straight-line distances, and microsatellites compared to c) river and d) straight-line distances. Lines show the linear fit to points. Values for r2 were calculated using Mantel tests.

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Xiphophorus cortezi Xiphophorus birchmanni Xiphophorus malinche

1.0 0.8 0.6 K=2 0.4 0.2 0.0

1.0 0.8 0.6 0.4 K=3 0.2 0.0

1.0 0.8 0.6 0.4 K=4 0.2 0.0 s o a ro a le z zo n n m d es o u o n a es o la o u e l um c H b la m l b t pa z P u z lu la t u u la a te n H te a a a ez H a m am c a c C m t C o T o S o am o c ec M M c ec o t A t M on on Z Z

Figure 5.6. Genetic groups across species for two, three and four genetic groups (K) based on STRUCTURE analysis of microsatellite loci. Species are listed above the graph and are separated by thick solid lines. Drainages are listed below the graph and are separated by dashed lines. Populations within each species are listed in the same order as for Figures 6-8, and are separated by narrow solid lines.

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n la a o at m c u lu ozo om z a s b c te m le la te c ca u a n o A H C Zo 1.0 M 0.8 0.6 K=2 0.4 0.2 0.0 1.0 0.8 0.6 K=3 0.4 0.2 0.0 1.0 0.8 0.6 K=4 0.4 0.2 0.0 s c a I I o a a I a l a n I I a o o n l e l a I l i l i r c t t j t t a l r g a c i h l o t d x l n a a s t t r a n t i r l n a l i e e e e C i a a i l a z a t m a z l l e p t l c s i a P r a m d a m n G a A l C X z l l a a t n n t z o a o T S c a a e G O u A C e C S P t H n o Z Figure 5.7. Genetic groups in X. birchmanni for two, three and four genetic groups (K) based on STRUCTURE analysis of microsatellite loci. Drainages are listed above the graph and are separated by dashed lines. Populations are listed below the graph and are separated by solid lines.

216

a m ro on zu ed a e P s p ct e m o an ul a M S H 1.0 T 0.8 0.6 K=2 0.4 0.2 0.0 1. 0 0. 8 0. 6 K=3 0. 4 0. 2 0. 0

1.0 0.8 0.6 K=4 0.4 0.2 0.0 e a e n a t n a a in n o o p l t l i t l r u i u o a l i i t i t t l r e q i n y o h u n a o a c a a lu ld x a b c b m u e n M c o n a O T h a c m a i C o a C n u e p h C a T a h c l T T m i S a u u T p H a h C

Figure 5.8. Genetic groups in X. cortezi for two, three and four genetic groups (K) based on STRUCTURE analysis of microsatellite loci. Drainages are listed above the graph and are separated by dashed lines. Populations are listed below the graph and are separated by solid lines.

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an a tl m zo a u o om ez s b c t le la te oc u a n M H C o 1.0 Z 0.8 0.6 K=2 0.4 0.2 0.0 1.0 0.8 0.6 K=3 0.4 0.2 0.0 1.0 0.8 K=4 0.6 0.4 0.2 0.0 n a o a a l r n c la l a t t l z a a a ja t i l a in a y c a m C y z e m a ua m o a p l o T S t e lh A c O e T u t C n o Z Figure 5.9. Genetic groups in X. malinche for two, three and four genetic groups (K) based on STRUCTURE analysis of microsatellite loci. Drainages are listed above the graph and are separated by dashed lines. Populations are listed below the graph and are separated by solid lines.

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