Testing for Convergent Evolution in Semi-Aquatic Anolis Lizards

Testing for Convergent Evolution in Semi-aquatic Anolis Lizards

Christopher Kevin Boccia

A thesis submitted in conformity with the requirements for the degree of Master of Science Department of Ecology and Evolutionary Biology University of Toronto

Testing for Convergent Evolution in Semi-aquatic Anolis Lizards

Christopher Kevin Boccia

Master of Science

Department of Ecology and Evolutionary Biology University of Toronto

2018 Abstract

Twelve species from six different clades of Anolis lizard exhibit a semi-aquatic lifestyle. These unusual species are found only along neotropical streams, and are known to swim, capture aquatic prey, and dive to escape predators. Based on ecomorphology theory, and anoles’ famed predisposition for convergence, we would predict that these anole lineages should have undergone convergent evolution. However, previous morphometric research suggested that semi- aquatic anoles are not convergent. This thesis reinvestigates whether semi-aquatic anoles have convergently evolved using novel morphometric and experimental approaches. I assessed the morphology, swimming speed, and diving performance of semi-aquatic and non-aquatic anole species from throughout the neotropics. My results suggest that semi-aquatic anoles have converged upon similar morphologies, superior swimming performance, and a previously undiscovered potential adaptation for diving: underwater rebreathing. Semi-aquatic anoles show evidence of repeated multidimensional convergence, and, somewhat uniquely for Anolis, provide strong evidence for convergence between mainland and island forms.

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Acknowledgments

I first became interested in semi-aquatic Anolis lizards while travelling through Panama and Costa Rica in the summer of 2015. No formal field guide exists for the reptiles and amphibians of Panama, so I constructed my own using checklists and online databases of herpetological images. Among the many anole species I researched, the ripple-patterned ‘semi-aquatics’ were particularly fascinating. I managed to find two of these species during my trip. The first sighting was spectacularly bizarre—while hiking through the mountains in Parque Nacional Omar Torrijos, I spotted an A. lionotus (highly stream associated) sitting in the middle of a heavily rutted dirt track, with no waterway in sight. Due in part to this curious observation, semi-aquatic anoles were first in line when I was deciding on an Anolis lizard-focused thesis.

A project of this scope and complexity would not have been possible without the assistance of a small army of friends and lab-mates: Claire Manglicmot, Shree Senthivasan, Michael Foisy, James Boyko, Ken Toyama, Viviana Astudillo-Clavijo, Patrick Moldowan, Hollis Dahn, Sean Anderson, Meredith Swartwout, Alan Ward, Phil Honlë, Bryan Ospina, Elodie Morneau, Margarita Cantero Guerrero, field assistants: James Boccia, Isabela Borges, Camilo Estupiñan, Sebastian Ovalle, lab volunteers: Erica Fellin, Cole Brookson, Sophia Samuelsson, Perlina Lim, collaborators: Rosario Castañeda, Andrés García Aguayo, Ramón Martínez, museum loan coordinators: Amy Lathrop, Neftali Camacho, José Rosado, Jonathan Losos, and research station and permit staff: Organization for Tropical Studies, Bernal Matarrita Carranza, Minor Porras, Rebecca Cole.

Special thanks to Luke Mahler for his endless hours of assistance with all aspects of the project, to Rosario Castañeda, Camilo Estupiñan, Sebastian Ovalle, Margarita Cantero Guerrero, and Ramón Martínez for helping me visit amazing sites in Colombia and Mexico, and to Shree Senthivasan, James Boccia, Ken Toyama, and Isabela Borges, who endured close encounters with lightning strikes, rat and ant invasions, and bites from all manner of tropical insects to help me complete all of my fieldwork.

My research was supported by a National Geographic Young Explorer Grant, a Sigma Xi Grant- in-Aid of Research, and a Canada Graduate Scholarship-Master’s Program from the Natural Sciences and Engineering Research Council of Canada

I obtained research permits to work with Costa Rican species from MINAE, the Costa Rican environmental agency (permit #: SINAC-SE-102-2017).

All experimental methods were approved by the University of Toronto Local Animal Care Committee (LACC; protocol #: 20011469).

Table of Contents

Acknowledgments...... iii

Table of Contents ...... v

List of Tables ...... viii

List of Figures ...... ix

List of Appendices ...... xii

1 Morphological convergence in semi-aquatic anoles ...... 1

1.1 Introduction ...... 1

1.1.1 Convergent evolution ...... 1

1.1.2 Convergence in Anolis lizards ...... 1

1.1.3 Island/mainland disparity in convergence in anoles ...... 2

1.1.4 The expectation of convergence among semi-aquatic anoles ...... 3

1.1.5 Hypotheses and predictions ...... 6

1.2 Methods...... 6

1.2.1 Preamble ...... 6

1.2.2 Linear morphometric data collection ...... 7

1.2.3 Phylogenetic principal component analysis of linear morphometric data ...... 10

1.2.4 Analysis of putative convergence in semi-aquatic anoles using linear discriminant analysis, nearest neighbour distances, and simulation ...... 10

1.2.5 Testing for convergence using the “convevol” R package ...... 11

1.3 Linear morphometry results ...... 12

1.3.1 Male phylogenetic morphospace ...... 12

1.3.2 Female phylogenetic morphospace ...... 19

1.3.3 “convevol” metric results ...... 26

1.4 Discussion ...... 28

1.4.1 Evidence for convergence in semi-aquatic anoles ...... 28

1.4.2 Conclusions and future directions ...... 31

2 Aquatic performance of semi-aquatic anoles ...... 33

2.1 Introduction ...... 33

2.1.1 Background ...... 33

2.1.2 Linking ecology, morphology, and performance in anoles ...... 34

2.1.3 Performance demands of semi-aquatic habitats ...... 35

2.1.4 Hypotheses and predictions ...... 35

2.2 Methods...... 36

2.2.1 Field work and lizard capture ...... 36

2.2.2 Swimming speed experiments ...... 38

2.2.3 Quantification of swimming speed ...... 42

2.2.4 Analysis of aquatic and non-aquatic anole swimming speeds ...... 43

2.2.5 Observation and analysis of voluntary diving ...... 45

2.3 Results ...... 45

2.3.1 Swimming speed analysis ...... 45

2.3.2 Voluntary diving results ...... 49

2.4 Discussion ...... 53

2.4.1 Convergence in swimming and diving performance in aquatic anoles ...... 53

2.4.2 Conclusions and future directions ...... 54

3 “Rebreathing” in semi-aquatic anoles: a novel adaptation for diving? ...... 56

3.1 Introduction ...... 56

3.1.1 Background ...... 56

3.1.2 Do aquatic anoles possess respiratory adaptations for diving? ...... 56

3.1.3 Hypotheses and predictions ...... 57

3.2 Methods...... 70

3.2.1 Testing for rebreathing during voluntary dives by anoles ...... 70

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3.2.2 Lizard submersion experiments ...... 59

3.2.3 Analysis of rebreathing videos...... 60

3.3 Results ...... 61

3.3.1 Rebreathing—general trends ...... 61

3.3.2 Description of rebreathing behaviours observed in aquatic and non-aquatic anoles ...... 67

3.3.3 Oxygen probe results ...... 68

3.4 Discussion ...... 71

3.4.1 Are rebreathing bubbles involved in respiration? ...... 71

3.4.2 Is rebreathing adaptive for diving? ...... 71

3.4.3 What physiological benefits might anoles gain from rebreathing? ...... 73

3.4.4 Conclusions and future directions ...... 74

References ...... 76

Appendices ...... 85

4.1 Descriptions of measurements taken on museum specimens ...... 85

4.2 Reasons for unusual convergence results returned by the convnum function ...... 86

4.3 Swimming Speed—nonsignificant putative covariates ...... 87

4.4 Results of Tukey honest significant differences test on anole swimming speed data ...... 88

4.5 Swimming and rebreathing videos...... 90

4.5.1 Swimming speed demonstration ...... 90

4.5.2 Rebreathing demonstration ...... 90

4.6 Male and female species mean morphology data sets ...... 90

4.6.1 Male data set ...... 90

4.6.2 Female data set ...... 90

4.7 Museum specimens consulted for this project ...... 90

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List of Tables

Table 1: Variance explained by each PC axis for the male PCA...... 13

Table 2: Loadings for the first five principal components of a phylogenetic PCA conducted on the male anole morphology data set...... 17

Table 3: Variance explained by each PC axis for the female PCA...... 20

Table 4: Loadings for the first five principal components of a phylogenetic PCA conducted on the female anole morphology data set...... 24

Table 5: P-values and results of “convevol” analysis (Stayton 2015)...... 28

Table 6: Summary of anoles caught for this project...... 41

Table 7: ANOVA results for ln-transformed mean swimming speeds ...... 47

Table 8: Results of a model comparison test conducted on generalized least squares models conducted with a phylogenetic correlation matrix...... 48

Table 9: Results of a PGLS regression of ln(swimming speed) on ln(SVL) ...... 49

Table 10: ANOVA results for maximum dive durations in aquatic and non-aquatic anoles...... 52

Table 11: Diving summary statistics...... 52

Table 12: Rebreathing summary statistics ...... 62

Table 13: Transition rate matrix and model fitting results for Pagel’s method of detecting correlated evolution between binary traits—analysis run using habitat and sustained rebreathing as the binary traits...... 64

Table 14: Transition rate matrix and model fitting results for Pagel’s method of detecting correlated evolution between binary traits—analysis run using habitat and incidental rebreathing as the binary traits...... 67

List of Figures

Figure 1: Ranges of semi-aquatic anole species from Mexico, Central and South America, and the Caribbean...... 4

Figure 2: Phylogenetic relationships of semi-aquatic anoles...... 5

Figure 3: Morphological coverage tree...... 9

Figure 4: Scree plot of the first ten principal components of the male linear morphology data set...... 13

Figure 5: Male anole morphospace, PCs 1 and 2...... 14

Figure 6: Male anole morphospace, PCs 1 and 3...... 15

Figure 7: Male anole morphospace, PCs 1, 2 and 3. Blue spheres are semi-aquatic species, brown sphere are non-aquatics...... 15

Figure 8: Male anole morphospace, PCs 3, 4 and 5...... 16

Figure 9: Phylogeny that includes all male anoles measured for this project ...... 16

Figure 10: Histogram of expected nearest neighbour distances among aquatics...... 18

Figure 11: Histogram of expected mean Euclidean inter-aquatic distances...... 18

Figure 12: Histogram of expected LDA identification scores...... 19

Figure 13: Scree plot of the first ten principal components of the female linear morphology data set...... 20

Figure 14: Female phylogeny used for phylogenetic principal component analysis ...... 21

Figure 15: Female anole morphospace, PCs 1 and 2...... 21

Figure 16: Female anole morphospace, PCs 1 and 3...... 22

Figure 17: Female anole morphospace, PCs 1, 2, and 3...... 22

Figure 18: Female anole morphospace, PCs 3, 4, and 5...... 23

Figure 19: Histogram of expected nearest neighbour distances among female aquatics...... 24

Figure 20: Histogram of expected mean Euclidean inter-aquatic distances...... 25

Figure 21: Histogram of expected LDA identification scores...... 25

Figure 22: Histogram of convergence events detected by convnum in simulated data sets based on male PC data ...... 26

Figure 23: Histogram of convergence events detected by convnum in simulated data sets based on female PC data ...... 27

Figure 24: Histograms of 99 simulated values for each of Stayton’s C metrics for the male anole morphology data set ...... 27

Figure 25: Histograms of 99 simulated values for each of Stayton’s C metrics for the female anole morphology data set ...... 28

Figure 26: Modified phylogeny from Gamble et al. (2014) used for phylogenetic comparative analyses...... 44

Figure 27: Plot of mean swimming speed observed for all anole species tested during this study...... 46

Figure 28: Plot of ln-transformed mean swimming speed observed for all anole species tested during this study...... 46

Figure 29: Mean swimming speed by study site...... 47

Figure 30: Results of a PGLS regression on species size vs. swimming speed...... 49

Figure 31: Mean voluntary dive durations...... 50

Figure 32: Diving frequency of anole species that exhibited voluntary dives...... 51

Figure 33: Max observed voluntary dive durations...... 51

Figure 34: Proportion of individuals tested which re-inspired at least one air bubble during a submersion trial...... 63

Figure 35: Proportion of individuals tested which exhibited sustained rebreathing...... 63

Figure 36: Distribution of sustained rebreathing and aquatic habitat on a phylogeny derived from Gamble et al. (2014)...... 64

Figure 37: Distribution of incidental rebreathing and aquatic habitat on a phylogeny derived from Gamble et al. (2014)...... 66

Figure 38: Plots of partial pressures of oxygen measured in rebreathing bubbles exhaled and reinhaled by a diving aquatic anole...... 70

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List of Appendices

Appendices ...... 85

4.1 Descriptions of measurements taken on museum specimens ...... 85

4.2 Reasons for unusual convergence results returned by the convnum function ...... 86

4.3 Swimming Speed—nonsignificant putative covariates ...... 87

4.4 Results of Tukey honest significant differences test on anole swimming speed data ...... 88

4.5 Swimming and rebreathing videos...... 90

4.5.1 Swimming speed demonstration ...... 90

4.5.2 Rebreathing demonstration ...... 90

4.6 Male and female species mean morphology data sets ...... 90

4.6.1 Male data set ...... 90

4.6.2 Female data set ...... 90

4.7 Museum specimens consulted for this project ...... 90

1 Morphological convergence in semi-aquatic anoles 1.1 Introduction

1.1.1 Convergent evolution

Convergence, the independent evolution of similar phenotypes in different organismal lineages, is one of the most striking of all natural phenomena (Losos 2011; Stayton 2015; Mahler et al. 2017). Convergence is frequently theorized to be the product of adaptive evolution in situations where lineages have adopted the same environmental allegiances and correspondingly have come under similar sets of adaptive pressures (Darwin 1859; Hoekstra et al. 2006; Rosenblum et al. 2010). However, convergent patterns can also come about through non-adaptive processes (e.g., chance, or constraint) (Wake et al. 2011; Stayton 2015). Researchers have described a variety of types of convergence. Among others, these include “incomplete convergence,” wherein the phenotypes of putatively convergent species do not cluster in morphospace, but the vectors of morphological differentiation between convergent taxa and their closest relatives share a common orientation (Collar et al. 2014), and parallelism, a phenomenon in which taxa have evolved the same feature via the same alterations to the same developmental pathway (Arendt and Reznick 2008; Stayton 2015). For this work, I regard convergence as the independent evolution of phenotypic and functional similarity in daughter lineages from comparatively dissimilar ancestors.

Convergence has occurred many times across the vertebrate phylogeny. Marquee examples include the highly similar body plans and ecologies of many metatherian and eutherian mammals (Luo 2007), the morphologies and behaviours of burrowing anurans (Nomura et al. 2009), and wing-powered flight in bats, birds, and insects (Marden 1987).

1.1.2 Convergence in Anolis lizards

Anolis lizards, my focal taxon, are also celebrated for evolving convergently. On each island of the Greater Antilles (Cuba, Jamaica, Hispaniola, and Puerto Rico), anole clades have undergone replicated adaptive radiations, which have converged upon a stereotyped set of between four and seven “ecomorphs” (Williams 1983; Losos 1990; Mahler et al. 2016). These ecomorphs are defined based on anoles’ use of arboreal substrates and are named accordingly—the ecomorphs are as follows: trunk, trunk-ground, trunk-crown, crown giant, grass-bush, twig, and giant-twig.

The morphologies, ecologies, behaviours, and performance attributes of each species within an ecomorph category are remarkably similar, despite their phylogenetic separation (Losos et al. 1998; Mahler et al. 2013).

1.1.3 Island/mainland disparity in convergence in anoles

The Greater Antillean anole convergence story is well-known, and the statistical novelty of a replicated set of adaptive radiations has made anoles the focus of numerous evolutionary studies (Losos 2009). However, Greater Antillean anoles account for less than a third of the diversity of the Anolis clade (Losos 2009; Poe et al. 2017). Hundreds of species are found in the mainland neotropics, from the southern United States to southern Peru, northern Bolivia, and central Brazil. Unlike their Greater Antillean relatives, mainland anoles generally do not exhibit the same broadscale pattern of morphological and ecological convergence (Pinto et al. 2008; Schaad and Poe 2010). Attempts have been made to search for convergent phenotypes in mainland anoles (Leal et al. 2002; Schaad and Poe 2010; Moreno-Arias and Calderón-Espinosa 2016), but to date there are no broadly recognized mainland ecomorphs.

Two explanations have been proposed for this disparity. The first is that environments and ecological communities may differ radically between island and mainland regions. For example, relative to island habitats, we might expect that mainland environments might have higher predation pressure, a greater diversity of predators, differing substrate availability or habitat complexity, and a greater diversity of prey options, among other possible differences. Some studies have indeed found evidence for life history differences between island and mainland anoles (Fitch 1976; Andrews 1979), but there is, as yet, no consensus as to whether ecological differences are the cause of the lack of mainland anole convergence. Alternatively, the absence of convergence in mainland anoles can perhaps be ascribed to historical constraint—much of the anole diversity on the mainland comes from a single clade (Draconura) and it is possible the sort of morphological convergence noted in the Caribbean has not been possible for this clade to achieve, due to temporal or genetic limitations (Losos 2011).

A third possibility, of course, is that mainland anoles indeed exhibit convergent evolution, but that this convergence has been overlooked. Particularly if mainland and island settings differ in their principal axes of ecological structure, we may only expect mainland ecomorphological convergence in those specific instances in which anoles interact with their environment in highly

3 similar ways. Mainland anoles are much less well-studied ecologically than their Caribbean counterparts, so this possibility has yet to receive much consideration.

1.1.4 The expectation of convergence among semi-aquatic anoles

Given the prevalence of convergence in anoles, we expect phylogenetically independent anole species that occupy highly similar habitats should converge in multivariate niche space. We would thus predict that semi-aquatic anoles should exhibit convergent phenotypes. There have been at least six independent origins of the semi-aquatic lifestyle in Anolis (Leal et al. 2002; Gamble et al. 2014)—(see Figures 1 and 2 for a depiction of the semi-aquatic species and their ranges and phylogenetic relationships) and there are currently 12 recognized species that inhabit semi-aquatic environments (henceforth “semi-aquatic anoles,” “semi-aquatics,” or “aquatic anoles”). Different aquatic anole species occur on two Caribbean islands (Cuba and Hispaniola), in southern Mexico, and from Honduras to Ecuador.

Figure 1: Ranges of semi-aquatic anole species from Mexico, Central and South America, and the Caribbean. Red arrows denote species studied in the field during the course of this study.

Figure 2: Phylogenetic relationships of semi-aquatic anoles, adapted from Gamble et al. (2014). Semi-aquatics are shown in blue.

These anoles are restricted almost entirely to streamsides—they will rarely, if ever, be found more than 15 metres from a stream. Semi-aquatics typically perch on rocks and logs near stream edges; though they spend the majority of their time out of the water, swimming and diving are their main methods for escaping predators—aquatic anoles head straight for the water when threatened (Meyer 1968; Leal et al. 2002; Eifler and Eifler 2010a). At least four species (each phylogenetically independent) are known to capture and consume aquatic prey—A. vermiculatus (Gonalez Bermudez and Rodriguez Schettino 1982; Rodríguez-Schettino et al. 1987), A. aquaticus (Naskrecki 2012), A. barkeri (Meyer 1968), and A. oxylophus (Losin 2018 pers. comm.). Although they have evolved many times independently and are found in geographically disparate locations, semi-aquatic anoles all utilize stream resources in much the same way.

Surprisingly, however, Manuel Leal et al. reported little evidence for convergence in semi- aquatic anole morphology in a 2002 study. These authors examined nine morphological traits (snout-vent length, tail length, tail height at the base, lengths of the 4th toes of the hind and forefoot, femur, tibia, and longest tarsal bone lengths, and the number of subdigital lamellae on the 4th hindtoe). Their results suggested that island and mainland semi-aquatics did not cluster in a multidimensional trait morphospace (Leal et al. 2002; Muñoz et al. 2015).

Though Leal et al. (2002) considered a diversity of traits, they mainly considered structures which have known relationships with arboreal performance (Williams 1972; Williams 1983; Losos 1990). However, other morphological characters may be more relevant for semi-aquatic habitats. For this project, I measured several morphological features not considered by Leal et al. (2002) to test for potential evidence of morphological convergence in these ecologically similar lizards. I also analyzed potential avenues of phenotypic convergence other than morphology; these are presented in later chapters.

1.1.5 Hypotheses and predictions

I hypothesize that semi-aquatic Anolis lizards constitute a distinct and novel anole ecomorph which straddles both mainland and island regions. This hypothesis leads to the following testable predictions: Semi-aquatic anoles should cluster in high-dimensional morphospace, and statistical clustering methods (e.g., linear discriminant function analysis, hierarchical clustering, nearest neighbour distances) should reliably differentiate independent lineages of semi-aquatic anoles from other, non-aquatic congeners. Furthermore, this similarity is predicted to have arisen convergently from comparatively dissimilar ancestors.

This hypothesis also generates predictions about performance, behaviour, and ecology—the former two will be addressed in Chapters 2 and 3, respectively. This first chapter will address the morphological aspects of anole convergence.

1.2 Methods

1.2.1 Preamble

I measured preserved whole lizard specimens from the following research collections: the Museum of Comparative Zoology at Harvard University (MCZ), the Royal Ontario Museum

(ROM), the Los Angeles County Museum of Natural History (LACM), El Museo de Zoología de la Pontificia Universidad Católica del Ecuador (QCAZ), the personal research collection of Ian Wang, a collaborator from UC Berkeley (IW) and the personal research collection of my supervisor D.L. Mahler (Mahler). I gathered morphological data either at the Mahler Lab at the University of Toronto (via museum loans) or at the MCZ during a 2016 research visit. I used the same equipment and methods for all linear morphometric data collection. All specimens were stored in 70-75% ethanol. A complete list of specimens used for this project can be found in section 4.7 of the Appendices.

1.2.2 Linear morphometric data collection

Linear morphometric measurements have been used extensively by previous authors to identify multivariate morphological convergence in anoles (Losos 1990; Leal et al. 2002; Mahler et al. 2013). This thesis makes use of the data set previously assembled by D.L. Mahler, who measured 22 morphological traits relevant to arboreal habitats (see Appendix 4.1 for a complete list) on virtually all Greater Antillean Anolis lizards (Mahler et al. 2010; Mahler et al. 2013). Since publication, Mahler has augmented this data set with measurements from additional individuals and species, particularly for mainland taxa, and these were included in the present work—I used 18 of these 22 traits for my analysis. I have built upon this data set by measuring new traits theorized to be relevant to semi-aquatic living on a subset of species in the Mahler data set that includes all semi-aquatic anole species plus their close relatives. The traits I measured include: inter-narial distance, neck length, pectoral width and height, torso length, inter-ocular distance, and three measures each of tail height and width, taken along the tail at distances of 25%, 50%, and 75% of the lizard’s snout-vent length from the anterior edge of the cloaca (see Table A2 in the Appendices for descriptions of each measurement). Inter-narial width and inter-ocular distance, which capture the width of the dorsal surface of the head, were measured to test if an aquatic lifestyle might have selected for narrower head shapes. This phenomenon has been observed previously in aquatic snakes, where it has been interpreted as an adaptation to reduce drag during swimming (Segall et al. 2016). Neck length and torso length were measured in case they might be important for the sinusoidal movements that occur during swimming (Meyer 1968); pectoral girdle width and height were measured to test the idea that semi-aquatic anoles might exhibit dorso-ventral or lateral flattening relative to non-aquatic species (to minimize drag). Tail width and height characteristics were measured to test if semi-

8 aquatic anoles have laterally compressed tails, like many other semi-aquatic lizard taxa (Leal et al. 2002; Bauer and Jackman 2008). All “aquatic” measurements were taken using digital calipers (Mitutoyo 500 series) with a computer input cable to preclude transcription error. I also measured snout-vent length (SVL) and tail length (traits from Mahler et al. 2013); I used a fabric tape measure taped to the edge of a lab bench to obtain estimates of these lengths.

In total, I measured male and female anole specimens from all six semi-aquatic clades (11 of 12 species, plus 3 putative new aquatic species contained in the MCZ collections) as well as 60 non- aquatic species. When selecting non-aquatic anole taxa for this project, I prioritized species that were closely related to my semi-aquatic focal taxa so that I could determine whether semi- aquatics had diverged significantly in morphology relative to these congeners. Measuring close relatives also permitted me to assess whether any potential pattern of similarity could be attributed to adaptive convergence (as opposed to stasis or constraint), since convergent species that have undergone adaptive evolution should exhibit divergence from the phenotypes of their ancestors. I also measured a number of species more distantly related to semi-aquatics so that my final morphospace would more completely represent anole morphological diversity. Figure 3 depicts the anole phylogeny that I used for my analysis and the coverage of my linear morphometric data set. Time-calibrated phylogenetic trees containing all of my study species are not yet available. Thus, for all phylogenetic comparative analyses, I used the maximum clade credibility time-calibrated phylogeny of Gamble et al. (2014) and manually added tips representing all missing species using the function bind.tip from the R package “phytools” (Revell 2012). Placement of missing tips was determined by D.L. Mahler based on taxonomic expertise or unpublished phylogenetic analyses. Gamble et al.(2014) generated this phylogeny from 1500 bp of mitochondrial DNA (NADH and COI)—these sequences were taken from previous papers (Mahler et al. 2010; Rabosky and Glor 2010; Castañeda and de Queiroz 2011) and GenBank. The phylogeny was estimated using Bayesian Metropolis-coupled Markov Chain Monte Carlo methods and contains 216 anole species (Gamble et al. 2014). See Section 4.6 in the Appendices for the full male and female data sets.

Figure 3: Morphological coverage tree. Green tips denote both male and female data are present in the data set, yellow tips denote male data only, red tips indicate female data only, and blue tips denote aquatic species. Black tips indicate that no data are present for that species.

1.2.3 Phylogenetic principal component analysis of linear morphometric data

I transformed all measurements using the natural logarithm prior to analysis to improve normality and homogeneity of variance among groups, and to represent trait variation on a proportional, rather than absolute, scale. I generated separate vectors of male and female trait means for each species, and these data were then entered into separate phylogenetically-weighted principal component analyses (Revell 2012). Principal component analysis (PCA) leverages linear algebra to determine the primary orthogonal axes of variation within a high-dimensional data set. It is therefore a useful tool for visualizing and understanding complex data sets. Since species are not independent units, it is necessary to account for phylogenetic non-independence when conducting principal component rotation. All analyses were conducted on separate male and female morphospaces, as there are currently no methods to assess sexes simultaneously. I retained principal components in sequence until their cumulative variance explained reached 95%.

1.2.4 Analysis of putative convergence in semi-aquatic anoles using linear discriminant analysis, nearest neighbour distances, and simulation

For each sex, I conducted a linear discriminant analysis (LDA) to test whether semi-aquatic anoles could be reliably distinguished from non-aquatic anoles using PC axes derived from morphology. LDA generates a linear discriminant function which is a linear combination of the input variables optimized such that the “scores,” the output of the function, maximize the distinguishability of groups defined a priori. Using these scores, it is then possible to calculate the probabilities of each individual being classified into each group and make predictions (Izenman 2008). LDAs, however, are prone to overfitting (Luo et al. 2011), which could mean that the analyses’ confidence in their ability to make identifications might be unwarranted (and only applicable to a given data set).

I therefore conducted a test of convergence based on the Euclidean distances between aquatic taxa in morphospace. I calculated two distance measures: 1) the Euclidean distance to the nearest-aquatic neighbour taxon for each aquatic, and 2) the mean Euclidean distance between each aquatic and all others. I used these metrics as a measure of phenotypic similarity among aquatic anoles. I then conducted a phylogenetic bootstrap simulation analysis to determine if this

11 observed level of similarity was unusual given their phylogenetic relationships (as would be expected if the species were convergent). To this end, I simulated 999 data sets using the modified Gamble et al. (2014) phylogeny (Gamble et al. 2014) and the ratematrix and sim.char functions from the “geiger” R package (Harmon et al. 2008). I used the former function to generate an evolutionary variance-covariance matrix for all retained PCs (1-5) so that data would be simulated under the empirically-estimated rate of evolution for each trait axis. I then used the sim.char function to simulate data sets—this function simulates evolution under a Brownian motion model along an input tree following a user-input rate matrix. Because sim.char only accepts fully bifurcating trees, and my tree included several polytomies due to uncertainty about the relationships of taxa manually added the Gamble et al. tree, I used the multi2di function from the “ape” package to randomly resolve all polytomies with branches of zero length. The resulting tree can be used with geiger functions but effectively simulates Brownian motion evolution along tree with true polytomies. For each of these simulated data sets, I calculated mean Euclidean nearest-neighbour similarity among semi-aquatic anole species as described above, and then compared the distance from the actual morphology data set to the phylogenetically simulated null distribution, using an alpha level of 0.05.

I also conducted linear discriminant analysis on all simulated data sets and compared the performance of each of the simulated data set LDAs to the empirical LDA; once again, my significance level was 0.05.

1.2.5 Testing for convergence using the “convevol” R package

To more explicitly test for convergence from more dissimilar ancestors, I conducted several convergence tests using the R package “convevol” (Stayton 2015). I ran the convrat and convnum functions on my data set which generated the five convergence estimators laid out in

(Stayton 2015)—C1 through C5. All C metrics are calculated between pairs of putatively convergent taxa; where there are >2 convergent taxa, as with semi-aquatic anoles, pairwise values are calculated and then averaged. C1 is the ratio of the Euclidean distance between the two focal tips to the maximum distance between their independent evolutionary lineages (i.e., the two lineages of ancestors that directly trace from the present species pair back to their most recent common ancestor [MRCA]). Note that this maximum distance and other C-metric parameters are calculated using ancestral character estimates assuming a Brownian motion model of evolution

(Stayton 2015; Mahler et al. 2017). C2 measures the magnitude of convergence by subtracting the Euclidean distance between two putatively convergent tips from the maximum distance between the two taxa. C3 is the ratio of this metric, the magnitude of convergence, divided by the total amount of evolution that occurred in convergent lineages (i.e., the total phenotypic distance between the ancestor of all convergent taxa and all convergent descendants) (Stayton 2015) . C4 is the ratio of the magnitude of convergence to the amount of phenotypic evolution that occurred across the entire clade containing convergent tips, from the MRCA of all convergent taxa to all descendants (including non-convergent tips). Lastly, C5 is an estimate of the number of times phylogenetic lineages have entered the area of morphospace delineated by the putatively convergent taxa. The “convevol” package also includes significance testing functions for these metrics, which simulate null data sets in a manner akin to the bootstrapping analyses described above. I also conducted these significance tests.

1.3 Linear morphometry results

1.3.1 Male phylogenetic morphospace

In a phylogenetic principal component analysis of my morphometric data, PCs 1 to 5 explained 94.9% of variation and were thus retained for downstream analyses (Figure 4, Table 1). Each subsequent PC explained one percent of the total variation or less. Trait loadings for retained axes are presented in Table 2.

Figure 4: Scree plot of the first ten principal components of the male linear morphology data set; red vertical line delineates point at which 95% of variation has been captured. PCs 1-5 were retained.

PC1 PC2 PC3 PC4 PC5

Standard Deviation 0.686 0.149 0.106 0.097 0.095

Proportion of Variance 0.855 0.041 0.02 0.017 0.017

Cumulative Proportion 0.855 0.895 0.915 0.932 0.949

Table 1: Variance explained by each PC axis for the male PCA

Male semi-aquatic anoles broadly share the same area of morphospace (Figures 5-8). One semi- aquatic species, A. vermiculatus, is larger than all others and thus lies outside the main aquatic cluster due to its value for PC1 (which correlates strongly with overall body size). This analysis features at least one aquatic species from each independent clade; the phylogenetic tree in Figure 9 illustrates which aquatic species and close congeners were included in the male morphospace analysis.

A linear discriminant analysis (LDA) with leave-one-out cross-validation conducted on the five PCs retained from the phylogenetic principal component analysis was able to distinguish

14 between semi-aquatic and non-aquatic anoles 86.7% of the time; when compared to a null distribution of LDA scores, I found that this score was significantly better than expected (one- tailed p-value =0.022)—see Figure 12.

The mean nearest neighbour distance (MNND) for the aquatic data set was 1.19; the mean distance from the simulated data sets was 1.92. The MNND of the actual data set was significantly lower than that of the simulated data sets (p = 0.004; Figure 10).

The mean Euclidean distance between all aquatics in the observed data set was 3.06 while the expected mean distance under phylogenetic simulation was 5.65. This observed value was significantly lower than expected based on phylogenetic history alone (p = 0.006; Figure 11).

Figure 5: Male anole morphospace, PCs 1 and 2. Blue points are semi-aquatic species, peach points are non-aquatics.

Figure 6: Male anole morphospace, PCs 1 and 3. Blue points are semi-aquatic species

Figure 7: Male anole morphospace, PCs 1, 2 and 3. Blue spheres are semi-aquatic species, brown sphere are non-aquatics.

Figure 8: Male anole morphospace, PCs 3, 4 and 5. Blue spheres are semi-aquatic species

Figure 9: Phylogeny that includes all male anoles measured for this project

PC1 PC2 PC3 PC4 PC5 Snout-vent length -0.97 0.069 -0.014 0.119 0.011 Tail height at ¼ of SVL -0.939 -0.277 -0.024 0.071 -0.019 Tail width at ¼ of SVL -0.911 -0.029 -0.154 -0.27 0.129 Tail height at ½ of SVL -0.9 -0.379 -0.059 0.152 -0.031 Tail width at ½ of SVL -0.902 -0.139 -0.226 -0.251 0.134 Tail height at ¾ of SVL -0.904 -0.336 -0.102 0.102 -0.134 Tail width at ¾ of SVL -0.922 -0.076 -0.201 -0.208 0.003 Neck length -0.847 0.036 -0.113 0.104 -0.245 Pectoral width -0.935 -0.147 0.148 -0.174 0.064 Pectoral height -0.963 -0.076 0.127 -0.025 0.085 Torso length -0.929 0.092 -0.032 0.185 0.048 Min. inter-ocular -0.91 0.07 0.084 0.198 0.191 Inter-narial -0.793 -0.161 0.543 -0.131 -0.075 Head length -0.944 0.256 0.02 0.134 0.022 Head width -0.941 0.266 -0.014 0.055 0.049 Head height -0.937 0.272 0.048 0.122 0.009 Lower jaw length -0.949 0.247 0.024 0.123 0.03 Outlever length -0.946 0.261 0.012 0.122 0.032 Jugal to symphysis dist. -0.937 0.273 0.013 0.132 0.054 Femur length -0.921 0.261 -0.02 -0.059 -0.228 Tibia length -0.913 0.248 -0.008 -0.079 -0.268 Metatarsal length -0.889 0.303 0.02 -0.12 -0.263 4th toe length -0.918 0.244 -0.035 -0.078 -0.199 4th toe lamellae width -0.897 0.173 0.009 0.049 0.234 Humerus length -0.928 0.068 -0.038 -0.062 -0.03 Radius length -0.947 0.187 -0.023 -0.064 -0.138 4th finger length -0.935 0.228 -0.023 -0.043 -0.12 4th finger lamellae width -0.896 0.19 0.004 0.055 0.247 Pelvic height -0.948 0.167 -0.051 -0.036 -0.015 Pelvic width -0.964 0.143 -0.049 -0.001 0.087

Table 2: Loadings for the first five principal components of a phylogenetic PCA conducted on the male anole morphology data set.

Figure 10: Histogram of expected nearest neighbour distances among aquatics. Red line denotes observed MNND (1.19). 2-tailed p-value based on 999 simulations = 0.004.

Figure 11: Histogram of expected mean Euclidean inter-aquatic distances. Red line denotes observed mean distance (3.06). 2-tailed p-value based on 999 simulations = 0.006.

Figure 12: Histogram of expected LDA identification scores. Red line denotes observed score (86.7%).

1.3.2 Female phylogenetic morphospace

The distribution of female aquatic anoles within morphospace generally resembles that of their male counterparts—female aquatic anoles also appear to cluster along PC axes, although the pattern seems slightly less clear visually as other, non-aquatic species have encroached on the main cluster (see Figures 15-17). Similarly to the male analysis, I also retained five PCs (Figure 13; Table 3). The species complement present in the female morphospace is slightly different from that of the male due to specimen availability (see Figure 14).

Figure 13: Scree plot of the first ten principal components of the female linear morphology data set; red vertical line delineates point at which 95% of variation has been captured. PCs 1-5 were retained.

PC1 PC2 PC3 PC4 PC5

Standard Deviation 0.694 0.154 0.112 0.0897 0.0811

Proportion of Variance 0.859 0.042 0.022 0.014 0.012

Cumulative Proportion 0.859 0.901 0.923 0.938 0.949

Table 3: Variance explained by each PC axis for the female PCA.

The female data set yielded a similar significantly low MNND for the aquatic taxa indicating that they too cluster significantly in 5-dimensional morphospace (p < 0.001; Figure 19). The mean Euclidean distance between all female aquatics (2.41) was also significantly lower than expected (p < 0.001; see Figure 20). However, female semi-aquatics were not as distinct from non- aquatics as were males, according to my LDA. The LDA performed on the actual data set only outperformed those performed on simulated data sets 92.6% of the time (p = 0.074, Figure 21). The LDA’s accuracy was also lower for the female data set, with a classification success rate of 80.5%.

Figure 14: Female phylogeny used for phylogenetic principal component analysis. Blue denotes aquatic species.

Figure 15: Female anole morphospace, PCs 1 and 2. Blue points are semi-aquatic species.

Figure 16: Female anole morphospace, PCs 1 and 3. Blue points are semi-aquatic species

Figure 17: Female anole morphospace, PCs 1, 2, and 3. Blue spheres are semi-aquatic species

Figure 18: Female anole morphospace, PCs 3, 4, and 5. Blue spheres are semi-aquatic species

PC1 PC2 PC3 PC4 PC5 Snout-vent length -0.969 0.134 0.105 -0.056 -0.048 Tail height at ¼ of SVL -0.935 -0.208 0.108 -0.077 -0.165 Tail width at ¼ of SVL -0.91 -0.251 -0.067 0.128 -0.013 Tail height at ½ of SVL -0.914 -0.322 0.082 -0.03 -0.129 Tail width at ½ of SVL -0.874 -0.364 -0.051 0.257 -0.004 Tail height at ¾ of SVL -0.888 -0.381 0.021 -0.008 -0.142 Tail width at ¾ of SVL -0.881 -0.354 -0.098 0.179 0.001 Neck length -0.899 0.119 -0.047 -0.077 -0.292 Pectoral width -0.872 -0.341 0.061 -0.151 0.143 Pectoral height -0.953 -0.104 0.097 0.011 0.166 Torso length -0.923 0.209 0.172 -0.017 -0.094 Min. inter-ocular -0.869 0.197 0.295 0.032 0.07 Inter-narial -0.791 -0.324 0.067 -0.335 0.271 Head length -0.969 0.156 0.105 -0.04 0.003 Head width -0.97 0.097 -0.001 -0.031 0.041

Head height -0.969 0.136 0.085 -0.034 0.025 Lower jaw length -0.975 0.155 0.086 -0.041 -0.025 Outlever length -0.973 0.166 0.092 -0.046 -0.023 Jugal to symphysis dist. -0.969 0.178 0.098 -0.049 -0.026 Femur length -0.938 0.128 -0.258 -0.083 0.032 Tibia length -0.923 0.162 -0.314 -0.055 0.041 Metatarsal length -0.923 0.092 -0.314 0.004 0.052 4th toe length -0.941 0.094 -0.256 -0.036 0.037 4th toe lamellae width -0.884 0.175 0.155 0.264 0.164 Humerus length -0.886 0.122 -0.016 0.125 -0.115 Radius length -0.946 0.137 -0.175 0.094 0.021 4th finger length -0.953 0.108 -0.158 0.058 0.05 4th finger lamellae width -0.906 0.129 0.193 0.252 0.128 Pelvic height -0.972 -0.011 -0.006 -0.088 -0.041 Pelvic width -0.962 -0.016 0.035 -0.039 -0.011

Table 4: Loadings for the first five principal components of a phylogenetic PCA conducted on the female anole morphology data set.

Figure 19: Histogram of expected nearest neighbour distances among female aquatics. Red line denotes observed MNND (0.98). 2-tailed p-value based on 999 simulations < 0.001.

Figure 20: Histogram of expected mean Euclidean inter-aquatic distances. Red line denotes observed mean distance (2.41). 2-tailed p-value based on 999 simulations = 0.006.

Figure 21: Histogram of expected LDA identification scores. Red line denotes observed score (80.5%). P-value based on 999 simulated replicates = 0.072.

1.3.3 “convevol” metric results

The convnum function, which quantifies the number of times that convergent taxa have entered the region of morphospace that the tips of the phylogeny delineate (i.e., C5), recovered seven convergence events based on the phylogeny and male morphology data. This number of convergence events is significantly greater than expected given the tree and data (p=0.001; Figure 22). Similarly, convnum detected 8 convergent shifts in female aquatic anoles (p < 0.001; Figure 23).

Both male and female aquatic anoles also exhibited convergence relative to their ancestors and to the clade of anoles that I measured as a whole, as estimated via Stayton’s four quantitative convergence metrics (C1 – C4). For all four metrics semi-aquatic anoles exhibited significantly greater convergence than expected from phylogenetic null simulations (Table 5; Figures 24 and 25).

Figure 22: Histogram of convergence events detected by convnum in simulated data sets based on male PC data; red line shows observed number of convergence events (7).

Figure 23: Histogram of convergence events detected by convnum in simulated data sets based on female PC data; red line shows observed number of convergence events (8).

Figure 24: Histograms of 99 simulated values for each of Stayton’s C metrics for the male anole morphology data set. Red vertical lines denote the observed value. All observed values were significantly different from the expected (p < 0.01).

Figure 25: Histograms of 99 simulated values for each of Stayton’s C metrics for the female anole morphology data set. Red vertical lines denote the observed value. All observed values were significantly different from the expected (p < 0.01 for C1-C3; p = 0.04 for C4).

C1 C2 C3 C4 C5

Male 0.445 3.15 0.240 0.012 7

P-values <0.01 <0.01 <0.01 <0.01 0.001

Female 0.428 2.43 0.211 0.011 8

P-values <0.01 <0.01 <0.01 0.04 <0.001

Table 5: P-values and results of “convevol” analysis (Stayton 2015).

1.4 Discussion

1.4.1 Evidence for convergence in semi-aquatic anoles

Based on ecomorphological theory (Wainwright 1994; Morris 2010; Stayton 2015) and the well- documented history of morphological convergence in the genus Anolis (Williams 1983; Losos

1990; Mahler et al. 2013), I predicted that the independent clades of semi-aquatic anoles should occupy the same region of morphospace when plotted alongside other non-aquatic anoles. Anoles as a group have shown a great propensity for adaptive evolution—we would thus predict that each separate aquatic anole clade should evolve common morphological specializations to the shared features of their similar environments and lifestyles.

The results of my morphometric analyses appear to support this prediction. Phylogenetically- distinct semi-aquatic clades were found to occupy the same region of a PC morphospace and are significantly more clustered than we would expect by chance. The significance of this multidimensional clustering was robust to the inclusion of A. vermiculatus, which lies outside the main aquatic group by a considerable margin along PC 1 due to its especially large size. Taken together, the results of my Euclidean distance analysis and LDA indicate that aquatics cluster more closely together in a five-dimensional morphospace than we would expect by chance given their phylogenetic relationships, and that they can be differentiated from non-aquatic anoles with significantly more confidence than we would expect by chance.

More historically explicit tests for convergence from dissimilar ancestors also support the conclusion that aquatic anoles are convergent. Using Stayton’s (2015) convnum approach, I estimated seven and eight distinct convergence events within the male and female semi-aquatic anole groups, respectively—numbers greatly exceeding null expectations, and, in fact, one or two greater than the number of anole clades with known semi-aquatic affiliations (see Appendix 4.2 for discussion of potential reasons for this). Results from Stayton’s other convergence tests likewise reveal that aquatic anoles are exceptional in the strength of convergence, in addition to its frequency. In fact, aquatic anole species (both male and female) score higher on the C1 ratio index (0.42 to 0.44) than any Caribbean ecomorph (0.41-0.01, which Stayton calculated using Anolis data from Mahler et al. (2013); see also Table 5, as well as Table 1 from Stayton 2015). , This means that pairs of aquatic taxa, on average, closed a greater percentage of the maximum distance between them over evolutionary time than did the taxa in any particular ecomorph group. Stayton’s C2 metric is not comparable between data sets, but aquatics also exhibited higher C3 metric values, which reflect the percentage of evolutionary change since the most recent common ancestor of a pair of taxa that can be assigned to convergence. In male and female aquatics, this metric (averaged across all aquatics) is 22.6%, whereas the Caribbean ecomorphs averaged 1.6%. Similar comparisons were observed for Stayton’s C4 and C5

30 convergence metrics (not shown). Together, these results suggest that convergence in aquatic anoles is as least as strong as in the famed Caribbean anole ecomorphs.

My hypothesis of ecomorphological convergence in aquatic anoles is also supported by the fact that I observed similar convergence patterns in both male and female anole morphospaces. Though this is not unexpected, it has frequently gone untested (Losos 2009)—most previous anole studies (e.g., Mahler et al. 2010) have only considered the morphologies of adult males. This study shows that female aquatic anoles exhibit similar patterns of morphological convergence as males. That both sexes show concordant patterns suggests that this morphological convergence is not driven by sexual selection, indirectly strengthening the case for performance-based adaptation to a shared environment.

My finding of convergence in aquatic anoles is directly contrary to the conclusions of Leal et al. (2002), who conducted PCAs and discriminant function analyses on a smaller data set and did not find significant clustering among my focal taxa. This difference in results may be in due in part to the absence of an explicitly phylogenetic analytical approach in the Leal et al. 2002 paper—as was typical at the time, the authors did not use the phylogenetic variance-covariance matrix when conducting their PCA. One possibility is that the Euclidean distances they measured between the Caribbean aquatics, A. vermiculatus and A. eugenegrahami, and their mainland counterparts may have been inflated by use of a non-phylogenetic PCA, as the lamella count variable they used has high phylogenetic signal and is known to differ greatly between island and mainland anole clades. However, I suspect the main reason for the difference between my results and Leal’s come down to the data themselves. Nearly all “aquatic-specific” traits I measured (e.g., tail width and height, neck length, internarial distance, and pectoral width and height) were not analyzed by Leal et al. (2002) and were ultimately important to my analyses. These additional traits loaded heavily on PCs 2-5 (see Tables 2 and 4), and likely provided the information needed to identify aquatics as a distinct and convergent cluster. Additionally, I measured all recognized aquatic anole species except A. purpuronectes (which is sister to and highly morphologically similar to A. barkeri, which I did measure) whereas Leal et al. (2002) only measured seven aquatic species total. I also measured roughly twice the number of non- aquatic taxa included by Leal et al. (2002). Leal and colleagues may have thus failed to detect significant evidence of convergence in aquatic anoles due to a lack of statistical power.

There is a long history of finding convergence in anole clades that occupy the same habitats, beginning with the mainly descriptive efforts of Ernest Williams in the 1970s (Williams 1972) and progressing to multidimensional morphological analyses which take phylogenetic history into account (Butler and King 2004; Harmon et al. 2005; Langerhans et al. 2006; Mahler et al. 2013). However, these efforts have generally focused on the replicated adaptive radiations of anoles found on the four Greater Antillean islands. In contrast, the ecomorphology of mainland anoles has rarely been studied (but see Velasco and Herrel 2007; Pinto et al. 2008; Moreno-Arias and Calderón-Espinosa 2016).

My work thus stands to help resolve a long-standing question in anole biology about the different frequencies of convergence in mainland and island settings. If historical constraint were responsible for the observed disparity in convergence between island and mainland anole species, we would not expect island and mainland aquatic taxa to cluster on the same morphospace plot, as the constraints should prevent such an evolutionary outcome (Hardy et al. 2015). We observe the opposite pattern here—aquatic anoles, mainland and island alike, cluster quite significantly. I suggest that island-mainland environmental differences (e.g., Fitch 1976; Andrews 1979) are more likely the cause of the apparent absence of convergence in mainland anoles. Streamside habitats are one ecological setting that is likely quite similar between islands and the mainland (Boccia pers. obs.). I have now demonstrated that, in such habitats at least, mainland and island clades have converged on similar morphological solutions despite their phylogenetic distance. It thus seems that similar habitats can in principle yield convergence among mainland and island anoles. Why we do not see such convergence in non-aquatic and arboreal anoles will require additional study.

1.4.2 Conclusions and future directions

Based on a multi-dimensional morphometric study that includes novel traits likely relevant to aquatic performance, I conclude that semi-aquatic anoles exhibit morphological convergence.

I hope to build on this finding by analyzing 3D skeletal structures of both aquatic and non- aquatic species to determine whether they reveal the same pattern of convergence evident from external measurements. Specifically, I plan to assess both the pelvic and pectoral girdles of all aquatic lineages along with a set of non-aquatic anole species similar to that discussed above for comparison in the near future. I am also interested in testing for convergence in the colouration

32 and scalation of aquatic anoles. I plan to use NaturePatternMatch (Stoddard et al. 2014) to analyze colouration photos taken during the course of my last three field trips.

Aquatic performance of semi-aquatic anoles 2.1 Introduction

2.1.1 Background

As discussed in Chapter 1, ecomorphological theory predicts that organisms that live in similar environments and are subject to similar challenges are likely to converge in morphology, behaviour, and performance (Wainwright 1994). We generally predict convergence when phylogenetically independent members of the same clade are found in similar habitats, provided that the relationship between form and function is a relatively simple one. This hypothesis is often tested via morphological analysis, with the assumption that similar morphologies reflect similar niche use (Stayton 2006). However, morphology is linked to the niche through organismal performance (Arnold 1983). Thus, it is important to consider performance when testing for ecologically driven convergence (Losos 2011). In this chapter, I will build upon my morphology results by testing whether or not semi-aquatic anoles exhibit superior performance in riparian habitats relative to their non-aquatic congeners.

Understanding organismal performance can be especially important for detecting functional convergence that might otherwise be missed (Stayton 2006). When two or more taxa converge in performance abilities, they can do so in one of two ways—evolution of structures of similar design which fulfill a performance function via the same physical mechanism (one-to-one mapping) or the evolution of alternative structures which achieve the same performance function via different mechanisms (many-to-one mapping) (Alfaro et al. 2005; Wainwright et al. 2005; Wainwright 2007). An example of this is the four-bar linkage in the jaws of labrid fishes. By shortening or lengthening different components of the jaw structure, labrid fishes which have similar feeding requirements can achieve the same jaw-closing performance despite possessing fundamentally different underlying jaw morphologies (Wainwright et al. 2004). Thus, taxa with differing morphologies can still be functionally convergent; however, this convergence would not be detected via study of morphology alone.

Similarly, species with apparently similar morphological traits may nonetheless exhibit important differences in functional performance. This is especially likely if key components of a functional system (e.g., musculature, or metabolic rate) were not measured, a common reality in

34 studies of phenotypic diversity. For these reasons, when testing the hypothesis that ecological factors have driven morphological convergence, it is important to test whether morphologically convergent species also exhibit superior performance at the ecological tasks to which they are putatively specialized.

2.1.2 Linking ecology, morphology, and performance in anoles

It is widely assumed that there is a one-to-one mapping between form and functional performance in Anolis lizards. In part, this is due to the spectacular repeated morphological convergence that has made anoles a famous model system for evolution—if the ancestral Caribbean island colonist anoles had been able to use a wide range of equivalent structural forms to occupy the similar ecological niches available on these islands, it is unlikely that they would exhibit the deterministic macroscale convergence that we observe in the anole ecomorphs.

The primary reason for this assumption, however, is that a great deal of experimental research has been conducted on anole ecomorphology, providing empirical evidence for strong links between the morphology of Greater Antillean anoles, their gripping and sprinting performance, and their ecological preferences [Losos and Sinervo 1989; Losos 1990; Boggs and Irschick 1996; Macrini and Irschick 1998; Irschick et al. 1999; Crandell et al. 2014; reviewed in Losos (2009)]. For example, anoles that prefer broad substrates tend to practice a sit-and-wait ambush feeding style (e.g., trunk-ground ecomorph anoles). This foraging style requires prey-pursuit dashes, and these species correspondingly tend to have longer hindlimbs, which give them demonstrably faster sprint speeds relative to narrow-substrate species (e.g., twig ecomorph anoles) (Losos 1990). Narrow-substrate species have shorter hindlimbs, but greater agility and clinging ability on narrow surfaces (Losos and Sinervo 1989). Similarly, lamella width, which correlates with an anole’s clinging performance on smooth substrates, is greater in anoles that occupy leafy, upper canopy habitats (trunk-crown and crown-giant ecomorphs) (Glossip and Losos 1997). These relationships between morphology, performance, and ecology have arisen independently many times in anoles occupying similar habitats on the islands of the Greater Antilles. We therefore expect that, when anole species occupy similar habitats, they should demonstrate similar performance abilities, even if they are distant relatives within the Anolis clade.

2.1.3 Performance demands of semi-aquatic habitats

Semi-aquatic anoles are generally found within fifteen metres of a stream and spend a great deal of their time foraging around (and sometimes in) streams (Meyer 1968; Williams 1984; Leal et al. 2002; Eifler and Eifler 2010b; Herrmann 2017). Aquatics readily use streams as a refuge— when approached by a predator (or biologist), aquatics generally dive into the water to escape (Kennedy 1962; Robinson 1962; Meyer 1968; Campbell 1973; Eifler and Eifler 2010b). Therefore, we might expect that semi-aquatics would experience selection for superior swimming and diving performance, as it appears to be the primary means by which they escape predators. Superior swimming performance would also be important for the species that have been observed to take fish and aquatic invertebrates as prey (Rodríguez-Schettino et al. 1987; Leal et al. 2002). Additionally, strong swimming and diving abilities also seem prudent for any lizard that spends a good deal of time alongside streams with strong currents, as individuals that fall in (intentionally or not) and are unable to outswim the current risk being swept far from their territories or drowned (Boccia pers. obs. and (Eifler and Eifler 2010b)). Swimming is also sometimes the easiest way to get around between perches and food sources in streamside environments (Eifler and Eifler 2010b)—this might provide additional evolutionary motivation for the evolution of superior swimming abilities.

2.1.4 Hypotheses and predictions

Ecomorphological theory suggests that semi-aquatic anoles should be adept at swimming, which is integral to their use of and survival in streamside habitats. I therefore hypothesize that semi- aquatic anole lineages should converge in exhibiting improved swimming performance relative to non-aquatic anole species. Correspondingly, I predict that the semi-aquatic species that I test should demonstrate faster average swimming speeds than co-occurring non-aquatic anoles.

For the same reasons, I would also expect that semi-aquatic anoles would show superior diving performance relative to non-aquatic anoles, which rarely have the need or opportunity to dive (Heatwole et al. 2009). I therefore also hypothesize that semi-aquatic anoles should also show convergence in diving ability and predict that semi-aquatics should dive more often to escape perceived threats than non-aquatic anoles and should be able to remain underwater for longer durations than those non-aquatic anoles that do dive.

2.2 Methods

2.2.1 Field work and lizard capture

To conduct swimming performance trials, I needed to obtain test subjects from wild semi-aquatic and non-aquatic anole populations. To this end, I travelled to four field stations in three countries: La Selva and Las Cruces field stations in Costa Rica (I spent three weeks at each, from April-June, 2017), Parque Nacional Tatamá in Colombia (2 weeks in June, 2018), and Los Tuxtlas field station in Mexico (3 weeks in July, 2018). My field assistants and I captured as many anoles of as many species as possible at each site, using lizard nooses and hand capture techniques (we also received some lizards from other researchers working at the station). Lizards were placed into cloth bags and brought back to our field station workspace for performance testing, morphological measurements, and photography. All lizards were tested within 12-18 hours of capture. In total, we captured and tested individuals representing 24 Anolis species. My field assistants and I recorded the following information whenever we captured a lizard: species identification, sex, time of capture, location of capture (within +/- 50m of GPS waypoints), and perch characteristics (type, underlying substrate, width, height, temperature). I also collected measurements of body size for each individual (mass and SVL). Mass measurements were taken using a field scale before performance trials were conducted. SVL measurements were taken after all performance work had been completed, since handling during the SVL measuring process might otherwise have impacted individuals’ subsequent performance abilities. Following swimming speed, diving, and rebreathing tests (see Chapter 3 for discussion of the rebreathing phenomenon), we released each anole at the site of its capture.

2.2.1.1 Costa Rica localities and number of anoles captured

Lizard capture was conducted in Costa Rica at two field stations maintained by the Organization for Tropical Studies (La Selva and Las Cruces). La Selva field station (Heredia) is located in north-central Costa Rica (10°25′19″ N, 84°00′54″ W) and has an Anolis diversity of 8 species, including the aquatic A. oxylophus (Guyer 1994; Savage 2002). At La Selva, we tested A. oxylophus, A. limifrons, A. lemurinus, A. capito, A. humilis, and A. biporcatus (A. pentaprion and A. carpenteri also occur at the site but are rarely encountered and were not tested). The La Selva property consists of marked trails in primary and secondary tropical rainforest, and a lodging area and research station campus. The semi-aquatic anole Anolis oxylophus was found solely

37 along rocky and mud-bottomed streams. Anolis lemurinus was found predominantly on tree trunks in the station arboretum. Anolis limifrons was found throughout secondary and primary forest in low shrubs. Anolis humilis was found throughout the property in leaf litter. We also captured one A. biporcatus on high palm fronds in mature forest and one A. capito, which was found on a tree trunk.

The other Costa Rican station we visited, Las Cruces, is located in extreme southern Costa Rica and is only a few kilometres from the Panama border (8° 47' 7'' N, 82° 57' 32'' W). Las Cruces is home to 10 anole species (Savage 2002), including the semi-aquatic A. aquaticus. Of the nine other species present, we captured and tested individuals of A. polylepis, A. capito, A. biporcatus, and A. insignis. Anolis aquaticus was found only along rocky and sliprock canyon streams. Anolis polylepis was found on mid-height shrubs and trees in the forest and in disturbed areas. Our sole A. insignis was found on a banana plant in the cabin area. Our A. capito were on vines or (curiously) on the ground. In total, we captured 165 individuals representing nine different anole species in Costa Rica. Only one aquatic species was present at each site and two wide- ranging non-aquatic species were present at both field sites (A. capito and A. biporcatus).

2.2.1.2 Colombia localities and number of anoles captured

I conducted fieldwork in Colombia at the Parque Nacional Natural Tatamá in the western Andes (5°13'49.2"N, 76°04'58.0"W). This high elevation park spans a roughly 1300 elevational gradient from wet montane rainforest at ~1300 m to elfin forest at ~2600 m (Terbough 1977). In total, I and my team captured 102 anoles representing ten different species at Tatamá. The aquatic anole A. maculigula was captured along a small stream next to an abandoned school house (~1400 m), and non-aquatic anole species were captured along the Montezuma road (1300 m to 2600 m). Anolis antonii was found along roadsides from the montane rainforest at 1300 m to cloud forest at about 1800 m. Anolis chloris was found primarily in the disturbed diversified agricultural lands of the community we were staying in at 1300 m, and A. frenatus, A. purpurescens, and A. princeps were found along roadsides in this area. Anolis limon, A. megalopithecus, A. ventrimaculatus, and A. antioquiae were only found at high elevation (1800 to 2400 m) in the temperate or grassland zones.

2.2.1.3 Mexico localities and number of anoles captured

I visited Estación de Biología Tropical Los Tuxtlas in July of 2018. Anolis barkeri individuals were primarily captured at the nearby “Reserva Anolis” which is a locally-owned hiking and waterfall nature park southeast of Lake Catemaco (18°21'48.0", 95°02'35.0"W). Non-aquatic anoles were captured on the station grounds (18°35'06.4"N, 95°04'30.0"W), at Reserva Anolis, and at sites in the Los Tuxtlas biological reserve. We captured 91 anoles, of five different species. Anolis barkeri was found solely along permanent, rocky tropical streams at low elevation (less than 200 m). Anolis rodriguezi was locally rare, and our single individual was found along a roadside. Anolis duellmani is an endemic that is only found on the slopes of two volcanoes in the Tuxtla region—we found our single female on the slopes of Volcan San Martin. Anolis sericeus was found solely along roadsides in tall grass/shrublands, or along barbed wire fences. Anolis uniformis was found predominantly in tropical forest leaf litter and on low shrubs.

2.2.2 Swimming speed experiments

I quantified the swimming speed of each individual that we captured using a field lab setup that included an aquatic arena, a standardized grid for scale, and a high-speed camera (see Section 4.5 of the Appendices for a video showing this setup). These experiments were modelled after previous vertebrate swimming studies (Burgess et al. 2006; Young and Blob 2015) Though the general setup remained constant, the aquatic arena changed between my 2017 and 2018 field seasons.

In Costa Rica in 2017, I used a Plexiglas aquarium (122 cm x 30.5 cm x 30.5 cm), which I constructed in the field, to test anole swimming abilities. A one-inch square grid was placed underneath the tank to provide scale. However, I found that the long and narrow dimensions of the aquarium were suboptimal for swimming tests because anoles would frequently try to escape by immediately swimming to the walls of tank, instead of swimming the length of the tank to the hide as I had intended. The tank was also not quite large enough to prevent lizards from occasionally escaping by jumping over the walls (when this occurred during a swimming trial, the lizard was quickly captured and returned to the central rock). I was able to obtain good data from this first set of experiments, but I altered my test arena design in 2018 for fieldwork in Colombia and Mexico. I obtained a circular pet wading pool with 20 cm high walls and a radius of 0.75 m; the interior coating of the pool was navy blue. By placing my anoline test subjects in

39 the center of this pool, I was able to ensure that each anole had to swim at least three-quarters of a meter to exit the arena. I positioned the high-speed camera facing directly downwards using a level; the camera’s field of view captured approximately 75% of the area of the wading pool. The same calibration grid (one inch x one inch) used in 2017 was also used during my 2018 experiments.

For 2017 trials, I filled the Plexiglas tank with 20 cm of de-chlorinated water, two rock perches, and a dark plastic “hide” that sat on one of the rocks. At the beginning of a trial, lizards were placed upon the rock that lacked a hide and given two minutes to acclimate to the tank environment. I then encouraged them to swim by simulating predation attempts; I would quickly move my hand behind the lizard and tap the sides of its tail—this generally caused all individuals to attempt to escape this perceived threat. Each swimming trial was recorded from above by a high-speed camera (Sony RX-100 V) that recorded images at a rate of 120 frames per second. The camera’s field of view encompassed the area of the tank that was between the initial perch and the hide.

Experiments conducted in the wading pool in 2018 were identical to those from 2017 except that lizards tested in this latter setup were initially dropped directly into the water rather than placed on the central rock. Any individuals that immediately swam to the central rock were encouraged (via simulated predations attempts) to swim to the margins of the pool.

In total, I tested the swimming abilities of 353 individuals from 24 anole species (4 semi-aquatic, 20 non-aquatic). I also tested 7 non-anoline lizards—three Iguana iguana juveniles and four juvenile basilisks (Basiliscus vittatus). I tested both males and females whenever possible, although some species were so uncommon that we did not find individuals of both sexes. The number of lizards tested per species for each country and at each field site is reported in Table 6. Not all lizards in this table yielded usable data—swimming speed analyses were conducted using solely adults which were in good condition and for which I had snout-vent length data available.

Further, only a subset of anole species (those with n>5) were well-enough sampled to be included in species pattern statistical analysis (see bold entries in Table 6); in total, 257 lizards were analyzed for the species pattern subsection. All 276 usable trials were analyzed for the phylogenetic analysis of swimming speed.

Species Male Female Juvenile Total Total usable

Tatamá, Colombia

A. antonii 18 15 3 36 17

A. antioquiae 0 1 0 1 1

A. chloris 12 10 0 22 20

A. frenatus 0 0 1 1 0

A. limon 2 1 0 3 3

A. maculigula 15 8 9 32 17

A. megalopithecus 1 0 0 1 1

A. princeps 1 1 0 2 2

A. purpurescens 0 1 0 1 1

A. ventrimaculatus 3 1 0 4 4

Las Cruces, Costa Rica

A. aquaticus 17 6 10 33 22

A. biporcatus 0 1 0 1 1

A. capito 1 0 2 3 1

A. insignis 1 0 0 1 1

A. polylepis 9 9 4 22 17

La Selva, Costa Rica

A. biporcatus 1 0 0 1 1

A. capito 1 0 0 1 1

A. humilis 22 5 1 28 27

A. lemurinus 16 7 0 23 22

A. limifrons 9 15 0 24 24

A. oxylophus 10 9 4 23 19

Los Tuxtlas, Mexico

A. barkeri 17 10 9 36 27

A. duellmani 0 1 0 1 1

A. rodriguezi 0 1 0 1 1

A. sericeus 9 12 3 24 20

A. uniformis 11 13 4 28 25

Grand Totals

Total (Colombia) 52 38 13 103 66

Total (La Selva, CR) 59 36 5 100 94

Total (Las Cruces, CR) 28 16 16 60 42

Total (Mexico) 37 37 16 90 74

Total (all sites) 176 127 50 353 276

Table 6: Summary of anoles caught for this project. Bold rows indicate that I had a large enough sample size for that species to include it in species pattern statistical analyses.

2.2.3 Quantification of swimming speed

To estimate swimming speed, I used the physics software program Tracker (Brown 2018). Swimming videos were trimmed to the few seconds containing the swimming burst. A swimming bout was considered the time between the lizard’s first stroke after entering the water and the time it reached the exterior wall of the tank/pool/other object, or the point at which it stopped swimming and began floating. If lizards turned sharply during a trial, I only considered the longest straight-line portion of the swim. Using the calibration grids that were in view of the camera in both the tank and wading pool setups, I calibrated distance in each video using the “Calibration Stick” function in Tracker. For my 2017 Costa Rica videos, I used the point mass tracking tool to place tracking landmarks on the anteriormost point of the lizard’s head; this was done frame-by-frame such that the coordinates of the lizard within the recording frame were recorded for the entirety for the video. For trials conducted in 2018 (i.e., in Colombia and Mexico), I marked the posterodorsal region of each lizard’s head with a small (1 mm) spot of nontoxic white paint. I was therefore able to use Tracker’s built-in “autotracker” function to automatically identify and record the position of this conspicuous landmark in each frame for these videos. Because the autotracker’s patch identification abilities were imperfect, I reviewed all autotracked videos for errors and manually corrected mismarked frames as needed. I also aligned Tracker’s axes such that positive values along the x-axis indicated swimming away from the starting location. This allowed me to obtain estimates of the x-component of velocity of the lizard (i.e., in this case, the forward swimming velocity of the lizards). Most lizard species that I observed used sinusoidal swimming styles—their bodies undulated laterally, leading to noise in instantaneous velocity measurements (i.e., instantaneous velocity estimates captured velocity from side-to-side as well as actual forward speed). However, taking the x-component of velocity addressed this problem, as quick movements in the y-axis would not impact the accuracy of the speed estimates. Once I had placed tracking points throughout the video, I exported all data to Excel and calculated the average speed across the entire trial for each individual. Undergraduate volunteer Cole Brookson assisted me with the processing of videos taken in Costa Rica; I conducted all video analysis for the recordings from Colombia and Mexico.

2.2.4 Analysis of aquatic and non-aquatic anole swimming speeds

I chose mean swimming speed during the course of a trial as my response variable. I chose mean speed rather than mean acceleration or maximum velocity because accurate acceleration estimation requires measurements be generated using center of mass analysis (Riskin 2017, pers. comm.), and because maximum velocity measurements are more sensitive to aberrant or outlier movements. I generated mean velocity estimates from each video and analyzed the data in the R statistical environment. Since there was a great deal of variability in juvenile swimming performance (and the number of juveniles captured differed between species), I only analyzed swimming speed in adult lizards. I ln-transformed all swimming speed measurements before analysis, as this improved both the normality and homogeneity of variances among species.

Average swimming speed was not correlated with sex, ambient temperature, or water temperature, so there was no need to correct for these potential performance covariates (Figures A1-A3). Additionally, swimming speeds did not differ across the three countries I collected data from (see Figure 29), so only the results of analyses done on the entire swimming speed data set are presented here.

To compare swimming performance among all species in my sample, I conducted an Analysis of Variance (ANOVA) on the ln-transformed swimming speeds of all aquatic and non-aquatic individuals that I tested, with species as my grouping variable. When that ANOVA returned a significant result, I subsequently conducted a Tukey Honest Significant Differences test (TukeyHSD) to determine where the differences between species lay.

2.2.4.1 Phylogenetic analysis of anole swimming speeds

Since my primary question involves testing for macroevolutionary convergence in semi-aquatic anole performance, I also conducted analyses to ask whether semi-aquatics exhibit superior swimming performance to non-aquatics, while accounting for phylogenetic history. Time- calibrated phylogenetic trees containing all of my study species are not yet available. Thus, for all phylogenetic comparative analyses, I used the modified maximum clade credibility time- calibrated phylogeny of Gamble et al. (2014) described in Chapter 1 (Figure 26).

Figure 26: Modified phylogeny from Gamble et al. (2014) used for phylogenetic comparative analyses. Blue tips denote aquatic species.

I conducted a simulation-based phylogenetic ANOVA using the phylANOVA function from the R package “phytools” (Revell 2012). I used habitat (aquatic or not aquatic) as a grouping variable, and ln-transformed species means as the response variable.

Size is often correlated with performance in anoles and lizards in general (Herrel et al. 1999; Wittorski et al. 2016). I therefore tested whether size is an important predictor of swimming speed using two different phylogenetic methods. First, I used phylogenetic generalized least squares (PGLS) regression to ask whether ln(snout-vent length) is a significant predictor of ln(mean swimming speed) using the pgls.SEy function in phytools.

Next, I conducted a phylogenetic ANCOVA using generalized least squares and the phylogenetic correlation matrix for my combined species tree to test whether size was an important (and

45 potentially confounding) covariate in the relationship between semi-aquatic lifestyle and mean swimming speed. I used the R function gls to evaluate three models, and in each I used the Gamble et al. (2014) phylogeny and Pagel’s lambda model of evolution to model potential phylogenetic correlations among residuals: (1) I modeled mean swimming speed as a function of size and habitat (semi-aquatic vs. non-aquatic); (2) I modeled mean swimming speed as a function of body size; (3) I modeled swimming speed as a function of habitat. I compared AIC model fits using the anova function in R.

2.2.5 Observation and analysis of voluntary diving

To test whether semi-aquatic anoles exhibit a greater propensity to dive, and superior diving performance than non-aquatic anoles, we studied anole diving using an opportunistic observational approach. During the swimming speed experiments discussed above, some anoles would sometimes choose to dive to escape rather than swimming to the edge of the test area. The stimulus for this response remains unknown, and we were unable to repeatably induce this behaviour in the lab. When anoles dove in the lab (or, on a few occasions, in the field) we recorded this response, and timed the duration of the dive using a stopwatch. Most dives were also incidentally recorded with a handheld GoPro Hero 4 camera being used to record aquatic performance trials from an underwater perspective.

2.3 Results

2.3.1 Swimming speed analysis

2.3.1.1 Swimming speed: species patterns

All aquatic anoles were found to have exceeded the swimming speeds of all well-sampled (n>5) non-aquatic anole species, with the exception of A. aquaticus, whose advantage over A. limifrons was nearly significant (p = 0. 054)—see ANOVA results in Table 7 and full TukeyHSD results in Table A3 in the Appendices. Aquatics typically swam at speeds from about 0.6 m/s to 0.8 m/s on average, while most non-aquatic species swam at speeds less than 0.4 m/s. Figure 27 shows untransformed swimming speed species means for ease of interpretation; ln-transformed results are shown in Figure 28. All species tested are plotted.

Figure 27: Plot of mean swimming speed observed for all anole species tested during this study. Error bars show +/- 1 SEM

Figure 28: Plot of ln-transformed mean swimming speed observed for all anole species tested during this study. The value 1.0 was added to all raw speeds prior to ln- transformation to obtain positive values. Error bars show +/- 1 SEM

Df Sum of Mean squares F-value p-value Squares

Species 22 42.00 1.9091 13.86 <2e-16

Residuals 253 34.85 0.1377

Table 7: ANOVA results for ln-transformed mean swimming speeds for all anole species tested.

Figure 29: Mean swimming speed by country. Means are not significantly different from one another (ANOVA: F=0.294, p=0.764).

2.3.1.2 Phylogenetically-corrected analyses

According to the simulation-based phylogenetic ANOVA, semi-aquatic anoles swam significantly faster than non-aquatics (F=17.5 p = 0.001, n.tips=23).

PGLS models yielded concordant results—a model in which mean swimming speed varies as a function of habitat outperformed a model including habitat plus body size as predictors, as well as one including just body size (Table 8).

I did not detect a significant relationship between SVL and mean swimming speed in any of the PGLS linear models, suggesting that size-correction of mean swimming speed is not warranted (Table 9). Furthermore, the four aquatic species had the most positive residuals in this analysis (Figure 30).

Model df AIC BIC loglikelihood

Swimming 4 28.99 32.97 -10.50 speed ~ size+habitat

Swimming 3 37.78 40.91 -15.89 speed ~ size

Swimming 3 26.19 29.32 -10.09 speed ~ habitat

Table 8: Results of a model comparison test conducted on generalized least squares models conducted with a phylogenetic correlation matrix.

Figure 30: Results of a PGLS regression on species size vs. swimming speed. Trendline shows non-significant relationship between the two; blue points are aquatic species.

Coefficients Value Std. Error t-value p-value

(intercept) 2.027 0.5493 3.690 0.0014

Ln(SVL) 0.3083 0.2573 1.199 0.2441

Table 9: Results of a PGLS regression of ln(swimming speed) on ln(SVL) using species means for all anole species tested.

2.3.2 Voluntary diving results

Anole species varied considerably in their propensity to voluntarily dive, as well as in dive duration, with semi-aquatic species generally outperforming non-aquatics (Tables 10, 11, Figures 31-32). In Costa Rica, only A. oxylophus (the aquatic anole found at La Selva) and A. humilis (a leaf-litter dwelling species from La Selva) engaged in voluntary dives during predation simulation trials.

In Colombia, the aquatic species A. maculigula engaged in voluntary dives—seven individuals performed sustained dives lasting from 30 seconds to over ten minutes. Six of these dives

50 occurred in the lab, but we observed and timed one full-length field dive by a male A. maculigula that remained submerged beneath a rock for 10 minutes and 26 seconds before surfacing. Additionally, we recorded one voluntary dive each for A. antioquiae and A. chloris in the lab. Both of these individuals remained underwater for less than two minutes, and both dives occurred following submersion tests (see Chapter 3)—no non-aquatic individuals dove during swimming speed/escape tests in Colombia.

At Los Tuxtlas, we only observed voluntary diving behaviours from A. barkeri, the region’s semi-aquatic species. Anolis barkeri dove both in the lab and in the field following release.

Dive duration means for A. maculigula and A. oxylophus are likely underestimates due to disturbance during experimental trials (for the rebreathing portion of this thesis, Chapter 3, I attempted to measure the oxygen partial pressures of these individuals during natural dives where possible if the animal exhibited rebreathing, which sometimes resulted in the lizard surfacing immediately). Maximum dive times, which are perhaps more representative of the abilities of these species, were also recorded, and aquatic anole species as a group had significantly longer maximum voluntary dive times than non-aquatic anole species (F=12.9, p=0.023; Table 10). I did not observe diving in the two non-anoline taxa I tested (B. vittatus and I. iguana).

Figure 31: Mean voluntary dive durations. Error bars show +/- 1 SEM

Figure 32: Diving frequency of anole species that exhibited voluntary dives.

Figure 33: Max observed voluntary dive durations.

ANOVA results

Df Sum of Mean F-value p-value Squares squares

Habitat 1 441731 441731 12.9 0.0229

Residuals 4 136921 34230

Table 10: ANOVA results for maximum dive durations in aquatic and non-aquatic anoles.

Species Site Sample Ecology Mean Number of Mean Max size weight (g) voluntarily voluntary dive voluntary diving duration dive duration individuals (m:ss)

Anolis humilis La Selva, 28 Non-aquatic (leaf- 1.00 3 3:51 4:12 litter) Costa Rica

A. oxylophus La Selva, 26 Aquatic 3.92 4 5:22 8:26

Costa Rica

A. aquaticus Las Cruces 35 Aquatic 3.57 0 ------

A. antioquiae Tatamá, 1 Non-aquatic 9.5 1 1:20 1:20 Colombia (montane)

A. maculigula Tatamá, 32 Aquatic 15.7 7 5:06 10:26 Colombia

A. chloris Tatamá, 22 Non-aquatic 2.9 1 2:33 2:33 Colombia (arboreal)

A. barkeri Los Tuxtlas, 36 Aquatic 8.40 4 11:53 16:21

Mexico

Table 11: Diving summary statistics

At all locations, lizards that dove voluntarily hid beneath rocks or the hide and frequently closed their eyes during dives. Once in such a location, the lizards remained motionless for between forty seconds and, in the case of one A. barkeri, 16 minutes, 21 seconds.

2.4 Discussion

2.4.1 Convergence in swimming and diving performance in aquatic anoles

Ecomorphology theory leads us to expect convergence in functional performance among taxa that must accomplish kinematically similar tasks to survive, as there will be positive selection on individuals with superior performance (Wainwright 1996). I hypothesized that phylogenetically independent semi-aquatic anoles should convergently evolve superior swimming and diving performance relative to non-aquatic relatives due to the demands of their aquatic habitats (Meyer 1968; Eifler and Eifler 2010b).

The results of my aquatic performance experiments support this prediction. I found a significant difference between the mean swimming speeds of aquatic and non-aquatic anoles, with natatorial anoles besting their dry-land congeners. Aquatic anoles also converge in possessing strong diving abilities, as the three aquatic species whose dives I was able to observe in the lab had significantly longer maximum dive durations relative to the few non-aquatics that dove. The 16 minute 21 second dive I observed in an A. barkeri individual is possibly the longest recorded dive for any member of the genus Anolis (Heatwole and Torres 1963; Heatwole et al. 2009; Boronow et al. 2012).

When considered together with the morphological results discussed in Chapter 1, it appears that semi-aquatic anoles exhibit one-to-one mapping of morphology to function when it comes to swimming performance. Given the morphospace clustering I discovered in Chapter 1, the four semi-aquatic anoles species I tested appear to have converged on a single morphological optimum that enables them to swim faster than non-aquatic species. A previous morphometric study that failed to detect convergence in aquatic anoles was strongly influenced by size differences between certain aquatic anole clades (Leal et al. 2002). Our analyses suggest that such size differences may be of only minor importance to swimming performance in aquatic anoles. Among species, body size was not a significant predictor of swimming speed in anoles, a

54 result that helps to explain the fact that semi-aquatic anoles are not particularly convergent along this axis despite strong convergence in other morphological traits (Chapter 1).

Identifying the ultimate drivers of convergence among semi-aquatic anoles will require additional field study of their natural interactions with the aquatic environment. That said, we suggest that predation pressure may be a particularly important driving force behind this repeated evolutionary pattern (Diego-Rasilla 2003). Tropical streams are home to many diurnal and nocturnal predators that aquatic anoles must evade to survive. Aquatics differ from non-aquatic anoles in their escape behaviours in that they generally dive or swim away from approaching predators, as opposed to running along substrates and hiding, the strategy favoured by most non- aquatic anoles we studied (Boccia pers. obs.). Microhabitat is known to strongly influence escape behaviour in lizards (Schulte et al. 2004), and this is likely the case in aquatic anoles as rocky streams (which many aquatics generally favour ((Birt et al. 2001); Boccia. unpub. obs.) frequently lack above-ground crevices or trees to which an aquatic lizard might flee. Thus, for aquatic anoles, swimming speed is likely a more appropriate measure of escape performance than sprint speed, the standard escape performance measure used for anoles (Losos 1990). An interesting extension of this study would be to compare the swimming performance of aquatic and non-aquatic anoles to their sprint speeds—I predict that aquatics would not show the same performance advantage in sprinting that they enjoy over non-aquatics in swimming speed.

My study of aquatic anole performance also shed light on the aquatic abilities of anoles that are much less closely affiliated with aquatic habitats. I observed voluntary diving in three non- aquatic anole species—A. humilis, A. chloris, and A. antioquiae. To my knowledge, diving has never previously been reported in these species.

2.4.2 Conclusions and future directions

As predicted, semi-aquatic anoles outperform non-aquatic anoles at swimming and diving, important activities in their streamside habitats. During the course of my work, I was only able to test the performance of four phylogenetically independent species of aquatic anoles—for logistical reasons, I was unable to visit Cuba or Haiti to observe the phylogenetically distinct species found on those islands. I hope to add those species to my data set in the future to determine if my swimming performance findings apply generally to all aquatic anole clades.

Another potential avenue for future work would be to investigate additional aspects of performance in aquatic environments. Swimming speed, while important, is only one dimension of overall aquatic performance. It would be worthwhile to also assess swimming efficiency by measuring the magnitude of acceleration and de-acceleration during swimming bouts. Accurate acceleration estimation requires a more sophisticated experiment than I was able to conduct in the field—it would require additional point mass tracking and then a subsequent center-of-mass analysis that would take into consideration the relative masses of the axial column and each element of the appendicular skeleton. Center-of-mass analysis might also enable a future study to more meaningfully assess maximum swimming speeds, as, unlike my methodology, this analysis would not be susceptible to side-to-side noise during swimming.

Another indicator of swimming ability which may potentially separate aquatic and non-aquatic anoles is endurance. Indeed, during trials I frequently noticed that whereas non-aquatic anoles would stop swimming once they reached the edge of the tank/wading pools, semi-aquatics would frequently continue swimming along the sides; similarly, non-aquatic anoles would often stop swimming entirely after a short distance and start floating. I rarely saw such behavior in semi- aquatics, which would generally continue swimming until they were recaptured, or had found a perch.

Rebreathing in semi-aquatic anoles: a novel adaptation for diving? 3.1 Introduction

3.1.1 Background

The colonization of aquatic environments presents a number of challenges to ancestrally terrestrial animal lineages. Obtaining and managing oxygen while engaging in aquatic behaviours is a critical hurdle that must be overcome when adapting to an aquatic lifestyle. Accordingly, many aquatic tetrapods have evolved respiratory adaptations—examples include the heavily modified blow-hole bearing skulls of whales (Oelschläger 2000), tissue oxygen storage in deep-diving mammals (Snyder 1983), and the unusual (for reptiles) oxygen permeability of sea snake epidermis (Graham 1974).

To date, such respiratory adaptations for aquatic living have been reported only rarely in extant lizards (non-ophidian squamates)—Nile monitors (Varanus niloticus) and green iguanas have been reported to have pulmo-circulatory adaptations for diving (Moberly 1968; Wood and Johansen 1974). Although no living lizard species are fully aquatic (i.e., none spend their entire life in water), representatives of at least 11 families have evolved semi-aquatic lifestyles (Bauer and Jackman 2008). The roughly 75 species in this category are restricted to streamside, lakeside, marsh, or shoreline environments, and will enter the water to escape predators or obtain prey (Bauer and Jackman 2008). Although a semi-aquatic lifestyle has arisen many times in lizards, previous authors have suggested that these taxa exhibit little phenotypic convergence (aside from frequent lateral flattening of the tail) and that semi-aquatic lizards generally lack aquatic specialization (Leal et al. 2002; Bauer and Jackman 2008). Conventional wisdom has held this to be the case for semi-aquatic anoles, just as for other lizard groups (Leal et al. 2002; Losos 2009; but see Chapter 1, Chapter 2).

3.1.2 Do aquatic anoles possess respiratory adaptations for diving?

In theory, one might expect semi-aquatic anoles to be likely candidates for the evolution of underwater respiratory adaptations. As discussed in Chapter 2, aquatic anoles frequently dive, and have been documented to remain underwater for up to 16 minutes in order to evade predation (Campbell 1973; Boronow et al. 2012). We might therefore expect to see adaptations

57 akin to those reported in diving monitor lizards or iguanas (e.g., low hemoglobin oxygen binding affinity, high tolerance of acid build up) (Moberly 1968; Wood and Johansen 1974).

In August 2009, my graduate supervisor D.L. Mahler observed an interesting phenomenon in a semi-aquatic anole that suggested a potential respiratory adaptation for diving. During fieldwork in northern Haiti, Dr. Mahler and his colleague Dr. R.E. Glor observed underwater rebreathing behavior in a submerged individual of the semi-aquatic anole Anolis eugenegrahami. While perched underwater on the rocky substrate of clear, shallow stream, this individual repeatedly exhaled and then re-inhaled a large air bubble (Mahler unpub. obs.). This bubble was never released from the snout of the lizard during respiration, such that exhaled air was recovered again via inhalation rather than detaching and floating to the surface.

This observation in A. eugenegrahami suggests a potential adaptive function—however, key questions remained unanswered:

1) Is the activity Mahler and Glor observed in Haiti truly involved in respiration? Is the air in this rebreathed bubble involved in the oxygenation of blood, and is this behaviour employed with any regularity during diving?

2) Does this behaviour arise repeatedly in aquatic specialist anoles? All anoles can dive if they need to (e.g., (Heatwole et al. 2009)), but if this behavior is truly a specialized adaptation, we only expect it to be well-developed in diving specialists. Thus, if we observe rebreathing in semi- aquatics, but not other anoles, this represents strong comparative evidence for adaptation.

3.1.3 Hypotheses and predictions

I seek to address the above questions for the final chapter of my thesis. I thus test two hypotheses:

1) Air bubble(s) that are exhaled and re-inspired by submerged anoles play a role in respiration. Specifically, I predict that the air bubbles produced by these species should gradually decrease in oxygen content through time, showing evidence of recirculation into the lungs.

2) Rebreathing is a novel behaviour that is related to diving and has convergently evolved in multiple lineages of semi-aquatic Anolis lizards.

To test these hypotheses, I examined 4 semi-aquatic and 20 non-aquatic anole species.

3.2 Methods

3.2.1 Testing for rebreathing during voluntary dives by anoles

Along with two research assistants, I travelled to Costa Rica, which is home to two phylogenetically distinct aquatic anole lineages, A. oxylophus and A. aquaticus, as well as Colombia and Mexico, each of which also support at least one distinct aquatic lineage (Gamble et al. 2014).

As described in Chapter 2, I opportunistically observed voluntary dives performed by lizards during the swimming speed escape trials I conducted. I placed each lizard into an aquarium filled with water to a depth of 30 cm or a wading pool with a water depth of approximately 10 cm. Both arenas also contained several rocks and a shaded underwater “hide” which mimicked a refuge inaccessible to terrestrial predators; see Chapter 2 for more details regarding the swimming speed and diving arena. If a lizard dove voluntarily following simulated predation attempts, I timed the dive, noted the presence of any rebreathing behaviours, and if these were present, attempted to insert an oxygen probe (described below) into any air bubble produced.

However, testing for rebreathing in this manner was not a viable option for most individuals, as voluntary dives were rare among all aquatic (and non-aquatic) species tested. Additionally, voluntarily diving lizards generally managed to wedge themselves into difficult to access areas of the arena (e.g., under rocks). This was true for individuals from all sites, with the exception of one particularly cooperative A. maculigula in Colombia. Though diving anole individuals appeared to be in a resting state during rebreathing dives (they remained essentially motionless for the duration of each dive) they were still sensitive to physical disturbances caused by the probe; hence it was difficult to insert the oxygen probe into the diving lizard’s air bubbles without startling the lizard and causing it to flee the probe and swim to the surface. I therefore conducted experimental submersions on all individuals that we captured to test for and quantify rebreathing in a controlled setting; in addition to our anole subjects, this included three juvenile iguanas (Iguana iguana) and four juvenile basilisks (Basiliscus vittatus) that we captured in Mexico.

3.2.2 Lizard submersion experiments

I experimentally submerged each lizard we tested (both aquatic and non-aquatic species) for at least 30 seconds to check for rebreathing. Lizards were gently grasped around their pelvic girdle and slowly lowered into the water. Aquatic lizards usually gripped the experimenter’s hand during this procedure, while non-aquatic anoles would sometimes let go and float upwards to the surface if not gently held in place. Lizards restrained in this manner were held loosely during submersion trials, such that they could easily free themselves and swim to the surface at any point.

If lizards did not release themselves from the experimenter’s hand and float upwards, we continued submersion until the lizard freed itself and swam to the surface. To quantify underwater behaviours during submersion, I recorded each trial using a submerged GoPro Hero 4 Silver video camera in a waterproof case. In addition, the presence or absence of rebreathing behaviours was visually scored during trials.

While gently keeping the rebreathing anole submerged, I inserted the end of a bare fibre oxygen probe (PyroScience FireSting GO2) into the air bubbles sequentially inhaled and exhaled by the anole. The FireSting oxygen probe logs the partial pressure of oxygen (in hectopascals, hPa) in the air or water surrounding the tip once every second. After a few trials, our particular sensor ceased to record oxygen partial pressures in water; because we were only interested in the oxygen content of respired air, this did not affect our experiment.

Once a submerged, rebreathing anole moved to free itself from the experimenter’s hand (lizards were generally calm and motionless until this point) we released the lizard and allowed it to swim to the surface. Submersion trials lasted from 30 seconds to up to eighteen minutes. Individuals that were observed to rebreathe were tested 1-5 times depending on the quality of the data obtained. If tested multiple times, rebreathing anoles were given 15-30 minutes to recuperate between rebreathing trials. Following the completion of all experiments and measurements, we released each lizard at the site of its capture.

D.L. Mahler conducted parallel submersion trials in Jamaica during the summer of 2018. The following species were tested during these trials: A. valencienni, A. garmani, A. sagrei, A. lineatopus, A. reconditus, and A. opalinus.

I also conducted experiments to test whether the oxygen pressure change patterns I recorded could have been an artefact of the oxygen sensor, or simply due to the repeated exposure of a small air bubble to a water medium. I filled a syringe with room air, submerged it in water, and then repeatedly extruded an air bubble from the tip of the syringe for five minutes. I used the FireSting oxygen probe to measure the oxygen partial pressure of the air bubble during this control trial; this procedure was conducted five times.

3.2.3 Analysis of rebreathing videos

Though I recorded whether or not I observed rebreathing during experimental submersion trials, I also consulted the GoPro videos I filmed of each trial when determining if a lizard had performed rebreathing, and to what extent they exhibited the phenomenon. Diving anoles of multiple species (aquatic and non-aquatic) would sometimes re-inspire single bubbles during the course of experimental submersion—frequently this would happen just after initial submersion. However, in many cases, this rebreathing phenomenon would not be sustained after 1 or a small number of bubble intakes, whereas other individuals would exhibit rebreathing over the longer periods of time, sometimes the entire course of the dive. I therefore developed two different sets of criteria for rebreathing and scored each video accordingly. I noted if individuals performed only single bubble intake, or up to four exhalations and inhalations (“incidental rebreathing”) or a series of at least 5 exhalations and inhalations during the course of a trial (“sustained rebreathing”); individuals that performed this latter behaviour were coded as being able to perform both.

Once I had determined the appropriate rebreathing scores for each individual, I attempted to determine if the occurrence of general and sustained rebreathing were correlated on the Anolis phylogeny with the occurrence of an aquatic lifestyle. I used the fitPagel function in phytools (Revell 2012) to conduct Pagel’s test for correlated evolution in binary traits using the modified version of the Gamble et al. (2014) tree described in Chapter 1. Pagel’s test compares the fit of two different models to user data: 1) a model in which the two traits have evolved independently, and 2) a model in which the traits’ evolution is dependent upon each other. In the independent model, the probability of any combination of states is just the product of the probabilities of those states, whereas the dependent model uses a 4x4 matrix of transition probabilities—i.e., the model in effect considers that there are 4 possible 2-state combinations and attempts to estimate

61 transition parameters between them. These models are compared via AIC and a likelihood-ratio test.

3.3 Results

3.3.1 Rebreathing—general trends

I observed rebreathing in all four aquatic anole species that I tested (see Appendix 4.5 for a link to a video of an A. aquaticus rebreathing). Anolis maculigula, A. aquaticus, and A. barkeri all rebreathed during experimental submersion. A. oxylophus only rebreathed during voluntary dives. All aquatic species were observed to perform sustained rebreathing a minimum of three times, though the prevalence of this type of rebreathing varied between species—see Table 11.

Interestingly, several non-aquatic anoles were also observed to exhale and inhale bubbles underwater. The majority of these individuals only performed single intakes (falling under the incidental rebreathing category)—one non-aquatic anole from Colombia and several non- aquatics from Mexico and Jamaica exhibited this behaviour (see Table 12). However, three non- aquatic individuals from Colombia (one each of A. chloris, A. frenatus, and A. limon) were observed to rebreathe for a sustained duration.

When non-aquatic species exhibited either type of rebreathing, the proportion of individuals of that species that performed the behaviour was generally lower than the proportions observed in aquatic anoles (Figures 34, 35, Table 12). The only exceptions were species of which we sampled very few individuals, precluding meaningful estimation of rebreathing frequency.

Only six species (three aquatic, three non-aquatic) performed voluntary dives during the course of my experiments. I only observed rebreathing in the aquatic species. All A. oxylophus rebreathed during voluntary dives; two of four diving A. barkeri rebreathed; and three of seven diving A. maculigula rebreathed (see Figures 34 and 35). Rebreathing during voluntary submersion proceeded in the same manner observed during manual submersion—see section 3.3.2.

Species Site Sample Ecology Number of Number of size rebreathing rebreathing individuals individuals (general) (sustained) A. antioquiae Tatamá, Colombia 1 Non-aquatic 0 0 (montane cloud forest)

A. antonii Tatamá, Colombia 36 Non-aquatic 0 0 (low bushes and shrubs) A. aquaticus Las Cruces, Costa 35 Aquatic 22 22 Rica A. barkeri Los Tuxtlas, 36 Aquatic 31 22 Mexico A. biporcatus Costa Rica (both 2 Non-aquatic (arboreal) 0 0 sites) A. chloris Tatamá, Colombia 22 Non-aquatic (arboreal) 2 1

A. duellmani Los Tuxtlas, 1 Non-aquatic (terrestrial) 0 0 Mexico A. frenatus Tatamá, Colombia 1 Non-aquatic (arboreal) 1 1

A. garmani Jamaica 3 Non-aquatic 1 0 (crown-giant) A. humilis La Selva, Costa 28 Non-aquatic (leaf litter) 0 0 Rica A. insignis Las Cruces, Costa 1 Non-aquatic (arboreal) 0 0 Rica A. lemurinus La Selva, Costa 23 Non-aquatic (trunk) 0 0 Rica A. limifrons La Selva, Costa 24 Non-aquatic (shrubs) 0 0 Rica A. limon Tatamá, Colombia 3 Non-aquatic 1 1 (montane cloud forest) A. lineatopus Jamaica 6 Non-aquatic 2 0 (trunk-ground) A. maculigula Tatamá, Colombia 32 Aquatic 31 16

A. megalopithecus Tatamá, Colombia 1 Non-aquatic (montane 0 0 forest) A. opalinus Jamaica 2 Non-aquatic (trunk- 0 0 ground) A. oxylophus La Selva, Costa 26 Aquatic 4 4 Rica A. polylepis Las Cruces, Costa 22 Non-aquatic (arboreal) 0 0 Rica A. princeps Tatamá, Colombia 2 Non-aquatic 1 0 (arboreal) A. purpurescens Tatamá, Colombia 1 Non-aquatic 0 0 (arboreal) A. reconditus Jamaica 2 Non-aquatic (trunk) 0 0

A. rodriguezi Jamaica 1 Non-aquatic (arboreal) 0 0

A. sagrei Jamaica 2 Non-aquatic (trunk- 0 0 ground) A. sericeus Los Tuxtlas, 23 Non-aquatic 1 0 Mexico (grass) A. uniformis Los Tuxtlas, 26 Non-aquatic 5 0 Mexico (leaf-litter) A. valencienni Jamaica 4 Non-aquatic 0 0 (twig) A. ventrimaculatus Tatamá, Colombia 4 Non-aquatic (montane 0 0 cloud forest) Basiliscus vittatus Los Tuxtlas, 5 Aquatic 2 0 Mexico Iguana iguana Los Tuxtlas, 3 Non-aquatic (terrestrial) 0 0 Mexico

Table 12: Rebreathing summary statistics

Figure 34: Proportion of individuals tested which re-inspired at least one air bubble during a submersion trial. Results are sorted by habitat. The alpha level of bars indicates sample size—translucent bars indicate that we sampled fewer than five adult individuals of that species. Error bars show +/- 1 SE of the proportion for species with more than 1 sample.

Figure 35: Proportion of individuals tested which exhibited sustained rebreathing. Results are sorted by habitat. The alpha level of bars indicates sample size—translucent bars

64 indicate that we sampled fewer than five adult individuals of that species. Error bars show +/- 1 SE of the proportion for species with more than 1 sample.

3.3.1.1 Results of correlated evolution tests

The fitPagel analysis I conducted found that a model in which sustained rebreathing and aquatic habitat affiliation evolved in a correlated manner was a better fit to the data then a model of trait evolution in which these traits evolved independently (p = 0.0073; see Table 13 for transition rate estimates and likelihood scores).

The correlated evolution model for habitat affiliation and incidental rebreathing, conversely, did not significantly outperform the independent model (p = 0.089; Table 14).

Figure 36: Distribution of sustained rebreathing and aquatic habitat on a phylogeny derived from Gamble et al. (2014).

Dependent model transition rate matrix for habitat and sustained rebreathing estimated by fitPagel

Aquatic | no Aquatic | Non-aquatic | no Non-aquatic | sustained sustained sustained sustained rebreathing rebreathing rebreathing rebreathing

Aquatic | no -2.904 2.828 0.0759 0.000 sustained rebreathing

Aquatic | 0.000 -0.712 0.000 0.712 sustained rebreathing

Non-aquatic | no 0.000 0.000 -0.384 0.384 sustained rebreathing

Non-aquatic | 0.000 0.949 2.942 -3.891 sustained rebreathing

Model fitting results

Log-likelihood AIC

Independent model -28.1 64.1

Dependent model -21.1 58.2

Likelihood ratio: 13.99; p-value = 0.0073

Figure 37: Distribution of incidental rebreathing and aquatic habitat on a phylogeny derived from Gamble et al. (2014).

Independent model transition rate matrix for habitat and incidental rebreathing estimated by fitPagel

Aquatic | no Aquatic | Non-aquatic | no Non-aquatic | incidental incidental incidental incidental rebreathing rebreathing rebreathing rebreathing

Aquatic | no -0.133 0.033 0.101 0.000 incidental rebreathing

Aquatic | 0.050 -0.151 0.000 0.101 incidental rebreathing

Non-aquatic | no 0.016 0.000 -0.048 0.033 incidental rebreathing

Non-aquatic | 0.000 0.016 0.050 -0.066 incidental rebreathing

Model fitting results

Log-likelihood AIC

Independent model -31.9 71.7

Dependent model -27.8. 71.6

Likelihood ratio: 8.07; p-value = 0.089

3.3.2 Description of rebreathing behaviours observed in aquatic and non- aquatic anoles

Rebreathing usually proceeded in the following fashion: after submersion (voluntary or experimental), the lizard then would begin to exhale, but not release, air bubbles. The bubbles produced generally appeared to remain connected to the air supply in the nares and were attached to the lizard’s head scales (either as a continuous, large bubble resting over the nasals, prefrontals, and frontals, or twin small bubbles exhaled along the maxillae). Rebreathing bubbles were sequentially exhaled and then re-inhaled by the lizard. Lizards would sometimes release air bubbles during the course of the dive; this would most commonly happen before the start of rebreathing—lizards would exhale a small number of bubbles before a stable rebreathing bubble was maintained. However, rebreathing bubbles would sometimes detach from the submerged lizard’s head and rise to the surface; these were usually immediately replaced by another rebreathed bubble. The lizard’s thoracic cavity also contracted and expanded during rebreathing, as during normal respiration. The behaviours discussed above were observed in all rebreathing A. aquaticus and A. oxylophus.

Anolis barkeri and A. maculigula exhibited similar rebreathing patterns—some individuals of both species performed the large single bubble behaviour. However, there were some behavioural differences. Anolis maculigula from Colombia would frequently exhale and take in bubbles after a burst of exhalation. Additionally, large individuals of A. maculigula and A. barkeri would frequently generate separated medium sized bubbles that remained attached close to or over the orbits (most individuals of both species), or tiny bubbles that were extruded a small distance above the nares (some A. maculigula). A few individuals generated small flat air bubbles that rested over the center of the nasals (A. maculigula). Bubbles extruded over the eyes or just above the lip of the nares were the most difficult to quantify with the probe, as lizards were particularly sensitive to placement of the probe near these areas.

Non-aquatic anole rebreathing behaviours were generally limited to small bubbles directly over the nares or separated bubbles along the maxillae that were exhaled and pulled in once or twice at the start of a submersion trial. However, as mentioned previously, three non-aquatics performed sustained rebreathing. The A. limon and A. chloris that rebreathed continuously for a short period did so by exhaling and inhaling separated bubbles vertically over the nares. Conversely, the A. frenatus that performed sustained rebreathed used the rebreathing style wherein a single large bubble is exhaled over the center of the head.

3.3.3 Oxygen probe results

I was able to obtain reliable oxygen partial pressure reads from each aquatic species that rebreathed during experimental submersion (i.e., all species except A. oxylophus, which would only rebreathe when diving voluntarily).

The oxygen pressure values I recorded gradually decreased in a linear fashion during trials. This supports my hypothesis that the air contained within rebreathing bubbles is used in respiration, as the gradual decline in oxygen values corresponds to the predicted removal of oxygen by the anoles’ lung tissues. Representative oxygen pressure/time graphs obtained during these trials for three aquatic anole species are shown in Figure 38. All trials in which we successfully inserted the probe into the air bubble at different intervals during submersion appeared visually similar to the graphs presented. In all of these, the partial pressure of oxygen within the rebreathing bubble was initially similar to that of ambient air (between 160 and 200 hPa, depending on the altitude) and decreased linearly over time to a value between 91 and 53 hPa.

Note that I did obtain some probe data from one voluntary A. oxylophus that may be comparable to the data obtained for other species during manual submersion trials. During this trial, I noted two oxygen pressure readings that exceeded the oxygen partial pressure the probe had been recording in water but were lower than the oxygen content of lab air. However, more observations would be necessary to verify that these readings were not merely noise.

I was unable to obtain oxygen bubble readings from any of the non-aquatic rebreathers as these lizards usually rebreathed only briefly, and individuals that had previously rebreathed were not observed to do so again if tested a second time with this purpose in mind.

The oxygen reads obtained from the abiotic bubble extrusion simulations I conducted using a syringe did not decrease over a five-minute time span, indicating that probe error or other processes were not responsible for the observed changes in oxygen content.

Figure 38: Plots of partial pressures of oxygen measured in rebreathing bubbles exhaled and reinhaled by a diving aquatic anole. Red line shows mean room air; blue line depicts a regression line of oxygen partial pressure against time, for the period in which the probe was inserted into the rebreathing bubble of a submerged lizard. a) shows a rebreathing trace for an A. aquaticus individual (R2 = 0.98, p < 0.001); b) shows a trace for an A. maculigula individual (R2 = 0.88, p < 0.001); and c) shows a trace for an A. barkeri individual (R2 = 0.93, p < 0.001).

3.4 Discussion

To my knowledge, the observations and experiments reported here constitute the first formal documentation of underwater rebreathing behavior in a reptile. True rebreathing may also, to my knowledge, never have been observed previously in vertebrates. Some aquatic mammals re- inhale their own exhaled air bubbles in a behaviour called “aquatic sniffing” but this is thought to serve a olfactory sensory function (Catania 2006). It is possible that rebreathing occurs in other diving lizard lineages (which are relatively numerous—see (Hare and Miller 2009))—I observed single bubble inhalations during submersion tests of two juvenile Basiliscus vittatus in Mexico. Below I discuss what we have learned thus far about the function, origins, and utility of this fascinating behaviour.

3.4.1 Are rebreathing bubbles involved in respiration?

The results of my oxygen probe measurements suggest that rebreathing bubbles are involved in respiration, as the oxygen concentrations of sequentially exhaled and re-inhaled bubbles dropped over time. This is what we would expect to see if the rebreathing bubble was continuous with or sequentially merging with the air supply contained in the anole’s lungs if this total volume of air was gradually being depleted of oxygen over the course of the submersion event. If the bubbles were not involved in respiration and were simply trapped against the anoles’ scales, we would not expect to see oxygen pressure declines.

3.4.2 Is rebreathing adaptive for diving?

The discovery of regular, deliberate rebreathing behavior in aquatic anoles raises the obvious question: is this behavior adaptive? And if the answer to this question is yes, the next question is: how? I propose that sustained rebreathing in aquatic anoles is most likely adaptive for sustained diving and suggest that the function of this technique may be to make relatively large volumes of unutilized dead-space air available for respiration.

It could be argued that rebreathing may not be not be adaptive and might simply be an unusual behaviour that sometimes occurs during anole submersion. If this were the case, we would not expect to observe the behaviour in multiple aquatic anole lineages and we would not expect this behaviour to correlate with the use of semi-aquatic habitats across the anole phylogeny. My observations and experiments reveal such phylogenetic patterns in anoles however. Further, the

72 rebreathing phenotype is generally more consistent and better developed in aquatic anoles relative to non-aquatics. While numerous anole species were observed to exhibit incidental rebreathing behaviours (such as single bubble re-inspirations), all aquatic anole species examined exhibited sustained, regular rebreathing, often for the duration of a dive. Aquatic anoles generally exhibited these stereotyped behaviours with greater frequency than those non-aquatics that rebreathed.

If rebreathing permits aquatic anoles to remain underwater longer, or to perform better while submerged, its adaptive benefits to these species are quite clear. Diving aquatics could remain underwater for longer time periods to avoid predation without needing to surface and risk exposing their locations. Further, longer dive durations would also be advantageous for the species which forage underwater, as they could forage for longer time periods without interruptions for surfacing.

Our observations and results suggest that rebreathing is likely of adaptive value to diving anoles. The results of the binary trait evolution analysis I conducted support this, as the greatest transition rate estimated by fitPagel for the sustained rebreathing model was from “aquatic, no sustained rebreathing” to “aquatic, sustained rebreathing.”

The transition matrix for the sustained rebreathing habitat-dependent model also does include a possible exaptive, rather than adaptive, pathway to the phenotype (Gould and Vrba 1982), in which rebreathing evolves before aquatic habitat colonization—see Tables 13 and 14. However, the transition rates for this pathway were much lower than that of the adaptive pathway.

It is therefore possible that rebreathing evolved via multiple pathways across the anole tree, both adaptive and exaptive. Sustained rebreathing was strongly associated with semi-aquatic habitat affiliation but was not restricted to semi-aquatic anoles—a handful of non-aquatics in the Dactyloa clade also occasionally demonstrated this ability (Figure 36). It is the observation of rebreathing in these species that likely lends credence to the possibility of an exaptive pathway, with one possible history being an early origin of sustained rebreathing in the Dactyloa clade, followed by repeated loss in most (but not all) non-aquatic lineages. Incidental rebreathing was even more broadly phylogenetically distributed (Figure 37). We did not find any evidence in

73 these data, however, that incidental rebreathing was an evolutionary substrate for the aquatic lifestyle (Table 13).

3.4.3 What physiological benefits might anoles gain from rebreathing?

While the ecological benefits of underwater rebreathing are easy to imagine, understanding the physiological mechanisms by which underwater re-inspiration of air contributes to respiration is less straightforward. Here I discuss and compare several possible physiological functions of underwater rebreathing in anoles.

One possible function of rebreathing using a bubble apparatus is collection of additional oxygen from the environment. Depending on the dissolved oxygen concentration of the surrounding water (i.e., if the stream was well-aerated, and the dissolved oxygen concentration of the water exceeded that of the rebreathed air bubble), it is theoretically possible that anoles could replenish a small amount of oxygen through passive diffusion of O2 into the bubble while it was extruded from the lizard’s nostril. Such use of air bubbles has been previously described from aquatic insects and arachnids, which require minute amounts of oxygen and are able to rebreathe from an air bubble trapped underwater almost indefinitely (Flynn and Bush 2008; Seymour and Matthews 2013). The amount of oxygen regained through rebreathing can be modelled using Fick’s law. However, oxygen diffusion would likely occur only at extremely low bubble oxygen partial pressures or unrealistically high dissolved oxygen concentrations (Flynn and Bush 2008). As such, this mechanism seems unlikely to explain sustained rebreathing in anoles.

Rebreathing could also increase dive times by allowing clearance of CO2—submerged vertebrates generally build up CO2 during prolonged submersion, which eventually forces the diving animal to take a breath (with, presumably, a negative marginal impact on survival)

(Panneton et al. 2010). CO2 is usually at lower concentrations in the water column relative to other gases (Flynn and Bush 2008) and thus might diffuse efficiently out of a bubble, potentially allowing the diving anole to avoid problems associated with CO2 accumulation and extend its aerobic dive limit (Panneton et al. 2010). Measuring CO2 concentrations in conjunction with O2 concentrations within the rebreathed air bubble would be one means of testing this hypothesis in future studies. Additionally, it is possible that rebreathing is a compromise between oxygen

retention and CO2 clearance. Anoles frequently exhale air bubbles during diving bouts, which also assists with CO2 clearance—however, by releasing the bubble, the anole is contemporaneously losing oxygen as well; rebreathing could theoretically bridge this trade-off by allowing for CO2 clearance while not depriving the diving anole of potentially necessary oxygen.

However, perhaps the most likely explanation for rebreathing relates to diving anoles’ respiratory dead space. Pharyngeal, nasal, and buccal tissues do not allow for gas exchange and the reptilian glottis usually closes off the airway between the lungs and the voluminous buccal and nasal passages, which would prevent oxygen in these space from being involved in respiration during diving. Rebreathing could thus allow the diving lizard to make use of this additional air volume—the glottis opens during inspiration and exhalation, and rebreathing should cause (relatively) oxygen depleted air from the lungs to be mixed with (relatively) oxygen rich air contained in buccal and nasal dead space, perhaps ensuring higher oxygen partial pressures for a longer duration within the lungs and allowing the lizard to extract more oxygen from a single breath of air (by the same mechanism, the respiratory CO2 load could be distributed throughout a larger volume of air).

Along the same vein, it is also possible that rebreathing might allow diving anoles to reincorporate some of the oxygen trapped on their scales at the start of the dive. During the experimental submersion trials discussed above, I frequently noted that anoles of all species had very small volumes of air trapped against their scales. Exhaling a gas bubble that merges briefly with these air pockets could allow the anole to incorporate this additional oxygen into its air supply.

3.4.4 Conclusions and future directions

Rebreathing thus appears to be a convergent feature of at least five aquatic anole lineages (including A. eugenegrahami, which was not part of this study)—suggesting that aquatic anoles may be more convergent than they would appear at first glance. It seems likely that many anoles may possess the capability to exhibit rudimentary rebreathing behaviors, but that aquatic anoles have repeatedly evolved the ability to rebreathe in a regular, stereotyped manner. The phylogenetic distribution of incidental and sustained rebreathing suggests a possible exaptive origin of the specialized rebreathing phenotype observed so frequently in aquatic anoles.

Rebreathing in anoles warrants additional physiological study. Our data are not able to strongly support a particular hypothesis for the functional significance of rebreathing to diving anoles, although we think dead-space mixing or CO2 clearance are the most likely respiratory mechanisms. However, its potential benefits could be tested with more rigorous experimentation carried out in a laboratory, instead of field conditions. Heart rate measurements and blood acid and base analysis could shed more light on aquatic anole behaviour during diving (Wood and Johansen 1974). Further, venous and arterial blood samples from diving and non-aquatic anoles could be compared following fixed-time manual submersion to determine if rebreathing elevates oxygen content in the blood stream, or if aquatic anoles manage lactic acid accumulation during diving better than non-aquatic anoles. We were unable to measure the concentration of gases other than oxygen in the rebreathing bubbles and were also unable to measure the lung oxygen pressures of submerged non-aquatic anoles, as they did not rebreathe. This limitation could be addressed in future experiments—the air contained within the lungs of non-aquatic and aquatic anoles submerged for the same amount of time could be extracted and analyzed, allowing us to compare O2 and CO2 concentrations. Such data (in addition to O2 consumption data derived during normal, non-diving activity) would permit us to determine whether aquatic anoles are able to extract additional oxygen from dissolved O2 or are more efficient at clearing CO2.

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Appendices 4.1 Descriptions of measurements taken on museum specimens

Snout-vent length Head length Head width Head height Lower jaw length Outlever length Jugal to symphysis dist. Femur length Tibia length Metatarsal length 4th toe length 4th toe lamellae width Humerus length Radius length 4th finger length 4th finger lamellae width Pelvic height Pelvic width

Table A1: List of ecologically relevant traits measured by D.L. Mahler and J. Boyko. See Mahler 2010 and Mahler 2013.

Trait Measurement details Measured length from base of tail to dorsal surface at ¼ of SVL Tail height at ¼ of SVL along tail Measured cross-section of tail at Tail width at ¼ of SVL ¼ of SVL along tail Measured length from base of tail to dorsal surface at ½ of SVL Tail height at ½ of SVL along tail Measured cross-section of tail at Tail width at ½ of SVL ½of SVL along tail Measured length from base of tail to dorsal surface at ¼ of SVL Tail height at ¾ of SVL along tail

Measured cross-section of tail at Tail width at ¾ of SVL ¼ of SVL along tail Measured length from the posterior boundary of the ear to the anterior boundary of the Neck length pectoral girdle Measured cross-section from above right forearm to above left Pectoral width forearm, across pectoral girdle Measured distance from sternum Pectoral height to top of pectoral girdle. Measured length between the Torso length right forearm and right hindleg. Measured distance at the narrowest point between the Min. inter-ocular width orbits. Measured distance between the Inter narial width two nares.

Table A2: List of traits relevant to aquatic habitats measured by C. Boccia

4.2 Reasons for unusual convergence results returned by the convnum function

The reason for the additional convergence events is likely two-fold—first, there is very likely a topological error in the Gamble et al. (2014) phylogeny. In this tree, A. poecilopus is sister to A. trachyderma rather than nesting within the A. lionotus/A. oxylophus clade. This unexpected placement is likely due to gene tree – species tree discordance in this mitochondrial DNA phylogeny (Mahler pers. comm.). Thus A. poecilopus is free in our analyses to “converge” with what we think are likely its true sister taxa. The second reason that this additional convergence finding is possible is that many phylogenetic methods require fully resolved (i.e., bifurcating) phylogenetic trees, so I was forced to use a tree with random bifurcations. Doing so could conceivably permit the convnum function to detect a higher number of convergence events. In both cases, these issues concern just one out of six aquatic anole clades, and are not expected to qualitatively affect our findings.

4.3 Swimming speed—nonsignificant putative covariates

Figure A1: ln(Mean Swimming Speed) vs. ln(Water Temperature in degrees Celsius). F- statistic: 0.567 on 1 and 274 DF, p-value: 0.452

Figure A2: ln(Mean swimming speed) vs. ln(Water temperature in degrees Celsius). F- statistic: 0.262 on 1 and 274 DF, p-value: 0.609.

Figure A3: ln(Mean Swimming Speed) by lizard sex. Df = 246, t=-0.52658, p = 0.599

4.4 Results of Tukey honest significant differences test on anole swimming speed data

diff lwr upr p adj aquaticus-antonii 0.752 0.358 1.146 9.07E-08 barkeri-antonii 0.995 0.617 1.373 1.48E-13 chloris-antonii 0.093 -0.309 0.496 0.999 humilis-antonii 0.065 -0.313 0.443 0.999 lemurinus-antonii 0.293 -0.101 0.687 0.375 limifrons-antonii 0.395 0.008 0.782 0.0405 maculigula-antonii 0.934 0.515 1.353 1.80E-10 oxylophus-antonii 0.884 0.476 1.291 6.28E-10 polylepis-antonii 0.089 -0.33 0.508 0.999 sericeus-antonii 0.034 -0.369 0.437 1 uniformis-antonii 0.034 -0.35 0.418 1 barkeri-aquaticus 0.242 -0.108 0.593 0.491 chloris-aquaticus -0.659 -1.036 -0.282 1.57E-06 humilis-aquaticus -0.687 -1.038 -0.337 3.49E-08 lemurinus-aquaticus -0.459 -0.827 -0.091 0.00298 limifrons-aquaticus -0.357 -0.717 0.003 0.0543

89 maculigula-aquaticus 0.182 -0.212 0.576 0.933 oxylophus-aquaticus 0.131 -0.251 0.514 0.992 polylepis-aquaticus -0.663 -1.057 -0.269 4.70E-06 sericeus-aquaticus -0.718 -1.095 -0.341 9.72E-08 uniformis-aquaticus -0.718 -1.075 -0.361 1.29E-08 chloris-barkeri -0.902 -1.262 -0.541 7.19E-13 humilis-barkeri -0.93 -1.262 -0.597 1.10E-13 lemurinus-barkeri -0.702 -1.052 -0.351 1.60E-08 limifrons-barkeri -0.6 -0.942 -0.257 1.48E-06 maculigula-barkeri -0.061 -0.439 0.317 0.999 oxylophus-barkeri -0.111 -0.476 0.255 0.997 polylepis-barkeri -0.906 -1.284 -0.528 5.95E-12 sericeus-barkeri -0.961 -1.321 -0.601 1.29E-13 uniformis-barkeri -0.961 -1.299 -0.622 1.12E-13 humilis-chloris -0.028 -0.388 0.332 1 lemurinus-chloris 0.2 -0.177 0.577 0.843 limifrons-chloris 0.302 -0.068 0.671 0.234 maculigula-chloris 0.841 0.438 1.243 3.05E-09 oxylophus-chloris 0.791 0.4 1.182 1.10E-08 polylepis-chloris -0.004 -0.407 0.398 1 sericeus-chloris -0.059 -0.445 0.327 0.999 uniformis-chloris -0.059 -0.425 0.307 0.999 lemurinus-humilis 0.228 -0.123 0.578 0.59 limifrons-humilis 0.33 -0.012 0.672 0.0705 maculigula-humilis 0.869 0.491 1.247 4.45E-11 oxylophus-humilis 0.819 0.453 1.184 1.50E-10 polylepis-humilis 0.024 -0.354 0.402 1 sericeus-humilis -0.031 -0.391 0.329 1 uniformis-humilis -0.031 -0.37 0.308 1 limifrons-lemurinus 0.102 -0.258 0.462 0.998 maculigula-lemurinus 0.641 0.247 1.035 1.19E-05 oxylophus-lemurinus 0.591 0.209 0.973 4.32E-05 polylepis-lemurinus -0.204 -0.598 0.19 0.863 sericeus-lemurinus -0.259 -0.636 0.118 0.503 uniformis-lemurinus -0.259 -0.616 0.098 0.413 maculigula-limifrons 0.539 0.152 0.926 0.00042 oxylophus-limifrons 0.489 0.114 0.863 0.00144 polylepis-limifrons -0.306 -0.693 0.081 0.279 sericeus-limifrons -0.361 -0.731 0.008 0.0622 uniformis-limifrons -0.361 -0.71 -0.012 0.035 oxylophus-maculigula -0.05 -0.458 0.357 1 polylepis-maculigula -0.845 -1.264 -0.426 1.16E-08 sericeus-maculigula -0.9 -1.303 -0.497 1.65E-10 uniformis-maculigula -0.9 -1.284 -0.516 1.71E-11 polylepis-oxylophus -0.795 -1.202 -0.387 4.19E-08 sericeus-oxylophus -0.85 -1.241 -0.459 5.75E-10 uniformis-oxylophus -0.85 -1.221 -0.478 5.70E-11

90 sericeus-polylepis -0.055 -0.458 0.348 0.999 uniformis-polylepis -0.055 -0.439 0.329 0.999 uniformis-sericeus 0 -0.366 0.366 1

Table A3: TukeyHSD results from complete data set swimming speed analysis. Significant results are shown in bold-face type.

4.5 Swimming and rebreathing videos

4.5.1 Swimming speed demonstration

A video showing a swimming speed test of an A. maculigula individual can be found in the supplement to this thesis—see file “Boccia_Christopher_K_201811_MSc_video1.mp4”.

4.5.2 Rebreathing demonstration

A video of an A. aquaticus performing sustained rebreathing can be found in the supplement to this thesis—see file “Boccia_Christopher_K_201811_MSc_video2.mp4”.

4.6 Male and female species mean morphology data sets

4.6.1 Male data set

Please see the following Excel file, contained in the supplement to this thesis—see file “Boccia_Christopher_K_201811_MSc_maledatatable.csv”.

4.6.2 Female data set

Please see the following Excel file, contained in the in the supplement to this thesis—see file “Boccia_Christopher_K_201811_MSc_femaledatatable.csv”.

4.7 Museum specimens consulted for this project

Please see the following Excel file, contained in the in the supplement to this thesis—see file “Boccia_Christopher_K_201811_MSc_specimensconsultedlist.xlsx”.