Conservation Genetics and the Ctenosaura Palearis Clade

Home , Brachylophus, Ctenosaura, Ctenosaura bakeri, Ctenosaura melanosterna, Ctenosaura palearis, Ctenosaura pectinata

University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange

Doctoral Dissertations Graduate School

8-2010

Conservation genetics and the Ctenosaura palearis clade

Follow this and additional works at: https://trace.tennessee.edu/utk_graddiss

Part of the Ecology and Evolutionary Biology Commons

Recommended Citation Pasachnik, Stesha Ann, "Conservation genetics and the Ctenosaura palearis clade. " PhD diss., University of Tennessee, 2010. https://trace.tennessee.edu/utk_graddiss/840

This Dissertation is brought to you for free and open access by the Graduate School at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Doctoral Dissertations by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. To the Graduate Council:

I am submitting herewith a dissertation written by Stesha Ann Pasachnik entitled "Conservation genetics and the Ctenosaura palearis clade." I have examined the final electronic copy of this dissertation for form and content and recommend that it be accepted in partial fulfillment of the requirements for the degree of Doctor of Philosophy, with a major in Ecology and Evolutionary Biology.

Arthur C. Echternacht, Major Professor

We have read this dissertation and recommend its acceptance:

Benjamin M. Fitzpatrick, Sally Horn, James Fordyce

Accepted for the Council:

Carolyn R. Hodges

Vice Provost and Dean of the Graduate School

(Original signatures are on file with official studentecor r ds.) To the Graduate Council:

I am submitting herewith a dissertation written by Stesha Ann Pasachnik entitled “Conservation genetics and the Ctenosaura palearis clade.” I have examined the final electronic copy of this dissertation for form and content and recommend that it be accepted in partial fulfillment of the requirements for the degree of Doctor of Philosophy, with a major in Ecology and Evolutionary Biology.

Arthur C. Echternacht, Major Professor

We have read this dissertation and recommend its acceptance:

Benjamin Fitzpatrick

James Fordyce

Sally Horn

Accepted for the Council:

Carolyn R. Hodges

Vice Provost and Dean of the Graduate School

(Original signatures are on file with official student records.)

Conservation Genetics and the Ctenosaura palearis clade

A Dissertation Presented for The Doctor of Philosophy Degree The University of Tennessee, Knoxville

Stesha Ann Pasachnik August 2010

Dedication

This dissertation is dedicated to the protection of the world’s biodiversity and to the people who have given and continue to give their lives to protect threatened areas and the species that inhabit them.

iii

ACKNOWLEDGEMENTS

This study would not have been possible without the help of many thoughtful and inspiring individuals. I have had the opportunity to work with so many wonderful people throughout this research and during the time leading up to my graduate career. Had it not been for my family, friends and mentors I would not have had the ability and courage to begin and complete this process. A special thanks is needed for my dear friend and mentor John Iverson who showed me the amazing world of herpetology and conservation as a career, and to my mother for showing me the importance of nature throughout my early years. Without this guidance I know I would not have pursued this path. While in graduate school, I was lucky enough to have greats friends and lab mates, in particular; Sarah

Duncan, Christen Bossu, Jason Jones, Lara Souza, Melissa Cregger, Clara

Pregitzer, Jamie Call, Matt Niemiller, and Graham Reynolds.

My major professor, Sandy Echternacht, made this entire project possible.

He has been a great inspiration in the field and has had faith in my abilities and me since the beginning of this project. One of the first things that he told me was that he is a hands off advisor. At first I didn’t completely understand this but through time it has become clear to me that this takes a great amount of confidence in a student and now gives me a great amount of pride in my work. In

1968 Sandy was the first to document a population of C. melanosterna on the mainland on Honduras. This same population has become not only the focus of part of my dissertation but also the focus of many side projects. This connection was not immediately apparent but seems to have been a little bit of fate.

Ben Fitzpatrick must be given a great amount of thanks for his role, though unofficial, as co-advisor. Without his guidance and expertise I would not have been able to critically evaluate the threats that face the focal species of this research from a molecular genetics perspective. My committee members Jim

Fordyce and Sally Horn have provided much insight into this research and have been extremely supportive throughout this process.

There are not enough thanks I can give to all of the amazing volunteers who helped me in the field. Among these are Dennis Baulechner, Edoardo

Antunez Pineda, Jeffery Corneil, Gilberto Salazar, Paola Coti, Daniel Ariano,

Corey Shaffer, Jeff Liechty, Wendy Naira, Melissa Issis Medina, Sammy Nuñez, and Hadas Grushka. In addition to these individuals there are numerous local guides who helped throughout this process in immense ways.

Without the help of The Bay Island Foundation (formally the Iguana

Research and Breeding Station) and its incredibly helpful staff, Organización

Zootropic, the Overseas Research Station on Roatan and David Evans, the

Cayos Cochinos Foundation, the many offices of AFE-COHDEFOR (now ICF) and CONAP I would not have been able to work within the various areas of

Honduras and Guatemala. Jimena Castillo and Monica Sofia Perez, of the Bay

Islands Foundation, have been instrumental during this research. I am greatly indebted to them and cannot express enough gratitude to them for their cooperation and aid.

Funding from Sigma Xi, the International Iguana Foundation, The US

Department of the Interior CAFTA-DR program, The International Reptile

Conservation Foundation, and the Department of Ecology and Evolutionary

Biology of the University of Tennessee, Knoxville made this work possible.

ABSTRACT

We are now in the midst of a mass extinction crisis. The top threats to biodiversity include habitat destruction, pollution, over-harvesting, and invasive species. The field of conservation genetics seeks to understand these threats and devise management plans to preserve taxa with the ability to cope with environmental change. Preserving genetic variation and the processes in which variation is created and maintained is vital to long-term conservation goals.

Limited conservation resources are cause for the prioritization of taxa and areas.

Nine basic methods of prioritization have been developed. Differences in these methods, result in highly variable target maps however, many list Mesoamerica, in which the highest diversity of iguanids confined to a single genus, Ctenosaura, occur. Though ctenosaurs are the most diverse genus of iguanas, have the most

Redlisted species, lack protection and are in danger of extinction, they have been overlooked. The Ctenosaura palearis complex occurs in central Mesoamerica and is made up of four endangered species. In order to aid in the conservation of this biodiversity, a multi-scale molecular evaluation of this complex was performed. I first used a species tree approach to elucidate the relationships between the focal species, showing that these species have gone through recent and rapid speciation, resulting in four closely related endemics. Thus, the nominal groupings should be upheld and given individual protection. Second, I evaluated the degree to which gene flow from the widely distributed congener threatens the genetic distinctiveness of the endemic C. bakeri. Low levels of introgression indicated no current threat. Hybridization could increase if habitat

vii

destruction or changes in relative abundance increase the probability of interbreeding. Continued monitoring of this situation is justified. Third, I used a variety of population genetic techniques to elucidate the genetic structure within and among populations of C. melanosterna. These results indicate that the populations in the Valle de Aguán and Cayos Cochinos are not interchangeable.

Thus protection of both areas is necessary, and extreme caution should be used when implementing breeding and translocation programs. Local conservation efforts may be evaluated and developed using this information.

viii

TABLE OF CONTENTS

GENERAL INTRODUCTION ...... 1 Literature Cited ...... 5

PART I. GENE TREES, SPECIES AND SPECIES TREES WITHIN THE CTENOSAURA PALEARIS CLADE ...... 7 Abstract...... 8 Introduction ...... 9 Methods...... 15 Results...... 26 Discussion ...... 30 Literature Cited ...... 36 Appendix Ia. Figures and Tables ...... 43 Appendix Ib. Genbank accession numbers by locus. Localities refer to Figure I - 1 unless otherwise specified...... 53 PART II. GENE FLOW BETWEEN AN ENDANGERED ENDEMIC IGUANA, AND ITS WIDESPREAD RELATIVE ON THE ISLAND OF UTILA, HONDURAS: WHEN IS HYBRIDIZATION A THREAT? ...... 58 Abstract...... 59 Introduction ...... 60 Methods...... 64 Results...... 69 Discussion ...... 72 Literature Cited ...... 75 Appendix IIa. Figures and Tables ...... 79 PART III. POPULATION GENETICS OF CTENOSAURA MELANOSTERNA: IMPLICATIONS FOR CONSERVATION AND MANAGEMENT ...... 84 Abstract...... 85 Introduction ...... 86 Methods...... 94 Results...... 101 Discussion ...... 106 Literature Cited ...... 111 Appendix IIIa. Figures and Tables ...... 117 Appendix IIIb. Habitat photos...... 125 Appendix IIIc. F parameters from SAMOVA ...... 127 Appendix IIId. Average log probability of the data (left) and change of log probability ...... 129

GENERAL CONCLUSIONS...... 131 VITA...... 138

LIST OF FIGURES

Part I. Genes, species and species trees within the Ctenosaura palearis clade

Figure I -1. Geographic range of the four species within the C. palearis clade within Central America. Yellow=C. palearis (4-6), green=C. melanosterna (10-16), blue=C. oedirhina (7-9), purple=C. bakeri (1-3). Numbers correspond to haplotypes in Figures 2 and 5...... 44 Figure I – 2. Gene tree estimates: a. mtDNA, b. C-mos, C. LDHA, and d. PACs. Values above nodes represent posterior probabilities; values below nodes represent bootstrap values. Asterisk indicates haplotypes that were included in the species tree analyses. Value within parentheses indicates the number of sequences used in each analysis. Values outside of parentheses represent geographic location, corresponding to Figure 1 (if no value is indicated the haplotype represents all general locations)...... 45 Figure I – 3. C. palearis clade species tree generated from BEST. Posterior probabilities vary slightly from run to run. Therefore the average values after 160 million generations are reported. Topology remains consistent across runs and is identical to the topology found using the MDC and STAR methods...... 47 Figure I - 4. Relationships between the species tree estimate and each gene tree: a. mtDNA, b. C-mos, c. LDHA, and d. PACs...... 48 Figure I - 5. Consensus tree from the partitioned Bayesian concatenated analysis of the C. palearis clade. Values at nodes represent posterior probabilities.49

Part II. Gene flow between an endangered endemic iguana, and its wide spread relative on the island of Utila, Honduras: when is hybridization a threat?

Figure II - 1. Markers indicate sampling sites for Ctenosaura bakeri (black) and C. similis (white) on Utila, Honduras. Numbers indicate how many individuals of each species were used in the molecular analysis from each area...... 80 Figure II - 2. Consensus phylograms of Ctenosaura bakeri and C. similis haplotypes, from Utila, Honduras. A) ND4, B) LDHA, C) PACs. Numbers before nodes indicate bootstrap support from Maximum Likelihood analysis and posterior probabilities from Bayesian analyses. Amblyrhynchus critatus was used as the outgroup...... 81 Figure II - 3. Examples of heterozygous sites in A) LDHA and B) PACs nuclear genes for Ctenosaura bakeri, C. similis, and the putative hybrid described by Köhler and Blinn (2000) from Isla Utila, Honduras...... 82

Part III. Population genetics of Ctenosaura melanosterna; implications for conservation and management

Figure III - 1. Map of the distribution of Ctenosaura melanosterna in the Valle de Aguán and Cayos Cochinos, Honduras. Top photo depicts the typical beach habitat of Cayos Cochinos including numerous palms. Bottom photo depicts typical habitat in the Valle de Aguán with a cactus in the foreground...... 118 Figure III - 2. Maximum likelihood and Bayesian combined mitochondrial gene tree. Values above nodes represent posterior probabilities and values below nodes represent bootstrap support. Value inside parentheses indicates sample size. S=south of the Rio Aguán and N=north of the Rio Aguán. ... 119 Figure III - 3. Structure plots by primer, indicating the number of groups best supported. South indicated south of the Rio Aguán and north indicates north of the Rio Aguán...... 120 Figure III - 4. The frequnecy by which Foll and Gaggiotti's (2008) α is observerd, illustrating variation among AFLP markers in the degree of differentiation between mainland island samples of C. melanosterna. Outliers detected by BayeScan (Foll and Gaggiotti 2008) are shown in grey (Pr{αi ≠ 0 | data} > 0.95) and black (Pr{αi ≠ 0 | data} > 0.99)...... 121

LIST OF TABLES

Part I. Genes, species and species trees within the Ctenosaura palearis clade

Table I - 1. AMOVA results for C. bakeri, C. melanosterna, C. oedirhina, and C. palearis for five loci independently and then averaged across loci...... 50 Table I - 2. Pairwise ΦST estimates among the four Ctenosaurs species sequenced, calculated for five loci independently and then averages across loci: a) ND4 b) CytB, c) LDHA, d), PACs, e) C-mos, and f) averaged across loci...... 51 Table I - 3. Kimura 2-parameter distance matrix ...... 52

Part II. Gene flow between an endangered endemic iguana, and its wide spread relative on the island of Utila, Honduras: when is hybridization a threat?

Table II - 1. Distribution of ND4, LDHA and PACs Ctenosaura bakeri and C. similis haplotypes from Utila, Honduras. Haplotype numbers correspond to Figure II - 2...... 83

Part III. Population genetics of Ctenosaura melanosterna; implications for conservation and management

Table III - 1. A priori and SAMOVA groupings for three and four groups. Percent variation and associated significance obtained from AMOVA for both sets of groups...... 122 Table III - 2. Sample size, population genetic information, and demographic statistics for each Ctenosaura melanosterna populations. Significance based on p<0.05 and calculated from the data/coalescent simulations (following Finn et al. 2009)...... 123 Table III - 3. FST values from AFLP SURV...... 124

xii

GENERAL INTRODUCTION

According to the International Union for Conservation of Nature (IUCN

2010), as much as 36% of the world’s species and at least 50% of the world’s animals are threatened by extinction. Mace and Purvis (2008) suggested that 1% of populations and habitat is being lost per year. The extinction rate that we are witnessing today is estimated to exceed the natural rate of extinction by 1,000 to

10,000 times (IUCN 2010). We are in the midst of a biodiversity crisis (e.g. Pimm et al. 1995, Myers and Knoll 2001, Wake and Vrendenburg 2008). In 2002, an international pledge was made to achieve a significant reduction in the rate of biodiversity loss by 2010. This goal was far from being met.

The top threats to biodiversity, causing this elevated rate of extinction, are: habitat destruction and fragmentation, invasive species, pollution and over- harvesting resulting from human population growth (Wilson 2002). Conservation biology seeks to understand and reduce the impact of these threats on biodiversity loss. This new and growing field must bring together not only research but also education, outreach, public policy and economics if we are to be successful in conserving and managing the earth’s biodiversity (Primack

1993).

Preserving genetic variation is an important component in the preservation of species and populations. Through an understanding of genetics the processes which create and maintain biodiversity can be managed and protected, such that adaptive variation is conserved (Mace and Purvis 2008). The field of

conservation genetics seeks to understand and elucidate the threats to biodiversity by incorporating the use of molecular genetic techniques and developing management strategies that preserve taxa as dynamic entities capable of dealing with a changing environment (Frankham et al. 2004). Vital to this field are studies of gene flow, hybridization, genetic drift, accumulation of deleterious mutations, taxonomic uncertainties, forensics, and inbreeding depression, to name a few.

Given that conservation funding is often limited, efforts must be made to organize and prioritize areas and populations that need to be targeted for protection and management. The task of developing means by which to prioritize is both daunting and difficult. In a review by Brooks et al. (2006), nine strategies for prioritization were recognized. Due to the numerous studies focusing on bird and plant distributions, endemism of these taxa is often used as a measure of irreplaceability (e.g. Statterfield et al. 1998, Mittermeier et al. 2003, Myers et al.

2000).

One of the most well-known and accepted concepts for prioritization was developed by Myers et al. (2000) and termed biodiversity hotspots. A total of 25 sites were identified on the basis of plant and vertebrate endemism and total area. The goal of the hotspots reasoning is to conserve the greatest number of species while focusing on a small portion of the earth’s land surface. If these 25 hotspots, covering only 1.4 % of the earth’s land surface, are protected, 44% of all species of vascular plants and 35 % of vertebrate species will be conserved.

The other methods of prioritization use similar criteria of irreplaceability

and also include an evaluation of vulnerability. In the comparison of these nine methods (Brooks et al. 2006), the resulting target maps from each method overlapped as little as one-tenth of each other, raising controversy over the validity of the methods. Though there may be inconsistencies, the difficultly in defining criteria should not lead us away from the overall goal of biodiversity conservation. If we are to be successful in conserving biodiversity, funds need to be targeted. Thus these strategies should be seen as a place to start rather than a place to end (Myers et al. 2000, Mittermeier et al. 2003). Further, and perhaps more importantly, these methods have been criticized for not incorporating clear guidance on a local scale and, therefore, in the implementation of conservation actions on the ground (Mace 2000, Brummitt and Lughadha 2003).

In order to take steps in the direction of localized conservation the research herein focuses on a unique portion of biodiversity that is found within the Mesoamerican biodiversity hotspot (Myers et al. 2000), a crisis ecoregions

(Hoekstra et al. 2005) and an endemic bird area (Statterfield et al. 1998). Under the hotspots criteria, Mesoamerica ranked sixth overall and second in the number of endemic vertebrates and endemic reptiles. Among the many endemic reptiles in danger of extinction in Mesoamerica are the ctenosaurs. Of the 11 genera of iguanid lizards, the genus Ctenosaura is the most species rich, currently encompassing 18 distinct species; is threatened with extinction by habitat destruction and fragmentation, over-harvesting, and exportation through the illegal pet trade; and lacks any active means of protection. The Ctenosaura palearis complex occurs within the center of Mesoamerica, in Honduras and

Guatemala. This clade is made up for four species (C. bakeri, C. oedirhina, C. palearis and C. melanosterna), each identified by the IUCN as threatened on the basis of limited geographic range, habitat destruction and over-exploitation for food and pets.

To contribute to the protection of these unique and threatened species and, thus, a portion of Mesoamerican biodiversity, I have conducted a multi-scale molecular evaluation of this clade. The first objective was to evaluate the species boundaries within this clade using a variety of species tree estimation techniques. Prior to this work the only study that had evaluated all four species within this group was based solely on morphology (Buckley 1997, Buckley and

Axtell 1997), therefore, genetic data was needed in order to fully understand the status of these species. The second objective was to evaluate the potential threat that gene flow from the common and widely distributed congener, C. similis, could have to the genetic distinctiveness of the island endemic C. bakeri. The final objective of this research was to elucidate the within and among population variation of Ctenosaura melanosterna throughout its range in the Valle de Aguán and Cayos Cochinos, Honduras. Through the use of this information, local conservation plans and actions may be evaluated and developed so as to maximize the effects of such efforts.

Literature Cited

Brooks TM, Mittermeier RA, da Fonseca GAB, Gerlach J, Hoffman M, Lamoreux JF, Mittermeier CG, Pilgrim JD, Rodrigues ASL (2006) Global biodiversity conservation priorities. Science 313:58-61.

Brummitt, N and Lughadha, EN (2003) Biodiversity: Where's hot and where's not. Cons. Biol. 17: 1442-1448.

Buckley LJ (1997) Phylogeny and evolution of the genus Ctenosaura (Squamata: Iguanidae). Dissertation. Southern Illinois University at Carbondale.

Buckley LJ, Axtell RW (1997) Evidence for specific status of the Honduran lizards formally referred to as Ctenosaura palearis (Reptilia: Squamata: Iguanidae). Copeia 1997:138-150.

Frankham R, Ballou JD, Briscoe DA (2004) Introduction to conservation genetics. Cambridge University Press, Cambridge, UK.

Hoekstra JM, Boucher TM, Ricketts TH, Roberts C (2005) Confronting a biome crisis: global disparities of habitat loss and protection. Ecol Lett 8:23-29.

IUCN (2010) http://www.iucn.org/what/tpas/biodiversity/about/. Downloaded 15 March 2010.

Mace GM (2000) Its time to work together and stop duplicating conservation efforts… Nature 405:393.

Mace GM, Purvis A (2008) Evolutionary biology and practical conservation: bridging a widening gap. Mol Ecol 17:9-19.

Mittermeier RA, da Fonsec GAB, Brooks T, Pilgrim J, Rodrigues A, Myers N, Michael SJ, Bug A (2003) Hotspots and Coldspots. Am Sci 91:384.

Myers N, Knoll AH (2001) The biotic crisis and the future of evolution. Proc. Nat. Acad. Sci. USA 98:5389-5392.

Myers N, Mittermeier RA, Mittermeier CG, da Fonseca GAB, Kent J (2000) Biodiversity hotspots for conservation priorities. Nature 403:853-858.

Pasachnik SA (2006) Ctenosaurs of Honduras: Notes from the field. IGUANA 13:264-271.

Pimm SL, Russell GJ, Gittleman JL, Brooks TM (1995) Hotspots and the conservation of evolutionary history. Science 269:347-350.

Primack, RB (1993) Essentials of conservation biology. Sinauer Associates Inc., Massachusetts.

Stattersfeild AJ, Crosby MJ, Long, AJ, Wege DC (1998) Endemic bird areas of the world. Birdlife International, Cambridge, UK.

Wake, DB and Vredenburg VT (2008) Are we in the midst of the sixth mass extinction? A view form the world of amphibians. PNAS 105:11466-11473.

Wilson EO (2002) The future of life. Random House Inc., New York.

PART I. GENE TREES, SPECIES AND SPECIES TREES WITHIN THE CTENOSAURA PALEARIS CLADE

The following section is a slightly modified version of a paper published in the journal Conservation Genetics:

Pasachnik, S. A., B. M. Fitzpatrick, A. C. Echternacht. Gene trees, species, and species trees in the Ctenosaura palearis clade. Conservation Genetics. DOI 10.1007/s10592-010-0070-3.

Abstract

The growing use of molecular systematics in conservation has increased the importance of accurate resolution of taxonomic units and relationships. DNA data relate most directly to genealogies, which need not have perfect relationships with species limits and phylogenies. We used a multilocus gene tree approach to elucidate the relationships between four endangered Central American iguanas.

We found support for the proposition that the described species taxa correspond to distinct evolutionary lineages warranting individual protection. We combined gene trees to estimate a phylogeny using Bayesian Estimation of Species Trees

(BEST), minimizing deep coalescence, Species Trees from Average Ranks

(STAR), and traditional concatenation. The estimate from concatenation conflicted with the other methods, likely owing to the disproportionate effect of mtDNA on concatenated analyses. This illustrates the importance of appropriate treatment of multilocus sequence data in phylogenetics. Our results indicate that these species have gone through recent and rapid speciation, resulting in four closely related narrow-range endemics.

Introduction

It has recently become clear that species trees and gene trees are not expected to have identical topologies, especially in rapidly diversifying groups (e.g.,

Maddison 1997, Page and Charleston 1997, Degnan and Rosenberg 2006,

Edwards 2009). In addition, gene trees are not expected to be congruent with species boundaries for many generations after speciation (Wakeley 1996, Funk and Omland 2003, Forister et al. 2008), unless of course speciation is defined as the evolution of reciprocally monophyletic gene trees, a practice that would be misleading for many groups (Hudson and Coyne 2002). These problems are particularly meaningful in light of the growing influence of molecular systematics on conservation. A large number of decisions regarding legal status and management practices have depended on the systematic interpretation of genetic data (Fallon 2007). Thus, the validity of such interpretations is of more than academic interest. Here we use several of the most recently developed methods for using DNA sequence data to evaluate species boundaries and relationships from a population genetics perspective. We assess the morphologically and geographically defined species of the Ctenosaura palearis clade of Spiny-tailed Iguanas and estimate a species phylogeny using multilocus molecular approaches. The findings of the study will allow for more confident and thorough management and monitoring of these endangered species.

Species designation . Delimiting species boundaries is an important, yet difficult, component of conservation biology as these are the units most often recognized and/or given protection through governmental and international agencies (Sites and Crandall 1997, Peterson and Navarro-Siguenza 1999, Sites and Marshall

2003, Stockman and Bond 2007). In conservation management, a pragmatic definition of "species" is a distinct group of organisms meriting independent legal status because extinction of such a group would constitute a substantial loss of biological diversity. Most biologists probably agree with Allendorf and Luikart

(2007) that species status should be determined based on multiple lines of data, from phenotypic to ecological to molecular. However, decisions to recognize or deny species status are sometimes made based on limited and inconclusive data

(see for example, O’Brien and Mayr 1991 and references therein, Karl and

Bowen 1999). Here we illustrate critical analysis and interpretation of the best available data for an important and endangered group of tropical vertebrates.

The common practice of evaluating species boundaries on the basis of genetic exclusivity within a gene tree (Herbert et al. 2003a and b, Sites and

Marshall 2003) can create inconsistency between molecular phylogenetic inference and true evolutionary patterns (Hickerson et al. 2006). This issue is most troublesome in cases of recent or rapid divergence where retention or incomplete sorting of ancestral polymorphisms, leading to a lack of reciprocal monophyly among taxa in the gene tree, is more prevalent (Nigel and Avise

1986, Pamilo and Nei 1988, Avise 1989, Takahata 1989, Avise and Ball 1990,

Wu 1991, Maddison 1997, Hudson and Coyne 2002, Rosenberg 2002, Funk and

Omland 2003, Forister et al. 2008, Niemiller et al. 2008). It is well known that adaptive divergence can dramatically outpace lineage sorting of neutral loci

(Lande and Arnold 1983, Schluter and Smith 1986, Reznick and Ghalambor

2001). Thus, some of the most interesting units of biological diversity might be missed by uncritical application of genealogical species concepts, and good species might be denied protection under, for example, the Endangered Species

Act (ESA).

On the other hand, naïve interpretation of genealogical patterns from a single marker can overestimate species diversity (Agapow et al. 2004, Isaac et al. 2004) and potentially misdiagnose evolutionarily significant units (Irwin, 2002).

Fallon (2007) found that a large number of listing and delisting decisions by federal agencies were influenced by genetic data, thus it is imperative that this information is interpreted correctly. Conservation biologists and managers alike must be cautious to avoid misinterpreting or over weighting the information gained from such genetic techniques (Irwin 2002, Isaac et al. 2004).

Species trees and gene trees. When multiple markers are available for resolving taxonomic questions, multiple individual gene trees are often constructed.

Because single gene trees do not always represent the true species tree relationships (Maddison 1997, Funk and Omland 2003, Degnan and Rosenberg

2006), understanding the most appropriate way to use multiple gene tree estimates to inform a species tree is critical (Edwards 2009). This is especially important in cases where conservation priorities are being assessed.

The commonly followed practice of concatenating separate sequences into a single alignment (Bull et al. 1993, de Queiroz 1993, Huelsenbeck 1994, de

Queiroz et al. 1995) violates the assumption that each character in the data matrix is independent and ignores the fact that different alleles within a diploid individual have different true histories. Further, concatenated data can result in high estimated confidence in the wrong species tree topology when internal branches are short relative to the rate of gene tree coalescence (the so-called anomaly zone; Degnan and Rosenberg, 2006) or when only one or a few data partitions contribute a disproportionate amount of information (commonly the case for mtDNA).

An early solution to the problem of estimating a species phylogeny from gene trees is to assume species are reproductively isolated so that the species phylogeny is a "containing tree" that gene trees must fit within. Then a parsimonious phylogeny is one that minimizes the number of deep coalescences

(Madisson 1997, Page and Charleston 1997). Recently, methods have been developed using neutral coalescent theory to calculate the likelihoods of gene histories given a containing species tree, and then to find the species tree with maximum likelihood or posterior probability (e.g. COAL Degnan and Salter 2005,

BEST Edwards et al. 2007). These methods assume that different loci follow independent coalescent processes within a single containing tree where there is random mating within branches and no gene flow between branches. A third class of species tree methods uses average genetic distances or coalescent times between species as a distance matrix from which to infer a phylogeny

(Knowles and Carstens 2007, Liu et al. 2009). These methods are more robust to hybridization, assuming only that interspecific gene flow has not washed out the expected relationship between divergence time and average genetic similarity

(Niemiller et al. 2008). All of these species tree estimation methods require that the species taxa be defined a priori, and all assume that species relationships are essentially tree-like rather than reticulate.

The primary objective of this study is to assess the morphologically and geographically defined species of the C. palearis clade and to estimate the relationships between these species using a multilocus molecular approach. We first evaluated gene tree estimates from two mitochondrial and three nuclear markers independently. We then performed three analyses: AMOVA, Slatkin-

Maddison’s s, and constrained tree searches in PAUP*, to address the question of whether the prior species-level taxonomy accurately reflects distinct evolutionary lineages. Finally, we combined the gene tree data to estimate a species tree using three methods: Bayesian Estimation of Species Trees (BEST:

Liu et al. 2008), minimizing deep coalescence (MDC; Maddison 1997), and

Species Tree estimation using Average Ranks of coalescences among sequences (STAR; Liu and Yu 2007; Liu et al. 2009). For comparison, we also performed a traditional partitioned Bayesian analysis of concatenated sequences.

Study group. The Ctenosaura palearis clade is composed of four Critically

Endangered species that have recently become the focus of conservation

initiatives. C. palearis, the first species of this clade to be described (Stejneger

1899), occurs solely in limited areas within the Valle de Motagua, Guatemala

(Coti and Ariano 2008, SAP pers. obs). In 1968, a new population thought to belong to this species was described in the Valle de Aguán, Honduras

(Echternacht 1968), and was later described as C. melanosterna based on morphology and geographic isolation (Buckley and Axtel 1997). C. melanosterna occurs in limited areas of the Valle de Aguán (SAP pers. obs.) and two islands

(Cayos Cochinos Pequeño and Grande) within the Cayos Cochinos archipelago,

Honduras. C. bakeri was described from the islands of Utila and Roatan, Bay

Islands, Honduras (Stejneger 1901). The Roatan population, however, was split from C. bakeri and named C. oedirhina based on a morphological analysis of 21 characters (de Queiroz 1987).

The C. palearis clade was hypothesized to be monophyletic based on two morphological synapomorphies, a lateral dentary flange and frontal-parietal skull rugosities (Köhler 1995, Buckley 1997). All four species are medium sized iguanas (200-350 mm snout vent length) that are primarily herbivorous though opportunistically carnivorous in some life stages (Köhler 2003, Gutsche 2005,

McCranie et al. 2005, Coti and Ariano 2008). C. palearis and C. melanosterna occur in arid tropical scrub forests. C. bakeri is found primarily in black and white mangrove forest habitats, though they have also been observed in drier beach-front habitat (Buckley 1997, SAP pers. obs.). C. oedirhina seems to be a habitat generalist on the island of Roatan, appearing in mangrove habitat, dry beach front and heavily developed areas (SAP pers. obs.). With the exception of

limited ecological and behavioral data on C. bakeri (Gutsche 2005, Gutsche and

Streich 2009), natural history research on C. palearis (Coti and Ariano 2008) and the previously discussed morphological work, there is little known about the basic biology of this clade.

Since the species descriptions, genus level phylogenies using morphology

(Buckley 1997) and RAPDs (Köhler 2000) and a phylogeographic study using limited sequence data (zero to five individuals per species, evaluated for one or two molecular markers: Gutsche and Köhler 2008) have been produced. Only the morphological analysis conducted by Buckley (1997) included representatives of all four species; thus, a molecular evaluation of this group was warranted.

Methods

Field Collection. DNA samples were collected from individuals across the geographic range of each taxon in the Valle de Motagua in Guatemala and Utila,

Roatan, Cayos Cochinos, and the Valle de Aguán in Honduras over a four-year period from 2003 to 2007 (Figure 1). The exact locations of these individuals are not recorded herein as all four of these species are Critically Endangered and are listed under CITES Appendix II due to the threats they face from the international pet trade and look a like status. If desired, additional information concerning this topic may be requested from the authors.

Upon capture, a digital photograph was taken and snout-vent length, tail length, sex and weight were recorded, and each individual was given a unique 15

dorsal paint mark. The photographs and unique paint marks allowed us to avoid re-sampling in any given area. Either a one cm section of the tail tip was removed and stored in 100% ETOH, or a 0.5ml sample of blood was drawn from the caudal vein and stored in an EDTA buffer (Longmire et al. 1992) for molecular analysis. For individuals from which a tissue sample was taken, the area was disinfected with ETOH prior to removal, and pressure was applied to the wound until bleeding ceased and the area was sealed with a topical skin adhesive to prevent infection. For individuals from which a blood sample was taken, the area around the puncture site was disinfected with ETOH before the blood was drawn and was sealed with a topical adhesive after blood was drawn.

DNA Sequencing. Genomic DNA was extracted using the Qiagen DNeasy extraction kit (Qiagen, Valcencia, CA). The polymerase chain reaction (PCR) was used to amplify portions of two mitochondrial markers, 674 bp of NADH dehydrogenase subunit 4 and 1067 bp of cytochrome oxidase B (CytB), and three nuclear markers, 418 bp of lactate dehydrogenase A (LDHA) and 569 bp of polymerase alpha catalytic subunit (PACs) and 393 bp of oocyte maturation factor Mos (c-mos). The c–mos fragment was amplified using primers G73 and

G74 (Saint et al. 1998). PCR cycling for the c-mos was performed using the following conditions: denaturation at 94 ºC for 3 min., followed by 30 cycles at 94

ºC for 30 seconds, 55 ºC for 30 seconds, 72 ºC for 90 seconds, and final extension at 72 ºC for 5 minutes. For all other primer sequences and PCR

procedures see Pasachnik et al. (2009). PCR products were verified by gel electrophoresis and successful amplicons were purified using either exonuclease

I/shrimp alkaline phosphatase (ExoSap) or a QIAquick PCR purification kit

(Qiagen, Valcencia, CA).

Sequencing reactions were performed using the PCR primers and were aligned using Sequencher 4.6 (Gene Code Corporation). Ambiguous base calls were verified manually by examining the forward and reverse electropherogram reads. Sequences were aligned manually in PAUP* 4.0 (Swofford 2002) and verified in MacClade 4.07 (Maddison and Maddison 2005) by comparison with published sequences on Genbank (see supplementary material). Sequencing the nuclear markers revealed a few heterozygous sites; however, levels of heterozygosity were low enough for haplotypes to be determined unambiguously.

The LDHA locus has indels that differentiate between some taxa. C. melanosterna, C. bakeri, C. oedirhina, and C. palearis all have five fewer bps than the outgroup. In addition, C. melanosterna consistently has seven fewer bps than C. bakeri, C. oedirhina, and C. palearis. The missing basepairs were treated as missing data.

We assayed 166 individuals for the mitochondrial marker ND4. Of these

166 individuals 90 individuals were assayed for the mitochondrial marker CytB,

99 individuals for the nuclear marker LDHA, 37 individuals for the nuclear marker

PACs, and 34 individuals for the nuclear marker C-mos (Appendix Ia; Genbank accession numbers GU331964-GU332029, GU906218-GU906223, EU271876,

EU271879). In the combined mtDNA gene tree analysis only the 90 individuals

that we had sequenced for both loci were used. Uneven sample sizes are reflective of field sampling effort (other projects involving C. bakeri and C. melanosterna made many more samples from these species available) and by diminishing returns from sequencing nuclear markers with little nucleotide variation. Ctenosaura similis was used as an outgroup.

Gene trees. Gene trees were estimated independently for each of the three nuclear loci using both a maximum likelihood (ML) and a Bayesian approach.

The two mtDNA loci were combined to estimate a mitochondrial genealogy using only a Bayesian approach. ML analysis was conducted in PAUP* 4.0 (Swofford

2002) using a heuristic search with 1000 random-taxon-addition replicates.

Confidence at each node was assessed using nonparametric bootstrapping

(Felsenstein 1985) based on 1000 pseudo-replicates with 10 random-taxon- addition replicates per pseudo-replicate. The optimal model of sequence evolution for each locus was determined in Modeltest 3.7 (Posada and Crandall

1998). Bayesian trees and posterior probabilities were estimated using MrBayes

3.1 (Ronquist and Huelsenbeck 2003) with four Markov chains, the temperature profile at the default setting of 0.2, run for 2 million generations and sampling every 100th generation with a final burnin of 10,000 generations.

Testing species designations. We performed three analyses to address the question of whether the prior species-level taxonomy based on morphology and geography accurately reflects distinct evolutionary lineages. First, rejecting the

null hypothesis of no population structure is a minimal criterion for delimiting phylogenetically distinct taxa (Shaffer and Thomson 2007). In Arlequin 3.1

(Excoffier et al. 2005) we used an analysis of molecular variance (AMOVA) as a population genetic approach to test the null hypothesis of a random distribution of sequences among nominal taxa and to estimate ΦST among taxa. ΦST is inversely related to contemporary and historical levels of gene flow, but is also influenced by mutation and drift. Independent analyses were run using sequence data from five loci: ND4, CytB, LDHA, PACs, and C-mos. The overall pairwise ΦST estimates were then calculated by averaging across loci (Arlequin cannot analyze multilocus sequence data).

Second, we used Slatkin and Maddison’s s (Slatkin and Maddison 1989) to quantify discordance between the estimated gene trees and the prior species grouping. This method takes taxon membership as a categorical character state and finds the minimum number of parsimony steps in taxon membership on each gene tree. With four taxa, the minimum number of steps under total concordance is three, therefore the number over and above three was taken as a measure of discordance. Under a strict genealogical species concept requiring reciprocal monophyly of gene trees within taxa, any discordance would be grounds for rejecting the prior species taxonomy. Under more relaxed approaches, concordance of a subset of markers might be taken as adequate support for evolutionary independence (Wiens and Penkrot 2002).

Finally, we used the Shimodaira-Hasegawa (S-H) test in PAUP* to test the null hypothesis of monophyly of prior taxa by comparing the maximum likelihoods

of constrained trees to the likelihood of the best unconstrained tree using the

RELL approach and 1000 bootstrap replicates (Kishimo et al. 1990, Shimodaira and Hasegawa 1999, Goldman et al. 2000). This analysis addresses uncertainty in gene tree estimates in relation to the question of whether the true gene trees might be reciprocally monophyletic (Felsenstein 2004). As implemented, this test is capable only of rejecting or failing to reject reciprocal monophyly and failure to reject should not be taken as support for the null hypothesis. Some species definitions require reciprocal monophyly of gene trees, and this is a way to ask whether the data are inconsistent with the reciprocal monophyly criterion.

Because all four taxa are mutually allopatric, we cannot address the question of intrinsic reproductive isolation (Coyne and Orr 2004, Price 2008). We also cannot test ecological “exchangeability” because all differences between taxa are confounded by geography, and we cannot evaluate the degree to which ecological and morphological differences might be phenotypically plastic. Thus, the species question for this group is limited to the existence of genetically distinct lineages, without regard for the potential fate of those lineages if they were to be geographically reunited.

Bayesian estimation of species trees (BEST) analysis . Using the modified version of the MrBayes program (BEST) we first tried including the full set of sequences for all five markers used to create the individual gene trees; however, the analysis did not run properly because missing data could not be pruned from individual gene trees. That is, individuals missing sequence data for an entire

locus still had to be included in the gene tree for that locus, leading to completely unresolved gene trees being passed from MrBayes to BEST. Thus, a subset of the individuals, those including data from all markers, was used in our analysis to estimate the species tree. A total of 27 individuals were included in this subset and 3062 bps across five loci (ND4, CytB, LDHA, PACs, and C-mos) were analyzed. Seven individuals of C. melanosterna, three C. palearis, 13 C. bakeri, three C. oedirhina, and one C. similis (outgroup) were included. For nuclear markers, diploid individuals do not correspond to the tips of a gene tree because each individual contains two alleles that may or may not be identical by state and formally cannot be identical by descent from the previous generation (Nordborg

2001). Construction of a concatenated file such as that required by BEST is equivalent to randomly sampling one allele per individual. This corresponds to the coalescent assumption of random sampling of alleles provided that a single allele is randomly selected from each heterozygous individual. Our data set included very few heterozygotes and which allele was included did not affect the topology of the species tree or the support for any node. We verified this by randomly selecting which allele was used and running these data separately to compare the resulting species trees and support values. It would be inappropriate to use the consensus sequence from a heterozygous individual because heterozygous sites would have to be coded as ambiguous; this confuses real variation with uncertainty, and could potentially distort inferences based on coalescent theory.

The prior distribution of the scaled population size (θ) was an inverse gamma distribution and we used the default settings for alpha (3.0) and beta

(0.03) (Liu et al. 2008). This corresponds to a relatively uninformative prior and is appropriate given that little is known about the population size and mutation rates for this group. When we experimented with other priors, the program often failed to converge. Two chains with two runs each were run for 100 million generations, with every 10,000th gene tree saved. The burnin was 20 million generations.

Four independent runs were used to assess consistency in topology. The posterior probabilities reported on the species tree reflect the average over all runs.

This hierarchical Bayesian method considers the possibility that both deep coalescence and uncertainty in gene tree estimates affect discordance between species and gene trees. BEST incorporates uncertainty in each gene tree by considering the posterior distributions returned by MrBayes, and uses an explicit coalescent model to calculate the likelihoods of gene trees given a possible species tree.

Minimizing Deep Coalescence (MDC). We used Mesquite 2.5 (Maddison and

Maddison 2009) to estimate a species tree using the Deep Coalescence Multiple

Loci approach (Maddison 1997), where calculations of deep coalescence are simultaneously computed for multiple given gene trees. The Bayesian gene trees presented herein were used in these constructions. The discordance between the gene tree and species tree, in this approach, is assumed to be due

only to incomplete lineage sorting. The gene trees are taken as given and there is no explicit coalescent model underlying the analysis, only the assumption that gene tree topologies tend be concordant with the species tree.

Species Tree estimation using Average Ranks of coalescences among sequences (STAR). Following Liu and Yu (2007) and Liu et al. (2009), we ranked each interspecific coalescence in each Bayesian consensus gene tree and calculated the average for each species pair. The pairwise matrix of average ranks was then used to calculate a neighbor-joining tree. The expected rank for true sister taxa is always smaller than that for non-sisters if there is no gene flow after speciation (Liu et al. 2009). Gene flow after speciation will add noise but will not necessarily make STAR an inconsistent estimator of the species tree. No explicit coalescent model is assumed, and both gene flow and deep coalescence can contribute to gene tree discordance in this method. The only assumptions are that the given gene trees are accurate and that interspecific coalescence between closely related species tends to be more recent than coalescence between more distantly related species.

Concatenation. Using MrBayes 3.1 we ran a fully partitioned analysis where each locus was considered a partition and was assigned its own substitution model, but all were assumed to have the same tree topology. To avoid the problems associated with missing data the same 27 individuals that were used in the BEST analysis where used in this analysis. The MCMC analysis was run for 10 million

generations sampling every 1000 generations after a burnin on 5 million generations. We analyzed four separate runs with four linked Markov chains each. Concatenated analyses can be viewed either as assuming perfect concordance among the true gene trees (as if there were no recombination between loci) or as generating some sort of mean gene tree. Either way, the assumption (required for parsimony or likelihood calculations) that each nucleotide in the analysis is independent is incorrect when multiple nucleotides from each of several loci are used. In addition, the assumption of tree-like relationships among tips is incorrect when more than one individual per sexually reproducing species is included in the analysis (individual organism relationships are described by pedigrees).

Molecular dating. In addition to generating a simple Kimura 2- parameter distance matrix in PAUP* to infer divergence times, we also used both BEAST version 1.5.3 (Drummond and Rambaut 2007) and r8s version 1.5 (Sanderson

2002) to generate divergence times within the subfamily Iguaninae. There are no published fossil records corresponding to the focal species in this study, thus, following Zarza et al. (2008) we incorporated paleontological data from other iguana species as external calibration points. One calibration point corresponds to the oldest record of an iguanid lizard, Pristiguana, dated at 93 MYA (Estes and

Price 1973). The second point corresponds to the minimum age of the appearance of the Iguaninae genus Dipsosaurus, dated at 24 MYA (Carroll

1988). The mitochondrial locus ND4 was used in these analyses, as it is the only

locus for which sequences are available for all genera within this subfamily. Thus representatives of all Iguaninae genera plus the ND4 haplotypes elucidated for the focal species within this study were incorporated.

The input file for the BEAST analysis was constructed using the BEAUTI interface of the BEAST package (Drummond and Rambaut 2007). It was then executed using an uncorrelated lognormal relaxed molecular clock model and substitution model parameters that were based on our modeltest results from the genetree analysis (GTR, Gamma, Nst=6). The tree model used a randomly generated starting tree and the Yule Process tree prior. The prior for the tmrca parameter was a uniform distribution with a lower boundary of 24 MYA and an upper boundary of 93 MYA. Three runs of one million generations were selected with a burnin of 10% of the sampled trees. These runs were combined using

LOGCOMBINER 1.5.3 of the BEAST package (Drummond and Rambaut 2007).

We then repeated this analysis using each of the calibration points independently with a normal distribution prior.

Similarly when using the r8s program (Sanderson 2002) we both constrained the analysis with the 24 MYA and 93 MYA boundaries and ran the analysis separately with each calibration point fixed. We used Langely-Fitch,

NPRS and penalized likelihood smoothing algorithms. These analyses were runs using an ND4 consensus tree created from a Bayesian analysis of representatives from all Iguaninae genera and the haplotypes of the focal species elucidated in this study (parameters follow those discussed above for the

gene tree estimates). We had to prune Brachylophus due to a polytomy that was preventing the program from running.

Results

Gene trees. The mitochondrial gene tree shows reciprocal monophyly for all four of the species within the C. palearis clade. The first split separates C. bakeri from the rest of the C. palearis clade; within the latter group, C. oedirhina is the sister taxon to a clade comprising C. melanosterna and C. palearis (Figure 2a).

Intraspecific variation occurs within all four species. Only four haplotypes were found from the 17 individuals sequenced for C. bakeri. Each of the three C. oedirhina individuals sequenced had unique haplotypes, as did each of the three

C. palearis individuals sequenced from the Valle de Motagua. Seven haplotypes were observed among 67 C. melanosterna sampled.

Nuclear gene trees were not well resolved, and alleles were shared among species in every case (Fig. 2 b-d). Only the PACs gene tree showed coherent structure, with weak evidence of a relationship between C. bakeri and

C. oedirhina and between C. palearis and a subset of C. melanosterna alleles.

While these poorly resolved gene trees give the appearance of discordance, polytomies are no more indicative of paraphyly than they are of monophyly.

Testing species designations. The AMOVA results reveal variation in the pairwise

ΦST estimates across loci. However, all of the overall ΦST estimates are significant, indicating that a high degree of variation exists between taxa within 26

each marker. The average percent of variation explained, calculated across loci, indicates that species differences account for over 75% of the observed genetic variation (Table 1). For each taxon there is at least one nuclear marker in addition to the mitochondrial data that supports a significant difference between the focal taxon and all other taxa. Thus, we can reject the null hypothesis of no population structure in the group as a whole. Table 2 shows the breakdown of pairwise differences between all species for all loci as well as averaged across loci.

Slatkin and Maddison’s s (Slatkin and Maddison 1989) was used to quantify discordance between our Bayesian estimates of the gene trees and the previously defined taxa. Given reciprocal monophyly in the mitochondrial regions, the number of parsimonious steps is three. Likewise, a minimum of three steps are observed in the PACs, LDHA and C-mos markers (polytomies could always be resolved to minimize discordance). Thus each marker is concordant with the previously described species boundaries, with no evidence in the data set of post-speciation gene flow.

Because some species definitions require reciprocal monophyly of gene trees (Baum and Shaw 1995, Hudson and Coyne 2002), but our nuclear gene trees are not well-resolved, we tested whether they are inconsistent with reciprocal monophyly using the S-H test. Using constrained searches in PAUP*, we compared maximum likelihoods of constrained reciprocally monophyletic trees to the likelihood of the best unconstrained trees. The results of these comparisons indicate that we cannot reject the null hypothesis of reciprocal

monophyly, as the maximum likelihood scores for the constrained and unconstrained tree are identical when compared for each locus, except in the case of PACs, where we find a significant difference between topologies

(p=0.035). The nuclear gene trees are largely unresolved, and thus are consistent with several hypotheses, and provide no reason to reject (nor support) a null hypothesis of reciprocal monophyly of all designated taxa, except in the case of PACs, where all observed alleles appear to be nested within the C. melanosterna gene tree (Fig. 2d).

Species tree estimation. All three species tree methods (BEST, MDC and STAR) agreed on a symmetrical phylogeny with C. bakeri being the sister taxon to C. oedirhina and C. palearis being the sister taxon to C. melanosterna (Fig. 3). Only

BEST provides estimates of support for each node. From run to run in this analysis, we consistently found high posterior probabilities for both sister pairs.

The relationships between the species tree estimate and each gene tree are illustrated as a set of four contained trees (Fig. 4). No single gene tree was perfectly concordant with the species tree estimate.

Concatenation. The partitioned Bayesian concatenated analysis (Figure 5) agrees with the combined mtDNA gene tree but disagrees in part with the species tree estimate. Although the concatenated dataset finds support for C. palearis and C. melanosterna being sister species, it does not find C. bakeri and

C. oedirhina to be sister taxa. Instead, this analysis shows C. oedirhina as being

the sister taxon to the C. palearis/C.melanosterna pair and C. bakeri then being the sister taxon to these three. This approach indicates stronger support for each node than that obtained from the mtDNA data alone (Fig 2a). However, the concatenated topology is probably an artifact of the disproportionate contribution of mtDNA to the concatenated data set (57% of the total number of nucleotides and an even greater fraction of the variable sites in the multilocus data set).

Molecular dating. To estimate the approximate timescale of divergence we incorporated two external calibration points and ND4 sequence data for representatives of all of the Iguaninae genera into both the BEAST and r8s programs in order to estimate date the mrca of the C. palearis clade. In these analyses our calibration points constrained the Iguaninae to have originated no more than 93 MYA but not more recently than 24 MYA. From the BEAST analysis the mrca of the C. palearis clade is estimated at 3.55 MYA (95% CI:

1.33 - 7.17 MYA) and the overall mean mutation rate is 0.0062 (95% CI: 0.0025 -

0.01) or about 1.2% divergence per million years. Dates for other nodes within

Iguaninae were consistent with Zarza et al. (2008) and Malone et al. (2000).

When 93 and 24 MYA were used as a fixed calibration points the mrca for the C. palearis clade were 10.417 MYA (95% CI: 4.38 – 21.99 MYA) and 2.73 MYA

(95% CI: 1.13 – 5.89 MYA) respectively. When using the r8s program we found that the algorithm used did not affect the estimates to a great degree and estimates ranged from 1 to 5 MYA depending on which fossil was used to fix the age of the ancestral node.

Discussion

The results of this study support the prior species-level taxonomy, based on morphology and geography, of the C. palearis clade. Both tree and non-tree based analyses are consistent with the current nominal groups. Thus we see congruence among three crucial lines of data used in delimiting species; molecular, geographical, and morphological. The level of DNA sequence divergence among species of the C. palearis clade indicates that speciation occurred in quick succession a few million years ago, around the same time as the closing of the Isthmus of Panama. Discordance between gene tree topologies, and disagreement between the concatenated analysis and the species tree estimates from BEST, STAR, and MDC, illustrate the challenges of species tree estimation and the value of appropriate analysis of gene genealogies in phylogenetics (Edwards 2009).

Species designation. Our analyses show that the four nominal taxa are genetically distinct, with over 75% of the variation in the data set falling among species (Table 1). The species in the mitochondrial gene tree are demonstrably reciprocally monophyletic (Figure 2a). And, though the nuclear gene trees might appear to conflict, we cannot reject reciprocal monophyly of the underlying gene genealogies based on the S-H test, except in the case of PACs (p=0.035). That is, the true gene histories might be completely "sorted" with all alleles within a 30

species sharing a common ancestral allele not shared with any other species, but there are too few mutations in the data set to reconstruct that history. As it is, the set of nuclear gene trees is consistent with many alternatives, but the mtDNA data strongly support reciprocal monophyly of the species taxa. Thus, C. bakeri,

C. melanosterna, C. oedirhina, and C. palearis qualify as phylogenetic or genealogical species and represent isolated and independent evolutionary lineages.

The debate over how to apply the term "species" pre-dates evolutionary biology and much confusion and conflict about species concepts stems from the status of the term “species” as a Linnean rank. Different species definitions may be equally valid ways of describing real groups in nature. But the groupings they describe can be different without being mutually exclusive. Monophyletic species are real things just as reproductively isolated species are real things. Often, the same group of organisms can be described as both. But the terms (monophyletic or reproductively isolated) describe separate aspects of the group (or different stages in a process of speciation [de Queiroz 2007]). When different species criteria do not coincide (i.e., the groups they delineate intersect but are not identical), the debate is not about the accuracy with which the criteria describe the groups. Rather the debate is about which grouping is to be invested with the honor and prestige of a Linnean rank.

Patterns of concordance and discordance between grouping criteria might have interesting biological causes. The description of a group as one kind of species leads to the hypothesis that the same group is also another kind of

species. The answer, whether affirmative or negative, leads to further hypotheses as to why. These kinds of hypotheses constitute an extremely important component of the study of the evolution of diversity. Since the four species studied here are mutually allopatric, we cannot currently address the questions of intrinsic reproductive isolation nor ecological “exchangeability”

(Coyne and Orr 2004, Price 2008). However, our analyses do confirm that the groups described based on morphological distinctiveness correspond to genetically distinct lineages.

Timing of speciation. The low level of sequence divergence and lack of resolution in nuclear gene trees imply that divergence was relatively recent, however there has been adequate time for reciprocal monophyly of mtDNA gene trees and three methods of species tree estimation came to concordant results. While precise inference based on molecular clocks is notoriously difficult (particularly in light of gene tree-species tree discordance; Edwards and Beerli 2000), the rate of mtDNA evolution in vertebrates is well enough understood to place divergence times within the C. palearis clade in the range of 2-7 MYA (Table 3). This rough estimate is supported by the results found when using both the r8s (Sanderson

2002) and BEAST (Drummond and Rambaut 2007) programs. This indicates that most diversification occurred around the time of the closing of the Isthmus of

Panama and well before the isolation of the current island of Utila, home of the endemic C. bakeri and estimated to have been separated from mainland

Honduras 8000-9000 years ago (see Toscano and Macintyre 2003 for sea level

curves). The now small and isolated geographic ranges of the four species might reflect range contraction in the face of widespread competitors such as C. similis.

However, given that our best estimate of the species tree places the split between C. bakeri and C. oedirhina well after the most recent common ancestor of their mtDNA, it might be that these two island endemics arose more recently as sea levels rose with melting Pleistocene ice sheets. Likewise, it may be the case that orogenic activity fragmenting patches of preferable arid habitat in

Guatemala and Honduras has caused the current ranges of C. palearis and C. melanosterna (on the mainland) as speculated by Buckley (1997).

Species trees and gene trees. Our data show that the C. palearis clade is a recent radiation with few well-supported relationships that are consistent across gene trees. Thus resolution of a species tree clearly required a rigorous method for integrating the information contained in the different DNA sequence alignments. When we performed a partitioned Bayesian analysis of our concatenated data set, we obtained a tree topology identical to the mtDNA gene tree, but with strong support for the internal nodes (posterior probability estimates

> 97%) where the mtDNA topology was not well supported (posteriors of 78% and 83%). This topology was inconsistent with that estimated by BEST, MDC, and STAR. Disagreement between multilocus and concatenated analyses is most likely when internal branches are short relative to population sizes (i.e., when gene trees are most likely to be discordant) and/or when one locus dominates the data set (Degnan and Rosenberg 2006). In our case, the

disproportionate influence of mtDNA is probably the primary issue and this is likely to be a common problem in non-model organisms where molecular resources are limited.

The species tree results also illustrate the importance of sampling. Given the assumptions that (i) species designations are accurate, and (ii) speciation corresponds to complete cessation of gene flow, the universe of possible species trees is strongly affected by the most recent coalescence between species (see discussion of species tree priors in Edwards et al. 2007, Lui and Pearl 2007, Liu

2008, Liu et al. 2008). When intraspecific gene trees are not reciprocally monophyletic, the distribution of between-species coalescences will depend on sample size. This follows from the standard coalescent theory (Wakeley 2008,

Edwards and Beerli 2000). If there are two species, each with two sampled lineages that do not coalesce more recently than speciation, the expected time to the first coalescence is 4N/(4*3) generations earlier than speciation. If only one lineage is sampled per species, the expected coalescence time is 4N/2 generations earlier than speciation, six times older than in the four lineage deep coalescence case. This principle is illustrated in our data where, for example, failure to sample certain PACS sequences would reduce support for the sister relationship between C. melanosterna and C. palearis (Figure 2d; 10/14 sampled

C. melanosterna chromosomes would have supported C. melanosterna as the sister taxon to the remaining three).

Conclusions. Resolving the relationships between the four species within the C. palearis clade demonstrates the challenging nature of estimating a species tree for a group characterized by recent divergence. This study also illustrates the importance of using multiple lines of data to evaluate such a question, especially in cases where conservation and management might depend upon the conclusions. The commonly used practice of estimating a tree from concatenated data gives a tree with high support values but one that conflicts with the (also strongly supported) estimate from explicit species tree methods. We argue that the concatenated analysis is misleading, as it is heavily influenced by only one marker, and that the BEST/MDC/STAR species tree is more likely to be correct. Our analyses agree that the four species taxa in the C. palearis clade (all listed as Critically Endangered by the IUCN) are recently derived but distinct and independent evolutionary lineages that should each be protected as unique elements of Mesoamerican biodiversity.

Literature Cited

Agapow PM, Bininda-Edmonds ORP, Crandall KA, Gittleman JL, Mace GM, Marshall JC, Purvis A (2004) The impact of species concept on biodiversity studies. Q Rev Biol 79:161-179.

Allendorf FW, Luikart G (2007) Conservation and the genetics of populations. Blackwell Publishing, Oxford, UK.

Avise J. (1989) A role for molecular-genetics in the recognition and conservation of endangered species. Trends Ecol Evol 4:279-281

Avise JC, Ball RM (1990) Principles of genealogical concordance in species concepts and biological taxonomy. Oxford Surveys in Evolutionary Biology, Oxford University Press.

Baum DA, Shaw KL (1995) Genealogical perspectives on the species problem. Exp Mol App Plant BioSyst :289-303.

Buckley LJ (1997) Phylogeny and evolution of the genus Ctenosaura (Squamata: Iguanidae). Dissertation. Southern Illinois University at Carbondale.

Buckley LJ, Axtell RW (1997) Evidence for specific status of the Honduran lizards formally referred to as Ctenosaura palearis (Reptilia: Squamata: Iguanidae). Copeia 1997:138-150.

Bull JJ, Huelsenbeck JP, Cunningham CW, Swofford DL, Waddell PJ (1993) Partitioning and combining data in phylogenetic analysis. Syst Biol 42:384-397.

Carroll RL (1988) Vertebrate paleontology and evolution. W.H. Freeman, NY.

Coti P, Ariano D (2008) Ecology and traditional use of the Guatemalan Black Iguana (Ctenosaura palearis) in the dry forests of the Motagua Valley, Guatemala. IGUANA 3:142-149.

Coyne JA, Orr HA (2004) Speciation. Sinauer Associates, Inc Sunderland, MA. de Queiroz K (1987) A new Spiny-Tailed iguana from Honduras, with comments on relationships within Ctenosaura (Squamata: Iguania). Copeia 1987:892-902. de Queiroz A (1993) For consensus (sometimes). Syst Biol 42:369-372.

de Queiroz K (2007) Species concepts and species delimitation. Syst Biol 56:879-886. de Queiroz A, Donoghue MJ, Kim J (1995) Separate versus combined analysis of phylogenetic evidence. A Rev Ecol Syst 26:657-681.

Degnan JH, Rosenberg NA (2006) Discordance of species trees with their most likely gene trees. PLoS Genet 2:762-768.

Degnan JH, Salter LA (2005) Gene tree distributions under the coalescent process. Evolution 59:24-37.

Drummond AJ, Rambaut A (2007) BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evol Biol 7:214-221.

Echternacht AC (1968) Distributional and ecological notes on some reptiles from northern Honduras. Herpetologica 24:151-158.

Edwards SV (2009) Is a new and general theory of molecular systematics emerging? Evolution 63:1-19.

Edwards SV, Beerli P (2000) Perspective: gene divergence, population divergence, and the variance in coalescence time in phylogeographic studies. Evolution 54:1839-1854.

Edwards SV, Liu L, Pearl DK (2007) High resolution species trees without concatenation. Proc Natl Acad Sci USA 104:5936-5941.

Estes R, Price LI (1973) Iguanid lizard from upper Cretaceous of Brazil. Science 180:748-751.

Excoffier L, Laval G, Schneider S. (2005) Arlequin ver. 3.0: an integrated software package for population genetics data analysis. Evol Bioinf Online 1:47– 50.

Fallon SM (2007) Genetic data and the listing of species under the US endangered species act. Cons Biol 21:1186-1195.

Felsenstein J (1985) Confidence-limits on phylogenies – an approach using the bootstrap. Evolution 39:783-791.

Felsenstein J (2004) Inferring Phylogenies. Sinaur. Sunderland.

Forister ML, Nice CC, Fordyce JA, Gompert Z, Shapiro AM (2008) Considering evolutionary processes in the use of single-locus genetic data for conservation, with examples from the Lepidoptera. J Insect Cons 12:37-51.

Funk DJ, Omland KE (2003) Species-level paraphyly and polyphyly: Frequency, causes, and consequences, with insights from animal mitochondrial DNA. A Rev Ecol Evol Syst 34:397-423.

Goldman N, Anderson JP, Rodrigo AG (2000) Likelihood-based tests of topologies in phylogenetics. Syst Biol 49:652–670.

Gutsche A, (2005) Distribution and habitat utilization of Ctenosaura bakeri on Utila. IGUANA 12:143-151.

Gutsche A, Köhler F, (2008) Phylogeography and hybridization in Ctenosaura species (Sauria: Iguanidae) from Caribbean Honduras: insights from mitochondrial and nuclear DNA. Zoosyst Evol 84:253-261.

Gutsche A, Streich WJ (2009) Demography and endangerment of the Utila island spiny tailed iguana, Ctenosaura bakeri. J Herp 43:105-113.

Herbert PDN, Cywinska A, Ball SL, DeWaard JR (2003a) Biological identification through DNA barcodes. Proc Nat Acad Sci USA 270:313-321.

Herbert PDN, Ratnasingham S, deWaard JR (2003b) Barcoding animal life: cytochrome C oxidase subunit 1 divergences among closely related species. Proc Nat Acad Sci USA 270:S96-S99.

Hickerson M, Meyer C, Moritz C (2006) DNA barcoding will often fail to discover new animal species over broad parameter space. Syst Biol 55:729-739.

Hudson R, Coyne JA (2002) Mathematical consequences of the genealogical species concept. Evolution 56:1557-1565.

Huelsenbeck JP (1994) Is character weighting a panacea for the problem of data heterogeneity in phylogenetic analysis. Syst Biol 43:288-291.

Irwin DE (2002) Phylogeographic breaks without geographic barriers to gene flow. Evolution 56:2383-2394.

Isaac NJB, Mallet J, Mace GM (2004) Taxonomic inflation: its influence on macroecology and conservation. Trends Ecol Evol 19:464-469.

Karl SA, Bowen BW (1999) Evolutionary significant units versus geopolitical taxonomy: molecular systematics of an Endangered sea turtle (genus Chelonia). Cons Biol 13:990-999.

Kishino H, Miyata T, Hasegawa M (1990) Maximum likelihood inference of protein phylogeny and the origin of chloroplasts. J Mol Evol 31:151-160.

Knowles LL, Carstens BC (2007) Delimiting species without monophyletic gene trees. Syst Biol 56:887-895.

Köhler G (1995) Freilanduntersuchungen zur morphologie und ˆkologie von Ctenosaura bakeri and C. oedirhina auf den Islas de la Bahia, Honduras, mit bemerkunen zur schutzproblematik. Salamandra Rheinbach 31:93-106.

Köhler G (2000) Systematics of the Ctenosaura group of lizards (Reptilia: Sauria: Iguanidae). Amphibia-reptilia 21:177-191.

Köhler G (2003) The reptiles of Central America. Herpeton, Verlag Elke Köhler, Offenbach, Germany.

Lande R, Arnold SJ (1983) The measure of selection on correlated characters. Evolution 37:1210-1226.

Longmire JL, Gee GF, Hardekopf CL, Mark GA (1992) Establishing paternity in whooping cranes (Grus americana) by DNA analysis. The Auk 109:522-529.

Liu L (2008) BEST: Bayesian estimation of species trees under the coalescent model. Bioinformatics 24:2542-2543.

Liu L, Pearl DK (2007) Species trees from gene trees: Reconstructing Bayesian posterior distributions of a species phylogeny using estimated gene tree distributions. Syst Biol 56:504-514.

Liu L, Pearl DK, Brunfield RT, Edwards SV (2008) Estimating species trees using multiple-allele DNA sequence data. Evolution 62:2080-2091.

Liu L, Yu L (2007) Phybase: Phylogenetic analysis of multilocus sequences in R. http://www.stat.osu.edu/~liuliang/research/phybase.html.

Liu, L, Yu LL, Pearl DK, Edwards SV (2009) Estimating species phylogenies using coalescence times among sequences. Syst Biol 58:468-477

Maddison WP (1997) Gene trees in species trees. Syst Biol 46:523-536.

Maddison DR, Maddison WP (2005) MacClade 4 release version 4.07 for OSX. Sinauer Associates, Inc. Sunderland, Massachusetts.

Maddison WP, Maddison DR (2009) Mesquite: a modular system for evolutionary analysis. Version 2.6. http://mesquiteproject.org

Malone CL, Wheeler T, Tayloe JF, Davis SK (2000) Phylogeography of the Caribbean Rock Iguana (Cyclura): Implications for conservation and insights on the biogeographic history of the West Indies. Mol Phylogenet Evol 17:269-279.

McCranie JR, Wilson LD, Kohler G (2005) Amphibians and reptiles of the Bay Islands and Cayos Cochinos, Honduras. Bibliomania!, Salt Lake City, UT, USA.

Niemiller ML, Fitzpatrick BM, Miller BT (2008) Recent divergence with gene flow in Tennessee cave salamanders (Plethodontidae: Gyrinophilus) inferred from gene genealogies. Mol Ecol 17:2258-2275.

Nigel J, Avise JC (1986) Phylogenetic relationships of mitochondrial DNA under various demographic models of speciation. In: Nevo, E., Karlin, S. (Eds.), Evolutionary Processes and Theory. Academic Press, New York, pp 515–534.

Nordborg M (2001) Coalescent theory. In: Balding, D., Bishop, M., Cannings, C. (Eds.), Handbook of Statistical Genetics. Wiley, Chichester, UK, pp 179-212.

O’Brien SJ, Mayr E (1991) Bureaucratic mischief: recognizing endangered species and subspecies. Science 251:1187-1188.

Page RDM, Charleston MA (1997) From gene to organismal phylogeny: Reconciled trees and gene trees/species tree problem. Mol Phylogenet Evol 7:231-240.

Pamilo P, Nei M (1988) Relationships between gene trees and species trees. Mol Biol Evol 5:568-583.

Pasachnik SA, Fitzpatrick BM, Near TJ, Echternacht AC (2009) Gene flow between an endangered endemic iguana, and its wide spread relative, on the island of Utila, Honduras: when is hybridization a threat? Cons Genet. 10:1047- 1054.

Peterson AT, Navarro-Siguenza AG (1999) Alternative species concepts as bases for determining priority conservation areas. Cons Biol 13:427-431.

Posada D, Crandall KA (1998) Modeltest: testing the model of DNA substitution. Bioinformatics 14:817-818.

Price T (2008) Speciation in birds. Roberts and Company, Greenwood Village, Colorado, USA.

Reznick DN, Ghalambor CK (2001) The population ecology of contemporary adaptations: what empirical studies reveal about the conditions that promote adaptive evolution. Genetica 112:183-198.

Ronquist F, Huelsenbeck JP (2003) MRBAYES 3: Bayesian phylogenetics inference under mixed models. Bioinformatics 19:1572-1574.

Rosenberg NA (2002) The probability of topological concordance of gene trees and species trees. Theor Population Biol 61:225-247.

Saint KM, Austin CC, Donellan SC, Hutchinson MN (1998) C-mos, A nuclear marker useful for squamate phylogenetics analysis. Mol Phylogenet Evol 10:259- 263.

Sanderson Mj (2002) Estimating absoultet rates of molecular evolution and divergence times: a penalized likelihood approach. Mol Biol Evol 19:101-109.

Schluter D, Smith JNM (1986) Genetic and phenotypic correlations in a natural- population of song sparrows. Biological Journal of the Linnean Society 29:23-36.

Shaffer HB, Thomson RC (2007) Delimiting species in recent radiations. Syst Biol 56:896-906.

Shimodaira H, Hasegawa M (1999) Multiple comparisons of log-likelihoods with applications to phylogenetic inference. Mol Biol Evol 16:1114–1116.

Sites JW Jr, Crandall KA (1997) Testing species boundaries in biodiversity studies. Cons Biol 11:1289-1297.

Sites JW, Marshall JC (2003) Delimiting species: a Renaissance issue in systematic biology. Trends Ecol Evol 18:462-470.

Slatkin M, Maddison WP (1989) A cladistic measure of gene flow inferred from the phylogenies of alleles. Genetics 123:603-613.

Stejneger L (1899) Description of a new species of spiny-tailed iguana from Guatemala. Proc US Nat Mus 21:381-383.

Stejneger L (1901) On a new species of spiny-tailed iguana from Utila Island, Hondruas. Proc US Nat Mus 23:467-468.

Stockman AK, Bond JE (2007) Delimiting cohesion species: extreme population structuring and the role of ecological interchangeability. Mol Ecol 16:3374-3392.

Swofford DL (2002) PAUP*. Phylogenetic analysis using parsimony (*and other methods). Version 4.0. Sinauer Associates, Sutherland, Massachusetts.

Takahata N (1989) Gene genealogy in 3 related populations – consistency probability between gene and population trees. Genetics 122:957-966.

Toscano MA, Macintrye IG (2003) Corrected western Atlantic sea-level curve for the last 11,000 years based on calibrated 14C dates form Acropora palmata framework and intertidal mangrove peat. Coral Reefs 22:257-270.

Wakeley J (1996) The variance of pairwise nucleotide differences in two populations with migration. Theor Population Biol 49:39-57.

Wakeley J (2008) Coalescent Theory: An Introduction. Roberts & Company Publishers, Greenwood Village, Colorado.

Weins JJ, Penkrot TA (2002) Delimiting species using DNA and morphological variation and discordant species limits in Spiny Lizards (Sceloporus). Syst Biol 51:69-91.

Wu CI (1991) Inferences of species phylogeny in relation to segregation of ancient polymorphisms. Genetics 127:429-435.

Zarza E, Reynoso VH, Emerson BC (2008) Diversification in the northern neotropics: mitochondrial and nuclear DNA phylogeography of the iguana Ctenosaura pectinata and related species. Mol Evol 17:3259-3275.

Appendix Ia. Figures and Tables

Figure I – 2. Gene tree estimates: a. mtDNA, b. C-mos, C. LDHA, and d. PACs. Values above nodes represent posterior probabilities; values below nodes represent bootstrap values. Asterisk indicates haplotypes that were included in the species tree analyses. Value within parentheses indicates the number of sequences used in each analysis. Values outside of parentheses represent geographic location, corresponding to Figure 1 (if no value is indicated the haplotype represents all general locations).

Figure I – 3. C. palearis clade species tree generated from BEST. Posterior probabilities vary slightly from run to run. Therefore the average values after 160 million generations are reported. Topology remains consistent across runs and is identical to the topology found using the MDC and STAR methods.

Figure I - 4. Relationships between the species tree estimate and each gene tree: a. mtDNA, b. C-mos, c. LDHA, and d. PACs.

Figure I - 5. Consensus tree from the partitioned Bayesian concatenated analysis of the C. palearis clade. Values at nodes represent posterior probabilities.

Table I - 1. AMOVA results for C. bakeri, C. melanosterna, C. oedirhina, and C. palearis for five loci independently and then averaged across loci.

Table I - 2. Pairwise ΦST estimates among the four Ctenosaurs species sequenced, calculated for five loci independently and then averages across loci: a) ND4 b) CytB, c) LDHA, d), PACs, e) C-mos, and f) averaged across loci.

Table I - 3. Kimura 2-parameter distance matrix

Appendix Ib. Genbank accession numbers by locus. Localities refer to Figure I - 1 unless otherwise specified.

PART II. GENE FLOW BETWEEN AN ENDANGERED ENDEMIC IGUANA, AND ITS WIDESPREAD RELATIVE ON THE ISLAND OF UTILA, HONDURAS: WHEN IS HYBRIDIZATION A THREAT?

The following section is a slightly modified version of a paper published in the journal Conservation Genetics:

Pasachnik, S. A., B. M. Fitzpatrick, T. J. Near, A. C. Echternacht. 2009. Gene flow between an endangered endemic iguana, and its widespread relative, on the island of Utila, Honduras: When is hybridization a threat? Conservation Genetics 10:1247-1254.

Abstract

The island endemic Ctenosaura bakeri was listed as critically endangered by the

IUCN Redlist Assessment in 2004, seven years after it was recognized as a distinct species. Ctenosaura bakeri occupies a portion of Utila, a small continental island located off the northern coast of Honduras. Habitat destruction and over-harvesting are among the top threats facing this species. In addition, morphological evidence of hybridization was recently documented, raising the concern that gene flow from the common and widely distributed C. similis could threaten the genetic distinctiveness of C. bakeri. We show that hybridization occurs only at low levels and is not a current threat to C. bakeri. All ctenosaurs captured for this study were identified to species level without difficulty; none had intermediate or mosaic phenotypes. Sequence analysis of mitochondrial and nuclear markers revealed only two individuals with introgressed genotypes.

Molecular analysis of the previously described hybrid showed it to be heterozygous for C. bakeri and C. similis alleles. Hybridization between these two species is possible and occurs occasionally in the wild, and the rate of hybridization could increase if habitat destruction or changes in relative abundance increase the probability of interbreeding. However, the level of gene 59

flow indicated by current data is too low to threaten C. bakeri with genetic swamping or deleterious fitness effects.

Introduction

Natural hybridization is not intrinsically undesirable and may even enhance mean population fitness and responsiveness to natural selection (Arnold 2006,

Fitzpatrick and Shaffer 2007a). However, interspecific hybridization in nature presents several challenges for conservation management when it occurs because of anthropogenic factors or when one of the species involved is protected (Rhymer and Simberloff 1996, Allendorf et al. 2001). Hybridization can be a direct biological threat if it reduces population viability owing to the introduction of alleles that are maladaptive in the local environment or genetic background (Reisenbichler and Rubin 1999, Allendorf and Luikart 2007). Gene flow between protected and non-protected taxa also creates difficulty in defining and distinguishing protected from unprotected individuals or populations thus complicating management decisions (O'Brien and Mayr 1991, Allendorf et al.

2001, Haig et al. 2004, Fitzpatrick and Shaffer 2007b). Thorough genetic analysis of wild populations is therefore necessary to guide conservation decisions. In this paper, we investigate the potential for hybridization and gene flow between the critically endangered island endemic, Ctenosaura bakeri, and its widespread relative, C. similis.

The Utila Spiny-Tailed Iguana, C. bakeri (Stejneger 1901), along with three other species (C. palearis, C. oedirhina, and C. melanosterna), makes up a recent radiation of narrow range insular and mainland endemics, occurring in

Honduras and Guatemala. Ctenosaura palearis was the first species of this group to be described (Stejneger 1899), and C. bakeri was later distinguished from this species based on scutellation of the tail, dewlap size, and dorsal crest coloration (Bailey 1928, de Queiroz 1987, 1990). In addition, more recent morphological and molecular work based on RAPDs (Köhler et al. 2000) and sequence data (SAP unpublished data) supports this delimitation.

Ctenosaura bakeri is endemic to the small island (41 km2) of Utila, the most westerly of the Bay Islands (86° 56’ N; 16° 06’ W), which are located 15-50 km off the Caribbean versant of Honduras (McCranie et al. 2005). C. similis occupies lowland mainland habitats from the Isthmus of Tehuantepec in Mexico to Panama; and specifically within the Bay Islands is found on both Utila and

Guanaja, the most easterly of the Bay Islands (McCranie et al. 2005).

Preliminary data concerning the molecular phylogeography of C. similis suggest that the population occurring on Utila is not distinct from that on the adjacent mainland (SAP unpublished data). In recent years the Bay Islands and Utila in particular have experienced extensive anthropogenic development, which threatens the native flora and fauna through habitat destruction, introduction of non-native species, and pollution. Additionally, over-harvesting of iguanas persists owing to the lack of environmental protection and enforcement.

In 1994 the Honduran government designated C. bakeri as ‘in need of protection’ and in 2004 C. bakeri was listed as critically endangered by the IUCN

Red List Assessment (Zoerner and Köhler 2004). The latter listing was due primarily to its limited geographic range, increased habitat modification and destruction, and over-harvesting of adults and eggs. Ctenosaura bakeri is a charismatic and unique species that has been the subject of substantial conservation effort, including a captive breeding program, education, and community outreach. A recent report of hybridization between C. bakeri and its wide ranging congener, C. similis (Köhler and Blinn 2000), raises the concern that these conservation efforts will be in vain if C. bakeri is displaced via genetic swamping or suffers reduced fitness due to hybrid dysfunction or dilution of important adaptations.

Hybridization between C. bakeri and C. similis was first reported in 2000 when a freshly killed gravid female (Natur-Museum und Forschung-Institut

Senckenberg [SMF] 78870) was brought to the Iguana Research and Breeding

Station (IRBS) on Utila and identified as a hybrid on the basis of morphology

(Köhler and Blinn 2000). Eggs rescued from this female were artificially incubated, resulting in two viable hatchlings. Coloration and scale characteristics of these hatchlings were intermediate between C. bakeri and C. similis. One of these hatchlings was crossed with C. bakeri and fertile offspring were produced (pers. comm. Lutz Dirksen). In addition, Aurel Heidelberg (pers. comm.) informs us that ctenosaurs that were thought to be hybrids on the basis

of morphological characteristics have been observed since the original documentation by Köhler and Blinn (2000).

Historically, Ctenosaura bakeri has been said to thrive primarily in mangrove habitats where they seek refuge in hollows in the larger trees (Gutsche

2005). Zoerner and Köhler (2004) reported that these forests encompass only 8

2 km of the island. Because of the vast destruction of the mangrove habitat, C. bakeri has been displaced and is now often found in dry open areas (Pasachnik

2006). The wide-ranging species, C. similis, prefers dry open areas (Lee 1996,

Savage 2002, Campbell 1998, Köhler et al. 2006), though there are some records of C. similis in other habitats (Stafford and Meyer 2000) throughout its range. It is possible that the destruction of C. bakeri habitat and expansion of C. similis habitat have created new opportunities for contact and gene flow. In addition, contact between the two species appears most extensive in two areas where there have been extensive anthropogenic changes. The first is an abandoned residential foundation where both species can be found in holes in the cinder block walls. The second is a bed-and-breakfast situated at the edge of a mangrove stand. The proprietor feeds wild ctenosaurs daily and both species can be observed in large numbers. These situations may provide new opportunities for the production and survival of hybrids (e.g., Blair 1941,

Anderson 1948, Anderson and Stebbins 1954, Lewontin and Birch 1966,

Seehausen et al. 1997, Arnold 2006).

With the destruction of mangrove habitats and declining numbers of C. bakeri on Utila, extensive gene flow from C. similis could lead to "genetic

swamping" where C. bakeri alleles at many genes are replaced by C. similis alleles (Rhymer and Simberloff 1996, Allendorf et al. 2001). Introgression of C. bakeri alleles could also affect the genetic makeup of C. similis, however the conservation concern is not as great in this case as this species has a wide distribution throughout Mexico and Central America. The elimination of unique characters of C. bakeri, potentially including adaptations to mangrove habitats, could be detrimental to the preservation of this endangered species. However, the effects of a low level of gene flow (e.g., fewer than one hybridization event per generation [Wright 1931]) would be negligible, except for universally advantageous alleles (Barton 1979).

Methods

Several strategies for evaluating the possibility of hybridization have been used in different contexts (Arnold 2006). We used the joint distribution of field identification characters to assess whether the Ctenosaura on Utila exist as two distinct phenotypic clusters, as a mixed array of individuals with diverse character combinations, or as clusters with a minority of intermediate or mosaic morphologies. We then compared mitochondrial and nuclear haplotype distributions between morphologically identified C. bakeri and C. similis to determine whether or not those two groups could be interpreted as distinct, isolated gene pools. Finally, DNA sequences from the putative natural hybrid

housed at IRBF were examined to test whether she had a mixture of C. bakeri and C. similis alleles.

Field Identification. A total of 599 ctenosaurs were opportunistically captured on

Utila, Islas de la Bahia, Honduras during the summer of 2005, the spring and summer of 2006, and the summer of 2007. Individuals were collected from the entirety of the island with the exception of the interior on the western side of the canal, as it consists of unsuitable swamp habitat. Upon capture a digital photograph was taken and snout-vent length, tail length and weight were recorded. All individuals were morphologically evaluated for three characters that are typically used to distinguish between C. bakeri and C. similis (pers. obs.

A.C.E. and S.A.P., McCranie et al. 2005, Köhler 2003): (1) Color: C. bakeri is blue to light gray to black, C. similis is a light brownish gray (green on juveniles);

(2) Pattern: C. bakeri may have indistinct crossbands present on the dorsum, C. similis has distinct crossbands with a pale center along the dorsomedial line; and

(3) Scalation: C. bakeri has one row of intercalary scales between the third and fifth tail whorls, C. similis has two intercalary scale rows. A unique mark was given to each individual for future mark-recapture population estimates and to avoid re-sampling from year to year. A one cm section of the tail tip was removed and stored in 100% ETOH for molecular analysis. Pressure was applied to the wound until bleeding ceased and the area was sealed with a topical skin adhesive to prevent infection.

DNA sequencing. Sequence data were collected from a subset of specimens ranging throughout the entire island of Utila (Fig.1) and from the previously documented hybrid (progeny of SMF 78870). We sequenced 64 C. bakeri and

25 C. similis for the mitochondrial marker ND4, 61 C. bakeri and 25 C. similis for the nuclear marker LDHA, and 24 C. bakeri and 11 C. similis for the nuclear gene

PACs. Both of the nuclear markers are in non-coding 3’ UTRs. All sequences have been registered on Genbank (EU268007-EU268017, EU271874-

EU271881).

Sample processing, sequencing and sequence analysis was performed at the University of Tennessee with the exception of some samples which were sent to Yale University for sequencing. Genomic DNA was extracted using the

Qiagen DNeasy extraction kit (Qiagen, Valcencia, CA). The manufacturer's protocol was modified only by extending the cell lysis step (using Proteinase K) to at least 15 hours. Iguana iguana tissue samples were taken from a captive colony at the University of Tennessee for use as an outgroup. Blood samples from Amblyrhynchus cristatus were obtained from Scott Glaberman and Adalgisa

Caccone at Yale University for use as an additional outgroup. Outgroup choice was based on phylogenetic proximity (Norell and de Querioz 1991, Sites et al.

1996, Rassmann 1997, Wiens and Hollingsworth 2000, Hollingsworth 2004).

DNA extraction procedures for blood follow that of the Qiagen DNeasy manufacturer’s protocol.

The polymerase chain reaction (PCR) was used to amplify one portion of the mitochondrial genome (674 bp of NADH dehydrogenase subunit 4) and two

nuclear loci: 418 bp of Lactate dehydrogenase A (LDHA) and 569 bp of polymerase alpha catalytic subunit (PACs). The ND4 fragment was amplified using primers ND4 (Sites et al. 1996) and ND4R1 (5´–

CGAAACACCTCTCGGTTTGC–3´) developed specifically for ctenosaurs from data in Sites et al. (1996). The LDHA fragment was amplified using primers

LDHA1 (5´–AGCCTGGTCTCCTGTCAT–3´) and LDHA2 (5´–

GCAGCAGTGTTGGGAAAAAT–3´) developed from Iguana iguana sequence data (Hsu and Li unpublished data; AY130249). The PACs fragment was amplified using primers PACs1 (5´–AGACTTTGCTCCGGGGTATT–3´) and

PACs2 (5´–CTTTCCCCTCCCAAACAAAC–3´), developed from sequence data for Iguana iguana (Iwabe et al. 2005; AB178527). Amplifications for all fragments were conducted in a total volume of 25 µl using: 2.5 µl MgCl2, 2.5 µl

10X buffer, 2.0 µl dNTPs, 1.25ul forward primer, 1.25 µl reverse primer, 0.25 µl

Taq polymerase, 12.25 µl ddH2O, and 3.0 µl DNA template.

PCR cycling for the mitochondrial fragment was performed using the following conditions: denaturation at 94 ºC for 3 min., followed by 30 cycles at 94

ºC for 30 seconds, 50 ºC for 30 seconds, 72 ºC for 90 seconds, and final extension at 72 ºC for 5 minutes. PCR cycling for the two nuclear fragments was performed using the following conditions: denaturation at 94 ºC for 3 minutes, followed by 30 cycles at 94 ºC for 30 seconds, 60 ºC for 30 seconds, 72 ºC for 90 seconds, and final extension at 72 ºC for 5 minutes. PCR products were verified by gel electrophoresis and successful amplicons were purified using either

exonuclease I/shrimp alkaline phosphatase (ExoSap) or a QIAquick PCR purification kit (Qiagen, Valencia, CA).

Sequencing reactions were performed using original PCR primers.

Forward and reverse sequences for each template were aligned using

Sequencher 4.6 (Gene Code Corporation). Ambiguous base calls were verified manually by examining the electropherograms for the forward and reverse reads.

Sequence alignment was verified using MacClade 4.07 (Maddison and Maddison

2005) with the aid of published sequences from Genbank for Iguaninae. A few

LDHA and PACs sequences had heterozygous sites. Levels of heterozygosity, however, were relatively low and haplotypes could be determined unambiguously. LDHA had two species-specific indels. Ctenosaura bakeri consistently had five fewer bp than C. similis and two fewer than I. iguana.

Sequence analysis. The program DNAsp 4.10.9 (Rozas et al. 2003) was used to collapse redundant haplotypes. Haplotype trees were constructed using maximum likelihood (ML) and Bayesian analyses with each locus analyzed separately. ML analysis was conducted using Paup* 4.0 (Swofford 2002) using a heuristic search with 1000 random-taxon-addition replicates. Confidence at each node was assessed using nonparametric bootstrapping (Felsenstein 1985) based on 100 pseudo-replicates with 10 random-taxon-addition replicates per pseudo-replicate. The optimal model of sequence evolution for each locus was determined in Modeltest 3.7 (Posada and Crandall 1998). Bayesian posterior probabilities were estimated using MrBayes 3.1 (Ronquist and Huelsenback

2003) with four Markov chains, the temperature profile at the default setting of

0.2, run for 2 million generations and sampling every 100th generation with a final burnin of 10000 generations.

We compared haplotype distributions between morphologically described groups and used the estimated haplotype trees to examine the genealogical concordance of the three markers. To provide a numerical evaluation of the potential for gene flow, we used allele frequencies to estimate FST between C. bakeri and C. similis following Weir (1996). While other analyses could be implemented in cases of extensive hybridization, the simplicity of our results (see below) makes additional analyses unnecessary to address the question of whether hybridization with C. similis is likely to have significant effects on the C. bakeri gene pool.

Results

Field Identification. Visual identification of morphological characters did not reveal intermediate states between C. bakeri and C. similis for any of the 599 ctenosaurs captured within the time frame of this study. A total of 496 C. bakeri and 103 C. similis from the island of Utila were visually consistent in coloration, pattern, and intercalary tail whorls with the character states described and seen in photographs in standard field guides (Köhler 2003, McCranie et al. 2005).

Intermediate or mosaic character combinations were not observed. Additionally,

coloration, pattern and intercalary tail whorls observed in C. similis from Utila were consistent with those observed in C. similis on the adjacent mainland of

Honduras (SAP pers obs).

Sequence Analysis. ND4 sequence data obtained for 89 opportunistically collected ctenosaurs revealed seven unique haplotypes. Haplotypes 1- 6 were found primarily within C. bakeri; these haplotypes are very similar to one another and form a strongly supported group in the haplotype tree (Fig. 2A). Haplotype 7 was found primarily within C. similis and is very distinct from all other haplotypes

(Fig. 2A). Only one C. similis (of 25) did not have haplotype 7; this individual had

ND4 haplotype 1, one of the two most common C. bakeri haplotypes (Table 1).

Likewise, only one C. bakeri (of 64) did have haplotype 7 (Table 1). Thus, the morphologically identified C. bakeri and C. similis corresponded to two genealogically distinct groups of ND4 haplotypes with the exception of two out of

89 individuals. This may indicate initial misidentification or past hybridization events.

The LDHA sequence data obtained from 86 opportunistically collected ctenosaurs revealed two haplotypes in C. bakeri and four in C. similis (Fig. 2B).

Twenty five morphologically identified C. similis and 61 C. bakeri were sequenced. Molecular data were consistent with morphological data for all individuals including those that showed discordance in the ND4 analysis (Table

1). This supports the hypothesis of past introgression and not initial misidentification.

A subset of individuals (11 C. similis and 24 C. bakeri) was sequenced for an additional nuclear marker PACs. Molecular and morphological data were consistent for all individuals (Table 1). Phylogenetic analysis shows one haplotype in C. bakeri and two in C. similis for this marker (Fig. 2C). The smaller

PACs data set reinforces the agreement between morphological and molecular data (Table 1).

Reciprocal monophyly of the gene trees (with the two exceptions noted) indicates that most of the DNA variation within species is caused by mutation rather than gene flow between species. Because FST is decreased by both mutation and gene flow (Weir 1996), the best way to estimate gene flow (Nm the average number of "immigrants" or number of individuals contributing to the other species' gene pool per generation) is to first factor out the variation caused by mutation. In this case, it was simple to categorize haplotypes as "similis alleles" or "bakeri alleles" and estimate FST using a two-allele model for each marker.

This yields estimates of FST = 0.9522 for mtDNA, and FST = 1.0 for each nuclear marker for an overall average of 0.984. The corresponding estimate of Nm =

0.004, thus, an average of approximately 4 hybrid matings every thousand generations is estimated.

Sequence data for two nuclear markers, LDHA and PACs, and one mitochondrial marker, ND4, were collected for the offspring of the putative hybrid,

SMF 78870. The LDHA and PACs nuclear sequence data show that all sites distinguishing C. bakeri and C. similis were heterozygous (Fig. 3), indicating that this individual is indeed a hybrid between C. bakeri and C. similis. The

mitochondrial sequence data shows this individual’s maternal lineage to be C. bakeri.

Discussion

Our analysis of distinguishing morphological characters and DNA sequence data show that Ctenosaura bakeri and C. similis are morphologically and genealogically distinct and nearly completely reproductively isolated. Rare instances of genealogical discordance and marker heterozygosity of a putative natural hybrid indicate that fertile hybrids are occasionally produced in the wild.

The level of gene flow consistent with these observations is far too low to present a threat to the distinctiveness of C. bakeri. However, the possibility that hybridization may increase owing to future destruction of habitat justifies continued genetic monitoring of ctenosaurs on Utila.

Hybridization has been regarded as a complicating factor and even a threat in conservation contexts (O'Brien and Mayr 1991, Rhymer and Simberloff

1996, Allendorf et al. 2001, Allendorf & Luikart 2007); however, it also may play an important role in evolutionary processes in both plants and animals (Arnold

2006). To present a credible threat, hybridization must in some way reduce the viability of a population or result in the replacement of a protected taxon by a less desirable admixture. Both effects are dependent upon on a high degree of gene flow. Genetic swamping by foreign alleles that have no effect on fitness is unlikely when the number of immigrants per generation (Nm) is less than 1

(Wright 1931). Alleles causing local maladaptation or hybrid dysfunction would

affect C. bakeri only if gene flow is also large relative to the strength of selection

(e.g., Lenormand 2002). Thus, even if our estimate of gene flow (Nm = 0.004) is off by a factor of 100, hybridization with C. similis is unlikely to have a substantial effect on C. bakeri. This conclusion is supported by the absence (in a sample of

599) of individuals with intermediate or mosaic morphological characteristics.

From the molecular evaluation of the putative hybrid described by Köhler and Blinn (2000) and the fact that she produced viable offspring in captivity, we know that fertile hybrids can be produced when C. bakeri and C. similis mate.

One may thus speculate that the frequency of hybrids would increase if the frequency of interspecies matings were to increase or if ecological conditions favoring hybrid genotypes were to become widespread. Habitat disturbance can have the effect of breaking down barriers to interbreeding and/or generating an array of potential "hybrid niches" (Anderson 1948). While the two wild-caught individuals with introgressed genotypes were sampled from disturbed habitats

(described in the introduction), we have no statistical power to support a proposition that hybrids are more likely to be encountered in disturbed areas than in pristine areas.

Ctenosaura bakeri is listed as critically endangered by the IUCN and as in need of protection by the Honduran government because this species requires two rapidly disappearing habitats on Utila. Adults depend on mature red, black and white mangrove forest habitats for food and retreat sites, and relatively undisturbed sandy beaches for nesting (Zoerner and Köhler 2004). As this optimal habitat is destroyed, ecological interactions with C. similis may contribute

to the decline of C. bakeri if competitive interactions prevent the latter from using a broader range of habitats. Although concerns over a genetic threat from hybridization are not supported by our research, increased habitat destruction could increase the potential for hybridization. Thus, it seems clear that conservation efforts should focus on preservation and restoration of mangrove stands and nesting beaches in order to combat both direct and indirect affects of this destruction and to improve the chances of persistence for C. bakeri.

Literature Cited

Allendorf FW, Luikart G (2007) Conservation and the genetics of populations. Blackwell Publishing, London.

Allendorf WF, Leary RF, Spruell P, Wenburg JK (2001) The problem with hybrids: setting conservation guidelines. Trends Ecol. Evol. 16:613-622.

Anderson, E (1948) Hybridization of the habitat. Evolution 2, 1-9.

Anderson E, Stebbins GL (1954) Hybridization as an evolutionary stimulus. Evolution 8:378-388.

Arnold ML (2006) Evolution through genetic exchange. Oxford University Press, London.

Barton NH (1979) Gene flow past a cline. Heredity 43:333-339.

Blair AP (1941) Variation, isolating mechanisms, and hybridization in certain toads. Genetics 26:398-417

Bailey JW (1928) A revision of the lizards of the genus Ctenosaura. Proc. U.S. Nat. Mus. 73:1-69.

Campbell JA (1998) Amphibians and reptiles of northern Guatemala, the Yucután, and Belize. University of Oklahoma Press, Norman. de Queiroz K (1987) A new spiny-tailed iguana from Honduras, with comments on relationships within Ctenosaura (Squmata: Iguania). Copeia 1987:892-902. de Queiroz K (1990) Catalogue of American Amphibians and Reptiles.: Ctenosaura bakeri. Society for the Study of Amphibians and Reptiles.

Felsenstein J (1985) Confidence-limits on phylogenies – an approach using the bootstrap. Evolution 39:783-791.

Fitzpatrick BM, Shaffer HB (2007a) Hybrid vigor between native and introduced salamanders raises new challenges for conservation. Proc. Nat. Acad. Sci., USA 104:15793-15798.

Fitzpatrick BM, Shaffer HB (2007b) Introduction history and habitat variation explain the landscape genetics of hybrid tiger salamanders. Ecol. App. 17:598- 608.

Gutsche, A (2005) Distribution and habitat utilization of Ctenosaura bakeri on Utila. IGUANA 12:143-151.

Haig SM, Mullins TD, Forsman ED, Trail PW, Wennerberg L (2004) Genetic identification of spotted owls, barred owls, and their hybrids: legal implications of hybrid identity. Cons. Biol. 18:1347-1357.

Hollingsworth BD (2004) The evolution of iguana: An overview of relationships and a checklist of species. In: Iguanas: Biology and Conservation. Alberts AC, Carter RL, Hayes WK, Martins (eds), pp. 19-34. University of California Press, Berkeley.

Iwabe N, Hara Y, Kumazawa Y, Shibamoto K, Saito Y, Miyata T, Katoh K (2005) Sister group relationships of turtles to the bird-crocodilian clade revealed by nuclear DNA-coded proteins. Mol. Biol. Evol. 22:810-813.

Köhler G, Schroth W, Streit B (2000) Systematics of the Ctenosaura group of lizards (Reptilia: Sauris: Iguanidae). Amphibia-Reptilia 21:177-191.

Köhler G (2003) The reptiles of Central America. Herpeton, Verlag Elke Köhler, Offenbach, Germany.

Köhler G, Blinn E (2000) Naturliche Bastardierung zwischen Ctenosaura bakeri und Ctenosaura similis auf Utila, Honduras. Salamandra 36:1-3.

Köhler G, Vesely M, Greenbaum E (2006) The amphibians and reptiles of El Salvador. Krieger Publishing Company, Malabar, Florida.

Lee JC (1996) The amphibians and reptiles of the Yucután Peninsula. Comstock Publ. Assoc., Cornell Univ. Press, Ithaca, New York.

Lenormand T (2002) Gene flow and the limits to natural selection. Trends Ecol. Evol. 17:183-189.

Lewontin RC, Birch LC (1966) Hybridization as a source of variation for adaptation to new environments. Evolution 20:315-336.

Maddison DR Maddison WP (2005) MacClade 4 release version 4.07 for OSX. Sinauer Associates, Inc. Sunderland, Massachusetts.

McCranie JR, Wilson LD, Köhler G (2005) Amphibians and reptiles of the Bay Islands and Cayos Cochinos, Honduras. Bibliomania, Salt Lake City, Utah, USA.

Norell MA, de Queiroz K (1991) The earliest Iguanine lizard (Reptilia: Squamata) and its bearing on Iguanine phylogeny. Am. Mus. Novit. No. 2997.

O’Brien SJ, Mayr E (1991) Bureaucratic mischief: Recognizing species and subspecies. Science 251:1187-1188.

Pasachnik SA (2006) Ctenosaurs of Honduras: Notes from the field. IGUANA 13:264-271.

Posada D, Crandall KA (1998) Modeltest: testing the model of DNA substitution. Bioinformatics 14:817-818.

Rassmann K (1997) The evolutionary age of the Galapagos iguanas predates the age of the present Galapagos Islands. Mol. Phylogenet. Evol. 7:158-172.

Reisenbichler RR, Rubin SP (1999) Genetic changes from artificial propagation of Pacific salmon affect the productivity and viability of supplemented populations. ICES J. Mar. Sci. 56:459-466.

Rhymer JM, Simberloff D (1996) Extinction by hybridization and introgression. Annu. Rev. Ecol. Syst. 27:83-109.

Ronquist F, Huelsenback JP (2003) MRBAYES 3: Bayesian phylogenetics inference under mixed models. Bioinformatics 19:1572-1574.

Rozas J, Sanchez-Delbarrio JC, Messeguer X, Rozas, R (2003) DnaSP, DNA polymorphism analysis by the coalescent and other methods. Bioinformatics 19:2496-2497.

Savage JM (2002) The amphibians and reptiles of Costa Rico: a herpetofauna between two continents, between two seas. University of Chicago Press, Chicago, Illinois.

Seehausen O, van Alphen JJM, Witte F (1997) Cichlid fish diversity threatened by eutrophication that curbs sexual selection. Science 277:1808-1811.

Sites JWJr, Davis SK, Guerra T, Iverson JB, Snell HW (1996) Character congruence and phylogenetic signal in molecular and morphological data sets: A case study in the living iguanas (Squamata, Iguanaidae). Mol. Biol. Evol. 13:1087-1105.

Stafford PJ, Meyer JR (2000) A guide to the reptiles of Belize. The Natural History Museum, London and Academic Press, New York.

Stejneger L (1899) Description of a new species of spiny-tailed iguana from Guatemala. Proc. U.S. Nat. Mus. 21:381-383.

Stejneger L (1901) On a new species of spiny-tailed iguana from Utila Island, Honduras. Proc. U.S. Nat. Mus. 23:467-468

Swofford DL (2002) PAUP*. Phylogenetic analysis using parsimony (*and other methods). Version 4.0. Sinauer Associates, Sutherland, Massachusetts.

Weir BS (1996) Genetic data analysis II. Sinauer Associates, Inc. Publishers, Sunderland, Massachusetts.

Wiens JJ, Hollingsworth BD (2000) War of the iguanas: conflicting molecular and morphological phylogenies and long branch attraction in iguanid lizards. Syst. Biol. 49:143-159.

Wright S (1931) Evolution in Mendelian populations. Genetics 16:97-159

Zoerner S, Köhler G (2004) Ctenosaura bakeri. In: IUCN 2006. 2006 IUCN Red List of Threatened Species. www.iucnredlist.org. Downloaded on 16 August 2007.

Appendix IIa. Figures and Tables

Figure II - 2. Consensus phylograms of Ctenosaura bakeri and C. similis haplotypes, from Utila, Honduras. A) ND4, B) LDHA, C) PACs. Numbers before nodes indicate bootstrap support from Maximum Likelihood analysis and posterior probabilities from Bayesian analyses. Amblyrhynchus critatus was used as the outgroup.

Figure II - 3. Examples of heterozygous sites in A) LDHA and B) PACs nuclear genes for Ctenosaura bakeri, C. similis, and the putative hybrid described by Köhler and Blinn (2000) from Isla Utila, Honduras.

Table II - 1. Distribution of ND4, LDHA and PACs Ctenosaura bakeri and C. similis haplotypes from Utila, Honduras. Haplotype numbers correspond to Figure II - 2.

PART III. POPULATION GENETICS OF CTENOSAURA MELANOSTERNA: IMPLICATIONS FOR CONSERVATION AND MANAGEMENT

The following section is a slightly modified version of a paper that has been submitted to the journal Diversity and Distributions.

Abstract

In conservation, difficult decisions concerning prioritization of different geographic areas must be made. Large-scale prioritization methods such as defining biodiversity hotspots and crisis ecoregions have paved the way, however, these efforts then need to be localized. Various approaches have been taken, such as defining evolutionarily significant units (ESUs), management units, and core habitat areas within the range of a taxonomic species. These units can then be ranked as candidates for conservation, with the goal of preserving a given species by protecting only a subset of populations. Here we use a combination of

AFLPs and DNA sequence data to elucidate the relationships within and among populations of the spiny tailed iguana, Ctenosaura melanosterna, throughout its range in Honduras. Our findings indicate that there are two ESUs corresponding to geographically and ecologically distinct island and mainland habitats.

Management strategies consisting of translocation or captive breeding and release should not consider the island and mainland populations exchangeable.

In addition, the narrow geographic range of each group suggests that no region or subpopulation is likely expendable. This study demonstrates a situation, most likely increasingly common in conservation, in which it seems that only the high priority areas remain.

Introduction

We are in the midst of an extinction crisis, in which biodiversity is being lost at a rate that greatly exceeds that of the natural rate at which species have gone extinct throughout time (e.g. Pimm et al. 1995, Myers and Knoll 2001, Wake and

Vrendenburg 2008). Habitat destruction, overexploitation, pollution, invasive species, disease and climate change are among the top threats to biodiversity.

The development and enforced protection of designated areas, and programs for captive breeding and re-introduction, are among the top means by which conservation biologists combat this loss. In principle, and given the limited amount of funding available for such conservation initiatives, these efforts should be prioritized so as to maximize what is protected.

Large-scale methods of prioritizing areas in order to protect the greatest amount of biodiversity have been developed using the criteria of vulnerability and irreplaceability. These methods include the development of biodiversity hotspots

(Myers et al. 2000), crisis ecoregions (Hoekstra et al. 2005), last of the wild

(Sanderson et al. 2002), and high biodiversity wilderness areas (Mittermeier et al.

2003) to name a few (see Brooks et al. 2006 for a complete review). Controversy has been raised over these various methods of prioritization due to confusion over their criteria, resulting in target maps that overlap as little as one-tenth of each other (Brooks et al. 2006). In addition, these methods have been criticized for not incorporating clear guidance on a local scale and thus for inherent weakness when applied to the implementation of conservation actions on the ground (Mace 2000, Brummitt and Lughadha 2003). 86

In practice, decisions regarding reserve establishment center around flagship or charismatic threatened species (Caro et al. 2004), and a variety of socioeconomic factors (Davis 2005, Stewart and Possingham 2005). Even so, two questions should be addressed in these cases so that funds are allocated in the most effective way. First, are the individuals to be protected representative of the target species or will a given reserve system fail to protect an irreplaceable component of the group’s evolutionary diversity? And second, are the populations to be protected viable in the long term or will efforts be wasted by setting aside marginal sites that are not likely to be self-sustaining?

To address the first question, conservation biologists have developed concepts like distinct population segments (DPS, as defined under the

Endangered Species Act [ESA]) and evolutionarily significant units (ESU's –

Ryder 1986, Waples 1991, Dizon et al. 1992, Mortiz 1994, Crandall et al. 2000).

Protecting such variation might be important for aesthetic or cultural reasons, but also for preserving the evolutionary processes that create diversity (Ryder 1986,

Waples 1991, Crandall et al. 2000). Thus, focusing on intraspecific variation, or the preservation of multiple populations, by defining these units is a vital component to conservation and management, and is critical to the long-term persistence of a species (Hughes et al. 1997, Hobbs and Mooney 1998, Luck et al. 2003, Avise 2005). Though there is ample evidence for this, there are still issues surrounding how to define and identify these intraspecific units (Woinarski and Fisher 1999).

In 1986 Ryder proposed that evolutionarily significant unit (ESU) status should be given to populations that represent significant adaptive variation based on concordance between data sets, such as natural history, distribution and genetics, and that gene flow should be considered and protected. Under the ESA protection can be granted to DPSs. The definition of a DPS is, however, unclear.

In 1991 Waples proposed that DPSs be equivalent to ESUs, and two criteria were given: populations must have been reproductively isolated and be adaptively distinct, thus representing distinct components of an “evolutionary legacy.” These criteria, however, may restrict each other because if reproductive isolation is ensured, the creative role that gene flow may provide in adaptive distinctiveness is eliminated and thus some evolutionary potential may not be protected.

In 1994 another framework was proposed, which stated that populations must be reciprocally monophyletic for mtDNA and show significant divergence at nuclear loci in order to be given ESU status (Moritz 1994, Moritz and Cicero

2004). This approach focuses on neutral loci and thus ignores adaptive differences in favor of protecting history. Under this framework small populations that have been greatly affected by a bottleneck, for example, might be the ones that are given ESU status. In addition, the evolutionary process will not necessarily be protected because of the explicit focus on phylogeographic history rather than local adaptation and gene flow. Similarly, groups that have gone through rapid diversification will not necessarily be given the chance to persist independently under this framework.

Crandall et al. (2000) proposed criteria for ESUs that focus on genetic and ecological exchangeability in the past and present, emphasizing a continuum of possibilities. ESU status comes from rejecting exchangeability, but there is a continuum of management recommendations depending on the combination of ecological and genetic outcomes in both a historical and recent setting. A difficultly with this concept is that ecological exchangeability is rarely testable by direct experimentation. This framework does, however, focus on adaptive differences and evolutionary potential, and acknowledges the importance of gene flow in management.

A common problem in defining ESUs is that too few or too many populations receive status, which is due in part to the many definitions. Waples

(2006) reviewed the various definitions in the context of Pacific salmon

(Oncorhynchus spp.; Salmonidae). He concluded that they are problematic as his review resulted in either one or hundreds of ESUs depending on the criteria used. Thus, he called for additional studies using empirical data. The subjectivity of the different definitions is problematic, but identifying what is likely to be lost versus maintained, and evaluating alternative management strategies must be the overall goals of conservation science.

The objective of the research herein is to understand the genetic structure of the spiny tailed iguana, Ctenosaura melanosterna, including potentially adaptive differences, within and among its remaining populations, which are subject to varying levels of protection. We use mtDNA and AFLP data to test whether populations are genetically exchangeable and evaluate whether there is

evidence of recent demographic instability (which might imply problems with population viability over and above the overt anthropogenic threats (Finn et al.

2009)).

Study System. Ctenosaura melanosterna is a medium sized spiny tailed iguana

(200-350 mm snout vent length) that is primarily herbivorous though opportunistically carnivorous in some life stages (Köhler 2003, Gutsche 2005,

McCranie et al., 2005). The species is endemic to Honduras and occurs within approximately 1316 km2 of arid tropical scrub forest in the Valle de Aguán (north central mainland) and on two islands of the Cayos Cochinos Archipelago (Cayos

Pequeño and Cayos Grande). It occurs, therefore, in the Central American biodiversity hotspot described by Myers et al. (2000) and in a crisis ecoregion as described by Hoekstra et al. (2005). Buckley and Axtel described C. melanosterna in 1997 on the basis of morphology and geography. The population in the Valle de Aguán was first noted in 1966 and assigned to

Enyaliosaurus palearis (Echternacht 1968).

The island and mainland populations of this species are separately listed as Critically Endangered by the IUCN Red List Assessment (2010) based on limited geographic range, increased habitat fragmentation and destruction, and over-harvesting of adults and eggs. Wilson and McCranie (2004) have declared

C. melanosterna as one of the top four most ecologically vulnerable species in

Honduras. This species has also been accepted for CITES Appendix II listing due to the threats posed by the international pet trade and its similarity to C.

palearis. Considerable variation exists however, between, and in some cases within, the mainland and the island regions in terms of threats and protection.

The two islands of the Cayos Cochinos Archipelago are within the Cayos

Cochinos Natural Marine Reserve (CCANMR) administered by the Honduran

Coral Reef Foundation (HCRF). Though both islands are technically protected,

Cayos Pequeño gains additional protection through the presence of the HCRF research station. Cayos Grande has a small village and tourist resort on it and thus has increased threats due primarily to harvesting and feral dogs and cats

(SA Pasachnik, CE Montgomery pers. obs.). The populations on the mainland have little to no local protection and a higher threat level. There is a population of

C. melanosterna that occurs within Pico Bonito National Park in the Valle de

Aguán; however, this population is not afforded much protection due to a lack of policing in the area. In addition, the populations in the Valle de Aguán as a whole are threatened by large-scale habitat destruction and fragmentation, feral dogs and cats, and harvesting of adults and eggs. Harvesting is greatly increases in this areas due to a festival that celebrates the consumption of this species.

Given the extreme nature of the threats to the Valle de Aguán populations, it will be difficult for C. melanosterna to persist if the current rates of habitat destruction and consumption continue. Increasing the level of protection on the mainland will be no easy task. Thus, understanding the urgency of this action is important. Protection is already in place for the Cayos Cochinos populations

(though it does vary between islands). Thus the question becomes, is the species adequately conserved if the Valle de Aguán population is allowed to go

extinct and C. melanosterna persists only on the Cayos Cochinos? If iguanas in the two regions are genetically distinct and locally adapted, this lack of exchangeability supports the need for increased protection of the Valle de Aguán populations.

As part of an ongoing project characterizing the distribution of C. melanosterna within the Valle de Aguán (SA Pasachnik pers. obs.), the habitat has been surveyed for a variety of characteristics. The dominant tree species is

Acacia riparia (Leguminosae). Other abundant plants in the region include:

Opuntia sp., Stenocereus sp. (Cactaceae), and to a lesser extent Hematoxylum brasileto (Caesalpiniaceae), all of which are eaten by C. melanosterna. The average height among sites of the maximum emergent tree is 12m and the average height of the canopy is 5m. Deforestation as well as soil and water contamination is very high in these areas due to local agricultural activity associated with cattle farming and the presence of a large Dole fruit plantation

(see Figure 1 and Appendix I for photos).

Bermingham et al. (1998) conducted a survey of Cayos Cochinos

Pequeño over a four-day visit in 1995. During this time, a preliminary inventory of the flora and a characterization of the different vegetation types were conducted.

The dominant vegetation type found was evergreen oak forest, which is estimated to cover approximately 50% of the island and be made up of at least

90% Quercus cf. oleoides (Fagaceae). The understory in these forests is made up of Calliandra (Fabaceae-Mimosoid), Connarus (Connaraceae), Alibertia edulis

(Rubiaceae), Cupania (Sapindaceae) and Ouratea (Ochnaceae) (Bermingham et

al.1998). Most of the oak trees are slow growing yet several hundred years old, ranging from 5 – 10 m in the windier areas of the island to 35 m tall along some of the ridges. Most have hollow tree trunks, which are known to be optimal retreat sites for iguanas. Mature mixed forests also occur to some degree on the island, where few oak trees are found and the canopy consists mostly of evergreens ranging from 30 to 35 m tall. Palms are scattered throughout the island and on the three main beaches. Button mangrove (Conocarpus erectus, Combretaceae) and mangrove fern (Acrostichum aureum, Adiantaceae) can also be found in a small marsh area on the island (Bermingham et al. 1998; see Appendix I for general habitat photos). Though this survey was only conducted on Cayos

Cochinos Pequeño, the islands are ecologically extremely similar (Wilson and

Cruz Diaz 1993; SA Pasachnik and CE Montgomery pers. obs.).

There is little to no overlap in the vegetation of these two geographic isolates of C. melanosterna. Cayos Cochinos is dominated by evergreen oak forest whereas Acacia and cacti dominate the Valle de Aguán. Given that there is little to no overlap in vegetation, it is clear that individuals from each population have different diets. Likewise there are expected differences in reproductive biology as the different habitats afford different soil types and occur in areas of highly different weather patterns (SA Pasachnik pers. obs.), thus the egg deposition, clutch size, and timing of reproduction most likely vary (Colli 1991,

Gillis and Ballinger 1991, Iverson et al. 1993, Jenkins et al. 2009). In addition to ecological differences, the geography of the area clearly shows that the mainland and island populations are not only separated by an expanse of land but also by

the Caribbean Sea (separating the islands from the mainland 8,000-9,000 years ago, see Toscano and Macintyre 2003 for sea level curves). Thus, current gene flow between these areas is extremely unlikely.

Methods

Field Collection. DNA samples were collected from individuals across the geographic range of C. melanosterna within the Valle de Aguán and Cayos

Cochinos in Honduras over a five-year period from 2004 to 2009 (Figure 1). The exact locations of these individuals is not recorded herein as the two geographic isolates of this species are Critically Endangered and listed under CITES

Appendix II due to the threats they face from the international pet trade. If desired, additional information concerning this topic may be requested from the authors.

Upon capture, a digital photograph was taken and snout-vent length, tail length, sex and weight were recorded. In addition, each individual was given a unique mark to avoid re-sampling from year to year. Either a one cm section of the tail tip was removed and stored in 100% ethanol, or a 0.5ml sample of blood was drawn from the caudal vein and stored in an EDTA buffer (Longmire et al.,

1992) for molecular analysis. For individuals from which a tissue sample was taken, the area was disinfected with ethanol prior to removal, and pressure was applied to the wound until bleeding ceased and the area was sealed with a topical skin adhesive to prevent infection. For individuals from which a blood sample was taken, the area around the puncture site was disinfected with

ethanol before the blood was drawn and was sealed with a topical adhesive after blood was drawn.

DNA Sequencing. Genomic DNA was extracted using the Qiagen DNeasy extraction kit (Qiagen, Valcencia, CA). The polymerase chain reaction (PCR) was used to amplify portions of two mitochondrial markers, 674 bp of NADH dehydrogenase subunit 4 and 1067 bp of cytochrome oxidase B (CytB). For primer sequences and PCR procedures see Pasachnik et al. (2008). PCR products were verified by gel electrophoresis and successful amplicons were purified using either exonuclease I/shrimp alkaline phosphatase (ExoSap) or a

QIAquick PCR purification kit (Qiagen, Valcencia, CA).

GenBank using MacClade 4.07 (Maddison and Maddison 2005). We assayed 81 individuals for the two mitochondrial markers. Ctenosaura palearis was used as the outgroup. All sequences have been registered on Genbank (GU331986-

GU331993, GU332005-GU332012, GU906223).

Mitochondrial DNA analysis. The two mtDNA loci were combined to estimate a mitochondrial genealogy using a Bayesian and Maximum Likelihood approach

(ML). Bayesian posterior probabilities were estimated using MrBayes 3.1

(Ronquist and Huelsenbeck, 2003) with four Markov chains, the temperature profile at the default setting of 0.2, run for 2 million generations and sampling every 100th generation with a final burnin of 10,000 generations. ML analysis was conducted in PAUP* 4.0 (Swofford 2002) using a heuristic search with 1000 random-taxon-addition replicates. Confidence at each node was assessed using nonparametric bootstrapping (Felsenstein 1985) based on 1000 pseudo- replicates with 10 random-taxon-addition replicates per pseudo-replicate. The optimal model of sequence evolution for each locus was determined in Modeltest

3.7 (Posada and Crandall 1998).

Using the program Arlequin version 3.11 (Excoffier et al. 2005) we tested various hypotheses of genetic structuring by running AMOVA analyses based on a priori groupings created by considering geographic barriers. The first grouping tested considers the two island populations together, the north side of the Rio

Aguán and the south side of the Rio Aguán as three separate groups. The second tests the islands individually as well as the north and south side of the river, as four different groups. We then used the program SAMOVA version 1.0

(Spatial Analysis of Molecular Variation, Dupanloup et al. 2002) to explore the population structuring without the use of any a priori groups. This method assigns sampling sites or populations to groups based on geographic proximity and genetic homogeneity through a simulated annealing procedure. The number of groups must be specified for each run. Since we sampled 12 locations we assessed each number of groups ranging from two to 11 with 100 simulated annealing simulations. By exploring different numbers of groups, the most likely

groups could be determined based on the resulting F statistics (Dupanloup et al.

2002), which are calculated using an AMOVA approach (Excoffier et al. 1992).

Once these groups were chosen we used the same groupings in Arlequin to estimate p-values relative to 10,000 randomizations.

Demographic Statistics. To evaluate the possibility that populations have recently experienced large demographic changes, we followed Finn et al. (2009) in testing the mtDNA data for deviations from mutation-drift equilibrium using standard test statistics in DnaSP (Rozas et al. 2003). We used the results from SAMOVA,

AMOVA and a priori groups based on geography to determine how to define populations. Since there was some variation in these results we report on the

Cayos Cochinos islands together and separate and the Aguán Valley populations together and then grouped by the north and south sides of the Rio Aguán.

The demographic statistics used include: mean absolute error (MAE), raggedness, Fu’s Fs, Tajima’s D, Fu and Li’s D and Ramos-Onsins and Roza’s growth statistic (Finn et al. 2009). MAE is the differences between the observed mismatch distribution and the theoretical mismatch distributions under demographic expansion (for example, following a severe bottleneck). Thus MAE decreases as the probability of expansion increases (Rogers et al. 1996).

Raggedness describes the smoothness of the observed pairwise difference distribution and is expected to decrease with expansion, which increases smoothness (Harpending 1994). Fu’s Fs (1997) compares haplotype frequencies of the observed and expected (using the Ewens 1972 model, which assumes

migration drift equilibrium and neutral mutation). Negative values, indicating a low probability of the observed population having as many haplotypes as the Ewens simulation, are expected with population expansion. Tajima’s D compares the number of segregating sites and nucleotide diversity to test the hypothesis that all mutations are neutral. Values are negative under population expansion. Fu and Li’s D* (1993) is similar to Tajima’s D but computes the number of singletons in the external branches and is expected to be negative with population expansion. Ramos-Onsins and Rozas R2 statistic (2002) also accounts for singletons and has higher values with population expansion. Ramos-Onsins and

Rozas R2 statistic is more powerful for small populations whereas Fu’s Fs is most powerful when the population is large. For all demographic statistics, except

MAE, significance was assessed using 1000 coalescent replicate simulations, where the observed number of segregating sites was held constant and no recombination was allowed. In addition, significance for Tajima’s D and Fu and

Li’s D* was generated from the original test of the data.

We then categorized each group using these six demographic statistics.

The possible categories of demographic stability range from 1 – 5; 1 represents a monomorphic group inferred to be resultant of a recent founder effect or extreme bottleneck, 2 represents a recent strong bottleneck inferred from all statistics being significantly high, 3 represents a historic bottleneck inferred from some statistics being significantly high, 4 represents a long-term demographic stability inferred from no significant result, and 5 represents long term growth signature inferred from some statistics being significantly low (Finn et al. 2009).

While deviations from mutation-drift equilibrium might indicate demographic instability (and therefore, lower conservation value), they might also be caused by natural selection or population structure, and these alternatives cannot be distinguished when only a single marker is tested (Misawa and Tajima

1997, Tajima 1996). In addition, inference 4 (“long-term stability”) is based on failure to reject a null hypothesis and is therefore inherently weak. Rigorous risk assessment might better be approached from a Bayesian perspective where a variety of priors are explored and their probability assessed, instead of simply rejecting or accepting the null hypothesis.

Nuclear data analysis. AFLP markers were obtained following the general procedure described by Vos et al. (1995), using four different selective primers

(Fitzpatrick et al. 2008). The presence or absence of fragments was determined by running fluorescently labeled PCR product in an ABI 3100 sequencer at the

University of Tennessee’s sequencing facility. Peaks were aligned and called in both Genescan ® Analysis Softeware (Applied Biosystems) and Peak Scanner TM

Software v1.0 (Applied Biosystems), and then verified through visual inspection of each chromatogram. A complete technical replicate, from restriction-ligation through selective PCR, was performed for each individual by multiplexing with two different colored primers. Only those sites and individuals that showed the same pattern with both color primers were used in this analysis.

To evaluate population structure without a prior assumptions of groups, we used the clustering MCMC algorithm in Structure 2.2 (Pritchard et al. 2000,

Falush et al. 2007). To infer the number of genetic clusters (K) best supported by the data, we used both the approximate posterior probabilities (Pritchard et al.

2000), and) delta K method. For each K from 1 to 8, we ran the MCMC 10 independent times with 10,000 burn-in generations and 100,000 sampling generations. Due to inconsistency in missing data between primers the data from each primer was evaluated separately. Then all individuals with any missing data were removed and the analysis was repeated, such that 51 individuals were included. Lastly we removed the loci that were thought to be under selection, as discussed below, and repeated the analysis.

To directly address the question of island-mainland differentiation, we estimated multi-locus FST using AFLP-SURV 1.0 (Vekemans 2002) and screened for individual outlier markers using BayeScan (Foll and Gaggiotti 2008).

BayeScan uses posterior probability estimates to evaluate hierarchical models in which individual loci or populations are allowed to contribute differentially to the overall FST. AFLP markers linked to loci contributing to differential local adaptation between island and mainland habitats are expected to show greater than average FST if there is ongoing gene flow or if isolation is recent (such that mutation and drift have not yet maximized FST for most markers). Because we were concerned with rigorously evaluating the possibility of local adaptation rather than identifying or counting candidate loci, we used a high threshold (Pr{αi

≠ 0 | data} > 0.99) for accepting evidence of divergent selection. This is expected to produce a high false-negative rate for AFLP's if the underlying model is correct

(Foll and Gaggiotti 2008). However, unrecognized population structure (Excoffier

100

et al. 2009) or deviations from the assumed mutation process for AFLP's might increase the false-positive rate. No estimate of false positive rate for a situation such as the one described herein exists (Foll and Gaggiotti 2008), however we do find that the number of candidate loci in the most extreme bin (posterior probability > 0.99) is greater than the number with posterior probability between

0.95 and 0.99. This is not expected if only false positives are being identified.

Results

Mitochondrial DNA analysis. The results from the gene tree analysis, AMOVA and SAMOVA all show support for genetic structure separating the island populations from the mainland populations, a separation between the populations on the north and south side of the Rio Aguán and a possible separation between the two island populations. This indicates that the island populations have been present for longer than predicted if they were established by recent human introductions, over the last hundred years or so. The mitochondrial gene tree reveals that there were no haplotypes shared between the mainland and Cayos

Cochinos samples. In the Cayos Cochinos, one common haplotype is shared between the two islands, two are unique to the Cayos Pequeño sample and one is unique to the Cayos Grande sample. On the mainland, two haplotypes are found only on the north side of the river and three haplotypes on both the north and south sides of the river. The south side of the river had no unique haplotypes in this sample, however one haplotype was found only on the south side of the

101

river and in an area on the north side, close to the narrowing of the river (Figures

1 and 2).

The SAMOVA analysis shows that as the number of groups increases the

FCT increases (Appendix IIa) whereas FSC decreases (Appendix IIb), as predicted by Dupanloup et al. (2002). A plateau in the FCT values exists from k=3 through k=10, which suggests that dividing the populations into additional groups does not substantially improve the predicted population structure. We do see an increase in FCT after k=10 but this is likely an artifact of having only one individual sampled for some sites (Appendix II). When three groups are specified, the

Cayos Cochinos islands group together and there is a split mostly corresponding to the north and south sides of the river on the mainland (Table 1). Given this structure, 75% of the variation is explained as differences among groups and these results are significantly different from random grouping. When four groups are specified we still see the islands together, however there are basically two groups south of the Rio Aguán and one group north of the Rio Aguán (Table 1).

Given this structure, 76% of the variation is among groups, only a 1%

“improvement” over k=3.

The AMOVA results based on a priori grouping consistent with geography largely agree with the three group structuring from the SAMOVA results. The only difference is that one site on the north side of the river groups with the south side, and one group from the south side groups with the north side in the

SAMOVA k=3 model. The AMOVA analysis finds that 41% of the variation is among groups and this result is significant under the k=3 model where the

102

islands are grouped together and the north and the south side of the river are separate. However, when the two islands are separated for the k=4 model we find that only 18% of the variation is among groups and the result is not significantly better than random grouping (Table 1). This configuration has

13860 unique permutations, so there would have been ample power to reject the null hypothesis if it was the grouping that maximized FCT given k = 4 (Fitzpatrick

2009).

Demographic Statistics. The null hypothesis of mutation-drift equilibrium was not rejected when each of the four populations inferred from the mtDNA were used

(Table 2). Thus, following Finn et al. (2009), we are unable to reject the null hypothesis of long-term demographic stability. Caution should be taken when using this method of classifying both the stability of populations and in turn the long-term habitat stability, especially in the context of conservation and management. Though many of these statistics can be used with confidence to infer certain events, such as bottlenecks, failure to reject the null hypothesis should not be considered equivalent to accepting the conclusion of demographic stability. In other words, there may be biologically relevant events that have occurred which are statistically not significant, due to sample size or the power of the analysis.

Nuclear data analysis. Using the clustering methods, approximate posterior probabilities and delta K, in Structure 2.2 we find that variation in the best

103

number of groups is exhibited between the four primers (Appendix III). Two primers find the greatest support for K=2, one primer for K=1 and one for K=3

(Appendix III). This indicates substantial heterogeneity among markers in the degree of differentiation. However, when the data from all primers was run together, for the subset of 51 individuals, we saw support for K=2. In addition, all primers exhibited statistically significant multilocus differentiation between a priori groupings according to the randomization test in AFLP-SURV (Table 3). Our analysis using STRUCTURE might be conservative in identifying clusters, but the putative clusters found correspond well with expectations based on geography and mtDNA. When three groups are supported, the mainland and each island population are separate (Figure 3a). When two groups are supported, a split is evident between Cayos Cochinos and the mainland populations (Figure 3b and

3c).

Using AFLP-SURV 1.0 (Vekemans 2002) we estimated multi-locus FST in order to address differentiation between various populations, specifically to answer the question of mainland-island differentiation. All four primers showed significant FST values at both the global and mainland-island levels (Table 3)

Though some variation in the value of FST does exist between primers, these values are generally low. This indicates that recent isolation is most likely the force behind this division as contemporary gene flow between the mainland and island populations is extremely unlikely. When considering the two Cayos populations and the two mainland populations as four separate groups, the FST values differed between populations and between primers, however, FST was

104

always greatest between the population north of the Rio Aguán and the Cayos

Pequeño population and lowest between the two mainland populations (with the exception of CTTG), and at times between the island populations (Table 3).

BayeScan (Foll and Gaggiotti 2008) was used to screen for individual markers with deviant levels of geographic differentiation. From the posterior probability estimates we detected eight AFLP bands using a threshold of (Pr{αi ≠

0 | data} > 0.95) that show FST values that are higher than expected if due only to random variation among markers. However, because we were concerned with rigorously evaluating the possibility of local adaptation rather than identifying or counting candidate loci, we used a higher threshold (Pr{αi ≠ 0 | data} > 0.99) and detected five individual loci that showed evidence of exceptional divergence between the mainland and island populations (Figure 4). These AFLP markers might be linked to loci contributing to differential local adaptation between island and mainland habitats.

Candidate markers were not evenly distributed among the four AFLP primers, explaining the low level of multilocus differentiation exhibited by one primer. This heterogeneity among primers is not unexpected based on the heterogeneity among AFLP bands. Of 310 scored bands, 50% were fixed in the entire sample or showed only one individual iguana without the majority phenotype, and only a minority of variable bands were highly differentiated among groups. However, even when we removed the eight loci that are seemingly associated with selection we still see support for the island-mainland separation (K=2) in the STRUCTURE analysis.

105

Discussion

Four concordant lines of data demonstrate that two separate evolutionarily significant units should be considered within C. melanosterna. The results from both the mtDNA and AFLP analyses show support for a split between the populations in the Valle de Aguán and Cayos Cochinos. Further the AFLP data indicate possible adaptive differentiation between the two groups (Figure 4), consistent with the strong contrast between the xeric, Acacia dominated habitat of the Valle de Aguán and the more mesic oak forests of the Cayos Cochinos.

Additional management units within these ESUs may be appropriate; some data support differentiation between the two islands or across the Rio Aguán, however these patterns need to be verified by additional data. What seems clear is that the relatively protected population of C. melanosterna on Cayo Pequeño is not representative of (exchangeable with) the mainland form and, therefore, an irreplaceable element of biodiversity would be lost if the Valle de Aguán population is allowed to go extinct.

The gene tree analysis of the mtDNA data clearly demonstrates a division between the island populations and the mainland populations as none of the observed haplotypes were found in both general locations (Figure 2). The

AMOVA and SAMOVA analyses also show support for this separation with the addition of a separation between the mainland populations found on the south side of the Rio Aguán and those found to the north (Table 1). The AFLP data are

106

concordant with the principal separation of Cayos Cochinos from the mainland, however instead of then showing support for an additional mainland separation, some of these data show support for separating Cayos Grande from Cayos

Pequeño (Figure 3, Table 3).

Understanding the structure, and thus defining the units and prioritizing those units is vital to both a proactive and reactive conservation program (Brooks et al. 2006). One of the most commonly used and appropriate ways to classify groups of organisms for conservation is into ESUs, which are supported as

“species” or DPSs by the ESA. A variety of ways to define ESUs have been developed, and disagreement exists between these definitions (Waples 2005).

Pennock and Dimmick (1998) argued that this ambiguity is beneficial in allowing decisions to be made, on a case-by-case basis, as to which variables are most important. As things stand, research is needed on a case-by-case basis to predict the consequences of alternative conservation strategies.

From sequencing a portion of the mitochondrial genome or scanning the nuclear genome, individuals from the mainland can be differentiated from those on Cayos Cochinos. Thus Moritz’s (1994) criterion of significant differentiation at the nuclear level (Table 3) is met and the criterion of reciprocal monophyly

(Figure 2) is partially met with this dataset. In addition to the genetic data, simply looking at the geography of the area one can deduce that the mainland and island populations are not only separated by an expanse of land but also by the

Caribbean Sea; therefore, Waples’ (1991) first criterion of reproductive isolation is also met with these data. However, to meet Waples’ second criterion of distinct

107

adaptations or evolutionary legacy and the similar criteria of many of the other definitions of an ESU (Ryder 1986, Dizon et al. 1992, Crandall et al. 2000), our attention must turn to evidence for adaptive variation or differential selection and concordance between additional lines of data.

The genomic heterogeneity in the degree of divergence inferred from

BayeScan is consistent with adaptive differentiation between the mainland and island populations. The amount of variation exhibited by the AFLPs is low overall, implying recent isolation. However, at least five alleles are strongly differentiated, likely as a result of local selective sweeps at linked loci. The Cayos Cochinos island habitat is dominated by evergreen oak forest whereas cacti and Acacia plants dominate the Valle de Aguán mainland habitat. Though detailed dietary studies have not yet been conducted, it is clear that individuals in each population are foraging on extremely different plants, as there is little overlap in the flora between sites. Likewise, these different habitats afford different soil types and occur in areas of highly different weather patterns (SA Pasachnik pers. obs.). Therefore the reproductive biology, such as nesting times may also vary

(Colli 1991, Gillis and Ballinger 1991, Iverson et al. 1993, Jenkins et al. 2009).

Given the evidence of adaptive differentiation, Waples’ criterion of preserving evolutionary legacy is met. There is also concordance between different lines of data including genetics, geography and ecology, to support this conclusion. Thus the criteria of Dizon et al. (1992) are met and there is support for two ESUs. Further, following Crandall et al. (2000) we reject genetic and ecological exchangeability between the mainland and island populations.

108

Ctenosaura melanosterna is, therefore, a case in which all lines of evidence, under all sets of criteria, support the same conclusion of two unique ESUs.

The actions needed to protect these two ESU’s are very different. The

Cayos Cochinos populations are located within a National Monument and thus will continue to be afforded a certain degree of protection, though this varies from island to island as discussed above. In addition, the threats that the Cayos

Cochinos populations face are greatly reduced in comparison to the mainland populations, as anthropogenic factors are not as prevalent. Continued protection of the Cayos Cochinos populations is expected. However, given the data presented herein, neglecting to protect the variation within the Valle de Aguán will greatly reduce the amount of biodiversity that is conserved.

Failure to take further action in the Valle de Aguán will result in the extirpation of these populations, leaving those on Cayos Cochinos as the only representatives of this species. Given that the Cayos Cochinos islands are small and in a hurricane zone, deciding to protect only these populations could result in the extinction of this species. In addition, it is likely that C. melanosterna plays an integral role in the functioning of the unique dry tropical forest that occurs in the

Valle de Aguán, just as its sister species C. palearis (Pasachnik et al. 2010) plays in the ecologically similar Valle de Motagua (Coti and Ariano 2008). Thus the extirpation of C. melanosterna could have a negative impact on the entire

Valle de Aguán ecosystem.

Management strategies such as translocations, or the creation of rescue populations, and captive breeding and release programs have been discussed

109

for this species. Failure to preserve the two distinct units identified herein will result in the elimination of differential adaptations to their respective environments. The relocation or release of individuals into areas of the ‘other’

ESU and the subsequent interbreeding may result in the deleterious effects of outbreeding depression in the following generations (eg. Sunnucks and Tait

2001), and, in turn, the possible extinction of the species. Further, because the exact substructure within each of the units is not yet understood, breeding and translocation programs should respect the secondary subdivisions (separation of the islands and the north and south side of the Aguán river), until there is ample data to do otherwise. Lastly, those individuals that are currently in ex situ breeding programs, and for which the origin is unknown, should not be released into the wild until their origin can be determined, because of the potential harm outbreeding depression could cause to the species as a whole.

110

Literature Cited Avise JC (2005) Phylogenetic units and currencies above and below the species level. In Phylogeny and conservation. Purvis A, Gittleman JL, Brooks T (eds). Cambridge University Press, New York.

Bermingham E, Coates A, Cruz Diaz G, Emmons L, Foster RB, Leschen R, Seutin G, Thorn S, Weislo W, Werfel B (1998) Geology and terrestrial flora and fauna of Cayos Cochinos, Honduras. Rev, Biol. Trop. 46 Supl 4:15-37.

Brooks TM, Mittermeier RA, da Fonseca GAB, Gerlach J, Hoffman M, Lamoreux JF, Mittermeier CG, Pilgrim JD, Rodrigues ASL (2006) Global biodiversity conservation priorities. Science 313:58-61.

Brummitt, N and Lughadha, EN (2003) Biodiversity: Where's Hot and Where's Not. Cons. Biol. 17: 1442-1448.

Buckley LJ, Axtell RW (1997) Evidence for specific status of the Honduran lizards formally referred to as Ctenosaura palearis (Reptilia: Squamata: Iguanidae). Copeia 1997:138-150.

Caro T, Engilis A, Fitzherbert E, Gardner T (2004) Preliminary assessment of the flagship species concept at a small scale. Anim Conserv 7:63-70.

Colli GR (1991) Reproductive ecology of Ameiva ameiva ( Sauia, Teiidae) in the Cerrado of Central Brazil. Copeia 1991:1002-1012.

Coti P, Ariano D (2008) Ecology and traditional use of the Guatemalan Black Iguana (Ctenosaura palearis) in the dry forests of the Motagua Valley, Guatemala. IGUANA 3:142-149.

Crandall, KA, Bininda-Edmonds ORP, Mace GM, and Wayne RK. (2000) Considering evolutionary processes in conservation biology: an alternative to ‘evolutionarily significant units’. Trends Ecol Evol 15:290-295.

Davis GE (2005) Science and society: marine reserve design for the California Channel Islands. Cons Biol 19:1745-1751.

Dizon AE, Lockyer C, Perrin WF, Demaster DP, Sisson J (1992) Rethinking the stock concept – a phylogeographic approach. Cons Biol 6:24-36.

Dupanloup I, Schneider S, Excoffier L (2002) A simulated annealing approach to define the genetic structure of populations. Mol Ecol 11:2571-2581.

111

Echternacht AC (1968) Distributional and ecological notes on some reptiles from northern Honduras. Herpetologica 24:151-158.

Ewens WJ (1972) Sampling theory of selective neutral alleles. Theor Popul Biol 3:87-112.

Excoffier L, Smouse PE, Quattro JM (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes – application to human mitochondrial DNA restriction data. Genetics 131:479-491.

Excoffier L, Laval G, Schneider S. (2005) Arlequin ver. 3.0: an integrated software package for population genetics data analysis. Evol Bioinf Online 1:47– 50.

Excoffier L, Hofer T, Foll M (2009) Detecting loci under selection in a hierarchically structured population. Heredity 103:285-298.

Falush D, Stephens M, Pritchard JK (2007) Inference of population structure using multilocus genotype data: dominant markers and null alleles. Mol Ecol Notes 7:574-578.

Felsenstein J (1985) Confidence-limits on phylogenies – an approach using the bootstrap. Evolution 39:783-791.

Finn DS, Bogan MT, Lytle DA (2009) Demographic stability metrics for conservation prioritization of isolated populations. Cons Biol 23:1185-1194.

Fitzpatrick BM, Placyk JS, Niemiller ML, Casper GS, Burghardt GM (2008) Distinctiveness in the face of gene flow: hybridization between specialist and generalist gartersnakes. Mol Ecol 17:4107-4117.

Fitzpatrick BM (2009) Power and sample size for nested analysis of molecular variance. Mol Ecol 18:3961-3966.

Foll M, Gaggiotti O (2008) A genome-scan method to indentify selected loci appropriate for both dominant and codominant markers: A Bayesian perspective. Genetics 180:977-993.

Fu, YX (1997) Statistical tests of neutrality of mutations against population growth, hitchhiking and background selection. Genetics 147:915-925.

Fu YX, LI WH (1993) Statistical tests of neutrality of mutations. Genetics 133:693-709.

112

Gillis R, Ballinger RE (1991) Reproductive ecology of red-chinned lizards (Sceloporus undulatus erythrocheilus) in Southcentral Colorado: comparisons with other populations of a wide-ranging species . Oecologia 89:236-243.

Gutsche A, (2005) Distribution and habitat utilization of Ctenosaura bakeri on Utila. IGUANA 12:143-151.

Harpending H (1994) Signture of ancient population growth in a low-resolution mitochondrial NDA mismatch distribution. Hum Biol 66:591-600.

Hobbs RJ and Mooney HA (1998) Broadening the extinction debate: population deletions and additions in California and Western Australia. Cons Biol 12:271- 283.

Hoekstra JM, Boucher TM, Ricketts TH, Roberts C (2005) Confronting a biome crisis: global disparities of habitat loss and protection. Ecol Lett 8:23-29.

Hughes JB, Daily GC, Ehrlich PR (1997) Populations diversity: its extent and extinction. Science 278:689-692.

Iverson JB, Balgooyen CP, Byrd KK, Lyddan KK (1993) Latitudinal variation in egg and clutch size in turtles. Can J Zool 71:2448-2461.

Jenkins CL, Peterson CR, Doering SC, Cobb VA (2009) Microgeographical variation in reproductive characteristics among western rattlesnake (Crotalus oreganus) populations. Copeia 2009:774-780.

Köhler G (2003) The reptiles of Central America. Herpeton, Verlag Elke Köhler, Offenbach, Germany.

Longmire JL, Gee GF, Hardekopf CL, Mark GA (1992) Establishing paternity in whooping cranes (Grus americana) by DNA analysis. The Auk 109:522-529.

Luck GW, Daily GC, Ehrlich PR (2003) Population diversity and ecosystem services. Trends Ecol Evol 18:331-336.

Mace GM (2000) Its time to work together and stop duplicating conservation efforts… Nature 405:393.

Maddison DR, Maddison WP (2005) MacClade 4 release version 4.07 for OSX. Sinauer Associates, Inc. Sunderland, Massachusetts.

McCranie JR, Wilson LD, Kohler G (2005) Amphibians and reptiles of the Bay Islands and Cayos Cochinos, Honduras. Bibliomania!, Salt Lake City, UT, USA.

113

Misawa K, Tajima F (1997) Estimation of the amount of DNA polymorphism when the neutral mutation rate varies amoung sites. Genetics 147:1959-1964. Mittermeier RA, da Fonsec GAB, Brooks T, Pilgrim J, Rodrigues A, Myers, Michael SJ, Bug A (2003) Hotspots and Coldspots. American Scientist 91:384.

Moritz C (1994) Defining ‘evolutionarily significant units’ for conservation. Trends Ecol Evol 9:373-375.

Moritz C, Cicero C (2004) DNA barcoding: promise and pitfalls. PLoS Biol 2:e354.

Myers N, Knoll AH (2001) The biotic crisis and the future of evolution. Proc. Nat. Acad. Sci. USA 98:5389-5392.

Myers N, Mittermeier RA, Mittermeier CG, da Fonseca GAB, Kent J (2000) Biodiversity hotspots for conservation priorities. Nature 403:853-858.

Pasachnik SA, Echternacht AC, Fitzpatrick BM (2010) Gene trees, species and species trees in the Ctenosaura melanosterna clade. Cons. Genet. DOI 10.1007/s10592-010-0070-3

Pimm SL, Russell GJ, Gittleman JL, Brooks TM (1995) Hotspots and the conservation of evolutionary history. Science 269:347-350.

Posada D, Crandall KA (1998) Modeltest: testing the model of DNA substitution. Bioinformatics 14:817-818.

Pritchard JK, Stephen M, Donnelly P (2000). Inference of population structure using multilocus genotype data. Genetics 155:945-959.

Ramos-Onsins SE, Rozas J (2002) Statistical properties of new neutrality tests against population growth. Mol Biol Evol 19:2092-2100.

Rogers AR, Fraley, AE, Bamshad MJ, Watkins WS, Jorde LB (1996) Mitochondrial mismatch analysis is insensitive to the mutational process. Mol Biol Evol 13:895-902.

Ronquist F, Huelsenbeck JP (2003) MRBAYES 3: Bayesian phylogenetics inference under mixed models. Bioinformatics 19:1572-1574.

Rozas J, Sanchez-DelBarrio JC. Messeguer X, Rozas R (2003) DnaSP, DNA polymorphism analyses by the coalescent and other methods. Bioinformatics 19:2496-2497.

114

Ryder, O. A. 1986. Species conservation and systematics: the dilemma of subspecies. Trends in Ecology and Evolution 1:9-10.

Sanderson EW, Jaiteh M, Levy MA, Redford KH, Wannebo AV, Woolmer G (2002) The human footprint and the last of the wild. BioScience 52:891-904.

Stewart RR, Possingham HP (2005) Efficiency, costs and trade-offs in marine reserve system design. Environmental Modeling and Assessment 10:1420-2026.

Sunnucks P and Tait N (2001) Velvet worms: tales of the unexpected. Nature Australia 27:60-69.

Swofford DL (2002) PAUP*. Phylogenetic analysis using parsimony (*and other methods). Version 4.0. Sinauer Associates, Sutherland, Massachusetts.

Tajima F (1989) Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetcs 123:585-595.

Tajima F (1997) The amount of DNA polymorphism maintained in a finite population when neutral mutation rate varies among sites. Genetcs 143:1457- 1465.

Vekemans, X. 2002. AFLP-SURV version 1.0. Distributed by the author. Laboratoire de Génétique et Ecologie Végétale, Université Libre de Bruxelles, Belgium.

Vos P, Hogers M, Bleeker M, Reijans M, Van De Lee T, Hornes M, Frijters A, Pot J, Peleman J, Kuiper M, Zabeau M (1995) AFLP: a new technique for DNA finger printing. Nucleic Acids Res 23:4407-4414.

Wake, DB and Vredenburg VT (2008) Are we in the midst of the sixth mass extinction? A view form the world of amphibians. PNAS 105:11466-11473.

Waples RS (1991) Pacific Salmon, Oncorhynchus spp., and the definition of “species” under the Endangered Species Act. Marine Fisheries Review 53:11-22.

Waples RS (2006) Distinct population segments. In Scott JM, Goble DD, Davis FW eds. The Endangered Species Act at thirty: Conserving biodiversity in human dominated landscapes. Island Press, Washington DC.

115

Wilson, LD, Cruz Dias GA (1993) The herpetofauna of the Cayos Cochinos, Honduras. Herpetological Natural History 1:13-23.

Wilson, LD, McCranie JR (2004) The conservation status of the herpetofauna of Honduras. Amphibian and Reptile Cons 3:6-33.

Woinarski JCZ, Fisher A (1999) The Australian Endangered Species Act 1992. Cons Biol 13:959-962.

116

Appendix IIIa. Figures and Tables

117

118

Figure III - 2. Maximum likelihood and Bayesian combined mitochondrial gene tree. Values above nodes represent posterior probabilities and values below nodes represent bootstrap support. Value inside parentheses indicates sample size. S=south of the Aguán river and N=north of the Aguán river.

119

Figure III - 3. Structure plots by primer, indicating the number of groups best supported. South indicated south of the Aguán river and north indicates north of the Aguán river.

120

Figure III - 4. The frequency by which Foll and Gaggiotti's (2008) α is observed, illustrating variation among AFLP markers in the degree of differentiation between mainland island samples of C. melanosterna. Outliers detected by BayeScan (Foll and Gaggiotti 2008) are shown in grey (Pr{αi ≠ 0 | data} > 0.95) and black (Pr{αi ≠ 0 | data} > 0.99).

121

Table III - 1. A priori and SAMOVA groupings for three and four groups. Percent variation and associated significance obtained from AMOVA for both sets of groups.

122

Table III - 2. Sample size, population genetic information, and demographic statistics for each Ctenosaura melanosterna populations. Significance based on p<0.05 and calculated from the data/coalescent simulations (following Finn et al. 2009).

Cayos Cayo Pequeno Cayo Grande Aguan Valley North of Rio South of Rio n 34 24 10 47 31 16 No. of haplotypes 4 3 2 5 5 3 Nucleatide diversity 0.00014 0.00010 0.00021 0.00306 0.00160 0.00249 Demographic Statistics MAE 0.12230 0.07390 0.18650 0.66750 0.64570 1.31220 rg 0.35940 0.48330 0.20990 0.08980 0.07430 0.44520 R2 0.08070 0.13820 0.17780 0.20140 0.10350 0.20770 D -1.55550 -1.51469 0.01499 2.36041*/no -0.52703 1.53004 D* -1.53788 -2.15908 0.80424 1.51030*/no 1.05234 0.97526 Fs -2.9160 no/* -2.07800 0.41700 7.65600 2.49600 5.90600

Demographic Category 4/5 4 4 3/4 4 4

123

Table III - 3. FST values from AFLP SURV.

Mainland- Multilocus Global Island Primer CG CP N CTAC CG 0.072* 0.107* CP 0.074 N 0.086 0.103 S 0.076 0.103 0.000 CTAG CG 0.106* 0.078* CP 0.148 N 0.140 0.994 S 0.125 0.102 0.016 CTTC CG 0.070* 0.092* CP 0.085 N 0.063 0.101 S 0.088 0.092 0.000 CTTG CG 0.013** 0.039* CP 0.000 N 0.010 0.039 S 0.000 0.036 0.005

* p <0.0001 ** p = 0.02

124

Appendix IIIb. Habitat photos.

125

Photos of the Valle de Aguán (above, courtesy of JP Corneil) and Cayos Cochinos (below, courtesy of CH Montgomery). Notice the large cactus in the foreground of the top row of photos and the palms and oak trees in the bottom row of photos.

126

Appendix IIIc. F parameters from SAMOVA

127

F parameters for different numbers of groups (k) generated using SAMOVA a) FCT and b) FSC

128

Appendix IIId. Average log probability of the data (left) and change of log probability

129

Average log probability of the data (left) and change of log probability of the data (right), for each primer. K represents the number of groups ranging from 1-8.

130

GENERAL CONCLUSIONS

PART I. GENE TREES, SPECIES AND SPECIES TREES WITHIN THE CTENOSAURA PALEARIS CLADE

• The objective of this research was to resolve the relationships between

the four species within the C. palearis clade (C. bakeri, C. oedirhina, C.

melanosterna, and C. palearis) occurring in Honduras and Guatemala.

• We used several recently developed methods for using DNA sequence

data to evaluate the species boundaries and relationships, in addition to

an evaluation of morphological data, and taking into account geography.

• This process demonstrates the challenging nature of estimating a species

tree for a group characterized by recent divergence, and illustrates the

importance of using multiple lines of data to evaluate such a question,

especially in cases where conservation and management depend upon

the conclusions.

• In this case, the commonly used practice of estimating a phylogenetic tree

from concatenated data gives a tree with high support values but one that

conflicts with the (also strongly supported) estimate from explicit species

tree methods.

131

• The concatenated analysis is misleading, due to the strong influence of

one marker, and that the BEST/MDC/STAR species tree is most likely the

correct representation of the relationship between these species.

• Congruence among three crucial lines of data used in delimiting species -

molecular, geographical, and morphological - was observed. Thus, the

results of this study support the prior species-level taxonomy of the C.

palearis clade.

• The level of DNA sequence divergence among species of the C. palearis

clade indicates that speciation occurred in quick succession a few million

years ago, around the same time as the closing of the Isthmus of Panama.

• Our analyses show that the four species in the C. palearis clade are

recently derived but distinct and independent evolutionary lineages that

should each be protected as unique elements of Mesoamerican

biodiversity.

132

PART II. GENE FLOW BETWEEN AN ENDANGERED ENDEMIC IGUANA, AND ITS WIDE SPREAD RELATIVE ON THE ISLAND OF UTILA, HONDURAS: WHEN IS HYBRIDIZATION A THREAT?

• The objective of this research was to evaluate the potential threat that

gene flow from the common and widely distributed congener, C. similis,

could have to the genetic distinctiveness of the island endemic, C. bakeri.

• We used a combination of DNA sequence data and visual identification of

morphological characters to evaluate the level of introgression observed

across the island. We also used molecular techniques to evaluate a

putative hybrid described by Köhler and Blinn in 2000 that was known to

have produced viable offspring.

• Our results revealed two wild caught individuals that showed genealogical

discordance. Morphological evaluation of 599 wild caught individuals,

however, revealed no intermediate or mosaic phenotypes.

• The molecular evaluation of the putative hybrid revealed marker

heterozygosity, thus supporting conclusions drawn from the previous

morphological evaluation.

• These results indicate that fertile hybrids are occasionally produced in the

wild when C. bakeri and C. similis mate, however, Ctenosaura bakeri and

133

C. similis are morphologically and genealogically distinct and nearly

completely reproductively isolated.

• The frequency of hybrids could increase if the frequency of interspecies

matings increases or if ecological conditions favoring hybrid genotypes

were to become widespread, e.g. future destruction of habitat on Utila.

Therefore, continued genetic monitoring of this situation is justified.

• Ctenosaura bakeri is listed as Critically Endangered and as in need of

protection by the Honduran government. As its optimal habitat is

destroyed, ecological interactions with C. similis may contribute to the

decline of C. bakeri if competition prevents the latter from using a broader

range of habitats.

• Conservation efforts should thus focus on preservation and restoration of

mangrove stands and nesting beaches in order to combat both direct and

indirect affects of the destruction of the habitat and to improve the

chances of persistence for C. bakeri.

134

PART III. POPULATION GENETICS OF CTENOSAURA MELANOSTERNA: IMPLICATIONS FOR CONSERVATION AND MANAGEMENT

• The objective of this research was to elucidate the within and among

population variation of Ctenosaura melanosterna throughout its range in

the Valle de Aguán and Cayos Cochinos, Honduras.

• Four concordant lines of data demonstrate that two separate evolutionarily

significant units should be considered within Ctenosaura melanosterna.

The results from both the mtDNA and AFLP analyses show support for a

split between the populations in the Valle de Aguán and Cayos Cochinos,

Honduras.

• Further the AFLP data indicate possible adaptive differentiation between

the two groups, consistent with the strong contrast between the xeric,

Acacia dominated habitat of the Valle de Aguán and the more mesic oak

forests of the Cayos Cochinos.

• Additional management units within these ESUs may be appropriate;

some data support differentiation between the two islands or across the

Rio Aguán, however these patterns need to be verified by additional data.

135

• The relatively protected population of C. melanosterna on Cayo Pequeño

is not representative of (nor exchangeable with) the mainland form and is,

therefore, an irreplaceable element of biodiversity would be lost if the Valle

de Aguán population is allowed to go extinct.

• The actions needed to protect these two ESU’s are very different. The

Cayos Cochinos populations are located within a National Monument and

thus will continue to be afforded a certain degree of protection. In addition,

the threats that the Cayos Cochinos populations face are greatly reduced

in comparison to the mainland populations.

• Failure to preserve the two distinct units identified herein will result in the

elimination of differential adaptations to the environments of each of the

two units, and therefore a loss of biodiversity.

• The relocation or release of individuals into areas of the “other” ESU and

the subsequent interbreeding may result in the deleterious effects of

outbreeding depression in the following generations and, in turn,

contribute to the possible extinction of the species.

• Since the exact genetic substructure within each of the units is not yet

understood, breeding and translocation programs should respect the

136

secondary subdivisions (separation of the islands and the north and south

side of the Aguán river), until there is sufficient data to do otherwise.

• Those individuals that are currently in ex situ breeding programs, and for

which the origin is unknown, should not be released into the wild until their

origins are elucidated, because of the of risk of outbreeding depression

and the harm that this would cause to the species as a whole.

137

VITA

Stesha A. Pasachnik was born in Hamilton, New York, in 1980. She attended Hamilton Central School and graduated in 1999. She then entered into a biology program at Earlham College in Richmond, Indiana, and began working at the Joseph Moore Museum, developing an exhibit for a live collection of lizards. During this time Stesha spent her summers participating in two NSF REU programs (Avila College, Mountain Lake Biological Station), doing research in

Nebraska and on a variety of May terms that allowed her to travel from the

Galapagos to the Bahamas. Stesha received a Bachelors degree in Biology in

2003.

Having already been accepted into a doctoral program at the University of

Tennessee, Stesha deferred for a year in order to travel as a visiting fellow to the

National University of Australia, where she studied retreat site selection in the velvet gecko. While in Australia she worked with Dr. Sharon Downes in the lab of

Dr. Scott Keogh. After completing this fellowship she traveled to Costa Rica as an invited consultant on a sea turtle conservation project.

In the fall of 2004 Stesha began her dissertation program with Dr. Arthur

Echternacht. During this time she was invited to join the Iguana Specialists

Group, a Species Survival Commission of the IUCN. Stesha has been active in expanding the group’s focus to include the Spiny Tailed Iguanas of Mexico and

Central America, hosting their annual meeting in 2008. After completing her PhD in 2010 Stesha plans to return to Roatan, Honduras, to conduct natural history

138

research on Roatan’s endemic iguana and create an outreach and education program using this species as the flagship species. She will be working with the

Bay Islands Foundation as their conservation director and will be funded by grants that she independently received, from the International Iguana

Foundation, the Mohamed bin Zayed Species Conservation Fund, The Dutch

Iguana Foundation, and USFWS Wildlife Without Borders, during her last year of graduate school.

139