Evolutionary Pattern and Process

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Transitions Between Marine and Freshwaters in Fishes: Evolutionary Pattern and Process

Devin D. Bloom

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

Transitions Between Marine and Freshwaters in Fishes: Evolutionary Pattern and Process

Devin D. Bloom

Doctorate of Philosophy

Department of Ecology and Evolutionary Biology University of Toronto

2013 Abstract

Evolutionary transitions between marine and freshwater habitats are rare events that can have profound impacts on aquatic biodiversity. The main goal of my thesis is determining the processes involved in transitions between marine and freshwater biomes, and the resulting patterns of diversity using phylogenetic approaches. To test hypotheses regarding the geography, timing, frequency, and mechanisms regulating biome transitions I generated multi-locus time- calibrated molecular phylogenies for groups of fishes that include both exclusively marine and freshwater species. My analysis of anchovies demonstrated that Neotropical freshwater anchovies represent a monophyletic radiation with a single origin in South American freshwaters. I used a phylogeny of herring and allies (Clupeiformes) to investigate the evolution of diadromy, a migratory behavior in which individuals move between oceans and freshwater habitats for reproduction and feeding. These analyses do not support the hypothesis that differences in productivity between marine and freshwater explain the origins of diadromous lineages. Diadromy has been considered an evolutionary pathway for permanent biome transitions, however I found that diadromy almost never produces a fully marine or freshwater clade. Marine lineages often invade continental freshwaters during episodes of marine incursion. In South America, the rich diversity of marine derived fish lineages invaded during Eocene marine incursions from either the Pacific or the Caribbean, and Oligocene marine incursions from the Caribbean. I falsified the highly cited Miocene marine incursion hypothesis, but found that the Pebas Mega-Wetland catalyzed diversification in some marine derived lineages. Using diversification analyses, I investigated the evolutionary processes that have generated disparate

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patterns of diversity between continents and oceans. I found that freshwater silversides have higher speciation and extinction rates than marine silversides. Lineages accumulation plots suggest ecological limits are not regulating clade growth in either marine or freshwater biomes. Overall, biome conservatism is a widespread pattern among fishes, and this pattern is largely driven by competition in clades that are physiologically capable of biome transitions. Biome transitions are facilitated by rare paleogeographic events, such as marine incursions. Finally, a difference in net diversification rate is the macroevolutionary mechanism that best explains the difference in diversity between continents and oceans.

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This thesis is dedicated to the memories of Dr. Irwin and Lisa Bloom—whose unwavering devotion to education and the pursuit of knowledge started it all.

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Acknowledgments

Over the course of past five years I have been the beneficiary of an amazing support system— from friends, family, colleagues, and mentors. Many people fall into multiple categories. There were far too many people that had an important influence on my young career to mention here. I would like to acknowledge those that played integral roles.

First and foremost, thanks go to my advisor Dr. Nathan (Nate) Lovejoy. Nate was everything I needed in an advisor. He granted me the autonomy necessary to become an independent researcher, but was always available as a sounding board for ideas. When the University of Toronto and EEB decided to no longer fund PhD students past four years, Nate didn’t hesitate to provide financial support. Nate patiently taught me the art of crafting a well-written manuscript and developing my ideas in a broad scientific context. There is no doubt I am a far better scientist thanks to his guidance. It was also fortuitous and a joy to work with someone that enjoys sarcasm as much as I do! But perhaps I am most grateful that Nate cared deeply about his students as people, and would do everything in his power to see them succeed.

I would like to thank my advisory committee: Allan Baker, Belinda Chang, and Hernán López- Fernández. Their collective expertise, critical feedback and often animated discussion improved my research considerably.

Dr. Phil Cochran from Saint Mary’s University is thanked for recognizing and cultivating the enthusiasm of a young ichthyologist. Dr. C opened the door to the amazing world of scientific research. His endless pranks (fishing lures in my shoes, frozen rattlesnakes in the biology building parking lot) were a reminder to have fun along the way.

I would like to thank Dr. Kyle Piller for an immensely rewarding collaboration. As my master’s advisor, Kyle introduced me to Silversides, phylogenetics, DNA sequencing, international field and so much more. Kyle gave me an opportunity to go to graduate school when few others would. This is not something I will ever forget.

Dr. Hernán López-Fernández (Royal Ontario Museum) graciously took me on my first collecting expedition to South America (perhaps foolishly). This was the starting point of a friendship and

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collaboration that I certainly hope lasts the remainder of my career. The hours spent discussing science, fishes, and life over good food, beer, and scotch are some of favorite moments of the past five years.

Dr. Brian Sidlauskas (Oregon State University) brought me on a collecting trip to the Cuyuni River in Guyana. This not only was a great adventure and collecting opportunity, but started a collaboration that will expand my entire research program.

I had the great pleasure to share the Lovejoy lab with some awesome people: Eric Lewallen, Javiar Maldonado-Ocampo, Kristen Brochu, Megan McCusker, and Shawna Kjartanson. There were far to many undergraduates that helped out to name, but their contributions are not overlooked.

Fellow graduate students in the department made my time here much more enjoyable, particularly, Emily MacLeod, Maria Modanu, Caroline Tucker, Julie Helson, and Catherine Febria.

My nest of newfies (and honorary newfies) were the best friends I could possibly ask for. Stephen Pynn, David Andrews, Luke Barry, and Danielle Rhode are simply amazing people and no words here will convey my gratitude for these friendships. Boys, I will miss the ice and the locker room.

Finally, I owe the biggest thanks to Tiffany Anne Schriever and Tiktaalik (Teek) Bloom. I am eternally grateful that you are in my life.

The contributions to each individual study are acknowledged at the end of each data chapter.

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Table of Contents

Acknowledgments ...... v

Table of Contents ...... vii

List of Tables ...... x

List of Figures ...... xii

List of Appendices ...... xiv

1 General Introduction ...... 1

2 Molecular phylogenetics reveals a pattern of biome conservatism in New World Anchovies (Family Engraulidae) ...... 5 2.1 Abstract ...... 5 2.2 Introduction ...... 5 2.3 Methods ...... 9 2.3.1 Taxon sampling ...... 9 2.3.2 DNA extraction, PCR, sequence acquisition ...... 10 2.3.3 Alignment ...... 11 2.3.4 Data analysis ...... 11 2.3.5 Habitat reconstruction ...... 13 2.4 Results ...... 14 2.4.1 Molecular data ...... 14 2.4.2 Phylogenetic relationships ...... 14 2.4.3 Incongruence among analyses and partitions ...... 16 2.4.4 Habitat reconstructions ...... 17 2.5 Discussion ...... 17 2.5.1 Phylogeny of Engraulidae ...... 17 2.5.2 Transitions between marine and freshwater biomes ...... 20 2.6 Acknowledgments ...... 24

3 Time calibrated phylogeny of Clupeiformes (herring, anchovies, sardines, and allies) clarifies the evolution of diadromy and marine/freshwater transitions ...... 42 3.1 Abstract ...... 42 3.2 Introduction ...... 42 vii viii

3.3 Methods ...... 47 3.3.1 Taxon sampling and molecular data ...... 47 3.3.2 Phylogeny and diversification time estimation ...... 48 3.3.3 Ancestral character reconstructions ...... 50 3.4 Results ...... 50 3.4.1 Phylogenetic relationships ...... 50 3.4.2 Diversification times ...... 51 3.4.3 Ancestral character reconstructions: Evolution of diadromy ...... 52 3.4.4 Ancestral character reconstructions: Marine/freshwater transitions ...... 52 3.5 Discussion ...... 53 3.5.1 Phylogenetic relationships and divergence times in Clupeiformes ...... 53 3.5.2 Evolution of diadromy – Testing the Gross hypothesis ...... 57 3.5.3 Evolution of diadromy – Alternatives to the Gross hypothesis ...... 60 3.5.4 Is diadromy a pathway for marine/freshwater evolutionary transitions? ...... 62 3.5.5 Acknowledgements ...... 63

4 The evolutionary origins of marine derived freshwater fishes in South America ...... 87 4.1 Abstract ...... 87 4.2 Introduction ...... 87 4.3 Methods ...... 90 4.3.1 Data ...... 90 4.3.2 Divergence time estimation ...... 93 4.3.3 Ancestral reconstructions ...... 94 4.4 Results ...... 94 4.4.1 Phylogenetic and Biogeographic patterns ...... 94 4.4.2 Age of MDLs ...... 96 4.5 Discussion ...... 97 4.5.1 Biogeography of marine derived lineages in South America ...... 97 4.5.2 Biome transitions and the role of Pebas Mega-Wetland in diversification of MDLs ...... 99 4.6 Acknowledgements ...... 100

5 Do freshwater fishes diversify faster than marine fishes? A test using state-dependent diversification analyses and molecular phylogenetics of New World silversides (Atherinopsidae) ...... 107 5.1 Abstract ...... 107

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5.2 Introduction ...... 107 5.3 Materials and Methods ...... 111 5.3.1 Taxon sampling, DNA Extraction, PCR Amplification, and Sequencing ...... 111 5.3.2 Phylogenetic Analyses and Diversification Time Estimation ...... 111 5.3.3 Ancestral Character Reconstructions and Lineage Diversification Rate ...... 113 5.3.4 Lineage diversification through time ...... 114 5.4 Results ...... 114 5.4.1 Molecular data and phylogenetics ...... 114 5.4.2 Ancestral character reconstructions ...... 115 5.4.3 Diversification times ...... 115 5.4.4 Speciation, extinction, and transitions rates ...... 116 5.4.5 Lineage through time analyses ...... 116 5.5 Discussion ...... 117 5.5.1 Speciation rates elevated in freshwater ...... 117 5.5.2 Extinction rates elevated in freshwater ...... 119 5.5.3 Geographic patterns of diversity and lineage accumulation ...... 120 5.5.4 Species selection ...... 122 5.5.5 Acknowledgements ...... 123

6 Concluding discussion and synthesis ...... 137

7 References ...... 144

8 Appendices ...... 170

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List of Tables

Table 2.1 List of specimens included in the study with corresponding genbank accession and museum catalog numbers (NA= not available)...... 26

Table 2.2 Sequence length, parsimony informative sites, nucleotide substitution model, descriptive statistics, and MP score for each gene and the combined data set...... 33

Table 3.1 Taxon sampling, habitat type, and Genbank numbers of specimens used in this study. Habitat is scored as 0=marine, 1=freshwater, 2=anadromous, and 3=catadromous...... 64

Table 3.2 Models of evolution and partitioning strategy selected by PartitionFinder and implemented in RAxML...... 77

Table 4.1. Estimated times of divergences between MDLs and their marine sister lineage and time of the first diversification event in South American freshwaters. The highest posterior density for each node age is provided in parentheses. We also indicate the number of freshwater (FW) species included in each data set, and the total number of freshwater (FW) species for each lineage. The biogeographic type refers to the distributions discussed by Lovejoy et al. (2006) (see text for more details). For the distribution of the sister lineage to MDLs, W. Atl =Western Atlantic and Caribbean, E. Pac = Eastern Pacific, and FW = freshwater. Question marks indicate instances where candidate sister lineages were not included in the study...... 105

Table 5.1 Summary of specimens used in this study, including habitat (M=marine, F=Freshwater) and associated Genbank and museum numbers. [GENBANK AND MUSEUM NUMBERS ARE CURRENTLY BEING OBTAINED. AN “X” INDICATES SEQUENCE DATA IS AVAILABLE] ...... 128

Table 5.2 Summary of parameter estimates from BiSSE analyses...... 136

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List of Figures

Figure 2.1 Summary of previous hypotheses of anchovy relationships from Grande and Nelson 1985; Nelson 1984; and Whitehead 1988. Marine species are shown in red and freshwater species in blue...... 35

Figure 2.2 Strict consensus of three equally parsimonious trees from the combined (cytb, 16s, RAG1, RAG2) data. Numbers above nodes are bootstrap values from 1000 replicates and below indicate decay indices...... 37

Figure 2.3 Bayesian phylogeny estimated from a partitioned mixed-model analysis of the combined data set. Numbers above nodes represent posterior probabilities (PP). Asterisks above nodes indicate 100% PP values and below indicate nodes with maximum likelihood bootstrap values >70. The ML topology (not shown) was nearly identical to the Bayesian phylogeny...... 39

Figure 2.4 Ancestral character reconstructions of marine (red) and freshwater (blue) biomes on the Bayesian anchovy phylogeny. Pie charts at nodes show ML support for ancestral states and branch color indicate MP reconstructions...... 41

Figure 3.1 The number of anadromous and catadromous fish species found at different latitudes (A). The annual primary productivity of aquatic biomes across different latitudes (B). Both figures are redrawn from Gross et al. (1988); see this reference for details on how species numbers and primary productivity was estimated...... 78

Figure 3.2 Hypotheses and phylogenetic predictions for origins of diadromy based on (A) Gross (1987) and (B) Dodson et al. (2008)...... 80

Figure 3.3 Maximum likelihood phylogeny of Clupeiformes with bootstrap values (1000 replicates) shown at each node. Previously proposed sublclades within clupeiformes are color coded to demonstrate the lack of monophyly of most of these groups...... 82

Figure 3.4 Chronogram of Clupeiformes resulting from our BEAST analysis. The bars at nodes indicate the 95% HPD of the posterior age estimates...... 84

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Figure 3.5 Time-calibrated phylogeny of Clupeiformes showing ancestral character reconstructions of marine (red), freshwater (blue), anadromous (green), and catadromous (light blue) lineages. Branch colors indicate character states from maximum likelihood reconstructions with branches states considered unambiguous when the log-likelihood was 2.0 units higher than the alternative state...... 86

Figure 4.1 The approximate number of taxonomic orders of marine derived fishes from each continent (Berra 2001)...... 101

Figure 4.2 Summary of ages and distribution patterns for nine South American MDLs. The marine lineages are indicated in red, and freshwater in blue based on our ancestral character reconstructions. The gray shaded areas indicate the Eocene (43-34Ma) and Miocene (24-13Ma) marine incursions. When MP and ML ancestral reconstructions differed, we used the ML reconstructions. The thickened branches indicate the first diversification event (crown clade) of species rich MDL clades. The approximate distribution of MDLs (blue) and their marine sister group (Pacific = green, Atlantic = red, elsewhere = purple) is shown on the right...... 103

Figure 4.3 Clade age versus species richness of South American MDLs. There is no relationship between clade age and species richness (GLM, p = 0.476)...... 104

Figure 5.1 Time-calibrated phylogeny of silversides from BEAST analysis of four-gene data set. Branch colors and circles at nodes indicate maximum likelihood ancestral character reconstructions for marine (red) and freshwater (blue) habitats. Branches are proportional to absolute time and the x-axis is in millions of years (ma) before present day...... 124

Figure 5.2 Posterior distribution of speciation (A), extinction (B), and character transition rate (C) parameters for marine (red) and freshwater (blue) lineages from our BiSSE Bayesian analysis...... 126

Figure 5.3 Lineage through time plots (LTT) for silversides from marine (red) and freshwater (blue) habitats. Both LTT plots show a pattern of exponential lineage accumulation...... 127

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List of Appendices

Appendix 1. Supplementary Figure for chapter 3.

Appendix 2. Supplementary Tables and Figures for chapter 4.

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1 General Introduction

The disparity in species richness across clades and geographic areas is one of the greatest mysteries in evolutionary biology (Harmon 2012). For example, why are there so many beetles and so few coelacanths? Or why are there so many species in the tropics, and so few in northern latitudes (Hildebrand 2004)? Understanding these types of diversity patterns and the underlying evolutionary processes that generate them remains a challenging but fundamental goal of macroevolutionary studies (Ricklefs 2004) and a general goal of developing a more comprehensive knowledge of life on Earth.

Over the course of Earth’s biological history, there have been events considered to be “major transitions” that profoundly altered the course of evolutionary history. However, these major transitions were either unique (e.g. evolution of meiotic sex, genetic code), or exceedingly rare (e.g. multicellularity) events (Maynard-Smith and Szathmary 1997). On the opposite end of the spectrum are evolutionary events that happen rapidly and repeatedly, perhaps over one or two generations (e.g. evolution of coloration) (Hendry and Kinnison 1999). Both major and minor events help explain patterns of diversity and involve shared evolutionary processes. Nested in the middle of this spectrum are major transitions that occur relatively infrequently over macroevolutionary time scales, but nonetheless have occurred repeatedly across the tree of life. In this thesis, I investigate one example of these types of events: evolutionary transitions between marine and freshwater biomes in fishes.

Macroevolutionary biome transitions such as the colonization of terrestrial habitats by vertebrates (Sumida and Martin 1997; Daeschler et al. 2006; Shubin et al. 2006; Niedzwiedzki et al. 2010), mammals returning to the sea (Gingerich et al. 2001), and birds invading the air (Padian and Chiappe 1998) have fascinated biologists for many years (Romer and Grove 1935; Romer 1967; Griffith 1987; Griffith 1994; Holland and Chen 2001). Following Crisp (2006), I define a biome as a recognizable biogeographical region delineated by climate, vegetation structure, eco-physiology, and biota. Marine and freshwater biomes are generally treated as

independent zoogeographic regions (Darlington 1957). There are few organisms capable of moving between marine and freshwaters, and there is a pronounced turnover in community composition between marine, estuarine, and freshwater environments (Winemiller and Leslie 1992; Blaber 2000).

Transitions between marine and freshwater biomes have occurred across the tree of life from microbes (Stahl et al. 1992; Logares et al. 2007; Logares et al. 2009; Logares et al. 2010) to amoebae (Heger et al. 2010), crabs (Daniels et al. 2006), shrimp (Daniels et al. 2006; Augusto et al. 2009), fishes (Lovejoy et al. 1998; Lovejoy and Collette 2001; Yokoyama and Goto 2005; Lovejoy et al. 2006; Kawahara et al. 2009; Whitehead 2010), and mammals (Cassens et al. 2000; Hamilton et al. 2001); and these historical biotic interchanges bear important consequences for reshuffling community composition, species interactions, and species diversity (Vermeij 2005), and change the adaptive landscape for the newly invaded lineage. In general transitions between biomes are thought to be evolutionarily rare events. For example, Crisp et al. (2009) found the retention of an ancestral biome occurred twenty-five times more frequently than shifts to a new biome during speciation in plants, underscoring the difficulty of colonizing novel habitats on a macroevolutionary scale.

This pattern of biome conservatism appears to be common in aquatic organisms as well. Nearly all studies of aquatic biome transitions have found that transitions occur relatively rarely (e.g. Logares et al. 2009; Logares et al. 2010); indeed even those studies that indicate multiple transitions did not detect dozens or hundreds of transitions (Alverson et al. 2007). That transitions between marine and freshwater biomes have occurred infrequently over geological time is surprising given the apparent physical continuity between these ecosystems. This suggests that there are considerable abiotic and biotic barriers (or filters) in place between marine and freshwater environments (Lee and Bell 1999; Vermeij and Dudley 2000; Vermeij and Wesselingh 2002; Bloom and Lovejoy 2011). The most obvious and widely discussed barrier between marine and freshwater habitats is the drastic contrast in salinity concentration and the associated physiological demand for aquatic organisms to maintain osmotic balance with their environment. Freshwater animals are hyperosmotic to their environment, retaining salts and 2

excreting water, whereas marine animals are hypoosmotic and must retain water and excrete salts. Salinity levels are known to influence species distributions, even in so-called secondary freshwater fishes that are able to tolerate slightly brackish waters (Smith and Bermingham 2005). There can be little doubt that salinity acts as a physical barrier for dispersal between marine and freshwater biomes. However, transitions between oceans and continental freshwater habitats are far more difficult that transitions between continental freshwater habitats and continental saline lakes (Adamowicz et al. 2010), which suggests the physicochemical salinity barrier is likely not the only impediment to biotic interchange between marine and freshwater habitats. There are also biotic barriers presented by resident (or incumbent) fauna (Vermeij and Wesselingh 2002; Vermeij 2005) that prevent species from invading adjacent biomes. However, the role of these factors (and others) in marine/freshwater transitions remain poorly understood. Fortunately, some major fish clades have the ability to undergo biome transitions over macroevolutionary time scales; these groups are the model system for my thesis.

Fishes are a particularly good model system for investigating marine/freshwater transitions. Fishes are the most dominant vertebrates in nearly every aquatic habitat. Moreover, fishes constitute 50% of all living vertebrates, thus understanding this group is critical to a general knowledge of biodiversity. Fishes also make good model systems for comparing diversity patterns between continents (freshwater) and oceans because both are restricted to aquatic ecosystems. Comparisons between terrestrial-continental groups and oceanic groups are complicated by the differences between these mediums (Vega and Wiens 2012).

The transition between marine and freshwater biomes might have a profound effect on the evolutionary trajectory of a lineage. Indeed there is a emerging consensus that particular evolutionary events in the history of a lineage are just as or more important than intrinsic traits (i.e. key innovations) (Vamosi and Vamosi 2010). Studies of marine/freshwater transitions and their role in shaping the patterns of diversity of life on Earth (Wiens and Donoghue 2004) are in their infancy (Logares et al. 2009; Hou et al. 2011). In fact, some of the most basic questions lack answers, such as: How many biome transitions have occurred in fishes, and how frequently do they occur over evolutionary time? What factors determine when and where biome transitions 3

will occur? How do biome transitions impact a lineage? Are transitions asymmetrical? These and other questions regarding biome transitions remain critical questions in macroevolution (Crisp 2006; Crisp et al. 2009; Logares et al. 2009), but have not been the target of a comprehensive research program. My thesis and developing research program seek to fill this gap.

Thesis Objectives

My thesis is comprised of four data chapters. Each represents a stand-alone manuscript for submission to international scientific journals. The main objective of my thesis is to test hypotheses on the origins, timing, frequency and outcomes of marine/freshwater transitions. There is a rapidly growing body of research on the topic of marine/freshwater transitions. Most of this research has utilized molecular phylogenies to determine the number, frequency and direction of aquatic biome transitions. My thesis further contributes to this burgeoning topic in chapters 2 & 3, where I generated molecular phylogenies for anchovies (chapter 2) and all Clupeiformes (chapter 3) and reconstructed marine/freshwater transitions. This work (chapters 2 & 3) expands the field by demonstrating biome conservatism in a clade that was previously thought to have undergone multiple biome transitions and makes theoretical advances by considering the mechanisms that regulate biome transitions. Chapter 3 also investigates the evolution of diadromy—a behavior in which individuals migrate between marine and freshwaters for growth and reproduction. Importantly, this is the first study on diadromy in Clupeiformes, and one of very few to investigate diadromy in a phylogenetic context. I also investigated the why some areas such as South America, have so many marine derived fishes, and what role paleogeographic events had in shaping this pattern of diversity (Chapter 4). Using nine independent marine derived lineages, I falsified the widely cited Miocene marine incursion hypothesis. Instead I found that there were two waves of invaders that preceded the Miocene. Finally I provide one of the first tests of the mechanisms behind the disparity in continental versus oceanic species diversity (Chapter 5). Using lineage diversification analyses I demonstrated that a faster net diversification rate best explains higher species richness on continents than oceans.

2 Molecular phylogenetics reveals a pattern of biome conservatism in New World Anchovies (Family Engraulidae)

2.1 Abstract

Evolutionary transitions between marine and freshwater biomes are relatively rare events, yielding a widespread pattern of biome conservatism among aquatic organisms. We investigated biome transitions in anchovies (Engraulidae), a globally distributed clade of economically important fishes. Most anchovy species are near-shore marine fishes, but several exclusively freshwater species are known from tropical rivers of South America and were previously thought to be the product of six or more independent freshwater invasions. We generated a comprehensive molecular phylogeny for Engraulidae, including representatives from 15 of 17 currently recognized genera. Our data support previous hypotheses of higher-level relationships within Engraulidae, but show that most New World genera are not monophyletic and in need of revision. Ancestral character reconstruction reveals that New World freshwater anchovies are the product of a single marine to freshwater transition, supporting a pattern of biome conservatism. We argue that competition is the principal mechanism that regulates aquatic biome transitions on a continental scale.

2.2 Introduction

Understanding the frequency of major evolutionary transitions and how these events alter the trajectory of a clade is a primary interest of evolutionary biologists (Maynard-Smith and

Szathmary 1997; Anderson and Sues 2007; Hendry et al. 2010). Evolutionary transitions between biomes, such as marine and freshwater environments, are relatively rare events (Gray 1988; Lee and Bell 1999; Vermeij and Dudley 2000; Vermeij and Wesselingh 2002; Crisp et al. 2009) that can have a profound impact on the history of a clade (Sumida and Martin 1997; Gingerich et al. 2001; Daeschler et al. 2006; Shubin et al. 2006; Niedzwiedzki et al. 2010). These historical biotic interchanges can expose lineages to novel ecological opportunities, alter rates of evolution, and prompt adaptive diversification (Schluter 2000; Yoder et al. 2010), as well as reshuffling community composition, altering species interactions, and altering regional species diversity (Vermeij 2005). Many clades in the tree of life have undergone macroevolutionary transitions between biomes and understanding these events is integral to interpreting general patterns of biodiversity (Vermeij 2006).

The integration of phylogenetics and ecology has led to the concept of phylogenetic niche conservatism (PNC) (Wiens and Donoghue 2004; Wiens and Graham 2005). In the broadest definition, niche conservatism predicts that closely related species will be ecologically similar, that is, they will retain (and share) a niche inherited from a common ancestor due to intrinsic (fundamental niche) or extrinsic (realized niche) constraints. From a biogeographic perspective, this translates to a tendency for lineages to track their ancestral habitat rather than exhibit transitions between different habitats (Harvey and Pagel 1991). Alternatively, some clades show evidence for repeated transitions between habitats, demonstrating a niche lability or niche evolution model. Under the niche lability model, a trait or niche axis may evolve repeatedly within a clade, provided there is limited competition and recurring biogeographic opportunity (Wiens et al. 2006). Thus, the niche evolution model posits that closely related species are not necessarily ecologically similar (Losos et al. 2003).

To date, most studies on phylogenetic niche conservatism and niche lability have focused on small-scale microhabitat shifts, such as switches between forest and savannah in flycatchers (Rheindt et al. 2008), flowing or stagnant water in aquatic dysticid beetles (Ribera and Vogler 2000; Ribera et al. 2001), and tidal or intertidal habitats in sculpin fishes (Ramon and Knope 2008). The prevalence of continental scale habitat (or biome) transitions, such as those between 6

major aquatic biomes (Crisp et al. 2009), remains largely unexamined despite considerable interest (Pearse 1927; Romer and Grove 1935; Robertson 1957; Parry 1966; Halstead 1985; Griffith 1987; Crisp 2006). Marine and freshwater biomes are profoundly different aquatic environments separated by stringent physiological barriers (Bloom and Lovejoy 2011). Correspondingly, biotic interchanges between these biomes are thought to occur infrequently over geological time (Gray 1988; Winemiller and Leslie 1992; Lee and Bell 1999; Mank 2006; Logares et al. 2010), and many clades have distributions in either freshwater or marine habitats, but not both. Nonetheless, transitions between marine and freshwater biomes have occurred across the tree of life, in microbes (Stahl et al. 1992; Logares et al. 2007; Logares et al. 2009; Logares et al. 2010), amoebae (Heger et al. 2010), crabs (Daniels et al. 2006), shrimp (Daniels et al. 2006; Augusto et al. 2009), mammals (Cassens et al. 2000; Hamilton et al. 2001), and fishes (Lovejoy et al. 1998; Lovejoy and Collette 2001; Yokoyama and Goto 2005; Lovejoy et al. 2006; Kawahara et al. 2009; Whitehead 2010). The fish clades for which phylogenetic data are available have shown patterns of both biome conservatism (Lovejoy et al. 1998; Lovejoy and Collette 2001; Yokoyama and Goto 2005; Whitehead 2010) and lability (Lovejoy and Collette 2001; Betancur-R 2010; Whitehead 2010). Here we use anchovies as a model system to investigate the evolution of transitions between marine and freshwater biomes at a continental scale. We present a new phylogenetic hypothesis for anchovies, and clarify the evolutionary origins of the remarkable freshwater anchovies inhabiting the Amazon and other major rivers of South America.

The anchovy family Engraulidae is a well-defined monophyletic group (Grande and Nelson 1985; Lavoue et al. 2007; Lavoue et al. 2010) with ~140 species divided into 16 genera found in temperate and tropical regions around the world. Most anchovies are highly abundant, marine, planktivorous fishes that form large schools in near-shore habitats. However, there are some extraordinary ecological exceptions. In South America, there are 12+ anchovy species that occur in major tropical rivers, including the Amazon, Orinoco and Essequibo. Most of these species occur exclusively in freshwater, in some cases living thousands of kilometers from marine habitats. These peculiar freshwater anchovies exhibit great diversity in body size and ecology.

For example, Lycengraulis batesii is a large-bodied piscivorous species that reaches 300mm standard length (SL) and has canine teeth and enlarged gill raker denticles (Bornbusch 1988; Whitehead et al. 1988). At the opposite end of the spectrum is the miniaturized paedomorphic species Amazonsprattus scintilla, which has a maximum size of <20mm SL, making it the smallest known clupeomorph (Roberts 1984; Weitzman and Vari 1988). The currently recognized taxonomic arrangement of New World anchovies suggest that freshwater South American species are the result of multiple independent transitions from a marine environment (Nelson 1983, 1984b; Grande and Nelson 1985; Nelson 1986) (Figure 2.1). For example, Nelson (1984b) suggested that the Amazonian species Jurengraulis juruensis is nested within marine Cetengraulis and Engraulis species (Figure 2.1), and must therefore have invaded freshwater independently of other freshwater anchovy lineages. This pattern of freshwater species nested within a predominately marine group is repeated multiple times across New World anchovies. Four of the eight New World genera include both marine and freshwater species, and there are two monotypic freshwater genera (Pterengraulis and Amazonsprattus), indicating that six or more marine to freshwater transitions may have occurred in South America. This is a striking pattern given the physiological challenges of moving to a new biome (Lee and Bell 1999; Wiens and Donoghue 2004; Wiens and Graham 2005; Crisp et al. 2009) and suggests that New World anchovies fit a biome niche evolution model. However, a comprehensive phylogeny for anchovies has not yet been proposed, precluding analysis of the frequency of marine to freshwater transitions in this clade.

Based on morphological criteria, Grande and Nelson (1985) divided the 16 genera of the anchovies (family Engraulidae) into two subfamilies, Coilinae and Engraulinae. Coilinae is an entirely Old World group found in the Indo-Pacific and includes the genera Coilia, Lycothryssa, Papuengraulis, Setipinna, and Thryssa. Though often referred to as a New World clade, the Engraulinae includes the Indo-Pacific genera Stolephorus and Encrasicholina, the cosmopolitan genus Engraulis, and the New World genera Anchoa, Anchovia, Anchoviella, Amazonsprattus, Lycengraulis, Cetengraulis, Jurengraulis, and Pterengraulis. These New World genera and the widespread genus Engraulis together are thought to form the clade Engraulini (Nelson 1970;

Grande and Nelson 1985). Lavoue et al. (2010) was the only previous molecular phylogenetic study to investigate higher level relationships within Engraulidae. Using mitogenomics they supported the relationships proposed by Grande and Nelson (1985) and confirmed that Amazonsprattus scintilla is a member of Engraulini (Nelson 1984b), but they lacked the necessary taxon sampling to evaluate relationships among genera and species. Despite being recognized as one of the most important ecological and economical groups of fishes of all-time (Whitehead 1985; Whitehead et al. 1988), very little known about the evolutionary relationships of anchovies.

In this study we propose the first comprehensive molecular phylogeny for the anchovy family Engraulidae, including representatives from 15 of the recognized 17 genera, based on both mitochondrial and nuclear genes. Using this tree, we reconstruct transitions between marine and freshwater habitats in the New World Anchovies (Engraulini), and thereby test whether anchovies fit the niche conservatism or niche evolution model. We also evaluate previous hypotheses of higher-level anchovy relationships, and clarify the origins of the remarkable South American freshwater anchovies.

2.3 Methods

2.3.1 Taxon sampling

Our data set comprises 60 species (117 individuals) representing all nine New World genera and 15 of the 17 currently recognized genera in the anchovy family (Roberts 1984; Peng and Zhao 1988; Whitehead et al. 1988). We focused sampling on New World taxa, in order to provide the most robust test of habitat transitions in South American lineages (Table 2.1).

Currently there are 12 described freshwater species from six genera found in South American freshwaters; however, a number of additional species await formal taxonomic description and species limits are poorly known (Whitehead 1973). A number of freshwater specimens included in our study could not be unequivocally assigned to a particular described species and our molecular data indicated they might represent undescribed taxa. The taxonomic status of these

individuals was beyond the scope of this study; however, we included any freshwater individual that could potentially represent a distinct species. Our data set included eight currently recognized and three putative species from continental freshwaters of South America, with representatives of all six genera found in Neotropical freshwaters. We also comprehensively sampled marine species, including 30 New World species. We specifically targeted lineages that were previously proposed as sister to freshwater taxa from the Pacific, Atlantic and Caribbean Oceans. For outgroups we included 10 species representing the major lineages of Clupeiformes. Trees were rooted with Denticeps clupeoides, a basal clupeoid (Lavoue et al. 2007; Li and Orti 2007; Lavoue et al. 2010). When possible, multiple individuals of each species were sequenced for all genes. Specimens were collected using seine nets, dip-nets, and cast-nets, or purchased from fish markets. Muscle or fin tissue was stored in either 95% ethanol or a salt solution consisting of 20% DMSO and 0.25 M EDTA saturated with NaCl.

2.3.2 DNA extraction, PCR, sequence acquisition

Whole genomic DNA was extracted using the DNEasy spin column tissue kit (Qiagen Inc., Valencia, CA). We collected DNA sequence data from fragments of two mitochondrial genes 16s and cytochrome b (Cytb). The 16s fragment was PCR amplified using primers 16S135F and 16S1072R from Li and Orti (2007). Cytochrome b was amplified using newly designed primers CytbAnchF (5` TGACTTGAAAAACCACCGTTGTTATTCAAC 3`) and CytbAnchR (5` CTAGCTTTGGGAGYTAGDGGTGGRAGTT 3`). Additionally, we sequenced fragments of the nuclear recombination activating genes –1 and –2 (RAG1 and RAG2). Primers for PCR amplification of RAG1 were RAG12510F from Li and Orti (2007) and RAG14078R from Lopez et al. (2004). The primers RAG2AnchF (5’ TTCAAGCTTCGCCCYATCTCTTTCTCCAA 3’) and RAG2AnchR (5’ CTCCATGCACTGGGCGTGGACCCA 3’) were newly designed for this study. PCR reactions for 16s and cytb were performed in 25µl reactions, which included 2.5µl 10x PCR buffer, 2µl MgCl2, 2 µl dNTPs (10mM), 2µl of each primer (10mM), 0.5µl Taq polymerase, 1-4µl genomic DNA, and the remaining volume of H20. PCR thermocycling conditions were 95° for 2 min, followed by 30-40 cycles of 95° for 30 sec, 53° for 1 min, 72° for 90 sec, and a final extension of 72° for 5 min. PCR reactions for RAG1 and RAG2 were 10

conducted in 50µl reactions containing 5µl 10x PCR buffer, 4µl MgCl2, 2µl dNTPs (10mM), 2µl each primer (10mM), 1µl Taq polymerase, 1-5µl genomic DNA, and the remaining volume consisting of H20. Thermocycling conditions for the RAG genes were 95° for 4 min, 35-40 cycles of 95° for 1min, 50-55 for 1min, 72° for 90sec, and a final extension of 72° for 5 min. The PCR products for all four genes were purified using Qiagen spin column PCR purification kit. Both 16s and Cytb were sequenced using the PCR amplification primers. Internal sequencing primers used for RAG1 were 3222F from Li and Orti (2007) and the newly designed RAG1SEQF (5’ TACCACAAGATGTACCGCAC 3’). Internal sequencing primers for RAG2 were RAG2-526F and RAG2-1096F from Li and Orti (2007), as well as newly designed RAG2SEQR (5’ CAGCTTAGGGCTGCCCAACAGAAGCTCGAC 3’). Samples were sequenced at the SickKids Centre for Applied Genomics, Toronto, Canada.

2.3.3 Alignment

Forward and reverse sequences were edited, used to build consensus sequences, and then exported for analysis using Sequencher 4.6. (Genecodes). Multiple alignment for each gene was conducted using Clustal X (Thompson et al. 1997). Default settings were used for cytb, RAG1 and RAG2. The resulting alignments were evaluated in MacClade (Maddison and Maddison 2001) to ensure no stop codons were present. The 16s data was subjected to gap opening and extension parameters (10/10, 10/5, 20/5, 25/5, 30/5, 35/5), the resulting alignments were compared qualitatively, and it was determined that 16s alignment was stable across this range of alignment parameters.

2.3.4 Data analysis

Aligned sequences were used to produce four data sets: (1) the two mitochondrial genes combined, (2) RAG1, (3) RAG2, and (4) all genes (16s, cytb, RAG1, RAG2) concatenated into a single total evidence matrix. The total evidence matrix was partitioned by gene for maximum likelihood and Bayesian analysis. Congruence among partitions was assessed using an incongruence length difference test (ILD) implemented in PAUP* (Swofford 2002). We tested for selection and recombination in our nuclear dataset to confirm the appropriateness of these 11

genes for reconstructing the evolutionary history of anchovies from different environments and selective regimes. In order to test for positive selection, codon-based likelihood methods were used to estimate dN/dS ratios in the RAG1/RAG2 data set. Random-sites (Nielsen and Yang 1998; Yang et al. 2000) models were implemented using the codeml program of the PAML software package (Yang 2007). We used PhiPack (Bruen et al. 2006) to test for possible recombination in the RAG genes.

Maximum parsimony analysis (MP) was applied to the four-gene data set using PAUP* (Swofford 2002). For MP tree searches we used the heuristic search algorithm with 1000 random addition replicates, and TBR branch swapping. All characters were equally weighted and gaps were treated as missing data. Bootstrap support values were calculated using 1000 replicates with 10 random sequence additions per replicate.

A best-fit model of sequence evolution and parameter estimation for each gene was determined under the Akaike information criterion using ModelTest (Nylander et al. 2004). Partitioned maximum likelihood (ML) tree searches were performed with GTR+G models for each partition using the program RAxML (Stamatakis 2006). Maximum likelihood bootstrap estimates were based on 100 replicates using the rapid bootstrapping algorithm in RAxML.

Bayesian inferences are known to improve when heterogeneity is accommodating using mixed- model partitioned approaches (Brandley et al. 2005; Brown and Lemmon 2007); therefore we partitioned our data by gene, using the best-fit model of evolution chosen by ModelTest. We conducted a Bayesian analysis using MrBayes v3.1.2 software (Ronquist and Huelsenbeck 2003). Four independent runs were conducted and each search consisted of four chains sampling every 100 generations for 20 million generations. All parameters were unlinked and default priors were used. Adequate mixing of Metropolis coupled chains was checked to ensure acceptance rates fell between 10-70%. Convergence was assessed in several ways. First likelihood vs. generation plots were evaluated using the sump command in MrBayes. Second, average standard deviation of split frequencies were checked to ensure they remained below 0.01 and potential scale reduction factors were 1.0. Finally, cumulative posterior probability plots

were constructed using the compare command in AWTY (Nylander et al. 2008). Based on these measures we conservatively determined that convergence had been reached within four million generations, and these were discarded as burn-in. The remaining 16,000 trees from each run were combined and the frequency of clade occurrence represented posterior probabilities of clades.

2.3.5 Habitat reconstruction

The evolutionary history of habitat transitions was inferred using ancestral character reconstruction. We classified species as either marine or freshwater using literature sources, museum sources, and personal observations. Estuarine species were categorized as marine, because these species are rarely or never found in entirely freshwater habitats, and likely do not reproduce in freshwater habitats.

Habitat type (marine or freshwater) was coded as a discrete, unordered, binary character. Maximum parsimony and maximum likelihood character reconstruction was implemented using Mesquite version 2.6 (Maddison and Maddison 2011). The MP criterion minimizes the number character state changes needed to explain the current state at the tips of the tree, while allowing a single character state per branch. MP reconstruction is agnostic to branch length information, and any character state may change to any other state. Maximum likelihood determines the likelihood of a character state at each internal node using the Mk model (Pagel 1999), thus providing a measure of uncertainty for character states, while taking into account branch length information (Schluter et al. 1997). Ideally reconstructions would be conducted on a chronogram to determine the explicit timing of biome transitions. However, the scarcity of fossil anchovies precluded our ability to generate a time-calibrated phylogeny (see discussion). Thus character reconstructions were optimized on the Bayesian (BI) tree from the concatenated four-gene data set, utilizing branch length information for ML reconstructions.

2.4 Results

2.4.1 Molecular data

The 16s dataset resulted in 804 aligned characters including gaps, 398 of which were parsimony informative. We also removed all gaps and constructed MP trees and found that removing gaps had no effect on the topology of the 16s tree, thus further discussion will only focus on the alignment that included gaps. The cytochrome b data set yielded 1131 base pairs, including 490 informative sites. The RAG1 and RAG2 data resulted in 1493 and 1219 base pairs, of which 550 and 519 were parsimony informative. An intron spanning 390 base pairs was detected in Anchoa cubana, this intron was previously reported by Li and Orti (2007), however the specimen was erroneously identified as Anchoa lyolepis. Chi-square tests of homogeneity indicated that none of the datasets consisted of biased base pair composition (data not shown). We found no evidence for positive selection in our RAG1/RAG2 dataset, as a model incorporating selection was not found to be a better fit to the data than one without selection (M1a-M2a LRT, d.f. = 2, P=1.00) in our analysis using random sites models. We also failed to detect evidence for recombination in either RAG1 (P =0.489) or RAG2 (P = 0.480). Uncorrected sequence variation ranged from 0.12 to 22.0% for 16s, 0.17 to 22.9% in cytochrome b, and ~0.5 to 18% in both RAG1 and RAG2 genes. The combined data set consisted of 4647 characters, of which 1957 were parsimony informative (Table 2.2).

2.4.2 Phylogenetic relationships

The equally weighted MP analysis of the four-gene dataset produced three equally parsimonious trees of 13121 steps (Figure 2.2). The ML analysis produced a well-resolved tree with a score of –63198.938072 (not shown, but discussed below). The BI analysis was run four times with identical results recovered from each run, the resulting tree is shown in Figure 2.3.

All analyses and partitions strongly supported the monophyly of the anchovy family Engraulidae. We also recovered the separation of Engraulidae into two major clades corresponding to subfamilies Coilinae and Engraulinae. The subfamily Coilinae consisted of the

Indo-Pacific genera Setipinna, Lycothrissa, Coilia, and Thryssa, while Engraulinae included Indo-Pacific genera Stolephorus and Encrasicholina as sister to the clade Engraulini including all New World anchovies and the genus Engraulis. Genera within Coilinae were all monophyletic, albeit with limited taxon sampling for those groups.

Within Engraulini, only two (Lycengraulis and Cetengraulis) of the six polytypic genera were monophyletic. The Eastern Pacific Engraulis anchoita and Western Atlantic E. ringens formed a group that was sister to two well-supported major subclades. The first major subclade (Marine clade) included all members of the speciose marine genus Anchoa, the Atlantic and Pacific species of Cetengraulis and Anchovia, the remaining species of Engraulis, and two marine species of Anchoviella. Our data indicate that the commercially important genus Engraulis is not a monophyletic assemblage; in fact, E. eurystole (W. Atlantic), E. encrasicolus (E. Atlantic) and E. japonicus (W. Pacific) were the only members of Engraulis to form a clade. The Eastern Pacific Anchovia marcrolepidota and Western Atlantic Anchovia clupeoides were nested within Anchoa, while the freshwater lineage Anchovia surinamensis was a member of the South American freshwater clade (see below). The genus Cetengraulis was recovered as closely related to A. lyolepis and A. nasus.

The second major clade (Freshwater clade) consisted of the South American freshwater species of Anchoviella, Lycengraulis, Anchovia, Juruengraulis and Amazonsprattus; as well as the coastal marine taxa Lycengraulis poeyi, L. grossidens, Anchoviella brevirostris, and Anchoviella lepidentostole. We refer to this clade as the ‘Freshwater clade’ because although it includes several estuarine or marine taxa, these species were derived from freshwater lineages (see habitat transitions below). Within the Freshwater clade, Jurengraulis juruensis was the basal lineage in the combined data, but this relationship was not supported by all partitions (see below). The large predatory species of Lycengraulis and Pterengraulis were sister lineages and part of clade that included the large bodied planktivorous Anchovia surinamensis and the estuarine species Anchoviella lepidentostole. This group of large bodied taxa was in turn closely related to a clade of very small bodied species including the paedomorphic species Amazonsprattus scintilla, however support for this relationship was low (PP = 0.61). Finally we found strong support for a 15

clade of widely distributed Amazonian freshwater taxa including Anchoviella carrikeri, A. alleni, A. guianensis and several lineages that appear to represent undescribed species; as well as the estuarine species Anchoviella brevirostris.

2.4.3 Incongruence among analyses and partitions

Maximum likelihood and Bayesian reconstructions of the four-gene dataset were nearly identical; and while the major findings were consistent between MP and ML+BI, here we report the few notable differences between these methods. In addition, while we consider the four-gene dataset the best estimate of anchovy relationships, we explore the relative contribution of each data partition. The major differences between analyses and partitions primarily deal with internal nodes within Engraulini that display very short branches for all genes.

Our Bayesian analysis recovers Cetengraulis as sister to a clade consisting of Anchoa lyolepis and A. nasus (PP= 0.99) while MP suggests Cetengraulis is sister to a large clade of Anchoa, Engraulis and some species of Anchoviella however bootstrap support was low. Further, BI indicates that Anchovia macrolepidota is sister to Anchoa chamensis and Anchovia clupeoides is sister to Anchoa colonensis (but PP for both <0.55), while MP supports Anchovia clupeoides and A. macrolepidota as a monophletic clade (but BS <50)

Topological structure among major lineages within the South American freshwater clade received poor statistical support and correspondingly suggested different relationships between MP and BI+ML. Most notably BI suggested a close relationship between a clade of small bodied species Anchoviella spp. and Amazonsprattus scintilla with a clade including the piscivorous genera Lycengraulis and Pterengraulis in addition to Anchovia surinamensis and Anchoviella lepidentostole, while MP was unable to resolve these clades.

The nuclear genes, RAG1 and RAG2, showed very similar topologies overall, however RAG2 had less resolution and lower bootstrap support for most clades. The only two differences between the RAG genes were: 1) RAG2 suggested J. juruensis was part of the Marine clade (but BS<50) rather than the basal lineage of the Freshwater clade and 2) the Indo-Pacific genus

Stolephorus was recovered as sister to Engraulis mordax by RAG2 (BS<50) and as a basal member of Engraulinae by all other partitions (BS>85 and PP=1.0). The mtDNA supports a sister relationship between Cetengraulis and Engraulis mordax (but BS <50) while both RAG genes indicate Cetengraulis form a clade with A. lyolepis and A. nasus and places E. mordax as a basal Engraulini. The mtDNA and RAG1 datasets propose E. ringens + E. anchoita as basal to the Marine clade (mtDNA BS=72; RAG1 BS<50), while RAG2 and the four-gene data set strongly support the E. ringens + E. anchoita lineage as the basal Engraulini.

2.4.4 Habitat reconstructions

Ancestral character reconstruction using both MP and ML approaches yielded identical results and are summarized in Fig 2.5. Critical nodes for habitat transitions received high statistical support from posterior probabilities and MP and ML bootstrap support. Our analyses all support the long-standing hypothesis that anchovies are an ancestrally marine clade, including members of the New World Clade Engraulini. Further, our data clearly showed that freshwater anchovies in South America are the result of a single transition from a marine to freshwater biome. The sister lineage to freshwater anchovies was a clade consisting of all remaining Engraulini, except E. anchoita and E. ringens, which were the basal Engraulini lineage. Subsequently, freshwater lineages made three independent invasions back into marine habitats. These marine/estuarine invaders include: (1) the clade of Pacific Lycengraulis poeyi and Caribbean + W. Atlantic L. grossidens, (2) Anchoviella brevirostris and (3) Anchoviella lepidentostole. These results were robust to a range of transition rates; even with a 100 times higher transition rate than the optimal rate estimated by Mesquite, the ancestral states remain in the estimated state. Further, a two-rate model was not significantly better than a 1-rate model (LRT, p=0.1835).

2.5 Discussion

2.5.1 Phylogeny of Engraulidae

The higher-level relationships of anchovies recovered in our study are consistent with previous investigations based on both molecular (Lavoue et al. 2007; Li and Orti 2007; Wilson et al. 2008;

Lavoue et al. 2010) and morphological data (Grande and Nelson 1985; Di Dario 2002, 2009). The anchovy family Engraulidae is monophyletic and divided into two major clades that correspond to the subfamilies Coilinae and Engraulinae. The subfamily Coilinae is an entirely Indo-Pacific clade including the genera Coilia, Lycothrissa, Setipinna, Thryssa, and presumably Paupengraulis, which has yet to be included in any phylogenetic study. Engraulinae includes the Indo-Pacific genera Stolephorus and Encrasicholina, along with widespread Engraulis and seven New World genera. The relationship of (Stolephorus (Encrasicholina (New World taxa))) was also supported by a recent mitogenomic study by Lavoue et al. (2010). Within Engraulinae, the New World taxa and Engraulis form a clade referred to as Engraulini following Lavoue et al. (2009). Several morphological characters support the monophyly of Engraulini, most notably the loss of ventral scutes (Nelson 1970, 1983; Grande 1985; Grande and Nelson 1985), a character present in nearly all other clupeomorph fishes.

No previous phylogenetic study has included sufficient taxon sampling to determine relationships within Engraulini, thus our study offers the first insight into New World anchovy relationships. All freshwater taxa are the result of a single marine to freshwater transition. A well-supported deep divergence between predominantly marine and freshwater clades indicates this biome transition took place early in the diversification of New World anchovies, and that freshwater lineages are nearly as old as New World marine lineages. This phylogenetic arrangement differs significantly from the currently accepted taxonomy for New World anchovies where several different genera include both marine and freshwater species, suggesting multiple transitions to freshwater. In the phylogeny presented here, the marine members of these genera are either a result of reversal to marine habitats (Lycengraulis, several Anchoviella spp.), or are members of the large “Marine clade” (Anchovia, Cetengraulis, remaining Anchoviella). In the former case, the relationships previously proposed by taxonomy are consistent with our study, but the inferred phylogenetic pattern requires a different biogeographical interpretation (reversal to marine state versus multiple freshwater invasions; see below). The latter case, marine taxa thought to have close affinities to freshwater lineages (e.g. Anchovia clupeoides & Anchovia macrolepidota), is likely the result of classifying lineages based on homoplasious morphological

characters. For example, a deep body and high number of fine gill rakers are shared by members currently recognized as Anchovia (Whitehead 1973), and a posteriorly rounded short maxilla is a defining character of all species recognized as in Anchoviella (Hildebrand 1943), but the non- monophyly of these genera suggests that these functional characters likely reflect trophic niche rather than phylogenetic relatedness.

Within the freshwater anchovies, we identified three major multi-species clades, in addition to the basal lineage Jurengraulis juruensis. The first clade was composed entirely of large-bodied anchovies (most larger than 250 mm standard length), including the piscivorous genera Lycengraulis and Pterengraulis atherinoides, as well as the coastal marine-estuarine Anchoviella lepidentostole and the freshwater species Anchovia surinamensis. Since this clade includes marine lineages (L. grossidens + L. poeyi, and A. lepidentostole) that are well nested within freshwater species, the tree suggests these marine anchovy lineages are the product of two independent re-invasions of coastal habitats. The second clade is a diverse array of Anchoviella lineages from the Upper Amazon, Orinoco, and Essequibo rivers, several of which are likely undescribed species. The inclusion of the coastal marine/estuarine A. brevirostris in this clade represents a third re-invasion of the marine environment along the northern South American coast. The third major clade included the paedomorphic Amazonsprattus scintilla and several diminutive species of Anchoviella (likely including undescribed species), a relationship previously proposed by Nelson (Nelson 1986). The placement of Amazonsprattus scintilla as a member of this clade refines Lavoue et al.'s (2010) recent mitogenomic work confirming this taxon as a member of Engraulinae. The structuring of body size among clades suggests an early and substantial diversification of large and small-bodied lineages of freshwater anchovies, possibly in response to the ecological opportunity of invading a novel habitat (Yoder et al. 2010). More recently, at least three lineages have re-invaded coastal marine/esturarine habitats along Northeastern South America. Further investigations may reveal why this region has been fertile ground for re-invasion of marine habitat.

The Marine clade includes all species of Anchoa and members of Anchovia, Anchoviella, and Engraulis from both the Eastern Pacific and Western Atlantic (mostly Caribbean) oceans. 19

The genus Anchoviella is clearly in need of revision; Anchoviella elongata and Anchoviella balboa are nested within a large clade of Anchoa and did not group with other marine and freshwater species of Anchoviella. Further, we reject the close relationship between Anchovia and Cetengraulis suggested by similarities in overall appearance and gill raker count and structure (Nelson 1984b). Cetengraulis is closely related to tropical Caribbean Anchoa lyolepis and Eastern Tropical Pacific A. nasu (but see results for incongruence between MP and BI+ML), contrary to proposed affinities with Engraulis and Jurengraulis (Nelson 1970, 1983, 1984b, 1986). Our data suggests E. eurystole (Western Atlantic), E. encrasicolus (Mediterranean and Eastern Atlantic), and E. japonicus (Western Pacific), are included in the Marine clade, and although our data set did not include E. australis and E. capensis, these taxa are also likely members of this clade (Whitehead et al. 1988; Grant et al. 2005). Engraulis anchoita and E. ringens together form the basal Engraulini lineage, and thus fall outside the Marine clade. In summary, none of the polytypic marine genera within Engraulini were monophyletic, with the exceptions of Cetengraulis. This incongruence between phylogenetic relationships and current anchovy taxonomy has significant implications for resource management and conservation (Whitehead 1985), particularly for species of Engraulis, which constitute one of the world’s largest fisheries (Whitehead 1985; Whitehead et al. 1988). Several previous biogeographic and evolutionary studies have assumed that marine anchovy taxonomy adequately reflects phylogeny (Grant and Bowen 1998; Grant et al. 2005; Grant and Bowen 2006; Grant et al. 2010). Our results clearly show that this is not the case.

2.5.2 Transitions between marine and freshwater biomes

Our molecular phylogeny and habitat reconstruction for anchovies reveals that South American freshwater anchovies are the product of a single evolutionary transition from a marine to freshwater environment. This is a striking result, given that previous taxonomic arrangements suggested six or more invasions of South American freshwaters. Interestingly, several other clades of fishes share a similar pattern of only a single or very few invasions of freshwater by marine lineages into particular geographic area. For example, South American freshwater stingrays are exceptionally diverse (>20 species), found across the entire continent, and resulted 20

from a single transition from marine to freshwater (Lovejoy 1996; Lovejoy et al. 1998; Lovejoy and Collette 2001). Lovejoy and Collette (2001) argued that needlefishes invaded freshwaters of Amazonia twice, but a single transition has an equal probability under a likelihood model (D. Bloom unpublished data). Herring invaded freshwaters of West Africa between 25-50mya and subsequently spread across the continent to include Lake Tanganyika, and later independently invaded both South Africa and Malagasy (Wilson et al. 2008). Yamanoue et al. (2011) found that freshwater pufferfishes in South America, Central Africa, and Southeast Asia are each products of single independent invasions. Possible reasons for this pattern are discussed below.

Intriguingly, while a pattern of single invasions of freshwaters is common, anchovies are apparently unique in that they have re-invaded marine habitats. It appears that transitions from marine to freshwater are far more common than freshwater to marine (Vermeij and Dudley 2000). Indeed, we know of no other instances of reversals back to the marine biome in fishes at similar taxonomic scales (but seeBetancur-R 2010). Although we acknowledge that making these comparisons based on taxonomy is somewhat arbitrary, the absence of a detailed phylogeny for teleost fishes prevents more phylogenetically correct assessments.

Our data on anchovies and evidence from a growing number of studies on other aquatic lineages (Hamilton et al. 2001; Daniels et al. 2006; Heger et al. 2010; Logares et al. 2010; Hou et al. 2011) strongly suggest a pervasive pattern of aquatic biome conservatism, evidenced by evolutionary transitions between biomes occurring far less frequently than lineages remaining in their ancestral biome (Vermeij and Dudley 2000; Wiens and Donoghue 2004; Wiens and Graham 2005; Crisp et al. 2009). However, there is a lack of mechanistic explanations for what might be driving this widespread biogeographic pattern. We suggest that the factors regulating the frequency of transitions between marine and freshwater biomes, and thus the widespread pattern of biome conservatism, include: 1) geographic opportunity for invasion, 2) physiological barriers, 3) competition, and 4) unique biogeographical events. Below, we discuss these factors with particular reference to the evidence from the freshwater invasion of New World anchovies.

In order for a transition between biomes to occur there must be geographic opportunity. For example, a lineage occurring in the Antarctic Ocean would be unable to invade the Amazon river, while a lineage occurring along of the Atlantic coast of South America would have ample opportunity for invasion (Wiens et al. 2006). Anchovies are found along nearly every coastline in the Western hemisphere (except polar regions) suggesting that over macroevolutionary time these fishes (and others discussed above) must have had many opportunities to invade freshwater habitats, including those in South America, and yet they failed to do so more than once. Clearly lack of geographic opportunity does not explain biome conservatism in New World anchovies and many other fishes.

The strongest physiological barrier between marine and freshwater biomes is the salinity gradient– a transition between these biomes requires osmoregulatory adaptations during all stages of a species lifecycle (Lee and Bell 1999). Constraints on the ability to evolve novel osmoregulatory capabilities has likely caused biome conservatism in many clades of fishes (and other aquatic organisms), and resulted in taxa with persistent and ancient associations with either freshwater or marine habitats (Myers 1949b). However, anchovies are members of Clupeiformes, a group that has colonized freshwater habitats numerous times across the globe (Whitehead et al. 1988; Wilson et al. 2008), including several Indo-Pacific anchovies in the subfamily Coilinae. Further, the freshwater invasion of South America occurred early in the diversification of New World anchovies (the second branching event), suggesting that ancestral anchovy lineages were physiological capable of habitat transitions. Finally, freshwater South American anchovies made three independent re-invasions of marine/estuarine habitats. This evidence suggests that anchovy lineages have long possessed the evolutionary and physiological capacity for adaptation to new salinity regimes. Thus, intrinsic physiological constraints do not offer a good explanation of biome conservatism in anchovies.

Harvey and Pagel (1991) argued that adjacent habitats are rarely invaded because well-adapted incumbent species out compete invaders. Thus competition, particularly among closely related species, can drive biome conservatism just as readily as constraints on the fundamental niche (Vermeij and Dudley 2000; Vermeij and Wesselingh 2002; Wiens et al. 2006; Wiens et al. 22

2010). If a lineage invades a particular area, diversifies, and becomes widespread, open niches will be filled, preventing future invasions (Wiens et al. 2006). The pattern observed in anchovies makes a compelling case for competition playing a major role in driving biome conservatism. Once anchovies invaded freshwaters of South America, they diversified into a wide array of ecologies, including large bodied piscivores (Lycengraulis and Pterengraulis and several miniature species (Amazonsprattus and Anchoviella spp.), that are unparalleled by marine engraulid lineages (Whitehead et al. 1988). The freshwater anchovy clade also expanded geographically to nearly every major river basin in South America. Competition as a general driving force behind marine/freshwater biome conservatism is supported by the fact that many other marine derived freshwater fish lineages show similar a pattern similar to anchovies. For example, pufferfishes have invaded multiple continents, but never invaded the same continent more than once (Yamanoue et al. 2011). We suggest that the presence of a diverse and widespread anchovy fauna in South America that originated early in the history of New World anchovies has precluded subsequent freshwater invasions by the same clade.

Finally, the conservatism of transitions between habitats may be connected to unique paleogeographic events. The large numbers of marine derived freshwater fishes found in South American river systems have been hypothesized to be the product of a continental scale marine incursion that occurred during the Miocene paleo-environmental ecosystem known as the Pebas wetland (Lovejoy et al. 1998; Lovejoy et al. 2006; Bloom and Lovejoy 2012). The Pebas wetland was a spatially and temporally dynamic ecological setting with shifting salinity levels (Hoorn et al. 2010), and may have muted competition with incumbent freshwater lineages, thereby allowing marine invaders to gain a foothold in a new environment (Lovejoy et al. 2006). Further, the fluctuating salinity levels of the Pebas wetland may have provided a fertile landscape for adaptation to freshwater habitats during all life-history stages (Bloom and Lovejoy 2011). Linking marine invaders with this unique paleogeographic event requires knowledge of the timing of transition to South American freshwaters (Donoghue and Moore 2002; Wiens and Donoghue 2004). A time-calibrated phylogeny was beyond the scope of our study because anchovies have an extremely sparse fossil record (Grande and Nelson 1985). However, the split

between L. poeyi (Pacific) and L. grossidens (Atlantic), occurs at the tips of the Freshwater clade, and the distribution of these taxa on both sides of the Isthmus of Panama requires the age of the freshwater clade to be considerably older than 3.5 mya.

Here we have demonstrated the effectiveness of phylogenetic approaches for studying the evolution and ecology of biome conservation at a continental scale. Our study highlights the importance of robust phylogenetic inference, and cautions against uncritical use of taxonomy for inferring macroevolutionary patterns of biome transition. In contrast to taxonomic expectations, we determined that the remarkable freshwater anchovies of South America are the product of a single evolutionary transition from marine habitats. However, we also found evidence for three independent re-invasions of marine habitats. We propose that the rarity of biome shifts is due neither to limited geographical opportunity nor physiological constraint. Rather we believe that competition and paleogeographic events are the principal factors affecting anchovy habitat evolution. Similar habitat patterns in other aquatic taxa should be investigated with competition and paleogeography in mind.

2.6 Acknowledgments

We thank the following people for generously providing tissue samples and specimens: Hernan Lopez-Fernandez (ROM), Mark Sabaj (ANSP), Kyle Piller (SELU), Sabastien Lavoue, Edward Wiley (KHM), H.J. Walker (SIO), Kevin Lim (RMBR), Anthony Wilson (University of Zurich), and Barbara Brown (AMNH). For assistance in the field, we thank Hernan Lopez-Fernandez, Don Taphorn, Calvin Bernard, Javier Maldonado-Ocampo, Dawn Phillip, Eric Lewallen, Mike Littmann, Alex Flecker, Patrick Traynor, and Josh Lovejoy. Chenhong Li offered helpful suggestions for sequencing RAG genes. Hernan Lopez-Fernandez, Belinda Chang, and Allan Baker contributed insightful discussions of this project. Belinda Chang graciously helped with the PAML analysis. G. Nelson offered helpful suggestions for identifying anchovy specimens. Members of the Lovejoy Lab and Jason Weir provided comments that greatly improved an earlier version of this manuscript. Financial support was provided by Sigma Xi, Lerner Gray

grant (AMNH), Centre for Global Change (University of Toronto), the NSERC Discovery Grant program, and National Science Foundation grant DEB-0614334.

Table 2.1 List of specimens included in the study with corresponding genbank accession and museum catalog numbers (NA= not available).

Species Sample Number Museum Catalog NumberRAG1 RAG2 CYTB 16s Locality

Amazonsprattus scintilla 3081 ANSP 181130 JQ012538 JQ012667 JQ012351 JQ012456 Rio Casiquiare, Venezuela

Amazonsprattus scintilla 3083 ANSP 181133 JQ012539 JQ012668 JQ012352 JQ012457 Rio Casiquiare, Venezuela

Anchoa cubana 2665 ROM 91251 JQ012550 JQ012705 JQ012342 JQ012447 Sabastian Inlet, Atlantic Ocean, FL, USA

Anchoa cubana 2666 ROM 91251 JQ012551 JQ012706 JQ012343 JQ012448 Sabastian Inlet, Atlantic Ocean, FL, USA

Anchoa lyolepis 2698 ROM 91252 JQ012573 JQ012688 JQ012344 JQ012449 Bocas del Toro, Caribbean Sea, Panama

Anchoa lyolepis 2699 ROM 91252 JQ012574 JQ012689 JQ012345 JQ012450 Bocas del Toro, Caribbean Sea, Panama

Anchoa cayorum 3019 ROM 91253 JQ012555 JQ012700 JQ012346 JQ012451 Caribbean Sea, Barbados

Anchoa cayorum 3020 ROM 91253 JQ012554 JQ012701 JQ012347 JQ012452 Caribbean Sea, Barbados

Anchoa mitchelli 3091 ROM 91254 JQ012552 JQ012698 JQ012357 JQ012462 L. Ponchartrain, Gulf of Mexico, LA, USA

Anchoa mitchilli 3092 ROM 91254 JQ012553 JQ012699 JQ012358 JQ012463 L. Ponchartrain, Gulf of Mexico, LA, USA

Anchoa walkeri 3287 ROM 91235 JQ012568 JQ012713 JQ012369 JQ012474 Veracruz, Pacific Ocean, Panama

Anchoa nasus 3299 ROM 91238 JQ012575 JQ012690 JQ012373 JQ012478 Veracruz, Pacific Ocean, Panama

Anchoa nasus 3300 ROM 91238 JQ012576 JQ012691 JQ012374 JQ012479 Veracruz, Pacific Ocean, Panama

Anchoa chamensis 3323 ROM 91240 JQ012563 JQ012718 JQ012375 JQ012480 Punta Chame, Pacific Ocean, Panama 26

Anchoa chamensis 3324 ROM 91240 JQ012564 JQ012719 JQ012376 JQ012481 Punta Chame, Pacific Ocean, Panama

Anchoa parva 3330 NA JQ012558 JQ012702 JQ012377 JQ012482 Punta Chame, Pacific Ocean, Panama

Anchoa parva 3331 NA JQ012556 JQ012702 JQ012378 JQ012483 Punta Chame, Pacific Ocean, Panama

Anchoa lamprotaenia 3355 ROM 91241 JQ012630 JQ012696 JQ012379 JQ012484 Galeta Point, Caribbean Sea, Panama

Anchoa lamprotaenia 3356 ROM 91241 JQ012630 JQ012697 JQ012380 JQ012485 Galeta Point, Caribbean Sea, Panama

Anchoa colonensis 3369 ROM 91243 JQ012559 JQ012716 JQ012383 JQ012488 Bocas del Toro, Caribbean, Panama

Anchoa colonensis 3370 ROM 91243 JQ012560 JQ012717 JQ012384 JQ012489 Bocas del Toro, Caribbean, Panama

Anchoa lyolepis 3421 ROM 91246 JQ012572 JQ012733 JQ012389 JQ012494 Bocas del Toro, Caribbean, Panama

Anchoa panamensis 3460 ROM 91255 JQ012570 JQ012712 JQ012392 JQ012497 Playa Peten, Pacific Ocean, Panama

Anchoa walkeri 3461 ROM 91256 JQ012569 JQ012714 JQ012393 JQ012498 Playa Peten, Pacific Ocean, Panama

Anchoa mundeoloides 3622 ROM 91249 JQ012565 JQ012715 JQ012419 JQ012524 Pacific Ocean, Mexico

Anchoa delicatissima 3076 SIO 03051 JQ012557 JQ012704 JQ012348 JQ012453 Pacific Ocean

Anchoa schofieldi 3077 SIO 07-193 JQ012571 JQ012711 JQ012349 JQ012454 Pacific Ocean

Anchoa fiilfera 3409 ROM 91245 JQ012542 JQ012722 JQ012387 JQ012492 Bocas del Toro, Caribbean, Panama

Anchoa filifera 3410 ROM 91245 JQ012543 JQ012723 JQ012388 JQ012493 Bocas del Toro, Caribbean, Panama

Anchovia macrolepidota 3495 ROM 91248 JQ012561 JQ012709 JQ012394 JQ012499 Playa la Cruzas, Pacific Ocean, Panama

Anchovia macrolepidota 3496 ROM 91248 JQ012562 JQ012710 JQ012395 JQ012500 Playa la Cruzas, Pacific Ocean, Panama

Anchovia surinamensis 3548 ROM 85699 JQ012613 JQ012665 JQ012402 JQ012507 Sawariwau River (Rio Branco), Guyana

Anchovia surinamensis 3549 ROM 85699 JQ012613 JQ012666 JQ012403 JQ012508 Sawariwau River (Rio Branco), Guyana

Anchovia clupeoides 3626 NA NA NA EU552570 JQ012525 Braganca, Atlantic Ocean, Brazil

Anchoviella guianensis 503 ROM 91229 JQ012606 JQ012657 JQ012324 JQ012429 Rio Orinoco, Venezuela

Anchoviella carrikeri 706 INHS 54728 JQ012604 JQ012658 JQ012330 JQ012435 Nauta, Peru

Anchoviella carrikeri 707 INHS 54728 JQ012603 JQ012660 JQ012331 JQ012436 Nauta, Peru

Anchoviella carrikeri 720 NA JQ012602 JQ012661 JQ012332 JQ012437 Rio Nanay, Peru

Anchoviella alleni 729 INHS 53667 JQ012598 JQ012655 JQ012333 JQ012438 Rio Nanay, Peru

Anchoviella alleni 730 INHS 53667 JQ012607 JQ012656 JQ012334 JQ012439 Rio Nanay, Peru

Anchoviella alleni 733 INHS 53667 JQ012628 JQ012669 JQ012335 JQ012440 Rio Nanay, Peru

Anchoviella alleni 734 INHS 53667 JQ012629 JQ012670 JQ012336 JQ012441 Rio Nanay, Peru

Anchoviella n. sp2. 739 NA JQ012581 JQ012648 JQ012337 JQ012442 Rio Nanay, Peru

Anchoviella n. sp2. 740 NA JQ012582 JQ012649 JQ012338 JQ012443 Rio Nanay, Peru

Anchoviella carrikeri 806 ANSP 178232 JQ012605 JQ012659 JQ012339 JQ012444 Rio Amazonas, Peru

Anchoviella n. sp1. 3084 ANSP 187406 JQ012589 JQ012677 JQ012353 JQ012458 Lawa River, Suriname

Anchoviella n. sp1. 3085 ANSP 187406 JQ012588 JQ012675 JQ012354 JQ012459 Lawa River, Suriname

Anchoviella n. sp1. 3086 ANSP 187406 JQ012587 JQ012676 JQ012355 JQ012460 Lawa River, Suriname

Anchoviella balboa 3289 ROM 91237 JQ012566 JQ012720 JQ012371 JQ012476 Veracruz, Pacific Ocean, Panama

Anchoviella balboa 3290 ROM 91237 JQ012567 JQ012721 JQ012372 JQ012477 Veracruz, Pacific Ocean, Panama

Anchoviella elongata 3364 ROM 91242 JQ012548 JQ012707 JQ012381 JQ012486 Salud, Caribbean Sea, Panama

Anchoviella elongata 3365 ROM 91242 JQ012549 JQ012708 JQ012382 JQ012487 Salud, Caribbean Sea, Panama

Anchoviella c.f. guianensis 3542 ROM T6301 JQ012585 JQ012673 JQ012400 JQ012505 Rupununi River, Guyana

Anchoviella c.f. guianensis 3544 ROM T6303 JQ012586 JQ012674 JQ012401 JQ012506 Rupununi River, Guyana

Anchoviella n. sp3. 3573 ROM T6880 JQ012593 JQ012632 JQ012404 JQ012509 Rupununi River, Guyana

Anchoviella n. sp3. 3574 ROM T6881 JQ012594 JQ012633 JQ012405 JQ012510 Rupununi River, Guyana

Anchoviella guianensis 3577 ROM T6884 JQ012591 JQ012652 JQ012406 JQ012511 Rupununi River, Guyana

Anchoviella c.f guianensis 3578 ROM T6885 JQ012601 JQ012662 JQ012407 JQ012512 Rupununi River, Guyana

Anchoviella guianensis 3579 ROM T6887 JQ012590 JQ012653 JQ012408 JQ012513 Rupununi River, Guyana

Anchoviella guianensis 3580 ROM T6888 JQ012592 JQ012654 JQ012409 JQ012514 Rupununi River, Guyana

Anchoviella brevirostris 3602 ROM T7105 JQ012608 JQ012686 JQ012412 JQ012517 Atlantic Ocean, Georgetown, Guyana

Anchoviella brevirostris 3603 ROM T7106 JQ012609 JQ012687 JQ012413 JQ012518 Atlantic Ocean, Georgetown, Guyana

Anchoviella lepidentostole 3607 ROM T7115 JQ012596 JQ012634 JQ012414 JQ012519 Atlantic Ocean, Georgetown, Guyana

Anchoviella lepidentostole 3608 ROM T7116 JQ012597 JQ012635 JQ012415 JQ012520 Atlantic Ocean, Georgetown, Guyana

Anchoviella carrikeri 3680 ROM 91250 JQ012583 JQ012650 JQ012422 JQ012528 Rio Tambopata, Peru

Anchoviella carrikeri 3681 ROM 91250 JQ012584 JQ012651 JQ012423 JQ012529 Rio Tambopata, Peru

Anchoviella carrikeri 3694 ROM T7666 JQ012599 JQ012663 JQ012424 JQ012530 Xingu River, Brazil

Anchoviella carrikeri 3698 ROM T7662 JQ012600 JQ012664 JQ012425 JQ012531 Xingu River, Brazil

Anchoviella c.f. guianensis 652 NA JQ012544 JQ012646 JQ012327 JQ012432 Rio Napo, Peru

Anchoviella c.f. guianensis 655 NA JQ012545 JQ012647 JQ012328 JQ012433 Rio Napo, Peru

Cetengraulis edentulus 3391 ROM 91244 JQ012577 JQ012692 JQ012385 JQ012490 Bocas del Toro, Caribbean, Panama

Cetengraulis edentulus 3392 ROM 91244 JQ012578 JQ012693 JQ012386 JQ012491 Bocas del Toro, Caribbean, Panama

Cetengraulis mysticetus 3453 ROM 91247 JQ012579 JQ012694 JQ012390 JQ012495 Golfo de Montijo, Pacific Ocean, Panama

Cetengraulis mysticetus 3454 ROM 91247 JQ012580 JQ012695 JQ012390 JQ012496 Golfo de Montijo, Pacific Ocean, Panama

Coilia brachygnathus4001 NA DQ912124 DQ912159EU694409 DQ912089Pudong, Shanghai, China

Coilia mystus 4002 NA DQ912126 DQ912162EU694407 DQ912092Pudong, Shanghai, China

Coilia nasus 4003 NA DQ912123 DQ912157AP009135 DQ912087Pudong, Shanghai, China

Encrasicholina devisi 3239 ROM 91232 JQ012626 JQ012684 JQ012364 JQ012469 Senoko Fishing Port, Singapore

Encrasicholina devisi 3247 NA JQ012627 JQ012685 JQ012366 JQ012472 Senoko Fishing Port, Singapore

Engraulis anchoita 3613 NA NA NA JQ012416 JQ012521 Atlantic Ocean, Brazil

Engraulis anchoita 3614 NA NA NA JQ012417 JQ012522 Atlantic Ocean, Brazil

Engraulis ringens 3739 NA JQ012533 JQ012731 JQ012426 JQ012532 Fish Market, Peru

Engraulis eurystole 3902 KU 30199 DQ912121 DQ912155JQ012427 DQ912085Baffin Bay, Texas, Gulf of Mexico

Engraulis japonicus 4000 NA AY430205 NA NC003097 NC003097 Pacific Ocean, Japan

Engraulis mordax 3080 SIO 05-79 JQ012546 JQ012728 JQ012350 JQ012455 Pacific Ocean

Engraulis encrasicolus 3123 ROM 91230 JQ012540 JQ012726 JQ012359 JQ012464 Fish Market, Israel

Engraulis encrasicolus 3124 ROM 91230 JQ012541 JQ012727 JQ012360 JQ012464 Fish Market, Israel

Engraulis ringens 3616 NA JQ012595 JQ012730 JQ012418 JQ012523 Pacific Ocean, Peru

Engraulis mordax 3651 NA JQ012547 JQ012729 JQ012421 JQ012527 Pacific Ocean, Oregon, USA

Jurengraulis juruensis 696 INHS 54730 JQ012610 JQ012732 JQ012329 JQ012434 Nauta, Peru

Jurengraulis juruensis 827 ANSP 178278 JQ012611 JQ012724 JQ012340 JQ012445 Rio Amazonas, Peru

Jurengraulis juruensis 828 ANSP 178278 JQ012612 JQ012725 JQ012341 JQ012446 Rio Amazonas, Peru

Lycengraulis poeyi 3288 ROM 91236 JQ012621 JQ012642 JQ012370 JQ012475 Veracruz, Pacific Ocean, Panama

Lycengraulis grossidens 3509 STRI 05365 JQ012622 JQ012639 JQ012396 JQ012501 Atlantic Ocean, Argentina

Lycengraulis grossidens 3510 STRI 05365 JQ012623 JQ012640 JQ012397 JQ012502 Atlantic Ocean, Argentina

Lycengraulis grossidens 3541 ROM T6249 JQ012624 JQ012641 JQ012399 JQ012504 Atlantic Ocean, Georgetown, Guyana

Lycengraulis batesii 3588 ROM T7076 JQ012619 JQ012643 JQ012410 JQ012515 Rupununi River, Guyana

Lycengraulis batesii 3589 ROM T7077 JQ012620 JQ012644 JQ012411 JQ012516 Rupununi River, Guyana

Lycengraulis batesii 651 INHS 53777 JQ012618 JQ012645 JQ012326 JQ012431 Rio Napo, Peru

Lycothrissa crocodilus 3632 KAUM-I 8669 JQ012534 JQ012683 JQ012420 JQ012526 Lake Tonle Sap, Cambodia

Pterengraulis atherinoides 501 ROM 91228 JQ012616 JQ012636 JQ012323 JQ012428 Rio Orinoco, Venezuela

Pterengraulis atherinoides 527 ROM 91228 JQ012617 JQ012637 JQ012325 JQ012430 Rio Orinoco, Venezuela

Pterengraulis atherinoides 3088 ROM 66175 JQ012615 JQ012638 JQ012356 JQ012461 Waini River, Guyana

Setipinna taty 3242 ROM 91233 NA JQ012681 JQ012365 JQ012470 Singapore

Setipinna cf. tenuifilis 3535 AMNH 242124 NA JQ012682 JQ012398 JQ012503 Gulf of Siam, Thailand

Stolephorus sp. 3217 NA JQ012536 JQ012671 JQ012361 JQ012466 Senoko Fishing Port, Singapore

Stolephorus sp. 3219 NA NA JQ012672 JQ012362 JQ012467 Senoko Fishing Port, Singapore

Thryssa c.f. dussumieri 3226 ROM 91231 JQ012535 JQ012678 JQ012363 JQ012468 Senoko Fishing Port, Singapore

Thryssa mystax 3243 ROM 91234 JQ012537 JQ012680 JQ012366 JQ012471 Juronj Fishing Port, Singapore

Thryssa cf. dussumieri 3249 ROM 91231 JQ012625 JQ012679 JQ012368 JQ012473 Juronj Fishing Port, Singapore

Alosa sapidissima 4004 KU 27207 DQ912116 DQ912150EU552616 DQ912080Atlantic Ocean, USA

Brevoortia tyrannus 4005 NA DQ912106 DQ912139EU552614 DQ912069Atlantic Ocean, USA

Clupea harengus 4006 KU 27205 DQ912114 DQ912148EU552606 DQ912078Atlantic Ocean, USA

Dorosoma cepedianum 4007 NA DQ912099 DQ912132EU552586 DQ912062Nebraska, USA

Pellona flavipinnis 4008 NA DQ912101 DQ912134EU552551 DQ912064South America

Pellonula leonensis 4009 NA DQ912130 DQ912166EU552624 DQ912095South America

Denticeps clupeoides 4010 NSMT P68224 DQ912100 DQ912133EU552629 DQ912063West Africa

Table 2.2 Sequence length, parsimony informative sites, nucleotide substitution model, descriptive statistics, and MP score for each gene and the combined data set.

Data Partition Bp Model PI char CI RI RC MP tree score

CytB 1131 GTR+I+G 490 0.1659 0.6743 0.1118 5933

16s 804 TVM+I+G 398 0.3219 0.7623 0.2454 2339

RAG1 1493 TIM+I+G 550 0.4569 0.7795 0.3562 2390

RAG2 1219 GTR+I+G 519 0.4840 0.7791 0.3771 2126

Total 4647 1957 0.2940 0.7169 0.2108 13121

Figure 2.1 Summary of previous hypotheses of anchovy relationships from Grande and Nelson 1985; Nelson 1984; and Whitehead 1988. Marine species are shown in red and freshwater species in blue.

3 Time calibrated phylogeny of Clupeiformes (herring, anchovies, sardines, and allies) clarifies the evolution of diadromy and marine/freshwater transitions 3.1 Abstract

Evolutionary transitions between aquatic biomes are rare events. However, some lineages have crossed the marine/freshwater boundary multiple times and across multiple geographic areas. Among fishes, clades with a propensity for undergoing evolutionary transitions between marine and freshwaters often include diadromous species, which migrate between marine and freshwater environments to complete their life cycle. In the most cited hypothesis for the origins of diadromy, Gross posited that productivity determines the geography and ancestral source (marine/freshwater) of diadromous lineages. Specifically, this hypothesis predicts that anadromy should evolve in temperate areas from freshwater ancestors and catadromy should evolve in tropical areas from marine ancestors. An alternative is the ‘safe-site’ hypothesis, which states that anadromous species reproduce in areas of low predation; this scenario predicts that anadromy should evolve from marine ancestors. We generated a time-calibrated phylogeny for Clupeiformes, an ecologically and economically important group that includes a relatively high diversity of diadromous species. We used the resulting chronogram and ancestral character reconstruction to determine the history of diadromy in Clupeiformes and test the predictions of the Gross and safe-site hypotheses. Our results reject Gross’ hypothesis, and find limited support for the safe-site hypothesis. However, we also find that neither hypothesis suffices as a general explanation for the evolution of diadromy. Our study provides the most comprehensive phylogeny of Clupeiformes to date, and provides a temporal context for understanding the evolution of this group.

3.2 Introduction

There are strong biotic and abiotic barriers that prevent organisms from moving between marine and freshwater habitats (Lee and Bell 1999; Miller and Labandeira 2002; Lee et al. 2011; Lee et

al. 2012). Indeed, most major clades of aquatic organisms are restricted to either marine or freshwater (continental) environments, resulting in vastly different communities in each biome. Furthermore, studies across a wide spectrum of organisms such as microbes (Logares et al. 2009; Logares et al. 2010), protists (Logares et al. 2007), copepods (Adamowicz et al. 2010), amoeba (Heger et al. 2010), and fishes (Lovejoy et al. 1998; Lovejoy and Collette 2001; Almada et al. 2009; Betancur-R 2010; Whitehead 2010; Yamanoue et al. 2011; Bloom and Lovejoy 2012; Vega and Wiens 2012) have shown that evolutionary transitions between aquatic biomes are rare events. Yet, clearly some lineages are able to traverse the marine/freshwater boundary, in some cases multiple times and across multiple geographic areas. Among fishes, clades with a propensity for undergoing evolutionary transitions between marine and freshwaters often include diadromous species, which migrate between marine and freshwater environments to complete their life cycle (McDowall 1988). However, few studies have investigated the evolutionary origins and the possible role of diadromy in marine/freshwater transitions.

Diadromy is a behavior in which individuals migrate between marine and freshwaters during a predictable phase of the life cycle, typically for feeding and/or reproduction. Fishes that move freely and opportunistically between marine and freshwater at any given time are not considered diadromous, but rather euryhaline wanderers (McDowall 2009). The ~250 species of diadromous fishes are found nearly worldwide, yet make up less than 1% of the nearly 30,000 fish species (Nelson 2006; McDowall 2008a, 2009). Although diadromous species make up a small percentage of fishes, many diadromous species have significant ecological and economic importance. These include sport fishes and species used for human consumption such as salmon (Salmonidae), American shad (Alosa), Sturgeon (Acipenseridae) and eels (Anguillidae). There are three types of diadromy: catadromy, amphidromy, and anadromy. Catadromous fishes are born in marine biomes and migrate to freshwater where they spend most of their lives feeding and growing before returning to the ocean to reproduce. Anadromous fishes do the opposite, they are born in freshwater and migrate to the ocean where they spend most of their lives feeding and growing, before migrating to freshwater to reproduce. Amphidromous species migrate between marine and freshwaters at a particular life cycle stage (often as juveniles), but not for the purpose of breeding. It is important to note that diadromy is distinctly different from a lineage undergoing

an evolutionary transition from a marine to freshwater biome (or vice versa). Diadromy is a migratory behavior that occurs during the lifetime of a single individual and diadromous species can be classified as being both marine (oceanic) and freshwater (continental) (Parenti 2008). More detailed descriptions and definitions of diadromy have been reviewed elsewhere (Myers 1949a; McDowall 1988, 1992, 2007, 2009).

The evolutionary origins of diadromy have been the subject of considerable theoretical discussion (Gross 1987; McDowall 1987; Gross et al. 1988; McDowall 1988, 1997, 1998; Parenti 2008; McDowall 2009). A long-standing hypothesis proposed by Gross (1987) is that the difference in productivity between marine and freshwater biomes is the critical factor driving the origins of the different modes of diadromy. Oceans have higher productivity than freshwaters in temperate regions, and freshwaters have higher productivity in tropical regions. Gross et al. (1988) argued that natural selection would favor migration towards higher productivity habitats for feeding, thus explaining why higher latitudes have more anadromous species and lower latitudes have more catadromous species (Fig 3.1). This apparent geographic relationship between productivity and mode of diadromy led Gross (1987) to propose that temperate anadromous fishes were derived from freshwater ancestors because the opportunity for foraging and growth was greater in temperate marine compared to temperate freshwater environments. Support for the ecological component of this hypothesis comes from data showing increased growth in salmon that migrate to the ocean compared to those that remain in freshwater habitats (e.g. Wood and Foote 1996). Meanwhile in tropical regions, catadromous fishes were predicted to have evolved from marine ancestors because the opportunity for foraging and growth was greater in freshwaters compared to marine environments (Gross 1987). The scenario proposed by Gross is that diadromy represents an intermediate condition between the evolution of fully freshwater to fully marine species (or vice versa), while amphidromy is an ancestral precursor to both anadromy and catadromy (Gross 1987; Gross et al. 1988). Gross’s model therefore makes the phylogenetic prediction (Fig 3.2) that anadromous species have evolved from a freshwater ancestor, while catadromous species evolved from a marine ancestor. Amphidromous species could have a marine or freshwater ancestor. This model for the evolution of diadromy and its role in marine/freshwater transitions has since been questioned (McDowall 1993, 1997, 2002; Parenti

2008), but few studies have tested Gross’s hypothesis in a phylogenetic framework (but see Dodson et al. 2009).

As an alternative explanation for the evolution of diadromy, Dodson et al. (2009) proposed the “safe site hypothesis” as an evolutionary pathway to anadromy in smelts (Osmeriformes). The “safe site hypothesis” posits that freshwater habitats offer a sanctuary from predators for the eggs and larvae of marine fishes. Anadromy is thought to be the outcome of the adaptive advantage offered by migration to freshwater habitats to reproduce by marine fishes. The “safe site hypothesis” predicts that anadromous species evolved from a marine ancestor, and that freshwater species eventually evolve from anadromous lineages (Fig. 3.2).

In this study we investigate the evolution of diadromy in Clupeiformes (herring, sardines, anchovies, and their allies) because while most major fish clades are restricted to either marine or freshwater (Berra 2001; Nelson 2006), clupeiforms include marine, freshwater, and diadromous species. In fact, Clupeidae alone has more diadromous species (~30) than any other family of fishes except Gobiidae and Salmonidae (McDowall 2003). McDowall (2003) estimated that the proportion of diadromous clupeids is about 10 times higher than in all other fishes. Moreover, clupeiforms include representatives of all three forms of diadromy (anadromy, catadromy, amphidromy), making this group well suited for testing Gross’s hypothesis on the evolution of diadromy and evolutionary transitions between aquatic biomes.

Clupeiformes include some of the worlds most ecologically and economically important species such as anchovies, herring, and sardines, with more than 360 species found in temperate and tropical waters worldwide. Many clupeiform species form massive schools and are a critical component of local ecosystems because they contribute an enormous amount of biomass (Whitehead et al. 1988) and are a major forage base for aquatic predators (Whitehead 1985; Harlin-Cognato et al. 2007). Further, many clupeiforms are a major component of global fisheries that date back to ancient Peruvian civilizations (Sandweiss et al. 2004) and persist today with harvests nearing 20 tons annually (Whitehead 1985; Whitehead et al. 1988). Clupeiforms also have a rich fossil record that provides a temporal framework for interpreting their evolution.

Given the remarkable importance of these fishes it is surprising that phylogenetic relationships and absolute ages of clupeiform lineages remain largely unresolved.

Previous work on the systematics of clupeiformes has included morphological (Grande 1985; Grande and Nelson 1985; Di Dario 2002, 2004, 2009) and molecular (Lavoue et al. 2007; Li and Orti 2007; Lavoue et al. 2008; Wilson et al. 2008; Lavoue et al. 2010) studies that focused on higher-level relationships. These studies consistently supported Engraulidae, Chirocentridae, and Pristigasteridae as monophyletic groups. However, studies have differed on the placement of Chirocentridae; some studies indicated that Chirocentridae is sister to Clupeidae, a clade referred to as Clupeoidea (Grande 1985; Di Dario 2002), while others have suggested Chirocentridae is the sister to Engraulidae (Di Dario 2009), a hypothesis that has remained untested. Previous molecular data suggested that Chirocentridae is nested within Clupeidae and that Pristigasteridae is sister to Clupeidae (Lavoue et al. 2007; Li and Orti 2007).

Within Clupeidae, Grande (1985) noted there are no osteological characters that support the monophyly of Dorosomatinae, Alosinae, and Clupeinae, and that these taxa are artificial groupings that fail to reflect phylogenetic relationships. Recent molecular studies have further questioned the monophyly of these taxa, and that of Pellonulinae (Lavoue et al. 2007; Li and Orti 2007; Wilson et al. 2008). However, limited taxon sampling has hampered all of these studies, with no more than 12% of all clupeiforms included in any study.

In this study we assembled the largest molecular data set for Clupeifomes to date, and provide a comprehensive time-calibrated phylogeny for anchovies, herring, sardines and their allies. Using this chronogram and ancestral character analyses, we reconstruct the evolution of marine, freshwater, and diadromous lineages to explicitly test the Gross and the safe-site hypotheses on the origins of diadromous fishes. Finally, we consider the role of diadromy in transitions between marine and continental freshwaters biomes, and test whether diadromy facilitates evolutionary transitions between habitat types.

3.3 Methods

3.3.1 Taxon sampling and molecular data

Our strategy was to include the broadest taxon sampling possible for clupeiforms. To accomplish this, we identified four candidate genes (rag1, rag2, cytb, 16s) from previously published studies (Lavoue et al. 2007; Li and Orti 2007; Lavoue et al. 2008; Wilson et al. 2008; Lavoue et al. 2010; Bloom and Lovejoy 2012) to form the core of our data set. We added to this matrix newly generated sequence data for available taxa and data available on Genbank (Table 3.1). Whenever possible we included sequence data collected from the same individual for multiple genes. Our approach results in a modest amount of missing data, and maximizes taxon sampling. The data set includes 153 species from 64 of the 84 currently recognized genera of Clupeifomes. For outgroups, we included Cyprinus carpio (Cypriniformes), Ictalurus punctatus (Siluriformes), Hepsetus odoe (Characiformes), and Chanos chanos (Gonorynchiformes), which comprehensively cover Ostariophysi, the sister group to Clupeomorphs (Lecointre and Nelson 1996). We used Oncorhynchus mykiss (Salmoniformes) to root our phylogeny.

Molecular lab protocols and primer information for newly generated sequences have previously been published (Li and Orti 2007; Bloom and Lovejoy 2012). Whenever possible, two or more specimens per species were sequenced for each gene and preliminary analyses were conducted as a measure of quality control. Duplicate species representatives were removed for all subsequent analyses. Sequences were edited using the computer software Geneious v5.4 (Drummond et al. 2010) and aligned using the MUSCLE plugin (Edgar 2004) implemented in Geneious. For alignment of the 16s data, we also used the Clustal X (Thompson et al. 1997) plugin in Geneious to employ a range of gap opening and extension parameters to test the robustness of the MUSCLE alignment. Protein coding genes were translated to amino acids to confirm open reading frames. Following alignment, we concatenated all four genes into a single matrix consisting of 5211bp. The final matrix includes data for >70% of all possible cells and comprises data from 152 species for 16s (1352bp), 155 species for cytb (1131bp), 98 species for rag1 (1491bp), and 102 species for rag2 (1237).

3.3.2 Phylogeny and diversification time estimation

We conducted phylogenetic inference using maximum likelihood (ML) and Bayesian methods. Our maximum likelihood phylogenetic reconstructions were conducted using the program RAxML v7.3 (Stamatakis 2006). For ML estimates we used the best partitioning strategy chosen by PartitionFinder and a GTRGAMMA model for each partition. We estimated support for nodes using the rapid-bootstrapping algorithm for 1000 non-parametric bootstrap replicates. We performed two additional ML searches to ensure we searched tree space thoroughly and were not trapped on a local optima.

We jointly estimated phylogeny and diversification times using a Bayesian relaxed clock method (Drummond et al. 2006) in the program BEAST v1.7.2 (Drummond et al. 2012). We used an uncorrelated lognormal tree prior and a birth-death prior for rates of cladogenesis. Several initial BEAST runs showed that the partitioning strategy chosen by PartitionFinder resulted in over- parameterization, so the dataset was partitioned by gene with partitions unlinked and a GTR model with gamma-distributed rate heterogeneity used for each partition. We ran four independent analyses for 300 million generations, sampling every 1,000th generation. We used Tracer 1.5 (Drummond and Rambaut 2007) to evaluate convergence and mixing of runs and to verify that effective sample sizes were >200 for all parameters. We determined that the first 50 million generations from the MCMC sample were a conservative burn-in. The two converged runs were combined using LogCombiner v1.6.1 (Drummond and Rambaut 2007) and the maximum credibility tree was generated in TreeAnnotator v1.6.1 (Drummond and Rambaut 2007).

To determine absolute divergence times, we used eight fossil and biogeographic age calibrations with exponential priors to set a hard minimum and soft maximum bound (Ho and Phillips 2009). Several of the fossil calibrations have been used in recent studies (Wilson et al. 2008; Alfaro et al. 2009; Santini et al. 2009), however we include additional clupeiform fossils that have not yet been included in diversification time analysis of this group. Our calibrations include:

1) For the MRCA of ostarioclupeomorpha we used Tischlingerichthys viohli from the Thitonian (early Jurrasic; 149ma), the oldest known crown species of this group (Arratia 2004a). We used Anaethalion, the oldest stem elopomorph from the late Kimmeridgian (Jurassic; 152ma) (Arratia 2004b) for the 95% upper boundary.

2) We used the oldest known crown Ostariophysi, Gordichthys and Rubiesichthys from the Berriasian-Barrermian boundary (125ma), for a minimum age of the MRCA of this group (Poyato-Ariza 1996). For the 95% upper bound we used the oldest known crown ostarioclupeomorpha, Tischlingerichthys viohli from the Thitonian (early Jurrasic; 149ma).

3) For the MRCA of Clupeidae+Sundasalangidae we used the oldest crown Clupeidae, Nolfia riachuelensis from Albian (late Lower Cretaceous, 99ma) marine deposits in northeastern Brazil (Figueiredo 2009b). The 95% upper boundary was determined by the oldest stem clupeomorphs (Murray et al. 2005; Figueiredo 2009b, a) from the Barremian (Lower Cretaceous; 125ma).

4) For the MRCA of Pristigasterids, we used Gasteroclupea branisai, the oldest crown Pristigasteridae from the late Cretaceous (67ma) (Grande 1985). The 95% upper boundary was determined by the oldest stem clupeomorphs from the Barremian (Murray et al. 2005; Figueiredo 2009b, a).

5) A fossil of Dorosoma petenense from the Gatuña Formation in southeastern New Mexico dated to the Pliocene-Pleistocene boundary (2.5ma) was used for the MRCA of Dorosoma petenense and Dorosoma cepedianum (Miller 1982). The 95% upper boundary for this node was determined by Nolfia riachuelensis from the Albian (late Lower Creteaceous, 99ma, the oldest known crown Clupeidae (Figueiredo 2009b).

6-8) The following pairs of anchovies are each sister taxa separated by the Isthmus of Panama: 1) Cetengraulis edentulus / C. mysticetus, 2) Anchovia macrolepidota / Anchovia clupeoides, and 3) Lycengraulis grossidens / L. poeyi (Nelson 1984a; Whitehead et al. 1988; Bloom and Lovejoy 2012). For each species pair we used a minimum age of 3.0ma. For a 95% upper bound we used the oldest crown Pristigasteridae, Gasteroclupea branisai, from the late Cretaceous (67ma).

3.3.3 Ancestral character reconstructions

We used ancestral character reconstruction to determine the history of diadromous, marine and freshwater lineages. Each species was coded for a discrete, unordered character (biome requirement) with four states: marine (0), freshwater (1), anadromous (3), or catadromous (4). Diadromy is generally defined as a behavior, but it can also be conceptualized as a habitat (biome) requirement that changes over ontogeny. For this study, we treated occupancy in exclusively marine or freshwater biomes, and each mode of diadromy, as distinct habitat requirements and character states. Our coding scheme assumes that biome requirement evolved in an ancestor-descendant manner, a necessary requirement for using ancestral character reconstruction. Some species are thought to be facultatively diadromous, in which not all individuals migrate (e.g. alewife) (McDowall 2003). We coded facultative diadromous species as having the respective diadromous state (anadromous or catadromous).

We used the program Mesquite version 2.73 (Maddison and Maddison 2011) to conduct and maximum parsimony (MP) and maximum likelihood (ML) character reconstructions. Character states from ML reconstructions were considered unambiguously reconstructed when the log- likelihood was 2.0 units higher than the alternative state. For ML reconstructions we used the Mk model (Pagel 1999). By conducting these reconstructions on our time-calibrated phylogeny we are able to determine the number, order, and timing of transitions between marine, freshwater and diadromous life histories in clupeiforms.

3.4 Results

3.4.1 Phylogenetic relationships

The best ML tree (-lnL = -147977.650367) with bootstrap support values is shown in Figure 3.3. Our results show that Clupeiformes are not monophyletic because Denticeps clupeoides was sister to all remaining Ostarioclupeomorphs. However, clupeoidei (all Clupeiformes except Denticeps) was well supported as monophyletic. Our higher-level relationships among clupeiforms indicate that Chirocentridae is sister to Engraulidae with bootstrap of 93% and posterior probability of 1.0. Pristigasteridae was well supported as monophyletic and our ML tree

places this clade as sister to the Engraulidae + Chirocentridae clade (but bootstrap <70%), but our BEAST analysis recovers Pristigasteridae as sister to Clupeidae (PP = 0.98).

We found that Clupeidae is not monophyletic because Spratelloidini (Spratelloides + Jenkinsia) (Grande 1985) was sister to all other Clupeiformes, rather than part of the Clupeidae clade in both the ML and BEAST trees. This is a novel placement for Spratelloidini, which was previously considered sister to Dussumieriini, forming the clade Dussumieriinae. The BEAST tree also places Gilchristella+Sauvagella as sister to all other Clupeiformes except the Spratelloidini clade. Sundasalanx mekongensis (Sundasalangidae) was nested within Clupeidae as a member of the Ehiravini clade (Grande 1985; Stiassny 2002) in the ML tree and in the same clade excluding Gilchristella+Sauvagella in the BEAST tree. We also did not find support for the monophyly of Alosinae, Clupeinae, Dorosomatinae, or Pellonulinae; instead the members of these previously recognized groups were spread throughout Clupeidae. Our analyses provide the first molecular support for Pellonulini; however, our analyses indicate that this clade is not sister to Ehiravini as previously suggest (Grande 1985).

Engraulidae was well supported as a monophyletic clade with a bootstrap of 100% and posterior probability of 1.0. The relationships among engraulids were well resolved and supported the monophyly of both Engraulinae, comprised of New World anchovies and Indo-Pacific genera Stolephorus and Encrasicholina, and Coilinae, the remaining Indo-Pacific genera. Engraulini (New World anchovies) are well supported as a monophyletic group.

3.4.2 Diversification times

The diversification time estimates for Clupeiformes are shown in Figures 3.4 and 3.5. The mean posterior age for the MRCA of Clupeiformes dated to the Early Cretaceous (117.2 Ma). Clupeidae was the oldest major lineage dating to the Early Cretaceous with a mean posterior age for the MRCA of 81.8 Ma. The mean posterior age for the MRCA’s of Engraulidae (72.8 Ma) and Pristigasteridae were nearly synchronous, dating (69.6 Ma) to end of the Late Cretaceous.

3.4.3 Ancestral character reconstructions: Evolution of diadromy

Our ancestral character reconstructions indicate that catadromy evolved twice and anadromy independently evolved five times in Clupeiformes. Amphidromy may have evolved once (see discussion). In general, diadromous clupeiform lineages are monotypic and often in their own genus (Alosa is a notable exception); therefore the ages reported below are stem ages unless explicitly stated otherwise.

The catadromous herring species Potamalosa richmondia was derived from a marine ancestor in the temperate regions of southeastern Australia and dated to the Oligocene (27.3 Ma). Ethmalosa fimbriata is a tropical catadromous herring species from the eastern Atlantic and western African rivers, and was derived from a marine ancestor and is sister to a clade of freshwater herring from Africa. The stem age of E. fimbriata dates to the Eocene (38.5 Ma).

The earliest instance of anadromy is Clupeonella cultriventris, which dates to 65 Ma. C. cultriventris is a temperate anadromous lineage derived from a marine ancestor, although this is a tentative assessment because the phylogenetic placement of this species is not well supported. Our analyses indicate that seven anadromous species in the genus Alosa from temperate eastern North America and Eurasia were derived from a marine ancestor and had a stem age of 17 Ma and a crown age of 8.9 Ma, giving this clade a Miocene origin. Nested within the anadromous Alosa clade is a purely freshwater species (Alosa chrysochloris). Of the five anadromous lineages, there were three separate instances of an anadromous lineage evolving from a freshwater ancestor, all of which occurred in tropical regions. Southeast Asian diadromous shad also date to the Miocene (Tenualosa ilisha; 11.6 Ma). The anadromous tropical anchovies from northeastern South America date to the Miocene (Anchoviella lepidentostole; 14.5 Ma), and Pliocene (Lycengraulis grossidens; 4.6 Ma).

3.4.4 Ancestral character reconstructions: Marine/freshwater transitions

Our analyses show that Clupeiformes are an ancestrally marine group that invaded continental freshwaters 12 times (excluding diadromous lineages). There were only three only reversals (freshwater to marine), all of which occurred in New World anchovies along the northeastern

coast of South America. Lineages rarely invaded freshwaters in the same geographic area more than once (Appendix 1). Freshwater lineages are generally much more diverse than diadromous lineages. In, fact Alosa is the only diadromous lineage that is not monotypic (see above). Freshwater clupeiform lineages are particularly diverse in South America (mostly anchovies), southeastern Asia, and western Africa.

3.5 Discussion

3.5.1 Phylogenetic relationships and divergence times in Clupeiformes

The higher-level relationships among Clupeiformes have proven difficult to resolve. Even the monophyly of Clupeiformes has been questioned recently because Denticeps clupeoides, the lone extant representative of Denticepitoidei, has been grouped with Ostariophysi (Li and Orti 2007) or as the sister to Ostariophysi and all other clupeiforms (Wilson et al. 2008). Our study is consistent with the latter arrangement, however bootstrap and posterior probabilities were low. The inclusion of Denticeps in Clupeiformes has been supported by mitogenomics (Lavoue et al. 2007) and Li and Orti (2007) argued that the exclusion of Denticeps from Clupeiformes is a result of GC compositional bias in rag genes. A large-scale study on Actinopterygii phylogenetics including nine nuclear genes supported Denticeps as a clupeiform (Near et al. 2012). Morphological data has placed Denticeps in Clupeiformes based on the presence of a recessus lateralis, a definitive synapomorphy for Clupeiformes (Grande 1985; Di Dario 2004). Di Dario (2004) proposed the recessus lateralis should not be used as a single presence/absence character, but rather is a character complex comprising several syanpomorphies for Clupeiformes (including Denticeps), further strengthening the hypothesis that Denticeps is a clupeiform. We predict that future studies including multiple nuclear genes and extensive sampling of clupeiforms will corroborate the hypothesis that Denticeps is a clupeiform.

Several studies have yielded conflicting evidence for the phylogenetic placement of Chirocentridae within Clupeiformes. Chirocentridae is comprised of two species (Chirocentrus dorab & C. nudus) commonly referred to as wolf herring because they are pelagic predators with large jaws and fang-like canines, an elongate body, and deeply forked caudal fin. Determining the position of this lineage has proved challenging in part because of this anomalous morphology 53

for a clupeiform. Grande (1985) grouped Chirocentridae with Clupeidae based on a high ratio of ribs to preural vertebrae, although the interpretation of this character was later shown to be ambiguous (Di Dario 2009). However, Patterson and Johnson (1995) support the Chirocentridae+Clupeidae relationship based on the fusion of epicentrals with anterior ribs, and Miyashita (2010) argued for a Pristigasteridae+Clupeidae+Chirocentridae clade based on a W- shaped occipital articulation in the first vertebra. Several molecular studies have indicated that Chirocentridae is sister to Spratelloidini (the latter clade discussed below), and nested within Clupeidae (Lavoue et al. 2007; Li and Orti 2007; Wilson et al. 2008; Lavoue et al. 2010). Di Dario (2009) proposed that Chirocentridae is sister to Engraulidae (anchovies); this novel phylogenetic hypothesis was based on seven morphological characters from the suspensorium, branchial arches, and infraorbitals. Our study provides the first molecular support for Chirocentridae and Engraulidae as sister taxa and the weight of the evidence supports the decision to include Chirocentridae in Engrauloidea (Di Dario 2009).

The affinity of Pristigasteridae continues to be one of the most uncertain elements of higher-level clupeiform phylogenetics. Morphological studies have placed pristigasterids either in a polytomy with engraulids and clupeids, or as sister to all other clupeiforms except Denticeps (Grande 1985; Di Dario 2002, 2009). Molecular evidence has pointed towards a close relationship between Clupeidae and Pristigasteridae; studies based on mitochondridal data suggest Clupeidae is sister to Pristigasteridae (Lavoue et al. 2007; Wilson et al. 2008; Lavoue et al. 2010), while a combined nuclear and mitochondrial study found Pristigasteridae was nested within Clupeidae (Li and Orti 2007), but neither study had statistical support for these respective topologies. Our ML analysis recovered Pristigasteridae as sister to Engrauloidea (Engraulidae+Chirocentridae), but this was not statistically supported. Our BEAST analysis supports Pristigasteridae as sister to Clupeidae (PP =0.98). Given that our data set includes genes with a wide range of substitution rates, the BEAST may be better able to accommodate this heterogeneity and provide a more robust phylogenetic inference (Drummond et al. 2006).

The monophyly of Clupeidae has been questioned because studies have shown that Chirocentridae, Pristigasteridae, and Sundasalangidae are nested within this group. Our results

only support the latter as a member of Clupeidae (see above). However we also find the Spratelloidini are sister to all remaining clupeiforms, rather than sister to the Dussmieriini. The proposed Spratelloidini+Dussmieriini relationship forms the Dussumieriinae, and is supported by the presence of a W-shaped, un-keeled pelvic scute unique to these lineages (Grande 1985). Based on morphological data, Nelson (1970) suggested that Dussumieriinae is a basal clupeid, implicitly recognizing they are distinct from other clupeids. Moreover, Li and Orti (2007) reported a low GC composition in Spratelloides delicatulus and the presence of an undescribed intron in both rag1 and rag2 for Spratelloides gracilis. Thus, there is concordant evidence that these taxa have a unique evolutionary history among clupeids. We excluded the introns from our dataset and other members of Spratelloidini have nucleotide compositions comparable to other clupeiforms, suggesting this is not biasing our results. Nonetheless, Dussumierinae (including Spratelloidini) possess two long, rod-like postcleithra, the only morphological synapomorphy proposed for Clupeidae (Grande 1985). The conflicting evidence discussed here suggests future studies are needed to confirm the exclusion of Spratelloidini from Clupeidae.

Members of Clupeidae have traditionally been divided into five so-called subfamilies: Alosinae, Dorosomatinae, Clupeinae, Dussumieriinae, and Pellonulinae. However, there has been little evidence that any of these proposed groups are monophyletic. Grande acknowledged that Alosinae, Dorosomatinae, and Clupeinae were simply “groups of convenience” with no morphological characters supporting these clades. While previous molecular studies had limited taxon sampling to test the monophyly of these groups, no study has found convincing support for these three clades. The Ehiravini and Pellonulini were thought to be sister taxa that together comprised the Pellonulinae, based on the loss of anterior supramaxilla (Grande 1985). However, this character state also occurs in Dussumieriinae, Dorosomatinae, and Engrauloidea (Grande 1985) and molecular studies show there is no evidence for the Ehiravini+Pellonulini relationship (Wilson et al. 2008; this study). Our study corroborates the non-monophyly of Alosinae, Dorosomatinae, and Pellonulinae, and Dussumieriinae and suggests these taxonomic names need to be redefined or dropped from use altogether.

While the clades recognized as subfamilies within Clupeidae are clearly in need of revision, we do find support for the monophyly of Pellonulini, but not Ehirvani. Pellonulini is a freshwater clade restricted to western and central Africa, and includes Pellonula, Odaxothrissa, Microthrissa, Limnothrissa, Stolothrissa, Potamothrissa, Sierrathrissa, Nanothrissa, Poecilothrissa, Laeviscutella, Thrattidion, Congothrissa, and Cynothrissa. The Pellonulini are diagnosed by the articulation of the postcleithrum with the supracleithrum occurring well behind the cleithrum (Grande 1985). This character state was apparently independently derived in the Ehiravini genera Clupeichthys and Ehirava (Grande 1985), although Ehirava has never been included in a molecular study. Ehiravini is a freshwater clade from southern Africa, Madagascar, and southeastern Asia, comprised of Spratellomorpha, Sauvagella, Dayella, Ehirava, Clupeichthys, Corica, Spratellomorpha, and Gilchristella; this clade is diagnosed by the unique elements in sensory canals and caudal fin structure (Grande 1985; Stiassny 2002). Our ML results recover these taxa as a clade (although with no bootstrap support), but also find that Sundasalanx mekongensis (Sundasalangidae) is nested within this clade. However, our BEAST analysis suggests Ehiravani is paraphyletic because Gilchristella+Sauvagella is sister to all other clupeiforms rather than closely related to other members of Ehiravini.

Our results were largely consistent with a recent study on the phylogenetics of engraulids (Bloom and Lovejoy 2012). The Indo-Pacific anchovies in Coilinae, which include Coilia, Thryssa, Lycothrissa, and Setipinna, are well supported as monophyletic. Coilinae is sister to Engraulinae, which includes the Indo-Pacific genera Stolephorus and Encrasicolina, and the New World anchovy clade Engraulini. In this study, our analyses indicate that Stolephorus may be paraphyletic, which has not previously been reported (Bloom and Lovejoy 2012). Engraulini is well supported as a monophyletic clade. Within Engraulini, Engraulis ringens and E. anchoita are sister to two large clades, the first comprised of New World marine anchovies and the second comprised mostly of South American freshwater anchovies.

In his comprehensive monograph, Grande (1985) declared the phylogenetic relationships of Alosinae, Dorosomatinae, and Clupeinae are “the greatest remaining problem in Clupeomorph systematics”. Our study reveals that the uncertainty of interrelationships among clupeomorphs,

which include some of the worlds most economically and ecologically important fishes of all time, is much farther-reaching than previously known. The current taxonomy of these fishes is clearly in need of revision.

Our diversification time estimates indicate that the MRCA of Clupeiformes dates to the Early Cretaceous. The major clupeiform clades, pristigasterids, engraulids, and clupeids, date to the Early to Late Cretaceous. Our age estimates are older than those of Wilson et al. (2008), who estimated a date of ~80 Ma for the MRCA of Clupeiformes and ~64 Ma for Clupeidae. The taxon sampling for engraulids and pristigasterids in Wilson et al.’s study was too low to estimate ages for these groups. However, a recent study (Near et al. 2012) on higher-level fish relationships and ages suggested that crown Clupeiformes date at least to 175 Ma, which is much older than the maximum age (126.7 Ma) from the 95% HPD of this node from of our study. Our chronogram indicates that much of the diversity of clupeiforms originated during the Eocene to more recent, which is consistent with the diversity of Clupeiformes in the fossil record (Grande 1982, 1984, 1985; Grande and Nelson 1985; Murray et al. 2005; Figueiredo 2009b, a). Our chronogram for Clupeiformes provides a temporal context for future studies to investigate how paleogeographic events shaped the evolutionary history of this ecologically and economically important group.

3.5.2 Evolution of diadromy – Testing the Gross hypothesis

Diadromous fishes undergo (often spectacular) migrations between marine and freshwaters for feeding and reproduction. Diadromous fishes include a number of socially and economically important species, and so not surprisingly have been a long-standing fascination of biologists (Roule 1933; Talbot and Sykers 1958; McDowall 1988). More importantly, diadromy has significant implications for the ecology, evolution and biogeography of fishes (McDowall 1999; McDowall 2001; Waters and Wallis 2001; McDowall 2008a), particularly in clupeiforms because this group includes an unusually high proportion of diadromous species (McDowall 2003). Despite the longstanding interest and biological implications, the evolutionary origins of diadromy have rarely been studied. Here we present the first phylogenetic analysis of the evolution of diadromy in herring, sardines, anchovies and their allies, and one of only a few such

studies in any group. We find that clupeiforms were an ancestrally marine group that independently evolved anadromy five times (possibly more), and catadromy twice. Only one of these seven diadromous lineages shows a pattern that is (partially) consistent with Gross’s predictions. Our results suggest that viewing productivity as the primary determinate for where and when each mode of diadromy will evolve (Gross 1987; Gross et al. 1988) is overly simplistic and not a robust general model.

As a scenario for the origin of catadromy, the Gross hypothesis predicts that a marine (euryhaline) ancestor would first invade tropical freshwaters to capitalize on the higher productivity of this environment. The fitness gain from these freshwater excursions would lead to annual migration to freshwaters for an extended period of growth, yielding catadromous lineages. Over time, the migration back to the natal marine habitat would cease, severing the link to the marine environment, and yielding an endemic, entirely freshwater lineage (Gross 1987; Gross et al. 1988). Our results show that the catadromous African bonga shad, Ethmalosa fimbriata, was derived from a marine ancestor, a pattern consistent with Gross’s model for diadromy in the tropics. Furthermore, E. fimbriata is sister to a clade of freshwater herring (Pellonulini) that has diversified in African rivers and lakes (Wilson et al. 2008). The pattern of a freshwater clade closely related to a tropical catadromous lineage is consistent with Gross’s model. The close affinity of Ethmalosa and Pellonulini needs to be further investigated because our results did not provide strong statistical support for this relationship. Nonetheless, if this topology is correct, this clade represents an interesting opportunity for comparative studies of the traits such as egg size, age at maturity, maximum size, and fecundity that Gross used in his model (Gross 1987).

The second catadromous lineage shows a pattern that is inconsistent with the Gross hypothesis. The Australian catadromous herring Potamalosa richmondia was derived from a marine ancestor and is sister to Hyperlophus, a marine lineage that occurs along the southern and eastern coasts of Australia. However, P. richmondia occurs in temperate rather than tropical regions. Further, P. richmondia does not have close phylogenetic affinity to freshwater lineages, despite having more than 25 million years to produce a freshwater descendant. The only non-diadromous

freshwater clupeid in Australia is Nematalosa erebi, which is phylogenetically distant from P. richmondia, and is related to a different set of marine species (Fig. 3.4).

Although few other catadromous lineages have been studied in detail, the pattern of marine ancestry for catadromous fishes may be fairly general (McDowall 1988). Anguillid eels are the best-known and most species-rich catadromous group. These widespread fishes were derived from a deep-sea ancestor, and while they may have originated in the tropics (Inoue et al. 2010), many catadromous eels migrate to temperate freshwaters, not tropical freshwaters. These migrations to temperate freshwaters contradict Gross’s predictions because temperate freshwaters have relatively low productivity. Furthermore, catadromous eels have never yielded freshwater lineages, or even produced landlocked forms (McDowall 2001) even though as a group they have a broad distribution suggesting ample opportunity for landlocking. McDowall (1997) also argued against Gross’s hypothesis because there is no example of an amphidromous precursor to a catadromous lineage. We agree that amphidromy is not an intermediary stage in the pathway to catadromy (or anadromy), but removing this step does not reject the major tenets of the Gross model. Regardless, phylogenetic evidence from clupeiforms provide little support for the Gross hypothesis on the origin of catadromous lineages.

Gross’s model posits a mirror opposite pattern for the origins of anadromous fishes. Gross’s scenario proposes that a freshwater ancestor in temperate regions would start by making excursions into more productive marine habitats for feeding and growth. Initially, this would involve a euryhaline wanderer, which eventually would give rise to an anadromous lineage. Over time the annual migrations from freshwater to marine habitats would cease, resulting in an entirely marine descendant. We find no evidence in clupeiform lineages to support Gross’s predictions for the origins of anadromy. Three of the five anadromous lineages Tenualosa ilisha, Lycengraulis grossidens, and Anchoviella lepidentostole, were each independently derived from a freshwater ancestor. However, these lineages all occur in tropical rather than temperate regions. On the other hand, the well-known anadromous Alosa spp. and the lesser-known Clupeonella were independently derived from marine ancestors but these taxa occur in temperate regions. Thus, none of the anadromous clupeiform lineages fit the Gross model.

Other diadromous fish groups also fail to show show clear patterns supporting the Gross hypothesis (McDowall 1988). Some anadromous groups such as sticklebacks (Kawahara et al. 2009), smelts (Dodson et al. 2009) occur in temperate areas, but are derived from marine ancestors. Anadromous ariid catfishes (Betancur-R 2010; Betancur-R et al. 2012) are derived from marine ancestors and occur in tropical regions. Thus, none of these lineages fit Gross’s model. Salmonids have a complicated history, but anadromous lineages likely evolved from freshwater ancestors and occur in temperate regions (McLennan 1994; Dodson et al. 2009), thus salmonids are only group that is consistent with Gross’s model. The preponderance of phylogenetic evidence indicates that other factors that are at least as important as productivity in the origins of diadromy.

3.5.3 Evolution of diadromy – Alternatives to the Gross hypothesis

Another important aspect of the evolution of diadromy is likely predation. Dodson et al. (2009) proposed the safe-site hypothesis which suggests a marine ancestor would migrate to freshwater habitats to reproduce in freshwater habitats that have lower predation pressure. Over time, a population would stop returning to the sea, leaving entirely freshwater descendants (Dodson et al. 2009). Alosa shows a pattern that fits the safe-site hypothesis; an anadromous clade was derived from a marine ancestor and gave rise to a fully freshwater lineage (A. chrysochloris). Clupeonella cultriventris was also derived from a marine ancestor, but is sister to a clade that includes both marine and freshwater members. This pattern does not fit the safe-site hypothesis because once a lineage has successfully established itself in freshwater, there should be no advantage to returning to the marine environment. The remaining anadromous lineages (T. ilisha, A. lepidentostole, and L. grossidens) were derived from freshwater ancestors and thus do not support the safe-site hypothesis. Dodson et al. (2009) found that phylogenetic data for smelts (Osmeroidei) supported the safe-site hypothesis, but not for salmonids. There is limited support for the safe-site hypothesis in clupeiforms (one of five anadromous clupeiform lineages), but some evidence in other fish groups. However more work is needed to determine whether the clades that have a phylogenetic pattern consistent with the safe-site hypothesis actually experience a reduction in predation in freshwater habitats compared to the marine environment.

Competition has been suggested as a mechanism determining macroevolutionary transitions between marine and freshwater lineages (Betancur-R et al. 2012; Bloom and Lovejoy 2012), and the same factors likely play a role in determining which geographic regions diadromous species are able to invade (McDowall 2008b). This hypothesis is based on the concept that competition will be strongest among closely related taxa (Wiens et al. 2006; Wiens et al. 2010; Violle et al. 2011). In clupeiforms, diadromy generally does not evolve multiple times in the same geographic area (Fig 3.5), suggesting that once a diadromous lineage invades a region, it may prevent ecologically similar species from evolving the same migratory behavior. Anadromous species also tend to predominate in regions with low species diversity such as high northern latitudes, which McDowall (2008b) argued was a result of the dispersal ability of diadromous species as well as reduced competition from incumbent species. Catadromous species may migrate to freshwaters because there is reduced competition during the juvenile and adult feeding stage. For example, there are many marine eel lineages, but catadromous anguillid eels are the only eels found in freshwater habitats (Inoue et al. 2010). Thus freshwaters may offer a low competition environment in which anguillid eels can reach maturity before returning to the ocean for a brief period to spawn. Although Gross (1987) argued that intraspecific competition does not explain the origins of diadromy, there is growing evidence (albeit mostly indirect) that diadromous species exploit areas of reduced interspecific competition (McDowall 2008b), and we suggest future studies should investigate the origins of diadromy with competition in mind.

There are a few caveats to our conclusions. Some of our results are preliminary due to the incomplete taxon sampling of putative congeneric taxa. Specifically, the tropical Indo-Pacific genus Tenualsoa includes three additional species in the genus, all of which are considered anadromous. The lone freshwater species, T. thibaudeaui (included in our data set), could either be the basal member of this clade, or nested within the anadromous clade. Also, as we noted earlier, the phylogenetic placement of Clupeonella is uncertain, and our data set includes only one of four species in the genus. The missing taxa consist of one freshwater and two marine species. Clearly our conclusions for the evolution of diadromy will need to be reinterpreted in light of more comprehensive phylogenies for these particular clades. Further, the extent that the putatively anadromous anchovies migrate into freshwater is questionable. Neither L. grossidens

nor A. lepidentostole have been caught far inland and it is unclear that these incursions are tightly linked to spawning or if these species are best categorized as euryhaline wanderers (McDowall 1987, 1988, 1992). Interestingly, both anchovy species are frequently caught in estuaries near river mouths (along with many other marine taxa), suggesting the tight link to freshwater (their ancestral habitat) has not been severed. Indeed, these taxa are apparently feeding in the highly productive Neotropical river mouths along the coast of South America (DDB, personal observation). Future studies should investigate what extent of these species’ diet is comprised of continentally (freshwater) derived origins.

Taken together, our results and those of other studies suggest that Gross’s model for the origins of diadromy fit some lineages, but not most. While productivity may play a role in the origin and maintenance of diadromy, the prominence of this role is contingent on the lineage in question; other mechanisms likely have an equal or greater influence in some clades. Further elucidating the processes involved in the evolution of diadromy will require investigating migratory behavior in non-diadromous lineages. Some freshwater riverine fishes are known to be migratory, and many marine fishes undergo migrations. The comparison of migration within a single biome with migration across biomes (diadromy) may offer clues into the factors are most important in the origins of diadromy.

3.5.4 Is diadromy a pathway for marine/freshwater evolutionary transitions?

An expected outcome in both the Gross and safe-site hypotheses is that diadromy is a precursor to a permanent transition between marine and freshwater biomes in fish lineages. The basic concept is intuitively appealing; a species that migrates between marine and freshwaters becomes isolated in one habitat and successfully establishes a permanent population, which over time results in speciation and subsequent diversification. The expected phylogenetic pattern from this process, assuming extinction has not erased the ancestor, is illustrated in Figure 3.2. Clupeiformes were seemingly a likely candidate group for fulfilling this scenario because there were many diadromous, marine, and freshwater species. However, we find that diadromy has played a minimal role (if any) in transitions between marine and freshwater biomes (Fig. 3.5). To

date, we lack an empirical example of a freshwater lineage evolving via catadromous ancestry (Ethmalosa is a possible exception), or an exclusively marine lineage evolving from an anadromous ancestor (McDowall 2001), which are the expected ‘endpoints’ of Gross’s model (Gross 1987). The decoupled relationship between diadromy and biome transitions is a pattern that is repeated in other lineages that have undergone biome transitions and include diadromous lineages (Betancur-R 2010; Betancur-R et al. 2012). There are instances of landlocking generating freshwater populations, including lineages such as shads, salmon and sticklebacks, which in some cases have undergone morphological divergence (McKinnon and Rundle 2002; Palkovacs et al. 2008). Interestingly, these cases are all very recent (Pleistocene or younger), and generally neither diverse nor spread across large geographic areas, suggesting there are constraints on diversification of freshwater populations derived from anadromous ancestors.

3.5.5 Acknowledgements

For tissues and specimens we thank the following people and institutions: Wayne Starnes (North Carolina Museum of Natural History), Andrew Bentley (Kansas University Biodiversity Institute), and Kevin Conway. Allan Baker, Hernán López-Fernández, and Belinda Chang provided helpful feedback on this study. Hernán López-Fernández graciously offered computer computation time for BEAST analyses.

Table 3.1 Taxon sampling, habitat type, and Genbank numbers of specimens used in this study. Habitat is scored as 0=marine, 1=freshwater, 2=anadromous, and 3=catadromous.

Taxa Habitat rag1 rag2 16s cytb

Clupeidae Alosa aestivalis 2 NA DQ912146 DQ912076 EU552615

Alosa alabamae 2 NA DDB4413 DDB4413 DDB4413

Alosa alosa 0 NA NA NC_009575 NC_009575

Alosa chrysochloris 1 DQ912117 DQ912151 DQ912081 DDB4415

Alosa fallax 0 NA NA EU552737 EU552574

Alosa mediocris 2 DDB4418 DDB4418 DDB4418 DDB4418

Alosa pseudoharengus 2 DQ912115 DQ912149 DQ912079 AP009132

Alosa sapidissima 2 DQ912116 DQ912150 DQ912080 EU552616

Anodontostoma chacunda 0 NA NA AP011614 AP011614

Brevoortia aurea 0 NA NA NA EF564665

Brevoortia patronus 0 DQ912105 DQ912138 DQ912068 EU552618

Brevoortia smithi 0 DDB4430 DDB4430 DDB4430 DDB4430

Brevoortia tyrannus 0 DQ912106 DQ912139 DQ912069 EU552614

Clupea harengus 0 DQ912114 DQ912148 DQ912078 EU552606

Clupea pallasii 0 DQ912118 DQ912152 DQ912082 EU552599

Clupeichthys aesarnensis 1 NA NA AP011584 AP011584

Clupeichthys perakensis 1 NA NA AP011585 AP011585

Clupeoides borneensis 1 NA NA AP011586 AP011586

Clupeonella cultriventris 2 NA NA NC_015109 NC_015109

Corica laciniata 1 NA NA AP011589 AP011589

Dorosoma cepedianum 1 DQ912099 DQ912132 DQ912062 EU552586

Dorosoma petenense 1 DDB4422 DDB4422 NC_009580 EU552581

Ehirava fluviatilis 0 NA NA AP011588 AP011588

Escualosa thoracata 0 NA NA AP011601 AP011601

Ethmidium maculatum 0 NA NA AP011602 AP011602

Ethmalosa fimbriata 0 NA NA NC_009582 NC_009582

Etrumeus teres 0 DQ912110 DQ912143 DQ912073 EU552621

Etrumeus whiteheadi 0 NA NA EU552730 EU552567

Gilchristella aestuaria 1 NA NA EU552741 EU552578

Gudusia chapra 1 DDB4409 DDB4409 DDB4409 DDB4409

Harengula humeralis 0 DDB3011 DDB3011 DDB3011 NA

Harengula jaguana 0 DQ912122 DQ912156 DQ912086 EU552617

Hilsa kelee 0 NA NA AP011613 AP011613

Hyperlophus vittatus 0 NA NA EU552750 EU552587

Jenkinsia lamprotaenia 0 DQ912107 DQ912140 DQ912070 EU552613

Konosirus punctatus 0 NA NA NA AB548682

Lile stolifera 0 DDB3311 DDB3311 DDB3311 DDB3311

Limnothrissa miodon 1 NA NA EU552720 EU552553

Microthrissa congica 1 NA NA EU552789 EU552625

Microthrissa royauxi 1 NA NA EU552790 EU552626

Nematalosa erebi 1 NA NA EU552755 EU552592

Nematalosa japonica 0 NA NA NC_009586 NC_009586

Odaxothrissa vittata 1 DQ912131 DQ912167 DQ912096 NC_009590

Opisthonema libertate 0 NA DDB3329 DDB3329 DDB3329

Opisthonema oglinum 0 DQ912111 DQ912144 DQ912074 EU552620

Pellonula vorax 1 NA na EU552792 EU552628

Pellonula leonensis 1 DQ912130 DQ912166 DQ912095 EU552624

Potamalosa richmondia 1 NA NA AP011594 AP011594

Potamothrissa obtusirostris 1 NA NA EU552787 EU552623

Ramnogaster sp. 0 NA NA NA GQ890211

Rhinosardinia amazonica 1 NA NA EU552713 EU552550

Rhinosardinia bahiensis 1 DDB500 DDB500 DDB500 DDB500

Sardina pilchardus 0 NA DQ912158 NC_009592 AF472582

Sardinella aurita 0 DQ912104 DQ912137 DQ912067 EU552619

Sardinella lemuru 0 DDB3223 NA DDB3223 DDB3223

Sardinella maderensis 0 NA NA NC_009587 NC_009587

Sardinops sagax 0 NA NA NC_002616 EU552565

Sauvagella madagascariensis 1 NA NA EU552773 EU552610

Sauvagella robusta 1 NA NA EU552770 EU552608

Sierrathrissa leonensis 1 NA NA EU552756 EU552593

Spratelloides delicatulus 0 DQ912128 DQ912164 NC_009588 NC_009588

Spratelloides gracilis 0 DQ912129 DQ912165 NC_009589 NC_009589

Spratelloides robustus 0 NA NA EU552786 NA

Sprattus antipodum 0 NA NA AP011608 AP011608

Sprattus muelleri 0 NA NA AP011607 AP011607

Sprattus sprattus 0 NA NA AP009234 AP009234

Stolothrissa tanganicae 1 NA NA EU552719 EU552552

Tenualosa ilisha 2 NA NA DQ400344 EU552622

Tenualosa thibaudeaui 1 NA NA AP011604 AP011604

Chirocentridae Chirocentrus dorab 0 DQ912127 DQ912163 AP006229 NC_006913

Denticipitidae Denticeps clupeoides 1 DQ912100 DQ912133 DQ912063 EU552629

Engraulidae Amazonsprattus scintilla 1 JQ012538 JQ012667 JQ012456 JQ012351

Anchoa cubana 0 JQ012550 JQ012705 JQ012447 JQ012342

Anchoa lyolepis 0 JQ012573 JQ012688 JQ012449 JQ012344

Anchoa cayorum 0 JQ012555 JQ012700 JQ012451 JQ012347

Anchoa mitchilli 0 JQ012552 JQ012698 JQ012462 JQ012357

Anchoa walkeri 0 JQ012568 JQ012713 JQ012474 JQ012369

Anchoa nasus 0 JQ012575 JQ012690 JQ012478 JQ012373

Anchoa chamensis 0 JQ012563 JQ012718 JQ012480 JQ012375

Anchoa parva 0 JQ012558 JQ012702 JQ012482 JQ012377

Anchoa lamprotaenia 0 JQ012630 JQ012696 JQ012484 JQ012379

Anchoa colonensis 0 JQ012559 JQ012716 JQ012488 JQ012383

Anchoa panamensis 0 JQ012570 JQ012712 JQ012497 JQ012392

Anchoa mundeoloides 0 JQ012565 JQ012715 JQ012524 JQ012419

Anchoa delicatissima 0 JQ012557 JQ012704 JQ012453 JQ012348

Anchoa schofieldi 0 JQ012571 JQ012711 JQ012454 JQ012349

Anchoa filfera 0 JQ012542 JQ012722 JQ012492 JQ012387

Anchoa spinifer 0 DDB4206 DDB4206 DDB4206 DDB4206

Anchoa sp. 0 DDB4271 DDB4271 DDB4271 DDB4271

Anchovia macrolepidota 0 JQ012561 JQ012709 JQ012499 JQ012394

Anchovia surinamensis 1 JQ012613 JQ012665 JQ012507 JQ012402

Anchovia clupeoides 0 DDB4274 DDB4274 DDB4274 DDB4274

Anchoviella guianensis 1 JQ012606 JQ012657 JQ012429 JQ012324

Anchoviella alleni 1 JQ012598 JQ012655 JQ012438 JQ012333

Anchoviella alleni 1 JQ012628 JQ012669 JQ012440 JQ012335

Anchoviella sp. 2 1 JQ012581 JQ012648 JQ012442 JQ012337

Anchoviella carrikeri 1 JQ012605 JQ012659 JQ012444 JQ012339

Anchoviella sp. 1 1 JQ012589 JQ012677 JQ012458 JQ012353

Anchoviella balboae 0 JQ012566 JQ012720 JQ012476 JQ012371

Anchoviella elongata 0 JQ012548 JQ012707 JQ012486 JQ012381

Anchoviella cf. guianensis 1 JQ012585 JQ012673 JQ012505 JQ012400

Anchoviella sp. 3 1 JQ012593 JQ012632 JQ012509 JQ012404

Anchoviella guianensis 1 JQ012591 JQ012652 JQ012511 JQ012406

Anchoviella brevirostris 0 JQ012608 JQ012686 JQ012517 JQ012412

Anchoviella lepidentistole 0 JQ012596 JQ012634 JQ012519 JQ012414

Anchoviella carrikeri 1 JQ012583 JQ012650 JQ012528 JQ012422

Anchoviella carrikeri 1 JQ012599 JQ012663 JQ012530 JQ012424

Anchoviella cf. guianensis 1 JQ012544 JQ012646 JQ012432 JQ012327

Anchoviella jamesi 1 DDB3735 DDB3735 NA DDB3735

Anchoviella manamensis 1 DDB4169 DDB4169 NA DDB4169

Cetengraulis edentulus 0 JQ012577 JQ012692 JQ012490 JQ012385

Cetengraulis mysticetus 0 JQ012579 JQ012694 JQ012495 JQ012390

Coilia brachygnathus 1 DQ912124 DQ912159 DQ912089 EU694410

Coilia lyndmani 1 NA NA NC_014271 NC_014271

Coilia mystus 0 DQ912126 DQ912162 DQ912092 EU694407

Coilia nasus 0 DQ912123 DQ912157 AP009135 AP009135

Coilia reynaldi 0 NA NA NC_014276 NC_014276

Encrasicholina devisi 0 JQ012626 JQ012684 JQ012469 JQ012364

Encrasicholina punctifer 0 NA NA AP011561 AP011561

Engraulis anchoita 0 NA NA JQ012521 JQ012416

Engraulis ringens 0 JQ012533 JQ012731 JQ012532 JQ012426

Engraulis eurystole 0 DQ912121 DQ912155 DQ912085 JQ012427

Engraulis japonicus 0 AY430205 NA NC003097 NC_003097

Engraulis mordax 0 JQ012546 JQ012728 JQ012455 JQ012350

Engraulis encrasicolus 0 JQ012540 JQ012726 JQ012464 JQ012359

Jurengraulis juruensis 1 JQ012610 JQ012732 JQ012434 JQ012329

Lycengraulis poeyi 0 JQ012621 JQ012642 JQ012475 JQ012370

Lycengraulis grossidens 0 JQ012622 JQ012639 JQ012501 JQ012396

Lycengraulis batesii 1 JQ012619 JQ012643 JQ012515 JQ012411

Lycothrissa crocodilus 0 JQ012534 JQ012683 JQ012526 JQ012420

Pterengraulis atherinoides 1 JQ012616 JQ012636 JQ012428 JQ012323

Setipinna melanochir 0 NA NA AP011565 AP011565

Setipinna taty 0 NA JQ012681 JQ012470 JQ012365

Setipinna cf. tenuifilis 0 NA JQ012682 JQ012503 JQ012398

Stolephorus cf. chinensis 0 NA NA AP011566 AP011566

Stolephorus cf. waitei 0 NA NA AP011567 AP011567

Stolephorus sp. 0 JQ012536 JQ012671 JQ012466 JQ012361

Thryssa baelama 0 NA NA NC_014264 NC_014264

Thryssa c.f. dussumieri 0 JQ012535 JQ012678 JQ012468 JQ012363

Thryssa mystax 0 JQ012537 JQ012680 JQ012471 JQ012366

Pristigasteridae Chirocentrodon bleekerianus NA NA DDB3452 NA

Ilisha africana 0 NA NA NC_009584 NC_009584

Ilisha amazonica 1 DDB717 DDB717 DDB717 DDB717

Ilisha elongata 0 NA DQ912160 DQ912090 AP009141

Ilisha megaloptera 0 NA DDB3240 DDB3240 DDB3240

Odontognathus mucronatus 0 NA NA DDB3595 DDB3595

Pellona castelnaeana 1 DQ912102 DQ912135 DQ912065 EU552554

Pellona flavipinnis 1 DQ912101 DQ912134 DQ912064 EU552551

Pellona harroweri 0 DDB4309 DDB4309 DDB4309 DDB4309

Pristigaster cayana 1 DDB657 DDB657 DDB657 DDB657

Pristigaster whiteheadi 1 DDB4397 NA DDB4397 DDB4397

Sundasalangidae Sundasalanx mekongensis 1 NA NA AP006232 AP006232

Outgroups

Salmonidae Oncorhynchus mykiss 2 U15663 U31670 NC_001717 NC_001717

Cyprinidae Danio rerio 1 U71093 DRU71094 NC_002333 NC_002333

Cyprinidae Cyprinus carpio 1 AY787040 DQ366994 NC_001606 NC_001606

Ictuluridae Ictalurus punctatus 1 AY423859 AY184245 NC003489 NC_003489

Hepsetidae Hepsetus odoe 1 DQ912097 AY804086 NC_015819 NC_015819

Chanidae Chanos chanos 0 AY430207 NA NC_004693 NC_004693

Table 3.2 Models of evolution and partitioning strategy selected by PartitionFinder and implemented in RAxML.

Partition Model selected Model used rag1, 1st position SYM+G GTR+G rag1, 2nd position, rag2 2nd position SYM+I+G GTR+G rag1, 3rd position SYM+I+G GTR+G rag2, 1st position GTR+I+G GTR+G rag2, 3rd position K80+I+G HKY+G cytb, 1st position SYM+I+G GTR+G cytb 2nd position GTR+I+G GTR+G cytb, 3rd position GTR+G GTR+G

16s GTR+G GTR+G

'ROSS HYPOTHESIS 4EMPERATE REGIONS &RESHWATER %URYHALINE !MPHIDROMOUS !NADROMOUS -ARINE SPECIES SPECIES WANDERER SPECIES SPECIES

'ROSS HYPOTHESIS 4ROPICAL REGIONS

-ARINE SPECIES %URYHALINE !MPHIDROMOUS #ATADROMOUS &RESHWATER WANDERER SPECIES SPECIES SPECIES

3AFE SITE HYPOTHESIS -ARINE SPECIES %URYHALINE !NADROMOUS !MPHIDROMOUS &RESHWATER WANDERER SPECIES SPECIES SPECIES

Figure 3.2 Hypotheses and phylogenetic predictions for origins of diadromy based on (A) Gross (1987) and (B) Dodson et al. (2008).

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Figure 3.4 Chronogram of Clupeiformes resulting from our BEAST analysis. The bars at nodes indicate the 95% HPD of the posterior age estimates.

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-ILLIONS OF YEARS AGO

4 The evolutionary origins of marine derived freshwater fishes in South America 4.1 Abstract

The South American fish fauna is renowned for its extraordinary diversity. The majority of this diversity is comprised of a few major clades that have ancient associations to freshwater habitats. However, at a higher taxonomic level, the South American ichthyofauna is enriched by an extraordinary number of marine derived lineages. In fact, there are more marine derived fish species in South America than any other continent. This diverse community of marine derived fishes was hypothesized to have invaded during Miocene marine incursions into the Pebas mega- wetland in present-day upper Amazonia. Using time-calibrated phylogenies for nine independent marine invaders we reject the Miocene marine incursion hypothesis. Instead, we find there were two waves of marine invasions into South America. The first wave occurred during a marine incursion into the Andean foreland basin in the Eocene, and the second wave invaded during a marine incursion into the Llanos in the Late Oligocene. Although the Pebas mega-wetland and Miocene incursions appear not to have facilitated transitions into South American freshwaters, these paleogeographic events were important for the diversification of several marine derived lineages of fishes.

4.2 Introduction

The South American fish fauna is renowned for its ecological diversity and species richness (Vari and Malabarba 1998; Winemiller et al. 2008). Indeed, with >6,000 fish species, the rivers, lakes, and swamps of South America are home to the greatest diversity of freshwater fishes in the world, totaling approximately 25% of all fish species. Yet, more than 97% of all Neotropical fishes are members of three clades: Ostariophysi (catfishes, tetras, and electric fishes) Cichlinae (cichlids), and Cyprinodontiformes (killifishes) (Lovejoy et al. 2010). These clades have an ancient association with continental (fresh) waters and have dominated the Neotropical fish community since the formation the South America continent (Lundberg et al. 2010; Albert and Carvalho 2011). However, at a higher taxonomic level, the South American ichthyofauna is 87

enriched by an extraordinary number of marine derived lineages (MDLs) – lineages that are endemic to continental freshwaters, but are derived from clades that are primarily and ancestrally distributed in marine environments – including stingrays, needlefishes, anchovies, herring, pufferfishes, and drums (croakers). The high diversity of MDLs also includes many non-fishes such as iniid dolphins (Cassens et al. 2000; Hamilton et al. 2001), manatees, shrimps, crabs, sponges, and mollusks (Nuttall 1990; Wesselingh et al. 2002; Lovejoy et al. 2006). This remarkable number and diversity of marine-derived lineages sets the South American biota apart from other continents (Figure 4.1).

Marine and freshwater habitats are generally considered independent zoogeographic areas (Darlington 1957; Hutchinson 1957; Lee and Bell 1999; Blaber 2000). Biotic interchanges between marine and freshwater ecosystems are evolutionarily rare events due to the strong biotic and abiotic barriers in place between these habitats (Vermeij and Dudley 2000; Proches 2001; Vermeij and Wesselingh 2002). In general, biotic interchange between areas is predictable and one sided, and the fauna that is larger, more species rich, more competitive, and having a high reproductive ability is usually the donor fauna (Vermeij 2005). Given the ancient history of a species rich and ecologically diverse incumbent fish fauna in South America, the biotic barriers in the form of competition are be expected to be particularly robust (Vermeij and Dudley 2000; Vermeij and Wesselingh 2002; Bloom and Lovejoy 2012; Betancur et al. In Press). The high potential for competition (and predation), in addition to abiotic barriers, make the presence of such a large number of MDLs in South America all the more surprising.

Recent studies have suggested that the origins of MDLs in South America are linked to marine incursion events (Lovejoy et al. 1998; Lovejoy et al. 2006; Wilson et al. 2008; Bloom and Lovejoy 2011). Marine incursions are the inundation of continental land by oceanic waters, resulting from the rise of sea levels, regional tectonics (or other geological activity), or both. Although South America has experienced numerous marine incursions following its separation from Africa (Lundberg et al. 1998), previous authors identified the Miocene marine incursions into the Pebas Mega-wetland system as the most likely conduit for marine invaders into South America (Lovejoy et al. 1998; Monsch 1998; Boeger and Kritsky 2003; Lovejoy et al. 2006;

Bloom and Lovejoy 2011; Cooke et al. 2012). The Pebas Mega-wetland occurred during the Early to Middle Miocene (24-11Ma) in the present day upper Amazon. The Pebas system was more than 1 million km2 in area, stretching east from the Andes Mountains in the east to the Guiana and Brazilian shields in the west, from Bolivia in the south to the Llanos basin in Colombia and Venezuela where it eventually drained into the Caribbean Sea. The Pebas Mega- wetland was a dynamic ecosystem with variety of habitat types including lakes, swamps, deltas, and estuaries. Geological evidence has shown there were several marine incursion events from the Caribbean into the Pebas system between 24-11Ma (Hoorn 1993; Hovikoski et al. 2005; Hovikoski et al. 2007; Hoorn et al. 2010). Thus, the ecological and biogeographical context of the Pebas system is thought to have offered ideal conditions for invasions by marine lineages. A Pebas origin for MDLs predicts: 1) the age of MDLs should correspond to 24-11Ma, 2) the sister lineage to MDLs should include taxa distributed in the Atlantic (Caribbean), and 3) there should be biogeographic congruence among multiple unrelated taxa (Bloom and Lovejoy 2011).

While the Miocene marine incursions have received the majority of consideration, Wesselingh and Hoorn (2011) suggested that some MDLs may have originated during Eocene marine incursion events. Marine incursions during the Eocene are known to have occurred in the Andean foreland basin, which today form the Amazon basins of the Colombian Llanos and Putumayo, Ecuadorian Oriente, Peruvian Marañon and Ucayali basins (Lundberg et al. 1998; Santos et al. 2008). During the Late Eocene, the Peruvian and Ecuadorian areas were inundated by a series of lakes under marine influence known as Lago Pozo (Lundberg et al. 1998). These paleoenvironments were intermittently connected to the Pacific through a low-lying area in the proto Andes and to the Caribbean through present day Colombia. Marine influence during the Eocene occurred from 43-34 Ma. The Eocene marine incursion hypothesis predicts: 1) the age of MDLs should correspond to 43-34 Ma, 2) the sister lineage to MDLs could include either Atlantic or Pacific members, and 3) there should be biogeographic congruence among multiple unrelated taxa (Bloom and Lovejoy 2011).

The null biogeographic hypothesis is that the origins of MDLs in South America are not linked to specific geological events, but rather a result of random invasions over time. Roberts

(Roberts 1972) argued that South America was “open” to invasion because the vast majority of the major river drainages (Amazon, Orinoco, Parana) are relatively low-lying with fewer impermeable barriers (e.g. waterfalls) than other major river drainages such as the Congo. It is difficult to test for random invasions, but this hypothesis would be supported by lack of congruence of phylogenetic, biogeographic, and temporal patterns among independent clades.

While some authors have considered the evolutionary and paleo-geological processes that explain the high diversity of MDLs in South America (Roberts 1972; Goulding 1980; Lovejoy 1996; Lovejoy et al. 1998; Boeger and Kritsky 2003; Lovejoy et al. 2006; Bloom and Lovejoy 2011, 2012), few empirical studies have used modern time-calibrated phylogenies to test for congruent patterns among multiple MDLs. Thus, the origins of MDL’s in South America remain an enigmatic component of Neotropical fish diversity. In this study, we integrate geological, paleontological, and neontological data to reconstruct a synthetic history (Sidlauskas et al. 2010) of MDLs in South America. We use time-calibrated phylogenies for multiple clades to link phylogenetic pattern with earth history events, and test biogeographic hypotheses on the origin of MDLs in South America. Our study provides the first evidence that Eocene marine incursions played a critical role in multiple clades transitioning from marine environments into to the freshwaters of South America.

4.3 Methods

4.3.1 Data

Our sampling strategy was to assemble the most comprehensive phylogenies for as many clades including South American MDLs as possible. These clades necessarily must include both MDL(s) and a dense sampling of the possible marine relatives in order to determine the marine sister lineage to each MDL. To that end, we assembled published time-calibrated molecular phylogenies for stingrays, anchovies, pristigasterids, herring, needlefishes, halfbeaks, and drum. The data for these clades was available on Genbank, although members of our research group generated most of the DNA sequences used in our study. The data sets for every clade included in our study are comprised of both mitochondrial and nuclear genes. The accession numbers for

all sequences included in this study are available in our supplementary information (S1). Below we briefly describe each data set.

Stingrays

For the stingray dataset we used the Aschliman et al. (Aschliman et al. 2012) dataset as a backbone, but included only Myliobatiformes and added sequences of Potamotrygonidae (South American freshwater stingrays) from Lovejoy et al. (Lovejoy et al. 1998), de Carvalho and Lovejoy (de Carvalho and Lovejoy 2011), and Toffoli et al. (Toffoli et al. 2008). To reduce the amount of missing data and maximize overlapping gene sampling, we discarded all mitochondrial genes except cytb and CO1, but included both rag1 and SCFD2 nuclear genes from the Aschliman data set. Our taxon sampling includes 12 of the 20 species of Potamotrygonidae, which is well established as a monophyletic clade (Lovejoy 1996; Lovejoy et al. 1998). The stingray data set also includes 16 species of marine myliobatids.

Anchovies, Herring, and Pristigasterids

The anchovies (Engraulidae), herring (Clupeidae), and Pristigasterids (Pristigasteridae) are all members of Clupeiformes. Bloom and Lovejoy (in prep; chapter 3) recently presented the most comprehensive molecular phylogeny of Clupeiformes, and their chronogram is used herein. The Bloom and Lovejoy data set is comprised of 159 species of clupeiformes, with representatives from 64 of the 84 genera. The clupeiform data set was comprised of four genes (16s, cytb, rag1, rag2). The taxon sampling of freshwater anchovies includes all six genera that have freshwater members and comprehensive species level sampling, and is missing only Anchoviella vaillanti from the Rio Sao Francisco and the recently described Anchoviella juruasangai, from the lower Amazon river (Loeb 2012). A recent study (Bloom and Lovejoy 2012; chapter 2) on engraulid phylogenetics, that included widespread geographic sampling across South America, demonstrated that South American freshwater anchovies are monophyletic group and thus we expect these missing taxa are members of the South American clade. There are two species of freshwater herring found in South America, Rhinosardina amazonica and R. bahiensis; both of these species were included in the clupeiform data set. The

pristigasterid taxon sampling included all five species found in South American freshwaters: Ilisha amazonica, Pellona castelnaeana, Pellona flavipinnis, Pristigaster cayana, and Pristgaster whiteheadi. The clupeiform dataset also included a broad sampling of marine anchovies, herring and pristigaterids, both from along the coast of South America and elsewhere, which are putatively closely related to each of these respective freshwater lineages.

Needlefishes and Halfbeaks

Needlefishes and Halfbeaks are members of Beloniformes, a group that includes flyingfish, sauries, and ricefish. Lovejoy, Bloom, et al. (in prep) presented the largest beloniform phylogeny to date. This dataset is a four-gene matrix (cytb, rag1, rag2, tmo4c4) totaling 3318bp and includes 104 species of beloniforms. Taxon sampling is near complete for needlefishes with 29 of the 34 recognized species represented in the dataset, this includes all seven described species of South American freshwater needlefishes and their marine relatives (Lovejoy and Collette 2001; Lovejoy et al. 2004). The only freshwater halfbeak, Hyporhamphus brederi, is also included in the Lovejoy, Bloom, et al. dataset, along with 10 marine species of Hyporhamphus, and the monotypic marine genera Arrhamphus, Chriodorus, and Melapedalion, which are all members of the “Hyporhamphus clade” (Lovejoy and Bloom, in prep); thus marine species occurring along the coasts of South America are well represented in the data set.

Drums

There are 287 species of drum worldwide, most of which inhabit the coastal areas of the Atlantic, Pacific, and Indian oceans. There are approximately 20 species of freshwater drums in South America, which are members of the genera Plagioscion, Pachypops, Pachyurus, and Pelitipinnis. Cooke and Beheregaray (Cooke et al. 2012) recently investigated relationship among South American drum. These authors found support for a single origin of freshwater drum in South America, however the taxon sampling of marine species was limited. Here we build on the Cooke and Beheregaray study, by including additional DNA sequence data available on genbank to greatly expand the taxon sampling to a total of 91 species of drums. This includes data from four genes (cytb, co1, ATPase 6&8, rag1) for a total of 3560bp. No comprehensive

phylogenetic analysis of Sciaenidae has been previously published, thus our data set is the largest drum phylogeny to date.

4.3.2 Divergence time estimation

Time-calibrated phylogenies for all MDLs in this study were generated using Bayesian relaxed clock methods (Drummond et al. 2006) in the program BEAST v1.7.2 (Drummond et al. 2012). These analyses used an uncorrelated lognormal tree prior that allows rates to vary across branches, and a birth-death prior for rates of cladogenesis.

Time-calibrated phylogenies for Beloniformes and Clupeiformes were taken directly from, respectively, Lovejoy, Bloom, et al. (in prep) and Bloom and Lovejoy, (in prep; chapter 3). We analyzed the stingray dataset following the settings, parameters, and fossil calibrations from Aschilman et al. (Aschliman et al. 2012), however we used exponential priors on the fossil calibrations rather than lognormal priors to minimize the ambiguity in setting the prior distribution of fossil ages (Ho and Phillips 2009). We also used 10Ma as the minimum age for the fossil potamotrygonid, rather than 15Ma used by Aschilman et al. (Aschliman et al. 2012). We elected to use 10Ma because this was the minimum age of the fossil, while Aschilman et al. used the minimum age estimated by Lovejoy et al. (Lovejoy et al. 1998) as a hard lower bound.

The drum data set was analyzed using the fossil species Plagioscion marinus from the early Miocene as a minimum age for the split between Plagioscion and their sister lineage (Pachypops/Pachyurus clade). We used 15.97 as a hard minimum bound and 99Ma (offset=27.72) as the soft upper bound because this is the age of the oldest crown acanthomorphs (Alfaro et al. 2009; Santini et al. 2009). We used an exponential distribution for this prior (Ho and Phillips 2009). While other drum fossils are known, P. marinus is the oldest sciaenid fossil, and the only one that can be accurately placed in the drum phylogeny. We ran two separate BEAST analyses for 100 million generations, sampling every 1000 generations. We used Tracer 1.5 (Drummond and Rambaut 2007) to assess convergence and mixing of runs and to verify that effective sample sizes were >200 for all parameters. The first 20 million generations from each run were discarded as burn-in. The two runs were combined using LogCombiner v1.6.1

(Drummond and Rambaut 2007) and a maximum credibility tree was generated in TreeAnnotator v1.6.1 (Drummond and Rambaut 2007).

4.3.3 Ancestral reconstructions

We determined the origin of South American freshwater lineages using ancestral character reconstruction (ACR). For each species, we coded habitat (marine/freshwater) as a binary, unordered character. While we are specifically interested in the origin of South American freshwater lineages, some clades include freshwater members in other biogeographic areas, thus using this coding scheme, rather than some alternative (such as biogeographic area) helps rule out the possibility that Amazonian lineages were derived from freshwater lineages outside of South America rather than a marine ancestor. We used the chronograms for each dataset to conduct maximum parsimony (MP) and maximum likelihood (ML) ancestral character reconstruction in Mesquite v2.6 (Maddison and Maddison 2011). Maximum likelihood reconstructions were conducted using the Mk model (Pagel 1999).

4.4 Results

4.4.1 Phylogenetic and Biogeographic patterns

Our analyses revealed nine independent MDLs. Figure 4.2 and Table 4.1 summarize the time- calibrated phylogenies and distribution patterns for MDLs and their sister lineages (see appendix 2 for detailed MP and ML ACRs and age estimates for each data set). In general, MDLs have marine sister taxa distributed along the Atlantic (Caribbean) and/or Pacific coasts of South America. We found there were two major waves of invasion, the first occurred during the Eocene, and the second wave occurred during the Oligocene. Both waves of invasion coincided with periods of marine incursion into continental South American drainages.

South American freshwater stingrays (Potamotrygonidae) are the product of a single invasion into South American freshwaters. The potamotrygonids are sister to Himantura pacifica from the eastern Pacific and Himantura schmardae from the western Atlantic (Lovejoy 1996; Lovejoy et al. 1998; Dunn et al. 2003, this study; Aschliman et al. 2012).

The South American herring, Rhinosardinia, is sister to Lile stolifera from the eastern Pacific. However, Lile piquitinga from the Western Atlantic is the likely sister species of L. stolifera, but was not included in the Clupeiform phylogeny.

There were two independent transitions into South American freshwaters by pristigasterids. One lineage includes Ilisha amazonica, Pellona castelnaeana, and Pellona flavipinnis; the sister to this lineage is Pellona harroweri, which is the only marine species of Pellona in the New World and has a western Atlantic distribution. Ilisha furthii from the eastern Pacific is the only New World marine Ilisha, and a candidate sister species to the South American Ilisha+Pellona clade, but was not included in the Clupeiform phylogeny. Bloom and Lovejoy (in prep) found that Ilisha is not monophyletic, so the placement of Ilisha furthii within Pristigasterids is uncertain. The second South American pristigasterid lineage includes Pristigaster whiteheadi and Pristigaster cayana. The marine sister lineage is a clade that includes Odontagnathus mucronatus from the western Atlantic and Indo-Pacific species of Ilisha. There are also a number of marine pristigasterids along the coasts of South America from both the Atlantic and Pacific (e.g Neoopisthopterus, Pliosteostoma, Opisthopterus) that have not been included in any phylogenetic study, but are morphologically similar to Odontagnathus (Whitehead et al. 1988); these taxa remain candidate marine sister lineages to freshwater South America pristigasterids.

The BEAST analysis from Bloom and Lovejoy (in prep) indicates that South American freshwater anchovies are sister to Anchoa filifera, a marine species from the western Atlantic, distributed along the coasts of northern South America and Central America. However, Bloom and Lovejoy (Bloom and Lovejoy 2012) found that the South American freshwater anchovy clade is sister to a large clade that includes nearly all marine New World anchovies from both the western Atlantic and eastern Pacific marine species (Bloom and Lovejoy 2012). In this alternative topology the large marine clade included A. filifera. The basal New World anchovy lineage is Engraulis ringens and Engraulis anchoita, which are distributed along the Pacific and Atlantic coasts of South America. Thus the sister group to South American anchovies was either widespread across both the Atlantic and Pacific, or restricted to the western Atlantic.

There were two separate marine invasions by needlefishes, and one invasion by a halfbeak. The first South American needlefish lineage, Potamorhaphis/Belonion, is sister to a clade that includes western Atlantic and eastern Pacific marine species. The second needlefish MDL, Pseudotylosurus, is sister to a pair of trans-Atlantic species that recently diverged. Needlefish relationships have previously been discussed in more detail (Lovejoy and Collette 2001; Lovejoy et al. 2006). The halfbeak Hyporhamphus brederi is sister to an Atlantic species.

Our BEAST analysis of 91 sciaenid species (of 287 species worldwide) suggests that South American freshwater drum were the result of a single invasion (although Petilipinnis was not included in our analysis). The South American freshwater clade is well supported (posterior probability = 1.0). The sister group to South American drums is a clade of 24 marine species, 20 of which are from either the western Atlantic or the eastern Pacific, while the remaining four species are from the eastern Atlantic and Indo-Pacific.

4.4.2 Age of MDLs

The most conservative estimate for the origins of MDLs is bracketed by the stem time of the split from the closest marine ancestor (stem age) and the first diversification event (crown age) of the freshwater clade. The actual evolutionary event, the transition from marine to freshwater, could have occurred anytime along this branch. Determining exactly when along this branch the transition occurred is not possible, therefore we report the ages and 95% highest posterior density of these nodes for each MDL (Figure 4.2 and Table 4.1). However, in our opinion the stem age is the best estimate because species limits have not been investigated for most MDLs so the crown age may be considerably biased to a younger age. In some cases (e.g. halfbeaks) MDLs are monospecific, so crown ages can not be determined Further, if the event (i.e. dispersal or vicariance) that resulted in the split between the MDL and the marine ancestor was tied to the invasion of freshwater habitat (which seems likely), then the stem age is the appropriate age estimate. We report both stem and crown ages below, but focus our discussion on stem ages.

Our diversification time estimates recovered synchronous Eocene origins for four MDLs: stingrays, two needlefish lineages (Pseudotylusurus and Potamorhaphis/Belonion), and

Pristigaster. The stem ages of these clades were all between 38-42Ma. The crown ages of these clades were all Late Oligocene - Early Miocene, except for Pristigaster, which had a late Miocene crown age. We also found that four MDLs that had synchronous origins during the Late Oligocene to Early Miocene. These included anchovies, herring, Pellona/Ilisha and drum. These MDLs had stem ages between 25.6-28.1Ma. The crown ages for these clades were older than 23Ma for anchovies and drum, 13.8Ma for herring and 6.7Ma for Pellona/Ilisha. Only the halfbeak, Hyporhamphus brederi, with a stem age of 1.7Ma was estimated to be younger than the Miocene.

4.5 Discussion

4.5.1 Biogeography of marine derived lineages in South America

The origins of the remarkable diversity of MDLs in South America has long perplexed and fascinated biologists (Roberts 1972; Goulding 1980). We analyzed nine independent South American MDLs and found congruent biogeographic patterns and synchronic ages that provide novel evidence for two separate waves of marine invaders into Amazonia (Nelson and Platnick 1981; Donoghue and Moore 2003), each linked to a different marine incursion into continental South America. The shared response by multiple lineages to common paleogeographic events rejects the hypothesis that MDLs resulted from repeated random dispersal events (Roberts 1972). Further, our results show that nearly all MDLs in South America had reached modern day higher-level taxonomic and ecological diversity by the Middle Miocene, supporting the “Tertiary diversification hypothesis” as a general model for understanding the extraordinary diversity of South American fishes (Lundberg et al. 2010; Albert and Carvalho 2011).

The Eocene marine incursion hypothesis predicts that the marine sister group to MDLs could include either the Caribbean or the Pacific and the origin of MDLs would date to 34-43Ma. The first wave of invasion involving stingrays (Potamotrygonids), two independent needlefish lineages (Pseudotylusurus and Potamorhaphis/Belonion), and one pristigasterid lineage (Pristigaster) shows strong concordance with the predictions for an Eocene marine incursion origin (Figure 4.2). The first three lineages have sister groups from both the Atlantic and Pacific, while Pristigaster is sister to a group that includes the Atlantic and the Indo-Pacific. All four of 97

these MDLs have stem ages of ~40Ma, which coincides with marine incursions that inundated the interior of Amazonia. South American stingrays and needlefishes were previously thought to have originated during the Miocene (Lovejoy et al. 1998; but see de Carvalho et al. 2004; Lovejoy et al. 2006; Bloom and Lovejoy 2011), although molecular estimates did not rule out an Eocene origin for stingrays (Lovejoy et al. 1998; Lovejoy et al. 2006). Our estimate of an Eocene origin for stingrays and needlefishes are older than found in previous studies for these MDLs (Lovejoy et al. 2006). We cannot rule out the possibility that our diversification times are over estimates (see below), however the time-calibration methods used in previous studies were based on fewer genes (~600bp of cytb for stingrays) and models of evolution that assumed constant substitution rates. The time-calibration methods used for this study incorporate a more comprehensive sampling of the fossil record and utilize improved methods that account for rate variation among lineages, and thus represent the most robust diversification time estimates to date.

The Miocene marine incursion hypothesis predicts that the marine sister group of MDLs should include the Caribbean and the age of MDLs should date to 24-11Ma. The biogeographic distribution patterns of anchovies, herring, one pristigasterid lineage (Pellona/Ilisha) and drums, in the second wave of invasion indicate an Atlantic (Caribbean) origin. Anchovies and Pellona/Ilisha have a sister group that only includes the Atlantic, while the sister to South American herring and drum includes both the Atlantic and Pacific (and Indo-Pacific for drums). Interestingly, the estimated stem ages of these lineages all slightly pre-date (28-25Ma) Miocene marine incursions and the early stages of the Pebas Mega-wetland. Intriguingly, the stem age of South American ‘river dolphins’ also falls within this time period (Slater et al. 2010). We argue it is not trivial that the ages for these MDLs are consistently older than the Pebas Mega-wetland and associated Miocene marine incursions, but rather this indicates a common response to a specific paleogeographic event. During the Late Oligocene there was a small marine incursion in the Llanos region of northern South America that created an estuarine environment that later formed part of the northern portal that connected the Pebas Mega-wetland to the Caribbean (Bayona et al. 2008; Hoorn et al. 2010; Roddaz et al. 2010). Our data indicates the second wave of invaders established residency in continental waters during this Late Oligocene marine

incursion (28-25Ma), and later penetrated deep into Amazonia during the Pebas mega-wetland, and subsequently diversified across the continent. If this is true, our study falsifies the Miocene marine incursion hypothesis as the primary paleogeographic event that explains the origins of MDLs in South America. Nonetheless, the Miocene marine incursions and the Pegas Mega- wetland seem to have had a profound impact on the diversification of MDLs in South American (see below).

The biogeographic scenarios described above are based on the stem ages for the origin of MDLs. While we regard these the appropriate ages to consider, the most conservative estimate is any time between the split between marine lineages (stem age) and the first diversification event of MDLs (crown age). Interpreting Crown ages would suggest that most lineages invaded South American freshwaters during the Miocene, and some would have invaded even more recently.

It is also possible that some of our MDL ages are overestimates because we did not sample the true marine sister clade. The Pristigaster, Rhinosardina, and drum ages are the most susceptible to overestimates due to limited taxon sampling, while the remaining MDLs in our study are part of densely sampled clades that likely include the true sister lineage. If our age estimates were biased towards older ages, then the stem ages would suggest that the second wave invaded during the Miocene marine incursions, rather than during Oligocene marine incursions.

4.5.2 Biome transitions and the role of Pebas Mega-Wetland in diversification of MDLs

Recent studies have suggested that competition may be the primary mechanism regulating biome transitions in these clades (Betancur-R et al. 2012; Bloom and Lovejoy 2012). If this is the case, South America might be particularly well guarded against invaders, given the rich ecological and taxonomic diversity of the South American ichthyofauna (Bloom and Lovejoy 2011). Marine incursions are thought to facilitate marine to freshwater transitions by reducing competition with incumbent freshwater fishes that are unable to tolerate even slightly elevated salinity levels (Vermeij and Wesselingh 2002; Lovejoy et al. 2006). Lovejoy et al. (Lovejoy et al. 2006) proposed the Pebas Mega-wetland was a “lineage pump that acted to ‘inject’ marine taxa into freshwater habitats” due to a “competition trough” resulting from increased salinity levels. 99

However, our study suggests that nearly all MDLs were either already present prior to the Pebas Mega-wetland and Miocene marine influence.

Nonetheless, some of the MDL clades experienced considerable diversification during this time period. In some cases, MDLs became more species rich than their respective marine sister groups, despite being the same age (e.g. anchovies, stingrays, possibly drums), but these MDLs show limited diversification until the Early to Middle Miocene. Thus, although the Pebas Mega- wetland did not ‘inject’ lineages into Amazonia, the dynamic setting of the Pebas Mega-Wetland (Wesselingh et al. 2002; Wesselingh et al. 2006) may indeed have created a “competition trough” that facilitated diversification in MDLs. The fluctuating salinity levels and periodic estuarine settings may have generated favorable conditions for diversification in lineages with marine ancestry, particularly because the dominant fish clades in South America (Siluriformes, Characiforms, Gymontiformes, Cichlidae) are unable to tolerate increases in salinity.

The Pebas mega-wetland did not promote diversification in all MDLs. Lineage diversity is generally expected to increase with clade age under a simple birth-death model (Nee 2006). Herring, needlefishes, and both pristigasterid lineages have five or fewer described species despite being present in South American freshwaters for 25-40 million years, a time span that includes the Pebas Mega-wetland. The diversity of other marine derived clades such as stingrays, drums and anchovies, does increase with clade age (Figure 4.3) but overall there is no correlation between clade age and species richness in South American MDLs (GLM, p = 0.476). Taken together, it seems the Pebas Mega-wetland prompted diversification in some MDLs, while others have experienced minimal diversification, possibly due to ecological limits imposed by the rich ichthyofauna of South America (Rabosky 2009a, b).

4.6 Acknowledgements

This study was made possible by the wealth of sequence data made available by previous authors, particularly Neil Aschilman, Anthony Wilson, Sébastien Lavoué, and Chenhong Li. Jason Weir, Allan Baker, Hernan Lopez-Fernandez, and Belinda Chang are thanked for helpful discussions regarding this study.

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RUGHUV RUGHUV RUGHUV RUGHUV

RUGHUV RUGHUV

Figure 4.1 The approximate number of taxonomic orders of marine derived fishes from each continent (Berra 2001).

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Figure 4.3 Clade age versus species richness of South American MDLs. There is no relationship between clade age and species richness (GLM, p = 0.476).

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Table 4.1. Estimated times of divergences between MDLs and their marine sister lineage and time of the first diversification event in South American freshwaters. The highest posterior density for each node age is provided in parentheses. We also indicate the number of freshwater (FW) species included in each data set, and the total number of freshwater (FW) species for each lineage. For the distribution of the sister lineage to MDLs, W. Atl =Western Atlantic and Caribbean, E. Pac = Eastern Pacific, and FW = freshwater. Question marks indicate instances where candidate sister lineages were not included in the study.

MDLs FW species Stem Age Crown age Distribution of sister In study/total lineage

Potamotrygonidae Potamotrygon, Paratrygon, 12/20 38.2 (30.1, 47.7) 25.9 (19.6, 33.3) W. Atl/E. Pac (stingrays) Heliotrygon, Plesiotrygon

Engraulidae (anchovies) Anchoviella, Anchovia, Lycengraulis, ~14/15 28.1 (22.3, 34.1) 25.0 (19.6, 30.2) W. Atl/E. Pac Pterengraulis, Amazonsprattus, Jurengraulis

Pristigasteridae Pellona/Ilisha 3/3 25.9 (11.6, 41.5) 6.7 (2.6, 11.8) W. Atl/other (pristigasterids) A

Pristigasteridae B Pristigaster 2/2 39.9 (24.8, 55.5) 5.6 (1.6, 10.9) W. Atl

Clupeidae (herring) Rhinosardina 2/2 25.6 (16.2, 35.3) 13.8 (6.1, 22.3) W. Atl/E. Pac(?)

Belonidae (needlefishes) A Pseudotylusurus 2/2 42.3 (25.7, 59.3) 23.5 (9.6, 37.3) E. Atl & W. Atl

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Belonidae B Potamorhaphis/Belonion 5/5 40.0 (25.2, 56.1) 30.0 (16.7, 42.6)

Hemirhamphidae (halfbeaks) Hyporhamphus brederi 1/1 1.7 (0.2, 2.5) - W. Atl

Sciaenidae (drums) Plagioscion, Pachypops, Pachyurus, ~12/22 27.4 (16.7, 48.2) 23.1 (16.0, 39.7) W.Atl/E.Pac/ Petilipinnis (not included) other

Tetraodontidae Colomesus asellus 1/1 9.6 (4.1-17.8) - W. Atl (pufferfishes)1

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5 Do freshwater fishes diversify faster than marine fishes? A test using state-dependent diversification analyses and molecular phylogenetics of New World silversides (Atherinopsidae) 5.1 Abstract

Freshwater habitats make up only ~0.01% of available aquatic habitat and yet harbor 40% of all fish species, while marine habitats comprise >99% of available aquatic habitat and have only 60% of fish species. One possible explanation for this pattern is that net diversification rates (speciation minus extinction) are higher in freshwater habitats than in marine habitats. In this study, we investigate diversification rates of marine and freshwater lineages in the New World silverside fish clade Menidiinae (Teleostei, Atherinopsidae). Using a multi-gene (>4kb) time- calibrated phylogeny and a state dependent speciation-extinction framework, we determined the frequency and timing of habitat transitions in Menidiinae and tested for differences in diversification rates between marine and freshwater lineages. We found that Menidiinae is an ancestrally marine lineage that independently colonized freshwater habitats four times followed by three reversals to the marine environment. Our state-dependent diversification analyses showed that freshwater lineages have a 20 fold higher speciation rate than marine lineages, but freshwater lineages also have a higher extinction rate. Lineage-through time plots show that both marine and freshwater lineages accumulate constantly through time, suggesting that ecological limits to clade growth have not played a major role in the diversification of silversides.

5.2 Introduction

Explaining the disparity in species richness among clades and areas is a major goal of evolutionary biology. One of the more intriguing patterns of biodiversity is the extraordinary number of species on continents compared to oceans (Vermeij and Grosberg 2010; Mora et al.

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2011). In fact, it has been estimated that species diversity on continents is 25 times that found in oceans (Briggs 1994; Benton 2001), despite the fact that oceans are vastly greater in size. For aquatic organisms, freshwater (continental) habitats make up only ~0.01% of available aquatic habitat and yet harbor 40% of all fish species, while marine habitats comprise >99% of available aquatic habitat and yield only 60% of fish diversity (Horn 1972; Lundberg et al. 2000; Leveque et al. 2008; Eschmeyer et al. 2010). The question of why continental diversity greatly exceeds that found in oceans remains largely unanswered.

To explain the discrepancy between marine and freshwater diversity, several hypotheses emphasizing ecological factors (e.g. productivity, size of primary producers, and ecological specialization) have been proposed (May 1994; Vermeij and Grosberg 2010). While ecological factors undoubtedly play a role in shaping biodiversity, ultimately disparity in species richness among clades and areas is the result of differences in net diversification (speciation minus extinction) and transition (or dispersal) rates between habitats (Barraclough and Nee 2001; Wiens and Donoghue 2004; Ricklefs 2007; Wiens et al. 2011), and the age of clades (McPeek and Brown 2007). Indeed, Benton (2001) hypothesized that the disparity in species richness among continental and oceanic lineages is an outcome of “rocketing diversification rates” in continental lineages compared to “the more sluggish rates of diversification of life in the sea”. A largely unconsidered possibility is biased transition rates between marine and freshwater lineages over evolutionary time; there may be a high number of freshwater species because marine to freshwater transition rates are higher than freshwater to marine transitions (Maddison 2006; Maddison et al. 2007). Alternatively, freshwater lineages may be older than marine lineages, suggesting continents have simply had more time to accumulate diversity (McPeek and Brown 2007).

There are a number of reasons for predicting that freshwater lineages should have higher diversification rates than marine lineages. Causes of differential diversification may include environmental parameters, as well as intrinsic properties of organisms from each environment. Freshwater environments are generally expected to have more barriers limiting population connectivity, to have greater habitat complexity, and to be more heavily influenced by tectonic

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activity than marine environments (Strathmann 1990; May 1994). Marine organisms have greater geographic range size and less genetic structuring (Palumbi 1994; Bierne et al. 2003). All of these factors are known to influence speciation and extinction rates (Cracraft 1982; Jablonski 1987; Barraclough et al. 1998; Ribera et al. 2001; Jablonski 2008; Badgley 2010). However, the interaction of some of these parameters may yield unexpected patterns. For example, the probability of speciation should increase as geographic range size increases, and decrease as levels of gene flow increase (Kisel and Barraclough 2010; Kisel et al. 2011). So while oceans are vastly greater in size, thus predicting higher speciation rates, marine taxa also have higher levels of gene flow (Palumbi 1994; Bierne et al. 2003; Puebla 2009), which is thought to reduce probability of speciation events (Kisel and Barraclough 2010). The first step towards disentangling how these various habitat parameters affect macroevolutionary patterns is testing the prediction that freshwater lineages have faster diversification rates.

Previous studies have demonstrated that macrohabitat (e.g. coral reefs versus pelagic ocean) can dictate diversification rates in marine fishes (Ruber et al. 2003; Ruber and Zardoya 2005; Alfaro et al. 2007). However, comparative studies on the diversification of marine and freshwater fishes have proven challenging. A recent study (Vega and Wiens 2012) addressed patterns of aquatic diversity but did not detect differences in diversification rates between marine and freshwater ray-finned fishes (Actinopterygii). However, due to the large number of actinopterygian species (~30,000), the authors were not able to use methods that explicitly estimate speciation and extinction rates for marine or freshwater character states (Maddison et al. 2007; FitzJohn et al. 2009; Vega and Wiens 2012).

Testing for the effects of marine versus freshwater habitat on macroevolutionary patterns is possible using a time-calibrated phylogenetic framework that allows speciation, extinction, and character transition rates to be parameterized independently. Ideally, the clade to be analyzed should contain multiple freshwater and marine lineages. However, many clades of fishes (and other taxa) are restricted to either marine or freshwater habitats (Lee and Bell 1999; Vermeij and Dudley 2000; Vermeij and Wesselingh 2002; Bloom and Lovejoy 2011). For this reason, New World silversides (Atherinopsidae) are an excellent system for investigating patterns of aquatic

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diversification because current taxonomy and (albeit limited) phylogenetic data suggests multiple marine/freshwater transitions have occured. In this study, we focus on the subfamily Menidiinae, which is comprised of 44 freshwater and 25 marine species. Marine species are distributed in the western Atlantic from southern Canada to northern Brazil, and in the eastern Pacific from Baja California to Peru. Marine silversides are generally near-shore fishes, with a few representatives in pelagic ocean habitats (Dyer 2006). Freshwater species are distributed in eastern United States and Canada, central and southern Mexico, and throughout Central America (Lee et al. 1980; Reis et al. 2003; Miller 2005; Dyer 2006). Freshwater silversides are largely riverine fishes, rarely occurring in natural lakes. The Central Mexican lakes clade of silversides is an exception with up to 13 species occurring in three lakes (Barbour 1973a, b; Bloom et al. 2009). Previous phylogenetic studies utilizing morphological (Chernoff 1986a; White 1986; Dyer and Chernoff 1996; Dyer 1998) and molecular data (Bloom et al. 2012) have supported the monophyly of Menidiinae. Although several studies have investigated species level relationships in subclades within Menidiinae (Gosline 1948; Barbour 1973b; Echelle and Echelle 1984; Chernoff 1986b; Dyer 1998; Bloom et al. 2009), no molecular study has investigated the relationships among the major lineages of Menidiinae.

Here we use a phylogenetic approach to test for differences in diversification rates between marine and freshwater lineages of menidiine silversides. We generate a time-calibrated molecular phylogeny for Menidiinae, and reconstruct the number and timing of marine and freshwater habitat transitions. We ask whether freshwater lineages are older than marine lineages, and we use state-dependent models of diversification to test for differences in rates of speciation, extinction, and character state change between marine and freshwater lineages. Finally, we use lineage through time plots to evaluate whether marine and freshwater lineages fit similar or different patterns of clade growth. Together, these tests and analyses provide novel insights into the macroevolutionary processes that determine differences in large-scale patterns of diversity between continents and oceans.

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5.3 Materials and Methods

5.3.1 Taxon sampling, DNA Extraction, PCR Amplification, and Sequencing

Our taxon sampling included 50 out of 69 species and representatives of all genera currently recognized in Menidiinae. We also included, as outgroups, six species from Atherinopsinae, Notocheirus hubbsi (Notocheirinae), and Atherinomorus stipes (Atherinidae) for a total of 58 species in the dataset. Our taxon sampling includes representatives from every genus in the family Atherinopsidae except Colpichthys and comprises the most comprehensive molecular phylogenetic study of Atherinopsidae to date. Some data were available from previous studies (Bloom et al. 2009; Bloom et al. 2012), while most were newly sequenced for this study; all new sequences were deposited in Genbank (Table 5.1).

Whole genomic DNA was extracted using DNeasy tissue kit (Qiagen, Valencia, CA). We PCR amplified fragments of two mitochondrial (nd2 & cytb) and two single-copy protein-coding nuclear (tmo4C4 and rag1) genes. For amplification and sequencing, we used protocols and primers from Bloom et al. (2009; 2012) for nd2, cytb, and rag1, and Lovejoy et al. (2004) for tmo4c4. Sequences were edited using the computer software Geneious v5.4 (Drummond et al. 2010) and aligned using the MUSCLE module (Edgar 2004) implemented in Genious. Following alignment, coding regions were translated to amino acids to confirm the integrity of reading frames and absence of stop codons. To test the monophyly of species and as a measure of quality control, we sequenced multiple individuals for nearly all newly sequenced species. We included multiple individuals of each species in the MrBayes analyses (below), but removed duplicate species representatives for all subsequent BEAST and diversification analyses described below.

5.3.2 Phylogenetic Analyses and Diversification Time Estimation

Best-fit models of nucleotide substitution were selected for each gene using Akaike information criteria in the program jModelTest (Posada 2008). We estimated phylogenetic relationships using a mixed-model by-gene-partitioned Bayesian analysis implemented in MrBayes v3.1.2 software (Ronquist and Huelsenbeck 2003). We ran two MrBayes analyses, which consisted of four

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independent chains run for 10 million generations, sampling every 1000 generations with all parameters unlinked and default priors. Convergence of MrBayes analyses was assessed by comparing likelihood states over generations using the sump command in MrBayes and by confirming standard deviation of split frequencies remained below 0.01 and potential scale reduction factors were 1.0. Adequate mixing of chains was confirmed by determining that acceptance rates were between 10% and 70%. MrBayes tree searches were used to confirm the topology recovered in our BEAST analyses (below), but subsequent diversification analyses and trait reconstructions were estimated using the trees from the BEAST analyses.

We used BEAST v1.6.1 (Drummond and Rambaut 2007) to jointly estimate phylogeny and divergence times under a relaxed clock, uncorrelated lognormal model (Drummond et al. 2006) that allows rates to vary among branches. The dataset was partitioned by gene, with each partition unlinked and set to a GTR model with gamma-distributed rate heterogeneity. We used a birth-death prior for rates of cladogenesis and ran two independent analyses of 100 million generations sampling every 1000 generations. We used Tracer 1.5 (Drummond and Rambaut 2007) to evaluate convergence and mixing of runs and to verify that effective sample sizes were >200 for all parameters. We determined that the first 30 million generations from the MCMC sample were a conservative burn-in. The two converged runs were combined using LogCombiner v1.6.1 (Drummond and Rambaut 2007) and the maximum credibility tree was generated in TreeAnnotator v1.6.1 (Drummond and Rambaut 2007).

We used three fossil constraints in the BEAST analysis. A fossil Basilichthys is dated to the late Miocene (Rubilar 1994) and was used to constrain the Basilichthys/Odontesthes clade to a hard minimum bound of 5.33ma with a soft upper bound of 75ma based on previous molecular estimates that show Atherinomorpha is less that 75 million years old (Alfaro et al. 2009; Santini et al. 2009). A fossil Menidia from Oklahoma was dated to the lower Pliocene (Hubbs 1942). This fossil was used to constrain the clade including Menidia beryllina, M. colei, and M. peninsulae with a hard minimum bound of 1.8ma and a soft upper bound of 75ma. A fossil Chirostoma is known from the Lerma Basin in Central Mexico and dated to the Pleistocene with a minimum age reported of 46,000 years before present (Bradbury 1971; Piller and Barbour In

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Press). This fossil was used to date the clade including C. humboldtianum, C. sphryaena, C. lucius, C. chapalae, C. estor, C. grandocule, and C. consocium to a hard minimum age of 0.0046ma and a soft upper bound of 5.33ma based on the fossil Menidia (Hubbs 1942) and because this fossil is part of the extant crown clade of large bodied Chirostoma (Bradbury 1971; Echelle and Echelle 1984; Bloom et al. 2009). We used exponential priors for all fossil constraints because this distribution is appropriate for crown fossils and when no information is available to determine the shape of a lognormal distribution (Ho and Phillips 2009).

5.3.3 Ancestral Character Reconstructions and Lineage Diversification Rate

We coded marine and freshwater habitats as discrete, unordered character states. All character reconstructions were conducted on the chronogram resulting from the BEAST analyses. We used maximum parsimony (MP) and maximum likelihood (ML) in Mesquite v2.6 (Maddison and Maddison 2011) to reconstruct ancestral character states and determine the number of transitions between marine and freshwater habitats. Maximum likelihood reconstructions were estimated using the Mk model (Pagel 1999).

Our diversification analyses were conducted on Menidiinae only by pruning other tips from the tree. We used a state-dependent speciation and extinction model to estimate diversification rates for lineages with marine or freshwater states. For binary characters, the BiSSE model estimates the probability that a lineage evolved as observed given a set of speciation (λ), extinction (µ) and character transition (q01 and q10) parameters (Maddison et al. 2007). Using this framework, we compared the fit of models with unconstrained parameters (speciation, extinction, and transition rates allowed to vary) to models with these parameters constrained to be equal (in all possible combinations) to explicitly test the hypothesis that speciation and extinction rates were different between marine and freshwater habitats, and that there were asymmetrical transition rates between habitats (i.e. test for asymmetrical character transitions). Model parameters were optimized in a maximum likelihood framework and best-fit models selected using Akaike Information Criteria (AIC) and likelihood ratio tests (LRT) following Maddison et al. (2007). We also estimated parameters in a Bayesian framework utilizing Markov chain Monte Carlo

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(MCMC) sampling to more effectively search for optimal parameter estimates. Our MCMC parameter searches consisted of 10,000 iterations with 2,500 discarded as burnin. All BiSSE analyses were conducted in the R package diversitree (FitzJohn et al. 2009).

5.3.4 Lineage diversification through time

We generated lineage-through time plots (LTT) to evaluate patterns of clade growth. The slope of LTT plots indicates the relative rate of lineage accumulation (Weir 2006). If there are no limits to clade growth, lineages are expected to accrue constantly over time yielding an exponential LTT plot. Alternatively, a slowdown in lineage accumulation over time is characterized by a logistic curve and indicates that a density-dependent threshold on clade growth has been reached. We explored patterns of clade growth for the entire Menidiinae clade as well as clade growth separately in marine and freshwater habitats. We followed the approach of Weir (2006) to generate LTT plots for marine and freshwater clades separately; this method uses information from ancestral state reconstructions to determine lineage accumulation patterns based on character state (see Weir 2006 for a detailed description). We also calculated the γ statistic (Pybus and Harvey 2000) for marine and freshwater lineages independently using the R package APE (Paradis et al. 2004).

5.4 Results

5.4.1 Molecular data and phylogenetics

Our final dataset consisted of 1047bp from nd2, 1121bp of cytb, 534bp of tmo4c4, and 1141bp of rag1. The combined dataset included 4143 characters, 1441 of which were parsimony informative. Figure 5.1 shows our time-calibrated phylogeny, which is well resolved and has strong support for clades associated with habitat transitions, indicating phylogenetic uncertainty is not problematic for character reconstructions (Appendix 2). We find strong support for a monophyletic Atherinopsidae, and our focal clade, Menidiinae. Within Menidiinae, we found two major species groups: the Menidiini, distributed in North America, the Caribbean, and the Central Mexican Plateau, and the Membradini, distributed in Central America and southern Mexico. Our analyses place Atherinella brasiliensis as sister to all other members of Menidiinae;

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previously this taxon was thought to be a member of the Membradini clade (Chernoff 1986a). We also recovered Melanorhinus microps as sister to all other Menidinii, rather than in its previously proposed position as a member of Membradini (Chernoff 1986a; Dyer 1997). Many currently recognized genera were not recovered as monophyletic and are likely in need of taxonomic revision. Aside from these differences, our results are consistent with previous studies on silverside phylogenetics at or above the genus level (Chernoff 1986a; Dyer and Chernoff 1996; Dyer 1998, 2006; Bloom et al. 2009; Bloom et al. 2012).

5.4.2 Ancestral character reconstructions

Ancestral character reconstructions indicate a marine state for the most recent common ancestor (MRCA) of Menidiinae and both of the major clades Menidiini and Membradini. Within Menidiinae, there were four independent transitions from marine to freshwater habitats, occurring in the following geographic regions: 1) Mississippi and Atlantic drainages of eastern North America and the central plateau region of Mexico (within Menidiini), 2) Atlantic drainages along the Isthmus of Tehuantepec and western margins of the Yucutan Peninsula in southern Mexico (Atherinella schultzi and A. ammophila), 3) coastal and southern Mexico and Central America, including Atlantic and Pacific drainages (clade of 10 Atherinella spp.), and 4) the Pacific slope of Colombia (Atherinella colombiensis). There were also three reversals from freshwater back to marine habitats. These freshwater to marine transitions occurred: 1) along the Atlantic coast of North America (Menidia menidia), 2) in the Gulf of Mexico (Menidia peninsulae and Menidia colei), and 3) along the Atlantic coast of Central America (Atherinella argentea). Qualitatively, this indicates that asymmetrical transition rates do not explain freshwater species richness; quantitative evidence is provided below.

5.4.3 Diversification times

Our diversification time analysis dates the MRCA of Atherinopsidae to 36.94ma, and the MRCA of Menidiinae to 26.89ma (Fig. 5.1, Appendix 2). The oldest node reconstructed as freshwater was the MRCA of Melanorhinus and members of Menidiini, dated to 19.59ma. Within the Membradini clade, the oldest reconstructed freshwater node was dated to 15.97ma. Over half of the 37 freshwater species included in our study date to less than 3.5ma, and nine are members of 115

a clade from the central Mexican plateau region that date to only 0.52ma. Together this indicates that marine Menidiinae are at least 7 million years older than the earliest freshwater lineage and the majority of freshwater silverside lineages are relatively young.

5.4.4 Speciation, extinction, and transitions rates

We found that speciation rates were 20 times higher in freshwater than marine silversides (Figure 5.2a) in both the full model (no parameters constrained) and a model with transition rates set as equal (q01=q10; see transition rates below). The 95% highest posterior distributions for these speciation parameters were non-overlapping, indicating a high degree of certainty in this estimate (Figure 5.2a). Our results (Table 5.2) indicate that a model allowing speciation rates to vary is preferred over a constrained model where speciation rates were equal. We also found that extinction rates were high in freshwater lineages and nearly zero in marine lineages, with 95% highest posterior distributions entirely non-overlapping (Table 5.2 and Figure 5.2b). Models that allowed extinction rates to vary were preferred over models that constrained extinction rates to be equal (Table 5.2). Our BiSSE analyses showed that a model allowing marine/freshwater transition rates to vary was not preferred over a model with constrained (q01=q10) transition rates (Table 5.2), meaning that transition rates between marine and freshwater habitats are not significantly different (Figure 5.2c). This rejects the hypothesis of asymmetrical transition rates between habitats.

5.4.5 Lineage through time analyses

Our lineage through time (LTT) plots (Figure 5.3) show that the slope of the LTT is steeper in freshwater lineages than in marine lineages, which is consistent with faster rates of lineage diversification. Freshwater lineages also show an upturn near the present that is characteristic of either high extinction rates or rapid recent speciation rates (Nee et al. 1994; Rabosky 2006). Although marine lineages have a shallower slope, lineage accumulation also appears to be relatively constant over time. Neither marine nor freshwater lineages show patterns of slowing through time that characterize density-dependent diversification. The observed γ values for marine (-1.26) and freshwater (3.83) also suggest there has not been a slowdown in lineage accumulation in either environment (a slowdown is indicated when γ ≤ -1.645). 116

5.5 Discussion

Oceans cover more than 70% of the earth’s surface and contain between 90 and 99% of aquatic space by volume. In contrast, freshwater ecosystems cover less than 2% of the earth’s surface (May 1994). Theory on species-area relationships (MacArthur and Wilson 1967) suggest that oceans should be more species rich than continents, and yet oceans harbor only 5-15% of all species (Vermeij and Grosberg 2010). Here we provide explicit estimates of speciation and extinction parameters using state-dependent diversification analysis to test the hypothesis that freshwater (continental) lineages have higher diversification rates than marine lineages. Our data suggest that freshwater silversides had higher speciation rates than marine lineages, but also higher extinction rates. Importantly, marine silverside lineages are generally older than freshwater lineages, suggesting that freshwater lineages have not had more time to generate species. We also found that freshwater silverside diversity is not due to asymmetrical transition rates between habitats, because transition rates between habitats were roughly equal. Together, these results support the idea that differences in habitats can drive macroevolutionary processes (Ribera et al. 2001; Hughes and Eastwood 2006; Alfaro et al. 2007; Moore and Donoghue 2007, 2009; Kozak and Wiens 2010) and are an important determinant of broad-scale patterns of diversity (Wiens et al. 2011). Below we discuss the evidence and possible causes for the differences in diversification rates between aquatic habitats.

5.5.1 Speciation rates elevated in freshwater

Our results confirm that speciation rates are higher in freshwater than marine silverside lineages, showing a 20 fold difference in rate. We propose that the most probable cause of this discrepancy is differences in the abundance of physical (vicariant) barriers that limit gene flow and promote genetic divergence. Most speciation events in fishes are likely a result of allopatric speciation via vicariance (Cracraft 1985; Lynch 1989; Coyne and Orr 2004), and the frequency of vicariant events is likely higher in freshwater than marine habitats (Strathmann 1990; May 1994; but see Paulay and Meyer 2002; Dawson and Hamner 2008). Rivers in particular are strongly influenced by geological events that cause stream capture or drainage subdivision, which are widely recognized causes of vicariant events in freshwater fishes (Rosen 1978; Mayden 1988; Waters et

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al. 2001; Burridge et al. 2006; Albert and Carvalho 2011). In fact, freshwater habitats are often highly fragmented even on small spatial scales (i.e. within drainages, or between adjacent drainages) (Burridge et al. 2008), resulting in high levels of microendemism and population structure (Hollingsworth and Near 2009; Keck and Near 2010), which may lead to elevated speciation rates. In addition, the high degree of habitat complexity in freshwater systems likely facilitates local adaptation, a process that has been demonstrated to play an important role in the diversification of freshwater fishes (Fuller et al. 2007; Tobler et al. 2008; Plath et al. 2010; Tobler et al. 2011). Many freshwater silverside lineages show biogeographic patterns that are consistent with allopatric speciation via river basin isolation.

In contrast, oceans are considered to be more ‘open’ and contiguously connected ecosystems (Rapoport 1994; Carr et al. 2003). Furthermore many marine fishes, including silversides (Watson 1996), have pelagic planktonic larvae that disperse long distances, and accordingly, marine species are known to have high levels of gene flow and population connectivity (Waples 1987; Palumbi 1994; Bohonak 1999; Bierne et al. 2003; Hellberg 2009; Puebla 2009). As a result marine fishes tend to have lower levels of population structure than freshwater fishes (Ward et al. 1994; MaKinen et al. 2006). Together, high population connectivity and gene flow in marine ecosystems dampen the effects of local adaptation and impede speciation (Bierne et al. 2003). There are notable exceptions where marine species show signatures of restricted gene flow over small spatial scales (e.g. Taylor and Hellberg 2003; Taylor and Hellberg 2005), but interestingly many of these taxa are reef associated and might have diversification rates on par with freshwater lineages (Bellwood and Wainwright 2002; Rocha et al. 2005; Alfaro et al. 2007; Rocha and Bowen 2008; Price et al. 2010; Price et al. 2011). Marine silversides in our study are not reef associated, precluding our ability to compare diversification rates between reef and freshwater lineages. Rather most marine silversides have large, coastal distributions that likely contribute to low speciation rates.

Freshwater silversides from lakes of the Central Mexican Plateau (Chirostoma and Poblana) may represent a “species flock” that resulted (in part) from intra-lacustrine sympatric speciation (Echelle 1984). It is possible that the estimate of overall speciation rate in freshwater silversides

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is strongly influenced by rapid speciation in this clade. Although some studies suggest that allopatric speciation may be slower than sympatric speciation (McCune and Lovejoy 1998), others have demonstrated that allopatric speciation can occur just as rapidly, even on par with clades thought to be classic examples of sympatric speciation (Near and Benard 2004). If the latter is true, then the prevalence of a particular mode of speciation on continents or in oceans may not be a good predictor of disparity in species richness. To our knowledge, there is no study comparing the frequency of speciation modes between closely related marine and continental lineages. If sympatric speciation is more common in continental lineages, then the inclusion of a clade that underwent sympatric speciation in our study is informative and a critical component of a complete explanation for why continental species richness is high.

5.5.2 Extinction rates elevated in freshwater

Marine silverside lineages have a near zero extinction rate, while extinction rates in freshwater silverside lineages were considerably higher (Figure 5.2b). However, despite high extinction rates in freshwater lineages, net diversification is still higher in freshwater lineages due to much greater speciation rates than marine lineages. Extinction rates estimated from molecular phylogenies are problematic (Rabosky 2010) and must be interpreted with caution. Nonetheless, our results for higher extinction rates in freshwater lineages are both biologically plausible and intriguing.

We propose that habitat connectivity and the ability to move in response to environmental disturbance are likely key parameters that result in differences in extinction rates between marine and freshwater lineages (Jablonski 2008, and references therein). Marine habitats are stable, long lasting and have high levels of connectivity (Lee and Bell 1999). In contrast, freshwater habitats are highly compartmentalized and spatially fragmented, with connectivity among drainages (and populations) dictated by the geomorphology of the region (Carr et al. 2003). Rivers and streams in particular have unique spatial structuring and ecosystem dynamics because they are dendritic networks, with drainages separated by uninhabitable (terrestrial and marine) areas (Grant et al. 2007). In the event of environmental disturbance (e.g. temperature change), marine fishes may be able to track suitable habitat because there are fewer barriers and physical restrictions to

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geographic species range shifts. For instance, during cooler periods tropical species occurring at higher latitudes might shift their ranges, moving to warmer latitudes near the equator (assuming biotic interactions allow it). Meanwhile, the fragmented nature of freshwater habitats reduces the possibility of range shifts in response to environmental disturbance such as climate change and marine incursions. Freshwater species may not have the necessary inter-drainage connections for dispersal, putting them at a higher risk of extinction (Fagan 2002; Fagan et al. 2002; Carr et al. 2003).

Both species range size and population size may also affect extinction rate. An inverse relationship between extinction rate and range size is widely supported by empirical and theoretical evidence (Jablonski 1987; Jablonski and Hunt 2006; Jablonski 2007; Jablonski 2008; Eastman and Storfer 2012), indeed range size is frequently cited as a likely cause of differential survival above the species level (i.e. species selection; Rabosky and McCune 2010). Marine silverside species tend to have large ranges while freshwater species are narrowly distributed, often limited to a single river drainage (Barbour 1973a; Chernoff 1986b); this pattern is likely general among teleost fishes. Numerically large populations are also expected to have lower extinction rates (Jablonksi 2008). Although there are no data comparing population sizes in silversides, marine taxa likely have larger populations, which may further reduce extinction risk. Our finding of higher extinction rates in freshwater compared to marine lineages may be a widespread pattern among aquatic taxa. If so, this finding has significant implications for both macroevolutionary patterns and conservation.

5.5.3 Geographic patterns of diversity and lineage accumulation

When resources are plentiful and competitors are limited, lineages are expected to accumulate exponentially. As diversification continues and niche space fills, resources become limited and competition increases, resulting in density-dependent diversification and a slowdown (downturn) in lineage accumulation in a LTT plot (Weir 2006; Rabosky and Lovette 2008; Rabosky 2009a, b). Benton (2001; 2009) suggested that density-dependent processes may have regulated marine diversity, while continental diversity has not been subjected to ecological constraints on clade growth. However, our results showed that neither continental nor marine silversides showed a

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pattern of density-dependent lineage accumulation. Instead both continental and marine lineages fit a constant growth (exponential) pattern of lineage accumulation. This suggests that silversides have not diversified to the point of saturating niche space in either marine or freshwater environments (although diversification seems to be more limited in eastern North America as discussed below). We find that marine lineage accumulation plots have a shallower slope than freshwater lineages, which is consistent with our hypothesis that marine lineages accumulate at a slower rate due to lower diversification rates. The few studies to investigate patterns of lineage accumulation in marine fishes have shown mixed results, but have focused on clades that are reef associated and thought to be examples of marine adaptive radiations (Ruber et al. 2003; Ruber and Zardoya 2005; Alfaro et al. 2007; Cowman and Bellwood 2011). As discussed above, it is likely that reef associated clades have different diversification dynamics than non-reef associated clades. We suspect that the processes determining marine silverside diversification are likely shared with other near-shore non-reef marine fishes, and that ecological limits might not be the primary control on clade growth in these taxa.

The geography of marine to freshwater transitions has played an important role in shaping patterns of diversity of silversides, as well as other fishes including anchovies (Bloom and Lovejoy 2012), needlefishes (Lovejoy and Collette 2001), and sea catfishes (Betancur-R. et al. in press). Silversides independently invaded freshwaters in eastern North America/Central Mexican Plateau, southern Mexico/Central America (twice), and the Pacific coast of Colombia. However, freshwater silverside diversity is not evenly distributed among these regions (Figure 5.1). Diversity is low in Colombia (one species) and eastern North America (four species, of which only Labidesthes sicculus has invaded far beyond lowland coastal rivers), and high in the Central Mexican Plateau (>19 species) and southern Mexico/Central America (>13 species). Overall, the fish fauna of eastern North America is very diverse (more so than southern Mexico/Central America and the Central Mexican Plateau region), and probably has been for a long time (Cavender 1986; Wilson and Williams 1992; Near et al. 2003). Both the initial invasion and subsequent diversification of lineages that have transitioned from marine to freshwater habitats may depend on the amount of competition with the incumbent freshwater community (Vermeij and Dudley 2000; Lovejoy et al. 2006; Betancur-R 2010; Yoder et al. 2010; Bloom and Lovejoy

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2011, 2012). We propose that competition with older, more diverse groups has prevented silversides from extensive diversification in North America. In contrast, the Central Mexican Plateau region has a relatively depauperate fish fauna and lacks large predatory fishes (Miller 2005). Also, our time-calibrated tree suggests that silversides were present in southern Mexico and northern Central America prior to the formation of the Panamanian Isthmus; thus, silversides were able to diversify before many South America fishes colonized Central America (Albert and Reis 2011). We suggest that in both the Central Mexican Plateau and southern Mexico/Central American there was ample ecological opportunity for diversification due to reduced competition with incumbents, which explains the greater freshwater silverside diversity in these regions. Our results highlight the usefulness of marine/freshwater sister lineage comparisions for understanding the effect of habitat on lineage diversity.

5.5.4 Species selection

Our finding that freshwater silversides have higher net diversification rates than marine silversides raises the possibility that the exceptional diversity found on continents is an example of species selection (or species sorting). A growing number of studies have demonstrated phylogenetic niche/biome conservatism (Lee and Bell 1999; Wiens and Graham 2005; Wiens et al. 2006; Crisp et al. 2009; Wiens et al. 2010; Bloom et al. 2012) across much of the tree of life, supporting macrohabitat (or habitat preference) as a heritable trait at the species level, a central tenet of species selection (Rabosky and McCune 2010). Benton (2001; 2009) suggested that differential survival among marine and freshwater lineages explains the disparity in species richness among marine and continental clades. Our results provide evidence supporting this claim. If Benton (2001; 2009) is correct, and high net diversification rates are a universal phenomenon of continental lineages, then a strong case can be made for species selection among marine and continental lineages. The current suite of approaches now available (Maddison et al. 2007; FitzJohn et al. 2009) and the increasing availability of high-resolution phylogenies for clades that include marine and freshwater members provide the necessary tools for testing hypotheses of differential survival at the species level.

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5.5.5 Acknowledgements

For contributing specimens/tissues or help collecting specimens in the field we thank John Lyons, Norman Mercado-Silva, Hernan Lopez-Fernandez, Dawn Phillip, Don Taphorn, Erling Holm, Eric Lewallen, Wayne Starnes, Mark Sabaj, Pablo Gesundheidt, Guillermo Orti, Mollie Cashner, and HJ Walker. The Smithsonian Tropical Research Institute provided logistical support and help with permits for collecting in Panama. Matt Davis offered helpful advice on BEAST analyses. Jason Weir provided guidance and discussion on diversification analyses and lineage through time plots. We thank members of the Lovejoy Lab and Lopez-Fernandez lab for constructive comments on this paper. Funding was provided by AMNH Lerner-Gray and the University of Toronto Centre for Global Change Studies grants to DDB, an NSERC Discovery Grant to NRL, and NSF DEB 0918073 to KRP.

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125

Figure 5.2 Posterior distribution of speciation (A), extinction (B), and character transition rate (C) parameters for marine (red) and freshwater (blue) lineages from our BiSSE Bayesian analysis.

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Figure 5.3 Lineage through time plots (LTT) for silversides from marine (red) and freshwater (blue) habitats. Both LTT plots show a pattern of exponential lineage accumulation. 127

Genu Species Habitat CytB ND2 TMO RAG1 Museum number Collection locality

Atherinella balsanas F x x x x SLU 6637 Rio Cancita, Michoacan, Mexico

Atherinella brasiliensis M x x x x ROM 88861 Chatham, Trinidad

Atherinella chagresi F x x x x STRI-02090 Rio Canazas, Panama

Atherinella alvarezi F x x x x SLU 6772 Laguna de Caobas, Mexico

Atherinella alvarezi F x x x na SLU 6772 Laguna de Caobas, Mexico

Atherinella ammophila F x x x x SLU-TC 380 Rio la Palma, Mexico

Atherinella argentea M JQ282017 x x JQ282062 ROM 91571 Playla Cruzas, Panama

BEING Atherinella argentea M x x x x PROCESSED Playla Cruzas, Panama

Atherinella blackburni M x x x x BEING Playa Baraka, Galeta, Panama 128

PROCESSED

BEING Atherinella blackburni M x x x x PROCESSED Playa Baraka, Galeta, Panama

Atherinella crystallina F x x x x SLU 6087 Rio Acaponeta, Nayarit, Mexico

Atherinella pellosemion F x x x x SLU 6115 Rio Mancuernas, Nayarit, Mexico

Atherinella colombiensis F x x x x STRI 02097 Rio San Juan, Colombia

Atherinella guatamalanensis F x x x x SLU 5012 Rio Tehuantepec, Mexico

Atherinella guatamalanensis F x x x x SLU 5085 Laguna Coyucan, Mexico

Atherinella guatamalanensis F x EF602045 x x SLU 6074 El Teucan Lagoon, Mexico

Atherinella guatamalanensis F x x x x SLU 6074 El Teucan Lagoon, Mexico

Atherinella hubbsi F x x x x SLU 6853 Costa Rica

Atherinella hubbsi F JQ282020 x x JQ282065 SLU 6853 Costa Rica

Atherinella marvalae F JQ282021 x x JQ282066 SLU 6690 Rio Papaloapan, Mexico

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Atherinella marvalae F x x x x SLU 6690 Rio Papaloapan, Mexico

Atherinella milleri F x x x x SLU 5104 Cangrejal river, Honduras

BEING Atherinella serrivomer M x x na x PROCESSED Play Peten, Boca Parita, Panama

BEING Atherinella panamensis M x x na x PROCESSED Playa la Cruzas, Panama

Atherinella sallei F x x x x SLU 5005 Rio Hueyapan, Mexico

BEING Atherinella sardina F x x x x PROCESSED L. Apoyo, Nicaragua

Atherinella schultzi F x EF602044 x na SLU 5103 Rio Palenque, Mexico

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Atherinella schultzi F x x x x SLU 5103 Rio Palenque, Mexico

Atherinella n. sp. M x x x x SLU 6853 Pacific Ocean, Mazatlan, Mexico

Atherinella schultzi F x x x x SLU TC5008 Rio Almoloya, Mexico

BEING Atherinella starksi M x x x x PROCESSED Tabago Island, Panama

Atherinomorus stipes M JQ282023 x x JQ282068 ROM 91573 Barbados

Atherinomorus stipes M x x x x ROM 91573 Barbados

Atherinops affinis M na x x JQ282061 SIO 0581 Pacific Ocean, California, USA

Atherinopsis californiensis M JQ282018 x x JQ282063 SIO 03458 Pacific Ocean, California, USA

Basilichthys semotilus F JQ282024 EF602042 na JQ282069 ANSP 180736 R. Santuario, Peru

Chirostoma arge F na EF602099 x na SLU 5110 Laguna Negritas, Mexico

Chirostoma attenuatum F x EF602083 x x SLU 5036 L. Zirahuen, Mexico

Chirostoma attenuatum F x EF602082 x x SLU 5036 L. Patzcuaro, Mexico

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Chirostoma chapalae F x EF602075 x x SLU 5016 L. Chapala, Mexico

Chirostoma consocium F JQ282025 EF602078 x JQ282070 SLU 5023 L. Chapala, Mexico

Chirostoma consocium F x x x x SLU 5023 L. Chapala, Mexico

Chirostoma contrerasi F x EF602098 x x SLU 5080 Rio Laja, Mexico

Chirostoma estor F x EF602068 x x SLU 5114 L. Patzcuaro, Mexico

Chirostoma grandocule F x EF602061 na na SLU 5118 L. Patzcuaro, Mexico

Chirostoma humboldtianum F x EF602070 x na SLU 5095 San Pedro Lagunillas, Mexico

Chirostoma humboldtianum F JQ282026 EF602071 x JQ282071 SLU 5011 Lago de Zacapu, Mexico

Chirostoma jordani F x EF602086 x x SLU 5033 L. Chapala, Mexico

Chirostoma jordani F JQ282027 EF602090 x JQ282072 SLU 5033 L. Cuitzeo, Mexico

Chirostoma labarcae F x EF602084 x x SLU 5017 L. Chapala, Mexico

Chirostoma labarcae F JQ282073 EF602085 x JQ282028 SLU 5017 L. Chapala, Mexico

Chirostoma lucius F EF602059 na SLU 5022 L. Negritos, Mexico

Chirostoma patzcuaro F JQ282029 EF602063 x JQ282074 SLU 5117 L. Patzcuaro, Mexico

Chirostoma promelas F x EF602060 x na SLU-TC 925 Tizaplan Hatchery, Mexico

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Chirostoma riojai F x EF602096 x x SLU 5079 L. Guadalupe Victoria, Mexico

Chirostoma riojai F JQ282030 EF602097 x JQ282075 SLU 5079 L. Guadalupe Victoria, Mexico

Chirostoma sphyraena F x EF602065 x x SLU 5025 L. Chapala, Mexico

Labidesthes vanhyningi F x EF602057 x x SLU 5106 Pine Log Creek, FL, USA

Labidesthes sicculus F JQ282031 x x JQ282077 SLU-TC 607 Duck River, TN, USA

Leuresthes tenuis M JQ282032 x x JQ282078 SIO 0563 Pacific Ocean, California, USA

Melanorhinus microps M x x x x ROM 91572 Archers Bay, Barbados

Melanorhinus microps M JQ282037 x x JQ282083 ROM 91572 Archers Bay, Barbados

Membras gilberti M x x x JQ282080 ROM 91569 Tabago Island, Panama

Membras gilberti M x x x x ROM 91569 Tabago Island, Panama

Membras martinica M JQ282035 x x x SLU 5102 Wrightsville Beach, NC, USA

Membras martinica M x x x JQ282081 SLU 5102 Wrightsville Beach, NC, USA

Menidia beryllina F x EF602049 x x SLU 5108 Bayou Lacombe, LA, USA

Menidia beryllina F JQ282033 x x JQ282079 ROM 91570 L. Ponchartrain, LA, USA

Menidia colei M x x x x SLU-TC 1914 Laguna de Caobas, Mexico

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Menidia colei M x x x x SLU-TC 1915 Laguna de Caobas, Mexico

Menidia extensa F x x x na na Lake Waccamaw, NC, USA

Menidia menidia M JQ282036 x x JQ282082 SLU-TC 2240 Wrightsville Beach, NC, USA

Menidia menidia M x EF602050 x x SLU-TC 2241 Wrightsville Beach, NC, USA

Menidia peninsulae M JQ282038 x x JQ282084 SLU 5107 Panama City, FL, USA

Menidia peninsulae M x x x x SLU 5107 Panama City, FL, USA

Notocheirus hubbsi M x na na x na Atlantic Ocean, Argentina

Odonthesthes mauleanum F x x x x na Rio Itata, Chile

Odonthesthes smitti M x x x x na Puerto Madryn, Argentina

Poblana letholepis F x EF602105 x x SLU 5116 L. Preciosa, Mexico

Poblana squamata F x EF602112 x na SLU 5115 L. Preciosa, Mexico

Poblana alchichica F x EF602109 x x SLU 5034 L. Alchichica, Mexico

Poblana alchichica F x EF602110 x x SLU 5034 L. Alchichica, Mexico

Poblana ferdebueni F x EF602100 x x SLU 5028 L. Chignahuapan, Mexico

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Poblana ferdebueni F JQ282039 EF602101 x JQ282085 SLU 5028 L. Chignahuapan, Mexico

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Table 5.2 Summary of parameter estimates from BiSSE analyses.

Model Parameters Logln AIC λ 0 λ 1 µ 0 µ 1 q01 q10

Unconstrained 6 -143.881 299.76 0.03023 0.61959 0.00002 0.57429 0.01727 0.01479

q10=q01 5 -143.883 297.77 0.02993 0.61564 0 0.57429 0.01453 0.01453

µ0=µ1 5 -148.326 306.65 0.08615 0.32038 0.18986 0.18986 0 0.06467

λ0=λ1 5 -152.527 315.06 0.32590 0.32590 0.40445 0.21520 0 0.07389

µ0=µ1, q01=q10 4 -151.108 310.21 0.08821 0.30205 0.17812 0.17812 0.06127 0.06127

λ0=λ1, q01=q10 4 -155.110 318.21 0.32355 0.32355 0.31156 0.25633 0.04679 0.04679

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6 Concluding discussion and synthesis

In this thesis I investigated macroevolutionary transitions between marine and freshwater biomes at continental scales. To this end, I generated molecular phylogenies for numerous groups of fishes that include both exclusively marine and freshwater species to test a number of hypotheses regarding the geography, timing, frequency, and mechanisms regulating biome transitions. Further, I investigated the evolutionary processes that generated disparate patterns of diversity between continents and oceans. Below I briefly summarize the main conclusions of the preceding chapters, provide a synthesis that represents a state-of-the-union for the burgeoning topic of marine/freshwater transitions, and consider new directions for the field.

Summary of data chapters

Chapter two: Molecular phylogenetics reveals a pattern of biome conservatism in New World anchovies (family Engraulidae). In this chapter I investigated the number of transitions between marine and freshwaters in New World anchovies. I generated DNA sequence data for multiple (mitochondrial and nuclear) genes, and generated the first comprehensive phylogeny for anchovies, including 15 of 17 recognized genera in Engraulidae. South American freshwater anchovies exhibit rather remarkable ecological and morphological diversity for anchovies and previous taxonomic classification indicated multiple origins for these lineages. Using ancestral character reconstruction to estimate biome transitions, I found that South American freshwater anchovies are the result of a single marine to freshwater transition, rejecting the hypothesis of multiple origins and supporting a pattern of biome conservatism. New World anchovies clearly had ample opportunity to invade freshwaters habitats and the physiological ability for marine/freshwater transitions. I argue that competition is the primary mechanism driving biome conservatism at continental scales and across macroevolutionary time.

Chapter three: A time calibrated phylogeny for Clupeiformes (herrings, anchovies, sardines and allies) clarifies the evolution of diadromy and marine/freshwater transitions. In chapter three I explored the evolutionary origins of diadromy and its role in biome transitions in Clupeiformes. I assembled the largest phylogenetic dataset to date for Clupeiformes, a clade that includes some 137

of the world’s most important fishes, such as sardines, herring, shads, and anchovies. Using a time-calibrated phylogeny with eight fossil and biogeographic calibration points, I rejected a long-standing hypothesis that suggested primary productivity was the major determinant for the origins of the different modes of diadromy. Importantly, I also showed that there is no evidence that diadromy is an intermediate step in marine/freshwater transitions. The divergences time estimates for major clupeiform lineages in this chapter represent the most extensive age estimates available, and provides a robust temporal framework for interpreting the evolution of this group.

Chapter four: The evolutionary origins of marine derived freshwater fishes in South America. In chapter four I investigated the remarkable diversity of marine derived freshwater fishes in South America. I investigated the biogeographic patterns and timing of eight independent marine derived lineages to reveal two waves of marine invaders into South America, each linked to a unique earth history event. The first wave of marine invaders colonized Amazonia during an Eocene marine incursion from either the Caribbean or the Pacific. The second wave of invaders colonized South America from the Caribbean during a relatively small marine incursion into the Llanos region in the Oligocene. Importantly, this study rejects the Miocene marine incursion hypothesis as the primary explanation for marine derived lineages in South America. However, both waves of invaders seem to have undergone extensive diversification during the Miocene, a period characterized by an enormous wetland system called Pebas Mega-wetland. The Pebas Mega-wetland received periodic marine incursions, which may have created favorable conditions for diversification in lineages with a relatively recent marine ancestry. This study is notable for its taxonomic breadth and demonstrates the effectiveness of using a phylogenetic framework to test broad biogeographic hypotheses.

Chapter five: Do freshwater fishes diversify faster than marine fishes? A test using state- dependent diversification analyses and molecular phylogenetics of New World silversides (Atherinopsidae). The disparity in species richness between continents and oceans has been called one of the steepest biodiversity gradients in the world (Vega and Wiens 2012). In chapter five I investigated the evolutionary mechanisms driving this extraordinary pattern of diversity using a time-calibrated phylogeny of silversides and recently developed diversification analyses.

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State-dependent diversification analysis that test for differences in speciation, extinction and character transition rates demonstrated that freshwater silversides have higher net diversification rates than marine silversides. Interestingly, both marine and freshwater lineages accumulated more or less constantly over time, suggesting that neither is regulated by ecological limits on clade growth. Instead, freshwater fishes simply accumulate new lineages at a faster rate than marine lineages. This finding constitutes the first direct test for macroevolutionary processes that determined the much greater species diversity found on continents than in oceans.

Synthesis

Transitions between biomes are major evolutionary events that have profound impacts on the diversity of life on earth. Thus not surprisingly these events attract considerable attention among evolutionary biologists. Indeed, discoveries of transitional fossils such as Tiktaalik rosae, that provide a direct link between aquatic and terrestrial ecosystems are considered some of the most important biological discoveries of all-time (Shubin et al. 2006; Niedzwiedzki et al. 2010). Studying these deep-time evolutionary events was historically a task for paleontologists (Gray 1988). However, the advent of DNA sequencing facilitated the production of high-resolution molecular phylogenies. Tools were subsequently developed that allowed users to produce robust time-calibrated trees, reconstruct character histories on those trees, and estimate diversification rates to test macroevolutionary hypotheses. These rapid methodological developments over the past 20+ years have opened the door for neontological data to investigate the deep-time events. The proliferation of macroevoutionary studies on marine/freshwater transitions is an excellent example of this enormous progress. The first study utilizing molecular phylogenetics to investigate marine/freshwater transitions was published 14 years ago (Lovejoy et al. 1998). Since that time, there have been dozens of similar studies spanning taxonomic groups across the tree of life (see references in chapter two). Below I provide a synthesis of what we have learned from these studies and point out opportunities for future research.

Most studies to date have investigated the number, frequency, and directionality of marine/freshwater transitions. The most common patterns among these studies were that biome transitions were rare events and the directionality is most often from marine to freshwaters. In 139

chapter two I investigated these topics in anchovies and found that a pattern of biome conservatism, which is evidently common across the tree of life (Crisp et al. 2009), although there are some exceptions (Alverson et al. 2007). The tendency for closely related taxa to have similar ecologies is not unique to aquatic biomes, but rather a widespread pattern (Wiens and Graham 2005; Wiens et al. 2010). In an effort to explain why plants are more apt to move to a new geographic area than evolve a new thermal niche evolutionary biologist Michael Donoghue stated, “It’s easier to move than evolve (unless it isn’t)” (Donoghue 2008). Donoghue’s quote succinctly summarizes our general understanding of the relative difficulty and infrequency of biome transitions. But why might this be? Competition has been championed as an important mechanism driving ecological niche conservatism (Wiens and Donoghue 2004; Wiens et al. 2010). In chapter two I presented an argument for competition being the driving mechanism behind biome conservatism. Clupeiformes were of marine origin, but have invaded freshwaters up to 12 times (chapter 3), suggesting that this group has the physiological ability to undergo biome transitions. Despite ample opportunity to invade freshwater habitats, Clupeiformes rarely invade the same geographic area more than once and when multiple invasions did occur, the invading lineages were vastly different morphologically and ecologically. This suggests that that once an invasion has occurred, competition from closely related taxa prevents subsequent invasions (Wiens et al. 2006; chapters 2 and 3).

Recently, Betancur-R et al. (2012) investigated diversification and biome transitions in ariid catfishes and found that when marine lineages invaded areas of high incumbent diversity, diversification of the invading lineage was dampened. However, when ariids invaded Australia- New Guinea, an area of low incumbent diversity, the invading lineage experienced increased morphological and lineage diversification. This indicates that competition from distantly related taxa may limit diversification following biome transitions. In chapter 5, I investigated marine/freshwater transitions in New World silversides and found that lineages in Central Mexico and Central America had much greater species diversity than found in North and South America (see also Bloom et al. 2009). Both Central Mexico and Central America have a high degree of endemism, but relatively low species diversity (Abell et al. 2008), suggesting that when silversides invaded these novel areas, there was ample opportunity for diversification due

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to reduced competition (Schluter 2000; Yoder et al. 2010). In sum, biome transitions have occurred relatively rarely over large spatial and temporal scales, and competition seems to have played an important role in driving this pattern. Determining the mechanisms driving biome conservatism should be a fruitful topic for future studies.

Given that marine/freshwater transitions are difficult, what processes facilitate these evolutionary events? In chapter three I investigated whether diadromy (migration between marine and freshwaters) is involved in biome transitions. Several models for the evolution of diadromous lineages call for a selective regime that results in the permanent isolation of a once migratory species in either marine or freshwater (Gross 1987; Gross et al. 1988; Dodson et al. 2009). Although there are a number of landlocked populations of otherwise diadromous species, there is no evidence that diadromy facilitates continental scale diversification (see chapter three). An alternative is that transitions from marine to freshwaters are linked to paleogeographic events such as marine incursions. In chapter four I demonstrated that the origins of marine derived lineages in South America could be traced to two episodes of marine incursion that penetrated deep into the continent. Interestingly, freshwater herring in African rivers and lakes are thought to have colonized during marine incursions into western Africa (Wilson et al. 2008). Furthermore, pufferfishes have independently colonized South America, central Africa, and southeastern Asia, and the timing of each invasion can be linked to a period of marine incursion into these respective continents (Yamanoue et al. 2011). Marine incursions likely do not explain all marine to freshwater transitions. Some groups, such as killifishes are osmotolerant specialists and have undergone repeated biome transitions (Whitehead 2010). Some non-fish studies have invoked a dispersal explanation (Hershler and Liu 2008), which while certainly possible, seem to lack a general mechanism for how this might occur.

To my knowledge, no study has linked a particular paleogeographic event to freshwater to marine transitions. This may in part be due to the relative rarity of this type of transition (see above and chapter 2) but how and when it does occur is largely unknown. Anchovies have several lineages that have invaded coastal marine habitats from a freshwater ancestry, however these events were not synchronous and neither appears to correlate to any particular earth history

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event (chapters 2 and 3). Clearly this topic is in need of further investigation. The emerging picture is that many marine/freshwater transitions are often, but not always linked to marine incursions. However, most studies have focused on South American marine derived lineages (Lovejoy et al. 2006; Bloom and Lovejoy 2011). Future studies should consider the role of paleogeography in facilitating on biome transitions in other geographic areas.

The disparity in species richness between continents and oceans is one of the most dramatic biodiversity gradients on earth. Yet this pattern of diversity has rarely been studied from a macroevolutionary perspective. In fact, Vega and Wiens (2012) was the first study to test for differences in net diversification rates between continental (freshwater) and oceanic lineages. In chapter five I explicitly tested for differences in diversification rates between marine and freshwater lineages and found that freshwater lineages diversify faster than marine lineages. These results are novel and important because they offer a mechanistic explanation for the disparity between continental and oceanic diversity. In chapter five, I presented a detailed discussion for why freshwater lineages might experience faster diversification rates than marine lineages, and suggest allopatric speciation occurs more frequently due to the prevalence of barriers in freshwater habitats. There is also some indication that adaptive radiation is more common in freshwater clades, though this has never been the focus of a study. Several recent studies have also found a pattern that suggests freshwater lineages diversify faster than closely related marine lineages. For example, Davis et al. (2012) found that grunters experienced an increase in lineage diversification rates and morphological diversification following the transition to freshwaters of Australia. Betancur et al. (2012) found that freshwater ariid catfishes underwent rapid diversification in Australia and New Guinea, but not in other continental areas. The ecological opportunity offered by biome transitions extends to non-fishes; amphipods experienced rapid diversification following colonization of freshwaters during the Eocene in Eurasia (Hou et al. 2011). Together, these studies and chapter five of my thesis comprise an emergent body of work that indicates marine/freshwater transitions can profoundly impact lineage diversification rates.

Community phylogenetics

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The merging fields of ecology and evolutionary biology (Webb et al. 2002; Cavender-Bares and Wilczek 2003; Cavender-Bares et al. 2009) have yielded thought-provoking avenues for studying aquatic community assemblages that include marine derived lineages. Biotic interchange, or species invasions can enrich community assemblages (Sax et al. 2007). An elegant example is the movement of species between Atlantic and Pacific oceans facilitated by the opening of the Panama canal, which ultimately lead to an increase in species richness in local fish communities (Smith et al. 2004). By the same token, transitions between marine and freshwaters may increase species richness at local scales. Perhaps even more interestingly, invading lineages may alter the phylogenetic community structure at different taxonomic scales. The emerging field of community phylogenetics investigates whether co-occuring species are phylogenetically more (phylogenetically conserved) or less (phylogenetically over-dispersed) closely related than expected by chance (Webb et al. 2002). One might predict that regions that have been invaded by numerous marine lineages become increasingly phylogenetically over-dispersed. For example, South America ichthyofauna is dominated by very few higher-level clades (see chapter 4). However, the extraordinary numbers of marine lineages that have colonized the South American continent add an additional 14 taxonomic orders of fishes to the continental scale community pool. Even on more local scales, marine derived lineages often dominate the community composition (D. Bloom personal observation). Investigating how marine derived lineages can alter phylogenetic community structure seems to have enormous potential for insight into the interface between macroevolutionary events and community ecology.

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8 Appendices

Appendix 1. Supplementary figure for chapter 3.

170

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-ILLIONS OF YEARS AGO

171

Time-calibrated phylogeny of Clupeiformes showing ancestral character reconstructions of marine (red), freshwater (blue), anadromous (green), and catadromous (light blue) lineages. Branch colors indicate character states from maximum likelihood reconstructions with branches states considered unambiguous when the log-likelihood was 2.0 units higher than the alternative state. This is the same as figure 5 from chapter 3 with geographic areas indicated for freshwater and anadromous lineages to illustrate that freshwater lineages rarely invade the same area more than once.

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Appendix 2. Supplementary figures and tables for chapter 4.

Figures show maximum parsimony and maximum likelihood ancestral character reconstructions. Marine lineages are red and freshwater lineages are blue. Tables include taxon sampling and genbank numbers for each group used in chapter 4, respectively. The table for Clupeiformes can be found in chapter 3 and thus is not provided here.

Maximum parsimony reconstructions for stingrays. Time scale is in millions of years.

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Maximum likelihood reconstructions for stingrays. Time scale is in millions of years.

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Chronogram for stingrays showing 95% HPD of node ages.

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Maximum parsimony reconstructions for Clupeifomes.

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Maximum likelihood reconstructions for Clupeiformes.

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Chronogram of Clupeiformes showing 95% HPD for node ages.

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Maximum parsimony reconstructions for Beloniformes. Time scale is in millions of years.

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Maximum likelihood reconstructions for Beloniformes. Time scale is in millions of years.

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Chronogram for Beloniformes showing 95% HPD for node ages.

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Maximum parsimony reconstructions for Sciaenidae (drums).

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Maximum likelihood reconstructions for Sciaenidae (drums).

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Chronogram for Sciaenidae showing 95% showing 95% HPD for node ages.

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Taxon sampling and genbank numbers for stingrays used in chapter 4.

Family Genus species C01 Cytb Rag1 SCFD2

Zanobatidae Zanobatus schoenleinii JN184086 JN184086 JN184113 JN184156

Hexatrygonidae Hexatrygon bickelli JN184061 JN184061 JN184120 JN184163

Urolophidae Urolophous cruciatus JN184085 JN184085 JN184129 JN184172

Gymnuridae Gymnura crebripunctata JN184060 JN184060 JN184119 JN184162

Plesiobatidae Plesiobatis daviesi JN184070 JN184070 JN184125 JN184168

Myliobatidae Myliobatis australis JN184064 JN184064 JN184123 JN184166

Aetobatus ocellatus JN184054 JN184054 JN184121 JN184164

Rhinopteridae Rhinoptera steindachneri JN184076 JN184076 JN184124 JN184167

Mobulidae Mobula japanica JN184063 JN184063 JN184122 JN184165

Dasyatidae Pastinachus solocirostris JN184066 JN184066 JN184116 JN184159

Urogymnus asperrimus JN184084 JN184084 JN184118 JN184161

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Dasyatis brevis JN184058 JN184058 JN184114 JN184157

Neotrygon kuhlii JN184065 JN184065 JN184115 JN184158

Taeniura lymma JN184079 JN184079 JN184117 JN184160

Urotrygonidae Urobatis hallleri JN184083 JN184083 JN184128 JN184171

Potamotrygonidae Himantura schmardae JN184062 JN184062 JN184126 JN184169

Himantura pacifica EF532645 AF110638 NA NA

Heliotrygon gomesi NA JF358007 NA NA

Paratrygon ajereba NA AF110629 NA NA

Plesiotrygon iwamae EF532668 AF110636 NA NA

Potamotrygon falkneri EF532679 NA NA NA

Potamotrygon henlei EF532665 NA NA NA

Potamotrygon hystrix JN184071 JN184071 JN184127 JN184170

Potamotrygon leopoldi EF532677 NA NA NA

Potamotrygon motoro EF532653 AF110626 NA NA

195

Potamotrygon orbignyi EF532646 AF110625 NA NA

Potamotrygon schroederi EF532673 NA NA NA

Potamotrygon scobina EF532654 NA NA NA

Potamotrygon yepezi NA AF110628 NA NA

Taxon sampling and genbank numbers used for Beloniformes in chapter 4.

Family Genus Species Cytb Rag 1 Rag2 TMO4c4

Adrianichthyidae Oryzias javanicus X X X NA

Adrianichthyidae Oryzias matanensis X X X AF244068

Adrianichthyidae Xenopoecilus oophorus X X X X

Belonidae Ablennes hians AF243859 X AY693520 AF244011

Belonidae Belone belone AF243907 X AY693547 AF244059

Belonidae Belone svetovidovi AF243880 X AY693531 AF244032

Belonidae Belonion apodion AF243931 X AF306488 AF244082

196

Belonidae Belonion dibranchodon AF243879 X AF306468 AF244031

Belonidae Petalichthys capensis AY693506 X AY693577 AY693446

Belonidae Platybelone argalus AF243874 X AF306464 AF244026

Belonidae Potamorrhaphis eigenmanni AF243882 X AF306470 AF244034

Belonidae Potamorrhaphis guianenis AF243876 X AF306466 AF244028

Belonidae Potamorrhaphis petersi AF243892 X AF306474 AF244044

Belonidae Pseudotylosurus angusticeps AF243893 X AF306475 AF244045

Belonidae Pseudotylosurus microps AY693505 X AY693576 AY693445

Belonidae Strongylura anastomella AY693515 X NA AY693455

Belonidae Strongylura exilis AF243910 X AF306482 AF244062

Belonidae Strongylura fluviatilis AF243895 X AF306477 AF244047

Belonidae Strongylura hubbsi AF243897 X AF306479 AF244049

Belonidae Strongylura incisa AF243884 X AF306472 AF244036

Belonidae Strongylura krefftii AF243899 X AY693539 AF244051

197

Belonidae Strongylura leiura AF243901 X AY693541 AF244053

Belonidae Strongylura marina AF243866 X AF306462 AF244018

Belonidae Strongylura notata AF243856 X AF306489 AF244008

Belonidae Strongylura scapularis AF243918 X AF306487 AF244069

Belonidae Strongylura senegalensis AF243912 X AF306484 AF244064

Belonidae Strongylura strongylura AF243886 X AY693534 AF244038

Belonidae Strongylura timucu AF243862 X AF306460 AF244014

Belonidae Tylosurus acus AF243860 X AY693521 AF244012

Belonidae Tylosurus crocodilus AF243888 X AY693536 AF244040

Belonidae Tylosurus gavialoides AF243903 X AY693543 AF244055

Belonidae Tylosurus punctulatus AF243905 X AY693545 AF244057

Belonidae Xenentodon cancila AF243890 X AF306473 AF244042

Exocoetidae Cheilopogon abei HQ325604 X HQ325671 X

Exocoetidae Cheilopogon astrisignis HQ325606 X HQ325673 X

198

Exocoetidae Cheilopogon cyanopterus HQ325608 X HQ325675 X

Exocoetidae Cheilopogon dorsomacula AY693497 X AY693568 AY693437

Exocoetidae Cheilopogon exsiliens HQ325612 NA HQ325679 X

Exocoetidae Cheilopogon furcatus HQ325614 X HQ325681 X

Exocoetidae Cheilopogon melanurus AF243870 X AY693527 AF244022

Exocoetidae Cheilopogon pinnatibarbatus HQ325618 X HQ325685 X

Exocoetidae Cheilopogon spilonotopterus AY693504 X AY693575 AY693444

Exocoetidae Cheilopogon xenopterus HQ325621 X HQ325688 X

Exocoetidae Cypselurus angusticeps HQ325623 X HQ325690 X

Exocoetidae Cypselurus callopterus HQ325625 X HQ325692 X

Exocoetidae Cypselurus hexazona HQ325627 X HQ325694 X

Exocoetidae Exocoetus monocirrhus AY693496 NA AY693567 AY693436

Exocoetidae Exocoetus obtusirostris HQ325630 X HQ325697 X

Exocoetidae Exocoetus peruvianus HQ325632 X HQ325699 X

199

Exocoetidae Exocoetus volitans HQ325634 X HQ325701 X

Exocoetidae Fodiator rostratus AY693500 X AY693571 X

Exocoetidae Hirundichthys affinis HQ325640 X HQ325707 X

Exocoetidae Hirundichthys albimaculatus HQ325643 NA HQ325710 NA

Exocoetidae Hirundichthys marginatus HQ325644 X HQ325711 X

Exocoetidae Hirundichthys rondeletii HQ325647 X HQ325714 X

Exocoetidae Hirundichthys speculiger HQ325651 X HQ325718 X

Exocoetidae Parexocoetus brachypterus HQ325657 X HQ325724 X

Exocoetidae Parexocoetus hillianus AF243868 NA AY693525 AF244020

Exocoetidae Parexocoetus mento HQ325661 X HQ325728 X

Exocoetidae Prognichthys gibbifrons HQ325662 NA HQ325729 NA

Exocoetidae Prognichthys glaphyrae HQ325664 X HQ325730 X

Exocoetidae Prognichthys occidentalis HQ325666 X HQ325732 X

Exocoetidae Prognichthys seali HQ325667 X HQ325733 NA

200

Exocoetidae Prognichthys tringa AY693493 X AY693564 AY693433

Hemiramphidae Arrhamphus sclerolepis AY693510 X X AY693450

Hemiramphidae Chriodorus atherinoides X X X X

Hemiramphidae Dermogenys bruneiensis X X NA NA

Hemiramphidae Dermogenys collettei X X X X

Hemiramphidae Dermogenys siamensis X X X X

Hemiramphidae Euleptorhamphus velox X X X X

Hemiramphidae Euleptorhamphus viridis X X X X

Hemiramphidae Hemiramphus archipelagus X X X X

Hemiramphidae Hemiramphus balao X X AY693529 AF244024

Hemiramphidae Hemiramphus brasiliensis X X AY693524 AF244017

Hemiramphidae Hemiramphus lutkei X X X X

Hemiramphidae Hemiramphus robustus X X X X

Hemiramphidae Hemiramphus saltator X X X X

201

Hemiramphidae Hemiramphus far AY693516 X AY693582 AY693456

Hemiramphidae Hemirhamphodon pogognathus X X AY693559 AF244005

Hemiramphidae Hyporhamphus affinis X X X X

Hemiramphidae Hyporhamphus brederi X X X X

Hemiramphidae Hyporhamphus dussemieri X X X X

Hemiramphidae Hyporhamphus limbatus X X X X

Hemiramphidae Hyporhamphus naos X X X X

Hemiramphidae Hyporhamphus regularis ardelio X X X X

Hemiramphidae Hyporhamphus roberti X X X X

Hemiramphidae Hyporhamphus sajori AY693508 X NA AY693448

Hemiramphidae Hyporhamphus snyderi X X X X

Hemiramphidae Hyporhamphus mexicanus X X X X

Hemiramphidae Hyporhamphus quoyi AF243920.1 X AY693552 AF244071

Hemiramphidae Melapedalion breve X X X X

202

Hemiramphidae Nomorhamphus megarrhampus X NA NA X

Hemiramphidae Nomorhamphus ravnaki AY693556 X AY693556 AF244077

Hemiramphidae Nomorhamphus vivipara X X X X

Hemiramphidae Nomorhamphus weberi X X AY693557 AF244078

Hemiramphidae Oxyporhamphus convexus X X X X

Hemiramphidae Oxyporhamphus similis AY693490 X HQ325722 X

Hemiramphidae Oxyporhamphus micropterus X X X X

Hemiramphidae Zenarchopterus dispar X X X NA

Hemiramphidae Zenarchopterus buffonis AF243921 X AY693553 AF244072

Hemiramphidae Zenarchopterus gilli X X X NA

Scomberesocidae Cololabis saira AF243915 X AY693549 AF244067

Scomberesocidae Elassichthys adocetus AY693512 X AY693580 AY693452

Scomberesocidae Scomberesox saurus AF243909 X AY693548 AF244061

203

Taxon sampling and genbank numbers used for Sciaenidae in chapter 4.

Species co1 atp cytb rag1

Aplodinotus grunniens EU522441 NA AY225662 NA

Argyrosomus hololepidotus DQ107796 NA NA NA

Argyrosomus inodorus HM007716 NA NA NA

Argyrosomus regius NA NA DQ197924 NA

Atractoscion aequidens HM007698 NA DQ197926 NA

Atractoscion nobilis GU440241 GQ220049 GQ220018 NA

Bairdiella armata NA GQ220055 FJ620884 NA

Bairdiella chrysoura GU225145 NA DQ060514 NA

Bairdiella ronchus GU225149 GQ220056 NA NA

Bairdiella sanctaeluciae GU225153 NA NA NA

Cheilotrema saturnum GU440274 NA NA NA

Chrysochir aureus EF609333 NA NA NA

204

Collichthys lucidus HM180539 NA NA NA

Cynoscion acoupa NA GQ220026 GQ219995 NA

Cynoscion albus NA GQ220032 FJ620875 NA

Cynoscion analis NA GQ220043 GQ220012 NA

Cynoscion arenarius EU180144 GQ220035 DQ060516 NA

Cynoscion guatucupa EU074395 GQ220042 GQ220011 NA

Cynoscion jamaicensis NA GQ220027 GQ219996 NA

Cynoscion leiarchus NA GQ220030 GQ219999 NA

Cynoscion microlepidotus NA GQ220028 GQ219997 NA

Cynoscion nebulosus EU180146 GQ220044 DQ060515 NA

Cynoscion nothus EU180147 GQ220037 GQ220006 NA

Cynoscion othonopterus NA GQ220038 GQ220007 NA

Cynoscion parvipinnis NA GQ220031 GQ220000 NA

Cynoscion phoxocephalus NA GQ220041 GQ220010 NA

205

Cynoscion praedatorius NA GQ220039 GQ220008 NA

Cynoscion regalis EU180145 GQ220034 GQ220003 EF095660

Cynoscion reticulatus NA GQ220036 FJ620876 NA

Cynoscion squamipinnis NA GQ220040 FJ620878 NA

Cynoscion striatus NA JN683807 NA JN683822

Cynoscion sp. HQ689365 NA NA NA

Cynoscion virescens HQ689373 GQ220029 GQ219998 NA

Cynoscion xanthulus NA GQ220033 GQ220002 NA

Dendrophysa russelii EU148580 NA NA NA

Equetus lanceolatus FJ583400 NA NA NA

Equetus punctatus FJ583402 NA NA NA

Genyonemus lineatus GU936486 NA NA NA

Isopisthus remifer NA GQ220048 NA NA

Johnius belangerii EF607410 NA NA NA

206

Johnius borneensis FJ347919 NA NA NA

Johnius dussumieri FJ347915 NA NA NA

Johnius elongatus EF534122 NA NA NA

Johnius sp HQ945876 NA NA NA

Larimichthys crocea HM180640 NC_011710 EU346914 NA

Larimichthys polyactis DQ107816 NC_013754 AB372028 NA

Larimus fasciatus NA NA DQ059327 NA

Leiostomus xanthurus HQ024954 NA DQ060511 EU167843

Macrodon ancylodon NA GQ220045 AY253610 NA

Macrodon mordax NA GQ220046 FJ620880 NA

Menticirrhus americanus EU074463 NA DQ060513 NA

Menticirrhus littoralis NA NA DQ060512 NA

Menticirrhus undulatus GU440404 NA DQ059325 NA

Micropogonias furnieri EU074482 JN683808 NA JN683821

207

Micropogonias undulatus HQ024968 NA NA EU167848

Miichthys miiuy EU266377 NC_014351 HM447240 NA

Nebris microps NA GQ220053 GQ220022 NA

Nebris occidentalis NA GQ220052 GQ220021 NA

Nibea albiflora EU595222 HQ890947 EU219529 NA

Nibea maculata EU014247 NA NA NA

Nibea soldado HQ219157 NA NA NA

Otolithes ruber EF536896 NA NA NA

Otolithoides biauritus EF536892 NA NA NA

Pachypops fourcroi NA JN683803 NA NA

Pachypops sp. 'Tapajos' NA NA NA JN683820

Pachypops/Pachyurus sp. 1 NA JN683804 NA JN683817

Pachypops/Pachyurus sp. 2 NA JN683805 NA JN683818

Pachypops/Pachyurus sp. 3 NA JN683806 NA JN683819

208

Pareques acuminatus FJ583830 NA NA NA

Pareques sp. GU224573 NA NA NA

Pennahia anea EU676149 NA NA NA

Pennahia argentata JF952682 NC_015202 AB372025 NA

Pennahia macrocephalus JF952684 NA NA NA

Plagioscion auratus FJ418762 JN683801 NA JN683815

Plagioscion magdalenae NA JN683799 NA JN683814

Plagioscion montei NA JN683800 NA JN683813

Plagioscion sp. 1 NA JN683797 NA JN683811

Plagioscion sp. 2 NA JN683798 NA JN683812

Plagioscion squamosissimus NA JN683756 GQ220020 JN683809

Plagioscion ternetzi NA JN683802 NA JN683816

Pogonias cromis EU752164 NA NA NA

Protonibea diacanthus EF528230 NA NA NA

209

Pseudotolithus senegalensis NA NA DQ197986 NA

Pseudotolithus typus NA NA DQ197988 NA

Roncador stearnsii EU547248 NA NA NA

Sciaenops ocellatus EU180148 NA DQ059324 GU368832

Seriphus politus NA GQ220050 GQ220019 NA

Stellifer illecebrosus NA GQ220054 FJ620883 NA

Stellifer lanceolatus NA NA DQ060517 NA

Umbrina canariensis NA NA EF392638 NA

Umbrina roncador GU440563 NA NA NA

OUTGROUPS

Beryx splendens AP002939 AP002939 NA EF095636

Lates calcarifer NC_007439 NC_007439 NA GU368820

Morone chrysops NA NA AY770838 GU368823

210

Halichoeres melanurus AP006018 AP006018 NA AY208617

Chaetodon striatus NA NA NA EF530085

Zebrasoma scopas NA NA NA AY308776

211