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Evolution of the latitudinal species diversity gradient of New World birds and mammals Weir, Jason Tyler 2007

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EVOLUTION OF THE LATITUDINAL SPECIES DIVERSITY GRADIENT OF NEW WORLD BIRDS AND MAMMALS By JASON TYLER WEIR B.Sc, Canadian University College, 2001 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF T H E REQUIREMENTS FOR T H E D E G R E E OF DOCTOR OF PHILOSOPHY iri T H E F A C U L T Y OF G R A D U A T E STUDIES (Zoology) T H E UNIVERSITY OF BRITISH COLUMBIA August 2007 © Jason Tyler Weir, 2007 ABSTRACT The latitudinal diversity gradient in which species diversity is highest near the equator and declines toward the poles is well characterized in most higher level taxonomic groups and is strongest in the New World. However, the underlying causes of this gradient are poorly understood. By sampling New World birds and mammals, we found that the distribution of the evolutionary ages of sister species adheres to a latitudinal gradient. The time to divergence for sister species is shortest at high latitudes and longer in the tropics. Birth-death models fitting these data estimate that the highest recent speciation and extinction rates occur at high latitudes and decline toward the tropics suggesting that rates of species turnover are greatest where diversity is lowest. A pattern of endemism in boreal superspecies plausibly links the recent divergence of high latitude species to the fragmentation of the North American boreal forest by climatic oscillations during the Pleistocene ice ages. While all boreal superspecies tested date to the Pleistocene, only 56% of sub-boreal superspecies members date to this period. Similarly, montane tropical faunas, which were also directly impacted by buildup of glaciers during ice age cycles, were composed of younger species than low elevation faunas. Together these results suggest that faunas directly fragmented by expanding and retracting ice sheets experienced rapid rates of species turnover contributing to the lower species diversity of these regions. In contrast, the older ages of faunas at lower latitudes and altitudes suggest that long-term climatic stability promoted the gradual accumulation of high species diversity in these regions. Faunal interchange between continents may also have contributed to the exceptionally high species diversity of the New World tropics. Molecular dating suggests interchange rates between the distinctive avifaunas of North and South America were significantly faster after completion of the Central American landbridge three million years ago. Composition of tropical bird faunas were directly impacted by a relatively recent burst of faunal mixing which had the potential to elevate Neotropical species diversity over other tropical regions. ii T A B L E O F C O N T E N T S Abstract ii Table of Contents iii List of Tables iv List of Figures v List of Appendces vi Acknowledgments vii Dedication ix Co-Authorship Statement x Chapter One General Introduction 1 1.1 Literature Cited 5 Chapter Two The Latitudinal Gradient in Recent Speciation and Extinction of Birds and Mammals V 2.1 Introduction, Results and Discussion 7 2.2 Methods '., 13 2.3 Literature Cited 27 Chapter Three Ice sheets promote speciation in boreal birds 30 3.1 Introduction 30 3.2 Materials and Methods 31 3.3 Results 35 3.4 Discussion 37 3.5 Literature Cited 44 Chapter Four Divergent timing and patterns of species accumulation in lowland and highland Neotropical birds 48 4.1 Introduction 48 4.2 Methods 52 4.3 Results 65 4.4 Discussion 70 4.5 Literature Cited 81 Chapter Five Splendid Isolation: The Great American Biotic Interchange in Birds . . 91 5.1 Results and Discussion 91 5.2 Methods 97 5.3 Literature Cited : 107 Chapter Six General Discussion 112 iii LIST OF TABLES Table 2.1 21 Table 2.2 22 Table 4.1 76 Table 5.1 103 Table 5 .2 . . . . 104 iv LIST OF FIGURES Figure 2.1 24 Figure 2.2 25 Figure 2.3 26 Figure 3.1 41 Figure 3.2 42 Figure 3.3 43 Figure 4.1 78 Figure 4.2 79 Figure 4.3 80 Figure 4.4 80 Figure 5.1 105 Figure 5.2 106 Figure 5.3 .• 107 v LIST OF APPENICES Appendix 1 Additional sequencing methods 116 Appendix 2 Divergence dates of superspecies 119 Appendix 3 Genbank accession numbers for Chapter Three 122 Appendix 4 Simulated distributions of sister species ages 132 Appendix 5 Neotropical ancestor state reconstructions of altitude 133 Appendix 6 Mean intraspecific sequence divergence in Neotropical birds 140 Appendix 7 Individual localities for genetic samples in Chapter Five 143 Appendix 8 Bayesian phylogeny of nine-primaried oscines 169 Appendix 9 Taxonomic changes to nine-primaried oscines 172 Appendix 10 Great American Interchange phylogenies and reconstructions 174 vi A C K N O W L E D G E M E N T S Foremost, I would like to thank my supervisor and mentor, Dolph Schluter. Dolph, you provided a constant flow of guidance and intellectual stimulation. I doubt few supervisors take as much interest in their students as you do. Our weekly meetings were the most valuable part of my graduate experience. Besides keeping me on my toes, they provided a place to debate, develop ideas and on rare occasions get completely confused. Your endless revisions of manuscripts and expertise as an editor were invaluable. Your breadth of knowledge in many areas of biology always amazes me. You always knew where to direct me next. I hope I will be able to provide my own graduate students with even half as much knowledge as you imparted to me. A special thanks to committee members: Mike Whitlock, Sally Aitken, Eric Taylor and Trevor Price. All of you provided useful comments and suggestions throughout my graduate experience. Eric, you provided lab space and your guidance in lab methods was useful. Your light-hearted humor always added a smile. Sally and Eric, I enjoyed your conservation genetics course and hope my flood of continual questions was not too annoying. Mike, you are the only professor who has ever hit me with a snow-ball. Thanks for your mathematical expertise and useful comments. Trevor, as the only ornithologist on my committee I was continually harassing you with questions. You provided a lion's share of help. You took the time to read and edit multiple versions of each of my manuscripts. Debating, arguing and in some cases actually agreeing was always a delight on those rare opportunities when we interacted in person. I feel honored to join your lab as a post-doc. A special thanks to Elderege Bermingham for providing logistical support during field work in Panama. Additionally, Irby Lovette assisted in field collection and was a delight to work with. Oris Sangjur provided valuable assistance at every stage of field work, the success of which would not have been possible without her. Matt Miller taught me how to prepare museum skins and his contributions of genetic tissues from the Darien were invaluable. \ A host of undergraduates, graduates, post docs and professors provided useful assistance at various points. In particular, I would like to thank Katriina lives for her vii phylogenetic expertise, Anthony Waldron and Andrew MacColl for interesting discussions, Patrick Tamkee, Sean Rogers and Tim Vines for help in the lab, Jenny Boughman and Arianne Albert for encouragement and Sally Otto for editing Chapter 2 of this thesis. A special thanks to Luke Harmon who provided a suite of useful R code essential to my analysis of Chapter 5. Our interactions will be cherished. Darren Irwin, what a joy to work in your lab (a breath of fresh air to get away from fish people). You and your students (Andrew Rush, Alan Brelsford, David Toews) provided useful comments on several manuscripts. Kayla King, Ida Molavi and Momoko Price each spent a summer assisting me in sequencing DNA. A large number of museums provided tissue samples for genetic analysis: the Cowan Vertebrate Museum, Field Museum of Natural History, Louisiana State University Museum of Natural Science, Kansas University Natural History Museum, University of California Museum of Vertebrate Zoology, University of Washington Burke Museum, American Museum of Natural History, National Museum of Natural History, University of Alaska Museum of the North, Smithsonian Tropical Research Institute, University of Nevada Marjorie Barrick Museum of Natural History and Universidad Nacional Autonoma de Mexico Museo de Zoologia "Alfonso L. Herrera". Financial support was supplied by two Natural Sciences and Engineering Research Council doctoral fellowships and a Smithsonian Tropical Research Institute Short Term Fellowship to myself and grants from Natural Sciences and Engineering Research Council and Canada Foundation for Innovation to Dolph Schluter. Finally, a special thanks to my wife Laura Weir. In addition to your continual support and encouragement, you aided in DNA sequence editing, measuring museum bird skins, extracting liver samples from freezer birds and a host of other tasks when the pressure was on. I couldn't ask for a better companion. viii For Dr. Dolph Schluter whose contribution to evolutionary biology is greatly admired CO-AUTHORSHIP STATEMENT Chapters two and three were co-authored in published form with Dolph Schluter. Dr. Schluter and myself both contributed to the research design in these chapters. I performed all necessary field and genetic work. With the direction and input of Dr. Schluter, I also performed all analysis. Manuscripts were prepared by myself and edited by Dolph Schluter and a series of anonymous reviewers (Chapters two, three and four). Chapter 5 was co-authored with both Dolph Schluter and Elderege Bermingham. My contribution to this project was the same with Dr. Schluter assisting in research design and data analysis and Dr. Bermingham assisting by contributing a limited number of DNA sequences, a large number of genetic tissues and providing logistical support for field-work. I acknowledge the contributions of Dr. Schluter to chapters 2 and 3 and Dr Schluter and Dr. Bermingham in chapter 5 by using the plural tense ("we") throughout these chapters. x ^ CHAPTER ONE GENERAL INTRODUCTION Understanding why species diversity is unevenly distributed spatially is a major aim of biogeography and ecology. With a few exceptions (e.g. temperate South African flora), faunas and floras are more species rich at tropical latitudes (latitudinal diversity gradient; Hillebrand 2004) and in more productive regions (Willig et al. 2003). However, species diversity may vary spatially even within biomes at the same latitude. One of the most productive biomes, tropical rainforest, is generally most diverse in the New World. For example, species diversity of terrestrial birds is greater in the New World tropics than all other tropical regions (Newton 2003). Consequently, the latitudinal diversity gradient in birds is steepest in the New World. Factors promoting these patterns of special heterogeneity in species diversity are poorly understood and remain highly controversial (Mittelbach et al. 2007). Speculation regarding the processes that result in the buildup and maintenance of species diversity began in the nineteenth century when prominent figures such as Darwin and Wallace first described the pattern of higher tropical diversity. A review by Pianka (1966) presented six main explanations and the number of models has continued to increase with no general consensus (Mittelbach et al. 2007). These models are summarized here under four general headings. Ecological Hypotheses: This first category of hypotheses explain patterns of species diversity using purely ecological terms (Willig et al. 2003). Under these models, local environmental conditions (i.e. productivity, precipitation, available carbon etc) set upper limits on the number of individuals and presumably species that can co-exist in space and time. Species diversity increases until it reaches the upper limit or "carrying capacity" supported by the environment. Once at carrying capacity species diversity remains fixed provided carrying capacity remains stable. A new species can be added to the local fauna through speciation or immigration only following a local extinction event. 1 Most effort aimed at exploring species diversity gradients has been devoted to ecological correlates of diversity. Time Hypotheses: This second category of hypothesis explain species diversity as a product of time. Those geographic regions or biomes that are the oldest have had the greatest amount of time to accumulate new species and will exhibit the highest species diversity. Fossil records do support the occurrence of temperate and tropical biomes at least since the Paleocene and it is difficult to determine from the fossil record if tropical biomes are older than temperate ones. However, global cooling trends occurred over large portions of the Cenozoic, resulting in a steady retraction of tropical biomes to low latitudes and expansion of temperate and arctic ones. Under the time hypothesis, the greater species diversity of tropical biomes is explained as a product of their older geological ages and the comparatively younger ages of temperate and arctic biomes at most latitudes (Fine and Ree 2006). Evidence supporting the time hypothesis come from phylogenetic and paleontological analysis of birds (Hawkins et al. 2006), frogs (Weins et al. 2006) and bivalves (Jablonski et al. 2006) which suggest that most high latitude clades in these groups were derived from tropical groups. Evolutionary Hypothesis: This category of hypothesis explain species diversity as a product of net diversification rates, the difference between speciation and extinction rates. Species diversity is predicted to be highest in those geographic regions that support the fastest net diversification rates (Fischer 1960). Several studies using both paleontological and phylogenetic data have supported higher net diversification rates in tropical versus temperate groups lending support to this category of hypothesis (summarized in Jablonkski et al. 2006). Net diversification rates are governed by factors that promote speciation or retard extinction. The contributions of speciation and extinction in driving higher net diversification rates in the tropics are poorly understood and have resulted in models that stress higher tropical speciation (the tropics as a "speciation pump" or "cradle of diversity") or lower tropical extinction (tropics as a "museum of diversity"; Stebbins 1974). Historical Hypothesis: This set of hypothesis try to explain patterns of species diversity using local historical biogeographic processes which are often unique to the region in question and thus do not provide a general mechanism to explain species 2 diversity. Examples include biogeographic events that promote faunal interchange potentially leading to increased diversity of involved faunas, uplift of mountain chains (Andean other tropical highland regions are hotbeds of speciation), and formation of biogeographic barriers to dispersal (mountain chains, rivers, marine incursions etc.) which may increase the geographic opportunity for speciation in allopatry. Traditionally, investigation of gradients in species diversity was confined to theoretical modeling, mapping ecological correlates of diversity and to paleontological investigation of diversification rates in a few well preserved marine fossil records. The recent advent of modern molecular based techniques has resulted in an explosion of phylogenetic information which allow many diversity gradient models to be directly tested for the first time. Molecular phylogenetic information provide two useful pieces of information, both of which I have used to test different aspects of diversity gradient models throughout this thesis. First, in the absence of a detailed terrestrial fossil record, phylogenetic information, with the application of a molecular clock, allows dating of key biogeographic events. Second, speciation and extinction rates can be estimated from phylogenetic information allowing for direct testing of Evolutionary Hypotheses of diversity gradients. Chapter two (Weir and Schluter 2007) investigates the role of speciation and extinction in promoting higher net diversification rates at tropical latitudes. A large dataset on the evolutionary ages of sister species of birds and mammals was used to estimate speciation and extinction rates across the New World latitudinal gradient. Speciation and extinction rates were both highest at high latitudes and declined towards the tropics. Though I am unable to determine which factors drove faster rates of diversification at high latitudes, it is probable that long-term patterns of climatic instability have played an important role. Chapters three (Weir and Schluter 2004) and four (Weir 2006) investigate the role of longterm climatic instability in promoting speciation across the latitudinal gradient. In chapter three, the role of Pleistocene climatic fluctuations in promoting diversification of temperate North American avifaunas was investigated. A large proportion of contemporary North American species was long believed to have diverged during recent glacial cycles of the Pleistocene ice ages. This view was challenged by molecular data 3 that suggested many species once believed to have diverged during the Pleistocene actually predate the ice age periods (Klicka and Zink 1997). However, this analysis focused primarily on low latitude faunas within North America while ice sheets had the greatest effect on high latitude faunas. In chapter three, the origin of a common pattern of endemism within the high latitude boreal coniferous forest biome is investigated. Similar Pleistocene ages and common patterns of branching shared across a series of codistributed boreal superspecies complexes give support for the role of fragmentation of Pleistocene ice sheets and confirms that those faunas distributed at high latitudes were heavily impacted by the climatic fluctuations, probably resulting in the faster speciation and extinction rates obtained for high latitude faunas in chapter two. Chapter four investigates the role of long-term climatic instability in promoting diversification rates in lowland and highland faunas of the Neotropical region. Molecular data was used to investigate diversification rates and evolutionary ages of species in highland versus lowland faunas. The comparison is useful because, like high latitude boreal faunas, highland regions of the Neotropics were directly glaciated while lowland regions were not. Finally, Chapter five investigates the role of the Great American Biotic Interchange in promoting faunal mixing and the possible buildup of avian species diversity at tropical latitudes of the New World. Prior to modern molecular techniques, the poorly sampled avian fossil record did not allow interchange events between the North and South America continents to be dated and the Great American Biotic Interchange in birds was poorly understood. Using molecular techniques I obtained dates for 100 interchange events. To obtain the necessary genetic tissues for this analysis, I spend a total of 14 weeks collecting more than 270 species from eastern and western provinces of the Republic of Panama, straddling the region where the last marine channel isolating North and South America occurred until ca. 3.5 Ma (Coates et al 1992). Dating of dispersal events in birds is compared to that for fossil mammals (Stehli and Webb 1985). To summarize, I use molecular dating and phylogenetic information to address the following questions: 4 i) Do speciation and extinction rates follow a latitudinal gradient and if so can they explain the higher species diversity of tropical latitudes? ii) What role did expanding and retracting ice sheets have on the diversification of North American temperate birds? iii) What role did glaciation and climatic cycles play in the diversification of high and low altitude Neotropical faunas? iv) Did formation of the Central American landbridge promote a sudden mixing of avian faunas as it did in mammals? While most research effort has focused on purely ecological models of species diversity, these questions largely investigate the role of evolution and biogeographic history in promoting patterns of spatial heterogeneity in species diversity. 1.1 Literature Cited Coates A.G., J. B. C. Jackson, L. S. Collins T. M . Cronin, H. J. Dowsett, L. M . Bybell, P. Jung, J: A. Obando. 1992. Closure of the Isthmus of Panama: the near shore marine record of Costa Rica and western Panama. Geol Soc Am Bull 104: 814-828. Fine, P. V. A. and R. H. Ree. 2006. Evidence for a time-integrated species-area effect on the latitudinal gradient in tree diversity. Am. Nat. 168, 796-804. Fischer, A.G. 1960. Latitudinal variations in organic diversity. Evolution, 14, 64-81. Hawkins, B.A., J.A.F. Diniz-Filho, C. A. Jaramillo and S. A. Soeller. 2006 Post-Eocene climate change, niche conservatism, and the latitudinal diversity gradient of new World birds. J. Biogeogr. 33, 770-780 Hillebrand, H. 2004. On the generality of the latitudinal diversity gradient. Am. Nat. 163, 192-211. Jablonski, D., K. Roy and J. W. Valentine. 2006. Out of the tropics: evolutionary dynamics of the latitudinal diversity gradient. Science. 314, 102-106. Klicka, J. and R. M . Zink. 1997. The importance of recent ice ages in speciation: a failed paradigm. Science 277, 1666-1669. Mittelbach, G. G., et al. 2007. Evolution and the latitudinal diversity gradient: speciation, extinction and biogeography. Ecology Letters. 10, 315-311. Newton, I. 2003. The Speciation and Biogeography of Birds. Academic Press, Amsterdam. Pianka, E. R. 1966. Latitudinal Gradients in Species Diversity: A Review of Concepts. American Naturalist. 100, 33-46. -5-Stebbins, G.L. 1974. Flowering Plants: Evolution above the Species Level. The Belknap Press of Harvard University Press, Cambridge, MA. Stehli, F. G. and S. D. Webb. 1985. The Great American Biotic Interchange. Phlenum Press, New Work. Weir, J. T. 2006. Divergent timing and patterns of species accumulation in lowland and highland Neotropical birds. Evolution 60: 842-855. Weir, J. T. and D. Schluter. 2004. Ice sheets promote bird speciation. Proceedings of the Royal Society of London Series B, Biological Sciences 271: 1881-1887. Weir, J. T. and D. Schluter. 2007. The latitudinal gradient in recent speciation and extinction rates of birds and mammals. Science 315: 1574-1576. Wiens, J. J., C. H. Graham, D. S. Moen, S. A. Smith,. And T. W. Reederm. 2006. Evolutionary and ecological causes of the latitudinal diversity gradient in hylid frogs: tree frogs unearth the roots of high tropical diversity. Am. Nat. 168, 579-596. Wiens, JJ . and Donoghue, M.J. (2004). Historical biogeography, ecology and species richness. Trends Ecol. Evol., 19, 639-644. Willig, M.R., Kaufman, D.M. and Stevens, R.D. 2003. Latitudinal gradients of biodiversity: pattern, process, scale, and synthesis. Ann. Rev. Ecol. Syst. 34, 273-309. 6 CHAPTER TWO T H E L A T I T U D I N A L G R A D I E N T IN R E C E N T S P E C I A T I O N A N D E X T I N C T I O N O F B I R D S A N D M A M M A L S 1 2.1 INTRODUCTION, RESULTS AND DISCUSSION Although the tropics harbor greater numbers of species than in temperate zones, it is not known whether the rates of speciation and extinction also follow a latitudinal gradient. By sampling birds and mammals we show that the distribution of the evolutionary ages of sister species, pairs of species in which each is the others' closest relative, follows a latitudinal gradient. The time to divergence for sister species is shorter at high latitudes and longer in the tropics. Birth-death models fitting these data estimate that the highest recent speciation and extinction rates occur at high latitudes and decline toward the tropics. These results conflict with the prevailing view that links high tropical diversity to elevated tropical speciation rates. Instead, our findings suggest that faster turnover at high latitudes contributes to the latitudinal diversity gradient. The tropics possess many more species than temperate regions, yet the underlying causes of this latitudinal gradient in species diversity are poorly understood (Pianka 1966, Gaston 2000, Hillebrand 2004). A number of authors have estimated net diversification rates (speciation minus extinction) across a latitudinal gradient and concluded that more 1 A version of this chapter has been published. Weir, J. T. and D. Schluter. 2007. The latitudinal gradient in recent speciation and extinction rates in birds and mammals. Science 315: 1928-1933. 7 species accumulate per unit time at tropical latitudes [birds (Cardillo 1999, Cardillo et al. 2005, Ricklefs 2005), primates (Bbhm and Mayhew 2005), marine bivalves (Crame 2002), foraminifera (Buzas et al. 2002), butterflies (Cardillo 1999)]. By examining the age distributions of the youngest species of birds and mammals, and how they change with latitude, we have examined the contributions of recent speciation and extinction to the latitudinal gradient in net diversification. We studied a large data set comprising the ages and midpoint latitudes of breeding range for 309 sister species pairs of New World birds and mammals. We defined sister species as the most closely related pair of extant species descended from an immediate common ancestor. Their ages were estimated from genetic distances of mitochondrial DNA from the cytochrome b gene. The rate of evolution in this gene is approximately constant with time within birds and mammals (Honeycutt et al. 1995, Weir 2006, Ho et al. 2005) and has been used widely to date phylogenetic events in these groups. The average of the absolute value of midpoint breeding latitude for a sister species pair was used to approximate the latitude at which speciation occurred. This approach is reasonable for sister species pairs having narrow latitudinal ranges, but greater uncertainty exists when latitudinal ranges are broad. Excluding all species pairs with a combined latitudinal range (defined by the northern and southern limits for the pair) of greater than 40 degrees did not affect the relationship between age and midpoint-latitude. Latitudinal ranges of species at high latitudes have shifted in response to glacial cycles. However, using the presumed latitudes of species ranges during past glacial maxima, when many temperate species were forced southwards, would only steepen the gradients estimated here. 8 Near the equator, the ages of sister species pairs spanned the last 10 million years, with a mean age of 3.4 Mya (million years ago) (Fig. 2.1 A). As distance from the equator increased, the upper limit and mean ages of sister species declined significantly (slope = -0.043 ±0.007 Mya/degrees latitude, ^-statistic = -6.5, P < 0.0001, intercept = 3.37, df = 307). At the highest latitudes all of the sister species diverged less than 1.0 Mya. This pattern of declining age with latitude is opposite to that expected if faster rates of speciation drove the buildup of Neotropical diversity because sister species ages should be youngest where speciation rates are highest. The differences in species ages between low and high latitudes is partly the result of a longer lag-time in tropical faunas between population splitting, as measured by genetic markers, and species designation (Fig. 2. IB and C). The evidence for this lies in the coincident latitudinal gradient in the ages of the oldest haplotype splits within 154 currently defined species of birds and mammals (Fig 2.IB) and in the oldest phylogroup splits within 130 species (Fig. 2.1C). Following Avise (Avise and Walker 198, Avise et al. 1998), a phylogroup is defined as a reciprocally monophyletic geographic subdivision within a species. By examining sets of closely linked alleles (haplotypes) we were able to use maximum haplotype divergence as well as the age of the deepest phylogroup splits to compare the lag-time to species formation, because species at high latitudes are so young that most lack phylogroups. Both haplotype and phylogroup splits are older in the tropics than in temperate zones, on average, implying that the process of speciation takes longer at low latitudes. This may be in part an artifact of the greater taxonomic uncertainty at lower latitudes because a higher proportion of tropical species are currently undescribed and thus considered together in our analysis. Nevertheless, taxonomic uncertainty is 9 unlikely to be the sole cause of the gradient. This is because the latitudinal gradient in sister species ages is present even within the Nearctic fauna of North America, which is well defined taxonomically north of approximately 30°N (slope = - 0.041 ± 0.017, t = -2.44, P = 0.017, intercept = 3.3, df = 99). Reproductive isolation, marking the completion of the speciation process, usually takes time to evolve after population splitting, and our data suggests that this process might take a longer period of time at lower latitudes, though we are uncertain why this is the case. There are differences in the age distributions of sister species across the latitudinal gradient apart from the lag-time difference. Therefore, it may be possible to extract information about speciation (rate of cladogenesis) and extinction rates from the distribution of sister species ages after correcting for the lag-time, because speciation and extinction can be inferred by the shape of the age distributions of sister species. In phylogenetic simulations using a pure birth model, in which speciation rates are constant through time and no extinction occurs (Yule 1924), sister species ages approximate an exponential distribution with the mean of the distribution proportional to the speciation rate; adding a lag-time shifts the mode in the distribution towards the mean lag-time. Extinction changes the shape of these distributions, by increasing the breadth of the tails (seeSOM). We used maximum likelihood to fit a birth-death (see 1.2 Materials and Methods) model in which speciation (X) and extinction (u) rates changed linearly across the latitudinal gradient as follows: X - b\L + cx Equation 2.1 (x = byJL + c^ Equation 2.2 10 where L is the absolute value of latitude, b is the slope and c is the rate at 0° latitude. The model estimated the slopes (b^ b^) and intercepts (c\, cM) for the linear relationships between X, u. and L (Fig. 2.2) by fitting data points at each latitude to simulated probability distributions of sister species ages corresponding to different values of speciation and extinction in a reconstructed birth-death process. We generated probability i distributions of sister species ages by simulating a large number of phylogenetic trees under a birth-death process and recording the resulting distribution of sister species ages for a range of parameter values. Simulated trees were corrected for the lag-time to species recognition assuming that lag- times had an exponential distribution with mean equal either to the average age of the oldest known haplotype splits, or to the average age of phylogroup splits within species at that latitude. The maximum likelihood model estimated significantly positive slopes for the relationship between X (support interval, 0.0076 to 0.0117), | i (support interval, 0.0046 to 0.0135), and latitude for the combined dataset of bird and mammal sister species (Fig. 2.2). Results were similar when maximum haplotype or oldest phylogroup splits were used to correct for lag-times and only the correction with haplotypes is reported here. Estimated speciation and extinction rates were lowest at the equator and increased significantly towards the poles (Fig. 2.2). The same trends were obtained when excluding sister species pairs with combined latitudinal ranges greater than 40° and when bird and mammal datasets were fit separately, but results were not significant in the mammal dataset. These results hold true even when correcting for the latitudinal gradient in lag-time to speciation. We expect that better knowledge of species level taxonomy in the tropics will revise the lag-time and sister species age gradients. This revision should have 11 minimal impact on the estimates of speciation and extinction since they are adjusted for lag-time. These results are surprising. because the latitudinal gradient in estimated speciation rate is opposite to the gradient in net rate of diversification estimated by many studies to be highest in tropical taxa (Cardillo 1999, Cardillo et al. 2005, Ricklefs 2005, Bbhm and Mayhew 2005, Crame 2002, Buzas et al. 2002). For our data on sister species, the gradient in net diversification is not significantly different from zero (b\ = b^). Still, the range of estimates for the net diversification gradient supported by this study are consistent with estimates obtained elsewhere for birds (Cardillo et al. 2005). If the gradient is real, as other studies encompassing longer time periods indicate (Cardillo 1999, Cardillo et al. 2005, Ricklefs 2005, Bohm and Mayhew 2005, Crame 2002, Buzas et al. 2002), our findings would support the classic views of Wallace (1878), Fisher (1960) and others (Weir 2006, Stebbins 1974, Hawkins et al. 2006) that reduced extinction risks at tropical latitudes promoted the gradual buildup of high species diversity there. These quantitative estimates are based on the assumption that speciation and extinction can be approximated by a continuous birth-death process as one moves up or down in latitude. Yet, we know that there have been fluctuations in the opportunities for speciation and extinction over the past few million years (Weir 2006, Weir and Schluter 2007). For example, extensive climatic fluctuations that occurred at high latitudes during the late Pliocene and Pleistocene (2.5 Mya to recent) may have concentrated speciation and extinction events in time resulting in episodic species turnover. In contrast, the bursts of diversification in tropical faunas may predate the late Pliocene and Pleistocene, and the 12 patterns observed today may be the result of a subsequent decline in diversification either because the geological processes that promoted diversification (e.g. formation of Isthmus of Panama, marine incursions, orogeny, river formation) have slowed or because diversification rates declined as the number of tropical species approached a "carrying capacity" (Ricklefs 2005, Weir 2006). Given such variability, our estimates are best regarded as averages over the periods studied. Despite these uncertainties, our results suggest that elevated speciation and extinction rates in the temperate zone can drive high turnover of species while rates of species turnover at tropical latitudes are reduced. A recent study of fossil marine bivalves also showed higher per capita rates of genus extinction at high latitudes, suggesting higher species extinction rates as well (Jablonski et al. 2006; estimates of per capita speciation rates are still lacking). Together, these results suggest that extinction rates are greatest where species diversity is lowest. While most efforts have aimed at identifying the geological, climatic and ecological factors that might have elevated tropical speciation rates, our results suggest that both speciation and extinction vary with latitude and contributed importantly to the latitudinal diversity gradient. 2.2 MATERIALS AND METHODS (a) Data New World sister species pairs were chosen from complete or nearly complete published molecular phylogenies for terrestrial bird and mammal taxa. In addition, a few sister species pairs were obtained from phylogenies we generated from Genbank sequences. Occasionally, a species may not be monophyletic and may contain a daughter 13 species nestled within it. In such cases, we used the age at which the daughter split from its parent species. Sister species pairs in which one or both species were endemic to oceanic islands were excluded, with the exception of continental shelf islands that were connected to the continent during Pleistocene periods of low sea level. At arctic latitudes, some pairs of sister species are circumpolar in distribution and were included as long as both members reside in the New World. Marine mammal and marine and aquatic bird families were excluded. In this paper the speciation process is defined as beginning at population splitting and is completed when reproductive isolation evolves. Following Avise et al. (14, 15), we used the maximum age of mitochondrial haplotypes within New World species to provide a lower bound estimate of the duration of the speciation process (lag-time to speciation). Avise et al. primarily used species that were geographically segregated into monophyletic groups of mitochondrial haplotypes termed phylogroups. Using only species possessing phylogroups however may overestimate the duration of the speciation process because it represents a non-random sample of species. At tropical latitudes a large proportion of species analyzed in this study possessed phylogroups. However, at high latitudes, many species are very young and have not had time to form phylogroups. At high latitudes the mean ages of phylogroups in our dataset was older than the mean age of sister species and thus do not accurately estimate the duration of the speciation process. To provide better estimates, we measured maximum haplotype divergence within widespread species possessing multiple morphologically differentiated subspecies that may or may not have diagnosed phylogroups but nevertheless do possess haplotype variation. When phylogroups were lacking, we used the maximum sequence divergence (GTR-gamma 14 distance) between haplotypes and a molecular clock to obtain estimates of the dates when extant haplotypes first began to diverge. We present both phylogroup (Fig. 2,1c) and haplotype (including both species with and without phylogroups; Fig. 2.1b) datasets across the latitudinal gradient. Estimates of haplotype variation within species were generated primarily from molecular datasets associated with published phylogeographic studies. We sequenced additional sisterspecies and phylogroups (Table 2.1). Approximate dates of splitting were estimated for sister species and intraspecific haplotype splits from GTR-gamma distances obtained from the mitochondrial cytochrome b DNA sequences. A few very young pairs of sister species were not reciprocally monophyletic for cytochrome b haplotypes because haplotypes have not had enough time to become reciprocally monophyletic following population splitting. In such cases, we used the average divergence between species as a rough approximation of their ages. However, we did not estimate maximum haplotype ages for species that were not monophyletic. Sequences were obtained from Genbank or were sequenced (Table 2.1) using standard protocols (Weir and Schluter 2004) with primers O-H16065 (5'-AGTCTTC A ATCTTTGGCTTAC A AGAC-3') and 0-L14851 (5'-CCTACCTAGGATCATTCGCCCT-3'), which we developed specifically for oscine passerines, or S-L14987 (5'- CCATCAAACATYTCAGCYTGATG -3') for suboscine passerines and non-passerines. PAUP 4.0bl0 (Swofford 2002) was used to generate GTR-gamma distances. Model parameters were estimated separately by PAUP (Swofford 2002) for the bird and mammal dataset using maximum likelihood. Though some rate variation occurs, an average molecular clock of 2.0% sequence divergence per million years (1% per lineage) 15 holds true across a large sample of avian orders (Weir 2006, Fleischer et al. 1998, Klicka and Zink 1997, Garcia-Moreno 2004) (calibrated in Weir 2006 for cytochrome b using GTR-gamma distances). We used this clock for all avian dates. We.remeasured the rate of evolution using GTR-gamma distances for 21 published mammalian clocks representing seven of the eight mammalian orders included in this study (Table 2.2). These rates varied between 2% and 4% for all orders tested except Rodentia and Lagomorpha, for which calibrated rates ranged as high as 8%. We used the average calibrated rate for each order to convert GTR-gamma distances into time estimates. Because no calibration was available for the order Erinaceomorpha, we used the rate obtained for the closely related order Soricomorpha to date the single sister species pair of Erinaceomorphid included in this study. It should be noted that sequences may begin to diverge before the actual splitting events if ancestral populations possessed sequence polymorphisms at the time of splitting. However, the discrepancy between coalescerit times estimated from cytochrome b sequences and splitting times average only 2 to 3 hundred thousand years for temperate and tropical bird taxa (Weir 2006, Edwards and Beerli 2004), and as such we treat coalescent dates as close approximations to the actual dates of splitting. Midpoint latitude for each sister species pair was calculated as follows: midpoint latitude = (|A| + |B|)/2 Equation 3 where A and B are midpoint latitudes for each member of the sister species pair and | | indicates absolute value. Likewise, midpoint latitudes were obtained for each species in the lag-time dataset. Latitudinal ranges were obtained from digitized range maps for all New World birds and mammals (Ridgely et al. 2005). Latitudinal limits are well known 16 for most New World birds. Greater uncertainty exists for some mammal groups. Additional information on range limits may alter midpoint latitudes, but should not affect our results greatly. (b) Estimation To estimate speciation and extinction rates, probability distributions of the ages of sister species were generated from simulations of phylogenetic trees under a stochastic birth-death process in which speciation and extinction rates are constant through time (Kendall 1948, Nee and May 1994). At any point in time in a birth death process, the waiting time to the next speciation event (t\) follows an exponential distribution with mean equal to the inverse of the speciation rate (A) multiplied by the total number of lineages extant in the tree. Likewise, the waiting time to the next extinction event (tM) follows an exponential distribution with mean equal to the inverse of the extinction rate (w) multiplied by the total number of lineages extant in the tree. Phylogenetic trees were simulated in R (code submitted as package PhySim 1.0 (Weir and Schluter 2007)) for 10 time units (f) to represent 10 million years. Starting with a single lineage at t = 0, the next event in the tree can be either a speciation or extinction event. Waiting times to the next speciation and extinction event were drawn randomly from distributions of waiting times as described above. If the waiting time to speciation was shorter than to extinction a speciation event (bifurcation) was added to a randomly chosen lineage in the tree at time = t + tx. If the waiting time to extinction was shortest, then an extinction event was added to a randomly chosen lineages at time = t + tM. This process was repeated until either t = 10 or the entire lineage went extinct leaving no 17 descendents at the present. In order to produce distributions of sister species ages for a given speciation and extinction rate, between 1000 and 15000 such simulations were performed. Probability distributions were simulated for 18 different values of birth (X; 0.05, 0.1 0.15, 0.2...0.9) where units are the number of new lineages per lineage per million years. For birth rates less than 0.5, 12 death rates (p.) were simulated (OA, Q.iX, 0.2A, ...0.8/1, 0.9A, 0.95/1, 0.991). For.birth rates greater than 0.5, the same death rates were used as long as X-/J. < 0.5. This restriction was necessary because phylogenetic trees became very large and computationally expensive when the net diversification rates exceeded 0.5. The lag-time to speciation was modeled as having an exponential probability distribution with rate inversely proportional to the average lag-time. We used an exponential distribution because distributions of lag-times were highly skewed with most lag-times young in age. Beginning at the root of a simulated tree and moving to the tips, each node was classified as either a "species level" or "intraspecific split". This was done by a drawing a lag-time from the corresponding exponential distribution. If the node age was greater than the lag-time it was classified as a species level node and was retained. Otherwise, the node was classified as an "intraspecific split" and all descendants were pruned from the tree. The resulting pruned trees contained only "species level" nodes. Sister species ages were then extracted from these trees to generate probability distributions of sister species ages. Maximum haplotype divergence within bird and mammal species suggests that the average lag-time ranges between close to 0 (at high latitudes) and 2 million years 18 (near the equator). Thus, for each set of trees simulated under different combinations of birth and death rates, 21 different probability distributions of sister species were extracted, each with a different mean lag-time (0, 0.1, 0.2...1.9, 2.0). In total; 3927 simulated sister species distributions were obtained. For each set of simulated sister species distributions, the probability density function was obtained using the locfit package in R (Locfit 2005). The probability, of drawing a sister species with age t from a simulated sister species age distribution equals the probability density at time t in the simulated distribution. For a given set of values for bx, bM, cx, and c^, the appropriate simulated distribution for a sister species with latitude L was determined by solving for X and fx in Equations 1 and 2. For each value of bx, bM, cx, and cM, the likelihood was obtained by multiplying the probabilities of each sister species. The values of bx, b^, cx, and cM with the highest likelihood are the maximum likelihood estimates. The likelihood support intervals (equivalent to the 95% confidence interval) includes all parameter combinations within 2 log likelihood units of the maximum likelihood estimate. Bird and mammal sister species datasets had similar distributions across the latitudinal gradient and a linear regression resulted in almost identical slopes and y-intercepts (Fig. 2.1a). Due to their similarity, these datasets were pooled when estimating diversification rates. However, lag-time datasets (Fig. 2.1b and c) were not pooled because the relationship between latitude and age of intraspecific splits was less steep in mammals than in birds. As such, separate corrections for the waiting time to species recognition were applied to bird and mammal sister species. 19 These diversification rate estimates obtained from many independent data points (i.e. sister species) account for the fact that many lineages alive 10 million years ago went extinct leaving no descendents at the present. As a result, we are able to estimate fauna-wide extinction rates despite the fact that we posses information only for extant species. , (c) Phylogenetic Signature in Sister Species Distributions The shape of sister species age distributions contains the phylogenetic signature of speciation and extinction. In a pure birth model (no extinction), simulated distributions of sister species ages appear exponentially distributed (Fig. 2.3a). The means of these distributions are inversely proportional to the speciation rate. At low speciation rates, age distributions have relatively large means, and the tails are spread over broad time intervals. In contrast, when speciation rates are high, the mean of the distributions are low and the tails are narrow. As extinction rate increases, sister species age distributions depart more strongly from an exponential distribution (Fig. 2.3b) with more species dating ins the tails and heads and fewer near the mean. This results in every combination of birth and death rates producing a distribution with a unique mean and shape, where the phylogenetic signals of the speciation and extinction rates are contained in the mean and shape of the distribution respectively. Applying a lag time correction to sister species age distributions simulated under a pure birth model creates a mode in the distribution near the mean lag time (Fig 2.1c). 20 Table 2.1 Cytochrome b sequences submitted to Genbank. Museums: Field Museum of Natural Flistory (FM), Cowan Vertebrate Museum (CO), Smithsonian Tropical Research Institute (Naos tissue collection; STRI), Louisiana Museum of Natural History (LMN). Species Location Museum Tissue No. Accession No. Campylorliamphus pusillus PANAMA, Bocas del Toro, Continental Divide SI'RI IWO'U JF202815 Corvus caurinus CANADA, British Columbia, Vancouver CO none " EF2T0778 1 Dendrocolaptes sahctitliomae PANAMA, Bocas del Toro, Cerro Chalite SIK1 TW251 ' • •• " '!R12895' :"'--H Dendrocolaptes sanctithomae PANAMA? Bocas del Toro, Cerro Chalite M k l ULu7v EF212896 F Heterospingus riibrifrons PANAMA, Bocas del Toro, Cerro Chalite S'IRI 7 - " " T W 2 7 8 ~ ^ " 1F202820 ' ' 1 Manacus vitellinus PANAMA, Panama Province, Achiote Road STRI TA-MVI-PC16 EF202819 ~ f Pseudocolaptes lawrehcii. COSTA RICA, San-Jo^- '• IAIN II'WU iF202814 j Tityra semifasciata PANAMA, Bocas del Toro, Cerro Chalite STRI JTW298 EF212894 Trogon viridis PANAMA, Panama Province, confluence of Rio Charges and Rio Chagrecito STRp •A-'l"\ i:i)^4 5F202818 "! 21 Table 2.2 Molecular clock calibrations for Mammalian orders. ORDER (Family) Calibration Taxon Date of Split GTR-gamma distance Rate (%) Calibration Reference ARTIOD ACTYLA Bovidae split Myotragus balearicus and Ovis 5.4 0.1757 3.28 Lalueza-Fox et al 2005 CARNIVORA Canidae earliest split within Vulpes 9.5 0.1921 2.02 Wayne et al 1997 split Canis and Lycaon 6.7 0.1716 2.56 Wayne et al 1997 split Canis latrans / C. lupus and C. simensis 3.5 0.0823 2.35 Wayne et al 1997 CHIROPTERA Vespertilionidae split Myotis nattereri and M. schaubi 6 0.2209 3.68 Stadelma nn et al in press split Myotis daubentonii from M. bechsteinii 5 0.1929 3.86 Stadelma nn et al in press DIDELPHIMORPHIA Didelphidae split Micoureus and Marmosa murina / M. lepida 14.1 0.2884 2.05 Steiner et al 2005 split Didelphis and Philander 5.9 0.1758 2.98 Steiner et al 2005 LAGOMORPHA Ochotonidae first split within extant species of Ochotona 5.5 0.2769 5.04 Yu et al 2000 PRIMATE Hominidae split Homo and Pan 5.4 0.1490 2.76 RONDENTIA Geomyidae split Perognathus / Chaetodipus and Dipodomys / 16.5 0.5800 3.52 Riddle Microdipodops , et al 22 split Geomys and Cratogeomys/Pappogeomys 6 0.3447 5.75 split Pappogeomys and Cratogeomys split Thomomyini and Geomyini 0.2546 6.36 5.6 0.4399 7.93 2000 DeWalt et al 1993 DeWalt et al 1993 DeWalt et al 1993 Muridae split Batomys and all other Murine genera 12 0.3492 2.91 split Microtus califomicus and M. mexicanus 2.1 0.1532 7.30 Steppan and Adkin s2004 Conroy and Cook 2000 Sciuridae SORICOMORPHA Soricidae split Marmota and sister clade of Spermophilus / 7.7 Cynomys 0.2038 2.65 split Cynomys and sister clade of Spermophilus 2.7 0.1504 5.57 First split within Spermophilus, Marmota and 16.5 Cynomys split Cryptotis and Blarina split Crocidurinae and Soricinae 0.2680 1.62 0.2354 2.62 20 0.5125 2.56 Harrison et al 2003 Harrison et al 2003 Harrison et al 2003 Brant and orti 2002 Fumagall i et al 1999 23 o o o o o °o % 9? 10 20 30 40 50 60 7.0 0 Midpoint latitude (N or S) o o o o ° o o ° < f e " V ^ S - - - * ^ . - i T 1 r 1 r— 10 20 30 40 50 60 70 Figure 2.1 Relationship between time since splitting and average absolute midpoint latitude for sister taxa of New World birds and mammals. A) Ages of 309 sister species pairs of New World birds (red; n = 191) and mammals (blue; n = 118). Linear regression lines as follows: birds (slope = -0.040, t = -4.368, p <0.0001, intercept = 3.38 Ma), mammals (slope = -0.042, t = -4.26.900, p < 0.0001, intercept = 3.26 Ma). B) Ages of 154 maximum coalescent dates for intraspecific haplotype variation within bird (n = 81) and mammal (n = 73) species. Linear regression lines as follows: birds (slope = -0.028, t 24 = - 4.58, p <0.0001, intercept = 2.03 Ma), mammals (slope = -0.019, t = -3.62, p < 0.0006, intercept =1.91 Ma). C) 130 phylogroup splits for birds (n = 68) and mammals (n = 62). Linear regression lines as follows: birds (slope = -0.018, t = -2.00, p = 0.049, intercept = 1.98 Ma), mammals (slope = -0.016, t = -2.67, p < 0.01, intercept = 1.91 Ma). 20 40 Midpoint latitude (N or S) Figure 2.2 Estimates of speciation (light gray) and extinction (dark gray) rates across latitude (L) for New World birds and mammals. All rate estimates within 1 log likelihood unit of the maximum likelihood estimate are shown. Region of overlap shown in charcoal. 25 Age (Ma) Fig. 2.3 Simulated probability distributions of sister species ages under different rates of speciation and extinction. A) Speciation rate equals 0.4 (red) and 0.1 (blue) lineages / lineage / million years, no extinction and no correction for lag time to speciation. B ) the effect of adding extinction. Speciation rate equals 0.4 and death rate equals 0 (red) and 0.38 (blue). C) speciation and extinction rates (rates same as in b) with a mean lag time of 2.0 Ma. 26 2.3 L I T E R A T U R E CITED Avise, J. C , and D. Walker. 1998. Pleistocene phylogeographic effects on avian populations and the speciation process. Proceedings of the Royal Society of London Series B-Biological Sciences 265:457-463. Avise, J. C , D. Walker, and G. C. Johns. 1998. Speciation durations and Pleistocene effects on vertebrate phylogeography. 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R package version 1.0. http://CRAN.R-project.org/ Weir, J. T., and D. Schluter. 2004. Ice sheets promote speciation in boreal birds. Proceedings of the Royal Society of London Series B-Biological Sciences 271:1881-1887. Yu N. , C. Zheng, Y. P. Zhang, and W. H. Li , 2000 Molecular systematics of Pikas (Genus Ochotona) inferred from mitochondrial DNA sequences Mol. Phylogenet. Evol 16: 85-89. Yule, G. U. 1924. A mathematical theory of evolution based on the conclusions of Dr. J. C. Willis. F. R. S. Phil. Trans. R. Soc. Lond. B 213:21-87. 29 CHAPTER 3 ICE SHEETS PROMOTED SPECIATION IN BOREAL BIRDS2 3.1 I N T R O D U C T I O N The role of recent ice ages in vertebrate speciation is controversial (Zink and Slowinski 1995; Klicka and Zink 1997, 1999; Arbogast and Slowinski 1998; Avise and Walker 1998; Avise et al. 1998; Zink et al. 2004). Traditionally, Late Pleistocene glacial advances and their associated trends of global cooling were believed to have promoted speciation by fragmenting the geographical distributions of vertebrate faunas at both temperate and tropical latitudes (Mengel 1964; Haffer 1969; Hubbard 1974; Diamond and Hamilton 1980). Molecular investigations of temperate species have revealed numerous examples of phylogeographical structure concordant with segregation and subsequent genetic divergence in fragmented habitats during Pleistocene glacial cycles (Taberlet et al. 1998). Surprisingly few of these examples resulted in speciation (Drovetski 2003). Instead, the most recent speciation events in both temperate and tropical faunas, those involving present-day sister species, are now believed to have been initiated mostly before the Pleistocene, as indicated by their large values of sequence divergence (Klicka and Zink 1997; Avise and Walker 1998; Moritz et al. 2000). Although it remains true that speciation events initiated before the Pleistocene may have been completed during Pleistocene glacial events (Avise and Walker 1998; Avise et al. 1998), currently there is little evidence that many present-day species both diverged and speciated within Pleistocene glacial periods as originally held. Recent studies have also failed to find support for increased rates of species proliferation during the Pleistocene (Zink and Slowinski 1995; Zink et al. 2004). Using a series of North American sister taxa, Zink et al. (2004) found that rates of lineage 2 A version of this chapter has been published. Weir, J. T., and D. Schluter. 2004. Ice sheets promote speciation in boreal birds. Proc. R. Soc. Lond. B Biol . Sci. 271:1881-1887. 30 accumulation through time best fit a model of constant diversification rather than indicating a recent burst of speciation during the Pleistocene. These previous molecular investigations of ice-age speciation have studied faunas distributed largely to the south of the regions covered by the expanding and retracting ice sheets (Klicka and Zink 1997; Avise et al. 1998; Moritz et al. 2000). The geographical distributions of such faunas may have been fragmented periodically by habitat changes accompanying global cooling but not directly by advancing glaciers. The boreal forest of North America is a geographically, extensive habitat zone that was directly fragmented by advancing glaciers into multiple refugia. To determine whether speciation was more prevalent near the advancing and retreating ice sheets we examined sequence divergence between members of avian superspecies complexes restricted to. the boreal forest of North America. We compared these divergence events to those of North American superspecies not confined to, and distributed in habitats largely south of, the boreal forest and to those of Neotropical lowland superspecies. A superspecies is a monophyletic group of two or more allospecies (geographically allopatric species) or semispecies (species connected geographically by a narrow hybrid zone) that have just crossed the species threshold and are presumed to be the youngest species in an avifauna (Amadon 1966; Sibley and Monroe 1990). The ages at which superspecies members in an avifauna diverged give an approximation of the time frames needed for speciation to occur. If Pleistocene ice ages both initiated and completed the process of speciation in a fauna, then a high proportion of species belonging to superspecies in the fauna should date to glacial periods. Because the boreal forest was directly fragmented by expanding ice sheets whereas habitats farther south were not, we expect to find a higher proportion of superspecies dating to the Pleistocene in the boreal regions than in the sub-boreal and Neotropical lowland regions. 3.2 M E T H O D S (a) Avifaunas compared 31 We compared the relative dates of origin for members of superspecies complexes in three avifaunas: the boreal forest avifauna, the sub-boreal avifauna and the Neotropical lowland avifauna. The boreal avifauna here includes species restricted to boreal coniferous forests characterized by spruce (Picea), fir (Abies) Douglas-fir (Pseudotsuga), hemlock (Tsuga), cedar (Thuja plicata) or, more rarely, pine (Pinus), or to brushy habitat along the edges of these forests. The boreal coniferous forest biome stretches in a broad belt from Newfoundland to Alaska and south along the Pacific coast to California and along the Rocky Mountains into the mid-western USA and is present very locally at high elevations in northern Mexico. The sub-boreal avifauna includes species distributed in temperate habitats south of the boreal forest, including widespread species that extend their ranges up into the boreal zone but are not restricted to it. The Neotropical avifauna includes species distributed in lowland habitats of tropical America from southern Mexico south to southern Brazil and Bolivia. Island endemics and oceanic and aquatic species were not included in any of the avifaunal comparisons. We compared nine out of 10 boreal superspecies with a random sample of 20 sub-boreal and 21 Neotropical superspecies. The boreal superspecies sampled are composed of 24 species, which represent a sizeable sample of the taxa restricted to the boreal zone. The only boreal superspecies that was not included was the alpine-inhabiting rosy-finch complex (Leucosticte tephrocotis), for which tissues were not available for genetic analysis. In addition, the boreal sparrows Zonotrichia atricapilla and Z. albicollis are believed to form a superspecies. Because mitochondrial DNA phylogenies do not support a sister-species relationship between these species, we excluded them from the analysis. Several boreal and Neotropical lowland superspecies complexes contained a species distributed completely outside of their respective zones. Because we wished to compare only speciation events that occurred within each avifauna, we eliminated these taxa from our analysis. Molecular phylogenetic studies have indicated that a number of traditionally held superspecies are not monophyletic and these have.been excluded from this study. Such 'superspecies' do not represent taxonomic entities and their inclusion in this analysis would have the effect of creating artificially old dates. To be certain that superspecies were monophyletic, we included only superspecies from genera for which complete or 32 nearly complete species-level phylogenies were available, or sister species whose relationship to each other is undisputed (i.e. they have been considered conspecific). Superspecies boundaries were taken from Sibley and Monroe (1990) and the checklist of North American birds (American Ornithologists Union 1998) with several exceptions where recent phylogenetic studies challenged the boundaries of traditionally held superspecies. We consider Piranga bidentata and P. ludoviciana to represent a superspecies rather than P. olivacea and P. ludoviciana. We also treated the Passerella iliaca complex as a superspecies because it contains four genetically and morphologically distinct taxa that, although traditionally classified as a single species, have evolved a degree of reproductive isolation and are on the threshold of becoming distinct biological species (Zink 1994; Zink and Weckstein 2003). Excluding Pa. iliaca did not significantly alter our results. (b) Sequencing and phylogenetic analysis Cytochrome b was sequenced using standard protocols or obtained from GenBank and the literature for all superspecies and outgroups analysed (Appendix 1). Sequences from multiple individuals representing separate subspecies or geographical regions were included where available. To increase phylogenetic accuracy in the Pa. iliaca superspecies we added sequences of the mitochondrial ND2 (NADH dehydrogenase subunit 2) gene to the 450 bp sequences of cytochrome b. Both gene regions were evolving at similar rates. We performed all phylogenetic analyses in PAUP v. 4.0bl0 (Swofford 2002). The general time reversible (GTR) model of sequence evolution (Kimura 1980) with among-site rate variation following a discrete gamma distribution (Yang 1993) was used in all maximum likelihood analyses because this model provides a more realistic estimation of branch length and genetic distance, which are often underestimated by simpler models even for very recently diverged taxa (Arbogast et al. 2002). Parameters of the GTR-gamma model were estimated for the combined boreal, sub-boreal and Neotropical dataset of 115 species (-In likelihood - 23 146:72; a = 0:34). GTR-gamma distances between species were generated using these parameters and were dated using molecular clocks. 33 The passerine molecular clock has been previously calibrated for Hawaiian honeycreepers (Drepanidinae) using gamma corrected Kimura 2-parameter distances generated from 675 bp of cytochrome b (Fleischer et al. 1998). We used similar methods and the same dataset to calibrate this clock using GTR-gamma distances. Parameters for the GTR-gamma model of sequence evolution were estimated from a parsimony tree (-In likelihood = 2651:58; a = 0:16). A corrected divergence of 0.0352 was generated for the species pair Hemignathus flavus and H. virens wilsonia inhabiting Oahu and Maui, respectively. The latter species is believed to have colonized the island of Maui shortly after it formed 1.6 Myr ago (Fleischer et al. 1998). A minimum calibration of 2.2% Myr-1 (0.011 substitutions per site, per myr) is derived by dividing the gamma-GTR divergence by the age of Maui. An identical rate was obtained for the species pair H. virens wilsonia and H. v. virens; the latter is thought to have colonized Hawaii from Maui shortly after its formation 0.43 Myr ago. Our calibration of the passerine molecular clock is slightly older than the traditional molecular clock of 2.0% / Myr (see note 11 in Klicka and Zink (1997)). Most attempts to calibrate the molecular clock have used simple models of sequence evolution, which underestimate the true number of substitutions separating species pairs (Arbogast et al. 2002). The GTR-gamma model that we used corrects for homoplasy in sequences and provides a better estimate of pairwise divergence. We applied this passerine clock of 2.2% / Myr throughout this study. However, although many mitochondrial-clock calibrations for diverse groups of land birds seem consistent with a rate of ca. 2% / Myr (Klicka and Zink 1997), a global molecular clock consistent across avian orders may not exist. Excluding non-passerine taxa from our analysis did not significantly alter our results. Maximum likelihood was used to generate clock-like phylogenies with the GTR-gamma model of sequence evolution for each boreal superspecies complex (Fig. 3.1). Each complex was rooted with one or more closely related outgroups (Appendix 1). Likelihood ratio tests (Huelsenbeck and Rannala 1997) failed to reject the molecular clock in all boreal analyses. Owing to the presence of ancestral polymorphism in DNA sequences, the time at which a population splits into two (population divergence) often postdates the 34 coalescence times of DNA markers, resulting in species being younger than they appear. Coalescence theory predicts that if daughter populations have each maintained the same mean effective population size as the ancestral population that gave rise to them then the levels of polymorphism within each daughter population can be used as an estimate of ancestral polymorphism. Using this approach, a mean correction factor of 0.18 Myr for birds was derived by calculating the mean intraspecific variation within present-day species (Moore 1995; Edwards and Beerli 2000). Although a large variance was associated with this value, it suggests that, on average, coalescence dates are only a few hundred thousand years older than the time at which population divergence occurs. While this correction cannot be used to adjust individual coalescence dates it provides a yardstick whereby mean divergence times for an avifauna can be approximated. Throughout this paper we report uncorrected dates. 3.3 R E S U L T S Coalescence times for all members of boreal forest superspecies fall completely within the Pleistocene (Fig. 3.1), suggesting that habitat fragmentation associated with recent ice ages played a major role in initiating speciation. A pattern of endemism is shared by eight out of the nine boreal superspecies (the Catharus minimus superspecies did not conform to this pattern). These eight superspecies each have two or three differentiated species presently restricted to the Eastern Taiga, Pacific Coast and Rocky Mountain regions of the boreal zone. Phylogenetic analysis of these superspecies revealed similar branching orders in cladograms (Fig. 3.1). The taxa inhabiting the Rocky Mountain and Pacific Coast endemism regions tend to be most closely related, and the taxa endemic to the Taiga tend to be basal..Dates of divergence in each of these complexes are similar, assuming that the molecular rate of evolution is approximately the same in all lineages. The regularity of the timing and order of splitting events in so many clades points to a common basis in range fragmentation as the initial cause of speciation events. 35 To explore the potential role of glaciation in forming this pattern of endemism, a consensus cladogram was generated by creating a clock-like maximum-likelihood tree with molecular sequences from each superspecies complex combined (excluding the C. minimus superspecies, which does not display this pattern of endemism). This was achieved by combining a single DNA sequence from each species within an endemism region into a composite sequence. If a representative of a superspecies was not present in an endemism region then a series of n's of appropriate length was inserted to represent the missing sequence. Composite sequences were generated for each of the Tiaga, Pacific Coast and Rocky Mountain endemism regions with representatives of each superspecies added in the same order. Character weights were assigned to each base pair such that sequences from each species contributed equally to the cladogram. This was necessary because sequence length varied between 711 and 1463 bp between different species. A consensus cladogram of 100 bootstrap replicates was generated with the gamma-GTR model. If a single vicariant history affected each superspecies complex in a similar fashion then a high bootstrap support in the combined analysis would be generated. This method is similar to creating an area cladogram (Page 1988), except it assigns the actual sequence data to geographical areas and thus provides branch-length information, which can be used to date divergence events. The resulting consensus cladogram was robust with 100% bootstrap support for the initial segregation of the boreal forest avifauna into eastern and western fragments and later divergence of the western fragment into Pacific Coast and Rocky Mountain refugia (Fig. 3.2). Randomly choosing a second set of sequences from each species did not alter the results. Dates of branching events on the consensus cladogram suggest that the earlier coalescence event in these complexes occurred on average 1.20 Myr ago and the later 0.61 Myr ago These approximate dates are based on the rate of 2.2% / myr calibrated for Hawaiian honeycreepers. Applying the traditional molecular clock of 2.0% Myr"1 does not change these results greatly. These coalescence times are expected to be slightly older than actual population splitting times. Coalescence times for boreal birds have a very different distribution from those for birds from North American sub-boreal and Neotropical lowland regions (Appendix 2). In contrast to boreal superspecies members, which coalesce exclusively during the 36 Pleistocene, superspecies from sub-boreal and Neotropical avifaunas speciated throughout the Pleistocene and Pliocene, with mean coalescence dates of 1.75 Myr ago -and 1.89 Myr ago, respectively. 3.4 DISCUSSION Estimated dates of splitting in the boreal avifauna correspond to important events of the Pleistocene ice age. The intensities and durations of Pleistocene glacial advances are recorded in the oxygen isotope record preserved in deep-sea foraminiferan deposits (Fig. 3.2; Barendregt and Irving 1998). A high oxygen 8 1 8 to 8 1 6 ratio in these deposits * 18 indicates environmental cooling. During the early Pleistocene, weak peaks in the 8 palaeotemperature record indicate that glacial advances were initially mild and short in duration. During this period, major ice sheets were initially confined to the Pacific northwest, high arctic and Atlantic northeast and did not unite to form a single ice mass until the second half of the Pleistocene'(Barendregt and Irving 1998). Consequently, it is likely that prolonged fragmentation of the boreal zone into eastern and western sectors occurred sometime during the Early to Mid-Pleistocene (1.8-0.8 Myr ago) when the intensities of glacial advances began steadily to increase (Fig. 3.2). This period corresponds with the earliest splits observed in most boreal superspecies. As indicated by the 8 1 8 palaeotemperature record, a series of major glacial advances southward began 0.7 Myr ago and continued to the Recent. These major glacial advances probably pushed the eastern and western boreal forest fragments farther south and divided the western forest fragment into Pacific Coast and Rocky Mountain fragments (Fig. 3.2). This corresponds to the later split in the lineages of most boreal superspecies. Although there is uncertainty in rates of molecular evolution and in phylogenetic trees, we suggest that this pattern of habitat fragmentation is responsible for the similarity in the branching patterns and timings of splits in boreal birds. These splits persist in the molecular record even though there were multiple retreats and advances of the ice sheets over the subsequent 0.7 Myr, suggesting limited opportunity for excessive gene flow after the first major advance. Whether boreal 37 populations reconnected as they expanded their ranges during the brief interglacials is not known, but it is probable, suggesting that speciation occurred in spite of repeated periods >of secondary contact. It is unlikely that reproductive isolation evolved to completion during single glacial advances, because most sister-species pairs in the western sector of the boreal zone that currently come into contact still hybridize occasionally, even after 0.7 Myr. Though it is not known when reproductive isolation was achieved, the most recent glacial advances of the Late Pleistocene may have been instrumental in completing the speciation process for many boreal species. Did Pleistocene ice ages promote speciation exclusively in high-latitude faunas fragmented by ice? Coalescence dates for many members of superspecies distributed in subboreal North America and in the Neotropics also fall within the Pleistocene (Fig 3.3), suggesting that fragmentation resulting from global cooling associated with glaciation may have promoted speciation in these avifaunas as well. However, in contrast to 100% of boreal superspecies, only 56% of sub-boreal and 46% of tropical superspecies coalesced during the Pleistocene. The remainder of the coalescence events in superspecies of these avifaunas date to the Pliocene and Miocene. Therefore, the key difference between boreal and other avifaunas is not that Pleistocene speciation was rare elsewhere but that such a high proportion of superspecies members in the boreal zone date to the Pleistocene rather than earlier. The absence of boreal superspecies members that predate the Pleistocene is surprising given that the boreal biome existed in North America throughout the Miocene and Pliocene (Brunsfeld et al. 2001). Diversification did occur in the boreal zone prior to the Pleistocene. For example, the closest sister taxa to boreal superspecies (J. T. Weir, unpublished data) and the radiation of Dendroica warblers (Lovette and Bermingham 1999) date primarily to the Pliocene and early Miocene. However, in contrast to many sub-boreal and tropical species, these pre-Pleistocene boreal species have evolved beyond the status of superspecies. Three explanations for this pattern are as follows. First, the older dates associated with tropical superspecies may be an artefact of current uncertainty regarding species boundaries in the tropics. However, the superspecies in the sub-boreal North American avifauna were also older on average than those in the boreal avifauna, and taxonomic treatment of species between these two avifaunas is comparable. 38 Therefore we suggest that a taxonomic artifact does not fully account for the pattern, even though it may play a role. Second, the frequency of hybridization and complete mitochondrial introgression across species boundaries may be higher in the boreal zone than in other avifaunas. This would have the effect of making the members of boreal superspecies appear artificially younger. Evidence of extensive introgression has been found in two species of boreal bird (Rohwer et al. 2001; Weckstein et al. 2001). Although it cannot be ruled out, we do not regard this explanation as the most likely one because introgression has also been observed in sub-boreal taxa (Gill 1997; Lovette and Bermingham 2001). Third, the divergence of boreal superspecies members may be confined to the Pleistocene because the rate of evolution may have been faster in the boreal avifauna. This faster rate of evolution would result in boreal species leaving the taxonomic category of superspecies much sooner than species in sub-boreal and tropical avifaunas. Species leave the taxonomic category of superspecies when they become sufficiently differentiated ecologically that they become sympatric, or when they achieve sufficient distinctness in morphology and ecology (Amadon 1966; Sibley and Monroe 1990). The rate at which ecological differentiation evolves could have been accelerated in the Pleistocene. glaciations, perhaps because of stronger divergent selection resulting from greater ecological opportunities in depauperate boreal habitats. By contrast, fewer ecological opportunities in the more species-rich sub-boreal and tropical habitats could have led to weaker divergent selection pressures and longer waiting times in the superspecies state. We feel that this is the most likely explanation for our findings, although further tests are needed. The data also suggest, but do not confirm, that a greater proportion of lineages entering the Pleistocene produced new species in the boreal zone than elsewhere. In other words, Pleistocene speciation rates were highest in the boreal avifauna as confirmed in Chapter Two. A high fraction of all passerine songbirds restricted to the boreal forest belt have been shown by this study to trace their origin to the Pleistocene (at least 24 out of 82 species). This fraction is almost certainly lower in avifaunas further south. These results support the view that Pleistocene climatic changes were a major factor in the initiation and completion of speciation of New World birds, but suggest that 39 they had the greatest impact on the boreal avifauna. Apparently, the effect of the ice ages in promoting diversification was strongest near the edges of the advancing glaciers. The contrast between boreal birds and more southern avifaunas suggests that direct fragmentation by ice was more important in promoting diversification than the global climatic changes accompanying the advances. North American fishes show a similar trend: clades occupying formerly glaciated areas date to recent Pleistocene glacial periods (Bernatchez and Wilson 1998; Taylor and McPhail 1999), while clades distributed south of the glaciated regions are older and most often predate the Pleistocene altogether (Near et al. 2003). Furthermore, there is an indication that the fragmentation of the boreal forest affected mammals in a similar fashion. Many boreal species of mammal have genetically differentiated populations in the eastern and western sections of the boreal forest (Wooding and Ward 1997; Arbogast and Kenagy 2001; Demboski and Cook 2001; Stone et al. 2002), the origins of which appear to correspond with the first glacial vicariant event in birds, but, unlike birds, few of these populations are known to be reproductively isolated. Studies of this variation in the reproductive isolation exhibited by avian and mammalian faunas should yield a greater understanding of the mechanisms of speciation following fragmentation. 40 branch length (o) Sphyrapicus Dendroica Vermivora Passerella Vireo Empidonax Oporornis Poecile (A l Cat ha JUS 1 i estimated age (Myr) 0 S. nuchalis O & ruber 9 S. varius ^ D. townsendi O occidentalis 9 D. virens ^ virginiae O ' ; W ridgwayi 9 If (>J mficapilla © rt.y unalaschensis (jj) P. (i'J megarhyncha Q P. schistacea • P. fi.> (fiocn 9 V. plumbeus O cassinii 9 V solitarius 9 £. occidentalis 0. lolmiei 0. Philadelphia O ^ rufescens 9 P. hudsonica C. bicknelli C. minimus r i Fig. 3.1 Cladograms derived from clock-like maximum-likelihood trees of superspecies complexes inhabiting the boreal forest zone, (a) Superspecies that contain two or more endemic taxa in the Taiga (magenta), Rocky Mountain (cyan) and Pacific Coast (yellow) regions of endemism. (b) The Catharus minimus superspecies displays a different geographical pattern of distribution. Standard errors are given for the dates of each node. 41 2 1 0 estimated time (Myr ago) 18 Fig. 3.2 Consensus cladogram of boreal superspecies complexes, the Pleistocene 8 oxygen palaeotemperature record (redrawn from Barendregt and Irving 1998) and approximate distributions of boreal forest fragments during the last glacial maxima (Williams 2003; Lindbladh et al. 2003). Bootstrap support for the cladogram is indicated above the node, and standard errors are given for the dates of each node. All boreal forest superspecies were used to create the consensus cladogram except for the Catharus minimus superspecies, which displays a different biogeographical pattern. Peaks in the palaeotemperature record indicate cold periods of glacial advance, with seven major maxima occurring in the last 0.7 Myr. 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Bermingham and C. Wood. 2001. Plumage and mitochondrial DNA haplotype variation across a moving hybrid zone. Evolution 55, 405^122. Sibley, C. G. and B. L. Monroe. 1990. Distribution and taxonomy of birds of the world. New Haven, CT: Yale University Press. Stone, K. D., W. Flynn, and J. A. Cook. 2002. Post-glacial colonization of northwestern North America by the forestassociated American marten (Martes americana, Mammalia Carnivora: Mustelidae). Mol. Ecol. 11, 2049-2063. Swofford, D. L. 2002. PAUP* 4.0bl0: phylogenetic analysis using parsimony (*and other methods). Sunderland, MA: Sinauer. Taberlet, P., L. Fumagalli, A. Wust-Saucy, and J. Cosson. 1998. Comparative phylogeography and postglacial colonization routes in Europe. Mol. Ecol. 7, 453-464. Taylor, E. B. and J. D. McPhail. 1999. Evolutionary history of an adaptive radiation in species pairs of threespine sticklebacks (Gasterosteus aculeatus): insights from mitochondrial DNA. Biol. J. Linn. Soc. 66, 271-291. Weckstein, J. D., R..M. Zink, R. C. Blackwell-Rago, and D. A. Nelson. 2001. Anomalous variation in mitochondrial genomes of white-crowned (Zonotrichia leucophrys) and golden-crowned (Z. atricapilla) sparrows: pseudogenes, hybridization, or incomplete lineage sorting? Auk 118, 231-236. Williams, J. W. 2003. Variations in tree cover in North America since the last glacial maximum. Global Planet. Change 35, 1-23. Wooding, S. and R. Ward. 1997. Phylogeography and Pleistocene evolution in the North American black bear. Mol. Biol. Evol. 14, 1096-1105. 46 Yang, Z. H. 1993. Maximum likelihood estimation of phylogeny from DNA sequences when substitution rates differ over sites. Mol. Biol. Evol. 10, 1396-1401. Zink, R. M . 1994. The geography of mitochondrial DNA variation, population structure, hybridization, and species limits in the fox sparrow (Passerella iliaca). Evolution 48,96-111. Zink, R. M . and J . B. Slowinski. 1995. Evidence from molecular systematics for decreased avian diversification in the Pleistocene epoch. Proc. Natl Acad. Sci. USA 92, 5832-5835. Zink, R. M . and J . D. Weckstein. 2003. Recent evolutionary history of the fox sparrows (genus: Passerella). Auk 120, 522-527. Zink, R. M. , J. Klicka, and B. R. Barber. 2004. The tempo of avian diversification during the Quaternary. Phil. Trans. R. Soc. Lond. B 359, 215-220. 47 CHAPTER 4 DIVERGENT PATTERNS OF SPECIES ACCUMULATION IN HIGHLAND AND LOWLAND NEOTROPICAL BIRDS3 4.1 I N T R O D U C T I O N Understanding the historical processes driving the diversification of contemporary faunas is a major aim of biogeography, yet the timing and rate of diversification in some of the most species rich faunas are poorly understood. Species diversity is highest in the Neotropics (Rosenzweig 1995). For example, approximately three thousand species of birds occur there (Haffer 1990), more than all other tropical regions combined. This pattern is repeated in many other groups. A number of theories have been proposed to explain the origin of this diversity (see review in Haffer 1997). These theories differ in their view of what processes promoted speciation and of the age of species in Neotropical faunas, but no consensus has been reached. Originally, Neotropical forests and climates were believed to have been stable through most of their Cenozoic history (Richards 1952; Fisher 1960; Schwabe 1969). This stability was thought to have promoted low extinction rates and allowed for the gradual buildup of high species diversity (Darlington 1957; Sanders 1969; Schwabe 1969). Under this view, species in Neotropical faunas were thought to be relatively old. This theory was challenged when it became apparent that intense climatic fluctuations 3 A version of this chapter has been published. Weir, J. T. 2006. Divergent timing and patterns of species accumulation in lowland and highland Neotropical birds. Evolution 60, 842-855. 48 during the Northern Hemisphere ice ages also affected climate in the Neotropics. The temperate latitude model of glacial refugia (Rand 1948; Mengel 1964) was applied to explain Neotropical diversification. The resulting refuge hypothesis and its variant forms (e.g. river refuge hypothesis) predicted that the majority of current Neotropical species diversified during recent episodes of climatic fluctuation when Neotropical habitats were believed to have been repeatedly fragmented (Haffer 1969, 1974, 1997; Vanzolini and Williams 1970; Brown et al. 1974; Prance 1978; Simpson and Haffer 1978; Cerqueira 1982; Whitmore and Prance 1987; Capparella 1991; Ayres and Cluttonbrock 1992; Haffer and Prance 2001). Though the refuge hypothesis has been invoked most often to explain diversification in lowland wet-forest habitats, climatic fluctuations may have also fragmented other Neotropical habitats in both lowland (Meave et al. 1991; Meave and Kellman 1994) and highland faunas (Steyermark and Dunsterville 1980). Climatic fluctuations have occurred throughout the history of the Neotropics and may have contributed to diversification at any period (Haffer 1997; Haffer and Prance 2001). However, the glacial cycles of the late Pliocene and Pleistocene produced the most intense fluctuations. Beginning about 2.5 million years ago (mya; Bloemendal and Demenocal 1989; Hooghiemstra 1989; Andriessen et al. 1993; van der Hammen and Hooghiemstra 1997; Ravelo et al. 2004; mya; Liu and Herbert 2004), these fluctuations persisted through the late Pliocene (2.5 to 2.0 mya) and early Pleistocene (2.0 to 1.0 mya) and culminated in a series of severe glacial cycles during the late Pleistocene (~ 1.0 mya to recent; Bennett 1990; Hooghiemstra et al. 1993). The intensity of these late Pleistocene glacial cycles led most proponents of the refuge hypothesis to predict that the majority of Neotropical species dated to this time. Recently some proponents have 49 extended this prediction to earlier time periods (Haffer 1997; Haffer and Prance 2001). Nevertheless, if climate fluctuations drove Neotropical diversification then we would expect the rate of speciation to increase during time periods when the duration and intensity of fluctuations were greatest. Speciation rates should increase at the onset of glacial cycles 2.5 mya and again at the onset of the late Pleistocene 1.0 mya. Several other theories have endeavored to link Neotropical diversification to specific geological events that mostly predate the climatic cycles of the late Pliocene and Pleistocene. In the lowlands, events such as uplift of montane barriers in north-western South America (Sick 1967), formation of the Amazon drainage system (Sick 1967; Capparela 1988; Hoorn et al. 1995; Aleixo 2004; Rossetti et al. 2005), marine incursions (Hoorn 1993, 1994; Irion et al. 1995; Webb 1995; Rasanen et al. 1995; Nores 1999; Gregory-Wodzicki 2000; Nores 2004), or fresh water lake barriers (Vonhof et al. 2003; Rossetti et al. 2005) occurred primarily during the late Miocene (10 to 5 mya) and early Pliocene (5 to 2.5 mya) and are thought to have promoted diversification. The effect of the these geological events may have been temporary (e.g. marine incursions) resulting in a burst of diversification at the time of the event or their effect may persist to the present (e.g. mountain and river barriers; see Bates et al. 2004) resulting in ongoing opportunities for speciation. Due to the overlap in the predictions of the timing of diversification, it is difficult to investigate the potential role played by any one geological event. In the highlands, rapid uplift of the Andes and other highland regions occurred during the last 10 million years (Hooghiemstra and van der Hammen 1998). For instance, 60 to 80 percent of the current height of the central and northern Andes resulted from uplift during this time period (Gregory-Wodzicki 2000) and the Talamanca highlands of 50 Central America formed within the last 5 million years (Grafe et al. 2002). This dynamic history of uplift may have provided ongoing opportunities for diversification of highland species to the present. Fjeldsa and Lovett (Fjeldsa and Lovett 1997a, 1997b) proposed that highland regions were the main source of diversification for the Neotropics and that highland species dispersed to lowland faunas where they were preserved from extinction . Only those hypothesis that stress climatic fluctuations as driving diversification predict that Neotropical faunas should be recently derived with an increase in diversification rates near the recent. With the advent of molecular dating techniques it is now possible to test these predictions. Several molecular based reviews of Neotropical speciation in birds are available but are incomplete and have not addressed patterns in rates of diversification through time. The review by Moritz et al. (2000) suggested that Pleistocene speciation was rare in Neotropical birds and other vertebrates, with the majority of species dating to the Pliocene and Miocene. However, their conclusions were based on only a few genera, and further sampling may find greater support for diversification near the recent. In contrast, a review of speciation in Andean birds suggested a protracted history of diversification from the Miocene to the present with substantial numbers of species dating to the late Pliocene and Pleistocene (Garcia-Moreno and Fjeldsa 2000). The larger sampling design in the Andean study suggests that further sampling of lowland avian genera may provide a more complete picture of Neotropical diversification. I compared the timing and rate of diversification in lowland and highland avian radiations of the Neotropics. To make this comparison, patterns of species accumulation were analyzed from mitochondrial DNA phylogenies for 16 lowland and 11 highland 51 radiations. Patterns in the rate of diversification through time were used to determine peak periods of diversification for the faunas in each region and to test for increasing, decreasing or constant diversification rates through time. The separation of Neotropical taxa into lowland and highland faunas is useful because both regions experienced different geological histories. In addition, climatic fluctuations were more intense in highland regions where extensive glaciation directly fragmented high elevation habitats. In contrast, lowland faunas did not experience direct fragmentation by glaciers but habitats may have been fragmented due to fluctuations in temperature and rainfall that accompanied them (Hooghiemstra and van der Hammen 1998; Bush and Silman 2004). If recent climatic fluctuations drove Neotropical diversification, then the majority of species should date to the late Pliocene and Pleistocene. Additionally, speciation rates should increase through this period and peak during the last one million years when climatic fluctuations were most intense. In contrast, if events that predate the climatic fluctuations were instrumental in Neotropical diversification then we would not expect an increase in diversification during recent periods of climatic instability and a large proportion of species should date to the Miocene and early Pliocene. 4.2 METHODS (a) Phylogenetic Analysis The Neotropical zoogeographic region extends from central Mexico to the southern tip of South America. In this analysis I excluded the Caribbean and other 52 Neotropical islands'because I was interested in analyzing rates of diversification within continental faunas. I included all terrestrial taxa possessing five or more species in highland or lowland regions for which mitochondrial DNA sequences were available for at least 75% of species (Table 4.1). In some cases recent molecular phylogenetic studies have demonstrated that two or more genera together formed a monophyletic group but individually were paraphyletic. These were analyzed as a single taxon (Troglodytes and Thryorchilus; Crax and Northocrax; Psarocolius, Cacicus and Ocyalus; Geositta and Geobates). In addition, a monophyletic assemblage of South American blackbirds (Macroagelaius, Gymnomystax, Hypopyrrhus, Lampropsar, Gnorimopsar, Curaeus, Amblyamphus, Chrysomus, Xanthopsar, Pseudoleistes, Orepsar and Agelaioides) and Neotropical swallows (Progne, Phaeoprogne, Notiochelidon, Atticora, Neocelidon and Stelgidopteryx) were also included and each was analyzed as a single taxon because many of their respective genera were paraphyletic or they did not have enough species to allow for separate analysis. Wide taxonomic and ecological coverage are included in the sample of Neotropical taxa used in this analysis. In addition, taxon size ranged from taxa with only 5 species to one of the largest Neotropical genera, Tangara, with 49 species distributed in both highland and lowland regions. Nevertheless, this sample is constrained to currently available phylogenies that may not represent a completely random sample of Neotropical taxa. Phylogenetic analyses have mostly been confined to regions amenable to genetic sampling. Species restricted to countries such as Colombia and Venezuela are poorly represented in the phylogenies included. I do not expect these potential biases to greatly affect the patterns of diversification uncovered, in this study. Nevertheless, further 53 sampling undoubtedly will provide a more complete understanding of Neotropical diversification. For each taxon, phylogenetic trees were generated and calibrated so that branch lengths were proportional to time as follows. Protein coding mitochondrial DNA sequences were obtained from Genbank or were sequenced for this project (Appendix 3). Phylogenetic analyses were performed with multiple outgroups in MrBayes version 3.0b4 (Huelsenbeck and Ronquist 2001) under the GTR-y model of evolution. Al l Bayesian analysis were run for two million generations and were sampled every 200 generations. The first 500,000 generations were excluded as the burn-in period and trees sampled from the remaining 1.5 million generations were used to construct majority-rule consensus cladograms. Parameters of the GTR- y model were then estimated from the Bayesian consensus trees using maximum likelihood in PAUP* v. 4.0M0 (Swofford 2002). These parameter estimates were used to obtain maximum likelihood estimates of branch lengths along the Bayesian consensus topologies. The only exception was that for Tangara I used a published Bayesian topology (Fig 2 in Burns and Naoki 2004) and then calculated branch lengths along it using maximum likelihood. Penalized likelihood methods, implemented in r8s (Sanderson 2003), were then used to create ultrametric trees that allow for local rate variation in the molecular clock. The cross validation routine implemented in r8s was used to estimate the appropriate value of the smoothing parameter for each tree. Branch lengths generated using penalized likelihood are proportional to time, but require calibration. The timing of the basal most split within each taxon was used as a calibration point. The timing of this split was estimated with 54 maximum likelihood in PAUP* by determining branch lengths under the assumption of a global clock and applying a molecular clock calibration to date this split. Uncertainty if the rate of molecular evolution is constant through time and across taxonomic groups needs to be accounted for when dating splitting events. Calibrations obtained for several orders of birds suggest an avian molecular clock of approximately 2% per million years for protein-coding mitochondrial DNA (see note 11 in Klicka and Zink 1997). Nevertheless, the validity of this rate has been challenged due to inconsistent phylogenetic methods used to arrive at this calibration (Lovette 2004a). Moreover, this rate may not be valid for splitting events near the recent (Garcia-Moreno 2004; Penny 2005; Ho et al. 2005). To address these issues, I recalibrated published avian calibrations using GTR-gamma distances. I obtained additional calibrations using fossil material and island ages (Weir unpublished data). A total of 47 avian calibrations from 19 families were obtained for the mitochondrial cytochrome b gene. Some calibrations obtained for splitting events less than 0.5 mya were much higher than the 2% rate. However, calibrations obtained for splitting events between 0.5 and 20 mya closely clustered around a rate of 2.0%. I used this rate throughout this study. The resulting calibrated, clock-like trees provide useful sources of information for analyzing both the timing and rate of diversification within each geographic region. Nodes in such phylogenies provide estimates of the dates when species diverged (population splitting). Node ages actually measure the coalescence times of DNA haplotypes which may predate population subdivision. The discrepancy results due to the presence of polymorphism within populations at the time of splitting. Assuming that ancestral levels of polymorphism are similar to current levels, then the mean divergence 55 within current populations can be used to correct splitting dates. This is done by subtracting the mean intraspecific divergence from coalescent dates (Nei and Li 1979; Avise et al. 1998). I estimated the average intraspecific GTR-gamma divergence between individuals of a species (Appendix 6). If species possessed genetic subdivisions then I estimated average divergence between individuals at the phylogroup level following Avise et al. (1998). These estimates were derived from available population level phylogenetic datasets for Neotropical birds and often come from different taxa then those analyzed here. Nevertheless, these corrections are assumed to be reflective of the Neotropical avifauna as a whole. Throughout this study, coalescence dates are reported and are used as a maximum estimate of the age at which population divergence occurred. Estimates of mean intraspecific divergences are then used to explore the magnitude of. the discrepancy between node ages and splitting ages. (b) Ancestor State Reconstructions I analyzed the timing and rate of diversification in the Neotropics for lowland and highland faunas separately. The division between the lowlands and highlands was drawn at 1000m, the approximate upper limit of the tropical lowland habitats, and the lower limit of subtropical montane habitats. Neotropical species whose elevational distributions were predominantly above or below 1000m were assigned to highland and lowland faunas respectively. However, in Patagonia, alpine habitats typical of the high Andes further north descend to sea level. The few species included in this dataset that occur there were considered to belong to the highland avifauna. 56 Ancestor state reconstruction was used to classify interior nodes to their appropriate faunas. Species in each tree were classified as highland, lowland, Caribbean, North American or other. Ancestor state reconstructions either assigned nodes to one of these faunas or designated them as dispersal events from one fauna to another. Dispersal events between faunas occur at nodes in which each of the sister lineages occur in different faunas (Fig. 4.1a). A splitting event within a fauna occurs at nodes in which each of the daughter lineages occur within the fauna. Mesquite (Maddison and Maddison 2003) was used to obtain the most parsimonious ancestor state reconstruction for each phylogenetic tree (see Apprndix 5). For several taxa (Amazona, Icterus, Tangara), multiple most parsimonious reconstructions were obtained. In such cases a maximum likelihood method of ancestor state reconstruction was used to differentiate between the competing alternatives. For maximum likelihood reconstructions of geographic origin, a punctuation model is most appropriate because it places character change at the time of splitting (at the node) rather than along branches. This model was implemented by constraining all inter-node branches to have equal length (Pagel 1994). Node reconstructions with the highest likelihood were chosen. These methods of reconstructing ancestral states assume that the most parsimonious or the most likely reconstruction is the correct one. This assumption is probably valid for phylogenetic trees with few transitions between states (most taxa in this study). More uncertainty exists when frequent transitions occur (e.g. Tangara). In addition, I assume that transitions occur at nodes. However, extinction eliminates nodes and may result in transitions being pushed back to earlier nodes in a tree. 57 ( (c) Rates of Diversification Within Taxa To investigate the timing and rate of diversification within taxa, I constructed plots of the log number of lineages (species) through time (Lineages Through Time or LTT plots; Fig 4.1c) for each taxon. Under a null hypothesis of a constant speciation rate with no extinction (pure birth model), the number of lineages increases exponentially through time (Yule 1924; Nee 2004) and forms a straight line on an LTT plot with slope equal to the speciation rate. I used a method similar to that of Pybus and Harvey (2000) to test the overall fit of a LTT plot to the pure birth expectation of a constant slope. The y-statistic they develop compares the relative position of node ages in a phylogenetic tree to that expected under the pure birth model. For a phylogeny with n taxa, let gi be the distance between the root of the tree and the first node, let g2, g3,...gn-i be the internode distances and gn be the distance between the most recent node and the present (Fig 4.1b). The statistic I use here is identical to that developed by Pybus and Harvey except that it excludes gn. This last interval should be excluded from real phylogenies because unlike the simulated phylogenetic trees used by Pybus and Harvey there is no splitting event at the present and thus the interval gn is not drawn from the same distribution as other internode distances (i.e. the next splitting event may occur in the future or it may have already occurred but is not taxonomically recognized as a species). The statistic follows f 1 n-m-l E E*** - T r = v i=m \k=m J J V Z / Equation 4.1 58 where S is the sum of the branch lengths in the phylogeny (excluding the interval gn) and m is the number of initial lineages. Under the pure birth expectation of exponential growth, y approaches a standard normal distribution with mean equal to 0. Departures from the pure birth model can be detected by a y-value that is either too large or too small. Values of y > 0 indicate that internode distances are shorter than expected towards the recent, which is also reflected in an upturn in the LTT plot (Fig. 4.1c). Simulations of phylogenetic trees demonstrate that this can result if the rate of speciation increased through time (Appendix 4). Values of y < 0 indicate, that internode distances are longer than expected towards the recent, which is reflected in a downturn in the LTT plot (Fig. 4.1c). This can result if the rate of speciation has declined through time (Appendix 4). Values of y greater than 1.96 or less than -1.96 are significantly different at the 5% level from the pure birth expectation. Extinction may also result in departure from the pure birth model. Simulations using a variety of extinction rates demonstrate that constant or increasing rates of extinction usually increased and more rarely decreased y values slightly, but not significantly (Appendix 4). Significantly positive and negative values of y were only obtained in simulations where speciation rate increased or decreased respectively. Some of the taxa included in this study possessed one or more clades distributed outside of the geographic region of interest (Fig. 4.1a gray arrows). These were simply pruned so that all resulting nodes represented diversification events within the region of interest. However, a small proportion of taxa (4 of 26) exhibited a more complex biogeographic history in which a clade distributed outside of a region back-colonized into the region (Fig. 4.1a, black arrow). Lineages resulting from such back-colonization 59 events usually possessed at least one node that represented splitting within the region of interest and were included in the LTT analysis. The node at which the back-colonization occurred represents the addition of a new lineage to the fauna following immigration. This node was included in the analysis even though it does not represent splitting within the fauna. Exclusion of this node resulted in similar LTT plots and values of y. Missing taxa may result in biased diversification patterns. As many as 23% of species were missing from phylogenetic trees (Table 4.1). Missing taxa may result in artificial downturns in LTT plots. The effect of missing taxa can be corrected for in the y statistic using Monte Carlo simulation (Pybus and Harvey 2000). The following method assumes that missing taxa are randomly distributed on the tree. Ten thousand pure birth trees with n tips were simulated in Phyl-O-Gen (Rambaut 2002) and k tips were randomly pruned from each, where n is the number of species in-a taxon and k is the number of species sampled. The y statistic was calculated for each simulated tree. Average values of y in simulated pure birth trees equal 0. When tips are deleted in simulated trees, average values are less than 0. The difference is proportional to the expected discrepancy in actual calculated y values. Calculated values of y were corrected by subtracting the mean value in simulated trees. The resulting corrected values were only marginally greater than calculated values suggesting that missing taxa did not have a large effect. The distribution of values in the simulated datasets were used to determine the level of significance. LTT plots use splitting times from phylogenetic reconstructions of species level taxa. However, there is a lag time between lineage splitting and the time when lineages are recognized as separate species. As a result, older lineages are more likely to be recognized as distinct species today than younger lineages. It follows that there are likely 60 to be recent lineage splitting events in the tree that are not recorded because the resulting taxa are not recognized as distinct species (phylogroups hereafter). Some of these phylogroups will evolve to become species in the future and these particular lineages really should be included in LTT plots and the y-statistic. Failure to include such splits may also result in an artificial downturn in LTT plots towards the present. Most phylogroups are likely to be recent in age and do not confound the LTT analysis because they date to the time interval gn which is excluded from LTT plots and the y statistic. Nevertheless, some of these splits may predate gn<. This is especially true when the interval gn> is short. Because detailed intraspecific sampling was lacking for most of the species in this dataset, I was not able to determine the effect of missing phylogroups on diversification rates. Fauna wide trends in the mode of diversification within taxa were analyzed using a combined Z test (Whitlock 2005): Under the null model of pure birth, Z has a standard normal distribution where / is the number of taxa being combined and yp is the y-statistic for taxon p. Values of Z greater than 1.96 or less than -1.96 are significantly different at the 5% level from the pure birth expectation. The Z test of combined y values identifies trends towards negative or positive values across a series of taxa. I tested for density dependent cladogenesis in lowland and highland taxa. Density dependent cladogenesis may occur if speciation rates slow through time as ecological niches become progressively occupied. Alternatively, if the processes that promote Equation 4.2 61 speciation diminish through time, the speciation rates will slow in a correlated fashion irrespective of species density. Negative values of y reflect a slow-down in speciation through time. If a fauna experiences density dependent cladogenesis then a negative relationship should exist between y and the maximum number of sympatric species. I tested for this relationship using a regression analysis. The maximum number of regionally sympatric species in each taxon was determined by overlaying range maps for each species and determining the geographic location with the highest density of species. Finally, extinction rates were estimated directly from phylogenetic trees. Equation 17 in Nee et al (1994) gives the likelihood of an internode distance for a given extinction and speciation rate. Following methods similar to Barraclough and Vogler (2002), I used the "optim" function in R (R Development Core Team 2005) to obtain estimates of extinction and speciation rates that maximized the likelihood of internode distances g2 to gn-l (Fig. 4.1) for each tree. The utility of this estimate is limited because it assumes rates are constant, when in reality rates may vary. (d) Fauna-wide Analysis of Diversification Rates To illustrate fauna wide rates of diversification during different time periods, I used the Kendall/Moran estimator to calculate the net diversification rate during million year intervals for lowland and highland regions separately (Kendall 1949; Moran 1951; Hey 1992; Baldwin and Sanderson 1998; Nee 2001). For each of a series of phylogenetic trees, the per lineage diversification rate during a time window t is b(t) = (n-m) / S Equation 4.3 62 where n and m are the number of lineages at the end and beginning of the time period t and S is the sum of branch lengths (excluding the time interval gn in each taxon; see Equation 4.1) occurring within t. A single rate of diversification during each one million year time interval was obtained by summing n - m and S across all phylogenies in lowland and highland regions separately. The variance of the estimate b(t) provided by Nee (2001) is Var = b11 (n-m) Equation 4.4 and was used to determine 95% confidence intervals (equation 17 in Nee 2001). Diversification rates were calculated back to 8 mya (late Miocene), because not enough nodes were available before this period. This fauna wide analysis is useful for uncovering patterns in net diversification rates through time. If Pleistocene climatic fluctuations were a major factor in promoting speciation then diversification rates should increase during the late Pliocene and early Pleistocene and again during the late Pleistocene when climatic fluctuations were most intense. This fauna wide analysis of diversification rates assumes that rates (b) are constant across taxa. To test for rate constancy across taxa I compared overall diversification rates within each taxa using the joint scaling test borrowed from quantitative genetics (Lynch and Walsh 1998, pp 216). This test compares observed values of a parameter, in this case b, calculated for each of k taxa with the expected value of the parameter b if all taxa shared the same value. The expected value is b = ( M T V " ' M ) " ' M T V l i Equation 4 .5 63 where V is the covariance matrix with diagonal elements equal to the variance of each bk (Equation 4.4) and M is a matrix with one column of length k with each element equal to one. The statistic follows a Chi-squared distribution with k-l degrees of freedom 2 = y (bt-b,)2 Equation 4.6 tT Var(b,) Constant diversification rates across taxa were rejected for both lowland (X 2 = 26.6, d.f. = 16, p = 0.05) and highland (X 2 = 24.57, d.f. = 10, p = 0.006) datasets. To address the error associated with significantly different diversification rates across taxa I systematically removed outlier taxa with extremely high values of b. When Crax was excluded, constant rates in lowland faunas could not be rejected (X 2 = 21.07, d.f. = 15, p = 0.13). When Carduelis, Cranioleuca, and Muscisaxicola were excluded, constant rates in highland faunas could not be rejected (X 2 = 8.7, d.f. = 7, p = 0.27). For both lowland and highland datasets, rates were analyzed through time using both the complete datasets and datasets with outliers excluded. To determine if fauna wide estimates of diversification rate b increased during the late Pliocene and Pleistocene, rates before and after 2.5 and 1.0 mya were compared using the joint-scaling test (Equation 4.6). Rates were also compared between highland and lowland faunas before and after 2.5 mya to determine if diversification rates were different in each fauna. 64 4.3 R E S U L T S A total of 198 lowland and 146 highland species were included in the 27 taxa. Ancestor state reconstructions recovered 313 nodes with both descendents in the Neotropics (Appendix 5). Fifty-two percent of nodes were reconstructed as divergence events within the lowland fauna (Fig. 4.2a), 33% within the highland fauna (Fig. 4.2b) and 15% as interchange events between these faunas (Fig. 4.3). In the lowlands, 26% of nodes (43% of terminal species) dated (coalesced) to the glacial periods of the late Pliocene and Pleistocene and 5% (12% of species) to the late Pleistocene. The frequency of nodes decreased over the past .1.5 million years similar to simulations in which speciation rates declined through time (Appendix 4). In contrast, highland faunas had 42% and 21% of nodes (43% and 27% of species) dating to these periods respectively. The shape of the distribution of nodes had a strong upturn near the recent that appeared intermediate between simulations in which speciation or extinction rates increased towards the present (Appendix 4). Thus, even though widespread diversification occurred during the periods of climatic instability in both faunas, only the pattern in the highland fauna was consistent with an increase in diversification rate during glacial periods (though extinction may have contributed to this pattern). Nodes representing dispersal events between highland and lowland regions were most frequent during the last one million years and during the late Miocene and Pliocene (Fig. 4.3). Figure 4.3 also includes dates for intraspecific dispersal events for species distributed in both faunas. A few additional intraspecific interchange events are 65 unrecorded because the relevant sequence data was not available. These are expected to date near the recent. These dates represent coalescent dates. The actual dates of population splitting may occur after the coalescent dates if populations possessed polymorphism at the time of splitting. Current levels of intraspecific polymorphism are low, suggest that on average lowland and highland coalescent dates predate actual population splitting by only 0.35 and 0.2 million years respectively (Appendix 6). These corrections are similar to those reported for Northern Hemisphere taxa (Moore 1995). Applying these corrections did not greatly change any of the results of this study. Patterns in LTT plots also suggest that the timing of diversification was different in lowland and highland taxa (Fig. 4.2). Many lowland taxa had very steep slopes between 8 and 4 mya suggesting rapid diversification during this period. Only one lowland taxon experienced rapid diversification primarily within the late Pliocene and Pleistocene (Crax). The remaining lowland taxa exhibited slower, but relatively constant rates of diversification through time. In contrast, Pleistocene diversification was most prevalent in highland taxa (Fig. 4.2b). In the LTT plots, four of the 11 highland taxa (Cranioleuca, Carduelis, Cinclodes and Muscisaxicola) displayed steep slopes during the Pleistocene suggesting rapid rates of speciation during this period. The remaining seven taxa diversified primarily before the Pleistocene and had less steep slopes but unlike lowland taxa were not aggregated during any given time period. LTT plots and the y statistic further suggest that the rate of diversification decreased through time in most lowland taxa but remained constant in most highland taxa. Most lowland taxa displayed a downturn towards the recent in their LTT plots 66 consistent with a decrease in speciation rates through time (Fig. 4.2a). Values of the y statistic were likewise negative in 12 of 17 lowland taxa (Table 4.1) and were significantly negative in 5 taxa. No taxa had significantly positive values. The Z test of combined y values (Equation 4.2) rejected the pure birth process (Table 4.1) for the lowland avifauna as a whole, suggesting a significant fauna wide trend towards decreasing speciation rates through time. In contrast to the lowlands, the relatively constant slopes in LTT plots for most highland genera were reflected in y-values closer to 0, the pure-birth expectation. One genus had a significantly positive y-value and one had a significantly negative value. The remaining genera were not significantly different from the pure birth expectation. The Z test of combined y-values was negative, but failed to reject the pure birth process for the avifauna as a whole (Table 4.1) suggesting that the mode of diversification within highland taxa is not significantly different from exponential growth. In the lowlands, values of the y statistic were negatively correlated with the maximum number of regionally sympatric species in each taxon (Fig. 4.4; r2 = 0.57, p = -0.360 ±0.083 SE, T = -4.28, p < 0.0007 2-tailed), suggesting that the rate of speciation declined as the number of sympatric species increased. This relationship remained significant after correcting for taxon size and taxon age (age of first split within taxon) in a multiple repression (p = -0.297 ±0.127 SE,T = -2.34, p < 0.036 2-tailed). However, highland taxa exhibited no significant relationship between the values of the y statistic and the maximum number of sympatric species per taxon (Fig. 4.4; r 2 = 0.19, P = -0.192 ±0.187 SE, T = -1.03, p = 0.34, 2-tailed). 67 Maximum likelihood estimates of extinction rates (d) were low relative to speciation rates (b) for most taxa in both lowland and highland faunas (Table 4.1). At face value, these results suggest that extinction has probably not contributed significantly to observed patterns of species accumulation in either fauna. However, extinction rates estimated from reconstructed phylogenetic trees should be viewed with caution because these estimates may be biased. For instance, trees that display a downturn in LTT plots (or negative y values) exhibit negative extinction rates when maximum likelihood searches are not constrained, but extinction rates of 0 when they are constrained to positive values (values reported in Table 4.1 were constrained). In addition, these estimates of extinction assume a constant rate of extinction through time. While separate rates of extinction for different time periods can be estimated from large phylogenetic trees (Barraclough and Vogler 2002), most of the taxa included here did not have enough nodes. The Z test of combined y values detects common trends toward increasing or decreasing rates through time in a series of taxa. However, because this test lacks a temporal timescale a significant trend does not suggest that all taxa experienced increasing or decreasing rates concordantly. For example, two taxa may exhibit similar y values, but if the timing and rate of diversification differ between them, then the resulting net patterns of diversification may give different results. This is best illustrated in the highland fauna where several taxa exhibit very steep slopes during the Pleistocene period in their LTT plots (Carduelis and Craniolecua) yet had similar y-values to taxa that did not have steep slopes and diverged mostly before the Pleistocene (Fig. 4.2). Likewise, the significant trend towards negative values of y in the lowlands does not suggest that 68 diversification rates decline over the same time periods in lowland taxa. While LTT plots for many lowland taxa do appear to decline somewhat concordantly, this is not true of all taxa (Fig. 4.2a). The Kendal-Moran estimator was used to determine fauna wide values of diversification rate during million-year intervals. In the lowlands, both the full dataset and the dataset with Crax excluded exhibited very similar rates during each time period, thus only the full dataset was used. Fauna wide diversification rates declined steadily through time from a high of 0.35 species per lineage/Ma between 7 and 8 mya to 0.16 species per lineage/Ma between the recent and 1 mya (Fig. 4.2a). Diversification rates were almost significantly lower after 2.5 mya (X2 = 3.60, df = 1, p = 0.058) but no difference was found before and after 1.0 mya = 2.34, df = l,p = 0.126). In highland taxa, fauna-wide rates during the late Pliocene and early Pleistocene were not different from previous rates (X2 = 0.54, df = 1, p < 0.46). However, rates significantly doubled (as high as 0.52 species per lineage/Ma) during the late Pleistocene (X2 = 7.16, df = 1, p < 0.008; Fig. 4.2b). This late Pleistocene increase was not significant when the three taxa (Carduelis, Cranioleuca and Muscisaxicola) with the highest birth rates and which diversified primarily within the Pleistocene were excluded (JT < 0.001, df = 1, p = 0.98). In addition, late Pliocene and Pleistocene rates in the highlands were significantly higher than those in the lowlands when using the complete highland dataset (X2 = 5.1, df = 1, p < 0.024) but when highland outliers were excluded lowland rates were higher (X2 = 6.51, df = 1,p = 0.01). No difference inrates between these faunas occurred before the Pleistocene (all highland taxa included X2 = 1.88, df = 1, p = 0.17, outliers excluded X2 = 2.58, df = l,p = 0.11). These data suggest that recent climatic fluctuations 69 had an effect on fauna wide diversification in the highlands but not the lowlands. However, the fauna wide increase in highland faunas resulted from elevated late Pleistocene rates in a subset of highland taxa. 4.4 DISCUSSION Lowland and highland faunas exhibited divergent patterns of species accumulation suggesting that different processes resulted in their diversification. In the highlands, fauna-wide diversification rates increased throughout the Pliocene and Pleistocene and culminated in a late Pleistocene diversification rate more than double previous values. This increase in rate resulted in a burst of diversification during the last 1 million years (Fig. 4.2b) consistent with the hypothesis that climatic fluctuations resulted in a recent build-up of species in this fauna. In contrast, lowland diversification rates slowed through time (Fig. 4.2a) and were lowest during the late Pleistocene. Though the fauna-wide slow down was not quite significant, this result demonstrates that rates did not increase through the Pleistocene as expected if climatic fluctuations drove lowland diversification. What processes promoted these divergent patterns of species accumulation in lowland and highland faunas? In lowland taxa, y values revealed a significant trend towards decreasing diversification rates (Table 4.1). This pattern is consistent with the fauna wide decrease in diversification rate and suggests that a decline in rates within taxa resulted in the fauna-wide pattern. Simulations demonstrate that a decline in the rate of speciation was more likely to generate such a strong pattern than an increase in the rate of extinction (Appendix 4). Likewise, estimates of extinction rates, though potentially 7 0 biased, were low in most taxa (Table 4.1). The decrease in speciation rates may simply reflect the lack of geographic opportunity for speciation towards the recent. Alternatively, the decrease may reflect density dependent cladogenesis. The significantly negative relationship between the value of y and the number of sympatric species in each taxon (even after correcting for taxon age and size) suggests that density dependent cladogenesis is responsible for the slowdown in species accumulation in lowland faunas. These preliminary results are consistent with the view that low extinction rates have allowed the accumulation of high species diversity and suggest that the number of species in lowland faunas may be approaching their capacity. Possible low extinction rates for birds contrast preliminary findings from Amazonian paleopollen records in which species diversity may have declined from the Miocene to the present (van der Hammen and Absy 1994; Hooghiemstra and van der Hammen 1998; van der Hammen and Hooghiemstra 2000; Willis and Niklas 2004). Further estimates of extinction rates from other taxonomic,. groups are needed in order to establish the role of extinction in the build-up of high species diversity in the Neotropics. Could the observed slow down in speciation rates through time in lowland taxa be an artefact of not sampling intraspecific splits (i.e. phylogroups) in this study? Indeed, a number of phylogenetic studies have uncovered genetically distinct lineages within many currently named lowland species (Aleixo 2002, 2004; Marks et al. 2002; Joseph et al. 2003; Burns and Naoki 2004; Joseph et al. 2004; Lovette 2004b; Armenta et al. 2005; Cheviron et al. 2005b). However, detailed population level sampling was not available for most species in my dataset. To address this question, I determined the initial diversification rate (slope) for each taxon from its LTT plot using only the first five 71 nodes. I extended this rate to the present in order to determine the number of expected lineages if diversification rates had remain constant. In highland taxa, the expected number of lineages was very similar to the actual number in all taxa, with 0.4 additional lineages expected within each species on average (Table 4.1). However, in many lowland taxa the expected number of lineages was much higher than the actual number (88 additional lineages per species on average). It is doubtful that the actual number of lineages in many lowland species approaches, let alone surpasses their pure birth expectation. Thus it appears that even if unrecognized lineages were included in the LTT plots, there still would be no evidence for a Pleistocene increase in lowland diversification rates. Detailed phylogenies that include all genetically distinct lineages regardless of taxonomic status are needed for confirmation. In contrast to the lowlands, LTT analysis suggests that most highland taxa did not exhibit a significant trend away from the pure birth expectation. This is not unreasonable given that continual uplift of highland regions could provide ongoing opportunities for speciation. Likewise, evidence for density dependence was lacking (Fig. 4.4) further suggesting that ecological opportunity is not currently a limiting factor in highland diversification. This pattern of constant diversification rates within taxa did not match the fauna wide pattern of increasing diversification rates during the late Pleistocene. This apparent discrepancy is best explained by the faster speciation rate in taxa that diversified primarily within the Pleistocene (slopes in LTT plots for Carduelis, Cranioleuca, Cinclodes and Muscisaxicola are steeper than in taxa which diversified primarily before the Pleistocene, Fig. 4.2b). Thus it appears that only a subset of highland taxa strongly contributed to the fauna wide increase in diversification rates during the late Pleistocene. 72 Could extinction also generate the apparent late Pleistocene increase in diversification rate? Simulations that included extinction often did result in a recent upturn, though this effect was less pronounced than in models with an increase in speciation rate (Appendix 4). Nevertheless, estimates from highland phylogenetic trees (Table 4.1) suggest that extinction rates (estimates assume constant rates through time) are low in most highland taxa. Rapid speciation rates in a subset of highland taxa probably drove the late Pleistocene increase. However, until better estimates of extinction rates (i.e. non-constant extinction rates) are obtained, the role of extinction cannot be ruled out entirely. These differences in species accumulation through time resulted in differently aged faunas (Fig. 4.2). The most striking difference is the abundance of highland species and scarcity of lowland species dating to the late Pleistocene. Less than one fifth of lowland species date to this period even after correcting for ancestral polymorphism. Yet, global climatic fluctuations were most intense during this period. If these climatic fluctuations were not enough to promote widespread fragmentation and speciation in the lowlands, then it is unlikely that the weaker climatic fluctuations of the late Pliocene and early Pleistocene were important in lowland diversification either. In contrast, the late Pleistocene increase in highland diversification rate resulted in a fauna with one third of its species dating to the last million years. Unlike lowland regions, extensive evidence suggests that widespread alteration of highland habitats occurred repeatedly during the late Pleistocene. Extensive glaciation occurred throughout highland regions (Hooghiemstra and van der Hammen 2004). Glaciers undoubtedly fragmented the ranges of many Andean species by providing a hard barrier between 7 3 populations displaced along the eastern and western slopes. In addition, cooling resulted in an elevational migration of habitat zones to lower altitudes resulting in an elevational compression of some zones and expansion of others (van't Veer and Hooghiemstra 2000; Hooghiemstra and van der Hammen 2004). The correlation between the onset of severe glaciation in the Neotropics about 0.8 to 0.9 mya (Bennett 1990; Hooghiemstra et al. 1993) and the late Pleistocene increase in speciation rates suggests a causal link. Interchange between highland and lowland faunas also played an important role in Neotropical diversification (Fig. 4.3). Dispersal events from the lowlands to the highlands occurred primarily during the late Miocene and early Pliocene when extensive uplift of the central and northern Andes provided new elevation zones and habitats. Thirty-three nodes represent dispersal from lowlands to highlands compared to 146 nodes that represent divergence within highland faunas. This fairly large proportion suggests that dispersal from lowland regions contributed importantly to the build-up of species diversity in the highlands. In contrast, Fjeldsa and Lovett (Fjeldsa and Lovett 1997a, 1997b) envisioned dispersal out of highland regions as a major source of species diversity for lowland faunas. While 16 dispersal events from highland to lowland faunas are reconstructed in this dataset, compared to the 198 splitting events that occurred within the lowlands, dispersal from highland faunas represents only a small contribution to lowland diversity. Rather, diversification within lowland regions was the predominant mode by which species accumulated in this fauna. Moreover, most dispersal events from the highlands into the lowlands occurred during the last one million years (Fig. 4.3) and correlate with major glacial cycles in the Andes (Bennett 1990; Hooghiemstra et al. 1993). Glacial lowering of elevational zones resulted in mixed floras (Colinvaux et al. 74 1996, 2000; van der Hammen and Hooghiemstra 2000; Bush et al. 2004) and presumably mixed faunas near the base of highland regions that included both lowland and highland components. This mixing may have facilitated adaptation to and subsequent invasion of lowland regions (Rull 2005). These results are inconsistent with the once prevalent view that late Pliocene and Pleistocene climatic fluctuations drove the recent buildup of species diversity in lowland Neotropical faunas. Many Nearctic avian taxa also display decreasing speciation rates through time (Zink and Slowinski 1995; Zink et al. 2004) suggesting that the processes that promoted speciation in both faunas occurred primarily before the onset of the late Pliocene and Pleistocene ice ages. Nevertheless, this study suggests that the proportion of species of glacial age is much higher in highland regions of the Neotropics where expanding and retracting glaciers directly fragmented habitats. A late Pleistocene increase in fauna-wide rates of diversification correlates with the onset of severe glaciation in highland regions and resulted in a fauna in which one third of extant species are less than a million years old. Likewise, ice sheets directly fragmented the high latitude boreal forests of the Nearctic where a greater proportion of avian sister species date to the Pleistocene than in sub-boreal regions (Weir and Schluter 2004). Together, these studies suggest that diversification rates in faunas distributed closest to the expanding and retracting glaciers were most heavily impacted by climatic fluctuations while faunas distributed further from the glaciers were impacted to a lesser degree. Further sampling of other glaciated regions is necessary to determine the generality of this pattern. 75 Table 4.1 Lowland and highland taxa analyzed. Results of the y statistic, the expected number of lineages for each clade and phylogenetic sources from which the majority of DNA sequences were obtained for each phylogenetic analysis. Taxon Number of Species Youngest y (p value) Expected Phylogenetic Source Species4 (species / (species / phylogroups lineage per Ma) lineage per Ma) per species6 Region1 Available2 Sympatric3 a) Lowland Amazon 16 14 6 1.05 -2.12 (0.033) 0.35 0.00 11.6 Russello and Amato 2004 Blackbird clade 14 13 9 0.27 -3.26 (0.001) 0.25 0.00 631.0 Lanyon and Omland 1999 Crax . 13 13 3 0.73 -1.80 (0.072) 0.65 0.00 0.2 Pereira and Baker 2004 Dendrocincla 7 7 3 1.38 0.07 (0.944) 0.51 0.60 0.7 this study Icterus 16 16 6 0.33 -2.06 (0.039) 0.22 0.00 2.3 Omland etal. 1999 Myiarchus 11 10 5 0.31 0.27 (0.842) 0.40 0.43 -0.5 Joseph et al. 2003 Nyctibius 6 5 5 10.10 -0.34 (0.730)* 0.11 0.00 6.3 Mariaux and Braun 1996 Pionopsitia 9 8 3 1.38 1.15 (0.248) 0.32 0.42 -0.1 Eberhard and Bermingham 2005 Psarocolius 19 15 11 1.10 -1.79 (0.068) 0.26 0.00 53.7 Price and Lanyon 2002, 2004 Pteroglossus 12 12 4 0.91 -0.11 (0.912) 0.49 0.24 0.3 - Eberhard and Bermingham 2005 Ramphocelus 7 6 2 1.95 0.27.(0.785) 0.80 1.08 0.4 Hackett 1996 Swallow clade 12 12 8 0.40 -2.02 (0.043) 0.12 0.00 1.8 Sheldon et al. 2005 Tachycineta 5 5 2 2.34 0.56 (0.576) 1.37 2.19 0.7 Whittingham et al. 2002 Tangara 22 19 8 1.87 -2.11 (0.032) 0.30 0.00 781.2 Burns and Naoki 2004 Trogon 14 11 5 3.69 -1.18 (0.229) 0.13 0.00 0.8 this study, Espinosa de los 1998 Veniliornis 10 8 3 3.30 -0.37 (0.707) 0.64 0.39 2.6 Moore et al. 2005 Xiphorhynchus 13 13 6 1.63 -1.26 (0.208) 0.25 0.00 7.6 Aleixo2002 Z-test -3.92 (<0.0001) Average 12 11 5 1.93 0.42 0.32 88.3 b) Highland Anairetes 7 6 5 1.21 -1.07 (0.282) 0.30 0.00 0.4 Roy et al. 1999 Carduelis 10 8 5 0.59 1.04(0.290) 4.28 5.59 0.0 van den Elzen et al. 2001 Cinclodes 11 11 3 0.42 -0.62 (0.535) 0.49 0.08 0.0 Chesser 2004 . Cranioleuca 11 10 3 0.34 -1.15 (0.251) 0.83 0.00 0.8 Garcia-Moreno et al. 1999a Geositta 9 9 4 4.14 0.21 (0.834) 0.33 0.31 0.5 Cheviron et al. 2005a Hemispingus 14 12 7 0.57 -1.72 (0.081) 0.12 0.00 1.2 Garcia-Moreno et al. 2001 Metallura 10 9 2 0.34 -0.85 (0.394) 0.24 0.00 0.3 Garcia-Moreno et al. 1999b Muscisaxicola 12 12 6 0.33 4.07 (0.000) 5.31 6.64 -0.6 Chesser2000 Ochthoeca 11 11 7 2.19 -0.13 (0.897) 0.32 0.17 0.7 Garcia-Moreno et al. 1998 Tangara 26 23 13 0.29 -3.17 (0.032) 0.20 0.00 0.7 Burns and Naoki 2004 Troglodytes 7 6 3 3.29 -0.04 (0.968) 0.24 0.03 0.5 Rice etal. 1999 Z-test -1.03 (0.300) Average 12 11 5 1.25 1.15 1.17 0.4 1) species in each geographic region of interest. 2) number of species for which DNA samples were available. 3) maximum number of regionally sympatric species in geographic region. 4) approximation of the lag time to speciation estimated as youngest sister species within the geographic region of interest in each taxon. 5) speciation (b) and extinction (d) rates estimated using a birth death model. 6) expected number of lineages at present if initial rates of diversification remained constant. Initial diversification rates were calculated from the first five nodes in each phylogeny. See text for details. * Assuming a 2% molecular clock, Nyctibius does not speciate during the last 10 million years. It seems unlikely that the speciation process (evolution of reproductive isolation) would require more than a few million years, thus this long time period (g„) probably represents a genuine slow down in the rate of splitting. However, it is not known if intraspecific splitting events have occurred along g„. If gn is not excluded, y equals -2.3 (p = 0.02) A) Phylogenetic tree Time (mya) Fig. 4.1 Example of how patterns of species accumulation are obtained from a reconstructed phylogenetic tree. (A) a reconstructed phylogenetic tree containing species within (black) and outside of (grey) a geographic region of interest. For lineage through time (LTT) analysis, only node ages representing splitting events within the geographic region of interest (black circles) or that represent colonization from an outside source followed by speciation (black arrow) were used. Nodes leading to the formation of a clade outside of the region of interest were excluded (grey arrows) because they do not represent the addition of a new lineage to the fauna. (B) Internode distances for geographic region of interest labelled g2 to gs- (C) L T T plot for taxa in the geographic region of interest. Values of the y statistic are equal to zero when the slope of the L T T plot is constant through time. Downturns in the slope produce negative y-values whereas upturns produce positive values. 7 8 A) Lowland B) Highland Miocene Pliocene Pleistocene Miocene Pliocene - i 1 Pleistocene Fig. 4.2 Lineage through time (LTT) plots and faunawide rates of diversification through time for Neotropical lowland (A) and highland taxa (B). Maximum-likelihood estimates of rates of diversification are plotted with 95% confidence intervals. Two highland datasets were used to analyze faunawide rates: all highland genera (black) and Carduelis, Cranioleuca and Muscisaxicola excluded (gray). Numbers refer to the following taxa: (1) Crax, (2) Muscisaxicola, (3) Cranioleuca, (4) Carduelis, and (5) Cinclodes. The levels of shading on histograms and pie charts increase from light to dark for warm periods of the Miocene and early Pliocene (in yellow online), mild ice ages of the late Pliocene and early Pleistocene (in blue online) and severe ice ages of the late Pleistocene (in red online). 79 12T 10 9 8 7 6 5 4 3 2 1 time (mya) Fig. 4.3 Nodes representing interchange events between highland and lowland faunas as reconstructed from ancestor state reconstructions for 27 Neotropical taxa. Dispersal from lowland to highland faunas (gray) and highland to lowland faunas (black). 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B Biol. Sci. 359:215-219. Zink, R. M. , and J. B. Slowinski. 1995. Evidence from molecular systematics for decreased avian diversification in the Pleistocene epoch 10. Proc. Natl. Acad. Sci. U. S. A. 92:5832-5835. 90 Chapter 5 SPLENDID ISOLATION: THE GREAT AMERICAN BIOTIC INTERCHANGE IN BIRDS4 5.1 R E S U L T S A N D DISCUSSION Completion of the Central American Landbridge during the mid-Pliocene initiated the Great American Biotic Interchange (GABI) in mammals, the largest and most rapid episode of interchange known between Continental faunas (Simpson 1980; Stehli and Webb 1985). Following the mid-Cretaceous breakup of Gondwanaland (ca. 95 million years ago, Ma hereafter), South America drifted as an island continent until landbridge completion between 3.1 and 4.0 Ma (Coates et al. 1992; Coates and Obando 1996). During its island interval, South American mammals evolved in what has been coined "splendid isolation" (Simpson 1980) resulting in a fauna highly distinctive from North American mammals. Like mammals, birds and other taxonomic groups also evolved distinctive South American faunas (Ericson et al. 2002, 2003). The fossil record documents a burst of mammalian interchange shortly after landbridge completion and subsequent increase in species diversity as continental faunas merged (Webb 1985; Marshall 1985). However, incompleteness of the fossil record has hindered a more general assessment of the role of the GABI in non-mammalian taxa (e.g. Vuilleumier 1984, 1985). Terrestrial mammals may be particularly poor at crossing marine barriers while other taxonomic groups may have had less difficulty dispersing prior to landbridge completion. Birds in particular are capable of dispersing across oceanic barriers, as evidenced by their colonization of many isolated islands. As a result, avian participation 4 A version of this chapter has will be submitted for publication. Weir, J. T., E. Bermingham, and D. Schluter. Splendid isolation: the Great American Biotic Interchange in birds. 91 in the GABI is poorly understood (Vuilleumier 1985). To determine if completion of the landbridge significantly increased interchange rates in birds, we used molecular phylogenetic techniques to compare rates before and after landbridge completion. The timing and rates of interchange were compared for four speciose passerine families (Thamnophilidae, antbirds; Dendrocolaptidae, woodcreepers; Thraupidae, tanagers; Icteridae, blackbirds) that straddle the Americas. Antbirds and woodcreepers specialize in rainforest understory and interior and are expected to have poor dispersal abilities as evidenced by their absence from Caribbean islands and their propensity to form genetically distinctive populations on opposite river banks in the Amazon (Capparela 1991; Bates et al. 2004; Hayes and Sewlal 2005). In contrast, blackbirds and tanagers predominate in rainforest canopy and a variety of non-forest habitats and have each colonized the Caribbean multiple times. These indicators of dispersal ability across water barriers suggest interchange rates in forest specializing antbirds and woodcreepers should have been more heavily impacted by completion of the Central American Landbridge than in the more generalist blackbirds and tanagers. For each family, dated molecular phylogenies using cytochrome b data (for dating) and a series of mitochondrial genes and nuclear introns (for tree construction) were generated that included North and South American representatives for each interchange event. A maximum likelihood framework was used to compare two models of interchange along each phylogeny: a single rate model in which interchange rates remained constant through time and a two rate model (Mooers and Schluter 1999) in which interchange rates were allowed to vary before and after landbridge completion (a date of 3.5 Ma was used for landbridge completion). These models have the advantage of not conditioning on any given ancestor state reconstruction of continental distribution at interior phylogeny nodes, but instead estimate rates over all possible reconstructions, 92 weighting each by its likelihood support (Schluter et al. 1997; Mooers and Schluter 1999; Pagel 1999). The two-rate model gave a significantly better fit in all four families and estimated accelerated post-landbridge rates in each (Table 5.1). However, while post-landbridge rates were estimated to be 2 and 3.6 times greater in blackbirds and tanagers respectively, post-landbridge rates in antbird and woodcreepers were more than 50 times greater (Table 5.1). These differences correlate with inferred dispersal abilities and suggest that interchange in forest specialists was more strongly facilitated by landbridge completion than in generalist families. The maximum likelihood estimates of rates before and after landbridge formation were used to reconstruct ancestral geographic ranges at interior nodes in each phylogeny, with states coded as North or South American. Interchange events between continents were identified along these phylogenies by nodes having one daughter in South America and the other in North America. More rarely, interchange events between North and. South America occurred via the Antilles, in which case the node at which a lineage left the Antilles and entered the new continent was used to date the interchange event. While ancestor state reconstructions do not provide a definite biogeographic history, they do provide the best estimate of that history in the absence of fossil data. A total of 114 interchange events were reconstructed (woodcreepers, 18; antbirds, 25; tanagers, 46; blackbirds, 25). Our molecular sampling enabled dating for 88 of these interchange events, 83% of which postdated landbridge completion (ca. 3.5 Ma; Fig. 5.1, 5.2). Error intervals associated with molecular dating (on average ±0.96 million years for splitting events between 3 and 4 Ma) leaves open the possibility that some dispersal events that are estimated to date just prior to landbridge completion may actually postdate 3.5 Ma. Conversely, others that date just before its completion may actually predate the landbridge. Despite uncertainty in molecular based dating and ancestor state 93 reconstructions, these data give overwhelming evidence for the role of an emerging landbridge in facilitating interchange in birds. Ancestor state reconstructions strongly support a South American ancestry for antbirds, woodcreepers and tanagers and a North American ancestry for blackbirds. Dispersal rates during 0.5 or 1.0 million year time intervals were estimated by dividing the number of reconstructed crossing events by the sum of evolutionary time (branch lengths) during each interval (Fig. 5.1). Dispersal in the three families of South American origin was almost entirely unidirectional with dispersal primarily into North America and only one reconstructed back colonization event into South America in tanagers (Fig. 5.1). In contrast, bi-directional interchange in the blackbirds of North American origin was frequent. In the antbirds and woodcreepers earliest dispersal events date near the completion of the landbridge (antbirds, 3.3 Ma; woodcreepers 3.8 Ma) demonstrating that all interchange in these families occurred near or after landbridge completion. In contrast several early dispersal events into North America occurred in tanagers, one of which produced the only endemic North America genus (Acanthidops). Likewise in blackbirds a pre-landbridge burst of dispersal from North to South America occurred between 6 and 7 Ma, when three major clades simultaneously colonized the continent (Fig 5.1). Blackbird dispersal from North into South America continued up to the recent with no apparent increase after landbridge completion. However, dispersal from South America into North America occurred only after landbridge completion in blackbirds (Fig. 5.1) and matches the pattern observed in woodcreepers and antbirds. Like those families, most northward dispersing taxa of blackbirds were forest specialists, further supporting the reliance of forest taxa on a completed landbridge. Patterns of interchange in birds and mammals have broadly similar patterns. In both groups a handful of interchange events occurred in the late Miocene prior to 94 landbridge completion. These early dispersal events are presumed to have occurred along the proto-landbridge, which at this time consisted of a string of islands separated by ocean channels between the Pacific and Caribbean. Early interchange was bi-directional in both birds and mammals with a few tanagers, four genera-of ground sloths and armadillos moving north and blackbirds, racoons, camels, tapirs, peccaries and proboscideans moving south (Fig. 5.2; Marshall 1985; Campbell et al. 2000; Flynn et al. 2005). A sudden increase in dispersal rates indicates the initiation of full scale interchange in birds between 3 and 4 Ma (Fig. 5.1 and 5.2). The wave of mammals followed slightly later between 2.5 and 2.8 Ma (Fig. 5.2; Marshall 1985; Webb 1985). Whether this slight discrepancy in timing represents an earlier dispersal response by birds or is an artefact of scarce fossil records just prior to 2.8 Ma in mammals (Flynn et al. 2005) is unknown. Nevertheless, the general concordance between the onset of interchange in birds and mammals suggests completion or near completion of the landbridge facilitated a burst of faunal mixing in both groups. The scanty fossil record from tropical rainforest environments does not allow a detailed chronology of interchange in rainforest specializing mammalian groups and what is known of mammalian interchange comes mostly from those groups capable of dispersing through the tropics to temperate latitudes at either end of each continent (Flynn et al. 2005; MacFadden 2006). Where fossils fail, our molecular data provide the first detailed look at vertebrate interchange in rainforest specializing taxa (antbirds and woodcreepers). Unlike the more generalist tanagers and blackbirds, interchange in antbirds and woodcreepers appears to have been closely tied to a completed landbridge suggesting that tropical rainforest inhabiting species were not able to disperse prior to landbridge completion. To determine if this is also true in the host of tropical rainforest-95 inhabiting mammalian species that dispersed between continents will also require a molecular phylogenetic approach given the lack of fossils. To further test the association between landbridge reliance in tropical forest specialists, we reconstructed earliest dates of dispersal in 14 of the 26 passerine families involved in the Great American Biotic Interchange. Earliest interchange dates predated landbridge completion by 3 to 10 million years in all but one of those families not specializing in tropical forest (Fig. 5.3). These results are not surprising, given that most families not restricted to tropical forest have colonized Caribbean islands and evolved long distance migration to tropical latitudes during winter months, suggesting ease of dispersal across water barriers. The only non-forest taxon that first dispersed during the landbridge era were the dippers (Voelker 2002), but because dippers entered the New World slightly prior to landbridge completion, it is uncertain whether they would require a landbridge for dispersal. In contrast, none of seven tropical forest specializing families involved in the interchange undergo annual long distance migrations or have reached the Caribbean. Earliest dispersal dates in the three forest specializing families for which we had sequence data all date between 3.0 and 4.0 Ma. The association between rainforest specialization and the need for a completed landbridge was signifiant (p = 0.011, Fisher's exact test) suggesting interchange was strictly tied to a completed landbridge in rain forest groups. Tropical forest specializing families are all South American in origin, suggesting a largely unidirectional post-landbridge interchange with families of Amazonian origin invading Central America for the first time but not vice versa. The current tropical forest avian communities of Central America are dominated by these families of South American origin, but Amazonian tropical communities appear to have fewer Central American passerine elements. Likewise, the current floral makeup of Central American 96 rainforest is comprised to a large extent of South American elements but conversely few Central American elements occur in Amazonian tropical forest (Graham 1976; Gentry 1982; Simpson and Neff 1985; Cronquist 1988; Gentry 1990; Wendt 1993; Burnham and Graham 1999). These similar patterns in birds and plants suggest that both the rainforest flora and avifauna of South America invaded North America together in a post-landbridge wave. This wave of immigration had the potential to rapidly increase tropical species diversity in North America with South American tropical faunal components joining the endemic North American fauna. In the landbridge, the contemporary avifauna of tropical North America is composed almost equally of species belonging to families of North and South American origin (ratio of north to South American species in Panama is 0.94), demonstrating complete faunal mixing. Whether this faunal mixing increased species diversity or resulted in widespread extinction of the previous native avifaunal components remains to be tested. 5.2 M E T H O D S (a) Taxon sampling Though available sequence data was not sufficient to calculate all interchange dates, it did allow earliest dispersal dates to be estimated in 16 passerine families involve in interchange between North and South America (Fig. 5.2, Table 5.2). All dispersal events were reconstructed in four families: woodcreepers (Dendrocolaptidae), antbirds (Thamnophilidae) tanagers (Thraupidae) and blackbirds (Icteridae). These families were chosen because they are species diverse with multiple clades in both North and South America. Published molecular phylogenies, with at least 60 percent of genera sampled, are available for each [antbirds (Irestedt et al. 2004a; Brumfield and Edwards 2007); 97 woodcreepers (Aleixo 2000; Irestedt et al. 2004b); tanagers (Burns 1997; Klicka et al. 2001; Burns et al. 2002, 2003; Burns and Naolki 2003); blackbirds (Lanyon and Omland 1999; Omland et al. 1999; Cadena et al. 2004; Price and Lanyon 2002, 2004)]. Almost all interchange dates represented by extant taxa were reconstructed along these phylogenies by including molecular sequences from individuals sampled on either side of the Isthmus of Panama. I collected genetic samples representing the North American side of the isthmus in western Panama (west of the Canal Zone), mostly in the provinces near the Costa Rican boarder. The South American side was represented by samples collected in Darien Province near the Colombian borders (Appendix 7). This sampling design was augmented with museum samples collected from throughout Central and South America (Appendix 7). Adequate phylogeographic coverage was not available for some dispersal events. In such cases, closely related outgroups were used to obtain an upper bound on dispersal dates. Phylogenetic boundaries of woodcreepers, antbirds and blackbirds are without question, and each represents a monophyletic group. However, boundaries of tanagers (Thraupidae) are more problematic with a number of recent molecular phylogenetic analysis redefining the core tanager group, but none of them present the data in a single analysis. Tanagers belong to the New World nine-primaried oscine radiation. This radiation includes more than 790 species currently placed in five families (Fringillidae, Cardinalidae, Thraupidae, Emberizidae, Parulidae and Icteridae). Bayesian phylogenetic analysis using available cytochrome b sequence data for 136 nine-primaried oscine genera (68%) and almost all genera traditionally included in the tanagers were used to define a monophyletic Thraupidae for the purposes of this analysis. Strong support was found for a core Thraupidae that included several genera currently classified in other nine-primed oscine families, and excluded several genera traditionally placed with the tanagers (Appendices 8 and 9). Confirmation of tanager boundaries requires a more 98 extensive molecular dataset including both nuclear and mitochondrial genes. The tanager phylogeny (Appendix 10) generated to test the Great American Biotic Interchange (outgroups not shown) comprised multiple nuclear and mitochondrial genes for a subset of taxa including most major lineages of tanagers and several representatives from all other nine-primaried oscine families. Boundaries of the tanagers in this second analysis were identical to the dataset using only cytochrome.b, supporting our classification of a monophyletic Thraupidae. (b) DNA sequencing and phylogenetic analysis The woodcreeper, antbird, tanager and blackbird phylogenies were generated from a combination of Genbank sequences and sequences collected and generated specifically for this study (Appendix 7). Partial (-1000 bp) or complete (1143 bp) sequences of the mitochondrial cytochrome b (cyt b) gene were sequenced for all individuals using standard protocols (Weir and Schluter 2007). The complete mitochondrial NADH dehydrogenase subunit 2 gene (ND2: 1041 bp) was sequenced using primers L5215 (Hackett 1996) and H6313 (Johnson and Sorenson 1998) for a subset of individuals representing most of the major lineages included in each phylogeny and for at least one individual from most of the taxa representing interchange events. Partial sequences of the nuclear recombination activating protein 1 (RAG1) gene and c-myc exon 3 were sequenced (for protocols see Irestedt et al. 2002) for major woodcreeper lineages to add better resolution to basal nodes. This sequencing effort was augmented with other mitochondrial genes and nuclear introns available from Genbank (Dendrocolaptidae: myoglobin; Thamnophilidae: myoglobin, NADPH, ND3, NADPH, B-fibrinogen; Thraupidae: ATPase, COI, 12s, myoglobin, RAG1, cmyc; Icteridae: COI, 12s). 99 DNA sequences were edited and aligned in BioEdit (Hall 1999). Dated phylogenetic trees were generated in two steps. First, Bayesian topology estimates were obtained in MrBayes v3.1.2 (Huelseneck and Ronquist 2001) using the GTR-gamma model and a full dataset of mitochondrial and nuclear genes. Analyses were run for a minimum of five million generations and were sampled every 5000 generations after an initial burn-in of at least 1 million generations. Sampled Bayesian trees were used to construct majority-rule consensus cladograms (Appendix 10). Given the extensive sequence datasets for the focal families (antbirds, woodcreepers, blackbirds and tanagers), posterior support was strong for most nodes. Second, ultrametric estimates of branch-lengths along the consensus topology were generated under a Bayesian framework in BEAST vl.4.2 (Drummond and Rambaut 2006) using only the cytochrome b dataset. The uncorrelated lognormal relaxed clock model (with Yule prior for branch lengths; Drummond et al. 2006), which does not rely on the assumption of molecular rate constancy, was used in combination with the GTR-gamma model of sequence evolution. Analyses were run for a minimum of 5 million generations, sampled every 5000 generations, and a burnin appropriate to each analysis was discarded. Mean consensus branch-lengths were obtained from the Bayesian samples. Dated molecular phylogenies (using cyt b, ND2 or both genes) were also generated for 11 additional passerine families using identical methods. These phylogenies (not shown) were used to reconstruct earliest dates of dispersal in these groups. To date trees, we set the molecular rate prior to 2.2% sequence divergence per million years (1.1% per lineage; Weir 2004). A molecular rate of -2% has traditionally been used for cytochrome b in birds, but support for this rate is based on a limited number of calibrations. To determine the utility of a 2% clock, a total of 70 calibrations were obtained using fossil and biogeographic data and fossil cross validation was used to identify and exclude erroneous calibrations (Weir 2006, Weir and Schluter 2007, 100 unpublished data). Results strongly support an average molecular rate of 2.2% both for passerines and most non-passerine families, and this rate is used throughout this study. (c) Biogeographic methods Interchange rates before and after landbridge completion 3.5 Ma were calculated using maximum likelihood models of character evolution along phylogenetic trees as implemented in the R package GEIGER (Harmon et al. submitted). Because extinction rates are estimated to be low in Neotropical birds (Weir 2006, Weir and Schluter 2007), most interchange events probably occurred at nodes rather than along branches. With this consideration, a punctuational model, in which character change occurs at nodes rather than along branches, was implemented by constraining all branch lengths to be equal (following Weir 2006). For further details of these models see Pagel 1994, 1999, Schluter et al. 1997, and Mooers and Schluter 1999. Rate estimates before and after 3.5 Ma were then used to generate maximum likelihood ancestor state reconstructions of continental distribution at interior nodes (Appendix 10) using Mesquite vl.12 (Maddison and Maddison 2006). Samples from western Panama northwards through North America were coded as North American and those from near the Colombian boarder and throughout South America were coded as South American. Caribbean taxa were coded as belonging to the continent from which the Caribbean was colonized. Parsimony reconstructions were also generated for comparison and yielded almost identical results to the maximum likelihood reconstructions (Appendix 10) suggesting these reconstructions are robust using different methodologies. As such, we used only the maximum likelihood reconstructions in our analysis. Two blackbird dispersal events (Molothrus bonariensis colonizing Florida from the Caribbean and Leistes militaris colonizing Central America from Colombia) occurred 101 within historical times and parsimony reconstructions were constrained to conform to the known history of colonization. Finally, our reconstructions were incomplete for some dispersal events because genetic data were unavailable from one side of the landbridge. Missing taxa or populations were added manually to the phylogenies for purposes of ancestor state reconstruction and maximum likelihood model testing. Under parsimony-based ancestor state reconstructions and the maximum likelihood 1 rate punctuational model, branch length information is irrelevant and the dates at which missing taxa connect to the phylogeny are unnecessary. However, these dates are relevant for the 2 rate model and the maximum likelihood ancestor state reconstructions based on it. Because the 2 rate model is also punctuation, it is only necessary to know if missing lineages joined the phylogeny before or after the 3.5 Ma breakpoint. By default, some of these incompletely reconstructed dispersal events are known to have occurred after landbridge completion because their most closely rated outgroups diverged from them after 3.5 Ma. In these cases, taxa were dated after 3.5 Ma. If outgroup taxa pre-dated the landbridge, then it remains unknown if missing lineages date before or after 3.5 Ma. In such cases, a conservative approach was taken by adding missing taxa prior to landbridge completion. This will have the effect of artificially increasing rates before landbridge completion. Taxa missing from these phylogenies, but not involved in dispersal between North and South America, were ignored. Finally, rates of interchange were calculated during narrow time intervals by dividing the sum of interchange events by the sum of branch lengths (evolutionary time) during each time interval. These rates correspond to net diversification rate estimators presented in equation 3.3 (Chapter3; Weir 2006). Missing taxa were ignored in these rate estimates. Very few species were missing from blackbird and woodcreeper phylogenies but considerable numbers of taxa were missing in the tanagers and blackbirds. Missing taxa result in an underestimation of branch length and thus overestimate rates. Rates are more likely to be overestimated near the recent, but this is unlikely to eliminate the faster post-landbridge rates estimate here. 102 Table 5.1 Maximum likelihood estimates of interchange rates. Parameters estimated as follows: q, rate parameter under 1 rate model; qb and qa, rates before and after 3.5 Ma under 2 rates model. Abbreviations as follows: n, number of free parameters; LR, likelihood ratio; p, p-value for likelihood ratio test; AIC, Akaike Information Criterion. Significant results for likelihood ratio test and AIC are shown in bold. Family and Model n Qb <7a Qa/Qb Log Like LR P AIC Antbird 1 rate 2 rate 1 2 30 0.00595 0.2975 50.0 -96.36 -58.26 76.2 2 . 5 6 E - 1 8 194.72 1 2 0 . 5 2 Woodcreeper 1 rate 2 rate 1 2 36.5 0.00456 0.3418 75.0 -58.92 -42.93 31.98 1 . 5 6 E - 0 8 119.84 8 9 . 8 6 Tanager 1 rate 2 rate 1 2 4.8307 0.0579 0.2062 4.0 -178.74 -139.72 78.04 1 . 0 1 E - 1 8 359.48 2 8 3 . 4 4 Blackbird 1 rate 2 rate 1 2 49 0.1052 0.2104 2.0 -91.12 -65.67 50.9 9 . 7 2 E - 1 3 184.24 1 3 5 . 3 4 103 Table 5.2 Passerine families involved in the Great American Biotic Interchange. F a m i l y C o m m o n n a m e Cont inent of Or ig in Ear l iest in terchange date Migratory C o l o n i z e d C a r i b b e a n T r o p i c a l Fores t S p e c i a l i s t C o n o p h a g i d a e 1 G n a t e a t e r s S A no n o y e s I C o t i n g i d a e 2 C o t i n g a s S A no n o • y e s " 1 D e n d r o c o l a p t i d a e W o o d c r e e p e r s S A 4 . 2 no n o y e s . " F o r m i c a r i i d a e " 3 . i . . '. A n t p i t t a s S A ' n ° . ' • no , * Ves | " F o r m i c a r i i d a e " 4 A n t t h r u s h e s S A no n o y e s F u r n a r n d a e ' O v e n b i r d s n o m i x e d P i p r i d a e M a n a k i n s S A no n o y e s R h i n o c r y p t i d a e T a p a c u l o s ' " S A " ' no n o y e s T h a m n o p h i l l i d a e A n t b i r d s S A 3 .2 no n o y e s '. T y r a n n i d a e F l y c a t c h e r s S A ' 1 4 3 y e s '. y e s " ' ' . m i x e d j A l a u d i d a e L a r k s N A y e s n o no l C a r d i n a l i d a e , „ ' ' C a r d i n a l s N A y e s m i x e d - - ~ | C i n c l i d a e D i p p e r s N A 3 . 5 n o n o no C o r v i d a e C r o w s N A no" y e s m i x e d E m b e r i z i d a e S p a r r o w s N A -10.0 y e s y e s m i x e d F r i n g i l l i d a e F i n c h e s N A y e s y e s m i x e d ~~~~] H i r u n d i n i d a e S w a l l o w s N A >5.0 y e s y e s n o i I c te r idae '' B j a c k b i r d s N A y e s m i x e d 1 ? M e g a l u r i d a e 6 D o n a c o b i u s S A 1 4 . 5 n o no no j M i m i d a e M o c k i n g b i r d s N A 7 .2 . y e s y e s - n o • 1 M o t a c i l l i d a e P i p i t s N A 8 .2 y e s no no P a r u l i d a e • W a r b l e r s N A y e s y e s . m i x e d P o l i o p t i l i d a e G n a t c a t c h e r s ? N A y e s y e s m i x e d T h r a u p i d a e T a n a g e r s no y e s ' ' m i x e d • T r o g l o d y t i d a e W r e n s N A 1 3 . 8 y e s y e s m i x e d i T u r d i d a e T h r u s h i • ? 7 1 5 Cfy«s|jj y e s m i x e d 1 V i r e o n i d a e V i r e o s ? N A y e s y e s m i x e d 1 including Pittasoma traditionally considered a Formicariid. 2 including Oxyruncus 3 includes Grallaria, Grallariluca, Hylopezus, Myrmothera 4 includes Formicarius 5 not.a monophyletic group. Recently show to comprise 3 separate radiations, all of which participated in the GABI. These will likely be split into separate families or combined along with Dendrocolaptidae into an expanded family. 6 This enigmatic taxon has recently been shown to be sister to the Megaluridae. Whether it colonized South America via North America is unknown for certain. 7 Molecular phylogenies suggest this Old World family independently colonized North America from Eurasia and South America possibly from Africa. The earliest interchange date is presumed to have occurred from North America to South America. 8 Only one North American corvid (Corvus brachyrhynchos) undergoes a partial migration from northern parts of range 9 Very few clades of tanager have colonized the Caribbean. 104 Antbird H 1 1 1 1 1 1 h 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 0.2 0.16 + 0 1 2 3 4 5 6 7 9 10 11 12 13 14 Time (Ma) Fig 5.1 Dispersal rates between North and South American avifaunas. Rates estimated in 0.5 million year intervals to 4.0 Ma and 1 Ma from 4 to 14 Ma. Rates from South to North America shown by black circles. Rates from North American to South America shown by white circles. Final completion of the Central American Landbridge between 3 and 4 Ma shown by gray. 105 0 1 2 3 4 5 6 7 8 9 10 11 Time (Ma) Fig 5.2 Comparison between dispersal dates and rates between North and South American avian and mammalian faunas. Dispersal dates from North to South America shown in gray and South to North America in black. Dispersal rates from North to South America in blue (dotted line) and South to North America in red (solid line). Mammalian fossil dates taken from Marshall 1985, Campbell et al 2000, Flynn et al 2005. 106 o I 1 l 1 I 1 l 1 I 1 I 1 l 1 l 1 0 2 4 6 8 10 12 14 Time (Ma) Fig 5.3 First date of interchange in 16 passerine families involved in the Great American Biotic Interchange. Tropical forest specializing families shown in black, families not specializing in forest in white. 5.3 L I T E R A T U R E CITED Aleixo, A, 2002. 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Plenum Press, New York. Weir, J. T., and D. Schluter. 2004. Ice sheets promote speciation in boreal birds. Proc. R. Soc. Lond. B 271:1881-1887. Weir, J. T. 2006. Divergent timing and patterns of species accumulation in lowland and highland Neotropical birds. Evolution 60, 842-855. Weir, J.T. and D. Schluter. 2007. A latitudinal gradient in recent speciation and extinction rates in birds and mammals. Science in press. Wendt, T. 1993. Composition, floristic affinities, and origins of the canopy tree flora of the Mexican Atlantic slope rain forests. Pp. 595-680. in T. P. Ramamoorthy, R. Bye, A. Lot, and J. E. Fa, eds, Biological diversity of Mexico: origins and distribution. Oxford University Press, New York. I l l Chapter 6 GENERAL DISCUSSION In Chapter Two, I provide the first published estimates of speciation and extinction rates across a latitudinal gradient. Contrary to the view that sees the tropics as a "cradle of diversity", speciation rates were highest at high latitudes and declined towards the tropics. These results suggest that the hot-bed of evolution today is not in the Amazon where New World species diversity is highest, but rather occurs in high latitude depauperate faunas. Extinction rates were likewise elevated at high latitudes and declined towards the tropics supporting the view of the tropics as a "museum of diversity". If these estimates of speciation and extinction rates, obtained from sister species that diversified within the past 10 million years, are reflective of earlier time periods, then it would support the role of extinction as a primary factor driving the latitudinal diversity gradient. Low extinction rates estimated for equatorial faunas suggest that tropical faunas are more stable ecologically than at higher latitudes. While a number of factors may contribute to the stability of the tropics, the lack of intense long-term climatic fluctuations at tropical latitudes is a likely candidate. For example, paleo-temperature records estimated over the past several hundred thousand years support mean annual temperature fluctuations as great as 15°C at a high latitude site but only 3°C near the equator. The small variance in temperature fluctuations in the tropics is likely to have resulted in a climatically stable environment promoting low extinction rates. Nevertheless, previous authors have suggested that global climatic fluctuations of the Pleistocene may have fragmented lowland tropical rain forest, driving a burst of recent diversification. In Chapter Four I investigated the role of climatic change in promoting an increase in lowland tropical diversity. Only a small proportion of presently defined avian species diverged during the most intense periods of climate change. Neotropical lowland faunas exhibit a decline in diversification rates.through time rather than exhibiting an increase in rates during key periods of climatic fluctuation. These results support the emerging consensus from the paleopollen record in suggesting that global climatic fluctuations had 112 little impact on lowland tropical diversity. In contrast, highland Neotropical faunas exhibit a burst of diversification during the last one million years when the Andes and other Neotropical highland regions experienced a series of glacial advances and retreats and floral elevation zones were lowered by as much as 1000 m. The contrast suggests that those faunas which experienced the strongest climatic fluctuations have experienced the greatest impact on speciation rates. Like Andean faunas, high latitude boreal faunas experienced intense climatic fluctuations. A steady global cooling trend since the mid-Miocene (ca. 15 Ma) culminated in a series of intense climatic fluctuations during the past 2.5 million years when ice sheets expanded and retracted numerous times over North America. In Chapter Three I investigated the role of ice sheet advance in promoting recent speciation in boreal birds. Prior to 0.7 Ma these advances were limited in extent but were probably enough to cause a fragmentation of the boreal biome into an eastern and western sector when most east - west splits in boreal species date to. From 0.7 Ma to the present a series of major glacial advances covered most of Canada and parts of the northern United States resulting in further fragmentation of the boreal biome into a Pacific Coast, Rocky Mountain and eastern refugia. Most splits between Pacific Coast and Rocky Mountain boreal species occur at this time. The correlation between the extent of ice sheet advance and the diversification of boreal species in different parts of the boreal zone supports the direct role of glacial vicariance in promoting extensive speciation at high latitudes. Though a link between ice sheet advance and elevated extinction rate cannot be tested directly using our data, it appears likely that the same processes which promote rapid fragmentation and allopatric diversification of high latitude faunas would also promote a higher risk of extinction. Further analyses are necessary before a direct link between the strength of long-term climatic fluctuation and the intensity of extinction and speciation rates can be established. Due to the poor fossil record for birds, extensive phylogenetic information of high latitude species may be the only means by which extinction rates during different time periods of the Pleistocene glacial periods might be estimated. The connection between climatic instability and elevated high latitude extinction rates could be 113 confirmed if extinction rates during the past 0.7 Ma when ice sheet advance was most extensive were estimated to be higher than rates during earlier ice age periods. Additionally, while these results support the Evolutionary Hypothesis as an explanation for the Latitudinal diversity gradient they do not exclude the Ecological or Time Hypothesis. For example, the lower speciation rates estimated for tropical faunas may indicate tropical faunas are closer to their species carrying capacity than high latitude faunas. The fauna-wide decline in diversification rates in lowland but not highland tropical faunas estimated in Chapter Four provides preliminary evidence of density dependent cladogenesis and of a possible species carrying capacity. If diversity is ultimately governed by ecological resources then the diversification rates will only govern the speed at which a fauna approaches its carrying capacity but will not ultimately determine the species diversity of that fauna. Additional testing of carrying capacities are necessary. Why is the latitudinal diversity gradient strongest in New World avifaunas? Tropical avifaunas of the New World are more species diverse than other tropical faunas resulting in a steeper latitudinal gradient in species diversity. In Chapter Five I investigate the Great American Biotic Interchange which may have promoted this disparity between New World and Old World tropical diversity. While the completion of the Central American Landbridge ca. 3.5 Ma was known to have initiated a burst of interchange between the distinctive mammalian faunas of North and South America it was unknown if landbridge completion resulted in as dramatic faunal mixing in other taxonomic groups. I used molecular techniques to date over 100 interchange events in birds. Results suggest rates of interchange were significantly faster after landbridge formation in four large passerine families that straddle the New World tropics. However, landbridge completion had the greatest impact on tropical forest specializing families of South American origin. Such families colonized North America near the final completion of the landbridge and rates of interchange were more than 50 times faster after landbridge completion. Because interchange in many avian groups was impacted by formation of the Central American landbridge despite their volant capabilities, it appears likely that interchange in other taxonomic groups which lack volant capabilities was probably also 114 impacted by landbridge completion. These results suggest that Great American Biotic Interchange was a key feature in New World faunas and may have resulted in an almost instantaneous increase in diversity at tropical latitudes as a direct result of post landbridge faunal mixing. Further tests are necessary to determine if faunal mixing resulted in a net increase in species diversity or in widespread extinction of native faunal components. 115 APPENDIX 1 ADDITIONAL METHODS (a) DNA Sequencing Total genomic DNA was extracted from muscle or liver tissue using a Qiagen tissue extraction kit. A fragment of the mitochondrial cytochrome b was amplified using the primers L14990 (5' CCATCCAACATCTCMGCATGATGAAA) and H16065 (5' GGAGTCTTCAGTCTYTGGTTTACAAGAC). For the PCR reaction we used 0.2 mM dNTPs, 1.5 mM MgCk, 200 pM of each primer, 0.02 U/jtl Taq polymerase and 20 - 100ng//il of DNA. PCR conditions were as follows: denaturation at 93°C for 3 minutes, annealing between 50 and 55°C for 1 minute, extension at 72°C for 10 minutes. Amplified products where purified on Qiagen spin columns and sequenced using the BigDye cycle sequencing kit with the primer L14990. We sequenced one or more samples from each superspecies complex in the reverse direction using the primer H16065. Sequenced products where run on a ABI sequencer and aligned in Clustal X. Between 826 to 1006 bp of the sequenced product were used in each complex. Sequences generated for this study have been deposited in Genbank. (b) Sequences Used Sequences produced for this study are as follows. 1) Empidonax occidentalis (MVZ 167081) Custer Co., Colorado, USA (Genbank, AY309249). 2) Empidonax occidentalis (MVZ 167099) Apache Co., Arizona, USA (Genbank, AY309248). 3) Poecile rufescens (CVM 15432) Vancouver, British Columbia, Canada (Genbank, AY309247). 4) Vermivora (r.) ruficapilla (LSUMNS B-27333) Baton Rouge, Louisiana, USA (AY640935). 5) Vermivora uirginiae (UWBM 56395) Canon Qity, Colorado, USA (AY309246). 6) Vermivora (r.)ridgewayi (MVZ 173509) Plumas 116 Co., California, USA (AY309245). 7) Oporornis Philadelphia (KUNHM 2404) Topeka, Kansas, USA (AY309244). 8) Oporornis tolmiei (FMNH 393953), Jalisco, Mexico (Genbank, AY309242). 9) Oporornis tolmiei (FMNH 393954), Jalisco, Mexico (Genbank, AY309243). CVM = Cowan Vertebrate Museum, Vancouver; FMNH = Field Museum of Natural History, Chicago; LSUMNS = Louisiana State University Museum of Natural Science, Baton Rouge; KUNHM = Kansas University Natural History Museum; MVZ = Museum of Vertebrate Zoology, Berkley; UWBM = University of Washington Burke Museum, Seattle. Sequences (and Genbank accession numbers) used for the analysis of the boreal avifauna in Appendix 2 are as follows: Sphyrapicus AF123532, U83296; Empidonax AF447597, AF447598, AY143200, AY143201, AY309248, AY309249; Vireo AF81963, AF81964, AF81967, AF81970, AF81978, AF81981, AF81984, AF81987, AF81991, AF81993, AF82000, AF82001; Poecile AF347948-AF347950, AY309247; Catharus AY049490, AY049495, AY049496, AY049502, AY049503; Vermivora AF256510, AY309245, AY309246, AY640935; Oporornis AF383029, AY309242-AY309244; Passerella U40162-U40166, U40168-U40171, AY138920, AY138922-AY138924, AY138927-AY138929, AY138933, AY138934. Additional Sphyrapicus sequences where obtained from Cicero and Johnson (1995) and Dendroica sequences (two sequences for each of three species) were provided by Irby Lovette. Sequences used as outgroup taxa for phylogenetic analysis of superspecies complexes in Figure 3.1 are as follows: Sphyrapicus - S. thyroideus (1); Empidonax - E. flavescens (AY143191, AF447599, AF447600); Vireo - V flavifrons (AF081961, AF081962); Poecile - P. sclateri (AF347947), P. cincta (AF347950), P. gambeli (AF347938), and P. atricapillus (AF347937); Vermivora - V. celata (AF489902, AY030123); Oporornis - O. formosus (AF383017) and Geothlypis trichas (AF383003); Passerella - Junco hyemalis U l (U26199, AY138936 ), Zonotrichia capensis (U40174, AF383139), Spizella arborea (U26190, AY138925) and Pipilo chlorurus (U26201, AY138935); Dendroica - D. adelaidae (AF256504). Sequences used for the Sub-boreal avifauna are as follows: Aphelocoma U77335, AY030116; Callipepla AF028759, AF028762, AF028765, AF028768, AF028771; Chaetura AF168105, CVU50029, CVU50030; Contopus AF447607-AF447610; Icterus spurius group AY211197-AY211215; Icterus galbula group AF099290, AF099309; Megascops AF115864, AF294997, AJ004016; Polioptila AF027840-AF027843; Parula AY030122, AF256502, AF256503, AF256509; Picoides AF389322, AF389323, AF389326, AF389327; Pipilo AF092887, AF284075; Piranga AF290146, AF011759, AF011760, AF011773, AF011774; Quiscalus AF089055, AF089056, AF290171; Sturnella AF089063, AF089064, AF290164; Toxostoma AF130235, AF130237, AF130238, AF130240, AF287541, AF130242, AF287548, AF287560; Tympanuchus AF230179, AF230180; Vireo AF081960, AY030111. Sequences used for the Neotropical avifauna (Figure 3.3, Appendix 2) are as follows: Agelaius AF089005, AF089013, AF290174; Cacicus AY117700-AY117704; Columbina AF182683, AF182684, AF483347; Cranioleuca AF053780-AF053782; Icterus icterus AF099296, AF099297, AF089031; Megascops AJ3904, AJ4039, AJ4040, AF295003, AF295004; Petrochelidon AF182380 AF182381 AF182388-AF182391; Psarcolius AF089053, AF472377-AF472381; Ramphocelus AF310048, RCU15723, U15717, U15719, U15720, U15722, U15724; Selenidera AF100552, AF123517, AF123518; Tachycineta AY052445-AY052448; Xiphorhynchus AY089791-AY089794, AY089799-AY089801, AY089803, AY089805, AY089807, AY089808, AY089812, AY089814- AY089816, AY089820, AY089824, AY089826, AY089827, AY089828, AY089830- AY089832; Zenaida AF182699, AF251533, AF251534. Literature Cited 118 Cicero, C. and Johnson, N. K. 1995 Speciation in sapsuckers (Sphyrapicus): III. Mitochondrial-DNA sequence divergence at the cytochrome-b locus. Auk 112, 546-563. 119 APPENDIX 2 Molecular based estimates of divergence dates for members of New World superspecies complexes. Taxa Comparison GTR-gamma Divergence (Standard Deviation) Coalescence Date Data a) Boreal superspecies Sphyrapicus varius versus S. nuchalis / S. ruber Sphyrapicus nuchalis versus S. ruber Empidonax occidentalis versus E. difficilis Vireo plumbeus versus V. solitarius / V. cassinii Vireo solitarius versus V. cassinii Poecile hudsonica versus P. rufescens Catharus minimus versus C. bicknelli Vermivora (r.) ruficapilla versus V. virginiae / V. (r.) ridgwayi Vermivora virginiae versus V. (ruficapilla) ridgwayi Dendroica virens versus D. townsendi / D. occidentalis Dendroica townsendi versus D. occidentalis Oporornis Philadelphia versus O. tolmiei Passerella (i.) iliaca versus P. (i.) schistacea, P. (i.) megarhyncha and P. (i.) unalaschensis Passerella (i.) schistacea versus P. (i.) megarhyncha and P. (i.) unalaschensis Passerella (i.) megarhyncha versus P. (i.) unalaschensis b) Sub-boreal superspecies Tympanuchus pallidicinctus versus T. cupido Callipepla californica versus C. gambelii Megascops asio versus M. kennicottii Picoides nuttailii versus P. scalaris Contopus sordidulus versus V. virens Aphelocoma californica versus A. coerulescens Vireo gilvus versus V. leucophrys Toxostoma cinereum versus T. bendirei Toxostoma curvirostre versus T. ocellatum Parula americana versus P. pitiayumi Piranga ludoviciana versus P. bidentata Pipilo maculatus versus P. erythrophthalmus Quiscalus major versus Q. mexicanus Icterus galbula versus /. abeillei 2.40% (± 0.11%) 0.71 % (± 0.00%) 0.87% (± 0.14%) 3.23% (± 0.31%) 2.96% (± 0.17%) 3.60% (± 0.05%) 1.12% (± 0.22%) 2.14% (± 0.53%) 2.01% (±0.19%) 2.37% (± 0.16%) 0.95% (± 0.12%) 2.49% (± 0.07%) 1.69% (± 0.22%) 1.57% (± 0.21%) 1.59% (± 0.22%) 0.50% 2.46% (± 0.17%) 9.37% (± 2.12%) 1.05% (± 0.13%) 1.97% (± 0.14%) 5.68% . 6.66% 1.46% 6.59% (± 0.50%) 4.68% (± 0.00%) 5.38% (± 0.33%) 1.20% 3.06% (± 0.00%) 0.81% 1,090,000 711bpCytB 320,000 390,000 1,470,000 1,350,000 1,640,000 510,000 970,000 910,000 1,080,000 430,000 1,130,000 770,000 720,000 720,000 711 bp C y t B 1006 bp Cyt B 1143 bp C y t B 1143 bp Cy tB 1001 bp Cy tB 1066 bp Cyt B 961 bp C y t B 961 bp C y t B 1143 bp Cyt B 1143 bp Cy tB 946 bp Cyt B 433 bp C y t B , 1030 bp ND2 434 bp C y t B , 1030 bp ND2 435 bp C y t B , 1030 bp ND2 250,000 609 bp Cyt B 1,230,000 4,690,000 530,000 990,000 2,840,000 3,330,000 730,000 3,300,000 2,340,000 2,690,000 600,000 1,530,000 410,000 699 bp Cyt B 395 bp Cyt B 1028 bp Cyt B 1143 bp Cy tB 1143 bp Cy tB 1143 bp Cy tB 433 bp Cyt B 433 bp Cyt B 1143 bp Cy tB 1073 bp Cyt B 433 bp Cyt B 881 bp Cy tB 876 bp Cyt B 120 Icterus spurius versus /. fuertesi Sturnella neglecta versus S. magna 0.19% (± 0.10%)* 4.82% (± 0.00%) 100,000 2,410,000 925 bp Cyt B 893 bp Cyt B c) Lowland Tropical superspecies Zenaida asiatica versus Z. meloda 5.14% (± 0.05%) 2,570,000 1045 bp C y t B Columbina squammata versus C. inca 3.16% (± 0.22%) 1,580,000 1039 bp Cyt B Selenidera maculirostris versus 5. gouldii 2.00% 1,000,000 925 bp Cyt B Megascops usta versus M. watsonii 1.73% (± 0.63%) 865,000 393 bp Cyt B Xiphorhynchus spixii versus X. elegans 5.34% (± 0.17%) 2,670,000 1003 bp Cyt B Xiphorhynchus chunchotambo versus X. 5.63% (± 0.62%) 2,820,000 964 bp Cyt B pardalotus /X. ocellatus Xiphorhynchus pardalotus versus X. 4.03% (± 038%) 2,020,000 964 bp Cyt B ocellatus Xiphorhynchus erythropygius versus X. 5.81% (± 0.68%) 2,910,000 965 bp Cyt B triangularis Xiphorhynchus guttatoides versus X. 7.25% (± 0.83%) 3,630,000 1006 bp Cyt B guttatus / susurrans Xiphorhynchus guttatus versus X. 4.39% (± 0.06%) 2,200,000 1022 bp Cy tB susurrans Xiphorhynchus lachrymosus versus X. 4.74% (± 0.57%) 2,370,000 968 bp Cyt B flavigaster Cranioleuca pyrrhophia versus C. obsoleta 2.06% (± 1.26%) 1,030,000 209 bp C y t B Tachycineta albiventer versus T. albilinea 6.97% 3,490,000 936 bp Cyt B Tachycineta meyeni versus T. leucorrhoa 4.12% 2,060,000 913 bp C y t B Petrochelidon fulva versus P. rufocolaris 1.97% (± 0.13%) 990,000 921 bp C y t B Ramphocelus carbo versus R. bresilius 4.35% (± 0.49%) 2,180,000 1045 bp Cyt B Ramphocelus flammigerus versus R. 5.69% (± 0.26%) 2,850,000 1045 bp Cyt B passerinii /R. costaricensis Ramphocelus passerinii versus R. 1.67% (± 0.08%) 840,000 1045 bp Cyt B costaricensis Agelaius cyanopus versus A. 0.57% (± 0.00%) 290,000 879 bp Cyt B xanthophthalmus Icterus icterus versus I. jamacaii /1. 4.72% (± 0.60%) 2,360,000 890 bp Cyt B croconotus Icterus jamacaii versus /. croconotus 1.96% 980,000 890 bp Cyt B Cacicus cela versus C. vitellinus 4.86% (± 0.13%) 2,430,000 906 bp Cyt B Psarocolius montezuma versus P. 1.76% (± 0.16%) 880,000 920 bp Cyt B bifasciatus / P. yuracares Psarocolius bifasciatus versus P. 0.87% (± 0.04%) 440,000 920 bp Cyt B yuracares 121 A P P E N D I X 3 Species, genes and Genbank accession numbers for mitochondrial DNA sequences used in Chapter 4. The outgroup taxon used to root trees is shown in bold. Abbreviations as follows: Cyt B, cytochrome B; ND2, NADH dehydrogenase subunit 2; ND3, NADH dehydrogenase subunit 3; ND5, NADH dehydrogenase subunit 5; COI, cytochrome c oxidase subunit I; COLI, cytochrome c oxidase subunit U; ATPase 6 and 8, ATPase 6 and ATPase 8. Taxon Gene Ingroup species and Genbank Accession Numbers Outgroup species and Genbank Accession Numbers Anairetes 632 bp C y t B andND2 C v t B : agilis: AF067007, alpinus: AF067004, fernandezianus: AF067001, flavirostris: AF067006, nigrocristatus: AF067005, parulus: AF067002, reguloides: AP067003 ND2: Agilis: AF066998, alpinus: AF066995, fernandezianus: AF066992, flavirostris: AF066997, nigrocristatus: AF066996, parulus: AF066993, reguloides: AF066994 CvtB: Cnemotriccus fuscatus: AF447622, Empidonax wrightii: AY143208, Stigmatura napensis: AF067000 ND2: Cnemotriccus fuscatus: AF447649, Empidonax wrightii: AY143235, Stigmatura napensis: AF066999 Amazon 562 bp COI aestiva: AY301425, AY301424, AY194367, AF370743, AF370742, agilis: AY301426, albifrons: AY301428, AY301427, AY301429, amazonica: AY301430, AY194399, arausiaca: AY301431, auropalliata: AY301432, AY301433, autumnalis: AY301434, AY301435, AY194379, barbadensis: AY301436, AY194403, brasiliensis: AY301437, collaria: AY301438, dufresniana: AY301439, farinosa: AY301443, AY301441, AY301442, AY301440, AY194394, festiva: AY301444, finschi: AY301445, guildingii: AY301446, imperialis: AY301447, kawalli: AY301448, leucocephala: AY301449, ochrocephala: AY301452, AY301453, AY301450, AY301451, oratrix: AY301456, AY301454, AY301455, pretrei: AY301457, rhodocorytha: AY301458, tucumana: AY301459, ventralis: AY301460, versicolor: "Amazona" xanthops: AY301465, Ara ararauna: AY301467, Ara severa: AF370747, Aratinga auricapilla: AY301466, Aratinga cactorum: AF370750, Aratinga leucophthalmus: AF370749, Graydidascalus brachyurus: AY301468, Pionus menstruus: AY301469, Poicephalus gulielmi: AY301470, Psittacus erithacus: AY301471 AY301461, vinacea: AY301462, viridigenalis: AY301463, vittata: AY301464 Carduelis 926 bp C y t B atrata: L76385, barbata: L77868, crassirostris: L77869, cucullata: L76299, magellanica: AF310066, U79016 notata: U79019, olivacea: L77871, spinescens: U79017, xanthogastra: L76389, yarrellii: U83200 cannabina: L76298, carduelis: L76388, lawrencei: L76392, pinus: U79020, psaltria: L76390, U78324, spinus: L76391, tristis: U79022 Cinclodes 684 bp con antarcticus: AY613373, aricomae: AY613374, atacamensis: AY613375, comechingonus: AY613377, AY613376, excelsior: AY613378, fuscus: AY613380, AY613379, nigrofumosus: AY613381, olrogi: AY613383, AY613382, oustaleti: AY613385, AY613384, pabsti: AY613386, palliatus: AY613387, patagonicus: AY613388, taczanowski: AY613389 Synallaxis spixi: AY613370, Upucerthia dumeteria: AY613371, Upucerthia validirostis: AY613372 Cranioleuca 508 bp C y t B ND2 C y t B : albicapilla: AF053794, albiceps: AF053800, antisiensis: AF053791, baroni: AF053790, AF053789, curtata: AF053925, demissa: AF053793, erythrops: AF053792, henricae: AF053798, marcapatae: AF053799, obsoleta: AF053797, pyrrhophia: AF053796, AF053795, vulpina: AF053801 ND2: albicapilla: AF053811, albiceps: AF053817, antisiensis: AF053807, baroni: AF053805, AF053806, curtata: AF053808, demissa: AF053810, erythrops: AF053809, henricae: AF053815, marcapatae: AF053816, obsoleta: AF053814, pyrrhophia: AF053812, AF053813, vulpina: AF053818, CvtB:Asthenes dorbignvi: AF053803, Hellmavrea gularis: AF053802, Synallaxis albescens: AF118186 ND2: Asthenes dorbignyi: AF053820, Hellmayrea gularis: AF053819, Synallaxis albescens: AF118220 Crax 1003 bp C y t B Crax alberti: AY141920, Crax alector: AY141921, Crax blumenbachii: AF165468, Crax daubentoni: AY141922, Crax fasciolata: AY141923, Crax globulosa: AY141924, Crax mitu: AY141926, Crax pauxi: AF068190, AF165473, Crax rubra: AY141925, Crax salvini: AY141927, Crax tomentosa: AY141928, Crax tuberosa: AF165469, Crax unicornis: AY141929, Nothocrax urumutum: AF165470 Aburria aburri: AF165466, Alectura lathami: AF082058, Anhima cornuta: AY140735, Chamaepetes goudotii: AF165467, Chauna torquata: A Y 140736, Megapodius eremita: AF082065, Megapodius reinwardt: AF165465, Oreophasis derbianus: AF165471, Ortalis canicollis: AF165472, Ortalis vetula: L08384, Penelope obscura: AF165474, Penelopina nigra: AF165475, Pipile jacutinga: AF165476 Hemispingus 301 bp ND2 atropileus: AY039290, auricularis: AY039291, AF383135,calophrys: AY039300, frontalis: AY139640, AF447285, AF383136, AY039292, melanotis: AY039293, parodii: AY180913, piurae: AY039294, rufosuperciliaris: AY039297,superciliaris: AY039298, trifasciatus: AY039299, verticalis: AY039296, xanthophthalmus: AY039295 Basileuterus luteoviridis: AY039289, Cissopis leveriana: AY383169, Chlorochrysa calliparaea: AY383168 Metallura 856 bp C y t B , ND2 and ND5 C y t B : aeneocauda: AF022666, baroni: AF022661, eupogon: AF022665, odomae: AF022663, phoebe: AF022662, theresiae: AF022664, tyrianthina: AF022668, AF022669, AF022670, AF022671, AF022672, AF022667, williami: AF022659, (williami) primolinus: AF022660 ND2: aeneocauda: AF022683, baroni: AF022678, eupogon: AF022682, odomae: AF022680, phoebe: AF022679, theresiae: AF022681, tyrianthina: AF022685, AF022686, AF022687, AF022688, AF022689, AF022684, williami: AF022676, (williami) primolinus: AF022677 ND5: aeneocauda: AF022700, baroni: AF022695, eupogon: AF022699, odomae: AF022697, phoebe: AF022696, theresiae: AF022698, tyrianthina: AF022703,AF022704, AF022705, AF022706, AF022707, AF022702, williami: AF022693, (williami) primolinus: AF022694 Cy tB : Chalcostigma herrani: AF022674, Chalcostigma ruficeps: AF022673 ND2: Chalcostigma herrani: AF022691, Chalcostigma ruficeps: AF022690 ND5: Chalcostigma herrani: AF022709, Chalcostigma ruficeps: AF022673 Muscisaxicol a 1038 bp ND3 and con N D 3 : albifrons: AF132646, AF132647, albilora: AF132648, AF132649, alpina: AF132650, (alpina) grisea: AF132651, capistrata: AF132652, AF132653, cinerea: AF132654, AF132655, flavinucha: AF132656, AF132657, fluviatilis: AF132658, frontalis: AF132659, AF132660, juninensis: AF132661, macloviana: AF132662, AF132663, maculirostris: AF132664, AF132665, rufivertex: AF132666, AF132667 COII: albifrons: AF132620, AF132619, albilora: AF132622, AF132621,alpina: AF132623, (alpina) grisea: AF132624, capistrata: AF132626, AF132625, cinerea: AF132628, AF132627, flavinucha: AF132630, AF132629, fluviatilis: AF132631, frontalis: AF132633, AF132632, juninensis: AF132634, macloviana: AF132636, AF132635, maculirostris: AF132638, AF132637, rufivertex: AF132640, AF132639 NDIII : Muscigralla brevicauda: AF132645, Agriornis montana: AF132644, Xolmis pyrope: AF132643, Lessonia rufa: AF132642, Tyrannus melancholicus: AF132641 COII: Muscigralla brevicauda: AF132618, Agriornis montana: AF132617, Xolmis pyrope: AF132616, Lessonia rufa: AF132615, Tyrannus melancholicus: AF132614 Ochthoeca 321 bp ND2 Garcia-Moreno unpublished sequences (only the lowland Ochthoeca sqlvini excluded) Aphanotriccus audax: AF447648, AF447647, Cnemotriccus fuscatus: AF447649, Empidonax minimus: AY030125, Mitrephanes phaeocercus: AF447646, Stigmatura napensis: AF066999 Troglodytes 513 bp ND2 Troglodytes (Thryorchilus) browni: AF104974, Troglodytes aedon: AY460233, AF104980, AF104979,Troglodytes brunneicollis: AF104973, Troglodytes musculus: AF104978, Troglodytes ochraceus: AF104982, Troglodytes rufociliatus: AF104977, Troglodytes rufulus: AF104983, Troglodytes sissonii: AY465888, Troglodytes solstitialis: AY460232 Cistothorus platensis: AY465889, Troglodytes troglodytes: AF104976, AY460313 Icterus 1946 bp Cytb andND2 C y t B : abeillei: AF099309, auratus: AF099276, auricapillus: AF099310, bonana: AF099277, bullockii: AF089029, AF099278, cayanensis: AF089027, AF099279, AF099280, AF290166, AF089028, chrysater: AF099281, AF099282, cucullatus: AF099283, AF099284, dominicensis: AF099285, AF099286, AF099287, AF099288, fuertesi AF099307, galbula: AF099290, graceaneae: AF089030, graduacauda: AF099291, AF099292, gularis: AF099293, AF099294, AF099295, icterus: AF099296, jamacaii: AF089031, AF099297, laudabilis: AF099298, leucopteryx: AF089032, maculialatus: AF099299, mesomelas: AF089033, AF099300, AF099301, nigrogularis: AF089034, AF099302, oberi: AF099303, parisorum: AF089035, pectoralis: AF099304, prosthemalis: AF099289, pustulatus: AF099305, AF099306, spurius: AF089036, wagleri: AF099308 ND2: abeillei: AF099311, auratus: AF099312, bonana: AF099313, bullockii: AF099314, AF099315, cayanensis: AF099316, AF099318, AF099319, chrysater: AF099320, AF099321, cucullatus: AF099322, AF099323, dominicensis: AF099324, AF099325, AF099326, prosthemelas AF099327, galbula: AF099328, graceaneae: AF099329, graduacauda: AF099330, AF099331, gularis: AF099332, AF099333, AF099334, icterus: AF099335, jamacaii: AF099336, AF099337, laudabilis: AF099338, leucopteryx: AF099339, maculialatus: AF099340, mesomelas: AF099341, AF099342, AF099343, nigrogularis: AF099344, AF099345, oberi: AF099346, parisorum: AF099347, pectoralis: AF099348, AF099349, AF099350', fuertesi: AF099351, spurius: AF099352, wagleri: AF099353 C y t B : Cacicus (c.) vitellinus: AY117704, Cacicus chrysonotus: AY117717, Ocyalus latirostris: AF472382, Psarocolius bifasciatus: AY117699, Psarocolius viridis: AY117698, Sturnella magna: AF089063 ND2: Cacicus (c.) vitellinus: AY117732, Cacicus chrysonotus: AY117745, Ocyalus latirostris: AF472407, Psarocolius bifasciatus: AY117727, Psarocolius viridis: AY117726, Sturnella magna: AF447307 Dendrocincl a 999 bp C y t B [Genbank numbers will be placed here.] /Genbank numbers will be placed here.] Pionopsitta 1306 bp C y t B , COI C v t B : coccinicolaris: AY661236, haematotis: AY661237, pulchra: AY661239, aurantiigena: AY661234, caica: AY661235, vulturina: AY661233, pileata: AY661238 COI: coccinicolaris: AY661224, haematotis: AY661222, pulchra: AY661230, barrabandi: AY661215, aurantiigena: AY661214, caica: AY661220, vulturina: AY661212, pileata: AY661227 C v t B : Pionus chalcopterus: AY661240 COI: Pionus chalcopterus: AY661232 Psarocolius 898 bp C y t B Cacicus (cela) cela: AY117703, Cacicus (cela) vitellinus: AY117704, Cacicus chrysonotus: AY117716, AY117717, Cacicus (chrysonotus) leucoramphus: AF089017, AY117715, Cacicus (u.) pacificus: AY117710, AY117707, Cacicus uropygialis: AY117708, Cacicus haemorrhous: AY117706, Cacicus melanicterus: AF472384, Cacicus sclateri: AY117718, Cacicus solitarius: AF089018, AF472385, Ocyalus latirostris: AF472382, Psarocolius angustifrons: AF472364, AF472365, AY117697, Psarocolius atrovirens: AF472367, Psarocolius decumanus: AF472371, AF472372, AF472373, AF472376, Psarocolius montezuma: AF472377, AF472378, Psarocolius oseryi: AF472383, Psarocolius viridis: AY117698, Psarocolius wagleri: AF472368, AF472370, Psarocolius bifasciatus: AF089053, AY117699 Amblycercus holosericeus: AY117723, AY117724, Icterus gularis: AF099293, Icterus jamacaii: AF099297, Molothrus aeneus: AF089040 Pteroglossus 2168 bp C y t B , COI, ATPase 6 and 8 C y t B : Pteroglossus bitorquatus: AY661376, Pteroglossus flavirostris: AY661379, Pteroglossus mariae: AY661382, Pteroglossus beauharnaesii: AY661375, Pteroglossus torquatus: AY661386, Pteroglossus torquatus: AY661385, Pteroglossus sanguineus: AY661384, Pteroglossus erythropygius: AY661378, Pteroglossus aracari: AY661374, Pteroglossus pluricinctus: AY661383, Pteroglossus castanotis: AY661377, Pteroglossus viridis: AY661387, Pteroglossus inscriptus: AY661381, Pteroglossus inscriptus: AY661380, Baillonius bailloni: AY661373 COI: Pteroglossus bitorquatus: AY661309, Pteroglossus flavirostris: AY661316, Pteroglossus mariae: AY661323, Pteroglossus beauharnaesii: AY661307, Pteroglossus torquatus: AY661332, Pteroglossus torquatus: AY661330, Pteroglossus sanguineus: C y t B : Selenidera culik: AY661372 COI: Selenidera culik: AY661337 ATPase 6: Selenidera culik: AY661300 ATPase 8: Selenidera culik: AY661371 AY661328, Pteroglossus erythropygius: AY661313, Pteroglossus aracari: AY661305, Pteroglossus pluricinctus: AY661326, Pteroglossus castanotis: AY661312, Pteroglossus viridis: AY661336, Pteroglossus inscriptus: AY661321, Pteroglossus inscriptus: AY661318, Baillonius bailloni: AY661304 ATPase 6: Pteroglossus bitorquatus: AY661272, Pteroglossus flavirostris: AY661279, Pteroglossus mariae: AY661286, Pteroglossus beauharnaesii: AY661270, Pteroglossus torquatus: AY661295, Pteroglossus torquatus: AY661293, Pteroglossus sanguineus: AY661291, Pteroglossus erythropygius: AY661276, Pteroglossus aracari: AY661268, Pteroglossus pluricinctus: AY661289, Pteroglossus castanotis: AY661275, Pteroglossus viridis: AY661299, Pteroglossus inscriptus: AY661284, Pteroglossus inscriptus: AY661281, Baillonius bailloni: AY661267 ATPase 8: Pteroglossus bitorquatus: AY661344, Pteroglossus flavirostris: AY661350, Pteroglossus mariae: AY661357, Pteroglossus beauharnaesii: AY661342, Pteroglossus torquatus: AY661366, Pteroglossus torquatus: AY661364, Pteroglossus sanguineus: AY661362, Pteroglossus erythropygius: AY661347, Pteroglossus aracari: AY661340, Pteroglossus pluricinctus: AY661360, Pteroglossus castanotis: AY661346, Pteroglossus viridis: AY661370, Pteroglossus inscriptus: AY661355, Pteroglossus inscriptus: AY661352, Baillonius bailloni: AY661339 Myiarchus 842 bp ATPase 6 and 8 antillarum: AY115182, AY115181, barbirostris: AY266207, AF497962, cephalotes: AY266183, crinitus: AY266197, ferox: AY266196, AY266189, AF497965, oberi: AY115179, AY115173, panamensis: AF497959, phaeocephalus: AY266171, AF497964, swainsoni ("species" 1): AF497955, swainsoni ("species" 2): AF497956, AF497913, AF497950, AF497954, AF497953, sagrae: AY266205, AY266204, AY266203, semirufus: AY266170, stolidus: AY266202, AY266201, AY266200, tuberculifer: AY266174, AY266173, AY266172, AF497961, AF497960, tyrannulus: AY266217, AY266208, AY115171, validus: AY266206, venezuelens: Tyrannus melancholicus: AY266226, Tyrannus caudifasciatus: AF497968, Elaenia martinica: AY082541 AY266182, yucatanensis: AY266181 Nyctibius 656 Cyt B aethereus: X95781, bracteatus: X95765, grandis: X95766, griseus: X95767, leucopterus: X95768, maculosus: X95769 Aegotheles cristatus: X95775, Chordeiles rupestris: X95778, Eurostopodus papuensis: X95780, Phalaenoptilus nuttallii: X95770, Steatornis caripensis: X95773 Ramphocelu s 1046 bp C y t B bresilius: U15724, carbo: U15723, AF310048, icteronotus: U15719, nigrogularis: U15721, passerinii: U15717, U15722, U15720, sanguinolentus: U15718 Eucometis penicillata: AY228059, Plectrophenax nivalis: AY156449,Tangara seledon: AY228083 South American Blackbird clade 906 bp C y t B Agelaius cyanopus: AF089005, Agelaius flavus: AF089066, Agelaius icterocephalus: AF089007, Agelaius ruficapillus: AF089009, Agelaius thilius: AF089010, Agelaius xanthophthalmus: AF089013, Amblyramphus holosericeus: AF089014, Curaeus curaeus: AF089020, Gnorimopsar chopi: AF089025, Gymnomystax mexicanus: AF089026, Lampropsar tanagrinus: AF089037, Macroagelaius imthurni: AF089039, Molothrus badius: AF089042, Oreopsar bolivianus: AF089046, Pseudoleistes guirahuro: AF089051, Pseudoleistes virescens: AF089052 Agelaius humeralis: AF089006, Agelaius phoeniceus: AF089004, Agelaius tricolor: AF089011, Agelaius xanthomus: AF089012, Dives warszwewiczi: AF089021, Euphagus carolinus: AF089023, Euphagus cyanocephalus: AF089024, Icterus abeillei: AF099309, Molothrus aeneus: AF089040, Molothrus ater: AF089041, Molothrus bonariensis: AF089043, Molothrus rufoaxillaris: AF089044, Nesopsar nigerrimus: AF089045, Psarocolius decumanus: AF472373, Quiscalus lugubris: AF089054, Quiscalus major: AF089055, Quiscalus mexicanus: AF089056, Quiscalus niger: AF089057, Quiscalus quiscula: AF089058, Scaphidura oryzivora: AF089060 Tachycineta 908 bp C y t B albilinea: AY052445, albiventer: AY052446, bicolor: AF074585, cyaneovirids: AY052450, euchrysea: AY052451, leucorrhoa: AY052447, meyeni: AY052448, stolzmanni: AY052444, thalassina: AY052449 Atticora fasciata: AF074584, Hirundo rustica: AF074577, Neochelidon tibialis: AF074590, Notiochelidon cyanole: AF074586, Phaeoprogne tapera: AF074588, Progne chalybea: AF074583, Progne subis: AY052443, Riparia cincta: AF074580, Riparia riparia: AF074578, Stelgidopteryx ruficollis: AF074589 Trogon 1143 bp C y t B collaris: U94808, comptus: U94804, curucui: U94801, elegans: U94806, melanocephalus: AY275863, melanurus: U94805, mexicanus: U94809, personatus: U89201, rufus: U94807, violaceus: U94802, viridis: U94803. Euptilotis neoxenus: U89203, Harpactes oreskios: U89199, Pharomachrus pavoninus: U94800, Priotelus temnurus: U89202 Xiphorhynch us 1096 bp C y t B chunchotambo: AY089793, AY089815, elegans elegans: AY089805, elegans juruanus: AY089824, elegans ornatus: AY089812, erythropygius: AY442997, AY089830, AY089832, flavigaster: AY089828, AY089799, fuscus: AY442993, AY089819, guttatus: AY442998, AY089816, AY089814, AY089808, AY089803, AY089794, AY089792, AY089791, kienerii: AY089818, lachrymosus: AY089807, obsoletus: AY443000, AY089823, ocellatus ocellatus: AY089804, ocellatus weddellii: AY089820, Campyloramphus falcularius: AY089810, Campyloramphus procurvoides: AY089795, Campyloramphus trochilirostris: AY089822, Campylorhamphus pusillus: AY442988, Campylorhamphus trochilirostris: AY442987, Dendrocincla merula: AY442986, Dendrocincla taunayi: AY065713, Dendrocincla tyrannina: AY442985, Drymornis bridgesii: AY065711, Lepidocolaptes affinis: pardalotus: AY089831, picus: AY089821, AY089813, AY089802, AY089790, spixii: AY089801, susurrans: AY089800, triangularis: AY442999, AY089827, AY089826 AY442994, Lepidocolaptes albolineatus: AF045745, Lepidocolaptes angustirostris: AY078175, AY089811, Lepidocolaptes souleyetii: AF045743, Lepidocolaptes squamatus: AF045747, Lepidocolaptes wagleri: AF045748, Sittasomus griseicapillus: AY065714 Geositta 854 bp Cytb, ND2, ND3 C y t B : antarctica: AY695011, AY695012, crassirostris: AY695020, AY695028, cunicularia: AY695010, AY695021, AY695022, AY695023, isabellina: AY695015, maritima: AY695016, peruviana: AY695017, punensis: AY695019, ruficauda: AY695025, rufipennis: AY695026, saxicolina: AY695029, tenuirostris: AY695018, Geobates poeciloptera: AY695013, AY695014, AY695027 ND2: antarctica: AY694991, AY694992, crassirostris: AY695000, AY695008, cunicularia: AY694990, AY695001, AY695002, . AY695003, isabellina: AY694995, maritima: AY694996, peruviana: AY694997, punensis: AY694999, ruficauda: AY695005, rufipennis: AY695006, saxicolina: AY695009, tenuirostris: AY694998, Geobates poeciloptera: AY695007, AY694994, AY694993 ND3: antarctica: AY694991, AY694992, crassirostris: AY695000, AY695008, cunicularia: AY694990, AY695001, AY695002, AY695003, isabellina: AY694995, maritima: AY694996, peruviana: AY694997, punensis: AY694999, ruficauda: AY695045, rufipennis: AY695006, saxicolina: AY695009, tenuirostris: AY694998, Geobates poeciloptera: AY694993, AY694994, AY695007 C y t B : Aphrastura spinacauda: AY695024, Upucerthia ruficauda: AY695025 ND2: Aphrastura spinacauda: AY695004, Upucerthia ruficauda: AY695005 ND3: Aphrastura spinacauda: AY695004, Upucerthia ruficauda: AY695005 Neotropical Swallow clade 1950 bp C y t B and ND2 C y t B : Alopochelidon fucata: AY825943, Atticora fasciata: AF074584, Atticora melanoleuca: AY825954, Haplochelidon andecola: AY825980, Neochelidon tibialis: AF074590, Notiochelidon cyanoleuea: AF074586, Notiochelidon flavipes: AY825952, Notiochelidon murina: AY825951, Notiochelidon pileata: AY825953, Phaeoprogne tapera: AF074588, Progne chalybea (South American "species"): AF074583, Progne chalybea (Central American "species"): AY825948, Progne cryptoleuca: AY825945, Progne dominicensis: C y t B : Riparia paludicola: AY825957, Riparia riparia: AF074578 N D 2 : Riparia paludicola: AY826016, Riparia riparia: AY826015 AY825946, Progne elegans: AY825949, Progne murphyi: AY825950, Progne sinaloae: AY825947, Progne subis: AY052443, Stelgidopteryx ruficollis: AF074589, Stelgidopteryx serripennis: AY825955 C v t B : Alopochelidon fucata: AY826009, Atticora fasciata: AY826006, Atticora melanoleuca: AY826007, Haplochelidon andecola: AY826010, Neochelidon tibialis: AY826008, Notiochelidon cyanoleuca: AY826003, Notiochelidon flavipes: AY826004, Notiochelidon murina: AY826002, Notiochelidon pileata: AY826005, Phaeoprogne tapera: AY826001, Progne chalybea (South American "species"): AY825999, Progne dominicensis: AY825998, Progne elegans: AY826000, Progne subis: AY825996, Stelgidopteryx ruficollis: AY826012, Stelgidopteryx serripennis: AY826011 Veniliornis 2353 bp C y t B , COI C y t B : Veniliornis affinis: AY927209, Veniliornis callonotus: AF389336, AY942892, Veniliornis cassini: AY927210, Veniliornis chocoensis: AY927211, Veniliornis dignus: AY927212, AY927213, Veniliornis frontalis: AY927214, AY927215, Veniliornis kirkii: AY927218, Veniliornis nigriceps: AF389337, AY942893, Veniliornis passerinus: AY927219, AY927220, Veniliornis spilogaster: AY927221, AY927222, Picoides mixtus: AF389320, AF389321, Picoides lignarius: AF389314 COI: Veniliornis affinis: AY927189, Veniliornis callonotus: AF394305, AY942879, Veniliornis cassini: AY927190, Veniliornis chocoensis: AY927191, Veniliornis dignus: AY927192, AY927193, Veniliornis frontalis: AY927194, AY927195, Veniliornis fumigatus: AY927196, AY927197, Veniliornis kirkii: AY927198, Veniliornis nigriceps: AF394306, AY942880, Veniliornis passerinus: AY927199, AY927200, Veniliornis spilogaster: AY927201, AY927202, Picoides mixtus: AF394290, AF394291, Picoides lignarius: AF394284 Cy tB : Campephilus haematogaster: AY942882, Capito niger: AY940799, Colaptes auratus: AY942881, Dendrocopos kizuki: AF389310, AF389311, Dendropicos griseocephalus: AY942884, Indicator variegatus: AY940802, Jynx torquilla: AY940803, Melanerpes carolinus: AY942886, Picoides albolarvatus: AF389302, AF389303, AY942887, Picoides arcticus: AF389304, AF389305, Picoides borealis: AF389307, AF389308, Picoides canicapillus: AF389309, Picoides leucotos: AF389312, AF389313, Picoides maculatus: AF389315, Picoides major: AF389316, AF389317, Picoides minor: AF389318, AF389319, Picoides nuttallii: AF389322, AF389323, Picoides pubescens: AF389324, AF389325, Picoides scalaris: AF389326, AF389327, Picoides stricklandi: AF389329, Picoides tridactylus: AF389330, AF389331, Picoides villosus: AF389332, AF389333, AY942890, Piculus chrysochloros: AY927203, Picumnus aurifrons: AY942888, Picumnus cirratus: AY940809, Sasia abnormis: AY940813, Sphyrapicus varius: AY942891, Veniliornis fumigatus (more closely related to Picoides): AY927216, AY927217 COLCampephilus haematogaster: AY942869, Captio niger: AY940778, Colaptes auratus: AY942868, Dendrocopos kizuki: AF394280, AF394281, Dendropicos griseocephalus: AY942871, Indicator variegatus: AY940781, Jynx torquilla: AY940782, Melanerpes carolinus: AY942873, Picoides albolarvatus: AF394273, AF394274, AY942874, Picoides arcticus: AF394275, Picoides arcticus: AF394276, Picoides borealis: AF394277, AF394278, Picoides canicapillus: AF394279, Picoides leucotos: AF394282, AF394283, Picoides maculatus: AF394285, Picoides major: AF394286, AF394287, Picoides minor: AF394288, AF394289, Picoides nuttallii: AF394292, AF394293, Picoides pubescens: AF394294, AF394295, Picoides scalaris: AF394296, AF394297, Picoides stricklandi: AF394298, Picoides tridactylus: AF394299, AF394300, Picoides villosus: AF394301, AF394302, AY942877, Piculus chrysochloros: AY927183, Picumnus cirratus: AY940788, Sasia abnormis: AY940792, Sphyrapicus varius: AY942878 Appendix 4 Distributions of node ages and y statistics for phylogenetic trees simulated under six models of diversification. A) pure birth, (b=0.6); B) constant speciation (b=0.6) and extinction (d=0.5); C ) increasing speciation rates (bl=0.3, b2=0.6, b3=1.2); D) increasing extinction rates (b=0.6, dl=0.1, d2=0.2, d3=0.6); E) increasing speciation and extinction rates (bl=0.3, b2=0.6, b3=1.2, dl=0.15, d2=0.3, d3=0.6); F) decreasing speciation rates (bl=0.6, b2=0.3, b3=0.15). One thousand trees were simulated for 8 time units (representing millions of years) in each simulation, b = speciation rate, d = extinction rate, bl and dl from 0 to 5.5, b2 and d2 from 5.5 to 7, b3 and d3 from 7 to 8 million years in simulation. Only trees with five or more extant tips were analyzed because I did not sample actual taxa with fewer than five species. Pale gray (late Miocene and early Pliocene); gray (late Pliocene and early Pleistocene); slate (late Pleistocene). Mean values of y are reported. i 1 1 1 1 — i 1 i i i — i i i i i 0 2 4 6 8 0 2 4 6 8 0 2 4 6 8 simulation time (millions of years) 132 Appendix 5 Chapter Four molecular phylogenies and reconstructions of ancestral geographic distribution in lowland, highland, Caribbean, North America or other regions (e.j Galapagos Islands). 133 Tangara Key 0 M B M Highland • mmmn Lowland • Caribbean • AforrA American • • OrA?r Dispersal G> Lowland to Highland 9 Highland to Lowland Amazon barbadensis ochrocephalus versicolor ariimiaca kawalli autumnalis rhodocorytha dufresniana farinosa imperialis brasiliensis gui/dingii amazonica viridigenalis finschi agtiii albifrons collaria vittata ventralis leucocephala vinacea festiva tucumana pretrei callophrys velia chilensis inornata mexicana seledon fastuosa desmaresti cyanocephala lavinia gyrola gyrola gyrola chrysotis xanthocephala parzudakii schrankii johannae icterocepha florida arthus cyanotis labradorides vassorii nigroviridis fucosa dowii ruficervix heinei argyrofenges viridicollis cyanoptera vitriolina cucullata cayana meyerdeschaue palmeri cyanicollis cyanicollis larvata nigrocincta varia rufigula xanthogastra guttata punctata punctata -11.0 million years •4 2.5 million years 134 Trogon Nyctibius i . bairdii • melanocephalus • violaceus • curucui • comptus • melanurus • massena • rufus • personatus • collaris • mexicanus • elegans Trogon collaris occurs both widely in lowlands and highlands maculosus leucopterus griseus grand is bracteatus aethereus Blackbird clade Xiphorhynchus Pseudoleistes guirahuro Pseudoleistes virescens Agelaius flavus Agelaius icterocephalus Agelaius ruficapillus Molothrus badius Oreopsar bolivianus Agelaius thilius Agelaius cyanopus Agelaius xanthophthalmus\ Ambtyramphus holoseri Curaeus curaeus Gnorimopsar chopi Ijampropsar tanagrinus Gymnomystax mexicanus Macroagelaius imthumi • guttatoides i susurrans . guttatu ' flavigaster • lachrymosus 1 erythropygius , triangularis , obsoletus • kienerii . picus • fuscus ' elegans , spixii • chunchotambo , ocellatus . pardalotus -11.0 million years HI 2.5 million years 135 Psarocolius and relatives (f.) ridgwayi anabalina fuliginosa lurdina (f.) taunayi homochroa merula tvrianna chrysocephalus cayonensis auricapillus bonuna (d.) portorkxnsii oberi laudabilis {d.) northropi (d.) melaaopsis proslhemelas spurius fuertesi cue igneus wagleri maculialatus mes mesomelas pectoralis graceaneae icterus croconotus chrysater graduacauda parisorum pustulaius buliockii galbula abeillei leucopte.ryx auratus nigrogularis gularis Crax and relatives Ramphocelus Psarocolius viridis Psarocolius bifasciatus Gymnoslinops momezuma Psarocolius decumamts Psarocolius wagleri Psarocolius atrovirens Psarocolius angustifrons Cacicus solitarius Cacicus sclateri Ocyalus latirostris Psarocolius oseryi Cacicus haemorrhous Cacicus leucoramphus Cacicus chrysonotus Cacicus cela Cacicus (u.) microrhynchus Cacicus uropygialis Cacicus (u.) pacificus Cacicus melanicterus fasciolata alector globulosa blumenbachii rubra alberti daubemoni Nothocrax urumutum salvini Pauxi unicornis tuberosa tomentosa mitu Pauxi pauxi carbo i bresilius i nigrogularis i icteronotus , passerinii • sanguinolentus Taxonomic note: costancensis has been recognized as a species but but is not considered so here 11.0 million years 12.5 million years 136 Pteroglossus bitorquatus beauharnaesii flavirostris aracari pluricinctus castanotis torquatus frantzii erythropygius Baillonius bailloni viridis inscriptus Taxonomic note: humbolti, sanguineus and mariae are not considered full species due to lack of reproductive isolation and are excluded Veniliornis 45 affinis nigriceps callonotus dignus frontalis passerinus cassini kirkii spilogaster Picoides lignarius Picoides mixtus chocoensis Pionopsitta • pileata • pulchra • haematotis • coccinicolaris • barrabandi • aurantigena • caica • vulturina Neotropical Swallow clade HI *-i: ^—Progne elegans Progne chalybea (South) ^—Progne subis ^—Progne murphyi Progne dominicensis rogne cryploleuca Progne chalybea (North) Progne sinaloae Phaeoprogne lapera Stelgidopteryx ruficollis Stelgidopteryx serripennis Neochelidon tibialis Notiochelidon pileata Atticora fascima Atticora melanoleuca Notiochelidon cyanoleuca Alopochelidon fucata Notiochelidon flavipes Haplochelidon andecola Notiochelidon murina 11.0 million years 12.5 million years 137 Myarchus Craniolueca Anairetes albiceps marcapata vulpina albicapilla pyrrhophia henricae obsoleta erythrops demissa antisiensis carta ta baroni Tachycineta nigrocristatus reguloides agilis flavirostris alpinus parulus fernandezianus t semirufus tuberculifer barbirostris swainsoni 1 cephalotes phaeocephalus panamensis ferox venezuelensis SM-ainsoni 2 validus stolidus sagrue oberi antitlarum crinitus yucatanensis tyrannulus ' albiventer i albilinea i stolzmanni i meyeni < leucorrhoa i bicolor ' cyaneoviridis ' euchrysea ' thalassina reconstruction uncertain at base Geositta ^ poeciloptera crassirostris punensis —— rufipennis —— niaritima ^ — — a n t a r c t i c a — — i s a b e l l i n a — — — — saxicolina —— peruviana — — tenuirostris cunicularia 1 — — ^ — cunicularia 2 Taxonomic note: Highland and lowland forms of cunicularia are treated as separate species here. 11.0 million years 12.5 million years 138 Carduelis yarellii magellanica 2 crassirostris spinescens cucullata atraia olivacea magellanica 1 barbata xanthogastra notata Troglodytes ft musculus aedon 1 sissonii aedon 2 brunneicollis rufociliatus solstitialis rufulus ochraceus Thrvorchilus browni Ochthoeca Metallura odomae (williami) primolina baroni (williami) atrigularis phoebe theresiae eupogon aeneocauda tyrianthina pulchella jelskii diadema spodionota frontalis cinnamomeiveniris thoracica leucophrys oenanlhoides rufipectoralis fumicolor Muscisaxicola juninensis rufivertex cinera (a.lpina) grisea albifrons flavinucha alpina macloviana albilora frontalis capistrata maculirostris Amazonian fluviatilis (not shown) is basal to rest of genus • E Cinclodes nigrofumosus taczanowski palagonicus palliatus atacamensis excelsior aricomae antarcticus fuscus comechingonus oustaleti olrogi pabsti Hemispingus •i melanotis _A ^ frontalis • piurae — r u f o s u p e r c i l i a r u s trifasciatus superciliaris A verticalis T xanthophthalmus atropileus — — ^ — ^ — c a l o p h r y s I—11.0 million years ——^—^———————"~-auricularis _ _ I | 2.5 million years 139 Appendix 6 Mean intraspecific sequence divergence between individuals of species or phylogroups for lowland and highland Neotropical birds. Sequence divergence was calculated with the GTR-gamma model. Age is in millions of years based on a 2% molecular clock. Abbreviations as follows: n, number of individuals; Cyt B, cytochrome b; COI, cytochrome c oxidase 1; ATPase 6 and 8, ATPase 6 and ATPase 8. Family Taxon n Sequence Divergenc e Age Gene Source a) Lowland Pipridae Lepidothrix coronata 5 0.0055 . 0.28 CytB, 307 bp Cheviron et Maranon al. 2005 Pipridae Lepidothrix coronata North 9 0.0054 0.27 CytB, 307 bp Amazon Pipridae Lepidothrix coronata 13 0.0097 0.48 CytB, 307 bp Central Peru Pipridae Lepidothrix coronata 8 0.0052 0.26 CytB, 307 bp Bolivia / Southern Peru Pipridae Lepidothrix coronata 11 0.0106 0.53 CytB, 307 bp Venezuela Pipridae Lepidothrix coronata Trans- 11 0.0150 0.75 CytB, 307 bp Andean Dendrocolaptidae Xiphorhynchus spixii 21 0.0053 0.26 CytB, 1005 hn Aleixo 2004 Dendrocolaptidae Xiphorhynchus elegans 13 0.0030 0.15 Dp CytB, 1005 orntus bp Dendrocolaptidae Xiphorhynchus elegans 21 0.0094 0.47 CytB, 1005 elegans bp Dendrocolaptidae Xiphorhynchus elegans 18 0.0027 0.13 CytB, 1005 juruanus bp Dendrocolaptidae Xiphorhynchus elegans 6 0.0023 0.11 CytB, 1005 insignis bp Psittacidae Aragtinga solstitialis • 4 0.0020 0.10 CytB, 340bp Ribas and Miyaki 2004 Psittacidae Aragtingajandaya 5 0.0000 0.00 CytB, 340bp Psittacidae Aragtinga auricapilla 7 0.0095 0.47 CytB, 340bp Psittacidae Aragtinga weddellii 4 0.0012 0.06 CytB, 340bp Troglodytidae Thryothorus nigricapillus 14 0.0062 0.31 ATPase Gonzales et 6and8, 842 bp al. 2003 Ramphastidae Pteroglossus viridis 4 0.0019 0.10 COI 622 bp Eberhard and Bermingha m2005 Dendrocolaptidae Glyphoiynchus spirirus 14 0.0138 ' 0.69 CytB, 379 bp Marks et al. Central America, Choco, 2002 Imeri Dendrocolaptidae Glyphoiynchus spirirus 7 0.0148 0.74 CytB, 379 bp Para, SE. Brazil Dendrocolaptidae Glyphoiynchus spirirus 9 0.0120 0.60 CytB, 379bp Guyana Dendrocolaptidae Glyphoiynchus spirirus 11 0.0096 0.48 CytB, 379 bp Peruvian Inambari Mean 0.0069 0.35 b) Highland 140 Emberizidae Chlorospingus (flavigularis) hypophaeus Emberizidae Chlorospingus (flavigularis) flavigularis Emberizidae Chlorospingus pileatus Emberizidae Chlorospingus ophthalmicus phaeocephalus Emberizidae Chlorospingus ophthalmicus novicius Emberizidae Chlorospingus ophthalmicus regionalis Emberizidae Chlorospingus ophthalmicus honduratius Emberizidae Chlorospingus ophthalmicus dwighti Emberizidae Chlorospingus ophthalmicus ophthalmicus Emberizidae Chlorospingus ophthalmicus wetmorei Emberizidae Chlorospingus ophthalmicus albifrons 0.0024 0.12 ATPase 6and8, 842 bp 0.0092 0.46 ATPase 6and8, 842 bp 0.0041 0.21 ATPase 6and8, 842 bp 0.0025 0.13 ATPase 6and8, 842 bp 0.0010 0.05 ATPase 6and8, 842 bp 0.0088 0.44 ATPase 6and8, 842 bp 0.0029 0.15 ATPase 6and8, 842 bp 0.0046 0.23 ATPase 6and8, 842 bp 0.0062 0.31 ATPase 6and8, 842 bp 0.0014 0.07 ATPase 6and8, 842 bp 0.0012 0.06 ATPase 6and8, 842 bp Weir unpublished Mean 0.0040 0.20 Literature Cited Aleixo, A. 2004. Historical diversification of a Terra-firme forest bird superspecies: A phylogeographic perspective on the role of different hypotheses of Amazonian diversification. Evolution 58:1303-1317. Cheviron, Z. A., S. J. Hackett, and A. P. Capparella. 2005. Complex evolutionary history of a Neotropical lowland forest bird (Lepidothrix coronata) and its implications for historical hypotheses of the origin of Neotropical avian diversity Mol. Phylogenet. Evol. 36:338-357. Eberhard, J. R., and E. Bermingham. 2005. Phylogeny and comparative biogeography of Pionopsitta parrots and Pteroglossus toucans. Mol. Phylogenet. Evol. 36:288-304. Gonzales, M . A., J. R. Eberhard, I. J. Lovett, S. L. Olson, and E. Bermingham. 2003. Mitochondrial DNA phylogeography of the bay wren (Troglodytidae: Thryothorus nigricapillus) complex. Condor 105:228-238. 141 Marks, B. D., S. J. Hackett, and A. P. Capparella. 2002. Historical relationships among Neotropical lowland forest areas of endemism as determined by mitochondrial DNA sequence variation within the Wedge-billed Woodcreeper (Aves : Dendrocolaptidae : Glyphorynchus spirurus). Mol. Phylogenet. Evol. 24:153-167. Ribas, C. C , and C. Y. Miyaki. 2004. Molecular systematics in Aratinga parakeets: species limits and historical biogeography in the 'solstitialis' group, and the systematic position of Nandayus nenday. Mol. Phylogenet. Evol. 30:663-675. 142 APPENDIX 7 Individuals sequenced for mitochondrial cytochrome b or obtained from Genbank for Chapter 5. 143 -1^  -1^  Family Genus species subspecies Museum Tissue Number Genbank number Locality Dendrocolaptidae Campylorhamphus falcularius MZUSP LFS 99/378 AY089810 Bahia; Brazil Dendrocolaptidae Campylorhamphus procurvoides FMNH DEW 2685 AY089795 Amazonas; Venezuela Dendrocolaptidae Campylorhamphus pusillus ?borealis STRI JTW094 Panama; Bocas del Toro; Chiriqui to Chiriqui Grande Road at continental divide Dendrocolaptidae Campylorhamphus pusillus olivaceus LSUMZ B1411 Panama; Darien; Cerro Pirre; 9 km NW Cana Dendrocolaptidae Campylorhamphus pusillus pusillus LSUMZ B11879 Ecuador; Esmeraldes; EI Placer Dendrocolaptidae Campylorhamphus pusillus pusillus LSUMZ B33822 Peru; Cajamarca; Cordillera del Condor; Picorana Dendrocolaptidae Campylorhamphus trochilirostris LSUMZ 153671 AY089822 Santa Cruz; Bolivia Dendrocolaptidae Deconychura • longicauda typica STRI CR-DLO-2761 Costa Rica; Tinamastes Dendrocolaptidae Deconychura longicauda darienensis LSUMZ B2088 Panama; Darien; Cerro Pirre; 6 km NW Cana Dendrocolaptidae Deconychura longicauda connectens LSUMZ B7565 Venezuela; Amazonas Territory; Cerro de la Neblina base camp Dendrocolaptidae Dendrexetastes rufigula MHNJP SWC 2358 AY089829 Peru; Loreto Dendrocolaptidae Dendrocincla anabatina Kansas KU536 Mexico University Dendrocolaptidae Dendrocincla fuliginosa fuliginosa FMNH FM391298 Brazil; Amapa Dendrocolaptidae Dendrocincla fuliginosa taunayi FMNH FM399181 Brazil; Alagoas Dendrocolaptidae Dendrocincla fuliginosa atrirostris FMNH FM429948 Peru; Cuzco; Paucartambo Dendrocolaptidae Dendrocincla fuliginosa ridgewayi STRI JTW253 Panama; Bocas del Toro; Valle de Risco Dendrocolaptidae Dendrocincla fuliginosa ridgewayi STRI JTW744 Panama; Darien; Puerto Pina Dendrocolaptidae Dendrocincla fuliginosa heglecta STRI EC-DFU1 Ecuador; Jatun Sacha Dendrocolaptidae Dendrocincla fuliginosa meruloides STRI TR-DFU1 Trinidad; Simla Research Station Dendrocolaptidae Dendrocincla homochroa homochroa FMNH FM434035 El Salvador Dendrocolaptidae Dendrocincla homochroa ruficeps STRI PA-DHO-PA671 Panama; Panama; Cerro Azul; ANAM Station Dendrocolaptidae Dendrocincla merula olivascens FMNH FM389810 Brazil; Rondonia Dendrocolaptidae Dendrocincla turdina Kansas KU 3698 Paraguay University Dendrocolaptidae Dendrocincla tyrannina tyrannina FMNH FM429946 Peru; Cuzco Dendrocolaptidae Dendrocolaptes certhia MHNJP DLD 133 AY089817 Loreto; Peru Dendrocolaptidae Dendrocolaptes picumnus LSU B35728 Brazil; Amazonas; Sao Fransico Rio Solimoes; 13.3 Km NE Sau Paulo Dendrocolaptidae Dendrocolaptes platyrostris FMNH NRM 976714 AY442990 South America Dendrocolaptidae Dendrocolaptes sanctithomae sanctithomae STRI JTW251 Panama; Bocas del Toro; Valle de Risco Dendrocolaptidae Drymornis bridgesii NRM NRM 966930 AY065711 South America Dendrocolaptidae Glyphorynchus • spirurus MPEG JDW445 AY089806 Brazil; Bahia Dendrocolaptidae Glyphorynchus spirurus LSUMZ B8760 AY096891 Belize Dendrocolaptidae Glyphorynchus spirurus LSUMZ B11878 AY096899 Ecuador: Esmeraldas Dendrocolaptidae Glyphorynchus spirurus LSUMZ B5967 AY096910 Ecuador: Morona-Santiago Province Dendrocolaptidae Glyphorynchus spirurus LSUMZ B5081 AY096911 Peru: Loreto Department Dendrocolaptidae Glyphorynchus spirurus LSUMZ B9229 AY096922 Bolivia: Pando Department Dendrocolaptidae Glyphorynchus spirurus LSUMZ B12753 AY096931 Bolivia Dendrocolaptidae Glyphorynchus spirurus FMNH JH-274 AY096939 Brazil Dendrocolaptidae Glyphorynchus spirurus FMNH CH-285 , AY096950 Brazil Dendrocolaptidae Hylexetastes perrotii LSUMZ 150674 AY089809 Bolivia; Santa Cruz Dendrocolaptidae Ledipocolpates lacrymiger UWBM RCF2209 Bolivia; Santa Cruz; Provincia de Vallegrande; 29 K M SE Vallegrande Dendrocolaptidae Lepidocqla souleyetii STRI VE-LSOI Venezuela; Guaraunos Dendrocolaptidae Lepidocolaptes affinis affinis UWBM UWBM70115 Nicaragua; Matagalpa; 10 km N Dendrocolaptidae Lepidocolaptes albolineatus LSUMZ 153311 AY089825 Bolivia; Santa Cruz Dendrocolaptidae Lepidocolaptes angustirostris MHNNKM MDC 363 AY0898U Bolivia; Santa Cruz Dendrocolaptidae Lepidocolaptes leucogaster bolivianus Mexico ME40 Mexico Dendrocolaptidae Lepidocolaptes souleyetii compressus UWBM UWBM70010 Nicaragua; La Luz Rio Uli near Wani Dendrocolaptidae Nasica longirostris LSUMZ 115014 AY089797 Peru; Loreto Dendrocolaptidae Sittasomus griseicapillus reiseri FMNH FM392419 Brazil; Pemambuco Dendrocolaptidae Sittasomus griseicapillus sylvioides FMNH FM343231 Mexico; Veracruz Dendrocolaptidae Sittasomus griseicapillus CBF SWC 6769 AY089796 Bolivia; La Paz Dendrocolaptidae Xiphocolaptes major NRM NRM 966847 AY065712 South America Dendrocolaptidae Xiphocolaptes promeropirhynchus LSUMZ CCW718 AY089798 Peru; Cajamarca Dendrocolaptidae Xiphocolaptes promeropirhynchus emigrans UWBM UWBM56169 Nicaragua; Matagalpa; 10 km N Dendrocolaptidae Xiphocolaptes promeropirhynchus sclateri FMNH FM394013 ' Mexico; Hidalgo Dendrocolaptidae Xiphorhynchus erythropygius ANSP FHS 85 AY089832 Ecuador; Pichincha Dendrocolaptidae Xiphorhynchus erythropygius punctigula STRI JTW105 Panama; Bocas del Toro; Chiriqui to Chiriqui Grande Road at continental divide Dendrocolaptidae Xiphorhynchus erythropygius insolitus STRI JTW669 Panama; Darien; Puerto Pina Dendrocolaptidae Xiphorhynchus flavigaster FMNH DSW 2986 AY089799 Belize; Toledo district Dendrocolaptidae Xiphorhynchus fitscus MPEG AA568 AY089819 Brazil; Bahia Dendrocolaptidae Xiphorhynchus guttatus eytoni MPEG MR-003 AY089794 Brazil; Para Dendrocolaptidae Xiphorhynchus guttatus MPEG Ch202 AY089814 Brazil; Amapa Dendrocolaptidae Xiphorhynchus guttatus dorbignyanus LSUMZ 153308 AY089816 Bolivia; Santa Cruz Dendrocolaptidae Xiphorhynchus kienerii LSUMZ 165752 AY089818 Amazonas; Brazil Dendrocolaptidae Xiphorhynchus lachrymosus ANSP 185351 AY089807 Esmeraldas; Ecuador Dendrocolaptidae Xiphorhynchus lachrymosus lachrymosus STRI JTW317 Panama; Bocas del Toro; Cerro Chalite Dendrocolaptidae Xiphorhynchus obsoletus obsoletus ANSP 188595 AY089823 Iwokrama; Guyana Dendrocolaptidae Xiphorhynchus ocellatus brevirostris LSUMZ 101904 AY089793 La Paz; Bolivia Dendrocolaptidae Xiphorhynchus ocellatus ocellatus MPEG AA581 AY089804 Para; Brazil Dendrocolaptidae Xiphorhynchus chunchotambo LSUMZ 161705 AY089815 Loreto; Peru Dendrocolaptidae Xiphorhynchus ocellatus weddellii LSUMZ 119520 AY089820 Loreto; Peru Dendrocolaptidae Xiphorhynchus pardalotus MPEG AA602 AY089831 Para; Brazil Dendrocolaptidae Xiphorhynchus picus altirostris AY089790 Island of Trinidad Dendrocolaptidae Xiphorhynchus picus AY089802 Venezuela Dendrocolaptidae Xiphorhynchus picus extimus STRI JTW543 Panama; Cocle; Aguadulce Dendrocolaptidae Xiphorhynchus spixii spixii MPEG MR-002 AY089801 Para; Brazil Dendrocolaptidae Xiphorhynchus elegans elegans MPEG AA290 AY089805 Rondonia; Brazil Dendrocolaptidae Xiphorhynchus elegans ornatus LSUMZ 109706 AY089812 Loreto; Peru Dendrocolaptidae Xiphorhynchus elegans juruanus MPEG AA 236 AY089824 Rondonia; Brazil Dendrocolaptidae Xiphorhynchus susurrans LSUMZ 163545 AY089800 Panama; Panama Dendrocolaptidae Xiphorhynchus susurrans costaricensis STRI CR-XSU2753 Costa Rica; Dominical Baru Dendrocolaptidae Xiphorhynchus triangularis LSUMZ 162637 AY089826 La Paz; Boliva Dendrocolaptidae Xiphorhynchus triangularis FMNH ZMCU S45 AY442999 South America Icteridae Agelaius cyanopus AF290174 South America Icteridae Agelaius flavus AF089066 South America Icteridae Agelaius humeralis AF089006 Cuba or Hispaniol Icteridae Agelaius icterocephalus AF089007 South America Icteridae Agelaius phoeniceus AF290173 North America Icteridae Agelaius ruficapillus AF089009 South America Icteridae Agelaius thilius AF089010 South America Icteridae Agelaius tricolor AF089011 North America Icteridae Agelaius xanthomus AF089012 Puerto Rico Icteridae Agelaius xanthophthalmus AF089013 South America Icteridae Amblycercus holosericeus holosericeus KU 1928 AY117722 Mexico Icteridae Amblycercus holosericeus australis LSUMZ LSUMNH 98900 AF472386 South America Icteridae Cacicus cela cela Icteridae Cacicus cela vitellinus Icteridae Cacicus chrysonotus chrysonotus Icteridae Cacicus chrysopterus Icteridae Cacicus haemorrhous haemorrhous Icteridae Cacicus leucoramphus Icteridae Cacicus melanicterus Icteridae Cacicus sclateri Icteridae Cacicus solitarius Icteridae Cacicus uropygialis microrhynchu Icteridae Cacicus uropygialis pacificus Icteridae Cacicus uropygialis uropygialis Icteridae Curaeus curaeus Icteridae Dives dives Icteridae Dives warszewiczi Icteridae Dolichonyx oryzivorus Icteridae Euphagus carolinus Icteridae Euphagus cyanocephalus Icteridae Gnorimopsar chopi Icteridae Gymnomystax mexicanus Icteridae Icterus auratus Icteridae Icterus auricapillus Icteridae Icterus bonana Icteridae Icterus bullockii . bullockii Icteridae Icterus cayanensis pyrrhopterus Icteridae Icterus chrysater chrysater Icteridae Icterus chrysater hondae Icteridae Icterus cucullatus nelsoni Icteridae Icterus dominicensis dominicensis Icteridae Icterus dominicensis melanopsis Icteridae Icterus dominicensis portoricensis Icteridae Icterus galbula FMNH 339733 AY117721 Venezuela AY117712 Panama B103278 AY117718 Bolivia USNM USNM 620761 AY117704 Argentina USNM 621068 AY117701 Guyana AY117707 South America FMNH 52204 AY117708 Mexico, Oaxaca ANSP ANSP 177931 AY117710 Peru FMNH 324091 AY117717 Peru, Madre de Dios PACUR-PC99 AF089017 Panama FMNH 182884 AF472382 Fxuador LSUMZ B6093 AY117705 Fxuador, Morona-Santiago Province AF089020 South America UWBM SRF318 Mexico; Chiapas; Estacion Juarez, 15 km NE; near San Vicente river, Rancho Aldebaran AF089021 South America AF447367 North America AF089023 North America AF089024 North America AF089025 South America AF089026 South America UAM 7222- AF099276 Mex. Yucatan, El Coyo ANSP 173534 AF099310 . Columbia, Meta STRI MA-IB02 AF099277 Martinique, Fond Baron FMNH FMNH 341938 A Y611476 USA, CA, Monterey Co. FMNH 334608 AF099280 Bolivia, Santa Cruz, Chiquitos UWBM UWBM DAB- AF099281 Nicaragua, Casitta 1573 STRI PA-ICHPP4 AF099282 Panama, Farfan-Antenna FMNH FMNH ATP88- AF099284 USA, CA, Riverside Co. 081 LSUMZ 9897 AF099285 Haiti MHNC 4/8/92 AF099286 Cuba STRIPR-IDOl AF099288 Puerto Rico, Maricao AY607658 North America Icteridae Icterus graceannae Icteridae Icterus graduacauda audubonii Icteridae Icterus gularis tamaulipensis Icteridae Icterus icterus ridgewayi Icteridae Icterus icterus croconotus Icteridae Icterus jamacaii stricifrons Icteridae Icterus laudabilis Icteridae Icterus leucopteryx leucopteryx Icteridae Icterus maculialatus Icteridae Icterus mesomelas mesomelas Icteridae Icterus nigrogularis nigrogularis Icteridae Icterus oberi Icteridae Icterus parisorum Icteridae Icterus pectoralis (¥\oniz) Icteridae Icterus prosthemelas prosthemelas Icteridae Icterus pustulatus sclateri Icteridae Icterus spurius spurius Icteridae Icterus spurius fuertesi Icteridae Icterus wagleri wagleri Icteridae Lampropsar tanagrinus Icteridae Leistes militaris Icteridae Macroagelaius imthurni Icteridae Molothrus aeneus Icteridae Molothrus ater Icteridae Molothrus badius Icteridae Molothrus bonariensis Icteridae Molothrus rufoaxillaris Icteridae Nesopsar nigerrimus Icteridae Ocyalus latirostris Icteridae Oreopsar boliviartus Icteridae Psarocolius angustifrons Icteridae Psarocolius angustifrons angustifrons ANSP 181810 AF310064 Ecuador, Loja, Celica LSUMZ LSUMZ 4023 AF099291 USA, TX, Atascosa Co. MZFC KEO-003 AF099294 Mex. Veracruz, Tlacotalpan LSUMZ LSUMZ 11328 AF099296 Puerto Rico, Cabo Rojo FMNH 324092 AF089031 Peru, Madre de Dios LSUMZ LSUMZ 6700 AF099297 Bolivia, Santa Cruz STRI SL-ELA4 AF099298 St. Lucia, Anse la Sorciere FMNH 331144/ AF089032 Jamaica, Cornwall INIREB SRF-387 AF099299 Mex. Chiapas, Tuxtla Gut. UWBM 52153 AF089033 Mex. Chiapas, Estacion Juarez FMNH 339739 AF099302 Venezuela, Falcon, Boca de Aroa STRI MO-IOB4 AF099303 Monserrat, Soufriere FMNH 341943 AF089035 USA, CA, San Bernardino Co. BMNH BMNH 42544 AF099304 USA, FL, Dade Co. BMNH 42543 AY211212 Mex. Campeche, Xpujil UWBM UWBM DAB- AF099306 Nicaragua, La Flor 1670 NCSM NCSM DLD-2538 AY211211 USA, CO, Weld Co. BMNH BMNH 42538 AY211215 Mex. Veracruz, Tlacotalpan MZFC MZFC QRO-216 AF099308 Mex. Queretaro AF089037 South America FMNH 334657 AF089038 Bolivia: Santa Cruz AF089039 South America AF089040 North America AF089041 North America AF089042 South America AF089043 Puerto Rico AF089044 South America AF089045 South America FMNH 177928 AF472383 Peru, Loreto AF089046 South America LSUMZ B-7776 AY117719 Ecuador FMNH 120397 AF472376 Peru, Loreto Icteridae Psarocolius atrovirens FMNH 324106 AF472373 Peru, Cuzco Icteridae Psarocolius bifasciatus yuracares FMNH 153616 AF472375 Bolivia, Santa Cruz Icteridae Psarocolius decumanus insularis STRI TR-PDE1 AF472371 Trinidad Icteridae Psarocolius decumanus maculosus FMNH 334605 AY117698 Bolivia, Santa Cruz Icteridae Psarocolius decumanus maculosus LSUMZ B06848 AF472377 Brazil, Para Icteridae Psarocolius decumanus melanterus FMNH 164425 AY117699 Panama, Colo'n Icteridae Psarocolius montezuma LSUMZ B-18096 AF472370 Mexico Icteridae Psarocolius oseryi FMNH 120394 AF472368 Peru, Loreto Icteridae Psarocolius viridis USNM USNM 609202 AF472366 Guyana Icteridae Psarocolius wagleri ridgwayi LSUMZ B-27280 AF472365 Costa Rica, Cartago Icteridae Psarocolius wagleri wagleri STRI HAPWAHA29 AF472364 Honduras Icteridae Pseudoleistes giiirahuro AF089051 South America Icteridae Pseudoleistes virescens AF089052 South America Icteridae Quiscalus lugubris lugubris STRI GU-QLU1 Guadeloupe; Duquerry Icteridae Quiscalus lugubris lugubris STRI BA-QLU1 Barbados; Barclay's Park Icteridae Quiscalus major AF089055 USA, Louisiana Icteridae Quiscalus mexicanus STRI PA-QME-PP15 Panama; Panama City Icteridae Quiscalus mexicanus AF089056 USA, California Icteridae Quiscalus nicaraguensis nicaraguensis STRI NI-QNG996 Nicaragua; Tipitapa; along shore of Lago deManagua, near Rio Tipitapa Icteridae Quiscalus niger niger STRI PR-QNI11450 Puerto Rico; Llanos Costa Icteridae Quiscalus niger AF089057 Jamaica Icteridae Quiscalus niger niger STRI JA-QNI1 Jamaica; Bluefield Jerk Icteridae Quiscalus quiscula AF089058 USA, Illinois Icteridae Scaphidura oryzivora AF089060 Peru, Madre de Dios Icteridae Sturnella bellicosa AF310065 South America Icteridae Sturnella magna AF089063 Icteridae Sturnella magna paralios FMNH FM339779 Venezuela, Falcon Icteridae Sturnella neglecta AF089064 North America Icteridae Xanthocephalus xanthocephalus AF089067 North America Thamnophilidae Batara cinerea NRM NRM 947099 AY676937 Paraguay; Dpto. Alto Paraguay; Est. Dona Julia Thamnophilidae Cercomacra laeta sabinoi FMNH FM392376 Brazil; Pernambuco Thamnophilidae Cercomacra melanaria AY065723 South America Thamnophilidae Cercomacra nigrescens LSUMZ O Thamnophilidae Cercomacra serva STRI Thamnophilidae Cercomacra tyrannina crepera UWBM Thamnophilidae Cercomacra tyrannina crepera STRI Thamnophilidae Cercomacra tyrannina tyrannina STRI Thamnophilidae Conopophaga lineata FMNH Thamnophilidae Cymbilaimus lineatus fasciatus LSUMZ Thamnophilidae Cymbilaimus lineatus fasciatus STRI Thamnophilidae Cymbilaimus lineatus LSUMZ Thamnophilidae Dichrozona cincta ZMCU Thamnophilidae Dichrozona cincta NRM Thamnophilidae Drymophila caudata ANSP Thamnophilidae Drymophila caudata FMNH Thamnophilidae Drymophila devillei FMNH Thamnophilidae Drymophila devillei LSUMZ Thamnophilidae Drymophila squamata Thamnophilidae Dysithamnus mentalis NRM Thamnophilidae Dysithamnus mentalis septentrionalis STRI Thamnophilidae Dysithamnus mentalis napensis LSUMZ Thamnophilidae Dysithamnus puncticeps STRI Thamnophilidae Dysithamnus puncticeps STRI Thamnophilidae Dysithamnus puncticeps STRI Thamnophilidae Dysithamnus puncticeps LSUMZ Thamnophilidae Dysithamnus mentalis tavarae FMNH Thamnophilidae Formicivora grisea FMNH Thamnophilidae Formicivora rufa LSUMZ Thamnophilidae Formicivora rufa NRM Thamnophilidae Frederickena unduligera ZMCU B12661 EC-CSE1 Bolivia; Santa Cruz Department; Velasco; W. Bank Rio Paucerna, 4 km upstream from Rio Itenez Ecuador; Jatun Sacha DAB 1036 JTW400 RCF53 Nicaragua; La Luz, 4 km S, 8 km W, near Wani, on Rio Uli about 1 km from Rio Wani Panama; Chiriqui Province; Yerbazales, Burica Peninsula Panama; Veraguas; Santa Fe 5288 AY370555 South America B2252 JTW154 B18168 EF030315 Panama; Darien Province; Cana on E. slope Cerro Pirre Panama; Bocas del Toro; Chiriqui to Chiriqui Grande Road at continental divide Bolivia; depto. Santa Cruz; Velasco S1882 AY676962 Ecuador; Napo; C. Canaday NRM 956653 ANSP 185468 AY676962 AF118170 Paraguay; Dpto. Caazapa; P.N. Caaguazii (Sector Enramadita Ecuador; Napo 107208 AFI 18173 Peru; Pasco FMNH REAJ001 AFI 18174 Brazil; Acre B1849 AF118184 Bolivia; Santa Cruz S2199 AY065722 Brazil; Sao Paulo; Brazil NRM 956629 JTW128 B6155 JTW321 AY676948 Paraguay; Dpto. Caazapa; P.N. Caaguazu (Sector Enramadita Panama; Bocas del Toro Province; Chiriqui to Chiriqui Grande Road at continental divide Ecuador; Morona-Santiago Province; W- slope Cordillera del Cutucu, Yapitya, on Logrono-Yaupi trail Panama; Bocas del Toro Province; Cerro Chalite JTW635 Panama; Darien Province; Peurto Pina RCF018 Panama; Veraguas Province; Santa Fe B11951 Ecuador; Esmeraldas Province; El Placer CA 670M FM433393 Peru; Cuzco ; Paucartambo FMNH 73357 AF118169 Brazil; Roraima B14601 AY115421 South America NRM 947236 AY676958 Paraguay; Dpto. Amambay; Est. Apami S1776 AY676934 Ecuador; Napo; SE Pompeya Thamnophilidae Frederickena unduligera LSUMZ B4281 EF030316 Peru; depto. Loreto; Lower R'yo Napo Thamnophilidae Gymnocichla nudiceps ZMCU S2732 AY676974 Panama; Bocas del Toro; Rio SanSari Thamnophilidae Gymnocichla nudiceps nudiceps STRI PA-GNU-PC34 Panama; Panama; Achiote Road Thamnophilidae Gymnocichla nudiceps erratilis STRI JTW448 Panama; Chiriqui Province; Bartolo Arriba, Burica Peninsula Thamnophilidae Gymnopithys leucaspis ZMCU S1843 AY676977 Ecuador; Napo; C Canaday Thamnophilidae Gymnopithys leucaspis bicolor STRI PA-GLE914 Panama; Panama; Darien; Tropic Star Lodge; 9km up Rio Pifias; Rio Pichinde Thamnophilidae Gymnopithys leucaspis olivascens STRI JTW268 Panama; Bocas del Toro ; Valle de Risco Thamnophilidae Gymnopithys leucaspis castaneus STRI EC-GLE1 Ecuador; Jatun Sacha Thamnophilidae Gymnopithys leucaspis bicolor STRI JTW333 Panama; Panama Province; Cerro Campana Thamnophilidae Herpsilochmus atricapillus ZMCU S1086 AY676949 Brazil; Goias, Sao Domingos; Fazenda CIPASA Thamnophilidae Herpsilochmus rufimarginatus FMNH FMNH 339650 AF118157 Venezuela; Bolivar Thamnophilidae Hylophylax naevia ZMCU S1913 AY676963 Ecuador; Napo; SE Pompeya Thamnophilidae Hylophylax naevioides ?capnitis STRI JTW560 Panama; Cocle Province; Cascajal Thamnophilidae Hylophylax naevioides naevioides STRI JTW682 Panama; Darien Province; Puerto Pina Thamnophilidae Hylophylax poecilonotus griseiventris B1255 AY612487 Bolivia; Santa Cruz, Los Fierros Thamnophilidae Hylophylax poecilonotus griseiventris JH-452 AY612498 Brazil; Mato Grosso do Norte, Municipio Alta Floresta, upper Rio Teles Pires-Rio Cristalino Thamnophilidae Hylophylax poecilonotus lepidonota STRI EC-HPOl Ecuador; Jatun Sacha Thamnophilidae Hypocnemis cantator LSUMZ LSUB15308 AF118163 Bolivia; Santa Cruz Thamnophilidae Hypocnemis cantator FMNH FMNH DW 3755 AF118168 Brazil; Rondonia Thamnophilidae Hypocnemis cantator ZMCU SI 300 AY676964 Brazil; Mato Grosso; Rio Cristalino Thamnophilidae Hypocnemis hypoxantha LSUMZ LSUB156543 AF118161 Peru; Madre de Dios Thamnophilidae Hypocnemis hypoxantha FMNH . FMNH REAJ232 AF118162 Brazil; Acre Thamnophilidae Hypocnemoides maculicauda ZMCU S1301 AY676966 Brazil; Mato Grosso; Rio Teles Pires Thamnophilidae Hypoedaleus guttatus LSUMZ B-25895 AY676936 Paraguay; Caaguazu Department Thamnophilidae Mackenziaena severa NRM NRM 956630 AY676935 Paraguay; Dpto. Caazapa; P.N. Caaguazu (Sector Enramadita Thamnophilidae Megastictus margaritatus ZMCU S2130 AY676944 Ecuador; Napo; S Pompeya Thamnophilidae Microrhopias axillaris albigula STRI JTW644 Panama; Darien Province; Puerto Pina Thamnophilidae Microrhopias quixensis FMNH FMNH 321993 AY676950 Thamnophilidae Microrhopias quixensis virgatus STRI JTW 423 Panama; Chiriqui Province; Yerbazales, Burica Peninsula Thamnophilidae Microrhopias quixensis virgatus STRI JTW301 Panama; Bocas del Toro; Cerro Chalite Thamnophilidae Microrhopias quixensis virgatus STRI JTW078 Panama; Chiriqui Province; Puerto Limones, Burica Peninsula Thamnophilidae Microrhopias quixensis consobrinus STRI JTW724 Panama; Darien Province; Puerto Pina Thamnophilidae Myrtneciza berlepschi ZMCU S1631 AY676973 Ecuador; Esmeraldas; NNW Alto Tambo Thamnophilidae Myrmeciza exsul exsul STRI JTW258 Panama; Bocas del Toro Province; Valle de Risco Thamnophilidae Myrtneciza exsul exsul STRI JTW287 Panama; Bocas del Toro Province; Cerro Chalite Thamnophilidae Myrmeciza exsul exsul STRI JTW289 Panama; Bocas del Toro Province; Cerro Chalite Thamnophilidae Myrmeciza exsul exsul STRI JTW309 Panama; Bocas del Toro Province; Cerro Chalite Thamnophilidae Myrmeciza exsul exsul STRI JTW323 Panama; Bocas del Toro Province; Cerro Chalite Thamnophi lidae Myrmeciza exsul exsul STRI JTW324 Panama; Bocas del Toro Province; Cerro Chalite Thamnophilidae Myrmeciza exsul exsul STRI JTW287 Panama; Bocas del Toro Province; Cerro Chalite Thamnophilidae Myrmeciza exsul occidentalis STRI JTW086 Panama; Chiriqui Province; Puerto Limones, Burica Peninsula Thamnophilidae Myrmeciza fortis ZMCU SI 795 AY676972 Ecuador; Napo; SE Pompeya Thamnophilidae Myrmeciza griseiceps ZMCU S1221 AY676969 Ecuador; Loja; El Limo Thamnophilidae Myrmeciza hemimelaena ZMCU S1821 AY676970 Ecuador; Zamora-Chinchipe; Cord, del Condor Thamnophilidae Myrmeciza immaculata macrorhyncha LSUMZ B11900 Ecuador; Esmeraldas Province; El Placer CA 670M Thamnophilidae Myrmeciza immaculata seledoni STRI JTW183 Panama; Bocas del Toro Province; Chiriqui to Chiriqui Grande Road at continental divide Thamnophilidae Myrmeciza laemosticta STRI JTW573 Panama; Cocle Province; El Cope National Park Thamnophilidae Myrmeciza longipes griseipectus FMNH FM391420 Brazil; Amapa Thamnophilidae Myrmeciza longipes panamensis STRI JTW561 Panama; Cocle Province; Cascajal Thamnophilidae Myrmeciza loricata ZMCU SI 062 AY676971 Brazil; Bahia; Andarai Thamnophilidae Myrmoborus myotherinus ZMCU S1303 AY676961 Brazil; Mato Grosso; Rio Cristalino Thamnophilidae Myrmochanes hemileucus LSUMZ B-7245 AY676965 South America Thamnophilidae Myrmorchilus strigilatus NRM NRM 956742 AY676959 Paraguay; Dpto. Alto Chaco; P.N. Defensores del Chaco, Madrejon Thamnophilidae Myrmornis torquata KUNHM 1311 AY370565 ? Thamnophilidae Myrmornis torquata LSUMZ B-3228 AY676975 Peru; Loreto Department Thamnophilidae Myrmornis torquata strictoptera LSUMZ B2142 Panama; Darien Province; About 6 km NW Cana Thamnophilidae Myrmornis torquata torquata FMNH FM391446 Brazil; Para Thamnophilidae Myrmotherula axillaris ZMCU S2319 AY676954 Ecuador; Pastaza; N Canelos, 600 m Thamnophilidae Myrmotherula axillaris albigula STRI JTW422 Panama; Chiriqui Province; Yerbazales, Burica Peninsula Thamnophilidae Myrmotherula axillaris albigula STRI JTW653 Panama; Darien Province; Puerto Pina Thamnophilidae Myrmotherula axillaris albigula STRI JTW574 Panama; Cocle Province; El Cope National Park Thamnophilidae Myrmotherula axillaris axillaris STRI TR-MAX1 Trinidad; Simla Research Station Thamnophilidae Myrmotherula axillaris axillaris STRI TR-MAX2 Trinidad; Simla Research Station Thamnophilidae Myrmotherula axillaris heterozyga FMNH FM433469 Peru; Madre de Dios Thamnophilidae Myrmotherula behni ZMCU AY676956 Ecuador; Napo; 3 km N Guagua Sumaco Thamnophilidae Myrmotherula cherriei AMNH 12392 Venezuela; Amazonas; Rio Mawarinumo Thamnophilidae Myrmotherula fulviventris ZMCU SI 649 AY676953 Ecuador; Esmeraldas; NNW Alto Tambo Thamnophilidae Myrmotherula fulviventris LSUMZ B11848 Ecuador; Esmeraldas Province; El Placer 670 M Thamnophilidae Myrmotherula fulviventris STRI JTW638 Panama; Darien Province; Puerto Pina Thamnophilidae Myrmotherula fulviventris STRI JTW214 Panama; Bocas del Toro; Valle de Risco Thamnophilidae Myrmotherula fulviventris STRI JTW645 Panama; Darien Province; Puerto Pina Thamnophilidae Myrmotherula fulviventris STRI JTW215 Panama; Bocas del Toro; Valle de Risco Thamnophilidae Myrmotherula hauxwelli clarior FMNH JH-098 AY612525 Brazil; Mato Grosso do Norte, Municipio Alta Floresta, upper Rio Teles Pires-Rio Cristalino Thamnophilidae Myrmotherula hauxwelli clarior FMNH DFS86-1373 AY612532 - Brazil; Rondonia, Cachoeira Nazare, W bank Rio Jiparana Thamnophilidae Myrmotherula hauxwelli FMNH FMNH 51490 AF118160 Brazil; Mato Grosso Thamnophilidae Myrmotherula leucophthalma FMNH FMNH 51500 AF118158 Brazil; Mato Grosso Thamnophilidae Myrmotherula leucophthalma FMNH DFS86-1201 AY612547 Brazil; Rondonia, Cachoeira Nazare, W bank Rio Jiparana Thamnophilidae Myrmotherula leucophthalma ZMCU SI 306 AY676952 Brazil; Mato Grosso; Rio Teles Pires Thamnophilidae Myrmotherula longipennis FMNH FMNH 51516 AF118159 Brazil; Mato Grosso Thamnophilidae Myrmotherula longipennis FMNH JH-105 AY612559 Brazil; Mato Grosso do Norte, Municipio Alta Floresta, upper Rio Teles Pires-Rio Cristalino Thamnophilidae Myrmotherula longipennis FMNH DFS86-1206 AY612563 Brazil; Rondonia, Cachoeira Nazare, W bank Rio . Jiparana Thamnophilidae Myrmotherula menetriesii ZMCU SI 893 AY676955 Ecuador; Napo; C. Canaday Thamnophilidae Myrmotherula multostriata LSUMZ B4354 Peru; Loreto Department; Lower Rio Napo region, E bank Rio Yanayacu, ca 90 km N Iquitos Thamnophilidae Myrmotherula obscura ZMCU S1836 AY676951 Ecuador; Sucumbios; NE Lumbaqui Thamnophilidae Myrmotherula pacifica UWBM UWBM76933 Panama; Panama; Panama City Thamnophilidae Myrmotherula pacifica STRI JTW722 Panama; Darien Province; Puerto Pina Thamnophilidae Myrmotherula schisticolor interior FMNH FM429987 Peru; Cuzco ; Paucartambo Thamnophilidae Myrmotherula schisticolor schisticolor LSUMZ B16048 Costa Rica; Heredia Province; 4 km SE Virgen del Socorro; Finca La Fortuna Thamnophilidae Myrmotherula schisticolor schisticolor LSUMZ B2124 Panama; Darien Province; About 6 km NW Cana Thamnophilidae Myrmotherula schisticolor schisticolor LSUMZ B11979 Ecuador; Esmeraldas Province; El Placer, CA 670 M 4^ Thamnophilidae Myrmotherula surinamensis AMNH Thamnophilidae Neoctantes niger FMNH Thamnophilidae Phaenostictus mcleannani ZMCU Thamnophilidae Phaenostictus mcleannani mcleannani STRI Thamnophilidae Phaenostictus mcleannani mcleannani STRI Thamnophilidae Phlegopsis erythroptera ZMCU Thamnophilidae Phlegopsis nigromaculata FMNH Thamnophilidae Phlegopsis nigromaculata FMNH Thamnophilidae Pithys albifrons ZMCU Thamnophilidae Pyriglena leuconota ZMCU Thamnophilidae Rhegmatorhina gymnops FMNH Thamnophilidae Rhegmatorhina gymnops FMNH Thamnophilidae Rhegmatorhina melanosticta ZMCU Thamnophilidae Sakesphorus bernardi ZMCU Thamnophilidae Sakesphorus bernardi LSUMZ Thamnophilidae Sakesphorus canadensis KU Thamnophilidae Sakesphorus luctuosus USNM Thamnophilidae Schistocichla leucostigma ZMCU Thamnophilidae Sclateria naevia ZMCU Thamnophilidae Taraba major NRM Thamnophilidae Taraba major obscurus STRI Thamnophilidae Taraba tnajor obscurus STRI Thamnophilidae Taraba major obscurus STRI Thamnophilidae Taraba major obscurus STRI Thamnophilidae Tereriura callinota callinota LSUMZ Thamnophilidae Terenura callinota callinota LSUMZ Thamnophilidae Terenura humeralis FMNH Thamnophilidae Terenura humeralis FMNH AMNH2988 321806 AY676960 Venezuela; Bolivar; RIO CARAPO; GUAIQUINIMA BASE CAMP Peru, Cuzco SI 647 AY676980 Ecuador; Esmeraldas; NNW Alto Tambo JTW655 Panama; Darien Province; Puerto Pina JTW656 Panama; Darien Province; Puerto Pina SI 860 AY676979 Ecuador; Napo; C. Canaday JH-348 DW-3797 SI 857 AY612573 AY612576 AY676976 Brazil; Mato Grosso do Norte, Municipio Alta Floresta, upper Rio Teles Pires-Rio Cristalino Brazil; Rondonia, Cachoeira Nazare, W bank Rio Jiparana Ecuador; Napo; C. Canaday ZMCU S2007 AY065724 Ecuador; Zamora-Chinchipe; Rio Bombuscara JH-061 JH-423 SI 825 AY612581 AY612591 AY676978 Brazil; Mato Grosso do Norte, Municipio Alta Floresta, upper Rio Teles Pires-Rio Cristalino Brazil; Mato Grosso do Norte, Municipio Alta Floresta, upper Rio Teles Pires-Rio Cristalino Ecuador; Sucumbios; N Tigre Playa S101 AY676939 Ecuador; Loja; ca 5 km SW Sabiango B5136 EF030317 Peru; depto. Lambayeque; Las Pampas, MBR6243 EF030318 Guyana; along Washikunhmra River B7012 EF030319 Brazil; Para; 52 km SSW Altamira ZMCU SI207 AY676968 S102 AY676967 Ecuador; Napo; 1 km S Puerto Napo NRM 956694 JTW664 AY676938 Paraguay; Dpto. Alto Chaco; P.N. Defensores del Chaco, Madrejon, 42 km W Panama; Darien Province; Puerto Pina JTW664 Panama; Darien Province; Puerto Pina PA-TMA-PP101 Panama; Panama; Old Gamboa Rd. JTW681 Panama; Darien Province; Puerto Pina B6176 B2198 FMNH DFS 86-130 389941 AF118156 Ecuador; Morona-Santiago Province; W slope Cordillera del Cutucu, Yapitya, on Logrono-Yaupi trail Panama; Darien Province; About 6 km NW Cana on E slope Cerro Pirre Brazil; Rondonia AY676957 Brazil, Rondonia Thamnophilidae Thamnistes anabatinus ZMCU Thamnophilidae Thamnistes anabatinus coronatus LSUMZ Thamnophilidae Thamnistes anabatinus aequatorialis LSUMZ Thamnophilidae Thamnistes anabatinus ?saturatus STRI Thamnophilidae Thamnomanes caesius ZMCU Thamnophilidae Thamnomanes . caesius LSUMZ Thamnophilidae Thamnophilus palliatus UWBM Thamnophilidae Thamnophilus aethiops LSUMZ Thamnophilidae Thamnophilus amazonicus LSUMZ Thamnophilidae Thamnophilus aroyae UWBM Thamnophilidae Thamnophilus atrinucha USNM Thamnophilidae Thamnophilus atrinucha STRI Thamnophilidae Thamnophilus atrinucha STRI Thamnophilidae Thamnophilus bridgesi LSUMZ Thamnophilidae Thamnophilus bridgesi STRI Thamnophilidae Thamnophilus bridgesi • STRI Thamnophilidae Thamnophilus bridgesi STRI Thamnophilidae Thamnophilus bridgesi STRI Thamnophilidae Thamnophilus bridgesi STRI Thamnophilidae Thamnophilus caerulescens NRM Thamnophilidae Thamnophilus caerulescens UWBM Thamnophilidae Thamnophilus caerulescens FMNH Thamnophilidae Thamnophilus cryptoleucus ZMCU Thamnophilidae Thamnophilus cryptoleucus LSUMZ Thamnophilidae Thamnophilus divisorius PNSD Thamnophilidae Thamnophilus doliatus Thamnophilidae Thamnophilus doliatus Thamnophilidae Thamnophilus doliatus NRM S1607 B2154 B6152 JTW179 S1312 B9482 MAB02 B14649 B13045 RTB395 B393 JTW254 JTW673 B16149 JTW056 CR-TBR2756 RCF035 JTW388 JTW080 NRM 967007 RCF2148 395426 S1196 B7285 228 NRM 956691 AY676946 AY676947 EF030320 AY962686 EF030321 EF030322 EF030323 EF030324 AY078176 AY962812 EF030325 AY676941 EF030326 EF030341 AF082057 AY370563 AY676940 Ecuador; Esmeraldas; Alto Tambo Panama; Darien Province; About 6 km NW Cana Ecuador; Morona-Santiago Province; W slope Cordillera del Cutucu, Yapitya, on Logrono-Yaupi trail Panama; Bocas del Toro Province; Chiriqui to Chiriqui Grande Road at continental divide Brazil; Mato Grosso; Rio Teles Pires Guyana; Northwest District; Baramita Bolivia; Departamento de Santa Cruz; Provincia de Florida; Samaipata, 23.2 km E; 1350 m Bolivia.Santa Cruz Department Bolivia; depto. Santa Cruz; Velasco, W bank Rio Paucema Bolivia; depto. Cochabamba; prov. Chapare, San Onofre, ca 43 km W Villa Tunari Panama; prov. Bocas del Toro; Isla San Cristobal Panama; Bocas del Toro Panama; Darien Province; Puerto Pina Costa Rica; prov. Puntarenas; 2 km SE Dominical Panama; Chiriqui Province; Puerto Limones, Burica Peninsula Costa Rica; Dominical Baru Panama; Veraguas Province; Pontuga Panama; Chiriqui Province; Yerbazales, Burica Peninsula Panama; Chiriqui Province; Puerto Limones, Burica Peninsula South America South America Brazil; Sao Paulo; Boraceia Ecuador; Napo; Rio Napo/Aguarico Peru; depto. Loreto; Amazonas I. Pasto, 80 km NE Iquitos Brazil; Acre, Munic. Mancio Lima, Parque Nacional da Serra do Divisor ? Paraguay; Dpto. Alto Chaco; P.N. Defensores del Chaco, Madrejon, 42 km W Thamnophilidae Thamnophilus doliatus UWBM Thamnophilidae Thamnophilus doliatus nigricristatus STRI Thamnophilidae Thamnophilus doliatus radiatus LSUMZ Thamnophilidae Thamnophilus doliatus doliatus STRI Thamnophilidae Thamnophilus insignis LSUMZ Thamnophilidae Thamnophilus murinus USNM Thamnophilidae Thamnophilus nigriceps UAM Thamnophilidae Thamnophilus nigriceps STRI Thamnophilidae Thamnophilus nigriceps STRI Thamnophilidae Thamnophilus nigrocinereus LSUMZ Thamnophilidae Thamnophilus palliatus UWBM Thamnophilidae Thamnophilus praecox ZMCU Thamnophilidae Thamnophilus praecox ANSP Thamnophilidae Thamnophilus punctatus USNM Thamnophilidae Thamnophilus ruficapillus UWBM Thamnophilidae Thamnophilus ruficapillus cochabambe UWBM Thamnophilidae Thamnophilus schistaceus LSUMZ Thamnophilidae Thamnophilus stictocephalus LSUMZ Thamnophilidae Thamnophilus sticturus UWBM Thamnophilidae Thamnophilus tenuepunctatus ANSP Thamnophilidae Thamnophilus torquatus LSUMZ Thamnophilidae Thamnophilus unicolor ZMCU Thamnophilidae Thamnophilus unicolor LSUMZ Thamnophilidae Thamnophilus zarumae LSUMZ Thraupidae Acanthidops bairdii LSUMZ Thraupidae Anisognathus flavinucha LSUMZ Thraupidae Bangsia arcaei STRI RTB390 EF030327 Bolivia; depto. Santa Cruz; prov. Cordillera, 10.6 km E Abapo JTW582 Panama; Code Province; Rosario (near Anton B10890 Peru; Ucayali Department; N. bank Rio Abujao, 2 km E Caserio de Abujao TR-THD2 Trinidad; Simla Research Station-site 2 B7486 EF030328 Venezuela; terr. Amazonas; Cerro de Neblina camp \JW B9206 EF030329 V l l Guyana; Northwest District; Baramita 20238 EF030330 Panama; prov. Panama, Lago Bayano PA-TNG-PA300 Panama; Panama; Lago Bayano; Isla Maje PA-TNG-PA301 Panama; Panama; Lago Bayano; Isla Maje B20233 EF030331 Brazil; Amazonas; Munic. Novo Airao; Arquipelago das Anavilhanas MAB2 EF030332 Bolivia; depto. Santa Cruz; prov. Florida, 23.2 km E Samaipata S108 AY676942 Ecuador; Sucumbios; Rio Lagarto Cocha B3190 EF030333 Ecuador; prov. Sucumbios; Imuya Cocha B4172 EF030334 Guyana; Berbice; West bank Dubulay ranch RTB347 EF030336 Bolivia; depto. Santa Cruz; prov. Cordillera, El Tambo, 14 km SE Comarapa RTB347 Bolivia; Departamento de Santa Cruz; Provincia de Caballero; Tambo; Comarapa, 14 km SE; 1600 m B12559 EF030337 Bolivia; depto. Santa Cruz; Velasco; 50 km ESE Florida, Arroyo de Encanto B13850 EF030335 Bolivia; depto. Santa Cruz; Serrania de Huanchaca, ca 45 km E Florida RTB355 Bolivia; Departmento de Santa Cruz; Province de Cordillero; Abapo 10.6 K M E. B1686 EF030338 Ecuador; prov. Zamora Chinchipe; Zaruma B13900 EF030339 Bolivia; depto. Santa Cruz; Serrania de Huanchaca, 45 km E Florida S i l l AY676943 Ecuador; El Oro; 9 km W Pinas B12144 AY962685 Ecuador; Pichincha Province B191 EF030340 Peru; depto. Piura; km 34 on Olmos-Bagua Chica Hwy B-16267 AF489878 Costa Rica: Provincia San Jose', Cerro de la Muerte, km 113 Pan American Highway; B-566 A Y3 83090 Peru: Dept. Puno, Abra de Maruncunca JTW157 Panama;Bocas del Toro; Chiriqui to Chiriqui Grande Road at continental divide Thraupidae Basileuterus rivularis LSUMZ Thraupidae Buthraupis montana LSUMZ Thraupidae Calochaetes coccineus LSUMZ Thraupidae Calyptophilus frugivorus Thraupidae Calyptophilus tertius Thraupidae Camarhynchus parvulus Thraupidae Cainarhynchus pauper Thraupidae Camarhynchus psittacula Thraupidae Catamenia inornata Thraupidae Certhidea fusca Thraupidae Certhidea olivacea Thraupidae Chlorochrysa calliparaea LSUMZ Thraupidae Chlorochrysa phoenicotis LSUMZ Thraupidae Chlorophanes spiza LSUMZ Thraupidae Chlorophanes spiza STRI Thraupidae Chlorophanes spiza STRI Thraupidae Chlorophanes spiza LSUMZ Thraupidae Chlorophanes spiza STRI Thraupidae Chlorophanes spiza STRI Thraupidae Chlorornis riefferii LSUMZ Thraupidae. Chrysothlypis chrysomelas STRI Thraupidae Chrysothlypis chrysomelas LSUMZ Thraupidae Cissopis leveriana LSUMZ Thraupidae Cnemoscopus rubrirostris LSUMZ Thraupidae Coereba flaveola UMMZ Thraupidae Coereba flaveola UMMZ Thraupidae Coereba flaveola Thraupidae Coereba flaveola Thraupidae Coereba flaveola Thraupidae Coereba flaveola STRI Thraupidae Coereba flaveola STRI B-7499 . AY340217 B-365 AY383091 B-6134 AY383092 DQ166566 DQ166575 AF108796 AF108795 AF108798 AF310049 AY672052 AF108806 B-8103 AY383095 B-34873 AY383094 B-2838 AF006215 HA-CSP-HA15 HA-CSP-HA51 B2226 JTW598 TR-CSP4 B-1859 AY383093 JTW016 B-2189 AF006220 B-1143 AY383096 B-5624 AF006222 227691 AF489880 227711 AF489882 AF310068 AF290151 AF382993 AB-CFA2 BH-CFA3 Venezuela, Amazonas Territory Peru: Dept. Cajamarca, Cerro Chinguela Ecuador: Prov. Morona-Santiago Hispanola Hispanola Galapagos Galapagos Galapagos South America Ecuador, Galapagos, San Cristobal Galapagos Peru: Dept.' Pasco, Playa Pampa Ecuador: Prov. Pichincha Peru: Dept. Loreto, 1 km N Rio Napo, 157 km by river NNE Iquitos Honduras;La Ceiba; Honduras;La Ceiba; Panama; Darien Province: Cana on E slope Cerro Pirre Panama;Cocle; El Cope National Park Trinidad;Lemon Road off of Las Lapis; Peru: Dept. Pasco, Cumbre de Ollon Panama;Veraguas;Santa Fe Panama: Prov. Darien, about 6 km NW Cana Bolivia: Dept. La Paz, Rio Beni Peru: Dept. Amazonas, 30 km by road E Florida on road to Rioja Puerto Rico: Mun. Guayama, Bahia de Jobos, 178559N 668179W; Venezuela: Distrito Federal, highway between Colonia Tovan and Chichiriviche; ? Bahamas Bahamas Bahamas;Abaco; Bahamas;Ridge; Thraupidae Coereba flaveola UMMZ UMMZ 225179 AY383089 Jamaica: Trelawny Par., Cornwall Thraupidae Coereba flaveola STRI JA-CFA1 Jamaica;Luana Point; Thraupidae Coereba flaveola STRI JA-CFA4 Jamaica;Paradise, near Sav-la-mar; Thraupidae Coereba flaveola AMNH AMNH6829 Mexico;Quintana Roo, Cozumel Island, El . Codral;SAN MIGUEL Thraupidae Coereba flaveola STRI PA-CFA341 Panama;Bocas, Isla San Cristobal; Thraupidae Coereba flaveola STRI PA-CFA2 Panama;Isla Chapera; Thraupidae Coereba flaveola STRI PR-CFA11367 Puerto Rico;Boqueron; Thraupidae Coereba flaveola STRI RD-CFA1 Republica Dominicana;Golf Club-Jarabacoa; Thraupidae Coereba flaveola STRI RD-CFA2 Republica Dominicana;Golf Club-Jarabacoa; Thraupidae Coereba flaveola AF310045 St. Lucia Thraupidae Coereba flaveola STRI SV-CFA2129 St. Vincent;St. George Parish, Indian Bay; Thraupidae Conirostrum albifrons AF447365 Peru Thraupidae Conirostrum bicolor STRI TR-CBC1 AK383025 South America Thraupidae Conirostrum sitticolor AF383000 South America Thraupidae Conirostrum speciosum FMNH FMNH 334602 AY190168 Bolivia: Santa Cruz, Chiquitos Thraupidae Conothraupis speculigera LSUMZ B-5127 AF006223 Peru: Dept. Lambayeque, Las Pampas, km 885 Pan-American Hwy, 11 km by road from Olmos Thraupidae Coryphospingus cucullata UMMZ 235435 AF447366 captive Thraupidae Creurgops dentata LSUMZ B-580 AF006224 Peru: Dept. Puno, Abra de Maruncunca, 10 km SW San Juan del Oro Thraupidae Creurgops verticalis LSUMZ B-7974 AY190166 Peru, Dept. Pasco, Playa 8 Km NW Cushi Thraupidae Cyanerpes caeruleus LSUMZ B-14737 AF006225 Bolivia: Dept. Santa Cruz, Serrania de Huanchaca, 25 km SE Catarata Arco Iris Thraupidae Cyanerpes caeruleus LSUMZ B11825 Ecuador Esmeraldas Province: El Placer, CA 670 M Thraupidae Cyanerpes caeruleus STRI EC-CCE1612 Ecuador;Provincia de Santiago; Thraupidae Cyanerpes caeruleus STRI TR-CCE1 Trinidad;Simla Research Station; Thraupidae Cyanerpes cyaneus cyaneus FMNH FM391637 Brazil;Amapa; Thraupidae Cyanerpes cyaneus STRI HA-CCN-HA82 Honduras;La Ceiba; Thraupidae Cyanerpes cyaneus STRI JTW451 Panama;Chiriqui;Bartolo Arriba, Burica Peninsula Thraupidae Cyanerpes cyaneus STRI CC-CCN1 Trinidad;Chacachacare Island; Thraupidae Cyanerpes lucidus STRI PA-CLC34493 ' Panama;Prov. Darien near Rancho Frio Station; 400m; Thraupidae Cyanerpes nitidus FMNH FMNH MPEG AY190167 Brazil: Rhondonia DW3813 Thraupidae Cyanerpes nitidus FMNH FM390048 Brazil;Rondonia; Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Cypsnagra Dacnis Dacnis Dacnis Dacnis Dacnis Delothraupis Diglossa Diglossa Diglossa Diglossa Diglossa Diglossa Diglossa Diglossa Diglossa Diglossa Dolospingus Dubusia Emberizoides Emberizoides Eucometis Eucometis Eucometis Eucometis Euneornis Geospiza Geospiza Geospiza hirundinacea cayana cayana cayana cayana venusta castaneoventris albilatera baritula baritula humeralis humeralis lafresnayii major plumbeal plumbea.2 sittoides fringilloides taeniata herbicola ypiranganus penicillata penicillata penicillata penicillata campestris conirostris difficilis fords LSUMZ B15289 STRI LTL102 LSUMZ B-15077 STRI UL056 STRI TR-DAC1 LSUMZ B2192 . LSUMZ B-6931 LSUMZ B262 University MEX350 of Mexico STRI JTW465 LSUMZ LSUMZ LSUMZ LSUMZ USNM LSUMZ NRM UWBM LSUMZ LSUMZ UWBM STRI FMNH B-351 B16068 B16239 B5558 625323 B-7710 NRM 976735 UWBM70773 B-6551 B18544 UWBM69247 JTW443 331119 AY 115394 Bolivia, Santa Cruz Department PA;Bocas del Toro; Cerro Chalite AF006227 Bolivia: Dept. Santa Cruz, Velasco, 13 km SW Piso Firme Panama;Bocas del Toro; Cerro Chalite Trinidad;Simla Research Station; Panama; Darien Province: Ca 6km NW Cana. AY383097 Peru: Dept. Huanuco, Quebrada Shugush Peru;Departmento Cajamarca;"Batan" on Sapalache-carmen Trail Mexico;Jalisco;Sierra de Manantlan, Las Joyas Panama;Chiriqui;Volcan Baru Parque National Peru;Departmento Piura; "Cruz Blanca" ca. 33 road K M SW Huancabamba; South America Peru: Dept.Cajamarca, Cerro Chinguela, 5 km NE Sapalache South America Costa Rica Provincia Heredia; Finca la Fortuna Costa Rica Provincia San Jose; La Georgina Peru;Departmento San Martin; 28km NE Tarapoto; South America Peru: Dept. Huanuco, Unchog Pass NNW Acomayo Argentina;Provincia de Corrientes;Corrientes Bolivia: Dept. Santa Cruz, Rio Quizer Bolivia Santa Cruz Department: Velasco; Parque Nacional Noel Keonpff Mercado 60 km ESE of Florida Nicaragua;Departamento de Managua, Managua 17 KM S; Panama;Chiriqui;Yerbazales, Burica Peninsula AF489885 Jamaica: Surrey, Portland, Hollywell Park; AFI 08769 Galapagos AF108788 Galapagos AFI 08771 Galapagos AF310050 AF006229 AF290155 AY705435 AY383098 AY228057 AF006231 ON O Thraupidae Geospiza fuliginosa AF108784 Galapagos Thraupidae Geospiza magnirostris AF108778 Galapagos Thraupidae Geospiza scandens AF108779 Galapagos Thraupidae Haplospiza rustica LSUMZ B16173 Costa Rica San Jose Province: La Georgina, km 95 Pan American Hwy. Thraupidae Haplospiza rustica STRI EC-HRU514 Ecuador;Provincia Carchi; Thraupidae Haplospiza rustica LSUMZ B7451 Venezuela Amazonas Territory: Cerro De La Neblina Camp Vn 1800 M Thraupidae Haplospiza unicolor AF290156 South America Thraupidae Hemispingus atropileus AF383019 South America Thraupidae Hemispingus auricularis AY039291 Thraupidae Hemispingus calophrys AY039300 Thraupidae Hemispingus frontalis AF383020 South America Thraupidae Hemispingus melanotis AF100537 South America Thraupidae Hemispingus parodii AY180913 Thraupidae Hemispingus piurae AY039294 Thraupidae Hemispingus rufosuperciliaris AY039297 Thraupidae Hemispingus verticalis AF100538 South America Thraupidae Hemithraupis flavicollis LSUMZ B-5102 AF006235 Peru: Dept. Loreto, S Rio Amazonas, ca. 10 km SSW mouth Rio Napo on E bank Quebrada Vainilla Thraupidae Heterospingus rubrifrons STRI JTW278 Panama;Bocas del Toro; Cerro Chalite Thraupidae Heterospingus rubrifrons LSUMZ B28692 Panama; Colon Province: Achiote Road at Rio Providencia Thraupidae Heterospingus xanthopygius LSUMZ B-2324 AF006236 Panama: Prov. Darien, Cana on E slope Cerro Pirre Thraupidae Iridosornis analis LSUMZ B-1706 AY383099 Peru: Dept. Pasco, Santa Cruz Thraupidae Lamprospiza melanoleuca LSUMZ B-9678 AF006238 Bolivia: Dept. Pando, Nicolas Suarez, 12 km by road S of Cobija, 8 km W on road to Mucden Thraupidae Lanio aurantius Nevada DHB3785 Honduras;Departmento Atlantida; Thraupidae Lanio fulvous LSUMZ B34944 Ecuador Napo Province: 40 km NNE Tena Thraupidae Lanio leucothorax STRI JTW572 Panama;Cocle; El Cope National Park, Thraupidae Lanio versicolor LSUMZ B-1014 AF006239 Bolivia: Dept. La Paz, Rio Beni, ca. 20 km by river N. Puerto Linares Thraupidae Loxigilla noctis AF310041 Saint Lucia Thraupidae Loxigilla portoricensis LSUMZ B-11351 AF489886 Puerto Rico: Cabo Rojo, Boqueron, Penones de Melones; Thraupidae Loxigilla violacea AMNH 25433 AF489887 Dominican Republic: Provincia Independencia, Parque Nacional Sierra de Baoruco; Thraupidae Loxipasser anoxanthus FMNH 331107 AF489888 Jamaica: Surrey, Portland, Hollywell Park; Thraupidae Melanospiza richardsoni AF310043 Saint Lucia Thraupidae Nemosia pileata LSUMZ B-7295 AF006241 Peru: Dept. Loreto, Amazonas I. Pasto, 80 km NE Iquitos Thraupidae Neothraupis fasciata B-13914 AY383100 Bolivia: Dept. Santa Cruz, Serrania de Huanchaca, 45 km E Florida Thraupidae Nephelornis oneilli LSUMZ B-8402 AF006243 Peru: Dept. Pasco, Millpo, E. Tambo de Vacas on Pozuzo-Chaglla trail Thraupidae Nesospingus speculiferus LSUMZ B-11375 AF489889 Puerto Rico: San German, along route 120 near Mt. Alegrillo; LSUMZ 150230; Thraupidae Oreomanes fraseri LSUMZ B-2069 AF006244 Peru: Dept. Lima, about 13 road km W. Milloc Thraupidae Oryzoborus angolensis STRI HA-OFU-HA37 Honduras;La Ceiba; Thraupidae Oryzoborus angolensis STRI OAN PA Thraupidae Oryzoborus angolensis AF310055 Ecuador Thraupidae Oryzoborus angolensis STRI EC-OAN1 Ecuador.Jatun Sacha; Thraupidae Oryzoborus angolensis STRI JTW209 Panama;Bocas del Toro; Valle de Risco Thraupidae Oryzoborus angolensis STRI JTW435 Panama;Chiriqui;Yerbazales, Burica Peninsula Thraupidae Oryzoborus crassirostris FMNH 339668 AF489890 Venezuela: Sucre, Guaraunos, 14 km SSE; Thraupidae Oryzoborus funereus STRI PE-OAN10892 Peru;Rio Abujao; Thraupidae Paroaria coronata UMMZ 233278 AF447371 captive Thraupidae Phrygilus alaudinus QUMEL na AY005218 Argentina, Tafi del Valle, Tucuman, Thraupidae Pinaroloxias inornata AF108791 Galapagos Thraupidae Pipraeidea melanonota LSUMZ B-12070 AY383101 Ecuador: Prov. Pinchincha, Mindo Thraupidae Poospiza alticola ZMUC 664 AY005199 Peru, Ancash Thraupidae Poospiza baeri QUMEL na AY005200 Argentina, Tafi del Valle, Tucuman, Thraupidae Poospiza boliviano LSUMZ B1198 AY005201 .Bolivia, La Paz Department Thraupidae Poospiza. caesar ZMUC 667 AY005202 Peru, Andamarca, Ayacucho, Thraupidae Poospiza erythrophrys QUMEL na AY005203 Argentina, Finca El Rey, Salta Thraupidae Poospiza garleppi LSUMZ B106745 AY005204 Bolivia, Cochabamba Department Thraupidae Poospiza . hispaniolensis LSUMZ B5205 AY005205 Peru, Lambayeque Department Thraupidae Poospiza hypochondria ZMUC 671 AY005207 Bolivia, Cochabamba Thraupidae Poospiza melanoleuca ZMUC 5031 AY005210 Bolivia, Palmarcito, Chuquisaca Thraupidae Poospiza ornata QUMEL na AY005213 Argentina, Amanao, Catamarca Thraupidae Poospiza torquata ZMUC 5036 AY005215 Bolivia, Chuquisaca Thraupidae Poospiza whitii ZMUC 5057 AY005212 Bolivia, Sopachuy, Chuquisaca Thraupidae Pyrrhocoma ruficeps MVZ 165617 AF006249 Paraguay: Dept. Itapu, El Tirol, 19.5 km by road NNE Encarnacion Thraupidae Ramphocelus passer STRI RPA Honduras Thraupidae Ramphocelus passer STRI RPA Honduras Thraupidae Ramphocelus bresilius U15724 9 Thraupidae Ramphocelus carbo LSUMZ B4988 U15723 Peru: Dpto. Loreto; S Ry'o Amazonas, ca. 10 km SSW Ry'o Napo Thraupidae Ramphocelus costaricensis U15720 Costa Rica, Punteranas Thraupidae Ramphocelus costaricensis U15722 Costa Rica, Punteranas Thraupidae Ramphocelus costaricensis STRI JTW396 Panama;Chiriqui;Yerbazales, Burica Peninsula Thraupidae Ramphocelus dimidiatus STRI RDI PA Thraupidae Ramphocelus icteronotus LSUMZ B12017 U15719 Ecuador: Prov. Esmeraldas; El Placer Thraupidae Ramphocelus icteronotus STRI JTW611 Panama;Darien;Puerto Pina Thraupidae Ramphocelus icteronotus STRI JTW676 Panama;Darien;Puerto Pina Thraupidae Ramphocelus nigrogularis LSUMZ B2850 U15721 Peru: Dpto. Loreto; 1 km N Ry'o Napo, Thraupidae Ramphocelus passerinii LSUMZ B16152 U15717 Costa Rica: Prov. Heredia; ca. 5 km by road S. Puerto Viejo Thraupidae Ramphocelus sanguinolentus MEX-117 U15718 Mexico: Vera Cruz; Sierra de Santa Martha, El Bastanol Thraupidae Rhodinocichla rosea STRI PA-RRO-PA59 Panama;01d Gamboa Road-washout; Thraupidae Saltator albicollis STRI EC-SAL3580 Ecuador; Provincia Azuay; Thraupidae Saltator albicollis STRI EC-SAL4541 Ecuador;Provincia Zanora-Chinchipe; Thraupidae Saltator albicollis STRI JTW409 Panama;Chiriqui;Yerbazales, Burica Peninsula Thraupidae Saltator albicollis STRI PU-SAL5251 Peru;Lambayeque; Thraupidae Saltator • atriceps Kansas KU5984 El Salvador University Thraupidae Saltator atriceps Kansas KU1979 Mexico University Thraupidae Saltator atriceps Kansas KU1979 Mexico University Thraupidae Saltator atricollis NRM 966978 AY228082 ? Thraupidae Saltator caerulescens mutus FMNH FM391613 Brazil;Amapa; Thraupidae Saltator caerulescens AF089059 ? Thraupidae Saltator coerulescens AF290154 Bolivia, Santa Cruz Thraupidae Saltator caerulescens FM334590 Bolivia;El Beni; Thraupidae Saltator coerulescens FM393897 Mexico;Jalisco; Thraupidae Saltator maximus LSUMZ B28178 Panama; Chiriqui Province: Dist. Gualaca, Codillera Thraupidae Saltator maximus STRI Thraupidae Saltator maximus STRI Thraupidae Saltator maximus . AMNH Thraupidae Saltator striatipectus STRI Thraupidae Saltatricula multicolor M V Z Thraupidae Schistochlamys melanopsis LSUMZ Thraupidae Sericossypha albocristata LSUMZ Thraupidae Sicalis flaveola Thraupidae Sicalis luteola FMNH Thraupidae Sporophila americana Thraupidae Sporophila americana STRI Thraupidae Sporophila americana STRI Thraupidae Sporophila americana STRI Thraupidae Sporophila bouvreuil MACN Thraupidae Sporophila caerulescens UWBM Thraupidae Sporophila caerulescens MACN Thraupidae Sporophila castaneiven Thraupidae Sporophila castaneivent AMNH Thraupidae Sporophila cinnamomea MACN Thraupidae Sporophila collaris FMNH Thraupidae Sporophila collaris MACN Thraupidae Sporophila falcirostris MACN Thraupidae Sporophila hypochroma MACN Thraupidae Sporophila hypoxantha MACN Thraupidae Sporophila leucoptera MACN Thraupidae Sporophila luctuosa AMNH Thraupidae Sporophila melanogaster AMNH Thraupidae • Sporophila minuta USNM Thraupidae Sporophila minuta STRI JTW282 JTW717 AMNH 11984 CC-SAL1 179401 B-9669 B-5630 389274 JTW124 JTW445 JTW688 MACN 39763 UWBM 70776 MACN 46181 AMNH 277325 MACN 52374 334566 MACN 1132a MACN 39081 MACN 48247 MACN 45378 MACN 45392 AMNH 822336 315886 USNM 62108 le JTW371 AF383107 AF489892 AY383102 AF006251 AY491528 AF489893 AF310054 AY387415 AY387417 AF310056 AY387419 AY387423 AF489895 AY387424 AY387425 AY387428 AY387430 AY387431 AY387432 AY387433 AY387435 Central, 4.3 km by road S. Lago Fortuna dam Panama;Bocas del Toro; Cerro Chalite Panama;Darien;Puerto Pina Venezuela;Bolivar;40 KM E TUMAREMO ON ROAD TO BOCHINCHE Aviary of Luis F. Baptista, CAS Accn. 5067; Bolivia: Dept. Pando, Nicolas Suarez Peru: Dept. Amazonas, 30 km by road E Florida on road to Rioja ? Brazil: Roraima, Fazenda Santa Cecilia, E bank Rio Branco, across from Boa Vista; Ecuador, Pedernales Panama;Bocas del Toro; Chiriqui to Chiriqui Grande Road at continental divide Panama;Chiriqui;Bartolo Arriba, Burica Peninsula Panama;Darien;Puerto Pina Misiones, Argentina Argentina;Provincia de Corrientes, Corrientes 45 kmS.; Cordoba, Argentina South America Amazonas River, Brasil Entre Rios, Argentina Bolivia: El Beni, Laguna Suarez, 5 km SW Trinidad; Mendoza, Argentina Misiones, Argentina Corrientes, Argentina Corrientes, Argentina Corrientes, Argentina Loreto, Peru Rio Grande do Sul, Brasil Berbice, Guyana Panama;Cocle; Penenome Thraupidae Sporophila minuta AMNH Thraupidae Sporophila minuta STRI Thraupidae Sporophila minuta USNM Thraupidae Sporophila nigricollis nigricollis FMNH Thraupidae Sporophila nigricollis Thraupidae Sporophila nigricollis MACN Thraupidae Sporophila palustris MACN Thraupidae Sporophila plumbea Thraupidae Sporophila ruficollis FMNH Thraupidae Sporophila ruficollis MACN Thraupidae Sporophila schistacea FMNH Thraupidae Sporophila schistacea Thraupidae Sporophila schistacea FMNH Thraupidae Sporophila schistacea STRI Thraupidae Sporophila telasco AMNH Thraupidae Sporophila torqueola NEVADA Thraupidae Sporophila zelichi MACN Thraupidae Tachyphonus coronatus UWBM Thraupidae Tachyphonus cristatus AMNH Thraupidae Tachyphonus delatrii STRI Thraupidae Tachyphonus delatrii STRI Thraupidae Tachyphonus delatrii STRI Thraupidae Tachyphonus delatrii STRI Thraupidae Tachyphonus delatrii STRI Thraupidae Tachyphonus luctuosus STRI Thraupidae Tachyphonus luctuosus NEVADA Thraupidae Tachyphonus luctuosus Thraupidae Tachyphonus rufus FMNH Thraupidae Tachyphonus rufus STRI Thraupidae Tachyphonus surinamus LSUMZ Thraupidae Tangara argyrofenges ANSP 287785 TR-SMI1 622227f FM392597 MACN 39761 MACN 48513 B13986 334582 MACN 31342 FM433821 FM433822 JTW506 AMNH 152815 AY387443 DHB3560 MACN 52378 AY387444 UWBM70535 AMNH11925 JTW255 JTW257 JTW004 JTW622 JTW634 PA-TLC190 GAV1988 JKO1-236 FM392631 CC-TRF3 B-4795 AF006253 4482 AY383104 AY387434 AY387436 AF310053 AY387437 AY387438 AY115407 AF489896 AY387440 AF290149 Tapajoz river, Brasil Trinidad;Livestock Research Station; Guyana; Wiwitau Mount Brazil;Para; Ecuador, Santo Domingo Misiones, Argentina Entre Rios, Argentina Bolivia, Santa Cruz Department Bolivia: Santa Cruz, Chiquitos Purubi, 30 km S San Jose de Chiquitos; Cordoba, Argentina Cuzco;Paucartambo Bolivia, La Paz Peru;Cuzco;Paucartambo Panama;Chiriqui;Volcan Baru Parque National Lima, Peru Honduras;Departmento Copan; Entre Rios, Argentina Argentina;Provincia de Corrientes, Corrientes 10 kmN; Venezuela;Bolivar;40 KM E TUMAREMO ON ROAD TO BOCHINCHE Panama;Bocas del Toro; Valle de Risco Panama;Bocas del Toro; Valle de Risco Panama;Cocle; El Cope National Park Panama;Darien;Puerto Pina Panama;Darien;Puerto Pina Panama;Cocle: Molejon: Finca Moreno; Honduras;Departamento Atlantida; Honduras;Departamento Atlantida; Brazil;Para; Trinidad;Chacachacare Island; Peru: Dept. Loreto, S Rio Amazonas, about 10 km SSW Rio Napo Peru: Dept. Puno, Abra de Maruncunca, 10km SW San Juan del Oro Thraupidae Tangara arthus LSUMZ B-22591 AY383106 Fxuador: Prov. Morona-Santiago, W Slope de Cutucci Yapitya Thraupidae Tangara arthus LSUMZ B-34876 AY383105 Peru: Dept. Cajamarca, Cerro Chinguela, 5 km NE Sapalache Thraupidae Tangara callophrys LSUMZ B-34961 AY383107 Peru: Dept. Pasco, Playa Pampa, about 8 km NW Cushi on trail to Chaglla Thraupidae Tangara cayana LSUMZ B-15414 AY383108 Ecuador: Prov. Pichincha, 30 km SE Santo Domingo de los Colorados; Thraupidae Tangara chilensis MVZ 169699 AY383110 Bolivia: Dept. La Paz, Rio Beni, ca 20km by river N. Puerto Linares Thraupidae Tangara chrysotis LSUMZ B-34927 AY383111 Jamaica: Trelawny Par., Cornwall, Good Hope Plantation Thraupidae Tangara cucullata STRI GR-TCU2 AY383112 Peru: Dept. Huanuco, Quebrada Shugush, 30km on Huanuco-La Union road Thraupidae Tangara cyanicollis LSUMZ B-15352 AY383115 Dominican Republic: Prov. Independencia, Parque Nacional Sierra de Baoruco, Zapoten, Sawmill Clearing Thraupidae Tangara cyanicollis LSUMZ B-34904 AY383114 Peru: Dept. Pasco, Santa Cruz, about 9 km SSE Oxapampa Thraupidae Tangara cyanocephala FMNH 427278 AY383117 Jamaica: Surrey, Portland, Hollywell Park Thraupidae Tangara cyanoptera LSUMZ B-7436 AY383116 Ecuador: Prov. Pinchincha, Mindo Thraupidae Tangara cyanotis LSUMZ B-22708 AY383119 Bolivia: Dept. Pando, Nicolas Suarez, 12km by road S of Cobija, 8 km W on road to Mucden Thraupidae Tangara desmaresti FMNH 395478 AY383120 Ecuador: Zamora-Chinchipe, Panguri about 12km NE San Francisco del Vergel, 4 370S, 78 580W Thraupidae Tangara dowii LSUMZ B-16020 AY383121 Ecuador: Prov. Pichincha, 35 km SE Santo Domingo de los Colorados; 00 160N, 78 500W Thraupidae Tangara dowii STRI JTW535 Panama;Chiriqui;Cerro Colorado Thraupidae Tangara fastuosa FMNH 427276 AY383123 Bolivia: Dept. La Paz, Prov. B. Saavedra, 83 km by road E Charazani, Cerro Asunta Pata Thraupidae Tangara florida LSUMZ B-34982 AY383122 Bolivia: Dept. Santa Cruz, Serrania de Huanchaca, 45 km E Florida Thraupidae Tangara florida LSUMZ B11989 Ecuador Esmeraldas Province: El Placer, CA 670 M Thraupidae Tangara florida STRI UL106 PA;Panama Province;Cerro Jefe Thraupidae Tangara florida STRI JTW169 Panama;Bocas del Toro; Chiriqui to Chiriqui Grande Road at continental divide Thraupidae Tangara florida STRI JTW607 Panama;Cocle; El Cope National Park Thraupidae Tangara florida STRI PA-TAL1014 Panama;Panama:Darien: Tropic Star Lodge: Pinas-Sambu Trail; Thraupidae Tangara fucosa LSUMZ B-1398 AY383125 Ecuador: Prov. Napo, 40km NNE Tena; 00 440N, 77 420W Thraupidae Tangara . fucosa STRI PA-TFU1008 Panama;Panama:Darien: Tropic Star Lodge: Pinas-Sambu Trail N 07° 41.448 W 78° 11.882; Thraupidae Tangara guttata LSUMZ B-2190 AY383126 Peru: Dept. Cajamarca, 1 mi N San Jose de Lourdes, Cordillera del Condor Thraupidae Tangara guttata STRI JTW013 Panama;Veraguas;Santa Fe Thraupidae Tangara guttata AMNH AMNH8807 Venezuela; Amazonas ;TAM ACU ARI Thraupidae Tangara gyrola LSUMZ B-4258 AY383131 Bolivia: Dept. Santa Cruz, Serrania de Huanchaca, 45km E Florida Thraupidae Tangara gyrola LSUMZ B-2149 AY383127 Ecuador: Prov. Napo, 40km NNE Tena; 00 440N, 77 420W Thraupidae Tangara gyrola LSUMZ B-27281 AY383130 Ecuador: Prov. Pichincha, 5 km NE Puento Quito; 00 090N, 79 120W Thraupidae Tangara gyrola LSUMZ B-14862 AY383128 Grenada: 6.5km SW Grenville Thraupidae Tangara gyrola LSUMZ B-22850 AY383129 St. Vincent: Cumberland Valley Thraupidae Tangara gyrola LSUMZ B34911 Ecuador;Pichincha; Thraupidae Tangara gyrola STRI JTW599 Panama;Cocle; El Cope National Park Thraupidae Tangara gyrola STRI PA-TGY1016 Panama;Panama:Darien: Tropic Star Lodge: Pinas-Sambu Trail; Thraupidae Tangara gyrola STRI TR-TGY1 Trinidad;Simla Research Station; Thraupidae Tangara heinei LSUMZ B-34896 AY383132 Brazil: Pernambuco, Taquaritinga Thraupidae Tangara icterocephala LSUMZ B-16032 AY383133 Brazil: Pernambuco, Taquaritinga Thraupidae Tangara icterocephala STRI JTW093 Panama;Bocas del Toro; Chiriqui to Chiriqui Grande Road at continental divide Thraupidae Tangara icterocephala STRI JTW336 Panama;Panama;Cerro Campana Thraupidae Tangara icterocephala STRI RCF020 Panama;Veraguas;Santa Fe Thraupidae Tangara inornata LSUMZ B-28766 AY383134 Venezuela: Amazonas Territory, Cerro de la Neblina Camp VII Thraupidae Tangara inornata STRI JTW716 Panama;Darien;Puerto Pina Thraupidae Tangara inornata STRI JTW718 Panama;Darien;Puerto Pina Thraupidae Tangara johannae LSUMZ B-29956 AY383135 Bolivia: Dept. La Paz, Prov. B. Saavedra, 83 km by road E Charazani, Cerro Asunta Pata Thraupidae Tangara labradorides LSUMZ B-32686 AY383136 Brazil: Alagoas, Ibateouara, Envenho Ceimba, Usina Serra Grande Thraupidae Tangara labradorides LSUMZ B-34976 AY383137 Costa Rica: Prov. Heredia, 4 km SE Virgen del Socorro Thraupidae Tangara larvata LSUMZ B-34909 AY383138 Brazil: Alagoas, Ibateouara, Envenho Ceimba, Usina Serra Grande Thraupidae Tangara larvata LSUMZ B34988 Ecuador Esmeraldas Province: 30 km SE San Lorenzo Thraupidae Tangara larvata STRI JTW296 Panama;Bocas del Toro; Cerro Chalite Thraupidae Tangara lavinia LSUMZ B-34987 AY383139 Brazil: Alagoas, Ibateouara, Envenho Ceimba, Usina Serra Grande Thraupidae Tangara lavinia Nevada JKO1-234 Honduras;Departamento Atlantida; Thraupidae Tangara mexicana LSUMZ B-18465 AY383140 Ecuador: Prov. Esmeraldas, 2 km W Alto Tambo; 00 550N, 78 350W Thraupidae Tangara inexicana LSUMZ B-35572 AY383141 Panama: Prov. Darien, about 9 km NW Cana on slopes Cerro Pirre Thraupidae Tangara meyerdeschauenseei LSUMZ B-43111 AY383142 Panama: Prov. Darien, about 6 km NW Cana Thraupidae Tangara nigrocincta LSUMZ B-9758 AY383143 Panama: Prov. Darien, about 6 km NW Cana Thraupidae Tangara nigroviridis LSUMZ B-34857 AY383145 Bolivia: Dept. La Paz, Prov. B. Saavedra, 83 km by road E Charazani, Cerro Asunta Pata Thraupidae Tangara nigroviridis LSUMZ B-1627 AY383144 Bolivia: Dept. Santa Cruz, Serrania de Huanchaca, 21km SE Catarata Arco Iris Thraupidae Tangara palmer LSUMZ B11999 Ecuador; Esmeraldas; Thraupidae Tangara palmeri LSUMZ B-11999 AY383146 Costa Rica: Prov. Cartago, 28km ESE Turrialba Thraupidae Tangara palmeri LSUMZ B34859 Ecuador Pichincha Province: 5 km NE Puerto Quito Thraupidae Tangara parzudakii LSUMZ B-30007 AY383147 Peru: Loreto, Lower Napo region, E bank Rio Yanayacu, ca 90km N Iquitos Thraupidae Tangara pulcherrima MVZ169712 AY190169 Bolivia, Dept. Cajamarca Thraupidae Tangara punctata LSUMZ B-35552 AY383149 Costa Rica: Prov. Heredia, 4 km SE Virgen del Socorro Thraupidae Tangara punctata LSUMZ B-34931 AY383148 Ecuador: Prov. Pichincha, 5km S Nanegalito; 00 010N.74 410W Thraupidae Tangara ruficervix LSUMZ B-33410 AY383151 Panama: Prov. Colon, Achitoe Road, about 2 km Bridge at Rio Providencia Thraupidae Tangara ruflgula LSUMZ B-11930 AY383152 Peru: Dept. Cajamarca, Quebrada Las Palmas, about 13km WSW Chontali Thraupidae Tangara schrankii LSUMZ B-34932 AY383153 Ecuador: Prov. Pinchincha, 4 km NE Mindo, 00 010N, 78 440W Thraupidae Tangara seledon LSUMZ B-16942 AY383154 Ecuador: Prov. Imbabura, 15km N Pedro Vicente Maldonado Thraupidae Tangara varia LSUMZ B-28010 AY383155 Ecuador: Prov. Esmeraldas, 30km SE San Lorenzo Thraupidae Tangara vassorii LSUMZ B-1711 AY383156 Bolivia: Dept. Santa Cruz, Velasco; Parque Nacional Noel Kempff Mercado, 86km ESE of Florida Thraupidae Tangara velia FMNH 390060 AY383158 Peru: Dept. Puno, 9.5 km N of S andia Thraupidae Tangara viridicollis LSUMZ Br8090 AY383159 Bolivia: Dept. Pando, Nicolas Suarez, 12km by road S of Cobija.km W on road to Mucden Thraupidae Tangara vitriolina LSUMZ B-34921 AY383160 Peru: Dept. Pasco, Santa Cruz, about 9 km SSE Oxapampa Thraupidae Tangara xanthocephala LSUMZ B-34922 AY383161 Ecuador: Prov. Pinchincha, 5 km S Nanegalito Thraupidae Tangara xanthogastra LSUMZ , B-34934 AY383162 Ecuador: Prov. Esmeraldas, el Placer Thraupidae Tersina viridis LSUMZ B-9680 AF006255 Bolivia: Dept. Pando, Nicolas Suarez, 12 km by road S of Cobija, 8 km W on road to Mucden Thraupidae Thlypopsis sordida LSUMZ B-7260 AF006256 Peru: Dept. Loreto, Amazonas I. Pasto, 80 km NE Iquito ON Thraupidae Thraupis abbas UWBM UWBM70095 Nicaragua;Matagalpa 10 km N; Thraupidae Thraupis bonariensis LSUMZ B-3587 AY383103 Peru: Dept. Huanuco: Nuevas Flores Thraupidae Thraupis episcopus Barrick M B M 7057, AY329477 ? Thraupidae Thraupis episcopus STRI JTW054 Panama;Chiriqui;Puerto Limones, Burica Peninsula Thraupidae Thraupis episcopus STRI JTW553 Panama;Hererra;El Limon Thraupidae Thraupis episcopus AF290153 Venezuela, Falcon Thraupidae Thraupis palinarum STRI JTW285 Panama;Bocas del Toro; Cerro Chalite Thraupidae Thraupis palmarum STRI TR-TPA3 Trinidad;Simla Research Station; Thraupidae Thraupidae Thraupis Tiaris sayaca bicolor AMNH MVZ AMNH2241 179402 AF489899 Bolivia; Departamento Santa Cruz;Prov. Cordillera;COMUNIDAD KARAPARI, ESTANCIA SAN JULIAN, 1000M W OF RIO PARAPETI Aviary of Luis F. Baptista, CAS Accn. 5067; Thraupidae Tiaris canora AF310042 Cuba or Bahamas Thraupidae Thraupidae Tiaris Tiaris fuliginosa obscura LSUMZ B12612 AF108807 Bolivia Santa Cruz Department: Velasco; 50 km ESE Florida, Arroyo del Encanto South America Thraupidae Thraupidae Tiaris Tiaris olivacea olivacea AMNH 25429 AF489901 AF447375 Dominican Republic: Provincia Independencia, Parque Nacional Sierra de Baoruco; captive Thraupidae . Tiaris olivacea pusilla FMNH FM394094 Mexico;Hidalgo; Thraupidae Tiaris olivacea AMNH AMNH6843 Mexico;Quintana Roo; Cozumel Island, El Codral; Thraupidae Tiaris olivacea AY700047 Panama Thraupidae Tiaris olivacea STRI JTW010 Panama;Cocle; El Cope National Park Thraupidae Volatinia jacarina STRI JTW076 Panama;Chiriqui;Puerto Limones, Burica Peninsula Thraupidae Volatinia jacarina STRI JTW709 Panama;Darien;Puerto Pina Thraupidae Volatinia jacarina STRI TR-VJA10 Trinidad;Livestock Research Station; Thraupidae Volatinia jacarina FMNH 394403 AF489903 Bolivia; Thraupidae Volatinia jacarina AF290150 Bolivia, Santa Cruz Thraupidae Volatinia jacarina AF310046 Ecuador, Santo Domingo Thraupidae Volatinia jacarina MACN 18154 AY387446 Tucuman, Argentina Thraupidae Xenodacnis parina LSUMZ B-7760 AF006257 Ecuador: Prov. Azuay APPENDIX 8 Bayesian phylogeny of 136 genera and 200 species of nine-primaried oscines using cytochrome b sequence data. A Bayesian analysis was run under the GTR-gamma model of sequence evolution for 30 million generations, sampled every 400 generations and the first 16 million generations were discarded as the burnin. A consensus phylogeny was constructed from remaining sampled trees. Posterior probabilities are shown at nodes. Clades recovered are as follows: a) Passeridae, b) Fringillidae, c) Motacillidae, d) undescribed clade of snow buntings and longspurs, e) Cardinalidae, f) Lamprospiza, g) Thraupidae, h) Parulidae, i) Emberizidae, j) Icteridae. An asterisk marks genera which grouped in a family different than that assigned by the traditional taxonomic sequence (Peters 1972). The analysis was rooted with Sylvia layardi (Genbank sequence AJ534528). Genbank sequences used are as follows: AF489878, AF089005, AF089066, AF089006, AF089007, AF089011, AF447362, AY117723, AF089014, AF290162, AF006211, AF310061, AF382994, AF382997, AF489879, AF006212, AY117717, AY117706, AF089017, AF472384, AY117718, AF089018, AF284073, AF006213, AF108802, AF108792, AF108795, AF447363, AF310049, AF383024, AF108805, AF006214, AF006215, AF006217, AF006218, AF006219, AF006220, , AF006221, AF006222, AF489881, AF489883, AF383000, AF006223, AF447366, AF006224, AF006224, AF089020, AF006225, AY190167, AF301462, AF301460, AF006226, AF006227, AF006228, AF256504, AF489884, AF382996, AF383002, AF006229, AF089021, AF089022, AF006230, AF284081, AF284080, AF284083, AF284082, AF290157, AY228057, AF383010, AF006231, AF489885, AF089023, AF383009, AF108778, AF383003, AF089025, AF382995, AF301449, AF089026, AY117699, AF089053, AF006233, AF290156, AF383004, AF383019, AF383020, AF006235, AF006236, AF383028, AF099277, AF099278, AF099288, AF099296, AF089033, AF099302, AF099307, AY190169, AF006237, AF290161, AF089037, AF006238, AF006239, AF089038, AF383005, AF489886, AF489888, AF089039, AF310043, AY156182, AY156181, AF383021, AF284079, AF006240, AF383006, AF089041, AF089042, AF089043, AF383031, AF006241, AF006242, AF006243, AF089045, AF489889, AF472382, AF383017, AF383029, AF006244, AF089046, AF310055, AF489890, AF447371, AF284078, AY124544, AF301447, AF489891, AF006245, AF310057, AF310058, AF108790, AF284075, AF290160, AF006246, AF011772, AF011780, AF011781, AF284074, AF310052, AF383030, AF472383, AY117698, AF472368, AF089051, AF006249, AF089054, AF089057, AF089058, AF310048, U15718, AY228082, AF089059, AF383107, AF489892, AF089060, AF006250, AF383007, AF383001, AF383008, AF489893, AF383018, AF006252, AF089061, AF118231, AF255710, AF310054, AF310053, AF489896, AF290149, AF089062, AF089063, AF089064, AF006253, AF489897, AF006254, AF382999, AF006255, AF006256, AF489898, AF290153, AF489899, AF310042, AF489900, AF108807, AF489901, AF489903, AF383016, AF089067, AF006257, AF383022, AF382998, AF284076, AF383023, AY228056, AF255705, AF171659, AF310066, AF290142, AF342883, AF447364, AF342866, AF342869, AF006216, AY228055, AF342871, AF290143, AF383014, AF006232, AF310067, AF447368, L77903, AF342875, AF015760, AF015755, AF015754, AY156385, AF342877, AF015757, AF342879, AF015763, AF015758, AF015761, AF015759, AF342882, AF015762, AF342884, L76265, L76263, AF365877, AF015756, U46769, ACU46776, U46774, ATU46775, U46777, AF526468, AY228045, AF290138, AY228068, AY030117, AY030118, AY228074, AF290139, AY228061, AF290141, AF255709, AY228080, AJ534526, AF376887, AY124542, AY124540, AJ534528. 169 Cnemosopus rubrirostris ispinQus atrcpileua Naphsloras oneilei — Cypsnayn hirundinoeM ~ ispingu* trartalii nguinolenlus Hetrwpingu* xanthopysius ~" Hemilhraupis flavicdlis ChfysotHypiB chrysarteliw 170 171 APPENDIX 9 Comparison of the traditional morphology based (Howard and Moore 1991, Peters 1970) and DNA hybridization based taxonomies (Sibley and Ahlquist 1990) of the nine-primaried oscines with the results of the analysis in Appendix 8. Posterior probability is the proportion of 35,000 MCMC trees in which a genus occurred within the family indicated. Sequence based studies which support the taxonomic transfers presented here are as follows: 1) Klicka et al. 2000, 2) Yuri and Mindell 2002, 3) Lovette and Bermingham 2002, 4) Burns 2002, 5) Ericson et al. 2003, 6) Klicka et al. 2003, 7) Ericson and Johnson 2003, 8) Lougheed et al. 2000, and 9) Burns et al. 2003. Genus Traditional Taxonomy Hybridization Taxonomy DNA Taxonomy Posterior Probability Supporting References Embenzidae • EmberiaftafflB ^ ^ ^ ^ r i b e d , i o \ v K 1 2 5 6 7 Plectrophenax Emberizidae Emberizidae undescribed family 1.0 2,6,7 mmmmuia • -Vtifnbe/izidae* Thraupidae •• Car l f i l l l idae 1 0 Habia Thraupidae Thraupidae Cardinalidae 1.0 2,9 •Thraupidae.:. "^h.raupidrefi ;- 8 •VCarSISl ic lae 1.0 9 . Z-Mitrospingus Thraupidae Thraupidae Cardinalidae 1.0 3 W<£}jjgi0§llus. s^ParJilidae ' Rarulifa'e " " 'I Caipfr|Ii idae 1 0 1,2,6;9. Piranga Thraupidae Thraupidae Cardinalidae 1.0 2 , 9 isem^ptza Thraup.idaej i ^incejae^sedis 2 . - 3 . • • Paroaria Cardinalidae Thraupidae Thraupidae 1.0 1,4,9 P a r f i f a e - ^ R a r u W a e * T h r t l f i d a e 1 0 1,2,4,6,9 Tiaris Emberizidae Thraupidae Thraupidae 1.0 4,9 ! Loxigrila . - • E m f M i r d a e - " T h r a l l idae 7" Thraupjdae 1 0 ' 4,9 Euneornis Emberizidae Thraupidae Thraupidae 1.0 4,9 ^^Thratiipjdae^"' 1 0 4,9 Loxipasser Emberizidae Thraupidae Thraupidae 1.0 4,9 WMMlMMspiza' bmbei iz ipae- Thra jpdae , Thraupjdae 1.0 4,9 * Certhidea Emberizidae Thraupidae Thraupidae 1.0 2,4,9 » T a & l I a e * - - - t h r ^ S i d a e , - 1 0 4,9 Camarhynchus Emberizidae Thraupidae Thraupidae 1.0 4,9 ' Err i l^ iz i f iae^ rhraMilatl-* Thrafpi.d.ae 1.0 1,6 .. < Saltator1 Cardinalidae Cardinalidae Thraupidae 1.0 1,69 Emrjenzidae,^ ''Thraupidae-* Thraupidae 1.0 4,9 \ Oryzoborus Emberizidae Thraupidae Thraupidae 1.0 1,4,6,9 imatinia"'" ^ Emberjzrdae, .Thraupidae.** * Thrafpfidae 1.0 4,9 ) Sicalis Emberizidae Thraupidae Thraupidae 1.0 4,9 Emberizidae^ Fhralp.@ae\ „ Thraupidae. 1.Q • 1,6,9.-? Haplospiza Emberizidae Thraupidae Thraupidae 1.0 4 WMMMnia : - . jEmlS lG lae? ' ^\ThraupjrJae *, '^Thraupidae 1 0 2,9 Coryphospingus Emberizidae Thraupidae Thraupidae 1.0 7 \ Emberizoides E m b e r i i i l a H ^ l l r t S l l i a e - ^ Thraupidae 1 0 8,9 -JS" 172 Nephelornis Parulidae 7 Thraupidae 1.0 2,4,9 Conirostrum Parulidae Parulidae Thraupidae 1.0 2,4,9 Oreomanes Tharupidae Parulidae Thraupidae 1.0 2,4,9 Tersina Tersinidae Thraupidae Thraupidae 1.0 4,5,8,9 Poospiza Emberizidae Thraupidae Thraupidae 1.0 2 Nesospingus Thraupidae Thraupidae Parulidae 0.84 Spindalis Thraupidae Thraupidae Parulidae 0.84 Phaenicophilus Thraupidae Thraupidae Parulidae 0.84 Chlorospingus Thraupidae Thraupidae Emberizidae 1.0 2 1 Saltator. a polytypic genus. 5. striatipectus and S. coerulescens belong in the Thraupidae and S. atricollis is retained in Cardinalidae. Literature Cited Burns, K. L, S. J. Hackett, and N. K. Klein. 2002. Phylogenetic relationships and morphological diversity in Darwin's finches and their relatives. Evolution 5 6 : 1240-1252. Burns, K. J., S. J. Hackett, and N. K. Klein. 2003. Phylogenetic relationships of Neotropical honeycreepers and the evolution of feeding morphology. J. Avian Biol. 3 4 : 360-370. Ericson, G. P. and U. S. Johansson. 2003. Phylogeny of Passerida (Aves: Passeriformes) based on nuclear and mitochondrial sequence data. Mol. Phyl. Evol. 2 9 : 126-138. Ericson, P. G. P., M . Irestedt, and U. S. Johansson. 2003. Evolution, biogeography, and patterns of diversification in passerine birds. J. Avian Biol. 3 4 : 3-15. Howard, R. and A. Moore. 1991. A complete checklist of the birds of the World. 2nd Ed. Academic Press, New York. Klicka, J., K. P. Johnson, and S. M . Lanyon. 2000. New world nine-primaried oscine relationships: constructing a mitochondrial DNA framework. Auk 1 1 7 : 321-336. Klicka, J., R., M . Zink, and K. Winker. 2003. Longspurs and snow buntings: phylogeny and biogeography of a high-latitude clade (Calcarius). Mol. Phyl. Evol. 2 6 : 165-175. Lougheed, S. C , J. R. Freeland, P. Handford, and P. T. Boag. 2000. A molecular phylogeny of warbling-finches (Poospiza): paraphyly in a Neotropical Emberizid genus. Mol. Phyl. Evol. 1 7 : 367-378. Lovette, I. J. and E. Bermingham. 2002. What is a wood-warbler? Molecular characterization of a monophyletic Parulidae. Auk 1 1 9 : 695-714. Peters, J.L. 1970, Check-list of birds of the world, vol. 13: Museum of Comparative Biology, Cambridge, Massachusetts. Sibley, C. G. and Monroe, B. L. (1990). Distribution and taxonomy of the birds of the world. Yale University Press, New Haven, Connecticut. Yuri, T. and D. P. Mindell. 2002. Molecular phylogenetic analysis of Fringillidae, "New World nine-primaried oscines" (Aves: Passeriformes). Mol. Phyl. Evol. 2 3 : 229-243. 173 Appendix 10 Parsimony and maximum likelihood reconstruction of acestral geographic range along bayesian molecular phylogenies for antbirds, woodcreepers, tanagers and blackbirds. North American distribution indicated by black and South American by white. Gray vertical line demarks completion of Central American Landbridge on parsiomony reconstructions. Branchlengths on parsimony reconstructions obtained from bayesian relaxed clock model. Branchlengths on maximum likelihood reconstructions are not informative. Taxa with a red asterix were manually added to the tree as indicated in text and the date at which they connect in the phylogeny (red circle) is arbitrary. - 174-Antbird parsimony ancestor state reconstruction Terenura humeralis AY676957 Terenura callinota B2198 Terenura callinota B6176 Myrmornis torquata FM391446 Myrmomis torquata AY676975 Pygiptila stellaris AY676945 Thamnistes anabatinus B6152 Thamnistes anabatinus JTW179 ri rjzp Thamnistes anabatinus AY676946 1 1 H n Thamnistes anabatinus B2154 Dysithamnus mentalis B6155 Dysithamnus mentalis JTW128 Megastictus margaritatus AY676944 Thamnomanes caesius EF030320 Myrmotherula sunnamensis CJW74 Myrmotherula pacifica RCF2068 Myrmotherula pacifica JTW722 Myrmotherula multostrista B4354 Myrmotherula cherriei RWP17257 Myrmochanes hemileucus AY676965 Myrmotherula obscura AY676951 Myrmotherula menetriesii AY676955 Myrmotherula longipennis AY612563 Myrmotherula axillaris FM433469 i i-i Myrmotherula axillaris AY676954 i [• n Myrmotherula axillaris T R MAX1 U Myrmotherula axillaris JTW574 1—i L n Myrmotherula axillaris JTW644 Myrmotherula behni AY676956 Myrmotherula schistacea FM429987 j n Myrmotherula schisticolor B11979 1 L j p Myrmotherula schisticolor B16048 '—tin Myrmotherula schisticolor B2124 Formicivora grisea AF118169 Formicivora rufa AY676958 Myrmorchilus strig latus AY676959 Microrhopias quixensis AY676950 Microrhopias quixensis JTW724 Microrhopias quixensis JTW301 Microrhopias quixensis JTW078 Neoctantes niger AY676960 Myrmotherula fulviventris JTW215 Myrmotherula fulviventris B11848 Myrmotherula leucophthalma AY676952 Myrmotherula leucophthalma AF118158 Myrmotherula hauxwelli AY612532 Rhegmatorhina melanosticta AY676978 Rhegmatorhina gymnops AY612581 Gymnopithys leucaspis E C GLE1 Gymnopithys leucaspis JTW268 Hylophylax poecilinota E C H P 0 1 Hylophylax poecilinota AY612487 Phlegopsis erythroptera AY676979 Phlegopsis nigromaculata AY612576 Pithys albifrons AY676976 S Phaenostictus mcleannani AY676980 Phaenostictus mcleannani JTW655 Cercomacra melanaria AY065723 Cercomacra nigricans2 :; : Cercomacra nigr icans* ' Myrmeciza hemimelaeria AY676970 Cercomacra nigrescens B12661 Cercomacra serva C S E 1 Cercomacra laeta FM392376 Cercomacra tyrannina DAB1036 Hypocnemis hypoxantha AF118162 Hypocnemis cantator AY676964 Hypocnemis cantator AF118163 Drymophila squamata AY065722 Drymophila devillei AF118174 Drymophila caudata AF118173 Schistocichla leucostigma AY676968 Sclateria naevia AY676967 Myrmeciza longipes JTW561 Myrmeciza longipes FM391420 Myrmoborus myotherinus AY676961 Gymnocichla nudiceps AY676974 Gymnocichla nudiceps P A G N U PC34 Pyriglena leuconota AY065724 Myrmeciza fortis AY676972 Myrmeciza immaculata B11900 Myrmeciza immaculata JTW183 Hypocnemoides maculicauda AY676966 Hylophylax naevia AY676963 S Hylophylax naevoides JTW682 Hylophylax naevoides JTW560 Myrmeciza loricata AY676971 Myrmeciza berlepschi AY676973 Myrmeciza laemosticta , ;. Myrmeciza laemosticta JTW573 Myrmeciza griseiceps AY676969 Myremciza exsul * Myrmeciza exsul JTW086 Myrmeciza exsul JTW309 • ichrozona cincta AY676962 Cymbilaimus lineatus EF030315 Cyambilaimus lineatus B2252 Cyambilaimus lineatus JTW154 Taraba major AY676938 Taraba major JTW681 Taraba major P A T M A PP101 Batara cinerea AY676937 Hypoedaleus guttatus AY676936 Mackenziaena severa AY676935 Frederickena unduligera EF030316 Herpsilochmus rufimarginatus AF118157 Herpsilochmus alricapiTlus AY676949 Sakesphorus bernardi EF030317 Thamnophilus bridgesi EF030324 Thamnophilus atrinu JTW673 Thamnophilus atrinucha EF030323 Thamnophilus murinus EF030329 Thamnophilus schistaceus EF030337 Thamnophilus nigriceps EF030330 Thamnophilus praecox EF030333 Thamnophilus nigrocinereus EF030331 Thamnophilus cryptoleucus EF030326 Thamnophilus stictocephalus EF030335 Thamnophilus punctatus EF030334 Thamnophilus punctatus RTB355 Thamnophilus caerulescens EF030325 Thamnophilus unicolor AY962685 Thamnophilus aethiops AY962686 Thamnophilus aroyae EF030322 Thamnophilus amazonicus EF030321 Thamnophilus divisorius EF030341 Thamnophilus insignis EF030328 Thamnophilus doliatus T R T H D 2 Thamnophilus doliatus JTW582 Thamnophilus doliatus B10890 Thamnophilus zarumae EF030340 Thamnophilus tenuepunctatus EF030338 Thamnophilus palliatus EF030332 Thamnophilus torquatus EF030339 Thamnophilus ruficapitlus EF030336 Dysithamnus puncticeps B11951 Dysithamnus puncticeps JTW321 Sakesphorus canadensis EF030318 Sakesphorus luctuosus EF030319 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 1 7 5 -Antbird likelihood ancestor state reconstruction 176 Woodcreeper parsimony ancestor state reconstruction 1 G l y p h o r y n c h u s spi rurus A Y 0 9 6 9 1 1 1 G l y p h o r y n c h u s spi rurus A Y 0 9 6 9 2 2 1 G l y p h o r y n c h u s spi rurus A Y 0 9 6 9 5 0 i G l y p h o r y n c h u s spi rurus A Y 0 9 6 9 3 1 1 G l y p h o r y n c h u s spi rurus A Y 0 9 6 9 3 9 1 G l y p h o r y n c h u s spi rurus A Y 0 8 9 8 0 6 i G l y p h o r y n c h u s spi rurus A Y 0 9 6 9 1 0 1 G l y p h o r y n c h u s spi rurus A Y 0 9 6 8 9 1 i G l y p h o r y n c h u s spirurus A Y 0 9 6 8 9 9 •X ipho rhynchus kieneri i A Y 0 8 9 8 1 8 •X ipho rhynchus p icus A Y 0 8 9 7 9 0 ' X i pho rhynchus p icus A Y 0 8 9 8 0 2 1 X i pho rhynchus p icus J T W 5 4 3 1 C a m p y l o r h a m p h u s fa lcular A Y 0 8 9 8 1 0 ' C a m p y l o r h a m p h u s pusi l lus B 3 3 8 2 2 ' C a m p y l o r h a m p h u s pusi l lus B 1 1 8 7 9 i C a m p y l o r h a m p h u s pusi l lus B1411 ' C a m p y l o r h a m p h u s pusi l lus J T W 0 9 4 ' C a m p y l o r h a m p h u s procurvo A Y 0 8 9 7 9 5 ' C a m p y l o r h a m p h u s trochi l i rostr is * 1 C a m p y l o r h a m p h u s trochil irostris A Y 0 8 9 8 2 2 ' Drymorn is br idgesi i A Y 0 6 5 7 1 1 ' Led ipoco lpa tes l ach rymosus R C F 2 2 0 9 ' Led ipoco lpa tes aff inis D A B 1 3 6 0 ' Led ipoco lpa tes leucogas te r M E 4 0 1 Led ipoco lpa tes souleyet i i D A B 1 1 1 7 ' Led ipoco lpa tes souleyet i i V E L S O I ' Lep idoco lap tes a lbo l inea A Y 0 8 9 8 2 5 > Lep idoco lap tes angust i ro A Y 0 8 9 8 1 1 ' X i pho rhynchus fuscus A Y 0 8 9 8 1 9 ' X i p h o r h y n c h u s pardalotus A Y 0 8 9 8 3 1 > X ipho rhynchus oce l la tus A Y 0 8 9 8 0 4 =n X i pho rhynchus oce l la tus A Y 0 8 9 8 2 0 ' X i pho rhynchus chuncho tambo A Y 0 8 9 7 9 3 ' X i p h o r h y n c h u s chuncho tambo A Y 0 8 9 8 1 5 ' X i p h o r h y n c h u s spixi i A Y 0 8 9 8 0 1 1 X i pho rhynchus e legans A Y 0 8 9 8 1 2 r j r p = n X i p h o r h y n c h u s e legans A Y 0 8 9 8 2 4 Ti==n X i pho rhynchus e legans A Y 0 8 9 8 0 5 X ipho rhynchus tr iangularis A Y 4 4 2 9 9 9 X ipho rhynchus tr iangularis A Y 0 8 9 8 2 6 X i p h o r h y n c h u s erythropygius A Y 0 8 9 8 3 2 X ipho rhynchus erythropygius J T W 6 6 9 X i p h o r h y n c h u s erythropygius J T W 1 0 5 X i p h o r h y n c h u s obso le tus A Y 0 8 9 8 2 3 X i p h o r h y n c h u s f lavigaster A Y 0 8 9 7 9 9 . r — X i p h o r h y n c h u s l ach rymosus A Y 0 8 9 8 0 7 • " X i p h o r h y n c h u s l ach rymosus J T W 3 1 7 X ipho rhynchus g eytoni A Y 0 8 9 7 9 4 X i p h o r h y n c h u s g guttatoides A Y 0 8 9 8 1 6 X ipho rhynchus guttatus A Y 0 8 9 8 1 4 X i p h o r h y n c h u s susur rans C R X S U 2 7 5 3 X i p h o r h y n c h u s susur rans A Y 0 8 9 8 0 0 Hy lexe tas tes perrotii A Y 0 8 9 8 0 9 X iphoco lap tes major A Y 0 6 5 7 1 2 X iphoco lap tes p romerop i rhynchus A Y 0 8 9 7 9 8 X iphoco lap tes p romerop i rhynchus F M 3 9 4 0 1 3 X iphoco lap tes p romerop i rhynchus O A B 1 3 7 7 N a s i c a longirostr is A Y 0 8 9 7 9 7 Dendrexe tas tes rufigula A Y 0 8 9 8 2 9 Dendroco lap tes certh ia A Y 0 8 9 8 1 7 Q p Dend roco lap tes sanc t i thomae i ^ ^ " " " " Dendroco laDtes l p tes sanc t i thomae J T W 2 5 1 Dendroco lap tes platyrostr is A Y 4 4 2 9 9 0 Dendroco lap tes p i cumnus Dend roco lap tes p icumnus B 3 5 7 2 8 Dendroc inc la homochroa P A D H O P A 6 7 1 Dendroc inc la homoch roa F M 4 3 4 0 3 5 Dendroc inc la taunay i F M 3 9 9 1 8 1 Dendroc inc la turdina K U 3 6 9 8 Dend roc inc la f atrirostris F M 4 2 9 9 4 8 Dendroc inc la f fu l ig inosa F M 3 9 1 2 9 8 Dendroc inc la anabat ina K U 5 3 6 Dendroc inc la f neg lec ta E C D F U 1 Dendroc inc la f meru lo ides T R D F U 1 Dendroc inc la f r idgewayi J T W 2 5 3 Dend roc inc la f r idgewayi J T W 7 4 4 Dendroc inc la tyrannina F M 4 2 9 9 4 6 Dendroc inc la meru la F M 3 8 9 8 1 0 S i t t asomus gr ise icapi l lus A Y 0 8 9 7 9 6 S i t t asomus gr ise icapi l lus F M 3 9 2 4 1 9 S i t t asomus gr ise icapi l lus F M 3 4 3 2 3 1 D e c o n y c h u r a long icauda B 7 5 6 5 D e c o n y c h u r a long icauda B 2 0 8 8 D e c o n y c h u r a long icauda C R D L Q 2 7 6 1 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 Time (Ma) 1 o 177 Glyphorynchus spirurus A Y 0 9 6 9 1 1 G lyphorynchus spirurus A Y 0 9 6 9 2 2 G lyphorynchus spirurus A Y 0 9 6 9 5 0 G lyphorynchus spi rurus A Y 0 9 6 9 3 1 G lyphorynchus spirurus A Y 0 9 6 9 3 9 G lypho rynchussp i ru rus A Y 0 8 9 8 0 6 G lyphorynchus spirurus A Y 0 9 6 9 1 0 G lyphorynchus spirurus A Y 0 9 6 8 9 1 G lyphorynchus spirurus A Y 0 9 6 8 9 9 X iphorhynchus kienerii A Y 0 8 9 8 1 8 X iphorhynchus p icus A Y 0 8 9 7 9 0 X iphorhynchus p icus A Y 0 8 9 8 0 2 X iphorhynchus p i cus J T W 5 4 3 Campy lo rhamphus falcular A Y 0 8 9 8 1 0 Campy lo rhamphus pusi l lus B 3 3 8 2 2 Campy lo rhamphus pusi l lus B 1 1 8 7 9 Campy lo rhamphus pusi l lus B1411 Campy lo rhamphus pusi l lus J T W 0 9 4 Campy lo rhamphus procurvo A Y 0 8 9 7 9 5 Campy lo rhamphus trochil irostris Campy lo rhamphus trochilirostris A Y 0 8 9 8 2 2 Drymornis bridgesi i A Y 0 6 5 7 1 1 Led ipoco lpates lachrymosus R C F 2 2 0 9 Led ipoco lpates affinis D A B 1 3 6 0 Led ipoco lpates leucogaster M E 4 0 Led ipoco lpa tes souleyet i i D A B 1 1 1 7 Led ipoco lpa tes souleyet i i V E L S O I Lep idoco lap tes a lbol inea A Y 0 8 9 8 2 5 Lep idoco laptes angust i ro A Y 0 8 9 8 1 1 X iphorhynchus fuscus A Y 0 8 9 8 1 9 X iphorhynchus pardalotus A Y 0 8 9 8 3 1 X iphorhynchus ocel la tus A Y 0 8 9 8 0 4 X iphorhynchus ocel la tus A Y 0 8 9 8 2 0 X iphorhynchus chunchotambo A Y 0 8 9 7 9 3 X iphorhynchus chunchotambo A Y 0 8 9 8 1 5 X iphorhynchus spixii A Y 0 8 9 8 0 1 X iphorhynchus e legans A Y 0 8 9 8 1 2 X iphorhynchus e legans A Y 0 8 9 8 2 4 X iphorhynchus e legans A Y 0 8 9 8 0 5 X iphorhynchus tr iangularis A Y 4 4 2 9 9 9 X iphorhynchus tr iangularis A Y 0 8 9 8 2 6 X iphorhynchus erythropygius A Y 0 8 9 8 3 2 X iphorhynchus erythropygius J T W 6 6 9 X iphorhynchus erythropygius J T W 1 0 5 X iphorhynchus obsoletus A Y 0 8 9 8 2 3 X iphorhynchus f lavigaster A Y 0 8 9 7 9 9 X iphorhynchus lachrymosus A Y 0 8 9 8 0 7 X iphorhynchus lachrymosus J T W 3 1 7 X iphorhynchus g eytoni A Y 0 8 9 7 9 4 X iphorhynchus g guttatoides A Y 0 8 9 8 1 6 X iphorhynchus guttatus A Y 0 8 9 8 1 4 X iphorhynchus susur rans C R X S U 2753 X iphorhynchus susur rans A Y 0 8 9 8 0 0 Hy lexetas tes perrotii A Y 0 8 9 8 0 9 X iphoco lap tes major A Y 0 6 5 7 1 2 X iphoco lap tes promeropi rhynchus A Y 0 8 9 7 9 8 X iphoco lap tes promeropi rhynchus F M 3 9 4 0 1 3 X iphoco lap tes promeropi rhynchus O A B 1 3 7 7 N a s i c a longirostris A Y 0 8 9 7 9 7 Dendrexetas tes rufigula A Y 0 8 9 8 2 9 Dendroco lap tes cerfhia A Y 0 8 9 8 1 7 Dendroco laptes sanct i thomae Dendroco laptes sanct i thomae J T W 2 5 1 Dendroco lap tes platyrostris A Y 4 4 2 9 9 0 Dendroco laptes p icumnus Dendroco laptes p icumnus B 3 5 7 2 8 Dendroc inc la homochroa P A D H O PA671 Dendroc inc la homochroa F M 4 3 4 0 3 5 Dendroc inc la taunayi FM399181 Dendroc inc la turdina K U 3 6 9 8 Dendroc inc la f atrirostris F M 4 2 9 9 4 8 Dendroc inc la f ful ig inosa F M 3 9 1 2 9 8 Dendroc inc la anabat ina K U 5 3 6 Dendroc inc la f neglecta E C D F U 1 Dendroc inc la f meru lo ides T R D F U 1 Dendroc inc la f r idgewayi J T W 2 5 3 Dendroc inc la f r idgewayi J T W 7 4 4 Dendroc inc la tyrannina F M 4 2 9 9 4 6 Dendroc inc la merula F M 3 8 9 8 1 0 S i t tasomus gr iseicapi l lus A Y 0 8 9 7 9 6 S i t tasomus gr iseicapi l lus F M 3 9 2 4 1 9 S i t tasomus gr iseicapi l lus F M 3 4 3 2 3 1 Deconychura long icauda B 7 5 6 5 Deconychura longicauda B2088 Deconychura long icauda C R D L Q 2 7 6 1 Tachyphonus coronatus GAV826 Tachyphonus rufus y. Tachyphonus rufus TR C C TRF3 Tachyphonus rutus FM392631 1 Ramphocelus sanguinolentus U15718 •° Ramphocelus bresllius U15724 Ramphocelus carbo U15723 Ramphocelus nigrogularis U15721 Ramphocelus dimid PA RDI PA75 Ramphocelus p.isserinii U15717 Ramphocelus costaricensis JTW396 a Ramphocelus icteronotus U15719 Ramphocelus icteronotus JTW611 Tachyphonus surinarnus AF006253 Eucornetis penicillata DAB1513 Eucometis penicillata B18544 Lanio versicolor AF0O6239 Lanio leucothorax JTW572 Lanio aurantius HO DHB3785 scucullatusAF447366 ii JTW257 T.id iryphospingu  c l chyphonus delatr J achyphonus delatrii JTW634 Tachyphonus cristatus ROP231 Tachyphonus luctu PA TLC 190 Tachyphonus luctuosus GAV1988 Tangara labradorides AY383136 Tangara labfadbrides AY383137 Tangara (astuosa AY383123 Tangara seledon AY383154 Tangara cyanocephala AY383117 Tangara desmaresli AY383120 «Tangara chlanais AY383110 Tangara callophrys AY383107 Tangara velia AY383158 Tangara mexicana AY383140 Tangara mexicana AY383141 • Tangara inornata AY383134 • Tangara tomaia JTW718 Tangara chrysolis AY38311 1 Tangara xanlliocephala AY383161 Tangara arthus AY383105 • Tangari arthus AY383106 Tangara icterocephala JTW093 Tangara icterocephala -Tangara llorida AY383122 Tangara florida JTW169 Tangara johannae AY383135 Tangara parzudakii AY383147 Tangara schrankii AY383153 Tangara cyanotis AY383119 Tangara lavinia AY383139 Tangara lavinia * Tangara gyrola TR T G Y i Tangara gyrola B34911 Tangara gyrola AY383129 Tangara mlicervix AY383151 Tangara cyanoptera AY383116 Tangara viridicollis AY383159 Tangara argyrotenges AY383104 Tangara heinei AY383132 Thraupis palmarum TR 1PA3 Thraupis palmarum^ Thraupis abbas D A B l 315 Thraupis sayaca ALP152 - Thraupis eprscopus AF290153 Thraupis episcopus JTW054 Tangara meyerdeschauenseei AY383142 Tangara cayana AY383108 l.niyaia cucullata AYJHJ112 Tangara vitriolina AY383160 Tangara nigrocincta AY383143 Tangara cyanicollis AY383114 Tangara cyanicollis AY383115 Tangara larvata AY383138 Tangara larvata JTW296 Tangara palmeri AY383146 Tangara varia AY383155 Tangara xamhogaslra AY383162 Tangara guttata V E PEP1979 Tangara guttata AY383126 1,'ifKjara guttata JTW013 Tangara rufigula AY383152 Tangara punctata AY383148 Tangara punctata AY383149 Tangara vassoni AY383156 Tangaia iiigrovindis AY383144 Tangara dowii AY383121 Tangara lucosa AY383125 Chlorochrysa calliparaea AY383095 Chlorochrysa phoenicoiis AY383094 Paroana coronata AF447371 o Neothraupis lasciata AY383100 Crs^opis leveriana AY383096 Sclustochlamys melanopsis AY383102 Calochaetes coccineus AY383092 Buthraupis montana AY3B3091 Arnsrxjnathus tlavinuchus AY383090 Chlorornis riefterii AY383093 Delothraupis castaneovenlns AY383097 Dubusia taeniata AY383098 Pipraeidea melanonota AY383101 Thraupis bonariensis AY383103 Iridosornis analis AY383099 Efamgsta rnHanochlamys Bangsia arcaei JTW157 * Creurgops dentata AF0O6224 Creurgops verticals AY190166 Loxigilla portoricerisis AF489886 Loxigilla violacea AF489887 Poospiza baeri AY005200 i 1• i. • •• n • • .• n \ • .::i AF489885 Loxipasser anoxanthus AF489888 Tiaris canora AF310042 Certhidea olivacea AF108806 Certhidea lusca AY672052 Pinaroloxias inornata AF108791 Geospiza magniroslris AF 108778 Geospiza scandens AF108779 Geospiza conirostris AF108769 ["ito Geospiza lortis AF108771 f j = » Geospiza ditticilis AF108788 ' "Geospiza tuliginosa AF108784 r^rnartrynchus parvulus AF108796 C.iniarhynchus pauper AF108795 Camarhynchus psittacula AF108798 Tiaris obscura AF108807 Tiaris fuliginosa B12612 Tiaris bicolor AF489899 Loxigilla noctis AF310041 Melanospiza richardsoni AF310043 Tiaris olivacea NKK823 Tiaris olivacea JTW010 Tiaris olivacea Coereba (laveola AF382993 Coereba flaveola AF489882 Coereba flaveola PA CFA2 Coereba flaveola PA CFA11367 Coereba flaveola SV CFA2129 Coereba (laveola JA CFA4 Coereba flaveola RD CFA1 179 Tanager parsimony ancestor state reconstruction continued VoUin.1 jacarina JTW076 Volatina jacarina TR VJA10 Saltator coerulescens FM393897 Saltator caerulescens FM391613 Saltator coerulescens FM 334590 Saltator coerulescens AF290154 Saltator albicollis E C SAL3580 Saltator albicollis PE SAL5251 Saltator albicollis E C SAL 4541 Saltator albicollis JTW409 Saltator atriceps KU1979 Saltator maximus ROP291 Saltator maximus Saltator maximus JTW282 Emberizoides herbicola AY228057 Emberizoides herbicola ^ Emberizoides ypiraiigan'tis Oryzoborus crassirostris AF489890 Oryzoborus nuttingi Sporophila castaneiventris AF310O56 Sporophila telasco AY387443 Sporophila palustrts AY387438 Sporophila rnelanoqaster AY387433 Sporophila minuta JTW371 ° Sporophila minuta TR SMI1 " Sporophila bouvreuil AY387415 Sporophila hypoxarvtha AY387430 i — S p o r o p h i l a cinnamomea AY387423 Sporophila tiypochroma AY387428 Sporophila rulicollis AY387440 » Sporophila zelichi AY387444 Sporophila americana JTW124 Sporophila americana JTW688 Dolospingus fringilloides AY705435 ° Sporophila taicirostris AY387425 " Sporophila schistacea * Sporophila schistacea FM433822 Sporophila luciuosa AY387432 Sporophila collaris AY387424 Sporophila caerulescens AY387417 Sporophila nigricollis J. Sporophila nigricollis F)v1392597 Oryzoborus funereus HA O F U HA37 Oryzoborus angolensis EC O A N l Sporophila plumbea AY115407 Sporophila collaris AF489895 Sporophila leucoptera AY387431 Phrygilus alaudinus AY0O5218 Diglossa humeralis AF310050 Diglossa major AF290155 n Diglossa albilatera " Diglossa lafresnayii AF006229 Diglossa sittoides Diglossa baritula Diglossa baritula JTW465 Diglossa plumbea Catamema inornata AF31O049 Xenodacnis parina AF006257 Haplospiza unicolor AF290156 Acanthtdops bairdii AF489878 Haplospiza rustica B16173 Haplospiza rustica B7451 Conirostrum sirticolor AF383000 Conirostrum albifrons AF447365 o Oreomanes fraseri AF006244 Conirostrum bicolor AF383025 Conirostrum speciosum AY190168 Sicalis luteola AF489893 Sli.llls luteOla gfa Sicalis tlaveola AY491528 o Nemosia pileata AF006241 - Sericossypha albocnstata AF006251 Cyanerpes cyaneus HA CNN HA82 Cyanerpes cyaneus TR C C CCN1 Cyanerpes caeruleus EC CCE1612 Cyanerpes caeruleus TR CCE1 Cyanerpes lucidius PA CLC34493 Cyanerpes nitidus FM390048 Tersina viridis AF006255 Dacnis venusta B82192 Dacnis venusta * Dacis cayana UL102 Dacnis cayana TR D A C l Tangara pulcherrima AY190169 Chlorophanes spiza H O C S P HA51 Chlorophanes spiza TR CSP4 Chrysothlypis chrysomelas JTW016 Chrysothlypsis salmon! * Hemithraupis tlavicollis AT006235 Heterospingus xanthopygius AF006236 Heterospitigus rubrilrons 1TW278 Conothmupis speculiqera AF006223 Poospiza whitii AY005212 Poospiza garleppi AY005204 o Cnemoscopus rubrirosiris AFO06222 - Hemispingus atropileus AF383019 Hemispingus auricularis AY039291 Hemispingus calophrys AY039300 Hemispingus parodii AY180913 Cypsnagra hirundinacea AY115394 Pyrrhocoma ruticeps AF006249 Nephelornis oneilli AF006243 Poospiza erythrophrys AY0O5203 Poospiza melanoleuca AY005210 Poospiza alticola AY005199 Poospiza torquata AY005215 Poospiza caesar AYO052O2 Poospiza hypochondria AY005207 Hemispingus piurae AY039294 Hemispingus ironlalis AF383020 o Hemispingus melanotis AF100537 Hemispinijiiv mlosiinen..iliarts AY039297 Thlypopsis sordida AF006256 Poospiza hispaniolensis AY0O5205 Hemispingus verticalls AF100538 Poospiza boliviana AY005201 Poospiza ornata AY005213 4 3 Time (Ma) 180 Tanager likelihood ancestor state reconstruction Tachyphonus coronatus GAV82B Tachyphonus rufus Tachyphonus rufus TR CC TRF3 Tachyphonus rufus FM392631 Ramphocelus sanguinolentus U15718 Ramphocelus brestlius U15724 Ramphocelus carbo U15723 Ramphocelus nigrogularis U15721 Ramphocelus dimidPA RDI PA75 Ramphocelus passerinit U15717 Ramphocelus costaricensis JTW396 Ramphocelus icteronotus U15719 Ramphocelus icteronotus JTW611 Tachyphonus surinamus AF006253 -Eucometis penicillata DA81513 Eucometis penicillata B18544 Lanio versicolor AF006239 Lanio leucothorax JTW572 Lanio aurantius HO DHB3785 Coryphospingus cucultatus AF447366 Tachyphonus delatrii JTW257 Tachyphonus delatrii JTW634 Tachyphonus cristatus ROP231 Tachyphonus luctu PA TLC190 Tachyphonus luctuosus GAV1988 Tangara labradorides AY383136 Tangara labradorides AY383137 Tangara fastuosa AY383123 Tangara seledon AY383154 Tangara cyanocephala AY383117 Tangara desmaresti AY383120 Tangara chilensis AY383110 Tangara callophrys AY383107 Tangara velia AY383158 Tangara mexicana AY383140 Tangara mexicana AY383141 Tangara inornata AY383134 Tangara iornata JTW718 Tangara chrysotis AY383111 Tangara xanthocephala AY383161 Tangara arthus AY383105 Tangara arthus AY383106 Tangara icterocephala JTW093 Tangara icterocephala Tangara florida AY383122 Tangara florida JTW169 Tangara joharmae AY383135 Tangara parzudakii AY383147 Tangara sdirankii AY383153 Tangara cyanotis AY383119 Tangara lavinia AY383139 Tangara lavinia Tangara gyrola TR TGY1 Tangara gyrola B34911 Tangara gyrola AY383129 Tangara ruficervix AY383151 Tangara cyanoptera AY383116 Tangara vtridicollis AY383159 Tangara argyrofenges AY3S3104 Tangara heinei AY383132 Thraupis palm arum TR TP A3 Thraupis palmarum Thraupis abbas DAB1315 Thraupis sayaca ALP152 Thraupis episcopus AF290153 Thraupis episcopus JTW054 Tangara meyerdeschauenseei AY383142 Tangara cayana AY383108 Tangara cucullafa AY383112 Tangara vitriol in a AY383160 Tangara nigrocincta AY383143 Tangara cyanicollis AY383114 Tangara cyanicollis AY383115 Tangara larvata AY383138 Tangara larvata JTW296 Tangara palmeri AY383146 Tangara varia AY383155 Tangara xanthogastra AY383162 Tangara guttata V E PEP1979 Tangara guttata AY383126 Tangara guttata JTW013 Tangara rufigula AY383152 Tangara punctata AY383148 Tangara punctata AY383149 Tangara vassorii AY383156 Tangara nigroviridis AY383144 Tangara dowii AY383121 Tangara fucosa AY383125 Chlorochrysa calliparaea AY383095 Chlorochrysa phoenicotis AY383094 Paroaria coronata AF447371 Neothraupis fasciata AY383100 Cissopis (everiana AY383096 Schistochiamys melanopsis AY383102 Calochaetes coccineus AY3S3092 Buthraupis montana AY383091 Anisognathus fiavinuchus AY383090 Chloromis riefferii AY383093 Delothraupis casta ne oven tris AY383097 Dubusia taenlata AY383098 Pipraeidea melanonota AY383101 Thraupis bonariensis AY383103 Iridosornis analis AY363099 Bang si a melanochlamys Bangsia arcaei JTW157 Creurgops dentata AF006224 Creurgops verticals AY190168 Loxigilla portoricensis AF489886 Loxigilla violacea AF4898B7 Poospiza baeri AY005200 Euneomis campestris AF4 69885 Loxipasser anoxanthus AF489888 Tians canora AF310042 Certhidea olivacea AF108806 Certhidea fusca AY672052 Pinaroloxias inornata AF108791 Geospiza magnirostris AF108778 Geospiza scandens AF10877S Geospiza conirostris AF108769 Geospiza fortis AF108771 Geospiza difficilis AF108788 Geospiza fuliginosa AF108784 Camarhynchus parvulus AF108796 Camarhynchus pauper AF 108795 Camarhynchus psittacuia AF108798 Tiaris obscura AF108807 • • Tiaris fuliginosa B12612 Tiaris bicolor AF48G899 Loxigilla noctis AF310041 Melanospiza richardsoni AF310043 00 to Tanager likelihood ancestor state reconstruction continued Tiaris olivacea Tiaris olivacea NKK823 Tiaris olivacea JTW010 " Coereba flaveola AF382993 Coereba flaveola AF4898S2 Coereba flaveola PA CFA2 Coereba flaveola PA CFA11367 Coereba flaveola SV CFA2129 Coereba flaveola JA CFA4 Coereba flaveola RD CFA1 Volatinia jacarina AY387446 Volatina jacarina JTW076 Volatina jacarina TR VJA10 Saltator coerulescens FM393897 . Saltator caerulescens FM391613 Saltator coerulescens FM334590 Saltator coerulescens AF290154 Saltator albicollis EC SAL3580 Saltator albicollis PE SAL5251 Saltator albicollis EC SAL 4541 Saltator albicollis JTW4Q9 Saltator atriceps KU1979 Saltator maximus ROP291 Saltator maximus Saltator maximus JTW282 Emberizoides yptranganus Emberizoides herbicola AY228057 Emberizoides herbicola Oryzoborus crassirostris AF489890 Oryzoborus nuttingi Sporophila castaneiventris AF310056 Sporophila teiasco AY387443 Sporophila palustris AY387438 Sporophila melanogaster AY387433 Sporophila minuta JTW371 Sporophila minuta TR SUM Sporophila bouvreuil AY387415 Sporophila hypoxantha AY387430 Sporophila cinnamomea AY387423 Sporophila hypochroma AY387428 Sporophila ruficollis AY38744Q Sporophila 2elichi AY387444 Sporophila americana JTW124 Sporophila americana JTW688 Dolospingus fringilloides AY705435 SporophiTa falcirostris AY387425 Sporophila schistacea Sporophila schistacea FM433822 Sporophila luctuosa AY387432 Sporophila collaris AY387424 Sporophila caerulescens AY387417 Sporophila nigricollis Sporophila nigricotlis FM392597 Oryzoborus funereus HA OFU HA37 Oryzoborus angolensis EC OAN1 Sporophila plumbea AY115407 Sporophila collaris AF489895 Sporophila leucoptera AY387431 Phrygilus aiaudinus AY005218 Diglossa humeralis AF310050 Diglossa major AF290155 Diglossa albilatera Diglossa lafresnayii AF006229 Diglossa slttoides Diglossa baritula Diglossa baritula JTW465 Diglossa plumbea Catamenia inornata AF310049 Xenodacms parina AF006257 Haplospiza unicolor AF290158 Acanthidops bairdii AF489878 Haplospiza rustica B16173 Haplospiza rustica B7451 Conirostrum sitticolor AF383000 Conirostrum albifrons AF447365 Oreomanes fraseri AF006244 Conirostrum bicolor AF383025 Conirostrum speckssum AY190168 Sicalis flaveola AY491528 Sicalis luteola AF489893 Sicalis luteola Nemosia pileata AF006241 Sericossypha albocristata AF006251 Cyanerpes cyaneus HA CNN HA82 Cyanerpes cyaneus TR C C CCN1 Cyanerpes caeruleus EC CCE1612 Cyanerpes caeruleus TR CCE1 Cyanerpes lucidtus PA CLC34493 Cyanerpes nitidus FM390048 Tersina viridis AF008255 Dacnis venusta B82192 Dacnis venusta Daciscayana IJL102 Dacnis cayana TR DAC1 Tangara pulcherrima AY190169 Chlorophanes spiza HO CSP HA51 Chlorophanes spiza TR CSP4 Chrysothlypis chrysomelas JTW016 Chrysothlypsis salmoni Hemithraupis flavicollis AFO06235 Heterospingus xanthopygius AF006236 Heterospingus rubrifrons JTW278 Conothraupts speculigera AF006223 Poospiza whitii AY005212 Poospiza garleppi AY005204 Cnemoscopus rubrirostris AF006222 Hemispingus atropileus AF383019 Hemispingus auricuiaris AY039291 Hemispingus calophrys AY039300 Hemispingus parodii AY180913 Cypsnagra hirundinacea AY115394 Pyrrfiocoma ruficeps AF006249 Nepheiomis oneilli AF006243 Poospiza erythrophrys AY005203 Poospiza meianoleuca AY005210 . Poospiza alticola AY005199 Poospiza torquata AY005215 Poospiza caesar AY0052O2 Poospiza hypochondria AY005207 Hemispingus piurae AY039294 Hemispingus frontalis AF383020 HemispingusmelanotisAF100537 Hemispingus rufosuperciliaris AY039297 Thlypopsis sordida AF006256 Poospiza hispaniolensis AY005205 Hemispingus verticalis AF10053S Poospiza bolrviana AY005201 Poospiza omata AY005213 Blackbird parsimony ancestor state reconstruction Sturnella neglecta AF089064 Sturnella magna AF089063 Sturnella magna FM339779 no Leistes militaris AF089038 m Leistes militarius Sturnella bellicosa AF310065 Xanthocephalus xanthoce AF089067 Dolichonyx oryzivorus AF447367 Cacicus melanicterusAY117721 Cacicus chrysopterus AY117712 Cacicus sclateri AY117718 Cacicus vitellinus AY117704 Cacicus vitellinus * Cacicus cela AY 117701 Cacicus microrhynchus AY117710 D Cacicus pacificus AY117707 Cacicus uropygialis AY117708 Cacicus chrysonotus AY117717 Cacicus leucoramphus AF089017 Ocyalus latirostris AF472382 Cacicus haemorrhous AY117705 Psarocolius oseryi AF472383 Cacicus solitarius AY117719 Psarocolius decumanus AF472376 Psarocolius decumanus AF472373 Psarocolius decumanus AF472375 Psarocolius decumanus AF472371 Psarocolius viridis AY117698 Gymnostinops monlezuma AF472377 Psarocolius bifasciatus AY117699 Psarocolius wagleri AF472370 Psarocolius wagleri AF472368 Psarocolius atrovirens AF472366 Psarocolius angustifrons AF472365 Psarocolius angustifrons AF472364 Icterus leucopteryx AF089032 cterus auratus AF099276 Icterus nigrogularis AF099302 Icterus gularis AF099294 cterus galbula AY607658 cterus bullockii AY611476 cterus pustulatus AF099306 cterus parisorum AF089035 cterus graduacauda AF099291 cterus chrysater AF099282 cterus chrysater AF099281 cterus mesomelas AF089033 cterus mesomelas AF099300 cterus icterus AF099296 cterus icterus AF089031 cterus croconotus AF099297 cterus pectoralis AF099304 cterus graceannae AF310064 cterus maculialatus AF099299 cterus wagleri AF099308 cterus cucullatu AF099284 cterus prosthemelas AY211212 cterus fuertesi AY211215 cterus spurius AY211211 cterus dominicensis AF099285 cterus melanopsis AF099286 cterus portoricensis AF099288 cterus oberi AF099303 cterus bonana AF099277 cterus laudabilis AF099298 cterus auricapillus AF099310 cterus cayanensis AF099280 Amblycercus holosericeus AY 117722 Amblycercus holosericus Amblycercus holosericeus AF472386 Nesopsar nigerrimus AF089045 Gnorimopsar chopi AF089025 Oreopsar bolivianus AF089046 Molothrus badius AF089042 Agelaius icterocephalus AF089007 Agelaius ruficapillus AF089009 Agelaius flavus AF089066 Pseudoleistes guirahuro AF089051 Pseudoleistes virescens AF089052 Curaeus curaeus AF089020 o Agelaius thilius AF089010 Agelaius cyanopus AF290174 Agelaius xanthophthalmus AF089013 Lampropsar tanagrinus AF089037 Gymnomystax mexicanus AF089026 Macroagelaius imthurni AF089039 Dives dives SRF318 Dives warszwewiczi AF089021 Euphagus carolinus AF089023 Euphagus cyanocephalus AF089024 Quiscalus quiscula AF089058 Quiscalus mexican PA QME PP15 Quiscalus major AF089055 Quiscalus mexicanus AF089056 Quiscalus niger PR ON111450 Quiscalus niger AF089057 Quiscalus lugubris GU QLLM Quiscalus nicar NI QNG996 Agelaius humeralis AF089006 Agelaius xanthomus AF089012 Agelaius tricolor AF089011 Agelaius phoeniceus AF290173 Molothrus rufoaxillaris AF089044 Scaphidura oryzivora AF089060 Scaphidura oryzivora ^  Molothrus aeneus AF089040 Molothrus ater AF089041 ap Molothrus bonariensis un Molothrus bonariensis AF089043 10 Time (Ma) 183 Coda CKta* uropyglBIH AVlUTOfl " ' us dvysonolus AY117717 LA wucampiv. AFaesoi 7 I I I.M... .1  . f-M . CaUnn rionmontiou* AY11770S I'-,v. .1 • -lm A1 J '. JL" i I :>i I !••. M ,11 At 1 1 ; I ''j Purocaliis riocumaiiir, AF472376 PSKOPifcra dHCinuis AF472373 PWW.L*U* dBcumoiLis AF472375 ,.Anv;-.>;i i> ..i. < • .in. •. i) I, i-... ,u-. AY 11 7699 :ahK «9l*ri AF4JMJ0 Psoroeolk.1 wagtert AF472J6B Psarocolius auoviruns AF 172 366 f'-.,.i<,i-..iln:.,.i.,i|i|..tir •. AF47?7i5.r. . , . , , ! „ • I.I • 1r 11 J .". • • i IMK.i.^ wiy. AF08QO32 H U auialu-. AF09B276 torn- mgroynlari'i AF09S302 kwi» yuan AFOWJBJ LB yatuU AY60!fii« pusliiiulus AlOWiOU pansoiurn AF0890S5 A y HIUiKaudii AF0W2U1 us (Ivy**** AF099282 • ft mcMtrnttr. AF0B9OS3 I- -.i.=r-.l„- AifK* WS .• ., :-i i AF0992.9C Iii .1 •. ... I . • • l5IXTIWUl'iAF»93(W i . i - AF 310064 » miKutalmu* AF 09*298 ltt»L»»nglwi AF099308 icuxus cucullalu AF0992B4 orui1traAY21121S .. I..,,, AY211211 a dnmin>uam%AF09S2S& ii mi lanofwii AF0992B6 is pon«ti:nsisAF0992B8 B olxn AF099J03 IS botlMiH AF069277 • •., I .:- I • "I • i'i -1."• • tonus uy.monU AF 0992SQ AmUytemis m*n**wus AVI 17722 AmhtyCPreus hdmariMUS AmHycacus twlo-jiiecir. AF47! J98 ip-.< r>g»<im^ AF089046 mousa clufM Af09902'. pui 1**4.,™* AF089046 ih, LIS bulk,-. AFOB9M2 AqMaiia Icieroceptolu? AFOB9007 Aipi l.ii.i-. rLifit.ipilL.i- AF0B9Q09 :-i 11 i i...' AF0MO66 (Hnudotersiei gurahuro AFU89uil Piaui)uli;«ios viicbtcns AF089052 us cuiiHus AF089020 IftlM ryanupua AF 280174 AiH'n'. >.pil...i|:lilh:ilmin AFQB9013 ' , , j • .. AF0B9O37 ymnomyslai mtuiainiis AF0B9026 M p. ..., r.ri, i Af089039 " <im I f III Euphadu* iiatolinui A F08902 3 Eiipliagir- tyan«c[twlur> AF DB9024 11 L-. .,.„-. .,.„.,. ,i, AF089058 CMwniu! menlfBn PA QME PP15 Qui see his major AF0B90SS QuiscjIUT. nn:i.lcanu. AF 089056 ausr»j<i PS0NH14W OuiaCJUS 1I9M AFOBBOi? • i ... • i j'. 1.  i .I. GU Min Qi4«calu* nlear NI dNGiSt AquhmA UMPJMh AF0S9QQ6 A.j. I.,,,,-. <.!II|I».TIIISAF0B9012 • • ni%tricuo< Afoeaon us \f»mtkm* AF280173 VLIS rufoiuilMiis A F 08934* VafitwIiiM oryiivurn AF08B060 Sr^ ihHlurj oryzrvori UuHiltKUi Wm AF0S9O41 

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