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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 T Y L E R WEIR  B.Sc, Canadian University College, 2001  A THESIS SUBMITTED IN PARTIAL FULFILLMENT O F T H E REQUIREMENTS FOR T H E D E G R E E O F 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  TABLE O F CONTENTS  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 O F T A B L E S Table Table Table Table Table  2.1 2.2 4.1 5.1 5.2....  21 22 76 103 104  iv  LIST OF FIGURES Figure 2.1 Figure 2.2 Figure 2.3 Figure 3.1 Figure 3.2 Figure 3.3 Figure 4.1 Figure 4.2 Figure 4.3 Figure 4.4 Figure 5.1 Figure 5.2 Figure 5.3  24 25 26 41 42 43 78 79 80 80 105 106 107  .•  v  LIST OF APPENICES Appendix Appendix Appendix Appendix Appendix Appendix Appendix Appendix Appendix Appendix  1 Additional sequencing methods 2 Divergence dates of superspecies 3 Genbank accession numbers for Chapter Three 4 Simulated distributions of sister species ages 5 Neotropical ancestor state reconstructions of altitude 6 Mean intraspecific sequence divergence in Neotropical birds 7 Individual localities for genetic samples in Chapter Five 8 Bayesian phylogeny of nine-primaried oscines 9 Taxonomic changes to nine-primaried oscines 10 Great American Interchange phylogenies and reconstructions  vi  116 119 122 132 133 140 143 169 172 174  ACKNOWLEDGEMENTS  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: 814828. 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, 579596. Wiens, J J . 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, 273309.  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 SPECIATION A N D EXTINCTION O F BIRDS A N D MAMMALS 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 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. 1  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 midpointlatitude. 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\, c ) for the linear relationships M  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 lagtime 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 M A T E R I A L S 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 (t ) M  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 + t . This M  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, b , cx, and c^, the appropriate simulated distribution for a sister species with latitude L M  was determined by solving for X and fx in Equations 1 and 2. For each value of bx, b , cx, M  and c , the likelihood was obtained by multiplying the probabilities of each sister species. M  The values of bx, b^, cx, and c with the highest likelihood are the maximum likelihood M  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 yintercepts (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 faunawide 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 in the tails and heads and fewer near the mean. This results in every combination s  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  Campylorliamphus pusillus  PANAMA, Bocas del Toro, Continental Divide  SI'RI  Corvus caurinus  CANADA, British Columbia, Vancouver  CO  Tissue No. IWO'U none  JF202815 " EF2T0778  1 Dendrocolaptes sahctitliomae PANAMA, Bocas del Toro, Cerro Chalite  SIK1  Dendrocolaptes sanctithomae PANAMA? Bocas del Toro, Cerro Chalite  Mkl  PANAMA, Bocas del Toro, Cerro Chalite  S'IRI  PANAMA, Panama Province, Achiote Road  STRI  EF202819  ~  COSTA RICA, San-Jo^-  IAIN  II'WU  iF202814  j  JTW298  EF212894  F Heterospingus riibrifrons Manacus vitellinus f Pseudocolaptes lawrehcii.  '•  Tityra semifasciata  PANAMA, Bocas del Toro, Cerro Chalite  STRI  Trogon viridis  PANAMA, Panama Province, confluence of Rio Charges and Rio Chagrecito  STRp  21  TW251 ' • ••  Accession No.  ULu7v 7-""TW278~ TA-MVI-PC16  •A-'l"\ i:i)^4  " '!R12895' "'--H :  EF212896 ^ " 1F202820 ' '  5F202818  1  "!  Table 2.2 Molecular clock calibrations for Mammalian orders. ORDER (Family)  Date of Split  GTRgamma distance  Rate (%)  Calibration Reference  split Myotragus balearicus and Ovis  5.4  0.1757  3.28  LaluezaFox et al 2005  earliest split within Vulpes  9.5  0.1921  2.02  split Canis and Lycaon  6.7  0.1716  2.56  split Canis latrans / C. lupus and C. simensis  3.5  0.0823  2.35  Wayne et al 1997 Wayne et al 1997 Wayne et al 1997  split Myotis nattereri and M. schaubi  6  0.2209  3.68  split Myotis daubentonii from M. bechsteinii  5  0.1929  3.86  split Micoureus and Marmosa murina / M. lepida  14.1  0.2884  2.05  split Didelphis and Philander  5.9  0.1758  2.98  first split within extant species of Ochotona  5.5  0.2769  5.04  split Homo and Pan  5.4  0.1490  2.76  Calibration Taxon  ARTIOD A C T Y L A Bovidae  CARNIVORA Canidae  CHIROPTERA Vespertilionidae  Stadelma nn et al in press Stadelma nn et al in press  DIDELPHIMORPHIA Didelphidae  Steiner et al 2005 Steiner et al 2005  LAGOMORPHA Ochotonidae  Yu et al 2000  PRIMATE Hominidae  RONDENTIA Geomyidae  split Perognathus / Chaetodipus and Dipodomys / Microdipodops  16.5  0.5800  Riddle  3.52  ,  et  22  al  split Geomys and Cratogeomys/Pappogeomys  6  split Pappogeomys and Cratogeomys  Muridae  Sciuridae  0.3447  5.75  0.2546  6.36  split Thomomyini and Geomyini  5.6  0.4399  7.93  split Batomys and all other Murine genera  12  0.3492  2.91  split Microtus califomicus and M. mexicanus  2.1  split Marmota and sister clade of Spermophilus / Cynomys  7.7  split Cynomys and sister clade of Spermophilus  2.7  First split within Spermophilus, Marmota and Cynomys  16.5  0.1532  0.2038  0.1504  7.30  2.65  5.57  0.2680  1.62  0.2354  2.62  0.5125  2.56  2000 DeWalt et al 1993 DeWalt et al 1993 DeWalt et al 1993 Steppan and Adkin s2004 Conroy and Cook 2000 Harrison et al 2003 Harrison et al 2003 Harrison et al 2003  SORICOMORPHA Soricidae  split Cryptotis and Blarina  split Crocidurinae and Soricinae  20  23  Brant and orti 2002 Fumagall i et al 1999  o o °o  oo  o %  9? o ooo°oo° -i  10 20 30 40 50 60  7.0  0  <fe"V^S --*^. -  T  1  r  1  r—  10 20 30 40 50 60 70  Midpoint latitude (N or S)  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 C I T E D  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. Proceedings of the Royal Society of London Series B-Biological Sciences 265 :1707-1712. Bohm M and P. J. Mayhew. 2005. Historical biogeography and the evolution of the latittudinal gradient in species richness in the Papionini (Primata: Cercopithecidae). Biological Journal of the Linnean Society 85: 235-246. Brant, S. V., and G. Orti 2002. Molecular phylogeny of short-tailed shrews, Blarina (Insectivora: Soricidae). Mol. Phylogenet. Evol. 22:163-173. Buzas, M . A., L. S. Collins, and S. J. Culver. 2002. Latitudinal difference in biodiversity caused by higher tropical rate of increase. Proceedings of the National Academy of Sciences of the United States of America 99: 7841-7843. Conroy C. J. and J. A. Cook. 2000) Molecular systematics of a Holarctic rodent (Microtus: Muridae). Journal of Mammalogy, 81: 344-359. Cardillo, M . 1999. Latitude and rates of diversification in birds and butterflies. Proceedings of the Royal Society of London Series B-Biological Sciences 266:12211225. Cardillo, M., C. D. L. Orme, and I. P. F. Owens. 2005. Testing for latitudinal bias in diversification rates: An example using New World birds. Ecology 86: 2278-2287. Crame, J.A. 2002. Evolution of taxonomic diversity gradients in the marine realm: a comparison of Late Jurassic and Recent bivalve faunas. Paleobiology, 28, 184-207 DeWalt, T. S., P. D. Sudman, M . S. Hafner, and S. K. Davis. 1993. Phylogenetic relationships of pocket gophers (Cratogeomys and Pappogeomys) based on mitochondrial DNA cytochrome b sequences. Mol. Phylogenet. Evol. 2:193-204 Edwards, S. V. and P. Beerli. 2000. Perspective: gene divergence, population divergence, and the variance in coalescence time in phylogeographic studies. Evolution 54: 1839-1854. Fischer, A.G. 1960. Latitudinal variations in organic diversity. Evolution 14: 64-81. Fleischer, R. C , C. E. Mcintosh, and C. L. Tarr. 1998. Evolution on a volcanic conveyor belt: using phylogeographic reconstructions and K-Ar-based ages of the Hawaiian Islands to estimate molecular evolutionary rates. Mol. Ecol. 7, 533-545. Fumagalli, L., P. Taberlet, D. T. Stewart, L. Gielly, J. Hausser, and P. Vogel. 1999. Molecular phylogeny and evolution of Sorex shrews (Soricidae: Insectivora) inferred from mitochondrial DNA sequence data. Mol. Phylogenet. Evol. 11: 222-235.  27  Garcia-Moreno, J. 2004. Is there a universal mtDNA clock for birds? J. Avian Biol. 35: 465-468. Gaston, K. J. 2000. Global patterns in biodiversity. Nature 405: 220-227. Harrison R. G., S. M . Bogdanowicz, R. S, Hoffmann, E. Yensen, and P. W. Sherman. 2003. Phylogeny and evolutionary history of the ground squirrels (Rodentia: Marmotinae). Journal of Mammalian Evolution, 10, 249-276. Hawkins, B. A., J. A. F. Diniz, C. A. Jaramillo, and S. A. Soeller. 2006. Post-Eocene climate change, niche conservatism, and the latitudinal diversity gradient of New World birds. Journal of Biogeography 33:770-780. Hillebrand, H. 2004. On the generality of the latitudinal diversity gradient. American Naturalist 163:192-211. Ho, S. Y. W., M . J. Phillips, A. Cooper, and A. J. Drummond. 2005. Time dependency of molecular rate estimates and systematic overestimation of recent divergence times. Mol. Biol. Evol. 22: 1561-1568. Honeycutt, R.L., M.A. Nedbal, R.M. Adkins, and L.L. Janacek. 1995. Mammalian mitochondrial DNA evolution: a comparison of the cytochrome b and cytochrome c oxidase II genes. Journal of Molecular Evolution 40: 260-272 Jablonski, D., K. Roy, and J.W. Valentine. 2006. Out of the tropics: evolutionary dynamics of the latitudinal diversity gradient. Science 314:102-106. Kendall, M . G. 1948. The Advanced Theory of Statistics, vol i. Charles Griffin and Co. Ltd. Klicka, R. M . and R. M . Zink. 1997. The importance of recent ice ages in speciation: a failed paradigm. Science 277: 1666-1669. Lalueza-Fox, C , J. Castresana, L. Sampietro, T. Marques-Bonet, J. A. Alcover, and J. Bertranpetit. 2005. Molecular dating of caprines using ancient DNA sequences of Myotragus balearicus, an extinct endemic Balearic mammal. BMC Evol. Biol. 5: 111. Locfit. 2005. http://www.locfit.info/ Nee S., R. May, and P. Harvey. 1994. The reconstructed evolutionary process. Philos. Trans. R. Soc. Lond. B. 344: 305-311 Nee, S., E. C. Holmes, R. M . May, and P. H. Harvey. 1994. Extinction rates can be estimated from molecular phylogenies. Philos. Trans. R. Soc. Lond. B Biol. Sci. 344: 77-82. Pianka, E. R. 1966. Latitudinal gradients in species diversity - a review of concepts. American Naturalist 100:33-46. Ricklefs R.E. Global variation in the diversification rate of passerine birds. American Naturalist in press. 2006.  28  Ricklefs, R. E. 2005. Phylogenetic perspectives on patterns of regional and local species richness. Pages 16-40 in C. D. a. C. M . E.Bermingham editor. Tropical Rainforests: Past, Present, and Future. University of Chicago Press, Chincago. Riddle, B. R., D. J. Hafner, and L. F. Alexander. 2000. Comparative phylogeography of Baileys' Pocket Mouse (Chaetodipus baileyi) and the Peromyscus eremicus species group: Historical vicariance of the Baja California peninsular desert. Mol. Phyl. Evol. 17:161-172. Ridgely, R. S. et al. 2005. Digital Distribution Maps of the Birds of the Western Hemisphere, version 2.1. NatureServe, Arlington, Virginia, USA Stadelmann B, L. K. Lin, T. H. Kunz, M . Ruedi. 2007. Molecular phylogeny of New World Myotis (Chiroptera, Vespertilionidae) inferred from mitochondrial and nuclear DNA genes. Molecular Phylogenetics and Evolution 43: 32-48 Stebbins G. C. 1974. Flowering plants: Evolution above the species level. Harvard University Press, Cambridge, MA. Steiner C, M . Tilak, E. J. P. Douzery, F. M . Catzeflis. 2005. New DNA data from a transthyretin nuclear intron suggest an Oligocene to Miocene diversification of living South America opposums (Marsupialia: Didelphidae). Mol Phylogenet Evol.35: 363379 Steppan, S. J., R. M . Adkins, and J. Anderson. 2004. Phylogeny and divergence-date estimates of rapid radiations in muroid rodents based on multiple nuclear genes. Syst. Biol. 53: 533-553. Swofford D.L. 2002. PAUP*4.0blO: phylogenetic analysis using parsimony (*and oher methods). Sunderland, Sinauer. Wallace A. R. 1878. Tropical Nature and Other Essays. MacMillan, London and New York. Wayne R. K., E. Geffen, D. J. Girman, K. P. Koepfli, L. M . Lau, and C. R. Marshall. 1997. Molecular systematics of the Canidae. Systematic Biology. 46: 622-653. 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. PhySim: Phylogenetic Tree Simulation Package. 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 271:18811887. 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 BIRDS  2  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  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. 2  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 subboreal 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% Myr1 (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 GTRgamma 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" does not change these results greatly. These coalescence times are expected to be 1  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  18  to 8  16  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 palaeotemperature record, a series of major glacial advances southward began 0.7 18  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)  1  Sphyrapicus  0 S. nuchalis O & ruber 9 S. varius  Dendroica  ^ D. townsendi O occidentalis 9 D. virens  Vermivora  ^ virginiae O ' W ridgwayi 9 If (>J mficapilla  Passerella  ©rt.yunalaschensis (jj) P. (i'J megarhyncha Q P. schistacea  ;  •  P. fi.> (fiocn  9 V. plumbeus O cassinii 9 V solitarius  Vireo  9  Empidonax  ri  £. occidentalis  0. lolmiei 0. Philadelphia  Oporornis  O ^ rufescens  Poecile  9 P. hudsonica (Al  C. bicknelli C. minimus  CathaJUS  i  estimated age (Myr)  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  0  1  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. The present-day interglacial is represented by the black arrow.  42  Fig. 3.3 Genetic distances (GTR-gamma distances) and approximate dates of coalescence events between closely related species belonging to superspecies in boreal forest, subboreal and Neotropical lowland avifaunas. The Pleistocene is indicated- by the shaded area.  43  3.5 L I T E R A T U R E C I T E D  Amadon, D. 1966. The superspecies concept. Syst. Zool. 15, 245-2491 American Ornithologists Union 1998. Checklist of North American birds, 7th edn. Washington, DC: American Ornithologists Union. Arbogast, B. S. and G. J. Kenagy. 2001. Comparative phylogeography as an integrative approach in biogeography. J. Biogeogr. 28, 819-825. Arbogast, B. S. and J. B. Slowinski. 1998. Pleistocene speciation and the mitochondrial DNA clock. Science 282, 1955a. Arbogast, B. S., S. V. Edwards, J. Wakeley, P. Beerli, and J. B. Slowinski. 2002. Estimating divergence times from molecular data on phylogenetic and population genetic time-scales. A. Rev. Ecol. Syst. 33, 707-740. Avise, J. C. and D. Walker. 1998. Pleistocene phylogeographic effects on avian populations and the speciation process. Proc. R. Soc. Lond. B 265, 457-463. Avise, J. C , D. Walker, and G. C. Johns. 1998. Speciation durations and Pleistocene effects on vertebrate phylogeography. Proc. R. Soc. Lond. B 265, 1707-1712. Barendregt, R. W. and E. Irving. 1998. Changes in the extent of North American ice sheets during the late Cenozoic. Can. J. Earth Sci. 35, 504-509. Bernatchez, L. and C. C. Wilson. 1998. Comparative phylogeography of Nearctic and Palearctic fishes. Mol. Ecol. 7, 431^152. Brunsfeld, S. J., J. Sullivan, D. E. Soltis and P. S. Soltis. 2001. Comparative phylogeography of northwestern North America: a synthesis. In Integrating ecological and evolutionary processes in a spatial context (ed. J. Silvertown and J. Antonovics), pp. 319-339. Oxford: Blackwell Science. Demboski, J. R. and J. A. Cook. 2001. Phylogeography of the dusky shrew, Sorex monticolus (Insectivora, Soricidae): insight into deep and shallow history in northwestern North America. Mol. Ecol. 10, 1227-1240. Diamond, A. W. and A. C. Hamilton. 1980. The distribution of forest passerine birds and Quaternary climatic change in tropical Africa. J. Zool. Lond. 191, 379^4-02. Drovetski, S. V. 2003. Plio-Pleistocene climatic oscillations, Holarctic biogeography and speciation in an avian subfamily. J. Biogeogr. 30, 1173-1181. 44  Edwards, S. V. and P. Beerli. 2000. Perspective: gene divergence, population divergence, and the variance in coalescence time in phylogeographic studies. Evolution 54, 1839-1854. Fleischer, R. C , C. E. Mcintosh, and C. L. Tarr. 1998. Evolution on a volcanic conveyor belt: using phylogeographic reconstructions and K-Ar-based ages of the Hawaiian Islands to estimate molecular evolutionary rates. Mol.Ecol. 7, 533-545. Gill, F. B. 1997. Local cytonuclear extinction of the goldenwinged warbler. Evolution 51, 519-525. Haffer, J. 1969. Speciation in Amazonian forest birds. Science 165, 131-137. Hubbard, J. P. 1974. Avian evolution in the aridlands of North America. Living Bird 12, 155-196. Huelsenbeck, J. and B. Rannala. 1997. Phylogenetic methods come of age: testing hypotheses in an evolutionary context. Science 276, 227-232. Kimura, M . 1980. A simple method for estimating evolutionary rate of base substitutions through comparative studies of nucleotide sequences. J. Mol. Evol. 16, 111-120. Klicka, R. M . and R. M . Zink. 1997. The importance of recent ice ages in speciation: a failed paradigm. Science 277, 1666- 1669. Klicka, R. M . and R. M . Zink. 1999. Pleistocene effects on North American songbird evolution. Proc. R. Soc. Lond. B 266, 695-700. Lindbladh, M., G. L. Jacobson Jr, and M . Schauffler. 2003. The postglacial history of three Picea species in New England, USA. Quatern. Res. 59, 61-69. Lovette, I. J. and E. Bermingham. 1999. Explosive speciation in the New World Dendroica warblers.  Proc. R. Soc. Lond. B 266, 1629-1636.  Lovette, I. J. and E. Bermingham. 2001. A mitochondrial sequence-based phylogenetic analysis of Parula woodwarblers (Aves: Parulidae). Auk 1.18, 211-215. Mengel, R. M . 1964 .The probable history of species formation in some northern wood warblers (Parulidae). Living Bird 3, 9-43. Moore, W. S. 1995. Inferring phylogenies from mtDNA variation: mitochondrial gene trees vs. nuclear gene trees. Evolution 49, 718-726.  45  Moritz, C , J. L. Patton, C. J. Schneider, and T. B. Smith. 2000. Diversification of rainforest faunas: an integrated molecular approach. A. Rev. Ecol. Syst. 31, 533563. Near, T. J., T. W. Kassler, J. B. Koppelman, C. B. Dillman, and D. P. Philipp. 2003. Speciation in North American black basses, Micropterus. Evolution 57, 16101621. Page, R. D. M . 1988. Quantitative cladistic biogeography: constructing and comparing area cladograms. Syst. Zool. 37, 254-270. Rohwer, S., E. 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, 453464. 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 BIRDS 3  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  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.  3  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 (GarciaMoreno 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. All 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 ystatistic 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,...g -i be the internode n  distances and g be the distance between the most recent node and the present (Fig 4.1b). n  The statistic I use here is identical to that developed by Pybus and Harvey except that it excludes g . This last interval should be excluded from real phylogenies because unlike n  the simulated phylogenetic trees used by Pybus and Harvey there is no splitting event at the present and thus the interval g is not drawn from the same distribution as other n  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  r=  1 n-m-l  v  E E*** - T i=m \k=m  JJ  V  Z  /  58  Equation 4.1  where S is the sum of the branch lengths in the phylogeny (excluding the interval g ) and n  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 g which is excluded from LTT plots and the y statistic. n  Nevertheless, some of these splits may predate g . This is especially true when the n<  interval g is short. Because detailed intraspecific sampling was lacking for most of the n>  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): Equation 4.2 Under the null model of pure birth, Z has a standard normal distribution where / is the number of taxa being combined and y is the y-statistic for taxon p. Values of Z greater p  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  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 g -l (Fig. 4.1) for each tree. The utility of this estimate is limited because it assumes rates n  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 Equation 4.3  b(t) = (n-m) / S  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 g in each taxon; see n  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 = b 1 (n-m)  Equation 4 . 4  1  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 V"'M)"' M V i T  T  Equation 4 . 5  l  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,)  Equation 4.6  2  =  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 = 24.57, d.f. = 10, p = 0.006) datasets. To 2  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 = 21.07, d.f. = 15, p 2  = 0.13). When Carduelis, Cranioleuca, and Muscisaxicola were excluded, constant rates in highland faunas could not be rejected (X = 8.7, d.f. = 7, p = 0.27). For both lowland 2  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; r = 0.57, p = 2  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 = 0.19, P = -0.192 2  ±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 (X = 3.60, df = 1, p = 0.058) but no 2  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 (X = 0.54, df = 1, p < 0.46). However, rates 2  significantly doubled (as high as 0.52 species per lineage/Ma) during the late Pleistocene (X = 7.16, df = 1, p < 0.008; Fig. 4.2b). This late Pleistocene increase was not significant 2  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 (X = 5.1, df = 1, p < 0.024) but when highland outliers were excluded lowland rates were 2  higher (X = 6.51, df = 1,p = 0.01). No difference inrates between these faunas occurred 2  before the Pleistocene (all highland taxa included X = 1.88, df = 1, p = 0.17, outliers 2  excluded X = 2.58, df = l,p = 0.11). These data suggest that recent climatic fluctuations 2  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  70  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  73  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 Species  y (p value)  4  Region a) Lowland Amazon Blackbird clade Crax Dendrocincla Icterus Myiarchus Nyctibius Pionopsitia Psarocolius Pteroglossus Ramphocelus Swallow clade Tachycineta Tangara Trogon Veniliornis Xiphorhynchus Z-test Average b) Highland Anairetes Carduelis Cinclodes . Cranioleuca  1  Available  2  Sympatric  Expected phylogroups per species  (species / lineage per Ma)  (species / lineage per Ma)  0.35 0.25 0.65 0.51 0.22 0.40 0.11 0.32 0.26 0.49 0.80 0.12 1.37 0.30 0.13 0.64 0.25  0.00 0.00 0.00 0.60 0.00 0.43 0.00 0.42 0.00 0.24 1.08 0.00 2.19 0.00 0.00 0.39 0.00  11.6 631.0 0.2 0.7 2.3 -0.5 6.3 -0.1 53.7 0.3 0.4 1.8 0.7 781.2 0.8 2.6 7.6  0.42  0.32  88.3  0.30 4.28 0.49 0.83  0.00 5.59 0.08 0.00  0.4 0.0 0.0 0.8  Phylogenetic Source  6  3  16 14 . 13 7 16 11 6 9 19 12 7 12 5 22 14 10 13  14 13 13 7 16 10 5 8 15 12 6 12 5 19 11 8 13  6 9 3 3 6 5 5 3 11 4 2 8 2 8 5 3 6  1.05 0.27 0.73 1.38 0.33 0.31 10.10 1.38 1.10 0.91 1.95 0.40 2.34 1.87 3.69 3.30 1.63  12  11  5  1.93  7 10 11 11  6 8 11 10  5 5 3 3  1.21 0.59 0.42 0.34  -2.12 (0.033) -3.26 (0.001) -1.80 (0.072) 0.07 (0.944) -2.06 (0.039) 0.27 (0.842) -0.34 (0.730)* 1.15 (0.248) -1.79 (0.068) -0.11 (0.912) 0.27.(0.785) -2.02 (0.043) 0.56 (0.576) -2.11 (0.032) -1.18 (0.229) -0.37 (0.707) -1.26 (0.208) -3.92 (<0.0001)  -1.07 (0.282) 1.04(0.290) -0.62 (0.535) -1.15 (0.251)  Russello and Amato 2004 Lanyon and Omland 1999 Pereira and Baker 2004 this study Omland etal. 1999 Joseph et al. 2003 Mariaux and Braun 1996 Eberhard and Bermingham 2005 Price and Lanyon 2002, 2004 - Eberhard and Bermingham 2005 Hackett 1996 Sheldon et al. 2005 Whittingham et al. 2002 Burns and Naoki 2004 this study, Espinosa de los 1998 Moore et al. 2005 Aleixo2002  Roy et al. 1999 van den Elzen et al. 2001 Chesser 2004 Garcia-Moreno et al. 1999a  Geositta Hemispingus Metallura Muscisaxicola Ochthoeca Tangara Troglodytes  9 14 10 12 11 26 7  9 12 9 12 11 23 6  4 7 2 6 7 13 3  4.14 0.57 0.34 0.33 2.19 0.29 3.29  0.33 0.12 0.24 5.31 0.32 0.20 0.24  0.21 (0.834) -1.72 (0.081) -0.85 (0.394)  4.07 (0.000)  -0.13 (0.897)  -3.17 (0.032)  0.31 0.00 0.00 6.64 0.17 0.00 0.03  0.5 1.2 0.3 -0.6 0.7 0.7 0.5  Cheviron et al. 2005a Garcia-Moreno et al. 2001 Garcia-Moreno et al. 1999b Chesser2000 Garcia-Moreno et al. 1998 Burns and Naoki 2004  -0.04 (0.968) -1.03 (0.300) Z-test 11 5 1.25 1.15 1.17 0.4 Average 12 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 g is not excluded, y equals -2.3 (p = 0.02) n  Rice etal. 1999  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 ( L T T ) 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.  78  A) Lowland  B) Highland  Miocene  Fig. 4.2  Pliocene  Miocene  Pleistocene  Pliocene  -i 1 Pleistocene  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).  A) Lowland  0  2  4  6  B) Highland  8  10 12 14  0  2  4  6  8  10 12 14  s y m p a t r i c species  Fig. 4.4 The relationship between the maximum number of regionally sympatric species in each taxa and values of the corrected y-statistic for (A) lowland and (B) highland Neotropical faunas.  80  4.5 L I T E R A T U R E C I T E D  Aleixo, A. 2002. Molecular systematics and the role of the "varzea" - "terra-firme" ecotone in the diversification of Xiphorhynchus woodcreepers (Aves : Dendrocolaptidae). Auk 119:621-640. 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. Andriessen, P. A. M., K. F. Helmens, H. Hooghiemstra, P. A. Riezebos, and T. van der Hammen. 1993. Absolute chronology of the Pliocene-Quaternary sediment sequence of the Bogota area, Colombia 60. Quatern. Sci. Rev. 12:483-501. Armenta, J. K., J. D. Weckstein, and D. F. Lane. 2005. Geographic variation in mitochondrial DNA sequences of an Amazonian nonpasserine: The black-spotted barbet complex. Condor 107:527-536. Avise, J. C , D. Walker, and G. C. Johns. 1998. Speciation durations and Pleistocene effects on vertebrate phylogeography. Proc. R. Soc. Lond. B Biol. Sci. 265:17071712. Ayres, J. M., and T. H. Cluttonbrock. 1992. River boundaries and species range size in Amazonian primates. Am. Nat. 140:531-537. Baldwin, B. G., and M . J. Sanderson. 1998. Age and rate of diversification of the Hawaiian silversword alliance (Compositae) 1. Proc. Natl. Acad. Sci. U. S. A. 95:9402-9406. Barraclough, T. G., and A. P. Vogler. 2002. Recent diversification rates in North American tiger beetles estimated from a dated mtDNA phylogenetic tree. Mol. Biol. Evol. 19:1706-1716. Bates, J. M . , J. Haffer, and E. Grismer. 2004. Avian mitochondrial DNA sequence divergence across a headwater stream of the Rio Tapajos, a major Amazonian river. J. Ornithol. 145:199-205. Bennett, K. D. 1990. Milankovitch Cycles and their effects on species in ecological and evolutionary time. Paleobiology 16:11-21. Bloemendal, J., and P. Demenocal. 1989. Evidence for a change in the periodicity of tropical climate cycles at 2.4 myr from whole-core magnetic-susceptibility measurements. Nature 342:897-900.  81  Brown, K. S., P. M . Sheppard, and J. R. G. Turner. 1974. quaternary refugia in tropical America - evidence from race formation in Heliconius butterflies 305. Proc. R. Soc. Lond. B Biol. Sci. 187:369-378. Burns, K. J., and K. Naoki. 2004. Molecular phylogenetics and biogeography of Neotropical tanagers in the genus Tangara. Mol. Phylogenet. Evol. 32:838-854. Bush, M . B., P. E. De Oliveira, P. A. Colinvaux, M . C. Miller, and J. E. Moreno. 2004. Amazonian paleoecological histories: one hill, three watersheds. Palaeogeogr. Palaeoclimatol. Palaeoecol. 214:359-393. Bush, M . B., and M . R. Silman. 2004. Observations on Late Pleistocene cooling and precipitation in the lowland Neotropics. J. Quaternary Sci. 19:677-684. Capparela, A. P. 1988. Genetic variation in Neotropical birds: implications for the speciation process. Acta XLX Congr. Int. Ornithol. 101:189-208. Capparela, A. P. 1991. Neotropical avian diversity and riverine barriers. Acta X X Congr. Int. Ornithol. 1:307-316. Cerqueira, R. 1982. South American landscapes and their mammals. Pages 53-75 in M . A. Mares, and H. H. Genoways editors. Mammalian biology in South America. Pymatuning Laboratory of Ecology, University of Pittsburgh, Linesville, Pa. Chesser, R. T. 2000. Evolution in the high Andes: The phylogenetics of Muscisaxicola ground-tyrants. Mol. Phylogenet. Evol. 15:369-380. Chesser, R. T. 2004. Systematics, evolution, and biogeography of the South American ovenbird genus Cinclodes. Auk 121:752-766. Cheviron, Z. A., A. P. Capparella, and F. Vuilleumier. 2005a. Molecular phylogenetic relationships among the Geositta miners (Furnariidae) and biogeographic implications for avian speciation in Fuego-Patagonia. Auk 122:158-174. Cheviron, Z. A., S. J. Hackett, and A. P. Capparella. 2005b. Complex evolutionary history of a Neotropical lowland forest bird (Lepidothrix coronatd) and its implications for historical hypotheses of the origin of Neotropical avian diversity. Mol. Phylogenet. Evol. 36:338-357. Colinvaux, P. A., P. E. De Oliveira, and M . B. Bush. 2000. Amazonian and Neotropical plant communities on glacial time-scales: The failure of the aridity and refuge hypotheses. Quatern. Sci. Rev. 19:141-169. Colinvaux, P. A., P. E. DeOliveira, J. E. Moreno, M . C. Miller, and M . B. Bush. 1996. A long pollen record from lowland Amazonia: Forest and cooling in glacial times. Science 274:85-88.  82  Cox D. R., and P. A. W. Lewis. 1966. The statistical analysis of series of events. Methuen, London. Darlington P. J. 1957. Zoogeography: the geographical distribution of animals. Wiley, New York. Eberhard, J. R., and E. Bermingham. 2005. Phylogeny and comparative biogeography of Pionopsitta parrots and Pteroglossus toucans. Mol. Phylogenet. Evol. 36:288-304. Espinosa de los, M . A. 1998. Phylogenetic relationships among the trogons. Auk 115:937-954. ' Fisher, A. G. 1960. Latitudinal variations in organic diversity. Evolution 14:64-81. Fjeldsa, J., and J. C. Lovett. 1997a. Geographical patterns of old and young species in African forest biota: The significance of specific montane areas as evolutionary centres. Biodivers.Conserv. 6:325-346. Fjeldsa, J., and J. C. Lovett. 1997b. Biodiversity and environmental stability. Biodivers. Conserv. 6:315-323. Garcia-Moreno, J. 2004. Is there a universal mfDNA clock for birds? J. Avian Biol. 35:465-468. Garcia-Moreno, J., P. Arctander, and J. Fjeldsa. 1998. Pre-Pleistocene differentiation among chat-tyrants. Condor 100:629-640. Garcia-Moreno, J., P. Arctander, and J. Fjeldsa. 1999a. A case of rapid diversification in the Neotropics: Phylogenetic relationships among Cranioleuca spinetails (Aves, Furnariidae). Mol. Phylogenet. Evol. 12:273-281. Garcia-Moreno, J., P. Arctander, and J. Fjeldsa. 1999b. Strong diversification at the treeline among Metallura hummingbirds. Auk 116:702-711. Garcia-Moreno, J., and J. Fjeldsa. 2000. Chronology and mode of speciation in the Andean avifauna. Bonn. Zool. Monogr. 46:25-46. Garcia-Moreno, J., J. Ohlson, and J. Fjeldsa. 2001. MtDNA sequences support monophyly of Hemispingus tanagers. Mol. Phylogenet. Evol. 21:424-435. Grafe, K., W. Frisch, I. M . Villa, and M . Meschede. 2002. Geodynamic evolution of southern Costa Rica related to low-angle subduction of the Cocos Ridge; constraints from thermochronology. Tectonophysics 348:187-204. Gregory-Wodzicki, K. M . 2000. Uplift history of the Central and Northern Andes: A review. Geol. Soc. Amer. Bull. 112:1091-1105.  83  Hackett, S. J. 1996. Molecular phylogenetics and biogeography of tanagers in the genus Ramphocelus (Aves). Mol. Phylogenet. Evol. 5:368-382. Haffer, J. 1969. Speciation in Amazonian forest birds. Science 165:131-137. Haffer, J. 1974. Avian speciation in tropical South America, with a systematic survey of the toucans (Ramphastidae) and jacamars (Galbulidae), Publ. Nuttall Ornithol. Club no. 14. Haffer, J. 1990. Avian species richness in tropical South America. Stud. Neotrop. Fauna Environ. 25:157-183. Haffer, J. 1997. Alternative models of vertebrate speciation in Amazonia: An overview. Biodivers.Conserv. 6:451-476. Haffer, J., and G. T. Prance. 2001. Climatic forcing of evolution in Amazonia during the Cenozoic: On the refuge theory of biotic differentiation. Amazoniana 16:579-605. Hey, J. 1992. Using phylogenetic trees to study speciation and extinction. Evolution 46:627-640. Ho, S. Y. W., M . J. Phillips, A. Cooper, and A. J. Drummond. 2005. Time dependency of molecular rate estimates and systematic overestimation of recent divergence times. Mol. Biol. Evol. 22:1561-1568. Hooghiemstra, H. 1989. Quaternary and Upper-Pliocene glaciations and forest development in the tropical Andes - evidence from a long high-resolution pollen record from the sedimentary basin of Bogota, Colombia. Palaeogeogr. Palaeoclimatol. Palaeoecol. 72:11-26. Hooghiemstra, H., J. L. Melice, A. Berger, and N. J. Shackleton. 1993. Frequency-spectra and paleoclimatic variability of the high-resolution 30-1450-Ka Funza I pollen record (Eastern Cordillera, Colombia). Quatern. Sci. Rev. 12:141-156. Hooghiemstra, H., and T. van der Hammen. 2004. Quaternary Ice-Age dynamics in the Colombian Andes: developing an understanding of our legacy. Philos. Trans. R. Soc. Lond. B Biol. Sci. 359:173-180. Hoorn, C. 1993. Marine incursions and the influence of Andean tectonics on the Miocene depositional history of northwestern Amazonia - results of a palynostratigraphic study. Palaeogeogr. Palaeoclimatol. Palaeoecol. 105:267-309. Hoorn, C. 1994. Fluvial paleoenvironments in the intracratonic Amazonas basin (Early Miocene - Early Middle Miocene, Colombia). Palaeogeogr. Palaeoclimatol. Palaeoecol. 109: l-and.  84  Hoorn, C , J. Guerrero, G. A. Sarmiento, and M . A. Lorente. 1995. Andean tectonics as a cause for changing drainage patterns in Miocene northern South-America. Geology 23:237-240. Huelsenbeck, J. P., and F. Ronquist. 2001. MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics 17:754-755. Irion, G., J. ivluller, J. N . deMello, and W. J. Junk. 1995. Quaternary geology of the Amazonian lowland. Geo-Marine Letters 15:172-178. Joseph, L., T. Wilke, and D. Alpers. 2003. Independent evolution of migration on the South American landscape in a long-distance temperate-tropical migratory bird, Swainson's flycatcher (Myiarchus swainsoni). J. Biogeogr. 30:925-937. Joseph, L., T. Wilke, E. Bermingham, D. Alpers, and R. Ricklefs. 2004. Towards a phylogenetic framework for the evolution of shakes, rattles, and rolls in Myiarchus tyrant-flycatchers (Aves : Passeriformes : Tyrannidae). Mol. Phylogenet. Evol. 31:139-152. Kendall, P. G. 1949. Stochastic processes and population growth. J. R. Statis. Soc. B 11:230-264. Klicka, J., and R. M . Zink. 1997. The importance of recent ice ages in speciation: A failed paradigm. Science 277:1666-1669. Lanyon, S. M . , and K. E. Omland. 1999. A molecular phylogeny of the blackbirds (Icteridae): Five lineages revealed by cytochrome-b sequence data. Auk 116:629639. Liu, Z. H., and T. D. Herbert. 2004. High-latitude influence on the eastern equatorial Pacific climate in the early Pleistocene epoch. Nature 427:720-723. . Lovette, I. J. 2004a. Mitochondrial dating and mixed-support for the "2% rule" in birds. Auk 121:1-6. Lovette, I. J. 2004b. Molecular phylogeny and plumage signal evolution in a trans Andean and circum Amazonian avian species complex. Mol. Phylogenet. Evol. 32:512-523. Lynch M., and B. Walsh. 1998. Genetics and analysis of quantitative traits. Sinauer, Sunderland, Ma. Maddison W.P. and Maddison D.R. 2003. Mesquite: a modular system for evolutionary analysis. Version 1.0. http://mesquitepoject.org.  85  Mariaux, J., and M . J. Braun. 1996. A molecular phylogenetic survey of the nightjars and allies (Caprimulgiformes) with special emphasis on the potoos (Nyctibiidae). Mol. Phylogenet. Evol. 6:228-244. 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 : Glyphoryhchus spirurus). Mol. Phylogenet. Evol. 24:153-167. Meave, J., and M . Kellman. 1994. Maintenance of rain-forest diversity in riparian forests of tropical savannas - implications for species conservation during Pleistocene drought. J.Biogeogr. 21:121-135. Meave, J., M . Kellman, A. Macdougall, and J. Rosales. 1991. Riparian habitats as tropical forest refugia. Glob. Ecol. Biogeogr. Lett. 1:69-76. Mengel, R. M . 1964. The probably history of species formation in some northern wood warblers (Parulidae). Living Bird 3:9-43. Moore, W. S. 1995. Inferring phylogenies from mtDNA variation: mitochondrial gene trees vs. nuclear gene trees. Evolution 49:718-726. Moore, W. S., A. C. Weibel, and A. Agius. 2005. Mitochondrial DNA phylogeny of the woodpecker genus Veniliornis (Picidae, Picinae) and related genera implies convergent evolution of plumage patterns. Biol. J. Linn. Soc. In press. Moran, P. A. P. 1951. Estimation methods for evolutive processes. J. R. Statis. Soc. B 13:141-146. Moritz, C., J. L. Patton, C. J. Schneider, and T. B. Smith. 2000. Diversification of rainforest faunas: An integrated molecular approach. Annu. Rev. Ecol. Syst. 31:533-563. Nee, S. 2001. Inferring speciation rates from phylogenies. Evolution 55:661-668. —. 2004. Extinct meets extant: simple models in paleontology and molecular phylogenetics. Paleobiology 30:172-178. Nee, S., E. C. Holmes, R. M . May, and P. H. Harvey. 1994. Extinction rates can be estimated from molecular phylogenies. Philos. Trans. R. Soc. Lond. B Biol. Sci. 344:77-82. Nei, M . , and W. H. Li. 1979. Mathematical model for studying genetic variation in terms of restriction endonucleases. Proc. Natl. Acad. Sci. U.S.A 76:5269-5273. Nores, M . 1999. An alternative hypothesis for the origin of Amazonian bird diversity. J. Biogeogr. 26:475-485.  86  Nores, M . 2004. The implications of Tertiary and Quaternary sea level rise events for avian distribution patterns in the lowlands of northern South America. Glob. Ecol. Biogeogr. 13:149-161. Omland, K. E., S. M . Lanyon, and S. J. Fritz. 1999. A molecular phylogeny of the new world orioles (Icterus): The importance of dense taxon sampling. Mol. Phylogenet. Evol. 12:224-239. Pagel, M . 1994. Detecting correlated evolution on phylogenies: a general method for the comparative analysis of discrete characters. Proc. R. Soc. Lond. B Biol. Sci. 255:37-45. Paradis, E. 1997. Assessing temporal variations in diversification rates from phylogenies: estimation and hypothesis testing. Proc. R. Soc. Lond. B Biol. Sci. 264:11411147. Penny, D. 2005. Evolutionary biology - Relativity for molecular clocks. Nature 436:183184. Pereira, S. L., and A. J. Baker. 2004. Vicariant speciation of curassows (Aves, Cracidae): A hypothesis based on mitochondrial DNA phylogeny. Auk 121:682-694. Prance, G. T. 1978. Origin and evolution of Amazon flora. Interciencia 3:207-222. Price, J. J., and S. M . Lanyon. 2002. A robust phylogeny of the oropendolas: Polyphyly revealed by mitochondrial sequence data. Auk 119:335-348. Price, J. J., and S. M . Lanyon. 2004. Song and molecular data identify congruent but novel affinities of the Green Oropendola (Psarocolius viridis). Auk 121:224-229. Pybus, O. G., and P. H. Harvey. 2000b. Testing macro-evolutionary models using incomplete molecular phylogenies. Proc. R. Soc. Lond. B Biol. Sci. 267:22672272. Pybus, O. G., and P. H. Harvey. 2000a. Testing macro-evolutionary models using incomplete molecular phylogenies. Proc. R. Soc. Lond. B Biol. Sci. 267:22672272. R Development Core Team. 2005. R: A language and environment for statistical computing. http://www.R-project.org. Rambaut A. 2002. Phyl-O-Gen v l . l Available at http://evolve.zoo.ox.ac.uk/. Rand, A. L. 1948. Glaciation, an isolating factor in speciation. Evolution 2:314-321. Rasanen, M . E., A. M . Linna, J. C. R. Santos, and F. R. Negri. 1995. Late Miocene tidal deposits in the Amazonian foreland basin. Science 269:386-390.  87  Ravelo, A. C , D. H. Andreasen, M . Lyle, A. O. Lyle, and M . W. Wara. 2004. Regional climate shifts caused by gradual global cooling in the Pliocene epoch. Nature 429:263-267. Rice, N . H., A. T. Peterson, and G. Escaloria-Segura. 1999. Phylogenetic patterns in montane Troglodytes wrens. Condor 101:446-451. Richards P. W. 1952. The tropical rain forest: an ecological study. Cambridge University Press, Cambridge. Rosenzweig M . L. 1995. Species diversity in space and time. Cambridge University Press, Cambridge. Rossetti, D. D., P. M . de Toledo, and A. M . Goes. 2005. New geological framework for western Amazonia (Brazil) and implications for biogeography and evolution. Quaternary Res. 63:78-89. Roy, M . S., J. C. Torres-Mura, and F. Ffertel. 1999. Molecular phylogeny and evolutionary history of the tit-tyrants (Aves : Tyrannidae). Mol. Phylogenet. Evol. 11:67-76. Rull, V. 2005. Biotic diversification in the Guyana highlands: a proposal. J. 32:921-927.  Biogeogr.  Russello, M . A., and G. Amato. 2004. A molecular phylogeny of Amazona: implications for Neotropical parrot biogeography, taxonomy, and conservation. Mol. Phylogenet. Evol. 30:421-437. Sanders, H. L. 1969. Benthic marine diversity and stability-time hypothesis. Brookhaven Symp. Biol. 71-81. Schwabe, G. H. 1969. Towards an ecological characterization of the South American continent. Pp. 113-136 in E. J. Fittkau et al., ed. Biogeography and ecology in South America. Dr. W. Junk, Dordrecht. Sheldon, F. H., L. A. Whittingham, R. G. Moyle, B. Slikas, and D. W. Winkler. 2005. Phylogeny of swallows (Aves : Flirundinidae) estimated from nuclear and mitochondrial DNA sequences. Mol. Phylogenet. Evol. 35:254-270. Sick, H. 1967. Rios e enchentes na Amazonia como obstaculo para a avifauna. Pp. 495520 in H. Lent, ed. Atlas do simposio sobre a biota Amazonica, vol. 5 (Zoologia). Conselho Nacional de Pesquisas, Rio de Janeiro. Simpson, B. B., and J. Haffer. 1978. Speciation Patterns in Amazonian Forest Biota. Annu. Rev. Ecol. Syst. 9:497-518.  88  Steyermark, J. A., and G. C. K. Dunsterville. 1980. The lowland floral element on the summit of Cerro-Guaiquinima and other cerros of the Guayana Highland of Venezuela. J. of Biogeogr. 7:285-303. Swofford D.L. 2002. PAUP*4.0blO: phylogenetic analysis using parsimony (*and oher methods). Sunderland, Sinauer. van den Elzen, R., J. Guillen, V. Ruiz-del-Valle, L. M . Allende, E. Lowy, J. Zamora, and A. Arnaiz-Villena. 2001. Both morphological and molecular characters support speciation of South American siskins by sexual selection. Cell. Mol. Life Sci. 58:2.117-2128. van der Hammen, T., and H. Hooghiemstra. 1997. Chronostratigraphy and correlation of the Pliocene and Quaternary of Colombia. Quatern. Int. 40:81-91. van der Hammen, T., and H. Hooghiemstra. 2000. Neogene and Quaternary history of vegetation, climate, and plant diversity in Amazonia. Quaternary Sci. Rev. 19:725-742. van der Hammen, T., and M . L. Absy. 1994. Amazonia during the last glacial. Palaeogeogr. Palaeoclimatol. Palaeoecol. 109:247-261. van't Veer, R., and H. Hooghiemstra. 2000. Montane forest evolution during the last 650 000 yr in Colombia: a multivariate approach based on pollen record Funza-I 35. J. Quaternary Sci. 15:329-346. Vanzolini, P. E., and E. E. Williams. 1970. South American anoles: The geographic differentiation and evolution of the Anolis chrysolepis species group (Sauria: Iguanidae). Arq. Zool. Sao Paulo 19:1-298. Vonhof, H. B., F. P. Wesselingh, R. J. G. Kaandorp, G. R. Davies, J. E. van Hinte, J. Guerrero, M . Rasanen, L. Romero-Pittman, and A. Ranzi. 2003. Paleogeography of Miocene Western Amazonia: Isotopic composition of molluscan shells constrains the influence of marine incursions. Geol. Soc. Am. Bull. 115:983-993. Webb, S. D. 1995. Biological implications of the Middle Miocene Amazon seaway. Science 269:361-362. Weir, J. T., and D. Schluter. 2004. Ice sheets promote speciation in boreal birds. Proc. R. Soc. Lond. B Biol. Sci. 271:1881-1887. Whitlock, M . C. 2005. Combining probability from independent tests: the weighted Zmethod is superior to Fisher's approach. J. Evol. Biol. 18:1368-1373. Whitmore T. C , and G. T. Prance. 1987. Biogeography and Quaternary history in tropical America. Clarendon Press, Oxford.  89  Whittingham, L. A., B. Slikas, D. W. Winkler, and F. H. Sheldon. 2002. Phylogeny of the tree swallow genus, Tachycineta (Aves : Hirundinidae), by Bayesian analysis of mitochondrial DNA sequences 4. Mol. Phylogenet. Evol. 22:430-441. Willis, K. J., and K. J. Niklas. 2004. The role of Quaternary environmental change in plant macroevolution: the exception or the rule? Philos. Trans. R. Soc. Lond. B Biol. Sci. 359:159-172. Yule, G. U . 1924. A mathematical theory of evolution based on the conclusions of Dr. J.C. Willis, FRS. Philos. Trans. R. Soc. Lond. B Biol. Sci. 213:21-87. Zink, R. M., J. Klicka, and B. R. Barber. 2004. The tempo of avian diversification during the Quaternary. Philos. Trans. R. Soc. Lond. 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 BIRDS 4  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  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. 4  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 postlandbridge 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 postlandbridge 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; q and q , rates before and after 3.5 Ma b  a  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  Antbird 1 rate 2 rate  Qb  <7a  Qa/Qb  Log Like  LR  P  AIC  1 2  30 0.00595  0.2975  50.0  -96.36 -58.26  76.2  2.56E-18  120.52  1 2  36.5 0.00456  0.3418  75.0  -58.92 -42.93  31.98  1.56E-08  89.86  1 2  4.8307 0.0579  0.2062  4.0  -178.74 -139.72  78.04  1.01E-18  283.44  1 2  49 0.1052  0.2104  2.0  -91.12 -65.67  50.9  9.72E-13  135.34  Woodcreeper  1 rate 2 rate  Tanager  1 rate 2 rate  Blackbird  1 rate 2 rate  103  194.72  119.84  359.48  184.24  Table 5.2 Passerine families involved in the Great American Biotic Interchange. Family  C o m m o n name  Continent  Earliest  of O r i g i n  interchange  Migratory  Tropical  Colonized Caribbean  Forest Specialist  date Conophagidae I  Cotingidae  1  2  Dendrocolaptidae . "Formicariidae" i  .  .  4  yes  Cotingas  SA  no  no  • yes  Woodcreepers  SA  Antpittas  SA  Antthrushes  SA  Pipridae  Manakins  4.2  no ' °. n  no  SA "SA"  '  yes  no  yes  no  143  yes  Flycatchers  SA'  Larks  NA  yes  Cardinals  NA  Cinclidae  Dippers  NA  Corvidae  Crows  NA  Emberizidae  Sparrows  NA  Fringillidae  Finches  NA  Swallows  NA  Bjackbirds  NA  Donacobius  SA  14.5  Mimidae  Mockingbirds  NA  Motacillidae  Pipits  NA  Parulidae •  Warblers  Polioptilidae  Gnatcatchers  Thraupidae  Tanagers  Troglodytidae  Wrens  ''  Icteridae ?Megaluridae  6  Turdidae  Thrushi  Vireonidae  Vireos  •  mixed yes  3.2  |  yes  no  no  SA  ''  yes  no  Antbirds  '. y e s " '  '  .mixed  mixed- -  no  no  no  no"  yes  mixed  yes  yes  mixed  yes  yes  mixed  yes  yes  no  yes  mixed  no  no  no  7.2  . yes  yes  8.2  yes  no  NA  yes  yes  . mixed  ?NA  yes  yes  mixed  no  yes''  mixed  yes  yes  mixed  yes  mixed  yes  mixed  -10.0  >5.0  NA  13.8  ?  15  7  ?NA  Cfy«s|jj yes  j  no  no  yes 3.5  1  "  Ves  ,*  no  Thamnophillidae  ,„  • no  no  Tapaculos'  Tyrannidae  no  '  no  Rhinocryptidae  Hirundinidae  i  no  Ovenbirds  l Cardinalidae  j  no  Furnarndae'  Alaudidae  i  SA  '.  .  "Formicariidae"  '.  3  Gnateaters  -  n o  ~  |  ~~~~]  1  •  1  no  •  1  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  0  1  1  1  1  2  3  4  5  6  7  8  9 10 11 12 13 14  1  1  1  h  1  2  3  4  5  6  7  0.2 0.16 +  0  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 l 1  0  2  1  I l I I l 1  4  1  1  6  8  1  1  10  l  1  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 C I T E D  Aleixo, A, 2002. Molecular systematics and the role of the "varzea"-"terra firme" ecotone in the diversification of Xiphorhynchus woodcreepers (Aves: Dendrocolaptidae). Auk 119,621-640. Bates, J. M . , J. Haffer, and E. Grismer. 2004. Avian mitochondrial DNA sequence divergence across a headwater stream of the Rio Tapajos, a major Amazonian river. J. Ornithol. 145:199-205. Brumfield, R. T., and S. V. Edwards. 2007. Evolution into and out of the Andes: a Bayesian analysis of historical diversification in Thamnophilus antshrikes. Evolution 61, 346-367.  107  Burnham, R. J. and A. Graham 1999. The History of Neotropical vegetation: new developments and status. Annals of the Missouri Botanical Garden 86:546-589. Burns,. K. J. 1997. Molecular systematics of tanagers (Thraupinae): evolution and biogeography of a diverse radiation of Neotropical birds. Molecular Phylogenetics and Evolution 8, 334-348. Burns, K. J., S. J. Hackett, and N . K. Klein. 2003. Phylogenetic relationships of Neotropical honeycreepers and the evolution of feeding morphology. Journal of Avian Biology 34, 360-370. Burns, K. J., S. J. Hackett, and N . K. Klein. 2002. Phylogenetic relationships and morphological diversity in Darwin's finches and their relatives. Evolution 56: 1240-1252. Burns, K. J. and K. Naoki. 2004. Molecular phylogenetics and biogeography of Neotropical tanagers in the genus Tangara. Molecular Phylogenetics and Evolution 32, 838-854. Cadena C. D., A. M . Cuervo, and S. M . Lanyon. 2004. Phylogenetic relationships of the Redbellied Grackle (Icteridae: Hypopyrrhus pyrohypogaster) inferred from mitochondrial DNA sequence data. Condor. 106, 664-670. Campbell, K., C. D. Frailey, M . Heizier, L. Romero-Pittman, D.R. Prothero. 2000. Late Miocene dynamics of the Great American faunal interchange; waifs are out. Journal of Vertebrate Paleontology, 20 (3, supplement), 33 A. Capparela, A. P. 1991. Neotropical avian diversity and riverine barriers. Acta X X Congr. Int. Ornithol. 1:307-316. 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: 814828. Coates, A.G. and J.A. Obando. 1996. The Geologic evolution of the Central American Isthmus. Pp. 21-56 In Jackson, J. B.C., Budd, A. F. and Coates, A.G., Evolution and environment in Tropical America. University of Chicago Press, Chicago. 425pp. Cronquist. A. 1988. The Evolution and Classification of Flowering Plants, 2nd ed. New York Botanical Garden, Bronx. Drummond A. J. and A. Rambaut. http://beast.bio.ed.ac.uk/  2006. BEAST  vl.4, Available  from  Drummond A. J., S. Y. W. Ho, M . J. Phillips, and A. Rambaut. 2006. Relaxed phylogenetics and dating with confidence. PLoS Biology 4, e88. Ericson, P. G. P. M . Irestedt, and U. S. Johansson. 2003. Evolution, biogeography, and patterns of diversification in passerine birds. Journal of Avian Biology 34: 3-15.  108  Ericson, P. G. P., L. Christidis, A. Cooper, M . Irestedt, J. Jackson, U. S. Johansson, and J. A. Norman. 2002. A Gondwanan origin of passerine birds supported by DNA sequences of the endemic New Zealand wrens. - Proc. R. Soc. Lond. B 269: 235241. Flynn, J.J. B. J. Kowallis, C. Nunez, O. Carranza-Castaneda, W. E. Miller, C. C. Swisher HI, and E. Lindsay. 2005. Geochronology of Hemphillian-Blancan aged strata, Guanajuato, Mexico, and implications for timing of the Great American Biotic Interchange. J. Geol. 113, 287-307. Gently, A. H. 1982. Neotropical floristic diversity: Phytogeographical connections between Central and South America, Pleistocene climatic fluctuations or an accident of the Andean orogeny? Ann. Missouri Bot. Gard. 69: 557-393. Gently, A. H. 1990. Floristic similarities and differences between southern Central America and Upper and Central Amazonia. Pp. 141-157 in A. H. Gentry ed. Four Neotropical Forests. Yale Univ. Press, New Haven. Graham, A. 1976. The Miocene communities of Verazrux, Mexico. Ann. Missouri Bot. Gard. 63: 787-2342. Hackett, S. J. 1996. Molecular phylogenetics and biogeography of tanagers in the genus Ramphocelus (Aves). Mol. Phylogenet.Evol. 5:368-382. Hall, T.A., 1999. BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucl. Acids. Symp. Ser. 41, 95-98. Harmon, L. J., J. T. Weir, C. Brock, R. E. Glor, and W. Challenger. Submitted. Geiger: A Statistical Package for Investigating Evolutionary Radiation in a Comparative Context. Bioinformatics. submitted. Hayes, F. E. and J. N. Sewlal. 2004. The Amazon River as a dispersal barrier to passerine birds: effects of river width, habitat and taxonomy. Journal of Biogeography 31, 1809-1818. Huelsenbeck, J.P., and F. Ronquist. 2001. MRBAYES: phylogenetic trees. Bioinformatics 17, 754-755.  Bayesian inference of  Irestedt, M . , J. Fjeldsa, U.S. Johansson, and P.G.P. Ericson. 2002. Systematic relationsgips and biogeography of the tracheophone suboscines (Aves: Passeriformes). Molecular Phylogenetics and Evolution 23, 499-512. Irestedt, M . , J. Fjeldsa, J. A. A. Nylander, and P. G. P. Ericson. 2004a. Phylogenetic relationships of typical antbirds (Thamnophilidae) and test of incongruence based on Bayes factors. BMC Evolutionary Biology 4: 23. Irestedt, M . , J. Fjeldsa, and P. G. P. Ericson. 2004b. Phylogenetic relationships of woodcreepers (Aves: Dendrocolaptinae) - incongruence between molecular and morphological data. J. Avian Biol. 35: 280-288. Johnson, K.P., and M . D. Sorenson. 1998. Comparing molecular evolution in two mitochondrial protein coding genes (cytochrome b and ND2) in the dabbling ducks (Tribe Anatini). Mol. Phylogenet. Evol. 10, 82-94.  109  Klicka, J., K. P. Johnson, and S. M . Lanyon. 2000. New World nine-primaried oscine relationships: Constructing a mitochondrial DNA framework. Auk 117, 321-336. Lanyon S. M . and K. E. Omland. 1999. A molecular phylogeny of the blackbirds (Icteridae): five lineages revealed by cytochrome-^ sequence data. Auk. 116, 629-639. MacFadden, B. J. 2006. Extinct mammalian biodiversity of the ancient New World tropics. TRENDS in Ecology and Evolution 21, 157-165. Maddison, W. P. and D.R. Maddison. 2006. Mesquite: a modular system for evolutionary analysis. Version 1.12 http://mesquiteproject.org Marshall, L. G. 1985. Geochronology and land-mammal biochronology of the transamerican faunal interchange. Pp. 49-85 in F. G. Stehli and S. D. Webb, eds. The Great American Biotic Interchange. Plenum Press, New York. Mooers, A. LJ. and D. Schluter. 1999. Reconstructing ancestor states with maximum likelihood: support for one- and two-rate models. Systematic Biology 48: 623633. Omland, K., S. Lanyon, and S. Fritz. 1999. A Molecular Phylogeny of the New World Orioles (Icterus): The Importance of Dense Taxon Sampling. Molecular Phylogenetics and Evolution, 12, 224-239. Pagel, M . 1994. Detecting correlated evolution on phylogenies: a general method for the comparative analysis of discrete characters. Proceedings of the Royal Society (B) 255,37-45. Pagel, M . 1999. The maximum likelihood approach to reconstructing ancestral character states of discrete characters on phylogenies. Systematic Biology. 48, 612-622. Price J. J. and S. M . Lanyon. 2002. A robust phylogeny of the oropendolas: polyphyly revealed by mitochondrial sequence data. Auk. 119, 335-348. Price, J. J., and S. M . Lanyon. 2004. Patterns of song evolution and sexual selection in the oropendolas and caciques. Behavioral Ecology 15, 485-497. Schluter, D, T. D. Price, A. LJ. Mooers, and D. Ludwig. 1997. Likelihood of ancestor states in adaptive radiation. Evolution 51: 1699-1711. Simpson B.B., J.L. Neff. 1985. Plants, their pollinating bees, and the Great American Interchange. Pp 427-452 in F.G. Stehli and S.D. Webb (eds.), The great American biotic interchange. Plenum, New York. Simpson, G. G.. 1980. Splendid Isolation. The Curious History of South American Mammals. Yale University Press, New Haven Stehli, F. G. and S. D. Webb. 1985. The Great American Biotic Interchange.Phlenum Press, New Work. Voelker, G. 2002. Molecular phylogenetics and the historical biogeography of dippers (Cinclus). Ibis, 144, 577-584.  110  Vuilleurnier, F. 1984. Faunal turnover and development of fossil avifaunas in South America. Evolution 38, 1384-1396. Vuilleurnier, F. 1985. Fossil and recent avifaunas and the interamerican interchange. Pp. 387^124. in F. G. Stehli and S. D. Webb, eds. The Great American Biotic Interchange. Plenum Press, New York. Webb, S. D. 1985. Late Cenozoic mammal dispersals between the Americas. Pp. 357386. in F. G. Stehli and S. D. Webb, eds. The Great American Biotic Interchange. 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.  Ill  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 longterm 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'  and  H16065  (5'  CCATCCAACATCTCMGCATGATGAAA)  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,  AY138927-AY138929,  AY138933,  AY138920, AY138934.  AY138922-AY138924,  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,  AF287560;  AF287548,  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 AY117700AY117704;  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, AF472377AF472381; 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)  a) Boreal superspecies Sphyrapicus varius versus S. nuchalis / S.2.40% (± 0.11%) ruber 0.71 % (± 0.00%) Sphyrapicus nuchalis versus S. ruber 0.87% (± 0.14%) Empidonax occidentalis versus E. difficilis Vireo plumbeus versus V. solitarius / V. 3.23% (± 0.31%) cassinii 2.96% (± 0.17%) Vireo solitarius versus V. cassinii Poecile hudsonica versus P. rufescens 3.60% (± 0.05%) 1.12% (± 0.22%) Catharus minimus versus C. bicknelli 2.14% (± 0.53%) Vermivora (r.) ruficapilla versus V. virginiae / V. (r.) ridgwayi Vermivora virginiae versus V. (ruficapilla)2.01% (±0.19%) ridgwayi Dendroica virens versus D. townsendi / D.2.37% (± 0.16%) occidentalis Dendroica townsendi versus D. 0.95% (± 0.12%) occidentalis Oporornis Philadelphia versus O. tolmiei 2.49% (± 0.07%) Passerella (i.) iliaca versus P. (i.) 1.69% (± 0.22%) schistacea, P. (i.) megarhyncha and P. (i.) unalaschensis Passerella (i.) schistacea versus P. (i.) 1.57% (± 0.21%) megarhyncha and P. (i.) unalaschensis Passerella (i.) megarhyncha versus P. (i.) 1.59% (± 0.22%) unalaschensis b) Sub-boreal superspecies 0.50% Tympanuchus pallidicinctus versus T. cupido Callipepla californica versus C. gambelii 2.46% (± 0.17%) 9.37% (± 2.12%) Megascops asio versus M. kennicottii 1.05% (± 0.13%) Picoides nuttailii versus P. scalaris 1.97% (± 0.14%) Contopus sordidulus versus V. virens 5.68% . Aphelocoma californica versus A. coerulescens 6.66% Vireo gilvus versus V. leucophrys Toxostoma cinereum versus T. bendirei 1.46% 6.59% (± 0.50%) Toxostoma curvirostre versus T. ocellatum 4.68% (± 0.00%) Parula americana versus P. pitiayumi Piranga ludoviciana versus P. bidentata 5.38% (± 0.33%) 1.20% Pipilo maculatus versus P. erythrophthalmus 3.06% (± 0.00%) Quiscalus major versus Q. mexicanus 0.81% Icterus galbula versus /. abeillei  120  Coalescence Date  Data  1,090,000  711bpCytB  320,000 390,000 1,470,000  711 bp C y t B 1006 bp Cyt B 1143 bp C y t B  1,350,000 1,640,000 510,000 970,000  1143 bp C y t B 1001 bp C y t B 1066 bp Cyt B 961 bp C y t B  910,000  961 bp C y t B  1,080,000  1143 bp Cyt B  430,000  1143 bp C y t B  1,130,000 770,000  720,000 720,000  250,000  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  609 bp Cyt B  1,230,000 4,690,000 530,000 990,000 2,840,000  699 bp Cyt B 395 bp Cyt B 1028 bp Cyt B 1143 bp C y t B 1143 bp C y t B  3,330,000 730,000 3,300,000 2,340,000 2,690,000 600,000  1143 bp C y t B 433 bp Cyt B 433 bp Cyt B 1143 bp C y t B 1073 bp Cyt B 433 bp Cyt B  1,530,000 410,000  881 bp C y t B 876 bp Cyt B  Icterus spurius versus /. fuertesi Sturnella neglecta versus S. magna  100,000 2,410,000  925 bp Cyt B 893 bp Cyt B  0.63%) 0.17%) 0.62%)  2,570,000 1,580,000 1,000,000 865,000 2,670,000 2,820,000  1045 bp C y t B 1039 bp Cyt B 925 bp Cyt B 393 bp Cyt B 1003 bp Cyt B 964 bp Cyt B  038%)  2,020,000  964 bp Cyt B  0.68%)  2,910,000  965 bp Cyt B  0.83%)  3,630,000  1006 bp Cyt B  0.06%)  2,200,000  1022 bp C y t B  0.57%)  2,370,000  968 bp Cyt B  1.26%)  0.13%) 0.49%) 0.26%)  1,030,000 3,490,000 2,060,000 990,000 2,180,000 2,850,000  209 bp C y t B 936 bp Cyt B 913 bp C y t B 921 bp C y t B 1045 bp Cyt B 1045 bp Cyt B  0.08%)  840,000  1045 bp Cyt B  0.00%)  290,000  879 bp Cyt B  0.60%)  2,360,000  890 bp Cyt B  0.13%) 0.16%)  980,000 2,430,000 880,000  890 bp Cyt B 906 bp Cyt B 920 bp Cyt B  0.04%)  440,000  920 bp Cyt B  0.19% (± 0.10%)* 4.82% (± 0.00%)  c) Lowland Tropical superspecies Zenaida asiatica versus Z. meloda 5.14% (± Columbina squammata versus C. inca 3.16% (± Selenidera maculirostris versus 5. gouldii2.00% Megascops usta versus M. watsonii 1.73% (± Xiphorhynchus spixii versus X. elegans 5.34% (± Xiphorhynchus chunchotambo versus X. 5.63% (± pardalotus /X. ocellatus Xiphorhynchus pardalotus versus X. 4.03% (± ocellatus Xiphorhynchus erythropygius versus X. 5.81% (± triangularis Xiphorhynchus guttatoides versus X. 7.25% (± guttatus / susurrans Xiphorhynchus guttatus versus X. 4.39% (± susurrans 4.74% (± Xiphorhynchus lachrymosus versus X. flavigaster Cranioleuca pyrrhophia versus C. obsoleta 2.06% (± Tachycineta albiventer versus T. albilinea6.97% Tachycineta meyeni versus T. leucorrhoa4.12% Petrochelidon fulva versus P. rufocolaris 1.97% (± Ramphocelus carbo versus R. bresilius 4.35% (± Ramphocelusflammigerusversus R. 5.69% (± passerinii /R. costaricensis Ramphocelus passerinii versus R. 1.67% (± costaricensis Agelaius cyanopus versus A. 0.57% (± xanthophthalmus 4.72% (± Icterus icterus versus I. jamacaii /1. croconotus Icterus jamacaii versus /. croconotus 1.96% Cacicus cela versus C. vitellinus 4.86% (± Psarocolius montezuma versus P. 1.76% (± bifasciatus / P. yuracares Psarocolius bifasciatus versus P. 0.87% (± yuracares  121  0.05%) 0.22%)  APPENDIX 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 Anairetes  Amazon  Gene 632 bp CytB andND2  562 bp COI  Ingroup species and Genbank Accession Numbers CvtB: 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 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:  Outgroup species and Genbank Accession Numbers CvtB: Cnemotriccus fuscatus: AF447622, Empidonax wrightii: AY143208, Stigmatura napensis: AF067000 ND2: Cnemotriccus fuscatus: AF447649, Empidonax wrightii: AY143235, Stigmatura napensis: AF066999  "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  Carduelis  926 bp CytB  Cinclodes  684 bp  Cranioleuca  Crax  con  508 bp CytB ND2  1003 bp CytB  Hemispingus 301 bp ND2  AY301461, vinacea: AY301462, viridigenalis: AY301463, vittata: AY301464 atrata: L76385, barbata: L77868, crassirostris: L77869, cucullata: L76299, magellanica: AF310066, U79016 notata: U79019, olivacea: L77871, spinescens: U79017, xanthogastra: L76389, yarrellii: U83200 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 CytB: 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, 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  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  cannabina: L76298, carduelis: L76388, lawrencei: L76392, pinus: U79020, psaltria: L76390, U78324, spinus: L76391, tristis: U79022 Synallaxis spixi: AY613370, Upucerthia dumeteria: AY613371, Upucerthia validirostis: AY613372  CvtB:Asthenes dorbignvi: AF053803, Hellmavrea gularis: AF053802, Synallaxis albescens: AF118186 ND2: Asthenes dorbignyi: AF053820, Hellmayrea gularis: AF053819, Synallaxis albescens: AF118220  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 Basileuterus luteoviridis: AY039289, Cissopis leveriana: AY383169, Chlorochrysa calliparaea: AY383168  Metallura  856 bp CytB, ND2 and ND5  CytB: 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  Muscisaxicol 1038 bp a ND3 and  con  Ochthoeca  321 bp ND2  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 ND3: 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 Garcia-Moreno unpublished sequences (only the lowland Ochthoeca sqlvini excluded)  CytB: Chalcostigma herrani: AF022674, Chalcostigma ruficeps: AF022673 ND2: Chalcostigma herrani: AF022691, Chalcostigma ruficeps: AF022690 ND5: Chalcostigma herrani: AF022709, Chalcostigma ruficeps: AF022673  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  Aphanotriccus audax: AF447648, AF447647, Cnemotriccus fuscatus: AF447649, Empidonax minimus: AY030125, Mitrephanes phaeocercus: AF447646,  Troglodytes 513 bp ND2  Icterus  Dendrocincl a  1946 bp Cytb andND2  999 bp CytB  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 CytB: 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 [Genbank numbers will be placed here.]  Stigmatura napensis: AF066999 Cistothorus platensis: AY465889, Troglodytes troglodytes: AF104976, AY460313  CytB: 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  /Genbank numbers will be placed here.]  Pionopsitta  Psarocolius  1306 bp CytB, COI  898 bp CytB  Pteroglossus 2168 bp CytB, COI, ATPase 6 and 8  CvtB: 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 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 CytB: 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:  CvtB: Pionus chalcopterus: AY661240 COI: Pionus chalcopterus: AY661232  Amblycercus holosericeus: AY117723, AY117724, Icterus gularis: AF099293, Icterus jamacaii: AF099297, Molothrus aeneus: AF089040  CytB: 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  Nyctibius  656 Cyt B  Ramphocelu 1046 bp CytB s South American Blackbird clade  906 bp CytB  AY266182, yucatanensis: AY266181 aethereus: X95781, bracteatus: X95765, grandis: X95766, griseus: X95767, leucopterus: X95768, maculosus: X95769 bresilius: U15724, carbo: U15723, AF310048, icteronotus: U15719, nigrogularis: U15721, passerinii: U15717, U15722, U15720, sanguinolentus: U15718 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  Tachycineta 908 bp CytB  albilinea: AY052445, albiventer: AY052446, bicolor: AF074585, cyaneovirids: AY052450, euchrysea: AY052451, leucorrhoa: AY052447, meyeni: AY052448, stolzmanni: AY052444, thalassina: AY052449  Trogon  collaris: U94808, comptus: U94804, curucui: U94801, elegans: U94806, melanocephalus: AY275863, melanurus: U94805, mexicanus: U94809, personatus: U89201, rufus: U94807, violaceus: U94802, viridis: U94803. 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,  1143 bp CytB  Xiphorhynch 1096 bp us CytB  Aegotheles cristatus: X95775, Chordeiles rupestris: X95778, Eurostopodus papuensis: X95780, Phalaenoptilus nuttallii: X95770, Steatornis caripensis: X95773 Eucometis penicillata: AY228059, Plectrophenax nivalis: AY156449,Tangara seledon: AY228083 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 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 Euptilotis neoxenus: U89203, Harpactes oreskios: U89199, Pharomachrus pavoninus: U94800, Priotelus temnurus: U89202 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  Geositta  854 bp Cytb, ND2, ND3  CytB: 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  Neotropical Swallow clade  1950 bp CytB and ND2  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 CytB: 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:  AY442994, Lepidocolaptes albolineatus: AF045745, Lepidocolaptes angustirostris: AY078175, AY089811, Lepidocolaptes souleyetii: AF045743, Lepidocolaptes squamatus: AF045747, Lepidocolaptes wagleri: AF045748, Sittasomus griseicapillus: AY065714 CytB: Aphrastura spinacauda: AY695024, Upucerthia ruficauda: AY695025 ND2: Aphrastura spinacauda: AY695004, Upucerthia ruficauda: AY695005 ND3: Aphrastura spinacauda: AY695004, Upucerthia ruficauda: AY695005  CytB: Riparia paludicola: AY825957, Riparia riparia: AF074578 ND2: 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 CvtB: 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 CytB, COI  CytB: 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  CytB: 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, b l 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  0  1  2  1  4  1  6  1  8  —  i  0  1  2  i  4  i  6  i  8  simulation time (millions of years)  132  —  i  i  0  i  2  i  4  6  i  8  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  callophrys velia chilensis inornata mexicana seledon fastuosa desmaresti cyanocephala lavinia gyrola gyrola gyrola chrysotis xanthocephala parzudakii schrankii johannae icterocepha florida arthus cyanotis labradorides vassorii  Amazon barbadensis ochrocephalus versicolor  nigroviridis fucosa dowii ruficervix heinei argyrofenges viridicollis cyanoptera vitriolina cucullata cayana meyerdeschaue palmeri cyanicollis cyanicollis larvata nigrocincta varia rufigula xanthogastra guttata punctata punctata  ariimiaca kawalli autumnalis rhodocorytha dufresniana farinosa imperialis brasiliensis gui/dingii amazonica viridigenalis finschi  agtiii albifrons collaria vittata ventralis leucocephala vinacea festiva tucumana pretrei  -11.0 million years •4 2.5 million years  134  Trogon  i  . bairdii • melanocephalus • violaceus • curucui • comptus • melanurus • massena • rufus • personatus • collaris • mexicanus • elegans  Trogon collaris occurs both widely in lowlands and highlands  Nyctibius maculosus leucopterus griseus grandis bracteatus aethereus  Xiphorhynchus  Blackbird clade  Pseudoleistes guirahuro  • guttatoides i susurrans  Pseudoleistes virescens  . guttatu  Agelaius flavus  ' flavigaster  Agelaius icterocephalus  • lachrymosus  Agelaius ruficapillus  1  Molothrus badius  , triangularis  Oreopsar bolivianus  , obsoletus  Agelaius thilius  • kienerii  Agelaius cyanopus  . picus  Agelaius xanthophthalmus\  • fuscus  Ambtyramphus holoseri  ' elegans  Curaeus curaeus  , spixii  Gnorimopsar chopi  • chunchotambo  Ijampropsar tanagrinus  , ocellatus  Gymnomystax mexicanus  . pardalotus  erythropygius  Macroagelaius imthumi  -11.0 million years HI 2.5 million years  135  Psarocolius and relatives  Psarocolius viridis Psarocolius bifasciatus Gymnoslinops momezuma Psarocolius decumamts  (f.) ridgwayi  Psarocolius wagleri  anabalina  Psarocolius atrovirens  fuliginosa  Psarocolius angustifrons  lurdina  Cacicus solitarius  (f.) taunayi  Cacicus sclateri Ocyalus latirostris  homochroa  Psarocolius oseryi  merula  Cacicus haemorrhous  tvrianna  Cacicus leucoramphus Cacicus chrysonotus Cacicus cela Cacicus (u.) microrhynchus Cacicus uropygialis Cacicus (u.) pacificus Cacicus melanicterus  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  Crax and relatives  fasciolata alector globulosa blumenbachii rubra alberti daubemoni Nothocrax urumutum salvini Pauxi unicornis tuberosa tomentosa mitu Pauxi pauxi  Ramphocelus  carbo  chrysater  i bresilius  graduacauda parisorum pustulaius  i nigrogularis i icteronotus , passerinii  buliockii galbula abeillei leucopte.ryx auratus  • sanguinolentus Taxonomic note: costancensis has been recognized a s a species but but is not considered s o here  nigrogularis  11.0 million years  gularis  12.5 million years  136  Veniliornis  Pteroglossus bitorquatus  affinis  beauharnaesii  nigriceps callonotus dignus frontalis passerinus cassini kirkii spilogaster Picoides lignarius Picoides mixtus chocoensis  flavirostris aracari pluricinctus  45  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  Pionopsitta • pileata • pulchra • haematotis • coccinicolaris • barrabandi • aurantigena • caica • vulturina  Neotropical Swallow clade  ^—Progne elegans Progne chalybea (South)  HI  ^—Progne subis ^—Progne murphyi Progne dominicensis *-i: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 semirufus tuberculifer  barbirostris swainsoni 1 cephalotes phaeocephalus panamensis ferox venezuelensis SM-ainsoni 2  Craniolueca albiceps marcapata vulpina albicapilla pyrrhophia henricae obsoleta erythrops demissa antisiensis carta ta baroni  validus stolidus sagrue oberi  antitlarum crinitus yucatanensis tyrannulus  Tachycineta ' albiventer i albilinea i stolzmanni  Anairetes  i meyeni  nigrocristatus reguloides agilis flavirostris alpinus parulus fernandezianus  < leucorrhoa i bicolor  t  ' 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 Troglodytes  yarellii magellanica 2 crassirostris spinescens cucullata atraia olivacea magellanica 1 barbata xanthogastra notata  musculus aedon 1 sissonii aedon 2 brunneicollis rufociliatus solstitialis rufulus ochraceus Thrvorchilus browni  ft  Ochthoeca  pulchella  Metallura  jelskii  odomae (williami) primolina baroni (williami) atrigularis phoebe theresiae eupogon aeneocauda tyrianthina  Muscisaxicola  •  diadema spodionota frontalis cinnamomeiveniris thoracica leucophrys oenanlhoides rufipectoralis fumicolor  juninensis rufivertex cinera (a.lpina) grisea albifrons E flavinucha alpina macloviana albilora frontalis capistrata maculirostris  Cinclodes  nigrofumosus taczanowski palagonicus palliatus atacamensis excelsior aricomae antarcticus fuscus comechingonus oustaleti olrogi pabsti  Amazonian fluviatilis (not shown) is basal to rest of genus  Hemispingus  melanotis frontalis piurae u f o s u p e r c i l i a r u s trifasciatus superciliaris A verticalis xanthophthalmus atropileus — — ^ — ^ — c a l o p h r y s ——^—^———————"~-auricularis _A • — r  •i  ^  T  I  139  I—11.0 million years __  | 2.5 million years  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  a) Lowland Pipridae  Lepidothrix coronata  Sequence Divergenc e  Pipridae  Source  Cheviron et al. 2005  0.0055  . 0.28  CytB, 307 bp  9  0.0054  0.27  CytB, 307 bp  13  0.0097  0.48  CytB, 307 bp  8  0.0052  0.26  CytB, 307 bp  11  0.0106  0.53  CytB, 307 bp  11  0.0150  0.75  CytB, 307 bp  21  0.0053  0.26  CytB, 1005  13  0.0030  0.15  CytB, 1005  21  0.0094  0.47  18  0.0027  0.13  Xiphorhynchus elegans insignis  6  0.0023  0.11  Aragtinga solstitialis •  4  0.0020  0.10  5 7 4 14  0.0000 0.0095 0.0012 0.0062  0.00 0.47 0.06 0.31  4  0.0019  0.10  CytB, 340bp CytB, 340bp CytB, 340bp ATPase 6and8, 842 bp COI 622 bp  14  0.0138  ' 0.69  CytB, 379 bp  spirirus  7  0.0148  0.74  CytB, 379 bp  spirirus  9  0.0120  0.60  CytB, 379bp  spirirus  11  0.0096  0.48  CytB, 379 bp  0.0069  0.35  Lepidothrix coronata  North  Amazon Pipridae  Gene  5  Maranon Pipridae  Age  Lepidothrix coronata  Central Peru Lepidothrix coronata  Bolivia / Southern Peru Pipridae  Lepidothrix coronata  Venezuela Pipridae  Lepidothrix coronata  Dendrocolaptidae  Andean Xiphorhynchus spixii  Dendrocolaptidae Dendrocolaptidae Dendrocolaptidae Dendrocolaptidae Psittacidae Psittacidae Psittacidae Psittacidae Troglodytidae Ramphastidae  Dendrocolaptidae  Trans-  Xiphorhynchus elegans orntus Xiphorhynchus elegans elegans  Xiphorhynchus elegans juruanus  Aragtingajandaya Aragtinga  auricapilla  Aragtinga weddellii Thryothorus nigricapillus Pteroglossus viridis  Glyphoiynchus  spirirus  bp  CytB, 1005 bp  CytB, 1005 bp CytB, 1005 bp CytB, 340bp  Central America, Choco, Imeri Dendrocolaptidae  Glyphoiynchus  Para, SE. Brazil Dendrocolaptidae  Glyphoiynchus  Guyana Dendrocolaptidae  Glyphoiynchus  Aleixo 2004  hn Dp  Peruvian Inambari Mean b) Highland  140  Ribas and Miyaki 2004  Gonzales et al. 2003 Eberhard and Bermingha m2005 Marks et al. 2002  Emberizidae Emberizidae Emberizidae Emberizidae Emberizidae Emberizidae Emberizidae Emberizidae Emberizidae Emberizidae Emberizidae  Chlorospingus (flavigularis) hypophaeus  0.0024  Chlorospingus (flavigularis) flavigularis  0.0092  Chlorospingus pileatus  0.0041  Chlorospingus ophthalmicus phaeocephalus Chlorospingus ophthalmicus novicius  0.0025  Chlorospingus ophthalmicus regionalis  0.0088  Chlorospingus ophthalmicus honduratius  0.0029  Chlorospingus ophthalmicus dwighti  0.0046  Chlorospingus ophthalmicus ophthalmicus  0.0062  Chlorospingus ophthalmicus wetmorei  0.0014  Chlorospingus ophthalmicus albifrons  0.0012  0.0010  Mean  0.0040  0.12 0.46 0.21 0.13 0.05 0.44 0.15 0.23 0.31 0.07 0.06 0.20  ATPase 6and8, bp ATPase 6and8, bp ATPase 6and8, bp ATPase 6and8, bp ATPase 6and8, bp ATPase 6and8, bp ATPase 6and8, bp ATPase 6and8, bp ATPase 6and8, bp ATPase 6and8, bp ATPase 6and8, bp  842  Weir unpublished  842 842 842 842 842 842 842 842 842 842  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  Family  Genus  species  Dendrocolaptidae  Campylorhamphus  falcularius  Dendrocolaptidae  Campylorhamphus  procurvoides  Dendrocolaptidae  Campylorhamphus  pusillus  Dendrocolaptidae  Campylorhamphus  Dendrocolaptidae  Campylorhamphus  Dendrocolaptidae  Campylorhamphus  Museum  Tissue Number  Locality  LFS 99/378  Genbank number AY089810  MZUSP  AY089795  Amazonas; Venezuela  Bahia; Brazil  FMNH  DEW 2685  ?borealis  STRI  JTW094  pusillus  olivaceus  LSUMZ  B1411  Panama; Bocas del Toro; Chiriqui to Chiriqui Grande Road at continental divide Panama; Darien; Cerro Pirre; 9 km NW Cana  pusillus  pusillus  LSUMZ  B11879  Ecuador; Esmeraldes; EI Placer  pusillus  pusillus  LSUMZ  B33822  LSUMZ  153671  Peru; Cajamarca; Cordillera del Condor; Picorana AY089822  Santa Cruz; Bolivia  Campylorhamphus  trochilirostris  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  Dendrocolaptidae  Dendrexetastes  rufigula  MHNJP  SWC 2358  Venezuela; Amazonas Territory; Cerro de la Neblina base camp Peru; Loreto  Dendrocolaptidae  Dendrocincla  anabatina  KU536  Mexico  Dendrocolaptidae  Dendrocincla  fuliginosa  fuliginosa  Kansas University 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; A N A M Station  Dendrocolaptidae  Dendrocincla  merula  olivascens  FMNH  FM389810  Brazil; Rondonia  Dendrocolaptidae  Dendrocincla  turdina  KU 3698  Paraguay  Dendrocolaptidae  Dendrocincla  tyrannina  tyrannina  Kansas University FMNH  FM429946  Dendrocolaptidae  Dendrocolaptes  certhia  MHNJP  DLD 133  Dendrocolaptidae  Dendrocolaptes  picumnus  LSU  B35728  Dendrocolaptidae  Dendrocolaptes  platyrostris  FMNH  NRM 976714  Dendrocolaptidae  Dendrocolaptes  sanctithomae  STRI  JTW251  NRM  NRM 966930  Dendrocolaptidae  -1^ -1^  subspecies  Dendrocolaptidae  Drymornis  bridgesii  sanctithomae  AY089829  Peru; Cuzco AY089817  Loreto; Peru  AY442990  Brazil; Amazonas; Sao Fransico Rio Solimoes; 13.3 Km NE Sau Paulo South America Panama; Bocas del Toro; Valle de Risco  AY065711  South America  Brazil; Bahia  Dendrocolaptidae  Glyphorynchus •  spirurus  MPEG  JDW445  AY089806  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 Brazil  Dendrocolaptidae  Glyphorynchus  spirurus  FMNH  CH-285  , AY096950  Dendrocolaptidae  Hylexetastes  perrotii  LSUMZ  150674  AY089809  Dendrocolaptidae  Ledipocolpates  lacrymiger  UWBM  RCF2209  Dendrocolaptidae  Lepidocqla  souleyetii  STRI  VE-LSOI  Dendrocolaptidae  Lepidocolaptes  affinis  UWBM  UWBM70115  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  Dendrocolaptidae  Lepidocolaptes  souleyetii  compressus  UWBM  UWBM70010  Dendrocolaptidae  Nasica  longirostris  LSUMZ  115014  Dendrocolaptidae  Sittasomus  griseicapillus  reiseri  FMNH  FM392419  Dendrocolaptidae  Sittasomus  griseicapillus  sylvioides  FMNH  FM343231  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  Dendrocolaptidae  Xiphocolaptes  promeropirhynchus sclateri  FMNH  FM394013 '  Dendrocolaptidae  Xiphorhynchus  erythropygius  ANSP  FHS 85  Dendrocolaptidae  Xiphorhynchus  erythropygius  punctigula  STRI  JTW105  Dendrocolaptidae  Xiphorhynchus  erythropygius  insolitus  STRI  JTW669  Dendrocolaptidae  Xiphorhynchus  flavigaster  FMNH  DSW 2986  AY089799  Belize; Toledo district  Dendrocolaptidae  Xiphorhynchus  fitscus  MPEG  AA568  AY089819  Brazil; Bahia  Dendrocolaptidae  Xiphorhynchus  guttatus  MPEG  MR-003  AY089794  Brazil; Para  Dendrocolaptidae  Xiphorhynchus  guttatus  MPEG  Ch202  AY089814  Brazil; Amapa  affinis  eytoni  Bolivia; Santa Cruz Bolivia; Santa Cruz; Provincia de Vallegrande; 29 K M SE Vallegrande Venezuela; Guaraunos Nicaragua; Matagalpa; 10 km N  Mexico Nicaragua; La Luz Rio Uli near Wani AY089797  Peru; Loreto Brazil; Pemambuco Mexico; Veracruz  Nicaragua; Matagalpa; 10 km N Mexico; Hidalgo AY089832  Ecuador; Pichincha Panama; Bocas del Toro; Chiriqui to Chiriqui Grande Road at continental divide Panama; Darien; Puerto Pina  Dendrocolaptidae  Xiphorhynchus  guttatus  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  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  LSUMZ  119520  AY089820  Loreto; Peru  Dendrocolaptidae  Xiphorhynchus  pardalotus  MPEG  AA602  AY089831  Para; Brazil  Dendrocolaptidae  Xiphorhynchus  picus  AY089790  Island of Trinidad  AY089802  Venezuela  dorbignyanus  weddellii  altirostris  Panama; Bocas del Toro; Cerro Chalite  Dendrocolaptidae  Xiphorhynchus  picus  Dendrocolaptidae  Xiphorhynchus  picus  extimus  STRI  JTW543  Dendrocolaptidae  Xiphorhynchus  spixii  spixii  MPEG  MR-002  AY089801  Para; Brazil  Dendrocolaptidae  Xiphorhynchus  elegans  elegans  MPEG  AA290  AY089805  Rondonia; Brazil Loreto; Peru  Panama; Cocle; Aguadulce  elegans  ornatus  LSUMZ  109706  AY089812  Xiphorhynchus  elegans  juruanus  MPEG  AA 236  AY089824  Rondonia; Brazil  Xiphorhynchus  susurrans  LSUMZ  163545  AY089800  Panama; Panama  Xiphorhynchus  susurrans  STRI  CR-XSU2753 162637  AY089826  La Paz; Boliva  Z M C U S45  Dendrocolaptidae  Xiphorhynchus  Dendrocolaptidae Dendrocolaptidae Dendrocolaptidae  costaricensis  Costa Rica; Dominical Baru  Dendrocolaptidae  Xiphorhynchus  triangularis  LSUMZ  Dendrocolaptidae  Xiphorhynchus  triangularis  FMNH  AY442999  South America  Icteridae  Agelaius  cyanopus  AF290174  South America  Icteridae  Agelaius  flavus  AF089066  South America  humeralis  AF089006  Cuba or Hispaniol  Icteridae  Agelaius  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  LSUMNH 98900  AF472386  South America  LSUMZ  FMNH  AY117721  Venezuela  AY117712  Panama  B103278  AY117718  Bolivia  USNM 620761  AY117704  Argentina  USNM 621068  AY117701  Guyana  AY117707  South America  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  warszewiczi  AF089021  Mexico; Chiapas; Estacion Juarez, 15 km NE; near San Vicenteriver,Rancho Aldebaran South America  Dolichonyx  oryzivorus  AF447367  North America  Euphagus  carolinus  AF089023  North America  Icteridae  Euphagus  cyanocephalus  AF089024  North America  Icteridae  Gnorimopsar  chopi  AF089025  South America  Icteridae  Gymnomystax  mexicanus  AF089026  South America  Icteridae  Icterus  auratus  U A M 7222-  AF099276  Mex. Yucatan, El Coyo  Icteridae  Icterus  auricapillus  ANSP 173534  AF099310 .  Columbia, Meta  Icteridae  Icterus  bonana  STRI MA-IB02  AF099277  Martinique, Fond Baron  Icteridae  Icterus  bullockii  FMNH 341938  A Y611476  USA, CA, Monterey Co.  Icteridae  Icterus  cayanensis  pyrrhopterus  FMNH 334608  AF099280  Bolivia, Santa Cruz, Chiquitos  Icteridae  Icterus  chrysater  chrysater  UWBM  AF099281  Nicaragua, Casitta  Icteridae  Icterus  chrysater  hondae  STRI  UWBM DAB1573 PA-ICHPP4  AF099282  Panama, Farfan-Antenna  Icteridae  Icterus  cucullatus  nelsoni  FMNH  AF099284  USA, CA, Riverside Co.  Icteridae  Icterus  dominicensis  dominicensis  FMNH ATP88081 LSUMZ 9897  AF099285  Haiti  Icteridae  Icterus  dominicensis  melanopsis  MHNC 4/8/92  AF099286  Cuba  Icteridae  Icterus  dominicensis  portoricensis  STRIPR-IDOl  AF099288  Puerto Rico, Maricao  Icteridae  Icterus  galbula  AY607658  North America  Icteridae  Cacicus  cela  cela  Icteridae  Cacicus  cela  vitellinus  Icteridae  Cacicus  chrysonotus  chrysonotus  Icteridae  Cacicus  chrysopterus  Icteridae  Cacicus  haemorrhous  Icteridae  Cacicus  leucoramphus  Icteridae  Cacicus  melanicterus  FMNH  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  Icteridae Icteridae  USNM haemorrhous  . bullockii  FMNH  339733  Icteridae  Icterus  graceannae  Icteridae  Icterus  graduacauda  audubonii  Icteridae  Icterus  gularis  tamaulipensis  LSUMZ  LSUMZ  ANSP 181810  AF310064  Ecuador, Loja, Celica  LSUMZ 4023  AF099291  USA, TX, Atascosa Co.  MZFC KEO-003  AF099294  Mex. Veracruz, Tlacotalpan  LSUMZ 11328  AF099296  Puerto Rico, Cabo Rojo  FMNH 324092  AF089031  Peru, Madre de Dios  LSUMZ 6700  AF099297  Bolivia, Santa Cruz  icterus  ridgewayi  Icterus  icterus  croconotus  Icterus  jamacaii  stricifrons  Icterus  laudabilis  STRI SL-ELA4  AF099298  St. Lucia, Anse la Sorciere  FMNH 331144/  AF089032  Jamaica, Cornwall  Icteridae  Icterus  Icteridae Icteridae Icteridae  LSUMZ  leucopteryx  Icteridae  Icterus  leucopteryx  Icteridae  Icterus  maculialatus  Icteridae  Icterus  mesomelas  mesomelas  UWBM 52153  AF089033  Icteridae  Icterus  nigrogularis  nigrogularis  FMNH 339739  AF099302  Venezuela, Falcon, Boca de Aroa  STRI MO-IOB4  AF099303  Monserrat, Soufriere  FMNH 341943  AF089035  USA, CA, San Bernardino Co.  BMNH 42544  AF099304  USA, FL, Dade Co.  BMNH 42543  AY211212  Mex. Campeche, Xpujil  INIREB SRF-387 AF099299  Icteridae  Icterus  oberi  Icteridae  Icterus  parisorum  Icteridae  Icterus  pectoralis  (¥\oniz)  Icteridae  Icterus  prosthemelas  prosthemelas sclateri  UWBM  BMNH  Mex. Chiapas, Tuxtla Gut. Mex. Chiapas, Estacion Juarez  Nicaragua, La Flor  Icteridae  Icterus  pustulatus  Icteridae  Icterus  spurius  spurius  NCSM  UWBM DABAF099306 1670 NCSM DLD-2538 AY211211  Icteridae  Icterus  spurius  fuertesi  BMNH  BMNH 42538  AY211215  Mex. Veracruz, Tlacotalpan  MZFC  MZFC QRO-216  AF099308  Mex. Queretaro  AF089037  South America  FMNH  334657  AF089038  Bolivia: Santa Cruz  wagleri  wagleri  USA, CO, Weld Co.  Icteridae  Icterus  Icteridae  Lampropsar  tanagrinus  Icteridae  Leistes  militaris  Icteridae  Macroagelaius  imthurni  AF089039  South America  Icteridae  Molothrus  aeneus  AF089040  North America  Icteridae  Molothrus  ater  AF089041  North America  Icteridae  Molothrus  badius  AF089042  South America  Icteridae  Molothrus  bonariensis  AF089043  Puerto Rico  Icteridae  Molothrus  rufoaxillaris  AF089044  South America  Icteridae  Nesopsar  nigerrimus  AF089045  South America  Icteridae  Ocyalus  latirostris  AF472383  Peru, Loreto  AF089046  South America  Icteridae  Oreopsar  boliviartus  Icteridae  Psarocolius  angustifrons  Icteridae  Psarocolius  angustifrons  FMNH  angustifrons  177928  LSUMZ  B-7776  AY117719  Ecuador  FMNH  120397  AF472376  Peru, Loreto  Icteridae  Psarocolius  atrovirens  FMNH  324106  AF472373  Icteridae  Psarocolius  bifasciatus  yuracares  FMNH  153616  AF472375  Peru, Cuzco 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  FMNH  120394  AF472368  Peru, Loreto  Icteridae  Psarocolius  oseryi  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  AF089051  South America  Icteridae  Pseudoleistes  giiirahuro  Icteridae  Pseudoleistes  virescens  Icteridae  Quiscalus  lugubris  lugubris  STRI  GU-QLU1  Icteridae  Quiscalus  lugubris  lugubris  STRI  BA-QLU1  AF089052  South America Guadeloupe; Duquerry Barbados; Barclay's Park  AF089055  USA, Louisiana  Icteridae  Quiscalus  major  Icteridae  Quiscalus  mexicanus  Icteridae  Quiscalus  mexicanus  Icteridae  Quiscalus  nicaraguensis  nicaraguensis  STRI  NI-QNG996  Icteridae  Quiscalus  niger  niger  STRI  PR-QNI11450  Icteridae  Quiscalus  niger  Icteridae  Quiscalus  niger  niger  STRI  JA-QNI1  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  Icteridae  Sturnella  neglecta  AF089064  North America  Icteridae  Xanthocephalus  xanthocephalus  AF089067  North America  AY676937  Paraguay; Dpto. Alto Paraguay; Est. Dona Julia  Thamnophilidae  Batara  cinerea  Thamnophilidae  Cercomacra  laeta  Thamnophilidae  Cercomacra  melanaria  STRI  Panama; Panama City  PA-QME-PP15 AF089056  AF089057  paralios  sabinoi  FMNH  NRM 947099  FMNH  FM392376  Jamaica Jamaica; Bluefield Jerk  Venezuela, Falcon  FM339779  NRM  USA, California Nicaragua; Tipitapa; along shore of Lago deManagua, near Rio Tipitapa Puerto Rico; Llanos Costa  Brazil; Pernambuco AY065723  South America  O  Thamnophilidae  Cercomacra  nigrescens  LSUMZ  B12661  Thamnophilidae  Cercomacra  serva  STRI  EC-CSE1  Thamnophilidae  Cercomacra  tyrannina  crepera  UWBM  DAB 1036  Thamnophilidae  Cercomacra  tyrannina  crepera  STRI  JTW400  Thamnophilidae  Cercomacra  tyrannina  tyrannina  STRI  RCF53  Thamnophilidae  Conopophaga  lineata  FMNH  5288  Thamnophilidae  Cymbilaimus  lineatus  fasciatus  LSUMZ  B2252  Thamnophilidae  Cymbilaimus  lineatus  fasciatus  STRI  JTW154  Thamnophilidae  Cymbilaimus  lineatus  LSUMZ  Thamnophilidae  Dichrozona  cincta  ZMCU  Thamnophilidae  Dichrozona  cincta  Thamnophilidae  Drymophila  Thamnophilidae  Drymophila  Thamnophilidae  Bolivia; Santa Cruz Department; Velasco; W. Bank Rio Paucerna, 4 km upstream from Rio Itenez Ecuador; Jatun Sacha 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 AY370555  South America  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  NRM 956653  AY676962  caudata  ANSP  ANSP 185468  AF118170  Paraguay; Dpto. Caazapa; P.N. Caaguazii (Sector Enramadita Ecuador; Napo  caudata  FMNH  107208  AFI 18173  Peru; Pasco  Drymophila  devillei  FMNH  FMNH REAJ001 AFI 18174  Brazil; Acre  Thamnophilidae  Drymophila  devillei  LSUMZ  B1849  AF118184  Bolivia; Santa Cruz  Thamnophilidae  Drymophila  squamata  Thamnophilidae  Dysithamnus  mentalis  Thamnophilidae  Dysithamnus  mentalis  Thamnophilidae  Dysithamnus  mentalis  Thamnophilidae  Dysithamnus  Thamnophilidae  Dysithamnus  Thamnophilidae Thamnophilidae Thamnophilidae  S2199  AY065722  Brazil; Sao Paulo; Brazil  NRM  NRM 956629  AY676948  septentrionalis  STRI  JTW128  napensis  LSUMZ  B6155  puncticeps  STRI  JTW321  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  puncticeps  STRI  JTW635  Panama; Darien Province; Peurto Pina  Dysithamnus  puncticeps  STRI  RCF018  Panama; Veraguas Province; Santa Fe  Dysithamnus  puncticeps  LSUMZ  B11951  Ecuador; Esmeraldas Province; El Placer CA 670M  Dysithamnus  mentalis  FMNH  FM433393 FMNH 73357  AF118169  tavarae  Peru; Cuzco ; Paucartambo Brazil; Roraima  Thamnophilidae  Formicivora  grisea  FMNH  Thamnophilidae  Formicivora  rufa  LSUMZ  B14601  AY115421  South America  Thamnophilidae  Formicivora  rufa  NRM  NRM 947236  AY676958  Paraguay; Dpto. Amambay; Est. Apami  Thamnophilidae  Frederickena  unduligera  ZMCU  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  erratilis  STRI  JTW448  Panama; Chiriqui Province; Bartolo Arriba, Burica Peninsula Ecuador; Napo; C Canaday  Thamnophilidae  Gymnocichla  nudiceps  Thamnophilidae  Gymnopithys  leucaspis  ZMCU  S1843  Thamnophilidae  Gymnopithys  leucaspis  bicolor  STRI  PA-GLE914  Thamnophilidae  Gymnopithys  leucaspis  olivascens  STRI  JTW268  Panama; Panama; Darien; Tropic Star Lodge; 9km up Rio Pifias; Rio Pichinde Panama; Bocas del Toro ; Valle de Risco  Thamnophilidae  Gymnopithys  leucaspis  castaneus  STRI  EC-GLE1  Ecuador; Jatun Sacha  bicolor  STRI  JTW333  Panama; Panama Province; Cerro Campana  AY676977  Thamnophilidae  Gymnopithys  leucaspis  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  naevioides  ?capnitis  STRI  JTW560  STRI  JTW682  Panama; Cocle Province; Cascajal  Thamnophilidae  Hylophylax  Thamnophilidae  Hylophylax  naevioides  naevioides  Thamnophilidae  Hylophylax  poecilonotus  griseiventris  B1255  AY612487  Bolivia; Santa Cruz, Los Fierros  Thamnophilidae  Hylophylax  poecilonotus  griseiventris  JH-452  AY612498  Thamnophilidae  Hylophylax  poecilonotus  lepidonota  STRI  EC-HPOl  Brazil; Mato Grosso do Norte, Municipio Alta Floresta, upper Rio Teles Pires-Rio Cristalino Ecuador; Jatun Sacha  Thamnophilidae  Hypocnemis  cantator  LSUMZ  LSUB15308  AF118163  Bolivia; Santa Cruz  Thamnophilidae  Hypocnemis  cantator  FMNH  FMNH DW 3755 AF118168 SI 300  AY676964  Brazil; Mato Grosso; Rio Cristalino  LSUB156543  AF118161  Peru; Madre de Dios  Thamnophilidae  Hypocnemis  cantator  ZMCU  Thamnophilidae  Hypocnemis  hypoxantha  LSUMZ  Thamnophilidae  Hypocnemis  hypoxantha  FMNH  Thamnophilidae  Hypocnemoides  maculicauda  ZMCU  Panama; Darien Province; Puerto Pina  . FMNH REAJ232 AF118162  Brazil; Rondonia  Brazil; Acre  S1301  AY676966  Brazil; Mato Grosso; Rio Teles Pires Paraguay; Caaguazu Department Paraguay; Dpto. Caazapa; P.N. Caaguazu (Sector Enramadita Ecuador; Napo; S Pompeya  Thamnophilidae  Hypoedaleus  guttatus  LSUMZ  B-25895  AY676936  Thamnophilidae  Mackenziaena  severa  NRM  NRM 956630  AY676935  Thamnophilidae  Megastictus  margaritatus  ZMCU  S2130  AY676944  Thamnophilidae  Microrhopias  axillaris  STRI  JTW644  Thamnophilidae  Microrhopias  quixensis  Thamnophilidae  Microrhopias  quixensis  virgatus  STRI  JTW 423  Thamnophilidae  Microrhopias  quixensis  virgatus  STRI  JTW301  Panama; Chiriqui Province; Yerbazales, Burica Peninsula Panama; Bocas del Toro; Cerro Chalite  Thamnophilidae  Microrhopias  quixensis  virgatus  STRI  JTW078  Panama; Chiriqui Province; Puerto Limones,  albigula  FMNH  FMNH 321993  Panama; Darien Province; Puerto Pina AY676950  Burica Peninsula Thamnophilidae  Microrhopias  quixensis  consobrinus  STRI  JTW724  Thamnophilidae  Myrtneciza  berlepschi  ZMCU  S1631  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  Thamnophilidae  Myrmeciza  fortis  ZMCU  SI 795  AY676972  Panama; Chiriqui Province; Puerto Limones, Burica Peninsula 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 C A 670M  Thamnophilidae  Myrmeciza  immaculata  seledoni  STRI  JTW183  Thamnophilidae  Myrmeciza  laemosticta  STRI  JTW573  Panama; Bocas del Toro Province; Chiriqui to Chiriqui Grande Road at continental divide Panama; Cocle Province; El Cope National Park  Panama; Darien Province; Puerto Pina AY676973  Ecuador; Esmeraldas; NNW Alto Tambo  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  Thamnophilidae  Myrmornis  torquata  KUNHM  1311  AY370565  Paraguay; Dpto. Alto Chaco; P.N. Defensores del Chaco, Madrejon ?  Thamnophilidae  Myrmornis  torquata  LSUMZ  B-3228  AY676975  Peru; Loreto Department  Thamnophilidae  Myrmornis  torquata  strictoptera  LSUMZ  B2142  Thamnophilidae  Myrmornis  torquata  torquata  FMNH  FM391446  Panama; Darien Province; About 6 km NW Cana Brazil; Para  Thamnophilidae  AY676954  Myrmotherula  axillaris  ZMCU  S2319  Thamnophilidae  Myrmotherula  axillaris  albigula  STRI  JTW422  Thamnophilidae  Myrmotherula  axillaris  albigula  STRI  JTW653  Panama; Chiriqui Province; Yerbazales, Burica Peninsula Panama; Darien Province; Puerto Pina  Thamnophilidae  Myrmotherula  axillaris  albigula  STRI  JTW574  Panama; Cocle Province; El Cope National Park  Ecuador; Pastaza; N Canelos, 600 m  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  ZMCU  behni  Peru; Madre de Dios AY676956  Ecuador; Napo; 3 km N Guagua Sumaco  Thamnophilidae  Myrmotherula  Thamnophilidae  Myrmotherula  cherriei  AMNH  12392  Thamnophilidae  Myrmotherula  fulviventris  ZMCU  SI 649  Thamnophilidae  Myrmotherula  fulviventris  LSUMZ  B11848  Ecuador; Esmeraldas Province; El Placer 670 M Panama; Darien Province; Puerto Pina  Venezuela; Amazonas; Rio Mawarinumo AY676953  Ecuador; Esmeraldas; NNW Alto Tambo  Thamnophilidae  Myrmotherula  fulviventris  STRI  JTW638  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 JH-098  AY612525  DFS86-1373  AY612532 -  Panama; Bocas del Toro; Valle de Risco  Thamnophilidae  Myrmotherula  hauxwelli  clarior  FMNH  Thamnophilidae  Myrmotherula  hauxwelli  clarior  FMNH  Thamnophilidae  Myrmotherula  hauxwelli  FMNH  FMNH 51490  AF118160  Brazil; Mato Grosso do Norte, Municipio Alta Floresta, upper Rio Teles Pires-Rio Cristalino Brazil; Rondonia, Cachoeira Nazare, W bank Rio Jiparana Brazil; Mato Grosso  Thamnophilidae  Myrmotherula  leucophthalma  FMNH  FMNH 51500  AF118158  Brazil; Mato Grosso  Thamnophilidae  Myrmotherula  leucophthalma  FMNH  DFS86-1201  AY612547  Thamnophilidae  Myrmotherula  leucophthalma  ZMCU  SI 306  AY676952  Brazil; Rondonia, Cachoeira Nazare, W bank Rio Jiparana Brazil; Mato Grosso; Rio Teles Pires  Thamnophilidae  Myrmotherula  longipennis  FMNH  FMNH 51516  AF118159  Brazil; Mato Grosso  Thamnophilidae  Myrmotherula  longipennis  FMNH  JH-105  AY612559  Thamnophilidae  Myrmotherula  longipennis  FMNH  DFS86-1206  AY612563  Thamnophilidae  Myrmotherula  menetriesii  ZMCU  SI 893  AY676955  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  Thamnophilidae  Myrmotherula  multostriata  LSUMZ  B4354  Thamnophilidae  Myrmotherula  obscura  ZMCU  S1836  AY676951  Peru; Loreto Department; Lower Rio Napo region, E bank Rio Yanayacu, ca 90 km N Iquitos 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  Thamnophilidae  Myrmotherula  schisticolor  schisticolor  LSUMZ  B2124  Costa Rica; Heredia Province; 4 km SE Virgen del Socorro; Finca La Fortuna Panama; Darien Province; About 6 km NW Cana  schisticolor  schisticolor  LSUMZ  B11979  Thamnophilidae  Myrmotherula  Ecuador; Esmeraldas Province; El Placer, CA 670 M  4^  Thamnophilidae  Myrmotherula  surinamensis  AMNH  AMNH2988  niger  FMNH  321806  AY676960  Venezuela; Bolivar; RIO CARAPO; GUAIQUINIMA BASE CAMP Peru, Cuzco  Thamnophilidae  Neoctantes Phaenostictus  mcleannani  ZMCU  SI 647  Thamnophilidae  AY676980  Ecuador; Esmeraldas; NNW Alto Tambo  Thamnophilidae  Phaenostictus  mcleannani  mcleannani  STRI  JTW655  Thamnophilidae  Phaenostictus  mcleannani  mcleannani  STRI  JTW656  Thamnophilidae  Phlegopsis  erythroptera  ZMCU  SI 860  AY676979  Ecuador; Napo; C. Canaday  JH-348  AY612573  DW-3797  AY612576  Panama; Darien Province; Puerto Pina Panama; Darien Province; Puerto Pina  Thamnophilidae  Phlegopsis  nigromaculata  FMNH  Thamnophilidae  Phlegopsis  nigromaculata  FMNH  Thamnophilidae  Pithys  albifrons  ZMCU  SI 857  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  Thamnophilidae  Pyriglena  leuconota  ZMCU  ZMCU S2007  AY065724  Ecuador; Zamora-Chinchipe; Rio Bombuscara  Thamnophilidae  Rhegmatorhina  gymnops  FMNH  JH-061  AY612581  Thamnophilidae  Rhegmatorhina  gymnops  FMNH  JH-423  AY612591  Thamnophilidae  Rhegmatorhina  melanosticta  ZMCU  SI 825  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  Thamnophilidae  Sakesphorus  bernardi  ZMCU  S101  AY676939  Ecuador; Loja; ca 5 km SW Sabiango  Thamnophilidae  Sakesphorus  bernardi  LSUMZ  B5136  EF030317  Peru; depto. Lambayeque; Las Pampas,  Thamnophilidae  Sakesphorus  canadensis  KU  MBR6243  EF030318  Guyana; along Washikunhmra River  Thamnophilidae  Sakesphorus  luctuosus  USNM  B7012  EF030319  Brazil; Para; 52 km SSW Altamira  Thamnophilidae  Schistocichla  leucostigma  ZMCU  Z M C U SI207  AY676968  Thamnophilidae  Sclateria  naevia  ZMCU  S102  AY676967  Ecuador; Napo; 1 km S Puerto Napo  Thamnophilidae  Taraba  major  NRM  NRM 956694  AY676938  Thamnophilidae  Taraba  major  obscurus  STRI  JTW664  Paraguay; Dpto. Alto Chaco; P.N. Defensores del Chaco, Madrejon, 42 km W Panama; Darien Province; Puerto Pina  Thamnophilidae  Taraba  tnajor  obscurus  STRI  JTW664  Panama; Darien Province; Puerto Pina  Thamnophilidae  Taraba  major  obscurus  STRI  PA-TMA-PP101  Panama; Panama; Old Gamboa Rd.  Thamnophilidae  Taraba  major  obscurus  STRI  JTW681  Panama; Darien Province; Puerto Pina  Thamnophilidae  Tereriura  callinota  callinota  LSUMZ  B6176  Thamnophilidae  Terenura  callinota  callinota  LSUMZ  B2198  Thamnophilidae  Terenura  humeralis  FMNH  AF118156  Thamnophilidae  Terenura  humeralis  FMNH  FMNH DFS 86130 389941  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  Thamnistes  anabatinus  ZMCU  S1607  Thamnophilidae  Thamnistes  anabatinus  coronatus  LSUMZ  B2154  Panama; Darien Province; About 6 km NW Cana  Thamnophilidae  Thamnistes  anabatinus  aequatorialis  LSUMZ  B6152  Thamnophilidae  Thamnistes  anabatinus  ?saturatus  STRI  JTW179  Thamnophilidae  Thamnomanes  caesius  ZMCU  S1312  AY676947  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  Thamnophilidae  Thamnomanes .  caesius  LSUMZ  B9482  EF030320  Guyana; Northwest District; Baramita  Thamnophilidae  Thamnophilus  palliatus  UWBM  MAB02  Thamnophilidae  Thamnophilus  aethiops  LSUMZ  B14649  AY962686  Bolivia; Departamento de Santa Cruz; Provincia de Florida; Samaipata, 23.2 km E; 1350 m Bolivia.Santa Cruz Department  Thamnophilidae  Thamnophilus  amazonicus  LSUMZ  B13045  Thamnophilidae  Thamnophilus  aroyae  UWBM  RTB395  EF030322  Thamnophilidae  Thamnophilus  atrinucha  USNM  B393  EF030323  Thamnophilidae  Thamnophilus  atrinucha  STRI  JTW254  Thamnophilidae  Thamnophilus  atrinucha  STRI  JTW673  Thamnophilidae  Thamnophilus  bridgesi  LSUMZ  B16149  Thamnophilidae  Thamnophilus  bridgesi  STRI  JTW056  Thamnophilidae  Thamnophilus  bridgesi  STRI  CR-TBR2756  Panama; Chiriqui Province; Puerto Limones, Burica Peninsula Costa Rica; Dominical Baru  Thamnophilidae  Thamnophilus  bridgesi  STRI  RCF035  Panama; Veraguas Province; Pontuga  JTW388  •  AY676946  Ecuador; Esmeraldas; Alto Tambo  Thamnophilidae  EF030321  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  EF030324  Costa Rica; prov. Puntarenas; 2 km SE Dominical  Thamnophilidae  Thamnophilus  bridgesi  STRI  Thamnophilidae  Thamnophilus  bridgesi  STRI  JTW080  Thamnophilidae  Thamnophilus  caerulescens  NRM  NRM 967007  AY078176  Panama; Chiriqui Province; Yerbazales, Burica Peninsula Panama; Chiriqui Province; Puerto Limones, Burica Peninsula South America  Thamnophilidae  Thamnophilus  caerulescens  UWBM  RCF2148  AY962812  South America  Thamnophilidae  Thamnophilus  caerulescens  FMNH  395426  EF030325  Brazil; Sao Paulo; Boraceia  AY676941  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  Thamnophilidae  Thamnophilus  cryptoleucus  ZMCU  S1196  Thamnophilidae  Thamnophilus  cryptoleucus  LSUMZ  B7285  EF030326  Thamnophilidae  Thamnophilus  divisorius  PNSD  228  EF030341  Thamnophilidae  Thamnophilus  doliatus  AF082057  Thamnophilidae  Thamnophilus  doliatus  AY370563  Thamnophilidae  Thamnophilus  doliatus  NRM  NRM 956691  AY676940  ?  Paraguay; Dpto. Alto Chaco; P.N. Defensores del Chaco, Madrejon, 42 km W  Thamnophilidae  Thamnophilus  doliatus  UWBM  RTB390  Thamnophilidae  Thamnophilus  doliatus  Thamnophilidae  Thamnophilus  Thamnophilidae  Thamnophilus  EF030327  Bolivia; depto. Santa Cruz; prov. Cordillera, 10.6 km E Abapo Panama; Code Province; Rosario (near Anton  nigricristatus  STRI  JTW582  doliatus  radiatus  LSUMZ  B10890  doliatus  doliatus  STRI  TR-THD2 B7486  EF030328  Venezuela; terr. Amazonas; Cerro de Neblina camp \JW Vll  Peru; Ucayali Department; N. bank Rio Abujao, 2 km E Caserio de Abujao Trinidad; Simla Research Station-site 2  Thamnophilidae  Thamnophilus  insignis  LSUMZ  Thamnophilidae  Thamnophilus  murinus  USNM  B9206  EF030329  Guyana; Northwest District; Baramita  Thamnophilidae  Thamnophilus  nigriceps  UAM  20238  EF030330  Panama; prov. Panama, Lago Bayano  Thamnophilidae  Thamnophilus  nigriceps  STRI  PA-TNG-PA300  Thamnophilidae  Thamnophilus  nigriceps  STRI  PA-TNG-PA301  Thamnophilidae  Thamnophilus  nigrocinereus  LSUMZ  B20233  EF030331  Thamnophilidae  Thamnophilus  palliatus  UWBM  MAB2  EF030332  Thamnophilidae  Thamnophilus  praecox  ZMCU  S108  AY676942  Brazil; Amazonas; Munic. Novo Airao; Arquipelago das Anavilhanas Bolivia; depto. Santa Cruz; prov. Florida, 23.2 km E Samaipata Ecuador; Sucumbios; Rio Lagarto Cocha  Thamnophilidae  Thamnophilus  praecox  ANSP  B3190  EF030333  Ecuador; prov. Sucumbios; Imuya Cocha  Thamnophilidae  Thamnophilus  punctatus  USNM  B4172  EF030334  Guyana; Berbice; West bank Dubulay ranch  Thamnophilidae  Thamnophilus  ruficapillus  UWBM  RTB347  EF030336  Thamnophilidae  Thamnophilus  ruficapillus  UWBM  RTB347  Thamnophilidae  Thamnophilus  schistaceus  LSUMZ  B12559  EF030337  Thamnophilidae  Thamnophilus  stictocephalus  LSUMZ  B13850  EF030335  Thamnophilidae  Thamnophilus  sticturus  UWBM  RTB355  Thamnophilidae  Thamnophilus  tenuepunctatus  ANSP  B1686  EF030338  Bolivia; depto. Santa Cruz; prov. Cordillera, El Tambo, 14 km SE Comarapa Bolivia; Departamento de Santa Cruz; Provincia de Caballero; Tambo; Comarapa, 14 km SE; 1600 m Bolivia; depto. Santa Cruz; Velasco; 50 km ESE Florida, Arroyo de Encanto Bolivia; depto. Santa Cruz; Serrania de Huanchaca, ca 45 km E Florida Bolivia; Departmento de Santa Cruz; Province de Cordillero; Abapo 10.6 K M E. Ecuador; prov. Zamora Chinchipe; Zaruma  Thamnophilidae  Thamnophilus  torquatus  LSUMZ  B13900  EF030339  Thamnophilidae  Thamnophilus  unicolor  ZMCU  Sill  AY676943  Bolivia; depto. Santa Cruz; Serrania de Huanchaca, 45 km E Florida Ecuador; El Oro; 9 km W Pinas  Thamnophilidae  Thamnophilus  unicolor  LSUMZ  B12144  AY962685  Ecuador; Pichincha Province  Thamnophilidae  Thamnophilus  zarumae  LSUMZ  B191  EF030340  Thraupidae  Acanthidops  bairdii  LSUMZ  B-16267  AF489878  Thraupidae  Anisognathus  flavinucha  LSUMZ  B-566  A Y3 83090  Peru; depto. Piura; km 34 on Olmos-Bagua Chica Hwy Costa Rica: Provincia San Jose', Cerro de la Muerte, km 113 Pan American Highway; Peru: Dept. Puno, Abra de Maruncunca  Thraupidae  Bangsia  arcaei  STRI  JTW157  cochabambe  Panama; Panama; Lago Bayano; Isla Maje Panama; Panama; Lago Bayano; Isla Maje  Panama;Bocas del Toro; Chiriqui to Chiriqui Grande Road at continental divide  Thraupidae  Basileuterus  rivularis  LSUMZ  B-7499  AY340217  Venezuela, Amazonas Territory  Thraupidae  Buthraupis  montana  LSUMZ  Thraupidae  Calochaetes  coccineus  LSUMZ  B-365  AY383091  Peru: Dept. Cajamarca, Cerro Chinguela  B-6134  AY383092  Thraupidae  Calyptophilus  Ecuador: Prov. Morona-Santiago  frugivorus  DQ166566  Hispanola  Thraupidae Thraupidae  Calyptophilus  tertius  DQ166575  Hispanola  Camarhynchus  parvulus  AF108796  Galapagos  Thraupidae  Cainarhynchus  pauper  AF108795  Galapagos  Thraupidae  Camarhynchus  psittacula  AF108798  Galapagos South America  .  Thraupidae  Catamenia  inornata  AF310049  Thraupidae  Certhidea  fusca  AY672052  Ecuador, Galapagos, San Cristobal  Thraupidae  Certhidea  olivacea  AF108806  Galapagos  Thraupidae  Chlorochrysa  calliparaea  LSUMZ  B-8103  AY383095  Peru: Dept.' Pasco, Playa Pampa  B-34873  AY383094  Ecuador: Prov. Pichincha  AF006215  Thraupidae  Chlorochrysa  phoenicotis  LSUMZ  Thraupidae  Chlorophanes  spiza  LSUMZ  B-2838  Thraupidae  Chlorophanes  spiza  STRI  HA-CSP-HA15  Peru: Dept. Loreto, 1 km N Rio Napo, 157 km by river NNE Iquitos Honduras;La Ceiba;  Thraupidae  Chlorophanes  spiza  STRI  HA-CSP-HA51  Honduras;La Ceiba;  Thraupidae  Chlorophanes  spiza  LSUMZ  B2226  Thraupidae  Chlorophanes  spiza  STRI  JTW598  Panama; Darien Province: Cana on E slope Cerro Pirre Panama;Cocle; El Cope National Park  Thraupidae  Chlorophanes  spiza  STRI  TR-CSP4  Thraupidae  Chlorornis  riefferii  LSUMZ  B-1859  Thraupidae.  Chrysothlypis  chrysomelas  STRI  JTW016  Thraupidae  Chrysothlypis  chrysomelas  LSUMZ  B-2189  Thraupidae  Cissopis  leveriana  LSUMZ  Thraupidae  Cnemoscopus  rubrirostris  LSUMZ  Thraupidae  Coereba  flaveola  Thraupidae  Coereba  flaveola  Thraupidae  Coereba  flaveola  Thraupidae  Coereba  flaveola  Thraupidae  Coereba  flaveola  Thraupidae  Coereba  flaveola  STRI  AB-CFA2  Bahamas;Abaco;  Thraupidae  Coereba  flaveola  STRI  BH-CFA3  Bahamas;Ridge;  Trinidad;Lemon Road off of Las Lapis; AY383093  Peru: Dept. Pasco, Cumbre de Ollon Panama;Veraguas;Santa Fe  AF006220  Panama: Prov. Darien, about 6 km NW Cana  B-1143  AY383096  Bolivia: Dept. La Paz, Rio Beni  B-5624  AF006222  UMMZ  227691  AF489880  UMMZ  227711  AF489882 AF310068  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; ?  AF290151  Bahamas  AF382993  Bahamas  Thraupidae  Coereba  flaveola  UMMZ  U M M Z 225179  Thraupidae  Coereba  flaveola  STRI  JA-CFA1  AY383089  Jamaica: Trelawny Par., Cornwall Jamaica;Luana Point;  Thraupidae  Coereba  flaveola  STRI  JA-CFA4  Jamaica;Paradise, near Sav-la-mar;  Thraupidae  Coereba  flaveola  AMNH  AMNH6829  Thraupidae  Coereba  flaveola  STRI  PA-CFA341  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  Mexico;Quintana Roo, Cozumel Island, El . Codral;SAN MIGUEL Panama;Bocas, Isla San Cristobal;  Republica Dominicana;Golf Club-Jarabacoa; AF310045  St. Lucia  Thraupidae  Coereba  flaveola  Thraupidae  Coereba  flaveola  Thraupidae  Conirostrum  albifrons  Thraupidae  Conirostrum  bicolor  Thraupidae  Conirostrum  sitticolor  Thraupidae  Conirostrum  speciosum  FMNH  FMNH 334602  AY190168  Bolivia: Santa Cruz, Chiquitos  Thraupidae  Conothraupis  speculigera  LSUMZ  B-5127  AF006223  Thraupidae  Coryphospingus  cucullata  UMMZ  235435  AF447366  Peru: Dept. Lambayeque, Las Pampas, km 885 PanAmerican Hwy, 11 km by road from Olmos captive  Thraupidae  Creurgops  dentata  LSUMZ  B-580  AF006224  Thraupidae  Creurgops  verticalis  LSUMZ  B-7974  AY190166  Thraupidae  Cyanerpes  caeruleus  LSUMZ  B-14737  AF006225  Thraupidae  Cyanerpes  caeruleus  LSUMZ  B11825  Bolivia: Dept. Santa Cruz, Serrania de Huanchaca, 25 km SE Catarata Arco Iris Ecuador Esmeraldas Province: El Placer, C A 670 M  STRI  EC-CCE1612  Ecuador;Provincia de Santiago;  Thraupidae  Cyanerpes  caeruleus  Thraupidae  Cyanerpes  caeruleus  Thraupidae  Cyanerpes  cyaneus  Thraupidae  Cyanerpes  Thraupidae Thraupidae  STRI  STRI  St. Vincent;St. George Parish, Indian Bay;  SV-CFA2129  TR-CBC1  AF447365  Peru  AK383025  South America  AF383000  South America  Peru: Dept. Puno, Abra de Maruncunca, 10 km SW San Juan del Oro Peru, Dept. Pasco, Playa 8 Km NW Cushi  STRI  TR-CCE1  Trinidad;Simla Research Station;  FMNH  FM391637  Brazil;Amapa;  cyaneus  STRI  HA-CCN-HA82  Honduras;La Ceiba;  Cyanerpes  cyaneus  STRI  JTW451  Panama;Chiriqui;Bartolo Arriba, Burica Peninsula  Cyanerpes  cyaneus  STRI  CC-CCN1  Trinidad;Chacachacare Island;  Thraupidae  Cyanerpes  lucidus  STRI  PA-CLC34493 '  Thraupidae  Cyanerpes  nitidus  FMNH  Thraupidae  Cyanerpes  nitidus  FMNH  FMNH MPEG DW3813 FM390048  Panama;Prov. Darien near Rancho Frio Station; 400m; Brazil: Rhondonia  cyaneus  AY190167  Brazil;Rondonia;  Thraupidae  Cypsnagra  hirundinacea  LSUMZ  B15289  Thraupidae  Dacnis  cayana  STRI  LTL102  AY 115394  Bolivia, Santa Cruz Department  Thraupidae  Dacnis  cayana  LSUMZ  B-15077  Thraupidae  Dacnis  cayana  STRI  UL056  Bolivia: Dept. Santa Cruz, Velasco, 13 km SW Piso Firme Panama;Bocas del Toro; Cerro Chalite  Thraupidae  Dacnis  cayana  STRI  TR-DAC1  Trinidad;Simla Research Station;  Thraupidae  Dacnis  venusta  LSUMZ  B2192  Thraupidae  Delothraupis  castaneoventris  . LSUMZ  B-6931  Thraupidae  Diglossa  albilatera  LSUMZ  B262  Thraupidae  Diglossa  baritula  MEX350  Thraupidae  Diglossa  baritula  University of Mexico STRI  Peru;Departmento Cajamarca;"Batan" on Sapalache-carmen Trail Mexico;Jalisco;Sierra de Manantlan, Las Joyas  JTW465  Panama;Chiriqui;Volcan Baru Parque National  Thraupidae  Diglossa  humeralis  Thraupidae  Diglossa  humeralis  Thraupidae  Diglossa  lafresnayii  Thraupidae  Diglossa  major  Thraupidae  Diglossa  Thraupidae  PA;Bocas del Toro; Cerro Chalite AF006227  Panama; Darien Province: Ca 6km NW Cana. AY383097  AF310050  Peru: Dept. Huanuco, Quebrada Shugush  Peru;Departmento Piura; "Cruz Blanca" ca. 33 road K M SW Huancabamba; South America  LSUMZ  B-351  plumbeal  LSUMZ  B16068  Costa Rica Provincia Heredia; Finca la Fortuna  Diglossa  plumbea.2  LSUMZ  B16239  Costa Rica Provincia San Jose; La Georgina  Thraupidae  Diglossa  sittoides  LSUMZ  B5558  Peru;Departmento San Martin; 28km NE Tarapoto;  Thraupidae  Dolospingus  fringilloides  USNM  625323  AY705435  South America  Thraupidae  Dubusia  taeniata  LSUMZ  B-7710  AY383098  Peru: Dept. Huanuco, Unchog Pass NNW Acomayo  Thraupidae  Emberizoides  herbicola  NRM  NRM 976735  AY228057  Thraupidae  Emberizoides  ypiranganus  UWBM  UWBM70773  Thraupidae  Eucometis  penicillata  LSUMZ  B-6551  Thraupidae  Eucometis  penicillata  LSUMZ  B18544  Thraupidae  Eucometis  penicillata  UWBM  UWBM69247  Thraupidae  Eucometis  penicillata  STRI  JTW443  Thraupidae  Euneornis  campestris  FMNH  331119  AF489885  Jamaica: Surrey, Portland, Hollywell Park;  Thraupidae  Geospiza  conirostris  AFI 08769  Galapagos  Thraupidae  Geospiza  difficilis  AF108788  Galapagos  Thraupidae  Geospiza  fords  AFI 08771  Galapagos  AF006229 AF290155  Peru: Dept.Cajamarca, Cerro Chinguela, 5 km NE Sapalache South America  Argentina;Provincia de Corrientes;Corrientes AF006231  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 K M S; Panama;Chiriqui;Yerbazales, Burica Peninsula  ON  O  Thraupidae  Geospiza  fuliginosa  AF108784  Galapagos  Thraupidae  Geospiza  magnirostris  AF108778  Galapagos  Thraupidae  Geospiza  scandens  AF108779  Galapagos  Thraupidae  Haplospiza  rustica  Thraupidae  Haplospiza  LSUMZ  B16173  rustica  STRI  EC-HRU514  Costa Rica San Jose Province: La Georgina, km 95 Pan American Hwy. Ecuador;Provincia Carchi;  LSUMZ  B7451  Venezuela Amazonas Territory: Cerro De La  Thraupidae  Haplospiza  rustica  Thraupidae  Haplospiza  unicolor  AF290156  Neblina Camp Vn 1800 M 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  AF006235  Peru: Dept. Loreto, S Rio Amazonas, ca. 10 km SSW mouth Rio Napo on E bank Quebrada Vainilla Panama;Bocas del Toro; Cerro Chalite  Thraupidae  Hemithraupis  flavicollis  LSUMZ  B-5102  Thraupidae  Heterospingus  rubrifrons  STRI  JTW278 B28692  Thraupidae  Heterospingus  rubrifrons  LSUMZ  Thraupidae  Heterospingus  xanthopygius  LSUMZ  B-2324  AF006236  Panama; Colon Province: Achiote Road at Rio Providencia Panama: Prov. Darien, Cana on E slope Cerro Pirre  Thraupidae  Iridosornis  analis  LSUMZ  B-1706  AY383099  Peru: Dept. Pasco, Santa Cruz  AF006238  Thraupidae  Lamprospiza  melanoleuca  LSUMZ  B-9678  Thraupidae  Lanio  aurantius  Nevada  DHB3785  Bolivia: Dept. Pando, Nicolas Suarez, 12 km by road S of Cobija, 8 km W on road to Mucden Honduras;Departmento Atlantida;  B34944  Ecuador Napo Province: 40 km NNE Tena  Thraupidae  Lanio  fulvous  LSUMZ  Thraupidae  Lanio  leucothorax  STRI  JTW572  Thraupidae  Lanio  versicolor  LSUMZ  B-1014  Thraupidae  Loxigilla  noctis  Thraupidae  Loxigilla  portoricensis  LSUMZ  B-11351  AF489886  Thraupidae  Loxigilla  violacea  AMNH  25433  AF489887  Panama;Cocle; El Cope National Park, AF006239 AF310041  Bolivia: Dept. La Paz, Rio Beni, ca. 20 km by river N. Puerto Linares Saint Lucia Puerto Rico: Cabo Rojo, Boqueron, Penones de Melones; Dominican Republic: Provincia Independencia, Parque Nacional Sierra de Baoruco;  Thraupidae  Loxipasser  anoxanthus  Thraupidae  Melanospiza  richardsoni  Thraupidae  Nemosia  pileata  Thraupidae  Neothraupis  fasciata  Thraupidae  Nephelornis  oneilli  Thraupidae  Nesospingus  Thraupidae Thraupidae  FMNH  331107  AF489888  Jamaica: Surrey, Portland, Hollywell Park;  AF310043  Saint Lucia  B-7295  AF006241  B-13914  AY383100  LSUMZ  B-8402  AF006243  speculiferus  LSUMZ  B-11375  AF489889  Oreomanes  fraseri  LSUMZ  B-2069  AF006244  Peru: Dept. Loreto, Amazonas I. Pasto, 80 km NE Iquitos Bolivia: Dept. Santa Cruz, Serrania de Huanchaca, 45 km E Florida Peru: Dept. Pasco, Millpo, E. Tambo de Vacas on Pozuzo-Chaglla trail Puerto Rico: San German, along route 120 near Mt. Alegrillo; LSUMZ 150230; Peru: Dept. Lima, about 13 road km W. Milloc  Oryzoborus  angolensis  STRI  HA-OFU-HA37  Thraupidae  Oryzoborus  angolensis  STRI  OAN  Thraupidae  Oryzoborus  angolensis  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  Thraupidae  Oryzoborus  crassirostris  FMNH  339668  Thraupidae  Oryzoborus  funereus  STRI  PE-OAN10892  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  LSUMZ  B5205  AY005205  Peru, Lambayeque Department Bolivia, Cochabamba  LSUMZ  Honduras;La Ceiba; PA AF310055  Ecuador  Panama;Chiriqui;Yerbazales, Burica Peninsula AF489890  Venezuela: Sucre, Guaraunos, 14 km SSE; Peru;Rio Abujao;  Thraupidae  Poospiza  . hispaniolensis  Thraupidae  Poospiza  hypochondria  ZMUC  671  AY005207  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  Thraupidae  Ramphocelus  passer  STRI  RPA  Paraguay: Dept. Itapu, El Tirol, 19.5 km by road NNE Encarnacion Honduras  Thraupidae  Ramphocelus  passer  STRI  RPA  Honduras  Thraupidae  Ramphocelus  bresilius  Thraupidae  Ramphocelus  carbo  LSUMZ  B4988  Thraupidae  Ramphocelus  costaricensis  Thraupidae  Ramphocelus  costaricensis  Thraupidae  Ramphocelus  costaricensis  STRI  JTW396  Thraupidae  Ramphocelus  dimidiatus  STRI  RDI  Thraupidae  Ramphocelus  icteronotus  LSUMZ  B12017  Thraupidae  Ramphocelus  icteronotus  STRI  JTW611  Thraupidae  Ramphocelus  icteronotus  STRI  JTW676  Thraupidae  Ramphocelus  nigrogularis  LSUMZ  B2850  U15721  Peru: Dpto. Loreto; 1 km N Ry'o Napo,  Thraupidae  Ramphocelus  passerinii  LSUMZ  B16152  U15717  Thraupidae  Ramphocelus  sanguinolentus  MEX-117  U15718  Thraupidae  Rhodinocichla  rosea  STRI  PA-RRO-PA59  Costa Rica: Prov. Heredia; ca. 5 km by road S. Puerto Viejo Mexico: Vera Cruz; Sierra de Santa Martha, El Bastanol 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  165617  AF006249  U15724  9  U15723 U15720  Peru: Dpto. Loreto; S Ry'o Amazonas, ca. 10 km SSW Ry'o Napo Costa Rica, Punteranas  U15722  Costa Rica, Punteranas Panama;Chiriqui;Yerbazales, Burica Peninsula PA  U15719  Ecuador: Prov. Esmeraldas; El Placer Panama;Darien;Puerto Pina Panama;Darien;Puerto Pina  Thraupidae  Saltator  albicollis  STRI  PU-SAL5251  Peru;Lambayeque;  Thraupidae  Saltator •  atriceps  KU5984  El Salvador  Thraupidae  Saltator  atriceps  KU1979  Mexico  Thraupidae  Saltator  atriceps  KU1979  Mexico  Thraupidae  Saltator  atricollis  Kansas University Kansas University Kansas University NRM  Thraupidae  Saltator  caerulescens  FMNH  FM391613  Thraupidae  Saltator  caerulescens  Thraupidae  Saltator  coerulescens  Thraupidae  Saltator  caerulescens  FM334590  Bolivia;El Beni;  Thraupidae  Saltator  coerulescens  FM393897  Mexico;Jalisco;  Thraupidae  Saltator  maximus  B28178  Panama; Chiriqui Province: Dist. Gualaca, Codillera  mutus  LSUMZ  966978  AY228082  ? Brazil;Amapa;  AF089059  ?  AF290154  Bolivia, Santa Cruz  Central, 4.3 km by road S. Lago Fortuna dam Thraupidae  Saltator  maximus  STRI  JTW282  Thraupidae  Saltator  maximus  STRI  JTW717  Panama;Darien;Puerto Pina  Thraupidae  Saltator  maximus  AMNH  AMNH 11984  Venezuela;Bolivar;40 K M E T U M A R E M O ON ROAD TO BOCHINCHE  Thraupidae  Saltator  striatipectus  STRI  CC-SAL1  AF383107  Thraupidae  Saltatricula  multicolor  MVZ  179401  AF489892  Aviary of Luis F. Baptista, CAS Accn. 5067;  Thraupidae  Schistochlamys  melanopsis  LSUMZ  B-9669  AY383102  Bolivia: Dept. Pando, Nicolas Suarez  Thraupidae  Sericossypha  albocristata  LSUMZ  B-5630  AF006251  Thraupidae  Sicalis  flaveola  Peru: Dept. Amazonas, 30 km by road E Florida on road to Rioja ?  Thraupidae  Sicalis  luteola  Thraupidae  Sporophila  americana  Thraupidae  Sporophila  Thraupidae Thraupidae  .  Panama;Bocas del Toro; Cerro Chalite  AY491528 FMNH  389274  americana  STRI  JTW124  Sporophila  americana  STRI  JTW445  Sporophila  americana  STRI  JTW688  Thraupidae  Sporophila  bouvreuil  MACN  MACN 39763  Thraupidae  Sporophila  caerulescens  UWBM  UWBM 70776  Thraupidae  Sporophila  caerulescens  MACN  MACN 46181  Thraupidae  Sporophila  castaneiven  Thraupidae  Sporophila  castaneivent  AMNH  AMNH 277325  Thraupidae  Sporophila  cinnamomea  MACN  Thraupidae  Sporophila  collaris  Thraupidae  Sporophila  Thraupidae  Sporophila  Thraupidae  Sporophila  Thraupidae  AF489893 AF310054  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  AY387415  Misiones, Argentina  AY387417  Argentina;Provincia de Corrientes, Corrientes 45 kmS.; Cordoba, Argentina  AF310056  South America  AY387419  Amazonas River, Brasil  M A C N 52374  AY387423  Entre Rios, Argentina  FMNH  334566  AF489895  Bolivia: El Beni, Laguna Suarez, 5 km SW Trinidad;  collaris  MACN  M A C N 1132a  AY387424  Mendoza, Argentina  falcirostris  MACN  M A C N 39081  AY387425  Misiones, Argentina  hypochroma  MACN  M A C N 48247  AY387428  Corrientes, Argentina  Sporophila  hypoxantha  MACN  M A C N 45378  AY387430  Corrientes, Argentina  Thraupidae  Sporophila  leucoptera  MACN  M A C N 45392  AY387431  Corrientes, Argentina  Thraupidae  Sporophila  luctuosa  AMNH  AMNH 822336  AY387432  Loreto, Peru  Thraupidae  Sporophila  melanogaster  AMNH  315886  AY387433  Rio Grande do Sul, Brasil  Thraupidae •  Sporophila  minuta  USNM  USNM 62108 le  AY387435  Berbice, Guyana  Thraupidae  Sporophila  minuta  STRI  JTW371  Panama;Cocle; Penenome  Thraupidae  Sporophila  minuta  AMNH  287785  Thraupidae  Sporophila  minuta  STRI  TR-SMI1  Thraupidae  Sporophila  minuta  USNM  622227f  FMNH  FM392597  nigricollis  AY387434  Tapajoz river, Brasil Trinidad;Livestock Research Station;  AY387436  Guyana; Wiwitau Mount Brazil;Para;  Thraupidae  Sporophila  nigricollis  Thraupidae  Sporophila  nigricollis  AF310053  Ecuador, Santo Domingo  Thraupidae  Sporophila  nigricollis  MACN  M A C N 39761  AY387437  Misiones, Argentina  Thraupidae  Sporophila  palustris  MACN  M A C N 48513  AY387438  Entre Rios, Argentina  B13986  AY115407  Bolivia, Santa Cruz Department  AF489896  Bolivia: Santa Cruz, Chiquitos Purubi, 30 km S San Jose de Chiquitos; Cordoba, Argentina  Thraupidae  Sporophila  plumbea  Thraupidae  Sporophila  ruficollis  FMNH  334582  Thraupidae  Sporophila  ruficollis  MACN  M A C N 31342  Thraupidae  Sporophila  schistacea  FMNH  FM433821  Thraupidae  Sporophila  schistacea  Thraupidae  Sporophila  schistacea  FMNH  FM433822  Peru;Cuzco;Paucartambo  Thraupidae  Sporophila  schistacea  STRI  JTW506  Panama;Chiriqui;Volcan Baru Parque National  Thraupidae  Sporophila  telasco  AMNH  AMNH 152815  Thraupidae  Sporophila  torqueola  NEVADA  DHB3560  Thraupidae  Sporophila  zelichi  MACN  M A C N 52378  Thraupidae  Tachyphonus  coronatus  UWBM  UWBM70535  Thraupidae  Tachyphonus  cristatus  AMNH  AMNH11925  AY387440  Cuzco;Paucartambo AF290149  AY387443  Bolivia, La Paz  Lima, Peru Honduras;Departmento Copan;  AY387444  Entre Rios, Argentina  Thraupidae  Tachyphonus  delatrii  STRI  JTW255  Argentina;Provincia de Corrientes, Corrientes 10 kmN; Venezuela;Bolivar;40 K M E T U M A R E M O ON ROAD TO BOCHINCHE Panama;Bocas del Toro; Valle de Risco  Thraupidae  Tachyphonus  delatrii  STRI  JTW257  Panama;Bocas del Toro; Valle de Risco  Thraupidae  Tachyphonus  delatrii  STRI  JTW004  Panama;Cocle; El Cope National Park  Thraupidae  Tachyphonus  delatrii  STRI  JTW622  Panama;Darien;Puerto Pina  Thraupidae  Tachyphonus  delatrii  STRI  JTW634  Panama;Darien;Puerto Pina  Thraupidae  Tachyphonus  luctuosus  STRI  PA-TLC190  Panama;Cocle: Molejon: Finca Moreno;  Thraupidae  Tachyphonus  luctuosus  NEVADA  GAV1988  Honduras;Departamento Atlantida;  Thraupidae  Tachyphonus  luctuosus  JKO1-236  Honduras;Departamento Atlantida;  Thraupidae  Tachyphonus  rufus  FMNH  FM392631  Brazil;Para;  Thraupidae  Tachyphonus  rufus  STRI  CC-TRF3  Trinidad;Chacachacare Island;  Thraupidae  Tachyphonus  surinamus  LSUMZ  Thraupidae  Tangara  argyrofenges  ANSP  B-4795  AF006253  4482  AY383104  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  Thraupidae  Tangara  arthus  LSUMZ  B-34876  AY383105  Thraupidae  Tangara  callophrys  LSUMZ  B-34961  AY383107  Thraupidae  Tangara  cayana  LSUMZ  B-15414  AY383108  Thraupidae  Tangara  chilensis  MVZ  169699  AY383110  Thraupidae  Tangara  chrysotis  LSUMZ  B-34927  AY383111  Thraupidae  Tangara  cucullata  STRI  GR-TCU2  AY383112  Thraupidae  Tangara  cyanicollis  LSUMZ  B-15352  AY383115  Thraupidae  Tangara  cyanicollis  LSUMZ  B-34904  AY383114  Thraupidae  Tangara  cyanocephala  FMNH  427278  AY383117  Fxuador: Prov. Morona-Santiago, W Slope de Cutucci Yapitya Peru: Dept. Cajamarca, Cerro Chinguela, 5 km NE Sapalache Peru: Dept. Pasco, Playa Pampa, about 8 km NW Cushi on trail to Chaglla Ecuador: Prov. Pichincha, 30 km SE Santo Domingo de los Colorados; Bolivia: Dept. La Paz, Rio Beni, ca 20km by river N. Puerto Linares Jamaica: Trelawny Par., Cornwall, Good Hope Plantation Peru: Dept. Huanuco, Quebrada Shugush, 30km on Huanuco-La Union road Dominican Republic: Prov. Independencia, Parque Nacional Sierra de Baoruco, Zapoten, Sawmill Clearing Peru: Dept. Pasco, Santa Cruz, about 9 km SSE Oxapampa Jamaica: Surrey, Portland, Hollywell Park  Thraupidae  Tangara  cyanoptera  LSUMZ  B-7436  AY383116  Ecuador: Prov. Pinchincha, Mindo  Thraupidae  Tangara  cyanotis  LSUMZ  B-22708  AY383119  Thraupidae  Tangara  desmaresti  FMNH  395478  AY383120  Thraupidae  Tangara  dowii  LSUMZ  B-16020  AY383121  Thraupidae  Tangara  dowii  STRI  JTW535  Bolivia: Dept. Pando, Nicolas Suarez, 12km by road S of Cobija, 8 km W on road to Mucden Ecuador: Zamora-Chinchipe, Panguri about 12km NE San Francisco del Vergel, 4 370S, 78 580W Ecuador: Prov. Pichincha, 35 km SE Santo Domingo de los Colorados; 00 160N, 78 500W Panama;Chiriqui;Cerro Colorado  Thraupidae  Tangara  fastuosa  FMNH  427276  AY383123  Thraupidae  Tangara  florida  LSUMZ  B-34982  AY383122  Thraupidae  Tangara  florida  LSUMZ  B11989  Bolivia: Dept. La Paz, Prov. B. Saavedra, 83 km by road E Charazani, Cerro Asunta Pata Bolivia: Dept. Santa Cruz, Serrania de Huanchaca, 45 km E Florida Ecuador Esmeraldas Province: El Placer, C A 670 M  Thraupidae  Tangara  florida  STRI  UL106  PA;Panama Province;Cerro Jefe  Thraupidae  Tangara  florida  STRI  JTW169  Thraupidae  Tangara  florida  STRI  JTW607  Panama;Bocas del Toro; Chiriqui to Chiriqui Grande Road at continental divide Panama;Cocle; El Cope National Park  Thraupidae  Tangara  florida  STRI  PA-TAL1014  Thraupidae  Tangara  fucosa  LSUMZ  B-1398  Thraupidae  Tangara  . fucosa  STRI  PA-TFU1008  Thraupidae  Tangara  LSUMZ  B-2190  guttata  AY383125  AY383126  Panama;Panama:Darien: Tropic Star Lodge: PinasSambu Trail; Ecuador: Prov. Napo, 40km NNE Tena; 00 440N, 77 420W Panama;Panama:Darien: Tropic Star Lodge: PinasSambu Trail N 07° 41.448 W 78° 11.882; Peru: Dept. Cajamarca, 1 mi N San Jose de  Lourdes, Cordillera del Condor Panama;Veraguas;Santa Fe  Thraupidae  Tangara  guttata  STRI  JTW013  Thraupidae  Tangara  guttata  AMNH  AMNH8807 B-4258  AY383131  Venezuela; Amazonas ;TAM A C U ARI  Thraupidae  Tangara  gyrola  LSUMZ  Thraupidae  Tangara  gyrola  LSUMZ  B-2149  AY383127  Thraupidae  Tangara  gyrola  LSUMZ  B-27281  AY383130  Thraupidae  Tangara  gyrola  LSUMZ  B-14862  AY383128  Bolivia: Dept. Santa Cruz, Serrania de Huanchaca, 45km E Florida Ecuador: Prov. Napo, 40km NNE Tena; 00 440N, 77 420W Ecuador: Prov. Pichincha, 5 km NE Puento Quito; 00 090N, 79 120W 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  Thraupidae  Tangara  gyrola  STRI  TR-TGY1  Panama;Panama:Darien: Tropic Star Lodge: PinasSambu Trail; 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  Thraupidae  Tangara  icterocephala  STRI  JTW336  Panama;Bocas del Toro; Chiriqui to Chiriqui Grande Road at continental divide Panama;Panama;Cerro Campana  RCF020  Panama;Veraguas;Santa Fe  Thraupidae  Tangara  icterocephala  STRI  Thraupidae  Tangara  inornata  LSUMZ  B-28766  Thraupidae  Tangara  inornata  STRI  JTW716  Thraupidae  Tangara  inornata  STRI  JTW718  Thraupidae  Tangara  johannae  LSUMZ  B-29956  AY383135  Thraupidae  Tangara  labradorides  LSUMZ  B-32686  AY383136  Thraupidae  Tangara  labradorides  LSUMZ  B-34976  AY383137  Thraupidae  Tangara  larvata  LSUMZ  B-34909  AY383138  Thraupidae  Tangara  larvata  LSUMZ  B34988  Thraupidae  Tangara  larvata  STRI  JTW296  Thraupidae  Tangara  lavinia  LSUMZ  B-34987  Thraupidae  Tangara  lavinia  Nevada  JKO1-234  AY383134  Venezuela: Amazonas Territory, Cerro de la Neblina Camp VII Panama;Darien;Puerto Pina Panama;Darien;Puerto Pina  AY383139  Bolivia: Dept. La Paz, Prov. B. Saavedra, 83 km by road E Charazani, Cerro Asunta Pata Brazil: Alagoas, Ibateouara, Envenho Ceimba, Usina Serra Grande Costa Rica: Prov. Heredia, 4 km SE Virgen del Socorro Brazil: Alagoas, Ibateouara, Envenho Ceimba, Usina Serra Grande Ecuador Esmeraldas Province: 30 km SE San Lorenzo Panama;Bocas del Toro; Cerro Chalite Brazil: Alagoas, Ibateouara, Envenho Ceimba, Usina Serra Grande Honduras;Departamento Atlantida;  Thraupidae  Tangara  mexicana  LSUMZ  B-18465  AY383140  Thraupidae  Tangara  inexicana  LSUMZ  B-35572  AY383141  Thraupidae  Tangara  meyerdeschauenseei  LSUMZ  B-43111  AY383142  Ecuador: Prov. Esmeraldas, 2 km W Alto Tambo; 00 550N, 78 350W Panama: Prov. Darien, about 9 km NW Cana on slopes Cerro Pirre Panama: Prov. Darien, about 6 km NW Cana  B-9758  AY383143  Panama: Prov. Darien, about 6 km NW Cana  Thraupidae  Tangara  nigrocincta  LSUMZ  Thraupidae  Tangara  nigroviridis  LSUMZ  B-34857  AY383145  Thraupidae  Tangara  nigroviridis  LSUMZ  B-1627  AY383144  Thraupidae  Tangara  palmer  LSUMZ  B11999  Bolivia: Dept. La Paz, Prov. B. Saavedra, 83 km by road E Charazani, Cerro Asunta Pata Bolivia: Dept. Santa Cruz, Serrania de Huanchaca, 21km SE Catarata Arco Iris Ecuador; Esmeraldas;  Thraupidae  Tangara  palmeri  LSUMZ  B-11999  AY383146  Costa Rica: Prov. Cartago, 28km ESE Turrialba  B34859 B-30007  AY383147  Ecuador Pichincha Province: 5 km NE Puerto Quito  Thraupidae  Tangara  palmeri  LSUMZ  Thraupidae  Tangara  parzudakii  LSUMZ  Thraupidae  Tangara  pulcherrima  MVZ169712  AY190169 AY383149  Peru: Loreto, Lower Napo region, E bank Rio Yanayacu, ca 90km N Iquitos Bolivia, Dept. Cajamarca Costa Rica: Prov. Heredia, 4 km SE Virgen del Socorro Ecuador: Prov. Pichincha, 5km S Nanegalito; 00 010N.74 410W Panama: Prov. Colon, Achitoe Road, about 2 km Bridge at Rio Providencia Peru: Dept. Cajamarca, Quebrada Las Palmas, about 13km WSW Chontali Ecuador: Prov. Pinchincha, 4 km NE Mindo, 00 010N, 78 440W Ecuador: Prov. Imbabura, 15km N Pedro Vicente Maldonado Ecuador: Prov. Esmeraldas, 30km SE San Lorenzo  Thraupidae  Tangara  punctata  LSUMZ  B-35552  Thraupidae  Tangara  punctata  LSUMZ  B-34931  AY383148  Thraupidae  Tangara  ruficervix  LSUMZ  B-33410  AY383151  Thraupidae  Tangara  ruflgula  LSUMZ  B-11930  AY383152  Thraupidae  Tangara  schrankii  LSUMZ  B-34932  AY383153  Thraupidae  Tangara  seledon  LSUMZ  B-16942  AY383154  Thraupidae  Tangara  varia  LSUMZ  B-28010  AY383155  Thraupidae  Tangara  vassorii  LSUMZ  B-1711  AY383156  Thraupidae  Tangara  velia  FMNH  390060  AY383158  Thraupidae  Tangara  viridicollis  LSUMZ  Br8090  AY383159  Thraupidae  Tangara  vitriolina  LSUMZ  B-34921  AY383160  Thraupidae  Tangara  xanthocephala  LSUMZ  B-34922  AY383161  Bolivia: Dept. Pando, Nicolas Suarez, 12km by road S of Cobija.km W on road to Mucden Peru: Dept. Pasco, Santa Cruz, about 9 km SSE Oxapampa Ecuador: Prov. Pinchincha, 5 km S Nanegalito  Thraupidae  Tangara  xanthogastra  LSUMZ  , B-34934  AY383162  Ecuador: Prov. Esmeraldas, el Placer  B-9680  AF006255  B-7260  AF006256  Bolivia: Dept. Pando, Nicolas Suarez, 12 km by road S of Cobija, 8 km W on road to Mucden Peru: Dept. Loreto, Amazonas I. Pasto, 80 km NE  Thraupidae  Tersina  viridis  LSUMZ  Thraupidae  Thlypopsis  sordida  LSUMZ  Bolivia: Dept. Santa Cruz, Velasco; Parque Nacional Noel Kempff Mercado, 86km ESE of Florida Peru: Dept. Puno, 9.5 km N of S andia  Iquito  ON  Thraupidae  Thraupis  abbas  UWBM  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  Thraupidae  Thraupis  episcopus  STRI  JTW553  Thraupidae  Thraupis  episcopus  Thraupidae  Thraupis  palinarum  Thraupidae  Thraupis  Thraupidae  Thraupis  Thraupidae Thraupidae  UWBM70095  Nicaragua;Matagalpa 10 km N;  Panama;Chiriqui;Puerto Limones, Burica Peninsula Panama;Hererra;El Limon AF290153  Venezuela, Falcon  STRI  JTW285  Panama;Bocas del Toro; Cerro Chalite  palmarum  STRI  TR-TPA3  Trinidad;Simla Research Station;  sayaca  AMNH  AMNH2241  Tiaris  bicolor  MVZ  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;  Tiaris  canora  AF310042  Cuba or Bahamas  Thraupidae  Tiaris  fuliginosa  Thraupidae  Tiaris  obscura  AF108807  Bolivia Santa Cruz Department: Velasco; 50 km ESE Florida, Arroyo del Encanto South America  Thraupidae  Tiaris  olivacea  Thraupidae  Tiaris  olivacea  Thraupidae .  Tiaris  olivacea  LSUMZ  B12612  AMNH  25429  FMNH  FM394094  AMNH  AMNH6843  AF489901 AF447375  pusilla  Dominican Republic: Provincia Independencia, Parque Nacional Sierra de Baoruco; captive Mexico;Hidalgo;  Thraupidae  Tiaris  olivacea  Thraupidae  Tiaris  olivacea  Thraupidae  Tiaris  olivacea  STRI  JTW010  Panama;Cocle; El Cope National Park  Thraupidae  Volatinia  jacarina  STRI  JTW076  Panama;Chiriqui;Puerto Limones, Burica Peninsula  Mexico;Quintana Roo; Cozumel Island, El Codral; AY700047  Panama  Thraupidae  Volatinia  jacarina  STRI  JTW709  Panama;Darien;Puerto Pina  Thraupidae  Volatinia  jacarina  STRI  TR-VJA10  Trinidad;Livestock Research Station;  Thraupidae  Volatinia  jacarina  FMNH  394403  Thraupidae  Volatinia  jacarina  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  AF489903  Bolivia;  AF290150  Bolivia, Santa Cruz  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  neu m oso opuisleuraubrirostris sipn iC Q sh N ap sa o ltrrcap s onC eilei hriundn oeM ~ypsnayisn pingu* itrartalii —  ny gsu isoe lnu ls Hetrwpingu* xanthop iun ~" C H liry au p hfeym soH th pB isi chflavicdlis rysarteliw  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 nineprimaried 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 Embenzidae  Plectrophenax  Emberizidae  Hybridization DNA Taxonomy Taxonomy • EmberiaftafflB ^ ^ ^ ^ r i b e d Emberizidae  mmmmuia •Vtifnbe/izidae* -  undescribed family Carlfilllidae Cardinalidae •VCarSISliclae Cardinalidae 'I Caipfr|Iiidae Cardinalidae ^incejae^sedis Thraupidae Thrtlfidae Thraupidae Thraupjdae Thraupidae  Thraupidae •• Thraupidae Thraupidae •Thraupidae.:. "^h.raupidrefi;Mitrospingus Thraupidae Thraupidae ' Rarulifa'e " " W<£}jjgi0§llus.s^ParJilidae Piranga Thraupidae Thraupidae Thraup.idaej i isem^ptza Paroaria Cardinalidae Thraupidae Parfifae - ^RaruWae* Tiaris Emberizidae Thraupidae " T h r a l l idae " ! Loxigrila . •EmfMirdaeEuneornis Emberizidae Thraupidae ^^Thratiipjdae^"' Loxipasser Emberizidae Thraupidae Thraupidae , Thraupjdae WMMlMMspiza' bmbeiizipae- T h r a j p d a e Certhidea Emberizidae Thraupidae Thraupidae »Ta&lIae*- - -thr^Sidae, Camarhynchus Emberizidae Thraupidae Thraupidae ' Erril^izifiae^ rhraMilatl-* Thrafpi.d.ae Saltator Cardinalidae Cardinalidae Thraupidae Emrjenzidae,^ ''Thraupidae-* Thraupidae Oryzoborus Emberizidae Thraupidae Thraupidae imatinia"'" ^ Emberjzrdae, .Thraupidae.** * Thrafpfidae Sicalis Emberizidae Thraupidae Thraupidae Emberizidae^ Fhralp.@ae\ „ Thraupidae. Haplospiza Emberizidae Thraupidae Thraupidae WMMMnia : - . j E m l S l G l a e ? ' ^\ThraupjrJae *, '^Thraupidae Coryphospingus Emberizidae Thraupidae Thraupidae E m b e r i i i l a H^ l l r t S l l i a e - ^ Thraupidae \ Emberizoides Habia  8  -  7  1  172  Posterior Probability ,  io\vK  Supporting References 1 2567  1.0  2,6,7  1 0 1.0 1.0 1.0 1 0 1.0 1.0 1 0 1.0 10 ' 1.0 1 0 1.0 1.0 1.0 1 0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.Q • 1.0 1 0 1.0 1 0  2,9 9 . Z3 1,2,6;9. 2,9 2 . - 3 . 1,4,9 1,2,4,6,9 4,9 4,9 4,9 4,9 4,9 4,9 * 2,4,9 4,9 4,9 1,6 .. < 1,69 4,9 \ 1,4,6,9 4,9 ) 4,9 1,6,9.-? 4 2,9 7 8,9 -JS"  ••  Nephelornis Conirostrum Oreomanes Tersina Poospiza Nesospingus Spindalis Phaenicophilus Chlorospingus  Parulidae Parulidae Tharupidae Tersinidae Emberizidae Thraupidae Thraupidae Thraupidae Thraupidae  7 Parulidae Parulidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae  Thraupidae Thraupidae Thraupidae Thraupidae Thraupidae Parulidae Parulidae Parulidae Emberizidae  1.0 1.0 1.0 1.0 1.0 0.84 0.84 0.84 1.0  2,4,9 2,4,9 2,4,9 4,5,8,9 2  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 : 12401252. 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. 17: 367-378. Lovette, I. J. and E. Bermingham. 2002. What is a wood-warbler? Molecular characterization of a monophyletic Parulidae. Auk 119: 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  ri 1  Terenura humeralis A Y 6 7 6 9 5 7 Terenura callinota B2198 Terenura callinota B6176 Myrmornis torquata FM391446 Myrmomis torquata A Y 6 7 6 9 7 5 Pygiptila stellaris AY676945 Thamnistes anabatinus B6152 Thamnistes anabatinus J T W 1 7 9 rjzp Thamnistes anabatinus A Y 6 7 6 9 4 6 1 H n Thamnistes anabatinus B2154 Dysithamnus mentalis B6155 Dysithamnus mentalis J T W 1 2 8 Megastictus margaritatus AY676944 T h a m n o m a n e s caesius E F 0 3 0 3 2 0 Myrmotherula sunnamensis C J W 7 4 Myrmotherula pacifica R C F 2 0 6 8 Myrmotherula pacifica J T W 7 2 2 Myrmotherula multostrista B4354 Myrmotherula cherriei R W P 1 7 2 5 7 Myrmochanes hemileucus A Y 6 7 6 9 6 5 Myrmotherula obscura AY676951 Myrmotherula menetriesii A Y 6 7 6 9 5 5 Myrmotherula longipennis A Y 6 1 2 5 6 3 Myrmotherula axillaris F M 4 3 3 4 6 9 i i-i Myrmotherula axillaris A Y 6 7 6 9 5 4 i [• n Myrmotherula axillaris T R M A X 1 U Myrmotherula axillaris J T W 5 7 4 —i n Myrmotherula axillaris J T W 6 4 4 Myrmotherula behni A Y 6 7 6 9 5 6 Myrmotherula schistacea FM429987 j n Myrmotherula schisticolor B11979 1 L j p Myrmotherula schisticolor B16048 ' — t i n Myrmotherula schisticolor B2124 Formicivora grisea A F 1 1 8 1 6 9 Formicivora rufa A Y 6 7 6 9 5 8 Myrmorchilus strig latus A Y 6 7 6 9 5 9 Microrhopias quixensis A Y 6 7 6 9 5 0 Microrhopias quixensis J T W 7 2 4 Microrhopias quixensis JTW301 Microrhopias quixensis J T W 0 7 8 Neoctantes niger AY676960 Myrmotherula fulviventris J T W 2 1 5 Myrmotherula fulviventris B11848 Myrmotherula leucophthalma AY676952 Myrmotherula leucophthalma A F 1 1 8 1 5 8 Myrmotherula hauxwelli A Y 6 1 2 5 3 2 Rhegmatorhina melanosticta A Y 6 7 6 9 7 8 Rhegmatorhina gymnops AY612581 Gymnopithys leucaspis E C G L E 1 Gymnopithys leucaspis J T W 2 6 8 Hylophylax poecilinota E C H P 0 1 Hylophylax poecilinota A Y 6 1 2 4 8 7 Phlegopsis erythroptera A Y 6 7 6 9 7 9 Phlegopsis nigromaculata A Y 6 1 2 5 7 6 Pithys albifrons AY676976 1  L  S  Phaenostictus mcleannani A Y 6 7 6 9 8 0 Phaenostictus mcleannani J T W 6 5 5 C e r c o m a c r a melanaria A Y 0 6 5 7 2 3 C e r c o m a c r a nigricans2 ; Cercomacra nigricans*' Myrmeciza hemimelaeria A Y 6 7 6 9 7 0 C e r c o m a c r a nigrescens B12661 C e r c o m a c r a serva C S E 1 C e r c o m a c r a laeta FM392376 C e r c o m a c r a tyrannina D A B 1 0 3 6 Hypocnemis hypoxantha AF118162 Hypocnemis cantator A Y 6 7 6 9 6 4 Hypocnemis cantator A F 1 1 8 1 6 3 Drymophila squamata A Y 0 6 5 7 2 2 Drymophila devillei AF118174 Drymophila caudata A F 1 1 8 1 7 3 Schistocichla leucostigma A Y 6 7 6 9 6 8 Sclateria naevia A Y 6 7 6 9 6 7 Myrmeciza longipes J T W 5 6 1 Myrmeciza longipes F M 3 9 1 4 2 0 Myrmoborus myotherinus AY676961 Gymnocichla nudiceps A Y 6 7 6 9 7 4 Gymnocichla nudiceps P A G N U P C 3 4 Pyriglena leuconota AY065724 Myrmeciza fortis AY676972 Myrmeciza immaculata B11900 Myrmeciza immaculata J T W 1 8 3 Hypocnemoides maculicauda A Y 6 7 6 9 6 6 Hylophylax naevia A Y 6 7 6 9 6 3 :  S  :  Hylophylax naevoides J T W 6 8 2 Hylophylax naevoides J T W 5 6 0 Myrmeciza loricata AY676971 Myrmeciza berlepschi A Y 6 7 6 9 7 3 Myrmeciza laemosticta , . Myrmeciza laemosticta J T W 5 7 3 Myrmeciza griseiceps A Y 6 7 6 9 6 9 Myremciza exsul * Myrmeciza exsul J T W 0 8 6 Myrmeciza exsul J T W 3 0 9 • i c h r o z o n a cincta AY676962 Cymbilaimus lineatus E F 0 3 0 3 1 5 Cyambilaimus lineatus B2252 Cyambilaimus lineatus J T W 1 5 4 T a r a b a major AY676938 T a r a b a major JTW681 T a r a b a major P A T M A PP101 Batara cinerea AY676937 Hypoedaleus guttatus AY676936 Mackenziaena severa A Y 6 7 6 9 3 5 Frederickena unduligera E F 0 3 0 3 1 6 Herpsilochmus rufimarginatus A F 1 1 8 1 5 7 Herpsilochmus alricapiTlus A Y 6 7 6 9 4 9 Sakesphorus bernardi E F 0 3 0 3 1 7 Thamnophilus bridgesi E F 0 3 0 3 2 4 Thamnophilus atrinu J T W 6 7 3 Thamnophilus atrinucha E F 0 3 0 3 2 3 Thamnophilus murinus E F 0 3 0 3 2 9 Thamnophilus schistaceus E F 0 3 0 3 3 7 Thamnophilus nigriceps E F 0 3 0 3 3 0 Thamnophilus praecox E F 0 3 0 3 3 3 Thamnophilus nigrocinereus EF030331 Thamnophilus cryptoleucus E F 0 3 0 3 2 6 Thamnophilus stictocephalus E F 0 3 0 3 3 5 Thamnophilus punctatus E F 0 3 0 3 3 4 Thamnophilus punctatus R T B 3 5 5 Thamnophilus caerulescens E F 0 3 0 3 2 5 Thamnophilus unicolor A Y 9 6 2 6 8 5 Thamnophilus aethiops A Y 9 6 2 6 8 6 Thamnophilus aroyae E F 0 3 0 3 2 2 Thamnophilus amazonicus EF030321 Thamnophilus divisorius EF030341 Thamnophilus insignis E F 0 3 0 3 2 8 Thamnophilus doliatus T R T H D 2 Thamnophilus doliatus J T W 5 8 2 Thamnophilus doliatus B10890 Thamnophilus zarumae E F 0 3 0 3 4 0 Thamnophilus tenuepunctatus E F 0 3 0 3 3 8 Thamnophilus palliatus E F 0 3 0 3 3 2 Thamnophilus torquatus E F 0 3 0 3 3 9 Thamnophilus ruficapitlus E F 0 3 0 3 3 6 Dysithamnus puncticeps B11951 Dysithamnus puncticeps JTW321 Sakesphorus canadensis E F 0 3 0 3 1 8 Sakesphorus luctuosus E F 0 3 0 3 1 9 ;  16 15 14 13 12  11 10 9 8  7  6  5  4  3  2  1  0  175-  Antbird likelihood ancestor state reconstruction  176  Woodcreeper parsimony ancestor state reconstruction G l y p h o r y n c h u s spirurus A Y 0 9 6 9 1 1 G l y p h o r y n c h u s spirurus A Y 0 9 6 9 2 2 G l y p h o r y n c h u s spirurus A Y 0 9 6 9 5 0 i G l y p h o r y n c h u s spirurus A Y 0 9 6 9 3 1 G l y p h o r y n c h u s spirurus A Y 0 9 6 9 3 9 G l y p h o r y n c h u s spirurus A Y 0 8 9 8 0 6 i G l y p h o r y n c h u s spirurus A Y 0 9 6 9 1 0 G l y p h o r y n c h u s spirurus 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 i p h o r h y n c h u s kienerii A Y 0 8 9 8 1 8 •Xiphorhynchus picus A Y 0 8 9 7 9 0 ' Xiphorhynchus picus A Y 0 8 9 8 0 2 Xiphorhynchus picus J T W 5 4 3 C a m p y l o r h a m p h u s falcular A Y 0 8 9 8 1 0 ' C a m p y l o r h a m p h u s pusillus B 3 3 8 2 2 ' C a m p y l o r h a m p h u s pusillus B 1 1 8 7 9 i C a m p y l o r h a m p h u s pusillus B 1 4 1 1 ' C a m p y l o r h a m p h u s pusillus 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 trochilirostris * C a m p y l o r h a m p h u s trochilirostris A Y 0 8 9 8 2 2 ' Drymornis bridgesii A Y 0 6 5 7 1 1 ' Ledipocolpates lachrymosus R C F 2 2 0 9 ' L e d i p o c o l p a t e s affinis D A B 1 3 6 0 ' Ledipocolpates leucogaster M E 4 0 Ledipocolpates souleyetii D A B 1 1 1 7 ' Ledipocolpates souleyetii V E L S O I ' Lepidocolaptes albolinea A Y 0 8 9 8 2 5  1 1 1  1 1  1  1 1  1  1  > Lepidocolaptes angustiro A Y 0 8 9 8 1 1 ' Xiphorhynchus 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 > Xiphorhynchus ocellatus A Y 0 8 9 8 0 4 =n X i p h o r h y n c h u s o c e l l a t u s A Y 0 8 9 8 2 0 ' Xiphorhynchus chunchotambo AY089793 'Xiphorhynchus chunchotambo A Y 0 8 9 8 1 5 ' X i p h o r h y n c h u s spixii A Y 0 8 9 8 0 1 Xiphorhynchus elegans A Y 0 8 9 8 1 2 rjrp=n Xiphorhynchus elegans AY089824 Ti==n Xiphorhynchus elegans A Y 0 8 9 8 0 5 X i p h o r h y n c h u s triangularis A Y 4 4 2 9 9 9 X i p h o r h y n c h u s triangularis A Y 0 8 9 8 2 6 Xiphorhynchus erythropygius A Y 0 8 9 8 3 2 Xiphorhynchus erythropygius J T W 6 6 9 Xiphorhynchus erythropygius J T W 1 0 5 Xiphorhynchus obsoletus A Y 0 8 9 8 2 3 X i p h o r h y n c h u s flavigaster A Y 0 8 9 7 9 9 . r — Xiphorhynchus lachrymosus A Y 0 8 9 8 0 7 • " X i p h o r h y n c h u s lachrymosus J T W 3 1 7 X i p h o r h y n c h u s 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 i p h o r h y n c h u s guttatus A Y 0 8 9 8 1 4 Xiphorhynchus susurrans C R X S U 2753 Xiphorhynchus susurrans A Y 0 8 9 8 0 0 H y l e x e t a s t e s perrotii A Y 0 8 9 8 0 9 X i p h o c o l a p t e s major A Y 0 6 5 7 1 2 Xiphocolaptes promeropirhynchus A Y 0 8 9 7 9 8 Xiphocolaptes promeropirhynchus F M 3 9 4 0 1 3 Xiphocolaptes promeropirhynchus O A B 1 3 7 7 N a s i c a longirostris A Y 0 8 9 7 9 7 D e n d r e x e t a s t e s rufigula A Y 0 8 9 8 2 9 D e n d r o c o l a p t e s certhia A Y 0 8 9 8 1 7 1  Q p Dendrocolaptes sanctithomae i^^"""" D Deennddrro c o l a pDtteess s a n c t i t h o m a e J T W 2 5 1 D e n d r o c o l a p t e s platyrostris A Y 4 4 2 9 9 0 Dendrocolaptes picumnus Dendrocolaptes picumnus B35728 Dendrocincla homochroa P A D H O PA671 Dendrocincla homochroa F M 4 3 4 0 3 5 Dendrocincla taunayi FM399181 Dendrocincla turdina K U 3 6 9 8 D e n d r o c i n c l a f atrirostris F M 4 2 9 9 4 8 Dendrocincla f fuliginosa F M 3 9 1 2 9 8 Dendrocincla anabatina K U 5 3 6 Dendrocincla f neglecta E C D F U 1 Dendrocincla f meruloides T R D F U 1 Dendrocincla f ridgewayi J T W 2 5 3 Dendrocincla f ridgewayi J T W 7 4 4 Dendrocincla tyrannina F M 4 2 9 9 4 6 Dendrocincla merula F M 3 8 9 8 1 0 Sittasomus griseicapillus A Y 0 8 9 7 9 6 Sittasomus griseicapillus F M 3 9 2 4 1 9 Sittasomus griseicapillus F M 3 4 3 2 3 1 Deconychura longicauda B7565 Deconychura longicauda B2088 Deconychura longicauda C R DLQ2761 16  15  14  13  12  11  10  9  8  7  Time (Ma)  6  5  4  3  2  1  o 177  G l y p h o r y n c h u s spirurus A Y 0 9 6 9 1 1 G l y p h o r y n c h u s spirurus A Y 0 9 6 9 2 2 G l y p h o r y n c h u s spirurus A Y 0 9 6 9 5 0 Glyphorynchus spirurus A Y 0 9 6 9 3 1 G l y p h o r y n c h u s spirurus A Y 0 9 6 9 3 9 Glyphorynchusspirurus AY089806 G l y p h o r y n c h u s spirurus A Y 0 9 6 9 1 0 G l y p h o r y n c h u s spirurus A Y 0 9 6 8 9 1 G l y p h o r y n c h u s spirurus A Y 0 9 6 8 9 9 X i p h o r h y n c h u s kienerii A Y 0 8 9 8 1 8 Xiphorhynchus picus A Y 0 8 9 7 9 0 Xiphorhynchus picus A Y 0 8 9 8 0 2 Xiphorhynchus picus J T W 5 4 3 C a m p y l o r h a m p h u s falcular A Y 0 8 9 8 1 0 C a m p y l o r h a m p h u s pusillus B 3 3 8 2 2 C a m p y l o r h a m p h u s pusillus B 1 1 8 7 9 C a m p y l o r h a m p h u s pusillus B 1 4 1 1 C a m p y l o r h a m p h u s pusillus 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 trochilirostris C a m p y l o r h a m p h u s trochilirostris A Y 0 8 9 8 2 2 D r y m o r n i s bridgesii A Y 0 6 5 7 1 1 Ledipocolpates lachrymosus R C F 2 2 0 9 L e d i p o c o l p a t e s affinis D A B 1 3 6 0 Ledipocolpates leucogaster M E 4 0 L e d i p o c o l p a t e s souleyetii D A B 1 1 1 7 L e d i p o c o l p a t e s souleyetii V E L S O I Lepidocolaptes albolinea A Y 0 8 9 8 2 5 L e p i d o c o l a p t e s angustiro A Y 0 8 9 8 1 1 Xiphorhynchus 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 Xiphorhynchus ocellatus A Y 0 8 9 8 0 4 Xiphorhynchus ocellatus A Y 0 8 9 8 2 0 Xiphorhynchus chunchotambo A Y 0 8 9 7 9 3 Xiphorhynchus chunchotambo A Y 0 8 9 8 1 5 X i p h o r h y n c h u s spixii A Y 0 8 9 8 0 1 Xiphorhynchus elegans A Y 0 8 9 8 1 2 Xiphorhynchus elegans A Y 0 8 9 8 2 4 Xiphorhynchus elegans A Y 0 8 9 8 0 5 X i p h o r h y n c h u s triangularis A Y 4 4 2 9 9 9 X i p h o r h y n c h u s triangularis 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 i p h o r h y n c h u s 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 Xiphorhynchus obsoletus A Y 0 8 9 8 2 3 X i p h o r h y n c h u s flavigaster A Y 0 8 9 7 9 9 Xiphorhynchus lachrymosus A Y 0 8 9 8 0 7 Xiphorhynchus lachrymosus J T W 3 1 7 X i p h o r h y n c h u s 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 i p h o r h y n c h u s guttatus A Y 0 8 9 8 1 4 Xiphorhynchus susurrans C R X S U 2753 Xiphorhynchus susurrans A Y 0 8 9 8 0 0 H y l e x e t a s t e s perrotii A Y 0 8 9 8 0 9 Xiphocolaptes major A Y 0 6 5 7 1 2 Xiphocolaptes promeropirhynchus A Y 0 8 9 7 9 8 Xiphocolaptes promeropirhynchus F M 3 9 4 0 1 3 Xiphocolaptes promeropirhynchus O A B 1 3 7 7 N a s i c a longirostris A Y 0 8 9 7 9 7 D e n d r e x e t a s t e s rufigula A Y 0 8 9 8 2 9 D e n d r o c o l a p t e s cerfhia A Y 0 8 9 8 1 7 Dendrocolaptes sanctithomae Dendrocolaptes sanctithomae JTW251 D e n d r o c o l a p t e s platyrostris A Y 4 4 2 9 9 0 Dendrocolaptes picumnus Dendrocolaptes picumnus B35728 Dendrocincla homochroa P A D H O PA671 Dendrocincla homochroa F M 4 3 4 0 3 5 D e n d r o c i n c l a taunayi F M 3 9 9 1 8 1 D e n d r o c i n c l a turdina K U 3 6 9 8 D e n d r o c i n c l a f atrirostris F M 4 2 9 9 4 8 D e n d r o c i n c l a f fuliginosa F M 3 9 1 2 9 8 Dendrocincla anabatina K U 5 3 6 Dendrocincla f neglecta E C D F U 1 Dendrocincla f meruloides T R D F U 1 D e n d r o c i n c l a f ridgewayi J T W 2 5 3 D e n d r o c i n c l a f ridgewayi J T W 7 4 4 D e n d r o c i n c l a tyrannina F M 4 2 9 9 4 6 Dendrocincla merula F M 3 8 9 8 1 0 S i t t a s o m u s griseicapillus A Y 0 8 9 7 9 6 S i t t a s o m u s griseicapillus F M 3 9 2 4 1 9 S i t t a s o m u s griseicapillus F M 3 4 3 2 3 1 Deconychura longicauda B7565 Deconychura longicauda B2088 Deconychura longicauda C R DLQ2761  Tachyphonus coronatus GAV826 Tachyphonus rufus y. Tachyphonus rufus T R C C T R F 3 Tachyphonus rutus FM392631 Ramphocelus sanguinolentus U15718 •° Ramphocelus bresllius U15724 Ramphocelus carbo U15723 Ramphocelus nigrogularis U15721 Ramphocelus dimid P A RDI PA75 Ramphocelus p.isserinii U15717 Ramphocelus costaricensis JTW396 Ramphocelus icteronotus U15719 Ramphocelus icteronotus JTW611 Tachyphonus surinarnus AF006253 Eucornetis penicillata DAB1513 Eucometis penicillata B18544 Lanio versicolor AF0O6239 Lanio leucothorax JTW572 Lanio aurantius H O DHB3785 iryphospingus cucull scucullatusAF447366 chyphonus delatrii ii JJTW257 Tachyphonus delatrii JTW634 Tachyphonus cristatus ROP231 Tachyphonus luctu PA T L C 190 Tachyphonus luctuosus GAV1988 Tangara labradorides AY383136 Tangara labfadbrides AY383137 Tangara (astuosa AY383123 Tangara seledon AY383154 Tangara cyanocephala AY383117 Tangara desmaresli AY383120 1  a  T.id  «Tangara chlanais AY383110  Tangara Tangara Tangara Tangara • Tangara • Tangara Tangara Tangara Tangara  callophrys AY383107 velia AY383158 mexicana AY383140 mexicana AY383141 inornata AY383134 tomaia JTW718 chrysolis AY38311 1 xanlliocephala AY383161 arthus AY383105 • Tangari arthus AY383106 Tangara icterocephala JTW093 Tangara icterocephala - T a n g a r a llorida AY383122 Tangara florida JTW169 Tangara johannae AY383135 Tangara parzudakii AY383147 Tangara schrankii AY383153 Tangara cyanotis AY383119 Tangara lavinia AY383139 Tangara lavinia * Tangara gyrola T R 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 p a l m a r u m ^ Thraupis abbas D A B l 315 Thraupis sayaca A L P 1 5 2 - 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 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  1,'ifKjara  Efamgsta rnHanochlamys  Bangsia arcaei JTW157 * Creurgops dentata AF0O6224 Creurgops verticals AY190166 Loxigilla portoricerisis AF489886 Loxigilla violacea AF489887 Poospiza baeri AY005200 i 11• i. • •• n • • .• n \ • .::i AF489885 Loxipasser anoxanthus AF489888 Tiaris canora AF310042 Certhidea olivacea AF108806 Certhidea lusca AY672052 Pinaroloxias inornata AF108791 Geospiza magniroslris A F 108778 Geospiza scandens AF108779  Geospiza conirostris AF108769 ["ito Geospiza lortis AF108771 f j = » Geospiza ditticilis AF108788 ' " G e o s p i z a 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 P A C F A 2 Coereba flaveola P A CFA11367 Coereba flaveola S V CFA2129 Coereba (laveola JA C F A 4 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 F M 334590 Saltator coerulescens AF290154 Saltator albicollis E C SAL3580 Saltator albicollis P E SAL5251 Saltator albicollis E C S A L 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 T R 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 E C O A N l Sporophila plumbea AY115407 Sporophila collaris AF489895 Sporophila leucoptera AY387431 Phrygilus alaudinus AY0O5218 Diglossa humeralis AF310050 Diglossa major AF290155 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 n  Sli.llls luteOla gfa Sicalis tlaveola AY491528 o Nemosia pileata AF006241 - Sericossypha albocnstata AF006251 Cyanerpes cyaneus HA C N N HA82 Cyanerpes cyaneus TR C C C C N 1 Cyanerpes caeruleus E C C C E 1 6 1 2 Cyanerpes caeruleus TR C C E 1 Cyanerpes lucidius PA CLC34493 Cyanerpes nitidus FM390048 Tersina viridis AF006255 Dacnis venusta B82192 Dacnis venusta * Dacis cayana UL102 Dacnis cayana T R D A C l Tangara pulcherrima AY190169 Chlorophanes spiza H O C S P HA51 Chlorophanes spiza TR C S P 4 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  Time (Ma)  180  3  Tanager likelihood ancestor state reconstruction  Tachyphonus coronatus GAV82B Tachyphonus rufus Tachyphonus rufus TR C C 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 E C SAL3580 Saltator albicollis PE SAL5251 Saltator albicollis E C 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 O F U HA37 Oryzoborus angolensis E C 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 E C 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 C S P 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. 7 II  CaUnn  I.M... 1.1 . M f-  AFaesoi .  rionmontiou* AY11770S 1 J  I'-,v. 1 . • -m l  A J '.L" i IPurocaliis :>i I !••riocumaiiir, . M1 ,1AF472376 At 1 ; I ''j P S K O P f c i r a d H C n i u u i s AF472373 PWW.L*U* dBcumoiLis AF472375 ,.Anv;-.>;i 1  i> ..i. < • .in. •. i) I, i-... ,u-. AY 11 7699 a :hK «9l*ri AF4JMJ0 Psoroeolk.1 wagtert AF472J6B Psarocolius auoviruns AF 172 366 r  f'-.,.i<,i-..iln:.,.i.,i|i|..tir •. AF47?7i5.. .,.,,!„•  I.I • 11r 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  . • •  5 l IXTIWUA i'l F»93(W  » mK i ua tm l u*  i . i - AF 310064 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 AF069277  IS bo M lt H i • I I • "I • i'i -1."• • •.,  .:-  tonus uy.monU AF 0992SQ AmUytemis m*n**wus AVI 17722 AmhtyCPreus AmHycacus twlo-jiiecir. AF47! J98 ip-.< r>g»<im^ AF089046 mousa Af09902'. pui 1**4.,™* AF089046 ih, LIS bulk,-. AFOB9M2 AqMaiia Icieroceptolu? AFOB9007 Aipi l.ii.i-. AF0B9Q09 :-i 11 i i...' AF0MO66 gurahuro AFU89uil Piaui)uli;«ios viicbtcns AF089052 us AF089020  hdmaM ir US culM f  rLifit.ipilL.i(Hnudoterse ii cuH i us  I f t l M ryanupua AF 280174 AiH'n'. >.pil...i|:lilh:ilmin AFQB9013 ' , , j • .. AF0B9O37 ymnomyslai mtuiainiis AF0B9026 Af089039  M p. ..., r.rii, i "  <im I f III Euphadu* iiatolinui A F08902 3 Eiipliagir- tyan«c[twlur> AF DB9024 11 L-. .,.„-. .,.„.,. ,i, AF089058 CMwniu! PA QME PP15 Qui see his major AF0B90SS nn:i.lcanu. AF 089056 ausr»j<i PS0NH14W OuiaCJUS 1 9 IM AFOBBOi? •i i GU M i n Qi4«calu* NI dNGiSt UMPJMh AF0S9QQ6 A.j. I.,,,,-. <.!II|I».TIIISAF0B9012 • • ni%tricuo< us \f»mtkm* AF280173 VLIS rufoiuilMiis A F 08934* VafitwIiiM oryiivurn AF08B060 Sr^ihHlurj oryzrvori  menB fln QusicU Ij T. ... • i j'. 11 . .I. AquhmAnelar Afoeaon UuHK tli Ui Wm AF0S9O41  

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