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Elevational Differentiation Increases Rates of Trait Evolution but Not Diversification in Neotropical Passerine Birds

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Elevational Differentiation Increases Rates of Trait Evolution but Not Diversification in Neotropical Passerine Birds Elevational Differentiation Increases Rates of Trait Evolution but not Diversification in Neotropical Passerine Birds by Vanessa Estefanía Luzuriaga-Aveiga A thesis submitted in conformity with the requirements for the degree of Master of Science Department of Ecology and Evolutionary Biology University of Toronto © Copyright by Vanessa Estefanía Luzuriaga-Aveiga 2018 Elevational Differentiation Increases Rates of Trait Evolution but not Diversification in Neotropical Passerine Birds Vanessa Estefanía Luzuriaga-Aveiga Master of Science Department of Ecology and Evolutionary Biology University of Toronto 2018 Abstract The importance of ecologically-mediated divergent selection in elevating rates of trait evolution has been poorly studied in the most species-rich biome of the planet, the continental tropics. I performed a macroevolutionary analysis of trait divergence and diversification rates across closely-related pairs of passerine birds, belonging to the Amazon basin and adjacent Andean slopes, to assess whether the difference in elevational range separating species pairs influences the speed of trait evolution and diversification rates. Difference in elevation was used as a proxy for the degree of ecological divergence. I found that the amount of elevational separation is associated with faster differentiation of song frequency, a trait important for premating isolation, and several morphological traits, which may contribute to extrinsic postmating isolation. However, ecological differentiation does not primarily drive bird diversification and, thus, may have limited influence on patterns of species richness along the eastern slope of the tropical Andes. ii Acknowledgements I will like to especially thank my supervisor, Jason Weir, for his extraordinary guidance and support during the development of this research project. I thank Santiago Claramunt and Nick Mandrak, for their constructive feedback during committee meetings. I also thank my labbies: Maya Faccio, Ashley Bramwell and Sean Anderson for their helpful advice. I thank Michael Swift too, for his help with the data collection of song files. I thank the National Secretariat of Science, Technology and Innovation (SENESCYT) for awarding me with a full graduate fellowship, from the Ecuadorian government, to pursue my graduate studies at the University of Toronto. iii Table of Contents Acknowledgements ........................................................................................................................ iii Table of Contents ........................................................................................................................... iv List of Tables ................................................................................................................................. vi List of Figures ............................................................................................................................... vii List of Appendices ......................................................................................................................... ix Chapter 1: Elevational Differentiation Increseses Rates of Trait Evolution but not Diversification in Neotropical Passerine Birds ...........................................................................1 Introduction .................................................................................................................................1 Methods .......................................................................................................................................5 2.1 Data collection .....................................................................................................................5 2.2 Time estimation ...................................................................................................................6 2.3 Song analysis .......................................................................................................................7 2.4 Morphometric analysis.........................................................................................................8 2.5 Patterns across the elevational gradient ...............................................................................8 2.6 Evolutionary rates and gradient effect .................................................................................9 2.7 Age distribution and diversification rates ..........................................................................10 Results .......................................................................................................................................11 3.1 Songs ..................................................................................................................................11 3.2 Morphometrics ...................................................................................................................11 3.3 Patterns across the elevational gradient .............................................................................12 3.4 Age distribution and diversification rates ..........................................................................12 Discussion .................................................................................................................................13 4.1 Speciation ...........................................................................................................................16 4.2 Conclusions ........................................................................................................................18 References ......................................................................................................................................20 iv Appendices .....................................................................................................................................43 v List of Tables Table 1: Loadings of the PCA analysis for song measurements. ................................................. 31 Table 2: Loadings of the PCA analysis for morphometric measurements. .................................. 31 Table 3: Comparison of support for Brownian Motion (BM) and Ornstein–Ulhenbeck models of trait evolution. ΔAICc scores (AICc for each model – smallest AICc score) and Akaike weights (AICc weight) were used as metrics of model support. N is the number of model parameters. The best-fit model (bolded) has the smallest ΔACc (a value of 0) and largest AICc weight. Values for the slope of β (change in evolutionary rate with elevational difference per 1000 meters) and 95% confidence intervals are shown for models that test for the elevational difference. Change in β shows the proportional increase in β gained with 2000 meters increase in elevational difference. ....................................................................................................................................................... 32 vi List of Figures Figure 1: Map of the study region, outlined in orange, includes the Guiana shield, Amazonian biome and adjacent eastern slopes of the Andes (from Bogotá-Colombia to Cochabamba-Bolivia) that drain into the Amazon basin. ................................................................................................. 36 Figure 2: Measurements taken from an example song spectrogram. ........................................... 36 Figure 3: Example of morphometric measurements taken from museum specimens. ................ 37 Figure 4: Consensus phylogenetic tree of species pairs with cyt b within my dataset. Three clades are differentiated: Furnarioidea in blue, Tyrannoides in green, and Oscines in orange. .............. 39 Figure 5: Change in evolutionary rates of traits as a function of midpoint elevational difference between species pairs of birds from the Amazon basin and adjacent Andean slopes. Maximum likelihood estimates for the best fitting model are shown for songs (frequency (PC1) in green and length (PC2), in black) and morphometrics (body size (PC1) in orange, bill width (PC2) in purple, tail length (PC3) in yellow, bill length (PC4) in red, wing length (PC5) in blue and bill depth (PC6) in pink). All characters, except song length and body size, best fit models in which rates of evolution increased with increasing difference in midpoint elevation. Song frequency bill width, tail length, bill length, and wing length were best fitted by Ornsetin-Ulhenbeck (OU) models, with other models best fit by Brownian Motion (BM). ML estimates for morphometrics are shown with a solid line for oscines and with a dashed line for suboscines wing length and bill depth, because those traits best supported a model with separate rates between these groups. At the bottom-right, I show an example of a morphologically-differentiated species pair, Campylorhamphus pusillus – C. procurvoides, with a Euclidean distance for bill length is 0.43 and difference in midpoint elevational ranges of 1320m. In contrast, the bottom-left corner illustrates a sister species pair, Dendroplex kienerii – D. picus, with weak morphometric differentiation (Euclidean distance for bill length = 0.18) that occur at similar elevations (Δ midpoint elevational range = 400m). Bird illustrations were taken with permission from Schulenberg et al. (2010). ................................... 39 Figure 6: Mean PC values for behavioral and morphometric traits for individual species as a response of increasing elevation. Song traits are shown in (a-b) and morphometric traits in (c-h). Lines represent phylogenetically-corrected
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