Collaborative Research: Disentangling Biological and Environmental Drivers of Diversification in the Andean Flora

PROJECT SUMMARY Overview: Spurred by recent mountain uplift, topographic complexity, and an abundance of ecological interactions, tropical Andean plant clades exhibit some of the highest rates of diversification across the Tree of Life. While this pattern is well-established, the processes that generate this stunning pattern remain understudied. To gain insight into Andean plant diversification, the proposed research adopts an integrative framework that ties novel technique development to the application of these new methods in four Andean-centered plant clades that span two distinct Andean habitats: mid-elevation cloud forests and high-elevation grasslands. First, we establish a phylogenetic framework (including uncertainty) for each clade using genome skim and targeted sequence data. To explore phylogenetic signal and infer the most accurate phylogenies possible, we adapt an existing phylogenomic pipeline, SISRS (Schwartz et al. 2015), to incorporate complexities common in plant genome evolution, including polyploidy and paralogy. Second, we develop novel state-dependent diversification models to jointly infer the roles of long-distance dispersal, movement along elevational gradients, and trait evolution in lineage diversification. By applying this shared framework to multiple clades that share Andean occurrence, but differ in environmental preferences, morphology, and ecological interactions, we will capture the complexity of species diversification processes in the tropical Andes, the World’s most species-rich biodiversity hotspot. Intellectual Merit: We examine the roles of abiotic and biotic drivers of Andean plant diversification across two integrated aims. In both, we develop new computational tools and statistical models applicable beyond our study system. In Aim 1, we determine species relationships in focal lineages, while closely examining genomic data to ensure accurate phylogenetic resolution. This allows us to determine the impact of locus selection on phylogenetic inference, as well as to quantify occurrence of introgression and incomplete lineage sorting. In Aim 2, we develop state-dependent diversification models in RevBayes and apply these to newly-inferred phylogenies. These models will be the first to integrate three aspects of organismal evolution that are commonly studied independently: biogeography, trait evolution, and lineage diversification. This will be one of the first tests to test the relative roles of abiotic and biotic drivers of diversification in a single integrated framework. By comparing across clades, we will determine the generality (or idiosyncrasy) of biogeographic and ecological processes facilitating rapid radiation in tropical Andean plants. This research enables not only a clearer understanding of our focal groups, but also a more nuanced understanding of diversification processes in topographically complex regions more broadly. Further, with an emphasis on collecting phylogenomic, morphological, and distribution data from herbaria, this research highlights the multi- dimensional importance of natural history collections in cutting-edge biological research. Broader Impacts: A major goal of this proposal is to train and support the development of a diverse future workforce in evolutionary biology. We accomplish this via the development Course-based Undergraduate Research Experiences (CUREs), in consultation with an expert in inclusive pedagogy, to support the early research training of students from groups underrepresented in STEM; by holistically training a diverse team of researchers deliberately recruited from community programs that seek to increase participation in STEM, including SACNAS and DiversifySEE; developing a computational outreach program to reach communities of Native Hawaiian women; and by training international teams composed of students both from the US and Colombia, allowing us to center the importance of diverse perspectives. Further, we will build scientific infrastructure via the development of new methods, including an expansion of the open- source SISRS pipeline and diversification models in RevBayes. This research both generates and relies on herbarium collections for sequence and trait data, allowing us to add to biological collections and genomic resources, develop efficient protocols, and demonstrate the 21st century relevance of natural history collections. Finally, this collaborative research will build capacity and infrastructure in three EPSCoR states, as well as provide opportunities for diverse US-based undergraduates in these states to participate in international fieldwork and computational biology.