MSB-ECA: Phylogenetically-informed modeling of the regional context of community assembly

Utah State University, Logan UT

Investigators

Abstract

Ecologists have made great progress using observations from projects such as the National Ecological Observatory Network (NEON) to understand how communities of species will adapt to environmental change. This project builds on this progress by examining communities of species within the context of their evolutionary history, asking whether close relatives respond similarly (or differently) to environmental change. This research will focus first on modelling the plants, mammals, and birds observed at NEON sites, using this information to predict regions where non-native species could invade and degrade the valuable ecosystem services that these communities provide. Building on these foundations, this project will statistically model and predict species? associations, giving insight into costly beetle pest outbreaks and ticks that can carry diseases. As part of this work, teaching materials will be developed to help under-represented groups develop data science skills and make use of the data publicly available from NEON. Additionally, the project will develop a data science class for the Native American STEM Mentorship Program at Utah State, focusing on the use and analysis of NEON data. Integrating the cross-scale drivers of the distribution of biodiversity requires an understanding of both ongoing ecology and historic evolution. Species? shared evolutionary history reflects the biogeographical history that shaped them, and can inform us of constraints on species? ecology in the present. This proposal will integrate local-scale ecological community assembly with macro-scale regional assembly and trait evolution. Evolution is the context within which ecological processes take place: there can be no macro-scale synthesis of ecology without addressing phylogenetic context. This will be achieved through three major research objectives: (1) develop and release new datasets of North American plants, birds, mammals, beetles, and ticks found at and around NEON sites; (2) extend previous analyses (Phylogenetic Generalized Linear Mixed Models; PGLMMs) of the evolution of species? environmental tolerances to test macro-evolutionary models of local-scale competition within the plants, bird, and mammals of the NEON sites; and (3) extend these models to incorporate cross-guild interactions, focusing on plant-beetle and mammal-tick associations. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.