Data-driven insights into constraints in ecological, evolutionary, and human-managed systems

Abstract

Ecological patterns are shaped not only by what is possible, but by the constraints that define what is not. Arising from environmental conditions, ecological interactions, evolutionary history, and resource limitations, these constraints bound the space of viable forms and strategies, as well as the configurations that can emerge. In this dissertation, I develop data-driven approaches to identify and interpret constraints across ecological and environmental contexts.Chapter 1 examines how the global distribution of avian nest architectures reflects constraints imposed by predation risk and climate on reproductive strategies. Chapter 2 investigates evolutionary constraints in avian morphology, revealing persistent gaps in trait space shaped by species interactions over evolutionary time. Chapter 3 explores how resource constraints can guide more efficient agricultural production, showing that irrigation water use can be substantially reduced while maintaining yields through optimized crop redistribution across the United States. These studies show how constraints structure ecological function, evolutionary diversification, and agricultural production, and demonstrate how integrating large-scale ecological and environmental data with quantitative approaches can reveal patterns, uncover underlying mechanism, and inform actionable strategies.