Quantifying Predator-Prey Interactions: Methods, Challenges, and Applications

Abstract

Knowledge of predator-prey interactions is vital in many subfields of ecology, including food web ecology, behavioral ecology, and population ecology. Information on predator-prey interactions is obtained from a variety of sources, including stomach contents, biochemical tracers such as stable isotopes, fecal matter, and direct observation. These data sources are used to infer the predator’s diet and each presents analytical and interpretation challenges. In this dissertation, I pursue research to improve the analysis, interpretation, and application of varied data sources to study predator-prey interactions. My first chapter develops a mixture model to increase the accuracy and precision of diet estimates from stomach content data by addressing several challenges inherent to most stomach content datasets. I extend this model in my second chapter to address sample interdependence, which is a common issue due to sample collection methods. My third chapter addresses the challenges of applying stable isotope analysis to jellyfish due to their unique physiology and proposes a path forward to be able to use this data source effectively. My fourth chapter predicts the effect of hypoxia, a common environmental stressor, on energy flow from zooplankton to zooplanktivorous fish by merging multiple data sources in a Bayesian integrated assessment. Together, my dissertation research identifies and addresses some common challenges of analyzing predator-prey interactions.