A Novel Method to Estimate Prey Contributions to Predator Diets

Stomach content data are frequently used to characterize predator feeding habits, often by describing the proportional contribution by weight or number of each prey type (diet fractions). These data pose several statistical challenges for analysis and estimation that have hindered our ability to create quantitative diet fraction estimates from stomach content data. To address these challenges, we developed a novel, likelihood-based mixture model to quantitatively estimate diet fractions. Simulation testing indicated that estimated diet fractions from the mixture model were more precise than those estimated either from a (stomach-mass) weighted mean or the sample mean, and were more accurate than a sample mean. Additionally, we applied the mixture model, a weighted mean, and sample mean to stomach content data for multiple types of predators. For three of four of these datasets, the mixture model demonstrated higher precision than and similar accuracy to a weighted-mean, and similar precision and better accuracy than a sample mean. The mixture model represents an important step in advancing statistical methods to address the challenges of stomach content data.

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