Measuring the Additive Effects of Predation Across Spatial Scales Using Capture-Recapture-Recovery Data

• Activity Number: 125 - A New Era of Mark-Recapture: Advances in Bayesian Methods for Modeling and Inference
• Type: Topic-Contributed
• Date/Time: Monday, August 9, 2021 : 1:30 PM to 3:20 PM
• Sponsor: Section on Bayesian Statistical Science
• Author(s): Quinn Payton*
• Companies: Real Time Research
• Keywords: capture–recapture–recovery; compensatory mortality; population dynamics; predator–prey dynamics; hierarchical Bayesian modelling; state-space models

Abstract

The degree to which predation is an additive versus compensatory source of mortality is often a critical uncertainty in studies of predator-prey interactions. Evaluating a possible relationship between predation and survival by measuring correlations (as is common) limits inference to only whether evidence of a relationship exists. We constructed a multinomial state-space model to instead directly measure relationships between predation and survival probabilities using capture-recapture-recovery data. We then investigated an 11-year dataset of tagged steelhead trout which were exposed to predation by Caspian Terns during migration through imbricate spatial scales (smolt out?migration and smolt?to?adult returns), jointly estimating probabilities of steelhead survival and mortality due to several causes. We found evidence that increases in predation were associated with decreases in survival in all years and spatial scales evaluated. On average, observed annual survival probabilities were estimated to be 29.0% (22.7–34.3) less than baseline (i.e. estimated survival in the absence of tern predation) during the smolt life stage and 71.1% (65.3–76.8) less than baseline to adulthood.