UW Aquatic & Fishery Sciences Quantitative Seminar

Jin Gao

JISAO; University of Washington

Predicting impacts of fishing: perspectives from nonlinear population dynamics and life history evolution

Abstract

Fishing induces many changes to a population including both demographic and life history characteristics. I would like to talk about two statistical methods that I have used to predict recruitment and evolutionary potential in size separately. The first study is to extend the current nonlinear state space reconstruction (SSR) framework to incorporate population age structure. We show that including age specific dynamics improves forecast ability of recruitment compared to traditional method and SSR without age structure. The second study is about using a Bayesian hierarchical model to estimate the genetic basis of growth rate, which forms the foundation of evolutionary changes under selective fishing pressure.