B1499
Title: State-space models in ecology: Opportunities and challenges
Authors: Marie Auger-Methe - The University of British Columbia (Canada) [presenting]
Abstract: State-space models (SSMs) are increasingly used in ecology to model time-series such as animal movement paths and population dynamics. This type of hierarchical model is structured to account for two levels of variability: biological stochasticity and measurement error. Because they can account for large measurement error, they are particularly popular to study marine animals for which it is often hard to get accurate time-series of geographic locations and population counts. SSMs are flexible. They can model linear and nonlinear processes using a variety of statistical distributions. We will use marine movement data to introduce SSMs and to demonstrate when these models are useful and when they can fail. We will also highlight new tools that can help fit state-space models to data.
