Registration & talk details
This talk is one of Data Science Applied Research and Education Seminar (ARES) series. Learn more and register for this talk here.
Talk Title: Understanding animal movement with state-space models
Abstract: Movement data have become essential for our understanding of animal ecology. However, such data are associated with a broad range of challenges. For example, tracking the movement of many species (e.g. fish and small birds) is still limited to inaccurate technology, such as light-based geolocation. Making behavioral and spatial inferences based on such data is difficult because the tracks they create are not good representations of the animals’ movement. Understanding the behavior of animals using movement data is challenging even with accurate movement data, because we are often making inference on a process that is not observed directly. Through a set of examples from a broad range of animals (fish, bears, marine mammals), I will demonstrate how a state-space modeling framework can improve our understanding of animal movement.