Scaling marine fish movement behavior from individuals to populations.

ABSTRACT: Understanding how, where, and when animals move is a central problem in marine ecology and conservation. Key to improving our knowledge about what drives animal movement is the rising deployment of telemetry devices on a range of free-roaming species. An increasingly popular way of gaining meaningful inference from an animal's recorded movements is the application of hidden Markov models (HMMs), which allow for the identification of latent behavioral states in the movement paths of individuals. However, the use of HMMs to explore the population-level consequences of movement is often limited by model complexity and insufficient sample sizes. Here, we introduce an alternative approach to current practices and provide evidence of how the inclusion of prior information in model structure can

SUBMITTER: Griffiths CA 

PROVIDER: S-EPMC6065275 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature