Animal movement tools (amt): R package for managing tracking data and conducting habitat selection analyses.

ABSTRACT: Advances in tracking technology have led to an exponential increase in animal location data, greatly enhancing our ability to address interesting questions in movement ecology, but also presenting new challenges related to data management and analysis. Step-selection functions (SSFs) are commonly used to link environmental covariates to animal location data collected at fine temporal resolution. SSFs are estimated by comparing observed steps connecting successive animal locations to random steps, using a likelihood equivalent of a Cox proportional hazards model. By using common statistical distributions to model step length and turn angle distributions, and including habitat- and movement-related covariates (functions of distances between points, angular deviations), it is possible to make

SUBMITTER: Signer J 

PROVIDER: S-EPMC6362447 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature