Using piecewise regression to identify biological phenomena in biotelemetry datasets.

ABSTRACT: Technological advances in the field of animal tracking have greatly expanded the potential to remotely monitor animals, opening the door to exploring how animals shift their behaviour over time or respond to external stimuli. A wide variety of animal-borne sensors can provide information on an animal's location, movement characteristics, external environmental conditions and internal physiological status. Here, we demonstrate how piecewise regression can be used to identify the presence and timing of potential shifts in a variety of biological responses using multiple biotelemetry data streams. Different biological latent states can be inferred by partitioning a time-series into multiple segments based on changes in modelled responses (e.g. their mean, variance, trend, degree of autocorrel

SUBMITTER: Wolfson DW 

PROVIDER: S-EPMC9540865 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature