Identification of reindeer fine-scale foraging behaviour using tri-axial accelerometer data.

ABSTRACT: Animal behavioural responses to the environment ultimately affect their survival. Monitoring animal fine-scale behaviour may improve understanding of animal functional response to the environment and provide an important indicator of the welfare of both wild and domesticated species. In this study, we illustrate the application of collar-attached acceleration sensors for investigating reindeer fine-scale behaviour. Using data from 19 reindeer, we tested the supervised machine learning algorithms Random forests, Support vector machines, and hidden Markov models to classify reindeer behaviour into seven classes: grazing, browsing low from shrubs or browsing high from trees, inactivity, walking, trotting, and other behaviours. We implemented leave-one-subject-out cross-validation to assess ge

SUBMITTER: Rautiainen H 

PROVIDER: S-EPMC9490970 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature