Inferring an animal’s environment through biologging: quantifying the environmental influence on animal movement

Background Animals respond to environmental variation by changing their movement in a multifaceted way. Recent advancements in biologging increasingly allow for detailed measurements of the multifaceted nature of movement, from descriptors of animal movement trajectories (e.g., using GPS) to descrip...

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Veröffentlicht in:	Movement ecology Jg. 8; H. 1; S. 40
Hauptverfasser:	Eikelboom, J. A. J., de Knegt, H. J., Klaver, M., van Langevelde, F., van der Wal, T., Prins, H. H. T.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London BioMed Central 19.10.2020 BioMed Central Ltd BMC
Schlagworte:	accelerometers algorithms Analysis Animal Ecology animal physiology artificial intelligence Behaviour classification Biomedical and Life Sciences Case studies Collective movement Conservation Biology/Ecology Cows Data mining ecology environmental factors Foraging Global Positioning System global positioning systems grasses grazing Group dynamics Lactation landscapes Life Sciences Machine learning Methodology Methodology Article milking neck prediction statistical analysis Terrestial Ecology Netherlands Collective movement Behaviour classification Lactation Foraging Machine learning Random forest regression Cows Resource availability Group dynamics Support vector machine
ISSN:	2051-3933, 2051-3933
Online-Zugang:	Volltext
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