|
|
| Heerah, Karine; Woillez, Mathieu; Fablet, Ronan; Garren, Francois; Martin, Stephane; De Pontual, Helene. |
| Background Movement pattern variations are reflective of behavioural switches, likely associated with different life history traits in response to the animals’ abiotic and biotic environment. Detecting these can provide rich information on the underlying processes driving animal movement patterns. However, extracting these signals from movement time series, requires tools that objectively extract, describe and quantify these behaviours. The inference of behavioural modes from movement patterns has been mainly addressed through hidden Markov models. Until now, the metrics implemented in these models did not allow to characterize cyclic patterns directly from the raw time series. To address these challenges, we developed an approach to i) extract new metrics... |
| Tipo: Text |
Palavras-chave: Fourier transform; Non negative matrix factorization; Classification; Animal behaviour; European sea bass; Movement ecology; Diurnal and tidal cycles; Biologging; Data storage tags. |
| Ano: 2017 |
URL: https://archimer.ifremer.fr/doc/00402/51400/51974.pdf |
| |
