Comparison of subjective and statistical methods of dive classification using data from a time-depth recorder attached to a gray whale (Eschrichtius robustus)
Contenu principal de l'article
Résumé
This paper presents dive data obtained from the deployment of a suction-cup attached time-depth recorder (TDR) on a gray whale off the west coast of Vancouver Island, Canada. Data are presented in the form of dive profiles. This represents the first time that dive data have been collected from a gray whale. The data were used to compare subjective classification of dive types to statistical methods of classification, and to test the ability of the statistical methods to classify dives. Each dive was analysed using maximum depth, dive duration and bottom time variables for both subjective and statistical methods to make direct comparison of results. Subjective classification suggests that the tagged animal performed five distinct dive types. Two of these dive types, termed Interventilation and Feeding, were assigned a purpose. Two statistical techniques were then used to classify dives: k-means cluster analysis and discriminant function analysis. Cluster analysis and subjective classification showed poor agreement due to the statistical technique’s inability to account for dive geometry. Discriminant function analysis proved more successful, although this technique also demonstrated some weakness in testing for dive geometry. It was concluded that while statistical analysis of dive data is useful to classify dive types in a general manner, subtle differences, which may be indicative of behavioural differences, still depend on subjective analysis for identification. Detailed analyses of the third, or depth, dimension of the marine mammal environment will be important for the development of effective management strategies, especially as whalewatching grows in popularity.
Details de l'article
Ce travail est disponible sous licence Creative Commons Attribution - Pas d’Utilisation Commerciale 4.0 International.
You are free to:
- Share copy and redistribute the material in any medium or format
- Adapt remix, transform, and build upon the material
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- NonCommercial You may not use the material for commercial purposes.
- No additional restrictions You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.