Endangered Species Research | |
Challenges in marine mammal habitat modelling: evidence of multiple foraging habitats from the identification of feeding events in blue whales | |
Véronique Lesage1  Robert Michaud1  Thomas Doniol-Valcroze1  Janie Giard1  | |
关键词: Habitat modelling; Feeding behaviour; Habitat suitability; ENFA; Blue whale; St. Lawrence River; Marine mammals; | |
DOI : 10.3354/esr00427 | |
学科分类:动物科学 | |
来源: Inter-Research | |
【 摘 要 】
ABSTRACT: Effective conservation of animal species depends on accurate identification of their critical habitat. Marine mammals, however, often transit through heterogeneous habitats and perform various activities within short periods of time. The predictive power of habitat modelling techniques can thus suffer from variability in behaviour and the use of multiple habitat types. We used data loggers and ■ecological-niche factor analysis (ENFA) modelling techniques to determine blue whale Balaenoptera musculus associations with underwater topography on a feeding ground in the St. Lawrence River estuary, Canada. We compared a naïve model that had no knowledge of behaviour with a model that used the locations of feeding events inferred from specific velocity signatures. Blue whales travelled over several habitat types with different characteristics, which confounded modelling efforts when pooled together. The model based on the feeding set had considerably higher predictive power but could not highlight all suitable habitats at the same time. Using cluster analysis, we identified 4 habitat types used for feeding, each corresponding to distinct underwater topographies. Feeding depth and behaviour varied across these habitats, which were used preferentially at different times of the tidal cycle and appeared linked to known prey aggregation mechanisms. Our results suggest that failure to identify feeding activity or to take into account the existence of multiple foraging habitats at a fine scale could result in spurious modelling results.
【 授权许可】
Unknown
【 预 览 】
Files | Size | Format | View |
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RO201912080708702ZK.pdf | 1395KB | download |