A thorough and quantified method for classifying seabird diving behaviour

Time-depth recorders are commonly deployed on diving animals to obtain information on their aquatic behaviour. The recorded data provide a 2D profile of diving activity. As analyses of diving behaviour from such profiles have become more complex, these analyses have often suffered from a lack of con...

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Bibliographic Details
Published in:Polar biology 2007-07, Vol.30 (8), p.991-1004
Main Authors: HALSEY, L. G, BOST, C.-A, HANDRICH, Y
Format: Article
Language:English
Subjects:
Animal ethology
Aquatic birds
Aves
Behavior
Biodiversity
Biological and medical sciences
Classification
Depth recorders
Diving
Diving behavior
Fundamental and applied biological sciences. Psychology
Life Sciences
Marine
Methods
Populations and Evolution
Predators
Psychology. Psychoanalysis. Psychiatry
Seabirds
Two dimensional analysis
Vertebrata
Vertebrates: general zoology, morphology, phylogeny, systematics, cytogenetics, geographical distribution
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Summary:Time-depth recorders are commonly deployed on diving animals to obtain information on their aquatic behaviour. The recorded data provide a 2D profile of diving activity. As analyses of diving behaviour from such profiles have become more complex, these analyses have often suffered from a lack of consistency and rigour. There is a growing need for a simple, comparative method to classify diving behaviour thoroughly and quantitatively. Here, a new approach to the classification of the dive profiles of penguins is described, which probably has applicability for many other diving predators as well. This simple approach uses a small, coherent set of criteria to classify behaviours in a detailed and quantified manner, and with relative objectivity. Classification of diving behaviour is possible from the temporal scale of a wiggle within a dive to the scale of a bout of dives. The new method will make comparisons between species easier and clearer because these comparisons will be undertaken within a consistent, more objective framework.
ISSN:0722-4060
1432-2056
DOI:10.1007/s00300-007-0257-3