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Inferring activity budgets in wild animals to estimate the consequences of disturbances

Christiansen, Fredrik, Rasmussen, Marianne H. and Lusseau, David 2013, Inferring activity budgets in wild animals to estimate the consequences of disturbances, Behavioral ecology, vol. 24, no. 6, pp. 1415-1425, doi: 10.1093/beheco/art086.

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Title Inferring activity budgets in wild animals to estimate the consequences of disturbances
Author(s) Christiansen, Fredrik
Rasmussen, Marianne H.
Lusseau, David
Journal name Behavioral ecology
Volume number 24
Issue number 6
Start page 1415
End page 1425
Total pages 11
Publisher Oxford University Press
Place of publication Oxford, England
Publication date 2013
ISSN 1045-2249
1465-7279
Keyword(s) Animal movement
Markov chains
minke whale
mixture model
Monte Carlo
tourism impact
Summary Activity budgets can provide a direct link to an animal's bioenergetic budget and is thus a valuable unit of measure when assessing human-induced nonlethal effects on wildlife conservation status. However, activity budget inference can be challenging for species that are difficult to observe and require multiple observational variables. Here, we assessed whether whalewatching boat interactions could affect the activity budgets of minke whales (Balaenoptera acutorostrata). We used a stepwise modeling approach to quantitatively record, identify, and assign activity states to continuous behavioral time series data, to estimate activity budgets. First, we used multiple behavioral variables, recorded from continuous visual observations of individual animals, to quantitatively identify and define behavioral types. Activity states were then assigned to each sampling unit, using a combination of hidden and observed states. Three activity states were identified: nonfeeding, foraging, and surface feeding (SF). From the resulting time series of activity states, transition probability matrices were estimated using first-order Markov chains. We then simulated time series of activity states, using Monte Carlo methods based on the transition probability matrices, to obtain activity budgets, accounting for heterogeneity in state duration. Whalewatching interactions reduced the time whales spend foraging and SF, potentially resulting in an overall decrease in energy intake of 42%. This modeling approach thus provides a means to link short-term behavioral changes resulting from human disturbance to potential long-term bioenergetic consequences in animals. It also provides an analytical framework applicable to other species when direct observations of activity states are not possible.
Language eng
DOI 10.1093/beheco/art086
Field of Research 060201 Behavioural Ecology
Socio Economic Objective 970106 Expanding Knowledge in the Biological Sciences
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2013, Oxford University Press
Persistent URL http://hdl.handle.net/10536/DRO/DU:30058898

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