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

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 an...

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Main Authors: Christiansen, F., Rasmussen, M.H., Lusseau, D.
Format: Article in Journal/Newspaper
Language:English
Published: Springer-Verlag 2013
Subjects:
Online Access:https://researchrepository.murdoch.edu.au/id/eprint/28958/
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spelling ftmurdochuniv:oai:researchrepository.murdoch.edu.au:28958 2023-05-15T15:36:09+02:00 Inferring activity budgets in wild animals to estimate the consequences of disturbances Christiansen, F. Rasmussen, M.H. Lusseau, D. 2013 https://researchrepository.murdoch.edu.au/id/eprint/28958/ eng eng Springer-Verlag https://researchrepository.murdoch.edu.au/id/eprint/28958/ full_text_status:none © The Author 2013. Christiansen, F. <https://researchrepository.murdoch.edu.au/view/author/Christiansen, Fredrik.html>, Rasmussen, M.H. and Lusseau, D. (2013) Inferring activity budgets in wild animals to estimate the consequences of disturbances. Behavioral Ecology and Sociobiology, 24 (6). pp. 1415-1425. Journal Article 2013 ftmurdochuniv 2020-01-05T18:55:22Z 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. Article in Journal/Newspaper Balaenoptera acutorostrata Murdoch University: Murdoch Research Repository
institution Open Polar
collection Murdoch University: Murdoch Research Repository
op_collection_id ftmurdochuniv
language English
description 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.
format Article in Journal/Newspaper
author Christiansen, F.
Rasmussen, M.H.
Lusseau, D.
spellingShingle Christiansen, F.
Rasmussen, M.H.
Lusseau, D.
Inferring activity budgets in wild animals to estimate the consequences of disturbances
author_facet Christiansen, F.
Rasmussen, M.H.
Lusseau, D.
author_sort Christiansen, F.
title Inferring activity budgets in wild animals to estimate the consequences of disturbances
title_short Inferring activity budgets in wild animals to estimate the consequences of disturbances
title_full Inferring activity budgets in wild animals to estimate the consequences of disturbances
title_fullStr Inferring activity budgets in wild animals to estimate the consequences of disturbances
title_full_unstemmed Inferring activity budgets in wild animals to estimate the consequences of disturbances
title_sort inferring activity budgets in wild animals to estimate the consequences of disturbances
publisher Springer-Verlag
publishDate 2013
url https://researchrepository.murdoch.edu.au/id/eprint/28958/
genre Balaenoptera acutorostrata
genre_facet Balaenoptera acutorostrata
op_source Christiansen, F. <https://researchrepository.murdoch.edu.au/view/author/Christiansen, Fredrik.html>, Rasmussen, M.H. and Lusseau, D. (2013) Inferring activity budgets in wild animals to estimate the consequences of disturbances. Behavioral Ecology and Sociobiology, 24 (6). pp. 1415-1425.
op_relation https://researchrepository.murdoch.edu.au/id/eprint/28958/
full_text_status:none
op_rights © The Author 2013.
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