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J Anim Ecol. 2019 Jun 7. doi: 10.1111/1365-2656.13040. [Epub ahead of print]

Estimates for energy expenditure in free-living animals using acceleration proxies: A reappraisal.

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Department of Biosciences, Swansea University, Swansea, UK.
Department of Computing Science, Swansea University, Swansea, UK.
School of Biological Sciences, Institute for Global Food Security, Queen's University Belfast, Belfast, UK.
Instituto de Biología de Organismos Marinos IBIOMAR-CONICET, Puerto Madryn, Argentina.
Department of Natural Sciences and Environmental Health, Faculty of Technology, Natural Sciences, and Maritime Sciences, University of South-Eastern Norway, Bø i Telemark, Norway.
Department of Forestry and Renewable Forest Resources, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia.
Institute of Wildlife Biology and Game Management, University of Natural Resources and Life Sciences, Vienna, Vienna, Austria.
Red Sea Research Centre and Computational Biology Research Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
Geomar Helmholz Centre for Ocean Research Kiel, Kiel, Germany.
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
Max Planck Institute for Ornithology, Seewiesen, Germany.
School of Biological and Chemical Sciences, Queen Mary University of London, London, UK.
Departamento de Investigación, Fundación Oceanogràfic de la Comunidad Valenciana, Valencia, Spain.
Max Planck Institute for Ornithology, Radolfzell, Germany.


It is fundamentally important for many animal ecologists to quantify the costs of animal activities, although it is not straightforward to do so. The recording of triaxial acceleration by animal-attached devices has been proposed as a way forward for this, with the specific suggestion that dynamic body acceleration (DBA) be used as a proxy for movement-based power. Dynamic body acceleration has now been validated frequently, both in the laboratory and in the field, although the literature still shows that some aspects of DBA theory and practice are misunderstood. Here, we examine the theory behind DBA and employ modelling approaches to assess factors that affect the link between DBA and energy expenditure, from the deployment of the tag, through to the calibration of DBA with energy use in laboratory and field settings. Using data from a range of species and movement modes, we illustrate that vectorial and additive DBA metrics are proportional to each other. Either can be used as a proxy for energy and summed to estimate total energy expended over a given period, or divided by time to give a proxy for movement-related metabolic power. Nonetheless, we highlight how the ability of DBA to predict metabolic rate declines as the contribution of non-movement-related factors, such as heat production, increases. Overall, DBA seems to be a substantive proxy for movement-based power but consideration of other movement-related metrics, such as the static body acceleration and the rate of change of body pitch and roll, may enable researchers to refine movement-based metabolic costs, particularly in animals where movement is not characterized by marked changes in body acceleration.


doubly labelled water; dynamic body acceleration; energy expenditure; movement costs; wild animals


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