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.

BackgroundResearch on wild animal ecology is increasingly employing GPS telemetry in order to determine animal movement. However, GPS systems record position intermittently, providing no information on latent position or track tortuosity. High frequency GPS have high power requirements, which necessitates large batteries (often effectively precluding their use on small animals) or reduced deployment duration. Dead-reckoning is an alternative approach which has the potential to ‘fill in the gaps’ between less resolute forms of telemetry without incurring the power costs. However, although this method has been used in aquatic environments, no explicit demonstration of terrestrial dead-reckoning has been presented.ResultsWe perform a simple validation experiment to assess the rate of error accumulation in terrestrial dead-reckoning. In addition, examples of successful implementation of dead-reckoning are given using data from the domestic dog Canus lupus, horse Equus ferus, cow Bos taurus and wild badger Meles meles.ConclusionsThis study documents how terrestrial dead-reckoning can be undertaken, describing derivation of heading from tri-axial accelerometer and tri-axial magnetometer data, correction for hard and soft iron distortions on the magnetometer output, and presenting a novel correction procedure to marry dead-reckoned paths to ground-truthed positions. This study is the first explicit demonstration of terrestrial dead-reckoning, which provides a workable method of deriving the paths of animals on a step-by-step scale. The wider implications of this method for the understanding of animal movement ecology are discussed.Electronic supplementary materialThe online version of this article (doi:10.1186/s40462-015-0055-4) contains supplementary material, which is available to authorized users.

Resting metabolic rates at thermoneutral (RMRts) are unexpectedly variable. One explanation is that high RMRts intrinsically potentiate a greater total daily energy expenditure (DEE), but recent work has suggested that DEE is extrinsically defined by the environment, which independently affects RMRt. This extrinsic effect could occur because expenditure is forced upwards in poor habitats or enabled to rise in good habitats. We provide here an intraspecific test for an association between RMRt and DEE that separates intrinsic from extrinsic effects and forcing from enabling effects. We measured the DEE and RMRt of 75 free-living shorttailed field voles at two time points in late winter. Across all sites, there was a positive link between individual variation in RMRt and DEE. This correlation, however, emerged only because of an effect across sites, rather than because of an intrinsic association within sites. We defined site quality from the survivorship of voles at the sites and the time at which they commenced breeding in spring. The associations between DEE͞RMRt and site quality suggested that in February voles in poorer sites had higher energy demands, indicating that DEE was forced upwards, but in March the opposite was true, with higher demands in good sites, indicating that high expenditure was enabled. These data show that daily energy demands are extrinsically defined, with a link to RMRt that is secondary or independent. Both forcing and enabling effects of the environment may pertain at different times of year.T he basal metabolic rate (BMR) is defined as the metabolic rate of a quiescent animal, in the thermoneutral zone, that is neither digesting food nor engaged in reproduction or growth (1). A slightly less rigorously defined measurement, resting metabolic rate at thermoneutral (RMRt), incorporates all of these requirements except that the animal need not be postabsorptive (2). BMR and RMRt are highly variable. This variability is most manifest at the interspecific level, where species that have the same body mass may differ in their RMRts by almost an order of magnitude (3-5). However, intraspecific variation in these traits is also substantial, particularly in small mammals, where individuals of the same body mass may differ by 100% in their BMR or RMRt (6-10).Understanding the nature of these differences is important because RMRt (and BMR) are major components of total energy budgets. Typically in free-living animals, RMRt accounts for Ϸ30-40% of total daily energy demands (11)(12)(13)(14). Because animals must spend time feeding to sustain their daily energy demands, including the component comprising their RMRts, there is presumably selection on animals to minimize this component of their daily energy budgets [to reduce foraging times and exposure to predation or adverse environmental conditions (15) or to allocate the saved energy to the processes of growth and reproduction (16)]. Attempts at understanding why some individual animals have much greater RMRts than others have therefore focused ...