An animal's behaviour is a response to its environment and physiological condition, and as such, gives vital clues as to its well-being, which is highly relevant in conservation issues. Behaviour can generally be typified by body motion and body posture, parameters that are both measurable using animal-attached accelerometers. Interpretation of acceleration data, however, can be complex, as the static (indicative of posture) and dynamic (motion) components are derived from the total acceleration values, which should ideally be recorded in all 3-dimensional axes. The principles of triaxial accelerometry are summarised and discussed in terms of the commonalities that arise in patterns of acceleration across species that vary in body pattern, life-history strategy, and the medium they inhabit. Using tri-axial acceleration data from deployments on captive and free-living animals (n = 12 species), behaviours were identified that varied in complexity, from the rhythmic patterns of locomotion, to feeding, and more variable patterns including those relating to social interactions. These data can be combined with positional information to qualify patterns of area-use and map the distribution of target behaviours. The range and distribution of behaviour may also provide insight into the transmission of disease. In this way, the measurement of tri-axial acceleration can provide insight into individual and population level processes, which may ultimately influence the effectiveness of conservation practice.

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Summary1. The energetic costs of different behaviours are critical in modulating the behavioural ecology of free-living animals. Despite this, measurement of energy expenditure in the field has proved difficult. 2. A new method with broad application for field studies has been proposed for determining the rate at which animals expend energy, based on measurements of overall dynamic body acceleration (ODBA) through the attachment of miniature acceleration data-loggers. This technique is easy to implement and has the promise to be able to resolve energy expenditure with fine (sub-second) temporal resolution, making it the only method which promises to able to determine the cost of shortlived behaviours. Increasing evidence supports the validity of the approach although the rationale behind it is vague. 3. This study explores link between metabolic energy and acceleration by examining what is known about how muscular tissue converts metabolic energy to mechanical work via muscular contraction and how Newtonian physics facilitates a derivation of Power (the rate at which work is performed) from acceleration. The link between metabolic energy and acceleration appears to involve three discrete processes: (i) the ratio of mechanical work to metabolic work performed by a single muscle (mechano-chemical efficiency); (ii) the ratio of external and internal work performed (mechanical work of the limbs in relation to that of the centre of mass); and (iii) the ratio of inertial to de novo mechanical work. These processes may vary according to the animal's mass, the medium in which it travels and its gait or behaviour. 4. Assessment of movement has limited application in defining non-movement energy expenditure such as that involved in specific dynamic action or non-shivering thermogenesis. However, this non-movement energy expenditure may often be modelled with reasonable confidence. The utility and appropriateness of the ODBA-energy expenditure method depends on a set of conditions, which we define and suggest should be assessed a priori. 5. This study explores the framework behind the ODBA-energy expenditure method to enable informed decisions to be made regarding the suitability for specific research questions addressed, as well as highlighting calibration needs.

Dynamic body acceleration (DBA) has been used as a proxy for energy expenditure in logger-equipped animals, with researchers summing the acceleration (overall dynamic body acceleration - ODBA) from the three orthogonal axes of devices. The vector of the dynamic body acceleration (VeDBA) may be a better proxy so this study compared ODBA and VeDBA as proxies for rate of oxygen consumption using humans and 6 other species. Twenty-one humans on a treadmill ran at different speeds while equipped with two loggers, one in a straight orientation and the other skewed, while rate of oxygen consumption () was recorded. Similar data were obtained from animals but using only one (straight) logger. In humans, both ODBA and VeDBA were good proxies for with all r2 values exceeding 0.88, although ODBA accounted for slightly but significantly more of the variation in than did VeDBA (P<0.03). There were no significant differences between ODBA and VeDBA in terms of the change in estimated by the acceleration data in a simulated situation of the logger being mounted straight but then becoming skewed (P = 0.744). In the animal study, ODBA and VeDBA were again good proxies for with all r2 values exceeding 0.70 although, again, ODBA accounted for slightly, but significantly, more of the variation in than did VeDBA (P<0.03). The simultaneous contraction of muscles, inserted variously for limb stability, may produce muscle oxygen use that at least partially equates with summing components to derive DBA. Thus, a vectorial summation to derive DBA cannot be assumed to be the more ‘correct’ calculation. However, although within the limitations of our simple study, ODBA appears a marginally better proxy for . In the unusual situation where researchers are unable to guarantee at least reasonably consistent device orientation, they should use VeDBA as a proxy for .

Animal movement, as measured by the overall dynamic body acceleration (ODBA), has recently been shown to correlate well with energy expenditure. However, accelerometers measure a summed acceleration derived from 2 components: static (due to gravity) and dynamic (due to motion). Since only the dynamic component is necessary for the calculation of ODBA, there is a need to establish a robust method for determining dynamic acceleration, currently done by substracting static values from the total acceleration. This study investigated the variability in ODBA arising from deriving static acceleration by smoothing total acceleration over different durations. ODBA was calculated for 3 different modes of locomotion within 1 species (the imperial shag) and for swimming in 4 species of marine vertebrates that varied considerably in body size. ODBA was found to vary significantly with the length of the running mean. Furthermore, the variability of ODBA across running means appeared to be related to the stroke period and hence body size. The results suggest that the running mean should be taken over a minimum period of 3 s for species with a dominant stroke period of up to this value. For species with a dominant stroke period above 3 s, it is suggested that static acceleration be derived over a period of no less than 1 stroke cycle.