Derivation of body motion via appropriate smoothing of acceleration data

Abstract

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.

Construction of energy landscapes can clarify the movement and distribution of foraging animals

“…figure 1 and figure 2b). In fact, cognizance of the difference between time-and energy-based efficiency may fundamentally change our understanding of optimum strategies [20]. For example, authors examining diving capacity in air-breathers conventionally use the proportion of time that animals remain in the bottom phase as a fraction of the whole dive cycle duration to measure efficiency [38] (figure 4).…”

“…The durations of these phases were determined with respect to maximum depths reached during the dive as were their ODBA totals and means (see [24] for details). ODBA (in g) was calculated using the sum of the absolute values of dynamic acceleration from each of the three spatial axes (corresponding to surge, heave and sway) after subtracting the static acceleration from the raw acceleration values, itself derived using a running mean over 2 s [20] so that…”

“…Although imperial cormorants may occasionally feed in groups on pelagic school fish in the upper water layers [18], they generally hunt solitarily, executing benthic dives to the seabed [19]. Such dives to the seabed are executed virtually exclusively by birds at Punta Leon [20] in a foraging area consisting exclusively of an extensive sandy substrate [21]. Here, they exploit benthic prey such as Raneya fluminensis, Triathalassothia argentina and Octopus tehuelchus) [22], all species which are widely distributed in coastal waters over the Patagonian Shelf (www.fishbase.org) [23].…”

A new algorithm for the identification of dives reveals the foraging ecology of a shallow-diving seabird using accelerometer data

“…Accelerometers can be used to identify and quantify animal movements (Shepard et al 2008;Gómez Laich et al 2011;Chimienti et al 2016), and thus, they may help to determine shallow feeding events. Accelerometers were previously used to analyse details of diving behaviour in deep-diving birds (Ropert-Coudert et al 2006;Sakamoto et al 2009;Gómez Laich et al 2011;Berlincourt et al 2015).…”

Convergent evolution in locomotory patterns of flying and swimming animals

“…The size of the filtering window was determined using the method described in Shepard et al 47 Static acceleration was subsequently subtracted from the raw acceleration to yield dynamic acceleration (acceleration due to motion). This was performed for all three acceleration channels representing the three spatial planes.…”