Accelerometry predicts daily energy expenditure in a bird with high activity levels

Abstract

Animal ecology is shaped by energy costs, yet it is difficult to measure finescale energy expenditure in the wild. Because metabolism is often closely correlated with mechanical work, accelerometers have the potential to provide detailed information on energy expenditure of wild animals over fine temporal scales. Nonetheless, accelerometry needs to be validated on wild animals, especially across different locomotory modes. We merged data collected on 20 thick-billed murres (Uria lomvia) from miniature accelerometers with measurements of daily energy expenditure over 24 h using doubly labelled water. Across three different locomotory modes (swimming, flying and movement on land), dynamic body acceleration was a good predictor of daily energy expenditure as measured independently by doubly labelled water (R 2 ¼ 0.73).The most parsimonious model suggested that different equations were needed to predict energy expenditure from accelerometry for flying than for surface swimming or activity on land (R 2 ¼ 0.81). Our results demonstrate that accelerometers can provide an accurate integrated measure of energy expenditure in wild animals using many different locomotory modes.

Counting calories in cormorants: dynamic body acceleration predicts daily energy expenditure measured in pelagic cormorants

“…The doubly labelled water (DLW) method provides only a single, time-averaged estimate whereas heart-rate methods need to account for cardiovascular adjustments independent of energy expenditure (Speakman, 1997;Butler et al, 2004;Green et al, 2009;Green, 2011). The invention of miniature accelerometers has led to the development of accelerometry as a novel technique for estimating energy expenditure that accurately predicts oxygen consumption for humans (Plasqui and Westerterp, 2007;Halsey et al, 2008;Leenders et al, 2006), captive or semi-captive animals (Williams et al, 2004;Fahlman et al, 2008;Wilson et al, 2006;Halsey et al, 2009;Enstipp et al, 2011), domesticated animals Miwa et al, 2015), animals in the wild (Payne et al, 2011;Elliott et al, 2013a;Bishop et al, 2015) and even relatively sedentary animals (Lyons et al, 2013).…”

The foraging benefits of being fat in a highly migratory marine mammal

“…An alternative approach is to quantify the behaviour of animals to estimate swimming costs. A key behavioural parameter is flipper stroking frequency because the number of strokes and the dynamic acceleration caused by stroking correlate linearly with oxygen consumption in a variety of species [30][31][32][33][34] (but see [35]). Accelerometry is an effective method to measure propulsive strokes, which are recorded as oscillating acceleration signals at high sampling rates (usually more than 10 Hz).…”

Correlations of metabolic rate and body acceleration in three species of coastal sharks under contrasting temperature regimes

“…Elliott et al, 2012;Stothart et al, 2016;Roos et al, 2016). This type of concomitant validation in the field is unfortunately not possible for water-breathing taxa; instead, calibrations in the laboratory represent the most comprehensive validation possible for the method in fish.…”

“…This technique is based on the principle that animal movement, which can be measured through multi-dimensional acceleration, results directly from muscle contraction, which is catalysed by adenosine triphosphate (ATP) hydrolysis and thus requires oxygen (Wilson et al, 2006;Gleiss et al, 2011). Past accelerometry studies have investigated the relationship between animal movement and metabolic rate, most commonly measured through respirometry, and have indicated strong correlations between the two in a variety of animal taxa, including birds (Wilson et al, 2006;Green et al, 2009;Halsey et al, 2009aHalsey et al, ,b, 2011bElliott et al, 2012), amphibians (Halsey and White, 2010), marine turtles (Enstipp et al, 2011;Halsey et al, 2011c), mammals (Fahlman et al, 2008;Halsey et al, 2009a), marine invertebrates (Payne et al, 2011;Lyons et al, 2013;Robson et al, 2012) and fish (Clark et al, 2010;Gleiss et al, 2010;Yasuda et al, 2012;Wilson et al, 2013a,b;Wright et al, 2014;Mori et al, 2015). These studies have shown great promise in the applicability of accelerometry as a proxy for metabolic rate, maintaining strong correlations across diverse taxa and through a variety of behaviours, with low error compared with other techniques (Halsey et al, 2009a).…”