The challenge of measuring energy expenditure: Current field and laboratory methods

Field and laboratory metabolism and thermoregulation in rhinoceros auklets

Seabirds spend most of their lives at sea, except when visiting their breeding sites. Since the thermal conductivity of water is 25 times higher than that of air, seabirds resting on water lose heat and expend a considerable amount of energy for thermoregulation. For example, rhinoceros auklet (Cerorhinca monocerata), a medium-sized (480620 g) alcid, spends most of its time floating on the sea. In order to estimate the cost of this behavior in terms of their daily energy expenditure (DEE), we studied rhinoceros auklets breeding on Teuri Island, Hokkaido Japan. We measured their resting metabolic rate (RMR) in air and on water by respirometry, and estimated their DEE by the doubly labeled water method. While RMR on water did not vary significantly between 10C and 15C, it was significantly higher at 5C. Air temperature (5.020.0C) had no effect on RMR. The DEE of free-ranging auklets averaged 1,005.5kJday¹ (130.2, n=3). Our results indicate that RMRs are elevated for auklets resting on water, particularly below their lower critical temperature (LCT), compared with in air. Accordingly, spending time above their LCT on water at any time of year will provide enhanced benefits, particularly to seabirds such as rhinoceros auklets which rest a considerable amount of time on water.

Using accelerometers to develop time-energy budgets of wild fur seals from captive surrogates

Background

Accurate time-energy budgets summarise an animal's energy expenditure in a given environment, and are potentially a sensitive indicator of how an animal responds to changing resources. Deriving accurate time-energy budgets requires an estimate of time spent in different activities and of the energetic cost of that activity. Bio-loggers (e.g., accelerometers) may provide a solution for monitoring animals such as fur seals that make long-duration foraging trips. Using low resolution to record behaviour may aid in the transmission of data, negating the need to recover the device.

Methods

This study used controlled captive experiments and previous energetic research to derive time-energy budgets of juvenile Australian fur seals (Arctocephalus pusillus) equipped with tri-axial accelerometers. First, captive fur seals and sea lions were equipped with accelerometers recording at high (20 Hz) and low (1 Hz) resolutions, and their behaviour recorded. Using this data, machine learning models were trained to recognise four states-foraging, grooming, travelling and resting. Next, the energetic cost of each behaviour, as a function of location (land or water), season and digestive state (pre- or post-prandial) was estimated. Then, diving and movement data were collected from nine wild juvenile fur seals wearing accelerometers recording at high- and low- resolutions. Models developed from captive seals were applied to accelerometry data from wild juvenile Australian fur seals and, finally, their time-energy budgets were reconstructed.

Results

Behaviour classification models built with low resolution (1 Hz) data correctly classified captive seal behaviours with very high accuracy (up to 90%) and recorded without interruption. Therefore, time-energy budgets of wild fur seals were constructed with these data. The reconstructed time-energy budgets revealed that juvenile fur seals expended the same amount of energy as adults of similar species. No significant differences in daily energy expenditure (DEE) were found across sex or season (winter or summer), but fur seals rested more when their energy expenditure was expected to be higher. Juvenile fur seals used behavioural compensatory techniques to conserve energy during activities that were expected to have high energetic outputs (such as diving).

Discussion

As low resolution accelerometry (1 Hz) was able to classify behaviour with very high accuracy, future studies may be able to transmit more data at a lower rate, reducing the need for tag recovery. Reconstructed time-energy budgets demonstrated that juvenile fur seals appear to expend the same amount of energy as their adult counterparts. Through pairing estimates of energy expenditure with behaviour this study demonstrates the potential to understand how fur seals expend energy, and where and how behavioural compensations are made to retain constant energy expenditure over a short (dive) and long (season) period.

Terrestrial movement energetics: current knowledge and its application to the optimising animal

The energetic cost of locomotion can be a substantial proportion of an animal's daily energy budget and thus key to its ecology. Studies on myriad species have added to our knowledge about the general cost of animal movement, including the effects of variations in the environment such as terrain angle. However, further such studies might provide diminishing returns on the development of a deeper understanding of how animals trade-off the cost of movement with other energy costs, and other ecological currencies such as time. Here, I propose the ‘individual energy landscape’ as an approach to conceptualising the choices facing the optimising animal. In this Commentary, first I outline previous broad findings about animal walking and running locomotion, focusing in particular on the use of net cost of transport as a metric of comparison between species, and then considering the effects of environmental perturbations and other extrinsic factors on movement costs. I then introduce and explore the idea that these factors combine with the behaviour of the animal in seeking short-term optimality to create that animal's individual energy landscape – the result of the geographical landscape and environmental factors combined with the animal's selected trade-offs. Considering an animal's locomotion energy expenditure within this context enables hard-won empirical data on transport costs to be applied to questions about how an animal can and does move through its environment to maximise its fitness, and the relative importance, or otherwise, of locomotion energy economy.

Comparative locomotor costs of domestic dogs reveal energetic economy of wolf-like breeds

The broad diversity in morphology and geographic distribution of the 35 free-ranging members of the family Canidae is only rivaled by that of the domesticated dog, Canis lupus familiaris. Considered to be among nature's most elite endurance athletes, both domestic and wild canids provide a unique opportunity to examine the variability in mammalian aerobic exercise performance and energy expenditure. To determine the potential effects of domestication and selective breeding on locomotor gait and economy in canids, we measured the kinematics and mass-specific metabolism of three large (>20 kg) dog breed groups (northern breeds, retrievers, and hounds) of varying morphological and genomic relatedness to their shared progenitor, the gray wolf. By measuring all individuals moving in preferred steady-state gaits along a level transect and on a treadmill, we found distinct biomechanical, kinematic, and energetic patterns for each breed group. While all groups exhibited reduced total cost of transport (COT) at faster speeds, the total COT and net COT during trotting and galloping were significantly lower for northern breed dogs (3.0 and 2.1 J∙kg−1∙m−1, respectively) relative to hound (4.2 and 3.4 J∙kg−1∙m−1, respectively) and retriever dogs (3.8 and 3.0 J∙kg−1∙m−1, respectively) of comparable mass. Similarly, northern breeds expended less energy per stride (3.47 J∙kg−1∙stride−1) than hounds or retrievers (4.97 and 4.02 J∙kg−1∙stride−1, respectively). These results suggest that, in addition to their close genetic and morphological ties to gray wolves, northern breed dogs have retained highly cursorial kinematic and physiological traits that promote economical movement across the landscape.

High levels of isotope elimination improve precision and allow individual-based measurements of metabolic rates in animals using the doubly labeled water method

Doubly labeled water (DLW) can be used to measure energy expenditure in free-ranging animals, but questions have been raised about its accuracy in different species or contexts. We investigated whether differences in the extent of isotope elimination affects the precision and accuracy of the DLW method, which can vary according to the experimental design or metabolic rate of the species. Estimated total energy expenditure by the DLW method (TEEdlw) was compared with actual total energy expenditure simultaneously measured via respirometry (TEEresp) in streaked shearwaters Calonectris leucomelas, a pelagic seabird. Subjects were divided into three groups with different experimental conditions: at rest on the ground for 24 h (Group A) or for 48 h (Group B), and at rest on the water for 24 h (Group C). TEEdlw in Group A matched TEEresp, whereas there was an overestimation of TEEdlw in both Groups B and C compared with TEEresp. However, compared with Group A, TEEdlw in Groups B and C had reduced the isotopic analytical variability and thus higher precision. The best regression model (TEEdlw = 1.37 TEEresp - 14.12) showed a high correlation (R(2) = 0.82) between TEEdlw and TEEresp and allows a correction factor for field metabolic rates in streaked shearwaters. Our results demonstrate that the commonly made assumption that the DLW method is not appropriate for individual-based estimates may be incorrect in certain circumstances. Although a correction factor may be necessary when using the DLW method to estimate metabolic rate, greater levels of isotope eliminations provides DLW estimates with high precision, which can adequately represent relative individual estimates. Nevertheless, the DLW method, should be used with caution when characterizing interspecies difference of energy expenditures.

Using heart rate to predict energy expenditure in large domestic dogs

The aim of this study was to establish heart rate as a measure of energy expenditure in large active kennel dogs (28 ± 3 kg bw). Therefore, the heart rate (HR)-oxygen consumption (V˙O2) relationship was analysed in Foxhound-Boxer-Ingelheim-Labrador cross-breds (FBI dogs) at rest and graded levels of exercise on a treadmill up to 60-65% of maximal aerobic capacity. To test for effects of training, HR and V˙O2 were measured in female dogs, before and after a training period, and after an adjacent training pause to test for reversibility of potential effects. Least squares regression was applied to describe the relationship between HR and V˙O2. The applied training had no statistically significant effect on the HR-V˙O2 regression. A general regression line from all data collected was prepared to establish a general predictive equation for energy expenditure from HR in FBI dogs. The regression equation established in this study enables fast estimation of energy requirement for running activity. The equation is valid for large dogs weighing around 30 kg that run at ground level up to 15 km/h with a heart rate maximum of 190 bpm irrespective of the training level.

The interactions between temperature and activity levels in driving metabolic rate: theory, with empirical validation from contrasting ectotherms

The rate of change in resting metabolic rate (RMR) as a result of a temperature increase of 10 °C is termed the temperature coefficient (Q10), which is often used to predict how an organism's total MR will change with temperature. However, this method neglects a potentially key component of MR; changes in activity level (and thus activity MR; AMR) with temperature may significantly alter the relationship between MR and temperature. The present study seeks to describe how thermal effects on total MR estimated from RMR-temperature measurements can be misleading when the contribution of activity to total MR is neglected. A simple conceptual framework illustrates that since the relationship between activity levels and temperature can be different to the relationship between RMR and temperature, a consistent relationship between RMR and total MR cannot be assumed. Thus the thermal effect on total MR can be considerably different to the thermal effect on RMR. Simultaneously measured MR and activity from three ectotherm species with differing behavioural and physiological ecologies were used to empirically examine how changes in temperature drive changes in RMR, activity level, AMR and the Q10 of MR. These species exhibited varied activity- and MR-temperature relationships, underlining the difficulty in predicting thermal influences on activity levels and total MR. These data support a model showing that thermal effects on total MR will deviate from predictions based solely on RMR; this deviation will depend upon the difference in Q10 between AMR and RMR, and the relative contribution of AMR to total MR. To develop mechanistic, predictive models for species' metabolic responses to temperature changes, empirical information about the relationships between activity levels, MR and temperature, such as reported here, is required. This will supersede predictions based on RMR alone.

Metabolic scaling in animals: methods, empirical results, and theoretical explanations

Life on earth spans a size range of around 21 orders of magnitude across species and can span a range of more than 6 orders of magnitude within species of animal. The effect of size on physiology is, therefore, enormous and is typically expressed by how physiological phenomena scale with mass(b). When b ≠ 1 a trait does not vary in direct proportion to mass and is said to scale allometrically. The study of allometric scaling goes back to at least the time of Galileo Galilei, and published scaling relationships are now available for hundreds of traits. Here, the methods of scaling analysis are reviewed, using examples for a range of traits with an emphasis on those related to metabolism in animals. Where necessary, new relationships have been generated from published data using modern phylogenetically informed techniques. During recent decades one of the most controversial scaling relationships has been that between metabolic rate and body mass and a number of explanations have been proposed for the scaling of this trait. Examples of these mechanistic explanations for metabolic scaling are reviewed, and suggestions made for comparing between them. Finally, the conceptual links between metabolic scaling and ecological patterns are examined, emphasizing the distinction between (1) the hypothesis that size- and temperature-dependent variation among species and individuals in metabolic rate influences ecological processes at levels of organization from individuals to the biosphere and (2) mechanistic explanations for metabolic rate that may explain the size- and temperature-dependence of this trait.

The aerodynamic cost of flight in the short-tailed fruit bat (Carollia perspicillata): comparing theory with measurement

Aerodynamic theory has long been used to predict the power required for animal flight, but widely used models contain many simplifications. It has been difficult to ascertain how closely biological reality matches model predictions, largely because of the technical challenges of accurately measuring the power expended when an animal flies. We designed a study to measure flight speed-dependent aerodynamic power directly from the kinetic energy contained in the wake of bats flying in a wind tunnel. We compared these measurements with two theoretical predictions that have been used for several decades in diverse fields of vertebrate biology and to metabolic measurements from a previous study using the same individuals. A high-accuracy displaced laser sheet stereo particle image velocimetry experimental design measured the wake velocities in the Trefftz plane behind four bats flying over a range of speeds (3-7 m s(-1)). We computed the aerodynamic power contained in the wake using a novel interpolation method and compared these results with the power predicted by Pennycuick's and Rayner's models. The measured aerodynamic power falls between the two theoretical predictions, demonstrating that the models effectively predict the appropriate range of flight power, but the models do not accurately predict minimum power or maximum range speeds. Mechanical efficiency--the ratio of aerodynamic power output to metabolic power input--varied from 5.9% to 9.8% for the same individuals, changing with flight speed.

Interpretation of body-mounted accelerometry in flying animals and estimation of biomechanical power

An idealized energy fluctuation model of a bird's body undergoing horizontal flapping flight is developed, focusing on the biomechanical power discernible to a body-mounted accelerometer. Expressions for flight body power constructed from root mean square dynamic body accelerations and wingstroke frequency are derived from first principles and presented in dimensionally appropriate units. As wingstroke frequency increases, the model generally predicts a gradual transition in power from a linear to an asymptotically cubic relationship. However, the onset of this transition and the degree to which this occurs depends upon whether and how forward vibrations are exploited for temporary energy storage and retrieval. While this may vary considerably between species and individual birds, it is found that a quadrature phase arrangement is generally advantageous during level flight. Gravity-aligned vertical acceleration always enters into the calculation of body power, but, whenever forward acceleration becomes relevant, its contribution is subtractive. Several novel kinematic measures descriptive of flapping flight are postulated, offering fresh insights into the processes involved in airborne locomotion. The limitations of the model are briefly discussed, and departures from its predictions during ascending and descending flight evaluated. These findings highlight how body-mounted accelerometers can offer a valuable, insightful and non-invasive technique for investigating the flight of free-ranging birds and bats.

The energy expenditure of stair climbing one step and two steps at a time: estimations from measures of heart rate

Stairway climbing provides a ubiquitous and inconspicuous method of burning calories. While typically two strategies are employed for climbing stairs, climbing one stair step per stride or two steps per stride, research to date has not clarified if there are any differences in energy expenditure between them. Fourteen participants took part in two stair climbing trials whereby measures of heart rate were used to estimate energy expenditure during stairway ascent at speeds chosen by the participants. The relationship between rate of oxygen consumption ([Formula: see text]) and heart rate was calibrated for each participant using an inclined treadmill. The trials involved climbing up and down a 14.05 m high stairway, either ascending one step per stride or ascending two stair steps per stride. Single-step climbing used 8.5±0.1 kcal min(-1), whereas double step climbing used 9.2±0.1 kcal min(-1). These estimations are similar to equivalent measures in all previous studies, which have all directly measured [Formula: see text] The present study findings indicate that (1) treadmill-calibrated heart rate recordings can be used as a valid alternative to respirometry to ascertain rate of energy expenditure during stair climbing; (2) two step climbing invokes a higher rate of energy expenditure; however, one step climbing is energetically more expensive in total over the entirety of a stairway. Therefore to expend the maximum number of calories when climbing a set of stairs the single-step strategy is better.

Tri-axial dynamic acceleration as a proxy for animal energy expenditure; should we be summing values or calculating the vector?

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 (VO2) was recorded. Similar data were obtained from animals but using only one (straight) logger. In humans, both ODBA and VeDBA were good proxies for VO2 with all r(2) values exceeding 0.88, although ODBA accounted for slightly but significantly more of the variation in VO2 than did VeDBA (P<0.03). There were no significant differences between ODBA and VeDBA in terms of the change in VO2 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 VO2 with all r(2) values exceeding 0.70 although, again, ODBA accounted for slightly, but significantly, more of the variation in VO2 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 VO2. In the unusual situation where researchers are unable to guarantee at least reasonably consistent device orientation, they should use VeDBA as a proxy for VO2.