Lewis G. Halsey

The fickle P value generates irreproducible results

The reliability and reproducibility of science are under scrutiny. However, a major cause of this lack of repeatability is not being considered: the wide sample-to-sample variability in the P value. We explain why P is fickle to discourage the ill-informed practice of interpreting analyses based predominantly on this statistic.

A Phylogenetic Analysis of the Allometry of Diving

The oxygen store/usage hypothesis suggests that larger animals are able to dive for longer and hence deeper because oxygen storage scales isometrically with body mass, whereas oxygen usage scales allometrically with an exponent <1 (typically 0.67–0.75). Previous tests of the allometry of diving tend to reject this hypothesis, but they are based on restricted data sets or invalid statistical analyses (which assume that every species provides independent information). Here we apply information‐theoretic statistical methods that are phylogenetically informed to a large data set on diving variables for birds and mammals to describe the allometry of diving. Body mass is strongly related to all dive variables except dive:pause ratio. We demonstrate that many diving variables covary strongly with body mass and that they have allometric exponents close to 0.33. Thus, our results fail to falsify the oxygen store/usage hypothesis. The allometric relationships for most diving variables are statistically indistinguishable for birds and mammals, but birds tend to dive deeper than mammals of equivalent mass. The allometric relationships for all diving variables except mean dive duration are also statistically indistinguishable for all major taxonomic groups of divers within birds and mammals, with the exception of the procellariiforms, which, strictly speaking, are not true divers.

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 () 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 .

Estimating energy expenditure of animals using the accelerometry technique: activity, inactivity and comparison with the heart-rate technique

SUMMARY Several methods have been used to estimate the energy expenditure of free-ranging animals. A relatively new technique uses measures of dynamic body acceleration as a calibrated proxy for energy expenditure and has proved an excellent predictor of energy expenditure in active animals. However, some animals can spend much of their time inactive and still expend energy at varying rates for a range of physiological processes. We tested the utility of dynamic body acceleration to estimate energy expenditure during a range of active (locomotion, eating) and inactive (digesting, thermoregulating) behaviours exhibited by domestic chickens. We also compared this technique with the more established heart-rate method for estimating energy expenditure. During activity, the error of estimation using body acceleration was very similar to that from the heart-rate method. Importantly, our results also showed that body acceleration can be used to estimate energy expenditure when birds are inactive. While the errors surrounding these estimates were greater than those during activity, and those made using the heart-rate method, they were less than those made using interspecific allometric equations. We highlight the importance of selecting a methodology that is appropriate for the life-history of the subject animal. We suggest that, to achieve the greatest possible accuracy and precision when estimating energy expenditure in free-ranging animals, the two techniques should be combined, and both heart rate (fH) and dynamic body acceleration could be included as covariates in predictive models. Alternatively, measures of acceleration can be used to ascertain which behaviour is being exhibited at each moment and hence which predictive model should be applied.

Accelerometry to Estimate Energy Expenditure during Activity: Best Practice with Data Loggers

Measurement of acceleration can be a proxy for energy expenditure during movement. The variable overall dynamic body acceleration (ODBA), used in recent studies, combines the dynamic elements of acceleration recorded in all three dimensions to measure acceleration and hence energy expenditure due to body movement. However, the simplicity of ODBA affords it limitations. Furthermore, while accelerometry data loggers enable measures to be stored, recording at high frequencies represents a limit to deployment periods as a result of logger memory and/or battery exhaustion. Using bantam chickens walking at different speeds in a respirometer while wearing an accelerometer logger, we investigated the best proxies for rate of oxygen consumption (V̇o2) from a range of different models using acceleration. We also investigated the effects of sampling acceleration at different frequencies. The best predictor of V̇o2 was a multiple regression including individual measures of dynamic acceleration in each of the three dimensions. However, R2 was relatively high for ODBA as well and also for certain measures of dynamic acceleration in single dimensions. The aforementioned are single variables, therefore easily derived onboard a data logger and from which a simple calibration equation can be derived. For calibrations of V̇o2 against ODBA, R2 was consistent as sampling number decreased down to 600 samples of each acceleration channel per ODBA data point, beyond which R2 tended to be considerably lower. In conclusion, data storage can be maximized when using acceleration as a proxy for V̇o2 by consideration of reductions in (1) number of axes measured and (2) sampling frequency.

Acceleration versus heart rate for estimating energy expenditure and speed during locomotion in animals: Tests with an easy model species, Homo sapiens

An important element in the measurement of energy budgets of free-living animals is the estimation of energy costs during locomotion. Using humans as a particularly tractable model species, we conducted treadmill experiments to test the validity of tri-axial accelerometry loggers, designed for use with animals in the field, to estimate rate of oxygen consumption (VO2: an indirect measure of metabolic rate) and speed during locomotion. The predictive power of overall dynamic body acceleration (ODBA) obtained from loggers attached to different parts of the body was compared to that of heart rate (fH). When subject identity was included in the statistical analysis, ODBA was a good, though slightly poorer, predictor of VO2 and speed during locomotion on the flat (mean of two-part regressions: R2=0.91 and 0.91, from a logger placed on the neck) and VO2 during gradient walking (single regression: R2=0.77 from a logger placed on the upper back) than was fH (R2=0.96, 0.94, 0.86, respectively). For locomotion on the flat, ODBA was still a good predictor when subject identity was replaced by subject mass and height (morphometrics typically obtainable from animals in the field; R2=0.92 and 0.89) and a slightly better overall predictor than fH (R2=0.92 and 0.85). For gradient walking, ODBA predicted VO2 more accurately than before (R2=0.83) and considerably better than did fH (R2=0.77). ODBA and fH combined were the most powerful predictor of VO2 and speed during locomotion. However, ODBA alone appears to be a good predictor and suitable for use in the field in particular, given that accelerometry traces also provide information on the timing, frequency and duration of locomotion events, and also the gait being used.

Flow-through respirometry applied to chamber systems: pros and cons, hints and tips.

Flow-through respirometry is a powerful, accurate methodology for metabolic measurement that is applicable to organisms spanning a body mass range of many orders of magnitude. Concentrating on flow-through respirometry that utilizes a chamber to contain the experimental animals, we describe the most common flow measurement and control methodologies (push, pull and stop-flow) and their associated advantages and disadvantages. Objective methods for calculating air flow rates through the chamber, based on the body mass and taxon of the experimental organism, are presented. Techniques for removing the effect of water vapor dilution, including the direct measurement of water vapor pressure and mathematical compensation for its presence, are described and evaluated, as are issues surrounding the analysis of one or both of the respiratory gases (oxygen and carbon dioxide), and issues related to the mathematical correction of wash-out phenomena (response correction). Two important biomedical applications of flow-through respirometry (metabolic phenotyping and room calorimetry) are discussed in detail, and we conclude with a list of suggestions aimed primarily at investigators starting out in applying flow-through respirometry.

Turn costs change the value of animal search paths

The tortuosity of the track taken by an animal searching for food profoundly affects search efficiency, which should be optimised to maximise net energy gain. Models examining this generally describe movement as a series of straight steps interspaced by turns, and implicitly assume no turn costs. We used both empirical- and modelling-based approaches to show that the energetic costs for turns in both terrestrial and aerial locomotion are substantial, which calls into question the value of conventional movement models such as correlated random walk or Lévy walk for assessing optimum path types. We show how, because straight-line travel is energetically most efficient, search strategies should favour constrained turn angles, with uninformed foragers continuing in straight lines unless the potential benefits of turning offset the cost.

A thorough and quantified method for classifying seabird diving behaviour

Time-depth recorders are commonly deployed on diving animals to obtain information on their aquatic behaviour. The recorded data provide a 2D profile of diving activity. As analyses of diving behaviour from such profiles have become more complex, these analyses have often suffered from a lack of consistency and rigour. There is a growing need for a simple, comparative method to classify diving behaviour thoroughly and quantitatively. Here, a new approach to the classification of the dive profiles of penguins is described, which probably has applicability for many other diving predators as well. This simple approach uses a small, coherent set of criteria to classify behaviours in a detailed and quantified manner, and with relative objectivity. Classification of diving behaviour is possible from the temporal scale of a wiggle within a dive to the scale of a bout of dives. The new method will make comparisons between species easier and clearer because these comparisons will be undertaken within a consistent, more objective framework.

Measuring Energetics and Behaviour Using Accelerometry in Cane Toads Bufo marinus

Cane toads Bufo marinus were introduced to Australia as a control agent but now have a rapidly progressing invasion front and damage new habitats they enter. Predictive models that can give expansion rates as functions of energy supply and feeding ground distribution could help to maximise control efficiency but to date no study has measured rates of field energy expenditure in an amphibian. In the present study we used the accelerometry technique to generate behavioural time budgets and, through the derivation of ODBA (overall dynamic body acceleration), to obtain estimates of energetics in free ranging cane toads. This represents the first time that accelerometers have been used to not only quantify the behaviour of animals but also assign to those behaviours rates of energy expenditure. Firstly, laboratory calibrations between ODBA and metabolic rate were obtained and used to generate a common prediction equation for the subject toads (R2 = 0.74). Furthermore, acceleration data recorded during different behaviours was studied to ascertain threshold values for objectively defining behaviour categories. Importantly, while subsequent accelerometer field deployments were relatively short they agreed with previous studies on the proportion of time that cane toads locomote yet suggest that the metabolic rate of cane toads in the wild may sometimes be considerably higher than might be assumed based on data for other species.