Emily L. C. Shepard

Scaling laws of marine predator search behaviour

Many free-ranging predators have to make foraging decisions with little, if any, knowledge of present resource distribution and availability. The optimal search strategy they should use to maximize encounter rates with prey in heterogeneous natural environments remains a largely unresolved issue in ecology. Lévy walks are specialized random walks giving rise to fractal movement trajectories that may represent an optimal solution for searching complex landscapes. However, the adaptive significance of this putative strategy in response to natural prey distributions remains untested. Here we analyse over a million movement displacements recorded from animal-attached electronic tags to show that diverse marine predators—sharks, bony fishes, sea turtles and penguins—exhibit Lévy-walk-like behaviour close to a theoretical optimum. Prey density distributions also display Lévy-like fractal patterns, suggesting response movements by predators to prey distributions. Simulations show that predators have higher encounter rates when adopting Lévy-type foraging in natural-like prey fields compared with purely random landscapes. This is consistent with the hypothesis that observed search patterns are adapted to observed statistical patterns of the landscape. This may explain why Lévy-like behaviour seems to be widespread among diverse organisms, from microbes to humans, as a ‘rule’ that evolved in response to patchy resource distributions.

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 .

Energy Landscapes Shape Animal Movement Ecology

The metabolic costs of animal movement have been studied extensively under laboratory conditions, although frequently these are a poor approximation of the costs of operating in the natural, heterogeneous environment. Construction of “energy landscapes,” which relate animal locality to the cost of transport, can clarify whether, to what extent, and how movement properties are attributable to environmental heterogeneity. Although behavioral responses to aspects of the energy landscape are well documented in some fields (notably, the selection of tailwinds by aerial migrants) and scales (typically large), the principles of the energy landscape extend across habitat types and spatial scales. We provide a brief synthesis of the mechanisms by which environmentally driven changes in the cost of transport can modulate the behavioral ecology of animal movement in different media, develop example cost functions for movement in heterogeneous environments, present methods for visualizing these energy landscapes, and derive specific predictions of expected outcomes from individual- to population- and species-level processes. Animals modulate a suite of movement parameters (e.g., route, speed, timing of movement, and tortuosity) in relation to the energy landscape, with the nature of their response being related to the energy savings available. Overall, variation in movement costs influences the quality of habitat patches and causes nonrandom movement of individuals between them. This can provide spatial and/or temporal structure to a range of population- and species-level processes, ultimately including gene flow. Advances in animal-attached technology and geographic information systems are opening up new avenues for measuring and mapping energy landscapes that are likely to provide new insight into their influence in animal ecology.

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.

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.

Pushed for time or saving on fuel: fine-scale energy budgets shed light on currencies in a diving bird.

Animals may forage using different currencies depending on whether time minimization or energy maximization is more pertinent at the time. Assessment of net energy acquisition requires detailed information on instantaneous activity-specific power use, which varies according to animal performance, being influenced, for example, by speed and prey loading, and which has not been measured before in wild animals. We used a new proxy for instantaneous energy expenditure (overall dynamic body acceleration), to quantify foraging effort in a model species, the imperial shag Phalacrocorax atriceps, during diving. Power costs varied nonlinearly with depth exploited owing to depth-related buoyancy. Consequently, solutions for maximizing the gross rate of gain and energetic efficiency differed for dives to any given depth. Dive effort in free-ranging imperial shags measured during the breeding season was consistent with a strategy to maximize the gross rate of energy gain. We suggest that the divergence of time and energy costs with dive depth has implications for the measurement of dive efficiency across diverse diving taxa.

Energy Beyond Food: Foraging Theory Informs Time Spent in Thermals by a Large Soaring Bird

Current understanding of how animals search for and exploit food resources is based on microeconomic models. Although widely used to examine feeding, such constructs should inform other energy-harvesting situations where theoretical assumptions are met. In fact, some animals extract non-food forms of energy from the environment, such as birds that soar in updraughts. This study examined whether the gains in potential energy (altitude) followed efficiency-maximising predictions in the worlds heaviest soaring bird, the Andean condor (Vultur gryphus). Animal-attached technology was used to record condor flight paths in three-dimensions. Tracks showed that time spent in patchy thermals was broadly consistent with a strategy to maximise the rate of potential energy gain. However, the rate of climb just prior to leaving a thermal increased with thermal strength and exit altitude. This suggests higher rates of energetic gain may not be advantageous where the resulting gain in altitude would lead to a reduction in the ability to search the ground for food. Consequently, soaring behaviour appeared to be modulated by the need to reconcile differing potential energy and food energy distributions. We suggest that foraging constructs may provide insight into the exploitation of non-food energy forms, and that non-food energy distributions may be more important in informing patterns of movement and residency over a range of scales than previously considered.

Visualisation of sensor data from animal movement

A new area of biological research is identifying and grouping patterns of behaviour in wild animals by analysing data obtained through the attachment of tri‐axial accelerometers. As these recording devices become smaller and less expensive their use has increased. Currently acceleration data are visualised as 2D time series plots, and analyses are based on summary statistics and the application of Fourier transforms. We develop alternate visualisations of this data so as to analyse, explore and present new patterns of animal behaviour. Our visualisations include interactive spherical scatterplots, spherical histograms, clustering methods, and feature‐based state diagrams of the data. We study the application of these visualisation methods to accelerometry data from animal movement. The reaction of biologists to these visualisations is also reported.

The need for speed: testing acceleration for estimating animal travel rates in terrestrial dead-reckoning systems

Numerous methods are currently available to track animal movements. However, only one of these, dead-reckoning, has the capacity to provide continuous data for animal movements over fine scales. Dead-reckoning has been applied almost exclusively in the study of marine species, in part due to the difficulty of accurately measuring the speed of terrestrial species. In the present study we evaluate the use of accelerometers and a metric known as overall dynamic body acceleration (ODBA) as a proxy for the measurement of speed for use in dead-reckoning. Data were collated from previous studies, for 10 species locomoting on a treadmill and their ODBA measured by an attached data logger. All species except one showed a highly significant linear relationship between speed and ODBA; however, there was appreciable inter- and intra-specific variance in this relationship. ODBA was then used to estimate speed in a simple trial run of a dead-reckoning track. Estimating distance travelled using speed derived from prior calibration for ODBA resulted in appreciable errors. We describe a method by which these errors can be minimised, by periodic ground-truthing (e.g., by GPS or VHF telemetry) of the dead-reckoned track and adjusting the relationship between speed and ODBA until actual known positions and dead-reckoned positions accord.

Human-wildlife conflicts in a crowded airspace

How can the ecological consequences of the increasing use of airspace by humans be minimized? Over the past century, humans have increasingly used the airspace for purposes such as transportation, energy generation, and surveillance. Conflict with wildlife may arise from buildings, turbines, power lines, and antennae that project into space and from flying objects such as aircrafts, helicopters, and unmanned aerial vehicles (UAVs, or drones) (see the figure) (1–3). The resulting collision and disturbance risks profoundly affect species ecology and conservation (1, 4, 5). Yet, aerial interactions between humans and wildlife are often neglected when considering the ecological consequences of human activities.