Biomechanics of predator-prey arms race in lion, zebra, cheetah and impala.

The fastest and most manoeuvrable terrestrial animals are found in savannah habitats, where predators chase and capture running prey. Hunt outcome and success rate are critical to survival, so both predator and prey should evolve to be faster and/or more manoeuvrable. Here we compare locomotor characteristics in two pursuit predator-prey pairs, lion-zebra and cheetah-impala, in their natural savannah habitat in Botswana. We show that although cheetahs and impalas were universally more athletic than lions and zebras in terms of speed, acceleration and turning, within each predator-prey pair, the predators had 20% higher muscle fibre power than prey, 37% greater acceleration and 72% greater deceleration capacity than their prey. We simulated hunt dynamics with these data and showed that hunts at lower speeds enable prey to use their maximum manoeuvring capacity and favour prey survival, and that the predator needs to be more athletic than its prey to sustain a viable success rate.

An exploratory clustering approach for extracting stride parameters from tracking collars on free-ranging wild animals.

Changes in stride frequency and length with speed are key parameters in animal locomotion research. They are commonly measured in a laboratory on a treadmill or by filming trained captive animals. Here, we show that a clustering approach can be used to extract these variables from data collected by a tracking collar containing a GPS module and tri-axis accelerometers and gyroscopes. The method enables stride parameters to be measured during free-ranging locomotion in natural habitats. As it does not require labelled data, it is particularly suitable for use with difficult to observe animals. The method was tested on large data sets collected from collars on free-ranging lions and African wild dogs and validated using a domestic dog.

Improving the accuracy of estimates of animal path and travel distance using GPS drift-corrected dead reckoning.

Route taken and distance travelled are important parameters for studies of animal locomotion. They are often measured using a collar equipped with GPS. Collar weight restrictions limit battery size, which leads to a compromise between collar operating life and GPS fix rate. In studies that rely on linear interpolation between intermittent GPS fixes, path tortuosity will often lead to inaccurate path and distance travelled estimates. Here, we investigate whether GPS-corrected dead reckoning can improve the accuracy of localization and distance travelled estimates while maximizing collar operating life. Custom-built tracking collars were deployed on nine freely exercising domestic dogs to collect high fix rate GPS data. Simulations were carried out to measure the extent to which combining accelerometer-based speed and magnetometer heading estimates (dead reckoning) with low fix rate GPS drift correction could improve the accuracy of path and distance travelled estimates. In our study, median 2-dimensional root-mean-squared (2D-RMS) position error was between 158 and 463 m (median path length 16.43 km) and distance travelled was underestimated by between 30% and 64% when a GPS position fix was taken every 5 min. Dead reckoning with GPS drift correction (1 GPS fix every 5 min) reduced 2D-RMS position error to between 15 and 38 m and distance travelled to between an underestimation of 2% and an overestimation of 5%. Achieving this accuracy from GPS alone would require approximately 12 fixes every minute and result in a battery life of approximately 11 days; dead reckoning reduces the number of fixes required, enabling a collar life of approximately 10 months. Our results are generally applicable to GPS-based tracking studies of quadrupedal animals and could be applied to studies of energetics, behavioral ecology, and locomotion. This low-cost approach overcomes the limitation of low fix rate GPS and enables the long-term deployment of lightweight GPS collars.

Additive opportunistic capture explains group hunting benefits in African wild dogs.

African wild dogs (Lycaon pictus) are described as highly collaborative endurance pursuit hunters based on observations derived primarily from the grass plains of East Africa. However, the remaining population of this endangered species mainly occupies mixed woodland savannah where hunting strategies appear to differ from those previously described. We used high-resolution GPS and inertial technology to record fine-scale movement of all members of a single pack of six adult African wild dogs in northern Botswana. The dogs used multiple short-distance hunting attempts with a low individual kill rate (15.5%), but high group feeding rate due to the sharing of prey. Use of high-level cooperative chase strategies (coordination and collaboration) was not recorded. In the mixed woodland habitats typical of their current range, simultaneous, opportunistic, short-distance chasing by dogs pursuing multiple prey (rather than long collaborative pursuits of single prey by multiple individuals) could be the key to their relative success in these habitats.

Energy cost and return for hunting in African wild dogs and cheetahs.

African wild dogs (Lycaon pictus) are reported to hunt with energetically costly long chase distances. We used high-resolution GPS and inertial technology to record 1,119 high-speed chases of all members of a pack of six adult African wild dogs in northern Botswana. Dogs performed multiple short, high-speed, mostly unsuccessful chases to capture prey, while cheetahs (Acinonyx jubatus) undertook even shorter, higher-speed hunts. We used an energy balance model to show that the energy return from group hunting and feeding substantially outweighs the cost of multiple short chases, which indicates that African wild dogs are more energetically robust than previously believed. Comparison with cheetah illustrates the trade-off between sheer athleticism and high individual kill rate characteristic of cheetahs, and the energetic robustness of frequent opportunistic group hunting and feeding by African wild dogs.

A system identification analysis of neural adaptation dynamics and nonlinear responses in the local reflex control of locust hind limbs.

Nonlinear type system identification models coupled with white noise stimulation provide an experimentally convenient and quick way to investigate the often complex and nonlinear interactions between the mechanical and neural elements of reflex limb control systems. Previous steady state analysis has allowed the neurons in such systems to be categorised by their sensitivity to position, velocity or acceleration (dynamics) and has improved our understanding of network function. These neurons, however, are known to adapt their output amplitude or spike firing rate during repetitive stimulation and this transient response may be more important than the steady state response for reflex control. In the current study previously used system identification methods are developed and applied to investigate both steady state and transient dynamic and nonlinear changes in the neural circuit responsible for controlling reflex movements of the locust hind limbs. Through the use of a parsimonious model structure and Monte Carlo simulations we conclude that key system dynamics remain relatively unchanged during repetitive stimulation while output amplitude adaptation is occurring. Whilst some evidence of a significant change was found in parts of the systems nonlinear response, the effect was small and probably of little physiological relevance. Analysis using biologically more realistic stimulation reinforces this conclusion.

The dynamics of analogue signalling in local networks controlling limb movement.

Communication by analogue signals is relatively common in arthropod local networks. In the locust, non-spiking local interneurons play a key role in controlling sets of motor neurons in the generation of local reflex movements of the limbs. Here, our aim was two-fold. Our first aim was to determine the coding properties of a subpopulation of these interneurons by using system identification approaches. To this end, the femoro-tibial chordotonal organ, which monitors the movements of the tibia about the femur, was stimulated with Gaussian white noise and with more natural stimuli corresponding to the movements of the tibia during walking. The results showed that the sample of interneurons analysed displayed a wide, and overlapping, range of response characteristics. The second aim was to develop and test improved data analysis methods for describing neuronal function that are more robust and allow statistical analysis, a need emphasized by the high levels of background neuronal activity usually observed. We found that nonlinear models provided an improved fit in describing the response properties of interneurons that were then classified with statistical clustering methods. We identified four distinct categories of interneuron response that can be further divided into nine groups, with most interneurons being excited during extension movements of the leg, reflecting the outputs of upstream spiking local interneurons.