Krystyna A. Golabek

Locomotion dynamics of hunting in wild cheetahs

Although the cheetah is recognised as the fastest land animal, little is known about other aspects of its notable athleticism, particularly when hunting in the wild. Here we describe and use a new tracking collar of our own design, containing a combination of Global Positioning System (GPS) and inertial measurement units, to capture the locomotor dynamics and outcome of 367 predominantly hunting runs of five wild cheetahs in Botswana. A remarkable top speed of 25.9 m s−1 (58 m.p.h. or 93 km h−1) was recorded, but most cheetah hunts involved only moderate speeds. We recorded some of the highest measured values for lateral and forward acceleration, deceleration and body-mass-specific power for any terrestrial mammal. To our knowledge, this is the first detailed locomotor information on the hunting dynamics of a large cursorial predator in its natural habitat.

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

ABSTRACT 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. Summary: An unsupervised machine learning and phase-based steady locomotion detection method allows stride parameters to be extracted from GPS/accelerometer animal tracking collar data collected from free-ranging wild animals.

Movement patterns and athletic performance of leopards in the Okavango Delta

Although leopards are the most widespread of all the big cats and are known for their adaptability, they are elusive and little is known in detail about their movement and hunting energetics. We used high-resolution GPS/IMU (inertial measurement unit) collars to record position, activity and the first high-speed movement data on four male leopards in the Okavango Delta, an area with high habitat diversity and habitat fragmentation. Leopards in this study were generally active and conducted more runs during the night, with peaks in activity and number of runs in the morning and evening twilight. Runs were generally short (less than 100 m) and relatively slow (maximum speed 5.3 m s−1, mean of individual medians) compared to other large predators. Average daily travel distance was 11 km and maximum daily travel distance was 29 km. No direct correlation was found between average daily temperature and travel distance or between season and travel distance. Total daily energy requirements based on locomotor cost and basal metabolic rate varied little between individuals and over time. This study provides novel insights into movement patterns and athletic performance of leopards through quantitative high-resolution measurement of the locomotor, energetic, spatial and temporal movement characteristics. The results are unbiased by methodological and observational limitations characteristic of previous studies and demonstrate the utility of applying new technologies to field studies of elusive nocturnal species.

Pair-Specific Scents in African Wild Dogs, Lycaon pictus , and an Example of a Potential Method to Identify Signals Within Complex Mixtures

Identifying specific signaling components within complex mixtures is a common problem in semiochemistry. Both glandular secretions and excretory products contain components of semiochemical importance, but identifying these signals is problematic because they are usually parts of mixtures with several 100 components, of which only a subset may be involved with signaling. In contrast to waste and metabolic byproducts—which can be expected to vary both between and within individuals according to extrinsic factors—signaling compounds are expected to be uniform among animals sending the same signal and stable over time. In group-living territorial species we would expect there to be a degree of group-specificity in signals that advertise territory residence. As part of an ongoing study investigating and manipulating scent-marking and territorial behavior in African wild dogs, several 100 volatile components have been located from their urine. How many and which, if any, of these have active roles in semiochemical communication of territory residence is currently unknown. Observations of scent marking behaviors of African wild dogs strongly suggest that dominant urine overmarks (DUOs)—where one member of a pair deposits urine on the urine of its partner—are the most likely source of such signals. We used multivariate statistics to investigate >990 separated chemical components (some of which could be multiple compounds) found in these DUOs, and found as few as 10 chemical components that together enabled statistical discrimination of specific dominant pairs. We suggest that this method may be broadly applied across communication systems to locate components of signals within complex “mixtures.”