Surface friction alters the agility of a small Australian marsupial

Abstract

Movement speed can underpin an animal's probability of success in ecological tasks. Prey often use agility to outmanoeuvre predators; however, faster speeds increase inertia and reduce agility. Agility is also constrained by grip, as the foot must have sufficient friction with the ground to apply the forces required for turning. Consequently, ground surface should affect optimum turning speed. We tested the speed-agility trade-off in buff-footed antechinus () on two different surfaces. Antechinus used slower turning speeds over smaller turning radii on both surfaces, as predicted by the speed-agility trade-off. Slipping was 64% more likely on the low-friction surface, and had a higher probability of occurring the faster the antechinus were running before the turn. However, antechinus compensated for differences in surface friction by using slower pre-turn speeds as their amount of experience on the low-friction surface increased, which consequently reduced their probability of slipping. Conversely, on the high-friction surface, antechinus used faster pre-turn speeds in later trials, which had no effect on their probability of slipping. Overall, antechinus used larger turning radii (0.733±0.062 versus 0.576±0.051 m) and slower pre-turn (1.595±0.058 versus 2.174±0.050 m s) and turning speeds (1.649±0.061 versus 2.01±0.054 m s) on the low-friction surface. Our results demonstrate the interactive effect of surface friction and the speed-agility trade-off on speed choice. To predict wild animals' movement speeds, future studies should examine the interactions between biomechanical trade-offs and terrain, and quantify the costs of motor mistakes in different ecological activities.

Habitat features and performance interact to determine the outcomes of terrestrial predator–prey pursuits

“…While our model provides a comprehensive method of assessing the effect of specific habitat features on predation risk in a general setting, it has several limitations. We investigate how obstacles and refuges influence terrestrial predator–prey interactions, but there are a myriad of other landscape features that can affect the behaviour and performance of predators and prey, including snow cover, uneven terrain and surface friction and narrowness (Bergman et al., 2006; Druelle et al., 2019; Wheatley, et al., 2018; Wheatley et al., 2018). For example, snow can reduce maximum achievable velocity while simultaneously increasing the energetic costs of movement (Parker et al., 1984), and morphological adaptations such as foot‐loading can determine how well predators and prey fare in such habitat features (Murray & Boutin, 1991).…”

“…Animals can also use abrupt changes in direction, or manoeuvrability gambits, to outmanoeuvre faster predators (Brown & Taylor, 1995; Howland, 1974; Humphries & Driver, 1970; Wilson et al., 2018). Although speed, acceleration and agility are all important for escaping predators, performing at maximal capacity across all traits is impossible due to biomechanical constraints; the faster an animal runs, the greater its inertia and the harder it is to rapidly change direction and remain stable (Wheatley et al., 2018; Wynn et al., 2015). Thus, animals must trade sprint speed for agility—the faster an animal runs, the lower its agility (Howland, 1974; Wilson et al., 2018).…”

Accidents alter animal fitness landscapes

“…2017; Wheatley et al . 2018a; Wheatley et al . 2018b), they are far more challenging to study in the wild, particularly where severe accidents are likely to be deliberately avoided and therefore rare.…”

“…Accidents are fundamentally dependent on biophysical factors, most particularly mismatches in forces exerted by travelling animals and those needed to maintain control (Wheatley et al 2015;Wynn et al 2015;Shepherd et al 2016;Amir Abdul Nasir et al 2017;Wheatley et al 2018a;Wheatley et al 2018b). The incidence or likelihood of these mismatches depends, therefore, on the structure of the landscape through which an animal is travelling, and particularly on heterogeneity that results in projected forces for controlled travel in one part of the landscape being inappropriate in another (anyone who has slipped on a patch of ice will understand this).…”

“…This is not because accidents never occur; rather, many laboratory studies observe and exclude trials containing accidents in an effort to measure optimal or maximal movement parameters (Huey & Hertz 1984;Losos & Sinervo 1989;Sinervo & Losos 1991;Losos & Irschick 1996;Clemente et al 2019) and/or present a qualitative description of accidents without empirical data (Sinervo & Losos 1991;Gese & Grothe 1995;Byrnes & Jayne 2010;Machovsky Capuska et al 2011;Gilman et al 2012). The relatively few studies that have collected empirical data on accidents suggest that both the specifics of movement and features of the landscape affect the likelihood that accidents will happen (Gerald et al 2008), and confirm that animals moderate their behaviour to minimise this (Daley et al 2006;Clark & Higham 2011;Wheatley et al 2015;Wynn et al 2015;Amir Abdul Nasir et al 2017;Wheatley et al 2018a;Wheatley et al 2018b). Here, we propose a theoretical framework to predict how features of the physical landscape affect the probability and severity of accidents, and describe how accident landscapes fit into pre-existing movement frameworks such as the landscape of fear and environmental stress models to explain how animals decide where and how to move (Fig.…”