Redcliffe, J. | bioRxiv Science

bioRxiv2020

Path tortuosity changes the transport cost paradigm in terrestrial animals

Animal movement paths are variously tortuous, with high turn rates predicted to be energetically costly, especially at high speeds. Animals travel most efficiently at the speed that gives the lowest cost of transport (COT), a well-defined point for movement in fluid media. However, theoretically, land animals should travel at their maximum speed to minimize COT, which they do not, instead travelling at walking pace. We measured oxygen consumption in humans to demonstrate that the energetic costs of turning increase disproportionately with both speed and angular velocity. This resulted in the minimum COT speed occurring at very low speeds, which reduced with increased path tortuosity. Data on turn rates from six free-ranging terrestrial species underpinned this because all individuals turned faster at the slowest speeds across the full speed range. The optimum movement speed for minimum COT in land animals thus depends on the environment and behavior since both affect track tortuosity.

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bioRxiv2020

Why did the animal turn? Time-varying step selection analysis for inference between observed turning points in high frequency data

O_LIStep selection analysis (SSA) is a fundamental technique for uncovering the drivers of animal movement decisions. Its typical use has been to view an animal as "selecting" each measured location, given its current (and possibly previous) locations. Although an animal is unlikely to make decisions precisely at the times its locations are measured, if data are gathered at a relatively low frequency (every few minutes or hours) this is often the best that can be done. Nowadays, though, tracking data is increasingly gathered at very high frequencies, often [≥]1Hz, so it may be possible to exploit these data to perform more behaviourally-meaningful step selection analysis. C_LIO_LIHere, we present a technique to do this. We first use an existing algorithm to determine the turning-points in an animals movement path. We define a "step" to be a straight-line movement between successive turning-points. We then construct a generalised version of integrated SSA (iSSA), called time-varying iSSA (tiSSA), which deals with the fact that turning-points are usually irregularly spaced in time. We demonstrate the efficacy of tiSSA by application to data on both simulated animals and free-ranging goats (Capra aegagrus hircus), comparing our results to those of regular iSSA with locations that are separated by a constant time-interval. C_LIO_LIUsing (regular) iSSA with constant time-steps can give results that are misleading compared to using tiSSA with the actual turns made by the animals. Furthermore, tiSSA can be used to infer covariates that are dependent on the time between turns, which is not possible with regular iSSA. As an example, we show that our study animals tend to spend less time between successive turns when the ground is rockier and/or the temperature is hotter. C_LIO_LIBy constructing a step selection technique that works between observed turning-points of animals, we enable step selection to be used on high-frequency movement data, which are becoming increasingly prevalent in modern biologging studies. Furthermore, since turning-points can be viewed as decisions, our method places step selection analysis on a more behaviourally-meaningful footing compared to previous techniques. C_LI

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