Data from: Optimal running speeds when there is a trade-off between speed and the probability of mistakes

1. Do prey run as fast as they can to avoid capture? This is a common assumption in studies of animal performance, yet a recent mathematical model (Wheatley et al. 2015) of escape behaviour predicts that animals should instead use speeds below their maximum capabilities even when running from predators. Fast speeds may compromise motor control and accuracy of limb placement, particularly as the animal runs along narrow structures like beams or branches. Mistakes decrease speed and increase the probability of capture. 2. We tested several key assumptions and predictions of Wheatley et al.’s (2015) model using wild-caught northern quolls (Dasyurus hallucatus), a squirrel-sized marsupial carnivore. We quantified the speeds of quolls as they traversed beams of differing width and expected animals should balance the benefits of higher speeds against the increased probability of mistakes when selecting speeds. 3. We first explored whether the probability of mistakes when running along a beam increased at faster running speeds (speed-accuracy trade-off) and when the difficulty of a task was greater (narrower beam). In addition, we quantified the costs of locomotor mistakes to test the assumption that mistakes decreased overall running speed. Finally, we tested whether individual northern quolls modulated their running speeds when moving on narrow beams, which would decrease the probability of making catastrophic mistakes. 4. We found quolls were more likely to make mistakes when running faster and on the narrower beam. Locomotor mistakes increased the total time needed to traverse the entire beam, and each mistake decreased average escape speed by around 50%, representing a substantial cost for slips or trips. To circumvent the costs of these mistakes, quolls voluntarily reduced speeds in situations when they are more likely to make a mistake (i.e. narrower beams), thereby allowing them to decrease the total time it took to traverse the beam. 5. Our data provide support for the assumptions and predictions of Wheatley et al.’s (2015) model of optimal escape speeds, and suggest that animals optimise rather than simply maximise speeds when running along challenging substrates. Our work provides a foundation for understanding the movement behaviour of animals when their objective is to escape predatory attacks, and demonstrates that animals should select their escape strategy based on how both the speed of movement and motor control affect task success.1. 猎物是否会以最快速度奔跑以躲避被捕食者捕获？这是动物运动性能研究中的普遍假设，但近期一项针对逃逸行为的数学模型（Wheatley等人，2015）提出了相反预测：即便在躲避捕食者时，动物的奔跑速度也应低于其最大能力。高速奔跑可能损害运动控制能力与肢体落点精度，尤其当动物在横梁、树枝等狭窄结构上奔跑时。奔跑失误会降低行进速度，并提升被捕食的概率。 2. 本研究以野外捕获的北澳袋鼬（*Dasyurus hallucatus*，一种体型与松鼠相当的有袋食肉动物）为实验对象，对Wheatley等人（2015）模型的多项核心假设与预测进行了验证。我们量化了袋鼬在不同宽度横梁上穿行时的奔跑速度，并假设动物在选择奔跑速度时，会在更高速度带来的收益与失误概率上升之间寻求平衡。 3. 首先，我们探究了两个变量：一是奔跑速度提升时，横梁上的失误概率是否会上升（即速度-精度权衡（speed-accuracy trade-off））；二是任务难度提升（横梁宽度变窄）时，失误概率是否会增加。此外，我们量化了运动失误带来的代价，以验证“失误会降低整体奔跑速度”这一假设。最后，我们验证了北澳袋鼬在狭窄横梁上移动时，是否会调整奔跑速度以降低发生灾难性失误的概率。 4. 实验结果显示，袋鼬在奔跑速度更快、横梁宽度更窄时，失误概率更高。运动失误会延长横梁穿行的总耗时，且每一次失误都会使平均逃逸速度降低约50%，这对打滑或绊脚而言是显著的代价。为规避这类失误带来的代价，袋鼬会在失误风险更高的场景（即狭窄横梁）中主动降低奔跑速度，从而缩短横梁穿行的总耗时。 5. 本研究的数据验证了Wheatley等人（2015）提出的最优逃逸速度模型的假设与预测，表明动物在具有挑战性的基质上奔跑时，会对奔跑速度进行优化，而非单纯追求速度最大化。本研究为理解动物以躲避捕食为目标时的运动行为提供了理论基础，并证实动物应结合运动速度与运动控制对任务成功率的影响，来选择逃逸策略。