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. 猎物是否会竭尽所能地快速奔跑以避免被捕食？这是动物运动性能研究中的常见假设，但近期一项针对逃逸行为的数学模型（Wheatley等人，2015）却预测，动物在遭遇捕食者时，实际应选择低于自身最大极限的奔跑速度。高速奔跑可能会损害运动控制能力与肢体落点的精准度，尤其是当动物沿横梁或树枝等狭窄结构奔跑时。一旦出现失误，不仅会降低奔跑速度，还会提升被捕食的概率。 2. 我们以野外捕获的北袋鼬（Dasyurus hallucatus，一种体型与松鼠相当的有袋类食肉动物）为实验对象，对Wheatley等人（2015）提出的模型中的多项核心假设与预测进行了验证。我们量化了袋鼬在穿越不同宽度横梁时的奔跑速度，并预期动物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. 我们首先探究了两个问题：其一，沿横梁奔跑时，失误概率是否会随奔跑速度提升而上升（即速度-准确率权衡，speed-accuracy trade-off）；其二，任务难度更高时（即横梁更窄时），失误概率是否会增加。此外，我们还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，我们测试了北袋鼬在狭窄横梁上移动时，是否会主动调整奔跑速度，以此降低出现致命失误的概率。 4. 实验结果显示，袋鼬在奔跑速度更快、横梁更窄的情况下，失误概率更高。运动失误会延长穿越横梁的总耗时，且每一次失误都会使平均逃逸速度降低约50%，这意味着滑倒或绊脚等失误会带来极高的代价。为规避这类失误的代价，袋鼬会在失误风险更高的场景（即更狭窄的横梁）中主动降低奔跑速度，从而缩短了穿越横梁的总耗时。 5. 我们的研究结果支持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支撑基质上奔跑时，并非单纯追求速度最大化，而是会进行速度优化。本研究为理解动物在遭遇捕食者攻击时的运动行为提供了理论基础，同时证实了动物会综合考量运动速度与运动控制对任务成功率的影响，以此选择最优逃逸策略。