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规避被捕食？这是动物运动性能研究中的一项普遍假设，但近期一项针对逃逸行为的数学模型（Wheatley等人，2015）却预测，即便在遭遇捕食者时，动物也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摆放精度，尤其是当动物在横梁或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方袋鼬（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。我们量化了袋鼬在穿越不同宽度横梁时的奔跑速度，并预期动物在选择奔跑速度时，会权衡更高速度带来的收益与失误概率上升的代价。3. 本研究首先探讨了两个问题：一是在横梁上奔跑时，失误概率是否会随奔跑速度提升而上升（即速度-准确性权衡（speed-accuracy trade-off））；二是任务难度更高（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，我们测试了单只北方袋鼬在狭窄横梁上移动时，是否会调整奔跑速度——这一调整可降低出现严重失误的概率。4. 研究结果显示，袋鼬在奔跑速度更快且横梁更窄时，失误概率更高。运动失误会延长穿越整条横梁所需的总时长，且每一次失误都会使平均逃逸速度降低约50%，这对滑倒或绊脚而言是显著的代价。为规避这类失误带来的代价，袋鼬会在更易出现失误的场景（即狭窄横梁）中主动降低奔跑速度，从而缩短穿越横梁的总耗时。5. 本研究数据支持了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，并非单纯追求速度最大化，而是对奔跑速度进行优化。本研究为理解动物以规避捕食为目标的运动行为提供了理论基础，并证实动物应综合考量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。