Croft Simon, Budgey Richard, Pitchford Jonathan W, Wood A Jamie
Department of Biology, University of York, Heslington, York YO10 5DD, UK National Wildlife Management Centre, Animal and Plant Health Agency (APHA), Sand Hutton Campus, York YO41 1LZ, UK.
National Wildlife Management Centre, Animal and Plant Health Agency (APHA), Sand Hutton Campus, York YO41 1LZ, UK.
J R Soc Interface. 2015 May 6;12(106). doi: 10.1098/rsif.2015.0178.
For moving animals, the successful avoidance of hazardous obstacles is an important capability. Despite this, few models of collective motion have addressed the relationship between behavioural and social features and obstacle avoidance. We develop an asynchronous individual-based model for social movement which allows social structure within groups to be included. We assess the dynamics of group navigation and resulting collision risk in the context of information transfer through the system. In agreement with previous work, we find that group size has a nonlinear effect on collision risk. We implement examples of possible network structures to explore the impact social preferences have on collision risk. We show that any social heterogeneity induces greater obstacle avoidance with further improvements corresponding to groups containing fewer influential individuals. The model provides a platform for both further theoretical investigation and practical application. In particular, we argue that the role of social structures within bird flocks may have an important role to play in assessing the risk of collisions with wind turbines, but that new methods of data analysis are needed to identify these social structures.
对于移动中的动物而言，成功避开危险障碍物是一项重要能力。尽管如此，很少有集体运动模型探讨行为和社会特征与避障之间的关系。我们开发了一种基于个体的异步社会运动模型，该模型能够纳入群体内部的社会结构。我们在通过系统进行信息传递的背景下，评估群体导航的动态过程以及由此产生的碰撞风险。与之前的研究一致，我们发现群体规模对碰撞风险具有非线性影响。我们实现了可能的网络结构示例，以探究社会偏好对碰撞风险的影响。我们表明，任何社会异质性都会促使更强的避障行为，且随着群体中具有影响力的个体数量减少，避障行为会进一步改善。该模型为进一步的理论研究和实际应用提供了一个平台。特别是，我们认为鸟群中的社会结构在评估与风力涡轮机碰撞风险方面可能发挥重要作用，但需要新的数据分析方法来识别这些社会结构。
