Data from: The spatial dynamics of predators and the benefits and costs of sharing information

Predators of all kinds, be they lions hunting in the Serengeti or fishermen searching for their catch, display various collective strategies. A common strategy is to share information about the location of prey. However, depending on the spatial characteristics and mobility of predators and prey, information sharing can either improve or hinder individual success. Here, our goal is to investigate the interacting effects of space and information sharing on predation efficiency, represented by the expected rate at which prey are found and consumed. We derive a feeding functional response that accounts for both spatio-temporal heterogeneity and communication, and validate this mathematical analysis with a computational agent-based model. This agent-based model has an explicit yet minimal representation of space, as well as information sharing about the location of prey. The analytical model simplifies predator behavior into a few discrete states and one essential trade-off, between the individual benefit of acquiring information and the cost of creating spatial and temporal correlation between predators. Despite the absence of an explicit spatial dimension in these equations, they quantitatively predict the predator consumption rates measured in the agent-based simulations across the explored parameter space. Together, the mathematical analysis and agent-based simulations identify the conditions for when there is a benefit to sharing information, and also when there is a cost.无论是在塞伦盖蒂平原狩猎的狮群，还是寻觅渔获的渔民，各类捕食者均展现出多样的集体策略。其中一项常见策略为共享猎物位置相关的信息。然而，根据捕食者与猎物的空间特征及移动能力差异，信息共享既可能提升个体的捕食成功率，也可能对其造成阻碍。本研究旨在探究空间与信息共享对捕食效率的交互影响——捕食效率以被发现并被捕食的猎物期望速率为表征。我们推导得到了同时兼顾时空异质性与信息交流的取食功能响应，并通过计算型基于智能体的模型（agent-based model）对该数学分析进行验证。该基于智能体的模型对空间进行了显式且极简的表征，同时包含猎物位置相关的信息共享机制。该分析模型将捕食者行为简化为若干离散状态与一项核心权衡：获取信息的个体收益，与在捕食者间构建空间及时间相关性所产生的成本之间的权衡。尽管这些方程未包含显式的空间维度，但其仍能在所有探究过的参数空间内，定量预测基于智能体的模拟中测得的捕食者捕食速率。综上，该数学分析与基于智能体的模拟共同确定了信息共享存在收益与成本的具体条件。