Institute of Informatics, Slovak Academy of Sciences, 845 07, Bratislava, Slovakia.
Institute of Forest Ecology, Slovak Academy of Sciences, 960 53, Zvolen, Slovakia.
Sci Rep. 2020 Oct 8;10(1):16793. doi: 10.1038/s41598-020-72999-0.
Utilization of computational approach in the study of social behaviour of animals is increasing and we attempted such an approach in our study of tree-dwelling bats. These bats live in highly dynamic fission-fusion societies that share multiple roosts in a common home range. The key behavioural component associated with complex and non-centralized decision-making processes in roost switching is swarming around potential locations in order to recruit members to the new roost. To understand roost switching dynamics of bat groups in their natural environment, we employed a computational model, the SkyBat, which is based on swarm algorithm, to model this process. In a simulated environment of this agent-based model, we replicated natural fission-fusion dynamics of the Leisler's bat, Nyctalus leisleri, groups according to predefined species and habitat parameters. Spatiotemporal patterns of swarming activity of agents were similar to bats. The number of simulated groups formed prior to sunrise, the mean number of individuals in groups and the roost height did not differ significantly from data on a local population of bats collected in the field. Thus, the swarm algorithm gave a basic framework of roost-switching, suggesting possible applications in the study of bat behaviour in rapidly changing environments as well as in the field of computer science.
利用计算方法研究动物的社会行为正变得越来越普遍，我们在对树栖蝙蝠的研究中也尝试了这种方法。这些蝙蝠生活在高度动态的分裂-融合社会中，它们在一个共同的栖息地范围内共享多个栖息地。与在新栖息地中招募成员相关的关键行为成分是在潜在的位置周围聚集，以招募成员到新的栖息地。为了了解蝙蝠群体在自然环境中的栖息地转换动态，我们采用了一种基于群体算法的计算模型——SkyBat，来模拟这一过程。在这个基于代理的模型的模拟环境中，我们根据预设的物种和栖息地参数复制了 Leisler 的蝙蝠（Nyctalus leisleri）群体的自然分裂-融合动态。代理的聚集活动的时空模式与蝙蝠相似。在日出前形成的模拟群体数量、群体中的个体平均数量和栖息地高度与在野外收集的蝙蝠局部种群的数据没有显著差异。因此，群体算法为栖息地转换提供了一个基本框架，这表明它可能适用于在快速变化的环境中研究蝙蝠行为，以及在计算机科学领域。
