Systems Biology Laboratory, School of Mathematics and Statistics, and Department of Biomedical Engineering, University of Melbourne, Parkville, Victoria 3010, Australia.
Dipartimento Interateneo di Scienze, Progetto e Politiche del Territorio (DIST) Politecnico di Torino, Viale Pier Andrea Mattioli, Torino 39 10125, Italy.
J R Soc Interface. 2021 Sep;18(182):20210383. doi: 10.1098/rsif.2021.0383. Epub 2021 Sep 29.
Collective migration occurs throughout the animal kingdom, and demands both the interpretation of navigational cues and the perception of other individuals within the group. Navigational cues orient individuals towards a destination, while it has been demonstrated that communication between individuals enhances navigation through a reduction in orientation error. We develop a mathematical model of collective navigation that synthesizes navigational cues and perception of other individuals. Crucially, this approach incorporates uncertainty inherent to cue interpretation and perception in the decision making process, which can arise due to noisy environments. We demonstrate that collective navigation is more efficient than individual navigation, provided a threshold number of other individuals are perceptible. This benefit is even more pronounced in low navigation information environments. In navigation 'blindspots', where no information is available, navigation is enhanced through a relay that connects individuals in information-poor regions to individuals in information-rich regions. As an expository case study, we apply our framework to minke whale migration in the northeast Atlantic Ocean, and quantify the decrease in navigation ability due to anthropogenic noise pollution.
集体迁移发生在整个动物界,需要对导航线索进行解释,还需要感知群体中的其他个体。导航线索使个体朝着目标前进,而已经证明个体之间的通信可以通过减少定向误差来增强导航。我们开发了一个集体导航的数学模型,该模型综合了导航线索和对其他个体的感知。至关重要的是,这种方法将决策过程中由于嘈杂环境而导致的线索解释和感知固有的不确定性纳入其中。我们证明,只要能感知到一定数量的其他个体,集体导航比个体导航更有效率。在低导航信息环境中,这种优势更为明显。在没有信息的“导航盲点”中,导航会通过连接信息匮乏区域和信息丰富区域的个体的接力来增强。作为一个说明性的案例研究,我们将我们的框架应用于东北大西洋小须鲸的洄游,并量化了由于人为噪声污染导致的导航能力下降。