Department of Migration, Max Planck Institute of Animal Behavior, 78315 Radolfzell, Germany; University of Konstanz, Department of Biology, Universitätsstraße 10, 78464 Konstanz, Germany; Centre for the Advanced Study of Collective Behaviour, University of Konstanz, 78464 Konstanz, Germany.
Department of Migration, Max Planck Institute of Animal Behavior, 78315 Radolfzell, Germany; University of Konstanz, Department of Biology, Universitätsstraße 10, 78464 Konstanz, Germany.
Trends Ecol Evol. 2021 Nov;36(11):990-999. doi: 10.1016/j.tree.2021.06.013. Epub 2021 Jul 21.
Physical energy defines the energy landscape and determines the species-specific cost of movement, thus influencing movement decisions. In unpredictable and dynamic environments, observing the locomotion of others increases individual certainty in the distribution of physical energy to increase movement efficiency. Beyond the physical energy landscape, social sampling increases certainty in all ecological landscapes that influence animal movement (including fear and resource landscapes), and individuals use energy to express each of these. We call for the development of an 'optimal movement theory' (OMT) that integrates the multidimensional reality of movement decisions by combining ecological landscapes according to a single expectation of energy cost-benefit, where social sampling provides up-to-date information under uncertain conditions. This mechanistic framework has implications for predicting individual movement patterns and for investigating the emergence of aggregations.
体力能定义能量景观,并决定了物种特有的运动成本,从而影响运动决策。在不可预测和动态的环境中,观察他人的运动可以增加个人对体力分配的确定性,从而提高运动效率。除了体力景观之外,社会抽样还增加了所有影响动物运动的生态景观的确定性(包括恐惧和资源景观),而个体则利用能量来表达其中的每一个。我们呼吁发展一种“最优运动理论”(OMT),该理论通过根据能量成本效益的单一预期将生态景观结合起来,整合运动决策的多维现实,其中社会抽样在不确定条件下提供最新信息。这个机械框架对预测个体运动模式和研究聚集的出现具有重要意义。