Université de Lille, CNRS, UMR 8198, Evo-Eco-Paleo, 59000 Lille, France
Centre de Mathématiques Appliquées, CNRS UMR 7644, Ecole Polytechnique, 91128 Palaiseau Cedex, France.
J R Soc Interface. 2018 Sep;15(146). doi: 10.1098/rsif.2018.0239.
Functional responses are widely used to describe interactions and resource exchange between individuals in ecology. The form given to functional responses dramatically affects the dynamics and stability of populations and communities. Despite their importance, functional responses are generally considered with a phenomenological approach, without clear mechanistic justifications from individual traits and behaviours. Here, we develop a bottom-up stochastic framework grounded in renewal theory that shows how functional responses emerge from the level of the individuals through the decomposition of interactions into different activities. Our framework has many applications for conceptual, theoretical and empirical purposes. First, we show how the mean and variance of classical functional responses are obtained with explicit ecological assumptions, for instance regarding foraging behaviours. Second, we give examples in specific ecological contexts, such as in nuptial-feeding species or size-dependent handling times. Finally, we demonstrate how to analyse data with our framework, especially highlighting that observed variability in the number of interactions can be used to infer parameters and compare functional response models.
功能反应被广泛用于描述生态学中个体之间的相互作用和资源交换。功能反应的形式对种群和群落的动态和稳定性有显著影响。尽管它们很重要,但功能反应通常被认为是一种现象学方法,没有从个体特征和行为上给出明确的机制解释。在这里,我们开发了一个基于更新理论的自下而上的随机框架,展示了功能反应如何通过将相互作用分解为不同的活动,从个体层面上显现出来。我们的框架有许多用于概念、理论和经验目的的应用。首先,我们展示了如何根据明确的生态假设(例如觅食行为),从个体层面上获得经典功能反应的均值和方差。其次,我们给出了具体生态背景下的例子,例如在求偶喂食物种或与体型相关的处理时间。最后,我们展示了如何使用我们的框架来分析数据,特别是强调观察到的相互作用数量的可变性可以用来推断参数和比较功能反应模型。