Department of Computing, Faculty of Technology, University of Turku, Turku, Finland.
Unité de Chronobiologie Théorique, Faculté des Sciences CP 231, Université Libre de Bruxelles, Brussels, Belgium.
PLoS Comput Biol. 2022 Jun 3;18(6):e1009396. doi: 10.1371/journal.pcbi.1009396. eCollection 2022 Jun.
Ecological memory refers to the influence of past events on the response of an ecosystem to exogenous or endogenous changes. Memory has been widely recognized as a key contributor to the dynamics of ecosystems and other complex systems, yet quantitative community models often ignore memory and its implications. Recent modeling studies have shown how interactions between community members can lead to the emergence of resilience and multistability under environmental perturbations. We demonstrate how memory can be introduced in such models using the framework of fractional calculus. We study how the dynamics of a well-characterized interaction model is affected by gradual increases in ecological memory under varying initial conditions, perturbations, and stochasticity. Our results highlight the implications of memory on several key aspects of community dynamics. In general, memory introduces inertia into the dynamics. This favors species coexistence under perturbation, enhances system resistance to state shifts, mitigates hysteresis, and can affect system resilience both ways depending on the time scale considered. Memory also promotes long transient dynamics, such as long-standing oscillations and delayed regime shifts, and contributes to the emergence and persistence of alternative stable states. Our study highlights the fundamental role of memory in communities, and provides quantitative tools to introduce it in ecological models and analyse its impact under varying conditions.
生态记忆是指过去事件对生态系统对外源或内源性变化的响应的影响。记忆已被广泛认为是生态系统和其他复杂系统动态的关键因素,但定量群落模型通常忽略了记忆及其影响。最近的建模研究表明,群落成员之间的相互作用如何在环境干扰下导致弹性和多稳定性的出现。我们使用分数微积分的框架展示了如何在这些模型中引入记忆。我们研究了在不同的初始条件、干扰和随机性下,生态记忆逐渐增加如何影响一个特征明确的相互作用模型的动态。我们的结果突出了记忆对群落动态的几个关键方面的影响。一般来说,记忆会给动态带来惯性。这有利于在干扰下的物种共存,增强系统对状态转变的抵抗力,减轻滞后,并且可以根据所考虑的时间尺度对系统的恢复力产生正反两方面的影响。记忆还促进了长暂态动力学,如长期的振荡和延迟的状态转变,并有助于替代稳定状态的出现和持续。我们的研究强调了记忆在群落中的基本作用,并提供了定量工具,可在生态模型中引入记忆,并在不同条件下分析其影响。