Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, Burwood, Victoria, Australia.
Biodiversity Division, Department of Environment, Land, Water and Planning, East Melbourne, Victoria, Australia.
Nat Ecol Evol. 2020 Nov;4(11):1459-1471. doi: 10.1038/s41559-020-01298-8. Epub 2020 Sep 14.
Applied ecology has traditionally approached management problems through a simplified, single-species lens. Repeated failures of single-species management have led us to a new paradigm - managing at the ecosystem level. Ecosystem management involves a complex array of interacting organisms, processes and scientific disciplines. Accounting for interactions, feedback loops and dependencies between ecosystem components is therefore fundamental to understanding and managing ecosystems. We provide an overview of the main types of ecosystem models and their uses, and discuss challenges related to modelling complex ecological systems. Existing modelling approaches typically attempt to do one or more of the following: describe and disentangle ecosystem components and interactions; make predictions about future ecosystem states; and inform decision making by comparing alternative strategies and identifying important uncertainties. Modelling ecosystems is challenging, particularly when balancing the desire to represent many components of an ecosystem with the limitations of available data and the modelling objective. Explicitly considering different forms of uncertainty is therefore a primary concern. We provide some recommended strategies (such as ensemble ecosystem models and multi-model approaches) to aid the explicit consideration of uncertainty while also meeting the challenges of modelling ecosystems.
应用生态学传统上通过简化的单一物种视角来解决管理问题。单一物种管理的反复失败使我们进入了一个新的范式——在生态系统层面进行管理。生态系统管理涉及到一系列复杂的相互作用的生物、过程和科学学科。因此，考虑生态系统组成部分之间的相互作用、反馈回路和依存关系对于理解和管理生态系统至关重要。我们提供了主要类型的生态系统模型及其用途的概述，并讨论了与建模复杂生态系统相关的挑战。现有的建模方法通常试图完成以下一项或多项任务：描述和理清生态系统组成部分和相互作用；对未来生态系统状态进行预测；通过比较替代策略和确定重要的不确定性来为决策提供信息。生态系统建模具有挑战性，特别是在平衡表示生态系统的许多组成部分与可用数据和建模目标的限制时。因此，明确考虑不同形式的不确定性是一个主要关注点。我们提供了一些推荐的策略（例如集合生态系统模型和多模型方法），以帮助在明确考虑不确定性的同时应对生态系统建模的挑战。
