Representing ecosystems at equilibrium has been foundational for building ecological theories, forecasting species populations and planning conservation actions. The equilibrium "balance of nature" ideal suggests that populations will eventually stabilise to a coexisting balance of species. However, a growing body of literature argues that the equilibrium ideal is inappropriate for ecosystems. Here, we develop and demonstrate a new framework for representing ecosystems without considering equilibrium dynamics. Instead, far more pragmatic ecosystem models are constructed by considering population trajectories, regardless of whether they exhibit equilibrium or transient (i.e. non-equilibrium) behaviour. This novel framework maximally utilises readily available, but often overlooked, knowledge from field observations and expert elicitation, rather than relying on theoretical ecosystem properties. We developed innovative Bayesian algorithms to generate ecosystem models in this new statistical framework, without excessive computational burden. Our results reveal that our pragmatic framework could have a dramatic impact on conservation decision-making and enhance the realism of ecosystem models and forecasts.

翻译：将生态系统视为平衡态一直是构建生态理论、预测物种种群及规划保护行动的基础。平衡态的"自然平衡"理念认为，种群最终会稳定在物种共存的平衡状态。然而，越来越多的文献指出，这种平衡理想并不适用于现实生态系统。本文开发并展示了一种新的生态系统表达框架，该框架无需考虑平衡态动力学。取而代之的是，通过考虑种群轨迹（无论其表现出平衡态还是瞬态（即非平衡态）行为）来构建更具实用性的生态系统模型。这一创新框架最大限度地利用了现有但常被忽视的实地观测与专家启发知识，而非依赖于理论化的生态系统属性。我们开发了创新的贝叶斯算法，以在该新统计框架下生成生态系统模型，且无需承受过高的计算负担。结果表明，我们的实用框架可能对保护决策产生显著影响，并提升生态系统模型与预测的逼真度。