Department of Environmental Science and Policy, University of California Davis, Davis, CA, USA.
J R Soc Interface. 2024 Mar;21(212):20240059. doi: 10.1098/rsif.2024.0059. Epub 2024 Mar 27.
Transient dynamics pose unique challenges when dealing with predictions and management of ecological systems yet little headway has been made on understanding when an ecological system might be in a transient state. As a start we consider a specific model, here focusing on a canonical model for anaerobic digestion. Through a series of simplifications, we analyse the potential of the model for transient dynamics, and the driving mechanisms. Using a stochastic analogue of this model, we create synthetic ecological data. Thus, combining our understanding of the deterministic transient dynamics with the use of empirical dynamical modelling, we propose several new metrics to indicate when the synthetic time series is leaving a transient state.
在处理生态系统的预测和管理时,瞬态动态带来了独特的挑战,但人们在理解生态系统何时可能处于瞬态状态方面几乎没有取得进展。作为一个起点,我们考虑一个特定的模型,这里重点关注用于厌氧消化的典型模型。通过一系列简化,我们分析了模型用于瞬态动态的潜力和驱动机制。我们使用该模型的随机模拟,创建了合成生态数据。因此,通过将我们对确定性瞬态动态的理解与使用经验动力建模相结合,我们提出了几个新指标来指示合成时间序列何时离开瞬态状态。