Suppr超能文献

生态系统关键转变的非平衡早期预警信号。

Non-equilibrium early-warning signals for critical transitions in ecological systems.

机构信息

State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin 130022, P.R. China.

High Meadows Environmental Institute, Princeton University, Princeton, NJ 08544.

出版信息

Proc Natl Acad Sci U S A. 2023 Jan 31;120(5):e2218663120. doi: 10.1073/pnas.2218663120. Epub 2023 Jan 23.

Abstract

Complex systems can exhibit sudden transitions or regime shifts from one stable state to another, typically referred to as critical transitions. It becomes a great challenge to identify a robust warning sufficiently early that action can be taken to avert a regime shift. We employ landscape-flux theory from nonequilibrium statistical mechanics as a general framework to quantify the global stability of ecological systems and provide warning signals for critical transitions. We quantify the average flux as the nonequilibrium driving force and the dynamical origin of the nonequilibrium transition while the entropy production rate as the nonequilibrium thermodynamic cost and thermodynamic origin of the nonequilibrium transition. Average flux, entropy production, nonequilibrium free energy, and time irreversibility quantified by the difference in cross-correlation functions forward and backward in time can serve as early warning signals for critical transitions much earlier than other conventional predictors. We utilize a classical shallow lake model as an exemplar for our early warning prediction. Our proposed method is general and can be readily applied to assess the resilience of many other ecological systems. The early warning signals proposed here can potentially predict critical transitions earlier than established methods and perhaps even sufficiently early to avert catastrophic shifts.

摘要

复杂系统可能会从一种稳定状态突然转变或跃迁到另一种稳定状态,通常被称为关键跃迁。识别出足够早的稳健预警信号,以便采取行动避免跃迁是一个巨大的挑战。我们采用非平衡统计力学中的景观通量理论作为一般框架,来量化生态系统的全局稳定性,并为关键跃迁提供预警信号。我们将平均通量量化为非平衡驱动力和非平衡跃迁的动力学起源,同时将熵产生率量化为非平衡热力学代价和非平衡跃迁的热力学起源。通过向前和向后的交叉相关函数差异量化的平均通量、熵产生、非平衡自由能和时间不可逆性,可以作为关键跃迁的早期预警信号,比其他传统预测方法更早。我们利用一个经典的浅水湖模型作为我们的预警预测的范例。我们提出的方法具有普遍性,可以很容易地应用于评估许多其他生态系统的恢复力。这里提出的预警信号有可能比现有的方法更早地预测关键跃迁,甚至可能足够早地避免灾难性的转变。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3864/9945981/90ee464d07da/pnas.2218663120fig01.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验