Suppr超能文献

早期预警指标捕捉到了由环境变化明确速度驱动的灾难性转变。

Early warning indicators capture catastrophic transitions driven by explicit rates of environmental change.

机构信息

Department of Biology, McGill University, Montreal, Quebec, Canada.

Department of Mathematics and Statistics, and Department of Biology, University of Ottawa, Ottawa, Ontario, Canada.

出版信息

Ecology. 2024 Apr;105(4):e4240. doi: 10.1002/ecy.4240. Epub 2024 Feb 23.

Abstract

In response to external changes, ecosystems can undergo catastrophic transitions. Early warning indicators aim to predict such transitions based on the phenomenon of critical slowing down at bifurcation points found under a constant environment. When an explicit rate of environmental change is considered, catastrophic transitions can become distinct phenomena from bifurcations, and result from a delayed response to noncatastrophic bifurcations. We use a trophic metacommunity model where transitions in time series and bifurcations of the system are distinct phenomena. We calculate early warning indicators from the time series of the continually changing system and show that they predict not the bifurcation of the underlying system but the actual catastrophic transition driven by the explicit rate of change. Predictions based on the bifurcation structure could miss catastrophic transitions that can still be captured by early warning signals calculated from time series. Our results expand the repertoire of mechanistic models used to anticipate catastrophic transitions to nonequilibrium ecological systems exposed to a constant rate of environmental change.

摘要

针对外部变化,生态系统可能会经历灾难性的转变。早期预警指标旨在根据在恒定环境下发现的分岔点处的临界减速现象来预测这种转变。当考虑到环境变化的明确速度时,灾难性转变可能会与分岔区分开来,并且是由对非灾难性分岔的延迟反应引起的。我们使用一个营养级元群落模型,其中时间序列的转变和系统的分岔是不同的现象。我们从不断变化的系统的时间序列中计算早期预警指标,并表明它们预测的不是基础系统的分岔,而是由明确的变化率驱动的实际灾难性转变。基于分岔结构的预测可能会错过仍然可以通过从时间序列计算得出的早期预警信号来捕捉的灾难性转变。我们的结果扩展了用于预测暴露于恒定环境变化率的非平衡生态系统的灾难性转变的机制模型的范围。

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