生态学
预测(人工智能)
人口
多样性(控制论)
理论生态学
生态系统理论
计算机科学
生物
社会学
人工智能
人口学
作者
А. Морозов,Karen C. Abbott,Kim Cuddington,Tessa B. Francis,Gabriel Gellner,Alan Hastings,Ying Cheng Lai,Sergei Petrovskii,Katherine Scranton,Mary Lou Zeeman
标识
DOI:10.1016/j.plrev.2019.09.004
摘要
This paper discusses the recent progress in understanding the properties of transient dynamics in complex ecological systems. Predicting long-term trends as well as sudden changes and regime shifts in ecosystems dynamics is a major issue for ecology as such changes often result in population collapse and extinctions. Analysis of population dynamics has traditionally been focused on their long-term, asymptotic behavior whilst largely disregarding the effect of transients. However, there is a growing understanding that in ecosystems the asymptotic behavior is rarely seen. A big new challenge for theoretical and empirical ecology is to understand the implications of long transients. It is believed that the identification of the corresponding mechanisms along with the knowledge of scaling laws of the transient's lifetime should substantially improve the quality of long-term forecasting and crisis anticipation. Although transient dynamics have received considerable attention in physical literature, research into ecological transients is in its infancy and systematic studies are lacking. This text aims to partially bridge this gap and facilitate further progress in quantitative analysis of long transients in ecology. By revisiting and critically examining a broad variety of mathematical models used in ecological applications as well as empirical facts, we reveal several main mechanisms leading to the emergence of long transients and hence lays the basis for a unifying theory.
科研通智能强力驱动
Strongly Powered by AbleSci AI