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DOI	10.1073/pnas.2103779118
	Unifying deterministic and stochastic ecological dynamics via a landscape-flux approach
	Xu L.; Patterson D.; Staver A.C.; Levin S.A.; Wang J.
发表日期	2021
ISSN	0027-8424
卷号	118 期号:24
英文摘要	The frequency distributions can characterize the population-potential landscape related to the stability of ecological states. We illustrate the practical utility of this approach by analyzing a forest–savanna model. Savanna and forest states coexist under certain conditions, consistent with past theoretical work and empirical observations. However, a grassland state, unseen in the corresponding deterministic model, emerges as an alternative quasi-stable state under fluctuations, providing a theoretical basis for the appearance of widespread grasslands in some empirical analyses. The ecological dynamics are determined by both the population-potential landscape gradient and the steady-state probability flux. The flux quantifies the net input/output to the ecological system and therefore the degree of nonequilibriumness. Landscape and flux together determine the transitions between stable states characterized by dominant paths and switching rates. The intrinsic potential landscape admits a Lyapunov function, which provides a quantitative measure of global stability. We find that the average flux, entropy production rate, and free energy have significant changes near bifurcations under both finite and zero fluctuation. These may provide both dynamical and thermodynamic origins of the bifurcations. We identified the variances in observed frequency time traces, fluctuations, and time irreversibility as kinematic measures for bifurcations. This framework opens the way to characterize ecological systems globally, to uncover how they change among states, and to quantify the emergence of quasi-stable states under stochastic fluctuations. © 2021 National Academy of Sciences. All rights reserved.
英文关键词	Ecological system; Flux; Global stability; Landscape
语种	英语
scopus关键词	article; entropy; grassland; landscape; probability; quantitative analysis; steady state; stochastic model; theoretical study
来源期刊	Proceedings of the National Academy of Sciences of the United States of America
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/238892
作者单位	State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, 130022, China; High Meadows Environmental Institute, Princeton University, Princeton, NJ 08544, United States; Department of Mathematics, Brandeis University, Waltham, MA 02454, United States; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, United States; Department of Ecology and EvolutionaryBiology, Princeton University, Princeton, NJ 08544, United States; Department of Chemistry, Physics and Applied Mathematics, State University of New York at Stony, Stony Brook, NY 11794-3400, United States
推荐引用方式 GB/T 7714	Xu L.,Patterson D.,Staver A.C.,et al. Unifying deterministic and stochastic ecological dynamics via a landscape-flux approach[J],2021,118(24).
APA	Xu L.,Patterson D.,Staver A.C.,Levin S.A.,&Wang J..(2021).Unifying deterministic and stochastic ecological dynamics via a landscape-flux approach.Proceedings of the National Academy of Sciences of the United States of America,118(24).
MLA	Xu L.,et al."Unifying deterministic and stochastic ecological dynamics via a landscape-flux approach".Proceedings of the National Academy of Sciences of the United States of America 118.24(2021).