Generalized Mechanism Model for Ecosystem Hysteresis

Ecosystem hysteresis, the occurrence of catastrophic transitions due to external disturbances, is a prevalent phenomenon in dynamic ecosystems. Understanding hysteresis is essential for predicting ecosystem responses and developing effective restoration strategies. However, the intrinsic dynamics quantifying the positive-negative feedback in driving hysteresis and its intensity remain undisclosed. We introduce a quantitative framework to address hysteresis by assessing ecosystem states and feedback loops, which diverges from prior phenomenological theories of hysteresis. Employing this framework, a generalized mechanism model is proposed to estimate positive-negative feedback strengths and defines the irreversible potential of hysteresis to determine its intensity. We identify a dimensionless critical constant that indicates whether hysteresis occurs. The model effectively captures both forward and backward trajectories of hysteresis across various ecological scales. The direction of state transitions may be predicted using unidirectional data. Our findings offer a universal framework for predicting and mitigating catastrophic state shifts of ecosystems.

Authors

Institutions

Publication Details

Journal
Advanced Science
Published
2026-01-14
DOI
https://doi.org/10.1002/advs.202509008
Primary Topic
Ecosystem dynamics and resilience
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Generalized Mechanism Model for Ecosystem Hysteresis

Mingzi Wu, Kai Xue, Yanbin Hao, Xiaoyong Cui et al.
Advanced Science
Ecosystem dynamics and resilience
article

Generalized Mechanism Model for Ecosystem Hysteresis

Mingzi Wu, Kai Xue, Yanbin Hao, Xiaoyong Cui, Yanfen Wang, Xiaoning Song, Jie Liu, Jianqing Du, Tong Zhao, Xin Wang
article en

Abstract

Ecosystem hysteresis, the occurrence of catastrophic transitions due to external disturbances, is a prevalent phenomenon in dynamic ecosystems. Understanding hysteresis is essential for predicting ecosystem responses and developing effective restoration strategies. However, the intrinsic dynamics quantifying the positive-negative feedback in driving hysteresis and its intensity remain undisclosed. We introduce a quantitative framework to address hysteresis by assessing ecosystem states and feedback loops, which diverges from prior phenomenological theories of hysteresis. Employing this framework, a generalized mechanism model is proposed to estimate positive-negative feedback strengths and defines the irreversible potential of hysteresis to determine its intensity. We identify a dimensionless critical constant that indicates whether hysteresis occurs. The model effectively captures both forward and backward trajectories of hysteresis across various ecological scales. The direction of state transitions may be predicted using unidirectional data. Our findings offer a universal framework for predicting and mitigating catastrophic state shifts of ecosystems.

Advanced ScienceVol. 13(17)
Beijing National Laboratory for Molecular Sciences (CN), University of Chinese Academy of Sciences (CN)
Life in Land
Openalex Percentile: Top 92%
Ecosystem dynamics and resilience
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.