Evidence map›Paper›PMID 42031795›Full record

ArticleScientific reports2026

Spatial early-warning assessment of ecological security in the Poyang Lake Basin based on PSR and Spatial Durbin Modeling.

HaiXiang Guo, CongLe Hu, MeiYi Xin, Qi Wu

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In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

HaiXiang GuoSchool of Economics and Management, China University of Geosciences, Wuhan, 430074, China.
CongLe HuSchool of Economics and Management, China University of Geosciences, Wuhan, 430074, China. 2334483767@qq.com.
MeiYi XinSchool of Economics and Management, China University of Geosciences, Wuhan, 430074, China.
Qi WuSchool of Economics and Management, China University of Geosciences, Wuhan, 430074, China.

Funding

Foundation for Innovative Research Groups of Hubei Province 2024AFA015National Natural Science Foundation of China 72074198National Social Science Fund of China 23AZD072
6 · The paper itself

Abstract

Constructing a basin-level ecological security early-warning (ESEW) system is critical for overcoming the fragmentation of administrative management and achieving holistic watershed governance. Focusing on the Poyang Lake Basin, this study develops a spatial ESEW assessment framework based on the Pressure-State-Response (PSR) model. By integrating 1 km grid-scale data with the Spatial Durbin Model (SDM), we investigate the spatiotemporal evolution of ecological security and quantify the cross-regional spillover effects of key drivers from 2000 to 2020. The results reveal a structural "deterioration-then-recovery" trajectory: the area of "Moderate Warning" expanded from 52.40% in 2000 to a peak of 64.53% in 2010 due to rapid industrialization, before dropping to 37.93% in 2020 as "Light Warning" areas became dominant (62.00%). Spatial analysis confirms significant clustering of ecological risks. Crucially, the SDM identifies a strong spatial spillover effect, indicating that ecological degradation is highly contagious across county borders. Specifically, industrial sulfur dioxide emissions and urbanization intensity (NUADI) in neighboring areas exert significant negative spillovers on local ecological security, whereas farmland-to-forest conversion generates positive externalities. Based on these findings, we propose a differentiated governance strategy, including "Source Control" for high-risk pollution clusters and market-oriented ecological compensation mechanisms to internalize the benefits of upstream protection, providing a scientific basis for cross-regional collaborative governance.

Indexed as

Early-warningEcological securityPSR modelSDM model

Identifiers

PMID42031795
PMCPMC13275731

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