AccScience Publishing / AJWEP / Online First / DOI: 10.36922/AJWEP025470358
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ORIGINAL RESEARCH ARTICLE

Recognition of ecological security patterns based on the geographical detector model

Zhuangzhuang Hou1,2,3 ,  Yiyue Ren1,2 ,  Yizhou Li1,2 ,  Qiushi Zheng1,2 ,  Jingyu Shen1,2 ,  Xinyu Zuo4 ,  Yan Wu1,2* ,  Guoxin Lan1,2*
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1 Chongqing Key Laboratory of Water Environment Evolution and Pollution Control in Three Gorges Reservoir, Chongqing Three Gorges University, Chongqing, Wan Zhou, China
2 Three Gorges Reservoir Area Environment and Ecology of Chongqing Observation and Research Station (Chongqing Three Gorges University), Wan Zhou, China
3 Shanxi Coal Geology 144th Exploration Institute Co., Ltd, Linfen, Shanxi, China
4 Upper Changjiang River Bureau of Hydrological and Water Resources Survey, Chongqing, China
AJWEP, 025470358 https://doi.org/10.36922/AJWEP025470358
Received: 17 November 2025 | Revised: 28 January 2026 | Accepted: 27 February 2026 | Published online: 24 April 2026
(This article belongs to the Special Issue Frontiers in Sustainable Development of Ecology and Environment)
© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

Constructing a regional ecological security pattern (ESP) is essential for maintaining ecosystem health and enhancing ecosystem service functions. However, most existing ESP studies focus only on future scenarios and lack an integrated analysis of historical and future conditions. The selection of resistance factors usually depends on expert experience, which is often constrained by insufficient basic data. This study takes northeastern Chongqing as the study area and innovatively combines the geographical detector model with the patch-level land use simulation model, morphological spatial pattern analysis model, and circuit theory to establish a cross-temporal ESP from 2000 to 2030, integrating historical retrospective analysis and future scenario prediction. The geographical detector model was used to quantitatively identify the core driving factors of the comprehensive ecosystem service index (CESI), avoiding subjective factor selection and providing a scientific method for ESP construction in data-scarce regions. Coupling multi-scenario land-use simulation with ecosystem service assessment enables dynamic identification of ecological sources and objective construction of resistance surfaces, filling the research gap of integrated past–future ESP analysis. The results show that changes in forest land from 2000 to 2030 are concentrated in the central and northeastern parts, reflecting the trade-off between ecological protection and urbanization in the Three Gorges Reservoir Area. Temperature, digital elevation model, land use, and railroads are the dominant drivers of CESI, revealing the combined effects of natural and human activities. The northeast has complex ecological corridors and pinch points with high connectivity, while the southwest suffers from serious ecosystem fragmentation. This study provides a reproducible technical framework for ESP research in ecologically sensitive areas with limited data.

Graphical abstract
Keywords
Ecological security pattern
Geographical detector
Patch-level land use simulation
Land use simulation
Circuit theory
Ecological environment planning
Funding
This study was supported by the National Natural Science Foundation of China (Award Number: 31670467), the Study on City-based Tracking of Yangtze River Ecological Environment Protection and Restoration (Award Number: 2022-LHYJ-02-0508-02), and the Graduate Innovation and Entrepreneurship Program (Award Number: YJSKY24016).
Conflict of interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this study. Zhuangzhuang Hou is affiliated with Shanxi Coal Geology 144th Exploration Institute Co., Ltd; however, this affiliation did not influence the study design, data collection, data analysis, interpretation of results, manuscript preparation, or the decision to publish.
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Asian Journal of Water, Environment and Pollution, Electronic ISSN: 1875-8568 Print ISSN: 0972-9860, Published by AccScience Publishing
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