Author
Listed:
- Shengjun Yan
(Key Laboratory of Marine Ecosystem Restoration, Ministry of Ecology and Environment, National Marine Environmental Monitoring Center, Dalian 116023, China
Key Laboratory of Water and Sediment Sciences, Ministry of Education, Beijing Normal University, Beijing 100875, China)
- Xiaoping Zhang
(Institute of Soil and Water Conservation, Northwest A&F University, Yangling 712100, China)
- Rui Yan
(College of Marine Science and Environment, Dalian Ocean University, Dalian 116023, China)
- Yilong Luo
(College of Marine Science and Environment, Dalian Ocean University, Dalian 116023, China)
- Haoze Wang
(College of Marine Science and Environment, Dalian Ocean University, Dalian 116023, China)
- Baokang Xing
(College of Marine Science and Environment, Dalian Ocean University, Dalian 116023, China)
- Changan Liu
(Key Laboratory of Marine Ecosystem Restoration, Ministry of Ecology and Environment, National Marine Environmental Monitoring Center, Dalian 116023, China)
- Daoyan Xu
(Key Laboratory of Marine Ecosystem Restoration, Ministry of Ecology and Environment, National Marine Environmental Monitoring Center, Dalian 116023, China)
- Guoxiang Liao
(Key Laboratory of Marine Ecosystem Restoration, Ministry of Ecology and Environment, National Marine Environmental Monitoring Center, Dalian 116023, China)
Abstract
Rapid urbanization has intensified ecological problems such as landscape fragmentation and biodiversity decline, underscoring the need to maintain regional ecological integrity. The construction of ecological security patterns and the optimization of ecological restoration areas are crucial for addressing these ecological issues. However, research on how to couple ecological security patterns with ecological risk assessment to scientifically identify priority areas for ecological restoration and guide spatially targeted restoration remains insufficient. To address this gap, we investigated Liaoning Province by integrating morphological spatial pattern analysis, landscape connectivity assessment, and ecosystem service hotspot analysis to identify ecological sources. We then applied the minimum cumulative resistance model and circuit theory to extract ecological corridors, constructing a comprehensive ecological security pattern. Integrating landscape ecological risk assessment with ecological security patterns established a conservation and restoration-oriented ecological security framework. The results show that the ecological security pattern comprises 40 ecological source patches and 89 potential ecological corridors. Ecological sources encompass a total of 17,628 km 2 (approximately 12% of the province), primarily comprising water bodies, grasslands, shrublands, and forests. The ecological corridors span a total of 3533.9 km, with an average length of 39.7 km. We also identified 139 ecological pinch points and 109 ecological barrier points. Integrating these findings with landscape ecological risk zoning delineates ecological restoration zones, revealing a spatial pattern characterized by east–west differentiation and north–south continuity. This ecological conservation and restoration network provides a clear spatial guide and a robust scientific foundation for territorial spatial planning, ecological conservation, and restoration efforts.
Suggested Citation
Shengjun Yan & Xiaoping Zhang & Rui Yan & Yilong Luo & Haoze Wang & Baokang Xing & Changan Liu & Daoyan Xu & Guoxiang Liao, 2025.
"Identification of Ecological Restoration Zones Based on Ecological Security Pattern and Ecological Risk Assessment—A Case Study of Liaoning Province,"
Sustainability, MDPI, vol. 18(1), pages 1-22, December.
Handle:
RePEc:gam:jsusta:v:18:y:2025:i:1:p:204-:d:1825795
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