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安徽农业大学资源与环境学院, 合肥 230036
Received:06 January 2026,
Revised:2026-03-12,
Accepted:27 March 2026,
Online First:14 April 2026,
Published:28 August 2026
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赵云文,徐志立.多目标分区下安徽省景观生态风险演变与影响因素[J].水土保持学报,2026,40(4):372-385.
Zhao Yunwen, Xu Zhili. Evolution and influencing factors of landscape ecological risk in Anhui Province under multi-objective zoning[J]. Journal of Soil and Water Conservation, 2026, 40(4):372-385.
赵云文,徐志立.多目标分区下安徽省景观生态风险演变与影响因素[J].水土保持学报,2026,40(4):372-385. DOI: 10.13870/j.cnki.stbcxb.2026.04.019. CSTR: 32310.14.stbcxb.2026.04.019.
Zhao Yunwen, Xu Zhili. Evolution and influencing factors of landscape ecological risk in Anhui Province under multi-objective zoning[J]. Journal of Soil and Water Conservation, 2026, 40(4):372-385. DOI: 10.13870/j.cnki.stbcxb.2026.04.019. CSTR: 32310.14.stbcxb.2026.04.019.
目的
2
科学划定安徽省土地利用功能分区,识别景观生态风险的关键驱动因子,揭示景观生态风险时空演变特征及空间冲突格局,为区域生态安全维护与国土空间规划提供科学支撑。
方法
2
以安徽省为研究区,整合MSPA模型、Conefor模型与最小累积阻力模型(MCR),利用阻力阈值法构建土地利用功能分区方案。在此基础上,将XGBoost模型与SHAP解释方法相结合,定量剖析地形条件、气候要素及社会经济因子对景观生态风险产生的作用效应。
结果
2
1)依据土地利用功能可将安徽省划分为三大核心区域,其中生态保护核心区占比30.96%,农业生产核心区占比35.52%,建设开发核心区占比33.52%;在空间分布上,三者分别集中分布于皖南地区、皖北区域及皖中城市群一带。2)2000—2020年,区域景观生态风险整体呈不断加剧态势,较高风险区与高风险区面积占比由16.95%上升至32.81%。空间分布上,低风险区与生态保护区高度重合,而高风险区集中于建设开发区。3) 影响因素分析显示,地形因素对全省风险格局影响最大,气候因素是生态保护区和建设开发区的主导因子,而社会经济因素对农业生产区的风险影响最为显著。4) 全省生态风险冲突显著,较高及高风险冲突区占比为30.78%,主要分布于安庆、合肥等市。
结论
2
安徽省景观生态风险呈加剧态势,全省主要受地形因素影响,各分区受气候和社会经济因素驱动,高风险区集聚于建设开发核心区。建议实施基于功能分区的差异化管控策略,重点缓解安庆、合肥等地的空间冲突,以提升区域生态安全水平。研究结果可为国土空间规划与生态风险协同治理提供科学依据。
Objective
2
This study aims to scientifically delineate land use functional zones in Anhui Province, identify the key driving factors of landscape ecological risk, and reveal the spatiotemporal evolution characteristics and spatial conflict patterns of ecological risk, providing scientific support for regional ecological security and territorial space planning.
Methods
2
Taking Anhui Province as the study area, a land use functional zoning scheme was developed by integrating the morphological spatial pattern analysis (MSPA), Conefor, and minimum cumulative resistance (MCR) models and applying the resistance threshold method. On this basis, This study combines the XGBoost model with the SHAP interpretation method to quantitatively analyze the effects of topographic conditions, climatic factors, and socio-economic factors on landscape ecological risks.
Results
2
1)According to land use functions, Anhui Province can be divided into three core areas, among which the ecological protection core area accounts for 30.96%, the agricultural production core area accounts for 35.52%, and the construction and development core area accounts for 33.52%. Spatially, the three areas are respectively concentrated in the southern Anhui region, the northern Anhui region, and the urban agglomeration in central Anhui. 2) From 2000 to 2020, the overall landscape ecological risk in the region has been continuously intensifying, with the proportion of areas with high and very high risks increasing from 16.95% to 32.81%. In terms of spatial distribution, low-risk zones largely coincided with ecological protection zones, while high-risk zones were concentrated in construction development zones. 3) The analysis of influencing factors showed that topographic factors exerted the greatest influence on the provincial risk pattern. Climatic factors were the dominant factors in ecological protection and construction development zones, whereas socio-economic factors had the most significant influence on risk in agricultural production zones. 4) Ecological risk conflicts within the province were significant, with relatively high- and high-conflict zones accounting for 30.78%, mainly distributed in cities such as Anqing and Hefei.
Conclusion
2
Landscape ecological risk in Anhui Province shows an intensifying trend. The province is influenced by topographic factors, while different zones are driven by climatic and socio-economic factors, and high-risk zones are concentrated in construction development core zones. It is recommended to implement differentiated management strategies based on functional zoning, focusing on mitigating spatial conflicts in areas such as Anqing and Hefei to improve regional ecological security. The findings provide a scientific basis for the synergistic governance of territorial space planning and ecological risk.
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