基于地理探测器的泾河流域景观生态风险及驱动因素

doi:10.13866/j.azr.2025.08.12

Abstract

Abstract:

The ecological security of the Jinghe River Basin, a crucial component of the ecological barrier in northwest China, is of paramount importance. This study constructed a landscape ecological risk assessment model using land use data and landscape pattern indices to evaluate the dynamic characteristics of landscape ecological risk evolution in the Jinghe River Basin. Key driving factors affecting this risk were identified through geodetector analysis. The results revealed the following: (1) Cultivated land and grassland are the predominant landscape types in the basin, with frequent mutual transfer between the two. In addition, the construction land has shown a continuous expansion trend, increasing by a total of 394.5 km² during the study period. (2) Medium-risk areas account for over 41% of the landscape ecological risk types in the Jinghe River Basin. High- and medium-high-risk areas are primarily located along the Jinghe River network, particularly concentrated in the middle and southeastern flat terrain, together constituting about one-tenth of the basin area. Low-risk areas are predominantly found in the eastern and southwestern parts of the basin, where human interference is minimal. (3) Throughout the study period, more than 80% of the basin’s areas maintained stable risk levels, contributing to a reduction in the overall landscape ecological risk. (4) The main driving factors influencing landscape ecological risk include average annual temperature, GDP density, and elevation. The interaction between average annual temperature, average annual precipitation, and other influencing factors has significant effects on landscape ecological risk.

Key words: landscape ecological risk, space-time evolution, geographical detector, driving factor, Jinghe River Basin

LIU Fenglian, LUO Qinqin, YANG Bowen, CHEN Hongmin, GAO Ziyi. Landscape ecological risk and driving factors in the Jinghe River Basin based on geodetector analysis[J].Arid Zone Research, 2025, 42(8): 1488-1500.

Figures/Tables 11

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名称	公式	含义
景观破碎度指数（P_i）	${P}_{i}=\frac{{n}_{i}}{{A}_{i}}$	指景观被分割成不连续、破碎化斑块的程度，是衡量区域景观空间复杂性的重要指标
景观分离度指数（K_i）	${K}_{i}=\frac{1}{2}\times \frac{A}{{A}_{i}}\sqrt{\frac{{n}_{i}}{{A}_{i}}}$	指同一类型景观的不同斑块之间在空间上的分离程度，用于反映景观在空间分布上的分散状态
景观优势度指数（T_i）	${T}_{i}=\frac{{S}_{i}+{U}_{i}}{4}+\frac{{L}_{i}}{2}$	用于测度整体景观结构中某一景观类型支配其他景观类型的程度，反映景观在生态、美学和社会层面上的优势度
景观干扰度指数（G_i）	${G}_{i}=a{P}_{i}+b{K}_{i}+c{T}_{i}$	用于表示景观生态环境受外界因素活动影响的程度
景观脆弱度指数（W_i）	建设用地赋值为1，林地为2，草地为3，耕地为4，水域为5，未利用地为6，进行归一化处理	指用于衡量景观系统对外界干扰的敏感性和恢复能力
景观损失度指数（X_i）	X_i=G_i×W_i	指景观生态系统在受到外界因素影响后受损状况和恢复能力的强弱

变化趋势	2000—2010年		2010—2020年		2000—2020年
变化趋势	面积/km²	占比/%	面积/km²	占比/%	面积/km²	占比/%
稳定	3.83×10⁴	82.35	4.13×10⁴	88.71	3.74×10⁴	80.24
升高	924.81	1.99	2681.24	5.74	1725.17	3.71
降低	7022.51	15.07	2080.93	4.47	6888.20	14.78
显著升高	172.30	0.37	398.68	0.86	396.27	0.85
显著降低	101.91	0.22	100.56	0.22	196.07	0.42

影响因素	因子/序号	贡献度/%
影响因素	因子/序号	2000年	2005年	2010年	2015年	2020年
自然因素	高程（X1）	17.23	22.09	22.31	19.86	20.66
	NDVI（X2）	6.56	7.06	5.61	6.37	2.37
	年均降水量（X3）	5.54	5.98	7.90	8.03	13.34
	年均气温（X4）	19.56	24.57	25.53	23.03	24.48
社会经济因素	人口密度（X5）	1.60	5.08	5.71	5.33	7.65
	夜间灯光（X6）	19.19	8.31	6.46	5.29	5.99
	GDP密度（X7）	21.50	18.27	18.70	18.54	18.44
	人为干扰度（X8）	8.82	8.64	7.78	13.55	7.07

Landscape ecological risk and driving factors in the Jinghe River Basin based on geodetector analysis

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