王舒, 刘凤莲, 陈威廷, 刘艳, 蔡巍. 滇中高原湖泊流域景观生态风险评价及驱动因素识别[J]. 中国生态农业学报 (中英文), 2024, 32(3): 391−404. DOI: 10.12357/cjea.20230412
引用本文: 王舒, 刘凤莲, 陈威廷, 刘艳, 蔡巍. 滇中高原湖泊流域景观生态风险评价及驱动因素识别[J]. 中国生态农业学报 (中英文), 2024, 32(3): 391−404. DOI: 10.12357/cjea.20230412
WANG S, LIU F L, CHEN W T, LIU Y, CAI W. Landscape ecological risk evaluation and driving factors in the lake basin of Central Yunnan Plateau[J]. Chinese Journal of Eco-Agriculture, 2024, 32(3): 391−404. DOI: 10.12357/cjea.20230412
Citation: WANG S, LIU F L, CHEN W T, LIU Y, CAI W. Landscape ecological risk evaluation and driving factors in the lake basin of Central Yunnan Plateau[J]. Chinese Journal of Eco-Agriculture, 2024, 32(3): 391−404. DOI: 10.12357/cjea.20230412

滇中高原湖泊流域景观生态风险评价及驱动因素识别

Landscape ecological risk evaluation and driving factors in the lake basin of Central Yunnan Plateau

  • 摘要: 滇中高原湖泊流域位于我国西南生态安全屏障内, 担负着擘画生态文明新蓝图的重任。评估流域景观生态风险、揭示驱动因素是保障其生态功能稳定性和防控生态风险的关键。本文基于2000年、2005年、2010年、2015年、2020年的土地利用数据, 借助ArcGIS 10.8和Fragstatas 4.2构建景观生态风险评价模型, 运用空间分析工具探究流域景观生态风险的时空分异特征和变化趋势, 采用地理探测器识别全流域及局部区域自然因素和社会经济因素对景观生态风险的影响。研究结果显示: 1) 2000—2020年, 林地和耕地是滇中高原湖泊流域内面积最大的景观, 未利用地的面积最小。2)研究区内景观生态风险以中风险、中低风险为主。高风险区位于滇池以北, 呈扩张趋势并向西北和东南方向延伸; 中风险区、中高风险区不断向中部压缩; 中低风险区、低风险区主要位于湖泊周围及流域北部, 并围绕这些区域向外扩张。3)流域内大部分区域生态系统较为稳定, 等级未发生变化。景观生态风险整体呈下降趋势, 生态系统发展向好。4)从整体来看, 景观生态风险主要受植被归一化指数、夜间灯光等因子的影响; 从局部来看, 夜间灯光、年降水量、植被归一化指数对景观生态风险影响较为显著。为此, 滇中高原湖泊流域的景观生态风险具有明显的空间分布格局及变化特征并被多种因素驱动, 相关政策的制定应围绕这些方面展开。

     

    Abstract: The lake basin of the Central Yunnan Plateau is located in the ecological security zone of southwest China. Therefore, it bears the important responsibility of drawing a new blueprint for ecological civilization. Assessing the landscape ecological risk of the basin and revealing the driving factors are key to guaranteeing the stability of its ecological function and controlling the ecological risk. Therefore, this study used the land use data of 2000, 2005, 2010, 2015, and 2020 to construct a long-term series landscape ecological risk assessment model using ArcGIS 10.8 and Fragstatas 4.2. Furthermore, spatial analysis tools were used to explore the spatial and temporal characteristics of the landscape ecological risk of the basin and its trend, whereas geographic probes were utilized to explore the influence mechanism of natural factors and socioeconomic factors on landscape ecological risk from the whole basin and in local areas. The results of the study showed that: 1) From 2000 to 2020, woodland and cultivated land were the largest landscapes in the lake basin of the Central Yunnan Plateau, accounting for more than 67% of the total basin area; unused land was the smallest, accounting for less than 0.2% of the total basin area, whereas construction land showed an expanding trend. 2) The ecological risk of the landscapes in the study area was dominated by medium-risk and medium-low-risk landscapes, which accounted for more than 50% of the total basin area. The high-risk area was located in the Wuhua District, Panlong District, Guandu District, and Xishan District north of Dianchi Lake, with an expanding trend to the northwest and southeast; medium-high-risk and medium-risk areas were mainly located in the Dianchi Lake Basin, which was constantly compressed to the center, whereas medium-low-risk and low-risk areas were closely connected, mainly located around the lakes and in the northern part of the basin, and expanding outward around these areas. 3) During the study period, most ecosystems in the basin were relatively stable, and more than 70% of the areas remained unchanged. The levels increased in relatively densely populated areas and did not change or even decrease in more ecologically favorable areas. The landscape ecosystems experienced the transformation process of improvement followed by deterioration, continuous deterioration, and then improvement. Overall, the landscape ecological risk showed a decreasing trend, and the ecosystems developed well. 4) From an overall perspective, the results of single-factor detection showed that the landscape ecological risk was mainly affected by factors such as the normalized difference in vegetation index and nighttime lighting. The results of interaction factor detection showed that the interaction of these factors enhanced the spatial evolution of landscape ecological risk compared with the individual factors, and the normalized difference in vegetation index, nighttime lighting, population density, and elevation had the greatest effect on landscape ecological risk. From a local perspective, natural factors have a greater influence on the evolution of ecological risk in the landscape than socioeconomic factors, mainly influenced by factors such as nighttime light, annual precipitation, and normalized difference vegetation index. Based on the findings of this study, suggestions for improving the ecological environment should focus on spatial differentiation patterns, changing characteristics, and the driving factors.

     

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