Key Laboratory of Ecohydrology of Inland River Basin, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
Key Laboratory of Ecohydrology of Inland River Basin, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China.
J Environ Manage. 2024 Jun;362:121335. doi: 10.1016/j.jenvman.2024.121335. Epub 2024 Jun 4.
Transitional features of desert environments partially determine the risks associated with ecosystems. Influenced by climate change and human activities, the variability and uncertainty of desertification levels and ecological risks in the Qinghai Area of Qilian Mountain National Park (QMNPQA) has become increasingly prominent. As a critical ecological barrier in northwest China, monitoring desertification dynamics and ecological risks is crucial for maintaining ecosystem stability. This study identifies the optimal monitoring model from four constructed desertification monitoring models and analyzes spatiotemporal changes in desertification. The spatial and temporal changes in ecological risks and their primary driving factors were analyzed using methods such as raster overlay calculation, geographic detector, cloud model, and trend analysis. The main conclusions are as follows: The desertification feature spatial model based on GNDVI-Albedo demonstrates better applicability in the study area, with an inversion accuracy of 81.24%. The levels of desertification and ecological risks in QMNPQA exhibit significant spatial heterogeneity, with a gradual decrease observed from northwest to southeast. From 2000 to 2020, there is an overall decreasing trend in desertification levels and ecological risks, with the decreasing trend area accounting for 89.82% and 85.71% respectively, mainly concentrated in the southeastern and northwestern parts of the study area. The proportion of areas with increasing trends is 4.49% and 7.05% respectively, scattered in patches in the central and southern edge areas. Surface temperature (ST), Digital Elevation Map (DEM), and Green normalized difference vegetation index (GNDVI) are the most influential factors determining the spatial distribution of ecological risks in QMNPQA. The effects of management and climatic factors on ecological risks demonstrate a significant antagonistic effect, highlighting the positive contributions of human activities in mitigating the driving effects of climate change on ecological risks. The research results can provide reference for desertification prevention and ecological quality improvement in QMNPQA.
荒漠环境的过渡特征部分决定了与生态系统相关的风险。受气候变化和人类活动的影响，祁连山国家公园青海片区（以下简称“青海片区”）荒漠化水平和生态风险的变异性和不确定性日益突出。作为中国西北的重要生态屏障，监测荒漠化动态和生态风险对于维护生态系统稳定性至关重要。本研究从构建的四个荒漠化监测模型中选择了最优的监测模型，并对荒漠化时空变化进行了分析。采用栅格叠加计算、地理探测器、云模型和趋势分析等方法，分析了生态风险的时空变化及其主要驱动因素。主要结论如下：基于 GNDVI-Albedo 的荒漠化特征空间模型在研究区具有更好的适用性，反演精度为 81.24%。青海片区的荒漠化和生态风险水平具有显著的空间异质性，从西北向东南逐渐降低。2000 年至 2020 年，荒漠化水平和生态风险呈整体下降趋势，下降趋势区分别占研究区的 89.82%和 85.71%，主要集中在研究区的东南和西北部分。分别有 4.49%和 7.05%的地区呈上升趋势，呈斑块状分布在研究区的中南部边缘地区。地表温度（ST）、数字高程图（DEM）和归一化植被指数（GNDVI）是决定青海片区生态风险空间分布的最主要因素。管理和气候因素对生态风险的影响表现出显著的拮抗作用，这突出了人类活动在减轻气候变化对生态风险的驱动作用方面的积极贡献。研究结果可为青海片区的荒漠化防治和生态质量改善提供参考。
