长江流域资源与环境 >> 2025, Vol. 34 >> Issue (1): 140-154.doi: 10.11870/cjlyzyyhj202501011

• 自然资源 • 上一篇    下一篇

小流域尺度生态系统服务的时空异质性及其影响因素分析——以府澴河流域为例

胡秀荣1,2,张雪松1,2*,彭宏杰1,2,周晓雯1,2   

  1. (1. 华中师范大学地理过程分析与模拟湖北省重点实验室,湖北 武汉 430079;2. 华中师范大学城市与环境科学学院,湖北 武汉 430079)
  • 出版日期:2025-01-20 发布日期:2025-01-24

Spatial-temporal Heterogeneity of Ecosystem Services at the Watershed Scale and Corresponding Social-Ecological Drivers: A Case of the Fuhuan River Basin, China

HU Xiu-rong1,2,ZHANG Xue-song1,2,PENG Hong-jie1,2,ZHOU Xiao-wen1,2   

  1. (1.Key Laboratory of Geographical Process Analysis and Simulation, Central China Normal University, Wuhan 430079, China;2.College of Urban and Environmental Sciences, Central China Normal University, Wuhan 430079, China)
  • Online:2025-01-20 Published:2025-01-24

摘要: 探究小流域尺度下多种生态系统服务时空格局和驱动因素是实施流域生态系统综合管理的前提。针对府澴河流域产水量、碳存储服务、土壤保持服务和生境质量的时空动态及其驱动因素进行研究。首先,通过量化方法描述了生态系统服务在网格尺度和子流域尺度上的时空异质性特征,并在子流域单元上识别多种生态系统服务簇。其次,利用地理探测器确定不同因素对生态系统服务的影响,最后构建时空地理加权回归(GTWR)模型探讨各影响因素的空间异质性。结果表明:(1)2000~2020年府澴河流域4种生态系统服务分布具有明显的时空异质性,但其空间格局保持相对稳定,研究区生态系统服务整体上呈现出上升趋势,在网格和子流域尺度上呈现相似的空间分布;(2)地理探测器结果显示,各因子的影响程度存在差异,DEM、年均降水量、人均GDP及人口密度是影响多种生态系统服务的主导因素,q值分别为0.64、0.52、0.47和0.44;此外,同一时段内,单一的自然社会因子在对各生态系统服务类型的贡献方面呈现出异质性,而在不同年份也展现出明显的差异特征。(3)GTWR模型结果表明,高程和降水与多种生态系统服务呈正相关,作用强度由东向西递减,人均GDP、人口密度与多种生态系统服务整体上呈负相关,但在中下游部分地区呈正相关。

Abstract: Exploring the spatial and temporal patterns and the drivers of multiple ecosystem services at the watershed scale is essential for implementing integrated watershed ecosystem management. This study focused on the spatial and temporal dynamics of water yield, carbon storage services, soil conservation services, and habitat quality, along with the drivers in the Fuhuan River Basin. Initially, the spatio-temporal heterogeneity of ecosystem services at the grid and sub-watershed scales was characterized using quantitative methods to identify multiple clusters of ecosystem services at the sub-watershed level. Subsequently, the geo-detector technique was applied to assess the impacts of various factors on ecosystem services. Finally, a spatio-temporal Geographically Weighted Regression (GTWR) model was developed to investigate the spatial heterogeneity of each influential factor. The findings revealed that: (i) the distribution of the four ecosystem services in the Fuhuan River Basin between 2000 and 2020 exhibited significant spatio-temporal heterogeneity, while maintaining a relatively stable spatial pattern. The overall trend of ecosystem services within the study area showed an upward trajectory, with similar spatial distributions observed at both grid and sub-basin scales; (ii) the geo-detector analysis indicated varying degrees of influence from different factors. The factors of Digital Elevation Model (DEM), mean annual precipitation, average land GDP, and population density were identified as dominant factors affecting multiple ecosystem services, with q-values of 0.64, 0.52, 0.47, and 0.44, respectively. Moreover, individual natural-social factors displayed heterogeneous contributions to each ecosystem service type over the same time period, exhibiting distinct variations across different years; (iii) results from the GTWR model demonstrated a positive correlation between elevation, precipitation, and multiple ecosystem services, with the effect intensity diminishing from east to west. Per capita GDP and population density were negatively correlated with overall ecosystem services, yet exhibited positive correlations in certain downstream areas.

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