Spatial Correlation between the Changes in Supply and Demand for Water-Related Ecosystem Services
Spatial Correlation between the Changes in Supply and Demand for Water-Related Ecosystem Services
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DOI：
10.3390/ijgi13030068
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发表时间：
2024-02
期刊：
影响因子：
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通讯作者：
Yuncheng Jiang;Bin Ouyang;Zhigang Yan
中科院分区：
文献类型：
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作者：
Yuncheng Jiang;Bin Ouyang;Zhigang Yan
阐明与水相关的生态系统服务（WES）供需的时空变化可以为生态治理决策提供全面的支持信息。然而，可持续能源服务的供给和需求之间的空间不匹配往往被忽视，导致缺乏有针对性的决策。在网格尺度上，在保留自然属性和社会属性的前提下，定量分析了2000 - 2020年南河流域水环境服务供给和需求的时空变化。生态分区的基础上的WESs的供应和需求的时间变化。运用OPGD模型，考察了社会经济和自然因素对不同区域水环境服务供给要素的影响，并进一步探讨了不同区域水环境服务供需变化的空间相关性。研究结果表明，水环境服务供给与需求变化存在显著的空间异质性。经济带和特大城市发生了显著变化，可持续能源供给减少，需求增加。可再生能源需求变化显著影响可再生能源供给变化。所有地区的WES供应受WES需求的影响。在高供给低需求区间，WY对WES需求变化的解释力最高。从高供给-中等需求区到低供给-中等需求区再到高供给-高需求区，PE对WES需求变化的解释力逐渐增强。随着WES的需求从中间层次开始，HAI逐渐主导WES的需求变化。土地利用变化的增加可能会促进WES需求变化对WES供给变化的影响。该研究有助于将水环境系统的供需变化及其相互关系纳入生态保护与恢复体系，为区域可持续管理提供新的视角和方法。
Clarifying the spatiotemporal changes in the supply and demand of water-related ecosystem services (WESs) can provide comprehensive support information for ecological governance decisions. However, the spatial mismatch between the supply and demand of WESs is often overlooked, resulting in a lack of targeted decision-making. At the grid scale, while preserving both natural and social attributes, this study quantitatively analyzed the spatiotemporal changes in the supply and demand of WESs in the Southern River Basin from 2000 to 2020. Ecological zoning was performed based on the temporal changes in WESs supply and demand. The OPGD model was used to investigate the impacts of socio-economic and natural factors on different WESs supply factors and further explore the spatial correlation of WESs supply and demand changes in different zones. The results show that there is significant spatial heterogeneity in the changes in WESs supply and demand. Economic belts and megacities have experienced remarkable changes, with WESs supply decreasing and WESs demand increasing. WESs demand changes significantly affect WESs supply changes. The supply of WESs in all zones is influenced by WESs demand. In the high supply–low demand zone, WY has the highest explanatory power for WESs demand changes. From the high supply–middle demand zone to the low supply–middle demand zone and then to the high supply–high demand zone, the explanatory power of PE for WESs demand changes gradually increases. As WESs demand starts from the middle level, HAI gradually dominates WESs demand changes. The increase in land use changes may promote the impact of WESs demand changes on WESs supply changes. This study contributes to incorporating the supply and demand changes of WESs and their correlations into the ecological protection and restoration system, providing a new perspective and method for regional sustainable management.