横断山区产水服务空间异质性及归因分析  

Spatial heterogeneity and driving mechanisms of water yield service in the Hengduan Mountain region

作　　者：戴尔阜[1,2] 王亚慧 DAI Erfu;WANG Yahui(Lhasa Plateau Ecosystem Research Station,Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research,CAS,Beijing 100101,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院地理科学与资源研究所,生态系统网络观测与模拟重点实验室,拉萨高原生态系统研究站,北京100101 [2]中国科学院大学,北京100049

出　　处：《地理学报》2020年第3期607-619,共13页Acta Geographica Sinica

基　　金：国家重点基础研究发展计划(2015CB452702);国家自然科学基金项目(41571098,41530749);国家重点研发计划(2017YFC1502903);中国科学院科技战略咨询研究院重大咨询项目(Y02015003)。

摘　　要：包括产水服务在内的生态系统服务已被纳入区域土地利用规划以及可持续发展决策中,识别其空间分异特征及影响因素是进行决策的基础,而空间分异的定量归因研究仍需进一步加强。以空间异质性明显的中国横断山区为研究区,借助InVEST模型模拟产水服务空间分布,选择气候、地形、土壤、植被、土地利用等因子,采用地理探测器开展产水服务空间异质性归因分析。结果表明,①气候类因子是产水服务空间异质性的主要控制因子,其中以降水量和蒸散量为主。②在不同地貌及气候分区中,各因子对产水的空间分异的解释能力存在显著差异:平缓地区,蒸散量解释能力远高于降水量,随着起伏度的增大,降水量解释能力逐步增强,最终成为主要因子;在高原气候区,以蒸散量解释能力最强,而在中亚热带气候区,降水量为主要的控制因子。③值得注意的是,平缓地区土地利用类型因子的解释能力较为突出,在山区发展中应注意土地利用的合理规划,以减轻土地利用变化对产水服务空间变化的影响。④风险探测识别的产水服务重要区主要为初育土及人为土分布区、灌木林区以及坡度在≤5°和25°~35°区域,而其对应的高程值则在不同区域之间存在差异,因此,在横断山区产水服务的维持与保护工作中应充分考虑不同分区的具体情况。Ecosystem services, which include water yield services, have been incorporated into decision processes of regional land use planning and sustainable development. Spatial pattern characteristics and identification of factors that influence water yield are the basis for decision making. However, there are limited studies on the driving mechanisms that affect the spatial heterogeneity of ecosystem services. In this study, we used the Hengduan Mountain region in Southwest China, with obvious spatial heterogeneity, as the research site. The water yield module in the InVEST software was used to simulate the spatial distribution of water yield.Also, quantitative attribution analysis was conducted for various geomorphologic and climatic zones in the Hengduan Mountain region by using the geographical detector method.Influencing factors, such as climate, topography, soil, vegetation type, and land use type and pattern, were taken into consideration for this analysis. Four key findings were obtained. First,water yield spatial heterogeneity are influenced most by climate-related factors, among which precipitation and evapotranspiration are the dominant factors. Second, the relative importance of each impact factor to the water yield heterogeneity differs significantly by geomorphologic and climatic zones. In flat areas, the influence of evapotranspiration is higher than that of precipitation. As relief increases, the importance of precipitation increases and eventually, it becomes the most important factor. Evapotranspiration is the most important factor in a plateau climatic zone, while in the mid-subtropical zone, precipitation is the main controlling factor.Third, land use type is also an important driving force in flat areas. Thus, more attention should be paid to urbanization and land use planning, which involves land use changes, to mitigate the impact on water yield spatial pattern. The fourth finding was that a risk detector showed that Primarosol and Anthropogenic soil areas, shrub areas, and areas with slopes <5°

关 键 词：产水服务 InVEST模型 地理探测器 归因分析 横断山区 

分 类 号：X171.1[环境科学与工程—环境科学]