京津冀地区生态系统服务价值时空变化及驱动因子分析

基于京津冀地区2000年、2010年和2018年土地利用分类数据，通过分析土地利用结构及其动态变化、构建生态系统服务价值（ESV）模型，探究京津冀地区13个地市ESV的时空演变，运用地理探测器分析京津冀地区ESV驱动因子。结果表明：1）2000—2018年，耕地是京津冀地区最主要的土地利用类型，建设用地是面积和动态度变化最剧烈的土地利用类型。2）2000—2018年京津冀地区ESV呈先下降后上升趋势，调节服务与支持服务始终是京津冀地区生态系统服务的核心功能，其中水文调节的贡献率最大。3）从时间上看，京津冀地区地均生态系统服务价值（AESV）变化不大。从空间上看，京津冀地区AESV空间分布差异明显，高值区主要分布在冀北和京津地区，低值区主要分布在中南部的平原地区。京津冀各地市AESV的变化较为明显，大多数地市呈减少趋势。4）各土地利用类型的敏感性指数均小于1，其中林地的敏感性指数最高，对ESV的影响最大。5）地理探测器分析表明，京津冀地区AESV在空间上的分布差异受到区域自然因子、经济因子和社会因子共同作用，其中高程、地均GDP、人口密度等因子的贡献率较大，不同驱动力之间的交互作用对京津冀地区AESV的空间分异影响明显增强。

Spatio-temporal change and driving factor analysis of ecosystem service value in the Beijing-Tianjin-Hebei Region

Based on land use classification data in 2000, 2010 and 2018 in Beijing-Tianjin-Hebei Region, the spatial-temporal evolution of ecosystem service value (ESV) in 13 cities were explored by analyzing land use structure and dynamic changes and constructing the ESV model, and the driving factors of ESV in Beijing-Tianjin-Hebei Region were analyzed by geodetector. The results showed that: 1) From 2000 to 2018, cultivated land was the main land use type in Beijing-Tianjin-Hebei Region. Construction land was the land use type with the largest changes in area and amplitude. 2) From 2000 to 2018, ESV in Beijing-Tianjin-Hebei Region showed a downward trend and then an upward trend. Regulation services and support services were always the core functions of ecosystem services in Beijing-Tianjin-Hebei Region, in which hydrological regulation contributed the most. 3) In terms of time, the average ESV (AESV) of Beijing-Tianjin-Hebei Region had little change. From the perspective of space, the spatial distribution difference of AESV in Beijing-Tianjin-Hebei Region was obvious. The high value areas were mainly distributed in the northern Hebei and Beijing-Tianjin regions, and the low value areas were mainly distributed in the plain areas in the central and southern regions. The change of AESV in Beijing-Tianjin-Hebei Region was obvious, and most cities showed a decreasing trend. 4) The sensitivity index of each land use type was less than 1, and the sensitivity index of woodland was the highest, which had the greatest impact on ESV. 5) Geodetector analysis showed that the spatial distribution difference of AESV in Beijing-Tianjin-Hebei Region was affected by regional natural, economic and social factors. The contribution rate of elevation, average GDP and population density was larger. The interaction between different driving forces had a significant effect on the spatial differentiation of AESV in Beijing-Tianjin-Hebei Region.