不同格网尺度下生态系统服务价值空间分异及其影响因素差异——以大南昌都市圈为例

在江西省持续推进生态文明建设的背景下，生态系统服务价值（ESV）空间分异及其影响因素的探析对生态环境保护与改善、促进区域性可持续发展等方面具有重要意义。以大南昌都市圈为例，利用当量因子法、空间自相关分析等方法，分析1 km×1 km、3 km×3 km、5 km×5 km及10 km×10 km各个格网尺度下地均生态系统服务价值的空间分布特征，并利用地理探测器和空间回归模型，研究不同尺度下ESV空间异质性的影响因素及其尺度差异性。研究结果表明：（1） ESV分布总体呈现西北部高，东南部低的特点，且各种格网尺度下均存在显著空间正相关性和空间集聚效应，但随着格网尺度增大其集聚效应减弱。（2） ESV空间异质性受自然、社会的协同作用，其中，人为影响指数的贡献最大，且任意双因子都比单一因子对ESV空间异质性的解释力高，但随着格网尺度增大，各因子及因子间的耦合协调作用对ESV的解释力都呈下降趋势。（3）随着格网尺度的增大，空间回归模型的拟合度下降，且不同格网尺度下影响ESV空间异质性的影响因素的作用强度不同，作用方向也有发生变化。

Spatial difference of ecological services and its influencing factors under different scales: Taking the Nanchang Urban Agglomeration as an example

Under the background of continuously promoting the construction of ecological civilization in Jiangxi Province, analysis of the spatial differentiation of ecosystem service value (ESV) and its influencing factors is of great significance to the protection of ecological environment and the promotion of regional sustainable development. Taking the Nanchang Urban Agglomeration as an example, this paper uses the equivalent factor method and spatial autocorrelation analysis to analyze the spatial distribution characteristics of the average ESV at various grid scales of 1 km×1 km, 3 km×3 km, 5 km×5 km and 10 km×10 km. The influencing factors and scale differences of spatial heterogeneity of ESV at different scales are studied by using geographic detector and spatial regression model. This paper aims to reveal the role of various influencing factors in the Nanchang Urban Agglomeration on the spatial heterogeneity of ESV, and provides scientific basis for improving the quality of ecological environment and promoting green development. The results show that:(1) At different grid scales, the spatial distribution of the average ESV is relatively consistent, which is generally higher in the west and north, and lower in the east and south. There is significantly spatially positive correlation and spatial agglomeration effect at various grid scales, but the agglomeration effect decreases with the increase of grid scale. (2) The results of geographical detectors show that the spatial heterogeneity of ESV in the Nanchang Urban Agglomeration is affected by the synergy of natural environment and economic and social development. The degree of influence of different factors on ESV is significant. At different grid scales, the contribution of HAI is the largest, which is the leading factor affecting the spatial heterogeneity of the Greater Nanchang Metropolitan Area. The reason is that the increase of human activities, such as urban expansion and farmland reclamation, has led to changes in the structure of land use. This affects the spatial distribution of ESV. Moreover, any two factors have higher explanatory power for spatial heterogeneity of ESV than a single factor. However, with the increase of grid scale, the explanatory power of each factor and the coupling and coordination between factors for ESV decreases. (3) With the increase of grid scale, the fitting degree of spatial regression model decreases, and the action intensity and direction of the influencing factors affecting the spatial heterogeneity of ESV are different at different grid scales. At different grid scales, HAI has the strongest explanatory power to ESV, and has obviously negative effects, indicating that human activities have strong inhibition to ESV.