气候与社会经济因素对土壤有机质影响的空间异质性分析——以黑龙江省中部地区为例  

Influence of spatial heterogeneity of climatic and socio-economic factors on soil organic matter——A case study of the central Heilongjiang Province, China

作　　者：石淑芹[1] 曹祺文[1] 李正国[2,3] 许恒周[4] 

机构地区：[1]天津工业大学管理学院,天津300387 [2]农业部农业信息技术重点实验室,北京100081 [3]中国农业科学院农业资源与农业区划研究所,北京100081 [4]天津大学管理学院,天津300372

出　　处：《中国生态农业学报》2014年第9期1102-1112,共11页Chinese Journal of Eco-Agriculture

基　　金：国家自然科学基金项目(41101537;40930101;41201184和71203157);国家重点基础研究发展计划(973计划)项目(2010CB951502)资助

摘　　要：为探讨土壤性质对外部因素的响应机制及空间规律,本文以黑龙江省中部为例,利用地统计学理论、GIS空间分析与地理加权回归模型(geographically weighted regression,GWR),从空间分异角度分析了气候和社会经济因素对土壤有机质的影响程度。结果表明,有机质含量分布在研究区域西部呈现出东高西低的特征,在研究区域东部则表现为中部高南北低;气候变量(均在0.01水平上显著)中,降水和年均温对有机质含量以负影响为主;年日照时数对除嫩江平原西南部和松江平原南部外的多数区域有机质含量产生正影响。社会经济因素(均在0.01水平上显著)中机械化耕作水平对嫩江平原北部、西部和克拜丘陵部分区域有机质含量产生正影响;灌溉面积对有机质含量的正影响范围较广;施肥量对嫩江平原南部、松江平原西北部和三江低平原东北部等有机质含量主要产生负影响,其他区域则主要为正效应;地膜用量对有机质含量的正影响范围较广;农药用量对研究区域西部以正影响为主,对东部以负影响为主。因此,反映自然条件差异的气候因素与反映农业投入的社会经济因素对土壤有机质的影响均具有空间异质性,采用允许局部估计的GWR模型是适合的。The aim of this paper was to provide methodological support for understanding the response mechanism of soil properties to external factors and the related spatial distribution, which could also serve as a decision-making reference for farmers and agricultural management authorities. Using geostatistical theory, spatial analysis in GIS and geographically weighted regression （GWR） model, the study analyzed the response of soil organic matter to climatic and socio-economic factors in the central Heilongjiang Province in years of 2000 to 2005. For the period 2005, soil organic matter was spatially interpolated along with auxiliary soil type and pH datasets using Co-Kriging in GIS and the temporal variability analyzed. The result showed that in the western region of the study area, organic matter was higher in the east than in the west. Then in the eastern region of the study area, organic matter was higher in the central zone than in the northern and southern zones. Based on conventional regression model and variance inflation factor （VIF）, the paper selected suitable variables for GWR model. Spatial autocorrelation analysis of soil organic matter content yielded global Moran’s I index of 0.433 （P=0.00）, indicating that significant spatial autocorrelation in soil organic＆amp;nbsp;matter. Thus the GWR model was considered to be suitable for local parameter estimation and was used to determine the relationship between organic matter content and its driving factors. The CV method was used to determine the optimal bandwidth and to establish an adaptive kernel-type GWR model. Results showed that the GWR model accounted for over 57% of the total variance in soil organic matter content in the region. The spatial stability of the strength of the influence of each variable on organic matter content was analyzed. It showed that all variables had significant spatial instability. In addition, the minimum, maximum, upper quartile and lower quartile of the regression coefficients of the variables were largely diff

关 键 词：土壤有机质 气候因素 社会经济因素 地理加权回归 空间异质性 黑龙江省 

分 类 号：S151.95[农业科学—土壤学] S17[农业科学—农业基础科学]