Total nitrogen(TN),total phosphorus(TP),total potassium(TK),and soil organic matter(OM)can significantly affect forest growth.However,these soil properties are spatially heterogeneously distributed,complicating the pr...Total nitrogen(TN),total phosphorus(TP),total potassium(TK),and soil organic matter(OM)can significantly affect forest growth.However,these soil properties are spatially heterogeneously distributed,complicating the prescription of forest management strategies.Thus,it is imperative to obtain an in-depth understanding of the spatial distribution of soil properties.In this study,soils were sampled at 181 locations in the Tropical Forest Research Center in the southwestern Guangxi Zhuang Autonomous Region in southern China.We investigated the spatial variability of soil OM,TN,TP,and TK using geostatistical analysis.The nugget to sill ratio indicated a strong spatial dependence of soil TN and a moderate spatial dependence of soil OM,TP,and TK,suggesting that TN was primarily controlled by intrinsic factors(e.g.,soil texture,parent material,vegetation type,and topography),whereas soil OM,TP,and TK were controlled by intrinsic and extrinsic factors(e.g.,cultivation practices,fertilization,and planting systems).Based on the spatial variability determined by the geostatistical analysis,we performed ordinary kriging to create thematic maps of soil TN,TP,TK,and OM.Model validation indicated that the thematic maps were reliable to inform forest management.展开更多
Soil organic matter (SOM) content is one of the main factors to be considered in the evaluation of soil health and fertility. As timing, human and monetary resources often limit the amount of available data, geostatis...Soil organic matter (SOM) content is one of the main factors to be considered in the evaluation of soil health and fertility. As timing, human and monetary resources often limit the amount of available data, geostatistical techniques provide a valid scientific approach to cope with spatial variability, to interpolate existing data and to predict values at unsampled locations for accurate SOM status survey. Using geostatistical and geographic information system (GIS) approaches, the spatial variability of some physical and chemical soil parameters was investigated under Mediterranean climatic condition in the Abruzzo region of central Italy, where soil erosion processes accelerated by human induced factors are the main causes of soil degradation associated with low SOM content. Experimental semivariograms were established to determine the spatial dependence of the soil variables under investigation. The results of 250 soil sampling point data were interpolated by means of ordinary kriging coupled with a GIS to produce contour maps distribution of soil texture, SOM content related to texture, and C/N ratio. The resulting spatial interpolation of the dataset highlighted a low content of SOM in relation with soil texture in most of the surveyed area (87%) and an optimal C/N ratio for only half of the investigated surface area. Spatial location of degraded area and the assessment of its magnitude can provide decision makers with an accurate support to design appropriate soil conservation strategies and then facilitate a regional planning of agri-environmental measures in the framework of the European Common Agricultural Policy.展开更多
基金The National Key Research&Development Program of China(2016YFD060020501).
文摘Total nitrogen(TN),total phosphorus(TP),total potassium(TK),and soil organic matter(OM)can significantly affect forest growth.However,these soil properties are spatially heterogeneously distributed,complicating the prescription of forest management strategies.Thus,it is imperative to obtain an in-depth understanding of the spatial distribution of soil properties.In this study,soils were sampled at 181 locations in the Tropical Forest Research Center in the southwestern Guangxi Zhuang Autonomous Region in southern China.We investigated the spatial variability of soil OM,TN,TP,and TK using geostatistical analysis.The nugget to sill ratio indicated a strong spatial dependence of soil TN and a moderate spatial dependence of soil OM,TP,and TK,suggesting that TN was primarily controlled by intrinsic factors(e.g.,soil texture,parent material,vegetation type,and topography),whereas soil OM,TP,and TK were controlled by intrinsic and extrinsic factors(e.g.,cultivation practices,fertilization,and planting systems).Based on the spatial variability determined by the geostatistical analysis,we performed ordinary kriging to create thematic maps of soil TN,TP,TK,and OM.Model validation indicated that the thematic maps were reliable to inform forest management.
基金Supported by the Italian Ministry of Agricultural, Food and Forestry Policies (No. DM 19366)
文摘Soil organic matter (SOM) content is one of the main factors to be considered in the evaluation of soil health and fertility. As timing, human and monetary resources often limit the amount of available data, geostatistical techniques provide a valid scientific approach to cope with spatial variability, to interpolate existing data and to predict values at unsampled locations for accurate SOM status survey. Using geostatistical and geographic information system (GIS) approaches, the spatial variability of some physical and chemical soil parameters was investigated under Mediterranean climatic condition in the Abruzzo region of central Italy, where soil erosion processes accelerated by human induced factors are the main causes of soil degradation associated with low SOM content. Experimental semivariograms were established to determine the spatial dependence of the soil variables under investigation. The results of 250 soil sampling point data were interpolated by means of ordinary kriging coupled with a GIS to produce contour maps distribution of soil texture, SOM content related to texture, and C/N ratio. The resulting spatial interpolation of the dataset highlighted a low content of SOM in relation with soil texture in most of the surveyed area (87%) and an optimal C/N ratio for only half of the investigated surface area. Spatial location of degraded area and the assessment of its magnitude can provide decision makers with an accurate support to design appropriate soil conservation strategies and then facilitate a regional planning of agri-environmental measures in the framework of the European Common Agricultural Policy.
