Spatial Variation of Soil P in Grassland - Fu, Weijun;Zhao, Keli
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The spatial variation of soil nutrients such as soil P is becoming important because of the use of STP as a basis for policies such as the EU-introduced Nitrate Directive. Traditionally, fertilizers have been applied to grasslands based on soil test results, without considering within-field spatial variability. Such agricultural management may be inefficient due to under-application or over-application in specific sites. Under-application zones do not reach optimal levels of grass yield whereas in over-application areas there will be an increase of costs and high risk of environmental…mehr

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Produktbeschreibung
The spatial variation of soil nutrients such as soil P is becoming important because of the use of STP as a basis for policies such as the EU-introduced Nitrate Directive. Traditionally, fertilizers have been applied to grasslands based on soil test results, without considering within-field spatial variability. Such agricultural management may be inefficient due to under-application or over-application in specific sites. Under-application zones do not reach optimal levels of grass yield whereas in over-application areas there will be an increase of costs and high risk of environmental pollution such as runoff with high P or nitrogen (N) concentrations which can cause water eutrophication. This book,therefore, provides a combined spatial analysis method (geostatistics, GIS and Moran's I) to reveal spatial pattern and to produce spatial distribution maps of soil nutrients at field- and farm- scales in temporate grasslands. Such information can provide useful information for agronomic and environmental management. Furthermore, the method should be useful for studying spatial variation of environmental variables.
Autorenporträt
Dr. Weijun Fu and Keli Zhao are Associate Professors in Zhejiang A & F University in China. They have published more than 50 peer-reviewed papers in scientific journals. Their research interests focus on spatial analyses of environmental variables, especially heavy metals in soils, using GIS, geostatistics and other spatial statistical techniques.