地质统计学
变异函数
空间变异性
草原
空间分布
空间分析
环境科学
空间异质性
空间相关性
土壤科学
土工试验
肥料
土壤水分
水文学(农业)
地理
农学
生态学
统计
数学
遥感
克里金
地质学
生物
岩土工程
作者
Weijun Fu,H. Tunney,Chaosheng Zhang
标识
DOI:10.1002/jpln.200800275
摘要
Abstract The spatial variation of soil test P (STP) in grassland soils is becoming important because of the use of STP as a basis for policies such as the recently EU‐introduced Nitrate Directive. This research investigates the spatial variation of soil P in grazed grassland plots with a long‐term (38 y) experiment. A total of 326 soil samples (including 14 samples from an adjacent grass‐wood buffer zone) were collected based on a 10 × 10 m 2 grid system. The samples were measured for STP and other nutrients. The results were analyzed using conventional statistics, geostatistics, and a geographic information system (GIS). Soil test P concentrations followed a lognormal distribution, with a median of 5.30 mg L –1 and a geometric mean of 5.35 mg L –1 . Statistically significant ( p < 0.01) positive correlation between STP and pH was found. Spatial clusters and spatial outliers were detected using the local Moran's I index (a local indicator of spatial association) and were mapped using GIS. An obvious low‐value spatial‐cluster area was observed on the plots that received zero‐P fertilizer application from 1968 to 1998 and a large high‐value spatial‐cluster area was found on the relatively high‐P fertilizer application plots (15 kg ha –1 y –1 ). The local Moran's I index was also effective in detecting spatial outliers, especially at locations close to spatial‐cluster areas. To obtain a reliable and stable spatial structure, semivariogram of soil‐P data was produced after elimination of spatial outliers. A spherical model with a nugget effect was chosen to fit the experimental semivariogram. The spatial‐distribution map of soil P was produced using the kriging interpolation method. The interpolated distribution map was dominated by medium STP values, ranging from 3 mg to 8 mg L –1 . An evidently low‐P‐value area was present in the upper side of the study area, as zero or short‐term P fertilizer was applied on the plots. Meanwhile, high‐P‐value area was located mainly on the plots receiving 15 kg P ha –1 y –1 (for 38 y) as these plots accumulated excess P after a long‐term P‐fertilizer spreading. The high‐ or low‐value patterns were in line with the spatial clusters. Geostatistics, combined with GIS and the local spatial autocorrelation index, provides a useful tool for analyzing the spatial variation in soil nutrients.
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