Spatial variation of soil test phosphorus in a long‐term grazed experimental grassland field

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 grasswood 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.

Using Moran's I and GIS to study spatial pattern of forest litter carbon density in typical subtropical region, China

“…5. Significant positive spatial autocorrelation (Moran's I = 0.112, p < 0.05) was observed for FLC density, revealing the existence of potential spatial patterns in their spatial distribution (Fu et al, 2010).…”

Guiding fall fertilization of cool‐season turfgrass lawns with verdure tissue‐N tests

“…The 23.6% CV of total N concentrations and 55.1% CV for fresh sap NO 3 –N concentrations are within reported CV ranges of 18–54% for tissue nutrient concentrations in cool‐season grasses (Bailey, Beattie, & Kilpatrick, 1997). The CV for extractable soil nutrients in turfgrass and grassland soils can range from 4 to 66% (Donohue, 2002; Fu, Tunney, & Zhang, 2010; Trotter et al., 2014). Therefore, verdure sampling for total N and fresh sap NO 3 –N tests would not be any more variable or less reliable than the currently recommended turfgrass soil and tissue tests used to guide nutrient management.…”

Soil phosphorus dynamics along a loess–limestone transect in Mihla, Thuringia (Germany)

“…As soil P originally comes from bedrock ( Smeck , ; Kruse et al, ), bedrock and substratum are often expected to shape the spatial P distribution most ( Blume et al, ; Fu et al, ; Pecoroni et al, ). In our study bedrock/substrata by their geogenic loading draw a general frame of P levels to be expected in a certain area.…”