Within-field variability of mineral nitrogen in grassland

Abstract

The within-field variability of soil mineral nitrogen (N-min) in a grazed grassland of 8000 m(2) was examined. NO3--N concentrations were characterized by a high spatial variability. This can be explained by the uneven deposition of animal excreta. All NH4+-N as well as NO3--N values were lognormally distributed, be fore and after the grazing season. At the end of the grazing season the largest part of the variability of NO3--N was found for NO3--N concentrations measured within a distance of a few metres. A high variability for NO3--N over very short distances was also indicated by a large nugget variance. During the grazing season, observed mean N-mn, values increased from 22 to 132 kg N ha(-1). Regions with clearly higher NO3--N concentrations could be identified. These zones matched with the drinking place and the entrance of the pasture, places which were more frequently visited than others. High residual N levels in autumn led to relatively high losses of N, mostly by leaching, during the subsequent drainage period. Knowing the variability of N-min, the number of samples needed to estimate the average N-min in a field could be calculated for different probabilities and various degrees of precision. From the spatial distribution of the N-min concentrations and the restrictions imposed by the new European decree, adapted fertilizer strategies can be proposed at least for places where systematically higher N-min concentrations can be expected

Characterising the within-field scale spatial variation of nitrogen in a grassland soil to inform the efficient design of in-situ nitrogen sensor networks for precision agriculture

“…These results contrast with similar studies performed on arable soils, which were characterised by ranges of spatial dependencies for NO 3 À of greater than 39 m (van Meirvenne et al, 2003;Haberle et al, 2004). The observed variation at larger spatial-scales, especially NO 3 À , could be due to the habit of sheep to frequent certain areas of the pasture such as paths, a drinking trough and areas of shade (Bogaert et al, 2000).…”

“…The proportion of the total accumulated variance attributed to the 1-cm scale was much larger for amino acid-N and NH 4 + -N than NO 3 -N which may be related to their relative diffusion coefficients, interactions with the solid phase (Owen and Jones, 2001) and the rapid rate of amino acid turnover and mineralisation in this soil (Jones et al, 2004;Wilkinson et al, 2014). Similar small-scale variation of NO 3 À in grazed pastures has been identified in previous studies, with semi-variograms exhibiting the range of spatial dependency of less than 5 m (White et al, 1987;Broeke et al, 1996;Wade et al, 1996;Bogaert et al, 2000), and a nugget variance of 60% (Bogaert et al, 2000). These results contrast with similar studies performed on arable soils, which were characterised by ranges of spatial dependencies for NO 3 À of greater than 39 m (van Meirvenne et al, 2003;Haberle et al, 2004).…”

“…In particular, it was necessary to examine the relative importance of variance between and within local regions each of which might be represented by a cluster of soil N sensors deployed around a single data logger such that the maximum distance between any two sensors is about 2 m. In a grassland environment it was expected that one of the main sources of variation in soil N would be the uneven and relatively random distribution of urine patches of linear dimensions about 40 cm (Bogaert et al, 2000;Selbie et al, 2015). Variation at larger scales may also be important due to preferential use of certain areas of the field such as tracks, areas of shade and around drinking troughs (Bogaert et al, 2000), which may be reflected in local gradients in soil chemistry. The study field is broadly homogenous in terms of its topography and soil type.…”

A comprehensive study of nutrient losses, soil properties and groundwater concentrations in a degraded peatland used as an intensive meadow – Implications for re-wetting

“…When splitting the data set, the data was strongly skewed: the N t and C org data of the mineral soil samples (C org < 15%) was right-skewed, while the data of the organic soil samples (C org > 15%) was left-skewed. Logarithmic transformation of the subset 'mineral soil' led to a normal distribution, which is typical for many properties of mineral soils (Bogaert et al, 2000;Cambardella et al, 1994). In transect A and B, the soil samples (N t and C org ) were also distributed bimodally, and splitting the data set showed that the data of the mineral subset was rightskewed, while the subset 'organic soil' was left-skewed (Tables 4 and 5).…”

Application of a widely used denitrification model to Dutch data sets

“…(2) above were chosen based on reported variation coefficients (in percent) for denitrification, nitrate content, water-filled pore space and soil temperature (e.g., Christensen et al, 1990;Clemens et al, 1999;Luo et al, 1999;Rö ver and Kaiser, 1999;Rö ver et al, 1999;Bogaert et al, 2000;Luo et al, 2000;Yanai et al, 2003); i.e., denitrification in range [6%-1677%], N in range [11%-256%], S in range [6%-11%], and for T one value was reported, namely, 4%. Thus, errors in S and T are relatively small, while those for N and D r are relatively large.…”