RATIONALE: Organic nitrogen (N) greatly exceeds inorganic N in soils, but the complexity and heterogeneity of this important soil N pool make investigations into the fate of N-containing additions and soil organic N cycling challenging. This paper details a novel approach to investigate the fate of applied N in soils, generating quantitative measures of microbial assimilation and of newly synthesized soil protein. METHODS:Laboratory incubation experiments applying 15 N-ammonium, 15 N-nitrate and 15 N-glutamate were carried out and the high sensitivity and selectivity of gas chromatography/combustion/isotope ratio mass spectrometry (GC/C/IRMS) exploited for compound-specific 15 N stable isotope probing ( 15 N-SIP) of extracted incubation soil amino acids (AAs; as N-acetyl, O-isopropyl derivatives). We then describe the interpretation of these data to obtain a measure of the assimilation of the applied 15 N-labelled substrate by the soil microbial biomass and an estimate of newly synthesised soil protein. RESULTS:The cycling of agriculturally relevant N additions is undetectable via bulk soil N content and δ 15 N values and AA concentrations. The assimilation pathways of the three substrates were revealed via patterns in AA δ 15 N values with time, reflecting known biosynthetic pathways (e.g. ammonium uptake occurs first via glutamate) and these data were used to expose differences in the rates and fluxes of the applied N substrates into the soil protein pool (glutamate > ammonium > nitrate). CONCLUSIONS: Our compound-specific 15 N-SIP approach using GC/C/IRMS offers a number of insights, inaccessible via existing techniques, into the fate of applied 15 N in soils and is potentially widely applicable to the study of N cycling in any soil, or indeed, in any complex ecosystem.

Although amino sugars represent a major component of soil organic nitrogen (ON), the assimilation of nitrate (NO3 −) and ammonium (NH4 +) into amino sugars (AS) by soil bacteria and fungi represents a neglected aspect of the global N cycle. A deeper knowledge of AS responses to N fertiliser addition may help enhance N use efficiency (NUE) within agricultural systems. Our aim was to extend a sensitive compound-specific 15 N-stable isotope probing (SIP) approach developed for amino acids to investigate the immobilization of inorganic N into a range of amino sugars (muramic acid, glucosamine, galactosamine, mannosamine). Laboratory incubations using 15 N-ammonium and 15 N-nitrate applied at agriculturally relevant rates (190 and 100 kg N ha −1 for 15 NH4 + and 15 NO3 − , respectively) were carried out to obtain quantitative measures of N-assimilation into the AS pool of a grassland soil over a 32-d period. Using gas chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS) we found that δ 15 N values for individual AS reflected differences in routing of the applied ammonium and nitrate. The contrasting N-assimilation dynamics of bacterial and fungal communities were demonstrated through determinations of percentage 15 N incorporation into diagnostic AS. Nassimilation dynamics of the bacterial community were altered with the applied substrate whilst fungal N-assimilation dynamics were unaffected. Rates and fluxes of the applied N-substrates into the bacterial AS pool reflected known biosynthetic pathways for AS, with fungal glucosamine appearing to be biosynthetically further from the applied substrates than bacterial glucosamine due to different turnover rates. This sensitive and specific compound-specific 15 N-SIP approach using AS, building on existing approaches with amino acids (AA), enables differentiation of N-assimilation dynamics within the microbial community and assessment of microbial NUE with agriculturally relevant fertilisation rates.

Nitrous oxide (N2O) is an air pollutant of major environmental concern, with agriculture representing 60% of anthropogenic global N2O emissions. Much of the N2O emissions from livestock production systems result from transformation of N deposited to soil within animal excreta. There exists a substantial body of literature on urine patch N2O dynamics, we aimed to identify key controlling factors influencing N2O emissions and to aid understanding of knowledge gaps to improve GHG reporting and prioritize future research. We conducted an extensive literature review and random effect meta‐analysis (using REML) of results to identify key relationships between multiple potential independent factors and global N2O emissions factors (EFs) from urine patches. Mean air temperature, soil pH and ruminant animal species (sheep or cow) were significant factors influencing the EFs reviewed. However, several factors that are known to influence N2O emissions, such as animal diet and urine composition, could not be considered due to the lack of reported data. The review highlighted a widespread tendency for inadequate metadata and uncertainty reporting in the published studies, as well as the limited geographical extent of investigations, which are more often conducted in temperate regions thus far. Therefore, here we give recommendations for factors that are likely to affect the EFs and should be included in all future studies, these include the following: soil pH and texture; experimental set‐up; direct measurement of soil moisture and temperature during the study period; amount and composition of urine applied; animal type and diet; N2O emissions with a measure of uncertainty; data from a control with zero‐N application and meteorological data.

Adequately estimating soil nitrous oxide (N 2 O) emissions using static chambers is challenging due to the high spatial variability and episodic nature of these fluxes. We discuss how to design experiments using static chambers to better account for this variability and reduce the uncertainty of N 2 O emission estimates. This paper is part of a series, each discussing different facets of N 2 O chamber methodology. Aspects of experimental design and sampling affected by spatial variability include site selection and chamber layout, size, and areal coverage. Where used, treatment application adds a further level of spatial variability. Time of day, frequency, and duration of sampling (both individual chamber closure and overall experiment duration) affect the temporal variability captured. We also present best practice recommendations for chamber installation and sampling protocols to reduce further uncertainty. To obtain the best N 2 O emission estimates, resources should be allocated to minimize the overall uncertainty in line with experiment objectives. Sometimes this will mean prioritizing individual flux measurements and increasing their accuracy and precision by, for example, collecting four or more headspace samples during each chamber closure. However,

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