Impact of nitrogen and phosphorus additions on soil gross nitrogen transformations in a temperate desert steppe

Nutrient addition has a significant impact on plant growth and nutrient cycling. Yet, the understanding of how the addition of nitrogen (N) or phosphorus (P) significantly affects soil gross N transformations and N availability in temperate desert steppes is still limited. Therefore, a ¹⁵N tracing experiment was conducted to study these processes and their underlying mechanism in a desert steppe soil that had been supplemented with N and P for 4 years in northwestern China. Soil N mineralization was increased significantly by P addition, and N and P additions significantly promoted soil autotrophic nitrification, rather than NH₄⁺-N immobilization. The addition of N promoted dissimilatory NO₃⁻ reduction to NH₄⁺, while that of P inhibited it. Soil NO₃⁻-N production was greatly increased by N added alone and by that of N and P combined, while net NH₄⁺-N production was decreased by these treatments. Soil N mineralization was primarily mediated by pH, P content or organic carbon, while soil NH₄⁺-N content regulated autotrophic nitrification mainly, and this process was mainly controlled by ammonia-oxidizing bacteria rather than archaea and comammox. NH₄⁺-N immobilization was mainly affected by functional microorganisms, the abundance of narG gene and comammox Ntsp-amoA. In conclusion, gross N transformations in the temperate desert steppe largely depended on soil inorganic N, P contents and related functional microorganisms. Soil acidification plays a more key role in N mineralization than other environmental factors or functional microorganisms.     

Sustainable grassland systems: a modelling perspective based on the North Wyke Farm Platform

The North Wyke Farm Platform (NWFP) provides data from the field‐ to the farm‐scale, enabling the research community to address key issues in sustainable agriculture better and to test models that are capable of simulating soil, plant and animal processes involved in the systems. The tested models can then be used to simulate how agro‐ecosystems will respond to changes in the environment and management. In this study, we used baseline datasets generated from the NWFP to validate the Soil‐Plant‐Atmosphere Continuum System (SPACSYS) model in relation to the dynamics of soil water content, water loss from runoff and forage biomass removal. The validated model, together with future climate scenarios for the 2020s, 2050s and 2080s (from the International Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES): medium (A1B) and large (A1F1) emission scenarios), were used to simulate the long‐term responses of the system with three contrasting treatments on the NWFP. Simulation results demonstrated that the SPACSYS model could estimate reliably the dynamics of soil water content, water loss from runoff and drainage, and cut biomass for a permanent sward. The treatments responded in different ways under the climate change scenarios. More carbon (C) is fixed and respired by the swards treated with an increased use of legumes, whereas less C was lost through soil respiration with the planned reseeding. The deep‐rooting grass in the reseeding treatment reduced N losses through leaching, runoff and gaseous emissions, and water loss from runoff compared with the other two treatments.     

Using time domain reflectometry to characterize cattle and pig slurry infiltration into soil

Abstract. The rate and extent to which cattle or pig slurry infiltrates into soil after application is one of the important factors determining the rate and extent of subsequent ammonia (NH₃) volatilization. Better characterization of the infiltration process is required to improve predictive models of NH₃ losses after land spreading. This paper describes a laboratory system using time domain reflectometry to measure slurry infiltration into soil columns. This system enabled semi-continuous, non-destructive infiltration measurements to be made, assessing the influence of slurry type, dry matter (DM) content, soil type and soil water tension. Differences were noted in the infiltration behaviour of cattle and pig slurries. For cattle slurry, DM content (range 1.7–7.1%) was the main influencing factor. Infiltration rate rapidly decreased with increasing DM content and there was no influence of soil type or water tension. For pig slurry, all of the slurry infiltrated into a sandy clay loam soil within the first hour, regardless of DM content (range 1.5–4.7%), whereas only 60% infiltrated into a clay loam soil over the same time period (slurry DM content 2.1%).     

Optimizing chamber methods for measuring nitrous oxide emissions from plot‐based agricultural experiments

Nitrous oxide emissions (N₂O) from agricultural land are spatially and temporally variable. Most emission measurements are made with small (? 1 m² area) static chambers. We used N₂O chamber data collected from multiple field experiments across different geo‐climatic zones in the UK and from a range of nitrogen treatments to quantify uncertainties associated with flux measurements. Data were analysed to assess the spatial variability of fluxes, the degree of linearity of headspace N₂O accumulation and the robustness of using ambient air N₂O concentrations as a surrogate for sampling immediately after closure (T₀). Data showed differences of up to more than 50‐fold between the maximum and minimum N₂O flux from five chambers within one plot on a single sampling occasion, and that reliability of flux measurements increased with greater numbers of chambers. In more than 90% of the 1970 cases where linearity of headspace N₂O accumulation was measured (with four or more sampling points), linear accumulation was observed; however, where non‐linear accumulation was seen this could result in a 26% under‐estimate of the flux. Statistical analysis demonstrated that the use of ambient air as a surrogate for T₀ headspace samples did not result in any consistent bias in calculated fluxes. Spatial variability has the potential to result in erroneous flux estimates if not taken into account, and generally introduces a far larger uncertainty into the calculated flux (commonly orders of magnitude more) than any uncertainties introduced through reduced headspace sampling or assumption of linearity of headspace accumulation. Hence, when deploying finite resources, maximizing chamber numbers should be given priority over maximizing the number of headspace samplings per enclosure period.     

A simple process-based model for estimating ammonia emissions from agricultural land after fertilizer applications

Abstract. Fertilizer applications to agricultural land are a significant source of ammonia (NH₃) emission to the atmosphere, accounting for approximately 10% of the total emissions from agriculture. Current estimates of emissions from fertilizer applications use 'fixed' emission factors. This paper describes a model in which the emission factors are expressed as a function of the important influencing variables: fertilizer type, soil pH, land use, application rate, rainfall and temperature. Total emission in 2002 for the UK were estimated by running the model for a 'standard UK' scenario, viz. 28.7 kt NH₃-N, which compares well with the UK inventory estimate of 30.4 kt NH₃-N. Differences exist in the estimates for specific fertilizer types, with the mean emission factor for urea applications to grassland, in particular, being lower by use of this model (13% compared with 23% of applied N for the UK inventory). Emission estimates were most sensitive to temperature and fertilizer type. Scenario testing showed that significant reductions in emission could be achieved by replacing urea with other forms of N fertilizer, by combining urea use with a urease inhibitor, or by modifying some management practices.