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Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi-species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi-model ensembles to predict productivity and nitrous oxide (N 2 O) emissions for wheat, maize, rice and temperate grasslands. Using a multi-stage modelling protocol, from blind simulations (stage 1) to partial (stages 2-4) and full calibration (stage 5), 24 process-based biogeochemical models were assessed individually or as an ensemble against long-term experimental data from four temperate grassland and five arable crop rotation sites spanning four continents. Comparisons were performed by reference to the experimental uncertainties of observed yields and N 2 O emissions. Results showed that across sites and crop/grassland types, 23%-40% of the uncalibrated individual models were within two standard deviations (SD) of observed yields, while 42 (rice) to 96% (grasslands) of the models were within 1 SD of observed N 2 O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N 2 O emissions within experimental uncertainties for 44% and 33% of the crop and grassland growth cycles, respectively. Partial model calibration (stages 2-4) markedly reduced prediction errors of the full model ensemble E-median for crop grain yields (from 36% at stage 1 down to 4% on average) and grassland productivity (from 44% to 27%) and to a lesser and more variable extent for N 2 O emissions. Yield-scaled N 2 O emissions (N 2 O emissions divided by crop yields) were ranked accurately by three-model ensembles across crop species and field sites. The potential of using process-based model ensembles to predict jointly productivity and N 2 O emissions at field scale is discussed., (© 2017 John Wiley & Sons Ltd.)

Breeding high-yielding rice cultivars through increasing biomass is a key strategy to meet rising global food demands. Yet, increasing rice growth can stimulate methane (CH 4 ) emissions, exacerbating global climate change, as rice cultivation is a major source of this powerful greenhouse gas. Here, we show in a series of experiments that high-yielding rice cultivars actually reduce CH 4 emissions from typical paddy soils. Averaged across 33 rice cultivars, a biomass increase of 10% resulted in a 10.3% decrease in CH 4 emissions in a soil with a high carbon (C) content. Compared to a low-yielding cultivar, a high-yielding cultivar significantly increased root porosity and the abundance of methane-consuming microorganisms, suggesting that the larger and more porous root systems of high-yielding cultivars facilitated CH 4 oxidation by promoting O 2 transport to soils. Our results were further supported by a meta-analysis, showing that high-yielding rice cultivars strongly decrease CH 4 emissions from paddy soils with high organic C contents. Based on our results, increasing rice biomass by 10% could reduce annual CH 4 emissions from Chinese rice agriculture by 7.1%. Our findings suggest that modern rice breeding strategies for high-yielding cultivars can substantially mitigate paddy CH 4 emission in China and other rice growing regions., (© 2017 John Wiley & Sons Ltd.)

Although organic carbon sequestration in agricultural soils has been recommended as a 'win-win strategy' for mitigating climate change and ensuring food security, great uncertainty still remains in identifying the relationships between soil organic carbon (SOC) sequestration and crop productivity. Using data from 17 long-term experiments in China we determined the effects of fertilization strategies on SOC stocks at 0-20cm depth in the North, North East, North West and South. The impacts of changes in topsoil SOC stocks on the yield and yield stability of winter wheat (Triticum aestivum L.) and maize (Zea mays L.) were determined. Results showed that application of inorganic fertilizers (NPK) plus animal manure over 20-30years significantly increased SOC stocks to 20-cm depth by 32-87% whilst NPK plus wheat/maize straw application increased it by 26-38% compared to controls. The efficiency of SOC sequestration differed between regions with 7.4-13.1% of annual C input into the topsoil being retained as SOC over the study periods. In the northern regions, application of manure had little additional effect on yield compared to NPK over a wide range of topsoil SOC stocks (18->50MgCha(-1)). In the South, average yield from manure applied treatments was 2.5 times greater than that from NPK treatments. Moreover, the yield with NPK plus manure increased until SOC stocks (20-cm depth) increased to ~35MgCha(-1). In the northern regions, yield stability was not increased by application of NPK plus manure compared to NPK, whereas in the South there was a significant improvement. We conclude that manure application and straw incorporation could potentially lead to SOC sequestration in topsoil in China, but beneficial effects of this increase in SOC stocks to 20-cm depth on crop yield and yield stability may only be achieved in the South., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Current research on macronutrient cycling in UK agricultural systems aims to optimise soil and nutrient management for improved agricultural production and minimise effects on the environment and provision of ecosystem services. Nutrient use inefficiencies can cause environmental pollution through the release of greenhouse gases into the atmosphere and of soluble and particulate forms of N, P and carbon (C) in leachate and run-off into watercourses. Improving nutrient use efficiencies in agriculture calls for the development of sustainable nutrient management strategies: more efficient use of mineral fertilisers, increased recovery and recycling of waste nutrients, and, better exploitation of the substantial inorganic and organic reserves of nutrients in the soil. Long-term field experimentation in the UK has provided key knowledge of the main nutrient transformations in agricultural soils. Emerging analytical technologies, especially stable isotope labelling, that better characterise macronutrient forms and bioavailability and improve the quantification of the complex relationships between the macronutrients in soils at the molecular scale, are augmenting this knowledge by revealing the underlying processes. The challenge for the future is to determine the relationships between the dynamics of N, P and C across scales, which will require both new modelling approaches and integrated approaches to macronutrient cycling., (Copyright © 2012 Elsevier B.V. All rights reserved.)

This paper describes an agricultural model (Roth-CNP) that estimates carbon (C), nitrogen (N) and phosphorus (P) pools, pool changes, their balance and the nutrient fluxes exported from arable and grassland systems in the UK during 1800–2010. The Roth-CNP model was developed as part of an Integrated Model (IM) to simulate C, N and P cycling for the whole of UK, by loosely coupling terrestrial, hydrological and hydro-chemical models. The model was calibrated and tested using long term experiment (LTE) data from Broadbalk (1843) and Park Grass (1856) at Rothamsted. We estimated C, N and P balance and their fluxes exported from arable and grassland systems on a 5 km × 5 km grid across the whole of UK by using the area of arable of crops and livestock numbers in each grid and their management. The model estimated crop and grass yields, soil organic carbon (SOC) stocks and nutrient fluxes in the form of NH 4 -N, NO 3 -N and PO 4 -P. The simulated crop yields were compared to that reported by national agricultural statistics for the historical to the current period. Overall, arable land in the UK have lost SOC by −0.18, −0.25 and −0.08 Mg C ha −1 y −1 whereas land under improved grassland SOC stock has increased by 0.20, 0.47 and 0.24 Mg C ha −1 y −1 during 1800–1950, 1950–1970 and 1970–2010 simulated in this study. Simulated N loss (by leaching, runoff, soil erosion and denitrification) increased both under arable (−15, −18 and −53 kg N ha −1 y −1 ) and grass (−18, −22 and −36 kg N ha −1 y −1 ) during different time periods. Simulated P surplus increased from 2.6, 10.8 and 18.1 kg P ha −1 y −1 under arable and 2.8, 11.3 and 3.6 kg P ha −1 y −1 under grass lands 1800–1950, 1950–1970 and 1970–2010. [ABSTRACT FROM AUTHOR]