Approaches and concepts of modelling denitrification: increased process understanding using observational data can reduce uncertainties

Denitrification is a key but poorly quantified component of the Ncycle. Because it is difficult to measure the gaseous (NO$_{x}$, N$_{2}$O, N$_{2}$)and soluble (NO$_{3}$) components of denitrification with sufficientintensity, models of varying scope and complexity have beendeveloped and applied to estimate how vegetation cover, landmanagement and environmental factors such as soil type andweather interact to control these variables. In this paper we assessthe strengths and limitations of different modeling approaches,highlight major uncertainties, and suggest how differentobservational methods and process-based understanding can becombined to better quantify N cycling. Representation of howbiogeochemical (e.g. org. C., pH) and physical (e.g. soil structure)factors influence denitrification rates and product ratios combinedwith ensemble approaches may increase accuracy withoutrequiring additional site level model inputs

Impact de l'introduction des légumineuses dans les systèmes de culture sur les émissions de protoxyde d'azote

Dans un objectif d'atténuation du réchauffement climatique, la mise en place de systèmes de culture plus autonomes vis - à - vis des engrais minéraux devient incontournable pour réduire les émissions de gaz à effet de serre (GES) tout en diminuant le coût de la fertilisation. L'insertion de légumineuses dans ces systèmes semble être un levier prometteur pour y parvenir. Les économies d'azote permises par différents modes d'introduction de légumineuses et leur impact sur les émissions de GES ont été estimés et évalués en quantifiant au préalable les flux d'azote dans les systèmes avec ou sans légumineuses à partir de données issues de dispositifs expérimentaux préexistants, disponibles dans la bibliographie ou acquises dans de nouveaux essais. L'introduction de légumineuses présente régulièrement un impact positif sur la réduction de l'emploi des engrais azotés. Le risque d'augmentation de la lixiviation du nitrate dépend de leur mode d'introduction et de leur place dans les rotations. Enfin, les émissions mesurées en cul tures principales de légumineuses sont généralement très significativement réduites en comparaison des cultures fertilisées, cependant la dégradation des résidus des légumineuses (en culture ou en couverts) peut générer des émissions de N 2 O corrélées à leur impact sur les flux d'azote, variable selon les conditions pédoclimatiques. Ces résultats devraient permettre d'élaborer des recommandations pour mieux prendre en compte les légumineuses dans la conception de systèmes de culture plus autonomes vis - à - vis des engrais azotés de synthèse et moins émetteurs de N 2 0

Challenges of accounting nitrous oxide emissions from agricultural crop residues

Crop residues are important inputs of carbon (C) and nitrogen (N) to soils and thus directly and indirectly affect nitrous oxide (N$_2$O) emissions. As the current inventory methodology considers N inputs by crop residues as the sole determining factor for N$_2$O emissions, it fails to consider other underlying factors and processes. There is compelling evidence that emissions vary greatly between residues with different biochemical and physical characteristics, with the concentrations of mineralizable N and decomposable C in the residue biomass both enhancing the soil N$_2$O production potential. High concentrations of these components are associated with immature residues (e.g., cover crops, grass, legumes, and vegetables) as opposed to mature residues (e.g., straw). A more accurate estimation of the short-term (months) effects of the crop residues on N$_2$O could involve distinguishing mature and immature crop residues with distinctly different emission factors. The medium-term (years) and long-term (decades) effects relate to the effects of residue management on soil N fertility and soil physical and chemical properties, considering that these are affected by local climatic and soil conditions as well as land use and management. More targeted mitigation efforts for N$_2$O emissions, after addition of crop residues to the soil, are urgently needed and require an improved methodology for emission accounting. This work needs to be underpinned by research to (1) develop and validate N$_2$O emission factors for mature and immature crop residues, (2) assess emissions from belowground residues of terminated crops, (3) improve activity data on management of different residue types, in particular immature residues, and (4) evaluate long-term effects of residue addition on N$_2$O emissions

Challenges of accounting nitrous oxide emissions from agricultural crop residues

Crop residues are important inputs of carbon (C) and nitrogen (N) to soils and thus directly and indirectly affect nitrous oxide (N2O) emissions. As the current inventory methodology considers N inputs by crop residues as the sole determining factor for N2O emissions, it fails to consider other underlying factors and processes. There is compelling evidence that emissions vary greatly between residues with different biochemical and physical characteristics, with the concentrations of mineralizable N and decomposable C in the residue biomass both enhancing the soil N2O production potential. High concentrations of these components are associated with immature residues (e.g., cover crops, grass, legumes, and vegetables) as opposed to mature residues (e.g., straw). A more accurate estimation of the short-term (months) effects of the crop residues on N2O could involve distinguishing mature and immature crop residues with distinctly different emission factors. The medium-term (years) and long-term (decades) effects relate to the effects of residue management on soil N fertility and soil physical and chemical properties, considering that these are affected by local climatic and soil conditions as well as land use and management. More targeted mitigation efforts for N2O emissions, after addition of crop residues to the soil, are urgently needed and require an improved methodology for emission accounting. This work needs to be underpinned by research to (1) develop and validate N2O emission factors for mature and immature crop residues, (2) assess emissions from belowground residues of terminated crops, (3) improve activity data on management of different residue types, in particular immature residues, and (4) evaluate long-term effects of residue addition on N2O emissions

Challenges of accounting nitrous oxide emissions from agricultural crop residues

Crop residues are important inputs of carbon (C) and nitrogen (N) to soils and thus directly and indirectly affect nitrous oxide (N2O) emissions. As the current inventory methodology considers N inputs by crop residues as the sole determining factor for N2O emissions, it fails to consider other underlying factors and processes. There is compelling evidence that emissions vary greatly between residues with different biochemical and physical characteristics, with the concentrations of mineralizable N and decomposable C in the residue biomass both enhancing the soil N2O production potential. High concentrations of these components are associated with immature residues (e.g., cover crops, grass, legumes, and vegetables) as opposed to mature residues (e.g., straw). A more accurate estimation of the short-term (months) effects of the crop residues on N2O could involve distinguishing mature and immature crop residues with distinctly different emission factors. The medium-term (years) and long-term (decades) effects relate to the effects of residue management on soil N fertility and soil physical and chemical properties, considering that these are affected by local climatic and soil conditions as well as land use and management. More targeted mitigation efforts for N2O emissions, after addition of crop residues to the soil, are urgently needed and require an improved methodology for emission accounting. This work needs to be underpinned by research to (1) develop and validate N2O emission factors for mature and immature crop residues, (2) assess emissions from belowground residues of terminated crops, (3) improve activity data on management of different residue types, in particular immature residues, and (4) evaluate long-term effects of residue addition on N2O emissions

Global Research Alliance on agricultural greenhouse gases - benchmark and ensemble crop and grassland model estimates

CT3 Biogéochimie, physique et écologie des solsEnjS4 Bouclage des cycles N et P et stockage de carboneTyp_Proj_Bourse de thèse/Post-DocTyp_Proj_Projet ANRUncertainties in the response of crop and grassland models to management and environmental drivers can be attributed to differences in the structure of different models. This has created an urgent need for international benchmarking of models, where uncertainties are estimated by running several models that simulate the same physical and management conditions (ensemble modelling) to generate expanded envelopes of uncertainty (e.g. Asseng et al., 2013). Simulations of the agricultural C and N fluxes, in particular, are inherently uncertain because they are driven by complex interactions (e.g. Sándor et al., 2016) and characterized by considerable spatial and temporal variability in the measurements. In this context, the Integrative Research Group of the Global Research Alliance (GRA) on Agricultural Greenhouse Gases promotes a coordinated activity across multiple international projects (e.g. C-N MIP and Models4Pastures of the FACCE-JPI, https://www.faccejpi.com) to benchmark and compare simulation models that estimate C-N related outputs (including greenhouse gas emissions) from arable crop and grassland systems (http://globalresearchalliance.org/e/model-intercomparison-on-agricultural-ghg-emissions). This study presents some preliminary results on the uncertainty of outputs from 12 grassland models while exploring model differences when models were calibrated with increasing data resources

The patterns of Syrian uprising: Comparing Hama in 1980–1982 and Homs in 2011

Economic grievances that marginalized rural citizens and eroded the Syrian government’s political base are widely considered to have sparked the 2011 uprising. Although the country’s 1980–1982 protests were also blamed on economic factors, commentators to date have largely resisted comparing the events. This article draws parallels between Hama in the lead-up to 1980–1982 and Homs pre-2011, arguing that while there are differences between the uprisings—including the socioeconomic group involved—the root causes of grievance were remarkably similar. Both uprisings followed a redrawing of Syria’s social contract that marginalized a group that had previously had a stake in the Syrian state. In both cases, a new underclass was formed that became the backbone of the political unrest. Although economic factors cannot explain the 2011 uprising in its entirety, this article argues that some of the seed dynamics in 2011 were remarkably similar to 1980–1982

Assessing uncertainties in crop and pasture ensemble model simulations of productivity and N2O emissions

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 (N2O) 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 N2O 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 N2O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N2O 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 N2O emissions. Yield-scaled N2O emissions (N2O 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 N2O emissions at field scale is discussed.</p