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Agricultural activities are important sources of atmospheric nitrous oxide (N2O), methane (CH4), and carbon dioxide (CO2). In the European Union, the agricultural sector contributes approximately 10% of the total emitted greenhouse gases (GhG). We search for evaluating GhG emissions at the farm level and desiging mitigation options from a biotechnical point of view. As GhG emissions occur at several stages within the farm operation, it is essential to combine nutrient cycling and farm working through an integrated farm approach to reach a full accounting of processes. Our proposal comprises the following characteristics: - Our whole farm approach (FarmSim) combines empirical and mechanistic modelling through describing of above and below ground C and N fluxes ; with respect to GhG, emissions can be also calculated with emissions factors, comparable to the IPCC methodology when no model is available yet as for manure management for instance. - Rebuilding farmers' practices description from available data (on farm and through farms'network databases) needs to choose a level of information to translate real situations to generic ones. It requires thus to choose a set of farm components and compatible spatio-temporal scales in respect with the data needed by the models. - At the moment, we coupled two models allowing to quantify the emissions of the different land uses (in our case PaSim, a grassland ecosystem model and CERES-EGC, a crop model). - The system boundaries are limited to the farm gate, or may include pre- and post-chain effects according to more and less high inputs and the difficulty to forecast produce fate if databases are available. - Building plausible scenarios requires to control a set of farm operation coherences to account for standing mitigation options. In a first step, we used a case study formalized by the French Livestock Institute (IE) and some farm working data from an experimental dairy farm belonging to the French Institute for Agricultural Research (INRA), both located in semi-continental conditions (Mirecourt - North-Eastern France). The simulated farming system is a mixed dairy and crops system so as to account for a rather generic farming system.

Spatial interactions within a landscape may lead to large inputs of reactive nitrogen (Nr) transferred from cultivated areas and farms to oligotrophic ecosystems and induce environmental threats such as acidification, nitric pollution or eutrophication of protected areas. The paper presents a new methodology to estimate Nr fluxes at the landscape scale by taking into account spatial interactions between landscape elements. This methodology includes estimates of indirect Nr emissions due to short-range atmospheric and hydrological transfers. We used the NitroScape model which integrates processes of Nr transformation and short-range transfer in a dynamic and spatially distributed way to simulate Nr fluxes and budgets at the landscape scale. Four configurations of NitroScape were implemented by taking into account or not the atmospheric, hydrological or both pathways of Nr transfer. We simulated Nr fluxes, especially direct and indirect Nr emissions, within a test landscape including pig farms, croplands and unmanaged ecosystems. Simulation results showed the ability of NitroScape to simulate patterns of Nr emissions and recapture for each landscape element and the whole landscape. NitroScape made it possible to quantify the contribution of both atmospheric and hydrological transfers to Nr fluxes, budgets and indirect Nr emissions. For instance, indirect N2O emissions were estimated at around 21% of the total N2O emissions. They varied within the landscape according to land use, meteorological and soil conditions as well as topography. This first attempt proved that the NitroScape model is a useful tool to estimate the effect of spatial interactions on Nr fluxes and budgets as well as indirect Nr emissions within landscapes. Our approach needs to be further tested by applying NitroScape to several spatial arrangements of agro-ecosystems within the landscape and to real and larger landscapes.

Spatial interactions at short-term may lead to large inputs of reactive nitrogen (Nr) to oligotrophic ecosystems and induce environmental threats such as additional N2O emissions and global warming. The paper presents a new methodology to estimate Nr fluxes, especially additional N2O emissions, at the landscape scale by taking into account spatial interactions between landscape elements. We used the NitroScape model which integrates processes of Nr transformation and short-term transfer in a dynamic and spatially distributed way to simulate Nr fluxes and budgets at the landscape scale. Four configurations of NitroScape were implemented by taking into account or not the atmospheric, hydrological or both pathways of Nr transfer. We simulated Nr fluxes, especially direct and indirect N2O emissions, within a test landscape including pig farms, croplands and unmanaged ecosystems. Simulation results showed the ability of NitroScape to simulate patterns of Nr losses and recapture for each landscape element and the whole landscape. They made it possible to quantify the contribution of both atmospheric and hydrological transfers in Nr fluxes and budgets. Indirect N2O emissions were estimated at almost 25 % of the total N2O emissions. They varied within the landscape according to land use, meteorological and soil conditions as well as topography. This first attempt has proved that the NitroScape model is a useful tool to estimate the effect of spatial interactions on Nr fluxes and budgets as well as indirect N2O emissions within landscapes. Our approach needs to be further tested by applying NitroScape to several spatial distributions of ecosystems within the landscape and to real and larger landscapes.

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no sp Assessment of Nitrogen Fluxes to Air and Water from Site Scale to Continental Scale; Modelling complex systems such as farms often requires quantification of a large number of input factors. Sensitivity analyses are useful to reduce the number of input factors that are required to be measured or estimated accurately. Three methods of sensitivity analyses (The Morris method, the rank regression and correlation method and the Extended Fourrier Amplitude Sensitivity Test method) were compared in the case of the CERES-EGC model applied to crops of a dairy farm. The qualitative Morris method provided a screening of the input factors. The two other quantitative methods were used to investigate more thoroughly the effects of input factors. The two other quantitative methods were used to investigate more thoroughly the effectos on input factors on output variables.Despite differences in terms of concepts and assumptions, the three methods provided similar results. Among the 44 factors under study, N2O emissions were mainly sensitive to the fraction of N2O emitted during denitrification, the maximum rate of nitrification, the soil bulk density and the cropland area.

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