Linking an economic model for European agriculture with a mechanistic model to estimate nitrogen and carbon losses from arable soils in Europe

Leip, Adrian; Marchi, Giulio; Koeble, Renate; Kempen, Markus; Britz, Wolfgang; Li, C.

doi:10.5194/bg-5-73-2008

Cited by 171 publications

(119 citation statements)

References 37 publications

(35 reference statements)

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“…Gridded fertilizer application rates on grassland are not available worldwide. The only exception that we are aware of is for European grasslands (Leip et al, 2008(Leip et al, , 2011(Leip et al, , 2014; data available for EU-27 as used in Chang et al, 2015a). For countries/regions other than EU-27, the following data were used.…”

Section: Model Inputmentioning

confidence: 99%

Combining livestock production information in a process-based vegetation model to reconstruct the history of grassland management

et al. 2016

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Abstract. Grassland management type (grazed or mown) and intensity (intensive or extensive) play a crucial role in the greenhouse gas balance and surface energy budget of this biome, both at field scale and at large spatial scale. However, global gridded historical information on grassland management intensity is not available. Combining modelled grass-biomass productivity with statistics of the grassbiomass demand by livestock, we reconstruct gridded maps of grassland management intensity from 1901 to 2012. These maps include the minimum area of managed vs. maximum area of unmanaged grasslands and the fraction of mown vs. grazed area at a resolution of 0.5 • by 0.5 • . The grassbiomass demand is derived from a livestock dataset for 2000, extended to cover the period 1901-2012. The grassbiomass supply (i.e. forage grass from mown grassland and biomass grazed) is simulated by the process-based model ORCHIDEE-GM driven by historical climate change, rising CO 2 concentration, and changes in nitrogen fertilization. The global area of managed grassland obtained in this study increases from 6

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Section: Model Inputmentioning

confidence: 99%

Combining livestock production information in a process-based vegetation model to reconstruct the history of grassland management

et al. 2016

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“…These NCUs are composed of multipart polygons, each of the polygons being a cluster of 1 km × 1 km pixels. (Leip et al, 2008(Leip et al, , 2011. However, as a main difference, a criterion on homogeneous altitude was added for the NCU.…”

Section: R Cameron Et Al: Environmental Change Impacts On the C-mentioning

confidence: 99%

Environmental change impacts on the C- and N-cycle of European forests: a model comparison study

et al. 2013

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Forests are important components of the greenhouse gas balance of Europe. There is considerable uncertainty about how predicted changes to climate and nitrogen deposition will perturb the carbon and nitrogen cycles of European forests and thereby alter forest growth, carbon sequestration and N₂O emission. The present study aimed to quantify the carbon and nitrogen balance, including the exchange of greenhouse gases, of European forests over the period 2010–2030, with a particular emphasis on the spatial variability of change. The analysis was carried out for two tree species: European beech and Scots pine. For this purpose, four different dynamic models were used: BASFOR, DailyDayCent, INTEGRATOR and Landscape-DNDC. These models span a range from semi-empirical to complex mechanistic. Comparison of these models allowed assessment of the extent to which model predictions depended on differences in model inputs and structure. We found a European average carbon sink of 0.160 ± 0.020 kgC m⁻² yr⁻¹ (pine) and 0.138 ± 0.062 kgC m⁻² yr⁻¹ (beech) and N₂O source of 0.285 ± 0.125 kgN ha⁻¹ yr⁻¹ (pine) and 0.575 ± 0.105 kgN ha⁻¹ yr⁻¹ (beech). The European average greenhouse gas potential of the carbon sink was 18 (pine) and 8 (beech) times that of the N₂O source. Carbon sequestration was larger in the trees than in the soil. Carbon sequestration and forest growth were largest in central Europe and lowest in northern Sweden and Finland, N. Poland and S. Spain. No single driver was found to dominate change across Europe. Forests were found to be most sensitive to change in environmental drivers where the drivers were limiting growth, where changes were particularly large or where changes acted in concert. The models disagreed as to which environmental changes were most significant for the geographical variation in forest growth and as to which tree species showed the largest rate of carbon sequestration. Pine and beech forests were found to have differing sensitivities to environmental change, in particular the response to changes in nitrogen and precipitation, with beech forest more vulnerable to drought. There was considerable uncertainty about the geographical location of N₂O emissions. Two of the models BASFOR and LandscapeDNDC had largest emissions in central Europe where nitrogen deposition and soil nitrogen were largest, whereas the two other models identified different regions with large N₂O emission. N₂O emissions were found to be larger from beech than pine forests and were found to be particularly sensitive to forest growth

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“…1) calculates the total manure production for each FSSNUTS region, i.e. Farm Structure Survey (FSS) regions which are either at NUTS (Nomenclature of Territorial Units for Statistics) 2 or 3 level (Leip et al, 2008). The manure production is calculated from the animal numbers, available at FSSNUTS level, and the N excretion per animal category, available at country level.…”

Section: Modelling N Fluxes In Agriculture At the European Scalementioning

confidence: 99%

Uncertainties in model predictions of nitrogen fluxes from agro-ecosystems in Europe

et al. 2012

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Abstract.To assess the responses of nitrogen and greenhouse gas emissions to pan-European changes in land cover, land management and climate, an integrated dynamic model, INTEGRATOR, has been developed. This model includes both simple process-based descriptions and empirical relationships and uses detailed GIS-based environmental and farming data in combination with various downscaling methods. This paper analyses the propagation of uncertainties in model inputs and parameters to outputs of INTEGRA-TOR, using a Monte Carlo analysis. Uncertain model inputs and parameters were represented by probability distributions, while spatial correlation in these uncertainties was taken into account by assigning correlation coefficients at various spatial scales. The uncertainty propagation was analysed for the emissions of NH 3 , N 2 O and NO x , N leaching to groundwater and N runoff to surface water for the entire EU27 and for individual countries. Results show large uncertainties for N leaching and runoff (relative errors of ∼ 19 % for Europe as a whole), and smaller uncertainties for emission of N 2 O, NH 3 and NO x (relative errors of ∼ 12 %). Uncertainties for Europe as a whole were much smaller compared to uncertainties at country level, because errors partly cancelled out due to spatial aggregation.

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Linking an economic model for European agriculture with a mechanistic model to estimate nitrogen and carbon losses from arable soils in Europe

Cited by 171 publications

References 37 publications

Combining livestock production information in a process-based vegetation model to reconstruct the history of grassland management

Combining livestock production information in a process-based vegetation model to reconstruct the history of grassland management

Environmental change impacts on the C- and N-cycle of European forests: a model comparison study

Uncertainties in model predictions of nitrogen fluxes from agro-ecosystems in Europe

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