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| Author |
Kersebaum, K.; C, |
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Results of uncalibrated model runs available (ROTATIONEFFECTS) |
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2014 |
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FACCE MACSUR Reports |
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3 |
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D-C1.5 |
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The study ROTATIONEFFECT aims to compare the output of different models simulating field data sets with multi-year crop rotations including different treatments. Data sets for 5 locations in Europe were distributed to 19 interested modeller groups comprising a total of 201 crop growth seasons. In a first step only minimal information for calibration were provided to the modellers. In total 14 modelling teams sent their “uncalibrated” results as single-year calculations and/or calculations of rotation depending on the capability of the model. 7-10 models were capable to run the rotations as continuous runs. Up to 12 models provided single year simulations of at least one crop. Comparing results of models which provided both single year and continuous runs, show a little lower root mean square error for the continuous rotations runs. Cereal crop yields were generally better simulated than tuber/beet yields. Additionally, the models’ response to various treatments (irrigation/rainfed, nitrogen level, CO2 level, residue management/ tillage, catch crops) were compared to observed differences. First indicators of model performance have been developed and presented at international conferences. No Label |
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MA @ admin @ |
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2230 |
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Bellocchi, G.; Ma, S. |
| Title |
Results of uncalibrated grassland model runs |
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Report |
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2014 |
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FACCE MACSUR Reports |
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3 |
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D-L2.3 |
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This deliverable focuses on the some illustrative results obtained with the grassland models selected (D-L2.1.1) to simulate biomass and flux data from grassland sites in Europe and peri-Mediterranean regions (D-L2.1.1 and D-L2.1.2). This is a blind exercise, carried out without model calibration. The complete set of results will include simulations from calibrated models. The results shown are illustrative of the methodology adopted for grassland model intercomparison in MACSUR. The insights gained from this ongoing study are relevant for some crop and vegetation models, which in some cases proved comparable to grassland-specific models to simulate biomass data from managed grasslands. The results reported here cannot be considered conclusive. Additional results will be published as they become available together with calibration results, as well as the comprehensive evaluation of models with fuzzy logic-based indicators. No Label |
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2234 |
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Haas, E. |
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Responses of soil N2O emissions and nitrate leaching on climate input data aggregation: a biogeochemistry model ensemble study |
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2015 |
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FACCE MACSUR Reports |
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5 |
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Sp5-20 |
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Numerical simulation models are increasingly used to estimate greenhouse gas (GHG) emissions at site to regional scales and are outlined as the most advanced methodology (Tier 3) for national emission inventory in the framework of UNFCCC reporting.Low resolution simulations needs less effort in computation and data management, but details could be lost during data aggregation associated with high uncertainties of the simulation results. This aggregation effect and its uncertainty will be propagated with the simulations. This paper aims to study the aggregation effects of climate and soil input data on soil N2O emissions and nitrate leaching by comparing different biogeochemistry models. We simulated two 30-year cropping systems (winter wheat and maize monocultures) under nutrient-limited conditions. Input data (climate and soil) was based on a 1 km resolution aggregated on resolutions of 10, 25, 50, and 100. In the first step, the soil data was kept homogenous using representative soil properties while climate data was used on all different scales. In the second step, the climate data was kept homogeneous while soil initial data was used on all different scales. Finally in the third step we have used spatially explicit climate and soil data on all different scales. We analyzed the N2O emissions per unit of crop yield as well as the nitrate leaching on the annual average as well as on daily resolution to study pulsing events for all scenarios and on all scales. The study presents an analysis of the influence of data aggregation.The study gives an indication on adequate spatial aggregation schemes in dependence on the scope of regionalization studies addressing the quantification of losses of reactive nitrogen from managed arable systems. No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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MA @ admin @ |
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2135 |
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Biewald, A. |
| Title |
Representative Agricultural Pathways for Europe |
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2016 |
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FACCE MACSUR Reports |
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9 C6 - |
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Sp9-1 |
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Agricultural aspects have been covered in the scenario process on shared socio-economic pathways (SSPs), but only to a limited extent. In order to analyze the future dynamics of agricultural development they need to be complemented and specified by Representative Agricultural Pathways (RAPs), which cover different aspects of agricultural development as for example European agricultural and domestic policy, environmental policies, different livestock management systems, cropping systems or irrigation efficiencies.In this paper we will develop a general framework for RAPs where we define for each SSP the corresponding specific agricultural development. Some aspects of the above mentioned specifics can be derived from the definitions in the SSPs, as for example irrigation efficiencies which are linked to technological development. Agricultural policies on the other hand are not included in the SSP definitions. Here we will define agricultural and environmental policies, including the available funding in each area of the common agricultural policy (CAP) (pillars 1 and 2). As RAPs can only to a small degree be developed as European guidelines and implemented unilaterally, it is important to translate the overall storylines into specific scenario parameterization at national levels. Concerned by this are 1. national policies, as well as the agri-environmental schemes of the CAP in Pillar II, 2. livestock efficiencies and the development of extensive and intensive farm management, and 3. crop management systems.Additionally we will define which respresentative concentration pathways (RCPs) will match best the future agricultural and agro-economic trajectories. The following 5 preliminary RAPs for Europe will be further developed in our analysis:EU-RAP1 (Sustainable Europe) : strong CAP, strong shift on environmental regulation, no producer support, green CAP with strong mititgation componentEU-RAP2 (Middle of the road): BAU or things will stay as they are.EU-RAP3 (Fragmented Europe): Europe breaks up, rich countries support farmers with national subsidies, poor countries do not. There is no CAP anymoreEU-RAP4 (Two Europes): Europe is divided in a poor and a rich part. In the rich part a green and environmental friendly CAP will be implemented, in the poor part of Europe, the CAP will cease to existEU-RAP5(Fossil fueled Europe): free market world, strong institutions, weak on enviromental regulations, low domestic polices? Local green CAP without mitigation |
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MA @ admin @ |
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4836 |
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Lacetera, N.; Vitali, A.; Bernabucci, U.; Nardone, A. |
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Report on the analysis of interannual and seasonal variations in productive, reproductive and health data |
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2015 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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4 |
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D-L1.2.2 |
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The work carried out under LiveM, L1.2 and described herein was based on construction and query of large databases which included multiannual productive and health field data. Productive data referred to dairy cows, whereas health data were relative both to dairy cows and pigs. The analysis pointed out significant seasonal variations of parameters under study. In synthesis, summer/hot season was associated with significant worsening of dairy cows milk composition and with significant higher risk of death in pigs. These results may help to predict consequences of climate change in economically important sectors of the livestock industry and also to identify and target adaptation options that are appropriate for specific contexts, and that can contribute to environmental sustainability as well as to economic development. No Label |
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MA @ admin @ |
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2216 |
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