Abstract: This paper addresses protein crop production in Europe. European food and feed industries highly depend on imported protein crops and derived products and climate change is likely to affect domestic protein crop production and thus the import dependency. The recent reform of EU agricultural policy reform aims at promoting climate friendly agricultural practices and stimulating the production of protein crops. We choose three contrasting climate change scenarios as well as specifications of the recent CAP reform in order to investigate how farmers might adapt to changing land use restrictions and climate conditions. Output response, land allocation and nitrogen use are the main variables of interest. Exemplified for Austrian cropland, we apply an integrated modeling framework consisting of a statistical climate change model, a crop rotation model, the bio-physical process model EPIC, and the economic bottom-up land use optimization model BiomAT. This model maximizes total gross margins by optimizing for land use and crop management practices for different scenarios of climate change and market conditions. Results obtained at a 1 km grid are aggregated to the national level. The model results indicate that changes in policy conditions, cropland use, and flexibility in crop management practices may have stronger effects on total protein crop production than climate change in the next decades. An expansion of current protein crop production leads to an increase in marginal opportunity costs, reduces mineral fertilizer input demand, and mainly replaces maize in the crop rotations. No Label

Abstract: This deliverable lays out the work as done as part of MACSUR CropM on data, with the  focus on improving data management and have shared data curation for future use. The  issue was tackled with help from the MACSUR central hub coordination in the form of Jason  Jargenson from University of Reading. The data management as proposed and  implemented in this deliverable is very much a bottom up process, in which partners in a  meeting in Spring 2013 in Aarhus investigated the best way forward for data management  across activities in CropM.As a follow up to this, the work was mainly divided in three  parts:  1. The  Open  Data  Journal  for  Agricultural  Research,  mainly  focused  on  long  term  data  archival  and  citation  of  data  sets,  as  input  and  outputs  to  the  modelling  work,  as  part  of  MACSUR,  lead  by  Wageningen  UR  2. The  Geonetwork  data  catalog  hosted  at  Aarhus  Universitet,  that  allows  for  operational  access  and  storage  of  data  sets  as  part  of  the  ongoing  work,  also  for  restricted  access  of  the  consortium,  and  as  a  first  step  to  visualization,  lead  by  Aarhus  Universitet.  3. The  work  on  rating  data  sets,  that  provides  a  tool  for  improving  data  set  access  in  an  early  phase  for  connecting  them  to  models,  lead  by  Reading  University.  At the end of the deliverable some next steps are giving for data activities in the context  of AgMIP and beyond. No Label

Abstract: This deliverable focuses on some illustrative results obtained with different grassland- specific, grassland adapted crop and dynamic vegetation models selected out of the first list of models compiled in 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). Results from uncalibrated simulations were documented in the D-L2.3 report as a blind exercise. Some model improvements are emphasized in this report due to the higher information level of the model calibrations. The complete set of results will include simulations from uncalibrated and calibrated models. No Label