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Author (up) Janssen, S.; Hansen, J.G.; Jorgensen, J.; Jørgensen, M.S. url  openurl
  Title Operational database for storing and extracting data Type Report
  Year 2015 Publication FACCE MACSUR Reports Abbreviated Journal  
  Volume 6 Issue Pages D-C2.2  
  Keywords  
  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  
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  Call Number MA @ admin @ Serial 2091  
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Author (up) Janssen, S.; Houtkamp, J.; De Groot, H.; Schils, R. url  openurl
  Title Online web tool for data visualization Type Report
  Year 2015 Publication FACCE MACSUR Reports Abbreviated Journal  
  Volume 6 Issue Pages D-C2.6  
  Keywords  
  Abstract This deliverable lays out the work as done as part of MACSUR CropM on data, with the focus on providing a web tool for visualization of model output. It was decided early on that not a specific MACSUR web tool would be developed as part of MACSUR for phase 1, and mostly results would be visualized in other available tools, such as the Global Yield Gap Atlas, which are recognised resources for visualizations. Only in relationship to the MACSUR Geonetwork data catalog hosted at Aarhus University some developments where started. Operationally speaking, most data was still being generated during phase 1, so there was not enough to visualize on specific websites and partners did not commit financial resources to their development, and only in kind was available. No Label  
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  Call Number MA @ admin @ Serial 2093  
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Author (up) Kässi, P.; Känkänen, H.; Niskanen, O.; Lehtonen, H.; Höglind, M. url  doi
openurl 
  Title Farm level approach to manage grass yield variation under climate change in Finland and north-western Russia Type Journal Article
  Year 2015 Publication Biosystems Engineering Abbreviated Journal Biosystems Engineering  
  Volume 140 Issue Pages 11-22  
  Keywords silage grass; risk management; dairy farms; buffer storage; agricultural economics; grassland modelling; dairy-cows; impact; security; timothy; harvest; future; growth; norway; europe; time  
  Abstract Cattle feeding in Northern Europe is based on grass silage, but grass growth is highly dependent on weather conditions. If ensuring sufficient silage availability in every situation is prioritised, the lowest expected yield level determines the cultivated area in farmers’ decision-making. One way to manage the variation in grass yield is to increase grass production and silage storage capacity so that they exceed the annual consumption at the farm. The cost of risk management in the current and the projected future climate was calculated taking into account grassland yield and yield variability for three study areas under current and mid-21st century climate conditions. The dataset on simulated future grass yields used as input for the risk management calculations were taken from a previously published simulation study. Strategies investigated included using up to 60% more silage grass area than needed in a year with average grass yields, and storing silage for up to 6 months more than consumed in a year (buffer storage). According to the results, utilising an excess silage grass area of 20% and a silage buffer storage capacity of 6 months were the most economic ways of managing drought risk in both the baseline climate and the projected climate of 2046-2065. It was found that the silage yield risk due to drought is likely to decrease in all studied locations, but the drought risk and costs implied still remain significant. (C) 2015 IAgrE. Published by Elsevier Ltd. All rights reserved.  
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  ISSN 1537-5110 ISBN Medium Article  
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  Notes TradeM Approved no  
  Call Number MA @ admin @ Serial 4671  
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Author (up) Katajajuuri, J.-M.; Pulkkinen, H.; Hietala, S.; Järvenranta, K.; Virkajärvi, P.; Nousiainen, J.I.; Huuskonen, A. url  doi
openurl 
  Title A holistic, dynamic model to quantify and mitigate the environmental impacts of cattle farming Type Journal Article
  Year 2015 Publication Advances in Animal Biosciences Abbreviated Journal Advances in Animal Biosciences  
  Volume 6 Issue 01 Pages 35-36  
  Keywords GHG mitigation; LCA; livestock; dynamic farm model  
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  ISSN 2040-4700 ISBN Medium Article  
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  Notes LiveM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4680  
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Author (up) Kersebaum, K.; C url  openurl
  Title Model intercomparison for calibrated models Type Report
  Year 2015 Publication FACCE MACSUR Reports Abbreviated Journal  
  Volume 4 Issue Pages D-C1.6  
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  Abstract The study ROTATIONEFFECT aims to compare the output of different models simulating field data sets with multi-year crop rotations including different treatments.Within the first Step (1a2a) data sets (comprising a total of 301 crop growth seasons) for 5 locations in Europe were distributed to 15 interested modeller groups.For this step only minimal information for calibration were provided to the modellers. In total 15 modelling teams sent their “uncalibrated” results as single-year calculations and/or continuous calculations of rotation depending on the capability of the model. Results have been evaluated and the paper submitted (European Journal of Agronomy).Now, within the 2nd step (1b2b) modellers were provided with more information on the crop for the calibration of models. Again, results of calibrated runs were collected.6 models were capable to run the rotations as continuous runs and another set of 6 models provided single year simulations.A first overview of the improvement of predictions due to calibration has been produced. Result files have been uploaded to the web platform for CropM results at Aarhus University (Work package C2 – data management). No Label  
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  Area Expedition Conference  
  Notes Approved no  
  Call Number MA @ admin @ Serial 2213  
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