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Author Kipling, R.; Özkan, Ş. url  openurl
  Title Stakeholder engagement and the perceptions of researchers: How agricultural modellers view challenges to communication Type Report
  Year 2016 Publication FACCE MACSUR Reports Abbreviated Journal  
  Volume 8 Issue Pages SP8-20  
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  Abstract Conference presentation PDF  
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  Area Expedition Conference LiveM2016: International livestock modelling conference – Modelling grassland-livestock systems under climate change  
  Notes (up) Approved no  
  Call Number MA @ admin @ Serial 4835  
Permanent link to this record
 

 
Author Kipling, R. url  openurl
  Title LiveM2016: International livestock modelling conference – Modelling grassland-livestock systems under climate change Type Report
  Year 2016 Publication FACCE MACSUR Reports Abbreviated Journal  
  Volume 8 Issue Pages L0.1-D1  
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  Notes (up) Approved no  
  Call Number MA @ admin @ Serial 4841  
Permanent link to this record
 

 
Author Foskolis, A.; Moorby, J. url  openurl
  Title Lifetime nitrogen efficiency of dairy cattle: Model description and sensitivity analysis Type Conference Article
  Year 2016 Publication FACCE MACSUR Reports Abbreviated Journal  
  Volume 8 Issue Pages SP8-9  
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  Abstract Conference poster PDF  
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  Language Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference LiveM2016: International livestock modelling conference – Modelling grassland-livestock systems under climate change  
  Notes (up) Approved no  
  Call Number MA @ admin @ Serial 4842  
Permanent link to this record
 

 
Author Wallach, D.; Thorburn, P.; Asseng, S.; Challinor, A.J.; Ewert, F.; Jones, J.W.; Rötter, R.; Ruane, A. url  openurl
  Title Overview paper on comprehensive framework for assessment of error and uncertainty in crop model predictions Type Report
  Year 2016 Publication FACCE MACSUR Reports Abbreviated Journal  
  Volume 8 Issue Pages C4.1-D  
  Keywords MACSUR_ACK; CropM  
  Abstract Crop models are important tools for impact assessment of climate change, as well as for  exploring management options under current climate. It is essential to evaluate the  uncertainty associated with predictions of these models. Several ways of quantifying  prediction uncertainty have been explored in the literature, but there have been no  studies of how the different approaches are related to one another, and how they are  related to some overall measure of prediction uncertainty. Here we show that all the  different approaches can be related to two different viewpoints about the model; either  the model is treated as a fixed predictor with some average error, or the model can be  treated as a random variable with uncertainty in one or more of model structure, model  inputs and model parameters. We discuss the differences, and show how mean squared  error of prediction can be estimated in both cases. The results can be used to put  uncertainty estimates into a more general framework and to relate different uncertainty  estimates to one another and to overall prediction uncertainty. This should lead to a  better understanding of crop model prediction uncertainty and the underlying causes of  that uncertainty. This study was published as (Wallach et al. 2016)  
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  Notes (up) Approved no  
  Call Number MA @ office @ Serial 2954  
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Author Calanca, P. url  openurl
  Title Modelling the impacts of seasonal drought on herbage growth under climate change Type Report
  Year 2016 Publication FACCE MACSUR Reports Abbreviated Journal  
  Volume 8 Issue Pages SP8-3  
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  Abstract Conference presentation PDF  
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  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference LiveM2016: International livestock modelling conference – Modelling grassland-livestock systems under climate change  
  Notes (up) Approved no  
  Call Number MA @ admin @ Serial 4837  
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