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Author Sándor, R.; Ma, S.; Acutis, M.; Barcza, Z.; Ben Touhami, H.; Doro, L.; Hidy, D.; Köchy, M.; Lellei-Kovács, E.; Minet, J.; Perego, A.; Rolinski, S.; Ruget, F.; Seddaiu, G.; Wu, L.; Bellocchi, G. url  doi
openurl 
  Title Uncertainty in simulating biomass yield and carbon–water fluxes from grasslands under climate change Type Journal Article
  Year 2015 Publication Advances in Animal Biosciences Abbreviated Journal Advances in Animal Biosciences  
  Volume 6 Issue 01 Pages 49-51  
  Keywords grassland productivity; carbon balance; model simulation; uncertainty; sensitivity  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2040-4700 ISBN Medium Article  
  Area Expedition Conference  
  Notes (up) CropM, LiveM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4651  
Permanent link to this record
 

 
Author Bellocchi, G.; Rivington, M.; Matthews, K.; Acutis, M. url  doi
openurl 
  Title Deliberative processes for comprehensive evaluation of agroecological models. A review Type Journal Article
  Year 2015 Publication Agronomy for Sustainable Development Abbreviated Journal Agron. Sust. Developm.  
  Volume 35 Issue 2 Pages 589-605  
  Keywords component-oriented programing; deliberative approach; modeling; model evaluation; multiple metrics; stakeholders; decision-support-systems; environmental-models; performance evaluation; groundwater models; farming systems; climate-change; irene-dll; simulation; validation; integration  
  Abstract The use of biophysical models in agroecology has increased in the last few decades for two main reasons: the need to formalize empirical knowledge and the need to disseminate model-based decision support for decision makers (such as farmers, advisors, and policy makers). The first has encouraged the development and use of mathematical models to enhance the efficiency of field research through extrapolation beyond the limits of site, season, and management. The second reflects the increasing need (by scientists, managers, and the public) for simulation experimentation to explore options and consequences, for example, future resource use efficiency (i.e., management in sustainable intensification), impacts of and adaptation to climate change, understanding market and policy responses to shocks initiated at a biophysical level under increasing demand, and limited supply capacity. Production concerns thus dominate most model applications, but there is a notable growing emphasis on environmental, economic, and policy dimensions. Identifying effective methods of assessing model quality and performance has become a challenging but vital imperative, considering the variety of factors influencing model outputs. Understanding the requirements of stakeholders, in respect of model use, logically implies the need for their inclusion in model evaluation methods. We reviewed the use of metrics of model evaluation, with a particular emphasis on the involvement of stakeholders to expand horizons beyond conventional structured, numeric analyses. Two major topics are discussed: (1) the importance of deliberative processes for model evaluation, and (2) the role computer-aided techniques may play to integrate deliberative processes into the evaluation of agroecological models. We point out that (i) the evaluation of agroecological models can be improved through stakeholder follow-up, which is a key for the acceptability of model realizations in practice, (ii) model credibility depends not only on the outcomes of well-structured, numerically based evaluation, but also on less tangible factors that may need to be addressed using complementary deliberative processes, (iii) comprehensive evaluation of simulation models can be achieved by integrating the expectations of stakeholders via a weighting system of preferences and perception, (iv) questionnaire-based surveys can help understand the challenges posed by the deliberative process, and (v) a benefit can be obtained if model evaluation is conceived in a decisional perspective and evaluation techniques are developed at the same pace with which the models themselves are created and improved. Scientific knowledge hubs are also recognized as critical pillars to advance good modeling practice in relation to model evaluation (including access to dedicated software tools), an activity which is frequently neglected in the context of time-limited framework programs.  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1774-0746 1773-0155 ISBN Medium Review  
  Area Expedition Conference  
  Notes (up) CropM, LiveM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4551  
Permanent link to this record
 

 
Author Rolinski, S.; Weindl, I.; Heinke, J.; Bodirsky, B.L.; Biewald, A.; Lotze-Campen, H. url  doi
openurl 
  Title Pasture harvest, carbon sequestration and feeding potentials under different grazing intensities Type Journal Article
  Year 2015 Publication Advances in Animal Biosciences Abbreviated Journal Advances in Animal Biosciences  
  Volume 6 Issue 01 Pages 43-45  
  Keywords global dynamic vegetation model; LPJmL; grasslands; livestock production  
  Abstract  
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  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium Article  
  Area Expedition Conference  
  Notes (up) CropM, LiveM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4541  
Permanent link to this record
 

 
Author Shrestha, S.; Abdalla, M.; Hennessy, T.; Forristal, D.; Jones, M.B. url  doi
openurl 
  Title Irish farms under climate change – is there a regional variation on farm responses? Type Journal Article
  Year 2015 Publication Journal of Agricultural Science Abbreviated Journal J. Agric. Sci.  
  Volume 153 Issue 03 Pages 385-398  
  Keywords change impacts; elevated co2; potential impacts; maize production; united-states; winter-wheat; plant-growth; adaptation; ireland; yield  
  Abstract The current paper aims to determine regional impacts of climate change on Irish farms examining the variation in farm responses. A set of crop growth models were used to determine crop and grass yields under a baseline scenario and a future climate scenario. These crop and grass yields were used along with farm-level data taken from the Irish National Farm Survey in an optimizing farm-level (farm-level linear programming) model, which maximizes farm profits under limiting resources. A change in farm net margins under the climate change scenario compared to the baseline scenario was taken as a measure to determine the effect of climate change on farms. The growth models suggested a decrease in cereal crop yields (up to 9%) but substantial increase in yields of forage maize (up to 97%) and grass (up to 56%) in all regions. Farms in the border, midlands and south-east regions suffered, whereas farms in all other regions generally fared better under the climate change scenario used in the current study. The results suggest that there is a regional variability between farms in their responses to the climate change scenario. Although substituting concentrate feed with grass feeds is the main adaptation on all livestock farms, the extent of such substitution differs between farms in different regions. For example, large dairy farms in the south-east region adopted total substitution of concentrate feed while similar dairy farms in the south-west region opted to replace only 0.30 of concentrate feed. Farms in most of the regions benefitted from increasing stocking rate, except for sheep farms in the border and dairy farms in the south-east regions. The tillage farms in the mid-east region responded to the climate change scenario by shifting arable production to beef production on farms.  
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  Language English Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN 0021-8596 1469-5146 ISBN Medium Article  
  Area Expedition Conference  
  Notes (up) CropM, TradeM Approved no  
  Call Number MA @ admin @ Serial 4542  
Permanent link to this record
 

 
Author Wallach, D. url  doi
openurl 
  Title Developing skills: how to train adaptive modelers Type Journal Article
  Year 2015 Publication Advances in Animal Biosciences Abbreviated Journal Advances in Animal Biosciences  
  Volume 6 Issue 01 Pages 52-53  
  Keywords capacity building; skills development; training; integrated modeling  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2040-4700 ISBN Medium Article  
  Area Expedition Conference  
  Notes (up) Hub, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4683  
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