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Author Holman, I.P.; Brown, C.; Carter, T.R.; Harrison, P.A.; Rounsevell, M. doi  openurl
  Title (up) Improving the representation of adaptation in climate change impact models Type Journal Article
  Year 2019 Publication Regional Environmental Change Abbreviated Journal Reg. Environ. Change  
  Volume 19 Issue 3 Pages 711-721  
  Keywords Adaptive capacity; Limits; Water; Land; Decision making; Integrated assessment; Land-Cover Change; Global Change; River-Basin; Integrated Assessment; Adaptive Capacity; Vulnerability; Variability; Precautionary; Agriculture; Management  
  Abstract Climate change adaptation is a complex human process, framed by uncertainties and constraints, which is difficult to capture in existing assessment models. Attempts to improve model representations are hampered by a shortage of systematic descriptions of adaptation processes and their relevance to models. This paper reviews the scientific literature to investigate conceptualisations and models of climate change adaptation, and the ways in which representation of adaptation in models can be improved. The review shows that real-world adaptive responses can be differentiated along a number of dimensions including intent or purpose, timescale, spatial scale, beneficiaries and providers, type of action, and sector. However, models of climate change consequences for land use and water management currently provide poor coverage of these dimensions, instead modelling adaptation in an artificial and subjective manner. While different modelling approaches do capture distinct aspects of the adaptive process, they have done so in relative isolation, without producing improved unified representations. Furthermore, adaptation is often assumed to be objective, effective and consistent through time, with only a minority of models taking account of the human decisions underpinning the choice of adaptation measures (14%), the triggers that motivate actions (38%) or the time-lags and constraints that may limit their uptake and effectiveness (14%). No models included adaptation to take advantage of beneficial opportunities of climate change. Based on these insights, transferable recommendations are made on directions for future model development that may enhance realism within models, while also advancing our understanding of the processes and effectiveness of adaptation to a changing climate.  
  Address 2019-04-27  
  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 1436-3798 ISBN Medium Article  
  Area Expedition Conference  
  Notes TradeM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 5220  
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Author Sandars, D.; Audsley, E.; Holman, I. url  openurl
  Title (up) Predicting the optimum land use at any location for any future scenario (CLIMSAVE/IMPRESSIONS) Type Conference Article
  Year 2014 Publication Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Given any socio-, techno-, economic scenario and location specific soil and climate scenario, the farm model predicts the most profitable land use at that location.  This model is encapsulated within a Europe-wide interactive interface, to allow adaptation and mitigation options to be explored by any user.  With 5 climate models and 19 parameters, the user can study the sensitivity of the results to the chosen scenario settings.  A scenario’s land use can be classified as intensive arable, intensive grassland, extensive grassland, forestry, or abandoned depending on potential profitability.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title FACCE MACSUR Mid-term Scientific Conference  
  Series Volume 3(S) Sassari, Italy Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy  
  Notes Approved no  
  Call Number MA @ admin @ Serial 5113  
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