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Author (up) Höglind, M.; Van Oijen, M.; Cameron, D.; Persson, T. doi  openurl
  Title Process-based simulation of growth and overwintering of grassland using the BASGRA model Type Journal Article
  Year 2016 Publication Ecological Modelling Abbreviated Journal Ecol. Model.  
  Volume 335 Issue Pages 1-15  
  Keywords Cold hardening; Frost injury; Phleum pratense L.; Process-based; modelling; Winter survival; Yield; low-temperature tolerance; perennial forage crops; dry-matter; production; climate-change; nutritive-value; snow-cover; bayesian; calibration; timothy regrowth; phleum-pratense; lolium-perenne  
  Abstract Process-based models (PBM) for simulation of weather dependent grass growth can assist farmers and plant breeders in addressing the challenges of climate change by simulating alternative roads of adaptation. They can also provide management decision support under current conditions. A drawback of existing grass models is that they do not take into account the effect of winter stresses, limiting their use for full-year simulations in areas where winter survival is a key factor for yield security. Here, we present a novel full-year PBM for grassland named BASGRA. It was developed by combining the LINGRA grassland model (Van Oijen et al., 2005a) with models for cold hardening and soil physical winter processes. We present the model and show how it was parameterized for timothy (Phleum pratense L.), the most important forage grass in Scandinavia and parts of North America and Asia. Uniquely, BASGRA simulates the processes taking place in the sward during the transition from summer to winter, including growth cessation and gradual cold hardening, and functions for simulating plant injury due to low temperatures, snow and ice affecting regrowth in spring. For the calibration, we used detailed data from five different locations in Norway, covering a wide range of agroclimatic regions, day lengths (latitudes from 59 degrees to 70 degrees N) and soil conditions. The total dataset included 11 variables, notably above-ground dry matter, leaf area index, tiller density, content of C reserves, and frost tolerance. All data were used in the calibration. When BASGRA was run with the maximum a-posteriori (MAP) parameter vector from the single, Bayesian calibration, nearly all measured variables were simulated to an overall normalized root mean squared error (NRMSE) <0.5. For many site x experiment combinations, NRMSE was <0.3. The temporal dynamics were captured well for most variables, as evaluated by comparing simulated time courses versus data for the individual sites. The results may suggest that BASGRA is a reasonably robust model, allowing for simulation of growth and several important underlying processes with acceptable accuracy for a range of agroclimatic conditions. However, the robustness of the model needs to be tested further using independent data from a wide range of growing conditions. Finally we show an example of application of the model, comparing overwintering risks in two climatically different sites, and discuss future model applications. Further development work should include improved simulation of the dynamics of C reserves, and validation of winter tiller dynamics against independent data. (C) 2016 Elsevier B.V. All rights reserved.  
  Address 2016-07-28  
  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 0304-3800 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, LiveM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4764  
Permanent link to this record
 

 
Author (up) Högner, K. openurl 
  Title Improving the methodology for global agricultural water availability and identifying hot spots for potential dam sites in East-Africa Type Book Whole
  Year 2013 Publication Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
  Address  
  Corporate Author Thesis Master's thesis  
  Publisher Potsdam Institute for Climate Impact Research Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title M.Sc.  
  Series Volume M.Sc. Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes TradeM Approved no  
  Call Number MA @ admin @ Serial 5148  
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Author (up) Höhn, J.; Rötter, R.P. url  doi
openurl 
  Title Impact of global warming on European cereal production Type Journal Article
  Year 2014 Publication CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources Abbreviated Journal CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources  
  Volume 9 Issue 022 Pages 1-15  
  Keywords Climate change; Food security; Uncertainty; Wheat; Maize; Barley  
  Abstract This review examines relevant impact assessments identified by a literature search from 1991to date. A bibliographic search was applied to the CAB Abstracts database with a given searchstring. Resultant papers were checked for relevance, based on expert judgment. This yielded 91 papers, which were subjected to further analysis. Firstly, publication intensity over time and distribution by geographic location and cereal crop were examined. Next, for a given crop, the assessments and their outcomes were grouped by type and number of the change variables considered – that is, effects of climate change only, elevated CO 2 and technological progress(improved breeds, management). Finally, separately for individual countries/subregions and Europe as a whole, we examined whether and to what extent study results have changed over time, for example become more positive/negative. Based on our sample, we found that publication intensity increased exponentially during thelast 4 years, the majority of studies are Europe-wide, but some concentrated on a few countries(Italy, Spain and UK), whereby studies on wheat are clearly most popular. Taking the factor of technological progress into account has an overruling influence on results. Finally, over time, projected yield impacts have become more negative. This is in line with finding from global analyses, as reflected by the most recent comparison of agricultural impact chapters, of the 4thand 5th Assessment Reports of Intergovernmental Panel on Climate Change, Working Group II.In the future, there is particular need to consider impacts under various incremental and transformational adaptation measures in more depth (e.g. their interconnections across scales)and with more breadth (e.g. anticipated new breeds). Follow-up reviews should also examine how projected impacts are changing with the new climate scenario data sets (CMIP5) and with improved impact models and assessment approaches.  
  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 1749-8848 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4524  
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Author (up) Holman, I. url  openurl
  Title How do models treat climate change adaptation? Type Conference Article
  Year 2016 Publication Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Presentation SC 8.4 Impact indicators & models. How do models treat climate change adaptation?, Ian Holman, Cranfield University, United Kingdom (2016). Presented at the international conference Adaptation Futures 2016, Rotterdam, the Netherlands. No Label  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Rotterdam (Netherlands) Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
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  Area Expedition Conference AdaptationFutures 2016, 10-13 May 2016, Rotterdam  
  Notes Approved no  
  Call Number MA @ admin @ Serial 2490  
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Author (up) Holman, I. url  openurl
  Title Identifying where future landuse allocation in Europe is robust to climate and socio-economic uncertainty Type
  Year 2015 Publication FACCE MACSUR Reports Abbreviated Journal  
  Volume 5 Issue Pages Sp5-23  
  Keywords  
  Abstract The spatial distribution of future European landuse will be influenced by yield changes arising from climate change and changes in profitability as a consequence of socio-economic change (arising from changing food demand; prices; technology etc).  To understand how these factors affect future land use allocation, a modelling system has been set up to predict agricultural land use across the EU under any scenario set of climate and socio- and techno-economic data. Metamodels of crop and forest yields, and optimal cropping and profit are derived from the outputs of the IMPEL, GOTILWA+, SFARMODand WaterGAP models. Profitability of each possible land use is modelled across the EU, assuming that use will change to the most profitable in the timescale being considered (2050). Land use in a grid is then allocated based on profit, with minimum profit thresholds set for intensive agriculture (arable or grassland), extensive agriculture, managed forest and finally unmanaged forest or unmanaged land.  The European demand for food as a function of population, imports, food preferences and bioenergy, is a production constraint, as is irrigation water available.  The model iterates prices until demand is satisfied (or cannot be met) and basin water usage for irrigation is not more than is available.This presentation describes the application of the modelling system across future climate change uncertainty space (as given by 60 combinations of downscaled 10’x10’ gridded climate outputs from 5 Global Climate Models, 3 climate sensitivities and 4 emissions scenario) under both baseline and four future socio-economic scenarios to identify those areas of Europe in which the spatial allocation of agricultural landcovers are robust to this uncertainty. No Label  
  Address  
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  Area Expedition Conference MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK  
  Notes Approved no  
  Call Number MA @ admin @ Serial 2138  
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