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Author Persson, T.; Kværnø, S.; Höglind, M. url  doi
openurl 
  Title Impact of soil type extrapolation on timothy grass yield under baseline and future climate conditions in southeastern Norway Type Journal Article
  Year 2015 Publication Climate Research Abbreviated Journal Clim. Res.  
  Volume 65 Issue Pages 71-86  
  Keywords climate change scenarios; crop modelling; forage grass; lingra; soil properties; spatial variability; phleum pretense; poaceae; simulation-model; nutritive-value; systems simulation; catimo model; crop models; growth; nitrogen; scale; productivity; regrowth  
  Abstract Interactions between soil properties and climate affect forage grass productivity. Dynamic models, simulating crop performance as a function of environmental conditions, are valid for a specific location with given soil and weather conditions. Extrapolations of local soil properties to larger regions can help assess the requirement for soil input in regional yield estimations. Using the LINGRA model, we simulated the regional yield level and variability of timothy, a forage grass, in Akershus and Ostfold counties, Norway. Soils were grouped according to physical similarities according to 4 sets of criteria. This resulted in 66, 15, 5 and 1 groups of soils. The properties of the soil with the largest area was extrapolated to the other soils within each group and input to the simulations. All analyses were conducted for 100 yr of generated weather representing the period 1961-1990, and climate projections for the period 2046-2065, the Intergovernmental Panel on Climate Change greenhouse gas emission scenario A1B, and 4 global climate models. The simulated regional seasonal timothy yields were 5-13% lower on average and had higher inter-annual variability for the least detailed soil extrapolation than for the other soil extrapolations, across climates. There were up to 20% spatial intra-regional differences in simulated yield between soil extrapolations. The results indicate that, for conditions similar to these studied here, a few representative profiles are sufficient for simulations of average regional seasonal timothy yield. More spatially detailed yield analyses would benefit from more detailed soil input.  
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  Language English Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN 0936-577x 1616-1572 ISBN Medium Article  
  Area Expedition Conference (up)  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4674  
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Author Dono, G.; Raffaele, C.; Luca, G.; Roggero, P.P. openurl 
  Title Income Impacts of Climate Change: Irrigated Farming in the Mediterranean and Expected Changes in Probability of Favorable and Adverse Weather Conditions Type Journal Article
  Year 2014 Publication German Journal of Agricultural Economics Abbreviated Journal German Journal of Agricultural Economics  
  Volume 63 Issue 3 Pages 177-186  
  Keywords discrete stochastic programming; rdp measures to adapt to climate change; economic impact of climate change; irrigated agriculture and climate change; insurance tools for adaptation to climate change; water markets; risk; variability; management; systems  
  Abstract EU rural development policy (RDP) regulation 1305/2013 aims to protect farmers’ incomes from ongoing change of climate variability (CCV), and the increase in frequency of adverse climatic events. An income stabilization tool (IST) is provided to compensate drastic drops in income, including those caused by climatic events. The present study examines some aspect of its application focussing on Mediterranean irrigation area where frequent water shortages may generate significant income reductions in the current climate conditions, and may be further exacerbated by climate change. This enhanced loss of income in the future would occur due to a change in climate variability. This change would appreciably reduce the probability of weather conditions that are favourable for irrigation, but would not significantly increase either the probability of unfavourable weather conditions or the magnitude of their impact. As the IST and other insurance tools that protect against adversity and catastrophic events are only activated under extreme conditions, farmers may not consider them to be suitable in dealing with the new climate regime. This would leave a portion of the financial resources allocated by the RDP unused, resulting in less support for climate change adaptation.  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0002-1121 ISBN Medium Article  
  Area Expedition Conference (up)  
  Notes CropM, TradeM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4669  
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Author Mansouri, M.; Destain, M.-F. url  doi
openurl 
  Title Predicting biomass and grain protein content using Bayesian methods Type Journal Article
  Year 2015 Publication Stochastic Environmental Research and Risk Assessment Abbreviated Journal Stoch. Environ. Res. Risk Assess.  
  Volume 29 Issue 4 Pages 1167-1177  
  Keywords crop model; particle filter; prediction; ensemble kalman filter; parameter-estimation; particle filters; decision-support; state estimation; model; nitrogen; navigation; tracking; systems  
  Abstract This paper deals with the problem of predicting biomass and grain protein content using improved particle filtering (IPF) based on minimizing the Kullback-Leibler divergence. The performances of IPF are compared with those of the conventional particle filtering (PF) in two comparative studies. In the first one, we apply IPF and PF at a simple dynamic crop model with the aim to predict a single state variable, namely the winter wheat biomass, and to estimate several model parameters. In the second study, the proposed IPF and the PF are applied to a complex crop model (AZODYN) to predict a winter-wheat quality criterion, namely the grain protein content. The results of both comparative studies reveal that the IPF method provides a better estimation accuracy than the PF method. The benefit of the IPF method lies in its ability to provide accuracy related advantages over the PF method since, unlike the PF which depends on the choice of the sampling distribution used to estimate the posterior distribution, the IPF yields an optimum choice of this sampling distribution, which also utilizes the observed data. The performance of the proposed method is evaluated in terms of estimation accuracy, root mean square error, mean absolute error and execution times.  
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  Language English Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN 1436-3240 1436-3259 ISBN Medium Article  
  Area Expedition Conference (up)  
  Notes CropM Approved no  
  Call Number MA @ admin @ Serial 4664  
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Author Graß, R.; Thies, B.; Kersebaum, K.-C.; Wachendorf, M. url  doi
openurl 
  Title Simulating dry matter yield of two cropping systems with the simulation model HERMES to evaluate impact of future climate change Type Journal Article
  Year 2015 Publication European Journal of Agronomy Abbreviated Journal European Journal of Agronomy  
  Volume 70 Issue Pages 1-10  
  Keywords Climate change; Double cropping system; Biomass yield; Sowing and; harvesting dates; mean-square error; nitrogen dynamics; wheat production; carbon-dioxide; soil; water; management; sunflower; responses; crops  
  Abstract Regionalized model calculations showed increased rainfall and temperatures in winter and less precipitation and higher temperatures in summer due to climate change effects in the future for numerous countries in the northern hemisphere. Furthermore, model simulations predicted enhanced weather variability with an increased risk of yield losses and reduced yield stability. Recently, double cropping systems (DCS) were suggested as an environmental friendly and productive adaptation strategy with increased yield stability. This paper reviews the potential benefit of four DCS (rye (Secale cereale L.) as first crop and maize (Zea mays L.), sunflower (Helianthus annuus L.), sorghum (Sorghum sudanense L. x Sorghum bicolor L.) and sudan grass (S. sudanense L.) as second crops) in comparison with four conventional sole cropping systems (SCS) (maize, sunflower, sorghum and sudan grass) with regard to dry matter (DM) yield and soil water under conditions of climate change. We used the agro-ecosystem model HERMES for simulating these variables until the year 2100. The investigated crops sunflower, sorghum and sudan grass were parameterised first for HERMES achieving a satisfying performance. Results showed always higher DM yields per year of DCS compared with SCS. This was mainly caused by yield increases of the first crop winter rye harvested at the stage of milk ripeness. As a winter hardy crop, rye will benefit from increased precipitation and higher temperatures during winter months as well as from extended growth periods with an earlier onset in spring and an increase of growing days. Furthermore, rye is able to use the increased winter humidity for its spring growth in an efficient way. By contrast, model simulations showed that summer crops will be affected by reduced precipitation and higher temperatures during summer month for periods from 2050 onwards with the consequence of reduced yields. This yield reduction was found for all summer crops both in conventional sole crop and in DCS. Preponed harvesting of first crop winter rye as a consequence of earlier onset of growth period in spring under prospective climatic conditions lead to yield decrease, which could not be equalised by preponed sowing of second crops and extension of their growth period. Hence, total annual yield of both crops together decreased. The modification of sowing and harvesting dates as an adaptation strategy requires further research with the use of more holistic simulation models. To summarize, DCS may provide a promising adaptation strategy to effects of climate change with a substantial stabilisation of crop yields.  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1161-0301 ISBN Medium Article  
  Area Expedition Conference (up)  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4659  
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Author Lardy, R.; Bellocchi, G.; Martin, R. url  doi
openurl 
  Title Vuln-Indices: Software to assess vulnerability to climate change Type Journal Article
  Year 2015 Publication Computers and Electronics in Agriculture Abbreviated Journal Computers and Electronics in Agriculture  
  Volume 114 Issue Pages 53-57  
  Keywords climate change; Java; vulnerability indices; pasture simulation-model; integrated assessment; environmental-change; change impacts; system  
  Abstract Vuln-Indices Java-based software was developed on concepts of vulnerability to climate change of agro-ecological systems. It implements the calculation of vulnerability indices on series of state variables for assessments at both site and region levels. The tool is useful because synthetic indices help capturing complex processes and prove effective to identify the factors responsible for vulnerability and their relative importance. It is suggested that the tool may be plausible for use with stakeholders to disseminate information of climate change impacts. (C) 2015 Elsevier B.V. All rights reserved.  
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  Language English Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN 0168-1699 ISBN Medium Article  
  Area Expedition Conference (up)  
  Notes LiveM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4648  
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