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Author Ventrella, D.; Giglio, L.; Charfeddine, M.; Lopez, R.; Castellini, M.; Sollitto, D.; Castrignanò, A.; Fornaro, F. url  doi
openurl 
  Title Climate change impact on crop rotations of winter durum wheat and tomato in southern Italy: yield analysis and soil fertility Type Journal Article
  Year 2012 Publication Italian Journal of Agronomy Abbreviated Journal Ital. J. Agron.  
  Volume 7 Issue 1 Pages 15  
  Keywords DSSAT model; CENTURY-module; climate change; winter durum wheat; tomato, crop rotation  
  Abstract Cropping systems are affected by climate change because of the strong relationship between crop development, growth, yield, CO2 atmospheric concentration and climate conditions. The increasing temperatures and the reduction of available water resources may result in negative impacts on the agricultural activity in Mediterranean environments than other areas. In this study the CERES-Wheat and CROPGRO-Tomato models were used to assess the effects of climate change on winter wheat (Triticum durum L.) and processing tomato (Lycopersicon aesculentum Mill.) in one of most productive areas of Italy, located in the northern part of the Puglia region. In particular we have compared three different General Circulation Models (HadCM3, CCSM3, ECHAM5) subjected to a statistical downscaling under two future IPCC scenarios (B1 and A2). The analysis was carried out at regional scale repeating the simulations for seven homogeneous area characterizing the spatial variability of the region. In the second part of the study, considering only HadCM3 data set, climate change impact on long-term sequences of the two crops combined in three crop rotations were evaluated in terms of yield performances and soil fertility as indicated by the soil organic content of carbon and nitrogen. The comparison between GCMs showed no significant differences for winter durum wheat yield, while noticeable differences were found for yield and irrigation requirements of tomato. Under future scenarios, the production levels were reduced for tomato, whereas positive yield effects were observed for winter durum wheat. For winter durum wheat the simulation indicated that two- and three-year rotations, including one year of tomato cultivation, improved the cereal yield and this positive effect maintained its validity also in future scenarios. For both crops higher requirements of water and nitrogen were predicted under future scenarios. This result coupled with the decrease of yield caused negative reduction of water use efficiency and nitrogen use efficiency for tomato cultivation.  
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  Language English Summary Language Original Title  
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  ISSN 2039-6805 1125-4718 ISBN (up) Medium Article  
  Area Expedition Conference  
  Notes CropM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4481  
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Author Angulo, C.; Gaiser, T.; Rötter, R.P.; Børgesen, C.D.; Hlavinka, P.; Trnka, M.; Ewert, F. url  doi
openurl 
  Title ‘Fingerprints’ of four crop models as affected by soil input data aggregation Type Journal Article
  Year 2014 Publication European Journal of Agronomy Abbreviated Journal European Journal of Agronomy  
  Volume 61 Issue Pages 35-48  
  Keywords crop model; soil data; spatial resolution; yield distribution; aggregation; us great-plains; climate-change; integrated assessment; simulating wheat; yields; scale; productivity; uncertainty; variability; responses  
  Abstract • Systematic analysis of the influence of spatial soil data resolution on simulated regional yields and total growing season evapotranspiration. • The responses of four crop models of different complexity are compared. • Differences between models are larger than the effect of the chosen spatial soil data resolution. • Low influence of soil data resolution due to: high precipitation amount, methods for calculating water retention and method of data aggregation. The spatial variability of soil properties is an important driver of yield variability at both field and regional scale. Thus, when using crop growth simulation models, the choice of spatial resolution of soil input data might be key in order to accurately reproduce observed yield variability. In this study we used four crop models (SIMPLACE<LINTUL-SLIM>, DSSAT-CSM, EPIC and DAISY) differing in the detail of modeling above-ground biomass and yield as well as of modeling soil water dynamics, water uptake and drought effects on plants to simulate winter wheat in two (agro-climatologically and geo-morphologically) contrasting regions of the federal state of North-Rhine-Westphalia (Germany) for the period from 1995 to 2008. Three spatial resolutions of soil input data were taken into consideration, corresponding to the following map scales: 1:50 000, 1:300 000 and 1:1 000 000. The four crop models were run for water-limited production conditions and model results were evaluated in the form of frequency distributions, depicted by bean-plots. In both regions, soil data aggregation had very small influence on the shape and range of frequency distributions of simulated yield and simulated total growing season evapotranspiration for all models. Further analysis revealed that the small influence of spatial resolution of soil input data might be related to: (a) the high precipitation amount in the region which partly masked differences in soil characteristics for water holding capacity, (b) the loss of variability in hydraulic soil properties due to the methods applied to calculate water retention properties of the used soil profiles, and (c) the method of soil data aggregation. No characteristic “fingerprint” between sites, years and resolutions could be found for any of the models. Our results support earlier recommendation to evaluate model results on the basis of frequency distributions since these offer quick and better insight into the distribution of simulation results as compared to summary statistics only. Finally, our results support conclusions from other studies about the usefulness of considering a multi-model approach to quantify the uncertainty in simulated yields introduced by the crop growth simulation approach when exploring the effects of scaling for regional yield impact assessments.  
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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 (up) Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4511  
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Author Semenov, M.A.; Mitchell, R.A.C.; Whitmore, A.P.; Hawkesford, M.J.; Parry, M.A.J.; Shewry, P.R. url  doi
openurl 
  Title Shortcomings in wheat yield predictions Type Journal Article
  Year 2012 Publication Nature Climate Change Abbreviated Journal Nat. Clim. Change  
  Volume 2 Issue 6 Pages 380-382  
  Keywords winter-wheat; elevated CO2; temperature; growth  
  Abstract Predictions of a 40–140% increase in wheat yield by 2050, reported in the UK Climate Change Risk Assessment, are based on a simplistic approach that ignores key factors affecting yields and hence are seriously misleading.  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1758-678x 1758-6798 ISBN (up) Medium Commentary  
  Area Expedition Conference  
  Notes CropM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4504  
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Author Semenov, M.A.; Stratonovitch, P. doi  openurl
  Title Designing high-yielding wheat ideotypes for a changing climate Type Journal Article
  Year 2013 Publication Food and Energy Security Abbreviated Journal Food Energy Secur.  
  Volume 2 Issue 3 Pages 185-196  
  Keywords Climate change impacts; crop modeling; LARS-WG; Sirius; wheat  
  Abstract Global warming is characterized by shifts in weather patterns and increases in climatic variability and extreme events. New wheat cultivars will be required for a rapidly changing environment, putting severe pressure on breeders who must select for climate conditions which can only be predicted with a great degree of uncertainty. To assist breeders to identify key wheat traits for improvements under climate change, wheat ideotypes can be designed and tested in silico using a wheat simulation model for a wide range of future climate scenarios predicted by global climate models. A wheat ideotype is represented by a set of cultivar parameters in a model, which could be optimized for best wheat performance under projected climate change. As an example, high-yielding wheat ideotypes were designed at two contrasting European sites for the 2050 (A1B) climate scenario. Simulations showed that wheat yield potential can be substantially increased for new ideotypes compared with current wheat varieties under climate change. The main factors contributing to yield increase were improvement in light conversion efficiency, extended duration of grain filling resulting in a higher harvest index, and optimal phenology.  
  Address  
  Corporate Author Thesis  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2048-3694 ISBN (up) Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4505  
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Author Dono, G.; Cortignani, R.; Doro, L.; Giraldo, L.; Ledda, L.; Pasqui, M.; Roggero, P.P. url  doi
openurl 
  Title An integrated assessment of the impacts of changing climate variability on agricultural productivity and profitability in an irrigated Mediterranean catchment Type Journal Article
  Year 2013 Publication Water Resource Management Abbreviated Journal Water Resource Manage.  
  Volume 27 Issue 10 Pages 3607-3622  
  Keywords discrete stochastic programming; climate change variability; adaptation to climate change; net evapotranspiration and irrigation requirements; water availability; epic crops model; economic impact of climate change; precipitation; uncertainty; region; series; yield; model; scale; wheat; gis  
  Abstract Climate change is likely to have a profound effect on many agricultural variables, although the extent of its influence will vary over the course of the annual farm management cycle. Consequently, the effect of different and interconnected physical, technical and economic factors must be modeled in order to estimate the effects of climate change on agricultural productivity. Such modeling commonly makes use of indicators that summarize the among environmental factors that are considered when farmers plan their activities. This study uses net evapotranspiration (ETN), estimated using EPIC, as a proxy index for the physical factors considered by farmers when managing irrigation. Recent trends suggest that the probability distribution function of ETN may continue to change in the near future due to changes in the irrigation needs of crops. Also, water availability may continue to vary due to changes in the rainfall regime. The impacts of the uncertainties related to these changes on costs are evaluated using a Discrete Stochastic Programming model representing an irrigable Mediterranean area where limited water is supplied from a reservoir. In this context, adaptation to climate change can be best supported by improvements to the collective irrigation systems, rather than by measures aimed at individual farms such as those contained within the rural development policy.  
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  Series Volume Series Issue Edition  
  ISSN 0920-4741 ISBN (up) Medium Article  
  Area Expedition Conference  
  Notes TradeM Approved no  
  Call Number MA @ admin @ Serial 4487  
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