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Carter, T. |
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Scenarios and related data for MACSUR2 Timothy Carter Finnish Environment |
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2015 |
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FACCE MACSUR Reports |
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5 |
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Sp5-11 |
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Framing scenario selection (RCP/SSP)Ongoing scenario development in FP7 IMPRESSIONSSome examples of sources of data and scenarios No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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MA @ admin @ |
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2126 |
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Dader, B. |
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Elevated CO2 impacts bell pepper growth with consequences in the feeding behaviour and performance of the green peach aphid, Myzus persicae |
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2015 |
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FACCE MACSUR Reports |
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5 |
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Sp5-14 |
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Future CO2 predictions estimate an increase up to 550 ppm within only few decades away. Among the observed effects on plants, increasing CO2 stimulates growth, reduces stomatal conductance and transpiration, improves water-use efficiency and induces photosynthesis. These changes have an indirect impact on pest biology and behaviour, e.g. altering their population growth or feeding habits.Our first aim was to study the effect of ambient (400 ppm) (aCO2) and elevated CO2 (650 ppm) (eCO2) on pepper (Capsicum annuum L.). Height, leaf area, dry weight and leaf temperature by thermal imaging were measured. Chlorophyll was measured in SPAD units as an indirect indicator of nitrogen foliar content. Peppers under eCO2 were significantly taller although they had the same number of leaves than under aCO2. SPAD was significantly lower under eCO2. Leaf, stem and above-ground dry weight were significantly higher under eCO2. There was a significant decrease in specific leaf area under eCO2. Canopy temperature was 1.2 °C higher under eCO2.Secondly, pepper plants were used to assess the development and fecundity of M. persicae. The pre-reproductive period was 11% longer in eCO2 peppers. Aphids grew significantly slower and produced fewer nymphs under eCO2. Lastly, aphid feeding behaviour was studied using the Electrical Penetration Graph (EPG) technique, which provides a live visualization and recording of plant penetration by aphid mouthparts. EPG results will be presented and discussed. No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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MA @ admin @ |
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2129 |
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Lehtonen, H. |
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Sector level agricultural development following different adaptations to climate change |
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2015 |
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FACCE MACSUR Reports |
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5 |
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Sp5-36 |
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Future crop yields in northern Europe are subject to many factors and uncertainties, according to recent agro-ecological studies. Based on our farm level analysis, we concluded that prices of agricultural products are the primary drivers in the adaptation to climate change. They, as well as the policy conditions, affect the level of fertilization and the use of other inputs, land use and the intensity and the volume of agricultural production. We outlined 5 main scenarios of agricultural adaptation in Finland, and used an agricultural sector model to assess the impacts of the 5 scenarios on total production and land use in the whole country and in its four main regions. In the scenarios with unchanged product prices in the real terms, we find that a small increase or decrease in crop yields is possible. Significantly higher yields would require also 20-30% higher prices of crop products. Our sector modeling results suggest that avoiding decreases in crop yields is important for agricultural income in the long-term, even if livestock production in also maintained by national subsidies. Decreasing yields will result in increasing nutrient surplus and most likely in increased nutrient leaching, while increasing crop yields, even slightly, would significantly decrease nutrient surplus and increase farm income. Significant increases in crop yields and prices, however, are required before production clearly increases in Finland. Interestingly, cereals production would increase relatively more than livestock production, in the case of high future prices. This is explained by the abundant land resources, as well as the high opportunity cost of labor and policy systems maintaining current livestock production. No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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MA @ admin @ |
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2151 |
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Martre, P.; He, J.; Le Gouis, J.; Semenov, M.A. |
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In silico system analysis of physiological traits determining grain yield and protein concentration for wheat as influenced by climate and crop management |
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2015 |
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Journal of Experimental Botany |
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J. Experim. Bot. |
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66 |
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12 |
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3581-3598 |
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Climate; *Computer Simulation; Crops, Agricultural/*growth & development/physiology; Edible Grain/*growth & development; Models, Biological; Nitrogen/metabolism; Plant Proteins/*metabolism; Plant Transpiration; Probability; *Quantitative Trait, Heritable; Soil/chemistry; Triticum/growth & development/metabolism/*physiology; Water/chemistry; Crop growth model; genetic adaptation; grain protein concentration; grain yield; interannual variability; sensitivity analysis; wheat (Triticum aestivum L.); yield stability |
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Genetic improvement of grain yield (GY) and grain protein concentration (GPC) is impeded by large genotype×environment×management interactions and by compensatory effects between traits. Here global uncertainty and sensitivity analyses of the process-based wheat model SiriusQuality2 were conducted with the aim of identifying candidate traits to increase GY and GPC. Three contrasted European sites were selected and simulations were performed using long-term weather data and two nitrogen (N) treatments in order to quantify the effect of parameter uncertainty on GY and GPC under variable environments. The overall influence of all 75 plant parameters of SiriusQuality2 was first analysed using the Morris method. Forty-one influential parameters were identified and their individual (first-order) and total effects on the model outputs were investigated using the extended Fourier amplitude sensitivity test. The overall effect of the parameters was dominated by their interactions with other parameters. Under high N supply, a few influential parameters with respect to GY were identified (e.g. radiation use efficiency, potential duration of grain filling, and phyllochron). However, under low N, >10 parameters showed similar effects on GY and GPC. All parameters had opposite effects on GY and GPC, but leaf and stem N storage capacity appeared as good candidate traits to change the intercept of the negative relationship between GY and GPC. This study provides a system analysis of traits determining GY and GPC under variable environments and delivers valuable information to prioritize model development and experimental work. |
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1460-2431 (Electronic) 0022-0957 (Linking) |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4567 |
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Ramirez-Villegas, J.; Watson, J.; Challinor, A.J. |
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Identifying traits for genotypic adaptation using crop models |
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2015 |
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Journal of Experimental Botany |
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J. Experim. Bot. |
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66 |
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12 |
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3451-3462 |
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Adaptation, Physiological/*genetics; Crops, Agricultural/*genetics; Environment; Genotype; *Models, Theoretical; *Quantitative Trait, Heritable; Climate change; crop models; genotypic adaptation; ideotypes; impacts |
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Genotypic adaptation involves the incorporation of novel traits in crop varieties so as to enhance food productivity and stability and is expected to be one of the most important adaptation strategies to future climate change. Simulation modelling can provide the basis for evaluating the biophysical potential of crop traits for genotypic adaptation. This review focuses on the use of models for assessing the potential benefits of genotypic adaptation as a response strategy to projected climate change impacts. Some key crop responses to the environment, as well as the role of models and model ensembles for assessing impacts and adaptation, are first reviewed. Next, the review describes crop-climate models can help focus the development of future-adapted crop germplasm in breeding programmes. While recently published modelling studies have demonstrated the potential of genotypic adaptation strategies and ideotype design, it is argued that, for model-based studies of genotypic adaptation to be used in crop breeding, it is critical that modelled traits are better grounded in genetic and physiological knowledge. To this aim, two main goals need to be pursued in future studies: (i) a better understanding of plant processes that limit productivity under future climate change; and (ii) a coupling between genetic and crop growth models-perhaps at the expense of the number of traits analysed. Importantly, the latter may imply additional complexity (and likely uncertainty) in crop modelling studies. Hence, appropriately constraining processes and parameters in models and a shift from simply quantifying uncertainty to actually quantifying robustness towards modelling choices are two key aspects that need to be included into future crop model-based analyses of genotypic adaptation. |
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0022-0957 1460-2431 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4645 |
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