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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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Dáder, B.; Fereres, A.; Moreno, A. |
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Effects of UV radiation on pests and plant pathogens. Keynote lecture |
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2014 |
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CropM |
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Conference Horticultural Stakeholders UV4Growth COST-Action FA0906. Odense, Denmark., 2014-03-09 to 2014-03-11 |
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MA @ admin @ |
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2375 |
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Hoffmann, H.; Zhao, G.; Constantin, J.; Raynal, H.; Wallach, D.; Coucheney, E.; Sosa, C.; Lewan, E.; Eckersten, H.; Specka, X.; Kersebaum, K.-C.; Nendel, C.; Grosz, B.; Dechow, R.; Kuhnert, M.; Yeluripati, J.; Kiese, R.; Haas, E.; Klatt, S.; Teixeira, E.; Bindi, M.; Trombi, G.; Moriondo, M.; Doro, L.; Roggero, P.P.; Zhao, Z.; Wang, E.; Vanuytrecht, E.; Tao, F.; Rötter, R.; Cammarano, D.; Asseng, S.; Weihermüller, L.; Siebert, S.; Gaiser, T.; Ewert, F. |
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Effects of soil and climate input data aggregation on modelling regional crop yields |
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2015 |
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MACSUR Science Conference |
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MACSUR Science Conference, 2015-04-08 to 2015-04-10, Reading, United Kingdom |
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MA @ admin @ |
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5037 |
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Hoffmann, H.; Zhao, G.; Van Bussel, L.G.J.; Enders, A.; Specka, X.; Sosa, C.; Yeluripati, J.; Tao, F.A.U.-, C.J.; Teixeira, E.; Grosz, B.; Doro, L.; Nendel, C.; Kiese, R.; Raynal, H.; Eckersten, H.; Haas, E.; Kuhnert, M.; Lewan, E.; Bach, M.; Kersebaum, K.-C.; Rötter, R.; Wallach, D.; Gaiser, T.; Ewert, F. |
Title ![sorted by Title field, descending order (down)](img/sort_desc.gif) |
Effects of climate input data aggregation on modelling regional crop yields |
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CropM International Symposium and Workshop |
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CropM International Symposium and Workshop, 2014-02-10 to 2014-02-12, Oslo, Norway |
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MA @ admin @ |
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5044 |
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Hoffmann, H.; Zhao, G.; Van Bussel, L.; Enders, A.; Specka, X.; Sosa, C.; Yeluripati, J.; Tao, F.; Constantin, J.; Teixeira, E.; Grosz, B.; Doro, L.; Nendel, C.; Kiese, R.; Raynal, H.; Eckersten, H.; Haas, E.; Kuhnert, M.; Lewan, E.; Bach, M.; Kersebaum, K.-C.; Roggero, P.P.; Rötter, R.; Wallach, D.; Krauss, G.; Siebert, S.; Gaiser, T.; Wang, E.; Zhao, Z.; Ewert, F. |
Title ![sorted by Title field, descending order (down)](img/sort_desc.gif) |
Effects of climate input data aggregation on modelling regional crop yields |
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2014 |
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Crop models can be sensitive to climate input data aggregation and this response may differ among models. This should be considered when applying field-scale models for assessment of climate change impacts on larger spatial scales or when coupling models across scales. In order to evaluate these effects systematically, an ensemble of ten crop models was run with climate input data on different spatial aggregations ranging from 1, 10, 25, 50 and 100 km horizontal resolution for the state of North Rhine-Westphalia, Germany. Models were minimally calibrated to typical sowing and harvest dates, and crop yields observed in the region, subsequently simulating potential, water-limited and nitrogen-limited production of winter wheat and silage maize for 1982-2011. Outputs were analysed for 19 variables (yield, evapotranspiration, soil organic carbon, etc.). In this study the sensitivity of the individual models and the model ensemble in response to input data aggregation is assessed for crop yield. Results show that the mean yield of the region calculated from climate time series of 1 km horizontal resolution changes only little when using climate input data of higher aggregation levels for most models. However, yield frequency distributions change with aggregation, resembling observed data better with increasing resolution. With few exceptions, these results apply to the two crops and three production situations (potential, water-, nitrogen-limited) and across models including the model ensemble, regardless of differences among models in simulated yield levels and spatial yield patterns. Results of this study improve the confidence of using crop models at varying scales. |
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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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MA @ admin @ |
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5077 |
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