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Wu, L.; Whitmore, A.P. |
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Using SPACSYS to analyse the interaction between plant and environment in a systems approach |
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2013 |
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TradeM |
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MACSUR TradeM workshop: Exploring new ideas for trade and agriculture model integration for assessing the impacts of climate change on food security, The Natural Resource and Environmental Research Center (NRERC), University of Haifa, Israel, 2013-03-03 t |
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MA @ admin @ |
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2908 |
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Woolnough, S. |
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Climate Modelling and Sub-seasonal to Seasonal Prediction: Opportunities and Challenges |
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2015 |
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FACCE MACSUR Reports |
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5 |
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Sp5-71 |
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Dr Steve Woolnough is a Principal Research Fellow in the Climate directorate of the National Centre for Atmospheric Science, and leads their Tropical Group. His interests are in the variability of the Tropical Climate System on intraseasonal to seasonal timescales, and the representation of the tropical climate system in weather and climate prediction models. He is a member of three international panels of the WMO including the Steering Group of their sub-seasonal to seasonal prediction project. Dr Woolnough will discuss the current state of climate modelling and introduce some of the uncertainties in prediction of regional climate change, and the opportunities to narrow these uncertainties. He will also discuss the current state of sub-seasonal to seasonal prediction and introduce the WCRP/WWRP Sub-seasonal Prediction Project, a new WMO project to promote research into and application of operational prediction systems. 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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2186 |
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Wolf, P.; Holz, K. |
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LandPaKT |
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2014 |
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LandPaKT (agricultural techniques: potentials and costs of greenhouse gas mitigation) is a joint project of the Leibniz Institute for Agricultural Engineering (ATB) and the Agricultural-Horticultural Faculty of the Humboldt University Berlin. Within the established graduate school LandPaKT, seven PhD students analyse the mitigation potentials and costs of greenhouse gas emissions systematically and merge them at the farm level. With the re-wetting of organic soils, the carbon sequestration in mineral soils depending on agricultural activities and the livestock husbandry, the most important sectors of agriculture are included in the analyses. With modelling and simulation approaches, single as well as combined measures are analysed with regard to their overall effect. Recommendations for the most-promising measures at farm level are deduced. Based on a farm model for water-use efficiency, developed within another ATB project (AgroHyd), LandPaKT aims to expand the model by greenhouse gas emissions. The graduate school started in May 2013.The increase of the global human population with the resulting increase in food demand accompanied by changed consumption patterns urgently calls for the exploitation of mitigation options in animal husbandry. Based on the Life Cycle Assessment (LCA) approach, methodological recommendations for carbon footprint analyses for dairy farming will be developed. Furthermore, the influence of different feeds and feeding strategies on greenhouse gas emission from dairy farming will be investigated. |
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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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5095 |
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Wolf, J.; Ouattara, K.; Supit, I. |
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Sowing rules for estimating rainfed yield potential of sorghum and maize in Burkina Faso |
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2015 |
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Agricultural and Forest Meteorology |
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Agricultural and Forest Meteorology |
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214-215 |
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208-218 |
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crop modelling; maize; sorghum; sowing; WOFOST; yield potential; semiarid west-africa; pearl-millet cultivation; soil organic-matter; climate-change; planting dates; crop model; variability; water; adaptation; tillage |
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To reduce the dependence on local expert knowledge, which is important for large-scale crop modelling studies, we analyzed sowing dates and rules for maize (Zea mays L.) and sorghum (Sorghum bicolor (L)) at three locations in Burkina Faso with strongly decreasing rainfall amounts from south to north. We tested in total 22 methods to derive optimal sowing dates that result in highest water-limited yields and lowest yield variation in a reproducible and objective way. The WOFOST crop growth simulation model was used. We found that sowing dates that are based on local expert knowledge, may work quite well for Burkina Faso and for West Africa in general. However, when no a priori information is available, maize should be sown between Julian days 160 and 200, with application of the following criteria: (a) cumulative rainfall in the sowing window is >= 3 cm or available soil moisture content is >2 cm in the moderately dry central part of Burkina Faso, (b) cumulative rainfall in this period is >= 2 cm or available soil moisture content is >1 cm in the more humid regions in the southern part of Burkina Faso. Sorghum should also be sown between Julian days 160 and 200 with application of the following criteria: (a) in the dry northern part of Burkina Faso the long duration sorghum variety should be sown when cumulative rainfall is >2 cm in the sowing window, and the short duration sorghum variety should be sown later when cumulative rainfall is >= 3 cm, (b) in central Burkina Faso sowing should start when cumulative rainfall in this period is >= 2 cm or when available soil moisture content is >1 cm. Sowing date rules are shown to be generally crop and location specific and are not generic for West Africa. However, the required precision of the sowing rules appears to rapidly decrease with increasing duration and intensity of the rainy season. Sowing delay as a result of, for example, labour constraints, has a disastrous effect on rainfed maize and sorghum yields, particularly in the northern part of West Africa with low rainfall. Optimization of sowing dates can also be done by simulating crop yields in a time window of two months around a predefined sowing date. Using these optimized dates appears to result in a good estimate of the maximal mean rainfed yield level. (C) 2015 Elsevier B.V. All rights reserved. |
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2015-10-12 |
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0168-1923 |
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CropM |
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MA @ admin @ |
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4702 |
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Wolf, J.; Kanellopoulos, A.; Kros, J.; Webber, H.; Zhao, G.; Britz, W.; Reinds, G.J.; Ewert, F.; de Vries, W. |
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Combined analysis of climate, technological and price changes on future arable farming systems in Europe |
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Journal Article |
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2015 |
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Agricultural Systems |
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Agricultural Systems |
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140 |
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56-73 |
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agriculture; capri; climate change; environmental impact; farming system; fssim; integrated assessment; integrator; model linkage; n emission; price change; scenarios; simplace; technological change; crop simulation-models; agricultural land-use; integrated assessment; growth; strategies; nitrogen; soils; environment; scenarios; emissions |
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In this study, we compare the relative importance of climate change to technological, management, price and policy changes on European arable farming systems. This required linking four models: the SIMPLACE crop growth modelling framework to calculate future yields under climate change for arable crops; the CAPRI model to estimate impacts on global agricultural markets, specifically product prices; the bio-economic farm model FSSIM to calculate the future changes in cropping patterns and farm net income at the farm and regional level; and the environmental model INTEGRATOR to calculate nitrogen (N) uptake and losses to air and water. First, the four linked models were applied to analyse the effect of climate change only or a most likely baseline (i.e. B1) scenario for 2050 as well as for two alternative scenarios with, respectively, strong (i.e. A1-b1) and weak economic growth (B2) for five regions/countries across Europe (i.e. Denmark, Flevoland, Midi Pyrenees, Zachodniopomorsld and Andalucia). These analyses Were repeated but assuming in addition to climate change impacts, also the effects of changes in technology and management on crop yields, the effects of changes in prices and policies in 2050, and the effects of all factors together. The outcomes show that the effects of climate change to 2050 result in higher farm net incomes in the Northern and Northern-Central EU regions, in practically unchanged farm net incomes in the Central and Central-Southern EU regions, and in much lower farm net incomes in Southern EU regions compared to those in the base year. Climate change in combination with improved technology and farm management and/or with price changes towards 2050 results in a higher to much higher farm net incomes. Increases in farm net income for the B1 and A1-b1 scenarios are moderately stronger than those for the B2 scenario, due to the smaller increases in product prices and/or yields for the B2 scenario. Farm labour demand slightly to moderately increases towards 2050 as related to changes in cropping patterns. Changes in N2O emissions and N leaching compared to the base year are mainly caused by changes in total N inputs from the applied fertilizers and animal manure, which in turn are influenced by changes in crop yields and cropping patterns, whereas NH3 emissions are mainly determined by assumed improvements in manure application techniques. N emissions and N leaching strongly increase in Denmark and Zachodniopomorski, slightly decrease to moderately increase in Flevoland and Midi-Pyrenees, and strongly decrease in Andalucia, except for NH3 emissions which zero to moderately decrease in Flevoland and Denmark. (C) 2015 Elsevier Ltd. All tights reserved. |
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2015-10-12 |
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0308-521x |
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CropM |
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MA @ admin @ |
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4703 |
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