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Author |
Kipling, R.; Topp, K.; Don, A. |
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Title |
Appropriate meta-data for modellers |
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2014 |
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FACCE MACSUR Reports |
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3 |
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D-L1.4.1 |
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Report D-L1.4.1 provided an overview of the data and related resources available online and through EU funded projects, relating to soil organic carbon (SOC), and carbon sequestration in grasslands in particular. Building on D-L1.4.1, the report presented here discusses how meta-data describing these types of data (and experimental data more generally) can best be presented in an online resource useful to grassland modellers requiring data to use in their modelling work. Identifying the useful categories of meta-data is a necessary precursor to providing such a resource, which could facilitate better communication between modelling and experimental research groups, allowing researchers to more efficiently locate relevant data and to link up with other scientists working on similar topics. A survey among grassland modelling teams and an assessment of online meta-data resources was used to produce recommendations about the meta-data categories that should be included in an online resource. The categories are generic, so that the recommendations can be followed in the design of meta-data resources for the more general agricultural modelling community. No Label |
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MA @ admin @ |
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2235 |
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Reidsma, P.; Wolf, J.; Kanellopoulos, A.; Schaap, B.F.; Mandryk, M.; Verhagen, J.; Van Ittersum, M.K. |
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Climate change impact and adaptation research requires integrated assessment and farming systems analysis: a case study in the Netherlands |
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2015 |
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FACCE MACSUR Reports |
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6 |
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D-C3.4 |
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Rather than on crop modelling only, climate change impact assessments in agriculture need to be based on integrated assessment and farming systems analysis, and account for adaptation at different levels. With a case study for Flevoland, the Netherlands, we illustrate that 1) crop models cannot account for all relevant climate change impacts and adaptation options, and 2) changes in technology, policy and prices have had and are likely to have larger impacts on farms than climate change. While crop modelling indicates positive impacts of climate change on yields of major crops in 2050, a semi-quantitative and participatory method assessing impacts of extreme events shows that there are nevertheless several climate risks. A range of adaptation measures are, however, available to reduce possible negative effects at crop level. In addition, at farm level farmers can change cropping patterns, and adjust inputs and outputs. Also farm structural change will influence impacts and adaptation. While the 5th IPCC report is more negative regarding impacts of climate change on agriculture compared to the previous report, also for temperate regions, our results show that when putting climate change in context of other drivers, and when explicitly accounting for adaptation at crop and farm level, impacts may be less negative in some regions and opportunities are revealed. These results refer to a temperate region, but an integrated assessment may also change perspectives on climate change for other parts of the world. No Label |
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2097 |
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Author |
Martre, P. |
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Reducing uncertainty in prediction of wheat performance under climate change |
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2015 |
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FACCE MACSUR Reports |
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5 |
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Sp5-38 |
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Projections of climate change impacts on crop performances are inherently uncertain. However, multimodel uncertainty analysis of crop responses is rare because systematic and objective comparisons among process-based crop simulation models are difficult. Here we report on the Agricultural Model Intercomparison and Improvement Project ensemble of 30 wheat models tested using both crop and climate observed data in diverse environments, including infra-red heating field experiments, for their accuracy in simulating multiple crop growth, N economy and yield variables. The relative error averaged over models in reproducing observations was 24-38% for the different end-of-season variables. Clusters of wheat models organized by their correlations with temperature, precipitation, and solar radiation revealed common characteristics of climatic responses; however, models are rarely in the same cluster when comparing across sites. We also found that the amount of information used for calibration has only a minor effect on model ensemble climatic responses, but can be large for any single model. When simulating impacts assuming a mid-century A2 emissions scenario for climate projections from 16 downscaled general circulation models and 26 wheat models, a greater proportion of the uncertainty in climate change impact projections was due to variations among wheat models rather than to variations among climate models. Uncertainties in simulated impacts increased with atmospheric [CO2] and associated warming. Extrapolating the model ensemble temperature response (at current atmospheric [CO2]) indicated that warming is already reducing yields at a majority of wheat-growing locations. Finally, only a very weak relationship was found between the models’ sensitivities to interannual temperature variability and their response to long-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs. In conclusion, uncertainties in prediction of climate change impacts on crop performance can be reduced by improving temperature and CO2 relationships in models and are better quantified through use of impact ensembles. 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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2153 |
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Knox, J. |
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Title |
Meta-analysis of recent scientific evidence on climate impacts and uncertainty on crop yields in Europe |
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2015 |
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FACCE MACSUR Reports |
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5 |
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Sp5-30 |
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Projected changes in temperature, rainfall and soil moisture could threaten agricultural land use and crop productivity in Europe, with major consequences for food security (Daccache et al., 2014). We assessed the projected impacts of climate change on the yield of seven crops (viz wheat, barley, maize, potato, sugar beet, rice and rye) in Europe using a systematic review (SR) and meta-analysis of data reported in 67 original publications from an initial screening of 1424 studies. Whilst similar studies exist for Africa and South Asia (Roudier et al., 2011; Knox et al., 2012), surprisingly, no such comparable synthesis has been undertaken for Europe. Our study focussed on the biophysical impacts of climate change on productivity (i.e. yield per unit area) and did not consider ‘food production’ as this is dependent on many ‘non-biophysical’ factors, such as international trade policy and world markets. The data relate to the projected mean yield variations for each crop type, for all crop models, all GCM models and all time slices.For Europe, most studies projected a positive impact on yield; the reported increases largely being due to rising atmospheric CO2 concentrations enhancing both productivity and resource use efficiencies. Overall, a mean yield increase of +14% was identified, but with large differences between individual crops (e.g. wheat +22%; potato +12%) and regions (e.g. northern Europe +17%; southern Europe +7%). It is important to note that projected yield data were not available for all crops in all regions, so lack of a significant response may in part be due to the absence, or limited number of studies for certain crops and/or regions. Furthermore, the results include all reported yield projections, for all time slices, for all GCM combinations (whether single or ensemble) and for all crop modelling approaches (whether based on simple statistical trends or more complex biophysical modelling approaches). This highlights the magnitude of variability that exists when all possible sources of uncertainty are included. Further statistical analyses were conducted to disaggregate the data by time slice, climate and crop model to identify which factors were likely to contribute most to yield variations and uncertainty.The SR showed that evidence of climate change impacts on crop yield in Europe is extensive for wheat, maize, sugar beet and potato but very limited for barley, rice and rye. Interpreting the reported yield observations was compounded by ‘effect modifiers’ or reasons for heterogeneity. These included different emission scenarios and climate ensembles, implicit assumptions regarding crop varieties, the agricultural systems studied, and assumed levels of mechanization and crop husbandry. Despite its limitations, the SR helps identify where further research should be targeted and regions where adaptation will be most needed. It confirms that climate change is likely to increase productivity of Europe’s major agricultural cropping systems, with more favourable impacts in northern and central Europe. 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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2145 |
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Author |
Kersebaum, K.C. |
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Title |
Simulating crop rotations and management across climatic zones in Europe – an intercomparison study using fifteen models |
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2015 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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5 |
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Sp5-28 |
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Abstract ![sorted by Abstract field, descending order (down)](img/sort_desc.gif) |
Process based crop simulation models are widely used to assess crop production under current or future climate conditions. Most studies on climate impacts on crop growth are so far focussed on single crops and single-year simulations. However, it is known that the position of crops within a rotation can influence crop growth significantly due to carry-over effects between seasons. We compared crop models on crop rotation effects from five sites across Central Europe providing in total data of 301 cropping seasons and treatments. Treatments comprised irrigation, nitrogen (N) fertilisation, atmospheric [CO2], tillage, residue management, cover crops and soils. Crop rotations were simulated with 15 crop models as single-year simulations and/or continuous simulations over whole crop rotations in “restricted calibration” runs. Lower RMSE between observed and simulated crop yields were obtained for continuous runs as compared to single-year runs. Relatively low carry-over effects were observed due to equilibration of soil water over winter and high N fertilisation levels. Consistently, a sub-set of models applied to an additional rainfed Mediterranean site reproduced larger carry-over effects of soil water. Irrigation, N supply, cover crops and atmospheric [CO2] showed clearer effects than tillage and crop residue management. Model performance varied distinctly between crops showing the necessity to provide experimental data for model calibration also for less prominent crops. 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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2143 |
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