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Cammarano, D.; Rivington, M.; Matthew, K.B.; Miller, D.G.; Bellocchi, G. |
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Uncertainties of different weather data input on three multi-models simulations of yield and water use |
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2016 |
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Berlin (Germany) |
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International Crop Modelling Symposium iCROPM 2016, 2016-05-15 to 2016-05-17, Berlin, Germany |
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MA @ admin @ |
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4901 |
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Schönhart, M. |
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Uncertainties from Climate Change on Farms and Ecosystem Services of a Grassland Dominated Austrian Landscape |
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2016 |
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FACCE MACSUR Reports |
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9 C6 - |
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Sp9-9 |
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MACSUR 1: development of a method to analysefarm and landscape scale impacts of CC, mitigationand adaptation effects– cropland dominated landscape, crop choice and soilmanagement– climate model uncertainty• Now: test and improve the robustness of the method– grassland landscape, cropland expansion and livestock– uncertainty analysis– variability of weather conditions High spatial resolution creates interfaces to disciplinarymodels and indicators• Challenging data & modelling demand• Increasing productivity can increase intensification pressures• Threatened permanent (extensive) grasslands and landscape elements, but• subject to resource constraints, costs and prices• Future RDP and environmental policy design (e.g. WFD) may need to takechanging productivity into account• Future research: analyze uncertainties & environmentalimpacts• Ensembles of crop and grassland models• Sensitivity analysis on economic input parameters• Qualitative surveys with agricultural experts and farmers |
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4832 |
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Fetzel et al. |
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Towards sustainable livestock production systems: Analyzing ecological constraints to grazing intensity |
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2016 |
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FACCE MACSUR Reports |
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8 |
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SP8-8 |
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4833 |
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Van Oijen, M.; Höglind, M. |
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Toward a Bayesian procedure for using process-based models in plant breeding, with application to ideotype design |
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2016 |
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Euphytica |
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Euphytica |
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207 |
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3 |
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627-643 |
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BASGRA; cold tolerance; genotype-environment interaction; plant breeding; process-based modelling; yield stability; grassland productivity; timothy regrowth; climate-change; water-deficit; forest models; late blight; leaf-area; calibration; growth; tolerance |
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Process-based grassland models (PBMs) simulate growth and development of vegetation over time. The models tend to have a large number of parameters that represent properties of the plants. To simulate different cultivars of the same species, different parameter values are required. Parameter differences may be interpreted as genetic variation for plant traits. Despite this natural connection between PBMs and plant genetics, there are only few examples of successful use of PBMs in plant breeding. Here we present a new procedure by which PBMs can help design ideotypes, i.e. virtual cultivars that optimally combine properties of existing cultivars. Ideotypes constitute selection targets for breeding. The procedure consists of four steps: (1) Bayesian calibration of model parameters using data from cultivar trials, (2) Estimating genetic variation for parameters from the combination of cultivar-specific calibrated parameter distributions, (3) Identifying parameter combinations that meet breeding objectives, (4) Translating model results to practice, i.e. interpreting parameters in terms of practical selection criteria. We show an application of the procedure to timothy (Phleum pratense L.) as grown in different regions of Norway. |
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2016-10-31 |
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English |
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0014-2336 |
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CropM, ft_macsur |
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MA @ admin @ |
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4820 |
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Ventrella, D. |
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The time factor in the long term resarches: statistichal and modelling approaches |
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2016 |
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XIX National conference of Italian Agrometeorology. New adversities and new services for agroecosystems. 2016-04-14 to 2016-04-16 |
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MA @ admin @ |
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4889 |
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