| Records |
| Author |
Wallach, D.; Mearns, L.O.; Ruane, A.C.; Rötter, R.P.; Asseng, S. |
| Title |
Lessons from climate modeling on the design and use of ensembles for crop modeling |
Type |
Journal Article |
| Year |
2016 |
Publication |
Climatic Change |
Abbreviated Journal |
Clim. Change |
| Volume |
139 |
Issue |
3-4 |
Pages  |
551-564 |
| Keywords |
change projections; elevated CO2; uncertainty; wheat; water; soil; simulations; yield; rice; 21st-century; Model ensembles; Crop models; Climate models; Model weighting; Super ensembles |
| Abstract |
Working with ensembles of crop models is a recent but important development in crop modeling which promises to lead to better uncertainty estimates for model projections and predictions, better predictions using the ensemble mean or median, and closer collaboration within the modeling community. There are numerous open questions about the best way to create and analyze such ensembles. Much can be learned from the field of climate modeling, given its much longer experience with ensembles. We draw on that experience to identify questions and make propositions that should help make ensemble modeling with crop models more rigorous and informative. The propositions include defining criteria for acceptance of models in a crop MME, exploring criteria for evaluating the degree of relatedness of models in a MME, studying the effect of number of models in the ensemble, development of a statistical model of model sampling, creation of a repository for MME results, studies of possible differential weighting of models in an ensemble, creation of single model ensembles based on sampling from the uncertainty distribution of parameter values or inputs specifically oriented toward uncertainty estimation, the creation of super ensembles that sample more than one source of uncertainty, the analysis of super ensemble results to obtain information on total uncertainty and the separate contributions of different sources of uncertainty and finally further investigation of the use of the multi-model mean or median as a predictor. |
| Address |
2017-01-06 |
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| Language |
English |
Summary Language |
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Edition |
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| ISSN |
0165-0009 |
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Article |
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Conference |
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| Notes |
CropM, ft_MACSUR |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4933 |
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| Author |
Kersebaum, K.; Kroes, J.; Gobin, A.; Takáč, J.; Hlavinka, P.; Trnka, M.; Ventrella, D.; Giglio, L.; Ferrise, R.; Moriondo, M.; Dalla Marta, A.; Luo, Q.; Eitzinger, J.; Mirschel, W.; Weigel, H.-J.; Manderscheid, R.; Hoffmann, M.; Nejedlik, P.; Iqbal, M.; Hösch, J. |
| Title |
Assessing uncertainties of water footprints using an ensemble of crop growth models on winter wheat |
Type |
Journal Article |
| Year |
2016 |
Publication |
Water |
Abbreviated Journal |
Water |
| Volume |
8 |
Issue |
12 |
Pages |
571 |
| Keywords |
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| Abstract |
Crop productivity and water consumption form the basis to calculate the water footprint (WF) of a specific crop. Under current climate conditions, calculated evapotranspiration is related to observed crop yields to calculate WF. The assessment of WF under future climate conditions requires the simulation of crop yields adding further uncertainty. To assess the uncertainty of model based assessments of WF, an ensemble of crop models was applied to data from five field experiments across Europe. Only limited data were provided for a rough calibration, which corresponds to a typical situation for regional assessments, where data availability is limited. Up to eight models were applied for wheat. The coefficient of variation for the simulated actual evapotranspiration between models was in the range of 13%–19%, which was higher than the inter-annual variability. Simulated yields showed a higher variability between models in the range of 17%–39%. Models responded differently to elevated CO2 in a FACE (Free-Air Carbon Dioxide Enrichment) experiment, especially regarding the reduction of water consumption. The variability of calculated WF between models was in the range of 15%–49%. Yield predictions contributed more to this variance than the estimation of water consumption. Transpiration accounts on average for 51%–68% of the total actual evapotranspiration. |
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Edition |
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| ISSN |
2073-4441 |
ISBN |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4987 |
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| Author |
Van Oijen, M.; Höglind, M. |
| Title |
Toward a Bayesian procedure for using process-based models in plant breeding, with application to ideotype design |
Type |
Journal Article |
| Year |
2016 |
Publication |
Euphytica |
Abbreviated Journal |
Euphytica |
| Volume |
207 |
Issue |
3 |
Pages |
627-643 |
| Keywords |
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 |
| Abstract |
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. |
| Address |
2016-10-31 |
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| Language |
English |
Summary Language |
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Series Issue |
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Edition |
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| ISSN |
0014-2336 |
ISBN |
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Medium |
Article |
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Conference |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4820 |
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| Author |
Savary, S.; Jouanin, C.; Félix, I.; Gourdain, E.; Piraux, F.; Brun, F.; Willocquet, L. |
| Title |
Assessing plant health in a network of experiments on hardy winter wheat varieties in France: patterns of disease-climate associations |
Type |
Journal Article |
| Year |
2016 |
Publication |
European Journal of Plant Pathology |
Abbreviated Journal |
Eur. J. Plant Pathol. |
| Volume |
146 |
Issue |
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Pages |
741-755 |
| Keywords |
Puccinia triticina; Puccinia striiformis; Fusarium graminearum; Fusarium culmorum; Fusarium avenaceum; Blumeria graminis; Zymoseptoria tritici; Categorical data; Risk factor; Multiple pathosystem; Correspondence analysis; Logistic regression |
| Abstract |
A data set generated by a multi-year (2003–2010) and multi-site network of experiments on winter wheat varieties grown at different levels of crop management is analysed in order to assess the importance of climate on the variability of wheat health. Wheat health is represented by the multiple pathosystem involving five components: leaf rust, yellow rust, fusarium head blight, powdery mildew, and septoria tritici blotch. An overall framework of associations between multiple diseases and climate variables is developed. This framework involves disease levels in a binary form (i.e. epidemic vs. non-epidemic) and synthesis variables accounting for climate over spring and early summer. The multiple disease-climate pattern of associations of this framework conforms to disease-specific knowledge of climate effects on the components of the pathosystem. It also concurs with a (climate-based) risk factor approach to wheat diseases. This report emphasizes the value of large scale data in crop health assessment and the usefulness of a risk factor approach for both tactical and strategic decisions for crop health management. |
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English |
Summary Language |
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| ISSN |
0929-1873 1573-8469 |
ISBN |
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Medium |
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| Area |
CropM |
Expedition |
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Conference |
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| Notes |
CropMwp;wos; ftnot_macsur; |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4755 |
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| Author |
Bennetzen, E.H.; Smith, P.; Porter, J.R. |
| Title |
Decoupling of greenhouse gas emissions from global agricultural production: 1970-2050 |
Type |
Journal Article |
| Year |
2016 |
Publication |
Global Change Biology |
Abbreviated Journal |
Glob. Chang. Biol. |
| Volume |
22 |
Issue |
2 |
Pages |
763-781 |
| Keywords |
climate change; energy use; global agriculture; greenhouse gas emissions; land use; mitigation; sustainable intensification |
| Abstract |
Since 1970 global agricultural production has more than doubled; contributing ~1/4 of total anthropogenic greenhouse gas (GHG) burden in 2010. Food production must increase to feed our growing demands, but to address climate change, GHG emissions must decrease. Using an identity approach, we estimate and analyse past trends in GHG emission intensities from global agricultural production and land-use change and project potential future emissions. The novel Kaya-Porter identity framework deconstructs the entity of emissions from a mix of multiple sources of GHGs into attributable elements allowing not only a combined analysis of the total level of all emissions jointly with emissions per unit area and emissions per unit product. It also allows us to examine how a change in emissions from a given source contributes to the change in total emissions over time. We show that agricultural production and GHGs have been steadily decoupled over recent decades. Emissions peaked in 1991 at ~12 Pg CO2 -eq. yr(-1) and have not exceeded this since. Since 1970 GHG emissions per unit product have declined by 39% and 44% for crop- and livestock-production, respectively. Except for the energy-use component of farming, emissions from all sources have increased less than agricultural production. Our projected business-as-usual range suggests that emissions may be further decoupled by 20-55% giving absolute agricultural emissions of 8.2-14.5 Pg CO2 -eq. yr(-1) by 2050, significantly lower than many previous estimates that do not allow for decoupling. Beyond this, several additional costcompetitive mitigation measures could reduce emissions further. However, agricultural GHG emissions can only be reduced to a certain level and a simultaneous focus on other parts of the food-system is necessary to increase food security whilst reducing emissions. The identity approach presented here could be used as a methodological framework for more holistic food systems analysis. |
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English |
Summary Language |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1354-1013 |
ISBN |
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Article |
| Area |
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| Notes |
CropM, ftnotmacsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4706 |
| Permanent link to this record |
