| Records |
| Author |
Rötter, R.P.; Tao, F.; Höhn, J.G.; Palosuo, T. |
| Title |
Use of crop simulation modelling to aid ideotype design of future cereal cultivars |
Type |
Journal Article |
| Year |
2015 |
Publication |
Journal of Experimental Botany |
Abbreviated Journal |
J. Experim. Bot. |
| Volume |
66 |
Issue |
12 |
Pages |
3463-3476 |
| Keywords |
Breeding/*methods; Climate Change; *Computer Simulation; Ecotype; Edible Grain/*growth & development; *Models, Theoretical; cereals; climate extremes; crop growth simulation; ensemble modelling; future cultivars; genetic modelling; ideotype breeding; model improvement; model-aided design |
| Abstract |
A major challenge of the 21st century is to achieve food supply security under a changing climate and roughly a doubling in food demand by 2050 compared to present, the majority of which needs to be met by the cereals wheat, rice, maize, and barley. Future harvests are expected to be especially threatened through increased frequency and severity of extreme events, such as heat waves and drought, that pose particular challenges to plant breeders and crop scientists. Process-based crop models developed for simulating interactions between genotype, environment, and management are widely applied to assess impacts of environmental change on crop yield potentials, phenology, water use, etc. During the last decades, crop simulation has become important for supporting plant breeding, in particular in designing ideotypes, i.e. ‘model plants’, for different crops and cultivation environments. In this review we (i) examine the main limitations of crop simulation modelling for supporting ideotype breeding, (ii) describe developments in cultivar traits in response to climate variations, and (iii) present examples of how crop simulation has supported evaluation and design of cereal cultivars for future conditions. An early success story for rice demonstrates the potential of crop simulation modelling for ideotype breeding. Combining conventional crop simulation with new breeding methods and genetic modelling holds promise to accelerate delivery of future cereal cultivars for different environments. Robustness of model-aided ideotype design can further be enhanced through continued improvements of simulation models to better capture effects of extremes and the use of multi-model ensembles. |
| Address |
2016-10-31 |
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English |
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| ISSN |
0022-0957 1460-2431 |
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Medium  |
Review |
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Conference |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4804 |
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| Author |
Bellocchi, G.; Rivington, M.; Matthews, K.; Acutis, M. |
| Title |
Deliberative processes for comprehensive evaluation of agroecological models. A review |
Type |
Journal Article |
| Year |
2015 |
Publication |
Agronomy for Sustainable Development |
Abbreviated Journal |
Agron. Sust. Developm. |
| Volume |
35 |
Issue |
2 |
Pages |
589-605 |
| Keywords |
component-oriented programing; deliberative approach; modeling; model evaluation; multiple metrics; stakeholders; decision-support-systems; environmental-models; performance evaluation; groundwater models; farming systems; climate-change; irene-dll; simulation; validation; integration |
| Abstract |
The use of biophysical models in agroecology has increased in the last few decades for two main reasons: the need to formalize empirical knowledge and the need to disseminate model-based decision support for decision makers (such as farmers, advisors, and policy makers). The first has encouraged the development and use of mathematical models to enhance the efficiency of field research through extrapolation beyond the limits of site, season, and management. The second reflects the increasing need (by scientists, managers, and the public) for simulation experimentation to explore options and consequences, for example, future resource use efficiency (i.e., management in sustainable intensification), impacts of and adaptation to climate change, understanding market and policy responses to shocks initiated at a biophysical level under increasing demand, and limited supply capacity. Production concerns thus dominate most model applications, but there is a notable growing emphasis on environmental, economic, and policy dimensions. Identifying effective methods of assessing model quality and performance has become a challenging but vital imperative, considering the variety of factors influencing model outputs. Understanding the requirements of stakeholders, in respect of model use, logically implies the need for their inclusion in model evaluation methods. We reviewed the use of metrics of model evaluation, with a particular emphasis on the involvement of stakeholders to expand horizons beyond conventional structured, numeric analyses. Two major topics are discussed: (1) the importance of deliberative processes for model evaluation, and (2) the role computer-aided techniques may play to integrate deliberative processes into the evaluation of agroecological models. We point out that (i) the evaluation of agroecological models can be improved through stakeholder follow-up, which is a key for the acceptability of model realizations in practice, (ii) model credibility depends not only on the outcomes of well-structured, numerically based evaluation, but also on less tangible factors that may need to be addressed using complementary deliberative processes, (iii) comprehensive evaluation of simulation models can be achieved by integrating the expectations of stakeholders via a weighting system of preferences and perception, (iv) questionnaire-based surveys can help understand the challenges posed by the deliberative process, and (v) a benefit can be obtained if model evaluation is conceived in a decisional perspective and evaluation techniques are developed at the same pace with which the models themselves are created and improved. Scientific knowledge hubs are also recognized as critical pillars to advance good modeling practice in relation to model evaluation (including access to dedicated software tools), an activity which is frequently neglected in the context of time-limited framework programs. |
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| ISSN |
1774-0746 1773-0155 |
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Medium |
Review |
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| Notes |
CropM, LiveM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4551 |
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| Author |
Sándor, R.; Barcza, Z.; Hidy, D.; Lellei-Kovács, E.; Ma, S.; Bellocchi, G. |
| Title |
Modelling of grassland fluxes in Europe: evaluation of two biogeochemical models |
Type |
Journal Article |
| Year |
2016 |
Publication |
Agriculture, Ecosystems and Environment |
Abbreviated Journal |
Agric. Ecosyst. Environ. |
| Volume |
215 |
Issue |
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Pages |
1-19 |
| Keywords |
carbon-water fluxes; climate change; grasslands; model comparison; net ecosystem exchange; terrestrial carbon balance; pasture simulation-model; climate-change; nitrous-oxide; land-use; co2; photosynthesis; responses; water |
| Abstract |
Two independently developed simulation models – the grassland-specific PaSim and the biome-generic Biome-BGC MuSo (BBGC MuSo) – linking climate, soil, vegetation and management to ecosystem biogeochemical cycles were compared in a simulation of carbon (C) and water fluxes. The results were assessed against eddy-covariance flux data from five observational grassland sites representing a range of conditions in Europe: Grillenburg in Germany, Laqueuille in France with both extensive and intensive management, Monte Bondone in Italy and Oensingen in Switzerland. Model comparison (after calibration) gave substantial agreement, the performances being marginal to acceptable for weekly-aggregated gross primary production and ecosystem respiration (R-2 similar to 0.66 – 0.91), weekly evapotranspiration (R-2 similar to 0.78 – 0.94), soil water content in the topsoil (R-2 similar to 0.1 -0.7) and soil temperature (R-2 similar to 0.88 – 0.96). The bias was limited to the range -13 to 9 g C m(-2) week(-1) for C fluxes (-11 to 8 g C m(-2) week(-1) in case of BBGC MuSo, and -13 to 9 g C m(-2) week(-1) in case of PaSim) and -4 to 6 mm week for water fluxes (with BBGC MuSo providing somewhat higher estimates than PaSim), but some higher relative root mean square errors indicate low accuracy for prediction, especially for net ecosystem exchange The sensitivity of simulated outputs to changes in atmospheric carbon dioxide concentration ([CO2]), temperature and precipitation indicate, with certain agreement between the two models, that C outcomes are dominated by [CO2] and temperature gradients, and are less due to precipitation. ET rates decrease with increasing [CO2] in PaSim (consistent with experimental knowledge), while lack of appropriate stomatal response could be a limit in BBGC MuSo responsiveness. Results of the study indicate that some of the errors might be related to the improper representation of soil water content and soil temperature. Improvement is needed in the model representations of soil processes (especially soil water balance) that strongly influence the biogeochemical cycles of managed and unmanaged grasslands. (C) 2015 Elsevier B.V. All rights reserved. |
| Address |
2016-10-31 |
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English |
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| ISSN |
0167-8809 |
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Article |
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| Notes |
CropM, LiveM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4808 |
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| Author |
Siebert, S.; Ewert, F. |
| Title |
Future crop production threatened by extreme heat |
Type |
Journal Article |
| Year |
2014 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
| Volume |
9 |
Issue |
4 |
Pages |
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| Keywords |
climate-change; simulation-models; wheat yields; day length; temperature; growth; impact; co2; phenology; patterns |
| Abstract |
Heat is considered to be a major stress limiting crop growth and yields. While important findings on the impact of heat on crop yield have been made based on experiments in controlled environments, little is known about the effects under field conditions at larger scales. The study of Deryng et al (2014 Global crop yield response to extreme heat stress under multiple climate change futures Environ. Res. Lett. 9 034011), analysing the impact of heat stress on maize, spring wheat and soya bean under climate change, represents an important contribution to this emerging research field. Uncertainties in the occurrence of heat stress under field conditions, plant responses to heat and appropriate adaptation measures still need further investigation. |
| Address |
2016-10-31 |
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English |
Summary Language |
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Edition |
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| ISSN |
1748-9326 |
ISBN |
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Article |
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| Notes |
CropM, ftnotmacsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4813 |
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| Author |
Ruiz-Ramos, M.; Rodriguez, A.; Dosio, A.; Goodess, C.M.; Harpham, C.; Minguez, M.I.; Sanchez, E. |
| Title |
Comparing correction methods of RCM outputs for improving crop impact projections in the Iberian Peninsula for 21st century |
Type |
Journal Article |
| Year |
2016 |
Publication |
Climatic Change |
Abbreviated Journal |
Clim. Change |
| Volume |
134 |
Issue |
1-2 |
Pages |
283-297 |
| Keywords |
regional climate model; bias correction; weather generator; circulation model; simulations; temperature; precipitation; ensemble; uncertainty; extremes |
| Abstract |
Assessment of climate change impacts on crops in regions of complex orography such as the Iberian Peninsula (IP) requires climate model output which is able to describe accurately the observed climate. The high resolution of output provided by Regional Climate Models (RCMs) is expected to be a suitable tool to describe regional and local climatic features, although their simulation results may still present biases. For these reasons, we compared several post-processing methods to correct or reduce the biases of RCM simulations from the ENSEMBLES project for the IP. The bias-corrected datasets were also evaluated in terms of their applicability and consequences in improving the results of a crop model to simulate maize growth and development at two IP locations, using this crop as a reference for summer cropping systems in the region. The use of bias-corrected climate runs improved crop phenology and yield simulation overall and reduced the inter-model variability and thus the uncertainty. The number of observational stations underlying each reference observational dataset used to correct the bias affected the correction performance. Although no single technique showed to be the best one, some methods proved to be more adequate for small initial biases, while others were useful when initial biases were so large as to prevent data application for impact studies. An initial evaluation of the climate data, the bias correction/reduction method and the consequences for impact assessment would be needed to design the most robust, reduced uncertainty ensemble for a specific combination of location, crop, and crop management. |
| Address |
2016-10-31 |
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Thesis |
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Place of Publication |
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English |
Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
0165-0009 |
ISBN |
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Article |
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Expedition |
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Conference |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4805 |
| Permanent link to this record |
