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Ewert, F.; Rötter, R.P.; Bindi, M.; Webber, H.; Trnka, M.; Kersebaum, K.C.; Olesen, J.E.; van Ittersum, M.K.; Janssen, S.; Rivington, M.; Semenov, M.A.; Wallach, D.; Porter, J.R.; Stewart, D.; Verhagen, J.; Gaiser, T.; Palosuo, T.; Tao, F.; Nendel, C.; Roggero, P.P.; Bartošová, L.; Asseng, S. |
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Title  |
Crop modelling for integrated assessment of risk to food production from climate change |
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Journal Article |
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Year |
2015 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
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Volume |
72 |
Issue |
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Pages |
287-303 |
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Keywords |
uncertainty; scaling; integrated assessment; risk assessment; adaptation; crop models; agricultural land-use; change adaptation strategies; farming systems simulation; agri-environmental systems; enrichment face experiment; high-temperature stress; change impacts; nitrogen dynamics; atmospheric co2; spring wheat |
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The complexity of risks posed by climate change and possible adaptations for crop production has called for integrated assessment and modelling (IAM) approaches linking biophysical and economic models. This paper attempts to provide an overview of the present state of crop modelling to assess climate change risks to food production and to which extent crop models comply with IAM demands. Considerable progress has been made in modelling effects of climate variables, where crop models best satisfy IAM demands. Demands are partly satisfied for simulating commonly required assessment variables. However, progress on the number of simulated crops, uncertainty propagation related to model parameters and structure, adaptations and scaling are less advanced and lagging behind IAM demands. The limitations are considered substantial and apply to a different extent to all crop models. Overcoming these limitations will require joint efforts, and consideration of novel modelling approaches. |
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1364-8152 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
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4521 |
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Kollas, C.; Kersebaum, K.C.; Nendel, C.; Manevski, K.; Müller, C.; Palosuo, T.; Armas-Herrera, C.M.; Beaudoin, N.; Bindi, M.; Charfeddine, M.; Conradt, T.; Constantin, J.; Eitzinger, J.; Ewert, F.; Ferrise, R.; Gaiser, T.; Cortazar-Atauri, I.G. de; Giglio, L.; Hlavinka, P.; Hoffmann, H.; Hoffmann, M.P.; Launay, M.; Manderscheid, R.; Mary, B.; Mirschel, W.; Moriondo, M.; Olesen, J.E.; Öztürk, I.; Pacholski, A.; Ripoche-Wachter, D.; Roggero, P.P.; Roncossek, S.; Rötter, R.P.; Ruget, F.; Sharif, B.; Trnka, M.; Ventrella, D.; Waha, K.; Wegehenkel, M.; Weigel, H.-J.; Wu, L. |
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Title |
Crop rotation modelling—A European model intercomparison |
Type |
Journal Article |
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Year |
2015 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
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70 |
Issue |
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Pages |
98-111 |
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Model ensemble; Crop simulation models; Catch crop; Intermediate crop; Treatment; Multi-year; long-term experiment; climate-change; wheat production; n-fertilization; systems simulation; nitrogen dynamics; tillage intensity; winter-wheat; soil carbon; growth |
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• First model inter-comparison on crop rotations. • Continuous simulation of multi-year crop rotations yields outperformed single-year simulation. • Low accuracy of yield predictions in less commonly modelled crops such as potato, radish, grass vegetation. • Multi-model mean prediction was found to minimise the likely error arising from single-model predictions. • The representation of intermediate crops and carry-over effects in the models require further research efforts.
Diversification of crop rotations is considered an option to increase the resilience of European crop production under climate change. So far, however, many crop simulation studies have focused on predicting single crops in separate one-year simulations. Here, we compared the capability of fifteen crop growth simulation models to predict yields in crop rotations at five sites across Europe under minimal calibration. Crop rotations encompassed 301 seasons of ten crop types common to European agriculture and a diverse set of treatments (irrigation, fertilisation, CO2 concentration, soil types, tillage, residues, intermediate or catch crops). We found that the continuous simulation of multi-year crop rotations yielded results of slightly higher quality compared to the simulation of single years and single crops. Intermediate crops (oilseed radish and grass vegetation) were simulated less accurately than main crops (cereals). The majority of models performed better for the treatments of increased CO2 and nitrogen fertilisation than for irrigation and soil-related treatments. The yield simulation of the multi-model ensemble reduced the error compared to single-model simulations. The low degree of superiority of continuous simulations over single year simulation was caused by (a) insufficiently parameterised crops, which affect the performance of the following crop, and (b) the lack of growth-limiting water and/or nitrogen in the crop rotations under investigation. In order to achieve a sound representation of crop rotations, further research is required to synthesise existing knowledge of the physiology of intermediate crops and of carry-over effects from the preceding to the following crop, and to implement/improve the modelling of processes that condition these effects. |
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1161-0301 |
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CropM, ft_macsur |
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MA @ admin @ |
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4660 |
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Kahiluoto, H.; Kaseva, J.; Hakala, K.; Himanen, S.J.; Jauhiainen, L.; Rötter, R.P.; Salo, T.; Trnka, M. |
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Title |
Cultivating resilience by empirically revealing response diversity |
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Journal Article |
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Year |
2014 |
Publication |
Global Environmental Change |
Abbreviated Journal |
Glob. Environ. Change |
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25 |
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186-193 |
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Keywords |
generic approach; climate change; food security; agrifood systems; cultivars; adaptive capacity; climate-change; functional diversity; plant-communities; genetic diversity; biodiversity; ecosystems; management; redundancy; evenness; weather |
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Intensified climate and market turbulence requires resilience to a multitude of changes. Diversity reduces the sensitivity to disturbance and fosters the capacity to adapt to various future scenarios. What really matters is diversity of responses. Despite appeals to manage resilience, conceptual developments have not yet yielded a break-through in empirical applications. Here, we present an approach to empirically reveal the ‘response diversity’: the factors of change that are critical to a system are identified, and the response diversity is determined based on the documented component responses to these factors. We illustrate this approach and its added value using an example of securing food supply in the face of climate variability and change. This example demonstrates that quantifying response diversity allows for a new perspective: despite continued increase in cultivar diversity of barley, the diversity in responses to weather declined during the last decade in the regions where most of the barley is grown in Finland. This was due to greater homogeneity in responses among new cultivars than among older ones. Such a decline in the response diversity indicates increased vulnerability and reduced resilience. The assessment serves adaptive management in the face of both ecological and socioeconomic drivers. Supplier diversity in the food retail industry in order to secure affordable food in spite of global price volatility could represent another application. The approach is, indeed, applicable to any system for which it is possible to adopt empirical information regarding the response by its components to the critical factors of variability and change. Targeting diversification in response to critical change brings efficiency into diversity. We propose the generic procedure that is demonstrated in this study as a means to efficiently enhance resilience at multiple levels of agrifood systems and beyond. (C) 2014 The Authors. Published by Elsevier Ltd. |
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0959-3780 |
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CropM |
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MA @ admin @ |
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4525 |
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Kahiluoto, H.; Kaseva, J.; Balek, J.; Olesen, J.E.; Ruiz-Ramos, M.; Gobin, A.; Kersebaum, K.C.; Takac, J.; Ruget, F.; Ferrise, R.; Bezak, P.; Capellades, G.; Dibari, C.; Makinen, H.; Nendel, C.; Ventrella, D.; Rodriguez, A.; Bindi, M.; Trnka, M. |
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Title |
Decline in climate resilience of European wheat |
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Journal Article |
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Year |
2019 |
Publication |
Proceedings of the National Academy of Sciences of the United States of America |
Abbreviated Journal |
Proc. Natl. Acad. Sci. U. S. A. |
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116 |
Issue |
1 |
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123-128 |
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Keywords |
wheat; cultivar; Europe; climate resilience; response diversity; Diversity; Weather; Growth; Shifts; Crops; Yield; Variability |
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Food security relies on the resilience of staple food crops to climatic variability and extremes, but the climate resilience of European wheat is unknown. A diversity of responses to disturbance is considered a key determinant of resilience. The capacity of a sole crop genotype to perform well under climatic variability is limited; therefore, a set of cultivars with diverse responses to weather conditions critical to crop yield is required. Here, we show a decline in the response diversity of wheat in farmers’ fields in most European countries after 2002-2009 based on 101,000 cultivar yield observations. Similar responses to weather were identified in cultivar trials among central European countries and southern European countries. A response diversity hotspot appeared in the trials in Slovakia, while response diversity “deserts” were identified in Czechia and Germany and for durum wheat in southern Europe. Positive responses to abundant precipitation were lacking. This assessment suggests that current breeding programs and cultivar selection practices do not sufficiently prepare for climatic uncertainty and variability. Consequently, the demand for climate resilience of staple food crops such as wheat must be better articulated. Assessments and communication of response diversity enable collective learning across supply chains. Increased awareness could foster governance of resilience through research and breeding programs, incentives, and regulation. |
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2019-01-17 |
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0027-8424 |
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CropM, ft_macsur |
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MA @ admin @ |
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5226 |
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Trnka, M.; Kersebaum, K.; Christian,; Olesen, J.E. |
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Description of the compiled experimental data available in the MACSUR CropM database |
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Report |
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2015 |
Publication |
FACCE MACSUR Reports |
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6 |
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D-C2.1 |
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The input data necessary for crop model simulations and data for their calibration/validation (and thus requirements for observations and measurements in suitable experiments) have been collected through out the project together with data for additional analysis of abiotic factors influencing yields. A list of possible dataset was collated in the first year of project however very few of the existing datasets were found usable for the crop model simulation as they fell short of the requirements defined in the part 2.3. However database has been populated as planned with the results of the ongoing MACSUR studies and will serve in the same way for the MACSUR 2 duration. No Label |
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MA @ admin @ |
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2090 |
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