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Kersebaum, K.C.; Boote, K.J.; Jorgenson, J.S.; Nendel, C.; Bindi, M.; Frühauf, C.; Gaiser, T.; Hoogenboom, G.; Kollas, C.; Olesen, J.E.; Rötter, R.P.; Ruget, F.; Thorburn, P.J.; Trnka, M.; Wegehenkel, M. |
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Title |
Analysis and classification of data sets for calibration and validation of agro-ecosystem models |
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Journal Article |
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Year |
2015 |
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Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
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72 |
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402-417 |
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field experiments; data quality; crop modelling; data requirement; minimum data; software; different climatic zones; soil-moisture sensors; spatial variability; nitrogen dynamics; crop models; systems simulation; wheat yields; elevated co2; growth; field |
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Abstract |
Experimental field data are used at different levels of complexity to calibrate, validate and improve agroecosystem models to enhance their reliability for regional impact assessment. A methodological framework and software are presented to evaluate and classify data sets into four classes regarding their suitability for different modelling purposes. Weighting of inputs and variables for testing was set from the aspect of crop modelling. The software allows users to adjust weights according to their specific requirements. Background information is given for the variables with respect to their relevance for modelling and possible uncertainties. Examples are given for data sets of the different classes. The framework helps to assemble high quality data bases, to select data from data bases according to modellers requirements and gives guidelines to experimentalists for experimental design and decide on the most effective measurements to improve the usefulness of their data for modelling, statistical analysis and data assimilation. (C) 2015 Elsevier Ltd. All rights reserved. |
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1364-8152 |
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CropM, ft_macsur |
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MA @ admin @ |
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4563 |
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Elliott, J.; Müller, C.; Deryng, D.; Chryssanthacopoulos, J.; Boote, K.J.; Büchner, M.; Foster, I.; Glotter, M.; Heinke, J.; Iizumi, T.; Izaurralde, R.C.; Mueller, N.D.; Ray, D.K.; Rosenzweig, C.; Ruane, A.C.; Sheffield, J. |
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Title |
The Global Gridded Crop Model Intercomparison: data and modeling protocols for Phase 1 (v1.0) |
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Journal Article |
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Year |
2015 |
Publication |
Geoscientific Model Development |
Abbreviated Journal |
Geosci. Model Dev. |
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8 |
Issue |
2 |
Pages |
261-277 |
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Keywords |
land-surface model; climate-change; systems simulation; high-resolution; water; carbon; yield; agriculture; patterns; growth |
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We present protocols and input data for Phase 1 of the Global Gridded Crop Model Intercomparison, a project of the Agricultural Model Intercomparison and Improvement Project (AgMIP). The project includes global simulations of yields, phenologies, and many land-surface fluxes using 12-15 modeling groups for many crops, climate forcing data sets, and scenarios over the historical period from 1948 to 2012. The primary outcomes of the project include (1) a detailed comparison of the major differences and similarities among global models commonly used for large-scale climate impact assessment, (2) an evaluation of model and ensemble hindcasting skill, (3) quantification of key uncertainties from climate input data, model choice, and other sources, and (4) a multi-model analysis of the agricultural impacts of large-scale climate extremes from the historical record. |
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1991-9603 |
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CropM, ft_macsur |
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MA @ admin @ |
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4559 |
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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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72 |
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287-303 |
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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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MA @ admin @ |
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4521 |
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Fan, F.; Henriksen, C.B.; Porter, J. |
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Title |
Valuation of ecosystem services in organic cereal crop production systems with different management practices in relation to organic matter input |
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Journal Article |
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2016 |
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Ecosystem Services |
Abbreviated Journal |
Ecosystem Services |
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22 |
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117-127 |
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soil physical-properties; carbon sequestration; microbial biomass; farming systems; nitrogen mineralization; earthworm populations; straw; incorporation; economic valuation; agricultural soils; different tillage; Organic farming; Ecosystem services; Economic valuation; Management; Informed decision making |
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As the degradation of global ecosystem services (ES) continues in the last five decades, maintaining or even enhancing the ES of agro-ecosystem is one of the approaches to mitigate the global ES loss. This study provides the first estimate of an economic valuation of ES provided by organic cereal crop production systems with different management practices in relation to organic matter input (low, medium and high). Our results show that organic matter inputs significantly affect the total ES value on organic cereal crop production systems. The system with high organic matter input has the highest gross total ES value (US$ 1969 ha(-1) yr(-1)), followed by the low organic matter input system (US$ 1688 ha(-1) yr(-1)), and the lowest ES value are found in the medium organic matter input system (US$ 1492 ha(-1) yr(-1)). Organic matter inputs have strong positive relationship with non-marketable ES values, while this relationship was not found in marketable ES values. Monetizing the ES can be used by land managers and policy makers to adjust management practices in terms of organic matter input in cereal production system with a long term goal for sustainable agriculture. |
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2017-01-12 |
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2212-0416 |
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CropM, ft_MACSUR |
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MA @ admin @ |
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4934 |
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Author |
Tao, F.; Roetter, R.P.; Palosuo, T.; Diaz-Ambrona, C.G.H.; Ines Minguez, M.; Semenov, M.A.; Kersebaum, K.C.; Nendel, C.; Cammarano, D.; Hoffmann, H.; Ewert, F.; Dambreville, A.; Martre, P.; Rodriguez, L.; Ruiz-Ramos, M.; Gaiser, T.; Hohn, J.G.; Salo, T.; Ferrise, R.; Bindi, M.; Schulman, A.H. |
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Title |
Designing future barley ideotypes using a crop model ensemble |
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Journal Article |
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Year |
2017 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
Europ. J. Agron. |
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82 |
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144-162 |
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Keywords |
Water-Use Efficiency; Climate-Change; Nitrogen Dynamics; Systems; Simulation; Wheat Cultivars; Grain Weight; Yield; Growth; Fertilization; Adaptation; Adaptation; Breeding; Climate change; Crop simulation models; Impact; Genotype; Genetic traits |
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Climate change and its associated higher frequency and severity of adverse weather events require genotypic adaptation. Process-based ecophysiological modelling offers a powerful means to better target and accelerate development of new crop cultivars. Barley (Hordeum vulgare L) is an important crop throughout the world, and a good model for study of the genetics of stress adaptation because many quantitative trait loci and candidate genes for biotic and abiotic stress tolerance have been identified in it. Here, we developed a new approach to design future crop ideotypes using an ensemble of eight barley simulation models (i.e. APSIM, CropSyst, HERMES, MCWLA, MONICA, SIMPLACE, Sirius Quality, and WOFOST), and applied it to design climate-resilient barley ideotypes for Boreal and Mediterranean climatic zones in Europe. The results showed that specific barley genotypes, represented by sets of cultivar parameters in the crop models, could be promising under future climate change conditions, resulting in increased yields and low inter-annual yield variability. In contrast, other genotypes could result in substantial yield declines. The most favorable climate-zone-specific barley ideotypes were further proposed, having combinations of several key genetic traits in terms of phenology, leaf growth, photosynthesis, drought tolerance, and grain formation. For both Boreal and Mediterranean climatic zones, barley ideotypes under future climatic conditions should have a longer reproductive growing period, lower leaf senescence rate, larger radiation use efficiency or maximum assimilation rate, and higher drought tolerance. Such characteristics can produce substantial positive impacts on yields under contrasting conditions. Moreover, barley ideotypes should have a low photoperiod and high vernalization sensitivity for the Boreal climatic zone; for the Mediterranean, in contrast, it should have a low photoperiod and low vernalization sensitivity. The drought-tolerance trait is more beneficial for the Mediterranean than for the Boreal climatic zone. Our study demonstrates a sound approach to design future barley ideotypes based on an ensemble of well-tested, diverse crop models and on integration of knowledge from multiple disciplines. The robustness of model-aided ideotypes design can be further enhanced by continuously improving crop models and enhancing information exchange between modellers, agro-meteorologists, geneticists, physiologists, and plant breeders. (C) 2016 Elsevier B.V. All rights reserved. |
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2017-01-20 |
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1161-0301 |
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CropM, ft_MACSUR |
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MA @ admin @ |
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4935 |
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