| Records |
| Author |
Tao, F.; Rötter, R.P.; Palosuo, T.; Höhn, J.; Peltonen-Sainio, P.; Rajala, A.; Salo, T. |
| Title |
Assessing climate effects on wheat yield and water use in Finland using a super-ensemble-based probabilistic approach |
Type |
Journal Article |
| Year |
2015 |
Publication |
Climate Research |
Abbreviated Journal |
Clim. Res. |
| Volume |
65 |
Issue |
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Pages |
23-37 |
| Keywords |
adaptation; drought; evapotranspiration; heat stress; risk; uncertainties; northern agriculture; model; weather; variability; precipitation; uncertainty; adaptation; simulation; dynamics; impacts |
| Abstract |
We adapted a large area crop model, MCWLA-Wheat, to winter wheat Triticum aestivum L. and spring wheat in Finland. We then applied Bayesian probability inversion and a Markov Chain Monte Carlo technique to analyze uncertainties in parameter estimations and to optimize parameters. Finally, a super-ensemble-based probabilistic projection system was updated and applied to project the effects of climate change on wheat productivity and water use in Finland. The system used 6 climate scenarios and 20 sets of crop model parameters. We projected spatiotemporal changes of wheat productivity and water use due to climate change/variability during 2021-2040, 2041-2070, and 2071-2100. The results indicate that with a high probability wheat yields will increase substantially in Finland under the tested climate change scenarios, and spring wheat can benefit more from climate change than winter wheat. Nevertheless, in some areas of southern Finland, wheat production will face increasing risk of high temperature and drought, which can offset the benefits of climate change on wheat yield, resulting in an increase in yield variability and about 30% probability of yield decrease for spring wheat. Compared with spring wheat, the development, photosynthesis, and consequently yield will be much less enhanced for winter wheat, which, together with the risk of extreme weather, will result in an up to 56% probability of yield decrease in eastern parts of Finland. Our study explicitly para meterized the effects of extreme temperature and drought stress on wheat yields, and accounted for a wide range of wheat cultivars with contrasting phenological characteristics and thermal requirements. |
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English |
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| ISSN |
0936-577x 1616-1572 |
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CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4667 |
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| Author |
Martre, P.; Wallach, D.; Asseng, S.; Ewert, F.; Jones, J.W.; Rötter, R.P.; Boote, K.J.; Ruane, A.C.; Thorburn, P.J.; Cammarano, D.; Hatfield, J.L.; Rosenzweig, C.; Aggarwal, P.K.; Angulo, C.; Basso, B.; Bertuzzi, P.; Biernath, C.; Brisson, N.; Challinor, A.J.; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, R.F.; Heng, L.; Hooker, J.; Hunt, L.A.; Ingwersen, J.; Izaurralde, R.C.; Kersebaum, K.C.; Müller, C.; Kumar, S.N.; Nendel, C.; O’Leary, G.; Olesen, J.E.; Osborne, T.M.; Palosuo, T.; Priesack, E.; Ripoche, D.; Semenov, M.A.; Shcherbak, I.; Steduto, P.; Stöckle, C.O.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; White, J.W.; Wolf, J. |
| Title |
Multimodel ensembles of wheat growth: many models are better than one |
Type |
Journal Article |
| Year |
2015 |
Publication |
Global Change Biology |
Abbreviated Journal |
Glob. Chang. Biol. |
| Volume |
21 |
Issue |
2 |
Pages |
911-925 |
| Keywords |
Climate; Climate Change; Environment; *Models, Biological; Seasons; Triticum/*growth & development; ecophysiological model; ensemble modeling; model intercomparison; process-based model; uncertainty; wheat (Triticum aestivum L.) |
| Abstract |
Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24-38% for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models. |
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Edition |
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1354-1013 |
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CropM, ftnotmacsur |
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no |
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MA @ admin @ |
Serial |
4665 |
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Eitzinger, J.; Thaler, S.; Schmid, E.; Strauss, F.; Ferrise, R.; Moriondo, M.; Bindi, M.; Palosuo, T.; Rotter, R.; Kersebaum, K.C.; Olesen, J.E.; Patil, R.H.; Saylan, L.; Caldag, B.; Caylak, O. |
| Title |
Sensitivities of crop models to extreme weather conditions during flowering period demonstrated for maize and winter wheat in Austria |
Type |
Journal Article |
| Year |
2013 |
Publication |
Journal of Agricultural Science |
Abbreviated Journal |
J. Agric. Sci. |
| Volume |
151 |
Issue |
6 |
Pages |
813-835 |
| Keywords |
simulate yield response; climate-change scenarios; central-europe; nitrogen dynamics; high-temperature; future climate; elevated co2; soil; growth; variability |
| Abstract |
The objective of the present study was to compare the performance of seven different, widely applied crop models in predicting heat and drought stress effects. The study was part of a recent suite of model inter-comparisons initiated at European level and constitutes a component that has been lacking in the analysis of sources of uncertainties in crop models used to study the impacts of climate change. There was a specific focus on the sensitivity of models for winter wheat and maize to extreme weather conditions (heat and drought) during the short but critical period of 2 weeks after the start of flowering. Two locations in Austria, representing different agro-climatic zones and soil conditions, were included in the simulations over 2 years, 2003 and 2004, exhibiting contrasting weather conditions. In addition, soil management was modified at both sites by following either ploughing or minimum tillage. Since no comprehensive field experimental data sets were available, a relative comparison of simulated grain yields and soil moisture contents under defined weather scenarios with modified temperatures and precipitation was performed for a 2-week period after flowering. The results may help to reduce the uncertainty of simulated crop yields to extreme weather conditions through better understanding of the models’ behaviour. Although the crop models considered (DSSAT, EPIC, WOFOST, AQUACROP, FASSET, HERMES and CROPSYST) mostly showed similar trends in simulated grain yields for the different weather scenarios, it was obvious that heat and drought stress caused by changes in temperature and/or precipitation for a short period of 2 weeks resulted in different grain yields simulated by different models. The present study also revealed that the models responded differently to changes in soil tillage practices, which affected soil water storage capacity. |
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0021-8596 |
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Article |
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CropM |
Approved |
no |
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MA @ admin @ |
Serial |
4601 |
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Rötter, R.P.; Palosuo, T.; Kersebaum, K.-C.; Angulo, C.; Bindi, M.; Ewert, F.; Ferrise, R.; Hlavinka, P.; Moriondo, M.; Olesen, J.E.; Takáč, J.; Trnka, M. |
| Title |
Simulation of spring barley yield in different climatic zones of Northern and Central Europe: A comparison of nine crop models |
Type |
Journal Article |
| Year |
2012 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
| Volume |
133 |
Issue |
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Pages |
23-36 |
| Keywords |
Climate; Crop growth simulation; Model comparison; Spring barley; Yield variability; Uncertainty; change impacts; nitrogen dynamics; high-temperature; soil-moisture; elevated co2; ceres-wheat; data set; growth; drought; sensitivity |
| Abstract |
► We compared nine crop simulation models for spring barley at seven sites in Europe. ► Applying crop models with restricted calibration leads to high uncertainties. ► Multi-crop model mean yield estimates were in good agreement with observations. ► The degree of uncertainty for simulated grain yield of barley was similar to winter wheat. ► We need more suitable data enabling us to verify different processes in the models. In this study, the performance of nine widely used and accessible crop growth simulation models (APES-ACE, CROPSYST, DAISY, DSSAT-CERES, FASSET, HERMES, MONICA, STICS and WOFOST) was compared during 44 growing seasons of spring barley (Hordeum vulgare L) at seven sites in Northern and Central Europe. The aims of this model comparison were to examine how different process-based crop models perform at multiple sites across Europe when applied with minimal information for model calibration of spring barley at field scale, whether individual models perform better than the multi-model mean, and what the uncertainty ranges are in simulated grain yields. The reasons for differences among the models and how results for barley compare to winter wheat are discussed. Regarding yield estimation, best performing based on the root mean square error (RMSE) were models HERMES, MONICA and WOFOST with lowest values of 1124, 1282 and 1325 (kg ha(-1)), respectively. Applying the index of agreement (IA), models WOFOST, DAISY and HERMES scored best having highest values (0.632, 0.631 and 0.585, respectively). Most models systematically underestimated yields, whereby CROPSYST showed the highest deviation as indicated by the mean bias error (MBE) (-1159 kg ha(-1)). While the wide range of simulated yields across all sites and years shows the high uncertainties in model estimates with only restricted calibration, mean predictions from the nine models agreed well with observations. Results of this paper also show that models that were more accurate in predicting phenology were not necessarily the ones better estimating grain yields. Total above-ground biomass estimates often did not follow the patterns of grain yield estimates and, thus, harvest indices were also different. Estimates of soil moisture dynamics varied greatly. In comparison, even though the growing cycle for winter wheat is several months longer than for spring barley, using RMSE and IA as indicators, models performed slightly, but not significantly, better in predicting wheat yields. Errors in reproducing crop phenology were similar, which in conjunction with the shorter growth cycle of barley has higher effects on accuracy in yield prediction. |
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CropM, ftnotmacsur |
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no |
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MA @ admin @ |
Serial |
4592 |
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| Author |
Olesen, J.E.; Børgesen, C.D.; Elsgaard, L.; Palosuo, T.; Rötter, R.P.; Skjelvåg, A.O.; Peltonen-Sainio, P.; Börjesson, T.; Trnka, M.; Ewert, F.; Siebert, S.; Brisson, N.; Eitzinger, J.; van Asselt, E.D.; Oberforster, M.; van der Fels-Klerx, H.J. |
| Title |
Changes in time of sowing, flowering and maturity of cereals in Europe under climate change |
Type |
Journal Article |
| Year |
2012 |
Publication |
Food Additives & Contaminants: Part A |
Abbreviated Journal |
Food Addit. Contam. Part A |
| Volume |
29 |
Issue |
10 |
Pages |
1527-1542 |
| Keywords |
Agriculture/*methods/trends; Avena/growth & development; *Climate Change; Crops, Agricultural/*growth & development; Edible Grain/*growth & development; Europe; Flowering Tops/growth & development; Forecasting/methods; Germination; Humans; Models, Biological; Models, Statistical; Seasons; Seeds/growth & development; Spatio-Temporal Analysis; Triticum/growth & development; Zea mays/growth & development |
| Abstract |
The phenological development of cereal crops from emergence through flowering to maturity is largely controlled by temperature, but also affected by day length and potential physiological stresses. Responses may vary between species and varieties. Climate change will affect the timing of cereal crop development, but exact changes will also depend on changes in varieties as affected by plant breeding and variety choices. This study aimed to assess changes in timing of major phenological stages of cereal crops in Northern and Central Europe under climate change. Records on dates of sowing, flowering, and maturity of wheat, oats and maize were collected from field experiments conducted during the period 1985-2009. Data for spring wheat and spring oats covered latitudes from 46 to 64°N, winter wheat from 46 to 61°N, and maize from 47 to 58°N. The number of observations (site-year-variety combinations) varied with phenological phase, but exceeded 2190, 227, 2076 and 1506 for winter wheat, spring wheat, spring oats and maize, respectively. The data were used to fit simple crop development models, assuming that the duration of the period until flowering depends on temperature and day length for wheat and oats, and on temperature for maize, and that the duration of the period from flowering to maturity in all species depends on temperature only. Species-specific base temperatures were used. Sowing date of spring cereals was estimated using a threshold temperature for the mean air temperature during 10 days prior to sowing. The mean estimated temperature thresholds for sowing were 6.1, 7.1 and 10.1°C for oats, wheat and maize, respectively. For spring oats and wheat the temperature threshold increased with latitude. The effective temperature sums required for both flowering and maturity increased with increasing mean annual temperature of the location, indicating that varieties are well adapted to given conditions. The responses of wheat and oats were largest for the period from flowering to maturity. Changes in timing of cereal phenology by 2040 were assessed for two climate model projections according to the observed dependencies on temperature and day length. The results showed advancements of sowing date of spring cereals by 1-3 weeks depending on climate model and region within Europe. The changes were largest in Northern Europe. Timing of flowering and maturity were projected to advance by 1-3 weeks. The changes were largest for grain maize and smallest for winter wheat, and they were generally largest in the western and northern part of the domain. There were considerable differences in predicted timing of sowing, flowering and maturity between the two climate model projections applied. |
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1944-0049 1944-0057 |
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CropM |
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no |
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MA @ admin @ |
Serial |
4590 |
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