| Records |
| Author |
Rötter, R.P.; Palosuo, T.; Kersebaum, K.C.; Angulo, C.; Bindi, M.; Ewert, F.; Ferrise, R.; Hlavinka, P.; Moriondo, M.; Nendel, C.; Olesen, J.E.; Patil, R.H.; Ruget, F.; Takác, 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 |
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. (C) 2012 Elsevier B.V. All rights reserved. |
| Address |
2016-10-31 |
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English |
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| ISSN |
0378-4290 |
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Article |
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| Notes |
CropM, ftnotmacsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial  |
4803 |
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| Author |
Rötter, R.P.; Höhn, J.G.; Fronzek, S. |
| Title |
Projections of climate change impacts on crop production: A global and a Nordic perspective |
Type |
Journal Article |
| Year |
2012 |
Publication |
Acta Agriculturae Scandinavica, Section A – Animal Science |
Abbreviated Journal |
Acta Agriculturae Scandinavica, Section A – Animal Science |
| Volume |
62 |
Issue |
4 |
Pages |
166-180 |
| Keywords |
climate change; impact projection; food production; uncertainty; crop simulation model; food security; integrated assessment; winter-wheat; scenarios; agriculture; adaptation; temperature; models; yield; scale |
| Abstract |
Global climate is changing and food production is very sensitive to weather and climate variations. Global assessments of climate change impacts on food production have been made since the early 1990s, initially with little attention to the uncertainties involved. Although there has been abundant analysis of uncertainties in future greenhouse gas emissions and their impacts on the climate system, uncertainties related to the way climate change projections are scaled down as appropriate for different analyses and in modelling crop responses to climate change, have been neglected. This review paper mainly addresses uncertainties in crop impact modelling and possibilities to reduce them. We specifically aim to (i) show ranges of projected climate change-induced impacts on crop yields, (ii) give recommendations on use of emission scenarios, climate models, regionalization and ensemble crop model simulations for different purposes and (iii) discuss improvements and a few known unknowns’ affecting crop impact projections. |
| Address |
2016-10-31 |
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English |
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| ISSN |
0906-4702 1651-1972 |
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| Notes |
CropM, ftnotmacsur |
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no |
| Call Number |
MA @ admin @ |
Serial |
4802 |
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| Author |
Reidsma, P.; Wolf, J.; Kanellopoulos, A.; Schaap, B.F.; Mandryk, M.; Verhagen, J.; van Ittersum, M.K. |
| Title |
Climate change impact and adaptation research requires integrated assessment and farming systems analysis: a case study in the Netherlands |
Type |
Journal Article |
| Year |
2015 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
| Volume |
10 |
Issue |
4 |
Pages |
045004 |
| Keywords |
climate change adaptation; scenario; farm diversity; crop simulation; bio-economic farm modelling; european-union; crop yields; agriculture; responses; models; wheat; variability; improvement; strategies; scenarios |
| Abstract |
Rather than on crop modelling only, climate change impact assessments in agriculture need to be based on integrated assessment and farming systems analysis, and account for adaptation at different levels. With a case study for Flevoland, the Netherlands, we illustrate that (1) crop models cannot account for all relevant climate change impacts and adaptation options, and (2) changes in technology, policy and prices have had and are likely to have larger impacts on farms than climate change. While crop modelling indicates positive impacts of climate change on yields of major crops in 2050, a semiquantitative and participatory method assessing impacts of extreme events shows that there are nevertheless several climate risks. A range of adaptation measures are, however, available to reduce possible negative effects at crop level. In addition, at farm level farmers can change cropping patterns, and adjust inputs and outputs. Also farm structural change will influence impacts and adaptation. While the 5th IPCC report is more negative regarding impacts of climate change on agriculture compared to the previous report, also for temperate regions, our results show that when putting climate change in context of other drivers, and when explicitly accounting for adaptation at crop and farm level, impacts may be less negative in some regions and opportunities are revealed. These results refer to a temperate region, but an integrated assessment may also change perspectives on climate change for other parts of the world. |
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2016-10-31 |
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English |
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| ISSN |
1748-9326 |
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Article |
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| Notes |
CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4800 |
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| Author |
Moraru, P.I.; Rusu, T.; Guș, P.; Bogdan, I.; Pop, A.I. |
| Title |
The role of minimum tillage in protecting environmental resources of the Transylvanian Plain, Romania |
Type |
Journal Article |
| Year |
2015 |
Publication |
Romanian Agricultural Research |
Abbreviated Journal |
Romanian Agricultural Research |
| Volume |
32 |
Issue |
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Pages |
127-135 |
| Keywords |
minimum tillage; soil conservation; crop production; winter-wheat; systems; maize; conservation; temperature; yield; l. |
| Abstract |
Conservative tillage systems tested in the hilly area of the Transylvanian Plain (Romania), confirms the possibility of improving the biological, physical, chemical and technologizcal properties of the soil. Conservative components include minimum tillage systems and surface incorporation of crop residues. The minimum tillage soil systems with paraplow, chisel or rotary harrow are polyvalent alternatives for basic preparation, germination bed preparation and sowing, for fields and crops with moderate loose requirements being optimized technologies for: soil natural fertility activation and rationalization, reduction of erosion, increasing the accumulation capacity for water and realization of sowing in the optimal period. The minimum tillage systems ensure an adequate aerial-hydrical regime for the biological activity intensity and for the nutrients solubility equilibrium. The vegetal material remaining at the soil surface or superficially incorporated has its contribution to intensifying the biological activity, being an important resource of organic matter. Humus content increases by 0.41%. The minimum tillage systems rebuild the soil structure (hydrostable macroagregate content increases up to 2.2% to 5.2%), improving the global drainage of soil which allows a rapid infiltration of water in soil. Water reserve, accumulated in the 0-50 cm depth is with 1-32 m(3) ha(-1) higher in the minimum tillage variants. The result is a more productive soil, better protected against wind and water erosion and needing less fuel for preparing the germination bed. |
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2016-10-31 |
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English |
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Edition |
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| ISSN |
1222-4227 |
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Article |
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| Notes |
CropM, ftnotmacsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4795 |
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| Author |
Dietrich, J.P.; Schmitz, C.; Lotze-Campen, H.; Popp, A.; Muller, C. |
| Title |
Forecasting technological change in agriculture-An endogenous implementation in a global, and use model |
Type |
Journal Article |
| Year |
2014 |
Publication |
Technological Forecasting and Social Change |
Abbreviated Journal |
Technological Forecasting and Social Change |
| Volume |
81 |
Issue |
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Pages |
236-249 |
| Keywords |
Technological change; Land use; Agricultural productivity; Land use; intensity; Research and development; land-use; research expenditures; productivity growth; impact; deforestation; forest; yield; Business & Economics; Public Administration |
| Abstract |
Technological change in agriculture plays a decisive role for meeting future demands for agricultural goods. However, up to now, agricultural sector models and models on land use change have used technological change as an exogenous input due to various information and data deficiencies. This paper provides a first attempt towards an endogenous implementation based on a measure of agricultural land use intensity. We relate this measure to empirical data on investments in technological change. Our estimated yield elasticity with respect to research investments is 029 and production costs per area increase linearly with an increasing yield level. Implemented in the global land use model MAgPIE (”Model of Agricultural Production and its Impact on the Environment”) this approach provides estimates of future yield growth. Highest future yield increases are required in Sub-Saharan Africa, the Middle East and South Asia. Our validation with FAO data for the period 1995-2005 indicates that the model behavior is in line with observations. By comparing two scenarios on forest conservation we show that protecting sensitive forest areas in the future is possible but requires substantial investments into technological change. (C) 2013 Elsevier Inc. All rights reserved. |
| Address |
2016-10-31 |
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English |
Summary Language |
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| ISSN |
0040-1625 |
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Article |
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| Notes |
CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4789 |
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