| Records |
| Author |
Sharif, B.; Makowski, D.; Plauborg, F.; Olesen, J.E. |
| Title |
Comparison of regression techniques to predict response of oilseed rape yield to variation in climatic conditions in Denmark |
Type |
Journal Article |
| Year |
2017 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
Europ. J. Agron. |
| Volume |
82 |
Issue |
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Pages |
11-20 |
Keywords  |
Winter oilseed rape; Statistical models; Yield; Climate; Regression |
| Abstract |
Highlights • Regularization techniques for regression outperformed the classical regression techniques in predicting crop yields. • Different regression techniques with similar prediction accuracy showed different responses of major climatic variables to crop yield. • The regression models showed some responses of crop yield to climatic conditions that is mostly absent in process based crop models. Abstract Statistical regression models represent alternatives to process-based dynamic models for predicting the response of crop yields to variation in climatic conditions. Regression models can be used to quantify the effect of change in temperature and precipitation on yields. However, it is difficult to identify the most relevant input variables that should be included in regression models due to the high number of candidate variables and to their correlations. This paper compares several regression techniques for modeling response of winter oilseed rape yield to a high number of correlated input variables. Several statistical regression methods were fitted to a dataset including 689 observations of winter oilseed rape yield from replicated field experiments conducted in 239 sites in Denmark, covering nearly all regions of the country from 1992 to 2013. Regression methods were compared by cross-validation. The regression methods leading to the most accurate yield predictions were Lasso and Elastic Net, and the least accurate methods were ordinary least squares and stepwise regression. Partial least squares and ridge regression methods gave intermediate results. The estimated relative yield change for a +1°C temperature increase during flowering was estimated to range between 0 and +6 %, depending on choice of regression method. Precipitation was found to have an adverse effect on yield during autumn and winter. It was estimated that an increase in precipitation of +1 mm/day would result in a relative yield change ranging from 0 to −4 %. Soil type was also important for crop yields with lower yields on sandy soils compared to loamy soils. Later sowing was found to result in increased crop yield. The estimated effect of climate on yield was highly sensitive to the chosen regression method. Regression models showing similar performance led in some cases to different conclusions with respect to effect of temperature and precipitation. Hence, it is recommended to apply an ensemble of regression models, in order to account for the sensitivity of the data driven models for projecting crop yield under climate change. |
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1161-0301 |
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article |
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CropM, ft_macsur |
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no |
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MA @ admin @ |
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4966 |
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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. |
| Title |
Designing future barley ideotypes using a crop model ensemble |
Type |
Journal Article |
| Year |
2017 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
Europ. J. Agron. |
| Volume |
82 |
Issue |
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Pages |
144-162 |
| 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 |
| Abstract |
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 @ |
Serial |
4935 |
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| Author |
Schmid, E. |
| Title |
Integrated land use modelling — a course for doctoral students |
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Report |
| Year |
2017 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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10 |
Issue |
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Pages |
T4.1-4.2-XC4.3-4.4-D |
| Keywords |
TradeM |
| Abstract |
The course on “Integrated land use modelling” took place at BOKU Vienna between 24. – 28. April 2017. It was a five-days course capturing many aspects in quantitative integrated land use modelling using GAMS (see course outline). 10 students have participated the course coming from several countries. Students finishing the course have received 3 ECTS points. The course was offered by BOKU and the Doctoral Certificate Program in Agricultural Economics (https://www.agraroekonomik.de/index.html ). |
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MA @ admin @ |
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5036 |
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Malone, R.W.; Kersebaum, K.C.; Kaspar, T.C.; Ma, L.; Jaynes, D.B.; Gillette, K. |
| Title |
Winter rye as a cover crop reduces nitrate loss to subsurface drainage as simulated by HERMES |
Type |
Journal Article |
| Year |
2017 |
Publication |
Agricultural Water Management |
Abbreviated Journal |
Agric. Water Manage. |
| Volume |
184 |
Issue |
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Pages |
156-169 |
| Keywords |
Subsurface drainage, Cover crop, Nitrate loss, Modeling, Denitrification; NITROGEN DYNAMICS; TILE DRAINAGE; AGROECOSYSTEM MODELS; MISSISSIPPI; RIVER; GROWTH-MODEL; RZWQM-DSSAT; DRAINMOD-N; CATCH CROP; SOIL; WATER |
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HERMES is a widely used agricultural system model; however, it has never been tested for simulating N loss to subsurface drainage. Here, we integrated a simple drain flbw component into HERMES. We then compared the predictions to four years of data (2002-2005) from central Iowa fields in corn-oybean with winter rye as a cover crop (CC) and without winter rye (NCC). We also compared the HERMES predictions to the more complex Root Zone Water Quality Model (RZWQM) predictions for the same dataset. The average annual observed and simulated N loss to drain flow were 43.8 and 44.4 kg N/ha (NCC) and 17.6 and 18.9 kg N/ha (CC). The slightly over predicted N loss for CC was because of over predicted nitrate concentration, which may be partly caused by slightly under predicted average annual rye shoot N (observed and simulated values were 47.8 and 46.0 kg N/ha). Also, recent research from the site suggests that the soil field capacity may be greater in CC while we used the same soil parameters for both treatments. A local sensitivity analysis suggests that increased field capacity affects HERMES simulations, which includes reduced drain flow nitrate concentrations, increased denitrification, and reduced drain flow volume. HERMES-simulated cumulative monthly drain flow and annual drain flow were reasonable compared to field data and HERMES performance was comparable to other published drainage model tests. Unlike the RZWQM simulations, however, the modified HERMES did riot accurately simulate the year to year variability in nitrate concentration difference between NCC and CC, possibly due in part to the lack of partial mixing and displacement of the soil solution. The results suggest that 1) the relatively simple model HERMES is a promising tool to estimate annual N loss to drain flow under corn-soybean rotations with winter rye as a cover crop and 2) soil field capacity is a critical parameter to investigate to more thoroughly understand and appropriately model denitrification and N losses to subsurface drainage. Published by Elsevier B.V. |
| Address |
2017-04-28 |
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English |
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0378-3774 |
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CropM, ft_macsur |
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MA @ admin @ |
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4946 |
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Riahi, K.; van Vuuren, D.P.; Kriegler, E.; Edmonds, J.; O’Neill, B.C.; Fujimori, S.; Bauer, N.; Calvin, K.; Dellink, R.; Fricko, O.; Lutz, W.; Popp, A.; Cuaresma, J.C.; KC, S.; Leimbach, M.; Jiang, L.; Kram, T.; Rao, S.; Emmerling, J.; Ebi, K.; Hasegawa, T.; Havlik, P.; Humpenöder, F.; Da Silva, L.A.; Smith, S.; Stehfest, E.; Bosetti, V.; Eom, J.; Gernaat, D.; Masui, T.; Rogelj, J.; Strefler, J.; Drouet, L.; Krey, V.; Luderer, G.; Harmsen, M.; Takahashi, K.; Baumstark, L.; Doelman, J.C.; Kainuma, M.; Klimont, Z.; Marangoni, G.; Lotze-Campen, H.; Obersteiner, M.; Tabeau, A.; Tavoni, M. |
| Title |
The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview |
Type |
Journal Article |
| Year |
2017 |
Publication |
Global Environmental Change |
Abbreviated Journal |
Glob. Environ. Change |
| Volume |
42 |
Issue |
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Pages |
153-168 |
| Keywords |
Shared Socioeconomic Pathways; SSP; Climate change; RCP; Community scenarios; Mitigation; Adaptation |
| Abstract |
Abstract This paper presents the overview of the Shared Socioeconomic Pathways (SSPs) and their energy, land use, and emissions implications. The SSPs are part of a new scenario framework, established by the climate change research community in order to facilitate the integrated analysis of future climate impacts, vulnerabilities, adaptation, and mitigation. The pathways were developed over the last years as a joint community effort and describe plausible major global developments that together would lead in the future to different challenges for mitigation and adaptation to climate change. The SSPs are based on five narratives describing alternative socio-economic developments, including sustainable development, regional rivalry, inequality, fossil-fueled development, and middle-of-the-road development. The long-term demographic and economic projections of the SSPs depict a wide uncertainty range consistent with the scenario literature. A multi-model approach was used for the elaboration of the energy, land-use and the emissions trajectories of SSP-based scenarios. The baseline scenarios lead to global energy consumption of 400–1200 EJ in 2100, and feature vastly different land-use dynamics, ranging from a possible reduction in cropland area up to a massive expansion by more than 700 million hectares by 2100. The associated annual CO2 emissions of the baseline scenarios range from about 25 GtCO2 to more than 120 GtCO2 per year by 2100. With respect to mitigation, we find that associated costs strongly depend on three factors: (1) the policy assumptions, (2) the socio-economic narrative, and (3) the stringency of the target. The carbon price for reaching the target of 2.6 W/m2 that is consistent with a temperature change limit of 2 °C, differs in our analysis thus by about a factor of three across the SSP marker scenarios. Moreover, many models could not reach this target from the SSPs with high mitigation challenges. While the SSPs were designed to represent different mitigation and adaptation challenges, the resulting narratives and quantifications span a wide range of different futures broadly representative of the current literature. This allows their subsequent use and development in new assessments and research projects. Critical next steps for the community scenario process will, among others, involve regional and sectoral extensions, further elaboration of the adaptation and impacts dimension, as well as employing the SSP scenarios with the new generation of earth system models as part of the 6th climate model intercomparison project (CMIP6). |
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2017-06-13 |
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0959-3780 |
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TradeM, ftnotmacsur |
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no |
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MA @ admin @ |
Serial |
5008 |
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