Siebert, Stefan

[["dc.bibliographiccitation.firstpage","141"],["dc.bibliographiccitation.journal","Climate Research"],["dc.bibliographiccitation.lastpage","157"],["dc.bibliographiccitation.volume","65"],["dc.contributor.author","Zhao, H.-G."],["dc.contributor.author","Hoffmann, Holger"],["dc.contributor.author","van Bussel, Lenny G. J."],["dc.contributor.author","Enders, Andreas"],["dc.contributor.author","Specka, Xenia"],["dc.contributor.author","Sosa, C."],["dc.contributor.author","Yeluripati, J."],["dc.contributor.author","Tao, Fulu"],["dc.contributor.author","Constantin, Julie"],["dc.contributor.author","Raynal, Helene"],["dc.contributor.author","Teixeira, Edmar"],["dc.contributor.author","Grosz, B."],["dc.contributor.author","Doro, Luca"],["dc.contributor.author","Zhao, Zhigan"],["dc.contributor.author","Nendel, Claas"],["dc.contributor.author","Kiese, Ralf"],["dc.contributor.author","Eckersten, Henrik"],["dc.contributor.author","Haas, Edwin"],["dc.contributor.author","Vanuytrecht, E."],["dc.contributor.author","Wang, Enli"],["dc.contributor.author","Kuhnert, Matthias"],["dc.contributor.author","Trombi, Giacomo"],["dc.contributor.author","Moriondo, Marco"],["dc.contributor.author","Bindi, Marco"],["dc.contributor.author","Lewan, Elisabet"],["dc.contributor.author","Bach, M."],["dc.contributor.author","Kersebaum, Kurt Christian"],["dc.contributor.author","Rötter, Reimund Paul"],["dc.contributor.author","Roggero, Pier Paolo"],["dc.contributor.author","Wallach, Daniel"],["dc.contributor.author","Cammarano, Davide"],["dc.contributor.author","Asseng, Senthold"],["dc.contributor.author","Krauss, G."],["dc.contributor.author","Siebert, Stefan"],["dc.contributor.author","Gaiser, Thomas"],["dc.contributor.author","Ewert, Frank"],["dc.date.accessioned","2017-09-07T11:47:54Z"],["dc.date.available","2017-09-07T11:47:54Z"],["dc.date.issued","2015"],["dc.description.abstract","We assessed the weather data aggregation effect (DAE) on the simulation of cropping systems for different crops, response variables, and production conditions. Using 13 process-based crop models and the ensemble mean, we simulated 30 yr continuous cropping systems for 2 crops (winter wheat and silage maize) under 3 production conditions for the state of North Rhine-Westphalia, Germany. The DAE was evaluated for 5 weather data resolutions (i.e. 1, 10, 25, 50, and 100 km) for 3 response variables including yield, growing season evapotranspiration, and water use efficiency. Five metrics, viz. the spatial bias (Δ), average absolute deviation (AAD), relative AAD, root mean squared error (RMSE), and relative RMSE, were used to evaluate the DAE on both the input weather data and simulated results. For weather data, we found that data aggregation narrowed the spatial variability but widened the Δ, especially across mountainous areas. The DAE on loss of spatial heterogeneity and hotspots was stronger than on the average changes over the region. The DAE increased when coarsening the spatial resolution of the input weather data. The DAE varied considerably across different models, but changed only slightly for different production conditions and crops. We conclude that if spatially detailed information is essential for local management decision, higher resolution is desirable to adequately capture the spatial variability for heterogeneous regions. The required resolution depends on the choice of the model as well as the environmental condition of the study area."],["dc.identifier.doi","10.3354/cr01301"],["dc.identifier.gro","3149393"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/6064"],["dc.language.iso","en"],["dc.notes.intern","Roetter Crossref Import"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","0936-577X"],["dc.title","Effect of weather data aggregation on regional crop simulation for different crops, production conditions, and response variables"],["dc.type","journal_article"],["dc.type.internalPublication","no"],["dc.type.peerReviewed","no"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","014003"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Environmental Research Letters"],["dc.bibliographiccitation.volume","16"],["dc.contributor.affiliation","Ahrends, Hella Ellen;"],["dc.contributor.affiliation","Siebert, Stefan;"],["dc.contributor.affiliation","Rezaei, Ehsan Eyshi;"],["dc.contributor.affiliation","Seidel, Sabine Julia;"],["dc.contributor.affiliation","Hüging, Hubert;"],["dc.contributor.affiliation","Ewert, Frank;"],["dc.contributor.affiliation","Döring, Thomas;"],["dc.contributor.affiliation","Rueda-Ayala, Victor;"],["dc.contributor.affiliation","Eugster, Werner;"],["dc.contributor.affiliation","Gaiser, Thomas;"],["dc.contributor.author","Ahrends, Hella Ellen"],["dc.contributor.author","Siebert, Stefan"],["dc.contributor.author","Rezaei, Ehsan Eyshi"],["dc.contributor.author","Seidel, Sabine Julia"],["dc.contributor.author","Hüging, Hubert"],["dc.contributor.author","Ewert, Frank"],["dc.contributor.author","Döring, Thomas"],["dc.contributor.author","Rueda-Ayala, Victor"],["dc.contributor.author","Eugster, Werner"],["dc.contributor.author","Gaiser, Thomas"],["dc.date.accessioned","2021-04-14T08:30:10Z"],["dc.date.available","2021-04-14T08:30:10Z"],["dc.date.issued","2021"],["dc.date.updated","2022-02-09T13:18:57Z"],["dc.description.abstract","Yield stability is important for food security and a sustainable crop production, especially under changing climatic conditions. It is well known that the variability of yields is linked to changes in meteorological conditions. However, little is known about the long-term effects of agronomic management strategies, such as the supply of important nutrients. We analysed the stability of four major European crops grown between 1955 and 2008 at a long-term fertilization experiment located in Germany. Six fertilizer treatments ranged from no fertilization over the omission of individual macronutrients to complete mineral fertilization with all major macronutrients (nitrogen, phosphorus, potassium and calcium). Yield stability was estimated for each crop × treatment combination using the relative yield deviation in each year from the corresponding (nonlinear) trend value (relative yield anomalies (RYA)). Stability was lowest for potato, followed by sugar beet and winter wheat and highest for winter rye. Stability was highest when soils had received all nutrients with the standard deviation of RYA being two to three times lower than for unfertilized plots. The omission of nitrogen and potassium was associated with a decrease in yield stability and a decrease in the number of simultaneous positive and negative yield anomalies among treatments. Especially in root crops nutrient supply strongly influenced both annual yield anomalies and changes in anomalies over time. During the second half of the observation period yield stability decreased for sugar beet and increased for winter wheat. Potato yields were more stable during the second period, but only under complete nutrient supply. The critical role of potassium supply for yield stability suggests potential links to changes in the water balance during the last decades. Results demonstrate the need to explicitly consider the response of crops to long-term nutrient supply for understanding and predicting changes in yield stability."],["dc.identifier.doi","10.1088/1748-9326/abc849"],["dc.identifier.eissn","1748-9326"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/83134"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.publisher","IOP Publishing"],["dc.relation.eissn","1748-9326"],["dc.relation.orgunit","Department für Nutzpflanzenwissenschaften"],["dc.relation.orgunit","Abteilung Pflanzenbau"],["dc.relation.orgunit","Fakultät für Agrarwissenschaften"],["dc.rights.uri","http://creativecommons.org/licenses/by/4.0"],["dc.title","Nutrient supply affects the yield stability of major European crops—a 50 year study"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","53"],["dc.bibliographiccitation.journal","Climate Research"],["dc.bibliographiccitation.lastpage","69"],["dc.bibliographiccitation.volume","65"],["dc.contributor.author","Hoffmann, Holger"],["dc.contributor.author","Zhao, G."],["dc.contributor.author","van Bussel, Lenny G. J."],["dc.contributor.author","Enders, Andreas"],["dc.contributor.author","Specka, Xenia"],["dc.contributor.author","Sosa, C."],["dc.contributor.author","Yeluripati, J."],["dc.contributor.author","Tao, Fulu"],["dc.contributor.author","Constantin, Julie"],["dc.contributor.author","Raynal, Helene"],["dc.contributor.author","Teixeira, Edmar"],["dc.contributor.author","Grosz, B."],["dc.contributor.author","Doro, Luca"],["dc.contributor.author","Zhao, Zhigan"],["dc.contributor.author","Wang, Enli"],["dc.contributor.author","Nendel, Claas"],["dc.contributor.author","Kersebaum, Kurt Christian"],["dc.contributor.author","Haas, Edwin"],["dc.contributor.author","Kiese, Ralf"],["dc.contributor.author","Klatt, S."],["dc.contributor.author","Eckersten, Henrik"],["dc.contributor.author","Vanuytrecht, E."],["dc.contributor.author","Kuhnert, Matthias"],["dc.contributor.author","Lewan, Elisabet"],["dc.contributor.author","Rötter, Reimund Paul"],["dc.contributor.author","Roggero, Pier Paolo"],["dc.contributor.author","Wallach, Daniel"],["dc.contributor.author","Cammarano, Davide"],["dc.contributor.author","Asseng, Senthold"],["dc.contributor.author","Krauss, G."],["dc.contributor.author","Siebert, Stefan"],["dc.contributor.author","Gaiser, Thomas"],["dc.contributor.author","Ewert, Frank"],["dc.date.accessioned","2017-09-07T11:47:53Z"],["dc.date.available","2017-09-07T11:47:53Z"],["dc.date.issued","2015"],["dc.description.abstract","Field-scale crop models are often applied at spatial resolutions coarser than that of the arable field. However, little is known about the response of the models to spatially aggregated climate input data and why these responses can differ across models. Depending on the model, regional yield estimates from large-scale simulations may be biased, compared to simulations with high-resolution input data. We evaluated this so-called aggregation effect for 13 crop models for the region of North Rhine-Westphalia in Germany. The models were supplied with climate data of 1 km resolution and spatial aggregates of up to 100 km resolution raster. The models were used with 2 crops (winter wheat and silage maize) and 3 production situations (potential, water-limited and nitrogen-water-limited growth) to improve the understanding of errors in model simulations related to data aggregation and possible interactions with the model structure. The most important climate variables identified in determining the model-specific input data aggregation on simulated yields were mainly related to changes in radiation (wheat) and temperature (maize). Additionally, aggregation effects were systematic, regardless of the extent of the effect. Climate input data aggregation changed the mean simulated regional yield by up to 0.2 t ha-1, whereas simulated yields from single years and models differed considerably, depending on the data aggregation. This implies that large-scale crop yield simulations are robust against climate data aggregation. However, large-scale simulations can be systematically biased when being evaluated at higher temporal or spatial resolution depending on the model and its parameterization."],["dc.identifier.doi","10.3354/cr01326"],["dc.identifier.gro","3149398"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/6070"],["dc.language.iso","en"],["dc.notes.intern","Roetter Crossref Import"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","0936-577X"],["dc.title","Variability of effects of spatial climate data aggregation on regional yield simulation by crop models"],["dc.type","journal_article"],["dc.type.internalPublication","no"],["dc.type.peerReviewed","no"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","361"],["dc.bibliographiccitation.journal","Environmental Modelling & Software"],["dc.bibliographiccitation.lastpage","377"],["dc.bibliographiccitation.volume","96"],["dc.contributor.author","Grosz, Balázs"],["dc.contributor.author","Gebbert, Sören"],["dc.contributor.author","Dechow, Rene"],["dc.contributor.author","Zhao, Gang"],["dc.contributor.author","Hoffmann, Holger"],["dc.contributor.author","Constantin, Julie"],["dc.contributor.author","Raynal, Helene"],["dc.contributor.author","Wallach, Daniel"],["dc.contributor.author","Coucheney, Elsa"],["dc.contributor.author","Lewan, Elisabet"],["dc.contributor.author","Eckersten, Henrik"],["dc.contributor.author","Specka, Xenia"],["dc.contributor.author","Kersebaum, Kurt-Christian"],["dc.contributor.author","Nendel, Claas"],["dc.contributor.author","Kuhnert, Matthias"],["dc.contributor.author","Yeluripati, Jagadeesh"],["dc.contributor.author","Haas, Edwin"],["dc.contributor.author","Teixeira, Edmar"],["dc.contributor.author","Bindi, Marco"],["dc.contributor.author","Trombi, Giacomo"],["dc.contributor.author","Moriondo, Marco"],["dc.contributor.author","Doro, Luca"],["dc.contributor.author","Roggero, Pier Paolo"],["dc.contributor.author","Zhao, Zhigan"],["dc.contributor.author","Wang, Enli"],["dc.contributor.author","Tao, Fulu"],["dc.contributor.author","Rötter, Reimund P."],["dc.contributor.author","Kassie, Belay"],["dc.contributor.author","Cammarano, Davide"],["dc.contributor.author","Asseng, Senthold"],["dc.contributor.author","Weihermüller, Lutz"],["dc.contributor.author","Siebert, Stefan"],["dc.contributor.author","Gaiser, Thomas"],["dc.contributor.author","Ewert, Frank"],["dc.date.accessioned","2018-02-12T10:49:55Z"],["dc.date.available","2018-02-12T10:49:55Z"],["dc.date.issued","2017"],["dc.description.abstract","In up-scaling studies, model input data aggregation is a common method to cope with deficient data availability and limit the computational effort. We analyzed model errors due to soil data aggregation for modeled SOC trends. For a region in North West Germany, gridded soil data of spatial resolutions between 1 km and 100 km has been derived by majority selection. This data was used to simulate changes in SOC for a period of 30 years by 7 biogeochemical models. Soil data aggregation strongly affected modeled SOC trends. Prediction errors of simulated SOC changes decreased with increasing spatial resolution of model output. Output data aggregation only marginally reduced differences of model outputs between models indicating that errors caused by deficient model structure are likely to persist even if requirements on the spatial resolution of model outputs are low."],["dc.identifier.doi","10.1016/j.envsoft.2017.06.046"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/12153"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.relation.orgunit","Department für Nutzpflanzenwissenschaften"],["dc.relation.orgunit","Fakultät für Agrarwissenschaften"],["dc.relation.orgunit","Abteilung Pflanzenbau"],["dc.title","The implication of input data aggregation on up-scaling soil organic carbon changes"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","12"],["dc.bibliographiccitation.journal","Environmental Research Letters"],["dc.bibliographiccitation.volume","17"],["dc.contributor.affiliation","Guarin, Jose Rafael;"],["dc.contributor.affiliation","Martre, Pierre;"],["dc.contributor.affiliation","Ewert, Frank;"],["dc.contributor.affiliation","Webber, Heidi;"],["dc.contributor.affiliation","Dueri, Sibylle;"],["dc.contributor.affiliation","Calderini, Daniel;"],["dc.contributor.affiliation","Reynolds, Matthew;"],["dc.contributor.affiliation","Molero, Gemma;"],["dc.contributor.affiliation","Miralles, Daniel;"],["dc.contributor.affiliation","Garcia, Guillermo;"],["dc.contributor.affiliation","Slafer, Gustavo;"],["dc.contributor.affiliation","Giunta, Francesco;"],["dc.contributor.affiliation","Pequeno, Diego N L;"],["dc.contributor.affiliation","Stella, Tommaso;"],["dc.contributor.affiliation","Ahmed, Mukhtar;"],["dc.contributor.affiliation","Alderman, Phillip D;"],["dc.contributor.affiliation","Basso, Bruno;"],["dc.contributor.affiliation","Berger, Andres G;"],["dc.contributor.affiliation","Bindi, Marco;"],["dc.contributor.affiliation","Bracho-Mujica, Gennady;"],["dc.contributor.affiliation","Cammarano, Davide;"],["dc.contributor.affiliation","Chen, Yi;"],["dc.contributor.affiliation","Dumont, Benjamin;"],["dc.contributor.affiliation","Rezaei, Ehsan Eyshi;"],["dc.contributor.affiliation","Fereres, Elias;"],["dc.contributor.affiliation","Ferrise, Roberto;"],["dc.contributor.affiliation","Gaiser, Thomas;"],["dc.contributor.affiliation","Gao, Yujing;"],["dc.contributor.affiliation","Garcia-Vila, Margarita;"],["dc.contributor.affiliation","Gayler, Sebastian;"],["dc.contributor.affiliation","Hochman, Zvi;"],["dc.contributor.affiliation","Hoogenboom, Gerrit;"],["dc.contributor.affiliation","Hunt, Leslie A;"],["dc.contributor.affiliation","Kersebaum, Kurt C;"],["dc.contributor.affiliation","Nendel, Claas;"],["dc.contributor.affiliation","Olesen, Jørgen E;"],["dc.contributor.affiliation","Palosuo, Taru;"],["dc.contributor.affiliation","Priesack, Eckart;"],["dc.contributor.affiliation","Pullens, Johannes W M;"],["dc.contributor.affiliation","Rodríguez, Alfredo;"],["dc.contributor.affiliation","Rötter, Reimund P;"],["dc.contributor.affiliation","Ramos, Margarita Ruiz;"],["dc.contributor.affiliation","Semenov, Mikhail A;"],["dc.contributor.affiliation","Senapati, Nimai;"],["dc.contributor.affiliation","Siebert, Stefan;"],["dc.contributor.affiliation","Srivastava, Amit Kumar;"],["dc.contributor.affiliation","Stöckle, Claudio;"],["dc.contributor.affiliation","Supit, Iwan;"],["dc.contributor.affiliation","Tao, Fulu;"],["dc.contributor.affiliation","Thorburn, Peter;"],["dc.contributor.affiliation","Wang, Enli;"],["dc.contributor.affiliation","Weber, Tobias Karl David;"],["dc.contributor.affiliation","Xiao, Liujun;"],["dc.contributor.affiliation","Zhang, Zhao;"],["dc.contributor.affiliation","Zhao, Chuang;"],["dc.contributor.affiliation","Zhao, Jin;"],["dc.contributor.affiliation","Zhao, Zhigan;"],["dc.contributor.affiliation","Zhu, Yan;"],["dc.contributor.affiliation","Asseng, Senthold;"],["dc.contributor.author","Guarin, Jose Rafael"],["dc.contributor.author","Martre, Pierre"],["dc.contributor.author","Ewert, Frank"],["dc.contributor.author","Webber, Heidi"],["dc.contributor.author","Dueri, Sibylle"],["dc.contributor.author","Calderini, Daniel"],["dc.contributor.author","Reynolds, Matthew"],["dc.contributor.author","Molero, Gemma"],["dc.contributor.author","Miralles, Daniel"],["dc.contributor.author","Garcia, Guillermo"],["dc.contributor.author","Slafer, Gustavo"],["dc.contributor.author","Giunta, Francesco"],["dc.contributor.author","Pequeno, Diego N. L."],["dc.contributor.author","Stella, Tommaso"],["dc.contributor.author","Ahmed, Mukhtar"],["dc.contributor.author","Alderman, Phillip D."],["dc.contributor.author","Basso, Bruno"],["dc.contributor.author","Berger, Andres G."],["dc.contributor.author","Bindi, Marco"],["dc.contributor.author","Bracho-Mujica, Gennady"],["dc.contributor.author","Cammarano, Davide"],["dc.contributor.author","Chen, Yi"],["dc.contributor.author","Dumont, Benjamin"],["dc.contributor.author","Rezaei, Ehsan Eyshi"],["dc.contributor.author","Fereres, Elias"],["dc.contributor.author","Ferrise, Roberto"],["dc.contributor.author","Gaiser, Thomas"],["dc.contributor.author","Gao, Yujing"],["dc.contributor.author","Garcia-Vila, Margarita"],["dc.contributor.author","Gayler, Sebastian"],["dc.contributor.author","Hochman, Zvi"],["dc.contributor.author","Hoogenboom, Gerrit"],["dc.contributor.author","Hunt, Leslie A."],["dc.contributor.author","Kersebaum, Kurt C."],["dc.contributor.author","Nendel, Claas"],["dc.contributor.author","Olesen, Jørgen E."],["dc.contributor.author","Palosuo, Taru"],["dc.contributor.author","Priesack, Eckart"],["dc.contributor.author","Pullens, Johannes W. M."],["dc.contributor.author","Rodríguez, Alfredo"],["dc.contributor.author","Rötter, Reimund P."],["dc.contributor.author","Ramos, Margarita Ruiz"],["dc.contributor.author","Semenov, Mikhail A."],["dc.contributor.author","Senapati, Nimai"],["dc.contributor.author","Siebert, Stefan"],["dc.contributor.author","Srivastava, Amit Kumar"],["dc.contributor.author","Stöckle, Claudio"],["dc.contributor.author","Supit, Iwan"],["dc.contributor.author","Tao, Fulu"],["dc.contributor.author","Thorburn, Peter"],["dc.contributor.author","Wang, Enli"],["dc.contributor.author","Weber, Tobias Karl David"],["dc.contributor.author","Xiao, Liujun"],["dc.contributor.author","Zhang, Zhao"],["dc.contributor.author","Zhao, Chuang"],["dc.contributor.author","Zhao, Jin"],["dc.contributor.author","Zhao, Zhigan"],["dc.contributor.author","Zhu, Yan"],["dc.contributor.author","Asseng, Senthold"],["dc.date.accessioned","2022-12-14T07:22:09Z"],["dc.date.available","2022-12-14T07:22:09Z"],["dc.date.issued","2022-12-12"],["dc.date.updated","2022-12-14T05:58:37Z"],["dc.description.abstract","AbstractWheat is the most widely grown food crop, with 761 Mt produced globally in 2020. To meet the expected grain demand by mid-century, wheat breeding strategies must continue to improve upon yield-advancing physiological traits, regardless of climate change impacts. Here, the best performing doubled haploid (DH) crosses with an increased canopy photosynthesis from wheat field experiments in the literature were extrapolated to the global scale with a multi-model ensemble of process-based wheat crop models to estimate global wheat production. The DH field experiments were also used to determine a quantitative relationship between wheat production and solar radiation to estimate genetic yield potential. The multi-model ensemble projected a global annual wheat production of 1050 ± 145 Mt due to the improved canopy photosynthesis, a 37% increase, without expanding cropping area. Achieving this genetic yield potential would meet the lower estimate of the projected grain demand in 2050, albeit with considerable challenges."],["dc.description.sponsorship","Ministry of Education, Youth and Sports of Czech Republic SustES"],["dc.description.sponsorship","International Wheat Yield Partnership (IWYP)"],["dc.description.sponsorship","Biotechnology and Biological Sciences Research Council (BBSRC)"],["dc.description.sponsorship","National Natural Science Foundation of Chinahttp://dx.doi.org/10.13039/501100001809"],["dc.description.sponsorship","Chilean Technical and Scientific Research Council (CONICYT) FONDECYT Project"],["dc.description.sponsorship","International Maize and Wheat Improvement Center (CIMMYT)"],["dc.identifier.doi","10.1088/1748-9326/aca77c"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/118610"],["dc.language.iso","en"],["dc.relation.eissn","1748-9326"],["dc.rights","CC BY 4.0"],["dc.rights.uri","http://creativecommons.org/licenses/by/4.0"],["dc.title","Evidence for increasing global wheat yield potential"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","4079"],["dc.bibliographiccitation.issue","7"],["dc.bibliographiccitation.journal","Global Change Biology"],["dc.bibliographiccitation.lastpage","4093"],["dc.bibliographiccitation.volume","26"],["dc.contributor.author","Bourgault, Maryse"],["dc.contributor.author","Webber, Heidi A."],["dc.contributor.author","Chenu, Karine"],["dc.contributor.author","O’Leary, Garry J."],["dc.contributor.author","Gaiser, Thomas"],["dc.contributor.author","Siebert, Stefan"],["dc.contributor.author","Dreccer, Fernanda"],["dc.contributor.author","Huth, Neil"],["dc.contributor.author","Fitzgerald, Glenn J."],["dc.contributor.author","Tausz, Michael"],["dc.contributor.author","Ewert, Frank"],["dc.date.accessioned","2021-04-14T08:26:36Z"],["dc.date.available","2021-04-14T08:26:36Z"],["dc.date.issued","2020"],["dc.description.abstract","Early vigour in wheat is a trait that has received attention for its benefits reducing evaporation from the soil surface early in the season. However, with the growth enhancement common to crops grown under elevated atmospheric CO2 concentrations (e[CO2]), there is a risk that too much early growth might deplete soil water and lead to more severe terminal drought stress in environments where production relies on stored soil water content. If this is the case, the incorporation of such a trait in wheat breeding programmes might have unintended negative consequences in the future, especially in dry years. We used selected data from cultivars with proven expression of high and low early vigour from the Australian Grains Free Air CO2 Enrichment (AGFACE) facility, and complemented this analysis with simulation results from two crop growth models which differ in the modelling of leaf area development and crop water use. Grain yield responses to e[CO2] were lower in the high early vigour group compared to the low early vigour group, and although these differences were not significant, they were corroborated by simulation model results. However, the simulated lower response with high early vigour lines was not caused by an earlier or greater depletion of soil water under e[CO2] and the mechanisms responsible appear to be related to an earlier saturation of the radiation intercepted. Whether this is the case in the field needs to be further investigated. In addition, there was some evidence that the timing of the drought stress during crop growth influenced the effect of e[CO2] regardless of the early vigour trait. There is a need for FACE investigations of the value of traits for drought adaptation to be conducted under more severe drought conditions and variable timing of drought stress, a risky but necessary endeavour."],["dc.identifier.doi","10.1111/gcb.15128"],["dc.identifier.eissn","1365-2486"],["dc.identifier.issn","1354-1013"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/82008"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.relation.eissn","1365-2486"],["dc.relation.issn","1354-1013"],["dc.relation.orgunit","Department für Nutzpflanzenwissenschaften"],["dc.relation.orgunit","Fakultät für Agrarwissenschaften"],["dc.relation.orgunit","Abteilung Pflanzenbau"],["dc.title","Early vigour in wheat: Could it lead to more severe terminal drought stress under elevated atmospheric [CO 2 ] and semi‐arid conditions?"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","e0151782"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","PLOS ONE"],["dc.bibliographiccitation.volume","11"],["dc.contributor.author","Hoffmann, Holger"],["dc.contributor.author","Zhao, Gang"],["dc.contributor.author","Asseng, Senthold"],["dc.contributor.author","Bindi, Marco"],["dc.contributor.author","Biernath, Christian"],["dc.contributor.author","Constantin, Julie"],["dc.contributor.author","Coucheney, Elsa"],["dc.contributor.author","Dechow, Rene"],["dc.contributor.author","Doro, Luca"],["dc.contributor.author","Eckersten, Henrik"],["dc.contributor.author","Gaiser, Thomas"],["dc.contributor.author","Grosz, Balázs"],["dc.contributor.author","Heinlein, Florian"],["dc.contributor.author","Kassie, Belay T."],["dc.contributor.author","Kersebaum, Kurt Christian"],["dc.contributor.author","Klein, Christian"],["dc.contributor.author","Kuhnert, Matthias"],["dc.contributor.author","Lewan, Elisabet"],["dc.contributor.author","Moriondo, Marco"],["dc.contributor.author","Nendel, Claas"],["dc.contributor.author","Priesack, Eckart"],["dc.contributor.author","Raynal, Helene"],["dc.contributor.author","Roggero, Pier Paolo"],["dc.contributor.author","Rötter, Reimund Paul"],["dc.contributor.author","Siebert, Stefan"],["dc.contributor.author","Specka, Xenia"],["dc.contributor.author","Tao, Fulu"],["dc.contributor.author","Teixeira, Edmar"],["dc.contributor.author","Trombi, Giacomo"],["dc.contributor.author","Wallach, Daniel"],["dc.contributor.author","Weihermüller, Lutz"],["dc.contributor.author","Yeluripati, Jagadeesh"],["dc.contributor.author","Ewert, Frank"],["dc.date.accessioned","2017-09-07T11:47:53Z"],["dc.date.available","2017-09-07T11:47:53Z"],["dc.date.issued","2016"],["dc.description.abstract","We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations."],["dc.identifier.doi","10.1371/journal.pone.0151782"],["dc.identifier.gro","3149395"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/6067"],["dc.language.iso","en"],["dc.notes.intern","Roetter Crossref Import"],["dc.notes.status","public"],["dc.notes.submitter","chake"],["dc.relation.issn","1932-6203"],["dc.title","Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations"],["dc.type","journal_article"],["dc.type.internalPublication","no"],["dc.type.peerReviewed","no"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","100"],["dc.bibliographiccitation.journal","Environmental Modelling & Software"],["dc.bibliographiccitation.lastpage","112"],["dc.bibliographiccitation.volume","80"],["dc.contributor.author","Zhao, Gang"],["dc.contributor.author","Hoffmann, Holger"],["dc.contributor.author","Yeluripati, Jagadeesh"],["dc.contributor.author","Xenia, Specka"],["dc.contributor.author","Nendel, Claas"],["dc.contributor.author","Coucheney, Elsa"],["dc.contributor.author","Kuhnert, Matthias"],["dc.contributor.author","Tao, Fulu"],["dc.contributor.author","Constantin, Julie"],["dc.contributor.author","Raynal, Helene"],["dc.contributor.author","Teixeira, Edmar"],["dc.contributor.author","Grosz, Balázs"],["dc.contributor.author","Doro, Luca"],["dc.contributor.author","Kiese, Ralf"],["dc.contributor.author","Eckersten, Henrik"],["dc.contributor.author","Haas, Edwin"],["dc.contributor.author","Cammarano, Davide"],["dc.contributor.author","Kassie, Belay T."],["dc.contributor.author","Moriondo, Marco"],["dc.contributor.author","Trombi, Giacomo"],["dc.contributor.author","Bindi, Marco"],["dc.contributor.author","Biernath, Christian"],["dc.contributor.author","Heinlein, Florian"],["dc.contributor.author","Klein, Christian"],["dc.contributor.author","Priesack, Eckart"],["dc.contributor.author","Lewan, Elisabet"],["dc.contributor.author","Kersebaum, Kurt Christian"],["dc.contributor.author","Rötter, Reimund Paul"],["dc.contributor.author","Roggero, Pier Paolo"],["dc.contributor.author","Wallach, Daniel"],["dc.contributor.author","Asseng, Senthold"],["dc.contributor.author","Siebert, Stefan"],["dc.contributor.author","Gaiser, Thomas"],["dc.contributor.author","Ewert, Frank"],["dc.date.accessioned","2017-09-07T11:47:59Z"],["dc.date.available","2017-09-07T11:47:59Z"],["dc.date.issued","2016"],["dc.description.abstract","We compared the precision of simple random sampling (SimRS) and seven types of stratified random sampling (StrRS) schemes in estimating regional mean of water-limited yields for two crops (winter wheat and silage maize) that were simulated by fourteen crop models. We found that the precision gains of StrRS varied considerably across stratification methods and crop models. Precision gains for compact geographical stratification were positive, stable and consistent across crop models. Stratification with soil water holding capacity had very high precision gains for twelve models, but resulted in negative gains for two models. Increasing the sample size monotonously decreased the sampling errors for all the sampling schemes. We conclude that compact geographical stratification can modestly but consistently improve the precision in estimating regional mean yields. Using the most influential environmental variable for stratification can notably improve the sampling precision, especially when the sensitivity behavior of a crop model is known."],["dc.identifier.doi","10.1016/j.envsoft.2016.02.022"],["dc.identifier.gro","3149434"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/6108"],["dc.language.iso","en"],["dc.notes.intern","Roetter Crossref Import"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","1364-8152"],["dc.title","Evaluating the precision of eight spatial sampling schemes in estimating regional means of simulated yield for two crops"],["dc.type","journal_article"],["dc.type.internalPublication","no"],["dc.type.peerReviewed","no"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","n.n"],["dc.bibliographiccitation.lastpage","n.n"],["dc.contributor.author","Zhao, Gang"],["dc.contributor.author","Hoffmann, Holger"],["dc.contributor.author","Bussel, Lenny G. J. van"],["dc.contributor.author","Enders, Andreas"],["dc.contributor.author","Specka, Xenia"],["dc.contributor.author","Sosa, Carmen"],["dc.contributor.author","Yeluripati, Jagadeesh"],["dc.contributor.author","Tao, Fulu"],["dc.contributor.author","Constantin, Julie"],["dc.contributor.author","Teixeira, Edmar"],["dc.contributor.author","Grosz, Balázs"],["dc.contributor.author","Doro, Luca"],["dc.contributor.author","Zhao, Zhigan"],["dc.contributor.author","Nendel, Claas"],["dc.contributor.author","Kiese, Ralf"],["dc.contributor.author","Raynal, Helene"],["dc.contributor.author","Eckersten, Henrik"],["dc.contributor.author","Haas, Edwin"],["dc.contributor.author","Wang, Enli"],["dc.contributor.author","Kuhnert, Matthias"],["dc.contributor.author","Lewan, Elisabet"],["dc.contributor.author","Bach, Michaela"],["dc.contributor.author","Kersebaum, Kurt Christian"],["dc.contributor.author","Rötter, Reimund P."],["dc.contributor.author","Roggero, Pier Paolo"],["dc.contributor.author","Wallach, Daniel"],["dc.contributor.author","Krauss, Gunther"],["dc.contributor.author","Siebert, Stefan"],["dc.contributor.author","Gaiser, Thomas"],["dc.contributor.author","Ewert, Frank"],["dc.date.accessioned","2018-06-11T13:06:36Z"],["dc.date.available","2018-06-11T13:06:36Z"],["dc.date.issued","2014"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/15013"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.relation.conference","13th European Society for Agronomy Congress"],["dc.relation.eventend","2014-08-29"],["dc.relation.eventlocation","Debrecen, Hungary"],["dc.relation.eventstart","2014-08-25"],["dc.relation.ispartof","Proceedings, 13 th ESA Conference held on 29-31 August 2014 at Debrecen, Hungary"],["dc.title","Weather data aggregation’s effects on simulation of cropping systems"],["dc.title.subtitle","A model, production system and crop comparison"],["dc.type","conference_paper"],["dc.type.internalPublication","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","34"],["dc.bibliographiccitation.journal","European Journal of Agronomy"],["dc.bibliographiccitation.lastpage","46"],["dc.bibliographiccitation.volume","96"],["dc.contributor.author","Rueda-Ayala, Victor"],["dc.contributor.author","Ahrends, Hella Ellen"],["dc.contributor.author","Siebert, Stefan"],["dc.contributor.author","Gaiser, Thomas"],["dc.contributor.author","Hüging, Hubert"],["dc.contributor.author","Ewert, Frank"],["dc.date.accessioned","2020-12-10T14:23:38Z"],["dc.date.available","2020-12-10T14:23:38Z"],["dc.date.issued","2018"],["dc.description.abstract","Impacts of nutrient supply and different cultivars (genotypes) on actual yield levels have been studied before, but the long-term response of yield trends is hardly known. We present the effects of 24 different fertilizer treatments on long-term yield trends (1953–2009) of winter wheat, winter rye, sugar beet and potato, with improved cultivars changing gradually over time. Data was obtained from the crop rotation within the long-term fertilization experiment at Dikopshof, Germany. Yield trends were derived as the slope regression estimates between adjusted yield means and polynomials of the first year of cultivation of each tested cultivar, when tested for more than two years. A linear trend fitted best all data and crops. Yields in highly fertilized treatments increased linearly, exceeding 0.08 t ha−1 a−1 for both, winter wheat and winter rye, and ≥0.30 and ≥0.20 t ha−1 a−1 for sugar beet and potato fresh matter yields. Yield trends of winter cereals and sugar beet increased over time at N rates ≥40 kg ha−1 a−1, being 0.04–0.10 t ha−1 a−1 for cereals and 0.26–0.34 t ha−1 a−1 for sugar beet, although N rates >80 kg ha−1 a−1 produced a stronger effect. Nitrogen was the most influential nutrient for realisation of the genetic yield potential. Additional supply of P and K had an effect on yield trends for rye and sugar beet, when N fertilization was also sufficient; high K rates benefited potato yield trends. We highlight the importance of adequate nutrient supply for maintaining yield progress to actually achieve the crop genetic yield potentials. The explicit consideration of the interaction between crop fertilization and genetic progress on a long-term basis is critical for understanding past and projecting future yield trends. Long-term fertilization experiments provide a suitable data source for such studies."],["dc.identifier.doi","10.1016/j.eja.2018.03.002"],["dc.identifier.issn","1161-0301"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/71998"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.relation.orgunit","Department für Nutzpflanzenwissenschaften"],["dc.relation.orgunit","Fakultät für Agrarwissenschaften"],["dc.relation.orgunit","Abteilung Pflanzenbau"],["dc.title","Impact of nutrient supply on the expression of genetic improvements of cereals and row crops – A case study using data from a long-term fertilization experiment in Germany"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]