Rötter, Reimund Paul

[["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.firstpage","287"],["dc.bibliographiccitation.journal","Environmental Modelling & Software"],["dc.bibliographiccitation.lastpage","303"],["dc.bibliographiccitation.volume","72"],["dc.contributor.author","Ewert, Frank"],["dc.contributor.author","Rötter, Reimund Paul"],["dc.contributor.author","Bindi, Marco"],["dc.contributor.author","Webber, Heidi"],["dc.contributor.author","Trnka, Mirek"],["dc.contributor.author","Kersebaum, Kurt Christian"],["dc.contributor.author","Olesen, Jørgen E."],["dc.contributor.author","Van Ittersum, Martin K."],["dc.contributor.author","Janssen, S."],["dc.contributor.author","Rivington, M."],["dc.contributor.author","Semenov, Mikhail A."],["dc.contributor.author","Wallach, Daniel"],["dc.contributor.author","Porter, J.R."],["dc.contributor.author","Stewart, D."],["dc.contributor.author","Verhagen, J."],["dc.contributor.author","Gaiser, Thomas"],["dc.contributor.author","Palosuo, Taru"],["dc.contributor.author","Tao, Fulu"],["dc.contributor.author","Nendel, Claas"],["dc.contributor.author","Roggero, Pier Paolo"],["dc.contributor.author","Bartošová, L."],["dc.contributor.author","Asseng, Senthold"],["dc.date.accessioned","2017-09-07T11:47:54Z"],["dc.date.available","2017-09-07T11:47:54Z"],["dc.date.issued","2015"],["dc.description.abstract","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."],["dc.identifier.doi","10.1016/j.envsoft.2014.12.003"],["dc.identifier.gro","3149400"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/6072"],["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","Crop modelling for integrated assessment of risk to food production from climate change"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1"],["dc.bibliographiccitation.journal","Agricultural and Forest Meteorology"],["dc.bibliographiccitation.lastpage","14"],["dc.bibliographiccitation.volume","239"],["dc.contributor.author","Tao, Fulu"],["dc.contributor.author","Xiao, Dengpan"],["dc.contributor.author","Zhang, Shuai"],["dc.contributor.author","Zhang, Zhao"],["dc.contributor.author","Rötter, Reimund P."],["dc.date.accessioned","2017-09-07T11:47:58Z"],["dc.date.available","2017-09-07T11:47:58Z"],["dc.date.issued","2017"],["dc.description.abstract","Our understanding of climate impacts and adaptations on crop growth and productivity can be accelerated by analyzing historical data over the past few decades. We used crop trial and climate data from 1981 to 2009 at 34 national agro-meteorological stations in the Huang-Huai-Hai Plain (HHHP) of China to investigate the impacts of climate factors during different growth stages on the growth and yields of winter wheat, accounting for the adaptations such as shifts in sowing dates, cultivars, and agronomic management. Maximum (Tmax) and minimum temperature (Tmin) during the growth period of winter wheat increased significantly, by 0.4 and 0.6 °C/decade, respectively, from 1981 to 2009, while solar radiation decreased significantly by 0.2 MJ/m2/day and precipitation did not change significantly. The trends in climate shifted wheat phenology significantly at 21 stations and affected wheat yields significantly at five stations. The impacts of Tmax and Tmin differed in different growth stages of winter wheat. Across the stations, during 1981–2009, wheat yields increased on average by 14.5% with increasing trends in Tmin over the whole growth period, which reduced frost damage, however, decreased by 3.0% with the decreasing trends in solar radiation. Trends in Tmax and precipitation had comparatively smaller impacts on wheat yields. From 1981 to 2009, climate trends were associated with a ≤ 30% (or ≤1.0% per year) wheat yield increase at 23 stations in eastern and southern parts of HHHP; however with a ≤ 30% (or ≤1.0% per year) reduction at 11 other stations, mainly in western part of HHHP. We also found that wheat reproductive growth duration increased due to shifts in cultivars and flowering date, and the duration was significantly and positively correlated with wheat yield. This study highlights the different impacts of Tmax and Tmin in different growth stages of winter wheat, as well as the importance of management (e.g. shift of sowing date) and cultivars shift in adapting to climate change in the major wheat production region."],["dc.identifier.doi","10.1016/j.agrformet.2017.02.033"],["dc.identifier.gro","3149421"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/6095"],["dc.language.iso","en"],["dc.notes.intern","Roetter Crossref Import"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","0168-1923"],["dc.title","Wheat yield benefited from increases in minimum temperature in the Huang-Huai-Hai Plain of China in the past three decades"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","44"],["dc.bibliographiccitation.journal","European Journal of Agronomy"],["dc.bibliographiccitation.lastpage","52"],["dc.bibliographiccitation.volume","71"],["dc.contributor.author","Tao, Fulu"],["dc.contributor.author","Zhang, Zhao"],["dc.contributor.author","Zhang, Shuai"],["dc.contributor.author","Rötter, Reimund Paul"],["dc.date.accessioned","2017-09-07T11:48:00Z"],["dc.date.available","2017-09-07T11:48:00Z"],["dc.date.issued","2015"],["dc.description.abstract","Heat stress impacts on crop growth and yield have been investigated by controlled-environment experiments, however little is known about the impacts under field conditions at large spatial and temporal scales, particularly in a setting with farmers’ autonomous adaptations. Here, using detailed experiment observations at 34 national agricultural meteorological stations spanning from 1981 to 2009 in the Huang-Huai-Hai Plain (HHHP) of China, we investigated the changes in climate and heat stress during wheat reproductive growing period (from heading to maturity) and the impacts of climate change and heat stress on reproductive growing duration (RGD) and yield in a setting with farmers' autonomous adaptations. We found that RGD and growing degree days above 0 °C (GDD) from heading to maturity increased, which increased yield by ∼14.85%, although heat stress had negative impacts on RGD and yield. During 1981–2009, high temperature (>34 °C) degree days (HDD) increased in the northern part, however decreased in the middle and southern parts of HHHP due to advances in heading and maturity dates. Change in HDD, together with increase in GDD and decrease in solar radiation (SRD), jointly increased wheat yield in the northern and middle parts but reduced it in the southern part of HHHP. During the study period, increase in GDD and decrease in SRD had larger impacts on yield than change in HDD. However, with climate warming of 2 °C, damage of heat stress on yield may offset a large portion of the benefits from increases in RGD and GDD, and eventually result in net negative impacts on yield in the northern part of HHHP. Our study showed that shifts in cultivars and wheat production system dynamics in the past three decades reduced heat stress impacts in the HHHP. The insights into crop response and adaptation to climate change and climate extremes provide excellent evidences and basis for improving climate change impact study and designing adaptation measures for the future."],["dc.identifier.doi","10.1016/j.eja.2015.08.003"],["dc.identifier.gro","3149439"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/6113"],["dc.language.iso","en"],["dc.notes.intern","Roetter Crossref Import"],["dc.notes.status","public"],["dc.notes.submitter","chake"],["dc.relation.issn","1161-0301"],["dc.title","Heat stress impacts on wheat growth and yield were reduced in the Huang-Huai-Hai Plain of China in the past three decades"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","91"],["dc.bibliographiccitation.journal","Agricultural and Forest Meteorology"],["dc.bibliographiccitation.lastpage","104"],["dc.bibliographiccitation.volume","189-190"],["dc.contributor.author","Tao, Fulu"],["dc.contributor.author","Zhang, Zhao"],["dc.contributor.author","Xiao, Dengpan"],["dc.contributor.author","Zhang, Shuai"],["dc.contributor.author","Rötter, Reimund Paul"],["dc.contributor.author","Shi, Wenjiao"],["dc.contributor.author","Liu, Yujie"],["dc.contributor.author","Wang, Meng"],["dc.contributor.author","Liu, Fengshan"],["dc.contributor.author","Zhang, He"],["dc.date.accessioned","2017-09-07T11:48:00Z"],["dc.date.available","2017-09-07T11:48:00Z"],["dc.date.issued","2014"],["dc.description.abstract","The experiment observations at 120 agricultural meteorological stations spanning from 1981 to 2009 across China were used to accelerate understandings of the response of wheat growth and productivity to climate change in different climate zones, with panel regression models. We found climate during wheat growth period had changed significantly during 1981–2009, and the change had caused measurable impacts on wheat growth and yield in most of the zones. Wheat anthesis date and maturity date advanced significantly, and the lengths of growth period before anthesis and whole growth period were significantly shortened, however the length of reproductive growth period was significantly prolonged despite of the negative impacts of temperature increase. The increasing adoption of cultivars with longer reproductive growth period offset the negative impacts of climate change and increased yield. Changes in temperature, precipitation and solar radiation in the past three decades jointly increased wheat yield in northern China by 0.9–12.9%, however reduced wheat yield in southern China by 1.2–10.2%, with a large spatial difference. Our studies better represented crop system dynamics using detailed phenological records, consequently better accounted for adaptations such as shifts in sowing date and crop cultivars photo-thermal traits when quantifying climate impacts on wheat yield. Our findings suggest the response of wheat growth and yield to climate change is underway in China. The changes in crop system dynamics and cultivars traits have to be sufficiently taken into account to improve the prediction of climate impacts and to plan adaptations for future."],["dc.identifier.doi","10.1016/j.agrformet.2014.01.013"],["dc.identifier.gro","3149423"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/6097"],["dc.language.iso","en"],["dc.notes.intern","Roetter Crossref Import"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","0168-1923"],["dc.title","Responses of wheat growth and yield to climate change in different climate zones of China, 1981–2009"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","260"],["dc.bibliographiccitation.journal","Agricultural Systems"],["dc.bibliographiccitation.lastpage","274"],["dc.bibliographiccitation.volume","159"],["dc.contributor.author","Ruiz-Ramos, Margarita"],["dc.contributor.author","Ferrise, R."],["dc.contributor.author","Rodríguez, A."],["dc.contributor.author","Lorite, I. J."],["dc.contributor.author","Bindi, Marco"],["dc.contributor.author","Carter, T. R."],["dc.contributor.author","Fronzek, S."],["dc.contributor.author","Palosuo, Taru"],["dc.contributor.author","Pirttioja, N."],["dc.contributor.author","Baranowski, P."],["dc.contributor.author","Buis, S."],["dc.contributor.author","Cammarano, Davide"],["dc.contributor.author","Chen, Y."],["dc.contributor.author","Dumont, B."],["dc.contributor.author","Ewert, Frank"],["dc.contributor.author","Gaiser, Thomas"],["dc.contributor.author","Hlavinka, Petr"],["dc.contributor.author","Hoffmann, Holger"],["dc.contributor.author","Höhn, Jukka G."],["dc.contributor.author","Jurecka, F."],["dc.contributor.author","Kersebaum, Kurt Christian"],["dc.contributor.author","Krzyszczak, J."],["dc.contributor.author","Lana, Marcos"],["dc.contributor.author","Mechiche-Alami, A."],["dc.contributor.author","Minet, J."],["dc.contributor.author","Montesino, M."],["dc.contributor.author","Nendel, Claas"],["dc.contributor.author","Porter, J. R."],["dc.contributor.author","Ruget, F."],["dc.contributor.author","Semenov, Mikhail A."],["dc.contributor.author","Steinmetz, Z."],["dc.contributor.author","Stratonovitch, Pierre"],["dc.contributor.author","Sun, Jian"],["dc.contributor.author","Tao, Fulu"],["dc.contributor.author","Trnka, Mirek"],["dc.contributor.author","Wit, Allard de"],["dc.contributor.author","Rötter, Reimund P."],["dc.date.accessioned","2017-09-07T11:47:57Z"],["dc.date.available","2017-09-07T11:47:57Z"],["dc.date.issued","2018"],["dc.description.abstract","Adaptation of crops to climate change has to be addressed locally due to the variability of soil, climate and the specific socio-economic settings influencing farm management decisions. Adaptation of rainfed cropping systems in the Mediterranean is especially challenging due to the projected decline in precipitation in the coming decades, which will increase the risk of droughts. Methods that can help explore uncertainties in climate projections and crop modelling, such as impact response surfaces (IRSs) and ensemble modelling, can then be valuable for identifying effective adaptations. Here, an ensemble of 17 crop models was used to simulate a total of 54 adaptation options for rainfed winter wheat (Triticum aestivum) at Lleida (NE Spain). To support the ensemble building, an ex post quality check of model simulations based on several criteria was performed. Those criteria were based on the “According to Our Current Knowledge” (AOCK) concept, which has been formalized here. Adaptations were based on changes in cultivars and management regarding phenology, vernalization, sowing date and irrigation. The effects of adaptation options under changed precipitation (P), temperature (T), [CO2] and soil type were analysed by constructing response surfaces, which we termed, in accordance with their specific purpose, adaptation response surfaces (ARSs). These were created to assess the effect of adaptations through a range of plausible P, T and [CO2] perturbations. The results indicated that impacts of altered climate were predominantly negative. No single adaptation was capable of overcoming the detrimental effect of the complex interactions imposed by the P, T and [CO2] perturbations except for supplementary irrigation (sI), which reduced the potential impacts under most of the perturbations. Yet, a combination of adaptations for dealing with climate change demonstrated that effective adaptation is possible at Lleida. Combinations based on a cultivar without vernalization requirements showed good and wide adaptation potential. Few combined adaptation options performed well under rainfed conditions. However, a single sI was sufficient to develop a high adaptation potential, including options mainly based on spring wheat, current cycle duration and early sowing date. Depending on local environment (e.g. soil type), many of these adaptations can maintain current yield levels under moderate changes in T and P, and some also under strong changes. We conclude that ARSs can offer a useful tool for supporting planning of field level adaptation under conditions of high uncertainty."],["dc.identifier.doi","10.1016/j.agsy.2017.01.009"],["dc.identifier.gro","3149417"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/6091"],["dc.language.iso","en"],["dc.notes.intern","Roetter Crossref Import"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","chake"],["dc.relation.issn","0308-521X"],["dc.title","Adaptation response surfaces for managing wheat under perturbed climate and CO2 in a Mediterranean environment"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.journal","European Journal of Agronomy"],["dc.bibliographiccitation.volume","93"],["dc.contributor.author","Durand, Jean-Louis"],["dc.contributor.author","Delusca, Kenel"],["dc.contributor.author","Boote, Ken"],["dc.contributor.author","Lizaso, Jon"],["dc.contributor.author","Manderscheid, Remy"],["dc.contributor.author","Weigel, Hans-Joachim"],["dc.contributor.author","Ruane, Alex C."],["dc.contributor.author","Rosenzweig, Cynthia"],["dc.contributor.author","Jones, Jim"],["dc.contributor.author","Ahuja, Laj"],["dc.contributor.author","Anapalli, Saseendran"],["dc.contributor.author","Basso, Bruno"],["dc.contributor.author","Baron, Christian"],["dc.contributor.author","Bertuzzi, Patrick"],["dc.contributor.author","Biernath, Christian"],["dc.contributor.author","Deryng, Delphine"],["dc.contributor.author","Ewert, Frank"],["dc.contributor.author","Gaiser, Thomas"],["dc.contributor.author","Gayler, Sebastian"],["dc.contributor.author","Heinlein, Florian"],["dc.contributor.author","Kersebaum, Kurt Christian"],["dc.contributor.author","Kim, Soo-Hyung"],["dc.contributor.author","Müller, Christoph"],["dc.contributor.author","Nendel, Claas"],["dc.contributor.author","Olioso, Albert"],["dc.contributor.author","Priesack, Eckart"],["dc.contributor.author","Villegas, Julian Ramirez"],["dc.contributor.author","Ripoche, Dominique"],["dc.contributor.author","Rötter, Reimund Paul"],["dc.contributor.author","Seidel, Sabine I."],["dc.contributor.author","Srivastava, Amit"],["dc.contributor.author","Tao, Fulu"],["dc.contributor.author","Timlin, Dennis"],["dc.contributor.author","Twine, Tracy"],["dc.contributor.author","Wang, Enli"],["dc.contributor.author","Webber, Heidi"],["dc.contributor.author","Zhao, Zhigan"],["dc.date.accessioned","2017-09-07T11:47:54Z"],["dc.date.available","2017-09-07T11:47:54Z"],["dc.date.issued","2017"],["dc.description.abstract","This study assesses the ability of 21 crop models to capture the impact of elevated CO2 concentration ([CO2]) on maize yield and water use as measured in a 2-year Free Air Carbon dioxide Enrichment experiment conducted at the Thünen Institute in Braunschweig, Germany (Manderscheid et al., 2014). Data for ambient [CO2] and irrigated treatments were provided to the 21 models for calibrating plant traits, including weather, soil and management data as well as yield, grain number, above ground biomass, leaf area index, nitrogen concentration in biomass and grain, water use and soil water content. Models differed in their representation of carbon assimilation and evapotranspiration processes. The models reproduced the absence of yield response to elevated [CO2] under well-watered conditions, as well as the impact of water deficit at ambient [CO2], with 50% of models within a range of +/−1 Mg ha−1 around the mean. The bias of the median of the 21 models was less than 1 Mg ha−1. However under water deficit in one of the two years, the models captured only 30% of the exceptionally high [CO2] enhancement on yield observed. Furthermore the ensemble of models was unable to simulate the very low soil water content at anthesis and the increase of soil water and grain number brought about by the elevated [CO2] under dry conditions. Overall, we found models with explicit stomatal control on transpiration tended to perform better. Our results highlight the need for model improvement with respect to simulating transpirational water use and its impact on water status during the kernel-set phase."],["dc.identifier.doi","10.1016/j.eja.2017.01.002"],["dc.identifier.gro","3149399"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/6071"],["dc.language.iso","en"],["dc.notes.intern","Roetter Crossref Import"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","1161-0301"],["dc.title","How accurately do maize crop models simulate the interactions of atmospheric CO2 concentration levels with limited water supply on water use and yield?"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1291"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Global Change Biology"],["dc.bibliographiccitation.lastpage","1307"],["dc.bibliographiccitation.volume","24"],["dc.contributor.author","Tao, Fulu"],["dc.contributor.author","Rötter, Reimund P."],["dc.contributor.author","Palosuo, Taru"],["dc.contributor.author","Hernández Díaz-Ambrona, Carlos Gregorio"],["dc.contributor.author","Mínguez, M. Inés"],["dc.contributor.author","Semenov, Mikhail A."],["dc.contributor.author","Kersebaum, Kurt Christian"],["dc.contributor.author","Nendel, Claas"],["dc.contributor.author","Specka, Xenia"],["dc.contributor.author","Hoffmann, Holger"],["dc.contributor.author","Ewert, Frank"],["dc.contributor.author","Dambreville, Anaelle"],["dc.contributor.author","Martre, Pierre"],["dc.contributor.author","Rodríguez, Lucía"],["dc.contributor.author","Ruiz-Ramos, Margarita"],["dc.contributor.author","Gaiser, Thomas"],["dc.contributor.author","Höhn, Jukka G."],["dc.contributor.author","Salo, Tapio"],["dc.contributor.author","Ferrise, Roberto"],["dc.contributor.author","Bindi, Marco"],["dc.contributor.author","Cammarano, Davide"],["dc.contributor.author","Schulman, Alan H."],["dc.date.accessioned","2018-02-12T10:48:38Z"],["dc.date.available","2018-02-12T10:48:38Z"],["dc.date.issued","2018"],["dc.description.abstract","Climate change impact assessments are plagued with uncertainties from many sources, such as climate projections or the inadequacies in structure and parameters of the impact model. Previous studies tried to account for the uncertainty from one or two of these. Here, we developed a triple‐ensemble probabilistic assessment using seven crop models, multiple sets of model parameters and eight contrasting climate projections together to comprehensively account for uncertainties from these three important sources. We demonstrated the approach in assessing climate change impact on barley growth and yield at Jokioinen, Finland in the Boreal climatic zone and Lleida, Spain in the Mediterranean climatic zone, for the 2050s. We further quantified and compared the contribution of crop model structure, crop model parameters and climate projections to the total variance of ensemble output using Analysis of Variance (ANOVA). Based on the triple‐ensemble probabilistic assessment, the median of simulated yield change was −4% and +16%, and the probability of decreasing yield was 63% and 31% in the 2050s, at Jokioinen and Lleida, respectively, relative to 1981–2010. The contribution of crop model structure to the total variance of ensemble output was larger than that from downscaled climate projections and model parameters. The relative contribution of crop model parameters and downscaled climate projections to the total variance of ensemble output varied greatly among the seven crop models and between the two sites. The contribution of downscaled climate projections was on average larger than that of crop model parameters. This information on the uncertainty from different sources can be quite useful for model users to decide where to put the most effort when preparing or choosing models or parameters for impact analyses. We concluded that the triple‐ensemble probabilistic approach that accounts for the uncertainties from multiple important sources provide more comprehensive information for quantifying uncertainties in climate change impact assessments as compared to the conventional approaches that are deterministic or only account for the uncertainties from one or two of the uncertainty sources."],["dc.identifier.doi","10.1111/gcb.14019"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/12151"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.relation.doi","10.1111/gcb.14019"],["dc.title","Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","221"],["dc.bibliographiccitation.journal","Climate Research"],["dc.bibliographiccitation.lastpage","236"],["dc.bibliographiccitation.volume","65"],["dc.contributor.author","Palosuo, Taru"],["dc.contributor.author","Rötter, Reimund P."],["dc.contributor.author","Salo, Tapio"],["dc.contributor.author","Peltonen-Sainio, Pirjo"],["dc.contributor.author","Tao, Fulu"],["dc.contributor.author","Lehtonen, Heikki"],["dc.date.accessioned","2017-09-07T11:47:57Z"],["dc.date.available","2017-09-07T11:47:57Z"],["dc.date.issued","2015"],["dc.description.abstract","In this study, the WOFOST crop simulation model was used together with comprehensive empirical databases on barley Hordeum vulgare L. to study the contributions of different yield-determining and -limiting factors to observed trends of barley yield in Finland from 1988 to 2008. Simulations were performed at 3 study sites representing different agro-ecological zones, and compared with the data from experimental sites and that reported by local farmers. Yield gaps between simulated potential yields and farmers’ yields and their trends were assessed. Positive observed yield trends of Finnish barley mostly resulted from the development and usage of new, high-yielding cultivars. Simulated trends in climatic potential and water-limited potential yields of individual cultivars showed a slight declining trend. Yield gaps showed an increasing trend in 2 out of 3 study areas. Since the mid-1990s, a major reason for this has been the lack of market and policy incentives favouring crop management decisions, i.e. annual fertilisation, soil maintenance, drainage and crop rotation decisions, aiming for higher yields. The study indicates potential options for increasing or maintaining barley yields in the future. The breeding of new climate-resilient cultivars is the primary option. However, this needs to work alongside overall adjustments to farm management and must be supported by financial incentives for farmers to increase yields."],["dc.identifier.doi","10.3354/cr01317"],["dc.identifier.gro","3149415"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/6089"],["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","Effects of climate and historical adaptation measures on barley yield trends in Finland"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","18"],["dc.bibliographiccitation.lastpage","19"],["dc.contributor.author","Pirttioja, Nina"],["dc.contributor.author","Fronzek, Stefan"],["dc.contributor.author","Bindi, Marco"],["dc.contributor.author","Carter, Timothy R."],["dc.contributor.author","Hoffmann, Holger"],["dc.contributor.author","Palosuo, Taru"],["dc.contributor.author","Ruiz-Ramos, Margarita"],["dc.contributor.author","Trnka, Miroslav"],["dc.contributor.author","Acutis, Marco"],["dc.contributor.author","Asseng, Senthold"],["dc.contributor.author","Baranowski, Piotr"],["dc.contributor.author","Basso, Bruno"],["dc.contributor.author","Bodin, Per"],["dc.contributor.author","Buis, Samuel"],["dc.contributor.author","Cammarano, Davide"],["dc.contributor.author","Deligios, Paola"],["dc.contributor.author","Destain, Marie-France"],["dc.contributor.author","Doro, Luca"],["dc.contributor.author","Dumont, Benjamin"],["dc.contributor.author","Ewert, Frank"],["dc.contributor.author","Ferrise, Roberto"],["dc.contributor.author","François, Louis"],["dc.contributor.author","Gaiser, Thomas"],["dc.contributor.author","Hlavinka, Petr"],["dc.contributor.author","Kersebaum, Kurt Christian"],["dc.contributor.author","Kollas, Chris"],["dc.contributor.author","Krzyszczak, Jaromir"],["dc.contributor.author","Torres, Ignacio Lorite"],["dc.contributor.author","Minet, Julien"],["dc.contributor.author","Mínguez, M. Inés"],["dc.contributor.author","Montesino, Manuel"],["dc.contributor.author","Moriondo, Marco"],["dc.contributor.author","Nendel, Claas"],["dc.contributor.author","Öztürk, Isik"],["dc.contributor.author","Perego, Alessia"],["dc.contributor.author","Ruget, Françoise"],["dc.contributor.author","Rodríguez, Alfredo"],["dc.contributor.author","Sanna, Mattia"],["dc.contributor.author","Semenov, Mikhail A."],["dc.contributor.author","Slawinski, Cezary"],["dc.contributor.author","Stratonovitch, Pierre"],["dc.contributor.author","Supit, Iwan"],["dc.contributor.author","Tao, Fulu"],["dc.contributor.author","Wu, Lianhai"],["dc.contributor.author","Rötter, Reimund P."],["dc.date.accessioned","2018-06-11T14:02:07Z"],["dc.date.available","2018-06-11T14:02:07Z"],["dc.date.issued","2014"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/15015"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.relation.conference","FACCE MACSUR CropM International Symposium and Workshop \"Modelling climate change impacts on crop production for food security\""],["dc.relation.eventend","2014-02-12"],["dc.relation.eventlocation","Oslo"],["dc.relation.eventstart","2014-02-10"],["dc.relation.ispartof","Proceedings of the FACCE MACSUR CropM International Symposium and Workshop \"Modelling climate change impacts on crop production for food security\""],["dc.title","Examining wheat yield sensitivity to temperature and precipitation changes for a large ensemble of crop models using impact response surfaces"],["dc.type","conference_paper"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]