Kersebaum, Kurt Christian

[["dc.bibliographiccitation.firstpage","87"],["dc.bibliographiccitation.journal","Climate Research"],["dc.bibliographiccitation.lastpage","105"],["dc.bibliographiccitation.volume","65"],["dc.contributor.author","Pirttioja, N."],["dc.contributor.author","Carter, T. R."],["dc.contributor.author","Fronzek, S."],["dc.contributor.author","Bindi, M."],["dc.contributor.author","Hoffmann, H."],["dc.contributor.author","Palosuo, T."],["dc.contributor.author","Ruiz-Ramos, M."],["dc.contributor.author","Tao, F."],["dc.contributor.author","Trnka, M."],["dc.contributor.author","Acutis, M."],["dc.contributor.author","Asseng, S."],["dc.contributor.author","Baranowski, P."],["dc.contributor.author","Basso, B."],["dc.contributor.author","Bodin, P."],["dc.contributor.author","Buis, S."],["dc.contributor.author","Cammarano, D."],["dc.contributor.author","Deligios, P."],["dc.contributor.author","Destain, M. F."],["dc.contributor.author","Dumont, B."],["dc.contributor.author","Ewert, F."],["dc.contributor.author","Ferrise, R."],["dc.contributor.author","François, L."],["dc.contributor.author","Gaiser, T."],["dc.contributor.author","Hlavinka, P."],["dc.contributor.author","Jacquemin, I."],["dc.contributor.author","Kersebaum, K. C."],["dc.contributor.author","Kollas, C."],["dc.contributor.author","Krzyszczak, J."],["dc.contributor.author","Lorite, I. J."],["dc.contributor.author","Minet, J."],["dc.contributor.author","Mínguez, M. I."],["dc.contributor.author","Montesino, M."],["dc.contributor.author","Moriondo, M."],["dc.contributor.author","Müller, C."],["dc.contributor.author","Nendel, C."],["dc.contributor.author","Öztürk, I."],["dc.contributor.author","Perego, A."],["dc.contributor.author","Rodríguez, A."],["dc.contributor.author","Ruane, A. C."],["dc.contributor.author","Ruget, F."],["dc.contributor.author","Sanna, M."],["dc.contributor.author","Semenov, M. A."],["dc.contributor.author","Slawinski, C."],["dc.contributor.author","Stratonovitch, P."],["dc.contributor.author","Supit, I."],["dc.contributor.author","Waha, K."],["dc.contributor.author","Wang, E."],["dc.contributor.author","Wu, L."],["dc.contributor.author","Zhao, Z."],["dc.contributor.author","Rötter, R. P."],["dc.date.accessioned","2017-09-07T11:47:54Z"],["dc.date.available","2017-09-07T11:47:54Z"],["dc.date.issued","2015"],["dc.description.abstract","This study explored the utility of the impact response surface (IRS) approach for investigating model ensemble crop yield responses under a large range of changes in climate. IRSs of spring and winter wheat Triticum aestivum yields were constructed from a 26-member ensemble of process-based crop simulation models for sites in Finland, Germany and Spain across a latitudinal transect. The sensitivity of modelled yield to systematic increments of changes in temperature (-2 to +9°C) and precipitation (-50 to +50%) was tested by modifying values of baseline (1981 to 2010) daily weather, with CO2 concentration fixed at 360 ppm. The IRS approach offers an effective method of portraying model behaviour under changing climate as well as advantages for analysing, comparing and presenting results from multi-model ensemble simulations. Though individual model behaviour occasionally departed markedly from the average, ensemble median responses across sites and crop varieties indicated that yields decline with higher temperatures and decreased precipitation and increase with higher precipitation. Across the uncertainty ranges defined for the IRSs, yields were more sensitive to temperature than precipitation changes at the Finnish site while sensitivities were mixed at the German and Spanish sites. Precipitation effects diminished under higher temperature changes. While the bivariate and multi-model characteristics of the analysis impose some limits to interpretation, the IRS approach nonetheless provides additional insights into sensitivities to inter-model and inter-annual variability. Taken together, these sensitivities may help to pinpoint processes such as heat stress, vernalisation or drought effects requiring refinement in future model development."],["dc.identifier.doi","10.3354/cr01322"],["dc.identifier.gro","3149390"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/6061"],["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","Temperature and precipitation effects on wheat yield across a European transect: a crop model ensemble analysis using impact response surfaces"],["dc.type","journal_article"],["dc.type.internalPublication","no"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","813"],["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","The Journal of Agricultural Science"],["dc.bibliographiccitation.lastpage","835"],["dc.bibliographiccitation.volume","151"],["dc.contributor.author","Eitzinger, J."],["dc.contributor.author","Thaler, S."],["dc.contributor.author","Schmid, E."],["dc.contributor.author","Strauss, F."],["dc.contributor.author","Ferrise, R."],["dc.contributor.author","Moriondo, M."],["dc.contributor.author","Bindi, M."],["dc.contributor.author","Palosuo, T."],["dc.contributor.author","Rötter, R. P."],["dc.contributor.author","Kersebaum, Kurt Christian"],["dc.contributor.author","Olesen, J. E."],["dc.contributor.author","Patil, R. H."],["dc.contributor.author","Şaylan, L."],["dc.contributor.author","Çaldağ, B."],["dc.contributor.author","Çaylak, O."],["dc.date.accessioned","2018-05-19T14:22:50Z"],["dc.date.available","2018-05-19T14:22:50Z"],["dc.date.issued","2013"],["dc.description.abstract","The objective of the present study was to compare the performance of seven different, widely applied crop models in predicting heat and drought stress effects. The study was part of a recent suite of model inter-comparisons initiated at European level and constitutes a component that has been lacking in the analysis of sources of uncertainties in crop models used to study the impacts of climate change. There was a specific focus on the sensitivity of models for winter wheat and maize to extreme weather conditions (heat and drought) during the short but critical period of 2 weeks after the start of flowering. Two locations in Austria, representing different agro-climatic zones and soil conditions, were included in the simulations over 2 years, 2003 and 2004, exhibiting contrasting weather conditions. In addition, soil management was modified at both sites by following either ploughing or minimum tillage. Since no comprehensive field experimental data sets were available, a relative comparison of simulated grain yields and soil moisture contents under defined weather scenarios with modified temperatures and precipitation was performed for a 2-week period after flowering. The results may help to reduce the uncertainty of simulated crop yields to extreme weather conditions through better understanding of the models’ behaviour. Although the crop models considered (DSSAT, EPIC, WOFOST, AQUACROP, FASSET, HERMES and CROPSYST) mostly showed similar trends in simulated grain yields for the different weather scenarios, it was obvious that heat and drought stress caused by changes in temperature and/or precipitation for a short period of 2 weeks resulted in different grain yields simulated by different models. The present study also revealed that the models responded differently to changes in soil tillage practices, which affected soil water storage capacity."],["dc.identifier.doi","10.1017/S0021859612000779"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/14678"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.title","Sensitivities of crop models to extreme weather conditions during flowering period demonstrated for maize and winter wheat in Austria"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","351"],["dc.bibliographiccitation.journal","Agricultural and Forest Meteorology"],["dc.bibliographiccitation.lastpage","362"],["dc.bibliographiccitation.volume","264"],["dc.contributor.author","Rodríguez, A."],["dc.contributor.author","Ruiz-Ramos, M."],["dc.contributor.author","Palosuo, T."],["dc.contributor.author","Carter, T.R."],["dc.contributor.author","Fronzek, S."],["dc.contributor.author","Lorite, I.J."],["dc.contributor.author","Ferrise, R."],["dc.contributor.author","Pirttioja, N."],["dc.contributor.author","Bindi, M."],["dc.contributor.author","Baranowski, P."],["dc.contributor.author","Buis, S."],["dc.contributor.author","Cammarano, D."],["dc.contributor.author","Chen, Y."],["dc.contributor.author","Dumont, B."],["dc.contributor.author","Ewert, F."],["dc.contributor.author","Gaiser, T."],["dc.contributor.author","Hlavinka, P."],["dc.contributor.author","Hoffmann, H."],["dc.contributor.author","Höhn, J.G."],["dc.contributor.author","Jurecka, F."],["dc.contributor.author","Kersebaum, K.C."],["dc.contributor.author","Krzyszczak, J."],["dc.contributor.author","Lana, M."],["dc.contributor.author","Mechiche-Alami, A."],["dc.contributor.author","Minet, J."],["dc.contributor.author","Montesino, M."],["dc.contributor.author","Nendel, C."],["dc.contributor.author","Porter, J.R."],["dc.contributor.author","Ruget, F."],["dc.contributor.author","Semenov, M.A."],["dc.contributor.author","Steinmetz, Z."],["dc.contributor.author","Stratonovitch, P."],["dc.contributor.author","Supit, I."],["dc.contributor.author","Tao, F."],["dc.contributor.author","Trnka, M."],["dc.contributor.author","de Wit, A."],["dc.contributor.author","Rötter, R.P."],["dc.date.accessioned","2019-07-09T11:49:54Z"],["dc.date.available","2019-07-09T11:49:54Z"],["dc.date.issued","2019"],["dc.description.abstract","Climate change is expected to severely affect cropping systems and food production in many parts of the world unless local adaptation can ameliorate these impacts. Ensembles of crop simulation models can be useful tools for assessing if proposed adaptation options are capable of achieving target yields, whilst also quantifying the share of uncertainty in the simulated crop impact resulting from the crop models themselves. Although some studies have analysed the influence of ensemble size on model outcomes, the effect of ensemble composition has not yet been properly appraised. Moreover, results and derived recommendations typically rely on averaged ensemble simulation results without accounting sufficiently for the spread of model outcomes. Therefore, we developed an Ensemble Outcome Agreement (EOA) index, which analyses the effect of changes in composition and size of a multi-model ensemble (MME) to evaluate the level of agreement between MME outcomes with respect to a given hypothesis (e.g. that adaptation measures result in positive crop responses). We analysed the recommendations of a previous study performed with an ensemble of 17 crop models and testing 54 adaptation options for rainfed winter wheat (Triticum aestivum L.) at Lleida (NE Spain) under perturbed conditions of temperature, precipitation and atmospheric CO2 concentration. Our results confirmed that most adaptations recommended in the previous study have a positive effect. However, we also showed that some options did not remain recommendable in specific conditions if different ensembles were considered. Using EOA, we were able to identify the adaptation options for which there is high confidence in their effectiveness at enhancing yields, even under severe climate perturbations. These include substituting spring wheat for winter wheat combined with earlier sowing dates and standard or longer duration cultivars, or introducing supplementary irrigation, the latter increasing EOA values in all cases. There is low confidence in recovering yields to baseline levels, although this target could be attained for some adaptation options under moderate climate perturbations. Recommendations derived from such robust results may provide crucial information for stakeholders seeking to implement adaptation measures."],["dc.identifier.doi","10.1016/j.agrformet.2018.09.018"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/15802"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/59652"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation","info:eu-repo/grantAgreement/EC/FP7/603416/EU//IMPRESSIONS"],["dc.rights","CC BY 4.0"],["dc.rights.uri","http://creativecommons.org/licenses/by/4.0/"],["dc.subject.ddc","630"],["dc.title","Implications of crop model ensemble size and composition for estimates of adaptation effects and agreement of recommendations"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]