Rötter, Reimund Paul

[["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.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","204"],["dc.bibliographiccitation.lastpage","215"],["dc.contributor.author","Rötter, Reimund P."],["dc.contributor.author","Kahiluoto, Helena"],["dc.contributor.author","Webber, Heidi"],["dc.contributor.author","Ewert, Frank"],["dc.contributor.editor","Fuhrer, Jürg"],["dc.contributor.editor","Gasic, Gregory P."],["dc.date.accessioned","2018-05-28T17:02:32Z"],["dc.date.available","2018-05-28T17:02:32Z"],["dc.date.issued","2014"],["dc.identifier.doi","10.1079/9781780642895.0204"],["dc.identifier.uri","http://hdl.handle.net/2/14793"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.publisher","CABI"],["dc.publisher.place","Wallingford, UK"],["dc.relation.doi","10.1079/9781780642895.0000"],["dc.relation.isbn","978-1-78064-289-5"],["dc.relation.ispartof","Climate change impact and adaptation in agricultural systems"],["dc.title","The role of modelling in adapting and building the climate resilience of cropping systems"],["dc.type","book_chapter"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

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[["dc.bibliographiccitation.firstpage","167"],["dc.bibliographiccitation.lastpage","185"],["dc.contributor.author","Rötter, Reimund P."],["dc.contributor.author","Kahiluoto, Helena"],["dc.contributor.author","Webber, Heidi"],["dc.contributor.author","Ewert, Frank"],["dc.contributor.editor","Fuhrer, Jürg"],["dc.contributor.editor","Gregory, Peter J."],["dc.date.accessioned","2018-05-28T16:53:18Z"],["dc.date.available","2018-05-28T16:53:18Z"],["dc.date.issued","2014"],["dc.identifier.doi","10.1079/9781780642895.0167"],["dc.identifier.uri","http://hdl.handle.net/2/14792"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.publisher","CABI"],["dc.publisher.place","Wallingford, UK"],["dc.relation.doi","10.1079/9781780642895.0000"],["dc.relation.isbn","978-1-78064-289-5"],["dc.relation.ispartof","Climate change impact and adaptation in agricultural systems"],["dc.title","Enhancing climate resilience of cropping systems"],["dc.type","book_chapter"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","532"],["dc.bibliographiccitation.issue","7"],["dc.bibliographiccitation.journal","Nature Food"],["dc.bibliographiccitation.lastpage","541"],["dc.bibliographiccitation.volume","3"],["dc.contributor.author","Senapati, Nimai"],["dc.contributor.author","Semenov, Mikhail A."],["dc.contributor.author","Halford, Nigel G."],["dc.contributor.author","Hawkesford, Malcolm J."],["dc.contributor.author","Asseng, Senthold"],["dc.contributor.author","Cooper, Mark"],["dc.contributor.author","Ewert, Frank"],["dc.contributor.author","van Ittersum, Martin K."],["dc.contributor.author","Martre, Pierre"],["dc.contributor.author","Olesen, Jørgen E."],["dc.contributor.author","Webber, Heidi"],["dc.contributor.author","Roetter, Reimund P."],["dc.date.accessioned","2022-09-01T09:50:11Z"],["dc.date.available","2022-09-01T09:50:11Z"],["dc.date.issued","2022"],["dc.description.abstract","Global food security requires food production to be increased in the coming decades. The closure of any existing genetic yield gap (Yig) by genetic improvement could increase crop yield potential and global production. Here we estimated present global wheat Yig, covering all wheat-growing environments and major producers, by optimizing local wheat cultivars using the wheat model Sirius. The estimated mean global Yig was 51%, implying that global wheat production could benefit greatly from exploiting the untapped global Yig through the use of optimal cultivar designs, utilization of the vast variation available in wheat genetic resources, application of modern advanced breeding tools, and continuous improvements of crop and soil management."],["dc.identifier.doi","10.1038/s43016-022-00540-9"],["dc.identifier.pii","540"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/113640"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-597"],["dc.relation.eissn","2662-1355"],["dc.relation.orgunit","Abteilung Tropischer Pflanzenbau und Agrosystem Modellierung"],["dc.relation.orgunit","Zentrum für Biodiversität und Nachhaltige Landnutzung"],["dc.rights.uri","https://www.springer.com/tdm"],["dc.title","Global wheat production could benefit from closing the genetic yield gap"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

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