Rötter, Reimund Paul

[["dc.contributor.author","Ewert, Frank"],["dc.contributor.author","Angulo, C."],["dc.contributor.author","Rumbaur, Christian"],["dc.contributor.author","Lock, R."],["dc.contributor.author","Enders, Andreas"],["dc.contributor.author","Adenäuer, Marcel"],["dc.contributor.author","Heckelei, Thomas"],["dc.contributor.author","Van Ittersum, Martin K."],["dc.contributor.author","Wolf, J."],["dc.contributor.author","Rötter, Reimund Paul"],["dc.date.accessioned","2018-05-21T11:23:04Z"],["dc.date.available","2018-05-21T11:23:04Z"],["dc.date.issued","2012"],["dc.description.abstract","The Netherlands are an important producer and exporter of agricultural products. Changes in climate, markets and policies may have a large impact on the agricultural sector and farmers will need to adapt to these changes. Sector and policy documents have, so far, insufficiently considered the impacts of climate change and increased climate variability on the sector."],["dc.format.extent","72"],["dc.identifier.isbn","978-90-8815-051-7"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/14691"],["dc.language.iso","en"],["dc.notes.status","zu prüfen"],["dc.publisher","Programme Office Climate changes Spatial Planning"],["dc.publisher.place","Nieuwegein"],["dc.relation","KvR 059/12"],["dc.title","Assessing the adaptive capacity of agriculture in The Netherlands to the impacts of climate change under different market and policy scenarios"],["dc.type","book"],["dc.type.internalPublication","no"],["dspace.entity.type","Publication"]]

[["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","519"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Agronomy for Sustainable Development"],["dc.bibliographiccitation.lastpage","530"],["dc.bibliographiccitation.volume","33"],["dc.contributor.author","Ketoja, Elise"],["dc.contributor.author","Himanen, Sari J."],["dc.contributor.author","Rötter, Reimund P."],["dc.contributor.author","Hakala, Kaija"],["dc.contributor.author","Kahiluoto, Helena"],["dc.contributor.author","Salo, Tapio"],["dc.date.accessioned","2018-05-19T13:05:00Z"],["dc.date.available","2018-05-19T13:05:00Z"],["dc.date.issued","2013"],["dc.description.abstract","This study shows an average yield increase of 415–1,338 kg ha−1 per unit increase of the Shannon diversity index for feed barley cultivar use. There is a global quest to increase food production sustainably. Therefore, judicious farmer choices such as selection of crop cultivars are increasingly important. Cultivar diversity is limited and, as a consequence, corresponding crop yields are highly impacted by local weather variations and global climate change. Actually, there is little knowledge on the relationships between yields of regional crops and cultivar diversity, that is evenness and richness in cultivar use. Here, we hypothesized that higher cultivar diversity is related to higher regional yield. We also assumed that the diversity-yield relationship depends on weather during the growing season. Our data were based on farm yield surveys of feed and malting barley, Hordeum vulgare L.; spring wheat, Triticum aestivum L.; and spring turnip rape, Brassica rapa L. ssp. oleifera, from 1998 to 2009, representing about 4,500–5,500 farms annually. We modeled the relationships between regional yields and Shannon diversity indices in high-yielding (south-west) and low-yielding (central-east) regions of Finland using linear mixed models. Our results show that an increase of Shannon diversity index increases yield of feed barley. Feed barley had also the greatest cultivar diversity. In contrast, an average yield decrease of 1,052 kg ha−1 per unit increase in Shannon index was found for spring rape in 2006 and 2008. Our findings show that cultivar diversification has potential to raise mean regional yield of feed barley. Increasing cultivar diversity thus offers a novel, sustainability-favoring means to promote higher yields."],["dc.identifier.doi","10.1007/s13593-012-0120-y"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/14674"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.title","Cultivar diversity has great potential to increase yield of feed barley"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","166"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Acta Agriculturae Scandinavica, Section A - Animal Science"],["dc.bibliographiccitation.lastpage","180"],["dc.bibliographiccitation.volume","62"],["dc.contributor.author","Rötter, R. P."],["dc.contributor.author","Höhn, J. G."],["dc.contributor.author","Fronzek, S."],["dc.date.accessioned","2018-05-19T14:55:50Z"],["dc.date.available","2018-05-19T14:55:50Z"],["dc.date.issued","2012"],["dc.description.abstract","Global climate is changing and food production is very sensitive to weather and climate variations. Global assessments of climate change impacts on food production have been made since the early 1990s, initially with little attention to the uncertainties involved. Although there has been abundant analysis of uncertainties in future greenhouse gas emissions and their impacts on the climate system, uncertainties related to the way climate change projections are scaled down as appropriate for different analyses and in modelling crop responses to climate change, have been neglected. This review paper mainly addresses uncertainties in crop impact modelling and possibilities to reduce them. We specifically aim to (i) show ranges of projected climate change-induced impacts on crop yields, (ii) give recommendations on use of emission scenarios, climate models, regionalization and ensemble crop model simulations for different purposes and (iii) discuss improvements and a few ‘known unknowns’ affecting crop impact projections."],["dc.identifier.doi","10.1080/09064702.2013.793735"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/14680"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.title","Projections of climate change impacts on crop production: A global and a Nordic perspective"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["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","841"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Agricultural Systems"],["dc.bibliographiccitation.lastpage","850"],["dc.bibliographiccitation.volume","94"],["dc.contributor.author","Van den Berg, Marrit M."],["dc.contributor.author","Hengsdijk, Huib"],["dc.contributor.author","Wolf, Joost"],["dc.contributor.author","Van Ittersum, Martin K."],["dc.contributor.author","Guanghuo, Wang"],["dc.contributor.author","Rötter, Reimund P."],["dc.date.accessioned","2018-06-14T13:12:45Z"],["dc.date.available","2018-06-14T13:12:45Z"],["dc.date.issued","2007"],["dc.description.abstract","Economic growth in China’s agricultural sector lags behind growth in industry and services, creating an ever widening rural–urban income gap. Development of the non-agricultural sectors offers new opportunities for farmers in China’s more advanced provinces such as Zhejiang. Increased income in the urban sector creates markets for new products, and migrating farmers rent their land to those staying. Until now, the prevailing rice-based systems have been managed mainly using manual labour and animal traction, but the larger farms resulting from migration may facilitate, or even require mechanization. In this study, we use a simulation model of the farm household to analyse the effects of increasing farm size and the transition from rice to vegetable production, while also studying the effects of mechanization. Our results show that at the present scale of farming, the dual government objectives of increasing rural incomes and increasing rice production are clearly conflicting. Farmers can generate incomes comparable to non-farm wages, but only when they switch completely to production of more remunerative crops, such as vegetables. At larger farm sizes, however, labour constraints inhibit farmers from specialization in non-rice crops, and rising per capita incomes and increasing rice production go hand in hand. Mechanization is necessary to allow substantial increases in farm size."],["dc.identifier.doi","10.1016/j.agsy.2006.11.010"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/15058"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.title","The impact of increasing farm size and mechanization on rural income and rice production in Zhejiang province, China"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","695"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Food Security"],["dc.bibliographiccitation.lastpage","717"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Savary, Serge"],["dc.contributor.author","Akter, Sonia"],["dc.contributor.author","Almekinders, Conny"],["dc.contributor.author","Harris, Jody"],["dc.contributor.author","Korsten, Lise"],["dc.contributor.author","Rötter, Reimund"],["dc.contributor.author","Waddington, Stephen"],["dc.contributor.author","Watson, Derrill"],["dc.date.accessioned","2021-04-14T08:24:39Z"],["dc.date.available","2021-04-14T08:24:39Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.1007/s12571-020-01093-0"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/81370"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.relation.eissn","1876-4525"],["dc.relation.issn","1876-4517"],["dc.title","Mapping disruption and resilience mechanisms in food systems"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","186"],["dc.bibliographiccitation.journal","Global Environmental Change"],["dc.bibliographiccitation.lastpage","193"],["dc.bibliographiccitation.volume","25"],["dc.contributor.author","Kahiluoto, Helena"],["dc.contributor.author","Kaseva, Janne"],["dc.contributor.author","Hakala, Kaija"],["dc.contributor.author","Himanen, Sari J."],["dc.contributor.author","Jauhiainen, Lauri"],["dc.contributor.author","Rötter, Reimund Paul"],["dc.contributor.author","Salo, Tapio"],["dc.contributor.author","Trnka, Mirek"],["dc.date.accessioned","2017-09-07T11:48:01Z"],["dc.date.available","2017-09-07T11:48:01Z"],["dc.date.issued","2014"],["dc.description.abstract","Intensified climate and market turbulence requires resilience to a multitude of changes. Diversity reduces the sensitivity to disturbance and fosters the capacity to adapt to various future scenarios. What really matters is diversity of responses. Despite appeals to manage resilience, conceptual developments have not yet yielded a break-through in empirical applications. Here, we present an approach to empirically reveal the ‘response diversity’: the factors of change that are critical to a system are identified, and the response diversity is determined based on the documented component responses to these factors. We illustrate this approach and its added value using an example of securing food supply in the face of climate variability and change. This example demonstrates that quantifying response diversity allows for a new perspective: despite continued increase in cultivar diversity of barley, the diversity in responses to weather declined during the last decade in the regions where most of the barley is grown in Finland. This was due to greater homogeneity in responses among new cultivars than among older ones. Such a decline in the response diversity indicates increased vulnerability and reduced resilience. The assessment serves adaptive management in the face of both ecological and socio-economic drivers. Supplier diversity in the food retail industry in order to secure affordable food in spite of global price volatility could represent another application. The approach is, indeed, applicable to any system for which it is possible to adopt empirical information regarding the response by its components to the critical factors of variability and change. Targeting diversification in response to critical change brings efficiency into diversity. We propose the generic procedure that is demonstrated in this study as a means to efficiently enhance resilience at multiple levels of agrifood systems and beyond."],["dc.identifier.doi","10.1016/j.gloenvcha.2014.02.002"],["dc.identifier.gro","3149441"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/6115"],["dc.language.iso","en"],["dc.notes.intern","Roetter Crossref Import"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","0959-3780"],["dc.title","Cultivating resilience by empirically revealing response diversity"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","273"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Global Change Biology"],["dc.bibliographiccitation.lastpage","286"],["dc.bibliographiccitation.volume","24"],["dc.contributor.author","Abdulai, Issaka"],["dc.contributor.author","Vaast, Philippe"],["dc.contributor.author","Hoffmann, Munir P."],["dc.contributor.author","Asare, Richard"],["dc.contributor.author","Jassogne, Laurence"],["dc.contributor.author","Van Asten, Piet"],["dc.contributor.author","Rötter, Reimund P."],["dc.contributor.author","Graefe, Sophie"],["dc.date.accessioned","2020-12-10T18:28:41Z"],["dc.date.available","2020-12-10T18:28:41Z"],["dc.date.issued","2017"],["dc.identifier.doi","10.1111/gcb.13885"],["dc.identifier.issn","1354-1013"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/76381"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","Cocoa agroforestry is less resilient to sub-optimal and extreme climate than cocoa in full sun"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.journal","BioEssays"],["dc.contributor.author","Wang, J."],["dc.contributor.author","Wang, G."],["dc.contributor.author","Wolf, J."],["dc.contributor.author","Hengsdijk, H."],["dc.contributor.author","Lu, Changhe"],["dc.contributor.author","Van den Berg, Marrit M."],["dc.contributor.author","van Keulen, Herman"],["dc.contributor.author","Rötter, Reimund P."],["dc.date.accessioned","2018-06-16T08:37:46Z"],["dc.date.available","2018-06-16T08:37:46Z"],["dc.date.issued","2005"],["dc.description.abstract","Both, poverty reduction and preservation of biodiversity are high on the global agenda on sustainable development. The relationships between poverty, biodiversity of ecosystems and agricultural development are complex and poorly understood. In this paper we present an integrated framework for analysis of agricultural development and natural resource management options at ecosystem level. We use Pujiang county, in Zhejiang province, China as a case study area to perform the analysis. A regional Linear Programming (LP) model is applied maximizing regional economic surplus given product and labour market conditions in Pujiang. We use the model to determine the consequences of four so-called poverty reduction strategies, i.e. (i) intensification of production, (ii) diversification towards livestock production, (iii) land expansion, and (iv) an exit from agriculture, for a set of regional poverty and biodiversity indicators. Diversification seems the most promising poverty reduction strategy, but requires an efficient use of animal manure in cropping systems to avoid environmental problems."],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/15073"],["dc.language.iso","en"],["dc.notes.status","zu prüfen"],["dc.title","Disentangling poverty and biodiversity in the context of rural development: A case study for Pujiang country, China"],["dc.type","journal_article"],["dc.type.internalPublication","unknown"],["dspace.entity.type","Publication"]]