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Hoffmann, H.; Zhao, G.; Asseng, S.; Bindi, M.; Biernath, C.; Constantin, J.; Coucheney, E.; Dechow, R.; Doro, L.; Eckersten, H.; Gaiser, T.; Grosz, B.; Heinlein, F.; Kassie, B.T.; Kersebaum, K.-C.; Klein, C.; Kuhnert, M.; Lewan, E.; Moriondo, M.; Nendel, C.; Priesack, E.; Raynal, H.; Roggero, P.P.; Rötter, R.P.; Siebert, S.; Specka, X.; Tao, F.; Teixeira, E.; Trombi, G.; Wallach, D.; Weihermüller, L.; Yeluripati, J.; Ewert, F. |
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Title |
Impact of spatial soil and climate input data aggregation on regional yield simulations |
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Journal Article |
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Year |
2016 |
Publication |
PLoS One |
Abbreviated Journal |
PLoS One |
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Volume |
11 |
Issue |
4 |
Pages |
e0151782 |
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Keywords |
systems simulation; nitrogen dynamics; winter-wheat; crop models; data resolution; scale; water; variability; calibration; weather |
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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. |
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1932-6203 |
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CropM, ft_macsur |
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no |
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MA @ admin @ |
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4725 |
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Author |
Ramirez-Villegas, J.; Watson, J.; Challinor, A.J. |
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Title |
Identifying traits for genotypic adaptation using crop models |
Type |
Journal Article |
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Year |
2015 |
Publication |
Journal of Experimental Botany |
Abbreviated Journal |
J. Experim. Bot. |
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Volume |
66 |
Issue |
12 |
Pages |
3451-3462 |
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Keywords |
Adaptation, Physiological/*genetics; Crops, Agricultural/*genetics; Environment; Genotype; *Models, Theoretical; *Quantitative Trait, Heritable; Climate change; crop models; genotypic adaptation; ideotypes; impacts |
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Abstract |
Genotypic adaptation involves the incorporation of novel traits in crop varieties so as to enhance food productivity and stability and is expected to be one of the most important adaptation strategies to future climate change. Simulation modelling can provide the basis for evaluating the biophysical potential of crop traits for genotypic adaptation. This review focuses on the use of models for assessing the potential benefits of genotypic adaptation as a response strategy to projected climate change impacts. Some key crop responses to the environment, as well as the role of models and model ensembles for assessing impacts and adaptation, are first reviewed. Next, the review describes crop-climate models can help focus the development of future-adapted crop germplasm in breeding programmes. While recently published modelling studies have demonstrated the potential of genotypic adaptation strategies and ideotype design, it is argued that, for model-based studies of genotypic adaptation to be used in crop breeding, it is critical that modelled traits are better grounded in genetic and physiological knowledge. To this aim, two main goals need to be pursued in future studies: (i) a better understanding of plant processes that limit productivity under future climate change; and (ii) a coupling between genetic and crop growth models-perhaps at the expense of the number of traits analysed. Importantly, the latter may imply additional complexity (and likely uncertainty) in crop modelling studies. Hence, appropriately constraining processes and parameters in models and a shift from simply quantifying uncertainty to actually quantifying robustness towards modelling choices are two key aspects that need to be included into future crop model-based analyses of genotypic adaptation. |
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0022-0957 1460-2431 |
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Review |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4645 |
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Author |
Halford, N.G.; Foyer, C.H. |
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Title |
Producing a road map that enables plants to cope with future climate change |
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Journal Article |
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Year |
2015 |
Publication |
Journal of Experimental Botany |
Abbreviated Journal |
J. Experim. Bot. |
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66 |
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12 |
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3433-3434 |
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0022-0957 |
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Editorial Material |
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CropM |
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MA @ admin @ |
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4704 |
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Author |
Stürck, J.; Levers, C.; van der Zanden, E.H.; Schulp, C.J.E.; Verkerk, P.J.; Kuemmerle, T.; Helming, J.; Lotze-Campen, H.; Tabeau, A.; Popp, A.; Schrammeijer, E.; Verburg, P. |
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Title |
Simulating and delineating future land change trajectories across Europe |
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Journal Article |
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Year |
2015 |
Publication |
Regional Environmental Change |
Abbreviated Journal |
Reg. Environ. Change |
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Pages |
in press |
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Keywords |
land use change; land system; modeling; scenario; Europe; ecosystem services |
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Abstract |
Explorations of future land use change are important to understand potential conflicts between competing land uses, trade-offs associated with particular land change trajectories, and the effectiveness of policies to steer land systems into desirable states. Most model-based explorations and scenario studies focused on conversions in broad land use classes, but disregarded changes in land management or focused on individual sectors only. Using the European Union (EU) as a case study, we developed an approach to identifying typical combinations of land cover and management changes by combining the results of multimodel simulations in the agriculture and forest sectors for four scenarios from 2000 to 2040. We visualized land change trajectories by mapping regional hotspots of change. Land change trajectories differed in extent and spatial pattern across the EU and among scenarios, indicating trajectory-specific option spaces for alternative land system outcomes. In spite of the large variation in the area of change, similar hotspots of land change were observed among the scenarios. All scenarios indicate a stronger polarization of land use in Europe, with a loss of multifunctional landscapes. We analyzed locations subject to change by comparing location characteristics associated with certain land change trajectories. Results indicate differences in the location conditions of different land change trajectories, with diverging impacts on ecosystem service provisioning. Policy and planning for future land use needs to account for the spatial variation of land change trajectories to achieve both overarching and location-specific targets. |
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1436-3798 |
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TradeM, ftnotmacsur |
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Call Number |
MA @ admin @ |
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4996 |
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Lotze-Campen, H.; Verburg, P.H.; Popp, A.; Lindner, M.; Verkerk, P.J.; Moiseyev, A.; Schrammeijer, E.; Helming, J.; Tabeau, A.; Schulp, C.J.E.; van der Zanden, E.H.; Lavalle, C.; e Silva, F.B.; Walz, A.; Bodirsky, B. |
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Title |
A cross-scale impact assessment of European nature protection policies under contrasting future socio-economic pathways |
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Journal Article |
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Year |
2018 |
Publication |
Regional Environmental Change |
Abbreviated Journal |
Reg. Environ. Change |
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Volume |
18 |
Issue |
3 |
Pages |
751-762 |
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Keywords |
Land use change; Integrated modelling; Cross-scale interaction; Nature protection; Impact assessment |
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Abstract |
Protection of natural or semi-natural ecosystems is an important part of societal strategies for maintaining biodiversity, ecosystem services, and achieving overall sustainable development. The assessment of multiple emerging land use trade-offs is complicated by the fact that land use changes occur and have consequences at local, regional, and even global scale. Outcomes also depend on the underlying socio-economic trends. We apply a coupled, multi-scale modelling system to assess an increase in nature protection areas as a key policy option in the European Union (EU). The main goal of the analysis is to understand the interactions between policy-induced land use changes across different scales and sectors under two contrasting future socio-economic pathways. We demonstrate how complementary insights into land system change can be gained by coupling land use models for agriculture, forestry, and urban areas for Europe, in connection with other world regions. The simulated policy case of nature protection shows how the allocation of a certain share of total available land to newly protected areas, with specific management restrictions imposed, may have a range of impacts on different land-based sectors until the year 2040. Agricultural land in Europe is slightly reduced, which is partly compensated for by higher management intensity. As a consequence of higher costs, total calorie supply per capita is reduced within the EU. While wood harvest is projected to decrease, carbon sequestration rates increase in European forests. At the same time, imports of industrial roundwood from other world regions are expected to increase. Some of the aggregate effects of nature protection have very different implications at the local to regional scale in different parts of Europe. Due to nature protection measures, agricultural production is shifted from more productive land in Europe to on average less productive land in other parts of the world. This increases, at the global level, the allocation of land resources for agriculture, leading to a decrease in tropical forest areas, reduced carbon stocks, and higher greenhouse gas emissions outside of Europe. The integrated modelling framework provides a method to assess the land use effects of a single policy option while accounting for the trade-offs between locations, and between regional, European, and global scales. |
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1436-3798 |
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TradeM |
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TradeM, ftnotmacsur |
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MA @ admin @ |
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5004 |
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