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Author Zhao, G.; Hoffmann, H.; van Bussel, L.G.J.; Enders, A.; Specka, X.; Sosa, C.; Yeluripati, J.; Tao, F.L.; Constantin, J.; Raynal, H.; Teixeira, E.; Grosz, B.; Doro, L.; Zhao, Z.G.; Nendel, C.; Kiese, R.; Eckersten, H.; Haas, E.; Vanuytrecht, E.; Wang, E.; Kuhnert, M.; Trombi, G.; Moriondo, M.; Bindi, M.; Lewan, E.; Bach, M.; Kersebaum, K.C.; Rotter, R.; Roggero, P.P.; Wallach, D.; Cammarano, D.; Asseng, S.; Krauss, G.; Siebert, S.; Gaiser, T.; Ewert, F. url  doi
openurl 
  Title Effect of weather data aggregation on regional crop simulation for different crops, production conditions, and response variables Type Journal Article
  Year 2015 Publication Climate Research Abbreviated Journal Clim. Res.  
  Volume 65 Issue Pages 141-157  
  Keywords crop model; model comparison; spatial resolution; data aggregation; spatial heterogeneity; scaling; climate-change scenarios; sub-saharan africa; winter-wheat; spatial-resolution; yield response; input data; systems simulation; large-scale; soil data; part i  
  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 (Delta), 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., 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.  
  Address  
  Corporate Author Thesis  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (down) 0936-577x ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4754  
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Author Palosuo, T.; Rotter, R.P.; Salo, T.; Peltonen-Sainio, P.; Tao, F.; Lehtonen, H. url  doi
openurl 
  Title Effects of climate and historical adaptation measures on barley yield trends in Finland Type Journal Article
  Year 2015 Publication Climate Research Abbreviated Journal Clim. Res.  
  Volume 65 Issue Pages 221-236  
  Keywords adaptation; climate; crop simulation modelling; plant breeding; spring barley; yield gap; crop production; spring barley; quantitative-evaluation; european conditions; cereal cultivars; growing-season; use efficiency; field crops; wheat; northern  
  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.  
  Address  
  Corporate Author Thesis  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (down) 0936-577x ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4700  
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Author Mitter, H.; Schmid, E.; Sinabell, F. url  doi
openurl 
  Title Integrated modelling of protein crop production responses to climate change and agricultural policy scenarios in Austria Type Journal Article
  Year 2015 Publication Climate Research Abbreviated Journal Clim. Res.  
  Volume 65 Issue Pages 205-220  
  Keywords Climate change impact; Adaptation; Soybean; EPIC; Common Agricultural Policy; Land use  
  Abstract Climate and policy changes are likely to affect protein crop production and thus trade balances in Europe, which is highly dependent on imports. Exemplified for Austrian cropland, we developed an integrated modelling framework to analyze climate change and policy scenario impacts on protein crop production and environmental outcomes. The integrated modelling framework consists of a statistical climate change model, a crop rotation model, the bio-physical process model EPIC, and the economic bottom-up land use optimization model BiomAT. EPIC is applied to simulate annual dry matter crop yields for different crop management practices including crop rotations, fertilization intensities, and irrigation, as well as for 3 regional climate change scenarios until 2040 at a 1 km grid resolution. BiomAT maximizes total gross margins by optimizing land use choices and crop management practices subject to spatially explicit cropland endowments. The model results indicate that changes in agricultural policy conditions, cropland use, and higher flexibility in crop management practices may reduce protein import dependence under changing climatic conditions. Expanding protein crop production is most attractive in south-eastern Austria with its Central European continental climate where maize is most often replaced in crop rotations. However, the acreage of protein crops is limited by agronomically suitable cropland. An intended side effect is the reduction of nitrogen fertilizer inputs by about 0.1% if total protein crop production increases by 1%.  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (down) 0936-577x ISBN Medium  
  Area Expedition Conference  
  Notes TradeM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 5012  
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Author Kros, J.; Bakker, M.M.; Reidsma, P.; Kanellopoulos, A.; Jamal Alam, S.; de Vries, W. url  doi
openurl 
  Title Impacts of agricultural changes in response to climate and socioeconomic change on nitrogen deposition in nature reserves Type Journal Article
  Year 2015 Publication Landscape Ecology Abbreviated Journal Landscape Ecol.  
  Volume 30 Issue 5 Pages 871-885  
  Keywords Agricultural adaptation; Climate change; Land use change; Environmental; impact; Farming system; Nitrogen losses; netherlands; diversity; scenario  
  Abstract This paper describes the environmental consequences of agricultural adaptation on eutrophication of the nearby ecological network for a study area in the Netherlands. More specifically, we explored (i) likely responses of farmers to changes in climate, technology, policy, and markets; (ii) subsequent changes in nitrogen (N) emissions in responses to farmer adaptations; and (iii) to what extent the emitted N was deposited in nearby nature reserves, in view of the potential impacts on plant species diversity and desired nature targets. For this purpose, a spatially-explicit study at landscape level was performed by integrating the environmental model INITIATOR, the farm model FSSIM, and the land-use model RULEX. We evaluated two alternative scenarios of change in climate, technology, policy, and markets for 2050: one in line with a ‘global economy’ (GE) storyline and the other in line with a ‘regional communities’ (RC) storyline. Results show that the GE storyline resulted in a relatively strong increase in agricultural production compared to the RC storyline. Despite the projected conversions of agricultural land to nature (as part of the implementation of the National Ecological Network), we project an increase in N losses and N deposition due to N emissions in the study area of about 20 %. Even in the RC storyline, with a relatively modest increase in agricultural production and a larger expansion of the nature reserve, the N losses and deposition remain at the current level, whereas a reduction is required. We conclude that more ambitious green policies are needed in view of nature protection.  
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  Language English Summary Language Original Title  
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  ISSN (down) 0921-2973 1572-9761 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM Approved no  
  Call Number MA @ admin @ Serial 4565  
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Author Lotze-Campen, H.; von Witzke, H.; Noleppa, S.; Schwarz, G. url  doi
openurl 
  Title Science for food, climate protection and welfare: An economic analysis of plant breeding research in Germany Type Journal Article
  Year 2015 Publication Agricultural Systems Abbreviated Journal Agric. Syst.  
  Volume 136 Issue Pages 79-84  
  Keywords Plant breeding; CO2 emissions; Cost–benefit analysis; Social rate of return; Agricultural research policy  
  Abstract Highlights • We analyze the economic effects of plant breeding research in Germany. • Effects of reduced CO2 emissions due to productivity increases are being quantified. • Expansion of global agricultural area has been reduced by 1–1.5 million ha. • CO2 emissions have been reduced by 160–235 million tons. • German plant breeding research has an economic value of 10.8–15.6 billion EUR. Abstract We analyze the economic effects of plant breeding research in Germany. In addition to market effects, for the first time also effects of reduced CO2 emissions due to productivity increases are being quantified. The analysis shows that investments in German plant breeding research in the period 1991–2010 have reduced the global expansion of agricultural area by 1–1.5 million hectares. This has led to reduced CO2 emissions of 160–235 million tons. The economic value generated by plant breeding research, through increased production and reduced greenhouse gas emissions, is estimated at 10.8–15.6 billion EUR in the same period. This can be translated into a social rate of return on research investment in the range of 40–80% per year. Projections for the period 2011–2030 generate a return rate in the range of 65–140% per year. Investments into plant breeding research in Germany are highly profitable from a societal point of view. At the same time, our results show significant under-investments in agricultural research in Germany. These results provide a good justification for policy-makers to reverse funding cuts for public agricultural research over the last decades and to improve institutional conditions for private research, e.g. through better protection of intellectual property rights.  
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  Series Volume Series Issue Edition  
  ISSN (down) 0308521x ISBN Medium  
  Area Expedition Conference  
  Notes TradeM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4999  
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