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Author Nelson, G.C.; van der Mensbrugghe, D.; Ahammad, H.; Blanc, E.; Calvin, K.; Hasegawa, T.; Havlik, P.; Heyhoe, E.; Kyle, P.; Lotze-Campen, H.; von Lampe, M.; Mason, d’C., Daniel; van Meijl, H.; Müller, C.; Reilly, J.; Robertson, R.; Sands, R.D.; Schmitz, C.; Tabeau, A.; Takahashi, K.; Valin, H.; Willenbockel, D. url  doi
openurl 
  Title Agriculture and climate change in global scenarios: why don’t the models agree Type Journal Article
  Year 2014 Publication Agricultural Economics Abbreviated Journal Agric. Econ.  
  Volume 45 Issue 1 Pages 85-101  
  Keywords climate change impacts; economic models of agriculture; scenarios; system model; demand; CMIP5  
  Abstract (up) Agriculture is unique among economic sectors in the nature of impacts from climate change. The production activity that transforms inputs into agricultural outputs involves direct use of weather inputs (temperature, solar radiation available to the plant, and precipitation). Previous studies of the impacts of climate change on agriculture have reported substantial differences in outcomes such as prices, production, and trade arising from differences in model inputs and model specification. This article presents climate change results and underlying determinants from a model comparison exercise with 10 of the leading global economic models that include significant representation of agriculture. By harmonizing key drivers that include climate change effects, differences in model outcomes were reduced. The particular choice of climate change drivers for this comparison activity results in large and negative productivity effects. All models respond with higher prices. Producer behavior differs by model with some emphasizing area response and others yield response. Demand response is least important. The differences reflect both differences in model specification and perspectives on the future. The results from this study highlight the need to more fully compare the deep model parameters, to generate a call for a combination of econometric and validation studies to narrow the degree of uncertainty and variability in these parameters and to move to Monte Carlo type simulations to better map the contours of economic uncertainty.  
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  Language English Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN 0169-5150 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, TradeM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4536  
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Author van Bussel, L.G.J.; Stehfest, E.; Siebert, S.; Müller, C.; Ewert, F. url  doi
openurl 
  Title Simulation of the phenological development of wheat and maize at the global scale Type Journal Article
  Year 2015 Publication Global Ecology and Biogeography Abbreviated Journal Glob. Ecol. Biogeogr.  
  Volume 24 Issue 9 Pages 1018-1029  
  Keywords Agricultural management; crop calendars; cultivar; variety characteristics; global crop modelling; global harvest dates; phenology; climate-change; winter-wheat; annual crops; photoperiod sensitivity; geographical variation; temperature; responses; adaptation; cultivars; model  
  Abstract (up) AimTo derive location-specific parameters that reflect the geographic differences among cultivars in vernalization requirements, sensitivity to day length (photoperiod) and temperature, which can be used to simulate the phenological development of wheat and maize at the global scale. LocationGlobal. Methods Based on crop calendar observations and literature describing the large-scale patterns of phenological characteristics of cultivars, we developed algorithms to compute location-specific parameters to represent this large-scale pattern. Vernalization requirements were related to the duration and coldness of winter, sensitivity to day length was assumed to be represented by the minimum and maximum day lengths occurring at a location, and sensitivity to temperature was related to temperature conditions during the vegetative development phase of the crop. Results Application of the derived location-specific parameters resulted in high agreement between simulated and observed lengths of the cropping period. Agreement was especially high for wheat, with mean absolute errors of less than 3 weeks. In the main maize cropping regions, cropping periods were over- and underestimated by 0.5-1.5 months. We also found that interannual variability in simulated wheat harvest dates was more realistic when accounting for photoperiod effects. Main conclusions The methodology presented here provides a good basis for modelling the phenological characteristics of cultivars at the global scale. We show that current global patterns of growing season length as described in cropping calendars can be largely reproduced by phenology models if location-specific parameters are derived from temperature and day length indicators. Growing seasons can be modelled more accurately for wheat than for maize, especially in warm regions. Our method for computing parameters for phenology models from temperature and day length offers opportunities to improve the simulation of crop productivity by crop simulation models developed for large spatial areas and for long-term climate impact projections that account for adaptation in the selection of varieties  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1466-822x ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4729  
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Author Schmitz, C.; Lotze-Campen, H.; Gerten, D.; Dietrich, J.P.; Bodirsky, B.; Biewald, A.; Popp, A. url  doi
openurl 
  Title Blue water scarcity and the economic impacts of future agricultural trade and demand Type Journal Article
  Year 2013 Publication Water Resource Research Abbreviated Journal Water Resource Research  
  Volume 49 Issue 6 Pages 3601-3617  
  Keywords water scarcity; land use model; irrigation efficiency; trade liberalization; livestock consumption; modeling; land cover change; water budgets  
  Abstract (up) An increasing demand for agricultural goods affects the pressure on global water resources over the coming decades. In order to quantify these effects, we have developed a new agroeconomic water scarcity indicator, considering explicitly economic processes in the agricultural system. The indicator is based on the water shadow price generated by an economic land use model linked to a global vegetation-hydrology model. Irrigation efficiency is implemented as a dynamic input depending on the level of economic development. We are able to simulate the heterogeneous distribution of water supply and agricultural water demand for irrigation through the spatially explicit representation of agricultural production. This allows in identifying regional hot spots of blue water scarcity and explicit shadow prices for water. We generate scenarios based on moderate policies regarding future trade liberalization and the control of livestock-based consumption, dependent on different population and gross domestic product (GDP) projections. Results indicate increased water scarcity in the future, especially in South Asia, the Middle East, and north Africa. In general, water shadow prices decrease with increasing liberalization, foremost in South Asia, Southeast Asia, and the Middle East. Policies to reduce livestock consumption in developed countries not only lower the domestic pressure on water but also alleviate water scarcity to a large extent in developing countries. It is shown that one of the two policy options would be insufficient for most regions to retain water scarcity in 2045 on levels comparable to 2005.  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0043-1397 ISBN Medium Article  
  Area Expedition Conference  
  Notes TradeM Approved no  
  Call Number MA @ admin @ Serial 4502  
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Author Schönhart, M.; Mitter, H.; Schmid, E.; Heinrich, G.; Gobiet, A. openurl 
  Title Integrated analysis of climate change impacts and adaptation measures in Austrian agriculture Type Journal Article
  Year 2014 Publication German Journal of Agricultural Economics Abbreviated Journal German Journal of Agricultural Economics  
  Volume 63 Issue 3 Pages 156-176  
  Keywords land use; modelling; climate change impact; adaptation; integrated analysis; epic; pasma; crop production; land-use; management-practices; model projections; central-europe; soil-erosion; water; variability; strategies; region  
  Abstract (up) An integrated modelling framework (IMF) has been developed and applied to analyse climate change impacts and the effectiveness of adaptation measures in Austrian agriculture. The IMF couples the crop rotation model CropRota, the bio-physical process model EPIC and the bottom-up economic land use model PASMA at regional level (NUTS-3) considering agri-environmental indicators. Four contrasting regional climate model (RCM) simulations represent climate change until 2050. The RCM simulations are applied to a baseline and three adaptation and policy scenarios. Climate change increases crop productivity on national average in the IMF. Changes in average gross margins at national level range from 0% to + 5% between the baseline and the three adaptation and policy scenarios. The impacts at NUTS-3 level range from -5% to + 7% between the baseline and the three adaptation and policy scenarios. Adaptation measures such as planting of winter cover crops, reduced tillage and irrigation are effective in reducing yield losses, increasing revenues, or in improving environmental states under climate change. Future research should account for extreme weather events in order to analyse whether average productivity gains at the aggregated level suffice to cover costs from expected higher climate variability.  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0002-1121 ISBN Medium Article  
  Area Expedition Conference  
  Notes TradeM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4652  
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Author Hidy, D.; Barcza, Z.; Haszpra, L.; Churkina, G.; Pintér, K.; Nagy, Z. url  doi
openurl 
  Title Development of the Biome-BGC model for simulation of managed herbaceous ecosystems Type Journal Article
  Year 2012 Publication Ecological Modelling Abbreviated Journal Ecol. Model.  
  Volume 226 Issue Pages 99-119  
  Keywords biogeochemical model; biome-bgc; grassland; management; soil moisture; bayesian calibration; carbon flux model; regional applications; bayesian calibration; use efficiency; general-model; exchange; balance; climate; grassland; variability  
  Abstract (up) Apart from measurements, numerical models are the most convenient instruments to analyze the carbon and water balance of terrestrial ecosystems and their interactions with changing environmental conditions. The process-based Biome-BGC model is widely used to simulate the storage and flux of water, carbon, and nitrogen within the vegetation, litter, and soil of unmanaged terrestrial ecosystems. Considering herbaceous vegetation related simulations with Biome-BGC, soil moisture and growing season control on ecosystem functioning is inaccurate due to the simple soil hydrology and plant phenology representation within the model. Consequently, Biome-BGC has limited applicability in herbaceous ecosystems because (1) they are usually managed; (2) they are sensitive to soil processes, most of all hydrology; and (3) their carbon balance is closely connected with the growing season length. Our aim was to improve the applicability of Biome-BGC for managed herbaceous ecosystems by implementing several new modules, including management. A new index (heatsum growing season index) was defined to accurately estimate the first and the final days of the growing season. Instead of a simple bucket soil sub-model, a multilayer soil sub-model was implemented, which can handle the processes of runoff, diffusion and percolation. A new module was implemented to simulate the ecophysiological effect of drought stress on plant mortality. Mowing and grazing modules were integrated in order to quantify the functioning of managed ecosystems. After modifications, the Biome-BGC model was calibrated and validated using eddy covariance-based measurement data collected in Hungarian managed grassland ecosystems. Model calibration was performed based on the Bayes theorem. As a result of these developments and calibration, the performance of the model was substantially improved. Comparison with measurement-based estimate showed that the start and the end of the growing season are now predicted with an average accuracy of 5 and 4 days instead of 46 and 85 days as in the original model. Regarding the different sites and modeled fluxes (gross primary production, total ecosystem respiration, evapotranspiration), relative errors were between 18-60% using the original model and 10-18% using the developed model; squares of the correlation coefficients were between 0.02-0.49 using the original model and 0.50-0.81 using the developed model. (c) 2011 Elsevier B.V. All rights reserved.  
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  Language English Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN 0304-3800 ISBN Medium Article  
  Area Expedition Conference  
  Notes LiveM Approved no  
  Call Number MA @ admin @ Serial 4472  
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