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Author Hoffmann, M.P.; Haakana, M.; Asseng, S.; Höhn, J.G.; Palosuo, T.; Ruiz-Ramos, M.; Fronzek, S.; Ewert, F.; Gaiser, T.; Kassie, B.T.; Paff, K.; Rezaei, E.E.; Rodríguez, A.; Semenov, M.; Srivastava, A.K.; Stratonovitch, P.; Tao, F.; Chen, Y.; Rötter, R.P. url  doi
openurl 
  Title How does inter-annual variability of attainable yield affect the magnitude of yield gaps for wheat and maize? An analysis at ten sites Type Journal Article
  Year 2017 Publication Agricultural Systems Abbreviated Journal Agric. Syst.  
  Volume 159 Issue Pages (down) 199-208  
  Keywords  
  Abstract Highlights • The larger simulated attainable yield for a specific crop season, the larger the yield gap. • Average size of the yield gap is not affected by the inter-annual variability of attainable yield. • Technology levels (resource input and accessibility) determine average yield gap. • To reduce yield gaps in rainfed environments, farmers need to improve season-specific crop management. Abstract Provision of food security in the face of increasing global food demand requires narrowing of the gap between actual farmer’s yield and maximum attainable yield. So far, assessments of yield gaps have focused on average yield over 5–10 years, but yield gaps can vary substantially between crop seasons. In this study we hypothesized that climate-induced inter-annual yield variability and associated risk is a major barrier for farmers to invest, i.e. increase inputs to narrow the yield gap. We evaluated the importance of inter-annual attainable yield variability for the magnitude of the yield gap by utilizing data for wheat and maize at ten sites representing some major food production systems and a large range of climate and soil conditions across the world. Yield gaps were derived from the difference of simulated attainable yields and regional recorded farmer yields for 1981 to 2010. The size of the yield gap did not correlate with the amplitude of attainable yield variability at a site, but was rather associated with the level of available resources such as labor, fertilizer and plant protection inputs. For the sites in Africa, recorded yield reached only 20% of the attainable yield, while for European, Asian and North American sites it was 56–84%. Most sites showed that the higher the attainable yield of a specific season the larger was the yield gap. This significant relationship indicated that farmers were not able to take advantage of favorable seasonal weather conditions. To reduce yield gaps in the different environments, reliable seasonal weather forecasts would be required to allow farmers to manage each seasonal potential, i.e. overcoming season-specific yield limitations.  
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  ISSN 0308521x ISBN Medium  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 5185  
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Author Van Oijen, M.; Cameron, D.; Levy, P.E.; Preston, R. url  doi
openurl 
  Title Correcting errors from spatial upscaling of nonlinear greenhouse gas flux models Type Journal Article
  Year 2017 Publication Environmental Modelling & Software Abbreviated Journal Environmental Modelling & Software  
  Volume 94 Issue Pages (down) 157-165  
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  ISSN 1364-8152 ISBN Medium article  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4945  
Permanent link to this record
 

 
Author Özkan Gülzari, Ş.; Åby, B.A.; Persson, T.; Höglind, M.; Mittenzwei, K. doi  openurl
  Title Combining models to estimate the impacts of future climate scenarios on feed supply, greenhouse gas emissions and economic performance on dairy farms in Norway Type Journal Article
  Year 2017 Publication Agricultural Systems Abbreviated Journal Agric. Syst.  
  Volume 157 Issue Pages (down) 157-169  
  Keywords Climate change; Dairy farming; Dry matter yield; Economics; Greenhouse gas emission; Modelling  
  Abstract • This study combines crop, livestock and economic models.

• Models interaction is through use of relevant input and output variables.

• Future climate change will result in increased grass and wheat dry matter yields.

• Changes in grass, wheat and milk yields in future reduce farm emissions intensity.

• Changes in future dry matter yields and emissions lead to increased profitability.

There is a scientific consensus that the future climate change will affect grass and crop dry matter (DM) yields. Such yield changes may entail alterations to farm management practices to fulfill the feed requirements and reduce the farm greenhouse gas (GHG) emissions from dairy farms. While a large number of studies have focused on the impacts of projected climate change on a single farm output (e.g. GHG emissions or economic performance), several attempts have been made to combine bio-economic systems models with GHG accounting frameworks. In this study, we aimed to determine the physical impacts of future climate scenarios on grass and wheat DM yields, and demonstrate the effects such changes in future feed supply may have on farm GHG emissions and decision-making processes. For this purpose, we combined four models: BASGRA and CSM-CERES-Wheat models for simulating forage grass DM and wheat DM grain yields respectively; HolosNor for estimating the farm GHG emissions; and JORDMOD for calculating the impacts of changes in the climate and management on land use and farm economics. Four locations, with varying climate and soil conditions were included in the study: south-east Norway, south-west Norway, central Norway and northern Norway. Simulations were carried out for baseline (1961–1990) and future (2046–2065) climate conditions (projections based on two global climate models and the Special Report on Emissions Scenarios (SRES) A1B GHG emission scenario), and for production conditions with and without a milk quota. The GHG emissions intensities (kilogram carbon dioxide equivalent: kgCO2e emissions per kg fat and protein corrected milk: FPCM) varied between 0.8 kg and 1.23 kg CO2e (kg FPCM)− 1, with the lowest and highest emissions found in central Norway and south-east Norway, respectively. Emission intensities were generally lower under future compared to baseline conditions due mainly to higher future milk yields and to some extent to higher crop yields. The median seasonal above-ground timothy grass yield varied between 11,000 kg and 16,000 kg DM ha− 1 and was higher in all projected future climate conditions than in the baseline. The spring wheat grain DM yields simulated for the same weather conditions within each climate projection varied between 2200 kg and 6800 kg DM ha− 1. Similarly, the farm profitability as expressed by total national land rents varied between 1900 million Norwegian krone (NOK) for median yields under baseline climate conditions up to 3900 million NOK for median yield under future projected climate conditions.
 
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  Notes CropM, LiveM, TradeM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 5172  
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Author Malone, R.W.; Kersebaum, K.C.; Kaspar, T.C.; Ma, L.; Jaynes, D.B.; Gillette, K. doi  openurl
  Title Winter rye as a cover crop reduces nitrate loss to subsurface drainage as simulated by HERMES Type Journal Article
  Year 2017 Publication Agricultural Water Management Abbreviated Journal Agric. Water Manage.  
  Volume 184 Issue Pages (down) 156-169  
  Keywords Subsurface drainage, Cover crop, Nitrate loss, Modeling, Denitrification; NITROGEN DYNAMICS; TILE DRAINAGE; AGROECOSYSTEM MODELS; MISSISSIPPI; RIVER; GROWTH-MODEL; RZWQM-DSSAT; DRAINMOD-N; CATCH CROP; SOIL; WATER  
  Abstract HERMES is a widely used agricultural system model; however, it has never been tested for simulating N loss to subsurface drainage. Here, we integrated a simple drain flbw component into HERMES. We then compared the predictions to four years of data (2002-2005) from central Iowa fields in corn-oybean with winter rye as a cover crop (CC) and without winter rye (NCC). We also compared the HERMES predictions to the more complex Root Zone Water Quality Model (RZWQM) predictions for the same dataset. The average annual observed and simulated N loss to drain flow were 43.8 and 44.4 kg N/ha (NCC) and 17.6 and 18.9 kg N/ha (CC). The slightly over predicted N loss for CC was because of over predicted nitrate concentration, which may be partly caused by slightly under predicted average annual rye shoot N (observed and simulated values were 47.8 and 46.0 kg N/ha). Also, recent research from the site suggests that the soil field capacity may be greater in CC while we used the same soil parameters for both treatments. A local sensitivity analysis suggests that increased field capacity affects HERMES simulations, which includes reduced drain flow nitrate concentrations, increased denitrification, and reduced drain flow volume. HERMES-simulated cumulative monthly drain flow and annual drain flow were reasonable compared to field data and HERMES performance was comparable to other published drainage model tests. Unlike the RZWQM simulations, however, the modified HERMES did riot accurately simulate the year to year variability in nitrate concentration difference between NCC and CC, possibly due in part to the lack of partial mixing and displacement of the soil solution. The results suggest that 1) the relatively simple model HERMES is a promising tool to estimate annual N loss to drain flow under corn-soybean rotations with winter rye as a cover crop and 2) soil field capacity is a critical parameter to investigate to more thoroughly understand and appropriately model denitrification and N losses to subsurface drainage. Published by Elsevier B.V.  
  Address 2017-04-28  
  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 0378-3774 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4946  
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Author Mandryk, M.; Reidsma, P.; van Ittersum, M.K. url  doi
openurl 
  Title Crop and farm level adaptation under future climate challenges: An exploratory study considering multiple objectives for Flevoland, the Netherlands Type Journal Article
  Year 2017 Publication Agricultural Systems Abbreviated Journal Agric. Syst.  
  Volume 152 Issue Pages (down) 154-164  
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  ISSN 0308521x ISBN Medium  
  Area Expedition Conference  
  Notes CropM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4982  
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