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Author Schils, R.; Olesen, J.E.; Kersebaum, K.-C.; Rijk, B.; Oberforster, M.; Kalyada, V.; Khitrykau, M.; Gobin, A.; Kirchev, H.; Manolova, V.; Manolov, I.; Trnka, M.; Hlavinka, P.; Palosuo, T.; Peltonen-Sainio, P.; Jauhiainen, L.; Lorgeou, J.; Marrou, H.; Danalatos, N.; Archontoulis, S.; Fodor, N.; Spink, J.; Roggero, P.P.; Bassu, S.; Pulina, A.; Seehusen, T.; Uhlen, A.K.; Zylowska, K.; Nierobca, A.; Kozyra, J.; Silva, J.V.; Macas, B.M.; Coutinho, J.; Ion, V.; Takac, J.; Ines Minguez, M.; Eckersten, H.; Levy, L.; Herrera, J.M.; Hiltbrunner, J.; Kryvobok, O.; Kryvoshein, O.; Sylvester-Bradley, R.; Kindred, D.; Topp, C.F.E.; Boogaard, H.; de Groot, H.; Lesschen, J.P.; van Bussel, L.; Wolf, J.; Zijlstra, M.; van Loon, M.P.; van Ittersum, M.K. doi  openurl
  Title Cereal yield gaps across Europe Type Journal Article
  Year 2018 Publication European Journal of Agronomy Abbreviated Journal Europ. J. Agron.  
  Volume 101 Issue Pages 109-120  
  Keywords Wheat, Barley, Grain maize, Crop modelling, Yield potential, Nitrogen; Nitrogen Use Efficiency; Sustainable Intensification; Climate-Change; Land-Use; Wheat; Soil; Agriculture; Impacts; Fertility; Emissions  
  Abstract Europe accounts for around 20% of the global cereal production and is a net exporter of ca. 15% of that production. Increasing global demand for cereals justifies questions as to where and by how much Europe’s production can be increased to meet future global market demands, and how much additional nitrogen (N) crops would require. The latter is important as environmental concern and legislation are equally important as production aims in Europe. Here, we used a country-by-country, bottom-up approach to establish statistical estimates of actual grain yield, and compare these to modelled estimates of potential yields for either irrigated or rainfed conditions. In this way, we identified the yield gaps and the opportunities for increased cereal production for wheat, barley and maize, which represent 90% of the cereals grown in Europe. The combined mean annual yield gap of wheat, barley, maize was 239 Mt, or 42% of the yield potential. The national yield gaps ranged between 10 and 70%, with small gaps in many north-western European countries, and large gaps in eastern and south-western Europe. Yield gaps for rainfed and irrigated maize were consistently lower than those of wheat and barley. If the yield gaps of maize, wheat and barley would be reduced from 42% to 20% of potential yields, this would increase annual cereal production by 128 Mt (39%). Potential for higher cereal production exists predominantly in Eastern Europe, and half of Europe’s potential increase is located in Ukraine, Romania and Poland. Unlocking the identified potential for production growth requires a substantial increase of the crop N uptake of 4.8 Mt. Across Europe, the average N uptake gaps, to achieve 80% of the yield potential, were 87, 77 and 43 kg N ha(-1) for wheat, barley and maize, respectively. Emphasis on increasing the N use efficiency is necessary to minimize the need for additional N inputs. Whether yield gap reduction is desirable and feasible is a matter of balancing Europe’s role in global food security, farm economic objectives and environmental targets.  
  Address (up) 2019-01-07  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1161-0301 ISBN Medium  
  Area Expedition Conference  
  Notes CropM, TradeM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 5213  
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Author Sandor, R.; Ehrhardt, F.; Grace, P.; Recous, S.; Smith, P.; Snow, V.; Soussana, J.-F.; Basso, B.; Bhatia, A.; Brilli, L.; Doltra, J.; Dorich, C.D.; Doro, L.; Fitton, N.; Grant, B.; Harrison, M.T.; Kirschbaum, M.U.F.; Klumpp, K.; Laville, P.; Leonard, J.; Martin, R.; Massad, R.-S.; Moore, A.; Myrgiotis, V.; Pattey, E.; Rolinski, S.; Sharp, J.; Skiba, U.; Smith, W.; Wu, L.; Zhang, Q.; Bellocchi, G. doi  openurl
  Title Ensemble modelling of carbon fluxes in grasslands and croplands Type Journal Article
  Year 2020 Publication Field Crops Research Abbreviated Journal Field Crops Research  
  Volume 252 Issue Pages 107791  
  Keywords C fluxes; croplands; grasslands; multi-model ensemble; multi-model; median (mmm); soil organic-carbon; greenhouse-gas emissions; climate-change impacts; crop model; data aggregation; use efficiency; n2o emissions; maize; yield; wheat; productivity  
  Abstract Croplands and grasslands are agricultural systems that contribute to land–atmosphere exchanges of carbon (C). We evaluated and compared gross primary production (GPP), ecosystem respiration (RECO), net ecosystem exchange (NEE) of CO2, and two derived outputs – C use efficiency (CUE=-NEE/GPP) and C emission intensity (IntC= -NEE/Offtake [grazed or harvested biomass]). The outputs came from 23 models (11 crop-specific, eight grassland-specific, and four models covering both systems) at three cropping sites over several rotations with spring and winter cereals, soybean and rapeseed in Canada, France and India, and two temperate permanent grasslands in France and the United Kingdom. The models were run independently over multi-year simulation periods in five stages (S), either blind with no calibration and initialization data (S1), using historical management and climate for initialization (S2), calibrated against plant data (S3), plant and soil data together (S4), or with the addition of C and N fluxes (S5). Here, we provide a framework to address methodological uncertainties and contextualize results. Most of the models overestimated or underestimated the C fluxes observed during the growing seasons (or the whole years for grasslands), with substantial differences between models. For each simulated variable, changes in the multi-model median (MMM) from S1 to S5 was used as a descriptor of the ensemble performance. Overall, the greatest improvements (MMM approaching the mean of observations) were achieved at S3 or higher calibration stages. For instance, grassland GPP MMM was equal to 1632 g C m−2 yr-1 (S5) while the observed mean was equal to 1763 m-2 yr-1 (average for two sites). Nash-Sutcliffe modelling efficiency coefficients indicated that MMM outperformed individual models in 92.3 % of cases. Our study suggests a cautious use of large-scale, multi-model ensembles to estimate C fluxes in agricultural sites if some site-specific plant and soil observations are available for model calibration. The further development of crop/grassland ensemble modelling will hinge upon the interpretation of results in light of the way models represent the processes underlying C fluxes in complex agricultural systems (grassland and crop rotations including fallow periods).  
  Address (up) 2020-06-08  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium Article  
  Area Expedition Conference  
  Notes LiveM Approved no  
  Call Number MA @ admin @ Serial 5230  
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Author Gomara, I.; Bellocchi, G.; Martin, R.; Rodriguez-Fonseca, B.; Ruiz-Ramos, M. doi  openurl
  Title Influence of climate variability on the potential forage production of a mown permanent grassland in the French Massif Central Type Journal Article
  Year 2020 Publication Agricultural and Forest Meteorology Abbreviated Journal Agricultural and Forest Meteorology  
  Volume 280 Issue Pages 107768  
  Keywords climate variability; grasslands; potential yield; climate services; forage production forecasts; french massif central; pasture simulation-model; dry-matter production; atmospheric; circulation; crop yield; SST anomalies; maize yield; managed grasslands; storm track; ENSO; impacts  
  Abstract Climate Services (CS) provide support to decision makers across socio-economic sectors. In the agricultural sector, one of the most important CS applications is to provide timely and accurate yield forecasts based on climate prediction. In this study, the Pasture Simulation model (PaSim) was used to simulate, for the period 1959–2015, the forage production of a mown grassland system (Laqueuille, Massif Central of France) under different management conditions, with meteorological inputs extracted from the SAFRAN atmospheric database. The aim was to generate purely climate-dependent timeseries of optimal forage production, a variable that was maximized by brighter and warmer weather conditions at the grassland. A long-term increase was observed in simulated forage yield, with the 1995–2015 average being 29% higher than the 1959–1979 average. Such increase seems consistent with observed rising trends in temperature and CO2, and multi-decadal changes in incident solar radiation. At interannual timescales, sea surface temperature anomalies of the Mediterranean (MED), Tropical North Atlantic (TNA), equatorial Pacific (El Niño Southern Oscillation) and the North Atlantic Oscillation (NAO) index were found robustly correlated with annual forage yield values. Relying only on climatic predictors, we developed a stepwise statistical multi-regression model with leave-one-out cross-validation. Under specific management conditions (e.g., three annual cuts) and from one to five months in advance, the generated model successfully provided a p-value<0.01 in correlation (t-test), a root mean square error percentage (%RMSE) of 14.6% and a 71.43% hit rate predicting above/below average years in terms of forage yield collection. This is the first modeling study on the possible role of large-scale oceanic–atmospheric teleconnections in driving forage production in Europe. As such, it provides a useful springboard to implement a grassland seasonal forecasting system in this continent.  
  Address (up) 2020-06-08  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium article  
  Area Expedition Conference  
  Notes LiveM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 5233  
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