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Author Bellocchi, G.; Martin, R.; Shtiliyanova, A.; Ben Touhami, H.; Carrère, P. url  openurl
  Title Vul’Clim – Climate change vulnerability studies in the region Auvergne (France) Type Report
  Year 2014 Publication FACCE MACSUR Reports Abbreviated Journal  
  Volume 3 Issue Pages Sp3-6  
  Keywords  
  Abstract The region Auvergne (France) is a major livestock territory in Europe (beef and dairy cattle with permanent grasslands), with a place in climate change regional studies assisting policy makers and actors in identifying adaptation and mitigation measures. Vul’Clim is a research grant (Bourse Recherche Filière) of the region Auvergne (February 2014-September 2015) to develop model-based vulnerability analysis approaches for a detailed assessment of climate change impacts at regional scale. Its main goal is the creation of a computer-aided platform for vulnerability assessment of grasslands, in interaction with stakeholders from a cluster of eco-enterprises. A modelling engine provided by the mechanistic, biogeochemical model PaSim (Pasture Simulation model) is the core of the platform. An action studies the changes of scales by varying the granularity of the data available at a given scale (e.g. climate data supplied by global scenarios) to let them being exploited at another scale (e.g. high-resolution pixels). Another action is to develop an assessment framework linking modelling tools to entry data and outputs, including a variety of components: data-entry manager at different spatial resolutions; automatic computation of indicators; gap-filling and data quality check; simulation kernel with the model(s) used; device to represent results as maps and integrated indicators. No Label  
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  Notes Approved no  
  Call Number MA @ admin @ Serial 2223  
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Author Bellocchi, G.; Martin, R.; Shtiliyanova, A.; Ben Touhami, H.; Carrère, P. url  openurl
  Title Vul’Clim – Climate change vulnerability studies in the region Auvergne (France) Type Conference Article
  Year 2014 Publication Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract The region Auvergne (France) is a major livestock territory in Europe (beef and dairy cattle with permanent grasslands), with a place in climate change regional studies assisting policy makers and actors in identifying adaptation and mitigation measures. Vul’Clim is a research grant (Bourse Recherche Filière) of the region Auvergne (February 2014-September 2015) to develop model-based vulnerability analysis approaches for a detailed assessment of climate change impacts at regional scale. Its main goal is the creation of a computer-aided platform for vulnerability assessment of grasslands, in interaction with stakeholders from a cluster of eco-enterprises. A modelling engine provided by the mechanistic, biogeochemical model PaSim (Pasture Simulation model) is the core of the platform. An action studies the changes of scales by varying the granularity of the data available at a given scale (e.g. climate data supplied by global scenarios) to let them being exploited at another scale (e.g. high-resolution pixels). Another action is to develop an assessment framework linking modelling tools to entry data and outputs, including a variety of components: data-entry manager at different spatial resolutions; automatic computation of indicators; gap-filling and data quality check; simulation kernel with the model(s) used; device to represent results as maps and integrated indicators.  
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  Language (up) Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title FACCE MACSUR Mid-term Scientific Conference  
  Series Volume 3(S) Sassari, Italy Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy  
  Notes Approved no  
  Call Number MA @ admin @ Serial 5140  
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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 2020-06-08  
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  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 2020-06-08  
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  Notes LiveM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 5233  
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Author Sándor, R.; Ehrhardt, F.; Basso, B.; Bellocchi, G.; Bhatia, A.; Brilli, L.; Migliorati, M.D.A.; Doltra, J.; Dorich, C.; Doro, L.; Fitton, N.; Giacomini, S.J.; Grace, P.; Grant, B.; Harrison, M.T.; Jones, S.; Kirschbaum, M.U.F.; Klumpp, K.; Laville, P.; Léonard, J.; Liebig, M.; Lieffering, M.; Martin, R.; McAuliffe, R.; Meier, E.; Merbold, L.; Moore, A.; Myrgiotis, V.; Newton, P.; Pattey, E.; Recous, S.; Rolinski, S.; Sharp, J.; Massad, R.S.; Smith, P.; Smith, W.; Snow, V.; Wu, L.; Zhang, Q.; Soussana, J.F. url  doi
openurl 
  Title C and N models Intercomparison – benchmark and ensemble model estimates for grassland production Type Journal Article
  Year 2016 Publication Advances in Animal Biosciences Abbreviated Journal Advances in Animal Biosciences  
  Volume 7 Issue 03 Pages 245-247  
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  Series Volume Series Issue Edition  
  ISSN 2040-4700 ISBN Medium  
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  Notes LiveM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4868  
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