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Author Wu, L.; Whitmore, A.P.; Bellocchi, G.
Title Modelling the impact of environmental changes on grassland systems with SPACSYS Type Journal Article
Year 2015 Publication Advances in Animal Biosciences Abbreviated Journal Advances in Animal Biosciences
Volume 6 Issue 01 Pages 37-39
Keywords grassland production; dynamic simulation model; primary production; ecosystem respiration
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Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN 2040-4700 2040-4719 ISBN Medium (down) Article
Area Expedition Conference
Notes CropM, LiveM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4655
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Author Sándor, R.; Ma, S.; Acutis, M.; Barcza, Z.; Ben Touhami, H.; Doro, L.; Hidy, D.; Köchy, M.; Lellei-Kovács, E.; Minet, J.; Perego, A.; Rolinski, S.; Ruget, F.; Seddaiu, G.; Wu, L.; Bellocchi, G.
Title Uncertainty in simulating biomass yield and carbon–water fluxes from grasslands under climate change Type Journal Article
Year 2015 Publication Advances in Animal Biosciences Abbreviated Journal Advances in Animal Biosciences
Volume 6 Issue 01 Pages 49-51
Keywords grassland productivity; carbon balance; model simulation; uncertainty; sensitivity
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Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2040-4700 ISBN Medium (down) Article
Area Expedition Conference
Notes CropM, LiveM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4651
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Author Sanna, M.; Bellocchi, G.; Fumagalli, M.; Acutis, M.
Title A new method for analysing the interrelationship between performance indicators with an application to agrometeorological models Type Journal Article
Year 2015 Publication Environmental Modelling & Software Abbreviated Journal Env. Model. Softw.
Volume 73 Issue Pages 286-304
Keywords model evaluation; performance indicators; stable correlation; solar-radiation; simulation-model; environmental-models; statistical-methods; crop nitrogen; validation; rice; uncertainty; calibration; software
Abstract The use of a variety of metrics is advocated to assess model performance but correlated metrics may convey the same information, thus leading to redundancy. Starting from this assumption, a method was developed for selecting, from among a collection of performance indicators, one or more subsets providing the same information as the entire set. The method, based on the definition of “stable correlation”, was applied to 23 performance indicators of agrometeorological models, calculated on large sets of simulated and observed data of four agronomic and meteorological variables: above-ground biomass, leaf area index, hourly air relative humidity and daily solar radiation. Two subsets were determined: {Squared Bias, Root Mean Squared Relative Error, Coefficient of Determination, Pattern Index, Modified Modelling Efficiency}, {Persistence Model Efficiency, Root Mean Squared Relative Error, Coefficient of Determination, Pattern Index}. The method needs corroboration but is statistically founded and can support the implementation of standardized evaluation tools. (C) 2015 Elsevier Ltd. All rights reserved.
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Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1364-8152 ISBN Medium (down) Article
Area Expedition Conference
Notes CropM LiveM, ftnotmacsur Approved no
Call Number MA @ admin @ Serial 4503
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Author Pulina, A.; Lai, R.; Salis, L.; Seddaiu, G.; Roggero, P.P.; Bellocchi, G.
Title Modelling pasture production and soil temperature, water and carbon fluxes in Mediterranean grassland systems with the Pasture Simulation Model Type Journal Article
Year 2018 Publication Grass and Forage Science Abbreviated Journal Grass Forage Sci.
Volume 73 Issue 2 Pages 272-283
Keywords grassland production; Mediterranean pastures; model calibration; PaSim; sheep grazing systems; soil respiration
Abstract Grasslands play important roles in agricultural production and provide a range of ecosystem services. Modelling can be a valuable adjunct to experimental research in order to improve the knowledge and assess the impact of management practices in grassland systems. In this study, the PaSim model was assessed for its ability to simulate plant biomass production, soil temperature, water content, and total and heterotrophic soil respiration in Mediterranean grasslands. The study site was the extensively managed sheep grazing system at the Berchidda‐Monti Observatory (Sardinia, Italy), from which two data sets were derived for model calibration and validation respectively. A new model parameterization was derived for Mediterranean conditions from a set of eco‐physiological parameters. With the exception of heterotrophic respiration (Rh), for which modelling efficiency (EF) values were negative, the model outputs were in agreement with observations (e.g., EF ranging from ~0.2 for total soil respiration to ~0.7 for soil temperature). These results support the effectiveness of PaSim to simulate C cycle components in Mediterranean grasslands. The study also highlights the need of further model development to provide better representation of the seasonal dynamics of Mediterranean annual species‐rich grasslands and associated peculiar Rh features, for which the modelling is only implicitly being undertaken by the current PaSim release.
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Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN ISBN Medium (down) article
Area LiveM Expedition Conference
Notes LiveM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4973
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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.
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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Language Summary Language Original Title
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ISSN ISBN Medium (down) Article
Area Expedition Conference
Notes LiveM Approved no
Call Number MA @ admin @ Serial 5230
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