Contributors: Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia agraria = Council for Agricultural Research and Economics (CREA); Biological Research Center Hungarian Academy of Sciences; Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP); VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); University of Aberdeen; Fisica de Sistemas Pequenos, Consejo Superior de Investigaciones Cientificas; Universidad Autónoma de Madrid (UAM); Università degli Studi di Milano = University of Milan (UNIMI); Swedish University of Agricultural Sciences = Sveriges lantbruksuniversitet (SLU); Consiglio Nazionale delle Ricerche Bologna (CNR); Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS); AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); Laboratoire Agronomie et Environnement - Antenne Colmar (LAE-Colmar ); Laboratoire Agronomie et Environnement (LAE); Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); BioEcoAgro - UMR transfrontalière INRAE 1158; Université d'Artois (UA)-Université de Liège-Université de Picardie Jules Verne (UPJV)-Université du Littoral Côte d'Opale (ULCO)-Université de Lille-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-JUNIA (JUNIA); Université catholique de Lille (UCL)-Université catholique de Lille (UCL); Queensland University of Technology Brisbane (QUT); Colorado State University Fort Collins (CSU); Collège de Direction (CODIR); Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); Helmholtz-Gemeinschaft = Helmholtz Association; Manaaki Whenua – Landcare Research Lincoln; University of Ottawa Ottawa; Laboratoire de géologie de l'ENS (LGENS); Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris; École normale supérieure - Paris (ENS-PSL); Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL); Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL); Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE); Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)); Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA); Modélisation des Surfaces et Interfaces Continentales (MOSAIC); Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)); University of Tasmania Hobart, Australia (UTAS); Julius Kühn-Institut - Federal Research Centre for Cultivated Plants (JKI); Finnish Meteorological Institute (FMI); Commonwealth Scientific and Industrial Research Organisation Energy Technology (CSIRO Energy Technology); Commonwealth Scientific and Industrial Research Organisation Canberra (CSIRO); Göttingen State and University Library (SUB Göttingen); Georg-August-University = Georg-August-Universität Göttingen; Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF); University of Potsdam = Universität Potsdam; Fractionnement des AgroRessources et Environnement (FARE); Université de Reims Champagne-Ardenne (URCA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); Consejo Superior de Investigaciones Científicas Spain (CSIC); Biotechnology and Biological Sciences Research Council (BBSRC); Aarhus University Aarhus; Humboldt-Universität zu Berlin = Humboldt University of Berlin = Université Humboldt de Berlin (HU Berlin); DEVIL; SUPER-G; French-Italian Galileo program-CLIMSOC project; Joint Programming Initiative 'FACCE'; Soils-R-GRREAT; Agriculture & Agri Food Canada; Miljo- og Fodevareministeriet; ANR-16-CONV-0003,CLAND,CLAND : Changement climatique et usage des terres(2016); ANR-13-JFAC-0001,CN-MIP,C and N Models Intercomparison and Improvement to assess management options for GHG mitigation in agrosystems worldwide(2013); European Project: 774378,Horizon 2020,CIRCASA(2017)
نبذة مختصرة : International audience ; Simulation models represent soil organic carbon (SOC) dynamics in global carbon (C) cycle scenarios to support climate-change studies. It is imperative to increase confidence in long-term predictions of SOC dynamics by reducing the uncertainty in model estimates. We evaluated SOC simulated from an ensemble of 26 process-based C models by comparing simulations to experimental data from seven long-term bare-fallow (vegetation-free) plots at six sites: Denmark (two sites), France, Russia, Sweden and the United Kingdom. The decay of SOC in these plots has been monitored for decades since the last inputs of plant material, providing the opportunity to test decomposition without the continuous input of new organic material. The models were run independently over multi-year simulation periods (from 28 to 80 years) in a blind test with no calibration (Bln) and with the following three calibration scenarios, each providing different levels of information and/or allowing different levels of model fitting: (a) calibrating decomposition parameters separately at each experimental site (Spe); (b) using a generic, knowledge-based, parameterization applicable in the Central European region (Gen); and (c) using a combination of both (a) and (b) strategies (Mix). We addressed uncertainties from different modelling approaches with or without spin-up initialization of SOC. Changes in the multi-model median (MMM) of SOC were used as descriptors of the ensemble performance. On average across sites, Gen proved adequate in describing changes in SOC, with MMM equal to average SOC (and standard deviation) of 39.2 (+/- 15.5) Mg C/ha compared to the observed mean of 36.0 (+/- 19.7) Mg C/ha (last observed year), indicating sufficiently reliable SOC estimates. Moving to Mix (37.5 +/- 16.7 Mg C/ha) and Spe (36.8 +/- 19.8 Mg C/ha) provided only marginal gains in accuracy, but modellers would need to apply more knowledge and a greater calibration effort than in Gen, thereby limiting the wider applicability of models
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