Ensemble modelling, uncertainty and robust predictions of organic carbon in long-term bare-fallow soils

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  • Roberta Farina, CREA
  • ,
  • Renata Sándor, Hungarian Academy of Sciences, UCA
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  • Mohamed Abdalla, University of Aberdeen
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  • Jorge Álvaro-Fuentes, CSIC
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  • Luca Bechini, University of Milan
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  • Martin A. Bolinder, Swedish University of Agricultural Sciences
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  • Lorenzo Brilli, CNR
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  • Claire Chenu, Universite Paris-Saclay
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  • Hugues Clivot, BioEcoAgro, Universite de Lorraine
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  • Massimiliano De Antoni Migliorati, Queensland University of Technology
  • ,
  • Claudia Di Bene, CREA
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  • Christopher D. Dorich, Colorado State University
  • ,
  • Fiona Ehrhardt, UMR Herbivores
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  • Fabien Ferchaud, BioEcoAgro
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  • Nuala Fitton, University of Aberdeen
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  • Rosa Francaviglia, CREA
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  • Uwe Franko, Helmholtz Centre for Environmental Research
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  • Donna L. Giltrap, Landcare Research
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  • Brian B. Grant, AgriFood Canada
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  • Bertrand Guenet, Universite Paris-Saclay, PSL Research University
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  • Matthew T. Harrison, Tasmanian Institute of Agriculture
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  • Miko U.F. Kirschbaum, Landcare Research
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  • Katrin Kuka, JKI
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  • Liisa Kulmala, Finnish Meteorological Institute
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  • Jari Liski, Finnish Meteorological Institute
  • ,
  • Matthew J. McGrath, Universite Paris-Saclay
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  • Elizabeth Meier, CSIRO
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  • Lorenzo Menichetti, Swedish University of Agricultural Sciences
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  • Fernando Moyano, University of Göttingen
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  • Claas Nendel, Leibniz Centre for Agricultural Landscape Research, University of Potsdam
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  • Sylvie Recous, Universite de Reims Champagne-Ardenne
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  • Nils Reibold, University of Göttingen
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  • Anita Shepherd, University of Aberdeen, Rothamsted Research
  • ,
  • Ward N. Smith, AgriFood Canada
  • ,
  • Pete Smith, University of Aberdeen
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  • Jean François Soussana, UMR Herbivores
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  • Tommaso Stella, Leibniz Centre for Agricultural Landscape Research
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  • Arezoo Taghizadeh-Toosi
  • Elena Tsutskikh, Leibniz Centre for Agricultural Landscape Research
  • ,
  • Gianni Bellocchi, UCA

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.

OriginalsprogEngelsk
TidsskriftGlobal Change Biology
Vol/bind27
Nummer4
Sider (fra-til)904-928
Antal sider25
ISSN1354-1013
DOI
StatusUdgivet - feb. 2021

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