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

Roberta Farina* (Corresponding Author), Renáta Sándor, Mohamed Abdalla, Jorge Álvaro-Fuentes, Luca Bechini, Martin A. Bolinder, Lorenzo Brilli, Claire Chenu, Hugues Clivot, Massimiliano De Antoni Migliorati, Claudia Di Bene, Christopher D. Dorich, Fiona Ehrhardt, Fabien Ferchaud, Nuala Fitton, Rosa Francaviglia, Uwe Franko, Donna Giltrap, Brian B. Grant, Bertrand GuenetMatthew T. Harrison, Miko U. F. Kirschbaum, Katrin Kuka, Liisa Kulmala, Jari Liski, Matthew J. McGrath, Elizabeth Meier, Lorenzo Menichetti, Fernando Moyano, Claas Nendel, Sylvie Recous, Nils Reibold, Anita Shepherd, Ward N. Smith, Pete Smith, Jean-Francois Soussana, Tommaso Stella, Arezoo Taghizadeh-Toosi, Elena Tsutskikh, Gianni Bellocchi

*Corresponding author for this work

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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.

Original languageEnglish
Pages (from-to)904-928
Number of pages25
JournalGlobal Change Biology
Issue number4
Early online date24 Nov 2020
Publication statusPublished - 1 Feb 2021

Bibliographical note

This study was supported by the project “C and N models inter-comparison and improvement to assess management options for GHG mitigation in agro-systems worldwide” (CN-MIP, 2014- 2017), which received funding by a multi-partner call on agricultural greenhouse gas research of the Joint Programming Initiative ‘FACCE’ through national financing bodies. S. Recous, R. Farina, L. Brilli, G. Bellocchi and L. Bechini received mobility funding by way of the French Italian GALILEO programme (CLIMSOC project). The authors acknowledge particularly the data holders for the Long Term Bare-Fallows, who made their data available and provided additional information on the sites: V. Romanenkov, B.T. Christensen, T. Kätterer, S. Houot, F. van Oort, A. Mc Donald, as well as P. Barré. The input of B. Guenet and C. Chenu contributes to the ANR “Investissements d’avenir” programme with the reference CLAND ANR-16-CONV-0003. The input of P. Smith and C. Chenu contributes to the CIRCASA project, which received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement no 774378 and the projects: DEVIL (NE/M021327/1) and Soils‐R‐GRREAT (NE/P019455/1). The input of B. Grant and W. Smith was funded by Science and Technology Branch, Agriculture and Agri-Food Canada, under the scope of project J-001793. The input of A. Taghizadeh-Toosi was funded by Ministry of Environment and Food of Denmark as part of the SINKS2 project. The input of M. Abdalla contributes to the SUPER-G project, which received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement no 774124.


  • bare‐fallow soils
  • model parametrization
  • process-based models
  • protocol for model comparison
  • Soil organic carbon dynamics


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