Publication:
Multi-modelling predictions show high uncertainty of required carbon input changes to reach a 4‰ target

Consultable a partir de

Date

2022

Authors

Bruni, Elisa
Chenu, Claire
Abramoff, Rose Z.
Baldoni, Guido
Barkusky, Dietmar
Clivot, Hugues
Huang, Yuanyuan
Kätterer, Thomas
Pikula, Dorota
Spiegel, Heide

Director

Publisher

Wiley
Acceso abierto / Sarbide irekia
Artículo / Artikulua
Versión publicada / Argitaratu den bertsioa

Project identifier

European Commission/Horizon 2020 Framework Programme/101000289openaire

Abstract

Soils store vast amounts of carbon (C) on land, and increasing soil organic carbon (SOC) stocks in already managed soils such as croplands may be one way to remove C from the atmosphere, thereby limiting subsequent warming. The main objective of this study was to estimate the amount of additional C input needed to annually increase SOC stocks by 4‰ at 16 long-term agricultural experiments in Europe, including exogenous organic matter (EOM) additions. We used an ensemble of six SOC models and ran them under two configurations: (1) with default parametrization and (2) with parameters calibrated site-by-site to fit the evolution of SOC stocks in the control treatments (without EOM). We compared model simulations and analysed the factors generating variability across models. The calibrated ensemble was able to reproduce the SOC stock evolution in the unfertilised control treatments. We found that, on average, the experimental sites needed an additional 1.5 ± 1.2 Mg C ha−1 year−1 to increase SOC stocks by 4‰ per year over 30 years, compared to the C input in the control treatments (multi-model median ± median standard deviation across sites). That is, a 119% increase compared to the control. While mean annual temperature, initial SOC stocks and initial C input had a significant effect on the variability of the predicted C input in the default configuration (i.e., the relative standard deviation of the predicted C input from the mean), only water-related variables (i.e., mean annual precipitation and potential evapotranspiration) explained the divergence between models when calibrated. Our work highlights the challenge of increasing SOC stocks in agriculture and accentuates the need to increasingly lean on multi-model ensembles when predicting SOC stock trends and related processes. To increase the reliability of SOC models under future climate change, we suggest model developers to better constrain the effect of water-related variables on SOC decomposition.

Keywords

4 per 1000 initiative, Agriculture, Carbon sequestration, Climate change, European targets, Multi-modelling, Soil organic carbon

Department

Ciencias / Zientziak

Faculty/School

Degree

Doctorate program

Editor version

Funding entities

This work benefited from the French state aid managed by the ANR under the “Investissements d'avenir” programme with the reference ANR-16-CONV-0003 (CLAND project). EB, RZA and BG are supported by the European Union's Horizon 2020 research and innovation program under grant agreement No 101000289 (Holisoils project). RZA was also supported by the United States Department of Energy, Office of Science, and Office of Biological and Environmental Research. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the United States Department of Energy under contract DE-AC05-00OR22725.

Creative Commons Attribution 4.0 International (CC BY 4.0)

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