Preprints
https://doi.org/10.5194/gmd-2023-242
https://doi.org/10.5194/gmd-2023-242
Submitted as: model evaluation paper
 | 
19 Jan 2024
Submitted as: model evaluation paper |  | 19 Jan 2024
Status: a revised version of this preprint was accepted for the journal GMD and is expected to appear here in due course.

Radiocarbon analysis reveals underestimation of soil organic carbon persistence in new-generation soil models

Alexander S. Brunmayr, Frank Hagedorn, Margaux Moreno Duborgel, Luisa I. Minich, and Heather D. Graven

Abstract. Reflecting recent advances in our understanding of soil organic carbon (SOC) turnover and persistence, a new generation of models increasingly makes the distinction between the more labile soil particulate organic matter (POM) and the more persistent mineral-associated organic matter (MAOM). Unlike the typically poorly defined conceptual pools of traditional SOC models, the POM and MAOM pools can be directly measured for their carbon content and isotopic composition, allowing for pool-specific data assimilation. However, the new-generation models' predictions of POM and MAOM dynamics have not yet been validated with pool-specific carbon and 14C observations. In this study, we evaluate 5 influential and actively developed new-generation models (CORPSE, Millennial, MEND, MIMICS, SOMic) with pool-specific and bulk soil 14C measurements of 77 mineral topsoil profiles in the International Soil Radiocarbon Database (ISRaD). We find that all 5 models consistently overestimate the 14C content (Δ14C) of POM by 67 ‰ on average, and 3 out of the 5 models also strongly overestimate the Δ14C of MAOM by 74 ‰ on average, indicating that the models generally overestimate the turnover rates of SOC and do not adequately represent the long-term stabilization of carbon in soils. These results call for more widespread usage of pool-specific carbon and 14C measurements for parameter calibration, and may even suggest that some new-generation models might need to restructure their simulated pools (e.g., by adding inert pools to POM and MAOM) in order to accurately reproduce SOC dynamics.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Alexander S. Brunmayr, Frank Hagedorn, Margaux Moreno Duborgel, Luisa I. Minich, and Heather D. Graven

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Comment on gmd-2023-242', Juan Antonio Añel, 26 Jan 2024
    • AC1: 'Reply on CEC1', Alexander Brunmayr, 27 Jan 2024
  • RC1: 'Comment on gmd-2023-242', Jeffrey Beem Miller, 02 Feb 2024
    • AC2: 'Reply on RC1', Alexander Brunmayr, 13 May 2024
  • RC2: 'Comment on gmd-2023-242', Anonymous Referee #2, 18 Feb 2024
    • AC3: 'Reply on RC2', Alexander Brunmayr, 13 May 2024

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Comment on gmd-2023-242', Juan Antonio Añel, 26 Jan 2024
    • AC1: 'Reply on CEC1', Alexander Brunmayr, 27 Jan 2024
  • RC1: 'Comment on gmd-2023-242', Jeffrey Beem Miller, 02 Feb 2024
    • AC2: 'Reply on RC1', Alexander Brunmayr, 13 May 2024
  • RC2: 'Comment on gmd-2023-242', Anonymous Referee #2, 18 Feb 2024
    • AC3: 'Reply on RC2', Alexander Brunmayr, 13 May 2024
Alexander S. Brunmayr, Frank Hagedorn, Margaux Moreno Duborgel, Luisa I. Minich, and Heather D. Graven

Model code and software

evaluate-SOC-models Alexander S. Brunmayr https://github.com/asb219/evaluate-SOC-models

Alexander S. Brunmayr, Frank Hagedorn, Margaux Moreno Duborgel, Luisa I. Minich, and Heather D. Graven

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Short summary
A new generation of soil models promises to more accurately predict the carbon cycle in soils under climate change. However, measurements of 14C (the radioactive carbon isotope) in soils reveal that the new soil models face similar problems as the traditional models: they underestimate the residence time of carbon in soils and may therefore overestimate the net uptake of CO2 by the land ecosystem. Proposed solutions include restructuring the models and calibrating model parameters with 14C data.