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141754 - Ensemble modelling, uncertainty and robust predictions of organic carbon in long-term bare-fallow soils.pdf (366.22 kB)

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

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posted on 2023-05-20, 19:15 authored by Farina, R, Sandor, R, Abdalla, M, Alvaro-Fuentes, J, Bechini, L, Bolinder, MA, Brilli, L, Claire, C, Clivot, H, De Antoni Migliorati, M, Di Bene, C, Dorich, CD, Ehrhardt, F, Ferchaud, F, Fitton, N, Francaviglia, R, Franko, U, Giltrap, DL, BGrant, B, Guenet, B, Matthew HarrisonMatthew Harrison, Kirschbaum, MUF, Kuka, K, Kulmala, L, Liski, J, McGrath, MJ, Meier, E, Menichetti, L, Moyano, Fernando, Nendel, C, Recous, S, Reibold, N, Shepherd, A, Smith, WN, Smith, P, Soussana, JF, Stella, T, Taghizadeh-Toosi, A, Tsutskikh, E, Bellocchi, G
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, 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 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, parameterisation 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 initialisation 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‐1 compared to the observed mean of 36.0 (±19.7) Mg C ha‐1 (last observed year), indicating sufficiently reliable SOC estimates. Moving to Mix (37.5±16.7 Mg C ha‐1) and Spe (36.8±19.8 Mg C ha‐1) 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.

Funding

Grains Research & Development Corporation

History

Publication title

Global Change Biology

ISSN

1354-1013

Department/School

Tasmanian Institute of Agriculture (TIA)

Publisher

Blackwell Publishing Ltd

Place of publication

9600 Garsington Rd, Oxford, England, Oxon, Ox4 2Dg

Rights statement

Copyright 2020 John Wiley & Sons Ltd. This is the peer reviewed version of the following article, which has been published in final form at http://dx.doi.org/10.1111/gcb.15441. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.

Repository Status

  • Restricted

Socio-economic Objectives

Soils; Climate change adaptation measures (excl. ecosystem)

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