Evaluating CENTURY and Yasso soil carbon models for CO2 emissions and organic carbon stocks of boreal forest soil with Bayesian multi-model inference

Boris Ťupek, Samuli Launiainen, Mikko Peltoniemi, Risto Sievänen, Jari Perttunen, Liisa Kulmala, Timo Penttilä, Antti-Jussi Lindroos, Shoji Hashimoto, Aleksi Lehtonen

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Summary We can curb climate change by improved management decisions for the most important terrestrial carbon pool, soil organic carbon stock (SOC). However, we need to be confident we can obtain the correct representation of the simultanous effect of the input of plant litter, soil temperature and water (that could be altered by climate or management) on the decomposition of soil organic matter. In this research, we used regression and Bayesian statistics for testing process based models (Yasso07, Yasso15 and CENTURY) with soil heterotrophic respiration (Rh) and SOC, measured at four sites in Finland during 2015 and 2016. We extracted climate modifiers for calibration with Rh. The Rh values of Yasso07, Yasso15 and CENTURY models estimated with default parameterization correlated with measured monthly heterotrophic respiration. Despite a significant correlation, models on average underestimated measured soil respiration by 43%. After the Bayesian calibration, the fitted climate modifier of the Yasso07 model outperformed the Yasso15 and CENTURY models. The Yasso07 model had smaller residual mean square errors and temperature and water functions with fewer, thus more efficient, parameters than the other models. After calibration, there was a small overestimate of Rh by the models that used monotonic moisture functions and a small generic underestimate in autumn. The mismatch between measured and modelled Rh indicates that the Yasso and CENTURY models should be improved by adjusting climate modifiers of decomposition or by accounting for missing controls in e.g. microbial growth.
Original languageEnglish
JournalEuropean Journal of Soil Science
Volume0
Issue numberja
ISSN1351-0754
DOIs
Publication statusPublished - 19 Mar 2019
MoE publication typeA1 Journal article-refereed

Bibliographical note

doi: 10.1111/ejss.12805

Fields of Science

  • 1172 Environmental sciences
  • 4112 Forestry

Cite this

Ťupek, Boris ; Launiainen, Samuli ; Peltoniemi, Mikko ; Sievänen, Risto ; Perttunen, Jari ; Kulmala, Liisa ; Penttilä, Timo ; Lindroos, Antti-Jussi ; Hashimoto, Shoji ; Lehtonen, Aleksi. / Evaluating CENTURY and Yasso soil carbon models for CO2 emissions and organic carbon stocks of boreal forest soil with Bayesian multi-model inference. In: European Journal of Soil Science. 2019 ; Vol. 0, No. ja.
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Evaluating CENTURY and Yasso soil carbon models for CO2 emissions and organic carbon stocks of boreal forest soil with Bayesian multi-model inference. / Ťupek, Boris; Launiainen, Samuli; Peltoniemi, Mikko; Sievänen, Risto; Perttunen, Jari; Kulmala, Liisa; Penttilä, Timo; Lindroos, Antti-Jussi; Hashimoto, Shoji; Lehtonen, Aleksi.

In: European Journal of Soil Science, Vol. 0, No. ja, 19.03.2019.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Evaluating CENTURY and Yasso soil carbon models for CO2 emissions and organic carbon stocks of boreal forest soil with Bayesian multi-model inference

AU - Ťupek, Boris

AU - Launiainen, Samuli

AU - Peltoniemi, Mikko

AU - Sievänen, Risto

AU - Perttunen, Jari

AU - Kulmala, Liisa

AU - Penttilä, Timo

AU - Lindroos, Antti-Jussi

AU - Hashimoto, Shoji

AU - Lehtonen, Aleksi

N1 - doi: 10.1111/ejss.12805

PY - 2019/3/19

Y1 - 2019/3/19

N2 - Summary We can curb climate change by improved management decisions for the most important terrestrial carbon pool, soil organic carbon stock (SOC). However, we need to be confident we can obtain the correct representation of the simultanous effect of the input of plant litter, soil temperature and water (that could be altered by climate or management) on the decomposition of soil organic matter. In this research, we used regression and Bayesian statistics for testing process based models (Yasso07, Yasso15 and CENTURY) with soil heterotrophic respiration (Rh) and SOC, measured at four sites in Finland during 2015 and 2016. We extracted climate modifiers for calibration with Rh. The Rh values of Yasso07, Yasso15 and CENTURY models estimated with default parameterization correlated with measured monthly heterotrophic respiration. Despite a significant correlation, models on average underestimated measured soil respiration by 43%. After the Bayesian calibration, the fitted climate modifier of the Yasso07 model outperformed the Yasso15 and CENTURY models. The Yasso07 model had smaller residual mean square errors and temperature and water functions with fewer, thus more efficient, parameters than the other models. After calibration, there was a small overestimate of Rh by the models that used monotonic moisture functions and a small generic underestimate in autumn. The mismatch between measured and modelled Rh indicates that the Yasso and CENTURY models should be improved by adjusting climate modifiers of decomposition or by accounting for missing controls in e.g. microbial growth.

AB - Summary We can curb climate change by improved management decisions for the most important terrestrial carbon pool, soil organic carbon stock (SOC). However, we need to be confident we can obtain the correct representation of the simultanous effect of the input of plant litter, soil temperature and water (that could be altered by climate or management) on the decomposition of soil organic matter. In this research, we used regression and Bayesian statistics for testing process based models (Yasso07, Yasso15 and CENTURY) with soil heterotrophic respiration (Rh) and SOC, measured at four sites in Finland during 2015 and 2016. We extracted climate modifiers for calibration with Rh. The Rh values of Yasso07, Yasso15 and CENTURY models estimated with default parameterization correlated with measured monthly heterotrophic respiration. Despite a significant correlation, models on average underestimated measured soil respiration by 43%. After the Bayesian calibration, the fitted climate modifier of the Yasso07 model outperformed the Yasso15 and CENTURY models. The Yasso07 model had smaller residual mean square errors and temperature and water functions with fewer, thus more efficient, parameters than the other models. After calibration, there was a small overestimate of Rh by the models that used monotonic moisture functions and a small generic underestimate in autumn. The mismatch between measured and modelled Rh indicates that the Yasso and CENTURY models should be improved by adjusting climate modifiers of decomposition or by accounting for missing controls in e.g. microbial growth.

KW - 1172 Environmental sciences

KW - 4112 Forestry

U2 - 10.1111/ejss.12805

DO - 10.1111/ejss.12805

M3 - Article

VL - 0

JO - European Journal of Soil Science

JF - European Journal of Soil Science

SN - 1351-0754

IS - ja

ER -