Articles | Volume 16, issue 9
https://doi.org/10.5194/bg-16-1955-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-16-1955-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 May 2019
Research article |
| 13 May 2019
| 13 May 2019
Modeling soil organic carbon dynamics in temperate forests with Yasso07
INRA, UR BEF – Biogéochimie des Ecosystèmes Forestiers,
54280 Champenoux, France
Amap, INRA, CNRS, IRD, CIRAD, University Montpellier, Montpellier,
France
Delphine Derrien
INRA, UR BEF – Biogéochimie des Ecosystèmes Forestiers,
54280 Champenoux, France
Markus Didion
Swiss Federal Institute for Forest, Snow and Landscape Research
WSL, 8903 Birmensdorf, Switzerland
Jari Liski
Finnish Environment Institute, Ecosystem Change Unit, Natural
Environment Centre, Mechelininkatu 34a, P.O. Box 140, 00251 Helsinki, Finland
Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki,
Finland
Thomas Eglin
ADEME – DPED – Service Agriculture et Forêts, 49004 Angers,
France
Manuel Nicolas
Office National des Forêts, Direction Forêts et Risques
Naturels, Département Recherche-Développement-Innovation, Boulevard
de Constance, 77300 Fontainebleau, France
Mathieu Jonard
Earth and Life Institute, Université Catholique de Louvain,
Croix du Sud 2, L7.05.09, 1348 Louvain-la-Neuve, Belgium
Laurent Saint-André
INRA, UR BEF – Biogéochimie des Ecosystèmes Forestiers,
54280 Champenoux, France
CIRAD, UMR ECO&Sols, Place Viala, 34398 Montpellier Cedex 5,
France
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Cited
14 citations as recorded by crossref.
- Recent Global Distribution of Aridity Index and Land Use in Arid Regions R. Kimura & M. Moriyama 10.2151/sola.2024-011
- Analysis of Soil Carbon Stock Dynamics by Machine Learning—Polish Case Study A. Łopatka et al. 10.3390/land12081587
- Fungi determine increased soil organic carbon more than bacteria through their necromass inputs in conservation tillage croplands Y. Yang et al. 10.1016/j.soilbio.2022.108587
- Improving Yasso15 soil carbon model estimates with ensemble adjustment Kalman filter state data assimilation T. Viskari et al. 10.5194/gmd-13-5959-2020
- Silvicultural Interventions Drive the Changes in Soil Organic Carbon in Romanian Forests According to Two Model Simulations V. Blujdea et al. 10.3390/f12060795
- Combining Biophysical Modeling and Social Theory Pledges for a Re-Embedding of the Agri-Food System in 2050 in Austria J. Le Noe et al. 10.2139/ssrn.4000332
- Combining biophysical modeling and Polanyian theory pleads for a re-embedding of the agricultural system in 2050 in Austria J. Le Noë et al. 10.1016/j.envsci.2022.11.006
- Impact of Norway Spruce Pre-Degradation Stages Induced by G. Trabeum on Fungal and Bacterial Communities N. Valette et al. 10.2139/ssrn.4012421
- Maintaining biodiversity promotes the multifunctionality of social-ecological systems: holistic modelling of a mountain system Z. Mao et al. 10.1016/j.ecoser.2020.101220
- Evaluation of the Terrestrial Ecosystem Model Biome-BGCMuSo for Modelling Soil Organic Carbon under Different Land Uses M. Ostrogović Sever et al. 10.3390/land10090968
- Impact of Norway spruce pre-degradation stages induced by Gloeophyllum trabeum on fungal and bacterial communities N. Valette et al. 10.1016/j.funeco.2022.101188
- Accumulation and vertical distribution of glomalin-related soil protein in French temperate forest soils as a function of tree type, climate and soil properties G. Cissé et al. 10.1016/j.catena.2022.106635
- Carbon dynamics in tree plantings: How changes in woody biomass impact litter and soil carbon K. Paul et al. 10.1016/j.foreco.2022.120406
- Soil organic carbon models need independent time-series validation for reliable prediction J. Le Noë et al. 10.1038/s43247-023-00830-5
14 citations as recorded by crossref.
- Recent Global Distribution of Aridity Index and Land Use in Arid Regions R. Kimura & M. Moriyama 10.2151/sola.2024-011
- Analysis of Soil Carbon Stock Dynamics by Machine Learning—Polish Case Study A. Łopatka et al. 10.3390/land12081587
- Fungi determine increased soil organic carbon more than bacteria through their necromass inputs in conservation tillage croplands Y. Yang et al. 10.1016/j.soilbio.2022.108587
- Improving Yasso15 soil carbon model estimates with ensemble adjustment Kalman filter state data assimilation T. Viskari et al. 10.5194/gmd-13-5959-2020
- Silvicultural Interventions Drive the Changes in Soil Organic Carbon in Romanian Forests According to Two Model Simulations V. Blujdea et al. 10.3390/f12060795
- Combining Biophysical Modeling and Social Theory Pledges for a Re-Embedding of the Agri-Food System in 2050 in Austria J. Le Noe et al. 10.2139/ssrn.4000332
- Combining biophysical modeling and Polanyian theory pleads for a re-embedding of the agricultural system in 2050 in Austria J. Le Noë et al. 10.1016/j.envsci.2022.11.006
- Impact of Norway Spruce Pre-Degradation Stages Induced by G. Trabeum on Fungal and Bacterial Communities N. Valette et al. 10.2139/ssrn.4012421
- Maintaining biodiversity promotes the multifunctionality of social-ecological systems: holistic modelling of a mountain system Z. Mao et al. 10.1016/j.ecoser.2020.101220
- Evaluation of the Terrestrial Ecosystem Model Biome-BGCMuSo for Modelling Soil Organic Carbon under Different Land Uses M. Ostrogović Sever et al. 10.3390/land10090968
- Impact of Norway spruce pre-degradation stages induced by Gloeophyllum trabeum on fungal and bacterial communities N. Valette et al. 10.1016/j.funeco.2022.101188
- Accumulation and vertical distribution of glomalin-related soil protein in French temperate forest soils as a function of tree type, climate and soil properties G. Cissé et al. 10.1016/j.catena.2022.106635
- Carbon dynamics in tree plantings: How changes in woody biomass impact litter and soil carbon K. Paul et al. 10.1016/j.foreco.2022.120406
- Soil organic carbon models need independent time-series validation for reliable prediction J. Le Noë et al. 10.1038/s43247-023-00830-5
Latest update: 17 Apr 2024
Short summary
In a context of global changes, modeling and predicting the dynamics of soil carbon stocks in forest ecosystems are vital but challenging. Yasso07 is considered to be one of the most promising models for such a purpose. We examine the accuracy of its prediction of soil carbon dynamics over the whole French metropolitan territory at a decennial timescale. We revealed how the bottleneck in soil carbon modeling is linked with the lack of knowledge on soil carbon quality and fine-root litter.
In a context of global changes, modeling and predicting the dynamics of soil carbon stocks in...
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