Articles | Volume 11, issue 12
https://doi.org/10.5194/gmd-11-4779-2018
https://doi.org/10.5194/gmd-11-4779-2018
Model description paper
 | 
30 Nov 2018
Model description paper |  | 30 Nov 2018

Modeling the effects of litter stoichiometry and soil mineral N availability on soil organic matter formation using CENTURY-CUE (v1.0)

Haicheng Zhang, Daniel S. Goll, Stefano Manzoni, Philippe Ciais, Bertrand Guenet, and Yuanyuan Huang

Related authors

Global evaluation of the nutrient-enabled version of the land surface model ORCHIDEE-CNP v1.2 (r5986)
Yan Sun, Daniel S. Goll, Jinfeng Chang, Philippe Ciais, Betrand Guenet, Julian Helfenstein, Yuanyuan Huang, Ronny Lauerwald, Fabienne Maignan, Victoria Naipal, Yilong Wang, Hui Yang, and Haicheng Zhang
Geosci. Model Dev., 14, 1987–2010, https://doi.org/10.5194/gmd-14-1987-2021,https://doi.org/10.5194/gmd-14-1987-2021, 2021
Short summary

Related subject area

Biogeosciences
Alquimia v1.0: a generic interface to biogeochemical codes – a tool for interoperable development, prototyping and benchmarking for multiphysics simulators
Sergi Molins, Benjamin J. Andre, Jeffrey N. Johnson, Glenn E. Hammond, Benjamin N. Sulman, Konstantin Lipnikov, Marcus S. Day, James J. Beisman, Daniil Svyatsky, Hang Deng, Peter C. Lichtner, Carl I. Steefel, and J. David Moulton
Geosci. Model Dev., 18, 3241–3263, https://doi.org/10.5194/gmd-18-3241-2025,https://doi.org/10.5194/gmd-18-3241-2025, 2025
Short summary
Soil nitrous oxide emissions from global land ecosystems and their drivers within the LPJ-GUESS model (v4.1)
Jianyong Ma, Almut Arneth, Benjamin Smith, Peter Anthoni, Xu-Ri, Peter Eliasson, David Wårlind, Martin Wittenbrink, and Stefan Olin
Geosci. Model Dev., 18, 3131–3155, https://doi.org/10.5194/gmd-18-3131-2025,https://doi.org/10.5194/gmd-18-3131-2025, 2025
Short summary
Parameterization toolbox for a physical–biogeochemical model compatible with FABM – a case study: the coupled 1D GOTM–ECOSMO E2E for the Sylt–Rømø Bight, North Sea
Hoa Nguyen, Ute Daewel, Neil Banas, and Corinna Schrum
Geosci. Model Dev., 18, 2961–2982, https://doi.org/10.5194/gmd-18-2961-2025,https://doi.org/10.5194/gmd-18-2961-2025, 2025
Short summary
H2MV (v1.0): global physically constrained deep learning water cycle model with vegetation
Zavud Baghirov, Martin Jung, Markus Reichstein, Marco Körner, and Basil Kraft
Geosci. Model Dev., 18, 2921–2943, https://doi.org/10.5194/gmd-18-2921-2025,https://doi.org/10.5194/gmd-18-2921-2025, 2025
Short summary
NN-TOC v1: global prediction of total organic carbon in marine sediments using deep neural networks
Naveenkumar Parameswaran, Everardo González, Ewa Burwicz-Galerne, Malte Braack, and Klaus Wallmann
Geosci. Model Dev., 18, 2521–2544, https://doi.org/10.5194/gmd-18-2521-2025,https://doi.org/10.5194/gmd-18-2521-2025, 2025
Short summary

Cited articles

Allison, S. D.: A trait-based approach for modelling microbial litter decomposition, Ecol. Lett., 15, 1058–1070, https://doi.org/10.1111/j.1461-0248.2012.01807.x, 2012. 
Allison, S. D., Wallenstein, M. D., and Bradford, M. A.: Soil-carbon response to warming dependent on microbial physiology, Nat. Geosci., 3, 336–340, https://doi.org/10.1038/ngeo846, 2010. 
Averill, C. and Waring, B.: Nitrogen limitation of decomposition and decay: How can it occur?, Glob. Change Biol., 24, 1417–1427, https://doi.org/10.1111/gcb.13980, 2018. 
Bahri, H., Rasse, D. P., Rumpel, C., Dignac, M. F., Bardoux, G., Mariotti, A.: Lignin degradation during a laboratory incubation followed by 13C isotope analysis, Soil Biol. Biochem., 40, 1916–1922, 2008. 
Barnes, P. W., Throop, H. L., Hewins, D. B., Abbene, M. L., and Archer, S. R.: Soil coverage reduces photodegradation and promotes the development of soil microbial films on dryland leaf litter, Ecosystems, 15, 311–321, 2012. 
Download
Short summary
Carbon use efficiency (CUE) of decomposers depends strongly on the organic matter quality (C : N ratio) and soil nutrient availability rather than a fixed value. A soil biogeochemical model with flexible CUE can better capture the differences in respiration rate of litter with contrasting C : N ratios and under different levels of mineral N availability than the model with fixed CUE, and well represent the effect of varying litter quality (N content) on SOM formation across temporal scales.
Share