The DOI matches its Crossref record; 56 of the 56 references it cites were found in a registry or an index.
Development of microbial‐enzyme‐mediated decomposition model parameters through steady‐state and dynamic analyses
Abstract
We developed a microbial‐enzyme‐mediated decomposition (MEND) model, based on the Michaelis‐Menten kinetics, that describes the dynamics of physically defined pools of soil organic matter (SOC). These include particulate, mineral‐associated, dissolved organic matter (POC, MOC, and DOC, respectively), microbial biomass, and associated exoenzymes. The ranges and/or distributions of parameters were determined by both analytical steady‐state and dynamic analyses with SOC data from the literature. We used an improved multi‐objective parameter sensitivity analysis (MOPSA) to identify the most important parameters for the full model: maintenance of microbial biomass, turnover and synthesis of enzymes, and carbon use efficiency (CUE). The model predicted that an increase of 2°C (baseline temperature 12°C) caused the pools of POC‐cellulose, MOC, and total SOC to increase with dynamic CUE and decrease with constant CUE, as indicated by the 50% confidence intervals. Regardless of dynamic or constant CUE, the changes in pool size of POC, MOC, and total SOC varied from −8% to 8% under +2°C. The scenario analysis using a single parameter set indicates that higher temperature with dynamic CUE might result in greater net increases in both POC‐cellulose and MOC pools. Different dynamics of various SOC pools reflected the catalytic functions of specific enzymes targeting specific substrates and the interactions between microbes, enzymes, and SOC. With the feasible parameter values estimated in this study, models incorporating fundamental principles of microbial‐enzyme dynamics can lead to simulation results qualitatively different from traditional models with fast/slow/passive pools.
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R: A Language and Environment for Statistical Computing
R Core Team (2025) · doi:10.32614/r.manuals · Cited by 352,181
Temperature sensitivity of soil carbon decomposition and feedbacks to climate change
Davidson, E. A., & Janssens, I. A. (2006) · Nature · doi:10.1038/nature04514 · Cited by 6,919
Persistence of soil organic matter as an ecosystem property
Schmidt, M. W. I., Torn, M. S., Abiven, S., Dittmar, T., Guggenberger, G., Janssens, I. A., Kleber, M., Kögel-Knabner, I., Lehmann, J., Manning, D. A. C., et al. (2011) · Nature · doi:10.1038/nature10386 · Cited by 6,057
An Introduction to Statistical Methods and Data Analysis
(1994) · Technometrics · doi:10.1080/00401706.1994.10485832 · Cited by 5,346
The global k-means clustering algorithm
Likas, A., Vlassis, N., & J. Verbeek, J. (2003) · Pattern Recognition · doi:10.1016/s0031-3203(02)00060-2 · Cited by 3,733
The global carbon dioxide flux in soil respiration and its relationship to vegetation and climate
RAICH, J. W., & SCHLESINGER, W. H. (1992) · Tellus B · doi:10.1034/j.1600-0889.1992.t01-1-00001.x · Cited by 3,486
Cornwell, W. K., Cornelissen, J. H. C., Amatangelo, K., Dorrepaal, E., Eviner, V. T., Godoy, O., Hobbie, S. E., Hoorens, B., Kurokawa, H., Pérez‐Harguindeguy, N., et al. (2008) · Ecology Letters · doi:10.1111/j.1461-0248.2008.01219.x · Cited by 2,855
Stoichiometry of soil enzyme activity at global scale
Sinsabaugh, R. L., Lauber, C. L., Weintraub, M. N., Ahmed, B., Allison, S. D., Crenshaw, C., Contosta, A. R., Cusack, D., Frey, S., Gallo, M. E., et al. (2008) · Ecology Letters · doi:10.1111/j.1461-0248.2008.01245.x · Cited by 2,593
CONTROLS ON THE DYNAMICS OF DISSOLVED ORGANIC MATTER IN SOILS: A REVIEW
Kalbitz, K., Solinger, S., Park, J.-H., Michalzik, B., & Matzner, E. (2000) · Soil Science · doi:10.1097/00010694-200004000-00001 · Cited by 2,395
Soil carbon pools and world life zones
Post, W. M., Emanuel, W. R., Zinke, P. J., & Stangenberger, A. G. (1982) · Nature · doi:10.1038/298156a0 · Cited by 2,255
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Cited by
Life and death in the soil microbiome: how ecological processes influence biogeochemistry
Sokol, N. W., Slessarev, E., Marschmann, G. L., Nicolas, A., Blazewicz, S. J., Brodie, E. L., Firestone, M. K., Foley, M. M., Hestrin, R., Hungate, B. A., et al. (2022) · Nature Reviews Microbiology · doi:10.1038/s41579-022-00695-z · Cited by 1,179
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Sinsabaugh, R. L., Manzoni, S., Moorhead, D. L., & Richter, A. (2013) · Ecology Letters · doi:10.1111/ele.12113 · Cited by 991
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Luo, Y., Ahlström, A., Allison, S. D., Batjes, N. H., Brovkin, V., Carvalhais, N., Chappell, A., Ciais, P., Davidson, E. A., Finzi, A., et al. (2016) · Global Biogeochemical Cycles · doi:10.1002/2015gb005239 · Cited by 533
Moorhead, D. L., Rinkes, Z. L., Sinsabaugh, R. L., & Weintraub, M. N. (2013) · Frontiers in Microbiology · doi:10.3389/fmicb.2013.00223 · Cited by 455
Geyer, K. M., Kyker-Snowman, E., Grandy, A. S., & Frey, S. D. (2016) · Biogeochemistry · doi:10.1007/s10533-016-0191-y · Cited by 409
Metadata
- Authors
- Wang, G., Post, W. M., & Mayes, M. A.
- Venue
- Ecological Applications
- Publisher
- Wiley
- Published
- 2013-01
- Volume
- 23
- Issue
- 1
- Pages
- 255-272
- ISSN
- 1051-0761 (ISSN-L)
- 1939-5582
- OpenAlex
- W2123615179
- Cited by
- 285
- References
- 56
- FWCI
- 19.73
- Type
- journal article
- Language
- en
- Open access
- closed
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