The DOI matches its Crossref record; 92 of the 92 references it cites were found in a registry or an index.
Depth‐dependent drivers of soil microbial necromass carbon across Tibetan alpine grasslands
Abstract
Microbial necromass carbon (C) has been considered an important contributor to persistent soil C pool. However, there still lacks large‐scale systematic observations on microbial necromass C in different soil layers, particularly for alpine ecosystems. Besides, it is still unclear whether the relative importance of biotic and abiotic variables such as plant C input and mineral properties in regulating microbial necromass C would change with soil depth. Based on the combination of large‐scale sampling along a ~2200 km transect across Tibetan alpine grasslands and biomarker analysis, together with a global data synthesis across grassland ecosystems, we observed a relatively low proportion of microbial‐derived C in Tibetan alpine grasslands compared to global grasslands (topsoil: 45.4% vs. 58.1%; subsoil: 41.7% vs. 53.7%). We also found that major determinants of microbial necromass C depended on soil depth. In topsoil, both plant C input and mineral protection exerted dominant effects on microbial necromass C. However, in subsoil, the physico‐chemical protection provided by soil clay particles, iron‐aluminum oxides, and exchangeable calcium dominantly facilitated the preservation of microbial necromass C. The differential drivers over microbial necromass C between soil depths should be considered in Earth system models for accurately forecasting soil C dynamics and its potential feedback to global warming.
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Cites
R: A Language and Environment for Statistical Computing
R Core Team (2025) · doi:10.32614/r.manuals · Cited by 352,181
Model selection and multimodel inference: a practical information-theoretic approach.
Guthery, F. S., Burnham, K. P., & Anderson, D. R. (2003) · The Journal of Wildlife Management · doi:10.2307/3802723 · Cited by 41,495
An extraction method for measuring soil microbial biomass C
Vance, E. D., Brookes, P. C., & Jenkinson, D. S. (1987) · Soil Biology and Biochemistry · doi:10.1016/0038-0717(87)90052-6 · Cited by 12,887
Dormann, C. F., Elith, J., Bacher, S., Buchmann, C., Carl, G., Carré, G., Marquéz, J. R. G., Gruber, B., Lafourcade, B., Leitão, P. J., et al. (2013) · Ecography · doi:10.1111/j.1600-0587.2012.07348.x · Cited by 9,998
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
THE VERTICAL DISTRIBUTION OF SOIL ORGANIC CARBON AND ITS RELATION TO CLIMATE AND VEGETATION
Jobbágy, E. G., & Jackson, R. B. (2000) · Ecological Applications · doi:10.1890/1051-0761(2000)010[0423:tvdoso]2.0.co;2 · Cited by 5,428
The contentious nature of soil organic matter
Lehmann, J., & Kleber, M. (2015) · Nature · doi:10.1038/nature16069 · Cited by 4,525
Cotrufo, M. F., Wallenstein, M. D., Boot, C. M., Denef, K., & Paul, E. (2013) · Global Change Biology · doi:10.1111/gcb.12113 · Cited by 3,552
The importance of anabolism in microbial control over soil carbon storage
Liang, C., Schimel, J. P., & Jastrow, J. D. (2017) · Nature Microbiology · doi:10.1038/nmicrobiol.2017.105 · Cited by 3,320
Self-citationA global analysis of root distributions for terrestrial biomes
Jackson, R. B., Canadell, J., Ehleringer, J. R., Mooney, H. A., Sala, O. E., & Schulze, E. D. (1996) · Oecologia · doi:10.1007/bf00333714 · Cited by 3,071
Metadata
- Authors
- He, M., Fang, K., Chen, L., Feng, X., Qin, S., Kou, D., He, H., Liang, C., & Yang, Y.
- Venue
- Global Change Biology
- Publisher
- Wiley
- Published
- 2021-11-16
- Volume
- 28
- Issue
- 3
- Pages
- 936-949
- ISSN
- 1354-1013 (ISSN-L)
- 1365-2486
- OpenAlex
- W3208592396
- Cited by
- 253
- References
- 92
- FWCI
- 14.10
- Type
- journal article
- Language
- en
- Open access
- closed
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- He, M., Fang, K., Chen, L., Feng, X., Qin, S., Kou, D., He, H., Liang, C., & Yang, Y. (2022). Depth‐dependent drivers of soil microbial necromass carbon across Tibetan alpine grasslands. Global Change Biology. https://doi.org/10.1111/gcb.15969
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