The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.
Microbial regulation of the soil carbon cycle: evidence from gene–enzyme relationships
Open accessAbstract
A lack of empirical evidence for the microbial regulation of ecosystem processes, including carbon (C) degradation, hinders our ability to develop a framework to directly incorporate the genetic composition of microbial communities in the enzyme-driven Earth system models. Herein we evaluated the linkage between microbial functional genes and extracellular enzyme activity in soil samples collected across three geographical regions of Australia. We found a strong relationship between different functional genes and their corresponding enzyme activities. This relationship was maintained after considering microbial community structure, total C and soil pH using structural equation modelling. Results showed that the variations in the activity of enzymes involved in C degradation were predicted by the functional gene abundance of the soil microbial community (R2>0.90 in all cases). Our findings provide a strong framework for improved predictions on soil C dynamics that could be achieved by adopting a gene-centric approach incorporating the abundance of functional genes into process models.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
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
Classification and Regression by randomForest
Liaw, A. I., & Wiener, M. C. (2007) · Cited by 18,594
Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003) · Department of Psychology - University of Koblenz-Landau · doi:10.23668/psycharchives.12784 · Cited by 8,975
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
TOWARD AN ECOLOGICAL CLASSIFICATION OF SOIL BACTERIA
Fierer, N., Bradford, M. A., & Jackson, R. B. (2007) · Ecology · doi:10.1890/05-1839 · Cited by 5,079
Soil bacterial and fungal communities across a pH gradient in an arable soil
Rousk, J., Bååth, E., Brookes, P. C., Lauber, C. L., Lozupone, C., Caporaso, J. G., Knight, R., & Fierer, N. (2010) · The ISME Journal · doi:10.1038/ismej.2010.58 · Cited by 4,223
Belowground biodiversity and ecosystem functioning
Bardgett, R. D., & van der Putten, W. H. (2014) · Nature · doi:10.1038/nature13855 · Cited by 3,990
Geographically Weighted Regression: The Analysis of Spatially Varying Relationships
Fotheringham, A. S., Brunsdon, C., & Charlton, M. E. (2002) · doi:10.25405/ncl.34562610 · Cited by 3,938
Soil enzymes in a changing environment: Current knowledge and future directions
Burns, R. G., DeForest, J. L., Marxsen, J., Sinsabaugh, R. L., Stromberger, M. E., Wallenstein, M. D., Weintraub, M. N., & Zoppini, A. (2013) · Soil Biology and Biochemistry · doi:10.1016/j.soilbio.2012.11.009 · Cited by 2,552
Cited by
Structure and function of the global topsoil microbiome
Bahram, M., Hildebrand, F., Forslund, S. K., Anderson, J. L., Soudzilovskaia, N. A., Bodegom, P. M., Bengtsson-Palme, J., Anslan, S., Coelho, L. P., Harend, H., et al. (2018) · Nature · doi:10.1038/s41586-018-0386-6 · Cited by 2,538
Jiao, S., Chen, W., Wang, J., Du, N., Li, Q., & Wei, G. (2018) · Microbiome · doi:10.1186/s40168-018-0526-0 · Cited by 759
Abundant fungi adapt to broader environmental gradients than rare fungi in agricultural fields
Jiao, S., & Lu, Y. (2020) · Global Change Biology · doi:10.1111/gcb.15130 · Cited by 530
Nutrient limitation of soil microbial processes in tropical forests
Camenzind, T., Hättenschwiler, S., Treseder, K. K., Lehmann, A., & Rillig, M. C. (2018) · Ecological Monographs · doi:10.1002/ecm.1279 · Cited by 454
A closer look at the functions behind ecosystem multifunctionality: A review
Garland, G., Banerjee, S., Edlinger, A., Miranda Oliveira, E., Herzog, C., Wittwer, R., Philippot, L., Maestre, F. T., & van der Heijden, M. G. A. (2021) · Journal of Ecology · doi:10.1111/1365-2745.13511 · Cited by 377
Metadata
- Authors
- Trivedi, P., Delgado-Baquerizo, M., Trivedi, C., Hu, H., Anderson, I. C., Jeffries, T. C., Zhou, J., & Singh, B. K.
- Venue
- The ISME Journal
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-05-10
- Volume
- 10
- Issue
- 11
- Pages
- 2593-2604
- ISSN
- 1751-7362 (ISSN-L)
- 1751-7370
- OpenAlex
- W2354064285
- Cited by
- 628
- References
- 54
- FWCI
- 28.05
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Microbial regulation of the soil carbon cycle: evidence from gene–enzyme relationships. https://app.cochat.ai/papers/10.1038/ismej.2016.65
- The paper
- Trivedi, P., Delgado-Baquerizo, M., Trivedi, C., Hu, H., Anderson, I. C., Jeffries, T. C., Zhou, J., & Singh, B. K. (2016). Microbial regulation of the soil carbon cycle: evidence from gene–enzyme relationships. The ISME Journal. https://doi.org/10.1038/ismej.2016.65
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
