The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Root and rhizomicrobial respiration: A review of approaches to estimate respiration by autotrophic and heterotrophic organisms in soil
Abstract
Partitioning the root‐derived CO 2 efflux from soil (frequently termed rhizosphere respiration) into actual root respiration (RR, respiration by autotrophs) and rhizomicrobial respiration (RMR, respiration by heterotrophs) is crucial in determining the carbon (C) and energy balance of plants and soils. It is also essential in quantifying C sources for rhizosphere microorganisms and in estimation of the C contributing to turnover of soil organic matter (SOM), as well as in linking net ecosystem production (NEP) and net ecosystem exchange (NEE). Artificial‐environment studies such as hydroponics or sterile soils yield unrealistic C‐partitioning values and are unsuitable for predicting C flows under natural conditions. To date, several methods have been suggested to separate RR and RMR in nonsterile soils: 1) component integration, 2) substrate‐induced respiration, 3) respiration by excised roots, 4) comparison of root‐derived 14 CO 2 with rhizomicrobial 14 CO 2 after continuous labeling, 5) isotope dilution, 6) model‐rhizodeposition technique, 7) modeling of 14 CO 2 efflux dynamics, 8) exudate elution, and 9) δ 13 C of CO 2 and microbial biomass. This review describes the basic principles and assumptions of these methods and compares the results obtained in the original papers and in studies designed to compare the methods. The component‐integration method leads to strong disturbance and non‐proportional increase of CO 2 efflux from different sources. Four of the methods (5 to 8) are based on the pulse labeling of shoots in a 14 CO 2 atmosphere and subsequent monitoring of 14 CO 2 efflux from the soil. The model‐rhizodeposition technique and exudate‐elution procedure strongly overestimate RR and underestimate RMR. Despite alternative assumptions, isotope dilution and modeling of 14 CO 2‐efflux dynamics yield similar results. In crops and grasses (wheat, ryegrass, barley, buckwheat, maize, meadow fescue, prairie grasses), RR amounts on average to 48±5% and RMR to 52±5% of root‐derived CO 2. The method based on the 13 C isotopic signature of CO 2 and microbial biomass is the most promising approach, especially when the plants are continuously labeled in 13 CO 2 or 14 CO 2 atmosphere. The “difference” methods, i.e., trenching, tree girdling, root‐exclusion techniques, etc., are not suitable for separating the respiration by autotrophic and heterotrophic organisms because the difference methods neglect the importance of microbial respiration of rhizodeposits.
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
Will changes in soil organic carbon act as a positive or negative feedback on global warming?
Kirschbaum, M. U. F. (2000) · Biogeochemistry · doi:10.1023/a:1006238902976 · Cited by 793
Cited by
Measurements necessary for assessing the net ecosystem carbon budget of croplands
Smith, P., Lanigan, G., Kutsch, W. L., Buchmann, N., Eugster, W., Aubinet, M., Ceschia, E., Béziat, P., Yeluripati, J. B., Osborne, B., et al. (2010) · Agriculture, Ecosystems & Environment · doi:10.1016/j.agee.2010.04.004 · Cited by 308
Zatta, A., Clifton‐Brown, J., Robson, P., Hastings, A., & Monti, A. (2014) · GCB Bioenergy · doi:10.1111/gcbb.12054 · Cited by 104
Tillage and Corn Residue Harvesting Impact Surface and Subsurface Carbon Sequestration
Clay, D. E., Reicks, G., Carlson, C. G., Moriles-Miller, J., Stone, J. J., & Clay, S. A. (2015) · Journal of Environmental Quality · doi:10.2134/jeq2014.07.0322 · Cited by 38
Metadata
- Authors
- Kuzyakov, Y., & Larionova, A. A.
- Venue
- Journal of Plant Nutrition and Soil Science
- Publisher
- Wiley
- Published
- 2005-07-27
- Volume
- 168
- Issue
- 4
- Pages
- 503-520
- ISSN
- 1436-8730 (ISSN-L)
- 1522-2624
- OpenAlex
- W2099016234
- Cited by
- 246
- References
- 1
- FWCI
- 13.03
- Type
- journal article
- Language
- en
- Open access
- closed
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: Root and rhizomicrobial respiration: A review of approaches to estimate respiration by autotrophic and heterotrophic organisms in soil. https://app.cochat.ai/papers/10.1002/jpln.200421703
- The paper
- Kuzyakov, Y., & Larionova, A. A. (2005). Root and rhizomicrobial respiration: A review of approaches to estimate respiration by autotrophic and heterotrophic organisms in soil. Journal of Plant Nutrition and Soil Science. https://doi.org/10.1002/jpln.200421703
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.