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Substantial forest soil carbon accrual from absorptive fine roots over decadal timescales

Nature Geoscience (2025)Cite this article

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Abstract

Forest soils hold the largest terrestrial carbon pool, derived from dead plant tissues and transformed by soil biota. Current frameworks emphasize the role of soil microbes in highly persistent forms of carbon. However, moderately persistent forms of carbon also contribute substantially to forest soil carbon pools through the iterative effects of plant litter inputs and outputs over multi-decadal timescales. These sources of soil carbon are not well constrained. Here we synthesize published field data of the finest roots (absorptive roots) of mycorrhizal woody plants across major forest ecosystem types in the Northern Hemisphere. We estimate that, owing to fast turnover and slow decomposition, the iterative effects of absorptive roots on soil carbon accrual generate 2.4 ± 0.1 MgC ha−1 over two decades, exceeding that of leaves by 65%. Further, roots associated with arbuscular mycorrhizal fungi contribute 43% more soil carbon than roots associated with ectomycorrhizal fungi, despite ectomycorrhizal forests dominating soil carbon storage in forest soils overall. We also find that specific root length, a readily measured trait, can be used as a proxy for iterative effects associated with root dynamics. Our findings thus provide a long-needed belowground metric for carbon modelling in the Earth system.

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Fig. 1: Carbon-based dynamic processes and iterative effects on soil C accrual of absorptive roots in Northern Hemisphere forests.
Fig. 2: Carbon-based dynamic processes and iterative effects on soil C accrual of absorptive roots in different forest biomes.
Fig. 3: Carbon-based dynamic processes and iterative effects on soil C accrual of absorptive roots with two mycorrhizal types.
Fig. 4: SRL is the most indicative trait of absorptive root dynamics.

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Data availability

All data used in this study are available via figshare at https://doi.org/10.6084/m9.figshare.26995555.v3 (ref. 79).

Code availability

All R code used in the analyses is available via figshare at https://doi.org/10.6084/m9.figshare.26995555.v3 (ref. 79).

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Acknowledgements

The authors thank H. Z. Ma, L. J. Xiao and X.L. Fan for providing the reference data of belowground plant biomass, belowground net primary productivity and microbial decomposition rate, P. X. Wang, C. Z. Hu, L. Y. Zhang and L. Jiang for root data collection and J. L. Peng for providing R code assistance. L.K. and S.N. acknowledge funding support from the National Key Research and Development Program of China (grant no. 2022YFF0802100); L.K. from the National Natural Science Foundation of China (grant no. 32222059), H.W. from the National Natural Science Foundation of China (grant no. 32330071), G.T.F. from Laboratoires d’Excellence (LabEx) TULIP (grant no. ANR-10-LABX-41) and P.B.R. from the US National Science Foundation ASCEND Biology Integration Institute (grant no. NSF-DBI-2021898).

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Author notes

  1. These authors contributed equally: Ning Ma, Shenggong Li.

Authors and Affiliations

  1. Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

    Ning Ma, Shenggong Li, Huimin Wang, Shuli Niu, Bo Zhao, Decai Gao, Yuanyuan Huang, Xiaoli Fu, Xiaoqin Dai, Shengwang Meng, Jiajia Zheng, Fengting Yang & Liang Kou

  2. Qianyanzhou Ecological Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

    Ning Ma, Huimin Wang, Decai Gao, Xiaoli Fu, Xiaoqin Dai, Shengwang Meng, Jiajia Zheng, Fengting Yang & Liang Kou

  3. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China

    Ning Ma, Shenggong Li, Huimin Wang, Shuli Niu, Rongtian Zhao, Xiaoli Fu & Liang Kou

  4. Center for Tree Science, The Morton Arboretum, Lisle, IL, USA

    M. Luke McCormack

  5. Theoretical and Experimental Ecology Station, CNRS, Moulis, France

    Grégoire T. Freschet

  6. Laboratoire des Sciences du Climat et de l’Environnement, CEA/CNRS/UVSQ/Université Paris Saclay, Gif-sur-Yvette, France

    Philippe Ciais & Bo Zhao

  7. Department of Forest Resources, University of Minnesota, St. Paul, MN, USA

    Peter B. Reich

  8. Hawkesbury Institute for the Environment, Western Sydney University, Penrith, New South Wales, Australia

    Peter B. Reich

  9. Institute for Global Change Biology and School for Environment and Sustainability, University of Michigan, Ann Arbor, MI, USA

    Peter B. Reich

  10. State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China

    Miaomiao Zhang

  11. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

    Rongtian Zhao & Yuanyuan Huang

  12. Swiss Federal Research Institute WSL, Birmensdorf, Switzerland

    Arthur Gessler

  13. Institute of Terrestrial Ecosystems, ETH Zurich, Zurich, Switzerland

    Arthur Gessler

  14. Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, School of Forestry, Northeast Forestry University, Harbin, China

    Jiacun Gu

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  1. Ning Ma
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Contributions

L.K., S.L. and N.M. conceptualized the work. N.M., S.L., L.K., M.Z., R.Z., M.L.M., G.T.F., D.G. and B.Z. performed the data analyses. L.K., S.L., N.M., M.L.M., G.T.F., P.C., H.W., S.N., P.B.R., M.Z., R.Z., B.Z., D.G., A.G., Y.H., J.G., X.F., X.D., S.M., J.Z. and F.Y. contributed to framing and interpretation. N.M., L.K., M.Z. and R.Z. performed the data visualization. N.M., L.K. and S.L. wrote the original draft. All authors reviewed and commented on the manuscript.

Corresponding author

Correspondence to Liang Kou.

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Nature Geoscience thanks Björn Berg and Cindy Prescott for their contribution to the peer review of this work. Primary Handling Editors: Tamara Goldin and Xujia Jiang, in collaboration with the Nature Geoscience team.

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Extended data

Extended Data Fig. 1 Geographic locations of 328 forest sites across the Northern Hemisphere.

Different colors show three absorptive root processes. The size of each point indicates the number of observations in the same forest site.

Extended Data Fig. 2 Absorptive root-derived C flow and first-year absorptive root mass loss.

(a) Carbon inflow (0.66 PgC, green bar) and outflow (0.14 PgC, the light green part) are derived from annual absorptive root dynamics. (b) The percentage of absorptive root litter mass loss in first-year decomposition. Dots represent values of individual observations, and n represents the number of observations. The black point represents the mean value. The vertical black line represents the standard deviation around the mean value.

Extended Data Fig. 3 Microbial-derived soil C accrual through their iterative dynamics on a yearly scale.

Grey bars show soil C accrual of absorptive root dynamics through iterative effects across years.

Extended Data Fig. 4 Individual effects of seven predictors on absorptive root (a) biomass, (b) turnover, and (c) decomposition quantified by the hierarchical and variation partitioning for canonical analysis.

Two-sided permutation tests (n = 999) were used to assess statistical significance, without multiple comparisons. MAT, mean annual temperature; MAP, mean annual precipitation; TN, soil total nitrogen; TP, soil total phosphorus. Mycorrhizal types refer to arbuscular mycorrhizal or ectomycorrhizal; phylogeny refers to gymnosperm or angiosperm; leaf habit types refer to evergreen or deciduous species.

Extended Data Fig. 5 Trait-process relationships in absorptive roots.

All variables are log10-transformed. Dots represent values of species-mean levels and error bars show standard error around species-mean values. The grey shading around each regression line represents the 95% confidence interval. (a), (d), and (g) show relationships of root diameter (RD, mm) with root biomass (g m−2), turnover (yr−1), and decomposition rate (yr−1) by fitting linear regressions. (b), (e), and (h) show relationships of root tissue density (RTD, g cm−3) with root biomass (g m−2), turnover (yr−1), and decomposition rate (yr−1) by fitting linear regressions. (c), (f), and (i) show relationships of root nitrogen (N) concentration (mg g−1) with root biomass (g m−2), turnover (yr−1), and decomposition rate (yr−1) by fitting linear regressions. Statistical significance (P < 0.05) was tested with two-sided t-tests without multiple-comparison correction.

Extended Data Fig. 6 Relationships of traits with lifespan- and production-based turnover in absorptive roots.

The absorptive root traits include root diameter (mm), specific root length (SRL, m g−1), root tissue density (RTD, g cm−3), and root nitrogen (N, mg g−1) concentration. All variables are log10-transformed, except variables in (d). Dots represent values of species-mean levels and error bars show standard error around species-mean values. The grey shading around each regression line represents the 95% confidence interval. (a), (c), (e), and (g) show relationships between root traits and lifespan-based root turnover (yr−1) by fitting linear regressions. (b), (d), (f), and (h) show relationships between root traits and production-based root turnover (yr−1) by fitting linear regressions. Statistical significance (P < 0.05) was tested with two-sided t-tests without multiple-comparison correction.

Extended Data Table 1 Lifespan- and production-based absorptive root turnover rate across mycorrhizal groups
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Extended Data Table 2 Effects of significant predictors on three absorptive root processes
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Extended Data Table 3 Relevant information across mycorrhizal groups of absorptive roots in the same biome
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Supplementary Information

Supplementary Methods, Tables 1–5, Fig. 1 and Discussion.

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Ma, N., Li, S., McCormack, M.L. et al. Substantial forest soil carbon accrual from absorptive fine roots over decadal timescales. Nat. Geosci. (2025). https://doi.org/10.1038/s41561-025-01790-5

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