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Divergent phenological responses of soil microorganisms and plants to climate warming

Nature Geoscience volume 18, pages 753–760 (2025)Cite this article

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Abstract

Anthropogenic climate warming is altering phenology—the biological timing of life-cycle events—across trophic levels worldwide. However, it remains unclear whether warming induces differential changes in phenology between plants and soil microorganisms—two fundamental components of terrestrial biodiversity and food chains. Here we report a consistent mismatch between plant and soil microbial phenology under climate warming, on the basis of 1,032 globally distributed observations of phenological shifts in plant and/or soil microbial respiration in response to experimental warming. Advances in spring phenology and delays in autumn phenology are greater in soil microorganisms than in both plant shoots and roots, particularly under tall vegetation (for example, forests) compared with low vegetation (for example, grasslands). Furthermore, phenology shifts in soil microorganisms are greater in soils with high carbon-to-nitrogen ratios, such as those in boreal regions, than in those with lower ratios. Such phenological mismatches between plants and soil microorganisms could destabilize their temporal synchrony, decoupling above- and belowground processes, and ultimately degrading energy flow and ecosystem functioning under climate warming.

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Fig. 1: Warming study sites, phenology extraction approaches and hypotheses of phenological matching.
Fig. 2: Phenology shifts of plant and soil microbial respiration in response to warming.
Fig. 3: Key predictors for phenological shifts of plant and soil microbial respiration under warming.
Fig. 4: Phenological shifts of plant and soil microbial respiration under warming across the Northern Hemisphere (20°–90° N), along with associated prediction uncertainty, evaluated by s.d.

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Data availability

Data for the meta-analysis in this research are available in the figshare repository (https://doi.org/10.6084/m9.figshare.26317330). Climate data were obtained from WorldClim v.2.0 (http://www.worldclim.org/), soil moisture data from ESA CCI v.07.1 (https://www.esa-soilmoisture-cci.org/), other soil properties and leaf area index data from the Global Soil Dataset for Earth System Models (http://globalchange.bnu.edu.cn/) and canopy height data used for vegetation type classification from the Global 1 km Forest Canopy Height dataset (https://webmap.ornl.gov/wcsdown/dataset.jsp?ds_id=10023). Source data are provided with this paper.

Code availability

Codes for analysis will be accessible in the figshare repository (https://doi.org/10.6084/m9.figshare.26317330).

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Acknowledgements

This research was financially sponsored by the National Natural Science Foundation of China (grants 32422058 (H.W.), 32130065 (J.-S.H.), 32371618 (H.W.)), National Key Research and Development Program of China (grant 2023YFF0806800 (H.L.)) and Gansu Provincial Science and Technology Major Projects (grant 23ZDNA009 (H.W.)). M.P.T acknowledges funding from the Swiss State Secretariat for Education, Research and Innovation (SERI) under contract M822.0029.

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Author notes

  1. These authors jointly supervised this work: Hao Wang, Madhav P. Thakur.

Authors and Affiliations

  1. State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, and College of Ecology, Lanzhou University, Lanzhou, China

    Hao Wang, Huimin Zhou & Juanjuan Zhang

  2. State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, and College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, China

    Jin-Sheng He

  3. Zhejiang Tiantong Forest Ecosystem National Observation and Research Station, Institute of Eco-Chongming (IEC), Zhejiang Zhoushan Island Ecosystem Observation and Research Station, School of Ecological and Environmental Sciences, East China Normal University, Shanghai, China

    Chunyan Lu, Yixuan Huang, Juanjuan Zhang & Huiying Liu

  4. Institute of Ecology and Evolution and Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland

    Madhav P. Thakur

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Contributions

H.W. designed the research with inputs from M.P.T., J.-S. H. and H.L. H.Z., C.L., Y.H. and J.Z. compiled and analysed the data. H.W., H.Z., H.L., C.L. and M.P.T. wrote the paper.

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Correspondence to Hao Wang, Huimin Zhou or Jin-Sheng He.

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Nature Geoscience thanks Ana Asato, Gesche Blume-Werry and Nicolas Delpierre for their contribution to the peer review of this work. Primary Handling Editors: Xujia Jiang and Stefan Lachowycz, in collaboration with the Nature Geoscience team.

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Extended data

Extended Data Fig. 1 Phenological shifts of plant and soil microbial respiration in response to warming from studies with at least seven months of annual observations.

a, Ecosystem respiration, Re. b, Soil respiration, Rs. c, Soil microbial respiration, Rm. d, Plant root respiration, Rr. e, Plant aboveground respiration, Ra. The first row displays the components of each respiration metric (plant aboveground parts, roots and/or soil microorganisms, highlighted in bright colors), along with its respective observation count. The second row shows phenological shifts, while the third row displays phenological sensitivities to warming. Results are based on the absolute threshold approach. Points with error bars represent weighted means with 95% confidence intervals. Statistical significance (P < 0.05) for each phenological stage was tested using two-sided t-tests from linear mixed-effects models without multiple comparison correction.

Source data

Extended Data Fig. 2 Phenological shifts of soil microbial and plant root respiration in response to warming, based on studies that partitioned soil microbial (Rm) and root respiration (Rr).

a, Phenological shift of Rm. b, Phenological shift of Rr. c, Phenological sensitivity of Rm. d, Phenological sensitivity of Rr. Results are based on the absolute threshold approach. Points with error bars represent weighted means with 95% confidence intervals. Statistical significance (P < 0.05) for each phenological stage was tested using two-sided t-tests from linear mixed-effects models without multiple comparison correction.

Source data

Extended Data Fig. 3 Phenological sensitivity of plant and soil microbial respiration to warming, based on different phenological extraction approaches.

a, Ecosystem respiration, Re. b, Soil respiration, Rs. c, Soil microbial respiration, Rm. d, Plant root respiration, Rr. e, Plant aboveground respiration, Ra. The first row displays the components of each respiration metric (plant aboveground parts, roots and/or soil microorganisms, highlighted in bright colors), along with its respective observation count. The second and third rows depict phenological sensitivity to warming for each phenological stage, calculated using the absolute and dynamic threshold approaches, respectively. Potential outliers in phenological sensitivity (exceeding 15 days per degree of warming, based on the reported global range in Thackeray et al. (2016, ref. 3)) are removed in this analysis. Points with error bars represent weighted means with 95% confidence intervals. Statistical significance (P < 0.05) for each phenological stage was tested using two-sided t-tests from linear mixed-effects models without multiple comparison correction.

Source data

Extended Data Fig. 4 Influence of vegetation types on the phenological responses of soil microbial and plant root respiration to warming, based on studies that partitioned soil microbial (Rm) and root respiration (Rr).

a-b, Phenological shift (a) and sensitivity (b) under different vegetation types (tall vegetation and low vegetation). Results are based on the absolute threshold approach. Points with error bars represent weighted means with 95% confidence intervals. Statistical significance (P < 0.05) for each phenological stage was tested using two-sided t-tests from linear mixed-effects models without multiple comparison correction.

Source data

Extended Data Fig. 5 Influence of experimental warming and respiration partitioning methods on the phenological responses of soil microbial and plant root respiration to warming, based on studies that partitioned soil microbial (Rm) and root respiration (Rr).

a-b, Phenological shift (a) and sensitivity (b) under different warming methods (chamber, infrared heater, and heating cable). c-d, Phenological shift (c) and sensitivity (d) under different partitioning methods (trench and exclusion collars). Results are based on the absolute threshold approach. Points with error bars represent weighted means with 95% confidence intervals. Statistical significance (P < 0.05) for each phenological stage was tested using two-sided t-tests from linear mixed-effects models without multiple comparison correction.

Source data

Extended Data Fig. 6 Phenological sensitivity of soil microbial (Rm) and plant root respiration (Rr) to warming in the Northern Hemisphere (20°–90°N) and associated prediction uncertainty, evaluated by standard deviation (SD).

a, Phenological sensitivity of Rm. b, Phenological sensitivity of Rr. c, SD of phenological sensitivity of Rm. d, SD of phenological sensitivity of Rr. Phenological sensitivity is predicted using AutoML, averaged over five runs, while SD is derived from predictions across these runs. In (a-b), R2 indicates model performance based on the relationship between measured phenological sensitivities and predicted values. Numbers in brackets at the top show the percentage of pixels with advanced phenology (left) and delayed phenology (right). Comparisons are made between temperate (Tem., 2 °C ≤ Mean annual temperature ≤ 17 °C) and boreal regions (Bor., Mean annual temperature < 2 °C). Double asterisks (**) indicate statistically significant differences (P < 0.01).

Source data

Supplementary information

Supplementary Information

Supplementary Tables 2 and 3 and Figs. 1–7.

Supplementary Table 1

Summary of warming studies included in this meta-analysis.

Supplementary Dataset

Source data for Supplementary Figs. 1 and 4–7.

Source data

Source Data Fig. 1

Source data for Fig. 1a.

Source Data Fig. 2

Source data for Fig. 2.

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Source data for Fig. 3.

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Source data for Fig. 4.

Source Data Extended Data Fig. 1

Source data for Extended Data Fig. 1.

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Source data for Extended Data Fig. 5.

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Wang, H., Zhou, H., He, JS. et al. Divergent phenological responses of soil microorganisms and plants to climate warming. Nat. Geosci. 18, 753–760 (2025). https://doi.org/10.1038/s41561-025-01738-9

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