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Warming increases the phenological mismatch between carbon sources and sinks in conifers

Nature Climate Change volume 15, pages 1363–1370 (2025)Cite this article

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Abstract

The dynamics of carbon allocation in trees affect carbon storage of forest ecosystems and atmospheric carbon dioxide concentrations on Earth. Here, using carbon fluxes and xylem phenology from 84 conifer forests across the Northern Hemisphere, we quantify the phenology of carbon sources (photosynthesis) and sinks (stem growth) along a thermal gradient from −4.4 to 18.2 °C in mean annual temperature. The onset of stem growth advances by 2.3 days per degree Celsius with rising temperatures, 2 times slower than photosynthesis. Warmer sites accumulate less chilling than colder sites, thus trees require more heat to reactivate. The ending of photosynthesis and wood formation is delayed by 2.0 days per degree Celsius. Overall, the photosynthetic season lengthens by one month more than the growing season towards the warmest sites. Climate warming tends to intensify the mismatch between the phenology of carbon sources and sinks, potentially affecting the carbon sequestration in conifer forests.

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Fig. 1: Distribution of the study sites in the Northern Hemisphere.
Fig. 2: Temporal patterns of carbon sources and sinks in conifers along a thermal gradient across biomes.
Fig. 3: The time lag in the onset between photosynthesis and wood formation and its potential explanation across biomes.
Fig. 4: Relationships between wood production and the lengths of photosynthetic and wood-growing seasons for each biome.
Fig. 5: Phenological comparisons in photosynthesis and stem growth under cold and warm climates.

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Data availability

Data generated in this study are available from https://doi.org/10.11888/Terre.tpdc.301513 (ref. 65). Wood formation raw data can be accessed using the procedure in Borealis: https://doi.org/10.5683/SP3/JRDOU1 (ref. 66). FluxSat data can be accessed from https://doi.org/10.3334/ORNLDAAC/1835 (ref. 67). Climate data can be accessed from https://doi.org/10.24381/cds.6c68c9bb (ref. 68). Details of all study sites are listed in Supplementary Material. Source data are provided with this paper.

Code availability

Code generated in this study is available from https://doi.org/10.11888/Terre.tpdc.301513 (ref. 65).

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Acknowledgements

This research was supported by the National Key R&D Program of China (2024YFF0809101), the National Natural Science Foundation of China (42271065, 42361144710, 42361144856), the Sino-German Center for Research Promotion Project (M-0393), the Youth Innovation Promotion Association Program of Chinese Academy of Sciences (2020073), the Chinese Academy of Sciences President’s International Fellowship Initiative (2025PD0108) and the State Scholarship Fund (202004910219) provided by the China Scholarship Council. This research is also a product of the FAIRWOOD project funded by the Centre for the Synthesis and Analysis of Biodiversity (CESAB) of the French Foundation for Research on Biodiversity (FRB). Other funding agencies included the Ministère des Forêts, de la Faune et des Parcs du Québec (Quebec, Canada, project number 112332139 conducted at the Direction de la recherche forestière and led by J.D.S. and G.D.), Fonds de Recherche du Québec–Nature et Technologies (AccFor, project number 309064), the Observatoire régional de recherche en forêt boréale and Forêt d’Enseignement et de Recherche Simoncouche and Université Laval’s Forêt Montmorency. R. Silvestro received the Merit scholarship for international PhD students (PBEEE) by the Fonds de Recherche du Québec–Nature et Technologies (FRQNT) and a scholarship for an internship by the Centre d’étude de la forêt (CEF) realized at the Centre for Ecological Research and Forestry Applications (CREAF). F.B. was funded, in part, by the Experiment Station of the College of Agriculture, Biotechnology and Natural Resources at the University of Nevada, Reno. V.S. appreciated the support of the Ministry of Science and Higher Education of the Russian Federation (project number FSRZ-2023-0007). C.B.K.R. acknowledges support from ‘Laboratoire d’Excellence’ ARBRE (Agence Nationale de la Recherche (ANR), Investissements d’Avenir, ANR-11-LABX-0002-01) and the SILVATECH facility (https://doi.org/10.15454/1.5572400113627854E12) for its contribution to the acquisition of wood formation data. K.Č., J.G. and P.P. were funded by the Slovenian Research and Innovation Agency (ARIS), research core funding numbers P4-0430 and P4-0015, projects J4-2541, J4-4541 and Z4-7318, while K.Č., V.G., P.P. and H.V. were also funded by the European Union’s Horizon 2020 research and innovation programme ASFORCLIC under the grant agreement 36 number 952314. V.T. was supported by the Johannes Amos Comenius Programme (P JAC), project number CZ.02.01.01/00/22_008/0004605, Natural and Anthropogenic Georisks. A. Giovannelli received funding from National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.4-Call for tender number 3138 of 16 December 2021, rectified by decree number 3175 of 18 December 2021 of the Italian Ministry of University and Research funded by the European Union–NextGeneration EU; project code CN_00000033, concession decree number 1034 of 17 June 2022 adopted by the Italian Ministry of University and Research, Unique Project Code (CUP) B83C22002930006, project title ‘National Biodiversity Future Center—NBFC’. A. Gruber was funded by the Austrian Science Fund (FWF) (grant number https://doi.org/10.55776/P34706). P.F. was funded by the Swiss National Science Foundation through projects ‘INtra-seasonal Tree growth along Elevational GRAdients in the European ALps (INTEGRAL)’ (grant number 121859), ‘Coupling stem water flow and structural carbon allocation in a warming climate: the Lötschental study case (LOTFOR)’ (grant number 150205), and ‘Calibrating Earth Observation-based impacts of drought on mountain forests by monitoring Carbon fixation and transpiration: from individual tree responses to regional scale extrapolation (CALEIDOSCOPE)’ (grant number 212902).

Author information

Authors and Affiliations

  1. State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China

    X. Li & E. Liang

  2. Laboratoire sur les écosystemes terrestres boreaux, Département des Sciences Fondamentales, Université du Québec à Chicoutimi, Chicoutimi, Quebec, Canada

    R. Silvestro, A. Deslauriers & S. Rossi

  3. CREAF, Barcelona, Spain

    M. Mencuccini

  4. Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain

    M. Mencuccini

  5. Instituto Pirenaico de Ecología, Consejo Superior de Investigaciones Científicas (IPE-CSIC), Zaragoza, Spain

    J. J. Camarero

  6. Université de Lorraine, AgroParisTech, INRAE, SILVA, Nancy, France

    C. B. K. Rathgeber

  7. Direction de la Recherche Forestière, Ministère des Ressources Naturelles et des Forêts du Québec, Québec, Quebec, Canada

    J. D. Sylvain & G. Drolet

  8. Hydrology, Climate and Climate Change Laboratory, École de technologie supérieure, Université du Québec, Montréal, Quebec, Canada

    J. D. Sylvain

  9. Centre for Functional Ecology, Associate Laboratory TERRA, Department of Life Sciences, University of Coimbra, Coimbra, Portugal

    C. Nabais & F. Campelo

  10. Istituto di Ricerca sugli Ecosistemi Terrestri, Consiglio Nazionale delle Ricerche, Sesto Fiorentino, Italy

    A. Giovannelli

  11. Department of Agricultural Sciences, University of Naples Federico II, Portici, Italy

    A. Saracino & L. Saulino

  12. Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy

    R. Guerrieri

  13. Slovenian Forestry Institute, Ljubljana, Slovenia

    J. Gričar & P. Prislan

  14. Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland

    R. L. Peters, M. V. Fonti & P. Fonti

  15. Tree Growth and Wood Physiology, TUM School of Life Sciences, Technical University of Munich, Freising, Germany

    R. L. Peters

  16. Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia

    K. Čufar

  17. School of Geography and Ocean Science, Nanjing University, Nanjing, China

    B. Yang

  18. Dipartimento di Agricoltura, Ambiente e Alimenti, Università degli Studi del Molise, Campobasso, Italy

    S. Antonucci

  19. Khakass Technical Institute, Siberian Federal University, Abakan, Russia

    E. Babushkina

  20. DendroLab, Department of Natural Resources and Environmental Science, University of Nevada, Reno, NV, USA

    F. Biondi

  21. Dipartimento Territorio e Sistemi Agro-Forestali (TeSAF), Universitá degli Studi di Padova, Legnaro, Italy

    M. Carrer

  22. Department of Geography and Regional Planning, Environmental Science Institute, University of Zaragoza, Zaragoza, Spain

    M. De Luis

  23. Department of Xylogenesis and Biomass Allocation, Domain of Environmental Effects on Terrestrial Ecosystems, Czechglobe - Global Change Research Institute, The Czech Academy of Sciences, Brno, Czech Republic

    M. Fajstavr

  24. Departamento de Biología y Geología, Física y Química Inorgánica, Universidad Rey Juan Carlos (URJC), Móstoles, Spain

    R. García-Valdés

  25. Instituto de Investigación en Cambio Global (IICG-URJC), Universidad Rey Juan Carlos, Móstoles, Spain

    R. García-Valdés

  26. Department of Botany, Leopold-Franzens University of Innsbruck, Innsbruck, Austria

    A. Gruber & W. Oberhuber

  27. Department of Wood Science and Wood Technology, Mendel University in Brno, Brno, Czech Republic

    V. Gryc & H. Vavrčík

  28. Faculty of Forestry, Izmir Katip Çelebi University, Izmir, Turkey

    A. Güney

  29. Department of Physical Geography and Geoecology, Charles University, Prague, Czech Republic

    J. Kašpar & V. Treml

  30. Department of Forest Ecology, Landscape Research Institute, Brno, Czechia

    J. Kašpar

  31. Siberian Federal University, Krasnoyarsk, Russia

    A. V. Kirdyanov, A. A. Knorre & V. Shishov

  32. V.N. Sukachev Institute of Forest SB RAS, Federal Research Center ‘Krasnoyarsk Science Center SB RAS, Krasnoyarsk, Russia

    A. V. Kirdyanov

  33. Science Department, National Park ‘Krasnoyarsk Stolby’, Krasnoyarsk, Russia

    A. A. Knorre

  34. Dipartimento di Agraria, Università Mediterranea di Reggio Calabria, Reggio Calabria, Italy

    F. Lombardi

  35. Natural Resources Institute Finland, Helsinki, Finland

    H. Mäkinen & P. Nöjd

  36. Centre for Ecological Sciences, Indian Institute of Science (IISc), Bangalore, India

    R. A. Malik & R. Sukumar

  37. Department of Botany, University of Kashmir, Kashmir, India

    R. A. Malik

  38. Institute of Geography, Johannes Gutenberg University Mainz, Mainz, Germany

    E. Martinez del Castillo & E. Ziaco

  39. Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA

    A. P. Ouimette

  40. Faculty of Agricultural, Environmental and Food Sciences, Free University of Bozen-Bolzano, Piazza Università, Bolzano, Italy

    R. Tognetti

  41. CoLAB ForestWISE - Collaborative Laboratory for Integrated Forest and Fire Management, Vila Real, Portugal

    J. Vieira

  42. Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, China

    Q. Zeng

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  1. X. Li
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  2. R. Silvestro
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  3. E. Liang
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  4. M. Mencuccini
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  5. J. J. Camarero
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  6. C. B. K. Rathgeber
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  7. J. D. Sylvain
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  8. C. Nabais
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  9. A. Giovannelli
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  10. A. Saracino
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  11. L. Saulino
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  12. R. Guerrieri
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  13. J. Gričar
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  14. P. Prislan
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  15. R. L. Peters
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  16. K. Čufar
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  17. B. Yang
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  18. S. Antonucci
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  19. E. Babushkina
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  20. F. Biondi
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  21. F. Campelo
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  22. M. Carrer
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  23. M. De Luis
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  24. A. Deslauriers
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  25. G. Drolet
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  26. M. Fajstavr
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  27. M. V. Fonti
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  28. P. Fonti
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  29. R. García-Valdés
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Contributions

X.L., R. Silvestro, M.M., E.L. and S.R. conceived the ideas and designed methodology; M.M., J.J.C., C.B.K.R., J.D.S., C.N., A. Giovannelli, A.S., L.S., R.G., J.G., P.P., R.L.P., K.Č., B.Y., S.A., E.B., F.B., F.C., M.C., M.D.L., A.D., G.D., M.F., M.V.F., P.F., A. Gruber, V.G., A. Güney, J.K., A.V.K., A.A.K., F.L., H.M., R.A.M., E.M.d.C., P.N., W.O., A.P.O., V.S., R. Sukumar, R.T., V.T., H.V., J.V., Q.Z. and E.Z. provided local wood formation data. R.G.-V. downloaded and assembled FluxSat data; X.L. and S.R. assembled the final datasets; X.L., J.D.S., M.M. and R. Silvestro analysed data; X.L. led the writing of the paper. All authors contributed to the drafts and gave final approval for publication.

Corresponding authors

Correspondence to X. Li or E. Liang.

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The authors declare no competing interests.

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Nature Climate Change thanks Daniel Metcalfe and the other, anonymous, reviewers for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Variance partitioning of phenological events among biome, species and site levels.

Results were estimated from type I ANOVA (n = 121). Abbreviations: Ph_onset, onset of photosynthesis; EL_onset, onset of cell enlargement; WT_onset, onset of wall thickening; M_onset, onset of cell maturity; EL_end, end of cell enlargement; XL_end, end of wall thickening; Ph_end, end of photosynthesis.

Source data

Extended Data Fig. 2 Permutation importance of climatic factors on the onset, end and duration of wood formation and photosynthesis.

Random forest models were used to quantify and compare the effects of climate variables on the phenological events. Model performances including the root mean squared error (RMSE) and the R2 for both the training and test set have been shown in Supplementary Table 1. Temperature, precipitation, AI represent mean annual temperature, mean total annual precipitation, mean annual aridity index, and mean annual shortwave downward radiation, respectively.

Source data

Extended Data Fig. 3 Variation in timing gaps between photosynthesis and wood formation according to mean annual temperatures.

Individual points represent species×site observations, n = 121. The r and P values indicate the correlation between onset or end gaps and mean annual temperatures of the study sites. All the relationships are significant, with P values less than 0.05.

Source data

Extended Data Fig. 4 Relationships between wood production and maximum growth rate in the Mediterranean biome.

Individual points represent species×site observations, n = 19. The r and P values indicate the correlation between wood production and maximum growth rate in this biome. The relationship is significant with P values less than 0.05.

Source data

Extended Data Fig. 5 Relationships between wood production and photosynthetic and wood growing season lengths across four biomes.

Individual points represent species×site observations, n = 121. The r and P values indicate the correlation between wood production and photosynthetic and wood growing season lengths across four biomes. The relationships are significant with P values less than 0.05.

Source data

Supplementary information

Supplementary Information

Supplementary Methods, Tables 1–11, Figs. 1–13 and References.

Reporting Summary

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Li, X., Silvestro, R., Liang, E. et al. Warming increases the phenological mismatch between carbon sources and sinks in conifers. Nat. Clim. Chang. 15, 1363–1370 (2025). https://doi.org/10.1038/s41558-025-02474-z

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