Abstract
The timing of spring phenology represents a critical trade-off between growing season extension and frost risk avoidance, the balance of which governs plant fitness and shapes plant species’ distributions. However, few quantitative assessments exist, indicating that this trade-off is largely untested empirically. Here, we present a global meta-analysis encompassing 193 plant species across 126 study sites, finding consistently high freezing resistance (to −12 °C) with remarkably low lethal frost risk (safety margin of 17 °C) during spring emergence. Under projected climate warming scenarios, predictions indicate that advances in spring phenology do not affect the lethal frost risk under light and moderate warming scenarios. This is likely due to the reduced temperature sensitivity, consistent with trade-off predictions. By contrast, in the high-warming scenario, the freezing safety margin is predicted to expand (by ~1.7 °C), resulting in a lower lethal frost risk. This expansion may compensate for the diminished freezing resistance predicted under extreme warming. Our findings challenge the conventional view that simple environmental factors moderate spring phenology, and highlight the necessity of incorporating biotic factors (e.g., freezing resistance) and biotic processes (e.g., early growth versus frost risk trade-offs) into next-generation phenological models to enhance prediction accuracy under climate change.
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Data availability
All data used in this study are available and stored in Figshare repository: https://doi.org/10.6084/m9.figshare.2887707278. All data supporting the results are available as follows: WorldClim Database, www.worldclim.com; Climatic Research Unit (CRU TS Version 4.06), crudata.uea.ac.uk; USDA Plants Database, plants.usda.gov; China Flora/Fauna Handbook (CFH search), www.cfh.ac.cn; Future climatic data with three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5) derived from Coupled Model Inter-Comparison Project Phase 6 (CMIP6), esgf-node.llnl.gov/ projects/cmip6/. Source data are provided with this paper.
Code availability
All figures generate, models and statistical background were performed using R 4.4.2 and MATLAB R2022b, the complete codes used to generate the results reported in this study are available in the Figshare repository: https://doi.org/10.6084/m9.figshare.2887707278.
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Acknowledgements
We sincerely thank the editor and the anonymous reviewers for their insightful comments that substantially improved this paper. This research was financially sponsored by the National Natural Science Foundation of China (Grant No. 32130065 to J.-S.H.), National Key Research and Development Program Project (Grant No. 2022YFF0801902 to J.-S.H.).
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Z.J.Y. and J.-S.H. conceived the study. Z.J.Y. mobilized and processed data for the meta-analysis. Z.J.Y., Y.L., and Y.J.L. performed all analyses. Z.J.Y. wrote the first version of the paper. C.C., H.Y.L., H.W., T.Y., X.J., S.R., H.B.Z., Y.S., T.W., and J.-S.H. contributed to revisions of the manuscript. All authors read and approved the final version.
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Yan, Z., Chen, C., Liu, Y. et al. Quantifying the trade-off between spring phenology and lethal frost risk: a meta-analysis. Nat Commun (2026). https://doi.org/10.1038/s41467-026-70187-8
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DOI: https://doi.org/10.1038/s41467-026-70187-8
