Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Decreasing rainfall frequency contributes to earlier leaf onset in northern ecosystems

Abstract

Climate change substantially advances the leaf onset date (LOD) and regulates carbon uptake by plants. Unlike temperature, the effect of precipitation remains largely elusive. Here we use carbon-flux measurements, in situ records of leaf unfolding and satellite greenness observations to examine the role of precipitation frequency (Pfreq, number of rainy days) in controlling the LOD in northern ecosystems (>30° N). Widespread decreases in Pfreq during the past three decades positively contributed to the advance in LOD, possibly due to increased exposure to radiation, exhibiting a dominant control of LOD over ~10% of the area. Lower Pfreq may also enhance chilling at night and warming at daytime, consequently leading to earlier LOD. We further develop a weighted precipitation growing-degree-day algorithm that projected a generally earlier LOD than currently predicted. These results highlight the need for a comprehensive understanding of the impacts of precipitation on LOD, which is necessary for improved projections.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Temporal trends of precipitation frequency (Pfreq) in northern ecosystems (>30° N).
Fig. 2: Impact of precipitation on LOD in northern ecosystems (>30° N).
Fig. 3: Climatic response to LOD.
Fig. 4: Mechanisms of the effect of Pfreq on LOD.
Fig. 5: Comparison of the three predictive algorithms for modelling and projections of LOD.

Similar content being viewed by others

Data availability

The in situ phenological data can be accessed from http://www.pep725.eu/ and https://www.usanpn.org/. The flux datasets can be accessed from https://fluxnet.org/. The MODIS NDVI datasets can be accessed from https://modis.gsfc.nasa.gov/data/dataprod/mod13.php. The CRU TS4.00 datasets can be accessed from https://crudata.uea.ac.uk/cru/data/hrg/. The AgERA5 data can be accessed from https://cds.climate.copernicus.eu. The TerraClimate data can be accessed from http://www.climatologylab.org/terraclimate.html. The CPC datasets can be accessed from https://psl.noaa.gov/. The data for future climates (2019–2099) are available at https://esg.pik-potsdam.de/search/isimip/.

Code availability

The codes used for data analysis in this study are available on Zenodo at https://doi.org/10.5281/zenodo.5801049.

References

  1. Keenan, T. F. et al. Net carbon uptake has increased through warming-induced changes in temperate forest phenology. Nat. Clim. Change 4, 598–604 (2014).

    Article  CAS  Google Scholar 

  2. Barichivich, J. et al. Large-scale variations in the vegetation growing season and annual cycle of atmospheric CO2 at high northern latitudes from 1950 to 2011. Glob. Change Biol. 19, 3167–3183 (2013).

    Article  Google Scholar 

  3. Vitasse, Y. et al. Assessing the effects of climate change on the phenology of European temperate trees. Agr. Forest Meteorol. 151, 969–980 (2011).

    Article  Google Scholar 

  4. Menzel, A. et al. European phenological response to climate change matches the warming pattern. Glob. Change Biol. 12, 1969–1976 (2006).

    Article  Google Scholar 

  5. Fu, Y. H. et al. Declining global warming effects on the phenology of spring leaf unfolding. Nature 526, 104–107 (2015).

    Article  CAS  Google Scholar 

  6. Wang, H. et al. Overestimation of the effect of climatic warming on spring phenology due to misrepresentation of chilling. Nat. Commun. 11, 4945 (2020).

    Article  CAS  Google Scholar 

  7. Myneni, R. C. et al. Increased plant growth in the northern high latitudes from 1981 to 1991. Nature 386, 698–702 (1997).

    Article  CAS  Google Scholar 

  8. Piao, S. et al. Leaf onset in the Northern Hemisphere triggered by daytime temperature. Nat. Commun. 6, 6911 (2015).

    Article  CAS  Google Scholar 

  9. Richardson, A. D. et al. Influence of spring and autumn phenological transitions on forest ecosystem productivity. Phil. Trans. R. Soc. B 365, 3227–3246 (2010).

    Article  Google Scholar 

  10. Piao, S. et al. Plant phenology and global climate change: current progresses and challenges. Glob. Change Biol. 25, 1922–1940 (2019).

    Article  Google Scholar 

  11. White, A., Cannell, M. G. R. & Friend, A. D. The high-latitude terrestrial carbon sink: a model analysis. Glob. Change Biol. 6, 227–245 (2000).

    Article  Google Scholar 

  12. Piao, S. et al. Net carbon dioxide losses of northern ecosystems in response to autumn warming. Nature 451, 49–53 (2008).

    Article  CAS  Google Scholar 

  13. Fu, Y. H. et al. Unexpected role of winter precipitation in determining heat requirement for spring vegetation green-up at northern middle and high latitudes. Glob. Change Biol. 20, 3743–3755 (2014).

    Article  Google Scholar 

  14. Yun, J. et al. Influence of winter precipitation on spring phenology in boreal forests. Glob. Change Biol. 11, 5176–5187 (2018).

    Article  Google Scholar 

  15. Fu, Y. H. et al. Increased heat requirement for leaf flushing in temperate woody species over 1980–2012: effects of chilling, precipitation and insolation. Glob. Change Biol. 21, 2687–2697 (2015).

    Article  Google Scholar 

  16. Wipf, S., Stoeckli, V. & Bebi, P. Winter climate change in alpine tundra: plant responses to changes in snow depth and snowmelt timing. Climatic Change 94, 105–121 (2009).

    Article  Google Scholar 

  17. Peñuelas, J. et al. Complex spatiotemporal phenological shifts as a response to rainfall changes. New Phytol. 161, 837–846 (2004).

    Article  Google Scholar 

  18. Paschalis, A. et al. Rainfall manipulation experiments as simulated by terrestrial biosphere models: where do we stand? Glob. Change Biol. 26, 3336–3355 (2020).

    Article  Google Scholar 

  19. Green, J. K. et al. Regionally strong feedbacks between the atmosphere and terrestrial biosphere. Nat. Geosci. 10, 410–414 (2017).

    Article  CAS  Google Scholar 

  20. Trenberth, K. E., Dai, A., Rasmussen, R. M. & Parsons, D. B. The changing character of precipitation. Bull. Am. Meteorol. Soc. 84, 1205–1217 (2003).

    Article  Google Scholar 

  21. Qian, W., Fu, J. & Yan, Z. Decrease of light rain events in summer associated with a warming environment in China during 1961–2005. Geophys. Res. Lett. 34, L11705 (2007).

    Article  Google Scholar 

  22. Sun, Y., Solomon, S., Dai, A. & Portmann, R. W. How often will it rain? J. Clim. 20, 4801–4818 (2007).

    Article  Google Scholar 

  23. Chou, C. et al. Mechanisms for global warming impacts on precipitation frequency and intensity. J. Clim. 13, 3291–3306 (2012).

    Article  Google Scholar 

  24. Held, I. M. & Soden, B. J. Robust responses of the hydrological cycle to global warming. J. Clim. 19, 5686–5699 (2006).

    Article  Google Scholar 

  25. Fowler, M. D., Kooperman, G. J., Randerson, J. T. & Pritchard, M. S. The effect of plant physiological responses to rising CO2 on global streamflow. Nat. Clim. Change 9, 873–879 (2019).

    Article  CAS  Google Scholar 

  26. Belnap, J., Phillips, S. L. & Miller, M. E. Response of desert biological soil crusts to alterations in precipitation frequency. Oecologia 141, 306–316 (2004).

    Article  Google Scholar 

  27. Knapp, A. K. et al. Consequences of more extreme precipitation regimes for terrestrial ecosystems. Bioscience 58, 811–821 (2008).

    Article  Google Scholar 

  28. Chen, L. et al. Leaf senescence exhibits stronger climatic responses during warm than during cold autumns. Nat. Clim. Change 10, 777–780 (2020).

    Article  CAS  Google Scholar 

  29. De Boeck, H. J., Dreesen, F. E., Janssens, I. A. & Nijs, I. Climatic characteristics of heat waves and their simulation in plant experiments. Glob. Change Biol. 16, 1992–2000 (2010).

    Article  Google Scholar 

  30. Shen, M. et al. Precipitation impacts on vegetation spring phenology on the Tibetan Plateau. Glob. Change Biol. 21, 3647–3656 (2015).

    Article  Google Scholar 

  31. Peaucelle, M. et al. Spatial variance of spring phenology in temperate deciduous forests is constrained by background climatic conditions. Nat. Commun. 10, 5388 (2019).

    Article  Google Scholar 

  32. Estiarte, M. & Peñuelas, J. Alteration of the phenology of leaf senescence and fall in winter deciduous species by climate change: effects on nutrient proficiency. Glob. Change Biol. 21, 1005–1017 (2015).

    Article  Google Scholar 

  33. Austin, A. T. et al. Water pulses and biogeochemical cycles in arid and semiarid ecosystems. Oecologia 141, 221–235 (2004).

    Article  Google Scholar 

  34. White, M. A., Thornton, P. E. & Running, S. W. A continental phenology model for monitoring vegetation responses to interannual climatic variability. Glob. Biogeochem. Cycles 11, 217–234 (1997).

    Article  CAS  Google Scholar 

  35. Templ, B. et al. Pan European Phenological database (PEP725): a single point of access for European data. Int. J. Biometeorol. 62, 1109–1113 (2018).

    Article  Google Scholar 

  36. Ge, Q., Wang, H., Rutishauser, T. & Dai, J. Phenological response to climate change in China: a meta-analysis. Glob. Change Biol. 21, 265–274 (2015).

    Article  Google Scholar 

  37. Schwartz, M. D., Betancourt, J. L. & Weltzin, J. F. From Caprio’s lilacs to the USA National Phenology Network. Front. Ecol. Environ. 10, 324–327 (2012).

    Article  Google Scholar 

  38. Wu, C. et al. Interannual variability of net ecosystem productivity in forests is explained by carbon flux phenology in autumn. Glob. Ecol. Biogeogr. 22, 994–1006 (2013).

    Article  Google Scholar 

  39. Zhang, X. et al. Monitoring vegetation phenology using MODIS. Remote Sens. Environ. 84, 471–475 (2003).

    Article  Google Scholar 

  40. Shen, M. et al. Can changes in autumn phenology facilitate earlier green-up date of northern vegetation? Agr. Forest Meteorol. 291, 108077 (2020).

    Article  Google Scholar 

  41. Chen, J. et al. A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky–Golay filter. Remote Sens. Environ. 91, 332–344 (2004).

    Article  Google Scholar 

  42. Shen, M. et al. Increasing altitudinal gradient of spring vegetation phenology during the last decade on the Qinghai–Tibetan Plateau. Agr. Forest Meteorol. 189, 71–80 (2014).

    Article  Google Scholar 

  43. Wu, C. et al. Widespread decline in winds delayed autumn foliar senescence over high latitudes. Proc. Natl Acad. Sci. USA 118, e2015821118 (2021).

    Article  CAS  Google Scholar 

  44. Elmore, A. J. et al. Landscape controls on the timing of spring, autumn, and growing season length in mid-Atlantic forests. Glob. Change Biol. 18, 656–674 (2012).

    Article  Google Scholar 

  45. Olson, D. M. et al. Terrestrial ecoregions of the world: a new map of life on Earth. Bioscience 51, 933–938 (2001).

    Article  Google Scholar 

  46. Harris, I., Jones, P. D., Osborn, T. J. & Lister, D. H. Updated high-resolution grids of monthly climatic observations—the CRU TS3.10 dataset. Int. J. Climatol. 34, 623–642 (2014).

    Article  Google Scholar 

  47. New, M., Hulme, M. & Jones, P. D. Representing twentieth‐century space–time climate variability. Part I: development of a 1961–90 mean monthly terrestrial climatology. J. Clim. 12, 829–856 (1999).

    Article  Google Scholar 

  48. Hempel, S., Frieler, K., Warszawski, L., Schewe, J. & Piontek, F. A trend-preserving bias correction—the ISI-MIP approach. Earth Syst. Dynam. 4, 219–236 (2013).

    Article  Google Scholar 

  49. Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A. & Hegewisch, K. C. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015. Sci. Data 5, 170191 (2018).

    Article  Google Scholar 

  50. Vicenteserrano, S. M., Beguería, S. & López-Moreno, J. I. A multiscalar drought index sensitive to global warming: the Standardized Precipitation Evapotranspiration Index. J. Clim. 23, 1696–1718 (2010).

    Article  Google Scholar 

  51. Barr, A. G. et al. Inter‐annual variability in the leaf area index of a boreal aspen–hazelnut forest in relation to net ecosystem production. Agr. Forest Meteorol. 126, 237–255 (2004).

    Article  Google Scholar 

  52. Chen, J., Chen, W., Liu, J., Cihlar, J. & Gray, S. Annual carbon balance of Canada’s forests during 1895–1996. Glob. Biogeochem. Cycles 14, 839–849 (2000).

    Article  CAS  Google Scholar 

  53. Krinner, G. et al. A dynamic global vegetation model for studies of the coupled atmosphere–biosphere system. Glob. Biogeochem. Cycles 19, GB1015 (2005).

    Article  Google Scholar 

Download references

Acknowledgements

This study was funded by the National Science Foundation (no. 1724786). We appreciate principal investigators of flux sites for providing their valuable data for our analyses. We acknowledge all members of the PEP725, CPON and NPN networks for collecting and providing the phenological data. P.C. acknowledges support from the French state aid managed by the ANR under the Investissements d’avenir programme with the reference ANR-16-CONV-0003. J.P. was funded by the Spanish government grant PID2019-110521GB-I00, the Fundación Ramón Areces grant ELEMENTAL-CLIMATE and the Catalan government grant SGR2017-1005.

Author information

Authors and Affiliations

Authors

Contributions

J.W. and D.L. designed the research. J.W. performed research and analysed data. J.W. wrote the first draft of the manuscript. D.L., P.C. and J.P. substantially revised the manuscript with intensive suggestions.

Corresponding authors

Correspondence to Jian Wang or Desheng Liu.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Climate Change thanks Yongguang Zhang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–14 and Tables 1–4.

Reporting Summary

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, J., Liu, D., Ciais, P. et al. Decreasing rainfall frequency contributes to earlier leaf onset in northern ecosystems. Nat. Clim. Chang. 12, 386–392 (2022). https://doi.org/10.1038/s41558-022-01285-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41558-022-01285-w

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing