Letter | Published:

Ecosystem warming extends vegetation activity but heightens vulnerability to cold temperatures

Naturevolume 560pages368371 (2018) | Download Citation

Abstract

Shifts in vegetation phenology are a key example of the biological effects of climate change1,2,3. However, there is substantial uncertainty about whether these temperature-driven trends will continue, or whether other factors—for example, photoperiod—will become more important as warming exceeds the bounds of historical variability4,5. Here we use phenological transition dates derived from digital repeat photography6 to show that experimental whole-ecosystem warming treatments7 of up to +9 °C linearly correlate with a delayed autumn green-down and advanced spring green-up of the dominant woody species in a boreal PiceaSphagnum bog. Results were confirmed by direct observation of both vegetative and reproductive phenology of these and other bog plant species, and by multiple years of observations. There was little evidence that the observed responses were constrained by photoperiod. Our results indicate a likely extension of the period of vegetation activity by 1–2 weeks under a ‘CO2 stabilization’ climate scenario (+2.6 ± 0.7 °C), and 3–6 weeks under a ‘high-CO2 emission’ scenario (+5.9 ± 1.1 °C), by the end of the twenty-first century. We also observed severe tissue mortality in the warmest enclosures after a severe spring frost event. Failure to cue to photoperiod resulted in precocious green-up and a premature loss of frost hardiness8, which suggests that vulnerability to spring frost damage will increase in a warmer world9,10. Vegetation strategies that have evolved to balance tradeoffs associated with phenological temperature tracking may be optimal under historical climates, but these strategies may not be optimized for future climate regimes. These in situ experimental results are of particular importance because boreal forests have both a circumpolar distribution and a key role in the global carbon cycle11.

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Acknowledgements

This material is based upon work supported by the US Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for DOE under contract DE-AC05-00OR22725. Support for PhenoCam has come from the National Science Foundation (EF-1065029, EF-1702697). D. Hollinger, M. Carbone and C. Iverson provided feedback on a draft manuscript. E. Ward assisted with litter collection. For CMIP, we acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling. We thank the climate modelling groups (listed in Supplementary Note 3) for making their model output available. DOE’s Program for Climate Model Diagnosis and Intercomparison additionally provides coordinating support and led development of software infrastructure for CMIP in partnership with the Global Organization for Earth System Science Portals.

Reviewer information

Nature thanks M. Tjoelker and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

Affiliations

  1. Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA

    • Andrew D. Richardson
    • , Koen Hufkens
    • , Donald M. Aubrecht
    • , Morgan E. Furze
    •  & Bijan Seyednasrollah
  2. School of Informatics, Computing and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA

    • Andrew D. Richardson
    •  & Bijan Seyednasrollah
  3. Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, USA

    • Andrew D. Richardson
    •  & Bijan Seyednasrollah
  4. Institute for the Study of Earth, Oceans and Space, University of New Hampshire, Durham, NH, USA

    • Thomas Milliman
  5. Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA

    • Misha B. Krassovski
    • , John M. Latimer
    • , W. Robert Nettles
    • , Ryan R. Heiderman
    • , Jeffrey M. Warren
    •  & Paul J. Hanson

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Contributions

A.D.R. designed the study with input from P.J.H. A.D.R., K.H., D.M.A., T.M., M.E.F., B.S. and M.B.K. contributed PhenoCam imagery and derived data. J.M.L., W.R.N., J.M.W. and R.R.H. contributed phenological observations. J.M.W. contributed data on frost damage. M.B.K., W.R.N. and P.J.H. maintained site infrastructure including warming treatments and meteorological observations. A.D.R. assembled datasets and conducted the analysis. A.D.R. drafted the manuscript. All authors commented on and approved the final manuscript.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Andrew D. Richardson.

Extended data figures and tables

  1. Extended Data Fig. 1 Air temperature and precipitation in the SPRUCE S1 bog (August 2015 to December 2017) relative to long-term (1960–2000) means and variability.

    a, Long-term daily mean temperature (°C, ± 1 s.d. indicated by shading), compared with daily mean temperature (calculated from 30-min means, based on n = 2 sensors mounted at 2-m height in each enclosure) in a +0 °C enclosure (unheated control) and a +9.0 °C enclosure. b, Long-term monthly mean temperature (mean daily maximum and mean daily minimum indicated by shaded bars), compared with monthly mean temperature (calculated from daily means, as in a) in different experimental treatments. c, Long-term monthly mean precipitation (mm, ± 1 s.d. indicated by shading, with maxima and minima indicated by dotted lines), compared with measured monthly precipitation (n = 1 rain gauge) in the S1 bog. Source Data

  2. Extended Data Fig. 2 Decadal mean temperature change (relative to 2006–2015 mean) projections from ten CMIP5 earth system models for the SPRUCE site.

    a, Stabilization climate scenario (RCP4.5). b, High emission climate scenario (RCP8.5). Source Data

  3. Extended Data Fig. 3 Relationships between air temperature and the start and end of the photosynthetic uptake period, as derived from FLUXNET data for evergreen conifer-dominated sites.

    ad, Across-site patterns in spring (a) and autumn (b) in relation to mean annual temperature (n = 12 sites), and within-sites patterns in spring (c) and autumn (d) in relation to seasonal temperature anomalies (n = 86 site-years). Source Data

  4. Extended Data Fig. 4 Unusually warm weather in late winter, followed by extreme cold in early April, resulted in severe frost damage in the warmest enclosures at SPRUCE in 2016.

    a, Time series of daily mean air temperature, comparing plot 17 (+9.0 °C warming) and plot 19 (unheated enclosure), during the winter and spring of 2016. By the time the frost event occurred (grey shading), the daily mean temperature in plot 17 had been above freezing for over a month, but had repeatedly dropped below freezing in plot 19. b, Time series of 30-min air temperature—again comparing plot 17 and plot 19—leading up to and immediately following the frost event, which occurred on the morning of 9 April and again on 12 April. The thin red lines indicate the variability (maximum and minimum) across n = 5 temperature sensors in plot 17. c, Time series of daily GCC, the green chromatic coordinate, for Picea trees in plot 17 and plot 19. Arrows denote spring green-up dates (progressively larger arrows corresponding to 10%, 25% and 50% of seasonal amplitude) estimated from GCC. The pronounced decline in GCC in plot 17 following the frost event (grey shading) is readily apparent. Trees in plot 19 retained sufficient frost hardiness that they were undamaged, despite experiencing much colder temperatures. d, Brown frost-damaged Larix foliage in plot 17. e, Picea branches in plot 17, showing loss of most foliage from previous years, with green foliage from the 2015 flush retained only at branch tips. f, Picea branches with frost-damaged foliage from previous years, but healthy green foliage from the 2016 flush. Source Data

  5. Extended Data Table 1 Mean daily air temperature and temperature differentials associated with whole-ecosystem warming
  6. Extended Data Table 2 Effect of SPRUCE warming treatments on spring green-up and autumn green-down
  7. Extended Data Table 3 Projected future extension of the period of vegetation activity
  8. Extended Data Table 4 Effect of SPRUCE warming treatments on observed vegetative and reproductive phenological transitions (2016)
  9. Extended Data Table 5 Effect of SPRUCE warming treatments on observed vegetative and reproductive phenological transitions (2017)
  10. Extended Data Table 6 Impact of premature foliar senescence on nutrient content of L. laricina and P. mariana litter

Supplementary information

  1. Supplementary Information

    This file contains Supplementary Notes 1-6 and associated references.

  2. Reporting Summary

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DOI

https://doi.org/10.1038/s41586-018-0399-1

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