Temperature as a potent driver of regional forest drought stress and tree mortality

Journal name:
Nature Climate Change
Volume:
3,
Pages:
292–297
Year published:
DOI:
doi:10.1038/nclimate1693
Received
Accepted
Published online

Abstract

As the climate changes, drought may reduce tree productivity and survival across many forest ecosystems; however, the relative influence of specific climate parameters on forest decline is poorly understood. We derive a forest drought-stress index (FDSI) for the southwestern United States using a comprehensive tree-ring data set representing AD 1000–2007. The FDSI is approximately equally influenced by the warm-season vapour-pressure deficit (largely controlled by temperature) and cold-season precipitation, together explaining 82% of the FDSI variability. Correspondence between the FDSI and measures of forest productivity, mortality, bark-beetle outbreak and wildfire validate the FDSI as a holistic forest-vigour indicator. If the vapour-pressure deficit continues increasing as projected by climate models, the mean forest drought-stress by the 2050s will exceed that of the most severe droughts in the past 1,000 years. Collectively, the results foreshadow twenty-first-century changes in forest structures and compositions, with transition of forests in the southwestern United States, and perhaps water-limited forests globally, towards distributions unfamiliar to modern civilization.

At a glance

Figures

  1. Correlation between the FDSI and climate.
    Figure 1: Correlation between the FDSI and climate.

    a, The annual FDSI derived from tree ring-width index records (red, 1896–2007) and estimated with climate data using equation (1) (black, 1896–2012). See Supplementary Fig. S3 for estimated confidence ranges in the FDSI values. b, Curves show correlation between the estimated and the actual FDSI, allowing predictive contributions of the warm-season VPD and cold-season precipitation to vary from 0 to 100% and 100 to 0%, respectively. The straight lines connect optimal correlations with axes. Grey areas represent 95% confidence intervals.

  2. Measurements of forest productivity and mortality overlaid on the FDSI (red, right
y axis).
    Figure 2: Measurements of forest productivity and mortality overlaid on the FDSI (red, right y axis).

    a, The annual average late-June to early-August NDVI calculated from satellite (1981–1999: AVHRR, 2000–2012: MODIS) imagery. b, Annual forest inventory and analysis measurements of the percentage of standing dead trees in the SWUS for the three most common conifer species. Error bars represent standard deviation of the percentage dead when each year’s forest inventory and analysis measurements are randomly resampled 1,000 times (Supplementary Information). c, Aerial-survey-derived estimates of the area where ≥10 trees per acre were killed by bark-beetle attack. d, Satellite-derived moderately and severely burned forest and woodland area in the SWUS. See Supplementary Information and Supplementary Fig. S4 for methods to calculate burned area. The inset shows the percentage of years within a given FDSI class that were top-10% fire-scar years during AD1650–1899 (the horizontal line is at the expected frequency of 10%, bins are 0.25 FDSI units wide). In all panels, the FDSI values for 2008–2012 (open red squares) were estimated by applying climate data to equation (1). Note the inverted y axes for the FDSI in bd.

  3. Eleven-year smoothed FDSI for AD[thinsp]1000-2012.
    Figure 3: Eleven-year smoothed FDSI for AD1000–2012.

    Black area: 95% confidence range of the FDSI, representing the range of FDSI values expected if all 335 chronologies were available. Vertical grey areas highlight drought events.

  4. Observed and modelled climate and forest drought-stress.
    Figure 4: Observed and modelled climate and forest drought-stress.

    ad, The warm-season VPD (a), warm-season Tmax (b), cold-season precipitation (c) and the FDSI (d). Black: observed records. Coloured bold lines: CMIP3 ensemble mean values. Shading around time series: inner 50% of CMIP3 values. Green time series: 2042–2069 dynamically downscaled NARCCAP ensemble mean values. Horizontal brown line and shading in d show the mean and 95% confidence FDSI values of the most severe 50% of years during the 1572–1587 megadrought. The horizontal grey lines show the anomaly in standard deviations from the observed 1896–2007 mean (right y axis). See Supplementary Figs S5 and S6 for individual model projections and alternative emissions scenarios.

  5. Extreme drought stress.
    Figure 5: Extreme drought stress.

    a, Cumulative distribution functions of tree-ring derived FDSI during AD1000–2007 (black) and model-projected FDSI during AD2000–2100 for the A2 (red), A1B (green) and B1 (blue) emissions scenarios. Brown line: mean FDSI during the most extreme half of the 1572–1587 megadrought. b, Fifty-year running frequency of annual FDSI values more negative than the mean FDSI during the most negative half of the years during the 1572–1587 megadrought. The colours in b represent the same as in a. Shaded areas: 95% confidence ranges for tree-ring-derived values and inner-quartile values for model ensemble projections.

  6. Where have trees died?
    Figure 6: Where have trees died?

    The x axis represents a long-term drought-stress gradient among SWUS forest grid cells. The grid cells with the most severe long-term drought-stress are on the left side of plots. a, The percentage of grid cells in each drought-stress class with ≥10 trees per acre killed by bark beetles during 1997–2011. b,The percentage of grid cells in each drought-stress class where moderate or severe wildfire occurred during 1984–2011. Horizontal dotted black lines in a and b indicate expected percentages if these mortality processes were spatially uniform. c, Probability distribution function of the average FDSI during 1896–2007 among SWUS forest grid cells. The site-specific FDSI (x axis) estimated using equation (1). The methods are described in the Supplementary Information. Grey and white shading is intended to assist with interpretation.

References

  1. Allen, C. D. et al. A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. Forest Ecol. Manage. 259, 660684 (2010).
  2. Zhao, M. & Running, S. W. Drought-induced reduction in global terrestrial net primary production from 2000 through 2009. Science 329, 940943 (2010).
  3. Van Mantgem, P. J. et al. Widespread increase of tree mortality rates in the western United States. Science 323, 521524 (2009).
  4. Beck, P. S. A. et al. Changes in forest productivity across Alaska consistent with biome shift. Ecol. Lett. 14, 373379 (2011).
  5. Breshears, D. D. et al. Regional vegetation die-off in response to global-change-type drought. Proc. Natl Acad. Sci. USA 102, 1514415148 (2005).
  6. Phillips, O. L. et al. Drought sensitivity of the Amazon rainforest. Science 323, 13441347 (2009).
  7. Lewis, S. L., Brando, P. M., Phillips, O. L., van der Heijden, G. M. F. & Nepstad, D. The 2010 amazon drought. Science 331, 554 (2011).
  8. Peng, C. et al. A drought-induced pervasive increase in tree mortality across Canada’s boreal forests. Nature Clim. Change 1, 467471 (2011).
  9. Bentz, B. J. et al. Climate change and bark beetles of the western United States and Canada: Direct and indirect effects. Bioscience 60, 602613 (2010).
  10. Schwalm, C. R. et al. Reduction in carbon uptake during turn of the century drought in western North America. Nature Geosci. 5, 551556 (2012).
  11. Williams, A. P. et al. Forest responses to increasing aridity and warmth in the southwestern United States. Proc. Natl Acad. Sci. USA 107, 2129821294 (2010).
  12. Weiss, J. L., Castro, C. L. & Overpeck, J. T. Distinguishing pronounced droughts in the southwestern United States: Seasonality and effects of warmer temperatures. J. Clim. 22, 59185931 (2009).
  13. Swetnam, T. W. & Betancourt, J. L. Mesoscale disturbance and ecological response to decadal climatic variability in the American Southwest. J. Clim. 11, 31283147 (1998).
  14. Diffenbaugh, N. S., Ashfaq, M. & Scherer, M. Transient regional climate change: Analysis of the summer climate response in a high-resolution, century-scale ensemble experiment over the continental United States. J. Geophys. Res. 116, D24111 (2011).
  15. Seager, R. et al. Model projections of an imminent transition to a more arid climate in southwestern North America. Science 316, 11811184 (2007).
  16. McDowell, N. G. et al. Mechanisms of plant survival and mortality during drought: Why do some plants survive while others succumb to drought? New Phytol. 178, 719739 (2008).
  17. Fritts, H. C. Tree Rings and Climate (Academic, 1976).
  18. Cook, E. R., Woodhouse, C. A., Eakin, C. M., Meko, D. M. & Stahle, D. W. Long-term aridity changes in the western United States. Science 306, 10151018 (2004).
  19. McDowell, N. G., Allen, C. D. & Marshall, L. Growth, carbon-isotope discrimination, and drought-associated mortality across a Pinus ponderosa elevational transect. Glob. Change Biol. 16, 399415 (2010).
  20. St. George, S., Meko, D. M. & Cook, E. R. The seasonality of precipitation signals embedded within the North American Drought Atlas. Holocene 20, 983988 (2010).
  21. Adams, H. D. et al. Temperature sensitivity of drought-induced tree mortality portends increased regional die-off under global change-type drought. Proc. Natl Acad. Sci. USA 106, 70637066 (2009).
  22. McDowell, N. G. et al. The interdependence of mechanisms underlying climate-driven vegetation mortality. Trends Ecol. Evol. 26, 523532 (2011).
  23. Shaw, J. D., Steed, B. E. & DeBlander, L. T. Forest inventory and analysis (FIA) annual inventory answers the question: What is happening to pinyon-juniper woodlands? J. Forestry 103, 280285 (2005).
  24. Huang, C., Asner, G. P., Barger, N. N., Neff, J. C. & Floyd, M. L. Regional aboveground live carbon losses due to drought-induced tree dieback in piñon–juniper ecosystems. Remote Sens. Environ. 114, 14711479 (2010).
  25. Raffa, K. F. et al. Cross-scale drivers of natural disturbances prone to anthropogenic amplification: The dynamics of bark beetle eruptions. Bioscience 58, 501517 (2008).
  26. Grissino Mayer, H. D. & Swetnam, T. W. Century scale climate forcing of fire regimes in the American Southwest. Holocene 10, 213220 (2000).
  27. Westerling, A. L., Hidalgo, H. G., Cayan, D. R. & Swetnam, T. W. Warming and earlier spring increase western US forest wildfire activity. Science 313, 940943 (2006).
  28. Furniss, R. L. & Carolin, V. M. Western Forest Insects (United States Department of Agriculture (USDA) Forest Service (FS), 1977).
  29. Allen, C. D. Interactions across spatial scales among forest dieback, fire, and erosion in northern New Mexico landscapes. Ecosystems 10, 797808 (2007).
  30. Allen, C. D. & Breshears, D. D. Drought-induced shift of a forest-woodland ecotone: Rapid landscape response to climate variation. Proc. Natl Acad. Sci. USA 95, 1483914842 (1998).
  31. Betancourt, J. L., Pierson, E. A., Rylander, K. A., Fairchild-Parks, J. A. & Dean, J. S. in Managing Piñon-juniper Ecosystems for Sustainability and Social Needs (eds Aldon, A. F. & Shaw, D. W.) 4262 (USDA Forest Service, 1993).
  32. Savage, M. & Mast, J. N. How resilient are southwestern ponderosa pine forests after crown fires? Can. J. Forest Res. 35, 967977 (2005).
  33. Swetnam, T. W. & Betancourt, J. L. Fire-southern oscillation relations in the southwestern United States. Science 249, 10171020 (1990).
  34. Herweijer, C., Seager, R., Cook, E. R. & Emilie-Geay, J. North American droughts of the last millennium from a gridded network of tree-ring data. J. Clim. 20, 13531376 (2007).
  35. Potter, L. D. Phytosociological study of San Augustin Plains, New Mexico. Ecol. Monogr. 27, 114136 (1957).
  36. Plummer, F. G., Rixon, T. F. & Dodwell, A. Forest Conditions in the Black Mesa Forest Reserve, Arizona. Series H (Government Printing Office, 1904).
  37. Stahle, D. W. et al. Tree-ring data document 16th century megadrought over North America. EOS Trans. 81, 121121 (2000).
  38. Grissino-Mayer, H. D. in Tree Rings, Environment, and Humanity (eds Dean, J. S., Meko, D. M. & Swetnam, T. W.) 191204 (Radiocarbon, 1996).
  39. Dean, J. S. The medieval warm period on the southern Colorado Plateau. Climatic Change 26, 225241 (1994).
  40. Fall, P. L., Kelso, G. & Markgraf, V. Paleoenvironmental reconstruction at Canyon del Muerto, Arizona, based on principal-component analysis. J. Archaeol. Sci. 8, 297307 (1981).
  41. IPCC Special Report on Emissions Scenarios (eds Nakicenovic, N. & Swart, R.) (Cambridge Univ. Press, 2000).
  42. Williams, A. P., Michaelsen, J., Leavitt, S. W. & Still, C. J. Using tree rings to predict the response of tree growth to climate change in the continental United States during the twenty-first century. Earth Interact. 14, 120 (2010).
  43. Jackson, S. T., Betancourt, J. L., Booth, R. K. & Gray, S. T. Ecology and the ratchet of events: climate variability, niche dimensions, and species distributions. Proc. Natl Acad. Sci. USA 106, 1968519692 (2009).
  44. Goforth, B. R. & Minnich, R. A. Densification, stand-replacement wildfire, and extirpation of mixed conifer forest in Cuyamaca Rancho State Park, southern California. Forest Ecol. Manage. 256, 3645 (2008).
  45. Räisänen, J. CO2-induced climate change in CMIP2 experiments: Quantification of agreement and role of internal variability. J. Clim. 14, 20882104 (2001).
  46. Marlon, J. R. et al. Long-term perspective on wildfires in the western USA. Proc. Natl Acad. Sci. USA 109, E535E543 (2012).
  47. Cayan, D. R. et al. Evolution toward greater droughts in the SW United States. Proc. Natl Acad. Sci. USA 107, 2127121276 (2010).
  48. Held, I. M. & Soden, B. J. Robust responses of the hydrological cycle to global warming. J. Clim. 19, 56865699 (2006).
  49. Seager, R., Naik, N. & Vecchi, G. A. Thermodynamic and dynamic mechanisms for large-scale changes in the hydrological cycle in response to global warming. J. Clim. 23, 46514668 (2010).
  50. Seidel, D. J., Fu, Q., RanDel, W. J. & Reichler, T. S. J. Widening of the tropical belt in a changing climate. Nature Geosci. 1, 2124 (2008).

Download references

Author information

Affiliations

  1. Earth & Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA

    • A. Park Williams,
    • Chandana Gangodagamage &
    • Nate G. McDowell
  2. US Geological Survey, Fort Collins Science Center, Jemez Mountains Field Station, Los Alamos, New Mexico 87544, USA

    • Craig D. Allen
  3. School of Geography and Development, University of Arizona, Tucson, Arizona 85721, USA

    • Alison K. Macalady,
    • Daniel Griffin &
    • Connie A. Woodhouse
  4. Laboratory of Tree-ring Research, University of Arizona, Tucson, Arizona 85721, USA

    • Alison K. Macalady,
    • Daniel Griffin,
    • Connie A. Woodhouse,
    • David M. Meko,
    • Thomas W. Swetnam &
    • Jeffrey S. Dean
  5. Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA

    • Sara A. Rauscher
  6. Lamont-Doherty Earth Observatory of Columbia University, Palisades, New York 10964, USA

    • Richard Seager &
    • Edward R. Cook
  7. Laboratory of Tree-Ring Science, Department of Geography, The University of Tennessee, Knoxville, Tennessee 37996, USA

    • Henri D. Grissino-Mayer
  8. Space Data Systems, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA

    • Michael Cai

Contributions

A.P.W., C.D.A., A.K.M., D.G., C.A.W., D.M.M., T.W.S., S.A.R., R.S., M.C. and N.G.M. conceived and designed the experiments. A.P.W. performed the experiments. A.P.W. and E.R.C. analysed the data. A.K.M., D.G., C.A.W., C.G., D.M.M., T.W.S., S.A.R., H.D.G-M., J.S.D. and E.R.C. contributed data. A.P.W., C.D.A., A.K.M., D.G., C.A.W., D.M.M., T.W.S., S.A.R., R.S., H.D.G-M. and N.G.M. wrote the paper.

Competing financial interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to:

Author details

Supplementary information

PDF files

  1. Supplementary Information (1,096K)

    Supplementary Information

Additional data