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.

  • Letter
  • Published:

Palaeodata-informed modelling of large carbon losses from recent burning of boreal forests

Nature Climate Change volume 6, pages 79–82 (2016)Cite this article

Subjects

Abstract

Wildfires play a key role in the boreal forest carbon cycle1,2, and models suggest that accelerated burning will increase boreal C emissions in the coming century3. However, these predictions may be compromised because brief observational records provide limited constraints to model initial conditions4. We confronted this limitation by using palaeoenvironmental data to drive simulations of long-term C dynamics in the Alaskan boreal forest. Results show that fire was the dominant control on C cycling over the past millennium, with changes in fire frequency accounting for 84% of C stock variability. A recent rise in fire frequency inferred from the palaeorecord5 led to simulated C losses of 1.4 kg C m−2 (12% of ecosystem C stocks) from 1950 to 2006. In stark contrast, a small net C sink of 0.3 kg C m−2 occurred if the past fire regime was assumed to be similar to the modern regime, as is common in models of C dynamics. Although boreal fire regimes are heterogeneous, recent trends6 and future projections7 point to increasing fire activity in response to climate warming throughout the biome. Thus, predictions8 that terrestrial C sinks of northern high latitudes will mitigate rising atmospheric CO2 may be over-optimistic.

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

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

Figure 1: Carbon dynamics of the past millennium.
Figure 2: Simulated recent carbon dynamics based on spin-up conditions prescribed from palaeodata (spPaleo; black) or the assumption that prehistoric conditions were stationary and identical to modern (spModern; grey).

Similar content being viewed by others

References

  1. Kasischke, E. S. in Distribution of Forest Ecosystems and the Role of Fire in the North American Boreal Region (eds Kasischke, E. S. & Stocks, B. J.) 19–30 (Springer, 2000).

    Google Scholar 

  2. Bond-Lamberty, B., Peckham, S. D., Ahl, D. E. & Gower, S. T. Fire as the dominant driver of central Canadian boreal forest carbon balance. Nature 450, 89–92 (2007).

    Article  CAS  Google Scholar 

  3. Balshi, M. S., McGuire, A. D. & Duffy, P. A. Vulnerability of carbon storage in North American boreal forests to wildfires during the 21st century. Glob. Change Biol. 15, 1491–1510 (2009).

    Article  Google Scholar 

  4. McGuire, A. D. et al. in Land Change Science (eds Gutman, G. et al.) 139–161 (Springer, 2004).

    Google Scholar 

  5. Kelly, R. et al. Recent burning of boreal forests exceeds fire regime limits of the past 10,000 years. Proc. Natl Acad. Sci. USA 110, 13055–13060 (2013).

    Article  CAS  Google Scholar 

  6. Kasischke, E. S. & Turetsky, M. R. Recent changes in the fire regime across the North American boreal region—Spatial and temporal patterns of burning across Canada and Alaska. Geophys. Res. Lett. 33, L09703 (2006).

    Google Scholar 

  7. Flannigan, M. D., stocks, B. J., Turetsky, M. R. & Wotton, M. Impacts of climate change on fire activity and fire management in the circumboreal forest. Glob. Change Biol. 15, 549–560 (2009).

    Article  Google Scholar 

  8. Qian, H., Joseph, R. & Zeng, N. Enhanced terrestrial carbon uptake in the northern high latitudes in the 21st century from the coupled carbon cycle climate model intercomparison project model projections. Glob. Change Biol. 16, 641–656 (2010).

    Article  Google Scholar 

  9. IPCC Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) (Cambridge Univ. Press, 2013).

    Google Scholar 

  10. McGuire, A. D. et al. Sensitivity of the carbon cycle in the Arctic to climate change. Ecol. Monogr. 79, 523–555 (2009).

    Article  Google Scholar 

  11. Grosse, G. et al. Vulnerability of high-latitude soil organic carbon in North America to disturbance. J. Geophys. Res. 116, G00K06 (2011).

    Article  Google Scholar 

  12. Thonicke, K. et al. The influence of vegetation, fire spread and fire behaviour on biomass burning and trace gas emissions: Results from a process-based model. Biogeosciences 7, 1991–2011 (2010).

    Article  CAS  Google Scholar 

  13. Kurz, W. A., Stinson, G. & Rampley, G. Could increased boreal forest ecosystem productivity offset carbon losses from increased disturbances? Phil. Trans. R. Soc. B 363, 2259–2268 (2008).

    Article  Google Scholar 

  14. Hayes, D. J. et al. Is the northern high-latitude land-based CO2 sink weakening? Glob. Biogeochem. Cycles 25, GB3018 (2011).

    Article  Google Scholar 

  15. Balshi, M. S. et al. The role of historical fire disturbance in the carbon dynamics of the pan-boreal region: A process-based analysis. J. Geophys. Res. 112, G02029 (2007).

    Article  Google Scholar 

  16. Ali, A. A. et al. Control of the multimillennial wildfire size in boreal North America by spring climatic conditions. Proc. Natl Acad. Sci. USA 109, 20966–20970 (2012).

    Article  CAS  Google Scholar 

  17. Higuera, P. E., Brubaker, L. B., Anderson, P. M., Hu, F. S. & Brown, T. A. Vegetation mediated the impacts of postglacial climate change on fire regimes in the south-central Brooks Range, Alaska. Ecol. Monogr. 79, 201–219 (2009).

    Article  Google Scholar 

  18. Kasischke, E. S., Williams, D. & Barry, D. Analysis of the patterns of large fires in the boreal forest region of Alaska. Int. J. Wildland Fire 11, 131–144 (2002).

    Article  Google Scholar 

  19. Jungclaus, J. H. et al. Climate and carbon-cycle variability over the last millennium. Clim. Past 6, 723–737 (2010).

    Article  Google Scholar 

  20. Schmidt, G. A. et al. Climate forcing reconstructions for use in PMIP simulations of the last millennium (v1.0). Geosci. Model Dev. 4, 33–45 (2011).

    Article  Google Scholar 

  21. Hu, F. S., Ito, E., Brown, T. A., Curry, B. B. & Engstrom, D. R. Pronounced climatic variations in Alaska during the last two millennia. Proc. Natl Acad. Sci. USA 98, 10552–10556 (2001).

    Article  CAS  Google Scholar 

  22. O’Neill, K. P., Kasischke, E. S. & Richter, D. D. Seasonal and decadal patterns of soil carbon uptake and emission along an age sequence of burned black spruce stands in interior Alaska. J. Geophys. Res. 108(D1), 8155 (2003).

    Article  Google Scholar 

  23. Genet, H. et al. Modeling the effects of fire severity and climate warming on active layer thickness and soil carbon storage of black spruce forests across the landscape in interior Alaska. Environ. Res. Lett. 8, 045016 (2013).

    Article  Google Scholar 

  24. Kurz, W. A. et al. CBM-CFS3: A model of carbon-dynamics in forestry and land-use change implementing IPCC standards. Ecol. Model. 220, 480–504 (2009).

    Article  Google Scholar 

  25. Daniau, A.-L. et al. Predictability of biomass burning in response to climate changes. Glob. Biogeochem. Cycles 26, GB4007 (2012).

    Article  Google Scholar 

  26. Hugelius, G. et al. The Northern Circumpolar Soil Carbon Database: Spatially distributed datasets of soil coverage and soil carbon storage in the northern permafrost regions. Earth Syst. Sci. Data 5, 707–733 (2012).

    Article  Google Scholar 

  27. Luo, Y. et al. Ecological forecasting and data assimilation in a data-rich era. Ecol. Appl. 21, 1429–1442 (2011).

    Article  Google Scholar 

  28. Mitchell, T. D. & Jones, P. D. An improved method of constructing a database of monthly climate observations and associated high-resolution grids. Int. J. Climatol. 25, 693–712 (2005).

    Article  Google Scholar 

  29. Gallant, A. L., Binnian, E. F., Omernik, J. M. & Shasby, M. B. Ecoregions of Alaska (United States Government Printing Office, 1995).

    Book  Google Scholar 

  30. Zhuang, Q. et al. Modeling soil thermal and carbon dynamics of a fire chronosequence in interior Alaska. J. Geophys. Res. 107(D1), 8147 (2003).

    Google Scholar 

  31. Yi, S. et al. Interactions between soil thermal and hydrological dynamics in the response of Alaska ecosystems to fire disturbance. J. Geophys. Res. 114, G02015 (2009).

    Article  Google Scholar 

  32. Yi, S. et al. A dynamic organic soil biogeochemical model for simulating the effects of wildfire on soil environmental conditions and carbon dynamics of black spruce forests. J. Geophys. Res. 115, G04015 (2010).

    Google Scholar 

  33. Yuan, F. M. et al. Assessment of boreal forest historical C dynamics in the Yukon River Basin: Relative roles of warming and fire regime change. Ecol. Appl. 22, 2091–2109 (2012).

    Article  CAS  Google Scholar 

  34. Goulden, M. L. et al. Patterns of NPP, GPP, respiration, and NEP during boreal forest succession. Glob. Change Biol. 17, 855–871 (2011).

    Article  Google Scholar 

  35. Bond-Lamberty, B., Wang, C. & Gower, S. Net primary production and net ecosystem production of a boreal black spruce wildfire chronosequence. Glob. Change Biol. 10, 473–487 (2004).

    Article  Google Scholar 

  36. Viereck, L. A. Wildfire in the taiga of Alaska. Quat. Res. 3, 465–495 (1973).

    Article  Google Scholar 

  37. Johnson, K. D. et al. Soil carbon distribution in Alaska in relation to soil-forming factors. Geoderma 167–168, 71–84 (2011).

    Article  Google Scholar 

  38. Malone, T., Liang, J. & Packee, E. C. Cooperative Alaska Forest Inventory 1–50 (USDA, 2009).

    Book  Google Scholar 

  39. Yarie, J., Kane, E. & Mack, M. C. Aboveground biomass equations for the trees of interior Alaska Bulletin 115 (US Forest Service, 2007).

  40. Alexander, H. D., Mack, M. C., Goetz, S., Beck, P. S. A. & Belshe, E. F. Implications of increased deciduous cover on stand structure and aboveground carbon pools of Alaskan boreal forests. Ecosphere 3, 45 (2012).

    Article  Google Scholar 

  41. Turetsky, M. R. et al. Recent acceleration of biomass burning and carbon losses in Alaskan forests and peatlands. Nature Geosci. 4, 27–31 (2010).

    Article  Google Scholar 

  42. Walsh, J. E., Chapman, W. L., Romanovsky, V., Christensen, J. H. & Stendel, M. Global climate model performance over Alaska and Greenland. J. Clim. 21, 6156–6174 (2008).

    Article  Google Scholar 

  43. Schmidt, G. A. et al. Present-day atmospheric simulations using GISS ModelE: Comparison to in situ, satellite, and reanalysis data. J. Clim. 19, 153–192 (2006).

    Article  Google Scholar 

  44. Gent, P. R. et al. The community climate system model version 4. J. Clim. 24, 4973–4991 (2011).

    Article  Google Scholar 

  45. Crowley, T. J. et al. Volcanism and the little ice age. PAGES News 16, 22–23 (2008).

    Article  Google Scholar 

  46. Gao, C., Robock, A. & Ammann, C. Volcanic forcing of climate over the past 1500 years: An improved ice core-based index for climate models. J. Geophys. Res. Atmos. 113, D23111 (2008).

    Article  Google Scholar 

  47. Steinhilber, F., Beer, J. & Frohlich, C. Total solar irradiance during the Holocene. Geophys. Res. Lett. 36, 9–12 (2009).

    Article  Google Scholar 

  48. Vieira, L. E. A. & Solanki, S. Evolution of the solar magnetic flux on time scales of years to millenia. Astron. Astrophys. 509, A100 (2010).

    Article  Google Scholar 

Download references

Acknowledgements

We gratefully acknowledge comments on this work from M. L. Chipman, E. S. Euskirchen, Y. Zhang, D. Devotta, M. Urban and M. Fernandez, and technical support from J. Jungclaus and D. Rice. This work was supported by National Science Foundation (NSF) Grants ARC-0612366 and ARC-1023477 (F.S.H.), by University of Illinois funding from a Graduate College Dissertation Completion Fellowship, the School of Integrative Biology Enhancement Fund, and the Department of Plant Biology Graduate Research Enhancement Fund (R.K.), and by grants from the US Geological Survey, the US Fish and Wildlife Service, the National Science Foundation, and the Department of Defense (A.D.M. and H.G.). Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government.

Author information

Authors and Affiliations

  1. Department of Plant Biology, University of Illinois, Urbana, Illinois 61801, USA

    Ryan Kelly & Feng Sheng Hu

  2. Institute of Arctic Biology, University of Alaska, Fairbanks, Alaska 99775, USA

    Hélène Genet

  3. US Geological Survey, Alaska Cooperative Fish and Wildlife Research Unit, University of Alaska, Fairbanks, Alaska 99775, USA

    A. David McGuire

  4. Department of Geology, and Program in Ecology, Evolution, and Conservation Biology, University of Illinois, Urbana, Illinois 61801, USA

    Feng Sheng Hu

Authors
  1. Ryan Kelly
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hélène Genet
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. A. David McGuire
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Feng Sheng Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

R.K. conducted the analysis with assistance from H.G. All authors contributed in designing the study, interpreting results, and preparing the manuscript.

Corresponding authors

Correspondence to Ryan Kelly or Feng Sheng Hu.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kelly, R., Genet, H., McGuire, A. et al. Palaeodata-informed modelling of large carbon losses from recent burning of boreal forests. Nature Clim Change 6, 79–82 (2016). https://doi.org/10.1038/nclimate2832

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nclimate2832

This article is cited by

Search

Advanced search

Quick links

Nature Briefing Microbiology

Sign up for the Nature Briefing: Microbiology newsletter — what matters in microbiology research, free to your inbox weekly.

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