Advertisement

Climatic Change

, Volume 147, Issue 3–4, pp 617–631 | Cite as

Future southcentral US wildfire probability due to climate change

  • Michael C. Stambaugh
  • Richard P. Guyette
  • Esther D. Stroh
  • Matthew A. Struckhoff
  • Joanna B. Whittier
Article

Abstract

Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. In this paper, we present projections of future fire probability for the southcentral USA using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM). Future fire probability is projected to both increase and decrease across the study region of Oklahoma, New Mexico, and Texas. Among all end-of-century projections, change in fire probabilities (CFPs) range from − 51 to + 240%. Greatest absolute increases in fire probability are shown for areas within the range of approximately 75 to 160 cm mean annual precipitation (MAP), regardless of climate model. Although fire is likely to become more frequent across the southcentral USA, spatial patterns may remain similar unless significant increases in precipitation occur, whereby more extensive areas with increased fire probability are predicted. Perhaps one of the most important results is illumination of climate changes where fire probability response (+, −) may deviate (i.e., tipping points). Fire regimes of southcentral US ecosystems occur in a geographic transition zone from reactant- to reaction-limited conditions, potentially making them uniquely responsive to different scenarios of temperature and precipitation changes. Identification and description of these conditions may help anticipate fire regime changes that will affect human health, agriculture, species conservation, and nutrient and water cycling.

Keywords

Mean fire interval Physical Chemistry Fire Frequency Model (PC2FM) New Mexico Oklahoma Texas 

Notes

Acknowledgements

We acknowledge the National Science Foundation (NSF), Idaho EPSCoR, and the individual investigators responsible for the future climate projection data sets. In addition, we acknowledge the modeling groups, the Program for Climate Model Diagnosis and Intercomparison (PCMDI), and the WCRP’s Working Group on Coupled Modeling (WGCM) for their roles in making available the WCRP CMIP3 multi-model dataset. Support of this dataset is provided by the Office of Science, US Department of Energy. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government.

Funding

This project was funded, in part, by the US Geological Survey, South Central Climate Science Center, in cooperation with the University of Missouri, Columbia and the Great Rivers Cooperative Ecosystems Studies Unit.

References

  1. Atkins PW (1986) Physical chemistry, 3rd edn. W.H. Freeman and Company, New YorkGoogle Scholar
  2. Bailey RG (1995) Description of the ecoregions of the United States (2nd ed.). Misc. Pub. No. 1391, USDA Forest Service, Washington DCGoogle Scholar
  3. Batllori E, Parisien M-A, Krawchuk MA, Moritz MA (2013) Climate change-induced shifts in fire for Mediterranean ecosystems. Glob Ecol Biogeogr 22:1118–1129CrossRefGoogle Scholar
  4. Bernard ML, Nimour N (2007) Wildfires, weather, and productivity In Butler BW, Cook W (comps) The fire environment: innovations, management, and policy; conference proceedings. USDA Forest Service RMRS-P-46CD, pp 7-26Google Scholar
  5. Briggs JM, Knapp AK (1995) Interannual variability in primary production in tallgrass prairie: climate, soil moisture, topographic position, and fire as determinants of aboveground biomass. Amer J Bot 82:1024–1030CrossRefGoogle Scholar
  6. Chamrad AD, Box TW (1965) Drought-associated mortality of range grasses in south Texas. Ecol 46:780–785CrossRefGoogle Scholar
  7. Chandler C, Cheney P, Thomas P, Trabaud L, Williams D (1983) Fire in forestry. John Wiley & Sons, New YorkGoogle Scholar
  8. Daly C, Gibson WP, Doggett M, Smith J, Taylor G (2004) Up-to-date monthly climate maps for the conterminous United States In Proceedings of the 14th American Meteorological Society conference on applied climatology, American Meteorological SocietyGoogle Scholar
  9. Schweitzer DDC (2014) Restoration for the future: endpoints, targets, and indicators of progress and success. J Sustain For 33:S43–S65CrossRefGoogle Scholar
  10. Flato GM, Boer GJ, Lee WG, McFarlane NA, Ramsden D, Reader MC, Weaver AJ (2000) The Canadian Centre for Climate Modeling and Analysis global coupled model and its climate. Clim Dyn 16:451–467CrossRefGoogle Scholar
  11. Gonzalez P, Nielson RP, Lenihan JM, Drapek RJ (2010) Global patterns in the vulnerability of ecosystems to vegetation shifts due to climate change. Global Ecol Biogeog 19:755–768CrossRefGoogle Scholar
  12. Gordon C, Cooper C, Senior CA, Banks H, Gregory JM, Johns TC, Mitchell JFB, Wood RA (2000) The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley centre coupled model without flux adjustments. Clim Dyn 16:147–168CrossRefGoogle Scholar
  13. Guyette RP, Stambaugh MC, Dey DC, Muzika R-M (2012) Estimating fire frequency with the chemistry and climate. Ecosystems 15:322–335CrossRefGoogle Scholar
  14. Guyette RP, Thompson FR, Whittier J, Stambaugh MC, Dey DC (2014) Future fire probability modeling with climate change data and physical chemistry. For Sci 60:862–870Google Scholar
  15. Guyette RP, Stambaugh MC, Marschall JM, Abadir ER (2015) An analytic approach to climate dynamics and fire frequency in the Great Plains. Great Plains Res 25:139–150CrossRefGoogle Scholar
  16. Guyette RP, Stambaugh MC, Dey DC, Muzika R-M (2017) The theory, direction, and magnitude of ecosystem fire probability as constrained by precipitation and temperature. PLoS OneGoogle Scholar
  17. Hanson PR, Arbogast AF, Johnson WC, Joeckel RM, Young AR (2010) Megadroughts and late Holocene dune activation at the eastern margin of the Great Plains, north-central Kansas, USA. Aeolian Res 1:101–110CrossRefGoogle Scholar
  18. Harris DC (1987) Quantitative chemical analysis. W.H. Freeman and Company, New YorkGoogle Scholar
  19. Hoover K, Bracmort K (2015) Wildfire management: federal funding and related statistics. Report R43077, Congressional Research Service, Washington DCGoogle Scholar
  20. IPCC (2012) Managing the risks of extreme events and disasters to advance climate change adaptation: a special report of working groups i and ii of the intergovernmental panel on climate change. Cambridge University Press, CambridgeGoogle Scholar
  21. Keeley JE, Syphard A (2016) Climate change and future fire regimes: examples from California. Geosciences 6:37.  https://doi.org/10.3390/geosciences6030037 CrossRefGoogle Scholar
  22. Krawchuk MA, Moritz MA, Parisien M-A, Van Dorn J, Hayhoe K (2009) Global pyrogeography: the current and future distribution of wildfire. PLoS One 4:e5102CrossRefGoogle Scholar
  23. Lafon CW, Naito AT, Grissino-Mayer HD, Horn SP, Waldrop TA (2017) Fire history of the Appalachian region: a review and synthesis. GTR SRS-219. USDA Forest Service, Asheville, NCGoogle Scholar
  24. Margolis EQ, Woodhouse CA, Swetnam TW (2017) Drought, multi-seasonal climate, and wildfire in northern New Mexico. Clim Chang 142:433–446CrossRefGoogle Scholar
  25. McNab WH, Cleland DT, Freeouf JA, Keys JE Jr, Nowacki GJ, Carpenter CA (2007) Description of ecological subregions: sections of the conterminous United States [CD-ROM]. GTR WO-76B. USDA Forest Service, Washington DCCrossRefGoogle Scholar
  26. Melillo JM, McGuire AD, Kicklighter DW, Moore B III, Vorosmarty CJ, Schloss AL (1993) Global climate change and terrestrial net primary production. Nature 363:234–240CrossRefGoogle Scholar
  27. Mensing S, Livingston S, Barker P (2006) Long-term fire history in Great Basin sagebrush reconstructed from macroscopic charcoal in spring sediments, Newark Valley, Nevada. West N Amer Nat 66:64–77CrossRefGoogle Scholar
  28. Mitchell RJ, Liu Y, O’Brien JJ, Elliott KJ, Starr G, Miniat CF, Hiers JK (2014) Future climate and fire interactions in the southeastern region of the United States. For Ecol Manag 327:316–326CrossRefGoogle Scholar
  29. Moritz MA et al (2014) Learning to coexist with wildfire. Nature 515:58–66.  https://doi.org/10.1038/nature13946 CrossRefGoogle Scholar
  30. Moritz MA, Parisien M-A, Batllori E, Krawchuk MA, Van Dorn J, Ganz DJ, Hayhoe K (2012) Climate change and disruptions to global fire activity. Ecosphere 3:1–22CrossRefGoogle Scholar
  31. Muhs DR, Maat PB (1993) The potential response of eolian sands to greenhouse warming and precipitation reduction on the Great Plains of the USA. J Arid Environ 25:351–361CrossRefGoogle Scholar
  32. NOAA Geophysical Fluid Dynamics Laboratory (2009) Ocean simulation based on MOM4-beta2 release, Version: 4. NOAA/GFDL, Princeton University, PrincetonGoogle Scholar
  33. North M, Collins BM, Stephens S (2012) Using fire to increase the scale, benefits, and future maintenance of fuels treatments. J Forestry 110:392–401CrossRefGoogle Scholar
  34. Noss RF (2012) Forgotten grasslands of the south: natural history and conservation. Island Press, Washington DCGoogle Scholar
  35. Parisien MA, Moritz MA (2009) Environmental controls on the distribution of wildfire at multiple spatial scales. Ecol Monogr 79:127–154CrossRefGoogle Scholar
  36. Parisien MA, Snetsinger S, Greenberg JA, Nelson CR, Schoennagel T, Dobrowski SZ, Moritz MA (2012) Spatial variability in wildfire probability across the western United States. Int J Wildl Fire 21:313–327CrossRefGoogle Scholar
  37. Pierce D (2014) ncdf: Interface to Unidata netCDF data files. R package version 1.6.8. http://CRAN.R-project.org/package=ncdf
  38. Power MJ et al (2008) Changes in fire regimes since the Last Glacial Maximum: an assessment based on a global synthesis and analysis of charcoal data. Clim Dyn 30:887–907CrossRefGoogle Scholar
  39. Pyne SJ (2010) America’s fires, a historical context for practice. The Forest History Society, DurhamGoogle Scholar
  40. R Development Core Team (2008) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  41. Risser PG (1988) Abiotic controls on primary productivity and nutrient cycles in North American grasslands In Pomeroy LR, Alberts JJ (eds) Concepts of Ecosystem Ecology, Ecological Studies (Analysis and Synthesis), vol 67, Springer, New YorkGoogle Scholar
  42. Scasta JD, Weir JR, Stambaugh MC (2016) Droughts and wildfires in western U.S. rangelands. Rangelands 38:197–203CrossRefGoogle Scholar
  43. Stambaugh MC, Sparks JC, Abadir ER (2014) Historical pyrogeography of Texas. Fire Ecol 10:72–89CrossRefGoogle Scholar
  44. Stambaugh MC, Guyette RP, Stroh ED, Struckhoff MA, Whittier JB (2018) Future changes in southcentral U.S. wildfire probability due to climate change – Data. U.S. Geological Survey data release. https://www.doi.org/10.5066/F7PK0F4V
  45. Strachan S, Daly C (2017) Testing the daily PRISM air temperature model on semiarid mountain slopes. J Geophys Res Atmos  https://doi.org/10.1002/2016JD025920
  46. Stroh ED, Struckhoff MA, Stambaugh MC, Guyette RP (2018) Future fire and climate suitability for woody ecosystems in the south central United States. Fire Ecol (in press)Google Scholar
  47. USDA (2015) The rising cost of fire operations: effects on the Forest Service’s non-fire work. Washington DCGoogle Scholar
  48. Wright HA, Bailey AW (1982) Fire ecology. John Wiley & Sons, New YorkGoogle Scholar

Copyright information

© This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2018

Authors and Affiliations

  • Michael C. Stambaugh
    • 1
  • Richard P. Guyette
    • 1
  • Esther D. Stroh
    • 2
  • Matthew A. Struckhoff
    • 2
  • Joanna B. Whittier
    • 1
  1. 1.School of Natural ResourcesUniversity of MissouriColumbiaUSA
  2. 2.U.S. Geological Survey, Columbia Environmental Research CenterColumbiaUSA

Personalised recommendations