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Climatic Change

, Volume 87, Supplement 1, pp 215–230 | Cite as

Response of vegetation distribution, ecosystem productivity, and fire to climate change scenarios for California

  • James M. Lenihan
  • Dominique Bachelet
  • Ronald P. Neilson
  • Raymond Drapek
Article

Abstract

The response of vegetation distribution, carbon, and fire to three scenarios of future climate change was simulated for California using the MC1 Dynamic General Vegetation Model. Under all three scenarios, Alpine/Subalpine Forest cover declined, and increases in the productivity of evergreen hardwoods led to the displacement of Evergreen Conifer Forest by Mixed Evergreen Forest. Grassland expanded, largely at the expense of Woodland and Shrubland, even under the cooler and less dry climate scenario where increased woody plant production was offset by increased wildfire. Increases in net primary productivity under the cooler and less dry scenario contributed to a simulated carbon sink of about 321 teragrams for California by the end of the century. Declines in net primary productivity under the two warmer and drier scenarios contributed to a net loss of carbon ranging from about 76 to 129 teragrams. Total annual area burned in California increased under all three scenarios, ranging from 9–15% above the historical norm by the end of the century. Annual biomass consumption by fire by the end of the century was about 18% greater than the historical norm under the more productive cooler and less dry scenario. Under the warmer and drier scenarios, simulated biomass consumption was initially greater, but then at, or below, the historical norm by the end of the century.

Keywords

Emission Scenario Fire Spread Future Climate Scenario Geophysical Fluid Dynamic Laboratory Effective Moisture 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Aber J, Neilson R, McNulty S, Lenihan J, Bachelet D, Drapek R (2001) Forest processes and global environmental change: predicting the effects of individual and multiple stressors. Bioscience 51(9):735–751CrossRefGoogle Scholar
  2. Anderson GK, Ottmar RD, Prichard SJ (2005) CONSUME 3.0 User’s Guide. Pacific Wildland Fire Sciences Laboratory, USDA Foreset Service Pacific Northwest Research Station. Seattle, WA, 183 pGoogle Scholar
  3. Bachelet D, Lenihan J, Daly C, Neilson R (2000) Interactions between fire, grazing and climate change at Wind Cave National Park, SD. Ecol Model 134:229–224CrossRefGoogle Scholar
  4. Bachelet D, Neilson RP, Lenihan JM, Drapek RJ (2001) Climate change effects on vegetation distribution and carbon budget in the U.S. Ecosystems 4:164–185CrossRefGoogle Scholar
  5. Barbour M, Pavlik B, Drysdale F, Lindstrom S (1993) California’s changing landscapes: diversity and conservation of California vegetation. California Native Plant Society, 246 ppGoogle Scholar
  6. Callaway RM, Davis F (1993) Vegetation dynamics, fire, and the physical environment in coastal central California. Ecology 74:1567–1578CrossRefGoogle Scholar
  7. Caspersen JP, Pacala SW, Jenkins JC, Hurtt GC, Moorcroft PR, Birdsey RA (2000) Contributions of land-use history to carbon accumulation in U.S. forests. Science 290:1148–1151CrossRefGoogle Scholar
  8. Cayan D, Luers AL, Hanemann M, Franco G (2006) Scenarios of climate change in California: an overview. Report from the California Climate Change Center. Sacramento, CA. CEC-500-2005-186-SF, 47 pGoogle Scholar
  9. Cohen JD, Deeming JE (1985) The National Fire Danger Rating System: basic equations. USDA Forest Service Pacific Southwest Forest and Range Experimental Station General Technical Report PSW-82, 16 pGoogle Scholar
  10. Daly C, Neilson RP, Phillips DL (1994) A statistical-topographic model for mapping climatological precipitation over mountainous terrain. J Appl Meteorol 33:140–158CrossRefGoogle Scholar
  11. Daly C, Bachelet D, Lenihan J, Parton W, Neilson R, Ojima D (2000) Dynamic simulations of tree-grass interactions for global change studies. Ecol Appl 10:449–469Google Scholar
  12. Davis FW, Stoms DM, Hollander AD, Thomas KA, Stine PA, Odion D, Borchert MI, Thorne JH, Gray MV, Walker RE, Warner K, Graae J (1998) The California Gap Analysis Project, Final Report. University of California, Santa Barbara, CAGoogle Scholar
  13. Dukes J, Chiariello N, Cleland E, Moore L, Shaw M, Thayer S, Tobeck T, Mooney H, Field C (2005) Response of grassland production to single and multiple global environmental change. PLoS Biology 3(10):319eCrossRefGoogle Scholar
  14. Hayhoe K, Cayan D, Field C, Frumhoff P, Maurer E, Miller N, Moser S, Schneider S, Cahill K, Cleland E, Dale L, Drapek R, Hanemann R, Kalkstein L, Lenihan J, Lunch C, Neilson R, Sheridan S, Verville J (2004) Emission pathways, climate change, and impacts on California. Proc Natl Acad Sci U S A 101:12422–12427CrossRefGoogle Scholar
  15. Holland V, Keil D (1995) California vegetation. Kendall/Hunt, Dubuque, Iowa 515 pGoogle Scholar
  16. Intergovernmental Panel on Climate Change (2000) Special Report on Emissions Scenarios. In: Nakicenovic N, Swart R (eds) Cambridge University Press, UK, 570 ppGoogle Scholar
  17. Kattenberg A, Giorgi F, Grassl H, Meehl G, Mitchell J, Stouffer R, Tokioka T, Weaver A, Wigley T (1996) Climate models: projections of future climate. In: Houghton JL, Filho M, Callander B, Harris N, Kattenberg A, Maskell K (eds) Climate change 1995: the science of climate change. Contribution to Working Group 1 to the Second Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK, pp 285–357Google Scholar
  18. Keeley JE (2002) Native American impacts on fire regimes of the California coastal ranges. J Biogeogr 29:303–320CrossRefGoogle Scholar
  19. Kittel TGF, Rosenbloom NA, Royle JA, Daly C, Gibson WP, Fisher HH, Thornton P, Yates DN, Aulenbach S, Kaufman C, McKeown R, Bachelet D, Schimel DS, VEMAP2 Participants (2004) VEMAP phase 2 bioclimatic database. I. Gridded historical (20th century) climate for modeling ecosystem dynamics across the conterminous United States. Clim Res 27:151–170CrossRefGoogle Scholar
  20. Körner C, Asshoff R, Bignucolo O, Hättenschwiler S, Keel SG, Peláez-Riedl S, Pepin S, Siegwolf RTW, Zotz G (2005) Carbon flux and growth in mature deciduous forest trees exposed to elevated CO2. Science 309:1360–1362CrossRefGoogle Scholar
  21. Kueppers LM, Snyder MA, Sloan L, Zavaleta ES, Fulfrost B (2005) Modeled regional climate change and California endemic oak ranges. Proc Nat Acad 102(45):16281–16286CrossRefGoogle Scholar
  22. Lenihan JM, Drapek R, Bachelet D, Neilson R (2003) Climate change effects on vegetation distribution, carbon, and fire in California. Ecol Appl 13(6):1667–1681CrossRefGoogle Scholar
  23. Mooney H, Canadell J, Chapin F, Ehleringer J, Korner C (1999) Ecosystem physiology responses to global change. In: Walker B, Steffen W, Canadell J, Ingram J (eds) The terrestrial biosphere and global change. Cambridge University Press, Cambridge, U.K., pp 141–189Google Scholar
  24. Norby RJ, Luo Y (2004) Evaluating ecosystem responses to rising atmospheric CO2 and global warming in a multi-factor world. New Phytologist 162:281–293CrossRefGoogle Scholar
  25. Norby RJ, DeLucia EH, Gielen B, Calfapietra C, Giardina CP, King JS, Ledford J, McCarthy HR, Moore DJP, Ceulemans R, De Angelis P, Finzi AC, Karnosky DF, Kubiske ME, Lukac M, Pregitzer KS, Scarascia-Mugnozza GE, Schlesinger WH, Oren R (2005) Forest response to elevated CO2 is conserved across a broad range of productivity. Proc Natl Acad Sci U S A 102:18052–18056CrossRefGoogle Scholar
  26. Oren R, Ellsworth DS, Johnsen KH, Phillips N, Ewers BE, Maier C, Schafer KVR, McCarthy H, Hendrey G, McNulty SG, Katul GG (2001) Soil fertility limits carbon sequestration by forest ecosystems in a CO2 enriched world. Nature 411:469–472CrossRefGoogle Scholar
  27. Parton W, Schimel D, Ojima D, Cole C (1994) A general study model for soil organic model dynamics, sensitivity to litter chemistry, texture, and management. SSSA Special Publication 39. Soil Sci Soc Am 147–167Google Scholar
  28. Peterson D, Ryan K (1986) Modeling postfire conifer mortality for long-range planning. Environ Manage 10:797–808CrossRefGoogle Scholar
  29. Rothermel R (1972) A mathematical model for fire spread predictions in wildland fuels. USDA Forest Service Research Paper INT-115, 40 ppGoogle Scholar
  30. Strauss D, Bednar L, Mees R (1989) Do one percent of forest fires cause ninety-nine percent of the damage? For Sci 35:319–328Google Scholar
  31. Turner M, Romme W (1994) Landscape dynamics in crown fire ecosystems. Landsc Ecol 9(1):59–77CrossRefGoogle Scholar
  32. van Wagner CE (1993) Prediction of crown fire behavior in two stands of jack pine. Can J For Res 23:442–449CrossRefGoogle Scholar

Copyright information

© U.S.D.A. Forest Service 2007

Authors and Affiliations

  • James M. Lenihan
    • 1
    • 3
  • Dominique Bachelet
    • 2
  • Ronald P. Neilson
    • 1
  • Raymond Drapek
    • 1
  1. 1.USDA Forest Service Pacific Northwest Research StationCorvallisUSA
  2. 2.Oregon State UniversityCorvallisUSA
  3. 3.USFS Pacific Northwest Research LaboratoryCorvallisUSA

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