Carbon Tradeoffs of Restoration and Provision of Endangered Species Habitat in a Fire-Maintained Forest
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Forests are a significant part of the global carbon cycle and are increasingly viewed as tools for mitigating climate change. Natural disturbances, such as fire, can reduce carbon storage. However, many forests and dependent species evolved with frequent fire as an integral ecosystem process. We used a landscape forest simulation model to evaluate the effects of endangered species habitat management on carbon sequestration. We compared unmanaged forests (control) to forests managed with prescribed burning and prescribed burning combined with thinning. Management treatments followed guidelines of the recovery plan for the endangered red-cockaded woodpecker (RCW), which requires low-density longleaf pine (Pinus palustris) forest. The unmanaged treatment provided the greatest carbon storage, but at the cost of lost RCW habitat. Thinning and burning treatments expanded RCW habitat by increasing the dominance of longleaf pine and reducing forest density, but stored 22% less total ecosystem carbon compared to the control. Our results demonstrate that continued carbon sequestration and the provision of RCW habitat are not incompatible goals, although there is a tradeoff between habitat extent and total ecosystem carbon across the landscape. Management for RCW habitat might also increase ecosystem resilience, as longleaf pine is tolerant of fire and drought, and resistant to pests. Restoring fire-adapted forests requires a reduction in carbon. However, the size of the reduction, the effects on sequestration rates, and the co-benefits from other ecosystem services should be evaluated in the context of the specific forest community targeted for restoration.
Keywordscarbon sequestration climate change ecosystem services endangered species fire longleaf pine Pinus palustris prescribed burning red-cockaded woodpecker
Funding for this research was provided by the US Department of Defense’s Strategic Environmental Research Development Program (SERDP). We thank the Ft. Benning field crew for assistance with data collection and James Parker and Rob Addington for providing data and facilitating access to field locations. We are grateful for the constructive feedback from anonymous reviewers.
- Brown JK. 1974. Handbook for inventorying downed woody material. General Technical Report INT-16. Ogden, UT: US Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station.Google Scholar
- Canadell JG, Le Quéré C, Raupach MR, Field CB, Buitenhuis ET, Ciais P, Conway TJ, Gillett NP, Houghton RA, Marland G. 2007. Contributions to accelerating atmospheric CO2 growth from economic activity, carbon intensity, and efficiency of natural sinks. Proc Natl Acad Sci USA 104:18866–70.PubMedCentralPubMedCrossRefGoogle Scholar
- Chapin FS, Matson PPA. 2011. Principles of terrestrial ecosystem ecology. New York: Springer.Google Scholar
- Dangal SRS, Felzer BS, Hurteau MD. 2014. Effects of agriculture and timber harvest on carbon sequestration in the eastern US forests. J Geophys Res. doi: 10.1002/2013JG002409.
- Engstrom RT, Sanders FJ. 1997. Red-cockaded Woodpecker foraging ecology in an old-growth longleaf pine forest. Wilson Bull 109:203–17.Google Scholar
- Jenkins JC, Chojnacky DC, Heath LS, Birdsey RA. 2003. National-scale biomass estimators for United States tree species. For Sci 49:12–35.Google Scholar
- Johnsen KH, Butnor JR, Kush JS, Schmidtling RC, Nelson CD. 2009. Hurricane Katrina winds damaged longleaf pine less than loblolly pine. South J Appl For 33:178–81.Google Scholar
- Landers JL, Vanlear DH, Boyer WD. 1995. The longleaf pine forests of the Southeast—requiem or renaissance. J For 93:39–44.Google Scholar
- Metherell AK, Harding LA, Cole CV, Parton WJ. 1993. CENTURY soil organic matter model environment technical documentation. Agroecosystem Version 4.0. Fort Collins, CO: USDA-ARS.Google Scholar
- NRCS. 2013. Web Soil Survey. United States Department of Agriculture Natural Resources Conservation Service. Available online at http://websoilsurvey.nrcs.usda.gov. Accessed 1 July 2013.
- Onaindia M, Fernández de Manuel B, Madariaga I, Rodríguez-Loinaz G. 2013. Co-benefits and trade-offs between biodiversity, carbon storage and water flow regulation. For Ecol Manage 289:1–9.Google Scholar
- Parton WJ. 1996. The CENTURY model. In: Powlson D, Smith P, Smith J, Eds. Evaluation of soil organic matter models. Berlin: Springer. p 283–91.Google Scholar
- Parton WJ, Scurlock JMO, Ojima DS, Gilmanov TG, Scholes RJ, Schimel DS, Kirchner T, Menaut JC, Seastedt T, Moya EG, Kamnalrut A, Kinyamario JI. 1993. Observations and modeling of biomass and soil organic matter dynamics for the grassland biome worldwide. Global Biogeochem Cycles 7:785–809.CrossRefGoogle Scholar
- Remucal JM, McGee JD, Fehrenbacher MM, Best C, Mitchell RJ. 2013. Application of the climate action reserve’s forest project protocol to a longleaf pine forest under restoration management. J For 111:59–66.Google Scholar
- Samuelson LJ, Stokes TA, Butnor JR, Johnsen KH, Gonzalez-Benecke CA, Anderson P, Jackson J, Ferrari L, Martin TA, Cropper Jr WP. 2014. Ecosystem carbon stocks in Pinus palustris forests. Can J For Res (in press).Google Scholar
- Samuelson LJ, Whitaker WB. 2012. Relationships between soil CO2 efflux and forest structure in 50-year-old longleaf pine. For Sci 58:472–84.Google Scholar
- Scott JH, Burgan RE. 2005. Standard fire behavior fuel models: a comprehensive set for use with Rothermel’s surface fire spread model. The Bark Beetles, Fuels, and Fire Bibliography: 66.Google Scholar
- Smith P, Smith JU, Powlson DS, McGill WB, Arah JRM, Chertov OG, Coleman K, Franko U, Frolking S, Jenkinson DS, Jensen LS, Kelly RH, Klein-Gunnewiek H, Komarov AS, Li C, Molina JAE, Mueller T, Parton WJ, Thornley JHM, Whitmore AP. 1997. A comparison of the performance of nine soil organic matter models using datasets from seven long-term experiments. Geoderma 81:153–225.CrossRefGoogle Scholar
- USFWS. 2003. Recovery plan for the red-cockaded woodpecker (Picoides borealis): second revision. Atlanta, GA: United States Fish and Wildlife Service. p 296.Google Scholar
- Van Wagner CE, Stocks BJ, Lawson BD, Alexander ME, Lynham TJ, McAlpine RS. 1992. Development and structure of the Canadian forest fire behavior prediction system. Ottawa, ON: Fire Danger Group, Forestry Canada.Google Scholar