Forest managers need accurate biomass equations to plan thinning for fuel reduction or energy production. Estimates of carbon sequestration also rely upon such equations. The current allometric equations for ponderosa pine ( Pinus ponderosa) commonly employed for California forests were developed elsewhere, and are often applied without consideration potential for spatial or temporal variability. Individual-tree aboveground biomass allometric equations are presented from an analysis of 79 felled trees from four separate management units at Blacks Mountain Experimental Forest: one unthinned and three separate thinned units. A simultaneous set of allometric equations for foliage, branch and bole biomass were developed as well as branch-level equations for wood and foliage. Foliage biomass relationships varied substantially between units while branch and bole biomass estimates were more stable across a range of stand conditions. Trees of a given breast height diameter and crown ratio in thinned stands had more foliage biomass, but slightly less branch biomass than those in an unthinned stand. The observed variability in biomass relationships within Blacks Mountain Experimental Forest suggests that users should consider how well the data used to develop a selected model relate to the conditions in any given application.
References
[1]
Birdsey, R.A. Carbon Storage and Accumulation in United States Forest Ecosystems; USDA Forest Service: Washington, DC, USA, 1992.
[2]
Law, B.E.; Thornton, P.E.; Irvine, J.; Anthoni, P.M. Carbon storage and fluxes in ponderosa pine forests at different developmental stages. Glob. Chang. Biol. 2001, 7, 755–777, doi:10.1046/j.1354-1013.2001.00439.x.
[3]
Keane, R.E.; Reinhardt, E.D.; Scott, J.; Gray, K.; Reardon, J. Estimating forest canopy bulk density using six indirect methods. Can. J. For. Res. 2005, 3, 724–739.
[4]
Rothermel, R.C. A Mathematical Model for Predicting Fire Spread; USDA Forest Service Intermountain Forest and Range Experiment Station: Ogden, UT, USA, 1972.
[5]
Rothermel, R.C. How to Predict the Spread and Intensity of Forest and Range Fires; USDA Forest Service, Intermountain Forest and Range Experiment Station: Ogden, UT, USA, 1983.
[6]
Fitzgerald, S.A. Fire Ecology of Ponderosa Pine and the Rebuilding of Fire Resilient Ponderosa Pine Ecosystems. In Proceedings of the Symposium on Ponderosa Pine: Issues, Trends and Management, Klamath Falls, OR, USA, 18–21 October 2004; Ritchie, M.W., Maguire, D.A., Youngblood, A., Eds.; USDA Forest Service, Pacific Southwest Research Station: Albany, CA, USA, 2005; pp. 207–225.
Skinner, C.N.; Taylor, A.H. Southern Cascades Bioregion. In Fire in California’s Ecosystems; Sugihara, N.G, van Wagtendonk, J.W., Shaffer, K.E., Fites-Kaufman, J., Thode, A.E., Eds.; University of California Press: Berkeley, CA, USA, 2006; pp. 195–224.
[9]
Affleck, D.L.R.; Keyes, C.R.; Goodburn, J.M. Conifer crown fuel modeling: Current limits and potential for improvement. West. J. Appl. For. 2012, 4, 165–169, doi:10.5849/wjaf.11-039.
Zhang, J.W.; Powers, R.F.; Skinner, C.N. To Manage or Not to Manage: The Role of Silviculture in Sequestering Carbon in the Specter Of Climate Change. In Integrated Management of Carbon Sequestration and Biomass Utilization Opportunities in a Changing Climate, Proceedings of the 2009 National Silviculture Workshop, Boise, ID, USA, 15–18 June 2009; Jain, T.B., Graham, R.T., Sandquist, J., Tech., Eds.; USDA Forest Service Rocky Mountain Research Station: Fort. Collins, CO, USA, 2010; pp. 95–110.
[12]
Gholz, H.L.; Grier, C.C.; Campbell, A.G.; Brown, A.T. Equations for Estimating Biomass and Leaf Area of Plants in the Pacific Northwest, Research Paper 41; Oregon State University Forest Research Laboratory: Corvallis, OR, USA, 1979.
[13]
Cochran, P.H.; Jennings, J.W.; Youngberg, C.T. Biomass Estimators for Thinned Second-Growth Ponderosa Pine Trees; USDA Forest Service, Pacific Northwest Forest and Range Experiment Station: Portland, OR, USA, 1984.
[14]
Brown, J. Weight and Density of Crowns of Rocky Mountain Conifers; USDA Forest Service, Intermountain Forest and Range Experiment Station: Ogden, UT, USA, 1978.
[15]
Monserud, R.A.; Marshall, J.D. Allometric crown relations in three northern Idaho conifer species. Can. J. For. Res. 1999, 29, 521–535.
[16]
Jenkins, J.C.; Chojnacky, D.C.; Heath, L.S.; Birdsey, R.A. National scale biomass estimators for United States tree species. For. Sci. 2003, 49, 12–35.
[17]
Moeur, M. Crown Width and Foliage Weight of Northern Rocky Mountain Conifers; USDA Forest Service Intermountain Forest and Range Experiment Station: Ogden, UT, USA, 1981.
[18]
Assmann, E. Principles of Forest Yield Study; Pergamon Press: New York, NY, USA, 1970; p. 506.
[19]
Tappeiner, J.C.; Maguire, D.A.; Harrington, T.B. Silviculture and Ecology of Western U.S. Forests; Oregon State University Press: Corvallis, OR, USA, 2007; p. 440.
[20]
Harrod, R.J.; Peterson, D.W.; Povak, N.A.; Dodson, E.K. Thinning and prescribed fire effects on overstory tree and sang structure in dry coniferous forests of the interior Pacific Northwest. For. Ecol. Manag. 2009, 258, 712–721.
[21]
Agee, J.K. Fire Ecology of Pacific Northwest Forests; Island Press: Washington, DC, USA, 1933; p. 493.
[22]
Ritchie, M.W.; Skinner, C.N.; Hamilton, T.A. Probability of tree survival after wildfire in an interior pine forest of northern California: Effects of thinning and prescribed fire. For. Ecol. Manag. 2007, 247, 200–208.
[23]
Barrett, J.W. Height Growth and Site Index Curves for Managed, Even-aged Stands of Ponderosa Pine in the Pacific Northwest; USDA Forest Service, Pacific Northwest Forest and Range Experiment Station: Portland, OR, USA, 1978.
[24]
Alexander, E.B. Ecological Unit Inventory of Blacks Mountain Experimental Forest; On File, Redding Laboratory, Pacific Southwest Research Station: Redding, CA, USA, 1994.
[25]
Greene, W.H. Econometric Analysis, 5th ed.; Prentice Hall: Upper Saddle River, New York, NY, USA, 2003; p. 1026.
[26]
Parresol, B. Assessing tree and stand biomass: A review with examples and critical comparisons. For. Sci. 1999, 45, 573–593.
[27]
Parresol, B. Additivity of nonlinear biomass equations. Can. J. For. Res. 2001, 31, 865–878.
[28]
Burnham, K.P.; Anderson, D.R. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach, 2nd ed.; Springer: New York, NY, USA, 2002; p. 488.
[29]
Van Velsen, J.L. A Corrected AIC for Seemingly Unrelated Regressions Models; Cornell University: Ithaca, NY, USA, 2009.
[30]
Bozdogan, H. Akaike’s information criterion and recent developments in information complexity. J. Math. Psych. 2000, 44, 62–91.
[31]
Kittredge, J. Estimation of the amount of foliage of trees and stands. J. For. 1944, 42, 905–912.
[32]
Heath, L.S.; Hansen, M.H.; Smith, J.E.; Smith, W.B.; Miles, P.D. Investigation into Calculating Tree Biomass and Carbon in the FIADB Using a Biomass Expansion Factor Approach. In Proceedings of the 2008 Forest Inventory and Analysis (FIA) Symposium, Park City, UT, USA, 21–23 October 2008; McWilliams, W., Moisen, G., Czaplewski, R., Eds.; USDA Forest Service Rocky Mountain Research Station: Fort Collins, CO, USA, 2009.
[33]
California Environmental Protection Agency, Air Resources Board. Compliance Offset Protocol U.S. Forest Projects; California Environmental Protection Agency: Sacramento, CA, USA, 2011; p. 113. Available online: http://www.arb.ca.gov/regact/2010/capandtrade10/copusforest.pdf (accessed on 5 December 2012).
[34]
Jenkins, J.C.; Chojnacky, D.C.; Heath, L.S.; Birdsey, R.A. Comprehensive Database of Diameter-Based Biomass Regressions for North American Tree Species; USDA Forest Service, Northeastern Research Station: Newtown Square, PA, USA, 2004.
[35]
Návar Ch., J.J.; González B., N.; Graciano L., J.J.; Dale, V.; Parresol, B. Additive equations for pine species of forest plantations of Durango, Mexico. Madera y Bosques 2004, 10, 17–26.
