Urban Ecosystems

, Volume 12, Issue 1, pp 95–113 | Cite as

Urban forest biomass estimates: is it important to use allometric relationships developed specifically for urban trees?

  • M. R. McHale
  • I. C. Burke
  • M. A. Lefsky
  • P. J. Peper
  • E. G. McPherson


Many studies have analyzed the benefits, costs, and carbon storage capacity associated with urban trees. These studies have been limited by a lack of research on urban tree biomass, such that estimates of carbon storage in urban systems have relied upon allometric relationships developed in traditional forests. As urbanization increases globally, it is becoming important to more accurately evaluate carbon dynamics in these systems. Our goal was to understand the variability and range of potential error associated with using allometric relationships developed outside of urban environments. We compared biomass predictions from allometric relationships developed for urban trees in Fort Collins, Colorado to predictions from allometric equations from traditional forests, at both the individual species level and entire communities. A few of the equations from the literature predicted similar biomass to the urban-based predictions, but the range in variability for individual trees was over 300%. This variability declined at increasingly coarse scales, reaching as low as 60% for a street tree community containing 11 tree species and 10, 551 trees. When comparing biomass estimates between cities that implement various allometric relationships, we found that differences could be a function of variability rather than urban forest structure and function. Standardizing the methodology and implementing averaged equations across cities could be one potential solution to reducing variability; however, more accurate quantification of biomass and carbon storage in urban forests may depend on development of allometric relationships specifically for urban trees.


Biomass Carbon dioxide Allometric relationships Volume equations Urban forest 



We would like to thank Todd Wojtowicz and Krista Northcott for their priceless help in the field and lab. Sonia Hall, Sarah Hamman, and Molly Cavaleri were a source of general guidance in developing this project while the Colorado Tree Coalition was a source of inspiration, as well as a variety of forestry tools. We are grateful to the USDA Forest Service (Fort Collins Office) for loaning us the rare and endangered Barr and Stroud optical dendrometer. Mike Ryan and Scott Denning provided valuable input on several earlier versions of this manuscript. Finally, we are grateful to the anonymous reviewers whose advice significantly improved this manuscript. This research was supported in part by funds provided by the Pacific Southwest Research Station, Forest Service, U.S. Department of Agriculture.


  1. Alemdag IS (1984) Total tree and merchantable stem biomass equations for Ontario hardwoods. Information Report PI-X-46. Agriculture Canada, Petawawa National Forestry InstituteGoogle Scholar
  2. Alden HA (1995) Hardwoods of North America. FPL-GTR-83. USDA Forest Service, Forest Products Laboratory, Madison, WIGoogle Scholar
  3. Araújo TM, Higuchi N, Andrade de Carvalho Jr J (1999) Comparison of formulae for biomass content in a tropical rain forest site in the state of Para, Brazil. For Ecol Manag 117(1–3):43–52CrossRefGoogle Scholar
  4. Baker LA, Hartzheim PM, Hobbie SE, King JY, Nelson KC (2007) Effect of consumption choices on fluxes of carbon, nitrogen and phosphorus through households. Urban Ecosyst 10(2):97–117CrossRefGoogle Scholar
  5. Bickelhaupt D, Leaf A, Richards N (1973) Effect of branching habit on above-ground dry weight estimates of Acer saccharum stands. In: Young H (ed) IUFRO biomass stuies, Nancy, France and Vancouver, BC. University of Maine, College of Life Sciences and Agriculture, Orono, ME, pp 219–230Google Scholar
  6. Brenneman DF, Gardner W, Schoenhofen L, Marsh P (1978) Biomass of species and stands of West Virginia hardwoods. In: Pope P (ed) Proceedings, central hardwood conference II; 1978 November 14–16. West Lafayette, IN, Purdue University, pp 159–178Google Scholar
  7. Bunce RGH (1968) Biomass and production of trees in a mixed deciduous woodland I. Girth and height as parameters for the estimation of tree dry weight. J Ecol 56:759–775CrossRefGoogle Scholar
  8. Celestian SB, Martin CA (2005) Effects of parking lot location on size and physiology of four southwestern U.S. landscape trees. J Arboric 31(4):191–251Google Scholar
  9. Clark A III, Phillips DR, Fredrick DJ (1985) Weight, Volume, and Physical Properties of Major Hardwood Species in the Gulf and Atlantic Coastal Plains. RP SE-250. USDA Forest Service, Southeastern Forest Experiment Station, Ashville, NCGoogle Scholar
  10. Clark NA, Wynne RH, Schmoldt DL (2000) A review of past research on dendrometers. For Sci 46(4):570–576Google Scholar
  11. Clark DA, Brown S, Kicklighter DW, Chambers JQ, Thomlinson JR, Ni J (2001) Measuring net primary production in forests: Concepts and field methods. Ecol Appl 11(2):356–370CrossRefGoogle Scholar
  12. Close RE, Nguyen PV, Kieblaso JJ (1996a) Urban vs. natural sugar maple growth: I. Stress symptoms and phenology in relation to site characteristics. J Arboric 22(3):144–150Google Scholar
  13. Close RE, Kieblaso JJ, Nguyen PV, Schutzki RE (1996b) Urban vs. natural sugar maple growth: II. Water relations. J Arboric 22(4):187–192Google Scholar
  14. Golubiewski NE (2006) Urbanization increases grassland carbon pools: Effects of landscaping in Colorado’s Front Range. Ecol Appl 16(2):555–571PubMedCrossRefGoogle Scholar
  15. Hahn JT (1984) Tree volume and biomass equations for the lake states. Research Paper NC-250. USDA Forest Service, North Central Forest Experiment Station, St. Paul, MNGoogle Scholar
  16. Harris W, Goldstein R, Henderson G (1973) Analysis of forest biomass pool, annual primary production and turnover of biomass for a mixed deciduous watershed. In: Young H (ed) IUFRO biomass studies, Nancy, France and Vancouver, BC. University of Maine, College of Life Sciences and Agriculture, Orono, ME, pp 41–64Google Scholar
  17. Hepp TE, Brister GH (1982) Estimating crown biomass in loblolly pine plantations in the Carolina flatwoods. For Sci 28:115–127Google Scholar
  18. Imhoff ML, Bounoua L, DeFries R, Lawrence T, Stutzer D, Tucker CJ, Ricketts T (2004) The consequences of urban land transformation on net primary productivity in the United States. Remote Sens of Environ, 89:434–443CrossRefGoogle Scholar
  19. Jenkins JC, Chojnacky DC, Heath LS, Birdsey RA (2003) National-scale biomass estimators for United States tree species. For Sci 49(1):12–35Google Scholar
  20. Jenkins JC, Chojnacky DC, Heath LS, Birdsey RA (2004) Comprehensive database of diameter-based biomass regressions for North American tree species. GTR NE-319. USDA Forest Service, Northeastern Research Station, Newtown Square, PAGoogle Scholar
  21. Jo H-K, McPherson EG (2001) Indirect carbon reduction by residential vegetation and planting strategies in Chicago, USA. J Environ Manag 61:165–177CrossRefGoogle Scholar
  22. Kaye JP, McCulley RL, Burke IC (2005) Carbon fluxes, nitrogen cycling, and soil microbial communities in adjacent urban, native and agriculture ecosystems. Globl Chang Biol 11:575–587CrossRefGoogle Scholar
  23. Ketterings QM, Coe R, van Noordwijk M, Ambagau Y, Palm CA (2001) Reducing uncertainty in the use of allometric biomass equations for predicting above-ground tree biomass in mixed secondary forests. For Ecol Manag 146(1–3):199–209CrossRefGoogle Scholar
  24. Kramer PJ, Kozlowski TT (1979) Physiology of Plants. Academic Press, San Diego Ca, p 495Google Scholar
  25. Lefsky MA, McHale MR (2008) Volume estimates of trees with complex architecture from terrestrial laser scanning. Journal of Applied Remote Sensing 2(1):023521CrossRefGoogle Scholar
  26. Madgwick HAI, Satoo T (1975) On estimating aboveground weights of tree stands. Ecology 56:1446–1450CrossRefGoogle Scholar
  27. McPherson EG (1998) Atmospheric carbon dioxide reduction by Sacramento’s urban forest. J Arboric 24(4):215–223Google Scholar
  28. McPherson EG, Simpson JR (2001) Carbon dioxide reductions through urban forestry: guidelines for professional and volunteer tree planters. PSW GTR-171. USDA Forest Service, Pacific Southwest Research Station, Center for Urban Forest Research, Albany, CAGoogle Scholar
  29. McPherson EG, Simpson JR, Xiao Q, Peper PJ, Maco SE (2003) Benefit-Cost Analysis of Fort Collins’ Municipal Forest. Internal Report. CUFR-2. USDA Forest Service, Pacific Southwest Research Station, Center for Urban Forest ResearchGoogle Scholar
  30. McPherson EG, Simpson JR, Peper PF (2005) Municipal forest benefits and costs in five US cities. J For 103:411–416Google Scholar
  31. Nowak DJ (1994) Atmospheric carbon dioxide reduction by Chicago’s urban forest. In: McPherson EG, Nowak DJ, Rowntree RA (eds) Chicago’s urban forest ecosystem: results of the Chicago Urban Forest Climate Project. Gen. Tech. Rep. NE-186. U.S. Department of Agriculture, Forest Service, Northeastern Forest Experiment Station, Radnor, PA, pp 83–94Google Scholar
  32. Nowak DJ, Crane DE (2000) The urban forest effects (UFORE) model: quantifying urban forest structure and functions. In: Hansen M, Burk T (eds) Integrated tools for natural resources inventories in the 21st century: proceedings of the IUFRO conference; 1998 August 16–20; Boise, ID. Gen. Tech. Rep. NC-212. U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station, St. Paul, MN, pp 714–720Google Scholar
  33. Nowak DJ, Crane DE, Stevens JC, Ibarra M (2002) Brooklyn’s Urban Forest. GTR NE-290. USDA Forest Service, Northeastern Research Station., Newtown Square, PAGoogle Scholar
  34. Nyakuengama JG, Downes GM, Ng J (2002) Growth and wood density responses to later-age fertilizer application in Pinus radiata. IAWA Journal 23(4):431–448Google Scholar
  35. Parresol BR (1999) Assessing tree and stand biomass: A review with examples and critical comparisons. For Sci 45(4):573–593Google Scholar
  36. Pastor J, Aber JD, Melillo JM (1984) Biomass prediction using generalized allometric regressions for some northeast tree species. For Ecol Manag 7(4):265–274CrossRefGoogle Scholar
  37. Pataki DE, Alig RJ, Fung AS, Golubiewski NE, Kennedy CA, McPherson EG, Nowak DJ, Pouyat RV, Lankao PR (2006) Urban ecosystems and the North American carbon cycle. Glob Chang Biol 12(11):2092–2102CrossRefGoogle Scholar
  38. Perala DA, Alban DH (1994) Allometric biomass estimators for Aspen-dominated ecosystems in the upper Great Lakes. Research Paper NC-314. USDA Forest Service, North Central Experiment Station, St. Paul, MNGoogle Scholar
  39. Pillsbury NH, Reimer JL, Thompson RP (1998) Tree volume equations for fifteen urban species in California. Technical Report No. 7. Urban Forest Ecosystems Institute, California’s Polytech State University, San Luis ObsipoGoogle Scholar
  40. Rhoades RW, Stipes RJ (1999) Growth of trees on Virginia Tech campus in response to various factors. J Arboric 25(4):211–217Google Scholar
  41. Schlaegel BE (1984) Green ash volume and weight tables. Research Paper SO-206. USDA Forest Service, Southern Forest Experiment Station, New Orleans, LAGoogle Scholar
  42. Standish JT, Manning G, Demaerschalk J (1985) Development of biomass equations for British Columbia tree species. Information Report BC-X-254. Canadian Forestry Service, Pacific Forest Research Centre, Victoria, BCGoogle Scholar
  43. Steingraeber DA (1982) Phenotypic plasticity of branching patter in sugar maple (Acer saccharum). Am J Bot.69(4):638–640CrossRefGoogle Scholar
  44. Ter-Mikaelian MT, Korzukhin MD (1997) Biomass equations for sixty-five North American tree species. For Ecol Manag 97(1):1–24CrossRefGoogle Scholar
  45. Tritton LM, Hornbeck JW (1982) Biomass equations for major tree species of the Northeast. GTR NE-69. USDA Forest Service, Northeastern Forest Experiment Station, Broomall, PAGoogle Scholar
  46. Van Laar A, Akca A (1997) Forest Mensuration. Cuvillier Verlag, Gottingen, Germany, p 418Google Scholar
  47. Williams RA, McClenahen JR (1984) Biomass prediction equations for seedlings, sprouts, and saplings of 10 central hardwood species. For Sci 30(2):523–527Google Scholar
  48. Young HE, Ribe JH, Wainwright K (1980) Weight tables for tree and shrub species in Maine. Miscellaneous Report 230, Life Sciences and Agriculture Experiment Station, University of Maine at Orono, Orono, Maine, USAGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • M. R. McHale
    • 1
    • 4
  • I. C. Burke
    • 2
  • M. A. Lefsky
    • 1
  • P. J. Peper
    • 3
  • E. G. McPherson
    • 3
  1. 1.Department of Forest, Rangeland, and Watershed StewardshipColorado State UniversityFort CollinsUSA
  2. 2.Haub School and Ruckelshaus Institute of Environment and Natural ResourcesUniversity of WyomingLaramieUSA
  3. 3.USDA Forest Service, Pacific Southwest Research StationCenter for Urban Forest ResearchDavisUSA
  4. 4.Department of Forestry and Environmental ResourcesNorth Carolina State UniversityRaleighUSA

Personalised recommendations