Advertisement

European Journal of Forest Research

, Volume 123, Issue 1, pp 45–51 | Cite as

Generalized height–diameter models—an application for major tree species in complex stands of interior British Columbia

  • H. TemesgenEmail author
  • K. v. Gadow
Original Paper

Abstract

Using permanent sample-plot data, selected tree height and diameter functions were evaluated for their predictive abilities for major tree species in complex (multiple age, size and species cohort) stands of interior British Columbia (BC), Canada. Two sets of models were evaluated. The first set included five models for estimating height as a function of individual tree diameter, the second set also included five models for estimating height as a function of individual tree diameter and other stand-level attributes. The inclusion of the BAL index (which simultaneously indicates the relative position of a tree and stand density) into the base height–diameter models increased the accuracy of prediction for all species. On average, by including stand level attributes, root mean square values were reduced by 30.0 cm. Based on the residual plots and fit statistics, these models can be recommended for estimating tree heights for major tree species in complex stands of interior BC. The model coefficients are documented for future use.

Keywords

Multi-age forests BAL index Canada 

Notes

Acknowledgements

We gratefully acknowledge the cooperation and financial support provided by the German Academic Exchange Program (DAAD), the British Columbia Ministry of Forests and University of British Columbia. We thank Drs. V. LeMay and P.L. Marshall for their comments on an earlier draft, and two anonymous referees for constructive comments. Part of this analysis was carried out when the lead author was a visiting scientist at the University of Göttingen, Germany.

References

  1. Boisvenue C (1999) Early height growth and regeneration: applicability of prognosis components to the southern interior of British Columbia. Master’s Thesis, University of British Columbia, Vancouver Google Scholar
  2. Burkhart HE, Parker RC, Strub MR, Oderwald MR (1972) Yield of old-field loblolly pine plantations. School of Forestry and Wildlife Resources, Virginia Polytechnic Institute and State University, Blacksburg, Publication FWS-3-72Google Scholar
  3. Curtis RO (1967) Height-diameter and height-diameter-age equations for second-growth Douglas-fir. For Sci 13:365–375Google Scholar
  4. Flewelling JW de Jong RD (1994) Considerations in simultaneous curve fitting for repeated height-diameter measurements. Can J For Res 24:1408–1414Google Scholar
  5. Froese K, LeMay V, Marshall PL, Zumrawi A (2001) PrognosisBC calibaration in the IDFdm2, Invermere Forest District: field sampling. Report to the B.C. Science Council, Burnaby Google Scholar
  6. Gallant AR (1987) Nonlinear statistical models. Wiley, New YorkGoogle Scholar
  7. Goldfield SM, Quandt RE (1965) Some tests for homoscedasticity. J Am Stat Assoc 60:539–547Google Scholar
  8. Hamilton DA, Edwards BM (1976) Modeling the probability of individual tree mortality. USDA Forest Service Research Paper INT-185, Intermountain Forest and Range Experiment Station, Ogden, UTGoogle Scholar
  9. Hasani BT, Marshall PL, LeMay V, Temesgen H (2001) Development of regeneration imputation models for the ICHmw2 in the vicinity of Nelson. Report to the BC Science Council, Burnaby Google Scholar
  10. Huang S, Titus SJ (1994) An age-independent individual tree height prediction model for boreal spruce-aspen stands in Alberta. Can J For Res 24:1295–1301Google Scholar
  11. Huang S, Titus SJ, Wiens DP (1992) Comparison of nonlinear height-diameter functions for major Alberta tree species. Can J For Res 22:1297–1304Google Scholar
  12. Hui GY, Gadow K v (1993) Zur Entwicklung von Einheitshöhenkurven am Beispel der Baumart Cunninghamia lanceolata. Allg Forst Jagdztg 164 12:218–220Google Scholar
  13. Kennel E (1972) Waldinventur und Holzaufkommensprognose für Bayern. Allg Forstz 615–616Google Scholar
  14. Kramer H (1964) Die Genauigkeit der Massenermittlung nach dem “Reihenverfahren”—zu dem gleichlautenden Beitrag von Oberforstmeister von Laer. Forst Holzwirt 140–141Google Scholar
  15. Lang A (1938) Bestandeseinheitshöhenkurven der Württembergischen Forsteinrichtungsanstalt. Allg Forst Jagdztg 168–176Google Scholar
  16. Larsen DR, Hann DW (1987) Height-diameter equations for seventeen tree species in southwest Oregon. Oregon State University Forest Research Laboratory, Corvallis, Research Paper 49Google Scholar
  17. Lencar C, Marshall PL (2000) Small tree height growth and stocking in the IDF dk1, dk2, dk3 subzones, Kamloops and Cariboo Forest Regions. Report to the Forest Practices and Research Branches, BC, Ministry of Forests, VictoriaGoogle Scholar
  18. Meidinger D, Pojar J (1991) Ecosystems of British Columbia. BC Ministry of Forests, VictoriaGoogle Scholar
  19. Nagel J (1991) Einheitshöhenkurvenmodell für Roteiche. Allg Forst Jagdztg 1:16–18Google Scholar
  20. Oliver CD, Larson BC (1990) Forest stand dynamics. McGraw Hill, New YorkGoogle Scholar
  21. Ratkowsky DA (1990) Handbook of nonlinear regression. Marcel and Dekker, New YorkGoogle Scholar
  22. SAS Institute Inc. (1990) SAS/STAT User’s Guide, Version 6, vol 2, 4th edn. Cary, NCGoogle Scholar
  23. Staudhammer C, LeMay V (2000) Height prediction equations using diameter and stand density measures. For Chron 76:303–309Google Scholar
  24. Temesgen H, LeMay VM (1999) Examination of tree height and diameter increment models fitted for PrognosisBC. A report submitted to the Forest Practices Branch, BC Ministry of Forests, Victoria, BCGoogle Scholar
  25. von Laer W (1964) Die Genauigkeit der Massenermittlung nach dem “Reihenverfahren”. Forst Holzwirt 139–140Google Scholar
  26. Wykoff WR, Crookston NL, Stage AR (1982) User’s guide to the stand prognosis model. USDA Forest Service General Technical Report INT-133, Ogden, UTGoogle Scholar
  27. Yang RC, Kozak A, Smith JHG (1978) The potential of Weibull-type functions as flexible growth curves. Can J For Res 8:424–431Google Scholar

Copyright information

© Springer-Verlag 2004

Authors and Affiliations

  1. 1.Department of Forest ResourcesOregon State UniversityCorvallisUSA
  2. 2.Georg-August-University GöttingenInstitute of Forest ManagementGöttingenGermany

Personalised recommendations