EDP Sciences logo
Search
Menu
All issues Volume 65 / No 2 (March-April 2008) Ann. For. Sci., 65 2 (2008) 203 References
Free Access
Issue
Ann. For. Sci.
Volume 65, Number 2, March-April 2008
Article Number 203
Number of page(s) 10
DOI https://doi.org/10.1051/forest:2007086
Published online 14 February 2008
References of  Ann. For. Sci. 65 (2008) 203
  1. Assmann E., The principles of forest yield study, Pergamon Press, Oxford, 1970.
  2. Briggs R.S., Site classification field guide, Maine Agri. Forest. Exp. Station Misc. Publ. 724, 1994.
  3. Briggs R.S., Lemin R.C. Jr., Soil drainage class effects on early response of balsam fir to precommercial thinning, Soil Sci. Soc. Am. J. 58 (1994) 1231-1239.
  4. Calama R., Montero G., Interregional nonlinear height-diameter model with random coefficients for stone pine in Spain, Can. J. For. Res. 34 (2004) 150-163 [CrossRef].
  5. Castedo Dorado F., Barrio Anta M., Parresol B.R., Álvarez González J.G., A stochastic height-diameter model for maritime pine ecoregions in Galicia (northwestern Spain), Ann. For. Sci. 62 (2005) 455-465 [EDP Sciences] [CrossRef].
  6. Castedo Dorado F., Diéguez-Aranda U., Barrio Anta M., Sánchez Rodríguez M., von Gadow K., A generalized height-diameter model including random components for radiata pine plantations in northwestern Spain, For. Ecol. Manage. 229 (2006) 202-213 [CrossRef].
  7. Chapman D.G., Statistical problems in population dynamics, Proc. Fourth Berkeley Symposium on Mathematical Statistics and Probability, Univ. Calif. Press, Berkeley and Los Angeles, 1961, pp. 153-168.
  8. Curtis R.O., Height-diameter and height-diameter-age equations for second-growth Douglas-fir, For. Sci. 13 (1967) 365-375.
  9. Daggett H., Long-term effects of herbicide and precommercial thinning treatments on species composition stand structure, and net present value in spruce-fir stands in Maine: the Austin Pond study, M.S. Thesis, University of Maine, 2003.
  10. Demidenko E., Mixed models: Theory and applications, John Wiley & Sons, Inc., Hoboken, New Jersey, 2004.
  11. Ek A.R., Birdsall E.T., Spears R.J., A simple model for estimating total and merchantable tree heights, USDA Forest Service, North Central Forest Experiment Station, St. Paul, Minnesota, Res. Note NC-309, 1984.
  12. Fang Z., Bailey R.L., Height-diameter models for tropical forests on Hainan Island in southern China, For. Ecol. Manage. 110 (1998) 315-327 [CrossRef].
  13. Fang Z., Bailey R.L., Shiver B.D., A multivariate simultaneous prediction system for stand growth and yield with fixed and random effects, For. Sci. 47 (2001) 550-562.
  14. Haglöf, AB, Users guide Vertex III and Transponder T3, Haglöf Sweden, AB, Långsele, Sweden, 2002.
  15. Hall D.B., Bailey R.L., Modeling and prediction of forest growth variables based on multilevel nonlinear mixed models, For. Sci. 47 (2001) 311-321.
  16. Huang S., Price D., Titus S.J., Development of ecoregion-based height $\pm $ diameter models for white spruce in boreal forests, For. Ecol. Manage. 129 (2000) 125-141 [CrossRef].
  17. Huang S., Titus S.J., Wiens D.P., Comparison of nonlinear height-diameter functions for major Alberta tree species, Can. J. For. Res. 22 (1992) 1297-1304 [CrossRef].
  18. Huang S., Yang Y., Wang Y., A critical look at procedures for validating growth and yield models, in: Amaro A., Reed D., Soares P., (Eds.), Modelling forest systems, CABI International, Cambridge, Massachusetts, pp. 271-293.
  19. Kozak A., Kozak R., Does cross validation provide additional information in the evaluation of regression models? Can. J. For. Res. 33 (2003) 976-987 [CrossRef].
  20. Lappi J., Calibration of height and volume equations with random parameters, For. Sci. 37 (1991) 781-801.
  21. Lappi J., Bailey R.I., Height prediction model with random stand and tree parameters: An alternative to traditional site index methods, For. Sci. 34 (1988) 907-927.
  22. Lappi J., Malinen J., Random-parameter height/age models when stand parameters and stand age are correlated, For. Sci. 40 (1994) 715-731.
  23. Lei Y., Parresol B.R., Remarks on height-diameter modeling, USDA Forest Service, Southern Research Station, Asheville, North Carolina, Res. Note SRS-10, 2001.
  24. Lorimer C.G., The presettlement forest and natural disturbance cycle of northeastern Maine, Ecology 58 (1977) 139-148 [CrossRef].
  25. Lynch T.B., Holley A.G., Stevenson D.J., A random-parameter height-dbh model for cherrybark oak, South. J. Appl. For. 29 (2005) 22-26.
  26. MacFarlane D.W., Ecologically stratified height-diameter models for hardwood species in northwestern lower Michigan, in: Yaussy D.A., Hix D.M. Long R.P., Goebel P.C. (Eds.), Proc. 14th Central Hardwood Forest Conf., USDA Forest Service, Newtown Square, Pennyslvania, Gen. Tech. Rep. NE-316, 2004, pp. 87-93.
  27. Mehtätalo L., A longitudinal height-diameter model for Norway spruce in Finland, Can. J. For. Res. 34 (2004) 131-140 [CrossRef].
  28. Meyer H.A., A mathematical expression for height curves, J. For. 38 (1940) 415-420.
  29. Nanos N., Calama R., Montero G., Gil L., Geostatistical prediction of height/diameter models, For. Ecol. Manage. 195 (2004) 221-235 [CrossRef].
  30. Oliver C.D., Larson B.C., Forest stand dynamics,(update edition), John Wiley & Sons, Inc., New York, 1996.
  31. Parresol B.R., Baldcypress height-diameter equations and their prediction confidence intervals, Can. J. For. Res. 22 (1992) 1429-1434 [CrossRef].
  32. Peng C., Zhang L., Liu J., Developing and validating nonlinear height-diameter models for major tree species of Ontario's boreal forests, North. J. Appl. For. 18 (2001) 87-94.
  33. Pienaar L.V., Turnbull K.J., The Chapman-Richards generalization of von Bertalanffy's growth model for basal area growth and yield in even-aged stands, For. Sci. 19 (1973) 2-22.
  34. Pinheiro J.C., Bates D.M., Mixed-effects models in S and S-PLUS, Springer, New York, 2000.
  35. Pinheiro J.C., Bates D.M., DebRoy S., Sarkar D, nlme: Linear and nonlinear mixed effects models, R package version 3.1-65, 2005, available online at http://www.R-project.org.
  36. R Development Core Team, R: A language and environment for statistical computing (Version 2.2), R Foundation for Statistical Computing, Vienna, Austria (ISBN 3-900051-07-0), 2005, available online at http://www.R-project.org.
  37. Ratkowsky D.A., Nonlinear regression modeling: a unified practical approach, Marcel Dekker, Inc., New York, 1983.
  38. Ratkowsky D.A., Reedy T.J., Choosing near-linear parameters in the four-parameter logistic model for radioligand and related assays, Biometrics 42 (1986) 575-582 [PubMed] [CrossRef].
  39. Richards F.J., A flexible growth function for empirical use, J. Exp. Bot. 10 (1959) 290-300 [CrossRef].
  40. Saunders M.R., Wagner, R.G., Long-term spatial and structural dynamics in Acadian mixedwood stands managed under various silvicultural systems, Can. J. For. Res., in press.
  41. Sendak P.E., Brissette J.C., Frank R.M., Silviculture affects composition, growth, and yield in mixed northern conifers: 40-year results from the Penobscot Experimental Forest, Can. J. For. Res. 33 (2003) 2116-2128 [CrossRef].
  42. Sharma M., Zhang S.Y., Height-diameter models using stand characteristics for Pinus banksiana and Picea mariana, Scand. J. For. Res. 19 (2004) 442-451 [CrossRef].
  43. Trorey L.G., A mathematical method for the construction of diameter height curves based on site, For. Chron. 8 (1932) 121-132.
  44. Weibull W., A statistical distribution function of wide applicability, J. Appl. Mech. 18 (1951) 293-296.
  45. Wilkinson R.C., Leader and growth characteristics of eastern white pine associated with white pine weevil attack susceptibility, Can. J. For. Res. 13 (1983) 78-84 [CrossRef].
  46. Yang, Y., Monserud, R.A., Huang, S., An evaluation of diagnostic tests and their roles in validating forest biometric models, Can. J. For. Res. 34 (2004) 619-629 [CrossRef].
  47. Zhang S., Burkhart H.E., Amateis R.L., The influence of thinning on tree height and diameter relationships in loblolly pine plantations, South. J. Appl. For. 21 (1997) 199-205.