Modeling forest canopy structure and density by combining point quadrat sampling and survival analysis

Forest Science

Volumn 59, Issue 6, 2013, Pages 681-692

  Maynard, Daniel S ^a   Ducey, Mark J ^b   Congalton, Russell G ^b   Hartter, Joel ^b  

^a Yale University   (United States)

^b UNIVERSITY OF NEW HAMPSHIRE   (United States)

Author keywords

Forest sampling; Leaf area index; Regression; Variance estimation; Vertical structure

Indexed keywords

CANOPY STRUCTURE; LASER RANGE FINDERS; LEAF AREA INDEX; NUMBER OF SAMPLES; REGRESSION; SURVIVAL ANALYSIS; VARIANCE ESTIMATION; VERTICAL STRUCTURES;

BIOINFORMATICS; ESTIMATION; REGRESSION ANALYSIS; WEIBULL DISTRIBUTION;

FORESTRY;

FORESTS; REGRESSION ANALYSIS; SAMPLING; STATISTICAL DISTRIBUTION;

EID: 84890249421     PISSN: 0015749X     EISSN: None     Source Type: Journal    
DOI: 10.5849/forsci.12-086     Document Type: Article

References (60)

1. Aalen, O.O. 1978. Nonparametric inference for a family of counting processes. Ann. Statist. 6(4):701-726.
2. Abdelfattah, A., and A. Mustafa. 2012. Reliability equivalence factors for some systems with mixture Weibull failure rates. Am. J. Math. Stat. 2(1):6-12.
3. Aber, J.D. 1979. Foliage-height profiles and succession in northern hardwood forests. Ecology 60(1):18-23.
4. Baldocchi, D.D., and P.C. Harley. 2006. Scaling carbon dioxide and water vapour exchange from leaf to canopy in a deciduous forest. II. Model testing and application. Plant Cell Environ. 18(10):1157-1173.
5. Baldocchi, D.D., K.B. Wilson, and L. Gu. 2002. How the environment, canopy structure and canopy physiological functioning influence carbon, water and energy fluxes of a temperate broad-leaved deciduous forest-an assessment with the biophysical model CANOAK. Tree Physiol. 22:1065-1077.
6. Bolstad, P.V., and S.T. Gower. 1990. Estimation of leaf area index in fourteen southern Wisconsin forest stands using a portable radiometer. Tree Physiol. 7:115-124.
7. Chen, J.M., and T.A. Black. 1992a. Defining leaf area index for non-flat leaves. Plant Cell Environ. 15:421-429.
8. Chen, J.M., and T.A. Black. 1992b. Foliage area and architecture of plant canopies from sunfleck size distributions. Agr. For. Meteorol. 60:249-266.
9. Chen, J.M., and J. Cihlar. 1995. Plant canopy gap-size analysis theory for improving optical measurements of leaf-area index. Appl. Opt. 34(27):6211-6222.
10. Coops, N.C., T. Hilker, M.A. Wulder, B. St-Onge, G. Newn-ham, A. Siggins, and J.A.T. Trofymow. 2007. Estimating canopy structure of Douglas-fir forest stands from discrete-return LiDAR. Trees 21(3):295-310.
11. Côté, J.F., R.A. Fournier, and R. Egli. 2011. An architectural model of trees to estimate forest structural attributes using terrestrial LiDAR. Environ. Model. Softw. 26:761-777.
12. Cox, D.R. 1972. Regression models and life-tables. J. R. Stat. Soc. Ser. B. 34(2):187-220.
13. De Angelis, R., R. Capocaccia, T. Hakulinen, B. Soderman, and A. Verdecchia. 1999. Mixture models for cancer survival analysis: Application to population-based data with covariates. Stat. Med. 18:441-454.
14. DeMaynadier, P.G., and M.L. Hunter Jr. 1999. Forest canopy closure and juvenile emigration by pool-breeding amphibians in Maine. J. Wildl. Manage. 63(2):441-450.
15. Denison, R.F. 1997. Minimizing errors in LAI estimates from laser-probe inclined-point quadrats. Field Crops Res. 51: 231-240.
16. Ford, E.D., and J.D. Deans. 1978. The effects of canopy structure on stemflow, throughfall and interception loss in a young Sitka spruce plantation. J. Appl. Ecol. 15(3):905-917.
17. Fujimori, T. 1971. Analysis of forest canopy on the basis of a Tsuga heterophylla stand. Jpn. J. Ecol. 59 (134-139).
18. Fukushima, Y., T. Hiura, and S.I. Tanabe. 1998. Accuracy of the MacArthur-Horn method for estimating a foliage profile. Agr. For. Meteorol. 92:203-210.
19. Gove, J.H. 2003. Moment and maximum likelihood estimators for Weibull distributions under length- and area-biased sampling. Environ. Econ. Stat. 10:455-467.
20. Green, P.J. 1984. Iteratively reweighted least squares for maximum likelihood estimation and some robust and resistant alternatives. J. R. Stat. Assoc. B 46(2):149-192.
21. Groeneveld, D. 1997. Vertical point quadrat sampling and an extinction factor to calculate leaf area index. J. Arid Environ. 36:475-485.
22. Hayes, J.P., S.S. Chan, W.H. Emmingham, J.C. Tappeiner, L.D. Kellogg, and J.D. Bailey. 1997. Wildlife response to thinning young forests in the Pacific Northwest. J. For. 95(8):28-33.
23. Hollinger, D.Y. 1989. Canopy organization and foliage photo-synthetic montane capacity in a broad-leaved evergreen montane forest. Funct. Ecol. 3(1):53-62.
24. Jennings, S.B., N.D. Brown, and D. Sheil. 1999. Assessing forest canopies and understory illumination: Canopy closure, canopy cover and other measures. For. 72(1):59-73.
25. Jonckheere, I., S. Fleck, K. Nackaerts, B. Muys, P. Coppin, M. Weiss, and F. Baret. 2004. Review of methods for in situ leaf area index determination: Part I. Theories, sensors and hemispherical photography. Agr. For. Meteorol. 121:19-35.
26. Kalbfleisch, J.D., and R.L. Prentice. 2002. The statistical analysis of failure time data, 2nd ed. John Wiley and Sons, Hoboken, NJ. 462 p.
27. Kaplan, E.L., and P. Meier. 1958. Nonparametric estimation from incomplete observations. J. Am. Stat. Assoc. 53:457-481.
28. Lambert, P.C., J.R. Thompson, C.L. Weston, and P.W. Dickman. 2007. Estimating and modeling the cure fraction in population-based cancer survival analysis. Biostatistics 8(3):576-594.
29. Levy, E.B., and E.A. Madden. 1933. The point method of pasture analysis. N. Z. J. Agr. 46:267-279.
30. Long, J.N., and T.W. Daniel. 1990. Assessment of growing stock in uneven-aged stands. West. J. Appl. For. 5(3):93-96.
31. Lovell, J.L., D.L.B. Jupp, D.S. Culvenor, and N.C. Coops. 2003. Using airborne and ground-based ranging LiDAR to measure canopy structure in Australian forests. Can. J. Remote Sens. 29(5):607-622.
32. MacArthur, R.H., and H.S. Horn. 1969. Foliage profile by vertical measurements. Ecology 50(5):802-804.
33. Maguire, D.A., and A. Kanaskie. 2002. The ratio of live crown length to sapwood area as a measure of crown sparseness. For. Sci. 48(1):93-100.
34. Martens, S.N., D.D. Breshears, and C.W. Meyer. 2000. Spatial distributions of understory light along the grassland/forest continuum: Effects of cover, height, and spatial pattern of tree canopies. Ecol. Model. 126:79-93.
35. Mitchell, R.G., R.H. Waring, and G.B. Pitman. 1983. Thinning lodgepole pine increases tree vigor and resistance to mountain pine beetle. For. Sci. 29(1):204-211.
36. Moril, S., and A. Hagihara. 1991. Crown profile of foliage area characterized with the Weibull distribution in a hinoki (Chamaecyparis obtusa) stand. Trees 5:149-152.
37. Nelson, W. 1972. Theory and applications of hazard plotting for censored failure data. Technometrics 14(4):945-966.
38. Ovington, J.D. 1963. Flower and seed production. A source of error in estimating woodland production, energy flow and mineral cycling. Oikos 14(2):148-153.
39. Parker, G.G., D.J. Harding, and M.L. Berger. 2004. A portable LiDAR system for rapid determination of forest canopy structure. J. Appl. Ecol. 41:755-767.
40. Radtke, P.J., and P.V. Bolstad. 2001. Laser point-quadrat sampling for estimating foliage-height profiles in broad-leaved forests. Can. J. For. Res. 31:410-418.
41. Rich, P.M. 1990. Characterizing plant canopies with hemispherical photographs. Remote Sens. Rev. 5:13-29.
42. Ross, J. 1981. Radiation regime and architecture of plant stands. Springer-Verlag (Kluwer), Hague, The Netherlands. 420 p.
43. Schlattmann, P. 2009. Medical applications of finite mixture models. Springer, Berlin, Germany. 256 p.
44. Schreuder, H.T., and W.T. Swank. 1974. Coniferous stands characterized with the Weibull distribution. Can. J. For. Res. 4:518-523.
45. Seidel, D., S. Fleck, and C. Leuschner. 2012. Analyzing forest canopies with ground-based laser scanning: A comparison with hemispherical photography. Agr. For. Meteorol. 154-155:1-8.
46. Seidel, D., S. Fleck, C. Leuschner, and T. Hammett. 2011. Review of ground-based methods to measure the distribution of biomass in forest canopies. Ann. For. Sci. 68(2):225-244.
47. Tableman, M., J.S. Kim, and S. Portnoy. 2004. Survival analysis using S: Analysis of time-to-event data. Chapman and Hall/CRC, Boca Raton, FL. 280 p.
48. Therneau, T.M. 1999. A package for survival analysis in S. Mayo Clinic Foundation, Minneapolis, MN, 1999, p. 70-73.
49. Vanderbilt, V.C., M.E. Bauer, and L.F. Silva. 1979. Prediction of solar irradiance distribution in a wheat canopy using a laser technique. Agr. Meteorol. 20:147-160.
50. Waring, R.H. 1983. Estimating forest growth and efficiency in relation to canopy leaf area. Adv. Ecol. Res. 13:327-354.
51. Waring, R.H., K. Newman, and J. Bell. 1981. Efficiency of tree crowns and stemwood production at different canopy leaf densities. For. 54(2):129-137.
52. Watson, D.J. 1947. Comparative physiological studies on the growth of field crops: I. Variation in net assimilation rate and leaf area between species and varieties, and within and between years. Ann. Bot. 11:41-67.
53. Weiss, M. 2004. Review of methods for in situ leaf area index (LAI) determination. Part II. Estimation of LAI, errors and sampling. Agr. For. Meteorol. 121(1-2):37-53.
54. Welles, J.M., and S. Cohen. 1996. Canopy structure measurement by gap fraction analysis using commercial instrumentation. J. Exp. Bot. 47(302):1335-1342.
55. Wilson, J.W. 1960. Inclined point quadrats. New Phytologist 59(1):1-8.
56. Wilson, J.W. 1963. Estimation of foliage denseness and foliage angle by inclined point quadrats. Aust. J. Bot. 11:95-105.
57. Wilson, J.W. 1965. Stand structure and light penetration. I. Analysis by point quadrats. J. Appl. Ecol. 2(2):383-390.
58. Wilson, R.F., H. Marsh, and J. Winter. 2007. Importance of canopy connectivity for home range and movements of the rainforest arboreal ringtail possum (Hemibelideus lemuroides). Wildl. Res. 34:177-184.
59. Yang, X., D.R. Miller, and M.E. Montgomery. 1993. Vertical distributions of canopy foliage and biologically active radiation in a defoliated/refoliated hardwood forest. Agr. For. Meteorol. 67:129-146.
60. Zhao, F., X. Yang, M.A. Schull, M.O. Romáén-Colón, T. Yao, Z. Wang, Q. Zhang, et al. 2011. Measuring effective leaf area index, foliage profile, and stand height in New England forest stands using a full-waveform ground-based LiDAR. Remote Sens. Environ. 115:2954-2964.