Adapting distance-independent forest growth models to represent spatial variability: Effects of sampling design on model coefficients

Forest Science

Volumn 44, Issue 2, 1998, Pages 224-238

  Stage, Albert R ^a   Wykoff, William R ^a  

^a ROCKY MOUNTAIN RESEARCH STATION   (United States)

Author keywords

Competition indices; Individual tree model; Measurement error models; Patchy stands; Structural based prediction

Indexed keywords

EID: 0031718430     PISSN: 0015749X     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (51)

1. BARTLETT, M.S. 1951. An inverse matrix adjustment arising in discriminant analysis. Ann. Math. Stat. 22:107-111.
2. BIGING, G.S., AND M. DOBBERTIN. 1992. A comparison of distance-dependent competition measures for height and basal area growth of individual conifer trees. For. Sci. 38:695-720.
3. BORMANN, F.H. 1957. Moisture transfer between plants through intertwined root systems. Plant Physiol. 32:48-55.
4. BUONACCORSI, J.P. 1995. Prediction in the presence of measurement error: General discussion and an example predicting defoliation. Biometrics 51:1562-1569.
5. CHISMAN, H.H., AND F.X. SCHUMACHER. 1940. On the tree-area ratio and certain of its applications. J. For. 38:311-317.
6. COOPER, S.V., K.E. NEIMAN, AND D.W. ROBERTS. Rev. 1991. Forest habitat types of Northern Idaho: A second approximation. USDA For. Serv. Gen. Tech. Rep. INT-236. 143 p.
7. CURTIS, R.O. 1982. A simple index of stand density for Douglas-fir. For. Sci. 28:92-94.
8. DIGGLE, P.J. 1983. Statistical analysis of spatial point patterns. Academic Press, London. 148 p.
9. FAIRWEATHER, S.E. 1988. Development of an individual tree growth model for Pennsylvania. P 61-67 in Proc. of IUFRO conf. on Forest growth modelling and prediction. Ek, A.R., et al. (eds.) USDA For. Serv. Gen. Tech. Rep. NC-120. Vol 1. 581 p.
10. FERGUSON, D.E., AND N.L. CROOKSTON. 1991. User's guide to version 2 of the Regeneration Establishment Model: Part of the Prognosis Model. USDA For. Serv. Gen. Tech. Rep. INT-279. 34 p.
11. FERGUSON, D.E., A.R. STAGE, AND R.J. BOYD. 1986. Predicting regeneration in the grand fir-cedar-hemlock ecosystem of the northern Rocky Mountains. For. Sci. Monogr. 26. Supplement to For. Sci. 32(1). 41 p.
12. FREESE, F. 1961. Relation of plot size to variability: An approximation. J. For. 59(9):679
13. FULLER, W.A. 1987. Measurement error models. Wiley, New York. 440 + xxiii p.
14. GARCIA, O. 1992. What is a diameter distribution? Presented at the IUFRO Symp. on Integrated Forest Management Information Systems.
15. GERTNER, G.Z. 1987. Approximating precision in simulation projections: An efficient alternative to Monte Carlo methods. For. Sci. 33:230-239.
16. GOODMAN, L.A. 1960. On the exact variance of products. J. Am. Stat. Assoc. 55:708-713.
17. GROSENBAUCH, L.R. 1955. Better diagnosis and prescription in southern forest management. USDA For. Serv. South. For. Exp. Sta. Occas. Pap. 145. 25 p.
18. GROSENBAUGH, L.R. 1967. REX - FORTRAN-4 SYSTEM for combinatorial screening or conventional analysis of multivariate regressions. USDA For. Serv. Res. Pap. PSW-44. 47 p.
19. HAMILTON, D.A., JR. 1991 Implications of random variation in the Stand Prognosis Model. USDA For. Serv. Res. Note INT-394. 11 p.
20. HENSOLD, T. 1989. Evaluating alternative target structures for an uneven-aged ponderosa pine stand using the Stand Prognosis Model. Unpubl. MS thesis, University of Idaho, Moscow, Idaho.
21. JAAKKOLA, S. 1967. On the use of variable size plots for increment research. P. 371-378 in Proc. IUFRO XIV Congress Sect 25.
22. JOHNSON, N.L., AND S. KOTZ. 1969. Distributions in statistics: Discrete distributions. Houghton Mifflin, Boston.
23. JOHNSON, R.R., AND G. DIXON. 1990. Blue Mountains geographic variant of the Stand Prognosis Model. USDA For. Serv., Washington Office Intern. Rep.
24. KRAJICEK, J., K. BRINKMAN, AND S. GINGRICH. 1961. Crown competition - a measure of density. For. Sci. 7:35-42
25. LAPPI, J. 1991. Estimating the distribution of a variable measured with error: stand densities in a forest inventory. Can. J. For. Res. 21:469-473.
26. MATÉRN, B. 1960. Spatial variation. Stochastic models and their application to some problems in forest surveys and other sampling investigations. Meddelanden från Statens Skogsforskningsinstitut, Band 49, Nr 5. 144 p.
27. MATÉRN, B. 1969. Wie gross ist die "Relaskop-Flache"? Allg. Forstzeitung Folge 2.
28. MOEUR, M. 1991. Spatial variation in conifers regenerating beneath old growth forest canopies. Ph.D. Diss., Univ. of Washington, Seattle. 301 p.
29. MOEUR, M. 1993. Characterizing spatial patterns of trees using stem-mapped data. For. Sci. 39:756-775.
30. MOWRER, H.T. 1991. Estimating components of propagated variance in growth simulation model projections. Can. J. For. Res. 21:379-386.
31. MUNRO, D.D. 1974. Forest growth models - a prognosis. P. 7-21 in Growth models for tree and stand simulation, Fries, J. (ed.). IUFRO Working party S4.01-4, Proc. of meetings in 1973. Dep. of For. Yield Res., For. Res. Note 30, Royal Coll. of Forestry, Stockholm, Sweden. 379 p.
32. MURPHY, P.A., AND M.G. SHELTON. 1996. An individual-tree basal area growth model for loblolly pine stands. Can. J. For. Res. 26:327-331.
33. PENTTINEN, A., D. STOYAN, AND H.M. HENTTONEN. 1992. Marked point processes in forest statistics. For. Sci. 38:806-824.
34. PERSSON, O. 1964. Distance methods. The use of distance measurements in the estimation of seedling density and open space frequency. Studia Forestalia Suecica Nr. 15 68 p.
35. PIELOU, E.C. 1969. An introduction to mathematical ecology. Wiley Interscience, New York. 286 + viii p.
36. PUKKALA, T. 1990. A method for incorporating the within-stand variation into forest management planning. Scand. J. For. Res. 5:263-275.
37. REED, D.D., AND H.E. BURKHART. 1985. Spatial autocorrelation of individual tree characteristics in loblolly pine stands. For. Sci. 31:575-587.
38. REICH, R.M. 1992. Sampling unit, spatial distribution of trees and precision. North. J. App. For. 9:3-6.
39. RIPLEY, B.D. 1981. Spatial statistics. Wiley, New York. 252 + x p.
40. SCHNELL, D., H.J. PARK, AND W.A. FULLER. 1988. EV CARP. Statistical Laboratory, Iowa State Univ. 112 + ii p.
41. SCHREUDER, H.T., AND M.S. WILLIAMS. 1995. Assessing measures of tree competition using fixed-area, variable-radius, and horizontal-line sampling. Can. J. For. Res 25:1578-1582.
42. SMITH, H.F. 1938. An empirical law describing heterogeneity in the yield of agricultural crops. J. Agric. Sci. 28:1-23.
43. STAGE, A.R. 1973. Prognosis model for stand development. USDA For. Serv. Res. Pap. INT-137. 32 p.
44. STAGE, A.R., AND J.R. ALLEY. 1972. An inventory design using stand examinations for planning and programming timber management. USDA For. Serv. Res. Pap. INT-126. 17 p.
45. STAGE, A.R., AND W.R. WYKOFF. 1993. Calibrating a model of stochastic effects on diameter increment for individual-tree simulations of stand dynamics. For. Sci. 39:692-705.
46. SUKWONG, S., W.E. FRAYER, AND E.W. MOGREN. 1971. Generalized comparisons of the precision of fixed-radius and variable-radius plots for basal-area estimates. For. Sci. 17:263-271.
47. USDA FOREST SERVICE. 1962. Developing the data framework for effective timber management. Intermountain For. and Range Exp. Sta. Misc. Publ. 25. 13 p.
48. WENSEL, L.C., AND H.H. JOHN. 1969. A statistical procedure for combining different types of sampling units in a forest inventory. For. Sci. 15:307-317.
49. WILKS, S.S. 1962. Mathematical statistics. Wiley, New York. 644 + xvi p.
50. WYKOFF, W.R. 1990. A basal area increment model for individual conifers in the northern Rocky Mountains. For. Sci. 36:1077-1104.
51. WYKOFF, W.R., N.L. CROOKSTON, AND A.R. STAGE. 1982. User's guide to the Stand Prognosis Model. USDA For. Serv. Gen. Tech. Rep. INT-133. 112 p.