Genetic variation in the diameter-height relationship in Scots pine (Pinus sylvestris)

Canadian Journal of Forest Research

Volumn 38, Issue 6, 2008, Pages 1493-1503

  Kroon, Johan ^a   Andersson, Bengt ^a   Mullin, Tim J ^b  

^a THE FORESTRY RESEARCH INSTITUTE OF SWEDEN   (Sweden)

^b BioSylve Forest Science NZ Limited   (New Zealand)

Author keywords

[No Author keywords available]

Indexed keywords

ESTIMATION; FOOD ADDITIVES; FORESTRY; PARAMETER ESTIMATION;

BREAST HEIGHT; COEFFICIENT OF VARIATION (COV); COVARIATE; COVARIATES; DIAMETER GROWTH; GENETIC CORRELATIONS; GENETIC PARAMETERS; GENETIC VARIATIONS; HEIGHT GROWTH; LINEAR MIXED MODELS (LMM); MICROSITE; PHENOTYPIC VARIANCE; PINUS SYLVESTRIS L.; SCOTS PINES; TREE HEIGHT;

TREES (MATHEMATICS);

BREEDING; COMPETITION (ECOLOGY); CONIFEROUS TREE; DIAMETER; GENETIC VARIATION; GROWTH; HEIGHT; HETEROGENEITY;

DATA; FOOD ADDITIVES; FORESTRY; GROWTH; MATHEMATICAL MODELS; PARAMETERS; TREES;

PINUS SYLVESTRIS;

EID: 46749116500     PISSN: 00455067     EISSN: None     Source Type: Journal    
DOI: 10.1139/X07-233     Document Type: Article

References (55)

1. Abetz, P. 1976. Beiträge zum Baumwachstum - Der h/d-Wert mehr als ein Schlankheitsgrad. [A comment on tree growth - Highlighting the slenderness coefficient.] Der Forst- und Holzwirt. 31: 389-393. [In German.]
2. Andersson, B., Elfving, B., Ericsson, T., Persson, T., and Gregorsson, B. 2003. Performance of improved Pinus sylvestris in northern Sweden. Scand. J. For. Res. 18: 199-206. doi:10.1080/02827580308620.
3. Andersson, B., Elfving, B., Persson, T., Ericsson, T., and Kroon, J. 2007. Characteristics and development of improved Pinus sylvestris in northern Sweden. Can. J. For. Res. 37: 84-92. doi:10.1139/X06-224.
4. Andersson, S.-O. 1954. Funktioner och tabeller för kubering av småträd. [Volume functions and tables for cubing small tree.] Medd. Statens Skogsforskningsinst. 44: 1-29. [In Swedish.]
5. Besag, J., and Kempton, R. 1986. Statistical analysis of field experiments using neighbouring plots. Biometrics, 42: 231-251. doi:10.2307/2531047.
6. Biging, G., and Dobbertin, M. 1995. Evaluation of competition indices in individual tree growth model. For. Sci. 41: 360-377.
7. Brandel, G. 1990. Volymfunktioner för enskilda träd. Tall, gran och björk. [Volume functions for individual trees; Scots pine (Pinus sylvestris), Norway spruce (Picea abies) and birch (Betula pendula & Betula pubescens).] Vol. 26. Department of Forest Yield Research, Swedish University of Agricultural Sciences, Uppsala. pp. 1-73. [In Swedish with English summary.]
8. Brodie, C.L., and Debell, D.S. 2004. Evaluation of field performance of poplar clones using selected competition indices. New For. 27: 201-214.
9. Buford, M.A., and Burkhart, H.E. 1987. Genetic improvement effects on growth and yield of loblolly pine plantations. For. Sci. 33: 707-724.
10. Canham, C.D., LePage, P.T., and Coates, D. 2004. A neighborhood analysis of canopy tree competition: effects of shading versus crowding. Can. J. For. Res. 34: 778-787. doi:10.1139/x03-232.
11. Costa e Silva, J., Dutkowski, G.W., and Gilmour, A.R. 2001. Analysis of early tree height in forest genetic trials is enhanced by including a spatially correlated residual. Can. J. For. Res. 31: 1887-1893. doi:10.1139/cjfr-31-11-1887.
12. Costa e Silva, J., Dutkowski, G.W., and Borralho, N.M.G. 2005. Across-site heterogeneity of genetic and environmental variances in the genetic evaluation of Eucalyptus globulus trials for height growth. Ann. For. Sci. 62: 183-191. doi:10.1051/forest:2005010.
13. Dutkowski, G.W., Costa e Silva, J., Gilmour, A.R., and Lopez, G.A. 2002. Spatial analysis methods for forest genetic trials. Can. J. For. Res. 32: 2201-2214. doi:10.1139/x02-111.
14. Dutkowski, G.W., Costa e Silva, J., Gilmour, A.R., Wellendorf, H., and Aguiar, A. 2006. Spatial analysis enhances modelling of a wide variety of traits in forest genetic trials. Can. J. For. Res. 36: 1851-1870. doi:10.1139/X06-059.
15. Ericsson, T. 1997. Enhanced heritabilities and best linear unbiased predictors through appropriate blocking of progeny trials. Can. J. For. Res. 27: 2097-2101. doi:10.1139/cjfr-27-12-2097.
16. Gezan, S.A., Huber, D.A., and White, T.L. 2006. Post hoc blocking to improve heritability and precision of best linear unbiased genetic predictions. Can. J. For. Res. 36: 2141-2147. doi:10.1139/X06-112.
17. Gilmour, A.R., Cullis, B.R., and Verbyla, A.P. 1997. Accounting for natural and extraneous variation in the analysis of field experiments. J. Agric. Biol. Environ. Stat. 2: 269-293. doi:10.2307/1400446.
18. Gilmour, A.R., Gogel, B.J., Cullis, B.R., and Thompson, R. 2006. ASReml user guide release 2.0. VSN International Ltd., Hemel Hempstead, UK.
19. Hannrup, B., Ekberg, I., and Persson, A. 2000. Genetic correlations between wood, growth capacity and stem traits in Pinus sylvestris. Scand. J. For. Res. 15: 161-170. doi:10.1080/028275800750014966.
20. Harrington, C.A., and DeBell, D.S. 1996. Above- and below-ground characteristics associated with wind toppling in a young Populus plantation. Trees (Berl.), 11: 109-118.
21. Henry, H., and Aarssen, L. 1999. The interpretations of stem diameter-height allometry in trees: biomechanical constraints, neighbour effects, or biased regression? Ecol. Lett. 2: 89-97. doi:10.1046/j.1461- 0248.1999.22054.x.
22. Ilomäki, S., Nikinmaa, E., and Mäkelä, A. 2003. Crown rise due to competition drives biomass allocation in silver birch. Can. J. For. Res. 33: 2395-2404. doi:10.1139/x03-164.
23. Kempthorne, O., and Curnow, R.N. 1961. The partial diallel cross. Biometrics, 17: 229-250. doi:10.2307/2527989.
24. King, D.A. 1990. Allometry of saplings and understory trees of a Panamanian forest. Funct. Ecol. 4: 27-32. doi:10.2307/2389648.
25. Konopka, J., Petras, R., and Toma, R. 1987. Slenderness coefficient of the major tree species and its importance for static stability of stands. Lesnictvi (Prague), 33: 887-904.
26. La Farge, T. 1972. Inheritance and evolution of stem form in three northern pine species. UMI Dissertation service, 2007, Ann Arbor, Michigan.
27. Ledermann, T., and Stage, A.R. 2001. Effects of competitor spacing in individual-tree indices of competition. Can. J. For. Res. 31: 2143-2150. doi:10.1139/cjfr-31-12-2143.
28. Lu, P.X., Huber, D.A., and White, T.L. 1999. Potential biases of incomplete linear models in heritability estimation and breeding value predictions. Can. J. For. Res. 29: 724-736. doi:10.1139/cjfr-29-6-724.
29. Magnussen, S. 1990. Application and comparison of spatial models analyzing tree-genetics field trials. Can. J. For. Res. 20: 536-546.
30. Magnussen, S. 1993. Bias in genetic variance estimates due to spatial autocorrelation. Theor. Appl. Genet. 86: 349-355. doi:10.1007/BF00222101.
31. Magnussen, S. 1994. A method to adjust simultaneously for spatial microsite and competition effects. Can. J. For. Res. 24: 985-995. doi:10.1139/x94-129.
32. Marklund, L.G. 1988. Biomassafunktioner för tall, gran och björk i Sverige. [Biomass functions for pine, spruce and birch in Sweden.] Vol. 45. Department of Forest Survey, Swedish University of Agricultural Sciences, Uppsala. pp. 1-73. [In Swedish.]
33. Mäkinen, H. 1997. Possibilities of competition indices to describe competitive differences between Scots pine families. Silva Fenn. 31: 43-52.
34. Mäkinen, H. 1999. Effect of stand density on radial growth of branches of Scots pine in southern and central Finland. Can. J. For. Res. 29: 1216-1224. doi:10.1139/cjfr-29-8-1216.
35. Niklas, K.J. 1995. Size-dependent allometry of tree height, diameter and trunk-taper. Ann. Bot. (Lond.), 75: 217-227. doi:10.1006/anbo.1995.1015.
36. Nilsson, B. 1968. Studier av några kvalitetsegenskapers genetiska variation hos tall (Pinus sylvestris L.). [Studies of the genetical variation of some quality characters in Scots pine (Pinus sylvestris L.).] Department of Forest Genetics, Royal College of Forestry. Stockholm. Research notes, 3: 1-117. [In Swedish with English summary.]
37. Patterson, H.D., and Thompson, R. 1971. Recovery of inter-block information when block sizes are unequal. Biometrika, 58: 545-554. doi:10.1093/biomet/58.3.545.
38. Poorter, L., Bongers, F., Sterck, F.J., and Wöll, H. 2003. Architecture of 53 rain forest tree species differing in adult stature and shade tolerance. Ecology, 84: 602-608. doi:10.1890/0012-9658(2003)084[0602: AORFTS]2.0.CO;2.
39. Price, C.A., Enquist, B.J., and Savage, M. 2007. A general model for allometric covariation in botanical form and function. Proc. Natl. Acad. Sci. U.S.A. 104: 13204-13209. doi:10.1073/pnas.0702242104. PMID:17664421.
40. Pukkala, T. 1989. Methods to describe the competition process in a tree stand. Scand. J. For. Res. 4: 187-202.
41. Read, J., and Stokes, A. 2006. Plant biomechanics in an ecological context. Am. J. Bot. 93: 1546-1565.
42. Rouvinen, S., and Kuuluvainen, T. 1997. Structure and asymmetry of tree crowns in relation to local competition in a natural mature Scots pine forest. Can. J. For. Res. 27: 890-902. doi:10.1139/cjfr-27-6-890.
43. Searle, S.R., Casella, G., and McCulloch, C.E. 1992. Variance components. John Wiley & Sons Inc., New York.
44. Sharma, M., and Zhang, S.Y. 2004. Height-diameter models using stand characteristics for Pinus banksiana and Picea mariana. Scand. J. For. Res. 19: 442-451. doi:10.1080/02827580410030163.
45. Sherrill, J.R. 2005. Genetic and cultural effects on stem taper for loblolly pine. [Online] Master thesis. North Carolina State University. Raleigh. Available from www.lib.ncsu.edu/theses/available/etd-03222005-151742/ [accessed 4 October 2006].
46. Socha, J., and Kulej, M. 2005. Provenance-dependent variability of Abies grandis stem form under mountain conditions of Beskid Sa̧decki (southern Poland). Can. J. For. Res. 35: 2539-2552. doi:10.1139/x05-167.
47. Söderberg, U. 1992. Funktioner för skogsindelning: Höjd, formhöjd och barktjocklek för enskilda träd. [Functions for forest management: Height, form height and bark thickness of individual trees.] Department of Forest Survey, Swedish University of Agricultural Sciences, Uppsala, Report, 52: 1-87. [In Swedish with English summary.]
48. Sumida, A., Ito, H., and Isagi, Y. 1997. Trade-off between height growth and stem diameter growth for an evergreen Oak, Quercus glauca, in a mixed hardwood forest. Funct. Ecol. 11: 300-309. doi:10.1046/j.1365-2435.1997. 00085.x.
49. Vanninen, P. 2004. Allocation of above-ground growth in Pinus sylvestris - impacts of tree size and competition. Silva Fenn. 38: 155-166.
50. Waghorn, M.J., Watt, M.S., and Mason, E.G. 2007. Influence of tree morphology, genetics, and initial stand density on outerwood modulus of elasticity of 17-year-old Pinus radiata. For. Ecol. Manage. 244: 86-92. doi:10.1016/j.foreco.2007.03.057.
51. Wang, Y., Titus, S.J., and LeMay, V.M. 1998. Relationships between tree slenderness coefficient and tree or stand characteristics for major species in boreal mixed forest. Can. J. For. Res. 28: 1171-1183. doi:10.1139/cjfr-28-8-1171.
52. Werner, M., Hadders, G., and Rosvall, O. 1981. Förä dlingsprogram för tall, gran och contortatall. [Breeding. program for Scots pine, Norway spruce, and lodgepole pine.] Inst. For. Improv. Uppsala Sweden Yearb. 1980: 59-111. [In Swedish with English summary.]
53. White, T.L., Adams, W.T., and Neale, D.B. 2007. Forest genetics. CABI Publishing, USA.
54. Wilkinson, G.N., Eckert, S.R., Hancock, T.W., and Mayo, O. 1983. Nearest-neighbour (NN) analysis of field experiments. J. R. Stat. Soc. Ser. B, 45: 151-211.
55. Zas, R. 2006. Iterativ kriging for removing spatial autocorrelation in analysis of forest genetic trials. Tree Genet. Genom. 2: 177-185. doi:10.1007/s11295-006-0042-4.