Estimation of genetic parameters for height using spatial analysis in Tsuga heterophylla full-sibling family trials in British Columbia

ANEKONDA, T. S. and W. J. LIBBY (1996): Effectiveness of nearest neighbor data adjustment in a clonal test of Redwood. Silvae Genet. 45(1): 46-51.Search in Google Scholar

CANTET, R. J. C., A. N. BIRCHMEIER, A. W. CANAZA CAYO and C. FIORETT (2005): Semiparametric animal models via penalized splines as alternatives to models with contemporary groups. J. Anim. Sci. 83: 2482-2494.Search in Google Scholar

CAPPA, E. P. and R. J. C. CANTET (2007): Bayesian estimation of a surface to account for a spatial trend using penalized splines in an individual-tree mixed model. Can. J. For. Res. 37: 2677-2688.10.1139/X07-116Search in Google Scholar

CAPPA, E.P., A. D. YANCHUK and C. V. CARTWRIGHT (2012): Bayesian inference for multi-environment spatial individual-tree models with additive and full-sib family genetic effects for large forest genetic trials. Annals of Forest Science 69: 627-640. DOI: 10.1007/s13595-011-0179-7.10.1007/s13595-011-0179-7Search in Google Scholar

COSTA E SILVA, J., G. W. DUTKOWSKI and A. R. GILMOUR (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.Search in Google Scholar

DE BOOR, C. (1993): B(asic)-spline basics. Fundamental Developments of Computer-Aided Geometric Modeling. L. Piegl, ed. Academic Press, San Diego, CA.Search in Google Scholar

DURBAN, M., I. CURRIE and R. KEMPTON (2001): Adjusting for fertility and competition in variety trials. J. Agric. Sci. (Camb.) 136: 129-140.Search in Google Scholar

DUTKOWSKI, G. W., J. COSTA E SILVA, A. R. GILMOUR and G. A. LOPEZ (2002): Spatial analysis methods for forest genetic trials. Can. J. For. Res. 32: 2201-2214.Search in Google Scholar

DUTKOWSKI, G. W., J. COSTA E SILVA, A. R. GILMOUR, H. WELLENDORF and A. AGUIAR (2006): Spatial analysis enhances modeling of a wide variety of traits in forest genetic trials. Can. J. For. Res. 36: 1851-1870.Search in Google Scholar

FINLEY, A. O., S. BANERJEE, P. WALDMANN and T. ERICSSON (2009): Hierarchical spatial modeling of additive and dominance genetic variance for large spatial trial data sets. Biometrics 65: 441-451.10.1111/j.1541-0420.2008.01115.x277509518759829Search in Google Scholar

FOSTER, G. S. and D. T. LESTER (1983): Fifth-year height variation in western hemlock open pollinated families growing on four test sites. Can. J. For. Res. 13: 251-256.Search in Google Scholar

FU, Y. B., A. D. YANCHUK and G. NAMKOONG (1999): Spatial patterns of tree height variations in a series of Douglas-fir progeny trials: implications for genetic testing. Can. J. For. Res. 29: 714-723.Search in Google Scholar

FU, Y. B., G. P. Y. CLARKE, G. NAMKOONG and A. D. YANCHUK (1998): Incomplete block designs for genetic testing: statistical efficiencies of estimating family means. Can. J. For. Res. 28: 977-986.Search in Google Scholar

GILMOUR, A. R., B. J. GOGEL, B. R. CULLIS and R. THOMPSON (2006): ASReml User Guide Release 2.0 VSN International Ltd, Hemel Hempstead, HP1 1ES, UK.Search in Google Scholar

GREEN, P. J. and B. W. SILVERMAN (1994): Nonparametric Regression and Generalized Linear Model. Chapman & Hall, London, UK.10.1007/978-1-4899-4473-3Search in Google Scholar

GRONDONA, M. O., J. CROSSA, P. N. FOX and W. H. PFEIFFER (1996): Analysis of variety yield trials using 2-dimensional separable ARIMA processes. Biometrics 52: 763-770.10.2307/2532916Search in Google Scholar

HAMANN, A., M. KOSHY and G. NAMKOONG (2002): Improving precision of breeding values by removing spatially autocorrelated variation in forestry field experiments. Silvae Genet. 51: 210-215.Search in Google Scholar

HARVILLE, D. A. (1997): Matrix algebra from a statistician’s perspective. Springer-Verlag. New York.10.1007/b98818Search in Google Scholar

HENDERSON, C. R. (1984): Applications of Linear Models in Animal Breeding. Canada, University of Guelph, Guelph, Ont.Search in Google Scholar

HYNDMAN, R. J., M. L. KING, I. PITRUN and B. BILLAH (2005): Local lineal forecasts using cubic smoothing splines. Aust. N. Z. J. Stat. 47: 87-99.Search in Google Scholar

JAYAWICKRAMA, K. J. S. (2003): Genetic improvement and deployment of western hemlock in Oregon and Washington: Review and Future Prospects. Silvae Genet. 52(1): 26-36.Search in Google Scholar

JOYCE, D., R. FORD and Y. B. FU (2002): Spatial patterns of tree height variations in a black spruce farm-field progeny test and neighbors-adjusted estimations of genetic parameters. Silvae Genet. 51: 13-18.Search in Google Scholar

KING, J. N. (1990): The significance of geographic variation patterns for western hemlock genetic improvement. Technical Report, B.C. Ministry of Forests Research Branch, 12 p.Search in Google Scholar

KUSER, J. E. and K. K. CHING (1981): Provenance variation in seed weight, cotyledon number, and growth rate of western hemlock seedlings. Forest Science, 26: 463-470.10.1093/forestscience/26.3.463Search in Google Scholar

KUSER, J. E. and K. K. CHING (1981): Provenance variation in seed weight, cotyledon number, and growth rate of western hemlock seedlings. Can. J. For. Res. 11: 662-670.Search in Google Scholar

KUSNANDAR, D. and N. GALWEY (2000): A proposed method for estimation of genetic parameters on forest trees without raising progeny: critical evaluation and refinement. Silvae Genet. 49: 15-21.Search in Google Scholar

MAGNUSSEN, S. (1993): Bias in genetic variance estimates due to spatial autocorrelation. Theor. Appl. Genet. 86: 349-355.Search in Google Scholar

MAGNUSSEN , S. (1994): A method to adjust simultaneously for statial microsite and competition effects. Can. J. For. Res. 24: 985-995.Search in Google Scholar

POJAR, J. and A. MACKINNON (1994): Plants of the Pacific Northwest Coast, Washington, Oregon, British Columbia & Alaska. Lone Pine Publishing, Vancouver, British Columbia.Search in Google Scholar

POLLARD, D. F. W. and F. T. PORTLOCK (1986): Intraspecific variation in stem growth of western hemlock. Can. J. For. Res. 16: 149-151.Search in Google Scholar

R DEVELOPMENT CORE TEAM (2011): R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org/.Search in Google Scholar

RUPPERT, D., M. P. WAND and R. J. CARROLL (2003): Semiparametric Regression. Cambridge Univ. Press, Cambridge, UK.10.1017/CBO9780511755453Search in Google Scholar

SAENZ-ROMERO, C., E. V. NORDHEIM, R. P. GURIES and P. M. CRUMP (2001): A Case Study of a Provenance/ Progeny Test Using Trend Analysis with Correlated Errors and SAS PROC MIXED. Silvae Genet. 50: 127-135.Search in Google Scholar

SCHUTZ, W. M. and C. C. COCKERHAM (1966): The Effect of Field Blocking on Gain from Selection. Biometrics 22(4): 843-863.10.2307/2528078Search in Google Scholar

SILVERMAN, B. (1986): Density Estimation for Statistics and Data Analysis, Chapman and Hall, London. SMITH, B. J. (2003): Bayesian Output Analysis Program (BOA) version 1.0 user’s manual. Available from http://www.public-health.uiowa.edu/boa/Home.html.Search in Google Scholar

SPIEGELHALTER, D. J., N. G. BEST, B. P. CARLIN and A. VAN DER LINDE (2002): Bayesian measures of model complexity and fit (with discussion). Journal of the Royal Statistical Society Series B 64: 583-639.10.1111/1467-9868.00353Search in Google Scholar

WALDMANN, P., J. HALLANDER, F. HOTI and M. J. SILLANPÄÄ (2008): Efficient MCMC implementation of Bayesian analysis of additive and dominance genetic variances in non-inbred pedigrees. Genetics 179: 1101-1112.10.1534/genetics.107.084160242986318558655Search in Google Scholar

WEBBER, J. E. (2000): Western hemlock: a manual for tree improvement seed production. Res. Br., B. C. Min. For., Victoria, B.C.Work Pap. 44/2000.Search in Google Scholar

WHITE, T. L. (1996): Genetic parameter estimates and breeding value predictions: issues and implications in tree improvement programs. In: DIETERS, M. J., MATHESON, A. C., NIKLES, D. G., HARWOOD, C. E., WALKER, S. M. (eds) Proceedings of the QFRI-IUFRO Conference Tree Improvement for Sustainable Tropical Forestry. Caloundra, Queensland, Australia, pp 110-117.Search in Google Scholar

WILLIAMS, E. R. and A. C. MATHESON (1994): Experimental Design and Analysis for use in Tree Improvement. CSIRO, Melbourne, Australia.Search in Google Scholar

WU, H. X. and A. C. MATHESON (2004): General and specific combining ability from artial diallels of radiata pine: implications for utility of SCA in breeding and deployment populations. Theor. Appl. Genet. 108: 1503-1512.Search in Google Scholar

YANCHUK, A. (1996): General and specific combining ability from disconnected partial diallels of coastal Douglas-fir. Silvae Genet. 45: 37-45.Search in Google Scholar

YE, T. Z. and K. J. S. JAYAWICKRAMA (2008): Efficiency of using spatial analysis in firest-generation coastal Douglas-fir progeny tests in the US Pacific Northwest. Tree Genetics and Genomes 4: 677-692.10.1007/s11295-008-0142-4Search in Google Scholar

ZAS, R. (2006): Iterative kriging for removing spatial autocorrelation in analysis of forest genetic trials. Tree Genetics and Genomes 2: 177-185.10.1007/s11295-006-0042-4Search in Google Scholar

ZHELEV, P., I. EKBERG, G. ERIKSSON and L. NORELL (2003): Genotype environment interactions in four full-sib progeny trials of Pinus sylvestris (L.) with varying site indices. Forest Genetics 10: 93-102.Search in Google Scholar