References
- Anonymous (1984) Twenty-Eighth Annual Report (pp. 19-22). Cooperative Tree Improvement Program, NC State University. https://www.treeimprovement.org/annual-reports
- Balocchi CE, Bridgwater FE, Zobel BJ, Jahromi S (1993) Age trends in genetic parameters for tree height in a nonselected population of loblolly pine. Forest Science 39(2): 231-251. https://doi.org/10.1093/forestscience/39.2.231
- Cappa EP, Cantet RJC (2008) Direct and competition additive effects in tree breeding: Bayesian estimation from an individual tree mixed model. Silvae Genetica 57(1-6): 45-56. https://doi.org/10.1515/sg-2008-0008
- Carson SD, Garcia O, Hayes JD (1999) Realized gain and prediction of yield with genetically improved Pinus radiata in New Zealand. Forest Science 45(2): 186-200. https://doi.org/10.1093/forestscience/45.2.186
- Diao S, Hou Y, Xie Y, Sun X (2016) Age trends of genetic parameters, early selection and family by site interactions for growth traits in Larix kaempferi open-pollinated families. BMC Genetics 17(2016): 1-12. https://doi.org/10.1186/s12863-016-0400-7
- Ferreira FM, Chaves SF, Bhering LL, Alves RS, Takahashi EK, Sousa JE, Resende MD, Leite FP, Gezan SA, Viana JM (2023) A novel strategy to predict clonal composites by jointly modeling spatial variation and genetic competition. Forest Ecology and Management 548: 121393. https://doi.org/10.1016/j.foreco.2023.121393
- Foster GS (1986) Trends in genetic parameters with stand development and their influence on early selection for volume growth in loblolly pine. Forest Science 32(4): 944-959. https://doi.org/10.1093/forestscience/32.4.944
- Gilmour AR, Anderson RD, Rae AL (1985) The analysis of binomial data by a generalized linear mixed model. Biometrika 72(3): 593-599. https://doi.org/10.1093/biomet/72.3.593
- Gilmour AR, Gogel BJ, Cullis BR, Welham SJ, Thompson R (2015) ASReml user guide release 4.1 structural specification. Hemel Hempstead: VSN International Ltd.
- Goebel NB, Warner JR (1962) Volume tables for small diameter loblolly, shortleaf and Virginia pine in the upper South Carolina piedmont. Forest Research Series No. 7, Clemson, SC: Clemson University.
- Henderson CR (1984) Applications of linear models in animal breeding (Vol. 462). Guelph: University of Guelph.
- Hiraoka Y, Miura M, Fukatsu E, Iki T, Yamanobe T, Kurita M, Isoda K, Kubota M, Takahashi M (2019) Time trends of genetic parameters and genetic gains and optimum selection age for growth traits in sugi (Cryptomeria japonica) based on progeny tests conducted throughout Japan. Journal of Forest Research 24(5): 303-312. https://doi.org/10.1080/13416979.2019.1661068
- Isik F, Maltecca C, Holland J (2017) Genetic data analysis for plant and animal breeding. Vol. 400. Cham, Switzerland: Springer International Publishing. https://doi.org/10.1007/978-3-319-55177-7
- Isik F, McKeand SE (2019) Fourth cycle breeding and testing strategy for Pinus taeda in the NC State University Cooperative Tree Improvement Program. Tree Genetics & Genomes 15(5): 1-12. https://doi.org/10.1007/s11295-019-1377-y
- Isik K, Kleinschmit J, Svolba J (1995) Survival, growth trends and genetic gains in 17-year old Picea abies clones at seven test sites. Silvae Genetica 44(2-3): 116-128.
- Jansson G, Danell Ö, Stener LG (1998) Correspondence between single-tree and multiple-tree plot genetic tests for production traits in Pinus sylvestris. Canadian Journal of Forest Research 28(3): 450-458. https://doi.org/10.1139/x98-004
- Jansson G, Li B, Hannrup B (2003) Time trends in genetic parameters for height and optimal age for parental selection in Scots pine. Forest Science 49(5): 696-705. https://doi.org/10.1093/forestscience/49.5.696
- Kimberley M O, Moore JR, Dungey HS (2015) Quantification of realised genetic gain in radiata pine and its incorporation into growth and yield modelling systems. Canadian Journal of Forest Research 45(12): 1676-1687. https://doi.org/10.1139/cjfr-2015-0191
- Lai M, Sun X, Chen D, Xie Y, Zhang S (2014) Age-related trends in genetic parameters for Larix kaempferi and their implications for early selection. BMC Genetics 15: 1-8. https://doi.org/10.1186/1471-2156-15-S1-S10
- Lynch M, Walsh B (1998) Genetics and analysis of quantitative traits (Vol. 1). Sinauer Sunderland, MA. Magnussen S, Yanchuk AD (1994) Time trends of predicted breeding values in selected crosses of coastal Douglas-fir in British Columbia: A methodological study. Forest Science 40(4): 663-685. https://doi.org/10.1093/forestscience/40.4.663
- McKeand SE (1988) Optimum age for family selection for growth in genetic tests of loblolly pine. Forest Science 34(2): 400-411. https://doi.org/10.1093/forestscience/34.2.400
- McKeand SE (2019) The evolution of a seedling market for genetically improved loblolly pine in the southern United States. Journal of Forestry 117(3): 293-301. https://doi.org/10.1093/jofore/fvz006
- McKeand SE, Crook RP, Lee Allen H (1997) Genotypic stability effects on predicted family responses to silvicultural treatments in loblolly pine. Southern Journal of Applied Forestry 21(2): 84-89. https://doi.org/10.1093/sjaf/21.2.84
- McKeand SE, Bridgwater FE (1998) A strategy for the third breeding cycle of loblolly pine in the Southeastern US. Silvae Genetica 47(4): 223-234.
- Mihai G, Mirancea I (2016) Age trends in genetic parameters for growth and quality traits in Abies alba. iForest-Biogeosciences and Forestry 9(6): 954. https://doi.org/10.3832/ifor1766-009
- Sato T (1994) Time trends for genetic parameters in progeny tests of Abies sachalinensis (Fr Schm) Mast. Silvae Genetica 43(5/6).
- Shalizi MN, Walker TD, Heine AJ, Payn KG, Isik F, Bullock BP, McKeand SE (2023) Performance Based on Measurements from Individual-Tree Progeny Tests Strongly Predicts Early Stand Yield in Loblolly Pine. Forest Science 69(3): 299-310. https://doi-org.prox.lib.ncsu.edu/10.1093/forsci/fxad002
- Takahashi Y, Matsushita M, Tamura A, Ohira M, Takahashi M (2023) Age trends in genetic parameters and genetic gains of growth traits in multiple progeny test sites of hinoki cypress (Chamaecyparis obtusa). Journal of Forest Research 29(2): 103-111. https://doi.org/10.1080/13416979.2023.2265004
- Talbert JT (1979) An advanced-generation breeding plan for the NC State University-Industry pine tree improvement cooperative. Silvae Genetica 28(2/3): 72-75.
- Vergara R, White TL, Huber DA, Schmidt RA (2007) Realized genetic gains of rust resistant selections of slash pine (Pinus elliottii var. Elliottii) planted in high rust hazard sites. Silvae Genetica 56(5): 231-241. https://doi.org/10.1515/sg-2007-0034
- Vergara R, White TL, Huber DA, Shiver BD, Rockwood DL (2004) Estimated realized gains for first-generation slash pine (Pinus elliottii var. Elliottii) tree improvement in the southeastern United States. Canadian Journal of Forest Research 34(12): 2587-2600. https://doi.org/10.1139/x04-136
- Walker TD, McKeand SE (2018) Fusiform rust hazard mapping for loblolly pine in the southeastern United States using progeny test data. Journal of Forestry 116(2): 117-122. https://doi.org/10.5849/jof-2017-070
- White TL, Adams WT, Neale DB (2007) Forest Genetics. CABI. https://doi.org/10.1079/9781845932855.0000
- Xiang B, Li B, Isik F (2003a) Time trend of genetic parameters in growth traits of Pinus taeda L. Silvae Genetica 52(3-4): 114-120.
- Xiang B, Li B, McKeand S (2003b) Genetic gain and selection efficiency of loblolly pine in three geographic regions. Forest Science 49(2): 196-208. https://doi.org/10.1093/forestscience/49.2.196
- Xiaoyang CBH, Xie CY, Ying CC (2003) Age trends in genetic parameters and early selection of lodgepole pine provenances with particular reference to the lambeth model. https://kf.tuzvo.sk/sites/default/files/FG10-3_249-258.pdfdoi.org/10.1111/pce.13898