Genetic variances and selection efficiencies for growth traits of white spruce (Picea glauca (Moench) Voss) were estimated from clonally replicated full-sib progeny tests established both in nursery and field environments in New Brunswick, Canada. The available data included heights at 4, 5, and 6 years in the nursery test; height at 9 years, height, DBH, and volume at 14 years in the field test. Estimated variance components were interpreted according to an additive-dominance-epistasis model. For heights in the nursery test, while both non-additive and additive variances were important sources of genetic variation, the former decreased but the latter increased with age; among the non-additive genetic variance, the epistatic variance was much more important than the dominance variance. Different from the nursery traits, for traits in the field test, additive variance accounted for an average of 81% of the total genetic variance, whereas dominance variance explained most of the remaining genetic variance. Genetic parameters and selection efficiencies for three vegetative deployment strategies: deploying half-sib families (VD_FAM HS ), full-sib families (VD_FAM FS ), and multi-varietal forestry (MVF), were compared. Heritability estimates were moderate for VD_FAM HS and VD_FAM FS (0.61-0.72), high for MVF (>0.82) for the nursery heights, and high (>0.79) for the field traits for all strategies. Genetic correlations of volume at age 14 in the field test, the target trait for improvement, were strong (>0.85) with other field traits. Genetic correlations of VOL14 with the nursery heights were also strong (>0.71) at the half-sib and full-sib family levels, but were only moderate (>0.59) for MVF. Overall, practicing MVF is the most effective deployment strategy, yielding the highest genetic gains, followed by VD_FAM FS and VD_FAM HS , regardless of traits and selection methods. Furthermore, early selections for HT9 or for HT4-HT6 were very encouraging, resulting in higher gain in volume at age 14 on a per year basis.

Trends in genetic parameters for height growth of jack pine (Pinus banksiana Lamb.) were examined over three series of family tests throughout New Brunswick. Data were analyzed for each site and across sites within each series. Although individual narrow sense heritability estimates from single-site analyses varied substantially from site to site and showed no consistent age-related pattern, the estimates from across-site analyses showed an increasing trend to age 20. Similar as individual narrow sense heritability, the coefficient of additive genetic variance estimated from single site showed more variation than those estimated from across site analyses. Age-age (type-a) genetic correlations for height were high and could be well predicted by a LAR2 model, where LAR is the natural logarithm of the ratio between two ages at assessment. Type-b genetic correlations were high and of similar magnitude at different ages. Genetic correlations between height at different ages and volume at one-half rotation age were generally high. Taking the volume at one-half rotation age as the target trait, the selection for target trait from early selection at ages 5~7 could be more efficient per year than direct selection.

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Differences in height-diameter (H-DBH) relationship were investigated using the Chapman-Richards function among jack pine seedlots planted in a realized genetic gain test in New Brunswick. Three seedlots representing the bulk mixed cone collection from the 1979 J.D. Irving’s first-generation seedling seed orchard (JDISSO) before rogueing (UNR), after the first time genetic rogueing (1STR) and after the second time genetic rogueing (2NDR), respectively, were planted in the test. Unimproved commercial seedlots (UC) were also included for comparison. Results indicate that an overall H-DBH relationship for all the seedlots was not appropriate. Seedlot pairwise comparisons in H-DBH relationships showed that, whereas most seedlot pairs were significantly different from each other, there was no significant difference between the UNR and UC and between the 1STR and 2NDR. Two models were developed with one targeting the UNR and UC (UNIMPROVED) and the other targeting the 1STR and 2NDR (IMPROVED). The difference between the UNIMPROVED and IMPROVED models was caused only by asymptote of the Chapman-Richards function. Applying the UNIMPROVED or IMPROVED model to predict height of the 1STR and 2NDR or the UNR and UC would result in an under-estimated or an over-estimated bias by 2 to 3% in height. In light of this study, seedlot differences in H-DBH relationships should be integrated into growth and yield models by a multiplier for height depending on genetic improvement levels.

Family forestry, defined as the deployment of families in mixture into plantations, is becoming an attractive option for black spruce (Picea mariana (Mill.) BSP) in New Brunswick, Canada. With many elite families of black spruce being available, there is a knowledge gap regarding how to compose a mixture of families that optimally balances the objectives of increased yield and reduced risk. This study, based on real field test data, investigates the application of a model based on the modern portfolio theory to optimally balance yield and risk when selecting a portfolio (mixture) of black spruce families to deploy in reforestation. The risk was expressed as the variance of the family portfolio, an effective indicator of yield stability. This is an innovative approach in forestry and it is compared to the currently used method, truncation-deployment, defined as the equal deployment of seed of selected families. Results show that the portfolio theory searched for the combination of yield and stability and produced family portfolios maximizing yield at a given stability or minimizing yield instability at a given yield. The portfolio theory was never inferior in maximizing yield to the truncation- deployment approach when yield stability is a concern. We recommend using portfolio theory to determine family portfolios for family forestry. While this study targets to family forestry, the results may be relevant to other deployment strategies where stability is a concern, such as clonal forestry.