Sustainability robustness and efficiency of a multi- generation breeding strategy based on within-family clonal selection

Sustainability and robustness of genetic gain and diversity were analysed for breeding and production populations managed according to the Swedish breeding programme for Norway spruce. This strategy is based on double-pair mating and balanced, within-family selection with clonal testing within a number of reproductively isolated breeding populations. The importance of different characteristics was quantified by computer simulation, using a stochastic quantitative :infinitesimal genetic model. After ten generations, the linear increase in the additive genetic effect for the baseline scenario reached 11.0 sigma(A) and status effective number was reduced from 48 to 8.1 in a breeding population with 48 members. Six trees with status number 3.9 could be selected as seed orchard parents with a predicted inbreeding in the seed crop of less than 5% resulting in a total gain including inbreeding depression of 11.7 sigma(A). Meanwhile, available gain from a similar inbred clone mixof 6 genotypes was 13.1 sigma(A), mainly as a result of one more cycle of testing. Provided that populations had no fewer than 24 members, increases over ten generations in group coancestry, inbreeding and inbreeding depression were not substantial, andthe drop in additive gain per generation was negligible. :Reduction of additive variance and increased inbreeding had no apparent effect on accumulation of gain per generation, even after ten breeding cycles. Thus, it is concluded that the current programme is sustainable. Clonal testing continued to be efficient throughout ten generations at population sizes down to 24, allowing a substructure of two sublines within a population of 48 members. Non-additive variance reduced the rate of increase ofthe additive mean. A continuous accumulation of additive effects was more important than exploitation of non- additive variation, even when cloned planting stock is deployed. Clonal testing was highly effective and robust, even at low numbers of ramets and weak heritability. Low stochastic variation among replicate runs indicated high precision, thus predictions of the breeding programme outcome are reliable within the limits of the model.