Genetic changes in forests occur intentionally, through tree breeding, and unintentionally, through domestication and various other mechanisms (some natural, and others resulting from human actions). Forest tree improvement is done to improve health, growth, quality and economy of planted forests while avoiding severe restrictions of gene diversity.
Genetic change is predictable
The changes in gene diversity can be predicted, and the Centre for prediction and optimization of genetic change analyzes the likely impact of different tree improvement activities on gene diversity. The centre develops methods to optimize tree improvement, considering the balance between different factors (especially genetic improvement, gene diversity, time and cost).
The tactical and strategic decisions of breeders are evaluated using theoretical tools and real data to identify methods that are simple but efficient. The changes predicted are evaluated on different geographic and organizational levels and different time scales. To analyze gene diversity and its dynamics a method to quantify gene diversity has been developed (status number or group coancestry, Gea ). These measures are based on the probability that genes taken at random from a population are different by descent (and thus originate from different initial genes). Optimal selection procedures in tree breeding are designed to provide a group of selections, which maximize average breeding value and gene diversity (Lindgren and Mullin , Rosvall and Andersson ). Thus, optimal tree breeding can be seen as an activity that maximizes the combination of genetic gain and diversity. The idea is illustrated in the figure.
Seed orchard crops
The gene diversity of seed orchard crops can be quanti-fied by considering differences in reproductive success between orchard clones and the gene migration into the seed orchard (Lindgren and Mullin , Kang and Lindgren ). The new methods make it possible to develop more efficient methods of forest tree breeding. Phenotypic selection is a rather slow method of exploiting gene diversity, but compared to the gene diversity used, it is an efficient selection method for improving genetic quality (Andersson ). In combination with methods to study the effect of different levels of re-productive success in open pollinated breeding populations (Bila et al. ) this makes it possible to develop cheaper systems of breeding for resource poor circumstances. To maximize the benefit of seed orchards which can be derived from long term breeding it is useful to stratify the breeding population by mating individuals with similar breeding values rather than to mate at random (Rosvall ).
Wei, R.-P. () Predicting genetic diversity and optimizing gain for tree breeding programs. Ph.D. thesis, Swedish University of Agricultural Sciences, Department for Forest Genetics and Plant Physiology, Umeő.
Lindgren, D. & Mullin, T.J. () Balancing gain and relatedness in selection. Silvae Genetica. 46:124-129.
Gea, L.D. () Genetic diversity and gain. The concept of status number. PhD thesis, school of forestry. University of Canterbury, Christchurch, New Zealand.
Andersson, E.W. () Gain and Diversity in Multi-Generation Breeding Programs. Ph.D. thesis. Acta Universitatis Agriculturae Sueciae. Silvestria 95 42 pp.
Rosvall, O. () Enhancing Gain from Long-Term Forest Tree Breeding while Conserving Genetic Diversity. Ph.D. thesis. Acta Universitatis Agriculturae Sueciae. Silvestria 109 65pp.
Rosvall, O. & Andersson, E.W. () Group-merit selection compared to conventional restricted selection for trade-offs between genetic gain and diversity. Forest Genetics 6: 1-14.
Lindgren, D. & Mullin, T.J. () Relatedness and status number in seed orchard crops. Canadian Journal of Forest Research, 28:276-283.
Bila, A.D., Lindgren, D. & Mullin, T.J. () Fertility variation and its effect on diversity over generations in Teak plantation (Tectona grandis L.f.). Silvae Genetica 48:109-114.
Kang, K.S. & Lindgren, D. () Fertility variation among clones of korean pine (Pinus koraiensis s. et z.) and its implications on seed orchard management. Forest Genetics 6:183-192.
