Development of a universal height response model for transfer of Norway spruce (Picea abies L. Karst) in Fennoscandia.

Norway spruce is a major industrial tree species in Fennoscandia and future productivity of the species must be secured by matching the variation in adaptation of the species with suitable sites for optimized performance. An appropriate transfer model for forest reproductive material (FRM) is crucial for regeneration of productive forests in the changing climatic conditions that are predicted to occur in Fennoscandia. We have developed a transfer model for prediction of height of Norway spruce in Norway, Sweden, and Finland, using data acquired from 438 progeny and provenance trials with 1919 genetic entries of local and transferred origins. Transfer of genetic material at a given site was expressed in terms of the difference in daylength (photoperiod) between the site and its origin. This variable best reflected the nonlinear response to transfer that has been commonly reported in previous studies. Apart from the transfer variable, the height prediction model included the age of material when height measurements were acquired, annual temperature sum over 5 °C, precipitation during the vegetation period, and interaction terms between test site and transfer variables. The results show that long northward transfers (4-5° latitude) seem to be optimal for relatively mild sites in southern parts of the countries where growing season is longer, and shorter northward transfers (2-4° latitude) for harsher northern sites with shorter growing seasons. The transfer model also predicts that southward transfers of Norway spruce would result in height growth reductions. The developed model provides foundations for development of common or national recommendations for genetically improving Norway spruce material in Fennoscandia.

Predicting evolutionary potential: A numerical test of evolvability measures.

Despite sophisticated mathematical models, the theory of microevolution is mostly treated as a qualitative rather than a quantitative tool. Numerical measures of selection, constraints, and evolutionary potential are often too loosely connected to theory to provide operational predictions of the response to selection. In this paper, we study the ability of a set of operational measures of evolvability and constraint to predict short-term selection responses generated by individual-based simulations. We focus on the effects of selective constraints under which the response in one trait is impeded by stabilizing selection on other traits. The conditional evolvability is a measure of evolutionary potential explicitly developed for this situation. We show that the conditional evolvability successfully predicts rates of evolution in an equilibrium situation, and further that these equilibria are reached with characteristic times that are inversely proportional to the fitness load generated by the constraining characters. Overall, we find that evolvabilities and conditional evolvabilities bracket responses to selection, and that they together can be used to quantify evolutionary potential on time scales where the G-matrix remains relatively constant.