Height growth patterns of genetically improved Scots pine and silver birch

The breeding of forest tree species in the Baltic region has notably contributed to wood production for the bioeconomy. Growth modelling is used for long-term estimates of forest development. However, usually based on data from unimproved stands, they may underestimate the growth of improved trees. Accordingly, it is important to identify and integrate the altered stand dynamics associated with improved planting stock into existing growth models to accurately capture the resulting gains or, alternatively, develop new functions specifically designed for improved trees. We used the generalized algebraic difference approach to model and analyze height growth patterns of Scots pine and silver birch with different genetic improvement levels (improved forest reproductive material categories 'qualified' and 'tested'). Modelling was based on 14 260 and 55 926 height-age series from open-pollinated progeny trials in Latvia and Lithuania with an age range of 3-46 and 5-22 years for pine and birch, respectively. Dynamic generalized algebraic difference approach forms of commonly applied height growth functions with forest reproductive material-category-specific sets of coefficients were tested. The dynamic form of the Chapman-Richards and King-Prodan equations had the best fit for Scots pine and silver birch, respectively. The expected height growth of the category 'tested' was slightly better than the one for 'qualified', with more distinct differences in silver birch. The model with forest reproductive material-category-specific coefficients reflected the actual growth of improved trees; however, such application is limited to sites with medium and high site indices, where improved planting stock is typically used. We recommend the model for young stands up to the age of 20 and 40 years for pine and birch, respectively, considering the empirical data cover on which the functions are based. A unified dynamic height model with the same functional form but category-specific parameterization for different improvement levels allows a practical applicability and effective communication amongst diverse users, thereby promoting the utilization of the model amongst forest owners and managers who possess information regarding the origin of planting stock.