Advancing height growth models for the improved forest reproductive material of the main tree species in Latvia




The breeding of economically important forest tree species in the Baltic Sea region has contributed notably to the availability of quality wood for bioeconomy. Accordingly, the altered stand dynamics of improved trees should be identified and incorporated in growth models to accurately reflect these gains. Such advanced models can be used for assessment of different alternatives, e.g. strategies for increased carbon sequestration.

We tested and modified dynamic forms of the King-Prodan height growth function based on the remeasured National Forest Inventory plots in Latvia to predict the growth of improved Scots pine, Norway spruce and silver birch forest reproductive material (FRM) categories ‘qualified’ and ‘tested’ using height measurements from progenies of 371, 390, and 690 open-pollinated families, respectively. Both categories had steeper growth trajectories at young age compared to an unmodified function. Growth of category ‘tested’ for pine and birch exceeded that of category ‘qualified’ across the modelled age range, while trajectories mainly overlapped for spruce on lower site indices. The functions with FRM category-specific multipliers more accurately reflect the actual growth of improved stands, advancing planning of timely management activities like thinning. The single model with category-specific set of multipliers may be easy applicable in practice or incorporated in growth simulators without increased complexity for end-users. However, the predictions are limited to the sites with medium and high site indices, where improved planting stock is typically used.

Keywords: GADA approach, dynamic modelling, tree breeding, FRM categories



How to Cite

Zeltiņš, P., Šņepsts, G., Donis, J., Rieksts-Riekstiņš, R., Kangur, A., & Jansons, Āris. (2023). Advancing height growth models for the improved forest reproductive material of the main tree species in Latvia. Baltic Forestry, 28(2).



Forest Growth and Yield

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