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Heterobasidion parviporum is a fungal pathogen that is drastically damaging Norway spruce (Picea abies) in Europe. The infections will result in root and stem rot, causing significant economic losses for forest owners. Previous studies have shown that the PaLAR3 gene, which encodes the leucoanthocyanidin reductase enzyme, can increase resistance to H. parviporum in Norway spruce. The presence of the B allele at the PaLAR3 locus has been associated with higher (+)‐catechin concentrations and increased enzyme production in inoculation experiments, resulting in inhibited pathogen growth. The control of H. parviporum involves a multifaceted approach, including silvicultural and sustainable forestry practices, genetic resistance and chemical/biological control. In this study, we determined the PaLAR3 genotypes in a representative sample of Norway spruce breeding materials from southern Finland and examined their effect on necrosis caused by H. parviporum in spruce stems. The results showed that the homozygous PaLAR3BB genotype was present in only 9% of the trees. However, the necrotic area interacted with homozygous PaLAR3BB under low‐water treatment. These findings support the idea that the PaLAR3 locus may be a valuable marker for identifying P. abies resistance to different strains of Heterobasidion parviporum. [ABSTRACT FROM AUTHOR]

Great interests in silver birch (Betula pendula) forests have increased in an attempt to handle biodiversity and resilient forest management with more broad-leaved forests. However, up-to-date silver birch growth and yield models are still needed to predict the stand development in the future and support operational forest management and planning. The objectives of this study were to develop site index and stand characteristic models for silver birch plantations. Data for modelling were from the thinning and spacing experiments and tree breeding trials on silver birch plantations in southern and central Finland. The dominant height and site index (SI) models were fitted using the nonlinear mixed effect regression approach based on the Chapman-Richards function with the genetic effect from improved seedlings. The modelling result indicated a logical growth performance over age and higher dominant height with genetically improved seedlings. The stand characteristic models for unimproved seedlings were developed using multivariate mixed-effects modelling approach. The targeted, response variables were the basal area-weighted mean height (HW, m), the basal area-weighted mean diameter (DW, cm) and stand basal area (G, m2 ha−1) of silver birch. Stand biological age (AGE, year), SI estimated based on the model of the current study with the base age of 50 years, and the number of silver birch trees (N, trees ha−1) were all commonly applied as highly significant predictor variables for all of HW, DW, and G models. In addition to these predictors, thinning variables, comprised of the time since last thinning in year and the thinning intensity based on G, were highly significant in the DW and G models with logical behavior. Recent thinning affected negatively at first because trees in thinned stands were slimmer than those in unthinned stands that have grown from the early stage at the same level of N with thinned stands. After 13 years since last thinning, the effect turned positive indicating that the increments were expedited with thinning. Lastly, site type classified as either former agricultural land or forest site was included in the DW and G models. Consequently, all the models developed in this study were evaluated as practicable with easy-to-use predictors and desirable accuracy. • The dominant height and site index models were fitted well with genetic effect using the Chapman-Richards function. • Mean height and diameter and stand basal area were modelled using multivariate regression. • Age, site index, and stem number were the commonly-applied, driving predictors in stand characteristic models. • Thinning variables were highly significant in the models of mean diameter and stand basal area. • Simulations demonstrated model application, performance, and validity adequately. [ABSTRACT FROM AUTHOR]

Plantations of genetically improved forest trees are critical for economic sustainability in forestry. This review summarizes gains in objective traits and the resulting economic impact of tree breeding programmes in Scandinavia and Finland. Genetic improvement of forest trees in these countries began in the late 1940s, when the first phenotypically superior plus-trees were selected from natural environments. The main findings from this review are that (i) tree breeding can increase volume growth in the range 10–25%, and (ii) the bare land value associated with genetically improved trees gives a better return on investment and a shorter rotation period compared to the unimproved forests. As some Nordic countries are quite dependent on the forest industry, breeding programmes that have resulted in economic gains have been beneficial for society. Growth and wood quality traits are often adversely correlated, and the weighting of traits from an economic perspective could provide an index for determining maximum profit from breeding. Tree breeding faces an array of challenges in the future, such as changes in silviculture, climate, new pests and diseases, and demand for wood-based products. [ABSTRACT FROM PUBLISHER]