
doi: 10.3390/f12081101
The productivity of forests has been linked to the sensitivity of tree growth to meteorological conditions and their fluctuations, hence moderation of tree sensitivity is one of the goals for climate-smart forest management. For this, tree breeding is among the most effective means, particularly if breeding populations are supplemented with genotypes (provenances) adapted to the expected climates. Nonetheless, heritability of traits is essential for their improvement by breeding. In this study, heritability of growth sensitivity of south-eastern Baltic provenances of Scots pine differing by field performance to meteorological conditions was assessed combining methods of quantitative genetics and dendrochronology. Five parallel provenance trials within the south-eastern Baltic region were investigated. The effects of regional weather drivers of growth (moisture regime in summer, temperature regime in preceding summer and in the dormancy period) were estimated, yet their strengths differed among the provenances, indicating local specialization of metapopulations of Scots pine. The heritability of growth sensitivity to these factors ranged from low to moderate, similarly as observed for the morphometric traits within the region; however, the provenance (genetic) variation appeared to be higher. The differences in heritability of responses, however, indicated uneven adaptive significance of weather conditions. Although the estimates were based on a limited set of genotypes implying caution in the extrapolation of results, the weather-growth relationships and their heritability indicate that sensitivity of growth is a complementary trait aiding breeding of forest reproductive material best suited for future climates. Heritable weather-growth relationships also imply a high potential for forest breeding to moderate the sensitivity of the trees.
quantitative genetics, <i>Pinus sylvestris</i>, parallel trials, growth sensitivity, local specialization
quantitative genetics, <i>Pinus sylvestris</i>, parallel trials, growth sensitivity, local specialization
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