A Pollen-Based Assisted Migration for Rapid Forest Adaptation.

Climate change poses an unprecedented threat to forest ecosystems, necessitating innovative adaptation strategies. Traditional assisted migration approaches, while promising, face challenges related to environmental constraints, forestry practices, phytosanitary risks, economic barriers, and legal constraints. This has sparked debate within the scientific community, with some advocating for the broader implementation of assisted migration despite these limitations, while others emphasize the importance of local adaptation, which may not keep pace with the rapid rate of climate change.

Making the Genotypic Variation Visible: Hyperspectral Phenotyping in Scots Pine Seedlings.

Hyperspectral reflectance contains valuable information about leaf functional traits, which can indicate a plant's physiological status. Therefore, using hyperspectral reflectance for high-throughput phenotyping of foliar traits could be a powerful tool for tree breeders and nursery practitioners to distinguish and select seedlings with desired adaptation potential to local environments. We evaluated the use of 2 nondestructive methods (i.

Effect of clonal testing on the efficiency of genomic evaluation in forest tree breeding.

Through stochastic simulations, accuracies of breeding values and response to selection were assessed under traditional pedigree-(BLUP) and genomic-based evaluation methods (GBLUP) in forest tree breeding. The latter provides a methodological foundation for genomic selection. We evaluated the impact of clonal replication in progeny testing on the response to selection realized in seed orchards under variable marker density and target effective population sizes.

Accelerating Adaptation of Forest Trees to Climate Change Using Individual Tree Response Functions.

In forest tree breeding, assisted migration has been proposed to accelerate the adaptive response to climate change. Response functions are currently fitted across multiple populations and environments, enabling selections of the most appropriate seed sources for a specific reforestation site. So far, the approach has been limited to capturing adaptive variation among populations, neglecting tree-to-tree variation residing within a population.

Genetic diversity of Norway spruce ecotypes assessed by GBS-derived SNPs.

We investigated the genetic structure of three phenotypically distinct ecotypic groups of Norway spruce (Picea abies) belonging to three elevational classes; namely, low- (acuminata), medium- (europaea), and high-elevation (obovata) form, each represented by 150 trees. After rigorous filtering, we used 1916 Genotyping-by-Sequencing generated SNPs for analysis. Outputs from three multivariate analysis methods (Bayesian clustering algorithm implemented in STRUCTURE, Principal Component Analysis, and the Discriminant Analysis of Principal Components) indicated the presence of a distinct genetic cluster representing the high-elevation ecotypic group.