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. Our findings bring a vital message to forestry practice affirming that artificial transfer of forest reproductive material, especially for stands under harsh climate conditions, should be considered with caution.

Norway spruce is a widespread and economically highly important tree species in Central Europe which occurs there in different morphotypic forms (also known as ecotypes). Previously established common garden experiments indicated that the morphological differentiation is most likely genetically determined. The genetic structure of Norway spruce morphological variants might be an indicator (marker) of specific sustainability in forest ecosystems. In this study, we investigated 436 individuals from autochthonous populations belonging to three different ecotypes. The main aim was to evaluate a level of genetic intra and interpopulation diversity among the low, medium and high-elevation ecotypes using both expressed sequence tag simple sequence repeats (EST – SSR) and genomic SSR markers. Sixteen highly polymorphic microsatellite loci folded in two newly designed multiplexes were used to depicture the genetic structure of targeted trees. Important allele frequency parameters, such as the mean expected (0.722, SE = 0.061) and observed (0.585, SE = 0.062) heterozygosity and mean effective number of alleles (N_e = 5.943, SE = 1.279), were estimated. The low genetic differentiation detected among different ecotypes (F_st = 0.008) was further discussed and clarified.

Norway Spruce (Picea abies (L.) H. Karst.), a timber species of significant economic and ecological importance in the Northern Hemisphere, faces increasing threats imposed by drought and bark beetle infestation intensified by ongoing climate change. Despite the extensive mortality within stands, a small proportion of mature trees remarkably survive during severe bark beetle outbreaks. Hypothesizing that bark beetle resilience is genetically determined and thus is under natural selection, we anticipated that there is a genetic variation in genome regions linked to the respective resistance in surviving trees. In the Bohemian Forest, restricted to the area of the Czech–Austrian–German border, we identified those resistant individuals, referred to as the “Last Trees Standing” (LTS). Concurrently, we collected reference samples from randomly selected individuals from natural regeneration within concerned sites (seedlings, young trees) and in adjacent unaffected stands (mature trees). Genomic data were generated on a 50K SNPs genotyping array. We conducted a population genetic study based on the Discriminant Analysis of Principal Components (DAPC) method as well as the Genome-Wide Association Study (GWAS). We identified 12 markers (SNPs) significantly associated with tree survival using this approach. Three of those SNPs are located within the genes with the known function in Arabidopsis thaliana orthologs. After further confirmation, we argue that the identified SNPs can be instrumental in identifying trees of higher resistance to bark beetle infestation.

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. This opinion paper proposes a novel pollen‐based assisted migration strategy as a potential middle ground in this debate. By leveraging existing seed orchard infrastructure for controlled pollen transfer, this approach aims to enhance forest resilience through the introduction of genetic material from climatically suitable sources while acknowledging local adaptation. We assess the genetic implications of the proposed strategy through computer simulation. Additionally, we examine the ecological implications of assisted gene flow, discussing the potential benefits of heterosis and the risks of outbreeding depression in intra‐specific hybrid populations. We further explore the advantages of pollen‐based migration in mitigating phytosanitary risks, reducing economic barriers, and simplifying legal considerations compared to traditional seed or seedling transfer methods. Regional perspectives on adapting pollen‐based assisted migration are provided, with specific examples from Northern and Central Europe. We highlight how this approach could be integrated into existing forestry practices and regulatory frameworks within the European Union. We conclude by advocating for the inclusion of pollen‐based assisted migration in future international projects and operational forestry, emphasizing the need for adaptable policies that can support innovative forest management strategies in the face of climate change.

Norway spruce, economically and ecologically one of the most important European forest tree species, rapidly declines due to massive bark beetle outbreaks across many countries. As a prerequisite of ecosystem stability facing climate changes of uncertain predictions, the reforestation management promoting locally adapted resources of broad genetic diversity should be prioritized, especially in nature conservation areas. In our case study carried out in the national park, Krkonoše Mountains (the Giant Mountains, the Czech Republic), we demonstrated a tree breeding strategy aiming at maximizing genetic diversity. More than four hundred unique Norway spruce accessions were genotyped on 15 microsatellite loci (N_e = 5.764, I = 1.713 and H_e = 0.685). Two core collection selection approaches were proposed to establish a new deployment population providing local gene sources of high genetic diversity. Namely, the Core Hunter selection algorithm, with average entry-to-nearest-entry distance (EN) optimization, was applied to identify the most diverse core collection set with the highest genetic diversity parameters obtained for 57 selected individuals (N_e = 6.507, I = 1.807, and H_e = 0.731). The latter core collection method proposed is innovative, based on choosing appropriate genotypes from a clustered heatmap. For simplicity, we demonstrated the principle of selection strategy on a reduced dataset. It is vital to promote panmixia of a newly established production population from a core collection to complete the conservation breeding effort. Thus, we demonstrated the utilization of the Optimum Neighborhood Algorithm (ONA) deployment that outperformed other deployment algorithms, especially in the case of balanced clone representation and uneven shapes of planting plots. We believe that the case study presented can be generalized and considered as a guideline for analogical tree breeding intentions.