Silver fir (Abies alba Mill.) is a keystone conifer of European montane forest ecosystems that has experienced large fluctuations in population size during during the Quaternary and, more recently, due to land-use change. To forecast the species9 future distribution and survival, it is important to investigate the genetic basis of adaptation to environmental change, notably to extreme events. For this purpose, we here provide a first draft genome assembly and annotation of the silver fir genome, established through a community-based initiative. DNA obtained from haploid megagametophyte and diploid needle tissue was used to construct and sequence Illumina paired-end and mate-pair libraries, respectively, to high depth. The assembled A. alba genome sequence accounted for over 37 million scaffolds corresponding to 18.16 Gb, with a scaffold N50 of 14,051 bp. Despite the fragmented nature of the assembly, a total of 50,757 full-length genes were functionally annotated in the nuclear genome. The chloroplast genome was also assembled into a single scaffold (120,908 bp) that shows a high collinearity with both the A. koreana and A. sibirica complete chloroplast genomes. This first genome assembly of silver fir is an important genomic resource that is now publicly available in support of a new generation of research. By genome-enabling this important conifer, this resource will open the gate for new research and more precise genetic monitoring of European silver fir forests.

Genetic monitoring of populations currently attracts interest in the context of the Convention on Biological Diversity but needs long-term planning and investments. However, genetic diversity has been largely neglected in biodiversity monitoring, and when addressed, it is treated separately, detached from other conservation issues, such as habitat alteration due to climate change. We report an accounting of efforts to monitor population genetic diversity in Europe (genetic monitoring effort, GME), the evaluation of which can help guide future capacity building and collaboration towards areas most in need of expanded monitoring. Overlaying GME with areas where the ranges of selected species of conservation interest approach current and future climate niche limits helps identify whether GME coincides with anticipated climate change effects on biodiversity. Our analysis suggests that country area, financial resources and conservation policy influence GME, high values of which only partially match species’ joint patterns of limits to suitable climatic conditions. Populations at trailing climatic niche margins probably hold genetic diversity that is important for adaptation to changing climate. Our results illuminate the need in Europe for expanded investment in genetic monitoring across climate gradients occupied by focal species, a need arguably greatest in southeastern European countries. This need could be met in part by expanding the European Union’s Birds and Habitats Directives to fully address the conservation and monitoring of genetic diversity.

In the present paper we studied the genetic diversity and genetic structure of five Norway spruce (Picea abies (L.) Karsten) natural populations situated in Serbia, belonging to the southern lineage of the species at the southern margin of the species distribution range. Four populations occur as disjunct populations on the outskirts of the Dinaric Alps mountain chain, whereas one is located at the edge of Balkan Mountain range and, therefore, can be considered as ecologically marginal due to drier climatic conditions occurring in this region. Due to the negative effect of biotic and abiotic stress factors, the sustainability of these populations is endangered, making conservation of their genetic resources one of the key measures of Norway spruce persistence in Serbia under climatic changes. The insight on genetic diversity and genetic structure of the studied spruce populations can provide the information required for the initiation of programs aimed at the conservation and utilization of spruce genetic resources at the rear edge of species environmental limits. Norway spruce genetic variation and population genetic structure were estimated using eight EST-SSR markers. The results showed that mean expected heterozygosity was 0.616 and allelic richness 10.22. Genetic differentiation among populations was low (F_st = 0.007). No recent bottleneck effect or isolation by distance were detected. Bayesian clustering, obtained with STRUCTURE, grouped the populations into two genetic clusters, whereas UPGMA analysis distinguished three main groups approximately in line with the geographic area of occurrence. Based on the study results and the EUFORGEN Pan-European strategy for genetic conservation of forest trees, the establishment of additional dynamic gene conservation units must be considered in Serbia in order to protect the adaptive and neutral genetic diversity of the species.

Safeguarding sustainability of forest ecosystems with their habitat variability and all their functions is of highest priority. Therefore, the long-term adaptability of forest ecosystems to a changing environment must be secured, e.g., through sustainable forest management. High adaptability is based on biological variation starting at the genetic level. Thus, the ultimate goal of the Convention on Biological Diversity (CBD) to halt the ongoing erosion of biological variation is of utmost importance for forest ecosystem functioning and sustainability. Monitoring of biological diversity over time is needed to detect changes that threaten these biological resources. Genetic variation, as an integral part of biological diversity, needs special attention, and its monitoring can ensure its effective conservation. We compare forest genetic monitoring to other biodiversity monitoring concepts. Forest genetic monitoring (FGM) enables early detection of potentially harmful changes of forest adaptability before these appear at higher biodiversity levels (e.g., species or ecosystem diversity) and can improve the sustainability of applied forest management practices and direct further research. Theoretical genetic monitoring concepts developed up to now need to be evaluated before being implemented on a national and international scale. This article provides an overview of FGM concepts and definitions, discusses their advantages and disadvantages, and provides a flow chart of the steps needed for the optimization and implementation of FGM. FGM is an important module of biodiversity monitoring, and we define an effective FGM scheme as consisting of an assessment of a forest population’s capacity to survive, reproduce, and persist under rapid environmental changes on a long-term scale.

Common ash (Fraxinus excelsior) is under intensive attack from the invasive alien pathogenic fungus Hymenoscyphus fraxineus, causing ash dieback at epidemic levels throughout Europe. Previous studies have found significant genetic variation among genotypes in ash dieback susceptibility and that host phenology, such as autumn yellowing, is correlated with susceptibility of ash trees to H. fraxineus; however, the genomic basis of ash dieback tolerance in F. excelsior requires further investigation. Here, we integrate quantitative genetics based on multiple replicates and genome‐wide association analyses with machine learning to reveal the genetic architecture of ash dieback tolerance and of phenological traits in F. excelsior populations in six European countries (Austria, Denmark, Germany, Ireland, Lithuania, Sweden). Based on phenotypic data of 486 F. excelsior replicated genotypes we observed negative genotypic correlations between crown damage caused by ash dieback and intensity of autumn leaf yellowing within multiple sampling sites. Our results suggest that the examined traits are polygenic and using genomic prediction models, with ranked single nucleotide polymorphisms (SNPs) based on GWAS associations as input, a large proportion of the variation was predicted by unlinked SNPs. Based on 100 unlinked SNPs, we can predict 55% of the variation in disease tolerance among genotypes (as phenotyped in genetic trials), increasing to a maximum of 63% when predicted from 9155 SNPs. In autumn leaf yellowing, 52% of variation is predicted by 100 unlinked SNPs, reaching a peak of 72% using 3740 SNPs. Based on feature permutations within genomic prediction models, a total of eight nonsynonymous SNPs linked to ash dieback crown damage and autumn leaf yellowing (three and five SNPs, respectively) were identified, these were located within genes related to plant defence (pattern triggered immunity, pathogen detection) and phenology (regulation of flowering and seed maturation, auxin transport). We did not find an overlap between genes associated with crown damage level and autumn leaf yellowing. Hence, our results shed light on the difference in the genomic basis of ADB tolerance and autumn leaf yellowing despite these two traits being correlated in quantitative genetic analysis. Overall, our methods show the applicability of genomic prediction models when combined with GWAS to reveal the genomic architecture of polygenic disease tolerance enabling the identification of ash dieback tolerant trees for breeding or conservation purposes.