Aim: Marginal tree populations, either those located at the edges of the species’ range or in suboptimal environments, are often a valuable genetic resource for biological conservation. However, there is a lack of knowledge about the genetic consequences of population’s marginality, estimated across entire species’ ranges. Our study addresses this gap by providing information about several genetic indicators and their variability in marginal and core populations identified using quantitative marginality indices. Location: Southwestern Europe and North Africa. Methods: Using 10,185 SNPs across 82 populations of maritime pine ( Pinus pinaster Ait.), a widespread and economically important conifer characterised by a fragmented range, we modelled the relationship of seven genetic indicators potentially related to population evolutionary resilience, namely genetic diversity (based on all SNPs and two kind of outlier loci), inbreeding, genetic differentiation, recessive genetic load and genomic offset, with population geographical, demo-historical and ecological marginality (as estimated by nine quantitative indices). Models were constructed for both regional (introducing gene pool as random factor) and range-wide spatial scales. Results: We showed a trend towards decreasing overall genetic diversity (albeit not necessarily for genetic diversity estimates based on outlier loci) and increasing differentiation with geographic marginality, supporting the centre-periphery hypothesis (CPH). Moreover, we found no correlation between population inbreeding and marginality, while geographically marginal populations had a lower recessive genetic load (only models without the gene pool effect) and ecologically marginal populations had a higher genomic offset, suggesting higher maladaptation to future climate. Main conclusions: Overall, our results indicate that marginal populations could be at higher risk of maladaptation to climate change than core populations, despite reduced levels of genetic load, a risk that is exacerbated by typically small effective population sizes and increasing human impact.

Increasing forest productivity through afforestation under climate change is challenging, as maladaptation to current conditions may reduce trees’ growth capacity. Hence, understanding adaptation mechanisms can boost new tree plantations success, particularly in drought-prone environments such as the Mediterranean Basin. Here, we provide an example on how tree height measured in common gardens can be used to generate growth models and management scenarios for stone pine, an emblematic conifer widely used for restoration, landscaping, and nut production in Mediterranean countries. We used a multisite international network with nine common gardens testing 56 range-wide provenances and fitted Linear Mixed-Effects models of tree height at age 10, accounting for mortality, the climate of both the provenance and the common garden, tree density and microenvironment. Aridity at the common garden and tree density were the main drivers of tree height. The best-fitted model was used to project management scenarios under the current climate and for the period 2041–2070 for the Shared Socioeconomic Pathway 3-7.0. Taller trees resulted when using provenances from colder origins growing in high densities across the aridity range covered by the common gardens. Therefore, establishing new plantations with high densities during the juvenile stage might, albeit reducing nut production, enhances protective reforestation and carbon assimilation, provided that site-specific constraints, such as fire risk, are not limiting. Our results highlight the value of networks of common gardens to support reforestation programs and identify populations with high growth potential for protective and restorative afforestation under adverse climatic conditions.

Demographic history is expected to play a central role in shaping population vulnerability to climate change through its lasting effects on effective population sizes and genetic connectivity. However, existing studies report contrasting outcomes, and the consequences of alternative demographic histories have seldom been assessed concurrently across multiple taxa. Here, we analysed population genomic data from six of the major European forest tree species to address this gap. Across species, genetic isolation reduced adaptive potential, as reflected in lower standing genetic diversity. Greater genetic differentiation was also associated with increased maladaptation to climate, whereas the purge or accumulation of deleterious mutations depended on the severity of past demographic events. Finally, the beneficial effects of gene flow were evidenced across the six species by more optimal climate adaptation in highly connected populations. Altogether, our results provide valuable insights into how genetic differentiation, reflecting the combined effects of genetic drift and limited historical gene flow, influences current vulnerability of forest tree populations to climate change.

Conserving the genetic resources of major forest species is essential for mitigating climate risks associated with global change. Species distribution models and their projections under future emission scenarios are key tools for assessing climate-related threats to populations targeted for conservation efforts. In this study, we analyzed the populations included in the Spanish Network of Forest Genetic Conservation Units, comprising 297 units across twenty main forest tree species in Spain. We used species distribution models with high-resolution environmental data to assess habitat suitability across different climate scenarios and time periods. We introduced a Climatic Vulnerability Index to identify Genetic Conservation Units at risk of maladaptation by evaluating shifts in current conditions. Our results reveal spatial and interspecific heterogeneity in the future climatic vulnerability of the conservation network, as well as a relationship between expert-defined marginality and current climatic unsuitability under the Spanish Group model. Overall, our findings provide a basis for prioritizing conservation actions, guiding adaptive forest management, and supporting the long-term monitoring and viability of forest genetic resources under accelerating climate change.

Populations at ecological or geographic range limits experience distinctive genetic processes driven by demographic constraints, adaptation to atypical environments and reduced gene flow. These marginal populations can constitute valuable genetic resources, yet, the relationship between marginality and genetic variation remains poorly understood in forest trees. We investigated this relationship in four European conifers (Pinus pinea, Pinus pinaster, Pinus sylvestris and Taxus baccata), which share main life-history traits but represent contrasting demographic histories and evolutionary strategies. Across 230 native populations, we quantified six marginality indices related to climate, geography, or demographic history, together with five SNP-based genetic indicators describing inbreeding, genetic diversity and differentiation, genetic load, and genomic offset. Using a comparative multi-species framework, we assessed the influence of marginality on genetic indicators and evaluated the consistency of patterns across species. Historical (i.e., linked to the post-glacial colonization history) and climatic marginality mainly reflected species-specific evolutionary trajectories, whereas distance from the distribution centroid was consistently associated with lower genetic diversity and higher population differentiation across species. Importantly, marginality and genetic distinctiveness only partially overlapped, indicating that range-edge populations do not form a homogeneous evolutionary category. Overall, our findings highlight the key role of demographic isolation and historical processes in shaping genetic patterns at species' range limits. They also showed that marginal populations may represent either genetically vulnerable populations or reservoirs of unique evolutionary potential. Integrating genomic information with quantitative measures of marginality can improve assessment of population vulnerability, evolutionary resilience and conservation value in forest trees.