The notion that adaptive evolution markedly shapes species distribution probabilities has pushed for genomics-informed species distribution models (gSDMs). These models account for intraspecific variation and gene flow to enhance the accuracy of species range projections. Yet, gSDMs remain encumbered by limitations stemming from substantial sequencing costs and from a global change mindset skewed towards climate warming, likely resulting in an overly narrow view on genomic vulnerability. Current developments in sequencing methodologies are paving the way for gSDMs that transcend spatial and temporal constraints. Specifically, the ability to quantify genome-wide standing genetic variation across species’ ranges unlocks bottom-up gSDM, where range projections are shaped by the intrinsic ability of populations to evolve in response to a wide array of environmental stressors. By integrating range-wide variation in dispersal, drift, demographic history and overall adaptive potential, bottom-up gSDMs promise greater realism and robustness in addressing the full spectrum of environmental threats.

Climate change is increasingly impacting temperate forest ecosystems and many forest herbs might be unable to track the changing climate due to dispersal limitations. Forest herbs with a low adaptive capacity are prone to climate change effects and may benefit from conservation strategies mitigating dispersal limitations and evolutionary constraints, such as assisted migration. To assess the vulnerability of forest herbs to climate change it is key to evaluate their adaptive potential and to quantify the genetic offset. To this end, we quantified climate change vulnerability metrics using single nucleotide polymorphisms (SNPs) along a latitudinal gradient of the self-incompatible deciduous forest herb Primula elatior. Southern populations displayed a sharp genetic turnover and a considerable amount of local adaptation under diversifying selection was discovered. However, most of the outlier loci could not be linked to climate variables (71%) and were likely related to other local adaptation drivers, such as photoperiodism. Furthermore, specific adaptations to climate extremes, such as drought stress, could not be detected. Populations in the south of the distribution area had high sensitivity to climate change due to a low adaptive capacity and a moderate genetic offset, while central European populations were sensitive due to a high genetic offset. We conclude that assisted migration with southern source populations could bear significant risk due to local maladaptation and a low adaptive capacity. Local admixture and restoration of ecological connectivity to increase the adaptive capacity and assisted range expansion to suitable habitat in the north could be advised as potential mitigation strategies.