Fine‐scale spatial genetic structure across the species range reflects recent colonization of high elevation habitats in silver fir (Abies alba Mill.). Issue 20 (20th August 2021) - Major, Enikő I.; Höhn, Mária; Avanzi, Camilla; Fady, Bruno; Heer, Katrin; Opgenoorth, Lars; Piotti, Andrea; Popescu, Flaviu; Postolache, Dragos; Vendramin, Giovanni G.; Csilléry, Katalin
Abstract: Variation in genetic diversity across species ranges has long been recognized as highly informative for assessing populations' resilience and adaptive potential. The spatial distribution of genetic diversity within populations, referred to as fine‐scale spatial genetic structure (FSGS), also carries information about recent demographic changes, yet it has rarely been connected to range scale processes. We studied eight silver fir ( Abies alba Mill. ) population pairs (sites), growing at high and low elevations, representative of the main genetic lineages of the species. A total of 1, 368 adult trees and 540 seedlings were genotyped using 137 and 116 single nucleotide polymorphisms (SNPs), respectively. Sites revealed a clear east‐west isolation‐by‐distance pattern consistent with the post‐glacial colonization history of the species. Genetic differentiation among sites ( F CT = 0.148) was an order of magnitude greater than between elevations within sites ( F SC = 0.031), nevertheless high elevation populations consistently exhibited a stronger FSGS. Structural equation modelling revealed that elevation and, to a lesser extent, post‐glacial colonization history, but not climatic and habitat variables, were the best predictors of FSGS across populations. These results suggest that high elevation habitats have been colonized more recently across the species range. Additionally, paternity analysis revealed a high reproductive skew among adults and a stronger FSGS in seedlings than in adults, suggesting that FSGS may conserve the signature of demographic changes for several generations. Our results emphasize that spatial patterns of genetic diversity within populations provide information about demographic history complementary to non‐spatial statistics, and could be used for genetic diversity monitoring, especially in forest trees.