We investigated population genetics of the native tree species Acer velutinum Boiss., Fagus orientalis Lipsky, and Quercus castaneifolia C.A. Mey. in the Hyrcanian forests of northern Iran and also F. orientalis populations in the Euro-Siberian and Colchic subregions of northern Türkiye. We used the double-digest RADseq method and genotyped 90 populations and 1,589 individuals across the distribution range of the species. Genome-wide SNPs from 28 populations of A. velutinum, 32 populations of F. orientalis, and 30 Q. castaneifolia revealed higher genetic differentiation among A. velutinum populations than among F. orientalis and Q. castaneifolia. The global FST value was lowest for F. orientalis populations and highest for A. velutinum populations, while the global FIS value was negative for A. velutinum. Demographic history analysis revealed a bottleneck during the last glacial period (11,500—115,000 Kya) for the A. velutinum populations with reduced effective population size (Ne). All three species show multiple bottlenecks and reduced Ne during the Quaternary. Pronounced genetic divergence among A. velutinum populations in the Hyrcanian forests compared to the other two species suggests cryptic speciation. Conversely, F. orientalis and Q. castaneifolia populations showed low levels of genetic structure, suggesting that species-specific factors, such as pollen production and pollination efficiency, may have influenced the genetic patterns within these species in similar environments. The nucleotide diversity of F. orientalis populations in Iran is negatively correlated with altitude (p = 0.046). In contrast, A. velutinum populations show a significant correlation between nucleotide diversity and longitude (p = 0.008). Furthermore, the F. orientalis populations from Türkiye showed a distinct west–east genetic structure and were highly diverged from the Iranian F. orientalis populations.

Maximizing genetic gain at an acceptable diversity level is an ideal outcome of selection and deployment. Based on this criterion, this study investigated the efficiency of unequal clonal deployment strategies for clonal forestry and compared them with truncation selection and equal deployment (truncation deployment). Two unequal deployment strategies were considered: (1) deploying the clones in linear relationship to their genetic values (linear deployment) and (2) optimizing genetic gain at a given diversity level using an algorithm (optimal deployment). All strategies were applied to candidate clone sets constructed from two clonal tests of spruces with one having a complex relationship of clone, half-sib, and full-sib and the other having a simpler relationship of clone and half-sib. At a constant diversity level, substantially more expected gains were obtained by the unequal deployment strategies than by truncation deployment. Optimal deployment was at least equal to linear deployment. Optimal deployment’s superiority was more evident when the candidate clones in the set were more closely related, having less available diversity for selection, and/or when higher diversity levels were demanded, but diminished when the candidate clones were unrelated or equally related. We recommend using optimal deployment for clonal forestry, although in some cases, linear deployment might be a near-optimal alternative. As current clonal tests are based on advanced breeding cycles, candidate clones for selection are inevitably related to some degree, so optimal deployment is likely to become preferred.