Cryptic population structure at the northern range margin of the service tree Sorbus domestica

Abstract

Climate change has aroused interest in planting warm- and drought-adapted trees in managed forests and urban areas. An option is to focus on tree species that occur naturally, but have centers of distribution in warmer and drier areas. However, in order to protect the species pool of genetic diversity, efforts of planting and promotion should be informed by knowledge on the local genetic diversity. Here, we studied the macro- and micro-scale population genetic structure of the rare European fruit tree Sorbus domestica at its northern range margin, in western Switzerland. New microsatellite data were combined with published data from across the European distribution of the species. Analyses revealed the presence of mainly one of two species-wide ancestral clusters, i.e., the western European cluster, with evidence that it consists of two cryptic sub-clusters. Average pairwise F _ST of 0.118 was low across the range, and only allelic richness was reduced in the northern margin compared to more southern and southeastern areas of Europe. Based on our finding of considerable genetic diversity of the species in western and northern Switzerland, we suggest that a national propagation program should focus on collecting seeds from natural, high-density tree stands and propagate locally. More generally, our study shows that rare tree species in marginal areas of their distributions do not necessarily have low genetic diversity or heightened levels of inbreeding, and in those cases probably need no assisted migration in efforts to propagate them.

Keywords: Climate change; Drought-adapted; Forestry; Genetic diversity; Population genetics; Rare trees.

Figure 1. Summary of the individual-based cluster-assignment analysis using STRUCTURE.

Including either (A) all individuals from across Europe (localities abbreviated as in Table 2), (B) individuals from Switzerland and neighboring countries or (C) Switzerland only. Shown is the assignment (in percent) for K = 2, the best supported number of genetic clusters for all datasets.

Figure 2. Map of Switzerland with pie charts indicating cluster assignment based on STRUCTURE results.

For all genotyped individuals of Switzerland, from near Lake Geneva on the lower left to the area west of Lake Constance on the upper right (Fig. 1C). Inlets focus on the northwestern (NW) and northeastern (NE) regions, respectively. Major rivers are indicated in gray. (Map data adopted from the Federal Statistical Office, Neuchâtel, Switzerland).

Figure 3. Relationship among populations based on principal components (PC).

(A) Average PC scores for each population (±1 SD) along the first and second PC axes. (B) Relationship between the scores of the first PC axis for each individual and the overall STRUCTURE assignment (K = 2, Fig. 1A).

Figure 4. Pairwise relationship between the individual-based Euclidean genetic distance and the geographic distance.

For all Swiss individuals except samples from southwestern Switzerland. A Mantel test suggested a significant contribution of isolation-by-distance. The solid red line indicates the model fit of a local polynomial regression, and the dashed lines outline the 95% confidence limits.

Figure 5. Distribution of genetic diversity of Sorbus domestica across Europe.

(A) Observed heterozygosity, H_o, (B) inbreeding coefficient, F_IS (see Table 2 for details). Switzerland is highlighted in black.