Published October 28, 2015 | Version v1
Dataset Open

Data from: Detecting a hierarchical genetic population structure: the case study of the Fire Salamander (Salamandra salamandra) in Northern Italy

  • 1. University of Milano-Bicocca
  • 2. University of Milan
  • 3. Istituto Superiore per la Protezione e la Ricerca Ambientale

Description

The multi-step method here applied in studying the genetic structure of a low dispersal and philopatric species, like the Fire Salamander Salamandra salamandra, was proved to be effective in identifying the hierarchical structure of population living in broadleaved forest ecosystems in Northern Italy. In this study 477 salamander larvae, collected in 28 sampling populations (SPs) in the Prealpine and in the foothill areas of Northern Italy, were genotyped at 16 specie-specific microsatellites. SPs showed a significant overall genetic variation (Global FST=0.032, p<0.001). The genetic population structure was assessed by using STRUCTURE 2.3.4. We found two main genetic groups, one represented by populations inhabiting the Prealpine belt, which maintain connections with those of the Eastern foothill lowland (PEF), and a second group with the populations of the Western foothill lowland (WF). The two groups were significantly distinct with a Global FST of 0.010 (p<0.001). While the first group showed a moderate structure, with only one divergent sampling population (Global FST =0.006, p<0.001), the second group proved more structured being divided in four clusters (Global FST=0.017, p=0.058). This genetic population structure should be due to the large conurbations and main roads that separate the WF group from the Prealpine belt and the Eastern foothill lowland. The adopted methods allowed the analysis of the genetic population structure of Fire Salamander from wide to local scale, identifying different degrees of genetic divergence of their populations derived from forest fragmentation induced by urban and infrastructure sprawl.

Notes

Files

Macrosatellites_6digit.csv

Files (56.5 kB)

Name Size Download all
md5:a04637d2f3d314897b21537c48f556fc
56.5 kB Preview Download

Additional details

Related works

Is cited by
10.1002/ece3.1335 (DOI)