A range-wide postglacial history of Swiss stone pine based on molecular markers and palaeoecological evidence

Aim: Knowing a species’ response to historical climate shifts helps understanding its perspectives under global warming. We infer the hitherto unresolved postglacial history of Pinus cembra. Using independent evidence from genetic structure and demographic inference of extant populations, and from palaeoecological findings, we derive putative refugia and re-colonisation routes.
Location: European Alps and Carpathians.
Taxa: Pinus cembra.
Methods: We genotyped nuclear and chloroplast microsatellite markers in nearly 3,000 individuals from 147 locations across the entire natural range of P. cembra. Spatial genetic structure (Bayesian modelling) and demographic history (Approximate Bayesian Computation) were combined with palaeobotanical records (pollen, macrofossils) to infer putative refugial areas during the Last Glacial Maximum (LGM) and re-colonisation of the current range.
Results: We found distinct spatial genetic structure, despite low genetic differentiation even between the two d..., All methodological approaches are described in the associated paper (Gugerli et al., Journal of Biogeography 2023)., Genotype file with individual genotypes from 11 nuclear microsatellites (2 lines per individual), prepared for input in the clustering software STRUCTURE (Pritchard et al., Genetics 2000), available at https://web.stanford.edu/group/pritchardlab/structure_software/release_versions/v2.3.4/html/structure.html:
Gugerli_etal_JoB2023_nSSRs_STRUCTURE.csv
Gugerli_etal_JoB2023_nSSRs_GenePop.csv
 
Three files with data from 4 chloroplast microsatellites, formatted for input in the clustering software BAPS (Corander et al., Genetics 2003), currently under development as an R package at https://github.com/ocbe-uio/rBAPS:
Gugerli_etal_JoB2023_cpSSRs-BAPS_Pop_PopGroupsUnlinkedLoci.csv
Gugerli_etal_JoB2023_cpSSRs-BAPS_Pop_names.csv
Gugerli_etal_JoB2023_cpSSRs-BAPS_Pop_indices.csv
 
Populations file with information on sampling sites (population codes, mountain range, country, population name, geographic coordinates in WGS84 format) and sample numbers.
Gugerli_etal_JoB2023_PopulationSampling.csv,