Evolutionary stability, landscape heterogeneity, and human land-usage shape population genetic connectivity in the Cape Floristic Region biodiversity hotspot
Data files
Dec 15, 2020 version files 975.08 KB
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LocationSA1.csv
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LS_nuDNA_for_cGD.csv
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nu_FST.csv
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README.rtf
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RodneyIBRb.R
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SAcpFstFull.csv
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Salignum_cp_2020-06.csv
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Salignum_nu_2020-06.txt
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Salignum2.csv
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SalignumPCA.R
Abstract
As human-induced change eliminates natural habitats, it impacts genetic diversity and population connectivity for local biodiversity. The South African Cape Floristic Region (CFR) is the most diverse extratropical area for plant biodiversity, and much of its habitat is protected as a UNESCO World Heritage site. There has long been great interest in explaining the underlying factors driving this unique diversity, especially as much of the CFR is endangered by urbanization and other anthropogenic activity. Here, we use a population and landscape genetic analysis of SNP data from the CFR endemic plant Leucadendron salignum or “common sunshine conebush” as a model to address the evolutionary and environmental factors shaping the vast CFR diversity. We found that high population structure, along with relatively deeper and older genealogies, are characteristic of the southwestern CFR, whereas, low population structure and more recent lineage coalescence depicts the eastern CFR. Population network analyses show genetic connectivity is facilitated in areas of lower elevation and higher seasonal precipitation. These population genetic signatures corroborate CFR species-level patterns consistent with high Pleistocene biome stability and landscape heterogeneity in the southwest, but with coincident instability in the east. Finally, we also find evidence of human land-usage as a significant gene flow barrier, especially in severely-threatened lowlands where genetic connectivity has been historically the highest. These results help identify areas where conservation plans can prioritize protecting high genetic diversity threatened by contemporary human activities within this unique cultural UNESCO site.
Methods
These data include SNPs collected from nuclear and mitochondrial DNA. The data were analyzed in R