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Dryad

Microsatellite data for Cryptopygus antarcticus travei

Cite this dataset

Monsanto, Daniela et al. (2024). Microsatellite data for Cryptopygus antarcticus travei [Dataset]. Dryad. https://doi.org/10.5061/dryad.mkkwh715s

Abstract

Biodiversity patterns are shaped by the interplay between geodiversity and organis-mal characteristics. Superimposing genetic structure onto landscape heterogeneity(i.e., landscape genetics) can help to disentangle their interactions and better under-stand population dynamics. Previous studies on the sub-Antarctic Prince EdwardIslands (located midway between Antarctica and Africa) have highlighted the im-portance of landscape and climatic barriers in shaping spatial genetic patterns andhave drawn attention to the value of these islands as natural laboratories for study-ing fundamental concepts in biology. Here, we assessed the fine-scale spatial geneticstructure of the springtail, Cryptopygus antarcticus travei, which is endemic to MarionIsland, in tandem with high-resolution geological data. Using a species-specific suiteof microsatellite markers, a fine-scale sampling design incorporating landscape com-plexity and generalised linear models (GLMs), we examined genetic patterns overlaidonto high-resolution digital surface models and surface geology data across two 1-kmsampling transects. The GLMs revealed that genetic patterns across the landscapeclosely track landscape resistance data in concert with landscape discontinuities andbarriers to gene flow identified at a scale of a few metres. These results show thatthe island's geodiversity plays an important role in shaping biodiversity patterns andintraspecific genetic diversity. This study illustrates that fine-scale genetic patternsin soil arthropods are markedly more structured than anticipated, given that previ-ous studies have reported high levels of genetic diversity and evidence of geneticstructing linked to landscape changes for springtail species and considering the ho-mogeneity of the vegetation complexes characteristic of the island at the scale oftens to hundreds of metres. By incorporating fine-scale and high-resolution landscapefeatures into our study, we were able to explain much of the observed spatial geneticpatterns. Our study highlights geodiversity as a driver of spatial complexity. Morewidely, it holds important implications for the conservation and management of thesub-Antarctic islands.

Methods

Sampling

Transect sampling was conducted on eastern Marion Island at two sampling areas, namely Nellie Humps (NH) and Skua Ridge (SR); these sites are approximately 2.4 km apart. The transects were positioned in areas with high levels of habitat heterogeneity, consisting of grey and black lava formations of varying geological ages, rivers, footpaths, and various vegetation biomes. Each sampling area encompassed two transects approximately one km in length, which were positioned perpendicular to one another to form a cross shape. The NH site included 24 sampling points separated from each other by a geographic distance ranging from 30 to 120 m, while the SR site comprised 21 sampling points separated by distances ranging from 60 and 190 m.

Cryptopygus a. travei specimens were collected by extracting them from sampled moss and/or ferns (approximately 10 cm3) using Berlese-Tullgren funnels. Twenty individuals of C. a. travei from each sampling point were identified and sorted using a compound light microscope, and stored in absolute ethanol (Merck, South Africa).

Microsatellite genotyping

Whole genomic DNA was extracted using the DNeasy® Blood and Tissue Kit (Qiagen®, Hilden, Germany), according to the manufacturer's recommendations, with minor modifications that included a longer digestion step (overnight, but not more than 20 hours) and a reduced final elution volume (75 μl instead of 100 μl). Microsatellite loci were amplified in multiplex reactions (seven multiplex sets based on the criteria described by Rastorgueff et al., 2016) using 21 highly variable and species-specific markers (Rastorgueff et al., 2016), and fragment analysis was performed on a MultiGeneTM OptiMax Thermal Cycler (Applied Biosystems). Cleaned PCR amplicons were sized using the ABI Prism® 3500XL Genetic Analyser (Applied Biosystems, Foster City, California, USA). Alleles were analysed, scored, and binned manually using the Geneious v8.1.5 microsatellite plugin 1.4.

Usage notes

MS Excel

Missing data: -9

Funding

National Research Foundation, Award: 138016, Competitive Programme for Rated Researchers (CPRR) grant

National Research Foundation, Award: 129235, South African National Antarctic Programme (SANAP) grant