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Biology subjects

Hoelzel, A. R.

Publications and source records attributed to Hoelzel, A. R..

3 recordsLinked to original sources

Postglacial recolonization of the Southern Ocean by elephant seals occurred from multiple glacial refugia

The Southern Ocean is warming more rapidly than other parts of our planet. How this regions endemic biodiversity will respond to such changes can be illuminated by studying past events, through genetic analyses of time-series data sets including historic and fossil remains. Archaeological and subfossil remains show that the southern elephant seal (Mirounga leonina) was common along the coasts of Australia and New Zealand in the recent past. This species is now mostly confined to sub-Antarctic islands and the southern tip of South America. We analysed ancient seal samples from Australia (Tasmania), New Zealand, and the Antarctic mainland to examine how southern elephant seals have responded to a changing climate and anthropogenic pressures during the Holocene. Our analyses show that these seals formed part of a broader Australasian lineage, comprising seals from all sampled locations from the south Pacific sector of the Southern Ocean. Our study demonstrates that southern elephant seal populations have dynamically altered both range and population sizes under climatic and human pressures, over surprisingly short evolutionary timeframes for such a large, long-lived mammal. Significance StatementGenetic data, alongside historic, archaeological, and subfossil remains show that Australasian populations of the southern elephant seal have been shaped by range expansions and contractions following the Last Glacial Maximum, with subsequent contractions during the late Holocene. These expansion and contraction events are likely to have been a direct result of climate change-induced habitat expansion and contraction, along with Indigenous and European sealing. Prehistoric climate change and more recent human pressures have substantially altered the geographic distribution and population size of southern elephant seals over short evolutionary timescales.

ecology↗

Museum specimens of a landlocked pinniped reveal recent loss of genetic diversity and unexpected population connections

AimThe Saimaa ringed seal (Pusa hispida saimensis) is endemic to Lake Saimaa in Finland. The subspecies is thought to have originated when parts of the ringed seal population of the Baltic region were trapped in lakes emerging due to post-glacial bedrock rebound around 9,000 years ago. During the 20th century, the population experienced a drastic human-induced bottleneck. Today encompassing a little over 400 seals with extremely low genetic diversity, it is classified as endangered. Our main aim was to evaluate the role of the 20th century bottleneck in the erosion of genetic diversity in the Saimaa seal population. We also evaluated connections with other ringed seals from the Baltic Sea, Lake Ladoga, North America, Svalbard and the White Sea. LocationLake Saimaa, Finland, together with the Baltic Sea and the Arctic Ocean. MethodsWe sequenced sections of the mitochondrial control region from 60 up to 125 years old museum specimens of the Saimaa ringed seal. The generated dataset was combined with publicly available sequences. We studied how genetic variation has changed through time in this subspecies, and how it is phylogenetically related to other ringed seal populations. ResultsWe observed temporal fluctuations in haplotype frequencies and loss of haplotypes accompanied by a recent reduction in female effective population size. In apparent contrast with the traditionally held view of the Baltic origin of the population, the Saimaa ringed seal mtDNA variation shows also affinities to North American ringed seals. Main conclusionsOur results suggest that the Saimaa ringed seal has experienced recent genetic drift associated with small population size. The results further suggest that extant Baltic ringed seals do not represent well the ancestral population of the Saimaa ringed seal, which calls for re-evaluation of the deep history of this subspecies.

evolutionary biology↗

SambaR: an R package for fast, easy and reproducible population-genetic analyses of biallelic SNP datasets

BackgroundSNP datasets can be used to infer a wealth of information about natural populations, including information about their structure, genetic diversity, and the presence of loci under selection. However, SNP data analysis can be a time-consuming and challenging process, not in the least because at present many different software packages are needed to execute and depict the wide variety of mainstream population-genetic analyses. Here we present SambaR, an integrative and user-friendly R package which automates and simplifies quality control and population-genetic analyses of biallelic SNP datasets. SambaR allows users to perform mainstream population-genetic analyses and to generate a wide variety of ready to publish graphs with a minimum number of commands (less than ten). These wrapper commands call functions of existing packages (including adegenet, ape, LEA, poppr, pcadapt and StAMPP) as well as new tools uniquely implemented in SambaR. ResultsWe tested SambaR on online available SNP datasets and found that SambaR can process datasets of millions of SNPs and hundreds of individuals within hours, given sufficient computing power. Newly developed tools implemented in SambaR facilitate optimization of filter settings, objective interpretation of ordination analyses, enhance comparability of diversity estimates from reduced representation library SNP datasets, and generate reduced SNP panels and structure-like plots with Bayesian population assignment probabilities. ConclusionSambaR facilitates rapid population genetic analyses on biallelic SNP datasets by removing three major time sinks: file handling, software learning, and data plotting. In addition, SambaR provides a convenient platform for SNP data storage and management, as well as several new utilities, including guidance in setting appropriate data filters. Availability and implementationThe SambaR source script, manual and example datasets are distributed through GitHub: https://github.com/mennodejong1986/SambaR

genetics↗