期刊
MOLECULAR ECOLOGY
卷 32, 期 2, 页码 281-298出版社
WILEY
DOI: 10.1111/mec.16334
关键词
conservation genomics; demographic simulations; genetic load; population bottleneck; sea otters
The genetic consequences of species-wide declines are seldom studied, but sea otters provide an exceptional case as their population decline occurred range-wide and simultaneously. By using genomic data and simulations, we found distinct population structure among sea otters and identified Californian sea otters as survivors of a divergent lineage isolated for thousands of years. The simulations also revealed that the extreme population decline could have long-lasting effects on the fitness of recovering populations, but historically low effective population sizes may have mitigated the impact of decline on genetic health.
The genetic consequences of species-wide declines are rarely quantified because the timing and extent of the decline varies across the species' range. The sea otter (Enhydra lutris) is a unique model in this regard. Their dramatic decline from thousands to fewer than 100 individuals per population occurred range-wide and nearly simultaneously due to the 18th-19th century fur trade. Consequently, each sea otter population represents an independent natural experiment of recovery after extreme population decline. We designed sequence capture probes for 50 Mb of sea otter exonic and neutral genomic regions. We sequenced 107 sea otters from five populations that span the species range to high coverage (18-76x) and three historical Californian samples from similar to 1500 and similar to 200 years ago to low coverage (1.5-3.5x). We observe distinct population structure and find that sea otters in California are the last survivors of a divergent lineage isolated for thousands of years and therefore warrant special conservation concern. We detect signals of extreme population decline in every surviving sea otter population and use this demographic history to design forward-in-time simulations of coding sequence. Our simulations indicate that this decline could lower the fitness of recovering populations for generations. However, the simulations also demonstrate how historically low effective population sizes prior to the fur trade may have mitigated the effects of population decline on genetic health. Our comprehensive approach shows how demographic inference from genomic data, coupled with simulations, allows assessment of extinction risk and different models of recovery.
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