首页|Machine learning approaches to assess microendemicity and conservation risk in cave-dwelling arachnofauna
Machine learning approaches to assess microendemicity and conservation risk in cave-dwelling arachnofauna
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – According to news reporting based on a preprint abstract, our journalists obtained thefollowing quote sourced from biorxiv.org:“The biota of cave habitats faces heightened conservation risks, due to geographic isolation and highlevels of endemism. Molecular datasets, in tandem with ecological surveys, have the potential to delimitprecisely the nature of cave endemism and identify conservation priorities for microendemic species. Here,we sequenced ultraconserved elements of Tegenaria within, and at the entrances of, 25 cave sites to testphylogenetic relationships, combined with an unsupervised machine learning approach to delimit species.
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