DNA barcoding of scorpions from Kosovo, with the first record of Alpiscorpius dinaricus (Di Caporiacco) (Scorpiones: Euscorpiidae)

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  DNA barcoding of scorpions from Kosovo, with the first record of Alpiscorpius dinaricus (Di Caporiacco) (Scorpiones: Euscorpiidae) ABSTRACT This study presents DNA barcoding data for Alpiscorpius dinaricus (Di Caporiacco) and Euscorpius hadzii Caporiacco. Barcode sequences were compared with publicly available reference data to support species identification, together with the evaluation of diagnostic morphological characters. Alpiscorpius dinaricus is recorded from Kosovo for the first time, representing a new national record and contributing to the knowledge of euscorpiid diversity in the region. Diagnostic illustrations of A. dinaricus are provided to facilitate reliable identification and to support future faunistic, taxonomic, and biogeographic studies. Euscorpius hadzii , previously known only from Prizren district, is now reported also from Bjeshkët e Nemuna Mountains (Western Kosovo). Geci, D., Ibrahimi, H., Bilalli, A., Musliu, M., Strohmeier, T., Koblmüller, S., … S...

Machine learning approaches to assess microendemicity and conservation risk in cave-dwelling arachnofauna

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Machine learning approaches to assess microendemicity and conservation risk in cave-dwelling arachnofauna

Abstract

The biota of cave habitats faces heightened conservation risks, due to geographic isolation and high levels of endemism. Molecular datasets, in tandem with ecological surveys, have the potential to precisely delimit 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 test phylogenetic relationships, combined with an unsupervised machine learning approach for detecting species. Our analyses identified clear and well-supported genetic breaks in the dataset that accorded closely with morphologically diagnosable units. Through these analyses, we also detected some previously unidentified, potential cryptic morphospecies. We then performed conservation assessments for seven troglobitic Israeli species of this genus and determined five of these to be critically endangered.

Steiner, H.G., Aharon, S., Ballesteros, J. et al. Machine learning approaches to assess microendemicity and conservation risk in cave-dwelling arachnofauna. Conserv Genet (2024). https://doi.org/10.1007/s10592-024-01627-5