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Oribatid mites (Acari, Oribatida) are a large group of soil animals, with small body sizes and complex morphological structures. At present, oribatid mite species identification is essentially based on morphological characters. In this study, we collected 124 specimens of oribatid mites belonging to 110 species of 72 genera in Russia, and extracted their genomic DNA subsequently. In order to investigate whether the molecular data (DNA-barcoding marker, COI gene) and morphological classification results are consistent, we used three methods, ASAP, ABGD and GMYC, to delimit species, and calculate a maximum likelihood tree. The results indicate that COI gene fragments can be effectively used for species delimitation. There are some cryptic species identified in oribatid mites, which do not have distinct morphological differences, but diverge considerably in molecular data. Meanwhile, some formerly unidentified species could be identified through molecular means. The study enriches the molecular data of oribatid mites worldwide and provides the basis for more detailed taxonomic studies of oribatid mites in Russia. In the future, more analyses and mining of molecular data, combined with morphological analyses, will help to reveal and further understand the phylogenetic relationships of Oribatida. [ABSTRACT FROM AUTHOR]

Water mites (Hydrachnidia) are good model organisms for the assessment and long-term monitoring of the biological impacts of natural and human-induced environmental changes in freshwater ecosystems, including those related to global climate change. However, monitoring programs using water mites as bioindicators may be impeded by difficulties associated with species identification. Here we integrate conventional morphology, DNA sequence data (using the COX1 barcoding locus) and extensive voucher photo documentation to create and validate a tool for accurate species identification of water mites in Western Siberia (including a dedicated reference climate monitoring and research site). Using this approach, we detected a total of 95 species, of which, one was a conventional new species; 14 taxa were cryptic species having large among-species COX1 K2P distances but lacking any apparent morphological differences. Our a priori species delimitation was successfully validated a posteriori. An automatic species delimitation algorithm (ASAP) identified exactly the same set of 95 species, with a species delimitation threshold of 6.1%. This result agrees with previous works suggesting a large threshold of 5.6–6.0% for water mites, but contrasts with the BOLD approach which uses a much lower threshold to identify BINs (1%). Furthermore, by comparing our identified sequences with GenBank data, we expanded known geographic ranges of several water mite species. Using extensive GenBank data on mites in Canadian waters, four species were detected to be Holarctic rather than Palaearctic as thought previously (Lebertia obscura, Limnesia undulatoides, Oxus nodigerus and Arrenurus papillator). Four species, Lebertia obscura, Torrenticola brevirostris, Hygrobates limnocrenicus and Unionicola parvipora, were recorded for the first time in Russia. We provide an annotated species checklist reporting the distribution, ecology, bioindiocation potential, and COX1 barcode sequence data along with high-resolution photographs of each DNA voucher. Future ecological and biodiversity studies will benefit from using molecular tools for accurate identification of useful mesofaunal bioindicator organisms, such as water mites. [ABSTRACT FROM AUTHOR]