Ancient lakes are hotspots of species diversity and pose challenges and opportunities for exploration of the dynamics of endemic diversification. Lake Baikal in Siberia, the oldest lake in the world, hosts a particularly rich crustacean fauna, including the largest known species flock of harpacticoid copepods with some 70 species. Here we focused on exploring the diversity and evolution within a single nominal species Harpacticella inopinata Sars, 1908 using molecular markers (mitochondrial COI, nuclear ITS1 and 28S rRNA) and a set of qualitative and quantitative morphological traits. Five major mitochondrial lineages were recognized, with model-corrected COI distances 0.20-0.37. A concordant pattern was seen in a nuclear data set, and qualitative morphological traits also distinguish a part of the lineages. All this suggests the presence of several hitherto unrecognized cryptic taxa within the baikalian H. inopinata, with long independent histories. The abundances, distributions, and inferred demographic histories were different among taxa. Two taxa, H. inopinata CE and H. inopinata CW, were widespread on the Eastern and Western coasts respectively, and largely allopatric. Patterns in mitochondrial variation, i. e. shallow star-like haplotype networks suggest these taxa have spread through the lake relatively recently. Three other taxa H. inopinata RE, RW, and RW2 instead were rare and had more localized distributions on either coast, but showed deeper intraspecies genealogies suggesting older regional presence. The rare taxa were often found in sympatry with the others, and on occasion introgressed by mtDNA from the common ones. The mitochondrial divergence between and within the H. inopinata lineages is still unexpectedly deep, suggesting an unusually high molecular rate. The recognition of true systematic diversity in evaluation and management of ecosystems is important in hotspots as everywhere else, while the translation of the diversity into a formal taxonomy remains a challenge.

Sanger sequencing of ITS1 rRNA gene. The detailed description of the methods are included in the published paper (https://doi.org/10.1002/ece3.11471)