Investigation of didemnid species along the Turkish coastlines utilizing genetic, environmental, and morphological data

2026-1-16
Bekdemir, İrem
The Didemnidae family is the most speciose and taxonomically challenging group within the class Ascidiacea (Tunicata), because of the small size of zooids and the lack of diagnostic external characters. This thesis presents the first comprehensive and integrative assessment of the biogeographic distribution and diversity of Didemnidae family along the Turkish coastline. An integrative approach combining morphological analyses (including spicule morphology) with molecular analyses based on the mitochondrial cytochrome c oxidase subunit I (COI) gene was applied, together with population genetic analyses of Didemnum pseudovexillum. A total of 524 samples were collected from 20 stations across the Black Sea, Marmara Sea, Aegean Sea, and Mediterranean Sea. Species delimitation analyses using ASAP, PTP, and Bayesian phylogenetic inference identified 22 species-level lineages, of which 17 represent putative new species for the region. Additionally, four known species were genetically recorded, three of them for the first time in Turkish waters. Genetic distance analyses were conducted to evaluate interspecific divergence, and neutrality tests were applied to assess the phylogeographic structure of D. pseudovexillum. No didemnids were recorded from the Black Sea, whereas the Mediterranean Sea showed the highest species richness. A positive relationship was detected between species richness and salinity. Phylogeographic analyses of D. pseudovexillum suggest long-term demographic stability. Southeastern populations showed significant genetic structuring, whereas western populations exhibited higher connectivity. Overall, the results highlight the importance of integrative taxonomic approaches for accurately documenting Didemnidae biodiversity.
Citation Formats
İ. Bekdemir, “Investigation of didemnid species along the Turkish coastlines utilizing genetic, environmental, and morphological data,” M.S. - Master of Science, Middle East Technical University, 2026.