Molecular Phylogenies of Leeches and Haemoparasites Infecting Freshwater Turtles in Aquatic Ecosystems of Northern Africa Suggest Phylogenetic Congruence between Placobdella costata Sensu Lato and Haemogregarina stepanowi Sensu Lato
Bibliographic record
Abstract
Haemogregarines are blood parasites with a life-cycle involving a vertebrate as the intermediate host and an invertebrate as the definitive host and vector. Extensive phylogenetic investigations based on 18S-rRNA gene sequences have shown that Haemogregarina stepanowi (Apicomplexa: Haemogregarinidae) is able to infest a large diversity of freshwater turtle species, including the European pond turtle Emys orbicularis, the Sicilian pond turtle Emys trinacris, the Caspian turtle Mauremys caspica, the Mediterranean pond turtle Mauremys leprosa, and the Western Caspian turtle Mauremys rivulata, among others. From the same molecular markers, H. stepanowi is further considered to be a complex of cryptic species predisposed to infect the same host species. While Placobdella costata is known to be the unique vector of H. stepanowi, it is only recently that independent lineages within P. costata have been illustrated—suggesting the presence of at least five unique leech species across Western Europe. The aims of our study were therefore to investigate from mitochondrial markers (COI) the genetic diversity within haemogregarines and leeches infecting freshwater turtles of the Maghreb, in order to identify processes of parasite speciation. We showed that H. stepanowi consists of at least five cryptic species in the Maghreb, while two Placobella species were identified in the same area. Although an Eastern–Western speciation pattern was apparent for both leeches and haemogregarines, we cannot make definitive conclusions regarding co-speciation patterns between parasites and vectors. However, we cannot reject the hypothesis of a very strict host–parasite specificity within leeches.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".