Diversity and biogeography of Mediterranean freshwater blennies (Blenniidae, Salaria)
Bibliographic record
Abstract
Aim: In the Mediterranean Biodiversity Hotspot freshwater fishes are key biogeographical indicators while their habitats are vulnerable to ongoing anthropogenic pressures. The freshwater blenny is a widespread endemic taxon in this area. However, our understanding of the overall diversity of specific populations and their phylogenetic relationships is sparse. Thus, we aim to investigate the genetic diversity, infer relationships among sampled populations related to major paleoenvironmental changes and suggest insights for future research and conservation targets. Location: Mediterranean Basin Methods: We studied 171 Salaria specimens from 51 rivers and lakes, and from 13 countries surrounding the Mediterranean Sea. For assessing the phylogenetic relationships among different locations, we used mtDNA d-loop and Intron S7 sequences. Furthermore, we inferred absolute divergence times as well as demographic changes using secondary calibrations and investigated the diversity within major lineages using haplotype networks as well as several geographical and genetic clustering methods. Results: We found eight well differentiated lineages, each of which being confined to a particular geographic region. The onset of the freshwater blenny radiation was dated around the Messinian salinity crisis. Further differentiation happened during the Plio- and Pleistocene with signatures of population expansion after the Last Glacial Maximum in some of the main lineages. Main Conclusions: Due to their unusual widespread distribution, the freshwater blennies represent an excellent model for studying phylogeographic structure across the Mediterranean basin biodiversity hotspot. The extant diversity and distribution of the freshwater Salaria species mirrors
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".