Population structure and connectivity in Indo-Pacific deep-sea mussels of the Bathymodiolus septemdierum complex
Bibliographic record
Abstract
Abstract Current pressures to mine polymetallic sulfide deposits pose threats to the animal communities found at deep-sea hydrothermal vents. Management plans aimed at preserving these unusual communities require knowledge of historical and contemporary forces that shaped the distributions and connectivity of associated species. As most vent research has focused on the eastern Pacific and mid-Atlantic ridge systems less is known about Indo-Pacific vents, where mineral extraction activities are imminent. Deep-sea mussels (Bivalvia: Mytilidae) of the genus Bathymodiolus include the morphotypic species B. septemdierum , B. brevior , B. marisindicus , and B. elongatus which are among the dominant vent taxa in western Pacific back-arc basins and the Central Indian Ridge. To assess their interpopulational relationships, we examined multilocus genotypes based on DNA sequences from four nuclear and four mitochondrial genes, and allozyme variation encoded by eleven genes. Bayesian assignment methods grouped mussels from seven widespread western Pacific localities into a single cluster, whereas the Indian Ocean mussels were clearly divergent. Thus, we designate two regional metapopulations. Notably, contemporary migration rates among all sites appeared to be low despite limited population differentiation, which highlights the necessity of obtaining realistic data on recovery times and fine-scale population structure to develop and manage conservation units effectively. Future studies using population genomic methods to address these issues in a range of species will help to inform management plans aimed at mitigating potential impacts of deep-sea mining in the Indo-Pacific region.
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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 | 0.001 | 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".