Differential patterns of connectivity in Western Pacific hydrothermal vent metapopulations: A comparison of biophysical and genetic models
Bibliographic record
Abstract
Abstract Hydrothermal ecosystems face threats from planned deep‐seabed mining activities, despite the fact that patterns of realized connectivity among vent‐associated populations and communities are still poorly understood. Since populations of vent endemic species depend on larval dispersal to maintain connectivity and resilience to habitat changes, effective conservation strategies for hydrothermal ecosystems should include assessments of metapopulation dynamics. In this study, we combined population genetic methods with biophysical models to assess strength and direction of gene flow within four species of the genus Alviniconcha (A. boucheti, A. kojimai, A. strummeri and A. hessleri) that are ecologically dominant taxa at Western Pacific hydrothermal vents. In contrast to predictions from dispersal models, among‐basin migration in A. boucheti occurred predominantly in an eastward direction, while populations within the North Fiji Basin were clearly structured despite the absence of oceanographic barriers. Dispersal models and genetic data were largely in agreement for the other Alviniconcha species, suggesting limited between‐basin migration for A. kojimai, lack of genetic structure in A. strummeri within the Lau Basin and restricted gene flow between northern and southern A. hessleri populations in the Mariana back‐arc as a result of oceanic current conditions. Our findings show that gene flow patterns in ecologically similar congeneric species can be remarkably different and surprisingly limited depending on environmental and evolutionary contexts. These results are relevant to regional conservation planning and to considerations of similar integrated analyses for any vent metapopulations under threat from seabed mining.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".