How do shellfisheries influence genetic connectivity in metapopulations? A modeling study examining the role of lower size limits in oyster fisheries
Bibliographic record
Abstract
Fisheries can potentially alter evolutionary processes such as genetic connectivity and lead to genotypic changes in stocks. Using an individual-based metapopulation genetics model, we examined the possible influence of oyster (Crassostrea virginica) fisheries on genetic connectivity. We simulated a range of realistic fishing pressures, with and without a minimum size limit (limit = 63.5 mm), over a range of fishing scenarios including single-area and stock-wide fisheries. Movement of a neutral marker gene provided an indicator of gene transfer between populations. Simulations showed that fishing may alter genetic connectivity. Increasing fishing pressure tended to decrease potential for fished populations to export genes in fisheries with and without size limits. On average, when instantaneous fishing mortality, location, and time period are held constant, fishing unrestricted by size results in a 3.5% lower allele export. Depression of the spawning potential ratio by unrestricted fishing relative to size-limited fishing argues for more conservative fishing mortality targets for unrestricted fisheries. These results demonstrate the importance of considering the influence of fisheries on source–sink dynamics in future management of marine populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".