Genetic stock composition of marine bycatch reveals disproportional impacts on depleted river herring genetic stocks
Bibliographic record
Abstract
Bycatch of mid-trophic-level anadromous fishes that connect marine and freshwater ecosystems is a growing conservation concern. Anadromous alewife (Alosa pseudoharengus) and blueback herring (Alosa aestivalis) are important components of coastal freshwater and marine food webs, but have experienced dramatic declines in the abundances of spawning adults. Freshwater-focused restoration efforts have yielded few consistent signs of recovery, raising concerns that bycatch in Northwest Atlantic commercial fisheries may be negating these conservation actions. Using data from 15 microsatellites genotyped for baseline populations and bycatch, we conducted genetic stock identification to understand how bycatch was partitioned among previously identified regional genetic stocks. We then combined this information with fishery observer data to estimate genetic stock-specific bycatch mortality for the southern New England Atlantic herring fishery (2012–2013). Bycatch overall, but especially in the Atlantic herring fishery, was disproportionately assigned to the most severely depleted genetic stocks (alewife southern New England stock — 70% of assignments; blueback herring mid-Atlantic stock — 78% of assignments). These genetic stocks overlap in the region surrounding Long Island Sound, suggesting that bycatch taken from this area in recent years may be negatively impacting recovery efforts in this region. Our study suggests that mitigating bycatch on the southern New England fishing grounds may benefit recovery efforts for alewife and blueback herring genetic stocks that have experienced the greatest declines in spawning adult abundances.
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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".