Big runs of little fish: first estimates of run size and exploitation in an amphidromous postlarvae fishery
Bibliographic record
Abstract
Amphidromous postlarvae fisheries (APFs) constitute a globally widespread and distinctive class of fishery that is largely unknown to fisheries science. APFs harvest ocean-to-river migrating fishes at smaller sizes and younger ages than any other class of fishery. No quantitative estimates of run size and exploitation exist, which are needed to evaluate APF sustainability. Migrating amphidromous fishes are vectors of marine nutrients to estuaries and rivers, and run size quantification is needed to reveal the magnitude of this ecosystem function. We present a novel adaptation of trapezoidal area under the curve methods, which we apply in a Caribbean case study to yield the first simultaneous estimates of an APF run size and harvest. Run size estimates ranged 7.3–9.4 million postlarvae (926–1184 kg), and exploitation estimates (5.8%–7.0%) indicated low harvest in the Río Grande de Arecibo, Puerto Rico. Our representative run size estimates reveal that amphidromous postlarvae transport hundreds of kilograms of biomass per month to an estuary and river, the first empirical evidence that amphidromous migrations are large-magnitude material subsidies of lotic ecosystems.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".