Selectivity matters: Rules of thumb for management of plate‐sized, sex‐changing fish in the live reef food fish trade
Bibliographic record
Abstract
Abstract Effective management of fisheries depends on the selectivity of different fishing methods, control of fishing effort and the life history and mating system of the target species. For sex‐changing species, it is unclear how the truncation of age‐structure or selection of specific size or age classes (by fishing for specific markets) affects population dynamics. We specifically address the consequences of plate‐sized selectivity, whereby submature, “plate‐sized” fish are preferred in the live reef food fish trade. We use an age‐structured model to investigate the decline and recovery of populations fished with three different selectivity scenarios (asymptotic, dome‐shaped and plate‐sized) applied to two sexual systems (female‐first hermaphroditism and gonochorism). We parameterized our model with life‐history data from Brown‐marbled grouper ( Epinephelus fuscoguttatus ) and Napoleon fish ( Cheilinus undulatus ). “Plate‐sized” selectivity had the greatest negative effect on population trajectories, assuming accumulated fishing effort across ages was equal, while the relative effect of fishing on biomass was greatest with low natural mortality. Fishing such sex‐changing species before maturation decreased egg production (and the spawning potential ratio) in two ways: average individual size decreased and, assuming plasticity, females became males at a smaller size. Somatic growth rate affected biomass if selectivity was based on size at age because in slow growers, a smaller proportion of total biomass was vulnerable to fishing. We recommend fisheries avoid taking individuals near their maturation age, regardless of mating system, unless catch is tightly controlled. We also discuss the implications of fishing post‐settlement individuals on population dynamics and offer practical management recommendations.
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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 | 0.013 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".