Substantial impacts of subsistence fishing on the population status of an Endangered reef predator at a remote coral atoll
Bibliographic record
Abstract
Napoleon wrasse Cheilinus undulatus has declined drastically throughout most of its range, owing, in large part, to overexploitation. In Anaa, French Polynesia, the species is harvested as part of the subsistence catch by fishers using rockpile traps, spearguns, handmade harpoons, and baited handlines. We sampled 70 Napoleon wrasse captured by artisanal fishers of Anaa between 2015 and 2018 to assess the status of this population, and we applied data-poor fisheries models to assess the stock status of this iconic reef predator. The species was determined to be overexploited at a rate of 0.82 based on values of natural (0.14; Hoenig method) and fishing (0.58; difference of total and natural mortality) mortality as components of total mortality (0.72; Beverton-Holt estimation). The left-skewed length distribution (mean = 36 ± 13 cm SL) suggested an under-representation of large adults in the population, which would predominantly be terminal males in this sequentially hermaphroditic protogynous fish. This was not considered to be reflective of poor selectivity by gear types but could have arisen as a consequence of unequal accessibility of exceptionally deep habitats off the reef shelf. According to the length-based spawning potential ratio, Napoleon wrasse is fully recruited to this fishery prior to 50% maturation and 50% sex changing, with the spawning potential ratio estimated to be 6%, a characteristic of a highly overexploited species. Fishers were unselective towards size classes and harvest whatever they catch. Our analysis shows that even undirected, non-selective subsistence fishing yields overexploitation of this Endangered species.
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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 | 0.000 | 0.000 |
| 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".