Length-Based Assessment of an Artisanal Albulid Fishery in the South Pacific: a Data-Limited Approach for Management and Conservation
Bibliographic record
Abstract
Abstract Data-limited fisheries assessment methods have great potential to help inform small island communities on the status of their fisheries resources. In this paper, we provide a length-based assessment of an artisanal fishery that primarily targets spawning aggregations of Shortjaw Bonefish Albula glossodonta at Anaa Atoll in the Tuamotu Archipelago of French Polynesia. We assessed the length-frequency distribution of the spawning stock across a 3-year period (2016–2018). During this time, male and female Shortjaw Bonefish were fully recruited to the fishery at age 4 and age 5, respectively. Fishing mortality was over two times the range of natural mortality for this species (i.e., 0.21–0.32), and based on these estimates of natural mortality, the annual spawning potential ratio of the population was between 7% and 20% across the sampling years. The majority of the catch was sexually mature, with 78, 95, and 95% of the annual female catch in 2016, 2017, and 2018, respectively, being equal to or greater than the length of first maturity (i.e., 48 cm FL). However, every fisheries indicator and biological reference point suggested that the fishery was overexploited and in need of management intervention. To this aim, the community of Anaa (1) established an Educational Managed Marine Area, which overlaps with the Shortjaw Bonefish migratory corridor adjacent to Tukuhora village and (2) instated a temporal rahui (a traditional conservation method) inside the Educational Managed Marine Area during the peak months of the spawning season.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".