Life‐history, exploitation and extinction risk of the data‐poor Baraka's whipray (Maculabatis ambigua) in small‐scale tropical fisheries
Bibliographic record
Abstract
Abstract The Baraka's whipray ( Maculabatis ambigua ) is a major constituent of small‐scale fisheries catch in the south‐western Indian Ocean. Despite this, little is known of its life‐history or exploitation status. We provide the first estimates of crucial life‐history parameters and the maximum intrinsic population growth rate r max , using specimens collected from small‐scale fisheries landings in Kenya, Zanzibar and Madagascar (with northern Madagascar representing a range extension for this species). We assess the relative risk of overexploitation by combining r max with estimates of total Z , fishing F , and natural M mortality, and an estimate of the exploitation ratio E . The data indicate that Baraka's whipray is a medium‐sized, fast‐growing, early maturing species, with a relatively long lifespan. This results in a high r max relative to many other elasmobranchs, which when combined with estimates of F suggests that the species is not at imminent risk of extinction. Yet, estimates of exploitation ratio E indicate likely overfishing for the species, with full recruitment to the fishery being post‐maturation and exploitation occurring across a broad range of age and size classes. Thus, Baraka's whipray is unlikely to be biologically sustainable in the face of current fisheries pressures. This paper makes an important contribution to filling the gap in available data and is a step towards developing evidence‐based fisheries management for this species. Further, it demonstrates a simple and widely applicable framework for assessment of data‐poor elasmobranch exploitation status and extinction risk.
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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".