Three decades of longlining in Bimini, Bahamas, reveals long‐term trends in lemon shark <i>Negaprion brevirostris</i> (Carcharhinidae) catch per unit effort
Bibliographic record
Abstract
In Bimini, Bahamas, the consistent employment of longlines, beginning in 1982, provided a rare opportunity to explore population trends for large resident sharks. This study assessed three shallow water longline survey periods at this location; 1982-1989, 1992-2002 and 2003-2014, with the aim of determining trends in annual catch per unit effort (CPUE) for an IUCN listed near-threatened species, the lemon shark Negaprion brevirostris. A general additive model (GAM) was used to analyse the non-linear annual CPUE values over the entire 32-year research period. The GAM displayed high variability of annual CPUE, with a peak value of 0·026 N. brevirostris per hook day (hooks day(-1) ) in 2000. The temporal pattern of CPUE indicated an abundance trend with a complete cycle, from trough to trough, occurring over a period of approximately 18 years. The 1982-1989 survey period saw the highest proportion of mature individuals (19·8%) and the smallest average pre-caudal length (LPC ; 124·8 cm). The 1992-2002 survey period had the highest average annual CPUE (0·018 hooks day(-1) ), while the 2003-2014 research period saw largest average LPC size (134·8 cm) and the lowest average CPUE values (0·009 hooks day(-1) ) of the entire research period. The long-term trend identified in this study provides a baseline for future assessment.
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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 | 0.000 |
| 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 | 0.000 |
| 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".