Network analysis of the endemic spotted gully shark <i>Triakis megalopterus</i> reveals spatial vulnerability to exploitation in the Western Cape, South Africa
Bibliographic record
Abstract
The spotted gully shark Triakis megalopterus (Triakidae) is a mesopredatory species endemic to southern Africa. It is currently listed as Least Concern on the IUCN Red List in accordance with an estimated increase in population size, general release by recreational linefishers and incidental catches in the commercial linefisheries. Previous research suggests this species to be resident, and as such it is likely to receive protection in coastal marine protected areas (MPAs). However, its ecology and movement behaviour remain poorly studied. This study employed acoustic telemetry to provide information on the species’ movements along the coast of the Western Cape Province, South Africa. We used network analyses to investigate movement randomness, associations between individuals, sexual segregation, and the effectiveness of MPAs. Our findings reveal nonrandom movements as well as patterns of co-occurrence between individuals. Spatial network analysis suggested sexual segregation, because areas of high use (Walker Bay and De Hoop) differed between males and females. Co-occurrences were observed exclusively in Walker Bay, chiefly between males, with no co-occurrence found between females. The tagged spotted gully sharks were not detected extensively within existing MPA boundaries, though there was no significant difference between their movements inside and outside protected areas for both sexes.
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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 | 0.002 | 0.001 |
| 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".