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 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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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".