Preliminary insights into manta ray (Mobula alfredi and M. birostris) population demographics and distribution in South Africa
Bibliographic record
Abstract
Abstract Both the reef manta ray, Mobula alfredi and oceanic manta ray M. birostris , are repeatedly observed in South Africa, yet little is known about the distributions of either species. In this study, we collated citizen science observations since 2003 to reveal six areas in the KwaZulu-Natal (KZN) and Eastern Cape provinces, where manta rays have been sighted across multiple years. Using their unique ventral spot patterning, 184 individuals were photo-identified, comprising 139 M. alfredi and 45 M. birostris . Most of the photo-identified M. alfredi individuals were encountered in the iSimangaliso Wetland Park (IWP) in KZN (89%; n = 119) and for M. birostris , Aliwal Shoal (48%; n = 22). We identified 32 new transboundary records of 28 M. alfredi also photographed in the Inhambane Province, Mozambique, demonstrating connectivity, specifically to Závora ( n = 27). One M. alfredi individual traveled multiple times between the IWP and Závora, Mozambique, totaling 1305 km, and another individual traveled from the Pondoland MPA to the IWP in South Africa, a distance of over 600 km. Further, we extend the southern range for M. alfredi in Africa by over 500 km from Mdumbi Beach to Port Ngqura, Eastern Cape. These collective findings represent South Africa’s first in-water assessment of manta ray aggregations, showing the IWP in particular to be a critical habitat for M. alfredi . Further, the movements documented here suggest the M. alfredi population in southern Africa to be one of the most mobile globally. We hope the baseline data provided here will drive increased research and transboundary management for M. alfredi and M. birostris along the KZN and Eastern Cape coastlines.
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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 | 0.001 |
| 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) | 0.002 | 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".