Aerial Survey as a Tool to Estimate Abundance and Describe Distribution of a Carcharhinid Species, the Lemon Shark,<i>Negaprion brevirostris</i>
Bibliographic record
Abstract
Aerial survey provides an important tool to assess the abundance of both terrestrial and marine vertebrates. To date, limited work has tested the effectiveness of this technique to estimate the abundance of smaller shark species. In Bimini, Bahamas, the lemon shark ( Negaprion brevirostris ) shows high site fidelity to a shallow sandy lagoon, providing an ideal test species to determine the effectiveness of localised aerial survey techniques for a Carcharhinid species in shallow subtropical waters. Between September 2007 and September 2008, visual surveys were conducted from light aircraft following defined transects ranging in length between 8.8 and 4.4 km. Count results were corrected for “availability”, “perception”, and “survey intensity” to provide unbiased abundance estimates. The abundance of lemon sharks was greatest in the central area of the lagoon during high tide, with a change in abundance distribution to the east and western regions of the lagoon with low tide. Mean abundance of sharks was estimated at 49 (±8.6) individuals, and monthly abundance was significantly positively correlated with mean water temperature. The successful implementation of the aerial survey technique highlighted the potential of further employment for shark abundance assessments in shallow coastal marine environments.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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 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".