Marine hotspots of activity inform protection of a threatened community of pelagic species in a large oceanic jurisdiction
Bibliographic record
Abstract
Abstract Remote oceanic islands harbour unique biodiversity, especially of species that rely on the marine trophic resources around their breeding islands. Identifying marine areas used by such species is essential to manage and limit processes that threaten these species. The Tristan da Cunha territory in the South Atlantic Ocean hosts several endemic and globally threatened seabirds, and pinnipeds; how they use the waters surrounding the islands must be considered when planning commercial activities. To inform marine management in the Tristan da Cunha Exclusive Economic Zone (EEZ), we identified statistically significant areas of concentrated activity by collating animal tracking data from nine seabirds and one marine mammal. We first calculated the time that breeding adults of the tracked species spent in 10 × 10 km cells within the EEZ, for each of four seasons to account for temporal variability in space use. By applying a spatial aggregation statistic over these grids for each season, we detected areas that are used more than expected by chance. Most of the activity hotspots were either within 100 km of breeding colonies or were associated with seamounts, being spatially constant across several seasons. Our simple and effective approach highlights important areas for pelagic biodiversity that will benefit conservation planning and marine management strategies.
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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 | 0.000 | 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) | 0.000 | 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".