Distribution and breeding numbers of a recently split species, the West African Crested Tern <i>Thalasseus albididorsalis</i>
Bibliographic record
Abstract
This study investigated the distribution, numbers and conservation threats of the West African Crested Tern, which was recently elevated to full species after it was split from the Royal Tern with an American and African subspecies. In the period 1998–2019, a total of 13 West African coastal islands were identified as breeding localities, stretching from Mauritania to Guinea. All the islands are isolated, usually sandy and subject to erosion. There was great yearly variation in the numbers of breeding pairs within and between sites. A complete census of all breeding locations in 2015 and 2019 resulted in estimates of 79 000 and 77 000 pairs, respectively. The threats identified are predation, human disturbance, nest flooding and loss of breeding habitat as a result of coastal erosion. Predation of eggs and chicks by Sacred Ibises and especially Great White Pelicans may heavily impact on the species’ breeding output. Human disturbance is slight because most of the breeding islands are within protected areas. Flooding of nests has increasingly been observed in recent years, occurring at nine of 11 islands occupied by the terns in 2015. Most islands are subject to erosion, which has resulted in substantial loss of suitable breeding habitat over the 22-year study period. Two important islands have become completely unsuitable. We conclude that West African Crested Terns have an uncertain future. Food shortage resulting from industrial fishing is suspected, and the effects of climate change might negatively impact on habitat suitability and food availability. Monitoring of the total population at three-year intervals is recommended.
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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 | 0.000 |
| 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) | 0.001 | 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".