Lessons from an eradication under multiple constraints of an island rat population of record density
Bibliographic record
Abstract
Invasive rats threaten island biodiversity, disrupting ecosystems and endangering native species. Although rat eradication has succeeded on many islands, tropical islands present unique management challenges. Strict regulations and financial constraints on some tropical islands further limit proven eradication methods, complicating rodent management. We applied a real-time active adaptive management approach that provided a cautious, cost-efficient, and scientifically grounded pathway to rat eradication, while adhering to strict environmental regulations, on Ilha do Meio, Brazil. The cost was US$3300 per hectare, and the management actions were grounded in close interdisciplinary collaboration. We applied rodenticide (brodifacoum), monitored the rat population, and made iterative management adjustments. The rat overpopulation was eradicated within 5 months, and population increases were observed early on in the threatened masked booby (Sula dactylatra), and the endemic Noronha elaenia (Elaenia ridleyana) and Noronha skink (Trachylepis atlantica). Despite logistical constraints, our approach proved effective and cost-efficient, marking its first application in a biological system. Our findings highlight the value of innovation, close interdisciplinary collaboration, and adaptive decision-making when the application of best-practice methods is constrained.
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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".