Borderless Lizards: Unveiling Overlooked Records and the Expanding Invasion of Anolis sagrei in Ecuador
Bibliographic record
Abstract
We evaluated the global distribution of Anolis sagrei based on bibliographic records, GBIF, and iNaturalist data. Native to Cuba and the Bahamas, this lizard has spread across mainland America, particularly in the Caribbean, Central America, and parts of the U.S. It has also been introduced in Asia, and according to iNaturalist observations, it has been recorded in Israel, Canada, and northern South America. This species is especially abundant in the Caribbean and southeastern U.S., with high concentrations of records indicating a significant range expansion. In Ecuador, A. sagrei has been recorded along the coast and in the Amazon, with occurrences in Esmeraldas, Manabí, Guayas, Francisco de Orellana, and for the first time in Zamora Chinchipe (southern Amazon), specifically in El Pangui. The capture of 10 individuals confirmed their morphology, showing similarities with populations from Honduras and Cuba but differences in scalation and body size. In Ecuador, the fourth toe lamellae range from 29 to 33, consistent with those populations, while dorsal and ventral scales show variation (dorsal: 11–22, ventral: 10–25). Climate change favors its spread by enabling the colonization of new habitats. As an invasive species, it threatens local biodiversity, highlighting the need for monitoring and control in Amazonian Ecuador. An expanded abstract in Spanish is available, intended for local decision-makers.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".