Marine litter in mangrove soils of Roatán, Western Caribbean: Abundance, sources, and ingestion by an American crocodile (Crocodylus acutus)
Bibliographic record
Abstract
Mangrove forests in insular regions are increasingly exposed to marine litter, even within designated protected areas. These ecosystems provide key ecological services but remain vulnerable to pollution via solid waste accumulation. Caribbean mangroves, in particular, are underrepresented in global assessments. This study provides the first baseline of macrolitter accumulation in mangroves on Roatán Island, within the Bay Islands National Marine Park, Honduras. We assessed: (1) the abundance and composition of macrolitter (≥5 cm) across four mangrove sites; (2) potential sources of macroplastics through brand and country-of-origin analysis of labeled items; and (3) the composition of litter ingested by an American crocodile ( Crocodylus acutus ) found near one site. A total of 3417 litter items were collected across 20 quadrats, with an average concentration of 6.83 items m −2 . Plastics dominated the litter, making up 98.7 % of all items. Only 2.4 % items had legible labels, most originating from Honduras and Guatemala. Among the subset of bottles with visible dates, the average age was 7 years, suggesting long-term retention within the mangrove environment. The deceased C. acutus found near one of the sites had ingested 62 litter items. A Principal Component Analysis revealed that the composition of ingested materials closely matched the litter profile of the nearby sampling site, indicating likely local exposure. These findings confirm that mangroves act as long-term sinks for plastic and highlight risks to mangrove fauna. The presence of banned and foreign-sourced litter underscores poor enforcement and transboundary pollution. Coordinated regional policies, improved waste management, and targeted cleanup in protected ecosystems are urgently needed.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 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".