The leatherback turtle (Dermochelys coriacea) and plastics in the Northwest Atlantic ocean: A hazard assessment
Bibliographic record
Abstract
Atlantic leatherback turtles are faced with multiple threats, such as ship strikes, pollution and predation, throughout their annual migratory routes in the Northwest (NW) Atlantic. The risks associated with encounters with floating and submerged plastic debris are currently unknown. This study is a hazard assessment of plastics for this turtle's sub-population, using 2010-2019 data from the national Great Canadian Shoreline Cleanup (GSCS) program, therefore potential exposure, and published evidence on the interactions of plastics and leatherbacks, hence potential effects. The type of plastic items and their abundance along shorelines of three Atlantic Provinces - Nova Scotia (NS), Prince Edward Island (PEI), Newfoundland and Labrador (NL) - were evaluated and compared to plastic items known to interact with leatherbacks. During the 2010-2019 period, a total of 220,590 plastic items were collected from 578 sites, representing 1264 km of shoreline. Plastic bags and rope are in the top ten most common items found on shorelines of NS, PEI, and NL. Pot gear and trap nets are in the top ten for PEI and are the 14th most common plastic item found on all shorelines. Cigarette debris is also commonly found. From the literature, plastic bags, pot gear and trap nets, and rope are known to adversely affect leatherbacks. Assuming that a large proportion of the shoreline debris comes in from the sea, after being in coastal waters for unknown periods, the study shows that such items pose a hazard to leatherbacks through ingestion and entanglement, based on published studies. Evidence is now needed on actual exposure at sea to the most common items to establish the ecological risk of plastics to these turtles in NW Atlantic waters.
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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".