Impact of recreational power boating on two populations of northern map turtles (<i>Graptemys geographica</i>)
Bibliographic record
Abstract
Abstract Recreational power boating is growing in popularity in North America. This activity is known to have lethal and sub‐lethal effects on aquatic wildlife and freshwater turtles may be particularly sensitive to this activity. This study reports on patterns of traumatic injuries inflicted by powerboat propellers to northern map turtles ( Graptemys geographica ) from two sites differing in boat traffic intensity in Ontario, Canada. The relative vulnerability of turtles was assessed, in light of seasonal patterns in boat traffic, as a function of sex‐ and age‐specific movement patterns, habitat use, and basking behaviour obtained by radio‐telemetry. Population viability analyses (PVA) were also conducted to evaluate the potential demographic consequences of mortality induced by powerboats. The prevalence of propeller injuries was two to nine times higher in adult females than in adult males and juvenile females. Patterns of movement, habitat use, and aquatic basking indicated that adult females are more exposed to collisions with boats. PVA showed that boat‐induced mortality in adult females could lead to rapid population extinction if the risk of mortality when hit by a boat is greater than 10%. The results of this study showed that recreational power boating is a serious threat to northern map turtles, even under moderate boat traffic. The need to adopt measures restricting boat traffic in areas important to turtles is discussed. Copyright © 2009 John Wiley & Sons, Ltd.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".