Cues used by predators to detect freshwater turtle nests may persist late into incubation
Bibliographic record
Abstract
Previous studies have found that turtle nest depredation is concentrated immediately post-oviposition, likely because cues alerting predators to nest presence are most obvious during this time. In Algonquin Provincial Park, Ontario, we examined the frequency of nest depredation during the incubation period for Snapping Turtles (Chelydra serpentina [Linnaeus, 1758]) and Midland Painted Turtles (Chrysemys picta marginata [Agassiz, 1857]). Contrary to most past findings, nest depredation occurred throughout the incubation period for both species. In fact, 83% and 86% of depredation interactions with Snapping and Painted Turtle nests, respectively, occurred more than a week after oviposition at our study site. Peaks in nest depredation (weeks with ≥10% nest depredation) occurred late in incubation and may have coincided with hatching. Trail cameras deployed at four nesting sites revealed six predator species interacting with nests. The presence of predators at nest sites increased late in the incubation period indicating a persistence or renewal (from hatching) of cues; additional research is necessary to determine the nature of these cues. These findings have implications for both research and turtle conservation. Further research should examine the relationship between temporal changes in predator species’ density and patterns of nest depredation. Additionally, in areas where protective nest caging is used as a species recovery action, it may be important to ensure that cages remain in place throughout the incubation period until emergence of hatchlings.
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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 | 0.001 |
| 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) | 0.001 | 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".