Nesting in close quarters: causes and benefits of high-density nesting behaviour in Painted Turtles (<i>Chrysemys picta</i>)
Bibliographic record
Abstract
Many oviparous reptiles nest in aggregations and with temporal synchrony. We hypothesized that these traits reflect attraction by conspecifics rather than limiting suitable habitat. We quantified whether Painted Turtles (Chrysemys picta (Schneider, 1783)) in Algonquin Park, Ontario, Canada, were nesting communally, identified cues females used to select nest sites, and tested whether hatching success was higher in spatially clustered nests. We found that nests were closer to one another than expected by chance (i.e., were clustered), but that individual nest-site selection was only weakly influenced by microhabitat characteristics. Survival of clustered nests (49%) was not significantly higher than that of solitary nests (39%). When turtle models were placed on the nesting embankment, females nested most often with the highest density of models. Given that reproductive lifespan is the major axis of fitness and that there was little benefit to nest survival in clustered nests, we suggest that clustering is related to females cueing to conspecific nests to expedite the nesting process and gain a good-quality nest site (chosen by the first nesting female in the cluster) while investing little energy in nest-site selection. This strategy may reduce time spent on land, thereby minimizing chances of dehydration, temperature stress, and adult depredation.
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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 | 0.001 | 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".