Nest-Site Selection by Wood Turtles (<i>Glyptemys insculpta</i>) in a Thermally Limited Environment
Bibliographic record
Abstract
In oviparous species that lack parental care, fitness of the mother depends on the selection of a high-quality nest site, as mothers do not compensate for poor incubation environment post-hatching. Near the northern range limit of Glyptemys insculpta (Wood Turtle), short summers and cool temperatures may be factors that limit population persistence because potential nest sites may not provide adequate conditions for successful egg incubation in some years. We quantified nest-site selection by examining soil temperature and substrate composition of real Wood Turtle nests (n = 5) and constructed false nests. False nests comprised two treatments: negative-test false nests (n = 5) constructed on beaches not used by females, and positive-test false nests (n = 5) constructed on beaches used by females but in microsites not chosen by females. Temperature was measured as total thermal units and mean temperature during the diel cycle. Soil composition was quantified using moisture content, organic content, and grain-size distribution. Soil temperature was the most important factor in nest-site selection. Temperatures and total thermal units were significantly higher and more variable in real nests than in false nests, except during the night. Soil composition was not significantly different among treatments. Grain sizes ranged from fine to gravel, and real nests contained mainly (58% to 96%) medium sand or larger grains. There was little variation in soil moisture among real nests, suggesting that females were choosing specific humidity conditions for nesting. Our findings can be directly applied to protecting nesting beaches for Wood Turtles, which are considered a species at risk.
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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) | 0.001 | 0.001 |
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".