Thermal quality influences habitat selection at multiple spatial scales in milksnakes
Why this work is in the frame
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Bibliographic record
Abstract
Factors influencing habitat selection may be scale dependent, leading to different selection patterns at different spatial scales. By limiting habitat-selection studies to a single scale, important selection patterns could be missed. Despite this danger, many studies investigate habitat selection at a single scale, often ignoring macro-habitat selection: the selection of a home range within the study area. We investigated macro- and micro-habitat selection in milksnakes. Because of the importance of thermoregulation to ectotherms, we predicted that snakes would select habitats of high thermal quality at both micro- and macro-habitat scales. In 2003–2004, we located 25 individuals 890 times and characterized the habitat in detail at 279 locations used by milksnakes and at 279 paired random locations. Open habitats (fields, rocky outcrops, marshes) and edges have environmental temperatures that deviate less from the preferred body temperature range of milksnakes and offer characteristics that facilitate thermoregulation compared to forest. At the macro- and micro-habitat scales, milksnakes preferred habitats of high thermal quality: they used fields and rocky outcrops more than forests. Milksnakes also preferred edges at both scales. In addition, milksnakes preferred locations with open canopy and many rocks at the micro-habitat scale. These results support the notion that thermal quality influences habitat use in ectotherms and strengthen the idea that habitat-use studies should be conducted at more than one spatial scale to gain a complete understanding of the factors affecting selection.
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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 it