Partial support for food availability and thermal quality as drivers of density and area used in Yarrow’s Spiny Lizards (<i>Sceloporus jarrovii</i>)
Bibliographic record
Abstract
Contrary to traditional models, habitat selection in ectotherms may be chiefly based on a habitat’s thermal properties rather than its food availability, due to their physiological dependence on environmental temperature. We tested two hypotheses: that microhabitat use in ectotherms is driven by food availability and that it is driven by thermoregulatory requirements. We predicted that the density of lizards would increase and the mean area used would decrease with the natural arthropod (food) availability (or thermal quality) of a plot, as well as after experimentally increasing plot arthropod availability (or thermal quality). We established two plots in each of four treatments (food-supplemented, shaded, food-supplemented and shaded, and control) on a talus slope in Arizona, USA. We measured the density and area used in Yarrow’s Spiny Lizards (Sceloporus jarrovii Cope in Yarrow, 1875) before and after manipulations, and determined whether lizard density and area used were related to natural arthropod availability or thermal quality at the surface and in retreat sites. Density and area used were unaffected by the manipulations, but both increased with natural arthropod availability and decreased with higher thermal quality in retreat sites. These results provide partial support for both food availability and thermal quality as drivers of density and microhabitat use in S. jarrovii.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".