Habitat selection in two sympatric Chinese skinks, <i>Eumeces elegans</i> and <i>Sphenomorphus indicus</i>: do thermal preferences matter?
Bibliographic record
Abstract
We studied the habitat selection and thermal biology of two sympatric Chinese skinks ( Eumeces elegans Boulenger, 1887 and Sphenomorphus indicus (Schmidt, 1928)) to test the effect of thermal preference on habitat partitioning. We measured thermal and structural attributes of the microhabitats occupied by these two skink species, as well as their field body temperatures and activity patterns. We then quantified the preferred body temperatures of these species in a thermal gradient. Compared with S. indicus, E. elegans occupied microhabitats with fewer trees, more rocks, and higher ambient temperatures. Active S. indicus were mainly found in the morning, whereas active E. elegans were found at noon. The thermal environment of the microhabitats at these two periods correlated with the skinks’ thermal preferences. Preferred temperatures of E. elegans were significantly higher than those of S. indicus. These results support (i) the hypothesis that habitat partitioning between ectotherms is related to interspecific differences in thermal requirements; (ii) the labile hypothesis that describes the adaptability of thermal physiology, because the two sympatric skinks, which select different thermal environments, differed in thermal physiology; and (iii) the cold-climate hypothesis that explains the evolution of viviparity, because viviparous S. indicus occupy colder habitats than do oviparous E. elegans.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".