The impact of ectoparasitism on thermoregulation in Yarrow’s Spiny Lizards (<i>Sceloporus jarrovii</i>)
Bibliographic record
Abstract
Parasites are ubiquitous and can have large impacts on the fitness of their hosts. The effects of ectoparasites on physiology, behaviour, and immune function suggest that they could be part of the factors which impact thermoregulation. We tested the hypothesis that ectoparasites impact thermoregulation in Yarrow’s Spiny Lizards (Sceloporus jarrovii Cope in Yarrow, 1875) living along an elevational gradient. We predicted a positive association between ectoparasite load and body temperature (Tb), and a negative association between ectoparasite load and effectiveness of thermoregulation (de – db index). We also predicted that the impacts of ectoparasites would be greatest at high elevation where thermal quality of the environment is low because the costs of thermoregulation increase with elevation and these costs can impact thermal immune responses. We found a significant association between the number of chiggers (Trombiculoidea) harboured by lizards and Tb that depended on elevation, but no association between ectoparasite load and de – db index. The mean chigger infection rate was associated with a ΔTb of +0.18 °C at low elevation (consistent with fever) and of –1.07 °C at high elevation (consistent with hypothermia). These findings suggest that parasitism by chiggers impacts lizard Tb in a way that depends on environmental thermal quality.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".