Diurnal temperature variation impacts energetics but not reproductive effort across seasons in a temperate dung beetle
Bibliographic record
Abstract
Temperature varies on multiple timescales and ectotherms must adjust to these changes to survive. These adjustments may lead to energetic trade-offs between self-maintenance and reproductive investment. However, we know little about how diurnal and seasonal temperature changes impact energy allocation. Here we used a combination of empirical data and modeling of both thermoregulatory behaviors and body temperature to examine potential energetic trade-offs in the dung beetle Onthophagus taurus. Beginning in March 2020, universities and laboratories were officially closed due to the COVID-19 pandemic. We thus performed experiments at a private residence near Knoxville, Tennessee, USA, leveraging the heating, ventilation and air conditioning of the home to manipulate temperature and compare beetle responses to stable indoor temperatures versus variable outdoor temperatures. We collected O. taurus beetles in the early-, mid-, and late-breeding seasons to examine energetics and reproductive output in relation to diurnal and seasonal temperature fluctuations. We recorded the mass of field fresh beetles before and after a 24-h fast and used the resulting change in mass as a proxy for energetic costs of self-maintenance across seasons. To understand the impacts of diurnal fluctuations on energy allocation, we held beetles either indoors or outdoors for 14-day acclimation trials, fed them cow dung, and recorded mass change and reproductive output. Utilizing biophysical models, we integrated individual-level biophysical characteristics, microhabitat-specific performance, respirometry data, and thermoregulatory behaviors to predict temperature-induced changes to the allocation of energy toward survival and reproduction. During 24 h of outdoor fasting, we found that beetles experiencing reduced temperature variation lost more mass than those experiencing greater temperature variation, and this was not affected by season. By contrast, during the 14-day acclimation trials, we found that beetles experiencing reduced temperature variation (i.e., indoors) gained more mass than those experiencing greater temperature variation (i.e., outdoors). This effect may have been driven by shifts in the metabolism of the beetles during acclimation to increased temperature variation. Despite the negative relationship between temperature variation and energetic reserves, the only significant predictor of reproductive output was mean temperature. Taken together, we find that diurnal temperature fluctuations are important for driving energetics, but not reproductive output.
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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".