Effects of environmental warming during early life history on libellulid odonates
Bibliographic record
Abstract
Climate warming affects ectotherms globally, yet we know little regarding the variability in species’ responses to warming, particularly in early life stages. Additionally, intraspecific variation in response to warming is understudied but may determine species’ resilience to warming. To assess how temperature affects egg development rate in co-occurring dragonfly species, we manipulated temperature (range: 22–31 °C) and measured time to hatching. Warming decreased egg development time across all species, indicating that while climate warming will advance hatching phenology, maintained synchrony in hatching order will likely not affect species interactions. Our second experiment examined early life-history responses to warming in the dot-tailed whiteface (Leucorrhinia intacta (Hagen, 1861)) dragonfly. We measured time to hatching, hatchling size, growth rate, and survival at four temperatures (23–30 °C), including a treatment with increased thermal variation. Warming resulted in smaller hatchlings with increased growth and mortality rates, whereas higher thermal variation did not have effects different from those of warming alone. We observed significant intraspecific variation in the responses to warming in both egg development time and hatchling size and this variation was correlated with date of oviposition. High levels of intraspecific variation may be important in buffering populations from the effects of climate warming.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".