Climate-driven thermal opportunities and risks for leaf miners in aspen canopies
Bibliographic record
Abstract
Abstract In tree canopies, incoming solar radiation interacts with leaves and branches to generate temperature differences within and among leaves, presenting thermal opportunities and risks for leaf-dwelling ectotherms. Although leaf biophysics and insect thermal ecology are well understood, few studies have examined them together in single systems. We examined temperature variability in aspen canopies, Populus tremuloides, and its consequences for a common herbivore, the leaf-mining caterpillar Phyllocnistis populiella. We shaded leaves in the field and measured effects on leaf temperature and larval growth and survival. We also estimated larval thermal performance curves for feeding and growth and measured upper lethal temperatures. Sunlit leaves directly facing the incoming rays reached the highest temperatures, typically 3 – 8 °C above ambient air temperature. Irradiance driven increases in temperatures, however, were transient enough that they did not alter observed growth rates of leaf miners. Incubator and ramping experiments suggested that larval performance peaks between 25 and 32 °C and declines to zero between 35 and 40 °C, depending on duration of temperature exposure. Upper lethal temperatures during one-hour heat shocks were 42 – 43 °C. When larvae were active in early spring, temperatures generally were low enough to depress rates of feeding and growth below their maxima, and only rarely did estimated mine temperatures rise beyond optimal temperatures. Observed leaf or mine temperatures never approached larval upper lethal temperatures. At this site during our experiments, larvae thus appeared to have a significant thermal safety margin; the more pressing problem was inadequate heat. Detailed information on mine temperatures and larval performance curves, however, allowed us to leverage long-term data sets on air temperature to estimate potential future shifts in performance and longer-term risks to larvae from lethally high temperatures. This analysis suggests that, in the past 20 years, larval performance has often been limited by cold and that the risk of heat stress has been low. Future warming will raise mean rates of feeding and growth but also the risk of exposure to injuriously or lethally high temperatures.
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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 | 0.000 | 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".