Effects of Temperature on Development of Lymantria dispar asiatica and Lymantria dispar japonica (Lepidoptera: Erebidae)
Bibliographic record
Abstract
Periodic introductions of the Asian subspecies of gypsy moth, Lymantria dispar asiatica Vnukovskij and Lymantria dispar japonica Motschulsky, in North America are threatening forests and interrupting foreign trade. Although Asian gypsy moth has similar morphology to that of European and North American gypsy moth, it has several traits that make it a greater threat, the most important being the flight capability of females. Asian gypsy moth is not yet established in North America; however, infestations have been detected multiple times in Canada and the United States. To facilitate detection and eradication efforts, we evaluated the effect of a range of temperatures on development time, survivorship, and fertility of eight populations of Asian gypsy moth. There were significant impacts of temperature and population on these life history characteristics. The larval developmental rate increased with temperature until it reached an optimum at 29 °C. Larvae experienced significant molting problems at the highest and lowest temperatures tested (10 °C and 30 °C). At 30 °C, female fitness was markedly compromised, as evidenced by reduced fecundity and fertility. This suggests that development and survival of Asian gypsy moth may be limited by summer temperature extremes in the Southern United States. We also determined the degree-day requirements for two critical life stages and two populations of Asian gypsy moth, which represent the extremes in latitude, to predict the timing for biopesticide application and adult trap deployment. Our data will benefit pest managers in developing management strategies, pest risk assessments, and timing for implementation of management tactics.
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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".