Temperature-induced developmental plasticity, size and flight energetics in the hawkmoth <i>Manduca sexta</i>
Bibliographic record
Abstract
Flying insects exhibit substantial variation in size and body proportions, influencing both locomotor performance and metabolic demands during flight. For instance, intra- and interspecific morphological variation affects wingbeat frequency and flight metabolic rate. Temperature, a key driver of developmental plasticity in most ectotherms, often produces an inverse relationship between body mass and developmental temperature. Here, we assessed the extent to which temperature-induced developmental plasticity in body mass maintains or disrupts morpho-functional relationships in the hawkmoth Manduca sexta. By manipulating developmental temperature, we generated a 7.75-fold range in body mass. As body mass increased, body proportions changed via allometric scaling, with minor size-independent effects of temperature treatment but no co-plasticity in muscle metabolic phenotype. Our findings show that plasticity impacted flight energetics through its effect on body mass. Wingbeat frequency decreased with increasing body mass, despite negative wing area allometry, a pattern that, in other studies, has resulted in no correlation between body mass and wingbeat frequency. Energy expenditure during flight increased with body mass on a thorax mass-specific basis, driven by changes in body proportions and ultimately leading to flight challenges. The limited plasticity observed in flight muscle metabolic phenotype suggests it is governed more by genetic variation than environmental factors, explaining adaptive changes in flight energetics. Overall, we conclude that plasticity in body mass and proportions affects flight energetics, leading to compromises in flight ability without accompanying plasticity in flight muscle metabolic phenotypes, which may limit muscle metabolic power.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".