Morphological and Physiological Idiosyncrasies Lead to Interindividual Variation in Flight Metabolic Rate in Worker Bumblebees (<i>Bombus impatiens</i>)
Bibliographic record
Abstract
Although intraspecific variation in metabolic rate is associated with variation in body size, similarly sized individuals nonetheless vary greatly. At similar masses, hovering bumblebee workers (Bombus impatiens) can differ in metabolic rate up to twofold. We examined how such interindividual variation arises by studying covariation of flight metabolic rate with morphological and other physiological parameters. Body size alone explained roughly half the variation in flight metabolic rate. The remaining variation could be explained as the outcome of variation in wing morphology and possibly an association with variation in flight muscle metabolic enzyme activities. As shown using statistical models, for a given mass, higher metabolic rate was correlated with both higher thoracic temperature and higher wing stroke frequency, in turn resulting from smaller wing surface area. When organismal and cellular metabolism for a given mass were linked, variation in metabolic rate was positively correlated with the activities of trehalase and hexokinase. Altogether, covariation with morphology and other physiological parameters explains up to 75% of the variation in metabolic rate. We also investigated the role of flight experience and show that neither flight restriction nor the number of lifetime flights affected flight energetics or flight muscle phenotype. Additionally, manipulating the level of wing asymmetry increased flight wing stroke frequency, metabolic rate, and thoracic temperature, but it did not alter enzyme activity. We conclude that idiosyncrasies in body morphology largely explained interindividual variation in flight metabolic rate but flight muscle metabolic phenotype shows little variation associated with differences in flight experience.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".