Unravelling the Costs of Flight for Immune Defenses in the Migratory Monarch Butterfly
Bibliographic record
Abstract
Migratory animals undergo extreme physiological changes to prepare for and sustain energetically costly movements; one potential change is reduced investment in immune defenses. However, because some migrants have evolved to minimize the energetic demands of movement (for example, through the temporary atrophy of non-essential organs such as those involved in reproduction), migratory animals could potentially avoid immunosuppression during long-distance journeys. In this study, we used a tethered flight mill to examine immune consequences of experimentally induced powered flight in eastern North American monarch butterflies. These butterflies undergo an annual two-way long-distance migration each year from as far north as Canada to wintering sites in Central Mexico. We quantified immune measures as a function of categorical flight treatment (flown versus control groups) and continuous measures of flight effort (e.g., flight distance, duration, and measures of efficiency). We also examined whether relationships between flight and immune measures depended on reproductive investment by experimentally controlling whether monarchs were reproductive or in state of reproductive diapause (having atrophied reproductive organs) prior to flight. Of the three immune responses we measured, hemocyte concentration (the number of immune cells) was lower in flown monarchs relative to controls but increased with flight distance among flown monarchs; the other two immune measures showed no relationship to monarch flight. We also found that monarchs that were reproductively active were less efficient fliers, as they exerted more power during flight than monarchs in reproductive diapause. However, reproductive status did not modify relationships between flight and immune measures. Results of this study add to a growing body of work suggesting that migratory monarchs-like some other animals that travel vast distances-can complete their journeys with efficient use of resources and minimal costs.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".