Host demographic predicts ectoparasite dynamics for a colonial host during pre-hibernation mating
Bibliographic record
Abstract
Parasite dynamics can be mediated by host behaviours such as sociality, and seasonal changes in aggregation may influence risk of parasite exposure. We used little brown bats (Myotis lucifugus) captured during the autumn mating/swarming period to test the hypothesis that seasonal and demographic-based variation in sociality affect ectoparasitism. We predicted that ectoparasitism would: (1) be higher for adult females and young of the year (YOY) than adult males because of female coloniality; (2) increase for adult males throughout swarming because of increasing contact with females; (3) decrease for adult females and YOY throughout swarming because of reduced coloniality and transmission of individual ectoparasites to males; (4) be similar for male and female YOY because vertical transmission from adult females should be similar. Ectoparasitism was lowest for adult males and increased for males during swarming, but some effects of demographic were unexpected. Contrary to our prediction, ectoparasitism increased for adult females throughout swarming and YOY males also hosted fewer ectoparasites compared with adult and YOY females. Interestingly, females in the best body condition had the highest parasite loads. Our results suggest that host energetic constraints associated with future reproduction affect pre-hibernation parasite dynamics in bats.
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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 | 0.000 | 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) | 0.002 | 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".