Host and host-site specificity of bat flies (Diptera: Streblidae and Nycteribiidae) on Neotropical bats (Chiroptera)
Bibliographic record
Abstract
Ectoparasite host specificity can be influenced by factors such as the degree of host isolation and ectoparasite mobility. Host-site specificity can result from factors such as proximity to mates, competition, and host grooming behaviour. Ectoparasitic bat flies on bats from the Lamanai area of Belize were collected from hosts captured in mist nets to determine host specificity and host-site specificity. Bat grooming behaviour was also recorded and quantified. From 455 bats (25 species in five families), 773 bat flies (32 species in two families) were collected. Of 32 bat fly species, 25 were only found on 1 bat species, 6 were found on 2 species of the same genus, and 1 was found on 2 species of different genera (the latter appearing to be an accidental association). Specificity of the bat flies tended to follow the taxonomy of the bat hosts, not the ecological isolation of the host species, since bat species that often roost in polyspecific groups did not share bat fly species. Mobility of the bat flies was not related to host specificity. Host-site specificity of bat flies occurred for either fur or membrane on the host, and long hind legs and ctenidia appear to be morphological adaptations for living in fur. Bat grooming behaviour was consistent with the assumptions of a simulation model, which suggested that host grooming could be responsible for host-site segregation of bat flies.
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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".