Tropical bat ectoparasitism in continuous versus fragmented forests: A gap analysis and preliminary meta‐analysis
Bibliographic record
Abstract
Tropical regions are experiencing rapid rates of forest fragmentation, which can have several effects on wildlife, including altered parasite dynamics. Bats are a useful host group to consider the effects of fragmentation, because they are abundant in the tropics, serve important ecological roles, and harbor many parasites. Nevertheless, research on the effects of fragmentation on bat ectoparasites is still limited. To help guide ongoing and future research efforts, this study had two objectives: (1) conduct a gap analysis to characterize the state of currently available research on fragmentation effects on bat ectoparasites and (2) conduct a preliminary meta-analysis to identify current trends. We systematically highlighted several research gaps: Studies comparing the effects of fragmented versus continuous forests on ectoparasites are limited and have primarily been conducted in the Neotropics, with a focus on bats in the superfamily Noctilionidea (especially frugivorous phyllostomids). Our preliminary meta-analysis suggested that ectoparasite prevalence (but not the mean or variance in intensity) was higher in fragments than in continuous forests. Moreover, prevalence increased with increasing roost duration, and mean intensity was higher for bats with higher wing aspect ratios. Intensity variance was affected by an interaction between forest type and wing aspect ratio, such that variance increased for bats with high-wing aspect ratios in continuous forests but decreased in fragments. These results suggest that fragmentation can shape aspects of bat ectoparasitism and could have implications for the ecology, health, and conservation of bats in fragmented landscapes. However, existing research gaps could bias our current understanding of habitat change and bat health, and future research should thus investigate these effects in the Paleotropics and with other bat families.
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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 | 0.021 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.048 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".