Brazilian free-tailed bats (<i>Tadarida brasiliensis</i>) adjust foraging behaviour in response to migratory moths
Bibliographic record
Abstract
Insect migrations represent large movements of resources across a landscape, which are attractive to predators capable of detecting and catching them. Brazilian free-tailed bats (Tadarida brasiliensis (I. Geoffroy, 1824)) consume migratory noctuid moths, which concentrate in favourable winds resulting in aggregations of prey that attract bats hundreds of metres above ground. Although T. brasiliensis are known to feed on these aggregations of migratory moths, changes in their foraging behaviours have not been linked to moth migration events. We investigated possible shifts in the bats’ foraging behaviours when moths are migrating with respect to altitude and moth abundance. We recorded 1104 echolocation call passes of T. brasiliensis at ground level and at altitudes of ∼100 and ∼200 m above ground level. We found proportionally more bat activity at higher altitudes when migratory moth abundance was high. We also found that bats decreased call frequency and bandwidth and increased call duration at higher altitudes and behaved similarly with increasing moth abundance even at ground level. Our results support predictions that bats change foraging behaviour in response to seasonal availability of migratory moths and document alterations in echolocation call parameters that are consistent with optimizing prey detection.
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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 | 0.000 |
| 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 | 0.000 |
| 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".