Carbon (δ13C) and Nitrogen (δ15N) Stable Isotope Signatures in Bat Fur Indicate Swarming Sites Have Catchment Areas for Bats from Different Summering Areas
Bibliographic record
Abstract
Migratory patterns of bats are not well understood and traditional methods to study this, like capture-mark-recapture, may not provide enough detail unless there are many records. Stable isotope profiles of many animal species have been used to make inferences about migration. Each year Myotis lucifugus and M. septentrionalis migrate from summering roosts to swarming caves and mines in the fall, but the pattern of movement between them is not well understood. In this study, fur δ13C and δ15N values of 305 M. lucifugus and 200 M. septentrionalis were analyzed to make inferences about migration patterns between summering areas and swarming sites in Nova Scotia, Canada. We expected that there would be greater variability in δ13C and δ15N among individuals at swarming sites because it was believed that these sites are used by individuals originating from many summering areas. There was extensive overlap in the standard ellipse area, corrected for small sample sizes (SEAc), of bats at swarming sites and much less overlap in SEAc among groups sampled at summering areas. Meaningful inference could not be made on M. septentrionalis because their low variation in SEAc may have been the result of sampling only 3 summering areas. However, for M. lucifugus, swarming sites had larger SEAc than summering areas and predictive discriminant analysis assigned swarming bats to multiple summering areas, supporting the contention that swarming bats are mixed aggregations of bats from several summering areas. Together, these data support the contention that swarming sites have catchment areas for bats from multiple summering areas and it is likely that the catchment areas for swarming sites overlap. These data suggest that δ13C and δ15N profiling of bat fur offer some potential to make inferences about regional migration 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".