Migration, Diet, or Molt? Interpreting Stable‐Hydrogen Isotope Values in Neotropical Bats
Bibliographic record
Abstract
ABSTRACT Migratory behavior in bats is poorly described, particularly in the Neotropics. Stable‐hydrogen isotope (δD) analysis may allow tracking of altitudinal movements of bats but has not been explored. δD values in rainwater (δDp) deplete linearly with altitude and are reflected in the keratinous tissues of animals through diet. A mismatch between keratin δD (δDk) and that expected at the capture site based on δDp can indicate prior migration. We collected rainwater, claws and hair from eight bat species at two lower‐montane forest sites in Nicaragua. Claw δD for Carollia brevicauda and hair and claws for Desmodus rotundus (known to be non‐migratory) fell within the predicted range based on rainwater (−17 to −60‰) suggesting these tissues were synthesized at the study site. δD tissue values for Artibeus toltecus, Sturnira lilium, Glossophaga soricina, Anoura geoffroyi, and hair for C. brevicauda were more negative than predicted for the capture site (−60‰) suggesting tissue synthesis at higher elevation and migration downslope to the capture site. However, our study area represents the highest elevation in the region; the nearest appropriate higher elevations are 350–500 km away and seasonal migration is expected to be<200 km. Thus we consider that seasonal shifts in δDp (9 to −45‰) may result in differences in species which molt at different times, and that diet may have driven differences in δD. Our results suggest that the effects of molt timing and diet may first need to be understood before δD may be successfully used to track bat movements.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".