Variation in catchment areas of Indiana bat (<i>Myotis sodalis</i>) hibernacula inferred from stable hydrogen (δ<sup>2</sup>H) isotope analysis
Bibliographic record
Abstract
Understanding seasonal movements of bats is important for effective conservation efforts. Although female Indiana bats ( Myotis sodalis Miller and Allen, 1928) have been documented to migrate >500 km, knowledge of their migratory patterns is still extremely limited. We used the relationship between latitude and stable hydrogen isotope ratio in bat hair (δ2Hhair) to estimate the north–south extent of the summer range (catchment area) of bats hibernating in 14 Indiana bat hibernacula in eight states throughout its range. Range of δ2Hhair values varied substantially among hibernacula, suggesting large differences among sites in the north–south distance travelled by bats between summer and winter habitats. In particular, hibernacula in the southern portion of the range had greater catchment areas than those in the central and northern portions of the range. Variability in movement distances among sites was not associated with the number of hair samples analyzed or colony size. Significant year-to-year variation (2007–2008 to 2008–2009) in the distribution of δ2Hhair for two sites in Tennessee was observed. Currently, hibernacula considered important for species conservation are largely determined by population size, but our results suggest that migratory diversity should also be considered.
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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 | 0.000 |
| 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".