Active season body mass patterns of little brown and northern myotis bats
Bibliographic record
Abstract
Abstract Animals are expected to adjust their behavioral patterns to improve fitness outcomes, such as fecundity or offspring survival. For long‐lived hibernators, decisions made in each annual cycle may reflect considerations not just for concurrent survival and reproduction but also the pressure to maximize overwinter survival and future reproductive success. We examined how these elements manifest themselves in the body mass variation patterns of North American northern latitude temperate bats, whose size and roosting habits present considerable monitoring challenges. We characterized and compared the summer and fall mass variation patterns of little brown myotis (Myotis lucifugus) and northern myotis (M. septentrionalis) from a historic dataset. In summer, the estimated date of parturition was strongly associated with spring foraging conditions (low wind, low precipitation, and warm temperatures), and mass gain associated with female reproduction conferred considerable differentiation between the mass variation patterns of females and males. In fall, differences were most apparent among species, although adults exhibited a greater capacity for rapid mass gain than juveniles. These results demonstrate how reproductive constraints and interannual survival have important influences on the behavior of temperate bats. Future work should seek to quantify the fitness benefits of patterns identified in this study, such as the rate of prehibernation mass gain.
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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".