Effects of environmental variables on the calling behaviour of Northern Leopard Frogs (<i>Lithobates</i> <i>pipiens</i>) in Alberta, Canada
Bibliographic record
Abstract
Breeding behaviour of Temperate Zone amphibians is influenced by environmental variables, but the initiation of calling (phenology) and influences on calling activity may vary with species and region. We investigated the influence of the timing of ice melt, water temperature, and photoperiod on the breeding phenology of the Northern Leopard Frog (Lithobates pipiens (Schreber, 1782)) in southern Alberta, Canada, using automated recording units. We also examined the influence of wind speed, relative humidity, water temperature, and time of day on calling activity. The initiation of calling varied by 13 days at our three sites, suggesting that calling was influenced more by water temperature and timing of ice melt than photoperiod. Calling was first observed 8–11 days after ice melt at water temperatures of 7.5–8 °C at our sites. No calling was detected at water temperature <5 °C. We recorded nocturnal and diurnal calling at all sites; >50% of calling was diurnal, even on days with warm overnight temperatures. Calling activity was influenced by time of day, water temperature, wind, and relative humidity. Our results suggest that date of initiation of calling varies considerably among breeding ponds and that the time of day of peak calling varies with both site and water temperature.
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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 | 0.001 |
| 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".