Asynchronous breeding and variable embryonic development period in the threatened Northern Leopard Frog (<em>Lithobates pipiens</em>) in the Cypress Hills, Alberta, Canada: conservation and management implications
Bibliographic record
Abstract
Understanding breeding phenology is critical for establishing monitoring strategies, comprehending population dynamics, and developing conservation actions for at-risk species, such as the Northern Leopard Frog (Lithobates pipiens). The timing of spawning and hatching in the Northern Leopard Frog may be highly variable depending on regional environmental conditions, which can make establishing the timing of surveys difficult. In spring 2006, eggs were laid over 30 days (24 April to 23 May) and hatching occurred over 2 weeks (14–28 May) at three neighbouring ponds in Cypress Hills, Alberta, Canada. Although spawning occurred over a month, all eggs hatched within a 2-week period, indicating variable embryo development rate. Among 26 egg masses, eggs laid later in the season developed approximately four times faster than those laid earlier, and Akaike information criterion-ranked models suggested that both Julian date and water temperature were important predictors of embryo development rate: later spawning date and warmer water were associated with faster rates. Some egg masses survived colder temperatures than previously reported for this species. Asynchronous breeding and variable development rates reveal the need to conduct multiple surveys over the breeding season, even within a small geographic area, to document reliably the presence of egg masses and identify breeding habitat. Identification of key breeding habitat is necessary to mitigate human-caused disturbances of such regionally imperiled species.
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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 | 0.000 | 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".