Interactive effects of roads and weather on juvenile amphibian movements
Bibliographic record
Abstract
We investigated whether paved roads adjacent to 16 ponds acted as barriers to movements of juvenile wood frogs ( Lithobates sylvaticus ), green frogs ( Lithobates clamitans ), mole salamanders ( Ambystoma laterale , A. maculatum ), and American toads ( Anaxyrus americanus ) in eastern New Brunswick, Canada. Using pitfall traps and drift fences, we recorded captures of juveniles dispersing away from their natal ponds into forest habitat (pondside fences) or across the road (roadside fences) over two field seasons. To explain variations in abundance of dispersers among sites, we measured several road-associated variables including traffic intensity and roadside habitat structure, pond quality, and weather variables. We estimated the activity patterns (across 4-day periods) and seasonal abundance of juveniles in transit between ponds and terrestrial habitat using generalized linear mixed models. For all groups, activity across 4-day periods increased with either total precipitation or minimum air temperature. However, road-associated variables were also important for some species. Mole salamander activity was lowest next to roads. Wood frog activity increased with minimum air temperature, but the effect was weakest at roadside fences (minimum air temperature × fence position interaction). Seasonal abundance of most groups varied with habitat structure or pond hydroperiod. Green frog abundance decreased with increasing traffic intensity, but abundance was higher at roadside fences than pondside fences. In contrast, wood frog seasonal abundance tended to be lowest at roadside fences. We conclude that road-associated disturbances are detectable at fine temporal scales and that amphibian responses to such variables can be influenced by weather variables.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".