Habitat variables influencing breeding effort in northern clade Bufo fowleri: Implications for conservation
Bibliographic record
Abstract
Local extirpations of the northern clade of Fowler's toad, Bufo fowleri, have been documented in the northeastern United States and Canada. To facilitate conservation of this species, we identified key characteristics of its preferred breeding habitat and adjacent landscape at Cape Cod National Seashore. We conducted calling surveys at 67 wetlands to quantify B. fowleri annual breeding effort over three years. The resultant multivariate models were then tested with data collected at 30 additional wetlands. B. fowleri choruses were more likely to be detected in permanent wetlands than semi-permanent or temporary wetlands. Predaceous fish and Rana catesbeiana did not negatively affect breeding effort. Wetlands used for breeding typically had shallower shores, less emergent vegetation, less canopy cover, fewer organic acids, and were warmer and less acidic than sites with no evidence of breeding choruses. Large choruses of B. fowleri typically occurred in wetlands containing < ∼33% woody emergent vegetation and adjacent uplands had more bare habitat and less development than sites without breeding. Our results suggest that B. fowleri in the northeastern United States will decline as development and post-agrarian reforestation continue and that removal of woody vegetation in and adjacent to breeding ponds may be necessary to maintain some populations.
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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 | 0.000 | 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".