Frequency of adult amphibian abnormalities and consequences for fitness-related traits in an uncontaminated environment
Bibliographic record
Abstract
Morphological abnormalities in amphibians are commonly associated with anthropogenic activity, although little baseline information on the prevalence of abnormalities in uncontaminated environments exist. Here, we leverage a 12-year study of spotted salamanders ( Ambystoma maculatum (Shaw, 1802)) in an uncontaminated ecosystem in Algonquin Provincial Park, Canada, to estimate abnormality rates and explore how abnormalities affect fitness-related traits. Annual abnormality rates estimated from drift fence data ranged from 4.3% to 5.8% of individuals sampled. Abnormality rates from aquatic trapping between 2008 and 2019 varied from 1.2% to 16.7%, where temporal increases in abnormality rates were observed. We also performed a targeted, systematic literature survey and found that Caudata exhibited a slightly higher abnormality prevalence than Anura, and that the baseline frequency of abnormalities described at our drift fence site is slightly lower than rates reported in the literature (8.1%, 95% CI, 4.76%–13.3%). Salamanders with abnormalities exhibited a slightly, but not significantly, higher body condition and a significantly earlier arrival date at the breeding site, both of which are traits typically associated with high-fitness individuals. Our study suggests that abnormalities have detectable phenotypic consequences, and underlines the need for temporal sampling efforts to provide ranges of baseline abnormality rates, rather than a point estimate.
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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 | 0.001 | 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".