Indirect effects of fish winterkills on amphibian populations in boreal lakes
Bibliographic record
Abstract
We exploited fish winterkills in small, boreal Alberta lakes to determine if anuran amphibians respond to large but natural changes in fish densities. Eight large declines in fish abundance occurred in seven lakes over a 5 year period, while major increases in fish abundance, reflecting recovery after winterkill, were recorded 5 times. Summer pitfall trapping of young-of-the-year (YOY) Wood Frogs (Rana sylvatica LeConte, 1825) and Boreal (Bufo boreas boreas Baird and Girard, 1852) and Canadian (Bufo hemiophrys Cope, 1886) toads indicated that frog abundance responded consistently to such large changes in fish abundance, but especially if fish communities were dominated by small-bodied species (sticklebacks and minnows). As well, changes in YOY Wood Frog and fish abundance were negatively correlated; YOY Wood Frogs were as much as 7.7 times more abundant after winterkills than in non-winterkill years. These increases in metamorphs did not result from an increased immigration of breeding adults to winterkill lakes, suggesting instead that larval survival was greater. Higher abundance of YOY Wood Frogs and toads was associated with smaller body size at metamorphosis. Despite this apparent reduction in individual growth, abundance of juvenile frogs remained significantly elevated 1 year after winterkill. In contrast to Wood Frogs, YOY toads tended to respond positively to recoveries of small-fish populations. Because anuran amphibians can respond to fish winterkill, and because winterkill is a frequent natural disturbance, small fish-bearing lakes can serve as important breeding habitat for amphibians in Alberta's boreal forest.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".