Long-term assessment of the effect of introduced predatory fish on minnow diversity in a regional protected area
Bibliographic record
Abstract
Introduced piscivorous fishes had a dramatic impact on small-bodied fish species diversity of small temperate lakes in Gatineau Park, Quebec, Canada, on the basis of three surveys carried out over a 38-year period from 1970 to 2007. For three overlapping sets of lakes based on different combinations of survey years (lakes surveyed in 1970–1971, 1991–1992, and 2006–2007 (N = 14); lakes surveyed in 1970–1971 and 2006–2007 (N = 21); and lakes surveyed in 1991–1992 and 2006–2007 (N = 16)), those with introduced piscivores showed substantial and consistent temporal declines in average minnow species richness but much weaker, if any, declines in total species richness. By contrast, lakes without introduced piscivores showed no such decline. Whereas lakes without piscivores showed a strong species–elevation relationship early in the record, the strength of this relationship was much lower in lakes with introduced piscivores. Moreover, the strength of the species–elevation relationship declined precipitously over time in lakes with introduced piscivores, but remained stable in lakes where introduced piscivores were absent. The negative impact of piscivore introductions on small-bodied fish biodiversity in small lakes underscores the importance of action to mitigate the risk of future introductions or invasions.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".