Complex littoral habitat influences the response of native minnows to stocked trout: evidence from whole-lake comparisons and experimental predator enclosures
Bibliographic record
Abstract
Strong negative effects of introduced predatory fishes on native species are frequently reported but may not be universal. Recent research from productive lakes, for example, has documented few serious negative effects. Our objective was to determine how complex littoral habitat mediates the response of adult and young-of-year (YOY) native dace (Chrosomus spp.) and fathead minnow (Pimephales promelas) to the introduction of rainbow trout (Oncorhynchus mykiss) in productive lakes in Alberta, Canada. We first quantified inshore–offshore habitat use of native fish in stocked and unstocked lakes with heavily vegetated littoral zones. We then manipulated the presence or absence of trout and densities of macrophytes within enclosures in an unstocked lake and assessed the behavioral response of native fish. Our whole-lake comparisons revealed that adult and YOY fishes occurred in vegetated inshore areas to a greater extent in stocked relative to unstocked lakes. In the enclosure experiment, native fishes did not respond to the introduction of trout at natural macrophyte densities, but dace significantly reduced their occupation of enclosures with reduced macrophytes once trout were added. Our results suggest that complex littoral macrophyte beds provide important refuge habitat for native fishes, which can potentially mitigate negative effects associated with introductions of a piscivorous predator.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".