Limited effects of non-native trout on microcrustacean zooplankton in boreal foothills lakes: comparisons of stocked, unstocked, and fishless lakes
Bibliographic record
Abstract
Stocking lakes with trout can have strong effects on native communities; however, the nature of impacts is not universal across receiving ecosystems. To assess effects of non-native trout, relative to native small-bodied fish, on microcrustacean zooplankton, we compared stocked, unstocked (but fish-bearing), and fishless lakes in the boreal foothills of Alberta, Canada. Relative to unstocked lakes, stocked lakes had greater richness, but otherwise showed few additional effects on microcrustacean communities. In contrast, fishless lakes supported lower abundances of Cladocera, Calanoida, and Cyclopoida, but were dominated by larger cladoceran and calanoid taxa, compared with fish-bearing lakes (stocked and unstocked). Vertical distributions also differed significantly among lake types; microcrustaceans had far higher relative abundances at 1 m than at 2 m in fishless lakes compared with fish-bearing lakes (distributions in stocked and unstocked lakes were similar). Microcrustacean communities in fishless lakes were likely shaped by the invertebrate planktivore Chaoborus, which was abundant in these systems, whereas native fishes likely structured microcrustacean communities prior to trout introductions, with planktivory by trout causing few additional effects.
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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".