No evidence of sustained recovery of native trout in response to angling suppression of invasive Brook Trout
Bibliographic record
Abstract
Abstract Objective Nonnative fish invasions have had widespread impacts on freshwater ecosystems, including effects on native fish biodiversity and persistence. Brook Trout Salvelinus fontinalis were first introduced into the Elbow River watershed (Alberta, Canada) in the 1940s. They have since become established in Quirk Creek, and they dominated the fish community by the mid-1990s, raising concern about the native populations of Westslope Cutthroat Trout Oncorhynchus clarkii lewisi and Bull Trout S. confluentus. Methods A targeted angling program was operated from 1998 to 2015, along with limited electrofishing removals, to suppress the Brook Trout population. We used 25 years of fish monitoring data from 1978 to 2020 to evaluate the program's effectiveness for reducing the Brook Trout population and the program's consequences for native trout. Result Densities of Brook Trout larger than 150 mm declined after the onset of the suppression project, and the decline was attributed to removals through angling. However, Brook Trout recruitment remained comparable to presuppression levels. Westslope Cutthroat Trout recruitment increased during and after Brook Trout suppression. Densities of Westslope Cutthroat Trout larger than 150 mm increased during the suppression period but did not reach density goals targeted for recovery of the species. Bull Trout remained at very low densities throughout the suppression project. Conclusion The lack of native trout recovery during the suppression project was hypothesized to result from (1) incidental release mortality of native trout, (2) Brook Trout suppression that was insufficient to prompt an effective response in native trout populations, or (3) a combination of these factors. Continued low densities of Brook Trout larger than 150 mm and native trout after the end of the suppression project (when harvest and incidental release mortality were alleviated) may point to some other factor impacting the recovery of trout larger than 150 mm, particularly Westslope Cutthroat Trout, since recruitment was at its highest during this period. Overall, angling was not considered an effective method for promoting native trout recovery, and other techniques should be pursued depending on management goals.
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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 | 0.000 |
| 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".