Lack of Angling‐Sized Yellow Perch in a Canadian Boreal Lake: Potential Influences of Growth Rate, Diet, and Predation by Double‐Crested Cormorants
Bibliographic record
Abstract
Abstract Fisheries for yellow perch Perca flavescens are economically important in North America, but in many lakes this species does not attain sizes desirable to anglers (total length [TL] > 250 mm). We investigated factors potentially contributing to the lack of angling‐sized yellow perch in Dore Lake, Saskatchewan. This large boreal lake has a long history of exploitation and is subject to current controversy regarding the impact of double‐crested cormorants Phalacrocorax auritus on its fisheries. We found that yellow perch in Dore Lake attained greater maximum ages (mean ± SD = 7.4 ± 1.0 years) but smaller maximum sizes (215 ± 7 mm TL) than other yellow perch populations. Thus, the lack of angling‐sized yellow perch in Dore Lake is probably the result of slow growth rates rather than short life spans. Double‐crested cormorants preyed heavily on yellow perch, but predation was highly skewed toward much smaller sizes (<100 mm TL) than those preferred by anglers. Stomach contents and stable nitrogen isotopes confirmed that yellow perch in Dore Lake undergo expected ontogenetic diet shifts and become predominantly piscivorous at around age 3. Analysis with stable isotopes also revealed long‐term dietary differences between age‐2 and age‐3 yellow perch captured in littoral versus offshore habitats, suggesting some degree of intrapopulation variability in resource and habitat use among yellow perch in Dore Lake.
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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 | 0.001 |
| Science and technology studies | 0.002 | 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".