Growth and Diet of Northern Pike (Esox lucius) in Boreal Lakes: Implications for Ecosystem Management
Bibliographic record
Abstract
An important top-down predator, the northern pike (Esox lucius), faces harsh environmental conditions in the northern boreal ecoregion. They are often managed for recreational fishing and, more recently, to create environmental offsets; strategies aimed at balancing ecological impacts by enhancing or restoring habitats. Our study examines northern pike populations in two remote boreal lakes in northern Alberta: Steepbank and Wappau. The lakes differ in size, vegetation cover, and trophic status, providing a natural experiment for investigating northern pike growth, condition, diet, and population density. Over three years (2018–2020), northern pike were sampled using gill nets. Population metrics, including growth, condition, and stomach contents, were compared between the lakes. Steepbank, a smaller, oligotrophic lake with low vegetation cover, showed lower prey fish densities compared to the larger, eutrophic Wappau, but it did not differ in northern pike catch per unit effort. Growth rates and body condition varied significantly between the lakes, with the northern pike in Wappau exhibiting faster growth and a better condition in the older age groups, while the younger northern pike in Steepbank had higher relative weights. A diet analysis revealed significant differences in prey consumption: Steepbank northern pike displayed higher rates of conspecific predation and invertebrate consumption, particularly in the younger age classes. These findings highlight how lake characteristics and prey availability shape northern pike population dynamics, offering valuable insights for lake management approaches in northern Alberta.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".