Variation in female-biased sexual size dimorphism of Northern Pike ( <i>Esox lucius</i> ) associated with environment and life history
Bibliographic record
Abstract
ABSTRACT Background Sexual size dimorphism (SSD) is a widespread phenomenon in the animal world resulting from differential selection on the sexes. The Northern Pike ( Esox lucius ) is a freshwater apex predatory fish species that exhibits female-biased SSD, but the degree to which SSD varies among populations and what variables might dictate variation in SSD in this species remain poorly understood. Aim We sought to quantify the degree of variation in SSD among Northern Pike populations across a large portion of their North American range, as well as evaluate associations between the magnitude of SSD in Northern Pike populations with environmental variables and life history traits of populations. Methods We quantified SSD in 102 populations of Northern Pike across the province of Ontario, Canada, using a standardized gillnetting database. We further investigated the degree to which both environmental variables (Cisco abundance as catch-per-unit-effort, lake surface area, and latitude) and Northern Pike life-history traits (early growth and mortality rates) explained variation in female-biased SSD using linear models. Results Female-biased SSD in mean weight of Northern Pike increased with increasing Cisco ( Coregonus artedi ) abundance, and the difference in female and male mean age increased with increasing latitude. Furthermore, SSD was greater in populations with lower female mortality and early growth rates. Conclusion This study indicates that slow-growing, long-lived populations of Northern Pike should exhibit greater female-biased SSD, and that these conditions may be facilitated by the availability of large, energy-dense prey and cooler temperatures at northern latitudes.
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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 | 0.000 |
| 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".