Diet characterization and a preliminary investigation into trophic niche placement for an endangered lake sturgeon (Acipenser fulvescens) population in the Saskatchewan River, SK, Canada
Bibliographic record
Abstract
All Canadian lake sturgeon (Acipenser fulvescens) populations are listed under the Committee on the Status of Endangered Wildlife in Canada (COSEWIC) due to their complex life history, loss of habitat and negative interactions with anthropomorphic activities. Lake sturgeon diets vary considerably across their range and depend on the local benthic invertebrate fauna, substrata, and competition with congener species. Hence, determining population-specific prey assemblages is a vital contribution to effective conservation efforts. We used carbon and nitrogen stable isotopes to identify lake sturgeon prey preferences for juvenile (<100 cm) and adult (>100 cm) age classes and their trophic niche in the Saskatchewan River, SK, Canada. In this system, lake sturgeon were the top predator within the benthic food web with no direct competition for preferred prey items from congener species. Their diet was dominated by crayfish (49.1± 6.4%) and snails (36.3 ± 5.5%), with no significant differences between age classes. Furthermore, lake sturgeon favoured deep rocky pools throughout the river; a habitat where crayfish and snails are typically found. Therefore, conservation efforts should be directed at preserving these habitats for the residing benthic invertebrate community, and the lake sturgeon's ability to access them.
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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 | 0.001 | 0.002 |
| 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) | 0.001 | 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".