Seasonal habitat use of white sucker Catostomus commersonii in a small Boreal lake
Bibliographic record
Abstract
Abstract White sucker (Catostomus commersonii) is a large-bodied benthic fish species that is found across a broad geographic region in North America. Often overlooked, white suckers are an integral component of aquatic ecosystems in their role as the dominant nearshore benthivore in many lakes. Few detailed field investigations on habitat use and thermal occupancy of white sucker exist, limiting our ability to predict the risk of habitat loss from development and climate warming for this cool-water species. Here we investigated seasonal depth, temperature and spatial occupancy patterns of white suckers in a lake located in northern Ontario, Canada. Using a combination of positioning acoustic telemetry and environmental data, we determined depth and space use patterns, seasonal temperature preference indices, and the affinity of white sucker to the lake bottom (i.e., benthic habitat) over a year long period. We found that the white suckers were consistently observed in shallow waters (< 10 m depth) and near the lake bottom across all seasons but were positioned slightly deeper in the winter. The tagged white suckers showed a strong temperature selection preference for thermal habitat between 10 and 16 °C during the open-water seasons and tended to avoid cold (< 6 °C) thermal habitat. Space use patterns, calculated using kernel utilization distributions, and daily movement rates were surprisingly consistent across all seasons, with regular occupancy of only some nearshore areas. This study highlights a highly restrictive pattern of habitat use by white sucker that is consistent across seasons, suggesting that this generalist species may be more vulnerable to anthropogenic disturbance than previously thought.
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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 | 0.001 |
| 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".