Spatial and Temporal Movements of White Sucker: Implications for Use as a Sentinel Species
Bibliographic record
Abstract
Abstract White suckers Catostomus commersonii are widely distributed in rivers of North America and often used in environmental monitoring. The species' value as a sentinel has been questioned because some populations are known to travel long distances during spawning migrations and therefore can be exposed to multiple environments. The movements of white suckers in a 65‐km reach of the Saint John River, New Brunswick, were studied from 2001 to 2003 using radio and acoustic tracking and analyses of stable isotope ratios. Individuals maintained small home ranges in the river from summer to late winter, averaging 2.6 river kilometers [rkm] or less each year. During the spring spawning season, upstream and downstream movements to three tributaries occurred. Distances traveled were up to 40 rkm and averaged 9.2 rkm (SD = 11.0). Two males used separate tributaries within a spawning period, and there was evidence that spawning may not take place every year. Stable isotope results confirmed that white suckers maintained a high fidelity to well‐defined reaches in the main river outside the spawning period. These results indicate the importance of distinct, limited habitats and connectivity of habitats for white suckers in large rivers and support the hypothesis that white suckers reflect localized environmental conditions and can be used as a sentinel.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 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".