Habitat Use and Movement Patterns of Brook Trout in Nipigon Bay, Lake Superior
Bibliographic record
Abstract
Abstract Brook trout Salvelinus fontinalis are one of two salmonine species native to Lake Superior. Abundant and widely distributed a century ago, Lake Superior's brook trout (coasters) have been reduced to a few remnant stocks, probably as a result of exploitation and habitat loss. Twenty brook trout captured in Nipigon Bay, Lake Superior, were surgically implanted with radio transmitters and were located from June 1999 to October 2000. Brook trout locations were used to determine the characteristics of utilized lake habitat and to identify streams used for spawning and the spawning areas within them. These locations were also used to establish daily and seasonal movement patterns. A total of 638 locations were obtained during the tracking period, 483 occurring within Nipigon Bay and the remaining 155 within tributaries. Brook trout were located almost exclusively within the shallow nearshore areas of Nipigon Bay; 92% of the locations were less than 7 m deep and 94% were less than 400 m from shore. Brook trout occupied deeper areas with steeper shoreline slopes during July and August, when the water temperatures of shallow nearshore areas were at their highest. Following selected individuals for 24‐h periods revealed that brook trout often used deeper areas during daylight hours and moved to extremely shallow nearshore areas during the night. Radio‐tagged brook trout began ascending tributaries during late summer in both years of this study. The mean residency time for brook trout in tributaries was 46 d. Spawning occurred in early October, and most radio‐tagged brook trout returned to Lake Superior by mid‐October. Four different streams were used during the spawning period. Brook trout entering streams exhibited strong spawning site fidelity between years.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".