Diffusion in the littoral zone: scoping emergence times and movement to essential habitat for young‐of‐year brook trout in lakes
Bibliographic record
Abstract
Factors governing the process of dispersal of lake‐spawned brook trout (Salvelinus fontinalis) young‐of‐year (YOY) appear drastically different from those governing dispersal in more commonly studied stream salmonids. Rather than dispersal being highly density‐dependent and the result of territoriality and aggression, in brook trout it may be density‐independent and driven by a common need for coldwater habitat for summer survival. Emerging fish travel great distances from single spawning sites on lakes to cold groundwater habitat. Movement is a gradual, one‐dimensional diffusion around lake margins and represents a very unique and simplified natal dispersal pathway allowing for dispersal rates, distances, and factors controlling these parameters to be measured. We predicted timing of the emergence period for brook trout alevins from lake spawning sites using the known relation between water temperature and emergence times for salmonids. Emergence and dispersal was then observed in the field by visually estimating YOY density in segments of the littoral zone throughout the dispersal period. Fluxes in density in these sections were used to estimate rate of YOY spread. YOY behaviour and body condition was also assessed across the wave of spatial spread. We are working towards a spatially explicit model to identify critical groundwater rearing habitat needing protection from forestry activities.
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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) | 0.000 | 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".