Are wild populations ideally distributed? Variations in density-dependent habitat use by age class in juvenile Atlantic salmon (Salmo salar)
Bibliographic record
Abstract
We examined relationships between abundance and habitat use in three age classes of juvenile Atlantic salmon ( Salmo salar ) in the Stewiacke River, Nova Scotia, Canada. Using stream gradient as a proxy for habitat quality, we used a double half normal function, modified to include density dependence, to model the relationship between habitat quality and fish density. We found that density was asymmetrically distributed around a similar optimum gradient for all three age classes regardless of abundance. Habitat use was highly density-dependent for age-0 and age-1 juveniles, but not for age-2+ salmon. As abundance of age-0 and age-1 salmon increased, their relative density decreased in low-gradient habitat and increased in higher-gradient habitat, although their absolute density increased in all stream gradient categories. Variation in habitat use was consistent with ideal free theory for age-1 juveniles in high-gradient habitat, but not in low-gradient habitat. Age-2+ individuals appeared not to modify their distribution among habitats, even though increasing competition changes the relative benefit of low-gradient habitat in terms of resource acquisition. In contrast, age-1 individuals responded to increased competition by modifying their distribution along the habitat gradient, even though this may have slightly reduced an individual’s potential for growth.
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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".