Habitat quality enhances spatial variation in the self-thinning patterns of stream-resident brown trout (Salmo trutta)
Bibliographic record
Abstract
This study explored the extent to which variation in habitat factors related to growth and density influence self-thinning patterns in stream-living brown trout ( Salmo trutta ). Analysis of 110 cohorts at 12 sites of four contrasting streams revealed density–mass relationships in two phases. Density of survivors decreased little during the first half of their lifetime. A second phase commenced as individuals attained a threshold mass upon which density declined linearly with increased mass. The slopes of the second phase were greater than predicted by space and food demands. Among sites, these slopes were related to threshold densities at the beginning of the second phase. In turn, elevations, threshold densities, and slopes depicted concave trajectories against site depth, whereas threshold masses increased linearly. Apparently, cohorts remain below the carrying capacity during the first half of their lifetime and self-thin during the second half. Space-limited habitats impose site-specific carrying capacities and site-specific self-thinning coefficients, suggesting a common mechanism underlying self-thinning and an unanticipated, emerging property: two-phase patterns with far more variation in self-thinning coefficients. Variability in growth and density exhibited by brown trout and other salmonids across regions suggests that two-phase patterns may occur broadly, and self-thinning coefficients may vary widely.
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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 | 0.001 | 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".