Spatial and temporal variation in the influence of density dependence on growth of stream-living brown trout (<i>Salmo trutta</i>)
Bibliographic record
Abstract
The objective of this study was to investigate the extent to which, and the conditions under which, density operated on growth in stream-living brown trout (Salmo trutta). Observational data of 14 cohorts at four sites of Rio Chaballos (northwestern Spain) were examined. Consistent relationships between cohort-specific mass versus cohort-specific density and between year-to-year variations in brown trout mass at the end of five successive life stages versus mean densities corroborated one another and provided compelling evidence for the occurrence of density-dependent growth. However, density-dependent patterns varied in nature among sites to the extent that they were site-specific. A further comparison among 12 data sets revealed a smooth negative power trajectory between juvenile mass versus density. This plot suggested that detection of density-dependent growth might be facilitated in low density high growth populations located at the steep wing relative to high density slow growth populations. Current results emphasized the importance of density as a factor determining size-at-age and supported its operation as epiphenomena capable to obscure the effects of temperature on growth. The operation of density-dependent growth on numerical regulation of the population is further discussed.
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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 | 0.002 |
| 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".