Relative importance of size-based competitive ability and degree of niche overlap in inter-cohort competition of Atlantic salmon (<i>Salmo salar</i>) juveniles
Bibliographic record
Abstract
The competitive effect of older cohorts on younger cohorts may strengthen with increasing size differences owing to increasing differences in competitive abilities. Alternatively, it may weaken owing to increasing partitioning of resources as a result of ontogenetic niche shifts. Here, we test this by creating spatial variation in densities of one size class of overyearling Atlantic salmon ( Salmo salar ) and assess the effects on two size classes of young-of-the-year (YOY). The positive relationship between growth of overyearlings and final body size of YOY (a proxy for their growth) was steeper for the larger size class of YOY than for the smaller size class, which would be expected if the degree of niche overlap between two cohorts depended on their size difference. The negative relationship between overyearling density and YOY body size was also steeper for the larger size class (at least for body mass), suggesting that effects of body size differences on relative competitive abilities appear to be of less importance than the effects on degree of niche overlap. YOY should thus experience relatively less competition from older cohorts in rapidly growing populations, and this may also apply to many other fish species with ontogenetic niche shifts.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".