Density-dependent intercohort interactions and recruitment dynamics: models and a bull trout (<i>Salvelinus confluentus</i>) time series
Bibliographic record
Abstract
A simple theoretical model shows that mechanisms of density-dependent survival that result in stable dynamics for populations with only intracohort interactions during the juvenile phase can produce cyclic behaviour when cohorts interact together. We compared these theoretical results with a time series (1971-1985) on juvenile bull trout (Salvelinus confluentus) from Eunice Creek, Alberta. Abundance of bull trout in Eunice Creek ranged over two orders of magnitude over the 15 years. By assigning age-classes to the abundance data (using a probabilistic length-frequency analysis), we assessed yearly survival rates for age-classes 1-3. Survival rates for age-classes 1 and 2 were negatively correlated (P < 0.05) with the effective density (an index of total consumption) of all juvenile bull trout in Eunice Creek. These observations support the hypothesis that different age cohorts of juvenile bull trout do interact. Using a stochastic version of the model and parameter values estimated from Eunice Creek, we hypothesize that even moderate levels of adult mortality (an average adult spawns during two seasons) coupled with random variation in the density-independent component of juvenile mortality can result in an apparent cyclic pattern for bull trout. Finally, stock- recruitment relationships for these populations are not represented by a single average curve.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".