Stock-recruitment relationships for life cycles that exhibit concurrent density dependence
Bibliographic record
Abstract
This study provides theoretical stock-recruitment relationships for life cycles in which multiple, density-dependent mechanisms stemming from different periods during the life cycle act concurrently on a single demographic transition. Using graphical examples and analytical derivations, it is demonstrated that overcompensatory density dependence emerges from such life cycles despite the initial assumption that density-dependent mechanisms follow simple compensatory Beverton-Holt dynamics. These results indicate that concurrent demographic effects of temporally distinct density-dependent mechanisms provide a biologically plausible basis for empirically derived, three-parameter stock-recruitment models. This theory is inspired by, and may be most applicable to, spawner-recruit relationships in anadromous salmonids but may also inform analysis of stock and recruitment data for other taxa that putatively compete for both food and spawning space. Application of this theory will require the estimation of additional parameters from stock-recruitment data. Such parameters, however, have clear biological meaning and, at least theoretically, are accessible to empirical measurement. Stock-recruitment relationships analogous to those presented here may therefore facilitate the construction of models that incorporate independent empirical data and environmental covariates for populations that are currently better described by phenomenological equations and represent an important step towards models that incorporate spatial structure in populations.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".