Implications of protracted recruitment for perception of the spawnerrecruit relationship
Bibliographic record
Abstract
In European lobster, Homarus gammarus, wide growth variation means that annual recruitment to a fishery (individuals reaching legal size in the same year) consists of at least six year-classes (individuals hatching in the same year). In this paper, a simple simulation analysis is used to explore the effects of uncertainty about the specifics of this protracted recruitment pattern on the way that we perceive the spawnerrecruit relationship. In the simulation, if the age range of recruits is underestimated or a simple correction for growth variation is applied by averaging numbers of recruits across years, a spawnerrecruit relationship with artefactual curvature and noise arises. Growth variability is typical in animal populations and problems with protracted recruitment may occur in any situation where recruitment is based on size. Asymptotic spawnerrecruit curves may not necessarily reflect density-dependent compensatory mortality and resilience to harvesting. The evidence presented here has important management implications for lobster and other exploited species.
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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 | 0.002 | 0.036 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".