Does size matter? A cautionary experiment on overoptimism in length-based bioresource assessment
Bibliographic record
Abstract
Recently, there has been considerable progress in the development of neurolipofuscin-based age determination methods for crustacean stock assessment. Initial applications to lobster and crab fisheries suggest some important method-related differences between conventional length-based assessment parameter estimates and those derived with the new aging technique. Here, for the first time, we aim to clarify the basis for and implications of some of these discrepancies using an experimental fishery context. We estimate von Bertalanffy growth parameters (k and l∞), longevity (tmax), total and natural mortality (Z and M, respectively), maximum sustainable relative yield-per-recruit (MSY'/R), and the exploitation rate that produces MSY'/R (EMSY'/R) for a freshwater crayfish (Pacifastacus leniusculus) population by length–frequency analysis and tag–recapture (length-increment-at-length) and compare these results with simultaneous neurolipofuscin demographic estimates. Our central finding is that the length-based approaches are largely blind to the biological reality of asymptotic postmaturational growth, with the consequence that longevity is prone to underestimation, late growth trajectories and mortality rates to inflation, and sex differences to misjudgment. This inherent bias is likely to lead to pervasive undervaluing of potential yields and overly optimistic target exploitation rates that will heighten the risk of growth and recruitment overfishing. Neurolipofuscin offers a means of identifying and overcoming this important problem.
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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 | 0.263 | 0.410 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.016 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".