Report of the Workshop on Implementation of Stock Reproductive Potential into Assessment and Management Advice for Harvested Marine Species
Bibliographic record
Abstract
A workshop on Implementation of Stock Reproductive Potential into Assessment and Management Advice for Harvested Marine Species that was held at the University of Aberdeen, Scotland on April 12-14, 2011.This Workshop was a key deliverable for the NAFO WG on Reproductive Potential.This workshop was held in conjunction with the EU COST Action Fish Reproduction and Fisheries (FRESH).The workshop was organized by Tara Marshall (UK), Joanne Morgan (Canada), Loretta O'Brien (USA), Iago Mosqueira (UK) and Santiago Cervino (Spain).The objectives were to provide workshop participants with expert advice in implementing information on reproductive potential into the assessment of their stocks and to review and recommend best practices for incorporating information about growth, maturation, condition and fecundity into management of harvested marine species.Invited presenters were Bridget Green (Australia), Adriaan Rijnsdorp (Netherlands), Peter Wright (UK), Coby Needle (UK), Paul Spencer (USA) and Liz Brooks (USA).Presentations were also made by Joanne Morgan and Santiago Cerviño (Spain).The presentations were made under four themes: Estimating Stock Reproductive Potential; Implementing Estimates into Assessments; Are we doing it better, worse or just differently?; and Coding It Up.The workshop concluded that it is clear that the incorporation of more complex indices of SRP can make a difference in the perception of stock status.Trends in biological parameters and the quality of the data on these parameters are both important components.Variation in weight at age and in maturity at age are both common and can have a large impact on perceived SRP.The collection of data on weight, maturity, sex ratio and fecundity is encouraged.Work on whether or not advice is improved by incorporating more biology into our estimates of SRP is only beginning.These studies should be continued and applied to more stocks and species with more varied reproductive strategies.One possible approach is likely to be within a management strategy evaluation context.This type of process would require the input of both modelling experts and experts in species biology.
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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 | 0.019 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".