Harvest control rules: beyond F<sub>MSY</sub> for an ecosystem approach to fisheries?
Bibliographic record
Abstract
No abstracts are to be cited without prior reference to the author.Conveners: Didier Gascuel (France), Lisa Borges (Belgium), Dave Reid (Ireland).CM 2016/Q:147. A multi-stock harvest control rule as a step towards an ecosystem based fisheries management. Dorleta Garcia, Raúl Prellezo, Agurtzane Urtizberea, Sonia SanchezCM 2016/Q:525. A time-integrated approach to evaluating fishery management performance. Sarah R. Stein, Patrick D. Lynch, Richard D. MethotCM 2016/Q:378. Aged and children first! Challenges in the development of a new selectivity concept for trawl fisheries. Stefanie Haase, Juan Santos, Annemarie Schütz, Bernd Mieske, Daniel StepputtiCM 2016/Q:359. Are FMSY ranges a promising or a dangerous option?. Clara Ulrich, Anna RindorfCM 2016/Q:541. Beyond FMSY in the Barents Sea and beyond. Daniel Howell, Gjert Endre Dingør, Åge Fotland, Benjamin Planque, Asgeir Aglen, Matthias Bernreuther Alexy Russikh, Anatoli Chetyrkin, Ross Tallman Elvar Hallfredsson, Sigbjørn Mehl, Sergey Tarakanov, Yuri Kovalev, Natalia Yaragina, Tone Vollen, Dmitry Vasilyev, Alf Harbitz, Arved Staby, Bjarte BogstadCM 2016/Q:144. Developing an assessment framework for Goose Barnacles (Pollicipes polymerus) incorporating advancements in technology and local ecological knowledge in Clayoquot Sound off the west coast of Canada. Candace Picco, Alex GagneCM 2016/Q:504. Ecological implications of the Landing Obligation on balanced harvesting in Mediterranean fisheries. M. Hidalgo, L. Rueda, B. Guijarro, E. Massutí, A. QuetglasCM 2016/Q:393. Effects of herring fishing strategies on a modelled Northeast Pacific ecosystem. Szymon Surma, Tony J. PitcherCM 2016/Q:533. Effects of trophic and technical interactions on the definition of MSY reference points in a mixed-fisheries ecosystem. Morgane Travers-Trolet, Pierre Bourdaud, Youen VermardCM 2016/Q:77. Evaluating progress to restore EU fish populations in line with the CFP. Markus KniggeCM 2016/Q:118. Fisheries management under uncertainty using a hybrid instrument. Helge BerglannCM 2016/Q:119. Interaction between seabirds and trawlers: preliminary insights from the Bay of Biscay. Arkaitz Pedrajas, Maite Louzao, Iñaki Oyarzabal, Iñigo Krug, Mikel Basterretxea, Jon RuizCM 2016/Q:495. New Harvest Control Rules for minimizing the impact of fishing in Europe. Didier Gascuel, Rainer FroeseCM 2016/Q:340. Targeting sustainable salmon fisheries – what to aim at?. Maija Holma, Marko Lindroos, Soile Oinonen, Atso RomakkaniemiCM 2016/Q:55. The application of pretty good yield ranges to the North Sea multispecies fishery. Robert B. Thorpe, Simon JenningsCM 2016/Q:102. The MSY objective - the EU’s progress so far, and raising the bar. Liane Veitch, Heather Hamilton, Jenni Grossmann
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.013 | 0.018 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.068 | 0.022 |
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".