Science Response : Bocaccio Update in 2024
Notice bibliographique
Résumé
Bocaccio Rockfish (BOR, Sebastes paucispinis) was assessed in 2019 (Starr and Haigh 2022), and updated in 2021 (DFO 2022), using the Awatea catch-at-age stock assessment model platform tuned to six fishery-independent trawl survey series (spanning 1967–2021), a standardised commercial bottom trawl catch per unit effort (CPUE) series (1996–2012)1, annual estimates of commercial catch from two fisheries, and age composition data from the combined commercial trawl fishery and six surveys (two historical and four synoptic). The British Columbia (BC) outside coast model started from an assumed unfished equilibrium state in 1935. Three component base runs using a two-sex model were implemented in a Bayesian framework (using the Markov Chain Monte Carlo [MCMC] procedure) under scenarios that fixed natural mortality (M) to three levels (0.07, 0.08, 0.09) with the accumulator age (A) set to 50 years while estimating steepness of the stock-recruit function (h), catchability (q) for surveys and CPUE, and selectivity (µ) for four synoptic surveys and the commercial trawl fleet. These three runs were combined into a composite base case which explored the major axis of stock assessment uncertainty: natural mortality. The three selected M values encompassed an agreed plausible range for this parameter. A summary of the 2019 stock assessment can be found in Science Advisory Report 2020/025 and Proceedings 2021/014. Descriptions of earlier Bocaccio stock assessments (including reviews of this species by the Committee on the Status of Endangered Wildlife in Canada) can be found in Research Document 2022/001. The 2021 stock status update can be found in Science Response 2022/001. The 2019 stock assessment depicted a coastwide BOR stock experiencing a nearly continuous decline from the start of the population reconstruction in 1935, interrupted only by a period of arrested decline spanning the years 1970–86 resulting from a few moderate recruitment events in 1969, 1976, and 1978. The decline resumed in 1987, continuing until an extremely large recruitment event occurred in 2016, estimated by the 2019 model to be 44 times the long-term average recruitment (5% and 95% quantiles: 30 times, 58 times). The 2021 update revised this recruitment event to be even larger than that estimated in 2019, with a median of 60 times the long-term average (5% and 95% quantiles: 49 times, 68 times). The 2019 stock assessment predicted that the stock would recover (defined as being above the limit reference point, LRP = 0.4BMSY, with at least 95% probability) by the beginning of 2022. This was borne out for 2022 by the 2021 update, which also predicted that the stock would remain within the Healthy zone (defined as being above the upper stock reference, USR = 0.8BMSY, with at least 50% probability) for the next 10 years. While the 2021 update corroborated the optimism of the 2019 stock assessment, the technical working group in 2021 requested that another update be generated in two more years to again verify the robustness of the recovery. Within this time period, four additional synoptic survey index values became available, and new age data were also available. However, the primary empirical evidence for the progress of the large 2016 cohort remained the length frequency (LF) data. A second cohort, born in 2020, was also identified in the 2021 LF data, and evidence of its existence was flagged. This Science Response Report results from the regional peer review of March 28, 2024 on the Update of the 2019 Bocaccio (Sebastes paucispinis) Stock Assessment for British Columbia in 2024. 1The series was truncated at 2012 on the advice of the BOR Technical Working Group (TWG, 2019); it was felt that avoidance behaviour by the fleet would bias the indices after Total Allowable Catches were considerably reduced in 2013 in response to the COSEWIC ‘Endangered' designation.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,007 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,163 | 0,076 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».