An ASPIC Based Assessment of Redfish (S. mentella and S. fasciatus) in NAFO Divisions 3LN (assuming that the highest apparently sustained historical average level of catch is a sound proxy to MSY)
Notice bibliographique
Résumé
There are two species of redfish in Divisions 3L and 3N, the deep-sea redfish (Sebastes mentella) and the Acadian redfish (Sebastes fasciatus) that have been commercially fished and reported collectively as redfish in fishery statistics. Redfish in Div. 3LN is regarded as a management unit composed of two Grand Bank populations from those two very similar redfish species. The present ASPIC assessment is based on the logistic form of a non-equilibrium surplus production model (Schaeffer, 1954; Prager, 1994), adjusted to a standardized catch rate series (Power, 1997) and to most of the stratified-random bottom trawl surveys conducted in various years and seasons in Div. 3L and Div. 3N from 1978 onwards. Both CPUE and surveys were used with all observations of each series. \nThis assessment is not a follow up of the previous ones (Ávila de Melo et al., 2012 and 2010). The logistic Schaefer production model (1954) incorporated in ASPIC operating model (Prager, 1994) can not cope anymore with the most recent biomass increases observed in both spring and (mainly) autumn Canadian 3LN surveys, unless it is allowed to provide unrealistic assessment results. And continuing to strip off the highs of each one of these series, in order to get a picture in line to what is the perception of the stock history from commercial and survey data trends, is no longer a valid option, as reflected on the last STACFIS research recommendation on this matter (NAFO, 2012). \nBeing so, input has been reframed opening room to a new combination of Canadian autumn 3L and 3N surveys. The inclusion of the Spanish spring survey on Div. 3N and the removal of the historical CPUE series have also been considered. Two selected frameworks options have finally run with MSY kept constant at an initial starting guess, instead of being estimated by the model. Before entering the latest (2013) ASPIC Suite flow, the input selected from exploratory analysis was submitted to a sensitivity test in order to evaluate the robustness of the new framework against variability on random number seed, start user guesses for key model parameters and last year survey biomass. \nThe consistency of the new ASPIC assessment with their predecessors was checked by comparison of biomass and fishing mortality fit trajectories against previous ones from the 2012 and 2010 assessments. A 2014-2012 retrospective analysis was also performed with good results (small retro bias on relative biomass and fishing \n2 \nmortality in response to the general increase of the still standing survey series), and the assessment pursued successfully to bootstrap mode (again good consistency with previous results) and projections. \nA medium term management plan is finally proposed, based on bi-annual increases of the catch from the present TAC level of 6 500 t up to target catch/TAC of 18 100 t, the 2014 equilibrium yield from the present assessment, that should be in place by 2019-2020. This management plan allows, with a very high probability, that biomass is kept above Bmsy and fishing mortality below Fmsy.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,009 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 tête enseignante, 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 ».