Search

Selectivity is a key parameter in stock assessments that describes how fisheries interact with different ages and sizes of fish. It is usually confounded with other processes (e.g., natural mortality and recruitment) in stock assessments and the assumption of selectivity can strongly affect stock assessment outcome. Here, we introduce a new semi-parametric selectivity method, which we implement and test in Stock Synthesis. This selectivity method includes a parametric component and an autocorrelated nonparametric component consisting of deviations from the parametric component. We explore the new selectivity method using two simulation experiments, which show that the two autocorrelation parameters for selectivity deviations of data-rich fisheries are estimable using either mixed-effect or simpler sample-based algorithms. When selectivity deviations of a data-rich fishery are highly autocorrelated, using the new method to estimate the two autocorrelation parameters leads to more precise estimations of spawning biomass and fully selected fishing mortality. However, this new method fails to improve model performance in low data quality cases where measurement error in the data overwhelms the pattern caused by the autocorrelated process. Finally, we use a case study involving North Sea herring (Clupea harengus) to show that our new method substantially reduces autocorrelations in the Pearson residuals in fit to age composition data.La selectivity est un parametre cle des evaluations de stocks qui decrit comment les peches interagissent avec differents ages et differentes tailles de poissons. Elle est habituellement confondue avec d'autres processus (p. ex. mortalite naturelle et recrutement) dans les evaluations de stocks, et l'hypothese de la selectivity peut avoir une importante incidence sur le resultat de revaluation de stocks. Nous presentons une nouvelle methode de selectivite semi-parametrique que nous appliquons et validons dans Stock Synthesis. Cette methode de selectivite comprend une composante parametrique et une composante non parametrique autocorrelee qui est constituee d'ecarts par rapport a la composante parametrique. Nous explorons la nouvelle methode de selectivite en utilisant deux experiences de simulation qui montrent que les deux parametres d'autocorrelation pour les ecarts de selectivite de peches pour lesquelles les donnees sont abondantes peuvent etre estimes en utilisant des algorithmes a effets mixtes ou des algorithmes plus simples bases sur les echantillons. Quand les ecarts de selectivite d'une peche aux donnees abondantes sont fortement autocorreles, l'utilisation de la nouvelle methode pour estimer les deux parametres d'autocorrelation produit des estimations plus precises de la biomasse reproductrice et de la mortalite par peche entierement selectionnee. Cette nouvelle methode n'ameliore toutefois pas la performance des modeles dans les cas de faible qualite des donnees pour lesquels l'erreur de mesurage dans les donnees masque le motif resultant du processus autocorrele. Enfin, nous utilisons une etude de cas du hareng (Clupea harengus) de la mer du Nord pour demontrer que notre nouvelle methode reduit sensiblement les autocorrelations dans les residus de Pearson dans des donnees ajustees a la composition par age. [Traduit par la Redaction], IntroductionIn stock assessment models, selectivity is usually referred to as the combination of contact selectivity and population selectivity. It describes how relative fishing effectiveness varies with the age or size [...]

The justification for incorporating environmental effects into fisheries stock assessment models has been investigated and debated for a long time. Recently, a state-space age-structured assessment model which includes the stochastic change in the environmental covariate over time and its effect on recruitment was developed for Southern New England-Mid Atlantic yellowtail flounder ( Limanda ferruginea). In this paper, we first investigated the correlations of environmental covariates with Southern New England-Mid Atlantic yellowtail flounder recruitment deviations. The covariate that was most strongly correlated with the recruitment deviations was then incorporated into the state-space model and alternative effects on the stock-recruit relationship were estimated and compared. For the model that performed best as measured by Akaike information criterion, we also compared the estimates and predictions of various population attributes and biological reference points with those from an otherwise identical model without the environmental covariate in the stock-recruit function. We found that the estimates of population parameters are similar for the two models but the predictions differed substantially. To evaluate which model provided more reliable predictions, we quantitatively compared the prediction skill of the two models by generating two series of retrospective predictions. Comparison of the retrospective prediction pattern suggested that from an average point of view, the environmentally explicit model can provide more accurate near-term recruitment predictions especially the one year ahead recruitment prediction. However, the accuracy of the near-term recruitment prediction from the environmentally explicit model was largely determined by the accuracy of the corresponding environment prediction the model provides. [ABSTRACT FROM AUTHOR]

Multiple osteochondroma (MO), also known as multiple hereditary exostoses, is an autosomal dominant skeletal disorder with characteristic multiple cartilage-capped tumours (osteochondromas or exostoses) growing outward from the metaphyseal region of the long tubular bones. Mutations in exostosin glycosyltransferase 1 ( EXT1 ) or EXT2 are the most commonly associated mutations with MO and are responsible for 70-95% of cases. In the present study, a genetic analysis was performed on a large family with MO using polymerase chain reaction and direct DNA sequencing of the entire coding regions of EXT1 and EXT2 . Sanger sequencing identified a novel heterozygous frameshift mutation, c.119_120delCT (p.Thr40ArgfsX15), in exon 2 of the EXT2 gene in the proband and all other affected individuals, while this deleterious mutation was not detected in the healthy family members and normal controls. The c.119_120delCT mutation is located in the transmembrane region of the EXT2 protein and results in a truncated EXT2 protein lacking 665 amino acids at the C-terminus, which includes the critical exostosin and glycosyltransferase family 64 domains. Thus, the present study identified a novel causative frameshift mutation in EXT2 from a large MO family. This study is useful for extending the known mutational spectrum of EXT2 , for understanding the genetic basis of MO in the patients studied, and for further application of mutation screening in the genetic counseling and subsequent prenatal diagnosis of this family.