Population genetic studies of horse mackerel Trachurus trecae and Trachurus trachurus capensis off Angola

Genetic variability of the Kunene horse mackerel Trachurus trecae and the Cape horse mackerel Trachurus trachurus capensis was examined using starch gel electrophoresis of enzymatic proteins on individuals collected along the Angolan coast. Six polymorphic enzyme loci were found in both species. The idh-2* locus displayed differences between the two species, and several alleles at different loci exhibited different allele frequencies between the two species, indicating that they are genetically different. Significant differences found in the distribution of allele frequencies between Kunene horse mackerel from the Benguela region of Angola indicated that this species consist of more than one randomly mating population in Angolan waters.Keywords: Angolan coast, horse mackerel, isozymes, population studies, species identificationAfrican Journal of Marine Science 2002, 24: 49–5

Genome-Wide association study (GWAS) for growth rate and age at sexual maturation in atlantic salmon (Salmo salar)

Early sexual maturation is considered a serious drawback for Atlantic salmon aquaculture as it retards growth, increases production times and affects flesh quality. Although both growth and sexual maturation are thought to be complex processes controlled by several genetic and environmental factors, selection for these traits has been continuously accomplished since the beginning of Atlantic salmon selective breeding programs. In this genome-wide association study (GWAS) we used a 6.5K single-nucleotide polymorphism (SNP) array to genotype ∼480 individuals from the Cermaq Canada broodstock program and search for SNPs associated with growth and age at sexual maturation. Using a mixed model approach we identified markers showing a significant association with growth, grilsing (early sexual maturation) and late sexual maturation. The most significant associations were found for grilsing, with markers located in Ssa10, Ssa02, Ssa13, Ssa25 and Ssa12, and for late maturation with markers located in Ssa28, Ssa01 and Ssa21. A lower level of association was detected with growth on Ssa13. Candidate genes, which were linked to these genetic markers, were identified and some of them show a direct relationship with developmental processes, especially for those in association with sexual maturation. However, the relatively low power to detect genetic markers associated with growth (days to 5 kg) in this GWAS indicates the need to use a higher density SNP array in order to overcome the low levels of linkage disequilibrium observed in Atlantic salmon before the information can be incorporated into a selective breeding program

Evaluation of EnKF and Variants on the PUNQ-S3 Case Évaluation de l’EnKF et des variantes du cas PUNQ-S3

Over the last decade the ensemble Kalman filter (EnKF) has attracted attention as a promising method for solving the reservoir history matching problem: updating model parameters so that the model output matches the measured production data. The method possesses unique qualities, such as; it provides real-time updates and uncertainty quantification of the estimate, it can estimate any physical property at hand and it is easy to implement. The method does, however, have its limitations; in particular, it is derived based on an assumption of a Gaussian distribution of variables and measurement errors. Several refinements have been proposed to overcome the shortcomings of the EnKF. These refinements are, however, mainly tested on synthetic cases addressing one shortcoming at a time, not containing or combining the complexity and the high nonlinearity of a real field case. In this paper, we investigate some of the refined methods on a nonlinear reservoir, the 3D, three-phase, PUNQ-S3 model. We compare the performance of the original EnKF with the performance of the ensemble square root filter (EnSRF), an EnKF method with localization, which is named the hierarchical ensemble Kalman filter (HEnKF) and the newly proposed Adaptive Gaussian Mixture filter (AGM). To the best of our knowledge, this is the first time the EnKF and the EnSRF have been compared on a high-dimensional nonlinear field case. Overall, we see that the AGM and HEnKF work better than the EnSRF and EnKF. The EnSRF seems to have a slightly better performance than the EnKF. However, the introduction of a localization procedure (as in the HEnKF) seems to be much more influential than replacing the EnKF with the EnSRF. Comparing the top two methods, the AGM is preferable over the HEnKF, both when it comes to preserving the initial geology of the ensemble and to the consistency of the predictions. <br> Au cours de la dernière décennie, le filtre de Kalman d’Ensemble (EnKF, Ensemble Kalman Filter) a attiré l’attention en tant que méthode prometteuse pour résoudre le problème de calage d’historique de réservoir, à savoir l’actualisation des paramètres de modèle de sorte que la sortie de modèle corresponde aux données de production mesurées. La méthode présente des qualités uniques dans la mesure où elle procure des actualisations en temps réel et une quantification d’incertitude de l’estimation, peut estimer toute propriété physique disponible, et est facile à mettre en œuvre. Elle présente toutefois ses limitations : en particulier, elle est fondée sur une hypothèse d’une distribution gaussienne de variables et d’erreurs de mesure. Plusieurs affinements ont été proposés pour surmonter les points faibles de l’EnKF. Ces affinements sont, toutefois, principalement testés sur des cas synthétiques concernant un point faible à la fois, ne contenant ou ne combinant pas la complexité et la non-linéarité élevée d’un cas de champ réel. Dans cet article, nous étudions certaines des méthodes affinées sur un réservoir non linéaire, le modèle 3D, triphasé, PUNQ-S3. Nous comparons la performance de l’EnKF original avec la performance du filtre racine carrée d’ensemble (EnSRF, ensemble square root filter), une méthode EnKF avec localisation désignée sous le nom de filtre de Kalman d’ensemble hiérarchique (HEnKF, hierarchical ensemble Kalman filter), et le filtre mélange gaussien adaptatif (AGM, adaptive Gaussian mixture). Autant que nous sachions, il s’agit de la première fois que l’EnKF et l’EnSRF ont été comparés dans un cas de champ non linéaire de dimension élevée. Dans l’ensemble, nous constatons que l’AGM et le HEnKF fonctionnent mieux que l’EnSRF et l’EnKF. L’EnSRF semble présenter une performance légèrement meilleure que l’EnKF. Toutefois, l’introduction d’une procédure de localisation (telle que dans le HEnKF) semble avoir beaucoup plus d’influence que le remplacement de l’EnKF par l’EnSRF. En comparant les deux meilleures méthodes, l’AGM est préférable à l’HEnKF, à la fois quand il s’agit de préserver la géologie initiale de l’ensemble et pour la cohérence des prédictions

Optimal management of renewable resources with Darwinian selection induced by harvesting

We present a bioeconomic analysis of the optimal long-term management of a genetic resource in the presence of selective harvesting. It is assumed that individuals possessing a particular gene have a lower natural mortality rate and are more valuable to capture. Highly selective harvesting may cause such a gene to lose its fitness advantage, and hence change the evolutionary path of the species. Results indicate that in a zero-cost harvesting regime, the decision to preserve the valuable gene depends on the natural rate of selection against less valuable individuals and the interest rate. On the other hand, the decision to let the less valuable gene become a significant fraction of the genes depends only on biological parameters. If marginal costs are positive, it is never optimal to let a valuable gene become extinct. Further, for some parameter values, the system exhibits multiple equilibriums. Therefore, optimal regulation may depend on initial conditions.