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This paper deals with the diets of blue whiting Micromesistius poutassou (Risso 1810), hake Merluccius merluccius (L. 1758), horse mackerel Trachurus trachurus (L. 1758), and mackerel Scomber scombrus (L. 1758) off Portugal and explores variations in fish length, water depth, latitude and season. All four species feed on fish; however, hake and mackerel are the first and second most important predators, respectively, blue whiting being the most important fish prey for both species. The diets of blue whiting and horse mackerel are composed mainly of crustaceans. Diet variations according to predator fish size are more important than either latitude or depth. In the diets of blue whiting, hake and horse mackerel, prey importance increases with predator size. For blue whiting and horse mackerel, diet variations with fish length and water depth are correlated: small fish are closely associated with coastal areas where they feed on copepods and decapod larvae. Seasonality in the diet is apparent for blue whiting, hake and mackerel. For blue whiting, the decapod Pasiphaea sivado is the most important prey in summer and autumn, being replaced by the euphausid Meganyctiphanes norvegica in winter. In the diet of hake, seasonality was characterised by the major importance of Macroramphosus scolopax in autumn, whereas the diet of mackerel consisted of zooplankton in summer, fish and decapods in autumn and decapod larvae in winter. Seasonal changes in the diet of horse mackerel correspond to a higher diversity of prey in autumn compared to other seasons (although euphausids are the main prey in all seasons). Seasonality in feeding activity is not as marked for the other species as it is for horse mackerel; the percentage of empty stomachs of horse mackerel is greatest in winter, when spawning takes place at the Portuguese coast.

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BackgroundIt is widely accepted that the shift in case-fatality rate between waves during the 1918 influenza pandemic was due to a genetic change in the virus. In animal models, the infectious dose of influenza A virus was associated to the severity of disease which lead us to propose a new hypothesis. We propose that the increase in the case-fatality rate can be explained by the dynamics of disease and by a dose-dependent response mediated by the number of simultaneous contacts a susceptible person has with infectious ones.MethodsWe used a compartment model with seasonality, waning of immunity and a Holling type II function, to model simultaneous contacts between a susceptible person and infectious ones. In the model, infected persons having mild or severe illness depend both on the proportion of infectious persons in the population and on the level of simultaneous contacts between a susceptible and infectious persons. We further allowed for a high or low rate of waning immunity and volunteer isolation at different times of the epidemic.ResultsIn all scenarios, case-fatality rate was low during the first wave (Spring) due to a decrease in the effective reproduction number. The case-fatality rate in the second wave (Autumn) depended on the ratio between the number of severe cases to the number of mild cases since, for each 1000 mild infections only 4 deaths occurred whereas for 1000 severe infections there were 20 deaths. A third wave (late Winter) was dependent on the rate for waning immunity or on the introduction of new susceptible persons in the community. If a group of persons became voluntarily isolated and returned to the community some days latter, new waves occurred. For a fixed number of infected persons the overall case-fatality rate decreased as the number of waves increased. This is explained by the lower proportion of infectious individuals in each wave that prevented an increase in the number of severe infections and thus of the case-fatality rate.ConclusionThe increase on the proportion of infectious persons as a proxy for the increase of the infectious dose a susceptible person is exposed, as the epidemic develops, can explain the shift in case-fatality rate between waves during the 1918 influenza pandemic.

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The World Conference on Stock Assessment Methods (July 2013) included a workshop on testing assessment methods through simulations. The exercise was made up of two steps applied to datasets from 14 representative fish stocks from around the world.Step 1 involved applying stock assessments to datasets with varying degrees of effort dedicated to optimizing fit.Step 2 was applied to a subset of the stocks and involved characteristics of given model fits being used to generate pseudo-data with error. These pseudo-data were then provided to assessment modellers and fits to the pseudo-data provided consistency checks within (self-tests) and among (cross-tests) assessment models. Although trends in biomass were often similar across models, the scaling of absolute biomass was not consistent across models. Similar types of models tended to perform similarly (e.g. age based or production models). Self-testing and cross-testing of models are a useful diagnostic approach, and suggested that estimates in the most recent years of time-series were the least robust. Results from the simulation exercise provide a basis for guidance on future large-scale simulation experiments and demonstrate the need for strategic investments in the evaluation and development of stock assessment methods.

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