Olsen, E., Aanes, S., Mehl, S., Holst, J. C., Aglen, A., and Gjøsæter, H. 2010. Cod, haddock, saithe, herring, and capelin in the Barents Sea and adjacent waters: a review of the biological value of the area. – ICES Journal of Marine Science, 67: 87–101. Cod, haddock, saithe, herring, and capelin are the most important fish species in the Barents Sea and adjacent waters. Ecosystem-based management requires species-specific knowledge of the biological value and vulnerability throughout their life history and distributional range. For each of the five species and four annual quarters, the spawning (egg) areas, nursery areas for larvae and juveniles, and feeding grounds for adults are described and mapped. Areas of eggs (spawning) and larvae were the most important because these are the life stages when fish are most vulnerable to anthropogenic impact. The greatest overlap of spawning areas was from Røstbanken in the south to the Varanger Peninsula in the northeast, and overlap of larval distribution was more extensive.

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We examined whether differences in life-history characteristics can explain interspecific variation in stochastic population dynamics in nine marine fish species living in the Barents Sea system. After observation errors in population estimates were accounted for, temporal variability in natural mortality rate, annual recruitment, and population growth rate was negatively related to generation time. Mean natural mortality rate, annual recruitment, and population growth rate were lower in long-lived species than in short-lived species. Thus, important species-specific characteristics of the population dynamics were related to the species position along the slow-fast continuum of life-history variation. These relationships were further associated with interspecific differences in ecology: species at the fast end were mainly pelagic, with short generation times and high natural mortality, annual recruitment, and population growth rates, and also showed high temporal variability in those demographic traits. In contrast, species at the slow end were long-lived, deepwater species with low rates and reduced temporal variability in the same demographic traits. These interspecific relationships show that the life-history characteristics of a species can predict basic features of interspecific variation in population dynamical characteristics of marine fish, which should have implications for the choice of harvest strategy to facilitate sustainable yields.

Stochasticities in population dynamics as well as uncertainties in parameters often make it difficult to obtain reliable predictions of future population fluctuations. Here we use a long‐term data set to model the fluctuations of a Willow Ptarmigan (Lagopus lagopus) population in Central Sweden. We use this model to examine how different harvest strategies affect mean annual yield, and how these results are influenced by uncertainties in parameter estimates. Restricted proportional harvest (each hunter is allowed to shoot only a limited number of grouse per day) gave slightly higher mean annual yields than proportional threshold harvesting (harvesting only a fixed proportion of the difference between the estimated population size and the threshold when this difference is positive). However, variance in annual yield was reduced by restricted proportional harvesting because periods with low population size became shorter. Uncertainties in population parameters did not affect which strategy was optimal although those uncertainties strongly influenced the expected yield and the uncertainties in the hunting statistics. Inaccuracies in population projections are therefore important to estimate and to model when developing sustained harvest strategies for fluctuating populations.

Husebø, Å., Stenevik, E. K., Slotte, A., Fossum, P., Salthaug, A., Vikebø, F., Aanes, S., and Folkvord, A. 2009. Effects of hatching time on year-class strength in Norwegian spring-spawning herring (Clupea harengus). – ICES Journal of Marine Science, 66: 1710–1717. Effects of mean hatching date, post-hatching temperature, wintering temperature of adults, spawning stock size, and percentage of recruit spawners on larval survival in Norwegian spring-spawning herring (Clupea harengus) during the period 1987–2004 were analysed. In the final model, only hatching date proved to be significant. However, hatching date was itself negatively correlated with wintering temperature and positively correlated with the percentage of recruit spawners. This suggests indirect effects on larval survival, whereby low percentages of recruit spawners and high temperatures during gonad development lead to early spawning. Early hatching could be favourable for survival by allowing the larvae to drift away from areas where potential predators concentrate in spring, before predation pressure increases. Indirect support for this hypothesis was found in the activity of the purse-seine fishery for immature saithe (Pollachius virens) along the Norwegian coast. This fishery starts as soon as the saithe aggregate into large schools, which is presumed to reflect their feeding activity. The commercial catch data indicated that the saithe became active 2 months earlier in the area south of 67°N, than in areas to the north. Both field data and larval drift models confirmed that the majority of the early hatched larvae had passed across this border by that time of year.

The synchrony of population dynamics in space has important implications for ecological processes, for example affecting the spread of diseases, spatial distributions and risk of extinction. Here, we studied the relationship between spatial scaling in population dynamics and species position along the slow‐fast continuum of life history variation. Specifically, we explored how generation time, growth rate and mortality rate predicted the spatial scaling of abundance and yearly changes in abundance of eight marine fish species. Our results show that population dynamics of species' with ‘slow’ life histories are synchronised over greater distances than those of species with ‘fast’ life histories. These findings provide evidence for a relationship between the position of the species along the life history continuum and population dynamics in space, showing that the spatial distribution of abundance may be related to life history characteristics.

Abstract:A central problem when using commercial catch per unit effort (CPUE) as an index of fish stock abundance is that fishing vessels search for concentrations of fish. For a given stock abundance, CPUE may become high if the vessels succeed in finding patches of fish and low if the vessels distribute their catching operations more randomly. In this work, the relationship between catchability and two measures of the degree of spatial concentration of a trawl fleet (the fleet's spatial extent and the fleet's degree of spatial patchiness) is investigated for four different fish stocks. The catchability of northeast Arctic cod (Gadus morhua) is strongly related to the fleet's degree of spatial concentration, but the relationship is weaker for northeast Arctic haddock (Melanogrammus aeglefinus), and no relationships appear for two saithe (Pollachius virens) stocks. Our findings suggest that adjusting CPUE with a measure of the fleet's average degree of concentration relates CPUE more strongly with abundance for migratory stocks.Résumé : Les navires de pêche recherchent les concentrations de poissons, ce qui donne lieu à un problème sérieux lorsqu'on veut utiliser les données commerciales de prises par unité d'effort (CPUE) comme indice de l'abondance d'un stock de poissons. Pour une abondance donnée d'un stock, CPUE peut être élevé si les navires réussissent à trouver des regroupements de poissons et faible si les navires répartissent leurs opérations de pêche de façon plus aléatoire. Dans notre étude, nous examinons la relation entre la capturabilité et deux mesures du degré de concentration spatiale d'une flotte de chalutiers (la dispersion spatiale de la flotte et son degré de contagion) chez quatre stocks différents de poissons. La capturabilité des morues franches (Gadus morhua) du nord-est de l'Arctique est en forte corré-lation avec le degré de concentration spatiale de la flotte, mais la relation est plus faible dans le cas des aiglefins (Melanogrammus aeglefinus) du nord-est de l'Arctique; pour deux stocks de goberges (Pollachius virens), il n'y a pas de relation. Nos résultats indiquent que l'ajustement de CPUE à l'aide d'une mesure du degré moyen de concentration de la flotte établit une meilleure relation entre CPUE et l'abondance des stocks de poissons migrateurs.[Traduit par la Rédaction] Salthaug and Aanes 268 IntroductionCatch per unit effort (CPUE) from commercial fishing fleets is often used as an index of fish stock abundance. The traditional assumption is that the total catch (C) divided by the total effort (f) during a time period is proportional to the average population abundance (N) in the same period: C/f = qN, where q is the catchability coefficient (Ricker 1975;Gulland 1983). Catchability is in practice not constant between time periods, and the relationship between CPUE and stock abundance often seems to be nonlinear (Arreguín-Sánchez 1996;Harley et al. 2001). A major problem with commercial CPUE is that fishing vessels, to a varying degree, search for concentrations of fish rather th...

Models for fluctuations in size of fish stocks must include parameters that describe expected dynamics, as well as stochastic influences. In addition, reliable population projections also require assessments about the uncertainties in estimates of vital parameters. Here we develop an age-structured model of population dynamics based on catchat-age data and indices of abundance in which the natural and fishing mortality are separated in a Bayesian state-space model. Markov chain Monte Carlo methods are used to fit the model to the data. The model is fitted to a data set of 19 years for Northeast Arctic cod (Gadus morhua). By simulations of the fitted model we show that the model captures the dynamical pattern of natural mortality adequately, whereas the absolute size of natural mortality is difficult to estimate. Access to long time series of high-quality data are necessary for obtaining precise estimates of all the parameters in the model, but some parameters cannot be estimated without including some prior information. Nevertheless, our model demonstrates that temporal variability in natural mortality strongly affects perceived variability in stock sizes. Thus, using estimation procedures that neglect temporal fluctuations in natural mortality may therefore give biased estimates of fluctuations in fish stock sizes.Résumé : Les modèles fluctuation de la taille des stocks de poissons doivent inclure des paramètres qui décrivent la dynamique attendue ainsi que les influences stochastiques. De plus, des projections fiables de la population nécessitent une évaluation des incertitudes dans les estimations des paramètres vitaux. Nous mettons au point un modèle de la dynamique de la population structuré en fonction de l'âge qui est basé sur les données de captures en fonction de l'âge et les indices d'abondance dans lequel la mortalité naturelle et la mortalité due à la pêche sont séparées dans un modèle état-espace bayésien. Des méthodes de Monte Carlo par chaîne de Markov servent à ajuster le modèle aux données. Nous ajustons le modèle à une matrice de données récoltées sur 19 années chez la morue (Gadus morhua) du nord-est de l'Arctique. Par simulations du modèle ajusté, nous montrons que le modèle capture adéquatement le patron dynamique de la mortalité naturelle, bien que la taille absolue de la mortalité naturelle soit difficile à estimer. Il est nécessaire d'avoir accès à de longues séries chronologiques de données de haute qualité pour obtenir des estimations précises de tous les paramètres du modèle, mais certains paramètres ne peuvent être estimés sans l'inclusion de renseignements a priori. Néanmoins, notre modèle démontre que la variabilité temporelle de la mortalité naturelle affecte fortement la variabilité perçue des tailles des stocks. Ainsi, l'utilisation de procédures qui négligent les fluctuations temporelles de la mortalité naturelle peut donner des estimations erronées des fluctuations dans les tailles des stocks de poissons.[Traduit par la Rédaction] Aanes et al. 1142