Interannual variations in spawning time, defined as the peak in egg abundance, of cod (Gadus morhua) in the Bornholm Basin, Baltic Sea, were analysed. Effects of water temperature, size and age structure of the spawning stock, abundance of food, and timing of spawning in preceding years were studied as possible determinants of annual spawning time. During the 1970s and late 1980s, peak spawning took place between the end of April and mid-June. A remarkable shift in the timing of spawning to the end of July was observed in the 1990s. The key factors governing the timing of spawning are water temperature during the period of gonadal maturation, density-dependent processes related to the size of the spawning stock, and food availability. The age structure of the spawning stock is suggested to have an additional effect. A high proportion of first-time spawners and decreasing water temperature have caused progressively delayed spawning since the early 1990s. Late spawning involves several processes that are detrimental to the survival of the early life stages. Recruitment in the mid-1990s was below what could be expected from spawning stock biomass and favourable hydrographic conditions. It is therefore suggested that the rebuilding of the Baltic cod stock could be improved by reduced fishing pressure in spring on early spawners. 2000 International Council for the Exploration of the Sea

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Traditionally, multiple linear regression models (hlLR) are used to predict the somatic production/biomass ( P / B ) ratio of animal populatlons from empirical data of population parameters and environmental variables. Based on data from 899 benthic invertebrate populations, we compared the prediction of PIB by MLR models and by Artlflclal Neural Networks (ANN). The latter showed a slightly (about 6%) but significantly better performance. The accuracy of both approaches was low at the population level, but both MLR and ANN may be used to estimate production and productivity of larger population assemblages such as communities.

A modified version of the von Bertalanffy growth function (VBGF) is proposed in which a sine wave modifies a standard version of the VBGF, enabling a smooth transition between rapid summer growth and a variable period of zero growth (in length) during winter or during the dry season for aestivating fishes. The key features of a nonlinear routine for fitting this new model are also presented, with emphasis on the estimation of the period of zero growth. Application examples, to Salmo salar and Trisopterus esmarkii, are presented.

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