2 resultados para Gallen-Kallela, Akseli, 1865-1931.

em eResearch Archive - Queensland Department of Agriculture


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Linear mixed models were used to test the null hypothesis that there were no differences between seasons and locations in the reproductive potential of female eastern king prawns, Melicertus plebejus along the east coast of Australia. Three samples were collected in each season between autumn 1991 and winter 1992 (inclusive). Females capable of spawning were found at all locations but proportions were greater in lower than higher latitudes. Females capable of spawning were not found at the southern (highest latitude) most location in all seasons. There was a significant interaction in reproductive potential between seasons and locations suggesting that patterns among seasons differed between locations and vice versa. Reproductive potential was greatest amongst the northern (lower latitudes) most locations and was greatest in autumn at these locations. Seasonal patterns were less pronounced further south (higher latitudes). The length composition of females in catches differed between locations with more larger prawns found in samples from northern locations. The challenge that remains is to quantify the oceanic sources of larvae that contribute to recruitment in each nursery area and the estuarine sources of juveniles that contribute adults back to the effective spawning stock. Maintaining the effective spawning stock and important nursery areas are crucial to the sustainability of this resource.

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Stochastic growth models were fitted to length-increment data of eastern king prawns, Melicertus plebejus (Hess, 1865), tagged across eastern Australia. The estimated growth parameters and growth transition matrix are for each sex representative of the species' geographical distribution. Our study explicitly displays the stochastic nature of prawn growth. Capturing length-increment growth heterogeneity for short-lived exploited species such as prawns that cannot be readily aged is essential for length-based modelling and improved management.