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Abstract
Fish stocking is a popular management tool for freshwater and marine fisheries and is commonly used in impoundments to create or maintain recreational fisheries. The densities at which fish are stocked in these systems, however, often lack an ecological basis. The general aim of this thesis was to develop a stocking model which calculates stocking densities appropriate for an impoundment’s productive capacity. The Australian bass is a commonly stocked sport-fish in Australian impoundments and is used in this study as a model organism to demonstrate how species ecology (Chapters 2 and 3), population dynamics (Chapters 4 and 5), and modelling (Chapter 6), can be combined to place stocking densities in a predictive, ecological framework.
Analyses of the diet and habitat use of Australian bass indicated it is an adaptive species, exhibiting strong inter-individual variation in the use of the dietary and spatial niches, and therefore an ideal candidate for stocking in the hydrologically variable impoundments of Australia. The varied use of the spatial habitat justified the use of a production-based stocking model, given that food is likely to be the limiting resource, rather than access to a key habitat type. The dietary analysis also determined that zooplankton and phytoplankton were suitable sources of production for input into the stocking model. Annual and stochastic fluctuations in the volume of available habitat were observed, driven mainly by stratification and variable rainfall respectively. This justified the addition of a spatial component to the stocking model, which influences stocking density by altering both the total amount of production in the impoundment and the amount that is actually available to stocked fish.
Quantitative methods of assessing the potential capacity of environments for stocked fish were reviewed, including methods for estimating carrying capacity. It was deduced that carrying capacity is a useful reference for determining population status and for calculating stocking densities that should not be exceeded, but should probably not be the target for most stocked fisheries, due to the increase in density-dependent losses when approaching this point. Production and self-thinning models were also reviewed and their use for determining stocking densities demonstrated. Self thinning (i.e. the body-mass – abundance relationship) was found to be useful for heavily stocked closed systems and fisheries with high exploitation rates. A manipulative experiment with Australian bass fingerlings in tanks tested this use of self-thinning theory. The experiment showed that the body-mass – abundance relationship in Australian bass generally matched theoretical predictions for food-limited populations, and that simple feeding experiments can determine the ontogeny of food-limited consumption. It was also demonstrated that density-dependent energy allocation can significantly alter the relationship, which is a novel finding with important theoretical implications for the role of group dynamics in population regulation.
A stocking model incorporating trophic and dynamic-pool components estimated stocking densities in impoundments, consolidating much of the ecological data and theory of previous chapters. Stocking density was calculated by equating the energetic demand of stocked fish with an impoundment’s available surplus productivity. Monte-Carlo simulations were used to calculate probability distributions of stocking density for three New South Wales impoundments. A range of possible stocking densities was estimated for each impoundment, according to the minimum, average and maximum consumption rates by Australian bass. This approach demonstrates that stocking density can depend as much on a particular fishery’s objectives as the environment’s productive capacity. Similarity of modelled and actual estimates of population size offers support to the model’s accuracy. Variation in model outputs between impoundments and seasons highlights the need for ecologically-based stocking densities to be site-specific and demonstrates the value of incorporating the seasonality of consumption, production, and habitat availability.