The NSW oyster industry is one of the states oldest and most valuable fishery, with a farm gate value of more than $27 million in 1994/ 5. It has an impressive history covering more than a hundred years of farming the native Sydney rock oyster Saccostrea commercialis but has experienced a decline since its record year of 1976 / 7 (Chapter 2). Nevertheless the N SW industry produced more than 60% of the country's oyster output in 1994/5.
A strategic R & D plan covering six key project areas has been produced to help transform the NSW oyster industry into a united, forward looking industry, producing a range of quality assured oysters and other products, marketing in a more collaborative and profitable manner.
It is recognised by industry that the yield currently obtained from the western rock lobster fishery cannot be enhanced by increasing exploitation without also reducing the breeding stock to an unacceptable level. The value of the fishery can only be increased by reducing costs or by increasing the value of the catch. Modelling of the fishery is required to investigate the potential improvement in value that might be obtained from an optimal set of management controls designed to improve market prices through controlling the supply of lobsters to the market both within and among fishing seasons. The ability to predict future catches based on puerulus settlement indices offers the rock lobster industry in Western Australia a unique opportunity to improve prices by varying the exploitation rate between seasons in order to more closely match market demand.
A modelling project to address this need will require the development of a more statistically sound model of the lobster fishery than was provided by the descriptive model developed by Walters et al. (1993). This will benefit the participants in the fishery by providing an understanding of the uncertainties associated with model predictions, and the validity of the new model when applied to different sectors of the fishery. The earlier model used information from only a small subset of the data available from the fishery, and the new model will utilise far more of the available data, thus providing a more robust description of the rock lobster fishery.
Development of the proposed model is seen as an essential and strategic element of the research programme for this fishery.
The fishery for the western rock lobster (Panulirus cygnus) is Western Australia’s most important single species fishery, and yields an average annual catch of 10,500 to 11,000 tonnes valued at between $200 and $300 million at the point of landing. With a high level of exploitation and a product with a high export value, the need was recognised for the development of appropriate models to evaluate alternative management strategies. This study describes the models that were developed.
A number of outcomes of the study may be identified. A size-structured model was developed for the P. cygnus fishery. The monthly growth transition matrices required for this model were estimated from tagging data. Data on beach prices received for lobster and costs of bait, fuel, gear and crew were collected for 1998/99. Examples of the use of the size-structured model to explore alternative management strategies, and the results of a calculation of the net relative value of the catch estimated by the size-structured model are presented. The relationship between vulnerability and carapace length of the lobsters was investigated, and the concentration of fishing effort on locations and depths where the smaller lobsters are located was found to be a major factor affecting the size composition of the catch. An age-structured model of the fishery was also developed. This model was used to investigate the effect of the management changes introduced to the fishery in 1993/94. An example of the use of this age-structured model to explore the consequences of an alternative management strategy and the uncertainty of the resulting estimates of egg production under the alternative strategies was presented.
Keywords: lobster, model, stock assessment, economics
To assess whether the ESD and MEE objectives are met there is a need to determine the status of prawns stocks in the NPF and to develop guidelines to define whether the present status of the stocks may require management actions. It is important to precisely define what population parameters should be monitored and what biological reference points should these parameters be compared in order to determine whether management action is required. The Northern Prawn Fishery Assessment Group (NPFAG) has identified that spawning stock biomass and standardised fishing effort are the two most important indicators for target stocks in the NPF. The NPFAG has also established that targets and limits for these indicators need to be set and reassessed as new information is collected. The NPFAG has also recommended that future advice provided to them by researchers should include an explicit measurement of the probabilities that each of these targets may be exceeded. Calculation of such probabilities requires formal risk analysis to be carried out as part of the stock assessment.
Additionally, there are a number of future management options that have been recently considered by NORMAC. These include reductions of pool of the licensing units used in the NPF, (A-units, representing vessel length and engine power), gear restrictions as well as further seasonal and spatial closures. Although the operational implications of adopting some of these options have been the subject of NORMAC discussions, the scientific evaluation of options is not carried out in a structured framework but rather as individual assessments as different options are proposed by NORMAC. There is a need to establish a structured framework for management strategy evaluation so that the NPFAG and NORMAC can compare different options in a consistent way. This framework for management strategy evaluation should allow for the integration of risk analysis into the evaluation of management options. The consequences of each management strategy should be quantified and evaluated against the indicator of performance established by the NPFAG. The evaluation should include the estimation of the probability that, in the future, certain undesirable or desirable states of the stock are reached.