Age composition data provides the key information necessary to effectively manage fisheries. The proposal provides a mechanism where age composition data can be gained using length frequency data and age composition data from different years and sampling events, which has previously been impossible. The benefits will be a reduced need for production ageing, more timely age composition data and the ability to construct age composition data from historical length frequency data where no samples were collected for ageing.

Currently the Age-Length Key (ALK) is the most widely used numerical method for assessing the age composition in a large sample of length-frequency data. However, the application of ageing data in this approach is restricted to the original sample of length distribution (ageing data from the same year the length-frequency sample is taken). Due to this severe limitation, the ageing information must be regenerated for each new data sample. Using the Fredholm First Kind equations, previous years ageing data can be used to generate the underlying age composition from the current length-frequency data. Furthermore, the ageing data may be added to include many years, improving the robustness of the statistic which can then be used to decompose the underlying age distribution from the given length frequency.

As noted by a number of referees, the major problem with the current methods is variable recruitment. We have demonstrated that the technique is tolerant to the most extreme changes in age frequency (see accompanying text). These extreme changes in age frequency are greater than any changes that could occur naturally through recruitment. The issue of variable growth may affect the efficacy of the approach, but to our knowledge, has only been observed in two species. These are black bream and blue grenadier. It is proposed that the technique be demonstrated on blue grenadier in the first year.

The cost of collecting ageing data is high, with approximately $150,000 spent each year on ageing samples from commercially important species within the South East Fishery. Due to the cost, the number of species aged is not optimal and species are prioritised on a scientific and social-political basis. The cost-benefit of applying this approach is intuitively a large reduction in cost of ageing to industry and more timely information on the age structure of the population. A formal cost benefit analyses will need to be conducted on a species by species basis. This is a function of different cost structures for ageing different species, different numbers of samples that need to aged for each species. These different numbers of estimates that need to be made for each species is primarily due to longevity and stock structuring.

The age-structured data obtained from this project will benefit the South East Trawl Fishery, the Great Australian Bight Trawl Fishery and the Gillnet, Hook and Trap Fishery which are supported by The Integrated Scientific Monitoring Program (ISMP) and various other stock assessment programs that rely on age-structured data.

Further, age composition data will be able to be reconstructed historically from species where samples were not aged but length-frequency data were collected. This will enable age-structured population analysis where the lack of ageing data prevented these stock assessment techniques from being previously used. The net effect of this approach is to greatly improve the knowledge base from which species are managed. One of key advantages of this approach is, if successful, will at the very least compliment current methods and provide temporal and spatial coverage of age composition information which is currently cost prohibitive and only collected for a few, high value species.

The implication of a technique that can provide age-composition data free from the restriction of those associated with the ALK is more cost-effective resource management.

The proposal has been developed in two parts, the first component is a 'Proof of Concept Study' where the use of the Fredholm First Kind Equations to provide age compositions from length frequency data will be further examined. If this is not assessed as successful in a workshop environment, the project will be terminated at the end of the first year. The second and third year will examine a broad range of species.

Current age determination methods, even when aided by image analysis software still depend on interpretation by an experienced "reader". The process of ageing is also laborious, time consuming and hence, relatively expensive. For production ageing, where there is an ongoing requirement for age estimates, there is a problem of consistency of interpretation. At present, when readers change, there is a substantial training and verification period needed to ensure that the new reader is interpreting otolith structure in a consistent and correct manner. Automatic ageing would have the primary advantage of being a far more objective method than is possible with even the best training, reducing discrepancies both between readers and organisations. This factor will increase the precision of estimates and therefore provide greater confidence for the stock assessment process. Benefits associated with the development of this technique also include the reduced sample processing time which would increase the number of samples able to be processed and hence, reduce the cost.

The pilot project which has been completed has demonstrated the potential for artificial neural networks to objectively and consistently classify samples of some species. With refinements of the system, it should be applicable to any species for which production ageing is required.