Crustacean fisheries (such as those targeting rock losters, crabs and prawns) contribute more than a billion dollars to the Australian economy annually. Population models for stocks that support these fisheries often rely on indirect measures of age (e.g. size-modal analysis) which can confound estimates of other life history parameters and introduce errors into the modelling process.

A method to directly age commercially exploited crustaceans (by counting growth bands in calcified regions of the eyestalk and/or the gastric mill) has been developed by Dr Raouf Kalida at the University of New Brunswick, Canada and published last year. His technique has the potential to substantially improve the precision of stock assessments on crustacean fisheries around the world.

There is a need to transfer this technology to fisheries research agencies in Australia so that we can better understand growth patterns in crustaceans, reduce uncertainty in crustacean population models and provide better advice to fishery managers. This in turn should lead to improved management practices and greater stability in the national crustacean harvest, noting that production by several crustacean fisheries is also strongly linked to environmental factors.

The most effective means to address this need is to host Dr Kalida in Australia for a period of time to share his knowledge of crustacean ageing and provide guidance to domestic fisheries scientists working in the field. The proposed project aligns with a number of FRDC Strategic Priority Areas including: Theme 4 (Ecologically Sustainable Development), Theme 13 (Innovation Skills) and Theme 14 (Extension and Adoption).

Uncertainty poses a major challenge to the management and utilisation of marine fish resources. Significant efforts are made by fishing nations to estimate numbers and condition of exploited fish stocks, but assessments frequently bring unexpected results that range from relatively small shifts from former prognoses to changes of a significant and potentially detrimental magnitude. Such errors may be due to biased calculations or unaccounted causes of mortality, but can also stem from unforeseen changes in fish distribution or behaviour which remain unaccounted for.

To meet this challenge, SARDI and the University of Iceland aim to work together towards a solution that involves construction of a modeling environment, a “Multiverse”, which is a 3D modelled and data assimilated world of ocean physics and the living organism that can be evaluated with hindcasts and used to produce short- and long-term forecasts, as well as to test and answer key questions on climate change and fisheries monitoring/management.

Such an approach may be a suitable method for integrating the diverse data sets currently being proposed to be collected as part of a large-scale science program to explore mining exploration (and subsequent impacts) in the Great Australian Bight (GAB).

The collaboration will benefit from the complementary nature of the research groups from the highly data rich region of the North Atlantic to the relatively data poor environment of the GAB. The collaboration will facilitate discussion around the concept and potential for its application in an Australian context.