Effect of rainfall as a component of climate change on estuarine fish production in Queensland, Australia

The speculation that climate change may impact on sustainable fish production suggests a need to understand how these effects influence fish catch on a broad scale. With a gross annual value of A$ 2.2 billion, the fishing industry is a significant primary industry in Australia. Many commercially important fish species use estuarine habitats such as mangroves, tidal flats and seagrass beds as nurseries or breeding grounds and have lifecycles correlated to rainfall and temperature patterns. Correlation of catches of mullet (e.g. Mugil cephalus) and barramundi (Lates calcarifer) with rainfall suggests that fisheries may be sensitive to effects of climate change. This work reviews key commercial fish and crustacean species and their link to estuaries and climate parameters. A conceptual model demonstrates ecological and biophysical links of estuarine habitats that influences capture fisheries production. The difficulty involved in explaining the effect of climate change on fisheries arising from the lack of ecological knowledge may be overcome by relating climate parameters with long-term fish catch data. Catch per unit effort (CPUE), rainfall, the Southern Oscillation Index (SOI) and catch time series for specific combinations of climate seasons and regions have been explored and surplus production models applied to Queensland’s commercial fish catch data with the program CLIMPROD. Results indicate that up to 30% of Queensland’s total fish catch and up to 80% of the barramundi catch variation for specific regions can be explained by rainfall often with a lagged response to rainfall events. Our approach allows an evaluation of the economic consequences of climate parameters on estuarine fisheries, thus highlighting the need to develop forecast models and manage estuaries for future climate change impact by adjusting the quota for climate change sensitive species. Different modelling approaches are discussed with respect to their forecast ability.