Abstract. Estuaries are especially vulnerable to the impacts of climate change because changes in climatic and hydrologic variables that influence freshwater and marine systems will also affect estuaries. We review potential impacts of climate change on Australian estuaries and their fish. Geographic differences are likely because southern Australian climates are predicted to become warmer and drier, whereas northern regions may see increased precipitation. Environmental factors, including salinity gradients, suspended sediment, dissolved oxygen and nutrient concentrations, will be influenced by changing freshwater input and other climate variables. Potential impacts will vary depending on the geomorphology of the estuary and the level of build-up of sand bars across estuarine entrances. Changes to estuarine fish assemblages will depend on associated changes to salinity and estuarine-mouth morphology. Marine migrants may be severely affected by closure of estuarine mouths, depending on whether species 'must' use estuarine habitat and the level of migratory v. resident individuals. Depending on how fish in coastal waters locate estuaries, there may be reduced cues associated with estuarine mouths, particularly in southern Australia, potentially influencing abundance. In summary, climate change is expected to have major consequences for Australian estuaries and associated fish, although the nature of impacts will show significant regional variation.

Shade plots, simple visual representations of abundance matrices from multivariate species assemblage studies, are shown to be an effective aid in choosing an overall transformation (or other pre-treatment) of quantitative data for long-term use, striking an appropriate balance between dominant and less abundant taxa in ensuing resemblance-based multivariate analyses. Though the exposition is entirely general and applicable to all community studies, detailed illustrations of the comparative power and interpretative possibilities of shade plots are given in the case of two estuarine assemblage studies in south-western Australia: (a) macrobenthos in the upper Swan Estuary over a two-year period covering a highly significant precipitation event for the Perth area; and (b) a wide-scale spatial study of the nearshore fish fauna from five divergent estuaries. The utility of transformations of intermediate severity is again demonstrated and, with greater novelty, the potential importance seen of further mild transformation of all data after differential down-weighting (dispersion weighting) of spatially 'clumped' or 'schooled' species. Among the new techniques utilized is a two-way form of the RELATE test, which demonstrates linking of assemblage structure (fish) to continuous environmental variables (water quality), having removed a categorical factor (estuary differences). Re-orderings of sample and species axes in the associated shade plots are seen to provide transparent explanations at the species level for such continuous multivariate patterns.

Maintaining the health of aquatic systems is an essential component of sustainable catchment management, however, degradation of water quality and aquatic habitat continues to challenge scientists and policy-makers. To support management and restoration efforts aquatic system models are required that are able to capture the often complex trajectories that these systems display in response to multiple stressors. This paper explores the abilities and limitations of current model approaches in meeting this challenge, and outlines a strategy based on integration of flexible model libraries and data from observation networks, within a learning framework, as a means to improve the accuracy and scope of model predictions. The framework is comprised of a data assimilation component that utilizes diverse data streams from sensor networks, and a second component whereby model structural evolution can occur once the model is assessed against theoretically relevant metrics of system function. Given the scale and transdisciplinary nature of the prediction challenge, network science initiatives are identified as a means to develop and integrate diverse model libraries and workflows, and to obtain consensus on diagnostic approaches to model assessment that can guide model adaptation. We outline how such a framework can help us explore the theory of how aquatic systems respond to change by bridging bottom-up and top-down lines of enquiry, and, in doing so, also advance the role of prediction in aquatic ecosystem management. Modeling Aquatic Health: The Evolving Role of Aquatic System PredictionSustainable catchment management during the current era of global population growth and climate change is one of the most profound challenges confronting society [Bogardi et al., 2012;Gerten et al., 2013;Pahl-Wostl et al., 2013;Brookes et al., 2014]. Inland waters have changed more rapidly in the past 50 years than at any other time in human history. Water quality degradation and associated issues of water security, as well as loss of biodiversity Dudgeon, 2014], have been driven by widespread urban, agricultural and mining developments, and span both developed and emerging economies. Preserving the integrity of aquatic systems, including rivers, wetlands, lakes and estuaries, is an essential component of catchment management as these systems provide critical ecosystem services to support societal development [Zedler and Kercher, 2005;Carpenter et al., 2011]. However, the pace of contemporary environmental change is rapid and multifaceted, and hinders restoration efforts. The development of tools and approaches to quantify the function and response of aquatic systems is therefore essential to support a holistic view of catchment function [Wagener et al., 2010;Montanari et al., 2013], and guide investment in conservation and rehabilitation [Creighton et al., 2015].Substantial advances have been made toward describing changes in catchment hydrologic function and developing predictive ability to support water resource management [Bl...

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