Modeling recreational fishing intensity in a complex urbanised estuary.

Urbanised estuaries, ports and harbours are often utilised for recreational purposes, notably recreational angling. Yet there has been little quantitative assessment of the footprint and intensity of these activities at scales suitable for spatial management. Urban and industrialised estuaries have previously been considered as having low conservation value, perhaps due to issues with contamination and disturbance. Studies in recent decades have demonstrated that many of these systems are still highly biodiverse and of high value to local residents. As a response, urbanised estuaries are now being considered by coastal spatial management initiatives, where assessments of recreational use in these areas can help avoid 'user-environmental' and 'user-user' conflict. The models of these activities need to be developed at a scale relevant to governments and regulatory authorities, but the few human-use models that do exist integrate fishing intensity to a regional or even continental scale; too large to capture the fine scale variation inherent in complex urban fisheries. Species Distribution Modeling (SDM) is a tool commonly used to assess drivers of species range, but can be applied to models of recreational fishing in complex environments, at a scale relevant to regulatory bodies. Using point-data from 573 visual surveys with recently developed Poisson point process models, we examine the recreational fishery in Australia's busiest estuarine port, Sydney Harbour. We demonstrate the utility of these models for understanding the distribution of boat and shore-based fishers, and the effects of a range of temporally static (geographical) and dynamic (weather) predictors on these distributions.

Cumulative effects of multiple stressors impact an endangered seagrass population and fish communities.

Coastal ecosystems are becoming increasingly threatened by human activities and there is growing appreciation that management must consider the impacts of multiple stressors. Cumulative effects assessments (CEAs) have become a popular tool for identifying the distribution and intensity of multiple human stressors in coastal ecosystems. Few studies, however, have demonstrated strong correlations between CEAs and change in ecosystem condition, questioning its management use. Here, we apply a CEA to the endangered seagrass Posidonia australis in Pittwater, NSW, Australia, using spatial data on known stressors to seagrass related to foreshore development, water quality, vessel traffic and fishing. We tested how well cumulative effects scores explained changes in P. australis extent measured between 2005 and 2019 using high-resolution aerial imagery. A negative correlation between P. australis and estimated cumulative effects scores was observed (R2 = 22 %), and we identified a threshold of cumulative effects above which losses of P. australis became more likely. Using baited remote underwater video, we surveyed fishes over P. australis and non-vegetated sediments to infer and quantify how impacts of cumulative effects to P. australis extent would flow on to fish assemblages. P. australis contained a distinct assemblage of fish, and on non-vegetated sediments the abundance of sparids, which are of importance to fisheries, increased with closer proximity to P. australis. Our results demonstrate the negative impact of multiple stressors on P. australis and the consequences for fish biodiversity and fisheries production across much of the estuary. Management actions aimed at reducing or limiting cumulative effects to low and moderate levels will help conserve P. australis and its associated fish biodiversity and productivity.