Drifting blooms of the endemic filamentous brown alga Hincksia sordida at Noosa on the subtropical east Australian coast

Since 2002, the usually uncommon endemic filamentous brown alga Hincksia sordida (Harvey) Silva (Ectocarpales, Phaeophyta) has formed nuisance blooms annually during spring/early summer at Main Beach, Noosa on the subtropical east Australian coast. The Hincksia bloom coincides with the normally intensive recreational use of the popular bathing beach by the local population and tourists. The alga forms dense accumulations in the surf zone at Main Beach, giving the seawater a distinct brown coloration and deterring swimmers from entering the water. Decomposing algae stranded by receding tides emit a nauseating sulphurous stench which hangs over the beach. The stranded algal biomass is removed from the beach by bulldozers. During blooms, the usually crowded Main Beach is deserted, bathers preferring to use the many unaffected beaches on the Sunshine Coast to the south of Main Beach. The bloom worsens with north-easterly winds and is cleared from Noosa by south easterly winds, observations which have prompted the untenable proposal by local authorities that the bloom is forming offshore of Fraser Island in the South Pacific Ocean. The Noosa River estuarine system/Laguna Bay is the more probable source of the bloom and the nutrient inputs into this system must be substantial to generate the high bloom biomass. Current mitigation procedures of removing the blooming alga off the beach with bulldozers treat the symptom, not the cause and are proving ineffective. Environmental management must be based on science and the Noosa bloom would benefit greatly from the accurate ecological data on which to base management options. (c) 2006 Elsevier Ltd. All rights reserved.

An internet GIS and spatial model to benchmark local government socio-economic performance

This paper develops an Internet geographical information system (GIS) and spatial model application that provides socio-economic information and exploratory spatial data analysis for local government authorities (LGAs) in Queensland, Australia. The application aims to improve the means by which large quantities of data may be analysed, manipulated and displayed in order to highlight trends and patterns as well as provide performance benchmarking that is readily understandable and easily accessible for decision-makers. Measures of attribute similarity and spatial proximity are combined in a clustering model with a spatial autocorrelation index for exploratory spatial data analysis to support the identification of spatial patterns of change. Analysis of socio-economic changes in Queensland is presented. The results demonstrate the usefulness and potential appeal of the Internet GIS applications as a tool to inform the process of regional analysis, planning and policy.