Biogenic marine habitats are increasingly threatened by a multitude of human impacts, and temperate coasts in particular are exposed to progressively more intense and frequent anthropogenic stressors. In this study, the single and multiple effects of the urban stressors of nutrification and sedimentation on kelp bed communities were examined within Australia’s largest urbanised embayment (Port Phillip Bay, Victoria). Within this system, grazing by sea urchins (Heliocidaris erythrogramma) plays an important role in structuring reef communities by overgrazing kelp beds and maintaining an alternative and stable urchin barrens state. It is therefore important to explore the effects of urban stressors on kelp bed dynamics related to urchin abundance, and test the relative strengths of bottom-up and / or physical drivers (e.g. elevated nutrients and sediment) versus top-down (e.g. urchin grazing) forces on kelp bed community structure. The interactions of these drivers were assessed to determine whether their combination has synergistic, antagonistic, or additive effects on kelp beds. It was found that kelp responds positively to nutrient enhancement, but when combined with enhanced abundance of grazing sea urchins, the local positive effect of nutrient enhancement is overwhelmed by the negative effect of increased herbivory. Turf-forming algae behaved very differently, showing no detectable response to nutrification, yet showing a positive response to urchins, apparently mediated by overgrazing of canopy-forming algae that limit turf development. No direct effects of enhanced sediment load (at twice the ambient load) were found on intact kelp beds. Collectively, the results demonstrate that the ‘top-down’ control of urchin grazing locally overwhelms the positive ‘bottom-up’ effect of nutrient enhancement, and that intact kelp beds demonstrate resilience to direct impacts of urban stressors.

[This data has been superseded by a synthesised global dataset which includes additional ecological data contributed by non-RLS entities (National Reef Monitoring Network). Please visit the corresponding NRMN Collection (IMOS - National Reef Monitoring Network Sub-Facility - Survey metadata) for the most current version of this data. See "Downloads and Links" section below.] This dataset shows the location of Reef Life Survey (RLS) sites surveyed by divers along 50m transects on shallow rocky and coral reefs, worldwide. Although surveys are undertaken as part of monitoring programs at particular locations (mostly in Australia), this dataset contains only spatial information, with repeat surveys of sites not included. Biological data (abundance of invertebrates and fish, habitat quadrats) collected from these surveys is available as separate datasets through the AODN Data Portal (https://portal.aodn.org.au/ - search for 'NRMN')

The Oliver and Holbrook (Journal Atmospheric and Oceanic Technology, 2014), or OH14, data set provides spatially and temporally homogeneous measurements of sea surface temperature (SST) variability at high resolution on the continental shelf around Australia.

[This data has been superseded by a synthesised global dataset which includes additional ecological data contributed by non-RLS entities (National Reef Monitoring Network). Please visit the corresponding NRMN Collection (IMOS - National Reef Monitoring Network Sub-Facility - Global off-transect species observations || Global reef fish abundance and biomass) for the most current version of this data. See "Downloads and Links" section below.] This dataset contains records of bony fishes and elasmobranchs collected by Reef Life Survey (RLS) divers along 50m transects on shallow rocky and coral reefs, worldwide. Abundance information is available for all records found within quantitative survey limits (50 x 5 m swathes during a single swim either side of the transect line, each distinguished as a Block), and out-of-survey records are identified as presence-only (Method 0). Although surveys are undertaken as part of monitoring programs at particular locations (mostly in Australia), this dataset contains does not include repeat surveys of sites.