The Aqua and Orbview satellites carry a MODIS and SeaWIFS sensors (respectively) that observes sunlight reflected from within the ocean surface layer at multiple wavelengths. These multi-spectral measurements are used to infer the concentration of chlorophyll-a (Chl-a), most typically due to phytoplankton, present in the water. There are multiple retrieval algorithms for estimating Chl-a and aggregating the data over time. This data set is a reprocessed copy of 9km monthly and 8-day versions produced globally by NASA, adjusted for the Southern Ocean south of latitude 30S. The full methodology is described in Johnson, R., Strutton, P.G., Wright, S.W., McMinn, A., Meiners, K.M., 2013. Three improved satellite chlorophyll algorithms for the Southern Ocean. Journal of Geophysical Research: Oceans. doi: 10.1002/jgrc.20270. It is expected that the data set will be periodically updated with contemporary data as it becomes available. There are four sub-streams within this data set. A monthly and an 8-day series for MODIS/Aqua and similarly for SeaWIFS. Note that SeaWIFS ceased operation in late 2010 so there will be no further SeaWIFS data. The data represented by this record is weekly data for SeaWIFS.

[This data has been superseded by a synthesised global dataset which includes additional ecological data contributed by non-RLS entities (National Reef Monitoring Network).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 Aqua and Orbview satellites carry a MODIS and SeaWIFS sensors (respectively) that observes sunlight reflected from within the ocean surface layer at multiple wavelengths. These multi-spectral measurements are used to infer the concentration of chlorophyll-a (Chl-a), most typically due to phytoplankton, present in the water. There are multiple retrieval algorithms for estimating Chl-a and aggregating the data over time. This data set is a reprocessed copy of 9km monthly and 8-day versions produced globally by NASA, adjusted for the Southern Ocean south of latitude 30S. The full methodology is described in Johnson, R., Strutton, P.G., Wright, S.W., McMinn, A., Meiners, K.M., 2013. Three improved satellite chlorophyll algorithms for the Southern Ocean. Journal of Geophysical Research: Oceans. doi: 10.1002/jgrc.20270. It is expected that the data set will be periodically updated with contemporary data as it becomes available. There are four sub-streams within this data set. A monthly and an 8-day series for MODIS/Aqua and similarly for SeaWIFS. Note that SeaWIFS ceased operation in late 2010 so there will be no further SeaWIFS data. The data represented by this record is monthly data for SeaWIFS.

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 dataset contains the traditional and effective nitrate, phosphate, and silicate fluxes in Lombok, Ombai, and Timor passages, Indian Ocean. Fluxes are depth-resolved and cross-strait integrated, for the 2004-2006 time period of the INSTANT field program. In some cases depths extend below the functional sill depths, due to the moorings being in deeper water. Negative fluxes are westward, towards the Indian Ocean. Files are in self-describing netCDF format, as follows: (1) lombok_trad.nc. Traditional nutrient fluxes for Lombok Strait. (2) lombok_eff.nc. Effective nutrient fluxes for Lombok Strait. (3) ombai_trad.nc. Traditional nutrient fluxes for Ombai Strait. (4) ombai_eff.nc. Effective nutrient fluxes for Ombai Strait. (5) timor_trad.nc. Traditional nutrient fluxes for Timor Passage. (6) timor_eff.nc. Effective nutrient fluxes for Timor Passage.

The Aqua and Orbview satellites carry a MODIS and SeaWIFS sensors (respectively) that observes sunlight reflected from within the ocean surface layer at multiple wavelengths. These multi-spectral measurements are used to infer the concentration of chlorophyll-a (Chl-a), most typically due to phytoplankton, present in the water. There are multiple retrieval algorithms for estimating Chl-a and aggregating the data over time. This data set is a reprocessed copy of 9km monthly and 8-day versions produced globally by NASA, adjusted for the Southern Ocean south of latitude 30S. The full methodology is described in Johnson, R., Strutton, P.G., Wright, S.W., McMinn, A., Meiners, K.M., 2013. Three improved satellite chlorophyll algorithms for the Southern Ocean. Journal of Geophysical Research: Oceans. doi: 10.1002/jgrc.20270. It is expected that the data set will be periodically updated with contemporary data as it becomes available. There are four sub-streams within this data set. A monthly and an 8-day series for MODIS/Aqua and similarly for SeaWIFS. Note that SeaWIFS ceased operation in late 2010 so there will be no further SeaWIFS data. The data represented by this record is monthly data for MODIS/Aqua.

[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.