Seawater carbonate chemistry and aerobic performance of coral reef fishes during experiments, 2009

Concerns about the impacts of ocean acidification on marine life have mostly focused on how reduced carbonate saturation affects calcifying organisms. Here, we show that levels of CO2-induced acidification that may be attained by 2100 could also have significant effects on marine organisms by reducing their aerobic capacity. The effects of temperature and acidification on oxygen consumption were tested in 2 species of coral reef fishes, Ostorhinchus doederleini and O. cyanosoma, from the Great Barrier Reef, Australia. The capacity for aerobic activity (aerobic scope) declined at temperatures above the summer average (29°C) and in CO2-acidified water (pH 7.8 and ~1000 ppm CO2) compared to control water (pH 8.15). Aerobic scope declined by 36 and 32% for O. doederleini and O. cyanosoma at temperatures between 29 to 32°C, whereas it declined by 33 and 47% for O. doederleini and O. cyanosoma in acidified water compared to control water. Thus, the declines in aerobic scope in acidified water were similar to those caused by a 3°C increase in water temperature. Minimum aerobic scope values of ~200 mg O2 kg-1 h-1 were attained for both species in acidified water at 32°C, compared with over 600 mg O2 kg-1 h-1 in control water at 29°C. Mortality rate increased sharply at 33°C, indicating that this temperature is close to the lethal thermal limit for both species. Acidification further increased the mortality rate of O. doederleini, but not of O. cyanosoma. These results show that coral reef fishes are sensitive to both higher temperatures and increased levels of dissolved CO2, and that the aerobic performance of some reef fishes could be significantly reduced if climate change continues unabated.

Microphytobenthos composition in Heron Reef, Australia, by High Performance Liquid Chromatography (HPLC) (July 2012)

We quantified pigment biomarkers by high performance liquid chromatography (HPLC) to obtain a broad taxonomic classification of microphytobenthos (MPB) (i.e. identification of dominant taxa). Three replicate sediment cores were collected at 0, 50 and 100 m along transects 5-9 in Heron Reef lagoon (n=15) (Fig. 1). Transects 1-4 could not be processed because the means to have the samples analysed by HPLC were not available at the time of field data collection. Cores were stored frozen and scrapes taken from the top of each one and placed in cryovials immersed in dry ice. Samples were sent to the laboratory (CSIRO Marine and Atmospheric Research, Hobart, Australia) where pigments were extracted with 100% acetone during fifteen hours at 4°C after vortex mixing (30 seconds) and sonication (15 minutes). Samples were then centrifuged and filtered prior to the analysis of pigment composition with a Waters - Alliance HPLC system equipped with a photo-diode array detector. Pigments were separated using a Zorbax Eclipse XDB-C8 stainless steel 150 mm x 4.6 mm ID column with 3.5 µm particle size (Agilent Technologies) and a binary gradient system with an elevated column temperature following a modified version of the Van Heukelem and Thomas (2001) method. The separated pigments were detected at 436 nm and identified against standard spectra using Waters Empower software. Standards for HPLC system calibration were obtained from Sigma (USA) and DHI (Denmark).

Results of wave modelling for Moreton Bay, Southeast Queensland, and a reef lagoon off Lizard Island, Great Barrier Reef, Australia

The distribution, abundance, behaviour, and morphology of marine species is affected by spatial variability in the wave environment. Maps of wave metrics (e.g. significant wave height Hs, peak energy wave period Tp, and benthic wave orbital velocity URMS) are therefore useful for predictive ecological models of marine species and ecosystems. A number of techniques are available to generate maps of wave metrics, with varying levels of complexity in terms of input data requirements, operator knowledge, and computation time. Relatively simple "fetch-based" models are generated using geographic information system (GIS) layers of bathymetry and dominant wind speed and direction. More complex, but computationally expensive, "process-based" models are generated using numerical models such as the Simulating Waves Nearshore (SWAN) model. We generated maps of wave metrics based on both fetch-based and process-based models and asked whether predictive performance in models of benthic marine habitats differed. Predictive models of seagrass distribution for Moreton Bay, Southeast Queensland, and Lizard Island, Great Barrier Reef, Australia, were generated using maps based on each type of wave model. For Lizard Island, performance of the process-based wave maps was significantly better for describing the presence of seagrass, based on Hs, Tp, and URMS. Conversely, for the predictive model of seagrass in Moreton Bay, based on benthic light availability and Hs, there was no difference in performance using the maps of the different wave metrics. For predictive models where wave metrics are the dominant factor determining ecological processes it is recommended that process-based models be used. Our results suggest that for models where wave metrics provide secondarily useful information, either fetch- or process-based models may be equally useful.