Turbidity impacts the growth and productivity of marine benthic habitats due to light limitation. Daily/monthly synoptic and tidal influences often drive turbidity fluctuations, however, our understanding of what drives turbidity across seasonal/interannual timescales is often limited, thus impeding our ability to forecast climate change impacts to ecologically significant habitats. Here, we analysed long term (18-year) MODIS-aqua data to derive turbidity and the associated meteorological and oceanographic (metocean) processes in an arid tropical embayment (Exmouth Gulf in Western Australia) within the eastern Indian Ocean. We found turbidity was associated with El Niño Southern Oscillation (ENSO) cycles as well as Indian Ocean Dipole (IOD) events. Winds from the adjacent terrestrial region were also associated with turbidity and an upward trend in turbidity was evident in the body of the gulf over the 18 years. Our results identify hydrological processes that could be affected by global climate cycles undergoing change and reveal opportunities for managers to reduce impacts to ecologically important ecosystems.

Globally, coral reefs are under threat, with many exhibiting degradation or a shift towards algal-dominated regimes following marine heat waves, and other disturbance events. Marginal coral reefs existing under naturally extreme conditions, such as turbid water reefs, may be more resilient than their clear water counterparts as well as offer some insight into how reefs could look in the future under climate change. Here, we surveyed 27 benthic habitats across an environmental stress gradient in the Exmouth Gulf region of north Western Australia immediately following a marine heatwave event. We used multidecadal remotely sensed turbidity (from an in-situ validated dataset) and temperature, to assess how these environmental drivers influence variability in benthic communities and coral morphology. Long-term turbidity and temperature variability were associated with macroalgal colonisation when exceeding a combined threshold. Coral cover was strongly negatively associated with temperature variability, and positively associated with depth, and wave power, while coral morphology diversity was positively associated with turbidity. While moderate turbidity (long-term average ~ 2 mg/L suspended matter) appeared to raise the threshold for coral bleaching and macroalgal dominance, regions with higher temperature variability (> 3.5 °C) appeared to have already reached this threshold. The region with the least turbidity and temperature variability had the highest amount of coral bleaching from a recent heatwave event and moderate levels of both these variables may confer resilience to coral reefs.

Marine fauna, including coral reefs, exist under particular oceanographic and meteorological (metocean) processes that maintain water quality within the range limits to which they have adapted over millennia. Climate‐induced changes to these metocean processes could alter ambient marine water quality to ranges beyond those limits and at rates faster than species can adapt. Extreme (or marginal) coral reefs, such as those in arid tropical regions, already exist at the limits of their ranges for water quality parameters such as temperature and turbidity. Here, we apply projected anomalies from ensemble climate models to the metocean processes that drive turbidity in the Exmouth Gulf region of north Western Australia where habitats of significant environmental value exist. We also apply projected sea surface temperature anomalies to look at how a combined effect of turbidity and temperature might impact important habitats. We find that turbidity is predicted to increase in some parts of the Gulf and decrease in others due to differing metocean drivers of turbidity throughout the region. Temperature anomalies reveal year‐round increases in temperature consistent with current summer marine heat wave events (>2.5°C above mean temperatures). Climate models used in the predictions varied between themselves underscoring the importance of model choice and of using ensembles.