Predicting Suitable Areas for Cold‐Water Scleractinian Corals in Southwestern Australian Submarine Canyons

Abstract

Aim The exploration of submarine canyons offshore southwestern Australia using remotely operated vehicles (ROV) has documented the occurrence of cold‐water coral (CWC) ecosystems, predominantly along the heads and slopes of the canyons. Representing the first major ROV investigation in this region, information on CWC distribution in this area is still limited. Here we apply a habitat suitability model (HSM) to identify the potential distribution of scleractinian CWC habitats in these submarine canyon systems. We show that the integration of environmental and geomorphological variables allows the HSM to identify key conditions favourable for the occurrence of scleractinian CWC in this region. Location Southwestern Australian submarine canyons: Bremer canyon system (BCS), Mount Gabi seamount and Leeuwin Canyon and Perth Canyon. Taxon Cold‐water corals in the Order Scleractinia. Methods High‐resolution maximum entropy model (Maxent) was developed using remote sensing variables and geomorphological indices derived from bathymetry. Scleractinian CWC occurrences were obtained from videos acquired by ROV onboard RV Falkor during the Schmidt Ocean Institute cruise FK200126. The model identified portions of the seafloor most suitable for scleractinian CWC habitat in the SW Australian submarine canyons. Results Modelling predicted over 27.2 km 2 of suitable habitat for scleractinian CWC (suitability index > 0.6), representing only ~0.254% of the total surface area of the submarine canyon systems explored. Dissolved oxygen resulted as the most relevant factor, followed by terrain ruggedness, slope and bottom temperature, confirming their importance for CWC distribution. The most suitable locations were in canyon heads, slopes and geomorphological features emerging from the bottom along the continental shelf. Main Conclusion Our integrated approach identified potential scleractinian habitats using a combination of remote sensing and geomorphological data. The high performance of the model suggests that remote sensing data are valuable predictors to estimate scleractinian CWC distribution. The results of our modelling approach not only contribute to increasing the knowledge of the distribution of these ecologically relevant ecosystems in the poorly explored SW Australia submarine canyons but also of the key parameters limiting their distribution. Such information is crucial for establishing and implementing targeted conservation actions and effective natural resource management plans.

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