Dolphin distribution and habitat suitability in North Western Australia: Applications and implications of a Broad-Scale, Non-targeted Dataset

• Main Authors: Hanf, D., Hodgson, A.J., Kobryn, H., Bejder, L., Smith, J.N.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Frontiers Media 2022
• Subjects: Pacific; Killer Whale; Orca; Orcinus orca
• Online Access: https://researchrepository.murdoch.edu.au/id/eprint/64113/

Understanding species’ distribution patterns and the environmental and ecological interactions that drive them is fundamental for biodiversity conservation. Data deficiency exists in areas that are difficult to access, or where resources are limited. We use a broad-scale, non-targeted dataset to describe dolphin distribution and habitat suitability in remote north Western Australia, where there is a paucity of data to adequately inform species management. From 1,169 opportunistic dolphin sightings obtained from 10 dugong aerial surveys conducted over a four-year period, there were 661 Indo-Pacific bottlenose dolphin (Tursiops aduncus), 191 Australian humpback dolphin (Sousa sahulensis), nine Australian snubfin dolphin (Orcaella heinsohni), 16 Stenella sp., one killer whale (Orcinus orca), one false killer whale (Pseudorca crassidens), and 290 unidentified dolphin species sightings. Maximum Entropy (MaxEnt) habitat suitability models identified shallow intertidal areas around mainland coast, islands and shoals as important areas for humpback dolphins. In contrast, bottlenose dolphins are more likely to occur further offshore and at greater depths, suggesting niche partitioning between these two sympatric species. Bottlenose dolphin response to sea surface temperature is markedly different between seasons (positive in May; negative in October) and probably influenced by the Leeuwin Current, a prominent oceanographic feature. Our findings support broad marine spatial planning, impact assessment and the design of future surveys, which would benefit from the collection of high-resolution digital images for species identification verification. A substantial proportion of data were removed due to uncertainties resulting from non-targeted observations and this is likely to have reduced model performance. We highlight the importance of considering climatic and seasonal fluctuations in interpreting distribution patterns and species interactions in assuming habitat suitability.