Oral Presentation Australian Society for Fish Biology Conference 2025

Continental-scale biogeographic assessment of shark and ray communities in Australia (124901)

Tom Clarke 1 , Sasha Whitmarsh 2 , Leanne Currey-Randall 3 , Brooke Gibbons 4 , Christopher Henderson 5 , Andrew Hoey 6 , Daniel Ierodiaconou 2 , Stephen Newman 7 , Ben Radford 3 , Conrad Speed 8 , Claude Spencer 4 , Mike Travers 7 , Charlie Huveneers 9 , The Fish Collective 2
  1. South Australian Research and Development Institute, SARDI, Adelaide, SA, Australia
  2. Deakin University, Warrnambool, VIC, Australia
  3. AIMS, Townsville, Queensland, Australia
  4. University of Western Australia, Perth, WA, Australia
  5. University of Sunshine Coast, Sunshine Coast, QLD, Australia
  6. James Cook University, Townsville, QLD, Australia
  7. DPIRD, Perth, WA, Australia
  8. AIMS, Perth, WA, Australia
  9. College of Science and Engineering, Flinders University, Adelaide, SA, Australia

Background
Large-scale geographic trends in biodiversity can provide valuable information across a range of ecological and evolutionary disciplines. Biogeography studies linking species occurrences to environmental factors are important to understand the drivers of species distributions, predict shifts in response to human activities and climate change, and can be a powerful approach in conservation planning. Globally, distributional patterns of shark and ray biodiversity are generally associated with latitudinal and bathymetric gradients, but the drivers responsible can vary considerably between regions and are often poorly understood.
Methods
Here, we use a continental-scale dataset of over 29,000 baited video deployments, providing a standardised approach to quantify distributions. We aim to identify the environmental, anthropogenic, and habitat variables that best predict the species richness and composition of sharks and rays and identify where faunal breaks occur.
Results
We used Boosted Regression Trees to identify key drivers of elasmobranch occurrences and community composition, revealing geographically distinct clusters of species distributed around Australia.
Conclusion
These predictive models of the composition of elasmobranch communities will aid in the understanding of the role of these animals in marine ecosystems, spatial planning for conservation and management, and prediction of the likely resilience of these taxa under changing environments.