Using environmental drivers to model blue whale acoustic detection variability — Promaco Conventions

Using environmental drivers to model blue whale acoustic detection variability (#54)

Gary Truong 1 , Joy Tripovich 1 , Tracey Rogers 1
  1. UNSW, Kensington, NSW, Australia

Blue whales are difficult to study using traditional visual survey methods due to their endangered status and secretive behaviour. Passive acoustic monitoring (PAM) provides an alternative approach to better understand the ecology and behaviour of these rare majestic animals. PAM is cost effective, providing long term sampling that is not affected by adverse weather conditions. We compare two distinct acoustic populations of blue whales living in temperate waters across separate ocean basins. Using the CTBTO’s (Comprehensive Nuclear-test Ban Treaty Organisation) hydro-acoustic network, we have access to 15 years of continuous recordings of ocean noise from Cape Leeuwin, off Western Australia and 9 years of recordings from Juan Fernandez Island, off Chile. Hydrophones at each site record ocean noise continuously and whale calls are located using automated detectors. In addition, satellite derived environmental data was obtained which included sea surface temperature, sea surface height and productivity (chlorophyll-a). Using the satellite data, we constructed models to determine which of the environmental variables best predicted whale calls.  Our results show that blue whales responded to the inter-annual variability in environmental conditions. This has implications for the management and recovery of the species as we provide some insight to how they will adapt to changing conditions.

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