Ranging Patterns and Site Fidelity of Snubfin Dolphins in Yawuru Nagulagun/Roebuck Bay, Western Australia

Abstract

For long-lived species such as marine mammals, having sufficient data on ranging patterns and space use in a timescale suitable for population management and conservation can be difficult. Yawuru Nagulagun/Roebuck Bay in the northwest of Western Australia supports one of the largest known populations of Australian snubfin dolphins (Orcaella heinsohni)—a species with a limited distribution, vulnerable conservation status, and high cultural value. Understanding the species’ use of this area will inform management for the long-term conservation of this species. We combined 11 years of data collected from a variety of sources between 2007 and 2020 to assess the ranging patterns and site fidelity of this population. Ranging patterns were estimated using minimum convex polygons (MCPs) and fixed kernel densities (weighted to account for survey effort) to estimate core and representative areas of use for both the population and for individuals. We estimated the population to range over a small area within the bay (103.05 km2). The Mean individual representative area of use (95% Kernel density contour) was estimated as 39.88 km2 (± 32.65 SD) and the Mean individual core area of use (50% Kernel density contour) was estimated as 21.66 km2 (±18.85 SD) with the majority of sightings located in the northern part of the bay less than 10 km from the coastline. Most individuals (56%) showed moderate to high levels of site fidelity (i.e., part-time or long-term residency) when individual re-sight rates were classified using agglomerative hierarchical clustering (AHC). These results emphasize the importance of the area to this vulnerable species, particularly the area within the Port of Broome that has been identified within the population’s core range. The pressures associated with coastal development and exposure to vessel traffic, noise, and humans will need to be considered in ongoing management efforts. Analyzing datasets from multiple studies and across time could be beneficial for threatened species where little is known on their ranging patterns and site fidelity. Combined datasets can provide larger sample sizes over an extended period of time, fill knowledge gaps, highlight data limitations, and identify future research needs to be considered with dedicated studies.