Implementing conservation measures for data-limited species is a fundamental challenge for wildlife managers and policy-makers, and proves difficult for cryptic marine animals occurring in naturally low numbers across remote seascapes. There is currently scant information on the abundance and habitat preferences of Australian snubfin dolphins (Orcaella heinsohni) throughout much of their geographical range, and especially within the Kimberley region of northern Western Australia. Such knowledge gaps curtail rigorous threat assessments on both local and regional scales. To address this and assist future conservation listings, we built the first comprehensive catalog of snubfin dolphin sightings for the Kimberley. We used these data to estimate the species’ extent of occurrence (EOO) and area of occupancy (AOO) along the region’s 7,000 km coastline, following a simple Bootstrap bivariate kernel approach to combine datasets of varying quality and quantify uncertainty. Our catalog consists of 1,597 visual detections of snubfin dolphins made over a period of 17 years (2004–2020) and collated from multiple sources, including online biodiversity repositories, peer-reviewed scientific articles, citizen science programs, as well as dedicated marine wildlife surveys with local Indigenous communities and Ranger groups. Snubfin dolphins were consistently encountered in shallow waters (<21 m depth) close to (<15 km) freshwater inputs, with high detection rates in known hotspots (e.g., Roebuck Bay, Cygnet Bay) as well as in coastal habitats suspected to be suitable (e.g., Prince Regent River and surrounds, King Sound, Doubtful Bay, Napier Broome Bay and the upper Cambridge Gulf). Bootstrap estimates of EOO and AOO were 38,300 (95% CI: 25,451–42,437) km2 and 700 (656–736) km2 respectively, suggesting that snubfin dolphins in the Kimberley are likely Vulnerable under IUCN criteria B2 at a regional scale, in keeping with their global classification. Our study offers insights into the distribution of a vulnerable coastal cetacean species and demonstrates the value of integrating multiple data sources for informing conservation assessments in the face of uncertainty.
Read full abstract