%A Barkley,Yvonne M. %A Sakai,Taiki %A Oleson,Erin M. %A Franklin,Erik C. %D 2022 %J Frontiers in Remote Sensing %C %F %G English %K Sperm whales,Species distribution modeling,passive acoustics,Hawaiian Islands,Cetacean distribution %Q %R 10.3389/frsen.2022.940186 %W %L %M %P %7 %8 2022-October-07 %9 Original Research %# %! Sperm Whale Distributions in Hawaiʻi %* %< %T Examining distribution patterns of foraging and non-foraging sperm whales in Hawaiian waters using visual and passive acoustic data %U https://www.frontiersin.org/articles/10.3389/frsen.2022.940186 %V 3 %0 JOURNAL ARTICLE %@ 2673-6187 %X Following the end of over a century of intensive commercial whaling in 1986, the monitoring and assessment of sperm whale populations is essential for guiding management and conservation decisions for their recovery. Species distribution models (SDMs) are a useful tool for examining and predicting cetacean distribution patterns and typically incorporate visual, ship-based observations. However, understanding sperm whale distribution and habitat use based solely on surface visual observations is challenging due to the significant amount of time sperm whales spend foraging at depth. For the endangered sperm whale population occurring in Hawaiian waters, we used visual and passive acoustic data collected during four annual NOAA marine mammal line-transect surveys and a suite of biologically relevant environmental variables to develop SDMs within a generalized additive modeling framework to study the distribution of sperm whale groups throughout the island chain. Additionally, the passive acoustic data allowed us to differentiate sperm whale groups as foraging or non-foraging based on their click types to account for differences in distribution and behavior within the archipelago. Foraging groups were predicted primarily in the northwestern region of the archipelago between Laysan Island and Pearl and Hermes Reef as well as north of Maui and Hawaiʻi in the main Hawaiian Islands. Non-foraging groups were predicted to be more uniformly distributed throughout the archipelago. Foraging whale models selected temperature at 584 m depth, surface chlorophyll, and location, while the only significant variables for non-foraging whale models included the standard deviation of sea surface height and location. Each variable provides insight into the oceanographic processes influencing prey abundance and, thus, sperm whale foraging behavior. This study furthers our understanding of the distribution patterns for the sperm whale population in Hawaiʻi and contributes methods for building SDMs with visual and passive acoustic data that may be applied to other cetacean species.