Ocean Science Analytics is currently involved in the development of methods for the real-time detection and display of bottlenose dolphin whistles. The “Dolphin Whistle Detection and Vocalization Display” project is being led by Dr. Heidi Lyn, University of South Alabama, and Peter Sugarman and aims to better understand the whistle repertoire of a group of dolphins located at the Ocean Adventures facility in Gulfport, Mississippi. Our role in this project relates to the software components used in detecting and displaying whistles. For whistle detection, we are utilizing the bioacoustic monitoring and analysis software Ishmael by configuring detectors to log and clip whistles of interest based on several parameters. Ishmael will collect and display data continuously while simultaneously detecting whistles of interest in real-time. These .wav file clips are then loaded by R and displayed as a spectrogram in a window beside the real-time Ishmael display. We anticipate generating an additional element to the R routine to assign a percentage match of each whistle to a predetermined set of parameters. Elizabeth Ferguson and our partner Jennifer Pettis Schallert are involved in the software configuration and methods development of this project.
OSA is currently conducting a study to look marine mammal habitat use during and following the 2013-2016 warm water anomaly along the coastal northeast Pacific Ocean. The National Science Foundation-funded Ocean Observatories Initiative (OOI) maintains a series of coastal and oceanic monitoring sites that consists of a multitude of physical and biological sensors. As part of this program, OOI collects continuous data from a cabled array along the continental shelf and slope off Newport, Oregon. OSA is currently exploring the occurrence of vocally active marine mammal species in relation to coastal ocean parameters across several years that straddle the warm water “blob” anomaly. We are using bioacoustic analytical software and Python techniques learned during the 2018 Ocean Hack Week (https://oceanhackweek.github.io/) to explore this big ocean dataset. We expect to have an update in early 2019!