Widespread passive acoustic monitoring reveals spatio-temporal patterns of blue and fin whale song vocalizations in the Northeast Pacific Ocean

The NOAA-NPS Ocean Noise Reference Station Network (NRS) is a passive acoustic monitoring effort to record the low-frequency (<2 kHz) sound field throughout the U.S. Exclusive Economic Zone. Data collection began in 2014 and spans 12 acoustic recording locations. To date, NRS datasets have been analyzed to understand spatial variation of large-scale sound levels, however, assessment of specific sound sources is an area where these datasets can provide additional insights. To understand seasonal patterns of blue whale, Balaenoptera musculus, and fin whale, B. physalus, sound production in the eastern North Pacific Ocean, this study explored data recorded between 2014 and 2020 from four NRS recording sites. A call index (CI) was used to quantify the intensity of blue whale B calls and fin whale 20 Hz pulses. Diel and seasonal patterns were then determined in the context of their migratory patterns. Most sites shared similar patterns in blue whale CI: persistent acoustic presence for 4–5 months starting by August and ending by February with a CI maximum in October or November. Fin whale patterns included persistent acoustic presence for 5–7 months starting by October and ending before April with a CI maximum between October and December. The diel patterning of blue whale song varied across the sites with the Gulf of Alaska, Olympic Coast, Cordell Bank, and Channel Islands (2014–2015) exhibiting a tendency towards nighttime song detection. However, this diel pattern was not observed at Channel Islands (2018–2020). Fin whale song detection was distributed evenly across day and night at most recording sites and months, however, a tendency toward nighttime song detection was observed in Cordell Bank during fall, and Gulf of Alaska and Olympic Coast during spring. Understanding call and migration patterns for blue and fin whales is essential for conservation efforts. By using passive acoustic monitoring and efficient detection methods, such as CI, it is possible to process large amounts of bioacoustic data and better understand the migratory behaviors of endangered marine species.