Abstract

Seasonal variation in the acoustic presence of blue whale calls has been widely reported for feeding grounds worldwide, however variation over the submonthly scale (several days to 1 month) has been examined to a much lesser extent. This study combines passive acoustic, hydroacoustic, and in situ oceanographic observations collected at a mooring in the Corcovado Gulf, Northern Chilean Patagonia, from January 2016-February 2017, to examine the temporal variation in blue whale acoustic occurrence and prey backscatter over seasonal and submonthly scales. Time series data for a) Southeast Pacific blue whale song calls and D-calls, b) zooplankton backscatter, c) tidal amplitude, and d) meridional and zonal wind stress were examined visually for seasonal trends. To examine submonthly timescales over the summer feeding season (January-June), wavelet transforms and wavelet coherence were applied; generalized linear models (GLM) were also applied. There was a 3-month lag between the seasonal onsets of high zooplankton backscatter (October) and blue whale acoustic presence (January), and an almost immediate drop in blue whale acoustic presence with the seasonal decrease of backscatter (June). This may be due to the use of memory by animals when timing their arrival on the feeding ground, but the timing of their departure may be related to detection of low prey availability. Over the summer feeding season, blue whale acoustic presence was strongly associated with zooplankton backscatter (GLM coefficient p MUCH LESS-THAN 0.0001). Song calls followed a seasonal cycle, but D-calls appeared to respond to short term variations in environmental conditions over submonthly scales. Results suggest that spring tides may increase prey aggregation and/or transport into the Corcovado Gulf, leading to increased blue whale acoustic presence over 15-day or 30-day cycles; and short-lived events of increased wind stress with periodicities of 2-8 days and 16-30 days, may also contribute to the aggregation of prey. We discuss the strengths and limitations of coupling passive and active acoustic data to examine drivers of blue whale distribution.