Temporal and spatial lags between wind, coastal upwelling, and blue whale occurrence

Abstract

Understanding relationships between physical drivers and biological response is central to advancing ecological knowledge. Wind is the physical forcing mechanism in coastal upwelling systems, however lags between wind input and biological responses are seldom quantified for marine predators. Lags were examined between wind at an upwelling source, decreased temperatures along the upwelling plume's trajectory, and blue whale occurrence in New Zealand's South Taranaki Bight region (STB). Wind speed and sea surface temperature (SST) were extracted for austral spring-summer months between 2009 and 2019. A hydrophone recorded blue whale vocalizations October 2016-March 2017. Timeseries cross-correlation analyses were conducted between wind speed, SST at different locations along the upwelling plume, and blue whale downswept vocalizations (D calls). Results document increasing lag times (0-2 weeks) between wind speed and SST consistent with the spatial progression of upwelling, culminating with increased D call density at the distal end of the plume three weeks after increased wind speeds at the upwelling source. Lag between wind events and blue whale aggregations (n = 34 aggregations 2013-2019) was 2.09 ± 0.43 weeks. Variation in lag was significantly related to the amount of wind over the preceding 30 days, which likely influences stratification. This study enhances knowledge of physical-biological coupling in upwelling ecosystems and enables improved forecasting of species distribution patterns for dynamic management.

Figure 1

Map of the study region within the South Taranaki Bight (STB) of New Zealand, with location denoted by the white rectangle on inset map in the upper right panel. All spatial sampling locations for sea surface temperature are denoted by the boxes, with the four focal boxes shown in white that represent the typical path of the upwelling plume originating off Kahurangi shoals and moving north and east into the STB. The purple triangle represents the Farewell Spit weather station where wind measurements were acquired. The location of the focal hydrophone (MARU2) is shown by the green star.

Figure 2

Heatmap showing the number of D call detections per hour at the MARU2 hydrophone between 1 October 2016 and 31 March 2017. Note pulsed increases in D call detections.

Figure 3

Results from the cross-correlation analysis along the typical path of the upwelling plume and schematic of time lags. Lag values are reported in weeks (x-axes). The autocorrelation function (ACF) measures the strength of the correlation between timeseries at that lag value, with values > 0 representing positive correlation, and values < 0 representing negative correlation (y-axes). Mean ACF was calculated at each lag step for all years between 2010 and 2018, with 2016 and 2018 partitioned a priori because of documented marine heatwave conditions. The ACF values are plotted in blue for “typical” conditions (mean ± standard error), and values from known heatwave years are plotted in red. D call density was only calculated in 2017, therefore a single ACF value is reported for each lag step.

Figure 4

Left panel: the lag between wind events and blue whale aggregations vs. the number of days with wind speed above 5.5 m s⁻¹ in the preceding 30 days to the aggregation. Each point represents a blue whale aggregation, symbolized by month and colored by year. The black line represents the fitted relationship using a generalized linear model with a Poisson distribution. Right panels: mean daily wind speed recorded at the Farewell Spit weather station for each month in the spring–summer. The labeled year of each plot represents the year during January.