Processed data

Processed data corresponding to the following manuscript:
Temporal and spatial lags between wind,
coastal upwelling, and blue whale occurrence

Authors: Dawn R. Barlow1*, Holger Klinck2,3, Dimitri Ponirakis2, Christina Garvey4, Leigh G. Torres1

1Geospatial Ecology of Marine Megafauna Lab, Marine Mammal Institute, and Department of Fisheries and Wildlife, Oregon State University, Newport, Oregon, USA
2Center for Conservation Bioacoustics, Cornell University, Ithaca, New York, USA
3Marine Mammal Institute, Department of Fisheries and Wildlife, Oregon State University, Newport, Oregon, USA
4University of Maryland, College Park, Maryland, USA

*[e-mail]

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 2009-2019. 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.