Ecology and Distribution of Blue Whales in New Zealand Across Spatial and Temporal Scales

• Main Author: Barlow, Dawn R.
• Other Authors: Torres, Leigh G., Bernard, Kim S., Klinck, Holger, Palacios, Daniel M., White, J. Wilson, Henkel, Sarah K., Fisheries, Wildlife, and Conservation Sciences, Hatfield Marine Science Center, Oregon State University. Marine Mammal Institute
• Format: Doctoral or Postdoctoral Thesis
• Language: English; unknown
• Published: Oregon State University
• Subjects: Blue whale
• Online Access: https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/td96k949n

The distribution of mobile marine predators often reflects underlying dynamic ecological processes. The geographical focus of this PhD is the South Taranaki Bight (STB) of New Zealand, where wind-driven coastal upwelling generates productivity and prey to support a blue whale foraging ground. The STB is also New Zealand’s most industrial marine region, necessitating improved knowledge on blue whale ecology to enable informed management decisions. To accomplish this goal, I conducted a multidisciplinary assessment of physical, biological, and ecological processes in the STB region at multiple scales. Using vessel-based whale surveys paired with oceanographic sampling and prey mapping, I constructed models to examine relationships between water column structure, krill availability, and blue whale distribution under typical upwelling (2014 and 2017) and marine heatwave (2016) conditions. Findings confirmed that environmental drivers of prey availability are suitable proxies for blue whale distribution, and that models are particularly informative when based on functional relationships and trained across a range of conditions. Timeseries analyses documented increasing lags (0-2 weeks) between wind speed at the upwelling source and decreased temperature along the upwelling plume’s trajectory, culminating with increased blue whale D calls at the distal end of the plume three weeks after increased wind speeds at the upwelling source. These findings illustrate physical-biological coupling in the STB, and quantified lags were incorporated into models to forecast sea surface temperature and net primary productivity with up to three weeks lead time. Forecasted environmental layers were then implemented in models to predict blue whale habitat. The location and extent of forecasted suitable habitat was variable in space and time, indicating that the system is well-suited for dynamic management that could reduce anthropogenic threats to blue whales while decreasing regulatory burdens to industry users. While blue whale ...