Humpback whale (Megaptera novaeangliae) location in Southeast Alaska : modeling the influence of mesoscale krill (Euphausiacea) patch depth and size

Abstract

Humpback whales (Megaptera novaeangliae) require dense prey aggregations due to the high energetic cost of their feeding methods. Modeling studies have shown that when whales are on their feeding grounds, they are closely associated with high prey concentrations. These studies collapse the prey field into a two dimensional measure of prey abundance in horizontal space. However, patchiness is one of the dominant characteristics of marine systems. The three-dimensional structure of prey is known to affect rorqual whale (family Balaenopteridae) feeding kinematics and prey patchiness affects the foraging decisions of central-based marine predators.

This study aims to assess how spatial and temporal patterns in krill distribution affect the distribution of humpback whales across the feeding area of Frederick Sound and Lower Stephens Passage, Southeast Alaska, from 2006-2008. Data from hydroacoustic surveys were used to identify prey patches, and statistics related to their depth, size and backscatter intensity were calculated. These statistics, along with measures of prey hot spots for each survey, persistent prey hot spots, bathymetry and season were used in a spatially explicit Generalized Additive Model (GAM) to explain humpback whale distribution.

The model showed that whales preferred large, dense prey patches that occurred persistently. Whales were rarely found at patches covering less than 22 000 square meters vertically. With regards to depth, shallower patches at 40 meters depth were preferred. However, patches located at depths of approximately 90 meters were larger, occurred frequently, and were favored by whales as well. There was some indication that whales were more likely to be located at persistent prey hot spots.

A comparison of the prey patch explicit model and a model built using horizontal prey densities indicated that incorporating measures of prey depth and patch size greatly improved models of humpback whale distribution. The patch explicit model explained 59% of whale counts, while the horizontally averaged prey model explained 35%. Incorporating patch-explicit variables can be used to improve future modeling efforts for rorqual whale species abundance and distribution.

Popular Abstract

Humpack whales are looking for large, persistent krill patches

Humpback whales (Megaptera novaeangliae) feed on small schooling fish and krill. Krill is a small, schooling, shrimp-like crustacean. Humpback whales require dense prey aggregations to meet their energetic needs. This is because of their feeding strategy, called lunge feeding. Whales engulf a large mouthful of water, and any prey suspended in the water is filtered out through the whale’s baleen plates. These are brush-like ‘teeth’ that trap prey in the mouth. Whales must feed in areas with dense enough prey to make up for the cost of lunging. Whales also have to consider the cost of diving down to reach their prey and search costs in a patchy environment. Because of this, the density, size and depth of a prey patch should be important determinants of prey quality and should thus determine whale distribution.

In this study, I worked with a dataset showing the location of humpback whales and krill in Southeast Alaska, USA from 2006-2008. My aim was to see how spatial patterns in krill distribution affect the location of humpback whales. To do this, I built a spatially-explicit model that explained whale location based on various measures of krill patches.
I found that prey patchiness was important for whales in the study area. Whales were found in association with large prey patches. These are easier to find and take more time to deplete. Whales were associated most closely with two prey depths, at 90 and 40 meters. The largest and most frequently occurring patches were at approximately 90 meters. Whales may have optimized their search patterns for these patches, or they may be found at these patches because it is where the most food is available. Forty meters may represent the optimal foraging depth for a whale in this habitat. There was little prey above this depth. Presumably, whales prefer to minimize their diving cost and feed on shallower prey. Surprisingly, I did not find that prey density was important for foraging whales. This is most likely a result of how the data were processed, which smoothed out fine-scale variation in prey density.

In addition to the immediate prey conditions in an area, I found that whales were more likely to be found in persistent prey hot spots. Prey hot spots had more krill than the average conditions in the study area during most surveys. Whales may learn where prey conditions have been good in the past and return to these areas.
Understanding the foraging requirements of humpback whales is important for conservation. The krill fishery can be appropriately regulated as researchers begin to understand and protect what is important for marine predators. Conservation areas can be established based on knowledge of where whales and their preferred prey patches are regularly found. This work contributes to humpback whale conservation and expands on our general knowledge of the species.

• author: Walder, Christine
• supervisor: Jonathan Seaquist; Andrew Szabo
• organization: Dept of Physical Geography and Ecosystem Science
• alternative title: Lokalisering av knölvalar ([i]Megaptera novaeangliae[/i]) i sydöstra Alaska: vikten av krillstims ([i]Euphausiacea[/i]) djup och storlek inom modellering
• course: NGEM01 20181
• year: 2018
• type: H2 - Master's Degree (Two Years)
• subject: Earth and Environmental Sciences
• keywords: physical geography and ecosystem analysis, humpback whales, krill, patchiness, vertical distribution, Generalized Additive Models (GAMs), spatial modeling
• publication/series: Student thesis series INES
• report number: 443
• language: English
• additional info: External supervisor: Andrew Szabo, PhD, The Alaska Whale Foundation
• id: 8936797
• date added to LUP: 2018-04-27 10:51:47
• date last changed: 2020-03-04 03:39:30