Insight into the kinematics of blue whale surface foraging through drone observations and prey data

Abstract

To understand how predators optimize foraging strategies, extensive knowledge of predator behavior and prey distribution is needed. Blue whales employ an energetically demanding lunge feeding method that requires the whales to selectively feed where energetic gain exceeds energetic loss, while also balancing oxygen consumption, breath holding capacity, and surface recuperation time. Hence, blue whale foraging behavior is primarily driven by krill patch density and depth, but many studies have not fully considered surface feeding as a significant foraging strategy in energetic models. We collected predator and prey data on a blue whale (Balaenoptera musculus brevicauda) foraging ground in New Zealand in February 2017 to assess the distributional and behavioral response of blue whales to the distribution and density of krill prey aggregations. Krill density across the study region was greater toward the surface (upper 20 m), and blue whales were encountered where prey was relatively shallow and more dense. This relationship was particularly evident where foraging and surface lunge feeding were observed. Furthermore, New Zealand blue whales also had relatively short dive times (2.83 ± 0.27 SE min) as compared to other blue whale populations, which became even shorter at foraging sightings and where surface lunge feeding was observed. Using an unmanned aerial system (UAS; drone) we also captured unique video of a New Zealand blue whale's surface feeding behavior on well-illuminated krill patches. Video analysis illustrates the whale's potential use of vision to target prey, make foraging decisions, and orient body mechanics relative to prey patch characteristics. Kinematic analysis of a surface lunge feeding event revealed biomechanical coordination through speed, acceleration, head inclination, roll, and distance from krill patch to maximize prey engulfment. We compared these lunge kinematics to data previously reported from tagged blue whale lunges at depth to demonstrate strong similarities, and provide rare measurements of gape size, and krill response distance and time. These findings elucidate the predator-prey relationship between blue whales and krill, and provide support for the hypothesis that surface feeding by New Zealand blue whales is an important component to their foraging ecology used to optimize their energetic efficiency. Understanding how blue whales make foraging decisions presents logistical challenges, which may cause incomplete sampling and biased ecological knowledge if portions of their foraging behavior are undocumented. We conclude that surface foraging could be an important strategy for blue whales, and integration of UAS with tag-based studies may expand our understanding of their foraging ecology by examining surface feeding events in conjunction with behaviors at depth.

Keywords: Blue whale; Energetics; Foraging ecology; Krill; New Zealand; Optimal foraging theory; Predator-prey interactions; Prey response; Surface lunge feeding; Unmanned aerial systems.

Figure 1. Blue whale survey tracklines and sighting locations.

Survey tracklines in 2017 in the South Taranaki Bight (STB) with locations of blue whale sightings, and where surface lunge feeding was observed, denoted. Inset map shows location of the STB within New Zealand.

Figure 2. Body kinematics, and corresponding still images, during blue whale surface lunge feeding event derived from Unmanned Aerial Systems (UAS) image analysis.

(A) Mean head inclination and roll (with CV in shaded areas), (B) relative speed and acceleration, and (C) distance from the tip of the whale’s rostrum to the nearest edge of krill patch. Blue line on plots indicate when krill first respond to the predation event, and the purple dashed lines indicate strike at time = 0. The orange lines indicate the time at which the whale’s gape is widest, head inclination is maximum, and deceleration is greatest. (D) Image of whale eyeing krill patch with measured distance between eye and patch. (E) Image taken when krill begin to respond to predation event. (F) Image illustrating krill flee response. (G) Image of widest gape and angle measurement. Comparative images of krill patch size and density (H) pre- and (I) post-strike. Comparative images of head inclination (J) 2 s pre-strike, (K) at strike, and (L) post-strike of surface lunge feeding event (Example roll images in Fig. S2). Images in D–L are cropped to enhance illustrations (raw video available in the Supplemental Information). All images captured at 29.5 m altitude.

Figure 3. Density contours comparing the depth and density (Sv) of krill aggregations at blue whale foraging sightings (red shading) and in absence of blue whales (grey shading).

Density contours: 25% = darkest shade, 75% = medium shade, 95% = light shade. Blue circles indicate krill aggregations detected within 2 km of the sighting of the UAS filmed surface foraging whale analyzed in this study.

Figure 4. Still images from UAS video of three separate surface blue whale foraging events captured when it was estimated that the whale visually detects the krill patch with her right eye.

Measured distances between the eye and closest edge of krill patch are given for event 1 (A), event 2 (B) and event 3 (C). See Table 2 for details.