Baleen whales are gigantic obligate filter feeders that exploit aggregations of small-bodied prey in littoral, epipelagic, and mesopelagic ecosystems. At the extreme of maximum body size observed among mammals, baleen whales exhibit a unique combination of high overall energetic demands and low mass-specific metabolic rates. As a result, most baleen whale species have evolved filter-feeding mechanisms and foraging strategies that take advantage of seasonally abundant yet patchily and ephemerally distributed prey resources. New methodologies consisting of multi-sensor tags, active acoustic prey mapping, and hydrodynamic modeling have revolutionized our ability to study the physiology and ecology of baleen whale feeding mechanisms. Here, we review the current state of the field by exploring several hypotheses that aim to explain how baleen whales feed. Despite significant advances, major questions remain about the processes that underlie these extreme feeding mechanisms, which enabled the evolution of the largest animals of all time.

It's the prey that matters: Although many people think of dinosaurs as being the largest creatures to have lived on Earth, the true largest known animal is still here today—the blue whale. How whales were able to become so large has long been of interest. Goldbogen et al. used field-collected data on feeding and diving events across different types of whales to calculate rates of energy gain (see the Perspective by Williams). They found that increased body size facilitates increased prey capture. Furthermore, body-size increase in the marine environment appears to be limited only by prey availability. Science , this issue p. 1367 ; see also p. 1316

How fast animals move is critical to understanding their energetic requirements, locomotor capacity, and foraging performance, yet current methods for measuring speed via animal-attached devices are not universally applicable. Here we present and evaluate a new method that relates forward speed to the stochastic motion of biologging devices since tag jiggle, the amplitude of the tag vibrations as measured by high sample rate accelerometers, increases exponentially with increasing speed. We successfully tested this method in a flow tank using two types of biologging devices and tested the method in situ on wild cetaceans spanning ∼3 to >20 m in length using two types of suction cup-attached and two types of dart-attached tag. This technique provides some advantages over other approaches for determining speed as it is device-orientation independent and relies only on a pressure sensor and a high sample rate accelerometer, sensors that are nearly universal across biologging device types.

The biology of the blue whale has long fascinated physiologists because of the animal’s extreme size. Despite high energetic demands from a large body, low mass-specific metabolic rates are likely powered by low heart rates. Diving bradycardia should slow blood oxygen depletion and enhance dive time available for foraging at depth. However, blue whales exhibit a high-cost feeding mechanism, lunge feeding, whereby large volumes of prey-laden water are intermittently engulfed and filtered during dives. This paradox of such a large, slowly beating heart and the high cost of lunge feeding represents a unique test of our understanding of cardiac function, hemodynamics, and physiological limits to body size. Here, we used an electrocardiogram (ECG)-depth recorder tag to measure blue whale heart rates during foraging dives as deep as 184 m and as long as 16.5 min. Heart rates during dives were typically 4 to 8 beats min ⁻¹ (bpm) and as low as 2 bpm, while after-dive surface heart rates were 25 to 37 bpm, near the estimated maximum heart rate possible. Despite extreme bradycardia, we recorded a 2.5-fold increase above diving heart rate minima during the powered ascent phase of feeding lunges followed by a gradual decrease of heart rate during the prolonged glide as engulfed water is filtered. These heart rate dynamics explain the unique hemodynamic design in rorqual whales consisting of a large-diameter, highly compliant, elastic aortic arch that allows the aorta to accommodate blood ejected by the heart and maintain blood flow during the long and variable pauses between heartbeats.

Bio-logging devices equipped with inertial measurement units—particularly accelerometers, magnetometers, and pressure sensors—have revolutionized our ability to study animals as necessary electronics have gotten smaller and more affordable over the last two decades. These animal-attached tags allow for fine scale determination of behavior in the absence of direct observation, particularly useful in the marine realm, where direct observation is often impossible, and recent devices can integrate more power hungry and sensitive instruments, such as hydrophones, cameras, and physiological sensors. To convert the raw voltages recorded by bio-logging sensors into biologically meaningful metrics of orientation (e.g., pitch, roll and heading), motion (e.g., speed, specific acceleration) and position (e.g., depth and spatial coordinates), we developed a series of MATLAB tools and online instructional tutorials. Our tools are adaptable for a variety of devices, though we focus specifically on the integration of video, audio, 3-axis accelerometers, 3-axis magnetometers, 3-axis gyroscopes, pressure, temperature, light and GPS data that are the standard outputs from Customized Animal Tracking Solutions (CATS) video tags. Our tools were developed and tested on cetacean data but are designed to be modular and adaptable for a variety of marine and terrestrial species. In this text, we describe how to use these tools, the theories and ideas behind their development, and ideas and additional tools for applying the outputs of the process to biological research. We additionally explore and address common errors that can occur during processing and discuss future applications. All code is provided open source and is designed to be useful to both novice and experienced programmers.