Bulk filter feeding has enabled gigantism throughout evolutionary history. The largest animals, extant rorqual whales, utilize intermittent engulfment filtration feeding (lunge feeding), which increases in efficiency with body size, enabling their gigantism. The smallest extant rorquals (7–10 m minke whales), however, still exhibit short-term foraging efficiencies several times greater than smaller non-filter-feeding cetaceans, raising the question of why smaller animals do not utilize this foraging modality. We collected 437 h of bio-logging data from 23 Antarctic minke whales (Balaenoptera bonaerensis) to test the relationship of feeding rates (λf) to body size. Here, we show that while ultra-high nighttime λf (mean ± s.d.: 165 ± 40 lunges h−1; max: 236 lunges h−1; mean depth: 28 ± 46 m) were indistinguishable from predictions from observations of larger species, daytime λf (mean depth: 72 ± 72 m) were only 25–40% of predicted rates. Both λf were near the maxima allowed by calculated biomechanical, physiological and environmental constraints, but these temporal constraints meant that maximum λf was below the expected λf for animals smaller than ~5 m—the length of weaned minke whales. Our findings suggest that minimum size for specific filter-feeding body plans may relate broadly to temporal restrictions on filtration rate and have implications for the evolution of filter feeding.
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The datasets analysed during the current study are available at Stanford’s digital repository, https://purl.stanford.edu/pm378wm1385. This deposit includes processed bio-logging data describing animal orientation, motion and position; video data used to calculate engulfment timing; audited feeding data including indices of identified foraging events and start and end points of feeding bouts; summarized foraging data for all species; and aerial imagery and length analysis.
Custom code and a wiki tutorial for processing raw tag data into animal orientation, motion and position is available in ref. 84 and directly at https://github.com/wgough/CATS-Methods-Materials.
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This work was primarily funded with NSF OPP grant no. 1643877, with additional funding from ONR YIP grant no. N000141612477 and Stanford University’s Terman Fellowship. This work was authorized under NMFS permits 16111 and 23095 and ACA permit 2020-016. We wish to thank J. Dale, C. Taylor, E. Levy and P. Gray for their contributions to data collection. A special thanks is also extended to the scientists and crew of the Lawrence M Gould, especially E. Hutt and the marine techs.
The authors declare no competing interests.
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Extended Data Fig. 1 Constraints on intake rate in rorqual whales.
First published in34, reproduced with permission. Three-dimensional plot crafted in Echoview v.10 using a 10x vertical exaggeration and 120 kHz data, with the spatially matched track of a tagged blue whale. Biomass estimated as in48. Two-dimensional plots are temporally linked echosounding data with the tagged whale’s depth profile. Illustrations © Alex Boersma.
Extended Data Fig. 2 Proportion of diel periods spent feeding.
Proportion of diel periods spent feeding (deployments with at least 4 hours of data in corresponding diel period).
Extended Data Fig. 3 Regressions of feeding rate on length, using only measured whales.
Regressions of feeding rate using only measured blue and humpback whales. Shallow feeding slope is slightly shallower, other differences are non-significant from the regressions in Fig. 2H-J. Slope 95% confidence intervals (CI) and F-statistics are displayed, p-values are for the 2-sided F-test that the indicated regression has a slope different than the expected scaling slope. Both axes are log scales.
Extended Data Fig. 4 Relationship of dive behavior to body length.
Lack of relationship between A) mean dive duration or B) mean dive depth and body length in AMW for daytime dives. Error bars are standard error. C) Mean dive time relative to dive depth, as a function of length, for daytime dives > 70 m. Error bars are standard error. Sample sizes listed in Extended Data Table 1.
Extended Data Fig. 5 Dive interval compared to dive duration.
AMW surface interval increases with foraging dive duration. Colors represent individual animals. Shown is data for foraging dives > 100 s and with surface intervals > 10 s. Blue whale data reproduced from Fig. 2 in53. A) Surface interval between a foraging dive and the following foraging dive (> 35 m), n = 3158 dives. B) Surface interval between a foraging dive and the preceding foraging dive, n = 3147 dives.
Extended Data Fig. 6 Proportion of total lunge duration taken up by each component of lunge feeding.
Proportion of total lunge duration taken up by each component of lunge feeding. Filtration, the component with the strongest relationship to length, demonstrates a rapidly reduction in its effect on total lunge time (and maximum lunge rate) as size decreases.
Extended Data Fig. 7 Estimation of divisions between foraging bouts.
Surface interval between foraging dives for AMW. Black bars are surface intervals from foraging dives with at least 2 lunges until the next foraging dive. Red is the surface intervals for all foraging dives. The surface interval duration corresponding to the mean of the largest fitted Gaussian curve in the bulk of the data + 3 SD was used to differentiate “foraging bouts.” That is, a “foraging bout” was defined as the combined duration of all dives where the surface interval between dives with foraging effort was less than six minutes (the dashed vertical bar). The duration of a foraging bout was thus defined from the start of the first dive to six minutes after the last foraging dive. See48 for additional justification for this method in blue and humpback whales.
Extended Data Fig. 8 Seasonal changes in predicted Antarctic minke whale (AMW).
Seasonal changes in predicted Antarctic minke whale (AMW) daily intake over a six-month feeding season. A) Day/night lengths at the field site (64.8°S, 62.7°W). The period of no darkness lasts from Nov 19 to Jan 24. The results of this model could also be interpreted as the proportion of shallow or deep lunges available at a given point in time. B) Day, night and total lunges assuming the observed feeding rates during the field season are maintained as well as the observed portion of the day (64%) and night (57%) spent feeding. Solid lines are prediction from regression (Fig. 2F); for the theoretical 3 m whale, this is an extension past observed points. C) The portion of available daylight that an AMW would have to feed to match the mean total daily feeding rates we observed in late Feb/early Mar. Whales 7 m and larger could match the observed feeding rates during peak summer even if prey conditions didn’t change, but whales 5 m and smaller would require shallower daytime prey. In all cases, twilight feeding rates were assumed to be the corresponding mean of daytime and nighttime feeding rates. D) The proportion of daylight hours a whale of different lengths would have to spend feeding at the summer solstice to match the total intake observed in Feb/Mar, given the indicated day/night ratio of caloric value per lunge.
Supplementary Boxes 1–5.
Supplementary Video 1
Camera data for two minke whales, highlighting the three phases of lunge feeding. Credit for illustrations: Audrey Nguyen.
Supplementary Video 2
Identification of start and end frames of engulfment to determine VGBest (see Fig. 1a).
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Cade, D.E., Kahane-Rapport, S.R., Gough, W.T. et al. Minke whale feeding rate limitations suggest constraints on the minimum body size for engulfment filtration feeding. Nat Ecol Evol (2023). https://doi.org/10.1038/s41559-023-01993-2