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Baleen whale prey consumption based on high-resolution foraging measurements

Abstract

Baleen whales influence their ecosystems through immense prey consumption and nutrient recycling1,2,3. It is difficult to accurately gauge the magnitude of their current or historic ecosystem role without measuring feeding rates and prey consumed. To date, prey consumption of the largest species has been estimated using metabolic models3,4,5,6,7,8,9 based on extrapolations that lack empirical validation. Here, we used tags deployed on seven baleen whale (Mysticeti) species (n = 321 tag deployments) in conjunction with acoustic measurements of prey density to calculate prey consumption at daily to annual scales from the Atlantic, Pacific, and Southern Oceans. Our results suggest that previous studies3,4,5,6,7,8,9 have underestimated baleen whale prey consumption by threefold or more in some ecosystems. In the Southern Ocean alone, we calculate that pre-whaling populations of mysticetes annually consumed 430 million tonnes of Antarctic krill (Euphausia superba), twice the current estimated total biomass of E. superba10, and more than twice the global catch of marine fisheries today11. Larger whale populations may have supported higher productivity in large marine regions through enhanced nutrient recycling: our findings suggest mysticetes recycled 1.2 × 104 tonnes iron yr−1 in the Southern Ocean before whaling compared to 1.2 × 103 tonnes iron yr−1 recycled by whales today. The recovery of baleen whales and their nutrient recycling services2,3,7 could augment productivity and restore ecosystem function lost during 20th century whaling12,13.

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Fig. 1: Field measurements informing baleen whale prey consumption and nutrient recycling.
Fig. 2: Individual rorqual daily feeding rate, water filtered and krill consumed.
Fig. 3: Individual annual prey consumption estimates, with comparison to prior estimates.
Fig. 4: Southern Ocean rorqual population-level water filtration, prey consumption and iron recycling.

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Data availability

Code to reproduce the figures and analyses in this paper are available at: https://github.com/mssavoca/prey_consumption_paper; all data and code are available on GitHub.

References

  1. Enquist, B. J., Abraham, A. J., Harfoot, M. B. J., Malhi, Y. & Doughty, C. E. The megabiota are disproportionately important for biosphere functioning. Nat. Commun. 11, 699 (2020).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  2. Doughty, C. E. et al. Global nutrient transport in a world of giants. Proc. Natl Acad. Sci. USA 113, 868–873 (2016).

    Article  ADS  CAS  PubMed  Google Scholar 

  3. Roman, J. & McCarthy, J. J. The whale pump: marine mammals enhance primary productivity in a coastal basin. PLoS ONE 5, e13255 (2010).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  4. Barlow, J., Kahru, M. & Mitchell, B. G. Cetacean biomass, prey consumption, and primary production requirements in the California Current ecosystem. Mar. Ecol. Prog. Ser. 371, 285–295 (2008).

    Article  ADS  Google Scholar 

  5. Fortune, S. M. E., Trites, A. W., Mayo, C. A., Rosen, D. A. S. & Hamilton, P. K. Energetic requirements of North Atlantic right whales and the implications for species recovery. Mar. Ecol. Prog. Ser. 478, 253–272 (2013).

    Article  ADS  Google Scholar 

  6. Trites, A. W., Christensen, V. & Pauly, D. Competition between fisheries and marine mammals for prey and primary production in the Pacific Ocean. J. Northwest Atl. Fish. Sci. 22, 173–187 (1997).

    Article  Google Scholar 

  7. Lavery, T. J. et al. Whales sustain fisheries: blue whales stimulate primary production in the Southern Ocean. Mar. Mammal Sci. 30, 888–904 (2014).

    Article  CAS  Google Scholar 

  8. Croll, D. A., Kudela, R. & Tershy, B. R. in Whales, Whaling, and Ocean Ecosystems (eds. Estes, J. A. et al.) 202–214 (Univ. California Press, 2006).

  9. Smith, L. A., Link, J. S., Cadrin, S. X. & Palka, D. L. Consumption by marine mammals on the Northeast U.S. continental shelf. Ecol. Appl. 25, 373–389 (2015).

    Article  PubMed  Google Scholar 

  10. Atkinson, A., Siegel, V., Pakhomov, E. A., Jessopp, M. J. & Loeb, V. A re-appraisal of the total biomass and annual production of Antarctic krill. Deep. Res. Part I Oceanogr. Res. Pap. 56, 727–740 (2009).

    Article  ADS  Google Scholar 

  11. Pauly, D. & Zeller, D. Catch reconstructions reveal that global marine fisheries catches are higher than reported and declining. Nat. Commun. 7, 10244 (2016).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  12. Estes, J. A., Heithaus, M., McCauley, D. J., Rasher, D. B. & Worm, B. Megafaunal Impacts on Structure and Function of Ocean Ecosystems. Annu. Rev. Environ. Resour. 41, 83–116 (2016).

    Article  Google Scholar 

  13. Smetacek, V. in Impacts of Global Warming on Polar Ecosystems (ed. Duarte, C. M.) 46–80 (Fundacion BBVA, 2008).

  14. Wing, S. et al. Seabirds and marine mammals redistribute bioavailable iron in the Southern Ocean. Mar. Ecol. Prog. Ser. 510, 1–13 (2014).

    Article  ADS  Google Scholar 

  15. Nicol, S. et al. Southern Ocean iron fertilization by baleen whales and Antarctic krill. Fish Fish. 11, 203–209 (2010).

    Article  Google Scholar 

  16. Ripple, W. J., Wolf, C., Newsome, T. M., Hoffmann, M. & Wirsing, A. J. Extinction risk is most acute for the world’s largest and smallest vertebrates. Proc. Natl Acad. Sci. USA 114, 10678–10683 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. McCauley, D. J. et al. Marine defaunation: animal loss in the global ocean. Science 347, 1255641 (2015).

    Article  PubMed  Google Scholar 

  18. Goldbogen, J. A. et al. How baleen whales feed: the biomechanics of engulfment and filtration. Ann. Rev. Mar. Sci. 9, 367–386 (2017).

    Article  CAS  PubMed  Google Scholar 

  19. Kleiber, M. The Fire of Life: An Introduction to Animal Energetics (Krieger, 1975).

  20. Nagy, K. A. Field metabolic rate and body size. J. Exp. Biol. 208, 1621–1625 (2005).

    Article  PubMed  Google Scholar 

  21. Roman, J. et al. Whales as marine ecosystem engineers. Front. Ecol. Environ. 12, 377–385 (2014).

    Article  Google Scholar 

  22. Atkinson, A., Siegel, V., Pakhomov, E. & Rothery, P. Long-term decline in krill stock and increase in salps within the Southern Ocean. Nature 432, 100–103 (2004).

    Article  ADS  CAS  PubMed  Google Scholar 

  23. Lee, C. I. L., Pakhomov, E., Atkinson, A. & Siegel, V. Long-term relationships between the marine environment, krill and salps in the Southern Ocean. J. Mar. Biol. 2010, 410129 (2010).

    Article  Google Scholar 

  24. Kahane-Rapport, S. R. & Goldbogen, J. A. Allometric scaling of morphology and engulfment capacity in rorqual whales. J. Morphol. 279, 1256–1268 (2018).

    Article  PubMed  Google Scholar 

  25. Goldbogen, J. A. et al. Why whales are big but not bigger: physiological drivers and ecological limits in the age of ocean giants. Science 366, 1367–1372 (2019).

    Article  ADS  CAS  PubMed  Google Scholar 

  26. Nickels, C. F., Sala, L. M. & Ohman, M. D. The morphology of euphausiid mandibles used to assess selective predation by blue whales in the southern sector of the California Current System. J. Crustac. Biol. 38, 563–573 (2018).

    Article  Google Scholar 

  27. Croll, D. A., Kudela, R. & Tershy, B. R. in Whales, Whaling, and Ocean Ecosystems (eds. Estes, J. A. et al.) 202–214 (Univ. California Press, 2006).

  28. Fleming, A. H., Clark, C. T., Calambokidis, J. & Barlow, J. Humpback whale diets respond to variance in ocean climate and ecosystem conditions in the California Current. Glob. Chang. Biol. 22, 1214–1224 (2015).

    Article  ADS  PubMed  Google Scholar 

  29. Katija, K. Biogenic inputs to ocean mixing. J. Exp. Biol. 215, 1040–1049 (2012).

    Article  PubMed  Google Scholar 

  30. Katija, K., Sherlock, R. E., Sherman, A. D. & Robison, B. H. New technology reveals the role of giant larvaceans in oceanic carbon cycling. Sci. Adv. 3, e1602374 (2017).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  31. Riisgård, H. U. On measurement of filtration rates in bivalves — the stony road to reliable data: review and interpretation. Mar. Ecol. Prog. Ser. 211, 275–291 (2001).

    Article  ADS  Google Scholar 

  32. Drenner, R. W., Mummert, J. R. & O’Brien, W. J. Filter-feeding rates of gizzard shad. Trans. Am. Fish. Soc. 111, 210–215 (1982).

    Article  Google Scholar 

  33. Rocha, R. C. Jr, Clapham, P. J. & Ivashchenko, Y. V. Emptying the oceans: a summary of industrial whaling catches in the 20th century. Mar. Fish. Rev. 76, 37–48 (2014).

    Article  Google Scholar 

  34. Christensen, L. B. Marine mammal populations: reconstructing historical abundances at the global scale. Fish. Cent. Res. Reports 14, 167 (2006).

    Google Scholar 

  35. Laws, R. M. Seals and whales of the Southern Ocean. Philos. Trans. R. Soc. B Biol. Sci. 279, 81–96 (1977).

    ADS  Google Scholar 

  36. Myers, R. A. & Worm, B. Rapid worldwide depletion of predatory fish communities. Nature 423, 280–283 (2003).

    Article  ADS  CAS  PubMed  Google Scholar 

  37. Trathan, P. N., Ratcliffe, N. & Masden, E. A. Ecological drivers of change at South Georgia: the krill surplus, or climate variability. Ecography 35, 983–993 (2012).

    Article  Google Scholar 

  38. Dunn, M. J. et al. Population size and decadal trends of three penguin species nesting at Signy Island, South Orkney Islands. PLoS ONE 11, e0164025 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Falkowski, P. G., Barber, R. T. & Smetacek, V. Biogeochemical controls and feedbacks on ocean primary production. Science 281, 200–206 (1998).

    Article  CAS  PubMed  Google Scholar 

  40. Ratnarajah, L. et al. A preliminary model of iron fertilisation by baleen whales and Antarctic krill in the Southern Ocean: sensitivity of primary productivity estimates to parameter uncertainty. Ecol. Modell. 320, 203–212 (2016).

    Article  Google Scholar 

  41. Willis, J. Whales maintained a high abundance of krill; both are ecosystem engineers in the Southern Ocean. Mar. Ecol. Prog. Ser. 513, 51–69 (2014).

    Article  ADS  Google Scholar 

  42. Gerber, L. R., Morissette, L., Kaschner, K. & Pauly, D. Should whales be culled to increase fishery yield? Science 323, 880–881 (2009).

    Article  CAS  PubMed  Google Scholar 

  43. Ruzicka, J. J., Steele, J. H., Ballerini, T., Gaichas, S. K. & Ainley, D. G. Dividing up the pie: whales, fish, and humans as competitors. Prog. Oceanogr. 116, 207–219 (2013).

    Article  ADS  Google Scholar 

  44. Arrigo, K. R., van Dijken, G. L. & Bushinsky, S. Primary production in the Southern Ocean, 1997-2006. J. Geophys. Res. Ocean. 113, C08004 (2008).

    Article  ADS  Google Scholar 

  45. Geremia, C. et al. Migrating bison engineer the green wave. Proc. Natl Acad. Sci. USA 116, 25707–25713 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Abrahms, B. et al. Memory and resource tracking drive blue whale migrations. Proc. Natl Acad. Sci. USA 116, 5582–5587 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Bar-on, Y. M., Phillips, R. & Milo, R. The biomass distribution on Earth. Proc. Natl Acad. Sci. USA 115, 6506–6511 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Pallin, L. J. et al. High pregnancy rates in humpback whales (Megaptera novaeangliae) around the Western Antarctic Peninsula, evidence of a rapidly growing population. R. Soc. Open Sci. 5, 180017 (2018).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  49. Aksnes, D. L. & Ohman, M. D. Multi-decadal shoaling of the euphotic zone in the southern sector of the California Current System. Limnol. Oceanogr. 54, 1272–1281 (2009).

    Article  ADS  Google Scholar 

  50. Krough, A. The physiology of the blue whale. Nature 133, 635–637 (1934).

    Article  ADS  Google Scholar 

  51. Lockyer, C. in Mammals in the Seas: Large Cetaceans (eds. Clarke, J. G., Goodman, J. & Soave, G. A.) 379–487 (FAO, 1981).

  52. Tamura, T. & Ohsumi, S. Regional assessments of prey consumption by marine cetaceans in the world. International Whaling Comission Scientific Report (2000); https://doi.org/10.1079/9780851996332.0143

  53. Leaper, R. & Lavigne, D. How much do large whales eat? J. Cetacean Res. Manag. 9, 179–188 (2007).

    Google Scholar 

  54. Klumov, S. K. Food and helminth fauna of whalebone whales (Mystacoceti) in the main whaling regions of the world ocean. Tr. Instituta Okeanol. 71, 94–194 (1963).

    Google Scholar 

  55. Sigurjónsson, J. & Víkingsson, G. A. Estimation of food consumption by cetaceans in Icelandic and adjacent waters. J. Northw. Atl. Fish. Sci 22, 271–287 (1997).

    Article  Google Scholar 

  56. Tamura, T. & Konishi, K. Food habit and prey consumption of Antarctic minke whale Balaenoptera bonaerensis in JARPA research area. Inst. Cetacean Res. Rep. SC/D06/J18 (2006).

  57. Kenney, R. D., Scott, G. P., Thompson, T. J. & Winn, H. E. Estimates of prey consumption and trophic impacts of cetaceans in the USA northeast continental shelf ecosystem. J. Northwest Atl. Fish. Sci. 22, 155–171 (1997).

    Article  Google Scholar 

  58. Innes, B. Y. S., Lavigne, D. M., Earle, W. M. & Kovacs, K. M. Feeding rates of seals and whales. J. Anim. Ecol. 56, 115–130 (1987).

    Article  Google Scholar 

  59. Tamura, T. & Konishi, K. Prey composition and consumption rate by Antarctic minke whales based on JARPA and JARPAII data. Inst. Cetacean Res. Rep. SC/F14/J15 (2014).

  60. Tamura, T. Preliminary analyses on prey consumption by fin whales based on JARPAII data. Inst. Cetacean Res. Rep. SC/F14/J16 (2014).

  61. Tamura, T., Konishi, K. & Isoda, T. Updated estimation of prey consumption by common minke, Bryde’s and sei whales in the western North Pacific. Inst. Cetacean Res. Rep. SC/F16/JR15 (2016).

  62. Lockyer, C. All creatures great and smaller: a study in cetacean life history energetics. J. Mar. Biol. Assoc. UK 87, 1035–1045 (2007).

    Article  Google Scholar 

  63. Víkingsson, G. A. Feeding of fin whales (Balaenoptera physalus) off Iceland - diurnal and seasonal variation and possible rates. J. Northwest Atl. Fish. Sci. 22, 77–89 (1997).

    Article  Google Scholar 

  64. Ichii, T. & Kato, H. Food and daily food consumption of southern minke whales in the Antarctic (Balaenoptera acutorostrata). Polar Biol. 11, 479–487 (1991).

    Article  Google Scholar 

  65. Tamura, T. & Konishi, K. Feeding habits and prey consumption of Antarctic minke whale (Balaenoptera bonaerensis) in the Southern Ocean. J. Northwest Atl. Fish. Sci. 42, 13–25 (2009).

    Article  Google Scholar 

  66. Lockyer, C. Body fat condition in northeast Atlantic fin whales, Balaenoptera physalus, and its relationship with reproduction and food resource. Can. J. Fish. Aquat. Sci. 43, 142–147 (1986).

    Article  Google Scholar 

  67. Goldbogen, J. A. et al. Using digital tags with integrated video and inertial sensors to study moving morphology and associated function in large aquatic vertebrates. Anat. Rec. 300, 1935–1941 (2017).

    Article  CAS  Google Scholar 

  68. Sumich, J. L. Swimming velocities, breathing patterns, and estimated costs of locomotion in migrating gray whales, Eschrichtius robustus. Can. J. Zool. 61, 647–652 (1983).

    Article  Google Scholar 

  69. Pauly, D., Trites, A. W., Capuli, E. & Christensen, V. Diet composition and trophic levels of marine mammals. ICES J. Mar. Sci. 55, 467–481 (1998).

    Article  Google Scholar 

  70. White, C. R. & Kearney, M. R. Metabolic scaling in animals: methods, empirical results, and theoretical explanations. Compr. Physiol. 4, 231–256 (2014).

    Article  PubMed  Google Scholar 

  71. Schmitz, O. J. & Lavigne, D. M. Intrinsic rate of increase, body size, and specific metabolic rate in marine mammals. Oecologia 62, 305–309 (1984).

    Article  ADS  CAS  PubMed  Google Scholar 

  72. Nagy, K. A., Girard, I. A. & Brown, T. K. Energetics of free-ranging mammals, reptiles, and birds. Annu. Rev. Nutr. 19, 247–277 (1999).

    Article  CAS  PubMed  Google Scholar 

  73. Rivero, J.-L. L. Locomotor muscle fibre heterogeneity and metabolism in the fastest large-bodied rorqual: the fin whale (Balaenoptera physalus). J. Exp. Biol. 221, jeb177758 (2018).

    Article  PubMed  Google Scholar 

  74. Friedlaender, A. S. et al. The advantages of diving deep: Fin whales quadruple their energy intake when targeting deep krill patches. Funct. Ecol. 34, 497–506 (2019).

    Article  Google Scholar 

  75. Calambokidis, J. et al. Differential vulnerability to ship strikes between day and night for blue, fin, and humpback whales based on dive and movement data from medium duration archival tags. Front. Mar. Sci. 6, 543 (2019).

    Article  Google Scholar 

  76. Cade, D. E., Friedlaender, A. S., Calambokidis, J. & Goldbogen, J. A. Kinematic diversity in rorqual whale feeding mechanisms. Curr. Biol. 26, 2617–2624 (2016).

    Article  CAS  PubMed  Google Scholar 

  77. Gough, W. T. et al. Scaling of swimming performance in baleen whales. J. Exp. Biol. 222, jeb204172 (2019).

    Article  PubMed  Google Scholar 

  78. Parks, S. E., Warren, J. D., Stamieszkin, K., Mayo, C. A. & Wiley, D. Dangerous dining: Surface foraging of North Atlantic right whales increases risk of vessel collisions. Biol. Lett. 8, 57–60 (2012).

    Article  PubMed  Google Scholar 

  79. Nowacek, D. P. et al. Buoyant balaenids: the ups and downs of buoyancy in right whales. Proc. R. Soc. B Biol. Sci. 268, 1811–1816 (2001).

    Article  CAS  Google Scholar 

  80. Johnson, M. P. & Tyack, P. L. A digital acoustic recording tag for measuring the response of wild marine mammals to sound. IEEE J. Ocean. Eng. 28, 3–12 (2003).

    Article  ADS  Google Scholar 

  81. Cade, D. E., Barr, K. R., Calambokidis, J., Friedlaender, A. S. & Goldbogen, J. A. Determining forward speed from accelerometer jiggle in aquatic environments. J. Exp. Biol. 221, 170449 (2018).

    Google Scholar 

  82. Goldbogen, J. A. et al. Integrative approaches to the study of baleen whale diving behavior, feeding performance, and foraging ecology. Bioscience 63, 90–100 (2013).

    Article  Google Scholar 

  83. Hazen, E. L., Friedlaender, A. S. & Goldbogen, J. A. Blue whales (Balaenoptera musculus) optimize foraging efficiency by balancing oxygen use and energy gain as a function of prey density. Sci. Adv. 1, e1500469 (2015).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  84. Cade, D. E. et al. Predator-scale spatial analysis of intra-patch prey distribution reveals the energetic drivers of rorqual whale super group formation. Fucntional Ecol. 35, 894–908 (2021).

    Article  Google Scholar 

  85. Nowacek, D. P. et al. Super-aggregations of krill and humpback whales in Wilhelmina bay, Antarctic Peninsula. PLoS ONE 6, 2–6 (2011).

    Article  Google Scholar 

  86. Goldbogen, J. A. et al. Prey density and distribution drive the three-dimensional foraging strategies of the largest filter feeder. Funct. Ecol. 29, 951–961 (2015).

    Article  Google Scholar 

  87. Cade, D. E., Carey, N., Domenici, P., Potvin, J. & Goldbogen, J. A. Predator-informed looming stimulus experiments reveal how large filter feeding whales capture highly maneuverable forage fish. Proc. Natl Acad. Sci. USA 117, 472–478 (2020).

    Article  CAS  PubMed  Google Scholar 

  88. Goldbogen, J. A. et al. Mechanics, hydrodynamics and energetics of blue whale lunge feeding: efficiency dependence on krill density. J. Exp. Biol. 214, 131–146 (2011).

    Article  CAS  PubMed  Google Scholar 

  89. Hamner, W. M. Aspects of schooling in Euphausia superba. J. Crustac. Biol. 4, 67–74 (1984).

    Article  Google Scholar 

  90. Potvin, J., Goldbogen, J. A. & Shadwick, R. E. Passive versus active engulfment: verdict from trajectory simulations of lunge-feeding fin whales Balaenoptera physalus. J. R. Soc. Interface 6, 1005–1025 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Potvin, J., Goldbogen, J. A. & Shadwick, R. E. Scaling of lunge feeding in rorqual whales: an integrated model of engulfment duration. J. Theor. Biol. 267, 437–453 (2010).

    Article  ADS  MathSciNet  CAS  PubMed  MATH  Google Scholar 

  92. Goldbogen, J. A. et al. Underwater acrobatics by the world’s largest predator: 360° rolling manoeuvres by lunge-feeding blue whales. Biol. Lett. 9, 20120986 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  93. Rodriguez-Romero, J., Palacios-Salgado, D. S., Lopez-Martinez, J., Vazquez, S. H. & Velazquez-Abunader, J. I. The length – weight relationship parameters of demersal fish species off the western coast of Baja California Sur, Mexico. J. Appl. Ichthology 25, 114–116 (2009).

    Article  Google Scholar 

  94. Pitcher, T. J. & Partridge, B. L. Fish school density and volume. Mar. Biol. 394, 383–394 (1979).

    Article  Google Scholar 

  95. Laidre, K. L., Heide-Jørgensen, M. P. & Nielsen, T. G. Role of the bowhead whale as a predator in West Greenland. Mar. Ecol. Prog. Ser. 346, 285–297 (2007).

    Article  ADS  Google Scholar 

  96. Simon, M., Johnson, M., Tyack, P. & Madsen, P. T. Behaviour and kinematics of continuous ram filtration in bowhead whales (Balaena mysticetus). Proc. R. Soc. B Biol. Sci. 276, 3819–3828 (2009).

    Article  Google Scholar 

  97. Baumgartner, M. F. & Mate, B. R. Summertime foraging ecology of North Atlantic right whales. Mar. Ecol. Prog. Ser. 264, 123–135 (2003).

    Article  ADS  Google Scholar 

  98. van der Hoop, J. M. et al. Foraging rates of ram‐filtering North Atlantic right whales. Funct. Ecol. 33, 1290–1306 (2019).

    Article  Google Scholar 

  99. Burnett, J. D. et al. Estimating morphometric attributes of baleen whales with photogrammetry from small UASs: a case study with blue and gray whales. Mar. Mammal Sci. 35, 108–139 (2019).

    Article  Google Scholar 

  100. Torres, W. I. & Bierlich, K. C. MorphoMetriX: a photogrammetric measurement GUI for morphometric analysis of megafauna. J. Open Source Softw. 5, 1825 (2020).

    Article  ADS  Google Scholar 

  101. Johnston, D. W. Unoccupied aircraft systems in marine science and conservation. Ann. Rev. Mar. Sci. 11, 439–463 (2019).

    Article  PubMed  Google Scholar 

  102. Durban, J. W. et al. Photogrammetry of blue whales with an unmanned hexacopter. Mar. Mammal Sci. 32, 1510–1515 (2016).

    Article  Google Scholar 

  103. Kelley, D. & Richards, C. oce: Analysis of Oceanographic Data R Package v. 1.1 (2019).

  104. Dubreuil, J. & Petitgas, P. Energy density of anchovy Engraulis encrasicolus in the Bay of Biscay. J. Fish Biol. 74, 521–534 (2009).

    Article  CAS  PubMed  Google Scholar 

  105. Chenowith, E. M. Bioenergetic and Economic Impacts of Humpback Whale Depredation at Salmon Hatchery Release Sites. PhD thesis, Univ. Alaska (2018).

  106. Werth, A. J. Models of hydrodynamic flow in the bowhead whale filter feeding apparatus. J. Exp. Biol. 207, 3569–3580 (2004).

    Article  PubMed  Google Scholar 

  107. Werth, A. in Feeding: Form, Function, and Evolution in Tetrapod Vertebrates (ed. Schwenk, K.) 487–526 (Academic, 2000).

  108. Mckinstry, C. A. E., Westgate, A. J. & Koopman, H. N. Annual variation in the nutritional value of stage V Calanus finmarchicus: implications for right whales and other copepod predators. Endang. Species Res. 20, 195–204 (2013).

    Article  Google Scholar 

  109. Folkow, L. P., Haug, T., Nilssen, K. T. & Nordy, E. S. Estimated food consumption of minke whales Balaenoptera acutorostrata in Northeast Atlantic waters in 1992-1995. NAMMCO Sci. Publ. 2, 65–80 (2000).

    Article  Google Scholar 

  110. Brodie, P. F. Cetacean energetics, an overview of intraspecific size variation. Ecology 56, 152–161 (1975).

    Article  ADS  Google Scholar 

  111. Hill, S. L. et al. Is current management of the antarctic krill fishery in the atlantic sector of the southern ocean precautionary? CCAMLR Sci. 23, 31–51 (2016).

    Google Scholar 

  112. Atkinson, A. et al. Oceanic circumpolar habitats of Antarctic krill. Mar. Ecol. Prog. Ser. 362, 1–23 (2008).

    Article  ADS  CAS  Google Scholar 

  113. Ratnarajah, L., Bowie, A. R., Lannuzel, D., Meiners, K. M. & Nicol, S. The biogeochemical role of baleen whales and krill in Southern Ocean nutrient cycling. PLoS ONE 9, e114067 (2014).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  114. Rose, C., Parker, A., Jefferson, B. & Cartmell, E. The characterization of feces and urine: a review of the literature to inform advanced treatment technology. Crit. Rev. Environ. Sci. Technol. 45, 1827–1879 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Candela, E., Camacho, M. V. & Perdomo, J. Iron absorption by humans and swine from Fe (III)-EDTA. Further studies. J. Nutr. 114, 2204–2211 (1984).

    Article  CAS  PubMed  Google Scholar 

  116. Ratnarajah, L. et al. A preliminary model of iron fertilisation by baleen whales and Antarctic krill in the Southern Ocean: sensitivity of primary productivity estimates to parameter uncertainty. Ecol. Modell. 320, 203–212 (2016).

    Article  Google Scholar 

  117. Twining, B. S., Baines, S. B. & Fisher, N. S. Element stoichiometries of individual plankton cells collected during the Southern Ocean Iron Experiment (SOFeX). Limnol. Oceanogr. 49, 2115–2128 (2004).

    Article  ADS  CAS  Google Scholar 

  118. Strzepek, R. F., Maldonado, M. T., Hunter, K. A., Frew, R. D. & Boyd, P. W. Adaptive strategies by Southern Ocean phytoplankton to lessen iron limitation: uptake of organically complexed iron and reduced cellular iron requirements. Limnol. Oceanogr. 56, 1983–2002 (2011).

    Article  ADS  CAS  Google Scholar 

  119. Quigg, A. et al. The evolutionary inheritance of elemental stoichiometry in marine phytoplankton. Nature 425, 291–294 (2003).

    Article  ADS  CAS  PubMed  Google Scholar 

  120. Wickham, H. ggplot2: Elegant Graphics for Data Analysis 2nd edn (Springer, 2016).

  121. Lockyer, C. Body weights of some species of large whales. ICES J. Mar. Sci. 36, 259–273 (1976).

    Article  Google Scholar 

  122. Blix, A. S. & Folkow, L. P. Daily energy expenditure in free living minke whales (Balaenoptera acutorostrata). Acta Physiol. Scand. 153, 61–66 (1995).

    Article  CAS  PubMed  Google Scholar 

  123. Nordoy, E. S., Folkow, L. P., Martensson, P. & Blix, A. S. Food requirements of Northeast Atlantic minke whales. Dev. Mar. Biol. 4, 307–317 (1995).

    Google Scholar 

  124. Murase, H., Tamura, T., Matsuoka, K. & Hakamada, T. First attempt of estimation of feeding impact on krill standing stock by three baleen whale species (Antarctic minke, humpback and fin whales) in Areas IV and V using JARPA dat. Inst. Cetacean Res. Rep. SC/D06/J22 (2006).

  125. Southall, B. L. et al. Behavioral responses of individual blue whales (Balaenoptera musculus) to mid-frequency military sonar. J. Exp. Biol. 222, jeb190637 (2019).

    Article  PubMed  Google Scholar 

  126. Goldbogen, J. A. et al. Blue whales respond to simulated mid-frequency military sonar. Proc. R. Soc. B 280, 20130657 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  127. Stimpert, A. K. et al. Sound production and associated behavior of tagged fin whales (Balaenoptera physalus) in the Southern California Bight. Anim. Biotelemetry 3, 1–12 (2015).

    Article  Google Scholar 

  128. Goldbogen, J. A. et al. Foraging behavior of humpback whales: kinematic and respiratory patterns suggest a high cost for a lunge. J. Exp. Biol. 211, 3712–3719 (2008).

    Article  PubMed  Google Scholar 

  129. Wiley, D. et al. Underwater components of humpback whale bubble-net feeding behaviour. Behaviour 148, 575–602 (2011).

    Article  Google Scholar 

  130. Friedlaender, A. S., Tyson, R. B., Stimpert, A. K., Read, A. J. & Nowacek, D. P. Extreme diel variation in the feeding behavior of humpback whales along the western Antarctic Peninsula during autumn. Mar. Ecol. Prog. Ser. 494, 281–289 (2013).

    Article  ADS  Google Scholar 

  131. Kahane-Rapport, S. R. et al. Lunge filter feeding biomechanics constrain rorqual foraging ecology across scale. J. Exp. Biol. 223, jeb224196 (2020).

    Article  PubMed  Google Scholar 

  132. Friedlaender, A. S. et al. Feeding rates and under-ice foraging strategies of the smallest lunge filter feeder, the Antarctic minke whale (Balaenoptera bonaerensis). J. Exp. Biol. 217, 2851–2854 (2014).

    Article  CAS  PubMed  Google Scholar 

  133. Domenici, P., Batty, R. S. & Similä, T. Spacing of wild schooling herring while encircled by killer whales. J. Fish Biol. 57, 831–836 (2000).

    Article  Google Scholar 

  134. Tamura, T. et al. Some examinations of uncertainties in the prey consumption estimates of common minke, sei and Bryde’s whales in the western North Pacific. (2009).

  135. Innes, S., Lavigne, D. M., Earle, W. M. & Kovacs, K. M. Estimating feeding rates of marine mammals from heart mass to body mass ratios. Mar. Mammal Sci. 2, 227–229 (1986).

    Article  Google Scholar 

  136. Armstrong, A. J. & Siegfried, W. R. Consumption of Antarctic krill by minke whales (Balaenoptera acutorostrata). Antarct. Sci. 3(1)13-18. 1991. 3, 13–18 (1991).

    Google Scholar 

  137. Reilly, S. et al. Biomass and energy transfer to baleen whales in the South Atlantic sector of the Southern Ocean. Deep. Res. Part II Top. Stud. Oceanogr. 51, 1397–1409 (2004).

    Article  ADS  Google Scholar 

  138. Read, A. J. & Brownstein, C. R. Considering other consumers: Fisheries, predators, and Atlantic herring in the Gulf of Maine. Conserv. Ecol. 7 (2003).

  139. Nagy, K. Food requirements of wild animals: predictive equations for free-living mammals, reptiles, and birds. Nutr. Abstr. Rev. Ser. B 71, 21R–31R (2001).

    Google Scholar 

  140. Stevick, P. T. et al. Trophic relationships and oceanography on and around a small offshore bank. Mar. Ecol. Prog. Ser. 363, 15–28 (2008).

    Article  ADS  Google Scholar 

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Acknowledgements

We would like to thank J. Barlow at NOAA’s Southwest Fisheries Science Center for an internal review of our manuscript, and R. Anderson for editorial assistance. D. Cade was integral in the fieldwork and on advising with the methods used in the manuscript. A. Atkinson and O. Schofield advised on the methods relating to Southern Ocean productivity. Illustrations in Fig. 3 were provided by K. Duthie, all other illustrations were provided by A. Boersma. Funding for this work was provided by the National Science Foundation (IOS 1656691, OPP 1644209, 1643877, 1250208, 1440435, PRFB 1906332), the Office of Naval Research Young Investigator Program (N000141612477), the Defense University Research Instrumentation Program (N00014-16-1-2546), the National Geographic Society (EC-53352R-18), the Percy Sladen Memorial Trust, the PADI Foundation, the Society for Marine Mammalogy, Torben og Alice Frimodts Fond, the Volgenau Foundation, the International Fund for Animal Welfare, and MAC3 Impact Philanthropies. Data collection was also supported by NSF Palmer LTER, WWF, OneOcean Expeditions, the Hogwarts Running Club, Cheeseman’s Ecology Safaris, and the American Cetacean Society.

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Contributions

M.S.S. and J.A.G. conceived and led the project. Data collection and initial processing by S.R.K-R., W.T.G., J.A.F., K.C.B., P.S.S., J.D., G.S.P., D.N.W., J.C., D.W.J., A.S.F., E.L.H. and J.A.G. Data analysed and visualized by M.F.C. and M.S.S. Manuscript drafted by M.S.S. with substantial contributions from M.F.C., E.L.H., N.D.P. and J.A.G. All authors edited and proofread the paper.

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Correspondence to Matthew S. Savoca.

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Peer review information Nature thanks Peter Corkeron, Kimberly Davies, Victor Smetacek and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data figures and tables

Extended Data Fig. 1 Prior estimates of daily prey consumption.

See Extended Data Table 3 for studies that use specific parameter values plotted in panels d, e and f. a, Daily ration (R) estimate using equation (1). Note that here B. edeni is representative of the Bryde’s whale complex that includes B. brydei. b, Mean daily consumption (MDC) estimate using equation (1) if 120 days spent feeding. c, Mean daily consumption (MDC) estimate using equation (1) if 90 days spent feeding. d, Daily ration (R) estimate using equation (2). e, Mean daily consumption (MDC) estimate using equation (2) if 120 days spent feeding. f, Mean daily consumption (MDC) estimate using equation (2) if 90 days spent feeding.

Extended Data Fig. 2 Map of field data.

Each point represents a tag deployment, coloured by species. The world map was generated from ref. 120. The icons of the RHIB with the echosounder represent regions where we have prey mapping data and were illustrated by Alex Boersma; drone icons indicate where we conducted drone measurements.

Extended Data Fig. 3 Analysis flowchart.

The outline of the analytical steps from field measurements to modelled daily krill consumption, and finally to projected annual consumption, and nutrients (for example, iron) recycled. Boxes with solid lines are data we collected, modelled and projected; dashed boxes are data we retrieved from other sources. The majority of our data, analyses, results, and inferences focused on krill-feeding rorqual whales (207 of 321 tag deployments), and this flow chart highlights those methods in particular. For details on the measured data, see: Methods sections ‘Tagging data’ and ‘Lunge detection methods’ for tag data; Methods section ‘Prey methods’ for prey data; Methods section ‘Drone/engulfment capacity methods’ for drone data; Methods section ‘Iron recycling and primary production’ for fecal iron concentrations. For details on the calculated information from the field data, see: Methods sections ‘Rorqual feeding rate methods’ and ‘Feeding rate validation’ for feeding rate (lunges h−1) calculations; Methods section ‘Prey methods’ for prey biomass calculations; Methods section ‘Drone/engulfment capacity methods’ for engulfment capacity calculations; Methods section ‘Annual and population-level projections’ for population size information. For details on the modelled outputs of daily prey ingestion and water filtration, see: Methods section ‘Daily prey consumption methods for rorquals’ for rorquals; Methods section ‘Balaenid water filtration and prey estimation methods’ for balaenids. For details on annual projected prey ingested, water filtered and iron recycled see: Methods section ‘Annual and population-level projections’ for prey ingested; Methods section ‘Iron recycling and primary production’ for iron recycled. For specific methods on fish-feeding rorquals see the ‘Fish’ subsection of the ‘Prey methods’ section, and for specific details on methods regarding balaenids, see the ‘Copepod’ portion of the ‘Prey methods’ section as well as section ‘Balaenid water filtration and prey estimation methods’.

Extended Data Fig. 4 Balaenid daily water filtration and prey consumption.

a, Visualization of an example bowhead whale (Ba. mysticetus) showing how water filtration was calculated. b, Water filtered per day for an individual bowhead (Ba. mysticetus) and North Atlantic right whale (Eu. glacialis). Density plots illustrate the full scope of all daily simulations with the height representing the relative probability of each output; the boxplots show the quartiles of these outputs with the thick line representing the median and the shaded region representing the Q1–Q3 range (25th−75th percentiles) of all modelled daily rates. For each species, the lower distribution represents a low effort foraging day (10 h feeding) and the higher distribution represents a high effort foraging day (15 h feeding). c, Prey consumed per day for an individual bowhead and North Atlantic right whale. Density plots illustrate the full scope of all daily simulations with the height representing the relative probability of each output; the boxplots show the quartiles of these outputs with the thick line representing the median and the shaded region representing the Q1–Q3 range (25th−75th percentiles) of all modelled daily rates. For each species, the lower distribution represents a low effort foraging day (10 h feeding) and the higher distribution represents a high effort foraging day (15 h feeding).

Extended Data Fig. 5 Additional daily prey consumption results.

ac, Estimated individual daily feeding rates, filtration volumes and prey consumption for fish-feeding humpback whales (M. novaeangliae) from the California Current and North Atlantic Ocean (Stellwagen Bank, Gulf of Maine), as well as for Bryde’s whales (Balaenoptera brydei) tagged off South Africa. The smaller distributions assume smaller fish schools that are 29% of the size of the engulfment volume (see Methods). Density plots illustrate the full scope of all daily simulations with the height representing the relative probability of each output; the boxplots show the quartiles of these outputs with the thick line representing the median and the shaded region representing the 25th−75th percentiles of all modelled daily rates. d, Non-Antarctic humpback, fin (B. physalus), and blue whales (B. musculus) prey consumption estimates. Density plots illustrate the full scope of all daily simulations with the height representing the relative probability of each output; the boxplots show the quartiles of these outputs with the thick line representing the median and the shaded region representing the 25th−75th percentiles of all modelled daily rates. e, Mass-specific daily energy intake. Species-specific average whale mass was calculated using our drone-length measurements (Extended Data Table 1), converting to body weight according to ref. 121. Average prey energy density for Antarctic krill, eastern North Pacific krill (2 spp.), forage fish, and copepods described in sections ‘Daily prey consumption methods for rorquals’ and ‘Balaenid water filtration and prey estimation methods’. Dashed horizontal line represents 80 kJ kg−1 d−1 (converted to 242.36 kJ kg−1 d−1 via MDC methodology), which previous studies have used to estimate mysticete prey consumption122,123,124. Boxplots show the quartiles of all modelled daily outputs with the thick line representing the median and the shaded region representing the 25th−75th percentiles of all modelled daily rates. f, Mass-specific daily energy intake using Antarctic krill TS–L equations for North Pacific krill, as has been used in previous studies74,83,86. Boxplots show the quartiles of all modelled daily outputs with the thick line representing the median and the shaded region representing the 25th−75th percentiles of all modelled daily rates. Dashed horizontal line represents 80 kJ kg−1 d−1 (converted to 242.36 kJ kg−1 d−1 via MDC methodology), which previous studies have used to estimate mysticete prey consumption122,123,124. Falling largely below the horizontal dashed line, this level of prey consumption would probably not be possible for these rorqual species to meet their energetic demands.

Extended Data Fig. 6 Feeding rate validation measurements and weighting curve.

a, Using medium term tags attached to ENP blue whales (B. musculus), we calculated the mean absolute error in daily lunge rate estimation when randomly subsampling and quantifying hourly lunge rates from different duration blocks of multi-day tag deployments. This analysis showed that the longer a sub-daily deployment is, the more accurate and precise it becomes in estimating the daily lunge rate. b, Using data from panel a, we generated a custom weighting function which we applied to all deployments in our dataset, accounting for our increased confidence in the lunge rates of longer deployments. Deployments ≥10 h were weighted equally.

Extended Data Table 1 Summary of baleen whale data measured, calculated, and modelled
Extended Data Table 2 Calculations to estimate primary production stimulated by whale recycled iron in the Southern Ocean
Extended Data Table 3 Parameters used to estimate mysticete prey consumption
Extended Data Table 4 Summary of tag deployments

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Savoca, M.S., Czapanskiy, M.F., Kahane-Rapport, S.R. et al. Baleen whale prey consumption based on high-resolution foraging measurements. Nature 599, 85–90 (2021). https://doi.org/10.1038/s41586-021-03991-5

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