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Baleen whale prey consumption based on high-resolution foraging measurements

Nature volume 599, pages 85–90 (2021)Cite this article

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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.

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.

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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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Authors and Affiliations

  1. Hopkins Marine Station, Stanford University, Pacific Grove, CA, USA

    Matthew S. Savoca, Max F. Czapanskiy, Shirel R. Kahane-Rapport, William T. Gough, James A. Fahlbusch, Paolo S. Segre, Elliott L. Hazen & Jeremy A. Goldbogen

  2. Cascadia Research Collective, Olympia, WA, USA

    James A. Fahlbusch & John Calambokidis

  3. Duke University Marine Laboratory, Duke University, Beaufort, NC, USA

    K. C. Bierlich, Douglas P. Nowacek & David W. Johnston

  4. Marine Mammal Institute, Hatfield Marine Science Center, Oregon State University, Newport, OR, USA

    K. C. Bierlich

  5. Department of Biology, University of Copenhagen, Copenhagen, Denmark

    Jacopo Di Clemente

  6. Department of Biology, University of Southern Denmark, Odense, Denmark

    Jacopo Di Clemente

  7. Department of Bioscience, Aarhus University, Aarhus, Denmark

    Jacopo Di Clemente

  8. Institute for Coastal and Marine Research, Nelson Mandela University, Port Elizabeth, South Africa

    Gwenith S. Penry

  9. Stellwagen Bank National Marine Sanctuary, NOAA National Ocean Service, Scituate, MA, USA

    David N. Wiley

  10. Department of Paleobiology, National Museum of Natural History, Washington, DC, USA

    Nicholas D. Pyenson

  11. Department of Paleontology and Geology, Burke Museum of Natural History and Culture, Seattle, WA, USA

    Nicholas D. Pyenson

  12. Long Marine Laboratory, University of California, Santa Cruz, Santa Cruz, CA, USA

    Ari S. Friedlaender & Elliott L. Hazen

  13. Environmental Research Division, NOAA Southwest Fisheries Science Center, Monterey, CA, USA

    Elliott L. Hazen

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  1. Matthew S. Savoca
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  2. Max F. Czapanskiy
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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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The authors declare no competing interests.

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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.

a–c, 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
Full size table
Extended Data Table 2 Calculations to estimate primary production stimulated by whale recycled iron in the Southern Ocean
Full size table
Extended Data Table 3 Parameters used to estimate mysticete prey consumption
Full size table
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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