Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Vast assembly of vocal marine mammals from diverse species on fish spawning ground

Nature volume 531, pages 366–370 (2016)Cite this article

Subjects

Abstract

Observing marine mammal (MM) populations continuously in time and space over the immense ocean areas they inhabit is challenging but essential for gathering an unambiguous record of their distribution, as well as understanding their behaviour and interaction with prey species1,2,3,4,5,6. Here we use passive ocean acoustic waveguide remote sensing (POAWRS)7,8 in an important North Atlantic feeding ground9,10 to instantaneously detect, localize and classify MM vocalizations from diverse species over an approximately 100,000 km2 region. More than eight species of vocal MMs are found to spatially converge on fish spawning areas containing massive densely populated herring shoals at night-time11,12,13,14,15,16 and diffuse herring distributions during daytime. We find the vocal MMs divide the enormous fish prey field into species-specific foraging areas with varying degrees of spatial overlap, maintained for at least two weeks of the herring spawning period. The recorded vocalization rates are diel (24 h)-dependent for all MM species, with some significantly more vocal at night and others more vocal during the day. The four key baleen whale species of the region: fin, humpback, blue and minke have vocalization rate trends that are highly correlated to trends in fish shoaling density and to each other over the diel cycle. These results reveal the temporospatial dynamics of combined multi-species MM foraging activities in the vicinity of an extensive fish prey field that forms a massive ecological hotspot, and would be unattainable with conventional methodologies. Understanding MM behaviour and distributions is essential for management of marine ecosystems and for accessing anthropogenic impacts on these protected marine species1,2,3,4,5,17,18.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Full diel cycle distributions of MM vocalizations and fish.
Figure 2: Day and night distributions of MM vocalizations and fish.
Figure 3: POAWRS MM detection region and cumulative nocturnal MM call rate distribution.
Figure 4: Diel MM call rate and herring shoal areal population density time series.

Similar content being viewed by others

References

  1. Tittensor, D. P. et al. Global patterns and predictors of marine biodiversity across taxa. Nature 466, 1098–1101 (2010)

    ADS  CAS  Google Scholar 

  2. Schofield, O. et al. How do polar marine ecosystems respond to rapid climate change? Science 328, 1520–1523 (2010)

    ADS  CAS  Google Scholar 

  3. Block, B. A. et al. Tracking apex marine predator movements in a dynamic ocean. Nature 475, 86–90 (2011)

    CAS  Google Scholar 

  4. Noad, M., Cato, D., Bryden, M., Jenner, M. & Jenner, K. Cultural revolution in whale songs. Nature 408, 537 (2000)

    ADS  CAS  Google Scholar 

  5. Miller, P. J., Biassoni, N., Samuels, A. & Tyack, P. L. Whale songs lengthen in response to sonar. Nature 405, 903 (2000)

    ADS  CAS  Google Scholar 

  6. Kaschner, K., Quick, N. J., Jewell, R., Williams, R. & Harris, C. M. Global coverage of cetacean line-transect surveys: status quo, data gaps and future challenges. PLoS ONE 7, e44075 (2012)

    CAS  Google Scholar 

  7. Gong, Z. et al. Ecosystem scale acoustic sensing reveals humpback whale behavior synchronous with herring spawning processes and re-evaluation finds no effect of sonar on humpback song occurrence in the Gulf of Maine in fall 2006. PLoS ONE 9, e104733 (2014)

    ADS  PubMed  PubMed Central  Google Scholar 

  8. Tran, D. D. et al. Using a coherent hydrophone array for observing sperm whale range, classification, and shallow-water dive profiles. J. Acoust. Soc. Am. 135, 3352–3363 (2014)

    ADS  Google Scholar 

  9. Overholtz, W. J. & Link, J. S. Consumption impacts by marine mammals, fish, and seabirds on the Gulf of Maine–Georges Bank Atlantic herring (Clupea harengus) complex during the years 1977–2002. ICES J. Mar. Sci. 64, 83–96 (2007)

    Google Scholar 

  10. Waring, G. T., Josephson, E., Maze-Foley, K. & Rosel, P. E. U.S. Atlantic and Gulf of Mexico Marine Mammal Stock Assessments 2014. NOAA Tech Memo NMFS NE Vol. 231 (2014)

  11. Makris, N. C. et al. Fish population and behavior revealed by instantaneous continental shelf-scale imaging. Science 311, 660–663 (2006)

    ADS  CAS  Google Scholar 

  12. Makris, N. C. et al. Critical population density triggers rapid formation of vast oceanic fish shoals. Science 323, 1734–1737 (2009)

    ADS  CAS  Google Scholar 

  13. Gong, Z. et al. Low-frequency target strength and abundance of shoaling Atlantic herring (Clupea harengus) in the Gulf of Maine during the ocean acoustic waveguide remote sensing 2006 experiment. J. Acoust. Soc. Am. 127, 104–123 (2010)

    ADS  Google Scholar 

  14. Jagannathan, S. et al. Ocean acoustic waveguide remote sensing (OAWRS) of marine ecosystems. Mar. Ecol. Prog. Ser. 395, 137–160 (2009)

    ADS  Google Scholar 

  15. Jech, J. M. & Stroman, F. Aggregative patterns of pre-spawning Atlantic herring on Georges Bank from 1999–2010. Aquat. Living Resour. 25, 1–14 (2012)

    Google Scholar 

  16. 54th Northeast Regional Stock Assessment Workshop (54th SAW) Assessment Report. Part A. Atlantic herring stock assessment for 2012. US Dept Commer, Northeast Fish Sci. Cent. Ref. Doc. 12–18; 600 p. http://www.nefsc.noaa.gov/publications/ (2012)

  17. deYoung B., Heath, M., Werner, F., Chai, F., Megrey, B. & Monfray, P. Challenges of modeling ocean basin ecosystems. Science 304, 1463–1466 (2004)

    ADS  Google Scholar 

  18. Overholtz, W. & Link, J. A simulation model to explore the response of the Gulf of Maine food web to large-scale environmental and ecological changes. Ecol. Modell. 220, 2491–2502 (2009)

    Google Scholar 

  19. Kay, S. M. Fundamentals of statistical signal processing, Vol. II: Detection Theory. (Prentice Hall, 1998)

  20. Mayo, C. A. & Marx, M. K. Surface foraging behavior of the North Atlantic right whale, Eubalaena glacialis, and associated zooplankton characteristics. Can. J. Zool. 68, 2214–2220 (1990)

    Google Scholar 

  21. Dolphin, W. F. Prey densities and foraging of humpback whales, Megaptera novaeangliae. Experientia 43, 468–471 (1987)

    Google Scholar 

  22. Sims, D. W. & Quayle, V. A. Selective foraging behavior of basking sharks on zooplankton in a small scale front. Nature 393, 460–464 (1998)

    ADS  CAS  Google Scholar 

  23. Baumgartner, M. F. & Frantantoni, D. M. Diel periodicity in both sei whale vocalization rates and the vertical migration of their copepod prey observed from ocean gliders. Limnol. Oceanogr. 53, 2197–2209 (2008)

    ADS  Google Scholar 

  24. Nøttestad, L., Fern, A., Mackinson, S., Pitcher, T. & Misund, O. A. How whales influence herring school dynamics in a cold-front area of the Norwegian Sea. ICES J. Mar. Sci. 59, 393–400 (2002)

    Google Scholar 

  25. Janik, V. M. Whistle matching in wild bottlenose dolphins (Tursiops truncatus). Science 289, 1355–1357 (2000)

    ADS  CAS  Google Scholar 

  26. Berchok, C. L., Bradley, D. L. & Gabrielson, T. B. St. Lawrence blue whale vocalizations revisited: characterization of calls detected from 1998 to 2001. J. Acoust. Soc. Am. 120, 2340–2354 (2006 )

    ADS  Google Scholar 

  27. Wiggins, S. M., Oleson, E. M., McDonald, M. A. & Hildebrand, J. A. Blue whale (Blaenoptera musculus) diel call patterns offshore of Southern California. Aquat. Mamm. 31, 161–168 (2005)

    Google Scholar 

  28. Similä, T. Sonar observations of killer whales (Orcinus orca) feeding on herring schools. Aquat. Mamm. 23, 119–126 (1997)

    Google Scholar 

  29. Wiirsig, B. Delphinid foraging strategies in Dolphin cognition and Behavior: a Comparative Approach 347–359 (Psychology Press, 1986)

  30. Buckland, S. T. et al. Introduction to Distance Sampling: Estimating Abundance of Biological Population (Oxford Univ. Press, 2001)

  31. Becker, K. & Preston, J. R. The ONR five octave research array (FORA) at Penn State. Proc. OCEANS ‘03 5, 26072610 (2003)

    Google Scholar 

  32. Overholtz, W. J. et al. Stock assessment of the Gulf of Maine-Georges Bank Atlantic herring complex, 2003. Northeast Fisheries Science Center References Document 4, 1–290 (2004)

    Google Scholar 

  33. Melvin, G. D. & Stephenson, R. L. The dynamics of a recovering fish stock: Georges Bank herring. ICES J. Mar. Sci. 64, 69–82 (2007)

    Google Scholar 

  34. Read, A. J. & Brownstein, C. R. Considering other consumers: fisheries, predators, and Atlantic herring in the Gulf of Maine. Conserv. Ecol. 7, 2 (2003)

    Google Scholar 

  35. Oppenheim, A. V., Willsky, A. S. & Nawab, S. H. Signals and Systems (PrenticeHall, 1997)

  36. Johnson, D. H. & Dudgeon, D. E. Array Signal Processing: Concepts and Techniques (Simon & Schuster, 1992)

  37. Baumgartner, M. F. et al. A generalized baleen whale call detection and classification system. J. Acoust. Soc. Am. 129, 2889–2902 (2011)

    ADS  Google Scholar 

  38. Shapiro, A. D. & Wang, C. A versatile pitch tracking algorithm: From human speech to killer whale vocalizations. J. Acoust. Soc. Am. 126, 451–459 (2009)

    ADS  Google Scholar 

  39. Wang, C. & Seneff, S. Robust pitch tracking for prosodic modeling in telephone speech. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE, Piscataway, NJ) 1143–1145 (2000)

  40. Duda, R. O., Hart, P. E. & Stork, D. G. Pattern Classification 2nd edn (John Wiley & Sons, 2001)

  41. Watkins, W. A., Tyack, P., Moore, K. E. & Bird, J. E. The 20-Hz signals of finback whales (Balaenoptera physalus). J. Acoust. Soc. Am. 82, 1901–1912 (1987)

    ADS  CAS  Google Scholar 

  42. Edds, P. L. Characteristics of finback Balaenoptera physalus vocalizations in the St. Lawrence Estuary. Bioacoustics 1, 131–149 (1988)

    Google Scholar 

  43. Nieukirk, S. L. et al. Sounds from airguns and fin whales recorded in the mid-Atlantic Ocean, 1999–2009. J. Acoust. Soc. Am. 131, 1102–1112 (2012)

    ADS  Google Scholar 

  44. Thompson, P. O., Findley, L. T. & Vidal, O. 20 Hz pulses and other vocalizations of fin whales, Balaenoptera physalus, in the Gulf of California, Mexico. J. Acoust. Soc. Am. 92, 3051–3057 (1992)

    ADS  CAS  Google Scholar 

  45. McDonald, M. A., Hildebrand, J. A. & Webb, S. C. Blue and fin whales observed on a seafloor array in the Northeast Pacific. J. Acoust. Soc. Am. 98, 712–721 (1995)

    ADS  CAS  Google Scholar 

  46. Croll, D. A. et al. Only male fin whales sing loud songs. Nature 417, 809 (2002)

    ADS  CAS  Google Scholar 

  47. Oleson, E. M. Behavioral context of call production by eastern North Pacific blue whales. Mar. Ecol. Prog. Ser. 330, 269–284 (2007)

    ADS  Google Scholar 

  48. McDonald, M. A., Calambokidis, J., Teranishi, A. M. & Hildebrand, J. A. The acoustic calls of blue whales off California with gender data. J. Acoust. Soc. Am. 109, 1728–1735 (2001)

    ADS  CAS  Google Scholar 

  49. Thode, A. M., D’Spain, G. L. & Kuperman, W. A. Matched-field processing, geoacoustic inversion, and source signature recovery of blue whale vocalizations. J. Acoust. Soc. Am. 107, 1286–1300 (2000)

    ADS  CAS  Google Scholar 

  50. Di Iorio, L. & Clark, C. W. Exposure to seismic survey alters blue whale acoustic communication. Biol. Lett. 6, 51–54 (2010)

    Google Scholar 

  51. Rankin, S. & Barlow, J. Vocalizations of the sei whale Balaenoptera borealis off the Hawaiian Islands. Bioacoustics 16, 137–145 (2007)

    Google Scholar 

  52. Baumgartner, M. F. et al. Low frequency vocalizations attributed to sei whales (Balaenoptera borealis). J. Acoust. Soc. Am. 124, 1339–1349 (2008)

    ADS  Google Scholar 

  53. Edds-Walton, P. L. Vocalizations of minke whales Balaenoptera acutorostrata in the St. Lawrence Estuary. Bioacoustics 11, 31–50 (2000)

    Google Scholar 

  54. Mellinger, D. K., Carson, C. D. & Clark, C. W. Characteristics of minke whale (Balaenoptera acutorostrata) pulse trains recorded near Puerto Rico. Mar. Mamm. Sci. 16, 739–756 (2000)

    Google Scholar 

  55. Risch, D. et al. Minke whale acoustic behavior and multi-year seasonal and diel vocalization patterns in Massachusetts Bay, USA. Mar. Ecol. Prog. Ser. 489, 279–295 (2013)

    ADS  Google Scholar 

  56. Payne, R. S. & McVay, S. Songs of humpback whales. Science 173, 585–597 (1971)

    ADS  CAS  Google Scholar 

  57. Cerchio, S. & Dahlheim, M. Variation in feeding vocalizations of humpback whales (Megaptera novaeangliae) from southeast Alaska. Bioacoustics 11, 277–295 (2001)

    Google Scholar 

  58. Cato, D., McCauley, R., Rogers, T. & Noad, M. Passive acoustics for monitoring marine animals-progress and challenges. Proceedings of Acoustics 2006, 453–460 (2006)

    Google Scholar 

  59. Mattila, D. K., Guinee, L. N. & Mayo, C. A. Humpback whale songs on a North Atlantic feeding ground. J. Mamm. 68, 880–883 (1987)

    Google Scholar 

  60. McSweeney, D. J., Chu, K. C., Dolphin, W. F. & Guinee, L. N. North Pacific humpback whale songs: a comparison of southeast Alaskan feeding ground songs with Hawaiian wintering ground songs . Mar. Mamm. Sci. 5, 139–148 (1989)

    Google Scholar 

  61. Clark, C. W. & Clapham, P. J. Acoustic monitoring on a humpback whale (Megaptera novaeangliae) feeding ground shows continual singing into late spring. Proc. Royal Soc. B 271, 1051–1057 (2004)

    Google Scholar 

  62. Watkins, W. A. & Schevill, W. E. Sperm whale codas. J. Acoust. Soc. Am. 62, 1485–1490 (1977)

    ADS  Google Scholar 

  63. Tiemann, C. O., Thode, A. M., Straley, J., O’Connell, V. & Folkert, K. Three-dimensional localization of sperm whales using a single hydrophonea. J. Acoust. Soc. Am. 120, 2355–2365 (2006)

    ADS  Google Scholar 

  64. Nemiroff, L. & Whitehead, H. Structural characteristics of pulsed calls of long-finned pilot whales Globicephala melas. Bioacoustics 19, 67–92 (2009)

    Google Scholar 

  65. Weilgart, L. S. & Whitehead, H. Vocalizations of the North Atlantic pilot whale (Globicephala melas) as related to behavioral contexts. Behav. Ecol. Sociobiol. 26, 399–402 (1990)

    Google Scholar 

  66. Tyson, R. B., Nowacek, D. P. & Miller, P. J. Nonlinear phenomena in the vocalizations of North Atlantic right whales (Eubalaena glacialis) and killer whales (Orcinus orca). J. Acoust. Soc. Am. 122, 1365–1373 (2007)

    ADS  Google Scholar 

  67. Simon, M., Ugarte, F., Wahlberg, M. & Miller, L. A. Icelandic killer whales Orcinus orca use a pulsed call suitable for manipulating the schooling behaviour of herring Clupea harengus. Bioacoustics 16, 57–74 (2006)

    Google Scholar 

  68. Filatova, O. A. et al. Call diversity in the North Pacific killer whale populations: implications for dialect evolution and population history. Anim. Behav. 83, 595–603 (2012)

    Google Scholar 

  69. Oliveira, C., Wahlberg, M., Johnson, M., Miller, P. J. & Madsen, P. T. The function of male sperm whale slow clicks in a high latitude habitat: communication, echolocation, or prey debilitation? J. Acoust. Soc. Am. 133, 3135–3144 (2013)

    ADS  Google Scholar 

  70. Ford, J. K. Acoustic behavior of resident killer whales (Orcinus orca) off Vancouver Island, British Columbia. Can. J. Zool. 67, 727–745 (1989)

    Google Scholar 

  71. Gong, Z., Tran, D. & Ratilal, P. Comparing passive source localization and tracking approaches with a towed horizontal receiver array in an ocean waveguide. J. Acoust. Soc. Am. 134, 3705–3720 (2013)

    ADS  Google Scholar 

  72. Lee, S. & Makris, N. C. The array invariant. J. Acoust. Soc. Am. 119, 336–351 (2006)

    ADS  Google Scholar 

  73. Gong, Z., Ratilal, P. & Makris, N. C. Simultaneous localization of multiple broadband non-impulsive acoustic sources in an ocean waveguide using the array invariant. J. Acoust. Soc. Am. 138, 2649–2667 (2015)

    ADS  Google Scholar 

  74. Tran, D., Andrews, M. & Ratilal, P. Probability distribution for energy of saturated broadband ocean acoustic transmission: results from Gulf of Maine 2006 experiment. J. Acoust. Soc. Am. 132, 3659–3672 (2012)

    ADS  Google Scholar 

  75. Jain, A., Ignisca, A., Yi, D., Ratilal, P. & Makris, N. Feasibility of ocean acoustic waveguide remote sensing (OAWRS) of Atlantic cod with seafloor scattering limitations. Remote Sens. 6, 180–208 (2014)

  76. Jagannathan, S., Kusel, E., Ratilal, P. & Makris, N. Scattering from extended targets in range-dependent fluctuating ocean-waveguides with clutter from theory and experiments. J. Acoust. Soc. Am. 132, 680–693 (2012)

    ADS  Google Scholar 

  77. Andrews, M., Chen, T. & Ratilal, P. Empirical dependence of acoustic transmission scintillation statistics on bandwidth, frequency and range in New Jersey continental shelf. J. Acoust. Soc. Am. 125, 111–124 (2009)

    ADS  Google Scholar 

  78. Collins, M. D. Generalization of the split-step Padé solution. J. Acoust. Soc. Am. 93, 1736–1742 (1983)

    ADS  Google Scholar 

  79. Ainslie, M. A. Neglect of bandwidth of Odontocetes echo location clicks biases propagation loss and single hydrophone population estimates. J. Acoust. Soc. Am. 134, 3506–3512 (2013)

    ADS  Google Scholar 

  80. Makris, N. C. The effect of saturated transmission scintillation on ocean-acoustic intensity measurements. J. Acoust. Soc. Am. 100, 769–783 (1996)

    ADS  Google Scholar 

  81. Bertsatos, I., Zanolin, M., Chen, T. R., Ratilal, P. & Makris, N. C. General second order covariance of Gaussian maximum likelihood estimate applied to passive source localization in a fluctuating ocean waveguide. J. Acoust. Soc. Am. 128, 2635–2651 (2010)

    ADS  Google Scholar 

  82. Thode, A. et al. Necessary conditions for a maximum likelihood estimate to become asymptotically unbiased and attain the Cramer-Rao lower bound Part II: range and depth localization of a sound source in an ocean waveguide. J. Acoust. Soc. Am. 112, 1890–1910 (2002)

    ADS  Google Scholar 

  83. Andrews, M., Gong, Z. & Ratilal, P. Effects of multiple scattering, attenuation and dispersion in waveguide sensing of fish. J. Acoust. Soc. Am. 130, 1253–1271 (2011)

    ADS  Google Scholar 

  84. DiFranco, J. V. & Rubin, W. L. Radar Detection (Artech House, 1980)

  85. Bergmann, P. G., Yaspan, A., Gerjuoy, E., Major, J. K. & Wildt, R. Physics of Sound in the Sea (Gordon and Breach, 1968)

  86. Urick, R. J. Principles of Underwater Sound 29–65 and 343–366 ( McGraw Hill, 1983)

  87. Širovic´, A., Hildebrand, J. A. & Wiggins, S. M. Blue and fin whale call source levels and propagation range in Southern Ocean. J. Acoust. Soc. Am. 122, 1208–1215 (2007)

    ADS  Google Scholar 

  88. Weirathmueller, M. J., Wilcock, W. S. & Soule, D. C. Source levels of fin whale 20 Hz pulses measured in the Northeast Pacific Ocean. J. Acoust. Soc. Am. 133, 741–749 (2013)

    ADS  Google Scholar 

  89. Newhall, A. E., Lin, Y. T., Lynch, J. F., Baumgartner, M. F. & Gawarkiewicz, G. G. Long distance passive localization of vocalizing sei whales using an acoustic normal mode approach. J. Acoust. Soc. Am. 131, 1814–1825 (2012)

    ADS  Google Scholar 

  90. Jensen, F. B., Kuperman, W. A., Porter, M. B. & Schmidt, H. Computational Ocean Acoustics 708–713 (Springer-Verlag, 2011)

  91. Clay, C. S. & Medwin, H. Acoustical Oceanography 494–501 (John Wiley, 1977)

  92. Burdic, W. S. Underwater Acoustic System Analysis 322–360 (Prentice-Hall, 1984)

  93. Küsel E. T. et al. Cetacean population density estimation from single fixed sensors using passive acoustics. J. Acoust. Soc. Am. 129, 3610–3622 (1983)

    ADS  Google Scholar 

  94. Marques, T. A., Thomas, L., Ward, J., DiMarzio, N. & Tyack, P. L. Estimating cetacean population density using fixed passive acoustic sensors: an example with Blainvilles beaked whales. J. Acoust. Soc. Am. 125, 1982–1994 (2009)

    ADS  Google Scholar 

  95. Barlow, J. & Taylor, B. L. Estimates of sperm whale abundance in the northeastern temperate Pacific from a combined acoustic and visual survey. Mar. Mamm. Sci. 21, 429–445 (2005)

    Google Scholar 

  96. Martin, S. W. et al. Estimating minke whale (Balaenoptera acutorostrata) boing sound density using passive acoustic sensors. Mar. Mamm. Sci. 29, 142–158 (2013)

    Google Scholar 

  97. Marques, T. A., Munger, L., Thomas, L., Wiggins, S. & Hildebrand, J. A. Estimating North Pacific right whale Eubalaena japonica density using passive acoustic cue counting. Endanger. Species Res. 13, 163–172 (2011)

    Google Scholar 

  98. Marques, T. A. et al. Estimating animal population density using passive acoustics. Biol. Rev. Camb. Philos. Soc. 88, 287–309 (2013)

    Google Scholar 

  99. Battista, T. A., Clark, R. D. & Pittman, S. An ecological characterization of the Stellwagen Bank national marine sanctuary region: oceanographic, biogeographic, and contaminants assessment. US Department of Commerce, National Oceanic and Atmospheric Administration, National Ocean Service, Center for Coastal Monitoring and Assessment, 265282 (2006)

  100. Stark, H. & Woods, J. Probability, Statistics, and Random Processes for Engineers (Prentice Hall, 2011)

Download references

Acknowledgements

Permission for this National Oceanographic Partnership Program experiment was given in the Office of Naval Research document 5090 Ser 321RF/096/06. This research was supported by the US National Science Foundation, the US Office of Naval Research (Ocean Acoustics Program), the National Oceanographic Partnership Program, the US Presidential Early Career Award for Scientists and Engineers, the Alfred P. Sloan Foundation, the Census of Marine Life, and Northeastern University. The authors thank J. R. Preston for assistance with GOM 2006 experiment, D. H. Cato and P. L. Tyack for discussions.

Author information

Authors and Affiliations

  1. Laboratory for Ocean Acoustics and Ecosystem Sensing, Northeastern University, 360 Huntington Avenue, Boston, 02115, Massachusetts, USA

    Delin Wang, Heriberto Garcia, Wei Huang, Duong D. Tran, Zheng Gong & Purnima Ratilal

  2. Laboratory for Undersea Remote Sensing, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, 02139, Massachusetts, USA

    Ankita D. Jain, Dong Hoon Yi, Zheng Gong & Nicholas C. Makris

  3. Northeast Fisheries Science Center, 166 Water Street, Woods Hole, 02543, Massachusetts, USA

    J. Michael Jech

  4. Institute of Marine Research, Post Office Box 1870, Nordnes, Bergen, N-5817, Norway

    Olav Rune Godø

Authors
  1. Delin Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Heriberto Garcia
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wei Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Duong D. Tran
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ankita D. Jain
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Dong Hoon Yi
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Zheng Gong
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. J. Michael Jech
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Olav Rune Godø
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Nicholas C. Makris
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Purnima Ratilal
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Overall concept and approach conceived and developed by P.R. Implementation, data analysis and interpretation directed by P.R., conducted by D.W., W.H., H.G. and D.D.T. with contributions from A.D.J., D.H.Y. and Z.G. The GOM 2006 experiment data collection was led by N.C.M., P.R. and J.M.J. The article was written by P.R. with contributions from D.W., W.H., J.M.J., O.R.G. and N.C.M. All authors read and discussed the manuscript.

Corresponding author

Correspondence to Purnima Ratilal.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Spectrograms of MM vocalizations.

a–h, Beamformed spectrograms of typical repetitive vocalizations from diverse MM species observed using the POAWRS receiver array in the Gulf of Maine from 19 September to 6 October 2006.

Extended Data Figure 2 Coherent array processing enhances SNR.

a, b, Compare single hydrophone measured spectrogram (a) with spectrogram after coherent beamforming (b) with 64-element sub-aperture of POAWRS 160-element hydrophone array. The song vocalization from a humpback individual roughly 35 km away from the POAWRS receiver array recorded on 2 October 2006 at 23:48:45 EDT is enhanced by 18 dB above the background noise after beamforming in b where whale bearing is −64.16° from array broadside.

Extended Data Figure 3 Pitch-tracks of baleen and toothed whales.

a, Pitch-tracks of repetitive mysticete vocalizations in the 10 to 100 Hz range. Thick solid curves are the means of roughly 500 to 1,000 vocalizations of each type. Mean instantaneous bandwidth of the pitch-tracks are indicated by the dashed curve. Even though blue and sei type I calls have some overlapping bandwidth, they can be well separated using the upper frequency fU and slope df/dτ features (Extended Data Table 2). b, Mean pitch-track and instantaneous bandwidth of repetitive odontocete downsweep vocalizations in the 1 to 4 kHz range.

Extended Data Figure 4 Daily POAWRS measured MM vocalization bearings.

a, b, MM vocalization bearings from diverse species measured by POAWRS receiver array on 1 October 2006 (a) and 2 October 2006 (b). The bearings are measured from true North in clockwise direction with respect to the instantaneous spatial locations of the receiver array centre. The techniques used here for resolving source bearing ambiguity about the horizontal line-array axis are provided in Methods section 3. The shaded bars on the x axis indicate the operation time periods of the receiver array.

Extended Data Figure 5 Daily humpback vocalization repertoire.

a–c, Bearings and repertoire of humpback vocalizations measured by POAWRS receiver array on 1 October 2006 (a), 2 October 2006 (b), and 3 October 2006 (c). The ‘meow’, ‘bow’, and ‘feeding’ call characteristics are provided in ref. 7.

Extended Data Figure 6 Diel Atlantic herring shoaling areal population densities.

Measured herring shoaling areal population densities (ranging from 0.2 fish per m2 to over 10 fish per m2) determined from OAWRS12,13 survey in the Gulf of Maine from 26 September 2006 to 6 October 2006, upon calibration with tens of thousands of coincident and co-located conventional ultrasonic fisheries echosounding measurements, combined with trawl sampling for identity and biological–physiological characterization of fish populations15,16. The mean diffuse herring density of 0.053 fish per m2 is determined from conventional ultrasonic fisheries echosounding. The bathymetric data (contours shown in grey) were obtained from the US National Centers for Environmental Information.

Extended Data Figure 7 Diel MM call rate and herring shoal areal population density time series.

Mean diel call rates for sei whales and odontocetes in general are not correlated to the diel Atlantic herring shoal mean areal population density. The error bars indicate standard deviations obtained from averaging the time series over multiple diel cycles from 26 September 2006 to 6 October 2006. The period from roughly 2–6 EDT contains a data gap.

Extended Data Figure 8 Cumulative diurnal MM call rate distribution.

Cumulative diurnal MM vocalization rate distribution and azimuthally-averaged POAWRS MM POD as a function of minimum distance from diurnal herring shoaling areas. The e-folding distances of the cumulative MM vocalization rate distributions decrease from day (shown here) to night (in Fig. 3b) by 27.3 to 7 km (blue), 9.3 to 3.9 km (fin), 51.7 to 3.5 km (humpback), 22.5 to 0 km (minke), 11.2 to 8.1 km (sei), and 22.4 to 5.5 km (odontocetes). The percentage of vocalizations that fully overlap with herring shoaling areas increase from day to night by 0% to 18% (blue), 14% to 40% (fin), 6% to 44% (humpback), 0% to 71% (minke), and 5% to 24% (sei), but decrease by 36% to 29% (odontocetes).

Extended Data Table 1 MM species daily call rate and temporal correlations
Full size table
Extended Data Table 2 Large baleen whale repetitive vocalization pitch-track features
Full size table

Related audio

Supplementary information

Supplementary Information

This file contains Supplementary Text, Supplementary Figures 1-6, Supplementary Table 1 and Supplementary References. (PDF 2626 kb)

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, D., Garcia, H., Huang, W. et al. Vast assembly of vocal marine mammals from diverse species on fish spawning ground. Nature 531, 366–370 (2016). https://doi.org/10.1038/nature16960

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature16960

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing