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Climate change and overfishing increase neurotoxicant in marine predators

Nature volume 572, pages 648–650 (2019)Cite this article

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Abstract

More than three billion people rely on seafood for nutrition. However, fish are the predominant source of human exposure to methylmercury (MeHg), a potent neurotoxic substance. In the United States, 82% of population-wide exposure to MeHg is from the consumption of marine seafood and almost 40% is from fresh and canned tuna alone1. Around 80% of the inorganic mercury (Hg) that is emitted to the atmosphere from natural and human sources is deposited in the ocean2, where some is converted by microorganisms to MeHg. In predatory fish, environmental MeHg concentrations are amplified by a million times or more. Human exposure to MeHg has been associated with long-term neurocognitive deficits in children that persist into adulthood, with global costs to society that exceed US$20 billion3. The first global treaty on reductions in anthropogenic Hg emissions (the Minamata Convention on Mercury) entered into force in 2017. However, effects of ongoing changes in marine ecosystems on bioaccumulation of MeHg in marine predators that are frequently consumed by humans (for example, tuna, cod and swordfish) have not been considered when setting global policy targets. Here we use more than 30 years of data and ecosystem modelling to show that MeHg concentrations in Atlantic cod (Gadus morhua) increased by up to 23% between the 1970s and 2000s as a result of dietary shifts initiated by overfishing. Our model also predicts an estimated 56% increase in tissue MeHg concentrations in Atlantic bluefin tuna (Thunnus thynnus) due to increases in seawater temperature between a low point in 1969 and recent peak levels—which is consistent with 2017 observations. This estimated increase in tissue MeHg exceeds the modelled 22% reduction that was achieved in the late 1990s and 2000s as a result of decreased seawater MeHg concentrations. The recently reported plateau in global anthropogenic Hg emissions4 suggests that ocean warming and fisheries management programmes will be major drivers of future MeHg concentrations in marine predators.

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Fig. 1: Modelled effects of ecosystem change on MeHg concentrations in Atlantic cod and spiny dogfish.
Fig. 2: Effects of seawater warming in the Gulf of Maine on tissue MeHg concentrations in ABFT.

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Data availability

All data and model algorithms are available in the Extended Data and Supplementary Information.

Code availability

All model code is available at the following link: https://github.com/SunderlandLab/foodweb_bioaccumulation_model.

References

  1. Sunderland, E. M., Li, M. & Bullard, K. Decadal changes in the edible supply of seafood and methylmercury exposure in the United States. Environ. Health Perspect. 126, 017006 (2018).

    Article  Google Scholar 

  2. Horowitz, H. M. et al. A new mechanism for atmospheric mercury redox chemistry: implications for the global mercury budget. Atmos. Chem. Phys. 17, 6353–6371 (2017).

    Article  ADS  CAS  Google Scholar 

  3. Bellanger, M. et al. Economic benefits of methylmercury exposure control in Europe: monetary value of neurotoxicity prevention. Environ. Health 12, 3 (2013).

    Article  Google Scholar 

  4. Streets, D. et al. Global and regional trends in mercury emissions and concentrations. Atmos. Environ. 201, 417–427 (2019).

    Article  ADS  CAS  Google Scholar 

  5. Lotze, H. K. & Milewski, I. Two centuries of multiple human impacts and successive changes in a North Atlantic food web. Ecol. Appl. 14, 1428–1447 (2004).

    Article  Google Scholar 

  6. Schartup, A. T. et al. A model for methylmercury uptake and trophic transfer by marine plankton. Environ. Sci. Technol. 52, 654–662 (2018).

    Article  ADS  CAS  Google Scholar 

  7. Smith, B. E. & Link, J. S. The Trophic Dynamics of 50 Finfish and 2 Squid Species on the Northeast US Continental Shelf. NOAA Technical Memorandum NMFS-NE-21 (National Marine Fisheries Service, 2010).

  8. Pershing, A. J. et al. Slow adaptation in the face of rapid warming leads to collapse of the Gulf of Maine cod fishery. Science 350, 809–812 (2015).

    Article  ADS  CAS  Google Scholar 

  9. Dijkstra, J. A. et al. Experimental and natural warming elevates mercury concentrations in estuarine fish. PLoS ONE 8, e58401 (2013).

    Article  ADS  CAS  Google Scholar 

  10. Maulvault, A. L. et al. Bioaccumulation and elimination of mercury in juvenile seabass (Dicentrarchus labrax) in a warmer environment. Environ. Res. 149, 77–85 (2016).

    Article  CAS  Google Scholar 

  11. Cheung, W. W. L. et al. Projecting global marine biodiversity impacts under climate change scenarios. Fish Fish. 10, 235–251 (2009).

    Article  Google Scholar 

  12. Sunderland, E. M. et al. Mercury sources and fate in the Gulf of Maine. Environ. Res. 119, 27–41 (2012).

    Article  CAS  Google Scholar 

  13. Zhang, Y. et al. Observed decrease in atmospheric mercury explained by global decline in anthropogenic emissions. Proc. Natl Acad. Sci. USA 113, 526–531 (2016).

    Article  ADS  CAS  Google Scholar 

  14. Restrepo, V. et al. Updated estimate of the growth curve of Western Atlantic bluefin tuna. Aquat. Living Resour. 23, 335–342 (2010).

    Article  Google Scholar 

  15. Cross, F. A., Evans, D. W. & Barber, R. T. Decadal declines of mercury in adult bluefish (1972–2011) from the Mid-Atlantic coast of the U.S.A. Environ. Sci. Technol. 49, 9064–9072 (2015).

    Article  ADS  CAS  Google Scholar 

  16. Lee, C.-S. et al. Declining mercury concentrations in bluefin tuna reflect reduced emissions to the North Atlantic Ocean. Environ. Sci. Technol. 50, 12825–12830 (2016).

    Article  ADS  CAS  Google Scholar 

  17. Hammerschmidt, C. R., Finiguerra, M. B., Weller, R. L. & Fitzgerald, W. F. Methylmercury accumulation in plankton on the continental margin of the northwest Atlantic Ocean. Environ. Sci. Technol. 47, 3671–3677 (2013).

    Article  ADS  CAS  Google Scholar 

  18. Hellou, J., Fancey, L. & Payne, J. Concentrations of twenty-four elements in bluefin tuna, Thunnus thynnus from the Northwest Atlantic. Chemosphere 24, 211–218 (1992).

    Article  ADS  CAS  Google Scholar 

  19. Harding, G., Dalziel, J. & Vass, P. Bioaccumulation of methylmercury within the marine food web of the outer Bay of Fundy, Gulf of Maine. PLoS ONE 13, e0197220 (2018).

    Article  Google Scholar 

  20. Peterson, C. L., Klawe, W. L. & Sharp, G. D. Mercury in tunas: a review. Fish Bull. 71, 603–613 (1973).

    CAS  Google Scholar 

  21. Mendez, E., Giudice, H., Pereira, A., Inocente, G. & Medina, D. Total mercury content—fish weight relationship in swordfish (Xiphias gladius) caught in the Southwest Atlantic Ocean. J. Food Compos. Anal. 14, 453–460 (2001).

    Article  CAS  Google Scholar 

  22. Lavoie, R. A., Jardine, T. D., Chumchal, M. M., Kidd, K. A. & Campbell, L. M. Biomagnification of mercury in aquatic food webs: a worldwide meta-analysis. Environ. Sci. Technol. 47, 13385–13394 (2013).

    Article  ADS  CAS  Google Scholar 

  23. Hoen, D. K. et al. Amino acid 15N trophic enrichment factors of four large carnivorous fishes. J. Exp. Mar. Biol. Ecol. 453, 76–83 (2014).

    Article  CAS  Google Scholar 

  24. Streets, D. G. et al. Total mercury released to the environment by human activities. Environ. Sci. Technol. 51, 5969–5977 (2017).

    Article  ADS  CAS  Google Scholar 

  25. Sunderland, E. M. & Mason, R. P. Human impacts on open ocean mercury concentrations. Glob. Biogeochem. Cycles 21, GB4022 (2007).

    Article  ADS  Google Scholar 

  26. Kitchell, J. F., Stewart, D. J. & Weininger, D. Applications of a bioenergetics model to yellow perch (Perca flavescens) and walleye (Stizostedion vitreum vitreum). J. Fish. Res. Board Can. 34, 1922–1935 (1977).

    Article  Google Scholar 

  27. Nøttestad, L., Giske, J., Holst, J. C. & Huse, G. A length-based hypothesis for feeding migrations in pelagic fish. Can. J. Fish. Aquat. Sci. 56, 26–34 (1999).

    Article  Google Scholar 

  28. Rudstam, L. G. Exploring the dynamics of herring consumption in the Baltic: applications of an energetics model of fish growth. Kieler Meeresforschungen Sonderheft 6, 312–322 (1988).

    Google Scholar 

  29. Block, B. A. et al. Migratory movements, depth preferences, and thermal biology of Atlantic bluefin tuna. Science 293, 1310–1314 (2001).

    Article  ADS  CAS  Google Scholar 

  30. Neilson, J. D. et al. Seasonal distributions and migrations of Northwest Atlantic swordfish: inferences from integration of pop-up satellite archival tagging studies. PLoS ONE 9, e112736 (2014).

    Article  ADS  Google Scholar 

  31. Bowman, K. L., Hammerschmidt, C. R., Lamborg, C. H. & Swarr, G. Mercury in the North Atlantic Ocean: the U.S. GEOTRACES zonal and meridional sections. Deep Sea Res. Part II Top. Stud. Oceanogr. 116, 251–261 (2015).

    Article  ADS  CAS  Google Scholar 

  32. Scharf, F. S., Juanes, F. & Rountree, R. Predator size–prey size relationships of marine fish predators: interspecific variation and effects of ontogeny and body size on trophic-niche breadth. Mar. Ecol. Prog. Ser. 208, 229–248 (2000).

    Article  ADS  Google Scholar 

  33. Young, J., Lansdell, M., Riddoch, S. & Revill, A. Feeding ecology of broadbill swordfish, Xiphias gladius, off eastern Australia in relation to physical and environmental variables. Bull. Mar. Sci. 79, 793–809 (2006).

    Google Scholar 

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Acknowledgements

We thank S. Durkee at the US Environmental Protection Agency (EPA) for discussion of this work; P. Balcom and P. Béziat for assistance in analysing fish Hg samples; and C. S. Lee, N. Fisher and G. Harding for biological data. Financial support for this study was provided by the US EPA (contract EP-H-11-001346); the US National Science Foundation (OCE 1260464); and the Nereus Program sponsored by the Nippon Foundation. Statements in this publication represent the professional views of the authors and should not be construed to represent any determination or policy of the US EPA.

Author information

Authors and Affiliations

  1. Harvard John A. Paulson School of Engineering & Applied Sciences, Harvard University, Cambridge, MA, USA

    Amina T. Schartup, Colin P. Thackray, Clifton Dassuncao & Elsie M. Sunderland

  2. Department of Environmental Health, Harvard T. H. Chan School of Public Health, Harvard University, Boston, MA, USA

    Amina T. Schartup, Clifton Dassuncao & Elsie M. Sunderland

  3. Department of Civil Engineering, Indian Institute of Technology Hyderabad, Kandi, India

    Asif Qureshi

  4. Fisheries and Oceans Canada, St Andrews Biological Station, St Andrews, New Brunswick, Canada

    Kyle Gillespie & Alex Hanke

Authors
  1. Amina T. Schartup
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Contributions

E.M.S. initiated the study; A.T.S. synthesized data and performed research; A.T.S., C.P.T., A.Q. and C.D. developed the model; K.G. and A.H. provided new data on ABFT; and A.T.S. and E.M.S. wrote the manuscript. All authors helped to interpret the results and provided comments.

Corresponding authors

Correspondence to Amina T. Schartup or Elsie M. Sunderland.

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The authors declare no competing interests.

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Peer review information Nature thanks Richard T. Barber and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Extended data figures and tables

Extended Data Fig. 1 Comparison of observed and modelled MeHg concentrations from a marine food web in the Gulf of Maine.

a, Measured MeHg concentrations in biota and trophic positions based on nitrogen isotopes19. b, Measured (symbols) MeHg concentrations16,19 in ABFT from the Gulf of Maine compared to modelled concentrations based on standard bioenergetics algorithms (dashed line) and based on bioenergetics algorithms adjusted for the energy consumption that is associated with migration and rapid swimming speeds (solid line). The blue shaded region shows the 67% confidence interval around the model and the grey shaded region represents the upper and lower bounds of modelled seawater MeHg and DOC concentrations. Each data point represents an individual fish; n = 1,284. c, Measured (symbols) MeHg concentrations21 in swordfish and modelled MeHg concentrations based on standard bioenergetics algorithms (dashed line); algorithms adjusted for migratory energy expenditure and swimming speed (dotted line); and algorithms adjusted for energy expenditure and large prey consumption (solid line). The yellow shaded region indicates the upper and lower bounds of predator-to-prey length ratios (10:1 to 2:1), the orange shaded region shows the 67% confidence interval around the model and the grey shaded region represents the upper and lower bounds of modelled seawater MeHg and DOC. Each data point represents an individual fish; n = 203. d, Comparison of observed and modelled MeHg concentrations for the Gulf of Maine food web across five trophic levels19. The model is forced by seawater MeHg concentrations17 ranging from 0.015 to 0.055 pM. Each data point represents the mean MeHg concentration in fish of a similar weight (n = 119); error bars represent s.d.

Extended Data Fig. 2 Feeding relationships in the Gulf of Maine marine food web.

Trophic interactions for the Gulf of Maine food web that are included in our MeHg bioaccumulation model.

Extended Data Table 1 MeHg in Gulf of Maine plankton
Full size table
Extended Data Table 2 MeHg in Gulf of Maine fish and shellfish
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Extended Data Table 3 MeHg in Gulf of Maine ABFT
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Extended Data Table 4 Modelled changes in seawater MeHg in the Gulf of Maine
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Extended Data Table 5 Changes in seawater temperature in the Gulf of Maine
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Extended Data Table 6 Food web model algorithms
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Extended Data Table 7 Trophic interactions in the food web model
Full size table

Supplementary information

Supplementary Information

Supplementary methods on pages 1-11 provide a detailed description of the 20 Supplementary bioenergetics equations used in the model. The species-specific parameters used to model lifespans, energy content, preferred temperatures, growth, ingestion, respiration and swimming speeds are summarized in 4 Supplementary Tables.

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Schartup, A.T., Thackray, C.P., Qureshi, A. et al. Climate change and overfishing increase neurotoxicant in marine predators. Nature 572, 648–650 (2019). https://doi.org/10.1038/s41586-019-1468-9

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