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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All data and model algorithms are available in the Extended Data and Supplementary Information.
All model code is available at the following link: https://github.com/SunderlandLab/foodweb_bioaccumulation_model.
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).
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).
Bellanger, M. et al. Economic benefits of methylmercury exposure control in Europe: monetary value of neurotoxicity prevention. Environ. Health 12, 3 (2013).
Streets, D. et al. Global and regional trends in mercury emissions and concentrations. Atmos. Environ. 201, 417–427 (2019).
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).
Schartup, A. T. et al. A model for methylmercury uptake and trophic transfer by marine plankton. Environ. Sci. Technol. 52, 654–662 (2018).
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).
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).
Dijkstra, J. A. et al. Experimental and natural warming elevates mercury concentrations in estuarine fish. PLoS ONE 8, e58401 (2013).
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).
Cheung, W. W. L. et al. Projecting global marine biodiversity impacts under climate change scenarios. Fish Fish. 10, 235–251 (2009).
Sunderland, E. M. et al. Mercury sources and fate in the Gulf of Maine. Environ. Res. 119, 27–41 (2012).
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).
Restrepo, V. et al. Updated estimate of the growth curve of Western Atlantic bluefin tuna. Aquat. Living Resour. 23, 335–342 (2010).
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).
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).
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).
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).
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).
Peterson, C. L., Klawe, W. L. & Sharp, G. D. Mercury in tunas: a review. Fish Bull. 71, 603–613 (1973).
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).
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).
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).
Streets, D. G. et al. Total mercury released to the environment by human activities. Environ. Sci. Technol. 51, 5969–5977 (2017).
Sunderland, E. M. & Mason, R. P. Human impacts on open ocean mercury concentrations. Glob. Biogeochem. Cycles 21, GB4022 (2007).
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).
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).
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).
Block, B. A. et al. Migratory movements, depth preferences, and thermal biology of Atlantic bluefin tuna. Science 293, 1310–1314 (2001).
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).
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).
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).
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).
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.
The authors declare no competing interests.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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.
Trophic interactions for the Gulf of Maine food web that are included in our MeHg bioaccumulation model.
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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