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. 2022 Jan 11;119(2):e2113032119.
doi: 10.1073/pnas.2113032119.

Evidence that Pacific tuna mercury levels are driven by marine methylmercury production and anthropogenic inputs

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Evidence that Pacific tuna mercury levels are driven by marine methylmercury production and anthropogenic inputs

Anaïs Médieu et al. Proc Natl Acad Sci U S A. .

Abstract

Pacific Ocean tuna is among the most-consumed seafood products but contains relatively high levels of the neurotoxin methylmercury. Limited observations suggest tuna mercury levels vary in space and time, yet the drivers are not well understood. Here, we map mercury concentrations in skipjack tuna across the Pacific Ocean and build generalized additive models to quantify the anthropogenic, ecological, and biogeochemical drivers. Skipjack mercury levels display a fivefold spatial gradient, with maximum concentrations in the northwest near Asia, intermediate values in the east, and the lowest levels in the west, southwest, and central Pacific. Large spatial differences can be explained by the depth of the seawater methylmercury peak near low-oxygen zones, leading to enhanced tuna mercury concentrations in regions where oxygen depletion is shallow. Despite this natural biogeochemical control, the mercury hotspot in tuna caught near Asia is explained by elevated atmospheric mercury concentrations and/or mercury river inputs to the coastal shelf. While we cannot ignore the legacy mercury contribution from other regions to the Pacific Ocean (e.g., North America and Europe), our results suggest that recent anthropogenic mercury release, which is currently largest in Asia, contributes directly to present-day human mercury exposure.

Keywords: atmospheric inputs; biogeochemistry; methylmercury; skipjack tuna; spatial modeling.

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Conflict of interest statement

The authors declare no competing interest.

Figures

Fig. 1.
Fig. 1.
Skipjack tuna sample provenance and mercury concentrations. (A) Map of skipjack sampling locations, with the size of the circles proportional to the number of individuals collected. (B) Power-law relationship between log(observed Hg) and skipjack fork length. The relationship was fitted on samples from the SWPO and WCPO only, but Hg residuals were calculated for all samples (symbolized by the black arrows). Oceanic areas: NWPO, CNPO, NEPO, EPO, SWPO, and WCPO.
Fig. 2.
Fig. 2.
Spatial variability of skipjack mercury concentrations. Smoothed spatial contour maps of (A) observed and (B) standardized Hg concentrations (micrograms ⋅ grams−1, dw) in skipjack white muscle samples from the Pacific Ocean. The black dots represent the location of skipjack samples. Ocean areas correspond to the sample origin: NWPO, CNPO, NEPO, EPO, SWPO, and WCPO. The transparent dots represent the location of seawater samples with available and published MeHg data (see Materials and Methods).
Fig. 3.
Fig. 3.
Hemispheric mercury gradients in different Pacific Ocean reservoirs. The boxplots illustrate the hemispheric gradient of (A) atmospheric Hg0 model estimates (nanograms ⋅ meters−3) extracted at tuna sampling locations (see Materials and Methods), (B) observed total Hg concentrations (picomolar) in seawater (12, 34, 38, 53, 54, 56), (C) observed MeHg concentrations at peak (picomolar) in seawater (, , –57), (D) standardized total Hg concentrations (micrograms ⋅ grams−1, dw) in skipjack tuna (this study), and (E) observed total Hg concentrations (nanograms ⋅ grams−1, dw) in marine sediments (, –78). ** indicates significant differences between the northern and southern hemispheres (Kruskal–Wallis test; P < 0.01).
Fig. 4.
Fig. 4.
Optimal GAM predicting observed mercury concentrations in skipjack tuna. The main drivers of the spatial variability of log(observed Hg) were (A) fish length, (B) the depth of net heterotrophy, (C) [O2] in subsurface waters, and (D) Hg0 model estimates. The DE percentage of the model is reported on the top of the figure. Colored dots are the partial residuals of the GAM by oceanic areas. Black lines show the expected values, and gray bands show CIs for the expected value, which are twice the SE. Oceanic areas: NWPO, CNPO, NEPO, EPO, SWPO, and WCPO.
Fig. 5.
Fig. 5.
Relative contribution of current local anthropogenic emissions to tuna mercury concentrations. Smoothed spatial contour maps of the difference between observed and GAM predicted mercury concentration (micrograms ⋅ grams−1, dw) in skipjack white muscle samples from the Pacific Ocean. The GAM included fish length, depth of heterotrophy, and subsurface [O2], explaining most of tuna mercury variability, except an Asian outflow mercury contribution in the NWPO. The black dots represent the location of skipjack samples. Ocean areas correspond to the sample origin: NWPO, CNPO, NEPO, EPO, SWPO, and WCPO.

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