Mercury Temporal Trends in Top Predator Fish of the Laurentian Great

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Mercury temporal trends in top predator fish of the Laurentian Great Lakes from 2004 to 2015: are concentrations still decreasing? Chuanlong Zhou, Mark D. Cohen, Bernard S. Crimmins, Hao Zhou, Timothy A. Johnson, Philip K. Hopke, and Thomas M. Holsen Environ. Sci. Technol., Just Accepted Manuscript • Publication Date (Web): 05 Jun 2017 Downloaded from http://pubs.acs.org on June 7, 2017

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Environmental Science & Technology

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Mercury temporal trends in top predator fish of the

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Laurentian Great Lakes from 2004 to 2015: are

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concentrations still decreasing?

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Chuanlong Zhou1, Mark D. Cohen2, Bernard A. Crimmins1, Hao Zhou3, Timothy A. Johnson3, Philip K. Hopke1,

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Thomas M. Holsen1, *

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Department of Civil and Environmental Engineering, Clarkson University, Potsdam, NY 13676.

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Air Resources Laboratory, U.S. National Oceanic and Atmospheric Administration, College Park, MD 20740.

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Institute for a Sustainable Environment, Clarkson University, Potsdam, NY 13676.

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Address: 204 Rowley Laboratories

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Clarkson University

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PO Box 5710

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Potsdam, NY 13699-5710

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Phone: 315-268-3851

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Fax numbers: 315-268-7636

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Email address: [email protected]

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Table of Contents Graphic (TOC) Art:

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Abstract

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Mercury (Hg) concentration trends in top predator fish (lake trout and walleye) of the Great Lakes (GL)

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from 2004 to 2015 were determined by Kendall-Theil robust regression with a cluster-based age

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normalization method in order to control for the effect of changes in lake trophic status. Combining data

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from the GLs (except LE), a significant decreasing trend in the lake trout Hg concentrations was found

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between 2004 and 2015 with an annual decrease of 4.1% per year, consistent with the decline in regional

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atmospheric Hg emissions and water Hg concentrations. However, a breakpoint was detected with a

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significant decreasing slope (-8.1% per year) before the breakpoint (2010) and no trend after the

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breakpoint. When the lakes are examined individually Lakes Superior and Huron, which are dominated

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by atmospheric Hg inputs and are more likely to respond to declining emissions from areas surrounding

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the GL than the lower lakes, have significant decreasing trends with rates between 5.2% and 7.8% per

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year from 2004 to 2015. These declining trends appear to be driven by decreasing regional atmospheric

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Hg emissions although they may be partly counterbalanced by other factors including increasing local

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emissions, food web changes, eutrophication, and responses to global climate change. Lakes Michigan,

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Erie, and Ontario may have been more impacted by these other factors and have decreasing then non-

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decreasing or increasing trends.

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Keywords:

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Fish Mercury, Great Lakes, Lake Trout, Trends, Age normalization

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Introduction

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The Great Lakes watershed is a major water resource and fishery for North America.1 For this ecosystem,

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mercury (Hg) pollution is recognized as a serious environmental and health concern.2-4 Hg can be

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transformed among elemental, ionic, and organic species when it cycles within and among air, water, land

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and the biosphere.5 Once transformed into methylmercury (MeHg) in aquatic ecosystems, it becomes

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more toxic, highly bioaccumulative

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through fish consumption.8, 9 Currently there are more than 3900 fish consumption advisories for Hg in

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the U.S. including in the Great Lakes (GL),10, 12

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and a potential threat to aquatic ecosystems and to human health 11

and Hg is one of the major contaminants causing

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restriction on consuming fish.

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2014, which suggests that pregnant, and young children should eat fish with lower mercury concentration

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in order to gain important developmental and health benefits.13 Hg is one of the analytes of Great Lakes

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Fish Monitoring and Surveillance Program (GLFMSP), which monitors spatiotemporal trends of

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bioaccumulative chemicals in the GL using top predator fish as biomonitors.2

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Atmospheric Hg emissions and subsequent deposition can be strongly correlated with Hg levels in aquatic

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biota and fish,

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discharges of Hg containing effluents (e.g. chlor-alkali plant), were largely eliminated in the early 90s.25,

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2005, largely due to controls of Hg emissions through state, regional, binational, and voluntary actions.14,

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27, 28

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from 2002-2010.29 However the benefits of these reductions could be offset by increasing global Hg

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emissions which have been largely due to increases from Asian countries. 30

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The trophic status of a lake, fish species, size, and age are important determinants of fish Hg

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concentrations.31-33 For example, positive correlations have been reported between Hg concentration and

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fish size or age of a given species, 6, 34 however, consumption of prey with a higher caloric content could

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cause a lower Hg concentration in predator fish due to growth dilution.35 These variables need to be

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analyzed and then controlled for to better determine concentration trends and allow informative lake-to-

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lake comparisons.32, 36, 37 Fish growth rate has varied significantly in some GL ecosystems because of

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changing lake-specific food webs caused primarily by invasive species and eutrophication.38, 39, 40 Invasive

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species can also affect the methylation rate in a lake. For example, increased MeHg concentrations were

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found in nearshore regions of Lake Michigan with prominent invasive mussel infestations and associated

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filamentous benthic green algae. 41

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Other factors related to eutrophication and climate change can also affect fish Hg levels. Since the

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methylation process occurs primarily in organic-rich particles (in the water column) or surface sediment,

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EPA and FDA issued updated draft advice on fish consumption in June

and are likely the main contemporary source of Hg to the GL17-24 as the direct

Atmospheric Hg emissions in the GL region declined by approximately 50 percent between 1990 and

These and subsequent reductions contributed to observed decreases in atmospheric Hg concentrations

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42, 43

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by increasing the extent of anoxic conditions, favorable for methylating bacteria. Hg methylation rates

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also increase with sediment and water column temperature leading to increasing bioaccumulation44, 45 ,

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and so a warming climate can impact MeHg concentrations in fish. Climate change may also alter the Hg

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wet deposition and tributary runoff inputs to the lakes due to changes in precipitation depth. 18 A warmer

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climate can also increase lake sediment resuspension events due to increased and more intense storms,

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and decreased ice cover, causing the release of Hg accumulated in sediment.8, 42, 46

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In this study, Hg concentrations and fish age in top predator fish (lake trout for all of the lakes except for

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Lake Erie (LE) where walleye are the top predator fish) were measured as part of the GLFMSP from 2004

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to 2015.

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Kendall’s tau test and Kendall-Theil robust regression, after age normalization using a cluster-based

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method, to evaluate the potential impacts of changes in atmospheric Hg inputs, regional Hg emissions,

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eutrophication, and climate change.

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Methods

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Sample collection and total Hg analysis

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Lake trout (Salvelinus namaycush) samples (600-700 mm) were collected in Lakes Huron (LH),

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Michigan (LM), Ontario (LO), and Superior (LS). Walleye (Sander vitreus) samples (400-500 mm) were

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collected in LE. Fifty fish samples were collected annually and grouped into ten composites (based on

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size similarity) from two sampling sites for each lake, one site for even years (shallow site), and the other

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one for odd years (deep site). Note that all the sites are in offshore water ecosystems (both industrial area

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and non-industrial areas in each lake).

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DMA-80 Direct Mercury Analyzer (Milestone Srl, Bergamo, Italy) based on US EPA Method 7473. Other

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sample collection, preparation and analysis details are described in the Supplemental Information (SI) and

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by Zananski et al.2

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Fish age analysis

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Fish ages were determined by otoliths, fin clips, coded wire tags (CWT), and scales prior to 2012. A

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maxillae estimation method, developed at the Michigan Department of Natural Resources, was added in

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2012 and primarily used due to increased simplicity and accuracy.49 Ages used in this research were an

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average number of these methods. Significant increasing annualized age trends (%/yr) were found in LH

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(7.2% even years; 7.4% odd years), LM (4.8% even years) and LS sites (8.3% even years; 6.9% odd

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years). Additional details regarding the fish age analysis are presented in the SI.

eutrophication can accelerate the production of MeHg by increasing the organic carbon loading, and

Hg concentration trends within and among lakes were determined using non-parametric

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Composites were kept frozen before being analyzed with a

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Age normalization method

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The correlations between age and Hg concentration were found to be nonlinear and year-dependent

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(Figures 1b and S4). These results are unlike previous reported results that could be described using linear

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or logarithmic equations.

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linear model or analysis of covariance (ANCOVA),

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Hg concentration to a consistent age so that all the fish concentrations used for trends analysis likely

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resulted from the same Hg exposure time, sampling years with similar bioaccumulation patterns were

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grouped together (clustered) before normalization as follows: 1) an equation was used to describe the

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annual bioaccumulation patterns; in this case, a linear model was used because it yielded the best fits to

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the data with an average r2 in each year of 0.35 ranging from 0 ~ 0.85; 2) The distance between each

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year’s bioaccumulation pattern was calculated based on the equations obtained in step 1; the distance was

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determined by the average distance of each data point in one group to the other regression line (this

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approach considers both the distance of data points between the groups and the similarity of the

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regression lines); 3) hierarchical clustering was performed to define the clusters based on the distances

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obtained in step 2; as hierarchical clustering will generate new group combinations, the distances among

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new groups is recalculated in each step of hierarchical clustering; 4) linear regression equations were

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calculated for each cluster obtained in step 3; and 5) Hg concentrations were normalized to an average

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age (7.0 years) based on the equations obtained in step 4. A more detailed discussion and the algorithms

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used are presented in the SI.

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Trend analysis

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The non-parametric Kendall’s tau test and Kendall-Theil robust line (Sen’s slope) were used for trends

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and breakpoint analysis using SPSS 22 (2014 IBM Corporation) and KTRLine software developed by the

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U.S. Geological Survey (USGS).

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therefore, earlier fish Hg data (1999-2003) were not included in this analysis. An overall trend analysis

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for all the lake trout data following age normalization (2004-2015) was performed. In this analysis, all the

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lake trout data among sites and lakes (except Erie) were combined to develop a regional temporal trend.

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LE was not included because a different fish species was collected during this period. The changes in fish

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Hg concentrations are generally smooth, however, a breakpoint analysis can be used when times between

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sampling periods are long. Trends were also analyzed lake-by-lake with the shallow and deep sites

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analyzed separately if the age normalized concentrations had significant differences between the sites

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based on a rank sum test. A more detailed discussion of the trend analysis methodology is presented in the

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SI.

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Hg emission inventory

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Therefore, traditional age normalization approaches, such as the general

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6, 14, 33, 50-53

were not appropriate. To normalized fish

Age data were only available for fish from 2004 to present,

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U.S. Hg point-source air emissions data were obtained from the National Emissions Inventory (NEI)

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(1999-2014)

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emissions data from the National Pollutant Release Inventory (NPRI) were used (2000-2015).65

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Additional information regarding these emissions datasets is provided in the SI.

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Results and Discussion

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Age Normalization. Age normalization was used to control for biases in concentration trends caused by

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the differences in ages among the sampled fish. As shown in Figures 1 and S4, the clustering results for

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each site fell into one or multiple clusters. One cluster was found for the LO and LM even years, and LE

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and LO odd years, indicating that there was no significant change in the Hg bioaccumulation rates at

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those sites over time.

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bioaccumulation rates between 2004 and 2015 were significant. Detailed age normalization clustering

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results including r2 values for each lake are presented in Figure S4 and Table S1. The LM odd years and

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all of the sites in LH and LS have multiple clusters with clear patterns: 1) the clusters are separated by

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breakpoint year, which means that Hg bioaccumulation rate in lake trout changed between the early years

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and recent years; and 2) the slope and intercept of regression lines have decreased in recent years. These

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results indicate that the recently sampled fish in the upper lakes (LH and LS) have both lower Hg

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concentrations (smaller intercepts) and less Hg bioaccumulated over time (shallower slopes), indicating

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that the recent fish have lower Hg concentrations at the same age when compared to the earlier samples.

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Note that LE even years does not have a breakpoint year, but does have multiple clusters. The change in

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the Hg bioaccumulation pattern can be caused by changes in Hg inputs,15 and/or changes in the food-web

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structure and other ecosystem characteristics.35, 41

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Overall Trend. A significant decreasing trend in lake trout Hg concentrations was found between 2004

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and 2015 (Kendall’s tau = -0.32, p