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Using Sulfur Stable Isotopes to Understand Feeding Behavior and Selenium Concentrations in Yellow Perch (Perca flavescens) Dominic Ponton, and Landis Hare Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.5b00718 • Publication Date (Web): 28 May 2015 Downloaded from http://pubs.acs.org on June 5, 2015

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Environmental Science & Technology

Using Sulfur Stable Isotopes to Understand Feeding Behavior and Selenium Concentrations in Yellow Perch (Perca flavescens)

DOMINIC E. PONTON AND LANDIS HARE*

Institut national de la recherche scientifique, Centre – Eau Terre Environnement (INRS-ETE), Université du Québec, 490 rue de la Couronne, Quebec City, QC, Canada, G1K 9A9

Word count: 4,935 words + 2,100 words (3 figures at 600 + 1 figure at 300) = 7,035 words.

Keywords: Selenium, Prey, Sulfur isotopes, Bioaccumulation, Biomagnification, Food web, Fish, Yellow perch, Perca flavescens

* Corresponding author phone: (418) 654-2640; fax: (418) 654-2600; e-mail: [email protected]

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Abstract

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We measured selenium (Se) concentrations in yellow perch (Perca flavescens) muscle

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and their prey collected from four Se-contaminated lakes located near metal smelters in

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the eastern Canadian cities of Sudbury and Rouyn-Noranda. Yellow perch Se

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concentrations were related to their weight in two of the four lakes. Measurements of

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sulfur stable isotopes (δ34S) in yellow perch muscle and stomach contents showed that

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larger fish tended to feed less on zooplankton and more on benthic invertebrates than

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did smaller fish. Because Se concentrations are lower and δ34S signatures are higher in

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zooplankton than in sediment-feeding invertebrates, there was an inverse relationship

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between animal Se concentrations and δ34S signatures in all of our study lakes. δ34S

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signatures were highly effective in characterizing these food web relationships.

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Selenium concentrations in yellow perch were 1.6 times those of its prey, which

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indicates that Se is biomagnified by this fish in our study lakes. Estimated Se

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concentrations in yellow perch gonads suggest that in two of our study lakes a third of

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fish are at risk of reproductive toxicity.

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Introduction

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The minimum Se concentration required to satisfy physiological needs is only a factor

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of four below the concentration that can be toxic to fish.1 Thus high concentrations of

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Se in runoff from dryland irrigation or ash from coal-fired power plants have caused

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deformities in the embryos of fish and aquatic birds.2,3 Metal mines and smelters can

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also be important sources of Se contamination to aquatic systems.4 Yet in most such

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systems, environmental studies have focused on metals such as cadmium (Cd), copper

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(Cu), lead (Pb), nickel (Ni) and zinc (Zn) rather than on Se.5,6,7 For example, in eastern

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Canada, toxic effects on aquatic animals from major smelters in Rouyn-Noranda

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(Quebec) and Sudbury (Ontario) have been attributed to Cd8,9 and Ni,10 respectively.

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Selenium was not considered in these studies, in spite of the fact that high Se

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concentrations are found in the biota of lakes downwind from these point sources.11,12,13

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Rather, Se was studied more as a mercury (Hg) antagonist11,12 than as a potentially toxic

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element in its own right. Although emissions reductions from these smelters have led to 2 ACS Paragon Plus Environment

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lower trace metal concentrations in the water, surface sediments and animals of some

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nearby lakes,14-18 trace metal concentrations in surface sediments have not returned to

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background levels and they remain high at depth, which suggests that they still pose a

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risk to benthic invertebrates18,19,20 and to the fish that feed on them.21,22

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We set out to study the influence of fish feeding-behavior on their Se

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concentrations in four lakes that have been contaminated by the Rouyn-Noranda and

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Sudbury smelters. As a model organism, we chose the yellow perch, Perca flavescens

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(Percidae), since it persists in many metal-contaminated boreal-forest lakes and thus

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has been the subject of studies on the accumulation, trophic transfer and toxicity of

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Cd, Cu, Ni and Zn.9,23 In contrast, the relationships between Se concentrations in

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yellow perch, their diet and toxic effects have not been studied.

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Selenium uptake by fish is likely to differ from that of metals such as Cd and

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Ni because the latter are reported to be taken up mainly from water via the gills,24,25

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whereas fish take up Se mainly from their food.5,26 Given this fact, the exposure of

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yellow perch to Se is likely to vary according to their diet. Thus, early in their life,

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when yellow perch feed mostly on zooplankton,27,28 they will be exposed to Se from

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prey in the water-column compartment, whereas as they grow and switch to feeding

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on benthos27,28 they will be increasingly exposed to Se taken up by invertebrates in

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the sediment compartment. At even greater size, yellow perch can feed on small fish

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that could themselves be either planktivorous or benthivorous.27,28 Since Se

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concentrations are likely to differ among zooplankton, benthos and small fish, Se

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exposure to yellow perch is likely to change as they grow.29

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To determine the diet of yellow perch, we measured sulfur (S) stable isotopes

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in this predator and in its prey. This approach is based on the fact that δ34S signatures

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tend to be lower in sediment-feeding than in plankton-feeding invertebrates and these

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differences determine the δ34S signatures of their predators.30 Mechanisms that could

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explain this difference include fractionation during bacterial dissimilatory sulfate

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reduction,31 sulfate diffusion across the sediment-water interface,32 S fractionation in

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the drainage basins of these lakes,33 and historical changes in the isotopic

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composition of sulfate due to variations in atmospheric SO2 sources.34 Measurements

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of sulfur stable isotopes in fish provide a longer term assessment of diet than does the 3 ACS Paragon Plus Environment


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study of gut contents since the composition of gut contents varies from day to day

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and is influenced by the resistance of various prey types to digestion.

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To determine if Se is biomagnified, we compared Se concentrations in yellow

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perch and their prey. Lastly, we evaluated whether the yellow perch populations that

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we studied are likely to be at risk by comparing Se concentrations in their muscle

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with those of toxicity guidelines, as well as by estimating Se concentrations in their

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gonads and comparing these to published values for Se reproductive toxicity. Given

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the paucity of studies on Se in freshwater food webs, especially in lakes,35 the results

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of our study will be useful for understanding differences in Se concentrations among

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prey types, how diet influences fish Se exposure, how Se exposure varies with fish

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age and the possible consequences of such trends for Se risk assessments in lakes.

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Methods

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Study Sites and Animal Collection and Handling. We collected yellow perch and

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their prey from mid-May to mid-June for three years (2010 to 2012) in four lakes

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located on the Precambrian Shield that were downwind from metal smelters located

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near Sudbury, Ontario, and Rouyn-Noranda, Quebec, Canada (Supporting

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Information (SI), Table S1). We chose these lakes because of their high Se

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concentrations in lakewater (SI, Table S1), sediments (SI, Table S1) and zooplankton

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(> 10 µg g-1).13 At the time of sampling, the water columns at our sampling sites were

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of uniform temperature and saturated in oxygen.

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In each year, we collected 5 to 12 yellow perch in the littoral zone of each

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lake using a 0.5-cm mesh-size seine net (75 m × 1 m), which gave a total of 12-30

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fish from each lake. Live fish were held in a cooler with aerated lakewater until they

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were measured, weighed and sacrificed on shore by decapitation and decerebration.

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We removed the contents of each fish stomach and a piece of anterior dorsal muscle.

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Since we used the other organs of these fish for biochemical measurements (not

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reported), in 2009 we collected yellow perch from another Sudbury-area lake (Lohi

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Lake; 46o23'N, 81o02'W) to compare Se concentrations in fish muscle with those in

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gonads (SI, Figure S1) so that we could estimate the toxic potential of Se in the

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reproductive organs of yellow perch from our study lakes. Fish parts and stomach 4 ACS Paragon Plus Environment

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contents were placed individually in acid-washed, 1.5-mL, polypropylene, centrifuge

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tubes and stored at -20 oC. In the laboratory, fish stomach contents were thawed,

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identified and counted in ultrapure water under a dissecting microscope then refrozen

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at -20 oC for later analysis. Benthic prey were collected using an Ekman grab at the same site in each lake

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at which we collected yellow perch. Mud samples were sieved in lakewater using a

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0.5-mm mesh-size net and the invertebrates retained were held in a plastic bag in

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lakewater until their return to the laboratory where they were sorted according to

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lowest taxonomic level possible (SI, Table S2) and held at 4 oC for 3 days to depurate

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their gut contents. We retained only prey types that we had collected in yellow perch

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stomach contents for Se and S analyses. Three individuals of each taxon were placed

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on a pre-weighed piece of acid-washed Teflon sheeting in an acid-washed micro-

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centrifuge tube that was frozen at -20 °C until analysis. Pelagic prey were collected at night by hauling a 64 µm mesh-size plankton

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net horizontally in the water-column. We sieved bulk zooplankton to separate larvae

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of the phantom midge Chaoborus from micro-crustaceans (cladocerans and

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copepods). We verified under a microscope that plankton fractions were composed of

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at least 90% micro-crustaceans by volume. Samples for chemical analysis were

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prepared by placing either 10-20 similar-sized fourth-instar Chaoborus larvae or ~10

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mg wet weight of crustacean zooplankton on acid-washed, pre-weighed pieces of

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Teflon sheeting in acid-washed micro-centrifuge tubes and frozen at -20 °C until

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analysis.

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Analyses. Frozen samples were freeze-dried (FTS Systems) and crushed into a

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homogeneous powder in polypropylene centrifuge tubes using a plastic pestle and

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subsamples were taken for the measurement of Se and stable isotopes of S. Subsamples (3-4 mg; Sartorius M2P PRO 11 balance) for S stable-isotope

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analysis were put into tin capsules and weighed, along with ~8 mg of vanadium

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pentoxide powder as a catalyst, and placed in a 96-well microplate. Blind duplicates

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were made for quality assurance (reported as standard deviations in Figures 1, 3 and

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Table S2). Sulfur isotopic signatures are reported as δ34S (‰) = [(34S/32S sample /

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S/32S standard) – 1] × 103, where the S standard is from the Canyon Diablo Troilite 5 ACS Paragon Plus Environment


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(CDT). Sulfur stable-isotopes were measured by elemental analyzer – isotope ratio

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mass spectrometry at Iso-Analytical Limited (Crewe, UK) using a Sercon elemental

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analyzer and 20-20 mass spectrometer (Sercon Ltd, Crewe, UK). The certified

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reference materials used during S isotopic-analyses were IAEA-SO-5 (barium sulfate,

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δ34S = + 0.5‰; IAEA) and IA-R027 (whale baleen, δ34S = + 16.30‰; Iso-Analytical

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working standard). Values for both were within the certified ranges (+0.3 ± 0.2 ‰

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and +16.2 ± 0.3 ‰, respectively; ± standard deviation (SD)). Although we also

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measured carbon and nitrogen stable-isotopes, these data are not shown because they

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varied little among prey types and among yellow perch from a given lake.

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Subsamples (1 to 15 mg dry weight) for Se analysis were weighed and placed

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in acid-washed, 15 mL, high-density polyethylene bottles where they were digested at

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room temperature for 2 days in concentrated nitric acid (Aristar®, ACS grade; 100 µL

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per mg sample dry weight) followed by 1 day in concentrated hydrogen peroxide

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(TraceSELECT®, Ultratrace grade; 40 µL per mg sample dry weight); digestate

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volume was completed to 1 mL per mg sample dry weight using ultrapure water (18

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MΩ•cm). Certified reference material (lobster hepatopancreas, TORT-2, National

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Research Council of Canada) was submitted to the same digestion procedure.

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Selenium of mass 82 g mol-1 was measured using Inductively Coupled Plasma - Mass

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Spectrometry (ICP-MS; Thermo Elemental X Series) and interferences with bromine

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(Br) and hydrogen (81Br + 1H) were corrected using a standard curve of several Br

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concentrations. Selenium in TORT-2 (5.7 ± 0.1 (± SD) µg g-1; n = 4) was within the

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certified range (5.6 ± 0.7 (95% confidence interval) µg g-1) and the detection limit of

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the ICP-MS for Se was 0.2 µg L-1. Standard deviations reported for individual values

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(Figures 1, 3 and S2) are for three analyses of the same sample.

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Statistical Tests. Year to year differences in yellow perch muscle Se concentrations

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were assessed using ANOVA followed by either a Student T test or its non-

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parametric equivalent (Mann-Whitney U test).

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We compared yellow perch whole weight to their muscle Se concentrations

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and δ34S signatures. Where relationships were significant, we tested the adequacy of

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fit of either a humped-shaped, log-normal, curve (Se concentrations in Lake Dufault

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fish) or exponential curves (Se concentrations and δ34S signatures in Kelly Lake fish) 6 ACS Paragon Plus Environment

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when assumptions of normality (Shapiro-Wilk test) and equality of variances

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(Levene’s test) were satisfied. We then determined yellow perch weight at maximum

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Se concentrations using these bivariate scatterplots. In the case of Kelly Lake, we

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determined fish weight (x) at maximum [Se] by iteration from x = 0 up to a y value

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that was not significantly different from the plateau (± SD). This standard deviation is

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the weight of the variance from our measured [Se] from five different fish from Kelly

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Lake analyzed independently three times. Note that we did not consider the

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significant linear relationship between yellow perch weight and δ34S signatures for

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Lake Rouyn because it depended on a single large individual.

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Slopes and y-intercepts of Se concentrations as a function of δ34S signatures

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were compared independently for yellow perch muscle and invertebrates from each

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of the four lakes using an analysis of covariance and a general linear model. If

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regressions were significantly different, a Tukey multiple comparisons test was

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conducted to determine which lakes differed from one another (see SI, Table S3, for

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detailed results). The lack of significant differences between the slopes and y-

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intercepts of prey data and fish for Lakes Dufault and Osisko, as well as for Lakes

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Kelly and Rouyn (post hoc Tukey multiple comparisons; SI, Table 3), indicated that

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prey data for these pairs of lakes could be combined. Combined prey Se

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concentrations and δ34S signatures were compared using ANOVA followed by a non-

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parametric Dunn’s test on ranks. These same lake pairings were used to evaluate the

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risk posed by Se to yellow perch and the maximum consumption values of yellow

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perch by humans.

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Statistical analyses were carried out using Systat version 11, SigmaStat

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version 3.5 and Jump 9.0 (SAS Institute Inc.). A P value of 0.05 was used as the

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threshold for significance.

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Results and Discussion

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For a given lake, there was no significant difference (P > 0.05) among years in Se

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concentrations in yellow perch muscle (except for a slight difference between 2011

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and 2012 for Kelly Lake fish) and so we combined data for the three sampling years.



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Selenium concentrations in yellow perch muscle varied widely among

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individuals from a given lake (Figure 1, left panels; SI, Table S2). In Lakes Dufault

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and Kelly, Se concentrations increased significantly (P < 0.05) with increasing fish

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weight up to ~28 g and ~20 g, respectively (Figure 1, left panels), as determined by

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regression analysis (see Statistical Tests). Above this weight, Se concentrations in

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yellow perch muscle (Figure 1, left panels) either declined somewhat (Lake Dufault)

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or remained stable (Kelly Lake). No significant trends between Se concentrations and

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fish weight were observed in Lakes Osisko and Rouyn (Figure 1, left panels).

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In fish species other than yellow perch, size and Se concentrations are

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reported to show either a positive relationship (several marine predators36 and

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trout37), a negative relationship (catfish38 and halibut37), or no relationship (eels,39

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carp,40 common carp, green sunfish, bluegill38 and Arctic char41). The lack of

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consistent trends between fish size and Se concentrations among fish species, as well

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as for the same fish species at different sites (our study), suggests that fish weight is

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not a good predictor of Se concentrations in fish tissues. Indeed, fish feeding habits

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have been shown to control Se concentrations in two sympatric fish species that

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depended on either a high-Se (bivalve based) or low-Se (crustacean based) food

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chain.29 The fact that trophic transfer factors ([Se]predator / [Se]prey) tend to be

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similar among fish species42 also supports the idea that feeding habits are the major

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determinant of fish Se concentrations. In general, the high efficiency of Se

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assimilation by fish and invertebrates (usually > 50%)42-45 coupled with their low Se

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uptake rates from solution tends to favor food as their main Se source.26,42,46

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To determine yellow perch feeding habits and their relationship to individual

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size, we measured S stable isotopes in this fish species and its prey. There was no

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significant difference (P > 0.05) between the mean (±SD) δ34S signatures of yellow

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perch muscle (-3.0 ± 1.3 ‰) and those of the prey in their guts (-2.8 ± 2.9 ‰), which

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is consistent with that fact that there is little fractionation of sulfur isotopes between

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consumers and their food.32,47

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The δ34S signatures of zooplankton in Lakes Kelly and Rouyn were

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significantly more positive than those of sediment-feeding chironomids (grey bars in

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lower panel of Figure 2). The trend was the same in Lakes Dufault and Osisko, 8 ACS Paragon Plus Environment

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although the difference between these prey groups was not significant, although the

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δ34S signatures of chironomids and plankton-feeding minnows were significantly

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different in these lakes (grey bars in upper panel of Figure 2). In both pairs of lakes,

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the mean δ34S signatures of invertebrates feeding at the sediment-water interface were

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intermediate between those of zooplankton and burrowing chironomids (grey bars in

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Figure 2).

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Selenium concentrations also differed between planktonic and benthic prey,

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with the former being lower than the latter in both pairs of lakes (solid bars in Figure

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2). In Lakes Dufault and Osisko, there was also a significant difference in Se

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concentrations between zooplankton and epibenthic invertebrates (solid bars in the

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upper panel of Figure 2).

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Since zooplankton tend to have more positive δ34S signatures and lower Se

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concentrations than benthic invertebrates (Figure 2), small yellow perch (< 10 g)27

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and minnows feeding on zooplankton should mirror these trends. This was the case in

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Lakes Dufault and Kelly where Se concentrations tended to be lower and δ34S

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signatures higher in small yellow perch than in those of intermediate size up to ~24 g

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(Figure 1; mean of 28 g and 20 g, as explained above). However, this trend for small

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fish was not seen in the two other lakes (Osisko and Rouyn) and in all lakes there was

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considerable variability among small yellow perch. This variability is likely

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explained by the fact that in our study lakes small (< 10 g) yellow perch fed on both

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zooplankton (6 fish from 3 lakes) and benthos (9 fish from 4 lakes; SI, Table S2). For

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example, in Kelly Lake, we collected a 1 g fish that had consumed 22 chironomids

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whereas an 8 g fish had only zooplankton in its stomach (SI, Table S2).

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Intermediate-sized yellow perch (10 to 24 g) from Lakes Dufault and Kelly

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had lower δ34S signatures and higher Se concentrations than did smaller fish (Figure

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1), which suggests that as fish age they eat less zooplankton likely because this prey

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type provides less individual biomass than do benthic invertebrates.27 Above a mean

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mass of ~24 g (see above), the few yellow perch that we collected had Se

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concentrations (Figure 1, left panels) that tended to either remain stable (Kelly Lake)

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or decline somewhat (Lake Dufault). This difference is likely explained by the types

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of prey available to yellow perch in a given lake. If, on the one hand, small fish such 9 ACS Paragon Plus Environment


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as minnows are not abundant (as in Lake Kelly, where no minnows were found in gut

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contents; SI, Table S2), yellow perch are likely to remain dependent on benthos and

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thus their δ34S signatures and Se concentrations should change little as they grow

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(assuming no change in fish growth rates). On the other hand, in lakes where

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minnows are more readily available as prey (as in Lake Dufault, where 4 yellow

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perch had minnows in their guts; SI, Table S2), it would be energetically

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advantageous for yellow perch to shift from feeding on benthic invertebrates to

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feeding on minnows.27,28 If these prey fish are planktivores, then Se concentrations in

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large yellow perch are likely to decline (as in Lake Dufault; Figure 1), whereas if

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prey fish are benthivores then the Se concentrations of large yellow perch are likely

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to remain stable (assuming no change in fish growth rates). The Se concentrations of

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channel catfish are also reported to change with fish size, that is, Se concentrations

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decline as the fish’s diet shifts from benthic to non-benthic animals.38

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Ignoring differences in yellow perch weight, there was a clear negative

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relationship between muscle Se concentrations and δ34S signatures. On the one hand,

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lower Se concentrations and more positive δ34S signatures were associated with

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yellow perch that depended on zooplankton, either directly as prey, or indirectly

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when feeding on planktivorous minnows (Figure 3, closed symbols; SI, Table S3).

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On the other hand, higher Se concentrations and more negative δ34S signatures were

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associated with yellow perch feeding on benthic chironomids or benthivorous

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minnows (Figure 3, closed symbols; SI, Table S3). Prey of yellow perch followed

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similar trends (Figure 3, open symbols; SI, Table S3). Trout are also reported to have

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higher Se concentrations when feeding on sediment-based food webs than when

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feeding on periphyton exposed to Se in the water column.48 Likewise, lake chub are

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reported to have higher Se concentrations when feeding on free-living, unidentified,

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benthic invertebrates compared to when they feed only on Chironomus larvae raised

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in the laboratory in the absence of sediments.49 The extensive review of Janz et al.50

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discusses the importance of the sediment compartment as a source of Se for lake food

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webs.

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Higher Se concentrations in benthic as opposed to planktonic invertebrates, and thus in the fish that feed on them, could be explained in two ways. First, Se 10 ACS Paragon Plus Environment

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concentrations could be higher in sediments than in particles in the water column

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(mainly algae). Although total Se concentrations did not differ among these particle

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types (SI, Table S1), their concentrations of bioavailable Se could be different. This

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possibility is supported by the fact that sympatric Chironomus species differ in their

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trace element concentrations depending on whether they feed mainly on deep anoxic

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sediment or on surface oxic sediment.51,52 In the case of Se, Chironomus species

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feeding on deep sediments had Se concentrations that were double those of species

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feeding on surface sediments in spite of the fact that total Se concentrations were

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similar in sediments from the two zones.53 The similar physiology of these species

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was purported to rule out physiological differences as the main factor explaining

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differences in their trace-element concentrations.51,52,53 Higher Se bioavailability in

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anoxic sediments than in oxic sediments is likely dependent on their relative

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concentrations of organic Se, which tends to be more bioavailable than inorganic

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Se.13,54,55 For example, organic selenide produced by diatoms and sedimentary

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bacteria is reported to be more bioavailable to bivalves than is abiotically-formed

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elemental Se56 and Chironomus larvae have been shown to take up organic selenide

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in sediments to a greater extent than inorganic elemental Se.57 Abiotic reactions at the

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surface of sediments that reduce selenite to elemental Se58 and then biotic processes56

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that use it to produce organic Se in anoxic sediment (30 to 40% of total Se in

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sediments)50,59 would favor greater Se bioavailability to Chironomus and other

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invertebrates that feed directly or indirectly (via predation) on anoxic sediments.

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Physiological differences among various invertebrate groups could also

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explain in part differences in their Se concentrations. Thus the crustacean zooplankter

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Daphnia is reported to lose from 15-50% of its Se daily through the production of

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offspring,60 whereas there would be no such loss from immature larval insects. This

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difference could explain in part the lower Se concentrations that we measured in

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zooplankton crustaceans compared to those in benthic insects. Overall, a combination

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of physiological, behavioral and geochemical factors is likely to explain differences

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in the Se concentrations of various invertebrate groups from our study lakes.

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Selenium concentrations in yellow perch muscle were strongly correlated with those of prey in their gut contents (Figure 4), which suggests that prey Se 11 ACS Paragon Plus Environment


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concentrations are the main determinant of those in yellow perch. However, scatter

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around the regression line in Figure 4 could be explained by physiological factors

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such as yellow perch growth rates. Since the regression line in Figure 4 is above the 1

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to 1 line, Se is biomagnified between yellow perch and its prey. The trophic transfer

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factor for yellow perch (1.6 ± 0.7, SD, n = 51) is at the high end of those reported for

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various fish species (0.5 to 1.6).42 The equation for the regression in Figure 4, along

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with values for sediment-feeding invertebrates such as Chironomus or tubificid

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oligochaetes, could be used to estimate maximum Se concentrations in yellow perch

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from other lakes. Although the highest Se concentrations that we measured were in

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Chironomus larvae, Se concentrations in the oligochaete Tubifex tubifex are reported

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to be higher than those of Chironomus riparius raised in the same sediments,43 which

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suggests that tubificids (uncommon in our study lakes) could also be used for

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estimating maximum Se exposure to yellow perch.

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Our results suggest that benthivorous fish are likely to attain Se concentrations

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that are from 2 to 5 times higher than those of sympatric planktivorous fish, which

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would lead to a correspondingly higher risk of Se toxicity for fish feeding on benthos.

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To assess the likelihood that yellow perch in our study lakes are suffering toxic

323

effects, we compared their Se concentrations to those reported to induce deformities

324

in the taxonomically-related Centrarchidae.1 Since the Se concentrations reported for

325

this sister family of the Percidae are in terms of whole fish, we multiplied our values

326

for Se in muscle by 0.75 (as reported for the pike Esox lucius).61 The highest Se

327

concentration that we measured in yellow perch muscle (42 µg g-1) corresponds to a

328

whole body Se concentration of 32 µg g-1, which is the value at which deformities

329

occur in 10% of Centrarchidae,1 whereas the mean Se concentration in yellow perch

330

from Lakes Kelly and Rouyn (27 ± 8 µg g-1 in muscle; 20 µg g-1 in whole body)

331

corresponds to 6% deformed fish and the low mean Se value for fish from Lakes

332

Dufault and Osisko (14 ± 4 µg g-1 in muscle; 11 µg g-1 in whole fish) suggests that

333

deformities would not be above background level in these lakes.1

334

The likelihood of toxic effects due to Se exposure can also be assessed by

335

comparing our yellow perch Se measurements to the ovarian Se concentration that is

336

reported to produce reproductive toxicity in 10% of fish of a given species (20-25 µg 12 ACS Paragon Plus Environment

Page 12 of 25

Page 13 of 25


337

Se g-1 dry weight for more than 10 Canadian fish species).62 To estimate Se

338

concentrations in yellow perch gonads, we assumed that muscle Se concentrations are

339

155% of those in gonads (SI, Figure S1; values for Se in ovaries fell within those for

340

testes) such that yellow perch having a muscle Se concentration > 31 µg g-1 would be

341

at risk of Se reproductive toxicity. Using this threshold, we estimate that about one-

342

third (38% and 33%, respectively) of the yellow perch from Lakes Kelly and Rouyn,

343

are at risk of Se toxicity, whereas no Se concentrations exceeded this threshold value

344

in the other two lakes. The fact that Se concentrations in the biota and water of most

345

lakes in our study areas tend to be lower than those in Lakes Kelly and Rouyn,11,12,13,

346

our study

347

these lakes. Although we did not measure yellow perch population sizes in our four

348

study lakes, we note that the lowest catch per unit effort (data not shown) was in the

349

two lakes in which Se toxicity is most likely to occur (Lakes Kelly and Rouyn).

350

suggests that Se is not a major risk factor for yellow perch in the majority of

To determine the suitability of yellow perch from our study lakes as a food

351

source, we estimated consumption limits for humans. The maximum recommended

352

Se consumption is 400 µg of Se per day63 or 12 mg per month. Given the mean Se

353

values in yellow perch from Lakes Dufault and Osisko (14 ± 4 µg g-1 dry weight or

354

2.8 µg g-1 wet weight; dry to wet weight factor of 564), a person consuming 12 filets

355

per month (filet size of 0.23 kg fresh weight) would reach this limit, whereas in Lakes

356

Kelly and Rouyn (27 ± 8 µg g-1 dry weight) only 6 filets would be needed to reach

357

the maximum recommended Se intake.

358

Overall, our results suggest that freshwater fish species whose food webs are

359

based on planktonic organisms will have lower Se concentrations than fish dependent

360

on sediment-based food webs. Furthermore, since many freshwater fish species feed

361

mainly on zooplankton as larvae and then shift to benthic invertebrates and eventually

362

fish, their Se exposure is likely to change as they grow. We observed this trend for

363

yellow perch, but it is also likely the case for other sports fish such as walleye

364

(Sander vitreus), largemouth bass (Micropterus salmoides), pike (Esox lucius) and

365

lake trout (Salvelinus namaycush) that show similar age-related shifts in diet. Lastly,

366

our results suggest that changes in Se exposure within the life of a given species can

367

be site specific depending on the densities of various prey types in a given lake. Thus 13 ACS Paragon Plus Environment


368

the risk of Se toxicity is likely to be highly variable depending on the fish species, its

369

life stage and the site at which it is collected. Given the importance of diet in

370

determining Se exposure and effects on fish, an efficient technique is needed to

371

determine the dependence of various fish species and life stages on planktonic and

372

benthic food chains. Our results suggest that measurements of S stable isotopes in

373

fish fill this need.

374

Acknowledgments

375

We acknowledge John Gunn and the Cooperative Freshwater Ecology Unit at the

376

Vale Living with Lakes Center in Sudbury, Ontario for their help in the field. The

377

assistance of Maikel Rosabal, Julien Lacharité, Nicolas Fabien-Ouellet and Isabelle

378

Lavoie is also greatly appreciated. We thank Marc Amyot, Marie-Noële Croteau and

379

Claude Fortin for their comments on an earlier version of the manuscript. Our study

380

was supported by funding from the Natural Sciences and Engineering Research

381

Council of Canada.

382

Supporting Information Available

383

Table S1 gives information about lake locations, lakewater chemistry and Se

384

concentrations in sediments and in microplankton. Table S2 reports the length, wet

385

weight and stomach contents (when present) of all yellow perch (P. flavescens) that

386

we collected as well as Se concentrations and S stable isotopic signatures in prey and

387

in yellow perch dorsal muscle. Table S3 gives details about the correlations presented

388

in Figure 3. Figure S1 compares Se concentrations in the various tissues and organs

389

of P. flavescens from Lohi Lake, Ontario. This material is available free of charge via

390

the internet at http://pubs.acs.org.


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40. Levengood, J. M.; Soucek, D. J.; Sass, G. G.; Dickinson, A.; Epifanio, J. M. Elements of concern in fillets of bighead and silver carp from the Illinois river, Illinois. Chemosphere 2014, 104, 63–68. 41. Gantner, N.; Power, M.; Babaluk, J. A.; Reist, J. D.; Köck, G.; Lockhart, L. W.; Solomon, K. R.; Muir, D. C. G. Temporal trends of mercury, cesium, potassium, selenium, and thallium in Arctic char (Salvelinus alpinus) from lake Hazen, Nunavut, Canada: Effects of trophic position, size, and age. Environ. Toxicol. Chem. 2009, 28, 254–263. 42. Presser, T. S.; Luoma, S. N. A methodology for ecosystem-scale modeling of selenium. Integr. Environ. Assess. Manag. 2010, 6, 685–710. 43. Dubois, M.; Hare, L. Selenium assimilation and loss by an insect predator and its relationship to Se subcellular partitioning in two prey types. Environ. Poll. 2009, 157, 772–777. 44. Schlekat, C. E.; Lee, B. G.; Luoma, S. N. Assimilation of selenium from phytoplankton by three benthic invertebrates: effect of phytoplankton species. Mar. Ecol. Progr. Ser. 2002, 237, 79–85. 45. Reinfelder, J. R.; Fisher, N.S. The assimilation of elements ingested by marine copepods. Science 1991, 251, 794–796. 46. Wang, W. X.; Fisher, N. S. Delineating metal accumulation pathways for marine invertebrates. Sci. Total Environ.1999, 238, 459–472. 47. McCutchan, J. H.; Lewis, W. M.; Kendall, C.; McGrath, C. C. Variation in trophic shift for stable isotope ratios of carbon, nitrogen, and sulphur. Oikos 2003, 102, 378–390. 48. Orr, P. L.; Guiguer, K. R.; Russel, C. K. Food chain transfer of selenium in lentic and lotic habitats of a western Canadian watershed. Ecotox. Environ. Safe. 2006, 63, 175–188. 49. Phibbs, J.; Franz, E.; Hauck, D.; Gallego-Gallegos, M.; Tse, J. J.; Pickering, I. J.; Liber, K.; Janz, D. M. Evaluating the trophic transfer of selenium in aquatic ecosystems using caged fish, X-ray absorption spectroscopy and stable isotope analysis. Ecotox. Environ. Safe. 2011, 74, 1855–1863. 50. Martin, S.; Proulx, I.; Hare, L. Explaining metal concentrations in sympatric Chironomus species. Limnol. Oceanogr. 2008, 53, 411–419. 51. Proulx, I.; Hare, L. Differences in feeding behaviour among Chironomus species revealed by measurements of sulphur stable isotopes and cadmium in larvae. Freshwater Biol. 2014, 59, 73–86. 52. Proulx, I. Évaluation du potentiel d'utiliser les larves de Chironomus comme biomoniteurs de la biodisponibilité des éléments traces dans les sédiments. Doctorat en Sciences de l'eau, Université du Québec, Institut national de la recherche scientifique. Québec, QC, Canada. 2014. 275 pp. 53. Baines, S. B.; Fisher, N. S.; Doblin, M. A.; Cutter, G. A. Uptake of dissolved organic selenides by marine phytoplankton. Limnol. Oceanogr. 2001, 46, 1936– 1944. 18 ACS Paragon Plus Environment

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54. Besser, J. M.; Canfield, T. J.; Lapoint, T. W. Bioaccumulation of organic and inorganic selenium in a laboratory food-chain. Environ. Toxicol. Chem. 1993, 12, 57–72. 55. Schlekat, C. E.; Dowdle, P. R.; Lee, B. G.; Luoma, S. N.; Oremland, R. S. Bioavailability of particle-associated Se to the bivalve Potamocorbula amurensis. Environ. Sci. Technol. 2000, 34, 4504–4510. 56. Franz, E. D.; Wiramanaden, C. I. E.; Gallego-Gallegos, M.; Tse, J. J.; Phibbs, J.; Janz, D. M.; Pickering, I. J.; Liber, K. An in situ assessment of selenium bioaccumulation from water-, sediment-, and dietary-exposure pathways using caged Chironomus dilutus larvae. Environ. Toxicol. Chem. 2013, 32, 2836–2848. 57. Chen, Y. W.; Thi Truong, H. Y.; Belzile, N. Abiotic formation of elemental selenium and role of iron oxide surfaces. Chemosphere 2009, 74, 1079–1084. 58. Martin, A. J.; Simpson, S.; Fawcett, S.; Wiramanaden C. I. E.; Pickering, I. J.; Belzile, N.; Chen, Y. W.; London, J.; Wallschläger, D. Biogeochemical mechanisms of selenium exchange between water and sediments in two contrasting lentic environments. Environ. Sci. Technol. 2011, 45, 2605–2612. 59. Yu, R. Q.; Wang, W. X. Kinetic uptake of bioavailable cadmium, selenium, and zinc by Daphnia magna. Environ. Toxicol. Chem. 2002, 21, 2348–2355. 60. Muscatello, J. R.; Bennett, P. M.; Himbeault, K. T.; Belknap, A. M.; Janz, D. M. Larval deformities associated with selenium accumulation in northern pike (Esox lucius) exposed to metal mining effluent. Environ. Sci. Technol. 2006, 40, 6506– 6512. 61. DeForest, D. K.; Gilron, G.; Armstrong, S. A.; Robertson, E. L. Species sensitivity distribution evaluation for selenium in fish eggs: considerations for development of a Canadian tissue-based guideline. Integr. Environ. Assess. Manag. 2012, 8, 6–12. 62. Food and Agriculture Organization. Human vitamin and mineral requirements. FAO/WHO expert consultation on human vitamin and mineral requirements, 2001. http://www.fao.org/docrep/004/Y2809E/y2809e0l.htm. 63. CRESP, Consortium for Risk Evaluation with Stakeholder Participation. Note on: Wet to dry weight conversions for biota from Amchitka and Kiska. CRESP Amchitka Radionuclide Data Set, 2006. http://www.cresp.org/Amchitka/Final_WW_DW_3_13_06.pdf.



Figure Captions Figure 1. Mean (±SD) Se concentrations ([Se], µg g-1 dry weight; left panels) and sulfur stable-isotope signatures (δ34S, ‰; right panels) of yellow perch muscle as compared to whole-fish wet weights (g) in our four study lakes. Fish having wet weights < 28 g and < 20 g (see text) in Lakes Dufault and Kelly, respectively, are represented by solid symbols, whereas heavier fish are represented by open squares.

Figure 2. Selenium concentrations ([Se], µg g-1 dry weight; black bars) and sulfur stable-isotope signatures (δ34S, ‰; gray bars) of prey consumed by yellow perch that were collected in either Lakes Dufault and Osisko (upper panel) or Lakes Kelly and Rouyn (lower panel). Different letters represent a significant difference between prey types. Figure 3. Selenium concentrations ([Se]; µg g-1 dry weight) as a function of sulfur stable-isotope signatures (δ34S; ‰) in yellow perch muscle (closed circles) or in their prey (open squares) from our four study lakes. All linear regressions are significant at P < 0.03. Details of these regressions are presented in SI, Table S3. Figure 4. Selenium concentrations ([Se]; µg g-1 dry weight) in the muscle of yellow perch collected from our four study lakes as a function of the Se concentrations of prey in their stomachs. The equation for the regression line is [Se]Perca flavescens = 0.9 ± 0.1 ∗ [Se]Perca flavescens prey + 7 ± 2 where P < 0.001 and uncertainties are standard errors. The dotted line represents a 1:1 relationship.


Page 20 of 25

Page 21 of 25


25

0

Dufault

-1

15

-2

10

-3

5

-4

0 20

40

60 110 115 0

20

40

60 110

-5 115 6 4

Kelly

40

2

30

0

20

-2

Kelly

10

-4

0

-6 0

15

30

70

80 0

15

30

70

80

25

-2

20

-3

15

-4

10

-5

5

Osisko

Osisko

0 0

5

10 15 60

50

90

120 0

5

10

30 20 10

Rouyn

Rouyn

0 0

15

30

45

60 160180 0

15

30

-7 120 -1 -2 -3 -4 -5 -6 -7 -8 60 160 180

15 60

40

45

-6

90

Perca flavescens weight (g w.w.)

Fig. 1.


34

50

0

δ S(‰)

[Se] Perca flavescens (µg g-1)

20

Dufault


Fig. 2


Page 22 of 25

Page 23 of 25


25

A

Osisko

20

-1

[Se] (µg g )

B

Dufault

20

r2 = 0.49

15 10

25

r2 = 0.22

15 r2 = 0.72

10

5

r2 = 0.40

5

0 0 -12 -10 -8 -6 -4 -2 0 2 4 -12 -10 -8 -6 -4 -2 50 50 C D Rouyn 2 r = 0.39 40 40 30 20

0

2

4

Kelly 2

r = 0.57

30 20

r2 = 0.40

10

10

0 -12 -10 -8 -6 -4 -2

0

2

4

r2 = 0.28

0 -12 -10 -8 -6 -4 -2

34

δ S(‰)

Fig. 3


0

2

4

-1

[Se]P. flavescens (µg g )


Page 24 of 25

2

r = 0.50

40 30 20 10 0 0

10

20

30

40 -1

[Se] P. flavescens prey (µg g ) Fig. 4


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