(PBDEs) and alternative halogenated flame retardants in a vegetation

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Bioaccumulation of polybrominated diphenyl ethers (PBDEs) and alternative halogenated flame retardants in a vegetation-caribou-wolf food chain of the Canadian Arctic Adam David Morris, Derek Muir, Keith Solomon, Camilla Teixeira, Mark Duric, and Xiaowa Wang Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b04890 • Publication Date (Web): 10 Jan 2018 Downloaded from http://pubs.acs.org on January 10, 2018

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Environmental Science & Technology

Bioaccumulation of polybrominated diphenyl ethers (PBDEs) and alternative halogenated flame retardants in a vegetation-caribou-wolf food chain of the Canadian Arctic

Adam D. Morris,†* Derek C.G. Muir,‡ Keith R. Solomon,† Camilla F. Teixeira,‡ Mark D. Duric,‡ Xiaowa Wang‡ †

School of Environmental Sciences, University of Guelph, 50 Stone Road East, Guelph, ON,

Canada, N1G 2W1 ‡

Aquatic Contaminants Research Division, Environment and Climate Change Canada, 867

Lakeshore Road, Burlington, ON, Canada, L7S 1A1

Total word count (Abstract through SI description) = 7336 Main text = 5836 Table 1 + Table 2 + Table 3 = 3 × 300 words =900 words Figure 1 + 2 = 2 × 300 words = 600 Words * Corresponding author. Phone: (289)259-6089); E-mail: [email protected], ORCID ID : orcid.org/0000-0002-0695-023X. Current address: National Wildlife Research Centre, 1125 Colonel By Drive/Raven Road, Office 330, Desk J, Ottawa, ON, Canada, K1S 5B6

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Keywords: Bioaccumulation, trophic magnification, halogenated flame retardants,

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polybrominated diphenyl ethers, terrestrial

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Abstract The trophodynamics of halogenated flame retardants (HFRs) including polybrominated

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diphenyl ethers (PBDEs) and alternative HFRs were investigated in the terrestrial, vegetation-

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caribou-wolf food chain in the Bathurst Region of northern Canada. The greatest concentrations

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in vegetation (geometric mean of lichens, moss, grasses, willow, and mushrooms) were of the

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order 2,4,6-tribromophenyl allyl ether (TBP-AE) (10 ng g-1 lw) > BDE47 (5.5 ng g-1 lw) >

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BDE99 (3.9 ng g-1 lw) > BDE100 (0.82 ng g-1 lw) > 1,2,3,4,5-pentabromobenzene (PBBz) (0.72

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ng g-1 lw). Bioconcentration between types of vegetation was consistent, though it was typically

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greatest in rootless vegetation (lichens, moss). Biomagnification was limited in mammals; only

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BDE197, BDE206 to -208 and ΣPBDE biomagnified to caribou from vegetation

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[biomagnification factors (BMFs) = 2.0–5.1]. Wolves biomagnified BDE28/33, BDE153,

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BDE154, BDE206, BDE207, and ΣPBDE significantly from caribou (BMFs = 2.9–17) but

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neither mammal biomagnified any alternative HFRs. Only concentrations of BDE28/33,

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BDE198, nonaBDEs, and ∑PBDE increased with trophic level, though the magnitude of

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biomagnification was low relative to legacy, recalcitrant organochlorine contaminants [trophic

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magnification factors (TMFs) = 1.3–1.8]. Despite bioaccumulation in vegetation and mammals,

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the contaminants investigated here exhibited limited biomagnification potential and remained at

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low parts per billion concentrations in wolves.

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Introduction Halogenated flame retardants (HFRs) are consistently reported in environmental media

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and wildlife across the globe. The polybrominated diphenyl ethers (PBDEs) are environmentally

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abundant brominated FRs, with 209 congeners that were available as three commercial (c)

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mixtures (c-pentaBDE, c-octaBDE, c-decaBDE).1 The c-pentaBDE and c-octaBDE mixtures

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have been under phase-out in Europe and North America since the early 2000s, with c-decaBDE

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regulated later.2-4 The prominent congeners in all three c-PBDE mixtures are now regulated

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globally as new persistent organic pollutants (POPs) as of 2009 (c-penta- and c-octaBDE) or

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2017 (c-decaBDE).5 Despite regulations on production and new applications, PBDEs are

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released to the environment from a number of in-use products.6 These regulations have also led

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to the production of replacement (alternative) HFRs which are also detected in the environment,

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but less consistently than PBDEs.7-11

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Some of the most environmentally relevant alternative HFRs such as pentabromotoluene

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(PBT), hexabromobenzene (HBB), 1,2-bis 2,4,6-tribromophenoxy ethane (BTBPE),

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hexabromocyclododecane (HBCDD), and pentabromoethylbenzene (PBEB) have been detected

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throughout the arctic environment and the arctic marine food web.9, 12-17 Despite these

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observations, few studies have reported on the trophodynamics of these compounds in the

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terrestrial environment, particularly in the Arctic or Subarctic. The limited studies of PBDEs in

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terrestrial food chains suggest that like the marine environment, the biomagnification of PBDEs

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in mammals is congener, location, and food chain-specific.9, 18-24 Modeling has shown that

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organic contaminants with intermediate-high octanol-water partitioning (KOW > 102) and high

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lipid-air partitioning (KOA ≥106), including some PBDEs and alternative HFRs, can theoretically

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biomagnify more effectively in terrestrial food chains than in aquatic ones.11 This is primarily 4

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due to reduced depuration across the lungs and kidneys of terrestrial animals, an effect that can

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be particularly apparent in food chains with multiple air-breathing consumers.11, 25, 26

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The objective of this study was to improve scientific understanding of the

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bioaccumulation of PBDEs and alternative HFRs in terrestrial food chains. The study system was

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the vegetation-caribou-wolf food chain, sampled within the Bathurst Region caribou herd range,

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which overlaps the border between Nunavut (NU) and the Northwest Territories (NWT,

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Canada). This food chain was selected in conjunction with the Government of the NWT due to

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concerns regarding population declines of the caribou herd from approximately 186 000 to 22

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000 (2003–2015) and the related ecological and socioeconomic impacts.27, 28 Nearby mining

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operations, roadways, wildfires in their winter range, and climate change were among the

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challenges highlighted in the Bathurst Caribou Range Plan.29 Ecological interactions and current

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use pesticides,30 legacy organochlorine (OC) contaminants,11, 25, 31 and perfluorinated alkyl

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substances32 have previously been reported in this food chain. However the trophodynamics of

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HFRs have been poorly described in terrestrial ecosystems and in general there has been much

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less work on studies of trophic magnification factors (TMFs) in terrestrial food webs compared

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to aquatic systems.33 Therefore, in addition to adding to the overall profile of HFR

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contamination, this study provides valuable data for assessment of terrestrial TMFs, as well as

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for food chain modeling.

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Materials and Methods

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Sample collection and preparation

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Samples of lichens (Cladonia rangiferina/mitis and Flavocetraria cucullata, both n = 6),

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moss (Rhytidium rugosum, n = 6), willow leaves (Salix sp., n = 6), graminoids (Eriophorum

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vaginatum and Carex aquatilis, n = 8) and mushrooms (not speciated, n = 5) were collected 5

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within the Bathurst caribou herd range (64°04′N, 114°08′W) in the Northwest Territories (NWT)

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in August 2009. Muscle and liver samples were collected from caribou (Rangifer tarandus

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groenlandicus, n = 6) and wolves (Canis lupus, n = 7) in 2008-2009 and 2010 respectively by

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local subsistence hunters and trappers. Details of sample collection have been published

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previously [Supporting Information (SI), Table S1].30

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Analytes, sample extraction and cleanup

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The analytes and recoveries are provided in the SI (Table S2, structures in Figure S1).

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The PBDEs and alternative HFRs analyzed included 28 tri- to nonaBDE congeners (BDE17–

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BDE208), 1,2-bis(2,4,6-tribromophenoxy) ethane (BTBPE), 2,4,6-tribromophenyl allyl ether

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(TBP-AE), 2,4,6-tribromophenyl 2-bromoallyl ether (TBP-BAE), 2,4,6-tribromophenyl 2,3-

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dibromopropyl ether (TBP-DBPE), 1,2,3,4,5-pentabromobenzene (PBBz), pentabromotoluene

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(PBT), pentabromoethylbenzene (PBEB), hexabromobenzene (HBB), syn- and anti-Dechlorane

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plus (DP) (nomenclature from Bergman et al.34). The results of spike-recovery experiments were

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consistent for the mono-heptaBDEs (82–105%), and acceptable for the octa-nonaBDEs (57–

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93%), though recoveries decreased and became more variable with increasing bromination.

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Inconsistency of recoveries and in quantifications using two standards when run for confirmation

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(concentrations were 21–110% different) led us to eliminate BDE209 from further discussion.

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The alternative HFRs had more variable recoveries (42%–147%; Table S2), which may be

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related to their structural diversity (details in the SI).

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The sample extraction methods followed Hoesktra et al.35 and Johansen et al.,36 except

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that pressurized solvent extraction was used (ASE 300, Dionex, Sunnyvale, CA). Samples of

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muscle and liver (5–10 g) were extracted for contaminant analysis using the ASE, with the 6

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method and cleanup as described in Morris et al.,30 with secondary fractionation for HFR

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analyses. Lipid contents were determined gravimetrically via gel permeation chromatography

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(details of extraction/cleanup in the SI).

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Stable isotopes of carbon and nitrogen (13C/12C = δ13C and 15N/14N = δ15N respectively) were analyzed in muscle and have been reported previously with their analytical details.30

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Data analyses, quality assurance and quality control (QA/QC) Separation and measurement of contaminants was achieved using gas chromatography-

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low resolution mass spectrometry (GC-LRMS) with electron-capture negative chemical

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ionization (NCI) with the MS run in selective ion monitoring (SIM) mode (Agilent 7890A GC–

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5975C MS, Agilent Technologies, Mississauga, ON, Canada). Analytes were identified and

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quantified based on comparison with retention times and the relative responses of multilevel,

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external calibration standards. BDE198 co-eluted with BDE199, -200 and -203, but will be

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referred to as “BDE198”. Details regarding compounds excluded for QA/QC issues are provided

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in the SI.

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Batches of 10 to 12 samples were extracted with method blanks and standard reference

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materials (SRM 1588b or SRM 1947, National Institute of Standards and Technology,

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Gaithersburg, MD, USA, Table S2 and Table S3). Vegetation, caribou and wolf data were blank

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corrected separately, and data were recovery corrected relative internal spikes of BDE71

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(discussed further in the SI). Method detection limits (MDLs) were established as three times the

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standard deviation of the blank concentrations (Table S2). When detection frequencies (DFs) of

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an analyte were below 20 % in a subset of samples (type of vegetation, mammalian tissue), it

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was considered a non-detect (< MDL) When DFs were greater than 20 % but were not 100 %, 7

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MDL/2 concentrations were substituted for zero values in the wet weight (ww) dataset. If

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concentrations were below MDLs these were included rather than substituting MDL/2 values.37

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Instrument detection limits (IDLs)38 were used in place of MDLs if contaminants were not

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detected in the blanks (details of data handling in the SI).

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Lipid equivalent-normalized concentrations (φLeq) were calculated for vegetation to

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incorporate the sorption capacity of proteins and carbohydrates11, 18 while the φLeq in the

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relatively lipid-rich samples (mammals) were considered to be negligibly different than their

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lipid fractions (φLipid) as in previous investigations (calculations in the SI).18 Though correction

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for the φLeq accounts for the sorption capacity of some other non-lipid components, there are

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other components of vegetation that may not be accounted for here and that may affect the

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sorption of organic contaminants. Previously outlined methods were used here for consistency.11

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Total body concentrations (TBCs) were based on measured values in muscle and liver

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and estimated concentrations in fat, assuming that these tissues were the main deposits for HFRs.

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Calculations used previously reported body composition estimates32 and separately estimated

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body fat percentages (details of calculations in the SI).31

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Bioaccumulation and biomagnification

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Volumetric bioconcentration factors (BCFv) were calculated as the ratio of the geometric

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mean concentration of an analyte in vegetation to the total concentration (particulate + gas

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phases) in air from Alert, NU (Hung et al.39 supplied separately for 2009 alone) using Equations

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1 and 2:

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Cv = Cm × ρ × (1.0 × 106)

(1)

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BCFv = Ct,v/CA,T

(2)

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Air samples were collected bi-weekly and the annual concentration was used for analysis here.39

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Cv is the φLeq corrected, volumetric concentration (pg m-3), Cm represents the mass-based ww

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tissue concentration in vegetation (pg g-1 ww), ρ is the density of the vegetation (g cm-3, densities

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in the SI), 1.0 × 106 is the pg cm-3 to pg m-3conversion factor and CA is the air concentration (pg

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m-3). Mean BCFv values were then calculated for “Lichens,” “Green Plants” (moss, willow,

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graminoids), mushrooms, and “Total Vegetation (VT, all vegetation included),” as well as

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functionally grouped “Rootless” (lichens and moss) or “Rooted” (willow and graminoids)

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vegetation. Mushrooms are non-vascular organisms (fungi); however they were included in the

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geometric means calculated for VT. The BCFv has been shown to be a good measure of

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contaminant concentrations in fresh plant tissues, and relates well to the fugacity capacity in

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modeling studies.40

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Biomagnification factors (BMFs) for wolves were calculated as the ratio of the arithmetic

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mean, lipid-normalized concentrations in wolves to caribou, using tissue specific concentrations

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and TBCs. BMFs in caribou were calculated using TBCs compared to mixed diets of vegetation,

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calculated using proportions observed in feces of caribou from the Yukon Territory41 for

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fall/winter (70 % lichens, 30 % moss), spring (40 % lichens, 60 % graminoids) and summer (100

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% willow) as in Morris et al.30 The proportionate BMFs were then modeled using Monte Carlo

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analyses (Crystal Ball, Oracle Inc.) to obtain means and standard deviations. The different

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proportions of vegetation used for the caribou BMFs were used to gauge the effects of variable

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diet composition on the biomagnification of the HFRs. Since caribou and wolf samples were

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largely collected in fall or late summer (respectively), the “fall/winter” estimates are the most

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applicable (calculations provided in the SI).

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Trophic magnification factors (TMFs) were calculated as the anti-log of the slope of log-

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linear regression analyses of individually plotted, lipid-normalized concentrations (CB, pg g-1 lw)

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versus TL.42 TMFs were calculated using TBCs for mammals in combination with different

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groups of vegetation (VT, lichens, or green plants). TMFs were only presented when the DFs of

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the analytes exceeded 50 % across all of the biota included in the regression (Table S9).

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Statistics

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Sigmaplot v.11 and SYSTAT® v.11.0 (Systat Software, Inc) were used for the statistical

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analyses. Significant results were all assessed against a type-1 error rate of α = 0.05. The n

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values were relatively small which made normality tests less reliable, and also complicated the

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assessment of the type-1 error rate. Large differences in concentration are briefly discussed as

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these do provide some evidence of potential differences; however the variability of the data

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affected the significance of many of the tests. The log-transformed data were a better

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representation of the normal distribution (Shapiro-Wilk Test), so the data are presented as

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geometric means with their 95 % confidence intervals (CIs) and all statistical tests used log-

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transformed data.

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Multigroup comparisons were made using one-way analysis of variance (ANOVA) with

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Tukey’s post hoc tests. Pair-wise comparisons between mammals, and tests of BMFs for

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significant differences from one were assessed using 2-tailed student’s t-tests. When the log-

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transformed data failed the normality test (p < 0.05), equal variance tests (Levene’s median test,

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p < 0.05) or the power did not exceed 80 %, Kruskal-Wallis ANOVAs on ranks (with Dunn’s

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post hoc test), or Mann-Whitney U-tests were applied for multi-group and two-group

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comparisons (with recognition that the normality tests were less reliable due to the small n

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values). 10

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TMFs were reported when log-linear regressions had slopes significantly different from

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zero (p < 0.05). Pearson correlation analysis between bioaccumulation metrics (logBCFv, BMF,

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TMF) and the logKOA or logKOW used empirical values for the octanol partition coefficients

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where possible, or the values provided by the US EPA Estimation Programs Interface Suite (EPI

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Suite) v. 4.10 if they were unavailable (Table S6).

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Results & Discussion

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Ecological interactions

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The ecological data have been discussed previously,30 but are outlined here for context.

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These ecological interactions could also be useful in future assessments given the potential

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impact of climate warming on vegetation throughout the Arctic environment.43 Caribou graze

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opportunistically, having a seasonally variable diet.41 This complicates assessments of dietary

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transfer of contaminants from specific food sources, as the vegetation had broad ranges of stable

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isotope values for both δ13C [-23.8 ± 0.783 ‰ (Flavocetraria) to -29.9 ± 0.791 ‰ (willow)], and

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δ15N [-5.19 ± 1.86 ‰ (Cladonia) to 4.24 ± 2.02 ‰ (graminoids)] (Table S4). This range of stable

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isotope values reflects different modes of nutrient acquisition and interactions between the

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vegetation such as atmospheric uptake alone (lichens, moss), across roots (graminoids, willows),

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through decomposition (fungi/mushrooms), and via mycorrhizal symbioses between fungal

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mycelia and willow roots.30, 44, 45

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No vegetation (dietary) δ13C signal overlapped exceptionally well with the caribou δ13C

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except Flavocetraria lichens (Table S4 and Table S7), likely due to the efficient mixing and

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fermentation characteristic of digestion in ruminants,30, 46 in addition to relatively long isotopic

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turnover times in ruminant muscle (≈ 4.5 months).47 These factors made direct dietary 11

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interpretation illogical, so dietary compositions reported from a nearby caribou herd in

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fall/winter, spring and summer were used to test the effects of a variable diet (see methods and

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SI).41 The wolves in the Bathurst Region are known to feed primarily on caribou from this area,48

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an observation supported by the overlap of the δ13C in wolves (-23.1 ± 0.643 ‰) compared with

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that of caribou (-23.3 ± 0.255 ‰).

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The calculated TLs were logical for most vegetation (TLs = 1.0–1.5), and the consumers

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(mushrooms = 3.2 ± 0.20, caribou = 3.8 ± 0.081, wolves = 4.6 ± 0.16). Graminoid δ15N signals

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are representative of soil,44, 45 and thus had a relative enrichment of δ15N and an illogical TL out

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of range of the other primary producers (TL = 3.5 ± 0.53, Table S4). To position them in the

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food chain for TMF analyses, graminoids were randomly assigned TLs between 1.0 and 1.5.

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Concentrations and bioconcentration of HFRs in vegetation

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When assessed in VT, the descending order of geometric mean concentrations of

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individual contaminants was TBP-AE (10 ng g-1 lw) > BDE47 (5.5 ng g-1 lw) > BDE99 (3.9 ng

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g-1 lw) > BDE100 (0.82 ng g-1 lw) > PBBz (0.72 ng g-1 lw) > BDE153 (0.49 ng g-1 lw) > BTBPE

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(0.45 ng g-1 lw) (Table S4). BDE28/33, -66, and -154, were detected at lesser frequencies and

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concentrations (0.30–0.35 ng g-1 lw), but were found in at least one caribou food source. The

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octa- and nonaBDEs, which are generally particle-bound in the environment,49 had the fewest

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detections and had high variability in vegetation. When concentrations were assessed in

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vegetation grouped as lichens, green plants, or mushrooms, there were few differences in

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concentrations. TBP-AE was the only compound that varied significantly, being statistically

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greater in lichens (17 ng g-1 lw) than mushrooms (5.0 ng g-1 lw) (KW ANOVA with Dunn’s test,

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p < 0.05) (Figure 1A, Table S4). 12

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The Σtri-heptaBDE concentrations were greatest in moss (34 ng g-1 lw) > Cladonia (29

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ng g-1 lw) ≥ mushrooms (12 ng g-1 lw) > graminoids (9.8 ng g-1 lw) > willow (5.5 ng g-1 lw) >

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Flavocetraria (0.58 ng g-1 lw). The ∑tri-heptaBDE of Flavocetraria was significantly smaller

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than all other vegetation except willow, and no other significant differences were observed (KW

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ANOVA with Dunn’s tests, Table S4). The ∑tri–heptaBDE concentrations in Cladonia lichens

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were greater than those previously reported in Northern Quebec [9.3 (2.9–30) ng g-1 lw] between

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1999–2003,18 however comparisons should be made cautiously due to the substantial spatial and

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temporal differences.

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Most HFRs had their greatest concentrations in Cladonia lichens and/or moss, though

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few statistical differences were detected between vegetation due to the variability in

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concentrations (Table S4). Concentrations of HFRs in Flavocetraria lichens were particularly

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small in contrast to Cladonia, and there were few detections in excess of the MDLs (Table S4).

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This is likely due to their fruticose (Cladonia) versus foliose structures, and the maximization of

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surface area for gas/nutrient/contaminant exchange in fruticose species.50 Statistical differences

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were only observed for less prevalent PBDEs (BDE28/33, -49, -66), and HBB, BTBPE, and syn-

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DP, which were only greater in moss (range 0.64–1.4 ng g-1 lw) than in Flavocetraria and/or

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willow (< MDL) (Table S4).

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The greatest concentrations among the alternative HFRs were found for TBP-AE and

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PBBz (10 and 0.72 ng g-1 lw respectively in VT), which had concentrations comparable to

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prominent PBDE congeners (BDE47, -99, -100, -153, -154; Table S4). BTBPE was detected less

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frequently than TBP-AE and PBBz, but was generally more abundant (VT = 0.45 ng g-1 lw) than

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most of the remaining alternative HFRs (Figure 1A, Table S4). A significant, positive

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relationship was observed between concentrations of TBP-AE and BTBPE in VT (Pearson r2= 13

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0.12, p = 0.036, n = 37) and green plants (r2= 0.32, p = 0.0087, n = 20) (Table S5), which may be

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a result of common delivery pathways, and/or of environmental weathering and

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biotransformation (Figure S2).51, 52 TBP-AE concentrations can be increased by both photolytic

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and anaerobic debromination of TBP-DBPE for example,7, 51 however how this affected patterns

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here is unknown because TBP-BAE and TBP-DBPE were not detected.

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Most of the bromobenzene compounds had very low frequencies of detection excluding

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PBBz (Table S4). The order of decreasing concentrations in VT were PBBz > PBT (0.24 ng g-1

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lw) > HBB (0.23 ng g-1 lw) (Table S4). A wider range of bromobenzenes were detected in air

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around the Great Lakes,53 but transport to the Arctic may be limited for many due to their short

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atmospheric half-lives. PBBz, HBB, and PBT have greater atmospheric stability (Table S6)

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resulting in a greater likelihood of reaching high latitudes. The DP isomers were found at low

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frequencies (≤ 33 %) and concentrations (0.23–0.94 ng g-1 lw) in moss (anti- and syn-DP) and

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mushrooms (syn-DP only), though detections are supportive of reports of DP in arctic media.12, 15

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The homologue group profile of PBDEs measured in air at Alert (6 % triBDEs, 34 %

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tetraBDE, 27 % pentaBDEs, 3 % hexaBDEs, 5 % heptaBDEs, 25 % decaBDE) resembled the

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composition of c-pentaBDE (Bromkal 70-5DE = < 1 % triBDEs, 40 % tetraBDEs, 52 %

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pentaBDEs, 8 % hexaBDEs, < 1 % heptaBDEs), though air had measurable concentrations of

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decaBDE (based on total air concentrations, Figure 2).1 Comparing vegetation types (note that

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Flavocetraria were excluded from this comparison because they had few detectable

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concentrations) revealed only minor differences in their PBDE profiles relative to air and the

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technical mixture. The bulk of the ∑PBDE burden in vegetation are tetra- and pentaBDEs with

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minor contributions from the tri- and hexaBDEs, as well as some contribution from the hepta- to

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octaBDEs in mushrooms. Moss had a greater proportion of tetraBDEs and a less contribution 14

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from the pentaBDEs (≈ 60 % and 28 %, respectively) than did the remaining vegetation (≈44–50

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% and 42–50 %, respectively), with triBDEs only contributing to the ∑PBDE of Cladonia and

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moss (3.1–3.4 %). Accumulation of PBDEs in vegetation was in relative proportion to the

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pattern of congeners in the c-pentaBDE mixture and air, with the exception of BDE209 (Figure

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2).

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The logBCFv values in vegetation grouped as VT, lichens, green plants, or mushrooms

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also varied within a relatively small range (Table 1). The greatest values were observed for

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BTBPE (logBCFv = 8.2–8.6) , while the smallest logBCFv values were found for BDE28/33, -85,

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and -183 (logBCFv = 7.2–7.3), which likely corresponds to their lesser representation in the c-

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PBDE mixtures and atmosphere.1, 39. The most frequently detected PBDEs varied little across

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vegetation types, including BDE47 (logBCFv = 7.4–7.7), BDE99 (7.5–7.8), BDE100 (7.5–7.6),

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BDE153 (7.7–8.0), and BDE154 (7.7). Note that the air concentrations were collected

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throughout 2009 at Alert, NU, and thus represent average air concentrations about 2000 km north

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of the Bathurst caribou range. Therefore, the BCFv values may be overestimated due to low air

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concentrations. However, these were the only available atmospheric HFR data for the Canadian

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Arctic.39 The vegetation also have different life-cycles and modes of nutrient acquisition as

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indicated by their stable isotope values (as previously discussed),54,30 which affects their

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contaminant exposure regimes. These factors do increase the uncertainty of the BCFv, however

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they were suitable to compare bioconcentration between types of vegetation and contaminants.

293 294 295 296

Concentrations of HFRs in mammals The TBCs of HFRs were almost universally greater in wolves than caribou (BDE99 and PBBz were exceptions; Figure 1B, Table S7). The ΣPBDE concentration in wolves was 15

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approximately two times greater than caribou (51 ng g-1 lw and 23 ng g-1 lw), and the Σtri-

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heptaBDE was approximately three times greater in wolves, though they were not significantly

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different (2-tailed t tests, p > 0.05). The greatest TBCs in mammals were: wolves BDE207 (10

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ng g-1 lw) > BDE206 (8.7 ng g-1 lw) > BDE208 (5.0 ng g-1 lw) > BDE28 (4.1 ng g-1 lw) >

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BDE47 (3.3 ng g-1 lw); caribou BDE207 (6.8 ng g-1 lw) > BDE208 (3.8 ng g-1 lw) > BDE206

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(3.7 ng g-1 lw) > BDE99 (< 2.3 ng g-1 lw) > BDE47 (1.6 ng g-1 lw).

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The TBC of BDE28/33 in wolves was significantly greater than that in caribou (< MDL,

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2 tailed t test, p < 0.05) (Figure 1B, Table S7). BDE153 and BDE154 were the only other

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significant differences among TBCs in wolves (0.81 and 0.82 ng g-1 lw respectively) versus

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caribou (< 0.16 and 0.16 ng g-1 lw; p < 0.05), though there are other differences in HFR

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concentrations that seem visually disparate, but were not significant. Metabolic formation of the

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significantly different congeners in addition to biomagnification may be a factor in these

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differences. BDE28 and -154 have been identified as debromination products of higher

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brominated PBDEs in carp (Cyprinus carpo, ).55 Though BDE153 has been hypothesized to be

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part of the debromination pathway to BDE47, stable formation to this congener has not been

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catalogued to our knowledge.56, 57 Other top predators with high metabolic capacities such as

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polar bears (Ursus maritimus),58 cetaceans and pinnipeds,18, 59-62 and raptorial birds63 have been

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shown or hypothesized to metabolize PBDEs, though the specific capacity varies considerably

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by species and congener.

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In tissue-specific comparisons, the Σtri-heptaBDE concentrations were significantly

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smaller in muscle of caribou (2.7 ng g-1 lw) than in their liver and in both tissues of wolves,

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which were not significantly different from each other (caribou liver = 11 ng g-1 lw, wolf muscle

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= 30 ng g-1 lw, wolf liver = 14 ng g-1 lw) (KW ANOVA with Dunn’s tests). The ∑PBDE (tri16

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nonaBDEs) was greater in tissues of wolves (72–83 ng g-1 lw) than those of caribou (23–36 ng g-

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1

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differences in the order of TBCs in tissues of wolves: muscle = BDE207 > BDE206 > BDE28/33

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> BDE47 > BDE99; liver = BDE207 > BDE206 > BDE208 > BDE28/33 > BDE154. The pattern

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in liver in particular is again indicative of biotransformation of PBDEs, as nonaBDEs, BDE28/33

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and BDE154 have been identified as metabolic debromination products in fish and wildlife.55, 57,

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63, 64

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lw), however the results were not statistically significant (Table S7). There were distinctive

Concentrations of most PBDE congeners were not statistically different between tissues

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of mammals, though concentrations did tend to be highest in liver of caribou and muscle of

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wolves (Table S7). Greater concentrations of HFRs in muscle over liver in wolves are likely

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related to depletion of metabolically active HFRs58, 63 in the liver. Metabolism during

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fermentation via gut microorganisms is theoretically possible in ruminants, however this was

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found to be insignificant in dairy cows, while reductive debromination in liver was hypothesized

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to be the most important pathway producing higher brominated PBDE congeners.65 Species and

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congener-specific differences in hepatic biotransformation and depuration of organic

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contaminants are the most reasonable explanations for the differences between the tissues of

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wolves and caribou, as was observed for PCBs.31

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Mammalian ΣPBDE profiles had greater proportions of the highly brominated PBDEs

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than vegetation (Figure 2). The comparison is complicated as BDE 209 is not reported, however

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the consistent detections of nonaBDEs is suggestive that BDE209 is present in mammals. Both

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mammals had ΣPBDE congener profiles dominated by the nonaBDEs (TBC proportions ≈ 53 %

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and 66 % in wolves and caribou respectively) (Figure 2). Caribou had greater contributions from

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the pentaBDEs (≈16 %) than did wolves (≈ 8.5 %), while wolves had greater proportions of the 17

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hexaBDEs (5.5 % and 1.8 % in wolves and caribou respectively). In grizzly bears (Ursus arctos

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horribilis) from Western Canada, the highest concentrations of PBDEs were BDE209 > BDE206

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> BDE47 > BDE207 > BDE208 when the bears shifted to diets that had significant amounts of

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vegetation (grizzlies are omnivorous).66 Conversely the same bears had greater proportions of

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lower brominated PBDEs during salmon-feeding periods of their seasonal cycle, which

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suggested that eating vegetation increased their exposure to nonaBDEs.66 Measurable amounts of

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nonaBDEs in herbivorous caribou may be supportive of these previous results,66 however this

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hypothesis requires further validation. Unfortunately, the concentrations of most octa- to

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nonaBDEs were < MDL in vegetation, and thus the degree of debromination55, 57, 63, 64, 67, 68

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versus direct uptake and absorption (air inhalation or diet) is impossible to ascertain. Changing

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melt conditions and growing seasons in arctic terrestrial environments can alter exposure regimes

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of vegetation and ultimately of consumers, a factor which will be increasingly important in

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future assessments.43

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The concentrations of PBDEs in terrestrial consumers presented here were comparable to

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previous studies (Table S8). Concentrations of PBDEs in moose from two southern NWT herds

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were generally in a similar range as those for caribou,24 as were PBDEs in Norwegian moose.21

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However rodents in Belgium had concentrations of BDE153 and BDE183 that were

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approximately 5-fold greater than those in caribou (Table S8).22 Concentrations of most PBDE

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congeners in common between studies were greater in the Bathurst wolves than in Belgian

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foxes.22, 23

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TBP-AE and PBBz were the most frequently detected and abundant alternative HFRs in

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the mammals, as they were in vegetation (Table S5). TBP-AE was highest in muscle of wolves

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(4.0 ng g-1 lw), however significant differences were only detected between liver of caribou over 18

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those in the liver of wolves (3.3 and 0.99 ng g-1 lw respectively; Figure S3). BTBPE was

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detected solely in the muscle of wolves (2.4 ng g-1 lw), negating tests for correlations in caribou.

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Unlike vegetation, TBP-AE and BTBPE were not correlated within or between tissues of wolves

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or in TBCs (r2 = 0.0072–0.40, p = 0.13–0.86, n = 7). Terrestrial results for comparison are rare,

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however TBP-AE was also detected in liver of moose from southern NWT (