Bioaccumulation of Pcbs in Arctic Seabirds: Inﬂuence of Dietary Exposure and Congener Biotransformation

Environmental Pollution 134 (2005) 397–409 www.elsevier.com/locate/envpol

Bioaccumulation of PCBs in Arctic seabirds: inﬂuence of dietary exposure and congener biotransformation

Katrine Borga˚ a,*, Hans Wolkersa, Janneche U. Skaareb,c, Haakon Hopa, Derek C.G. Muird, Geir W. Gabrielsena

aNorwegian Polar Institute, N-9296 Tromsø, Norway bNational Veterinary Institute, P.O. Box 8156 Dep., N-0033 Oslo, Norway cNorwegian School of Veterinary Science, P.O. Box 8146 Dep., N-0033 Oslo, Norway dNational Water Research Institute, Environment Canada, Burlington, ON, L7R 4A6, Canada

Received 5 March 2004; accepted 17 September 2004

Contaminant patterns is linked to phylogeny and species-speciﬁc diﬀerences in enzyme systems and activity.

Abstract

Four seabird species and their prey (zooplankton or fish) were collected in the Barents Sea to determine how dietary exposure, cytochrome P450 (CYP) enzyme activities and sex influenced their hepatic PCB concentrations and accumulation patterns. Five males and five females from each seabird species (little auk (Alle alle), Bru¨ nnich’s guillemot (Uria lomvia), black guillemot (Cepphus grylle) and black-legged kittiwake (Rissa tridactyla)) were analysed. PCB concentrations could not be explained directly by carbon source (d13C) or trophic position (d15N), but by a combination of dietary parameters (d13C, d15N, migratory pattern, age) and contaminant metabolism. Contrary to previous studies, the PCB pattern differed among seabirds, with a higher proportion of persistent congeners (% of PCB-153, RPCB-153) in black-legged kittiwake than in auks. The PCB pattern also differed among auks, with little auk as the most efficient biotransformer (highest RPCB-153 values of persistent congeners). Based on high RPCB-153 values, Bru¨ nnich’s guillemot poorly metabolised ortho–meta-unsubstituted congeners, whereas black guillemot poorly metabolised meta–para unsubstituted congeners. Species-specific differences in PCB biotransformation were confirmed by metabolic indices, where PCB patternsP in seabirds were adjusted for PCB pattern in prey. The relative contribution of ortho–meta-unsubstituted congeners to PCBs decreased with increasing EROD activity. There were no differences in PCB concentrations, PCB patterns or cytochrome P450 enzyme activities between males and females. CYP P450 activities (CYP1A- and CYP2B/3A-like: EROD and testosterone 6b-hydroxylation, respectively) were low and did not correlate with concentrations of non- or mono-ortho Cl-substituted PCBs (NO- and MO-PCBs), or with total toxic equivalent concentrations (TEQs) for dioxin-like effects of NO- and MO-PCBs. Ó 2004 Elsevier Ltd. All rights reserved.

Keywords: Stable isotopes; Larids; Alcids; Biotransformation; Feeding rate; Toxic equivalent concentrations; Metabolic index

1. Introduction Compared to other Arctic regions, high levels of organic contaminants have been found in Barents Sea mammals The Barents Sea region sustains a highly productive and some seabirds, with particularly high abundance of marine ecosystem in the Arctic, supporting a variety of polychlorinated biphenyls (PCBs) (de March et al., wildlife species of which seabirds are numerous. 1998; Muir et al., 2000; de Wit et al., 2004). PCBs, which have been used for industrial purposes due to their * Corresponding author. Tel.: C47 777 505 35; fax: C47 777 505 chemical inertness, reach this Arctic region mainly 01. through atmospheric transport and ocean currents, E-mail address: [email protected] (K. Borga˚ ). and there are few or no local sources in the Barents

Sea (de March et al., 1998). The hydrophobicity and by the World Health Organization (Van den Berg et al., biological recalcitrance of PCBs results in bioaccumu- 1998). TEF is the order of magnitude toxicity of a com- lation in lipid-rich tissues of biota, often with increasing pound relative to that of 2,3,7,8-tetrachlorodibenzo- concentrations with tropic position in food webs (e.g. p-dioxin (TCDD), which has a coplanar configuration Borga˚ et al., 2001a; Fisk et al., 2001a). PCB accumu- and is assumed to be the most toxic compound acting lation in food web components, including in the Barents through the Ah-receptor complex. The TEFs combined Sea, is highly dependent on exposure (generally related with the organism’s concentrations are used to calculate to diet and thus trophic position) and physiology of the toxic equivalent concentrations (TEQs). Whereas several target species (e.g. biotransformation capacity) (e.g. studies have been carried out on CYP activity and its Fisk et al., 2001a; Hop et al., 2002). relationship to PCB concentrations or pattern in the high Although total PCB and its contribution to sum trophic level glaucous gull and marine mammals from the organochlorines in birds have been related to diet and Barents Sea (Wolkers et al., 1999; Henriksen et al., 2000), phylogeny (e.g. Buckman et al., 2004), detailed avian seabirds at the intermediate trophic levels have so far not PCB patterns have been reported to be independent of been studied. trophic position and food sources (Braune and Nor- The disparity between results on avian PCB pattern strom, 1989; Borlakoglu et al., 1990). In addition, when motivates closer investigation of which factors influence comparing different seabird species, the PCB pattern was avian PCB accumulation. The present study investigates found to be relatively similar across species (Borlakoglu the PCB bioaccumulation in one gull species (black- et al., 1990). However, in the Barents Sea, similar PCB legged kittiwake (Rissa tridactyla)) and three auks (little patterns were found among gulls that differ in trophic auk (Alle alle), Bru¨ nnich’s guillemot (Uria lomvia), black positions and PCB concentrations, whereas gulls and guillemot (Cepphus grylle)) from the Barents Sea. These auks with comparable PCB concentrations differed in long-lived seabirds are particularly numerous in the PCB pattern (Borga˚ et al., 2001a). Gulls had a higher Barents Sea region, especially during the breeding proportion of persistent PCBs than auks, a difference season, and represent the 3rd to 4th trophic levels in which might result from differences in biotransforma- the food web. Their main diet is calanoid copepods, tion, with gulls being better biotransformers than auks. larger zooplankton and fish, and fish, respectively, for The cytochrome P450 enzyme system (CYP) plays an little auk, Bru¨ nnich’s guillemot, and black guillemot and important role in regulating a variety of endogenous black-legged kittiwake (Lønne and Gabrielsen, 1992; substances such as hormones. CYP isoforms are also Mehlum and Gabrielsen, 1993; Weslawski et al., 1999). involved in the first oxidative step of contaminant Whereas kittiwake migrates, the auks reside in the biotransformation (Walker, 1998). The presence and Nordic waters throughout the year (Anker-Nilssen activity of CYP isoforms determine an organism’s ability et al., 2000). These species were selected as they are and capacity to biotransform contaminants and, thus, its very abundant and important in the flux of energy in the contaminant levels and patterns (Murk et al., 1994; Svalbard and the Barents Sea, and there are no data Walker, 1998). Based on PCB patterns in tissues, birds are available from the European Arctic on CYP activities suggested to eliminate congeners with chlorine (Cl) and TEQs in lower trophic level avian species. unsubstituted meta–para positions (through CYP2B/ The objective of the present study was to investigate 3A-like enzymes) to a higher extent than congeners with the relationship between avian hepatic Cl-unsubstituted ortho–meta positions (through CYP1A- like enzymes) (Braune and Norstrom, 1989; Borlakoglu (i) PCB concentrations and dietary parameters such as et al., 1990). Non- and mono-ortho Cl-substituted PCBs trophic position (d15N), carbon source (d13C), (NO-PCB and MO-PCBs) have high potency for feeding rate, migration pattern, and sex. coplanar configuration, and thus induction of CYP1A (ii) PCB pattern and biotransformation ability due to enzymes. Both NO- and MO-PCBs have been found in phylogeny and selected CYP enzyme activities Arctic air (Harner et al., 1998), ice-associated amphipods (ethoxyresorufin O-deethylation (EROD) and tes- (Borga˚ et al., 2001b), Canadian Arctic seabirds (Braune tosterone hydroxylation). and Simon, 2003) and European Arctic glaucous gulls (iii) PCB TEQ values and CYP induction. (Larus hyperboreus)(Daelemans et al., 1992). Although positive correlations have been found between PCB concentrations and various biochemical parameters (including CYP1A enzymes) in Barents Sea glaucous gull 2. Materials and methods (Henriksen et al., 2000), no studies are available on PCB toxicity in seabirds occupying lower trophic levels in the 2.1. Species and sampling Barents Sea. To evaluate aryl hydrocarbon (Ah) receptor mediated toxicity of NO- and MO-PCBs, toxic equiva- The seabirds were collected in the marginal ice zone lency factors (TEF) were established for these congeners of the north-central (76 08#–76 96#N, 32 52#–33 31#E) K. Borga˚ et al. / Environmental Pollution 134 (2005) 397–409 399 and north-western (76 46#–77 45#N, 27 00#–28 13#E) Chemscan A/S; Elverum, Norway) before separation of Barents Sea from 9 to 20 May 1999, using a shotgun PCBs by HRGC. The GC (Agilent 6890 Plus GC with steel pellets. Five females and five males from each system, Agilent Technologies) was equipped with two species were randomly selected from a pool of hunted fused silica capillary columns of different polarity (SPB- birds (total sample size Z 40). Within 15 min after 5 and SPB-1701; 60 m, 0.25 mm ID, 0.25 mm film; death, the seabirds were dissected and liver samples Supelco inc.) and 63Ni-micro electron capture detector for analyses of CYP enzyme activities were stored frozen (Agilent Technologies). in liquid nitrogen. Liver and muscle samples were frozen The samples were analysed for PCB congeners -28, -31, at ÿ20 C in containers of polypropylene and alumin- -47, -52, -66, -74, -99, -101, -105, -110, -118, -128, -137, ium foil, respectively, and analysed for PCBs and stable -138, -141, -149, -151, -153, -156, -157, -170, -180, -183, carbon and nitrogen isotopes, respectively. Body mass -187, -189, -194, -196, -199, -206, -209 (Ballschmiter and (g), sex, age (juvenile/adult based on plumage) were Zell, 1980). Most congeners were quantified on the SPB-5 registered. The seabirds’ main prey were collected column, except PCB-52, -101, -105 and -149 which had simultaneously and analysed for PCBs as described in a better resolution on the SPB-1701 column. Recoveries detail elsewhere (Borga˚ et al., 2001a; Borga˚ et al., 2002). of the analysed PCBs ranged from 78 to 122% (mean A seabird’s daily feeding rate is determined by its 93%). The congener dependent quantification limit daily energy requirement (Gabrielsen et al., 1991; Ellis (Z3 ! detection limit) ranged from 0.04 to 0.19 ng gÿ1 and Gabrielsen, 2002). Based on the measured body wet weight (mean 0.09). The reproducibility, precision, mass and its species-specific relationship with basal and linearity and sensitivity of the analyses were within the field metabolic rates (Gabrielsen et al., 1991; Ellis and accredited requirements of NS-EN ISO/IEC 17025. Gabrielsen, 2002), daily energy requirements were Hepatic lipid extracts (4–6 samples depending on calculated for each seabird species. Given the energy species, see Table 1 footnote) from the ETL were density of the species’ prey items in the Barents Sea shipped to Axys Analytical Services (Sidney, Canada), (Gabrielsen et al., 1991; Gabrielsen and Ryg, 1992) and where non-ortho Cl-substituted PCBs (NO-PCBs: PCB- the assimilation efficiencies of seabirds (Brekke and 77, -81, -126, -169) were isolated and quantified using Gabrielsen, 1994), the respective weight-specific feeding the United States Environmental Protection Agency rates were calculated assuming a diet of 100% copepods method 1668A. This technique is an isotope-dilution, in little auk, 20% euphausiids, 20% amphipods and congener-specific method using 13C-labelled PCB-77, 60% polar cod in Bru¨ nnich’s guillemot, and 100% polar -81, -126, -169 standards added to the extract. Lipids cod in black guillemot and kittiwake, based on previous were removed by gel permeation chromatography, and dietary analysis of these species in the Barents Sea NO-PCBs were isolated using a carbon column. GC-HR (Lønne and Gabrielsen, 1992; Mehlum and Gabrielsen, mass spectrometry was performed on a Micromass 1993; Weslawski et al., 1999). Autospec Ultima magnetic sector mass spectrometer. The liver microsome EROD rates were determined 2.2. Chemical analyses fluorimetrically as described by Wolkers et al. (1998), whereas testosterone hydroxylation activities were de- The hepatic concentrations of ortho Cl-substituted termined using high pressure liquid chromatography PCBs were determined by high-resolution gas chroma- according to Wortelboer et al. (1992). tography (HRGC) at the Environmental Toxicology Stable isotope ratios were analysed in seabirds’ Laboratory (ETL) at the Norwegian School of Veter- muscles at the Institute for Energy Technology, Kjeller, inary Science. Methods with modifications for extrac- Norway as described in details by Hop et al. (2002). tion, clean up, separation and identification are Stable isotope values of d15Nandd13C (SI) were described in previous publications (Brevik, 1978; Borga˚ expressed as SI Z ((Rsample/Rstandard)ÿ1)1000, where R et al., 2001a). In short, internal standards (PCB-29, -112 is the corresponding ratio of 15N/14Nor13C/12C related and -207: Promochem, GmbH, Germany) were added to to standard values in atmospheric air (IAEA-N-1 and 2) the individual livers before homogenisation (Cole or Pee Dee Belemnite (PDB: USGS 24), respectively. To Parmer ultrasonic homogeniser, 4710 Series, Cole convert d15N into trophic levels, the formula for seabirds Parmer Instrument Co., Chicago, IL, USA), and by Fisk et al. (2001a) was used (trophic level extraction of lipids and PCBs was carried out with Z 3 C (d15N ÿ 10.1)/3.8). cyclohexane and acetone (Rathburn Chemicals, Walkerburn, Scotland). A portion of the lipid extract 2.3. Data treatment and statistical analyses was used to gravimetrically determine the content of extractable organic matter (Sartorius analytic A200S, The PCBs were divided into metabolic groups Satorius AG, Go¨ ttingen, Germany), mainly neutral depending on Cl-substitution in the ortho–meta and lipids. To remove lipids, extracts were washed with meta–para position (Table 1), which influences the a surplus of concentrated sulphuric acid (Scanpure, persistency of congeners in homeotherms (Boon et al., 400 K. Borga˚ et al. / Environmental Pollution 134 (2005) 397–409

Table 1 Hepatic polychlorinated biphenyl (PCB) concentrations (ng gÿ1 lipid weight), carbon and nitrogen isotope ratios (d13C, d15N), cytochrome P450 enzyme activities (CYP), body mass and hepatic lipid content (arithmetic mean G SE, (min–max)) in four seabird speciesa from the Barents Sea, May 1999 Vicinal H-atoms in # Cl in Little auk, Bru¨ nnich’s guillemot, Black guillemot, Kittiwake, b c ortho Alle alle Uria lomvia Cepphus grylle Rissa tridactyla only om mp PPCBs NO-PCBsd 0 1.4 G 0.1 1.0 G 0.1 1.1 G 0.2 1.3 G 0.4 (0.9–2.5) (0.5–1.3) (0.4–2.4) (0.4–4.0) P MO-PCBse 1 869.3 G 161.7 572.4 G 68.0 684.9 G 52.8 1402.9 G 185.4 (425.8–2023.8) (315.9–1032.2) (398.1–1027.2) (696.7–2351.2) P DI-PCBsf 2 2339.8 G 412.5 891.6 G 132.2 1562.1 G 114.8 5990.2 G 900.0 (1068.6–4724.8) (365.5–1615.8) (923.4–2357.5) (2178.3–9960.9) P PCB group Ig – – 0–4 1340.5 G 234.2 500.9 G 67.8 690.6 G 40.5 3994.6 G 639.7 (590–2745.7) (141.9–813.3) (469.9–933.5) (1373.0–7024.4) P PCB group IIh C – Z2 1083.2 G 201.7 447.2 G 71.0 706.6 G 52.5 2483.218 G 350.2 (482.2–2254.9) (208.6–875.1) (426.3–1066.5) (965.8–3905.4) P PCB group IIIi C – !2 868.5 G 161.7 561.8 G 67.3 667.28660 G 52.4 1380.603 G 181.4 (424.9–2023.2) (296.5–1016.0) (386.8–1010.6) (689.1–2298.3) P PCB group IVj C Z2 159.0 G 25.7 40.0 G 4.3 274.9 G 31.8 108.2 G 17.9 (73.5–300.6) (23.4–59.9) (98.9–491.3) (51.2–230.0) P PCB group Vk – C O2 33.4 G 3.5 4.4 G 1.1 61.6 G 6.6 31.5 G 4.3 (18.5–52.9) (2.2–12.8) (25.0–110.4) (19.3–65.4) P PCBsl 3483.0 G 605.9 1545.2 G 204.4 2383.3 G 176.7 7981.0 G 1161.2 (1631.7–6787.6) (712.7–2749.8) (1395.7–3595.2) (3110.6–12794.9) P TEQm 0.16 G 0.04 0.08 G 0.01 0.08 G 0.01 0.17 G 0.02 (0.10–0.27) (0.05–0.10) (0.06–0.11) (0.06–0.32) P TEQ wet weight 0.01 G 0.00 0.00 G 0.00 0.00 G 0.00 0.01 G 0.00 (0.003–0.01) (0.001–0.004) (0.001–0.005) (0.005–0.01) Diet descriptors d13C(&) ÿ21.4 G 0.1 ÿ21.0 G 0.1 ÿ21.9 G 0.1 ÿ21.3 G 0.1 ÿ22.0 to ÿ20.8 ÿ21.3 to ÿ20.6 ÿ22.1 to ÿ21.6 ÿ21.9 to ÿ20.8 d13N(&) 10.5 G 0.1 13.1 G 0.1 14.2 G 0.1 13.5 G 0.1 9.5–11.0 12.8–13.6 13.7–15.0 12.9–14.2 Trophic positionn 3.0 G 0.04 3.7 G 0.02 4.0 G 0.03 3.8 G 0.04 2.7–3.1 3.6–3.80 3.8–4.2 3.6–4.0 CYP activities (pmol minÿ1 mg proteinÿ1) ERODo 36.9 G 3.2 8.2 G 1.5 10.1 G 0.7 12.0 G 1.4 21.3–51.3 3.0–16.2 7.0–13.4 4.7–20.3 Testosterone 6b-hydroxylation 118.5 G 7.8 139.7 G 14.8 89.8 G 9.7 129.1 G 8.3 87.2–175.9 78.3–211.4 59.9–160.5 94.2–167.2 Body mass (g) 181.0 G 3.6 1053.2 G 17.7 465.0 G 21.9 421.2 G 13.0 165.0–195.0 965.0–1130.0 370.0–560.0 370.0–500.0 Hepatic lipid content (%) 4.1 G 0.2 3.6 G 0.4 5.3 G 1.0 7.7 G 1.3 3.2–4.9 2.5–6.0 2.5–13.8 3.0–14.5 a Five males (M) and 5 females (F) were analysed from each species, except for the analysis of non-ortho Cl-substituted PCBs where n Z 4, 5, 5, 6 for in little auk (1F/3M), Bru¨ nnich’s guillemot (2F/3M), black guillemot (4F/1M) and kittiwake (3F/3M), respectively. b Ortho–meta position. c MetaP –para position. d Z PNO-PCBs PCB-77, -81, -126, -169. Non-ortho Cl-substituted PCBs. e Z PMO-PCBs PCB-28, -31, -66, -74, -105, -118, -156, -157, -189. Mono-ortho Cl-substituted PCBs. f PDI-PCBs Z PCB-47, -52, -99, -101, -110, -128, -137, -138, -141, -153, -170, -180, -194. Di-ortho Cl-substituted PCBs. g PPCB group I Z PCB-153, -169, -180, -183, -187, -189, -194, -196, -206, -209 (no vicinal H-atoms). h Z R P PCB group II PCB-47, -99, -128, -137, -138, -170 (vicinal H-atoms only in ortho–meta positions, 2Clinortho-position). i Z ! PPCB group III PCB-28, -66, -74, -77, -81, -105, -126, -118, -156, -157 (vicinal H-atoms only in ortho–meta positions, 2Clinortho-position). j PCB group IV Z PCB-31, -52, -101, -110, -141 (vicinal H-atoms in meta–para positions, %2Clinortho-position). PCB-31 and -110 have vicinalP H-atoms also in ortho–meta positions. k Z O P PCB group V PCB-149, -151, -199 (vicinal H-atoms in meta–para positions, 2Clinortho-position). l PPCBs Z sum of all analysed congeners. m TEQ based on all NO-PCB and the MO-PCB congeners -105, -118, -156, -157, -189. n Trophic position Z 3 C ((d15N ÿ 10.1)/3.8), based on Fisk et al. (Fisk et al., 2001a). o EROD Z ethoxyresoruﬁn O-deethylation. K. Borga˚ et al. / Environmental Pollution 134 (2005) 397–409 401

1997). Group I is persistent due to lack of vicinal matrix, adjusting for lipids in the ordination of hydrogen atoms (H), and groups II and III have vicinal concentrations. Since NO-PCBs were analysed in 4–6 H-atoms only in ortho–meta positions. Metabolism of samples per species (see Table 1 footnote), they were group II is inhibited due to the steric hindrance by di- excluded from the ordination analyses. Initially, the ortho Cl-substitution, whereas group III may be analyses only included congeners found in all species, metabolised by CYP1A mediated enzymes due to non- thus excluding PCB-31, -52, -110, -141, -149, -151, -189, or mono-ortho Cl-substitution (om-congeners). Groups -199 and -206. Values below quantification limit (1% of IV and V may be metabolised due to vicinal H-atoms in the data) were replaced by randomly generated normally meta–para positions (mp-congeners), group IV with two distributed data, assuming ½ the detection limit as the or less ortho Cl-substitutions and group V with more mean, with 40% variation (StatPlus V2.5 in Excel 2002 than di-ortho Cl-substitutions. Furthermore, the con- for Windows). However, as this excluded most mp- geners were categorised as non-, mono-, or di-ortho Cl- congeners, also congeners missing from only one species substituted (NO-, MO-, or DI-PCBs, respectively), with were included. This resulted in a final inclusion of 24 respectively decreasing coplanar configuration and congeners and exclusion of PCB-141, -151, -189, -199 ability to induce CYP1A-like isoenzymes through and -206, and missing values were replaced as described binding to the aryl hydrocarbon receptor. Based on above (6.7% of the data). Congeners with low RPCB-153 avian toxic equivalency factors (TEFs)P for dioxin-like (!5%) and high cumulative fits (O50%) (PCB-31 and PCBs (Van den Berg et al., 1998), toxic equivalent -196), were excluded from the final RDA to avoid that concentrations (TEQs) were calculated for NO- and congeners associated with higher uncertainty dominated MO-PCBs based on wet weight concentrations. The the ordination. Significant explanatory variables were TEF approach assumes that the toxic response through forward selected manually using Monte Carlo test with the Ah-receptor is dose or concentration additive, and unrestricted permutations (a Z 0.05) (Ter Braak and the TEFs were recommended based on various in vivo Sˇ milauer, 1998). After selecting significant explanatory and in vitro dose–response curves for different avian variables, the significance of each extracted canonical species (Van den Berg et al., 1998). axis was analysed by Monte Carlo test with unrestricted The PCB pattern in seabirds and their prey was permutations under the reduced model (a Z 0.05). To calculated as a proportion of each congener to the investigate the relationship between seabird species and recalcitrant PCB-153 (RPCB-153). The metabolic index the highly species-specific explanatory variables, an (MI) was calculated to determine the accumulation of initial RDA was performed with seabird species as a congener in seabirds relative to the accumulation of explanatory variable, and diet (d15N and d13C), feeding PCB-153 (MI Z RPCB-153_seabird/RPCB-153_prey)(Tanabe rate and CYP activity (EROD and testosterone 6b- et al., 1988). The seabirds’ diet composition was hydroxylation) as response variables. assumed to be the same as described above for The multivariate ordination assigns scores to the calculation of feeding rate. samples (e.g. individual birds) and response variables SAS 8.0 for Windows (SAS Institute Inc., 1989) was (e.g. PCB congeners). The scores are linear combina- used for univariate statistics (ANOVA Type III Sum of tions of the explanatory variables and are presented Squares, Tukey–Kramer’s test, Spearman rank correla- relative to their ordination axes (Figs. 1, 2 and 5). PCBs tions (rs)), such as interspecific comparison of lipid are presented as arrows pointing to the direction of content, stable isotope ratios and CYP activities. For increasing value. Categorical and continuous explana- correlations such as between different PCB groups and tory variables are presented by centroids (e.g. seabird CYP enzyme activities, ANOVA Type III Sum of species) and arrows (e.g. feeding rate), respectively. Squares was used with species as covariant to account Rules of interpretation of the diagram are described for the effect of species. The comparison of PCB concen- elsewhere (Ter Braak, 1995; Van Wijngaarden et al., trations among species was done on lipid adjusted 1995; Van den Brink and Ter Braak, 1999). concentrations, as the hepatic lipid content differed among species (ANOVA, F3,36 Z 4.71, p Z 0.0071). Direct (constrained) multivariate ordination analysis 3. Results (redundancy analysis RDA) was carried out in CAN- OCO 4.5 for Windows (Ter Braak and Sˇ milauer, 1998) 3.1. Seabird characteristics to analyse the structure in the seabirds’ PCB concentrations and patterns (RPCB-153 values), and to relate this All seabirds were adults, except for black guillemot of structure to the explanatory variables d15N, d13C, which 7 were yearlings. Little auk was by far the smallest EROD, testosterone hydroxylation, sex, feeding rate and and lightest species (Table 1), whereas black guillemot species identity. To reduce variance heterogeneity and and kittiwake had intermediate weights followed by skewness, data were log-transformed prior to ordina- Bru¨ nnich’s guillemot as the heaviest species (Tukey– tion, which was performed on the variance–covariance Kramer, p ! 0.05 for all comparisons except between 402 K. Borga˚ et al. / Environmental Pollution 134 (2005) 397–409

1.0 1.0 Black guillemot Black guillemot

#149 #101 #110

#52 δ15N Feeding rate Feeding rate

EROD Little auk #157 #137 Little auk #99 #105 #47 #128 #118 #138 #66 #153 RDA2 (30.5%) RDA2 (12.5%) #74 Kittiwake #183 #187 #180 #28 #156 #170 Testosterone 6β-hydroxylation #194 Brünnich’s Kittiwake δ13 Brünnich’s guillemot C guillemot

-1.0 -1.0 -1.0 1.0 -1.0 1.0 RDA1(37.8%) RDA1 (57.5%)

Fig. 1. Direct multivariate ordination analysis (redundancy analysis PCB group Explanatory variables RDA) of relationship between the four seabird species and chemically- Persistent I&II Seabird species 15 13 derived trophic position (d N) and carbon source (d C), feeding rate Metabolizable om (III) and CYP activities (EROD and testosterone 6b-hydroxylation). Black Metabolizable mp (IV&V) Feeding rate circles are centroid scores of the seabird species (mean of samples per species), whereas arrows are continuous response variables (diet, Fig. 2. Biplot (from redundancy analysis RDA) of PCB concentrations enzyme activity and feeding rate) pointing in the direction of increasing in four different seabird species from the Barents Sea in May 1999 with values. Seabird species explained 50.5% of the total variance, and the significant explanatory variables ( p Z 0.002). Nominal explanatory fraction of the unconstrained explained variance displayed by each variables are given as centroids (mean of samples per species), and ordination axis is given in brackets. arrows of PCBs and feeding rate point in the direction of increasing values. The total variation (53.4%) was accounted for by the kittiwake and black guillemot). As body mass was used constrained ordination, and each axis’ contribution is given in brackets. The fraction of unconstrained variance accounted for by each axis is to calculate weight- and species-specific feeding rates, given in brackets. The PCB grouping is according to Table 1. body mass was replaced by feeding rate in the RDA. The feeding rates were 0.80, 0.35, 0.42, 0.43 g dayÿ1 gÿ1 for little auk, Bru¨ nnich’s guillemot, black guillemot and (range: 3.8–4.2) (Tukey–Kramer, p ! 0.05 for all com- kittiwake, respectively. parisons except between kittiwake and Bru¨ nnich’s Of the total variance in feeding rates, carbon source, guillemot) (Fig. 1). When species variation was accounted trophic position and CYP activities, 50.5% was for, d13C and trophic position were not related (ANOVA explained by the seabird’s phylogeny (Fig. 1). Higher F1,34 Z 0.61, p Z 0.4402). EROD activity and feeding rate, and lower trophic The EROD activity ranged from 3 to position was found in little auk than in the other species, 51 pmol minÿ1 mg proteinÿ1 and was higher in little and lower testosterone 6b-hydroxylation and d13C levels auk than the other species (Table 1, Fig. 1, Tukey– were found in black guillemot than in the other seabirds Kramer, p ! 0.05). Testosterone hydroxylation activity (Fig. 1). The ordination axes significantly related the was only observed at the 6b-position, and ranged from variance of the explanatory variables to seabird species 50 to 250 pmol minÿ1 mg proteinÿ1 (Table 1). The (Monte Carlo F Z 12.2, p Z 0.002, for all axes). More testosterone 6b-hydroxylation was lower in black specifically, the interspecific variance in d13C values was guillemot than in Bru¨ nnich’s guillemot and kittiwake, minor, ranging from ÿ22.1 to ÿ20.6& (Table 1), with whereas no difference was found between the other lowest d13C values for black guillemot, intermediate for species (Fig. 1, Tukey–Kramer, p ! 0.05). When species little auk and kittiwake, and highest for Bru¨ nnich’s variation was accounted for, the CYP activities were not guillemot (Tukey–Kramer, p ! 0.05 for all comparisons correlated (ANOVA, F1,37 Z 0.03, p Z 0.8528). except between kittiwake and little auk or Bru¨ nnich’s Neither carbon source, trophic position nor CYP guillemot) (Fig. 1). Little auk had the lowest trophic activities differed between males and females within each 15 position (range: 2.7–3.1) assigned by d N, Bru¨ nnich’s species (ANOVA, F1,8 ! 2, p O 0.200). When species guillemot and kittiwake had intermediate trophic variation was accounted for, the CYP activities were not positions (range: 3.6–4.0), and black guillemot the highest related to body mass (ANOVA F1,34 ! 2.8 p O 0.1035), K. Borga˚ et al. / Environmental Pollution 134 (2005) 397–409 403

100 Group I Group II Group III Group IV Group V

40 % of PCB-153

PCB-47PCB-99 PCB-28PCB-66PCB-74PCB-77*PCB-81* PCB-31PCB-52 PCB-169*PCB-180PCB-183PCB-187PCB-189PCB-194PCB-196PCB-206 PCB-128PCB-137PCB-138PCB-170 PCB-105PCB-118PCB-126*PCB-156PCB-157 PCB-101PCB-110PCB-141PCB-149PCB-151PCB-199

Little aukBrünnich’s guillemot Black guillemot Kittiwake

Fig. 3. Polychlorinated biphenyl (PCB) pattern in four diﬀerent seabird species from the Barents Sea in May 1999 is presented as values relative to

PCB-153 (RPCB-153 values) (mean C SE). Sample size n Z 10 for each species, except for Bru¨ nnich’s guillemot where one extreme was excluded, and except for PCB-77, -81, -126, and -169, where four to six birds were analysed per species (see Table 1 footnote). *PCB-77, -81, -126, and -169 were multiplied with 100 to make visible on the same scale as the other congeners. The PCB grouping is according to Table 1.

however, the smallest species (little auk) had the highest higher in kittiwake than all other species (Table 1, EROD activities (Table 1). Tukey, p ! 0.05). The mp-metabolizable PCB groups IV and V were highest in black guillemot, followed by little auk and kittiwake, and then by Bru¨ nnich’s guillemot 3.2. PCB concentrations and patterns, TEQ values (Tukey, p ! 0.05). and metabolic indices Direct ordination (RDA) of PCB concentrations P ÿ1 resulted in the four seabird species and feeding rate as PCBs ranged from 700 to 13 000 ng g lipid significant explanatory variables (Monte Carlo weight, depending on species (Table 1). The individual F Z 15.9–23.8, p Z 0.002 for all variables) (Fig. 2). sums of persistent PCBs (groups I and II) were highest Feeding rate correlated highly with species identity and in kittiwake followed by little auk and black guillemot, was automatically selected along with species, pointing and then by Bru¨ nnich’s guillemot (Table 1, Tukey, in direction of little auk, although it did not contribute ! p 0.05). The om-metabolizable PCB group III was in explaining additional variance in PCB concentrations. Even though three ordination axes significantly explained the variation in PCB concentrations (Monte NO MO PCB-77 Carlo F Z 12.5–21.7, p Z 0.002 for all axes), only axes 1 Little auk PCB-81 NO and 2 are presented due to the higher degree of variance PCB-126 explained (42.0, 22.3, 9% of total variance explained by Brünnich's guillemot PCB-169 axes 1, 2 and 3, respectively). The seabirds species PCB-105 differed significantly in PCB concentrations (ANOVA of Black guillemot PCB-118 MO ! PCB-156 samples’ scores on ordination axes, p 0.0001), how- Black-legged kittiwake PCB-157 ever, little auk was not different from kittiwake and PCB-189 black guillemot along axis 1, Bru¨ nnich’s guillemot was 0 25 50 75 100 not different from kittiwake along axis 2 and from % of ΣTEQ kittiwake and black guillemot along axis 3 (Tukey test of samples’ scores on ordination axes, p ! 0.05). When the Fig. 4. Relative contribution (arithmetic mean C 1SE) of non-P (NO) and mono-ortho (MO) polychlorinated biphenyls (PCBs) to toxic effect of species was accounted for, neither chemically- equivalent concentrations (TEQ). Only PCBs with toxic equivalent derived trophic position nor carbon source, CYP factors in Van den Berg et al. (1998) are included. activities or sex explained the differences in PCB 404 K. Borga˚ et al. / Environmental Pollution 134 (2005) 397–409 concentrations among species, due to their high degree 1.0 of species-dependency as illustrated in Fig. 1. Brünnich’s #28 guillemot The NO-PCB concentrations were low relative to #74 #156 #66 other PCB congeners, with mean sum ranging from 1.0 #118 ÿ1 #187 to 1.4 ng g lipid weight depending on species (Table #105

1). The concentrations of NO-PCBs were lower than #128 #99 0.2% of PCB-153 for each congener, whereas the #137 concentrations of MO-PCBs were higher, more than #138 #157 #52 10% of the PCB-153P concentration for all congeners #47 #170 (Fig. 3). Mean TEQ ranged from 1 to 13 pg gÿ1 wet Little auk weight, depending on species (Table 1). Highest TEQ #101 Feeding rate values were found in little auk and Bru¨ nnich’s guillemot. RDA2 (31.7%) #183 Although the MO-PCB concentrations were higher than #180 Black the NO-PCBP concentrations, NO-PCBs contributed 70– guillemot 80% to TEQ, depending on species (Fig. 4). When #110 Kittiwake species variationP wasP accountedP for,P neither concen- trationsP of PCB, NO-, MO-, DI-PCBs nor TEQ were related to chemically-derived trophic -1.0 position or carbon source or CYP activities (ANOVA -1.0 RDA1 (47.8%) 1.0 F ! 2.89, p O 0.0986 for all analyses). 4,35 PCB group Explanatory variables The PCB pattern in all species was dominated by the Persistent I&II Seabird species persistent PCB-153, -138, -118, -180 and -99 (Fig. 3). Metabolizable om (III) Feeding rate The persistentP PCBs (groups I and II) contributed 74– Metabolizable mp (IV&V) 90% to PCBs in kittiwake,P whereas the contribution of groups IV and V to PCBs was !3% (Table 1). Fig. 5. Ordination diagram of PCB pattern (RPCB-153 values) in four P different seabird species from the Barents Sea in May 1999 with PCB groups VI and V contributed 2–17% to PCBs in significant explanatory variables ( p Z 0.002). Nominal explanatory auks. Compared to the other species, Bru¨ nnich’s variables are given as centroids (mean of samples per species), and guillemot had high RPCB-153-values of most PCBs in arrows of PCBs and feeding rate point in the direction of increasing groups II and III, whereas black guillemot had high values. The total variation (33.5%) was accounted for by the R -values of groups IV and V. Kittiwake had constrained ordination, and each axis’ contribution is given in PCB-153 brackets. The PCB grouping is according to Table 1. low RPCB-153-values of group IV. RDA of the seabirds’ RPCB-153-values showed the same differences between species as inferred from the individual RPCB-153-values (ANOVA, F4,35 Z 3.91, p Z 0.0558). The other meta- (Fig. 5), and all seabird species differed significantly in bolic groups did not showP any relationship between PCB pattern (ANOVA of samples’ scores on ordination their relative contribution to PCBs and CYP enzymes. axes, p ! 0.0001). More specifically, both little auk and The seabirds’ metabolic indices (MI), which reflects black guillemot differed from Bru¨ nnich’s guillemot by the seabirds’ congener pattern adjusted for the prey’s having high relative proportion of metabolizable mp- PCB content (prey PCB concentration in Table 2), congeners (groups IV and V), whereas Bru¨ nnich’s differed among PCBs in species-specific manner (Fig. 6). guillemot had more metabolizable om-congeners (group All seabirds had low bioaccumulation of mp-congeners III) (Tukey test of samples’ scores on ordination axes, p ! 0.05). Common for the auks was a higher relative contribution of metabolizable PCBs compared to Table 2 kittiwake (Fig. 5). The only significant explanatory Lipid content (%) and polychlorinated biphenyl (PCB) concentrations variable was seabird species and feeding rate (Monte (ng gÿ1 lipid weight) in the seabirds’ main zooplankton and fish prey Z Z from the Barents Sea in May 1999 (arithmetic mean G SE) Carlo F 3.75–6.25, p 0.002–0.006), whereas the P other explanatory variables did not contribute to Species Group n Lipid PCB9e explain additional variance. Sex did not explain any Calanus glacialis and Copepod 15 2.6 G 0.2 43.3 G 4.6 variation in the seabirds’ PCB pattern (results not C. hyperboreusa b shown). Of the total variance, 16.0, 10.7 and 6.9% were Thysanoessa inermis Euphausiid 9 1.8 G 0.2 74.5 G 8.8 c G G explained by axes 1, 2 and 3, respectively, which Themisto libellula Amphipod 3 1.9 0.4 120.2 27.1 Boreogadus saidad Fish 12 3.8 G 0.4 120.6 G 22.6 significantly explained the extracted variation in R PCB- a -values (Monte Carlo F Z 5.88, p Z 0.002). Samples of 580–1135 pooled individuals. 153 b Samples of 100–115 pooled individuals. When species variation was accounted for,P the c Samples of 7–16 pooled individuals. d relative contribution of congener group III to PCBs PSamples of individually homogenized fish. slightly decreased with increasing EROD activity e PCB9 Z PCB-28, -31, -52, -99, -105, -118, -138, -153, -180. K. Borga˚ et al. / Environmental Pollution 134 (2005) 397–409 405

) 2.0 Group I Group II Group III Group IV 1.8

153_prey 1.6 /R 1.4 1.2

153_seabird 1.0 0.8 0.6 0.4 0.2

Metabolic index (R 0.0 PCB-153 PCB-180 PCB-99 PCB-138 PCB-28 PCB-105 PCB-118 PCB-31 PCB-52 Little auk Brünnich’s guillemot Black guillemot Kittiwake

Fig. 6. PCB pattern in four different seabird species from the Barents Sea in May 1999 adjusted for the pattern in the mean prey (metabolic index Z RPCB-153_seabird/RPCB-153_prey) (mean C SE). The metabolic index describes whether a congener accumulates more (O1) or less (!1) than the persistent PCB-153. The PCB groups refer to the structure described in Table 1. relative to PCB-153 (groups VI and V, MIs ! 0.2), and NO-PCBs and TEQ values in these seabird species from intermediate bioaccumulation of om-congeners relative the European Arctic, or on hepatic PCB concentrations to PCB-153 (group II and III, MI 0.2–1). They had in little auk from the European Arctic. highest bioaccumulation relative to PCB-153 of persis- P When compared to other Arctic seabirds, the present tent congeners without vicinal H-atoms (group I, PCB concentrations in black and Bru¨ nnich’s guille- MIs 1–2) (Fig. 6). mot were comparable to, or in the higher range of, those recently reported from east and west Greenland and northern Baffin Bay in the Canadian Arctic, whereas the 4. Discussion present kittiwake and little auk levels were higher than those reported from Greenland and Canada (de Wit The present study shows that PCB concentrations et al., 2004; Buckman et al., 2004). Higher PCB and congener patterns in seabirds result from a com- concentrations in the Barents Sea biota have also been bined effect of dietary factors and biotransformation. reported in seabird eggs and marine mammals (ringed The independent effect of each of these factors is difficult seals Phoca hispida and polar bears Ursus maritimus)(de to assess due to their high species-specificity and, thus, March et al., 1998; Muir et al.,P 2000; de Wit et al., 2004). collinearity. Another factor confounding the relation- For the European Arctic, PCB concentrations in ships may be the different time-scales regarding changes black and Bru¨ nnich’s guillemots were generally within in an organism’s PCB concentrations, CYP activities the same range, or in the lower range, as those reported and stable isotope ratios. Contaminant half-lives in from the Barents Sea marginal ice zone in June 1995 birds are months to years (Clark et al., 1987; Drouillard (Borga˚ et al., 2001a). The present mean levels in and Norstrom, 2003), CYP activities may reflect kittiwake were generally lower than those reported from physiological changes over days (Schuetz et al., 1984), the Svalbard area in 1991 (Savinova et al., 1995), the and stable isotope ratios may reflect dietary and north Norwegian coast in 1992 (Henriksen et al., 1996), conditional changes on the basis of weeks to months and Bjørnøya in the southern Barents Sea in June 1995 (Hobson and Clark, 1992). Given the lack of year- (Borga˚ et al., 2001a). specific age-determination, age-related PCB accumula- The present study’s PCB–TEQs were lower than in tion and CYP activity could not be accounted for in this similar species from the Canadian Arctic in 1993 study. (Braune and Simon, 2003). The present lower PCB concentrations and TEQ values are in accordance with 4.1. PCB concentrations and TEQs in Arctic seabirds a general temporal decrease in Arctic PCB levels, as reported for seabirds’ eggs (Barrett et al., 1996; Braune Although comparison of PCB residues between et al., 2001) and polar bears (Henriksen et al., 2001). studies is difficult due to variation caused by confounding factors such as the organism’s age, sex, reproductive 4.2. Influence of dietary exposure and sex cycle and condition (e.g. Henriksen et al., 1996), the on PCB levels and patterns hepatic PCB concentrations were compared with corresponding levels in similar species from earlier studies on The d13C varied between species, with lowest and a lipid weight basis. No studies are available on highest values in black and Bru¨ nnich’s guillemot, 406 K. Borga˚ et al. / Environmental Pollution 134 (2005) 397–409 respectively. Because the d13C values reflect the source of feeding rate, in gulls compared to auks of similar size carbon to a system, species with enriched d13C values are (Ellis and Gabrielsen, 2002), may contribute to higher usually influenced by terrestrial carbon from benthic or PCB concentrations in kittiwake compared to black inshore feeding, whereas offshore pelagic feeders often guillemot. Finally, the low PCB levels in black have lower d13C values (Hobson, 1993). However, the guillemots may be due to their young age (yearlings). present range of d13C values was much smaller than in Generally juveniles have accumulated less contaminant studies where true benthic (e.g. common eider Somateria than adults (Donaldson et al., 1997; Bustnes et al., mollisima) and pelagic feeders (e.g. northern fulmar 2003), and their PCB levels might not yet have reached Fulmarus glacialis) are compared (Dahl et al., 2003). The equilibrium with the dietary contaminant exposure. seabirds’ trophic positions determined by stable nitro- Alternative prey and migration does not help explain gen isotopes generally confirmed those inferred from the high PCB levels in little auk, which is a northern dietary data. Trophic position was lowest for little auk, species and a strict feeder on herbivorous calanoid intermediate for Bru¨ nnich’s guillemot and kittiwake and copepods with low trophic position and contaminant highest for black guillemot. Being predominantly fish- concentrations (Hop et al., 2002). However, like in feeders, black guillemot and kittiwake were expected to kittiwakes, the higher feeding rate in little auk (due to its occupy the same trophic position (Lønne and Gabri- lower body mass) may contribute to the relatively high elsen, 1992; Mehlum and Gabrielsen, 1993), but black PCB concentrations, despite its low trophic position. guillemot had higher d15N values than kittiwake. Increased feeding rate was found to increase the PCB Relatively high d15N in black guillemot was also shown uptake rate constant from food in experimental studies in previous studies (Fisk et al., 2001a; Hop et al., 2002). of ringed doves (Streptopelia rissoria)(Drouillard and This indicates that black guillemot feeds higher in the Norstrom, 2003). In addition, the high lipid contents in food web, presumably on demersal or larger fish during calanoid copepods (40% of dry weight, (Scott et al., pursuit diving, whereas kittiwake is a surface feeder on 1999)) might contribute to elevated PCB concentrations smaller pelagic fish, and occasionally on amphipods and in little auk if the higher assimilation efficiency of lipids euphausiids (Lønne and Gabrielsen, 1992; Mehlum and than proteins (Brekke and Gabrielsen, 1994) influences Gabrielsen, 1993). the PCB uptake (Gobas et al., 1999). However, the Increasing PCB levels with trophic position have been ringed dove study showed that PCB assimilation shown previously for seabirds and seals in Arctic marine efficiencies were similar between doves fed a high or food webs (Fisk et al., 2001a; Hop et al., 2002), and a low lipid content diet (Drouillard and Norstrom, among Arctic seabirds from the Canadian Arctic 2003). (Buckman et al., 2004). In the present study, however, Like in Canadian Arctic seabirds (Buckman et al., PCB levels were high in little auk occupying the lowest 2004), there were no sex differences in PCB concen- trophic position, and generally lower in black guillemot trations. However, sample sizes in both studies were occupying the highest trophic position. Likewise, small (!7 per sex and species), hence the results must be kittiwakes had lower d15N and higher PCB concen- treated with some caution. trations than black guillemot. In the Canadian Arctic studies, seabird species spanning over a larger range of 4.3. CYP enzymes in relation to PCB concentrations trophic positions were included, from little auk (trophic and TEQ values level 3) to glaucous gull (trophic level 5) (Buckman et al., 2004). However, in glaucous gulls from Bjørnøya, The seabirds’ EROD and testosterone hydroxylation Barents Sea, only a weak relationship was reported activities differed among species, although auks were not between organochlorine levels and trophic position distinctly different from kittiwakes. Little auk had the (Sagerup et al., 2002). The present study’s discrepancy highest EROD activity compared to the other species, between d15N and PCB concentrations may be due to and higher than that measured in glaucous gull from the different turnover rates of proteins versus contaminants, same area (Henriksen et al., 2000). The EROD activity suggesting a previous diet of more contaminated prey in the other seabirds was lower than in glaucous gulls. for kittiwake in the over-wintering area or by occasion- Overall, the EROD activities were low compared to ally feeding on seal blubber from carcasses after polar seabirds from more industrialised areas (Bosveld and bear kills (Lønne and Gabrielsen, 1992). As the stable Van den Berg, 1994). However, comparisons between isotopes have half-lives of less than 30 days in muscle studies should be done with caution as species differ (Hobson and Clark, 1992), the d15N in kittiwake reflects widely in CYP response and as inter-laboratory differ- the diet in the marginal ice zone rather than in the over- ences in CYP-assays may cause additional variation wintering area. Black guillemot, on the other hand, is an between studies (Bosveld and Van den Berg, 1994). Arctic resident throughout the year (Anker-Nilssen NO- and MO-PCBs are known inducers of CYP1A et al., 2000) and is not observed feeding on seal enzymes (Safe, 1994P), however,P EROD activity was carcasses. In addition, a higher metabolic rate, and thus neither related to NO-, MO-PCB concentrations, K. Borga˚ et al. / Environmental Pollution 134 (2005) 397–409 407 P or TEQs. The present study’s seabird TEQ values in Barents Sea prey. Another explanation for the high were 100–200 times lower than the lowest observable concentrations of persistent PCBs in kittiwake may be effect level (LOEL) for CYP1A induction (EROD) in an occasional seal blubber diet (Lønne and Gabrielsen, common terns (Sterna hirundo) (25 ng gÿ1 TEQ lipid 1992), which will increase the exposure to persistent weight liver) (Bosveld et al., 2000). Even though the PCBs, as seals efficiently biotransform other PCBs effect threshold varies depending on species and sample (Wolkers et al., 1998). matrix, the presently investigated Arctic seabirds there- The little auk seems to be the most efficient PCB fore seem well below the threshold levels for effects biotransformer of the auks, due to its high relative mediated through the Ah-receptor. In the present study, contribution of persistent PCBs, low relative contribu- the TEQ values were calculated from NO- and MO- tion of om-congeners compared to Bru¨ nnich’s guillemot, PCBs. In Canadian Arctic kittiwake and Bru¨ Pnnich’s and low relative contribution of mp-congeners com- guillemot, NO-PCB contributed 40–60% to TEQ pared to black guillemot. Higher metabolic capacity was when TEQs were calculated also for furans and dioxins found in Bru¨ nnich’s guillemot than black guillemot for (Braune and Simon, 2003). mp-congeners, whereas Bru¨ nnich’s guillemot had higher The high EROD activity in little auk compared to the relative contribution of om-congeners than black guil- other auks and kittiwake may be caused by a higher lemot. The high relative contribution of om-congeners in feeding rate (Braune and Norstrom, 1989; Ronis and Bru¨ nnich’s guillemot concurs with its low EROD Walker, 1989), but also by a diet with different inducers, activity, and suggests a lower ability to metabolise these including natural inducers such as carotenoids from the congeners compared to the other investigated species. calanoid copepods. Calanoid copepods are rich in As previous Canadian studies suggested elevated bio- carotenoid pigments that may induce EROD activity transformation of chlorinated pesticides in Bru¨ nnich’s (Gradelet et al., 1996), which in combination with guillemot compared to other auks (Fisk et al., 2001b), a higher feeding rate results in higher exposure to biotransformation of PCBs and chlorinated pesticides in inducers of CYP1A. Similar to glaucous gulls from the seabirds seems mediated through different enzyme Barents Sea (Henriksen et al., 2000), testosterone systems. The higher contribution of mp-congeners in hydroxylation was only observed at the 6b-position at black guillemot than in Bru¨ nnich’s guillemot coincided comparably low levels in all seabirds. EROD and with the lowest testosterone 6b-hydroxylation, suggest- testosterone 6b-hydroxylation activities were not corre- ing low CYP2B/3A activity and a consequently low lated, suggesting involvement of different CYP enzymes. biotransformation ability in black guillemot. Some pattern-differences between species may also be 4.4. PCB pattern and biotransformation abilities due to dietary differences. However, the metabolic index (MI) confirmed the biotransformation difference among Contrary to previous avian studies (e.g. Borlakoglu seabird species. Although the seabirds may have fed et al., 1990), the PCB patterns differed significantly upon prey not adjusted for, there is only small difference among the seabirds in the present study, especially in PCB patterns among prey (relative to that in seabirds) between kittiwake and auks, but also among the auks. due to their low biotransformation ability (Borga˚ et al., The higher relative contribution of persistent PCBs, 2001a). MIs for all congeners, except for PCB-180, were such as in kittiwake than in auks, suggests a higher higher in black and Bru¨ nnich’s guillemot than in ability in the former to biotransform PCBs. Although kittiwake, supporting lower biotransformation in auks the present CYP activities in all seabirds were low, the than in kittiwake. The relative high MIs for om- Pcontribution of PCB group III (om-congeners) to congeners, although there are interspecific differences, PCBs decreased with increasing EROD activity, are in accordance with previous findings showing that suggesting that CYP1A-like activity influenced the these om-PCBs are slowly cleared from birds (Braune PCB pattern. Despite higher PCB biotransformation in and Norstrom, 1989; Borlakoglu et al., 1990). Similarly, kittiwake, both EROD and testosterone 6b-hydroxyl- the low metabolic indices of mp-congeners indicate that ation activities were low and comparable to the these PCBs are readily cleared from birds, as shown guillemots. The finding of high contribution of persis- previously (Braune and Norstrom, 1989; Borlakoglu tent congeners and low CYP activities in kittiwake et al., 1990). might be due to its migration and overwintering in more In summary, the interspecific PCB pattern in seabirds southern and industrialised areas. Feeding on more suggests that the contaminant pattern is strongly linked contaminated prey might result in a temporary in- to their phylogeny and species-specific differences in duction of CYP-mediated enzymes, leading to increased their enzyme system and activity, resulting both from PCB biotransformation and elevated relative proportion long-term specialisation (potential) and on short-term of persistent congeners in the PCB pattern. By the time exposure (induction). However, potential influence of of collection the CYP activities may have decreased to age and sex on CYP induction and PCB concentrations low levels due to the relatively low contamination levels in these species remains to be investigated. 408 K. Borga˚ et al. / Environmental Pollution 134 (2005) 397–409

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