The Occurrence of Organochlorines in Marine Avian Top Predators

Norwegian Institute for Nature Research, Unit for Arctic Ecology, The Polar Environmental Centre, N-9296 Tromsø, Norway, and Norwegian Institute for ...
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Environ. Sci. Technol. 2006, 40, 5139-5146

The Occurrence of Organochlorines in Marine Avian Top Predators along a Latitudinal Gradient C E C I L I E S T E F F E N , † K A T R I N E B O R G A° , ‡ JANNECHE U. SKAARE,§ AND J A N O V E B U S T N E S * ,† Norwegian Institute for Nature Research, Unit for Arctic Ecology, The Polar Environmental Centre, N-9296 Tromsø, Norway, and Norwegian Institute for Water Research, P.O. Box 173 Kjelsås, N-0411 Oslo, Norway, and National Veterinary Institute and Norwegian School of Veterinary Science, P.O. Box 8156 Dep., N-0033 Oslo, Norway

The aim of this study was to determine the role of cold condensation and fractionation on the occurrence of organochlorine contaminants (OCs) in avian marine top predators along a latitudinal gradient. We measured 24 polychlorinated biphenyl (PCB) congeners and six pesticide OCs in blood of great black-backed gulls (Larus marinus) from the Norwegian Coast (58°N-70°N) and glaucous gulls (Larus hyperboreus) from Bjørnøya in the Norwegian Arctic (74°N). Glaucous gulls had up to 3 times higher ΣOC concentrations compared to the great black-backed gulls, and a OC pattern dominated largely by persistent and low volatile compounds such as highly chlorinated PCBs and metabolites such as oxychlordane. This was not consistent with cold condensation and fractionation theory, but probably related to diet and elevated biomagnification. Among great black-backed gulls, however, there were indications of both cold condensation and fractionation. Higher and lower chlorinated PCBs had highest absolute concentrations in the south and in the north, respectively, except for one location at an intermediate latitude, where concentrations of most OCs exceeded all other locations. In terms of proportional contribution to ΣOC (pattern), relatively volatile OCs such as HCB, oxychlordane and tri- to penta- PCB congeners were more important at northern latitudes, while hexa- to nona-PCBs made up a larger proportion of ΣOC in the south. The results thus showed that differences in global distribution of compounds with different physicochemical properties could be detected in avian top predators such as large gulls, even if biomagnification and biotransformation influence both the absolute concentrations and the patterns of OCs.

Introduction Although the pollution by organochlorine contaminants (OCs) is usually highest near the sources, industrial and agricultural OCs undergo long-range transport and can be * Corresponding author phone: + 47 77 75 04 07; fax: + 47 77 75 04 01; e-mail: [email protected]. † Norwegian Institute for Nature Research. ‡ Norwegian Institute for Water Research. § National Veterinary Institute and Norwegian School of Veterinary Science. 10.1021/es060628v CCC: $33.50 Published on Web 07/19/2006

 2006 American Chemical Society

found in relatively high concentrations, even in remote environments, such as the Arctic and the Antarctic (1-3). Central concepts in the understanding of the global distribution of OCs are cold condensation and global fractionation. Cold condensation refers to shifts of partitioning equilibriums of semi-volatile chemicals from the gas phase to the condensed phases as temperature drops. Global fractionation is when mixtures of OCs, containing compounds of both high and low volatility, are transported from their source regions to remote areas, and the composition shifts toward more volatile constituents with increasing latitude and altitude (4, 5). A good example of fractionation of compounds is the distribution of airborne polychlorinated biphenyl (PCB) congeners and hexachlorobenzene (HCB) along a latitudinal transect from the south of the United Kingdom to northern Norway (6). These measurements showed that the relative contribution of volatile compounds, such as lower chlorinated PCB congeners and HCB, increased with latitude, providing evidence of latitudinal fractionation. Moreover, the absolute levels of HCB increased, while higher chlorinated PCB congeners decreased with increasing latitude. In addition, compositional shifts have been observed along latitudinal gradients in lake sediments (7), marine sediments (8), surface seawater (9), air (6, 10, 11), tree bark (12), and soil (13-15). OC concentrations and patterns in abiotic material provide valuable information about the distribution of pollutants, but they may not reflect the state of contamination in biota. OC concentrations and patterns in animals are determined by exposure through diet and uptake processes such as respiration, and from elimination by processes such as biotransformation, reproduction, respiration, growth, and egestion (16, 17). These processes, and thus an animal’s OC concentration, are influenced by a multitude of factors such as the animal’s age, sex, diet, physiological status, and metabolic capability, that vary both between and within species. It is thus difficult to ensure comparability of samples taken at various latitudes, and some studies from Europe have failed to observe compositional shifts in OC patterns in biota in accordance with global fractionation (18, 19). Such shifts have, however, been found when comparing harbor porpoise (Phocoena phocoena) from Danish and Norwegian waters (20), and in freshwater fish in Canada (21). Moreover, due to variation in recalcitrance and interspecies differences in uptake and elimination efficiencies, OCs bioaccumulate differently in the food web; i.e., more easily metabolized OCs are eliminated and more persistent ones are biomagnified. In general, the ability to selectively eliminate OCs is higher in homeothermic predators, such as seabirds, than in their poikilothermic prey, such as fish and crustaceans, which usually reflect the abiotic composition of OCs (17). Top predators will thus mainly accumulate the most persistent OCs (22-24), although various wildlife species have different biotransformation abilities (25-26). The present study was initiated to examine the influence of cold condensation and global fractionation on the concentrations and compositional patterns of long-range transported OCs in avian marine top predators. The aim was to determine whether an abiotic signal of exposure, e.g., caused by cold condensation and global fractionation, could be found even in a marine avian top predator due to exposure from prey, or whether the OC pattern was determined by biotransformation capabilities only. Since the early 1970s, high levels of PCB and p,p′-dichlorodiphenyldichloroethylene (p,p′-DDE) have been recorded in glaucous gulls (Larus hyperboreus) at Bjørnøya (Bear Island) in the Norwegian Arctic (27-29). If cold condensation and fractionation were VOL. 40, NO. 16, 2006 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 1. Study colonies on the Norwegian Coast; The North Sea (58°10′N, 7°10′E), Norwegian Sea (66°22′N,12°37′E), western Barents Sea (70°20′N,21°24E), eastern Barents Sea (70°22′N,31°10′E), and Bjørnøya (Bear Island: 74°30′N,19°01′E). important for the occurrence of OCs in glaucous gulls at Bjørnøya, higher levels of highly volatile compounds and a shift in relative proportions in accordance with the OCs’ physicochemical properties would be expected in large gulls along the temperate and sub-arctic coast of Norway (Figure 1). Since the glaucous gull only breeds in the Arctic, the great black-backed gull (Larus marinus) at the coast of Norway was chosen for comparison. Glaucous gulls and great blackbacked gulls are both top predators in the marine environment and are closely related taxonomically (30). Blood samples from great black-backed gulls were collected at 58°N, 66°N, and two sites at 70°N along the Norwegian Coast, while glaucous gulls were sampled at two locations at Bjørnøya, 74°N (Figure 1).

Materials and Methods Study Areas. Blood was collected from great black-backed gulls from four different locations along the Norwegian Coast (Figure 1), including the North Sea (58°10′N, 7°10′E; study area is described in Bustnes et al., ref 31), Norwegian Sea (66°22′N, 12°37′E; study area at Sleneset is described in Bustnes et al., ref 31), Western Barents Sea (70°20′N, 21°24E; study area at Loppa is described in Helberg et al., ref 32), and Eastern Barents Sea (70°22′N, 31°10′E; study area at Hornøya described in Furness & Barrett., ref 33). Glaucous gulls were sampled at two locations at Bjørnøya (Bear Island; 74°30′N, 19°01′E); one 100-150 m above sea level (Seabird Cliff) and one close to the sea level (Sea Level); study area described in Bustnes et al. (34). All blood samples were collected in 2001, apart from the North Sea, which was sampled in 2002. All study areas were near other seabird concentrations, either alcid colonies or in colonies with other gulls. 5140

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Samples. A total of 80 great black-backed gulls and 40 glaucous gulls (10 male and 10 females from each site) were caught at their nests during the incubation period, using a nest trap (35). Body mass controlled for head length was used as a measure of body condition (36). A blood sample was taken from the wing (∼10 mL), using a heparinized 20 mL-syringe and a 21 gauge needle, and frozen within 4-5 h. Both the great black-backed gull and the glaucous gull are sexually dimorphic; males are larger than females (30). Sex was determined by using head length (head + bill), the most useful single measurement in discriminating between sexes in both species (35, 37). Chemical Analysis. OC analyses were carried out at the Environmental Toxicology Laboratory at the Norwegian School of Veterinary Science/National Veterinary Institute. All details about the analyses have been described in Andersen et al. (38), including gas chromatographic conditions, temperature program, and quality assurance procedures. Percent recoveries and coefficient of variance of individual OCs in spiked sheep blood varied from 77 to 127 and 0.04 to 14.1, respectively, which are within the acceptable range set by the laboratory quality control system (38). The following PCB-congeners were determined: -28, -52, -47, -74, -66, -101, -99, -110, -149, -118, -153, -105, -138, -187, -183, -128, -156, -157, -180, -170, -196, -189, -194, and -206 (39). Other compounds analyzed were hexachlorobenzene (HCB), the chlordane compound trans-nonachlor and the metabolite oxychlordane, p,p′-DDE, mirex, and β-hexachlorocyclohexane (β-HCH). The analyzed compounds cover a wide range in physicochemical properties, such as octanolwater and octanol-air partition coefficients (KOW and KOA, respectively), and air-water partition coefficient (KAW), that

are of importance for cold condensation and global fractionation, and that also differ in persistence in wildlife. For further information on the physicochemical properties of the different compounds, see Mackay et al. (40). Data Analysis. To evaluate differences among colonies, and co-occurrence, in absolute and standardized OC concentrations (sample-standardized by norm, similar to relative contribution of individual OCs to ΣOC), the data were subjected to direct multivariate ordination analysis (redundancy analysis RDA, CANOCO 4.5 for Windows, ref 41). RDA is similar to the indirect ordination method principal component analysis (PCA), but included explanatory variables as well as response variables. It was, therefore, chosen to analyze if there was a relationship between the OCs and the different colonies. The RDA extracts axes (RA) minimizing the total residual sum of squares among all response variables (here OCs), and assigns scores to the samples that are linear combinations of the OCs as well as significant explanatory variables. Significant variables were chosen by forward automatic selection, using Monte Carlo permutation test with 499 unrestricted permutations and a significance level of p < 0.05. Colony was entered as nominal explanatory variable (dummy variable, Leps and Smilauer, ref 42), whereas the influence of sex and body condition (body mass and size) on the OC variance was removed by including them as covariables. They were included as covariables because earlier studies have shown an influence of these parameters on OC accumulation in glaucous gulls and great black-backed gulls (32, 35). In the RDA of absolute concentrations, OC concentrations were logarithmically transformed to reduce variance heterogeneity and skewness, and lipid content was accounted for as a covariable. The first RA extracted explains the largest part of the response variation among samples, while the second and later RAs explain remaining variance. OCs are presented as arrows pointing to the direction of increasing value, where OCs with short arrows vary little among the samples, whereas long arrows illustrate OCs with high variation among samples that thereby contribute more to the separation of samples in the ordination space. The angles between arrows indicate correlations (or covariance) between OCs; small angle means high correlation, whereas 90° means that the OCs’ occurrence in the samples is not correlated. For a more detailed description of RDA and diagram interpretation, see Ter Braak (43), Van Wijngaarden et al. (44), and Van den Brink and Ter Braak (45).

Results and Discussion Comparison Between the Arctic and the Norwegian Coast. The absolute OC concentrations differed among the colonies (Monte Carlo permutation F g 7.68, p e 0.01), except the Barents Sea east and west colonies which were omitted from the model as they did not improve the fit. The glaucous gulls at Bjørnøya had higher absolute concentrations of most OCs compared to great black-backed gulls on the Norwegian Coast (Monte Carlo permutation F g 31.1, p e 0.01) (Figure 2a). Also the two Bjørnøya colonies differed in OC concentrations, with generally higher absolute concentrations at the Seabird Cliff colony (Monte Carlo permutation F ) 37.0, p ) 0.01), in accordance with previous studies (34). The RDA accounted for 40% of the total variance, of which 50% was explained by colony. Most OCs increased in absolute concentration along redundancy axis (RA) 1 which accounted for 88% of the explained variance (∼ 44% of the total variance), whereas PCB-149 increased along RA2. PCB-149 was the only analyzed compound with decreasing concentration from south to north, when excluding the glaucous gull colonies at Bjørnøya (Figure 2a). However, only 7% of the explained variance (3% of the total variance) was accounted for by RA2.

The OC pattern differed among the colonies (Monte Carlo permutation F g 4.78, p e 0.03), except the western Barents Sea and the Norwegian Sea which were omitted from the model as they did not improve the fit. The pattern did not change in a latitudinal manner when all colonies were considered, but did when only the great black-backed gulls colonies along the Norwegian Coast were considered (Figure 2b). The RDA accounted for 28% of the total variance, of which 29% was explained by colony. RA1 accounted for 71% of explained variance (20% of total variance), whereas RA2 accounted for 20% of the explained variance (6% of total variance). The colonies were separated along RA1 due to high relative contribution of hexa- and hepta-CBs (PCB-183, -138, -187, -149, and -153) in great black-backed gulls from the southernmost colony (North Sea 58°N) compared to the other colonies. The North Sea colony also had lower relative contribution of chlorinated pesticides (mirex, oxychlordane, HCB, p,p′-DDE, β-HCH), and hexa- to nona-CBs (PCB-156, -180, -170, -194, -196, -206, -189) compared to the northernmost colonies (Bjørnøya 74°N) and tri- (PCB-28), tetra(PCB-66, -47), and penta- (PCB-118, -99, -105, -101) CBs compared to the Barents Sea colonies (70°N) (Figure 2b). Thus, great black-backed gulls from the southernmost (North Sea 55°N) and glaucous gulls from the northernmost colonies (Bjørnøya 74°N) showed higher relative values of highchlorinated PCBs (hexa- and hepta-CBs) compared to great black-backed gulls from the mid-colonies along Norwegian coast (Norwegian sea 66°N, Barents Sea east and west 70°N), which had higher relative values of lower-chlorinated PCBs (tri- to penta-CBs). High relative contribution of highchlorinated CBs were separated in two groups: PCB-149, -183, -187, -138, -153 in great black-backed gulls from the North Sea (55°N), and PCB-156, -180, -170, -194, -196, -206, -189) in glaucous gulls from Bjørnøya (74°N). Thus, absolute OC concentrations were higher, and chlorinated pesticides and high chlorinated CBs with high bioaccumulation potential had higher relative contribution to ΣOC in glaucous gulls from Bjørnøya compared to great black-backed gulls from the Norwegian Coast; i.e., no latitudinal pattern gradient was found when all six locations were included, suggesting that cold condensation and fractionation do not explain the high OCs levels in glaucous gulls on Bjørnøya. Differences in OC concentrations in seabirds, including glaucous gulls breeding in nearby locations, have been explained by diet (24, 34), increasing trophic position (24), conditional status (46), and species related differences in metabolism of OC compounds (25, 26). The high concentrations of OCs with high bioaccumulation potential suggest that glaucous gulls have a higher proportion of eggs and chicks of other seabirds in the diet than the great black-backed gulls. The importance of trophic position on OC levels in glaucous gulls is further supported by the fact that OC levels in abiotic environments in the Arctic, such as air and lake sediments, is similar to the levels at the Norwegian mainland (6, 47, 48), which may imply that the exposure from the base of the food web is comparable. Finally, the glaucous gull winters in more northern areas than the great black-backed gull (49), which are probably less polluted. Hence, differences in wintering areas cannot explain the differences in levels between the two species. Overall, this suggests that different dietary exposure and biomagnification account for the elevated levels of various OCs in the glaucous gull when compared to the great black-backed gull at the Norwegian Coast. The Norwegian Coast. When comparing absolute OC concentrations only among great black-backed gull colonies, the colonies differed with generally higher levels of most OCs in the mid-latitudinal colony (Norwegian Sea 66°N) compared to the other colonies (Figure 3A). The southernmost (North Sea 58°N) and northernmost (Barents Sea 70°N) VOL. 40, NO. 16, 2006 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 2. Interrelations among organochlorines in blood samples from great black backed gulls (Larus marinus) and glaucous gulls (Larus hyperboreus) from the Norwegian Coast and Bjørnøya, respectively, represented by the colonies’ mean score (symbols) in the ordination space displayed by redundancy axes (RA) 1 and 2. The latitude of each colony is following its name. Colony was entered as an environmental variable, and the samples score on the RAs is a result of both (A) OC concentrations and colony identity, or (B) OC pattern and colony identity. After fitting covariables, (A) 40% of the total variance was accounted for by the RDA, of which 50% was explained by the colony identity, and (B) 28% of the total variance was accounted for by the RDA, of which 29% was explained by the colony identity. The percentage of explained variance accounted for by the respective RAs are given in parentheses. Only compounds with more than 20% of their variation accounted for are displayed, as the others vary little among samples and do not contribute to the separation of samples. Black symbols are significant colonies, whereas gray symbols did not significantly improve the fit, but they are displayed to illustrate their position in the ordination diagram. samples did not differ in most OCs with high correlation on RA1, but were separated along RA2 due to gradually decreasing PCB-149 concentration with latitude from the North Sea (58°N) to the Norwegian Sea (66°N) and further to the Barents Sea (70°N). The RDA accounted for 28% of the total variance, of which 37% was explained by colony; all 5142

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colonies added significantly to the models (Monte Carlo permutation F g 11.3, p e 0.01). RA1 accounted for 78% of explained variance (29% of total variance), whereas RA2 accounted for 14% of explained variance (5% of total variance). In more details, the Barents Sea and the Norwegian Sea colonies had higher levels of HCB, oxychlordane, and

FIGURE 3. Interrelations among organochlorines in great black backed gull (Larus marinus) blood samples from the different colonies along the Norwegian Coast, represented by the colonies’ mean score (symbols) in the ordination space displayed by redundancy analyses axis (RA) 1 and 2. The latitude of each colony is following its name. Colony was entered as an environmental variable, and the samples score on the RAs is a result of both the (A) OC concentrations and colony identity, or (B) OC pattern and colony identity. After fitting covariables, (A) 28% of the total variance in absolute OC concentrations was accounted for by the RDA, of which 37% was explained by the colony identity, and (B) 28% of the total variance in standardized OC concentrations was accounted for by the RDA, of which 30% was explained by colony identity. The percentage explained variance accounted for by the respective RAs is given in parentheses. Only OCs with more than 20% of their variation accounted for are displayed, as the others vary little among samples, and do not contribute to the separation of samples. low chlorinated PCBs (PCB-28, -101, -74) compared to the southernmost colony (North Sea 58°N), whereas the North Sea and the Norwegian Sea had higher levels of hexa- to

nona-chlorinated PCBs compared to the Barents Sea colonies (Figure 3A). Thus, although there was no gradual change in absolute concentrations of OCs with latitude along the VOL. 40, NO. 16, 2006 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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TABLE 1. Body Mass, Body Size (head and bill length), Percentage Fat in Blood and Residues of Different Organochlorines (ng/g, wet weight) in the blood of great black-backed gulls (Larus marinus) from the Norwegian Coast and glaucous gulls (Larus hyperboreus) from Bjørnøya, Svalbard great black-backed gull North Sea

n latitude

21 58N

glaucous gull

Norwegian Sea

Western Barents Sea

Eastern Barents Sea

Bjørnøya Sea level

Bjørnøya Seabird cliff

20 66N

19 70N

20 70N

20 74N

20 74N

arithmetic mean

SD

arithmetic mean

SD

arithmetic mean

SD

arithmetic mean

SD

arithmetic mean

SD

arithmetic mean

SD

body mass (g) body size (mm) % fat in blood

1.71 142 0.47

0.2 6.3 0.17

1.62 142 0.47

0.2 9.2 0.18

1.54 142 0.42

0.3 7.9 0.23

1.72 141 0.43

0.2 6.3 0.17

1.60 141 0.48

0.2 7.1 0.13

1.63 141 0.51

0.2 6.2 0.23

organochlorines

median

SD

median

SD

median

SD

median

SD

median

SD

median

SD

0.9 0.1 0.3 0.5 11.7 0.5

0.6 0.2 0.6 1.5 28.5 0.8

4.4 0.3 3.7 4.0 37.5 1.4

1.7 0.1 2.0 3.4 27.8 0.7

3.6 0.2 1.7 1.4 18.7 0.8

4.7 0.2 3.4 2.8 34.4 0.8

3.0 0.1 2.0 0.9 11.0 0.4

3.3 0.2 4.9 0.9 25.8 0.9

11.9 0.6 9.7 1.3 70.5 4.5

8.7 1.1 10.9 0.5 49.3 6.2

28.4 1.5 13.4 1.0 107.4 7.1

8.0 0.6 5.7 1.0 49.7 3.7

PCBs PCB-28 PCB-47 PCB-52 PCB-74 PCB-66

.2 0.3 0.1 0.5 0.6

0.3 0.9 0.1 0.9 1.6

0.7 1.0 0.1 1.6 2.0

0.3 0.8 0.1 0.8 1.1

0.5 0.5 0.1 1.5 1.9

0.6 0.5 0.2 1.5 1.7

0.4 0.4 0.1 1.0 1.1

0.4 0.6 0.0 1.2 1.7

0.8 0.8 0.4 2.1 2.1

0.9 1.0 0.3 3.1 3.2

1.6 1.6 0.3 4.3 4.5

0.8 0.8 0.3 1.9 2.4

penta-CBs PCB-101 PCB-99 PCB-118 PCB-105 PCB-110 Hexa-CBs PCB-149 PCB-153 PCB-138 PCB-128 PCB-156 PCB-157

0.1 3.0 5.9 1.5 0.4 0.3 29.6 20.7 2.1 1.1 0.5

0.3 8.4 12.7 2.8 0.7 0.6 71.5 40.5 3.6 3.5 0.7

0.3 6.9 14.2 3.8 0.6 0.4 50.6 34.9 3.3 2.2 0.9

0.5 6.1 9.6 2.1 1.1 0.4 48.5 28.1 2.4 1.9 0.6

0.5 5.2 8.9 3.3 0.6 0.2 31.3 21.4 2.6 2.1 0.7

0.6 4.7 8.6 3.1 0.7 0.2 32.0 21.7 3.4 2.4 0.7

0.3 4.4 7.9 2.3 0.4 0.2 22.6 16.8 3.3 1.8 0.6

0.4 8.3 12.1 3.8 0.2 0.1 59.6 39.1 4.2 5.4 1.5

0.8 12.0 20.5 5.7 1.0 0.2 88.0 47.0 3.1 6.1 1.7

1.7 13.5 26.4 6.3 0.7 0.1 115.6 62.0 3.8 10.6 2.7

1.2 21.5 38.6 11.4 0.8 0.2 155.1 96.3 4.9 11.3 3.0

0.6 12.1 18.6 4.9 1.1 0.1 96.9 57.7 2.8 7.2 1.9

hepta-CBs PCB-187 PCB-183 PCB-180 PCB-170 PCB-189

3.2 1.7 9.3 2.8 0.1

9.8 5.8 30.3 12.5 0.4

5.6 2.7 18.7 5.5 0.3

6.6 2.2 18.9 6.0 0.3

3.8 2.6 11.6 3.9 0.2

3.8 2.6 14.7 4.7 0.3

2.0 1.6 7.5 2.4 0.1

3.2 4.3 18.4 6.0 0.3

4.0 3.0 41.1 11.9 0.5

7.7 6.8 67.7 20.2 1.0

11.0 5.2 66.6 20.0 1.1

5.7 4.3 48.0 14.4 0.7

octa-CBs

PCB-194 PCB-196

1.2 0.8

6.1 3.0

2.8 1.8

2.9 1.8

1.8 1.1

2.6 1.4

1.0 0.7

2.4 1.6

5.4 2.9

11.1 5.6

11.4 5.3

7.0 3.9

nona-CB

PCB-206

0.3

0.7

0.7

0.5

0.4

0.5

0.2

0.3

1.2

2.2

2.0

1.2

pesticides HCB β-HCH oxychlordane trans -nonachlor p,p′ -DDE Mirex tri-CB tetra-CBs

Norwegian Coast, as the highest concentrations of most compounds were found in the mid-colony (Norwegian Sea 66°N), the levels of low chlorinated PCBs, and oxychlordane and HCB were higher in concentration in north than in the south, whereas high-chlorinated PCBs were higher in concentrations in the south than in the north (Figure 3A). This south-north difference between the North Sea (58°N) and the Barents Sea (70°N) is in accordance with differences in physicochemical properties (40), consistent with cold condensation and fractionation theory (4). Moreover, there are three possible explanations for the generally highest OC concentrations at the Norwegian Sea compared to the other colonies, which are all related to elevated exposure through the diet; either (1) the Norwegian Sea great black backed gulls receive contamination from local sources through their diet, (2) they are wintering at some specific site where they are exposed to high levels of pollution, or (3) they are feeding on a higher trophic level. Of these explanations, feeding on a higher trophic level or on contaminated prey in the 5144

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wintering season seem more plausible, as there were no indications of local pollution such as higher occurrence of lower chlorinated PCBs (50). In terms of OC pattern, the southernmost colony (North Sea 58°N) is separated from the other colonies along RA1 due to high relative values of hexa- and hepta-CBs (PCB-149, -187, -138, -183, -153) and low relative values of the chlorinated pesticides mirex, oxychlordane, HCB, and heptato nona-CBs (PCB-180, -170, -194, -196, -206) (Figure 3B). Along RA2, the colonies are separated along a latitudinal gradient, due to decreasing relative values of tri- to pentaCBs (PCB-118, -66, -99, -105, -28, -47, -101) from the Barens Sea colonies (70°N) through the Norwegian Sea (66°N) to the North Sea (58°N) (Figure 3B). The RDA accounted for 28% of the total variance, of which 30% was explained by colony, all colonies added significantly to the models (Monte Carlo permutation F g 7.48, p e 0.01). RA1 accounted for 67% of explained variance (20% of total variance), whereas RA2 accounted for 25% of explained variance (% of total variance).

Most tri- to penta-chlorinated PCB congeners correlated positively among the samples, whereas hexa- and heptachlorinated PCBs showed higher degree of no or negative correlation among the samples (Figure 3B). This was also identified for the pattern-RDA including the glaucous gulls on Bjørnøya (Figure 2B). Unlike for the absolute concentrations, the mid-colony (Norwegian Sea 66°N) conformed to the gradual latitudinal pattern change, consistent with cold condensation and fractionation theory. The high relative importance of the hepta-, octa- and nona-CBs in the Norwegian Sea compared to the other three locations, in combination with the high concentrations, support that Norwegian Sea great black-backed gulls feed on a higher trophic position than at the other colonies. This study thus suggests that different processes may explain the pattern of pollution in large gulls in the Arctic and in temperate and sub-arctic areas. The high OC levels repeatedly found in glaucous gulls are likely due to feeding on a higher trophic position than great black-backed gulls. The latter species seems to have a more uniform contamination exposure through their diet, with the exception of the mid-latitudinal colony, and a significant part of the differences in OC pattern among gulls in different regions can thus be explained by different OC composition in the local environments, due to cold condensation and fractionation. These findings suggest that spatial distribution of compounds can be investigated in marine avian top predators such as large gulls, even if both biomagnification and biotransformation influence the OC pattern and absolute concentrations.

Acknowledgments We are grateful to Ø. O. Miland, M. Fjeld, J. A. Henden, Ø. Varpe, M. Helberg, and K.O. Kristiansen for valuable help during field work, and Anuschka Polder and her team for conducting the laboratory analyses. Three anonymous reviewers provided comments that greatly improved an earlier draft of the manuscript. The study was funded by the Norwegian Research Council (project no. 141443/S30)

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Received for review March 17, 2006. Revised manuscript received June 9, 2006. Accepted June 14, 2006. ES060628V