Environ. Sci. Technol. 2000, 34, 4878-4886
Concentrations of Organochlorine Substances in Relation to Fish Size and Trophic Position: A Study on Perch (Perca fluviatilis L.) A N D E R S O L S S O N , * ,† K A R L I S V A L T E R S , †,‡ A N D S V E N B U R R E A U §,| Department of Environmental Chemistry, Department of Zoology, and Institute of Applied Environmental Research, Stockholm University, S-106 91 Stockholm, Sweden, and Faculty of Geographical and Earth Sciences, University of Latvia, Raina Boulevard 19, LV-1586 Riga, Latvia
The aim of this study was to evaluate the importance of trophic position as a determinant of the concentrations of organochlorine substances (OCS) in fish. Perch (Perca fluvatilis) was selected since the species increases in trophic level over the course of its lifetime. The trophic position was characterized by stable isotope analysis of nitrogen and gut content. Perch (130 individuals) of different lengths and of both sexes were analyzed for polychlorinated biphenyls and chlorinated pesticides. There were no pronounced differences in the OCS concentrations between the perch sexes. Perch up to a length of 20 cm did not show any increase in OCS concentrations with increased length, despite a pronounced increase in trophic position. Thus, the trophic position cannot explain the observed concentrations of OCS in smaller perch. In perch >20 cm, the levels of all analytes increased with length or trophic position. The magnitude of the concentration increase was positively correlated with the lipophilicity of the substance. The increase of OCS concentrations in the large perch is explained by physiological changes leading to slower OCS clearance or by such changes in combination with higher OCS intake due to higher trophic position.
Introduction In a food web, biomagnification is defined as a dietdependent increase of contaminant concentrations, above the concentrations expected from equilibrium partitioning with the surrounding water (bioconcentration). Biomagnification of lipophilic organochlorine substances (OCS) has been shown to occur in aquatic food chains (1-3). The dynamics of OCS in food webs depend on the physicochemical properties of these chemicals, such as lipophilicity, in combination with biological factors of the animals under study. For example, the amount of lipid in organisms increases with the trophic level in many food webs. The partitioning of OCS into this increased lipid amount accounts for a major part of the proportional increases in wet weight * Corresponding author phone: +46 8 16 3781; fax: +46 8 152561; e-mail:
[email protected]. † Department of Environmental Chemistry, Stockholm University. ‡ University of Latvia. § Department of Zoology, Stockholm University. | Institute of Applied Environmental Research, Stockholm University. 4878
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concentration and trophic level (2-5). Several studies on food chains have however shown significant biomagnification of OCS even when the concentrations are lipid-normalized (1-4, 6). Models have been developed to describe the observed biomagnification in food chains (7-9). However, these models have rarely taken into consideration the seasonal variations within species. It is well-known that, for example, spawning among fish species results in large variations of OCS concentrations (10-12). In monitoring studies of OCS in biota, the dependence of the OCS concentration on physiological and ecological parameters that change with time is of importance for planning sampling strategies and for interpretation of the results. Biomagnification has been reported in food chains with different organisms representing different trophic levels. However, a rarely asked question is how OCS concentrations are affected in a species that changes trophic level over its lifetime. Rasmussen et al. (3) showed that a longer food chain significantly increased the PCB concentration in lake trout (Salvelinus namaycush), even after comparison of lipid-normalized concentrations. In contrast, lake trout from Lake Ontario did not show any correlation between PCB concentrations and their trophic level (1). Similarly, in the piscivorous pike (Esox lucius), concentrations of OCS are reported to be unaffected by size (13) and in some cases to decrease with age (14). These contradictory results indicate that trophic position may not be the dominating parameter to explain OCS concentrations in fish under natural conditions. A problem in studies on food web dynamics is the difficulty in ascribing and ranking species to a certain trophic level. Complex predator-prey relationships often exist within food webs, including the involvement of omnivorous species that complicate the concept of discrete trophic levels. Analysis of stable nitrogen isotopes has been used as a continuous, integrated measure of the trophic level of an organism. The method is based on the phenomenon that 15N is successively enriched relative to 14N in food chains (15-17). The enrichment of a stable isotope is determined by comparison to the standard composition of the chosen element. The deviation in the isotopic composition in a sample relative to the standard is expressed as a δ value (cf. Materials and Methods). The enrichment of the 15N isotope relative to 14N or δ15N has been reported to be approximately 3.4‰ for every traditional trophic level (16, 17). Perch (Perca fluviatilis) is a common and widespread species of fish in fresh and brackish waters in the Eurasian part of the Northern Hemisphere. The food preferences of perch change over their lifetime depending on the size of the individual. Perch of different lengths represent different trophic levels ranging from planktivorous to piscivorous (18, 19). Perch was investigated in this study to determine how biological parameters such as age, length, sex, and different food preferences (trophic level) affect the concentrations of PCB congeners and pesticides. The trophic levels of the individual perch were determined by stable nitrogen isotope ratios and gut content analysis.
Materials and Methods Area Description. Lake Burtnieku is located in northern Latvia (57°45′ N, 25°15′ E). The surface area is 38.4 km2, and the mean depth is 2.2 m (maximum depth of 3.3 m). The catchment area of the lake is 2200 km2 (20). Ten small rivers and streams flow into the lake, but there is only one outflow: into the river Salaca in the northwest of the lake. The lake has a simple topography, no islands, and a uniform depth, 10.1021/es991400t CCC: $19.00
2000 American Chemical Society Published on Web 10/21/2000
TABLE 1. Results of the Gut Content Analysis of All Perch Sampleda guts containing length group
mean length, cm
30 cm) at this location. Therefore, additional fishing was carried out in the central part of the lake, approximately 1 km north of the main fishing location but still distant from the main inflows and the outflow. The perch were placed in a freezer immediately after the catch and within 20 h examined with respect to length, weight, sex, and gut content. After inspection, each fish was packed in aluminum foil, placed in a plastic bag, and immediately frozen at -20 °C for later sample preparation. The left opercula were used for age determination (21). Gut Content Analysis. The gut contents of all collected perch were identified and classified into four major groups: zooplankton, benthic organisms, small fish (50 mm). Small fish were predominantly young of the year fry. For a certain length interval, food preferences of perch (cf. Table 1) were calculated as the ratio between guts containing a specific item and the number of guts containing food items. Sample Selection and Preparation. The perch were grouped according to sex and length (cf. Table 1). Ten fish (or all when less than 10 were available) were randomly selected from each length group for contaminant analysis. All fish longer than 20 cm were analyzed. In total, 130 perch were individually analyzed in respect to OCS concentrations and δ15N. After removal of the skin, approximately 10 g of muscle tissue was dissected from each fish for OCS analysis. For fish smaller than 12 cm, muscle tissue was taken as much as possible. A section along the middle line from the gills to the dorsal fin was taken from each fish for stable isotope analysis. Chemicals. CB-28 [CB numbers are according to Ballschmiter et al. (22)], CB-52, CB-101, CB-105, CB-118, CB138, CB-153, CB-180, and CB-189 as well as 2,2-bis(4-fluorophenyl)-1,1,1-trichloroethane (DFDT) had been previously synthesized at the Department of Environmental Chemistry (23-25). A commercial PCB mixture, Clophen A50, was obtained from Bayer AG (Germany). The pesticide reference standards 2,2-bis(4-chlorophenyl)-1,1-dichloroethene (DDE), 2,2-bis(4-chlorophenyl)-1,1-dichloroethane (DDD), R- and γ-isomers of hexachlorocyclohexane (R-HCH and γ-HCH),
hexachlorobenzene (HCB), and trans-nonachlor were purchased from Dr. Ehrenstorfer GmbH (Augsburg, Germany). All solvents were of the highest purity commercially available. Acetone and n-hexane were purchased from Fisher Scientific Ltd. (Loughborough, U.K.), and methyl tert-butyl ether (MTBE) was from Rathburn Chemicals Ltd. (Walkerburn, Scotland). Sulfuric acid (98% p.a.) from Merck (Darmstadt, Germany) was used. Silica gel, 60-200 mesh, from Macherey-Nagel (Du ¨ ren, Germany) was activated at 280 °C for 24 h before use. Contaminant Analysis. The samples were homogenized with an IKA T25 homogenizer (Labassco AB, Partille, Sweden) in n-hexane:acetone (2:5) and extracted with n-hexane:MTBE (9:1) according to Jensen et al. (26). The lipid amount was then determined gravimetrically, and the surrogate standard (CB-189) was added. The samples were treated with concentrated sulfuric acid to remove the bulk of lipids (26). Additional cleanup on two columns was necessary to obtain sufficiently clean samples. The two columns were prepared in Pasteur pipets; each contained 0.5 g of silica gel impregnated with sulfuric acid (2:1, w:w) and n-hexane (8 mL) was used as the mobile phase. The solvent volume was reduced to 0.5 mL, and an injection standard (DFDT) was added prior to analysis. A Varian 3400 gas chromatograph equipped with a model 8200 autosampler and an electron capture detector (ECD) was used for GC analysis. The separation was performed on a DB-5 capillary column (30 m, 0.25 mm i.d., 0.25 µm film thickness) from J&W Scientific (Folsom, CA). The injector and detector temperatures were 250 and 360 °C, respectively. The temperature program was 80 °C (2 min) followed by a 7 °C/min ramping to 160 °C, and thereafter ramped by 10 °C/min to 300 °C and held there for 12 min. Authentic standards were used to quantify eight PCB congeners (cf. above), DDE, DDD, R- and γ-HCHs, HCB, and trans-nonachlor. The technical PCB mixture, Clophen A50, was used as a reference standard to quantify total PCB (∑PCB). The PCB peaks in the samples were quantified in relation to those in Clophen A50, with the relative PCB congener composition as reported by Schultz et al. (27). The surrogate standard CB-189 served as an internal standard for quantification. Procedural blanks were analyzed for every 10 samples. The relative recovery of the surrogate standard (CB189) was calculated for each sample. The overall recovery of the surrogate standard in the samples was 83% with a standard deviation of 7.1% (n ) 130). To check the reproducibility and maintain stable quantification conditions, a set of external standards was injected for each 10 samples. The external standards run on the GC between series were quantified against each other to control the reproducibility of the analysis. The computer program ELDS Pro (ChromaVOL. 34, NO. 23, 2000 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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TABLE 2. Biological Parameters and Nitrogen Isotope Composition (δ15N) of the Perch That Were Analyzed for Organochlorine Substancesa length interval (cm)
n
length (cm)
J
7.0-9.9
4
7.5 7.2-7.9
F2
10.0-11.9
11
F3
12.0-13.9
10
F4
14.0-15.9
10
F5
16.0-17.9
9
F6
18.0-19.9
10
F7
20.0-21.9
10
F8
22.0-23.9
4
F9
24.0-29.9
3
F10
30.0-38.5
16
11.2 11.0-11.5 13.0 12.6-13.4 15.0 14.6-15.3 17.1 16.7-17.6 18.9 18.7-19.1 20.8 20.4-21.3 22.4 22.2-22.5 26.8 23.9-30.1 35.1 34.1-36.2
Females 16 15-17 25 22-29 40 36-44 63 59-68 82 78-87 110 101-120 144 127-163 262 214-322 657 600-718
M1 M2
7.0-9.9 10.0-11.9
1 10
M3
12.0-13.9
10
M4
14.0-15.9
10
M5
16.0-17.9
8
9.4 11.3 11.0-11.6 12.9 12.5-13.3 14.9 14.5-15.3 17.0 16.7-17.4 19.8 20.0 22.1 24.1
Males 10 17 16-18 26 24-28 39 36-42 62 57-67 88 110 125 167
group
M6 M7 M8 M9
1 1 1 1
weight (g) Juveniles 5
ageb (yr)
lipid (%)
δ15N (‰)
0
1.05 1.01-1.10
12.5 12.1-12.8
1
0.88 0.81-0.95 0.87 0.80-0.95 0.68 0.63-0.74 0.76 0.73-0.79 0.69 0.63-0.76 0.76 0.72-0.81 0.60 0.58-0.61 0.48 0.42-0.56 0.74 0.66-0.83
13.5 13.2-13.8 14.0 13.8-14.1 13.9 13.6-14.2 15.0 14.7-15.3 14.9 14.4-15.4 15.6 15.4-15.8 15.5 15.3-15.8 17.5 17.0-18.1 17.3 16.9-17.7
0.88 0.77 0.71-0.83 1.00 0.94-1.07 0.73 0.68-0.78 0.65 0.61-0.70 0.71 0.53 0.73 0.67
13.7 13.6c 13.4-13.9 14.2 13.9-14.5 14.2 13.6-14.8 14.7 14.2-15.2 16.7 15.1 15.1 17.0
1.6 1-2 2.1 2-4 3.4 2-5 3.6 2-5 4.0 3-5 4.7 4-6 5.3 5-6 7.6 6-10 1 1 1.9 1-4 3.3 3-5 5.0 3-7 2 7 d 5
a Geometric means and 95% confidence intervals for the respective length groups and both sexes are presented. b Since perch were sampled in October, the actual age of the fish was about half a year higher than the respective numbers of full years. Ranges instead of 95% confidence intervals are shown for age. c n ) 9; for one sample from this length group the isotope ratios were not determined. d Age of the individual was not possible to determine.
tography Data System, Svartsjo¨, Sweden) was used for the GC data acquisition and quantification. Isotope Analysis. For determination of the isotopic composition of nitrogen, samples of raw muscle tissue were dried at 60 °C for more than 48 h and powdered. Approximately 1 mg of the sample was weighed in a tin cup and combusted in the elemental analyzer. The samples were analyzed for δ15N using an elemental analyzer (EA 1108 CHNS-O, Carlo Erba, Milan, Italy) connected to an isotopic ratio mass spectrometer (Optima, Micromass, Manchester, U.K.). Samples and standards were run in continuous flow with a standard deviation of 0.2‰ among replicate standard samples. Nitrogen isotopic compositions in the samples are reported as deviations (in ‰) from the nitrogen isotopic composition in air and are calculated according to the following equation from ref 15:
δ15N ) [(15N/14N)sample/(15N/14N)air - 1] × 1000 Statistical Analysis. All concentrations were log-normal transformed prior to regression analysis. Comparison of variances, slopes, and elevations between linear regression lines were accomplished by ANOVA (28). The test for differences in elevation was made when there was no difference in regression slopes of y versus x between groups. A difference in elevation is when there is a significant difference in the adjusted means of y values between groups. 4880
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Results Growth Rate. Since the sampling was carried out approximately 0.5 yr after spawning, the age of each perch in this study was assumed to be 0.5 yr more than the number of years estimated from the opercula. The correlation between length and age was significantly different (p < 0.001) between the sexes within the length interval where fish of both sexes were present (10-18 cm, cf. Table 2), with females growing faster than males (females: length ) 5.17 × ln(age) + 9.68; males: length ) 3.49 × ln(age) + 10.0). Thus, at a certain age the females are in general larger than the males. Le Cren (29) has shown that, for perch, log-normal transformed weight and length data are highly correlated. This was the case also in this study with r 2 > 0.96 for the following regression lines. The regression lines for weight versus length for the females and males (10-18 cm) were ln(weight) ) 3.16 × ln(length) - 4.88 and ln(weight) ) 3.04 × ln(length) - 4.53, respectively. The equation for all females was ln(weight) ) 3.23 × ln(length) - 5.07. Gut Content. The results of gut content analysis in fish of different length are given in Table 1. The gut contents of 241 perch were examined, and 25% of the guts were empty. Zooplankton and Chironomideae larvae were the major items in perch smaller than 12 cm. Fish was the dominant item in perch larger than 16 cm. The food preferences in the length classes between 12 and 16 cm were mixed and contained a variety of benthic organisms (Table 1). The most common
FIGURE 1. Nitrogen isotope composition in females and males versus length (A) and age (B) of the perch sampled at Lake Burtnieku. benthic item was Chironomideae larvae followed by different species of leeches, mainly Herpobdella octaculata. Leeches were present in 38% of the guts containing benthic species. Other common items were Hydropsyche sp. (24%) and 15% each of other dragonfly larvae, Corixa sp. and Asellus sp. δ15N in Relation to Length, Age, and Sex. δ15N data and biological parameters for the different sex and length groups are given in Table 2. The δ15N values found in the perch ranged from 12.0 to 18.8‰ and were correlated with size. The correlation between δ15N and ln(length) was not significantly different between the sexes (p > 0.1) (Figure 1A). For males and females together, a logarithmic increase in δ15N with length (length ) 3.35 × ln(δ15N) + 5.35, r 2 ) 0.77, p < 0.001) was observed with the fastest increase occurring up to approximately 20 cm (Figure 2A). However, there was a significant difference between sexes for the δ15N versus age (p < 0.001) (Figure 1B). OCS Concentrations in Relation to Length, Sex, Age, and Trophic Position. The geometric mean concentrations and 95% CI of eight PCB congeners, ∑PCB, DDE, DDD, R-HCH, γ-HCH, HCB, and trans-nonachlor within each length class and of each sex are given in Table 3. Within the length interval of 10-18 cm, a sufficient number of fish of both sexes (40 females and 38 males) were available for statistical investigation of possible sexual differences in OCS concentrations. This was determined by comparing regression lines for log-normal concentrations versus length. There
was a significant difference between sexes for about half of the compounds with respect to variance, slope, or elevation but with no systematic pattern as a function of lipophilicity or type of substance. A representative example, the ∑PCB concentrations in relation to length for both sexes, is shown in Figure 3. No significant increase or decrease of ∑PCB levels in relation to length for either of the sexes was observed. However, there was a significant difference in the elevation of concentrations, the females being slightly lower in ∑PCB than the males. As can be seen in Figure 3, the difference is subtle and is due to a few females in the upper part of the length interval. We chose to neglect the differences between sexes and use all the analyzed perch in all further correlations. The concentrations of CB-138 and DDE are plotted versus length for all individual perch as presented in Figure 2B,C and compared with δ15N values versus length (Figure 2A). The CB-138 and DDE concentrations do not increase up to a length within 20 and 25 cm but increase thereafter. For smaller perch (20 cm (A) and δ15N >15‰ (B). and co-workers (40) showed that the initial decrease of CB153 concentrations was from approximately 17 to 8 ng/g in only 20 days, but the authors reported a half-time of 70 days. In another study on perch using constant water exchange, the elimination of CB-153 gave an estimated half-time of approximately 20 days (33). Seasonal concentration fluctuations of OCS for roach and perch in natural conditions indicated a PCB half-time of approximately 1 month (11, 12). Hence, in several studies on natural or artificial flow-through systems, the reported half-times of the most strongly retained PCB congeners in fish are less than 1 month. Thus, a possible explanation for the lack of an OCS concentration increase in perch smaller than 20 cm is that the rate of elimination is large enough to compensate for food intake regardless of diet. Increase of OCS Concentrations in Large Perch. There was an increase in the concentrations of all quantified OCS in perch larger than 20-25 cm (Figures 2 and 4). The potency of the concentration increase (BT and BL values) of different compounds was highly dependent on the lipophilicity of the substance (Figure 5). The same pattern was observed for the increase in relation to both length and δ15N. The more lipophilic the PCB congener, the more pronounced the tendency of reaching higher concentrations in large perch.
DDE deviated from the general trend and had a greater increase in potency than could be expected from its lipophilicity. Length and δ15N are correlated. It is therefore hard to distinguish which parameter causes the OCS concentration increase illustrated by the BT and BL values (Figure 4). The BL value, however, described more of the variation around the regression line than the corresponding BT value for any of the analyzed substances. Furthermore, in Figure 4 the residuals around the regression lines indicate that there is not a linear increase of CB-180 with length in perch >20 cm. The increase in concentration of CB-180 seems to be strongest in the beginning of the interval. The uncertainty about the best description of the increase is due to the limited number of samples between 25 and 30 cm. In the large perch (>20 cm), the gut content analysis showed smaller variation in food composition (Table 1), and only a marginal increase in the δ15N values was observed (Figure 2A). Since there is no increase in OCS concentrations with trophic status in perch below 20 cm, trophic status as the major determinant of the contaminant concentrations above 25 cm is questionable. If trophic position has any effect on OCS concentrations in large perch, there must be a critical threshold of OCS intake under which gill clearance is fast enough to compensate for changes in the dietary intake. Such a threshold could, for example, be the result of the successively decreased gill area to body mass ratio (43). It thus seems likely that physiological changes related to size, either alone or in combination with trophic position, are responsible for the OCS concentration increase in large perch. Several physiological factors have been suggested to affect biomagnification (7, 8, 35). Some have been reported to change with size in perch, such as gill area to body mass ratio (43) and the efficiency of converting food into body mass (44). Sijm et al. (35) suggested that “exchange surface and lipid content are the main fish properties that determine bioconcentration kinetics”. A reported factor with a dependence on length, strikingly similar to the OCS concentration dependence, is the deposit of mesenteric adipose tissue in perch. Data on the amount of mesenteric adipose tissues in perch are available from two locations on the Swedish coast (Figure 6) (45). This mesenteric adipose tissue in perch is deposited around the intestines and is not affecting the lipid amount in the muscle tissue. The large perch deposit this lipid amount during the summer months, and the lipids are probablyused in the development of the growing gonads in the autumn and winter (45). VOL. 34, NO. 23, 2000 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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The rate of the elimination of contaminants via the gills is dependent on (i) the circulation time of the OCS within the fish, (ii) the fugacity gradient of the contaminants over the gills, and (iii) the transfer efficiency over the gills. The concentrations of OCS in a fish with more fat but with the same gill surface would have a longer time to reach equilibrium. The intake of OCS via food is what creates the fugacity gradient between the fish and the water (8). The food intake in perch is however not a continuous input, as shown in our study by the number of perch with empty guts (Table 1). This results in assimilation and elimination periods of OCS in the fish (41). Between feeding events, a longer time to reach equilibrium in a fat fish might lead to OCS concentrations that are not reduced to the same steadystate level as in a leaner fish. Therefore, a size-associated increase in mesenteric adipose lipid amount in large perch could be a plausible cause of the observed OCS concentration increases in fish above 20 cm. Comparison with Other Studies. Some studies on fish have pointed out lack of trophic-enriched OCS concentrations despite obvious increase in trophic position, e.g., in lake trout from Lake Ontario (1) or in pike from the Swedish coast (13). Similarly, perch and roach collected from the same location were shown to contain similar concentrations of lipidnormalized PCB and DDE (11). This is despite the fact that the roach is partly herbivorous (44) and, therefore, belongs to a lower trophic level than perch. In studies showing biomagnification within food webs, there has also been an associated increase in lipid amount in the investigated organisms (1-4). Thus, in those cases there might not be the increased trophic position that has resulted in higher concentrations but an increased lipid pool to gill surface ratio. The present results do not support models using trophic position as the major determinant of OCS concentrations in aquatic organisms. The OCS concentrations in small perch (20 cm, the OCS concentrations increase and the extent of increase is positively correlated with lipophilicities of the substances. The discrepancy between small and large perch can be explained in one of two ways: (i) growth-dependent physiological factors (and not trophic position) cause the increase in OCS concentration in large perch or (ii) under a certain OCS input threshold (i.e., in small perch), the gill clearance counterbalance increased OCS intake. One growth-dependent factor affecting the OCS concentrations could be the increase of mesenteric adipose tissue with fish size, changing the lipid pool to gill surface ratio in the growing perch.
Acknowledgments We thank Eriks Aleksejevs, Roberts Silins, and others from the Latvian Fisheries Research Institute, Riga, Latvia, for their invaluable help in sampling. We are also grateful for the help of Peter Kara˚s and Olof Sandstro¨m of the Swedish Board of Fisheries and Janis Ozerinskis and Dzintars Vitols of the village of Burtnieki. A° ke Bergman and Mats Olsson are acknowledged for their fruitful comments on the manuscript.
Literature Cited (1) Kiriluk, R. M.; Servos, M. R.; Whittle, D. M.; Cabana, G.; Rasmussen, J. B. Can. J. Fish. Aquat. Sci. 1995, 52, 2660-2674. (2) Kucklick, J. R.; Harvey, H. R.; Ostrom, P. H.; Ostrom, N. E.; Baker, J. E. Environ. Toxicol. Chem. 1996, 15, 1388-1400. (3) Rasmussen, J. B.; Rowan, D. J.; Lean, D. R. S.; Carey, J. H. Can. J. Fish. Aquat. Sci. 1990, 47, 2030-2038. (4) Kucklick, J. R.; Baker, J. E. Environ. Sci. Technol. 1998, 32, 11921198. (5) Leblanc, G. A. Environ. Sci. Technol. 1995, 29, 154-160. (6) Kidd, K. A.; Schindler, D. W.; Muir, D. C. G.; Lockhart, W. L.; Hesslein, R. H. Science 1995, 269, 240-242.
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Received for review December 16, 1999. Revised manuscript received June 9, 2000. Accepted August 28, 2000. ES991400T
