USGS - Pesticide National Synthesis Project Pesticides Report

Reconnaissance of 17ß-Estradiol, 11-Ketotestosterone, Vitellogenin, and Gonad Histopathology in Common Carp of United States Streams: Potential for Contaminant-Induced Endocrine Disruption

By Steven L. Goodbred, Robert J. Gilliom, Timothy S. Gross, Nancy P. Denslow, Wade L. Bryant, and Trenton R. Schoeb

U.S. Geological Survey Open-File Report 96-627

METHODS

The study focuses on measurements of bio-markers for male and female adults of common carp (Cyprinus carpio), hereafter referred to as carp, an omnivore that is widely distributed and has been used in other endocrine-disruption studies. Site selection was based on availability of carp and on attaining broad geographic coverage and a representative range of land use and contaminant conditions. Six hundred and forty-seven carp were sampled during 1994 from 25 sites that represent varying degrees of contamination within 11 NAWQA study units (fig. 1). The sampling sites span a wide range of environmental and land-use settings (table 1) that occur in substantial portions of the nation. Land-use calculations were derived from land use- and landcover digital data in the Geographic Information Retrieval and Analysis System (GIRAS), which are organized by 1:250,000 or 1:100,000-scale quadrangle maps (U.S. Geological Survey, 1990).

Fish Collection, Plasma Sampling, and Age Determination

All fish were sampled with pulsed DC electro-shocking between August 29 and December 14, 1994, which is a postspawn period when gonadal recrudescence occurs (Down and others, 1990). Table 2 summarizes the characteristics of fish sampled. Fish were kept alive in a holding net or a live car until processed, which was usually less than 2 hours. The objective was to sample 10--15 fish of each sex at each site, but this was not always obtained. To ensure that adult fish were sampled, the target minimum total lengths were set at 300 mm for males and 375 mm for females (Panek, 1987), and almost all fish sampled met these criteria. Fish were weighed to the nearest 0.1 g and measured to the nearest millimeter. Fish scales were collected and external anomalies were noted (Meador and others, 1993). Blood was collected from the caudal vein using a 3 or 5 cc syringe and 20-gauge 1.5 in. (3.8 cm) needle. The sample then was transferred to a heparinized 5 mL vacutainer, chilled on wet ice, and centrifuged in the field for 10 minutes at 1000 x g (where the constant g is acceleration due to gravity). Plasma was pipetted into 2 mL cryotubes, immediately frozen on dry ice, and shipped on dry ice using overnight mail to the laboratory at the University of Florida's Biotechnologies for the Ecological, Evolutionary, and Conservation Sciences Program. All samples were stored at -80°C until analyzed.

Ages were determined from scales taken above the lateral line and slightly anterior to the middle of the fish using methods described in Jearld (1983). The ages of some fish could not be determined because regeneration caused scales to be unreadable. Scales from 10 percent of fish at each site were later reaged to assess variability, with at least 90 percent agreement between measurements.

Table 1

Table 2
Table 2

Biomarkers

Analysis of Sex Steroid Hormones

Plasma samples from carp were analyzed for 17ß-estradiol, 11-ketotestosterone, and testosterone using radioimmunoassay (RIA) procedures. Methods are described below for 17ß-estradiol and 11-ketotestosterone, which were used in data analysis. The method for testosterone is similar. Testosterone was not used in data analysis because it was closely correlated with 11-ketotestosterone (R²=0.90 for males and 0.81 for females), which is more important for spermatogenesis in males. Samples (50 µL) were extracted twice with 5 mL diethyl ether prior to RIA analysis. Each sample was analyzed in duplicate for both 17ß-estradiol and 11-ketotestosterone and corrected for extraction efficiencies of 92 ± 2.8 percent and 86 ± 3.3 percent, respectively. Standard curves were prepared in buffer with known amounts of radioinert 17ß-estradiol or 11-ketotestosterone (1, 5, 10, 25, 50, 100, 250, 500, and 1,000 pg). The minimum concentration detectable was 6.4 pg/mL for 17ß-estradiol and 8.1 pg/mL for 11-ketotestosterone.

Cross-reactivities of 17ß-estradiol antiserum (produced and characterized by Dr. T.S. Gross, University of Florida) with other steroids were as follows: 11.2 percent for estrone, 1.7 percent for estriol, less than 1.0 percent for 17a-estradiol and androstenedione, and less than 0.1 percent for all other steroids examined. Cross-reactivities of the 11-ketotestosterone antiserum (also produced and characterized by Dr. Gross) with other steroids were, 9.7 percent for testosterone, 3.7 percent for a-dihydrotestosterone, less than 1.0 percent for androstenedione, and less than 0.1 percent for all other steroids examined. A pooled sample (approximately 275 pg of 17ß-estradiol/mL and 220 pg 11-ketotestosterone/mL) was assayed serially in 10, 20, 30, 40, and 50 µL volumes (final volume of 50 µL with charcoalstripped plasma). The resulting inhibition curves were parallel to the respective standard curve, and the tests for homogeneity of regression indicated the curves did not differ.

Further characterization of the assays involved measurement of known amounts (1, 2, 5, 10, 25, 50, 100, 250, and 500 pg) of 17ß-estradiol or 11-ketotestosterone in 50 µL of charcoalstripped plasma. Values of R² for correlations between actual and measured amounts were 0.93 for 17ß-estradiol and 0.88 for 11-ketotestosterone. Interassay and intra-assay coefficients of variation were 7.3 and 9.5 percent, respectively, for plasma 17ß-estradiol; and 9.1 and 8.7 percent, respectively, for plasma 11-ketotestosterone.

Analysis of Vitellogenin

Vitellogenin concentrations in plasma of carp were assayed and quantified by capture ELISA (Enzyme-Linked Immunosorbent Assay) as previously described (Folmar and others, 1996) and summarized below. Initially, vitellogenin from carp was purified by chromatography, its protein concentration was determined by the Bradford assay (Peterson, 1993), and it was used as a standard. The monoclonal antibody, Mab HL 1147 2D3-3A9 (produced by Hybridoma facility, University of Florida and characterized by Dr. N.S. Denslow) was used in the ELISA assay. This antibody reacts specifically, and with high affinity, to carp vitellogenin and not with other plasma proteins.

Purified antibody was diluted to 10 µg/mL in phosphate-buffer saline and coated onto 96well microtitre plates (50 µg/well), and stored overnight at 4°C. Plates then were washed with tris-buffered saline Tween (TBST), blocked with 360 µL per well of 0.1 percent bovine serum albumin in TBST for 2 hours at room temperature, and thoroughly washed again three times with TBST. Plasma samples were diluted from 1:500 to 1:5,000 in 0.1 percent bovine serum albumin in TBST and 50 µL was added in duplicate to microtitre plate wells and incubated overnight.

Standard curves were constructed by adding serial dilutions of purified carp vitellogenin (0.0001 mg/mL to 0.002 mg/mL) to male control plasma and processed the same way as samples. Male control plasma was made from a pool of plasma from fish collected at an uncontaminated site, which was shown by Western Blot assay to have no vitellogenin. The next day plates were washed with TBST, incubated with 50 uL per well rabbit anti-vitellogenin polyclonal antibody OF114 (produced and characterized by Dr. N.S. Denslow, University of Florida), diluted to 1:500, and incubated for 2 hours at room temperature. This discloses the vitellogenin captured by the monoclonal antibody in the first step. The polyclonal antibody was in turn disclosed by a goat antirabbit immunoglobulin class G, which was diluted 1:1,000, linked to alkaline phosphatase, and incubated for 2 hours at room temperature.

After a final series of washes with TBST, 100 µL of p-nitro phenyl phosphate in carbonate buffer (pH 9.6) was added to each well and incubated for 30 minutes. The intensity of yellow color that developed was quantified at 405 nm with an automated ELISA reader. Vitellogenin concentrations were calculated from standard curves after subtracting the small value (around 0.2 A_{405 nm}) of a nonspecific color reaction with male control plasma.

The ELISA assay used in this study can detect between 10 and 100 ng of vitellogenin per well, resulting in a sensitivity of about 0.001 mg/mL. Each ELISA assay included a positive control, which was plasma with a known vitellogenin concentration, to test for interassay and intra-assay variation. The coefficient of variation was calculated for each duplicate sample and, if it exceeded 10 percent, samples were rerun. Standard curves fit by linear regression were used to calculate vitellogenin concentration, with R² values usually between 0.95 and 0.99.

Histopathology

Samples of male and female gonads were taken after blood had been sampled, fixed in the field with Bouins' Solution, and transferred to 100-percent ethanol in the laboratory prior to processing. Testes were cut longitudinally and ovaries were cut transversely. Samples were embedded in paraffin, sectioned to 5 µm, and stained with hematoxylin and eosin for histological evaluation. All tissue slides were evaluated by a histopathologist for anomalies.

Gonads of female fish were classified according to four stages of sexual maturation, based on evaluation of histological slides (fig. 2A,B,C,D). Ovaries containing mostly perinucleolar oocytes at various stages of previtellogenic growth were classified as undeveloped (stage 0). Ovaries showing a mixture of both perinucleolar and cortical alveoli oocytes were classified as previtellogenic (stage 1). Ovaries classified as early vitellogenic (stage 2) had some vitellogenic oocytes of various sizes and development, with few to moderate numbers of vitelline granules, and no (or only a few) fully developed oocytes. The latest stage of sexual development for females, classified as late vitellogenic (stage 3), had ovaries in which most oocytes were at or near maximum size and contained numerous, densely packed vitelline granules.

Male gonads were classified according to three stages of sexual maturation (fig. 2E,F,G). Testes that were classified as early spermatogenic (stage 1) had thick germinal epithelium, with diffuse pronounced proliteration and maturation of spermatozoa. Mid-spermatogenic (stage 2) testes had germinal epithelium of moderate thickness, with diffuse moderate proliferation and maturation of sperm. Testes classified as late spermatogenic (stage 3) had mostly thin germinal epithelium, with only scattered spermatogenic activity characteristic of full-grown testes and the latest stage of maturity.

Analysis of Hormone and Vitellogenin Data

Values for 17ß-estradiol, 11-ketotestosterone, and 17ß-estradiol/11-ketotestosterone (E₂/11-KT) in males and females, and for vitellogenin in females, were log₁₀ transformed prior to analysis. Significant differences between biomarkers within and between regions were tested using analysis of covariance (ANCOVA), accounting for age as a potential concomitant variable. When significant differences were found, Tukey's studentized range test (HSD) was used to compare group means. Vitellogenin values in males were ranked, and an analysis of variance (ANOVA) was performed. Tukey's HSD test then was used to compare group means of ranks. The 95 percent confidence level (a=0.05) was used in all tests of significance.

Potential complications to the large-scale reconnaissance approach taken in this study include geographic variation in biomarkers that are associated with stages of sexual maturation and variation because of environmental factors, such as photoperiod and water temperature. To be conservative in defining significant differences in biomarkers between sites, the biomarkers were evaluated and controlled for varia-tion from stages of sexual maturation, geographical region, and age.

Excluding vitellogenin in males, significant differences were detected in all biomarkers measured in both males and females using stage of sexual maturation as the classification variable. Fish with unknown stage of maturation (because gonads were not available) were treated as a distinct category. Age was not a significant factor, and the interaction between age and stage of maturation was not significant for any biomarker tested. The results of Tukey's HSD test for female carp showed no differences between stages 0 and 1 or between stages 2 and 3 and the unknowns, but these two groups were significantly different from each other. Therefore, female carp with ovaries in stages 2 and 3 (vitellogenic) and unknowns were combined for all subsequent analyses. Only 20 female carp in sexual maturation stages 0 and 1 were eliminated. Similar analyses for males showed no significant differences between stages 1 and 2 (early and midspermatogenic) and unknowns, but this group was significantly different from stage 3. Male carp with stages 1, 2, or unknown were combined for further analyses. Forty-nine male carp in the late spermatogenic stage were eliminated.

Figure 2A. Female adult carp ovary from Platte River at Louisville, Nebraska, with perinucleolar oocytes at various stages of previtellogenic growth. Some larger oocytes show indications of cortical alveoli stage; classified as stage 0, undeveloped. The carp was 8 years old, 368 mm in length, and weighed 672 g.

Figure 2B. Female adult carp ovary from South Platte River at Denver, Colorado, showing mixture of perinucleolar and cortical alveoli oocytes. Larger oocytes are early vitellogenic; classified as stage 1, previtellogenic. The carp was 7 years old, 604 mm in length, and weighed 2,900 g.

Figure 2C. Female adult carp ovary from Platte River at Louisville, Nebraska, containing some vitellogenic oocytes with moderate numbers of vitelline granules and a few perinucleolar and cortical alveoli oocytes. Two atretic oocytes (left and upper center) show granuosa cell hypertrophy; classified as stage 2, early vitellogenic. The carp was an undetermined age, 592 mm in length, and weighed 2,948 g.

Figure 2D. Female adult carp ovary from Hudson River, south of Lake Luzerne, New York, showing fully developed oocytes with numerous vitelline granules along with a few oocytes in earlier stages of development; classified as stage 3, late vitellogenic. The carp was 8 years old, 727 mm in length, and weighed 6,200 g.

Figure 2E. Male adult carp testis from Platte River at Louisville, Nebraska, showing thick germinal epithelium with diffuse pronounced proliferation and maturation of spermatozoa; classified as stage 1, early spermatogenic. The carp was 8 years old, 475 mm in length, and weighed 1,454 g.

Figure 2F. Male adult carp testis from Hudson River, south of Lake Luzerne, New York, showing moderately thick germinal epithelium with diffuse moderate proliferation and maturation of spermatozoa; classified as stage 2, mid-spermatogenic. The carp was 2 years old, 518 mm in length, and weighed 2,334 g.

Figure 2G. Male adult carp testis from Anacostia River at Washington Shipping Channel, District of Columbia, where germinal epithelium is mostly thin with only scattered spermatogenic activity characteristic of full-grown testes; classified as state 3, late spermatogenic. The carp was 5 years old, 530 mm in length, and weighed 2,286 g.

The potential influence of regionally varying conditions, such as temperature and photoperiod, was investigated in an aggregated manner by grouping sites into major regions (fig. 1) and testing for significant differences in biomarkers between regions. Analysis of covariance showed significant differences between regions by some measures, but not others. There were no consistent patterns in differences of biomarkers among regions. For males, the only significant differences were for E₂/11-KT ratio, with the Northern Midcontinent found different (higher) than the Northeast and Mississippi River Basin regions. For females, excluding the Southern Midcontinent (with only two sites), there were significant differences between regions in 11-ketotestosterone (less in the Northern Midcontinent than in the Mississippi River Basin or the West) and in E₂/11-KT ratio (less in the Mississippi River Basin and West than in the Northast or the Northern Midcontinent). Because differences were apparent in some of the biomarkers between some regions, and because of the potential for natural regional differences in biomarkers, site-to-site differences were tested only within each region.

Contaminants

The optimal characteristics of contaminant data for an exposure assessment, such as sampling media, timing, frequency, and specific constituents, are difficult to determine and are frequently too expensive to obtain. This is particularly true for a reconnaissance, such as the one described in this report, which needs to cover highly variable site conditions in a large geographic area and characterize exposure to a wide range of contaminants. To meet these objectives, sites were chosen where several aspects of contaminant exposure had already been assessed either at or near the same location as part of National Water Quality Assessment. Contaminant levels were characterized using tissue, bed sediment, and water data collected within 1 to 2 years of the time that fish were sampled for biomarker analysis. This approach results in an approximate and relative indication of recent exposure of fish to environmental contaminants at each site.

Specifically, three primary types of contaminant data were used to characterize exposure: (1) analyses of organochlorine pesticides and PCBs in tissue; (2) analyses of polycyclic aromatic hydrocarbons (PAHs), phenols, and phthalates in bed sediment; and (3) analyses of dissolved pesticides in water. Not all types of data were available for all sites. Though each type of contaminant data was managed somewhat differently before analysis, as described below, the general approach was to attain a balance between logical, relatively homogeneous groupings of contaminants and a small enough number of contaminant parameters to evaluate the 25-site data set. Tables 3, 4, and 5 summarize the individual compounds included in each contaminant group. Generally, there was a high degree of intercorrelation among the most detected individual contaminants within each group. This intercorrelation, combined with the small data set and the reconnaissance-level nature of the study design, supported a grouped analysis rather than an approach based on individual contaminants.

Table 3. Organochlorine pesticides analyzed in fish tissue samples
[Data reporting limits for most compounds were 5-10 micrograms per kilogram (ug/kg) wet weight for most samples, except for toxaphene, which was 200 ug/kg]

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Aldrin           p,p'-DDT             Hexachlorobenzene   
alpha-Chlordane  Dieldrin              o,p'-Methoxychlor  
gamma-Chlordane  Endrin                p,p'-Methoxychlor  
Dacthal (DCPA)   alpha-HCH            Mirex               
o,p'-DDD         beta-HCH             cis-Nonachlor       
p,p'-DDD         delta-HCH            trans-Nonachlor     
o,p'-DDE         gamma-HCH (Lindane)  Oxychlordane        
p,p'-DDE         Heptachlor           Pentachloroanisole  
o,p'-DDT         Heptachlor epoxide   Toxaphene           
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Organochlorine Pesticides and PCBs in Tissues

Fish for tissue analysis were collected at 21 sites, and a freshwater clam (Corbicula fluminea) was collected at 4 sites. Collections were made during 1992--1995, with most sites sampled during summer or autumn. Methods used for collecting both fish and clams are described by Crawford and Luoma (1993). The five species of fish collected were carp at 15 sites, white sucker (Catostomus commersoni) at 3 sites, black redhorse (Moxostoma duquesnei) at 1 site, channel catfish (Ictalurus punctatus) at 1 site, and largemouth bass (Micropterus salmoides) at 1 site. All tissue samples were whole-body composites, with fish having 5 to 10 individuals and clams 50 to 100 individuals. Samples were wrapped in aluminum foil and frozen with dry ice in the field until analysis.

Twenty-seven organochlorine pesticides (table 3), total PCBs, and lipid content were analyzed in 20 tissue samples by the U.S. Geological Survey's National Water Quality Laboratory (NWQL), with five tissue samples analyzed by the Mississippi State Chemical Laboratory, under contract with the U.S. Fish and Wildlife Service. The basic methods used at the NWQL included Soxhlet extraction, gel permetation and adsorption chromatographic fractionation, and analysis by dual capillary-column gas chromatography with electron capture detection. Detailed analytical methods for NWQL tissue analysis are described by Leiker and others (1995).

Methods for analyzing organochlorine pesticides and PCBs in tissue at the Mississippi State Chemical Laboratory included soxhlet extract with hexane for 7 hours, concentration by rotary evaporation dissolution in petroleum ether, and extraction four times with acetonitrile. Residues were partitioned into petroleum ether, washed, concentrated, and transferred to a glass chromatographic column with florisil. The column was eluted with 5 percent diethyl ether and 94 percent petroleum ether into Fraction I, and with 15 percent diethyl ether and 85 percent petroleum ether into Fraction II. Fraction II is concentrated by packed or capillary column and quantified by electron-capture gas chromatography. Fraction I is concentrated and transferred to a silicic and acid chromatographic column to separate PCBs into three fractions and quantified by electron-capture gas chromatography.

Total organochlorine pesticides in tissue from each site were calculated by summing concentrations of all individual analytes listed in table 3, with zero concentration assigned to all nondetections. This approach results in a comparatively low approximation of the actual concentration. To minimize effects of different species, total organochlorine pesticide and PCB values were normalized by dividing the values by the lipid concentration for each composite sample. Both total organochlorine pesticides and PCBs were significantly (a=0.05) correlated with lipid concentration for the complete, multispecies national data set. Except for carp, data on individual species are too limited to individually evaluate correlations with lipid concentration. By dividing each composite sample value by its respective lipid concentration, all species were treated similarly, and the resulting values showed no remaining correlation with lipid concentration. In addition, analysis of correlations between contaminants and biomarkers showed no major differences (based on p values and direction of correlation) between results for lipid-normalized and non-normalized data.

At sites for which tissues were analyzed, but no PCBs or organochlorine pesticides detected, one-half of the lowest detected lipid-normalized value for the respective total was used for further data analyses. This procedure ensured that the few sites with no detections had the lowest lipid-normalized concentrations compared to the other study sites. All values were then log₁₀ transformed for correlation analysis.

Two weaknesses of the tissue contaminant data are that analyses were not made on the same individual fish that were analyzed for biomarkers, and that the samples for contaminant and biomarker analyses were collected during different years for most sites. The relative stability of these contaminants over time, the reduced variability caused by summing of contaminants, and the averaging accomplished by compositing should, however, result in a robust indication of overall site conditions from the available data. Data from 34 river sites of the National Biocontaminant Monitoring Program (U.S. Fish and Wildlife Service, 1992) for 1984 and 1986 indicate that analysis of composite carp samples at a site had an average difference of about 64 percent between years for organochlorine pesticides and about 47 percent for PCBs (for organochlorine pesticides, five sites with extreme percentage changes resulting from a very low value in 1 of the 2 years were eliminated). These levels of interannual variability are relatively low compared to the order of magnitude of differences in contaminant levels among sites, but such levels may be an important source of unexplained variation in data analysis, particularly when comparing sites with similar contaminant concentrations.

PAHs, Phenols, and Phthalates in Bed Sediment

Composite bed sediment samples were collected at 22 sites. Collections were made during 1992--1995, with most sites sampled during summer or autumn. At each site, bed sediment was collected from depositional zones in the stream channel, where recently deposited, fine-grain material accumulates. A Teflon sampler or spoon was used to collect bed sediment from the upper 2 cm in 5 to 10 deposition zones and composited into a glass container. Sediment was sieved through a 2.0 mm stainless-steel sieve, decanted, and frozen prior to analysis. Further details of bed sediment sampling are available in Shelton and Capel (1994).

Fifty-two PAHs, 6 phenols, 6 phthalates, and organic-carbon content were analyzed by the NWQL. PAH, phenol, and phthalate compounds were extracted from the sediment with dichloromethane, followed by partial isolation using high-performance gel permeation chromatography and elution with dichloromethane. Compounds were then identified and quantified using dual capillary-column gas chromatography with electron-capture detection. Details on methods are reported in Furlong and others (1996).

Total concentrations of PAHs, phenols, and phthalates for each site were calculated by summing concentrations of all individual analytes listed for each group in table 4, with zero concentration assigned to all nondetections. This approach results in a comparatively low approximation of the actual concentration. Total concentration values were normalized by dividing the values by the organic carbon content of the sample to minimize affects of different site sediment characteristics in the results. Concentrations of PAHs, phenols, and phthalates in bed sediment were not significantly correlated with organic carbon concentrations for the complete national data set (21 sites), but p values for the three regressions ranged from 0.15 to 0.26, with positive slope coefficients of 0.14 to 0.17. Removal of two sites (NBMR-RL in the Northern Midcontinent and MRP-S in the West) with particularly high organic carbon levels resulted in a significant correlation between PAHs and organic carbon. Organic carbon normalization of bed-sediment data, similar to lipid normalization, probably results in the most comparable contaminant data possible for all sites. Analysis of relations between contaminants and biomarkers, however, showed no major differences (based on p values and directions of correlation) in results for carbon normalized and non-normalized data.

For any site where bed sediments were analyzed, but where no PAHs, phenols, or phthalates were detected, one half of the lowest detected organic carbon- normalized value for the respective group total was assigned for further data analysis. This procedure ensured that the sites with no detections had the lowest organic-carbon normalized concentrations compared to the other study sites. All values were log10 transformed for correlation analysis.

A potential weakness of the bed sediment contaminant data, as with tissue data, is that most samples were collected during a different year than that of the biomarkers. For reconnaissance purposes, however, the relative stability of these contaminants over time, the summation of contaminants by major groups, and the averaging accomplished by compositing, should result in a robust indication of overall site conditions. Nevertheless, the differences in timing of sample collection may be an important source of unexplained variation in data analysis.

Dissolved Pesticides

At 11 of the study sites, 7 to 34 filtered water samples were collected during 1993--1994, at least monthly from March through September at most sites. Depth-integrated, discharge-weighted water samples were collected and prepared for laboratory analysis of dissolved pesticides as described by Shelton (1994). Fifty-two pesticides (table 5) were analyzed by extracting compounds from filtered water (0.7 5m glassfiber filter) using a C-18 solid-phase extraction cartridge, eluting the cartridge with hexaneisopropanol, and analyzing by capillary-column gas chromatography with spectrometric detection in the "selected-ion" monitoring mode (Zaugg and others, 1995).

For each site, a time-weighted annual mean concentration of dissolved pesticides was computed by summing all detected pesticides from each sample, weighting each sample total by the number of days it represents within the year, summing the time-weighted concentrations over the year, and dividing by 365 days. Nondetections were treated as zero concentrations, resulting in a comparatively low estimate of the total pesticide concentration. Annual medians, which were considered but not used in final analyses, yielded the same overall findings as timeweighted means. Time-weighted means were log 10 transformed for correlation analysis.

The most relevant measure of exposure of fish to dissolved pesticides for assessing potential endocrine disruption is difficult to determine. Dissolved pesticides vary over time within and between seasons in different ways for different chemicals and in different regions. The time-weighted annual mean was chosen as a relatively stable measure of average exposure. One potential weakness of the dissolved pesticide values is that pesticide sampling was done in a different year than when fish were sampled for biomarker analysis. However, year-to-year seasonal patterns and overall levels tend to repeat annually at a site, as shown by data in Richards and Baker (1993) and Coupe and others (1995). Nevertheless, important potential sources of unexplained variation in data analysis are temporal variability and, in particular, the uncertainty in which temporal measure of pesticide concentrations (for example seasonal mean or annual mean) is most relevant to endocrine effects.

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