1.1 MB pdf - Bolsa Chica Lowlands Restoration Project
1.1 MB pdf - Bolsa Chica Lowlands Restoration Project 1.1 MB pdf - Bolsa Chica Lowlands Restoration Project
SECTION 3: ANALYSIS Amphipod (Eohaustorius estuarius) Regression Analysis Results of the amphipod toxicity bioassay consisted of counts of individuals surviving and counts of individuals exhibiting reburial behavior. Regression analyses were not performed for reburial behavior because few significant effects were observed; in more than 50 samples for which bioassays were performed, significantly decreased reburial was observed in only 3 (see Appendix F). Sample sizes within each replicate were constant among replicates (i.e., N=20). Therefore, regression analyses were performed with the count data as the dependent variable. The independent variables consisted of concentrations of chemicals in sediment (as mg/Kg or µg/Kg). (Note: TOC-normalized concentrations of organics were evaluated in initial data screens. As these data did not improve the predictive quality of the regression analyses, they were not considered further). Because environmental chemistry data are frequently log-normally distributed (Burmaster and Hull, 1997), analyses were also performed with natural-log-transformed concentration data as the independent variable. Simple linear regression analyses were performed using SAS (1994) PROC REG. All models were considered significant if p#0.05. Of 75 compounds detected in sediment samples used for amphipod toxicity bioassays based on all test media adjustment groups combined, significant linear relationships between untransformed concentrations and survival were observed for 39 (Table 3-15). This relationship (e.g., slope) was negative for 38 of the 39 compounds. The amount of variation (r 2 ) explained by these models ranged from 3.7 percent (e.g., r 2 =0.037; lead) to 99 percent (e.g., r 2 =0.99; total phenol and PCB-028). Natural-log-transformation of the concentrations resulted in significant fits for 43 of 75 compounds; 39 of them were negative (Table 3-15). Among these models, r 2 also ranged from 0.033 (e.g., 4,4’-DDD) to 0.99 (e.g., total phenol and PCB-028). Comparison of the results obtained based on transformed and untransformed data indicates that, in general, better model fits (e.g., higher r 2 values) were obtained from the transformed concentration data; untransformed data produced the best fit for 18 analytes whereas 24 analytes were fit best by transformed data (Table 3-15). If total sample size among all four test media adjustment groups exceeded 100, further regression analyses were performed for each group for each analyte. A total of 24 analytes met this criterion (Table 3-19). Although quality of model fits differed by test media adjustment group for each analyte , a significant fit was obtained for at least one group within each analyte. In addition, although a significant model fit had been obtained for all analytes with n>100 when test media adjustment groups where pooled (Table 3-15), better model fits (e.g., higher r 2 values) were obtained for at least one test media adjustment group within each analyte, except for chromium (Table 3-16). F-tests (Draper and Smith 1981) were performed to compare regression results among the four test media adjustment groups and among wet/dry sediment or the presence/absence of salinity adjustment. Differences were considered significant if p#0.05. A summary of the results is presented in Table 3-17. Significant differences between regression models among all four test media adjustment groups were observed for 47 of the 75 analytes detected in sediments used for amphipod bioassays (Table 3-17). In addition, regression models for wet vs. dry sediment differed significantly for 29 analytes; and 35 analytes differed significantly by presence/absence of salinity adjustment. SAC/143368(003.DOC) 3-33 ERA REPORT 7/31/02
SECTION 3: ANALYSIS Scatter plots associated with regression analyses for all chemicals, test media adjustment groups, and data transformations for amphipods are presented in Appendix H. Additional plots of exposure response results for selected compounds are presented in Figures 3-17 through 3-29. Mussel (Mytilus edulis) Regression Analysis Results of the Mytilus toxicity bioassay consisted of counts of individuals surviving and counts of individuals displaying abnormal development. Because sample sizes were not constant among replicates, all Mytilus effects data were expressed as the proportion of individuals at the start of the bioassay. Proportions were arcsine-square root transformed (Zar, 1984) prior to analyses to correct for non-normality of proportion data. The independent variables consisted of untransformed and natural-log-transformed concentrations of chemicals in pore water (µg/L). Simple linear regression analyses were performed using SAS (1994) PROC REG. All models were considered significant if p#0.05. Prior analyses indicated that Mytilus survival was poorly related to chemical concentrations in pore water, regardless of whether data were untransformed or natural-log transformed. Significant regression fits were obtained for only 10 of 46 compounds based on untransformed data and for only 8 of 46 based on transformed data. Values for r 2 were low for both approaches, ranging from 0.0058 to 0.1 for untransformed data and 0.0053 to 0.33 for transformed data. Due to the low quality of the relationship between Mytilus survival and pore water concentrations, this analysis was not pursued further. In contrast to Mytilus survival, the proportion of normal Mytilus was strongly related to chemical concentrations. Significant model fits were obtained for 37 of 41 chemicals based on untransformed data and 39 of 41 chemicals for transformed data (Table 3-18). The proportion of normal Mytilus was negatively related to chemical concentration for all chemicals evaluated. Among models for untransformed data, r 2 ranged from 0.029 (silver) to 0.84 (aldrin; Table 3-18). For models based on transformed data, r 2 ranged from 0.04 (4,4’-DDD) to 0.83 (4-nitrophenol, chrysene, high molecular weight PAHs, and 4-methylphenol; Table 3-18). With the exception of eight compounds (aldrin, arsenic, barium, beryllium, chromium, endrin aldehyde, total phenol, and vanadium), natural-log-transformed data explained more variability in the proportion of normal Mytilus than did untransformed data (Table 3-18). Although pore water used for the Mytilus toxicity tests was adjusted in a manner comparable to the sediment used for the amphipod tests (e.g., derived from wet or dry sediment, with or without salinity adjustment), because no relationship was found between sediment concentrations and pore water concentrations (see below), regression models for the four test media adjustment groups were not developed. Scatterplots associated with regression analyses for all chemicals and data transformations for Mytilus are presented in Appendix H. Additional plots of exposure-response results for selected compounds are presented in Figures 3-30 through 3-38. Estimated Effect Levels In addition to determining which compounds best described effects observed in the toxicity bioassays, regression models were used to estimate concentrations in sediment and pore water that were associated with 20 and 50 percent lethality (i.e., LC 20 or LC 50 ) or effects (i.e., EC 20 or EC 50 ) concentrations. LC and EC values were only calculated for those chemicals ERA REPORT 3-34 SAC/143368(003.DOC) 7/31/02
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SECTION 3: ANALYSIS<br />
Scatter plots associated with regression analyses for all chemicals, test media adjustment<br />
groups, and data transformations for amphipods are presented in Appendix H. Additional<br />
plots of exposure response results for selected compounds are presented in Figures 3-17<br />
through 3-29.<br />
Mussel (Mytilus edulis) Regression Analysis<br />
Results of the Mytilus toxicity bioassay consisted of counts of individuals surviving and<br />
counts of individuals displaying abnormal development. Because sample sizes were not<br />
constant among replicates, all Mytilus effects data were expressed as the proportion of<br />
individuals at the start of the bioassay. Proportions were arcsine-square root transformed<br />
(Zar, 1984) prior to analyses to correct for non-normality of proportion data. The<br />
independent variables consisted of untransformed and natural-log-transformed<br />
concentrations of chemicals in pore water (µg/L). Simple linear regression analyses were<br />
performed using SAS (1994) PROC REG. All models were considered significant if p#0.05.<br />
Prior analyses indicated that Mytilus survival was poorly related to chemical concentrations<br />
in pore water, regardless of whether data were untransformed or natural-log transformed.<br />
Significant regression fits were obtained for only 10 of 46 compounds based on<br />
untransformed data and for only 8 of 46 based on transformed data. Values for r 2 were low<br />
for both approaches, ranging from 0.0058 to 0.1 for untransformed data and 0.0053 to<br />
0.33 for transformed data. Due to the low quality of the relationship between Mytilus<br />
survival and pore water concentrations, this analysis was not pursued further.<br />
In contrast to Mytilus survival, the proportion of normal Mytilus was strongly related to<br />
chemical concentrations. Significant model fits were obtained for 37 of 41 chemicals based on<br />
untransformed data and 39 of 41 chemicals for transformed data (Table 3-18). The proportion<br />
of normal Mytilus was negatively related to chemical concentration for all chemicals<br />
evaluated. Among models for untransformed data, r 2 ranged from 0.029 (silver) to 0.84<br />
(aldrin; Table 3-18). For models based on transformed data, r 2 ranged from 0.04 (4,4’-DDD) to<br />
0.83 (4-nitrophenol, chrysene, high molecular weight PAHs, and 4-methylphenol; Table 3-18).<br />
With the exception of eight compounds (aldrin, arsenic, barium, beryllium, chromium,<br />
endrin aldehyde, total phenol, and vanadium), natural-log-transformed data explained more<br />
variability in the proportion of normal Mytilus than did untransformed data (Table 3-18).<br />
Although pore water used for the Mytilus toxicity tests was adjusted in a manner<br />
comparable to the sediment used for the amphipod tests (e.g., derived from wet or dry<br />
sediment, with or without salinity adjustment), because no relationship was found between<br />
sediment concentrations and pore water concentrations (see below), regression models for<br />
the four test media adjustment groups were not developed.<br />
Scatterplots associated with regression analyses for all chemicals and data transformations<br />
for Mytilus are presented in Appendix H. Additional plots of exposure-response results for<br />
selected compounds are presented in Figures 3-30 through 3-38.<br />
Estimated Effect Levels<br />
In addition to determining which compounds best described effects observed in the toxicity<br />
bioassays, regression models were used to estimate concentrations in sediment and pore<br />
water that were associated with 20 and 50 percent lethality (i.e., LC 20 or LC 50 ) or effects (i.e.,<br />
EC 20 or EC 50 ) concentrations. LC and EC values were only calculated for those chemicals<br />
ERA REPORT 3-34 SAC/143368(003.DOC)<br />
7/31/02