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