Full document / COSOC-W-86-002 - the National Sea Grant Library

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frequencies at which they correctly identified impacted stations and
misidentifled nonlmpacted stations. Stations were designated as
impacted or nonlmpacted by Independent statistical comparisons of
biological data to reference conditions. These Impaeted/noniapacted
designations were based on four biological indicators: amphipod
mortality bioassays, oyster larvae abnormality bioassays, Mlcrotox
btoluolnescence bioassays, and benthic Infauna) analyses. A subset
of impacted stations was designated as severely Impacted based on
somewhat arbitrary criteria: greater than 50 percent amphipod
mortality or oyster larvae abnormality, or statistically significant
depressions In the abundance of more than one major taxonomlc group
of benthic infauna (Including Hollusca, Polychaeta, Crustacea). This
subset of severely Impacted stations was only used as part of the
validation check on sediment quality values, and not to generate
sediment quality values.
The 40 sediment quality values generated using the equilibrium
partitioning approach correctly Identified between 13 and 43 percent
of the impacted stations, and between 0 and 46 percent of the
severely impacted stations, depending upon the biological indicator
used for validation. The equilibrium partitioning approach
misidentifled between 0 and 67 percent of the nonlmpacted stations,
depending upon the biological indicator used for validation. Hence,
the equilibrium partitioning approach was not highly accurate nor
efficient (see Figure 2) in identifying problem sediments.
The 64 sediment quality values generated using the AET approach
(using dry-weight normalization) correctly identified between 54 and
94 percent of the impacted stations, and between 92 and 100 percent
of the severely impacted stations, depending on the biological
indicator used for validation. Corresponding AET values generated
from chemical data normalized to total organic carbon content or to
percent fine-grained material in sediments correctly identified
between 37 and 88 percent of the impacted stations, and between 62
and 100 percent of the severely impacted stations, depending on the
type of normalization, and the biological indicator used for
validation. The AET approach misidentifled between 0 and 69 percent
of the nonlmpacted stations, depending on the type of normalization
used for chemical concentrations and biological indicator used for
validation. Hence, the AET approach was highly accurate in
Identifying problem sediments, although the approach was not
highly efficient in Identifying only problem sediments (see Figure 2).
A detailed evaluation of the accuracy of the SCI values was beyond
the scope of the study, because limitations in the database
restricted generation of values to only three chemicals. It was
assumed that such a small number of chemicals could not be expected
to correctly identify all Impacted stations. Hence, a preliminary
evaluation was made only of the number of nonlmpacted stations
misidentifled as being Impacted using each of the three SIC values.
The values misidentifled between 15 and 70 percent of the nonlmpacted
stations, depending on the chemical, type of normalization of
chemical concentrations, and biological indicator used for
validation. The approach warrants further investigation.