Food web bioaccumulation model for polychlorinated biphenyls in San Francisco Bay, California, USA.

Abstract

We document the development and application of a food web bioaccumulation model for polychlorinated biphenyls (PCBs) in San Francisco Bay, California, USA. The model calculates spatial distributions of PCB concentrations in a range of invertebrate, fish, avian, and mammalian organisms, including harbor seals, double-crested cormorants, and Forster's terns. The performance of the model is evaluated against independent empirical PCB concentrations and shows a mean deviation between observed and model-calculated concentrations of 36% for female harbor seals and 5% for benthic invertebrates and jack smelt. The model was applied to produce bay-wide PCB concentration distributions in fish and wildlife species, which were compared with threshold effect concentrations to determine ecological risks and human health risks of fish consumption. Because of their high trophic position in the food web, harbor seals exhibited the highest concentrations of summation operatorPCBs, which exceeded threshold concentrations for potential adverse effects. The model was also applied to derive bay-wide target sediment concentrations for remediation as part of an ongoing total maximum daily loading characterization. The model calculated bay-wide geometric mean concentrations of summation operatorPCB in sediments of 1.6 to 73 microg/kg dry weight to meet several ecological and human health risk objectives. The bay-wide geometric summation operatorPCB concentration in the sediments at the time of the study was 11.6 microg/kg dry weight. The model was developed for assessing the behavior and risks of bioaccumulative substances on an ecosystem level.

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FOOD WEB BIOACCUMULATION MODEL FOR POLYCHLORINATED BIPHENYLS
IN SAN FRANCISCO BAY, CALIFORNIA, USA
FRANK A.P.C. GOBAS* and JON A. ARNOT
School of Resource and Environmental Management, Simon Fraser University, 8888 University Drive, Burnaby, British Columbia V5A 1S6, Canada
(Submitted 28 April 2009; Returned for Revision 20 October 2009; Accepted 1 February 2010)
Abstract—We document the development and application of a food web bioaccumulation model for polychlorinated biphenyls (PCBs)
in San Francisco Bay, California, USA. The model calculates spatial distributions of PCB concentrations in a range of invertebrate, fish,
avian, and mammalian organisms, including harbor seals, double-crested cormorants, and Forster’s terns. The performance of the model
is evaluated against independent empirical PCB concentrations and shows a mean deviation between observed and model-calculated
concentrations of 36% for female harbor seals and 5% for benthic invertebrates and jack smelt. The model was applied to produce bay-
wide PCB concentration distributions in fish and wildlife species, which were compared with threshold effect concentrations to
determine ecological risks and human health risks of fish consumption. Because of their high trophic position in the food web, harbor
seals exhibited the highest concentrations ofPPCBs, which exceeded threshold concentrations for potential adverse effects. The model
was also applied to derive bay-wide target sediment concentrations for remediation as part of an ongoing total maximum daily loading
characterization.Themodelcalculatedbay-widegeometric meanconcentrationsofPPCBinsedimentsof1.6to73mg/kgdryweightto
meet several ecological and human health risk objectives. The bay-wide geometricPPCB concentration in the sediments at the time of
thestudywas11.6mg/kgdryweight. Themodel wasdevelopedforassessingthebehavior andrisksofbioaccumulative substances onan
ecosystem level. Environ. Toxicol. Chem. 2010;29:1385–1395. # 2010 SETAC
Keywords—Polychlorinated biphenyls BioaccumulationModelRisk assessmentEcosystem management
INTRODUCTION
San Francisco Bay is the largest estuary on the Pacific Coast
of America. It includes productive wetlands and supports
diverse wildlife communities alongside a densely populated
urban area. As a result of runoff from contaminated streams and
urban areas [1,2], effluent discharges [3,4], and atmospheric
deposition [5], polychlorinated biphenyls (PCBs) are found in
water and sediments throughout the estuary [6]. Concentrations
of PCBs in San Francisco Bay have exceeded water quality
guidelines at the majority of sampling stations throughout the
bay for the entire duration that samples have been collected.
Tissue concentrations of PCBs in San Francisco bay sport fish
became anissue ofpublicconcern whenafishtissue monitoring
study in the early 1990s resulted in a fish consumption advisory
issued by California’s Office of Environmental Health Hazard
Assessment. The U.S. Environmental Protection Agency, as a
result of the advisory, placed San Francisco Bay on the 303(d)
impaired water body list for PCBs and other contaminants [6].
The Regional Water Quality Control Board initiated a total
maximum daily loading (TMDL) study of the bay, as required
by the Clean Water Act, to understand better the relationships
between sources and PCB concentrations in water, sediments,
and wildlife throughout the bay and to facilitate and support
management decisions protective of wildlife and humans. An
abiotic mass balance model was developed as part of the TMDL
study, in order to describe the relationship between PCB inputs
into the bay and resulting PCB concentrations in water and
sediments [7]. The second phase of the TMDL study is the
development of a food web bioaccumulation model to inves-
tigatetherelationshipbetween PCBconcentrations inwaterand
sediments and resulting PCB concentrations in organisms of the
San Francisco Bay food web. The main purpose of the model is
to identify what PCB concentrations in the sediments and water
of the bay must be achieved before PCB concentrations in biota
of the bay will meet acceptable levels. The abiotic and biotic
models can be used to determine what reductions in PCB
loadings must be accomplished to ensure that wildlife are no
longer at risk of PCB contamination and that people can safely
consume fish caught in San Francisco Bay. The model is based
on Arnot and Gobas [8] but also includes new model equations
for fish-eating birds and marine mammals and is being applied
to a marine system.
The objective of the present study is to develop and evaluate
a food web bioaccumulation model for PCBs in San Francisco
Bay. We further discuss the application of the model for
deriving sediment remediation targets and the development
of sediment quality criteria that are protective of the health
of humans and wildlife consuming San Francisco Bay fish and
shellfish. Because this effort involves a risk assessment, which
is subject to judgment and interpretation, we have presented the
PCB food web bioaccumulation model in a format that allows
various scenarios regarding human health and ecological risks
to be evaluated.
THEORY: MODEL DEVELOPMENT
Model objective
The goal of this model is to characterize the relationship
between bay-wide concentrations of PCBs in sediment and key
biological species in the bay selected for their role as a vector
Environmental Toxicology and Chemistry, Vol. 29, No. 6, pp. 1385–1395, 2010
# 2010 SETAC
Printed in the USA
DOI: 10.1002/etc.164
All Supplemental Data may be found in the online version of this article.
* To whom correspondence may be addressed
(gobas@sfu.ca).
Published online 1 March 2010 in Wiley InterScience
(www.interscience.wiley.com).
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for human exposure and ecological significance. This relation-
ship between the PCB concentrations in biota (CBin g PCB/kg
wet wt organism) and the sediment (CSin g PCB/kg dry wt
sediment), developed for each species, i, is represented by the
biota–sediment accumulation factor (BSAF in kg dry wt/kg
wet wt).
BSAFi¼ CB;i=CS
(1)
TheBSAFisthemainoutputofthemodelandprovidesamethod
fortcalculating,inaforwardmanner,thechemicalconcentration
inselectedbiologicalspeciesfromthechemicalconcentrationin
thesedimentsasCB¼BSAF?CS.TheBSAFcanalsobeusedina
backward calculation, to derive a chemical concentration in the
sedimentthatisexpectedtocauseaparticularconcentration,CB
as CS¼CB/BSAF.
Polychlorinated biphenyls
Model calculations were performed on a PCB congener-
specific basis, because PCB congeners differ in partitioning
properties and toxicity. The Regional Monitoring Program
(RMP) for the bay analyzes approximately 40 PCB congeners,
i.e., PCBs 8, 18, 28, 31, 33, 44, 49, 52, 56, 60, 66, 70, 74, 87, 95,
97, 99, 101, 105, 110, 118, 128, 132, 138, 141, 149, 151, 153,
156, 158, 170, 174, 177, 180, 183, 187, 194, 195, 201, and 203.
These congeners, referred as the RMP40, were therefore
included in the model calculations. The majority of these
congeners are non-coplanar. Toxic equivalency factor (TEF)
valuesareavailableforonlythreeofthe40PCBcongeners(i.e.,
PCBs 101, 118, and 156). However, the TEFs of these con-
geners are low compared with those of coplanar PCBs such as
PCBs 77, 126, and 169. As a result, PCB concentrations were
expressed not in terms of toxic equivalents but as the total PCB
(PPCB) concentration, i.e., the sum of the concentrations of
the RMP40.
Food web
The food web structure of San Francisco Bay is complex.
The food web includes many different species with a variety of
habitats. Species composition varies between locations in the
bay and at different times of the year. Feeding relationships also
vary between species, life stages of species, abundance of the
variousspecies, location,timeoftheyear,andotherfactors.Itis
not possible, or necessary, to include all species in the San
Francisco Bayfood webin the modelor torepresent all possible
trophic interactions. In the development of a food web structure
for modeling the bioaccumulation of PCBs in SFB, we selected
to include species with the following characteristics.
Speciesofprimarymanagementinterest,i.e.,thedouble-crested
cormorant (Phalacrocorax auritus), Forster’s tern (Sterna
forsteri), harbor seal (Phoca vitulina richardsi), shiner
surfperch (Cymatogaster aggregata), jack smelt (Atherinop-
sis californiensis), and white croaker (Genyonemus lineatus).
The harbor seal, Forster’s tern, and double-crested cormorant
were included in the model because they represent species of
higher trophic levels in the food web and contain the highest
concentrations of PCBs. The white croaker, shiner surfperch,
and jack smelt were included in the model because they are
caught and consumed by local fishermen.
Species that are considered to be year-round residents of San
FranciscoBayor,foragepredominantlyinSanFranciscoBay,
and are expected to be affected by remediation.
Species representing trophic guilds that are of key relevance to
thefoodwebtransferandaccumulationofPCBsinthespecies
ofinterest.Relevanttrophicguildsincludephytoplanktonand
algae; zooplankton; filter-feeding invertebrates; benthic
detritovores; juvenile and adult fish; male and female fish-
eatingbirds;andmale,female,andjuvenilemarinemammals.
Species for which empirical concentration data are available.
This provides the opportunity to test and ground-verify
the model’s calculations. Concentration data were available
for Pacific oysters (Crassostrea gigas), California mussels
(Mytilus californianus), shiner surfperch (Cymatogaster
aggregata), jack smelt (Atherinopsis californiensis), white
croaker (Genyonemus lineatus), double-crested cormorant
(Phalacrocorax auritus), and harbor seal (Phoca vitulina
richardsi).
We further minimized the number of species in the model to
keep the model simple and make the model calculations more
transparent. This approach produced a food web model that
included one category for phytoplankton; one category for
zooplankton; eight invertebrate species (including detritovores
and filter feeders); two bird species (including male and female
birds as well as eggs for each avian species); and male, female,
juvenile, and newborn harbor seals. The species that were
included in the model and their feeding relationships are listed
Supplemental Data Tables S1, S2, and S3 and are illustrated in
Figure 1. The Supplemental Data include additional rationale
for species selection.
Spatial distribution
ThePPCBconcentrationsinsedimentsrangefromvirtually
nondetectable levels to concentrations as high as 9mg/kg (dry
sediment) [7], and concentrations in water range from approxi-
mately 77pg/L to approximately 3,700pg/L [9]. This spatial
variability in the total PCB concentrations causes significant
variation in exposure to PCBs among biota of the bay. Organ-
isms with limited mobility (e.g., certain invertebrates such as
mussels and polychaetes) are likely to reflect the PCB concen-
trationsin theirimmediateenvironment. Hence,ifthey reside in
a hot spot, PCB concentrations are likely to be greater than
concentrations in organisms that inhabit less PCB-polluted
sections of the bay. However, seals, cormorants, terns, and
several of the fish species investigated in the present study have
foraging areas that include large sections of the bay and
are therefore exposed to a wider range of PCB concentrations
in the sediments. The PCB concentrations in these organisms
are expected to reflect a spatial average of the concentrations to
which they are exposed. Also, species that are widely distrib-
uted in the bay will exhibit bay-wide spatially averaged con-
centrations depending on the areas within the bay where they
reside and forage. If information on the spatial distribution of
wildlife and associated PCB concentrations in sediments in the
bayisavailable,itispossibletocalculatePCBconcentrationsin
wildlife based on their foraging behavior. However, this infor-
mation is not currently available. To calculate the PCB con-
centrations in wildlife species that are widely distributed in the
bay, we assumed that the available PCB sediment concentration
data collected by monitoring programs in the bay represent the
distribution of PCB concentrations to which the wildlife pop-
ulations in the bay are exposed. This assumption is reasonable
for several reasons. First, PCB sediment concentration-
monitoring programs have included a large number of stations
throughoutthebay(SupplementalDataFig.S1).Largenumbers
of independent sediment PCB concentration measurements
(?1,284) have been collected from these stations and can
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provide a reasonable representation of the spatial distribution of
the PCB concentrations in the bay. Second, the wildlife species
included in the model are distributed over large areas of the bay
area and are year-round residents of the bay.
Time
The San Francisco Bay food web bioaccumulation model
applies a steady-state approach to estimate the PCB concen-
trationsin biotafromPCB concentrationsin thesediments.This
approach is based on the assumption that, under the conditions
of interest, PCB concentrations have had sufficient time to
exchange between water, sediments, and the organisms of
the food web to achieve a steady state or pseudosteady state.
An important implication of the selection of the steady-state
approach is that PCB concentrations in biota are directly
proportional to the PCB concentrations in the bay sediment.
This means that temporal changes in the PCB concentrations in
the biota of the bay will match those in the sediments. We
believe that this assumption is justified, because the time
response of the PCB concentrations in the sediment to changes
in loadings and external conditions is quite slow compared to
the time response of PCB concentrations in biota. Davis [7]
estimated that the half-life of PCBs in San Francisco Bay is
approximately 20 years. A comparable half-life of PCBs calcu-
latedinadultwhitecroakerisapproximately100d.Thisimplies
that the temporal response of the PCB concentration in most
organisms is controlled by the time response of the sediments,
which acts as the slowest compartment, and that the rate-
controlling step of PCB concentration changes over time.
Model description for phytoplankton, zooplankton, benthic
invertebrates, and fish
The algorithms used for phytoplankton, zooplankton,
benthic invertebrates and fish are essentially those reported
byArnotandGobas[8].Thismodelisbasedonthepresumption
that the exchange of PCB congeners between the organism and
its ambient environment (Supplemental Data Fig. S2) can
be described by a single equation for a number of aquatic
organisms.
CB¼ k1? mO?f?CWT;Oþ mP?CWD;S
???
þkD?SPi?CD;i?= k2þ kEþ kGþ kM
ðÞ
(2)
where CBis the wet weight concentration (g/kg wet wt) of the
PCB congener in the organism, k1is the clearance rate constant
([L/kg wet wt]/d) for uptake via the respiratory area (i.e., gills
and skin), mOis the fraction of the respiratory ventilation that
involves overlying water, mPis the fraction of the respiratory
ventilation that involves sediment associated pore water,
f (unitless) is the fraction of the total chemical concentration
in the overlying water that is freely dissolved and can be
absorbed via membrane diffusion, CWT,Ois the total concen-
tration of the PCB congener in the water column above the
sediments (g/L), CWD,Sis the freely dissolved PCB congener
concentration in the sediment associated pore (or interstitial)
water (g/L), kDis the clearance rate constant ([kg/kg wet wt]/d)
for chemical uptake via ingestion of food and water, Piis the
fraction of the diet consisting of prey item i, CD,i is the
concentration of PCB congener (g/kg) in prey item i, k2is
the rate constant (1/d) for elimination of PCBs via the respi-
ratory area (i.e., gills and skin), kEis the rate constant (1/d) for
the elimination of the PCB congener via excretion into egested
feces, kG, is the growth rate constant expressed as fixed annual
proportional increases in the organism’s wet weight WB(kg)
over time t, i.e., dWB/(WB? dt), and kMis the rate constant (1/d)
for metabolic biotransformation of the PCB congener. The
Fig. 1. Conceptual diagram illustrating organisms included in the model and their trophic interactions.
San Francisco Bay bioaccumulation model
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methodsforderivationofthemodelstatevariables canbefound
in the Supplemental Data.
Model description for harbor seals
Supplemental Data Figure S3 provides a conceptual over-
view of major routes of PCB uptake and elimination in harbor
seals. PCB uptake is due predominantly to dietary uptake and
inhalation of air. Elimination of PCBs from the seals is due to
exhalation of air and excretion in fecal matter and urine. In
addition, certain PCB congeners can be metabolized in harbor
seals [10,11]. Female seals can also transfer PCBs to their
offspring by giving birth to pups and by lactation. Molting and
growth periods can also affect PCB concentrations. Harbor
seals are known to fast and molt at particular times of the year,
and female animals give birth and nurse their pups for a period
of approximately four weeks. To represent these processes in a
relatively simple model, it is important to consider some key
characteristics of PCBs. First, PCBs are lipophilic chemicals
that build up high concentrations in the lipids of organisms.
Seals contain large amounts of fat in their blubber. The whole-
body-weight lipid content of healthy harbor seals in the bay
varies between 36 and 50%. This means that the great majority
of PCBs are found in the lipid tissues. Second, PCBs show a
natural tendency to establish a chemical equilibrium. This
means that, within an organism such as a seal, PCBs distribute
themselves between various parts of the organism in a way that
theconcentrationsinlipidsofanypartoftheorganismapproach
equality. This behavior of PCBs is particularly relevant to
transfer of PCBs from female seals to their pups. If it can be
assumed that PCBs in mother and pup achieve an internal
equilibrium, then the lipid-normalized concentration in female
seals will not change upon parturition. In essence, the reduction
in the mass of PCBs in the mother upon parturition (due to
transfer to the pup) is associated with a proportional drop in
lipid mass, causing the lipid-normalized concentration to
remain the same.The sameprinciple is at work during lactation.
Assuming that PCBs are equally distributed among fats in the
nursing female, transfer of PCB in milk does not cause a change
in concentration as proportional declines in PCB mass and lipid
mass occur during lactation. The same philosophy applies to
molting. Although production of offspring, lactation, and molt-
ing are not expected to have an immediate effect on the lipid-
normalized concentration in the seal, they do have a long-term
concentration effect in seals because of the growth dilution
effect that takes place during fetal development, milk produc-
tion, and skin formation. Seals have to grow body mass to
accommodate these processes in addition to any net (year-to-
year) increases in body weight. This process of growth takes
place more gradually over the seal’s life cycle and can be
represented as a continuous process. Naturally, the growth-
induced decline of the PCB concentration in seals is compen-
satedbyintakeofPCBwiththedietthatmakesgrowthpossible.
The steady-state solution of the mass balance equation (Sup-
plemental Data Eqn. S25) in the harbor seals is
CHS;l¼ kACAGþ kD:S Pi?CD;i
þkUþ kGþ kPþ kLþ kMÞ
????= kOþ kE
ð
(3)
where CHS,lis the lipid-normalized concentration of the PCB
congener in the seal, CAGis the gaseous aerial concentration (g/
L), kAis the inhalation rate constant ([L/kg lipid]/d), kDis the
clearance rate constant ([kg/kg lipid]/d) for PCB uptake via
ingestion of food and water, Pi is the fraction of the diet
consisting of prey item i, CD,i is the concentration of the
PCB congener (g/kg lipid) in prey item i, kOis the rate constant
(1/d) for exhalation of PCB via the lungs, kEis the rate constant
(1/d) for the elimination of the PCB congener via excretion into
egested feces, kUis the rate constant for urinary excretion of
PCBs, kGis the rate constant for growthdilution (accountingfor
year-to-yearincreasesinthenetgrowthoftheanimals),kPisthe
rateconstantfortransferofPCBsintothepups(representingthe
increase in lipid mass [equivalent to the postparturition lipid
mass of the pup] over the duration of the gestation period), kLis
the rate constant for transfer of PCBs to the pups as a result of
lactation(portrayingthegrowthoflipidmassofthefemaleseals
over the year that is transferred to the pup during lactation), and
kG, kP, and kL are expressed as fixed annual-proportional
increases in body lipid weight over time t, i.e., dWS,l/(WS,l?dt),
where WS,lis the weight of the lipids in the seal and has units of
d?1?kM, the rate constant for metabolic transformation of the
PCB congener. A whole-organism wet-weight-based concen-
tration in the seal, CHS, can be calculated from the lipid-
normalized concentration as CHS¼LHS?CHS,l, where LHSis
the lipid content of the harbor seal. The whole-organism lipid
content undergoes significant changes throughout the year.
Therefore, the wet weight concentration in the seal can be
expected to undergo changes of similar magnitude. These
changes can be represented in the model by varying LHS.
The lipid content in seals is high; hence, the contribution of
nonlipid organic matter as a storage compartment for PCBs is
relatively insignificant. Further description of the model for
harbor seals is included in the Supplemental Data.
Model description for cormorants and terns
The uptake of PCBs in birds is due to dietary uptake and
inhalation of air. Polychlorinated biphenyls are eliminated in
exhaled air, fecal matter, and urine and by metabolic biotrans-
formation (Supplemental Data Fig. S4). During periods of
growth, PCB concentrations can be affected by growth dilution,
which is not a real elimination process but reduces PCB
concentrations in the animals.
Female birds can also transfer PCBs into eggs. In the model,
theeffectofthedepositionofPCBsineggsonthematernalPCB
body burden is comparable to the transfer of PCBs to offspring
and milk in harbor seals. This assumes that PCBs are well
distributed among the lipid tissues in the bird. Hence, a reduc-
tion in the mass of PCBs in the mother as a result of transfer of
PCBs in the eggs is associated with a proportional drop in lipid
mass, causing the lipid-normalized concentration to remain
approximately the same. The main impact of producing eggs
on the maternal PCB body burden is the result of the increase in
body mass required to produce the eggs. Growth causes a
decline of the PCB concentration in the female birds. This is
compensated by intake of PCB with the diet that makes growth
possible. The PCB concentration in the bird is the result of the
balance between uptake and elimination rates, which at steady
state can be represented by
CC;l¼ kACAGþ kD?
X
Pi?CD;i
??
??
= kOþ kEþ kGþ kCþ kM
ðÞ
(4)
where CC,lis the lipid-normalized concentration of the PCB
congener in either the cormorant or the tern, CAGis the gaseous
aerial concentration (g/L), kAis the inhalation rate constant ([L/
kglipid]/d),kDistheclearancerateconstant([kg/kglipid]/d)for
PCB uptake via ingestion of food and water, Piis the fraction of
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the diet consisting of prey item i, CD,iis the concentration of the
PCB congener (g/kg) in prey item i, kOis the rate constant (1/d)
for exhalation of PCB via the lungs of the birds, kEis the rate
constant (1/d) for the elimination of the PCB congener via
excretion into egested feces, kGis the rate constant for growth
dilution resulting from year-to-year increases in the net body
massofthebirds,kCistherateconstantfortransferofPCBsinto
eggs in female birds (representing the increase in lipid mass
resulting from egg production), and kMis the rate constant for
biotransformation of the PCB congener in the bird. The whole-
organismwet-weight-basedconcentration,CC,canbecalculated
from CC,las CC¼LC?CC,l, where LCis the lipid content of the
cormorants or the terns. A detailed description of the model is
given in the Supplemental Data.
MATERIALS AND METHODS
Model parameterization
Model parameterization involves the selection of state var-
iables to ensure that the model is representative of conditions in
the bay. The octanol–water (KOW) and octanol–air (KOA)
partition coefficients of the PCB congeners that were used in
the model calculations are summarized in Supplemental Data
Table S4, which lists the freshwater-based KOWvalues at the
mean ambient water temperature of the bay (14.98C) and their
saltwater equivalents derived following Xie et al. [12]. The
saltwater-based KOWvalues were used in the calculations for
fish. The freshwater-based KOWvalues at 37.58C were used to
represent partitioning between lipids and aqueous media (e.g.,
urine) in warm-blooded mammals and birds. Supplemental
Data Table S4 also includes the KOAvalues at 37.58C, which
are used to estimate the exchange of PCBs between warm-
blooded animals and the air via the lungs. The input variables
used to characterize the environmental conditions in the bay are
included in Supplemental Data Table S5. The body weight and
lipid content of the species represented in the San Francisco
Bay food web model are listed in Supplemental Data Table S1.
They include 23 species, several age classes, male and female
animals, and their offspring and eggs. Supplemental Data Table
S6 details the selection of biological parameters for each
organism in the food web model. Supplemental Data
Table S7 includes the metabolic biotransformation rate con-
stants used in the model. Supplemental Data Tables S2 and S3
list the feeding preferences of the various species represented in
the model.
Model calculations and evaluation
The model is constructed in Microsoft Excel 2000TM(http://
www.rem.sfu.ca/toxicology/models/models.htm).Inthemodel,
the concentration in the sediments is presented in a logarithmic
format as log CS, such that the log normal distribution of the
sediment concentration can be presented as a normal distribu-
tion of log CS. The model outcome, i.e., the BSAF, is also
presented in a logarithmic format as log BSAF, which provides
the advantage that the log normal distribution of the BSAF can
be presented as a normal distribution of log BSAF. The model
can be applied in a forward manner to predict concentrations in
biota based on sediment concentrations or in a backward
manner to predict concentrations in sediment based on biota
concentrations.
In the forward application of the model, the actual distri-
butionofconcentrationsinthesedimentsisusedtocalculate the
concentration distributions in various species in the bay accord-
ing to
logCB¼ logBSAF þ logCS
(5)
The frequency distribution of concentrations in the target
organismscanbeusedtodeterminetherisksofexceedingtarget
or toxic threshold concentrations (Fig. 2). The effect of
remediation efforts on bay-wide PCB concentrations can be
explored with the current model by entering the anticipated or
actual spatialconcentrationdistributionofCSafter remediation.
In the backward application of the model (Fig. 2), the
concentration in the sediment expected to meet ecological
and/or human health criteria (CS) is calculated based on the
target PCB concentration in a fish or wildlife species (CB)
according to
logCS¼ logCB?logBSAF(6)
Uncertainty in the BSAF can produce a distribution of
concentrations in the sediments that meets the target.
Sensitivity analysis
The PCB food web bioaccumulation model for San Fran-
cisco Bay was evaluated by using a sensitivity analysis, a
model-performance analysis, and an uncertainty analysis.
The sensitivity analysis assesses the impact of variability or
error in the model’s state variables (e.g., organism weight, lipid
content, temperature) on the model outcome (i.e., the BSAF of
total PCBs in bay fish and wildlife) and is detailed in the
Supplemental Data.
Model testing and performance analysis
The model performance analysis evaluated the accuracy of
the model by comparing model predicted BSAFPto independ-
ent, observed BSAFOof PCB congeners. It involved entering
the geometric mean PCB congener concentrations in sediment
and water and calculating the concentrations in biota and
corresponding BSAFP. The observed BSAF (BSAFO) of PCB
congeners andPPCBs were calculated from measured con-
centrations in biota and sediments as CB/CS. Observed PCB
concentrations in sediments; filter feeders Mytilus californianus
(California mussels) and Crassostrea gigas (Pacific oyster);
three fish species, i.e., jack smelt (Atherinopsis californiensis),
white croaker (Genyonemus lineatus), and shiner surfperch
(Cymatogaster aggregate); and eggs from a resident bird
species (i.e., the double-crested cormorant, Phalacrocorax
auritus) were collected as part of regional monitoring programs
(RMPs) in 1999, 2000, and 2001. Harbor seals were sampled
between 1989 and 1993 as detailed in the Supplemental Data,
and eggs were collected from year-round colony residents that
eat fish from San Francisco Bay [13]. No model calibration
efforts were undertaken.
The mean model bias (MB) derived on a congener-specific
basis can be used as a measure of model performance for each
species as
MBj¼ 10
P
n
i¼1
log BSAFP;i=BSAF0;i
ðÞ½?
n
??
(7)
MBjisthegeometricmean(assumingalognormaldistributionof
theratioBSAFP,i/BSAFO,i)oftheratioofpredictedandobserved
BSAFs for all PCB congeners, i, in a particular species, j,
included in the analysis.
To express model performance forPPCBs quantitatively,
we used the model bias MB?, which is derived for each species
San Francisco Bay bioaccumulation model
Environ. Toxicol. Chem. 29, 2010 1389

Page 6

as
MB?
j¼ 10
P
m
i¼1
log BSAFP;SPCB=SSAF0;SPCB
ðÞ½?
m
??
(8)
MBj?isthegeometricmeanoftheratioofthepredictedBSAFof
PPCB (BSAFP,PPCB) and the observed BSAF of
(BSAFO,PPCB) for all observations, m, in species j.
The model bias (MB or MB?) is a measure of the systematic
overprediction (MB > 1) or underprediction (MB < 1) of the
model. In the calculation of MB, over- and underestimations of
the observed BSAF values have a tendency to cancel out.
Hence, MB tracks the central tendency of the ability of the
model to predict PCB congener concentrations. It is a useful
measure of model performance if total PCBs (PPCB) are of
primaryinterest.Thevariabilityofover-andunderestimationof
measured values is represented by the 95% confidence interval
(CI) of MB,i.e., 95% CI¼antilog(log MB?[tn,0.05?log stand-
ard deviation]). The 95% CI represents the range of BSAFs that
includes 95% of the observed BSAFs. It is a measure of the
uncertainty of the model predictions. Because of the log normal
distribution of the ratio of predicted and observed BSAFs, this
variability can be expressed as a factor (rather than a term) of
the geometric mean. The model’s performance improves when
MB and MB?approach 1.0 and their 95% CIs become smaller.
Model bias and MB?and their 95% CIs represent several
PPCB
sources of error, including model parameterization errors and
errors in model structure and philosophy, as well as analytical
and sampling errors in the empirical data (e.g., chemical con-
centrations in water, sediment, and biota) and natural, spatial,
and temporalvariabilityin theempirical datausedinthe model-
performance analysis.
Uncertainty analysis
Uncertainty in the model input parameters (i.e., log CS) and
in the model calculations (i.e., log BSAF) are propagated in the
estimate of log CBin terms of the standard deviation, SDCB, of
log CB (i.e., the geometric mean concentration). SDCB is
calculated from the standard deviation of log BSAF (SDBSAF)
and the standard deviation of log CS(SDCS) as
SDCB¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
SD2
CSþSD2
BSAF
??
q
(9)
The SDCSwas determined by representingPPCB concentra-
tions in sediment samples collected from the bay in terms of a
single log normal distribution with a mean log CB, which is the
geometric meanPPCB concentration in the sediment, and a
standarddeviationSDCS.The SDBSAFwasdeterminedastheSD
of the frequency distribution for log (BSAFO/BSAFP), where
BSAFOis the ratio of observed concentrations in biota, CB, and
the geometric mean concentration in the sediments, CS, and
BSAFPis the ratio of the calculated concentrations in biota, CB,
Fig. 2. Conceptual diagram illustrating the application of the model for risk assessment (i.e., calculation of the fraction of the population with concentrations
exceeding the threshold effect concentration [TEC]) in the forward calculation and the derivation of target concentrations for remediation in the backward
calculation.
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Page 7

and the geometric mean concentration in the sediments, CS. For
every observed concentration, CB, there is one BSAFO/BSAFP.
MultipleobservationsofCBcreatealognormaldistribution,and
SDBSAFis the SD of this distribution. One of the advantages of
using empirical observations to assess uncertainty is that it
includes many sources of uncertainty, whereas Monte Carlo
simulation is limited to model parameterization uncertainty.
Because uncertainty in observedPPCB concentrations in biota
reflects spatial variation inPPCB concentrations in sediments,
which is specifically considered by SDCSin Equation 9, the
estimated uncertainty in CBmay be somewhat overestimated by
this method. However, the spatial resolution of the monitoring
program for biota concentrations was quite limited and did not
includethefullgeographicdistributionofthebay.Asaresult,the
effect of double counting uncertainty resulting from spatial
distribution in sediment concentrations on the estimation of
uncertainty in CBis likely small.
Uncertainty analysis through Monte Carlo simulation was
considered (supporting document) but found to be problematic
because of the interdependence of state variables and lack of
data to define uncertainty distributions for several state varia-
bles. The interdependence of several state variables, including
feeding rates, growth rates, fecal egestion rates, and feeding
preferences, caused inconsistencies in the energy and mass
balance of the model. The associated error was deemed to be
toolargefortheMonteCarlosimulationstoprovidemeaningful
estimates of model uncertainty.
Model application for risk assessment
ToassesstherisksofPPCBconcentrationsoncertaintarget
species in San Francisco Bay, we compiledPPCB concen-
trations for 1,284 sediment samples collected from the bay
between 1999 and 2001 under the RMP sediment sampling
program and expressed the concentrations in terms of a single
log normal distribution. Equations 5 and 9 were then used to
calculate log normal distributions ofPPCB concentrations in
biota species. The resulting frequency distributions were then
compared with selected ecological and human health-based
threshold effect concentrations (Table 1). The ecological risks
of PCB concentrations in harbor seals were assessed by com-
paring the calculated PCB concentrations with a threshold
effect concentration (TEC) for total PCBs of 11mg/g lipid.
The TEC is the geometric mean of the no-observed-adverse-
effects level (NOAEL; 5.2mg/g lipid) and the lowest-observed-
adverse-effects level (LOAEL; 25mg/g lipid) as proposed by
Kannan et al. [14] based on studies by Boon et al. [10] and
Brouwer et al. [15]. Wet-weight-based concentrations of 3.6 to
6.8ppm, reported and reviewed by Hoffman et al. [16], were
selected to estimate ecological risks of total PCBs in double-
crested cormorants. These concentrations were associated with
embryonicmortality,beakdeformities,andclubfootinthefield.
To simplify the characterization of possible effects on double-
crested cormorants, we used an LOAEL of 5,000mg/kg wet-
weight body mass. Wet-weight-based concentrations of 6 to
26ppm in eggs, reported and reviewed by Hoffman et al. [16]
and based on data by Kubiak et al. [17], Hoffman et al. [18],and
Tillit et al. [19], were used to estimate the potential for PCBs to
cause toxic effects in Forster’s terns. These concentrations in
eggswereassociatedwithembryonicmortality,impaired repro-
ductive success, subcutaneous edema of head and neck, aryl
hydrocarbon hydroxylase induction, and beak deformities [16].
For the characterization of the toxic effects in Forster’s terns,
we used an LOAEL of 6,000mg/kg wet weight in eggs in the
model.Wealsocalculated thePPCBconcentrationin eachfish
species associated with an upper bound excess lifetime human
cancer risk of 10?5and a human health hazard index for 1 in
humans consuming fish from San Francisco Bay. This is
described in the Supplemental Data.
Model application to derive sediment target levels
To derive geometric meanPPCB concentrations expected
to meet particularPPCB concentrations in fish and wildlife
associated with various human health and ecological risks
(listedinTable1),weusedEquation6.Oneoftheconsequences
of the calculation of geometric means is that, at the calculated
sediment concentrations, approximately half the receptor pop-
ulationof thebay canbe expectedto contain concentrations that
exceed the target values, whereas the PCB concentration in the
other half of the population will be less than the target con-
centrations. An alternative application of the model is the
calculation of the geometric mean PCB concentration in the
bay sediments that is expected to result in a 5% exceedence of
target concentrations. To do this, we used Equation 5 and
changed the geometric mean
sediments (while maintaining SDCS) to produce a
concentration frequency distribution in biota at which 5% of
the expected PCB concentrations in biota are in excess of the
human health and ecological target concentrations for toxicity.
In essence, this involves shifting the PCB concentration dis-
tributions in the target organisms to make the upper 95% CI
equaltothecriterionvalue(e.g.,TEC)ratherthanthegeometric
mean of the distribution.
PPCB concentrations in the
PPCB
RESULTS AND DISCUSSION
Sensitivity analysis
Supplemental Data Tables S8 to S11 illustrate the sensitivity
of the abiotic and biotic state variables of the model. Certain
parameters such as organism water content and water absorp-
tion efficiency have little impact on model outputs. Other
parameterssuchasthelipidcontent(andorganiccarboncontent
in phytoplankton), lipid and nonlipid organic carbon (i.e.,
protein and carbohydrate), and digestion efficiencies are among
the most sensitive parameters in the model. These parameters
control the lipid and organic matter content in the gastrointes-
tinal tract of an organism following a feeding event and are
largely responsible for the dietary biomagnification of PCBs.
The growth rate (in, e.g., phytoplankton and seals) and the
coefficients used to calculate the growth rate (in invertebrates
and fish) are also sensitive model state variables. Organism
growth (concentration dilution) is an important process con-
Table 1. Internal concentrations in San Francisco Bay, California, USA,
sport fish and wildlife associated with a 1:100,000 upper bound excess
human cancer risk, a human health hazard index in excess of 1, and the no-
observed-adverse effect level (NOAEL), lowest-observed-adverse effect
level (LOAEL), and threshold effect concentration (TEC)
EndpointOrganismConcentration
Human excess lifetime
cancer risk (10?5)
Human health hazard (H¼1)
LOAEL
LOAEL
TEC
LOAEL
NOAEL
Fish52mg/kg wet wt
Fish207mg/kg wet wt
5,000mg/kg wet wt
6,000mg/kg wet wt
11,000mg/kg lipid
25,000mg/kg lipid
5,000mg/kg lipid
Cormorant egg
Tern egg
Harbor seal
Harbor seal
Harbor seal
San Francisco Bay bioaccumulation model
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Page 8

trolling the total body concentration for higher KOWPCBs that
are not effectively eliminated by other loss processes such as
respiration and biotransformation.
Model testing and performance analysis
Figure 3 and Supplemental Data Figure S5 to S11 illustrate
model-predicted and observed BSAFs for the 40 PCB conge-
ners included in the RMP monitoring program. The figures
show that the model-predicted BSAFs are within the range of
observed BSAFs. The figures further illustrate that the congener
patterns of PCBs in all of the organisms are reasonably well
reproduced by the model. Figure 4 illustrates model-predicted
and observed BSAFs forPPCB. The observed log BSAF of
PPCB contains 95% CIs ranging between approximately 0.4
(for cormorants) and 1.0 (for male harbor seals) and reflecting
considerable variability among the observed BSAFs in the bay.
Figure 4 illustrates that the model-predicted BSAFs ofPPCB
are well within the range of the observed values.
Table 2 illustrates that the mean MB among the 40 PCB
congeners ranges between 0.96 for female harbor seals to 1.56
for male harbor seals and is close to 1 for all organisms. The
mean MB?for the BSAF ofPPCB ranges between 0.64 for
female harbor seals to 1.05 for benthic invertebrates and jack
smelt and is also close to 1 for all organisms. Thus, the model
produces little systematic over- or underestimation of PCB
congener concentrations.
Uncertainty analysis
Table 2 shows that the 95% CIs of the mean MB (congeners)
range between factors of 3.74 for shiner surfperch and 7.43 for
male harbor seals. The 95% CIs of the mean MB?(PPCBs)
range between factors of 2.04 for cormorant eggs and 9.65 for
male harbor seals. This illustrates that over- and underestima-
tions of the BSAF for individual PCB congeners or for indi-
viduals of a specific species can be considerable even if the
predicted mean concentration values are close to the observed
values. The CIs can be viewed as the uncertainty in the BSAF
model estimates.
Model application for risk assessment
Table H in the Supplemental Data compilesPPCB con-
centrations from a total of 1,284 sediment samples collected
fromSanFranciscoBaybetween 1999and 2001undertheRMP
sediment-sampling program. It illustrates the distribution of
PCB concentrations in the bay and shows substantial variability
in thePPCB concentrations in the sediments of the various
sections of the bay (i.e., North, Central, and South). ThePPCB
concentration distributions range by approximately two orders
of magnitude in the northern and southern sections of the bay
and by three orders of magnitude in the central section of the
bay. ThePPCB concentrations in the northern section are
somewhat lower than those in the central and southern sections
of the bay. Figure 5 compiles all the data in a single bay-wide
concentration distribution, which was then represented by a
single log normal distribution to calculate bay-wide concen-
tration distributions. Figure 5 shows that the log normal dis-
tribution that was used in the model to represent the current
level of PCB contamination in the bay is in reasonable agree-
ment with the measured distribution of the 1,284 sediment
concentration data from the bay. The geometric mean of this
distribution is 11.6mg/kg dry sediment. The 95% CI of the
geometric mean
PPCB concentration in the sediments is
equivalent to a factor of 7.4. This indicates that fish and wildlife
in the bay are exposed to PCB concentrations that vary sub-
stantially.
Figure 6 illustrates the results of the model calculations of
the
PPCB concentration in some key species of the San
Francisco Bay food web. It shows predictedPPCB concen-
tration distributions (calculated with Eqn. 9) that include
uncertainty in the BSAF as well as the variability in thePPCB
concentrations in the sediments. The distributions of the pre-
dicted PCB concentrations in biota are therefore not solely a
reflection of model uncertainty. They also reflect the variability
Fig. 3. Model-predicted (gray columns) and observed (black columns;?1 SD) biota–sediment bioaccumulation factors (BSAFs in kg dry sediment/kg wet wt
organism)ofapproximately40polychlorinatedbiphenyl(PCB)congenersinadultmaleharborseals(Phocavitulinarichardsi)inSanFranciscoBay,California,
USA.
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Page 9

in PCB concentrations in the sediments of the bay. In fact, the
variability ofthe PCB concentrations in the bay sediments is the
largest contributor to the 95% CIs of the predicted geometric
meanPPCB concentrations in biota species. Figure 6 also
illustrates the distributions of observed PCB concentrations,
which are narrower than the predicted distribution of the PCB
concentrations for the entire bay. This is because animal-
sampling programs were carried out in certain areas of the
bay, which causes observed concentration distributions to
underrepresent the spatial distribution of PCB concentrations
in biota in the entire bay.
Figure 6 shows that approximately 80% of the bay-wide
male and 60% of the bay-wide female harbor seals are expected
to containPPCB concentrations in excess of the threshold
effect concentration of 11mg/kg lipid. It also shows that
approximately 20% of the resident cormorant egg population
in the bay is expected to exceed the LOAEL. Approximately
77% of the bay-wide white croaker population is expected to
contain PCB concentrations that, based on the risk assessment
scenariosusedinthepresentstudy,willproduceanupperbound
excess cancer risk of 1?10?5for consumers of fish. Half of the
white croaker population in the bay can be expected to contain
PCB concentrations that exceed the maximum acceptable daily
intake (i.e., H ? 1) for bay fish consumers considered in the risk
assessment scenario.
Model application to derive sediment target levels
Table 3 illustrates the results of the calculations conducted
to explore possible target concentrations for PCB concentra-
tions in the sediments that meet various human health and
ecological risk criteria. The geometric meanPPCB concen-
tration in the sediments that causes a geometric mean con-
centration in cormorant eggs equal to the LOAEL is
approximately 31mg/kg dry wt, i.e., substantially greater than
the current geometric meanPPCB concentration at the time
of the study of 11.6mg/kg dry wt. However, if only 5% of the
eggs are to contain concentrations equal to or below the
LOAEL, a geometric mean concentration less than 12mg/kg
dry wt is required. Bay-wide geometric mean PCB concen-
trations in sediments of 5.9 and 9.5mg/kg dry wt are expected
to cause geometric mean concentrations equal to the TEC in
adult male and female harbor seals, respectively. Geometric
mean concentrations less than 0.58 and 1.5mg/kg dry wt are
required to cause 95% of the male and female harbor seals in
the bay to fall below the TEC. It is important to stress that, in
the calculation of the 5% exceedence rate of threshold effect
concentrations, we have used the expected bay-wide distribu-
tions calculated with the help of past data. Remediation can
produce significant changes in bay-wide PCB concentration
distributions. These changes can affect the magnitude of the
Table 2. Themeanmodelbiasforspecificcongeners(MB)andforthecombinedtotalPCBcongener(PPCBs)concentrations(MB?),95%confidenceintervals
(95% CI), number of comparisons (n), and logarithmic equivalents, i.e., log MB and log MB?and their standard deviations (SD), for several species of San
Francisco Bay, California, USA
Species Name
MB (n) 95% CIa
Log MB (SD)
MB?(n) 95% CIa
Log MB?(SD)
California mussel
Pacific oyster
Shiner surfperch
Jack smelt
White croaker
Cormorant egg
Male harbor seal
Female harbor seal
Mytilus californianus
Crassostrea gigas
Cymatogaster aggregate
Atherinopsis californiensis
Genyonemus lineatus
Phalacrocorax auritus
Phoca vitulina
Phoca vitulina
1.33 (32) 0.37–4.78
1.34 (32) 0.37–4.86
1.00 (38) 0.27–3.74
1.30 (35) 0.43–3.94
1.31 (38) 0.33–5.18
1.33 (38) 0.39–4.50
1.51 (28) 0.31–7.43
0.96 (28) 0.17–5.38
0.12 (0.28)
0.13 (0.29)
0.00 (0.29)
0.12 (0.24)
0.12 (0.31)
0.12 (0.27)
0.18 (0.35)
?0.02 (0.38)
1.05 (13) 0.31–3.52
1.05 (9) 0.32–3.47
0.75 (18) 0.23–2.43
1.05 (15) 0.27–4.07
0.93 (8) 0.35–2.47
0.79 (8) 0.31–2.04
0.95 (4) 0.09–9.69
0.64 (2) 0.10–4.02
0.02 (0.25)
0.02 (0.23)
?0.13 (0.24)
0.02 (0.28)
?0.04 (0.21)
?0.10 (0.18)
?0.02 (0.36)
?0.19 (0.19)
a95% confidence interval (CI)¼antilog (log MB?[tn,0.05?standard deviation]).
Fig. 4. Model-predicted(graycolumns)andobserved(blackcolumns)mean
biota–sediment bioaccumulation factors (BSAFs in kg dry sediment/kg wet
wtorganism)oftotalpolychlorinatedbiphenyls(PPCBs)inseveralspecies
inSanFranciscoBay,California,USA.Errorbarsrepresent95%confidence
intervals.
Fig. 5. Distributions of the total combined PCB congener (PPCB)
concentrations in sediments of San Francisco Bay, California, USA. Solid
linerepresentsactualdistributionbasedon1,284sedimentconcentrationdata
collected in San Francisco Bay between 1999 and 2001. Dashed line
represents the distribution used in the model application.
San Francisco Bay bioaccumulation model
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Page 10

95% CIs. For example, when remediation involves PCB hot
spots in the bay, the after-remediation 95% CIs of bay-wide
PCB sediment concentration distributions can be expected to
be somewhat narrower than the before-remediation distribu-
tions. This implies that current estimates of geometric mean
concentrations associated with the 5% exceedence of threshold
effect concentrations may somewhat overestimate the extent
of the required concentration reduction. The scenarios used for
human health risk assessment indicate that geometric mean
PCB concentrations in the sediments equal to or less than
3.8mg/kg dry wt are required for the consumption of white
croaker at the assumed consumption rate to produce a 10?5
upper bound for human lifetime cancer risk. The selected
human health and ecological risk criteria are subjects of debate
and judgment dependent on ecological and human health
objectives and the state of science; therefore, we have con-
structed the model such that new criteria for CBcan be easily
introduced in Equation 6.
Fig. 6. Normal probability distributions for model calculated (solid line) and observed (dashed line) total combined PCB congener (PPCB) concentrations
inSanFranciscoBay,California,USA,fishandcormoranteggs(inmg/kgwetwt)andinadultmaleandfemaleharborseals(inmg/kglipid)fortheperiodbetween
1999and2001.HumanconsumptioncancerriskendpointRof10?5,humanhealthhazardindexHof1.0,lowest-observed-adverseeffectlevel(LOAEL)of5mg/g
wet wt body mass for cormorants, and threshold effect concentration (TEC) of 11mg/kg lipid in harbor seals.
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SUPPLEMENTAL DATA
Food web bioaccumulation model for polychlorinated
biphenyls in San Francisco Bay, California, USA. (1,818 KB
DOC)
Acknowledgement—TheauthorsacknowledgetheCleanEstuaryPartnership
(CEP) for their help and insights throughout the completion of the study as
well as their financial support of the study. Many individuals were crucial to
the success of the present study. They are acknowledged in the supporting
information.
REFERENCES
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15. BrouwerA,ReijndersPJH,KoemanJH.1989.Polychlorinatedbiphenyl
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Table 3. San FranciscoBay,California,USA, geometricmean target concentrations (in mg/kgdry wt) of combinedtotal PCB congeners(PPCBs) in sediment
expected to meet various human health and ecological criteria: no-observed-adverse effect level(NOAEL), lowest-observed-adverse effect level (LOAEL), and
threshold effect concentration (TEC)
Criterion Organism
PPCB
4.3
17
18
73
3.2
14
24
14
4.6
1.6
6.2
3.6
Geometric mean upper bound excess human lifetime cancer risk of 10?5among bay fish consumers
Geometric mean human health hazard (H¼1)
Geometric mean upper bound excess human lifetime cancer risk of 10?5among bay fish consumers
Geometric mean human health hazard (H¼1)
Geometric mean upper bound excess human lifetime cancer risk of 10?5among bay fish consumers
Geometric mean human health hazard (H¼1)
Geometric mean concentration equal to the LOAEL
5% of eggs exceed the LOAEL
Geometric mean concentration equal to the TEC (11,000mg/kg lipid)
5% of animals exceed the TEC (11,000mg/kg lipid)
Geometric mean concentration equal to the TEC (11,000mg/kg lipid)
5% of animals exceed the TEC (11,000mg/kg lipid)
Shiner surfperch
Shiner surfperch
Jack smelt
Jack smelt
White croaker
White croaker
Cormorant egg
Cormorant egg
Male harbor seal
Male harbor seal
Female harbor seal
Female harbor seal
San Francisco Bay bioaccumulation model
Environ. Toxicol. Chem. 29, 20101395