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Michigan State
University

 

 

This is to certify that the
dissertation entitled

Exposure and Risk of PCBs to Mink (Mustela vison) at the
Kalamazoo River Superfund Site, Michigan

presented by

Stephanie D. Pastva

has been accepted towards fulfillment
of the requirements for the

PhD. degree in Fisheries and Wildlife

 

 

G/%jor £0erle Saature

MM '7: ‘00 3

Date

MS U is an Affirmative Action/Equal Opportunity Institution

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6/01 cJCIRC/DatoDue.p65-p.15

 

EXPOSURE AND RISK OF POLYCHLORINATED BIPHENYLS TO MINK
(MUSTELA VISON) AT THE KALAMAZOO RIVER SUPERFUND SITE, MICHIGAN

By

Stephanie D. Pastva

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY
Department of Fisheries and Wildlife
2003

ABSTRACT

EXPOSURE AND RISK OF POLYCHLORINATED BIPHENYLS TO MINK

(MUSTELA VISON) AT THE KALAMAZOO RIVER SUPERFUND SITE, MICHIGAN
By
Stephanie D. Pastva
125 kilometers of the Kalamazoo River, located in southwestern Michigan,

has been designated a Superfund site with polychlorinated biphenyls (PCBs) as the
contaminant of concern. Mink are of special concern due to their trophic status and
sensitivity to PCBs. A top-down risk assessment was conducted by measuring
concentrations of total PCBs and TEQs in tissues of mink collected from the
Kalamazoo River area of concern (KRAOC). Mink were caught from areas within
the KRAOC and from Fort Custer Recreation Area (FC), an upstream reference area
on the same river system. Total PCB concentrations, in livers of mink, averaged 2.7
and 2.3 mg PCB/kg w from the KRAOC and FC, respectively. Total TEQs in livers
of mink averaged 300 and 110 pg TEQ/g w from KRAOC and FC respectively.
Previously conducted studies in which mink were fed PCB-contaminated diets were
used to calculate a range of hazard quotients (HQs) based on the no observed
. adverse effect level (NOAEL) and the lowest observed adverse effect level (LOAEL).
For mink livers from KRAOC, total PCB-based HQs ranged from 0.37 to 0.88 and
total TEQ-based HQs ranged from 1.1 to 1.4 (based on a comparison of the mean
exposure level and the LOAEL). For mink livers from FC, total PCB-based HQs
ranged from 0.31 — 0.73 and total TEQ-based HQs ranged from 0.39 — 0.49 (based

on a comparison of the mean exposure level and the LOAEL).

The extent to which mink (Mustela vison), were exposed to PCBs through
their diet and the resulting potential risk was estimated using three different dietary
models. Fish, crayfish, and mammalian species were collected from two sites:
Trowbridge (TB), a former impoundment within the KRAOC and FC. Prey items
were analyzed for total PCB and TEQ concentrations. Total PCB and TEQ
concentrations were greatest in fish species. Identified contents from
gastrointestinal tracts of mink collected from the sites yielded the following dietary
composition: 72% mammals, 14% fish, and 14% crayfish, and was used as one of
the dietary models. At TB, LOAEL-based HQs for total PCBs and TEQs are less
than 1.0 for all dietary models except the literature-based model in which fish
comprise 85% of the mink’s diet. Calculated risk, based on dietary models, was
slightly less than risk calculations based on site-specific mink tissue residues. Both
approaches were in agreement that the degree of exposure to PCBs and TEQs were
near the threshold for effects on reproduction in mink.

Multiple lines of evidence were considered, including the habitat quality,
number of animals trapped per territory, age and sex distributions, gross
morphology, liver histology, bacculum weight, and body weight. Based on these
multiple lines of evidence, the observed concentrations of PCBs measured in the
livers of mink in the KRAOC are unlikely sufficient to cause a reduction in the

number of mink inhabiting the KRAOC.

ACKNOWLEDGEMENTS

Funding was provided through a grant from the Kalamazoo River Study
Group to Michigan State University. This research would not have been
successfully completed without the assistance of the numerous people : Scott
Fitzgerald - necropsies; Steve Bursian - necropsies and equipment; Kevin Allen,
Jim Burns, Dan Keith, Daniel Villeneuve, and Alan Zwiemik - trapping; K.
Kannan, Dong-Hoon Khim, George Klemolin, and Jamie Kober - laboratory
support and analysis; Ryan Holem- organizational support. Additional thanks to
the MSU Kellog Biological Station for housing and laboratory space during
sample collection. Special thanks are extended to Alan L. Blankenship, Patrick
W. Bradley, Paul D. Jones, Denise Kay, Arianne M. Neigh, Karl D. Strause,
Matthew J. Zwiemik who are coauthors on the published manuscripts. They
have been involved in conducting the field research, laboratory work, quality
assurance, and their input was extremely valuable during the writing process.
Above all, my advisor John Giesy, deserves many thanks... for obtaining funding
for the research, for all the words of encouragement along the way, and for all

the great opportunities.

On a personal note, I need to thank my fiance, Scott, for all the little things
he did enabling me to work harder and longer and keeping me sane at the same
time. My friends have also offered prayers, support, and encouragement through
the process. Finally, thanks to God for putting me in the right place at the right
time and surrounded by awesome coworkers and friends.

iv

TABLE OF CONTENTS

LIST OF TABLES ............................................................................................... vii
LIST OF FIGURES ............................................................................................ viii
CHAPTER ONE: ................................................................................................... 1
Risks of Polychlorinated Biphenyls to Mink (Mustela vison) at the
Kalamazoo River Superfund Site, Michigan. .................................................... 1
Introduction ......................................................................................................... 1
Methodology ........................................................................................................ 5
Sample Collection ............................................................................................. 5
Necropsy ........................................................................................................... 5
Chemical Analysis ............................................................................................. 6
TEQ Computation .............................................................................................. 8
Toxicity Reference Values ................................................................................. 9
Results ............................................................................................................... 11
Mink ................................................................................................................. 11
Total PCB and TEQ concentrations ................................................................ 12
Discussion ......................................................................................................... 18
CHAPTER TWO: ................................................................................................ 30
Assessment of Risk Posed by Polychlorinated Biphenyls in the Diet of Mink
(Mustela vison) at the Kalamazoo River Superfund Site, Michigan .............. 30
Introduction ....................................................................................................... 30
Methods ............................................................................................................. 34
Sample Collection and Preparation ................................................................. 34
PCB Quantification and TEQ Computation ..................................................... 36

Site-Specific Dietary Analysis .......................................................................... 37

Average Potential Daily Dose Calculations ..................................................... 37
Toxicity Reference Values ............................................................................... 39
Results ............................................................................................................... 42
Concentrations of Total PCB and TEQ ............................................................ 42
Site-Specific Diet Composition ........................................................................ 42
Risk Calculations ............................................................................................. 46
Discussion ......................................................................................................... 50
Agreement in TRVs among studies ................................................................. 50
Dietary modeling ............................................................................................. 51
Comparison of top-down and bottom-up methodologies ................................. 52
CHAPTER THREE ............................................................................................. 57
Habitat Characterization and Mink (Mustela vison) Habitat Quality of the
Kalamazoo River Superfund Site, MI ............................................................... 57
Introduction ....................................................................................................... 57
Methods ............................................................................................................. 60
Results and Discussion ................................................................................... 65
BIBLIOGRAPHY ................................................................................................ 71

vi

LIST OF TABLES

Table 1. Hazard quotients calculated using Total PCB concentrations and Total
TEQS in mink livers collected from the Kalamazoo River. The TRVs used
to calculate HQs based on total PCBs are from feeding studies conducted by
Halbrook et al. (Halbrook et al. 1999) and Bursian et al. (Bursian et al. 2002).
The TRVs used to calculate total HOS based on TEQs are based upon mink
feeding studies by Heaton et al. (Heaton et al. 1995) and Bursian et al.
(Bursian et al. 2002). ................................................................................... 17

Table 2. Range of total PCB concentrations (mg/kg w) in mink liver reported in
North America .............................................................................................. 19

Table 3. Toxicity reference values (T RVs) used to calculate total PCB and TEQ
NOAEL and LOAEL-based hazard quotients ............................................... 41

Table 4. Total PCBs (mg PCB/kg ww) and TEQs (ng TEQ/kg w) in prey items
collected from two sites on the Kalamazoo River. ....................................... 43

Table 5. Range of average potential daily doses (ADDpot), based on mean and
the upper 95% confidence limit (U95% CL) of prey items for total PCBs (mg
PCB/kg bw/dand TEQS (ng TEQ/kg w/d), at both Trowbridge (TB) and Fort
Custer (FC). ................................................................................................. 47

Table 6. Hazard quotients (HQ) values based on mean and the upper 95%
confidence limit (U95% CL) of potential average daily doses of total PCBs
and TEQs, when assuming three different dietary compositions for mink.
The TRVs used to calculate HQs were based on feeding studies (Brunstrom
et al. 2001;Bursian et al. 2002;Halbrook et al. 1999;Heaton et al. 1995). The
range of calculated HQs is a result of using more than one TRV. ............... 48

vii

LIST OF FIGURES

Figure 1. Map of Kalamazoo River Area of Concern (KRAOC). The inset map of
Michigan indicates the locations of the two counties in which the study was
conducted. The KRAOC extends from Morrow Lake dam to Lake Michigan.
The mink collection area (MCA) in KRAOC is indicated by a box surrounding
the river. Fort Custer (FC) is the upstream reference area and is also
indicated by a box surrounding the river. ....................................................... 2

Figure 2. Total PCBs (mg/kg w) in mink collected from Kalamazoo River Area
of Concern (KRAOC) and the Fort Custer upstream reference area (FC). ..13

Figure 3. Total TEQ concentrations (pg/g w) in mink from the Kalamazoo River.
..................................................................................................................... 14

Figure 4. Relative contribution of individual PCB congeners to total TEQS in
individual mink. The last two bars to the right of the figure and represent the
arithmetic mean contribution of individual congeners to total TEQs in
KRAOC mink livers (n=9) and FC mink livers (n=3) ..................................... 15

Figure 5. Map of Kalamazoo River Area of Concern. The inset map of Michigan
indicates the locations of the two counties in which the study was conducted.
..................................................................................................................... 31

Figure 6. Mean total PCBs (mg/kg ww with 95% confidence intervals) in prey
items collected from the Trowbridge (TB) and Fort Custer (FC), an upstream
reference area, sections of the Kalamazoo River. Sample sizes and p-
values (Student t-test) comparing mean PCB concentrations between sites
are also presented. ...................................................................................... 44

Figure 7. Mean concentrations of TEQS (ng/kg ww, with 95% confidence
intervals) in prey items collected from Trowbridge (TB) and Fort Custer (FC),
an upstream reference area, sections of the Kalamazoo River. Sample
sizes and p-values (Student t-test) comparing mean PCB concentrations
between sites are also presented. ............................................................... 45

Figure 8. Comparison of HO values based on predicted concentrations of total
PCB determined based on dietary exposures or concentrations measured in
the livers of mink at Fort Custer (FC) and Trowbridge (TB). The arrows
represent the H03 of three mink dietary models. The solid vertical bars
represent the upper and lower 95% confidence limits of H05 estimated from
PCB concentrations in mink livers. The TRVs used to calculate HQs are
based upon a mink feeding study conducted by Bursian et al. (Bursian et al.
2002). .......................................................................................................... 53

viii

Figure 9. Comparison of HO values based on predicted concentrations of TEQ
determined based on dietary exposures to HQs based on TEQ
concentrations measured in the livers of mink at Fort Custer (FC) and
Trowbridge (TB). The arrows represent the H08 of three mink dietary
models. The solid vertical bars represent the H03 estimated from TEQ
concentrations in mink livers. The TRVs used to calculate HQs are based
upon a mink feeding study conducted by Bursian et al. (Bursian et al. 2002).
..................................................................................................................... 54

Figure 10.. Description of the assumptions, variables, and components used to
calculate HSI, as described by Loukmas (Loukmas 1994) .......................... 61

Figure 11. Suitability index scores for percent canopy and shoreline cover (Allen
1986). .......................................................................................................... 62

Figure 12. . Extent of Kalamazoo River through Kalamazoo and Allegan
counties with insets indicating close-up views of mink habitat suitability maps.
..................................................................................................................... 67

Figure 13. Mink habitat quality at the furthest downstream stretch of the
Kalamazoo River. This area extends from Lake Allegan to New Richmond.
This figure is presented in color. .................................................................. 68

Figure 14. Mink habitat quality through the middle section of river, extending
from D-Ave in Kalamazoo to the City of Allegan, and includes the
Trowbridge (TB) impoundment. This figure is presented in color ................ 69

Figure 15. Mink habitat quality through the Fort Custer section of Kalamazoo
River. This figure is presented in color ........................................................ 70

CHAPTER ONE:

Risks of Polychlorinated Biphenyls to Mink (Mustela vison) at

the Kalamazoo River Superfund Site, Michigan.

Introduction

In 1990, approximately eighty miles of the Kalamazoo River was
designated a Superfund site, referred to as the Kalamazoo River Area of
Concern (KRAOC). The site extends from Morrow Dam in Kalamazoo County to
Lake Michigan (Figure 1). The release of polychlorinated biphenyls (PCBs), the
contaminant of concern (COC), resulted primarily from PCB-contaminated waste
discharged from the recycling and processing of carbonless copy paper (CDM
1999). During the period of 1957 — 1971, the ink solvent used in carbonless copy
paper contained PCBs, primarily Aroclor 1242 (Durfee et al. 1976). A lesser
amount of PCBs may have also been added to inks and other additives, primarily

Aroclor 1254 (Durfee et al. 1976).

The mink (Mustela vison) is a semi-aquatic member of the mustelidae
family commonly found in waterways throughout North America, including
Michigan (U.S.Environmental Protection Agency 1993). Mink have been shown
to be one of the more sensitive mammals to the effects of PCBs, especially to
effects such as kit weight, litter size and, kit mortality (Aulerich et al. 1971;
Aulerich et al. 1973; Brunstrom et al. 2001; Heaton et al. 1995; Hochstein et al.

1998; Kihlstrom et al. 1992; Restum et al. 1998). Due to their sensitivity to PCBs

 

Lake

 

 

 

 

 

 

 

 

 

 

 

Michigan
MCA
Allegan County
F

Morrow

Lake Dam
[IT
LKalamazon__,

Figure 1. Map of Kalamazoo River Area of Concern (KRAOC). The inset map of
Michigan indicates the locations of the two counties in which the study was
conducted. The KRAOC extends from Morrow Lake dam to Lake Michigan. The
mink collection area (MCA) in KRAOC is indicated by a box surrounding the river.
Fort Custer (FC) is the upstream reference area and is also indicated by a box

surrounding the river.

and their relatively great potential for exposure as pisciverous, top predators,
mink often represent the “worst-case scenario” for the exposure of mammals to
persistent contaminants in North American riverine systems. Mink are often used
as a surrogate or sentinel species in risk assessments or monitoring programs,
respectively. Therefore, the mink was selected as a sensitive, indicator of the

effects of PCBs on animals residing in the KRAOC.

A congener-specific approach was utilized in this study since this method
has been shown to more accurately predict adverse affects than Aroclor-based
quantification methods for determination of total PCBs in environmentally
weathered samples (Schwartz and Stalling 1987;Valoppi et al. 1998;Leonards et
al. 1995;Tillitt et al. 1996). Furthermore, the most sensitive biological effects of
PCBs have been attributed to planar congeners that resemble 2,3,7,8-
tetrachlorodibenzo-p-dioxin (2,3,7,8-TCDD) and act through the aryl-hydrocarbon
receptor (AhR). A congener-specific approach allows for the calculation of
2,3,7,8-TCDD equivalents (TEQS) by integrating the total concentrations and
relative potencies of individual congeners identified in a mixture. The data
collected for this study were utilized in two ways: first, all congeners were
summed to obtain total PCB concentrations and secondly, key congeners were

quantified and used to calculate TEQS.

There are two primary approaches for assessing risk to wildlife for
bioaccumulative compounds like PCBs: bottom-up and top-down. In a bottom-up
risk assessment, PCBs are measured at lower levels of the food chain (or even

environmental matrices such as sediment). These models are used to predict an

average daily dose consumed by the species of interest. This estimated dose is
then compared to previously determined effect level doses referred to as toxicity
reference values (TRVs). Alternatively, in a top-down risk assessment, PCB
concentrations are measured in target tissues of the species of interest. These
site-specific tissue residue concentrations are then compared to published tissue
residue-based effects to determine risk. Here we report the results of a top-down
assessment in which concentrations of total PCBs and TEQs were measured in
livers of mink from the KRAOC and Fort Custer recreation area (FC), an
upstream reference area. The results of a bottom-up risk assessment are

presented elsewhere (Pastva et al. 2003a).

Methodology

Sample Collection

Wild mink were trapped throughout the KRAOC and the upstream
reference area, FC, during the winters from 2000-2002. Trapping was conducted
by Michigan State University (MSU) personnel and by local trappers. Collection
kits and oversight were utilized to ensure consistent sample handling and storage.
Collection kits contained aluminum foil, plastic bags, labels, and datasheets for
recording information including date and location of trapped specimen, and also
detailed instructions regarding sample collection, handling, and storage. Skinned

carcasses were frozen before shipment, under chain of custody, to MSU.

Necropsy

Mink carcasses were thawed and a gross necropsy was performed by a
board certified pathologist (Dr. Scott Fitzgerald, MSU). The sex, weight (without
pelt), and length (nose to base of tail) of each mink was determined. Organ
condition was assessed during dissection to determine if there were gross
abnormalities. Liver tissue was removed for PCB analysis and histology and a
tooth was removed for dental cementum analysis to determine age. The jaws
were also removed for histological analysis. Liver histology was performed by
the MSU Animal Health Diagnostics Laboratory (East Lansing, MI), jaw histology
was performed by Kerrie Beckett (MSU Department of Animal Science, East
Lansing, MI), and dental cementum analysis was performed by Matson's

Laboratory (Milltown, MT).

Chemical Analysis

The extraction method used was based on EPA method 3540 (Soxhlet
extraction). A known quantity (approximately 5 g) of liver tissue was
homogenized with anhydrous sodium sulfate (EM Science; Gibbstown, NJ) using
a mortar and pestle. Surrogate standards, PCB #204 (IUPAC) and PCB #30
(AccuStandard , New Haven CT), were added to all samples, blanks, and matrix
spikes before extraction. Samples were refluxed in a Soxhlet extraction
apparatus (VWR Scientific, Plainfield, NJ) for 18 h using 400 ml of 3:1
dichloromethane/hexane (pesticide residue grade). After extraction, extracts
were concentrated by rotary evaporation to a final volume of 11 ml. One ml of
the hexane extract was used for lipid content determination. The remaining 10
ml of extract was passed through a neutral/acidic silica gel column to remove
non-target analytes. Thirty cm glass columns, 15 mm in diameter, were packed
with approximately 0.5 g anhydrous sodium sulfate, 2 9 100-200 mesh size silica
gel (Aldrich; Milwaukee, WI), 2 g 40% sulfuric acid (JT Baker; Phillipsburg, NJ)
impregnated silica gel, and 2 g silica gel. If the extract was particularly dirty,
additional acid hydrolysis was performed. Briefly, 5 ml of concentrated sulfuric
acid was added to the extract and shaken for at least 30 sec. After the
separation of phases, the extract was transferred to another test tube and 5 ml of

water was added to remove acid residues from the extract.

The extract was evaporated to a final volume of 1.0 ml under a stream of
nitrogen. An aliquot of 0.5 ml was transferred to a GC vial for total PCB analysis

while the remaining 0.5 ml was subjected to carbon column chromatography for

the separation of non-ortho-substituted (coplanar) PCB congeners, as described

below.

PCBs including di- and mono-ortho-substituted congeners were quantified
by use of a gas chromatograph (Perkin Elmer AutoSystem) equipped with a 63Ni
electron capture detector (GC-ECD). A fused silica capillary column (Zebron 28-
5; 5%phenylpolysiloxane, 30m x 0.25mm i.d.) having a film thickness of 0.25 pm
was used (Phenomenex; Torrance, CA, USA). The column oven temperature
was programmed to change from 120°C (1 min hold) to 160°C at a rate of
10°C/min (1 min hold) and then to 260°C at a rate of 2°C /min with a final holding
time of 10 min. Injector and detector temperatures were kept at 225°C and
375°C, respectively. Helium and nitrogen were used as carrier and make up gas,
respectively. A solution containing 100 individual PCB congeners with known
composition and content was used as a standard. Congeners were identified by
comparing sample peak retention times to those of the known standard. In
sample extracts, concentrations of each congener were determined by
comparing the peak area to that of the appropriate peak in the standard mixture.
TurboChrom software (Perkin Elmer) was used to integrate the peaks.
Concentrations of all resolved PCB congeners were summed to obtain total PCB

concentrations.

Non-ortho-substituted (coplanar) PCB congeners #77, #81, #126, and
#169 were separated from coeluting congeners and interferences by clean-up on
a carbon column. Briefly, 30 cm glass columns, 15 mm in diameter, were

packed with anhydrous sodium sulfate, carbon dispersed on silica gel (Waco

Chemical, Japan), and anhydrous sodium sulfate. 20 microliters of 50 ug/L
radio-labeled 13C coplanar PCB congener (#77, #81, #126 and #169) standard
mix (Cambridge Isotope Laboratories, Andover MA) in isooctane were added to
each extract. The first fraction, containing loading solvent, washing hexane, and
column elutant of 100 ml 20% dichloromethane in hexane, was archived. After
addition of isooctane as a keeper solvent, the second fraction was eluted with
200 ml of toluene, and contained non-ortho coplanar PCB congeners. The

extract was then concentrated under a stream of nitrogen to a final volume of 20
pl.

Extracts were analyzed by GC-MS on a Hewlett Packard 5890 series ll
gas chromatograph equipped with an HP 5972 series mass selective detector. A
fused silica capillary column (as described above ) was used. Non-ortho-
substituted PCB congeners were detected and confirmed by selected ion
monitoring of the two ions of the molecular cluster. Congener concentrations

were calculated based on ion ratios for the native and 13C congener.

TE 0 Computation

Concentrations of TEQs in mink livers were calculated by multiplying the
concentration of individual PCB congeners by its respective World Health
Organization toxic equivalence factor (TEF) (Van den Berg et al. 1998). Total
TEQ concentrations were determined by summing the concentrations of TEQs of
the individual congeners. The following PCB congeners were included for
calculation of TEQ #77, #81, #105, #118, #126, #156, #157, #167, and #169.
Although frequently used in the calculation of TEQ, congeners #114, #123, and

8

#189 were not included in the calculation of concentrations of TEQ as they could
not be identified by the analytical method used. When a congener was not
detected, a surrogate value of one half of the method detection limit was
multiplied by the TEF to calculate TEQ. Congeners #156 and #157 frequently
coeluted with congeners #171 and #200, respectively. In those instances, it was
assumed that the entire concentration was due to congeners #156 and #157,
providing the maximum estimate of TEQ concentration. By making this
assumption congener #157 contributed < 5% of the total concentration of TEQ,
whereas congener #156 contributed between < 0.01% and 50% of the total TEQs

with a mean TEQ contribution of 10%.

Toxicity Reference Values

The PCB-based TRVs were calculated from two laboratory-based mink
feeding studies (Bursian et al. 2002;Halbrook et al. 1999). Mink liver-based TRV
values, reported by Halbrook et al. (Halbrook et al. 1999), for the LOAEL and
NOAEL were 7.3 and 6.0 mg PCB/kg respectively, and the value based on the
LOAEL could be used directly. However, the tissue-based NOAEL was not
reported by the authors, but was estimated from the relationship between PCB
concentrations in adipose and liver from the LOAEL diet. This adipose to liver
relationship was then applied to the concentration of PCBs in adipose tissue from
the NOAEL diet. The LOAEL reported by Halbrook et al., was based on a
reduction of male kit weight after 6 wk (Halbrook et al. 1999). In a study by
Bursian et al., the mink liver-based LOAEL was reported to be 3.1 mg PCB/kg

(Bursian et al. 2002). However, the tissue residues associated with

9

concentrations of PCBs and TEOs values for the NOAEL were not specified
(Bursian et al. 2002). Therefore, the NOAEL was estimated by using a
LOAELzNOAEL application factor derived from the known dietary-based LOAELs
and NAOELs., This estimation resulted in a NOAEL TRV of 1.3 mg PCB/kg
(Bursian et al. 2002). The LOAEL was based on reduced kit body weights after 3
wk and decreased kit survival after 6 wk (Bursian et al. 2002).

The TEQ-based TRVs were calculated from two laboratory-based mink
feeding studies (Bursian et al. 2002;Heaton et al. 1995). The Bursian LOAEL
and NOAEL mink liver-based TRVs used were 218 and 51 pg TEQ/g,
respectively (Bursian et al. 2002). The NOAEL was estimated from the dietary-
based LOAELzNOAEL ratio. Heaton et al. (Heaton et al. 1995) used different
TEF values to calculate TEQs. Therefore, the dietary concentrations of TEQ
were recalculated based on the WHO TEFs so that they were consistent with
those reported in this study. In addition, the LOAEL was based on the least
tested dose. Therefore, the NOAEL was estimated by taking the geometric
mean of the control and lowest dose. The resulting LOAEL and NOAEL mink
liver-based TRVs based on the Heaton study were 273 and 70.9 pg TEQ/g,
respectively (Heaton et al. 1995). The LOAEL was based on decreased kit

survivability and decreased weights of kits 3 and 6 wk after whelping.

1O

Results

Mink

Nine male and one female mink were collected within the KRAOC from D-
Ave downstream to the former Trowbridge (TB) impoundment, a distance of
approximately 25 river kilometers. Three mink (two male and one female) were
collected from the Fort Custer upstream reference area, approximately 25 river
kilometers upstream of D-Ave, in Kalamazoo, MI. The female collected from the
KRAOC was classified as a ranch escapee. The fur from this female was black,
which is rare in wild populations. The nearest mink ranch is located in
Shelbyville (R. Aulerich, pers. com.), approximately 17 km north of the mink’s
capture site in Plainwell. The owners of this ranch acknowledge that they raise
black colored mink and that mink occasionally do escape and they are not
tagged. Because it may not represent conditions found at the KRAOC, this
individual was excluded from further analyses and discussion. The concentration
of total PCBs in liver for this mink was 0.03 mg PCB/kg w. This value was
considerably lower than the site mean. Therefore, elimination of this data results

in increased estimates of risk.

Male mink from the KRAOC had an average weight and length of 1048 g
and 40 cm respectively, while male mink from FC averaged 990 g and 39 cm
respectively. The female mink from FC weighed 3909 and was 34 cm long.
Mink from KRAOC ranged in age from 1 to 3 y (average 1.6 y) and mink from FC

ranged in age from juvenile (< 1 y) to 2 y (average 1.2 y). All of the mink

11

collected appeared to be in good condition and did not exhibit external or internal
gross abnormalities. Bacculum mass was not correlated to PCB concentrations
(r2 = 0.09, p = 0.36), even after correction for mink body weight. Based on a
histological examination, the livers of the mink were normal. There were four
individuals which exhibited lesions in the squamous epithelium tissue in the jaw
bones (Kerrie Beckett, pers. com.), and three of these individuals also contained

the greatest liver PCB concentrations.

Total PCB and TEQ concentrations

Total concentrations of PCBs in mink from the KRAOC ranged from 0.05
to 6.0 mg PCB/kg w (average 2.7 mg PCB/kg ww) (Figure 2). Total PCB
concentrations in livers of mink from FC ranged from 1.6 to 3.7 mg PCB/kg w
(average 2.3 mg PCB/kg ww) (Figure 2). There were no significant differences in
PCB concentrations among the sites (Student’s t-test unequal variance, p=0.33).

Concentrations of total TEQs in mink liver from KRAOC ranged from 1.1 to
1300 ng TEQ/kg ww (mean = 301 ng TEQ/kg ww) (Figure 3). In comparison,
total TEQs in mink liver from PC ranged from 52 to 200 ng TEQ/kg ww (mean =
110 ng TEQ/kg ww) (Figure 3). There were no significant differences in
concentrations of TEQ between sites (Student's t-test unequal variance, p=0.10).
Total concentrations of PCBs were significantly correlated with total
concentrations of TEQS (r2 = 0.76, p < 0.01). Congener #126 contributed the
greatest amount of the TEQs at both sites, averaging 77% at KRAOC and 69%
at FC (Figure 4). Congeners #118 and #156 were the next greatest contributors

but their relative rankings were different for the two sites.

12

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of the figure and represent the arithmetic mean contribution of individual congeners to total TEQs in KRAOC mink livers

(n=9) and FC mink livers (n=3).

Hazard quotients (HQs) were calculated based on both total
concentrations of PCBs and on concentrations of TEQ in the liver (Table 1). H03
were also calculated based on both the LOAEL and NOAEL. HQ values were
also calculated based on the results of two different laboratory exposure studies.
Thus, there were two values presented for each combination of exposure
measure and TRV. LOAEL-based HQ values based on mean PCBs
concentrations in livers of mink ranged from 0.37 to 0.88 and from 0.31 to 0.7 for
the KRAOC and FC, respectively. NOAEL-based HQs based on mean PCB
concentrations and compared to the NOAEL values ranged from 0.45 to and 0.38
to 1.7 for mink from the KRAOC and FC, respectively. HQs based on the mean
concentration of TEQS ranged from 1.1 to 1.4 and 0.39 to 0.49 for the KRAOC
and FC, respectively. NOAEL-based HQ values for TEQS based on the NOAEL
values ranged from 4.3 to 5.9 and from 1.5 to 2.1 for the KRAOC and FC,

respectively.

16

Table 1. Hazard quotients calculated using Total PCB concentrations and Total
TEQS in mink livers collected from the Kalamazoo River. The TRVs used to
calculate HQs based on total PCBs are from feeding studies conducted by
Halbrook et al. (Halbrook et al. 1999) and Bursian et al. (Bursian et al. 2002).
The TRVs used to calculate total HQs based on TEQs are based upon mink

feeding studies by Heaton et al. (Heaton et al. 1995) and Bursian et al. (Bursian

 

 

et al. 2002).
Total PCB HQ Total TEQ HQ
NOAEL LOAEL NOAEL LOAEL
KRAOC mean (n=9) 0.45 — 2.0 0.37 — 0.88 4.3 - 5.9 1.1 — 1.4

KRAOC 95% UCL (mean) 0.67 - 3.0 0.55 — 1.3 8.0 - 11 2.1 — 2.6

FC Mean (n=3) 0.38 — 1.7 0.31 - 0.7 1.5 — 2.1 0.39 — 0.49
FC 95% UCL (mean) 0.61 — 2.8 0.50 — 1.2 2.7 — 3.8 0.71 — 0.89

 

17

Discussion

Concentrations of PCB in livers of mink from this study, both KRAOC and
FC, are greater than those reported from some other areas of North America.
While tissue residues of PCBs in mink liver have been measured at relatively few
locations, the only areas that had greater concentrations were from North
Carolina, Connecticut and the Hudson River (Table 2).

It is difficult to compare the lengths and weights of mink from the
Kalamazoo River to other wild mink due to differences in sampling methodology,
or lack of methodology provided. Studies conducted in the Pacific Northwest
using similar methods, found an average weight for males of 8809 (Harding et al.
1999). This is less than the average weight of male mink collected in this study.
PCB concentrations in the mink collected during that study (Harding et al. 1999)
were less than those in livers of mink from the Kalamazoo River (Table 2).
Although results reported by Harding et al (Harding et al. 1999) indicated a
negative correlation between bacculum mass and PCB concentrations, no such
correlation was observed in mink from the Kalamazoo River. Lesions in the
squamous epithelium tissue of jaws were observed. In laboratory studies, where
mink were fed PCB 126 in the diet, eventually the teeth of mink exhibiting this
lesion became displaced, loosened, with the end result being anorexia (Render
et al. 2000). This is the first report of this lesion observed in wild mink. The
presence of this lesion may be a good marker for PCB exposure. However, at
this time, information on dose-response relationships and ecologically relevant

endpoints are lacking so it is difficult to interpret these results. As the mink

18

Table 2. Range of total PCB concentrations (mg/kg w) in mink liver reported in

North America.

 

 

 

Total PCBs Year(s) of mink
Location (m 91—19 ww) collection References
Rural western (O'Shea et al.
Maryland 0.62 - 2.4 1978 — 1979 1981)
South Carolina 0.042 - 1.5 .
Georgia ND — 1.4 1989 - 1991 (owfiggft 3"
North Carolina ND - 12
5:313:00 R'Ver' 0.05 - 6.0 2000 - 2002 This study
. . _ _ (Halbrook et
lll1n01s 0.04 0.86 1984 1989 al. 1996)
. _ _ (Major and
Connecticut 0.57 10 1987 1988 Carr 1991)
. (Mayack and
“gasggri'ver' 0.04 - 8.8 1998 - 2000 Loukmas
2001)
New York 0.10 — 0.60 1982 — 1984 (“1333; a"
Southern Ontario, (Haffner et al.
Great Lakes 0.034 — 1.8 1988 — 1989 1998)
Ontario 0.016 -- 0.40 Unpgglijhed
St. Maurice River, 1 5 _ 2 4 1991 — 1992 (Champoux
LaTuque, Quebec ' ' 1994 — 1995 1996)
Oregon 0.52 - 3.5 1978 — 1979 (”3133;33"
British Columbia <0.001 - 0.024 (Elliot et 31
Washington 0.067 - 0.38 1990 -1992 1999) '
Oregon 0.039 - 0.36
Northwest (Poole et al.
Territories 0.007 - 0.07 1991 - 1993 1998)
British Columbia 0.07 - 0.08 1994 — 1996 (Harggngggft 3"

 

19

collected from the Kalamazoo River were all of normal weight, the lesions do not
appear to have progressed to a stage where fitness could be compromised.
Overall, based on size and the gross and histological analysis, mink from the
Kalamazoo River appeared to be in good physical condition.

This study was not designed to collect information on the size, age
structure or sex ratio of the populations studied. It was expected that the sample
sizes would be limited, and thus, the power to measure population dynamics is
low. While the absolute numbers of mink collected were few, the number of mink
collected is consistent with the numbers expected in an area of this size. Mink
can have territories of over 2 km in river length (Gerell 1970), the FC sampling
area was 10 km while the KRAOC sampling area was 25 km. In addition, mink
habitat suitability was assessed along the Kalamazoo River and the floodplain
areas were considered to have marginal habitat due to a lack of vegetative and
structural complexity (Pastva 2003). The fact that most of the mink captured
were adults and not juveniles as determined by dental cementum analysis
suggests that they were likely resident animals. Dietary assessments conducted
concurrently, within the KRAOC and FC study areas, concluded that risk based
on dietary models, was slightly less than risk calculations based on site-specific
mink tissue residues (Pastva et al. 2003a). Therefore, mink are most likely living
in the study areas and are not recent immigrants. The sex ratio of collected mink
was skewed toward males, this commonly occurs in trapping studies and harvest
results, including those with mustelids (Buskirk and Lindstedt 1989;Elliot et al.

1999;Harding et al. 1999). This result may or may not represent the actual sex

20

ratio of the population but is most likely a sampling artifact. Males mustellids
have larger territories and are more active than females (Buskirk and Lindstedt
1989), thereby increasing their likelihood of encountering a trap. Therefore, the
sex ratio of mink captured here were not inconsistent with that which would be
expected.

There was no attempt to estimate a site use factor, or determine the
amount of time that mink would have spent in the areas studied. To do studies of
this type would have required tagging and radio-telemetry studies that were
beyond the scope of our study. This study was also not conducted to determine
the duration of exposure that mink might receive. For this reason, we can not
directly assess questions about immigration and emigration. This results in some
uncertainties in addressing the potential impact of PCBs on mink populations.
For instance, it has been suggested that exposure to PCBs might result in overt
toxicity of adults or decrease reproduction to the point where the population is not
self-sustaining, but rather dependent on immigration to maintain the population.
While our data can not be used to assess this issue directly, the ages of the mink
collected indicate that the mink were residents. Normally, it is juvenile mink that
are émigrés. Thus, if the KROAC were acting as a “sink” for mink, one would
expect that the population would be comprised mostly of individual less than one
year old. This was not the case. No mink captured from KRAOC were less than
one year old with approximately 45% of the individuals being 1 and 2 years old

each, with one individual (~10%) being 3 years old.

21

There are two basic components to the HQ method of risk assessment,
exposure and hazard, each with its own inherent uncertainties and variability.
The measurement endpoint to assess exposure was the concentration of PCBs
in liver, expressed either as total PCBs or TEQs. Hazard was assessed by use
of TRVs based on ecologically relevant measurement endpoints such as survival,
growth and reproduction as determined in controlled laboratory studies in which
ranch mink were exposed to weathered mixtures of PCBs in the diet.

One of the null hypotheses being tested in this study was that there was
no difference in concentrations between the KRAOC and the reference area.
Use of measured instead of predicted estimates of exposure minimized the
degree of uncertainty in the exposure portion of the risk assessment. However,
the inherent nature of mink populations led to small sample sizes for statistical
analyses. The contribution of sources of PCBs within the KRAOC relative to that
occurring from other sources upstream of KRAOC was determined to be small
relative to mean concentrations at the two study areas (16%). The difference in
mean concentration between mink collected from KRAOC and PC was small
(0.44 mg PCB/kg) and not statistically significant. Statistical power (1- [3) based
on the variance sample sizes of the two populations, and type I error (a) of 0.05
and a type II error ((3) of 0.2, was< 0.1. If there had been a 2.5-fold difference in
the mean PCB concentrations, it would have been possible to show a statistical
difference between the means. Power would have been greater than 0.8, even
with the same sample size and variability. Therefore, the likely reason for the

lack of a significant difference was due primarily to the small difference between

22

the two populations, rather than to sample size or variance of the concentrations
of PCBs in the two populations.

In this study, concentrations of PCBs in the liver were used as a measure
of exposure that could be compared to a dose-response relationship to estimate
the potential for effects. However, the PCBs, particularly the congeners
contributing to effects mediated through the aryl hydrocarbon receptor (AhR), can
be sequestered in the liver and not be biologically active. Thus, the use of
concentrations of PCBs in the liver is a conservative measure of exposure and
potential effects and likely overestimates the potential for effects. If organisms
are exposed for a long period of time to low levels of AhR agonists, the ligands
can be sequestered in the liver without leading to adverse effects. For instance,
when mink were fed PCBs in the diet, hepatic cytochrome-450 1A activity, a
measure of biochemical response was induced in a dose-dependent manner, but
when the dietary exposure to PCBs was stopped, induction of the enzyme
decreased to controls levels within a few weeks while concentrations of both total
PCBs and TEQs in the liver did not decrease as rapidly (Shipp et al. 1998). The
proposed reason for this observation is that induction of the cytochrome P-450
system requires free agonists that are able to interact with the AhR and dioxin
response elements. Once exposure stops, agonists remain bound to the already
induced P450 enzymes, but there is insufficient free compound to result in
further induction. Thus, the TEQs are present in the liver, but sequestered so
that they are unavailable to interact further with biomolecules and cause adverse

effects. For this reason, Shipp et al (Shipp et al. 1998) suggested that induction

23

of the cytochrome P-450 was a good indicator of current exposures to TEQ. In
mink the critical mechanism of PCB toxicity has been suggested to be through
the AhR mechanisms (Kannan et al. 2000). The congeners contributing to TEQ
are known to be tightly bound to P450 1A1 and P4501A2 so that they are
unavailable to interact with other molecules (Hahn et al. 1993). The ligands are
in fact suicide substrates for these enzymes, one function of which has been
postulated is protection from the effects AhR-ligands.

Since the mink used in this study were trapped and could not be
recovered immediately or at the same time after death, it was not feasible to
measure the specific CYP—450 activity in the liver. If activity could have been
measured it would have been possible to estimate the proportion of the total
concentration that was not bound to P4501A2 protein, which would constitute the
biologically active fraction of the total concentrations of P088 or TEQs in the liver.
Since this was not possible, total concentrations of PCBs and TEQ in the liver
were used as a conservative estimate of maximum exposure that would be
expected to overestimate the actual or effective toxicologically relevant exposure
and predictor of possible effects. The same properties of enzyme binding, which
result in retention of the greatest concentrations of residues in the liver and make
the liver a useful organ for monitoring exposure also complicate the interpretation
of the toxicological significance for risk assessments.

Mink are one of the most sensitive organisms to the effects of PCBs
(Kannan et al. 2000) and are unusual, among wildlife species, in that there is a

large literature base of effects data from which to develop TRV information. In

24

particular, all the studies used to derive TRVs for this risk assessment were
chronic exposures and examined ecologically relevant endpoints such as number
of kits whelped, kit survival and kit weight. Furthermore, the endpoints on which
the TRVs were based were the most sensitive endpoints. Also, the studies were
not confounded by the potential effects of co-contamination. Thus, there was no
need to apply uncertainty factors for differences in species sensitivity or acute-to-
chronic adjustments. For these reasons, uncertainty related to the threshold for
adverse effects has also been minimized.

In the study reported by Bursian (Bursian et al. 2002) AhR agonist co-
contaminants, such as polychlorinated dibenzo-p-dioxin (PCDDs) and
polychlorinated dibenzofuran (PCDF) congeners, were measured and considered
to be minimal. Likewise, co-contaminants in fish from the Kalamazoo River were
also considered negligible (1994). In addition, in both of these feeding studies
the LOAEL dose was the critical dose. That is, there were at least two doses that
were lower than the LOAEL, which minimizes bias due to experimental design
and allows for an accurate estimate of the NOAEL. Although the Heaton study
(Heaton et al. 1995) wasn’t appropriate to use for PCB-based TRV derivation due
to the presence of substantial co-contaminants, it was suitable for the estimation
of TEQ-based TRVs.

An HQ of one or greater indicates that liver concentrations exceeded the
level of effect on which the TRV was based. While a HQ of 1.0 or greater
indicates the potential for risk, it does not mean that this level of effect would

actually be observed at the population level. Due to the conservative nature of

25

measures of both exposure and hazard, population level impacts are frequently
not observed until HQ values are above 10 (Giesy and Kannan 1998). The mean
HQ-based LOAELs of total PCBs were less than 1.0, while the upper 95%
confidence limit of those LOAEL-based HQ are less than 1.5 at both KRAOC and
the upstream reference area (Table 1). When NOAEL-based HQs, for total
PCBs, are considered, the mean HQs were 3.0 or less. HQs based on TEQs at
both sites were greater when compared to their respective PCB-based HQs. HQ
values based on total TEQs are approximately three times greater at KRAOC
than those from PC (Table 1). HQ values based on total PCBs would indicate
that exposure and subsequent risks to mink at both KRAOC and FC are similar.
However, when based on TEOs, the risk to mink is greater, even though the
exposure was not significantly greater. This may indicate an increased relative
potency of the PCB exposure mixture at KRAOC compared to FC, or simply a
large uncertainity in the conversion calculation.

The range of HO values calculated from the studies considered to be
relevant for deriving TRVs bracket 1.0 depending on the study and whether the
TRV was based on total PCB or TRV concentrations or based on the NOAEL or
LOAEL. Thus, it can be concluded that the current concentrations of PCBs in the
livers of mink in the KRAOC are near the threshold for effects observed in
laboratory studies of ranch mink. The LOAEL is the more accurate measure of
potential effect because since the concentration associated with no effect is, in
part a function of the experimental design and by definition an overestimate of

hazard. All that is known is that the NOAEL is the greatest concentration tested

26

that did not cause a statistically significant effect. When TRVs from the Bursian
study (Bursian et al. 2002) are used for comparison, concentrations of total PCBs
were greater than the LOAEL in 44% of the individuals from KRAOC, while 67%
of individuals from KRAOC had PCB concentrations that were greater than the
NOAEL-based TRV. At FC, no individuals had concentrations greater than the
LOAEL, while 100% of those individuals did have PCB concentrations great than
the NOAEL-based TRV derived from the Bursian study (Bursian et al. 2002).
However, no individuals from KRAOC or F0 have PCB concentrations greater
than the NOAEL or LOAEL-based TRVs derived from the Halbrook study
(Halbrook et al. 1999). Additionally, kit survival in treatment groups was not
significantly different than in the control group.

The estimates of hazard based on concentrations of TEQ in the liver were
similar to those based on total PCBs. Concentrations of TEQ in the liver of 33%
of the mink from KRAOC exceeded TRVs derived from the the LOAEL, while
56% exceeded the TRV based on NOAELs. The mean TEQ concentration from
KRAOC was also greater than the NOAEL-based TRVs. No concentrations of
TEQ exceeded the TRV values based on the LOAEL. However, depending on
which TRV was used, between 67and 100% TEQ concentrations exceeded the
NOAEL-based TRVs.

Survival of kits reported by Bursian et al. (Bursian et al. 2002) was
decreased by almost 50% at the LOAEL close when compared to the control.
Based on the number of individuals that had PCB concentrations exceeding this

LOAEL, kit survival is possibly depressed at the KRAOC. However, since

27

information regarding compensatory mortality in the field is not available, it is not
known how much this difference is likely to impact the population or ability of the
population to be sustained. To address this issue would require employing an
age-specific model of mortality and fecundity, the data for which is not available.
However, the results from a similar1y conducted study (Halbrook et al) indicate no
such decreases of survival at concentrations greater than that reported in the
Bursian study. Therefore, the results of the risk assessment based on
concentrations in the liver are equivacol and near the threshold for adverse
effects on the population. This conclusion is supported based the fact that PCB
and TEQ-based HQs bracket 1.0.

Some uncertainty is still associated with the PCB and TEQ-based TRVs,
because some values were extrapolated. For instance, the NOAELs from all
three studies were estimated. As a result, HQs estimated using NOAEL-based
TRVs have a greater amount of uncertainty associated with them than the
LOAEL TRVs. However, the ranges of H03 derived from both the total PCB and
total TEQ LOAEL-based TRVs are very similar, despite slight differences in
experimental design. This indicates agreement among the different studies for
effect concentrations. Finally, assumptions about co-eluting congeners and
treatment of non-detects made during estimation of TEQ concentrations are
conservative and lead to greater estimates of TEQ concentrations. Therefore, in
general the TEQ-based HQs have a greater uncertainty associated with them

and tend to be overestimates than do the PCB-based H05.

28

In conclusion a risk assessment was performed to determine the risk of
PCB exposure to mink residing along the Kalamazoo River. Uncertainties
associated with the hazard of P033 to mink were reduced, relative to estimates
of exposure derived from measuring concentrations of PCBs in potential dietary
items, by comparing concentrations of PCB in the liver with the results of suitable
feeding studies to derive TRVs. Although PCB concentrations were measured in
mink liver tissue, uncertainties still exist. However, these uncertainties would
result in greater estimates of risk and therefore should be protective. A mink
population is present at the KRAOC and data indicate that the mink were
resident animals. PCB exposure at KRAOC is not great enough to cause direct
mortality to adults or decrease number of kits born. However, based on results
under laboratory conditions with ranch mink, the weight and/ or number of kits
per litter six weeks post birth may be reduced at the present exposure level. It is
uncertain if PCB exposure (expressed as total PCBs or TEQS) could cause
adverse effects on the population. Information regarding the amount of kit
survival to adulthood and recruitment necessary to maintain a viable population
would have to be known to adequately determine risk at a population level.
Multiple lines of evidence were considered, including the number of animals
trapped per territory, age and sex distributions, gross morphology, liver histology,
bacculum weight, and body weight. Based on these multiple lines of evidence,
the observed concentrations of PCBs measured in the livers of mink in the
KRAOC are unlikely sufficient to cause a reduction in the number of mink

inhabiting the KRAOC.

29

CHAPTER TWO:

Assessment of Risk Posed by Polychlorinated Biphenyls in the
Diet of Mink (Mustela vison) at the Kalamazoo River Superfund

Site, Michigan

Introduction

Located in southwestern Michigan, the main stem of the Kalamazoo River
is approximately 195 km long and flows northwest, entering Lake Michigan near
Saugatuck, Michigan (Figure 5). In 1990, approximately 123 km of the
Kalamazoo River was designated a Superfund site. The site, referred to as the
Kalamazoo River Area of Concern (KRAOC), and extends from Morrow Lake
dam to Lake Michigan (CDM 1999). PCBs are the contaminant of concern, and
studies are being conducted to determine the extent to which biota, specifically
mink (Mustela vison), are being exposed to PCBs and the degree of risk posed
by this potential exposure.

Due to the large size of the KRAOC, two areas were chosen for sample
collection: the former Trowbridge impoundment (TB), as a worst-case scenario,
and Fort Custer Recreational Area (FC), as an upstream reference area. TB was
selected as a worst-case area within the KRAOC because it is the largest of the
four former impoundments (~132 hectares of former sediments and ~70 hectares
of existing impounded water), has the greatest estimated mass of PCBs, and has

the greatest mean surficial concentration of PCBs in soils (~11 mg/kg, dw)

30

 

 
 
   
    

Lake
Michigan

 

Allegan County

 

Morrow
Lake Dam

 

 

 

 

 

 

 

 

 

Kalamazoo CognL

 

Figure 5. Map of Kalamazoo River Area of Concern. The inset map of Michigan

indicates the locations of the two counties in which the study was conducted.

31

(Basland 2000). Since it was a former impoundment, both the aquatic and
terrestrial ecosystems are exposed to PCBs. Fort Custer was chosen as the
reference area because it is upstream of the KRAOC and has relatively little PCB
contamination.

Mink are one of the receptors of concern at the KRAOC due to their
sensitivity to PCBs and their relatively great potential for exposure as piscivorous,
top predators. Mink are solitary, nocturnal, and have territories that average over
2 km of stream length. Mink are often considered to be a species of concern at
other large sites, such as the Fox River (WI), Clinch River (TN), and Housatonic
River (NY), where risk assessments have been conducted for PCBs. The study
of mink exposure to PCBs and associated risks can incorporate top-down (based
on concentrations of PCBs in the liver) and/or bottom-up (based on predicted
dietary exposure) assessment methodologies.

The use of the top-down approach in which concentrations of PCBs are
measured in the tissues of the receptor of concern is the most accurate measure
of site-specific exposure. Results from the top—down approach applied to mink
from the Kalamazoo River are presented in a companion paper from this study
(Pastva et al. 2003b). In most cases, dietary models can be useful for predicting
tissue residue measurements of mink are not or cannot be taken
(U.S.Environmental Protection Agency 1998). Therefore, dietary models are
often used to estimate exposure. This study was conducted to determine the

accuracy of dietary exposure models.

32

One of the major factors in applying dietary exposure models is the dietary
composition used to model exposure. Although mink are a semi-aquatic predator,
they can occupy a wide range of habitat types including estuaries, rivers and
streams, and wetlands (U.S.Environmental Protection Agency 1993). Studies of
the diets of mink, including those conducted on Michigan rivers and streams,
indicate that mink are opportunistic feeders and eat a variety of food items
(aquatic and terrestrial animals) (Casson and Klimstra 1983;Hamilton, Jr.
1936;Sealander 1943;Whitman 1981 ). In addition, their food habits vary by
habitat type and season. Therefore, using just one standard dietary composition
may not be appropriate for every site. For this reason, several models, using
different assumptions about the diet of mink were used to predict exposure and
calculate risks. Specifically, in this study, the bottom-up assessment involved
characterizing the dietary composition of mink from the site, collecting and
measuring PCB concentrations in key prey items, and predicting dietary
exposure. Here, we report the results of the bottom-up assessment and
compare them to an assessment based on measured concentrations in the livers

of mink.

33

Methods

Sample Collection and Preparation

Samples of muskrat (Ondatra zibethicus) and other mammals were
collected during the period 2000 — 2002. Muskrats were trapped in the winter,
using previously described methods, from locations where mink were also
trapped (Pastva et al. 2003b). Muskrats were frozen with fur on. Later, muskrats
were thawed, skinned, weighed, and the whole body was homogenized in a
grinder (model 4732 SS; Hobart Corp., Troy, OH) which resulted in a coarse
grind. This coarsely ground material was then further homogenized in a Waring
Commercial Blender (model 368L29, Waring Commercial Inc., New Hartford,
CT), placed in cleaned glass jars (l-Chem, New Castle, DE) and stored at -20C
until PCB analysis. Small mammals were sampled in June/July 2000 and again
in August/September 2000 at 4 locations at TB and 3 locations at FC. Sampling
occurred in a 35x35 m area in which alternating Sherman (XLF15) and pitfall
(#10 canning tins) traps were placed ~5 m apart resulting in a total of 49 traps
per grid. Traps were baited with rolled oats and peanut butter as needed. Traps
were checked twice daily. Captured specimens were gently shaken out of traps
into clear quart sized zip-lock bags, identified, and euthanized by cervical
dislocation. Samples were then labeled, placed in a cooler, and transported back
to the laboratory. Upon arrival at the laboratory, weights, lengths, visual health,
sex, and species were recorded. Gut contents were removed, samples were

wrapped whole in aluminum foil, and then frozen until homogenization for

34

chemical analysis. The following small mammal species were analyzed for PCB
concentrations to use in the dietary assessment: eastern chipmunk (Tamias
stn'atus), red squirrel (Tamiasciurus husdonicus), meadow vole (Microtus
pennsylvanicus), deer mouse (Peromyscus maniculatus), white-footed mouse
(Peromyscus Ieucopus), and meadow jumping mouse (Zapas hudsonius).

Fish were collected by electro-fishing (Smith Root, Inc) in early winter
2000 (11/9/99-1/3/00) at TB and FC. Upon collection, fish samples were placed
in one of two live wells. Upon completion of the day’s sampling, or attainment of
live well capacity, samples were categorized, euthanized using MS-222 (Western
Chemical Inc, Femdale, WA), placed in labeled pro-cleaned coolers and
transported to the field laboratory where length and weight were determined.
Fish were wrapped whole in aluminum foil, labeled, and transported on dry ice to
the laboratory. Fish (whole body) were homogenized using a Waring
Commercial Blender (model 36BL29). l-lomogenate was stored in cleaned glass
jars (l-Chem, New Castle, DE) until PCB analysis was conducted. The following
fish species were analyzed for PCB concentrations to use in the dietary
assessment: carp (Cypn'nus carpio), forage fish (collected based only on size,
no species identification), smallmouth bass (Micropterus dolomieu), and suckers
(Catostomus commersoni, Hypentelium nigricans, and Moxostoma erythrurum).

Crayfish (Scientific name) were collected between June and September,
2000 from suitable habitat that was as proximal to the small mammal sampling
grids as possible. Crayfish were sampled using wire minnow traps baited with

dead fish that were captured within TB and FC. Traps were washed, allowed to

35

dry, then rinsed twice; first with acetone then hexane to avoid cross-
contamination between sampling locations. Crayfish were wrapped in foil,

labeled, placed in a cooler and transported to the secure field laboratory.

PCB Quantification and TEQ Computation

PCBs were analyzed using methods described previously (Pastva et al.
2003b). Briefly, after homogenization, samples were extracted with
dichloromethane and hexane in a soxhlet apparatus, and prepared by use of
silica gel column chromatography. The extract was concentrated to 1.0 ml and
0.5 ml was used for identification and quantification of individual PCB congeners
using a gas chromatography- electron capture device (GC-ECD). The remaining
0.5 ml was further prepared using carbon column chromatography for
identification and quantification of mono- and non-ortho PCB congeners with a
GC- mass spectrophotometer device (MSD) (Pastva et al. 2003b).

Concentrations of 2,3,7,8-tetrachlorodibenzo—p—dioxin (TCDD) equivalents
(TEQs) were calculated by multiplying the concentration of individual PCB
congeners by its respective World Health Organization (WHO) toxic equivalency
factor (TEF) (Van den Berg et al. 1998). Congeners #114, #123, and #189 could
not be detected in any of the samples analyzed, and therefore were not used to
calculate TEQs. However, the TEQ for congeners #77, #81, #105, #118, #126,
#156, #157, #167, and #169 were summed to predict a total TEQ. For instances
in which one or more of these congeners was not detected, a proxy value equal
to half of the method detection limit was used. Congeners #156, #157, and #167

frequently co-eluted with congeners #171, #200, and #185, respectively. In

36

those instances, it was assumed that the entire concentration was due to the

coplanar congener, providing a maximum estimate of TEQ concentration.

Site-Specific Dietary Analysis

Stomachs and large intestines of mink were dissected from mink
carcasses (Pastva et al. 2003b), and were stored frozen at -20°C. The stomach
was cut open and contents removed. Contents from the intestinal tract were
removed by squeezing. GI tract contents were rinsed through a stacking sieve
(mesh numbers 5-230; Hubbard Scientific, Fort Collins, CO). After rinsing, the
contents were dried at 90°C for 24 hours. Aftenrvards, the contents were hand
separated and classified as either bone, feathers, exoskeleton, hair, teeth, scales,
or miscellaneous (Litvaitis et al. 1996). From this, dietary composition was
expressed as percent mammal, fish, bird, and crayfish (Lockie 1959). In
instances in which no components were found, it was recorded as unknown and
these individuals were not used to calculate the dietary composition for use with

estimating dietary doses.

Average Potential Daily Dose Calculations

Average potential daily dose (ADDpot) was used estimate the total dose of
PCBs and TEQS present in food ingested (U.S.Environmental Protection Agency
1993) (Equation 1).
ADDpo, = 2(Ck x FRk x NIRk) (Eq 1)
Where:

Ck = Contaminant concentration in each prey item

37

FR.,= Fraction of time spent on site
Nle= Normalized Ingestion Rate = mean daily ingestion rate/mean body

weight

Each of the dietary models assumed different relative proportions of each
dietary component. Results from the site-specific dietary analysis were used as
one model. These results represent what mink from the Kalamazoo River ate
immediately prior to their capture. Due to the opportunistic nature of mink, two
other dietary models were also chosen to estimate ADme. These non-site
specific dietary models assumed different proportions of dietary items based on
values reported in the literature (Alexander 1977) or assumed and an equally
opportunistic consumption of specified prey items. The proportion of prey in the
literature-based diet was based on one study because it was a year-round study
on a Michigan river and because it provided a maximum estimate of fish in diet
compared to other studies (Alexander 1977). This literature-based diet consisted
of 85% fish, 9% crayfish, and 6% small mammals. The equally opportunistic
model gave equal weight (33.3%) to all three prey components. That model was
chosen because it represents a median exposure of mink diet which can vary
greatly, depending on prey availability. However, regardless of the model
chosen, the portion of the diet that consisted of mammals was assumed to
consist of 50% small mammals and 50% muskrat while the fish portion of the diet
was assumed to consist of 25% carp, 25% forage fish, 25% smallmouth bass,

and 25% sucker.

38

The concentrations of total PCBs and TEQs in site-specific prey items
were then used to calculate the daily dose of PCBs and TEQs to mink from
KRAOC and FC. Potential risks were estimated by use of a hazard quotient (HQ)
approach (Equation 2), in which the ADme for each dietary model was
compared to appropriate toxicity reference values (T RVs) for PCB and TEQ
TRVs from laboratory-based mink feeding studies (Brunstrom et al. 2001 ;Bursian

et al. 2002;Halbrook et al. 1999;Heaton et al. 1995).

ADDpot (mg PCB/kg/d or pg TEQ/kg/d)

Dietary Toxicity Reference Value

HQ=

 

(Eq 2)

Toxicity Reference Values

The dietary TRVs applied in this assessment, for total PCBs and TEQ
were based on studies in which mink had been chronically exposed to P035 or
TEQs in feed and ecologically relevant endpoints were evaluated. A summary of
the results of these studies and justification for their use has been provided
previously (Pastva et al. 2003b).

The TRV for total PCBs were based on two laboratory studies with mink
(Bursian et al. 2002;Halbrook et al. 1999). The TRVs for weathered PCBs
mixtures were determined to be 0.23 and 0.12 mg PCB/kg mink body weight/day,
based on the LOAEL and NOAEL, respectively (Halbrook et al. 1999). In a
second study (Bursian et al. 2002), where neither body weights nor ingestion
rates were provided, a standard mean body weight for females of 1.1 kg and a

standard ingestion rate of 0.13 kglmink (S. Bursian, personal communication)

39

were used to derive a NIR of 0.11 kg food/kg bwld. Based on these assumptions,
TRVs were calculated to be 0.42 and 0.18 mg PCB/kg bw/d for the LOAEL and
NOAEL, respectively (Bursian et al. 2002).

The TRVs for TEQs were based on three laboratory-based mink feeding
studies (Brunstrom et al. 2001;Bursian et al. 2002;Heaton et al. 1995). Again,
TRVs were calculated based on an estimated NIR if it was not given in the study.
TRVs based on the LOAEL and NOAEL were estimated to be 7.8 ng TEQ /kg
bwld and 1.8 ng TEQ/kg bwld, respectively (Bursian et al. 2002). Although a
study-specific NIR could be calculated from one study (Heaton et al. 1995), the
TEQ values in the mink diets of that study had to be adjusted to WHO TEFs
rather than the H4llE-potency factors that had been used to calculate TEQ in the
original study (Heaton et al. 1995). In addition, the LOAEL was based on the
lowest tested dose. Therefore, the NOAEL was estimated by taking the
geometric mean of the control and lowest dose. The resulting TRVs based on
the LOAEL and NOAEL were 4.5 and 1.1 ng TEQ/kg bwld, respectively (Heaton
et al. 1995). Finally, the TRVs from the third study (Brunstrom et al. 2001) were
calculated using a study-specific NIR to yield LOAEl. and NOAEL TRVs of 2.4
and 0.35 ng TEQ/kg bw/d, respectively. However, the TRV based on the NOAEL
corresponds to a 2-4-ortho-CB fraction rather than a complete technical mixture.
This fraction contained a seven-fold smaller concentration of TEQ than did the
LOAEL (Brunstrom et al. 2001) and has the greatest difference in dose range of
the studies used. TRVs are summarized in Table 3. Among the three studies

described above, the study by Bursian et al. (Bursian et al. 2002) is strengthened

40

by the absence of adverse effects observed at 5 lower doses. This, coupled with
the small dosing intervals provides confidence that this study bracketed the We

threshold with the doses tested.

Table 3. Toxicity reference values (TRVs) used to calculate total PCB and TEQ

NOAEL and LOAEL-based hazard quotients.

 

NOAEL LOAEL

 

TRV TRV Reference
lat/fir” ("‘9 "33"“? 0.12 0.23 (Halbrook et al. 1999)

0.18 0.42 (Bursian et al. 2002)
Total TEQ (n9 TEQ/kg 0 35 2 4 (Brunstrom et al.
bwld) ' ' 2001)

1.1 4.5 (Heaton et al. 1995)

1.8 7.8 (Bursian et al. 2002)

 

41

Results

Concentrations of Total PCB and TEQ

Concentrations of total PCB at TB ranged from 0.01 in both muskrat and
small mammals to 10 mg PCB/kg w in smallmouth bass (Table 4). At FC, PCB
concentrations in prey items ranged from 0.0014 in small mammals to 2.4 mg
PCB/kg in carp (Table 4). PCB concentrations in prey items from TB were
significantly greater (Student t-test p < 0.05) than those from the upstream
reference area, FC (Figure 6).

Concentrations of TEQ in prey items at TB ranged from a minimum of 0.22
in small mammals to 111 ng TEQ/kg in smallmouth bass, while those at FC
ranged from 0.08 in small mammals to 47 ng TEQ/kg w in carp (Table 4). Prey
items from TB contained significantly greater concentrations of TEQS than those
from FC (Student t-test p < 0.05), with the exception of muskrat and carp which
were not statistically different (Student t-test p = 0.24 and p = 0.11, respectively)

(Figure 7).

Site-Specific Diet Composition

No individual mink had more than one identifiable prey category in its
gastroinstestinal tract. One mink contained scales, 5 contained fur, 1 contained
crayfish exoskeleton, and 5 contained no major components in their GI tract.
This resulted in the following site-specific dietary composition for mink on the

Kalamazoo River: 72% mammals, 14% fish, and 14% crayfish.

42

 

 

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45

Risk Calculations

Dietary exposures were reported as both concentrations of total PCBs and
TEQs (Table 5). The rank order of ADDpot for the three different dietary models
were literature-based > equally opportunistic > site-specific. The resulting
dietary-based NOAEL and LOAEL HQs are presented (Table 6). A range of
values are presented based on several TRV values. For both NOAEL and
LOAEL-based HQs for PCBs, the TRVs derived from Bursian et al (Bursian et al.
2002) resulted in lesser HQs than those derived from Halbrook et al (Halbrook et
al. 1999). Of the three studies used to calculate HQs based on TEQ, the TRV
based on the study by from Bursian et al (Bursian et al. 2002) resulted in the
least HQs. Whereas, the TRVs based on the study by Brunstrom et al
(Brunstrom et al. 2001) resulted in the greatest HQs, and the TRVs from Heaton
et al. (Heaton et al. 1995) resulted in intermediate HQs.

Among the three diets assumed, mean LOAEL-based HQ values for PCB
ranged from 0.20 to 1.8 at TB, while those based on concentrations in prey from
PC ranged from 0.04 to 0.35. The NOAEL-based HQs ranged from 0.47 to 3.4 at
TB and from 0.09 to 0.68 at FC. LOAEL-based HQ vales for TEQ concentrations
in prey ranged from 0.17 to 2.0 at TB, while those based on concentrations at FC
ranged from 0.07 to 0.71. The mean NOAEL-based HQs of TEQ concentrations
from TB and FC ranged from 0.73 to 14 and 0.31 to 4.9, respectively. Overall,
there was relatively good agreement between HQ values based on total PCB and
those based on TEQ. Among locations, PCB-based HQs were 4-5 fold greater at

TB than FC, while TEQ-based HQs were 2—3 fold greater at TB than FC.

46

Table 5. Range of average potential daily doses (ADDpot), based on mean and

the upper 95% confidence limit (U95% CL) of prey items for total PCBs (mg

PCB/kg bw/dand TEQs (ng TEQ/kg w/d), at both Trowbridge (TB) and Fort

 

 

Custer (FC).
TB FC
PCB TEQ PCB TEQ

Dietary Models
Site-specifica

Mean 0.08 1.3 0.02 0.57

U95% CL 0.12 2.1 0.02 1.1
Equally opportunistic”

Mean 0.18 2.3 0.03 0.85

U95% CL 0.26 3.3 0.05 1.3
Literature-basedc

Mean 0.41 4.9 0.08 1.7

U95% CL 0.59 6.7 0.11 2.3

 

a: Model is based on results from field collected mink GI tract contents

b: Model assumes that consumption of specified prey items is equal

c: Model based upon one mink diet reported in literature (Alexander 1977)

47

Table 6. Hazard quotients (HQ) values based on mean and the upper 95%
confidence limit (U95% CL) of potential average daily doses of total PCBs and
TEQS, when assuming three different dietary compositions for mink. The TRVs
used to calculate HQs were based on feeding studies (Brunstrom et al.
2001;Bursian et al. 2002;Halbrook et al. 1999;Heaton et al. 1995). The range of

calculated HQs is a result of using more than one TRV.

48

 

 

TB FC
LOAEL NOAEL LOAEL NOAEL
PCB Based Dietary Models
Site-specific
Mean 0.20 — 0.36 0.47 - 0.70 0.04 — 0.07 0.09 - 0.13
U95% CL 0.29 - 0.52 0.67 — 1.0 0.05 — 0.10 0.12 - 0.18
Equally opportunistic
Mean 0.43 - 0.79 1.0 - 1.5 0.08 - 0.15 0.19 — 0.29
U95% CL 0.62 — 1.1 1.5 — 2.2 0.11 — 0.20 0.26 — 0.39
Literature-based
Mean 0.98 — 1.8 2.3 — 3.4 0.19 - 0.35 0.45 — 0.68
U95% CL 1.4 — 2.6 3.3 - 4.9 0.26 - 0.47 0.60 — 0.90
TEQ-Based Dietary Models
Site-specific
. Mean 0.17 - 0.56 0.73- 3.8 0.07 — 0.24 0.31 — 1.6
U95% CL 0.26 — 0.86 1.1 - 5.9 0.14 — 0.46 0.61 — 3.2
Equally opportunistic
Mean 0.30 - 0.97 1.3 - 6.7 0.11 - 0.35 0.46 - 2.4
U95% CL 0.42 - 1.4 1.8 — 9.5 0.17 — 0.54 0.71 - 3.7
Literature-based
Mean 0.63 — 2.0 2.7 — 14 0.22 — 0.71 0.94 - 4.9
U95% CL 0.87 — 2.8 3.7 — 19 0.29 - 0.94 1.2 - 6.5

 

49

Discussion

Agreement in TRVs among studies

Among the four different feeding studies that were used to derive LOAEL-
based TRVs for PCBs and TEQs, there is considerable agreement. For example,
there was only a 2-fold and 3-fold difference among the LOAEL-based TRVs for
P035 and TEQs respectively. Furthermore, in three of the four studies, the
LOAEL dose was one which caused decreased kit weight, but did not affect
whelping rate or kit survival (Brunstrom et al. 2001;Bursian et al. 2002). Thus, kit
weight after three or six weeks of birth appears to be the most sensitive endpoint.

NOAEL-based TRV values were also similar for the studies by Bursian et
al. (Bursian et al. 2002)and Halbrook et al. (Halbrook et al. 1999). This is likely a
result of a two-fold difference in dosing intervals and there being two tested
doses that were less than the LOAEL for both studies. This experimental design
minimizes bias and thus allows for an accurate estimate of the NOAEL. However,
the NOAEL-based HQs for TEQS varied by five-fold among the three feeding
studies. This greater uncertainty, relative to the other TRVs, is likely due to
biases and uncertainties introduced by their respective study designs. The study
conducted by Brunstrom et al. (Brunstrom et al. 2001) was designed to answer
questions regarding effects of ortho vs non-ortho substituted PCB fractions, not
as a typical dose-response study (there was a 7-fold difference in LOAEL and
NOAEL TEQ concentrations) (Brunstrom et al. 2001). The study conducted by

Heaton et al. (Heaton et al. 1995) NOAEL was not directly based on a tested

50

‘ dose. Instead, it was estimated by taking the geometric mean of the control and
lowest dose, which was the LOAEL (Heaton et al. 1995). As a result, HQs

estimated using the NOAEL-based TRV for TEQs based on the study by Bursian
et al. (Bursian et al. 2002) had the least uncertainty and thus were considered to

be the most reliable.

Dietary modeling

The use of three different dietary models encompasses a wide range of
potential mink feeding habits and also provides a measure of uncertainty when
estimating risk to mink. The most conservative (greatest) risk estimates on the
Kalamazoo River were obtained by using the literature-based dietary model
because of the greater proportion of the diet that was assumed to be fish and the
fact that concentrations of both PCBs and TEQs were greater in fish than in other
prey items. It is noteworthy that the Great Lakes Water Quality Initiative
assumes that fish comprise 85% of a mink’s diet (U.S.Environmental Protection
Agency 1995) for deriving water quality criteria protective of mammals. However,
site-specific determination on the Kalamazoo River suggests that the diet of mink
is comprised predominantly of mammalian species, especially during the winter.

The determination of risk to mink due to PCB concentrations in prey items,
is dependant upon the dietary assumptions and which TRVs were used. At TB,
LOAEL-based HQs for total PCBs and TEQs, based on mean estimated
exposure concentrations, are less than 1.0 for all dietary models except the
literature-based model in which fish comprise 85% of the mink’s diet. Thus, if

fish comprise 85% or more of the mink’s diet, then exposure is potentially great

51

enough to cause risk to mink. If the most conservatively modeled diet (85% fish)
is combined with the most conservative NOAEL-based dietary TRV, the mean
PCB and TEQ-based HQs were 3.4 and 14, respectively. However, the true
NOAEL lies somewhere between the LOAEL and NOAEL. At FC, total PCBs
and TEQs pose minimal risk to mink regardless of the percentage of fish in the

diet or which TRV was utilized.

Comparison of top-down and bottom-up methodologies

The results of the two basic approaches to determining exposure in risk
assessments were compared to determine the accuracy of predicted versus
measured exposures. This comparison was done by comparing resulting HQs
based on a single study from which TRVs were derived. The study conducted by
Bursian et al. (Bursian et al. 2002), was chosen to make this comparison for two
reasons. First, it was the only feeding study from which estimates of both
NOAEL- and LOAEL-based TRVs for both PCBs and TEQS could be derived.
Secondly, the tested doses exhibited the full dose-response range, including both
a NOAEL and LOAEL test dose.

When the upper and lower 95% confidence limits of mink HQs were
compared to the mean dietary HQs, the bottom-up approach consistently
estimated lesser exposure and thus risk of both PCBs and TEQ to mink (Figure 8
and Figure 9) This result was observed for all dietary models used, regardless of
site, effect level, or PCB contaminant expression as total PCBs or TEOs. There
did not appear to be a large difference among the LOAEL-based HQs for PCBs

and TEQs (based on mean exposure) between the top-down and bottom-up

52

 

 

 

 

 

 

    

 

 

 

 

 

 

4 4
A Literature-based
3 B Equally opportunistic . 3
C Site-specific
g 2 - 2 25
A
1 , \ If “‘
C C
\ «J
o . 1 0
TB FC TB FC

NOAEL- Based LOAEL- Based

Figure 8. Comparison of HO values based on predicted concentrations of total
PCB determined based on dietary exposures or concentrations measured in the
livers of mink at Fort Custer (FC) and Trowbridge (TB). The arrows represent the
H08 of three mink dietary models. The solid vertical bars represent the upper
and lower 95% confidence limits of H05 estimated from PCB concentrations in
mink livers. The TRVs used to calculate HQs are based upon a mink feeding

study conducted by Bursian et al. (Bursian et al. 2002).

53

 

 

 

 

 

 

 

 

 

 

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A Literature-based
10 r B E - — 10
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2 6 ~ - 6 25
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NOAEL- Based LOAEL- Based

Figure 9. Comparison of HO values based on predicted concentrations of TEQ
determined based on dietary exposures to HQs based on TEQ concentrations
measured in the livers of mink at Fort Custer (FC) and Trowbridge (TB). The
arrows represent the HQs of three mink dietary models. The solid vertical bars
represent the HQs estimated from TEQ concentrations in mink livers. The TRVs
used to calculate HQs are based upon a mink feeding study conducted by

Bursian et al. (Bursian et al. 2002).

54

approaches (Figures 8 and 9). For example, the LOAEL-based maximum HQs
for PCBs and TEQs were 0.63 for the dietary model and 1.4 for the tissue
residue-based approach. The range of LOAEL-based HQs was less than the
range of NOAEL-based HQs for both top-down and bottom-up approaches,
reflecting the greater uncertainty in the NOAEL-based TRVs.

One explanation of the underestimation of the bottom-up approach, is that
the NIR of a wild mink is greater than that of a confined mink. Although wild male
mink are of similar weight to ranch female mink, one would expect the wild mink
to expend greater energy while hunting for food and defending a territory. Wild
mink would have a greater NIR and therefore have a greater ADD than their
ranch-raised mink counterparts. Alternatively, since the tissue residue-based
TRVs were based on female mink liver and most of the mink captured were male,
there are likely to be gender-specific differences in the toxicokinetics of PCBs in
mink, specifically, from nursing—related elimination of PCBs.

In conclusion, mink on the Kalamazoo River appear to eat predominantly
mammals, at least seasonally, than most conventional models assume. There is
close agreement among different mink feeding studies in respect to effect levels,
except for slightly more uncertainty with TEQ-based NOAELS. Overall, based on
a bottom-up approach for estimating PCB exposure, mink from the KRAOC are
expected to have minimal risk due to PCB exposure. Both the bottom-up and
top-down approaches were in agreement that mink from TB have greater
exposures to PCBs and TEQs than mink from FC. In the reference area, both

exposures to PCBs and TEQs and the resulting estimates of risk were

55

approximately 3 to 5—fold less than in the area of concern, and ranged from 0.04
to 4.9. At TB, depending on the dietary model applied, NOAEL-based HQs
ranged from 0.47 to 3.4 and from 0.73 to 14 for total PCBs and TEQ, respectively.
LOAEL-based HQs for total PCBs and TEQ were less than 1.0 for all dietary
models except the literature-based model in which fish are assumed to comprise
85% of the mink’s diet where HQs were 1.8 and 2.0 for total PCBs and TEQS,
respectively. Because the LOAEL-based HQ values are more certain and
ecologically relevant, risks posed by PCBs in the diet of mink from the KRAOC
were predicted to be minimal. Calculated risk based on dietary models was
slightly less than risk calculations based on site-specific mink tissue residues.
Both approaches were in agreement that the degree of exposure to PCBs and
TEQs were near the threshold for effects on reproduction in mink, but unlikely to

cause population-level effects on mink in the KRAOC.

56

CHAPTER THREE

Habitat Characterization and Mink (Mustela vison) Habitat

Quality of the Kalamazoo River Superfund Site, MI.

Introduction

Located in southwestern Michigan, the main stem of the Kalamazoo River
is approximately 195 km long and flows northwest, entering Lake Michigan near
Saugatuck, Michigan. In 1990, approximately 125 km of the Kalamazoo River
was designated a Superfund site. The site, referred to as the Kalamazoo River
Area of Concern (KRAOC), and extends from Morrow Lake dam to Lake
Michigan (CDM 1999). Polychlorinated biphenyls (PCBs) are the contaminant of
concern, and studies are being conducted to determine the extent to which biota,
specifically mink (Mustela vison), could be potentially adversely affected by this
exposure. Mink are one of the receptors of concern at the KRAOC due to their
sensitivity to PCBs and their relatively great potential for exposure as piscivorous,
top predators (Alexander 1977;Aulerich et al. 1973;Restum et al. 1998).
However, non-contaminant environmental stressors on the Kalamazoo River,
including mink habitat availability and quality, have not been fully addressed in
previous environmental risk assessments.

The mink (Mustela vison) is a semi-aquatic member of the mustelidae
family commonly found in waterways throughout North America, including

Michigan (U.S.Environmental Protection Agency 1993). There is considerable

57

variation in both the type of habitat used and dietary composition (Casson and
Klimstra 1983;Hamilton, Jr. 1936;Sealander 1943;Whitman 1981). For instance,
during the waterfowl breeding season in the prairie pothole region of Canada,
mink had a large proportion of waterfowl in their diet (Arnold and Fritzell 1990).
Mink diet can be very variable in similar areas depending on season. In southern
Michigan, the dietary composition of mink have been reported to be primarily fish
(Alexander 1977) and primarily mammals (Sealander 1943), depending on
location and season.

Mink activity and dietary composition in an area have been shown to be
correlated to prey availability (Loukmas and Halbrook 2001). Stream
improvements such as the creation of pools, placement of logs, and other cover
within the steam channel resulted increased mink activity (Burgess and Bider
1980). Along Lake Ontario, shoreline development for cottages resulted in
decreased cover and vegetative complexity by the shores and mink activity was
found to decrease (Racey and Euler 1983). Therefore, land uses and vegetation
characteristics are likely to affect mink populations along the Kalamazoo River,
regardless of contaminant stressors.

One tool that wildlife managers can use to predict the distribution and
abundance of a species is a Habitat Suitability lndex (HSI). In addition, HSls can
be used to quantify and evaluate the effects of human alterations of the
environment. HSI scores are an index of theoretical carrying capacity and values
can range from 1.0 for optimal habitat to 0.0 for completely unsuitable habitat.

The HSI developed for mink by the US. Fish and Wildlife Service (Allen 1986)

58

assumes that if sufficient vegetation and cover is available in semi-aquatic
habitats to support a prey base, then the habitat is suitable for mink. In addition,
other assumptions include potential food availability, cover, and reproductive
habitat requirements are described by the same set of habitat characteristics
(Allen 1986).

The objective of this study was to quantify mink habitat quality along the
Kalamazoo River (including the KRAOC) using the HSI model. In addition,
habitat was characterized using land use and land cover data. A Geographic
lnforrnation System (GIS) was created to interpolate HSI values from field-
collected data to the entire river area. Habitat suitability data was used to
determine which areas along the Kalamazoo River would unsuitable for mink.
This data will also allow decision makers to visualize how river remediation

alternatives could affect mink habitat availability.

59

Methods

The variables describing suitable mink habitat vary by habitat type (Allen
1986) and the riverine model was chosen as the most suitable model to use for
the Kalamazoo River (Figure 10). The HSI for riverine habitat assumes that if
both terrestrial food and aquatic food items are present, the area will be suitable
for mink (Allen 1986). The variables to measure terrestrial food availability were
canopy cover within 100m of the shore and shoreline cover. The permanence of
water is the only variable that measures it aquatic food will be present. The
measured variables are then used to create a score fore each habitat component
to define a total HSI. Water is present in the Kalamazoo River year-round,
therefore, the terrestrial food availability component was assumed to limit habitat
suitability. Shoreline cover and canopy cover were the variables used to
calculate the suitability index scores (Figure 11). A geometric mean of the two

variables were calculated to calculate the final HSI (Allen 1986).

HSI = (canopy cover suitability index * shoreline cover suitability index)"2 Eqn 1.

60

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Figure 11. Suitability index scores for percent canopy and shoreline cover (Allen

1986).

62

The HSI is defined as:

HSI = Habitat conditions at the site
Optimum habitat conditions

In order to attain an HSI score of 1.0 for mink, the following variables must be
present in a riverine system (Allen 1986):
75% (or more) of year with surface (river) water present
75% (or more) canopy cover of trees and shrubs within 100 m of river's
edge

100% shoreline cover within 1 m of river's edge

Areas along the river that do not have sufficient canopy cover or shoreline
cover result in lesser HSI values. On-site inspection was conducted to measure
HSI components (percent canopy cover and shoreline cover). HSI components
were measured on both river banks at 30 m x 100m transects along the river
approximately 500 m from one another. Transects were reached by canoe (Old
Town Canoe 00.; Old Town, ME, USA). Exact location was recorded with a GPS
receiver (Garmin LTD, Loatha, KS, USA). At each transect, canopy cover was
measured from 100 m perpendicular to the river’s edge at 25 m intervals using a
convex mirror densitometer (Forestry Suppliers Inc; Jackson, MS). Shoreline
cover was ocularly estimated 30 In parallel to the riverbank, at 10 m intervals,
according to the cover class scale developed by Daubenmire (Daubenmire 1959).

Shoreline cover consisted of large and small woody debris, overhanging

63

vegetation, undercut banks, boulders, exposed roots, and emergent aquatic
vegetation.

The data from each transect was imported into ArcView 3.2 (ESRI;
Redland, CA, USA). The area between measured transects was interpolated
with Spatial Analyst using the IDW method to provide HSI data for the entire area
within 100m of the river. HSI was only interpolated in areas where HSI data was
collected, not in areas where no data was collected (such as the City of

Kalamazoo).

64

Results and Discussion

Shoreline and canopy cover was measured at 249 transects representing
approximately 45km of river shoreline (Figure 12). HSI of individual transects
ranged from 0.05 - 0.99 (average 0.76). 75% of transects were considered good
habitat. When transect data was interpolated throughout the river stretches, 770
km2 of riverine habitat was considered good habitat, while only 190km2 was
considered marginal or poor habitat (Figure 13 -Figure 15)

The section of river furthest downstream was located from Lake Allegan
downstream to New Richmond, Ml (Figure 13). This area was primarily
considered good habitat and is mostly located within the Allegan State Game
area (Figure 13). This section of river was characterized by forested areas that
had relatively complex shorelines (personal observation). The middle section of
the river is located from D-Ave in Kalamazoo, MI downstream to Allegan, Ml
(Figure 14). This area includes the portion of the KRAOC in which samples were
collected for the environmental risk assessments described in Chapters 1 and 2.
In this section, the areas described as marginal/poor habitat (Figure 14) typically
correspond to former impoundment areas that were dominated by grasses,
stinging nettle (Urtica dioica), and ragweed (Ambrosia artemisiifolia) which
provides no canopy cover (personal observation). In addition, the shoreline in
these areas tended to be very simple, with little shoreline cover (personal
observation). The section of river furthest upstream, corresponds to Fort Custer
(FC), the upstream reference area, used as a study site in Chapters 1 and 2

(Figure 15). In this section, marginal/poor habitat typically corresponded to

65

residential and industrial areas that are found at both the upstream and
downstream sections of FC (Figure 15). The good habitat in the middle of the FC
area corresponds to the Fort Custer State Recreation Area.

Because the HSI is so general, it produces very coarse results. The
areas identified as poor habitat were primarily urban/residential or areas with little
to no trees and simple shorelines. This level of assessment could be attained by
a quick look at the site. When prey availability was studied, mink habitat
suitability was correlated with with prey availability (Loukmas and Halbrook 2001).
Therefore, surveys of potential prey items would have to be conducted in order to
provide more specific and detailed results regarding habitat quality.

The areas of the Kalamazoo River that were sampled indicate there is
substantial habitat of good quality available to mink. While there are some areas
with poor habitat quality, habitat quality in the sampled areas is not likely a
limiting factor to mink populations residing along the Kalamazoo River. A
previous risk assessment conducted on the Kalamazoo River determined
observed levels of PCB exposure would not be expected to cause adverse
population-level effects on mink. However, if remedial actions within the KRAOC

are to be conducted, the effects upon mink habitat quality should be considered.

66

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BIBLIOGRAPHY

Alexander G. 1977. Food of vertebrate predators on trout waters in north central
lower Michigan. Michigan Academician 10:181-195.

Allen, Arthur W. 1986. Habitat suitability index models: mink, revised. 82(10.127).
US. Fish and Wildlife Service, Washington, D.C., USA.

Arnold TW, Fritzell EK. 1990. Habitat use by male mink in relation to wetland
characteristics and avian prey abundances. Can J Zool 68:2205-2208.

Aulerich RJ, Ringer RK, lwamato S. 1973. Reproductive failure and mortality in
mink fed on Great Lakes fish. J Reprod Fertil Suppl 19:365-376.

Aulerich RJ, Ringer RK, Seagran HL, Youatt WG. 1971. Effects of feeding coho
salmon and other Great Lakes fish on mink reproduction. Can J Zool 49:611-616.

Blasland Bouck and Lee, Inc. 1994. Allied Paper lnc./Portage Creek/Kalamazoo
River Superfund Site Remedial Investigation/Feasibility Study. Draft Technical
Memorandum 14 Biota Investigation Report. 1994. Syracuse, NY, USA

Blasland, Bouck and Lee Inc. 2000. Allied Paper, Inc/Portage Creek/Kalamazoo
River superfund site RI/FS Remedial Investigation Report Phase 1. Syracuse,
NY, USA,

Brunstrom B, Lund BO, Bergman A, Asplund L, Athanassiadis I, Athanasiadou M,
Jensen S, Orberg J. 2001. Reproductive toxicity in mink (Mustela vison)
chronically exposed to environmentally relevant polychlorinated biphenyl
concentrations. Environ Toxicol Chem 20:2318-2327.

Burgess SA, Bider JR. 1980. Effects of stream habitat improvements on
invertebrates, trout populations, and mink activity. J Wildl Manage 44:781-880.

Bursian SJ, Sharma C, Aulerich RJ, Yamini B, Mitchell RR, Tillitt DE, Orazio C.
11/2002. Dietary exposure of mink to fish from the Housatonic river: effects on

71

CCCC:

E

Eh CI“

F

n

CC.

reproduction and survival. Presented at: SETAC annual conference, Salt Lake
City, UT.

Buskirk SW, Lindstedt SL. 1989. Sex biases in trapped samples of mustelidae. J
Mammal 70:88-97.

Casson JE, Klimstra WD. 1983. Winter foods of mink in southern Illinois. Trans
Illinios Acad Sci 76:281-292.

Camp Dresser and McKee. 1999. Final Baseline Ecological Risk Assessment,
Allied Paper, lnc./ Portage Creek/ Kalamazoo River Superfund Site. Cambridge,
MA, USA.

Champoux L. 1996. PCBS, dioxins and furans in hooded merganser (Lophodytes
cucullatus), common merganser (Mergus merganser) and mink (Mustela vison)
collected along the St Maurice river near La Tuque, Quebec. Environ Poll
92:147-153.

Daubenmire RF. 1959. A canopy-coverage method of vegetaitional analysis.
Northwest Sci 33:43-64.

Durfee, Robert L., Contos, Gayaneh, Whitmore, Frank C., Barden, James D.,
Hackman, E. E., and Westin, Robert A. 1976. PCBs in the Unites States:
Industrial use and environmental distributions. EPA 560/6-76-005, -488. US.
Environmental Protection Agency, Washington, D.C., USA.

Elliot JE, Henny CJ, Harris ML, Wilson LK, Norstrom RJ. 1999. Chlorinated
hydrocarbons in livers of American mink (Mustela vison) and river otter (Lutra
canadensis) from the Columbia and Frasier River Basins, 1990-1992. Environ
Monit Assess 57:229-252.

Foley RE, Jackling SJ, Sloan RJ, Brown MK. 1988. Organochlorine and mercury
residues in wild mink and otter: comparison with fish. Environ Toxicol Chem
72363-374.

Gerell R. 1970. Home ranges and movements of the mink Mustela vison
Schreber in southern Sweden. Oikos 21:160-173.

72

ll" r

llrLrE1

Giesy JP, Kannan K. 1998. Dioxin-like and non-dioxin-Iike toxic effects of
polychlorinated biphenyls (PCBs): Implications for risk assessment. Crit Rev
Toxicol 28:51 1-569.

Haffner GD, Glooshenko V, Straugham CA, Hebert CE, Lazar R. 1998.
Concentrations and distributions of polychlorinated biphenyls, including non-ortho

congeners, in mink populations from southern Ontario. J Great Lakes Res
24:880-888.

Hahn ME, Lamb TM, Schultz ME, Smolowitz RM, Stegeman JJ. 1993.
Cytochrome P4501A induction and inhibition by 3,3’,4,4'-tetrachlorobiphenyl in
an Ah receptor-containing fish hepatoma cell line (PLHC-1). Aq Tox 26:185-208.

Halbrook RS, Aulerich RJ, Bursian SJ, Lewis L. 1999. Ecological risk
assessment in a large river-reservoir: 8. Experimental study of the effects of

polychlorinated biphenyls on reproductive success in mink. Environ Toxicol
Chem 18:649-654.

Halbrook RS, Woolf A, Hubert GF, Ross S, Braselton WE. 1996. Contaminant
concentrations in Illinois mink and otter. Ecotoxicology 5:103-1 14.

Hamilton WJ, Jr. 1936. Food habits of the mink in New York. J Mammal 17:169.

Harding LE, Harris ML, Stephen CR, Elliot JE. 1999. Reproductive and
morphological condition of wild mink (Mustela vison) and river otters (Lutra
canadensis) in relation to chlorinated hydrocarbon contamination. Environ Health
Perspect 107:141-147.

Heaton SN, Bursian SJ, Giesy JP, Tillitt DE, Render JA, Jones PD, Verbrugge
DA, Kubiak TJ, Aulerich RJ. 1995. Dietary exposure of mink to carp from
Saginaw Bay, Michigan. 1. Effects on reproduction and survival, and the potential
risks to wild mink populations. Arch Environ Contam Toxicol 28:334-343.

Henny CJ, Blus LJ, Gregory SV, Stafford CJ. 1981. PCBs and organochlorine
pesticides in wild mink and river otters from Oregon. In: Chapman JA, Pursley D,
editors. Worldwide furbearer conference proceedings Vol. III. unk: unk.p 1763-
1780.

73

lrf‘E

[\FCE

Lrtr‘

“NE

9WD

Hochstein JR, Bursian SJ, Aulerich RJ. 1998. Effects of dietary exposure to
2,3,7,8—tetrachlorodibenzo-p-dioxin in adult female mink (Mustela vison). Arch
Environ Contam Toxicol 35:348-353.

Kannan K, Blankenship AL, Jones PD, Giesy JP. 2000. Toxicity reference values
for the toxic effects of polychlorinated biphenyls to aquatic mammals. Hum Ecol
Risk Assess 62181-201.

Kihlstrom JE, Olsson M, Jensen S, Johansson A, Ahlbom J, Bergman A. 1992.
Effects of PCB and different fractions of PCB on the reproduction of the mink
(Mustela vison). Ambio 21 :563-569.

Leonards PEG, DeVries TH, Minnaard W, Stuijfzand S, De Voogt P, Cofino WP,
Van Straalen NM, van Hattum B. 1995. Assessment of experimental-data on
PCB-induced reproduction inhibition in mink, based on an isomer-specific and
congener-specific approach using 2,3,7,8-tetrachlorodibenzo-p-dioxin toxic
equivalency. Environ Toxicol Chem 14:639-652.

Litvaitis JA, Titus K, Anderson EM. 1996. Measuring vertebrate use of terrestrial
habitats and foods. In: Bookhout TA, editor. Research and management
techniques for wildlife and habitats. Bethesda, MD, USA: The Wildlife Society.p
254-274.

Lockie JD. 1959. The estimation of the food of foxes. J Wildl Manage 23:224-227.

Loukmas, Jefferey J. 1994. Criteria for quantifying mink (Mustela vison) habitat
quality in the Great Lakes basin. 72. Thesis. Southern Illinois University at
Carbondale. Carbondale. IL, USA.

Loukmas JJ, Halbrook RS. 2001. A test of the mink habitat suitability index model
for riverine systems. Wildl Soc Bull 29:821-826.

Major, AR Carr, KC. 1991. Contaminant concentrations in Connecticut and
Masssachusetts mink. RY91-NEFO-5-EC. US. Fish and Wildlife Service, New
England Field Office. Concord, NH, USA.

Mayack, DT Loukmas, JJ. 2001. Progress report on Hudson river mammals:
polychlorinated byphenyl (PCB) levels in mink, otter, and muskrat and trapping
results for mink, the upper Hudson river drainage, 1998-2000. New York State
Department of Environmental Conservation. Report. Albany, NY, USA..

74

O'Shea T, Kaiser JE, Askins GR, Chapman JA. 1981. Polychlorinated biphenyls
in a wild mink population. In: Chapman JA, Pursley D, editors. Proceedings of the
Worldwide Furbearer Conference Vol.3.p 1746-1751.

Osowski SL, Brewer LW, Baker OE, Cobb GP. 1995. The decline of mink in
Georgia, North Carolina, and South Carolina: the role of contaminants. Arch
Environ Contam Toxicol 29:418-423.

Pastva, Stephanie D. 2003. Exposure and risk of PCBs to mink (Mustela vison)
at the Kalamazoo River Superfund site, Michigan. Dissertation. Michigan State
University. East Lansing, MI, USA.

Pastva SD, Blankenship AL, Bradley P, Jones PD, Kay D, Neigh A, Park C,
Strause K, Zwiernik M, Giesy JP. 2003a. Dietary-based risk assessment of PCBs

to mink at the Kalamazoo River superfund site, Michigan. Environ Toxicol Chem
00:000.

Pastva SD, Blankenship AL, Bradley PW, Jones PD, Kay D, Zwiemik MJ, Giesy
JP. 2003b. Risks of polychlorinated biphenyls to mink (Mustela vison) at the
Kalamazoo River superfund site, Michigan. Environ Toxicol Chem 00:000.

Poole KG, Elkin BT, Bethke RW. 1998. Organochlorine and heavy metal
contaminants in wild mink in western Northwest Territories, Canada. Arch
Environ Contam Toxicol 34:406-413.

Racey GD, Euler DL. 1983. Changes in mink habitat and food selection as
influenced by cottage development in central Ontario. J Appl Ecol 20:387-402.

Render JA, Aulerich RJ, Bursian SJ, Nachreiner RF. 2000. Proliferation of
maxillary and mandibular periodontal squamous cells in mink fed 3,3',4,4',5-
pentachlorobiphenyl (PCB 126). J Vet Diagn Invest 12:477-479.

Restum JC, Bursian SJ, Giesy JP, Render JA, Helferich WG, Shipp EB,
Verbrugge DA. 1998. Multigenerational study of the effects of consumption of
PCB-contaminated carp from Saginaw Bay, Lake Huron, on mink. 1. Effects on
mink reproduction, kit growth and survivial, and selected biological parameters. J
Toxicol Environ Heal A 54:343-375.

Schwartz TR, Stalling DL. 1987. Are polychlorinated biphenyl residues
adequately described by Aroclor mixture equivalents? Isomer-specific principal

75

components analysis of such residues in fish and turtles. Environ Sci Technol
21 :72-76.

Sealander JA. 1943. Winter food habits of mink in southern Michigan. J Wildl
Manage 72411-417.

Shipp EB, Restum JC, Giesy JP, Bursian SJ, Aulerich RJ, Helferich WG. 1998.
Multigenerational study of the effects of consumption of PCB-contaminated carp
from Saginaw Bay, Lake Huron, on mink 2. Liver PCB concentration and
induction of hepatic cytochrome P-450 activity as a potential biomarker for PCB
exposure. J Toxicol Environ Heal A 54:377-401.

Tillitt DE, Gale RW, Meadows JC, Zajicek JL, Peterman PH, Heaton SN, Jones
PD, Bursian SJ, Kubiak TJ, Giesy JP, Aulerich RJ. 1996. Dietary exposure of
mink to carp from Saginaw Bay. 3: Characterization of dietary exposure to
planar halogenated hydrocarbons, dioxin equivalents, and biomagnification.
Environ Sci Technol 30:283-291.

US. Environmental Protection Agency. 1993. Environmental Factors Handbook.
Report. Washington, DC, USA.

U.S.Environmental Protection Agency. 1995. Great Lakes water quality initiative
criteria documents for the protection of wildlife. EPA-820-B-95-008. Report.
Washington, DC, USA.

US. Environmental Protection Agency. 1998. Guidelines for ecological risk
assessment. EPA/630/R-95/002F. Report. Washington, DC, USA.

Valoppi, Laura, Petreas, Myrto, Donohoe, Regina, Sullivan, Laurie, and Callahan,
Clarence. 1998. Use of PCB congener and homologue analysis in ecological risk
assessments. US. Environmental Protection Agency, Region 9, Biological
Technical Advisory Group. San Francisco, CA, USA.

Van den Berg M, Birnbaum L, Bosveld ATC, Brunstrom B, Cook P, Feeley M,
Giesy JP, Hanberg A, Hasegawa R, Kennedy SW, Kubiak TJ, Larsen JC, van
Leeuwen FXR, Liem AKD, Nolt C, Peterson RE, Poellinger L, Safe S, DS, Tillitt
D, Tysklind M, Younes M, Waem F, Zacharewski T. 1998. Toxic equivalency
factors (TEFs) for PCBs, PCDDs, PCDFs for humans and wildlife. Environ Health
Perspect 106:775-792.

76

Whitman, Jackson S. 1981. Ecology of the mink (Mustela vison) in west-central
Idaho. 101. 1981. Thesis. University of Idaho.

77