INFORMATION TO USERS

This manuscript has been reproduced from the microfilm master. UMI films

the text directly from the original or copy submitted. Thus, some thesis and

dissertation copies are in m e r face, while others may be from any type of

computer printer.

The quality of this reproduction is dependent upon the quality of the

copy submitted. Broken or indistinct print, dored or poor quality illustrations

and photographs, print bleedthrough, substandard margins, and improper

alignment can adversely affect reproduction.

In the unlikely event that the author did not send UMI a complete manuscript

and there are missing pages, these will be noted. Also, if unauthorized

copyright material had to be removed, a note will indicate the deletion.

Oversize materials (e-g., maps, drawings, charts) are reproduced by

sectioning the original, beginning at the upper left-hand corner and continuing

from left to right in equal sections with small overlaps.

Photographs included in the original manuscript have been reproduced

xerographically in this copy. Higher quality 6' x 9" black and white

photographic prints are available for any photographs or illustrations appearing

in this copy for an additional charge. Contact UMI directly to order.

Bell 8 Howell Information and Learning 300 North Zeeb Road, Ann Arbor, MI 481OS1346 USA

800-521-0600

THE AQUATIC MACROPHYTE VALLISNERLQ AMERICANA

AS A BIOMONITOR OF SITE QUALITY

IN GREAT LAKES AREAS OF CONCERN

by

Kelly L. Potter

A Thesis

Submitted to the Faculty o f Graduate Studies and Research

through the Department of Biological Sciences

in Partial Fulfillment of the Requirements for

the Degree of Master of Science at the

University of Windsor

Windsor, Ontario, Canada

1998

O 1998 Kelly Potter

National Library 1+1 of Canada Bibliot hwue nationale du Canada

Acquisitions and Acquisitions et Bibliographic Services services bibliographiques

395 Wellington Street 395. rue Wellington Ottawa ON K IA ON4 OttawaON KtAON4 Canada CaMda

The author has granted a non- exclusive licence allowing the National Library of Canada to reproduce, loan, distribute or sell copies of this thesis in microform, paper or electronic formats.

The author retains ownership of the copyright in this thesis. Neither the thesis nor substantial extracts fiom it may be printed or otherwise reproduced without the author's permission.

L'auteur a accorde une licence aon exclusive pennettant a la Bibliotheque nationale du Canada de reproduire, preter, distribuer ou vendre des copies de cette these sous la fome de rnicrofiche/~, de reproduction sur papier ou sur format electronique.

L'auteur conserve la propriete du droit d'auteur qui protege cette these. Ni la these ni des extraits substantiels de celle-ci ne doivent &e imprimes ou autrement reproduits sans son autotisation,

ABSTRACT

Leaf-to-root surface area ratios in VaNisneria americana provide a simple and

inexpensive. relative measure of sub-lethal effects of organochlorine contamination. The

present study was conducted to determine whether this index of surface area could be

used as an effective biomonitor of overall site quality in stressed aquatic ecosystems. The

leaf-to-root surface area ratio was determined for samples of C/. urnericana collected from

225 microsites within 12 Areas of Concern (environmentally contaminated areas

designated by the International Joint Commission) throughout the Laurentian Great Lakes

of Ontario. Statistical analyses indicate that 77% of the variation in the surface area

index could be attributed to differences behveen microsites. with only 23% of variation

occurring among plants within a microsite. A multiple regression equation was

deveIoped for predicting the leaf-to-root surface area ratio from several measures of

microsite qualit).. Significant parameters affecting the surface area ratio included plant

density. light intensity. and an index of sediment contamination. In contrast. measures of

water contamination did not show any corre1ation with leaf-to-root surface area ratio.

These observations support the hypothesis that K arnericana accumulates contaminants

primarily from the sediments. Both the leaf-to-root fresh mass ratio, and total fresh mass

of I: urnericana plants showed similar results and could be used as approximate

substitutes for the leaf-to-root surface area ratio. Mapping contours of leaf-to-root

surface area ratios appeared to correspond with suspected contours of contamination.

enabling the identification of point source impact zones. It is concluded that the

. . 111

regression model developed here provides a simple. inexpensive means for monitoring

overall site quality throughout the Great Lakes.

Measures of plant structure in K americana were also investigated for use in

sediment toxicity testing. Greenhouse studies using both a sediment dilution series. and

using sediments from diverse Areas of Concern. suggested that besides sediment

contamination. the leaf-to-root surface area ratio may be affected by other site quality

parameters such as nutrients and dissolved oxygen. The negative effects observed in

sediment toxicity tests differ from effects in the field however. since experimental plants

hakve not been allowed to adapt to the sediments. and can therefore experience growth

inhibition.

DEDICATION

This thesis is dedicated to my parents. John and Mary. who have always been

there to lend me moral (and financial!) support. and of course to Heather. for her

encouragement. and faith in me.

I would like to thank Dr. Maciej Biernacki. originator of the surface area ratio

biomonitoring technique. for his assistance with the field sampling in 1995 and for

providing valuable advice in the analysis of the data. I am also indebted to Dr. Jan

Ciborowski (Biological Sciences. University of Windsor) and Robyn Nease (Computing

Services. University of Windsor) for their statistical advice. Thanks are also due to my

committee members. Dr. Chris Lakhan (Geography. University of Windsor) and Dave

Dolan (International Joint Commission). for taking the time to review this manuscript and

for providing helpful input. Dr. Jon Lovett Doust (Biological Sciences) provided

\.aluable guidance in the planning stages of this research as well as offering much

appreciated editorial advice. I would aiso like to thank my colleagues Susan Roe. David

Susko and Jeremy VanDerWal for their support and advice throughout my research

endeavours. Numerous summer research assistants have been indispensible in helping

with the considerable tasks of data collection and entry. including: Nadine Jarrett. Allison

Sinclair. Bridget Wales. Erika Devos. Kawssar Nadi. Chantal Garnett, Jovi Asuncion.

Heather Meadows. Samantha Broderick. Khadra Nur. Aman Tut. and Seth O\vusu.

Finally. I would like to express my sincere appreciation towards my supervisor. Dr.

Leslq. Lovett Doust. for her encouragement. her assistance. and for providing me with

the opportunity to conduct research in the fascinating field of aquatic ecology.

TABLE OF CONTENTS

ABSTRACT

DEDICATION

ACrnOWLEDGEMENTS

LIST OF TABLES

LIST OF FIGURES

LIST OF ACRONYMS USED IN THIS THESIS

CH.4PTER

1 . lNTRODUCTION

Great Lakes Areas of Concern

Biomonitoring in the Great Lakes

Aquatic plants as biomonitors

Leaf-to-root surface area ratio

Outline o f research objectives

7 . SITE QUALITY M STRESSED AQUATIC ECOSYSTEMS

AND VALLISNERIA AhfERICAhiri: IMPLICATIONS FOR

WIDESPREAD BIOMONITOIUNG

introduction

Methods

Test organ ism

Study sites and sampling protocol

Calculation of plant perjorrnance and

microsite contamination indices

Star istical analyses

Mapping potential point source impuct zones

... 111

v

vi

xi

xiv

xvi i

Results

Variation in leaf-to-root surface area ratio

M..iltiple regression

Regression using addirionul data

Results obtained with the leaf-to-root mass rutio

and with lhe totalfiesh mass

Comparison of leaf-to-root surface area ratios

with previous srzrdies

Regressions using separate contaminant indices

for metal and organic compounds

Point source impact zones

Discussion

U S E OF VALLISKENA AMERICAM4 IN LABORATORY-

B A S E D SEDIMENT TOXICITY TESTING

Introduction

Experiment # 1 : Plant performance in sediment from

Rouge River: response o f Vallisneria

an~ericana to a sediment dilution series

Methods

Sediment

Experimental plants

Eiperirnental setup

Hanws~v

Dala collected

Statistical analyses

Results

Discussion

Experiment #2: Sediment toxicity tests using

Vullisneria americana

Methods

Sediment trearmenrs

Experimental plants

Erperirnental setup

Harvest and data collection

Sediment qualih database

Dutu analysis

Results

Discussion

GENERAL DISCUSSION

Comparison of reszrlrs between field and

greenhouse studies

Sedintent toxiciw testing

Comparison of plant measures used in this

study with root:shoor ratio

Contuntinun f indices

Recommended protocol for biomonitoring in

Areas of Concern

Sediment contamination

LITERATURE CITED

APPENDIX A: Description of Areas of Concern studied 129

APPENDIX B: References used in compilation of microsite database 137

APPENDIX C : Criteria for assigning contaminant scores 1 SO

APPENDLX D: Sediment contaminant scores for 1995 survey microsites 155

.QPEND[X E: Water contaminant scores for 1 995 survey microsites 171

.APPENDIX F: Sediment contaminant scores for toxicity test 182

.*PENDIX G: Maps of Areas of Concern showing collection locations

for sediments and Vuliisneria americana samples 192

LIST OF TABLES

Page Table

Chapter 2:

2.1 Results of multiple linear regression. with leaf-to-root surface

area ratio of I? americana as the dependent variable. 24

Comparison of regression coefficients for the two model

equations. 26

Results of regression with leaf-to-root surface area ratio using

pooled data. 28

Results of multiple linear regression with leaf-to-root fresh mass

ratio as the dependent variable. 30

Results of multiple linear regression with total fiesh mass of

Vallisneria americana plants as the dependent variable. 3 1

Results of multiple linear regression using separate sediment

contamination indices for metals and organics. 33

Chapter 3 :

3.1 Results of analysis of variance to determine the effects of

sediment treatment and aquaria on the iotd fresh mass

of If: umericann plants grown in various dilutions of

Rouge River sediment.

Description of eleven sediments collected from Areas of

Concern. and synthetic standardized sediment. used for

sediment toxicity testing. 78

Description of coHection sites for sediments used in sediment

toxicity test. 79

Page Table

3.4 P-values fiom analyses of variance to determine the effects of

sediment origin and aquaria on the leaf-to-root surface

area ratio. IeaGto-root fiesh mass ratio. and total fiesh

mass of VaNisneria americana. 86

Results of analysis of variance to determine the effects of

sediment origin and tank on the total number of

rarnets produced by V. americana.

Changes in fresh total plant mass. fresh leaf mass and fresh

root mass o f Vaffisneria americana plants grown for

eight weeks in standard sediment. or one of eleven

sediments originating from different Areas of Concern. 94

Changes in leaf surface area root surface area, and leaf-to-root

surface area ratio of Vallisneria americana plants grown

for eight weeks in standard sediment. or one of eleven

sediments originating from different Great Lakes Areas

of Concern. 95

Comparison of leaf-to-root surface area ratios for I/. americana

collected from six sites in Great Lakes Areas of Concern

in 1995. and of C': americana collected fiom Mitchells

Bay (Lake St. Clair) but subsequently grown in

sediments collected from the same six sites in 1996.

xii

Table

Appendices:

C. 1

C.3

C . 3

C .4

D. 1

Page

Scoring criteria for metals in the water column. 151

Scoring criteria for organic contaminants in the water column. 152

Scoring criteria for metals and nutrients in sediment. I 5 3

Scoring criteria for organic contaminants in sediment. 154

Severity of sediment contaminant concentrations at each

sampled microsite. 156

Severity of water column contaminant concentrations at each

sampled microsite. 172

Calculation of metal contaminant index. 188

Calculation of organic contaminant index. 189

Calculation of organic matter index. 191

Figure

LIST OF FIGURES

Page

Chapter 1 :

1 . 1 Areas of Concern in the Great Lakes - St. Lawrence River

Basin. 2

Drawing of Vallisneria americana Mich. (Hydroc haritaceae). 9

Chapter 2 :

2.1 Location of the Areas of Concern sampled in 1995.

3 3 -.- Mean (* SE) leaf-to-root surface area ratios for plants at each

of twelve Areas of Concern.

Histograms for three metal contaminants and three organic

contaminants. illustrating the range and frequency

distributions of concentrations present in sediments

from sites throughout the Great Lakes.

Mapping potential point source impact zones in the Bay of

Quinte Area of Concern:

a) Enlarged view of the sampling area near Trenton.

b) Enlarged view of the sampling area near Belleville.

c Enlarged view of the sampling area near Picton.

Potential point source impact zones in the St. L2wence River

Area of Concern.

Potential point source impact zones in the Severn Sound

Area of Concern.

Potential point source impact zones in the Spanish Harbour

Area of Concern.

xiv

Figure Page

Chapter 3:

3.1 Mean fresh mass (* SE) of V. americana plants grown in

various dilutions of Rouge River sediment for two

weeks.

Mean fresh mass (* SE) of V. americana plants grown in

various dilutions of Rouge River sediment for eight

weeks. 66

Changes in mean Ieaf-to-root surface area ratio with time for

C'allisneria americana plants grown in five dilutions

of Rouge River sediment.

Patterns of biomass aliocation to leaf tissue. caudex tissue. and

root tissue in 17allisneria americuna grown in various

dilutions of Rouge River sediment. 69

Linear regression of the leaf-to-root surface area ratio calculated

for only the original (parent) ramet and the leaf-to-root

surface area ratio calculated over all sister ramets

produced over the experimental period.

Effects of sediments with varying types and levels of

contamination on the mean (* SE) leaf-to-root surface

area ratio in Vallisneria americana. 87

Effects of sediments with varying types and levels of

contaminants on the mean (* SE) leaf-to-root fresh

mass ratio in Vallisneria arnericana.

Effects of sediments with varying types and levels of

contaminants on the mean (* SE) total fresh mass of

Fallisneria americana.

Figure

Appendices:

G. 1 The St. Marys River Area of Concern.

G.2 The Spanish Harbour Area of Concern.

G.3 The Severn Sound Area of Concern.

G.4 The Cotlingwood Harbour Area of Concern.

G.5 The St. Clair River Area of Concern.

G.6 The Detroit River Area of Concern.

G.7 The Rouge River Area of Concern.

G.8 The Wheatley Harbour Area of Concern.

G.9 The Niagara River Area of Concern-

G. 10 The Hamilton Harbour Area of Concern.

G.1 1 The Metropolitan Toronto and Region Area of Concern.

G.12 The Port Hope Harbour Area of Concern.

G. 13 The Bay of Quinte Area of Concern.

G.14 The St. Lawrence River Area of Concern.

Page

xvi

LIST OF ACRONYMS USED IN THIS THESIS

AOC

.ARCS

BHC

DO

COD

DDE

DDT

HCB

I JC

LO1

OCS

PAHs

PAR

PCBs

RAP

TCB

TCDD

TCE

TKN

TOC

area of concern

Assessment and Remediation of Contaminated Sediment

hexachlorocyclohexane (benzenehexachloride)

dissolved oxygen

chemical oxygen demand

dichlorodiphenyl dichloroethylene

dichlorodipheny 1 trichloroethane

hexachlorobenzene

International Joint Conmission

loss on ignition

octachlorostyrene

polynuclear (polycyclic) aromatic hydrocarbons

photosynthetically active radiation

polychlorinated biphenyls

remedial action plan

total chlorinated benzenes

tetrachlorodibenzodioxins

trichloroethy lene

total kjeldahl nitrogen

total organic carbon

Chapter 1 :

INTRODUCTION

Great Lakes Areas of Concern

The Great Lakes Water Quality Board of the International Joint Commission has

identified forty-three Areas of Concern (AOCs) in the Lawentian Great Lakes - St.

Lawrence River system (Fig. 1.1 ), These AOCs are locations where there has been an

impairment of the area's beneficial uses or ability to support aquatic life (Hartig &

Thomas 1988). The impairments at these AOCs may be due to any or all of the

fo 11 owing: excessive nutrient inputs: high bacterial counts; contamination of water

column and/or sediment with heavy metals. oil. pesticides. PCB's. organochlorines. and

other toxic substances.

In an effort to identie each site's particular problems and implement plans for

restoration. Remedial Action Plans (RAPS) are being developed for each of the forty-

three AOCs. The RAP process comprises three stages. Stage one involves defining the

problems particular to an area and identifying the possible causes or sources of those

problems. Stage two requires the development of plans for remedial and preventative

measures which will restore the area's beneficial uses. Once these remedial plans have

actually been carried out. stage three involves demonstrating that the beneficial uses of

the AOC have truly been restored (Hartig & Law 1994). As of 1998. stage two had been

completed for all but two Canadian AOCs (Gail Krantzberg, pers.com.). To date. stage

three of the RAP process has only been fdly completed for one AOC. Collingwood

Harbour. which was "delisted" in 1 994 (Krantzberg & Houghton 1 996).

There are 17 Great Lakes Areas of Concern located in the province of Ontario.

This study focusses on thirteen of these areas: three located in Lake Huron (Spanish

Harbour. Collingwood Harbour. Severn Sound), one in Lake Erie (Wheatley Harbour).

four in Lake Ontario (Hamilton Harbour. Toronto. Port Hope Harbour. Bay of Quinte).

and five connecting channels which are shared between Ontario and the United States (St.

M q s River. St. Clair River. Detroit River. Niagara River. St. Lawrence River). The

remaining four Ontario Areas of Concern. which were not studied in this thesis (Thunder

Ba>\ Nipigon Bay. Jackfish Bay. Peninsula Harbour) are ail located in Lake Superior. In

addition to the Ontario AOCs. one AOC in the United States. the Rouge River. was

included in this study. For a brief description of each of the studied AOCs and their

particular contamination concerns please refer to appendix A.

Biomonitoring in the Great Lakes

-4s the burden of persistent toxic compounds discharged into waterways continues

to increase. there is a growing need for simple. inexpensive methods to assess site quality

in aquatic ecosystems. and to identify degraded microsites requiring remediation (Dolan

& Hartig 1996). In order to effectively allocate funds for remediation projects. it is

important to determine relative contamination levels between different Areas of Concern.

as well as to locate contamination hotspots within an AOC. Assessmegt of contaminant

leveis over time is also needed in order to evaluate the effectiveness of remedial efforts.

Analytical methods for detecting organic and metallic pollutants in sediment, water or

4

tissue are so costly that it is impractical to use them for routine repeated assessments. and

in any event such measurements don't necessarily reflect bioavailability of contaminants

or the cumulative loadings to which the biota are exposed. For example. the availability

of sediment-bound metals for uptake by aquatic organisms has been found to be affected

by other factors. such as organic matter content (Coquery & Welbourn 1995). pH

(Jackson el al. 1993. Crowder 199 1 ). redox potential (Jackson et ul- 1993). and iron or

manganese oxides in sediments (Crowder 199 1 ). Therefore. measurements of total

contaminant concentrations in the environment may not be a good estimate of the

concentrations which are biologically available to the food web. An alternative

environmental management tool involves the use of living organisms as biomonitors.

Biomonitoring can be defined as. "the use of organisms in siru to identify and quantiQ

toxicants in an environment" (Chaphekar 199 1 ). This procedure takes advantage of the

ability of living organisms to accumulate contaminants in their tissues through

bioconcentration (uptake from the ambient environment) and biomagnification (uptake

through the food chain). In contrast to chemical analyses of abiotic samples that merely

measure the concentration of contaminants present in an area the ability of biota to

accumulate contaminants enables them to indicate the total pollution loadings present in

an environment (Lovett-Doust ei al. 1994a). With periodic sampling for chemical tests.

only ambient concentrations are measured and they may not give an accurate

representation of the situation if contaminants are being diluted or released in pulses

(Lovett-Doust et a[. 1993). The utility of chemical analyses can also be restricted by their

detection limits. Often toxicants can cause adverse biological effects at concentrations

bslou- the detection capabilities of analytical tests (Lovett Doust el al. 1994a).

Various animals (including fish. birds. and benthic invertebrates. among others)

have been studied as biomonitors in the Great Lakes. Spottail shiners (Nofropis

hrrdsonius: Suns et al. 1 99 1. Suns & Hitchin 1 992) and herring gull eggs (Lams

argentatzrs: Struger et al. 1985. Weseloh et al. 1990. Mineau et al. 1 984) have been used

estensiveiy to monitor water contaminants. Contamination of sediments has also been

studied using white suckers (Carosrorntrs commersoni: Smith el ai. 1992). Other popular

biomonitors include various species of molluscs (Krieger 1984. Kauss & Hamdp 1985.

Pugsley et ai. 1985. Pugsley et al. 1988. Muncaster et al. 1989. Richman 1992.

Krantzberg 1992). oligochaetes and larval chironomids (Krieger 1984). adult Trichoptera

and Ephemeroptera (Ciborowski & Corkum 1988. Kovats & Ciborowski 1 989). red-

~vinged blackbirds (Agelaitrs phoeniceus) and tree swallows (Tachyeineta bicoior: Bishop

ct ul. 1995. Martin el al. 1995) and even leeches (Richman 1992). However. many

difficulties and confounding variables are associated with the animal model as a

biomonitor (see. eg.. Lovett-Doust er al. 1994a).

Aquatic plants as biomonitors

Although they have been largely overlooked as biomonitoring candidates. there

are a number of reasons why aquatic macrophytes may actually be more appropriate in

these studies. As primary producers. macrophytes are located at the base of the aquatic

food web. Consequently. they will be among the first organisms affected by the release

of tosic substances into the water. perhaps serving as an early warning signal (Lovett-

Doust er al. 1994a). As stationary organisms there is no need to cage rooted aquatic

macrophytes. unlike some other organisms. Another advantage of being stationary is that

macrophytes will directly reflect their local conditions. in contrast with many fish which

are migratory. or top predators such as birds whose diet may not come entirely from the

aquatic food chain (Lovett-Doust et al. 1994a). Recent studies also have shown that

aquatic plants. in many cases. are actually more sensitive to various contaminants than

animal test species (Hughes 1992).

A Iimited number of studies have addressed the potential of aquatic plants as

biomonitors. Many of these studies have involved the use of analytical methods to

directly measure contaminant concentrations in tissues of vascular aquatic pIants

(Coquery & Welboum 1995. St.-Cyr & Campbell 1994. Haffner et al. 199 1. Chandra

L'I al. 1993. Mortimer 1985). and filamentous algae (Jackson 1985). Although the use

of plants as biomonitors in these studies likely provided a better estimation of

bioavai labi l ity than would chemical analyses of sediment and water, they still

employed expensive (chemical) analytical methods. Alternatively. from a community

ecology perspective. D e ~ i s o n er dl. ( 1993) looked at the distribution of submersed

aquatic rnacrophytes as a method of assessing water quality. Parameters based upon

the plants' habitat requirements. such as the light attenuation coefficient. total

suspended solids. chlorophyll a dissolved inorganic phosphorus, and dissoIved

inorganic nitrogen concentrations. were found to be good predictors of vegetation

distributions. and vice versa. However. the study of Dennison et al. did not

examine effects of sediment properties or anthropogenic contaminants. There are even

7

fewer studies which have examined plant physiological and rnorpological responses. such

as differential growth. reproduction. and survival. as biomonitoring metrics of site

quality. Sediment toxicity has been tested with the floating duckweed. Lemna sp.. in

terms of the number of fronds. chlorophyll production. root length. and carbon-14 uptake

(Taraldsen &= Norberg-King 1990. Huebert & Shay 1993). Root and shoot length.

peroxidase or dehydrogenase activity. as well as chlorophyll production. have been

studied as measures of sediment toxicity in the rooted submersed macrophyte Hydrilla

rerricillara (Klaine er al. 1 990). Walsh el at. ( 1 982) found that changes in the

photos]tinthesis/respiration ratio of the seagrass Thalassia testudinum occurred in response

to the presence of atrazine and pentachlorophenol. Root elongation in Punicwn

milirrceum has been used in toxicity testing of phenolic compounds (Wang 1986). The

submersed. rooted aquatic macrophyte Ifallisneria americana has also been previously

investigated as a potential biomonitor of water quality (Biernacki er al. 1995a, 1995b)

and sediment quality (Biernacki el 01. 1996. Biernacki er al. 1997a 1997b). as well as

being used as a biomonitor in pesticide toxicity testing (Solomon er al. 1996).

However. there is still a need for more aquatic macrophyte biomonitors (Smith 199 1.

Swanson el ui. 199 1. Hughes 1992). The present study investigates the use of the aquatic

macrophyte kll isneria americana as a biomonitor of overall site quality.

Vallisneria americana

I~bllisneriu americana (American Wildcelery), is a dioecious submersed

freshwater macrophyte (Catling et a / . 1994). It is prevalent throughout the Great Lakes

8

and indigenous to the area. CT: americana is a vital component of the aquatic ecosystem.

providing an important food source for many diving ducks. as well as serving as a refuge

for many fish and aquatic invertebrates (Edsall el al. 1988. Catling er ul. 1 994). The

plant has long. ribbon-like leaves attached in a basal rosette to a short modified stem

called a caudes (Catling et al. 1994). The roots are fiiiform. unbranched and cylindrical

(Fig. 1 -2 ) . Z'crllisneriu americana is capable of clonal growth through the production of

underground stolons fiom which new. genetically identical rosettes. are produced. Each

individual rosette is referred to as a ramet, and collectively. a group of genetically

identical ramets connected by stolons. is referred to as a genet. A single ramet generally

has between one and 18 leaves and 20 to 80 roots (Catiing el al. 1994). although as many

as 35 leaves and more than 200 roots have been observed (Potter. personal observation).

Towards the end of the growing season. V. americana produces overwintering buds

called turions at the tip of its stolons; this turion will sprout to produce new plants the

follo\ving spring. Vallisneria americana is believed to proliferate primarily through

clonal growth. however. sexual reproduction and establishment of new genets from seed

is also possible (Lokker er a/. 1997. Kimber er al. 1995).

As a rooted. submersed macrophyte. I/. americana is capable of nutrient uptake

from the water column via diffusion through the leaves. as well as uptake fiom interstitial

kvater in the sediments via the roots (Steward 199 1 ). Water is likely the main source for

elements present as dissolved salts. such as calcium. magnesium. sodium. potassium.

sulfate. and chloride (Barko er a/. 1991 a). Uptake of dissolved inorganic carbon in V.

americana has also been reported to occur primarily through the leaves, although limited

Figure 1 -2. Drawing of Vaffisneria arnericana Mich. (Hydrochari taceae).

I0

root uptake is also possible (Loczy et al. 1983). Nitrogen. phosphorus. iron. manganese.

and micronutrients. however. have been shown to enter the plant primarily via the roots

(Barko et al. 199 1 a 199 1 b). It has been suggested then. that potential routes for uptake

of contaminants will be the same as those for nutrients (Crowder 1991 ). The

predominant means of contaminant uptake in V. americana. however. likely depends

upon the chemical properties of the particular contaminant.

Ray & White ( 1976) recommended several criteria for choosing a plant species

for the purpose o f biomonitoring heavy metal pollution. They suggested that the plant

"should be representative of the locality. they should be abundant and easy to collect and

should have high tolerance of heavy metals and also a high concentration factor".

I idlisneria americana is a species which meets these requirements for the purpose of

biomonitoring in the Great Lakes. The species is native to the Great Lakes region and

can be found abundantly throughout the basin. The mere presence of the plant in Great

Lakes Areas of Concern testifies to its high tolerance of contaminants, and numerous

researchers have found that both metals (Manny er al. 1 99 1 ). and organic contaminants

( Lovett-Doust c't al. 1997) are bioconcentrated in C.'. americana.

Leaf-to-root surface area ratio

Previous studies have suggested that the leaf-to-root surface area ratio of

I ullisnei-iu may be usehl as a measure of water quality (Biemacki et al. 1996. Biernacki

et ul. 1995b . Lovett-Doust et a!. 1991). In controlled greenhouse experiments. Biernacki

al. ( 1995b) found that when plants were exposed to increasing concentrations of

11

introduced trichloroethy lene. they produced higher leaf-to-root surface area ratios. They

hrther tested this result by conducting a field study in which ramets of Vallisneria

umericuna were sampled from 243 natural populations in the Huron-Erie corridor of the

Great Lakes (Biernacki er al. 1996). Leaf-to-root surface area ratios determined for

ramets from each site were tbund to be highly correlated (pcO.00 1 ) with the ranking of

these sites in terms of concentrations of several organochlorine contaminants. as

determined from previously published data by various authors.

The leaf-to-root surface area ratio is a measure of plant performance which had

not been used before the work of Biernacki el al(1995b). It is likely (negatively)

correlated to some degree with the more commonly used measure of root:shoot biomass.

However. the leaf-to-root surface area ratio will be sensitive not only to the patterns of

relative biomass allocation between the ieaf and root tissues. but also to differences in the

shapes of those tissues (lengths. widths. thicknesses) that may characterize plastic

responses to environmental impairment.

Outline of research objectives

This study was conducted to determine if the leaf-to-root surface area ratio of

I uifisneriu arnericana. or other measures of the plant's growth form. could be

successfully used to monitor relative contamination levels and evaluate site quality within

and among the Great Lakes Areas of Concern. A field survey was conducted to

determine the effectiveness of this biomonitoring method when applied over the broad

geographical range of the Laurentian Great Lakes. Through this study it was also hoped

12

to determine which factors of site quality were capable of significantly affecting plant

growth form in K americana. Experiments were also conducted to assess the feasibility k

of using Cj. americana in laboratory-based sediment toxicity tests. One of these pilot

studies employed a sediment dilution series. Various measures of plant structure were

examined to assess whether amelioration of contaminated sediments through the addition

of clean. inert sediment would effectively reduce the impacts of the contaminants on local

biota. The second pilot study addressed the problem of assessing relative toxicity levels

for sediments differing in chemical and physical composition so that this toxicity testing

method might be used to characterize sites where I? americana was absent (e-g..

sediments fiom deep. or highly unstable. sites).

Chapter 2:

SITE QUALITY IN STRESSED AQUATIC ECOSYSTEMS AND VALLISNERU AMERICXNA: IMPLICATIONS FOR WIDESPREAD

BIOMONITORING

Introduction

Vallisnerio umerzca~ has shown particular promise as a biomonitor of aquatic

contaminants. In controlled greenhouse experiments. trichlorocthylene (TCE), a

degreasing solvent. was shown to effect changes in the ledto-root surface area ratio of V.

americana plants, with higher concentrations of TC E resulting in higher ratios (Biemacki

el al. I995b). TCE is extremely hydrophobic and tends to accumulate in the sediment.

Hence it was hypothesized that V. amer i cu~ plants accumulated the TCE primarily

through their roots, where it likely remained, since organochlorine contaminants typically

have very limited mobility within plant tissues (Guilizzoni 1 99 1 ). The increase in leaf-

to-root surface area ratio of the plants was due to both decreased root length and root

diameter and a proportionately greater allocation of biomass to the leaves, which were

surrounded by the relatively less contaminated water column (Biernacki er al. 1996). In

further field studies. Biernacki et a/. (1996) examined the leaf-to-root surface area ratio in

I: americana plants collected fiom 243 natural populations in the Huron-Erie corridor of

the Great Lakes. The ratio was found to be significantly correlated @<0.001) with the

ranking of the collection sites in terms of concentrations of various organochlorine

contaminants reported independently in the published literature. for both sediments and

14

biota (Biemacki et a(. 1 996). These studies. however. did not investigate the response of

the leaf- to-mot surface area ratio of K u m e r i c a ~ to other types of contaminant (such as

heavy metals). or other physical and chemical elements of site quality. such as levels of

macro-nutrients. dissolved oxygen. organic matter, etc.

The general purpose of the present study was to determine whether the leaf-to-

root surface area ratio of K a m e r i c u ~ was an effective monitor simply of organic

contamination, or whether it would respond to other site variables, for example. to

differences in metallic contaminant levels, or any of the array of standard limnological

parameters that characterize a site. and couid therefore be usefhl as a general metric of

overall site quality. We wished to develop a simple model for predicting site quality

using the leaf-to-root surf'e area ratio in Y. americana, a model that could be applied in

the field with minimal cost and effort. We also wished to test the effectiveness of other

plant measures, such as the leaf-to-root biomass ratio. or total biomass, as metrics of site

qualih. Finat 1 y. we sought to test the efficacy of these metrics over the broad geographic

range of the Laurentian Great Lakes.

Methods

Test organism

Fallisneria americana (var. americana Michx. ; family H ydroc hari taceae) is a

perennial. submersed freshwater macrophyte indigenous to eastern North America

(Catling el al. 1 994)- It is characterized by a rosette of long, ribbon-like leaves and

fibrous, unbranched roots. Sexual reproduction in this dioecious species (i.e., in this

15

species there are separate male and female individuals) follows upon water pollination

(Cox 1993). Extensive clonal growth occurs via the production of underground stolons

and overwintering turions (Lovett-Doust & LaPone 199 1).

Study sites and sampling protocol

During the period July 25 to August 22, 1995. sampling was conducted at 225

nearshore microsites throughout the Laurentian Great Lakes. These microsites were

located within twelve rivers, harbours or bays, each of which has been designated by the

International Joint Commission ( 1987) as an "Area of Concern" (AOC) (Fig. 2.1 ). For

locations of micrositcs, refer to appendix G. Areas were sampled sequentially from south

to north in order to sample plants at similar stages of develop men^ At each microsite. the

sediment particle size composition. the density of V. americanu plants, and the depth of

the water column were determined- For sediment composition. the results for each

microsite were converted to a coded value between 1 (particle composition most coarse)

and 6 (most fine). Photosynthetically active radiation at a microsite was measured at both

the water column/sediment interface and the water colUIIIl1/air interface using a LI-COR

waterproof spherical quantum sensor (model LI- 1 93 SA) attached to a LI-COR

quantum/radiometer/photometer (model LI- 189). From these measurements. the

proportion of incident light intensity reaching the sediment surface was calculated.

Ramets of K americam were extracted with a shovel and all excess sediment gently

washed from the roots. Five intact, undamaged ramets were used to represent each

microsite. Plants were preserved in 1L glass jars containing a 4% formaldehyde solution

Figure 2.1. Location o f the Areas o f Concern sampled in 1995.

1 ) Detroit River 5) Hamilton Harbour 9) Severn Sound 2) Rouge River 6) Toronto Harbour 1 0) Collingwood Harbour 3) St. Clair River 7) Bay of Quinte 1 1 ) Spanish River 4) Niagara River 8) St. Lawrence River 1 2) St. Marys River

and stored at room temperature until analysis. Rcvious studies have shown that this

method of preservation does not alter the surface area of the plants (Biernacki er ul.

1 996).

CaIafation of plant performance and microsite con tami~ t ion indices

The total length and mean width of all leaves, and the length and mean diameter

of all roots were measwed for each ramet using electronic digital calipers (Mitutoyo

Di gimatic Caliper). The leaf surface area was calculated by doubling the product of the

Length and the average width (to account for both sides of the flat, essentially two-

dimensional leaf) and totalling all leaves. Root surface area was calculated as for a

cylinder (the root is cylindricai rather than conical), by multiplying the length by the

average diameter. by the value of pi. The mean leaf-to-root surface area ratio was then

calculated for each microsite by dividing the mean leaf area for ail five plants collected

from the microsite. by the mean root surface area of the five plants. When determining

the mean of a ratio. such as the leaf-to-root surface area ratio. it is more appropriate to

divide the mean of-the numerator values by the mean of the denominator values. rather

than calculating the ratios for all cases and then taking a mean of the ratios (see Miller

1986).

Fresh mass of all leaf. root, and caudex (or stem base) tissue for each plant was

determined using a digital balance (Mettler BB244. DeltaRangeO). The leaf-to-root fresh

mass ratio was calculated for each microsite as the mean leaf mass for the five plants,

divided by the mean root mass. Total k s h mass was determined for each plant by

18

adding the masses of the leaves, roots and caudex. The mean total fksh mass over five

plants was then used to represent each microsite.

In addition to the site data collected in the field, an extensive literature review was

also conducted in order to construct a comprehensive database containing independently-

collected information about limnological and contaminant parameters for each microsite.

This information was compiled fiom a large pool of previously published, peer-reviewed

papers and government reports (see appendix B). Using published governmental water

and sediment quality guidelines as a basis (OMEE 1994; Environment Ontario 1988,

1989; CCREM 1987; Environment Canada 1992; USEPA 1977, 1990, 1993; NYSDEC

1993; Persaud ef al. 199 1 ; Fitchko 1989; Sullivan et al. 1985; Hart et al. 1988; Newell

1989) we then assigned individual contaminant data to one of five classes, corresponding

to their concentrations in water or sediment (value of 1 =least contaminated; +most

contaminated). An overall microsite contamination index was calculated, separately for

each of the sediment and water phases, by dividing the sum of the contaminant scores for

a site, by the maximum possible score (i.e., the number of individual contaminant scores

determined times five [the maximum individual score]). Using the overall contamination

indices, it was thereby possible to compare relatively heterogeneous sites, for which we

might have data on different numbers and kinds of contaminants. We believe this

categorical approach may reduce the effect of instrumentation and investigator variation

beween different studies. For a table of the criteria used to assign contamination scores,

refer to Appendix C. Appendices D and E contain complete spreadsheets of all

contaminant scores used for each sampled microsite.

Statistical amlyses

Statistical analyses were carried out using SYSTAT 6.0 (SPSS. tnc. 1 996).

Parameters were either natural log- or square root-transformed as needed to normalize

their distributions. and to remove heteroscedasticity (inequality of variances among

samples; Sokal and Rohlf 1995). A one-way analysis of variance was conducted to

determine the relative contributions of differences both among and within microsites to

variation in the leaf-to-mot surface area ratio. In order to develop an equation to predict

the leaf-to-root surface area ratio fiom measures of site quality, a multiple regression

analysis was conducted. The plants' leaf-to-mot surface area ratios were regressed

against various measures of site quality. Parameters considered for use in the regression

included measures of the physical properties of water and sediment, parameters related to

geographical location of the rnicrosites, and calculated indices of sediment and water

contamination by organic contaminants and metals. Percent Ioss on ignition.

conductivity . concentration of suspended solids. water current. total phosphorus. total

kjeldahl nitrogen. and chlorophyll-a concentrations were not included in the regression

due to the fact that these data were not available for enough microsites to produce a

sufficient sample size. This also eliminated many problems due to the non-independence

of some of these variables (e.g. conductivity and suspended solids). We ended up with a

subset of ten site parameters for use in the regression: water depth. plant density. PAR

(the proportion of incident photosynthetically active radiation reaching the plants),

sediment composition (coded in terms of particle size), sediment contamination. water

contamination. water temperature, microsite exposure (the number of compass degrees.

20

out of a maximum of 360". in which there is no land within 500 metres), latitude, and

rivermile (the downstream distance, in kilometres, of each site fiom the Mest upstream

site sampled, with Sault Ste. Marie on the St. Marys River as rivermile zero, and

Comwall on the St. Lawrence River as rivennile 1350). Cook's Distance measure was

calculated for all sites to determine whether the data fiom any particular locations were

having a disproportionate influence on the regression (Tabachnick & Fidell 1 996).

The one-way ANOVA and multiple linear regression were also repeated with leaf-

to-root fresh mass ratio or total k s h mass as the dependent variables to determine

whether these measures would show similar results to those seen with the leaf-to-root

surface area ratio.

To M e r test any relationship between contaminant concentrations and the leaf-

to-root surface area ratio, a Spearman rank correlation was conducted using both the

sediment and water contamhut indices. A Spearman rank comelation was also used to

compare the leaf-to-root surface area ratios observed for plants in this study with those of

a previous study (Biernacki et al. 1996) which included plants from some of the same

microsites harvested two years earlier.

Mapping potential point source impact zones

We were also interested in pinpointing the smaller regions within areas of concem

which were potential hotspots of contamination. Maps of AOCs were produced in which

we constructed isoclines of mean leaf-to-root surface area ratios based on the measures

firom our sampling sites. These isoclines were interpolated by measuring distances

21

between adjacent sampling points on the map and then dividing the distance by the

difference in the mean leaf-to-root surface area ratios for the two sites. This calculation

provided a measure of the number of millimetres on the map representing one unit of

leaf-to-root surfkce area ratio between those two sampling sites. The location of

interpolated surface area ratios. in increments of five. were marked on the map. Once this

procedure had been repeated for each pair of adjacent sites. the isoclines were drawn.

joining locations of equal surface area ratios.

Results

I ariariorz in leaf-lo-root surface area ratio

Results of one-way ANOVA indicate that microsite had a highly significant effect

on the leaf-to-root surface area ratio (pc 0.00 1 ; n= 1095: R2=0.8 16). Approximately 77%

of the variance in leaf-to-root surface area ratio was accounted for by differences between

microsites, with 33% of variance occurring among individual plants within a microsite.

The leaf-to-root surface area ratio ranged from 0.9 to 97.3. with a mean ratio over all

sampled plants of 10.3 (n=1095: SE = 0.28). The mean surface area ratios for plants

sampled within each of the areas of concern ranged from 5.1 (n = 175; SE = 0.26) for

Severn Sound. to 19.6 (n = 50: SE = 1.85) for Hamilton Harbour (Fig. 2.2).

.Lfzririple regression

A stepwise muItiple regression was conducted (backward selection. p-value of

0.10 to enter or remove [Sokal & Rohlf 19951). A highly significant regression line was

S S SC CD SM TO SL NA DT BQ RG SP HA

Area Of Concern

Figure 2.2. Mean (k SE) leaf-to-root surface area ratios for plants at each of twelve Areas of Concern.

SS = Severn Sound, SC = St. Clair River, CD = Collingwood Harbour, SM = St. Mary River, TO = Toronto Harbour, SL = St. Lawrence River, NA = Niagara River, DT = Detroit River, BQ = Bay of Quinte, RG = Rouge River, SP = Spanish Harbour, HA = Hamilton Harbour

obtained. with an R-square value of 0.294 (n=133. p<O.OOi). In other words, more than

one quarter of the variation in leaf-to-root surface area ratio could be explained by the

parameters examined (Table 2.1 ). Water contamination, latitude, temperature, sediment

composition and exposure were then rejected from the regression model due to their high

p-values (pO. 10). The remaining parameters. each of which was significant in the

regression, with the exception of water depth (p=0.08 l), included the sediment

contamination index (p=0.00 1 ), plant density (p4.00 1 ), photosynthetically active

radiation @=0.002), and rivermile m.003) . The regression equation was:

log (leaf-to-root surface arca ratio) =

2.608 (Jsediment contamination ) + 1.049 (Jwater depth ) +

0.03 1 (Jplant density ) - 0.075 (r/PAK ) + 3.7x104 (rivermile) - 0.858

Eqn. 1

A Spearman rank correlation analysis was also conducted between the relative

rankings of leaf-to-root surface area ratio and those for sediment and water contaminant

indices. This again showed a significant comlation (0.257: pcO.0 1: n=138) between

sediment contaminant indices and the leaf-to-root surface area ratios, but there was no

significant correlation between rankings of leaf-to-root surface area ratio and water-borne

contaminants.

Table 2.1. Results of multiple linear regression, with leaf-to-root surface area ratio of Y. americana as the dependent variable, using the first set of microsites. indicated as upright triangles (A) on the AOC maps (see Appendix G). N = 1 33. multiple R2 = 0.294.

Parameter Coefficient S. E. P-value (2 tail)

Plant density

PAR'

Rivermif eb

Water depth

Constant

Sediment contamination 2.6 1 0.75 0.001 *** 0.03 0.0 1 0.001 ***

- 0.08 0.02 0.002**

3.7 x lo4 1.2 x 10-4 0.003

1.05 0.60 0.08 1

- 0.86 0.83 0.304

Parameters rejected:

Sediment composition - 0.01

Water contamination - 0.01

Latitude - 0.09

Temperature - 0.04

Exposurec 0.08

' Percent of incident photosynthetically active radiation that reaches the sediment-water interface

Distance (km) downstream in the Great Lakes - St. Lawrence system. with Sault Sre. Marie as rivemile zero and Cornwall as rivennile 1350

Yumber of compass degrees in which there is no land within 500 metres of the microsite (out of a maximum possible of 360")

Reqession using additional &fa

Seventy-three cases were originally excluded fiom the analysis; these cases were

missing any published data on water contamination. but had data for all remaining

variables. Since water contamination was not found to be a significant component, and

therefore was excluded from the final regression equation. we conducted a second

multiple regression using only the 'extra' 73 cases. and incorporating the same

parameters as in the first regression equation. Through a standard multiple regression,

the following equation was obtained:

log (leaf-to-root surface area ratio) =

1 -767 (dsediment contamination ) - 1.1 7 1 (dwater depth ) +

0.0 19 (Jplant denmy ) - 0.07 1 (m ) - 22x1 O4 (rivemile) + 2.137

Eqn. 2

Comparison of the coefficients obtained for each of the regression analyses are shown in

Table 2.2.

Since both regressions (Eqns. 1 and 2) yielded similar results, at1 of the cases were

pooled (n=206) to produce one single, overall regression equation:

Table 2.2. Comparison of regression coefficients for the two model equations. Equation 1 is based on a set of 133 microsites, indicated as upright triangles (A) on the AOC maps, and equation 2 is based on a different set of 73 microsites, indicated as upside down triangles (V) on the AOC maps (see Appendix G).

Parameter Equatioo 1 Equation 2 DWenacc between Coefficient Coefficient equatioa values

Sediment contamination 2.608 1 -767

Plant density 0.03 1 0.019

PAR' - 0.075 - 0.071

Riverrnileb 3.7 x loJ - 2.2 x lo4

Water depth 1 -049 - 1.171

' Percent of incident photosynthetically active radiation that reaches the sediment-water interface

Distance (km) downstream in the Great Lakes - St. Lawrence system. with Sault Ste. Marie as rivermite zero and Cornwall as rivermile 1350.

log (leaf-to-root surf'ace area ratio) =

1.352 (dsediment contamination ) + 0.246 (v'water depth ) +

0.028 (Jplant dens~ty ) - 0.087 (m ) + 1 .Ox 1 O4 (rivermiie) + 1 -054

Eqn. 3

Results of the pooled regression are shown in Table 2.3. With all cases combined.

similar results were obtained as for the initial model. Parameters that displayed statistical

significance in the regression were. again. sediment contamination @<0.0 1 ).

photosynthetically active radiation @<0.00 1 ). and plant density (g60.00 1 ).

In all three regression equations, the regression cwfficient for rivermile was quite

small. We wished to determine whether the small coefficients were resulting because the

range for the rivermile variable was very large compared with the other parameters.

Therefore. rather than using absolute rivermile distances. the regressions were repeated

using coded values for rivermile. Microsites within each 200 krn stretch were assigned

the same code so that values for the riverrnile parameter ranged between one and seven.

However. regressions conducted with the recoded riverrnile variable still produced the

same results.

Cook's distance was calculated for all microsites used in the regression. This

measure of influence assesses changes in regression coefficients when a case is deleted

fiom the regression. and any cases that produce influence scores greater than 1.00 are

then considered as likely outliers (Tabachnick & Fidell 1996). The largest influence

score. for a microsite in Hamilton Harbour. was 0.102. Therefore. all scores were well

Table 2.3. Results of regression with leaf-to-root surface area ratio using pooled data- This regression incorporates the data fram all micmsites. N = 206: multiple R' = 0.2 18.

Parameter Cocfficien t S. E. P-value (2 tail)

Sediment contamination 1.352 0.482 0.006*

Plant density 0.028 0.007 < 0.001***

PAR' -0.087 0.0 17 < 0.001 ***

Water depth

Constant

Percent of incident photosynthetically active radiation that reaches the sediment-water intert'ace

Distance (krn) downstream in the Great Lakes - St. Lawrence system, with Sauit Ste. Marie as rivermile zero and Cornwail as rivermile 1350.

29

below the critical level for suspecting outliers and no locations appeared to be exerting a

greater proportionate influence on the regression equation. k

Results obtained with the leuf-to-root muss ratio and with totaffi-esh mass

The same statistical procedures were repeated. but with the leaf-to-root fresh mass

ratio substituted for the leaf-to-root surface area ratio as the dependent variabIe. A one-

way ANOVA revealed that there was also a significant effect on the leaf-to-root Fresh

mass ratio due to microsite (p<0.001. N=1094. multiple R2=0.715) with 68.3% of the

~Sariance due to differences among microsites. and 3 1.7% of the variation occurring

among individual plants within a microsite. The results of a multiple linear regression

nith the leaf-to-root fresh mass ratio were also similar to the results seen with the leaf-to-

root surface area ratio (Table 2.4). A significant regression was obtained (p4.001.

N=206. multiple R2=0.246) in which the statistically significant parameters included:

photosynthetically active radiation (p<O.OO 1 ). plant density (p<O.OO 1 ). sediment

contamination index (p-0.042). and ri vermile (p=O.OO 1 ).

A one-way ANOVA was conducted to determine the effect of microsite on the

total fresh mass of I/. americano plants. Again a significant effect was found (p<0.001.

N=1092. multiple R2=0.702) with 62.9% of the variance in the total mass due to

differences among microsites. and 37.1% of the variance due to differences among

individual plants within a microsite. The results of a multiple linear regression with the

total fresh mass were also similar to the results seen with the leaf-to-root surface area

ratio (Table 2.5). One case. a microsite from Hamilton Harbour. was identified as an

Table 2.1. Results of multiple linear regression with leaf-to-root fiesh mass ratio as the dependent variable. This regression incorporates the data from all microsites. N = 206: multiple R' = 0.246.

Parameter Coefficient S.E. P-value (2 tail)

Sediment contamination 0.4 I9 0.205 0.042*

Plant densip 0.0 15 0.003 < 0.001***

P A P -0.036 0.007 <O.OOl***

Ri\-ermiIeb 1.3 x 1 O4 4.0 x lo-' 0.001 ***

Water depth 0.121 0.207 0.559

Constant 0.5 10 0.240 0.035*

" Percent of incident photosynthetically active radiation that reaches the sediment-water interface

Wistance (h) downstream in the Great Lakes - St. Lawrence system. with Sault Ste. klarie as ri\.ermile zero and CornwaIl as rivermile 1350.

Table 2.5. Results of multiple linear regression with total fresh mass of Valfisneria americana plants as the dependent variable. This regression incorporates the data fiom all microsites. except for one microsite in Hamilton Harbour which was identified as an outlier. N = 205: multiple R' = 0.337.

Parameter Coefficient S.E. f -value (2 tail)

Sediment contamination 1.335 0.5 16 0.010**

Plant density 0.042 0.008 <0.001***

PAR" -0.107 0.01 8 <0.001***

Rivennileb 4.8 x 10-4 1.0 s 10-4 <0.001***

Water Depth 0.6 1 1 0.527 0.248

Constant 0.122 0.6 10 0.84 1

" Percent of incident photosynthetically active radiation that reaches the sediment-water interface

Distance (km) downstream in the Great Lakes - St. Lawrence system. with Sauit Ste. Marie as rivermile zero and Cornwall as rivermile 1350.

outlier. and therefore was excluded from the anatysis. A significant regression was

obtained (p<O.OOl. N=205. multiple R10.337) in which the statistically significant

parameters included: photosynthetically active radiation (p<O.OO 1 ). plant density

(p<0.00 1 ). sediment contamination index (p=0.0 10). and rivermile (p<O.OO 1 ).

Conzpar ison of leaf-lo-root surface area ratios with previous studies

Many of the microsites sampled from the Detroit River. Rouge River and St. Clair

River in this study corresponded with sampling sites used by Biernacki et al. (1 996). To

test whether the surface area ratios of I? americana. when determined by different

researchers and in different years. would still show the same relative ranking of site

quality. a Spearman rank correlation was conducted. In total. 56 microsites were found to

be shared between this study and that of Biernacki el a/. (1 996). The Spearman rank

correlation statistic. 0.45. was much larger than the critical value of 0.26 (n=56: p<0.05)

and was significant at p<0.001. Both studies showed the highest ratios (and potentially

poorest site quality) in three sites: the Trenton Channel. the mouth of the Rouge River.

and the mouth of the Ecorse River in the Huron-Erie comdor.

Regressions r (sing separate contaminant indices for metal and organic compounds

A significant regression effect due to an overall sediment contamination index

was observed (Table 2.3). We then explored whether this truly was a combined effect

due to both metals and organics. We subdivided the contamination index into two

separate components: sediment metals and sediment organics. Table 2.6 shows the result

Table 2.6. Results of multiple linear regression using separate sediment contamination indices for metals and organics. This regression incorporates the data from all microsites for which there was data for both organics and metals (refer to Appendix D). N = 138: multiple R' = 0.283.

- - -

Parameter Coeffkien t S.E. P-value (2 tail)

Sediment metals

Sediment organics

Plant density

PAR"

Ri\rerrnileb

Water depth

Constant

" Percent of incident photosynthetically active radiation that reaches the sediment-water interface

"Distance (km) downstream in the Great Lakes - St. Lawrence system. with Sault Ste. Marie as rivermile zero and Cornwall as rivermile 1350.

34

of the multiple linear regression. but with the two separate contamination components.

Again the overall regression was highly significant (p<0.001: n=138: R2=0.283). and the

parameters of plant density and light intensity were significant (p=0.007 and p=O.O03.

respectiveIy). The index for sediment metal contamination ~ v a s positive and highly

significant in the regression (p<0.00 1 ). but the index for sediment organic contamination

w-as not significant.

Figure 2.3 illustrates the range of concentrations in sediments found throughout

the sampled sites for a few select metals and organic contaminants. Generally

concentrations of metals in the Areas of Concern examined here are much higher than

organic contaminants. often by an order of magnitude or more. and the range in

concentrations of metals is also much broader.

Poirlr sozrrcc. irtzpacr zones

Maps n-ith interpolated isoclines of the leaf-to-root surface area ratio were

constructed for the Bay of Quinte. St. L a ~ ~ e n c e River. Severn Sound. and Spanish

Harbour. The other sampied AOCs were not mapped because not enough microsites had

been sampled at these locations to adequately represent the area at the smaller scale of

rnicrosites.

Assuming that the leaf-to-root surface area ratio is representative of site quality.

the mapped isoclines indicate the hotspots within the AOCs which are particularly

contaminated and that may be located near point source discharges that merit

imrestigation. Detailed maps of isoclines tbr the Bay of Quinte are shown in figure

TOTAL PCBs lml

Conccntmion (PPM)

Figure 2.3. Histograms for three metal contaminants and three organic contaminants, illustrating the range and frequency distributions of concentrations present in sediments from sites throughout the Great Lakes.

36

24(a.b.c). The locations showing K americana with the highest surface area ratios. and

presumably, therefore. the poorest site qualities in the Bay of Quinte. appear on the

dounstrearn side of the mouth of the Trent River. at Baker Island. at Snake Island. and

beside Woodville. Several of these sites are located downstream or adjacent to known

pollution point sources. The site at the mouth of the Trent River is directly downstream

from both the Domtar Packaging and Domtar Wood Preserving plants. as well as the

Trenton sewage treatment plant. The Baker Island site is located adjacent to the

Canadian Forces Base Trenton. which has an airfield on-site. and whose sewage

treatment plant has been cited as a point source for nutrient loading into the bay (Hartig &

Law I 994). The Snake Island site is directly adjacent to Bakelite Thermosets Limited. a

manufacturer of phenolic resins.

Construction of leaf-to-root surface area ratio isoclines for the St. Lawrence River

sho\ved that. in general. ratios increased with distance downstream (fig. 2.5). High

surface area ratios occurred along the southern shore of Cornwall Island. downstream

from Reynolds Metals Company and General Motors. Ratios were also high on the

northwestern tip of St. Regis Island. though no potential point source adjacent to this

location could be determined. (It may simply reflect cumulative loadings that converge

on that narron-ed portion of the St. Lawrence River.) Localized high surface area ratios

also occurred on the eastern outskirts of Cornwall. immediately downstream from a

discharge pipe. which. judging from the presence of numerous partiaily digested wood

fibres. likely delivered effluent from the nearby Howard Smith Paper Mills.

In Severn Sound. all of the sampled leaf-to-root surface area ratios were generally

37

quite low (fig. 2.6). However. mean ratios were slightly higher at the extreme southern

end of Penetang Harbour. hdfivay up Penetang Harbour. in the southwestern embayment

of Midland Bay. and in Matchedash Bay near Waubaushene. All of these sites. with the

exception of the last, are roughly adjacent to local Water Pollution Control Plant outfalls.

In contrast with Severn Sound. the leaf-to-root s -dace area ratios for Spanish

Harbour were generally quite high and more variable (fig. 2.7). Extremely high ratios

were found in two microsites located along the perimeter of the Spanish Marsh.

Although one of these locations was adjacent to a marina, I have not so far been able to

identifi potential point sources that could explain the second hotspot.

Discussion

This study consisted of a widexale survey in which many variables could not be

controlled, and in which there was, no doubt. variation in unmeasured environmental

factors from site to site. This may explain why the R-square value of the regression with

the leaf-to-root surface area ratio. although statistically significant. accounted for oni y

one quarter of the variation- Nevertheless. in spite of all the background "noise" in terms

of other factors which may atrect plant growth, we did still detect highly significant

c ffects of the three environmental parameters: sediment contamination level. V

americana plant density, and photosynthetically active radiation.

The regression coeficient for PAR is negative. In other words, at lower light

intensities. the leaf-to-root sutface area ratio tends to be greater. This likely reflects an

etiolation response by the plants. i.e., at lower radiation levels leaves must grow longer to

obtain enough light for photosynthesis. Other researchers have also found that shoot

length in F americana increases at lower light intensities (Twilley & Barko 1990: Barko.

el al. 199 1 b). The parameter PAR likely incorporates effects due to certain other water

quality parameters as well. Greater turbidity and higher concentrations of suspended

solids will both result in poorer light penetration (i-e.. smaller PAR values: Walker &

Willson 198 1 ).

An etiolation response may also explain why the regression coefficient for plant

density is positive. At higher plant densities. there is likely to be greater competition for

light. again promoting production of longer leaves. Titus & Stephens ( 1983) also found

that the presence of neighbouring plants influenced the growth pattern of K americana.

45

resulting in taller individuals. They attributed this response to the effect of shading.

The high significance of sediment contamination in the regression is of particular

interest. This result suggests that there is just as strong a response of plant growth form

to contaminants in the sediment as there is to light intensity and plant density. Since

there was no relationship between level of water contamination and growth form of the

plants. it is likely that the main source of contaminant uptake for the plants is tiom the

sediment, via the roots. Numerous researchers have reported that rooted. submersed

rnacrophytes primarily derive their nutrients from the sediment ( e g , Carignan & KaltT

1 980. Pip 1990. Barko & Sman 198 1 ). Except in exueme hyper-eutrophic waters. uptake

fiom sediments has been found to account for almost all phosphorus uptake in V.

americona (Carignan & Kalff 1980). Aquatic plants have also been found to accumulate

trace metals primarily through the mots. Arsenic, lead, zinc, chromium. mercury. nickel.

cadmium and copper have all been found to accumulate to a greater extent in the roots

than in the shoots of submersed plants (Coquery & Welbourn 1995. Dushenko er al.

1 995. Gupta & C handra 1 994. Reimer & Duthie 1 993. Pip & Stepaniuk 1 992. Ray &

Wlite 1976). -Metal concentrations in the sediment have been found to be reflected in the

metal content of aquatic plants such as Potamogeton sp.. ,VajusjlexiZis. iLlvriophyilum

exalbescens. Elodea canadensis. and Ceratophyllum demersurn (Pip 1990). St.-Cyr &

Campbell ( 1 994) found that the spatial pattern of heavy metal contamination of C:

americana corresponded with the spatial distribution of heavy metal contamination in

surficid sediments. Organic contaminants have also been reported to accumulate

primarily in the roots of I? americano. suggesting that for these substances. too. most

uptake occurs via the sediments (Lovett b u s t er d. 1994, Biemacki et of. 1996).

In addition to the above, sediment contamination may affect the leaf-to-root

surface area ratio more than water contamination because measurements of contamination

in the sediment are more reliable and indicative of site quality, while measured

- concentrations of pollutants in the water column are transient and can fluctuate grealy

over short periods of time. Periodic measures of contaminant concentrations in the water

column will only describe current conditions, and may not give an accurate representation

of site quality if contaminants arc king diluted or released in pulses (Lovett-Doust er al.

1993).

The rivermile parameter produced unusual results in the regressions conducted

with the leaf-to-root surface area ratio. In the first regression (eqn. 1. which used 133

microsites). rivermile was a significant factor and had a positive regression coefficient.

However. in the second regression (eqn 2. using 73 different microsites) rivermile was

not significant (p=0.232) and the regression coefficient was negative. In the final

regression which pooled all 206 sites. rivermile again was not significant. It is likely that

the positive relationship seen with the first 133 cases was cancelled out by the negative

relationship with the other 73 cases when all cases were pooled. We must then question

why the two sets of microsites displayed different effects due to rivermile. Rivermile is

actually a rather compiex parameter which is likely correlated with several other

measures. Our purpose for including rivermile as a parameter was to account for the

possible effects of accumulated loadings. Contaminants entering the system at an

upstream site will eventually flow downstream. so that theoretically, the sites located

m e s t downstream may be receiving the greatest non-point source contaminant

loadings. However. along certain portions of the Great Lakes - St. Lawence system.

where flow is running in a north/south direction. rivemile will also be directly related to

latitude (and potential1 y temperature). Looking at the locations of the microsites involved

in the second regression (eqn. 2). seven different AOCs were represented. however. 29 of

the 73 cases (i-e. 40% of the cases) were from the Bay of Quinte. The Bay of Quinte is a

very elongated bay in which the current flows tiom the head. where several tributary

rivers empty into the bay. towards the mouth located on the north shore of Lake Ontario.

Therefore. although the bay is located towards the lower end of the Great Lakes system. it

is not likely to be receiving many contaminant loadings f?om the system, but rather fiom

the tributary rivers at the head of the bay. So, the contaminant concentrations in the bay

likeiy increase in the direction of flow. which is negatively correlated with the rivermile-

Due to the predominance of Bay of Quinte microsites in the second regression. this likeiy

accounts for the negative rivermile regression coefficient.

In this study. no attempt was made to determine or account for differences in

genotype among the sampled rarnets of V. urnericana. In a previous study by Biemacki C

er a/. ( 1 997b) clones of r/. anrericana fiom six different genetic lines were subjected to

various sediments in a greenhouse setting. It was found that there were significant

differences in the leaf-to-root surface area ratios for plants grown in different sediments.

but within any given sediment treatment there were no significant differences in the leaf-

to-root surface area ratios among genetically different plants. In other words. it appeared

that the leaf-to-root surface area ratio was affected by environmental factors. rather than

48

genetics. Therefore, it is also unlikely that the diff-es observed in leaf-to-root surface

area ratios for plants collected in this survey were due to genotypic effects.

Using the third overall equation developed in this study (eqn. 3, which included

all rnicrosites), and measures of PAR, plant density, and the leaf-to-mot surface area ratio

of V. americana, it should be possible to predict the severity of sediment contamination-

Use of this model could provide a valuable, inexpensive resource management tool for

evaluating site quality and assessing the effectiveness of remediation efforts. The site-

specificity of the leaf-to-root surface area ratio could allow for evaluation of sediment

toxicity among individual microsites within areas of concern, perhaps providing a means

for mapping point source impact zones and pinpointing point sources (see International

Joint Commission 1987). For example, when ploned on a map of the area, the leaf-to-

root surface area ratios for microsites in the Bay of Quinte, St. Lawrence River, Severn

Sound and Spanish Harbour showed several potentid localized 'hotspots' (Fig. 2.4 to

2.7).

Implementation of this environmental monitoring procedure based on leaf-to-root

surface area ratio is relatively simple and could therefore be easily applied as a routine

biomonitoring program for the purpose of ranking the severity of impact at AOCs,

tracking remediation, and identifying point source impact zones within an AOC.

Within the present protocol we are seeking to improve the efficiency of riaking

surface area measurements. Preliminary results suggest that computer image analysis can

speed up the measurement process by 4 W ! over the manual methods used here (J.

VanDerWal 1998, unpublished data). Alternatively, for rough comparisons of relative

49

contamination severity among sites, the leaf-to-root fresh mass ratio or the total mass

could be used. These biomass metrics are even more simple and quick to measure. Both

measures showed greater variation among individual plants within a microsite.

Therefore. a larger sample size (1 0 to 20 plants per microsite) would be required for mass

measurements. Nonetheless, in the regression analysis using total fiesh mass. 33.7% of

the variance was explained, which is a greater portion than the 2 1.8% observed with the

leaf-to-root surface area ratio (Table 2 -4). Studies which first suggested the

biomonitoring potential of the Id-to-root surface area ratio in V . americunu also found

that ramet mass (Biernacki et al. 1995b ) and the leaf-to-root mass ratio (Biemacki ef al.

1 996, 1 997a) varied significantly with contaminant levels. However, these authors

concluded that the leaf-to-root surface area ratio was a superior monitoring measure

because correlations were more highly significant with this measure and because it was

the only one which did not differ significantly from year to year (Biernacki sf uZ. 1997a).

So, it appears that total fiesh mass could legitimately be used as a substitute for the leaf-

to-root surface area ratio if a rapid approximation of site quality is desired. However, the

leaf-to-root surface area ratio appears to be a more sensitive tool, and should be used

preferentially when fme-scale observations are required, such as in the mapping of point

source impact zones.

We have also shown that the relative ranking of sites, by different investigators, as

well as from year to year, are relatively consistent and can be validly compared. There

was a highly significant agreement between the ranking of our leaf-to-root surface area

ratio measurements for plants collected in 1995, and those of Biemacki er a/. (1 996)

50

collected from 56 of the same sites in 1993. The fact that both of these studies were able

to pinpoint the same locations as having poor site quality further reinforces the reliability

of this method. Biernacki et al. (1996, 1997a) have shown also that the leaf-to-root

surface area ratio could be used in comparing samples collected in different growing

seasons.

The importance of sediment contamination in the regression model that was

developed here (Eqn. 3) supports the observation of Biernacki et al. (1 996) that sediment

contamination was correlated with the leaf-to-root surface area ratio of K

americana. Our data, however, suggest that the response to sediment contamination

includes a significant effect due to heavy metals. Several sites with sediment containing

low concentrations of organochlorines, but high metal concentrations, still produced

plants having high surface area ratios. Our regression analyses with separate sediment

metal and organic contaminant indices indicated a highly significant effect due to metals,

but no significant effect by the organics. We suspect that a larger effect due to organic

contaminants in the sediments would have been observed if we had sampled sites with

higher organochlorine concentrations. The range in concentrations of organochlorine

contaminants is much smaller than that of metal contaminants in the Canadian Areas of

Concern (much higher organochlorine concentrations can be found in some of the

American AOCs such as the Buffalo River, Waukegan Harbor and Black River). In fact,

"There are relatively few sites in the Great Lakes where organochlorine contamination of sediments is great enough to cause lethal effects in organisms. The concern is primarily for bioaccumulation and chronic effects. On the other hand, metal contamination is still known to cause acute effects at a number of sites." (Dave Dolan, personal communication).

I had anticipated that the sediment particle size parameter would be significant in

the regression: however. in this study sediment type was not a statistically significant

contributing factor. This may have been because other factors were simply more

important. or the categories of sediment type may have been too broadly defined.

Numerous researchers have found that the texture of sediments does influence the

concentrations of contaminants at a site. since the adsorption of inorganic elements is a

function of particle surface area and electrostatic quati ties (Jackson & Kalff 1 993).

Generally. metals and nutrients are more highly concentrated in fine-grained sediments

such as silt and clay (Pip & Stepaniuk 1 992. Jackson & Kalff 1 993); organic

contaminants tend to be associated with organic matter in sediment (DiToro et al. 199 1 ).

Therefore. we would have expected to see greater leaf-to-root surface area ratios for

plants growing in more finely-grained sediments or sediments with high organic matter

content. However. our assessment of the sediment composition was qualitative and did

not evaluate organic matter content. We may have seen a significant relationship with

sediment composition if we had characterized particle size distributions for sediments

located in the rooting zones of plants at each microsite. Also, the particle size effect may

have covaried with the sediment contamination index so the main effect of particle size

may have been masked.

Based on the leaf-to-root surface area ratios recorded here. the Canadian AOCs

which should receive highest priority for remediation are Hamilton Harbour and Spanish

Harbour (Fig. 2.2). These locations contained plants with the highest mean leaf-to-root

surface area ratios. suggesting that they are also the locations with the poorest overall site

quality. Our results also indicate remedial attention should be focussed on the Bay of

Quinte. the Detroit River and the Niagara River. Many of these areas of concern are

geographically extensive and have numerous different site impairments that may require

a variety of targeted remedial approaches. Consequently, it may be of even greater

importance for governments or organizations funding remediation projects to pinpoint the

smaller sites within an AOC that are particularly problematic. Of the microsites

examined in this survey. the locations which appear to show the worst site quality

include: directly adjacent to Fort Erie on the Niagara River. the northeast comer of

Hamilton Harbour. the northeast comer of Spanish Harbour where the Spanish River

enters. the Trenton Channel of the Detroit River, and the mouth of the Rouge River where

it empties into the Detroit River at Zug Island. All of these locations are either adjacent

to. or directly downstream fiom major industrial discharges. The Fort Erie site is directly

adjacent to GNB (Can-) Ltd-. a large manufacturer of lead acid storage batteries. and in

the same vicinity as Canadian-Oxy Chemicals Ltd., and Fleet Manufacturing. a producer

of airplane and satellite components (OMEE 1993). The Hamilton Harbour site is located

directly across fiom two large steel manufacturers, Steel Company of Canada (Stelco)

and Dominion Foundries and Steel Company (Dofasco). The Spanish Harbour site is

downstream from E.B. Eddy Forest Products Ltd. (a pulp and paper mill) and mining

activities by WCO Ltd. and Falconbridge Ltd. (Spanish Harbour RAP Team 1993). The

Trenton Channel is Iined with three sewage treatment plants and more than a half dozen

industries. including McLouth Steel Corp., Elf Atochem Inc. (a chemical company).

Chrysler Trenton (a car manufacturer), Monsanto Corp. (a chemical plant). and the

Trenton Channel Power Plant (MDNR and OMEE 199 1 ). The mouth of the Rouge River

in Michigan is the site of Great Lakes Steel and the River Rouge Power Plant (a coal-

burning facility; SEMCOG 1988). Although the model generated in this study (Eqn. 3)

does not directly prove that discharges fkom these point sources are the cause of the larger

surface area ratios observed in I/. americana plants collected fiom these sites. it seems to

us very plausible that these point sources may be responsible for the impaired site quality

at these locations. In our view, these are the microsites -Win the Canadiaflntemationd

portion of the Great Lakes that should be given top priority for remediation efforts.

A model based on empirical data describes that data set well. There is, however, a

hazard attached to an empirical model, in that it must be validated against unconnected

data sets. Otherwise there is a risk of tautology. or "self-fulfilling prophecy". Therefore.

future work should include collection of a new, independent data set to test the validity of

the pooled regression model developed here and evaluate the predictive power of the

equation. Further sampling also should be conducted at the four Canadian Areas of

Concern on Lake Superior which were not sampled during this study. In addition. it may

be useful to develop separate regression equations for each individual Area of Concern

since the relative input of particular variables to the variation in plant structure may differ

among AOCs. To conduct these regressions. however. a larger sample size for each AOC

would be required than was used in this study. Generally. the recommended sample size

for a multiple regression is a minimum of 50 + 8m. where m is the number of independent

variables included in the analysis (Tabachnick & Fidell 1 996).

The focus so far has been on sites identified by the federal governments of Canada

and the U S A . as "Areas of Concern". It would be usefbl to collect data &om "clean"

reference sites as well, in order to determine the baseline and set targets for remediation

and "delisting". There may also be additional sites that merit assessment as candidates

for designation as AOCs. and our survey approach could swiftly identify or eliminate

such sites from fhther consideration. For example. the International Joint Commission is

currently considering the designation of Lake St. Clair as a new Area of Concern (David

D o h . personal communication). It would also be advantageous to collect direct field

measurements of additional physical parameters that may influence the surface area ratio.

Our model accounted for 22% variation in leaf-to-root surface area values. By adding

other parameters to the model. it may be possible to obtain a greater R-square value, and

hence an understanding that will account for a greater fiaction of the variation observed

in the plants.

Chapter 3 :

USE OF VALLISNERLA AMERICANA IN LABORATORY -BASED SEDIMENT TOXICITY TESTING

INTRODUCTION

Previous studies have shown that the Id-to-root surface area ratio of the aquatic

macrophyte Vallisneria americana (American wildcelery, family Hydrocharitaceae) can

be used as a metric of site quality in biomonitoring programs (Biernacki ef al. 1995,

1996; chapter 11). The purpose of the following two experimental studies was to

determine whether the leaf-to-root surface area ratio of K americana would also be a

use fd metric in laboratory-based sediment toxicity testing.

Sediment toxicity assays have several advantages over in siru biomonitoring.

First, sediment samples can be collected fiom anywhere for testing in the laboratory,

whereas biomonitoring in the field is restricted to locations where the test organism is

naturally living, or locations to which the organism can be transplanted. In the context of

C/: americana, laboratory assays would allow researchers to assess the toxicity of

sediments fiom locations which are regularly dredged or experience sufficient boat traff~c

to prevent the establishment of any macrophyte beds (e-g.. Wheatley Harbour and Pon

Hope Harbour). In locations such as these, naturally-occurring plant samples cannot be

collected and it would also be difficult to transplant ramets to the location and ensure

survival for the purpose of active biomonitoring (see Lovett-Doust et 01. 1994b).

However, sediment could easily be collected from these locations and brought to the

laboratory for toxicity assessment.

55

Ease of sarnpie collection is a second advantage of assessing sediment toxicity in

the laboratory. Sediment can readily be obtained fiom any water depth using a benthic

grab. Plant samples, however, must be obtained. with much care. by shovel. since their

roots must remain intact for analysis. If plant samples are required fiom a depth of more

than a metre, SCUBA is required, thus adding to the expenses of collection.

A third advantage pertains to the greater control of plant growth conditions. By

exposing ramets of V. arnericana to various sediments under controlled laboratory

conditions, all other possible factors that could influence the leaf-to-root surface area

ratio, or other measures of plant growth form, can be kept similar across all assays.

Consequently, a more reliable comparison of toxicities among sediments may be made.

In the field, comparisons among geographic locations may be complicated by differences

in various site conditions other than sediment toxicity (e.g., light intensity, plant density,

see Chapter 2).

Vallisneria americana has been previously used in pesticide toxicity assays, using

various endpoints such as leaf growth biomass, sexual reproduction, ovenvintering,

photosynthesis effect, mortality, leaf length, and dry weight (Cohn 1985; Stevenson er a/.

1 983). The leaf-to-root surface area ratio has been success firll y used in laboratory assays

for the assessment of trichloroethylene contamination in water (Biernacki ef al. 1995)-

This metric is also currently being investigated for assessing cadmium contamination (J.

VanDerWai 1998, personal communication). Biernacki ef al. (1997b) also looked at the

use of V. americana as a monitor of sediment toxicity using sediment samples fiom 6

locations in the Huron-Erie corridor, looking solely at organochlorines. However, there

56

have not been any studies of the use of Y. americana in assessing the toxicity of sediment

collected tiom areas which may be contaminated with a mixture of contaminants

(including a variety of heavy metals and organic contaminants).

EXPERIMENT # I : Plant performance in sediment from Rouge River: response of Vaiiisneriu americana to r sediment dilution series

During the process of deciding which remedial actions to take at a site with severe

sediment contamination, sometimes managers will decide that it is most appropriate to

leave the sediments in place. Efforts at removal of the sediment may be deemed too risky

if the resulting disturbance will mobilize or resuspend contaminants which are currently

buried or sediment-bound, thereby reintroducing them into the aquatic ecosystem. In

such cases preferred modes of remediation may involve simply burying the sediment

under clean material, or adding substances to the sediment which will ameliorate the

sediment by binding and stabilizing potentially hazardous contaminants. For example, in

siru stabilization was examined as a remedial option by the Assessment and Remediation

of Contaminated Sediments (ARCS) program initiated by the U. S. Environmental

Protection Agency. This technology involved capping, or "annoring" sediments in place

with plastic covers, geotextiles, or graded stone (USEPA 1992). Such an approach could

reduce the disturbance and resuspension of such contaminants into the water column. In

situ stablilization has aiready been used at the Manistique River AOC where a temporary

cover has been placed over a sediment deposit which is highly contaminated with PCBs

(Hartig & Law 1994). The Peninsula Harbour RAP committee is also considering

57

capping contaminated sediments, or alternatively, adding selenium or clay to the

sediments to inhibit methylation of mercury deposits (Hartig & Law 1994). In Hamilton

Harbour. a demonstration project carried out by the National Water Research Institute

involved injecting an oxidant into the sediments in siru to reduce the acute toxicity of the

sediment and to enhance bioremediation of organic contaminants* A similar

demonstration project was conducted by Environment Canada in the St. Marys River

( 1992-93) where sediment injection showed potential for remediation of oil and grease

contamination by increasing microbial activity to biodegrade these organic compounds

(Hartig & Law 1994). At the Wheadey Harbour AOC, two options are being considered

- in situ remediation, and a "no action" alternative whereby sediments would be buried

through natural processes (Hartig & Law 1994).

The objective of this experiment was to determine whether efforts at ameliorating

contaminated sediments in situ through the addition of clean, inert sediment would reduce

the impact of the contaminants on the aquatic food web. Specifically, we examined the

effects of a crude, contaminated sediment, diluted by varying proportions with a clean

synthetic sediment, on various measures of growth performance in ramets of V.

arnericana. Ow hypothesis, based on previous research (Biernacki et al. 1 995 b, 1 W6),

was that the leaf-to-root surface area ratio in V. americana would be greater in plants

exposed to sediment containing greater proportions of contaminated sediment and would

decline with increasing dilution of the original sediment sample by a clean prepared

sediment.

Methods

Sediment

Sediment was collected from the lower end of the Rouge River. Michigan on July

3. 1996 at a site on the southwest side of the river just west of the N.Y.C. railroad bridge

(near Jefferson Ave.. Detroit: see figure G.7). The sediment was a mix of sand. cla,v, and

organic maner and was covered by water approximately 0.6 metres deep. The sediment

in this location is known to be highly polluted with oil, PCBs, and heavy metals such as

cadmium. mercury. nickel and lead (SEMCOG 1988). We were confident that this

sediment would be capable of supporting plant growth because stands of I? umericana

were observed growing at the site. The uppermost 1 0 cm of sediment in an area of about

I0 m' was excavated by shovel and collected and transported in a 30 litre plastic bin with

a lid. The sediment was kept in cold storage for about 18 hours at 4°C. These procedures

complied with the American Society for Testing and Materials guidelines for storage of

sediment samples (ASTM 1 994). The sediment was then thoroughly mixed to ensure

homogeneity. and diluted to varying degrees with a clean, formulated sediment to

construct five different sediment compositions: 100% Rouge sediment, a 75% mixture

(containing 3 parts Rouge sediment to 1 part clean sediment), a 50% mix (with equd

proportions of Rouge and clean sediment), a 25% mix (with 1 part Rouge to 3 parts clean

sediment). and a 0% or standard mix composed entirely of clean sediment.

The composition of the clean synthetic sediment was based on the formula

developed by Hanes ( 1 992) as a contaminant- free medium for rearing Hexugenia mayfly

larvae. This formulation was designed to simulate the particle size distribution and

texture of sediments fiom Saginaw Bay, Lake Huron. and has a final organic matter

content of approximately 8 - 10 percent. Vaffisneria americuna is known to grow well in

Saginaw Bay (e.g., Wells er a!. 1980), so this sediment was expected to adequately

support plant growth. Three ingredients: fme sandblasting silica sand (produced by K&E

Sand and Gravel, Wyoming, Ontario); clay (Lewiscrafk Sculptor's Clay); and soil (Planet

Safe Professional Growing Mix, produced by the First Organic Garden Company

Limited, Ottawa, Ontario) were combined in a dry mass ratio of 42:42: 16. The dry

sediment was mixed with RO-pure water (filtered and dechlorinated by reverse osmosis)

to obtain a consistency similar to that of the contaminated sediments collected in the

field.

Once prepared, the five different sediment mixtures were placed into ha1 f-litre

glass jars (20 replicate jars of each sediment dilution) and stored, again at 4°C for 18

hours.

Experimental plants

Ramets of Vallisneria americana used for the experiment were collected fiom

Mitchells Bay, Lake St. Clair, on July 4, 1995. This site was selected due to the known

abundance of V. americana, ease of access to the location. and because the site is

relatively unpolluted (a public swimming beach is directly downstream of the collection

site). The site was located at a water depth of approximately 0.7 metres. The plants were

extracted by shovel and immediately placed in a cooler of lake water for transport. Plants

were stored overnight at 4°C.

Experimental setup

The experiment was initiated on Friday, July 5, 1996. Five glass aquaria (3 1 x 90

x 60 cm; capacity approximately 175 litres), had previously been placed in an unheated

greenhouse at the University of Windsor. The aquaria had been half-filled with water and

equipped with air pumps to provide aeration and water movement. Four jars of each

sediment dilution were placed in each of the five aquaria (i.e.. 20 jars per aquarium. for a

total of 100 jars) and ananged randomly within those aquaria. Jars of sediment were

labelled with plastic pot labels with writing in insoluble black marker. A single m e t

was then planted in each jar by gently pushing the roots into the sediment until covered.

All ramets used were first checked to ensure that the roots and leaves appeared intact and

undamaged. An effort was also made to use ramets of similar size. The mean fresh mass

for 25 other ramets of similar size collected at the same time and location was 5.86 grams

(SE = 0.5 1). Once all ramets had been planted, the aquaria were topped up with water to

a depth of approximately 0.5 metres.

Water temperature in the aquaria was allowed to fluctuate naturally with the

ambient temperature in the greenhouse and approximated temperature conditions that

would have been experienced in Mitchells Bay in summer (2 1-25 "C).

Harvests

Partial destructive harvests of the plants were conducted 2,4,6, and 8 weeks afier

initiation of the experiment. At each harvest, one randomly-selected jar of each dilution

was removed fiom each of the five tanks. To harvest the plants, the jars were removed

61

from the aquarium, and the sediment. still containing the plant, was carefully removed

from the jars by hand. Sediment was gently washed fiorn the roots of the plant in a

separate container of water ensuring recovery of all root tissue. The plant was then

preserved in a one litre glass jar containing a 4% formaldehyde solution and stored at

room temperature until processing. Each plant removed during a harvest was replaced

with a "dummy plant" so that a constant plant density was maintained in the tank for the

duration of the experiment. This procedure ensured that any differences observed in

plants from subsequent harvests were not due to reduced competition effects at lower

experimental plant densities. The replacement plants served as placeholders only, and

were not used for any data collection.

Ten days after planting, algal epiphytes were noted on the leaves of the ramets,

particularly in the aquaria located towards the centre of the greenhouse. This was thought

to be due to an excess of light reaching the aquaria. Consequently, two days later (July

17). the panes of the greenhouse were whitewashed to reduce the light intensity. and on

July 22 the tanks were covered with clear plexiglass (to reduce water loss throug.!

evaporation) and a black mesh shading cloth was placed over the top of the aquaria to

further reduce the amount of incident light. These measures significantly reduced the

amount of epiphytic algae within three days, but did not adversely affect the growth of V .

americana, which has been described as a shade-tolerant species, capable of efficient

carbon fixation at low light intensities (Meyer et al. 1943, Titus & Adarns 1979, Harley

& Findlay 1 994).

Data collected

During the processing of harvested ramets. data were collected about several

different structural components. The number of leaves and roots were counted for each

rarnet. The leaves were then removed fiom the caudex (stem base) and the roots were cut

off with a scalpel. Using a digital balance, the fiesh mass of the leaves, roots and caudex

were separately measured. We then determined the total surface area of all leaves and all

roots for each rarnet using digital calipers (Mitutoyo Digimatic). The leaves are flat and

ribbon-like. Their surface area was calculated by multiplying the product of the length

and the average width. by 2 (to account for the two sides of the leaf). The roots are

unbranched and do not taper significantly, so their surface area can be determined as that

of a cylinder by multiplying the length by the average diameter by pi (x). The leaves and

roots were kept in water until measured to prevent them from drying and shrivelling.

Once measured, however, the leaves and roots, as well as the caudex, were placed in

paper-lined petri dishes and allowed to dry at room temperature (20°C) for a minimum of

24 hours. The dry masses of each of these structures were then measured.

Sf a f is t ical analyses

Statistical analyses were conducted using the SYSTAT 7.0 statistical package

(SPSS Inc. 1997). A two-way analysis of variance was conducted to determine whether

the fiesh mass of the plants (pooled over all harvests) varied among sediment treatments

or among aquaria and a post hoc Tukey-Kramer test was used to determine which

treatments differed h r n each other. Tukey-Kramer tests were also used to determine

63

which sediment treatments caused differences in biomass allocation to leaves and roots of

the plants. Two-sample t-tests were used to compare the leaf-to-root surface area ratios

between plants harvested after two weeks and those harvested after eight weeks. The

ranking of results from sediment treatments on the leaf-to-root surface area ratio was

compared among harvest dates using a Spearman Rank Correlation. Parameters were

either natural log- or square root-transformed as needed to normalize their distributions,

and to remove any heteroscedastistic variation (Sokal and Rohlf 1995).

Results

A two-way ANOVA revealed that the total fresh mass of the plants (averaged

over a1 t harvest dates) was significantly affected by the sediment diIution (p<0.05, n=99).

with no significant effects due to the different aquaria, and no significant effects of the

interaction between aquaria and sediment dilution (Table 3.1 ). Plants which were grown

in the 100% sediment mixture had a significantly lower total biomass than plants grown

in the 25% @ = 0.05) and 75% @ = 0.04) mixtures, according to a post hoc Tukey-

Krarner multiple comparison test. By calculating the mean fresh mass of plants pooled

over all aquaria, we were able to compare differences among treatments at each harvest

date. Figure 3.1 shows the total fresh mass of plants grown in the five different sediment

compositions for the first harvest date (i.e., after two weeks of exposure). At th is stage,

plant mass was relatively similar over all sediment treatments, with an overall mean of

5.86 g (SE = 0.56; n = 25). By the final harvest date (after eight weeks of exposure), the

mean fresh mass had increased for all treatments (mean = 7.60 g; SE = 0.62; n = 25). with

Table 3.1. Results of analysis of variance to determine the effects of sediment treatment and aquaria on the total k h mass of C/. americana plants grown in various dilutions of Rouge River sediment. Fresh mass represents a mean over four different harvest dates.

Source of Sum of Degrees of Mean-square F-ratio P-value variation Squrrcs f d o m

Sediment treatment 5.1 54 4 1.288 2.883 0.028

Aquarium 0.888 4 0.222 0.497 0.738

Sediment x 4.532 16 0.283 0.634 0.846 aquarium

Error 33.069 74 0.447

Sediment treatment (% Rouge River sediment)

Figure 3.1. Mean fresh mass (* SE) of K americana plants grown in various dilutions of Rouge River sediment for two weeks.

Sediment treatment (% Rouge River sediment)

Figure 3.2. Mean fresh mass (k SE) of ?? americana plants grown in various dilutions of Rouge River sediment for eight weeks.

67

the greatest mass occurring in the 25% and 75% mixtures, and. to a lesser degree. in the

50% mixture. though none of the sediment treatments were significantly different fiom

each other at this time (Figure 3.2).

We were particularly interested in exploring the effect that sediment composition

had on leaf-to-root surface area ratios in Vallisneria americunu. A two-sample t-test was

used to compare mean leaf-to-root surface area ratios (over ail sediment treatments) for

the first harvest date (at two weeks) and the final harvest date (after eight weeks of

exposure). The results showed a significant overall increase in leaf-to-root surface area

ratio with time as the plants grew @<0.005, df = 35.9), although within a sediment

treatment, this increase was statistically significant only for the plants in the 50% Rouge

sediment mixture @<0.05; Figure 3.3).

Figure 3 -3 shows changes in the surface area ratio over time, with each line

representing the mean for plants grown in each of the five sediment mixtures. We had

anticipated that there would be an increase in the ratio with increasing Rouge sediment

content, but this was not observed. Results of the Spearman rank correlation test showed

there was no consistent ranking between mean leaf-to-root swface area ratio and the five

sediment types for any of the harvests @>>0.05 for all comparisons).

We also compared the percentage of biomass allocated to the roots, leaves and

caudex of plants fiom the different sediment treatments (Figure 3.4). Disregarding the

effects of harvest time, the pattern of biomass allocation was similar for most treatments.

However, the plants grown in the undiluted (1Wh) Rouge sediment allocated a

significantly greater proportion of biomass to root tissue (p4.05) and a significantly

Sediment treatment (% Rouge River sediment)

Sediment treatment (% Rouge River sediment)

Figure 3.4. Patterns o f biomass allocation to leaf tissue (Ci ), caudex tissue ( m), and root tissue (m ) in Vallisneria americana grown in various dilutions o f Rouge River sediment. Biomass allocated to each type of structure is shown as (A) percent biomass, and (B) absolute biomass.

70

lower proportion of biomass to leaf tissue (p~O.05) than plants grown in the 50% Rouge

sediment. The absolute root mass in the 100% treatment plants was no greater than any

of the other treatments, however, the plants were, overall, smaller in the 100% Rouge

sediment because they developed relatively little additional leaf tissue.

Discussion

We had expected that plants would be largest in the clean sediment, and would be

progressive1 y smaller as the proportion of Rouge sediment increased. However, the two

extreme intermediate sediment treatments (25% and 75% Rouge sediment) resulted in

significantly larger plants over the course of the experiment. The leaf-to-root surface area

ratios of plants in the intermediate treatment (50%) also increased significantly over the 8

week exposure period. The association between greater plant growth, and significant

increases in the leaf-to-root surface area ratio suggests a relationship between active plant

growth and contaminant uptake. It is plausible that the more actively growing plants

were also more actively absorbing nutrients from the sediment for growth, and were, in

the process, thereby accumulating greater levels of contaminants fiom the sediment.

Mortirner (1 98S), who studied metal contaminant accumulation in various freshwater

macrophyte species suggested that younger, more actively growing plants have greater

rates of uptake. So, despite the fact that the 1 W o Rouge sediment mixture contained the

greatest quantity of contaminants, it may be that the plants in the intermediate sediment

mixtures actually accumulated a greater contaminant load simply because they were

growing more rapidly. This contaminant uptake may, in turn, have caused the greater

71

leaf-to-root surface area ratios observed in these individuals.

If this explanation is correct, then one may pose the question: Why did the plants

in the intermediate sediment mixtures experience superior growth? There are at least two

possible factors that could have favoured growth in the intermediate sediment types.

First, the intermediate sediment mixtures may have been better aerated. The initial

preparation of the 294, 50% and 75% sediment types required more mixing, since the

Rouge and synthetic sediments had to be combined to formulate these blends. The 100%

mixture only received minimal initial mixing to ensure homogeneity, and the 0% mixture

was not mixed beyond its initial formulation. Therefore these two extreme sediment

treatments may have been more anoxic, resulting in poorer growth of the plants.

Numerous researchers have previously found a positive correlation between oxygen

concentrations in sediment and nitrogen uptake in aquatic plants (Moms & Dacey 1984,

Bradley & Morris 1990). Anoxic conditions have also been found to suppress carbon

assimilation (Vartapetian & Jackson 1997) and overall plant growth (van Wijck et a/.

1992).

Another possible reason for superior growth at intermediate sediment mixtures

relates to the relative balance between beneficial nutrients and detrimental contaminants.

The 0% mixture was composed entirely of synthetic sediment and no contaminants,

however it included only 16% organic matter and was low in available mineral nutrients.

The plants subjected to this treatment experienced very little growth. The 100% Rouge

sediment contained a larger proportion of organic matter and was therefore potentially an

excellent source of nutrients for growth; however, it also contained high levels of

contaminants which. by interfering with grow*. could have counteracted the beneficial

effect of the nutrients. This may explain the lack of growth in the 10W0 treatment. The

25%. 50%. and 75% treatments were likely exposed to intermediate nutrient availability.

but with reduced contaminant exposure. Therefore. if the contaminant levels were below

the critical level for total inhibition of growth, and the nutrient levels were still high

enough to promote growth. this would allow the significant increase in plant mass seen in

these treatments. It is also possible that low levels of contaminants could aIso result in

stimulated growth (a hormesis response). Numerous studies have shown that

contaminants, though toxic at high concentrations. may promote growth at low levels

(Kapustka 1997).

In this study, we used a sediment dilution series to see if the leaf-to-root surface

area ratio would show predictable differences among plants grown in different sediments

containing the same mixture of contaminants, but with a broad range in concentrations of

those contaminants. We chose to use a linear dilution series (i.e., 0,25, 50, 75. 100%

Rouge River sediment) in an attempt to represent a fidl range of contaminant

concentrations. However, perhaps it would have been more appropriate to use a series

based on geometric ratios of contaminated to clean sediment (i.e., 1 : 1,2: 1,4: I , 8: 1, etc.,

which in terms of percent Rouge River sediment would be 50,66, 80,89%, etc.). A

geometric series such as this would focus greater attention on the higher contaminant

concentrations where there may be greater detectable changes in the leaf-to-root surface

area ratio, particularly if there is a concentration threshold below which the plant does not

respond to contaminants present in the sediment.

73

The mean leaf-to-root surface area ratio remained relatively stable over the course

of the experiment for plants in the standard treatment, however the ratio appeared to be

still increasing after eight weeks of sediment exposure for plants in some of the other

treatments. It is possible that a longer period than eight weeks of exposure is required

before the plants will achieve a final leaf-to-root surface area ratio. Biernacki er al.

(1 995b) found that only a week of exposure was required for 1,'. arnericana subjected to

various concentrations of trichloroethylene to adjust its leaf-to-root surface area ratio to a

stable asymptote. However. TCE is a highly mobile contaminant; in the present study,

numerous. diverse types of contaminants were likely present in the sediments. including

metals and organochlorines. It is possible that some of these contaminants may have

been less readily available. or accumulated more slowly than TCE would be. It is also

conceivable that the leaf-to-root surface area ratio continued to change over time in

response to changes in contaminant concentrations as the initial contaminant pool was

depleted through uptake by plants. diffhion into the water column. or degradation. To

clarifL these questions. future studies could be conducted over a longer period of

exposure. or nith a replenishing supply of contaminants.

It is important to recognize that this experiment represents a simplitication of

natural conditions. In a static tank experiment like this. contaminants are introduced in

finite initial concentrations via the sediment medium only. with no recharging of

contamination in the sediment pore water from a contaminated water column. A static

assay such as this, which is carried out with an (initially) clean water column, will

obviously underestimate the overall level of contamination in the sampled sites.

Furhermore, given the small initial volume of sediment, and in the absence of any

replenishing sources of contaminants, the pool of initial contamination may be quickly

depleted as plants absorb materials, and contaminants diffuse fiom the sediment into the

well-aerated water column. Also, preparation of the sediment treatments for this

experiment did not realistically simulate methods that would be used in the field to bury

contaminated sediments. It is unlikely in the field that the sediments would be mixed to a

homogeneous composition. However, in cases where burying of sediments occurred,

either through the active addition of clean sediments dredged fiom another location, or

through natural deposition, at least some mixing would definitely occur due to wave-

action bioturbation by benthic fauna, and other disturbing forces.

This study has reinforced our perspective that the leaf-to-root surface area ratio is

a valid test of p v e d site quality, in that the response is based on an integrated growth

response including the effects of nutrients, oxygen, contaminants, etc.; therefore there

will not necessarily be a simple relationship with contaminant content alone. However,

nutrient availability and oxygen levels must be measured and/or controlled in tests that

compare dilution series in this way.

The results of this pilot study also indicate that when Vaiiisneria americana is

used in sediment toxicity testing, care must be taken to maintain the original sediment

structure so that the amount of oxygen available matches that for sediment in the field.

Furthermore, sediment toxicity tests will almost certainly underestimate the severity of

conditions in the field, in that contaminants are being gradually depleted and distributed

both to the test plants, and to the (initially) clean water column over the course of the

75

assay. Furthermore. in all aspects the quality of sediment. growing conditions for

test plants are otherwise optimal. thus only the sediment portion of the leaf-to-root

surface area ratio effect would be expected to show up. In the field. contaminants would

likely be recharged from the water column and other factors affecting plant growth would

contribute to the outcome in terms of growth and derived measures such as the leaf-to-

root surface area ratio.

Finally, the results of this study suggest that amelioration of sediments through

dilution with a clean sediment is not an effective remediation method. Aithough plant

growth improved moderately in some of the treatments with clean sediment added to the - Rouge River sediment, there was still no significant difference between plant

performance in the 100% Rouge River sediment and the 50% Rouge or the clean

standardized sediment. Even at diluted concentrations, contaminants will still be

biologically available and may negatively impact the biota until they are completely

absent from the system. Therefore. we would suggest that proper remediation of

sediments should involve complete degradation or removal of contaminants.

EXPERIMENT #2 : Sediment toxicity t a t s using VaIIisneria alt~ricana

Our objective in this experiment was to determine whether test rarnets would

adjust their leaf-to-root surface area ratio to reflect differences in overall sediment

quality. We also wished to determine whether other plant measures, such as total plant

biomass, or proportionate biomass allocation were as usefid as indicators of sediment

quality as the leaf-to-root surface area ratio, in laboratory-based toxicity tests. The

experiment involved obtaining ramets of V. americanu from a clean field site, and

growing them in tanks in a greenhouse, planted in sediments obtained fiom various

stressed aquatic locations. These various sediments were diverse in terms of their particle

size composition, nutrient concentrations, and the nature of their contamination (table

3.2); most of the sediments contained complex mixtures of contaminants, including both

heavy metals and organochlorines.

Methods

Sediment treatments

Sediment samples were collected between June 6 and July 4, 1996 fiom eleven

sites, each within a different Area of Concern (AOC); Table 3.3 describes the exact

location of each site. Sampling locations were dl at a water depth of approximately 0.7

metres. Twelve replicate samples were collected fkom each site; for each sample, the top

10 crn of sediment was collected and placed in half-litre glass jars with plastic lids. This

section of sediment represents the typical rooting zone in natural populations of Y.

77

americana (e.g.. Titus and Stephens [I9831 found that over 89% of Chflisneriu roots were

distributed within 10 cm of the sediment surface). The jars of sediment were kept on ice

during transportation. and then stored in a refrigerator at 4°C until the experiment began.

Samples were stored for no longer than 4 weeks. These sediment toxicity testing

procedures were followed to comply with recommended methods for sediment storage

and handling (see Dillon et al. 1994. Burton 1995).

A clean reference sediment was also formulated for the experiment to be used as a

standard. The composition of the synthetic sediment was based on the recipe developed

by Hanes (1992; see Ch. 3. p. 58). This synthetic reference sediment was then placed in

half-litre glass jars similar to those used for collection and study of the other sediment

samples.

Erperirnental plants

Ramets of Ydisneria americana used for the experiment were collected fiom

Mitchells Bay, Lake St. Clair. on July 4. 1995. This source site was chosen due to the

known abundance of V. americana. ease of access to the location. and because the site is

relatively unpolluted (a public swimming beach was located directly downstream from

the collection site). The sediment was sampled in water that was approximately 0.7

metres deep. The plants were excavated using a shovel. and immediately placed in a

cooler of lake water for transport. The plants were stored overnight at 4°C.

Table 3.3. Description of collection sites for sediments used in sediment toxicity test.

ArerolConcern County Township Latitude Longi tudc Location of colkction site

Bay of Quinte

Collingwood Harbour

Detroit River

Hamilton Harbour

Niagata River

Port Hope

Rouge River

Sevcrn Sound

St. Clair River

Toronto Harbour

Whcetlcy Harbour

Prince Edward

Simcoc

Waync, MI

Hamilton- Wentworth

N iagara

Durham

Waync, MI

Simcoe

Kent

York

Essex

Ameliasburg

Nottawasaga

Grosse Ile

West Flamborough

Willoughby

Hope

River Rouge

T ~ Y

Chatham

York

Mersea

Twelve O'clock Point, near Carrying Place

west of pier, adjacent to the Water Pollution Control Plant

western shore of Grow Ik, in Trenton Channel, just south of swing bridge

northwestern corner of harbour, just south o f Valley Inn Road

just inside mouth of Black Creek where it empties into Niagara River

beach just east of harbour, beside breakwall

western shore of Zug Island in the nonhern fork of the river

in western end of Midland Bay, bcside factory

in upper Chcnal Ecarte, across from public boat ramp on Hwy 33

Sunnyside Beach, Sir Casmir Gzowski Park

mouth of Muddy Creek at north end o f harbour. north side of bridnc

Experimen f al setup

The experiment commenced on Friday, July 5, 1996. Six glass aquaria. each with

a capacity of approximately 1 75 L, had previously been set up in the greenhouse at the

University of Windsor. The aquaria had been half-filled with water, and equipped with air

pumps to provide aeration and movement of the water. Two jars of sediment from each

site, as well as two jars of the formulated reference sediment, were placed in each of the

six aquaria (three rows of eight jars) and arranged randomly within those aquaria. The

different jars of sediments were labelled with plastic pot labels with writing in insoluble

black marker. A single rarnet was then planted in each of the jars by gently pushing the

roots into the sediment until covered. All ratnets used were first checked to ensure that

the roots and leaves were intact and undamaged. An effort was also made to use ramets

of similar size. Once all ramets had been planted, the aquaria were then fiuther filled

with water to a depth of approximately 0.5 metres. A lid of clear plexiglass was placed

on the top of each aquarium to prevent evaporation of the water. The temperature of the

greenhouse was not regulated, so the water temperature in the aquaria fluctuated;

however, it approximated temperatures which would have been experienced by the plants

in their original habitat in summer (2 1-25 "C). As in the dilution-series experiment, a

black mesh cloth was placed over the top of the aquaria to reduce the amount of incident

light, thereby controlling the growth of epiphytic algae. Vallisneria americana is known

to be shade-tolerant, capable of efficient carbon fixation at low light intensities (Titus &

Adarns 1979, Meyer et al. 1943, Harley & Findlay 1 994).

Harvesf and data collection

All ramets were harvested at the end of eight weeks. Each jar was removed from

its aquarium. and the sediment, still containing the plant. was gently scooped out of the

jar. The sediment was then gently washed from the roots of the plant and all root tissue

was recovered. Each plant was preserved in a labelled glass jar containing a 4%

formaldehyde solution and stored at room temperature until processing. This method of

preservation has been shown previously to have no effkct on the leaf-to-root surface area

ratio in V. americana (Biernacki et al. 1 996).

Processing of the plants followed the protocol described for the dilution-series

experiment. By the end of the eight weeks, many of the original plants had produced

additional ramets. Therefore, for each plant the number of attached rarnets was counted,

and the lei& and root- surface areas and masses were determined for each individual

m e t , as well as being summed over all rarnets in a plant.

At the same time that the plants for the experiment were collected at Mitchells

Bay, 25 fhrther m e t s were collected and preserved immediately in formaldehyde

solution. These plants were measured to provide a baseline estimate of the mean leaf-to-

root surface area ratio of plants at the field site, prior to their exposure to contaminated

sediment. We were also interested in comparing the changes in leaf-to-root surface area

ratio of the plants grown in the greenhouse with those of plants which remained in the

field. Consequently, an additional 25 ramets were obtained from the same location in

Mitchelis Bay at the end of the eight week period and preserved in formaldehyde

solution. The masses and surface areas of the leaves and roots fiom these plants were

also measured.

Sediment qualiry darabese

Actual nutrient and contaminant concentrations in each sediment sample were not

directly measured; instead, a database of nutrient and contaminant concentrations at each

sediment collection site was used to characterize each sample. These data had been

assembled f-rom previously published peer-reviewed articles and government reports.

From these data, indices of organic matter content and both organic and metal

contaminant severity for each sediment type were determined following the method

outlined in Chapter 11 (for raw scores, see Appendix F). In a few cases, information on

certain contaminant concentrations was not available for the exact site of sediment origin,

and instead data for locations directly adjacent to the actual sampling sites were used.

Daia analysis

Statistical analyses were conducted using SYSTAT 7.0 (SPSS Inc., 1997). First.

a linear regression was conducted to determine the relationship between measures of leaf-

to-root surface area ratio taken for the original (parent) rarnet only, and measures summed

over all ramets produced fiom (and including) an original ramet. A two-way model I1

ANOVA was conducted to determine whether the origin of the sediment had any effect

on the leaf-to-root surface area ratio and whether there were differences among plants

grown in the different aquaria A Tukey-Kramer multiple comparison post hoc test was

then used to examine the nature of the differences among sediment treatments. We were

also interested in the possible use of other measures of plant performance. such as the

leaf-to-root fiesh mass ratio, or total plant fiesh mass, as metrics of sediment quality.

Consequently, we conducted ANOVAs to determine whether there were significant

effects due to sediment origin on these other plant measures as well. Two-sample t-tests

were conducted to determine whether changes in mean plant measures over the course of

the experiment were statistically significant. Rankings of the sediment treatments by

plant performance measures were compared with rankings by sediment characteristics (as

determined fiom the literature) using Spearman Rank Correlation Analysis. T-tests were

used to compare leaf-to-root surface area ratios for plants grown in six of the sediment

treatments with leaf-to-root surface area ratios measured for plants growing naturally in

the same location as the sediment origin- All variables were natural log or square-root

transformed as necessary to nonnaiize the data and reduce heteroscedastistic variation

(Sokal and Rohlf 198 1, Tabachnick and Fidell 1996).

Results

Over the duration of the experiment, only one plant died (tank number 6, planted

in sediment fiom Wheatley Harbour).

Linear regressions were conducted to determine the relationship between final

plant measures taken for the original (parent) ramets alone, and for measures taken over

whole plants (i.e., for the original rarnet plus all rarnets that were produced during the

course of the experimental period). There was a very close relationship between the two

surface area measures (Figure 3.5; multiple R2 = 0.933, n= 143, p~O.00 1 ), between the

Total leaf-to-root surface area ratio

Figure 3.5. Linear regression of the leaf-to-root surface area ratio calculated for only the original (parent) rarnet and the leaf-to-root surface area ratio calculated over all sister rarnets produced over the experimental period. Both surface area ratios have been square-root transformed to normalize their distributions.

two measures of leaf-to-root fresh mass (multiple R2 = 0.906. n= 143. p<0.00 1 ). and

between the two measures of f m h biomass (multiple RL = 0.920. n= 142, p<O.00 1 ). Due

to the highly significant relationship between each set of measures, it was decided that

either measure could be used interchangeably. Therefore, fiom this point. the leaf-to-root

surface area ratio, leaf-to-root mass ratio and total k s h biomass will refer to measures

taken over the total plant (i.e., calcdated over all attached ramets).

Table 3.4 gives the results of two-way ANOVA, showing effects due to sediment

origin and the different aquaria, as well as their interaction, on the various plant

measures. There was no significant effet on the leaf-to-root surface area ratio of the

plants due to the different aquaria, nor was there a significant interaction between aquaria

and the different sediments. Origin of the sediment, however, had a highly significant

effect on the leaf-to-root surface area ratio w0.001; n = 143, d.f. = 11, R2 = 0.671). A

Tukey-Kramer multiple comparison post hoc test was conducted to determine which

sediment treatments were significantly different fiom others (Figure 3.6). The highest

surface area ratios were found in plants grown in sediments fiom Wheatiey Harbour and

Collingwood Harbour. The lowest surface area ratios occurred in the Rouge River and

Port Hope sediment treatments.

With the leaf-to-root k s h mass ratio as the dependent variable, both the sediment

origin and the tank had significant effects @<0.005 and p<0.01, respectively), but there

was no significant interaction effect. The ANOVA had a multiple R2 value of 0.739

(n= 143). Again, a post hoc Tukey-Kramer test was used to determine the nature of the

differences in mass ratio among the sediment treatments (Figure 3.7). The highest mass

Table 3.4. P-values tiom analyses of variance to determine the effects of sediment origin and aquaria on the leaf-to-root surface area ratio. leaf-to-root fresh mass ratio, and total fresh mass of Vaffisneriu omericana.

Source of Leaf-to-root Leaf-to-root fresh Total fresh mass variation surface area ratio mass ratio

Sediment origin <0.0005 *** <O.O005 *** 0.001 ***

Aquarium 0.2 18 NS 0.006 ** 0.085 N S

Sediment x 0.502 N S 0.236 N S 0.264 N S Aquarium

*** p<O.OOl ** p<O.OI * p < 0.05 NS Not significant

Origin of sediment

Figure 3.6. Effects of sediments with varying types and levels o f contamination on the mean (* SE) leaf-to-root surface area ratio in Vallisneria antericana. The standardized sediment did not contain any contaminants and was a formulated mixture of sand, clay, and soil. Bars with the same letter are not significantly different.

Origin of sediment

Figure 3.7. Effects of sediments with varying types and levels of contaminants on the mean ( S E ) leaf-to-root fresh mass ratio in Vallisneria arnericana. The standardized sediment did not contain any contaminants and was a formulated mixture o f sand, clay, and soil. Bars with the same letter are not significantly different.

Origin of sediment

Figure 3.8. Effects of sediments with varying types and levels of contaminants on the mean (* SE) total fresh mass o f Vallisneria arnericana. The standardized sediment did not contain any contaminants and was a formulated mixture o f sand, clay, and soil. Bars with the same letter are not significantly different.

90

ratio also occurred in plants g r o w in sediments from Wheatley Harbour. followed by the

standard and Collingwood Harbour treatments. The lowest mass ratios, as with the

surface area ratios, occurred in the Port Hope and Rouge River sediment treatments. The

differences among the tanks were also examined. The mean leaf-to-root tiesh mass ratio

was significantly lower for plants g r o w in tank 5 than for plants grown in tank 2. Means

tbr plants in all other tanks were not significantly different fiom each other.

With the total fiesh mass of the plant as the dependent variable, there was a

significant effect due to sediment origin @<0.001). but not due to tank @=0.085), nor the

interaction term (p=0.264). The ANOVA had a multiple R' value of 0.61 3 (n=l43).

Differences among treatments were explored using a Tukey-Kramer post hoc test (Figure

3.8). Ranking of the sediment treatments in terms of total biomass was similar to the

rankings provided by the surface area and mass ratios. but with less distinction between

treatments. The plants grown in the standard, Toronto. Ullheatley. and Bay of Quinte

sediment treatments had accumulated the greatest biomass. while plants in the Rouge

sediment treatment attained the lowest biomass.

To determine whether the observed effect of sediment origin on total plant mass

was due to a difference in the total number of ramets produced by plants in each sediment

type. another two-way ANOVA was conducted (Table 3.5). No effect of sediment origin

was found on the number of ramets produced by a plant. However, there was a

significant effect on the number of rarnets produced due to the particular tank in which a

plant was grown (p<0.05). A post hoc Tukey-Kramer test revealed that plants grown in

tank number six produced a significantly greater number of ramets than plants which

Table 3.5. Results of analysis of variance to determine the effects of sediment origin and tank on the total number of ramets produced by C/: americana

Source of Degrees of Mean F-mtio P-value variation f d o m squares

Sediment origin 1 I 0.699 1.242 0.276

Tank 5 1 646 2.926 0,018

Sediment x Tank 55 0.719 1.277 0.164

Error 72 0.562 - --

92

were grown in tank number two.

We examined the measurements of leaf-to-root surface area ratio, leaf-to-root

fresh mass ratio, and total plant fiesh mass. and compared the relative ranking of

sediment treatments by these characteristics using Spearman's Rank Order Correlation.

The ranking of treatments was significantly correlated for the leaf-to-root surface area

ratio and the leaf-to-root fiesh mass ratio @<O.OI, n= l2), for the leaf-to-root fresh mass

ratio and the total tiesh mass @<0.01. n=12), and for the leaf-to-root surface area ratio

and total fiesh mass @<0.05. n= 12).

Spearman's Rank Order Correlation was also used to compare rankings of

treatments by the three plant performance measures with rankings of the treatments by

the sediment characteristics shown in Table 3.2. There were no significant correlations

with any of the sediment characteristics (p0.05 for all comparisons).

Twenty-five control plants collected from Mitchells Bay at the beginning of the

eight week experimental period, as well as another twenty-five plants collected fiom

Mitchells Bay at the end of the experimental period were examined to observe the natural

changes in various plant measures in the field. There was a slight decrease in the total

fresh mass of the plants at Mitchells Bay over the duration of the experimental period.

The plants had a mean biomass of 5.86 g (SE=0.5 1) at the initiation of the experiment,

and by the end of the eight weeks, plants at Mitchells Bay had a mean biomass of 5.33 g

(SE4.70). However, using a two-sample t-test, these masses were not found to be

significantly different (j~0.547, df-43.9). However, despite the fact that the biomass of

the plants in the field did not change over the experimental period, their leaf-to-root

surface area ratio did change significantly (p<0.001. df=39.8). The mean leaf-to-root

surface area ratio at the beginning of the eight week period was 19.72 (SE=1.25 I ). At the

end of the experimental period. the second sample of 25 plants collected from Mitchells

Bay had a mean leaf-to-root surface area ratio of 9.1 55 (SE=O. 767). In other words. C:

americana plants left to grow naturally in Mitchells Bay fiom July to September actually

experienced more than a 50% decrease in their surface area ratio. This decrease in Ieaf-

to-root surface area ratio was due to a decrease in leaf area as well as an increase in root

area.

The measurements taken for plants collected from Mitchells Bay at the beginning

of the experiment were used to determine how the various structures of the experimental

plants changed over the eight week period. Table 3 -6 summarizes the mean changes in

leaf mass. root mass, and total mass for each of the sediment treatments. Plants grown in

Rouge River sediment were the only ones that experienced a significant decrease in total

mass (p<0.00 1 ) over the experiment: this was primarily due to a highly significant

decrease in leaf mass @<0.00 1 ). Plants grown in the standard and Toronto sediment

treatments experienced significant increases in total mass ( p 4 . 0 1 and p<0.05.

respectively) due to increases in both Ieaf mass @<0.01 and p<0.05. respectively) and

root mass @<0.05 and p<0.00 1, respectively). A11 other sediment treatments did not

result in significant changes in total mass. Several of the treatments did show significant

increases in root mass, but since roots account for such a small proportion of the total

plant biomass, these increases did not significantly affect the overalI plant mass.

Table 3.6. Changes in fiesh total plant mass. fresh leaf mass and fresh root mass of Vallisneria americana plants grown for eight weeks in standard sediment, or one of eleven sediments originating from different Areas of Concern ("+" represents an increase in mass. " - " represents a decrease in mass).

Sediment Origin Leaf Mass Root Mass Total Mass

Rouge River - *** NS - ***

Collingwood Harbour

Hamilton Harbour

St. Clair River

Wheatley Harbour NS NS NS

NS f N iagara River NS

Bay of Quinte

Severn Sound

Detroit River

Port Hope Harbour NS + *+* NS

Toronto Harbour + * t *** + *

Standard t ** c + **

Field Samples (Mitchells Bay)

NS no significant difference * p<o.os ** p<o.o 1 *** p<o.oo 1

Table 3.7. Changes in leaf surface area root surface area. and leaf-to-root surface area ratio o f Vallisneria americana plants grown for eight weeks in standard sediment. or one o f eleven sediments originating from different .. Great Lakes Areas of Concern ("4. represents an increase in mass. " - represents a decrease in mass).

- - - - -

Sediment Origin Leaf Area Root Area Leaf-to-Root Surface Area Ratio

Collingwood Harbour

Niagara River

Wheatley Harbour

Severn Sound

Hamilton Harbour

St. Clair River

Bay of Quinte

Detroit River

Rouge River

Port Hope Harbour

Toronto Harbour

Standard

Field Samples (Mitchells Bay)

S no significant difference * p<O.OS ** pc0.0 1 *** p<O.OOl

96

Table 3 -7 summarizes the changes observed in leaf area root area. and the leaf-to-root

surface area ratio for each of the sediment treatments. Plants from the Collingwood

Harbour. Niagara River. and Wheatley Harbour sediment treatments did not show any

signiticant changes in surface area over the course of the experiment. In all other

treatments. the plants experienced significant decreases in the leaf-to-root surface area

ratio. For the Detroit River and Bay of Quinte sediment treatments. the effects were due

to significant increases in the surface area of the roots (for both. p<0.05). In the case of

the Rouge River treatment, the decreased leaf-to-root surface area ratio could be

accounted for by the significant decrease in leaf area ( p 4 . 0 0 1 ). Plants from the Sevem

Sound. Hamilton Harbour. and St. Clair River sediments did not show significant

changes in either their leaf area or root area, therefore the significant decrease in their

leaf-to-root surface area ratio must have been due to slight decreases in leaf area

combined with slight increases in root area. Plants from the Port Hope sediment showed

significant decreases in leaf area @<0.05) as well as significant increases in root area

(p<O.OO 1 ). Significant increases were observed in both the leaf area and root area for the

standard and Toronto treatments. Presumably. then. in these latter two treatments, the

root area increases were large enough to balance the effect of the leaf area increase.

producing an overall decrease in the leaf-to-root surface area ratio.

Six of the locations from which sediment was obtained for use in this study.

corresponded with microsites studied in the 1995 survey described in chapter 2.

Therefore. we compared the leaf-to-root surface area ratios for K anrericana plants

growing naturally at these in sites in 1995 with the leaf-to-root surface area ratios for

Table 3.8. Comparison of leaf-to-root surface area ratios for Y. americana collected from six sites in Great Lakes Areas of Concern in 1995, and of I? americana collected fiom Mitchells Bay (Lake St. Clau) but subsequently grown in sediments collected fiom the same six sites in 1996. For all comparisons. N = 17,

Location of Mean (aE) Icrf-to-root Mean (ME) leaf-to-root P-value collection site surface area ratio for surface area ratio for

plants in the field plants in sediment toxicity test

-

Bay of Quinte 7.314 (1.291) 9.168 (0.833) 0.246

Detroit River 11.173 (2.932) 9.720 (1.893) 0.683

Niagara River 13.615 (3.375) 16.287 (2.1 78) 0.5 16

Rouge River 6.632 (2.226) 6.346 (1 -437) 0.91 5

Severn Sound 5.041 (3.051) 13.756 (1.970) 0.030

St. CIair River 4.586 (2.07 1 ) 1 1.603 (1.337) 0.012

98

Mitchells Bay plants transplanted into sediments from the same six sites in 1996. but then

grown in the greenhouse. T-tests revealed no significant differences in the leaf-to-root

surface area ratios between the field and the greenhow for four of the sediments (table

3.8). However, transplanted ramets grown in St. Clair River and Severn Sound sediments

in the greenhouse showed significantly higher leaf-to-root surface area ratios than those

of plants growing in the field at the S t Clair River and Sevem Sound sites @=0.012 and

p=0.030, respectively).

Discussion

The highly significant effect of sediment treatments on the leaf-to-root surface

area ratio suggests that the quality of the sediments did indeed affect the growth form of

the plants, with approximately two-thirds (RW.67 1) of the variation among plants

occurring due to sediment differences. This suggests that the leaf-to-root surface area

ratio is capable of responding to differences in at least some aspect of sediment quality.

Likewise, the total fresh mass of the plants was also sensitive to sediment differences.

The leaf-to-root fiesh mass ratio, although sensitive to sediment differences. also varied

significantly among the aquaria for any particular sediment treatment. Perhaps this plant

measure is also sensitive to site parameters besides sediment quality, such as differences

in the water column quality, or small differences in incident solar radiation.

Plants grown in tank number two produced the highest leaf-to-root fiesh mass

ratio, but the lowest number of ramets of all the aquaria. Perhaps, in response to slight

differences in e x t e d faftors among the aquaria (e.g., incident light intensity), a different

99

pattern of resource allocation occurred within the plants of tank two. The high mass ratio

and low ramet count may reflect a tradeoff occurring within the plant's resource

allocation towards vertical growth (i.e. original rarnet leaf mass) and horizontal growth

(i.e. clonal reproduction).

The mean leaf-to-root surface area ratio for plants collected in the field at the

beginning of the experiment was approximately 1 9 (cm2 leaf7cm2 root). If this is assumed

to be the average leaf-to-root surface area ratio for the plants fiom the same collection

site, then the surface area ratio must have decreased over the eight weeks for all plants,

except those placed in the Wheatley, Collingwood, and Niagara sediments. The final

leaf-to-root surface area ratio for plants grown in the field was less than half their initial

surface area ratios. This appeared to be due to a combination of an increase in root

surface area over the period and a decrease in leaf surface area due to leaf mortality at the

end of the growing season. Such a decrease in surface area ratio was unexpected as

previous studies indicated that the leaf-to-root surface area ratio tends to increase over the

growing season, peaking in September (Biernacki et a/. 1 996). Nonetheless, this

phenomenon of decreasing leaf-to-root surface area ratio with time was also observed in

the experimental plants in the greenhouse. although for most treatments (all except the

Port Hope and Rouge sediments) the decrease was less than that seen in the field. It is

difficult to say why all plants experienced a decrease in surface area ratio. It is possible

that the experiment was conducted late enough in the season that when the plants were

collected (July 4), they were already close to their peak size, and perhaps by the time the

plants were harvested (August 29) they had already started the process of ldsenescence.

100

This seems somewhat unlikely, as V. americana in southwestern Ontario reaches peak

biomass in mid-August and persists until late October before complete senescence

(Catting el al. 1994). However, it is worth noting that Titus and Stephens (1983) found

that J/. Americana growing in Chenango Lake, New York reached peak biomass in early

August with a slight decline by the end of the month foliowed by a rapid decline in

September with the onset of leaf senescence. it is also possible that the contaminants in

the sediments induced a senescence response. Exposure to solutions of h e a ~ y metals has

been found to promote senescence in leaves of Vailisneria spiraiis (Jana & Choudhuri

I 982, 1 984). It is possible then that a loss of leaf surface area due to senescence could

account for the decline in surface area ratio. However, this explanation cannot account

for the even greater senescence observed for plants which remained at Mitchells Bay, a

clean location. A reduction in biomass allocation to the leaves may have also occurred

around mid-August when several of the plants began flowering and producing nuions; at

this point biomass is typically diverted towards reproduction and stored reserves in

overwintering turions. In fbture studies, changes in leaf area due to senescence could be

documented through the examination of leaf demography (i.e., leaf "birth" and "death"

rates; see Biernacki el al. 199Sa).

Replicates of each sediment type were placed in each of the aquaria in order to

avoid pseudoreplication due to spatial segregation of treatments and non-independent

replicates (see Hurlbert 1984). Consequently, in each tank the different sediment

treatments shared common water columns, and it is possible that some exchange of

nutrients or contaminants may have occurred between sediments by diffusion via the

101

water column. It is likely that any crosscontamination was minimal. however. since

significant differences were still detected in the response of the plants to the various

sediment treatments. However, due to the use of a clean water column, the levels of

contamination experienced by plants in the present study were probably much diluted

relative to conditions in the actual field sites. In fbture studies, any direct diffusion of

contaminants from the sediments to the water column could be controlled by the use of a

barrier at the mouth of the jar. For example, Hinman and Klaine (1992) used an agar-

Teflon diffusion barrier to separate the sediment and water compartments in their study of

organic pesticide translocation in an aquatic macrophyte.

The ranking of the sediments in terms of the performance measures for plants

grown in them, did not directly correlate with any of the sediment characteristics

examined. For example, based on data obtained fiom the literature, we would have

expected the Wheatley Harbour sediment to be moderately contaminated, and yet piants

consistently responded well to h i s treatment. Perhaps the information obtained fiom the

literature was outdated, or conditions in the Wheatley Harbour sediments may be very

patchy. All three performance measures suggested that the poorest treatments were the

Port Hope and Rouge River sediments. The literature data was also in agreement that the

Rouge River sediment should be highly contaminated. However, the data did not rank

Port Hope sediment as being highly contaminated. We would suggest that this

discrepancy may be due to inaccuracies in the literature data, rather than a misleading

response of the plants because, at the time when the sediment was collected for the

experiment, large numbers of dead fish were observed in the area, suggesting that there is

indeed poor site quality at Port Hope.

Generally, sediments known to be more contaminated resulted in plants with

lower total fiesh mass. Other studies have also shown decreased plant biomass under

higher contaminant concentrations. For example. in a tank experiment conducted by

Biernacki et a!. (1995b), Y. americana plants were exposed to various concentrations of a

single contaminant, eichloroethylene (TCE). In that study the TCE was introduced

through the water column, rather than 6om the sediments; nonetheless. plants in the

higher TCE treatments resulted in lower mean biomass. Another study by Biemacki et

ol. ( 1 997) involved growing Y. americana in aquaria in sediments from six different sites

in the Detroit River. Ramets less than 4g showed significantly decreased biomass in the

more contaminated sediments @=0 .OO63). When larger ramets were included in the

analysis. there were no significant differences in plant biomass among the sediment

treatments. However. in the experiment plants were exposed to the sediments for only

one week; it is possible then that the larger plants may have also shown changes in their

biomass had they been given more exposure time. Declines in biomass have also been

observed for leaves of Vallisneria s p i d i s L. when exposed to heavy metals, either singly

or in mixtures (Jana & Choudhuri 1982, 1984). The metal exposure also resulted in

inhibition of protein and nucleic acid synthesis, decreased chlorophyll levels. and reduced

membrane integrity. I f these physiological effects occurred in the plants fkom our study,

they all could have contributed towards the reduction in biomass.

The leaf-to-root surface area and mass ratios also were lowest in the most

contaminated sediment. This was unexpected (see Chapter 11, and Biernacki er of. 1995b,

103

1996. 1997). but could be attributed to leaf mortality at the end of the period of vegetative

growth. It appeared that plants growing on cleaner sediment (in terms of known

contaminant concentration) were the only ones that increased in terms of leaf and total

mass. as well as leaf and root area.

The three plant measures examined in this study for use as biomonitorinp metrics

all produced similar rankings for the sediments tested. However. since the leaf-to-root

mass ratio also varied among aquaria it is a less reliable indicator of sediment quality for

a laboratory-based assay.

The development of this method for assessing sediment toxicity using E :

americana is still in the exploratory stages. It appears that total plant biomass provides a

useful ranking of sediment quality. with an actual loss of plant mass occurring in the

Rouge River sediment. no change in most of the other sediments. and net plant growth in

Toronto Harbour sediments and the standard. If such sediment toxicity tests are to be

used for routine monitoring purposes. f k h e r studies should be conducted to develop an

appropriate. standardized method for testing sediment samples. It may be advantageous

to devetop a standard laboratory culture of t: americana ramets, raised on a standardized

clean sediment in the greenhouse. for use as test organisms. These ramets could then be

used to establish baseline plant structure measures under controlled conditions. and when

exposed to known levels of contaminant severity so that certain values of the leaf-to-root

surface area ratio, or total biomass. could be used as criteria for classifying sediments on

a scale of contaminant severity.

Comparison of leaf-to-root surface area ratios observed in this study with those

104

observed for plants growing in the same sediments in the field, suggest that although

ratios are comparable in both situations for some sediments, others sediments produce

significantly different measures of plant growth. Plants exposed to both the Severn

Sound and St. Clair River sediments showed significantly higher leaf-to-root surface area

ratios when grown in the greenhouse than in the field. Since plants grown in the

greenhouse-based sediment toxicity tests were all originally fiom MitchelIs Bay. they

likely performed differently fiom plants naturally-occurring in the sediments due to

differences in the tolerances or requirements of the plants for contaminants and nutrients.

Chapter 4:

GENERAL DISCUSSION

Comparison of results between field and greenhouse studies

The studies described in this thesis all examined the relationship between

contaminant concentrations and the growth form of Vallisneria americana. However. the

relationship between the leaf-to-root surface area ratio of plants and the degree of

contamination of the sediments in which they are grown, appears to differ between plants

examined in their natural habitat and those grown under experimental conditions in a

greenhouse. In the 1995 survey of natural populations of Y, americana in Areas of

Concern throughout the Great Lakes, linear multiple regression revealed a significant

positive relationship between the leaf-to-root surface area ratio and an index of sediment

contamination. In other words, plants grown in sediments containing greater relative

levels of contamination produced greater leaf-to-root surface area ratios. However, the

opposite trend was obsewed in the greenhouse experiment of 1996. The experiment

involved transplanting ramets of K americana fkom Mitchells Bay into sediments fiom

various Areas of Concern, and then growing them for eight weeks in aquaria (with a clean

water column). In this case, it was observed that plants grown in sediments containing

greater relative levels of contamination actually produced leaf-to-root surface area

ratios. This seemingly paradoxical result may be due to the effects of transplantation.

The experimental plants grown in the most highly contaminated sediments experienced

significant decreases in biomass which we attributed to leaf death. Plants growing in

1 06

these same sediments in the field. however. do not appear to suffer fiom low biomass. I t

may be that plants which have k e n growing in highly contaminated sediment for several

years have become accustomed to the conditions. allowing them to achieve a large

biomass. as well as a high leaf-to-root surface area ratio.

The improved performance of the field plants exposed to contaminated conditions

may be due to acclimation, whereby individual plants have adjusted to the conditions at a

physiological level: or. it may be that evotutionary adaptation has occurred within the

local population through selection for tolerant individuals. Through tissue culture

studies. Lin and Antonovics ( 1978) showed that tolerance of Agrostis stoloni/era to zinc

and copper was an inherited genotypic trait. Biernacki er a/. ( 1997a) have also suggested

that there may be selection for contaminant resistance in K americana. Long-term

reciprocal transplant studies involving K americana have shown that there is also

certain1 y some phenotypic plasticity in plant structures (Biernacki et al. 1 997a). Plants

originating from a contaminated site. but transplanted into a cleaner location had a mean

leaf length in their first year which was similar to plants growing naturaily at the

contaminated site; however. over the following three years their mean leaf length changed

to resemble plants growing naturally at the new dean location- However. in contrast with

this evidence for physiological acclimation. there also appeared to be some genetic basis

for contamination tolerance; when plants fiom the clean location were transplanted to the

contaminated site. their mean leaf length did not change to resemble plants growing

naturally at the contaminated site. and they consistently showed poorer growth

perhrrnance over four years of exposure. It is likely then that there is genetic variation in

the tolerance of C'. americana plants to contaminants such that local populations of

tolerant individuals may arise at contaminated sites through evolutionary adaptation.

There is also evidence to suggest that tolerant plants will show improved

performance in the presence of contaminants. Previous studies have shown that C=.

americana seeds collected fiom sites which do not contain PCBs are inhibited by the

presence of PCBs during their germination; however. seeds collected fiom sites which are

already contaminated with PCBs will actually have higher germination rates if PCBs are

present than if they are placed in clean media (Ferasol el al. 1995). One suggested

explanation for this phenomenon was the selection for PCB-tolerant individuals at the

contaminated site. Other studies have also shown that plants tolerant of certain heavy

metals often show improved growth on soil enriched with those metals than on

uncontaminated soil ( McNeill y 1 968. Jowett 1 964. Allen & Sheppard 1 97 1. Jenkins &

Winfield 1964. Lin & Antonovics 1978). In light of these observations. Antonovics er al.

( 197 1 I proposed the *-need hypothesis". i-e.. that the evolution of plants tolerant to metals

also results in the requirement of those plants for higher levels of the metal to which they

have adapted. Perhaps we were seeing a similar trend with the growth of I/: arnericana in

this study. For example. plants collected from natural populations in the Rouge River

had likely dewloped a tolerance of the contaminants present at their particular location

through years of exposure. Therefore. they were able to produce high biomass.

accompanied by high leaf-to-root surface area ratios. However. plants collected fiom the

cleaner Mitchells Bay site. which had not had the opportunity to develop a tolerance to

any contaminants absent from Mitchells Bay, were detrimentally affected when placed

108

into Rouge River sediment. As a result. the Mitchells Bay plants. though exposed to the

same sediment. experienced growth inhibition. resulting in much lower biomass and

smaller leaf-to-root surface area ratios.

Due to the contributing effects of tolerance. adaptation and acclimation. it is

difficult to compare measures of plant performance between field and laboratory studies.

When using this biornonitoring technique. at1 sites which are to be compared must be

assessed using the same method. either through surveying natural populations OR

through laboratory-based sediment toxicity tests.

Sediment toxiciry resting

In Chapter 3. two greenhouse studies examined the use of r/: americana in

sediment toxicity tests. Results of toxicity tests such as these. and their applicability to

processes occurring under natural conditions. must be interpreted with some discretion.

Such tests are conducted under artificial conditions. where on1 y one parameter (the

sediment) is captured fiom the natural site. All other factors. such as temperature. light

availability. water qua1 it).. herbivory. and resource competition are generally maintained

at optimal levels. Therefore. the responses observed in plants fiom toxicity tests can be

expected to be mild compared with what would occur in siru, Also. due to the

reductionist nature of toxicity tests. which will only examine the response of piants to one

component of their environment. possible additive. synergistic. or antagonistic

interactions of multiple factors which may occur in the field. cannot be evaluated through

this type of experimental approach. Nonetheless, sediment toxicity testing may be a

useti1 tool for elucidating basic trends in sediment contamination.

The applicability of toxicity tests to what may actually be occurring in a

contaminated aquatic environment may be even funher artificial 1 y construed through the

use of questionable biomonitors. or inappropriate means of exposure. For example.

Wang ( 199 1 ) used lettuce plants for testing the toxicity of industrial effluents being

discharged into the aquatic ecosystem. In my opinion. however. the responses of a

terresnial plant will not necessarily be indicative of those for an aquatic plant. It would

be more appropriate to employ a biomonitor which actually occurs in the contaminated

habitat under investigation. In addition. Wang' s study ( 199 1 ) involved exposing the

lettuce seeds in a petri dish, an environment that does not even closely resemble a natural

environment. Many potential interactions between the sediment and water column, such

as di f k i o n of contaminants. and settling or resuspension of particles. were therefore

ignored in that artificial system. The toxicity tests conducted in this study should provide

3 more realistic estimate of the toxicity of the sediments in the field. because they

simulated an aquatic environment. and a plant commonly found growing in that

environment ( C/: americana) was used.

Comparison ofplant measures used in his srudy wirh roor:shoot ratio

To our knowledge. the leaf-to-root surface area ratio is a plant measure which has

not previously been used outside of work conducted in our laboratory. However. it is

likety comparable with some other plant growth measures and indices used elsewhere in

the literature. For example. often plant physiologists and ecologists examining biomass

partitioning among plant struct~~~s will measure root:shoot biomass ratios ( e g

Nicholson & Best 1974). T h s measure generally ranges between zero and one. since

plants rarely produce more below-ground biomass (roots. stolons. rhizomes. corms.

turions. etc.) than above-ground biomass (stems, leaves. etc.). Ratios approaching unity

represent relatively equal biomass allocation to the roots and shoots. while smaller ratios

represent a greater proportionate allocation towards the shoots. The leaf-to-root mass

ratio used in this study is essentially just the reciprocal of root:shoot biomass. However.

in contrast with traditional methods of calculating root:shoot biomass. we did not include

the masses of stolons, turions. fruiting/flowering structures. or caudices into the leaf and

root mass measurements. The Icaf-to-root surface area ratio should be strongly

(negatively) correlated with the root:shoot biomass for any given plant. However. we

argue that the leaf-to-root surface area ratio may be mote sensitive to environmental

stresses. Not on1 y will the leaf-to-root surface area ratio reflect changes in biomass

rtllocation between the leaves and roots. but it will also reflect any changes in the shapes

of those structures (i-e.. surface area:mass). For example. two plants may have the same

root mass. but one plant may have a smaller number of thicker roots than the other.

thereby resulting in a smaller exposed root surface area.

Some of the trends which we have observed with the leaf-to-root surface area

ratio. are likely comparable to effects seen with root:shoot biomass. For example. it has

been widely observed that.

"any growth limiting condition or resource ... will also induce a change in the resource partitioning of the plant. This will result in proportionally increased allocation of linear size. number or mass in favour of that part of the plant which draws most upon the growth limiting part of the environment. As plain examples: nutrient limited plants become more rooty. shaded plants. more shooty." (Hunt & Nicholls 1 986).

These trends were clearly observed among plants in the field with respect to the effects of

shade stress. in that under low light intensities and high plant densities, proportionately

more biomass was allocated to the above-ground structures. resulting in higher leaf-to-

root surface area (and mass) ratios. The applicability of this rule to contaminant stress.

however. is less clear. Under growth-limi ting conditions involving absence of resources

required for plant growth. it is logical for a plant to optimize structures for obtaining the

resources that are in short supply. However, when growth limiting conditions arc due to

the presence of undesirable constituents. it would be detrimental for the plant to partition

more biomass towards structures responsible for uptake of the hannfid materials. Most of

the studies into root:shoot partitioning, however, have focussed on terrestrial plants. The

functions of terrestrial plant structures are comparatively more canalized and defined than

those of aquatic plants. with uptake of most mineral nutrients occuning solely from the

soil. \ria the roots. while gases are obtained from the air. via the leaves. Aquatic plants

have the advantage of being able to obtain many of their resources through either the

leaves or roots. though generally one structure is more efficient at obtaining certain

nutrients. and is therefore the preferential route of uptake (see Chapter 1. p. 8). So. in the

case of an aquatic plant. the presence of contaminants in the sediments could stimulate

the plant to reduce its biomass allocation towards the roots. thereby minimizing the

112

absorptive surface area available for uptake of the contaminants. Instead. the plant may

then allocate more biomass towards the leaves, which are not in contact with the

sediment-borne contaminants. and the leaves can take over absorption of nutrients via the

water column instead of via the roots. Hunt and Nicholls ( 1986) suggested that the

partitioning of resources between above- and below-ground plant structures is controlled.

in part, by the relative amounts of above- and below-ground environmental stress. I

propose that the changes observed in the leaf-to-root surface area ratio of V. americana

likely reflect an attempt at balancing the stresses experienced. and the assimilative roles

performed. by the above- and below-ground structures.

Contaminant indices

In the 1995 field study, contaminant indices were calculated for sediment and

water phases in order to compare sites for which we might have different numbers and

kinds of contaminants. Similar contamination indices were used by Bishop er al. (1995)

in order to compare organochlorine loads in passerine eggs. nestlings. or sediment

samples among 14-different sites. They ranked the sites in terms of concentrations for

each contaminant. summed the ranks for a site. and then expressed that as a percentage of

the score that the site would have received had it been most contaminated for all

organochlorines considered. Our indices differed in that we did not rank the sites for

each contaminant. but instead assigned them a score between one and five in terms of

severity. Therefore. in our study it was possible for many sites to receive the same score

for a particular contaminant. Our approach may have resulted in overall indices with less

113

variation among sites (due to the use of fewer categories), however. due to the

conservative nature of our index calcdations, observed variations among the sites are

more likely to be significant. It also seems realistic to recognize that many sites may

have similar contamination levels. rather than enforcing a ranking between similar sites.

In addition. since this study involved over 200 sites (instead of just 14. as in Bishop's

study). ranking would have been much more tedious.

Recommended prorocol for biornoniroring in Areas of Concern

For managers considering using K americana for biomonitoring purposes, I

would suggest incorporating several considerations into the sampling protocol. First, I

would recommend that ramets of V . americanu be sampled from representative locations

throughout the area of interest. but with extra sampling effort concentrated around known

or suspected sites of pollution or point source discharges (rather than using a strictly

uniform grid pattern for the sampling scheme). It is of greater importance to focus

sam pi ing around potential ho tspo ts rather than unnecessari i y wasting financial resources

on areas that are not likely to reveal anything of interest. That is not to say. however. that

sampling should Q& be conducted in known areas of contamination. othemise.

previousiy unknown problem spots may continue to go unnoticed. However. less

detailed contours are needed in these non-suspect areas. If large leaf-to-root surface area

ratios are observed for isolated sites in more sparsely sampled areas. then the researcher

should return to those areas at a later date and conduct more intense sampling to confirm

and delineate the potentially impacted area.

1 lJ

Secondly. I would recommend collecting several ramets from each rnicrosite that

is sampled in order to give an estimate of within-site variation. In this study. collection

of five ramets per rnicrosite appeared to give sufficient measures of mean leaf-to-root

surface area ratios for the location. but a greater number of replicates may give even

better results (I wouid recommended that no fewer than five plants per site be used).

Finally. I would recommend that sampling of any locations which will be

compared should be conducted within a nanow t i m e - h e of each other (i.e.. over no

more than a span of a week or two). The leaf-to-root surface area ratio of V. arnericana

does change with time. increasing up to maturity as the plants grow (Biernacki er al.

1996), and declining at the end of the growing season (see Chapter 3, p. 99). Therefore,

plants coIlected at different stages of maturity cannot be reliably compared. However. the

relative ranking of sites in terms of the leaf-to-toot surface area ratio has been found to

remain constant over the growing period of the plants. Therefore. when comparing

relative r d i n g s of sites from studies conducted in different years. it is not important

whether the diflerent studies were conducted at the same time of year. as long as it is at

some point during the growing season. However. if a researcher is planning on collecting

plants from a large number of sites. such that the sampling process is expected to take

more than a couple of days. I would recommend that sampling be conducted around the

time of flowering (in southern Ontario this approximately corresponds to early August) .

At this stage in its life cycle. F americana has generally reached its peak biomass and its

grouth rate has slowed so that the leaf-to-root surface area ratio is more likely to remain

relatively stable until the onset of senescence.

Sediment conzaminaiion

The studies conducted in this thesis reinforce the importance of sediment

contamination in assessing site quality. Contaminants that have moved from the water

column to the sediments cannot be considered inert or "settled out" and no longer a

threat. From these studies. it is obvious that even buried or diluted sediment

contaminants may still be accumulated by aquatic plants such as C/. americana. thereby

making them biologically available to herbivores and enabling their passage throughout

the food web.

The importance of sediment contamination has been addressed in the United

States through the development of the ARCS (Assessment and Remediation of

Contaminated Sediments) Program. This six-year program. headed by the Great Lakes

National P r o g m O%ce of the Environmental Protection Agency, was initiated in 1988

in order to develop an effective approach towards assessing the extent and severity of in-

place sediment contamination. and to develop appropriate remedial approaches (C'SEP.4

1992). One of the recommendations produced from this program was that a multi-tiered

approach be taken towards contaminant assessment. with initial assessments being made

through the use of quick. inexpensive screening-level analyses. The ARCS program

recognized the need for biological assessments. in order to estimate potential impacts on

local biota and therefore included benthic invertebrates. fish. algae. and bacteria as test

organisms for toxicity testing and biomonitoring. However. there was no examination of

any kind into effects of contaminated sediments on vascular plants and the macrophyte

community. 1 would strongly urge that the use of a macrophyte biomonitor should be

116

included in the battery of tests used to analyse sediment quality. The use of plant growth

form in V. americana provides an ideal and inexpensive screening-level analysis of

sediment contamination by using an organism that is located at the base of the food web

at risk.

LITERATURE CITED

.Antonovics. J.. AD. Bradshaw and R.G. Turner. 197 1. Heavy metal tolerance in plants. Advances in Ecological Research 7: 1-85.

ASTM. 1994. Standard guide for collection. storage. characterization. and manipulation of sediments for toxicological testing. American Society for Testing and Materials. Standard Guide E 1 39 1 -94. Philadelphia PA.

Barko. J.W.. and R.M. Smart. 1981. Sediment-based nutrition of submersed macrophytes. Aquatic Botany LO: 3 39-35 2.

Barko. J.W.. D. Gunnison and S.R. Carpenter. 1991a. Sediment interactions with submersed macrophyte growth and community dynamics. Aquatic Botany 41: 4i-65-

Barko. J.W.. R.M. Smart. and D.G. McFarland. 1991 b. Interactive effects of environmental conditions on the growth of submersed aquatic macrophytes. Journal of Freshwater Ecology 6: 199-207.

Bay of Quinte RAP Coordinating Committee. 1990. Bay of Quinte remedial action plan. Stage 1 report: Environmental setting and problem definition. Environment Ontario. Environment Canada. Fisheries and Oceans Canada. Ontario Ministry of Natural Resources. Ontario Ministry of Agriculture and Food.

Biemacki. M.. J. Lovett-Doust. and L. Lovett-Doust. 1995a. The effects of trichloroethylene. plant sex and site of origin on modular demography in Callisneria americana. Journal of Applied Ecology 32: 76 1-777.

Biernacki. iV.. J. Lovett-Doust. and L. Lovea-Doust. 1995b. Sediment effects on the uptake of ttichloroethylene by roots and leaves of FbNisneria arnericana. Pages J 1 3-426 in M. Munawar. T. Edsall and J. Leach, editors. The Lake Huron Ecosystem: Ecology. Fisheries and Management. Ecovision World Monograph Series. S. P. B. Academic Publishing, Amsterdam. The Netherlands.

Biemacki. M.. J. Lovett-Doust. and L. Lovett-Doust. 1996. Vallisneria americana as a biomonitor of aquatic ecosystems: leaf-to-root surface area ratios and organic contamination in the Huron-Erie corridor. Journal of Great Lakes Research 22: 289-303.

B iernacki. M.. J. Lovett-Doust, and L. Loven-Doust, 1997a. Temporal biomonitoring using wild celery. Vallisneria anrericanu. Journal of Great Lakes Research 23: 97-1 07.

Biernacki. M.. J. Lovett-Doust. and L. Lovett-Doust. 1997b. Laboratory assay of sediment p h-ytotoxicity using the rnacrophyte Vallisneria americana. Environmental Toxicology and Chemistry 16: 472478.

Bishop. C.A.. M.D. Koster. A.A. Chek. D.J.T. Hussell and K. lock. 1995. Chlorinated hydrocarbons and mercury in sediments. red-winged blackbirds (Agelaius phoeniceus) and tree-swd lo ws ( Ta~h~vcineta bicolor ) from wetlands in the Great Lakes - St. Lawrence River basin. Environmental Toxicology and Chemistry 14: 491-501.

Bradley. P.M. and J.T. Morris. 1990. Influence of oxygen and sulfide concentration on nitrogen uptake kinetics in Spurtina aiterniflora. Ecology 7 1 : 282-287.

Bunon. G.A.. Jr. 1995. Critical issues in sediment bioassays and toxicity testing. Journal of Aquatic Ecosystem Health 4: 15 1 - 1 56.

Carignan. R.. and J. Kalff. 1980. Phosphorus sources for aquatic weeds: water or sediments? Science 207: 987-989.

Catling, P.M.. K.W. Spicer. M. Biernacki. and J. Lovett-Doust. 1994. The biology of Canadian weeds. 103. Vallisneria americana Michx. Canadian Journal of Plant Science 74: 883-897.

CCREM (Canadian Council of Resource and Environment Ministers), 1987. Canadian water quality guidelines. Task Force on Water Quality Guidelines. Ottawa ON. Canada.

Chandra P. R.D. Tripathi. U.N. Rai. S- Sinha and P. Garg. 1993. Biomonitoring and amelioration of nonpoint source pollution in some aquatic bodies. Water Science Technology 28: 323-326.

Chaphekar. S.B. 199!. An overview on bioindicators. Journal of Environmental Bioiogy 12: 163- 168.

Ciborowski. J.J.H. and L.D. Corkurn. 1988. Organic contaminants rn adult aquatic insects of the St. Clair and Detroit Rivers. Ontario. Canada. Journal of Great Lakes Research 14: 148- 1 56.

Cohn. S.L. 1985. An evaluation of the toxicity and sublethal effects of atrazine on the physiology and growth phases of the aquatic macrophyte. Vallisneria americana L. Ph.D. thesis. Faculty of the College of Arts and Science. American University. Washington. D.C.

Coquery. M. and P.M. Welboum. 1995. The relationship between metal concentration and organic matter in sediments and metal concentration in the aquatic macrophyte Eriocaulon sepmngulare. Water Research 29: 2094-2 1 02.

Cox. P.A. 1993. Water-pollinated plants. Scientific American 269: 68-74.

Crowder. A. 199 1. Acidification. metals and macrophytes. Environmental Pollution 71: 171-203.

Dennison. W.C.. R.J. Orth, K.A. Moore, J.C. Stevenson. V. Carter. S. Kollar. P.W+ Bergstrom, and R.A. Batiuk. 1993. Assessing water quality with submersed aquatic vegetation: Habitat requirements as barometers of Chesapeake Bay health. BioScience 13: 86-94.

Dillon. T.M., D.W. Moore and A.S. Jarvis. 1994. The effects of storage temperature and time on sediment toxicity. Archives of Environmental Contamination and Toxicology 27: 5 1-53.

DiToro. D.M- C.S. Zarba, D.J. Hansen. W.J. Barry. R-C. Schwartz, C.E. Cowan. S.P. Pavlov, H.E. Allen, N.A. Thomas, and P.R. Paquin. 199 1. Technical basis for establishing sediment quality criteria for nonionic organic chemicals by using equiiibrium partitioning. Environmental Toxicology and Chemistry LO: 1 54 1 - 1583.

Dolan. D.. and J. Hartig. 1996. Research managers seek innovative ways to deal with cutbacks. Focus 21: 3-4.

Dushenko. W.T., D.A. Bright, and K.J. Reimer. 1995. Arsenic bioaccurnulation and toxicity in aquatic rnacrophytes exposed to gold-mine effluent: Relationships with environmental partitioning, metal uptake and nutrients. Aquatic Botany 50: 127-140.

Edsall. T.A.. P.B. Kauss, D. Kenaga J. Leach. M. Munawar. T. Nalepa, G. Sprules. S. Thornley. 1988. Lake St. Clair biota and their habitats: A geographic area report of the Biota Work Group. Upper Great Lakes Connecting Channels Study. 1-80.

Environment Canada. 1992. Interim criteria for quality assessment of St. Lawrence River sediment. St- Lawrence Action Plan. St. Lawrence Centre and Ministere de 1'Enviromement de Quebec. Ottawa ON, Canada.

Environment Ontario. 1988. Scientific criteria document for development of provincial water quality objectives and guidelines. Aluminum. Water Resources Branch. Toronto, ON, Canada.

Environment Ontario. 1989. Provincial water quality objectives. Toronto. ON. Canada.

Ferasol. J.. L. Lovett-Doust. J. Lovea-Doust and M. Biernacki. 1995. Seed germination in Vallisneria arnericana: effects of cold stratification. scarification. seed coat morphology and PCB concentration. Ecoscience 2: 569-376.

Fitchko. J. 1989. Criteria for contaminated soil/sediment cleanup. Beak Consultants Limited. Brampton. Ontario. Canada. Pudvan Pub. Co. Inc.. Northbrook. IL.

Guiliaoni, P. 199 1. The role of heavy metals and toxic materials in the physiological ecology of submersed rnacrophytes. Aquatic Botany 11 : 87- 109.

Gupta M.. and P. Chandra. 1994. Lead accumulation and toxicity in Vuliisneria spiralis ( L .) and HydriNa verricillara (1.f.) Royle. Journal of Environmental Science and Health A29: 503-5 16.

Haffner. D., F. Gobas and P. Hebert. 199 1. The use of aquatic vegetation and invertebrates to monitor chlorinated hydrocarbons in the Lakes Huron - Lake Erie corridor. R.A.C. Project no. 24 1 PL. Environment Ontario.

Hanes. E.C. 1992. Life history characteristics and size variation of the burrowing mayfly Hexogenia (Epherneroptera : Ephemeridae): maternal vs. environmental constraints. M.Sc. thesis. Department of Biological Sciences. University of Windsor. Windsor. ON. Canada.

Harley. M.T. and S. Findlay. 1994. Photosynthesis-irradiance relationships for three species of submersed macrophytes in the tidal freshwater Hudson River. Estuaries 17: 200-205.

Hart. D.R., J. Fitchko. and P.M. McKee. 1988. Development of sediment quality guidelines. Phase I1 - guideline development. Prepared by BEAK Consultants Limited. Brampton, Ontario. Prepared for Ontario Ministry of the Environment. Toronto. ON. Canada.

Hartig. J.H. and N.L. Law. 1994. Progress in Great Lakes remedial action plans: implementing the ecosystem approach in Great Lakes Areas of Concern. U.S. Environmental Protection Agency and Environment Canada.

Hartig. J.H. and R.L. Thomas. 1988. Development of plans to restore degraded areas in the Great Lakes. Environmental Management 12: 327-347.

Hinman, M.L., and S.J. KIaine. 1992. Uptake and translocation of selected organic pesticides by the rooted aquatic plant Hydriila verticiilti~a Royle. Environmental Science and Technology 26: 609-61 3.

Hueben. D.B.. and J.M. Shay. 1993. Considerations in the assessment of toxicity using duckweeds. Environmental Toxicology and Chemistry 12: 48 1483.

Hughes, J.S. 1992. The use of aquatic plant toxicity tests in biomonitoring programs. Proceedings of the Eighteenth Annual Aquatic Toxicity Workshop: September 30-October 3. 199 1, Ottawa, Ontario. Canadian Technical Report of Fisheries and Aquatic Sciences, no. 1863.

Hunt. R. and A.O. Nicholls. 1986. Stress and the coarse control of growth and root- shoot partitioning in herbaceous plants. Oikos 17: 149- 1 58.

Hurlbert. S.H. 1984. Pseudoreplication and the design of ecological fieId experiments. Ecological Monographs 54: 187-2 1 1.

International Joint Commission. 1987. Revised Great Lakes Water Quality Agreement of 1978 as amended by protocol signed November 1 8. 1987. Ottawa, ON, Canada.

Jackson, L.J., and J. Kalff. 1993. Patterns in metal content of submerged aquatic macrophytes: the role of plant growth form. Freshwater Biology 29: 35 1-359.

Jackson, L.J., J. Kaiff and J.B. Rasrnussen. 1993. Sediment pH and redox potential affect the bioavailability of Al, Cu, Fe, Mn, and Zn to rooted aquatic rnacrophytes. Canadian Journal of Fisheries and Aquatic Sciences 50: 143- 148.

Jackson. M.B. 1985. The dominant attached filamentous algae of Lake Huron: field ecology and biomonitoring potential 1980. Aquatic Ecosystems Section, Water Resources Branch, Ontario Ministry of the Environment. 49 pp.

Jana, S . and M. A. Choudhuri. 1 982. Senescence in submerged aquatic angiosperms: effects of heavy metals. New Phytologist 90: 477484.

Jana, S. and M.A. Choudhuri. 1984. Synergistic effects of heavy metal pollutants on senescence in submerged aquatic plants. Water, Air, and Soil Pollution 21: 35 1-357.

Kapustka, L.A. 1997. Selection of phytotoxicity tests for use in ecological risk assessments. Pages 5 15-548 in W. Wang, J. W. Gorsuch and J.S. Hughes, editors. Plants for Environmental Studies. Lewis Publishers (CRC Press LLC), Boca Raton, FL.

Kauss. P.B. and Y .S. Hamdy . 1 985. Biological monitoring of organochlorine contaminants in the St. Clair and Detroit rivers using introduced clams. Elliptio cornplanatus. Journal of Great Lakes Research 1 1 : 247-263.

Kimber. A.. C.E. Korschgen and A.G. van der Valk. 1995. The dismbution of VaZlisnerio americanu seeds and seedling light requirements in the Upper Mississippi River. Canadian Journal of Botany 73: 1966- 1973.

Klaine. S.J.. K. Brown, T. Byl. and M.L. Hinman. 1990. Phytotoxicity of contaminated sediments. Abstracts h m the Annual Meeting of the Society of Environmental Toxicology and Chemistry. No. P092. Arlington. VA.

Kovats. Z.E. and J.J.H. Ciborowski. 1989. Aquatic insect adults as indicators of organochlorine contamination. Journal of Great Lakes Research 15: 623-634.

Krantzberg, G. 1992. Collingwood Harbour mussel biomonitoring, 1990 data repon. Water Resources Branch, Ontario Ministry of the Environment. Toronto. Ontario.

Krantzberg, G. & E. Houghton. 1996. The remedial action plan that led to the cleanup and delisting of Collingwood Harbour as an area of concern. Journal of Great Lakes Research 22: 469-483.

Krieger. K. A. 1 984. Benthic macroinverte braes as indicators of environmental degradation in the southern nearshore zone of the central basin of Lake Erie. Journal of Great Lakes Research LO: 197-209.

Locqr. S.. R. Carignan and D. Planas. 1983. The role of roots in carbon uptake by the submersed macro phytes Myriophyllum spicatum. Vallisneria americana. and Heteranrhera dubia. Hydrobiologia 9%: 3-7.

Lokker. C.. L. Lovett-Doust and J. Lovett-Doust. 1997. Seed output and the seed bank in Vallisneria a m e r i c a ~ ( H ydroc haritaceae). American Journal of Botany 84: 1320-1428.

Lovett-Doust. J. and G. Lapone. 1991. Population sex ratios, population mixtures and fecundity in a clonal dioecious macrophyte. Journal of Ecology 79: 477-489.

Loven-Doust. J.. L. Lovett-Doust. M. Biernacki. T.K. Ma1 and R- Lazar. 1997. Organic contaminants in submersed macrophytes drifting in the Detroit River. Canadian Journal of Fisheries and Aquatic Sciences 54: 241 7-2427.

Lovett-Doust. J., M. Schmidt. and L. Lovett-Doust. 1994a. Biological assessment of aquatic pollution: a review wirh emphasis on plants as biomonitors. Biological Reviews 69: 147- 1 86.

Lovett-Doust. L.. J. Lovett-bust, and M. Biemacki. 1994b. American wildcelery, Vallisneria a m e r i c a ~ , as a biomonitor of organic contaminants in aquatic ecosystems. Journal of Great Lakes Research 20: 333-3 54.

Lovett-Doust. L.. J. Lovett-Doust and M. Schmidt. 1993. in praise of plants as biomonitors - send in the clones. Functional Ecology 7: 754758-

~Ianny, B.A.. SJ . Nichols and D.W. Schioesser. 1991. Heavy metals in aquatic macrophytes drifting in a large river. Hydrobiologia 219: 333-344.

Martin. P.A., D.V. Weseloh, C.A. Bishop, K. Legierse, B. Braune and R.J. Norstrom. 1995. Organochlorine contaminants in avian wildlife of Severn Sound. Water Quality Resean: h Journai of Canada 30: 693 -7 1 1.

MDNR and OMEE. 199 1. Stage 1 remedial action plan for Detroit River Area of Concern. Michigan Department o f Natural Resources, Surface Water Quality Division. Lansing,MI. Ontario Ministry of the Environment, Detroit/St.Clair/St. Marys Rivers Project. S a m k ON, Canada.

Meyer. B.S.. F.H. Bell. LC. Thompson and E. Clay. 1943. Effect of depth of immersion on apparent photosynthesis in submersed vascular aquatics. Ecology 24: 393-399.

Miller. R.G.. Jr. 1986. Beyond ANOVA. basics of applied statistics. John Wiley & Sons. Inc. New York. NY.

Mineau. P.. G.A. Fox. R.J. Norstrom, D.V. Weseloh, D.J. Hallett. and J.A. Ellenton. 1 984. Usifig the herring gull to monitor levels and effects of organochlorine contamination in the Canadian Great Lakes. Chapter 19, pp- 425352. In: J.O. Nriagu and M S . Simmons (eds.). Toxic contaminants in the Great Lakes. J. Wiley and Sons. New York, NY.

Morris. J.T. and J.W.H. Dacey. 1984. Effects of 0, on ammonium uptake and root respiration by S'rtim alternifora. American Journal of Botany 7 1 : 979-98 5 .

Mortimer. D.C. 1985. Freshwater aquatic macrophytes as heavy metal monitors - the Ottawa River experience. Environmental Monitoring and Assessment 5: 3 1 1 -3 23.

Muncaster. B. W-. D.J. t ~ e s . P.D.N. Hebert and G.D. Hafher. 1989. Patterns of organic contaminant accumulation by frtshwatcr mussels in the St. Clair River. Ontario. Journal of Great Lakes Research 15: 645453.

Newell. A.J. 1989. Clean-up criteria for aquatic sediments. New York State Department of Environmental Conservation. Albany, NY.

NYSDEC (New York State Department of Environmental Conservation). 1993. Technical guidance for screening contaminated sediments. Division of Fish and Wildlife. Division of Marine Resources. Albany, NY.

OMEE. 1993. The Niagara River (Ontario) Area of Concern remedial action plan - stage 1 : environmental conditions and problem definitions. Ontario Ministry of Environment and Energy. Toronto, ON, Canada

OMEE. 1 994. Provincial water quality objectives and guidelines. Ontario Ministry of Environment and Energy. Toronto. ON. Canada

Persaud, D., R Jaagumaagi, and A. Hayton. 1991. The provincial sediment quality guide 1 ines. Draft Water Resources Branch. Ontario Ministry of the Environment, Toronto. ON, Canada.

Pip, E. 1990. Cadmium. copper and lead in aquatic macrophytes in Shoal Lake ( Manitoba-Ontario). Hydrobiologia 208: 253-260.

Pip. E. and .J. Stepaniuk, 1992. Cadmium, copper and lead in sediments and aquatic rnacroph>?es in the lower Nelson River system. Manitoba Canada. I. Interspecific differences and macrophyte-sediment relations. Archiv fur Hydrobiologie 121: 3 37-355.

Port Hope Harbout RAP Team. 1989. Port Hope Harbour remedial action plan. Stage 1 : Environmental conditions and problem definition. Environment Canada. Ontario Ministry of the Environment.

Pugsley. C.W.. P.D.N. Heben. G.W. Wood, G. Brotea and T.W. Obal. 1985. Distribution of contaminants in clams and sediments fiom the Huron-Erie comdor (I - PCBs and octachlorostyrene). Journal of Great Lakes Research 11: 275-289.

Pugsley, C.W.. P.D.N. Hebert and P.M. McQuarrie. 1988. Distribution of contaminants in cIams and sediments fiom the Huron-Erie corridor. I1 - Lead and cadmium. Journal of Great Lakes Research 14: 356-368.

Ray. S. and W. White. 1976. Selected aquatic plants as indicator species for heavy metal pollution. Journal of Environmental Science and Heal l A1 1 : 77-725.

Reimer. P. and H.C. Duthie. 1 993. Concentrations of zinc and chromium in aquatic macrophytes from the Sudbury and Muskoka regions of Ontario. Canada Environmental Pollution 9: 26 1 -265.

Richman. L. 1992. The Niagara River mussel and leech biomonitoring study. Water Resources Branch. Ontario Ministry of the Environment.

SEMCOG. 1 988. Remedial action plan for the Rouge River basin. Volume 2. Southeast Michigan Council of Governments. Detroit. MI.

Severn Sound RAP Team. 1988 (revised 1989). Severn Sound Remedial Action Plan. Part 1 : Environmental conditions and problem definition. Environment Ontario. Environment Canada Ontario Ministry of Natural Resources (Huronia District) and Ontario Ministry of Agriculture and Food.

Smith, B.M. 1 9 9 1. An inter- and inm-agency survey of the use of plants for toxicity assessment. Pages 4 1-59 in J. W. Gorsuch, W.R Lower, W. Wang and MA. Lewis. editors. Plants for toxicity assessment: second volume. ASTM STP 11 15. American Society for Testing and Materials, Philadelphia PA.

Smith. I.R.. C. Portt and D.A. Rokosh. 1992. Induced levels of hepatic mixed firnction oxidases in white suckers (Catostomus commersoni) as a biomarker for contamination of the sediments in lackfish Bay, and the Karninistiquia and St. Mary's Rivers. Water Resources Branch. Ontario Ministry of the Environment.

Sokal . R.R.. and F.J. RohIf. 1995. Biometry: the principles and practice of statistics in biological research. Third edition. W.H. Freeman and Company, New York. NY.

Solomon. K.R.. D.B. Baker. R.P. Richards. K.R. Dixon, S.J. Klaine. T.W. La Point. R. J. Kendall. C.P. Weisskopf, I.M. Giddings. J.P. Giesy. L.W. Hall. Jr. and W.M. Williams. 1996. Ecological risk assessment of atrazine in North American surface waters. Environmental Toxicology and Chemistry 15: 3 1-76.

Spanish River RAP Team. 1993. The Spanish Harbour Area of Concern remedial action plan. Stage 1 : Environmental conditions and problem definition. Ontario Ministry of the Environment.

SPSS. Inc. 1996. SYSTAT 6.0 for Windows. SPSS Inc.. Chicago. IL.

SPSS Inc. 1997. SYSTAT 7.0 for Windows. SPSS Inc.. Chicago. [L.

St. Clair River RAP Team. 1991. The St. Clair River Area of Concern remedial action plan. stage I : Environmental conditions and problem definitions. Submission to the International Joint Commission. Ontario Ministry of the Environment (Detroit / St-Clair / S t Marys River Project), Sarnia Ontario. and Michigan Department of Natural Resources (Surface Water Quality Division, Great Lakes Environmental Assessment Section), Lansing, MI.

St-Cyr. L., and P.G.C. Campbell. 1994. Trace metals in submerged plants of the S t Lawrence River. Canadian Journal of Botany 72: 429-439.

Stevenson, LC.. T. W. Jones. W.M. Kemp, W.R. Boynton and J.C. Means. 1983. An overview of atrazine dynamics in estuarine ecosystems. Chesapeake Biological Laboratory, Center for Environmental and Estuarine Studies. University of Maryland, Solomons, Maryland.

Steward. K.K. 199 1. Competitive interaction between monoecious hydrilla and American eelgass on sediments of varying fertility. Florida Scientist 54: 135-147.

Struger, J.. D.V. Weseloh, D.J. Hallen and P. Mineau. 1985. Organochlorine contaminants in herring gull eggs from the Detroit and Niagara Rivers and Saginaw Bay ( 1978- 1982): Contaminant discriminants. Joumai of Great Lakes Research 1 1 : 223-230.

Sullivan. J.. J. Bail. E. Brick. S. Hausmann. G. Pilarski, and D. Sopcich. 1985. Report of the technical subcommittee on determination of dredge material suitability for in- water disposal. Wisconsin Department of Natural Resources. Madison. WI .

Suns. K.. G. Hitchin and D. Toner. 1991. Spatial and temporal trends of organochlorine contaminants in spottail shiners (Nocropis hudsonius) from the Great Lakes and their connecting channels ( 1 975- 1 988). Water Resources Branch. Ontario .Ministry of the Environment.

Suns. K. R. and G.G. Hitchin. 1 992. Species-speci fic differences in organochlorine accumulation in young-of-the-year spottail shiners. emerald shiners. and yellow perch. Journal of Great Lakes Research 18: 280-285.

Swanson. S.M.. C.P. Rickard. K.E. Freemark. and P. MacQuamie- 199 1. Testing for pesticide toxicity to aquatic plants: recommendations for test species. Pages 77- 97 in J.W. Gorsuch. W.R. Lower. W. Wang, and M.A. Lewis. editors. Plants for toxicity assessment: second volume. ASTM STP 1 1 15. American Society for Testing and Materials. Philadelphia PA.

Tabachnick. B .G. and L.S. Fidell. 19%. Using multivariate statistics. Third edition. HarperCollins College Publishers. New Yo*, NY.

Taraldsen. J.E.. and T. J. Norberg-King. 1 990. New method for determining effluent toxicity using duckweed (Lemna minor). Environmental Toxicology and Chemistry 9: 76 1-767.

Titus. J.E. and M S . Adarns. 1979. Coexistence and the comparative light relations of the submersed macrophytes Myriophyflum spicarurn L. and Vallisnetia americana Michx. Oecologia 40: 273-286.

Titus. J.E.. and M.D. Stephens. 1983. Neighbour influences and seasonal growth patterns for Vullisneria a m e r i c a ~ in a mesomphic lake. Oecologia 56: 23-29.

Twilley, R.R.. and J. W. Barko. 1990. The growth of submersed macrophytes under experimental salinity and light conditions. Estuaries 13: 3 1 1-32 1.

USEPA (United States Environmental Protection Agency). 1977. Guidelines for the pollution classification of Great Lakes harbour sediments. US. Environmental Protection Agency, Region V. Great Lakes Surveillance Branch. Chicago, IL.

USEPA (United States Environmental Protection Agency). 1990. Quality criteria for water - 1989. Criteria and Standards Division. Office of Water Regulations and Standards. Washington, D.C.

USEPA (United States Environmental Protection Agency). 1 992. Assessment and remediation of contaminated sediments (ARCS) 1 992 work pian. U.S. Environmental Protection Agency, Great Lakes National Program Office. Chicago. IL.

USEPA (United States Environmental Protection Agency). 1993 . Water quality criteria summary. Office of Science and Technology. Health and Ecological Criteria Division. Ecologicai Risk Assessment Branch. Washington. D.C.

Van IVijck, C. . C.-J. de Groot and P. Grillas. 1992. The effect of anaerobic sediment on the growth of Poramogeton pecrinarw L. : the role of organic matter. sulphide and ferrous iron. Aquatic Botany 44: 3 1-49.

Vartapetian. B.B. and M.B. Jackson. 1997. Plant adaptations to anaerobic stress. Annals of Botany 79 (supplement A): 3-20.

Walker. R. and K. Willson. 1981. Plant community assessment techniques. data collection and field procedures. Grand River basin water management study, technical report series. report # 15. Water Modelling Section. Water Resources Branch. Ontario Ministry of the Environment. Toronto. Ontario. Canada.

Walsh. G.E., D.L. Hansen, and D.A. Lawrence. 1982. A flow-through system for exposure of seagrass to pollutants. Marine Environmental Research 7: 1 - 1 1 .

Wang. W. 1 99 1. Higher plants (common duckweed. lettuce. and rice) for effluent toxicity assessment. Pages 68-76 in J.W. Gorsuch, W.R. Lower, W. Wang, and M.A. Lewis. editors. Plants for Toxicity Assessment: Second Volume. ASTM STP 1 1 15. American Society for Testing and Materials. Philadelphia PA.

Wang, W.C. 1986. Comparative toxicology of phenolic compounds using root elongation method. Environmental Toxicology & Chemistry 5: 891 -896.

Wells, J.R.. P.B. Kaufman and J.D. Jones. 1980. Heavy metal contents in some macrophytes from Saginaw Bay (Lake Huron. U.S.A.). .Aquatic Botany 9: 185-193.

Weseloh. D.V.. P. Mineau and J. Srmger. 1 990. Geographical distribution of contaminants and productivity measures of herring gulls in the Great Lakes: Lake Erie and connecting channels. The Science of the Total Environment 91: 141 - 159.

APPENDIX A

DESCRIPTION OF AREAS OF CONCERN STUDIED

S L m c L L w e t

This 1 12 km connecting channel between Lake Superior and Lake Huron is

divided between the province of Onrario (Canada) and the state of Michigan (U.S.A.).

Impairments are primarily due to point sources on the Canadian side. including Algoma

Steel. St. M q s Paper. and two water poilution control plants. The major contaminants

are oil and grease. PAHs. phenols. ammonia metals and bacteria (Hartig & Law 1994).

This AOC covers the lower 53 krn of Spanish River. fiom the town of Espanola to

the mouth of the river at Spanish where it empties into the North Channel of Lake Huron.

Impairments in this area are primarily due to the mining industry in the Sudbur).. region.

and, historically. through discharges fiom the E.B Eddy Forest Products Ltd. pulp and

paper mill located at Espanola (though upgrades on the mill and remediation efforts have

significant1 y reduced the mill's impact: Hanig & Law 1 994).

Sevcrn Sound

Located in the southeastern comer of Georgian Bay. Lake Huron. this AOC

includes Penetang. Midland. Hog. and Sturgeon Bays. The major impairment is

eutrophication due to excessive phosphorus inputs from agricultural runoff. and the six

sewage treatment plants discharging directly into Severn Sound. In a few areas. certain

metal concentrations in the water and sediment have also been found to exceed

~uidelines. Major industries discharging waste in the Sevem Sound area include -

131

.Witsubishi Electronics Industries Canada Inc.. Bay Mills Ltd.. Dominion Electroplating,

Indusrnin Ltd.. and Waltec PIastics (Severn Sound RAP Team 1988).

Collinpwood Harbou

Collingwood Harbour is located on the southern shore of Nottawasaga Bay in the

Georgian Bay region of Lake Huron. Having completed stage three of the RAP process

in 1993. technically Collingwood Harbour is no longer an Area of Concern (Krantzberg

& Houghton 1996). Historically, the harbour's main impairments involved excessive

nutrient inputs fiom the sewage treatment facility , and contaminated sediments located

around the former Canada Steamship Limited shipyard slips. Upgrades to the sewage

treatment plant and the removal and disposal of 8.000 m' of contaminated sediment have

since been completed (Hartig & Law 1994).

St. CIair River

This 64 km connecting channel. divided between Ontario and Michigan. flows

south from Lake h r o n to Lake St. Clair. Major point sources of contaminants are

located along the northern reaches of the Canadian side. just south of Sarnia in a region

described locally as "Chemical Valley-'. This stretch of the river is lined with numerous

petroleum and chemical industries. including Imperial Oil Ltd. . Polysar Ltd.. Dow

Chemical of Canada Sun Oil Co. Ltd.. Shell Canada Ltd.. Ethyl Corp. of Canada.

DuPont of Canada. and Allied Chemical (St. Clair River RAP Team 1991 ). Major

contaminants released into the St. Clair River include organochlorines. heavy metals. oil

and grease, and phenols.

. . etrolt k v e ~

This 5 1 km river flows south fiom Lake St. Clair into Lake Erie and is divided

between Ontario and Michigan. Water and sediments are contaminated with PCBs,

PAHs. metals, oil and grease, and bacteria Major point sources are primarily located

along the Michigan shore, and include three Great Lakes Steel plants, McLouth Steel

Corp., five power plants, BASF, Chrysler, Monsanto Corp.. PVS Chemicals, Pemwalt

Corporation. Federal Marine Terminals, Michigan Foundation, and Atochem Inc.

Industrial point sources on the Ontario side include Ford Motor Co., Hiram Walker &

Sons, Canada Salt, Allied Chemicals Canada, and General Chemical Canada (MDNR &

OMEE 1991).

The entire watershed of this American river, located in southeastern Michigan,

has been designated as an Area of Concern. However, the studies conducted in this thesis

focus only on the lower portion of the river where it empties into the Detroit River. Water

and sediments near the mouth of the Rouge River are severely contaminated with heavy

metals, PCBs, oil and grease, nutrients, and fecal coliform bacteria. Some of the major

industries which discharge into the lower portion of the Rouge River include Rouge

Steel, Shell Oil Co., Ford Motor, Detroit Coke, Detroit Edison, and Double Eagle Steel

(SEMCOG 1988).

v This AOC is located along the north shore of Lake Erie. just east of Point Pelee.

and includes the harbour itself. as well as Muddy Creek and its associated wetlands

upstream fiom the harbour. Historically. the main source of contamination was due to

discharges fiom Omstead Foods. a food processing plant. Upgrades to the industry's

wastewater treatment plant have significant1 y reduced the inputs fiom this source (Hartig

& Law 1 994). However. there are still some concerns about bacterial contamination and

contamination of the sediments with moderate Levels of PCBs. The harbour experiences

heavy traffic. primarily due to commercial fishing boats.

River:

This river flows north fiom Lake Erie to Lake Ontario. and has a large waterfall

(hriagara Falls) approximately halfivay along i t s course. The Area of Concern includes

the entire 58 km length of the river and also the Wetland River watershed which drains

into the Niagara River. In Ontario there are 16 municipal and industrial point sources

w-hich discharge heavy metai, organic and nutrient contamination into the Niagara River

and its tributaries. Industries include Canadian-Oxy Chemicals. Gouid Manufacturing.

Fleet LManufacturing. Atlas Specialty Steels. Stelco-Stelpipe Welland Tube Works. the

Niagara Fails Glass Plant of the Ford Motor Company of Canada B.F. Goodrich. and

Cyanamid of Canada. However. the major inputs of toxic contaminants come fiom the

American side of the river which is lined with numerous industries as well as seven

Superfund waste disposal sites which are known to leach contaminants directly into the

Niagara River (OMEE 1993).

This is a relatively enclosed harbour located at the extreme western end of Lake

Ontario. .\lthough the northern shore of the harbour is lined with parks and private

residences. the southern shore is dominated by industry, including two large steel

manufacturers. Stelco and Dofasco- Sediments in the harbour are severely contaminated

with metals and PAHs. Several pilot projects have been conducted to determine the best

method for sediment remediation in the harbour (Hartig & Law 1994).

This Area of Concern is located on the northwestern shore of Lake Ontario. It

extends along much of the Iakefiont of Metropolitan Toronto. fiom Etobicoke Creek to

the Rouge + River (not to be confked with the Rouge River, Michigan 1. as well as

including six tributary watersheds. Contamination includes heavy metals. organics. and

bacteria from industrial discharges. sewage treatment plants. and combined sewer

overflows. Some contaminated sediment was removed from the inner harbour in 1992

and treated at a soil recycling facility (Hartig & Law 1994).

Port Hoge Harbour

This is one of the smaller AOCs. centrally located on the northern shore of Lake

Ontario at the mouth of the Ganaraska River. The harbour sediments are severely

135

contaminated with uranium and other radionuclides. heavy metals and PCBs. Much of

this contamination is due to historic waste management practices in the refining and

processing of uranium and radium during the 1930's and 1940's (Port Hope RAP Team

1989). The only industry discharging into the harbour is CAMECO (Eldorado Resources

Ltd.) which converts refined uranium trioxide to uranium hexafluoride. The harbour is

no longer used for commercial boat traffic. but serves as a mooring area for the Port Hope

Yacht Club.

B av of Quintg

This Area of Concern is a long (64 km), 2-shaped embayment on the northeastern

shore of Lake Ontario. Contamination includes agricultural and urban runoff, excessive

phosphorus inputs from sewage treatment plants, and contamination of sediments with

PCBs, organochlorines, and heavy metals fiom industrial discharges. Major industries in

the area include the Domtar Wood Preserving Plant, Domtar Packaging, Bakelite

Thermosets, Snathcona Paper, General Motors and Outboard Marine (Bay of Quinte

RAP Coordinating Cornmi ttee 1 990).

St. Lawrence Rivet

The St. Lawrence River is a major international river which flows fiom Lake

Ontario out into the St. Lawrence Gulf of the Atlantic Ocean. The Area of Concern in the

St. Lawrence River can actually be divided into two regions, the Cornwall AOC (which

represents the Canadian side, and was examined in this study) and the Massena AOC (the

U S . side). The AOC at Cornwall extends fiom the Moses Saunders Power Dam at

Cornwall. Ontario. to the Beauharnois Power Darn in Quebec and involves the province

of Ontario. New York State. as well as land owned by the Mohawks of Akwasasne.

Major causes of contamination are PCBs fiom U.S. Superfbnd sites in Massena New

York. and mercury fiom Ontario industries (Hartig & Law 1994).

APPENDIX B

REFERENCES USED IN COMPILATION OF

MICROSITE DATABASE

Anderson. 1. 1990. St. Lawrence River environmental investigations. Volume 4: Assessment of water and sediment quality in the Cornwall area of the St. Lawrence River. 1985. Great Lakes Section. Water Resources Branch, Ontario Ministry of the Environment. 40 pp + Appendix.

Beak Consultants Limited. 1988. An evaluation of persistent toxic contaminants in the Bay of Quinte ecosystem. Bay of Quinte Remedial Action Plan.

Bishop. C.A., M.D. Koster. A.A. Chek, D.J.T. Hussel. and K. Jock. 1995. Chlorinated hydrocarbons and mercury in sediments, red-winged blackbirds (Agelaius phoeniceus) and tree swallows (Tachycinera bicolor) from wetlands in the Great Lakes - St, Lawrence River basin. Environmental Toxicology and Chemistry 14: 491-501.

Boner, R.F. and 0. Meresz 198 1 . St. Clair River organics study. Identification and quantitation of organic compounds. Laboratory Services Branch, Ontario Ministry of the Environment. 2 19pp.

Borgmann, U. and W.P. Norwood. 1993. Spatial and temporal variability in toxicity of Hamilton Harbour sediments: Evaluation of the Hyalella uzfeca 4-week chronic toxicity test. Journal of Great Lakes Research 19: 72-82.

Boyd, D. 1988. The effect of contaminants associated with suspended sediment on water quality in the Toronto waterfront during 1985. Great Lakes Section, Water Resources Branch, Ontario Ministry of the Environment.

Chan. C.H. 1980. St. Lawrence River Water Quality Surveys, 1977. Scientific Series No. 1 13. Inland Waters Directorate, Ontario Region, Water Quality Branch, Environment Canada. Burlington, Ontario. l6pp.

Chan, C.H. and 3. Kohli. 1987. Surveys of trace contaminants in the St. Clair River, 1 985. Scientific Series No. 1 58. Inland WatersLands Directorate. Ontario Region. Water Quality Branch, Environment Canada. Burlington, Ontario. 10 pgs.

Chau, Y.K.. P.T.S. Wong, G.A. Bengert, J.L. Dunn and B. Glen. 1985. Occurrence of alkyllead compounds in the Detroit and St. Clak rivers. Journal of Great Lakes Research 11: 313-319.

Ciborowski, J. J.H. and L.D. Corkum. 1 988. Organic contaminants in adult aquatic h e c t s of the St. Clair and Detroit Rivers, Ontario, Canada Journal of Great Lakes Research 14: 148- 1 56.

Collingwood RAP Work Team. 1989. Collingwood Harbour remedial action plan. stage 1 : environmental conditions & problem definition. Environment Ontario and Environment Canada.

Comba M.E. and K.L.E. Kaiser. 1985. Volatile halocarbons in the Detroit River and their relationship with contaminant sources. Journal of Great Lakes Research 11: 404-418.

DeVault, D. 1984. Polychlorinated dioxins and polychlorinated furans in fish from the Great Lakes and Midwest. U.S. Environmental Protection Agency, Great Lakes National Program Offke. Chicago, Illinois. 39pp.

Dickrnan, M., I. Brindle and M. Benson. 1992. Evidence of teratogens in sediments of the Niagara River watershed as reflected by chironomid (Diptera: Chironomidae) deformities. Journal of Great Lakes Research 18: 467-480.

Dushenko, W.T. 1990. Physical and chemical factors affecting aquatic macrophytes in the Bay of Quinte, Lake Ontario. Ph.D. Thesis. Queen's University, Kingston, Ontario.

Dushenko, W.T., A. Crowder and J. Greig. 1989. Shoreline distribution of contaminants and submerged macrophytes in the Bay of Quinte, Ontario. pp. 377-84 In: Bardecki. M.J. and N. Patterson (Eds). 1989. Wetlands: Inertia or momentum. Federation of Ontario Naturalists, Don Mills. Ontario.

Edsall, T.A., P.B. Kauss, D. Kenaga, J. Leach, M. Munawar, T. Nalepa, G. Sprules, S. Thomley . 1988. Lake St. Clair biota and their habitats: A geographic area report of the Biota Work Group, Upper Great Lakes Connecting Channels Study. 1-80.

Edwards, C.J., P.L. Hudson, W.G. DufTy, S.J. Nepszy, C.D. McNabb, R.C. Haas, C.R. Liston, B. Manny, W.N. Busch. 1989. Hydological, morphomeaical, and biological characteristics of the connecting rivers of the international Great Lakes: A Review. p.240-264, in: D.P. ilodge (ed.). Proceedings of the International Large River Symposium. Volume 106. Canadian Special Publication of Fisheries and Aquatic Sciences.

Environmental Control Technology Corporation. 1974. Water pollution investigation: Detroit and St. Clair Rivers. U.S. Environmental Protection Agency, Region V, Enforcement Division, Great Lakes Initiative Contract Program. Report No. EPA-905/9-74-0 13. AM Arbor, MI.

Fallon, M.E. and F.J. Horvath. 1985. Preliminary assessment of contaminants in sofi sediments of the Detroit River. Journal of Great Lakes Research 11 : 373378.

Fitchko. J. and T.C. Hutchinson. 1975. A comparative study of heavy metal concentrations in river mouth sediments around the Great Lakes. Journal of Great Lakes Research 1 : 46-78.

Fox, M.E., J.H. Carey and B.G. Oliver. 1983. Compartmental distribution of organochlorine contaminants in the Niagara River and the Western Basin of Lake Ontario. Journal of Great Lakes Research 9: 287-294.

Frank, R., R. L. Thomas, M.V.H. Holdrinet and V. Darniani. 1980. PCB residues in bottom sediments collected from the Bay of Quinte 1 972- 1973. Journal of Great Lakes Research 6: 3 7 1-376.

Furlong, E.T., D.S. Carter and R.A. Hites. 1988. Organic contaminants in sediments from the Trenton Channel of the Detroit River, Michigan. Journal of Great Lakes Research 14: 489-50 1.

Gartner Lee Limited 1987. Water Resources of the Niagara Frontier and the Welland River drainage basin. The Ontario Ministry of the Environment. 104 pp. + appendix.

Gerrua, A.F. 1995. Spatial and temporal water q d i t y trends in Severn Sound. Georgian Bay, since the introduction of phosphorus control guidelines: Nutrients and phytoplankton, 1973 to 199 1. Water Quality Research Journal of Canada 30: 565-591

Gerrnain. A. and M. Janson. 1984. Quaiite des eaux du fleuve Saint-Laurent de Cornwall a Quebec, 1977- 198 1. Inland Waters Directorate, Water Quality Surveys, Quebec Region, Environment Canada. 232pp.

G tooschenko, W.A., W.M.J. Strachan and R.C.J. Sampson. 1 976. Distribution of pesticides and polychlorinated biphenyls in water, sediments, and seston of the Upper Great Lakes - 1974. Pesticides Monitoring Journal 10: 6 1-67,

Griffiths. M. (Ed.) 1 988. Aquatic environment of Humber Bay. Water Resources Branch, Ontario Ministry of the Environment. Toronto, Ontario. 93pp. + appendix.

Hamdy, Y., J.D. Kinked and M. Griffiths. 1 978. St. Marys River water quality investigations, 1973-74. Great Lakes Surveys Unit, Water Resources Branch, Ontario Ministry of the Environment. S3pp.

Harndy. Y. and D.I. Ross. 1983. An assessment of water quality conditions and remedial measures in Wheatley Harbour. Lake Erie. Great Lakes Section. Water Resources Branch. Ontario Ministry of the Environment. 4 1 pp.

Harndy. Y. and L. Post. 1985. Distribution of mercury. trace organics. and other heavy metals in Detroit River sediments. Journal of Great Lakes Research 11: 353-365.

Harndy. Y. and G. Johnson. 1987. Report on the bacteriological quality of the Detroit River 1975- 1984. Great Lakes Section, Water Resources Branch, Ontario Ministry of the Environment.

Hamilton Harbour RAP Writing Team. 1989. Remedial action plan for Hamilton Harbour, Stage 1 Report: Environmental conditions and problem definitions. Ontario Ministry of the Environment. Ontario Ministry of Nahtral Resources. Ontario Ministry of Agriculture and Food, Environment Canada. Fisheries and Oceans Canada, and Royal Botanical Gardens.

Harlow, H.E. and P.V. Hodson. 1988. Chemical contamination of Hamilton Harbour: A Review. Canadian Technical Report of Fisheries and Aquatic Sciences no. 1603. 91 PP-

Hart, C.J. 1986. Niagara River tributary survey, 1983 final report. Great Lakes Section. Water Resources Branch. Ontario Ministry of the Environment.

Hart, D.R., P.M. McKee and A.J. Burt. 1986. Benthic community and sediment quality assessment of fort Hope Harbour, Lake Ontario. Journal of Great Lakes Research 12: 206-220.

Hesselberg, R.J. and Y. Harndy. 1988. Current and historicd contamination of sediment in the St. Marys River. 1987. 17 pp. + appendix.

Hopkins, G.J. 1983. The trophic status of nearshore waters in southern Lake Huron at three Ontario water supply intakes, 1976- 1 98 1. Limnology Section, Water Resources Branch, Ontario Ministry of the Environment. Rexdale. Ontario.

I r k , G.J. 1992. Great lakes surface water temperature climatology. Climatological studies number 43. Environment Canada, Atmospheric Environment Service. 215 pp.

Jaagumagi, R. 1988. The in-place pollutants program, volume V, part B: Benthic invertebrate studies results. Aquatic Biology Section, Water Resources Branch, Ontario Ministry of the Environment.

Jaagumagi. R.. T. Lomas, and S. Petro. 199 I . A study of the effccts of in-place pollutants on the bottom water. sediments and sedimentdwelling organism of the St. Mary's River at Sault Ste Marie 1985 and 1987.. Water Resources Branch. Ontario Ministry of the Environment.

Jackson. M.B. 1985. The dominant attached filamentous algae of Lake Huron: field ecology and biornonitoring potential. 1980. Aquatic Ecosystems Section. Water Resources Branch. Ontario Ministry of the Environment.

Jackson, M., J. Milne, H. Johnston, and R. Dennott. 1995- Assays of Hamilton Harbour sediments using Diporeia hoyi (Amphipoda) and Chironomus Plumosus (Diptera). Canadian Technical Report of Fisheries and Aquatic Sciences 2039. Fisheries and Oceans Canada. Burlington, Ontario. 20 pp.

J a e . R. and R-A. Hites. 1986. Anthropogenic. polyhalogenated, organic compounds in non-migratory fish from the Niagara River area and tributaries to Lake Ontario. f ournal of Great Lakes Research 12: 63 -7 1 .

Kaiser, K.L.E, M.E. Comba, H. Hunter, R.J. Maguire, RJ. Tkacz and R.F. Platford. 1985. Trace organic contaminants in the Detroit River. Journal of Great Lakes Research 11: 386-399.

Kauss, P.B. 1983. Studies of trace contaminants, nutrients, and bacteria levels in the Niagara River. Journal of Great Lakes Research 9: 249-273.

Kauss, P.B. and Y.S. Hamdy. 1985. Biological monitoring of organochlorine contaminants in the St. Clair and Detroit rivers using introduced clams, EIIiprio complurzutus. Journal of Great Lakes Research 1 1 : 247-263-

Kauss, P.B. and L.E. Post, 1987. Contaminant concentrations in bottom sediments of the Sir Adam Beck Power Reservoir and Niagara River bar dredgeate. Great Lakes Section, Water Resources Branch, Ontario Ministry of the Environment. 40 pp.

Kauss, P.B.. Y .S. Hamdy and B.S. Hamma. 1988. St. Lawrence River environmental investigations. Volume 1. Background: Assessment of water. sediment and biota in the Cornwall. Ontario and Massena, New York section of the St. Lawrence River, 1979- 1982. Great Lakes Section, Water Resources Branch, Ontario Ministry of the Environment. Toronto, Ontario. 157pp.

Konasewich, D., W. Traversy and H. Zar. 1978. Great Lakes water quality - status report on organic and heavy metal contaminants in the Lakes Erie, Michigan, Huron and Superior basins. International Joint Commission, Great Lakes Water Quality Board. Windsor, ON, Canada.

Kovats. Z.E. and J.J.H. Ciborowski. 1989. Aquatic insect adults as indicators of organochlorine contamination. Journal of Great Lakes Research 15: 623-634.

Krantzberg. G. 1 992. Collingwood Harbour mussel biomonitoring. 1 990 data report. Water Resources Branch, Ontario Ministry of the Environment. Toronto, Ontario.

Krantzberg, G. 1994. Spatial and temporal variability in metal bioavailability and toxicity of sediment from Hamilton Harbour, Lake Ontario. Environmental Toxicology and Chemistry 13: 1685- t 698.

Krantzberg, G. & E. Houghton. 1996. The remedial action plan that led to the cleanup and delisting of Collingwood Harbour as an area of concern. Journal of Great Lakes Research 22: 469-483.

Kuntz, K. W., 1984. Toxic contaminants in the Niagara River, 1975- 1982. Technical bulletin no. 1 34. Inland Waters Directorate. Ontario Region. Water Quality Branch, Environment Canada. Burlington, Ontario.

Kuntz, K.W. 1984. Annual loadings from the Niagara River to Lake Ontario for 1982 and 1 983. Water Quality Branch, Ontario Region, Environment Canada.

Kuntz, K.W. 1988. Recent trends in water quality of the Niagara River. Technical Bulletin No. 146. Inland Waters Directorate, Ontario Region, Water Quality Branch. Environment Canada. Burlington, Ontario.

Kuntz K.W. 1988. Contaminants in bottom sediments of the St. Lawrence River in June 1 975. Technical Bulletin No. 147. Inland Waters Directorate, Ontario Region. Water Qua1 i ty Branch. Environment Canada. Burlington, Ontario.

Kuntz, K. W. (Ed.). 1 990. Joint evaluation of upstream/downstrearn Niagara River monitoring data for the period April 1988 to March 1989. Final Report. The Niagara River data interpretation group and the River Monitoring Committee.

Kuntz, K. W. 1 992. Joint Evalution of upstream/downstream Niagara River monitoring data for the period April 1989 to March 1990. Water Quality Branch. Ontario Region, Environment Canada

Kuntz, K.W. and I.K. Tsanis. 1993. Trends in nutrients, major ions, physical water quality parameters and trace metals in the Niagara River from 1975 to 1989. Water Pollution Research Jownal of Canada 28:473-493

Kuntz,, K. W. and N.D. Warry. 1983. Chlorinated organic contaminants in water and suspended sediments of the lower Niagara River. Jownal of Great Lakes Research 9: 241 -248.

Kwaitkowski. R.E. (ed.). 1986. Water quality in selected Canadian river basins - St. Croix. St. Lawrence. Niagara, Souris and the Fraser Estuary. Scientific Series No. f SO. inland Waters Directorate, Water Quality Branch, Environment Canada- Ottawa, Ontario. 46 pp.

Limno-Tech Inc. 1985. Summary of the existing status of the upper Great Lakes connecting channels data. Upper Great Lakes connecting channels study.

Ling, H.. M. Diamond and D. Mackay. 1993. Application of the QWASI fugacity/ aquivalence model to assessing sources and fate of contaminants in Hamilton Harbour. Journal of Great Lakes Research 19: 582-602.

Luck. G. and M. Young. 1978. Bacteriological water quality of the St. Mary's River in 1973 and 1974. Microbiology Section. Laboratory Services Branch, Ontario Ministry of the Enviroment. 11 pp.

Lum, K.R. and K.L. Gammon. 1985. Geochemical availability of some trace and major elements in surficial sediments of the Detroit River and Western Lake Erie- Journal of Great Lakes Research 1 1: 328-3 3 8.

~Maguire, R.J., K.W. Kuntz and E.J. Hale. 1983. Chlorinated hydrocarbons in the surface microlayer of the Niagara River. Journal of Great Lakes Research 9: 28 1-286.

Marsalek, J.. B.J. Dutka, A.J. McCorquodale and I.K. Tsanis. 1996. Microbiological pollution in the Canadian upper Great Lakes co~ect ing channels. Water Science Technology 33: 349-356.

Martin. P.A., D.V. Weseloh, C.A. Bishop, K. Legierse, B. Braune and R.J. Norstrom. 1995. Organochlorine contaminants in avian wildlife of Sevem Sound. Water Quality Research Journal of Canada 30: 693-7 1 I.

McCrea, R.C ., J.D. Fischer and K. W. Kuntz 1 985. Distribution of organochlorine pesticides and PCB's between aqueous and suspended sediment phases in the lower Great Lakes region. Water Pollution Research Journal of Canada 20: 67-78.

McKee, P.M., D.R. Hart. A.J. BUR 1985. Benthological, chemical. radiological and chronological evalution of sediments in Port Hope Harbour. Environmental Protection Service, Ontario Region. Beak Consultants Limited. Mississauga. Ontario.

Memman. J.C. 1987. Trace organic contaminants in sediment of the international section of the St. Lawrence River. 198 1. Technical Bulletin No. 148. Iniand WaterslLands Directorate, Ontario Region, Water Quality Branch, Environment Canada. Burlington, Ontario. 1 0 pgs.

Mineau, P., G.A. Fox. R.I. Norstrom, D.V. Weseloh, D.J. Hallett. and J.A. Ellenton. 1984. Using the herring gull to monitor levels and effects of organochlorine contamination in the Canadian Great Lakes. Chapter 19. pp. 425-452. In: J.O. Nriagu and M.S. Simmons (eds.). Toxic contaminants in the Great Lakes. J. Wiley and Sons, New York, NY.

Ministry of Environment and Energy. 1 994. Water quality data Ontario Lakes and Streams, 1990. Vol. XXVI. Northeastern Region. Queen's Printer for Ontario. 214 pp.

Minns, C.K., D.A. Hurley and K.H. Nicholls (eds). 1 986. Project Quinte: Point-source phosphorous control and ecosystem response in the Bay of Quinte, Lake Ontario. Canadian Special Publications of Fisheries and Aquatic Sciences, No. 86. Department of Fisheries and Oceans. Ottawa, Ontario.

Minns. C.K., V. W. Cairns, R.G. Randall, A. Crowder and A. McLaughlin. 1993. Macrophyte surveys of littoral habitats in Great Lakes' Areas of Concern: The Bay of Quinte, Hamilton Harbour, and Severn Sound - 1988 to 199 1. Canadian Technical Report of Fisheries and Aquatic Sciences No. 1936. 60 pp. +.

Mudroch, A. and G.A. Duncan. 1986. Distribution of metals in different size fractions of sediment fiom the Niagara River. Journal of Great Lakes Research 12: 1 1 7- 1 26.

Niagara River Data Interpretation Group. 1 988. A joint evaluation of upstread downstream Niagara River monitoring data for the period April 1986 to March 198% Pp. 1-30 + appendix.

Oliver, B.G. and K. D. Nicol. 1984. Chlorinated contaminants in the Niagara River, 198 1 - 1993. The Science of the Total Environment 39: 57-70.

Oliver, B.G. and K.L.E. Kaiser. 1986. Chlorinated organics in nearshore waters and tributaries of the St. Clair River. Water Pollution Research Journal of Canada 21: 344-350.

Oliver. B.G. and C.W. Pugsley. 1986. Chlorinated contaminants in St. Clair River sediments. Water Pollution Research Journal of Canada 2 1 : 368-3 79.

Oliver, B.G. 1988. St. Clair river sediments. A level I1 report for the upper Great Lakes c o ~ e c t i n g channels study. ELI Eco Laboratories Incorporated, Rockwood, Ontario- 54pp.

Ontario Ministry of Environment and Energy. 1994. Water quality data: Ontario lakes and streams. 1990. Volume XXVI Southwestern region. Ontario Ministry of Environment and Energy. 332 pp.

Onuska, F. I. and S. Davies. 1990. Multivariate observations of the distribution of polychlorinated biphenyls in Enviromental compartments of two harbours. National Water Research Institute. Environment Canada. Vol. 90, no. 10 1.

Persaud. D.. T. Lomas, D. Boyd and S. Mathai. 1985. Historical development and quality of the Toronto waterfront sediments - Part I . Great Lakes Section. Water Resources Branch, Ontario Ministry of the Environment.

Persaud, D., T.D. Lomas, A. Hayton and S. Petro. 1989. The in-place pollutants program, volume IV, phase 1 : Data summary. Aquatic Biology Section, Water Resources Branch, Ontario Ministry of the Environment.

Pope. R. 1993. An environmental evaluation of the lower Welland River. Ontario Ministry of the Environment. Toronto, Ontario. 170 pp.

Pon Hope Harbour RAP Team. 1989. Port Hope Harbour remedial action plan. Stage 1 : Environmental conditions and problem de fmition. Environment Canada Ontario Ministry of the Environment.

Poulton. D.J. 1986. Hamilton Harbour trace contaminants, 1982- 1983 loadings to, and concentrations in the harbour. Second ediiton. Great Lakes Section, Water Resources Branch. Ontario Ministry of the Environment. 58pp.

Prankevicius, P.E. 1 987. Detroit Michigan area sediment survey - 1982. Great Lakes National Program Office, Report No. 87- 1 1. United States Environmental Protection Agency. 43 pp + Appendices.

Pugsley, C. W., P.D.N. Hebert, G.W. Wood, G. Brotea, and T. W. Obal. 1985. Distribution of contaminants in clams and sediments from the Huron-Erie corridor (I - PCBs and octachlorostyrene). Journal of Great Lakes Research 11: 275-289.

Pugsley. C. W.. P.D.N. Hebert and P.M. McQuarrie. 1988. Distribution of contaminants in clams and sediments h r n the Huron-Erie comdor. II - Lead and cadmium. Journal of Great Lakes Research 14: 356-368.

Quemerais. B.. K.R. Lwn and C. Lemiew. 1996. Concentrations and transport of trace metals in the St. Lawrence River. Aquatic Sciences 5%: 53-68.

Reynoldson. T.B.. R.C. Bailey. K.E. Day and R.H. Noms. 1 995. Biological guidelines for freshwater sediment based on Benthic Assessment of SedimenT (the BEAST) using a multivariate approach for predicting biological state. Australian Journal of Ecology 20: 198-2 19.

Richman. L. 1992. The Niagara River mussel and leech biomonitoring study. Water Resources Branch, Ontario Ministry of the Environment.

Severn Sound RAP Team. 1988 (revised 1989). Sevem Sound Remedial Action Plan, Part 1 : Environmental conditions and problem definition. Environment Ontario. Environment Canada, Ontario Ministry of Natural Resources (H uronia District) and Ontario Ministry of Agriculture and Food.

Sherman. R.K. 1995. Severn Sound Remedial Action Plan. Water Quality Research Journal of Canada. Special Issue. 30: 635-671.

Sloterdijk, H. 1985. Substances toxiques dans les Gdirnents du Lac Saint-Fran~ois (Fleuve Saint-Laurent, Quebec). Inland Waters Directorate, Quebec Region, Environment Canada. 79pp. + figures.

Smith. V.E., J.M. Spurr, J.C. FiUcins and J.J. Jones. 1985. Organochlorine contaminants of wintering ducks foraging on Detroit River sediments. Journal of Great Lakes Research 1 1 : 23 1 -246.

Southeast Michigan Council of Governments (SEMCOG). 1 978. Water quality in southeast Michigan: The River Rouge Basin. 12 1 pp.

Southeast Michigan Council of Governments (SEMCOG). 1988. Remedial action plan for the Rouge River Basin. Volume 3 - Chapters VI, VII, VIII, IX. Rouge River Executive Steering Committee and Rouge Basin Committee. pp. 63 1-854.

Southeast Michigan Council of Governments (SEMCOG). 1988. Remedial action plan for the Rouge River Basin. Volume 5 - Appendices A, B, C. 1, C .2, E. Rouge River Executive Steering Committee and Rouge Basin Committee. pp. 1229- 1517.

Spanish Harbour RAP Team. 1993. The Spanish Harbour Area of Concern: Environmental conditions and problem definition. Remedial action plan stage 1.

St. Clair River RAP Team. 199 1. The St. Clair River Area of Concern remedial action plan. stage 1 : Environmental conditions and problem definitions. Submission to the International Joint Commission. Ontario Ministry of the Environment (Detroit / St-Clair / St. Marys River Project). Sarnia. Ontario. and Michigan Department of Natural Resources (Surface Water Quality Division, Great Lakes Environmental Assessment Section), Lansing. MI.

St. Lawrence Rap Team. 1991. The St. Lawrence River Area of Concern. Remedial action plan for the Cornwall-Lake St-Francis Area. Stage 1 report: Environmentd conditions and problem definitions.

Struger, J., D.V. Weseloh, D.J. Hallett and P. Mineau. 1985. Organochlorine contaminants in herring gull eggs from the Detroit and Niagara Rivers and Saginaw Bay (1 978- 1982): Contaminant discriminants. Journal of Great Lakes Research 11: 223-230.

Suns, K., G.R. Craig, B. Crawford, G.A. Rees, H. Tosine and J. Osborne. 1983. Organochlorine contaminant residues in spottail shiners (Nofropis hudronitrs) fiom the Niagara River. Journal of Great Lakes Research 9: 335-340.

Suns. K., G. Hitchin and D. Toner. 199 1. Spatial and temporal trends of organochlorine contaminants in spottail shiners (Norropis hudsonius) from the Great Lakes and their connecting channels (1 975- 1988). Water Resources Branch. Ontario Ministry of the Environment.

Suns, K.R. and G.G. Hitchin. 1992. Species-specific differences in organochlorine accumulation in young-of-the-year spottail shiners, emerald shiners. and yellow perch. Journal of Great Lakes Research 18: 280-285.

The St. Marys River area of concern. 1992. Environmental conditions and problem definitions. Remedial action plan, Stage 1. Ontario Ministry of the Environment and Michigan Department of Natural Resources.

Theis, T.L., T.C. Young and J.V. DePinto. 1988. Factors affecting metal partitioning during resuspension of sediments f?om the Detroit River. Journal of Great Lakes Research 14: 2 16-226.

Thomas, R. L., and A. Mudroch. 1979. Small craft harbours - sediment survey. Lakes Ontario, Erie and Lake St. Clair, 1978. Report to Small Craft Harbours Ontario Region fiom the Great Lakes Biolimnology Laboratory.

Thornley, S. and Y. Hamdy. 1984. An assessment of the bottom fauna and sediments of the D e ~ o i t River. Ontario Ministry of the Environment.

Toronto Harbour RAP Team. 1990. Metropolitan Toronto and Region Area of Concern remedial action plan, stage 1 : Environmental conditions and problem definitions.

Trudel, L. t 99 1. Dioxin and fbrans in bottom sediments near the 47 Canadian pulp and paper mills using chlorine bleaching. Water Quality Branch. Inland Water Directorate. Environment Canada. Ottawa Ontario. 292

Varier. C.. M. S y lvestre and D. Planas. 1996. Persistence and fate of PCBs in sediments of the Saint Lawrence River. The Science of the Total Environment 192: 229- 244.

Weseloh. D.V.. P. Mineau and J. Struger. 1990. Geographical distribution of contaminants and productivity measures of herring gulls in the Great Lakes: Lake Erie and connecting channels. The Science of the Total Environment 91: 14 1 - 159.

Wong, P.T.S. Y.K. Chau J. Yaromich, P. Hodson and M. Whittle. 1988. Alkyllead contamination in the St- Lawrence River and St. Clair River ( 198 1 - 1987). Canadian Technical Report of Fisheries and Aquatic Sciences No. 1602.

APPENDIX C

CRITERIA FOR ASSIGNING CONTAMINANT SCORES

(Contaminant concentrations in the water column and in the sediment are

divided into ranges for assigning scores between I and 5 ) .

Table C. 1. Sconng cntena for metals in the water column.

CONTAMINANT UNITS 1 2 3 4 5

aluminum (Al) c19/L I nd c 1s 15-45 45 - 75 > 75

arsenlc (As) v ~ / L #nd c SO 50 - 100 100 - 200 >200

banum (Ba) IJ9/L ' nd c 1000 1000 - 2500 2500 - 5000 > 5000

calcium (Ca) ua/L .nd < 10 10 -20 20 - 30 > 30

cadmlum (Cd) M I L .nd 4 . 2 0.2 - 0.4 0.4 - 1.0 1.0

chromium (Cr) pg/L .nd < 2 2 - 50 50 - 100 > 100

copper (Cu) ug/L I nd c 1 1 - 5 5 -10 > 10

iron (Fe) IJglL . nd c 100 100-300 300-1000 >lo00

mercury (Hg) / vg/L i nd c 0.05 0.05 - 0.1 0.1 - 0.2 > 0.2

manganese (Mn) pS/L nd < 1 1 -11 11 -45 > 45

nickel (Ni) pq/L .nd < 25 25 - 65 65-110 > 110 1

lead (Pb) c19fL !nd ( 1 1 - 7 7 - 25 > 25

zlnc (Zn) ~ g f L nd c 30 30 - 50 50 - 100 > 100

Table C.2. Sconng cnteria for organlc contaminants in the water column.

CONTAMINANT UNITS 1 ; 2 ; 3 4 S

chlordane ngiL nd < 10 110-60 60 - 100 > 100

BHC (alpha + beta) ng/L nd ' < 1 j l - 1 0 10 - 100 > 100 1

BHC (gamma)lindane ngk nd ( 5 ' 5 - 1 0 I 0 - 1 M > 100

DDE ng/L n d . < I i l - 3 3-6 > 6 I

DDT ng/L nd c 1 11 - 3 .3-6 > 6

endosulfan ng/L nd < 1 11 - 3 3 - 20 > 20

9 I

heptachlor ng/L 1 nd J S I 11 - 5 15- 10 > 70 I

HCB ng/L .nd I < 1 ! 1 - 6 6 - 10 > 10 I I

total chlorobenzenes ng/L nd ( 5 5 -15 15-50 > 50 I

methoxychlor ngiL nd ' < 20 '20 -40 40 - 60 > 60

OCS ng/L nd c 0.01 0.01 - 0.1 0.1 - 1 > 1

PAH ng/L nd < 10 : 10 -30 30 - 100 > 100

PCB ng/L nd < 1 I1 -10 10 - 100 > 100

phenol ng/L nd < 1.000 ; 1,000 - 5.000 ; 5.000 - 10.000 > 10.000

Table C.3. Scoring cntefia for metals and nutrients In sediment

CONTAMINANT UNITS . 1 2 3 4 5

srlver (Ag) mglkg nd ~ 0 . 5 ' 0.5 - 1 .O 1 .O - 2.0 > 2.0

alummum (AI) mglkg nd <~O.OOO j 10.000 - 20.000 i 20.000 - 30.000 > 30.000

arsenic (As) mg/kg ' nd c3 13-8 ' 8 -33 > 33

banum (Ba) mg/kg nd c 20 20 - 40 4 0 - 60 > 60 I

calc~um (Ca) mglkg nd < 10.000 16.000 - 20.000 I 20,000 - 30.000 I > 30.000

cadm~um (Cd) mglkg nd c 1 r l - 6 i6 - 10 > 10

chromium C r ) malka nd < 25 125 - 75 75 - 110 > 110

cobalt (Co) mglkg nd c10 , l o - 2 5 > 50

iron (Fe) mglkg !

I

mercury (Hg) mgl kg nd c 0.3 : 0.3 - 1.0 1 .O - 2.0 > 2.0 f

manganese (Mn) mglkg ' nd c 300 '300 - 500 500 - 1100 > 1100

molybdenum (Mo) mg/kg nd c 4 . 4 - 8 8-12 > 12

nckel (Ni) mglkg nd < 20 20 - 50 50 - 75 > 75

lead (Pb) mglkg nd c40 :40 - 60 '60 - 100 > 100

zinc (Zn) mg/kg nd < I00 700-200 200 - 500 > 500

total phosphorus mglkg nd c 420 420 - 650 650 - 2000 > 2000

TKN mg/kg nd c 1000 1000 - 2000 2000 - 4800 > 4800

COD mgg nd < 40 40 - 60 60 - 80 > 80

loss on ianibon % 0 c 4 :4 - 8 8 - 12 > 12

total organic carbon mg/g nd c 1 ' 1 - 5 5 -10 > 10

Table C.4. Sconng cntena for organrc contammanu In sediment.

CONTAMINANT UNITS 1 2 3 4 S

afdnnjdieldrin pg/kg nd 0.6 0.6 - 2 . 2 - 8 0 > 80

chlordane ~ g k g nd < 0.5 0.5 - 7 ' 7 - 6 0 > 60

BHC (alpha + beta) pgkg nd < 5 5-10 '10- 100 100

BHC (qammallindane pglkg nd < 0.2 0.2 - 3 ' 3 - 1 0 > 10

DOE ~ g k g nd c 5 5 - 20 2 0 - 190 > 190

DDT pgkg nd < 7 7 - 20 20 - 120 > 120

endosulfan pglkg nd < 0.3 0.3 - 30 30 - 780 > 780

endnn uglkg nd ~ 0 . 5 0-5 - 3 3 - 1300 > 1300

HCB pglkg nd < 10 10 -20 20 - 240 > 240

total chlorobenzenes ~ g l k g nd < 350 350 - 3500 a 3500 - 35000 > 35000

rnethoxychlor $@kg nd < 5 5 - 50 ,SO - 500 > 500

OCS pqlkg nd c 1 1 - 5 5-10 > 10

oil vglkg nd (1.0 1.0-1.5 > 1.5 - 2.0 > 2.0

PAH ~ g k g nd c 2 2 - 1 0 10 - 110 > 110

PCB ~ g k g nd < 5 5 -10 10 - 1000 > 1000

phenol pglkg nd c 200 200 - 600 600 - 1000 > 1000

APPENDIX D

SEDIMENT CONTAMINANT SCORES FOR 1995 SURVEY MICROSITES

Scores between 1 (least severe) and 5 (most severe) are assigned based on the criteria outlined in tables C.3 and C.4. Where no scores have been assigned, data was not available in the literature. For each microsite. the sum of all scores (TOTAL). the number of scores assigned (NUMBER), and the calculated index of sediment contamination severity (MDEX) are also given.

Table 0. f . Seventy of sediment contam~nant concentrations at each sampled mcroslte.

. ..

DETROIT 1 0 . 2 5 ' 3 1 2 2 2 2 2 2 : 2 2 2 ' 21 DETROIT 11 2 2 4 > 2 '

GETROlT tz 2 2 4 5 5 1 4 3 5 5 3 4 - 4 5 5 5 1 DETROIT I j 2 2 4 5 5 4 5 3 5 5 3 ' 4 q 4 5 5 5 1 DETROIT 14 2 5 4 3 4 3 4 2 5 3 5 1 3 DETROIT 15 2 2 2 2 3 3 2 2 3 DETROIT 16 2 2 DETROIT 17 4 4 DETROIT ' 18, 3 4 5 3 . 4 5 4 4 , 4 5 i 44

DETROIT 19, 2 5 4 3 4 3 2 : 4 5 : 51 DETROIT 20 DETROIT 21 2 2 5 51 4 5 2 5 , 5 41 4 . 3 5 5 1 5 . DEfROlT 22 2 2 5 5 5 5 3 5 5 5 4 3 5 5 5 DETROIT 23 4 3 4 3 4 3 5 . DETROIT 24 4 5 4 3 3 3 2 3 4 2 3 2 2 DETROIT 25 3 3 3 DETROIT 26 2 4 3 ' 5 3 31 3 ' DETROIT 27 2 3 4 4 3 3 3 3 4 . DETROIT 28 4 2 2 l

DETROIT I 291 5 51 51 3: 31 31 3 ! 31 21 41 2 31 31 21 HAMILTON I 1 4 3 5 : 3 4 5 21 3 51 51 HAMILTON' 2 3 3 5 1 3 3 5 2 : 3 3 i 41 HAMILTON I 3 4 3 5 1 3 4 ' 5 2 ' 3 5 i 5 1 HAMILTON 4 5 4 3 5 3 4 5 2 ' 5 ' 4 5 ' 51 HAMILTON1 S 3 5 , 3 4 5 2 3 5 5 HAMILTON 6 4 2 5 1 3 5 4 2 ' 2 5 5 1 HAMILTON 8 4 3 5 3 5 5 2 4 5 5 HAMILTON 9 5 3 5 3 5 5 2 4 5 . S HAMILTON 10 4 3 5 3 4 5 2 4 5 5 HAMILTON 12 4 2 3 3 2 4 2 2 4 2 3 4

NMSARA 1 4 2 2 2 N IAGARA 2 3 3 5 5 3 2 2 2 3 2 2 2 3 NlAGARA 3 3 2 2 2 2 2 2 2 2 NiAGARA 4 4 3 5 3 2 3 2 4 2 3 2 3 Y lAGARA 5 4 2 2 2 N IAGARA 6 4 2 2 2 2 NlAGARA 7 3 2 2 2 2 2 2 2 NIAGARA 8 4 4 3 5 2 2 3 2 2 2 2 3 2 2 NlAGARA 9 4 2 2 2 NIAGARA 10 d 2 2 2 - NLAGARA 11 4 3 3 5 2 2 2 3 3 2 2 4 4 NlAGARA 12 4 2 2 2 NIAGARA 13 4 2 2 2 NIAGARA 14 4 2 2 2 NIAGARA 15 3 2 2 2 2 2 2 2

LZ NU3A3S

Z Z C V Z V Z E Z C C 9 Z NU3n3S Z Z Z E Z E Z E Z Z E S Z N H 3 N S Z 2 - -- -- - -- - -- --- - - 2 z 2 - - - - - - - - - VZ NU3A3S - A- - Z Z Z E Z E Z E 2 Z Z CZ NM3A3S -- Z Z - - - - - - z Z "t - -- ZZ ---- ---- - -- NH3-S Z Z Z C Z Z f Z Z ? O? Nt13A3S - - -

Z Z Z Z Z E Z Z Z Z E Z 6 1 N U 3 N S

Z Z Z Z Z C Z Z Z Z C E Z 8 ; NU3A3S

f E E E E E Z E C 7 L N83A3S C 2 ' E Z E C E Z E: E E L N U 3 N S Z E f C Z C E E 2 Z C Z 1 ~ 8 3 - y C Z C Z S Z i Z E L L ~ ~ 3 ~ 3 s f 2 Z Z E E 0 1 Nti3A3S E V E Z E f E E 6 NU3A3S

-. - C Z I Z 2 C E 8 N U 3 N S

Z Z Z Z Z Z Z 2 Z Z L Nk43NS

*al!somu ~ d u e s toea ae s u o ! ~ e ~ ~ ~ u o = , aueu!wewm ~ ~ ~ ! p a s lo bua~as a qqel

: Z Z Z ' Z t 61 H I M 3 I S

Z 2 Z E Z Z Z Z Z C Z 81 U l M 3 I S Z Z Z Z Z Z Z Z Z Z Z Li H l W 3 1s

Z Z Z Z Z 9L B l v l 3 I S 2 - - - --- E Z Z Z SL H I M 3 I S

_ _ _ F _ _ - L _ _ _ _ -_-- - -- - - - - - - - 2 1 Z Z Z Z Z Z C 7 P+ H I M 3 I S

- EL B l M 3 I S

2 V Z Z Z Z Z t - H I M 3 l S z z z z v z z z z z z z c ~r 8lW3 IS 2 z Z Z Z Z Z Z L E Z 0k tllM3 I S

0 V Z Z Z 1 6 H I M 3 I S v Z 8 tllM3 I S

Z Z Z Z Z Z b ~ 1 ~ 3 IS

Z ' 2 Z Z V Z Z Z Z E 9 8lW3 I S

' I V Z Z Z Z S H I M 3 I S 2 v Z Z Z Z v tllvl3 -- IS

Z 9 2 2 2 Z t H I M 3 I S Z I Z Z S Z Z Z Z Z E 2 1 M l M 3 I S Z Z C Z Z C t 12 HSlNVdS

Z Z E Z Z Z S Z ' Z E Z OZ HSlNVdS Z Z * Z Z E S Z -- 0 1 HSlNVdS Z Z S Z E Z Z E E E Z V Z E L L HSINV~S Z !Z Z Z E C 9 1 HSlNVdS

* E E S I HSlNVdS iZ i Z S E E t t V L HSlNVdS

I 2 It ? ' 2 Z C 1 i It ZL HSlNVdS C L 1 HSINVdS 6 0 L HSlNVdS t 6 HSlNVdS E B HSlNVdS E L HSlNWdS E 9 HSlNVdS

2 . Z V C E O t 5 HSINVdS E 1 HSINV~S

E C HSlNVdS E Z HSlNVdS

1 2 I Z E Z Z Z Z Z .Z 82 Z L HSlNVdS

-- Z 9E NU3A3S SC N t f 3 N S

Z 'Z Z Z Z Z Z Z Z 2 K NM3A3S E E Ntl3A3S

Table D. 1. Severity of sediment contaminant concentrations at each sampled microsite.

ST CLAlR ! 21 2 3 . 3 2 . 2 2 2 3 j 21 21 21 ST. CLAIR ; 22 ! ! 2 5 2 2 2 3 ! 4 1 3 21 21 ST. CLAIR I 24 1 1 2 2 2 2 i i 2 1 I ST CLAIR 25 3 1 1 3 . 2 2 2 3 2! 2 2 i 2 /

ST. LAWR I 3 2 3 j 1 2 3 . 4 2 3 f j 2 31 41

ST LAWR I 4 2 1 2 3 3 3 31 31 3 31 21 ST LAWR 5 3 1 2 3 3 2 21 I

1 - 2 2 i 41 ST LAWR : 6 , 3 1 2 3 3 2 2 1 ; 2 2 / 4: ST LAW 7 3 1 2 34 3 2 3 1 1 ST LAWR ; 8 2 1 i 2 3 3 3 21 4 / ST LAWR 1 9 2 I I 2 1 3 4 4 21 41 3 41 41

ST LAWR ' 10 -- 2 1 2 3 ' 2 2 : 21 i 2 21 2 ! ST. UWR 11 2 2 1 1 2 2 2 2 2 1 ; 2 2 ; 2i

ST. LAWR i 14 2 1 1 2 3 1 Z 2 21 31 3 31 21

STMARYS / 2 2 i 2 2 2 2 2 2 1 2 i 2 2 ! 21 STMARYS 3 2 2 2 2 2 1 21 2 21 21

ST LAWR / 15 3 1 ST LAWR j 16 3 1 ST. LAWR 1 17 3 , 1 ST. LAWR 1 18 2

ST MARYS ' 4 2 . I j 2 2 2 2 2 21 2 j 2 21 2; ST.MARYS ' 5 2 3 1 1 2 3 2 2 3 2 i 3 ; 2 21 21

j 2 3 : r 3 21 31 3 5 j 4 1

- . . -

TORONTO ! 3 3 i 1 3 4 - 4 4 3 ; 37 51 4 ) TORONTO ; 4 ' 3 1 3 4 ; 2 4 21 31 2 21 41

2 3 3 2 . 31 1 2 2 41

ST. LAWR / 19 2 3 I i 2 3 ! 3 2 . 21 2 2j 21

TORONTO ! 8 3 1 1 3 4 . 4 4 3 1 3 1 TORONTO 1 9 3 1 1 3 4 2 4 21 31

2 3 3 2 3 1 1 2 2 4 j 2 3 3 2 3 1 1 2 2j 41

ST. LAWR ! 20 3 , [ 2 3 3 2 . 41 2 2 4 ST. LAW 1 21 3 i 2 3 3 2 41 I 2 2 . ST.MARYS ! I 2 2 3 ' 3 2 2 1 2 1 2 2

, - - - , - , J

TORONTO j 10 3 1 / 3 4 , 2 4 2 ! 31

31

TORONTO j 5 3 , [ TORONTO i 6 3 i

3 ' 4 : 2 4 , 21 31 2 21 4 3 4 , 2 4 3 ! 31 2 21 4

Table 0 I. Seventy of sediment contamrnant concentrations at each sampled mcrosrte.

AX SITE ALDRtN I CHLORDANE BHC .DOE DOT ENOOSULFAN ENDRIN I HEPTACHLOR PCB TC8 -. - . -

B QUlNlE 2 B QUINTE 3

B QUINTE 6 0 QUINTE 7

6 QUINT€ 8 0 QUINTE 9 B OUlNTE 10 B QUINT€ 11

B QUINTE 12 BQUlNTE 13

- -

8 QUlNTE 14

B QUINTE 15

B QUINTE 16

B QUlNTE 17

B QULNTE 18

- -. --- B u1NE 22 BQUlNTE 24 B QUINTE 25 8 QUINT€ 26 8 QUINTE 27 B QUINTE 28 --- CQUINTE 29 BQUlNTE 30

- - -

8 QUINTE 31

8 QUINTE 32

- - - - - . - -- - --

8 QUINTE M 8 QUINT€ 35

COLLING 2 2 2 2 2 2 --- 2 2 COLLING 2 2 2 2 2 2 2 2 2 COtLlNG 3 2 2 2 2 2 2 2 2 DETROIT 1 4 I I 2 DETROIT -

L 4 4 4 2 2 DETROIT 3 1

DETROIT .. ----- - - - - - - DETROIT 5 1 2 DETROIT 6 1 1 1 t

OETROlT - 3 DETROIT 8 - 3 DETROIT 9 1 1 1 2

Table D. 1. Seventy of sediment contaminant concentrations at each sampled mcr0sRe.

AOC SITE ALORlN I CHLORDANE '8HC DM DOT ENOOSULFAN ENDRIN I HEPTACnLOR HC8 IYCB

DETROIT 10 I

DETROIT 11 1

DETROIT 12 4 I 4 5 I 3 4 I 4 21 DEfROlT 13 4 I 4 5 1 3 4 1 4 21 OET'Rorr 14 31 2 3 41 21 4

D E T R O ~ IS 4 3 3 I 1 1

DETROIT 16

DETROIT 18 4 I 4 I 4 4i 4

O r n O f T 21 4 . 5 ; 3 ' 4 1

D m O l f 22 4 5 1 4 41 2 DETROIT 23 4

- -- - - -- -- -

DETROIT 25 4 I 3 DETROIT I 26 1 I 1 1 1 I 1

DETROIT 27 4 3 31 31 2 DEiftOlT I 28 I

OETROfl 1 2911 I 3 1 ! v

T

HAMILTON I 1 I 1 11 1 !

HAMILTON 1 2 4 I 1 1 ' 3 ' 31 1 I i 1 t i 7

HAMILTON I 3 I 1 1 I 1

HAMILTON 1 4 1 11 1

HAMILTON 5 1 1 I 1

HAMILTON ' 6 1 1 f 1

HAMILTON 8 1 1 1

HAMILTON1 9 1 ; 1 1 48 1 , I 1 I 1 11

HAMILTON 10 1 1 . 1 HAMILTON 12 1 1 1 1

N IAGARA 1

N lAGARA 2 3 3 ' NlAGARA 3 2 2 2 2 2 2 2 I 2 I N LAGARA 4 2 2 NlAGARA 5

NlAGARA 9 NIAGARA '0

NlAGARA 11 2 ; 2 2 2 3 ; 2 2 I 2 . NIAGARA 12 NIAGARA 13

NlAGARA 14

Table D.1. Seventy of sediment contaminant mantrations at each sampled microsite.

AOC SITE MMUN I CHLORDM 'BHC :DOE ! W T ENOOSULFAN. ENORIN I HEPTACHLOR . nCB fTC8 ;

NIAGARA i 16: 1 i

NIAGARA , 21 1 I 1 1 2 2 ; 1 1 ; 1 I !

NUGARA / 22' 1 i 1 ' 1 ' 2 ' 2 ; 2 f

ROUGE I 1 1 . 2 ROUGE ! 2 I

ROUGE 3 1 ' ! ROUGE 1 4 I

1

ROUGE 1 511 i I 3 ROUGE 1 61. SEVERN 1 1 i i I

SNERN 7 SEVERN ' 8 " I

1

SEVERN , 9 SEVERN : 10 I I

SEVERN 11 1 % 3 3 ' i

SEMRN 12

SEVERN 13 '

SEVERN I 14 SEVERN 15

SEWERN 16 SEVERN 17

SEVEUN 1 8 2 2 2 2

SEVERN 2 0 2 . 2 2 2 SEVERN 22 SEVERN 23

SNERN 24 SWERN j 25

26 SNERN SNERN I 27 SNERN 1 28. I

Table 0 . 1 . Severity of sediment contaminant comentrations at each sampffl microsite.

AOC SITE ALORlN I CHLORDANE 6HC DOT ENOOSUVAN ENDRIN t HEPTACHLOR HC8 KC8 1

S N E R N 1 2911 1 I 8

-

S E M R N ' 30' S M R N 31 I

S f M R N 32 , SEVERN 33 1

S N E R N I 34 2 3 2 2 S E M R N 35' I

S&RN 36 SPANISH 1 2 1 2 ' 21 2 1 2 : '

SPANISH ' 2 SPANISH 30 SPANISH i 4 ;.

SPANISH f 5.1 I 1

SPANISH : 6 SPANISH 1 7 '

SPANISH i 1 5 : ~ , !

SPANISH 8 SPANISH 1 91

SPANISH 1 10 ,

I

SPANISH 161i 2 1 2 : 21 2 1 2 i I SPANISH f 17 2 2 1 3 2 % 2 . t! 3 . 2 i 21 21

SPANISH

SPANISH i 18 I 2 ; 8 f

SPANISH i 201' r l 1 21 1

SPANISH 21 2 : ST. CLAIR ! 1 : 4 l 3 2 ' 2 21 2 : 4 I 3 ' 21 ST. CLAIR . 3 5 I

11"

ST. CLAlR 4 5 i ST. C U l R 5 5 i

I

ST. CLAtR 1 6 5 , ST C U l R 7 4 t

I ! 1

I

SPANISH

ST. ClAIR ' 10 4 ! 3 2 2 2 : 2 3 ' 3 3 ' ST. CLAIR ' 11 3 5 i ST CLAlR 12 5 i

SPANISH I 1411 I 1

1211

ST CLAlR 13 4 I

ST CLAIR 14 5 1

i

ST CLAlR 15 5 I ST CLAIR 16 5 1 ST CLAlR ' 17 2 ! ST CLAIR ' 78 3 1 3 2 2 2 ' 2 3 1 3 41

ST CLAlR 191 I 4 1

Table D. 1. Seventy of sediment contaminant concentrations at eacf~ simpled mrcrosite.

--

AOC 1 ~ 1 ~ ~ ALORIN I CHLOROANE BnC DOE 00T 5NOOSULFAN : ENORIN 1 HEPTACHLOR nC8 7CB I

ST CLAlR , 20 I I I I 1 4 1

ST. CUlR 21 3 1 31 2 2 2; 2 3 1 3 4 1 -- -- -

ST CLAlR 22 4 I

ST C U l R 24 4 I

ST CLAlR 25 ST LAWR 1 I I 4 1 3 2 1 1 1 I 4 2 ST LAWR ' 2 1 1 3 3 2 3 1 1 ' 1 l 1 3' ST LAWR , 3 1 4 4 2 2 1 1 1 i 1 3

ST. U W R j 4 1 1 1 , 1 1 , 11 t 11 1 l !

S T - L A W I 5 1 I 1 1 1 I ! 1 11 1 ' 1

ST. L A W , 6 I ! 1 1 1 1 1 1 11 1 I !

ST. UWR ! 7 1 I 1 1 1 l i I 11 1 I !

--- -

ST LAWR , 9 1 1 1 1 1 1 1 1 ' 1 i 1 1 '

ST U W R ' 10 l ! 1 1 1 11 1 11 1 1 '

ST L A W ' 1 7 1 i 1 3 2 1 ' 1 1 ' 1 1 '

S T U W R 12 2 1 3' 2 2 : 21 1 11 2 2! STLAWR 13 I ! 1 1 1 I ! 1 1 I 1 1 '

--

ST. UWR ! 17 3 1 3 2 3 21 2 . 2 i 3 . I 2- ST. CAWR 1 18 1 1 1 . 1 . 1 1 l i 1 ' 1 1 1 : 11

ST LAWR i 19 I ! 1 , 1 1 l ! 1 ' 11 1 1 ;

ST LAWR , 20 1 I 1 1 1 1 1 1 ; 1 1

ST L A W ' 21 I ! 1 1 1 1 1 1 ' 11 1 1 1

STMARYS 1

STMARYS I 2 STMARYS 3 ,

ST MARYS , 4

STMARYS ' 5 3 1 3 , 2 2 21 3 . 3 1 3 2 : TORONTO ' 1 2 TORONTO 1 3 2 TORONTO 4 2 TORONTO 5 2 TORONTO 6 2 TORONTO 8 2 TORONTO 9 2 TORONTO 10 2

Table 0. I. Sewenty of sediment contaminant conantrabons at each sampled microsite.

AOC SITE, LlNOANE MIREX OIL i PAH PCB .PHENOL TCDO : TOTAL NUMBER : INDEX 1

B.QUINT€: 2 " 4 42 ' 151 0.56: 8.QUINTE 3 : . 4 . 26 v 10 0.52: 8. QUINTE 4 4 4 t I 0.8

6. QUINTE ' 5 4 : 4 1 0.8 6. QUlNTE 6 4 4 , 1 0 .8 : 0. QUINTE , 7 4 8 2 0.8. 8. QUINT€ ' 8 ' 4 ' 4 1 0.8 i

6. QUIKtE ; 9 , 4 4 1 0.8 8. QUINTE j 10 : ' 4 n 4 , 1 0.8; 6. QUINTE : 11 4 : 4 1 0.81 8. QUINTE I 12 4 . 4 : 7 0-8' 6.QUINTE i 13 . . 4 ; 9 . 2 0.9: 6 QUINTE 1 14 ' 4 . 23 ' 9 0.511 1 B. QUINTE 15 . 4 9 4 1 0.8: B QUINTE I 16: 4 s 4 1 1 0.8 i 8. QUll 8. QUll 6. QUll 8. QUll 8. QUll 8 QUll 8. QUll 6. QUlf 6. QUlf 6 . QUII 6. QUll 8 QUINTE 29 4 41 13 0.6308 8 QUINT€ ' 30 4 4 a 1 0.8 r

8 QUINT€ 31 4 34 10 0.68. 8. QUINTE 32 4 42 13 0.6462 8. QUINT€ 33 4 36 10 0.72' 6. QUINTE 341 4 , 4 1 0.8: 8 QUINTE 35 4 4 1 0.8' COLLlNG 1 2 1 3 3 48 23 0.4774 COLLING 2 2 1 3 1 3 48 23 0.4174, COLLJNG ' 3 2 1 3 3 48 ' 23 0.4774 DETROIT 1 1 3 i 4 35 16 0.4375 DETROIT 2 1 2 2 4 2 so 19 0.5263 DETROIT 3 1 21 4 5 1 18 0 5667 DETROIT 4 t 4 2 U 16 055 DETROIT 5 1 1 4 15 8 0.375 DETROIT 6 1 21 4 2 33 17 0.3882 DETROIT 7 t 4 2 19 7 0 5429 DETROIT 8 t 1 3 26 13 0.4 DETROIT 9 1 21 4 2 32 17 0 3765

Tabte 0.1. Seventy of sediment contaminant concentrations at each sampled microsite.

AOC SITE LINDANE MI- OIL ( P M I PCB PHENOL TCOO i TOTAL NUMBER I N E X ,

DETROn t 10' 1 ' 1 s 4 ; 2 37' 16 I 0.4625 4

D m O l T t 1 1 : 4 a 16 7 0.4571 DETROIT , 12 4 1 51 41 5 111 21 0 7929 DETROIT 13 4 S t 4 5 111 28 i 0.7929 DETROIT 14 1 4 1 4 , 2 72 22, 0.6545 DETROIT 15 1 4 37 151 04933 DETROIY ' 16. 1 , 21 4 : 2 13l 6 ! 0.4333 I

DETROIT 17 1 , 4 4 2 19 I 6 ,0.6333

DETROIT 20 1 21 4 ' 5 ; 2 14 5 1 0.56. DETFIOIT 21 1 41 5 : 3 93: 24 0.775. DETROIT 22 1 5 1 4 : s 2 ' 100' 2s r 0.8 DETROIT ' 23 1 4 ' 4 391 11 0.7091 DETROIT 241 1 31 41 488 16; 0.61 DETROIT 25 1 3 4 2 26 9 0.5778 DETROIT i 26 1 1 1 1 4 i 33 i 14 i 0.4714 I DETROIT 27 1 2 ' 4 2 53. 18 * 0.5809 DETROIT I 2brI 1 : 4 1 13; 5 i 0.52 1

r m ~ I a11 I 1 1 I i 4 1 ! I ri 17 I 0.6353 I HAMILTON I 1 1 ! 2 : 4 ; 49 1 76 ' 0.6125 1

HAMILTON 1 2 1 : 2 ' 4 ' 57 221 0 5182- HAMILTON 1 3 ' 1 i 2 ; 41 49 1 16 i 0.6125 : HAMILTON i 4 % 1 2 4 . 60: 18'06667 HAMILTON 1 5 1 , 2 : 4 45. 15, 0.6 HAMILTON 1 6 1 3I 2 ' 4 . 50; 17 ' 0.5682 . HAMILTON 8 1 3 1 2 4 54 17 0.6353 HAMILTON ! 9 1 31 41 4 66 : 23 0.5739 1

HAMILTON 10 1 3 ! 2 4 53 17 0.6235 - -

HAMILTON t2 1 3 1 2 4 49 20 0.49 NlAGARA . I 10 4 0.5 NIAGARA 2 43 15 0.5733 NIAGARA 3 3 2 3 43 20 0.43 NIAGARA 4 40 14 0.5714 NtAGARA 5 10 4 0 5

NlAGARA 8 3 2 4 69 25 0.552 NIAGARA 9 10 4 0.5 NlAGARA 10 10 4 0 5 NlAGARA 11 3 2 3 U 24 0 5333 NlAGARA 12 101 4 0 5

-- --

NIAGARA 15 1 I 4 37 20 0.37

Table D f Seventy of sed~ment contammant concentratmns at each sampled mnroslte.

AOC SITE LINOANE MlRW OIL, PAH PC8 PHENOL TCOO TOTAL NUMBER INEX

NIAGARA 16 10 r 0 5 NUGARA 17 10 4 0 5 NUGARA 18 10 4 0 5 NlAGARA 19 10 4 0 5 - NUGARA 20 10 4 05 NlAGARA 21 3 1 32 ! 9 0 3368 NlAGARA 22 31 3 4 t 59 25 0472 NlAGARA 23 2 5 1 21 0 4857 NUGARA 24 5 2 4 70 23 0-7 NlAGARA 25 t 3 4 80 24 06667 NlAGARA 26 2 52 20 0 52 NUGARA 27 3 2 4 64 24 0 5333 ROUGE 1 4 ; 5 4 70 20 3.7

- - - - -

ROUGE 2 3 4 59 :8 07667 ROUGE 3 3 i 4 . 26 : 1 0.6545 ROUGE 4 3 . s 50 r 3 o 7692

ROUGE 5 2 1 2 58 n 19.0.810s.

ROUGE 5 3 ! 4 36 11 0.6545

SEMRN j t 8 ! I 32 I 1 i o . m a I SEVERN 3 4 37 12. 0 6167 SEVERN 4 24 8 0 6 -- -

SEVERN 5 4 26 9 0 5778 SEVERN 6 17 7 0 4857 S N E R N - 2 0 TO 0 4 SEVERN 8 --- - ---- - - - 5 0 .5 . ---- SEVERN 1 24 3 36

SEVERN r o 1s 6 0.5 SEWERN * t 6 36 ! 3 0 5538 ---- P

SEVERN : 2 29 ' 1 (3 5273 SEVERN ! 3 27 10 3.54 SNERN o 26 9 0 5778 -- - - SNERN ' 5 26 0 0 5778 - SEVERN '5 - - -. - - --- - -

26 .- . .- 9 0 5778

SEVERN -a

SEVERN 2 5 26 :I 0 4127 SEVERN f 5 30 * 1 0 5455

.-

SEVERN 27 - -- 0 S N E R N i 9 3

Table 0.1 Seventy of sed~rnent contarn~nant concentrations at each sampled m l c m u t e .

AOC SITE LINOANE MIREX OIL i PAH PC8 P H E W TCDO TOTAL NUMOER - IN=

SEVERN 29 ' 0 SEVERN 30 0 S E M R N 3 1 0 SEVERN 32 0 S M R N 3 3 0 SEVERN 34 2 4 35 1 6 0 4375 S E M R N 35 0 S N E R N 36 2 ! 0 4 SPANISH 1 2 4 39 18 0.4333 SPANISH 2 3 1 9 6

SPANISH 3 3 1 06 SPANISH 4 3 1 0.6

-- - - -

SPANISH 5 22 7 0 6286 SPANISH 6 3 3 6

SPANISH - I 3 1 0 6

SPANISH 0 3 t 3 6 SPANISH 9 . . 3 ? 0.6 SPANISH 10 3 1 9.6 SPMIS~ 11 3 t 0 6 SPANISH 1211 I 19 1 7 0.54291 SPANJSH 14 22 7 0 6286 SPANISH 15 6 2 0 6 SPANISH 16 2 4 30 13 04615 SPANISH 17 2 2 4 66 26 o SO^

SPANISH 7 0 4 28 10 3 56 SPANISH 20 - - - - - - - - - - 4 38 16 0475

SPANISH 21 4 24 3 0 5333

ST CWIR T 3 2 2 4 6 1 24 0 SO83 ST CLAlR - - -- - 2 4 2 5 -- P

4 0 5556 ST CMR J 2 4 2 5 4 0 5556 ST ClA lR 5 2 ' 4 25 9 0 5556 ST CLAIR 5 2 4 36 74 0 5143

ST CLAlR - --- 2 4 22 9 0 4889

ST CLAtR 3 ' 0 3 0 6667 -- -- -- - -- 4 -- ST CLPlR 9 2 4 25 9 0 5556 ST ClAlR 70 2 2 2 4 57 24 0 475 - -- - - - - ST CLAlR - 1 3 4 a* '7 0 5176 - - - - - ------- ST C l A R - 2 - a 25 2 3 5556 - - - - - -- ------- ------ ST CLAlR ' 3 - - - - - - - - .- - - 4 8 2 3 8 S T C W l R ' 3

- L - - -- 4 - - - -- 2 2 - ' 3 34023

ST CLAIR ' 5 2 4 24 3 0 5333 ST CLAlR 16 2 4 24 9 0 5333

Table 0.1 Seventy of sediment mtammant concentratmns at each sarnpkd mrcrosite.

AQC SITE CINOANE MIREX OIL PAH PC8 PHENOC TCDO TOTAL NUMBER INDEX

ST CUIR 20 2 ' 3 23 9 o s r i i ST CUlR 21 3 2 2 ' 4 60 24 057

S T CUlR 22 2 3 361 13 05538

ST CLAlR 24 2 4 22 9 0-9

ST C U l R 25 2 1 26 12 0 4333

ST LAWR , 1 1 3 4 5 58 24 0 4833 ST LAWR 2 4 1 3 : 4 1 5 6 1 24 1 0.5083 ST LAWR 3 4 1 3 4 5 64 24 0 5333 Sf LAM 4 1 1 5 1 4 2 4 53 251 0.4241

ST L A W 5 1 1 3 4 41 22 0 3727

ST LAWR 6 1 1 3 4 41 22 0 3727

ST LAWR 7 I 1 3 4 42 22 03818

ST L A M 8 7 7 5 5 3 52 24 0 4333

ST LAWR 9 1 1 5 5 3 56 24 0 4667

STLAWR !O 1 1 31 4 37 22 03364 S T L A W 1 1 1 1 2 3 39 23 0 3391

-- - -- --

STLAWR 12 1 1 3 i 5 47 9 22 ' 0.4273 1

STLAW? 13 1 2 3 . 4 38 22 0 3455

ST UWU , 14 1 2 5 2 2 S 3 6 1 25 04881 ST L A M I 151' 7 ' 1 1 31 4 I 4Z ! 221 0.38181

ST L~ - 18 1 I S 4 3 n 241 0.451 t S T L A W R 19 - 1 2 4 4 1 23 0 3565

ST LAWR 20 I 1 3 4 43 22 03909 STLAWR 21 -- - - - 1 1 3 4 43 22 0 3909

.-

STMARYS 1 - C d J 28 :r 0 5429

STMARYS 2 2 4 1 29 14 04143

STMARYS 5 3 2 3 3 4 Z 58 27 0.5037 TORONTO 4 32 :I 05818 TORONTO 3 d 39 1 t 0 7091

-- --- 'ORONTO 4 - - - - - - - 4 - - 35 72 0 5833 TORONTO 5 4 3 5 i 2 0 5 8 i

WATER CONTAMINANT SCORES FOR 1995 SURVEY MICROSITES

Scores between I (least severe) and 5 (most severe) are assigned based on the criteria outlined in tables C . I and C.2. Where no scores have k e n assigned, dam was not available in the literature. For each microsite. the sum of all scores (TOTAL). the number of scores assigned (NUMBER). and the calculated index of water column contamination severity (INDEX) are also given.

172 Table E. 1. Severity of water column contaminant concentrations at each sampled mlcrosite.

AOC S l E 1 AL AS1 BA CA CDI CRI CU FE; HG MNI NII PB ZNI

8. QUINTE 9 ! 0

8. QUINTE 10 !

8 QUlNTE 19 : B. QUINT€ 20 I 6. QUINT€ ! 21

T

I 1 I i 8. QUINTE 22 ! I ! I

8. QUlNTE 24 . ! I -

8 QUlNTE 25 1

8QUlNTE 261 : 2 2 : 3 21

6. QUINTE 29 5 3 i 2 2 3 2 8. QUlNTE 30 i I

B QUI- 31 ' 6 QUINTE 32 .

COILING 1 '

COLLING 2 r COLLING 3 . DETROIT 1 , 4

DETROIT 2 DETROIT 3 1 4

DETROIT d ! 2 : 3 2 DETROIT 5 I 3 DETROIT 6 1 I

DETROIT 7 1 I 5 I

DETROIT 8 ' 3 DETROIT 9 1 I !

173 Table E. 1. Seventy of water column contaminant concentrations at each sampled mmosite.

NlAGARA 6 1 5 21 5 31 5 21 2 NlAGARA 7 2 . 5 31 2 , 2 2

-

NlAGARA 8 ' 5 2 2 5 1 ' 5 41 2 21 3 2 NIAGARA 9 , 5 21 f 38 5 2 , 2 N~AGARA ro 1 5 21 5 3 1 5 2 1 2 NlAGARA 11 5 1 2 5 5 1 4 4 1 2 2 , 2 2 NlAGARA 12 I 2 1 5 31 2 i 2 2 NlAGARA 13 I 5 2! 5 21 3 41 2 4 1 21 2 2 N IAGARA 14 ' 2 : 5 3 ' 3! 2 ' 2 2 NIAGARA 15 I 2 1 5 31 I 2 1 2 2

DETROIT 10 I

DETROIT 11 2 ' 4 3 DETROIT 12 DETROIT 13 OETROIT 14 3 OETROlT 15 DETROIT 16 I

OETROIT 17 . DETROIT 18 1 4 I

DETROIT 19 I

OEfROlT 20 DETROIT 2 1

DETROIT 22 DETROIT 2 3 DETROIT 24 r DETROIT 25 3

DETROIT 26 1 4 DETROlf 27 i 3 DETROIT 28 1 I

DETROrr 29 1 1 HAMILTON 1 I 5

I i t , 1

5 : 3 S i 2 ! 3 2 HAMILTON 2 i 5 I 5 ' 3 5 i 21 3 2 HAMILTON 3 5 I 5 3 5 2 ' 3 2 M I L T O N 4 I 5 I 5 3 5 1 2! 3 2 HAMILTON 5 ' 2 I 2 1 3 4 l 2 3 2 HAMILTON 6 1 3 1 5 1 21 4 2 HAMILTON 8 I 3 ! 5 2 4 2 HAMILTON 9 1 3 1 5 : 2 ' 4 2 HAMILTON ! 0 4 - 3 ' 5 2 4 2 HAMILTON 12 2 2 ' 3 4 2 3 2 NlAGARA 1 5 21 5 31 5 2 1 2 NlAGARA 2 ' 5 2 ' 2 5 5 1 5 51 2 2 ' 3 2

175 Table E. 1 . Severity of water column contaminant concentrations at each sampled mlcrosne.

AOC SITE, A t ASi 8A CA CDI CR' CU FEI HG MNl Pb ZN

SEMRN - 29 1

S N E R N 30 '

-- -

SEMRN 33 :

SEVERN 34 3 SEVERN 35 i SEVERN 36 !

--

SPANISH 1 I 3 SPANISH 2 i

SPANISH 3 i 3 1 SPANISH 4 I 3 I

SPANISH 5 i - - - . -- - . - -- -

SPANISH 6 1 SPANISH 7 ' 2 3 -

SPANISH 8 ! 2 3

SPANISH 9 I

SPANISH 10 ;

SPANISH 11 I

SPANISH 1211 i I I I I

SPANISH t 4 : ( ! 1 SPANISH 15 ! I 21 3 2 ' SPANISH 16 1 I

SPANISH 17 I SPANISH 18 (

SPANISH 20 f SPANISH 21 ,

ST CLAlR 1 j , ST CLAlR 3 1 ST CLAIR 4 1

ST ClAlR 5 i

ST ClAlR 6 1 ST CLAlR 7

ST CLAIR 8 i

ST CLAIR 9 t

ST CLAlR 10 t

ST CLAlR 11 ' 4 3

ST. CLAlR 15 1

ST CLAlR 16 1 ST ClAIR 17 /

- - .- - - -

ST ClAIR 18 I

ST ClAlR 19 1

1 76 Table E. 1 Seventy of water column contaminant concenbatmns at each sampled mmsrte.

-- - -

AOC SITE! A 1 AS! BA CAm CDI CRi CtI F E HG MNI NII P0 , ZN

ST. ClAlR 20 ! 1 ST C U l R 21 i

- -

ST lAWR 1 ' 2 : ST LAWR 2 ' 2 1

ST iAWR 8 1 2 , ST L A W 9 1 2 ' 2 ST. LAWR 101 2 i S T . L A W 111 2 ! ST LAWR 12 i 2 : 2 ST LAWR 13 I 2 I ST lAWR 1401 2 3 2 ; 3 2 ST UWR 1s 11 1 i i 21 f I

ST lAWR 16 1 I 2 1 I 17 ST LAWR 2 ' 1

ST lAWR 18 / 2 STLAWR 191 2 3 ; 21 3 2 ST LAWR 20 1 I 2 5 i 21 3 2 ST LAWR 21 ' 2 : I

ST MARYS 1 .

ST MARYS 2 j ST MARYS 3 ! ST MARYS 6 ;

ST MARYS 5.1 s 2 ; 3 3i 3 4 . 4 31 2 1 3 2 TORONTO 1 I 1 i 1 1 3 1 21 3 2 TORONTO 3 I 1 ! t 3 1 2 ! 3 2 TORONTO a 1 . f I 3 1 2 ! 3 2 TORONTO 5 i I I t i 3 1 21 3 2 TORONTO 6 ' 11 1 ' 3 1 21 3 2 TORONTO 8 : 1 . 1 , 3 1 21 3 2 TORONfO 9 1 1 : 1 I 3 1 2 ; 3 2 TORONTO 1 0 . 1 I 1 1 3 1 21 3 2

Table E. 1. Seventy of water column contaminant concentrations at each sampled microstte.

AOC SITE + ALDRIN CHLORDANE 8% ODE 00T ENOOSULFAN ENORIN HEPTACHLOR HCB TC8

6 QUINT€ 2

8. QUlNTE 9 1 -

B QUINTE 10 1

B QUlNTE 11 -

6 QUlNTE 12

B. QUiNTE 13 ; B. QU1NTE 14 I

B. QUlNTE 15 f B. QUlNTE 16 ! 4

B QUINT€ 19 1

B QUINT€ 20 1 8. QUlNTE 21

8. QUINT€ 25 j 8. QUlNTE 26.1 8. QUINT€ 27 1

- -

B QUINT€ 28 1

6 QUlNTE 29 ,

- -

B QUINT€ 31 '

6. QUlNTE 32

- - - - - - . - -

COLLING 1

COLLING 2 - - - -

COLLING 3

DETROfT 1 , 3 3

- - -

DETROIT 3 I 3 1

OETROtf 4 1 1

DETROIT 5 2 3 2 2 3 2 DETROIT 6 1 DETROIT 7 !

DETROIT 8 ' 2 DETROIT 9 !

178 Table E. 1. Seventy of water column contaminant concentrations at each sampled mlcrosite.

AOC SITE ! ALDRlN CHLORDANE B H C ODE DOT ENOOSULFAN . ENORIN HEPTACHLOR HC8 TCS .

DETROIT 10 I

DETROIT 11

DETROIT 12

DETROIT 13

DETROIT 14 2 4 2 3 2 2

DETROF 16 I

DETROIT 17 '

DETROIT 18 8 3 3 DETROIT 19

DETROIT 20

DETROlf 21 - .. - . -

DETROIT 22 1

D e O l T 23 1

DETROIT 24 1

DETROIT 25 2

DETROIT 26 4 3 3 DETROIT 27 2 DETROIT 28 J

DEfROlT 29 1 1 HAMILTON 1 1 1 1 3 1 1 1 1

HAMILTON. 2 1 1 1 3 1 1 1 1

HAMILTON 3 1 1 3 1 1 1 1

HAMILTON 4 I 1 1 3 1 1 8 1 - - -- --

M I L T O N . 5 I 1 3 1 1 1 1

HAMILTON 6 , 1 1 3 1 1 1 t -- - - - - -

HAMILTON 8 1 1 3 1 1 t 1

HAMILTON, 9 1 1 1 3 1 1 1 1

HAMILTON- :O4 1 1 3 1 1 1 1

HAMILTON 12 1 1 3 1 1 1 1 -

NIAGARA 1 '

NlAGARA 2 1 1 3 ' - -- -

NlAGARA 3 '

NIAGARA 4 1 3 1 1 1 2

NIAGARA 7

NlAGARA 8 . 2 1 3 2 2 2 2 1 2 2

NVrGARA 9 NIAGARA 10 : NIAGARA -- 11 i 2 3 1 2 1 1 2 NIAGAUA 12 i

NIAGARA 13 ! 2 2 3 2 2 2

NlAGARA 14 I 2 2 3 2 2 2 NlAGARA 15 I 2 . 1 3 1 1 1 2 1 1

179 Table E. 1. Seventy of water column cantam~nant concentrabons at each sampled rnmsrte.

AOC SIT€ ! ALDRIN ,CHLORDANE 8% I DM: DOT 'ENOOSULFAN ENORIN .HEPTACHLOR HCB TCB

NIAGARA 16 i N ~ G A R A 17 ; NIAGARA 18 : 2 2 3 2 2 2 2 2 2

NIAGARA 23 ! 2 2 3 2 2 . 1 2 2 2 3

NlAGARA 26 1

NIAGARA 27 ' 2 3 2 2 2 ROUGE 1

ROUGE 2 i

ROUGE 3 1 ROUGE 4 I

ROUGE 5 i 4 - - - -

ROUGE 6 I

S E E R N 1 I

SEVERN 4 !

SEVERN 5 , S N E R N 6 1

SEVERN 7 '

SEVERN 8 ! - -- - - --

S N E R N 9 1

SEVERN 10 ! - - -

SEVERN 11 S N E R N 12 SEVERN f 3 S N E R N 14 '

SEVERN I S - --

S N E R N 16 '

SEVERN 17

S E M R N 18 ! S N E R N 19 !

SEVERN 20 . - -

SEVERN 22 SEVERN 23 i S N E R N 24 S N E R N 25 :

SEVERN 26 1

SEVERN 27

SEVERN 28 1

Table E. 1. Severity of water d u m n contaminant concentrations at each sarnpkd rnrcfosrte.

- - AOC SI%-~ ALDRIN CHLORDANE BHC ' DO€ DOT ENOOSULFAN . E N m I N HEPTACHLOR HC8 - TC8

SEVERN 29 1 SEMRN 30 i SEMRN 31 .

SEMRN 33 t

SEMRN 35 1 SEVERN 36

-- -

SPANISH 1 1 SPANISH 2 :

. - - SPANISH 3 1

SPANISH 4 i SPANISH 5 ; - -- - -

SPANISH 6 i SPANISH 7 !

SPANISH 8 SPANlSH 9 i SPANISH 10 1

SPANISH 11 1 SPANISH 12!1

SPANISH 14 11

SPANISH lsil

SPANISH 16 1 SPANISH 17 1 SPANISH 18.1 SPANISH 20 1 -- -. - -

SPANISH 2 1

ST CUlR 1 I 2 3 ' 2 2 2

ST CLAIR 6 i 2 3 2 2 ST CLAlR 7 ! 2 3 2 2

ST. CLAlR 13 i 2 3 2 2 3 ST. CLAIR 14 1i 2 ' 3 2 2 ST. ClAlR 15 ; 2 3 2 2 ST. CLAlR 16 ' j 2 3 ' 2 ' 2 ST. CLAlR 17 ! 2 ' 3 ' 2 2 ST CLAlR 18 ! 2 3 2 2 ST.CLAlR 19:j 2 2 3 2 2 2 3 2

Table E.1. Seventy of water column contammant concentrations at each sampled microslte.

AOC StTE I ALDRIN CHLORDANE BHC DO€ OOT ENOOSULFAN ENORIN HEPTACHLOR HC8 TC8

ST UWF? 5 ! ST LAWR 6 1 ST. UWR 7 t ST. LAWR 8 i

ST. LAWR 9 1

S T U W R 1 2 1

S T ~ A W R 1 3 :

ST. LAW 14 I 2 3 3 , 4 - - -

ST.UW 1 ~ 1 r ST. LAW 16;!

ST LAWR 17

S T m 181 S T U W R 191 2 3 3 4 ST LAWR 20 I 2 3 3 4 STLAWR 211

- - --

ST MARYS 1

STMARYS. 2 1 ST MARYS 3 i ST MARYS 6 :

- - -

TORONTO 1 1 2 1 2 7

TORONTO 3 : 1 2 1 2 1

TORONTO 4 1 2 1 2 1

TORONTO 5 1 1 2 1 2 1

TORONTO 6 , 1 2 1 2 1

TORONTO e 1 2 1 2 I

TOROHTO 9 1 1 2 1 2 1

TORONTO 10 i 1 2 1 2 1

Table E. 1. Seventy of water column contaminant concentrations at each sampled mlcrosite.

AOC SITE ! LINOANE METHOXYCHCOR I MIR€X I OCS I PAH PC6 PHENOL TOTAL NUMBER INEX

6. QUlNTE 2 i 0 B. QUINTE 3 0

B QUINT€ 10 I 0 6 QUINTE 11 0 '

B QUlKE 24 1 I 0,

8 QUINTE 25 0 8 QUINTE 26 1 9 4 0.45

COLLING 1 ' 0 COLLING 2 : 0 COLLING 3 . 0 DETROIT 1 1 1 1 13 6 0.43 DETROIT 2 4 2 8 3 053 -

DETROIT 3 , I 1 1 11 6 0.37 DETROIT 4 ! ' 4 2 3 17 7 0.49 DETROIT 5 r 2 31 5 2 29 1 1 0.53 DETROIT 6 .I I i 0 8

DETROIT 7 ! 5 1 1

DETROIT 8 1 4 2 11 4 0 55 DETROIT 9 1 0

Table E. 1. Seventy of water column contaminant concentrations at each sampled mlcroslte.

AOC SITE I L lNMNE MEtnOXYCHLOR l MlRUt, OCS I PAH PC8 PHENOL TOTAL NUMBER INOEX

OETRGT 10 1 o ORROIT 11 b 3 t t r 068 DETROIT 12 : 0

D€TROIT 17 1 0 DETROIT 18 1 1 11 5 17 6 0.57

DETROIT 20 I o OETROIT 21 ! 0 DETROIT 22 1 3 3 1 0.6 OETROiT 23 I 3 3 1 0 6 DETROff 24 I 3 3 1 0.6

-

DETROIT 25 1 5 3 13 4 065 OETRO~T 26 I 1 7 I 4 16 6 053 DETROIT 27 ' 5 3 13 4 065 OETROlT 28 * I 0 OETROK 29 i! 1 0 I

I , HAMILT ON 1 I 2 1 1 1 ! 2 40 180 O U HAMILTON 2 1 2 1 I 11 2 4 0 ' 181 0.441 HAMILTON 3 ; 2 1 ; 1 2 40 18 044 HAM l LTON 4 I 2 1 i 1 ' 2 40 18 O U HAMILTON 5 i 2 1 f t r 2 ' 33 I8 037 HAMILTON 6 ! 2 11 1 2 31 16 039 *

HAMILTON 8 2 1 1 2 31 16 039 HAMILTON 9 1 2 1 1 1 2 31 16 039 HAMILTON 1 0 , 2 1 1 2 3 1 16 0.39 HAMILTON 1 2 1 2 1 ' 1 2 33 18 037 N LAGAR4 1 t 24 7 0.69 NlAGARA 2 1 1 44 15 059 NlAGARA 31 I7 6 0.57

NIAGARA 5 I 24 7 069 NlAGARA 6 ' 24 7 0.69 NIAGARA 7 16 6 0.53 NlAGARA 8 2 4 i 1 2 61 25 049 NlAGARA 9 1 24 7 069

NIAGARA 12 ( 16 6 0.53 N IAGARA 13 1 2 3 2 53 20 0.53 NlAGARA 14 I 2 3 2 39 16 0.49

185 Table E. I. Seventy of water column contaminant concentrations at each sampled microsite.

AOC SITE LINDANE METHOXYCHLOR l M l R a l OCS t PAH PCB 'PHENOL TOTAL NUMBER ' I N E X

SEVERN 29 1 0

S E M R N 30 1 0

SEVERN 3 1 0

S E M R N 32 0

S E M R N 33 0

SEVERN 34 I 3 1 0 6

SEVERN 35 1 0 SEVERN 36 , 0

SPANISH 1 I 3 1 0 6

SPANISH 2 0

SPANISH 3 i 3 1 0 6

SPANISH 4 : 3 1 0 6

SPANISH 5 ! 0 SPANISH 6 I 0

SPANISH 7 1 2 7 3 047

SPANISH 8 1 2 7 3 047

SPANISH 9 1 0

SPANISH 30 I 0 .

SPANISH 11 1 1 i 0 SPANISH 12 1 1 I I i 0 1

I

SPANISH 14 0 : SPANISH 15 ! 7 3 : 0.47

SPANISH 16 : 0 SPANISH 17 : 0

SPANISH 18 r 0 - -- -- - - - - -

SPANISH 207 0

SPANISH 2 1 0 ST. ClAlR I I 2 ! 31 3 19. 8 . 0.475

ST ClAiR 3 1 2 3 14 6 - 0.47

ST C W R 6 ! 2 3 14 6 047 ST ClA lR 7 ' 2 3 14 6 047

ST CLAlR 8 I 2 3 14 6 047

ST. C U l R 9 ! 2 3 14, 6 047

ST CLAIR 10 I 2 3 14 6 047 ST CLAlR 1 1 ' 1 5 : 1 27 10 054

ST CLAlR 12 2 3 I 3 20 8 0 5

ST ClAiR 13 I 2 4 I 3 2 1 8 0.525 ST C U l R 14 I 2 3 14 6 0.47

ST. C U l R 15 i 2 3 14 6 0.47

2 ST.CLAlR 161 I 3 14. 6 , 047

ST. CLAlR 17 2 3 14 6 047

ST CLAlR 18 r 2 3 14 6 047 -

ST. ClAlR 19 1 2 1 ! I 31 3 26' 11 047

Table E. 1. Seventy of water column contaminant concentrations at each sampled mmsrte. 186

AOC SITE ; LINDANE MEntOXYCHLOU 1 MlRW I OCS l PAH PCB PHENOL TOTAL NUMBER INOEX

ST CLAlR 20 ! 2 3 14 61 047 ST ClAlR 21 I t 11 1 17 9 0 3 8 ' ST ClAlR 22 2 3 ' 3 39 5 052 ST C U l R 24 2 3 14 6 047 ST ClAlR 25 1 2 3 20 9 O U ST L A W 1 1 1 I 1 3 17 13 0 2 6 ST L A W 2 i 1 2 1 0.4 ST LAWR 3 1 3 5 2 0 5 ST LAWR 4 4 2 04

ST LAWR 5 i 2 3 7 3 047 ST LAWR 6 2 1 0 4 ST LAWR 7 1 2 1 0.4 ST LAWR 8 1 2 1 04

Sf LAWR 9 1 4 2 04

ST LAWR lob/ 2 1 0 4 ST L A W 1 1 ' 2 1 0 4 - -

STLAWR 121 4 2 0 4 ST LAWR 13 i 2 1 0 4 S f L A W 14 ( 2 2 3 3 1 12 052 ST lAWR 1511 I 1 I 2 1 ' 0.4' ST U W R 1611 I 2 1 0 4 ST tAWR 17 1 2 4

1 2' 0.4 ST LAWR 18 I 3 5 2 0 5 ST tAWR 19 I 2 4 5 35 12 0.58 ST LAWR 20 1 2 4 32 1 1 0.58 ST LAWR 21 / 3 5 2 0.5

- -

ST MARYS 1 0 ST MARYS 2 1 0 ST MARVS 3 o ST MARYS 4 0

ST MARYS 5 1 2 2 1 I! 4! I 3 69 27 051 TORONTO 1 i h 9 1 23 14 033 TORONTO 3 2 1 23 14 033 TOR ONTO^ 4 I 2 1 23 4 0 3 3 TORONTO 5 I 2 1 23 14 033 TORONTO 6 1 2 1 23 14' 0 33 TORONTO 8 1 2 1 23 14 033 TORONTO 9 1 2 1 23 14 033 TORONTO 10 1 2 1 23 14 0 33

SEDIMENT CONTAMINANT SCORES FOR TOXICITY TEST

Scores between 1 (least severe) and 5 (most severe) are assigned based on the criteria outlined in tables C.3 and C.4. Where no scores have been assigned. data was not available in the literature. For each microsite. the sum of all scores (SUM). the number of scores assigned (NUMBER). and the calculated index (INDEX) of metal contamination. organic contamination. and organic matter content of the sediment are also given.

Table F.2. Calculation of organic contaminant index.

- -

SEDIMENT . -. -- ORIGIN - --- ---- ---- SEVERN SOUND -4 ---- -------- NIAGARA RIVER R~uGER~VER - -- ----- DETROIT RIVER - - . - - - - - - - - - - - PORT HOPE WEATLEY ST: C ~ I R RIVER TORONTO- - HAMILTON COLL I N G ~ O D - - - - - - - BAY OF QUINTE STANDARD

BHC .. .

1 2

4

1 2

1 1 3 1

I

DDT . . ENDOSULFAN -- - - 1 1 2 2

ALDRlN . - - - - - -

1 2

3

1 1 4 1

HCB

2

4

4

1 2 3 1

CHLORDANE 1 2

4

4 2

1 1 3 1

ENDRIN 1 2

HEPTACHLOR . - - 1 2

Table F.3. Calculation of organic matter index.

SEDIMENT ORIGIN LO1 -- -- TOC , I SUM lNUMBERi INDEX ' -- SEVERN SOUND - 2 5 j 7 2 0.7 NIAGARA RIVER 5 5 1 1 ROUGE RIVER 5 5 t o 2 1 1

DETROIT RIVER 4 5 9 2 0.9 PORT HOPE 2 4 i 6 2 0 6 I

WHEATLEY 5 5 1 1 0 ! 2 1 ST CLAlR RIVER 4 j 4 1 ' 0 . 8 TORONTO 3 5 1 8 2 0.8 HAMILTON 4 4 1 0.8 1

COLLINGWOOO 3 1 3 7 1 : 0.6 i

BAY OF QUlNTE 3 I 3 1 0.6 STANDARD 4 4 8 2 0.8 ,

APPENDIX G

MAPS OF AREAS OF CONCERN SHOWING COLLECTION LOCATIONS FOR

SEDIMENTS AND VALLISNERLQ AMERICANA SAMPLES

Mean leaf-to-root surface area ratios of Vallisneria atnericana are given for each sampled microsite visited in 1995. Microsites indicated by an upright triangle (A ) were included in regression equation 1 (chapter 2. page 23). microsites indicated by an upside down miangle (V ) were included in regression equation 2 (chapter 2. page 25). and microsites indicated by a square ( I ) were not included in the regressions due to missing data.

The location of the collection site for sediment from the Rouge River used in the dilution experiment in chapter 3 is indicated by the following symbol: 4 b .

Locations of sediment collection sites for the toxicity rest in chapter 3 are indicated by an asterisk (*).

N

PORT HURON

Figure G.5. The St. Clair River Area of Concern.

! , I

1 I

I

i

!

WINDSOR -

! I ! I -_ - \

! I . .

j I i Elf Atochcn kc I

1 !

.- A -

SIctaritaritSteel C a p - f *

30.4'

I I

Figure G.6. The Detroit River Area of Concern-

LAKE ERIE

Figure G.8. The Wheatley Harbour Area o f Concern.

h?AGiUU FALLS

NEW YORK

Figure G.9. The Niagara River Area o f Concern.

PORT HOPE

LAKE ONTARIO

METRES

Figure G. t 2. The Port Hope Harbour Area of Concern.

VITA AUCTONS

NAME: Kelly Potter

PLACE OF BIRTH: S t . Catharines. Ontario

YEAR OF BIRTH: 1971

EDUCATION: EL. Crossiey Secondary School. Fonthill. Ontario

1985- 1990

University of Guelph, Gueiph. Ontario

1990-1994 B.Sc.

University of Windsor. Windsor. Ontario

1995- 1998 M.Sc.