State of the Lakes Ecosystem Conference 1996
Background Paper
INFORMATION AND INFORMATION
MANAGEMENT
Wendy Leger
Environment Canada, Ontario Region
Burlington, Ontario
Richard Greenwood
U.S. Fish and Wildlife Service
Chicago, Illinois
December, 1997
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Table of Contents
Acknowledgments v
1.0 Introduction 1
1.1 Obj ectives 1
1.2 Scope 1
1.3 Contributing Authors 2
2.0 Nearshore Information Definitions and Collection Methods 2
2.1 Definitions 2
2.1.1 Definition of Nearshore 2
2.1.2 Defining Nearshore Information 2
2.2 Methods of Determining the State of Nearshore Information 3
2.2.1 The Survey 3
2.2.2 Literature Search 3
3.0 State of Nearshore Information Holdings 4
3.1 Nearshore Waters 4
3.1.1A Fish and Fish Habitat: Canadian Holdings 4
3.1.IB Fish and Fish Habitat: U.S. Holdings 4
3.1.2A Other Aquatic Species: Canadian Holdings 5
3.1.2B Other Aquatic Species: U.S. Holdings 5
3.1.3A Water Quality: Canadian Holdings 6
3.1.3B Water Quality: U.S. Holdings 8
3.1.4A Hydrology: Canadian Holdings 9
3.1.4B Hydrology: U.S. Holdings 9
3.1.5A Nearshore Sediments: Canadian Holdings 10
3.1.5B Nearshore Sediments: U.S. Holdings 11
3.1.6A Spills: Canadian Holdings 11
3.1.6B Spills: Canadian and U.S. Holdings 12
3.1.7A Nearshore Bathymetry: Canadian Holdings 12
3.1.7B Nearshore Bathymetry: U.S. Holdings 12
3.2 Nearshore Terrestrial 12
3.2.1A Base Mapping/Topographic Data: Canadian Holdings 12
3.2.IB Base Mapping/Topographic Data: U.S. Holdings 13
3.2.2A Flooding and Erosion: Canadian Holdings 13
3.2.2B Flooding and Erosion: U.S. Holdings 14
3.2.3A Wildlife and Wildlife Habitat: Canadian Holdings 15
3.2.3B Wildlife and Wildlife Habitat: U.S. Holdings 16
3.2.4A Soils: Canadian Holdings 17
3.2.4B Soils: U.S. Holdings 17
3.3 Impacts of Changing Land Use 18
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3.3 A Impacts of Changing Land Use: Canadian Holdings 18
3.3B Impacts of Changing Land Use: U.S. Holdings 18
3.4 Coastal Wetlands 20
3.4A Coastal Wetlands: Canadian Holdings 20
3.4B Coastal Wetlands: U.S. Holdings 21
3.5 Other (Canadian and U.S. Holdings) 21
3.5.1 Weather and Climate Data 21
3.5.2 Air 21
3.5.3 Nearshore Ecosystem 22
4.0 Nearshore Data Needs and Gaps 23
4.1 Nearshore Waters Indicators and Identified Data/Information Needs and Gaps 25
4.2 Land by the Lakes Indicators, Data Needs and Gaps 29
4.3 Coastal Wetlands 31
4.4 Impacts of Changing Land Use 34
4.5 Information Indicators 37
4.5.1 Status of Information - General Findings 37
5.0 Nearshore Information Management 39
5.1 Definition of Information Management 39
5.2 Nearshore Information Management Issues 39
5.2.1 Data Collection Issues 39
5.2.2 Documenting/Cataloguing of Data (Metadata) 41
5.2.3 Medium of Storage/Archiving 41
5.2.4 Availability and Access 41
5.2.5 Data Integration 43
5.2.6 Security and Protection of Data 43
5.2.7 Data Stewardship 43
5.2.8 Methods of Dissemination 44
6.0 Significant Challenges and Opportunities 45
6.1 Agreed-Upon Indicators 45
6.2 Standardized Data-Collection Techniques 45
6.3 Coordinating Data-Gathering Initiatives 45
6.4 Finding the Data 46
6.4.1 Metadata Standards 46
6.5 Sharing/Accessing Data 47
6.5.1 Common Data-Exchange Formats 47
6.5.2 Using the World Wide Web 47
6.5.3 Existing Great Lakes Networks 48
7.0 Where Do We Go From Here? 49
8.0 References 50
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List of Tables
Table 1 Nearshore Waters 25
Table 2 Land by the Lakes 29
TableS Coastal Wetlands 31
Table 4 Impacts of Changing Land Use 34
Table 5 Assessing the Data 38
List of Appendices
APPENDIX 1 List of Reviewers and Contributing Authors 53
APPENDIX 2 Survey Questionnaire 58
APPENDIX 3 List of Catalogues, Directories, and Web Sites 62
APPENDIX 4 Great Lakes Nearshore Information Holdings 65
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Notice To Readers
This Background Paper is one of a series of such papers that were prepared to provide a concise overview of
the status of the nearshore conditions in the Great Lakes. The information they present has been selected as
representative of the much greater volume of data. They therefore do not present all research or monitoring
information available. The Papers were prepared with input from many individuals representing diverse
sectors of society.
The Papers provided the basis for discussions at SOLEC 96. Participants were encouraged to provide specific
information and references for use in preparing the final post-conference versions of the Papers. Together
with the information provided by SOLEC discussants, the Papers have been incorporated into the 1997 State of
the Great Lakes report, which provides key information required by managers to make better environmental
decisions.
IV
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Acknowledgments
The authors would like to thank the contributing authors and reviewers for their input and
guidance. They would also like to thank all those who took the time to complete and return the
nearshore questionnaire. Special thanks goes to Simone Rose of Environment Canada for her
efforts in compiling Appendix 4 and for her overall assistance with the report.
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1.0 Introduction
The focus for the State of the Lakes Ecosystem Conference (SOLEC) 1996 is the nearshore zone
of the Great Lakes. Nearshore ecosystems are complex and dynamic with many measurable
parameters. The nearshore area is extremely important to overall ecosystem function. It is the
most productive zone within each of the Great Lakes and is the area most affected by human
activity. Nearshore zones include embayments, tributaries and tributary mouths, marshes and
other wetlands, and dunes. Their size and ever-changing nature create a challenge for their study
and understanding. Yet timely access to accurate environmental information is critical for making
wise decisions to ensure nearshore ecosystem protection and management, and the promotion of
environmental stewardship.
To make informed decisions about the Great Lakes nearshore, we must have ready access to
reliable data/information that can be compared and shared effectively among partners and decision
makers. From a technological perspective, an ecosystem approach requires an electronically
based, integrated data-management system that enables interaction among disciplines and across
geographic boundaries. The new environmental information-management systems allow this
through improvements in data management, storage, and networking capabilities, together with
new data-transfer, processing, and visualization tools.
1.1 Objectives
The objectives of the paper are the following:
• To provide an overview of nearshore information holdings and information systems, with a
summary of information sources and content.
• To identify gaps and needs in nearshore information on the basis of a set of proposed
indicators to measure and monitor the state of the nearshore.
• To examine how nearshore information is currently being managed.
• To examine the issues facing the management of nearshore information.
• To identify possible improvements in managing the information.
1.2 Scope
The scope of this paper includes both U.S. and Canadian Great Lakes nearshore information and
data holdings from federal, state, and provincial agencies; non-government organizations; and
academia.
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1.3 Contributing Authors
Contributing authors to this paper represent federal, state, and provincial agencies and academia
from around the Great Lakes basin. All contributing authors have some involvement with data or
data management. For a complete list of contributing authors refer to Appendix 1.
2.0 Nearshore Information Definitions and Collection
Methods
2.1 Definitions
2.1.1 Definition of Nearshore
SOLEC '96 focuses specifically on the nearshore of the Great Lakes. The nearshore includes both
the nearshore waters and the terrestrial zone along the shoreline. The nearshore waters begin at
the shoreline or the lakeward edge of the coastal wetlands and extend offshore to the deepest
lake-bed depth contour where the thermocline typically intersects with the lake bed in the late
summer or early fall (Edsall and Charlton 1996). The nearshore terrestrial zone or "land by the
lakes" (Reid and Holland 1996) is defined by the Lakes themselves. The physical changes
wrought by the edge of the lakes and the local climatic effects of large water bodies exert huge
influences on shoreline habitats. Land-by-the-lakes ecosystems may be as narrow as a beach that
is weathered by wind and waves or they may extend several kilometres inland as part of
contiguous forests or dune fields (Reid and Holland 1996). The nearshore zone, for the purposes
of SOLEC '96, also includes wetlands that are affected by variations in lake levels, and looks at
how changing land use impacts on this zone.
2.1.2 Defining Nearshore Information
Data can be defined as the raw facts collected on a particular subject after some basic quality-
controls have been applied to the collection process. In this case, the subject is the nearshore of
the Great Lakes. Once data have been analysed, interpreted, and synthesized, they become
information. For the purposes of this report, little to no distinction is made between data and
information (although an emphasis has been placed on nearshore-related electronic databases). In
this report, nearshore information relates to four topic areas: nearshore waters, nearshore
terrestrial or "land by the lakes," impacts of changing land use, and coastal wetlands. It also
includes some information on a few data sets that do not fit neatly into any of these categories, for
example, climate data.
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The topic of nearshore waters includes information on fish and other aquatic species and their
habitat, water quality, nearshore sediments, physical processes, and spills in the water. The topic
of nearshore land includes information on nearshore topography, flooding and erosion, wildlife
and wildlife habitat, and soils.
2.2 Methods of Determining the State of Nearshore Information
2.2.1 The Survey
A primary source of information for this paper was a questionnaire sent to a range of agencies and
institutions around the basin on both sides of the border. Over 700 questionnaires were sent to
Canadian federal, provincial, regional governments; non-government agencies; and academia. A
total of 95 responses were received. Approximately 300 questionnaires were sent out to similar
U.S. agencies, and 65 were completed and returned. In addition, the questionnaire was posted on
the Internet and made available through Environment Canada's Great Lakes Information
Management home page, U.S. (Environmental Protection Agency's) (EPA's) Web pages, and the
Great Lakes Information Network (GLIN). The questionnaire, which was kept relatively short in
the hope that this would generate a greater response rate, asked organizations to identify their
nearshore databases and information holdings, and describe the purpose and content of the
database. It also asked respondents to identify their nearshore information needs. Although the
response rate appears low, this is misleading since many of the questionnaires were sent to
individuals at the same agency and only one questionnaire was returned on behalf of that agency.
A copy of the questionnaire can be found in Appendix 2.
2.2.2 Literature Search
Other sources of information for this report were existing catalogues and directories of
information holdings. Catalogues listing Great Lakes databases were the primary source of
information. These are listed in Appendix 3. A full search of the Internet was also conducted
using keywords such as Great Lakes, nearshore, coastal zone, coastline, shoreline.
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3.0 State of Nearshore Information Holdings
There are numerous databases and information holdings pertaining to some portion of the
nearshore environment. The purpose of this section is not to describe them all, but rather to touch
on a few of the larger, more encompassing databases that deal with a significant portion of the
Great Lakes nearshore. A detailed list of data and information holdings gathered for this report is
provided in Appendix 4.
3.1 Nearshore Waters
3.1.1 A Fish and Fish Habitat: Canadian Holdings
Nearshore Fish and Fish Habitat Database, Canadian Department of Fisheries and Oceans:
The purpose of this database is to develop a knowledge of fish communities in the Great Lakes
nearshore zone and to develop predictive models of fish attributes using habitat variables. The
database includes information on exposed shorelines of Lake Erie and Lake Ontario and on the
Bay of Quinte, Hamilton Harbour, and Severn Sound. (Survey Results 1996) [ID # 9, App. 4]
Ontario Fisheries Information System (FISHLIB), Ontario Ministry of Natural Resources:
Information was obtained from aquatic habitat inventory surveys, commercial harvest reporting,
commercial deck and port sampling, creel surveys, sport fishing diaries, sport fish sampling, index
fishing surveys, fish stocking, observations of significant events, observation of critical habitats,
habitat rehabilitation, harvest controls, and water body synopses. (Ontario Ministry of Natural
Resources, 1996) [ID # 120, App. 4]
3.1.1B Fish and Fish Habitat: U.S. Holdings
Bad River, Lake Superior, and Lake Sturgeon Database, US Fish and Wildlife Service:
Ashland (Wisconsin) Fishery Resources Office maintains this database. Assessment information
includes the distribution and movement, length, weight, girth, and habitat of juvenile lake
sturgeon. Data from 1993 through 1995. [ID # 106, App. 4]
Eurasian Ruffe Surveillance Database, U.S. Fish and Wildlife Service: Ashland (Wisconsin)
Fishery Resources Office maintains a program to detect the presence of ruffe and this database to
monitor the presence or absence of ruffe, relative abundance of cohabiting fish species, length and
age of ruffe, and length of subsample of other fish species. Geographic areas covered include
South Shore of Lake Superior; Thunder Bay, Lake Superior; shipping harbours in Lake Huron
and Lake Michigan; tributaries and harbours on the south shore of Lake Erie, and one in Lake
Ontario. Annual Reports, 1992-1995, available for all five Great Lakes. [ID # 105, App. 4]
Great Lakes Commercial Fishing Database, National Biological Service (NBS), Great Lakes
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Science Center, the National Marine Fisheries Service, and the Great Lakes states: This is a
database of U.S. commercial fishing data for the Great Lakes. Daily catch records are prepared by
states of Minnesota, Wisconsin, Illinois, Indiana, Michigan, Ohio, Pennsylvania, and New York.
[ID # 38, App. 4]
Great Lakes Research Vessel Catch System (RVCAT) Database, NBS, Great Lakes Science
Center: This database contains a log of vessel activities during routine assessments on the waters
of the five Great Lakes. The purpose of the database is to provide information on research and
monitoring offish population dynamics and to supply information to managers and scientists. [ID
# 37, App. 4]
Chemical Contaminants Database, NBS, Great Lakes Science Center: This database contains
information about fish tissue of four species archived in a deep freeze since 1970. The purpose of
the database is to monitor the trends of contaminants in Great Lakes fish. [ID # 36, App. 4]
Lake Huron/Thunder Bay and Lake Erie/Crane Creek Fishery Database: The U.S. Fish and
Wildlife Service's Aliena Fishery Resources Office maintains this database for the purpose of
compiling Lake Huron and Lake Erie fish community data, other biota, and abiotic information.
[ID # 104, App. 4]
Lake Michigan Creel Survey Database, Indiana Department of Natural Resources, Division of
Fish and Wildlife: Lake Michigan Research database for developing harvest estimates for trout,
salmon, bass, yellow perch, and other species; determining angler species preferences; determining
length and age offish harvested; and finding the occurrence of fin clips on salmonids. [ID # 26,
App. 4]
Nearshore Fish Community in Indiana Waters of Southern Lake Michigan Database: Ball
State University maintains this database to monitor trends in abundance and growth of nearshore
fishes. This information has been collected from 1977 to the present. [ID # 1, App. 4]
Lake Erie Fishery Database, National Biological Service: Lake Erie Biological Station
maintains a database on Lake Erie fish and other aquatic biota. [ID # 39, App. 4]
3.1.2A Other Aquatic Species: Canadian Holdings
Benthic Evaluation and Assessment of Sediment (BEAST), Environment Canada, National
Water Research Institute: This database contains information on benthic invertebrate community
structure (species level), sediment toxicity in the form of invertebrate species, and sediment
geochemistry for the entire Canadian nearshore waters of the Great Lakes and Lake Michigan. (S
Survey Results 1996) [ID # 30, App. 4]
3.1.2B Other Aquatic Species: U.S. Holdings
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Long-Term Trends in Benthic Populations: The National Oceanic and Atmospheric
Administration's Great Lakes Environmental Research Laboratory is determining trends in benthic
populations in selected areas of the Great Lakes and the significance of and reasons for such
trends. [ID # 48, App. 4]
Distribution of Zooplankton in Eastern Lake Michigan, Michigan Department of Natural
Resources: The purpose of this database is to determine the abundance, taxonomy, and
distribution of zooplankton in the nearshore waters of eastern Lake Michigan. [ID # 31, App. 4]
Biocriteria development to assess fish, macroinvertebrates, and periphyton communities in
Lake Erie estuaries, harbors, and nearshore areas, Ohio Environmental Protection Agency:
Existing environmental evaluation tools have been used to establish aquatic life and habitat goals
for the areas under study, and to provide a base against which to measure the progress and
effectiveness of Remedial Action Plans and Lakewide Management Plans for Lake Erie. [ID # 54,
App. 4]
3.1.3A Water Quality: Canadian Holdings
Numerous water-quality studies have been conducted on the Great Lakes over the years, primarily
to assess the problem of contaminants found in the Lakes. For Lake Ontario, data sources and
descriptions are referenced in the "Lake Ontario Categorization Committee Report," 1993.
Contaminant monitoring information includes open water and nearshore monitoring studies and
point and non-point source studies of contaminants released to the Lakes. Ambient water column
and fish tissue data are a primary source for water-quality data. Fish tissue data include sport fish
and forage fish species such as young-of-the-year spottail shiners. Ambient data for sediments are
also a source for water-quality data (Lake Ontario Categorization Committee 1993). Also
included are data on drinking water and beach closures as indicators of water quality.
Great Lakes Water Quality STAR Database (Storage and Retrieval), Environment Canada:
This database characterizes water quality in the Great Lakes. Information is collected to discover
nutrients and contaminants in each Great Lake. Regular spring (isothermal) and summer
(stratified) sampling cruises have been conducted since 1971 for nutrients, and since 1986 for
contaminant data. (Survey Results 1996) [ID # 13, App. 4]
Great Lakes Contaminants Surveillance Program, Department of Fisheries and Oceans, Great
Lakes Laboratory for Fisheries and Aquatic Sciences: This database contains information on
contaminants in Great Lakes sport fish. (Ball 1995) [ID #10, App. 4]
Juvenile Fish Biomonitoring Program and Database, Ontario Ministry of Environment and
Energy: This program documents temporal and spatial trends in organochlorine contaminant
levels in the nearshore waters of the Great Lakes from 1975 to 1994. (Suns, Hitchin, and Toner
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1991) [ID # 100, App. 4]
Drinking Water Surveillance Program, Ontario Ministry of Environment and Energy: This
program monitors drinking water quality of over 130 municipal drinking water systems in
Ontario. Raw, treated, and distributed water-quality data are available. Approximately 200
parameters are analysed, including microbiological parameters, general and organic chemicals,
metals, radionuclides, chemical dosage, flow ratios, field parameters, pH, turbidity, and plant
processes. (Lake Ontario Categorization Committee 1993) [ID # 109, App. 4]
In-Place Pollutant Program, Ontario Ministry of Environment and Energy: The program
assesses the extent and severity of sediment contamination through chemical analysis of the
sediment and biota resident in the sediment. The parameters monitored are metals, PCBs and
organochlorine pesticides, PAHs, and chlorophenols. (Jaagumagi and Persaud 1992) [ID #116,
App. 4]
Evaluation of Water, Sediment, and Benthic Invertebrates from Long-Term Sensing Sites,
Ontario Ministry of Environment and Energy: An objective of the study was to monitor the spatial
and temporal changes in environmental quality at nearshore locations in Lake Ontario. The report
documents information on water, sediment, and benthos. The water samples were monitored for
conventional water-quality parameters and trace metals. Surficial sediment was analysed for
metals, PAHs, and organochlorine compounds. (Tarandus Associates Ltd. 1992) [ID # 94, App.
4]
Upstream/Downstream Water Quality Monitoring Program, Environment Canada, United
States Environmental Protection Agency, New York State Department of Environmental
Conservation, and the Ontario Ministry of Environment and Energy: This database involves the
collection of ambient water and suspended sediment samples at the head (Fort Erie) and mouth
(Niagara-on-the-Lake) of the Niagara River. (Niagara River Data Interpretation Group 1989)
[ID # 50, App. 4]
Provincial Water Quality Monitoring Network, Ontario Ministry of Environment and Energy
(OMOEE): The purpose of the database is to determine water-quality trends in Ontario, to ensure
that provincial water-quality objectives are met for various uses, and to collect data for specific
OMOEE programs and studies. Water-quality sample analysis typically includes routine water-
chemistry results, such as nutrients, heavy metals, physical/chemical parameters, microbiology,
and some toxic organics. (Ontario Ministry of Environment and Energy 1996a) [ID # 107, App.
4]
Great Lakes Datastore, Sample Information System, Ontario Ministry of Environment and
Energy, Environmental Information and Systems Section: The purpose of the datastore is to store
sample results from Ministry monitoring activities in the Great Lakes and connecting channels.
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This database provides information on water, sediment, and biota. (Ontario Ministry of
Environment and Energy 1996a) [ID # 97, App. 4]
Municipal Industrial Strategy for Abatement (MISA), Sample Result Datastore (SRDS)
and Sample Result Datastore Oracle, Ontario Ministry of Environment and Energy: This
program was established to reduce flow of toxic chemicals to Ontario receiving waters. Database
includes industrial descriptor information, monthly summary effluent data from direct discharges,
and data submitted from control orders and Certificates of Approval. (Ontario Ministry of
Environment and Energy 1996a) [ID #101, App. 4]
Bacterial Levels in Recreational Water, Health Canada, Great Lakes Health Effects Program:
Existing bacterial levels have been gathered (E. Coli in Ontario) from public health units for
public beaches bordering the Great Lakes. Bacterial levels data have been supplemented by a
"beach postings" database produced annually by OMOEE and by information from each Health
Unit. (Survey Results 1996) [ID # 62, App. 4]
3.1.3B Water Quality: U.S. Holdings
Wisconsin Groundwater Contamination Susceptibility Model/Database, Wisconsin
Department of Natural Resources: The susceptibility of the state's groundwater to contamination
from surface activities was estimated by overlaying those physical resource layers of importance in
controlling water movement from the surface to the water table. Layers included in the model
were soil characteristics, surficial deposits, bedrock type, depth to bedrock, and depth to water
table. [ID# 117, App. 4]
Great Lakes ENVIROFACTS Database, EPA: This database contains relevant extracts about
the Great Lakes from several EPA databases and serves as a prototype for EPA's
ENVIROFACTS database. The individual databases contained in ENVIROFACTS are EPA's
facility-oriented Comprehensive Environmental Response, Compensation, and Liability
Information System (CERCLIS), Toxic Release Inventory (TRI) system, Facility Index System
(FINDS), and PCS databases, and the monitoring database, Resource Conservation and Recovery
Information System (RCRIS). An interface to the nationwide ENVIROFACTS is currently under
development. [ID # 75, App. 4]
Lake Michigan Mass Balance Database, EPA, Great Lakes National Program Office: This
database will include project description, station descriptions, sample collection, sample analysis,
results, and data quality information focusing on four major parameters: mercury, PCBs, atrazine,
and trans-nanachlor. Samples were collected from the following media: air (ambient, dry deposit,
precipitation), tributary mouths, open lake water, open lake sediment, and biota (predator fish,
prey fish, and invertebrates). [ID # 95, App. 4]
Green Bay Mass Balance Database, EPA, Great Lakes National Program Office: This database
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provides access to the results of the Green Bay Mass Balance Project, which focuses on four
chemical groups: PCBs, cadmium, lead, and dieldrin. Media sampled include tributaries, point
sources, atmosphere, non-point sources, sediment, water, food web, and groundwater. [ID # 94,
App. 4]
Rouge River Program Office Sampling Data/Geographic Information System (GIS)
Coverages: This database was developed by the Wayne County Rouge Program Office to
support watershed management activities including modelling and non-point source studies. [ID
#112, App. 4]
SARA Title Ill-Emergency Planning and Community Right-to-Know Database: The
Michigan Department of Environmental Quality SARA Title III Program Office maintains this
database to help comply with the Emergency Planning and Community Right-to-Know Act of
1986. [ID # 28, App. 4]
U.S. Great Lakes Beach Closings Database, U.S. Environmental Protection Agency, Great
Lakes National Program Office: Great Lakes bathing beaches in the U.S. are monitored to
determine their environmental suitability for use by the public. The database is based on responses
to the Survey of Great Lakes Bathing Beaches (1981 - 1994), conducted annually by the U.S.
EPAHs Great Lakes National Program Office. [ID # 97, App. 4 - U.S.]
3.1.4A Hydrology: Canadian Holdings
Surface Water Data for Ontario (HYDAT), Environment Canada: The database contains
water-quality and sediment data, descriptive information, and geographical coordinates for all
sites, period of operation for each site, and the type of hydrometric data collected. Data
maintained in the system include daily and/or instantaneous information with respect to
streamflow, water levels, suspended sediment concentration, sediment particle size, and sediment
loads. (Environment Canada 1996a) [ID # 17, App. 4]
Catalogue of Historical Storm Surges on the Great Lakes, Ontario Ministry of Natural
Resources: A study of Great Lakes storm surges was undertaken in 1988 to characterize the
synoptic condition (principally wind) associated with historical extreme storm surges and to give
some quantitative estimates of the probability of occurrences of these events. (Ontario Ministry of
Natural Resources 1996) [ID # 117, App. 4]
3.1.4B Hydrology: U.S. Holdings
Great Lakes Hydrology and Ice Databases: This National Oceanic and Atmospheric
Administration's Great Lakes Environmental Research Laboratory project develops and provides
new or improved historical hydrometeorological and ice cover databases. This contributes to the
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development of a GIS database of daily meteorological data for the United States, as well as some
data for Canada. [ID # 46, App. 4]
Wisconsin Watersheds Database: The Wisconsin Department of Natural Resources (DNR)
Statewide Watershed Boundary Geographic Data Layer was developed cooperatively by the
WiDNR Bureau of Water Resources Management (WRM) and the WiDNR Geographic Services
Section. [ID # 123, App. 4]
Natural Resources Conservation Service Mapping and Digitizing Watershed and
Subwatershed Hydrologic Unit Boundaries: This service collects information and databases to
use for management of renewable resources such as water, wildlife, and timber, and management
of recreational facilities. [ID # 50, App. 4]
Great Lakes Water Levels: The U.S. Army Corps of Engineers, Detroit Districts Great Lakes
Hydraulics and Hydrology Branch, in cooperation with its Canadian counterpart, provides
coordinated forecasts of Great Lakes water levels for periods up to six months. To produce these
forecasts, the branch maintains a database of real-time water level data from reporting gages
owned and operated by the branch, the National Oceanic and Atmospheric Administration's
(NOAA's) National Ocean Service (NOS), and the Canadian Hydrographic Service (CHS). [ID #
58, App. 4]
Wisconsin Hydrography GIS Database: The hydrography GIS data layer includes
representations of surface water at scales of 1:100,000 and 1:24,000. The data custodian is the
WiDNR Bureau of Water Resources Management. [ID # 122, App. 4]
Great Lakes Nearshore Hydrodynamics Database, National Oceanic and Atmospheric
Administration, Great Lakes Environmental Research Laboratory: This database synthesizes the
results of research studies on coastal hydrodynamics, biological processes, and water chemistry of
the nearshore region and applies them to practical problems of coastal environmental management
and planning. [ID # 47, App. 4]
3.1.5A Nearshore Sediments: Canadian Holdings
Great Lakes Sediment Database, Environment Canada, National Water Research Institute: The
purpose of the database is to research nearshore erosion, sedimentation, and sediment budgets.
This database includes information on Lakes Ontario and Erie, and parts of Lake Huron and
Georgian Bay. The database includes the nearshore bottom stratigraphy, grain size, and offshore
bathymetry. (Survey Results 1996) [ID # 49, App. 4]
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3.1.5B Nearshore Sediments: U.S. Holdings
U.S. Army Corps of Engineers (COE) Great Lakes Harbor and Lake Sediment Quality
Database: The U.S. Army COE, Environmental Analysis and Engineering Branch, Environmental
Analysis Section, developed this database to ascertain lake and harbour sediment quality for
dredging, and open lake and confined disposal. [ID # 59, App. 4]
HazDat, the Agency for Toxic Substances and Disease Registry's Hazardous Substance
Release/Health Effects Database, EPA: This database was developed to provide access to
information on the release of hazardous substances from Superfund sites or from emergency
events and on the effects of hazardous substances on the health of human populations. HazDat
also contains data from the U.S. EPA's CERCLIS database. [ID # 76, App. 4]
Assessment and Remediation of Contaminated Sediments Program: This is an EPA/Great
Lakes National Program Office five-year study and demonstration project relating to the
appropriate treatment of toxic pollutants in bottom sediments. Five areas were specified in the
Clean Water Act as requiring priority consideration in conducting demonstration projects:
Saginaw Bay, Michigan; Sheboygan Harbor, Wisconsin; Grand Calumet River, Indiana; Ashtabula
River, Ohio; and Buffalo River, New York. [ID # 90, App. 4]
Milwaukee Estuary Remedial Action Plan Sediment GIS Database, Center for the Great
Lakes Studies/University of Wisconsin-Milwaukee, and the Wisconsin Department of Natural
Resources: The purpose of the database is to assemble into a centralized database sediment
contaminant information that supports sound decision-making regarding remediation or other
treatment of contaminated sediments within the Milwaukee Estuary Area of Concern. [ID # 56,
App. 4]
3.1.6A Spills: Canadian Holdings
Transport Canada Ship Source Pollution Incident Reporting System, Transport Canada,
Marine Regulatory Directorate: The purpose of the database is to produce annual reports
concerning ship source pollution incidents, to support prosecution of polluters, and to analyze
causes of incidents. Data include the location, type of pollutant, quantity spilled, and action taken.
The database covers all waters under Canadian jurisdiction. (Survey Results 1996) [ID # 143,
App. 4]
3.1.6B Spills: Canadian and U.S. Holdings
Environmental Sensitivity Atlas and Associated Database, Environment Canada, US Coast
Guard, and the National Oceanic and Atmospheric Administration: This database includes
shoreline habitat descriptions, biological and human-use resources, and standard base map
SOLEC '96 - Information and Information Management 11
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features at 1:50,000 scale. These atlases identify the sensitive areas along the coasts of the Great
Lakes for use in hazardous material spill response. The atlases are designed for use in response to
spills of hazardous materials by helping responders to identify which resources are at risk during
a spill. (Snell et al. 1994) [ID # 43, App. 4 - Canadian, ID # 61, App. 4 - U.S.]
3.1.7A Nearshore Bathymetry: Canadian Holdings
Canadian Hydrographic Charts, Department of Fisheries and Oceans, Canadian Hydrographic
Service: Nautical charts and related publications are supplied to users to ensure safe commercial
and recreational shipping and boating. Hydrographic charts are available for all navigable waters
within Canada's territorial limits (i.e., parts of the Atlantic, Pacific, and Arctic Oceans, the St.
Lawrence River, the Great Lakes, and Hudson Bay). (Survey Results 1996) [ID # 7, App. 4]
3.1.7B Nearshore Bathymetry: U.S. Holdings
Computerized Bathymetry and Shorelines of the Great Lakes, National Oceanic and
Atmospheric Administration, Great Lakes Environmental Research Laboratory: This database
consists of bathymetric grid data and digitized shoreline data compiled for the five Great Lakes
and Lake St. Clair. [ID # 45, App. 4]
3.2 Nearshore Terrestrial
3.2.1 A Base Mapping/Topographic Data: Canadian Holdings
National Topographic Database (NTDB), Natural Resources Canada, Geomatics Canada: The
database comprises digital vector data sets that extend over the Canadian land mass. The major
topics covered are hydrography, road and transportation networks, infrastructures, vegetation,
landforms, and relief. Each data set consists of one National Topographic System (NTS) unit at a
scale of either 1:50,000 or 1:250,000. The NTDB provides a base of properly structured data
(segmentation, mathematical closure, connection and sharing between entities) specifically
designed and suited for GIS applications. (Natural Resources Canada 1996) [ID #58, App. 4]
Digital Topographic Database (DTDB), Ontario Ministry of Natural Resources: This database
includes a comprehensive information for the Ontario Basic Mapping (OEM) program. The
contents include the geographic references of the topographic, cultural, and cadastral features of
Ontario. These features include hydrography, vegetation, transportation, buildings,
communication, parks, hypsography, Native reserves, and the township boundaries. (Survey
Results 1996) [ID # 124, App. 4]
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Great Lakes Remote Sensing Data, Provincial Remote Sensing Office: The office conducts
technology and applications development projects, and mapping programs related to natural
resource inventories in such fields as forestry, geology, agriculture, and land-use planning,
through the analysis of airborne and spaceborne remote sensing. The office maintains a collection
of LANDS AT satellite imagery for Ontario and a literature library, both of which may be used by
the public. (Ontario 1996) [ID # 130, App. 4]
Coordinated Great Lakes Physical Data, Environment Canada, Coordinating Committee on
Great Lakes Basic Hydraulic and Hydrologic Data: The committee published coordinated physical
data of the Laurentian Great Lakes in its May 1977 report. The report describes the source
material and methods used to measure water areas, land areas, volume, shoreline lengths, and
general Great Lakes dimensions. (Environment Canada 1996a) [ID # 38, App. 4]
3.2.IB Base Mapping/Topographic Data: U.S. Holdings
Superfund National Priority List (NPL) Site Boundaries for the United States, US
Environmental Protection Agency, Office of Information Resources Management: This provides
Geographical Information System applications with a valuable data layer for base mapping of
NPL boundaries and environmental impact analysis. [ID # 99, App. 4]
USEPA Reach File Version 1.0 (RF1) for the Conterminous United States (CONUS), US
Environmental Protection Agency: This ARC/INFO coverage is intended for general water
resources applications within the GIS user community. It was created to replace the earlier U.S.
Geological Survey translations of Reach. Linking multiple databases to Reach can be
accomplished by the Reach indexing process. [ID # 87, App. 4]
Level III Ecoregions of the Conterminous United States (USECO), U.S. Environmental
Protection Agency: USECO provides polygon coverage of the Level III Ecoregions. Refinements
of ecoregion and sub-region definitions and locating sets of reference sites were conducted in
collaboration with the U.S. EPA's regional offices and the state resource management agencies.
These are designed to serve as a spatial framework for environmental resource management. This
coverage provides a valuable data layer for ARC/INFO polygon coverage in an Albers projection.
[ID # 78, App. 4]
3.2.2A Flooding and Erosion: Canadian Holdings
Canadian Great Lakes Coastal Zone Database, Environment Canada: The purpose of the
database is to view the Great Lakes environment in an integrative manner to identify and analyse
those areas susceptible to fluctuating water levels, flooding, and erosion. The database is housed
in a GIS and includes the Canadian shoreline, a land-use overlay, a bathymetry overlay, and the
SOLEC '96 - Information and Information Management 13
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100-year floodline/erosion hazard lines. (International Joint Commission 1989) [ID # 25, App. 4]
Canadian Great Lakes Shoreline Classification Database, Environment Canada: This database
was used in assessing the impact that changes in lake level ranges would have on erosion at given
locations. Each of 2,000 reaches is classified according to geomorphic type, proportion of
shoreline that has been protected from flooding and/or erosion, and subaqueous/nearshore
composition. (Note: This database has a complementary U.S. counterpart.) (Levels Reference
Study Board 1993) [ID # 24, App. 4]
Canada/Ontario Flood Damage Reduction Program, Environment Canada and the Ontario
Ministry of Natural Resources: The data set was developed to reduce flood damage and risk of
loss of life along Ontario rivers and lakes by mapping flood-risk areas where development should
be discouraged. Map attributes contain topographic map features that include contours, wooded
areas, buildings, roads, wetland symbols, usual water extent of rivers, regulatory flood line, point
elevations, and georeferences. (Environment Canada 1996a) [ID # 26, App. 4]
Canada/Ontario Great Lakes Erosion Monitoring Program Final Report, Government of
Canada and Province of Ontario: The program monitored and assessed erosion on the Great
Lakes Canadian shoreline from 1973 to 1980 at 162 sites, intended to represent the entire erodible
shore from Port Severn on Georgian Bay to Kingston on Lake Ontario. (Boyd 1981) [ID #141,
App. 4]
Coastal Zone Atlas and Canada/Ontario Great Lakes Shore Damage Survey, Ontario
Ministry of Natural Resources and Environment Canada: The nature and extent of damages
during a period of high lake levels were surveyed, along with shoreline characteristics, and
preliminary recommendations were made. These recommendations were aimed at more effective
shoreline management. The results are presented graphically in this coastal zone atlas and
discussed in detail in a technical report of the survey. (Boulden 1976) [ID # 28, App. 4]
Littoral Cell Definition and Sediment Budget for Ontario's Great Lakes: This study
addresses the littoral cell definition (an area under the continuous influence of specific longshore
currents) and sediment budget for Ontario's Great Lakes. Objectives of the study include defining
the limits of littoral cells and estimating subcells (for all of Ontario's Great Lakes shorelines),
estimating sediment budgets for the littoral cells, and identifying areas that warrant further
detailed studies. (Ontario Ministry of Natural Resources 1996) [ID # 118, App. 4]
3.2.2B Flooding and Erosion: U.S. Holdings
Shore Protection Information: The U.S. Army COE Detroit District's "Low Cost Shore
Protection: A Property Owner's Guide"; "Low Cost Shore Protection: A Guide for Local
Government Officials," and "Low Cost Shore Protection: A Guide for Engineers and
Contractors," include information pertinent to these groups, as well as lists of information sources
and government agencies. These reports are the latest products of the U.S. Army COE's
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long-term commitment to coastal planning and engineering. [ID # 57, App. 4]
Wisconsin Floodplain Zoning Database: The Wisconsin DNR Bureau of Water Regulation and
Zoning is the custodian for the Floodplain Zoning geographic data layer. The Federal Emergency
Management Agency (FEMA) produced the hard-copy Flood Insurance Report. The WiDNR
Bureau of Water Regulation and Zoning is prepared to assist other Wisconsin counties in
developing digital floodplain maps that more accurately match improved base and topographic
mapping. [ID # 121, App. 4]
Lake Erie Shoreline Erosion Control Structures Database: The Ohio Department of Natural
Resources, Division of Engineering developed this database to maintain records and track
installation of erosion control structures along Lake Erie's shoreline. Database attributes include
applicant's name and address; proposed type and material of structure; project location; U.S.
Army COE permit number; and dates that application was received and permit granted. [ID # 52,
App.4]
Annual Coastal Monitoring of Beach and Nearshore Changes at North Point Marina,
Illinois Coast of Lake Michigan, Illinois Department of Conservation: The purpose of this
database is to monitor beach and nearshore accretion and erosion near the newly constructed
(1987) North Point Marina. This database will be used to assist in remedial action and mitigation
of adverse impacts. [ID # 7, App. 4]
3.2.3A Wildlife and Wildlife Habitat: Canadian Holdings
Survey of Migrant Waterfowl on the Great Lakes, Environment Canada, Canadian Wildlife
Science Division: Surveys are conducted to establish spatial and temporal distribution of use of
the Great Lakes shoreline by migrating waterfowl. The database includes counts of waterfowl
species, or species group, in standardized shoreline sectors from the Quebec border to Tobermory
on Lake Huron. [ID # 20, App. 4]
Christmas Bird Count, National Audubon Society: Teams or "parties" of birdwatchers find,
count, and report as many birds as possible within a 24 km (15 mile) diameter circle, of which an
estimated 20-25 touch the Canadian Great Lakes shoreline. Each Christmas Bird Count is
organized locally, usually by the area naturalist club, and the data collected are sent to the
National Audubon Society in the U.S. (Cadman 1995) [ID # 78, App. 4]
Atlas of Colonial Waterbirds Nesting on the Canadian Great Lakes, Environment Canada,
Canadian Wildlife Service: This five-part atlas includes information on cormorants, gulls, and
island-nesting terns on Lake Superior, Lake Huron (1989), and the lower Great Lakes (1990) and
on marsh nesting terns on Lake Huron and the lower Great Lakes (1991). It also includes data on
SOLEC '96 - Information and Information Management 15
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herons and egrets in the Great Lakes system from 1989 to 1991. (Blokpoel and Tessier 1993)
[ID#21,App. 4]
Atlas of Contaminants in Eggs of Fish-Eating Colonial Birds of the Great Lakes,
Environment Canada, Canadian Wildlife Service: Each year, beginning in 1970, eggs were
collected from fish-eating colonial waterbirds from 50 colonies throughout the Great Lakes to
measure the levels of chlorinated hydrocarbons and lipid concentrations present in these eggs. The
purpose of the study was to understand the temporal and spatial trends in environmental
contaminant levels in biota of the Great Lakes. The atlas is organized in two parts: by contaminant
and by locations. Summaries currently exist for the time periods of 1970-88 and 1989-92. (Bishop
etal. 1992) [ID # 52, App. 4]
Wildlife Toxicology Database, Environment Canada, Environmental Conservation Branch:
Research has been conducted on topics of wildlife concern, such as the effects of toxic chemicals
on the bald eagle, the herring gull, amphibians, and species of birds that inhabit fields and
orchards. This type of wildlife research and monitoring activity is vital to understanding the
biological impact of activities that affect environmental sustainability. (Environment Canada
1996a) [ID #41, App. 4]
Marsh Monitoring Program, Environment Canada and the Long Point Bird Observatory: The
goal of the program is to have routes located throughout the Great Lakes basin monitored
annually on a long-term basis by volunteer surveyors. The information gained will provide needed
baseline data on habitat associations and population changes of indicator species, such as marsh
birds and amphibians. (Cadman 1995) [ID # 27, App. 4]
3.2.3B Wildlife and Wildlife Habitat: U.S. Holdings
Wildlife Mortality Information System Database (WILDMORT): NBS, National Wildlife
Health Center, Madison, Wisconsin, maintains this database to describe and understand the status
and trends of the nation's biota and to provide that information to decision makers in a form that
allows them to assess biological consequences of various policies and management practices. The
database provides a historical record of wildlife mortality in the United States and can be used to
identify trends/cycles in disease outbreaks and to provide information for management activities.
[ID # 40, App. 4]
Wisconsin Department of Natural Resources Deer Management Units Database: The
Wisconsin DNR is the custodian for the WiDNR statewide Deer Management Unit data layer,
which includes state and local roads, hydrography, railways, and county boundaries. Attribute
data include polygon unit codes and boundary codes for line features. [ID #115, App. 4]
North American Bird Banding Program Database, NBS, Population Inventory and
Monitoring Bird Banding Lab: Maintains records of all birds banded in North America and
16 SOLEC '96 - Information and Information Management
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records of all North American banded birds recovered. Purpose of database is to provide
information on avian survival, movement, and behaviour. Applications include promulgating
hunting regulations, monitoring populations, restoring endangered species, studying effects of
environmental contaminants, and addressing issues of human health, safety, and economy. [ID #
41, App. 4]
Annual Herpetological Index Database, maintained by the NBS: Purpose of the database is to
catalogue current herpetological publications for use by researchers and managers. [ID #35,
App. 4]
Ohio Natural Heritage Data Base: The Ohio Department of Natural Resources, Division of
Natural Areas and Preserves, developed this database to help identify and protect Ohio's rare
species and unique natural features. About 68 percent represent Ohio locations for rare plants, 22
percent are records for rare animals, and the remaining 10 percent include records for high-quality
plant communities, unique geologic features, breeding/non-breeding animal concentrations, and
other miscellaneous features. [ID # 53, App. 4]
3.2.4A Soils: Canadian Holdings
Digital Soils Database, Ontario Ministry of Agriculture, Food and Rural Affairs Resources and
Planning Branch: The database differentiates various soil types and contains information on their
physical and chemical composition along with specific landscape features for each soil unit.
Coverage has been referenced to the UTM grid (NAD27), on the 1:50,000 NTS sheets, although
original survey scale varies for each county. Digital coverage exists at the county level for most of
Southwestern Ontario. (Survey Results 1996) [ID # 92, App. 4]
3.2.4B Soils: U.S. Holdings
Wisconsin Soils Database: The database contains available statewide Wisconsin soils data. The
Wisconsin State Soil Geographic Database (STATSGO) is maintained by the U.S. Department of
Agriculture (USDA), Soil Conservation Service (SCS), Soils Section in Madison, but can also be
obtained through the WiDNR. [ID # 69, App. 4]
The USDA/Natural Resources Conservation Service (NRCS) Soil Survey Geographic
Database (SSURGO), the most detailed level of digital soils data, is currently under
development. Information about the content and status of SSURGO data, County/Project Area
soils data, as well as a variety of other GIS data, can be accessed via the NRCS Node to the
NSDI (National Spatial Data Infrastructure). [ID # 68, App. 4]
Groundwater Contamination Susceptibility Model: This model was designed to be used
primarily for regional, multi-state, river basin, state, and multi-county resource planning,
SOLEC '96 - Information and Information Management 17
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management, and monitoring. The USDA/NRCS maintains information on soil components,
layers, and other related information. The tabular data primarily provide information about map
unit acreage, the proportionate extent of soil components in each map unit, and soil properties
and interpretation data. [ID # 70, App. 4]
GCSM-Related Soils Database: The information in these data sets was developed specifically
for the Groundwater Contamination Susceptibility Model (GCSM) for Wisconsin. The Wisconsin
STATSGO is recommended for general use. Metadata is available for soils data layers in a form
consistent with the Federal Geographic Data Committee's Content Standard for Digital Geospatial
Metadata. Metadata structure information is available describing the format and structure of
metadata provided. [ID # 114, App. 4]
3.3 Impacts of Changing Land Use
3.3A Impacts of Changing Land Use: Canadian Holdings
Inventory and Assessment of Land Uses and Shoreline Management Practices,
Environment Canada, Environmental Services Branch: The inventory was collected in an effort to
review and assess patterns of shoreline uses and shoreline management practices on the Canadian
shoreline of the Great Lakes-St. Lawrence River basin. The investigation of land use included an
inventory and assessment of existing land uses and an investigation of past land-use changes and
projected future trends. (Ecologistics Limited 1992) [ID # 44, App. 4]
Natural Heritage Information System (NHIS): This database provides information on locations
and sites of protected areas (parks, Areas of Natural and Scientific Interest (ANSI), International
Biological Program Sites, environmentally sensitive areas, land protected by non-governmental
organizations and conservation authorities, rare species and their habitats, and species at risk).
(Ball 1995) [ID #119, App. 4]
National Conservation Areas Database, Environment Canada, Environmental Reporting: Areas
protected by federal and provincial governments, conservation authorities, and many non-
government agencies. (Ball 1995) [ID # 29, App. 4]
Protected Areas and Areas of Natural and Scientific Interest Databases, Ontario Ministry of
Natural Resources, Natural Heritage Policy Branch: This is a series of databases including the
Ontario Provincial Parks database, Conservation Areas Guide, Parks and Other Provincially
owned Protected Natural Areas Database, and ANSI database. (Ball 1995) [ID # 123, App. 4]
3.3B Impacts of Changing Land Use: U.S. Holdings
Wisconsin Land Use and Land Cover Digital Database: The US Geological Survey (USGS)
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has produced a digital representation of land use and land cover called "Land Use and Land Cover
Digital Data." Surface features are classified into 24 categories, which can be generalized into 6
major classes. Minimum area size for inclusion in the database was 4 hectares (10 acres) for urban
and water features and 16 hectares (40 acres) for all others. [ID #71, App. 4]
Rural Land Cover Vegetation Mapping GIS Data Set: This is currently under development by
WiDNR and other partners cooperating in WISCLAND (Wisconsin Initiative for Statewide
Cooperation on Landscape Analysis and Data). [ID # 113, App. 4]
Predicting Consequences of Land Management Practices on Water Quality: The US
Department of Agriculture, Agriculture Research Service, conducts research in watershed
engineering, soil management, water management, and air pollution control. [ID # 63, App. 4]
Agricultural Conservation and Environmental Programs: The U.S. Department of
Agriculture, Agricultural Stabilization and Conservation Service, maintains information and data
on its four major conservation programs: 1) agricultural conservation programs to support
conservation practices that solve soil, water, energy conservation and other environmental
problems; 2) Water Bank Program to conserve water and preserve and improve migratory
waterfowl habitat; 3) Forestry Incentives Program to encourage development of non-industrial
private forest lands; and 4) Rural Clean Water Program to control agricultural non-point source
pollution and improve water quality in rural areas. [ID # 62, App. 4]
Management of National Forest System Great Lakes Basin Lands for the Sustained Yields
of Renewable Resources: The U.S. Department of Agriculture, Forest Service, collects
information and databases about water, wildlife, timber, and recreational facilities. [ID # 64, App.
4]
Natural Resources Conservation Service National Resources Inventory: Assessments are
completed at five-year intervals. The inventory contains information on wetlands, land use, and
erosion patterns. Most of the information is summarized by state or major land resource areas.
[ID # 65, App. 4]
The Michigan Resource Inventory Program (MRIP) Database: This database has been
developed within the Land and Water Management Division, Michigan Department of Natural
Resources (MDNR). This effort is also known as the Michigan Resource Information System
(MIRIS). [ID # 33, App. 4]
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3.4 Coastal Wetlands
3.4A Coastal Wetlands: Canadian Holdings
Ontario Wetland Map Series, Federation of Ontario Naturalists: Data consist of 125 map sheets
covering Southern Ontario. They show location and boundaries of all wetlands in 1982; all
wetland losses since European settlement; and more recent wetland losses and gains.
Subcategories of marsh and swamp areas, and losses and conversion of uses were also identified
to provide comprehensive regional-scale coverage of wetland extent and conversion in Southern
Ontario in order to assist wetland policy and program decisions and provide a baseline for future
monitoring. (Environment Canada, Canadian Wildlife Service 1995) [ID # 56, App. 4]
Wetland Evaluation Information Management System: Contains data required for Ontario
Wetland Evaluation System, including selected ecological, social, and hydrological parameters of
individual wetlands and wetland complexes. Also contains documented occurrences of rare,
threatened, endangered, and significant species for the wetland or wetland complex (Environment
Canada, Canadian Wildlife Service 1995) [ID # 125, App. 4]
Lake Erie Basin Wetlands Digital Maps, Environment Canada, Environmental Services
Branch: The purpose of this database is to identify significant wetlands in the Canadian Lake Erie
basin that are potentially threatened by surface water contamination and to regionally target the
rural non-point sediment sources where remedial programs would be most effective. Data sets
required for this study included wetland location, wetland significance, locations of contaminant
sources, and estimates of the likelihood of a contaminant reaching a wetland. (Environment
Canada, Canadian Wildlife Service 1995) [ID # 45, App. 4]
Wetland, Agricultural Land Use, and Waterfowl Database, Ducks Unlimited Canada: The
database was designed to help plan improvements to habitat and intensively farmed areas of the
Great Lakes-St. Lawrence River waterfowl zone in Southern Ontario. This project compiled
mapped data on agricultural type, wetland extent, and resident waterfowl populations, as
background to build an effective waterfowl management plan tailored to regional differences.
(Environment Canada, Canadian Wildlife Service 1995) [ID # 12, App. 4]
Historical Coastal Wetland Database, Environment Canada, Canadian Wildlife Service, and
Snell and Cecil Environmental Research: The main focus was to analyse changes in wetland
quality, quantity, value, and function due to water-level fluctuations for six specific sites (St. Clair
Marsh, Lake St. Clair; Big Creek-Holiday Beach, Lake Erie; Rondeau Shores, Lake Erie; Turkey
Point, Lake Erie; Oshawa Second Marsh, Lake Ontario; and Presqu'ile Marsh, Lake Ontario).
Five to seven different years of air photos were used to identify and map up to 14
different classes of vegetation communities and up to 18 adjacent land-use types. (Environment
Canada, Canadian Wildlife Service 1995) [ID # 22, App. 4]
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3.4B Coastal Wetlands: U.S. Holdings
Interactions of Biotic and Abiotic components in Great Lakes Wetlands and Nearshore
Aquatic Habitats, U.S. Geological Survey-National Biological Service and the U.S. Fish and
Wildlife Service: This database investigates the interactions between abiotic components in the
nearshore zone and the biotic communities they support. [ID # 110, App. 4]
National Wetlands Inventory Maps and Metadata Database, U.S. Fish and Wildlife Service:
This database is used to track the status of wetland mapping by the National Wetlands Inventory
(NWI). Most of the database's maps correspond to 7.5 minute quad maps and are at a scale of
1:24,000. The database is used to track mapping and map updating efforts, and to produce maps
showing the status of wetland mapping. The database is updated weekly. [ID # 102, App 4]
3.5 Other (Canadian and U.S. Holdings)
3.5.1 Weather and Climate Data
Ontario Meteorological and Climatic Data, Environment Canada, Environmental Services
Branch: Measurements of hourly temperature, dew point, precipitation, visibility, cloud height,
amount and opacity, wind direction and speed, barometric pressure and the three-hour pressure
tendency are made by human observers at 34 stations, near the ground, in Ontario. Measurements
of the upper air are made at two stations. Most of the elements measured at the staffed stations
are also recorded automatically through electronic equipment at 60 additional stations.
(Environment Canada 1996a) [ID # 47, App. 4 - Canadian]
Stability Array (STAR) Meteorological Stations for the Conterminous United States, US
Environmental Protection Agency: The dataset summarizes National Weather Service data for
meteorological stations. Data for STAR meteorological stations includes joint frequencies of six
windspeeds, 16 wind directions, and six stability classes. These data elements were recorded on an
hourly basis for each station and stored in yearly files for use on EPA's Graphical Exposure
Modeling System. [ID # 83, App. 4 - U.S.]
3.5.2 Air
Integrated Atmospheric Deposition Network Database, U.S. Environmental Protection
Agency: Monitoring (1990 to the present) of regional trends in toxics deposited in the Great
Lakes via the atmosphere, made up of five master sites and eleven satellite stations. They are
located on land between 1 and 5 km (between 0.6 and 3 miles) from the lake. Monthly
concentrations of atmospheric deposition are measured in vapour, rain/snow, and particles.
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Compounds measured are PCBs, PAHs, some pesticides such as aldrin, dieldrin, DDT, lindane,
and some metals including lead, arsenic, and cadmium. (Survey Results 1996) [ID # 77, App. 4 -
U.S.]
Great Lakes Regional Air Toxics Emissions Inventory, U.S. Environmental Protection Agency
and the air regulatory agencies of the eight Great Lakes states: This inventory will be used to: 1)
successfully implement the key provisions of the Great Lakes Toxic Substances Control
Agreement, and 2) assess the atmospheric deposition to the Great Lakes under the efforts of the
U.S. EPA's Great Waters Program. [ID # 89, App. 4 - U.S.]
3.5.3 Nearshore Ecosystem
Wisconsin Department of Natural Resources GIS Database: The purpose of this database is
to provide tools for spatial data management and analysis for use in departmental policy
evaluation, decision-making, program management, and operations. WiDNR also provides certain
GIS data-sharing services to the public as required under Wisconsin's Open Records Law. [ID #
116, App. 4-U.S.]
Wisconsin Dam Inventory Database: The WiDNR Bureau of Water Regulation and Zoning
(WRZ) is the custodian for the state's dam inventory, which is maintained in tabular form in an
ORACLE database. The inventory contains locational information for over 3,500 large and small
dams in Wisconsin, but does not include detention ponds or dams located away from a waterway.
The dam inventory database contains a variety of attributes regarding dams, such as owner and
contact information, nearest town downstream, county, stream name, hazard rating, emergency
planning status, height, size, water volume, and DNR inspection history. Dam inventory data are
available from the bureau custodian. [ID # 120, App. 4 - U.S.]
Michigan Department of Environmental Quality GIS Database: The Environmental
Response Division effectively determines, evaluates, and controls risk to the environment and to
the health, safely, and welfare of Michigan's citizens by carrying out cleanup or other response
activities at sites of environmental contamination by promoting redevelopment of contaminated
sites and by developing and managing information about chemicals in the environment. [ID # 29,
App. 4-U.S.]
Wisconsin State Forest Stands Database: The Wisconsin DNR Bureau of Forestry is the
custodian for the State Forest Stand Map geographic data layer, with coverage available for
Wisconsin's six major state forests: Northern Highland American Legion, Brule River, Flambeau
River, Black River, Kettle Moraine South and North. The database contains over 25 items, such
as site index, primary cover type, primary cover size, board feet per acre, cords per acre. [ID #
118, App. 4-U.S.]
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The National PLANTS Database, USDA/NRCS: This database provides a single source of
standardized information about plants. PLANTS standardized information permits scientists and
other persons interested in plants across disciplines to freely exchange accurate plant-related
information. The purpose of the PLANTS database system is to provide plant information to
NRCS's natural resource conservation efforts, NRCS clients, cooperating agencies, and the
public. [ID #67, App. 4-U.S.]
Forest Inventory and Analysis: The U.S. Department of Agriculture, Forest Service, Southern
Forest Experiment Station, Forest Inventory and Analysis research unit began to map forest land
distributions for the United States. The project was performed in support of the Forest and
Rangeland Renewable Resources Planning Act 1993 Assessment Update program to provide
information on current forest and rangeland conditions. [ID # 66, App. 4 - U.S.]
4.0 Nearshore Data Needs and Gaps
The previous section identifies existing data and information for the nearshore zone of the Great
Lakes. It does not, however, indicate the value of these databases for assessing the state of the
nearshore ecosystem, nor does it address what information is needed but not available.
In order to measure or monitor the state of the nearshore in terms of the health of aquatic and
terrestrial communities and the physical, chemical, and biological habitat, and to examine the
stressors that affect them (such as exotic species and human activities together with underlying
socio-economic aspects), a set of indicators were proposed at SOLEC '94. These indicators were
expanded and built upon in an International Joint Commission (IJC) report titled "Indicators to
Evaluate Progress under the Great Lakes Water Quality Agreement" (International Joint
Commission 1996).
In addition, the lead authors of four SOLEC reports for SOLEC '96 have attempted to develop
indicators specifically for the nearshore of the Great Lakes. On the basis of the indicators
suggested by these authors and on those in the IJC report, the following section attempts to
identify data needs and gaps in the information needed to measure and monitor the nearshore
ecosystem. The tables that follow (Tables 1-4) identify the proposed indicators and the data
needed to measure these indicators (taken from the respective SOLEC papers, Edsall and
Charlton 1996, Reid and Holland 1996, Maynard and Wilcox 1996, Rivers and Thorp 1996 and
from International Joint Commission 1996). Using the information provided above in section 3.0,
we have attempted to identify data gaps for each indicator specified and to rate how well the
existing information meets the indicator's data requirements.
Please note that the purpose of this section is not to evaluate the indicators proposed, but rather
to determine the status of the information required to measure these indicators. In many cases
indicators are chosen or used because information exists.
SOLEC '96 - Information and Information Management 23
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The following tables identify the indicator, and the data needed to measure the indicator. The
table also includes a column which gives a rating of how well the data needs are being met. A
"good" rating indicates that data is universally available in a usable form; "fair" indicates the basic
data are available but that there are significant gaps in the data or the data is out of date. A "poor"
rating indicates that the data is not available at all or is severely deficient. Finally the table includes
a "Data Gaps" column which identifies major known gaps to the data requirements.
24 SOLEC '96 - Information and Information Management
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4.1 Nearshore Waters Indicators and Identified Data/Information Needs and Gaps
Table 1 Nearshore Waters
Desired
Outcome
Indicators
Data Needed
Rating
Data Gaps
Healthy human
populations
Fish consumption
advisories
Beach closings,
measured in median
number of
consecutive days
closed for a given
year
Drinking water purity
Contaminant levels in edible fish and
wildlife.
Total number of sport or commercial
species that have advisories.
Total geographic area that is restricted for
commercial fishing because offish
consumption advisories.
Fair
No basin-wide application of standardized
fish consumption advisories exists.
Limited amounts of data are available.
Beach closings based on the measurement
of the following:
• coliform count
• turbidity
• phosphorus concentrations
• aesthetics
• beach characteristics
Fair
No standardized reporting method of
beach status by geographic unit (e.g.,
beach number). Such a standard would
permit better interpretation of local and
basin-wide trends.
Limited amounts of data are available.
Bacterial count in treated drinking water.
Reports of human illness or infectious
diseases due to consumption of treated
water.
Number of warnings of water consumption
limitation.
Incidence of taste and odour problems in
treated water, based on public surveys and
complaints, measurement of biomass,
biomass composition and/or chlorophyll.
Reports of spill, process upsets, and other
incidents that release anthropogenic
chemicals into the raw water supply that
could threaten a drinking water treatment
plant.
Concentration of anthropogenic chemicals
in the raw water.
Treatment-plant closures.
Amount of treatment at the plant.
Good
Very little information on taste and odour.
Data on bacteria levels and many
chemicals are available form the Drinking
Water Surveillance Program and H2O
treatment plants.
Data on some chemicals is of limited use
due to high detection levels.
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Table 1 Nearshore Waters (continued)
Desired
Outcome
Indicators
Data Needed
Rating
Data Gaps
Healthy human
populations
(cont.)
Acute human illness
associated with locally
high levels of
contaminants
and/or
Chronic human illness
associated with long-
term exposure to low
levels of contaminants
Number of times established standards
for microbial, chemical, and radiological
contamination were exceeded.
Measurements include bacterial counts at
public beaches and number of beach-day
closings.
Number of people affected by waterborne
microbial diseases.
Toxic substance levels in human tissue,
especially those of exposed populations
(e.g., fish eaters).
Toxic contamination levels in human
breast milk.
Number of exceedances of established
air quality standards.
Hospital admissions for acute respiratory
distress of young children.
Poor to
Fair
Available references agree that more
research must be done specifically to study
the effects of environmental stresses on
human health, particularly with respect to
the effects of long-term exposure to complex
mixtures of low levels of toxic contaminants
(International Joint Commission 1996).
A limited amount of human health
information is available.
Healthy fish and
wildlife
Status of exotic
species
Cumulative number of exotic species
introduced.
Distribution and abundance of exotic
species in nearshore waters.
Annual control costs.
Effect on the ecosystem of exotic species.
Fair
More quantitative and reliable information on
the effects of each exotic species on native
species and communities is required.
More information on other potential invading
species is needed to help develop strategies
to prevent their entry and establishment.
Better status information and better control
methods are required.
26
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Table 1 Nearshore Waters (continued)
Desired
Outcome
Indicators
Data Needed
Rating
Data Gaps
Healthy fish and
wildlife (cont.)
Status of native
species and their
habitats
Number and abundance of endangered native
species, including fish, waterfowl, plants and
invertebrates.
Presence and abundance of selected native
indicator species representative of unimpaired
ologotropic and mesotrophic habitats in the
nearshore waters (e.g., lake trout, burrowing
mayfly).
Quantity and quality of particular habitat types
(e.g., wetlands and spawning habitat for desirable
native species).
Fish harvest statistics vs. spawning vs. biomass
levels.
Toxic contaminant levels in selected fish species
and in selected fish-eating birds.
Ambient phosphorus concentrations in the
nearshore water and sediment of the Great
Lakes.
Fair
Nearshore aquatic habitat
classification and mapping.
Virtual
elimination of
persistent toxic
substances
Levels of persistent
toxic chemicals
Quantities of persistent toxic substances
produced, used, and disposed of.
Total loadings of persistent toxic substances in
the Great Lakes system.
Concentration of persistent toxic substances in
non-biological ecosystem compartments (water,
sediment).
Fair
Concentrations of
persistent toxic
substances in biota
Concentrations of persistent toxic substances in
top predator fish and fish-eating birds.
Biochemical measures of changes in cellular or
subcellular processes within individual organs or
tissues of an organism.
Measurable changes in the development,
behaviour, reproductive success, or survival of
species (e.g., tumours, other visible deformities).
Fair
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Table 1 Nearshore Waters (continued)
Desired
Outcome
Absence of
excess nutrient
loading, leading
to cultural
eutrophication
Indicators
Dissolved oxygen
depletion of bottom
waters
Water clarity/algal
blooms
Data Needed
Ambient phosphorus concentrations in
selected areas of the Great Lakes
nearshore.
Phosphorus loading and effluent
information for point and non-point
sources.
Ambient water dissolved oxygen
concentrations.
Identified algal blooms from remote-
sensing and satellite imagery.
Reports of nuisance algal growth.
Beach closings due to excessive algal
growth.
Rating
Fair
Fair
Data Gaps
Sources: For Indicators, Edsall and Charlton 1996.
For Data Needed, modified from International Joint Commission 1996.
28
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4.2 Land by the Lakes Indicators, Data Needs and Gaps
The nearshore terrestrial paper, "Land by the Lakes," identifies three tiers of indicators of overall ecosystem health.
Table 2 Land by the Lakes
Desired
Outcome
Indicators
Data Needed
Rating
Data Gaps
A diversity of
coastal
physical
features and
unique
biological
components
within
ecoregions
Representation of
significant coastal
physical features and
biological diversity
within ecoregions
A uniform classification system that provides
biodiversity, stressor, and stewardship activity
information in addition to physical descriptors.
Community and species inventories throughout the
basin.
Fair
In the U.S., state Natural Heritage
Programs are continuing to inventory
unique areas in Ohio and New York,
where little field work has thus far been
done. In other states, inventories
continue on a local basis. Ecoregional
classification completed for Michigan,
Minnesota, and Wisconsin.
In Canada - community classification
under development (Bakowsky and Lee,
1996; Racey etal., 1995, etc.);
inventories incomplete.
Preservation
of significant
coastal
ecological
communities
and species
Summary of
stewardship activities
and stressors
Basinwide pre-European settlement biological data
to provide a basis for comparison with the present
landscape.
Inventories of all significant ecological communities
and their components and functions.
Analyses of stressors and sources of stress
affecting significant ecological communities.
Analyses of quantity and quality of protection
efforts.
Poor
In the U.S., Michigan Natural Features
Inventory mapping pre-European
settlement data; information spotty for
other states; inventories for some
communities complete in some states
(Michigan Lakeplain Prairie
communities); stressors and sources of
stress being analysed by The Nature
Conservancy Great Lakes Office for
several communities; no current
analysis of protection efforts; no
comprehensive analysis for the coastal
region.
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Table 2 Land by the Lakes (continued)
Desired
Outcome
Preservation
of significant
coastal
ecological
communities
and species
(cont.)
Overall
ecosystem
health
Indicators
Balance of
stewardship activities
and stressors (cont.)
Loss of significant
ecological
communities and
species
Interruption of
shoreline processes by
lake edge armouring
Representation of
coastal biodiversity
within parks and
protected areas
Gains in biodiversity
investment areas
protected
Data Needed
Inventories of significant shoreline ecological
communities and species.
Analyses of effects of shoreline processes by lake
edge armouring.
Measurement of biodiversity in parks and protected
areas.
Measurement of biodiversity investment area
protection efforts.
Rating
Poor
Fair
Poor
Poor
Data Gaps
In Canada, little pre-European
settlement data mapped; inventories
incomplete, particularly in northern Lake
Superior; no current analysis of
stressors, sources of stress, or
protection efforts.
Source: Reid and Holland 1996.
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4.3 Coastal Wetlands
Table 3 Coastal Wetlands
Desired
Outcome
Indicators
Data Needed
Rating
Data Gaps
Preservation
of wetland
area
Land-use changes,
encroachment
/development basin-
wide.
Landscape stressors
Wetland size,
abundance, and
susceptibility to threats
along its border
Remote-sensed imagery (aerial photographs,
satellite imagery) overtime to determine changes in
landscape and encroachment on wetlands, (e.g.,
conversion of wetlands to agricultural, urban, and
industrial land uses; upland development; shoreline
development; deforestation; road construction; dam
construction).
Good
For some locations, imagery is available
for numerous years, but is expensive to
purchase for large areas. For other
locations, imagery is limited.
Road density in the wetland watershed.
Extent of shoreline modification.
Changes in the status of protective barriers.
Proximity to navigable channels and recreational
boating activity.
Hydrologic connectivity with the lake.
Good
Although data are largely available, the
analysis of such data has been limited.
Digital wetland data from remote-sensed data in a
geographic information system (GIS) to determine:
• changes in wetland area overtime
• number of wetlands within a given area
• ratio of area to perimeter of wetland
Areas protected under the North American Wildfowl
Management Plan.
Ongoing inventory and status summary.
Fair
Digital wetlands mapping is available
only for some parts of the Great Lakes
shoreline.
Wetland
quality
Flooding and
dewatering of wetland
Water level data.
Ground elevations.
Nearshore bathymetry.
Fair
Detailed nearshore bathymetry
especially in the 0 to 2 metre (6.5 feet)
range.
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Table 3 Coastal Wetlands (continued)
Desired
Outcome
Wetland
quality
(cont.)
Healthy
habitat
Indicators
Protection from erosive
forces
Levels of persistent
toxic chemicals
Status of plant
communities
Status of individual
plant taxa
Data Needed
Sediment supply in the littoral drift.
Substrate type and particle size.
• Fetch.
Exposure to wave attack.
Shoreline slope.
Concentration of nutrients and toxic substances in
sediments, including carbon, total particulate
nitrogen, ammonium, nitrate-nitrite, soluble reactive
phosphorus, organic contaminant, and heavy
metals.
Nearshore water quality determinations of turbidity,
total suspended solids, total organic carbon, total
particulate carbon, ammonium, nitrate-nitrite, total
phosphorus, soluble reactive phosphorus, dissolved
oxygen pH, alkalinity, conductivity, temperature,
organic contaminants, and heavy metals.
Extent and percentage of each major vegetation
type.
Changes in vegetation types over time.
Plant species richness.
Species dominance (percentage cover) of plant
taxa.
Growth form of plant communities.
Presence of detrital plant material.
Presence or absence of rare taxa.
Presence or absence of invasive species.
Expansion or spread of invasive species.
Rating
Fair to
good
Fair
Fair to
good
Data Gaps
Data are available in some areas; not in
others.
Some data are available for specific
sites of interest, but are largely lacking
elsewhere.
Some data are available for specific
sites of interest, but are largely lacking
elsewhere.
Inventories are available in Michigan and
Ohio, but largely lacking elsewhere. No
data on expansion or spread.
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Table 3 Coastal Wetlands (continued)
Desired
Outcome
Indicators
Data Needed
Rating
Data Gaps
Healthy fish
and wildlife
Status of species
typical of a Great
Lakes wetland
Status of exotic
species
Concentrations of
persistent toxic
substances in biota
Presence or dominance of species tolerant of
degraded environmental conditions (e.g., percent of
turbidity-tolerant fish).
Stability of a faunal community productivity as
measured in biomass offish or emergence rate of
aquatic insects.
Population survival and mortality.
Ratios of guilds or traits (e.g., pelagic vs. benthic
fish ratio, predator vs. prey ratio).
Fair
Some data are available for specific
sites of interest, but are largely lacking
elsewhere.
Cumulative number of exotic species introduced.
Distribution and abundance of exotic species in
nearshore waters.
Annual control costs.
Effect of exotic species on the ecosystem.
Poor
More quantitative and reliable
information on the effect of each exotic
species on native species and
communities is required.
More information on other potential
invading species is needed to help
develop strategies to prevent their entry
and establishment.
Better status information and better
control methods are required.
Concentrations of persistent toxic substances in top
predator fish and fish-eating birds.
Biochemical measures of changes in cellular or
subcellular processes within individual organs or
tissues of an organism.
Measurable changes in the development,
behaviour, reproductive success, or survival of
species (e.g., tumours, other visible deformities).
Fair
Some data are available for specific
sites of interest, but are largely lacking
elsewhere.
Source: Maynard and Wilcox 1996.
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4.4 Impacts of Changing Land Use
Table 4 Impacts of Changing Land Use
Desired
Outcome
Efficient
urban
development
Indicators
Urban population
densities
Suburban land
conversion
Centre town economy
Brownfields
Recreation opportunity
Energy Use
Waste created
Wastewater quality
Industrial water use
Residential water use
Traffic congestion
Transit use
Data Needed
Urban populations per area.
Land conversion rates.
Fiscal condition/vacancies/etc.
Number and area.
Number and area of parks.
Energy usage per capita.
Residential and industrial waste.
Loadings of nutrients and toxics
Volume per facility/per capita
Volume per household
Time spent commuting
Public transit commuting rates
Rating
Good
Fair
Fair
Fair
Good
Good
Good
Fair
Good
Good
Fair
Good
Data Gaps
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Table 4 Impacts of Changing Land Use (continued)
Desired
Outcome
Human
Health
Protection
Indicators
Air-pollution levels
Beach closings
Land fill capacity
Stormwater quality
Sewage quality
Pollution-prevention
programs
Respiratory illness
Fish advisories
Outdoor recreation
Data Needed
Particulates and ozone levels.
Median number of consecutive days beach closed for
a given year. Measurements are based on the
following:
• coliform count
• turbidity
• phosphorus concentrations
• aesthetics
• beach characteristics
Percent capacity left in landfills around the Great
Lakes.
Loading of nutrients and toxics.
Loadings of nutrients and toxics.
Industrial and municipal programs.
Illness and mortality incidences.
Contaminant levels in edible fish and wildlife.
Total number of sport or commercial species that
have advisories.
Total geographic area that is restricted for
commercial fishing because offish consumption
advisories.
Opportunities and participation
Rating
Fair
Fair
Fair
Poor
Fair
Poor
Fair
Good
Fair
Data Gaps
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Table 4 Impacts of Changing Land Use (continued)
Desired
Outcome
Non-Human
Resource
Health
Protection
Indicators
Wetland Habitat
Agriculture and natural
land loss
Wildlife populations
Forest clearing
Forest replant and
renewal
Mineral extraction
Fisheries pressure
Hunting pressure
Hardening of land
surface
Municipal
pesticide/fertilizer use
Agriculture
pesticide/fertilizer use
Conservation tillage
Groundwater quality
Contaminated sites
Cottage/2nd home
Data Needed
Remote-sensing data showing number and
percentage increases or decreases of wetland area
overtime.
Area lost to rural development.
Species and populations
Cutting rates.
Successful forest replanting rates.
Estimated rates of depletion.
Fishing restrictions.
Number of catch.
Hunting restrictions.
Area of roads and buildings
Application rates
Application rates
Area practicing no-till.
Area/number of contaminated wells.
Improvement or degradation of existing contaminated
sites.
Increases or decreases in number of contaminated
sites.
Occupation per coastal area.
Rating
Fair
Fair
Fair
Fair
Fair
Fair
Good
Good
Poor
Fair
Good
Fair
Poor
Poor
Fair
Data Gaps
Source: Rivers and Thorp 1996.
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4.5 Information Indicators
The following table on assessing the data (Table 5) is intended to give a general idea of
how well nearshore information needs are being met overall. Four indicators have been
used: data coverage, data time frame, data applicability, and data usability.
Data coverage refers to how well the data cover the Great Lakes nearshore area. If a lot
of data are available for the entire Great Lakes shoreline, the rating is "good." If data
cover only a small portion of the Great Lakes shoreline, the rating is "poor."
Data time frame refers to how recent the data are. Ongoing monitoring programs that
collect data on a regular basis are considered "good." Data that are fairly recent but need
updating are considered "fair"; and old data are considered "poor."
Data applicability refers to how well data can be used to measure the indicators discussed
throughout section 4.0. If a lot of data are available and applicable to one or more
indicators, this is considered "good." If data can be used in support of measuring
indicators, the rating is "fair," and if the data do not measure any of the indicators
identified, they are considered "poor."
The final indicator, data usability, refers to how well the data can be used across
disciplines. If data can be used for more than one purpose and have cross-discipline
applications, the rating is "good." If the data are specific to a discipline, the rating is
"fair." If the data are collected for one unique study and have no use beyond that one
study, the rating is "poor."
4.5.1 Status of Information - General Findings
As is apparent from Appendix 4, a large amount of data is applicable to the nearshore of
the Great Lakes. However, how much these data tell us about the state of the nearshore is
debatable. Since there are at this point no set indicators for measuring the state of the
nearshore, data have generally been collected on an as-need basis by individual agencies.
International studies such as those done for the International Joint Commission have
provided major steps forward in data coverage. But unless the data-collection efforts are
repeated, the data quickly become out of date. Continuous monitoring programs provide
the best long-term data for comparison over the years; however, a number of these
programs seem to have been ended in recent years.
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Table 5 Assessing the Data
Desired
Outcome
Data to
measure all
indicators
Indicator
Data coverage
Data time frame
Data applicability
Data usability
Rating
Fair
Fair
Fair
Fair
Basis for Rating
Only a few data sets cover the entire Great Lakes shoreline. Most are
Lake or site specific. Data collected for international studies (e.g., IJC
studies or Lakewide Management Plan studies) generally have the
best data coverage.
Some long-term monitoring programs have excellent up-to-date data,
such as the water level information. Large data sets collected on a
one-time basis (e.g., shoreline classification) are becoming out of date.
Most data sets have some applicability to the indicators described
above. If they cannot be used directly, they can be used in support of
measuring the indicator.
This is a mixed bag. Some data are usable for a wide range of uses,
whereas others are specfic to particular studies.
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5.0 Nearshore Information Management
The first half of this report concentrated on information and data pertaining to the nearshore of
the Great Lakes. For this information to be of value, it needs to be readily available, reliable, and
shared effectively among partners. Managing all the data gathered for the nearshore is not a
simple task. Multiple agencies collect, analyze, and store information pertaining to the Great
Lakes. Today's electronic technology should facilitate identification and access of data sources,
and assembly of information. This section will explore some of the common issues in the
management of nearshore information.
5.1 Definition of Information Management
Simply stated, information management involves the collection, storage, manipulation, and
transfer of information and data. For the purposes of this report, information management is
considered synonymous with data management. Data management includes the following (revised
from Environment Canada 1996b):
1. creating and maintaining standards for collecting data,
2. documenting/cataloguing the data,
3. storing/archiving data,
4. accessing data,
5. integrating data,
6. securing and protecting data,
7. stewardship of data,
8. providing methods for disseminating the data.
It does not include actually observing data, nor deciding how the information should be portrayed,
visualized, or packaged.
5.2 Nearshore Information Management Issues
A number of issues have an influence on nearshore information management. These issues become
more complex given the large area of the Great Lakes and the large number of agencies,
organizations, institutions, and levels of government involved. The issues have been categorized
according to the eight functions included in the definition of data/information management.
5.2.1 Data Collection Issues
As is apparent from section 3.0 of this report, numerous agencies each gather information about
some component of the nearshore on both sides of the border. For this information to be used to
assess the state of the nearshore, it is important that the information gathered can be compared
over time and across disciplines, agencies, and countries.
Homogeneity of Data
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Homogeneity, or similarity or uniformity, of data sets is important for the comparison of data
sets. If data are collected at a similar location, using similar methodology, at a similar time each
year, such data can be compared over the years for changes. If, however, the data are collected
using different methodologies from one year to the next, comparisons of these data would be
difficult.
Inconsistencies are introduced as a result of different methodologies, standards, and collection
techniques. In many cases these inconsistencies are a result of improvements made to collection
and/or analytical techniques. For example, improvements to water sampling techniques made over
the years have allowed scientists to detect traces of chemicals that could not be measured in the
past. These inconsistencies must be assessed by all users and, if significant, must be taken into
account to eliminate bias or false conclusions.
Compatibility Among Disciplines
There are numerous disciplines collecting data for various purposes around the Great Lakes.
Generally data are collected by a discipline for a specific purpose. Trying to use data gathered by
different disciplines may not always be possible. For example, data have been collected on the
geomorphology of the shoreline, the level of shore protection, and the subaqueous or nearshore
bottom make-up. This database is a valuable resource for engineers assessing the potential impact
of water-level fluctuation along the Great Lakes shoreline; however, it may not be appropriate for
wetlands biologists for the study of nearshore habitats, since the database identifies only the
portion of the wetland that actually comes in contact with the shoreline and does not include the
area back from the shoreline. Certain agencies have primary responsibility for setting standards
and development methods for various areas of data. It is only reasonable to assume that these
agencies will generally consider their own data needs first and foremost.
Compatibility Among Agencies
Different agencies adopt different methodologies for collecting and analysing data. Often, these
differences are sufficient to prevent the combining or even comparing of data sets. For example, a
study conducted by Environment Canada and U.S. EPA (Esterby and Bertram 1993) compared
monitoring data of eight water-quality parameters of three ship laboratories on the central basin of
Lake Erie in August 1985. The study found significant differences, ranging from 30 to nearly 100
percent of the mean between the three ship laboratories for all but one of the parameters
measured. Differences such as these must always be taken into account when comparing data.
Standards, Guidelines, and Units
Standards and guidelines are often established to help alleviate some of the compatibility and
homogeneity issues described above. Standards and guidelines can be established for the way
information is collected, stored, updated, and retrieved. Standards can be helpful if everyone
agrees to adopt the same standard or, failing that, if differences between standards are adequately
documented so that users are aware of the limitations. To date, there are very few examples of set
standards for collecting data pertaining to the nearshore of the Great Lakes.
40 SOLEC '96 - Information and Information Management
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5.2.2 Documenting/Cataloguing of Data (Metadata)
The amount of data generated and stored by applications today presents serious challenges to
users of data. For researchers to make effective use of vast quantities of stored data, they need
more information about data content, such as that typically provided in an abstract of a document.
Large quantities of data become unmanageable if the user has no way of knowing what the
content of the data is, where to find it, or how to use it. The ability of scientists to make use of
these large data sets will depend on the ability to access and manage data intelligently and
efficiently.
5.2.3 Medium of Storage/Archiving
How information is stored and managed can be as important as the data itself. Data that are not
stored will be lost. Information management systems provide some method of organizing, storing,
and maintaining information. An information management system can range from a system that
manages office documents to a complex relational database management system.
From survey results, it is clear that many, if not most, of the agencies collecting data about the
Great Lakes make use of some form of electronic database management system. There is,
however, considerable diversity in the types of systems used. In some cases, the information has
been stored on a centralized mainframe using a relational database such as Oracle (e.g.,
Environment Canada's STAR— Storage and Retrieval database). In other cases, the data are
stored on a PC in whatever database management system the researcher is comfortable with (e.g.,
dBase, Access, Paradox). Often the data are stored in a spreadsheet format such as Lotus or
Excel, and in many cases, especially with historical information, the data are stored on a shelf in
hard copy (printed paper) format only.
No set guidelines for data storage, back-up, or maintenance exist among most of the agencies
compiling nearshore data. As a result, it is not uncommon for databases to have been lost or
misplaced over the years, especially when a department was reorganized or key personnel retired
or left. This ad hoc method of data management also makes it very difficult to keep track of
information sources, even within departments, let alone within the Great Lakes community.
5.2.4 Availability and Access
Availability of, and accessibility to, data and information are other issues. All the data in the world
may have been collected at great expense, but they are worthless if they are inaccessible.
Availability constraints enforced by an agency may restrict the use of data, or data simply may not
be accessible as a result of poor information management or format constraints. Other
restrictions to data access may result from the cost or ownership of the data. In addition, often
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research scientists who are using particular sets of data for publishing purposes are unwilling to
share the data with others.
Format Constraints
Although technology has in many ways improved our ability to manage information, it has also
created a number of access constraints. Because technology is changing at such a rapid rate, data
saved on a particular system one year may quickly become inaccessible if the technology changes
and the data stored are not upgraded to the new system. For example, in the late 1980s,
Environment Canada began developing a Great Lakes Coastal Zone database. Due to a lack of
funding and changes in personnel, this database was never completed. The data that do exist are
stored in a GIS format that is no longer accessible by today's systems. Until the data are
converted to the new system, they cannot be accessed. This is not an isolated case. Considerable
data have been stored on old backup tapes that can no longer be read by today's computer
systems, and in many cases data are stored by an agency in a format that cannot be easily read by
another agency using another system (e.g., SPANS GIS files are not easily read by ARC INFO).
Ownership/Propriety/Right-to-Use
The question of who owns the data can be a grey area. If one agency gathers the initial
information, another agency adds to it and manipulates the data, and another agency buys the
manipulated information, who has the rights to the data? Today's technology makes it very easy to
transfer and manipulate data. For example, Environment Canada purchased digital topographic
maps from another federal agency to use as base mapping for its shoreline sensitivity database.
The agency that provided the topographic information claimed rights to any royalties generated by
the database. This issue held up the project for over a year and has yet to be resolved. These
questions of ownership of digital data have been, and will undoubtedly continue to be, an issue for
the legal system. However, partnership arrangements for sharing data that respect the policies of
the partner agency may solve this issue. If such partnerships are not arranged, data can become
inaccessible if the assigned owner of the data is not able or willing to disseminate the information.
Along the same line are issues pertaining to the right to use data. Some data are very sensitive in
nature—for example, human health information— and cannot be distributed freely. In these cases,
very strict restrictions are placed on who has the right to use the data.
Commercialization/Revenue Questions
The question whether data, especially data collected with the use of public funds, should be free
or not is a continuing debate. So uneven are the current views that, at present, a person wishing to
obtain information may have to buy it from one agency, but find the same or similar data offered
for free by another agency. This is becoming a particularly serious issue between U.S. and Canada
since Canada is moving more towards a cost-recovery approach, whereas U.S. agencies have not
adopted this approach. This issue is causing concern that valuable data are not being used because
the agencies requiring the information cannot afford to buy it.
A workable, consistent approach must be found to share information that is needed for common
purposes.
42 SOLEC '96 - Information and Information Management
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5.2.5 Data Integration
The integration of data has been an ongoing information management issue. One of the more
recent methods of integrating data is to use Geographic Information Systems (GISs). GISs are
computer-based systems that are used to store and manipulate spatial information. A GIS is
designed to make the integration of diverse data sets easy. However, this capability also leads to a
number of data management issues—for example, the issue of the context of the data. A GIS will
allow its user to display information in various ways, by combining several layers of information.
Sometimes this can portray information in a very misleading way. There are also problems
associated with combining data sets. When one spatial data set is overlaid on another, the
resulting information will generally be less accurate than the least accurate input data set. There is
an implicit assumption that data shown together on a map meet a required level of accuracy;
however, this is often not the case.
Integration is key to meaningful policy formulation and planning decisions. Yet to be useful in
multiple applications, the data must be collected and automated according to specified and agreed
upon standards, including geographic coordinates, that allow for this integration of data.
5.2.6 Security and Protection of Data
Securing and protecting data is yet another information management issue. Although it is
important to make information available, this should not be done without proper assurance that
the data will not be used improperly. In field work that involves collecting data from humans, for
example, confidentiality is a key ethical issue. Storage and common access of data on humans
requires additional caution. If data are accessed and used without proper quality control, this may
result in decisions based on faulty data, which may lead to liability issues. It is important,
therefore, that proper care be taken to secure and protect data and information, including proper
documentation of the data, both to minimize the chances of the data being used for purposes for
which they were not intended and to prevent data being used without the knowledge and
understanding of their quality.
5.2.7 Data Stewardship
Once a database has been developed, the question arises of who should store and maintain the
data. Storage and maintenance imply responsibility for the data and require the appropriate
resources and corporate commitment. The question of who maintains the database is of particular
importance when more than one agency has been involved in the development of the data and
requires access to the data. Data collected for the Lakewide Management Plans and the Remedial
Action Plans are good examples. These programs involve numerous agencies at various levels on
both sides of the border. Each agency has contributed some amount of funding or expertise and
may require access to the data. No single agency controls the information, nor does any single
SOLEC '96 - Information and Information Management 43
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agency have the mandate and financial backing to be the custodian of the information. It becomes
crucial, therefore, that each agency involved be committed to the long-term maintenance and
access of the data it is responsible for.
5.2.8 Methods of Dissemination
Dissemination of data and information falls on the borderline of what might be considered
information management. For the purposes of this paper, we will not consider how the
information is packaged, visualized, or portrayed, but some discussion of the method of
disseminating the information does seem appropriate.
Until very recently, data and information have generally been disseminated by a tape or diskette
being sent by mail to the user. This method, although adequate, is time-consuming. For large data
sets, using diskettes to disseminate data can be cumbersome simply due to the number of diskettes
required (e.g., the Flood Damage Reduction Plan database is stored on 200 diskettes). Tapes
store much more data and are adequate as long as the user has a similar tape drive. But the many
versions of tapes on the market often create a problem for sharing data this way. Within the past
five years, CD ROMs have been used more often for data dissemination. This medium is superior
to the others in both the amount of data that can be stored and the compatibility of CD ROM
drives. Even more recently, the use of the Internet's file transfer protocol (ftp) for data transfer
has become more common. This is by far the fastest method of data transfer and dissemination.
Large data sets can be transferred around the globe in a matter of minutes, depending on the
bandwidth of the connecting lines. However, not all agencies have this capability, and even among
those that do, not all individuals are aware of this method of data transfer. Moreover, clogging the
Internet with huge data transfers violates one of the informal rules of Internet etiquette.
44 SOLEC '96 - Information and Information Management
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6.0 Significant Challenges and Opportunities
In section 5.0, we identified a number of information management issues. In this section, we will
attempt to identify the key challenges that emerge from these issues and suggest opportunities for
dealing with these challenges.
6.1 Agreed-Upon Indicators
Whether explicitly or implicitly, indicators have always been used to try to assess the state of the
Great Lakes. Indicators are required for us to make some statement about the status of the Great
Lakes nearshore and to gauge its relative improvement or degradation. However, a set of agreed-
upon indicators for measuring the nearshore ecosystems does not currently exist. Agreed-upon
indicators would help define and narrow the type of information that needs to be gathered and
would enhance the value of the information for making decisions. The challenge is to agree on a
set of indicators, along with the protocols for determining those indicators. Conferences such as
the State of the Lakes Ecosystem Conference provide an opportunity to discuss and make
progress in establishing a set of indicators.
6.2 Standardized Data-Collection Techniques
Once a set of indicators has been established, the next step is to agree upon some common data-
collection methodologies. Standards and guidelines are necessary to ensure quality and
consistency of data. They are needed, too, for the integration of data sets. But if standards are too
restrictive, they will not be followed or enforced. The challenge is to develop a set of standards
that provide the guidance necessary to ensure homogeneity and accuracy of data, yet that allow
enough flexibility for individuality of a study.
6.3 Coordinating Data-Gathering Initiatives
Homogeneity and compatibility of data require organizations to carefully plan their data-gathering
methodologies. Data collection does not come cheap and yet it is absolutely vital to understanding
and making decisions on the conservation and protection of our ecosystems. A collection
methodology that addresses the needs of varying disciplines and agencies is a cost-effective way
of gathering information. Organizations need to look for ways of pooling their resources in their
data-gathering initiatives. This type of endeavour has proven successful on the Niagara River,
where four agencies on both sides of the border make use of data collected by Environment
Canada under the Niagara River Toxics Management Plan. Using an agreed-upon methodology,
all four agencies benefit from the data. In all partnership arrangements, however, it is extremely
important that a custodian or custodians of the data be appointed to ensure the long-term
maintenance and accessibility of the data by all partners.
SOLEC '96 - Information and Information Management 45
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6.4 Finding the Data
One of the major computing trends over the last 15 years has been the move from large
centralized computers to distributed networks of computer systems. With the advent of PCs, data-
processing tasks have moved from corporate mainframes right to the desktop and now to the
laptop.
Computers and computer networks are spread through organizations, and computer data no
longer reside on a single system under the control of a single database management system.
Instead, data are spread across many different computer systems, each with its own method of
database management. Although this trend has undoubtedly made it easier to compile and
maintain databases, it has also created an environment in which organizations have literally lost
track of who is collecting data, where, and how often. The sheer size of the Great Lakes and the
myriad of organizations that collect and maintain data related to the Great Lakes is staggering. A
key challenge is how to keep track of data and information that is so widely distributed.
One method of keeping track of information is through the use of metadata.
6.4.1 Metadata Standards
Metadata is the common term assigned to a summary or catalogue of information about data or
information. Metadata can be considered data about data. The U.S. Federal Geographic Data
Committee defines metadata as "data about the content, quality, condition, and other
characteristics of data" (U.S. Federal Geographic Data Committee 1995).
With technology and performance issues gradually being resolved, the focus can now shift to the
need for more information about the data to effectively manage and access it. Metadata allows the
user to make more informed choices about what data to retrieve, while at the same time providing
a method for managing large data sets.
Metadata provides a standard set of details about a data set or information holding. It provides a
pointer to who has what and provides the context for an information holding. A metadata entry
has a standard set of field entries, which may include some or all of the following:
Title
Author
Originator
Date
Description or Abstract
Subject List
Availability
Point of Contact
Efforts are underway in both Canada and the United States to develop some form of metadata
standard for documenting data (e.g., Government Information Locator Service [GILS]). Agencies
collecting and using information about the nearshore of the Great Lakes need to agree to use
46 SOLEC '96 - Information and Information Management
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metadata (even if the standards used are not identical) so that data and information can be found.
If this metadata is made available on the World Wide Web on the Internet, it could provide
regional access to information about nearshore data and information. The first step is to agree to
develop the metadata.
6.5 Sharing/Accessing Data
Attempts to share data across platforms and operating systems have often proved futile because
many proprietary systems simply do not talk to each other. The challenge is to provide access to
information independent of the location of the data, the type of software used, or the capability of
the network or operating system, while at the same time ensuring that data integrity and security
is maintained.
The following subsections discuss a few of the opportunities for data sharing.
6.5.1 Common Data-Exchange Formats
In a perfect world, all agencies would store and maintain their information in common formats
that could easily be transferred and integrated. This, however, will likely never be the case. With
the number of agencies collecting nearshore information, the best that one could hope for is that
the information could be converted to some standard exchange format. For example, most
database management systems can save information as a .dbf file. Most GIS systems can save
information as a .dxf file; most spreadsheet packages can save information as a .wkl file; and
most word processors can accept WP5.1 files. If a set of standard exchange formats such as these
could be agreed upon, difficulties in transferring data between agencies could be minimized.
6.5.2 Using the World Wide Web
One of the single most technological phenomena to have hit this planet in the last decade is the
explosion of the use of the Internet. The Internet, which is not one big network, but rather a
network of networks all interlinked and talking to one another through a common
communications protocol, has made it possible for anyone with a computer, a phone line, and a
modem to be connected to people around the world. Information that once took days or weeks to
transfer (if it could be transferred at all) can now be transported in a just a few seconds around the
globe. This new trend opens up a world of opportunities for information exchange.
In the past three years, the number of users on the Internet has grown to over 40 million. This
incredible increase in Internet use is largely due to the creation of the World Wide Web (WWW),
which works over the Internet. The WWW provides seamless access to information through the
use of hyperlinks. The WWW is easy to use and provides a mechanism for finding and retrieving
information. What this means for information management is that organizations need post only
one copy of a document or database on-line, and millions of people can have access to it. The
WWW is a tool for sharing and archiving information and for linking information stored at various
SOLEC '96 - Information and Information Management 47
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locations. Potentially, the WWW could be used as a means of finding information about
nearshore databases and even of accessing those databases, since files can be downloaded directly
from the WWW. This method of data dissemination needs to be explored further as a way of
sharing and accessing nearshore information.
6.5.3 Existing Great Lakes Networks
There are a number of Great Lakes networks in existence that already make use of the WWW—
most notably the Great Lakes Information Network (GLIN). GLIN is a collaborative project of
agencies and organizations in the binational Great Lakes region that links data, information, and
people via the Internet. GLIN is a window to information about the Great Lakes and links to
numerous partner Web pages throughout the region. Its uniform resource locator (URL) is
. Two primary partners of GLIN are Environment Canada's Great
Lakes Information Management Resource (GLIMR), which provides an index of Environment
Canada's Great Lakes programs, publications, and databases , and
U.S.EPA's Great Lakes National Program Office (GLNPO) website
. GLIN, GLIMR and GLNPO are just a few examples of existing
networks that could be used as a basis for developing a Great Lakes nearshore consortium of Web
sites so that Great Lakes nearshore information could be easily found on the WWW.
48 SOLEC '96 - Information and Information Management
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7.0 Where Do We Go From Here?
The following is a summation of ideas presented throughout this report for suggested steps that
could be taken to improve the management of nearshore information.
1. Adopt a set of common indicators and protocols for assessing the state of the Great Lakes
nearshore ecosystems.
2. Develop some general guidelines and standards for collecting data on these indicators.
3. Identify target areas for data collection to minimize overlap and optimize the use of limited
funds.
4. Look for partnership opportunities for data collection and appoint custodians for the long-
term maintenance of that data.
5. Agree to document nearshore data and information using some form of metadata standard.
6. Agree on a set of common data-exchange formats.
7. Post metadata and, where possible, data on the World Wide Web.
8. Set up a consortium of nearshore partners over the World Wide Web through some
established Web site such as the Great Lakes Information Network (GLIN) and the Great
Lakes Information Management Resource (GLIMR).
SOLEC '96 - Information and Information Management 49
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8.0 References
Ball, Helen, Pisces Consultants. 1995. Guidelines for Collecting Baseline Aquatic Habitat Data
in the Great Lakes Areas of Concern. Ontario Ministry of Natural Resources.
Bishop, C.A., D.V. Weseloh, N.B. Burgess, RJ. Norstrom, R. Turle, and K.A. Logan. 1992. An
Atlas of Contaminants in Eggs of Colonial Fish-eating Birds of the Great Lakes (1970-1988),
vol. 1: Accounts by Chemicals. Technical Report Series No. 153. Environment Canada,
Canadian Wildlife Service.
Blokpoel, H., and G.D. Tessier. 1993. Atlas of Colonial Waterbirds Nesting on the Canadian
Great Lakes, 1989-1991. Part 1: Cormorants, Gulls and Island-nesting Terns on Lake
Superior in 1989. Technical Report Series No. 181. Environment Canada, Canadian Wildlife
Service.
Boulden, R.S., ed. 1976. Canada/Ontario Great Lakes Shore Damage Survey. Technical report.
Environment Canada and Ontario Ministry of Natural Resources.
Boyd, G.L. 1981. Canada/Ontario Great Lakes Erosion Monitoring Programme -Final Report
1973-1980. Ocean Science and Surveys. Manuscript Report Series No. 12. Burlington,
Ontario: Department of Fisheries and Oceans. Unpublished manuscript.
Cadman, M. 1995. Wildlife Watcher's Report on Monitor ing. Environment Canada, Canadian
Wildlife Service.
Ecologistics Limited. 1992. Evaluation of Shoreline Management Practices—Canadian
Shoreline. Submitted to the Land Use and Shoreline Management Task Group, Working
Committee 2, Phase II, IJC Levels Reference Study.
Edsall, T., and M. Charlton. 1996. "Nearshore Waters of the Great Lakes." State of the Lakes
Ecosystem Conference 1996. Working paper.
Environment Canada. 1996a. Great Lakes Information Management Resource (GLIMR). World
Wide Web site: http://www.cciw.ca/glimr/
Environment Canada. 1996b. Data Management Review, draft report. Review Branch,
Environment Canada.
Environment Canada, Canadian Wildlife Service. 1995. A Catalogue of Wetland Databases and
Inventories for the Canadian Great Lakes Basin.
Esterby, S.R., and P.E. Bertram. 1993. "Compatibility of Sampling and Laboratory Procedures
50 SOLEC '96 - Information and Information Management
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Evaluated for the 1985 Three-Ship Intercomparison Study on Lake Erie." Journal of Great
Lakes Research 19(2): 400-417.
Great Lakes Commission, 1996. Great Lakes Information Network. World-Wide Web site:
http://www.great-lakes.net/.
International Joint Commission. 1989. Project Management Team. Living with the Lakes:
Challenges and Opportunities. Progress Report to the International Joint Commission.
International Joint Commission. 1996. Indicators for Evaluation Task Force. Indicators to
Evaluate Progress under the Great Lakes Water Quality Agreement.
Jaagumagi, R., and D. Persaud. 1992. The In-Place Pollutant Program, vol. 7: A Synthesis of the
Program. Watershed Management Section, Water Resources Branch, Ontario Ministry of the
Environment.
Kidd, Joanna. 1994. Integration Paper. State of the Lakes Ecosystem Conference 1994. Prepared
for the SOLEC Steering Committee, Paul Horvatin and Harvey Shear, Co-Chairs. LURA
Group.
Lake Ontario Categorization Committee. 1993. Assessment and Identification of Priority
Substances in the Lake Ontario Basin, draft report.
Levels Reference Study Board. 1993. Levels Reference Study: Great Lakes-St. Lawrence River
Basin. Submitted to the International Joint Commission.
Maynard, L., and D. Wilcox. 1996. "Coastal Wetlands." State of the Lakes Ecosystem
Conference 1996. Working paper.
Natural Resources Canada. 1996. World Wide Web site: http://www.geocan.nrcan.gc.ca
Niagara River Data Interpretation Group. 1989. Joint Evaluation of Upstream/Downstream
Niagara River Monitoring Data for the Period April 1987 to March 1988. Joint publication of
New York State Department of Environmental Conservation, Environment Canada, United
States Environmental Protection Agency, and Ontario Ministry of Environment and Energy.
Ontario. 1996. Ontario - Open for Business. World Wide Web site: http://www.gov.on.ca.
Ontario Ministry of Environment and Energy. 1996. The Ontario Ministry of Environment and
Energy Data Share.
Ontario Ministry of Natural Resources. 1996. The Ontario Ministry of Natural Resources
Combined Database Holdings. (MS Access Database).
Reid, R., and K. Holland. 1996. "The Land by the Lakes: Nearshore Terrestrial Ecosystems."
State of the Lakes Ecosystem Conference 1996. Working paper.
SOLEC '96 - Information and Information Management 51
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Rivers, R., and S. Thorp. 1996. "Impacts of Changing Land Use." State of the Lakes Ecosystem
Conference 1996. Working paper.
Snell, E., A. Baril, N. Patterson and P. Cureton. 1994. A Catalogue of Databases Related to
Ontario Agro-Ecosystems. Technical Report Series No. 195. Environment Canada, Canadian
Wildlife Service.
Suns, K., G. Hitchin, and D. Toner. 1991. Spatial and Temporal Trends of Organochlorine
Contaminants in Spottail Shiners (Notropris hudsonius) from the Great Lakes and their
Connecting Channels (1975-1988). Report for the Water Resources Branch, Ontario Ministry
of the Environment.
Survey Results. 1996. Questionnaire: SOLEC 96 - Nearshore Database/Information Form.
Environment Canada and United States Environmental Protection Agency.
Tarandus Associates Limited. 1992. The Evaluation of Water, Sediment, andBenthic
Invertebrates from Long-Term Sensing Sites in 1990, draft. Prepared for the Ontario Ministry
of the Environment.
U.S. Federal Geographic Data Committee. 1995. Content Standards for Digital Geospatial
Metadata Workbook, Version 1.0.
52 SOLEC '96 - Information and Information Management
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APPENDIX 1
LIST OF REVIEWERS AND CONTRIBUTING
AUTHORS
SOLEC '96 - Information and Information Management_
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Appendix 1
Information and Information Management Paper
Canadian Contributing Authors/Review Team
Name
Affiliation/Address
Duncan Boyd
Environmental Monitoring and Reporting
Branch
Ministry of Environment and Energy
125 Resources Road, West Wing
Etobicoke, ON M9P 3V6
Mary-Louise Byrne
Department of Geography
and Environmental Studies
Wilfrid Laurier University
75 University Avenue West
Waterloo, ON N2L 3C5
Steve Douglas
Monitoring and Systems Branch
Environment Canada
4905 Dufferin St.
Downsview, ON M3H 5T4
Bob Duffield
National Water Research Institute
Environment Canada
867 Lakeshore Road
Burlington, ON L7R4A6
Barry Greer/Dave Greig
Monitoring and Systems Branch
Environment Canada
4905 Dufferin St.
Downsview, ON M3H 5T4
Mike Hall
SID
Environment Canada
Terrase de la Chaudiere
10 Wellington St.
Hull, PQ K1AOH3
Frank Kenny
Provincial Remote Sensing Office
Ministry of Natural Resources
90 Sheppard Ave. E.
North York, ON M2N 3A1
Bruce MacDonald
Ontario Land Resource Unit
Agriculture Canada
70 Fountain St.
Guelph.ON N1H3N6
Name
Affiliation/Address
54
SOLEC '96 - Information and Information Management
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Kevin McGunagle
International Joint Commission
100 Ouellette Avenue, 8
Windsor, ON N9A 6T3
,th
Floor
Ken Minns
Department of Fisheries and Oceans
867 Lakeshore Road
Burlington, ON L7R4A6
Joyce Mortimer
Great Lakes Health Effects Program
Health Canada
Room 1103, Main Building
Tunney's Pasture
Ottawa, ON K1AOK9
Ralph Moulton
Water Issues Division
Environment Canada
867 Lakeshore Road
Burlington, ON L7R4A6
Doug Obright
Ministry of Municipal Affairs and Housing
777 Bay St., 11th Floor
Toronto, ON M5G 2E5
Sandra Owens
Great Lakes Health Effects Program
Health Canada
Room 1106, Main Statistics Building
Tunney's Pasture
Ottawa, ON K1AOK9
Mike Shiomi
Environmental Conservation Branch
Environment Canada
867 Lakeshore Road
Burlington, ON L7R4A6
Mike Whittle
Department of Fisheries and Oceans
867 Lakeshore Road
Burlington, ON L7R4A6
SOLEC '96 - Information and Information Management_
55
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Appendix 1
Information and Information Management Paper
U.S. Contributing Authors/Review Team
Name
Affiliation/Address
Laura Beer
Great Lakes Commission
The Argus II Building
400 Fourth Street
Ann Arbor, Ml 48103-4816
Dieter Busch
Fish and Wildlife Service
Lower Great Lakes Fishery Research Office
405 North French Road, #120A
Amherst, NY 14228
Susan Crispin
The Nature Conservancy
Great Lakes Office
8 South Michigan Ave., Suite 2301
Chicago, IL 60603
Marg Dochoda
Great Lakes Fisheries Commission
2100 Commonwealth Blvd., Suite 209
Ann Arbor, Ml 48105-1563
Duane Heaton
U. S. Environmental Protection Agency
Great Lakes National Program Office
77 West Jackson Blvd. (G-9J)
Chicago, IL 60604
Carole Jett
Natural Resources Conservation Service
1405S. Harrison Road
Room 101
East Lansing, Michigan 48823
Joe Koonce
Case Western University
Biology Department
2080 Adelbert Road
Cleveland, OH 44106-7780
56
SOLEC '96 - Information and Information Management
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Name
Affiliation/Address
Robert Krska
Fish and Wildlife Service
Great Lakes Ecosystem Coordinator
Bishop Henry Whipple Fed. Bldg.
FortSnelling, MN55111
John Laedlein
Wisconsin Department of Natural Resources
Geographic Service Section, ET/8
P.O. Box 792221
101 South Webster Street
Madison, Wl 53707-7921
Pranas Pranckevicius
U. S. Environmental Protection Agency
Great Lakes National Program Office
77 West Jackson Blvd. (G-9J)
Chicago, IL 60604
David Reid
NOAA/Great Lakes Environmental Research
Laboratory
2205 Commonwealth Blvd.
Ann Arbor, Ml 48105-1593
SOLEC '96 - Information and Information Management_
57
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APPENDIX 2
SURVEY QUESTIONNAIRE
58 SOLEC '96 - Information and Information Management
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Appendix 2: Survey Questionnaire
QUESTIONNAIRE
SOLEC 96 - NEARSHORE DATABASE / INFORMATION FORM
Even if your organization does not have databases or information pertaining to the near shore,
we would still appreciate your input on questions 6 and 13.
1. Please identify a contact name for the information holding.
Contact Name:
Organization:
Address:
Telephone: Fax:
E-mail:
2. Please give a name or title to the database or information holding:
3. Please specify the agency (agencies) or organization(s) who are responsible for the
database/information holding:
4. Please indicate the purpose for which your database/information holding was developed.
5. Please give a brief description of the database/information holding specifying the attributes
associated with the database, (eg.plant species) (You may use the space below, or, attach
a separate sheet)
SOLEC '96 - Information and Information Management 59
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6. Does your agency/organization have a World Wide Web or gopher site on the Internet?
( ) yes - please give URL:
( ) no
( ) under development - anticipated date on-line
If yes, is the database or information holding...
( ) described on-line - please give URL:
( ) accessible on-line - please give URL:
7. Is the database/information holding catalogued elsewhere in a hardcopy or electronic
publication? Please specify:
8. Please idenfity what the database/information holding pertains to:
( ) Nearshore Waters
( ) Nearshore Terrestrial
( ) Land Use
( ) Coastal Wetlands
( ) Other, specify
9. When was the information gathered (start - end)?
10. How many data stations are involved (if pertinent) ?
11. What geographic area does the information cover? (be specific)
12. Please indicate the data storage format:
( ) paper - (in published or unpublished report - please give reference):
( ) word processor - software used?
( ) spreadsheet - software used?
( ) database management system (DBMS) - software used?
( ) geographic information system (GIS) - software used?
( ) other, please specify:
13. Please indicate any data/information that your agency requires that to your knowledge
60 SOLEC '96 - Information and Information Management
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does not exist, or cannot be accessed.
Form completed by: Date:
Phone:
Thank you for your cooperation and input. Please fax or mail this completed questionnaire
(ASAP) to:
Wendy Leger Phone: 905-336-4630
Water Issues Division Fax: 905-336-4906
Environment Canada E-mail: wendy.leger@cciw.ca
867 Lakeshore Road
Burlington, ON L7R 4A6
P.S.
If you know of anyone outside your agency who you think this questionnaire should be sent to,
please provide their name and address below. Thank you.
SOLEC '96 - Information and Information Management 61
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APPENDIX 3
LIST OF CATALOGUES, DIRECTORIES, AND WEB
SITES
62 SOLEC '96 - Information and Information Management
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Appendix 3: List of Catalogues, Directories, and Web Sites
Canadian
Ball, Helen, Pisces Consultants. Guidelines for Collecting Baseline Aquatic Habitat Data in the
Great Lakes Areas of Concern. Ontario Ministry of Natural Resources, 1995.
Environment Canada. Great Lakes Information Management Resource (GLIMR). World Wide
Web site: http://www.cciw.ca/glimr/
Environment Canada, Canadian Wildlife Service. A Catalogue of Wetland Databases and
Inventories for the Canadian Great Lakes Basin. 1995.
Environment Canada, Information Holdings Management Branch. Reference Directory to
Information Holdings, Isted. 1991.
Great Lakes Commission. Great Lakes Information Network (GLIN). World Wide Web site:
http://www.great-lakes.net/
Lake Ontario Categorization Committee. Assessment and Identification of Priority Substances in
the Lake Ontario Basin, draft report. 1993.
Ontario Ministry of Environment and Energy. The Ontario Ministry of Environment and Energy
Data Share. 1996.
Ontario Ministry of Natural Resources. Map and Aerial Photograph Catalogue. 1990/91.
Ontario Ministry of Natural Resources. Combined Database Holdings. 1996.
Snell, E., A. Baril, N. Patterson, and P. Cureton. A Catalogue of Databases Related to Ontario
Agro-Ecosystems. Technical Report Series No. 195. Environment Canada, Canadian Wildlife
Service, 1994.
United States
Great Lakes Commission. Great Lakes Information Network, World Wide Web site:
http://www.great-lakes.net/
National Biological Service. NBII Directory of Biological Data and Information. 1996. World
Wide Web site: http://www.nbs.gov/nbii/directory.html
SOLEC '96 - Information and Information Management 63
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NRCS Node to NSDI. The National Resources Conservation Service Node to the National
Spatial Data Infrastructure. World Wide Web site: http://www.ncg.nrcs.usda.gov/nsdi_node.html
United States Census Data at Lawrence Berkley National Laboratory. 1995. Demographic data
archive from the 1970, 1980, and 1990 U.S. censuses. World Wide Web site:
http://cedr.lbl.gov/mdocs/LBL_census.html 10/14/95
United States, Environmental Protection Agency, Center for Environmental Statistics, Geographic
Information Systems. 1996. Access to Geographic Information Systems (GIS) Spatial Data Sites.
Includes Great Lakes Ecosystem Initiative. Federal, state, and local levels. World Wide Web site:
http ://www. epa.gov/ngi spr/
United States Environmental Protection Agency. Great Lakes National Program Office. World
Wide Web site: http://www.epa.gov/glnpo/
United States Environmental Protection Agency-Great Lakes National Program Office, and the
Consortium for International Earth Science Information Network. Great Lakes Regional
Environmental Information System. 1996. A regional environmental directory and data access
system that provides services to the Great Lakes region. World Wide Web site:
http://epaserver.ciesin.org:7777/
United States Fish and Wildlife Service. Catalog of Automated Information Systems. 1996. A
reference of approximately 123 automated information systems owned by or used by the service.
Worldwide Web site: http://www.fws.gov/search/caisword.html
64 SOLEC '96 - Information and Information Management
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APPENDIX 4
GREAT LAKES NEARSHORE
INFORMATION HOLDINGS
SOLEC '96 - Information and Information Management 65
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NOTE: Appendix 4 is an abbreviated version of the information compiled. The full database,
which was based on survey results and information gathered from other catalogues, includes ID #,
title, purpose, description, WWW site (if it exists), catalogue name (if there is one), the topic area
(nearshore waters, nearshore land, wetlands, land use), date gathered, # of stations, geographic
area, storage format, agency responsible, contact (if given), telephone #, fax #, e-mail, and data
needs.
The full database will be made available with the on-line version of this report. Copies of the full
database will also be made available upon request from the SOLEC organizers:
Kent Fuller
United States Environmental Protection Agency
Great Lakes National Programs Office
77 West Jackson Blvd. (G-9J)
Chicago, IL 60604
Phone: (312)353-3503
Fax: (312)353-2018
E-mail: fuller.kent@epamail.epa.gov
Harvey Shear
Environment Canada - Ontario Region
4905 Dufferin Street
Downsview, ON M3H 5T4
Phone: (416)739-4704
Fax: (416)739-4781
E-mail: shearh@am.dow.on.doe.ca
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