CATALOG DOCUMENTATION
EMAP-GREAT LAKES PROGRAM LEVEL DATABASE
1994 LAKE ONTARIO NEARSHORE AND OFFSHORE
BENTHIC INVERTEBRATE DATA

TABLE OF CONTENTS

1.	DATA SET IDENTIFICATION

2.	INVESTIGATOR INFORMATION

3.	DATA SET ABSTRACT

4.	OBJECTIVES AND INTRODUCTION

5.	DATA ACQUISITION AND PROCESSING METHODS

6.	DATA MANIPULATIONS

7.	DATA DESCRIPTION

8.	GEOGRAPHIC AND SPATIAL INFORMATION

9.	QUALITY CONTROL/QUALITY ASSURANCE

10.	DATA ACCESS

11.	REFERENCES

12.	TABLE OF ACRONYMS

13.	PERSONNEL INFORMATION

1. DATA SET IDENTIFICATION

1.1	Title of Catalog document

EMAP-Great Lakes Program Level Database
1994 Lake Ontario Nearshore and Offshore
Benthic Invertebrate Data

1.2	Authors of the Catalog entry
Greg Elonen, ILS

1.3	Catalog revision date
9 April 1997

1.4	Data set name
L0BEN94


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1.5

Task Group

Great Lakes

1.6	Data set identification code
514

1.7	Version
001

1.8	Requested Acknowledgment

These data were produced as part of the U.S. EPA's Environmental Monitoring
and Assessment Program (EMAP). If you plan to publish these data in any
way, EPA requires a standard statement for work it has supported:

"Although the data described in this article has been funded wholly or in
part by the U.S. Environmental Protection Agency through its EMAP-Great
Lakes Program, it has not been subjected to Agency review, and therefore
does not necessarily reflect the views of the Agency and no official
endorsement should be inferred."

2. INVESTIGATOR INFORMATION

2.1	Principal Investigator
Stephen Lozano

U.S. Environmental Protection Agency
NHEERL-MED

2.2	Investigation Participant - Sample Collection
Floyd Boetcher

U.S. Environmental Protection Agency
NHEERL-MED

2.3	Investigation Participant - Sample Collection
Gary Phipps

U.S. Environmental Protection Agency
NHEERL-MED

2.4	Investigation Participant - Sample Collection
James Gangl

SAIC

(Currently, University of Minnesota)

2.5	Investigation Participant - Sample Processing
Jill Scharold

U.S. Environmental Protection Agency
NHEERL-MED


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3. DATA SET ABSTRACT

3.1	Abstract of the Data Set

The benthic invertebrate data set presents species composition data on each
benthic taxon identified from all acceptable grab samples collected at a
station. Total species abundance for each taxon identified from all grabs
(generally 3) is reported. Mean abundance and standard deviation of mean
abundance, number of grabs, sampling date and station identification are
also reported.

3.2	Keywords for the Data Set

Lake Ontario, benthic invertebrates, total species abundance, mean species
abundance, species composition, nearshore.

4. OBJECTIVES AND INTRODUCTION

4.1	Program Objective

The Environmental Monitoring and Assessment Program (EMAP) was designed to
periodically estimate the status and trends of the Nation's ecological
resources on a regional basis. EMAP provides a strategy to identify
and bound the extent, magnitude and location of environmental degradation
and improvement on a regional scale based on station sites randomly
located in the Great Lakes. Base grid and three-fold enhanced sampling
sites from nearshore and offshore regions of Lake Ontario are included
in this data set.

4.2	Data Set Objective

The objective of the benthic invertebrate species	data set is to provide

summary data for each taxon or species of benthic	invertebrate

identified from each station sampled in 1994 from	the nearshore and
offshore regions of Lake Ontario.

4.3	Background Discussion

Benthic invertebrate community structure is used extensively as a
biomonitoring tool. These communities generally form stable associations
that integrate and reflect environmental conditions. Owing to their
diverse taxonomy, wide range of physiological response to stress and
feeding modes, they tend to be sensitive to both natural and
anthropogenic disturbances and stresses. For these reasons benthic
invertebrate community structure is used as a tool for assessing the
biological condition of the Great Lakes.

4.4	Summary of Data Set Parameters

Total species abundance, mean species abundance, the standard deviation of
mean total abundance, and species composition at each station sampled.


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5. DATA ACQUISITION AND PROCESSING METHODS

5.1 Data Acqui si ti on

5.1.1	Sampling Objective

The primary objective was to collect sediment grab samples suitable for
analysis of benthic invertebrates. Three replicate sediment samples
were expected to be taken at each station.

5.1.2	Sample Collection Methods Summary

At sediment stations, sediment samples were collected for benthic
macroinvertebrates using a Ponar grab. Each sediment sample was washed
with an elutriation device equipped with a 500u m mesh Nitex screen.
The residue was rinsed into a pint plastic jar. An equal volume of
10% formalin solution containing rose bengal stain was added to
achieve a final concentration of 5% formalin.

The EMAP sampling strategy uses a global grid to identify sampling sites.
This grid is divided into sub-grids in accordance with the needs of
the ecosystem type. The baseline grid used in EMAP is an hexagonal
plate containing a triangular grid approximately 12,600 grid points
distributed randomly over the conterminous United States. These
grid points are about 27 km equidistant and large, contiguous hexagons
can be scribed around each grid point, each with an area of 635 sq. km.
Initial randomization of the grid on the United States establishes
the systematic sample (i.e., uniform and regular grid point and small
hexagons) as a probability sample. The grid structure reflects the
importance of achieving geographic coverage of ecological resources.
The uniformity of spatial coverage provided by a grid ensures that
each ecological resource can be sampled in proportion to its geographic
presence in the United States and that all ecological resources can
be included in the monitoring program.

5.1.3	Beginning Sampling Date
3 September 1994

5.1.4	Ending Sampling Date
19 September 1994

5.1.5	Platform

Sampling was conducted from the R/V Guardian.

5.1.6	Sampling Equipment
Standard size Ponar.

5.1.7	Manufacturer of Instrument
Wildco Manufacturing Company


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5.1.8 Key Variables

The number of grab samples at each station was recorded at the
time of collection.

5.1.9	Collection Method Calibration

The sampling gear did not require any calibration beyond inspection
for damage due to rough handling or rock damage.

5.1.10	Collection Quality Control

Criteria for rejection of Ponar samples: Soft bottom- sampler must
be at least 3/4 full and show minimal signs of disturbance. Hard
bottom- presence of rocks, signs of disturbance, or sampler less
than 1/4 full.

5.1.11	Sample Collection Method Reference

Strobel, C.J. and S.C. Schimmel, 1991. Environmental Monitoring and
Assessment Program-Near Coastal. 1991 Virginian Province, Field
Operations and Safety Manual. U.S. EPA, NHEERL-AED,

Narragansett, RI. June 1991.

5.2 Data Processing and Sample Processing

5.2.1	Sample Processing Objective

The primary sample processing objective was to accurately identify
and enumerate all benthic macroinvertebrate organisms found to the
lowest possible taxonomic category.

5.2.2	Sample Processing Methods Summary

Field samples returned to the lab were rinsed and preserved with 80%
ethanol.

5.2.3	Sample Processing Method Calibration
Not applicable.

5.2.4	Sample Processing Quality Control
None reported.

5.2.5	Sample Processing Method Reference

Nalepa, T.F. 1987. Long Term changes in the Macrobenthos of Southern
Lake Michigan. Can. J. Fish. Aquat. Sci. 44:515- 524.

5.2.6	Sample Processing Method Deviations
None reported.


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6. DATA ANALYSIS AND MANIPULATIONS

6.1 Name of New or Modified Values

T_ABN, M_ABN, SDABN

6.2	Data Manipulation Description

Species enumeration of samples on a "per grab" basis were received from
a taxonomy laboratory. The values reported in this data set were calculated
by 1) Summing replicate abundance over "n" samples, 2) calculating the
mean abundance across "n" replicates, 3) generating a standard deviation
based on the replicate abundance of each taxon.

6.3	Data Manipulation Examples

6.3.1	Total abundance for a taxon.

Abundance counts for a taxon were summed for all replicates collected at
stati on.

6.3.2	Mean abundance and Standard Deviation (SD) values of abundance.

The mean for each taxon identified at a station was calculated by summing
the replicate abundance and dividing by the number of grabs collected.
The SD was then calculated.

7. DATA DESCRIPTION

7.1 Description of Parameters

#

Name

Type

Length

Format

Parameter Label

1

STA NAME

Char

10

10.

Station Name

2

DATE

Num

6

6.

Sampling Date (YYMMDD)

3

LATIN NAME

Char

30

30.

Latin Name of the Taxon

4

# G

Num

1.

1.

Number of Replicate Samples
Taken

5

T_ABN

Num

3

4.

Total Number of Organisms of
a Taxon at a Station

6

M ABN

Num

5

3.2

Mean Number of Organisms/Grab

7

SDABN

Num

5

3.2

Standard Deviation of Mean

Abundance of Organisms/Grab

7.1.1	Precision to which values are reported

Total abundance is reported as a whole number. Mean abundance and
standard deviation are reported to 2 decimal places.

7.1.2	Minimum Value in Data Set

T ABN
M_ABN
SD ABN

1

0.33
0.00


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7.1.3 Maximum Value in Data Set

T ABN	1832

M_ABN	610.67

SD_ABN	147.00

7.2 Data Record Example

7.2.1	Column Names for Example Records
STA_NAME, DATE, LATIN NAME, #, T_ABN, M_ABN, SD_ABN

7.2.2	Example Data Records

L094-81 940906 Pisidium sp. 3 220 77.33 22.19
L094-82 940907 Diaporeia sp. 2 318 159.00 32.53

8.	GEOGRAPHIC AND SPATIAL INFORMATION

8.1	Minimum	Longitude
-79 deg 29' 59"

8.2	Maximum	Longitude
-76 deg 19' 22"

8.3. Minimum Latitude

42	deg 27' 29"

8.4	Maximum Latitude

43	deg 52' 57"

8.5	Name of Area or Region

Nearshore and Offshore Lake Ontario;

Stations were located within the Nearshore and Offshore resource class of
Lake Ontario. The nearshore sites were within the non-depositional zone
(13 sites) and the offshore sites were within the depositional zone (45
si tes) .

9.	QUALITY CONTROL/QUALITY ASSURANCE

9.1 Measurement Quality Objectives

90% correct identification.

9.2. Data Quality Assurance Procedures

For worms and midges: Michael Winnell, Freshwater Benthic, Inc., Krause
Rd., Petosky, MI.; for all others: Tom Nalepa, GLERL, N0AA, Ann Arbor,

MI.


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9.3 Actual Measurement Quality
Not reported.

10.	DATA ACCESS

10.1	Data Access Procedures

Data can be downloaded from the EMAP Website.

10.2	Data Access Restrictions
Not applicable.

10.3	Data Access Contact Persons

Stephen J. Lozano
U.S. E.P.A. NHEERL-MED
(218)720-5594
(218)720-5539 (FAX)
lozano.Stephen0epa.gov

10.4	Data Set Format

Data from the Website are in ASCii fixed format.

10.5	Information Concerning Anonymous FTP
Not accessible.

10.6	Information Concerning WWW

Data can be downloaded from the EMAP Website.

10.7	EMAP CD-ROM Containing the Data Set
Data are not available on CD-ROM.

11.	REFERENCES

Hedtke, S., A. Pilli, D. Dolan, G. McRae, B. Goodno, R. Kreis, G. Warren,
D. Swackhamer, and M. Henry. 1992. Great Lakes Monitoring and Research
Strategy: Environmental Monitoring and Assessment Program. USEPA, Office of
Research and Development, ERL-Duluth, Duluth, Minnesota. EPA/602/R-92/001.
204 p.

12. TABLE OF ACRONYMS


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PERSONNEL INFORMATION

Stephen J. Lozano

U.S. Environmental Protection Agency

NHEERL-MED

6201 Congdon Blvd

Duluth, MN 55804

(218)529-5205

(218)529-5003 (FAX)

lozano.Stephen0epa.gov

Gary L. Phipps

U.S. Environmental Protection Agency

NHEERL-MED

6201 Congdon Blvd

Duluth, MN 55804

(218)529-5205

(218)529-5003 (FAX)

phi pps.gary0epa.gov

Jill V. Scharold

U.S. Environmental Protection Agency

NHEERL-MED

6201 Congdon Blvd

Duluth, MN 55804

(218)529-5205

(218)529-5003 (FAX)

scharold.jill0epa.gov

Floyd L. Boettcher

U.S. Environmental Protection Agency

NHEERL-MED

6201 Congdon Blvd

Duluth, MN 55804

(218)529-5205

(218)529-5003 (FAX)

boetcher.floyd0epa.gov


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