FISH COMMUNITIES IN LAKES IN SUBREGION 2B
(UPPER PENINSULA OF MICHIGAN)
IN RELATION TO LAKE ACIDITY
U.S. Environmental Protection Agency
Office of Research and Development, Washington, DC
Environmental Research Laboratory, Corvallis, OR
Environmental Monitoring Systems Laboratory, Las Vegas, NV
Report No. E601-121-12/15/88-01F
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FISH COMMUNITIES IN LAKES IN SUBREGION 2B
(UPPER PENINSULA OF MICHIGAN)
IN RELATION TO LAKE ACIDITY
R.F. Cusimano
NSI Technology Services, Inc.
U.S. EPA Environmental Research Laboratory
Corvallis, Oregon
J.P. Baker
W.J. Warren-Hicks
V. Lesser
Kilkelly Environmental Associates
W.W. Taylor
M.C. Fabrizio
D.B. Hayes
Michigan State University
B.P. Baldigo
Lockheed Engineering and Sciences Company
Las Vegas, Nevada
oart hvZ TTIfSFlb-d m thiS fep°rt has been funded wholly or in
S^SSs^fSSy^f Pr°tec«on Agency under contract
?51 OH w?£^lN?r Jechnol°gy Services, contract 68-03-3439
(51-01) with Kilkelly Environmental Associates, cooperative
ftl^^^^ -State Univer^andTontract
with Lockheed Engineering and Sciences Company.
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EXECUTIVE SUMMARY
The research described in this document represents one component of Phase n of
the Eastern Lake Survey (ELS-H), a part of the National Surface Water Survey (NSWS).
Surveys of fish community status were conducted in summer 1987 in 49 lakes in ELS
Subregion 2B, the Upper Peninsula of Michigan. Subregion 2B was selected because of
its (1) high proportion of acidic (9.8% with ANC <; 0 peq/L) and low-pH lakes (9.4% with
pH < 5.0; 17.7% with pH < 6.0), (2) relative lack of existing data on fish communities in
lakes, and (3) diverse geological and hydrological conditions allowing optimal evaluation
of the association between lake characteristics and fish community status. A
companion study dealing with regional patterns in fish mercury content in Subregion 2B
was conducted concurrently; results from this study will be presented in a subsequent
report (U.S. Environmental Protection Agency [EPA], in prep.).
The NSWS is a survey, not a process-oriented, cause-and effect research program.
The emphasis is on developing a regional perspective on the current status of aquatic
resources with regard to potential impacts from acidic deposition. Regional surveys of
fish community status are needed to quantify the proportion and types of fishery
resources in lakes considered potentially sensitive to acidic deposition. In addition,
survey correlations between fish community status and water chemistry may be used to
evaluate dose-response relationships derived experimentally in laboratory or field
bioassays. Thus, the specific objectives of this project were as follows:
Estimate the percentage (by number and area) of lakes with few or no fish (i.e.,
with no fish caught in the survey) in Subregion 2B.
Estimate the percentage (by number and area) of fish populations that occur in
lakes with low acid neutralizing capacity (ANC), potentially susceptible to
effects from acidic deposition.
Determine the chemical characteristics of lakes with and without fish (as
estimated by catch/no catch).
Quantify the relationship between fish presence/absence and lake chemical and
physical characteristics.
Quantify the relationship between selected fish population characteristics (e.g.,
relative abundance and condition factors) and lake chemical and physical
characteristics.
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The lakes sampled in Subregion 2B during ELS-H to assess fish community status
were a subset of the lakes sampled during Phase I of the Eastern Lake Survey (ELS-I).
Lake selection involved a variable probability sampling design that (1) concentrated on
lakes with low pH, (2) covered the full range of values for dissolved organic carbon
(DOC), and (3) attempted to even-out the inclusion probabilities assigned in the ELS-I.
Several categories of lakes were excluded from the ELS-H and the ELS-H target
population in Subregion 2B: lakes < 1.5 m in depth, larger than 2000 ha, highly enriched
with nutrients, or modified by recent in-lake management practices (e.g., recent fish
stocking). Lakes smaller than < 4 ha in area were excluded from both the ELS-I and
ELS-H target populations.
The 49 ELS-H lakes in Subregion 2B were sampled between 8 June and
30 August 1987. Fish communities were surveyed using gill nets, trap nets, beach
seines, and angling. Coincident with the fish surveys, some data on lake physical and
chemical parameters were collected (e.g., measures of aluminum speciation). For the
most part, however, the ELS-H data on fish communities in lakes in Subregion 2B are
interpreted relative to the ELS-I index of lake chemistry collected in fall 1984. It is
recognized that the ELS-I data are not direct measures of chemical conditions during
those specific times and locales critical to fish population response. It is assumed,
however, that the ELS-I index chemistry is at least correlated with these water quality
values of interest.
Duplicate surveys of fish communities were conducted for ten of the 49 ELS-n
lakes between 31 August and 12 September 1987 as part of the quality assurance/
quality control (QA/QC) protocol. Comparison of results from these duplicate surveys
provides some information on sampling errors and variability. In general, measures of
species richness (i.e., the number of fish species caught) and fish species
presence/absence were similar in the duplicate samples. For species richness, all but
one lake had a coefficient of variation (CV) < 50%j all but two of the ten lakes had a
CV < 25%. The maximum deviation in species richness between the two samples was
two species. Variations in numbers of fish caught and catch per unit effort (CPUE), on
the other hand, were somewhat greater (coefficients of variation 10 to 140%). Many
factors influence fish capture efficiency, thereby limiting the utility of CPUE as an
index of relative fish abundance.
ii
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Fish were collected in 47 of the 49 lakes surveyed. The number of species caught
per lake ranged between 0 and 13, with a median of three. Thirty-one fish species were
caught in total. Yellow perch (Perca flavescens) was the most common species,
collected in 31 lakes. Seven other fish species occurred in 10 or more lakes. In
decreasing order of frequency, these species were largemouth bass (Micropterus
salmoides), bluegill sunfish (Lepomis macrochirus). pumpkinseed sunfish (Lepomis
gibbpsus), white sucker (Catostomus commersoni). brown bullhead (Ictalurus nebulosus).
golden shiner (Notemigonus crvsoleucas), and northern pike (Esox lucius). The species
caught are typical of those reported for lakes in the Upper Midwest as a whole
(including northern Minnesota, Wisconsin, and Michigan).
Extrapolation of these results to the ELS-H target population in Subregion 2B
suggests that 99.4% of the lakes in the area (in the defined target population) support
fish (99.5% of the lake area). Game species occur in 83.7% of the lakes (95.7% by lake
area); 16.6% of the lakes with game fish have ANC
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acidic conditions. Yellow perch, brown bullhead, brook trout, and central mudminnow
are considered relatively acid tolerant, while cyprinids and darters are considered acid
sensitive.
In contrast to the large number of variables associated with fish presence/absence
and species richness, variations in the numbers of fish caught (and CPUE) among lakes
appeared independent of lake characteristics. Only for yellow perch were any
statistically significant associations identified: higher numbers of yellow perch were
caught in lakes with lower pH, ANC, calcium, sum of the base cations, and silica, and
with higher levels of extractable aluminum. Thus, yellow perch are not only tolerant of
acidic conditions, but are actually more abundant in acidic waters with lower calcium
and silica, perhaps as a result of reduced competition from other fish species.
Survey data alone cannot establish causality. Many factors influence fish
distribution, abundance, and condition, and many of these factors are themselves
interrelated and correlated. The observed results for the ELS-H in Subregion 2B are,
however, consistent with existing hypotheses regarding factors that influence fish
community status. For example, seepage lakes tend to have relatively depauperate fish
communities, perhaps as a result of their relative isolation and reduced rates of fish
colonization. Larger lakes tend to support more diverse fish communities, reflecting
the generally greater habitat complexity in larger lakes. The ELS-H data also suggest a
negative effect of low ionic strength (i.e., low concentrations of calcium and other base
cations) and lake acidity (low pH and ANC) on several fish species and groups.
iv
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TABLE OF CONTENTS
Chapter
Title
Page
List of Figures . . . vii
List of Tables !.!!!! . '. '. .1'.'.'.'.'.'.'. .'. ix
1 INTRODUCTION AND BACKGROUND .. . . . . . , i-i
1.1 The National Surface Water Survey . . . ,.........!! 1-^1
1.2 Project Objectives '.'.'.'. 1-3
1.3 Report Format ............................... [ **[] .. '.'. 1-4
2 LAKE SELECTION . .'. . ..... . . .... 2-1
2.1 Eastern Lake Survey - Phase I ...................... 2-1
2.1.1 The Target Population ..........,..........'.*!!!!!!." 2-1
2.1.2 Statistical Design 2-2
2.2 Surveys of Fish Community Status (ELS-H) ........... !.*!.*!.'/! 2-5
2.2.1 The Target Population . '/, ] ] 2-5
2.2.2 Statistical Design ..... . . . ..... . . .'. . . . . . . . . . . . .... 2-6
3 FIELD IMPLEMENTATION . ... ..... . .'" 3-1
3.1 Field Personnel . ; . . . . . . . . . ...'.... . . . * * 3-1
3.2 Sampling Period .............. ... ...... ..... ...*.....!!* ! * 3-1
3.3 Initial Lake Reconnaissance 3-5
3.4 In Situ Measurements . . . 3-5
3.5 Collection of Water and Sediment Samples . . . . 3-6
3.6 Fish Surveys 3-6
3.6.1 Sampling Gear and Effort ....!!!!!!!!]] 3-6
3.6.2 Field Measurements and Samples 4 ..... 3-8
4 QUALITY ASSURANCE/QUALITY CONTROL ..... .... ............ . 4-1
4.1 Water Chemistry ... . !!.*!] 4-1
4.2 Fish Surveys ! ! ! ! ! 4-8
4.2.1 Field Measurements 4_g
4.2.2 Duplicate Fish Surveys 4_g
5 LAKE PHYSICAL CHARACTERISTICS 5-1
6 LAKE CHEMICAL CHARACTERISTICS 6-1
6.1 ELS-I Fall Index Sample !!!!!!!! 6-2
6.2 Comparison of 1984 Fall Index with 1987 Summer Chemistry "!!!!!!! 6-6
6.3 Aluminum Chemistry 6_g
7 FISH COMMUNITY STATUS 7_!
7.1 Fish Species Distribution . . . , ......!!!!!!!!!!!!!! 7-1
7.2 Total Catch and Catch Per Unit Effort . . !!!!!!!!!! 7-7
7.3 Fish Size and Condition Factors [ * 7-10
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Chapter
Title
Page
8 ASSOCIATION BETWEEN FISH COMMUNITY STATUS AND
LAKE CHARACTERISTICS 8-1
8.1 Multicollinearity Among Predictor Variables 8-4
8.2 Species Richness 8-6
8.3 Fish Species Presence/Absence o-ii
8.4 Total Catch and Catch Per Unit Effort 8-31
8.5 Fish Condition Factors 8-34
9 RREGIONAL POPULATION ESTIMATES 9-1
10 DISCUSSION AND SUMMARY 10-1
11 REFERENCES ll~l
APPENDICES
A QUALITY ASSURANCE AND QUALITY CONTROL PROTOCOLS
FOR MEASUREMENTS OF WATER CHEMISTRY A-l
B WATER CHEMISTRY AND FISH CATCH DATA
BY INDIVIDUAL LAKES AND SAMPLING DATES B-l
VI
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LIST OF FIGURES
Figure
Title
Page
1-1 Subregions surveyed during Phase I of the Eastern Lake Survey 1-2
2-1 Geographic distribution of the lakes sampled in Subregion 2B during
(a) ELS-I and (b) ELS-fl 2-4
2-2 Relationship between pH and calcium for the 105 lakes in
Subregion 2B sampled during ELS-I and in the ELS-n target
population 2-8
2-3 Relationship between pH and DOC for the 105 lakes in Subregion 2B
sampled during ELS-I and in the ELS-n target population 2-8
4-1 Standard error for the duplicate measures of total catch, as a
function of the mean catch per lake . . . 4-12
5-1 Comparison of ELS-I and ELS-n values for Secchi depth . 5-3
6-1 Cumulative frequency distributions for the ELS-I target population,
the ELS-n target population, and the 49 lakes sampled for (a) ANC,
(b) pH, (c) Ca, and (d) DOC 6-4
6-2 Comparison of chemical values measured in fall 1984 versus summer
1987 for the 49 ELS-n lakes in Subregion 2B, for (a) pH and
(b) conductivity 6-7
6-3 Distribution of inorganic aluminum in ELS-H lakes in Subregion 2B ... 6-9
7-1 Distribution of species richness values among the 49 ELS-H lakes .... 7-5
7-2 Distribution of total catch, gill-net CPUE, and trap-net CPUE for
all species, and total catch for game species for the
49 ELS-n lakes 7-9
7-3 Length-frequency histograms, by species, for all fish caught in all
gear types in all lakes 7-12
8-1 Bivariate plots of species richness and lake characteristics, for
those continuous physical and chemical variables associated
with species richness at p s 0.05 8-10
8-2 Box-and-whisker plots comparing species richness in (a) seepage
versus nonseepage lakes and (b) thermally stratified versus mixed
lakes 8-13
vn
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Figures
Title
Page
8-3
8-4
8-5
9-1
9-2
Species richness as a function of lake pH for (a) seepage and
(b) nonseepage lakes
Box-and-whisker plots comparing lake characteristics with
and without white sucker
The distribution of fish species in relation to pH for the
49 ELS-H lake
Cumulative frequency distributions of species richness (by number
of lakes) for lakes in Subregiori 2B, based on (a) the direct ELS-n
estimate with 49 lakes and (b) the model-based approach, with
species richness defined from catch with gill nets, trap nets,
and angling
Cumulative frequency distributions of species richness (by number
of lakes) for lakes in Subregion 2B, based on the model-based
approach with species richness defined from catch with gill nets,
trap nets, and angling (solid line) and with all four gear types
(dashed line)
8-16
8-21
8-30
9-4
9-5
Vlll
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LIST OF TABLES
Table
Title
Page
1.1 Population Percentage Estimates for Selected pH and ANC
Criteria, from Phase I of the Eastern Lake Survey 1-3
2.1 Description of Sample and Target Population for the Eastern Lake
Survey - Phase I (ELS-I) and Phase H (ELS-n) for Subregion 2B,
the Upper Peninsula of Michigan 2-2
2.2 Numbers of ELS-I Lakes Excluded from the ELS-H Target Population
in Subregion 2B 2-7
2.3 List of Lakes Selected for ELS-D in Subregion 2B . . . 2-11
3.1 Sampling Dates (1987) and Fish Sampling Effort Per Lake . . 3-2
3.2 Nonparametric Correlation Between Sampling Date and Lake
Characteristics 3-4
3.3 Standard Fish Sampling Effort Per Lake 3-7
4.1 Quality Assurance Objectives for Precision, Accuracy, and
Detectability, and Measurement Methods for Physiocochemical
Parameters Measured during ELS-I 4-2
4.2 Quality Assurance Objectives for Precision, Accuracy, and
Detectability and Measurement Methods for Physiochemical
Parameters Measured during ELS-n in Subregion 2B . , 4-4
4.3 Estimates of Precision for Physicochemical Parameters
Measured during ELS-n 4-5
4.4 Estimate of Laboratory Accuracy Using Synthetic Audits . . . . 4-7
4.5 Summary of Results for Species Richness from Duplicate Surveys of
Ten Lakes . . 4-10
4.6 Summary of Results for Fish Catch (All Species Combined) for the
Duplicate Surveys of Ten Lakes 4-11
4.7 Comparison of Fish Length, Weight, and Condition Factors for the
Duplicate Surveys of Ten Lakes 4-14
IX
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Table
Title
Page
6.1 Chemical Characteristics of Lakes in Subregion 2B, for the ELS-I
Target Population (N=1050), ELS-H Target Population (N=597),
and the 49 Lakes Sampled During ELS-n . . . . . 6-2
6.2 Comparison of Lake Chemistry by Lake Type: Seepage Lakes versus
Other Lake Types (Drainage, Reservpir, Closed) for the
49 Lakes Sampled During ELS-E 6-5
6.3 Summary of Long-Term Monitoring Data for Acid Neutralizing
Capacity (ANC), Calcium (Ca), and pH from Lakes Located in
the Upper Peninsula of Michigan and North Central Wisconsin 6-8
7.1 Fish Species Caught and Frequency of Occurrence . 7-2
7.2 Species Richness, by Lake, for the 49 Lakes Sampled in Subregion 2B . 7-3
7.3 Relative Gear Efficiency for Each Species, Calculated as the
Percent of Lakes for Which the Gear Detected Each Species Out
of the Total Number of Lakes in Which the Species Was Caught
Regardless of the Gear Used . 7-6
7.4 Total Catch and Catch Per Unit Effort (CPUE) by Lake, All Fish
Species Combined 7-7
7.5 Summary of Total Catch and Catch Per Unit Effort (CPUE) for
Selected Species, for Lakes where the Fish Species Was Caught
with Gill Nets or Trap Nets 7-11
7.6 Fish Condition Factors, by Species, Pooled Across All Lakes and
All Ages . 7-16
8.1 Correlation Matrix for the 17 Continuous Predictor Variables ....... 8-5
8.2 Results from Principal Components Analysis on 19 Physical and
Chemical Variables 8-7
8.3 Association Between Species Richness, Total Catch, and Catch Per
Unit Effort (CPUE, Averaged Over Gill Nets and Trap Nets)
and Lake Physical and Chemical Characteristics 8-9
8.4 Multivariate Regression Models for Species Richness 8-14
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Table
Title
Page
8.5 Analysis of Covariance: Variations in the Relationship Between
Species Richness and Lake pH, by Lake Type 8-15
8.6 Comparison of Lake Physical Characteristics for Lakes With (P)
and Without (A) Fish Caught 8-19
8.7 Comparison of Lake Chemical Characteristics for Lakes With (P)
and Without (A) Fish Caught 8-20
8.8 Model Coefficient Estimates for Those Single-Variable Logistic
Regression Models with p s 0.05 for the Predictor Variable 8-25
8.9 Association Between Total Catch and Catch Per Unit Effort and
Lake Physical and Chemical Characteristics for Selected
Fish Species . . . 8-32
8.10 Summary of Results from Ordinary Least Squares Regression of
Fish Condition Factors as a Function of Fish Length and Lake
Physical and Chemical Characteristics 8-35
9.1 Population Estimates (Subregion 2B) of Lakes With Fish, based on
Direct Estimation from the Sample of 49 ELS-n Lakes 9-3
10.1 Minimum pH Levels of Fish Species Occurrence in Synoptic
Lake Surveys . . 1Q-2
10.2 Fish Survival Exposed to Continuously Declining pH in Lctboratory
Bioassays (Source: Rahel and Magnuson 1983), Compared to the
Relative Sensitivity of Fish Species Inferred from the
ELS-H Survey 1Q-3
XI
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1. INTRODUCTION AND BACKGROUND
1.1 THE NATIONAL SURFACE WATER SURVEY
In 1983, the U.S. Environmental Protection Agency (EPA) initiated the National
Surface Water Survey (NSWS) to document the chemical and biological status of lakes
and streams in regions of the United States potentially susceptible to acidic deposition.
The NSWS was designed as a three-phase project:
Phase I a synoptic survey of lake and stream chemistry.
Phase n an evaluation of chemical variability and biological status for a
subset of surface waters in selected regions sampled during Phase I.
Phase HI a long-term monitoring program to quantify future changes in the
chemistry and biology of aquatic ecosystems characteristic of geographic
regions of the United States. Phase in of the NSWS has since been subsumed
within the broader EPA monitoring program, Temporally Integrated Monitoring
of Ecosystems (TIME).
The NSWS consists of two major components: the National Lake Survey and the
National Stream Survey. The National Lake Survey consists, in turn, of the Eastern
Lake Survey (ELS) and Western Lake Survey (WLS). The research described in this
document represents one component of Phase n of the Eastern Lake Survey (ELS-n).
Phase I of the ELS (ELS-I) was conducted in fall 1984, with the final results
presented in three volumes (Linthurst et al. 1986, Overton et al. 1986, Kanciruk et al.
1986). The ELS-I had three primary objectives:
1. to determine the percentage (by number and area) and location of lakes that
are acidic in potentially sensitive regions of the eastern United States,
2. to determine the percentage (by number and area) and location of lakes that
have low acid neutralizing capacity (ANC) in potentially sensitive regions of
the eastern United States, and
3. to determine the chemical characteristics of lake populations in potentially
sensitive regions of the eastern United States and provide the data base for
selecting lakes for future study.
To accomplish these objectives, a water sample was collected during fall overturn
at 1.5 m depth over the deepest point in the lake from 1612 lakes within 11 subregions in
the northeastern, southeastern, and upper midwestern regions of the United States
(Figure 1-1). A suite of chemical variables and physical attributes thought to influence
or be influenced by surface water acidification was measured for each lake. Lakes
sampled were selected by a systematic random process from the population of lakes in
1-1
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Upper Midwest
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Southeast
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Subregion Boundary
Figure 1-1. Subregions surveyed during Phase I of the Eastern Lake Survey.
the areas studied. Thus, the ELS-I data base provides the basis for regional estimates of
the chemical status of lakes within a specific region or subregion.
Three subregions sampled during ELS-I had the highest frequency and number of
acidic (defined by an ANC £ 0 peq/L) and low pH lakes (Table 1.1):
1. Subregion 3B (Florida), with an estimated 476 (22.7%) acidic lakes, 259 (12.4%)
lakes with pH < 5.0, and 687 (32.7%) lakes with pH < 6.0;
2. Subregion 1A (Adirondacks), with an estimated 181 (14.0%) acidic lakes, 128
(10.0%) lakes with pH < 5.0, and 343 (26.6%) lakes with pH < 6.0; and
3. Subregion 2B (Upper Peninsula of Michigan), with an estimated 119 (11.3%)
acidic lakes, 99 (9.4%) lakes with pH < 5.0, and 185 (17.7%) lakes with pH
£ 6.0.
1-2
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Table 1.1. Population Percentage Estimates for Selected pH and ANC Criteria,
from Phase I of the Eastern Lake Survey (Lakes < 2000 ha)
(Linthurst et al. 1986, Landers et al, 1988)
Region/Subregion
Northeast (1)
Adirondacks (1A)
Poconos/Catskills (IB)
Central New England (1C)
Southern New England (ID)
Maine (IE)
Upper Midwest (2)
Northeastern Minnesota (2A)
Upper Peninsula of Michigan (2B)
Northcentral Wisconsin (2C)
Upper Great Lakes Area (2D)
Southeast (3)
Southern Blue Ridge (3A)
Florida (3B)
Number
of
Lakes
1290
1479
1483
1318
1526
1457
1050
1480
4515
258
2098
ANC (ueq/L)a
<0
14.0
5.9
4.2
6.5
1.6
0.0
11.3
8.7
0.0
0.0
22.7
<50
37.8
13.5
23.3
22.6
14.7
5.2
19.6
41.8
9-8
1.4
39.8
<200
73.0
40.9
67.6
57.3
66.8
52.1
41.7
57.1
31.3
34.3
55.1
PH
<5.0
10.0
0.8
1.7
5.0
0.5
0.0
9.4
2.1
0.0
0.0
12.4
<6.0
26.6
7.8
12.9
14.6
4.8
1.4
17.7
27.7
4.5
0.4
32.7
a Population estimates based on recalculated ANC values (Hillman et al., in prep.)
Subregion 26, encompassing the majority of the Upper Peninsula of Michigan plus
a small portion of northern Wisconsin, was selected for the ELS-n survey of fish
community status because of (1) the high proportion of acidic and low pH lakes in the
subregion, (2) the relative lack of existing data on fish communities in lakes in the area,
and (3) the diversity of geological and hydrological conditions in the subregion, allowing
optimal evaluation of the association between lake characteristics and fish community
status.
1.2 PROJECT OBJECTIVES
The NSWS is a survey, not a process-oriented, cause-and-effeet research program.
The emphasis is on developing a regional perspective on the current status pf aquatic
resources with regard to potential impacts from acidic deposition. Regional surveys of
fish community status are needed to quantify the proportion and types of fishery
1-3
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resources in lakes considered potentially susceptible to or impacted by acidic deposition.
In addition, survey correlations between fish community status and water chemistry may
corroborate, in a field situation, dose-response relationships derived experimentally in
laboratory and field bioassays. The study described in this document is unique in
providing data on fish community status for a defined probability sample of lakes using
consistent sampling techniques across a broad region.
The specific objectives of the project are as follows:
Estimate the percentage (by number and area) and location of lakes with few or
no fish (i.e., with no fish caught in the survey) in Subregion 2B (Upper Peninsula
of Michigan).
Estimate the percentage (by number and lake area) of fish populations (by
species) that occur in lakes in Subregion 2B with low ANC, potentially
susceptible to effects from acidic deposition.
Determine the chemical characteristics of lakes with and without fish (as
estimated by catch/no catch).
- Do lakes with no fish caught (or without certain fish species) have
significantly lower pH (and/or higher aluminum [Al], lower calcium [Ca], or
lower dissolved organic carbon [DOC] levels) than do lakes with fish?
Quantify the relationship between fish presence/absence (by species) and lake
chemical and physical characteristics.
Are the pH, inorganic Al, and Ca levels associated with the absence of fish
species comparable to levels toxic to fish in laboratory and field bioassays?
Quantify the relationship between selected fish population characteristics (e.g.,
relative abundance and condition factors) and lake characteristics.
In conjunction with this study of fish community status in lakes in the Upper
Peninsula of Michigan, data were also collected on fish mercury content, to assess the
relationship between lake characteristics and mercury bioaccumulation. Results from
this component of the project are reported in a separate document (EPA, in prep.).
1.3 REPORT FORMAT
The report is divided into 11 sections:
Section 1, Introduction and Background
Section 2, Lake Selection provides an overview of the statistical sampling
design for the ELS-I and the procedures for selecting the subset of lakes
sampled in ELS-n.
1-4
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Section 3, Field Implementation describes the field sampling methodology
for water chemistry and fish communities.
Section 4, Quality Assurance/Quality Control (QA/QC) summarizes the
QA/QC results for field sampling and laboratory analyses.
Section 5, Lake Physical Characteristics describes the physical
characteristics of the lakes sampled, relative to the physical characteristics of
lakes in the region as a whole.
Section 6, Lake Chemical Characteristics summarizes results from water
chemistry measurements for ELS-n relative to results for ELS-I, and for the
lakes sampled in ELS-n relative to the population of lakes in the region as a
whole.
Section 7, Fish Community Status describes the characteristics of fish
communities in lakes in the region, including information on species
composition, relative abundance, and fish condition factors.
Section 8, Association Between Fish Community Status and Lake
Characteristics discusses the degree to which among-lake variations in fish
community characteristics are associated with variations in lake chemistry and
other lake characteristics.
Section 9, Regional Population Estimates provides regional estimates of the
percentage (by number and lake area) of lakes with few or no fish in Subregion
2B, and the proportion of the fishery resource in low-ANC waters.
Section 10, Discussion and Summary
Section 11, References
Two appendices are provided under separate cover (Volume n): Appendix A
describes in further detail the QA/QC protocols for measurements of water chemistry,
and Appendix B summarizes the data collected during ELS-I and ELS-H for each lake
sampled during the ELS-II.
1-5
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2. LAKE SELECTION
2.1 EASTERN LAKE SURVEY - PHASE I
The lakes sampled in Subregion 2B to assess fish community status were a subset
of the lakes sampled during ELS-I. Procedures for lake selection for the ELS-I survey
were described in Linthurst et al. (1986) and Landers et al. (1988) and are summarized
below.
2.1.1 The Target Population
The study area for ELS-I was restricted to those areas of the United States where
the majority of lakes were expected to have ANC < 400 peq/L, as delineated on the
national map of surface water alkalinity prepared by Omernik and Powers (1983) (see
Figure 1-1). Within this study area, all lakes appearing on 1:250,000 -scale topographic
maps from the U.S. Geological Survey (USGS) were identified and labeled. These lakes
define the "statistical frame" or "frame population." Lakes with a surface area of
< 4 ha (and up to 10 ha on some maps) are generally not shown on meips of this scale and
thus were not considered in the survey. The target population of lakes, for which
regional estimates are computed, consists of the frame population minus several
categories of non-interest lakes. Categories of non-interest lakes excluded from the
ELS-I target population include the following:
No lake present lakes initially identified on l:250,000-scale maps that did
not appear on larger-scale maps (1:25,000-or l:62,500-scale maps) or that were
found to be dry during the site visit.
Flowing water sites identified as flowing water (streams,, rivers) on larger-
scale maps or during the site visit.
Bay/Estuary (high conductance) lakes appearing as ocean embayments or
estuaries or with a measured specific conductance > 1500 pS/cm.
Urban/Industrial/Agricultural lakes surrounded by or adjeicent to intense
anthropogenic activities.
Marsh/Swamp lakes appearing as swamps or marshes on larger-scale maps.
Too Shallow lakes that were too shallow to collect a clean water sample,
free of debris and sediment.
Too Small lakes less than 4 ha in area based on the larger-scale maps.
Other lakes that were inaccessible due to a permanent feature of the lake
(e-g«» power lines that prevented helicopters from landing safely).
2-1
-------
In Subregion 2B, the frame population consists of 1698 lakes, with an estimated
1050.0 lakes in the target population (Table 2.1). The majority of the lakes eliminated
from the frame population were either too small (< 4 ha) or too shallow.
Table 2.1. Description of the Sample and Target Population for the Eastern Lake
Survey - Phase I (ELS-I) and Phase H (ELS-n) for Subregion 2B, the Upper
Peninsula of Michigan
Exclusion Category
Lakes in the ELS-I frame population ..
Lakes in the ELS-I probability sample
ELS-I weighting factor (Wl)
Lakes sampled for ELS-I
Lakes sampled for ELS-I within the ELS-n
target population
Estimated target population size (ft)
ELS-I
ELS-H
Standard error of ft
ELS-I
ELS-H
Estimated lake area (ha) of the target
population (A)
ELS-I
ELS-n
Standard error of A
ELS-I
ELS-H
2B1
118
74
1.878
41
36
77.0
67.61
4.89
2.72
893
811
90
77
Stratum
262
250
100
2.579
57
45
147.0
116.1
9.83
6.27
2,776
1,777
500
269
2B3
1330
80
17.208
48
24
826.0
413.0
71.69
58.46
30,357
12,493
10,842
4,601
Subregion
Total
1698
254
146
105
1050.0
596.7
72.5
58.9
34,026
15,081
10,854
4,609
2.1.2 Statistical Design
The sampling plan for ELS-I used a stratified design with equal allocation of
sample lakes among strata. Lakes were selected from each stratum by systematic
sampling of an ordered list following a random start.
The three regions, Northeast, Southeast, and Upper Midwest (Figure 1-1),
represented the first level of stratification. Subregion, the second stratification
2-2
-------
factor, identified areas within each region that were expected to be relatively
homogeneous with respect to water quality, physiography, vegetation, climate, and soils.
Four subregions were defined in the Upper Midwest region (Region 2): 2A (Northeastern
Minnesota), 2B (Upper Peninsula of Michigan), 2C (Northcentral Wisconsin), and 2D
(Upper Great Lakes Area) (Figure 1-1). Eleven subregions were defined in total: four in
the Upper Midwest, five in the Northeast, and two in the Southeast.
The third stratification factor, alkalinity map class, differentiated among areas
within each subregion based on the range of surface water alkalinity values expected to
dominate in different areas. The alkalinity map classes chosen were < 100 peq/L
(class 1), 100-200 peq/L (class 2), and > 200 peq/L (class 3). Spatial representations of
the three alkalinity classes within each subregion were derived from preliminary
versions of regional surface water alkalinity maps prepared by Omernik and Kinney
(1985), Omernik and Griffith (1985), and Omernik (1985). All three alkalinity map
classes were found within each of the 11 subregions. Thus, a total of 33 strata was
defined. Strata are coded by region, subregion, and alkalinity map class; for example,
2B1 designates the Upper Midwest Region (2), the Upper Peninsula of Michigan
Subregion (B), and alkalinity map class 1.
Map class boundaries according to region, subregion, and alkalinity class were
identified on l:250,000-scale USGS maps. All lakes represented on the map were
assigned a unique number, numbered consecutively according to location within the
mapping unit. Within each stratum, lakes were selected for sampling as a systematic
random sample. Non-target lakes, as defined in Section 2.1.1, were then eliminated by
examining larger-scale maps or during field operations. Approximately 50 lakes in the
target population were sampled per stratum, with a total of 146 lakes sampled in
Subregion 2B (Table 2.1, Figure 2-1).
For extrapolation from the sample of lakes to the target population within a
subregion or region, the sample data must be weighted by stratum-specific weights. The
2-3
-------
Figure 2-1. Geographic distribution of the lakes sampled in Subregion 2B during
(a) ELS-I and (b) ELS-IL
2-4
-------
ELS-I weighting factors (Wl) for Subregion 2B are presented in Table 2.1 and are
calculated as follows:
N*
Wl =
n*
where:
N* = the number of lakes in the frame population, and
n* = the number of lakes in the original ELS-I probability sample (including non-
interest lakes).
The estimated ELS-I target population size (N) for each stratum is then
calculated as:
JV=Wl(n***)
where:
n*** = the number of lakes sampled during ELS-I in the target population.
Procedures for calculating the variance and standard errors of population estimates are
outlined in Linthurst et al. (1986).
2.2 SURVEYS OF FISH COMMUNITY STATUS (ELS-n)
Fifty lakes in Subregion 2B were selected for surveys of fish community status as
part of ELS-n. Lakes to be surveyed were selected as a variable probcibility systematic
sample from among those lakes sampled during ELS-I. This approach is consistent with
the probability sampling frame used during ELS-I and was designed to optimize
assessment of the influence of key water chemistry variables on fish community status
and fish mercury content.
2.2.1 The Target Population
The ELS-I target population (Section 2.1.1) was further refined to eliminate
classes of lakes considered of little or no interest relative to the ELS-n objectives:
shallow lakes (site depth < 1.5 m), subject to winterkill and therefore unlikely
to support a significant fishery resource;
very large lakes (> 2000 ha), likely to exhibit considerable spatial variability
and thus difficult to adequately characterize both chemically and biologically;
2-5
-------
lakes highly enriched with nutrients that may distort the chemical composition
of the lakes and confound data interpretation; criteria include any of the
following:
- total phosphorus (P) > 90 peq/L
- nitrate (NOa) > 50 ueq/L
- ammonia (NH4) > 30 peq/L
- turbidity > 7 NTU
Secchi depth < 0.5 m
lakes modified by recent in-lake management practices resulting in a
disturbance of either biota or lake chemistry (e.g., recent stocking, lake liming,
rotenone treatment, dam removal);
lakes modified by anthropogenic disturbances to such an extent that the results
would not be representative of other lakes in the population (e.g., major
wastewater treatment plant discharge into the lake);
reservoirs less than 10 years old that may have experienced recent, major
influxes and mobilization of mercury associated with flooding land surfaces;
and
lakes heavily impacted by road salt or chloride (Cl) from other anthropogenic
sources (Cl > 100 peq/L), given that high levels of Cl may enhance mercury
mobilization and mask any potential influence of lake acidity on mercury
bioaccumulation.
Of the 146 lakes in Subregion 2B sampled in ELS-I, 41 were eliminated based on
the above exclusion criteria. Many of the lakes excluded (61%) were too shallow, with a
site depth < 1.5 m (Table 2.2). From the remaining 105 lakes sampled in ELS-I, 50 lakes
were selected for sampling in ELS-Q, as described in Section 2.2.2.
The ELS-IE target population size can be estimated in the same manner as
described in Section 2.1.2 for the ELS-I target population, adjusting for the change in
the number of ELS-I lakes sampled within the ELS-n target population. The weighting
factors per stratum do not change. The estimated size of the redefined ELS-n target
population is 596.7 lakes, as opposed to an estimated target population for ELS-I of
1050.0 lakes, in Subregion 2B (Table 2.1).
2.2.Z Statistical Design
Lake pH, inorganic Al, Ca, and DOC are considered the four chemical variables
most likely to influence fish community status and fish mercury content in acidic lakes
(Driscoll at al. 1980, Brown 1983, Altshuller and Linthurst 1984, Quinn and Bloomfield
2-6
-------
Table 2.2. Numbers of ELS-I Lakes Excluded from the ELS-H Target Population
in Subregion 2B
Stratum
Exclusion Category^
2B1
2B2
2B3
Subregion
Total
Site Depth <1.5 m 1
Lake Area >2000 ha 0
High Nutrients
P >90 peq/L
NO3 >50 peq/L
NH4 >30 peq/L
Turbidity >7 NTU
Secchi Depth <0.5 m
Modified by Recent
In-Lake Management
Anthropogenic 0
Disturbances
Recent Reservoir 0
Cl >100 peq/L Q
Total No. Lakes 5
6
0
18
0
0
0
0
0
0
4
0
0
0 .
0
1
4
1
0
0
0
0
44
25
0
1
0
0
0'
1
12
0
0
1
12
1
3
24
1
4
41
a Lakes may fit within more than one exclusion category; thus, the total number
of lakes excluded may be less than the sum of the individual categories.
1985). Levels of inorganic Al were not measured during ELS-I (Linthurst et al. 1986).
Levels of Ca and pH measured during ELS-I in Subregion 2B were highly correlated
(Figure 2-2). Thus, pH and DOC (Figure 2-3) were chosen as the two most important
factors to consider in lake selection.
The objectives of the sampling design were to select a probability subsample of
lakes from the ELS-I sample for Subregion 2B that (1) concentrated on lakes with low
pH, (2) covered the full range of DOC values, and (3) attempted to even-out the
inclusion probabilities (i.e., the inverse of the weighting factor) assigned in ELS-I. The
following methodology was used to select a subsample of 50 lakes for ELS-H from the
105 lakes sampled during ELS-I in the ELS-H target population.
2-7
-------
9-
8-
. * *
.. .
^ v "
r
500 1000 1500
CALCIUM (ueq/L)
2000
Figure 2-2. Relationship between pH and Ca for the 105 lakes in Subregion 2B
sampled during ELS-I and in the ELS-H target population.
8-
7-
6-
V .
5 10 15
DOC (mgfL)
20
Figure 2-3. Relationship between pH and DOC for the 105 lakes in Subregion 2B
sampled during ELS-I and in the ELS-H target population.
2-8
-------
For each lake, the function zi was calculated:
where pH is the lake pH (closed system) measured in ELS-I, and Wl is the ELS-I
weighting factor (Table 2.1). Inclusion of (pH)-7 in the calculation of zi increases the
probability of selecting lakes with lower pH levels, i.e., those lakes most likely to have
fish communities potentially impacted by acidification or higher levels of fish mercury
content resulting from lake acidity. The constant, 104, is an arbitrary value used to
adjust the scale of the function.
The 105 lakes were then ordered by DOC, and lakes to be;sampled during ELS-H
were selected from this ordered list by randomly picking a starting point and choosing
every Kth lake, where the distance between lakes is 2i. The sampling interval (K) for
selection of the systematic sample is defined by
IV
K~
where:
n - the number of lakes to be selected.
Thus, lakes for ELS-H were selected using a variable probability systematic procedure
with an inclusion probability for each lake proportional to zj (Cochran 1977).
A number of lakes with low pH arid/or a high value for Wl had Zi > K; as a result,
the probability of choosing these lakes in the sample is 100%. It was necessary,
therefore, to identify these lakes and to remove them from the lake list prior to
initiating the variable probability systematic sample selection. The initial value for K
(Ki) with n=50 was 0.39114. All lakes with 2i exceeding this value (n=ll) were edited
from the lake list and were automatically included in the ELS-H sample. A new value
for K (K2) was calculated based on the 94 lakes remaining and with n=39 (50-11). Ten
additional lakes had 2i values exceeding the new value of K (K2=0.23889), and thus were
also edited from the lake list and were included in the ELS-H sample. The process was
repeated a third time, with a third recalculated value for K (K3=0.22638). Two lakes
had zi > K3. Thus, 23 lakes were assigned to the ELS-H subsample with a conditional
inclusion probability (pc) of 1, leaving 27 lakes to be drawn based on a variable
probability systematic sample from the remaining 82 ELS-I lakes (K4=0.22581).
2-9
-------
For the 23 lakes selected with a Pc of 1, the ELS-n weighting factor (W2) equals
the ELS-I weighting factor (Wl). For all other ELS-H lakes, the weighting factor is
calculated as
K
z.
Values for zi, Wl, and W2 for the 50 lakes in Subregion 2B selected for sampling during
ELS-n are listed in Table 2.3. The estimated size (ft) and area (A) of the ELS-H target
population of lakes, based on this sample of 50 lakes and the ELS-n weighting factors,
are as follows:
ft = 642.3
Std. Error (ft) = 100.4
A = 22,003 ha
Std. Error (A) = 10,920 ha
The distinction between these estimates and those in Table 2.1 derived from the ELS-I
weighting factors (Wl) for the 105 ELS-I lakes in the ELS-H target population should be
noted.
At the request of the Michigan Department of Natural Resources, Lake 2B1-065
(Penegor Lake) was deleted from the list of lakes to be surveyed to avoid interference
with an ongoing study of fish populations in the lake. Excluding this lake from the
survey does not require redefinition of the ELS-n target population. Thus, 49 lakes in
Subregion 2B were sampled during ELS-H (Figure 2-1).
2-10
-------
Table 2-3. Last of Lakes Selected for ELS-II in Subregiion 2B
Lake ID
2B1-016
2B1-022
2Bl-035b
2Bl-038b
2Bl-039b
2Bl-040b
2B1-041
2Bl-042b
2Bl-047b
2Bl-048b
2Bl-052b
2B1-061
2B1-064
2B1-065"
2Bl-066b
2B2-004
2B2-007
2B2-024
2B2-038
2B2-044b
2B2-049b
2B2-055b
2B2-061
2B2-074
2B2-075
2B2-078
2B2-079
2B2-082
2B2-090b
2B2-098
2B2-100b
2B3-007b
2B3-008b
2B3-009
2B3-012
2B3-013b
2B3-020b
2B3-023
2B3-027
2B3-028
2B3-030b
2B3-031
2B3-034
2B3-037
2B3-051b
2B3-055
2B3-056b
2B3-057b
2B3-058b
2B3-071
* Zi=Wl*(pH-7)*104.
DOC
11.30
3.35
4.70
3.80
3.50
5.60
4.10
6.20
0.50
0.20
4.00
1.60
1.80
8.20
1.60
7.90
2.50
8.40
7.40
3.80
5.90
7.50
13.90
6.00
5.50
2.20
4.40
4.00
3.50
10.30
4.65
4.40
8.90
11.90
10.70
2.70
7.80
9.30
4.00
7.15
4.49
6.80
6.17
3.46
3.60
2.54
8.00
5.00
3.40
4.80
ELS-I
Weighting
pH Factor (Wl) z^
5.85
5.90
4.96
4.56
4.98
4.74
5.13
5.01
4.55
4.43
4.95
5.05
5.06
5.32
4.65
6.14
5.43
5.75
6.81
5.23
5.10
4.55
5.53
6.35
5.91
5.63
6.07
5.60
5.13
6.90
4.83
6.56
6.78
7.86
6.93
4.94
6.10
7.65
8.25
7.41
5.34
8.03
7.62
8.00
4.91
7.41
6.90
6.83
6.25
7.05
1.878
1.878
1.878
1.878
1.878
1.878
1.878
1.878
1.878
1.878
1.878
1.878
1.878
1.878
1.878
2.579
2.579
2.579
2.579
2.579
2.579
2.579
2.579
2.579
2.579
2.579
2.579
2.579
2.579
2.579
2.579
17.208
17.208
17.208
17.208
17.208
17.208
17.208
17.208
17.208
17.208
17.208
17.208
17.208
17.208
17.208
17.208
17.208
17.208
17.208
0.08009
0.07546
0.25429
0.45808
0.24722
0.34934
0.20085
0.23705
0.46517
0.56088
0.25790
0.22421
0.22113
0.15571
0.39951
0.07839
0.18529
0.12410
0.03797
0.24096
0.28738
0.63881
0.16307
0.06195
0.10241
0.14384
0.08494
0.14933
0.27582
0.034S3
0.42055
0.32916
0.26129
0.09285
0.22418
2.39685
0.54755
0.11223
0.06615
0.14028
1.38976
0.07993
0.11536
0.08205
2.50127
0.14028
0.23109
0.24819
0.46192
0.19880
ELS-II
Weighting
Factor (W2)
5.2947
5.6197
1.8780
1.8780
1.8780
1.8780
2.1114
1.8780
1.8780
1.8780
1.8780
1.8914
1.9178
2.7235
1.8780
7.4290
3.1430
4.6927
15.3385
2.5790
2.5790
2.5790
3.5713
9.4008
5.6867
4.0486
6.8560
3.9000
2.5790
16.8150
2.5790
17.2080
17.2080
41.8511
17.3333
17.2080
17.2080
34.6244
58.7394 '
27.6998
17.2080
48.6137
33.6849
47.3565
17.2080
27.6998
17.2080
17.2080
17.2080
19.5467
b Lakes selected with pc=l.
c Lake not surveyed at the reauest of the Michigan Denartment of Natural Rfismir^es
2-11
-------
-------
3. FIELD IMPLEMENTATION
Field activities at each lake included (1) an initial lake reconnaissance; (2) in situ
measurements of pH, conductivity, dissolved oxygen (DO), temperature, and Secchi
depth; (3) collection of water and sediment samples for subsequent chemical analysis;
(4) sampling of fish communities; and (5) preservation of a sample of fish for analysis of
tissue mercury content. Procedures for field sampling were described in detail in the
Field Training and Operations Manuals for the study (Fabrizio and Taylor 1987, Hagley
et al. 1987) and are summarized below. Activities and analyses specific to the study of
fish mercury content are described in EPA (in prep.).
3.1 FIELD PERSONNEL
Biological and chemical sampling operations were conducted concurrently.
Personnel from Michigan State University conducted fish sampling operations.
Personnel from Lockheed Engineering & Sciences Company collected water samples,
sediment samples, and in situ chemistry measurements. The 49 lakes were sampled by
two field crews, with five individuals per crew. All field personnel participated in a
two-day field training program (27-28 May 1987) on the field sampling protocol and
QA/QC procedures. This program provided hands-on experience with gear deployment,
fish handling procedures, fish identification, fish measurements, boat and trailer
handling, and proper data entry. Field crew leaders were given additional training in
lake reconnaissance, QA/QC procedures, and personnel management.
3.2 SAMPLING PERIOD
The 49 ELS-E lakes in Subregion 2B were sampled between 8 June and 30 August
1987 (Table 3.1). Ten lakes were resurveyed as part of the QA/QC protocol (Section 4)
between 31 August and 12 September 1987. In general, each lake was sampled over a
two-day period. Routine water sampling and fish net placement occurred on the first
day. During the second day, nets were retrieved and fish measured and processed.
Subregion 2B was subdivided into three zones corresponding with the location of
the three field base stations in Munising, MI; L'Anse, MI; and Iron River, WI. Within a
given zone, lake order for sampling was originally assigned at random to minimize
potential biases associated with any change in fish capture efficiency over time. Some
alteration of this predetermined schedule was necessary, however, due to problems with
lake access and a delay in initiating field sampling.
3-1
-------
Table 3.1. Sampling Dates (1987) and Fish Sampling Effort Per Lake
Units of Ef f orta
Lake ID
2B1-016
2B 1-022
2B1-035
2B1-038
2B1-039
2B1-040
2B1-041
2B1-042
2B1-047
2B1-048
2B1-052
2B1-061
2B1-064
2B1-066
2B2-004
2B2-007
2B2-024
2B2-038
2B2-044
2B2-049
2B2-055
2B2-061
2B2-074
2B2-075
2B2-078
2B2-079
2B2-082
2B2-090
Area
(ha)
4.2
8.6
4.3
6.3
15.7
4.5
19.7
8.3
16.7
£9.8
4.5
6.4
8.5
14.7
8.1
6.3
8.1
5.5
4.7
5.0
4.9
20.6
11.0
9.5
4.5
9.0
4.4
5.5
Sampling Date Gill Net Trap Net
24-25 Jun 3D 3
24-25 Jun 3 3
31 Aug-1 Sep 3 3
5-6 Aug 3 3
20-21 Aug 3 3
10-11 Sep 3 3
18-19 Jun 3 3
18-19 Jun 3 3
10-11 Aug 4 4
5-6 Aug 3 3
13- 14 Aug 3 3
12-13 Aug 6 6
12-13 Aug 3 3
24-25 Aug 3 3
20-21 Aug 3 3
6-7 Aug 3 3
22-23 Jun 3 3
16-17 Jul 3 3
8-9 Jul 3 3
27-28 Aug 3 3
24-25 Aug 3 3
30-31 Jul 3 3
8-9 Sep 3 3
30-31 Jul 3 3
1-2 Jul 4 4
23-24 Jun 3 3
1-2 Sep 3 3
26-27 Jun 3 3
31 Aug-1 Sep 3 3
13-14 Jul 3 3
2-3 Sep 3 3
22-23 Jul 3 3
13-14 Jul 3d 3
14-15 Jul 3 3
Seine Angling
~ " ~ ~ " yj
f\f 7
QC L
4 2
*"*
4 2
4-y
&
4 2
QC ic
i\f* 7
QC C,
57
&
4">
&
47
£
6-)
£
tr- *>
3C L
4-)
6
4-)
t*
47
t>
Af *y
l)c tf
4f
C*
40
£
4-)
&
4-j
&
/\« O
Oc £
3c 2
4 2
57
*
40
£
4 2
QC 2
4 2
A
3c 2
4 2
4 2
47
^
47
L
(continued)
3-2
-------
Table 3.1. Continued
Lake ID
2B2-098
2B2-100
2B3-007
2B3-008
2B3-009
2B3-012
2B3-013
2B3-020
2B3-023
2B3-027
2B3-028
2B3-030
2B3-031
2B3-034
2B3-037
2B3-051
2B3-055
2B3-056
2B3-057
2B3-058
2B3-071
Area
(ha)
26.2
12.7
11.6
4.4
262.3
16.7
4.6
9.7
63.2
21.7
32.3
14.7
38.0
16.8
7.6
6.6
5.5
9.1
18.5
13.2
21.7
Sampling Date
6-7 Jul
2-3 Jul
8-9 Sep
20-21 Jul
27-28 Aug
3-4 Aug
6-7 Jul
17-18 Aug
15-16 Jul
29-30 Jun
30 Jun-1 Jul
8-9 Jun
15-16 Jun
10-11 Aug
11-12 Jul
28-29 Jul
11-12 Sep
17-18 Aug
28-29 Jul
22-23 Jul
7-8 Jul
3-4 Sep
9-10 Jul
2-3 Sep
15-16 Jun
Gill Net
1C
3
3
3
3
8
3
3d
3
?e
4
5b
3
5
3
3
3
3
3
3
3
3
3
3
4
%***JL*0 *JM. J
Trap Net
4
2c
3
3
3
8
3
3
3
7
4
5
3
5
3
3
3
3
3
3
3
3
3
3
4
L_rtJ..B.«_». t
Seine
DC
4
4
4
DC
8
4
4
DC
8
5
5
4
5
3c
4
4
4
4
4
DC
4
4
4
5
Angling
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
b
c
d
e
Units of effort:
Gill net and trap net Number of nets set overnight
Seine Number of hauls
Angling Hours
Problems setting gear, with potential reductions in gear effectiveness.
Sampling effort less than proposed (standard) sampling effort; see Table 3.3.
One gill net set deeper than desired, but still fished effectively.
All nets set during the day for a shorter period of time (10-13 h), but still fished
effectively.
3-3
-------
Twenty-seven lakes were sampled from the Munising base station: 6 lakes at the
beginning of the sampling period (8 to 19 June) and 21 lakes at the end of the sampling
period (28 July to 30 August). The five lakes in Wisconsin were sampled from the Iron
River base station between 22 and 27 June. The 17 lakes near the L'Anse base station
were sampled 29 June to 23 July.
It is not expected that the variation in sampling dates, distributed over the threer
month sampling period, had a significant effect on the survey results or on the observed
patterns in fish community status. Except for lake elevation (Spearman's rank
correlation coefficient, r=-0.41), sampling date and lake characteristics were not
significantly correlated (at d=0.05 adjusted for 14 tests, p > 0.0036) (Table 3.2).
Analyses to evaluate the potential influence of sampling date on sampling efficiency are
discussed further in Section 4.2.
Table 3.2. Nonparametric Correlation Between Sampling Date and Lake
Characteristics
Variable
Spearman's Rank Correlation Coefficient
Lake Area
Depth
Elevation
Secchi Depth
pH
Ca
DOC ,
Al, Extractable
Sum Base Cations
ANC
Color
SO4
SiO2
Total P
-0.30
0.12
-0.41*
0.22
-0.33
-0.21
-0.32
-0.03
-0.24
-0.31
-0.21
0.06
-0.13
-0.15
* Correlation coefficient significant at «=0.05, adjusted for 14 tests, p =£ 0.0036.
Key: SO4 = sulf ate; SiOz = silica
3-4
-------
3.3 INITIAL LAKE RECONNAISSANCE
Prior to initiating field sampling activities, a reconnaissance of the lake was
conducted to select sites for deployment of fish sampling gear. Shoreline maps were
prepared identifying the approximate extent and location of various features and habitat
types in the lake littoral zone. Habitat types were defined based on the following
characteristics: water depth; slope of the lake bottom; abundance and type of aquatic
vegetation (emergent, submergent, floating); location of permanent inlets, outlets,
shoals, or other physical features (docks, woody debris, beaver dams, etc.); DO; and
temperature (see Section 3.4). These maps were not intended as an accurate depiction
of littoral zone features, but as an aid for selecting specific sites for sampling.
Bathymetric maps for the lake were also referenced, if available.
Appropriate sampling sites for fish were designated by the field crew leader and
identified on the shoreline map. Sites selected were dispersed around the lake and
included the following: a range of water depths and bottom slopes (e.g., shallow regions
with a wide littoral zone and steeper shorelines and littoral zones); regions near major
inlets; regions in the immediate vicinity of the lake outlet(s); sheltered bays and open
promontories; and regions with different types of shoreline vegetation (e.g., coniferous
forests, deciduous forests, marshes). More specific guidelines for selecting sampling
sites were provided in the Fisheries Field Training and Operations Manual (Fabrizio and
Taylor 1987). The objective was to sample the full diversity of lake habitats in order to
collect as many fish species as possible within the limitations of the sampling gear.
3.4 IN SITU MEASUREMENTS
In situ measurements were taken at the ELS-I sampling site over the deepest part
of the lake (Linthurst et al. 1986, Landers et al. 1988). In situ measurements consisted
of Hydrolab determinations of water temperature, DO, pH, and specific conductance
and determinations of Secchi transparency, air temperature, and site depth (Hagley et
al. 1987). The Hydrolab was calibrated each morning prior to sampling, a field quality
control check (QCC) was performed after arrival at the lake, and a final QCC was
completed at the end of the day at the base site. Measurements with the Hydrolab were
made first at 1.5 m below the water surface, then at 1.5 m above the lake bottom. If
the temperature difference between these two depths was greater than 4 °C, the lake
was considered stratified and a full vertical profile of measurements was conducted.
Profile measurements were taken at 1-m intervals from 2.5 m to 10.5 m below the
surface and at 2-m intervals from 10.5 m to 1.5 m above the lake bottom.
3-5
-------
Depth graphs of temperature and DO were provided to the field crew leader to
assist in selecting fish sampling locations. Hypoxic layers (with DO < 4 mg/L) were not
fished. If a lake was determined to be thermally stratified, fish sampling sites were
selected to include the thermocline and the upper hypolimnion.
3.5 COLLECTION OF WATER AND SEDIMENT SAMPLES
A routine water sample included two 60-mL polyethylene syringes (collected
without exposure to air) for pH and Al analyses and one 500-mL polyethylene bottle for
DOC, F, metals, and elements analyzed by inductively coupled plasma mass
spectrometry. Additionally, water and sediment samples were collected in 2.5-L glass
bottles and 60-mL Teflon jars, respectively, for mercury analyses (EPA, in prep.).
Water samples were collected with a 6.2-L Van Dorn bottle at 1.5 m.
After water samples were collected, they were capped and stored in a cooler with
frozen gel packs. Sediment samples for mercury analysis were placed in a separate
cooler with frozen gel packs. The two syringe samples and the 500-mL aliquot of lake
water were shipped from the base station to the Las Vegas processing laboratory within
24 hours from the time of collection.
3.6 FISH SURVEYS
3.6.1 Sampling Gear and Effort
Fish communities were sampled with four gear types: experimental gill net,
modified Indiana trap net, beach seine, and hook and line (angling). Experimental gill
nets consisted of five panels, each 7.6 m (25 ft) long and 1.8 m (6 ft) deep, of variable-
dimension, monofilament nylon (25-, 38-, 51-, 64-, and 76-mm stretch mesh). Trap nets
consisted of a 1.8 m by 0.9 m (6 ft by 3 ft) front box (19-mm stretch mesh) with two 6-m
(20-ft) wings and a 15.2-m (50-ft) leader. Beach seines were 1.2 m (4 ft) deep and 7.6 m
(25 ft) long of 4.8-mm woven mesh nylon. Angling was employed as a supplemental
sampling procedure focusing on larger game fish, to be used for analysis of fish mercury
content (EPA, in prep.). Detailed procedures and protocols for gear deployment and
retrieval are outlined in the Fisheries Field Training and Operations Manual (Fabrizio
and Taylor 1987).
With the exception of angling, the number of units of gear deployed varied as a
function of lake area (Tables 3.1 and 3.3). Deviations from the proposed standard
sampling effort occurred in some instances due to sampling problems or constraints
imposed by the Michigan Department of Natural Resources or private owners. The
3-6
_
-------
sampling effort applied was lower than proposed in one lake each for gill nets, trap nets,
and angling (Lakes 2B2-098, 2B2-100, and 2B1-039, respectively) (Table 3.1). Use of
beach seines was limited by the availability of suitable shoreline areas for effective
seining (i.e., shallow littoral areas without major obstructions or snags). Eleven of the
49 ELS-H lakes (22.4%) were not sampled with beach seines during the June-August
survey (Table 3.1).
Table 3.3. Standard Fish Sampling Effort Per Lake
Lake Area
(ha)
<20
20-29
30-39
40-59
60-79
>80
Experimental Gill
Nets
(number of
overnight sets)
3
4
5
6
7
8
Trap Nets
(number of
overnight sets)
3
4
5
6
7
8
Beach Seines
(number of
20-m hauls)
4
5
5
6
7
8
Angling
(h)
2
2
2
2
2
2
Gill nets and trap nets were set in the afternoon and retrieved the next morning,
with one exception. In Bone Lake (2B3-023), the Michigan Department of Natural
Resources requested that gill nets be set only during the day, for one day (10-13 hours
per net). Nets were set for periods ranging between 10 and 29 hours, although, in most
cases (87%), overnight sets lasted between 18 and 24 hours. In general, trap nets were
deployed and retrieved before gill nets. -Nets were tended in the same order in which
they were set.
Seining and angling were conducted on the first day, usually in the afternoon. One
unit of effort for the beach seine refers to one seine haul along approximately 20 m of
shoreline. Each unit of effort was applied at a different sampling location. Angling
effort involved two hours of hook and line fishing (one hour per each of two crew
members) using Mr. Twister spinner bait lures cast from a boat at various locations
around the lake. The time of day varied depending on the crew's schedule at the lake.
3-7
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3.6.2 Field Measurements and Samples
Most fish collected were identified to species in the field. Specimens of
questionable identity (e.g., apparent hybrids, uncommon species with limited
distributions) or in taxonomically difficult groups (e.g., minnows, shiners) were
preserved and returned to the base station for identification. These specimens were
processed, identified, and coded to the lowest possible taxonomic level in the field, prior
to preservation. The following references were used for fish identification: Scott and
Grossman (1973), Eddy (1969), and Hubbs and Lagler (1947).
All individuals caught were counted by species. Partial specimens were handled by
including all identifiable heads in the total count; pieces without heads and
unidentifiable head segments were discarded. Numbers of fish caught were tallied by
gear type, station (unit of sampling effort), and species on standard field data forms.
Game and index species were measured for length and weight and sampled for age
estimation. The following were defined as game species:
walleye
smallmouth bass
largemouth bass
northern pike
yellow perch
lake trout
brook trout
rainbow trout
Stizostedion vitreum
Micropterus dolomieui
Micropterus salmoides
Esox lucius
Perca flavescens
Salvelinus namaycush
Salvelinus fontinalis
Ohcorhynchus mykiss
Three species were defined as index species for mercury analyses:
yellow perch Perca flavescens
white sucker Catostomus commersoni
northern pike Esox lucius
Other species were also measured for length and weight and sampled for age estimation
if time permitted.
Total length measurements were tallied in 25-mm length intervals, by species and
sampling unit. Individual lengths and weights were recorded and samples collected for
age estimation for five fish (if available) per Z5-mm length class per species. Fish were
weighed using a spring balance (for individual or groups of fish > 0.5 kg) or portable
electronic balance (for fish < 0.5 kg). Balances were zeroed prior to each use and
checked for accuracy using a known weight at the beginning and end of each day and
3-8
-------
after every 30 fish. Weekly calibration checks were conducted with a series of known
weights. Fish weight was recorded to the nearest 2 g for the spring scale and 1 g for the
electronic balance; fish length was recorded to the nearest millimeter. Ten percent of
the specimens (by species) were re-measured and re-weighed by a different crew
member for estimates of precision (Section 4.2.1). Specimens re-weighed were not
necessarily the same as those re-measured for length.
Scales, cleithra, or pectoral fin rays were collected to estimate fish age depending
on the species:
walleye
smallmouth bass
largemouth bass
northern pike
yellow perch
lake trout
brook trout
rainbow trout
white sucker
scale
scale
scale
cleithrum
scale
scale
scale
scale
pectoral fin ray
Results from these analyses are presented in the report on fish mercury content
(EPA, in prep.)
Selected specimens were preserved as a reference sample for the survey, including
a set of representative specimens (up to three per species) for each species collected
and any unidentified specimens or species of questionable identity. Species
identifications were confirmed by Dr. L. Greenberg, ichthyologist, Michigan State
University. No fish with obvious abnormalities were collected. Also, no species
recognized by state agencies in Michigan and Wisconsin as rare, threatened, or
endangered were encountered.
3-9
-------
-------
4. QUALITY ASSURANCE/QUALITY CONTROL
Quality assurance (QA) and quality control (QC) procedures were implemented for
all aspects of the ELS-n survey of fish community status in Subregion 2B. Major
components of the QA/QC program were as follows:
audits of field crews by supervisory personnel from Lockheed and Michigan
State University to ensure compliance with the specif ied Scimpling protocol;
a field and laboratory QA/QC program for all chemical analyses, including
field and laboratory audit samples, field blanks, and field replicates;
replicate measurements of fish length and weight and analyses for fish age
estimation;
duplicate sampling of fish communities in 10 lakes to quantify fish sampling
variability (through time across the sampling period and between the two field
crews); and
rigorous data base verification and validation procedures, similar to those used
during ELS-I.
4.1 WATER CHEMISTRY
The measurement methods and QA objectives for precision, accuracy, and
detectability for physicochemical parameters measured during the ELS-I and ELS-n are
summarized in Tables 4.1 and 4.Z, respectively. The QA/QC procedures and results for
the ELS-I were described in detail in Linthurst et al. (1986) and Drouse et al. (1986).
Results from the ELS-n QA/QC program are summarized in Tables 4.3 and 4.4; the
ELS-n procedures and protocol are described in Appendix A (Volume H).
The overall within-batch (system) precision for the sampling, processing,
transportation, and analysis process for samples collected on a given, day (defined as a
batch) was estimated for 16 field replicates: four samples from each of four lakes. A
field replicate is an additional sample collected at the lake site by the same field crew
immediately after the routine sample is collected. The precision data quality objective
(DQO) of 10% (Table 4.2) was achieved, except when analyte concentrations were less
than ten times the required detection limit (Table 4.3).
The between-batch precision was estimated from multiple analyses of one natural
and three synthetic samples analyzed on different days, i.e., within different batches
(Table 4.3). The between-batch precision (expressed as the relative standard deviation)
was generally larger than the within-batch precision for most parameters. The DQOs
apply only to within-batch precision.
4-1
-------
Table 4.1. Quality Assurance Objectives for Precision, Accuracy, and Detectability,
and Measurement Methods for Physicochemical Parameters Measured
during ELS-I
Precision
Relative
r ' Standard Accuracy
Required " " Deviation Maximum
Detection Upper Limitb Absolute
Parameter* Units Limits (%) Bias (%) Method
Al, Total
Al, Total
Extractable
Acidity
(BNC)
Alkalinity
(ANC)
Ca
Cl
True Color
DIG
DOC
F, Total
Fe
K
Mg
pg/L,,;
pg/L, ,
peq/L ,
^-
mg/L* '
mg/L
Color -
Unitsc 1
, nig/L ,. '.
mg/L
Pg/L
-mg/Ly
mg/L
mg/L
0.5
'V5
-. 5
« ' * C ' ,
'-0.01-'
0.01
0
.,.,0.05 :
0.1
5
v-;o.oi
0.01
0.01
10 (<10)
20(<10)
20 (<;10)
10
10
5
5
±5d
10
5(>5)
10(^5)
5
10
5
5
10/20
10/20
10
10
10
10
10
10
10
10
10
10
EPA Method 202.2
(AASXfurnace)
Extraction with 8-
hydroxyquinoline into
MIBK followed by AAS
(furnace)
Titration with
Gran plot
Titration with
Gran plot
EPA Method 215.1
-AAS (flame)
Ion chromatography
Hatch Model CO-1
color determination
Instrumental (similar to
DOC)
EPA Method 415.2
Ion selective electrode
EPA Method 236.1 -
AAS (flame)
EPA Method 258.1 -
AAS (flame)
EPA Method 242.1 -
* * /-t / r»i \
AAS (flame)
(continued)
4-2
-------
Table 4.1. Continued
Parameter
P, Total
Precision
Relative
Standard Accuracy
Required Deviation Maximum
Detection Upper Limit*1 Absolute
Units Limits (%) Bias (%)
Method
Mn
Na
NH4
NO3
pH, Field
pH,
Analytical
Laboratory
mg/L 0.01
mg/L 0.01
mg/L 0.01
mg/L 0.005
pH
units
pH
units
10
5
5
10
±0.ld
±0.05d
10
10
10
10
±0.ld
±0.ld
EPA Method 243.1 -
AAS (flame)
EPA Method 273.1 -
AAS1. (flame)
EPA Method 350.1
Ion chromatography
pH electrode and meter
pH electrode and meter
Turbidity
Hg/L
SiOz
Si04
Specific
conductance
mg/L
mg/L
pS/cm
0.05
0.05
e
5
5
1
10
10
5
NTU
10(>10) 10/20 USGS Method 1-4600-78
20 (>10) of Modified USGS
method
USGS Method 1-2700-78
Ion chromatography
EPA Method 120.1
10 10 Monitek Model 21
nephelometer
a Dissolved ions and metals determined, except where noted.
h Unless otherwise noted, this is the relative standard deviation for concentrations
above 10 times the required detection limits.
c APHA platinum-cobalt units.
d Absolute precision goal in terms of applicable units.
e Blank must be < 0.09 pS/cm.
Key: AAS = atomic absorption spectroscopy; BNC = base neutralizing capacity;
DIG = dissolved inorganic carbon; Fe = iron; K - potassium; Mg = magnesium;
Mn = manganese; Na = sodium.
4-3
-------
Table 4.2. Quality Assurance Objectives for Precision, Accuracy, and Detectability
and Measurement Methods for Physicochemical Parameters Measured
during ELS-n in Subregion 2B
Precision
Relative
Standard Accuracy
Required Deviation Maximum
Detection Upper Limit* Absolute Bias
Parameter Units
Al, total pg/L
monomericb
Al, non- Pg/L
labile
monomericb
DOC mg/L
F, total ng/L
dissolved
Limit (%)
7 10 (>10)
20 ( s 10)
7 10 (>10)
20(<10)
0.1 5 (>5)
10(^5)
5 5
(%) Method
10 (>10) Flow
20(^10) injection
analysis
10 (>10) Flow
20(<10) injection
analysis
10 EPA
Method
415.2
10 Ion
Selective
Electrode
Specific pS/cm
conductance
pH,
laboratory
pH, field
pH units
pH units
±0.0ic
±0.ic
Hydrolab
±0.05c pH
electrode
±0.ic
Hydrolab
a Unless otherwise noted, this is the relative standard deviation for concentrations
above 10 times the required detection limit.
Labile monomeric Al, an estimate of the inorganic Al fraction, is calculated
the difference between total monomeric Al and non-labile monomeric Al.
c Precision and accuracy in absolute units.
b Labile
as
4-4
-------
Table 4.3. Estimates of Precision for Physicochemical Parameters Measured
during ELS-H
Lake ID or
Sample Code
pH
Routine Data Range:
4.45-8.74
2B1-048
2B2-061
2B2-079
2B3-009
FN10
LS6
LS7
LS8
Total Monomeric
AHug/L)
Routine Data Range:
124-207
2B 1-048
2B2-061
2B2-079
2B3-009
FN10
LS6
LS7
LS8
Non-Labile Monomeric
Al(ug/L)
Routine Data Range:
8.2-76.4
2B1-048
2B2-061
2B2-079
2B3-009
FN10
LS6
LS7
LS8
N
4
4
4
4
11
6
6
6
4
4
4
4
11
5
6
5
4
4
4
4
11
5
6
5
Mean
4.42500
5.58750
6.30500
8.17000
5.10455
4.28167
6.24333
8.52000
205.75
94.50
14.52
24.85
133.91
16.64
117.90
252.16
13.925
74.375
17.850
17.225
39.982
14.200
10.333
18.920
Standard
Deviation
0.02082
0.02630
0.06758
0.00816
0.06743
0.06882
0.11396
0.19204
1.328
2.159
1.756
6.648
4.059
2.476
4.785
15.615
1.2500
2.5851
1.3000
3.2253
5.7616
2.1012
5.1329
3.5181
Relative
Standard Type of
Deviation Precision
(%) Estimate*
0.47
0.47
1.07
0.10
0.65
2.28
12.09b
26.75b
. 8.98
3.48
7.28
18.72b
WB
WB
WB
WB
BB
BB
BB
BB
WB
WB
WB
WB
BB
BB
BB
BB
WB
WB
WB
WB
BB
BB
BB
BB
(continued)
4-5
-------
Table 4.3. Continued
Lake ID or Sample Code
N
Mean
Standard
Deviation
Relative
Standard
Deviation
Type of
Precision
Estimate*
DOC (mg/L)
Routine Data Range:
0.4-21.8
2B1-048
2B2-061
2B2-079
2B3-009
FN10
LS6
LS7
LS8
4
4
4
4
11
5
5
5
0.325
21.500
4.000
4.775
3.200
1.100
7.420
14.520
0.05000
0.35590
0.31623
0.41932
0.17889
0.07071
0.20494
0.42071
15.38b
1.66
7.91
8.78
WB
WB
WB
WB
BB
BB
BB
BB
Total F
(pg/L)
Routine Data Range:
5-76,
2B1-048
2B2-061
2B2-079
2B3-009
FN10
LS6
LS7
LS8
4
4
4
4
11
5
6
5
13.750
18.750
6.250
46.250
66.273
8.600
38.000
72.800
0.9574
2.6300
2.0616
1.2583
4.2916
2.5100
3.2863
6.9785
6.96
14.03b
32.99k
2.72
WB
WB
WB
WB
BB
BB
BB
BB
a WB- Within Batch
BB - Between Batch
b Concentration of the replicates was less than 10 times the required detection limit.
4-6
-------
10.0
0.30
10.0
4.50
16.64
1.10
8.6
4.282
66.40
266.67
14.00
4.85
Table 4.4. Estimate of Laboratory Accuracy Using Synthetic Aud^!elative
Theoretical Difference
Parameter Value MeanVakie (%)
Audit Type: LS6
Total Monomeric Al (pg/L)
DOC (mg/L)
F(pg/L)
pH
Audit Type: LS7
Total Monomeric Al (pg/L)
DOC (mg/L)
F (pg/L)
PH
Audit Type: LS8
Total Monomeric Al (pg/L)
DOC (mg/L)
F (pg/L)
PH
125.0
7.50
40.0
6.50
117.9
7.42
38.0
6.243
5.68
1.07
5.00
3.95
250.0
15.00
80.0
8.50
252.16
14.52
72.8
8.520
0.86
3.20
9.00
0.23
Results from the synthetic audit samples also provide estimates of the
measurement accuracy (A), calculated as the relative percent difference:
A =
*100
where:
X = the mean measured concentration for the audit sample, and
T = the theoretical value for the audit sample.
At concentrations near the detection limit (e.g., audit sample LS6), the values for
relative percent difference for total monomeric Al, DOC, and total F were quite high
(14-267%) (Table 4.4). For audit samples at middle to high concentrations, on the other
hand, the absolute bias was below 10% for all parameters, indicating a reasonable level
of accuracy within the DQOs (Table 4.2). The accuracy of measurements of non-labile
4-7
-------
monomeric Al could not be assessed* since the theoretical levels of non-labile
monomeric Al in the audit samples were not known.
4.2 FISH SURVEYS
4.2.1 Field Measurements
Duplicate measurements of fish length and weight were conducted on a random
10% sample of fish. Differences in length measurements averaged 1.4 mm (standard
deviation =1.7 mm). Weight measures differed by an average of 2.1 g (standard
deviation = 5.4 g). In most cases (72%), differences in length and weight between the
duplicate measurements were < 1% of the mean, indicating a high level of precision for
both measurements.
4.2.2 Duplicate Fish Surveys
In order to obtain an estimate of sampling variability^ 10 of the 49 lakes were
sampled twice over the three-month sampling period. All 49 lakes were sampled
initially (standard sample) between 8 June and 30 August 1987. Resampling of the 10
lakes for QA/QC occurred between 31 August and 12 September. In general, the two
surveys per lake were conducted by different field crews. Differences in results from
the duplicate surveys reflect, therefore, the combined effect of several major sources
of variation, including the sampling error for the ELS-n survey protocol, any trends
through time in fish catchability, and crew-to-crew differences in sampling
effectiveness. Given the effort required to complete a comprehensive fish survey per
lake, it was not possible to conduct sufficient sampling to separately quantify the
individual components of the total error term.
Several factors were considered in selecting lakes for resampling, including (1) the
need for additional fish of certain species for mercury analysis, (2) the time of the first
sample, and (3) the catch in the first sample (including lakes with few or no fish as well
as lakes with relatively large numbers of fish caught). Thus, the 10 lakes were not
selected at random, but were chosen based on examination of results from the initial
fish survey.
Four major types of data were collected on fish communities in lakes in
Subregion 2B:
1. species richness, i.e., the total number of fish species caught per lake;
2. presence/absence of individual fish species, estimated from the presence or
absence of the species in the catch (catch/no catch);
4-8
-------
3. relative fish abundance, estimated from the total number of fish caught (by
species) or the catch per unit of sampling effort [catch per unit effort (CPUE)]j
and
4. fish size and condition, based on measurements of fish length and weight.
Results from the duplicate surveys of the 10 QA/QC lakes are discussed below for each
of these indices of fish community status.
Measures of species richness were not significantly different (p > 0.05) for the two
sample periods, based on a Wilcoxon signed rank test (Hollander and Wolfe 1973). Equal
values were recorded for 7 of the 10 lakes, while in 3 lakes species richness measured in
the initial sample exceeded species richness in the second sample by one to two species
(Table 4.5). In addition, measures of species richness in all 49 lakes were not
significantly correlated (p > 0.05) with either sampling sequence (date) or the total
number of fish caught per lake, based on a Spearman's rank correlation (Hollander and
Wolfe 1973).
Czekanowski's similarity coefficient (Sc) (Bray and Curtis 1957) was calculated as
a measure of the similarity in species composition in the two samples per lake
(Table 4.5):
o
~
X.+ X.
j *
where:
Xj = the number of species in the first sample,
Xfc = the number of species in the second sample, and
Xjk = the number of species common to both samples.
One lake had no fish caught in either survey (Sc undefined). Five lakes had exactly
the same complement of species caught in both surveys (Sc = 1.0), arid one additional
lake had Sc = 0.91, indicating a high degree of similarity. Of the three remaining lakes,
two had Sc = 0.67, while one had Sc = 0 (Lake 2B2-078, with one fish species caught
during the initial survey but no fish caught in the duplicate sample). The types of fish
species present in one but not both samples varied for each lake.
The Fisher exact test (Fleiss 1981) was used to evaluate potential trends in the
presence/absence (catch/no catch) data by species. Four species occurred in a
sufficient number of the 10 QA/QC lakes for calculation of a valid chi-square test:
yellow perch, largemouth bass, northern pike, and bluegill sunf ish. In each case, the
proportion of lakes containing the species did not vary significantly (p > 0.05) between
the duplicate surveys.
4-9
-------
Table 4.5. Summary of Results for Species Richness from Duplicate Surveys of Ten
Lakes
Lake ID
2B1-022
2B1-038
2B2-049
2B2-074
2B2-075
2B2-078
2B2-100
2B3-037
2B3-057
2B3-058
Sample Dates
25 Jun
1 Sep
21 Aug
11 Sep
30 Jun
9 Sep
24 Jun
2 Sep
27 Jun
1 Sep
14 Jul
3 Sep
3 Jul
9 Sep
29 Jul
12 Sep
8 Jul
4 Sep
10 Jul
3 Sep
Species
Richness
4
2
0
0
1
1
3
3
4
4
1
0
1
1
11
11
7
5
1
1
Coefficient
of Variation^
47.1
-
0
0
0
141.4
0
0
23.6
0
Similarity
Coefficient^
0.67
-
1.0
1.0
1.0
0
1.0
0.91
0.67
1.0
a Coefficent of variation calculated as the standard deviation divided by the mean
for the duplicate samples, assuming a normally distributed within-lake variance.
b Czekanowski's similarity coefficient defined as two times the number of species
common to both samples divided by the sum of the number of fish species caught
in the first sample plus the number caught in the second sample.
All of the above analyses indicate that the sampling errors associated with
measuring species richness and fish species presence/absence in the ELS-H were
relatively minor and are not likely to measurably bias comparisons of fish community
status among lakes.
Results from the duplicate samples for total fish catch and CPUE are summarized
in Table 4.6. Given the high degree of variability in fish catch rates for angling and
beach seines, only fish collected using gill nets and trap nets are included in these
analyses. CPUE is calculated as the mean per net per hour fished. Coefficients of
variation for CPUE calculated per hour per net tended to be equal to or less than the
coefficients of variation for CPUE calculated on a per net (per overnight set) basis.
4-10
-------
Table 4.6. Summary of Results for Fish Catch (All Species Combined) for the
Duplicate Surveys of Ten Lakes
CPUE (fish/h/net)
Total Catena
Lake ID
2B1-022
2B1-038
2B2-049
2B2-074
2B2-075
2B2-078
2B2-100
2B2-037
2B3-057
2B3-058
Sample
Dates
25 Jun
1 Sep
21 Aug
1 1 Sep
30 Jun
9 Sep
24 Jun
2 Sep
27 Jun
1 Sep
14 Jul
3 Sep
3 Jul
9 Sep
29 Jul
12 Sep
8 Jul
4 Sep
10 Jul
3 Sep
Mean
28
60
0
0
792
538
3000
706
129
95
1
0
204a
253
238
77
97
14
2403
4555
Coefficient
of Variation
(%)
51.4
-
27.0
87.5
21.5
141.4
15.2
72.3
105.7
43.7
Gill Net
Mean
0.13
0.07
0
0
10.45
4.73
0.50
0.97
0.83
0.44
0
0
2.47
0.93
1.29
1.06
0.37
0.16
4.91
4.26
Coefficient
of Variation
(%)
45.2
-
53.3
44.5
42.5
-
64.4
13.7
57.7
10.0
Trap
Net
Coefficient
of Variation
Mean (%)
0.27
0.98
0
0
1.26
3.80
67.23
11.38
1.12
1.56
0.01
0
1.49
2.98
2.28
0.40
1.33
0.16
27.52
64.85
80.1
-
70.8
100.5
23.1
141.4
47.1
98.8
111.9
57.2
a Total catch based on gill and trap nets only. All lakes were fished with three gill
nets and three trap nets each date. However, in the 3 July sample for lake 2B2-100,
fish were lost from one of the three trap nets and thus could not be included in the
value for total catch.
4-11
-------
Values for total catch and CPUE in trap nets and gill nets were not significantly
different (p > 0.05) between the two sample dates, based on the Wilcoxon signed rank
test. In addition, no significant trend in fish catch over time was detected for the
49-lake data set (p > 0.05, Spearman's rank correlation).
The coefficient of variation for the duplicate measures of catch ranged between
15.2% and 141.4% for total catch, 9.5% and 141.4% for trap-net CPUE, and 10.0% and
64.4% for gill-net CPUE. Jn six of eight lakes with fish caught in both surveys in both
gear types, the variance in CPUE (and coefficient of variation) for trap nets exceeded
that for gill nets. The variability in fish catch (and CPUE) was also generally higher in
lakes with more fish caught (Figure 4-1).
1200
IIOO
1000
900
p 800
700
fc.
o
« 600
O
K
K
W
Q 500
CS
400
300-
200
100
' i '
1000
2000
MEAN TOTAL CATCH
3000
T
4000
Figure 4-1. Standard error for the duplicate measures of total catch, as a
function of the mean catch per lake.
4-12
-------
Assuming a constant capture (sampling) efficiency (q), the numbers of fish caught
(C) per unit sampling effort (f) (i.e., the CPUE) should be directly proportional to fish
abundance in the lake (N):
C=q*f*N
A large number of factors, however, influence fish capture efficiency, many of which
cannot be controlled by simply standardizing sampling methods, season, effort, and
location. As a result, for a constant N, the variability in CPUE is typically quite high,
making detection of patterns among lakes, or over time in a given lake, difficult (Ricker
1975, Bannerot and Austin 1983). The variability in catch and CPUE observed for the
ELS-n data is not atypical of that observed in most fisheries data sets. Although the
data are limited (only 10 lakes with duplicate samples), there is no indication of bias or
trends in capture efficiency that might result in misinterpretation of the survey results.
Four lakes had a sufficient number of a given species caught and measured to
compare estimates of fish size and condition factors from the duplicate surveys
(Table 4.7): yellow perch in lake 2B2-049; yellow perch in lake 2B2-100; yellow perch
and largemouth bass in lake 2B2-075; and yellow perch, largemouth bass, white sucker,
and northern pike in lake 2B3-037. Differences in fish length, weight, and condition in
the duplicate samples (paired by species, by lake) were not significant (p > 0.05,
Wilcoxon signed rank test).
4-13
-------
Table 4.7. Comparison of Fish Length, Weight, and Condition Factors for the Duplicate
Surveys of Ten Lakes
Total Length
(mm)
Species
Yellow
Perch
Largemouth
Bass
White
Sucker
Northern
Pike
Lake ID
2B2-049
2B2-075
2B2-100
2B3-037
2B2-075
2B3-037
2B3-037
2B3-037
Sample
Dates
30 Jim
9Sep
27 Jun
1 Sep
3 Jul
9 Sep
29 Jul
12 Sep
27 Jun
1 Sep
29 Jul
12 Sep
29 Jul
12 Sep
29 Jul
12 Sep
N
44
37
32
14
42
39
43
20
7
9
6
5
12
11
7
9
Mean
138.6
148.6
124.7
153.8
159.0
155.1
128.6
117.3
250.6
143.1
103.8
197.2
306.9
284.6
632.0
651.7
Std.
Dev.
24.8
46.3
17.3
46.7
26.1
27.4
33.0
6.1
60.9
114.3
25.4
146.8
82.7
70.1
75.0
120.3
Weight (g)
Mean
29.7
44.9
19.9
44.6
43.6
41.3
25.8
14.8
240.7
133.0
15.0
360.8
334.3
299.0
1462.9
1675.2
Std.
Dev.
15.0
52.6
13.0
41.1
19.3
21.8
29.5
2.2
156.8
264.7
13.4
706.0
217.8
217.6
485.7
1278.4
Condition
Factor8
Mean
1.03
1.01
0.95
0.90
1.02
1.00
0.97
0.91
1.31
1.24
1.15
1.35
1.04
1.09
0.56
0.55
Std.
Dev.
0.08
0.10
0.06
0.12
0.08
0.09
0.10
0.06
0.12
0.14
0.17
0.28
0.19
0.07
0.06
0.10
a Assumming isometric growth, the condition factor = (weight* 105)/(total length)3 (Anderson
and Gutreuter 1983)
4-14
-------
5. LAKE PHYSICAL CHARACTERISTICS
Lakes in the Upper Peninsula of Michigan (Subregion 2B) were among the smallest
(median area = 11 ha) and shallowest (median depth = 2.9 m) of any subregion sampled
during the ELS-I (Linthurst et al. 1986, Eilers et al. 1988). Since very shallow lakes,
considered unlikely to support a significant fishery, were excluded from the ELS-n
studies in Subregion 2B (see Section 2.2.1), ELS-n median depths were somewhat greater
than ELS-I medians. Median values for lake depth for the ELS-n target population and
for lakes sampled during ELS-n were 6.1 and 4.3 m, respectively (Table 5.1). The
exclusion of shallow lakes from the ELS-n extended to both small and large lakes,
however, so lake areas from ELS-I to ELS-H remained fairly similar: median values of
11 'ha for the ELS-I target population, 13 ha for the ELS-H target population, and 9 ha
for lakes sampled during ELS-H (Table 5.1). Lake area and lake depth (as estimated by
the ELS-I site depth) were not significantly correlated (p > 0.05, Spearman's rank
correlation) in the ELS-I data set for Subregion 2B.
Table 5.1. Physical Characteristics of Lakes in Subregion 2B, for the ELS-I Target
Population (ft=1050), ELS-n Target Population (ft=597), and the 49 Lakes
Sampled During ELS-n
ELS-I Target
Population
Variable
Lake Area (ha)
Site Depth (m)
Elevation (m)
Watershed Area
(ha)
Median
11
2.9
267
115
Range
4-578
0.9-21.9
184-558
10-54,501
ELS-n Target
Population
Median
13
6.1
289
91
Range
4-262
1.5-20.4
220-558
10-54,501
Lakes Sampled
in ELS-n
Median
9
4.3
282
60
Range
4-262
1.5-20.1
20-546
10-54,501
Watershed-to-
Lake Area Ratio
10.2 2.4-1703.2
Secchi Depth (m) 1.5
0.4-7.6
7.0
2.1
2.4-1703.2
0.8-7.6
7.0
2.2
2.4-1703.2
0.8-7.6
The majority of lakes in Subregion 2B occur at moderate elevation; median values
for the ELS-I target population, ELS-H target population, and lakes sampled in ELS-H
were 267, 289, and 282 m, respectively (Table 5.1). Over 75% of the lakes in each group
5-1
-------
occur at elevations below 450 m. No significant correlation was found for either lake
elevation to lake area or for lake elevation to lake depth (p > 0.05, Spearman's rank
correlation) in the ELS-I data set for Subregion 2B.
Watershed area and the watershed-to-lake area ratio provide a first-order index of
the water residence time (or flushing rate) for the lake. Median values for the
watershed-to-lake area ratio were 10.2 in the ELS-I target population, and 7.0 in both
the ELS-IE target population and the ELS-II sample (Table 5.1).
Four lake types were defined for the ELS-I:
1. drainage lakes lakes with surface water outlets or with both inlets and
outlets;
2. reservoirs artificial lakes as indicated by a dam at the lake outlet;
3. seepage lakes lakes with no permanent surface water inlets or outlets; and
4. closed lakes lakes with a surface water inlet but no surface water outlet.
The majority of lakes in Subregion 2B (51% of the ELS-I target population) are drainage
lakes. Seepage lakes are also quite common, however, comprising an estimated 37.7%
of the ELS-I target population and 39.8% of the ELS-n target population. Twenty-nine
of the 49 lakes sampled during the ELS-H (59.2%) were seepage lakes. Comparisons of
the physical characteristics (lake area, depth, and elevation) of seepage versus
nonseepage lakes for the 49 ELS-H lakes using non-parametric Wilcoxon rank sum and
Kolmogorov-Smirnov tests (Hollander and Wolfe 1973) indicate no significant
differences (p > 0.05) between the two lake groups.
During the ELS-n, in situ measurements of temperature and DO were taken at
1.5 m below the lake surface and at 1.5 m above the lake bottom. If the temperature
difference between these two depths exceeded 4 °C, the lake was considered thermally
stratified and additional profile data on temperature and DO were collected
(Section 3.4). Lakes in the ELS-n were sampled over a three-month period from early
June through the end of August. Thus, changes in the temperature and DO profile over
this sampling period may hinder among-lake comparisons.
Of the 49 lakes sampled during ELS-n, 24 (49.0%) were classified as thermally
stratified. Forty-one percent (n=20) of the lakes sampled had DO levels < 4 mg/L at one
or more depths in the water column. Thermally stratified lakes had significantly
(p ^ 0.05) lower minimum values for DO and a higher percentage of the water column
with DO < 4 mg/L (based on Wilcoxon rank sum and Kolmogorov-Smirnov tests). In
5-2
-------
addition, thermally stratified lakes were generally deeper (p <, 0.05) than nonstratified
lakes.
Measures of Secchi depth, an index of lake transparency, were taken during both
ELS-I (in fall 1984) and ELS-n (in summer 1987). The ELS-I and ELS-II values for Secchi
depth are significantly correlated (r=0.80), although some divergence between the two
samples is evident (Figure 5-1). Twelve of the ELS-n lakes had a Secchi depth
exceeding the lake depth (i.e., the Secchi disk was visible on the lake bottom) and are
not included in Figure 5-1.
W
w
5-
3-
1-
0-
2 3 4 56 7
PHASE-II SECCHI DEPTH (m)
10
Figure 5-1. Comparison of ELS-I and ELS-n values for Secchi depth (m).
5-3
-------
-------
6. LAKE CHEMICAL CHARACTERISTICS
The primary objective of the ELS-I was to characterize the population of lakes
expected to have low ANC in selected areas of the eastern United States. During the
design phase of the ELS-I, it was recognized that the effects of both temporal and
spatial variability in lake chemistry could compromise the survey results. The
within-lake variability had to be minimized in order to observe differences among lakes.
An attempt was made to overcome the effects of temporal and spatial variability
through the use of the "index" concept. The index concept rests on two major
assumptions: (1) that the chemical characteristics of a lake can be related to other
lakes by sampling at a time when within-lake variability is minimized and (2) that the
index sample is representative of within-lake chemistry and can be related to chemical
conditions in the lake in other locations and at other times of the year.
During the ELS-I, a single water sample was collected at 1.5 m depth over the
deepest part of the lake during fall overturn (i.e., the fall period when lakes were well
mixed). A review of sampling seasons indicated that the fall mixing period would
provide the most appropriate index period for sampling because of the low temporal and
spatial variability in lake chemistry (Landers et al. 1988). It is obvious that one sample,
at one location in the lake, at one time on one day, and at a specific season of a
particular year is incapable of characterizing the complex chemical or biological
dynamics of the sample lake. However, the purpose of the survey was to characterize
geographical areas, not the dynamics of individual lakes. With this in mind, the
chemical analysis for the fall 1984 sample provides a representative index of the lake
chemistry that can be compared with the chemistry of other lakes sampled to detect
regional patterns.
For the most part, the ELS-II data on fish communities in Subregion ZB that are
reported in this document are interpreted relative to the ELS-I index of lake chemistry
collected in fall 1984. Relatively few measurements of water chemistry were collected
coincident with the ELS-n fish surveys in summer 1987, largely because of the high
variability in lake chemistry expected to occur over the three-month sampling period
(8 June to 30 August 1987). Since fish grow and live through a number of years, fish
community status in 1987 would likely reflect both past and present-day physical and
chemical conditions in the lake. Thus, the 1984 ELS-I measure of lake chemistry was
selected as the best available index of the chemical conditions to which fish populations
6-1
-------
had been exposed. It is recognized that the ELS-I data are not direct measures of
chemical conditions during those specific times and locales critical to fish population
response, but it is assumed that the ELS-I index chemistry is at least correlated with
these water quality values of interest.
6.1 ELS-I FALL INDEX SAMPLE
The chemical characteristics of the ELS-I and ELS-n target populations and the
49 lakes sampled during ELS-n in Subregion 2B, based on the ELS-I index sample, are
summarized in Table 6.1. Lake-specific data for each of the 49 lakes sampled are
presented in Appendix B.
Table 6.1. Chemical Characteristics of Lakes in Subregion 2B, for the ELS-I Target
Population (ft=1050), ELS-H Target Population (N=597), and the 49 Lakes
Sampled During ELS-n
ELS-I Target
Population
Variable
ANC (peq/L)
pH
Ca (peq/L)
Mg (peq/L)
Na (ueq/L)
K (ueq/L
Sum Base
Cations (peq/L)
Ext. Al (pg/L)
DOC (mg/L)
Color (PCU)
SO4 (peq/L)
SiOz (mg/L)
Total P (pg/L)
Median
284
7.10
246
148
29
13
468
3
6.8
31
78
2.3
13
Range
-49-2726
4.43-8.58
13-1826
11-984
3-245
3-30
54-2966
0-213
0.2-28.8
5-345
16-281
0.0-17.6
0-146
ELS-n Target
Population
Median
164
6.93
179
95
25
14
282
5
9
28
77
2.1
12
Range
-48-2726
4.43-8.25
22-1826
13-984
3-171
5-30
54-2966
0-213
0.2-15.0
5-125
16-161
0.0-12.3
0-39
Lakes Sampled in
ELS-n
Median
25
5.75
51
32
12
12
119
11
4.7
25
67
0.3
12
Range
-48-2726
4.43-8.25
22-1826
13-984
3-171
5-30
54-2966
0-213
0.2-13.9
5-125
17-161
0.0-9.6
0-39
6-2
-------
In ELS-I, Subregion 2B was estimated to have the highest percentage of acidic
(11.3%) and low-pH lakes (9.4% with pH < 5.0) in the Upper Midwest region (see
Table 1.1). In addition, lakes selected for sampling for the ELS-n were specifically
weighted to favor systems with low pH (Section 2.2.2). Forty-one percent (40.8%) of the
lakes sampled were acidic, with ANC < 0 peq/L, and 24.5% had pH < 5.0. Thus, the
proportion of low ANC and low pH lakes among the 49 ELS-n lakes is distinctly higher
than for either the ELS-I target population or the ELS-n target population (Figures 6-la
and b). As noted in Section 2.2.2, pH and Ca levels in lakes in the subregion are highly
correlated (r=0.77, based on Spearman's rank correlation, p=0.0001). As a result, lakes
sampled in the ELS-n also had generally lower Ca levels than either the ELS-I or ELS-n
target populations (Figure 6-lc). Calcium concentrations for the 49 ELS-H lakes ranged
between 22 and 1826 peq/L (Table 6.1); 49.0% of the lakes had levels < 50 peq/L
(1.0 mg/L).
Subregion 2B also contains a relatively large population of high-ANC, high-pH
lakes. Median values for the subregion (ELS-I target population) for ANC (284 ]ieq/L)
and pH (7.10) are high relative to other subregions in the Upper Midwest (Linthurst et al.
1986). This heterogeneity in lake chemistry can be explained largely by the diversity of
bedrock types and geology in the area (Rapp et al. 1987, Eilers et al. 1988). Five of the
49 lakes sampled in the ELS-H (10.2%) had ANC > 1000 peq/L; nine (18.4%) had
ANC > 500
Acidic lakes in Subregion 2B are generally clear water, with a median color value
of 22 PCU (ELS-I target population). Fifteen of the 20 acidic lakes sampled (75%) had
color < 25 PCU; 65% had DOC <; 4 mg/L. Higher pH lakes tend to have higher DOC
(r=0.45 for the 49 ELS-n lakes; p=0.0011, Spearman's rank correlation analysis), although
a high degree of scatter is evident in the relationship (Figure 2-3). Reflecting the
weighted selection of low-pH lakes and the deletion of very shallow lakes (many of
which had quite high DOC), the ELS-H sample and target population had a higher
proportion of low DOC lakes relative to the ELS-I target population (Figure 6-ld).
As noted in Section 5, a high proportion of the lakes in Subregion 2B are seepage
lakes (37.7% of the ELS-I target population, 39.8% of the ELS-n target population, and
59.2% of the lakes sampled in ELS-H). The chemical characteristics of seepage and
nonseepage lakes are contrasted in Table 6.2 for the 49 ELS-H lakes. Levels of ANC,
Ca, Mg, Na, sum of base cations, color, and SiO2 were significantly lower (at a=0.05,
adjusted for 14 tests, p < 0.0036) in seepage lakes than in nonseepage lakes; differences
in pH, K, DOC, and SO4 occurred at 0.0036 < p < 0.05. Sixteen of the 20 acidic lakes
6-3
-------
-530 0 SO BOO HD
ANC(o4)
m m
5 6
pH
HISS us i HUM us ii IIIHI .us ii sum cuss us i IIIHI us n mtti us n sum
CALCIUM (4)
-------
Table 6.2. Comparison of Lake Chemistry by Lake Type: Seepage Lakes versus
Other Lake Types (Drainage, Reservoir, Closed) for the 49 Lakes Sampled
During ELS-IE
Seepage Lakes
Other Lake Types
Test Statisticsa
Variable
PH
ANC (peq/L)
Inorg. Al (pg/L)
Ext. Al (pg/L)
Ca (peq/L)
Mg (peq/L)
Na (peq/L)
K (peq/L)
Sum Base
Cations (peq/L)
DOC (mg/L)
Color (PCU)
S04 (peq/L)
SiOz (mg/L)
Total P (pg/L)
Median
5.23
-1
9
11
38
26
10
10
88
4.0
21
60
0.1
11
Range
4.43-8.25
-46-1665
0-192
0-213
22-860
13-766
3-34
5-21
50-1680
0.2-10.3
5-80
17-144
0-3.2
0-39
Median
6.79
134
12
10
131
83
25
14
254
6.5
37
85
2.2
13
Range
4.74-8.03
-20-2699
0-39
0-120
35-1826
16-984
6-171
5-30
68-2960
2.5-13.9
10-125
48-161
0.2-9.6
1-35
Wilcox.
0.0052
0.0014*
>0.05
>0.05
0.0004*
0.0005*
0.0002*
0.0050
0.0004*
0.0070
0.0017*
0.0101
0.0001*
>0.05
K-S
0.0128
0.0227*
>0.05
>0.05
0.0007*
0.0004*
0.0004*
0;0074
0.0007*
0.0264
0.0237
>0.05
0.0001*
>0.05
a Calculated p values for non-parametric comparisons of seepage lakes versus other
lake types using the Wilcoxon rank sum (Wilcox.) and Kolmogorov-Smirnov (K-S)
tests. Asterisks indicate statistical significance at °c=0.05 adjusted for 14 tests
i.e., p < 0.0036. '
sampled (80%) were seepage lakes. The high proportion of seepage lakes in the ELS-H
sample is evident in the distinctly lower median value for SiOz in the 49 sample lakes
than in either the ELS-I or ELS-H target populations (Table 6.1).
Concentrations of extractable (total monomeric) Al measured in ELS-I were
generally quite low. An estimated 80% of the ELS-I target population had < 12 pg/L
(Eilers et al. 1988). Values for the 49 ELS-H lakes ranged between 0 and 213 pg/L
(Table 6.1), although 85.7% of the lakes sampled had extractable Al levels < 50 pg/L.
Sulfate levels hi Subregion 2B (median value 78 peq/L for the ELS-I target
population) were slightly higher than for other subregions in the Upper Midwest (regional
6-5
-------
median 57 ueq/L), although lower than levels in lakes in the northeastern United States
(regional median 115 ueq/L) (Linthurst et al. 1986, Eilers et al. 1988). Concentrations
for the 49 ELS-H lakes ranged between 17 and 161 peq/L, with a median value of 67.
Sulfate concentrations in the 49 lakes sampled were similar to, although slightly lower
than, values for the ELS-I and ELS-H target populations (Table 6.1).
6.2 COMPARISON OF 1984 FALL INDEX WITH 1987 SUMMER CHEMISTRY
Water samples collected during the ELS-E surveys of fish communities in summer
1987 were analyzed for pH, total pyrocatechol violet (PCV) reactive Al, organic PCV
reactive Al, and total F (Sections 3.5 and 4.1). In addition, pH, conductivity,
temperature, and DO were measured in situ (Section 3.4). Lake-specific data for each
of the 49 ELS-H lakes are presented in Appendix B. Other samples were also collected
to assess concentrations of mercury and other trace metals in water and sediment; these
data are discussed in a separate report evaluating mercury bioaccumulation (EPA, in
prep.).
Measured values of pH and conductivity for fall 1984 (ELS-I) and summer 1987
(ELS-n) for the 49 ELS-H lakes in Subregion 2B are compared in Figure 6-2. Results for
the two sampling periods were similar, with no dramatic differences for either variable
between the sampling dates. Of the variables measured in both 1984 and 1987 (pH,
conductivity, fluoride, and temperature), only temperature differed markedly between
the two samples. As expected, temperatures measured at 1.5-m depth during summer
(1987) were 5 °C to 22 °C warmer than values measured in fall (1984). None of the
49 ELS-H lakes were thermally stratified during the fall 1984 sampling, while 24 of the
49 lakes were stratified when sampled in summer 1987.
As part of EPA's Long-Term Monitoring Program, chemical conditions in 25 lakes
in the Upper Peninsula of Michigan and northcentral Wisconsin have been monitored
seasonally (spring, summer, and fall) since fall 1983 (Newell et al. 1987). Data on ANC,
pH, and Ca for these lakes collected between 30 October 1984 and 4 November 1987 are
summarized in Table 6.3 to illustrate the approximate magnitude of within-lake seasonal
and year-to-year variations in water chemistry. Variations in ANC of 30 to 50 neq/L,
pH of 0.2 to 0.6 pH units, and Ca of 30 to 60 peq/L are not atypical. However, only one
lake, Lake Nevins, exhibited a detectable trend in lake chemistry (decreasing ANC, pH,
and Ca) over the three-year period.
6-6
-------
a
. a.
10-
9
8
7-
*r.
3 4 5 67 8 9 10
SUMMER 1987 pH
400-
I
5 300
8 150-
I
50-
I ' '. ' ' I ' ' ' ' I ! ' ' ' I '^ 1 ' I ' ' ' ' I ' ' ' ' I ' ' ' ' I ' '_ ' ' I
0 50 100 150 200 250 300 350 400
SUMMER 1987 CONDUCTIVITY (uS/cm)
Figure 6-Z. Comparison of chemical values measured in fall 1984 versus summer
1987 for the 49 ELS-H lakes in Subregion 2B, for (a) pH and
(b) conductivity.
6-7
-------
Table 6.3.
Summary of Long-Term Monitoring Data for Acid Neutralizing
Capacity (ANC), Calcium (Ca), and pH from Lakes Located in the
Upper Peninsula of Michigan and North Central Wisconsin
ANC (ueq/L)
Ca (ueq/L)
pH
Lake Name
Johnson
McNearney
Bass
Murray
Buckeye
Stuart
Cusino
Nevins
Monocle
Amdrus
Kelly
Chris Brown
McGrath
Sunset
Vandercook
Greater Bass
Sand
Nichols
Little Rock
Long
Clear
Camp Twelve
Lake Clara
Luna
Sugar Camp
N
9
9
9
9
8
8
8
9
10
8
9
10
8
9
8
8
11
10
14
8
8
9
9
9
8
Median
-18
-35
103
24
160
-13
-2
98
209
15
-5
204
3
23
13
6
-2
24
10
16
-6
-8
39
7
-7
Range
30
46
54
54
34
73
60
111
49
21
43
63
56
35
29
36
47
28
45
36
20
66
30
42
45
Median
58
61
109
37
156
26
55
126
202
66
49
148
46
67
60
61
79
62
43
53
40
40
84
61
77
Range
25
39
44
28
72
19
27
63
125
35
22
93
32
44
37
41
47
52
43
30
29
37
44
43
51
Median
4.7
4.4
6.7
5.8
6.9
4.8
5.2
6.7
7.0
5.5
5.1
7.0
5.3
6.1
6.0
5.4
5.1
5.8
5.9
5.9
4.9
5.2
6.4
5.7
5.2
Range
0.4
0.2
0.7
0.4
0.7
0.1
0.3
0.5
0.6
0.8
0.2
0.6
0.5
0.3
0.7
0.5
0.5
0.6
1.2
0.5
0.4
0.6
0.9
0.9
0.2
6.3 ALUMINUM CHEMISTRY
Inorganic (labile monomeric) Al has been identified as a potentially important
toxicant in acidic waters in at least some regions (Driscoll et al. 1980, Wright et al.
1980, LaZerte 1984). Levels of inorganic Al were not measured during ELS-I. Thus, to
6-8
-------
supplement the ELS-I data base, measurements of Al chemistry were conducted in
summer 1987 (Sections 3.5 and 4.1). The results indicate quite low levels (< 60 ug/L) of
inorganic Al in all but one ELS-H lake in Subregion 2B (Lake 2B1-048, McNearney Lake,
with 192 pg/L and pH 4.43) (Figure 6-3). Given that the values for pH measured in fall
1984 and summer 1987 were similar (Figure 6-2), levels of inorganic Al measured in
summer 1987 are used directly with ELS-I chemistry values (for all other chemical
variables) in assessing the association between fish communities and lake chemistry (see
Section 8).
30
20
Of
a
g
10
0 20 40 60 80 100 120 140 160 180 200
INORGANIC Al(ug/L)
Figure 6-3. Distribution of inorganic aluminum in ELS-n lakes in Subregion 2B.
6-9
-------
-------
7. FISH COMMUNITY STATUS
Unless otherwise noted, the data and analyses presented in this section are based
on a single sample per lake, collected between 8 June and 30 August 1987. Results from
the duplicate surveys on 10 lakes, conducted between 31 August to 1.2 September 1987,
are discussed and analyzed in Section 4.2. Measures of species richness and fish species
presence/absence are discussed in Section 7.1; numbers of fish caught (indices of
relative abundance) in Section 7.2; and information on fish size and condition factors in
Section 7.3. The survey data for each lake are summarized in Appendix B.
7.1 FISH SPECIES DISTRIBUTION
Thirty-one fish species were caught in surveys of 49 lakes in Subregion 2B (Table
7.1).l Yellow perch was the most common species, collected in 31 lakes. Seven other
species occurred in more'than 10 lakes, in decreasing order of frequency: largemouth
bass, bluegill sunfish (Lepbmis macrochirus). pumpkinseed sunfish (Lepomis gibbosus),
white sucker, brown bullhead (Ictalurus nebulosus), golden shiner (Notemigonus
crysoleucas), and northern pike. The remaining 23 species were caught in less than 10
lakes, although some of these species were collected in large numbers in individual lakes
(see Section 7.2). The types of fish caught in this survey are similar to those reported
for lakes in other areas of the Upper Midwest (Wiener and Eilers 1987).
The number of fish species caught per lake varied between 0 and 13, with a median
of 3 (Table 7.2). Two lakes (No Name, 2B1-038, and McNearney Lake, 2B1-048) had no
fish caught. A third lake (Bohmier Lake, 2B2-078) had one fish species (brook
stickleback, Culaea inconstans) caught during the initial survey but no fish caught during
the duplicate QA/QC survey in September (Section 4.2). Six lakes (12.2%) had only
yellow perch caught. Game fish, as defined in Section 3.6.2, were collected in 36 of the
49 lakes (73.5%).
In 11 lakes, beach seines could not be used because of the lack of suitable littoral
area for seining (i.e., with relatively smooth substrate and free of obstructions and
aquatic vegetation). In 16 of the 38 lakes in which beach seines were used (42%), beach
Includes a bluegill-pumpkinseed sunfish hybrid as a separate species. In no lakes
were all three caught: bluegill sunfish, pumpkinseed sunfish, and the hybrid sunfish.
Fish caught in lake 2B3-031 identified as brook trout were later determined to be
splake (a hybrid cross between brook trout and lake trout) based on stocking records
from the Michigan Department of Natural Resources, but are treated as brook
trout in these analyses.
7-1
-------
Table 7.1. Fish Species Caught and Frequency of Occurrence
: No. of Lakes
in Which Species Caught
Family and Species
Sahnonidae
Salvclinus fontinalis
Salvelinus namavcush
Osmeridae
Osmerus mordax
Umbridae
Umbri limi
Ksocidae
Esox lucius
Cyprinidae
Semolilus atromaculatus
Notemigonus crysoleucas
Notropis cornutus
Notropis atherinoides
Notropis emiliae
Pimpphales promelas
Pimephales notatus
Ilybognathus hankinsoni
Chrosomus neogaeus
Catostomidae
Catostous commersoni
Ictaluridae
Ictalurus nebulosus
Cyprinodontidae
Fundulus diaphanus
Gasterosteidae
Culaea inconsians
Centrarchidae
Ambloplites rupcstris
Microptorusdolomicui
Micropterus salmoides
Lepomis gibbosus
Lcpomis macrochirus
Lepomis SPP.
Pomoxis nigromaculatus
Percidae
Perca flavcscens
Stizostodion vitreum
Percina caprodes
Etheostoma nigrum
Ethcostoma exile
Cottidae
Coitus bairdi
Common Name
brook trout
lake trout
rainbow smelt
central mudminnow
northern pike
creek chub
golden shiner
common shiner
emerald shiner
pugnose minnow
fathead minnow
bluntnose minnow
brassy minnow
finescale dace
white sucker
brown bullhead
banded killifish
brook stickleback
rock bass
small moulh bass
largemouth bass
pumpkinseed sunfish
bluegill sunfish
sunfish hydrid
black crappie
yellow perch
walleye
logperch
johnny darter
Iowa darter
mottled sculpin
Gill Net,
All Gear Trap Net, &
Types Angling
4
1
1
6
11
5
12
7
1
1
3
7
1
6
14
13
1
3
4
5
17
15
16
3
3
31
2
1
3
7
1
. 4
1
1
5
11
4
12
7
0
0
2
2
0
5
14
13
0
3
4
4
16
15
13
3
3
31
2
0
0
1
1
Gill Net
&
Trap Net
4
1
1
5
11
4
12
7
0
0
2
2
0
5
14
13
0
3
4
4
13
15
1.3
3
2
31
2
0
6
1
1
7-2
-------
Table 7.2. Species Richness, by Lake, for the 49 Lakes Sampled in Subregion 2B
Species Richness
Lake ID
2B1-016
2B1-OZ2
2B1-035
2B1-038
2B1-039
2B1-040
2B1-041
2B 1-042
2B 1-047
2B 1-048
2B1-052
2B 1-061
2B1-064
2B1-066
2B2-004
2B2-007
2B2-024
2B2-038
2B2-044
2B2-049
2B2-055
2B2-061
2B2-074
2B2-075
2B2-078
2B2-079
2B2-082
2B2-090
2B2-098
2B2-100
2B3-007
2B3-008
2B3-009
2B3-012
3B3-013
All Gear Types
-
-
1
0
'
.
6
1
2
0
1
3
1
1
-
4
7
8
3
-
1
6
3
-
1 -
1
4a
2
, -. - .
1C
4
-
12
8
3
Gill Net, Trap Net
& Angling
2
4
1
0
2
2
5
1
2
0
1
3
1
.1
3
3
6
5
3
1
1
5
3
4
1
1
-
2
4b
lc
3
' -' 4 .''-. :-
10
6
3
GUI Net & Trap
Net
1
4
1
0
2
2
5
1
2
0
1
3
1
1
3
3
6
5
3
1
1
5
3
4
1
1
3
2
3b
1C
3
4
10
6
3
(continued)
7-3
-------
Table 7.2. Continued
Species Richness
Lake ID
2B3-020
2B3-023
2B3-027
2B3-028
2B3-030
2B3-031
2B3-034
2B3-037
2B3-051
2B3-055
2B3-056
2B3-057
2B3-058
2B3-071
All Gear Types
-
9
4
7
4
13
9
11
1
11
2
-
1
9
GUI Net, Trap Net
& Angling
7
9
2
6
4
9
7
9
1
8
2
7
1
8
GUI Net & Trap
Net
7
9
2
5
4
9
7
9
1
8
2
6
1
8
a Lake not sampled by angling.
b Only one gill net fished.
c Only two (rather than three) trap nets fished.
seines collected additional species not caught with the other three gear types
(Table 7.2). Small fish, particularly cyprinid (minnow) and darter species, were
frequently collected only with beach seines (Table 7.1). Given that beach seines were
not used in a relatively high percentage (22.4%) of lakes and that beach seines often
collected fish species not caught with other gear types, species richness is calculated
based on the catch from gill nets, trap nets, and angling, unless otherwise noted.
Results from the beach seines are used only for comparisons among the 38 lakes in
which beach seines were used. Species richness (based on fish caught with gill nets, trap
nets, and angling) ranged between 0 and 9 species per lake, with a median of 3
(Table 7.2, Figure 7-1).
7-4
-------
0123456789 10
SPECIES RICHNESS
Figure 7-1. Distribution of species richness values among the 49 ELS-n lakes.
The effectiveness of each gear type in detecting fish presence varied somewhat
among fish species (Tables 7.1 and 7.3). Salmonids (brook trout and lake trout) and
largemouth and smallmouth bass were caught more frequently in gill nets than in trap
nets, while the pumpkinseed sunfish, black crappie, and several minnow species were
caught more often in trap nets than in gill nets. As noted above, beach seines were
generally more effective at collecting cyprinids and darters than were other gear types.
Angling was the least effective gear overall for detecting fish species presence,
although the limited effort (total 2 man-hours) and time of day fished may have
decreased angling efficiency. In a few lakes, largemouth bass (n=3 lakes) and black
crappie (n=l lake) were collected only with angling (Table 7.1).
7-5
-------
Table 7.3. Relative Gear Efficiency for Each Species, Calculated as the Percent of
Lakes for Which the Gear Detected Each Species Out of the Total
Number of Lakes in Which the Species Was Caught Regardless of the
Gear Used
Relative Gear Efficiency (%)
Species
Brook Trout
Lake Trout
Rainbow Smelt
Central Minnow
Northern Pike
Creek Chub
Golden Shiner
Common Shiner
Emerald Shiner
Pugnose Minnow
Fathead Minnow
Bluntnose Minnow
Brassy Minnow
Finescale Dace
White Sucker
Brown Bullhead
Banded Killifish
Brook Stickleback
Rock Bass
Smallmouth Bass
Largemouth Bass
Pumpkinseed Sunfish
Bluegill Sunfish
Sunfish Hybrid
Black Crappie
Yellow Perch
Walleye
Logperch
Johnny Darter
Iowa Darter
Mottled Sculpin
Gill Net
100
100
100
17
82
60
75
57
0
0
0
14
0
17
93
77
0
0
100
60
71
33
62
33
33
97
50
0
0
0
100
Trap Net
0
0
0
83
55
60
75
43
0
0
67
29
0
67
79
92
0
100
75
20
24
100
81
67
67
90
50
0
0
14
0
a Only 38 of the 49 lakes were sampled with beach
Angling
0
0
0
0
36
20
0
0
0
0
0
0
0
0
0
0
0
0
25
0
29
0
12
0
33
19
0
0
0
0
0
seines.
Beach Seine3
0
0
0
67
0
40
25
29
100
100
33
100
100
67
0
8
100
100
25
40
24
27
44
0
0
29
0
100
100
86
0
7-6
_
-------
7.2 TOTAL CATCH AND CATCH PER UNIT EFFORT
The numbers of fish caught per lake and the CPUE potentially may serve as
indices of fish abundance, as discussed in Section 4.2. Catch rates from angling and
beach seines tend to be highly variable. Thus, only fish caught in gill nets and traps nets
are included in calculations of total catch and CPUE. Catch per unit effort is computed
as the number of fish caught per hour per net, averaged over all the nets per lake for a
given gear type (gill net or trap net).
Values for total catch and CPUE, summed across all fish species, are provided in
Table 7.4 for each lake. Total catch ranged between 0 and 3000 fish, with a median of
210. Gill-net CPUE ranged between 0 and 16.2 fish/h/net, with a median of 0.83;
trap-net CPUE from 0 to 67.2 fish/h/net, with a median of 1.33. For each of these
variables, the distribution of values among the 49 lakes is highly skewed and non-normal
(p=0.0001, Shapiro-Wilk test statistics, Conover 1980) (Figure 7-2).
Table 7.4. Total Catch and Catch Per Unit Effort (CPUE) by Lake,
All Fish Species Combined
CPUE (fish/h/net)
Lake ID
2B1-016
2B1-022
2B 1-035
2B1-038
2B1-039
2B 1-040
2B1-041
2B 1-042
2B 1-047
2B1-048
2B1-052
2B1-061
2B 1-064
2B1-066
2B2-004
2B2-007
2B2-024
2B2-038
Total Catch
6
28
407
0
378
138
218
1
748
0
1082
29
312
1
1058
210
344
364
Gill Net
0.03
0.13
2.45
0.00
3.53
1.35
1.12
0.00
3.03
0.00
6.39
0.43
1.22
0.00
0.60
0.82
0.23
1.33
Trap Net
0.06
0.27
3.40
0.00
1.76
0.74
1.52
0.01
9.67
o.oo
9.52
0.03
3.30
0.02
21.17
2.30
5.24
5.02
(continued)
7-7
-------
Table 7.4. Continued
CPUE (f ish/h/net)
Lake ID
2B2-044
2B2-049
2B2-055
2B2-061
2B2-074
2B2-075
2B2-078
2B2-079
2B2-082
2B2-090
2B2-098
2B2-100
2B3-007
2B3-008
2B3-009
2B3-012
2B3-013
2B3-020
2B3-023
2B3-027
2B3-028
2B3-012
2B3-013
2B3-020
2B3-023
2B3-027
2B3-028
2B3-030
2B3-031
2B3-034
2B3-037
2B3-051
2B3-055
2B3-056
2B3-057
2B3-058
2B3-071
Total Catch
260
792
25
686
3000
129
1
386
33
1540
51
204
52
266
187
86
630
456
262
32
118
86
630
456
262
32
118
502
373
53
238
3
232
153
97
2403
163
Gill Net
3.27
10.45
0.00
3.58
0.50
0.83
0.00
5.21
0.36
16.19
1.02
2.47
0.48
0.11
1.01
0.02
6.44
3.91
2.70
0.41
0.73
0.02
6.44
3.91
2.70
0.41
0.73
0.75
1.32
0.60
1.28
0.00
0.89
0.00
0.37
4.91
1.46
Trap Net
0.55
1.26
0.44
3.70
67.23
1.12
0.01
1.82
0.14
11.38
0.31
1.49
0.42
3.92
0.18
1.23
3.62
2.75
0.42
0.02
0.19
1.23
6.62
2.76
0.42
0.03
0.19
6.51
1.84
0.33
2.27
0.05
2.53
2.32
1.33
27.52
0.67
7-8
-------
ML CATCH
AYERAGBTRAPffiTCPUE
0 2 < 6 .1 1 12 14 16
AVERAGE GILL MCPUE
mm.
0 2 { 6 8 10 12 H 16
, ML GAME FISH CATCH
Figure 7-2. Distribution of total catch, gill-net CPUE, and trap-net CPUE for all
species, and total catch for game species for the 49 ELS-n lakes.
7-9
-------
Values for total catch and CPUE by fish species are summarized in Table 7.5, for
those lakes in which each species was caught. Seven species had over 100 fish caught (in
gill nets and trap nets) in at least one lake: golden shiner (maximum number caught per
lake, Z318), brown bullhead (maximum 2403), yellow perch (maximum 1538), common
shiner (maximum 1013), finescale dace (maximum 671), bluegill sunfish (maximum 458),
and white sucker (maximum 229). In addition, creek chub and bluntnose minnow were
caught in large numbers in beach seines in some lakes (maximum number caught per lake
in all four gear types combined: creek chub 340; bluntnose minnow 279). For the 35
lakes with game fish caught in gill nets and trap nets, total catch ranged between 3 and
1538} gill-net and trap-net CPUE from 0.02 to 16.2 and 0.01 to 11.4 fish/h/net,
respectively.
A Wilcoxon signed rank test was conducted to compare fish CPUE in gill nets
versus trap nets (for all fish species combined, for game fish, and for each of the fish
species caught in more than 10 lakes). No differences between gill nets and trap nets
were detected (p > 0.05) for yellow perch, white sucker, golden shiner, and all species
combined. GUI-net CPUE exceeded trap-net CPUE (p < 0.05) for largemouth bass,
northern pike, and game fish as a group, while trap-net CPUE exceeded gill-net CPUE
for brown bullhead, bluegill sunfish, and pumpkinseed sunfish.
7.3 FISH SIZE AND CONDITION FACTORS
Length-frequency histograms, by species, combined across all lakes and all gear
types (including duplicate samples where available), are presented in Figure 7-3 for the
six target and index species with >10 fish caught (brook trout, northern pike, white
sucker, smallmouth bass, largemouth bass, and yellow perch). Data for individual lakes,
by species, are summarized in Appendix B. Fish age estimates and associated analyses
of fish growth rates are discussed in the report on fish mercury bioaccumulation
(EPA, in prep.).
Fish condition factors reflect the relationship between fish weight and fish length.
The larger the condition factor, the heavier the fish for a given length, and presumably
the healthier the fish. The condition factor, K, is often calculated as follows, assuming
isometric growth (Anderson and Gutreuter 1983):
K =
(weight* 10s)
(total length)3
7-10
-------
Table 7.5. Summary of Total Catch and Catch Per Unit Effort (CPUE) for Selected
Species, for Lakes where the Fish Species Was Caught with Gill Nets or
Trap Nets
CPUE (fish/h/net)
Species/Group
Game Fish
Cyprinids
Brook Trout
Lake Trout
Rainbow
Smelt
Central
Mudminnow
Northern Pike
Creek Chub
Golden Shiner
Common
Shiner
Fathead
Minnow
Bluntnose
Minnow
Finescale
Dace
White Sucker
Brown
Bullhead
Brook
Stickleback
Rock Bass
Smallmouth
Bass
Largemouth
Bass
Pumpkinseed
Bluegill
Sunfish Hybrid
Black Crappie
Yellow Perch
Walleye
Iowa Darter
Mottled
Sculpin
No.
Lakes
35
17
4
1
1
5
11
4
12
7
2
2
5
14
13
3
4
4
13
15
13
3
2
31
2
1
1
Total
Median
93
39
8
2
41
9
7
4.5
36
4
7
12.5
14
30
29
1
21
1.5
3
8
52
2
6
116
4.5
1
1
Catch
Range
3-1538
4-2989
3-28
2-2
41-41
1-25
1-43
1-20
1-2318
1-1013
4-10
10-15
1-671
2-229
1-2403
1-1
11-25
1-17
1-29
1-63
2-458
2-38
1-11
2-1538
1-8
1-1
1-1
Gill
Median
0.98
0.08
0.09
0.01
0.25
_ ,
0
0.06
0.03
0.14
0.02
0
0.01
0
0.20
0.06
0
0.08
0.01
0.04
0
0.08
0
0.09
0.98
0.05
0
0.01
Nets
Range
0-16.17
0-1.48
0.04-0.50
0.01-0.01
0.25-0.25
0-0.13
0-0.52
0-0.07
0-1.41
0-0.26
0-0
0-0.02
0-0.03
0-1.54
0-4.91
0-0
0.04-0.14
..0-0.02
0-0.42
0-0.59
0-0.70
0-0.03
0-0.18
0-16.17
0-6.10
0-0
0.01-0.01
Trap
Median
0.30
0.42
0
6
0
0.05
0.01
0.04
0.34
0
0.13
0.20
0.25
0.06
0.27
0.01
0.09
0
0
0.08
0.27
0.04
0.02
0.47
0.01
0;01
0
Nets
Range
0-11.37
0-66.99
0-0
0-0
0-0
0.02-0.44
0-0.03
0-0.22
0-51.73
0-20.92
0.06-0.21
0.18-0.22
0-15.26
0-2.68
0-27.52
0.01-0.02
0-0.27
0-0.10
0-0.06
0.01-0.73
0.02-6.45
0-0.60
0.01-0.02
0-11.37
0.01-0.01
0.01-0.01
0-0
7-11
-------
BROOK TROUT
in
13 -
12 -
11 -
10 -
9 -
fc -
5
8 7"
u
e 6-
5 -
4 -
3 -
2 -
1 -
0 -
r/i
/
/
X
V
?
/
/
/
/
x
/
'/
/
/
/
x
X
/
/
/
X
x
/
7~
/
^
/
x
^
/
/
/
/
^
x
p-,
/'IT; pn
fTi x' M (/ m
fx) /j/i (/ M
"1 I 1 1 I I 1 1 1 1 ~I 1 1 1 1 1 1 1 1 1 1 1 1 T-
z
u
O
u
62 112 162 212 262 312 362 412 462 512 562 612
LENGTH CLASS MIDPOINT (MM)
NORTHERN PIKE
22 -
20 -
18 -
16 -
14 -
12 -
10 -
8 -
6 -
4 -
2 -
0 -
7
',
'/
/
/
/
/
y
y
y
y
T
X
/
x
/
/
x
171 MM M
ft
/
x
x
/
X
x
_
x
/
1
T~
x
/
1
^/
X
x
/
x
x
X
x
/
y'
/
1
1
^
x
/
/
1
x
/
/
/
X
X
1
/
X
/
^
1
^
/
/
/
/
^
^
/
x
/
x
X
/
1
62 112 162. 212 262. 312 362 412 .' 462- '512 562 612
LENGTH CLASS MIDPOINT (MM)
Figure 7-3. Length-frequency histograms, by species, for all fish caught in all gear
types in all lakes.
7-12
-------
WHITE SUCKER
»u
80 -
70 -
80 -
I =0-
u
O
c
30 -
20 -
10 -
0 -
rTi
j
^
/.
7
/
/
/
/
''/
/
/
/
y\
I
/
;
7
^
^
^
^
7
/
^
^
~jr
'/
^
/
^
7
/
^
^
^
/
^
^
f/1
/
/
/
^
^
/
/
/
pn
/
/
^
^
^
/
/
71
/
^
^
/ /cn
/ / /HplprnlT]
/ / / \A\A\A\A m
62 112 162 212. 262 312 362. 412 462 512 562 612
15
14
13
12
11
10
FREQUENCY ,
O) vl OJ ID
5 -
4 -
3 -
2 -
1 -
0 -
7j
/
/
/
^
/
/
/
',
'',
/
^
/
/
/
62
LENGTH CLASS MIDPOINT (MM)
SMALLMOUTH BASS
-,fl. . .'-.
s
/
/
p- P^
fl
0.
-
i i i i i r i i i i i i T i i i i i T i r*
112 162 212 262 312 362 412- 462 '512 562 612
LENGTH CLASS MIDPOINT (MM)
Figure 7-3. Continued
7-13
-------
LARGEMOUTH BASS
o
5
8
u
£
120 -
110 -
100 -
90 -
80 -
70 -
60 -
50 -
40 -
30 -
20 -
10 -
7\
/
/
^
/
/
/
/
/
/
/
/
/
/
r/\-
'.
'/
fe -nflJ^flm -
_ \f 1 IX 1 IX I IX I i i r i 1 r. I |.| .-j | [ 1 1 1 || ! ( 1 I 1 .
*llli . .... ., i..** Ki.'l K\'i
62 112 162 212 262 3<2 362 412 402 612 502 612
LENGTH CLASS MIDPOINT (MM)
YELLOW PERCH
3.5 -
3 -
2.5--
D 2 -
O 3
U 0
1.5 -
1 -
0.5 -
7
62 112
. '" f| " r| ' I ' | ' I 1 1 1 1 1 1 1 1 1 I I '
162 "212 262 ' '312 362 412 462 512 562 612
LENGTH CLASS MIDPOINT (MM)
Figure 7-3. Continued
7-14
-------
WALLEYE
o
3
2.8
2.6
2-4
2.2
2
1.8
1.6
1.4
t.2
1
0.8
o.a
0.4
0.2
0
62 112 162 212 202 312. 362 ' 412 462-
UNOTH CUSS MIDPOINT (MM)
512 562 612
Condition factors for the 10 species measured for length and weight pooled across
all lakes and all fish caught (including duplicate samples) are summarized in Table 7.6.
Values tend to be species-specific, reflecting differences in fish shape. Fish condition
factors also vary with season of the year, sex, stage of maturity, and size of the fish
(Everhart et al. 1975). For the three species for which statewide average condition
factors could be calculated (northern pike, largemouth bass, and yellow perch), values
for the ELS-n tended to be similar to or slightly lower than the statewide averages.
7-15
-------
Table 7.6. Fish Condition Factors, by Species, Pooled Across AH Lakes and All Ages
Condition Factor
Species
Brook Trout
Northern Pike
White Sucker
Rock Bass
Smallmouth Bass
Largemouth Bass
Pumpkinseed Sunf ish
Bluefill Sunfish
Yellow Perch
Walleye
N
27
91
288
14
6
106
27
46
1178
8
Range
0.78-1.70
0.31-0.75
0.38-1.50
1.42-2.23
1.15-1.55
0.89-2.51
1.52-2.42
0.97-2.00,
0.22-1.77
0.79-0.99
Std. Dev.
0.24
0.08
0.15
0.19
0.16
0.22
0.23
0.20
0.16
0.06
Mean
1.13
0.55
1.00
1.87
1.32
1.32
2.01
1.51
1.00
0.85
Statewide
Average8
-
0.54-0.65
-
-
-
1.19-1.50
-
-
1.06-1.25
-
8 Statewide average values calculated by age class based on data presented in Merna et al. (1981);
ranges for ages 0 to 9 for northern pike, 0 to 10 for largemouth bass, and 1 to 11 for yellow
perch. Generally, younger, smaller fish have lower condition factors.
7-16
-------
8. ASSOCIATION BETWEEN FISH COMMUNITY STATUS
AND LAKE CHARACTERISTICS
The ELS-n data for Subregion 2B may be used to develop and examine hypotheses
regarding the role of selected environmental factors in determining fish population
success and fish community characteristics in lakes in the Upper Peninsula of Michigan
and northeastern Wisconsin. Survey data alone, however, cannot establish causality.
Caution must be exercised not to assume that observed spatial associatlpns imply a
direct cause-and-effect relationship. Many factors influence fish community status, and
most of these factors are themselves interrelated and correlated.
A wide range of alternative predictor variables were examined that may directly
or indirectly influence fish community characteristics:
Lake type It is expected that seepage lakes, without inlets and outlets, would
have reduced rates of colonization and thus naturally lower numbers of species
and perhaps lower fish abundance. Drainage lakes, reservoirs, and closed lakes,
on the other hand, have connecting lakes and streams that may serve both as
potential refuges during severe conditions and as source areas for potential
immigrants (Tonn and Magnuson 1982). For analyses of fish community status,
lake type is defined as a binary variable, seepage versus nonseepage lakes.
* Lake area Many investigators have reported a positive association between
lake area and species richness (Magnuson 1976, Harvey 1979, Rago and Wiener
1986). Larger lakes generally provide greater habitat complexity and also are
more likely to include refuge areas during adverse environmental conditions.
Lake depth (based on the ELS-I site depth) Shallower lakes are less likely to
be thermally stratified, and thus are less likely to support fish species
intolerant of relatively warm water temperatures. It should be noted that the
ELS-I site depth is only a rough approximation of lake maximum depth
(Linthurst et al. 1986). Unpublished data for lakes in the northeastern United
States indicate relatively poor agreement between the ELS-I site depth and the
true maximum depth in some lakes.
Elevation Lakes at higher elevations tend to be cooler, favoring fish species
less tolerant of higher water temperatures. In addition, lakes at higher
elevations may experience longer periods of ice cover and as a result may be
more susceptible to oxygen depletion during the winter.
Dissolved oxygen Fish require adequate levels of DO to survive, although
minimum tolerance levels vary among fish species. Variations in DO
concentrations over the three-month sampling period may limit, however, the
utility of the ELS-n measurements for among-lake comparisons. Two indices
are computed from the ELS-n measurements: the minimum measured level of
DO and the proportion of the water column with DO levels below 4 mg/L.
8-1
-------
Thermal stratification The optimum temperature for fish survival and
growth varies among fish species. Thus, water temperatures play a major role
in determining fish community composition in surface waters. ELS-n water
temperature measurements were collected over a three-month period and are
not considered suitable for direct among-lake comparisons. Analyses of fish
community status, therefore, include only a binary index of thermal
stratification, as defined in Section 5.
Secchi depth Secchi depth is a measure of light transparency and
penetration, which in turn affects the lake thermal regime and light
availability for primary production. In addition, some fish species (e.g., fish
that rely heavily on visual prey selection) are relatively intolerant of turbid
waters.
Lake pH Low levels of pH may be toxic to fish (Altshuller and Linthurst
1984). Low pH levels may result from naturally acidic conditions, from acidic
deposition, or from other sources of acidity. Specific causes for low pH waters
in Subregion 2B are not examined in this document (see Eilers et al. 1988).
Inorganic aluminum High levels of inorganic Al may be toxic to fish.
Aluminum and pH (or the hydrogen ion concentration) are the principal toxic
agents for fish in acidic waters (Schofield and Trojnar 1980, Driscoll et al.
1980).
Calcium Higher levels of Ca may mitigate the potential toxic effects of low
pH and elevated levels of inorganic Al. Fish tolerate lower pH levels and
higher Al concentrations in waters with higher Ca concentrations (Brown 1983,
Ingersoll 1986).
Dissolved organic carbon High levels of DOC may complex Al and other
metals thereby decreasing metal toxicity (Driscoll et al. 1980, Parkhurst 1987).
High levels of DOC (and water color, discussed below) are in some cases
indicative of lakes with high levels of organic acids and/or extensive bog
development. Lakes with high levels of DOC tend to have higher water
temperatures (due to the effect of dissolved organics on light adsorption in
water). Lakes with extensive bog development may be subject to periodic
oxygen depletion. The occurrence of bog development was not directly
assessed in either the ELS-I or ELS-n.
Color Levels of DOC and water color are generally highly correlated.
However, neither is an exact measure of the availability of organics for metal
complexation or of organic acidity. Thus, both variables are included as
potential predictor variables of fish community status.
Acid neutralizing capacity Acidification is defined as the loss of ANC.
Acidic waters are defined by ANC < 0 »eq/L. While ANC, by itself, may have
no direct effects on fish survival, variations in the relationship between ANC
and pH may reflect the varying importance of weak acids (including Al and
organic acids), which in turn may influence fish survival and fish community
composition.
8-2
.
-------
Sum of the base cations Studies have demonstrated that Na, Mg, and K may
also influence the toxicity of acidic waters to fish, although to a lesser degree
than does Ca (Altshuller and Linthurst 1984).
Extractable Al Procedures for the fractionation and speciation of Al are still
fairly controversial. Thus, in addition to inclusion of the estimated inorganic
Al, noted above, measured values for extractable Al (i.e., total monomeric Al)
from ELS-I are also considered.
Total phosphorus (P) Phosphorous is the key nutrient controlling primary
productivity in most temperate, inland lakes (Schindler 1975). Levels of total
P are often positively correlated with levels of algal standing crop (Nicholls
and Dillon 1978, Schindler 1975), and may in turn influence fish abundance.
Sulf ate Levels of SO4 measured during ELS-I are included as a potential
index of the influence of SO4 deposition on lake chemistry. However, in-lake
SO4 reduction, especially in seepage lakes, may alter markedly regional
patterns in lake 804. Sulfate in lakes in Subregion 2B likely has no direct
measurable effects on fish.
Silica Seepage lakes tend to have lower levels of SiOz than do drainage
lakes, reservoirs, or closed systems (Linthurst et al. 1986). In addition, varying
levels of SiOz among seepage lakes may be indicative of the varying
importance of groundwater inflow to lake-ion budgets. Silica has no direct
effects on fish, but may serve as an independent index of lake tjrpe and of the
importance of watershed processes to lake chemistry.
The analyses in this document are considered exploratory. In order not to limit
data analyses to factors considered most important a priori, a large number of
statistical tests have been conducted involving all of the above parameters. Of primary
interest is the pattern of results and the consistency of these results with proposed
mechanisms of effects, rather than any one test per se. While some adjustment is made
for the number of tests conducted, individual spurious results may still occur.
Relationships between fish community characteristics and lake physical and
chemical attributes were evaluated using nonparametric statistics and regression
analyses. As part of each regression analysis, appropriate model diagnostics were
examined, including residual plots, normal plots, Cook's D influence statistic, and the
condition index (Belsley et al. 1980, Myers 1986). These tools were used to assess model
adequacy, to inspect for homogeneity of variance and collinearity problems, to detect
outliers and influential data points, and to test for normality.
The sample of 49 ELS-H lakes was assumed to be a sample from an infinite
population. Therefore, all analyses in this section are unweighted and do not include the
ELS-H weighting factors defined during lake selection (Section 2.2.2). The objective is
to better understand processes and factors that influence fish community status and fish
8-3
-------
distribution. Use of the ELS-H weighting factors to extrapolate from the sample of 49
lakes to the ELS-n target population is presented in Section 9.
Consistent with the basic format used in other sections, among-lake patterns in
fish community characteristics are discussed for each measured response variable in the
following order: species richness (Section 8.2), fish species presence/absence (Section
8.3), total catch and CPUE (Section 8.4), and fish size and condition factors (Section
8.5). Section 8.1 contains an evaluation of multicollinearity among the 19 predictor
variables of interest (i.e., the lake physical and chemical attributes described above).
As in Section 7, unless otherwise noted, the data and analyses presented are based on a
single sample per lake, collected between 8 June and 30 August 1987. Results from
duplicate surveys on 10 lakes, conducted 31 August to 12 September, are discussed and
analyzed in Section 4.2.
8.1 MULTICOLUNEARTTY AMONG PREDICTOR VARIABLES
Many of the predictor variables considered are themselves highly correlated (Table
8.1), causing problems with both model interpretation and inflated variance terms for
regression parameter estimates. Among-lake variations in lake pH, for example, were
significantly correlated (a=0.05, adjusted for 16 tests per variable, p< 0.0031) with ANC
(r=0.99, Spearman's rank correlation), the sum of base cations (r=0.81), Ca (r=0.77),
extractable Al (r=-0.68), SiOz (r=0.63), and DOC (r=0.45), and to a lesser degree (0.0031
< p <: 0.05) with inorganic Al (r=-0.41) and lake area (r=0.39). Seepage lakes had
significantly lower levels of ANC, Ca, sum of base cations, color, and SiOz than did
nonseepage lakes (Section 6.1, Table 6.2). These strong associations among key
predictor variables of interest make it difficult to determine the relative importance of
individual lake characteristics as factors influencing observed among-lake variations in
fish communities.
To quantify these patterns and associations among predictor variables, a principal
component analysis (Pielou 1984) was conducted on the full set of 19 chemical and
physical variables. Both nontransformed and log-transformed data were evaluated and
yielded similar results. The final data set consisted of a combination of nontransformed
and log-transformed variables, selected after examining the relationship between
individual predictor variables and the fish response data (see Sections 8.2 and 8.3). A
constant (100 peq/L) was added to ANC prior to the logarithmic (base e) transformation,
to adjust for ANC values ^ 0. Concentrations of extractable Al, inorganic Alj SiOz,
and total P £ 0 were converted to the lowest recorded positive value for the variable in
8-4
-------
I
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8-5
-------
the ELS-H data set (1 ug/L, 0.1 pg/L, 0.02 mg/L, and 0.5 pg/L, respectively) for log-
transformation. In each instance, these lowest recorded values were below the
minimum system detection limit defined in Linthurst et al. (1986).
Separate principal component analyses were conducted for the full set of 49 ELS-n
lakes in Subregion 2B and for the 38 lakes sampled with beach seines. Coefficients for
the first five principal components accounted for 82.8% and 85.2% of the total variation
in the 49-lake and 38-lake data sets, respectively; the first two principal components
accounted for 49.5% and 53.9% of the variation in the two data sets (Table 8.2). In both
data sets, the first principal component was defined primarily by terms related to ,
watershed weathering: Ca, the sum of base cations, lake pH, ANC, and SiO2« The
second principal component was determined largely by levels of DO, lake depth, and the
occurrence of thermal stratification. The relationships between these principal
components and fish response variables (species richness and fish species
presence/absence) are assessed in Sections 8.2 and 8.3.
8.2 SPECIES RICHNESS
Initially, simple associations between species richness and each lake characteristic
of interest were examined using nonparametric statistical tests: Spearman's rank
correlations for continuous predictor variables (e.g., lake pH) and the Wilcoxon rank sum
and Kolmogorov-Smirnov tests for binary predictor variables (i.e., lake type and the
occurrence of thermal stratification). The results were similar for the 49-lake data set
(with species richness defined by catch from gill nets, trap nets, and angling) and the 38-
lake data set (using the number of species caught in all four gear types, see Section 7.1).
Species richness was significantly correlated (a=0.05, adjusted for 19 tests per data set,
p £ 0.0026) with eight lake attributes: lake type, pH (r=0.74 for the 49-lake data set),
ANC (r=0.74), sum of base cations (r=0.65), Ca (r=0.64), SiOz (r=0.60), extractable Al
(r=-0.45), and DOC (r=0.42) (Table 8.3; Figures 8-1 and 8-2). Additional correlations
with 0.0026 < p := 0.05 include lake area, minimum DO, the occurrence of thermal
stratification, depth, and 804.
Multivariate models of species richness as a function of lake physical and chemical
characteristics were developed and explored using ordinary least-squares (OLS)
regression analysis (Myers 1986). As a first-step in OLS regression, single-variable
models and bivariate plots were examined for each variable to evaluate the need for
data transformations and to detect outliers and influential data points. For lake area,
depth, elevation, Ca, sum base cations, ANC, color, extractable Al, and total P, the log-
8-6
-------
Table 8.2. Results from Principal Components Analysis on 19 Physical and Chemical
Variables
Principal
Component 1
Variable
PH
In (Ca)
DOC
In (Inorg.Al)
In (Sum Base
Cations)
In (ANC)
hi (Color)
In (Ext Al)
SO4
SiOz
hi (Total P)
In (Area)
In (Depth)
In (Elevation)
In (Secchi
Depth)
Lake Type*
Minimum DO
% O2 < 4 mg/L
Thermal Strat.a
Eigenvalue
Proportion of
Total Variance
Cumulative
Variance
Explained
49
Lakes
0.369
0.379
0.211
-0.029
0.385
0.383
0.150
-0.207
0.156
0.366
0.075
0.208
0.092
0.014
-0.107
-0.263
-0.076
0.090
0.066
6.091
0.321
0.321
38
Lakes
0.363
0.370
0.216
-0.022
0.374
0.375
0.142
-0.217
0.155
0.362
0.113
0.218
0.110
-0.019
-0.095
-0.283
-0.062
0.077
0.099
6.432
0.339
0.339
Principal
Component 2
49
Lakes
-0.043
-0.055
-0.106
0.047
-0,060
-0.037
-0.125
-0^003
0.073
-0.029
-0.103
-0.132
-0.478
-0.085
0.208
-0.088
0,478 :-.
,0.425
0.480
3.309
0.174
0.495
38
Lakes
-0.011
-0.028
-0.195
0.032
-0.038
-0.013
-0.240
-0.069
0.090
-0.029
-0.162
-0.048
0.454
-0.061
0.358
-0.014
-0.432
0.367
0.446 ;
3.811
0.201
0.539
Principal
Component 3
49
Lakes
0.066
6.135
-0.360
0.035
0.121
0.110
-0.465
-0.173
0.271
0.033
-0.250
0.198
0.097
-0.221
6.457
0.169
0.184
-0.237
-0.109
2.968
0.156
0.651
38
Lakes
0.048
0.151
-0.299
0.104
0.140
0.098
-0.417
-0.055
0.328
0.040
-0.220
0.261
-0.016
-0.214
0.362
0.175
0.295
-0.325
-0.206
2.409
0.127
0.666
(continued)
8-7
-------
Table 8.2. Continued
Principal
Component 4
Variance
PH
In (Ca)
DOC
In (Inorg. Al)
In (Sum Base Cations)
In (ANC)
In (Color)
In (Ext. Al)
SO4
SiOz
In (Total P)
In (Area)
In (Depth)
In (Elevation)
In (Secchi Depth)
Lake Type^
Minimum DO
% Oz < 4mg/L
Thermal Strat.a
Eigenvalue
Proportion of Total Variance
Cumulative Variance
Explained
49
Lakes
-0.172
0.004
0.061
0.566
0.002
-Oil09
0.140
0.489
0.446
0.075
0.148
0.276
0.022
0.178
0.038
-0.183
0.054
0.017
-0.046
2.139
0.113
0.764
38
Lakes
-0.130
-0.018
0.182
0.512
-0.018
-0.115
0.205
0.484
0.387
0.035
-0.207
0.282
0.045
0.312
0.019
-0.131
-0.001
0.082
0.006
2.365
0.124
0.790
Principal
Component 5
49
Lakes
0.135
-0.001
0.104
-0.253
0.010
0.001
0.025
-0.060
0.000
-0.077
-0.608
0.079
-0.023
0.677
0.037
0.214
-0.090
0.067
-0.030
1.226
0.065
0.828
38
Lakes
-0.172
-0.057
-0.016
0.306
-0.074
-0.090
0.022
0.130
0.058
0.040
0.603
0.073
0.052
-0.653
0.029
-0.192
0.001
0.001
0.033
1.163
0.061
0.852
Lake type and thermal stratification are coded as binary variables. Lake type =
1 for seepage lakes and 0 for nonseepage lakes. Thermal stratification = 1 for
lakes thermally stratified at the time of sampling and 0 for nonstratified lakes.
transformation (base e) resulted in a higher model coefficient of determination, an
improved residual plot (improved homogeneity of variance), and/or fewer outliers with
less influence on the regression (based on Cook's D statistic) relative to the
nontransformed data. For minimum DO, percent of the water column with
DO < 4 mg/L, DOC, and SiO2, the nontransformed data resulted in a better OLS model
8-8
-------
Table 8.3. Association Between Species Richness, Total Catch, and Catch Per Unit
Effort (CPUE, Averaged Over Gill Nets and Trap Nets) and Lake Physical
and Chemical Characteristics
Species Richness
Variables
Lake Type
Area
Depth
Elevation
Min. DO
% DO < 4 mg/L
Therm. Strat.
Sec chi Depth
PH
Inorg. Al
Ca
DOC
Sum Base Cations
ANC
Color
Ext. Al
SO4
SiOz
Total P
49 Lakes
*
0.39
ns
ns
-0.31
ns
X
ns
0.74*
ns
0.64*
0.42*
0.65*
0.74*
ns
-0.45*
0.31
0.60*
ns
38 Lakes
*
0.38
0.38
ns
-0.36
ns
X
ns
0.79*
ns
0.68*
0.45
0.68*
0.79*
ns
-0.48*
ns
0.68*
ns
Total Catch
ns
ns
ns
ns
ns
ns
ns
-0.38
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
CPUE
ns
ns
-0.30
ns
ns
ns
ns
-0.40
ns
-0.29
ns
ns
ns
ns
ns
ns
ns
ns
ns
a Analyses based on Spearman's rank correlation for continuous variables and
Wilcoxon rank sum and Kolmogorov-Smirnov tests for binary variables (lake type and
thermal stratification). Tests with p >0.05 noted as ns (not significant). Numbers
indicate correlation coefficients for comparisons with p < 0.05. Asterisks indicate
tests significant at 4, were
inconclusive; therefore, for consistency with other similar variables in the data set and
with the logistic models of fish presence/absence (Section 8.3), log-transformed data
were used for Secchi depth and inorganic Al and nontransformed data for 804.
Transformation of the dependent variable, species richness, was also considered.
A Box-Cox analysis (Box and Cox 1964) for linear models of species richness fit to pH
8-9
-------
10
9
8
7
6
»5
4
3
2
1
0
fl
9
i
7
6
5
4
3
2
1
0
0
10
- 9
. S
7
* 6
5
» 4
**» 3
* 2
»* MM* 1
< 5 6 7 89
pH
, 10
. . . 9
8
7
* 6
5
M1 , i
3
2
- 1
.,,,,.,,,, , , , o
K» ffl) 300 I
LAKE SUEFAffi AREA (HA)
4,
t
» *
* *
* ««
0123456789
MiUMDOW
.
.
*
.. .
...
...
.-
. . .
"
- .-
M liUO KD 200)
CkMj
Figure 8-1. Bivariate plots of species richness and lake characteristics, for those
continuous physical and chemical variable:! associated with species
richness at p S 0.05 (see Table 8.3).
8-10
-------
10
9
a
o 0
... 7
. 5
. . 4
. . a . 2
a» a a» a aa aa a 1
a . 0
0 ! I 6 8 BE 11
n
a a a 9
8
... 7
a a a 6
5
4
3
a a a 2
. 1
0
m o m mm
a a
a. a
...
a- .
aa
-
a a a
** iii
o n m m
SUMOFlHEIUSECATiOllSW')
a
M
1
a a a
M
aiaai a
.. a.
M* e
* *
) 10) 20) Ss
Figure 8-1. Continued.
8-11
-------
10
. . 9
8
7
5
5
4
M 2
mmm* j
0
.
..
.
M) *
*
MM*
0 ffl 4)
SULKIER
123456189
SILICA W
Figure 8-1. Continued.
and Ca indicated no need for transformation. Thus, in the analyses that follow, species
richness was used directly without transformation.
For several predictor variables of interest, examination of the residual plots for
the single-variable OLS models indicated one or two outliers and/or influential data
points. Typically, these outliers/influential data points represented lakes with values at
the high end of the range for the 49 ELS-n lakes. The specific lake identified varied,
however, among predictor variables. In addition, there was no indication that errors in
data collection or recording could account for these outliers. Thus, no data points were
discarded from subsequent analyses, although the effects of outliers on model results
were continually examined as part of model development«
Three approaches -stepwise forward and backward and maximum r2 OLS
regressions - were conducted to examine the relationship between species richness and
multiple lake attributes. For the 49-lake data set, all three approaches identified the
same model, predicting species richness as a function of three variables (Table 8.4):
lake pH, SiO2, and the occurrence of thermal stratification (model r2=0.69). On the
other hand, for the 38-lake data set (including species collected with beach seines), each
8-12
-------
w
-
w
2
35
S
o
w
0.
93
NONSEEPAGE SEEPAGE
w
z
a
en '
5
w .
a.
MIXED STRATIFIED
Figure 8-2. Box-and-whisker plots comparing species richness in (a) seepage versus
nonseepage lakes and (b) thermally stratified versus mixed lakes. The
vertical bar represents the data range; the upper and lower boundaries
of the box, the 75% and 25% quartiles; the notch, the 90% confidence
limits around the median; the center of the box, the median; and the
cross-mark, the mean.
8-13
-------
approach selected a slightly different model, perhaps reflecting the model instability
typically associated with a high level of collinearity among predictor variables. Four
variables were included in the final model by stepwise forward OLS: pH, lake type, the
occurrence of thermal stratification, and SO4 (model r2=0.79). Stepwise backward OLS
identified a five-variable model including inorganic Al, DOC, the sum of the base
cations, SO4, and the occurrence of thermal stratification (model r2=0.82). Results
from the maximum r2 approach were consistent with results for the 49-lake data set,
selecting lake pH, SiOz, and the occurrence of thermal stratification as the best three-
variable model (model r2=0.78)(Table 8.4). In both data sets, species richness was
positively associated with all three variables; i.e., all other factors being equal, lakes
with more species tended to have higher pH and SiO2 and were more likely to be
thermally stratified. Silica in the model may serve as a surrogate for lake type.
Nonseepage lakes had significantly higher levels of SiO2 (Table 6.2) and higher numbers
of species (Table 8.3) than did seepage lakes.
Table 8.4. Multivariate Regression Models for Species Richness
Regression Coefficient
Data Set
49 lakes
38 lakes
Variable
Intercept
Lake pH
Si02
Thermal Strat.a
Intercept
Lake pH
Si02
Thermal Strat.a
Estimate
-4.02
1.06
0.46
1.22
-5.48
1.33
0.60
2.04
Std.
Error
1.65
0.30
0.14
0.45
2.14
0.40
0.18
0.62
Model
p-Value r2
0.0187 0.69
0.0010
0.0014
0.0095
0.0152 0.78
0.0021
0.0020
0.0023
Condition
16.0
17.7
a Thermal stratification coded as a binary variable = 1 for lakes thermally stratified at
the time of sampling and 0 for nonstratified lakes.
Interactions among predictor variables may also be important. For example, the
relationship between species richness and lake pH differs significantly (p < 0.05)
between seepage and nonseepage lakes (Table 8.5, analysis of covariance, Snedecor and
Cochran 1967). While species richness and lake pH are highly correlated in nonseepage
lakes (r=0.92, Spearman's rank correlation), the relationship is somewhat less consistent
in seepage lakes (r=0.60)(Figure 8-3). Inclusion of interaction terms in the above
8-14
-------
multivariate regression analyses would further aggravate problems with
multicollinearity, and thus was not pursued.
Table 8.5. Analysis of Covariance: Variations in the Relationship Between Species
Richness and Lake pH, by Lake Type
Source
Degrees of
Freedom
Type I Sum of
Squares
f-Value
p-Value
49 LAKES
Model
Lake Type
pH
pH*Lake Type
Error
Corrected Total
38 LAKES
Model
Lake Type
PH
pH*Lake Type
Error
Corrected Total
1
1
1
45
48
1
1
1
34
37
108.0
113.3
19.4
112.9
353.6
231.2
136.8
28.6
122.0
518.6
43.0
45.2
7.7
64.4
38.1
8.0
0.0001
0.0001
0.0079
0.0001
0.0001
0.0079
The relationship between species richness and each of the physical/chemical
principal components described in Section 8.1 was also examined. Only the first
principal component (determined largely by Ca, base cations, pH, ANC, and SiOz) was
significantly (p < 0.05) associated with species richness: model r2=().67 for the 49-lake
data set and 0.76 for the 38-lake data set.
Clearly, species richness is influenced by a number of lake attributes including,
but not limited to, factors related to lake acidity. Important variables include, at a
minimum, lake pH, lake type (or SiOz concentrations), and the occurrence of thermal
stratification. The observed relationships between species richness and each of these
variables are consistent with the expected patterns and hypotheses discussed at the
beginning of Section 8. The high degree of correlation among lake characteristics
complicates, however, interpretation of these results. The relative importance of
8-15
-------
10
g
8
I 7]
I
S 54
CO
I ^
firl
A . rt
CO ^'
2-
1-
0-
4 5 6 7 8 9 10
PH
10-
9-
8-
I ?
§ 6
O
S 5,
CO
§ 4
W
Q f O
co J"
2-
1-
0-
i i
i ' ' ' i
456789
pH
i
10
Figure 8-3. Species richness as a function of lake pH for (a) seepage and
(b) nonseepage lakes.
8-16
-------
acidity-related factors cannot be quantified with certainty, nor can the potential role of
other lake characteristics, not specifically identified in these analyses, be dismissed
with confidence.
8.3 FISH SPECIES PRESENCE/ABSENCE
Differences in the physical and chemical characteristics of lakes with fish caught
versus those without fish caught were examined for (1) individual fish species (for
species caught in at least three lakes), (2) cyprinid and darter species as a group (see
Table 7.1), (3) game fish as a group (defined in Section 3.6.2), and (4) all fish species
combined. As noted in Section 7.1, several fish species, especially cjrprinid and darter
species, were caught most effectively with beach seines, but beach seines were used in
only 38 of the 49 lakes. For those fish species, and for cyprinids and darters examined
as a group, analyses of lake characteristics were restricted to the 38 lakes sampled with
beach seines. For all other analyses, the full data set of 49 lakes was used.
Comparisons of the characteristics of lakes with and without fish were based on
the Wilcoxon rank sum and Kolmogorov-Smirnov tests for continuous variables and the
Fisher exact test for binary variables. The Fisher exact test requires that fewer than
25% of the cells have expected counts less than five observations to calculate a valid
chi-square. Thus, the tests for lake type and occurrence of thermal stratification could
be run for only some species.
Of the 20 species tested, statistically significant differences in lake
characteristics (a=0.05, adjusted for 19 tests per species, p < 0.0026) were detected only
for four species: white sucker, golden shiner, northern pike, and smallmouth bass
(Tables 8.6 and 8.7). All species except four (brook trout, central mudminnow, brook
stickleback, and yellow perch), however, had at least one physical or chemical variable
with p < 0.05. All four of these species have been reported in prior studies to be
tolerant of acidity (Althshuller and Linthurst 1984, Rahel and Magnuson 1983, Schofield
and Driscoll 1986) and other extreme environmental conditions (e.g.., Tonn and Magnuson
[1982] observed that central mudminnows are common in northern Wisconsin lakes that
experience near zero DO levels under ice cover).
Of the 19 variables examined, significant differences (p < 0.0026) between lakes
with and without individual fish species were found for eight variables: lake pH (for 4 of
20 species), Ca (3 species), ANC (3 species), sum of base cations (2 species), lake area
(2 species), SiOz (2 species), SO4 (1 species), and lake type (1 species^out of 8 with
sufficient numbers of lakes in each cell for a valid test). For those species for which
8-17
-------
Table 8.6. Comparison of Lake Physical Characteristics for Lakes With (P) and Without (A)
Fish Caughta
Fish Species/
Group
All Fish
Game Fish
Cyprinids
Darters
Brook Trout
Centra]
Mudminnow
Northern Pike
Creek Chub
Golden Shiner
Common
Shiner
Bluntnose
Minnow
Finescale Dace
White Sucker
Brown
Bullhead
Brook
Stickleback
Rock Bass
Smallmouth
Bass
Largemouth
Bass
Pumpkinseed
Bluegill
Sunfish
Black Crappic
Yellow Perch
Johnny Darter
Iowa Darter
» Stalisf.innl c.nr
No. of Lakes
with Fish
P
4V
36
16
9
4
5
11
4
12
7
7
5
14
13
3
4
5
16
15
13
3
31
3
6
nn»i'is<
A
2
13
22
29
45
44
38
45
37
42
31
44
35
36
46
45
33
33
34
36
46
18
35
32
nno Fnr
Lake
Type Area
ns
x ns
X X
ns
ns
ns
ns *
ns
x ns
ns
ns
ns
* x
x ns
ns
x
~ *
ns x
x ns
ns ns
ns
ns ns
ns
ns
1 /»nn( imirtttc 1/0 1
Site
Depth
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
x
ns
ns
ns
ns
x
x
ns
ns
ns
ns
ns
ns
ns
r* I o l-»l f\e* /»*
Eleva-
tion
ns
ns
ns
x
ns
ns
ns
ns
ns
ns
ns
ns
ns
x
ns
x
X
ns
ns
ns
ns
ns
x
ns
Min.
DO
x
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
x
ns
ns
ns
ns
ns
x
ns
ns
ns
ns
ns
- _..-..
%DO Therm.
< 4 mg/L Strat.
ns -
ns ns
ns
ns
ns
ns
ns ns
ns
ns ns
ns
ns
ns
x ns
ns ns
ns
ns
ns -
ns ns
x ns
ns ns
ns
ns ns
ns
ns
Secchi
Depth
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
_s
ns
ns
ns
ns
ns
__. vu...f,u. .uu.Ak> », fuiiuiiiuuua vai lauiea m e uabeu on me w ncoxon ranK sum and
Kolmogorov-Smirnov tests. Statistical comparisons for binary variables (lake type and thermal
stratification) are based on the Fisher exact test. Asterisks indicate tests considered
statistically significant at o=0.05 adjusted for 19 tests per species (including both chemical and
physical variables), i.e., p £ 0.0026. x's indicate tests with p<0.05; dashes indicate variables
and species for which statistical comparisons could not be conducted; and ns indicates variables
that were not significant, p > 0.05.
8-18
-------
Table 8.7. Comparison of Lake Chemical Characteristics for Lakes With (P) and Without (A)
FishCaughta
I
Fish Species/
Group
All Fish
Game Fish
Cyprinids
Darters
Brook Trout
Central
Mudminnow
Northern Pike
Creek Chub
Golden Shiner
Common
Shiner
Bluntnose
Minnow
Finescale Dace
White Sucker
Brown
Bullhead
Brook
Stickleback
Rock Bass
Smallmouth
Bass
Largemouth
Bass
Pumpkinseed
Bluegill
Sunfish
Black Crappie
Yellow Perch
Johnny Darter
Iowa Darter
>Jo. of Lakes
with Fish
P
47
36
16
9
4
5
11
4
12
7
7
5
14
13
3
4
5
16
15
13
3
31
3
6
A
2
13
22
29
45
44
38
45
37
42
31
44
35
36
46
45
33
33
34
36
46
18
35
32
Inorg.
pH Al
X
ns
*
*
ns
ns
*
ns
*
X
X
ns
*
ns
ns
X
*
X
X
X
X
ns
X
X
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
Ca
ns
ns
*
*
ns
ns
*
ns
*
X
X
ns
*
ns
ns
X
X
ns
X
X
X
ns
X
X
DOC
ns
ns
*
ns
ns
ns
X
ns
X
X
ns
ns
X
ns
ns
ns
X
ns
ns
ns
ns
ns
ns
ns
Base
Cations
ns
ns
*
*
ns
ns
ns
ns
*
X
X
ns
*
ns
ns
X
X
ns
X
X
X
ns
X.
X
ANC
X
ns
*
*
ns
ns
*
ns
*
X
X
ns
*
ns
ns
X
X
X
X
X
X
ns
X
X
Color
ns
ns
ns
ns
ns
ns
ns
ns
X
:ns
ns
ns
X
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
Ext.
Al
ns
ns
X
X
ns
ns
X
ns
ns
ns
ns
ns
ns
ns
ns
X
X
X
ns
X
X
ns
, X
ns
SO4
ns
ns
X
ns
ns
ns
ns
ns
*
ns
ns
ns
X
ns
ns
ns
ns
ns
ns
ns
ns
ris
ns
ns
SiO2
ns
ns
*
*
ns
ns
X
X
*
ns
X
ns
*
ns
ns
ns
X
ns
X
ns
X
ns
X
X
Total
P
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
X
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
a Statistical comparisons are based on the Wilcoxon rank sum and Kolmogorov-Smirnov tests.
Asterisks indicate tests considered statistically significant at q=0.05 adjusted for 19 tests per
species (including both chemical and physical variables), i.e., p ^ 0.0026. x's indicate tests with
p < 0.05; and ns indicates variables that were not significant, p > 0.05.
8-19
-------
statistical differences were identified, lakes without fish caught had consistently lower
pH, Ca, ANC, sum of base cations, SiO2, and SO4, had smaller lake area, and were more
often seepage lakes than nonseepage lakes. All variables except thermal stratification,
Secchi depth, and inorganic Al had a calculated p value < 0.05 for at least one fish
species. As an example, differences between lakes with and without white sucker are
illustrated in Figure 8.4 for those physical and chemical variables with p < 0.05.
Of the 38 lakes surveyed with beach seines, cyprinid species (8 species; see Table
7.1) were caught in 16 lakes; darters (2 species) were collected in 9 lakes. In all lakes in
which darters were caught, cyprinids were also collected. Statistical differences
(p :£ 0.0026) between lakes with and without cyprinids occurred for six variables: lake
pH, Ca, DOC, ANC, sum of the base cations, and SiOz (Tables 8.6 and 8.7). Lakes
without cyprinids had significantly lower pH, Ca, DOC, ANC, sum of base cations, and
BiOz concentrations. Similar results were found for darters, with statistical differences
detected for the same set of chemical variables except DOC. Of the 38 lakes sampled
with beach seines, 24 (63.2%) were seepage lakes. Cyprinids and darters were caught in
only 6 of these seepage lakes (25% of the seepage lakes), but in 10 of the 14 nonseepage
lakes (71.4%).
For game fish and all fish species combined, no statistical differences (p > 0.0026)
were detected for any of the lake characteristics for lakes with and without fish caught
(Tables 8.6 and 8.7).
The relationship between fish species presence/absence and lake characteristics 1
was quantified using maximum likelihood logistic regression (Harrell 1983):
1
P =
i
1 +e
where:
P{ is the predicted probability of fish presence in lake i,
bQ through bfc are the estimated regression coefficients, and
Xil through Xik represent the physical and chemical characteristics of lake i.
In general, logistic regression models should include no more than m/10 independent
variables, where m is the number of observations for the least frequent category of the
1 Logistic regression analyses were conducted for the 17 continuous predictor
variables; models could not be developed for the two binary variables (lake type and
thermal stratification).
8-20
-------
ABSENCE PRESENCE
O'
z
ABSENCE PRESENCE
2
<
ABSENCE PRESENCE
CO
2
O
ABSENCE PRESENCE
Figure 8HL. Box-and-whisker plots comparing lake characteristics with and without
white sucker. The vertical bar represents the data range; the upper and
lower boundaries of the box, the 75% and 2,5% quartileiij the notch, the
90% confidence limits around the median; the center of the box, the
median; and the cross-mark, the mean.
8-21
-------
a
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AUSKNCK PRESENCK
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CO
ABSENCE PKtiSUNCU
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ABSENCE I'UESENCE
Figure 8-4. Continued.
8-22
-------
z
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AIUSENCE PRESENCE
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ABSENCE PRESENCE
Figure 8-4. Continued.
8-23
-------
binary response variable (i.e., the number of lakes with the fish species
absent)(Harrell 1983). Thus, logistic regression models were developed only for the
eight species and two groups of fish (game fish and cyprinids) caught in at least 10 lakes
(see Table 8.6). For all of these species and groups, fish were caught in greater than 10
but fewer than 20 lakes (i.e., 10 < m < 20); thus these analyses were limited to single-
variable models.
For each variable of interest, models based on the nontransformed and
log-transformed (base e) data were compared, using the likelihood ratio statistic (a
goodness-of-fit test that compares the specified model with the unrestricted model;
Statistical Analysis System [SAS] 1987). The results were generally similar to the model
comparisons conducted for the OLS species richness models (Section 8.2). For lake area,
elevation, Ca, sum of base cations, ANC, color, and extractable Al, for most fish
species (for those models with p ^ 0.05 for the predictor variable) the log-transformed
data resulted in a better goodness-of-fit (higher likelihood ratio) than did the
nontransformed data. For SO4, DOC, minimum DO, and proportion of the water column
with DO < 4 mg/L, models based on the nontransformed data had a better goodness-of-
fit. For SiO^, lake depth, inorganic Al, and total P, results from the logistic regression
analysis provided no definitive indication of the relative merits of the nontransformed
and log-transformed data. For consistency with the species richness models,
log-transformations were used for lake depth, inorganic Al, and total P, while values for
were not transformed.
Estimates of the model coefficients for each of the single-variable logistic models
with p £ 0.05 are provided in Table 8.8. As expected, the pattern of results is quite
similar to that for the nonparametric comparisons of lakes with and without fish. Five
predictor variables resulted in models of fish species presence/absence significant at
a=0.05, adjusted for 17 tests per species (p ^ 0.0029): lake pH, ln(Ca), ln(base cations),
In(ANC), and SiO2. All other variables examined except In(depth), ln(Secchi depth),
ln(inorganic Al), and ln(total P) had 0.0029 < p =£ 0.05 in at least one model (for 10 fish
species or groups). The probability of fish presence was consistently higher in lakes with
higher pH, Ca, DOC, base cations, ANC, color, SO-i, and SiOz; lower levels of
extractable Al and minimum DO; and a higher proportion of the water column with DO
< 4 mg/L; and for larger lakes at lower elevations (Table 8.8).
Principal components, derived from the principal components analysis of lake
physical and chemical variables described in Section 8.1 (Table 8.2), were also
considered as predictor variables of fish presence/absence in single-variable logistic
8-24
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regression models. For 4 of the 10 species/groups, the first principal component
(defined primarily by Ca, sum of the base cations, pH, ANC, and SiOz) was significantly
associated with fish presence/absence at a=0.05, adjusted for 19 tests per species/group
(p < 0.0026); two additional species had 0.0026 < p < 0.05 for principal
component 1 (Table 8.8). Brown bullhead and cyprinid presence/absence were associated
at 0.0026 < p <: 0.05 with principal component 5 (defined primarily by lake elevation and
total P). Game fish and yellow perch were marginally associated (0.0026 < p =£ 0.05)
with higher-order principal components, 8 and 14, respectively. All other comparisons
between fish presence/absence and the lake physical/chemical principal components
were nonsignificant with p > 0.05.
Given that many of the above predictor variables (e.g., pH, Ca, ANC, sum of base
cations, SiOz, lake type, and lake area; Section 8.1) are themselves highly collinear, it is
not possible to determine definitively which lake attributes are actually most important
in controlling patterns of fish species distribution among the ELS-H lakes. Individual
predictor variables resulting in the highest likelihood ratio (goodness-of-fit) for each
species in the single-variable logistic regression models were as follows: white sucker,
SiOz (0.96)(also principal component 1, 0.97); cyprinids and northern pike, pH (0.92 and
0.89, respectively); golden shiner, ln(sum of base cations) (0.60)(also principal component
1, 0.71); bluegill sunfish and largemouth bass, ln(extractable Al) (0.59 and 0.44,
respectively); brown bullhead, ln(elevation)(0.55); and pumpkinseed sunifish, ln(Ca) (0.42).
In contrast, for yellow perch and game fish (which includes yellow perch),
presence/absence was not significantly associated with any of the lake physical or
chemical attributes considered.
The pH range of occurrence for each species caught in at least five ELS-H lakes is
illustrated in Figure 8-5. Consistent with the above results, yellow perch, central
mudminnow, and brown bullhead appear quite tolerant of acidic conditions, occurring at
pH levels as low as 4.55-4.74. Bluegill sunfish were also caught in lakes with very low
pH (4.55). Pumpkinseed sunfish, largemouth bass, and golden shiner occurred at pH
levels down to 4.9-5.1, while cyprinid and darter species were generally restricted to
lakes with pH > 5.7. A two-way analysis of variance (lake pH as a function of lake type
and fish presence/absence, for each species caught in at least 10 lakes) indicated no
significant differences (p >0.05) in the pH levels associated with fish presence/absence
in seepage as opposed to nonseepage lakes.
8-29
-------
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8-30
-------
8.4 TOTAL CATCH AND CATCH PER UNIT EFFORT
In contrast to the large number of variables associated with species richness and
fish presence/absence, nonparametric comparisons between total catch (and CPUE; all
fish species combined) and the 19 physical and chemical variables of interest indicated
no correlations significant at a=0.05 (adjusted for 19 tests per fish response variable,
p < 0.0026) and only three physical/chemical variables with 0.0026 < p ^ 0.05 (depth,
Secchi depth, and inorganic Al)(Table 8.3). Ordinary least-squares regression with
In(catch) (for the 47 lakes with fish caught) produced similar results. Stepwise forward
OLS regression identified only In(depth) as significant at p < 0.05. Total catch and lake
depth were inversely related with a very low model r2 (0.11). Likewise, regression of
the physical/chemical principal components (Table 8.2) on In(catch) and In(CPUE)
indicated no significant associations (all principal components had p > 0.05).
Among-lake patterns in catch and CPUE were also examined for the 8 individual
fish species caught with gill nets and trap nets in 10 or more lakes.. Oinly for yellow
perch were any significant associations (at a=0.05, adjusted for 19 tests per response
variable per species, p < 0.0026) identified between fish catch or CPUE and lake
physical and chemical characteristics (Table 8.9). Numbers of yellow perch caught and
yellow-perch CPUE (for both gill nets and trap nets) were higher in lakes with lower pH
(r=-0.68 to -0.72, Spearman's rank correlation), ANC (r=-0.68 to -0.71), Ca (r=-0.56 to
-0.61), sum of base cations (r=-0.55 to -0.60), and SK>2 (r=-0.48 to -0.56), and higher
concentrations of extractable Al (r=0.55 for trap-net CPUE). Thus, yellow perch appear
not only tolerant of acidic conditions, but actually more abundant in acidic waters with
low Ca, base cations, and SiOz.
The high variability in catch rates; discussed in Section 4.2.2, limits the utility of
catch and CPUE as indices of relative fish abundance. The lack of any clear
correlations between lake characteristics and fish catch for most species may result
largely from this high variability in catch efficiency. Definitive conclusions regarding
the relationship between lake characteristics and fish abundance are not possible based
solely on the ELS-n survey data.
8.5 FISH CONDITION FACTORS
Only four fish species had adequate numbers of fish caught and measured (at least
five fish per lake, including fish caught in the duplicate surveys, Section 4.2.2) in a
sufficient number of lakes (at least five) for evaluation of among-lake patterns in fish
condition factors: largemouth bass (7 lakes), northern pike (7), white sucker (11), and
8-31
-------
Table 8.9. Association Between Total Catch and Catch Per Unit Effort and Lake Physical
and Chemical Characteristics for Selected Fish Species3
Yellow Perch
Northern Pike
Largemouth Bass
No. of Lakes
VARIABLE
Lake Type
Area
Depth
Elevation
Minimum DO
%DO < 4mg/L
Thermal
Slratif.
Secchi Depth
pll
Inorg. Al
Ca
DOC
Sum Base
Cations
ANC
Color
Ext. Al
S04
S502
Total P
Total
Catch
31
-
-0.41
ns
ns
ns
ns
ns
ns
-0.71*
ns
-0.61*
-0.38
-0.60*
-0.71*
ns
0.46
ns
-0.55*
ns
Gill-
Net
CPUE
31
X
-0.47
ns
ns
ns
ns
ns
ns
-0.68*
ns
-0.60*
-0.41
-0.60*
-0.68*
ns
0.38
ns
-0.56*
ns
Trap-
Net
CPUE
31
X
-0.37
-0.42
ns
ns
ns
ns
ns
-0.72*
ns
-0.56*
-.036
-0.55*
-0.71*
ns
0.55*
ns
-0.48*
ns
Total
Catch
11
-
ns
ns
ns
ns
ns
ns
ns
0.62
ns
0.62
ns
0.64
0.61
ns
ns
ns
ns
ns
Gill-
Net
CPUE
11
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
Trap-
Net
CPUE
11
X
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
0.70
ns
Total
Catch
13
-
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
Gill-
Net
CPUE
13
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
Trap-
Net
CPUE
13
ns
-0.60
ns
ns
ns
ns
ns
ns
ns
hs
ns
ns
ns
ns
ns
ns
ns
ns
ns
(continued)
8-32
-------
Table 8.9. Continued
Pumpkinseed
Brown Bullead
Golden Shiner
No. of Lakes
VARIABLE
Lake Type
Area
Depth
Elevation
Minimum DO
%DO < 4mg/L
Thermal
Stratif.
Secchi Depth
pH
Inorg. Al
Ca
DOC
Sum Base
Cations
ANC
Color
Ext. Al
S04
Si02
Total P
Total
Catch
15
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
Gill-
Net
CPUE
15
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
0.56
ns
ns
Trap-
Net
CPUE
15
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
Total
Catch
13
_
-0.68
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
Gill-
Net
CPUE
.13
X
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
Trap-
Net
CPUE
13
ns
-0.66
ns
ns
ns
ns
ns
-0.60
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
Total
Catch
12
.
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
0.61
ns
ns
ns
ns
Gill-
Net
CPUE
12
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
Trap-
Net
CPUE
12
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
ns
Analyses restricted to those lakes in which the species was caught. For continuous variables,
values reported are the Spearman's rank correlation coefficient. For binary variables (lake type
and thermal stratification, comparisons are based on Wilcoxon rank sum and Kolmogorov-
Smirnov (K-S) tests. Asterisks indicate correlations significant at °c=0.05, adjusted for 19 tests
per response variable per species (p < 0.0026). For the Wilcoxon and K-S tests, x's indicate
p < 0.05. For two fish species, white sucker and bluegill sunfish, all comparisons were non-
significant with p > 0.05 (ns); therefore, no results for these species are included in the table.
8-33
-------
yellow perch (29). Variations in fish condition factors were analyzed as a function of
fish length and each of the 19 physical/chemical lake characteristics of interest, in
separate two-variable OLS regression models (Table 8.10). Three-variable models with
fish condition as a function of fish length, the number of fish caught per lake, and each
lake attribute were also evaluated and provided similar results.
For each of the four species, fish condition factors were significantly associated
(a=0.05, adjusted for 19 tests per species, p < 0.0026) with at least one lake
characteristic. For white sucker, higher condition factors (heavier fish for a given
length) occurred in lakes at lower elevation; with higher transparency (Secchi depth),
pH, ANC, Ca, sum of base cations, SiOz, and total P; and lower levels of DOC, color,
and extractable Al. Yellow perch condition factors were significantly (p :£ 0.0026)
higher in shallower lakes; lakes with higher ANC, color, and SiOz; lower transparency; a
smaller percentage of the water column with DO < 4 mg/L; and higher minimum DO
values; and in lakes not thermally stratified. In contrast, condition factors for northern
pike and largemouth bass were significantly correlated (p < 0.0026) with relatively few
lake characteristics. Northern pike tended to have higher condition factors in larger
lakes with higher levels of DO. Variations in largemouth bass condition factors were
significantly associated only with variations in total P: heavier fish (adjusted for fish
length) occurred in lakes with lower levels of total P.
Given the large number of factors that influence fish growth and condition, and
also expected variations in condition factors across the three-month sampling period,
the above results must be interpreted with caution. Specific factors responsible for
variations in fish condition among lakes cannot be determined from the ELS-H survey
data.
8-34
_
-------
Table 8.10 Summary of Results from Ordinary Least Squares Regression of Fish Condition
Factors as a Function of Fish Length and Lake Physical and Chemical
Characteristics8
Northern Pike
Largemouth
White Sucker Bass
Yellow Perch
No. of Fish
Lake Type
In (Area)
In (Depth)
In (Elevation)
Min.DO
%DO< 4mg/L
Thermal Strat.
In (Secchi Depth)
pH
In (Inorg. Al)
In (Ca)
DOC
In (Base Cations)
In (ANC)
In (Color)
In (Ext. Al)
SO4
SiO2
In (Total P)
88
X
*
ns
ns
X
*
ns
ns
ns
ns
ns
X
ns
ns
ns
ns
ns
ns
ns
,282
ns ,
ns
X
*
ns
ris
ns
*
*
X
*
*
*
. *
*
*
, ns
*
*
89
ns
ns
ns
X
ns
ns
ns
ns
ns
ns
ns
X
ns
ns
ns
X
ns
ns
*
1174
ns
ns
*
ns
*
*
* -
*
ns
ns
ns
ns
X
*
*
ns
X
*
ns
a In most cases, the relationship between fish condition and fish length was significant (p <
0.0029). Asterisks in the table indicate significant relationships between fish condition factors
and lake characteristics, adjusted for fish length [model: fish condition=f (fish length, lake
attribute)] at oc=0.05, adjusted for 19 tests per species (p < 0.0026); x's indicate models with p
< 0.05; ns indicates p > 0.05. Analyses include only lakes with at least five fish of the species
caught.
8-35
-------
-------
9. REGIONAL POPULATION ESTIMATES
Based on the probability sampling frame for the ELS-I and ELS-n surveys
(Section 2), data collected on fish community status for the 49 ELS-Et lakes can be
extrapolated to estimate fish community characteristics for Subregion 2B as a whole. In
this section, regional estimates are provided for (1) the numbers and area of lakes with
selected fish species and groups of fish (e.g., game fish) and (2) species richness. No
regional estimates are computed for fish catch, size, or condition factors.
Two methods of regional extrapolation were used to estimate the ELS-n target
population descriptions. The first approach involved a direct estimate from the ELS-n
sample using the ELS-n weighting factors described in Section 2.2.2 (Table 2.3). The
second approach incorporated the additional information collected in ELS-I (i.e., the
lake physical and chemical data). In this case, the observed relationships between fish
community status and lake characteristics for the 49 lakes sampled during ELS-H
(Section 8) were assumed to hold for all lakes in the ELS-H target population. Using
these relationships and the lake physical and chemical data collected in ELS-I, values
for the fish response variables (and associated estimates of standard error) can be
predicted for each ELS-I lake in the ELS-H target population (n=105 lakes). The ELS-I
weighting factors and algorithms for regional extrapolation were then applied to
calculate population estimates. Model-based population estimates were calculated only
for species richness. The specific procedures for computing population estimates and
appropriate measures of variance for both approaches are described in Overton (in
prep.), adapted from Overton (1987).
As discussed in Section 2.2, only 49 of the 50 lakes selected for ELS-H were
sampled. The lake not sampled, 2B1-065, has a small weighting factor (2.72) and
represents only 0.4% of the ELS-H target population (Table 2.3). As a result, the
absence of data for Lake 2B1-065 has a relatively minor impact on the ELS-Q population
estimates (and variances). For example, the estimated number of lakes in the ELS-U
target population based on the ELS-H weighting factors for the 49 lakes sampled is 639.5
(standard error = 148.3 lakes); as compared to 642.3 lakes (standard error = 100.4)
calculated from the ELS-H weighting factors for all 50 lakes, and 596.7 lakes (standard
error = 58.9) calculated using the ELS-I weighting factors for the 105 ELS-I lakes in the
ELS-n target population (see Section 2.2). The population estimates 1:hat follow,
therefore, were calculated from the 49-lake sample without any specific adjustment for
the missing data for Lake 2B1-065.
9-1
-------
Regional estimates of the number and area of lakes with fish present were
calculated for (1) all fish species combined, (2) for game fish as a group (see Section
3.6.2), and (3) for the 17 fish species susceptible to the three gear types fished in all
lakes (see Table 7.1), based on the ELS-n weighting factors and direct estimation from
the 49 lakes sampled in ELS-n (Table 9.1). The estimated proportion of the fishery
resource (i.e., lakes with the fish species present) occurring in lakes with low ANC
(< 50 peq/L) is also indicated in Table 9.1. Fish occurred in an estimated 99.4% of the
lakes in Subregion 2B (ELS-II target population), 99.5% based on lake area. Game
species (i.e., yellow perch, brook trout, lake trout, smallmouth bass, largemouth bass,
northern pike, and walleye) occurred in an estimated 83.7% of the lakes, 95.7% based on
lake area. Yellow perch was the most common species in Region 2B, occurring in an
estimated 69.8% of the lakes, 88.6% based on lake area. White sucker and largemouth
bass also occurred in over 50% of the lakes in the ELS-II target population (52.1% and
50.8%, respectively; 81.6% and 36.2% based on lake area). Of the estimated 535 lakes
supporting game species, 16.6% had ANC < 50 peq/L (4.0% based on lake area). Of the
estimated 73 acidic lakes in the ELS-n target population, 94.9% (69.5 lakes) support one
or more species of fish; 14.8% support only yellow perch.
Population estimates for species richness in lakes in Subregion 2B were calculated
in three manners:
1. a direct estimate from the ELS-n sample using the ELS-H weighting factors
and with species richness defined as the number of species caught with gill
nets, trap nets, and angling;
2. a model-based estimate based on the OLS regression model of species richness
as a function of the first 10 principal components derived from the 15 physical
and chemical lake characteristics measured during ELS-I and with species
richness defined as the number of fish species caught with gill nets, trap nets,
and angling; and
3. a model-based estimate as described above but with species richness defined as
the number of species caught in all four gear types, using data for only those 38
lakes sampled with beach seines.
The estimated mean number of species per lake from the direct estimation
procedure was 5.5 (median 5.4) as compared to 5.0 species per lake (median 5.3) from
the model-based approach. Inclusion of the catch in beach seines increases the
estimated mean number of species (using the model-based approach) to 6.3 (median 6.1).
Cumulative frequency distributions for the three population estimates (and associated
95% upper confidence limits) are presented in Figures 9-1 and 9-2.
9-2
-------
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-------
130-
120-
110-
100-
80-
70-
5 50-
I 40
O 30
20-
10
0
| I I I I I I I I I | I I L I 1 I I I I | I I I I ' I I I I | I I I t I I I I I | I I I I I I I I I |
0 2 4 6 8 10
SPECIES RICHNESS
2468
SPECIES RICHNESS
10
Figure 9-1. Cumulative frequency distributions of species richness (by number of
lakes) for lakes in Subregion 2B, based on (a) the direct ELS-n estimate
with 49 lakes and (b) the model-based approach, with species richness
defined from catch with gill nets, trap nets, and angling. Dashed line
indicates the 95% upper confidence limit.
9-4
-------
100-
90-
80-
§ 70-
W 60
CM
g 50
^ 40
§ 30
° 20
10
0
JT1 I ITl I 1 1 | I
0 2
468
SPECIES RICHNESS
10
Figure 9-2. Cumulative frequency distributions of species richness (by number of
lakes) for lakes in Subregion 2B, based on the model-based approach
with species richness defined from catch with gill nets, trap nets, and
angling (solid line) and with all four gear types (dashed line).
9-5
-------
-------
10. DISCUSSION AND SUMMARY
The fish species collected in the ELS-n were similar to those reported for lakes in
other areas of the Upper Midwest (Wiener and Eilers 1987). Thirty-one fish species were
collected in total. Yellow perch was the most common species, caught in 31 of the
49 lakes sampled and occurring in an estimated 69.8% of the lakes in the region (88.6%
based on lake area). Largemouth bass and white sucker also occurred in. over 50% of the
lakes in the ELS-n target population.
Several of the fish species common in the region are quite tolerant of acidic
conditions, as evidenced by their presence and reproduction in lakes with pH < 5.0.
Twelve of the 49 lakes surveyed had pH < 5.0, with a minimum lake pH of 4.43. Six fish
species occurred in at least one of these low-pH lakes: yellow perch (minimum pH of
occurrence 4.55), central mudminnow (pH 4.55), bluegill sunfish (pH 4.55), brook
stickleback (pH 4.65), brown bullhead (pH 4.74), and pumpkinseed sunfish (pH 4.94).
Three additional fish species were caught in the 8 ELS-n lakes with pH 5.0 to 5.5:
largemouth bass (pH 5.05), brook trout (pH 5.05), and golden shiner (pH 5.13). The
apparent tolerance of these species to acidic conditions is supported by their occurrence
in acidic waters in other surveys of lakes in the Upper Midwest (Rahel eind Magnuson
1983, Wiener 1983, Rahel 1986, Wiener and Eilers 1987) and in the Adirondack region of
New York State (Kretser et al. 1988) (Table 10.1).
While the presence of a reproducing population of fish in waters with low pH may
confirm the tolerance of the species to acidic conditions, the absence of fish from such
waters is not, by itself, sufficient evidence to conclude that the species is sensitive to
acidity. Eight fish species occurred in at least 5 of the ELS-H lakes, but only in lakes
with pH > 5.5: white sucker (n=14 lakes; minimum pH of occurrence 5.53), creek chub
(n=5; pH 5.75), bluntnose minnow (n=7; pH 5.75), Iowa darter (n=7; pH 5.75), finescale
dace (n=6; pH 5.75), northern pike (n=ll; pH 5.90), common shiner (n=7; pH 6.10), and
smallmouth bass (n=5; pH 7.05).
For some of these species, other information exists to support their classification
as acid sensitive. For example, cyprinid species have been identified as particularly
sensitive of low pH (pH 5.5-6.0) in laboratory and field bioassays (Johnson et al. 1987)
and during the experimental acidification of Lake 2Z3 (Mills et al. 1987, Mills and
Schindler 1986), consistent with their absence at pH < 5.7 in the ELS-H,, Rahel and
Magnuson (1983) exposed 12 fish species from northern Wisconsin lakes to low pH levels
in short-term laboratory bioassays. Cyprinids (e.g., bluntnose minnow and common
10-1
-------
Table 10.1. Minimum pH Levels of Fish Species Occurrence in Synoptic Lake Surveys
Fish Species
Acid-tolerant:
Yellow Perch
Central Mudminnow
Bluegill Sunfish
Brook Stickleback
Brown Bullhead
Pumpkinseed Sunfish
Moderately Acid-tolerant
Largemouth Bass
Brook Trout
Golden Shiner
Other Species
White Sucker
Creek Chub
Bluntnose Minnow
Finescale Dace
Iowa Darter
Northern Pike
Common Shiner
Smallmouth Bass
Upper Peninsula
of Michigan^
4.5
4.5
4.5
4.6
4.7
4.9
5.0
5.0
5.1
5.5
5.7
5.7
5.7
5.7
5.9
6.1
7.0
Northern
Wisconsin^
4.4
4.0
4.5
5.4
-
4.9
4.6
-
5.2
4.9
5.6
6.2
-
6.2
5.1
6.2
5.2
Adirondacks, NYC
4.5
4.2
-
-
4.5
4.6
4.7
4.6
4.5
4.6
4.6
6.6
-
-
5.6
4.9
5.6
ELS-n data base, for those species caught in 5 or more lakes of the 49 surveyed.
Wiener and Eilers (1987); species caught in 10 or more lakes of the 150 lakes
surveyed.
Kretser et al. (1988); species caught in 10 or more lakes of the 1123 surveyed.
shiner) were the most sensitive to low pH, while yellow perch, central mudminnows, and
black bullhead were the most acid tolerant (Table 10.2). Schofield and Driscoll (1987)
exposed seven species to acidic Adirondack stream water at pH 4.6. All common shiners
and creek chub had died within 28 days, while 72% of the yellow perch and 100% of the
central mudminnow survived. These results are consistent with the relative acid-
sensitivity of the species inferred from the ELS-n survey (Table 10.2).
10-2
-------
Table 10.2. Fish Survival Exposed to Continuously Declining pH in Laboratory
Bioassays (Source: Rahel and Magnuson 1983), Compared to the Relative
Sensitivity of Fish Species Inferred from the ELS-H Survey
Sensitivity Rank
Based on:
Blacknose Shiner
Bluntnose Minnow
Common Shiner
Northern Redbelly
Dace
Smallmouth Bass
Mottled Sculpin
Golden Shiner (young)
Golden Shiner (adult)
Walleye .
Rock Bass (adult)
Black Bullhead (young)
Rock Bass (young)
Black Bullhead (adult)
Central Mudminnow
Yellow Perch (young)
Yellow Perch (adult)
N
28
15
25
23
12
24
24
18
11
21
31
29
25
17
25
25
Median
Survival
Time (h)
99
105
105
126
160
162
174
176
220
223
223
236
240
240
>240
>240
J ~- m~- :
Median
Survival % Alive at Lab.
Time Termination Survival
4.05
4.00
4.00
3.85
3.60
3.55
3.45
3.45
3.20
3.15
3.15
3.10
3.05
3.05
<3.05
<3.05
0
0
0
0
0
0
0
0
18
14
3
31
48
41
96
80
-
1.5
1.5
-
3
-' -
- :.
4
.
-
5
-
-
6
-
7
ELS-H
Field
Distrib.
-
3
2
-
1
-
4
-
-
5
-
-
6.5
-
6.5
The absence of white sucker, northern pike, and smallmouth bass from ELS-n lakes
with pH < 5.5-5.7, on the other hand, may result from factors other than low pH. In
field surveys in northern Wisconsin (Rahel and Magnuson 1983) and New York (Schofield
and Driscoll 1987, Kretser et al. 1988), white sucker were caught in lakes with pH levels
as low as 4.6-4.9 (Table 10.1). During the experimental acidification! of Lake 223, no
adverse effects on white sucker populations were evident until pH levels reached 5.0-5.1
(Mills et al. 1987). Beamish et al. (1975) and Beggs et al. (1985) reported the extinction
of white sucker populations from Ontario lakes at pH 4.8-5.2. Similar thresholds for the
loss of northern pike and smallmouth bass in Ontario lakes were pH 4.7-6.2 (Beamish et
al. 1975) and pH 5.2-5.4 (Harvey and Lee 1982), respectively. Northern pike and
smallmouth bass have also been reported to occur at pH levels down to 5.1 to 5.2 in
10-3
-------
other areas of the Upper Midwest (Wiener and Eilers 1987) (Table 10.1). Rahel (1986)
proposed that the absence of these two species from small, low-ANC lakes resulted
from other habitat characteristics typical of these water bodies: the lack of vegetated
littoral areas required by northern pike for spawning and the preference of smallmouth
bass for wave-washed hard-bottomed substrates, generally rare in small, seepage lakes,
as habitat and spawning sites.
Fish species distributions among lakes in the Upper Peninsula of Michigan,
therefore, are influenced by a number of factors, not just acidity. In analyses of fish
community structure in lakes in northern Wisconsin, Tonn and Magnuson (1982), Rahel
and Magnuson (1983), Rahel (1986), and Rago and Wiener (1986) identified the
importance of lake isolation (i.e., lake type and connectedness), lake area, winter
anoxia, biological interactions, and lake pH and ANC as primary factors responsible for
fish community composition and species richness. Results from the Upper Peninsula of
Michigan were similar: fewer fish species occurred in seepage than in nonseepage lakes,
in smaller lakes, and in lakes with lower levels of ANC, Ca, and base cations, and higher
concentrations of extractable Al and DO.
Other than for yellow perch, no consistent relationship between fish catch, or
CPUE, and lake characteristics was evident for the 49 ELS-E lakes in the Upper
Peninsula of Michigan. Fish catch rates (capture efficiency) are often highly variable,
making detection of patterns among lakes difficult (Ricker 1975, Bannernot and Austin
1983). Associations between CPUE and lake chemistry have been reported for some
surveys (Kretser et al. 1988, Frenette et al. 1986), while other survey data sets suggest
no consistent trends or relationships (Beggs et al. 1985, Haines et al. 1986). It is unclear
whether the lack of a consistent pattern results from sampling variability or the absence
of simple relationships between fish abundance and lake characteristics, detectable in
synoptic surveys.
Likewise, fish condition factors tend to be highly variable, among seasons, among
years, and among lakes, and influenced by a large number of environmental variables. In
the ELS-n lakes, white sucker condition factors were significantly correlated with 11 of
the 19 lake attributes evaluated; yellow perch with 8. Interpretation of these patterns
to delineate effects related to acidity was not possible.
Studies in the Adirondack region of New York (Schofield and Trojnar 1980) and
laboratory bioassays (Driscoll et al. 1980, Baker 1982, Ingersoll 1986) identified low pH
and elevated levels of inorganic Al as the primary toxic agents in acidic waters. In the
10-4
-------
ELS-n survey, however, relatively little of the among-lake variation in fish community
status could be attributed to inorganic Al. Concentrations of Al are often low in
seepage lakes (Eilers et al. 1988); sixteen of the 20 acidic lakes sampled were seepage
lakes and all but one of the lakes sampled had levels of inorganic Al < 60 ug/L. As a
result of these low concentrations, inorganic Al may play a relatively minor role in the
effects of acidification on fish populations in the region.
Despite the relatively large numbers of acidic and low-pH lakes in the Upper
Peninsula of Michigan, Subregion 2B, most lakes in the area (over 99% of the ELS-n
target population by number and by lake area) support at least one fish species. Eighty-
four percent of the lakes (96% of the lake area) support at least one game species
(defined as yellow perch, walleye, largemouth and smallmouth bass, brook trout, and
lake trout). Of the estimated 636 lakes that currently support fish in Subregion 2B (in
the ELS-n target population), 23.3% have ANC < 50 peq/L and thus are potentially
sensitive to future effects from acidic deposition; an estimated 16.6% of the lakes with
game fish currently have ANC ^ 50 peq/L.
The ELS-n data base on fish communities in lakes in Subregion 2B provides a
regional perspective on the current status of the fishery resource in the Upper Peninsula
of Michigan and adjacent northeastern Wisconsin. It cannot be used., by itself, to
determine whether aquatic resources in the region have been impacted by acidic
deposition, nor to determine specific causes for observed among-lake patterns in fish
communities. The ELS-H may, however, provide insight into processes of importance in
controlling fish population responses to acidification and serve as a baseline for future
analyses of trends in fish communities in the area.
10-5
-------
-------
11. REFERENCES
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its effects. Critical assessment review papers - ffl: Effects sciences. EPA-600/8-
83/016BF. U.S. Environmental Protection Agency, Washington, DC.
Anderson, R.O., and S.J. Gutreuter. 1983. Length, weight, and associated structural
indices. Pages 283-300. In: L.A. Nielsen and D.L. Johnson, eds. Fisheries Techniques.
Am. Fish. Soc., Bethesda, MD.
Baker, J.P. 1982. Effects on fish metals associated with acidification. Pages 165-175.
In: R.E. Johnson, ed. Acid Rain/Fisheries. Am. Fish. Soc., Bethesda, MD.
Bannerot, S.P., and C.B. Austin. 1983. Using frequency distributions of catch per unit
effort to measure fish-stock abundance. Trans. Am. Fish. Soc. 112:608-617.
Beamish, R., W.L. Lockhart, J.C. Van Loon, and H.H. Harvey. 1975. Long-term
acidification of a lake and resulting efects oh fishes. Ambio. 4:98-102.
Beggs, G.L., J.M. Gunn, and C.H. Oliver. 1985. The sensitivity of Ontario lake trout
(Salvelinus namaycush) and lake trout lakes to acidification. Ontario Fisheries
Technical Report Series No. 17. Ontario Ministry of Nat. Resour., Toronto.
Belsley, D.A., E. Kuh, and R.E. Welsch. 1980. Regression Diagnostics: Identifying
Influential Data and Sources of Collinearity. John Wiley & Sons, New York.
Box, G.E.P., and D.R. Cox. 1964. An analysis of transformations. J. Roy. Statist. Soc.
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Bray, J.R., and J.T. Curtis. 1957. An ordination of the upland forest communities of
southern Wisconsin. Ecol. Monographs 27:325-349.
Brown, D.J.A. 1983. Effect of calcium and aluminum concentration on the survival of
brown trout (Salmo trutta) at low pH. Bull. Environ. Contam. Toxicol. 30:582-587.
Cochran, W.G. 1977. Sampling Techniques, 3rd ed. John Wiley & Sons, New York.
Conover, W.J. 1980. Practical Nonparametric Statistics, 2nd ed. John Wiley & Sons,
New York.
Driscoll, C.T., J.P. Baker, J.J. Bisogni, and C.L. Schofield. 1980. Effect of aluminum
speciation on fish in dilute acidified waters. Nature 284:161-164.
Drouse, S.K., D.C. Hillman, L.W. Creelmah, and S.J. Simon. 1986. National Surface
Water Survey Eastern Lake Survey (Phase I Synoptic Chemistry) Quality Assurance
Plan. EPA-600/4-86/008. U.S. Environmental Protection Agency, Las Vegas, NV.
Eddy, S. 1969. How to Know the Freshwater Fishes, 2nd ed. Wm. C. Brown Co.,
Dubuque, IA.
11-1
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Eilers, J.M., D.F. Brakke, and D.H. Landers. 1988. Chemical and physical
characteristics of lakes in the Upper Midwest, United States. Environ. Sci. Technol.
22:164-172.
Everhart, W., A. Eipper, and W. Youngs. 1975. Principles of Fishery Science. Cornell
University Press, Ithaca, NY.
Fabrizio, M.C., and W.W. Taylor. 1987. National Surface Water Survey Phase H - Upper
Midwest Lake Survey. Field Training and Operations Manual - Part I - Fish Surveys.
U.S. Environmental Protection Agency, Corvallis, OR.
Fleiss, J.L. 1981. Statistical Methods for Rates and Proportions, 2nd ed. J. Wilev &
Sons, New York.
Frenette, J.J., Y. Richard, and G. Moreau. 1986. Fish response to acidity in Quebec
lakes: A review. Water, Air, Soil Pollut. 30:461-475.
Hagley, C., G. Merritt, and B. Baldigo. 1987. National Surface Water Survey Phase H -
Upper Midwest Lake Survey, Field Training and Operations Manual - Part II, EPA Field
Activities. U.S. Environmental Protection Agency. Corvallis Environmental Research
Laboratory, Corvallis, OR.
Haines, T.A., S.J. Pauwels, and C.H. Jagoe. 1986. Predicting and evaluating the effects
of acidic deposition on water chemistry and endemic fish populations in the northeastern
United States. U.S. Fish and Wildl. Serv., Eastern Energy and Land Use Team. Biol.
Rep. 80(40.23).
Harrell, Jr., F.E. 1983. The LOGIST Procedure. Pages 181-202. In: SUGI
Supplemental Library User's Guide. SAS Institute, Gary, NC.
Harvey, H.H. 19?9. The acid deposition problem and emerging research needs in the
toxicology of fishes. Proceedings of the Fifth Annual Aquatic Toxicity Workshop,
Hamilton, Ontario, November 7-9, 1978. Fish Mar. Serv. Tech. Rep. 862.
Harvey, H., and C. Lee. 1982. Historical fisheries changes related to surface water pH
changes in Canada. Pages 45-55. In: Acid Rain/Fisheries, R.E. Johnson, ed. American
Fisheries Society, Bethesda, MD.
Hillman, D., J. Eilers, and C. Monaco. Recalculation of acid neutralizing capacity from
EPA s National Lake Survey and its impact on data interpretation. In Prep.
Hollander, M., and D.A. Wolfe. 1973. Nonparametric Statistical Methods. John Wilev
8c Sons, New York. -
Hubbs, C.L., and K.F. Lagler. 1947. Fishes of the Great Lakes region. The University
of Michigan Press, Ann Arbor.
Ingersoll, C.G. 1986. The effects of pH, aluminum, and calcium on survival and growth
of brook trout (Salvelinus fontinalis) early life stages. Ph.D. Thesis. University of
Wyoming, Laramie.
Johnson, D.W., H.A. Simonin, J.R. Colquhoun, and F.M. Flack. 1987. In situ toxicity
tests of fishes in acid waters. Biogeochem. 3:181-208.
11-2
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Kanciruk, P., J.M. Eilers, R.A. McGord, D.H. Landers, D.F. Brakke, and R.A. Linthurst.
1986. Characteristics of lakes in the eastern United States - Vol. m: Data compendium
of site characteristics and chemical variables. EPA-600/4-86/007c, U.S. Environmental
Protection Agency, Washington, DC. 439 pages.
Kretser, W., J. Gallagher, and J. Nicolette. 1988. Adirondack Lakes Study 1984-1987:
An evaluation of fish communities and water chemistry, Adirondack Lakes Survey
Corporation, Ray Brook, NY.
Landers, D.H., W.S. Overton, R.A. Linthurst, and D.F. Brakke. 1988. Eastern Lake
Survey: Regional estimates of lake chemistry. Environ. Sci. Technol. 22:128-135,
LaZerte, B.D. 1984. Forms of aqueous aluminum in acidified catchments of central
Ontario: A methodological analysis. Can. J. Fish. Aquat. Sci. 41:766-776.
Linthurst, R.A., D.H. Landers, J.M. Eilers, D.F. Brakke, W.S. Overton, E.P. Meier, and
R.E. Crowe. 1986. Characteristics of lakes in the eastern United States - Vol. Is
Population descriptions and physicochemical relationships. EPA-600/4-86/007a. U.S.
Environmental Protection Agency, Washington, DC. 136 pages,
Magnuson, J.J. 1976. Managing with exotics - a game of chance. Trans. Am. Fish. Soc.
105:1-9.
Merna, J.W., J.C. Schneider, G.R. Alexander, W.D. Alward, and R.L. Eshenroder. 1981.
Manual of Fisheries Survey Methods. Michigan Department of Natural Resources,
Fisheries Division. Lansing, MI.
Mills, K.H., and D.W. Schindler. 1986. Biological indicators of lake acidification.
Water, Air, Soil Pollut. 30:779-789.
Mills, K.H., S.M. Chalunchuck, L.C. Mohr, and I.J.. Davies. 1987. Responses of fish
populations in Lake 223 to eight years of experimental acidification. Can. J. Fish.
Aquat. Sci. 44:114-125.
Myers, R.H. 1986. Classical and Modern Regression with Applications. Duxbury Press,
Boston.
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Nicholls, K.H., and P.J. Dillon. 1978. An evaluation of phosphorus-chlorophyll-
phytoplankton relationships for lakes. Int. Rev. Ges. Hydrobiol. 63;:141-154.
Omernik, J.M. 1985. Total alkalinity of surface waters: A map of the Appalachian
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Omernik, J.M., and G.E. Griffith. 1985. Total alkalinity of surface waters: A map of
the Upper Midwest Region. EPA-600/D-85-043, U.S. Environmental Protection Agency,
Corvallis, OR.
11-3
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New England and New York Region. EPA-600/D-84-2 1 6, U.S. Environmental Protection
Agency, Corvalhs, OR.
Omernik, J.M., and C.F. Powers. 1983. Total alkalinity of surface waters - a national
map. Annals of the Assoc. Am. Geographers 73:133-136.
Overton, W.S. 1987. Phase II Analysis Plan, National Lake Survey-Working Draft,
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Agency, Washington, DC. 374 pages.
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the toxicity of acidic waters to brook trout. Ph.D. Dissertation, University of Wyoming,
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11-4
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U.S. Environmental Protection Agency. Fish mercury content in Subregion 2B, Upper
Peninsula of Michigan. Corvallis, OR. In Prep.
Wiener, J.G. 1983. Comparative analyses of fish populations in naturally acidic and
circumneutral lakes in northern Wisconsin. (FWS/BS-80/40.16) U.S. Fish Wildl. Serv.
Rep., Kearneysville, WV.
Wiener, J.G., and J.M. Eilers. 1987. Chemical and biological status of lakes and
streams in the Upper Midwest: Assessment of acidic deposition effects. J. Lake Reserv.
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Wright, R., N., Conroy, W. Dickson, R-. Harriman, A. Henriksen, and C. Schofield. 1980.
Acidified lake districts of the world: A comparison of water chemistry of lakes in
southern Norway, southern Sweden, southwestern Scotland, the Adirondack Mountains of
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Precipitation, D. Drablos and A. Tollan, eds. SNSF project, Olso, Norway.
11-5
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APPENDIX A
Quality Assurance and
Quality Control Protocols for
Measurement of Water Chemistry
-------
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APPENDIX A
A.1 INTRODUCTION
Basic information on quality assurance (QA) and quality control (QC) methods and
results for Phase H of the Eastern Lake Survey (ELS-n) in the Upper Peninsula of
Michigan were provided in Section 4 of Volume I of the project report. Further details
on QA/QC procedures and protocols specifically for ELS-n measurements of water
chemistry are described in the following sections: QA system audits (Section A.2), field
measurements and sampling (Section A.3), laboratory measurements (Section A.4), and
the overall QA procedures (Section A.5).
A.2 QUALITY ASSURANCE SYSTEM AUDITS
A system audit is a qualitative on-site evaluation of the field station and field
operations, the sample processing laboratory, and the analytical laboratory. Facilities,
equipment, and operations (e.g., record keeping, data reporting, and QC procedures)
were reviewed during the system audits for this study of Fish Communities in Lakes in
Subregion 2B (Upper Peninsula of Michigan) in Relation to Lake Acidity.
A.2.1 Field Operations On-Site Evaluation
During the course of field sampling, supervisory personnel from Michigan State
University (W. Taylor, M. Fabrizio, and D. Hayes) performed four audits of field
operations. In addition, periodic checks were made of completed data sheets for
completeness and accuracy of data entry.
A.2.2 Laboratory On-Site Evaluation
An authorized representative of the U.S. Environmental Protection Agency (EPA)
QA Manager conducted an in-depth evaluation of the analytical laboratory and the
processing laboratory 19 June 1987. QA sample (audit, duplicate, and blank) data and
QC data were reviewed, and methods for processing and analysis were observed. The
auditor summarized all observations in the QA logbook for the project,. All problems
encountered were brought to the attention of the responsible laboratory manager for
corrective action after the evaluation was completed.
A.3 FIELD MEASUREMENTS AND SAMPLING
In situ measurements consisted of four Hydrolab measurements (water
temperature, DO, pH, and conductance), Secchi transparency, air temperature, and site
depth, taken at the Eastern Lake Survey - Phase I (ELS-I) fall index site.
A-l
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The Hydrolab was calibrated each morning prior to sampling. Calibrations for pH
and conductivity were made with standards of low ionic strength applicable over a range
of temperatures and barometric pressures; settings were checked using quality control
check (QCC) solutions. The detailed calibration procedure is described in Hydrolab
(1985) and in Hagley et al. (1987). Conductivity was standardized with a 0.001 NKC1
solution (specific conductance = 147 uS/cm at 25 °C). National Bureau of Standards
(NBS) traceable buffers (pH = 4.00 and pH = 7.00 at 25 °C) were used to standardize the
pH electrode. Dissolved oxygen measurements were calibrated with water-saturated
air.
Following acceptable calibration, the Hydrolab pH and conductivity calibrations
were tested with the QCC solution. A table of theoretical values for various
temperatures and barometric pressures was used to determine the accuracy of the
calibrations (Hagley et al. 1987). If measurements of the QCC solution differed from
theoretical values by more than 0.15 pH units or by more than 15 uS/cm, then the
Hydrolab was recalibrated. If the recalibration failed, maintenance procedures were
performed according to manufacturer recommendations. The Hydrolab temperature
probe was also checked; the temperature reading of the QCC solution was required to be
within + 1 °C of the QCC solution temperature measured by an NBS-traceable
thermometer.
A field QCC was performed on the Hydrolab after arrival at the lake. Sulfuric
acid (0.0001 N, pH 4.03 at 25 °C) and KC1 (0.001 N, 147 pS/cm at 25 °C) solutions were
used for pH and conductivity checks, respectively.
Each afternoon, when sampling personnel returned to the base site, a QCC of each
Hydrolab was performed using the QCC solution; daily maintenance was also completed.
These procedures are described in detail in Hagley et al. (1987).
Secchi transparency was measured on the shaded side of the boat. The descending
and the ascending Secchi depth readings were recorded. There are no QC checks for
this measurement.
A-2
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Air temperature was measured in the shade with a hand-held thermometer. There
are no QC checks for this measurement.
Site depth was measured with an electronic depth (Ray Jefferson) recorder. The
depth recorder was checked each day against a calibrated sounding line.
A.4 LABORATORY MEASUREMENTS
Sample analyses (including analyses for assessment of mercury bioaccumulation
were performed by four laboratories (Table A.I) The methods for analysis, the
Table A.I. Laboratories Analyzing Water Chemistry Samples
for the ELS-n in Subregion 2B
Laboratory
Las Vegas Processing
Laboratory
EMSL-Las Vegas
Battelle Northwest
Cornell University
Sample Type
Water
Water
Water
Sediment
Fish
Analysis
PH
Total reactive aluminum
Nonlabile (organic)reactive aluminum
Dissolved organic carbon
Total dissolved fluoride
Dissolved mercury
Total mercury
Total mercury
Particle size
Organic carbon
Total mercury
Total organic: mercury
required detection limits and QA objectives were listed in Table 4.2 (Volume I). All
analyses for each parameter were performed within the specified maximum allowable
sample holding times [3 days for measurements of pH and aluminum (Al), 14 days for
dissolved organic carbon (DOC), and 28 days for total dissolved fluoride (F)]. Table A.2
summarizes QC protocols for the processing laboratory in Las Vegas and the analytical
laboratory at the EPA Environmental Monitoring Systems Laboratory (EMSL)-Las Vegas.
A-3
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Table A.2. Summary of Quality Control Procedures for Water Chemistry
Measurements for ELS-n in Subregion 2B
Parameters
pH
Total dissolved F
DOC
Total monomeric
Al
Nonlabile
monomeric Al
QC Check
1. Electrode
calibration
Nernstian
response
(check)
2. pHQCCS4
analyses
3. Duplicate
analysis
1. QCCS
analysis
(calibration
and
verification)
2. Detection
limit
determination
(biweekly)
3. Detection
limit QCCS
analysis
4. Calibration
and reagent
blank
analyses
5. Duplicate
analysis
Control Limits
1. Slope=1.00
±0.05
2. ±0.05 pH unit
3. ±0.05 pHunit
1. The lesser of
the 99%
confidence
interval or
value given in
Table A.3.
2. Required
detection
limits (RDL)
given in Table
1.2 (Vol. I).
3. ±20%
4. Blank value
<2 x RDL.
5. Duplicate
precision (%
relative
standard
deviation)
limits given
in Table 4.2
(Vol I).
Corrective Actionb
1. Recalibrate or replace
electrode
2. Recalibrate
3. Refine analytical
technique; analyze
another duplicate
1. Prepare new standards
and recalibrate;
reanalyze associated
samples
2. Refine instrumentation
and technique
3. Refine instrumentation
and technique
4. Determine and eliminate
contamination source;
prepare fresh blank
solution; reanalyze
affected samples
5. Investigate and
eliminate source of
imprecision; analyze
another duplicate
a F and Al measured in mg/L.
b To be followed when QC check is outside of control limits.
The following documents and information were kept current and available to the
analyst, supervisor, and QA representatives involved in the project:
Standard operating procedures (SOP) - detailed instructions about the
laboratory and the instrument operations.
A-4
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Laboratory QA plan - clearly defined laboratory protocols, including personnel
responsibilities and use of QC protocols.
Instrument performance study information - information on baseline noise,
calibration standard response, precision as a function of concentration, and
detection limits; used by the analyst and the supervisor to evaluate daily
instrument performance.
QG charts - the most recent QC charts with 99% warning limits and 95%
control limits for all QCC samples and detection limit QCC samples, generated
and updated for each batch of samples. The same QCC samples were used for
all QC charts to ensure continuity. These QC charts were prepared specifically
to ensure that the analysis remained in control. The actual control limits did
not exceed the values given in Table A.3.
Data sheet QC report - the laboratory manager's report reviewing the QC
results for each parameter and flagging all results outside the statistically
established QC limits for reanalysis before submitting the data to the Lockheed
QA personnel.
Table A.3. Maximum Allowable Control Limits for Chemical Measurements for the
ELS-II in Subregion 2B
Parameter
pH (pH units)
DOC (mg/L)
F, total dissolved (mg/L)
Al, total monomeric (mg/L)
Al, nonlabile monomeric (mg/L)
Detection Limit
±0.05
±10%
±5%
±10%
±10%
QCCS
N/A
±20%
±20%
±20%
±20%
An initial calibration was performed as required for each analytical method.
Next, the linear dynamic range (LDR) was determined for the initial calibration. The
concentrations of the calibration standards bracketed the expected sample
concentrations. The low standard was <10 times the detection limit. If the
concentration of a sample was above the LDR during the analysis, two options were
considered: (1) dilute (maintaining a matrix similar to the sample matrix with respect
to all preservatives) and reanalyze the sample or (2) calibrate a second concentration
range, requiring analysis of a separate QC sample for each concentration range.
Immediately after standardization of the instrument, a QCC sample containing the
analyte of interest at a concentration in the mid-calibration range was analyzed. The
A-5
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QCC samples were obtained commercially or prepared by the analyst from a source
independent of the calibration standards.
The calibration QC sample was analyzed to verify the calibration curve prior to
any sample analysis and after the last sample. The observed value for the QC sample
must not differ from the theoretical value by more than the limits given in Table A. 3.
When an unacceptable value for the calibration QC sample was obtained, the instrument
was recalibrated and all samples analyzed since the last acceptable QC calibrations
were reanalyzed.
Detection limit QCC samples were dilute (low-level) QC samples containing the
analyte of interest at a concentration of two to three times the required detection
limit. These QC samples were analyzed once per batch for total dissolved F, DOC, total
monomeric Al, and nonlabile monomeric Al. The results were reported on the analytical
data forms. The purpose of the detection limit QCC sample is to eliminate the
necessity of formally determining the detection limit on a daily basis. The measured
value of the analyte was required to be within 20% of the theoretical concentration to
be considered acceptable. If it was not, the problem was identified and corrected, and
an acceptable result or explanation was obtained prior to sample analysis.
A calibration blank was analyzed once per batch, immediately after the initial
calibration, to check for baseline drift. The instrument was rezeroed if necessary. The
calibration blank was defined as a "0" mg/L standard and contained only the matrix of
the calibration standards. The observed concentration of the calibration blank was
expected to be s 2 X the required detection limit. If it was not, the instrument was
rezeroed and the calibration rechecked.
A reagent blank was prepared and analyzed for each batch of samples for total
monomeric Al, nonlabile monomeric Al, and F analyses. A reagent blank is defined as a
deionized water sample plus all of the reagents (in the same quantities) used in
preparing a routine sample for analysis. The reagent blank was carried through the
same digestion/extraction procedure as a routine sample. The concentration of the
reagent blank must be £ 2 X the required detection limit. If the concentration
exceeded this limit, the source of contamination was investigated and corrective action
implemented. A new reagent blank was then prepared and analyzed for any sample in
which the high reagent blank value contributed significantly (>10%) to the value of the
parameter in question. Reagent blank results were reported on the analytical data form
but were not subtracted from sample results.
A-6
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One sample per batch was prepared and analyzed in duplicate for each parameter
to provide an estimate of analytical within-batch precision. The percent relative
standard deviation (%RSD) between duplicate measurements was calculated as follows:
%RSD= .,= *100
X
s =
n-l
where: s is the standard deviation of the pair of measurements,
X is a datum (either the routine or the duplicate measurement),
X is the mean of the pair of measurements, and
n is the population size (2).
The %RSD of each duplicate pair was then plotted on a QC chart and the 99% and
95% confidence intervals established. Initial control limits were set at the precision
levels given in Table 4.2 (Vol. I). If the precision of the laboratory duplicate values fell
outside the control limits, a second, different sample was analyzed in duplicate. No
further samples were analyzed until duplicate sample results were within the control
limits.
After the last sample, a QC sample was analyzed to verify the calibration curve.
If the measured value of the QC sample differed from the theoretical value by more
than the limits given in Table A.2, the instrument was recalibrated and the affected
samples reanalyzed.
Instrumental detection limits (DDLs) were determined and reported biweekly for
each parameter except pH. For this study, the detection limit was defined as three
times the standard deviation of eight nonconsecutive replicate reagent or calibration
blank analyses for DOC and total dissolved F. For both Al analyses, detection limits
were calculated using three times the standard deviation for the low-level audit sample.
Calibration blanks were analyzed when a method did not require a reagent blank.
Detection limits did not exceed the limits listed in Table 4.2 (Volume-1).
A-7
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A.5 OVERALL QUALITY ASSURANCE PROCEDURES
Field and laboratory audit samples, as well as field blanks and field replicates,
were used as part of the QA activities for the ELS-n in Subregion 2B. The audit
samples, field blanks, and field replicates were shipped to the analytical laboratory from
the sample processing facility as though they were routine lake samples. Every attempt
was made to ensure that the analytical laboratory did not recognize the audit samples as
different from the routine lake samples. As a result, the audit samples were double
blind to the analytical laboratory. That is, the laboratory neither recognized them as
audit samples nor knew their compositions. -
The purpose of field natural audit samples is to identify problems affecting data
quality that may occur during sample processing, shipment, or analysis. When used in
conjunction with laboratory audit samples, the analysis of these samples provides data
that can be used to distinguish shipping and sample processing problems from analytical
problems. Natural field audit samples were used to assess the overall among-batch
precision during the ELS-n.
The purpose of laboratory synthetic audit samples is to identify problems affecting
data quality that may occur during the analytical process. These samples help verify
the accuracy of analytical procedures and ensure that the laboratory is maintaining the
capability to properly analyze the samples. The synthetic laboratory audit samples were
sent to the sample processing facility from a central laboratory. The audit samples
were labeled at the sample processing facility, included in a batch with routine lake
samples processed on the same day, and shipped to the analytical laboratory for
analysis. The composition of the synthetic laboratory audit samples was designed to
include each analyte at concentrations representative of the range in the survey lakes.
A field blank is a deionized water sample meeting specifications for ASTM Type 1
reagent water (ASTM 1984) that is carried to the lake and is processed through the Van
Dorn sampler as though it were a routine sample. Field blank data are used to provide
an overall estimate of the normal background contamination that might occur during
sample collection, processing, transportation, and analysis, and to identify and correct
any significant contamination problems as they occur.
A field replicate is an additional sample collected at the lake site by the same
team immediately after the routine sample is collected. Field replicate data were used
to estimate the overall within-batch (system) precision for the sampling, processing,
transportation, and analysis process on a given day. Sixteen field replicates (one routine
A-8
-------
sample and three replicates from each of four lakes) were collected. Lakes were
selected for replicate sampling to cover the concentration range expected for the ELS-n
lakes.
A.6 REFERENCES
American Society for Testing and Materials (ASTM). 1984. Annual Book of ASTM
Standards. Vol. 11.01 Standard Test Methods for Anions in Water by Ion
Chromatography. Philadelphia.
Hagley, C., G. Merritt, and B. Baldigo. 1987. National Surface Water Survey Phase H -
Upper Midwest Lake Survey, Field Training and Operations Manual - Part n, EPA
Field Activities. Environ. Res. Lab., U.S. Environ. Prot. Agency, Corvallis, Or.
Hydrolab Corporation. 1985. Operation and Maintenance Manual for Hydrolab
Surveyor. 2nd rev. Austin, TX.
A-9
-------
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APPENDIX B
Water Chemistry and Fish Catch Data
by Individual Lakes and Sampling Dates
-------
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APPENDIX B
The variables reported in this Appendix are measured as follows:
Variable
PH
Ext. Al
Total Al
Ca2+
Conductivity
DOC
F
Mg2+
Air Eq. pH
Total P
Secchi Depth
Color
Na*
SiO,
so
2-
Site Depth
Lake Area
Elevation
Watershed Area
Unit
pH units
/zeq/L
mg/L
pH units
Mg/L
m
PCU
/ieq/L
mg/L
m
ha
m
ha
B-l
-------
NAME: DEEP LAKE
LONGITUDE: 91-14'30"W
ID: 2B1-016
LATITUDE: 46-29'37"N STATE: WI
ELS-I CHEMISTRY
SAMPLE DATE: 06NOV84
pH: 5.85 Ext. Al: 120.0 Tot. Al: 292.0 Ca: 97,30
Conductivity: 21.10 DOC: 11.30 F: 0.895 Mg: 59.23
Air Eq pH: 6.97 TP: 35.00 Secchi Depth: 0.95
Color: 99.00 Na: 22.18 Silica: 2.10 Sulfate: 54.13
Site Depth: 7.00 Lake Area: 4.2 Elevation: 361.2
Lake Type: DRAINAGE Watershed Area: 83.0
ELS-II CHEMISTRY
SAMPLE DATE: 24JUN87
pH: 6.24 Inorganic Al: 0.02 Minimum DO: 0.06
DOC: 9.30 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO: 0.68
ELS-II FISH CATCH SUMMARY*-- SAMPLE.DATE: 25JUN87
SAMPLING EFFORT:
NET TYPE
Gill Nets
Trap Nets
Seines
Angling
UNITS OF GEAR TOTAL HOURS FISHED
3
3
4
65.5
66.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Largemouth Bass
Bluegill
0
2
TRAP NET SEINE
0
4
0
0
ANGLING
5
12
SPECIES
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
12095
12096
12097
12099
912055
912056
912057
912058
912059
912060
912061
912062
912063
912064
217
234
307
220
153
183
171
203
166
140
132
180
137
165
132
169
380
127
61
113
85
167
91
45
40
100
49
83
B-2
-------
NAME: TWIN LAKES (EASTERN) ID: 2B1-022
LONGITUDE: 91-03'30"W LATITUDE: 46-41'06"N STATE: WI
ELS-I CHEMISTRY
SAMPLE DATE: 01NOV84
pH: 5.90 Ext. Al: 4.00 Tot. Al: 21.00 Ca: 41.17
Conductivity: 13.00 DOC: 3.35 F: 0.737 Mg: 32.08
Air Eq pH: 6.36 TP: 14.50 Secchi Depth:: 3.30
Color: 17.50 Na: 11.96 Silica: 0.02 Sulfate: 69.64
Site Depth: 3.30 Lake Area: 8.6 Elevation: 336.2
Lake Type: SEEPAGE ., Watershed Area: 197., 0
ELS-II CHEMISTRY
SAMPLE DATE:: 24JUN87
pH: 5.77 Inorganic Al: 0.01 Minimum DO:
DOC: 3.90 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 0.00
7.06
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 25JUN87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
66,7
69.7
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Largemouth Bass
Bluegill
Northern Pike
Sunfish Hybrid
3
1
3
2
TRAP NET SEINE
0
19
0
0
0
0
0
0
ANGLING
0
0
0
0
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 01SEP87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
GILL NETS
TRAP NETS
SEINES
ANGLING
3
3
4
TOTAL HOURS FISHED
57.2
57.5
2.0
B-3
-------
NAME: TWIN LAKES (EASTERN)
LONGITUDE: 91-03'30"W LATITUDE:
ID: 2B1-022
46-41'06"N STATE: WI
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
TRAP NET SEINE
Largemouth Bass
Bluegill
1
3
0
56
0
14
ANGLING
1
0
SPECIES
Northern Pike
Northern Pike
Northern Pike
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
264
265
266
267
268
269
12917
12918
850
620
634
211
207
220
255
240
4300
1515
1650
120
113
129
203
183
B-4
-------
NAME: LAKE NITA
LONGITUDE: 86-03 '51"W
ID: 2B1-035
LATITUDE: 46-33700"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 20OCT84
pH: 4.96 Ext. Al: 18.00 Tot. Al: 49.00 Ca: 21.96
Conductivity: 9.00 DOC: 4.70 F: 0.737 Mg: 13.16
Air Eg pH: 5.04 TP: 17.00 Secchi Depth: 1.50
Color: 80.00 Na: 6.52 Silica: 0.61 Sulfate: 16.86
Site Depth: 2.40 Lake Area: 4.3 Elevation: 281.9
Lake Type: SEEPAGE Watershed Area: 119.0
ELS-II CHEMISTRY
SAMPLE DATE: 05AUG87
pH: 4.84 Inorganic Al: 0.01 Minimum DO: 6.40
DOC: 7.80 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 0.00
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 06AUG87
SAMPLING EFFORT:
NET TYPE
Gill Nets
Trap Nets
Seines
Angling
UNITS OF GEAR TOTAL HOURS FISHED
3
3
4
66.5
72,0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET TRAP NET SEINE
Yellow Perch
162
245
ANGLING
0
SPECIES
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
12629
12630
12631
12632
12633
12634
12635
12636
12637
12638
12639
12640
12641
12642
12643
231
146
152
149
152
145
151
185
166
146
156
165
138
183
201
134
38
43
39
47
37
42
81
61
38
47
61
35
70
124
B-5
-------
NAME:
LONGITUDE:
LAKE NITA
86-03'51"W
ID: 2B1-035
LATITUDE: 46-33'00"N STATE: MI
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
12644
12645
12646
12647
12648
12649
12650
12651
12652
12653
12654
12655
12656
12657
12658
12659.
12660
12661
12662
12663
12664
12665
12666
12667
12668
12669
12670
191
139
287
296
240
230
242
229
230
194
141
140
191
195
142
140
142
144
144
143
146
142
144
140
142
135
126
108
37
380
460
200
180
220
160
160
93
35
36
88
97
36
35
41
38
38
36
40
36
38
32
34
29
24
B-6
-------
NAME: (NO NAME) ' -; ID: 2B1-038
LONGITUDE: 86-09/10"W LATITUDE: 46-30'42"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 20OCT84
pH: 4.56 Ext. Al: 18.00 Tot. Al: 5.00 Ca: 25.95
Conductivity: 17.40 DOC: 3.80 F: 0.579 Mg: 16.45
Air Eq pH: 4.56 TP: 12.00 Secchi Depth: 2.30
Color: 15.00 Na: 4.35 Silica: 0.06 Sulfate: 66.83
Site Depth: 1.80 Lake Area: 6.3 Elevation: 272.8
Lake Type: SEEPAGE Watershed Area: 57.0
ELS-II CHEMISTRY
SAMPLE DATE: 20AUG87
pH: 4.51 Inorganic Al: 0.02 Minimum DO: 8.61
DOC: 2.00 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 0.00
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 21AUG87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
63.0
65.7
2.0
NUMBER OF FISH CAUGHT:
NO FISH CAUGHT
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 11SEP87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
GILL NETS
TRAP NETS
SEINES
ANGLING
3
3
4
TOTAL HOURS FISHED
57.0
58.0
2.0
NUMBER OF FISH CAUGHT:
NO FISH CAUGHT
B-7
-------
NAME: WEST BRANCH LAKES (SW) ID: 2B1-039
LONGITUDE: 86-06'18"W LATITUDE: 46-30'38"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 20OCT84
pH: 4.98 Ext. Al: 55.00 ;Tot. Al: 108.0 Ca: 37.42
Conductivity: 15.70 DOC: 3.50 F: 0.842 Mg: 21.39
Air Eq pH: 4.93 TP: 13.00 Secchi Depth: 2.40
Color: 20.00 Na: 11.31 Silica: 0.21 Sulfate: 76.41
Site Depth: 2.40 Lake Area: 15.7 Elevation: 266.7
Lake Type: DRAINAGE Watershed Area: 122.0
ELS-II CHEMISTRY
SAMPLE DATE: 18JUN87
pH: 4.92 Inorganic Al: 0*04 Minimum DO: 5.61
DOC: 2.40 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO: 0.00
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 19JUN87
SAMPLING EFFORT:
NET TYPE
Gill Nets
Trap Nets
Seines
Angling
UNITS OF GEAR TOTAL HOURS FISHED
3
3
4
71.0
72.0
1.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
TRAP NET SEINE
Yellow Perch
Brown Bullhead
245
6
72
55
0
0
ANGLING
2
0
SPECIES
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
12001
12002
12005
12007
12009
12011
12013
12015
12016
12020
12021
12022
12023
12024
117
158
116
132
137
115
135
120
112
117
118
116
312
335
16
43
16
19
23
16
22
14
14
14
15
13
409
434
B-8
-------
NAME: WEST BRANCH LAKES (SW) ID: 2B1-039
LONGITUDE: 86-06'18"W LATITUDE: 46-30'38"N STATE: MI
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
12025
12026
12027
12028
12029
12032
12033
12038
12049
12050
12051
12053
12055
12056
12057
292
278
275
241
203
144
134
118
135
137
136
132
120
180
182
331
216
249
151
98
29
18
15
20
21
22
19
14
62
53
B-9
-------
NAME: WEST BRANCH LAKES (SE) ID: 2B1-040
LONGITUDE: 86-05'46"W LATITUDE: 46-30/44"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 20OCT84
pH: 4.74 Ext. Al: 56.00 Tot. Al: 98.00 Ca: 36.43
Conductivity: 16.90 DOC: 5.60 F: 0.737 Mg: 18.92
Air Eq pH: 4.77 TP: 19.00 Secchi Depth: 2.05
Color: 50.00 Na: 7.39 Silica: 0.53 Sulfate: 64.13
Site Depth: 5.50 Lake Area: 4.5 Elevation: 269.8
Lake Type: DRAINAGE Watershed Area: 21.0
ELS-II CHEMISTRY
SAMPLE DATE: 18JUN87
pH: 4.80 Inorganic Al: 0.02 Minimum DO: 7.34
DOC: 3.20 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO: 0.00
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 19JUN87
SAMPLING EFFORT:
NET TYPE
Gill Nets
Trap Nets
Seines
Angling
UNITS OF GEAR TOTAL HOURS FISHED
3
3
4
63.7
70.2
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Yellow Perch
Brown Bullhead
84
2
TRAP NET SEINE
33
19
0
0
ANGLING
0
0
SPECIES
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
211
212
213
214
215
216
217
218
219
220
221
222
223
224
115
112
116
114
348
162
108
117
106
112
88
85
113
141
12
13
13
13
470
37
10
18
12
14
6
6
13
24
B-10
-------
NAME: WEST BRANCH LAKES (SE) ID: 2B1-040
LONGITUDE: 86-05'46"W LATITUDE: 46-30'44"N STATE: MI
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
228
166
146
147
130
109
118
112
98
111
97
154
114
108
107
111
109
110
165
111
111
144
141
142
166
93
94
91
99
90
155
115
120
115
92
137
119
117
92
173
37
29
32
21
11
14
13
9
14
9
37
16
12
13
14
12
12
46
14
13
30
27
25
33
8
8
8
10
7
27
13
16
13
8
25
14
12
8
B-ll
-------
NAME: TRIANGLE LAKE ID: 2B1-041
LONGITUDE: 86-05'37"W LATITUDE: 46-31'48"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 23OCT84
pH: 5.13 Ext. Al: 28.00 Tot. Al: 34.00 Ca: 37.92
Conductivity: 15.10 DOC: 4.10 F: 0.790 Mg: 26.32
Air Eg pH: 5.12 TP: 22.00 Secchi Depth: 4.40
Color: 25.00 Na: 11.31 Silica: 0.00 Sulfate: 82.65
Site Depth: 7.00 Lake Area: 19.7 Elevation: 275.5
Lake Type: SEEPAGE Watershed Area: 60.0
ELS-II CHEMISTRY
SAMPLE DATE: 10AUG87
pH: 4.80 Inorganic Al: 0.02 Minimum DO: 1.18
DOC: 2.40 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO: 0.21
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 11AUG87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
4
4
5
TOTAL HOURS FISHED
77.0
86.5
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Yellow Perch
Largemouth Bass
Bluegill
Pumkinseed
Brown Bullhead
Golden Shiner
46
3
0
17
8
11
TRAP NET SEINE
70
0
0
46
7
10
0
0
10
0
0
0
ANGLING
0
0
0
0
0
0
SPECIES
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
735
736
737
738
739
740
741
742
743
744
118
257
180
166
110
135
130
119
130
135
14
174
54
41
11
21
18
13
18
21
B-12
-------
NAME: TRIANGLE LAKE ID: 2B1-041
LONGITUDE: 86-05'37"W LATITUDE: 46-31'48"N STATE: MI
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Largemouth Bass
Largemouth Bass
Largemouth Bass
745
746
747
748
749
750
751
752
753
754
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
110
120
135
110
119
118
107
120
118
135
118
118
111
111
111
110
131
133
118
110
130
105
110
111
131
111
120
118
103
132
168
105
200
186
178
11
14
19
12
13
13
11
14
12
19
13
15
13
13
11
13
19
20
14
11
18
10
12
JL3
18
11
15
14
9
19
41
10
107
84
71
B-13
-------
NAME: LONG LAKE ID: 2B1-042
LONGITUDE: 86-05'17"W LATITUDE: 46-30/08"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 20OCT84
pH: 5.01 Ext. Al: 21.00 Tot. Al: 37.00 Ca: 35.43
Conductivity: 11.50 DOC: 6.20 F: 0.684 Mg: 15.63
Air Eq pH: 5.07 TP: 18.00 Secchi Depth: 1.95
Color: 35.00 Na: 5.65 Silica: 0.59 Sulfate: 50.18
Site Depth: 4.30 Lake Area: 8.3 Elevation: 262.1
Lake Type: DRAINAGE Watershed Area: 36.0
ELS-II CHEMISTRY
SAMPLE DATE: 05AUG87
pH: 4.99 Inorganic Al: 0.01 Minimum DO: 7.51
DOC: 3.30 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 0.00
ELS-II FISH CATCH SUMMARY -- SAMPLE DATE: 06AUG87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
64.0
67.5
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET TRAP NET SEINE ANGLING
Brook Stickleback 0 l 60
B-14
-------
NAME: JOHNSON LAKE / ID: 2B1-047
LONGITUDE: 85-02 '38"W LATITUDE: 46-25'30"N STATE; MI
ELS-I CHEMISTRY
SAMPLE DATE:; 22OCT84
pH: 4.55 Ext..Al.: 45,00 Tot. Al: 61.00 Ca: 57.39
Conductivity: 27.90 DOC: 0.50 F: 0.684 Mg: 30.44
Air Eq pH: 4.58 TP: 2..000 Secchi Depth: 3.40
Color: 5.00 Na: 6.09. Silica: 0.00 Sulfate: 133.0
Site Depth: 3.40 Lake Area: 16.7 Elevation: ,2-52.1
Lake Type: SEEPAGE , Watershed Area: 137.0
ELS-II CHEMISTRY
SAMPLE DATE: 13AUG87
pH: 4.76 Inorganic Al: 0.01 Minimum DO:
DOC: 0.90 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 0.00
7.91
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 14AUG87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
55.5
60.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES. . GILL NET
TRAP NET SEINE
Yellow Perch
Bluegill
167
1
579
1
0
0
ANGLING
0
0
SPECIES
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
824
826
827
830
831
833
837
838
839
840
841
842
843
844
94
94
94
94
84
94
85
124
122
125
123
123
120
123
7
7
7
8
5
8
5
19
18
18
17
17
18
18
B-15
-------
NAME: JOHNSON LAKE , ID: 2B1-047
LONGITUDE: 85-02'38"W LATITUDE: 46-25/30"N STATE: MI
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
124
123
120
203
204
83
80
82
200
175
208
263
177
174
172
224
170
241
170
177
171
246
175
176
177
19
18
17
98
91
6
5
5
82
57
94
224
58
53
50
129
52
174
54
61
49
181
56
57
52
B-16
-------
NAME: MCNEARNEY LAKE ID: 2B1~°jl MT
LONGITUDE: 34-57'3o«w IATITUDE: 46-25'35»N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 22OCT84
pH: 4.43 Ext. Al: 213.0 Tot. Al: 287.0 Car 58V38
Conductivity: 32.60 DOC: 0.20 F: 0790 Mg: 19.74
Air Eq.pH: 4.51 TP: 0.000 Secchi Depth: 7-60
Colorf 10.00 Na: 7.83 Silica: 0.00 Sulfate: 143.9
Site Depth: 7.60 Lake Area: 49.8 Elevation: 264.3
Lake Type: SEEPAGE Watershed Area: 199.0
ELS-II CHEMISTRY
SAMPLE DATE: 12AUG87
pH: 4.42 Inorganic Al: 0.19 Minimum DO:
DOC: 0.32 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 0.00
8.33
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 13AUG87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
6
6
6
TOTAL HOURS FISHED
127.0
1.15.0
2.0
NUMBER OF FISH CAUGHT:
NO FISH CAUGHT
B-17
-------
NAME: PECK AND RYE LAKE ID: 2B1-052
LONGITUDE: 84-58/00"W LATITUDE: 46-23'50"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 22OCT84
pH: 4.95 Ext. Al: 6.00 Tot. Al: 23.00 Ca: 31.94
Conductivity: 14.90 DOC: 4.00 F: 1.000 Mg: 18.92
Air Eq pH: 4.99 TP: 7.000 Secchi Depth: 2.00
Color: 25.00 Na: 3.48 Silica: 0.00 Sulfate: 61.83
Site Depth: 1.80 Lake Area: 4.5 Elevation: 275.8
Lake Type: SEEPAGE Watershed Area: 39.0
ELS-II CHEMISTRY
SAMPLE DATE: 12AUG87
pH: 4.67 Inorganic Al: 0.01 Minimum DO: 5.22
DOC: 3.50 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 0.00
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 13AUG87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
66.5
69.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET TRAP NET SEINE
Yellow Perch
425
657
ANGLING
0
SPECIES
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
188
171
149
172
185
173
150
150
116
151
129
130
151
150
122
56
40
31
42
57
58
33
35
17
31
24
25
33
31
22
B-18
-------
NAME:
LONGITUDE:
PECK AND RYE LAKE ID:' 2B1-052
84-58'00"W LATITUDE: 46-23'50"N STATE: MI
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
131
130
176
150
130
129
121
131
130
176
122
130
130
118
150
123
123
123
149
119
122
150
122
123
123
180
196
25
26
47
30
23
22
21
25
25
53
22
24
25
19
34
24
20
21
34
21
22
33'
23
21
22
64
75
B-19
-------
NAME: GOPHER LAKE ID. 2B1-061
LONGITUDE: 86-03'30»W LATITUDE: 46-31'12"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 23OCT84
pH: 5.05 Ext. Al: 5.00 Tot. Al: 16.00 Ca: 29 94
Conductivity: 12.40 DOC: 1.60 F: 0.684 Mg-'l4 81
Air Eg pH: 5.11 TP: 11.00 Secchi Depth: 3.40 "
Color: 5.00 Na: 5.22 Silica: 0.17 Sulfate: 60.38
Site Depth: 9.80 Lake Area: 6.4 Elevation: 266.7
Lake Type: SEEPAGE Watershed Area: 4i.o
ELS-II CHEMISTRY
SAMPLE DATE: 24AUG87
pH: 4.93 Inorganic Al: -0.00 Minimum DO: 0.08
DOC: 2.90 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO: 0.29
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 25AUG87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
63.0
63.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Largemouth Bass 12
Central Mudminnow 8
Brook Trout 7
TRAP NET SEINE
1
1
0
0
0
0
ANGLING
0
0
0
SPECIES
Brook Trout
Brook Trout
Brook Trout
Brook Trout
Brook Trout
Brook Trout
Brook Trout
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
870
871
872
873
874
875
876
877
878
879
880
881
882
457
451
245
358
361
397
508
118
92
108
92
90
100
1400
1250
200
650
800
760
1775
21
11
17
10
11
13
B-20
-------
NAME: GOPHER LAKE ID: 2B1-061
LONGITUDE: 86-03'30"W LATITUDE: 46-31'12"N STATE: MI
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
883
884
885
886
887
888
889
95
96
100
117
116
90
90
12
13
13
23
23
10
10
B-21
-------
NAME: MALLARD LAKE ID: 2B1-064
LONGITUDE: 86-06/36"W LATITUDE: 46-33'51"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 20OCT84
pH: 5.06 Ext. Al: 7.00 Tot. Al: 36.00 Ca: 222.1
Conductivity: 12.40 DOC: 1.80 F: 0.579 Mg: 60.05
Air Eq pH: 5.11 TP: 10.00 ,Secchi Depth: 2.65
Color: 35.00 Na: 16.09 Silica: 0.32 Sulfate: 52.26
Site Depth: 3.00 Lake Area: 8.5 Elevation: 288.0
Lake Type: SEEPAGE Watershed Area: 39.0
ELS-II CHEMISTRY
SAMPLE DATE: 20AUG87
pH: 4.70 Inorganic Al: 0.01 Minimum DO: 7.87
DOC: 1.70 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: o.OO
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 21AUG87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
69,0
69.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET TRAP NET SEINE
Yellow Perch
84
228
ANGLING
0
SPECIES
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
12785
12786
12787
12788
12789
12790
12791
12792
12793
12794
12795
12796
12797
12798
12799
156
154
155
155
164
171
172
185
168
163
166
171
165
175
184
39
39
39
36
48
51
54
58
50
39
38
39
41
55
58
B-22
-------
NAME: MALLARD LAKE ID: 2B1-064
LONGITUDE: 86-06'36"W LATITUDE: 46-33'51"N STATE: MI
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
12800
12801
12802
12803
12804
12805
12806
12807
12808
12809
12810
12811
12812
12813
12814
12815
12816
12817
12818
12819
12820
12821
12822
12823
12824
12825
195
191
187
185
124
126
126
120
125
130
125
132
132
135
89
123
114
123
128
126
150
150
147
150
157
148
84
55
65
56
22
18
21
18
19
22
19
23
23
25
7
20
12
19
21
21
34
36
31
35
43
32
B-23
-------
NAME: LAMBERT LAKE ... ID: 2B1-066
LONGITUDE: 86-05/08"W LATITUDE: 46-30'33"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 20OCT84
pH: 4.65 Ext. Al: 71.00 Tot. Al: 103.0 Ca: 35.93
Conductivity: 19.40 DOC: 1^60 F: 0.842 Mg: 19.74
Air Eq pH: 4.66 TP: 15.00 Secchi Depth: 3.00
Color: 15.00 Na: 10.00 Silica: 0.18 Sulfate: 91.40
Site Depth: 3.00 Lake Area: ,14.7 Elevation: 266.1
Lake Type: SEEPAGE Watershed Area: 91.0
ELS-II CHEMISTRY
PSAMPLE DATE: 06AUG87
pH: 4.59 Inorganic Al: 0.06 Minimum DO: 7.91
DOC: 1.20 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 6.00
ELS-II FISH CATCH SUMMARY,-? SAMPLE DATE: 07AUG87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
55.5
63.0
2.0
NUMBER OF FISH CAUGHT: .
SPECIES GILL NET -. TRAP NET SEINE ANGLING
Brook Stickleback 0 1 30
B-24
-------
NAME: WRIGHT LAKE ID: 2B2-004
LONGITUDE: 91-28'45"W LATITUDE: 46-31/15"N STATE: WI
ELS-I CHEMISTRY
SAMPLE DATE: 05NOV8 4
pH: 6.14 Ext. Al: 22.00 Tot. Al: 52.00 Ca:-45.41
Conductivity: 8.80 DOC: 7.90 F: 0.737 Mg: 32.90
Air Eq pH: 6.80 TP: 14.00 Secchi Depth: 1.55
Color: 42.00 Na: 12.18 Silica: 0.18 Sulfate: 26.44
Site Depth: 3.60 Lake Area: 8.1 Elevation: 350.5
Lake Type: SEEPAGE --Watershed Area: 205.0
ELS-II CHEMISTRY
SAMPLE DATE: 22JUN87
pH: 6.44 Inorganic Al: 0.00 Minimum DO: 0.32
DOC: 7.70 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO: 0.24
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 23JUN87
SAMPLING EFFORT:
NET TYPE
Gill Nets
Trap Nets
Seines
Angling
UNITS OF GEAR TOTAL HOURS FISHED
3
3
4
54.0
49.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
White Sucker
Flathead Minnow
Common Shiner
TRAP NET SEINE
33
0
0
2
10
1013
0
0
0
ANGLING
0
0
0
SPECIES
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
White
White
White
White
White
White
White
White
White
White
White
White
White
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
12060
12061
12062
12063
12064
12065
12066
12067
12069
12070
12071
12072
12073
375
410
312
346
375
298
341
335
315
340
362
310
295
520
700
320
500
560
280
460
420
360
420
560
350
310
B-25
-------
NAME: WRIGHT LAKE ID: 2B2-004
LONGITUDE: 91-28/45"W LATITUDE: 46-31'15"N STATE: WI
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
12074
12075
12076
12077
12078
12079
12080
12081
12082
12083
12084
12085
12086
12087
12088
12089
12090
12091
12092
12093
12094
324
356
287
323
330
308
384
370
331
370
342
347
300
349
355
295
393
351
311
324
370
380
580
250
340
440
320
660
560
380
580
480
480
290
550
520
300
660
520
330
380
600
B-26
-------
NAME: TOIVOLA LAKES (WEST) ID: !2B2-007
LONGITUDE: 88-48'01"W LATITUDE: 46-59'14"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 18OCT84
pH: 5.43 Ext. Al: 3.00 Tot. Al: 20.00 Ca: 23.45
Conductivity: 8.30 DOC: 2.50 F: 0.579 Mg: 14.81
Air Eq pH: 5.65 TP: 0.000 Secchi Depth: .3.65
Color: 10.00 Na: 4.35 Silica: 0.08 Sulfate: 47.68
Site Depth: 10.40 Lake Area: 6.3 Elevation: 396.9
Lake Type: SEEPAGE Watershed Area: 44.0
ELS-II CHEMISTRY
SAMPLE DATE: 16JUL87
pH: 5.30 Inorganic Al: -0.00 Minimum DO: 0.77
DOC: 2.90 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO: 0.49
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 17JUL87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
65.0
68 . 5
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Yellow Perch
Largemouth Bass
Bluegill
Pumkinseed
53
1
0
0
TRAP NET SEINE
143
1
0
12
1
10
1
0
ANGLING
1
0
0
0
SPECIES
Ye~llow Perch
Largemouth Bass
Largemouth Bass
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
495
500
501
502
503
504
505
506
508
509
510
511
176
420
122
171
201
117
116
98
115
115
117
155
53
1320
18
52
73
15
15
9
15
15
14
38
B-27
-------
NAME:
LONGITUDE:
TOIVOLA LAKES (WEST) ID: 2B2-007
88-48'01"W LATITUDE: 46-59'14"N STATE: MI
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534 ,
537
538
540
543
544
545
546
547
548
549
117
115
119
126
126
150
115
125
136
127
135
119
143
139
125
102
128
126
153
125
127
128
100
95
100
98
146
149
141
146
158
161
160
15
15
16
18
18
35
14
18
26
20
22
15
31
26
20
10
18
20
36
20
20
20
10
8
10
10
29
36
33
35
42
43
41
B-Z8
-------
NAME: (NO NAME) ID: 2B2-024
LONGITUDE: 88-12'32"W LATITUDE: 46-38'05"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 14OCT84
pH: 5.75 Ext. Al: 41.00 Tot. Al: 108.0 Ca: 79.84
Conductivity: 18.00 DOC: 8.40 F: 1.053 Mg: 46.89
Air Eg pH: 6.38 TP: 1.000 Secchi Depth; 1.70
Color: 60.00 Na: 15.23 Silica: 1.77 Sulfate: 79.12
Site Depth: 5.80 Lake Area: 8.1 Elevation: 545.6
Lake Type: SEEPAGE Watershed Area: 44,0
ELS-II CHEMISTRY
SAMPLE DATE:: 08JUL87
pH: 5.93 Inorganic Al: 0.01 Minimum DO;; 0.97
DOC: 8.10 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO: 0.43
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 09JUL87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
60.0
63.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Iowa Darter
White Sucker
Creek Chub
Bluntnose Minnow
Finescale Dace
Golden Shiner
Sunfish Hybrid
0
13
0
1
0
0
0
TRAP NET SEINE
0
169
1
14
1
107
38
15
0
0
171
0
1
0
ANGLING
0
0
0
0
0
0
0
SPECIES
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
389
389
390
390
391
391
392
392
393
146
146
146
146
179
179
200
200
179
24
24
27
27
48
48
62
62
46
B-29
-------
NAME: (NO NAME) ID: 2B2-024
LONGITUDE: 88-12/32"W LATITUDE: 46-38'05"N STATE: MI
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
393
394
394
395
395
375
376
377
379
380
381
382
387
396
397
398
401
402
404
405
406
407
408
409
410
411
419
420
421
425
426
427
179
139
139
176
176
322
370
307
359
344
290
301
128
120
111
132
100
119
123
169
130
158
165
171
133
171
131
172
410
317
255
174
174
46
22
22
41
41
240
450
240
420
360
220
220
17
16
12
21
9
14
15
44
18
33
36
36
19
42
18
43
725
255
130
39
40
B-30
-------
NAME: OTTER LAKE
LONGITUDE: 85-39'32"W
ID: 2B2-038
LATITUDE: 46-35'45"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 24OCT84
pH: 6.81 Ext. Al: 3.00 Tot. Al: 12.00 Ca: 131.2
Conductivity: 23.20 DOC: 7.40 F: 1.158 Mg: 64.16
Air Eq pH: 7.45 TP: 13.00 Secchi Depth: 1.75
Color: 25.00 Na: 26.53 Silica: 0.85 Sulfate: 52.26
Site Depth: 3.70 Lake Area: 5.5 Elevation: 230.1
Lake Type: DRAINAGE Watershed Area: 117.0
ELS-II CHEMISTRY
SAMPLE DATE: 27AUG87
pH: 6.50 Inorganic Al: -0.00 Minimum DO:
DOC: 7.30 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 0.00
8.75
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 28AUG87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
58.5
57.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
TRAP NET SEINE
Yellow Perch
Iowa Darter
Bluegill
Pumkinseed
Brown Bullhead
Creek Chub
Pugnose Minnow
Golden Shiner
45
0
0
0
3
2
0
28
27
0
0
14
231
0
0
14
0
13
46
0
0
0
75
0
ANGLING
0
0
0
0
0
0
0
0
SPECIES
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
12871
12872
12873
12874
12875
12876
12877
12878
221
176
197
159
193
117
153
231
105
47
74
35
63
14
29
118
B-31
-------
NAME: OTTER LAKE
LONGITUDE: 85-39'32"W
ID: 2B2-038
LATITUDE: 46-35'45"N STATE: MI
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
12879
12880
12881
12882
12883
12884
12885
12886
12887
12888
12889
12890
12891
12892
12893
12894
12895
12896
12897
12898
12899
12900
12901
12902
12903
12904
12905
12906
12907
12908
12909
12910
12911
12912
12913
12914
219
134
165
164
166
190
217
233
150
153
123
126
125
127
127
125
154
123
124
126
262
127
105
179
180
160
191
182
134
142
142
107
109
115
117
109
111
21
40
43
38
70
98
122
31
28
19
23
20
21
21
21
34
18
19
20
205
19
12
57
56
44
72
66
25
29
25
13
14
16
18
13
B-32
-------
NAME: QUINLAN LAKE . ID: 2B2>-044
LONGITUDE: 85-46'31"W LATITUDE: 46-25'39"N STATE: MI
ELS'-I CHEMISTRY
SAMPLE DATE: 23OCT84
pH: 5.23 Ext. Al: 1.50 Tot. Al: 10.00 Ca: 25.20
Conductivity: 9.80 DOC: 3.80 F: 0.711 Mg: 15.63
Air Eq pH: 5.21 TP: 18.50 Secchi Depth:: 3.00
Color: 17.50 Na: 3.48 Silica: 0.34 Sulfate: 40.91
Site Depth: 8.80 Lake Area: 4.7 Elevation: 259.4
Lake Type: SEEPAGE Watershed Area: 39., 0
ELS-II CHEMISTRY
SAMPLE DATE: 24AUG87
pH: 5.06 Inorganic Al: -0.00 Minimum DO: 1.69
DOC: 3.00 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO: 0.29
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 25AUG87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
67.5
71.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Yellow Perch
Bluegill
Brown Bullhead
161
47
13
TRAP NET SEINE
18
5
16
0
0
0
ANGLING
0
0
0
SPECIES
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
12861
12826
12827
12828
12829
12830
12831
12832
12833
12834
12835
12836
12837
150
180
175
169
165
155
154
155
150
164
160
160
185
37
61
51
47
43
38
39
38
37
41
43
44
57
B-33
-------
NAME:
LONGITUDE:
QUINLAN LAKE ID: 2B2-044
85-46'31"W LATITUDE: 46-25'39"N STATE: MI
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
12838
12839
12840
12841 -"
12842
12843 '
12844
12845
12846
12847
12848
12849
12850
12851
12852 ' <
12853
12854
12855
12856
12857
12858
12859
12860
12862
12863
12864
12865
12866
12867
12868
12869
12870
912435
912436
912438
912439
912440 '
912441
912442
912443
912444
912445
155
155
155
150
155
146
162
160
165
162
160
'161
175
189
170
182
180
175
175
291
295
239
240
172
173
172
249
141
151
133
113
143
147
147
141
145
148
155
165
189
152
152
39
44
40
37
42
34
43
40
51
48
43
46
58
63
52
60
66
55
53
300
300
'^146
160
52
49
51
178
26
30
25
13
27
50
52 ;
45
48
49
59
, . 57
93
53
56
B-34
-------
NAME: CRANBERRY LAKE ID: 2B2-049
LONGITUDE: 86-ll'02"W; LATITUDE: 46-27'06"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 20OCT84
pH: 5.10 Ext. Al: 10.00 Tot. Al: 16.00 Ca: 33.43
Conductivity: 10.60 DOC: 5.90 F: 0.684 Mg: 18.10
Air Eq pH: 5.17 TP: 39.0.0 Secchi Depth: 1.20
Color: 25.00 Na: 4.35 Silica: 0.18 Sulfate: 46.22
Site Depth: 12.20 Lake Area: 5.0 Elevation: 257.6
Lake Type: SEEPAGE Watershed Area: 21.0
ELS-II CHEMISTRY
SAMPLE DATE: 30JUL87
pH: 4.96 Inorganic Al: 0.01 Minimum DO: 1.33
DOC: 4.00 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO; 0.73
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 30JUN87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
67.0
72.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET TRAP NET SEINE
Yellow Perch
701
91
ANGLING
1
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 09SEP87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
GILL NETS
TRAP NETS
SEINES
ANGLING
3
3
4
TOTAL HOURS FISHED
61.5
65.5
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET TRAP NET SEINE
Yellow Perch
291
247
0
ANGLING
0
B-35
-------
NAME:
LONGITUDE:
CRANBERRY LAKE ID: 2B2-049
86-ll'02"W LATITUDE: 46-27'06"N STATE: MI
SPECIES
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
12585
12586
12587
12588
12589
12590
12591.
12592
12593
12594
12595
12596
12597
12598
12599
12600
12601
12602
12603
12604
12605
12606
12607
12608
12609
12610
12611
12612
12613
12614
12615
12616
12617
12618
12619
12620
12621
12622
12623
12624
12625
12626
12627
12628
918
919
922
923
924
927
161
170
168
165
166
156
169
166
151
167
161
153
164
153
183
158
163
170
179
109
105
112
110
115
110
109
108
112
114
115
105
114
113
108
127
134
136
137
135
130
127
126
127
136
280
286
186
121
173
122
48
54
49
44
47
40
53
50
39
47
44
39
49
40
56
40
44
45
41
14
13
14
13
15
14
14
13
13
14
16
13
15
16
13
21
24
26
27
23
22
19
19
22
27
230
260
68
17
49
17
B-36
-------
NAME:
LONGITUDE:
CRANBERRY LAKE
86-11'02"W LATITUDE:
ID: 2B2-049
46-27'06"N STATE: MI
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
928
929
930
932
933
935
936
937
938
939
940
941
942
945
946
947
948
949
950
951
953
954
955
956
957
958
959
961
962
963
964
120
182
186
120
157
122
120
120
120
122
121
81
76
82
80
78
171
151
156
184
158
160
152
156
157
153
155
172
170
180
170
13
71
64
16
35
17
16
17
16
16
17
6
4
6
5
5
50
34
35
61
39
44
36
41
47
37
44
53
53
66
56
B-37
-------
NAME: (NO NAME) ID: 2B2-055
LONGITUDE: 86-11'30"W LATITUDE: 46-28'05"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 200CT84
pH: 4.55 Ext. Al: 53.00 Tot. Al: 107.0 Ca: 36.93
Conductivity: 16.10 DOC: 7.50 F: 0.737 Mg: 18.10
Air Eq pH: 4.57 TP: 22.00 Secchi Depth: 2.10
Color: 25.00 Na: 6.09 Silica: 0.46 Sulfate: 84.00
Site Depth: 2.10 Lake Area: 4.9 Elevation: 260.9
Lake Type: SEEPAGE Watershed Area: 18.0
ELS-II CHEMISTRY
SAMPLE DATE: 30JUL87
pH: 4.70 Inorganic Al: 0.04 Minimum DO: 7.50
DOC: 3.60 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 0.00
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 31JUL87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
51.0
56.5
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET TRAP NET SEINE
Central Mudminnow
25
ANGLING
0
B-38
-------
NAME: (NO NAME)
LONGITUDE: 88-08/30"W
ID: 2B2-061
LATITUDE: 46-35'38"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 14OCT84
pH: 5.53 Ext. Al: 49.00 Tot. Al: 142.0 Ca: 91.32
Conductivity: 20.70 DOC: 13.90 F: 1.316. Mg: 54.29
Air Eq pH: 5.76 TP: 18.00 Secchi Depth: 0.85
Color: 125.0 Na: 22.18 Silica: 3.74 Sulfate: 86.61
Site Depth: 2.70 Lake Area: 20.6 Elevation: 522.7
Lake Type: DRAINAGE Watershed Area: 210.0
ELS-II CHEMISTRY
SAMPLE DATE: 01JUL87
pH: 5.59 Inorganic Al: 0.02 Minimum DO: 7.61
DOC: 21.50 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 0.00
ELS-II FISH CATCH SUMMARY ' SAMPL'E DATE: 02JUL87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
4
4
5
TOTAL HOURS FISHED
93.0
95.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Yellow Perch
Largemouth Bass
Pumkinseed
White Sucker
Flathead Minnow
Golden Shiner
105
3
0
144
0
82
TRAP NET SEINE
165
0
1
85
0
101
0
77
0
0
18
12
ANGLING
0
0
0
0
0
0
SPECIES
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
White
White
White
White
White
White
White
White
White
White
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
12234
12236
12247
12254
12258
12261
12262
12263
12264
12267
388
297
240
196
282
196
170
178
170
174
220
250
138
77
243
75
48
62
51
74
B-39
-------
NAME: (NO NAME)
LONGITUDE: 88-08'30"W
ID: 2B2-061
LATITUDE: 46-35'38"N STATE: MI
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
Largemouth Bass
Largemouth Bass
Largemouth Bass
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
12269
12271
12274
12275
12276
12278
12280
12284
12285
12286
12294
12295
12297
12299
12302
12303
12304
12305
12306
12307
12309
12310
12311
12312
12313
12314
12315
12316
12317
12318
12319
12320
12321
12322
12323
12324
12325
12326
12327
12328
12329
12330
12331
12332
12333
12334
12335
12336
12337
12338
12339
12340
12341
12342
290
277
214
190
210
285
284
287
295
279
420
375
349
345
365
210
350
426
360
360
276
330
320
166
147
122
125
126
142
119
112
113
102
97
75
83
87
78
180
239
302
280
296
257
284
259
273
234
165
178
253
256
159
228
231
275
82
82
80
200
191
204
209
179
550
450
300
350
400
82
400
650
475
375
300
450
550
39
28
17
17
18
27
16
13
13
10
8
4
5
6
5
49
161
366
262
268
138
225
194
232
123
46
60
183
148
36
113
B-40
-------
NAME: (NO NAME)
LONGITUDE: 88-08'30"W
ID: 2B2-061
LATITUDE: 46-35'.'38 "N- STATE: MI
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
12343
12344
12345
12346
12349
12350
12351
92339
92340
170
237
201
234
222
220
174
195
285
46
126
71
120
103
99
50
70
262
B-41
-------
NAME: ROGER LAKE ID: 2B2-074
LONGITUDE: 91-25/24"W .LATITUDE: 46-31'34"N STATE: WI
ELS-I CHEMISTRY
SAMPLE DATE: 05NOV84
pH: 6.35 Ext. Al: 15.00 Tot. Al: 41.00 Ca: 58.88
Conductivity: 13.20 DOC: 6.00 F: 0.737 Mg: 41.13
Air Eg pH: 6.86 TP: 9.000 Secchi Depth: 2.05
Color: 35.00 Na: 24.36 Silica: 0.12 Sulfate: 32.48
Site Depth: 3.00 Lake Area: 11.0 Elevation: 344.4
Lake Type: SEEPAGE Watershed Area: 104.0
ELS-II CHEMISTRY
SAMPLE DATE: 22JUN87
pH: 6.43 Inorganic Al: 0.00 Minimum DO: 7.23
DOC: 7.20 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 0.00
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 24JUN87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
40.0
44.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Finescale Dace 0
Golden Shiner 20
Central Mudminnow 0
TRAP NET SEINE
671
2298
11
39
128
42
ANGLING
0
0
0
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 02SEP87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
GILL NETS
TRAP NETS
SEINES
ANGLING
3
3
4
TOTAL HOURS FISHED
60.0
56.5
2.0
B-42
-------
NAME: ROGER LAKE
LONGITUDE: 91-25'24"W
ID: 2B2-074
LATITUDE: 46-31'34"N STATE: WI
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Finescale Dace 0
Golden Shiner 58
Central Mudminnow 0
TRAP NET SEINE
238
240
170
4
1
3
ANGLING
0
0
0
B-43
-------
NAME: RICHARDSON LAKE ID: 2B2-075
LONGITUDE: 91-27'51"W LATITUDE: 46-32/22"N STATE: WI
ELS-I CHEMISTRY
SAMPLE DATE: 05NOV84
pH: 5.91 Ext. Al: 6.00 Tot. Al: 12.00 Ca: 37.92
Conductivity: 9.30 DOC: 5.50 F: 1.053 Mg: 26.32
Air Eg pH: 6.54 TP: 17.00 Secchi Depth: 4.25
Color: 21.00 Na: 9.57 Silica: 0.00 Sulfate: 47.89
Site Depth: 5.80 Lake Area: 9.5 Elevation: 344.4
Lake Type: SEEPAGE Watershed Area: 39.0
ELS-II CHEMISTRY
SAMPLE DATE: 26JUN87
pH: 6.09 Inorganic Al: -0.01 Minimum DO: 7.96
DOC: 4.50 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO: 0.00
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 27JUN87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
67.0
65.5
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Yellow Perch
Largemouth Bass
Bluegill
Northern Pike
37
1
16
1
TRAP NET SEINE
0
0
74
0
0
0
0
0
ANGLING
0
6
0
0
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 01SEP87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
GILL NETS
TRAP NETS
SEINES
ANGLING
3
3
4
TOTAL HOURS FISHED
45.0
48.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
TRAP NET SEINE
ANGLING
B-44
-------
NAME: RICHARDSON LAKE
LONGITUDE: 91-27'51lfW LATITUDE:
ID: 2B2-075
46-32'22"N STATE: WI
Yellow Perch
Largemouth Bass
Bluegill
Northern Pike
SPECIES
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Largemouth Bass
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
8
s 1
10
1
ELS-II INDIVIDUAL
FISH ID
12100 ,
12101
12102
12103
12104
12105
12107 .
12108
12109
12110
12111
12112
12113
12114
12115
12116
12117
12118
12119
12120
12121
12122
12123
12124
12125
12126
12127
12128
12129
12130
12131
12132
12133
12134
12135
12136
12137
12138
12139
892
893
894
895
896
897
0
0
75
0
FISH
LENGTH
310
314
261
183
180
203
128
175
111
115
121
121
118
120
121
121
115
111
131
122
135
125
112
130
125
106
125
194
115
120
127
129
121
118
125
129
110
115
303
112
113
111
107
114
122
8
6
10
0
DATA
WEIGHT
410
370
240
84
67
-104
20
52
12
13
15
17
14
16
16
17
15
13
21
19
24
19
14
21
19
12
19
80
15
17
18
18
17
16
19
22
13
14
410
12
12
10
10
13
15
0
2
0
0
B-45
-------
NAME: RICHARDSON LAKE ID: 2B2-075
LONGITUDE: 91-27/51"WT LATITUDE: 46-32'22"N STATE: WI
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Largemouth Bass
Largemouth Bass
Largemouth Bass
899
900
901
902
903
904
898
905
906
907
908
909
910
911
913
914
915
77
68
78
88
64
63
108
240
201
162
187
215
190
171
266
205
379
5
4'
6
7
3
3
10
135
76
39
63
103
82
44
260
109
800
B-46
-------
NAME: BOHMIER LAKE ID:;2B2-078
LONGITUDE: 88-52'47"W -LATITUDE: . 46-5.0'05"N STATE: MI
.ELS-I CHEMISTRY
SAMPLE DATE: 03NOV84
pH: 5.63 Ext. Al: 2.00 Tot. Al: 11.00 Ca: 38.42
Conductivity: 10.60 DOC: 2.20 F: 0.526 Mg: 20.56
Air Eq pH: 6.45 TP: 11.00 Secchi Depth: 4.50
Color: 10.00 Na: 8.70 Silica: 0.15 Sulfate: 61.63
Site Depth: 19.50 Lake Area: 4.5 Elevation: 364.9
Lake Type: SEEPAGE Watershed Area: 18.0
ELS-II CHEMISTRY
SAMPLE DATE: 13JUL87
pH: 5.77 Inorganic Al: 0.01 Minimum DO: 0.96
DOC: 2.20 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DC): 0.34
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 14JUL87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
57.0
67.2
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET TRAP NET SEINE
Brook Stickleback
0
8
ANGLING
0
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 03SEP87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
GILL NETS
TRAP NETS
SEINES
ANGLING
3
3
4
TOTAL HOURS FISHED
42.5
42.0
2.0
NUMBER OF FISH CAUGHT:
NO FISH CAUGHT
B-47
-------
NAME: PINE LAKE
LONGITUDE: 88-43' 07 "W
ID: 2B2-^079
LATITUDE: 4 6-58 ' 57 "N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 18OCT8 4
pH: 6.07 Ext. Al: 8.00 Tot. Al: 38.00 Ca: 48.40
Conductivity: 12.30 DOC: 4.40 F: 0.684 Mg: 27.97
Air Eq pH: 6.45 TP: 15.00 Secchi Depth: 2.20
Color: 25.00 Na: 9.57 Silica: 0.08 Sulfate: 56.42
Site Depth: 2.20 Lake Area: 9.0 Elevation: 381.6
Lake Type: SEEPAGE Watershed Area: 36.0
ELS-II CHEMISTRY
SAMPLE DATE: 22JUL87
pH: 6.30 Inorganic Al: -0.00 Minimum DO: 8.37
DOC: 4.00 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 0.00
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 23JUL87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
53.5
57.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET TRAP NET SEINE
Yellow Perch
282
104
ANGLING
0
SPECIES
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
324
160
172
167
165
170
122
120
211
183
191
118
121
124
122
520
43
54
47
47
56
19
17
86
72
64
18
19
21
20
B-48
-------
NAME: PINE LAKE
LONGITUDE: 88-43'07"W
ID: 2B2-079
LATITUDE: 46-58'57"N STATE: MI
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
575
576
577
578s
579
582
583
584
585
586
587
588
589
590
591
592
593
594
595.
596
597
598
59.9
127
118
120
125
121
167
167
161
168
167
167
158
163
153
146
158
146
159
147
150
153
146
112
22
17
19
21
17
51
51
38
42
45
55
35
40
36
31
35
33
41
34
34
37
32
15
B-49
-------
NAME: (NO NAME)
LONGITUDE: 88-50'48"W
ID: 2B2-082
LATITUDE: 46-51/41"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE:'03NOV84
pH: 5.60 Ext. Al: 25.50 Tot. Al: 69.00 Ca: 51.40
Conductivity: 14.00 DOC: 4.00 F: 0.632 Mg: 27.97
Air Eq pH: 6.43 TP: 9.000 Secchi Depth: 4.00
Color: 25.00 Na: 13.05 Silica: 0.29 Sulfate: 65.06
Site Depth: 17.30 Lake Area: 4.4 Elevation: 367.6
Lake Type: DRAINAGE Watershed Area: 98.0
ELS-II CHEMISTRY
SAMPLE DATE: 13JUL87
pH: 5.79 Inorganic Al: 0.00 Minimum DO: 0.05
DOC: 3.80 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO: 0.61
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 14JUL87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
65.0
63.0
50.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Yellow Perch
Largemouth Bass
Brown Bullhead
White Sucker
19
0
0
5
TRAP NET SEINE
3
0
5
1
52
25
0
0
ANGLING
0
0
0
0
SPECIES
Yellow Perch
Yellow Perch
White Sucker
Yellow Perch
White Sucker
White Sucker
White Sucker
White Sucker
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
12390
12391
12392
12393
12394
12396
12397
12398
12399
12400
12401
12402
170
147
398
135
361
333
334
326
170
184
170
176
43
29
620
23
460
400
440
360
44
60
46
41
B-50
-------
NAMES
LONGITUDE:
(NO NAME)
88-50'48"W
I'D: 2B2-082
LATITUDE: 46-51'41"N STATE: MI
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
12403
12404
12405
12406
12407
12408
12409
12410
12411
12412
12413
12414
12415
12416
12417
168
174
183
177
168
16?
161
172
167
170
168
167
111
121
185
45
46
55
51
40
47
37
45
41
41
47
42
16
21
56
B-51
-------
NAME: ELEVENMILE LAKE ID: 2B2-090
LONGITUDE: 88-42'30"W LATITUDE: 47-00'57"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 18OCT84
pH: 5.13 Ext. Al: 13.00 Tot. Al: 38.00 Ca: 31.94
Conductivity: , 12.70 DOC: 3.50 F: 0.579 Mg: 25.50
Air Eg pH: 5.11 TP: 2.000 Secchi Depth: 1.70
Color: 25.00 Na: 7.39 Silica: 0.00 Sulfate: 67.66
Site Depth: 1.70 Lake Area: 5.5 Elevation: 422.2
Lake Type: SEEPAGE Watershed Area: 44.0
ELS-II CHEMISTRY
SAMPLE DATE: 15JUL87
pH: 5.12 Inorganic Al: 0.01 Minimum DO: 8.00
DOC: 3.40 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 0.00
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 15JUL87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
54.0
58.5
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
TRAP NET SEINE
Yellow Perch
Pumkinseed
873
1
665
1
0
0
ANGLING
1
0
SPECIES
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
429
430
431
432
433
434
435
436
437
438
439
440
441
442
159
314
158
104
155
159
155
113
156
111
117
152
156
185
38
380
38
12
33
36
33
15
33
14
16
34
30
48
B-52
-------
NAME: ELEVENMILE LAKE ID: 2B2-090
LONGITUDE: 88-42/30"W LATITUDE: 47-00/57"N STATE: MI
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461,
462.
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
159
157
175
154
156
158
150
113
103
110
110
153
112
112
115
181
150
152
155
146
155
198
150
155
154
180
181
204
179
117
194
194
181
182
189
183
117
110
113
116
187
99
100
99
97
100
95
187
182
214
34
33
39
34
35
36
30
13
12
15
13
28
13
13
14
75
27
32
31
29
33
60
29
32
35
61
57
70
41
16
60
50
40
50
63
59
14
13
13
14
62
9
9
10
9
10
8
51
53
109
B-53
-------
NAME: DELENE LAKE ID: 2B2-098
LONGITUDE: 88-24/19"W LATITUDE: 46-32'29"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 17OCT84
pH: 6.90 Ext. Al: 2.00 Tot. Al: 25.00 Ca: 125.7
Conductivity: 19.60 DOC: 10.30 F: 1.158 Mg: 49.36
Air Eq pH: 7.24 TP: 11.00 Secchi Depth: 1.40
Color: 45.00 Na: 14.35 Silica: 0.80 Sulfate: 28.52
Site Depth: 1.50 Lake Area: 26.2 Elevation: 507.5
Lake Type: SEEPAGE Watershed Area: 202.0
ELS-II CHEMISTRY
SAMPLE DATE: 06JUL87
pH: 6.68 Inorganic Al: -OvOO Minimum DO: 8.50
DOC: 6.90 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 0.00
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 07JUL87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
4
4
4
TOTAL HOURS FISHED
22.5
88.5
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Yellow Perch
Iowa Darter
Largemouth Bass
Northern Pike
22
0
0
1
TRAP NET SEINE
27
1
0
0
0
0
0
0
ANGLING
0
0
1
0
SPECIES
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
12352
12353
12354
12355
12356
12357
12358
12359
12360
12361
12362
12363
90
103
106
231
113
109
102
120
115
110
110
115
6
11
14
133
13
10
9
14
12
12
12
11
B-54
-------
NAME: DELENE LAKE ID:: 2B2-098
LONGITUDE: 88-24'19"W LATITUDE: 46-32'29"N STATE: MJ
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
12364
12365
12366
12367
12368
12369
12370
12371
12372
12373
12374
12375
12376
12377
! 12378
12379
12380
12381
12382
12383
12384
12385
94
90
81
85
97
96
120
110
111
115
115
112
111
111
107
115
115
108
120
120
120
122
6
6
5
5
8
8
14
11
12
14
14
17
15
15
14
16
15
13
18
18
19
20
B-55
-------
NAME: HERBERT LAKE ID: 2B2-100
LONGITUDE: 88-06'25"W LATITUDE: 46-39/00"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 17OGT84
pH: 4.83 Ext. Al: 90.00 Tot. Al: 143.5 Ca: 49.65
Conductivity: 20.50 DOC: 4.65 F: 1.211 Mg: 34.55
Air Eg pH: 4.80 TP: 0.500 Secchi Depth: 2.85
Color: 25.00 Na: 14.14 Silica: 0.13 Sulfate: 114.0
Site Depth: 3.40 Lake Area: 12.7 Elevation: 521.2
Lake Type: SEEPAGE Watershed Area: 96.0
ELS-II CHEMISTRY
. SAMPLE DATE: 01JUL87
pH: 4.89 Inorganic Al: 0.04 Minimum DO: 7.34
DOC: 6.20 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 0.00
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 03JUL87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
57.0
65.5
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET TRAP NET SEINE
Yellow Perch
141
63
ANGLING
3
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 09SEP87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
GILL NETS
TRAP NETS
SEINES
ANGLING
3
3
4
TOTAL HOURS FISHED
60.5
66.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET TRAP NET SEINE
Yellow Perch
56
197
ANGLING
1
B-56
-------
NAME;
LONGITUDE:
HERBERT LAKE ID: 2B2-100
88-06'25"W LATITUDE: 46-39'00"N STATE: MI
SPECIES
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
281
282
": 294
298
305
307
308
311
283
284
286
288
291
292
293
295
296
297
299
300
301
302
303
304
306
309
310
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
12918
12920
12921
12922
12924
12925
12927
12923
196
197
155
178
142
145
177
175
190
165
163
188
161
161
160
165
117
167
162
165
134
183
186
135
130
128
188
185
133
135
120
140
139
140
185
117
191
185
110
184
189
113
186
169
154
207
157
170
154
150
75
79
39
55
31
28
52
52
73
45
40
46
41
41
40
44
15
47
44
45
26
65
68
27
21
24
70
57
25
26
17
28
26
29
66
19
76
61
15
67
68
17
63
42
39
99
39
58
39
40
B-57
-------
NAME:
LONGITUDE:
HERBERT LAKE ID: 2B2-100
88-06'25"W LATITUDE: 46-39'00"N STATE: MI
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
12926
12928
12929
12930
12931
12932 '
12933
12934
12935
12936
12937
12938
12939
12940
12941
12942
12943
12944
12945 -
12947
12948
12949
12950
12951
12952
12953
12954
12955
12956
12957
12958
176
173
169
176
174
157
175
171
146
151
151
151
169
198
203
205
90
99
90
115
140
140
140
140
149
145
140
144
142
142
141
56
53
52
56
52
39
47
57
35
35
37
35
48
88
84
88
7
9
7
17
26
27
23
26
31
27
27
26
28
23
24
B-58
-------
NAME: ISLAND LAKE ID: 2B3-007
LONGITUDE: 87-47/10"W LATITUDE: 46-40'18"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 13OCT84
pH: 6.56 Ext. Al:. 26.00 Tot. Al: 70.00 Ca: 120.8
Conductivity: 20.50 DOC: 4.40 F: 1.105 Mg: 38.66
Air Eq pH: 7.01 TP: 4.000 Secchi Depth: 4.60
Color: 20.00 Na: 14.35 Silica: 1,09 Sulfate: 100.-6
Site Depth: 14.90 Lake Area: 11.6 Elevation: 527.3
Lake Type: DRAINAGE Watershed Area: 52.0
ELS-II CHEMISTRY
SAMPLE DATE: 20JUL87
pH: 6.37 Inorganic Al: 0.03 Minimum DO: 1.33
DOC: 4.70 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO: 0.11 ,
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 21JUL87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
58.5
56.5
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Bluntnose Minnow
Finescale Dace
Brassy Minnow
Brook Trout
0
0
0
28
TRAP NET SEINE
10
14
0
0
269
3
43
0
ANGLING
0
0
0
0
SPECIES
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
Brook
Brook
Brook
Brook
Brook
Brook
Brook
Brook
Brook
Brook
Trout
Trout
Trout
Trout
Trout
Trout
Trout
Trout
Trout
Trout
550
551
552
553
554
555
556
557
558
559
266
190
270
276
274
195
211
215
272
188
210
85
210
245
285
80
110
100
240
60
B-59
-------
NAME: SECTION FOUR LAKE ID: 2B3-008
LONGITUDE: 85-18'15"W LATITUDE: 46-40'26"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 23OCT84
pH: 6.78 Ext. Al: 2.00 Tot. Al: 37.00 Ca: 149.7
Conductivity: 29.20 DOC: 8.90 F: 0.895 Mg: 92.95
Air Eq pH: 7.22 TP: 1.000 Secchi Depth: 2.00
Color: 30.00 Na: 18.70 Silica: 0.74 Sulfate: 97.65
Site Depth: 6.10 Lake Area: 4.4 Elevation: 219.5
Lake Type: DRAINAGE Watershed Area: 10.0
ELS-II CHEMISTRY
SAMPLE DATE: 27AUG87
pH: 7.02 Inorganic Al: -0.00 Minimum DO: 0.10
DOC: 6.30 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO: 0.45
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 28AUG87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
63.0
66.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
TRAP NET SEINE
Bluegill
Flathead Minnow
Finescale Dace
Central Mudminnow
5
0
2
0
254
4
0
1
0
0
0
0
ANGLING
0
0
0
0
B-60
-------
NAME: GRAND SABLE LAKE ID: 2B3-009
LONGITUDE: 86-02'30"W LATITUDE: 46-38'15"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 20OCT84
pH: 7.86 Ext. Al: 5.50 Tot. Al: 9.00 C«a: 711.3
Conductivity: 102.70 DOC: 11.90 F: 2.158 Mg: 399.8
Air Eq pH: 8.32 TP: 14.00 Secchi Depth: 3.30
Color: 30.00 Na: 37.41 Silica: 6.49 Sulfate: 104.7
Site Depth: 18.60 Lake Area:262.3 Elevation: 226.5
Lake Type: DRAINAGE Watershed Area: 2707
ELS-II CHEMISTRY
SAMPLE DATE: 03AUG87
pH: 8.17 Inorganic Al: ,0.01 Minimum DO: 5.02
DOC: 4.77 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO: 0.00
ELS-II FISH CATCH SUMMARY ~ SAMPLE DATE: 04AUG87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
8
8
8
TOTAL HOURS FISHED
153.0
176.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
TRAP NET SEINE
Mottled Sculpin
Logperch
Yellow Perch
Iowa Darter
Smallmouth Bass
Rock Bass
White Sucker
Common Shiner
Golden Shiner
Northern Pike
Rainbow Smelt
Lake Trout
1
0
38
0
0
23
2
38
1
9
41
2
0
0
11
0
17
0
3
0
0
1
0
0
0
1
0
7
2
0
0
0
0
0
0
0
ANGLING
0
0
0
0
0
0
0
0
0
0
0
0
SPECIES
Northern Pike
Northern Pike
Northern Pike
Northern Pike
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
670
671
672
673
496
608
591
655
920
1620
1480
1950
B-61
-------
NAME: GRAND SABLE LAKE ID: 2B3-009
LONGITUDE: 86-02'30"W LATITUDE: 46-38'15"N STATE: MI
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
White Sucker
White Sucker
White Sucker
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
White Sucker
Yellow Perch
Yellow Perch
Yellow Perch
White Sucker
Yellow Perch
Yellow Perch
Northern Pike
Smallraouth Bass
Smallmouth Bass
Yellow Perch
674
675
676
677
678
679
680
681'
684
685
686
687
688
690
692
693
694
695
69.6
697
698
700
701
702
703
705
707
709
710
712
713
714
715
716
718
721
722
723
724
726
727
728
729
731
732
733
734
587
598
705
578
556
315
232
228
236
197
189
196
181
161
161
163
112
176
165
122
165
241
191
164
126
115
168
180
114
168
178
207
200
166
166
103
234
115
176
119
146
175
118
656
2'97
256
116
1280
900
2110
1220
1140
321
121
131
143
74
71
84
63
48
48
42
14
55
48
17
44
124
66
40
17
14
45
58
15
55
59
88
87
53
47
10
128
14
5.3
17
31
54
17
1800
380
260
16
B-62
-------
NAME: ROUND LAKE ID: 2B3-012
LONGITUDE: 87-56'52"W LATITUDE: 46-33'24"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 14OCT84
pH: 6.93 Ext. Al: 25.00 Tot. Al: 111.0 Ca: 182.1
Conductivity: 31.30 DO.C: 10.70 F: 1.474 Mg: 96.24
Air Eg pH: 7.38 TP: 17.00 Secchi Depth: 1.20 .
Color: 85.00 Na: 24.36 Silica: 2.13 Sulfate: 91.61
Site Depth: 4.60 Lake Area: 16.7 Elevation: 485.9
Lake Type: DRAINAGE Watershed Area: 728.0
ELS-II CHEMISTRY
SAMPLE DATE: 06JUL87
pH: 6.73 Inorganic Al: 0.03 Minimum DO: 0.05
DOC: 12.20 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO: ; 0.80
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 07JUL87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
63.0
69.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
TRAP NET SEINE
Yellow Perch
Iowa Darter
Pumkinseed
White Sucker
Bluntnose Minnow
Common Shiner
Golden Shiner
Northern Pike
0
0
0
0
0
1
0
0
41
0
8
5
0
0
30
1
3
2
0
0
1
11
0
0
ANGLING
0
0
0
' 0
0
0
0
5
SPECIES
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
White Sucker
White Sucker
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
324
325
326
327
328
329
330
331
576
466
485
520
533
578
101
107
980
515
610
760
830
840
10
12
B-63
-------
NAME: ROUND LAKE
LONGITUDE: 87-56'52"W
ID: 2B3-012
LATITUDE: 46-33'24"N STATE: MI
White Sucker
White Sucker
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Pumpkinseed
Pumpkinseed
Pumpkinseed
Pumpkinseed
Pumpkinseed
Pumpkinseed
Pumpkinseed
Pumpkinseed
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
9169
9170
9171
9172
9173
9174
9175
9176
102
102
99
109
101
116
101
121
109
121
127
134
144
167
105
143
108
110
96
104
107
95
105
252
106
102
100
107
140
102
140
120
159
126
131
110
96
110
104
105
122
96
102
149
87
61
77
69
101
67
76
10
10
8
11
9
15
9
18
12
18
20
23
30
52
11
26
12
8
9
11
15
8
10
190
11
10
9
11
25
9
27
17
42
20
22
11
8
13
10
10
17
8
9
65
14
4
8
5
19
5
8
B-64
-------
NAME: FOX LAKE ID: 2133-013
LONGITUDE: 86-02'04"W LATITUDE: 46-35'32"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 20OCT84
pH: 4.94 Ext. All 50.00 Tot. Al: 116.0 Ca: 43.41
Conductivity: 13.50 DOC: 2.70 F: 0.684 Mg: 22.21
Air Eq pH: 5.03 TP: 20.00 Secchi Depth: 1.55
Color: 75.00 Na: 7.39 Silica: 0.63 Sulfate: 52.88
Site Depth: 7.30 Lake Area: 4.6 Elevation: 281.9
Lake Type: CLOSED Watershed Area: 132.0
ELS-II CHEMISTRY
SAMPLE DATE: 17AUG87
pH: 4.80 Inorganic Al: 0.02 Minimum DO: 0.05
DOC: 5.80 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO: .0.72
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 18AUG87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
64.0
59.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Yellow Perch
Pumkinseed
Brown Bullhead
417
0
2
TRAP NET SEINE
163
1
47
0
4
0
ANGLING
0
0
0
SPECIES
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
12745
12746
12747
12748
12749
12750
12751
12752
12753
12754
12755
12756
12757
143
135
135
173
125
143
121
115
137
132
125
120
128
26
20
22
46
18
27
13
12
22
23
17
15
18
B-65
-------
NAME:
LONGITUDE:
FOX LAKE
86-02'04"W
ID: 2B3-013
LATITUDE: 46-35'32"N STATE: MI
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Yellow
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
Perch
12758
12759
12760
12761
12762
12763
12764
12765
12766
12767
12768
12769
12770
12771
12772
12773
12774
12775
12776
12777
12778
12779
12780
12781
12782
12783
12784
111
145
113
192
217
164
309
90
92
93
95
95
90
95
91
92
95
93
92
95
95
90
120
123
110
110
115
12
29
14
73
105
43
410
7
7
8
8
8
7
8
7
7
8
7
7
8
8
7
15
17
13
14
13
B-66
-------
NAME: BUTO LAKE , ID: 2B3-020
LONGITUDE: 87-59'45"W LATITUDE: 46-26'44"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 16OCT84
pH: 6.10 Ext. Alt 15.00 Tot. Al: 65.00 Ca: 89,82
Conductivity: 22.40 DOC: 7.80 F: 2.106 Mg: 74.03
Air Eg pH: 7.01 TP: 13.00 Secchi Depth: 1.00
Color: 110.0 Na: 25.23 Silica: 2.32 Sulfate: 83.07
Site Depth: 5.50 Lake Area: 9.7 Elevation: 478.5
Lake Type: DRAINAGE Watershed Area: 60.0
ELS-II CHEMISTRY
SAMPLE DATE: 15JUL87
pH: 5.79 Inorganic Al: 0.00 Minimum DO: 0.03
DOC: 11.50 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO: ; 0.57
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 16JUL87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling ,
3
3
4
TOTAL HOURS FISHED,
66.0
72.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Yellow Perch
Pumkinseed
Brown Bullhead
White Sucker
Creek Chub
Common Shiner
Golden Shiner
121
0
0
39
2
3
93
TRAP NET SEINE
39
1
37
16
5
0
100
0
0
0
0
0
0
0
ANGLING
0
0
0
0
1
0
0
SPECIES
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
12418
12419
12420
12422
12423
12424
12425
12426
12464
B-67
180
326
295
343
286
113
120
121
138
47
400
320
400
280
14
16
16
25
-------
NAME:
LONGITUDE:
BUTO LAKE
87-59'45"W
ID: 2B3-020
LATITUDE: 46-26'44"N STATE: MI
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
12465
12466
12467
12468
12469
12470
12471
12472
12473
12474
12475
12476
12477
12478
12479
12480
12482
12483
12484
12485
12487
12488
12489
12490
12491
12492
12493
12494
12495
12496
12427
12428
12429
12430
12432
12433
12437
12441
12442
12443
12444
12446
12447
12448
12449
12454
12455
12456
12458
12460
12461
12462
12463
12504
172
126
117
156
113
133
117
116
127
126
112
122
122
127
140
132
168
138
135
89
93
94
93
92
122
116
120
121
118
121
362
356
325
303
366
316
355
351
365
225
195
172
333
310
305
359
310
375
316
356
189
170
190
185
49
19
16
40
14
19
17
16
18
20
13
18
19
18
24
20
42
23
19
6
6
7
7
7
15
14
14
15
14
14
440
440
300
280
460
320
400
390
460
100
68
49
350
310
250
450
300
460
310
440
62
49
63
54
B-68
-------
NAME: BUTO LAKE
LONGITUDE: 87-59'45"W
ID: 2B3-020
LATITUDE: 46-26'44"N STATE: MI
White
White
White
White
White
White
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
12505
12509
12510
12511
12512
12513
205
316
292
352
180
160
69
280
220
400
48
33
B-69
-------
NAME: BONE LAKE
LONGITUDE: 88-18'22"W
ID: 2B3-023
LATITUDE: 46-22'30"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 14OCT84
pH: 7.65 Ext. Al: 6.00 Tot. Al: 31.00 Ca: 694.6
Conductivity: 114.00 DOC: 9.30 F: 2.421 Mg: 422.0
Air Eg pH: 8.44 TP: 19.00 Secchi Depth: 1.60
Color: 55.00 Na: 58.29 Silica: 4.36 Sulfate: 101.4
Site Depth: 2.10 Lake Area: 63.2 Elevation: 490.7
Lake Type: DRAINAGE Watershed Area: 5467
ELS-II CHEMISTRY
SAMPLE DATE: 30JUN87
pH: 7.53 Inorganic Al: o.oo Minimum DO;
DOC: 9.10 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 0.00
7.95
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 30JUN87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
7
7
8
TOTAL HOURS FISHED
82.0
117.5
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Walleye
Yellow Perch
Largemouth Bass
Bluegill
Pumkinseed
White Sucker
Common Shiner
Golden Shiner
Northern Pike
8
37
0
0
46
53
0
30
41
TRAP NET SEINE
0
3
1
2
8
30
1
0
2
0
0
1
0
0
0
0
0
0
ANGLING
0
1
0
0
0
0
0
0
1
SPECIES
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
White Sucker
White Sucker
White Sucker
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
12106
12140
12141
12142
12143
12144
12145
144
220
175
75
470
322
385
33
120
58
5
1180
340
590
B-70
-------
NAME:
LONGITUDE:
BONE LAKE ID: 2B3-023
88-18'22"W LATITUDE: 46-22/30"N STATE: MI
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
Northern Pike
Yellow Perch
Northern Pike
Walleye
Walleye
Walleye
Walleye
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Northern Pike
Northern Pike
Yellow Perch
Yellow Perch
Yellow Perch
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
12146
12147
12148
,12149
12150
12151
12152
12153
12154
12155
12156
12157
12158
12159
12160
12161
12162
12163
12164
12165
12166
12167
12168
12169
12170
12171
12172
12174
12182
12183
12184
12185
12186
12187
12188
12189
12190
12191
12192
12193
12194
12201
12202
12203
12204
12205
12206
12207
12211
12212
12213
12214
12215
12216
326
306
320
380
380
420
405
349
311
440
451
470
419
462
395
393
457
336
405
419
381
366
502
516
496
540
106
504
560
196
431
404
215
188
211
156
111
111
109
172
169
410
464
171
157
91
620
490
437
625
476
367
396
402
360
330
250
540
51.0
780
690
440
310
900
1000
990
770
1070
690
650
925
490
660
720
620
580
1080
1300
1100
900
13
660
1380
65
660
540
105
81
93
48
21
15
16
57
58
340
500
69
43
10
1340
640
400
1390
500
250
320
360
B-71
-------
NAME:
LONGITUDE:
BONE LAKE
88-18'22"W
ID: 2B3-023
LATITUDE: 46-22'30"N STATE: MI
Yellow Perch
Walleye
Yellow Perch
Walleye
Yellow Perch
Yellow Perch
Walleye
Yellow Perch
Yellow Perch
Walleye
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Pumpkinseed
Pumpkinseed
Pumpkinseed
Pumpkinseed
Pumpkinseed
Pumpkinseed
Pumpkinseed
Pumpkinseed
Pumpkinseed
Pumpkinseed
Pumpkinseed
Pumpkinseed
Pumpkinseed
Pumpkinseed
Pumpkinseed
Pumpkinseed
Pumpkinseed
Pumpkinseed
White Sucker
12217
12218
12219
12220
12221
12222
12223
12224
12225
12226
12227
12228
12229
12230
12231
12232
12233
912079
912097
912098
912100
912101
912102
912103
912104
912105
912107
912112
912122
912123
912124
912125
912127
912128
912129
912167
260
321
267
368
193
197
409
174
216
415
114
92
242
127
145
192
147
182
183
180
153
150
166
110
170
149
137
182
129
110
74
100
77
70
174
366
200
280
250
420
60
100
680
50
140
600
18
10
160
25
39
90
42
134
129
123
82
73
100
25
119
72
58
130
45
27
8
19
8
6
112
580
B-72
-------
NAME: CASEY LAKE *&: 2B3-027
LONGITUDE: 87-55'00"W LATITUDE: 46-17'20»N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 16OCT84
8 25 Ext Al: 1.00 Tot. Alt 29.00 Ca: 859.8
cduciivityf' 157.20 DOC: 4.00 F. 2.158 Mg: 765.8
Air Eg pH: 8.69 TP: 5.000 Secchi Depth: 3-35
cJlor??5.00 Na: 32.63 Silica: 2.53 Sulfate: 74 54
Site Depth: 4.90 Lake Area: 21.7 Elevation: 447.8
Lake Type: SEEPAGE Watershed Area: 52 .,0
ELS-II CHEMISTRY
SAMPLE DATE;: 30JUN87
pH: 8.74 Inorganic Al: 0.01 Minimum DO::
DOC: 4.20 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 0.00
8.61
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 01JUN87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
4
4
5
TOTAL HOURS FISHED
73.2
80.0 -
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Iowa Darter
Largemouth Bass
Bluegill
Bluntnose Minnow
0
8
22
0
TRAP NET SEINE
0
0
2
0
5
0
104
181
ANGLING
0
4
0
0
SPECIES
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
270
271
272
273
274
275
276
277
278
279
285
318
297
297
275
297
261
267
263
271
300
400
400
350
300
350
200
240
450
500
B-73
-------
: MI
ELS-I CHEMISTRY
SAMPLE DATE: 16OCT84
ta^^-^g^r-a-'
ELS-II CHEMISTRY SAMPLE DATE: 08JUN87
DOC- ll2L I2?rgannlc J1: .°-°° Minimum DO: 7.45
% Water'com ^ Stratif ication: MIXED
* water Column < 4 mg/L DO: o.OO
ELS-II FISH CATCH SUMMARY - SAMPLE DATE: 09JUN87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
5
5
6
TOTAL HOURS FISHED
135.0
94.5
NUMBER OF FISH CAUGHT:
SPECIES GILL NET TRAP NET SEINE
Walleye
Yellow Perch
Black Crappie
Smallmouth Bass
White Sucker
Northern Pike
Central Mudminnow
0
68
0
2
20
10
0
1
10
0
0
5
2
0
0
0
0
0
0
0
5
ANGLING
0
0
1
0
0
1
0
SPECIES
White Sucker
Smallmouth Bass
White Sucker
White Sucker
Yellow Perch
Northern Pike
Yellow Perch
Yellow Perch
Yellow Perch
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
2
3
4
5
8
9
10
12
14
B-74
414
268
320
502
219
466
195
175
176
810
250
372
1261
173
545
126
81
86
-------
NAME: CATARACT BASIN ID: 2B3-028
LONGITUDE: 87-3i'oo"w LATITUDE: 46-i8'5o»N STATE: MI
Yellow Perch
Yellow Perch
Northern Pike
Northern Pike
White Sucker
White Sucker
White Sucker
Yellow Perch
White Sucker
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
White Sucker
White Sucker
Northern Pike
Northern Pike
White Sucker
White Sucker
White Sucker
Smallmouth Bass
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Northern Pike
White Sucker
White Sucker ,
White Sucker
Yellow Perch
Northern Pike
Northern Pike
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
White Sucker
White Sucker
Northern Pike
White Sucker
Northern Pike
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
15
16
19
20
23
24
26
29
32
33
35
36
37
39
43
44
46
48
50
51
53
55
56
57
70
76
77
78
79
81
82
83
86
98
103
108
109
110
111
112
114
117
118
119
122
17
58
59
84
85
107
192
210
398
349
390
410
342
276
320
292
272
258
261
220
155 ':
153
306
180
552
467
541
480
484
355
184
142
145
145
369
505
429
'419
200
430
325
162
165
143
130
146
573
503
289
566
415
146
260
285
270
281
160
111
142
380
260
824
943
600
340
385
372
350
277
299
163
54
39
348
64
878
590
1600
1100
1100
520
93
38
40
41
285
1360
, , 820
800
117
409
191
51
66
38
28
41
1840
1380
118
1920
350
40
258
327
313
335
59
B-75
-------
NAME: ISLAND LAKE Tn.
LONGITUDE: 86-38'51»W LATITUDE: 46-16'05'*'N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 25OCT84
pH: 5.34 Ext. Al: 11.00 Tot.
27 00
S
Lake Type: SEEPAGE
Watershed Area:
A-* /n
"
ELS-II CHEMISTRY SAMPLE DATE: 15JUN87
54X?n X£°r9anic Al: o.oi Minimum DO: 7.82
w=4- « -, Thermal Stratification: MIXED
Water Column < 4 mg/L DO: o.oo
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 16JUN87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
69.0
69.5
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET TRAP NET SEINE
Yellow Perch
Largemouth Bass
Bluegill
Brown Bullhead
7
29
12
4
4
0
446
0
1
0
125
0
ANGLING
0
0
0
0
SPECIES
Yellow Perch
Largemouth Bass
Largemouth Bass
Largemouth Bass
Yellow Perch
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Yellow Perch
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
1202
1206
1208
1209
1212
1213
1219
1224
1226
1227
1228
1232
124
257
351
273
100
334
370
275
268
269
330
176
23
210
530
270
10
480
640
270
230
225
430
59
B-76
-------
NAME: ISLAND LAKE ID: 2B3-030
LONGITUDE: 86-38'51"W LATITUDE: 46-16'05"N STATE: MI
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
Bluegill
1233
1234
1235
1236
1237
1238
1239
1240
1241
1203
1204
1205
1207
1210
1211
1214
1216
1217
1218
1220
1222
1223
1225
1229
1230
1231
912000
912001
912002
912003
912005
912006
912007
912008
912009
912010
912011
912012
912013
912014
912015
912016
912017
912018
912019
912020
912021
912022
912023
912024
912025
912026
182
120
112
110
107
158
129
160
154
284
293
282
285
301
301
331
280
292
284
310
310
291
287
286
290
289
101
114
111
97
155
114
117
118
118
113
112
98
137
148
135
150
140
136
150
160
171
95
95
95
190
93
65
18
13
12
13
38
18
9
31
300
340
370
300
370
380
400
280
320
300
360
375
330
295
280
285
310
15
22
18
13
36
20
21
23
24
21
21
13
33
50
36
44
36
37
47
58
77
13
12
12
102
11
B-77
-------
NAME: TWIN LAKES Tn. 9R.,_no,
LONGITUDE: 85-32'00»W LATITUDE: 46-18'29--N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 22OCT84
Color: 40.00 Na: 120.5 Silica: 962 Suifate- 160 5
Site Depth: 20.10 Lake Area: 38.0 Elevation* 221 o
Lake Type: DRAINAGE Watershed Area? Isl 0
ELS-II CHEMISTRY
SAMPLE DATE: 10AUG87
DOC-
DO: 1.62
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 11AUG87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
5
5
5
TOTAL HOURS FISHED
114.0
120.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
TRAP NET SEINE
Yellow Perch
Johnny Darter
Largemouth Bass
Smallmouth Bass
Bluegill
Pumkinseed
Rock Bass
Brown Bullhead
White Sucker
Creek Chub
Emerald Shiner
Golden Shiner
Brook Trout
14
0
8
0
23
6
7
8
61
0
0
16
9
8
0
0
0
30
10
18
1
7
0
0
147
0
8
2
0
2
0
4
0
0
0
19
1
0
0
ANGLING
0
0
0
0
0
0
0
0
0
0
0
0
0
SPECIES
White Sucker
White Sucker
White Sucker
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
12671
12672
12673
380
351
362
620
520
515
B-78
-------
NAME: TWIN
LONGITUDE: 85-32
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Brook Trout
Brook Trout
Brook Trout
Brook Trout
Brook Trout
Brook Trout
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Yellow Perch
Yellow Perch
Largemouth Bass
LAKES
'00»W LATITUDE:
12674
12675
12676
12677
12678
12679
12680
12681
12682
12684
12685
12686
12687
12688
12689
12690
12691
12692
12693
12694
12695
12696
12697
..'-. 12698
12699
12700
12701
12702
12703
12704
12705
12706
12707 '>
12708
12709
12710
12711
12712
12713
12714 '
12715
12716
12717
12718
12719
12720
12721
12722
12723
12724
12725
12726
12727
12728
46-18'
374
359
326
320
238
217
324
338
367
353
321
234
246
220
260
223
247
205
232
354
366 '
363
343
339
307
331
331
157
216
230
177
180'
166
172
164
180
165
126
170
246
383
240
233
217
221
302
296
292
296
333
304
192
166
241
ID: 2B3-031
29"N STATE: MI
570
200
420
380
140
120
380
400
530
440
380
150
170
120
190
120
170
90
140,
490
530
580
500
420
310
420
420
49
103
132
51
55
42
48
43
58
45
19
47
144
550
129
106
92
87
370
350
290
380
520
400
57
47
200
B-79
-------
NAME: TWIN LAKES
LONGITUDE: 85-32'oo»w
Tn. OTVJ n^n
LATITUDE: 46-i8'29«N STATE: MI
Largemouth Bass
Brook Trout
Brook Trout
Brook Trout
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
12729
12730
12731
12732
12733
12734
12735
12736
12737
12738
12739
12740
319
367
211
209
112
146
120
99
105
106
120
122
440
470
73
72
11
25
15
9
10
10
14
14
B-80
-------
: MI
ELS-I CHEMISTRY
SAMPLE DATE: 25OCT84
Ext Al: 0.00 Tot. Al: 3.00 Ca: 984.5
133.40 DOC: 6.17^F: 1 684 Mg: 389.1
Air Eq pH: 8.46 TP: 9.000 Secchi Depth: 3.05 .
Color? 25.00 Na: 29.58 Silica: 6.14 . Sulfate: 47 89
Site Depth: 13.70 Lake Area: 16.8 Elevation: 240.8
Lake Type: DRAINAGE Watershed Area: 54.0
ELS-II CHEMISTRY
SAMPLE DATE: 11JUN87
pH: 8.33 Inorganic Al: 0.00 Minimum DO: 0.68
boc: 4.60 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO: 0.39
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 12JUL87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
53 . 5
61.5
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
TRAP NET SEINE
Yellow Perch
Johnny Darter
Largemouth Bass
Smallmouth Bass
Pumkinseed
Rock Bass
White Sucker
Bluntnose Minnow
Northern Pike
6
0
2
1
0
2
2
0
19
0
0
0
0
2
17
0
0
2
7
5
0
0
0
0
0
17
0
ANGLING
0
0
0
0
0
0
0
0
6
SPECIES
Yellow Perch
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
130
131
132
133
134
135
136
169
421
449
493
403
490
410
46
372
422
550
324
680
332
B-81
-------
NAME: KLONDIKE LAKE
LONGXTUDE: 86-3o'io»w LATITUDE:
: M1
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Smallmouth Bass
Largemouth Bass
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Largemouth Bass
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Rock Bass
Rock Bass
Rock Bass
Rock Bass
Rock Bass
Rock Bass
Rock Bass
Rock Bass
Rock Bass
Rock Bass
Rock Bass
Rock Bass
Rock Bass
Rock Bass
Pumpkinseed
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
153
155
156
157
158
159
160
161
162
163
164
165
166
167
910
'911
912
913
914
915
916
917
920
921
922
925
926
927
929
440
430
410
451
370
470
461
463
315
351
425
436
434
526
408
320
251
267
220
239
165
384
473
440
414
478
393
409
390
143
142
114
113
167
189
185
153
75
75
95
84
82
117
158
417
379
357
456
245
500
480
480
400
590
450
460
460
740
340
410
203
221
108
138
46
285
420
405
365
524
324
356
296
56
54
26
27
104
121
114
67
6
7
16
12
11
33
93
B-82
-------
ELS-I CHEMISTRY
SAMPLE DATE: 25OCT84
g:0o8-52, ^sS-TiiicSntorSifa?; 137.6
Site Depth: 7.60 Lake Area :> 7 . 6 Elevation: 234.7
Lake Type: DRAINAGE Watershed Area: 47.0
ELS-II CHEMISTRY
SAMPLE DATE: 28JUL87
oH- 8.70 Inorganic Al: 0.02 Minimum DO: 1.39
DOC: 3.70 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO: 0.25
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 29JUL87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
63.0
69.0
2.0
NUMBER OF FISH CAUGHT
SPECIES
Yellow Perch
Iowa Darter
Black Crappie
Largemouth Bass
Bluegill
Pumkinseed
Brown Bullhead
White sucker
Bluntnose Minnow
Golden Shiner
Northern Pike
GILL NET TRAP NET SEINE
54
0
0
1
0
2
0
12
0
5
7
0
.. 0
1
4
147
4
1
, 0
0
0
0
4
2
0
0
5
0
0
0
160
0
0
ANGLING
0
0
. 0
0
0
0
0
.0
0
0
0
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 12SEP87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
GILL NETS
TRAP NETS
3
3
B-83
TOTAL HOURS FISHED
53.0
52.0
-------
NAME: RUMBLE LAKE Tn. ORT m-7
LONGITUDE: 86-33'33»W LATITUDE: 46-ll'00«N STATE: MI
SEINES
ANGLING
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Yellow Perch
Iowa Darter
Largemouth Bass
Bluegill
Pumkinseed
Brown Bullhead
White Sucker
Bluntnose Minnow
Golden Shiner
Northern Pike
Central Mudminnow
TRAP NET SEINE
SPECIES
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
Largemouth Bass
Largemouth Bass
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Largemouth Bass
Largemouth Bass
Yellow Perch
White Sucker
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
20
0
33 4
8
2
1 0
12
low 0
2
8
mow o
0
0
1
18
0
1
0
0
0
1
0
ELS-II INDIVIDUAL FISH
FISH ID
600
601
602
603
604
605
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
LENGTH
424
255
371
261
320
83
81
272
234
256
328
460
332
486
723
659
659
610
675
612
150
94
228
170
125
121
121
130
120
0
10
0
0
0
0
0
1
0
0
1
DATA
WEIGHT
820
160
560
213
360
8
6
226
137
175
410
460
440
620
2200
1300
1620
1280
1740
1480
42
10
134
51
18
16
14
19
1.6
ANGLING
0
0
1
0
0
0
0
0
0
0
0
B-84
-------
NAME: RUMBLE LAKE ID: 2B3-037
LONGITUDE: 86-33'33«W LATITUDE: 46-ll'00"N STATE:
MI
Largeraouth Bass
Largemouth Bass
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
Largeraouth Bass
Northern Pike
Northern Pike
Northern Pike
630
631
632
633
634
635
636
637
638
639
640
641
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
12968
12970
12971
12972
12973
12974
12975
12976
12979
12980
12982
12959
12960
12961
12962
105
110
124
118
118
198
192
217
119
123
102
108
121
121
161
104
232
117
116
126
109
118
115
117
109
111
126
115
117
104
118
119
113
106
125
123
114
109
101
420
261
260
169
180
320
320
285
283
337
296
216
927
565
610
11
13
19
15
13
77
68
108
15
20
12
14
16
16
43
11
1.21
15
16
17
14
15
15
16
14
15
16
16
12
12
14
16
15
12
19
17
16
13
11
850
209
196
50
58
378
320
256
251
440
281
139
5000
1150
1.200
B-85
-------
NAME: RUMBLE LAKE ID. 2BVm-7
LONGITUDE: 86-33'33"w LATITUDE: 46-ii'oo»N STAT£: MI
Northern Pike
Northern Pike '
Northern Pike
Northern Pike
Northern Pike
Largemouth Bass
Largemouth Bass
Largemouth Bass
Largemouth Bass
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Northern Pike
12963
12964
12965
12966
12967
12977
12981
12983
12984
12985
12986
12987
12988
12989
12990
12991
12992
12993
12994
12995
12996
12997
12998
12999
13000
13001
13002
13003
13004
92967
686
551
620
721
535
114
102
446
108
123
118
126
127
122
110
118
121
114
114
115
101
113
121
113
' 116
117
125
115
118
650
1800
1000
1450
1150
850
18
13
1620
14
17
14
19
18
15
13
15
16
13
14
13
11
13
17
12
14
15
18
14
16
1477
B-86
-------
NAME: JOHNS LAKES (WESTERN) ID: 2B3-051
LONGITUDE: 85-54'16"W LATITUDE: 46-31'50"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 23OCT84
pH: 4.91 Ext. Al: 13.00 Tot. Al: 42.00 Ca: 25.95
Conductivity: 13.80 DOC: 3.60 F: 0.684 Mg: 17.27
Air Eq pH: 4.85 TP: 1.000 Secchi Depth: 4.70
Color: 15.00 Na: 5.22 Silica: 0.00 Sulfate: 58.09
Site Depth: 18.90 Lake Area: 6.6 Elevation: 289.0
Lake Type: SEEPAGE Watershed Area: 26.0
ELS-II CHEMISTRY
SAMPLE DATE: 17AUG87
pH: 4.85 Inorganic Al: 0.01 Minimum DO: 1.72
DOC: 2.30 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO: 0.56
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 18AUG87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
52.7
60.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET TRAP NET
Central Mudminnow 0 3
SEINE
90
ANGLING
0
B-87
-------
NAME: (NO NAME) ID: 2B3-055
LONGITUDE: 86-39'37"W LATITUDE: 46-15'52"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 25OCT84
pH: 7.41 Ext. Al: 0.00 Tot. Al: 7.00 Ca: 684.6
Conductivity: 92.90 DOC: 2.54 F: 1.421 Mg: 289.6
Air Eq pH: 8.29 TP: 9.000 Secchi Depth: 2.40
Color: 20.00 Na: 31.32 Silica: 6.19 Sulfate: 94.73
Site Depth: 2.40 Lake Area: 5.5 Elevation: 246.9
Lake Type: DRAINAGE Watershed Area: 41.0
ELS-II CHEMISTRY
SAMPLE DATE: 28JUL87
pH: 7.55 Inorganic Al: -0.00 Minimum DO:
DOC: 1.90 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 0.00
6.96
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 29JUL87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
68.5
67.5
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
TRAP NET SEINE
Yellow Perch
Johnny Darter
Pumkinseed
Banded Killifish
Brown Bullhead
White Sucker
Creek Chub
Finescale Dace
Common Shiner
Golden Shiner
Brook Trout
24
0
0
0
11
18
5
0
0
0
3
8
0
18
0
79
39
15
0
7
5
0
0
3
1
1
1
0
320
7
15
0
0
ANGLING
0
0
0
0
0
0
0
0
0
0
0
SPECIES
White Sucker
White Sucker
White Sucker
White Sucker
White Sucker
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
12539
12540
12541
12542
12543
250
254
228
233
243
157
170
124
140
142
B-88
-------
NAME:
LONGITUDE:
(NO NAME)
86-39'37"W
ID: 2B3-055
LATITUDE: 46-15'52nN STATE: MI
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
White
Brook
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Sucker
Trout
12544
12545
12546
12547
12548
12549
12551
12552
12553
12554
12555
12556
12557
12558
12559
12560
12561
12562
12563
12564
12565
12566
12567
12568
12569
12570
12571
12572
12573
12574
12575
12584
237
240
246
237
182
180
195
260
225
218
195
211
221
223
225
205
213
205
212
218
243
126
138
132
130
126
131
132
145
120
130
344
141
146
151
138
58
58
72
180
122
97
59
81
106
108
99
81
84
81
87
95
132
19
23
21
19
20
20
22
27
15
18
560
B-89
-------
NAME: PINERY LAKES (LARGEST) ID: 2B3-056
LONGITUDE: 88-23'30"W LATITUDE: 46-46'03"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 17OCT84
PH. 6.90 Ext. Al: 2.00 Tot. Al: 24.00 Ca: 374.3
Conductivity: 56.40 DOC: 8.0Q F: 2.053 Mg: 136 6
Air Eg pH: 8.12 TP: 13.00 Secchi Depth: 1 ?0
Color: 50.00 Na: 33.93 Silica: 3.17 Sulfate: 31 02
Site Depth: 2.40 Lake Area: 9.1 ElevatioS? is3.0
Lake Type: SEEPAGE Watershed Area: 194 o
ELS-II CHEMISTRY
SAMPLE DATE: 22JUL87
pH. 7.27 Inorganic Al: -0.00 Minimum DO: 7.39
DOC: 6.60 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 0.00
ELS-II FISH CATCH SUMMARY ~ SAMPLE DATE: 23JUL87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
68.0
66.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
TRAP NET SEINE
Pumkinseed
Finescale Dace
0
0
48
105
0
90
ANGLING
0
0
B-90
-------
NAME: TWIN LAKE ; ID: 2B3-057
LONGITUDE: 87-59'57"W LATITUDE: 46-27'50"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 16OCT84
pH: 6.83 Ext. Al: 2.00 Tot. Al: 21.00 Ca: 131.7
Conductivity: 29.50 DOC: 5.00 F: . 1.842 , Mg: 106.1
Air Eq pH: 7.71 TP: 12.00 Secchi Depth: 1.55
Color: 45.00 Na: 25.23 Silica: 5.66 Sulfate: 70.37
Site Depth: 3.00 Lake Area: 18.5 Elevation: 488.0
Lake Type: DRAINAGE Watershed Area: 98.0
ELS-II CHEMISTRY
SAMPLE.DATE: 08JUL87
pH: 6.67 Inorganic Al: 0.01 Minimum DO:
DOC: 5.40 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 0.47
1.67
ELS-II FISH CATCH SUMMARY-- SAMPLE DATE: 08JUL87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL :HOURS FISHED
56.5
57.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES , GILL NET
Yellow Perch
Black Crappie
Largemouth Bass
Bluegill
White Sucker
Northern Pike
Sunfish Hybrid
1
10
0
8
2
0
0
TRAP NET SEINE
1
1
0
71
0
1
2
0
0
0
0
0
0
0
ANGLING
0
0
1
0
0
0
0
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 04SEP87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
GILL NETS
TRAP NETS
SEINES
ANGLING
3
3
4
TOTAL HOURS FISHED
44.5
45.0
2.0
B-91
-------
NAME: TWIN LAKE iD: 2B3-057
LONGITUDE: 87-59'57"W LATITUDE: 46-27'50"N STATE: MI
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Black Grapple
Bluegill
White Sucker
Golden Shiner
Northern Pike
3
3
1
0
0
TRAP NET SEINE
3
2
0
1
1
0
0
0
0
0
ANGLING
2
0
0
0
0
SPECIES
White Sucker
White Sucker
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
12386
12387
12388
12388
12389
12389
337
371
170
170
106
106
290
570
50
50
11
11
B-92
-------
NAME: LAKE ANNIE ID:-233-058
LONGITUDE: 88-35'25"W LATITUDE: 47-lp'39"N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 18OCT84
pH: 6.25 Ext. Al: 12.00 Tot. Al: 93.00 Ca: 36.43
Conductivity: 11.40 DOC: 3.40 F: 0.948 Mg: 27.15
Air Eq.pH: 6.77 TP: 13.00 Secchi Depth: 1.80
Color: 15.00 Na: 16.96 Silica: 0.00 Sulfate: 43.72
Site Depth: 1.80 Lake Area: 13.2 Elevation: 293.2
Lake Type: SEEPAGE Watershed Area: 91.0
ELS-II CHEMISTRY
SAMPLE DATE: 09JUL87
pH: 5.74 Inorganic Al: 0.00 Minimum DO: 7.75
DOC: 4.00 Thermal Stratification: MIXED
% Water Column < 4 mg/L DO: 0.00
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 10JUL87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
3
3
4
TOTAL HOURS FISHED
69.0
75.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET TRAP NET SEINE
Brown Bullhead
339
2064
0
ANGLING
0
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 03SEP87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
GILL NETS
TRAP NETS
SEINES
ANGLING
3
3
4
TOTAL HOURS FISHED
64.5
66.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET TRAP NET SEINE
Brown Bullhead
275
4280
ANGLING
0
B-93
-------
NAME: OSTRANDER LAKE ID« 2B3-071
LONGITUDE: 86-36'43"W LATITUDE: 46-10'05»N STATE: MI
ELS-I CHEMISTRY
SAMPLE DATE: 25OCT84
pH: 7.05 Ext. Al: 0.00 Tot. Al: 16.00 Ca: 207 1
Conductivity: 22.20 DOC: 4.80 F: 0.948 Ma- 42 78
Air Eq pH: 7.59 TP: 11.00 Secchi Depth: 2.85
Color: 15.00 Na: 10.00 Silica: 0.09 Sulfate: 77 45
Site Depth: 9.10 Lake Area: 21.7 Elevation: 234.7
Lake Type: SEEPAGE Watershed Area: 65.0
ELS-II CHEMISTRY
SAMPLE DATE: 15JUN87
pH: 7.03 Inorganic Al: 0.01 Minimum DO: 4.91
DOC: 5.60 Thermal Stratification: STRATIFIED
% Water Column < 4 mg/L DO: 0.00
ELS-II FISH CATCH SUMMARY SAMPLE DATE: 16JUN87
SAMPLING EFFORT:
NET TYPE UNITS OF GEAR
Gill Nets
Trap Nets
Seines
Angling
4
4
5
TOTAL HOURS FISHED
72.5
.. 85.0
2.0
NUMBER OF FISH CAUGHT:
SPECIES GILL NET
Yellow Perch
Largemouth Bass
Smallmouth Bass
Bluegill
Pumkinseed
Rock Bass
Bluntnose Minnow
Common Shiner
Northern Pike
83
3
1
0
0
8
0
4
7
TRAP NET SEINE
1
0
0
51
2
3
0
0
0
2
0
0
9
3
4
117
0
0
ANGLING
0,
0
0
1
0
3
0
0
0
SPECIES
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Largemouth Bass
ELS-II INDIVIDUAL FISH DATA
FISH ID LENGTH WEIGHT
168
169
170
171
172
173
174
117
118
110
116
118
109
431
11
11
11
11
12
13
1060
B-94
-------
NAME: OSTRANDER LAKE ID: 2B3-071
LONGITUDE: 86-36'43"W LATITUDE: 46-10'05"N STATE: MI
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Northern Pike
Largemouth Bass
Largemouth Bass
Smallmouth Bass
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
Yellow Perch
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
125
114
130
114
116
121
115
118
131
115
734
577
506
549
536
581
555
356
330
365
121
196
118
111
115
109
125
130
116
106
129
130
122
120
116
15
14
18
13
10
14
13
14
18
11
2400
1250
790
950
950
1260
1130
550
320
560
10
74
11
10
11
9
15
19
11
11
18
17
11
15
14
* U.S. GOVERNMENT PRINTING OFFICE: 1990 -795-30 2/2 3 0 8 it
B-95
-------
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