v-xEPA
United States
Environmental Protection
Agency
Office of Research
and Development
Washington DC 20460
Unpublished
Report
SURFACE WATERS
IMPLEMENTATION PLAN -
1992 NORTHEAST LAKES
PILOT SURVEY
Environmental Monitoring
and Assessment Program
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September 1992
ENVIRONMENTAL MONITORING AND ASSESSMENT PROGRAM:
SURFACE WATERS IMPLEMENTATION PLAN -
1992 NORTHEAST LAKES PILOT SURVEY
Environmental Monitoring Systems Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Las Vegas, Nevada 89193-3478
Environmental Research Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Corvallis, Oregon 97333
Environmental Monitoring Systems Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Cincinnati, Ohio 45219
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ENVIRONMENTAL MONITORING AND ASSESSMENT PROGRAM:
SURFACE WATERS IMPLEMENTATION PLAN -
1992 NORTHEAST LAKES PILOT SURVEY
edited by
K. M. Peres"
with contributions from:
S. G. Paulsenb, D. P. Larsen6, P. R. Kaufmann", T. Whittiei*.
J. R. Baker", D. V. Peck", J. M. Downey", J. Stoddard0,
W. L Kinney', C. Burch-Johnson", S. Dixit9, R. Stemberger11,
A. Herlihy", A. Moors', and R. Yeardley1
" Lockheed Engineering & Sciences Company
b Environmental Research Center, University of Nevada-Las Vegas
0 U.S. Environmental Protection Agency, Environmental Research Laboratory, Corvallis.Oregon
d Utah State University
e ManTech Environmental Technologies, Inc.
f U.S. Environmental Protection Agency, Environmental Monitoring Systems Laboratory, Las Vegas,
Nevada
9 Queens University
h Dartmouth College
1 University of Maine
' Technology Applications, Inc.
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NOTICE
This document is intended for internal Agency use only. Mention of trade names or commercial products
does not constitute endorsement or recommendation for use.
111
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ABSTRACT
This document was generated in draft form for the Environmental Monitoring and Assessment Program-
Surface Waters peer review panel, which met in Dallas, Texas in April, 1992. The document outlines the
proposed implementation plan for the Environmental Monitoring and Assessment Program's Surface
Waters Northeast Lakes Pilot Survey, to be conducted from July through September, 1992. The pilot
survey will evaluate not only the utility of the indicators selected thus far for the Surface Waters
component, but will provide an evaluation of the methods that have been identified for collection and
analysis of samples.
This implementation plan is not intended to be a step-by-step delineation of field activities planned for the
pilot; for more detailed discussion of concept, approach, and issues, please refer to either the Surface
Waters Research Plan (Paulsen, et al., 1991) or the respective subject plans (i.e., the quality assurance
project plan, the methods manual, the field operations manual, and the information management plan).
This plan outlines the objectives of th^ field pilot activities and the questions which we expect to answer
as a result of these activities. In addition, the plan contains a description of the indicators, the
measurement variables included in each indicator, the design rationale, and details including site selection
criteria and a list of selected sites. Brief descriptions of quality assurance, logistical considerations, and
the information management approach are also presented.
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TABLE OF CONTENTS
Section Page
Notice iii
Abstract iv
Tables x
Figures xi
Acknowledgments xii
Acronyms and Abbreviations xiii
1 INTRODUCTION 1 of 2
1.1 Overview of the Environmental Monitoring and
Assessment Program 1 of 2
1.2 Overview of EMAP-Siirface Waters 2 of 2
2 PILOT OBJECTIVES 11 of 8
2.1 Objectives of the 1992 Northeast Lakes Pilot Survey 1 of 8
2.2 Questions to be Answered Prior to Full-Scale Implementation 1 of 8
2.3 Pilot Study Description and Objectives 3 of 8
2.3.1 Regional Variability Assessment Study 4 of 8
2.3.2 TIME Demonstration 6 of 8
3 INDICATORS OF ECOLOGICAL CONDITION 1 of 35
3.1 Introduction 1 of 35
3.2 Trophic State 2 of 35
3.2.1 Overall Objective 2 of 35
3.2.2 Summary of FY91 Activities 2 of 35
3.2.3 Objectives for FY92 2 of 35
3.2.4 Data Collection Plan 3 of 35
3.2.4.1 Plot Design 3 of 35
3.2.4.2 Methods Summary 3 of 35
3.2.4.3 Collection Procedure 3 of 35
3.2.5 Data Analysis Plan 3 of 35
3.2.5.1 Index Definition and Development 3 of 35
3.2.5.2 Index Interpretation 3 of 35
3.2.5.3 Proposed Statistical Summary 4 of 35
3.2.5.4 Data Verification and Validation 4 of 35
3.3 Sedimentary Diatom Assemblage 4 of 35
3.3.1 Overall Objectives 4 of 35
3.3.2 Summary of FY91 Activities 4 of 35
3.3.3 Objectives for FY92 : 5 of 35
3.3.4 Data Collection Plan .. 5 of 35
3.3.5 Data Analysis Plan 6 of 35
3.3.5.1 Methods 6 of 35
3.3.5.2 Schedule 6 of 35
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TABLE OF CONTENTS (Continued)
Section Page
3.3.6 Index Definition, Development, Interpretation, and
Statistical Summary 6 of 35
3.3.7 Data Verification and Validation 7 of 35
3.4 Macroinvertebrate Assemblage 7 of 35
3.4.1 Overall Objectives 7 of 35
3.4.2 Summary of FY91 Activities 7 of 35
3.4.2.1 Mud Bottom Habitat 7 of 35
3.4.2.2 Mixed Vegetation Bed Habitat 8 of 35
3.4.2.3 Mixed Rock and Woody Debris Habitat . 8 of 35
3.4.2.4 Miscellaneous Habitats 8 of 35
3.4.3 Status of FY91 Analyses 8 of 35
3.4.4 Objectives for FY92 9 of 35
3.4.5 Data Collection Plan 9 of 35
3.4.5.1 Plot Design 9 of 35
3.4.5.2 Methods Summary 9 of 35
3.4.6 Data Analysis Plan 10 of 35
3.4.6.1 Index Definition and Development 10 of 35
3.4.6.2 Index Interpretation 10 of 35
3.4.6.3 Proposed Statistical Summary 11 of 35
3.4.6.4 Data Verification and Validation 11 of 35
3.5 Zooplankton 11 of 35
3.5.1 Overall Objectives 11 of 35
3.5.2 Summary of FY91 Activities 12 of 35
3.5.3 Objectives for FY92 12 of 35
3.5.4 Data Collection Plan 12 of 35
3.5.4.1 Plot Design 12 of 35
3.5.4.2 Methods Summary 13 of 35
3.5.4.3 Collection Procedure 13 of 35
3.5.5 Data Analysis Plan 13 of 35
3.5.5.1 Index Definition and Development 13 of 35
3.5.5.2 Index Interpretation 13 of 35
3.5.5.3 Proposed Statistical Summary 13 of 35
3.5.5.4 Data Verification and Validation 14 of 35
3.6 Fish Assemblage 14 of 35
3.6.1 Overall Objectives 14 of 35
3.6.2 Summary of FY91 Activities 14 of 35
3.6.3 Objectives for FY92 15 of 35
3.6.3.1 Collecting an Index Sample of Fish Assemblages 15 of 35
3.6.3.2 Developing Indices of Fish Assemblage Conditions 16 of 35
3.6.3.3 Evaluating a Portable Electrofishing System 16 of 35
3.6.3.4 Providing Samples for Tissue Contaminant Analyses 16 of 35
VI
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TABLE OF CONTENTS (Continued)
Section Page
3.6.4 Data Collection Plan 17 of 35
3.6.4.1 Plot Design 17 of 35
3.6.4.2 Collection Procedure 18 of 35
3.6.5 Data Analysis Plan 18 of 35
3.6.5.1 Index Definition, Development, and Interpretation 19 of 35
3.6.5.2 Proposed Statistical Summary 20 of 35
3.6.5.3 Data Verification and Validation 20 of 35
3.7 Bird Assemblage 20 of 35
3.7.1 Overall Objectives 20 of 35
3.7.2 Summary of FY91 Activities 21 of 35
3.7.3 Objectives for FY92 21 of 35
3.7.4 Data Collection and Analysis 21 of 35
3.7.4.1 Proposed Statistical Summary 22 of 35
3.7.4.2 Data Verification and Validation 22 of 35
3.8 Chemical Contaminants in Fish 23 of 35
3.8.1 Overall Objectives 23 of 35
3.8.2 Summary of FY91 Activities , 23 of 35
3.8.3 Objectives for FY92 23 of 35
3.8.4 Data Collection Plan 24 of 35
3.8.4.1 Plot Design 24 of 35
3.8.4.2 Methods Summary 24 of 35
3.8.4.3 Collection Procedure 24 of 35
3.8.5 Data Analysis Plan 25 of 35
3.8.5.1 Index Definition and Development 25 of 35
3.8.5.2 Proposed Statistical Summary 25 of 35
3.8.5.3 Data Verification and Validation 25 of 35
3.9. Physical Habitat Quality 27 of 35
3.9.1 Overall Objectives 27 of 35
3.9.2 Summary of FY91 Activities 27 of 35
3.9.3 Objectives for FY92 30 of 35
3.9.4 Data Collection and Analysis 31 of 35
3.9.4.1 Shoreline/Littoral Physical Habitat Survey 31 of 35
3.9.4.2 Rapid Protocol for Bathymetry and Aquatic Macrophytes 31 of 35
3.9.4.3 Other Physical Habitat Variables 32 of 35
3.9.5 Data Verification and Validation 32 of 35
3.10 Water Quality 32 of 35
3.10.1 Overall Objectives 32 of 35
3.10.2 Summary of FY91 Activities 33 of 35
3.10.3 Objectives for FY92 33 of 35
Vll
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TABLE OF CONTENTS (Continued)
Section Page
3.10.4 Data Collection Plan 33 of 35
3.10.4.1 Plot Design 33 of 35
3.10.4.2 Methods Summary 33 of 35
3.10.4.3 Collection Procedure 33 of 35
3.10.5 Data Analysis Plan 34 of 35
3.10.5.1 Index Definition and Development 34 of 35
3.10.5.2 Index Interpretation 34 of 35
3.10.5.3 Proposed Statistical Summary 34 of 35
3.10.5.4 Data Verification and Validation 34 of 35
4 DESIGN 1 of 9
4.1 Introduction and Objectives 1 of 9
4.2 Selection of Grid Lakes 1 of 9
4.2.1 Frame and Tier 1 Sample Selection 2 of 9
4.2.2 Identifying Frame Errors and Lakes for Field Sampling 2 of 9
4.2.3 Stratification Strategies 3 of 9
4.3 Tier 2 Sample Selection 4 of 9
4.3.1 Maintaining Spatial Distribution in the Tier 2 Sample 4 of 9
4.4 Grid Intensification 5 of 9
4.5 Annual Repeat Visits 5 of 9
5 FIELD OPERATIONS 1 of 6
5.1 Overview of Field Operations 1 of 6
5.2 EMAP-SW Regional Probability Lakes 1 of 6
5.3 TIME Project Lakes 5 of 6
5.4 Indicator Evaluation Lakes 5 of 6
6 QUALITY ASSURANCE PROGRAM 1 of 15
6.1 Data Quality Requirements 1 of 15
6.2 Synopsis of QA/QC Activities 3 of 15
6.3 Sampling Design and Site Selection 3 of 15
6.4 General Field and Laboratory Operations 5 of 15
6.5 QA/QC Activities for Indicator Research and Development Programs 6 of 15
6.5.1 Water Chemistry and Trophic State Indicators 6 of 15
6.5.2 Sedimentary Diatom Assemblage Indicator 9 of 15
6.5.3 Zooplankton Assemblage Indicator 10 of 15
6.5.4 Fish Assemblage Indicator 10 of 15
6.5.5 Riparian Bird Assemblage Indicator 11 of 15
6.5.6 Benthic Macroinvertebrate Assemblage Indicator 11 of 15
Vlll
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TABLE OF CONTENTS (Continued)
Section Page
6.5.7 Fish Tissue Contaminant Indicator 12 of 15
6.5.8 Physical Habitat Indicator 12 of 15
6.6 Data Review, Verification, and Validation 13 of 15
7 INFORMATION MANAGEMENT 1 of 7
7.1 Introduction 1 of 7
7.2 FY92 Information Management Activities 1 of 7
7.2.1 Field Forms and Sample Labels 2 of 7
7.2.2 Analytical Laboratory Results 2 of 7
7.2.3 Sample Tracking/Shipping/Reporting System 2 of 7
7.2.4 Data Transfer 3 of 7
7.2.5 Logistics Lake Information Data Entry/Access System 4 of 7
7.2.6 Field Data Entry System , 4 of 7
7.2.7 Field and Analytical Data Bases 5 of 7
7.2.8 Electronic Field Data Entry Prototype 5 of 7
7.2.9 Data Documentation, Access, and Management Prototype 6 of 7
7.2.10 User Involvement and Requirements 7 of 7
8 REFERENCES 1 of 5
IX
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TABLES
Table Page
3-1 Indicator Measurements Proposed for the 1992 EMAP-SW
Northeast Lakes Pilot Survey 2 of 35
3-2 Analytes to be Measured in Fish Tissue for the 1992 EMAP-SW
Northeast Lakes Pilot Survey 26 of 35
3-3 Lake Physical Habitat Indices to be Tested for EMAP-SW 28 of 35
3-4 List of EMAP-SW/EMAP-TIME Chemical Measurements and
Methodologies 35 of 35
4-1 National Lake Target Population, Tier 1 and Tier 2 Lakes,
with Inclusion Probabilities 5 of 9
5-1 Proposed Location of Lake Areas Assigned to Sampling Teams 2 of 6
5-2 Sampling Team Weekly Activities Schedule 3 of 6
5-3 Number and Type of Samples to be Collected, EMAP-SW FY92
Northeast Lakes Pilot Survey 5 of 6
6-1 Elements of the Quality Assurance Program for EMAP-SW 4 of 15
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FIGURES
Figure Page
2-1 Lake sampling scheme for the 1992 EMAP-SW Northeast Lakes Pilot
Survey and TIME Regional Lake Study. 5 of 8
2-2 Two regions of interest for acidic deposition in which the base
EMAP grid will not provide enough coverage. 7 of 8
4-1 Clusters used for the selection of Tier 2 lakes for the 1992
Pilot Survey. 7 of 9
4-2 Locations of Tier 2 lakes selected for a national lake survey,
corresponding to the second year of a four year EMAP cycle. 8 of 9
4-3 Super clusters used to select a subset of lakes monitored in
1991, which will be revisited during 1992-1994. One lake from
each super cluster will be revisited. Original 1991 clusters
are delineated by dashed lines. 9 of 9
5-1 Sampling activities for boat crews, EMAP-SW FY92 Northeast
Lakes Pilot Survey. 4 of 6
6-1 QA/QC activities associated with field operations. 7 of 15
6-2 QA/QC activities associated with laboratory operations. 8 of 15
6-3 Data review and verification process. 14 of 15
6-4 Generalized process of data validation. 15 of 15
XI
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ACKNOWLEDGMENTS
Critical review comments on this document provided by Dan Heggem (U.S. Environmental Protection
Agency, Environmental Monitoring Laboratory, Las Vegas, Nevada) are gratefully appreciated. The
exceptional word processing provided by Jan Aoyama (Lockheed Engineering and Sciences Company)
and Janet Mello (ManTech, Corvallis, OR) has been invaluable in the completion of this document.
Xll
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ACRONYMS AND ABBREVIATIONS
AAS Atomic Absorption Spectroscopy
AERP Aquatic Effects Research Program
ALSO Adirondack Lakes Survey Corporation
ANC acid neutralizing capacity
BBS Breeding Bird Survey '
BRC Biologically Relevant Chemistry (Survey)
CCA canonical correspondence analysis
cdfs cumulative distribution functions
chl a chlorophyll a
DBMS data base management system
DDT dichlorodiphenyltrichlorethane
DIC dissolved inorganic carbon
DITI diatom-based trophic index •
DLGs digital line graph (files)
DO dissolved oxygen
DOC dissolved organic carbon
DQOs data quality objectives
EMAP Environmental Monitoring and Assessment Program
EMAP-SW Environmental Monitoring and Assessment Program-Surface Waters
EMSL-CIN Environmental Monitoring Systems Laboratory-Cincinnati
EMSL-LV Environmental Monitoring Systems Laboratory-Las Vegas
EPA U.S. Environmental Protection Agency
FAX facsimile
FY fiscal year
FY91T1 fiscal year 1991, Tier 1
FY92T2 fiscal year 1992, Tier 2
GC/ECD gas chromatography/electron-capture detector
GIS Geographic Information System
GPS Global Positioning System
ha hectare
HBI Hilsenhoffs Biotic Index
ICP inductively coupled plasma
ID identification
IES Indicator Evaluation Study
IFD Industrial Facility Discharge File
LESC-LV Lockheed Engineering & Sciences Company, Las Vegas
MATC maximum allowable tissue concentration
METI ManTech Environmental Technologies, Incorporated
NIST National Institute of Standards and Technology
NSWS National Surface Water Survey
PAHs polynuclear aromatic hydrocarbons
PCA principal component analysis
PCBs polychlorinated biphenols
PE performance evaluation
xm
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FOR portable data recorder
PIRLA Paleolimnological Investigations of Recent Lake Acidification
ppm parts per million
QA quality assurance
QA/QC quality assurance/quality control
QAPjP quality assurance project plan
QC quality control
SCS Soil Conservation Service
SO Secchi disk transparency
SRM standard reference material
TAI Technology Applications, Incorporated
TIME Temporally Integrated Monitoring of Ecosystems
TL total length
TP total phosphorus
T1Y1 Tier 1 Year 1
USFWS United States Fish and Wildlife Service
USGS United States Geological Survey
VAX Victual Address Extension
xiv
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Section 1
September 1992
Page: 1 of 2
SECTION 1
INTRODUCTION
1.1 OVERVIEW OF THE ENVIRONMENTAL MONITORING AND ASSESSMENT PROGRAM
The U.S. Environmental Protection Agency (EPA), in cooperation with other federal and state
organizations, has designed the Environmental Monitoring and Assessment Program (EMAP) to
periodically assess the condition of the Nation's ecological resources. The program will assist
decision makers, both within and outside the Agency, to evaluate the cumulative effectiveness of
current environmental regulations in protecting the Nation's natural resources, prioritize issues of
concern and regions in which action is needed, and set environmental policy. The Environmental
Monitoring and Assessment Program is a strategy to identify and bound the extent, magnitude, and
location of degradation or improvement in the environment. When EMAP has been fully implemented,
the program will contribute to answering the following critical questions:
• What is the current extent of our ecological resources (e.g., estuaries, lakes, streams, forests,
grasslands, etc.) and how are they distributed geographically?
• What percentage of resources appears to be adversely affected by pollutants or other
anthropogenic environmental stresses?
• Which resources are degrading or improving, where, and at what rate?
• What are the relative magnitudes of the most likely causes of adverse effects?
• Are adversely affected ecosystems improving as expected in response to cumulative effects of
control and mitigation programs?
To answer these questions, the various, integrated monitoring networks within EMAP will focus on the
following objectives:
• Estimate the current status, extent, changes, and trends in indicators of condition of the Nation's
ecological resources on a regional basis with known confidence.
• Monitor indicators of pollutant exposure and habitat condition and seek associations between
human-induced stresses and ecological condition that identify possible causes of adverse effects.
• Provide periodic statistical summaries and interpretive reports on ecological status and trends to
the EPA Administrator and to the public.
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Section 1
September 1992
Page: 2 of 2
1.2 OVERVIEW OF EMAP-SURFACE WATERS
EMAP-Surface Waters (EMAP-SW) is intended to estimate the condition of lakes, reservoirs, streams,
and rivers on a national scale as well as on relatively broad, regional scales. The design of the
program, which utilizes an integrated, probability-based monitoring framework based on a systematic
grid, is explained in detail in Paulsen, et al., 1991 and in Section 4 of this document. Data obtained
from the program will allow estimation of the spatial extent and geographical distribution of various
classes of surface waters. Additionally, the program will estimate the current status and changes or
trends in indicators of ecological condition.
The EMAP-SW Resource Group uses a top-down approach to evaluate the condition of the lakes and
streams with respect to ecological attributes and societal values of concern (see Paulsen, et al., 1991).
The strategy chosen for EMAP-SW employs the following characteristics that will allow estimation, with
known confidence, of indicators of the ecological condition of regional surface water populations:
• Precise definition of surface water target populations and associated sampling units and the
selection of an explicit frame for listing or identifying all potential sampling units within each target
population.
• Probability-based sample site selection from the population frame; a uniform grid and clustered
sampling approach will be used to obtain a randomized, systematic sample of surface waters
with a geographical distribution reflecting that of the population.
• Representation of ecological conditions in sample lakes and streams using biological, chemical,
and physical indicators employing an index concept.
• A documented set of uniform sampling and analytical methods for a suite of response, exposure,
and stressor indicator measurements.
• A documented program of rigorous quality assurance/quality control (QA/QC), and assessment.
This document describes the proposed plan for continuing pilot investigations of the EMAP-SW lakes
program in the northeastern United States. The pilot, which will be conducted in the states of
Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Rhode Island, and
Vermont from July through September of 1992, will continue the evaluation of the regional probability
design and the performance of the biological indicators selected thus far.
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Section 2
September 1992
Page 1 of 8
SECTION 2
PILOT OBJECTIVES
2.1 OBJECTIVES OF THE 1992 NORTHEAST LAKES PILOT
Prior to full-scale implementation of EMAP-SW, a number of questions must be answered through a
combination of analyses of existing data and of data derived from new field activities. We distinguish
two types of field activities to undertake prior to full-scale implementation. These are pilot projects and
demonstration projects. The pilot projects are intended to answer .questions about proposed
indicators (e.g., plot design, indicator sensitivity to various stresses, magnitude of variance
components, alternative methods evaluations, and logistical constraints). Pilot studies are not
primarily intended to provide regional estimates of condition but may provide these estimates for a few
indicators. A demonstration activity may be designed to answer many of the same questions outlined
in Section 1, but also has as a fundamental objective the demonstration of the ability to estimate the
condition of regional populations. The first pilot activity for EMAP-SW was conducted in 1991 on lakes
in the northeastern United States. We anticipate additional pilots and demonstrations in various
regions of the country over the next three to four years, but will continue work in the northeast for the
foreseeable future. The pilot activity described in this document will build upon the questions
addressed in 1991. In conjunction with well designed follow-up studies, this pilot should provide the
information needed to fully implement the program in the northeast.
2.2 QUESTIONS TO BE ANSWERED PRIOR TO FULL-SCALE IMPLEMENTATION
The basic questions which need to be answered prior to full-scale implementation of EMAP-SW are:
1. What indicators/measurements will be used as part of the long-term monitoring
program?
2. What is the optimal sampling period?
3. What is the plot design within each lake for each indicator?
4. How will each indicator be used to describe condition of lakes or probable cause of
impaired and unimpaired conditions, and how well can this be statistically described?
The following are more specific questions which require answers prior to implementation of EMAP-SW:
1. What is the relative magnitude of the natural spatial variability compared with the
variability associated with temporal patterns in the index period, spatial variability
associated with the sample unit plot design, as well as crew and measurement variability
for identified biological response indicators (i.e., assemblages of fish, zooplankton,
sedimentary diatoms, benthic macroinvertebrates, and birds, in a set of regional lakes),
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Section 2
September 1992
Page 2 of 8
chemical-exposure, and physical habitat indicators? How does the magnitude of these
components impact our ability to describe status and trends in condition? Components
of variance which may need to be described include:
a Differences among lakes within a region resulting from true differences in different
lakes (true population variance).
b. Spatial and temporal differences at a lake within a given index period (index
variance).
c. Differences within index samples resulting from imprecision in sample collection,
sample processing, and sample analyses; and differences among index samples
resulting from different teams and different laboratories (measurement variance).
d. Year-to-year site variation (annual variance).
e. Spatial correlation effects within a region.
f. Temporal correlation effects within a region.
2. A variety of habitat types exist within any particular lake and the heterogeneity of these
varies between lakes. The basic question is, how do we index a lake at a particular time
for a particular indicator? For each biological-response indicator, chemical-exposure
indicator, and physical-habitat indicator, a series of questions must be answered relative
to habitat types:
a. How many discrete habitats need to be recognized and sampled in the regional set
of lakes?
b. How much sample replication is needed for each habitat within each lake?
c. How will data from the different habitats in each lake be combined to provide a
result for the whole lake to form the regional population among lakes?
d. Can a sample from a single location within the lake be used as an index of lake
condition?
3. Several questions exist concerning the logistics and variability in on-site performance of
sampling teams:
a. Can teams conduct the field sampling in the time frame described?
b. Can different teams be effectively trained, or will the variance be so great that the
program objectives will be compromised?
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Section 2
September 1992
Page 3 of 8
c. Can the field logistics be effectively monitored and controlled across a region?
4. Concerning the ability to define trends in biological-response indicators:
a. What types of rotational sampling schemes are needed to increase sampling
frequency so that trends can be discerned in reasonable time frames given the
levels of variance observed for the identified biological-response indicators?
b. What test will be used for trends in population data?
c. What is the magnitude of regional trend detectable given the indicator variability
and proposed design?
5. A host of subpopulations are of concern to various clients:
a. How will critical subpopulations of interest be identified?
b. Can post-stratification be used?
6. Can the impaired/unimpaired (nominal/subnominal) approach for defining conditions be
made to work for each of the biological-response indicators?
Questions 4, 5, and 6 above can be answered independently of field pilot activities. However,
answers to questions 1 through 3 require interpretation of existing data and data derived from a series
of carefully designed lake pilot studies. These field activities must be followed by exhaustive data
interpretation and reevaluation of the overall design and approach. In most instances, because of the
lead time necessary to plan each year's field effort, the results of a particular year's field pilot will not
be fully interpreted in time to influence the immediately succeeding field effort. We are designing the
pilot activities in two-year time increments; that is, results of the 1991 field pilot will be used to direct
the 1993 efforts. The 1992 pilot is designed to answer questions that we simply could not afford to
address during 1991 and will be used to make course corrections in our 1994 efforts.
This document describes the role the 1992 field pilot wHI play in answering some of the critical
questions outlined. This work will be complemented by extensive evaluation of existing data and
computer simulation.
2.3 PILOT STUDY DESCRIPTION AND OBJECTIVES
In this section, the questions to be addressed during the FY92 pilot are described. Further details on
specific indicators can be found in Section 3, while the details of site selection are addressed in
Section 4.
A critical aspect of the 1991 pilot was to determine specifically what the plot design for fish, riparian
birds, and lake physical habitat would be. That is, how will these indicators be indexed at each lake?
Having addressed these questions, an objective of the 1992 pilot will be to sample these indicators on
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Section 2
September 1992
Page 4 of 8
a probability set of lakes to estimate the natural spatial variability. This variability will be compared
with a confounded estimate of index plus measurement variability determined from repeat sampling of
these indicators on return visits to the lakes.
Figure 2-1 shows the basic components of the field pilot for 1992. The first is a demonstration of the
EMAP-SW design for sampling lakes on a regional scale. For this component, lakes to be sampled
were selected from the grid using the selection procedures described in Section 4.2. The second
continues the second year of sampling for the Temporally Integrated Monitoring of Ecosystems (TIME)
project (see Section 3.2.1.2). The difference between these two components is that the base EMAP
grid has been intensified in two regions where subpopulations of lakes are especially sensitive to
acidic deposition and sample sizes selected from the base grid were determined to be insufficient for
trend detection. At these additional sites, only chemistry important to acidic deposition will be
measured.
2.3.1 Regional Variability Assessment Study
In 1991, we generated information on true population variance and a confounded estimate of index
and measurement variance for trophic state indicators, zooplankton parameters, sedimentary diatoms
parameters, sediment toxicity, and water chemistry variables. We are in the process of evaluating the
relative magnitude of these variance components to determine the ability to describe status and detect
trends for each indicator. We will continue to collect these measurements on the full set of regional
probability lakes this year (~60 lakes) to improve our estimates of natural population variance. In
1992, we will determine similar variance components for an additional set of biological parameters (i.e.,
fish community structure, and riparian bird composition), as well as for the physical habitat measures
(Figure 2-1). This will be accomplished by collecting these data on 40 regional probability lakes (a
subset of the 60 mentioned above) and revisiting 20 of these lakes during the index period. These
revisits will provide a confounded measure of index and measurement variance. If the magnitude of
this confounded variance estimate is large relative to the natural population variance, then in future
years, we will need to investigate the specific components of the index and measurement variances to
determine which components can be reduced. If the relative magnitude is small, then the variability
associated with the index period and measurement errors will have little impact on our status
descriptions and trend detections. The remaining 20 lakes (a subset of the 60 probability lakes
mentioned above), or core-level lakes, will be sampled for a subset of indicators, which does not
include fish and bird assemblages or physical habitat
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Section 2
September1! 992
Page 5 of 8
EMAP SURFACE WATERS
RESOURCE GROUP
1
| NORTHEAST LAKES PILOT SURVEY (FY92) | | TIME REGIONAL LAKE SURVEY |
FIgur* 2-1. Lakt sampling scheme for the 1992 EMAP-SW Northeast Lakes Pilot Survey and TIME Regional Lake
Study.
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Section 2
September 1992
Page 6 of 8
Approximately 10 of the lakes sampled last year will be included in this and succeeding sampling
efforts to begin estimation of interannual variability, and to look at the variability associated with
regional subsets of lakes.
This population variability assessment study will estimate:
• natural population variability (regional spatial variability),
• index period variability confounded with total measurement variability,
• interannual variability and subset differences, and
• regional status for selected indicators.
This field study will specifically not estimate:
• spatial or temporal correlation effects within a region.
• differences at a site between different index periods.
• specific components of measurement variability.
• regional estimates of condition for the full suite of EMAP-SW indicators.
2.3.2 TIME Demonstration
As described in Paulsen et al., 1991 and Stoddard, 1990, the reauthorization of the Clean Air Act
mandates an assessment of the effects on aquatic systems of reductions in emissions. The TIME
project is a special program within EMAP-SW which will address the effectiveness of the changes
which might result from the Clean Air Act Amendments. The regional population descriptions
produced by the TIME project will result from enhancement of the general EMAP-SW design. The
base EMAP density will provide approximately 60 probability sites annually for use in the TIME project.
Based on the results presented in Linthurst, et al. (1986), two regions of high interest (Adirondacks
and southern Vermont and New Hampshire, see Figure 2-2) will not be adequately evaluated with this
base density (see Paulsen, et al., 1991 arid Stoddard, 1990). A three-fold increase in the grid density
in these regions results in the selection of approximately an* additional 30 sites in each year of a four-
year rotational cycle. Section 4 contains details of the site selection process for this project.
Indicators at the TIME sites will be chemical-exposure indicators (sulfate, nitrate, anions, and other
cations) intended to estimate the acidification status of these systems.
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Rgure 2-2. Two regions of Interact for acidic deposition In which the base EMAP grid will not provide
enough coverage. The grid wee Intensified by a factor of 3 In order to provide an additional
28 samples per year for the evaluation of acidification.
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This year's TIME project will:
• Estimate the Year-2 acidification status of a variety of sensitive lake subpopulations in the
Northeast. This is the second year of what is expected to be at least a 10-year period before
trends which might result from changes in the Clean Air Act are expected to be detectable.
• Evaluate the effectiveness of the design and site selection process in providing the needed
coverage of important lake subpopulations.
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SECTION 3
INDICATORS OF ECOLOGICAL CONDITION
3.1 INTRODUCTION
In the following section, the overall objectives of the EMAP-SW program are presented for each
indicator followed by a summary of the previous year's activities and the specific pilot objective for that
indicator for the current year. Following a brief outline of the data collection method(s) are the data
analysis plan and interpretation scenarios .proposed for each indicator.
EMAP has identified four types of indicators for determining ecological condition: response, exposure,
habitat, and stressor. These categories have been provided as a guideline for use in the selection,
evaluation, and development of the proposed indicators for EMAP-SW.
• Response Indicators are attributes that quantify the integrated response of ecological resources to
individual or multiple stressors. Examples of this kind of indicator include fish assemblage, diatom
assemblage, and zooplankton assemblage.
• Exposure Indicators are physical, chemical, and biological attributes that can be used to suggest
pollutant exposure and assist in the diagnosis of probable cause. In addition, exposure indicators
are extremely critical for assessing water body types and expected conditions for aquatic systems.
Examples of exposure indicators are chemical contaminants in fish, and ambient nutrient
concentration.
• Habitat Indicators are attributes that describe the condition of the environment. They are used to
suggest whether alteration or disturbance of the physical habitat is the cause of poor condition in
response indicators. Examples of this type of indicator are surface area, lake level, or hydrologic
residence time.
• Stressor indicators are economic, social, or engineering attributes that are used to identify the
most probable sources of environmental impairment or exposure to impact. Some examples of this
indicator type are human population density, land-use patterns, pesticide application rates, point-
source pollutant loadings, and stocking and harvest records.
Table 3-1 provides a list of indicator measurements (grouped by indicator type) proposed for the
Northeast Lakes Pilot. Each indicator is described in detail in the following sections.
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TABLE 3-1. INDICATOR MEASUREMENTS PROPOSED FOR THE 1992 EMAP-SW NORTHEAST LAKES PILOT SURVEY
Response Indicators Habitat Indicators
Trophic State Index Physical Habitat Quality
Sediment Diatom Assemblage
Benthic Macroinvertebrate Assemblage Stressor Indicators
Zooplankton Assemblage Land Use
Fish Assemblage Landscape Cover
Riparian Bird Assemblage
Exposure Indicators
Fish Tissue Contaminants
Fish Pathology
Water Chemistry
3.2 TROPHIC STATE
3.2.1 Overall Objective
Estimate the proportion of lakes that are in various trophic categories (oligotrophic, mesotrophic,
eutrophic, dystrophic) based primarily on measurements of chlorophyll a (chl a), macrophyte cover,
total phosphorus (TP), total nitrogen (TN), and Secchi disk transparency (SD).
3.2.2 Summary of FY91 Activities
During the FY91 EMAP-SW Northeast Lakes Pilot Survey, trophic state measurements were taken from
111 lakes: 19 indicator evaluation lakes, 28 augmented grid lakes for TIME, and 64 grid lakes. Using
the grid lake data, initial estimates of trophic condition can be made for northeast lakes. The data will
also provide the first year of data for assessing trends in condition.
Repeat samples, collected roughly 2-3 weeks apart, were taken in 22 of the grid lakes. In 4 grid lakes,
all 3 field crews sampled the lakes within a 1-2 day period to assess crew variability. In addition,
natural audit samples were analyzed to assess analytical precision and accuracy. From these data,
the variance components associated with analytical, crew, within-index period, and variability in trophic
state indicators will be quantified.
3.2.3 Objectives for FY92
• Assess annual variability in trophic state indicators.
• Develop lake trophic state indices (using combinations of TP, TN, chl a, and macrophyte
abundance) to assess trophic health.
• Gather data from the Year 2 grid lakes to make more robust estimates of trophic condition in the
northeast.
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• Evaluate associations between trophic state and landscape stressor indicators, and other biological
response indicators (diatoms, zooplankton, benthos, and fish assemblage).
3.2.4 Data Collection Plan
3.2.4.1 Plot Design
Lakes selected for sampling in FY92 are taken from the Year 2 EMAP hexagons in the northeast. In
addition, 10 of the Year 1 (FY91) grid lakes will be revisited to assess between year variability. Water
samples collected for TP, TN, and chl a analyses will be taken from a depth of 1.5m, and SD will be
measured at the deepest point in the lake according to protocols described in the FY92 EMAP-SW
Fields Operations and Training Manual (Merritt and Metcalf, in preparation). Macrophyte abundance
and density will also be assessed as described in Merritt and Metcalf (in preparation).
3.2.4.2 Methods Summary
Analytical protocols to be used for water sample analyses are given in Table 3-4.
3.2.4.3 Collection Procedure
Water samples will be collected from the index location using a Van Dom sampler (Merritt and Metcalf,
in preparation). From the Van Dorn, one 4L Cubitainer will be filled for analysis of trophic state
chemical variables. Samples will be kept in a cooler on ice and shipped by overnight courier to the
analytical laboratory for processing and analysis. Water from the Van Dorn (SOOmL) will also be
filtered, and the filter preserved frozen for chl a analysis. In situ measurements of SD and
DO/temperature depth profiles will be made as described in Merritt and Metcalf (in preparation).
3.2.5 Data Analysis Plan
3.2.5.1 Index Definition and Development
For trophic state water chemistry, lakes will be indexed using a single, deep water epilimnetic sample.
The basic trophic state measurements need to be combined into an overall index of trophic state. A
number of methods currently exist and will be evaluated. Possible candidates include Carlson's
(1977) trophic state index ( a log scale rating from 0-100); a point system based on TP, DO depletion,
macrophytes, and chl a such as that used by some states; or a scoring based on the loadings on the
first principal components analysis axis using all the trophic state chemical variables.
3.2.5.2 Index Interpretation
Status and trends in trophic state will be assessed through measurements of TP, TN, chl a, SD, and
macrophyte abundance. Estimates of indicator sampling precision, wrthin-index period variability from
FY91 data, information from FY92 data on between-year and regional variability, plus data from
available long-term data sets will be used to quantify these variance components for each chemical
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variable. This quantification will allow the assessment of significance in observed trends in trophic
state, as well as assessment of bias in the EMAP-SW population estimates.
3.2.5.3 Proposed Statistical Summary
Statistical summaries of the population mean, standard deviation, quartiles, and a plot for the cdf will
be made for each measured trophic state chemical variable and an overall trophic state indicator that
is yet to be developed. These population estimates will be made for both number and area
weightings. Estimates will also be made for the number and area of the lake resource in different
trophic categories.
3.2.5.4 Data Verification and Validation
Data will be verified and validated according to flow charts and protocols described in the EMAP-SW
QA Plan (Peck, in preparation). Verification primarily checks the chemical consistency of the data
within the sample (charge balance, calculated versus measured conductivity). Validation typically
addresses the relationship between the samples. Raw data from field forms will be double entered .
and checked for consistency.
3.3 SEDIMENTARY DIATOM ASSEMBLAGE
3.3.1 Overall Objectives
• Use paleolimnological reconstructions to calibrate current conditions against.
• Develop an indicator of biological conditions based on diatom community composition.
• Estimate the rate of environmental change (as these data accumulate over time).
3.3.2 Summary of FY91 Activities
Using the surface sediment trophic indicator diatom assemblages, a diatom-based trophic index (DITl)
has been developed for EMAP-SW lakes. The relationship between DITl and TP is strong (^=0.60).
DITl values were also computed for the bottom samples of the 19 indicator lakes, and estimates were
made for the DITl change in individual indicator lakes since preindustrial times. DITl has increased in
8 and declined in 5 of the 19 lakes, whereas the index value did not change in the remaining 6 lakes.
Using the weighted-averaging calibration and regression diatom-based inference, models have been
developed to infer TP, SD, pH, ANC, and chl a. Inferred TP and pH changes since pre-industrial times
are estimated for indicator lakes. With the exception of two lakes, TP concentrations have increased
in lakes with high current measured TP value. In low TP lakes, TP concentrations have slightly
declined. In general, the lake water pH has increased in lakes which have high measured TP,
whereas the pH has declined in low TP lakes (with a few exceptions). Maximum acidification has
occurred in one lake.
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3.3.3 Objectives for FY92
• Expand calibration data set.
• Calibrate surface sediment diatom assemblages to multiple environmental variables.
• Improve predictive models and indexes developed during the FY91 Pilot.
• Estimate environmental changes in lakes since preindustrial times using recent (tops) and
preindustrial (bottoms) sedimentary diatom assemblages.
• Draw recent and preindustrial population estimates of lakes fitting into various impact categories.
• Estimate the rate of environmental change in lakes revisited in FY92.
• Further evaluate and document methods, including:
field methods
coring procedures
core sampling and archiving
laboratory methods
diatom analysis
diatom QA
sediment dating
statistical methods
data base development
ordination techniques
Monte Carlo simulation
3.3.4 Data Collection Plan
Sediment core samples will be taken from the deep, central area of the lake, and preferably where the
bottom is relatively flat. In large lakes, cores should be taken from depths <35 m deep, as gravity
coring from very deep areas is more problematic. A modified K-B gravity corer will be used to collect
sediment cores from the EMAP-SW grid lakes. An attempt should be made to collect sediment cores
>35 cm in length. The upper 1 cm of sediment, and 1 cm of sediment from the bottom of the core
will be removed for diatom analyses. From all revisit sites (~ 10 lakes), only top sediment samples
(0.25 cm slice) will be collected. After siphoning off the water from the top of the core, the top and
bottom sediment samples will be removed using an extrusion device and calibrated cylinder.
Methods for sample collection have been evaluated and standardized for three large, multi-institution
paleolimnological research projects which investigated the effects of acid rain on aquatic resources in
the United States (Paleolimnological Investigations of Recent Lake Acidification [PIRLA]-!, Charles and
Whitehead, 1986; PIRLA-II, Charles and Smol, 1990), and the Surface Water Acidification Programme
of Great Britain and Scandinavia (Battarbee, et al., 1990). Details of the methods to be used in this
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study may be found in the EMAP-SW Pilot Field Operations and Training Manual (Merritt and Metcalf,
in preparation).
3.3.5 Data Analysis Plan
3.3.5.1 Methods
Sediment sample digestion and diatom analyses follow the basic protocols outlined in Charles and
Whitehead (1986) to make quantitative slides, except that the cleaned samples will be rinsed at least 6
times in distilled, deionized water before the slurry is allowed to evaporate in plates (Battarbee, 1973).
At least 500 diatom valves will be identified and counted from each of the samples at magnifications of
10OOX or higher. Identifications will be made to the lowest taxonomic level using standardized
taxonomic procedures (e.g., Camburn, et al., 1984-1986). The procedure has been standardized and
was approved by EPA during PIRLA-II (Smol, et al., 1989).
3.3.5.2 Schedule
Top sediment diatom analyses (slide preparation and counting) should be completed by December
1992. Analysis of bottom sediment samples should be completed by May 1993.
3.3.6 Index Definition, Development, Interpretation, and Statistical Summary
State-of-the-art, multivariate direct-gradient analysis techniques, such as CCA (ter Braak 1986, 1987;
Dixit, et al., 1991b) will be applied to examine the distributions of diatom taxa in relation to
environmental variables. CCA produces a simultaneous ordination of both taxa and samples that can
be related directly to environmental variables. Forward selection and Monte Carlo permutation tests,
available in the computer program CANOCO (ter Braak, 1988), will be used to identify which measured
environmental variables explain the maximum amount of variation in the species data (e.g., Dixit, et al.,
1991b). Simultaneous influence of multiple environmental variables on diatom assemblages will also
be analyzed using this technique.
a
A qualitative estimate of environmental change will simply be made by examining the changes in the
abundance of indicator taxa and indicator assemblages. Quantitative changes will be determined by
applying various weighted-averaging calibration models and indices developed from the surface
sediment study. Similarity coefficients, species richness, and diversity will also be examined in the top
and bottom samples. The relative importance of the causes of change in lakes will be identified where
possible (using indicator taxa and assemblages, and by placing bottom samples in CCA runs as
passive samples and examining the trajectory in relation to environmental arrows), and an assessment
will be made of the potential sensitivity and responsiveness of lakes to anthropogenic activity.
•Background' or "reference conditions' with which the current conditions for a particular site or region
can be compared will be established. Identification will be made on what percentage of the study
lakes have declined in water quality (by inferred change in environmental variables, and by a water
quality index), have remained in steady state, or have improved, and where the lakes in these
categories are concentrated. It should also be possible to provide information on regional status and
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overall trends in ecological conditions. At repeat sites, this approach will help to follow environmental
trends through time.
3.3.7 Data Verification and Validation
Diatom count data will be entered into computer using a worksheet (e.g., Lotus 1-2-3) program. The
data files will then be given to the PIRLA data base manager to be added to the PIRLA data base.
The diatom count data will be printed and given to the person who originally entered the data from the
count sheets for verification and validation. The investigator will then create final data files and do the
analysis (e.g. CCA, weighted-averaging calibration). A copy of the count data (on disk) will be sent to
the EMAP-SW information management staff. In this project, the use of the existing PIRLA data base
is a major advantage, because the data base is currently capable of handling the additional data, and
will require no modification of the overall schema. The PIRLA data base management system (DBMS)
was originally created to allow space for data for many more lakes than were involved in the PIRLA
project. Interactive programs for data entry (e.g., on IBM PCs) already exist, as do many retrieval
programs. The PIRLA DBMS uses Scientific Information Retrieval software and provides output of
system files for direct statistical analysis by SAS, SPSS, CANOCO, BMDP, and other packages.
3.4 MACRO-INVERTEBRATE ASSEMBLAGE
3.4.1 Overall Objectives
• Develop and measure quantifiable indices of lake condition based on invertebrate assemblages.
• Monitor the condition of lakes using invertebrate assemblage information.
3.4.2 Summary of FY91 Activities
During the period July 20 through August 10, 1991, a total of 19 research study lakes were sampled
for benthic macroinvertebrates. The sampling design was intended to provide representative
collections of invertebrates from the major habitats present in the lakes. While a variety of lake
conditions were anticipated, ultimately, the observed lake characteristics were the determining factors
in selecting the type of samples to collect.
Three major habitats were present in most of the lakes sampled during this study: (1) mud bottom, (2)
mixed vegetation beds, and (3) rocky bottom with mixed deciduous debris. Following is a description
of the types of samples that were collected, by habitat type.
3.4.2.1 Mud Bottom Habitat
Nineteen sets of 3 petite PONAR grab samples were taken from Site X. Site X was located at the
deepest part of the lake. This area of each lake was located based on bathymetric maps and
confirming sonar readings. In the absence of existing depth information, a sonar survey of the lake
was performed to find the deepest area.
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Eighteen sets of 3 petite PONAR grab samples were taken from Site 1. Site 1 was selected to
represent an oxygenated habitat of mud bottom within the trophogenic zone (illuminated zone). The
trophogenic zone, according to Hutchison (1957) generally corresponds with the epilimnion and can
easily be determined from oxygen/temperature profiles.
Eight sets of 3 petite PONAR grab samples were taken from Site 2. Site 2 was a spatial duplicate for
Site 1. The two sites were generally located at opposite ends of the lake.
3.4.2.2 Mixed Vegetation Bed Habitat
All vegetation wash samples were collected by vigorously disturbing vegetation beds with a large
frame, rectangular dip net with approximately 1 mm mesh openings in the net. One field sorted wash
sample was taken at 8 lakes, duplicate field sorted vegetation wash samples were taken at 8 lakes,
and a quadruplicate field sorted vegetation wash was taken at 1 lake.
3.4.2.3 Mixed Rock and Woody Debris Habitat
Rocky habitats were vigorously kicked and the net quickly rotated through the disturbed volume of
water. In addition, individual rocks were washed directly into a sorting pan and hand picked. Woody
debris was collected by the kicking process, as well as being examined and hand picked. One field
sorted rock kick/wash sample was taken at each of 10 lakes; duplicate sorted rock kick/wash samples
were taken at 8 lakes.
3.4.2.4 Miscellaneous Habitats
At some lakes, important invertebrate habitats were found that did not fit into the rock or vegetation
type habitat categories. While these habitats only represented a small area of the lake in most cases,
some collections were performed to determine the suitability of the habitat to support invertebrates.
These habitats were:
- Sand with organic debris or algae cover.
- Submerged, large woody debris/bark.
- Submerged, mossy terrestrial vegetation.
- Net sweeps of submerged brush.
3.4.3 Status of FY91 Analyses
•
Animals in the littoral zone samples from representative lakes were preliminarily separated into family
groups to provide an indication of the variability among habitats and lakes. Preliminary analyses of
the sample and data suggest that these samples will provide little information regarding the overall
condition of the lake. Consequently, no further processing of these samples has occurred and there
are no plans to process them in the near future.
Processing of samples from the soft sediments in the profundal and trophogenic zones is continuing
by EMSL-LV, EMSL-CIN, and the Aquatic Resource Center under contract to EMSL-LV.
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At one small lake, 3 samples were collected at the deepest site near the center of the lake. These
samples have been processed. Two sets of replicates (1 set each from the profundal zone and the
trophogenic zone, respectively) will be processed from each of the 16 holes. A third set of replicates
was collected from several of these lakes, but will not be processed due to funding limitations. Three
complete sets of replicates from 2 lakes (2 from the trophogenic zone and 1 from the profundal zone)
will be processed to provide information on spatial variability, particularly with respect to the
trophogenic zone. It is anticipated that all sample processing will be complete by the end of April.
3.4.4 Objectives for FY92
• Evaluate field and laboratory sample collection and processing methods and gear for analyzing
macroinvertebrate communities inhabiting soft lake sediments.
• Evaluate benthic macroinvertebrate indices and metrics to identify those most appropriate for the
purpose of characterizing the ecological condition of lakes.
3.4.5 Data Collection Plan
3.4.5.1 Plot Design
Four to 6 lakes will be selected for testing benthic macroinvertebrate sampling methods and gear from
the suite of grid lakes identified for the FY92 EMAP-SW Northeast Lakes Pilot. Lakes selected for
macrobenthos work must meet the following minimum criteria: (1) lake surface area must be between
20 and 200 ha; (2) lakes must be accessible by truck; (3) lakes should represent a range of trophic
conditions from eutrophic to oligotrophic; (4) at least 1 lake should demonstrate signs of impact as a
result of agriculture, silviculture, or urbanization, and at least 1 lake should be unimpacted (or only
marginally impacted) by human activities; and, (5) most lakes should be of sufficient depth that strong
thermal stratification occurs.
3.4.5.2 Methods Summary
The length and width of each lake will be transected, and the configuration of the bottom recorded on
the chart recorder prior to selecting sampling sites. Temperature and DO vertical profiles will be taken
at 2 or 3 sites to determine the depth of the thermocline, and oxygen concentrations will be taken at
various depths in the hypolimnion for purposes of selecting sampling sites. Benthic samples will be
collected with grab samplers, multi-tube corers, box corers, or a combination of each. Replicate
samples will be collected from within the trophogenic and profundal zones, and all samples will be
sieved in the field through a series of graded mesh size sieves (i.e., 600 /jm-200 /jm), preserved, and
transported for laboratory analysis. Laboratory analyses will involve sorting the materials retained by
each sieve under a low power stereo microscope and carrying identifications of organisms to the
lowest possible taxonomic level (e.g., species for oligochaetes, genus for most chironomids, and
genus or species where possible for most other forms such as amphipods, mayflies, molluscs).
Careful records will be maintained on sample processing times and effort expended to obtain cost
efficiency data on information gained per unit of processing effort.
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3.4.6 Data Analysis Plan
Each individual sample (replicate) will be processed as a discrete unit and the data from each treated
separately (i.e., samples will not be physically pooled or composited). However, in some instances,
the data from various replicates may be pooled to provide sufficient numbers of organisms and taxa
for statistical analyses.
A number of options are available for reducing highly complex biological community data to metrics
that fit the needs of EMAP-SW. Some metrics that have been used in water quality investigations
(although primarily in streams) will be tested during the FY92 pilot. These metrics include similarity
and community loss indices, total abundance, species richness, diversity, Hilsenhoffs Biotic Index
(HBI), ratios of groups of taxa (e.g., molluscs and Crustacea to other taxa; insect taxa to non-insects),
and ratios of taxonomic groups by function, habitat, or lake type.
In addition, non-linear multivariate statistical methods will be used with numerical and/or
presence/absence data to examine clustering of lakes based on community assemblage data and
environmental variables.
3.4.6.1 Index Definition and Development
The primary types of indices to be tested are listed above. Many are well developed for use with lotic
communities, but are less well developed for application to lentic assemblages (e.g., diversity,
similarity, community loss, HBI). Others, such as ratios of taxonomic groups based on habitat,
function, or lake type (trophic state) are in various states of development and testing for lake benthos.
The numerous combinations of groups of animals at various taxonomic levels (e.g., species, genus,
family) that could be tested are seemingly endless. Consequently, only those demonstrating
considerable progress for application to EMAP-SW needs (in the judgement of knowledgeable
scientists) will be evaluated during the FY92 pilot.
3.4.6.2 Index Interpretation
An approach that will be used to evaluate and interpret indices and metrics is through comparison of
values obtained in disturbed (human-impacted) lakes with those from undisturbed (unimpacted)
reference systems. The degree, nature, and extent of disturbance in impacted systems will be
documented through various means, including visual observations (watershed disturbances, outfalls,
texture and odor of sediments, presence of unusually dense plant growth, water clarity);
communication with people familiar with the lake (state personnel, locals, etc.); in situ measurements
of DO, pH, conductivity, temperature, and depth; and examination of other biological and chemical
data obtained by other EMAP-SW teams. Multivariate techniques will be applied to benthic data sets
to see where lakes or groups of lakes cluster in relation to expectations based on prior knowledge,
and chemical and other biological data.
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3.4.6.3 Proposed Statistical Summary
Summary data will be presented both graphically and in tabular form to demonstrate the utility of
various indices and metrics. Non-linear multivariate statistical methods will be applied to data metrics
to group lakes in statistically significant (e.g., habitat, lake morphometry, chemistry) data. The clusters
can be tested for significant overlap, allowing for correlation between community structure and
environmental variables.
3.4.6.4 Data Verification and Validation
Lake locations are verified using a combination of GPS, maps, and interaction with local residents, if
available. Sampling sites are plotted on lake map forms and described on field forms and assigned
site numbers. All sample containers are prelabeled with sample tracking information; upon return to
base, barcode labels are added to sample containers and the numbers recorded in the field log.
Copies of field forms are faxed to the Las Vegas Communications Center; originals are mailed via
overnight courier to the Communications Center. Copies of shipment tracking forms accompany the
sample shipment. All samples are logged in upon receipt at the processing laboratory and checked
against the tracking form; the processing laboratory signs the tracking form and returns it to the
Communications Center either via fax or mail. Records are kept by the processing laboratory
regarding sorting techniques, sorting personnel, sample identification numbers, sort times, keys used,
etc. Number and species of all animals counted and identified are entered on bench sheets.
Unidentified specimens are so noted and sent to independent taxonomic experts for identification or
confirmation. One copy of the bench sheet is retained by the processing laboratory and one copy is
forwarded to Las Vegas. All data are entered from the bench sheet on to coded, computerized data
screens and the entries are checked by benthos biologists familiar with taxonomy and nomenclature.
3.5 ZOO-PLANKTON
3.5.1 Overall Objectives
• Develop and refine zooplankton metrics which reflect lake resource, biological integrity,
fishability, and trophic state.
• Develop techniques for detecting changes in zooplankton community structure by classes of
lakes and at regional scales.
• Classify lakes according to zooplankton community assemblage data and display
biogeographical distribution.
• Evaluate zooplankton metrics with respect to components of variance.
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3.5.2 Summary of FY91 Activities
A total of 107 samples were enumerated and analyzed:
• 19 Indicator Lakes
• 50 Probability Lakes
• 24 Revisit Probability Lakes (1 lost to sediment contamination)
• 14 samples for crew effects on index site variance
Substantial effort was spent on quality assurance related to sample enumeration and taxonomy. The
pilot provided valuable experience in data management, exploratory analytical techniques, and data
interpretation. Both the indicator lake subset and probability lakes revealed that zooplankton body
size was the dominant feature which characterized differences among lakes. Microzooplankton
dominated systems associated with high nutrient levels and land use disturbance factors.
Macrozooplankton, particularly large calanoid copepods, dominated more pristine systems having
native cold water fish assemblages. We developed a body size metric which correlates with
disturbance factors and fish guilds.
3.5.3 Objectives for FY92
• Determine if zooplankton body size relationships correspond to environmental and land use factors
consistent with the FY91 pilot results.
• Refine regression models from zooplankton assemblage data and derived metrics with fish
assemblage attributes.
• Evaluate index period and between-year comparisons of variance for the zooplankton metrics.
• Develop regression models for a select group of indicator taxa for pH, temperature, salinity, and
trophic state.
• Evaluate present day biogeographic ranges with respect to glacial history, temperature, and water
chemistry.
• Evaluate ecoregion concept with respect to zooplankton assemblages.
3.5.4 Data Collection Plan
3.5.4.1 Plot Design
A single bongo net is hauled from the bottom to the surface at the deepest portion of the lake (mid-
lake for shallow systems). Standardized abundances are reported in units of individuals/L The
volume of water filtered is corrected for the oxygenated portion of the water column where DO is >0.1
parts-per million (ppm).
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3.5.4.2 Methods Summary
Zooplankton samples are narcotized with carbon dioxide and preserved with 4% buffered formalin and
sucrose. The samples are stored in 125 ml Nalgene screw cap bottles and sealed with electrical tape.
Zooplankton is identified to species, form, or variety. Three replicate counts are made on each
sample to give a total of 200-400 organisms using a stereoscope for macrozooplankton and inverted
compound microscope for microzooplankton.
3.5.4.3 Collection Procedure
A bongo net (202 fjm and 48 /jm Nitex mesh) is towed vertically at a rate of ~ 10 meters/minute (i.e.,
5-6 seconds/meter) from ~ 0.5m off bottom to the surface avoiding bottom sediments.
3.5.5 Data Analysis Plan
3.5.5.1 Index Definition and Development
Metrics will be examined for biological integrity (e.g., species richness, food web structure, and food
chain length), and for association with the fish assemblage data. We are interested in an aggregate
metric to characterize ecosystem function or rate process. For example, the ratio between the
abundance of long-lived macrozooplankton and short-lived microzooplankton may reflect major
differences in nutrient cycling among lakes.
3.5.5.2 Index Interpretation
We will develop conceptual models for metrics and make inferences from correlations with
concomitant environmental variables.
3.5.5.3 Proposed Statistical Summary
• Mean of species abundances and frequency of occurrence.
• Regression of species abundance versus variance.
• Analysis of covariance for major components of variance in metrics and index.
• Explained variance in multivariate statistics and correlations with environmental variables
summarized as vector biplots.
• Stepwise regression models using environmental components to explain zooplankton metrics and
index.
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3.5.5.4 Data Verification and Validation
Verification will be accomplished by recording all raw count data on data sheets having the same
format as the computer spreadsheet. The spreadsheet data are easily checked for entry errors
against the raw data sheets. We then use chemical and physical information to verify the occurrence
of specific taxa in a particular lake.
Data validation is done by identifying outliers in multivariate statistical methods. Metrics and species
abundance data are evaluated for their distribution patterns. Appropriate transformations on the data
are then made before analysis.
3.6 FISH ASSEMBLAGE
3.6.1 Overall Objectives
• Define and measure quantifiable indices of lake biological integrity based on fish assemblages.
• Develop and measure metrics of the fishability of lakes.
3.6.2 Summary of FY91 Activities
Fish were collected at the 19 Indicator Evaluation Study (IES) lakes during July and August 1991,
using electrofishing, Indiana trap nets, experimental gill nets (variable mesh sizes), seines (beach and
short), and small traps (minnow traps and eel pots). State agencies imposed varying restrictions on
gill netting in 13 lakes, from complete prohibition (4 lakes) to no overnight sets (2 lakes). One lake
was not accessible to the electrofishing boat. Substrate structure precluded seining completely at one
lake and prevented beach seining at 3 others.
The number of species collected ranged from 1 to 17 per lake with a median of 9 species. The
number of individuals ranged from 50 to 3,840 per lake. For both species and individuals the small
traps were least effective; the median proportion of species and individuals caught per lake was
approximately 30% and less than 5%, respectively. The combined seining methods were the next
most effective for collecting species (median approx. 50%) and collected on average nearly as many
individuals as did electrofishing (median approximately 30%). Gill nets and trap nets collected a
similar proportion of species (median by lakes 60% and 65%) and individuals (15% and 10%). The
most effective method was electrofishing, collecting a median of 73% of species (100% of the species
at 5 lakes) and a median of 35% of the individuals in the lakes. However, in low conductivity systems
electrofishing did rather poorly, collecting only 3 fish in one lake.
Overall, these results indicate, as expected, that no one method is sufficient at all lake types. Gill
netting is the only method for collecting cold water pelagic species. Although electrofishing is very
effective in many lakes, accessibility issues may impose limits on its usefulness in the overall lakes
program, unless a more portable system can be developed and/or better data comparability can be
determined.
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The FY91 Pilot Survey had five objectives for fish assemblages (Pollard and Peres, 1991). The data
derived allowed us to achieve most of the objective of determining optimal sampling methods for lake
fish. Some additional methods research will done in FY92 to evaluate alternative electrofishing
methods. These results, combined with data from other lake fish surveys, are being used to meet the
objective of evaluating effectiveness and components of variability among the gear. Additional
methods research is planned for FY92 to evaluate other components of variability, such as intra-index
and inter-crew sampling variability. Except for some of the cold water lakes with gill net restrictions,
we met the objective of determining the fish species presence and proportional abundances in the
individual lakes. For FY92, protocols are being revised to provide fish tissue for contaminants
analysis.
3.6.3 Objectives for FY92
• Use a reduced sampling protocol to collect an index sample of fish assemblage at 40 of the
probability lakes selected for biological sampling from the 1992 grid, and at the 10 lakes selected
for annual sampling. Repeat sample 20 of the 1992 lakes to estimate the size of the index and
measurement variance.
• Develop preliminary fish assemblage metrics and an index for biological integrity for northeast
lakes, and make preliminary population estimates of biological integrity using these fish metrics.
• At a subset of lakes, evaluate the effectiveness of small electrofishing systems.
• Provide sample materials for evaluation of fish tissue contaminants.
3.6.3.1 Collecting an Index Sample of Fish Assemblages
Unlike some indicators of ecological condition, such as lake chemical habitat, sedimentary diatoms, or
stream fish assemblages (in certain regions and stream types), currently there is no widely accepted
definition of what constitutes an index sample of a lake fish assemblage. The EMAP-SW working
definition is: an index sample of lake fish is achieved by (1) catching all species, except the
occasional rare species; (2) catching large enough numbers of individuals to determine the relative
proportions of the abundant and common species, determine which species are uncommon or rare,
and determine the general population size structure of the abundant and common long-lived species;
and (3) catching juveniles and/or young-of-year of at least the abundant and common naturally
reproducing species. An index sample should also relate these data to the proportions of various
habitat types within the lake. The index sample should characterize species relative abundances as
abundant (>20% of total abundance), common (5-20% of total), uncommon (1-5%), and rare (<1%).
Because of the various habitats in lakes, the preferences that different fish species and life stages
have for different habitats, and the habitat-specific nature of most fish sampling gear, there is no
widely accepted, single method to index the fish assemblage in all lakes. It will be necessary to use a
combination of gear types at a variety of habitat locations to characterize the fish assemblages for
EMAP-SW purposes.
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A part of this objective relates to the logistical challenge of collecting index samples of fish
assemblages in relatively large numbers of lakes of varying sizes, physical structures, and
accessibility, with multiple crews.
3.6.3.2 Developing Indices of Fish Assemblage Conditions
Currently, there is no agreed upon methodology for assessing the biological condition of fish
assemblages in lakes; this is largely unexplored territory. The implications for EMAP-SW are that we
will need to spend substantial time and effort in careful consideration of a variety of analyses,
combinations of data, and interpretations of results, and in consultations with other fisheries
professionals. We present here the broad outline of our approach to developing assessment metrics
and indices.
Changes in the overall species structure of the lake fish assemblage can be related to individual
stressors, a combination of stresses, or conversely, to reductions in cultural impacts. Over time,
changes in the species composition of the collections (matched with knowledge of the species'
autecology) will be related to such impacts as changes in land use, eutrophication, and pressure from
exotic species. For example, these human-induced stresses have been related to reductions of stocks
of several pelagic species such as lake trout, lake whitefish, and walleye, and increases in yellow
perch and rainbow smelt (an exotic species), in Lake Erie (Regier and Hartman, 1973). Since that
report, reductions in cultural nutrient loading have improved the trophic status of the lake, and with it,
the walleye sports fishery.
3.6.3.3 Evaluating a Portable Electrofishing System
Electrofishing is a widely used, very effective method for sampling littoral fishes. However, for EMAP-
SW, this method has some drawbacks which need to be addressed with further field work. The
primary concern is the physical size of electrofishing systems in common use on lakes; most lake
electrofishing is done with boats in the 18-20 foot size range and require relatively easy vehicle
access. A proportion of EMAP-SW lakes are not vehicle accessible. Smaller electrofishing systems
have been used successfully in wadeable streams, but have generally not been evaluated for use in
smaller boats in lakes. The assumption has been that the small systems will not deliver enough
power to be effective in the less confined habitat of lakes. Additional concerns about electrofishing
center around its effectiveness in low conductivity lakes, and whether a portable system can be safely
operated from an inflatable boat.
For this objective, at 10 of the lakes scheduled for the standard fishing protocols and over a range of
conductivities, we plan to sample with a smaller electrofishing system than is normally used in lakes,
and a modified backpack size system. We plan to evaluate these systems in the 'standard* EMAP-SW
boat and, at one or two lakes, in an inflatable boat.
3.6.3.4 Providing Samples for Tissue Contaminant Analyses
This objective primarily addresses a logistics issue. Problems occurred in our ability to provide fish
specimens for tissue contaminant analyses during the 1991 pilot survey. Field protocols have been
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modified to facilitate achieving this objective; dry ice is no longer being used, whole fish are being
used instead of fillets, and more latitude is given in selecting species for analyses (see Section 3.8 for
details).
3.6.4 Data Collection Plan
Based on the results of the 1991 pilot survey, analyses of other data bases, and discussions at the
January 1992 Lakes Fish Workshop, a standardized protocol for sampling fish assemblages will be
applied at 40 grid lakes selected for the Year 2 Tier 2 sample (which meet other EMAP-SW criteria),
and at the 10 lakes selected for annual sampling. This protocol will also be applied to the 20 lakes
chosen for within-index period resampling.
3.6.4.1 Plot Design
At each lake, an assessment of the presence and relative proportion of major fish habitats will be
made using temperature and oxygen profiles, bathymetric data, physical habitat data, and shoreline
maps of littoral habitat. Different species assemblages are expected among habitats and are sampled
effectively by different gear. The major habitats are littoral (which will be further subdivided based on
substrate, cover, and human modifications), pelagic, and profundal. In order to index the fish
assemblage at each lake, all (oxygenated) habitats will be sampled regardless of their expected
productivity (i.e., gear will not be placed to maximize catch).
Decisions about where to place sampling gear will generally use the following protocol. If the lake is
unstratified, gill nets will be placed on the bottom in deep areas. If the lake is stratified with
oxygenated water at or below the thermocline, the profundal habitat will be sampled with overnight
bottom-set gill nets. If the lake is unstratified or the thermocline is anoxic, it will be considered to have
no profundal habitat. Most EMAP-SW lakes are expected to have a pelagic habitat; areas deeper than
two meters will be sampled with overnight set gill nets above the thermocline. At larger lakes,
especially those with limited profundal habitat, at least one gill net will be set in the littoral zone.
Primarily, the littoral zone will be sampled with overnight set trap nets and minnow traps, and seining
after dark.
Within certain constraints (below) sampling will occur in all major habitats in the littoral zone. Gear will
be placed within these habitats using a stratified, random protocol. The littoral zone will be assessed
to determine what the major habitats are and their extents. Littoral habitats will be classified by
presence and type of cover, and substrate type. Areas of extensive human modification will be
considered as one or more habitat types. Sampling will be done in up to the four most extensive
littoral habitats at each lake. Specific trap net and minnow trap sites will be as close as possible to
the randomly chosen physical habitat evaluation site (see Section 3.9) within that habitat.
Choosing sampling locations in the littoral habitats is further constrained by whether the gear can be
effectively used. Beach seining can only be done in areas relatively clear of obstructions such as
snags, dense vegetation, and loose cobble or boulders, and with a relatively clear beach. Short haul
seines can be substituted for beach seines in shallow areas with moderate vegetation, and small
areas with limited substrate clutter. In some lakes, no seining will be possible; information on the
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littoral assemblages of small fishes will be derived from minnow trap catches. Trap nets will be
preferentially placed in water no deeper than the height of the frame opening.
The actual amount of sampling effort will be a function of lake size and morphometry, and habitat
complexity. The field crew will also perform additional discretionary fish sampling in areas and
habitats not covered by the standard protocol, but which are expected to be productive. These data
will be assessed separately.
The repeat visits will generally not be made by the original crew. Using the same protocol, the
second crew will perform its own site selection and sampling at the end of the field season. This
should incorporate most of the possible sources of variability (i.e., crew and within-lake site selection
differences, and greatest within-index period temporal variability).
3.6.4.2 Collection Procedure
Fish will be collected with passive gear. One to 8 experimental gill nets (14 mesh sizes) will be set
overnight in oxygenated profundal water and in pelagic areas, 1 to 8 Indiana frame trap nets will be
set overnight in littoral habitats, and minnow traps will be placed in shallow water with cover near the
trap nets. After sunset, 2 to 6 appropriate locations will be sampled with beach and/or short haul
seines. The level of effort is largely determined by lake size.
Sampling for lakes up to about 500 ha will require one and one-half days at each lake. Larger lakes
will be sampled either by increasing the time at the lake or by using two crews, depending on
logistics. Fish collected will be identified to species and examined for external gross pathology in the
field. Long-lived species will be measured for length, short-lived species will be recorded by size class
(young-of-year, juvenile, and adult). All fish data will be recorded by the specific gear/method used
and by the location and habitat type. Representative specimens of all small fishes collected will be
preserved as vouchers for confirmation of species, and archived in a museum collection. In addition,
up to 5 large specimens of species selected for tissue contaminant analyses will be collected (see
Section 3.8).
3.6.5 Data Analysis Plan
The use of fish assemblage data as an indicator of lake condition is still in the developmental stage.
To that extent, much of the data analyses are of an exploratory nature. Although there is some
overlap, in general, each objective has its'own data analysis needs.
•
Marginal return curves will be produced to continue to evaluate whether the level of effort is sufficient
to obtain an adequate index sample. These curves will be compared to those developed from the
1991 data, with existing species lists where they are available, and with the results of the "judgement"
sampling and repeat sampling. The index protocol should collect >80% of the expected species.
These analyses will also include data from electrofishing, where appropriate, to evaluate how well we
are achieving an index sample of the fish assemblages.
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Concordance in the species lists and species relative abundance of the repeat visits should indicate
how well we are sampling the lakes. The repeat visits will also be an estimate of index variance. It is
not expected that there will be any major shifts in the "true* species richness or relative abundances
within the index period (barring any local catastrophic event between the two sample acquisitions).
We will not be able to estimate the adequacy of the index sample completely until we also estimate
population, site year-to-year, and regional year-to-year variation. Our initial target is to achieve an
index coefficient of variation of 10-20% of the species richness. If index variation is significantly larger
than this amount, we will evaluate our options for improving our estimates.
Ordinations (detrended correspondence analysis and canonical correspondence analysis) will be used
to examine the species assemblage structure, identify lakes with similar species assemblages, and
assess the relationships of the species to components of the physical environment. Although the
number of lakes sampled for fish this year is relatively small, we can begin to develop metrics for
EMAP-SW applications from these data For example, a species richness model based on waterbody
size and type has potential as a regional-scale indicator of ecological condition (Whittier and Rankin,
1991), and can also be used as one component of a multimetric index.
Sections 3.6.5.1 and 3.6.5.2 address the analytical needs of the 1992 fish assemblage indicator, as
well as overall objectives related to developing indices of condition. There are no analytical needs for
the objective of providing materials for tissue contaminant analysis.
3.6.5.1 Index Definition, Development, and Interpretation
We plan to evaluate several potential metrics of lake fish assemblages as indicators of biological
integrity, including: (1) species richness, adjusted for lake size and type, as a measure of assemblage
diversity; (2) numbers of exotic species and individuals (including stocked fishes) relative to native
species, as one measure of biological stress and the resiliency of the native fauna; and (3) proportion
of individuals sensitive to human perturbation relative to proportion of those tolerant of such stress.
We will examine the usefulness of combining several of these metrics into an overall index of
biological integrity.
It should also be possible to develop fish species assemblage models or indices to evaluate biological
response to specific stressors. For example, an acidification stressor model would probably include
increased dominance by yellow perch, coupled with loss of acid-sensitive species such as common
shiner, bluntnose minnow, and johnny darter (Schindler, et at., 1989). A eutrophication model would
probably include an increased proportion of species tolerant of detritus-covered substrate (spawning
beds) and low DO conditions, such as common carp. At th§ same time, there would should be
decreases in pelagic top carnivores which require high oxygen levels, such as smallmouth bass.
We also plan to explore the multivariate analysis approach to assessing biological condition. For this,
we could run an ordination on a set of reference assemblages from relatively unimpaired lakes. The
ordination could then be run again, serially, with the assemblage data from a set of impaired lakes.
The ordination distance (and possibly direction) of each new assemblage from the centroid of the
reference assemblages could be a measure of biological impairment.
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Fish assemblage data may also be used to assess the fishability endpoint of concern. The
occurrence and size of game fish species evaluates the potential for a sports fishery. The presence of
external anomalies and/or tissue contaminants, as well as whether stocking is necessary, will partially
address the quality and sustainability of the fishery. It is probably not be possible to develop a single
fishability index due to the subjective nature of this endpoint. Instead, we will report on several
indices, such as the proportion of lakes with game species of catchable size, proportion of game
species with anomalies and/or consumption criteria violations due to contaminants, and proportion of
lakes requiring stocking programs to maintain a sports fishery.
3.6.5.2 Proposed Statistical Summary
The statistical summary of the 1992 data will include (1) cumulative distribution functions (cdf) of the
various individual metrics, such as native species richness, proportion of native species, etc.; (2)
bivariate plots of species richness and native species against lake size, and a preliminary species
richness and lake size model; (3) bivariate plots of various fish assemblage metrics against other
possible controlling factors, such as pH, ANC, and level of human modification to the riparian zone,
etc.
3.6.5.3 Data Verification and Validation
The data verification phase will involve the field crew checking the data sheets before sending them in
for data entry, using a 'double entry' system for data entry (two people entering the data
independently and then electronically comparing the results) to correct for typographical errors, and at
least one person from the field crew visually scanning the data base against the data sheets. The
data entry program will be designed to aid in identifying errors.
The field data will be validated by a reputable museum. At each station at each lake, at least one
voucher specimen of all species will be preserved. Larger numbers of small and/or difficult to identify
species, as well as possible hybrids, will be vouchered for validation. Where very large numbers of
small and/or difficult species are collected, all individual fishes will be counted, and a random
subsample will be preserved. The museum will examine and identify to species (or probable hybrid
crosses) specimens from all stations. Where large numbers of small fishes are preserved, the
museum will identify a random subset; the species proportions will then be used to calculate species
counts at each station.
3.7 BIRD ASSEMBLAGE
3.7.1 Overall Objectives
• Develop an indicator using avian assemblages in the near shore and riparian zone for lakes.
• Test the sensitivity and cost-effectiveness of birds as indicators of lake condition relative to other
indicators.
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3.7.2 Summary of FY91 Activities
Two 2-person teams surveyed 10 different lakes each, located in Maine, New Hampshire, Rhode
Island, and Massachusetts. One crew member on each team surveyed the birds, while the other
recorded habitat data. Each crew surveyed their 10 lakes twice. Each crew started at the
southernmost lake of their region and proceeded northward to take advantage of differences in
breeding times (i.e., the birds in Massachusetts begin breeding earlier than those in Maine). Crews
arrived at the lake the evening before the scheduled survey to determine access point and to confirm
that no problems would be encountered the following morning. The survey was conducted one-half
hour before sunrise to four hours after sunrise during the period of June 1 through July 3, 1991. A
transect parallel to and 10m from the shore was traveled using motorized canoes. Censuses were
made at 200-m intervals, unless a lake had a perimeter greater than 4,800m, in which case, points
were proportionately allocated according to the percentage of particular habitat types present. Each
census recorded the numbers of each species seen or heard during a 5-minute period, recording
separately those within and without a 200-m diameter circle centered on the census point. For the
habitat data collection, the circle was divided into quarters and the percent of each habitat type
present was estimated within each quarter.
3.7.3 Objectives for FY92
• Evaluate the two indicators developed from the FY91 data against an independent data set to be
collected during FY92.
• Use the FY92 data to enhance our understanding of the causal processes behind our FY91
indicators.
• Investigate the FY92 data for new indicators of environmental quality.
3.7.4 Data Collection and Analysis
The EMAP-SW bird survey will be conducted by cooperators from the University of Maine. Two teams
of two ornithologists each will visit 40 lakes of varying sizes and disturbance types. The index
sampling period is from May 30 to July 7, 1992. At each lake, the field crew will canoe a transect,
stopping every 200m to record birds seen or heard within a 5-minute period. This point-count method
is appropriate for estimating bird community composition in patchy habitats (Reynolds, et al., 1980).
The field crew will also record physical habitat information. Surveys will be conducted on days within
the index sampling period which meet the criteria (or weather conditions established for Breeding Bird
Survey participants by the U.S. Fish and Wildlife Service (USFWS, 1990).
The bird survey data from the 40 lakes will be used to develop a preliminary index that reflects the
cumulative disturbance of lakeshore habitats. The metrics that compose the index will be derived from
rankings of species' trophic status, habitat specificity, wetland dependency, etc.
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3.7.4.1 Proposed Statistical Summary
Two indicators developed in FY91 will be evaluated using the FY92 data. The first indicator is the
deviation of the abundance of species at a lake from that predicted by a multiple regression model
using its size and temperature class as independent variables. First, the FY91 model structure and
coefficient values will be used to predict the expected number of species on each lake in the FY92
sample, with the expectation that the larger deviations from the model will be correlated with higher
values of independently measured stressors at those lakes. Should this not be the case, the
possibility that the numerical values of the coefficients need to be recomputed will be investigated.
(This is not an unlikely scenario, given the extension of the geographical area of the survey into New
York and New Jersey, where the avifauna is somewhat different from that of New England alone.) In
this event, the coefficients will be reevaluated from a 67% sample of the lakes. This sample will be
screened for outliers on the basis of leverage values, and model coefficients reevaluated. The
remaining one-third sample can then be used to provide an independent assessment of the accuracy
of the recomputed model.
The second indicator consists of scores along a principal component axis where the independent
variables are functions of the guild composition of each lake's community. The efficacy of this
measure as an indicator will be evaluated initially on a two-thirds sample of the FY92 lakes, first using
the guild structures and species memberships used in the FY91 data, and then using a wider
definition of guild memberships to accommodate the additional species expected to be encountered
during FY91-FY92. Problems that arise with outliers or with emergent modifications of the model will
be independently evaluated on the remaining one-third sample after any exploratory data analysis has
been completed.
A third program of investigation using a variety of cluster analysis techniques will be conducted on the
larger dataset available during FY92. The primary objective of this program will be to investigate the
extent to which geographical clustering of the lake avifauna occurs, and how such change might
contribute to variation in the indicator values from unimpacted lake to unimpacted lake. This phase is
essentially exploratory data analysis in preparation for extension of the EMAP-SW program to other
regions in future years, to facilitate recognition of the generic features of the indicators currently under
consideration.
3.7.4.2 Data Verification and Validation
Data will be entered by a commercial data entry firm, using data bases that provide range and illegal
value checks. After the data set is received, it will be run through a program to check for errors.
SYSTAT will be used to cross-tabulate variables as a further check for errors. A subsample of the
data will be checked visually against the data sheets to determine the error rate. If the error rate is
>0.1%, then each line of data will be visually checked against the data sheets. All errors found will be
documented and corrected. Once those initial checks have been conducted, exploratory data
analysis, which includes a graphic comparison of variables of interest, will be conducted. Unusual
values found during exploratory data analysis will be double-checked.
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3.8 CHEMICAL CONTAMINANTS IN FISH
3.8.1 Overall Objectives
To estimate the proportion of lakes in a region (EPA or ecoregion) that have one or more of the target
analytes above an accepted tolerance or level of concern, for different groups of fish consumers -
wildlife and humans (an "average human consumer1, sports fishermen, subsistence fishermen).
3.8.2 Summary of FY91 Activities
During the 1991 pilot study, fish were collected from 4 of the 20 research lakes for analysis of tissue
for our target analytes (contaminants). However, target species, numbers of species, and numbers of
fish that this initial study called for were not found. It was decided for now not to analyze the fish
caught but instead focus our effort on answering some questions regarding risk assessment feasibility
and laboratory availability and selection. The feasibility analysis has been completed. A more in-
depth analysis is ongoing.
3.8.3 Objectives for FY92
As yet there has been no data on levels of contaminants in fish tissue collected to investigate how to
best achieve our overall objective. We hope to answer some of the questions below, that are
associated with achieving the overall objective, in the 1992 pilot, through the process of data
collection and analysis.
• What is the best way of formulating regional estimates of risk and putting them into the form of a
cdf?
• How representative is one five-fish composite of the level of contamination of a lake? How well
does one composite represent a population of one species in a lake and also of the trophic level
(top predators) that species occupies? Lake revisits within the index period are needed to answer
this question.
• Can meaningful relationships concerning bioaccumulation be established between a couple of the
most prevalent predator fish in a region? To answer this question, a subset of the lakes must be
sampled and analyzed for two species of fish.
• For a region, can we extrapolate from contaminant levels in whole fish to the levels in fillets by
collecting two five-fish composites from a subset of lakes and analyzing one composite of whole
fish and one composite from fillets only?
• How can the values for risk, which represent the combination of data from different sources -
chemical analysis (contaminant concentrations), toxicological studies (reference dose, potency
factor), surveys (rates of fish consumption) - be analyzed statistically, or is this possible?
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• What level of variability is associated with sample collection and laboratory analysis for contaminant
levels? Are there any improvements that can be made that will give better quality data?
• What types of contaminants are prevalent in a region? If only certain types are consistently found,
can we focus on these at some point in the future? This is a longer term question, and can only
be partially addressed by the pilot.
3.8.4 Data Collection Plan
3.8.4.1 Plot Design
It is planned to analyze 5-fish (which will be composited later), from each of the 60 to 70 grid lakes.
Fish used for this indicator will be a small sample from those caught for the fish assemblage indicator.
Sampling crews may be asked to collect two or three 5-fish samples if sufficient quantities of more
than one target fish are available, to give us a choice of species to analyze. This would also give us a
subset of lakes from which we could establish a relationship between two of the most abundant game
species in a region (e.g., Yellow Perch and Largemouth Bass) as to their relative rates of
bioaccumulation. In addition to this subset, we plan to collect enough fish for two 5-fish composites of
one species from a subset of lakes. In one 5-fish composite we will analyze for the target
contaminants in whole fish and in the other for these contaminants in fillets only, in order to be able
to extrapolate more accurately from whole fish levels to those in fillets and thus give a more accurate
estimate of human exposure. In addition, revisits within the index period to show level of
representativeness and reproducibility as well as seeking a 'positive control' (a highly impacted site to
show responsiveness of the analysis) if one doesn't occur within the grid lakes, should be considered.
3.8.4.2 Methods Summary
Once the whole fish reach the laboratory, they will be kept frozen until compositing and analysis.
Either the whole fish or the fillets from each 5-fish sample will be homogenized in a blender to make a
composite sample for that lake. Portions of the homogenate will undergo Soxhlet extraction and acid
digestion. The portion that has undergone Soxhlet extraction, after appropriate cleanup steps, will be
analyzed by Gas Chromatography/Electron-Capture Detector (GC/ECD) for halogenated organics
(pesticides and PCBs). The portion that has undergone acid digestion will be analyzed by either
Inductively Coupled Plasma (ICP), Atomic Absorption Spectroscopy (AAS) for metals, or cold vapor
(for mercury). Table 3-2 contains a list of target analytes from 1991. In addition to those in the table,
the coplanar PCB congeners 77, 126, and 169 may be analyzed for and percent lipids will be
analyzed during the 1992 pilot.
3.8.4.3 Collection Procedure
The five fish shall be of similar size, meeting (if possible) the criterion that the total length (TL) of the
smallest fish be at least 75% of the largest. What species collected at each lake will depend on what
is caught, with the following species being targeted:
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Yellow Perch
Largemouth Bass
Smallmouth Bass
Trout species
Chain Pickerel
A sampling protocol (in preparation) specifying species and size selection criteria will be issued to all
field crews. The fish are to be kept as cold as possible while in the field with synthetic ice and shipped
to the laboratory (in coolers with synthetic ice) as soon as possible by means of a next-day shipping
service such as Federal Express.
A detailed description of the data collection and analysis procedures for this indicator is included in
the EMAP-SW Laboratory Methods Manual (U.S. EPA, 1991).
3.8.5 Data Analysis Plan
3.8.5.1 Index Definition and Development
Once fish tissue contaminant data has been generated and analyzed on its own, efforts will be made
to integrate this data with data from other indicators to give a picture of regional lake health. We will
look for possible correlations between this data and data gathered on the other indicators.
3.8.5.2 Proposed Statistical Summary
It should be possible to produce individual cdfs showing the proportion of lakes that exceed a
specified "tolerable" risk level for each compound. In addition, a cdf showing the combined number of
contaminants found exceeding tolerable risk levels should be able to be produced. These cdfs can
be made consumer-specific, showing the level of risk that each consumer group is exposed to.
Statistical methods can be used to estimate the variance occurring in values for concentrations of
contaminants in fish tissue, but risk estimates may not be amenable to statistical analyses of variance
since they are in large part mathematical models. This is one of the issues that will be explored
during the 1992 pilot.
3.8.5.3 Data Verification and Validation
To date we have had no data to work with, so many details of data verification and validation still need
to be worked out. However, what will be required of the analytical laboratory is known in fair detail.
Laboratory QA/QC will be performance-based, requiring the laboratory to demonstrate consistent
precision and accuracy on a standard reference material (SRM) which is a similar matrix to the
samples. The closest SRM to fish tissue is the National Institute of Standards and Technology (MIST)
SRM 1974, which is mussel tissue. This will be used as the SRM. Other laboratory QC would include
laboratory method blanks, matrix spikes, duplicates, calibration check standards, and internal
standards or concentration corrections based on surrogate recovery.
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TABLE 3-2. ANALYTES TO BE MEASURED IN FISH TISSUE FOR THE 1992 EMAP-SW NORTHEAST LAKES
PILOT SURVEY
Analyte (CAS Number)
Detection Limits (ppm)
Aldrin (309-00-2)
Aluminum (7429-90-5)
Arsenic (7440-38-2)
Cadmium (7440-43-9)
Chlordane-cis (5103-71-9)
Chromium (7440-47-3)
Copper (7440-50-8)
2,4'-DDD (53-19-O)
4,4'-DDD (72-54-8)
2,4'-DDE (3424-82-6)
4,4'-DDE (72-55-9)
2,4'-DDT (789-02-6)
4,4'-DDT (50-29-3)
Dieldrin (60-57-1)
Endrin (72-20-8)
Heptachlor (76-44-8)
Heptachlor Epoxide (1024-57-3)
Hexachlorobenzene (118-74-1)
Hexachlorocyclohaxane [Gamma-BHC/Lindane] (58-89-9)
Iron (7439-89-6)
Lead (7439-92-1)
Mercury (7439-97-6)
Mirex (2385-85-5)
Nickel (7440-02-0)
trans-Nonachlor (3765-80-5)
PCB Congeners
2,4-Dichlorobiphenyl (34883-43-7)
2,2',5-Trichlorobiphenyl (37680-65-2)
2,4,4'-Trichlorobiphenyl (7012-37-5)
2,2',5,5'-Tetrachlorobiphenyl (35693-99-3)
2,2',3,5'-Tetrachlorobiphenyl
2,3',4,4'-Tetrachlorobiphenyl
2,2',4,5,5'-Pentachlorobiphenyl (37680-73-2)
2,3',4,4',5-Pentachlorobiphenyl (31508-00-6)
2,2',4,4',5,5'-Hexachlorobiphenyl (35065-27-1)
2,3,3',4,4'-Pentachlorobiphenyl
2,2',3,4,4',5-Hexachlorobiphenyl (35065-28-2)
2,2',3,4',5,5',6-Heptachlorobiphenyl (52663-68-0)
2,2',3,3',414'-Hexachlorobiphenyl (38380-07-3)
2,2',3,4,4',5,5'-Heptachlorobiphenyl (35065-29-3)
2,2',3,3',4,4',5-Heptachlorobiphenyl (35065-30-6)
2,2',3,3',4,4',5,6-Octachlorobiphenyl (52663-78-2)
2,2',3,3',4,4',5,5',6-Nonachlorobiphenyl (40186-72-9)
Decachlorobiphenyl (2051-24-3)
Silica [Silicon] (7631-86-9)
Silver (7440-22-4)
Tin (7440-31-5)
Zinc (7440-66-6)
0.00025
10.0
2.0
0.2
0.00025
0.1
5.0
0.00025
0.00025
0.00025
0.00025
0.00025
0.00025
0.00025
0.00025
0.00025
0.00025
0.00025
0.00025
50.0
0.1
0.01
0.00025
0.5
0.00025
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
1.0
0.01
0.05
50.0
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3.9 PHYSICAL HABITAT QUALITY
One of the overall EMAP-SW objectives is to describe the present condition of surface water resources
in a manner that will provide quantitative benchmarks against which to detect future trends. The
status of ecosystem 'health* will be gauged through a number of indices which are based on biotic
species and their relative abundance. The habitat templet concept (Southwood, 1977), suggests that
much of the variation in aquatic species and abundance within any given zoogeographic province
results from naturally occurring differences in physical habitat structure and hydraulic characteristics
among surface waters. Structural complexity in aquatic habitats provides the variety of physical and
chemical conditions that are necessary to support biological diversity and foster long-term ecosystem
stability (Gorman and Karr, 1978; Poff and Ward, 1989). Of critical importance to EMAP-SW is the
major role of anthropogenic alterations of physical habitat in loss of aquatic species and the
degradation of aquatic ecosystems (Miller, et al., 1989). The natural complexity of physical habitat in
aquatic ecosystems is often simplified greatly as a result of such activities as wetland drainage,
grazing, farming, bank revetment, and flow modifications (e.g., Seddell and Froggatt, 1984; Elmore
and Beschta, 1987; Naiman, et al., 1988).
A major role of physical habitat data interpretation in EMAP-SW is to aid the understanding of biotic
response indicators. Our current approach is to develop and test indices of lake size/persistence,
habitat structural complexity, shoreline vegetation structure, and shoreline anthropogenic disturbances
(Table 3-3). In addition, two critical lake attributes important for assessment of lake trophic status are
lake residence time and an estimate of the areal or volumetric extent of aquatic macrophytes. Lake
residence time can be approximated from precipitation and evapotranspiration if lake volume is known
(along with lake surface area and watershed area). Estimates, from lake bathymetry, of the
percentage of the lake area covered with aquatic macrophytes, or having depth less than some stated
value, also allow an index of the potential importance of shallow water habitat and littoral processes.
3.9.1 Overall Objectives
• Develop and measure quantitative, reproducible indices that:
Describe biologically relevant aspects of lake morphometry, hydrology, and shoreline
characteristics.
Can be used to classify lakes on the basis of physical habitat, and monitor change through
time.
3.9.2 Summary of FY91 Activities
Physical habitat pilot activities in FY91 were aimed primarily at testing the logistical feasibility of the
shoreline and littoral physical habitat survey, and assessing the biological relevance of physical habitat
measures and their sensitivity to anthropogenic disturbance. Although we did use map-derived
variables such as lake area, shoreline length, and 'development of shoreline* to help define expected
values of biological variables, less emphasis was placed on other measures of physical habitat
obtained from maps or that could potentially be obtained from remote imagery.
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TABLE 3-3. LAKE PHYSICAL HABITAT INDICES TO BE TESTED FOR EMAP-SW
Variable
Protocol
LAKE SIZE AND PERSISTENCE INDEX COMPONENTS
Lake Surface Area
Maximum Lake Depth
Lake Level Fluctuation
Lake Residence Time
Determined by planimetry on 1:24,000-scale maps. Where available, mapped lake areas will be
compared with those measured from recent aerial photographs.
Measured in field by crew judgement of deepest location. Compare results with those from
bathymetric map and/or sonar survey.
Measure and calculate percent changes in lake maximum depth and lake surface area from field
shoreline surveys. Field crews estimate typical annual depth variation by examining shoreline
vegetation and watermarks to determine (using rod and clinometer) the typical* annual difference
between high and low water levels. Useful nondimensional ratio is [annual depth
difference /[maximum depth . For percentage change in lake area, field crews examine shoreline
vegetation and watermarks in several locations to estimate and then roughly map the 'typical'
annual difference between shoreline location at low and high water - assumes late summer
sample time is a good surrogate for the lowest water level; this is not perfect for all regions.
Tr = [Estimated volume /[Runoff * Topographic watershed area , where volume is estimated from
bathymetric maps or known documents, runoff is from runoff maps, and topographic watershed
area is determined by planimetry from boundaries drawn on 1:24,000 scale U.S. Geological Service
(USGS) maps.
LAKE HABITAT COMPLEXITY INDEX COMPONENTS
Littoral Dominance
Bottom Habitat Complexity
Shoreline Complexity
Indices under consideration are the percentages of the lake area with aquatic macrophyte beds, the
percentage with depth less than some named value (e.g., 3m), or the percentage with depth less
than the measured Secchi depth.
We propose that field crews criss-cross each lake with 5 to 7 transects recording depth with a
recording analog sonar fish finder.' A bathymetric map is constructed from this data using a
contouring program. The coefficient of lake depth variation from a "smooth" bottom curve along a
transect of lake depth will be used to obtain an additional index of lake bottom complexity.
Shoreline development (DL) will be indexed as: DL = L/[2(_A)0.5 .where L is mapped shoreline
length from planimetry, and A is the lake surface area. DL relates the deviation of the lake
shoreline from a perfect circle. An alternate index under development is measured by evaluating
characteristic sizes of shoreline indentations over a range of spatial scales by examining aerial
photographs and field data with "box filling' algorithms (Loehle, in press). This approach calculates
the change in the fractal dimension of lake shoreline length with increasing spatial scale (from
meters to kilometers). •
LAKE SHORELINE CHARACTERIZATION
Shoreline Littoral Habitat
Near Shore Habitat
Shoreline/littoral habitat frequency and distribution of shoreline fish concealment, littoral substrate
size, emergent, submergent, and floating macrophytes, based on systematic field observations.
Percent and distribution of near-shore terrestrial/wetland habitat in various habitat classes based on
systematic field observations supplemented by maps and aerial photos. Potential classes include
urban, industrial, forest, shrub, grassland, row crops, barren, wetland.
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The physical habitat survey employed a randomized, systematic plot design that located 10 equally
spaced observation plots around each of the 19 indicator development lakes. From a boat anchored
10m offshore, field crews made semiquantrtative observations of vegetation structure and
anthropogenic disturbances on plots 15m wide extending 15m back from the shore. Littoral
observations of shoreline substrate, bottom substrate, near-shore fish cover, and anthropogenic
disturbances were made along the 15-m shoreline plots and the water between the shore and the
observation boat (10m). These procedures are described in detail in Appendix B of the operations
and training manual (Tallent-Halsell and Merritt, 1991).
Field crews usually required about 5 to 10 minutes to complete the required observations and move
on to the next station. Therefore, crews completed the 10 sites of the physical habitat survey in 1 to 2
hours, including time spent making qualitative habitat maps and assessing the potential of shoreline
sites for fish sampling. Not surprisingly, surveys of the largest lakes took the most time.
Two basic approaches were used to calculate whole lake index values of physical habitat observations
from the 10 station observations on each lake. In the first, they were made by tallying the frequency
of occurrence or the mean cover of the various vegetation types, human disturbances, or fish cover
types among the 10 shoreline stations. In the second, the nargets" of the observations themselves
were expanded or generalized before tallying the mean lake value or the frequency of occurrence.
For example, derived variables were created that enumerated the different types of human
disturbances and, separately, the number of types of fish cover at each station. Whole lake values
were then calculated for the mean number of human disturbances (or fish cover types) at the 10
stations, and also the proportion of lake shoreline stations with human disturbances (or fish cover) of
any type.
The primary approaches for assessing 'biological relevance* and sensitivity to anthropogenic
disturbance were:
• Examine associations between physical habitat variables and those quantifying in-lake biological
response or anthropogenic stressors at the landscape level to ascertain if the physical habitat
variable might presently be a control on EMAP-SW response variables.
• Examine conceptual models of stressors, exposures, and responses to ascertain whether each
physical habitat variable is measuring some attribute of exposure, habitat, or stress potentially
important as a control on EMAP-SW response variables - even if it appears not to be a control at
present.
Examination of associations is ongoing, but analyses to date indicate that the physical habitat
shoreline survey results probably provide useful information concerning controls on fish, birds, and
chemistry. Simple bivariate plots showed that Secchi disc transparency, percentage of intolerant fish
species, and percentage of native fish species, were all inversely related to the mean number of
human activities per station. Lake water chloride concentrations increased with progressive increases
in shoreline disturbances. The extent of canopy and mid-layer dominance in shoreline vegetation was
generally inversely related to the extent and number of observed human disturbances, but appeared
to detect more subtle effects of past silvicultural activities.
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After correcting for predictable increases in native fish species richness associated with increases in
lake surface area, most lakes followed a pattern of declining native fish species with increasing extent
and number of human disturbances along the lake shorelines. Exceptions to this pattern were Russell
and Nesowadnehunk lakes - Russell perhaps because of relatively acidic conditions; Nesowadnehunk
probably because shoreline observations of disturbance did not detect the effects of shoreline logging
within the last 20 years. The vegetation cover variables were also associated with the species
composition of fish assemblages, though the vegetation may simply be a good indicator of aggregate
lakeshore disturbances. After correcting for the predictable increase in total fish species richness that
is associated with increases in lake surface area, most lakes followed a pattern of increasing fish total
(and native) species richness with increasing extent of relatively undisturbed shoreline vegetation.
The shoreline vegetation cover observations were sensitive to silvicultural effects and appeared to
measure vegetation characteristics important for lake shore birds. Preliminary analyses of lakes with
and without residential development show a gradient in bird assemblages from dominance of canopy
and brush dwelling insectivorous birds to dominance by ground feeding generalist and seed-eating
species as the areal cover of tree canopy and mid-layer vegetation declines. Except for notable
exceptions, canopy and mid-layer vegetation cover were inversely related to indices of anthropogenic
disturbance, such as the extent and number of various types of disturbance, including buildings,
docks, lawns, and agricultural fields.
The replication of physical habitat shoreline surveys that was originally planned on the 19 indicator
lakes was not carried out, so measurement variability was only crudely estimated from replicates on
two lakes. Despite often large differences for many single variables at single physical habitat stations,
we recorded relatively minor differences between crews and between different station placements for
whole-lake values of summary physical habitat variables. These included mean areal cover of tree
canopy and mid-layer vegetation, the extent and mean number of human disturbances, dominant
shore and bottom substrates, and the extent and mean number of fish cover habitat. These results
suggest that the survey approach is probably sufficiently robust to 'correctly' classify lakes along
gradients of habitat quality, shoreline vegetation structure, or shoreline anthropogenic disturbances.
During FY92, physical habitat activities will test this supposition.
3.9.3 Objectives for FY92
• Implement physical habitat shoreline survey in all lakes in which fish assemblages are sampled.
• Quantify the precision of physical habitat variables obtained from the shoreline-littoral habitat
survey.
• Implement a rapid protocol for estimating lake bathymetry and assessing aquatic macrophyte cover
in all lakes sampled by field crews in boats.
• Quantify the precision and accuracy of rapid bathymetry and macrophyte protocols.
• Develop and refine definitions of lake physical habitat quality indices.
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3.9.4 Data Collection and Analysis
3.9.4.1 Shoreline/Littoral Physical Habitat Survey
The physical habitat survey employs a randomized, systematic plot design with 10 equally spaced
observation plots located around each sample lake. Crews will go into the field with pre-marked lake
outline maps showing the 10 physical habitat stations on each lake. Stations will be permanent, but
not monumented; crews will have to relocate them each time the lake is visited. From 10m offshore,
field crews in boats will make semiquantftative observations of vegetation structure and anthropogenic
disturbances on plots 15m wide extending 15m back from the shore. Littoral observations of shoreline
substrate, bottom substrate, near-shore fish cover, and anthropogenic disturbances were made along
the 15m shoreline plots, and the water between the shore and the observation boat (10m). These
procedures and the field forms used are described in detail in Appendix B of the operations and
training manual (Tallent-Halsell and Merritt, 1991).
The shoreline/littoral survey shall be replicated on 20 of the EMAP-SW 1992 Northeastern Lake Pilot
sample lakes. These will be the same lakes in which fish assemblage sampling is replicated. Physical
habitat survey replication will be done by a different crew that will independently locate and make
observations at the same 10 locations that are predetermined and marked on lake outline maps.
Other than calculation of pooled 1 degree-of-freedom estimates of "index" variance (measurement +
crew + within index period), data reduction and analysis will be as described above for the 19
indicator lakes under Section 3.9.2. The precision of physical habitat measures relative to the
magnitude of meaningful differences in lake condition will be assessed by comparing index variance
for individual and summary physical habitat variables with the total variance across the regional
sample. Additionally, comparisons of coefficients of variation among the various direct and derived
physical habitat measures will guide efforts at refining the survey methods.
3.9.4.2 Rapid Protocol for Bathymetry and Aquatic Macrophytes
Field crews will be given premarked lake outline maps showing 2 to 4 transects crossing each lake
along the long and short lake axes. Traversing these transects by boat at constant velocity, field
crews will use chart-recording fathometers to obtain sonar traces of the lake bottom depth and the
depth to the top of aquatic macrophytes along these transects. If portions of any transect are
inaccessible to the boat because of insufficient depth or dense macrophytes, they will mark the map
accordingly, and will record the latitude/longitude positions at the beginning and end of the actual
transect measured in the field.
The field sonar depths and the weed extent will be marked on lake outlines, interpolating bathymetric
contours and the line of weed extent. Our working approximation for contouring is that the rate of
depth change and the distance of weed extent from shore will change in linear fashion between
transects, but we will use judgment in smoothing bathymetric contour lines across bays and inlets.
The same procedures will be used to draw a map representing depths at the top of the weed beds.
We will use planimetry to estimate the areal extent of aquatic macrophytes and the lake areas
corresponding to the depth contours. Summing the areas of the separate depth contours will give an
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estimate of the lake volume. Similarly, summing the volumes at each depth contour from the map
describing the depth to the top of the weed beds yields an estimate of the lake volume minus weed
beds.
The information obtained will be approximate lake volume, percentage littoral area, percentage
macrophyte extent, and the percentage of lake volume occupied by aquatic macrophytes. The
precision of these measurements will be estimated by replicating them on 20 lakes. Their accuracy will
be assessed by comparing the rapid index values to those estimated using much more intensive
sonar methods on a subset of 10 lakes.
3.9.4.3 Other Physical Habitat Variables
Map-derived variables such as lake area, shoreline length, and 'development of shoreline* will be
measured and recorded to help define expected values of biological variables (Table 3-3). In addition,
an array of information including watershed morphometry, topography, land use, land cover, and
geographic location will be collected as part of the Landscape Stressor Indicator activities' At present
there are no formal plans to obtain other measures of physical habitat that might potentially be
obtained from remote imagery, although we will attempt to classify lake macrohabitats from aerial
photographs taken by field crews accessing a subset of lakes by helicopter.
3.9.5 Data Verification and Validation
The data quality objectives for lake physical habitat data are described by Paulsen, et al. (1991).
Peck, et al. (in preparation) describe protocols for insuring data representativeness, accuracy, and
precision necessary to meet those objectives. These include field personnel training, field audits,
sample unit definition and replication, and data verification/validation procedures. Data quality
assessment will be based upon measurement replications designed to assess variance due to
temporal, spatial, and crew differences (see Peck et al., in preparation). Data verification and
validation activities will involve double-entry of data from field forms and logic checks to detect and
recheck impossible and unlikely field data entries.
3.10 WATER QUALITY
3.10.1 Overall Objectives
• Develop and measure quantifiable, reproducible indices that describe the chemical characteristics
of lakes that influence biota.
• Assess the status and trends in lake trophic state.
• Monitor the change in acid-base status in acid-sensitive regions of the U.S. (EMAP-TIME).
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3.10.2 Summary of FY91 Activities
In the 1991 EMAP-SW Northeast Lake Pilot Survey, water chemistry samples were collected from 111
lakes: 19 indicator evaluation lakes, 28 augmented grid lakes for EMAP-TIME, and 64 regular grid
lakes. Using the grid lake data, we will make initial estimates of the trophic state and acid-base
condition of Northeast lakes. The data will also provide the first year of data for assessing trends in
condition in the future.
Repeat samples, collected roughly 2-3 weeks apart, were taken in 22 of the grid lakes. In 4 grid lakes,
all three field crews sampled the lake within a 1-2 day period to assess crew variability. In addition, 14
natural audit samples were collected over the course of the summer to assess system level, precision,
and accuracy. From this data we will quantify analytical, crew, within-index period, and regional
variability in chemical indicators.
3.10.3 Objectives for FY92
• Collect a second year of data for evaluating trends in acid-base status of Northeast lakes as
mandated in the revised Clean Air Act.
• Develop classification of lake water chemical types.
• Assess annual variability in chemical habitat indicators.
• Develop lake trophic state indices (using combinations of total phosphorous, total nitrogen,
chlorophyll, and macrophyte abundance to assess trophic state).
3.10.4 Data Collection Plan
3.10.4.1 Plot Design
Lakes for sampling in 1992 are chosen from the Year 2 EMAP-SW hexagons in the Northeast. In
addition, ten of the Year 1 (1991) grid lakes will be revisited to assess between year variability. Water
samples for lake characterization will be collected from a depth of 1.5m (0.5m depth in lakes < 2 m
depth) at the deepest point in the lake according to protocols described in the EMAP-SW Field
Methods Manual (Tallent-Halsell and Merritt, 1991).
3.10.4.2 Methods Summary
Variables to be measured and analytical protocols are described in Table 3-4.
3.10.4.3 Collection Procedure
Water samples will be collected from the index location using a Van Dorn Sampler (Tallent-Halsell and
Merritt, 1991). From the Van Dorn, four 60-mL syringes will be filled and sealed for analytes requiring
closed headspace samples. In addition, one 4-L cubitainer will be filled for analysis of other chemical
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variables. Samples will be kept in a cooler on ice and shipped by overnight courier to the analytical
laboratory for processing and analysis. In situ measurements of Secchi depth and DO/temperature
depth profiles will be made as described in the Field Methods Manual (Tallent-Halsell and Merritt,
1991). Water from the Van Dom sampler will be filtered, and the filter preserved frozen for chlorophyll
analysis.
3.10.5 Data Analysis Plan
3.10.5.1 Index Definition and Development
For water chemistry, lakes will be indexed using a single, deep water epilimnetic sample. In lakes with
no apparent deep basin, a single mid-lake location will be used. This approach was used with a great
deal of success in monitoring the acid-base status of lakes in the U.S. in the National Surface Water
Survey (Baker, et al., 1990). Intense spatial sampling in a small number of grid lakes in the summer of
1991 showed very little spatial variability in lake conductivity. Thus, spatial variability in the index is
probably not a major issue for the chemical variables in Table 3-4.
3.10.5.2 Index Interpretation
For EMAP-TIME, the water chemistry indicators are the endpoints of concern. Status and trends in
acid-base chemistry will be assessed through measurements of acid neutralizing capacity (ANC), pH,
inorganic monomeric aluminum, and other chemical variables. Estimates of indicator sampling
precision, within-season variability from FY91 data, information from FY92 data on between-year and
regional variability, plus data from available long-term data sets will be used to quantify the variance
components for each chemical indicator. This quantification will allow us to assess significance in
observed trends in EMAP-TIME chemical endpoints and to assess the bias in EMAP-SW population
estimates.
3.10.5.3 Proposed Statistical Summary
Statistical summaries of the population mean, standard deviation, quartiles, and a plot of the cdf will
be made for each measured chemical variable. These population estimates will be made for both
number and area weightings. Estimates will also be made for the number and area of the lake
resource with values of ANC, pH, inorganic aluminum, total phosphorous, and Secchi depth outside
standard reference values.
3.10.5.4 Data Verification and Validation
Data will be verified and validated according to flow charts and protocols described in the EMAP-SW
QA Plan (Peck , 1991). Verification primarily checks the chemical consistency of the data within the
sample (charge balance, calculated versus measured conductivity, etc.). Validation typically
addresses the relationship between the samples. Raw data from field forms will be double entered
and checked for consistency.
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TABLE 3-4. UST OF EMAP-SW/EMAP-TIME CHEMICAL MEASUREMENTS AND METHODOLOGIES'
Variable
Method
MAJOR ANIONS
Sutfate
Nitrate
Chloride
MAJOR CATIONS
Sodium
Potassium
Magnesium
Calcium
Ammonia
Total Dissolved Aluminum
CLOSED HEADSPACE MEASUREMENTS
PH
Dissolved Inorganic Carbon
Total/Organic Monomeric Aluminum
TfTRATION
Acid Neutralizing Capacity
NUTRIENTS/TROPHIC STATUS
Total Phosphorous
Total Nitrogen
Chlorophyll-a
Total Suspended Solids
Turbidity
Color
OTHER LABORATORY MEASUREMENTS
Dissolved Organic Carbon
Dissolved Silica
Air equilibrated pH
Specific Conductance
IN SITU MEASUREMENTS
Temperature
Dissolved Oxygen
Secchi Depth
Ion Chromatography
Ion Chromatography
Ion Chromatography
Atomic Absorption Spectroscopy
Atomic Absorption Spectroscopy
Atomic Absorption Spectroscopy
Atomic Absorption Spectroscopy
Phenate Colorimetry
Atomic Absorption Spectroscopy
Potentiometric
Instrumental Carbon Analyzer
Pyrocatechol Violet Colorimetry
Acid Titration with Gran plot
Digestion/Phosphomolybdate Colorimetry
Digestion/Nitrate Colorimetry
Spectrophotometrically
Fitter/Weighing
Spectrophotometrically
Comparison to Color Standards
Instrumental Carbon Analyzer
Molybdate Colorimetry
Potentiometric
Conductivity Cell
YSI Meter
YSI Meter
Secchi Disk
* All samples will be kept refrigerated and in the dark until analysis.
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SECTION 4
DESIGN
4.1 INTRODUCTION AND OBJECTIVES
One of the design objectives for the FY92 Northeast Lakes Pilot is to select a set of lakes from the
EMAP-SW grid for pilot field activities. The selection of these lakes must be in accordance with the
criteria established for the EMAP probability sampling design (Overton, et al., 1992). Analysis of
indicators from these lakes ultimately will allow us to evaluate the effectiveness of the baseline grid
probability sample design to adequately capture and characterize the diversity of lake resources.
4.2 SELECTION OF GRID LAKES
In accordance with the basic design principles established for EMAP, two fundamental criteria guide
lake selection. The first criterion is that samples are to be selected using probability methods, so that
uncertainty in the descriptions of the condition of resources can be calculated. The second criterion
is that the sample maintains spatial representativeness, so that the population descriptions reflect the
spatial distribution of the resources of interest. For lakes, spatial representation means that sample
selection reflects the spatial distribution of the population of lakes; where lake density is high,
sampling intensity should also be high, and where lake density is lower, sampling intensity should be
lower. Exceptions may occur where it is desirable to focus on selected subpopulations; however,
even within areas where these subpopulations can be defined, spatial representation remains an
important criterion.
The randomly placed, systematic triangular grid establishes the general framework by which these
requirements are met. The search areas specified by the 40 km2 hexagons centered around each
grid point assure spatial representation in the selection of lakes at the first stage (Tier 1 sample) of the
lake selection process. Only a subset of this Tier 1 sample of lakes will be visited in the field to make
measurements on the condition of lakes (Tier 2 sample). The selection of the Tier 2 sample also
should meet the two basic design criteria This section describes the steps for the selection of the
Tier 1 and Tier 2 samples for the 1992 Northeast Lakes Pilot Survey. During the spring of 1991, there
was a possibility that a national lake survey would be conducted during 1992; therefore, national Tier
1 and Tier 2 samples were drawn. Eventually, the survey was limited to the northeast, so for further
processing, the national sample was restricted to the northeast.
NOTE: In the following sections, unless otherwise noted, the base grid density (a triangular array of
approximately 12,600 points fixed across the conterminous United States) will be assumed,
and 'hexagon' will refer to the 40 km2 hexagon surrounding each grid point.
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4.2.1 Frame and Tier 1 Sample Selection
The hydrographic layer carried in the USGS 1:100,000-scale Digital Line Graph files (DLGs) is used as
the basic frame, representing the population of lakes across the conterminous United States. These
digital files contain the location, perimeter, area, and boundary of each lake and can be used to
display the spatial distribution of lakes, including sizes < 1 hectare (ha) as represented on the USGS
1:100,000-scale map series. Our target population consists of all lakes > 1 ha, with the exception of
the Laurentian Great Lakes.
The 1:100,000 DLGs have been incorporated into EPA's River Reach File, an inventory of hydrologic
features in the conterminous United States. The original version of the River Reach File was based on
hydrology (primarily stream traces) available on 1:500,000 scale maps. Subsequent versions have
increased the spatial coverage and have included other types of waterbodies. The present version,
termed RF3, incorporates the DLGs as the basic hydrologic framework. The RF3 has the capability to
identify and extract a file of lakes (or stream segments) for geographic areas specified, or for the
entire country. Therefore, the file of lakes extracted via RF3 was primarily used as the lake frame for
EMAP-SW.
At the time the lakes were selected for the FY92 pilot, RF3 was incomplete; the states of California,
Idaho, Oregon, and Washington had not been incorporated, and there were miscellaneous USGS
cataloging units (approximately 4% of the conterminous U.S.) that were not yet part of the file. For the
western states not part of RF3, we used the same GIS procedure developed for the FY91 pilot to
extract lakes directly from the DLGs (see Selle, et al., 1991 for.details of the procedure used). In both
cases (RF3 and direct extraction from the DLGs), because lake surface area is part of the file, the
inventory can be used to create size distributions, to select subpopulations based on size, and to
create maps of the distribution of various size classes of lakes.
The Tier 1 (T1) sample of lakes was obtained by evaluating which lakes had label points in the 40 km2
hexagons (each lake is uniquely represented as a set label point in the GIS). The initial screening of
the T1 sample indicated that there was an insufficient number of lakes > 500 ha selected from the
grid. Alternatives to increase the sample size of large lakes were to intensify the grid, or to select
large lakes from a list frame; the latter method was chosen for ease of implementation.
In accordance with the interpenetrating nature of the EMAP probability design, one-fourth of the Tier 1
sample is considered for field sampling each year. During FY91, the set of lakes associated with the
first cycle was chosen, designated here FY91T1; for FY92, the lakes associated with the second year
of the cycle are used (FY92T1).
4.2.2 Identifying Frame Errors and Lakes for Field Sampling
Creation of the lake frame from RF3 and the DLGs introduces errors that must be identified. Bays,
wide spots in rivers, or small sections of larger lakes occasionally appear as separate lakes in the
frame; also locations identified as waterbodies sometimes were misidentified features. These frame
errors can be quantified by field reconnaissance and queries of knowledgeable local individuals.
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In addition, the frame contains some features identified as waterbodies (selected as lakes with the lake
selection algorithms) that will not be sampled in the field for response, exposure, and habitat
indicators even though these features may be important types of waterbodies. For example, listed
waterbodies may be too shallow to sample for lake indicators, or may be marshes or be dried up
entirely at the time of sampling; in some cases, lakes and reservoirs may have been drained since the
time of mapping. Such changes of class may be a sensitive indicator of change. Consequently, we
plan to track the aquatic class of such places to determine the proportion of the frame population they
comprise, and eventually develop indicators of their condition, as resources permit and their
importance is clarified.
Prior to selection of the FY91 Tier 2 sample, we evaluated the FY91T1 sample for errors and changes
by examining larger scale maps (7.5-minute topographic and larger scale county maps) and via
discussions with local experts. Four categories of lakes were identified for exclusion from field
sampling in the Northeast: (1) cranberry bog reservoirs; (2) waterbodies identified as portions of larger
lakes; (3) wide spots on rivers; and (4) miscellaneous errors. Approximately 15% of the FY91T1
sample fell into these categories, with most lakes (45 out of 48) being less than 20 ha in surface area.
These types of waterbodies identified in the FY91T1 sample were excluded before the Tier 2 selection.
Because of a limitation on resources and time, we did not perform the Tier 1 screening for the FY92
selection. Instead, we used the information gathered during FY91, both at the Tier 1 and Tier 2 levels,
to estimate the amount of overselection necessary to achieve a desired Tier 2 sample of actual lakes
for field visitation.
Identifying lakes not represented by the frame materials will be more difficult and has not been
planned as part of this pilot activity. Some methods considered for identifying lakes not represented
in the frame include using remote aerial imagery/photography and relying on local experts to provide
detailed area knowledge. Both, either in conjunction or separately, can be compared to the lake
frame. Our initial sense is that the frame overrepresents lakes of interest and that there is a relatively
low proportion of lakes missing from the frame.
4.2.3 Stratification Strategies
Some discussion has centered on the desirability of stratifying lakes by subpopulations as part of the
Tier 1 activity. Part of the discussion was whether a lake classification (other than that based on size)
ought to be developed to stratify the Tier 1 sample. Because of the variety of overlapping
classifications, it was decided that classification would be best performed as part of the evaluation of
results; the lakes can be classified on the basis of the Tier 2 sample and the data summarized
according to various subpopulations. After evaluation of the pilot results, we may discover compelling
reasons to stratify at Tier 1 in the future.
A second part of the discussion was whether to select lakes of different sizes with variable
probabilities. A simple random sample would select lakes in proportion to their abundance; most of
the sampling effort would occur on the smaller lakes. An attractive approach was to allocate equal
numbers of samples along a logarithmic or square root transformation of surface area to select more
large lakes than would have been selected otherwise. However, allocating samples along a
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continuous scale requires using variable inclusion probabilities, substantially complicating variance
estimation (Overton, et al., 1992) and the use of model-based statistical methods. Therefore, size
classes were selected, summarized in Table 4-1, along with other information relevant to the target
population, and Tier 1 and Tier 2 sample sizes. This foresees the likelihood that some subpopulations
of interest may be based on size; unless inclusion probabilities are varied by size class, some
important subpopulations would be undersampled to support meaningful inferences.
4.3 TIER 2 SAMPLE SELECTION
The basic design requirements were followed for the Tier 2 selection of lakes for field sampling during
the 1992 index period. For general planning purposes, EMAP guidelines target field visitation of
approximately 800 sample units per resource type (i.e., 800 lakes). We used this as the target for
drawing the national FY92 Tier 2 sample, although we would only sample those lakes in the northeast
region of interest for the pilot activities. In this way, the selection of lakes in the northeast would be
representative of the allocation of sampling based on national lake distribution and abundance.
4.3.1 Maintaining Spatial Distribution in the Tier 2 Sample
The selection of the Tier 2 sample from the Tier 1 set of lakes was done both to meet the need for a
probability sample and to represent the spatial distribution of lakes. Conceptually, the selection
process starts by dividing the region of interest into smaller compact clusters, then randomly selecting
lakes within each cluster with a probability based on their size class. The clusters were constructed to
have total inclusion probability of at least 2 in each of the four years of sampling. The inclusion
probabilities in Table 4-1 were chosen to give annual sizes of samples in each size class of
approximately the sizes given in the column labeled Target Annual Tier 2 Sample".
Since the primary function of the delineation of the clusters is to distribute the sampling effort in
proportion to the spatial distribution of lakes, their actual dimensions and boundaries are not critical.
However, compactness is a desirable feature; long, thin clusters are undesirable. Also, it is desirable
that at least one lake per cluster be selected, but the purpose of defining the clusters is somewhat
defeated if more than two or three lakes are selected within each. These desired features of clusters
were incorporated in a computer algorithm written by Don Stevens (ManTech Environmental Services,
ERL-Corvallis). Thus, the target cluster size is such that two lakes would be selected in each cluster
for each size class. Figure 4-1 shows the clusters determined for the conterminous United States.
Once the clusters were determined and hexagons and lakes assigned to clusters, the set of Tier 2
lakes was drawn by first ordering the clusters randomly, then within each cluster, ordering the
hexagons randomly, then within each hexagon, ordering the lakes randomly. These lakes were then
selected from this randomized sequence by a systematic draw with a random start. Large lakes
(>500 ha) were selected the same way as small lakes, except sampling considered all lakes rather
than only those occurring in the hexagons. Each of the large lakes was associated with the nearest
hexagon for purposes of using the clusters.
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This procedure produced a list (plotted in Figure 4-2) of Tier 2 lakes selected from the grid, in the
desired size strata, to be field visited for FY92. Only those lakes in the northeast region associated
with the second cycle of the four-year grid cycle will be field visited during FY92.
TABLE 4-1. NATIONAL LAKE TARGET POPULATION. TIER 1 AND TIER 2 LAKES, WITH INCLUSION PROBABILITIES
NUMBER OF LAKES IN
Size Class
(ha)
1-5
5-10
10-50
50-500
500-5000
>5000
Total
Total Target
Population
161,616
43,744
41,648
11,712
1,661
257
260,638
Tier1
Sample (All
Years)
10,101
2,734
2,603
732
na'
na
Target
Tier 2
Sample
(Annual)
100
250
200
100
100
50
800
Adj.
Tier 2
Sample
(Annual)
200
375
200
100
100
50
1,025
Actual
Tier 2
Sample
(1992)
188
413
197
97
111
10"
1,016
Annual
Inclusion
Probability
0.08x1/64=0.00125
0.6x1/64=0.0094
0.3x1/64=0.0047
0.55x1/64=0.0086
0.25x1/4=0.0625
0.2x1/4=0.05
' The Tier 2 lakes were selected directly from the target population of large lakes, so there were no Tier 1 large lakes.
b A total of 50 large lakes will be sampled over the four-year period rather than sampling 50 per year, which would represent
almost the entire target population after four years.
4.4 GRID INTENSIFICATION
Occasionally, for some subpopulations of special interest, the Tier 2 sample generated from, the base
grid selection may be too small to estimate condition and trends with the desired sensitivity and
precision. The systematic triangular grid can be intensified, yet retain the basic triangular structure, to
allow increasing the sample size for such purposes. One aspect of the EMAP-SW program
(Temporally Integrated Monitoring of Ecosystems [TIME]) required larger sample size in specific areas
of the northeast. The TIME program is designed to detect the response of lakes sensitive to acid
precipitation to changes in sulfate emissions dictated by the revised Clean Air Act. For most of the
area of interest in the northeast, the Tier 2 sample selected from the base grid is sufficient; however,
in two areas, a denser grid was required. A three-fold grid intensification was sufficient to increase the
Tier 2 sample to an adequate size for TIME. Otherwise, actual site selection followed the same basic
rules as for the base grid.
4.5 ANNUAL REPEAT VISITS
The basic EMAP-SW design calls for visits to individual lakes on a four-year cycle. During the initial
phases of the program, it is necessary to conduct some repeat visits on a more frequent basis than
this four-year cycle for several purposes. One is to develop data to estimate the magnitude of year-to-
year variation among individual lakes, an important factor for estimating the sensitivity of the design for
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Section 4
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trend detection. A second reason is to identify any major trends that might be evident during early
phases of the monitoring program. For these reasons, a subset of the lakes visited during FY91 will
be revisited during the FY92 through FY94 period.
The availability of annual revisit lakes 'connects* the information collected in each year, so that initial
indications of trends, if present, will be available after five years. These lakes were selected by
constructing eight superclusters in the northeast from the clusters of lakes developed for the FY91
pilot (Figure 4-3). The annual revisit lakes were selected from the Tier 2 lakes visited in FY91, using
the superclusters in the same manner as the clusters had been used to select the single year lake
visits.
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Section 4
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EMAP Statistical Clusters and Hexagon Centroids
f13f*l> 1991
Figure 4-1. Clutters used for the selection of the Tier 2 lakes for the 1992 Pilot Survey.
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Section 4
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s_ x* ; ,'—-•• *"*"*+1 r»;>I*'*'*v~ * 'r'J* » **» ^'
7-^ i * * / * ! ; •* * > *'j* » \*r-v*-*'X< /
vr._ ; / * K*i/:***^\***;/l-?r*v XC/
"\ / M *^^^4-A;V*^/
- ----\;^ ->>T^CJ^^
EMAP Lakes
Tier 2 Sample / FY 92
EMAP-SR 190CC91
Figure 4-2. Location of Tier 2 takes selected for a national lake survey, corresponding to the second year of a four
year EMAP cycle.
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Section 4
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Super Clusters for 1991 Sample
With Cluster Lines
For Selection of Annual Revisit Lakes
Figure 4-3. Super clusters used to select a subset of lakes monitored In 1991, which will be revisited during 1992-
1994. One lake from each euper cluster will be revisited. Original 1991 clusters are delineated by dashed lines.
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SECTION 5
•FIELD OPERATIONS
5.1 OVERVIEW OF FIELD OPERATIONS
Field operations for FY91 were quite successful. Minor adjustment will be made as a result of lessons
learned from last year. Field operations for the FY92 EMAP-SW Northeast Lakes Pilot Survey consist
of three primary activities. Those activities are: (1) continuation of FY91 pilot activities on the EMAP-
SW grid lakes, with the addition of fish and bird assemblages as an indicator; (2) implementation of
the second year of the TIME project on lakes in the Northeast; and (3) further evaluation of indicators
and methods on selected lakes. It should be noted that macroinvertebrate and sediment toxicity
samples collected during FY91 from the EMAP-SW regional probability lakes will not be sampled
during FY92. These indicators will undergo further investigation prior to implementation on the
regional probability lakes.
5.2 EMAP-SW REGIONAL PROBABILITY LAKES
Field activities planned for FY92 will be implemented jointly by EPA and the U.S. Fish and Wildlife
Service (USFWS). The USFWS is responsible for obtaining state collection permits, staffing field
teams, developing lake sampling schedules, sampling EMAP-SW grid lakes, and shipping samples
and data forms to the appropriate locations. The EPA is responsible for obtaining access permission,
providing field supplies and equipment, laboratory facilities, sampling protocols, training, and
coordination of field activities through a centralized communications facility, which is located in Las
Vegas, Nevada.
Approximately 70 different regional probability lakes, located across the 6 New England states and the
states of New York and New Jersey, will be sampled during the index period between July 6 through
September 18, 1992 (see Figure 2-1). Sixty of these lakes were selected for FY92 field activities. The
remaining 10 lakes are annual revisit lakes that were sampled during the FY91 pilot, and will be
sampled every year. Fifty of the lakes (including the 10 revisit lakes) will be intensively sampled for all
indicators, including fish and bird assemblage. It should be noted that bird assemblage data will not
be collected by the USFWS teams, but will be collected by 2-person crews from the University of
Maine in early June. Twenty of the intensively sampled lakes will be resampled (index revisit lakes) for
fish assemblage and physical habitat only. The remaining 20 lakes (core level lakes) will be sampled
for water chemistry, trophic state, and zooplankton only (see Figure 2-1). A total of 90 lake visits will
be made by the USFWS field teams.
Fifteen of these lakes do not have road access. A float plane and/or a special hike-in team will be
used to access these lakes. The float plane will be use on those lakes with landing distance greater
than 800 meters. Two flights to each lake will be required to transport the field team and sampling
gear.
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Six field teams will be required to sample the lakes described above (90 lake visits). Five of the teams
will consist of a 3-person crew. The sixth team will be a special hike-in team consisting of 6 to 8
people. Each of the 5 regular teams will sample 16 lakes over the 10-week index period. It is
estimated that each of these teams can sample two lakes per week. This allows approximately 2
weeks for down time or additional time for sampling large lakes during the 10-week index period.
These teams will sample lakes located in relatively small geographical areas (Table 5-1), except during
the 20 index revisits, when team locations will be rotated to determine index and crew variation. The
sixth special hike-in team will sample approximately 10 lakes located in Maine and New York. Due to
the long hike-in to these lakes, this team will only be able to sample 1 lake per week.
TABLE 5-1. PROPOSED LOCATION OF LAKE AREAS ASSIGNED TO SAMPLING TEAMS
Team Area
1 • Northern Maine
2 Southern Maine
3 New Hampshire, Massachusetts
4 Northern New York, Vermont
5 Southern New York, Connecticut, New Jersey
Two consecutive days will be required to sample the intensively sampled lakes, annual revisit lakes,
and the 20 index revisit lakes. Two days are required on these lakes because fishing gear (gill nets,
fish traps, etc.) will be set out overnight and retrieved the following day. A proposed weekly schedule
for the teams is presented in Table 5-2. This schedule is for lakes where fish assemblage data are
collected. In addition to sampling activities, the field teams are responsible for coordinating their
activities with the Communications Center, preparing status reports, maintaining equipment and
supplies, and shipping samples.
Field teams should be housed at motels within 50 miles of the lake to be sampled whenever possible.
Activities will start in the morning by calibrating the instruments and ensuring that all necessary
equipment is loaded into the two vehicles or 15-foot aluminum boat. On arrival at the lake, the field
team will verify that they are at the appropriate lake. Lake verification will be based on a combination
of landscape features, topographical maps, and global positioning systems (GPS). Field team duties.
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TABLE 5-2. SAMPLING TEAM WEEKLY ACTIVITIES SCHEDULE
Day(s) Activity
1 Verify lakes scheduled to be sampled with Communications Center.
Contact land owners or public officials as required.
Receive/obtain supplies and equipment
Repair/check equipment
Prepare/load boat and vehicles.
2 Locate first lake.
Set fishing gear.
Return to hotel or camp as required.
3 Retrieve/process fish.
Return/move to hotel.
Ship samples (if possible).
4 Ship samples not shipped on Day 3.
Receive/obtain supplies and equipment
Send data and sample tracking forms to Communications Center.
5-6 Repeat lake sampling activities at second lake.
Send data and sample tracking forms to Communications Center.
Relay supply needs to Communications Center.
Prepare and send weekly status report to Communications Center.
7 Off.
will be split between a 2-person boat crew and 1 base coordinator. The coordinator is responsible for
all administrative activities, assures the accuracy and completeness of field forms, and provides
logistics support (picking up equipment and supplies, shipping and sample tracking, etc.). The
coordinator will assist in some sampling activities, but at times will be separated from the boat crew in
the course of carrying out his/her duties.
On-lake sampling activities for the boat crew are summarized in Figure 5-1. The first day's activities
include measures of physical habitat, sonar transects, and temperature/DO profiles, which are used to
deploy the fishing gear. Activities on the first day extend into the evening with beach seining after
dark when seining is more effective. On the second day, the fishing gear is retrieved and
water/sediment samples (Table 5-3) are collected. Large lakes (> 500 ha) will require fishing gear to
be deployed again on the second day and water/sediment samples to be collected on the following
(or third) day. All field protocols will be documented in the field training and operations manual
(Merritt and Metcalf, in preparation).
-------
ON-LAKE ACTIVITIES
FULL SUITE SAMPLING
Section 5
September 1992
Page 4 of 6
Day 1
Day 2
10:00
10X10-12:30
1:30-3:30
3:30 - 4:00
4:00 - 4:30
4:30 - 8:00
9:00-11:00
Launch Boat
}
r
Physical Habitat
LUt
i
ICH
\
Sonar Transects
\
r
Locate Index Site
J
r
Temp./DO Profile
Secchi
J
r
\
17:00-11:00
1 1 IUU * 1 .UU
r
^ •
k
•
flflEAKF^Sr
1
— RAtriovfl Pi<*h C^oar ^B
Return Rsh, \m
Gear to Shore |
Collect Water, L
Sediment, •
Zooplankton |
Deploy Rshing Gear •
DIM
*
VEfl
Seine
M
1
4
Figure 5-1. Sampling acUvHUs tar boat erawa, EMAP-SW FY92 Northeaat Ukaa Pilot Survey.
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Section 5
September 1992
Page 5 of 6
TABLE 5-3. NUMBER AND TYPE OF SAMPLES TO BE COLLECTED, EMAP-SW FY92 NORTHEAST LAKES PILOT
SURVEY
Sample Number Type of Container
Zooplankton
Sediment Core
Water Chemistry
Chlorophyll a
Fish Tissue
2
1 top, 1 bottom
1
4
1
variable
125-milliliter Nalgene
2 1 -quart Ziplocs
4-liter Cub'rtainer
60-mllliliter syringe
OFF filter in foil
aluminum foil
5.3 TIME PROJECT LAKES
Approximately 35 lakes will be sampled for the TIME project. These lakes are all located in the
Adirondack State Park of New York except for 7 lakes located in southern Vermont and New
Hampshire. These lakes will be sampled by a 3-person EPA crew from Massachusetts and in Regions
1 and 2. A helicopter will be used to access lakes. It is anticipated that 4 to 6 lakes can be sampled
in 1 day, requiring less than 10 days to complete the sampling activity. Water chemistry samples
(Table 5-3) are the only samples that will be collected at these lakes. Helicopter sampling activities
and protocols are similar to those used in the EPA acid deposition surveys as described in the
National Surface Water Survey, Eastern Lake Survey (Phase I) Field Operations Report (Morris, et al.,
1986). All lakes will be sampled during the index period, but actual dates will be based on the
availability of the helicopter.
5.4 INDICATOR EVALUATION LAKES
Ten lakes will be selected from the 40 intensively sampled lakes for further methods development and
indicator evaluation. Based on available information provided by state environmental resource
agencies and local scientists, these lakes will be selected to provide a range of lake type and
conditions (e.g., temperature, conductivity, size, morphometry, trophic state, and contamination levels).
Indicators/methods to be evaluated are fish electroshocking, non-standard fish gear, echosounding,
and macroinvertebrate sample/processing techniques. Fish electroshocking will focus on physical
logistics, safety issues, and quantifying what additional biological data are obtained with this
equipment. Non-standard fish gear will also be evaluated as to what additional biological data are
obtained. The list of non-standard fish gear for evaluation will include angling, cast nets, short seines,
and buoyant nets. Protocols using a strip chart echosounder to define lake bathymetry and assess
macrophyte coverage will be developed and evaluated. The minimum number of echosounding
transects required for these activities in different lake types will be the primary focus of this evaluation.
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Section 5
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Macroinvertebrate sampling evaluations will focus on field screening with fine mesh sieves and
microscopic sorting of samples, and how additional taxa will contribute to this proposed EMAP-SW
indicator.
Two, 2-person field teams will be used to sample these lakes. These teams will be staffed with EMAP-
SW indicator leads and/or training personnel. One team will be responsible for the fish/echosounding
activities and the second team will be responsible for macroinvertebrate activities. One sampling day
per lake should be adequate to conduct these sampling activities. These teams will also be
responsible for conducting audits on the other sampling teams. Therefore, activities for these teams
will extend over a 4-week period.
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Section 6
September 1992
Pagel of 15
SECTION 6
QUALITY ASSURANCE PROGRAM
The philosophy of the EMAP-SW Resource Group is that quality assurance and quality control
(QA/QC) activities are integrated into all activities associated with the collection, measurement, and
management of environmental data and information for the EMAP-SW FY92 Northeast Lakes Pilot
Survey and TIME project. A formalized QA program helps ensure that data can be used with
confidence to provide information to satisfy both policy-related objectives of both programs (Section
1), and specific, research-related objectives that have been stated in this implementation plan for the
sampling design and for individual ecological indicators.
The EMAP-SW developed and implemented an integrated QA program for the FY91 Northeast Lakes
Pilot Survey and the TIME project. This program was documented in the quality assurance project
plan (QAPjP). The QAPjP (Peck, 1991) is being revised for the FY92 pilot survey to reflect additions,
modifications, and refinements of the program, based on evaluation of FY91 results.
Many aspects of the QA program implemented for the pilot survey are themselves at a rudimentary
stage of development. For a number of the indicators being used and evaluated, formalized QA/QC
practices have not been developed, or existing practices are not appropriate for the proposed
sampling strategy of EMAP-SW (i.e., synoptic sampling at a large number of lakes concurrently
collecting data for several indicators). Appropriate criteria for defining the 'quality of information
associated with various ecological indicators is also currently lacking. As EMAP-SW evolves toward
full implementation and subsequent determination of ecological condition, status, and trends, the QA
program must also be refined to develop appropriate data quality requirements. The allocation of
QA/QC efforts can be optimized based on this information. The sampling design can be refined for
future efforts with this information, in terms of the required number of lakes, and the temporal and
spatial allocation of sampling effort.
6.1 DATA QUALITY REQUIREMENTS
When fully implemented, it is anticipated that EMAP-SW will be guided based on well-defined data
quality objectives (DQOs). An important overall objective of the pilot surveys is to obtain the
information necessary to define these DQOs. Estimates of various components of variation (Section
3), as well as other potential sources of error associated with individual indicators, are required to
formulate DQOs. For example, in most cases, condition will probably be estimated by an index based
on some combination of different measurements. The statistical properties, underlying distributions,
and required assumptions of such composite indices are not known at present, and are similar in
many respects to problems encountered using other ecologically-based indicators, such as diversity
indices or niche metrics to compare different assemblages or ecosystems (e.g., Ricklefs and Lau,
1980; Smith, 1985).
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Section 6
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For the present time, data quality requirements within the EMAP-SW are being focused at the
measurement level. For each data acquisition activity within EMAP-SW, data quality requirements are
established for measurements in five areas (following Smith, et al., 1988). Precision and bias
requirements relate to the tolerable amount of random and systematic errors, respectively. Precision
and bias are determined through the use of replicate sampling and analysis, use of performance
evaluation (PE) samples of known composition, and, in the case of taxonomic identification, through
confirmatory identifications by independent experts. Where appropriate, method detection limits are
prescribed to ensure that measurements for constituents present at very low concentrations can be
used with confidence.
Completeness requirements stipulate the minimum amount of valid data necessary to confidently
interpret the information relative to research or policy-related objectives. In general, a minimum
number of lakes must be sampled to provide lake population estimates which have acceptable
confidence limits. For indicator measurement programs, data may need to be collected from lakes
representing a gradient in stressor intensity to properly evaluate the sensitivity of the indicator.
Comparability requirements establish the criteria that allow information collected by different sampling
teams (see Section 6.3) and measured by different laboratories to be confidently combined before
interpretation. Consistent use of standard procedures for data acquisition and subsequent reporting,
results of PE samples analyzed by different laboratories, or QA samples (e.g., split samples) are used
to ensure comparability in data and information. Documentation of methods, precision and bias, and
other pertinent information are required to determine comparability of the pilot survey data with other
data sets.
Requirements for representativeness are established to ensure that the information and interpretative
conclusions that result from a study provide accurate inferences to the true state of nature. The first
requirement for representativeness is a sampling design (Section 4) that provides statistically unbiased
(and thus representative) population estimates. Criteria are also established for obtaining ecological
data from lakes which are characteristic of conditions during the specified index period. In some
cases (e.g., water chemistry), a single sample is sufficient; in others (e.g., fish assemblages), several
different locations on an individual lake must be visited to obtain a single sample that adequately
characterizes the extant assemblage composition and relative abundance.
Requirements or acceptance criteria for each of these areas are documented for each indicator
measurement program or other element (e.g., design and site selection) in the EMAP-SW integrated
QAPjP (Peck, in preparation). Requirements are modified as necessary based on the evaluation of
new information or as research or program objectives are modified.
The success of the QA and QC measures implemented to maintain data quality within established
acceptance criteria is evaluated in several ways. Precision and bias associated with important
components of the sampling and measurement processes of individual indicators are evaluated using
results from replicate sampling and PE samples. Results of verification and validation procedures
(Section 6.5) provide information on the amount of acceptable data of the type required to satisfy the
requirements established for completeness. Information on precision, bias, and completeness are
used to determine the comparability of data acquired during the study. This information is important
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for those ecological indicators that must use additional information acquired as part of measurement
programs for other indicators (e.g., the sediment diatom assemblage indicator requires water
chemistry data to allow historical inferences to be made regarding trends in water quality
characteristics). After acceptable comparability is determined, overall representativeness of the
information in satisfying the research objectives can be ascertained.
Assessments of data quality against the established data quality requirements are conducted to
determine the overall performance of the QA program and to identify possible limitations to use and
interpretation of the data by EMAP-SW and other potential users. Such assessments are a part of
project interpretative reports, as well as other products (e.g., accompanying data bases).
6.2 SYNOPSIS OF QA/QC ACTIVITIES
Major elements of the QA program are presented in Table 6-1, and are generally applicable to all
types of activities related to data acquisition and management. Management policies and guidelines
related to the overall QA program for EMAP are documented in a QA program plan that all resource
groups within EMAP are expected to follow. The QAPjP (Peck, in preparation) documents the policies,
procedures, and acceptance criteria to define, monitor, and evaluate data quality for all data collection
activities to ensure they meet or exceed established requirements.
The Technical Director for EMAP-SW has appointed a QA coordinator to oversee the development and
implementation of the QA program for EMAP-SW. There is also a designated QA representative who
oversees those portions of the QA program which are of direct relevance to the TIME project. Certain
groups responsible for indicator measurement programs or laboratory support services may also have
designated QA personnel. The organizational structure and responsibilities within EMAP-SW are
documented in the QAPjP (Peck, in preparation).
The following sections summarize the major QA/QC activities being conducted for integrated
operations within EMAP-SW (design and site selection, field, and general laboratory) These activities
are applicable to all data collection activities conducted by EMAP-SW. Additional specific activities or
requirements for individual indicator programs are summarized in Section 6.4. The process for data
review, verification, and validation for intended use is described in Section 6.5.
6.3 SAMPLING DESIGN AND SITE SELECTION
Major QA/QC aspects related to the design have been presented in Section 4.2 (identifying frame
errors) and Section 4.3 (maintaining spatial distribution of the Tier 2 sample). A first level of evaluation
occurs with preliminary reconnaissance of lakes in the region. During this phase, DLG-based
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TABLE 6-1. ELEMENTS OF THE QUALITY ASSURANCE PROGRAM FOR EMAP-SW
Program Element
Mode of Implementation
Document plans, procedures, methods, and data
quality requirements.
Responsibility and accountability.
Ensure appropriate technical skills and
competency of project participants.
Correct and consistent implementation of
required procedures.
Maintain data acquisition systems within required
data quality criteria.
Ensure recorded data and information are
accurate and of acceptable quality.
Determine and report achieved quality of data.
Preparation of implementation plan, field operations manual, methods
manual, QAPjP, and information management plan.
Define project organizational structure and responsibilities.
Training program for field personnel prior to initiation of sampling
operations; laboratory performance evaluation prior to any analyses
are conducted.
Site visits and auditing activities, with prompt implementation of
required corrective actions.
Define preventative maintenance requirements for equipment and
instrumentation. Specify calibration procedures and frequency.
Implement appropriate QC measures at critical points of system.
Monitor performance as data are acquired against acceptance
requirements and correct problems promptly.
Specify reporting format, units, and range of acceptable values (or
codes). Review recorded data at point of collection and after entry
into computerized data base. Verify accuracy and acceptability of
information using internal consistency checks and quality control
information; validate data for intended use by exploratory statistical
analyses.
Assessment of quality against requirements for precision, bias,
completeness, comparability, and representativeness, using estimates
of variance components, performance evaluation data, QC
information, and results of verification and validation analyses.
coordinates of target lakes are compared to the presence of the lake on existing topographic maps.
Contact is made with local contacts to help confirm the existence, location, and accessibility of target
lakes. Lakes that still remain questionable with respect to target status or accessibility may be visited
by a member of the EMAP-SW staff. A second level of evaluation occurs when a field crew visits a
site. Some lakes identified as target based on map evaluations or preliminary reconnaissance may be
reclassified upon direct observation during the index period. Some lakes may be inaccessible or
otherwise not sampled during the index period (due to denial of access permission, weather
conditions, or misidentification of a lake located in a tight cluster of lakes. Crews are provided with
defined criteria for non-target status, and geographic coordinates obtained by GPS units are
compared to the expected map coordinates for agreement before a lake is confirmed as the correct
target lake and sampled.
Spatial and temporal components of index period variation which are of interest to EMAP-SW (Section
2) are potentially confounded by variability or bias resulting from different sampling crews visiting a
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site and collecting a sample; from the same crew visiting a site more than once and introducing bias
due to increased experience; or increased variability due to a lack of attention to standard operating
procedures (SOPs) because of a crew's perceived familiarity with them. Such crew effects could
impair the interpretation of regional patterns or trends. It is not feasible to factor out crew effects by
assigning lakes to each crew at random (regardless of location), or to sample the lakes at random
within an index period. Thus, there is a potential for all lakes within a subpopulation of interest to be
sampled by the same crew. It is also likely that, for a given subpopulation, some lakes will be
sampled early (when crews are inexperienced), while others will be sampled later (when crews are
experienced).
In the FY91 pilot survey, the potential impact of crew effects was investigated by sampling a subset of
lakes by different teams within 24 hours of each other. Two lakes were subjected to replicate
sampling at the beginning of field operations, and two more lakes were visited by different teams at
the end of field operations. This design allowed for evaluation of possible effects due to experience.
It is anticipated that for the FY92 survey, team effects will be addressed again, but the design of such
a study has not yet been finalized.
6.4 GENERAL FIELD AND LABORATORY OPERATIONS
All field crews are provided with a standard set of equipment for all sample collection and field
measurement activities. Backup equipment is available to each crew or is stored at a central facility
for shipment by overnight courier, if needed. Standard procedures associated with field operations
are described in the field operations manual (Merritt and Metcalf, in preparation), and in a methods
manual which is currently under review. Field personnel participate in a comprehensive training
program before sampling activities commence. Field crews are provided with all required scientific
collection permits for states where lakes are visited. Operating manuals for field equipment and
instrumentation are available to the crews to facilitate troubleshooting. Safety criteria related to site
access and sampling activities are provided as part of the operations manual. Flow charts describing
the major steps associated with each sampling or measurement procedure are carried by each crew
to all sites. Checklists have been developed to systematically ensure all samples have been collected,
labeled, and stored properly, that all field measurements have been recorded correctly, and that site-
related information (locational and anecdotal) has been recorded legibly. Field data and samples are
collected using standardized data forms and sample labels, which are described in more detail in
Section 7.
Formal training programs for laboratory personnel involved in EMAP-SW analytical work are not
conducted. For most indicators (e.g., sediment diatom assemblage), laboratories are selected as pan
of the indicator research proposal. For other indicators (e.g., water chemistry or fish tissue
contaminants), laboratories are selected based on evaluation of competitive research and support
proposals. Proposals are evaluated as to demonstration of analytical support capability, proficiency
with required methodology, evidence of an internal QA/QC program that is compatible with the overall
QA program for EMAP-SW, evidence of long-term performance through participation in round-robin
studies or other performance evaluation (PE) studies, and analysis of PE samples provided by
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EMAP-SW. Once selected, EMAP-SW staff visit the laboratory or meet with principal investigators to
provide orientation regarding data collection activities and the role of the particular laboratory.
Laboratories are expected to follow general good laboratory practices regarding calibration of
analytical balances, source of reagent water, appropriate storage areas for samples and reagents, and
preventative maintenance of analytical instrumentation. Laboratories monitor statistical control at the
bench level with control charts, when appropriate. Analyses are conducted following SOPs for the
method; the SOPs are developed based on analytical and QA/QC requirements of EMAP-SW and on
requirements specific to the operation of a particular type or model of instrument. Laboratories are
expected to have a sample tracking and information management system that is compatible with the
EMAP-SW information management system (described in Section 7).
Site visits of field operations and laboratories are conducted by experienced technical and QA
personnel. Such visits ensure that documented procedures for data collection, analysis, and
management are being implemented correctly and consistently by all personnel.
6.5 QA/QC ACTIVITIES FOR INDICATOR RESEARCH AND DEVELOPMENT PROGRAMS
Ecological indicators being developed and evaluated for EMAP-SW have additional research
requirements, or have QA/QC activities over and above those described previously for general field
and laboratory operations. The following sections attempt to provide a brief summary of those
activities for each individual indicator. A generalized process chart of QA/QC activities for field
measurements and sample collection is presented in Figure 6-1. The QA/QC activities associated with
laboratory analyses are summarized in Figure 6-2.
6.5.1 Water Chemistry and Trophic State Indicators
For field-based measurements, Secchi disk determinations are occasionally conducted in duplicate (by
two different individuals at a lake, or by two crews visiting the same lake). These duplicate
measurements provide a measure of precision to be applied to all measurements. For DO and
temperature profiles, the temperature probe is checked weekly against a thermometer. The DO probe
is calibrated before use at each lake. A duplicate measurement is made at the surface at the end of a
profile to ensure that no drift occurred during data collection. The performance of the oxygen probes
will be evaluated periodically by comparison to measurements obtained with a portable Winkler
titration kit.
For water chemistry, field crews periodically process a field blank sample to provide an estimate of
background contamination. During the FY91 pilot survey, well-characterized natural PE samples were
sent to field crews to process at the lake to determine if their were any errors due to handling and
transport of the samples by field crews. Comparison with PE samples sent directly to laboratories will
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LAKESITE
[ FIELD MEASUREMENTS]^-
SAMPLE COLLECTION &
IDENTIFICATION
Cnwnteal, Physical*
Habitat M*uur*m*nt»
1
Blotofllea
I
/'do map ooordbutaa agra*
with OPS coordlnat**?
DupneataorOCClMok
maaauranwnta
acceptable?
Flag valu** **»oclat*d wtth
Instrument or othar
potantlel prooMnw
Ara fl«o« npltlmd?
Ar* d«t» form* compM».
comet and togibto?
Oear type A effort recorded correody?
8*v Inio oonvct •no oonwttonl
Spadee eode* raoerded eorraclh/7
Sp^ofeiMns rotwnto fof nrwvnoA And vouoncr
ooDectlon* •coounted for In taO**T
Aw •pedmeo* of uncertain IdenMcadon linked to
tpecMo voucher (peefenent?
Ara tafly marka cummed eorraetlyT
Ara edema! pathology data coded oorraettyT
Ouptkale ID*, court*, or rneaeurement* acc*pt*bto?
Ara flagged value* and entriee explalnedT
\Aw data form* correct, complete, and toglbl*? J
Corraol nufflbw of raplcatM
Comet labal matehad w»
data form
Mfnpto Irtogrty
lagDitoT
BASE SITE
[ DATA FORMS ]
SAMPLES
(Including voucher apaclnMn*)
CompM* **t of form* for aaeh
laka?
RagiExplalfwdT
Ara *R* data and map data
oentlctontfor *aoh lak*f
I
DATA BASE
CompM* **t of tamplaa
feraaohUi*?
latackkigMormallon
OOOMflMlt WV) WHIM 4VM
labal*?
Araaagaaaaooialadwlh
explained en tracking
tomfT
V. J
I
LABORATORY
Flgur* 6-1. QA/QC aetlvHto* CMOCtattd wtth field optrationa.
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Section 6
September 1992
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LABORATORY
Chemical Sample*
(IncL FW» Tteaua)
1
1
Sample conc&on upon receipt
Compare content* «*h tr»ctdng form.
Sample oondHen upon receipt
Compare content* wdh tracking form.
I
i
PROCESSING
[ PROCESSING J
T
Aliquot* property )Ab«n«dw/»«mpl«IO?
All tDquota pr«p*r*d p«r MmptoT
Ar» (lags vcptahwdT
Are correct number of aubaamplaa prepared?
Are aOtubeample* properly labelled wtth Sample ID?
QC cheek* on eubeampOng and torting.
Are flag* explained?
ANALYSIS
[ IDENTIFICATION 4 ENUMERATION ]
' OC meaeurement* within batch and Immediate re*nalyel*"\
or re-callbratlon (btanke, *td*, QCCS)
Poet Analy*!* Bench AettvWee:
Calibration Acceptance
Control chart update and review
QC retult* from §plit», *pik*e, or »urrogat*»
Data calculated and recorded correctly
Problem analyse* flagged and explained
Sample ID* recorded correctly
U bench *h*et (logbook) correct complete, and
legible for date entry? I
'Are epede* cede* correct?
Are oount* taBed oorrecdyT
OC check* on count* and D* OK?
Are problem D* flagged?
Are all •ubeamptea per (ample accounted for?
I* bench *heet compieie, correct and legible?
Are reference collection or voucher •peclmen*
property documented and archlvad?
DATA BASE
Figure 6-2. QA/QC actlvHiec associated with laboratory operations.
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Section 6
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determine whether field handling represents a significant source of additional variation, in which case
introduced from field handling and transport, PE samples will be sent directly to laboratories for
analyses. EMAP-SW is also looking at new audit sample material that will be more representative of
lakes that are mesotrophic or eutrophic. Currently, new sources of natural PE samples are being
identified for possible collection and stabilization. Preparation of multianalyte synthetic standards are
being evaluated using chemical speciation models (e.g., Peck and Metcalf, 1991) to provide initial
predictions regarding theoretical composition and stability. A third line of effort is aimed at using the
speciation models to determine the feasibility of spiking existing natural PE samples with specific
analytes that may not be present in concentrations that are of interest to EMAP-SW, such as
aluminum species or nutrients.
For chlorophyll analyses, field crews also periodically prepare field blank samples by processing a
known volume of reagent grade water through the same type of filter used for chlorophyll analyses.
During the FY91 pilot survey, a large volume of water was collected from two lakes, and multiple filters
were prepared for chlorophyll analyses. Filters from one of the lakes were used as double-blind audit
samples to monitor the consistency and precision of the analysis. Filters from the other lake were
used by the laboratory as internal reference samples. As an internal standard, a chlorophyll standard
(as an acetone extract) was obtained from the Environmental Monitoring Systems Laboratory-
Cincinnati (EMSL-CIN). The filters prepared from the natural PE samples appear to be stable, and
thus provide a means to develop reference materials that can be characterized more robustly by
repeated analysis before use.
Samples are packed in coolers with ice and shipped to the laboratory on the day of collection, using
an overnight courier service. The laboratory processes each sample into several aliquots using
filtration and preservation. Processing is completed within 36 hours of analysis. All analyses have
specified holding times, ranging from 48 hours of collection to 28 days (Peck, in preparation).
Acceptance criteria for calibration (range of standards, number of standards, and precision of the
calibration curve) are specified for each analysis. Internal laboratory QC samples include laboratory or
reagent blanks, and periodic analysis of QC check samples of known concentration (to monitor both
the method detection limit and analytical precision and bias). Periodically, an internal reference
sample (either a standard reference material or a certified reference material) is analyzed to ensure the
check samples are providing an accurate assessment of systematic error. To monitor analytical
precision of the sample matrix, samples are periodically selected and analyzed in duplicate. For
analytes where interferences are possible, matrix spike samples are prepared to monitor for analyte
recovery. When possible, laboratories are expected to participate in round-robin studies (e.g., the
Long Range Transboundary Air Pollution round-robin program administered by the Canadian
government). Such participation provides an independent means of assessing laboratory
performance with respect to other laboratories.
6.5.2 Sedimentary Diatom Assemblage Indicator
The QA program developed for this indicator is based largely on that developed for the
Paleolimnological Investigations of Recent Lake Acidification Program (PIRLA; Charles and Whitehead,
1986). For field sampling activities, criteria are specified for sample acceptance (e.g., length of core,
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Section 6
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condition of sediment-water interface). At some selected lakes, replicate cores may be taken. Core
samples are subsectioned into standard intervals (generally from the top and bottom of the core) and
stored moist for shipment to the laboratory.
At the laboratory, core interval samples are stored under controlled conditions. Standard procedures
are available for preparing subsamples of each core interval for identification and enumeration of fossil
diatoms. Identifications are made using standard taxonomic references. A reference collection is
prepared using both microscope slides and photomicrographs. Specimens of uncertain identity are
sent to independent experts for confirmation. Replicate determinations of both identifications and
counts are periodically made of slides, of core subsamples within an interval, or core intervals (from
different cores). A reference collection of slides and photographs are also provided to a museum (the
Academy of Natural Sciences in Philadelphia) for archive purposes.
Subsamples of sediment from various intervals within a core are sent to a laboratory for dating using
radiotracer techniques (either 210Pb or ^Ra). The laboratory, as part of its internal QA/QC program,
analyzes laboratory blank samples and prepares tracer solutions of known activity. Periodically, a
tracer solution obtained as a certified reference material is analyzed as an independent check of the
validity of the laboratory-prepared standards. The laboratory also participates in a round-robin
program.
6.5.3 Zooplankton Assemblage Indicator
Zooplankton are collected from the lake using nets of two mesh sizes arranged in a "bongo* fashion.
Criteria for net placement and acceptable retrieval rate are specified as part of the SOP for sample
collection. Zooplankton are narcotized and then preserved in an osmotically balanced formalin
solution to facilitate storage and identification.
The taxonomic composition and relative abundance of zooplankton within each sample are
determined following generally accepted methodology (Edmondson and Winberg, 1971), using fixed
volume subsamples or subsamples that have been prepared as split samples and quantified using a
counting cell. Acceptance criteria are established for obtaining an appropriate number of
representative subsamples (e.g., test for randomness, minimal number of organisms to be identified
and enumerated, and a precision goal to define the number of subsamples required). Identifications
are made using standard taxonomic references, and a reference collection of specimens is prepared
and maintained. A subset of samples are subject to repeat analysis by a second person to monitor
the precision of counts and the accuracy of counts and identifications. Taxa of uncertain identity are
sent to an independent expert for confirmation.
6.5.4 Fish Assemblage Indicator
For each type of collection gear, a standard unit of effort is defined and documented in the SOP.
Criteria for the number of each type of gear to be used per lake based on lake area are also
established. Field personnel are expected to participate in a short training course on field
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Section 6
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identification of non-game fishes of the region, taught by a professional ichthyologist who is familiar
with fishes of the region.
Fish are identified using standard taxonomic references for the region, and taxonomic nomenclature
for common and scientific names recommended by the American Fisheries Society. A reference
collection of species collected from each lake is prepared and maintained. This collection is then
archived into a museum as part of their fish collection. Specimens of uncertain identity are sent to an
independent expert for confirmation. Periodically, a collection of fish is recounted (and possibly
reidentified) by a second person. Lakes may be revisited and resampled either on a short-term (i.e.,
within a week) or long-term (i.e., within the index sampling window) to provide estimates of sampling
variation and efficiency.
6.5.5 Riparian Bird Assemblage Indicator
The QA program implemented for this indicator is documented in a separate QAPjP (Adamus and
O'Connor, 1991). Field personnel are trained and evaluated for their competency in identifying birds
visually and from songs. Standard levels of effort for the time and amount of area searched at each
lake are established as part of the SOPs. Crews visit a subset of lakes within the index period to
provide estimates of sampling precision and efficiency. Efficiency at locating and identifying birds is
also checked through the use of checkplots established along Breeding Bird Survey (BBS) transects
where crews conduct uncontrolled (i.e., there is no specified time limit) searches. Competency of
crews is monitored throughout the field season by periodic concurrent determinations at sites by an
independent ornithologist. The accuracy of habitat-related data obtained from interpretation of aerial
photographs of lakes and their associated riparian zone is monitored by periodic replicate
determinations by a second person. Habitat assessments made from visits to BBS transects are also
periodically repeated.
6.5.6 Benthic Macroinvertebrate Assemblage Indicator
The QA program for the benthic macroinvertebrate is based on that documented by EPA (Klemm, et
al., 1990) and certain aspects implemented for the Near Coastal component of EMAP (Valente, et al.,
1990). Acceptance criteria for different types of benthic samples are documented as part of SOPs for
sampling. Levels of effort for different types of sampling (e.g., number of replicates or length of time
spent at a site) are also established for each type of sampling gear. Samples are preserved in
buffered formalin with rose bengal stain to facilitate sorting and identification. Prior to processing, a
subset of samples may be split and sent to a separate laboratory for processing, identification, and
enumeration.
In the laboratory, samples are sorted to major taxa before identification and final enumeration to
determine relative abundance. Criteria for efficiency of sorting (i.e., sorting continues until no
organisms are recovered within a specified time period) are provided to technicians involved in sample
processing. A subset of samples are subjected to a re-sort by a second person. The number of vials
of major taxa prepared for each sample is recorded to ensure that all organisms sorted from the
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sample are eventually identified and enumerated. Organisms are identified using standard taxonomic
references for different taxonomic groups. A subset of samples are recounted and reidentified by a
second individual. A reference collection is prepared and updated as new taxa are encountered.
Acceptance criteria are established relative to the degree of taxonomic accuracy and precision of
counts. Specimens of uncertain identity are sent to independent experts for confirmation.
6.5.7 Fish Tissue Contaminant Indicator
A preselected list of potential target species and length requirements are provided to field personnel
as part of the SOPs. A minimum number of individuals required to prepare a composite sample for
the lake is also specified. Specimens are transported to the laboratory frozen via overnight courier;
shipment is planned for the day of collection.
Fish samples are maintained at the laboratory at -20° C until they can be processed. For Gas
Chromatographic (GC) analysis, retention times of pesticides and polychlorinated biphenol (PCB)
congeners are confirmed before analysis of fish tissue samples. Laboratory blank samples are
analyzed frequently to monitor possible contamination. QC check samples of known composition are
prepared for appropriate analytes and analyzed in replicate with each batch of samples. An SRM is
also analyzed with each batch of samples. Where appropriate, samples are analyzed in duplicate to
monitor analytical precision, and matrix spike samples are prepared and analyzed to monitor for
analyte recovery. For organic analyses, additional internal standards or surrogate compounds are
introduced into the batch and analyzed to monitor instrument performance. Periodically, a
dichlorodiphenyltrichlorethane (DDT) breakdown check is conducted to check on the efficiency of the
Chromatographic column.
In addition to the above QA/QC activities, analysis of a non-standard reference material is analyzed.
This material may be developed from a large composite sample of fish collected from a site where fish
are known to be contaminated with detectable levels of metals, pesticides, and PCBs. This sample
would be characterized through repeated analyses (perhaps by several different laboratories) and
would eventually represent a "natural" audit sample that could be used in place of the more expensive
SRM. QC check standards will also be analyzed periodically with each batch to monitor precision and
bias of the analyses. The laboratory conducting the fish tissue analyses is expected to participate in
at least one round-robin program that is suitable for fish tissue analyses of the analytes of interest for
EMAP-SW.
6.5.8 Physical Habitat Indicator
Information obtained from topographic or other types of maps will be subject to repeated
determinations by a second person to monitor precision and accuracy. At a subset of lake sites
where data are collected, replicate determinations will be made by a second crew member. At a
subset of lakes, a reassessment may be made at two different times by either the same crew or by a
different crew. For macrophyte surveys, a subset of lakes may be subjected to additional effort
sampling (i.e., additional transects) to evaluate the efficiency and accuracy of the proposed
procedure.
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6.6 DATA REVIEW, VERIFICATION, AND VAUDATION
All data are subjected to various review and error-checking routines at several points in the data
acquisition process, and are verified and validated before they are used for interpretation or
assessment purposes or distributed to authorized users. Review procedures (Figure 6-3) include an
independent review of forms and associated QC observations or measurements at the point of
measurement or collection, comparison of computerized entries against the original recording form, or
by double entry of data with subsequent automated comparison.
Data are verified to confirm that information associated with an individual sample or measurement is
accurate with respect to what was initially recorded, and that all QC acceptance requirements have
been met. Verification (Figure 6-3) is conducted using automated review procedures (e.g., range
checks, frequency distribution of coded variables) and other internal consistency checks (e.g.,
computed ion balances, summation of relative abundance estimates for biological assemblages, and
absence of expected taxonomic groups). Associated QA or QC information is also used to verify data
This information includes results of internal QC sample analyses, results of replicate or split samples,
and review of sample holding times, when appropriate. Verified data are subjected to validation
procedures to identify data values which are potentially unrepresentative because of anomalous
conditions at the time of sampling.
Data validation activities are partly dependent upon the intended use of the data. Developing
estimates of lake populations based on individual measurements or indicators may allow utilization of
data that is unsuitable for other purposes (e.g., developing predictive relationships between variables
or indicators for diagnostic or assessment purposes), or vice versa. During validation, additional
variables or metrics may be calculated using verified measurement data. Data validation (Figure 6-4)
generally involves examining verified measurement data for statistical outliers using various univariate
and/or multivariate statistical procedures. Identified data points are then subjected to additional
review. Validation also involves evaluating results of QA data from PE samples, field blanks, or round-
robin studies to provide information that can be used to ascertain the potential uncertainty of
measurement data or to help explain outlying data points.
A validated data base may be modified for use in certain interpretative or assessment activities.
Substitute values for missing or invalid data points may be derived from replicate measurements or
from predictive relationships to other measured variables. Replicate measurements obtained at
individual lakes may be averaged so that each lake is represented by a single record for each
variable. Variables measured only to become incorporated into calculated variables may be deleted.
A validated data base for one indicator may be combined with those from other indicators prior to
assessment or interpretation (e.g., diatom assemblage data and water chemistry data).
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FIELD DATA FORMS ] [ LABORATORY DATA FORMS OR FILES ]
Comet data forma and re-enter.
Obtain confirmatory species 10
and correct form.
I
[ DATA ENTRY ]
I
Doubkt entry or review agalmt forma.
Automated rang* checks for numeric varlablee.
Automated frequency check* tor character or coded
varlablee.
OupflpElt or niiiiinQ rvooratt.
^ Flag utx>ertalnsp«cleelD» for cordlrmallon.
1
I
I GoiTKit •fitoy
RAW DATA CASE
I
[DATA VERIFICATION ]
r QA/OC DM Review >
Batch-Specific QC data: (blanks, check samplee, Internal
stds., dupllcatee, and spikee for chemistry; RepDcate sorting,
counting, and ID for biological samplee).
Detection Uml OK for the batch?
Holding time check- Flag samplee analyzed outaide holding
time.
Evaluate PE sample, blanks, audit sample, and round robin
sample data.
la estimated among-bateh detection limit acceptable?
For biological samplee, check re-sorts and repeat IDs and
counts
Flag eamplee Associated w»h unacceptable results for
re-analysis
(
1
l ComMwiey
Chemical Samplee Biological Samplee
Ion Balance Dbcrepant Tax*
Conductivity Balance S urn Relative Abundances
S urn fractions (e.g. A) Repfleate precision
I
IdenMy unacceptable samples tor
review and poseMe re-«nalysis
i
Review re-analyzed data and (lag ee euoh
All verfleaDon flags assigned and documented?
I
VERIFIED DATA BASE
Figure 6-3. Data ravtow and verification proeeaa.
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Section 6
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VERIFIED DATA BASE
1
DATA VALIDATION
r«^L
i
xlMtt, bn*d upon t»p» el hittpraMoa wtrfty
•cptonrtoty *n«y ••*
Fteg uMeetptabte 0*1*. drtwmfcM toure* of problem fnmpfeig drt*. UWMM!
oondEUen* en itato e( Mfliplng. iMin «(lMt «|gu).
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ENHANCED DATA BASE
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SECTION 7
INFORMATION MANAGEMENT
7.1 INTRODUCTION
Information management is the comprehensive framework that facilitates the management and
communication of data and information collected from sources through time in a form appropriate for
users. This framework provides for the management of the data and information through the
application of established protocols, procedures, and standards. These activities are supported
through the use of a variety of electronic and manual information management systems technologies.
Functions supporting these systems assure the integrity, security, and quality of the data collected, by
the project.
Surface Waters information management developed a comprehensive information management
system to support the resource group's needs for FY91. Details of this information management
system can be found in the Information Management Program Plan (McGue, et al., 1991). This
document provides detailed information on the information management program implemented for
EMAP-SW activities. This plan incorporates information on the data collection and analysis activities
conducted between February 1991 and October 1991. It describes and documents the approach,
rationale, objectives, and plan for establishing an information management system to meet the needs
of EMAP-SW.
The FY91 pilot information management system was designed to be flexible in order to meet the
developing requirements of EMAP-SW. The system represents a prototype and is by no means
complete. Through the use and development of this prototype, and as the research efforts of EMAP-
SW become better defined, a more comprehensive definition of the system requirements has been
defined. Based on these requirements, modifications and enhancements can now be made to the
existing information management system, and new systems can be implemented based on these
requirements. All field systems were developed in C, and all data bases and associated systems were
developed in SAS on the Environmental Monitoring Systems Laboratory-Las Vegas Virtual Address
Extension (EMSL-LV VAX) system.
7.2 FY92 INFORMATION MANAGEMENT ACTIVITIES
For FY92, development of the core information management systems will be accomplished.
Modifications to existing components will be implemented, and external data (historical data, data from
other agencies, etc.) will be integrated with EMAP-SW data In addition, prototype systems for
electronic field data entry, and a central data documentation, access, and management system will be
designed and developed. The following describes the overall plans for the FY92 EMAP-SW Northeast
Lakes Survey pilot information management system.
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7.2.1 Field Forms and Sample Labels
For FY91, field data forms and sample labels were designed as a collaborative effort by indicator
leads, QA, logistics, and information mahagement to ensure efficient and accurate field data capture.
Examples of these forms are presented in the Information Management Plan (McGue, et al., 1991).
Standard paper recording forms were used for capturing all field data. These forms were printed on
water-resistant paper. Samples were prelabeled with adhesive labels having a standard recording
format, which included all required information to identify and track the sample.
Modifications and enhancements will be made to the forms to reflect the changes in the FY91
sampling procedures for the FY92 field year. Due to success of the bar code sample tracking system,
sample labels will only contain a bar code and the random sequential number associated with it.
Labels will still be color coded to indicate the sample type.
7.2.2 Analytical Laboratory Results
Analytical results are being received from the laboratories in predefined electronic formats by the
EMAP-SW Information Center as they are completed for further processing and/or storage and
distribution.
A system was designed for entering benthic data resulting from species identification. Rapid access
to valid lists of scientific names at the various taxonomic levels is obtained through the use of a
predetermined taxonomic coding scheme. The system is currently being tested by the benthic
indicator lead. Based upon the results of this evaluation, the system will be modified for FY92 and
distributed for use to the other biological indicator leads. This will aid in the standardization of
taxonomic codes and species lists for EMAP-SW.
7.2.3 Sample Tracking/Shipping/Reporting System
A sample tracking/shipping/reporting system was developed to assist logistics and information
management in sample collection activities for FY91. Bar code readers and laptop computers were
used to computerize and automate sample tracking. Although the primary function of this system was
to aid in the entry of sample tracking information, it also performed a variety of other functions.
Shipping forms were automatically printed, daily reports, of the tracking information were generated,
and a weekly status report of sampling activities was produced. The system was used by the
sampling team base site coordinator and by information management personnel. One hundred
percent of the samples were tracked successfully and in a timely manner.
For the FY91 Northeast Lakes Pilot Survey the fisheries team and the benthic macroinvertebrate team
used a manual system (i.e., without bar code readers or electronic storage of data). A number of
problems were encountered with this manual system. For the FY92 field season, all teams will be
required to use the computerized shipping and tracking system, thus reducing errors and time spent
by information management and laboratory personnel correcting problems.
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Based on user experience in FY91 and changes in the sampling procedures, modifications and
enhancements will be made to the system for FY92. The following is an initial list of some of these
changes.
• A screen will be added to allow input regarding the lakes not sampled and the reason for non-
sampling.
• Samples will sorted by tracking number.
• An option will be added to allow for automated restoration of archived shipping files.
• Sample tracking information will be sent by modem from the field crews to the EMAP-SW
information management personnel.
• Backups will be done automatically by the system.
• A time stamp will be added.
• It is recommended that the analytical laboratories use a version of this system.
• A list of the valid lakes and their identification numbers will be displayed as a menu for selection.
• A field for flagging QA samples will be added.
• Screens and protocols will be developed for fish collection.
• The EMAP-SW User Guide will be updated.
7.2.4 Data Transfer
During the FY91 field season, tracking information was sent to the EMAP-SW Communications Center
via facsimile the same day of data collection. Hard copies of the field forms were sent to the SWIC by
Federal Express on a weekly basis. Upon receipt of the samples, the analytical laboratories returned
the shipping forms via facsimile to the Communications Center, indicating condition of samples upon
receipt.
Since timely and reliable service was achieved during the FY91 pilot without imposition of more
restrictions and duties on the field crews, most of these methods will remain the same. One pen-
based computer, which can be set up to emulate the field forms, will be evaluated by one team this
summer. If the GridPAD is deemed appropriate for EMAP-SW field data collection, implementation for
all teams will be investigated for the FY93 field season. Specific attributes of this system are
discussed in more detail in Section 7.2.8. Sample tracking information and data recorded by the
GRIDPAD will be transferred via modem.
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7.2.5 Logistics Lake Information Data Entry/Access System
A lake data entry and access system was developed to facilitate the input, storage, and retrieval of
data obtained for lake access purposes. The system was developed in SAS on the EMSL-LV 6420
VAX. The information in the system includes, but is not limited to: logistical map-based information
regarding the location of the lakes selected; information regarding access to each lake; and general
information about the lake. The major functions of this system are:
• Adding the lake access information.
• Editing the lake access information.
• Browsing the lake access information.
• Printing the lake access information.
For FY92,this system has been modified and updated based on revised user requirements. A
program for automating access to the Las Vegas VAX has been implemented for logistics personnel in
the east. The data base will be modified to be directly linked to the field data. The lake information
can then be updated and/or completed during data entry of the field forms.
7.2.6 Field Data Entry System
A field data entry system was developed to facilitate the input, storage, retrieval, and management of
all data from the field data collection forms. It was developed in SAS on the EMSL-LV 6420 VAX.
Three systems were developed for each distinct field sampling team: limnological, fisheries, and
benthic macroinvertebrate. Although the kinds of data being entered for each team was different,
each system provided the same functions.
For FY92, the data entry screens will be modified to reflect changes to the field forms. The fisheries
and limnological entry systems will be combined due to the new sampling procedures. More rigorous
QA/QC checks will be added.
Issues regarding data entry have been raised based on the procedures used in FY91. For FY91, the
field forms were entered into the system in Las Vegas and then visually checked to verify the data.
Indicator leads were then required to visually validate the verified data. Some people feel that this was
too time consuming and costly. A majority of the indicator leads feel that double data entry will save
time and effort, and provide better QA. There are pros and cons with both methods, and at this time
a decision has not been made. The costs have to be weighed with the benefits of each method, and
the decision then made by the entire resource group.
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7.2.7 Field and Analytical Data Bases
For both the Northeast Lakes Pilot Survey and the TIME project, the data bases consisted of a
number of different data files. The data files were organized by map-based information, field data, and
data obtained from laboratories following analysis of samples. Field data and analytical data were
also organized by four major data categories; raw, verified, validated, and enhanced. The data
dictionaries for all data received to date have been generated. Data dictionaries for the laboratory
data will be developed as analytical results are received from the laboratories.
For FY92, the following file naming conventions will be used:
AAABBCCD
where: AAA = = > sample type (chemistry [CHM], chlorophyll a [CHL], zooplankton [ZOO],
benthic macroinvertebrates [BEN], sediment core [SCO])
BB ==> year (91,92,93 etc.)
CC = = > data category (Raw [RA], Verified [VE], Validated [VA], Enhanced [EN])
D = = > crew (Limnological [L], Indicator [I], Fisheries [F], Benthic Macroinvertebrates [B])
For example, raw chemistry data collected by a limnology crew for FY92 would be:
= = > CHM91RALsasext
Modifications to the data structure and documentation will change to reflect the sampling design for
FY92. The directory structure will also be modified in order to manage the system more effectively.
7.2.8 Electronic Field Data Entry Prototype
As mentioned in Section 7.2.4, one pen-based field computer will be evaluated for the EMAP-SW FY92
field survey. During FY91, paper field forms were used for entering data. Although these forms were
easy to use and were reliable, entering the data into the data base was time consuming. A portable
data recorder (PDR) was evaluated, but they were difficult to use when entering comments. The
results of this evaluation can be found in the Information Management Program Plan (McGue, et al.,
1991). Most of Surface Waters data entered in the field were in comment form, and as a result, the
PDR tended to hinder the field personnel. Therefore, a pen-based computer will be tested during
FY92 field data collection activities to see whether they are a viable method for entering field data.
The unit combines a pen interface with a character recognition utility (much like an optical reader)
which allows digital capture (in ASCII format) of text and numbers. These pads are PC-compatible
and are equipped with a high speed modem to upload and download large volumes of data. It is
anticipated that use of these units will result in cost and labor savings; because these units emulate
the field forms, field data entry will eliminate the need for data to be entered by information
management personnel, as well as time spent resolving interpretive data entry errors. Data from the
GridPAD will be stored electronically and automatically uploaded into the central repository for the field
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data The unit provides range checks on the data in the field to ensure the integrity of the data. The
pen systems are also able to interface with bar code readers, and will be tested for sample tracking.
7.2.9 Data Documentation, Access, and Management Prototype
Standardized documentation containing all pertinent information describing the data is an essential
component of a data base management system. A central repository system for all of the EMAP-SW
data has been implemented on the EMSL-LV VAX in SAS. It is the goal of EMAP-SW information
management to have documentation of all data bases available electronically, as part of the
computerized data documentation, access, and management system. The system will consist of the
following major components:
• data dictionary/catalog/directory
• data utilities (user and data management)
• data access and transfer
An initial prototype of this system was implemented for FY91 and includes data and information
received to date from the FY91 pilot. The EMAP-SW Resource Group can use this system and access
the data on the Las Vegas VAX from any VAX node on the EPA network. The prototype is not yet
complete, but is operable. Through the use and development of this prototype, a better definition of
requirements can be developed before a fully operational system is put in place. This will result in a
system that is not only functional, but meets the needs of EMAP-SW. This will require input from all
individuals who will be working with the data. The final system will be flexible, menu-driven, and will:
• Facilitate the organized storage of data base documentation and corresponding data files in a
logical, easily retrievable format.
• Link the data with a complete set of documentation that can be maintained as a permanent record
for future reference.
• Provide a mechanism for transferring documentation from an ASCII file into the system.
In addition to facilitating data base documentation, the system will:
• Provide a menu-driven system for subsetting the data, exporting the data to ASCII files, and
performing limited statistical analysis.
• Provide a mechanism for performing complex statistical analyses and for generating graphic
outputs.
• Automatically generate and transfer the data on a real-time basis.
Functionally, the prototype is complete; however, the contents of the prototype are still evolving.
Efforts must be increased to involve the indicator leads in documenting their work and in getting the
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documentation into the system. As this documentation is received and changes are suggested,
(based on hands-on experience and comments), modifications will be made to the system.
7.2.10 User Involvement and Requirements
The users of an information management system cannot be treated as passive observers. On the
contrary, they must play an active role in designing, prototyping, and testing the system if it is to meet
their needs. User involvement will drive data and functional system requirements. These, in turn, will
drive the system architecture. To meet user requirements, EMAP-SW information management will
attempt to include the users in evaluating the current system and in developing the system for FY92.
An additional objective is to educate users in the many applications of the systems, as well as how
they can make full use of EMAP-SW data and information during FY92.
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SECTION 8
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