EPA/600/^-93/231
December 1993
QUALITY ASSURANCE PROJECT PLAN
for
Evaluating and Refining the Estuarine Habitat Assessment Protocol
on Puget Sound and Pacific Northwest Reference Sites
Prepared by:
Charles Simenstad
Luanda Tear
Jeff Cordell
Wetland Ecosystem Team
Fisheries Research Institute
University of Washington WH-10
Seattle, WA 98195
For:
Mary E, Kentula
Project Officer
Enivronmental Research Laboratory
200 SW 35th Street
Corvallis, Oregon 9733
August 1993

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Signature Approval for Implementation
of
QUALITY ASSURANCE PROJECT PLAN
for
Evaluating and Refining the Estuarine Habitat Assessment Protocol
on Puget Sound and Pacific Northwest Reference Sites
Principal Investigator
Charles Simenstad
Wetland Ecosystem Team, Fisheries Research Institute
University of Washington
Seattle, Washington

Date
'foject Leader^QA Control
Jeffery Cordell
Wetland Ecosystem Team, Fisheries Research Institute
Seattle, Washington
IX OdK iHs^
Date
EPA Prpject Officer, Mary E. Kentula
EPA Quality Assurance Officer, Robert Lackey
QAO, ERL-C
ic//g/f3
Date
JC Ocj-
Date
11

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1.0 TABLE OF CONTENTS
of
QUALITY ASSURANCE PROJECT PLAN
for
Evaluating and Refining the Estuarine Habitat Assessment Protocol
on Puget Sound and Pacific Northwest Reference Sites
Page
1.0 TABLE OF CONTENTS....,	iii
2.0 LIST OF FIGURES			v
3.0 LIST OF TABLES	v
4.0 INTRODUCTION			1
5.0 PROJECT DESCRIPTION	3
5.1	Selection of Attributes, Methods, and Sampling Sites	4
5.2	Sampling Design	6
5.3	Schedule	•	7
6,0 PROJECT QA ORGANIZATION AND RESPONSIBILITIES	8
6.1	QA Responsibilities	8
6.2	QC Responsibilities			8
6.3	Field/Lab Team	9
7.0 OBJECTIVES FOR MEASUREMENT	10
7.1	Accuracy	10
7.1.1	Field	10
7.1.2	Laboratory	10
7.2	Precision			11
7.2.1	Field	11
7.2.2	Laboratory	12
7.3	Completeness	12
7.3.1	Field	'	13
7.3.2	Laboratory	13
7.4	Representativeness			-	13
7.5	Comparability	14
8.0 SAMPLING PROCEDURES	14
8.1	Elevation	14
8.1.1	Field-May 1992	 14
8.1.2	Lab - Fall 1992-Winter 1993			 15
8.2	Epibenthos			15
8,2.1 Field - May 1992 	 1-5
8.3	Benthic Meiofauna	16
8.3.1	Field-June 1992	 16
8.3.2	Laboratory - June 1992-October 1993	16
8.4	Benthic Microflora (Chlorophyll a)	17
8.4.1 Field-June 1992	17
iii

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8,4.2 Lab - 1992			17
8.5 Emergent Vegetation	18
8.5.1	Random Point Quadrat Method at All Sites	20
8.5.2	Above -ground Standing Stock at All Sites	22
8.5.3	Below -ground Standing Stock at All Sites	23
8.5.4	Porewater Salinity and Redox	23
8.5.5	Independent Tests of Percent Cover and Scale (Site SS2)	24
8.5.6	Independent Tests of Below-ground Standing Stock	27
8.5.7	Independent Tests of Pore Water Salinity and Redox	27
9.0 SAMPLE CUSTODY	28
9.1	Sample Custody	28
9.2	Sample Labeling					-	-	29
10.0 CALIBRATION PROCEDURES AND FREQUENCY	29
11.0 ANALYTICAL PROCEDURES					30
12.0 DATA REDUCTION, VALIDATION, AND REPORTING	30
12.1	Epibenthic Plankters and Benthic Infauna	30
12.2	All Other Attributes	31
13,0 INTERNAL QUALITY CONTROL CHECKS	32
14.0 PERFORMANCE AND SYSTEM AUDITS	32
15,0 PREVENTIVE MAINTENANCE	32
16,0 SPECIFIC ROUTINE PROCEDURES USED TO ASSESS DATA
PRECISION, ACCURACY, AND COMPLETENESS	32
16.1	Precision	32
16.2	Accuracy	33
16.3	Bias	34
16.4	Completeness	34
16.5	Representativeness	34
16.6	Comparability	34
16.7	System Error	34
17.0 CORRECTIVE ACTIONS	35
18.0 QUALITY ASSURANCE REPORTS (TO MANAGEMENT)	35
19.0 REFERENCES	-	35
20.0 APPENDICES	46
20.1 Appendix A; Sample field and laboratory data sheets	46
iv

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2.0 LIST OF FIGURES
Page
Figure 1 Locator map of coastal estuaries selected for sampling	43
Figure 2 Map of three gradient sites in Elk River and South Slough	44
Figure 3 Example of estuarine wetland reference site with strata, horizontal
sampling transects, sampling plots, and vertical elevation transects	45
3.0 LIST OF TABLES
Page
Table 1 Parameters proposed for selective testing of Estuarine Habitat
Assessment Protocol	 37
Table 2 Sampling design and sample sizes, by site and stratum,
for selected attributes	39
Table 3 Transport and storage of samples	40
Table 4 Lab and field equipment for measuring Protocol parameters	41
Table 5 Methods of assessing precision, accuracy, and completeness
of Protocol parameters	 42
V

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QUALITY ASSURANCE PROJECT PLAN
for
Evaluating and Refining the Estuarine Habitat Assessment Protocol
on Puget Sound and Pacific Northwest Reference Sites
4.0 INTRODUCTION
Many estuarine wetland scientists and managers are of the opinion that present
wetland habitat assessment procedures are inadequate for application to specific
geographic regions and may be too subjective to provide consistent results ^This is
particularly the case in Pacific Northwest estuaries, where wetlands are structurally and
functionally different from southeast and Gulf coast estuaries, for whielfmost assessment
approaches were originally developed. To increase the effectiveness of our management
and conservation of estuarine habitats, we need assessment and monitoring procedures
that; (1) are based explicitly on habitat,function; (2) are specific to the region of
application; (3) use methodsjhat'are standardized, consistent and comparable, (4)
generate quantitative data rather than qualitative indices, (5) are designed to be thoroughly
objective among different users and sites, (6) will be adaptive in terms of building on prior
results; and (7) are structured in a flexible form, wherein both the biotie community and
target (e.g., species) resources can be addressed.
>The Estuarine Habitat Assessment Protocol (Simenstad e/ i/:, 199-1; hereafter
referred to as the Protocol) represents such an approach to assessing the function of
estuarine habitats for fish and wildlife, and specifically for the Pacific Northwest region.
Fish and wildlife support functions of estuarine habitats were the chosen focus of the
Protocol because they have historically been the "forcing functions" behind resource
agency requirements for compensatory mitigation. Other important habitat functions, such
as maintenance of water quality or flood desynchronization, should be assessed with
similar rigor. The Protocol is intended to address the need for a systematic procedure that
can be applied uniformly across a variety of wetland and associated nearshore habitats
using objective, scientific methods.__Ihe approach is directly applicable for the study of
'X.
natural wetland systems and in evaluatingxcompensatory mitigation projects in estuarine
!¦ }•
habitats. The Protocol also has the potential to facilitate the development of design
criteria for estuarine habitat restoration,
The general purposes of this project are:
1) to evaluate the applicability of a subset of Protocol attributes to a regional
developed from experience in Puget Sound, We will assess whether the selected

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subset of attributes applies across a broader geographical range (the Pacific
Northwest coast) than was originally encompassed in the development of the
Protocol. To assess the geographical applicability of these attributes, we will
sample for selected attributes in appropriate strata,
2)	to refine the sampling designs, procedures/methods, and parameters for these
attributes by evaluating the monitoring strategies and approaches recommended in
the Protocol and determining the most statistically valid sampling designs
achievable considering the costs of field and laboratory efforts.
To address sampling designs we will:
a)	delineate major strata (e.g. low marsh, high marsh, mudflat) at each site
b)	conduct preliminary investigations of spatial scale for all attributes
To address procedures and methods, we will:
a)	pay particular attention to the details of each sampling method in order
to further refine instructions in the Protocol
b)	compare different methods of assessing percent cover of emergent
marsh vegetation and pore water salinity
To address parameters (see Table 1), we will evaluate the relative precision and
costs (field, processing, destruction to habitat) of assessing emergent marsh
vegetation using above ground biomass, below-ground biomass, and percent
cover, using the methods of Bros and Colwell (1987)
3)	to sample certain physical parameters (elevation, pore water salinity, sediment
redox potential) to establish correlations with abundances of biological attributes,
To assess physical parameters, we will:
a)	establish elevation transects at each site
b)	sample pore water salinity along these transects and within other
sampling areas
c)	sample sediment redox potential where samples are taken
4)	to develop QA/QC procedures to be added to the Protocol since the original
Protocol does not make specific recommendations about data quality assurance or
control.
The data produced by this project will be used to evaluate the appropriateness of
selected attributes from the Protocol, to further refine estuarine wetland sampling designs,
and to establish criteria and methodologies that will optimize the precision, accuracy,
representativeness and comparability of data collected given the limitations of time and
funding. In the future, we hope to use the data gathered to assess levels of variability to
be expected in natural wetlands and to cull from our experience in this project a general

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3
process of sampling and evaluation to be used in future investigations of Protocol
attributes and methods. It is hoped that the final procedural recommendations to the
Protocol will constitute a statistically evaluated suite of procedures for assessing fish and
wildlife support functions for estuarine wetlands. Such procedures could then be
incorporated into regulatory and other rule-making processes, such as evaluation of
compensatory mitigation under CWA1, Although not necessarily intended as a tool in
planning wetland management programs, the concept of the Protocol and its
accompanying Quality Assurance Project Plan may also contribute to consistency and
scientific validity incorporated into any wetland assessments associated with the planning
process.
This QA Plan is a first step in the development of a final QA Plan that will
accompany the Protocol, Some of the QA/QC procedures used to gather data this field
season are not final, but are being tested and evaluated, Due to the more limited scope of
the sampling effort and size of the work force during this field season, not all QA/QC
procedures will be folly developed (for example, data tracking). Development of
procedures will proceed according to the needs of the current effort; more full blown
procedures will be enumerated in final recommendations to the Protocol.
5.0 PROJECT DESCRIPTION
In order to provide a more empirically-based Protocol, we will focus especially on
investigating and specifying (1) sampling designs, i.e., how sampling effort should be
distributed to achieve optimal statistical representation with minimal cost; (2) sampling
parameters, whether the parameters designated by the Protocol are representative as
assessments of wetland attributes; and, (3) sampling methodologies, what sampling
methods and dimensions (e.g., sampling units) are the most effective statistically and in
terms of costs. These three levels are interdependent, their relationships are based on the
spatial distributions (scale of spatial variation) of the attributes. To improve our
understanding of the distribution of wetland attributes, to assess the efficiency of Protocol
methods for different attributes, and to provide information for decisions about how to
allocate future sampling efforts, spatial sampling schemes and independent tests of
Protocol methods were included in the sampling program. Because, for most attributes,
we currently have no means for assessing the accuracy of the methods (the "truth" in the
field is not possible to measure with our time and means) methods will be compared in
terms of their relative precisions and biases. Tests of accuracy may be developed in the
1 Clean Water Act

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4
future.
5,1 Selection of Attributes. Methods, and Sampling Sites
Attributes, parameters, and most sampling methods used during this project were
selected during the development of the Protocol. The history of the Protocol
development process is described in the Introduction to the Protocol and a list of
attributes and parameters used in this project is found in Table 1. Research sites and
possible strata within those sites were selected during a workshop conducted on 17
December 1990 at the Padilla Bay National Estuarine Research Center, Mt, Vernon,
Washington. Two technical representatives each from resource management agencies,
academic scientists, tribes and environmental consultants from the Pacific Northwest
region^ were invited to attend and provide input toward defining reference site selection
criteria and recommending specific sites in Puget Sound.
The following criteria were adopted as priorities in the selection of reference sites:
(1) the site contains a broad diversity of estuarine wetland habitats representative of the
(Columbian province) geographic region; (2) the site is available for long-term monitoring,
has comparatively easy access and there is some assurance that the integrity of the
wetlands will be protected from disturbance in the future; (3) there is minimal or no direct
disturbance to the existing natural wetland in the estuary (e.g., industrial or heavy
recreational or aquaculture usage) and indirect disruption of natural processes (e.g., major
regulation of riverine inflow; extensive logging in watershed) is minimal; and, (4) there is a
relatively short, undisrupted continuum of wetland habitats along the estuarine gradient,
from euhaline (e.g., eelgrass/mudflat) to freshwater tidal (e.g., Sitka spruce-Western red
cedar swamp),
In addition, the following criteria were considered desirable if found associated
with the site; (1) a dedicated local, state or Federal government site (e.g., National
Estuarine Research Researve [NERR], National Park, Washington Department of Natural
Resources [WDNR] Preserve) dedicated to or encouraging research rather than multiple
use or exploitation, (2) a historic or on-going research or monitoring history, including US
Geological Survey (USGS) gauging stations, National Oceanographic and Atmospheric
Administration-National Ocean Survey (NOAA-NOS) stations, meteorological stations,
etc.; (3) proximity to education facilities; and (4) proximity to past or current wetland
restoration sites.
^ Washington State departments of Fisheries, Game and Ecology; U.S. Environmental Protection Agency-Region 10, Wetlands Program
and Office of Coastal Waters; U.S. Army Corps of Engineers, Seattle District; U.S. National Oceanographic and Atmospheric
Administration, HAZMAT; Suquamish Tribe; University of Washington's School of Ocean and Fishery Sciences, Department of Zoology,
and Center for Urban Horticulture*, consultants: Shapiro & Assoc , G. L. Williams &. Assoc.

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5
Based on these criteria, the Workshop participants ranked a number of potential
sites in Puget Sound and the Washington coast as to their priority as reference sites. At
this time, the following sites have been established for testing the Protocol under the US
Environmental Protection Agency's Regional Applied Research Effort [RARE] grant:
Puget Sound:	Kennedy Creek, Toten Inlet
Washington Coast: Elk River estuary, Grays Harbor
Oregon Coast:	South Slough, Coos Bay (South Slough National Estuarine
Research Reserve)
All these sites meet the primary criteria to a large degree and many of the
secondary criteria. In particular, two out of the three sites are in close proximity to
existing (Elk River estuary) or proposed (South Slough) estuarine wetland mitigation
sites, which potentially broadens the potential test of the Protocol with supplemental
sampling at the mitigation sites (see Figure 1). In addition, the proposed reference site
monitoring at South Slough would intermesh extensively with an estuarine and upland
habitat inventory and monitoring activity recently initiated or proposed by the SSNERR^.
We have received permission to conduct sampling in both of these estuaries. Due to
delays in acquiring access for researchers to the Kennedy Creek property, which is on
private property, and to funding constrains involved in both research and QA/QC
development at the other two sites, a Puget Sound site was not included in this project.
However, support is being sought to initiate reference site monitoring within the next year
at Kennedy Creek or another site in Puget Sound or Hood Canal, and for this additional
monitoring site we will adopt modifications to the Protocol that have emerged or become
resolved as a result of this project.
The stratification of habitat in estuaries (see Protocol, pp. 15-18) enforces a
stratified sampling design for most Protocol attributes. For each estuary, large-scale
reference material (e.g., National Wetland Inventory [NWI] maps, aerial photographs,
USGS topo. maps) and ground surveys were used to aid selection of sites. Three
locations (herein termed "gradient site") along the estuarine gradient were chosen in each
estuary. In each estuary, a site at the mouth of the river (most saline, site number 1), a
"mid-estuary" (mesohaline, site number 2), and up-river (freshwater, site number 3), were
selected. In late summer/early fall 1991, the Elk River and South Slough sites were visited
(see Figure 2). Potential sites were visually surveyed, temporary transects were
established, and test sampling was conducted. During the summer of 1992, habitat strata
within the sites were delineated, Strata were selected as representative (spatially
South Slough National Estuarine Research Reserve

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6
prominent) in the estuary, common to all sites and fitting into broad categories of the
estuarine wetland vegetation assemblages designated in the Protocol (see
Representativeness, above). In 1992, it was possible to delineate each site into three
strata: (1) a high marsh stratum characterized by the presence of emergent vascular plants,
including Dechampsia caespilosa, (2) a low marsh stratum characterized by emergent
vegetation, where D. caespilosa was not prominent; and (3) a mudflat stratum with no
emergent vegetation. Microhabitats (e.g., tidal channels) and divergent plant assemblages
that vary over the habitat's tidal elevations, surface topography and exposure were
embedded in each stratum.
At each site, three permanent, elevation sampling transects were established
perpendicular to the tidal elevation, from the upper margin of the intertidal (irregularly
flooded) zone, at the upland transition, to the shallow subtidal (irregularly exposed) zone.
The endpoints of the transects were marked with metal survey stakes; the rest of the
transect stations were marked with PVC pipe. Transects were surveyed back to
established survey datum (USGS/NOAA benchmarks) for exact elevation profiles.
5.2 Sampling Design
The sampling design for the 1992 season was developed to address the fact that
plants and animals in wetlands are heterogeneously distributed in patches of variable sizes
with variable taxonomic compositions and abundances. Traditionally, "marsh wide"
averages, with concomitant, enormous standard deviations, were calculated from samples
distributed randomly throughout an entire marsh. Such data is not precise or local enough
to provide usable information for time series monitoring of changes. During the summer
of 1992, one of our highest priorities was to sample in ways that would allow us to
investigate the scale of spatial variation of as many of the attributes as we could, so that
future sampling efforts could be more efficiently distributed to provide more precise
estimates of species abundances. For attributes whose distribution are not visually
accessible (epibenthos, meiofauna, microbiota), we sampled systematically along transects
to see if such sampling revealed any information about scale or pattern for these
organisms. For emergent vegetation, the patchiness of which is visually more apparent,
we considered the usefulness of further stratifying the high and low marsh areas and of
"mapping" patches by 1) marking their borders and following their changes in size and
shape over time as well as 2) following changes in cover or standing stock within a patch
over time. -To develop marsh-wide averages, a rotating subset of patches could be
monitored for changes in percent cover or biomass (and size). It is hoped that the added

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7
precision of within-patch estimates of patches whose locations are known would be high
enough to provide more meaningful indicators of change over time. Our work in August
was aimed to test methods for sampling for within-patch cover and standing stock.
During the 1992 field season, sampling for most attributes was conducted at
measured locations along constant elevation, horizontal transects or within delineated,
constant elevation 25 x 10 m areas. Epibenthic plankters, benthic meiofauna, and benthic
microbiota were sampled along a horizontal transect through the mudflat at the two most
saline sites in each estuary. Emergent vegetation was sampled within 25 x 10 m areas at
each site and, at one site, independent tests included sampling at different resolutions and
with different methodologies. Above-ground and below-ground standing stock were
sampled within these delineated areas as well as along the three elevation transects at each
site.
Table 1 lists the attributes selected for investigation in 1992, the parameters
measured, the units of measurement and the precision of measurement. The sampling
design is summarized in Table 2 and explained in more detail in Section 8.0, "Sampling
Procedures, Description of Methods",
5.3 Schedule
1988-1990 *
12/17/90 *
Summer 1991*
Summer 1992*
2/15-4/15 *
4/15-4/22 *
Development of Protocol: Selection of appropriate attributes,
respective parameters, compilation of best known sampling
methods, sample size recommendations
Site selection: Selection of appropriate criteria for reference sites,
selection of estuaries fitting criteria, selection of sites along
estuarine gradient in each estuary.
Preliminary investigation of Estuaries: Investigation of gradient
sites within estuary, temporary transects, test sampling
Full Field Effort: Delineation of strata, permanent elevation
transects, sampling for selected Protocol attributes
preliminary evaluation of sample unit, replication, precision, and
accuracy estimated from 1991 data
field survey preparation: equipment assembly, map preparation,
training of field personnel, contact with local personnel
establish permanent transects at sites in Elk River and South
Slough, record site characteristics (location, elevation, other notes)

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4/22-5/30 *	finalize sampling design
*	draw up data sheets, labels, inventory sheets
*	gather containers, prepare storage areas
5/30-6/6 *	sample epibenthic plankters
6/27-7/5 *	sample benthic microbiota, sedentary infauna
8/25-9/2 *	sample rooted vascular plants, pore water
9/2 -> *	analyze data, develop final sampling and QA recommendations
6.0	PROJECT QA ORGANIZATION AND RESPONSIBILITIES
All project personnel participate in field activities and data analysis in order to
obtain maximum continuity between field collection of data, laboratory sample analyses,
and data evaluation. The Principal Investigator and Project Leader have primary
responsibility for developing appropriate QA/QC methods and ensuring that the research
tasks and procedures are followed according to methods listed in the Protocol and QA/QC
requirements in this report. The Project Leader, in conjunction with the Statistical
Coordinator, is specifically responsible for the QC aspect of the project, including
monitoring all plant and invertebrate sampling processing, generating the standards,
conducting the internal quality control checks and developing correction procedures.
Principal QA/QC responsibilities are as follows;
6.1	OA Responsibilities
Responsibilities under the Quality Assurance portion of the Plan are to:
(1)	lead the development of the QA plan;
(2)	ensure that all project participants follow both the Protocol procedures and
the emerging QA plan;
(3)	interact with the project officer and ERL-C QA staff to evaluate both on-
site and in-lab QA procedures;
(4)	verify that QC activities are performed and data quality is determined as
required in the QA project plan; and,
(5)	document QC outputs
6.2	PC Responsibilities
Responsibilities under the Quality Control components of the Plan are to:
(1) ensure that Protocol procedures are followed;

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(2
(3
(4
(S
(6
a
follow instrument manufacturer's specifications,
perform and document preventive maintenance;
maintain up-to-date field and laboratory notebooks;
track data acquisition and verification;
conduct analytical and data quality determinations; and,
report all problems and corrective actions to the Principal Investigator.
Ronald Thorn
Jeffery Cordell
Lucinda Tear
6.3 Field/Lab Team
The Wetlands Ecosystem Team is composed of the following investigators, with
their associated responsibilities:
Charles Simenstad Principal Investigator; team leader; responsible for overall
sampling program
Consultant; co-team leader, responsible for guidance and
quality control on rooted vascular plant, benthic
macroalgae, and benthic microbiota sampling
Project Leader, responsible for field logistics and for
guidance and quality control on sedentary infauna and
epibenthic plankters sampling
Statistical Coordinator; responsible for development of
field sampling design, organization, preparation, and
conductance of sampling, tracking of sample custody and
archiving, and statistical processing and evaluation of data
Fisheries Biologist, field assistant, with particular
responsibility for benthic infauna and epibenthos collections
and laboratory processing, collection of above and below
ground vegetation samples
Research Assistant, field assistant, with particular
responsibility for rooted vascular plant taxonomy, guidance
and quality control on tidal elevation surveying
Consultant
Field Assistant (South Slough), plant identification,
porewater (South Slough)
All members of the field team cooperated for establishing and surveying site
transects. Weitkamp, Cordell, Simenstad, and Tear participated in the first two sampling
trips. Comu and Hood joined for sampling emergent vegetation.
Laurie Weitkamp
W. Gregory Hood
David Shreffler
Craig Cornu

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7.0	OBJECTIVES FOR MEASUREMENT
7.1	Accuracy
7.1.1	Field
Accuracy of quantitative data collected in the field, such as percent cover of
vegetation, is difficult to assess because ground-truthing is either impossible or very
costly. It is not possible to know how accurate estimates of cover, standing stock, or
densities are without censusing the population. Therefore, in this project, we focus on
relative bias and precision of quantitative techniques through analysis of data gathered
using different techniques or approaches to the same measurement and bootstrap analyses
(see Precision below). Estimates of accuracy/bias of the methods will require an
experimental approach and mapping at some future time. Accuracy is enhanced, although
it can not be assessed, by use of consistent methods. Field team members who are not
familiar with a given field technique receive training through classroom education or
demonstration in the field. All field sampling methods are reviewed in the field by the
team to assure that all members use consistent methods. Training and consistent methods
also contribute to precision of estimates and representativeness of individual samples
Accuracy of species identification of vegetation in the field is guaranteed by field
assistants with experience with local wetland plants, taking voucher specimens when
necessary, and using local field keys and herbaria collections to identify species whose
identities are uncertain.
7.1.2	Laboratory
Accuracy in the laboratory pertains to the weighing, measuring, counting, sorting,
and identification of species collected in various types of samples. For weighing and
measuring, accuracy will depend on the accuracy of equipment used and calibration of
scales before each weight is taken. All equipment is maintained and serviced on a regular
basis as part of University of Washington servicing Contracts or other standard
procedures (see Calibration Procedures and Frequency), For counting and sorting, and
species identification a careful system of repeated measurement and cross checking,
described under "Precision" below is carried out for epibenthic plankters and benthic
meiofauna, and above ground and below-ground biomass. Training is important in
assuring good accuracy in counting, sorting, and species identification. Training for each
task is carried out by the person responsible for the quality control of the procedure.

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7.2 Precision
7.2.1 Field
Epibenthic plankters and sedentary infauna—Consistent methods are important in
assuring precision of estimators. The methods for collecting benthic fauna described in
detail under "Sampling Procedures, Description of Methods" were used in the collection
of all benthic fauna in this project. In epibenthic sampling, it is important to sample down
current of the sampling locations to prevent sediment plumes from footsteps or previous
sample taking from contaminating samples. We are always careful to determine the
current direction, and when possible, sample from a boat to minimize the number of
people in the water. It is also important to take all epibenthic samples on an incoming
tide, when the water is at a consistent depth.
Emergent marsh vegetation, above ground percent cover-? ox visual estimation of
percent cover, precision of individual measurements will be tested by having individuals
repeat measurements of the same quadrats several times. Effects of quadrat size, plant
form, and individual on the consistency of these measurements will be tested using
ANOVA techniques. Independent tests of methods to sample for percent cover are
conducted in the same areas to investigate comparability of estimators, and the data will
be used to assess the relative precision and/or relative bias of the methods for a given
number of samples or a given time. Confining these tests to the same spatial areas insures
that variability caused by spatial heterogeneity will not be confounded with differences
between methods. We are not able to test for individual measurement error or sampling
error related to point placement with the point quadrat method, but will be able to test
precision using points sampled by bootstrapping data to investigate effects of sample size
on precision.
Emergent marsh vegetation, above ground standing stock, Emergent marsh
vegetation, below ground standing stock, Microbiota—Collection methods for these and
all above data are standardized as much as possible and when tests for effects of individual
measurement error are not possible, effects will be controlled to the extent possible
through training, cross checking by another observer, using consistent methods, and
limiting the number of people involved in data collection. Specific methods to assure
precision are detailed in the "Sampling Procedures" section.

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7.2.2 Laboratory
Epibenthicplankters and sedentary irfauna—Sonzd samples are checked by a
second person until remains are less than 5%. 10% of samples are rechecked by the
Project Leader for proper species identifications. If similarity is less than 90%, all samples
are rechecked by the Project Leader.
Emergent marsh above-ground standing stock (biomass per unit area)—Ten
percent of samples are reweighed by a second technician, and if disagreement is greater
than 10%, then sources of error are investigated and, ultimately, all samples may be
reweighed.
Emergent marsh below-ground standing stock determination-Cores taken for
below-ground standing stock are kept frozen until analysis to prevent any deterioration of
organic matter. Protocols for separation of living and dead matter have been suggested by
Hsieh and Yang (1992). Some of our below-ground biomass samples have been
processed; one person made decisions about living vs. dead categories. New criteria for
making these decisions will be evaluated based on the above article, used in processing the
remaining samples, and written into revisions of the Protocol
Microbiota—The fluorometer is zeroed daily with 90% acetone and calibrated by
running a sample of known chlorophyll content (known dilution of a species that does not
produce phaeopigments) the chlorophyll content of which was previously measured using
a spectrophotometer,
7.3 Completeness
Completeness is measured as the number of samples processed or analyzed using
consistent methods vs. the number taken. Estimated sample sizes required for each
parameter were determined using preliminary pilot data and bootstrap analyses to
investigate the necessary number of samples required to detect a difference equal to the
mean of the samples or one half the mean. Because natural variability is high and sampling
and processing costly, minimum detectable differences must be set quite high to be
achieved with 90-95% confidence (with beta = . 1). In all our sampling, we tried to gather
more data than pilot studies indicated would be required and used a hierarchical sampling
design discussed below to assure collection of adequate groups of data, The field
methods we used to gain information about the spatial variability of sites and differences
between sampling methods were also useful in assuring that it would be possible to

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analyze whatever data was collected and insure desired levels of confidence.
7.3.1	Field
To insure the collection of adequate and useful groups of data, the sampling design
was created as a hierarchy of components or modules; the completion of each component
would allow statistical analysis, the completion the entire program would be ideal. For
example, if sampling occurs along transects, sampling is completed along one transect
before beginning another. Sites are surveyed in their entirety before they are linked to
benchmarks. Percent cover measurements in one area are completed before beginning
data gathering in another area. All independent tests of methodological differences are
conducted in one area and completed before beginning sampling other areas. Time
estimates from past sampling, careful scheduling of personnel, and attention to fatigue and
tides were considered in advance in order to minimize the chances that time would
unexpectedly curtail sampling,
7.3.2	Laboratory
Samples are stored in groups corresponding to the groupings in which they were
gathered, so processing may occur under the same hierarchical program as was used for
sampling. When feasible, samples are restored after laboratory processing so that any
errors discovered at a later date, such as species misidentifications or possible
misweighings or miscountings (outliers discovered during data analysis), can be
reevaluated. Data will also be analyzed in groups.
7.4 Representativeness
As explained in "Project Description", sampling sites and strata were chosen using
criteria for representativeness that had been determined by local experts. The estuaries
sampled have different hydrologic regimes, geographic locations, and geological forms,
and fall well within the continuum of estuary types found in the Pacific Northwest. Strata
within sites represent the range of habitat types that can be found within estuarine wetland
sites in the Pacific Northwest. In addition, the attributes in the Protocol have been
carefully chosen, through the Protocol development process, to enable development of
representative, reliable indices of wetland functions. The attributes selected for focus this
summer were also chosen, after careful consideration, to provide a representative sample
of Protocol attributes to ensure that Protocol methods will be adequately tested.
The units of measurement used for most parameters are direct; to whatever degree
sampling methods allow, they are measurements of the parameter of interest. For

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example, cover, biomass, density, and elevation are all direct measures of the parameter of
interest. We are still in the preliminary stages of learning how to sample certain physical
characteristics, but we will be measuring, for example, salinity and redox directly, and not
with indirect or secondary parameters.
Consistent methods are an important aspect of representativeness in that they
assure that each sample is an equivalent sampling unit; that it "represents" the population
in the same way.
7.5 Comparability
The purpose of the Protocol is to develop standardized procedures that can be
used by all wetland scientists to insure comparability among data sets. The parameters
and methods in the Protocol are a compilation of methods commonly used by estuarine
biologists. Parameters such as plant cover or biomass, animal abundance or standing
stock are parameters often measured by wetland scientists as well as by ecologists in other
habitat types. Use of consistent methods insures that estimates of abundance from
different areas can be compared.
8.0	SAMPLING PROCEDURES
Aspects of the sampling design and procedures that occurred before the 1992 field
season are described under "Project Description". Procedures and methods pertinent to
field and laboratory efforts of the 1992 season are described below, Types of equipment
and containers used, transport, and storage aspects of methods are described in Tables 3
and 4; Appendix 1 provides examples of field book and laboratory data collection formats.
8.1	Elevation
8.1.1 Field - May 1992
In May 1992, the Wetland Ecosystems Team:
1)	Delineated three estuarine habitat strata (high marsh, low marsh, and mudflat)
at
each of the three sites in each estuary according to the criteria listed under
"Project Description;" the up-river site in each estuary (site number 3) did not
contain a mudflat stratum.
2)	Laid out three permanent, baseline transects, 50-100 m apart, across habitat
strata,
from upland to mudflat, parallel to the elevation gradient; the upland end of

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each transect was marked with an iron rod, the transects themselves were
marked by PVC pipes placed 10-20 m apart depending on width and slope of
site. (See Figure 1)
3) "Surveyed" each transect using a Leitz Total Station to find the relative
elevations
of each of the transect markers and to tie the sites in to local USGS
benchmarks. In some cases, tying to benchmarks may need to be repeated.
Time, weather, the distances to be covered by boat, the difficulty in finding
stable ground for the total station, and the difficulty in estimating the range of
siting prevented completion of a few tie in's.
Surveying transects involves the following steps at each site:
1.	Set a "control point" at each site (marked with an iron rod) from which the
elevations of the "topographic" points (transect markers along the gradient) are
sited.
2.	Place the total station is placed at the control point.'
3.	Use Total Station to site mirror on rod held by second person at each "topo"
point.
4.	Use Total Station to calculate vertical angle, horizontal angle, difference in
elevation, and distance to each topo point.
5.	Record data electronically in data recorder using Sokkia software.
6.	Hand copy data into field books to prevent loss of data.
The Leitz system is extremely accurate, Difficulty in interpreting the very
"accurate" data arises because wetlands are highly channelized and irregular. In the
future, several points around marked topo points could be measured to show whether the
more local topography around each point and whether the point is on a hummock or in a
channel.
8.1.2 Lab - Fall 1992-Winter 1993
Electronically recorded data files were checked with hand copied data, back up
copies were made, and ASCII tiles were extracted to generate site maps.
8.2 Epibenthos
8.2.1 Field - May 1992
Epibenthic fauna were sampled every 2 meters along a 40-meter horizontal
(constant elevation) transect in the mudfiat stratum at ELK1 and SSI (most saline sites)
and along an 80 m transect at ELK2 and SS2 (mid-estuary sites). It is hoped that this

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sampling effort coincided with epibenthic blooms in each of the areas. Epibenthos were
collected using an 0.018-m^ epibenthic pump (see Protocol for description). To collect
epibenthic organisms:
1.	Place pump head lightly on the mud surface disturbing surface layer as little as
possible,
2.	Run pump for 20 seconds to suction a constant volume and take up epibenthic
fauna at each sampling location,
3.	Sieve suctioned water through a 130-um mesh screen.
4.	Wash screen contents into 8-16 oz. plastic jars.
5.	Add pre-made label and close jar.
6.	On return to shore, reopen each jar, add 10% buffered formaldehyde, close,
and store.
8.3 Benthic Meiofauna
8.3.1	Field - June 1992
Benthic meiofauna were collected at the same sites and using the same spatial
sampling scheme used for epibenthos (above) using the following method:
1.	Insert 1 1/2 inch diameter PVC core approximately 10 inches into the mud.
2.	Place stopper in core, remove from sediment.
3.	Place core contents into 16 oz plastic jars (use plunger if necessary) with pre-
made
label and close.
4.	On shore, reopen jars, add 10% buffered formaldehyde, shake well to insure all
particles are separated and preserved.
8.3.2	Laboratory - June 1992-October 199J
Benthic fauna samples are processed according to the following procedures:
1.	Samples are sorted at 25X magnification (key organisms removed from
sediment),
2.	All samples are rechecked for remains by another person until error is reduced
to 5%,
3.	Samples are filtered through a 153 jam screen and scanned to determine if
subsampling is necessary.
4.	If subsampling is necessary (more than 100 organisms per sample), samples are
split in a Fulsom™ plankton splitter or a known volume is taken up in a
Hensen's-Stempel™ pipette (Hensen 1895) (Wildco, 301 Cass Street, Saginaw,

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Michigan 48602) until the total count for the most numerous species exceeds
100.
5.	Samples are taxonomically enumerated by technician, the predominant forms
are identified to species. 10% of those samples are rechecked by the Project
Leader. If similarity is less than 90%, all samples are rechecked by the Project
Leader, who is an acknowledged taxonomic expert on Harpacticoida and other
epibenthic crustaceans in the Pacific Northwest. (See also Puget Sound
Protocols [Tetra Tech, Inc. 1986] and Cordell et al. 1992).
6.	Abundances are calculated to trr3 for each attribute
7.	Species identifications and abundances are recorded on data sheets using
NODC
codes and entered into a relational database by the data processing department
8.4 Benthic Microflora (Chlorophyll
8.4.1	Field - June 1992
Microflora samples were taken at every fourth meiofauna sample site (above) to
test correlation of meiofauna abundance with epibenthic primary productivity using the
following procedure:
1). Insert .5 diameter syringe (narrow end removed) 3 cm into sediment
2.	Pull up plunger to suction in surface scum and sediment
3.	Push plunger down to eject all but 2 cm of sediment
4.	Push remaining sample into black plastic jar with pre-made label and close
5.	Store samples on ice in field to slow photosynthesis
6.	Freeze samples on shore until processing time.
8.4.2	Lab-1992
Procedures used for processing microbiota samples follow Strickland and Parsons
(1977) IV. 3.IV. Fluourometric Determination of Chlorophylls. These procedures are well
accepted in the oceanographic community, and have been modified as follows to
accommodate benthic sampling regimes.
1.	Samples are frozen in the field and kept frozen and in the dark until processing.
(The freezing/thawing process aides in breaking down the cells and facilitating
the extraction of all pigments.)
2.	Thaw samples, add measured amounts of magnesium carbonate and acetone to
stabilize sample and extract chlorophyll. Eelgrass fragments are removed, and

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diluted samples are ground with a mortar and pestle for several minutes to
further crush cells and release pigments.
3.	Refrigerate samples in the dark for 8 hours
4.	Remove from refrigeration, stir to equalize suspension, spin in centrifuge at
2000
rpm for 10 minutes to separate organic matter and sediments.
5.	Process supernatant in a Turner 111 fluorometer
6.	Take readings of:
a)	(F0): measure excitation levels for all pigments
b)	(Fa): measure emission due to phaeopigments.
7.	Perform calculations in accordance with the above reference; chlorophyll
measurements are standardized to g/m2
8.5 Emergent Vegetation
In August, sampling of emergent marsh vegetation was conducted in the high and
low marsh strata. As stated, sampling of emergent vegetation was designed to investigate
methods for sampling within-patch abundances. Three parameters, percent cover, above-
arid below-ground standing stock, were investigated, and several methods were used.
Figure 1 summarizes the overall sampling design.
In the Protocol, the benthic quadrat is the recommended sampling unit for percent
cover and visual estimation is one of the recommended sampling methods. Since species
are distributed at different scales, percent cover estimations for many species will be
related to the size of the quadrat and the most appropriate quadrat size, i.e. the size that
will give the "truest" value for the entire area, will vary from species to species. In
addition, the statistics of the visual estimation technique are not known, within and
between observer variability and bias has not been quantified and appears to vary
unpredictably in different situations. Therefore, we tested the visual estimation within
quadrats method against a method that minimizes visual estimation errors, eliminates the
problems of scale associated with the benthic quadrat, and allows estimation of scale for
each species. Point quadrat (pq) sampling was chosen as the common strategy for
determining percent cover at all sites and against which to test the visual estimation
methods. In point quadrat sampling, the size of the quadrat is decreased to the size of a
point, and visual estimation is reduced to a frequency determination of contact or no
contact with species at that point. Frequently, point quadrats are clustered 50 to 100
within 1 x 1 or .5 x .5 m quadrats. Since one would assume that many points in a small

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area would carry a certain amount of redundancy because points close together would be
correlated, Goodall (1951) recommends distributing point quadrats randomly within the
area of interest, rather than clustering them in quadrats as a more efficient sampling
design, This version of pq sampling was chosen as the common strategy for percent cover
estimations at all sites. (Dethier 1990) found high within quadrat variability using 50
points within benthic quadrats. This variability is likely a function of both sampling error
and small scale variability in a plants form and distribution. Both of these complicate
estimation percent cover for the larger area of interest.)
If the locations of the x,y coordinates used are known, the correlation structure of
a species can be investigated and the distances required for sampling points to be
considered independent can be calculated. Variance estimates from the sampling effort
can be combined with distances required for sampling points to be independent to generate
density and total number of points required for a desired precision. This information can
be used to refine pq sampling within areas to create the most efficient designs (no
redundancy through sampling correlated points). We hope to use t his data to create a
systematic sampling grid that will obviate the need to precisely locate each new point,
facilitate relocating sampling points from minimal markers, and preserve independence and
sampling precision. While the size of the grid and total area required will vary from
species to species, the spatial information from this or similar studies will allow grids and
sampling designs to be tailored to meet the sampling needs of a given project at a given
site (e.g. to choose to sample for rare or abundant species in different sized patches.)
These methods will be elaborated on in future papers.
With the exception of South Slough Site mid-estuary site (SS2), where two areas
were sampled (SS2B and SS2D), each site was represented by only one plot or habitat
type. In this way, then, we have used pq estimation in seven different habitat types or
patches. Although it would have been desirable to have replicates within a habitat type,
time did not permit this given the program requirements to sample at all six sites in order
to test the applicability of the attributes. Such replication can be carried out at a future
date in order to investigate the effects of sampling error and differences between patches.
The data from 1992 sampling will serve as an excellent pilot study for future, more
complete, investigations. More complete characterization a site will involve mapping and
sampling representative patches as discussed in the "Project Description."
We used the plots at site SS2 (SS2B), to test the relative efficiency of the density
of pq estimates used at all sites against estimates derived from three other methods. Since
time did not permit such testing at every site, testing can not be said to be complete in that
methods may have different efficiencies in different community types. The methods tested

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include:
1.	higher intensity of sampling (increased the number of pq's),
2.	visual estimations of percent cover, controlling for individual measurement
errors; and,
3.	systematic pq sampling along a transect
At plot SS2D we investigated:
1.	ability of pq sampling to distinguish between visually different communities
at the same site. PQ sampling at a second plot at site SS2 (SS2D); and,
2.	within- and between-observer variability and effects of quadrat size using
visual estimation technique: repeated visual estimations by different observers
in
different sized quadrats (SS2D).
The sections below describe the field methods used to set up the point quadrat
sampling areas (plots), and to conduct the tests described above.
8.5,1 Random Point Quadrat Method at All Sites
Field
1.	Delineate a 25 x 10 m area within a relatively "homogeneous", high marsh area.
An area was judged homogeneous if there was no obvious elevational change
within the area (wide, deep channel or unusual hummock) and species
. composition was visually consistent. We chose areas with a range of plant
forms and coverage.
2.	Circumscribe area using meter tapes.
3.	Insert wooden stakes or flags every 5 m around the perimeter.
4.	Lay meter tape down the middle of the plot (The tapes and stakes served as
visual measurement aids for the sampler who noted species at 104 randomly
generated x.y coordinates within the plot)
5.	At each x,y coordinate chosen, point a thin metal rod vertically at the ground.
6.	Record all species touched by the rod in field books. Recordings are made by
a second person who also calls out the coordinates to the sampler. If a species
is intercepted more than once at a given point, it is recorded only once.
7.	Record any obvious clumps or species not sampled by the end of the sampling.

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Individual measurement error in the random point quadrat method is directly
related to the size of the pin used, whether readings are taken at fixed pins, or observers
place pins anew (Goodall 1951), and observer "bias" about what constitutes a "hit". We
did not test for these two effects, but tried to control for them by using the same, very
small diameter, pin in all trials the same two people taking readings. These two observers
agreed on a protocol and occasionally validation by the other observer was sought. To
truly test variability in pq estimates due to individual measurement error, repeat measures
by the same and different observers should be performed both on the same pins and
placing the pins anew at each reading. To estimate sampling error, repeated samplings of
individual plots, using the same and different points would need to be carried out. We will
not be able to assess these levels of error this field season
Sampling error in this method relates to the precision with which points can be
located and the number of points deployed. The methods used last summer have been
refined to allow much easier and more precise point location, By presorting sampling
points in the field book so that the sampler can move up and down rows in the area with
out trampling the area extensively and having the x and y axis measuring aids always
within one meter, points can be easily and precisely located. These methods involve:
1.	Generate two columns of numbers of desired n, uniform zero to the distance
desired there 0-10 and 0-25).
2.	Sort these numbers first by the first column (x coordinate).
3.	Stack the numbers in groups of one meter intervals (e.g., 0-1, 1 -2, 2-3.. .9-10).
4.	Sort each "stack" again, now by the second column. Alternate sorting such
that the first column is sorted in ascending order, the next in descending order,
the next in ascending, etc,
5.	Delimit the desired area using meter tapes.
6.	Place a stake at every meter mark along two opposite ends.
7.	Lay a tape between the second two meter markers as the y axis.
8.	Use a meter stick to measure the distance along the x axis.
9.	Have a reader read the x,y coordinates and record species touched as the
observer proceeds up the first row and down the second row.
10.	Move the y axis tape to the 4th meter mark.
11.	Continue recording points up and down successive rows until the area is
completely sampled.

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Laboratory
Data will be entered into a Microsoft Excel for Windows™ database, checked, and
three copies of all files were made. Percent cover is calculated as the number of intercepts
of a species per total number of points (random point quadrats or rpq's) investigated
(104). Binomial confidence intervals for each species percent cover estimations will be
calculated.
8.5.2 Above -ground Standing Stock at AH Sites
Field
Above-ground standing stock samples were taken within the 25 x 10 m plots for
estimates of local variability of individual species and along two to three of the elevational
transects at each site for estimates of cross gradient total above-ground biomass. Within
the plots, samples were taken at each fourth random point (until a maximum n of 24)
Along the elevation transects samples were taken at a random number of paces between
each topo transect marker. The methods for collecting the samples were;
1.	Clip above-ground standing stock of vegetation rooted within a 0.25 x 0.25 m
quadrat to ground level
2.	Place vegetation from each quadrat in a separate plastic bag with pre-made
label, tie bag.
3.	Keep samples cool in ice chests until return to shore.
Laboratory
Above-ground Standing Stock;
For samples gathered within 25 x 10 m plots;
1.	Sort plant matter in each sample bag by species. The team worked together,
and any identification questions were resolved by the team.
2.	For each sample, wrap each species loosely in aluminum foil, with label
including site, date, sample #, and species name. Label aluminum foil with
same information.
3.	Keep samples cool until drying.
4.	Place samples loosely in drying oven and dry at 150°C for two to three days.
5.	Check samples periodically to assure even drying.
6.	Weigh each sample, remove sample contents and weigh aluminum foil.
7.	Subtract weight of aluminum foil from total weight.

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For samples gathered along elevation transects (total biomass):
1.	Wrap each sample loosely in aluminum foil and label.
2.	Complete steps 3,4,5,6,7 above.
8.5.3	Below -ground Standing Stock at AH Sites
Field
At each site, below-ground standing stock was collected at the same locations as
above ground samples along the elevation transects. At SS2B, below-ground biomass
was also collected at the same locations as each above ground sample within the
delineated plot. One team of two people was responsible for collection of all above- and
below-ground standing stock samples. Methods for collecting below-ground biomass
include:
1.	Pound a 3 18-cm diameter PVC tube approximately 30-cm into the ground.
2.	Place a stopper on top of the tube, twist core, pull to extract.
3.	Place each core in a separate bag with label.
4.	Place each bag on ice.
5.	On return to shore, freeze samples.
Laboratory
1)	Store samples frozen until analysis.
2)	Thaw cores.
3)	Wash away sediment and remove organic matter.
4)	Separate dead and live matter, wrap labeled samples loosely methods of Hsieh
and Yang (1992) may be used to distinguish live from dead matter.
5)	Dry samples in drying oven and weigh as above for above-ground biomass.
8.5.4	Porewater Salinity and Redox
Field
The Protocol recommends measuring physicochemical parameters to see if
relationships with biological attributes can be found. To complement the elevation data
gathered, we attempted to take porewater salinity and sediment redox at each of our
sample locations. .Redox probes were quickly and unretrievably clogged by mud and
water and took a long time to equilibrate so that multiple readings with one probe were
very time consuming. In addition, the solid ground in the high marsh area required that
holes be dug in order to insert the probes. Therefore, subsequent "pore water" samples
were taken by inserting the probe of a salinometer into the water that seeped into the

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holes left after the removal of the below- ground standing stock samples taken along the
elevational transects. Holes were drilled in a line around 50 8 cm-long, 3 18-cm diameter
PVC pipes approximately six inches from one end. These pipes were inserted into the
holes left by the below-ground standing stock cores, stoppered, and later returned to for
salinity readings. In most pipes, water accumulated within an hour, in other pipes another
tidal cycle was required, in others still, water did not accumulate during our field stay.
Considerable controversy ensued about exactly what water was being sampled by this
technique and how much interchange of water there would be between water in the pipe
and water in the soil outside the pipe. It is not clear whether what we sampled was,
indeed, pore water, or rather ground water. Data from these wells will be compared to
readings taken by squeezing water from a syringe full of sediment onto a refractometer.
This test is described under "Independent Tests".
8.5.5 Independent Tests of Percent Cover and Scale (Site $$2)
At South Slough Site Number 2 (SS2), the following independent methods of
estimating percent cover and scale of spatial variability were carried out.
Random point quadrat, second plot M'ithin same site (SS2D)
A second 25 x 10 m plot at SS2 (S82D), was sampled using the same techniques
described above under "RPQ Methods, All Sites". This test was designed to assure that
the rpq method would detect differences between plots at the same site (SS2D had a very
different species composition than the first plot (SS2B)) and to provide alternate estimates
for the repeated (by individuals) measures test which was conducted in the same area.
Random point quadrat, higher intensity in a smaller area (SS2A)
While it seems likely, and has been shown in previous studies, that relatively
abundant species will be tend to be well estimated by a variety of techniques and
intensities of sampling, rarer species are more difficult to quantify precisely. To see if
rarer species could be more precisely estimated by higher resolution rpq sampling
(increasing "n"), we sampled at a higher intensity than in the larger area SS2B by assessing
67 additional random point quadrats for all species, and 220 additional random point
quadrats for the rarer species (Triglochin maritima, A triplex pa tula, and Glaux maritima)
in a 3 x 5-m area within SS2B called SS2A. These data will also be used to investigate
spatial scale (see Horizontal transect, below).

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RPQ vs. Visual Estimation Technique (SS2B)
This test was designed to compare estimates of percent cover produced by the
visual estimation technique with estimates from the random point quadrat method
described above. Because visual estimations of percent cover can be highly variable, even
within observer, to allow this comparison we tried to control individual estimation error by
creating teams to perform the estimations, by giving the teams visual aids to assist them is
their estimations, and by conducting several pre-experiment group estimations when all
observers discussed their reasons for making the estimations they did. Four people trained
in plant identification were used to create 6 teams of two people. At every fourth random
point (up to n=24) in the first 25 x 10-m area (SS2B). a 0.5 x 0.5 m quadrat was laid
down. Each team was randomly assigned four quadrats and given manila cards cut to
equal 1%, 2%, 5%, 10%, 15%, and 20% of the 0.25-m^ encompassed by each quadrat.
These cards were held over the quadrat to aid in estimating the total area covered by
dispersed clumps of plants or irregularly shaped clumps, and to assure that all teams were
operating with the same mental/visual "scales". Percent cover of all species in each
quadrat was estimated by each team reaching consensus about each estimation. Collecting
the data in this way controlled for individual measurement error as much as possible, and
will allow for testing of a team effect (One Way ANOVA) in data analysis.
Visual estimation - Individual Measurement Error (SS2D)
In this test, we investigated the distribution of an individual's visual estimations in
quadrats of different sizes, In the second 25 x 10 m area ( SS2D), we randomly selected
and marked five of the 104 rpq coordinates. At each point, we conducted three sets of
estimates. Each set was composed of three to four "rounds" at a given quadrat size.
During each round, each observer recorded his/her visual estimations of percent cover of
each species observed in each of the five quadrats. To do this, we laid a 0.5 x 0.5-m
quadrat at each of the five marked points. Each observer silently recorded his/her
estimations at each quadrat. After completing one "round" of estimations and taking a
break, each person then began again, until, for each quadrat, each person had recorded
four visual estimations. We all found that we did not remember estimates from past
rounds. When everyone was finished, we replaced the 0.5 x 0.5-m quadrats with 1 x 1-m
quadrats and each person completed three rounds of estimations. The third set of three
estimations was conducted used 0.25 x 0.25-m quadrats place within the 0.5 x 0.5 m area.
This "experiment" will allow us to see how individuals differ from one another in
their estimations, how consistent or inconsistent different individuals are, and whether this
individual consistency is related to the size of the area being estimated. It is well known

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that fatigue effects visual acumen in this technique. We did not try to control for or sort
out the effects of fatigue, but rather, because fatigue would play a role in any large scale
monitoring project, allowed it to have its effect. We do know the order in which
estimations were made on a quadrat by quadrat level if this information should seem
relevant later, The following types of comparisons will be made:
1.	Variability within observers:
a)	calculate variance and standard deviation of each observer's estimates for
each species and each quadrat;
b)	record maximum difference between any two estimates for a species in a
quadrat for each observer; and,
c)	compare mean differences and standard deviations for different species,
different quadrat sizes.
2.	Differences in between observer variability:
a)	compare variability estimates from (a), and,
b)	assess number of times an observer was high or low relative to other
observers.
3.	Differences between variability of estimates in different quadrat sizes:
a) compare average standard deviations and differences (from 1 above) at each
quadrat size for each species,
4.	Differences between variability of estimates of different species
a) compare average standard deviations and differences (from 1 above) of
different species for each quadrat size.
Horizontal Transect—RPQ Percent Cover and Determination of Scale (SS2B)
Line intercept sampling is sometimes used to measure vegetational percent cover
of species with very discrete or clumped forms. A straight transect is laid out and
distances along the transect covered by the species of interest are recorded. Percent cover
of that species is the proportion of the total transect length that intercepted the species,
Carlile et ah (1987) used this method to estimate percent cover of sagebrush and to
investigate the scale at which sagebrush was distributed along the transect. Because many
of the species in wetlands do not have such an easily measured, discrete form, we modified
the technique and used systematic pq sampling along a transect, A 50-m meter tape was
laid out along one edge of area SS2B. For the first 5 m. an rpq was placed every 5 cm (n
= 100); for the next 15 meters, an rpq was placed every 10 cm (total n at 10 cm resolution
= 200); and, from 20 to 50 m, an rpq was placed every 20 cm (total n at 20 cm resolution
= 250). We will use the methods of Carlile et al. (1987), Markov chains, and time series

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analysis to investigate pattern and scale along this transect, and to investigate how these
methods compare in terms of ease of use and abilities to detect scale and pattern. The first
two of these methods will also provide estimates of percent cover.
The estimates of scale from of the above methods will be compared to estimates of
scale calculated from the two dimensional pq data from the plots. The probability of
touching a species given a certain distance between points will be calculated for each
method. At the distance this probability equals the probability of finding the species,
samples will be considered independent. Distance to independence and estimates of
percent cover will be compared from all the above techniques in terms of their point
estimates and precision (confidence intervals and coefficients of variation), using
bootstrapping techniques when necessary. Because the sampling techniques used are so
different, and sampling units are not the same in each method, comparisons of the
precision of each method will be made relative to time and effort needed to sample.
8.5.6	Independent Tests of Below-ground Standing Stock
Local variability (SS2B)
At site SS2B, below-ground standing stock samples were taken in the center of
each of the 24 above-ground sample quadrats. These above- and below-ground samples
will allow evaluation of local, within-patch variability of below-ground standing stock and
direct comparison between above-ground standing stock, below ground standing stock,
and percent cover.
8.5.7	Independent Tests of Pore Water Salinity and Redox
Local variability (SS2B)
Using the same methods described above for pore water, pore water readings were
taken where each of the 24 below-ground standing stock cores were extracted in SS2B.
Comparison of methods (ELK J, ELK2, ELKS)
Because we were not certain about the methods used in collecting "pore water"
samples, we conducted two independent tests of our methods. The first method was
described above in the "Pore Water" Methods section. For the second method, we drilled
holes through the entire column length of 5 catchment tubes that were then inserted into
holes created next to those described in method one. It was hoped that these second tubes
would allow greater water flux through the tube than the original method. In the third
method, we took a small core of soil near the tube in a hypodermic syringe with a filter
paper at the needle end. We then squeezed a drop of water (true pore water) from the soil

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28
onto the refractometer by inserting and pressing the plunger into the syringe. A
refraetometer reading was recorded. Filter paper was replaced for each pore water
sample. At some locations, this last method was the only reading possible, since no water
had accumulated in the catchment tube. At ELK3, the last method was the only method
used, since no tubes accumulated water.
The first test involved taking readings in three ways at all "pore water" stations at
ELK1 and ELK2 (n=41). We first inserted a Yellow Spring Instrument™ [YSI] probe
into the well and recorded temperature and salinity using the YSI™ meter. We then
dripped water from the YSI™ probe onto a hand-held refractometer and took a reading.
Finally, we used method three above (syringe) to measure the "true pore water" salinity
with the refractometer. This series of tests will provide calibration of YSI™ readings with
refractometer readings (relative bias), comparison of the salinity of water in the tubes with
shallow sediment pore water, and comparison of water in tubes with inflow at the bottom
and one sediment depth with water from tubes with inflow at the bottom and from all
sediment depths.
Two people conducted the Elk River sampling and these people consulted on
almost each reading. A different person took readings in South Slough with a different
YSI™ meter. South Slough and Elk River readings will not be comparable, but all
readings within an estuary will be.
In the future, we favor using the syringe method, extracting soil from the depth(s)
of interest. Experimentation with the catchment tubes will continue using more
sophisticated equipment and soil from different depths. We also advocate measuring
redox potential using the method described by Faulkner et al. (1989). In this method,
many redox probes can be made in the lab by welding copper wire to strips of platinum
and encasing these in shrink wrap or plastic pipettes. The probes can then be inserted into
the ground at multiple locations and depths and left to equilibrate for as long as necessary.
The probes can be returned to later for rapid measurement of the extent of platinum
electrolysis with a redox meter.
9.0	SAMPLE CUSTODY
9.1	Sample Custody
Transport of samples in this project is limited to transport from the field to School
of Fisheries storage areas and from storage areas to labs of appropriate staff for analysis.
Detailed tracking of samples is not necessary; the following procedures assure that sample
whereabouts are known,

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29
1.	All sampling and data generation in the field and subsequent analyses of field-
collected samples are conducted by one team of investigators (WET) and one
laboratory (WET facilities at the Fisheries Research Institute, University of
Washington, Seattle, WA),
2.	Sample collection and labeling is documented in field sampling logbooks and a
daily inventory list of all samples collected is compiled and checked against the
samples at the end of each day and site visit
3.	Sample labels containing site locations and code numbers, date of collection,
name or initials of sample collector and the type of sample are added to samples
in the field. A specific hierarchical code series was developed for each estuary,
habitat, transect, grid and plot in order to guarantee that samples can be traced
to each other and to data gathered on environmental conditions at the time of
sampling.
4 All samples are returned to the WET laboratories at the University of
Washington, where they are stored under secure (e.g., locked) conditions.
5. Archived specimens are maintained with either the WET laboratories (e.g.,
epibenthic zooplankton) or at the School of Fisheries (e.g.,
macroinverteb rates).
Table 3 describes containers, transport and storage of samples.
9.2 Sample Labeling
All sample labels are prepared before going into the field and contain the following
information:
1 project acronym (e.g., WET RARE)
2.	date
3.	Site code
4.	sample method and sample number (e.g. MB T1 #12 = Microbiota Transect
1, #12)
Sorted samples may also include additional labels (e g., species, dead/live below-ground
organic matter, etc.) Field books contain clear enumerations of site/sample codes.
10.0 CALIBRATION PROCEDURES AND FREQUENCY
All field instruments are calibrated in the laboratory prior to deployment in the field
and recalibrated upon return to the laboratory in order to detect any changes from the pre-
field calibration. The redox/pH meter is calibrated with solutions of known pH that are

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30
provided by the manufacturing company. The YSI meter is borrowed from Ocean Tech
Services at the UW School of Oceanography, that is responsible for servicing and
maintaining equipment in good working condition. The Leitz Total System used for
elevation data was borrowed from Geoline, (Bellevue, WA). The company provided
training in the use of the equipment, guaranteeing precision of measurements, and is also
responsible for maintaining equipment in good working condition. Extra batteries were
carried in the field to assure that all equipment was operating with required power
sources,
WET Lab and School of Fisheries scales are serviced regularly and scales are
calibrated periodically with weights of known measure. The fluorometer is maintained by
and calibrated before each use by passing a sample of known chlorophyll content (see
"Objectives for Measurement, Precision, Microbiota").
Calibration for field estimation and sampling procedures is achieved through staff
training prior to work in the field. Whenever possible, reference material is made available
in the field and questions about plant identification cross-referenced to the University of
Washington or Oregon State University Herbaria,
Table 4 describes the field and laboratory equipment associated with monitoring
parameters,
11.0 ANALYTICAL PROCEDURES
Analytical procedures for parameters (i.e., benthic diatom standing stock, Table 1)
determined through laboratory analyses are specifically described in the Protocol.
12.0	DATA REDUCTION, VALIDATION, AND REPORTING
12.1	Epibenthic Plankters and Benthic Infanna
Species identifications, counts, and standing stock for epibenthic and benthic
meiofauna are entered in a hierarchical computer-coded form structure that provides direct
data entry/retrieval into/out of a computer (relational) data base. The data structure is
based upon, and whenever possible utilizes, the National Oceanographic Data Center
(NODC) system for recording and archiving oceanographic records, The basic field data
form was designed as a variant of NODC format #100, the Intertidal/Subtidal series of
data records developed for research in Puget Sound. For instance, the WET laboratory
uses a modification of the Species Identification Record (Record #4) for benthic
organisms and has created a form for epibenthic and pelagic zooplankton that nests within

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31
this data series. Data entry is performed by the Data Entry Services of the School of
Fisheries, who have their own data checking procedures
12.2 All Other Attributes
Units of measurement for all parameters are listed in Table 1. Field and laboratory
data entry forms were designed uniquely for this project and are included in Appendix I,
Data is entered from field books into Microsoft Excel for Windows™, a spreadsheet
format that has database capabilities.
One original and two backup copies of each file is always made. Two Xerox
copies of field books and database print-outs are also made; one copy stored at the WET
lab and one at the Center for Quantitative Science. Survey (elevation) data are stored in
ASCII files with two backups for use in plotting software.
Validation of data entry is ensured and assessed by two methods: (1) the
investigators who collect the data perform data entry to minimize illogical entries; and (2)
computer printouts of data are cross -checked with the field/laboratory data sheets and
scanned for out-of-range values by the Project Leader and the person responsible for data
entry. If out of range values are encountered, laboratory samples can be reprocessed to
insure that the value was not caused by measurement errors. If the "outlier" is valid or the
result of a field estimation that can not be repeated, it is of interest to the project to
investigate possible reasons for the outlying value. Outliers can be the most interesting
data points, providing information about scales, factors, or types of measurement errors
not assessed. In all cases, the reasons for the outlier would be investigated, and if no
reason could be found, the value would be used as is, and qualifying statements would
accompany data summaries or analyses. Interpolations of missing or outlying data points
will rarely be used.
Statistical analysis and graphical illustration of data will be carried out with the aid
of commercially-available computer programs. Simple graphs can be generated with
Microsoft Excel for Windows™ directly from data retrieved from that database. For more
sophisticated analyses and graphs data can be exported from Excel as ASCII files and
imported into one of the more dedicated programs, such as Statgraphics™, SigmaPlot™,
Graftool™, and Axum™. Most data files are relatively small and sample sizes for each
parameter known, so that the effectiveness of file transfer programs will be readily
apparent. Statistical tests to be performed have been described under the appropriate
Methods sections.

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32
13.0 INTERNAL QUALITY CONTROL CHECKS
Interna] quality control checks are described in "Objectives for Measurement,
Precision".
14.0 PERFORMANCE AND SYSTEM AUDITS
The QA staff of the Environmental Research Laboratory-Corvallis performed a
technical systems audit (TSA) of this project in September 1992. TSAs are conducted
prior to or concurrent with initial data collection activities to: (1) familiarize the project's
staff with EPA QA requirements and procedures; (2) evaluate the implementation of the
QA activities as specified in this document; and (3) provide assistance in attaining the
objective to collect data of known and documented quality.
15.0 PREVENTIVE MAINTENANCE
Equipment maintenance and calibration is described under "Calibration Procedures
and Frequency", Duplicate equipment is always carried, for ALL methods, to be used in
the event of equipment breakage or loss. Only rented equipment is not carried in
duplicate. For those parameters requiring meters or pumps that could break, equipment
was serviced before going in the field, sampling was conducted on only one sampling trip,
and equipment was serviced again on return from the sampling trip.
16.0	SPECIFIC ROUTINE PROCEDURES USED TO ASSESS DATA
PRECISION ACCURACY, AND COMPLETENESS
Precision, accuracy, and completeness, will be assessed in the field and the lab as
described as in earlier sections (see, especially "Methods"),
16.1	Precision
Precision is defined, here, as standard error (SE) about the sampling population
mean. When possible, we will try to distinguish the two components of this variability,
natural variability in the distribution of the attribute population and sampling error (e.g.,
variability due to estimation techniques).
Boot-strapping methods can be used to generate distributions of data and
investigate variability as related to sample size. In some cases bootstraps can be
performed using existing data. In other cases, it may be more meaningful to generate a

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33
distribution that fits the data at hand and sample from that distribution. The
appropriateness of each method will be assessed as we explore the data gathered. In these
cases, desired sample size desired will be that required to detect differences between
means equal to the mean or one half the mean (at a(2) = .05, J3( 1 )= . 1) for the attribute
and species of interest. The procedures for such power analyses will use the methods in
Zar (1894) for two sample t tests and ANOVA.
Vartotal(x) = Varnat(x) + Varmeas(x) Varnat(x) = Natural variability of x
Varmeas(x) = Measurement error of x
Var(x) = Z(Xi - X~ )2/(n-1)
calculated as: ZXj2 - (£Xj)2/n)	Xi - = value of ith measurement
X— = mean of all measurements
n = sample size
Normal SE = sqrt(Var(x)/n)
Binomial SE = p"q7(n-l)	p~ = estimated proportion
q = 1-p
16.2 Accuracy
In our project, accuracy criteria can be applied to the calibration of instruments the
taxonomic identification of species, and blank processing using the fluorometer (see
previous section on accuracy under "Data Quality Objectives"). No accuracy evaluations
are possible for parameters such as percent cover of rooted vascular plants. Accuracy will
be assessed, respectively, as product specifications for instruments, percentages of
specimens properly identified, divergence (bias) of reading from known values.

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34
16.3	Bias
Bias will be calculated as both the absolute and the percentage deviation of the
measurement/processing estimate from a known reference sample (both B=X-T and
B=100 (X-T)/T). Relative bias of different sampling methods will be calculated as
percentage of positive and negative estimates relative to another method (B= number
high/total number of samples), magnitude of maximum difference between two methods
(max (XrX2)).
16.4	Completeness
Completeness of sampling efforts, laboratory analysis, and data analysis will be
assessed as the ratio of the number of data intended versus the number actually completed.
Because much of our data gathering is exploratory, if the full sampling effort does not
achieve desired precision levels, additional required sampling will be recommended.
16.5	Representativeness
See above under "Data Quality Objectives - Representativeness".
16.6	Comparability
See above under "Data Quality Objectives -Comparability". The Protocol
specifically recommends that all monitoring procedures be deployed such that the data
generated are maximally comparable, and are standardized. For each attribute group (e.g.,
monitoring parameter), data were gathered from the different estuarine locations and
habitats using exactly the same procedures. In addition, all data were standardized to
common scientific dimensional (e.g., area, volume) references (e.g., grams wet m"2).
When measurement error could not be tested, it was controlled by training and methods
described in "Sampling Procedures". Because the methods for gathering data for each
parameter are standardized, the validity of comparisons will be based on biological interest
in the comparison.
16.7	System Error
System error is not an appropriate criterion for the purposes of this QA/QC
project, In this case, locating and correcting errors in specific procedures and estimates
will be the focus of this effort.

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35
17.0 CORRECTIVE ACTIONS
All deviations in accuracy or other quality indices discovered in quality control
checks will be investigated by the Project Leader (epibenthos, benthic infauna) or the
Statistical Consultant (all other attributes). The error source and the extent of affected
samples will be determined. If a directly translatable error can be identified (e.g., calling
species X species Z), all prior data will be corrected and spot checks of these samples will
be conducted to verify that the correction is proper. If a non-specific error is found, 25%
of the prior samples will be examined to determine the extent of the error If more than
10% of these samples illustrate the error, all samples will be reprocessed.
18.0 QUALITY ASSURANCE REPORTS (TO MANAGEMENT)
A final report is being submitted to EPA, including the results of all internal quality
control checks, documentation of accuracy and precision determinations, corrective
actions implemented if required, and other problems encountered that potentially affected
data quality.
19.0 REFERENCES
Bros, W. E., and B. C Cowell. 1987. A technique for optimizing sample size (replication).
Exp.Mar. Biol. Ecol. 114: 63-71.
Carlile D.W., J R. Skalski, J E. Batker, J.M. Thomas, and V.I. Cullinan. 1989.
Determination ofEcological Scale, Landscape Ecology 2: 203-213.
Cordell, J.R., C.A. Morgan, and C A Simenstad. 1992. Occurrence of the Asian
calanoid copepod Pseitdodiaptonms mopmus in the Columbia River Estuary.
Journal of Crustacean Biology. 12(2): 260-269.
Dethier, M. N. 1990. A marine and estuarine habitat classification system for Washington
¦ State. Wash. Nat. Heritage Prog., Dept. Nat. Res., Olympia, WA. 56 pp.
Faulkner, S. P., W H. Patrick, Jr., and R. P. Gambreil. 1989. Field techniques for
measuring wetland soil parameters. Am. J, Soil Sci. Soc, 53:883-890.
Goodall, D. W. 1951. Some considerations in the use of point quadrats for the analysis of
vegetation. Aust. J. Sci. Res, Ser. D 5: 1-41,
Hsieh, Y.P. and C.H. Yang, 1992, A method for quantifying living roots of Spartina
(cordgrass) and Juncus (needlerush). Estuaries 15: 414-419.

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36
Simenstad, C. A., C. D, Tanner, R. M. Thorn, and L. Conquest. In press. Estuarine
Habitat Assessment Protocol. FRI-UW-8918, Wetl. Ecosys. Team, Fish. Res.
Inst., Univ. Wash., prepared for U.S. Environ. Protect. Agency, Region 10, Off.
Coast. Wat., Seattle, WA.
Strickland, J, D, H., and T. R, Parsons. 1977. A Practical Handbook of Seawater
Analysis. Bull. 167, 2nd ed,, Fisheries Res. Bd. Canada, Ottowa, Canada.
Tetra Tech, Inc. 1986. Puget Sound Protocols. Puget Sound Estuary Program, Final
report to Region X EPA, TC-3991-04.
U.S. Environmental Protection Agency, 1985. NEIC policies and procedures. EPA-330/9-
78-001-R, Natl. Enforcement Invest, Cent., Denver, CO.
Zar, J.H Biostatistical Analysis. 1984 Second Edition. Prentice-Hall, Inc. Englewood
Cliffs, N J,

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37
Table 1 Parameters proposed for selective testing of Estuarine Habitat Assessment
Protocol; see QA Plan Appendix A for full description of methodology, NA =
no "true values" available for these parameters. Accuracy = Accuracy of
Instrumentation Precision = precision required on repeated measurement
Functional Attribute
Attributes
Parameter
Units of
Accuracy/
I Protocol



Measurement
Precision
1 page
Site Establishment
& characterization
elevation relative to ft relative to accuracy, 0.01 ft.,
Mean Water
benchmark
precision, 0.03 ft. on
"closing"
porcwatcr salinity ppt
YSI precision, 0.1,
refractometer, 1.0
redox
millivolts precision. 0.1
Rooted Vascular Plants
(Emergent Marsh
Vegetation)
(approximately 40
plant asseemblages;
see final Protocol, p.
42)
percent cover
above-ground
biomass/standing
stock
below-ground
biomass/standing
stock
% /	accuracy, NA;
sampling precision, to nearest
unit	whole number
g dry wt/m- accuracy, 1 mg;
precision, 5%
41-44
43
44
Benthic microbiota
benthic/epiphytic
algae (diatoms)
standing stock	mg/m2 accuracy, 0.1 mg;
precision, 1%
49-50
Sedentary I nfauna
Epibcnthic Plankters
Manayunkia
aestuarina
Macoma spp
Mya arenaria
Neanthes limnicola
Tanais spp.
Transenella tantilla
Corophium spp
Eogammarus
confervicolus
Cumella vulgaris
density
standing stock
densitv
standing stock
no./m2
no
/m^
I wet
(preserved/
m2
accuracy, NA;
precision, 1%
; dry wt/m' accuracy; NA;
precision, 2%
accuracy, NA;
prec. -subsampling,
5%, -sorting, 2%,
-counting, 1%
accuracy, 1 mg;
prec.-subsampling,
5%, -sorting, 2%,
-weighing, 5%
61-62
61-62
71-72
71-72

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38
% ovigerous	% total
females	density
accuracy, NA;	71-72
prcc. -subsampling,
5%, -sorting, 1%,
-counting, 1%

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39
Table 2 Sample design and sample sizes, by site and stratum for selected attributes (see
text for explanation of methods).
Site Vertical transect	25x10m plot 3x5 m plot Visual Horizontal transect
12 3	Estimate 40m 50m 160m
(all strata)	(hm)	(hm)	(hm) (mud) (hm) (mud)
ELK1 EL EL EL 104 RPQ	20 EP1
8 AG 15 AG	24 AG	20 MEI
8 BG 15 BG	10 MB
8 PW 15 PW	20 pH
20 RED
20 T
ELK2 EL EL EL 104 RPQ	80 EPI
5 AG 7 AG 7 AG 24 AG	80 MEI
5 BG 7 BG 7 BG	20 MB
5 PW 7 PW 7 PW	20 pH
20 RED
20 T
ELKJ EL	EL	EL 104 RPQ
7 AG	3 AG	7 AG 12 AG
7 BG	3 BG	7 BG
7 PW	3 PW	7 PW
20 EPI
20 MEI
10 MB
20 pH
20 RED
20 T
SSI EL	EL EL
10 AG	15 AG
10 BG	15 BG
10 PW	15 PW
104 RPQ
24 AG
552	EL EL	EL 104 RPQ	67 RPQ(a) 24 quad;	RPQ 80 EPI
8 AG	8 AG 24 AG	220 RPQ(r)	(teams) (syst) 80 MEI
8 BG	8 BG 24 BG	5 quad;	20 MB
8 PW	8 PW 24 PW	(repeat meas)
553	EL EL	EL 104 RPQ
8 AG	24 AG
8 BG
8 PW
AG - Above-ground standing slock	EL = Elevation	MEI = Meiofauna PW - Porewater
BG - Below-ground standing stock	EPI = Epibenthos	MB - Microbiota RED = Redox potential
RPQ = random point quadrat (% cover veg)	(a) = all species	(r) = rare species T = Temperature
hm = high marsh	mud = mudflat	repeal meas = J sizes, 4 people, 3-4 reps (% cover veg)

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Table 3 Transport and storage of samples
Functional Attribute
Parameter
Container
Transport Storage
Site Establishment
& characterization
elevation
porewater salinity
redox potential
NA
NA
NA
Rooted Vascular Plants
percent cover
above ground
biomass
below ground
biomass
NA
12"x24"
plastic bags
12".\224"
plastic bags
NA
ice chests
ice chests
NA
immediately
sorted and
dried
immediately
sorted and
dried
Bcnthic microbiota
standing stock
darkened
glass or
plastic jars
ice chests
frozen until
analysis
Sedentary Infauna
density
standing stock
¦ 16 oz. pvc
jars, buffered
formalin
buckets
boxes
shelved at
Fisheries until
analysis
Epibenthie Planktcrs
density
standing stock
% ovigerous
females
8 oz, pvc jars
buffered
formalin
buffered
formalin
buckets
boxes
shelved at
Fisheries until
analysis

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41
Table 4 Lab and field equipment for measuring parameters
Functional Attribute
Parameter
Field Equipment
Lab Equipment
Site Establishment
& characterization
Rooted Vascular Plants
(Emergent Marsh
Vegetation)
elevation
porewater salinity
redox potential
percent cover
above-ground
biomass
below ground
biomass
Leitz Total Station
YSI meter, refractometer
Beckkmann pH redox meter
(PHI 11) with Fisher no. 13-
620-82 electrode
visual estimates in benthic
quadrats; 50 m tape measures
for transects and delineating
areas, wooden stakes, thin rod
.125 quadrat
1.25" pvc core, 20 inches long
Sokkia software
NA
NA
NA
Metier top-loading
analytic balance
Metier top-loading
analytic balance
Benthic microbiota standing stock
.75" plastic syringe
Turner 111
flourometer
Sedentary Infauna	density
standing slock
1.25" pvc core,, 20 inches long dissecting
microscope
1.25" pvc core. 20 inches long Metier top-loading
analytic balance
Epibenthic Plankters
density
standing stock
% ovigerous
females
epibenthic suction pump
dissecting
microscope
Metier top-loading
analytic balance
dissecting
microscope

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42
Table 5 Methods of assuring precision, accuracy, and completeness of Protocol
assessment parameters, RPQ = random point quadrat, wrt = with respect to.
Parameters
Precision
Accuracy
Completeness
Taxonomic id
Epibenthic plankters.
benthic meiofauna,
% ovigerous females
Standing stock
Epibenthic plankters
benthic meiofauna
above-ground bioniass
below-ground biomass
Percent Cover
Rooted vascular plants
mean overlap in two
independent assessment
mean difference in 2 independent
sample counts applied to 5% of
samples
RPQ: binomial CI's,
vary sampling density
Visual: test for team effects
(ANOVA); mean, std dev of
individual measurement error,
wrt quadrat size, species, individual;
# hi. low estimations/individual
Scale: compare CI's vvn to constant n,
constant sampling effort (time, cost):
Time series, Markov chain. Carlile et.al.
Id's checked by
Project Leader
NA
NA
% samples
completed
% samples
completed
% samples
completed

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43
Figure 1. Locator map of estuaries sampled; Grays Harbor, WA and South Slough, Coos
Bay, OR
eattle
Aberdfegi
Grays Harbor
Willapa Bay, Jg
Tillamook Bay

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GRAYS
HARBOR
ELK 1 W'
ELK 2
Figure 2. Map of three gradient sites in South Slough and Elk River

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Figure 3. : Example of a wetland site with strata, sampling transects,
and sampling plots
li;
upland
high marsh
low marsh
mudflat
A, B 25 x 10 m RPQ sampling plots
C 3 x 4 m RPQ sampling plot
D, E horizontal sampling transect
F.G, H vertical elevationiransect
J, K, L topo point
I control point

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20.0	APPENDICES
20.1	Appendix A: Sample field and laboratory data sheets
A.
Rpq sampling at 5 cm interval along horizontal transect
B
Visual estimates of % cover emergent vegetation by teams
C.
RPQ sampling at random x,y coordinates in 25 x 10 m area
D.
Repeat visual estimates of % cover emergent vegetation by individuals
E,
pH, redox, temperature readings along horizontal transect
F.
Pore water readings along elevation transect, different methods
G
Above-ground standing stock by species; laboratory weights of sample

with aluminum foil
H.
Epibenthos, Meiofauna
I.
Microbiota Flourescence

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V
TECHNICAL REPORT DATA
(Please read Instrucnens on the reverse before completi
1. REPORT NO,
EPA/600/R-93/231
3,
lll lll III II'IIII
PB94-130341
4. titQiiA8j8§yBAli'&§rariCe Project Plan for Evaluating
and. Refining the Estuarine Habitat.Assessment
Protocol on Puget Sound and Pacific Northwest
Reference Sites
5. REPORT DATE
December 1993
6. PERFORMING ORGANIZATION COOS
7. AUTHOBIS!
e.Simenstad, L.Tear, J.Cordell
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANISATION NAME AND ADDRESS
U. of Washington, Seattle, WA
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
12. SPONSORING AGENCY NAME ANO ADDRESS
US EPA ENVIRONMENTAL RESEARCH LABORATORY
200 SW 35th Street
CorvaJUs, OR 97333
13. TYPE OF REPORT ANCLPJERIOO COVERED
Published Report
14. SPONSORING AGENCY CODE

15. su£^^ENT^.R^N!gEsrirormaen.tal Protection Agency, ERL-Corvallis, OR
'6- AHJfi^c5stuarine wetland scientists and managers are of the opinion that present
wetland habitat assessment procedures are inadequate for application to specific
geographic regions and may be too subjective to provide consistent results. This
is particularly the case in Pacific Northwest estuaries, where wetlands are
structurally and functionally different from southeast and Gulf coast estuaries,
for which most assessment approaches were originally .developed. To increase the
effectiveness of our management and conservation of estaurine habitats, we need
assessment and monitoring procedures that: (1) are based explicitly on habitat
function; (2) are specific to the region of applications; (3) use methods that
are standardized, consistent and comparable; (4) generate quantitative data
rather than qualitative indices; (5) are designed to be thoroughly objective
among different users and sites; (6) will be adaptive in terms of building on
prior results; and (7) are structured in a flexible form wherein both the biotic
community and target resources can be addresses. This report represents such an
approach to assessing the function of estuarine habitats for fish and wildlife,
and specifically for the Pacific Northwest region. Habitat functions, such as
maintenance of water quality or flood desynchronization, should be assessed with
similar rigor. The report is intended to address the need for a systematic
procedure that can be applied uniformly across a variety of wetland and
associated nearshore habitats using objective, scientific methods. The approach
is directly applicable for the study of natural wetland systems and in evaluating
compensatory mitigation projects in estuarine habitats. It also has the potential
to facilitate the development of design criteria for estuarine habitat
rootoration. 				 	 -	....
KEY WOROS AMD DOCUMENT ANALYSIS
a. DESCRIPTORS
b.IDENTIFIERS/OPEN ENDED TERMS
c. COSATI Fieid/Cioup
Wetlands, Quality assurance, Wetlc
assessment, Pacific Northwest, Est
wetlands.
Llld
.uarine

IB. DISTRIBUTION STATEMENT
13. SECURITY CLASS (Thit Report)
21. NO. C^PAGES
20. SECURITY CLASS (Tins pagel
22. PRICE
Ef>A Form 2220-1 (»•*¦ 4-77)
PREVIOUS EDITION >S OBSOLETE

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