United States
Environmental Protection
Agency
Environmental Research
Laboratory
CorvaUis, OR 97333
EPA/600/R-93/072
April, 1993
Research and Development
&EPA
RESEARCH PLAN AND METHODS MANUAL
FOR THE
OREGON WETLANDS STUDY
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EPA/600/R-93/072
April, 1993
RESEARCH PLAN & METHODS MANUAL
FOR THE
OREGON WETLANDS STUDY
Authors:
Teresa K. Magee1
Stephanie E. Gwin2
Robert G. Gibson2
Cindy C. Holland2
JoEllen Honea2
Paul W. Shaffer2
Jean C. Sifneos2
Mary E. Kentula3
Document Production by:
Kristina Miller2
Independent Consultant
371 ONWWitham hill Drive
Corvallis, OR 97330
2
'ManTech Environmental Technology, Inc.
USEPA Environmental Research Laboratory
200 SW 35th Street
Corvallis, OR 97333
3
'U.S. Environmental Protection Agency
Environmental Research Laboratory
200 SW 35th Street
Corvallis, OR 97333
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EPA/600/R-93/072
April, 1993
DISCLAIMER
The research described in this report has been funded wholly or in part by the
United States Environmental Protection Agency under Contract #68-08-0006 to
ManTech Environmental Technology, Inc., and Purchase Requisition #2B1149NATAto
Teresa Magee. Mention of trade names or commercial products does not constitute
endorsement or recommendation for use.
This document should be cited as:
Magee, T.K., S.E. Gwin, R.G. Gibson, C.C. Holland, J.E. Honea, P.W. Shaffer, J.C.
Sifneos, and M.E. Kentula. 1993. Research Plan and Methods Manual for the
Oregon Wetlands Study. Document production by K. Miller. EPA/600/R-93/072. U.S.
Environmental Protection Agency, Environmental Research Laboratory, Corvallis, OR.
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ACKNOWLEDGEMENTS
We would like to express our gratitude to the landowners of the properties on
which the study wetlands are located. Without their willingness to allow sampling
activities to occur on their land, this research could not be conducted. We also thank
the Oregon Division of State Lands for providing access to the wetland projects over
which they have jurisdiction, and for providing access to the permit files which contain
the information on the design and construction of these projects.
Preparing for this study required gathering a great deal of information on
wetland locations and surrounding land uses. The Portland Metropolitan Service
District (METRO) assisted in this task by creating maps of land use and wetland
locations for our use in selecting the study sites. The Port of Portland and the Oregon
Department of Transportation also assisted in our site selection efforts. Both agencies
provided information and access to sites located on properties within their control, and
often went one step further by providing historical data and information on future plans
for the sites.
The document benefited greatly from the suggestions of several reviewers.
EPA Region 10, other agencies, and members of the academic community gave
generously of their time to provide comments. Specifically, we thank the following
individuals for their thoughtful reviews: Cara H. Berman and Unda Storm (EPA
Region 10), Robert P. Brooks (Pennsylvania State University), Jim Goudzwaard
(Portland District, U.S. Army Corps of Engineers). James A Schafer (Washington
State Department of Transportation), Joel Shaich (Oregon Division of State Lands),
Virginia Burkett (U.S. Fish and Wildlife Service), Brian Lynn and Thomas Hruby
(Washington Department of Ecology), J. Herbert Huddleston (Oregon State
University), and Grady E. Neely (USEPA. Environmental Research Lab-Corvallis). In
addition, we would like to thank Ann Hairston, Deborah Coffey, and Kate Dwire
(ManTech Environmental Technology) for editorial and quality assurance review.
Finally, we thank Teresa Villena for producing many of the complicated tables found
throughout the document.
III
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1. !NTRODUC11ON AND STUDY OVERVIEW .
STUDY DESIGN
Sampling Strategy
Study Area
Site Selection
Wetland Characterization
11MELINES AND IMPLEMENTA11ON
2. SITE SELECTiON
DEFINING THE POPULATiON OF PROJECTS
DEFINING AND SAMPLING ThE POPULATION OF
WETLANDS
Locating Natural Wetlands
Field Reconnaissance of Natural Wetlands
3. OVERVIEW OF FIELD ACTIVITIES
CREW MEMBER EXPERTISE
GENERAL ORDER OF TASKS
DATA AND SAMPLE CUSTODY AND HANDLING
QUALITY ASSURANCE
STRUCTURE OF WETLAND CHARACTERIZATION
41
41
45
45
47
47
51
Transect Establishment Procedures in Atypical Situations 52
5. GENERAL SITE DATA
SITE MAPS
Equipment
The Brunton Cadet Compass .
Setting Up the Transit
Using the Transit to Map the Study
Drawing the Final Site Map
LAND USE AND BUFFERS
PHOTOGRAPHY
6. VEGETATiON
SAMPLING METHODS
FIELD METHODOLOGY
TABLE OF CONTENTS
I
7
7
10
11
11
19
21
21
25
25
31
33
33
35
38
40
40
NATURAL
SECTiONS
4. TRANSECT ESTABLISHMENT
TRANSECT TYPES AND OVERVIEW OF METHODS
FIELD METHODOLOGY
Site Characterization Transects
Wetland Morphology Transect
Vegetation Transects
General Transect Establishment Procedures
Site
55
55
56
56
58
60
66
68
72
76
77
79
iv
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Field Equipment and Supplies . 81
Pre-Sampling Activities 81
Vegetation Sampling 84
Placing the meter tape 89
Sampling Order for Vegetation Data 89
Line-intercept data collection (Figure 6-3) 92
Canopy cover estimation within quadrats 92
Basal area data collection within belt-transects 97
Establishing the Transect Endpoint 97
Post-Sampling Activities 98
Final Plant Collection and Plant Specimen Preservation 98
LABORATORY ACTiVITIES 100
Equipment 100
7. WETLAND MORPHOLOGY 102
FIELD METHODOLOGY 102
Equipment 103
Getting Started 103
Collecting Wetland Morphology Data 103
Turning with the Original Benchmark 107
Turning with a New Benchmark 108
AdjustingtheEye Level Plane 108
8. SOILAND HYDROLOGIC CHARACTERIZA11ON 111
FIELD METHODOLOGY 113
Genera] Considerations in Soil Descriptions and Sampling 113
Equipment and Supplies 117
Field Sampling Procedure 117
LABORATORY ANALYSIS - LOSS ON IGNI11ON 122
Equipment and Supplies 122
General Considerations for Laboratory Analysis 122
Laboratory Analysis Procedure 123
Calculations 125
9. EXISTiNG DATA 126
TRENDS IN DIRECT WETLAND LOSS 126
COMPLIANCE OF AS-BUILT CONDITIONS WITh PERMIT
SPECIFICATiONS 126
10. DATA MANAGEMENT 127
TERMS USED 127
DATA ENTRY 130
RECONCILING ThE DATA SETS 130
Comparison of the Data Sets 132
Correction of Differences 132
Recording Problems 136
TESTS PERFORMED AFTER RECONCILING ThE DATA SETS 136
v
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STORAGE OF DATA 136
11. DATA ANALYSIS 140
DATA ANALYSIS PROCEDURES 142
Characterization and Comparison of the Wetlands 142
SUMMARY 150
LITERATURE CITED 154
APPENDIX A 160
APPENDIX B 170
vi
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LIST OF TABLES
Table 1-1. Summary of study questions and research approaches for the
Oregon Wetlands Study 12
Table 1-2. List of variables to be sampled in the Oregon Wetlands Study. . . . 13
Table 1-3. Existing data used in the Oregon Wetlands Study . . . . 17
Table 1-4. Schedule of key events in the Oregon Wetlands Study 20
Table 2-1. Numbers of freshwater mitigation projects in Portland, Oregon, by
wetland type and size required in permits issued by the U.S. Army
Corps of Engineers and the Oregon Division of State Lands from
January 1987 through January 1991. ? indicates area unknown . . 22
Table 2-2. National Wetlands Inventory (NWI) wetland types included in site
selection of natural wetlands for the Oregon Wetlands Study 26
Table 10-1. Summary calculations for vegetation data (Homer and Raedeke
1989, Mueller-Dombois and Ellenberg 1974) 137
Table 11-1. Statistical analyses proposed for the Oregon Wetlands Study . . . . 143
VII
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LIST OF FIGURES
Figure 1-1. Types of information needed for a wetland management strategy
that employs restoration and creation to replace direct and indirect
losses of ecological function 4
Figure 1-2. Research strategy for determining the causes of direct wetland
loss, and the number of wetlands converted to other land types, in
the Portiand metropolitan area 5
Figure 1-3. Research strategy for evaluating the potential for indirect loss of
wetland function due to the effects of land use in the Portland
metropolitan area 6
Figure 1-4. Research strategy for evaluating the potential for indirect loss of
wetland function in the Portland metropolitan area due to level of
project performance 8
Figure 1-5. Research strategy for determining indirect loss of wetland function
in the Portland metropolitan area due to project design and
implementation 9
Figure 2-1. An example of a form that can be used to compile information on
wetland projects (Holland and Kentula 1990) 23
Figure 2-2. An example of a completed form that can be used during field
reconnaissance to collect information on potential study sites 27
Figure 2-3. An example of a typical wetland project visited during site
se!ection 29
Figure 2-4. An example of a natural wetland in Oregon 30
Figure 2-5. The letter given to landowners during site selection explaining the
Oregon Wetlands Study 32
Figure 3-1. Flowchart of Field Crew Member responsibilities and tasks 34
Figure 3-2. Equipment list for the Oregon Wetlands Study 36
Figure 3-3. Custody log for plant specimens and soil samples collected during
the Oregon Wetlands Study 39
Figure 4-1. Basic transect layout used to sample sites 42
Figure 4-2. Vegetation Transect (VT) placement when vegetation band is
more than two sampling intervals wide 43
Figure 4-3. Vegetation Transect (VT) placement when the vegetation is less
than two sampling intervals wide 44
Figure 4-4. Transect establishment protocol flowchart 46
Figure 4-5. Form F-i, used for recording transect establishment data 48
Figure 4-6. Procedures for transect establishment in cases where deep open
water interrupts one or more transects 53
Figure 5-1. A view through a transit telescope 57
Figure 5-2. Setting the magnetic declination on a compass 59
Figure 5-3. Form F-2, Sketch Map 61
Figure 5-4. Form F-3, Map Data Sheet 62
Figure 5-5. Example of the scale markings on a stadia rod 65
Figure 5-6. Illustration of procedure for triangulation 67
Figure 5-7. Example of a finished site map 69
vu’
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Figure 5-8.
Figure 5-9.
Figure 5-10.
Figure 5-11.
Figure 6-1.
Figure 6-2.
Figure 6-3.
Figure 6-4.
Figure 6-5.
Figure 6-6.
Figure 6-7.
Figure 6-8.
Figure 8-2.
Figure 8-3.
Figure 8-4.
Figure 10-1.
Figure 10-2.
Figure 10-3.
Figure 10-4.
Figure 10-5.
Figure 10-6.
Figure 10-7.
70
71
73
74
80
83
85
86
88
90
91
93
94
96
105
109
114
115
116
124
128
129
131
133
134
135
138
145
146
148
149
151
Figure
Figure
Figure
Figure
Figure
6-9.
6-10.
7-1.
7-2.
8-1.
Placement of transects for determination of presence, type and
width of buffers
Form F-4, for sketching types and extent of buffers and land uses
surrounding the site
Form F-5, photographic label
Form F-6, photo record
Vegetation sampling protocol flowchart
Form F-7, herbaceous vegetation/canopy coverage - quadrat data
Form F-8, all shrubs and trees <2m tall - line-intercept data
The position of the first and last quadrats on vegetation sampling
transects
Form F-9, used for tree identification and diameter breast height
Transects used for sampling herbaceous vegetation, shrubs, and
trees. (Adapted from Homer and Raedeke 1989)
Illustration of transect segments in which vegetation data are
collected and the order of data collection
Determining the intercept intervals for shrubs using the line-
intercept method
Placement of the 1-rn 2 quadrat along a transect line
Illustration of species cover estimation within a 1-rn 2 quadrat
Form F-I 0, wetland morphology
Adjusting the eye level plane
flowchart showing sampling options and sequence of sampling
activities for characterization of soil and hydrologic attributes
Form F-i I, soil/hydrology characterization
Form L-1, determination of soil organic matter
Form L-2, supplemental soil data for soils sampled using a coring
device
Example of a record from a vegetation database
Example of a key field in a vegetation database
Example computer screen showing a lookup table
Flowchart of the three step comparison and reconciliation process
Matching the filenames to be compared by the dual data entry
program
Example computer screen showing the reconciliation of a
GENUS/SPECIES name in a vegetation database
Example notebook entry for identifying problems encountered
during the data reconciliation process and their solutions
Example of approaches for characterizing wetlands
Hypothetical ordination and classification of wetland data
Plant diversity data from the 1987 Oregon Pilot Study
Weighted average scores for the type of vegetation found on
individual project (P) and natural (N) wetlands from the 1987
Oregon Pilot Study
Hypothetical characterization curves comparing the level of
function in groups of wetlands in different land use settings
Figure
Figure
Figure
Figure
11-1.
11-2.
11-3.
11-4.
Figure 11-5.
ix
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Figure 11 -6. Hypothetical performance curves comparing the anticipated
development of the projects constructed prior to 1987 to the
development of projects constructed since 1987 and to similar
natural wetlands 152
x
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1. INTRODUCTION AND STUDY OVERVIEW
Wetlands are recognized as valuable components of the landscape contributing
in many ways to overall environmental quality. Comprising only about 5% of the land
area in the conterminous United States (DahI 1990), wetlands have a significant
influence on the landscape because of their roles in regulatng watershed hydrology
and water quality. Moreover, they provide habitat for a diverse flora and fauna that
includes over one-third of the nation’s endangered species (U.S. Fish and Wildlife
Service 1990). Wetlands encompass a wide array of habitat types (Cowardin et al.
1979) and exhibit a level of productivity second only to tropical rainforests (liner
1984). During the last 200 years, more than half of all wetlands in the United States
have been lost due to human activities, primarily conversion for agricultural uses and
urban development. Losses in some states (e.g., California, Ohio) have been on the
order of 90% (Tiner 1984, DahI 1990).
Aithough many regulations govern wetland protection (e.g., Section 404 of the
Clean Water Act and the Food Securities Acts) they have proven to be only partially
successful. Consequently, the National Wetlands Policy Forum has recommended the
adoption of a clear policy designed to achieve no overall net loss of wetlands in terms
of area or function (Conservation Foundation 1988). Aiming toward fulfilling its
responsibilities for wetland conservation, the U.S. Environmental Protection Agency
(USEPA) has identified two points of national concern: 1) the need to advocate a
national goal for no net loss of wetlands and 2) the development of a risk-based
approach to wetland protection and management (Leibowitz et al. 1992).
Economic pressures to develop wetlands have resulted in wetland restoration
and creation projects (hereafter projects”) being constructed with increasing
frequency. However, the efficacy of restoration and creation methods remains
uncertain. The technology is unproven for many types of wetlands and the quality of
completed projects is inconsistent. The success of projects is not well documented,
because performance criteria are lacking and monitoring is insufficient (Kusler and
Kentula 1991, Leibowitz et al. 1992). Where specifications for final project condition or
quality exist, they are often vague and qualitative (e.g., replacement of ecological
function), and thus not amenable to rigorous evaluation. Post-construction monitoring
to insure that mitigation projects meet the minimum physical criteria (e.g., size, slope,
or wetland type) of permit requirements is seldom conducted. When monitoring does
occur, it is often noted that completed projects vary substantially from the permit
specifications and design plans (Gwin and Kentula 1990, Owen 1990b, Erwin 1991).
The information deficit regarding 1) the conditions and characteristics of natural
wetland ecosystems considered for permitted losses, and 2) appropriate design
specifications and performance criteria for replacement wetlands has made it difficult
to make sound management decisions. The Oregon Wetlands Study (OWS) is
designed to provide detailed characterizations of a large number of natural, created, or
restored freshwater wetlands that range from sites dominated by open water to those
dominated by emergent vegetation, and are located in the urban environment of
Portland, Oregon. The data arising from the proposed research is expected to add to
basic knowledge about wetlands and provide wetland regulators with information that
can improve management strategies, wetland project design, and factilitate
1
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implementation of a no net loss policy within the study area. This information may
also have general applicability for freshwater wetlands in geographic regions outside
the study area due to similarities in 1) hydrologic conditions that support grass and
sedge dominated vegetation (Mitsch and Gosselink 1986), and 2) wetland
management strategies (Gwin and Kentula 1990, Owen 1990, Brown 1991, and
Kentula et al. 1992a). It is, also, anticipated that the methodology developed in this
study can be adapted with minimal effort to wetlands elsewhere in the country.
particularly to other freshwater marsh systems.
Describing the approach and objectives of the OWS will require reference to
several terms that have regulatory implications or that may have multiple meanings.
In the interest of clarity, definitions are provided in the text block on page 3.
Several kinds of information are required for development of sound wetland
management strategies that employ restoration and creation to replace direct and
indirect wetland losses. An overview of information needs is provided in Figure 1-1.
The general approach of the OWS will be to collect data that can be used to
characterize and compare the structural and functional attributes of: 1) populations of
natural wetlands in different land use settings and 2) populations of natural wetlands
and wetland projects. Characterizations will be used to 1) document direct losses of
wetland area or function through conversion; 2) identify the relationships between land
use and attainable wetland quality; 3) evaluate indirect losses of wetland function due
to the impacts from surrounding land uses and poorly designed projects; and 4)
evaluate the potential for wetland restoration and replacement. This information will
aid in the development of performance criteria and design guidelines for wetland
projects, and ultimately, be used in evaluating the results of management strategies
and to suggest alternative approaches. Specifically, documenting the causes of direct
and indirect wetland losses and developing mechanisms for preventing continued
attrition are key steps in sound regulatory practices. This is particularly important in
rapidly developing urban areas. Direct losses arise from conversion of wetlands to
other land uses such as residential or commercial construction and industrialization.
Indirect losses arise primarily from two sources. Surrounding land use can cause
degradation of wetland structure and function via inputs of urban run-off, influx of
exotic taxa, alteration of hydrology or sedimentation rates, destruction of buffers,
habitat fragmentation and other disturbances. Inadequately designed or constructed
projects contribute to indirect loss by failing to completely replace the functions of
destroyed wetlands or achieve the attainable quality possible for the associated land
use setting.
Four research objectives and the associated research questions and
approaches have been identified to fill the information needs described above and
contribute to a cohesive management and regulatory program:
ObjectIve 1: Determine the number freshwater wetlands that have been converted to
other land types and identify causes of this direct loss (Figure 1-2).
ObjectIve 2: Evaluate the relationship between surrounding land uses andthe
attainable quality of freshwater wetlands (Figure 1-3).
2
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Characterize and Monitor
Natural Wetlands and Projects
Identity relationship Identify relationship
Determine Identify relationship between bween projed
between land use
amount of replacement performance and
and attainable
conversion potential and replacement
quality attainable quality potential
Document
Document Indirect Losses
Direct Losses
Wetland Management Strategies
Figure 1-1. Types of information needed for a wetland management strategy that employs
restoration and creation to replace direct and indirect losses of ecological
function. See text for definitions.
4
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Objective 1: Determine the number of freshwater wetlands that have been
converted to other land types and identify causes of this direct loss.
What are the principal reasons
What are the short term trends
in wetland loss due to conversion? (e.g., land uses) for wetland
losses due to conversion?
Document reasons for wetland
Compare the most recent NWI data
conversion identified in the course
with the results of the inventory
of conducting the inventory during
from the field reconnaissance.
the field reconnaissance.
Figure 1-2. Research strategy for determining the causes of direct wetland loss, and the
number of wetlands converted to other land types, in the Portland metropolitan
area. NWI=the U.S. Fish and Wildlife Service’s National Wetlands Inventory.
5
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Objective 2: Evaluate the relationship between surrounding land uses
and the attainable quality of freshwater wetlands.
What is the relative attainable
quality of wetlands in different land
uses, and how are differences in
quality reflected in wetland
structure and function?
‘I ,
Step 1: Quantify and
compare wetland structure
and function by land use
category.
Step 2: Rank the land
uses according to the
relative quality of the
wetlands.
Step 3: Explore whether
vegetated buffers
ameliorate effects of
land use.
Figure 1-3. Research strategy for evaluating the potential for indirect loss of wetland
function due to the effects of land use in the Portland metropolitan area.
Land use categories are undeveloped, agricultural, residential, commercial,
and industrial.
6
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Objective 3: Evaluate the replacement potential of freshwater wetlands to aid in the
development of performance criteria (Figure 1-4).
Objective 4: Evaluate how project design and implementation affect the replacement
potential of freshwater wetlands to aid in the development of design guidelines (Figure
1-5).
STUDY DESIGN
A brief 9verview of the sampling strategy, study area description, site selection
procedures, and variables sampled for wetland characterization is presented here.
These topics are discussed in detail in the chapters that follow this overview.
Sampling Strategy
The OWS builds on work from the Oregon Pilot Study conducted in the
metropolitan area of Portland, Oregon, in 1987 (Kentula et al. 1992a). During the
1993 growing season, approximately 150 freshwater wetlands ranging from sites
dominated by open water to those dominated by emergent vegetation will be sampled,
including the sites sampled in 1987. The OWS is designed to produce results that are
regionally applicable to wetland protection and management, therefore an extensive
sampling approach focusing on populations of wetlands has been adopted.
Populations have been chosen for study over single or paired sites, because the
general representativeness of single sites often cannot be determined, thus
extrapolating results from one site to other systems is, in most cases, unwise. In the
same way, data for a single site can not provide insight into variability among wetlands
of a given type or in a particular landscape setting. An extensive sampling plan is
required for quantitative and statistical evaluation of the effects of factors such as land
use or project age on wetland attributes. The natural wetlands sampled in this study
will serve as reference sites against which the projects are judged and as standards to
assess how well project goals are met. Older projects are reference sites against
which to judge more recently constructed projects to 1) verify that the projects are
developing as expected over time and 2) identify developmental patterns that are the
result of changes in project design (Kentula et al. 1992a).
The extensive sampling approach selected for the OWS will provide a better
information base for addressing study objectives than would more detailed study of a
small number of wetlands. Because resources for the field study are limited, however,
a consequence of the extensive sampling design is reduced sampling intensity on
individual wetlands. For the most part, sampling on individual wetlands will be limited
to one visit, during which we will and characterize wetland attributes. Phenology of
wetland vegetation is an important consideration when each site is visited only once
during a season. To alleviate problems of seasonal succession and identification of
immature grass and sedge dominants, sampling will be conducted from June 21
through August 15, 1993. Although some early flowering forbs may be missed, most
7
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Figure 1-4. Research strategy for evaluating the potential for indirect loss of wetland
function in the Portland metropolitan area due to level of project performance.
Objective 3: Evaluate the replacement potential of freshwater wetlands
to aid in the development of performance criteria.
Do projects replace the structure
and function of similar natural
wetlands, i.e., what is the replacement
potential?
Has the replacement potential
improved with time and experience?
Step 1: Compare structure and
function of projects representing
a range of ages to that of similar
natural wetlands as a measure of
performance.
Compare the data on performance of
pre-1987 projects with that of post-
1987 projects at the same stage of
development
Step 2: Investigate possible
differences in performance due
to age of project, land use sethng,
and presence of a vegetated
buffer.
8
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+
*
*
*
Figure 1-5. Research strategy for determining indirect loss of wetland function in the
Portland metropolitan area due to project design and implementation.
Objective 4: Evaluate how project design and implementation affect the
replacement potential of freshwater wetlands to aid in the development
of design guidelines.
How can information on project design and implementation be used to
improve performance?
How do project design
and as-built conditions
compare with structural
characteristics of
similar natural wetlands?
How do project design
specifications compare
with as-built conditions?
How has project design
and implementation
changed with time
and experience?
Step 1: Compare project
plans, permit conditions,
and as-built conditions
with the structural
characteristics of similar
natural wetlands.
Compare project plans
and permit conditions
with as-built conditions.
Compare project plans,
permit conditions, and
as-built conditions of
pre-1987 projects with
those of post-i 987
projects.
Step 2: Investigate
possible design
improvements suggested
by the structure of
natural wetlands of the
highest attainable
quality.
9
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plant species will be at peak biomass and in mature reproductive stages. Sampling as
closely as possible to peak growth will minimize variation in plant species cover due to
phenologicai differences. Field sampling will not include detailed delineation of
wetland boundaries or detailed characterization of soils or wetland hydrology at all the
study wetlands.
Because hydrology is central to the occurrence and persistence of wetlands,
and because prior research has documented the importance of hydrology in the
su’ccess of wetland projects (e.g., Erwin 1991), we are planning an intensive study of
hydrology on a subset of the study wetlands. The tentative design for this effort will
include installation and biweekly monitoring of staff gauges and piezometers at
approximately 40 wetlands, and continuous monitoring of water elevations at 3-4 pairs
of wetlands (e.g., adjacent natural wetlands with different land uses, or one natural
wetland and an adjacent project). Results of hydrologic monitoring will allow us to
evaluate differences in hydrology of wetlands related to differences in land use and
wetland origin (i.e., natural wetlands or projects). Comparison of data from
continuously monitored sites will provide an assessment of differences in 1) the short-
term dynamics in water stage associated with storm episodes, and 2) the relationship
between hydrologic forcing functions (e.g., changes in stage of an adjacent stream)
and wetland response. An analogous study is being planned to characterize and
compare rates of sediment accretion in wetlands with different land uses and origins.
This project will involve direct measurement (annually) of sediment deposited on
artificial marker horizons (e.g., DeLaune et al. 1983, Baumann et al. 1984, Frenkel
and Morlan 1920) placed at several locations per wetland in a subset of about 40
sites. Field studies of hydrology and sediment accretion will start in the summer of
1993; detailed study plans for these efforts will be described in separate plans that are
currently in preparation.
Study Area
The study sites are located in the Portland, Oregon, metropolitan area and are
restricted to portions of Clackamas, Multnomah, and Washington Counties that occur
within the Willamette Valley Plains subregion of the Willamette Valley ecoregion. The
Willamette Valley Plains subregion is a homogenous unit within the Willamette Valley
ecoregion defined by similar land use/cover, vegetation, soil and topography (Clarke et
al. 1991). . Limitation of sample sites to this subregion provides a restricted geographic
and physiographic area that includes a sufficient number of project and natural
wetlands in a variety of land use settings, and allows comparisons of wetlands in a
setting that minimizes confounding influences such as lithology, soils, and climate
differences (Omemik 1987). This area was chosen for study, in part, because rapid
development has placed wetlands at high risk for modification or destruction. Nearly
one-third of the Section 404 permits requiring compensatory mitigation issued in
Oregon from January 1977 through January 1987 involved wetlands in the Portland
Metropolitan area (Kentula et al. 1 992b). Extensive data exist for the Portland-metro
vicinity including Geographic Information System (GIS)-accessible land use maps and
data from intensive hydrologic monitoring. Such information can aid in research
design and data interpretation. Other data for the area come from the 1987 Oregon
10
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Pilot Study which affords an opportunity to revisit and evaluate the continued
development of previously sampled projects and the status of the previously sampled
natural wetlands. The location of the study area is
sufficiently close to 1) the USEPA Environmental Research Laboratory-Corvallis (ERL-
C) to permit project staff at the laboratory to be integral participants in field studies; 2)
a large population of teacher volunteers who will be involved in field sampling: and 3)
the facilities at Portland State University (PSU) which will be used for training of field
crews and processing of samples.
Site Selection
Specific criteria were used to define populations of natural wetlands and
wetland projects in the Portland metropolitan area. The populations represent a
gradient from sites dominated by open water to those dominated by emergent
vegetation. Most sites are <2ha in area. All natural wetlands and projects in the
Portland area meeting these criteria were considered for study. This included 10
natural wetlands and 11 projects sampled in 1987 and all mitigation projects required
in Section 404 permits and/or Oregon State Removal-Fill Permits since 1977.
Comparisons of these populations of natural wetlands and projects will be used to
address study questions 4, 5, and 6 (Table 1-1).
The most current National Wetland Inventory (NWI) maps were used to identify
all natural wetlands of the appropriate size and type that occurred in the study area.
This population was then stratified by land use categories defined on METRO
(Portland Metropolitan Service District) maps. Characterizations of this stratified
population of natural wetlands will be used to address study question 3 (Table 1-1).
All natural wetlands and projects from the NWI maps and permit records were
visited during field reconnaissance to verify that they existed, were of the appropriate
size and type, and were safe to sample. This resulted in a list comprising the entire
populations of both natural wetlands (111 sites) and projects (51 sites) occurring in the
study area and meeting site selection criteria. In addition, during the visits, each site
was sketched and photographed, and surrounding land use documented. The results
of this inventory will be used to address study questions 1 and 2 (Table 1-1).
The last step will be to secure access to all sites meeting the selection criteria.
Considering that access to some wetlands may be denied, the final number of sites to
be sampled will likely be less than the total number identified.
Wetland Characterization
Variables used to characterize wetlands sampled in the OWS were selected to
provide data that describe the structural and functional features of wetlands, and that
facilitate assessments of ecological condition and permit compliance. Table 1-2
provides a summary of the variables and the information they are expected to
generate, and Table 1-3 provides sources for existing data used in the study.
Structural features (vegetation, soils, hydrology, wetland morphology, etc.) are
used to characterize the current conditions and attributes of the sampled wetlands,
11
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Table 1-i. Summary of study questions and research approaches for the Oregon Wetlands Study.
1. What are the short term trends in wetland loss due to conversion?
• Compare the most recent National Wetland Inventory data with the results of the inventory
from the field reconnaissance.
2. What are the principle reasons (e.g., land uses) for wetland losses due to conversion?
• Document reasons for wetland conversion identified in the course of conducting the
inventory during the field reconnaissance.
3. What is the relative attainable quality of wetlands in different land uses, and how are
differences in quality reflected in wetland structure and function?
• Step 1 - Quantify and compare wetland structure and function by land use category.
• Step 2 - Rank the land uses according to the relative quality of the wetlands.
• Step 3 - Explore whether vegetated buffers ameliorate effects of land use.
4. Do projects replace the structure or function of similar natural wetlands, i.e. what is the
replacement potential?
• Step 1 - Compare structure and function in projects representing a range of ages to that of
similar natural wetlands as a measure of performance.
• Step 2 - Investigate possible differences in performance due to age of the project
and land use setting, and presence of a vegetated buffer.
5. Has replacement potential improved with time and experience?
• Compare the data on performance of pre-1987 projects with that of post-i 987 projects at
the same stage of development
6. How can information on project design and implementation be used to improve performance?
6a. How do project design and as-built conditions compare with structural characteristics
of similar natural wetlands?
• Step 1 - Compare project plans, permit conditions, and as-built conditions with the
structural characteristics of similar natural wetlands.
• Step 2 - Investigate possible design improvements suggested by the structure of natural
wetlands of the highest attainable quality.
6b. HoW do project design specifications compare with as-built conditions?
• Compare project plans and permit conditions with as-built conditions.
6c. How has project design and implementation changed with time and experience?
• Compare project plans, permit conditions, and as-built conditions for pre-1987 projects with
those of post-1987 projects.
12
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Table 1-2. Ust of variables to be sampled in the Oregon Wetlands Study. Numbers in
parentheses associated with variable uses refer to the study questions and research
approaches summarized in Table 1-1. Primary use of variable in answering a question
is indicated by bolded numbers; secondary use, by italicized numbers.
VARIABLES - ALL
SITES
RATIONALE FOR
INCLUSION
USES IN WETLAND
CHARACTERIZATION
AND COMPARISON
General
Location
Identifies site on local
map
Confirm site as part of
population of interest,
provide route information
for sampling
Wetland Type
Documents general
overall structure
Compare with project
goals and NWI
classification (1, 6b)
St?ucture
% bare ground
% vegetajion (trees,
shrubs, herbs)
% Open Water
(unvegetated and with
submerged aquatic
vegetation)
Describes distribution of
unvegetated land, reflects
site age and condition
Describes distribution of
vegetation, determines
wetland type
Reflects hydrology,
determines wetland type
Characterize site and
provide general
descriptive information
related to temporal
development, and
surrounding land use (3,
4, 6a, 6b)
Surrounding Land Use
Influences inputs to
wetlands (e.g., nonpoint
source pollution, industriai
outfalls, recreational use,
source of propagules,
wildlife corridors, etc.)
Relate wetland
performance to
surrounding land use (2,
3, 4, 5)
Buffer Type/Extent
Provides a barrier to and
amelioration of off-site
inputs (e.g., industrial or
agricultural run-oft) and
mediates the effects of
noise, foot traffic,
disturbance, etc., provides
habitat pathways for
animal movement
Explore the effect of
vegetated buffers of
different types (e.g.,
herbaceous, shrub, trees)
and widths on
ameliorating the effects of
land use and in
determining project
success (3, 4,
13
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VARIABLES - ALL
SITES
RATIONALE FOR
INCLUSION
USES IN WETLAND
CHARACTERIZATION
AND COMPARISON
Presence of Obvious
Stressors or Disturbance
Documents potential
causes of the erosion of
wetland quality
Document presence of
degraded landscape or
damaging influences to
aid in explaining effects
of land use and in
understanding outlier
sites (3, 4)
Morphology
Area
Influences habitat value,
plant community diversity,
and flood storage
Compare projects to
project construction
specifications (6)
Slope/Elevation
Influences hydrologic
gradient, vegetation
establishment and
distribution, animal
access, etc.
,
Determine minimum,
maximum, and mean
depth and slopes from
topographic profiles of
each site. Compare basin
morphologies of project
and natural wetlands (4,
5,6)
Perimeter: Area Ratio
Influences edge effect
(e.g., introductions of
exotic species and
extinction of native taxa),
habitat size and quality
.
Compare amount of edge
in projects to natural
wetlands, and document
variation in project
shape/edge over time
through analysis of map
data on project and
natural wetlands sampled
in both 1987 & 1993 (4,
5,6)
Vegetation
Species Usts -
Identification
Defines wetland type,
habitat, and plant diversity
Compare species corn-
position between natural
and project wetlands.
Compare speci&s found
on completed project with
project planting or
seeding lists (4, 6)
14
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VARIABLES - ALL
SITES
RATIONALE FOR
INCLUSION
USES IN WETLAND
CHARACTERIZATION
AND COMPARISON
Species Abundance
Provides information on
vegetation structure and
composition via species
richness, diversity,
dominance, community
type, ratios of native:
exotic taxa; ratios of
wetland:upland taxa
Describe and compare
project and natural
wetlands, relate
vegetation to
environmental or
disturbance gradients,
relate distribution and
abundance of individual
species with hydrology,
elevation, and soils (3, 4,
5,6)
Soils
Soil Color
Indicates hydric soil
characteristics such as
gleying, mottling, root
oxidation channels, etc.
Used for delineating
wetland boundary, tracing
project development over
time, identifying
relationships of soil
conditions to elevation
and plant distribution (3,
4,5,6)
Presence of Hydrogen
Sulfide
Indication of hydric soil,
i.e., strongly reducing
conditions
See color (3, 4, 5, 6)
Rough Description of Soil
Horizons
Characterized soil profiles
and development
Characterize wetland
soils in different land use
settings. Evaluate
differences between
project and natural
wetland soils (3, 4, 5, 6)
Soil Amendments (e.g.,
substrates salvaged from
destroyed wetlands)
Provides baseline
information about projects,
influences soil
development and
chemistry, and vegetation
establishment
Evaluate relationship of
project performance and
rate of development to
use of amendments. (4,
5, 6)
15
-------
VARIABLES - ALL
SITES
RATIONALE FOR
INCLUSION
USES IN WETLAND
CHARACTERIZATION
AND COMPARISON
Soil Organic Matter
Indicates suitabiIity as a
planting medium,
conditions of soil
processes and chemistry
Compare projects to
natural wetlands.
Document temporal
change in organic matter
levels (3, 4, 5, 6) by
comparing data from
wetlands sampled in both
1987 & 1993
Hydrology
Water Depth Site:
- to saturated soil
- of standing water
Influences which portions
of the site are wetland,
vegetation patterns,
wildlife and fisheries
habitat
Compare project and
natural wetlands. Look
for relationships between
water levels and plant
species composition and
abundance, soil
conditions (3, 4, 5, 6)
Flow Pattern
Influences plant
establishment, plant
produclivity, substrate
stability and chemistry
Compare flow patterns in
project vs. natural
wetlands (3, 4, 5, 6)
16
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Table 1-3. Existing data used in the Oregon Wetlands Study.
f Data Type
Source of Data
Data Transfer
Use of Data
Wetland type,
USFWS NWI’
Maps - sent
Site Selection and
location
maps
through mail
trends study
Section 404 permit
ODSL 2 permit files,
Data collected at
Site Selection and
information
COE 3 permit files,
ODSL, COE and
compliance study
includes:
and construction
construction
wetland type
contractors’ files
contractors’ offices
wetland size
slopes
location
plant species
to be planted
buffer type
buffer width
Land use
METRO 4
Maps obtained at
METRO office
Site Selection
‘U.S. Fish and Wildlife Service, National Wetlands Inventory
2 Oregon Division of State Lands
3 U.S. Army Corps of Engineers
4 Portland Metropolitan Service District
17
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providing a basis for the comparisons required to answer the study questions.
Function will be evaluated on a limited scale by using various aspects of structure as
indicators of function. Relationships between structure and function are assumed,
although the precise nature of these relationships is not well documented (Adamus
and Stockwell 1983, D’Avanzo 1986, Kentula et al. 1992a). Indicators of function are
variables whose presence reflects the existence and/or level of specific wetland
functions. For example, the presence of certain plant species might reflect wetland
functions of sediment trapping, shoreline anchoring, and wildlife habitat. Using
indicators rather than making direct measurements of functions is appropriate because
measures of wetland structure are generally more easily obtained in terms of time and
cost, and frequently result in less damage to the wetland. Additionally, some typical
measures of structure become measures of function when tracked over time. As an
example, plant diversity when measured once describes a componerit of vegetation
structure, when measured over time it describes a function--maintenance of a given
level of diversity. Although, each site will only be visited once, some comparisons
over time are possible because data exists for a subset of projects sampled in 1987
and it is anticipated that groups of similar projects will occur over a range of ages.
Sampling activities are briefly discussed below. Detailed rationales for the
selection of a variable and the associated field methodologies are presented in the
remainder of this research plan. Quality assurance procedures are presented in the
Quality Assurance Project Plan: Oregon Wetlands Study currently in preparation.
Each wetland will be mapped to provide a spatial representation of site
conditions and attributes at the time of sampling. This record will be useful for
interpreting results during data analysis and for identifying changes in a site over time.
Mapping will document and describe 1) wetland size and shape; 2) adjacent land
uses; 3) general distribution of vegetation and open water; and 4) location and
characteristics (e.g., width, vegetation type) of vegetated buffers, surface water
inlets/outlets, and anthropogenic structures such as water control devices, nearby
ditches, or pavement.
Actual land use within an approximately 100-rn perimeter surrounding each
wetland will be compared to land use data collected during the site selection
reconnaissance to ensure the conditions have not substantially changed since the
earlier visit Also, general data will be collected for use in association with the site
map. These include: 1) estimates of percent open water on the site; 2) percent cover
of herbs, shrubs, and trees both within the wetland and in an approximately 100-rn
perimeter outside the wetland boundary; 3) percent of the wetland disturbed and
nature of perturbation; 4) descriptions of general water flow patterns; and 5)
ide tiflcation of stressors such as industrial run-off, presence of livestock, evidence of
use by off-road vehicles, etc.
Photo points will be established at each site to provide a visual documentation
of site characteristics for qualitative comparisons to other sites and to future conditions
of the same site. Locations and directions of photo points will be recorded on the site
map.
The presence, nature, and extent of vegetated buffers will be explored by
documenting the occurrence, width, and type (herb, shrub, tree) of any vegetated
buffer present. Buffers will be sampled along four transect lines extending lOOm from
the wetland edges into the upland area surrounding the wetland.
18
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The basin shape will be characterized along a grid system composed of six
systematically placed transects. Elevations relative to the lowest measureable point
within the wetland will be measured at standard intervals along all six transects.
Herb, shrub, and tree components of the wetland vegetation will be evaluated in
terms of species composition and abundance. Sampling will be conducted along at
least five transects placed systematically to encompass obvious controlling gradients
(e.g., water depth or elevation) in the wetland. Canopy coverage values for
herbaceous species will be estimated within 1 -m 2 plots (quadrats) placed
systematically along the transects. Shrub species cover values will be obtained along
the length of each transect using line-intercept methods. Tree species abundance will
be evaluated by determining basal area of all individuals occurring within a 2-rn wide
belt centered on each of the transects.
Specie abundance data will provide information about species richness,
composition (e.g., ratios of native:exotic or wetland:upland species), diversity,
community structure, and wetland boundaries. Species abundance data will also be
helpful in assessing the relationships of species, or communities, to environmental
variables by using the species and environmental data in correlation or ordination
analyses.
Soils will be evaluated for a randomly selected subsample of the 1-rn 2 plots
along the systematically placed transects. Soil samples will be obtained from each
plot at two depths (0-5cm and 15-20cm) for laboratory analysis of organic matter
content (%). A partial profile characterization will be provided by examining the soil,
from 0-50cm deep to 1) identify Munsell color of soil matrix and mottles; 2) check for
the presence of oxidation channels around roots, hydrogen sulfide, and other hydric
soil indicators: 3) locate any obvious horizon breaks and general textural changes; and
4) note the presence of any soil amendments.
Hydrology data will be collected in association with both elevation
determinations and soil sampling. At each sampling point, the depth of standing water
or occurrence of saturated soils (if present) at the ground surface will be noted. In
addition, at each soil sampling plot, the depth of standing water or depth to standing
water (if occurring at a depth of 50 cm or less), the depth to saturated soil, and depth
of the free water surface will be recorded.
TIMELINES AND IMPLEMENTATION
Primary implementation of the study will be carried out by staff of ERL-C, in
particular from the on-site contractor (currently ManTech Environmental Technology,
Inc.). In addition, ERL-C has established a cooperative agreement with PSU to
support summer 1993 field sampling activities. As part of an environmental education
program for teachers, PSU staff have developed a program in which teachers will be
trained in field sampling and laboratory analysis techniques, then participate in field
work for the, program.
Initial planning, data collection and site reconnaissance for the OWS began in
1991. Site selection is close to completion. Field measurements, laboratory analyses,
data entry, data analysis and interpretation, and reporting of results will be conducted
over the next year. The schedule for completion of major components of the OWS is
listed in Table 1-4.
19
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Table 1-4. Schedule of key events in the Oregon Wetlands Study.
Winter 93
Complete landowner contacts to obtain permission
for access to sites for sampling.
Winter 93
Complete Quality Assurance Project Plan:
Oregon Wetlands Study to accompany this Study
Plan.
Winter 93
Select Field Crews and finalize training plans.
Spring 93
Train Field Crews.
Summer 93
Conduct field and laboratory work; Begin data
entry.
Fall 93
Complete data entry and verification.
Winter 94-Summer 94
Perform data analysis and report on preliminary
findings.
Winter 95
Report results in EPA documents and scientific
papers.
20
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2. SITE SELECTION
Site selection for the OWS involved a two-step process. First, it was necessary
to identify the kinds of wetland projects that have been constructed in the study area
and define the population of projects to be sampled. Second, the population of natural
wetlands to be sampled was defined based on correspondence with the most common
wetland types for projects. Once the populations of wetlands were identified, field
reconnaissance of potential sites for sampling was conducted to ensure sites met
selection criteria. All natural wetlands and projects meeting the site selection criteria
for which acccess was obtained will be sampled.
DEFINING THE POPULATION OF PROJECTS
Criteria for inclusion of wetland projects in the study population were: 1)
location of the project in the study area (the Portland Metropolitan area within the
Willamette Valley Plains subregion of the Willamette Valley ecoregion [ Omernik 1987,
Clarke et al. 19911); 2) wetland type (freshwater wetlands that range from sites
dominated by open water to those dominated by emergent vegetation); and 3) wetland
size ( 2ha). Refer to the Study Overview for details on study area selection and
description. Wetland type and size criteria are discussed below.
A list of Section 404 permits requiring compensatory mitigation was obtained
from the Oregon Division of State Lands (ODSL), the state agency responsible for
wetlands permitting, to identify potential projects for sampling. Data were compiled
from permits issued between January 1987 and January 1991 by transferring the
information from the files at ODSL to a permit tracking form (Figure 2-1). The
numbers of freshwater mitigation projects identified from the permits are listed by size
and type in Table 2-1. The wetland types considered are freshwater wetlands that
range from sites dominated by open water to those dominated by emergent
vegetation. These types were selected because they represent the most common
freshwater mitigation projects and natural wetlands found across a mosaic of land use
settings in the study area. This provides an opportunity for: 1) comparing natural
wetlands and wetland projects and 2) assessing land use influences on the level of
wetland function.
The selection of wetland type for this study does not imply an endorsement of
ponds as wetland projects. In fact, few natural ponds exist in the study area (Kentula
et al. 1992b). Adoption of the wetland type criterion for study was driven by the kind
of project available and the best natural analogs in the study area, i.e., we designed
our study to evaluate what exists. We believe that the primary considerations for
making management decisions about the type of a proposed project are the relative
rarity of wetland types and the need for wetland functions to be replaced. Project
design and type should not be based solely on what is most convenient because of
land availability or project cost (Kentula et al. 1 992a). Further, the ecological
ramifications of replacing impacted wetlands with wetlands of different types are
unknown (Kentula et al. 1992a), so reason suggests that we exercise caution and do
our best to establish types that occur naturally in the area.
21
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Table 2-1.
TOTALS
Numbers of the freshwater mitigation projects in Portland, Oregon, by wetland type
and size required in permits issued by the U.S. Army Corps of Engineers and the
Oregon Division of State Lands from January 1987 through January 1991. ?
indicates area unknown.
SIZE (Acres)
0-2 2-4 4-6 6-8 8-10 >10 ?
58 11 3 0 2 2 31
TYPE
TOTALS
Marsh
9
5
0
0
0
0
2
Pond
24
0
1
0
1
1
12
Marsh and Pond
4
1
0
0
0
0
3
Marsh and Shrub-scrub
2
2
1
0
0
0
1
Marsh and Forested
0
0
0
0
0
0
1
Marsh, Shrub-scrub, and Forested
1
0
0
0
0
0
0
Marsh, Pond, Shrub-scrub, and Forested
0
1
0
0
1
1
0
Marsh, Pond, Aquatic Bed, and Forested
0
1
0
0
0
0
0
Marsh, Pond, and Flooded Grassland
0
0
1
0
0
0
0
Pond, and Riparian
10
0
0
0
0
0
0
Pond, Forested, and Stream Channel
1
0
0
0
0
0
0
Riverine Wetland
0
1
0
0
0
0
0
Stream Channel
1
0
0
0
0
0
2
Creek Bank
1
0
0
0
0
0
0
100-year Floodplain
1
0
0
0
0
0
0
MudFlat
1
0
0
0
0
0
0
No Wetland Type Specified -
3
0
0
0
0
0
10
16
39
8
6
1
1
3
1
1
10
1
1
3
1
1
1
13
107
22
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Stat. — County
Stat. — County
Townsh & Range
thude&onghu
USGSR4 n name______
sese c t q Wate#rWer body narrie
Wu the inhlgatlon project Off she orOn.slte?
o AgrIcultural
o CommercIal
o kidustrlal
o Natural
o ResidentIal
Doairrants available-
S.lect(O-4J
Date construction began
o Maps
o BlueprInts
o Ground photos
o Aer Ial photos
/ I
Date construction con Ieted Ij,.
Were rSdane correctIons made? Yes / No
(Make notes hi comments section)
Milgatlon type-Sele/a(1J
o created 0 Enhanced 0 Preserved 0 Restored
ES1UARD4E RIVERINE RIVERINE (coot)
o sLit openntr 0 idalbndwb - 0 tximownpersnSs beedvb
o sitidS rodi born 0 $45 IS ____ 0 tflmown pemnrS opens
o bSridSaqrScbed 0 lodibotre 0 tflmownpersniilsrodtythor.
o hibrit emergent 0 $45 fleSbed 0 tflmrn perenriel tecre o tdeted born
fl Si t*ki flW1naEMaflaret s 1M äEIv1Sut S4seOtcre
o hk$45 bend ____ 0 $45 teiocnot Sed Store ___
W d Yee LSa t _________ PAUJSTR INE
o flsr$dS rod Store ____ 0’ pareivi t e SSvbs ____
s < — —
o hk$45 awted ____ 0 best parewrld let ___ 0 emergerd
o besrpeie.vi krodibo i drn ___ 0 basted
LAOJSTRR4E — —
o beer perervilS neanbed ____ 0 open eas
eS&# t e àn utontoo MiIi j Dam
o Ionic O Si S ____ 0 beer peiwedS tmoaieoldsd s Ine , 0 em.. isit
Q nkroSbotmç4 born —
o Ionic wiocreoldated torn perenriS tesdifter 0 tecreoldated sine
O l*$sflltbed MARINE
o leerS bndwber — 0 ispe perem$S open wflr
o IRIS IS ____ 0 per pererdSrodtyehore . . 0 etLitopsiesler
b lat - -
0 IRIS md c born 0. tçper pererriS wnneoldsted booom 0 stti45 toot born
o ISSrOckyshore O s&SdS unotneoldad born
o leeS imocreoldeted born 0 hitennISet spat bed - 0 hiueildS mtadc bed
0 bRImbe rdlet , 0 hk$45 let
0 MW I4MINt
o heemluerl root torn -,,, 0 hk$45 rocky shore
bt k l 3 il II flSIlflK 0 IntoridS ttoocn$Oldaled shore
o hrerm losr i steented
• —.—
Figure 2-1. An example of a form that can be used to Compile information on wetlands projects
(Holland and Kentuta 1990).
COE permit number
State permit number________
Date permit issued _I_J_
- Permit Tracking System
COMPENSATORY WETLAND DATA FORM
Form designed by CC. Holland and 1W. Gbson
ManTech Environmental Technology, kit,
U.S. Environmental Protection Agency,
Environmental Research Laboratory
200 SW 35th Street
Corvallis, OR 91333
— Mres,_
— Mres_,_
TOTAL,,,,,,,,,,,J__
SeeM __
23
-------
I i
The
Authors First IMlal Middle Initial last Name
Year________ Source____________
Conieni
First kiIUal_ Middle Inklal Last Name
Oiganlzatlon
Addmss
C v
State____ ________ Phone( _________
First Initial Middle Initial
Or anlzatbn__________
Mdrsu
City
Last Name
State Z Phone ( ____
R k dal Middle In a Last Name
Oiga tzatbn____________________
Add ss__
Omanl aflôn -
State___ ______ Phone( _______
City_______________ State___ Phon.(
Ob e ve:
Method:
As-built:
--_
Figure 2-1. (cont.)
Middle Inllal___ Last Name
24
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All of the projects meeting the wetland type criterion were visited during
Summer 1991 and Spring 1992. Access to the projects was granted by the ODSL
and, as a courtesy, most of the project supervisors (e.g. land owners or property
managers) were contacted to set up a convenient time to visit the site. During each
site visit, directions to the site and general site information were recorded (Figure 2-2)
and the site was photographed. Figure 2-3 is a typical wetland project visited during
site selection. Evaluation of reconnaissance information revealed that the most
common project size was 2ha (approximately 5 acres). Thus, the second criterion
for site selection was defined as wetlands < 2ha in size. Projects were rejected if: 1)
they were not constructed; 2) they did not meet the wetland type or size criteria; 3)
conditions at the site were hazardous; or 4) project construction confounded the ability
to sample the site (e.g., soils were underlain by plastic sheeting).
DEFINING AND SAMPLING THE POPULATION OF NATURAL WETLANDS
The population of natural wetlands was defined in terms of the population of
project wetlands. Selection criteria for natural wetlands were: 1) freshwater wetlands
that range from sites dominated by open water to those dominated by emergent
vegetation; 2) size 2ha; and 3) location in the study area. Figure 2-4 is an example
of a natural wetland being considered for study.
Locating Natural Wetlands
Land use is a major consideration in the OWS because data from the Oregon
Pilot Study suggested wetlands in different land uses within an urban setting exhibit
varying levels of function. It is important to document these differences to gain
information about attainable quality for wetlands within specific land uses. The
pool of natural wetlands potentially meeting the selection criteria was identified using a
procedure adapted from Abbruzzese et al. (1988). A color-coded map depicting the
five land use categories—undeveloped, commercial, industrial, agricultural, and
residential was created for the OWS by MEmO.
The land use map was overlain with NWI digital data for wetland types and
sizes appropriate to the OWS (Table 2-2). The study area was delineated by placing
overlays of the boundaries of the Wiilamette Valley Plains’ subregion on the land use
map. The 615 wetlands occurring within the study area were labeled, and surrounding
land use was identified from the map and recorded. Sites with NWI special modifiers
(e.g., partially drained/ditched, dikectrimpounded, artificial, spoil, excavated) were
dropped from consideration because they were not natural wetlands. In addition,
reconnaissance visits to the sites revealed the entire population of natural wetlands
could be censused, because a large proportion of the sites were destroyed or altered
by human activity.
25
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Table 2-2. National Wetlands Inventory (NWI) wetland types included in site selection
of natural wetlands for the Oregon Wetlands Study.
NWI wetland types included in the Oregon Wetlands Study
Palustrine aquatic bed
Palustrine emergent wetland
Palustnne moss/lichen
Palustnne open water
Palustnne rock bottom
Palustrine unconsolidated bottom
Palustrine unconsolidated shore
26
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FORM I GENERAL SItE INFORMAflON
Date
SITE NAME/CODE 5o .5 rosberg STATE Of COUNTY CI cMo mO
WETLAND TYPE PLt1
PERSONNEL NAME f-jo//o.nd/pr-o i-hoJrr,
A. Describe ease of access to and within the site (roads, parking, problems due to water depth.
etc.).
Ea 1y ce55ib1e. In f o ir79deLek’pn,eJ1- _ co.n p&r f aryi . ihe.re..
B. Provide directions to site. Attach a marked copy of a map if needed.
i+. ToJ e co.rn)en Rd t. T .j ri r, qhton CL fn PJ Rd C o Eo t). fl&rn Ie(t on Si.)
Me do rLLffl ri on -w r frito kJ ’5//aJ e Dr *hen
r, 1- on say Crec.li or: Wet Ic*r i i . rich 1 ( E oF 8Ay Cree)c/
C Document check of ownership of site. Was the owner contacted? ‘No
Was trespass permission granted? j ’No
Figure 2-2. An example of a completed form that can be used during field reconnaissance to collect
information on potential study sites.
D. Sketch the wetland below. Include information on ‘he factors influencing hydrology (e.g., water
control structures, ditching). Sketch in the landuses and natural cover on the wetland and in
the surrounding area (use categories listed on page 2). Indicate north.
l.4ous(r 3 - sin 1e ftAm Ifj
27
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FORM I: GENERAL SflE INFORMATION Page 2
Indicate % open water, % vegetated and % non-vegetated areas within the wetland (A-C
should add up to 100%)
A. 80 % open water
1. 5 % unvegetated
2. .5 % with submerged aquatic vegetation
B. 15 % vegetated
1. 0 %trees
a 0 % shrubs (15 feet or less)
3. 15 % herbs
C. 5 % unvegetated
TOTAL 100%
Indicate % relative cover of surrounding areas within 100 meters of the wetland
boundaries (A-E should add up to 100%):
A. ic’ %trees
B. 1 %shrubs
C. 8 % natural herbaceous vegetation
0. 0 % water body-specify type:___________________________
E. 80 % human landuse
1.__0%crops
a__O%faHow
3. p % grazing
4. 0 % industrial—specify type:____________________
5. 0 % commercial
6. 5 % transportation corridor
7. 5 % housing—single family dwellings
8. 0 % housing—muttiple family dwellings
TOTAL 100% **NOTh: 1-8 should total the percentage value in E.
Ill. Indicate % of wetland which is disturbed and describe the disturbance (for example,
ditches, water control structures, dumping, fill, and anything that might be hazardous):
5°I d 5 ktrbed - pla51-(c a.r ho i boie
3 plpe5
5orne. 5+oile5 tecf on sife.
IV. Comments:
V n 4 -erj u5’r 3 s ifr .
Figure 2-2. (cont.)
28
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4•4 . .4 ,
.4 -
I’ 1I
I.
-: s
4 ,.
N.)
Figure 2—3. An example of a typical wetland project visited during site selection.
-------
— P” Jr
I
r
Figure 2—4.
An example of a natural wetland tn Oregon.
-------
Field Reconnaissance of Natural Wetlands
Preparation for field reconnaissance of natural wetlands and securing
permission to sample consisted of:
1. The locations of sites identified on the land use map were transferred to an
NWI composite map and a current Portland Street atlas, for convenience in
locating the sites.
2. A route to each site was determined and approximate geographic coordinates
(latitudes and longitudes) were determined for each site. A hand-held, battery:
powered navigation system (a Trimble Global Positioning System [ GPS],
Transpak II unit) that receives data from U.S. Department of Defense satellites
and calculates and displays position, velocity, time, and navigational information
(Trimble Navigational Umited 1991) was used to locate each site. The
geographic coordinates were entered into the unit which then displayed the
distance and bearing to the site. After physically locating the site, the exact
geographic position was entered into the GPS for future field reference. The
GPS unit was extremely useful in site location, enabling us to find sites initially
believed to be destroyed because of the difficulty in translating mapped
information to exact locations on the ground.
3. We met with Portland area professionals who were able to provide information
about ownership of public and private properties, and to identify individuals to
contact for access and sampling permission. Permission was obtained to
sample the sites located on land owned or controlled by the agencies
represented by these professionals. For sites on privately held land, an attempt
was made to determine ownership by checking information on mail boxes and
real estate signs, and interviewing local residents. After ownership was
determined, the owner was contacted and given a copy of a letter (Figure 2-5)
explaining the study. Using this procedure, permission to sample was secured
from 40% of property owners.
Reconnaissance data was collected and site selection criteria were assessed
for each wetland:
General site information was collected for each wetland on Form I (Figure 2-2).
Observations were made at each site which were used to determine the
approximate proportion of land cover types within the wetland and land uses
directly surrounding the wetland. Also, a rough map of each site was sketched.
2. Each site was evaluated to see if it fit the criteria outlined for natural sites. A
site was eliminated during the selection process if: 1) type or size were
incorrect; 2) the wetland was destroyed; 3) conditions on or near the site would
make sampling hazardous (e.g., garbage being dumped); 4) the site was
altered substantially by human activities (e.g., grazing) or natural phenomena
(e.g., drought); or 5) access was denied by the land owner.
31
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Sr 41 ,
UNITED STATES ENVIRONMENTAL PROTECTION AGENCY
ENVIRONMENTAL RESEARCH LABORATORY
200 S W 35TH STREET
CORVALLIS. OREGON 97333
May 27, 1992
Dear landowner
U S Environmental Protection Agency’s (EPA) Wetlands Research Program is requesting your assistance in a
research project being initiated in the Portland Metropolitan Area. In recent years, humans have attempted to
create wetlands to replace those destroyed in the process of development. It is still undoer how effectively
these created wetlands are replacing the ecological functions of naturally-occurring wetlands. To find out how
these created wetlands compare to natural sites, the EPA is looking at a number of created and naturally-
occurring wetlands in the area. Your property may contain a naturally-occurring wetland that we would like to
include in our study. This would require allowing us on your property today to photograph and record some basic
features of the wetland (e g., wetland type and size, percent open water and vegetation, and surrounding land
uses)
It the wetland on your property is the type and size selected for our study, a field crew would return to the site
next summer (1993) for sampling They should not be on your property for more than half a day. We will notify
you of the exact day of the sampling as soon as we determine the final schedule. The field crew (consisting
of 7 people) will set up temporary markers (wooden stakes), record tl e elevation of the site with a transit, and
take notes on the vegetation. The field crew will dig no more than ten holes, uf deeper than 18 inches, to take
a soil sample. These samples will be scattered over the site. The field crew will remove the stakes and fill
in the holes after they are finished
It is, of course, totally up to you whether you will permit us to visit the wetland on your property. We hope
you will choose to assist us in this important project. Since we are only interested in the summary statistics
for the wetlands, information from your wetland will be combined with that of other similar wetlands. All
wetlands will be given a code name. Your name and property will not be specifically mentioned in the published
results If you wish, we can add your name to a list of people who receive information on the Wetlands
Research Program. The results of the study can also be sent to you when they are available; this should be
approximately two years after the sampling is complete. Simply inform the bearer of this letter, a member of
the field crew, or me of your desire for this information.
Thank you in advance for your consideration and cooperation in this matter. If you have any questions or
concerns, please feel free to call me at (503) 754-4478.
Sincerely,
Mar1. E ” entula, Program Leader
Wetlands Research Program
Figure 2-5. The letter given to landowners during site selection explaining the Oregon Wetlands
Study.
32
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3. OVERVIEW OF FIELD ACTIVITIES
Each Field Crew will consist of eight people: the Crew Leader, two Botanists,
two Recorders, and three Surveyors. The field crew is divided into three teams; two
Vegetation Teams, each made up of one Botanist and one Recorder, and the Survey
team, made up of three Surveyors. Figure 3-1 shows team member responsibilities
and the order in which tasks will be completed.
The Crew Leader is responsible for ensuring that all aspects of the sampling
are conducted properly and completely. The Crew Leader, with input from other crew
members, determines the wetland boundaries, the location and orientation of the
transect baseline, and the sampling transect starting points. The Crew Leader
photographs the site, ensures there is an adequate supply of data forms and that all
are filled out completely and accurately, ensures all samples are collected and stored
properly, and keeps a diary of field activities. Finally, the Crew Leader is responsible
for resolving questions or problems that arise in the field, filling in to assist other crew
members wherever necessary, and ensuring the safety of all crew members.
The Vegetation Teams are responsible for sampling vegetation and collecting
and preserving voucher specimens. The Survey Teams are responsible for mapping
the site, measuring relative elevations and collecting soil samples.
CREW MEMBER EXPERTISE
Project personnel must meet minimum education and experience qualifications.
The positions and their requirements are:
1. Crew Leaders: These individuals are responsible for managing the crews in the
field and for making onsite decisions regarding the execution of procedures.
Therefore, the Crew Leader must have thorough understanding of the goals of
the study, all sampling procedures, and some knowledge of plant taxonomy and
experience in identification of wetland plants. In addition, the Crew Leader
must possess good leadership and interpersonal skills, and be able to keep the
crews productive and cooperative.
2. Botanists: Accurate plant species identification is of primary importance to the
quality of data collected. Therefore, Botanists must, at minimum, demonstrate
ability in sight recognition of common wetland taxa, that is, must be capable of
recognizing dominant species to the level of genus and species, provided that
plants are at the proper phenological stage. The Botanist must also be familiar
with local flonstic references, show proficiency in the use of diagnostic keys,
and have experience with proper techniques for collection and preservation of
plant specimens. A competency test will be included at the end of training.
33
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Crew Leader & Botanists:
Surveyors & Recorders:
1
Crew Leader
•
Determines Transect
starting points
.
Photograph’s study site
Figure 3-1. Flowchart of field crew member responsibilities and tasks. A Field Crew
consists of a Crew Leader, two Vegetation Teams (each composed of a
Botanist and Recorder) and one Survey Team (composed of 3 Surveyors).
• Determine wetland perimeter
• Determine baseline location
• Organize and distribute
equipment and data forms
Vegetation Teams
• Recorders establish
transect starting points
• Botanists conduct
vegetation reconnaissance
• Vegetation Teams conduct
vegetation sampling
Survey Team
• Maps the site
*
• Assist in placement
of additional
transects for
sampling vegetation
if needed
• Determine if
additional transects
are necessary for
vegetation sampling
• Determine locations
of additional
transects
• Sample vegetation
• Assist crew members
when necessary.
• Resolve problems
• Measure elevations
and water depths,
record open water,
bare ground or
vegtated and collect
soil samples along
appropriate transects.
1
• Check all data forms
for completeness
and legibility; organize
forms into Site Packet
• Make entries into field
diary.
• Ensure study site is
left in good condition
and that all equipment
is returned to vehicle.
• Botanists collect and
preserve voucher
specimens. Key out
unknown species and
agree on pseudonyms .
• Recorders and
Surveyors gather
samples.
• Organize and
replace in vehicle.
• Assist Botanists with
plant preservation.
• Check supply of data
forms for next site .
34
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3. Recorders: These crew members provide support for the Botanists, and when
needed, for the Surveyors. Attention to detail, willingness to follow strict
procedures, and industry are required. Recorders should be self-motivated and
willing to “pitch-in” where needed. Botanical and Survey skills are desirable.
4. Surveyors: Skills in elementary surveying, mapping, and soil sampling
techniques are needed for these team members. Training will be provided in
these techniques, and a competency test will be given at the end of training.
GENERAL ORDER OF TASKS
Each numbered point represents a group of tasks that will be done
simultaneously by different sampling teams and crew members.
The Crew Leader will select one wetland or two in close proximity for sampling
each day. A site packet will have been prepared for each site that contains the
Street address (if applicable) and directions to each site, as well as identifying
photographs. All crew members will congregate at a predetermined meeting
point. From there, the Crew Leader will transport all crew members to the
site(s).
2. Upon arriving at the study site, Recorders and Surveyors organize and
distribute data forms and equipment. Use the equipment list (Form G-1, Figure
3-2) to ensure that all equipment is present. Routinely locate items in the same
places within the vehicle. Keeping the equipment organized by storing and
transporting items in the same locations allows items to be easily found,
facilitates packing and unpacking the vehicle, minimizes mess and confusion,
and helps prevent loss.
The large number of data sheets used in this study and the nature of
field work requires that data sheets be carefully organized and protected from
the elements. Therefore, data sheets will be organized and stored in a portable
file box or folder. Each crew member’s clipboard will be supplied with all the
data sheets needed for each site. The Recorders will organize the data sheets
on the clipboards while the Botanists conduct initial reconnaissance, and the
Surveyors organize equipment
All writing on data sheets will be done in pencil or waterproof ink to
prevent loss of data through water damage. Each data sheet will have a
standard heading that identifies the date, study site, personnel, and sampling
activity. The heading will be completed for every data sheet used.
3. Crew Leader and Botanists confer to determine wetland boundaries, any
predominating environmental gradients, and locate the transect baseline.
4. Crew Leader and Recorders lay out transect baseline. Crew Leader
determines transect starting points along baseline and Recorders mark with
35
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Page — of —
OREGON WETLAND STUDY - SUMMER 1993
Form G-1 Equipment Checklist
Site Name/Code____________________
Crew ______________________
___County
Personnel
Date:
GENERAL EQUIPMENT
_6 Clipboards
_Large rubber bands to go around clip boards
_Form Folders or File Folders
Data Forms
_First Aid Kit Induding Bee/insect
bite and sting medication
_Large plastic bags
_Baskets to contain equipment & supplies
TRANSECT ESTABUSHMENT
At least seven 100-rn all weather measuring
tapes (Ben Meadows #122608 or equivalent)
VEGETATION SAMPUNG
_Two 1 -m 2 Rectangular Quadrats (Dimensions
0.73m x 1.40m)
_Plant Presses with blotters,
ventilators & cinch straps
_80 flagged wire pins
_2 Pouches or packs for wire pins
(one per Recorder)
_Two diameter tapes
Tags for marking specimens of unknown plants
SOIL SAMPUNG
35 Soil Sample bags - prelabelled
_Bucket Auger
_Core Samplers
_Core sampler liners & caps
_Knife with long blade
WETLAND MORPHOLOGY
_Tra 1 nsit & Tripod
GENERAL SITE DATA
_Colored pencils
_Pencils and Waterproof Pens
Permanent Markers
_Cups
____Cooler for lunches
____Water Jug - for drinking
_Water Jug - for washing
_Paper Towels
_Handi-wipes (or equivalent)
_Tec-nu (or equivalent) for Poison Oak
Two 5-lb. Hammers
_Twelve 24-Wooden Stakes
4 Meter Sticks
_Regional Flora (Hitchcock & Cronquist)
15-cm ruler
Trowel
Hand Lenses
_Wetland species st
_Rare species list
_Gallon size ziploc bags
Ice chest wfice
Set of Dice
_Munsell color chart with gleyed color page
_lce chest w/ice & rack to hold sample tubes
2 Shovels
_Squirt bottle w/clean water
_Paper towels
Random # table
Stadia Rod
_Transit & Tripod
____Stadia Rod
____Flc’rescent Flagging Tape
_1 00-rn Measuring Tape
____Walkie Talkies
_Spare camera batteries
_35-mm Camera with 50-mm lens
_35-mm color slide film, ASA 100
_2 pouches or packs for wire pins
_360-Azimuth Compass
Figure 3-2. Equipment list for Oregon Wetlands Study to be used as Form G-1.
36
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stakes and appropriate flagging. Botanists conduct initial reconnais3ance of
wetland vegetation, and agree upon pseudonyms for unknown species.
Surveyors begin mapping procedures.
5. Vegetation Teams begin vegetation identification and estimation of cover of
plant species, bare ground and open water within 1-rn 2 quadrats, make line-
intercept determinations and belt transect measurements. Surveyors complete
mapping procedures. Crew Leader photographs the site.
6. Surveyors follow the Vegetation Teams and measure elevations and water
depths,,record data on whether transects intercept vegetation, open water or
bare ground, and collect soil samples. Vegetation Teams continue vegetation
sampling.
7. Crew Leader and Botanists determine if additional transects are required to
sufficiently characterize the vegetation. A minimum of 40 vegetation quadrats
are required. If additional transects are necessary to get 40 vegetation
quadrats, determine and mark locations of Vegetation Transects.
8. Vegetation Teams conduct vegetation sampling along Vegetation Transects.
Surveyors follow, and measure elevations and water depths.
9. Botanists collect voucher sam es, and key out and preserve plants for future
identification and archiving. Recorders assist Botanists and/or Surveyors.
10. Crew Leader reviews all data forms for completeness, errors, etc., organizes
them into the site packet, and makes entries into the field diary. Surveyors and
Recorders collect and organize equipment, and replace it in the vehicle. The
Recorders ensure there is an ample supply of data forms to be used at the next
site. If the supply of data forms is running low, they inform the Crew Leader
who ensures that more are obtained.
11. Crew Leader ensures the site is left in the best possible condition, checks to
ensure no equipment or samples are left behind.
Although the Crew Leader has ultimate responsibility for ensuring completeness
and legibility of data sheets, eath crew member should check the data sheets
completed during sampling activities to be sure they are complete and legible.
There should be no need for data entry personnel to interpret handwriting or
numbers. All calculations and the legibility of numbers should be checked. The
draft site map and data sheets should be checked to ensure all required
inforr-nation (transect locations, soil sample locations, landmarks, etc) are
included and correct.
All sample containers should be checked for seal tightness and code accuracy
and legibility. Soil pits must be filled in, and flagging, stakes, meter tapes, other
supplies and equipment retrieved and replaced in the vehicle. Aside from
37
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unavoidable trampling and soil sampling disturbance, the study site should look
as it did when the crew arrived.
12. Leave the site.
DATA AND SAMPLE CUSTODY AND HANDLING
Samples can be damaged through improper handling and lost if custodial
responsibilities are not clearly established and followed. The Crew Leader is
responsible for ensuring that all samples and data are safely delivered to the
laboratory at PSU. A record of all samples, including the type, number, date collected
and date custody was transferred is maintained for each site on Form G-2 (Figure 3-
3). In addition, the contents of each site packet will be copied, and the copies stored
separately (in a different building) from the original data sheets.
The Crew Leader has custody of the samples unth they are physically
transferred to, and acknowledged by, the receiving party. Custody transfer is
formalized by the signature of the representative of PSU’s lab on Form G-2 (Figure 3-
3). PSU is then responsible for sample handling and safety. Samples may not be
discarded until authorized in writing by ERL-C. Plant specimens will be kept
indefinitely at the PSU Herbarium; duplicates will be stored at ERL-C for a minimum of
5 years. Soil samples will be stored at PSU until organic matter data has been
validated (Winter 1993).
General considerations in sample handling:
1. Use only clean sample containers.
2. Discard defective containers.
3. Seal and label the container as soon as each sample is collected.
4. Keep soil samples cool and shaded to retard biological activity or other
chemical cnanges. When in the field, keep all samples in a cooler. Soil cores
should be disturbed as little as possible to minimize the possibility of mixing
soils within core tubes. Do not twist, shake or bump cores; keep them upright if
possible. Transfer soil samples to a dark, refrigerated, storage unit as soon as
possible.
5. Complete the Sample Custody Log (Form G-2, Figure 3-3). A copy of the log
will be kept with the samples from the time they are collected until they are
discarded. The original copy of Form G-2 is kept in the site packet.
6. Plant presses containing specimens should be stored in a dry, well ventilated
environment until validation is completed.
38
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OREGON WETLAND STUDY - SUMMER 1993
FORM G-2 Sample Custody Log Date: ___________
Site Name/Code_______________________ County__________________________
Crew_______________________________ Personnel___________________________
A copy of this form must accompany the soil samples and plant specimens to the Portland State
University (PSU) lab. The originals will be included in the packets for each site. Field personnel
complete items followed by (Field); lab personnel complete items followed by (Lab).
Soil Sample #‘s (Field):
Number of Soil Samples Collected
(Field): __________ _________
Delivered to lab personnel: (Initials of
field personnel responsible)___________ ___________ _________
Plant specimens received at PSU (Lab): __________ _________
Date received:_____________________
Personnel receiving:_________________ __________ _________
Soil samples received at PSU (Lab): __________ ________
Date received:_____________________
Personnel receiving:_________________ ___________ _________
Sample condition: __________ _________
Good / Poor (circle one)
Broken sample containers:__________
Open sample containers:____________
Leaking sample containers:___________
Other:____________________
List damaged sample numbers: __________ _________
Comments:
Figure 3-3. Form G-2. Custody log for plant specimens and soil samples collected during the Oregon
Wetlands Study.
39
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7. Remcve plant specimens from presses when plants are dried. Store, by site, in
boxes for later archiving.
QUALITY ASSURANCE
The data collected during the OWS must be of the highest quality possible.
This is accomplished through training and the use of standardized field and laboratory
pr 9 cedures, and through Quality Assurance (QA) activities. QA activities for all field
and laboratory procedures will be used to assess five data quality attributes:
accuracy, precision, comparability, completeness, and representativeness. These
attributes are described in detail in the Quality Assurance Project Plan: Oregon
Wetlands Study (QAPP) (Magee et al. in preparation). QA procedures will be
implemented at each site and during each laboratory session to evaluate all field
sampling and laboratory analyses. The resulting data will be evaluated to determine
whether they meet specific data quality objectives. If deficiencies are noted,
appropriate corrective actions in the field or lab technique will be taken. Detailed QA
procedures and explanations of the data quality objectives are presented in the QAPP.
Quality Assurance is an integral part of the OWS and it is imperative that the field
crews be well versed in the implementation of all QA activities as part of their normal
field sampling and laboratory analysis obligations. Throughout the study we will check
the quality of the data to verify that our QA objectives are being met.
STRUCTURE OF WETLAND CHARACTERIZATION SECTIONS
The following sections describe 1) the variables used to characterize and
compare the wetlands and project studied; 2) the field and laboratory methods used;
and 3) detailed procedures for executing sampling tasks and laboratory analyses.
Sections encompassing this information include Transect Establishment, General Site
Data, Wetland Morphology, Vegetation, and Soils and Hydrology. The format of each
section may vary slightly but each contains, as appropriate, several standard
components:
1. A discussion of the importance of the variable (e.g., vegetation, soils) in the
wetland ecosystem, and a description of the information that may be gained by
sampling this parameter.
2. Criteria and justification for selection of specific methods to sample or measure
a particular variable.
3. A detailed discussion of field and laboratory methodologies and their
implementation. This includes:
a. Protocols describing the order in which field or laboratory tasks are
completed and assigning crew members responsibility for these tasks.
b. Detailed procedures with step-by-step instructions for field or lab
activities.
40
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4. TRANSECT ESTABLISHMENT
The primary goal of sampling is to represent differences in vegetation.
substrate, hydrology, and topography, between project and natural wetlands in various
land use settings. Choosing a sampling method appropriate to the goals and scale of
the study requires consideration of time and logistic constraints, cost/effectiveness of
measurements, and field crew expertise. First, the number of sites (—150) to be
evaluated allows time for only one visit per site during the growing season with the
sampling date coinciding as closely as possible with peak vegetation cover and plant
species maturity at each site. Next, the sampling strategy should meet time and cost
restraints by accurately describing vegetation heterogeneity and environmental
gradients using the smallest number of sample points, the simplest method, and
minimizing damage to the site. Finally, the sampling design must be one that can be
rapidly learned and precisely executed by separate crews.
Using these criteria, a systematic sampling design has been selected because it
covers the site evenly and gives accurate results (Gauch 1982). Systematic sampling
meets the study goals because it is effective for assessing 1) spatial pattern and
variability in vegetation (Greig-Smith 1964, Kershaw 1973), and 2) vegetation
response to environmental gradients if samples are placed regularly along gradients
(Kershaw 1973). Sample placement in the field is convenient and rapid (Greig-Smith
1964) and removes observer bias. This is particularly important to this study because
three separate crews will be working simultaneously at different sites and
comparability is essential for optimal data quality and accurate interpretation of results.
TRANSECT TYPES AND OVERVIEW OF METHODS
Three types of transects will potentially be used at each site: Site
Characterization Transects, Wetland Morphology Transects, and Vegetation Transects.
Site Characterization Transects cross the wetland from edge to edge, perpendicular to
a baseline (Figure 4-1). To reduce researcher bias and subjectivity as much as
possible, the Site Characterization Transects will be placed systematically at evenly
spaced intervals along the Baseline. The Wetland Morphology Transect is placed
parallel to the Baseline and perpendicular to each Site Characterization Transect
(Figure 4-1). Vegetation transects will be necessary only when fewer than 40 of the
quadrats along the Site Characterization Transects contain vegetation. If used,
Vegetation Transects, either run parallel to and are inserted between the Site
Characterization Transects (Figure 4-2), or follow a narrow fringe of vegetation
encircling a pond (Figure 4-3).
To permit characterization of the relationships between vegetation and
environmental variables, the Baseline will be oriented in one of two ways. The
Baseline is placed so that it lies perpendicular to any obvious uni-directional gradient,
allowing the Site Characterization Transects to span the gradient. However, if no uni-
directional gradient can be identified, the Baseline is placed parallel to the longest
edge of the wetland.
Sampling points will be systematically spaced along all transects based on
wetland area. The sampling intervals used in this study have been adapted from
41
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= Wetland Morphology Transect (WM1)
- Site Characterization Transects (SCT)
Figure 4-1.
Basic transect layout used to sample sites. A Baseline is placed along one side of the wetland and is used to systematically
place the Site Characterization Transects. A Wetland Morphology Transect is placed parallel to the Baseline, as near as possible to
the center of the wetland. Five Site Characterization Transects originate from and are placed perpendicular to tbe Baseline.
They span the wetland from edge-to-edge and are placed at even itervals along the Baseline. The start and endpoints of the
transects are placed one sampling Interval beyond the wetland boundary.
WMT
Scale
1cm = 6m
I
= Baseline
Wetland
Boundary
-------
= Wetland Morphology Transect (WM1)
= Sfte Characterization Transects (SCT)
= Vegetation Transects (Vi)
= Vegetation Transects (VT) Area not sampled.
— = Sampling Interval Endpoints
Figure 4-2. Vegetation Transect (Vi) placement when the vegetation band le more than two sampling Intervals wide. Vis span the wetland from
edge-to-edge and are placed at even Intervals along the Baseline but sampled randomly in the order determined by rolling a die until the
number of transects needed to provIde 40 quadrats with vegetation are sampled.
WMT
Scale
1cm = 6m
t#J
= Baseline
Wetland
Boundary
-------
Wetland Morphok)gy Transect (WM1)
= Site Characterization Transects (SCT)
- = Vegetation Transects (VT)
tij = Start point for Vegetation Transect
— = Sampling Interval Endpoints
Scale
L! ’ = 6m
Upland
WMT
120m
I .
1 08m
Wetland
Boundary
GOm
Baseline In t I
____ op.nwatsr
Om
FIgure 4-3. Vegetation Transect (Vi) placement when the vegetation Is less than two sampling Intervals wide.
-------
Homer and Raedeke (1989) and are listed below. Additionally, the appropriate
placement of the vegetation quadrat frame in relation to the transect line is indicated
for each sampling interval (See also Vegetation Section).
Wetland Size Sampling Interval Quadrat Frame Placement
<0.lha (O.25a) lm Short side parallel to
transect line
> 0.lha (0.25a) but
<0.3 ha (0.75a) 3m Long side parallel to
transect line
> 0.3ha (0.75a) but
< 1.Oha (2.5a) 6m Long side parallel to
transect line
> 1.Oha (2.5a) but
< 2.Oha (5.Oa) 9m Long side parallel to
transect line
FIELD METHODOLOGY
The Crew Leader, Botanists, and Recorders all have roles in transect
establishment. Specific responsibilities for tasks are listed and the order in which
these tasks are completed are outlined in Figure 4-4 and discussed in greater detail in
the following sections.
Site Characterization Transects
Site Characterization Transects will be used to sample several wetland
variables at predetermined sampling intervals. The proportions and distribution of
vegetation, open water, and bare soil will be described. Measurements of elevation
will be made to determine wetland morphology (cross sectional shape). Vegetation will
be characterized in terms of composition and structure. General seasonal hydrology
will be assessed by obtaining values for standing water depth and depth to soil
saturation. Soils will be evaluated in terms of profile characteristics and organic
matter content at a subsample of the sample points. Details of sampling procedures
for each variable are described in the Supporting Data, Vegetation, and Soils and
Hydrology sections.
The field procedures for placement of site characterization transects are
adapted from Homer & Raedeke 1989.
1. Crew Leader and Botanists determine the approximate boundaries of the
wetland to be used to guide sampling.
45
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Determine Appropriate Wetland Boundary and Identify Gradients
(Crew Leader/Botanists)
Determine Baseline Length and Location
(Crew Leader)
Determine Locations of Transects
Flag Starting Points
(Recorders)
Figure 4-4. Transect Establishment Protocol Flowchart Crew responsibiUties and the order
in which sampling tasks must be completed.
Inspect Site
(Crew Leader/Botanists)
Determine Sampling Interval
Interval Based on Wetland Size
as Determined from Map
Information
(Crew Leader)
. *
Site Characterization
Transects
(Crew Leader)
Wetland Morphology
Transect
(Crew Leader)
Vegetation Transects
(if needed)
(Crew Leader
or Botanists)
‘ ii
14
Document Rationale for
Baseline Placement and
Vegetation Transect
Placement
(Crew Leader)
46
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2. The Crew Leader selects one side of the wetland as a Baseline. The Baseline
is located just upland of the wetland/upland edge, perpendicular to any
topographic gradient, if present, otherwise parallel to the long axis of the
wetland. If possible, the baseline should run the entire length of the wetland.
Lay out a meter tape along the baseline, and record the baseline length on
Form F-i (Figure 4-5).
3. Multiply the length of the baseline, measured to the nearest 0.lm, by 0.1, 0.3,
0.5, 0.7 and 0.9 to determine the starting points of each of the Site
Characterization Transects (Figure 4-5). This procedure allows each Site
Characterization Transect to bisect a 20% segment of the wetland. The Site
Characterization Transects (SCT) are perpendicular to the baseline and run
across the wetland from the Baseline, through the near edge of the wetland,
then across the wetland to the opposite wetland/upland boundary. The start
and endpoints are placed one sampling interval beyond the wetland boundary.
EXAMPLE: Using data presented in Figure 4-1.
Baseline length: 120m
Starting point SCT1: 120m x 0.1 = 12m
Starting point SCT2: 120m x 0.3 = 36m
Starting point SCT3: 120m x 0.5 = 6Cm
Starting point SCT4: 120m x 0.7 = 84m
Starting point SCT5: 120m x 0.9 = lOBm
Wetland Morphology Transect
A single Wetland Morphology Transect will be placed parallel to the Baseline so
that it bisects the wetland as close to the center as possible, and perpendicularly
intersects the Site Characterization Transects (Figure 4-1). The start and endpoints
for this transect are placed one sampling interval beyond the wetland boundary so that
the ends of the transect are placed in the upland. Elevations and water depths will be
measured along the Wetland Morphology Transect, and the type of land cover
(vegetation, open water, bare ground) at each sampling point will be recorded.
However, vegetation sampling will not be conducted along this transect. Wetland
Morphology Transect elevations will be used in conjunction with the elevation data
collected along the Site Characterization Transects to define the cross-sectional shape
(morphology) of the wetland.
Vegetation Transects
Some wetland physiognomies encountered during this study will necessitate an
increase in the number of transects to adequately characterize the vegetation of a
given site. This is expected to occur most frequently at sites with a narrow fringe of
47
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OREGON WETLANDS STUDY.- SUMMER 1993
FORM F-i Transect Esta Iishment
Site Name & Code______________________________
Crew____________________
Baseline Length________ Bearing
Calculations of Site Characterization Transect Length:
Baseline Length Starting Point Bearing
SCTI:
mx0.i=
m
mx0.3=
m
SCT2:
mxO.5=
m
SCT3:
SCT4:
mxO.7=
•
m
mxO.9=
rn
SCT5:
Rationale for Baseline Placement (e.g., presencelabsence of
uni-directional gradient) and other notes (e.g., triangulation
distance calculations, compass bearing for transect segments
across open water):
Page of____
Date__________
County_________
Personnel_________________________________________
Sampling Interval (Wetland Size): I m (<0.1 ha IO.25a1)
(Circle one) 3m ( O.i ha (0.25a1 but
-------
vegetation surrounding a large expanse of open water, a condition common in newly
constructed projects. In such situations, often fewer than 40 of the quadrats placed
along the site characterization transects are likely to contain vegetation. Since it is our
experience that a minimum of 40 quadrats per site is required to accurately represent
the herbaceous vegetation on wetlands 2 ha or less in size (unpublished data from the
Oregon Pilot Study, Brown 1991, Confer and Niering 1992), it will be necessary to add
additional transects until a minimum of 40 vegetation quadrats are obtained. The
additional transects will be referred to as Vegetation Transects to distinguish them
from the Site Characterization and Wetland Morphology Transects. Methods of data
collection on the Vegetation Transects are the same as those used for the Site
Charactenzati9n Transects.
Two standard procedures for Vegetation Transect placement accommodate two
different, but commonly encountered, wetland scenarios and reduce the effects of
observer subjectivity. These procedures address logistical problems related to the
width of the vegetation band surrounding a pond.
Case 1 - If the vegetation ring is greater than two sampling intervals in width,
Vegetation Transects are added until the needed number of vegetation quadrats is
obtained (Figure 4-2):
1. Vegetation Transects extend across the width of the vegetation band on both
sides.of the open water. Non-vegetated areas are not sampled.
2. Vegetation Transects 2 through 5 run parallel to and are located at the mid-
points between the site characterization transects. To determine their exact
positions in relation to the baseline, multiply the length of the baseline by 0.2,
0.4, 0.6, and 0.8 for Vegetation Transects (V I) 2, 3, 4, and 5 respectively.
Example: Using data presented in Figure 4-2.
Baseline length = 120m
Starting point V12: 120 X 0.2 = 24m
Starting point VT3: 120 X 0.4 = 48m
Starting point VT4: 120 X 0.6 = 72m
Starting point VT5: 120 X 0.8 = 96m
3. Vegetation transects I and 6 are placed parallel to and outside Site
Characterization Transects 1 and 5 and within the wetland boundary. Their
locations relative to the base-line are equidistant between the outer Site
Characterization Transects (1 and 5) and the edge of the wetland. To
determine their exact positions, multiply the length of the baseline by 0.05 and
0.95 for Vegetation Transects (VT) 1 and 6 respectively.
Example: See Figure 4-2.
Baseline length = 12Cm
Starting point VT6 = 12Cm X 0.95 = 11 4m
Starting point VT1 = 120 m X 0.05 = 6 m
49
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4. The Vegetation Transects are not sampled in chronological order. The order is
determined by randomly selecting Vegetation Transect numbers (1-6) by
casting a die. The number obtained on the first roll will be the first transect
sampled, the second roll will be the second transect sampled, and so on. If the
number of a transect already selected comes up on a roll of the die, disregard it
and roll again. Record the sampling order of the transects on Form F-I (Figure
4-5) and record the numbers of the transects actually sampled.
5. Establish only the number of transects required to obtain a minimum of 40
vegetation quadrats. If 40 vegetation quadrats are obtained prior to reaching
the end of a transect, continue sampling until that transect is completed.
6. The first quadrat on a Vegetation Transect is placed at the first sampling
interval from the transect starting point that falls within the wetland boundary
(See Vegetation Section for details on identifying the first quadrat position).
Sampling proceeds at the normal sampling intervals until open water is
reached. The open water area(s) is skipped and sampling begins again on the
other side of the water and continues to the wetland boundary (See Vegetation
Section for details on identifying the last quadrat position).
Case 2 - If the vegetation band is narrower than two sampling intervals, up to
six Vegetation Transects are placed so that they parallel the vegetation band (Figure
4-3). The start point for each transect is systematically determined and each transect
is sampled at the standard interval for the site. Only the number of vegetation
transects required to obtain 40 quadrats are randomly selected for sampling.
The order of placement for transects to be sampled is randomly selected by a
die to obtain a number from 1 to 6. These numbers correspond to pre-
assigned potential start points defined as the locations where the Site
Characterization Transects, 2 and 4, and the Wetland Morphology Transect
intersect the vegetation ring (Figure 4-3). After determining the sampling order
for the six transects, list the order on Form F-l (Figure 4-5) and circle, on the
diagram, the start points for each transect actually sampled.
2. To establish each transect during sampling, the meter tape is pinned at the
starting point and extended left, when facing the center of the wetland, until the
end of the transect is reached (e.g., the start point of the next transect) (Figure
4-3).
3. Quadrat placement differs from the normal procedure. Usually quadrats are
places with their long side parallel to the transect meter tape (See Vegetation
Section). Here, quadrats are placed with their short side adjacent to the meter
tape. This placement allows the long dimension of the quadrat to span the
maximum area possible, thus, encompassing the greatest level of vegetation
zonation and heterogeneity possible (Figure 4-3, inset).
50
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General Transect Establishment Procedures
Once the locations of the transects have been determined, the process for
laying out and marking all transect types is essentially the same. Wetlands are
sensitive to trampling so a sampling method that requires as few trips as possible
along each transect is used, and crew members always walk on the left side (when
walking from the beginning towards the end) of the transects to avoid trampling
vegetation to be sampled.
1. Transect starting points are located on the transect Baseline. For wetland
morphology measurements, the first sampling point along each transect will be
at the Baseline/transect intersection (Cm). For vegetation sampling, the first
sampling point will be the first point within the wetland boundary as determined
by quadrat placement according to the sampling interval for the site. The Crew
Leader must clearly document how the location of each transect was
determined on Form F-i (Figure 4-5) and ensure that the Recorders marking
the transect starting points understand where the transects should be located.
2. The Recorders mark transect starting points with stakes and flags. The
transect numbers are indicated with flags, e.g., transect one has one flag,
transect two has two flags, etc. Meter tapes are firmly attached to the stakes
marking the transect starting points.
3. The Recorders use a compass to determine the direction each transect should
take to cross the wetland perpendicular (90°) to the transect baseline. Record
the transect bearing on Form F-i (Figure 4-5).
4. The first sampling team (Botanists and Recorders along Site Characterization
and Vegetation Transects, or the Surveyors along the Wetland Morphology
Transect) lays out the meter tape as they proceed along a transect from its
starting point, sampling the plots at the predetermined intervals. On Site
Characterization and Vegetation Transects, the meter tape is left in place and
sampling point locations flagged with wire pins for the second sampling team
(the Surveyors). After sampling the Wetland Morphology Transect, the
Surveyors remove the meter tape.
5. Sampling order along each transect is designed to minimize vegetation
trampling by requiring each person to make only one pass along each transect.
The wetland Morphology Transect is traversed only by the Survey Team. As
they proceed along the transect they collect elevation and water depth
measurements, as well as soil information and soil samples. Site
Characterization and Vegetation Transects are traversed first by one of the
Vegetation Teams and then by the Survey Team. Vegetation Sampling will be
conducted on two transects simultaneously by separate Vegetation Teams. A
Botanist and a Recorder will sample vegetation as they proceed along a Site
Characterization or a Vegetation Transect. After vegetation sampling has been
completed along a given transect, the Survey Team follows and collects the
51
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appropriate data and samples. For Site Characterization Transects this
includes elevations, water depths, soil data, and soil samples. For Vegetation
Transects, only elevation and water depth measurements are obtained.
6. After all sampling has been completed and data forms checked for
completeness, the meter tapes will be removed by reeling them in from the end
of each transect. The stakes and flagging are retrieved by walking around the
wetland perimeter.
Transect Establishment Procedures In Atypical Situations
In cases where deep open water that cannot be crossed on foot interrupts one
or more transects, special procedures are required to locate the portions of the
transects lying on the far side of the wetland (Figure 4-6). This problem may affect all
three types of transects.
Commence transect establishment and sampling using the general procedures
described above. Sample the portions of all transects that can be reached on
one side of the open water. Once sampling has been completed on one side of
the water, walk around the perimeter of the wetland to the wetland/upland edge
opposite the transect start points.
2. Standing at the opposite wetland/upland edge look directly across the water
back toward the segment of a transect that has already been sampled.
Establish the direction along which the unsampled portion of the transect should
run by aiming a compass back toward the transect starting point stake along a
bearing 1800 from the bearing defining the original transect segment (Figure 4-
6). Move to the left or right as needed until the correct bearing is obtained.
3. Place a stake at this point so that it is located just upland from the wetland
boundary. This will be the transect endpoint and the first sampling point used
by the Survey Team for the portion of the transect extending from here to the
open water. The first vegetation qi adrat will be placed at the first sampling
interval inside the wetland boundary (Figure 4-6). Record, on the appropriate
data sheet the sampling point distances along the meter tape in chronological
order beginning with zero at the transect end-point and continuing with
increasing numbers to the water’s edge (Figure 4-6).
4. After sampling has been completed the Survey Team uses the transit to obtain
triangulation measurements (See General Site Information, Site Map Section for
details) that will permit calculation of the distance from each transect’s start
point to its endpoint on the opposite side of the wetland.
52
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• - - Compass Bearing
•“aBase llrie
Wetland Mor hoIogy Transect (WMT)
= Site Characterization Transects (SCT)
/36m
Transect start point
• = transect start or end-point = first sampling point for Survey Team
[ J = first sampflng point/quadrat for Vegetation Team
xm = distance from zero
= Portion of transects under water
WMT
Om
Om
Wetland
Boundary
Figure 4-6. Procedure for transect establishment in cases where deep open water interupts one or more transects.
-------
5. Jl triangulation distances and calculations are recorded on a transect
establishment data sheet, Form F-i (Figure 4-5), for each transect. The total
length of a given transect can then be used to convert the recorded distances
for the sampling points to the actual distances of the sampling points along the
transect. A completed Form F-i is filed together with all other data forms for
that transect so that data entry personnel can enter data into a computer in the
correct order.
54
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5. GENERALSITE DATA
The Surveyors and Crew Leader will generate a standardized description of
each wetland by sketching a map of the site, collecting specific qualitative information,
and photographing specific wetland attributes. This information is not intended for
detailed data analysis procedures, but to provide reconnaissance-level knowledge of
each site. Such data are easy and time-efficient to collect, and support data analysis
and interpretation.
First, a description provides a conceptual framework in which to visualize the
quantitative data used to characterize each site. It provides general familiarity with 1)
the landscape; 2) the plant communities or plant life forms and their distribution; 3) the
presence or absence of gradients; 4) the level and type(s) of disturbance; 5) patterns
of water flow; 6) sources of pollution or disturbance from adjacent lands; and 7) the
placement of sampling transects in relation to all of these factors. This backdrop is
important because it may help generate hypotheses and questions, not previously
obvious, that can be evaluated through analysis of the quantitative data. Familiarity
with the site gained through a systematic, qualitative survey will also offer a safeguard
against misinterpretation of the results. If the outcome of analysis is far from what
would be expected based on reconnaissance information, then rechecking the data
entry and analysis processes would be in order. If no errors are encountered, then it
would be appropriate to look for anomalies in the site and/or to reassess the initial
hypotheses.-
Second, gross differences between wetlands, in landscape setting, water flow
patterns, vegetation types, gradients, or levels of disturbance may be immediately
apparent from sketch maps, photographs, and qualitative data. Qualitative data could
be particularly useful if there are large consistent differences between natural and
project wetlands, and in corroborating classification and ordination results. Also, it
may be used in informal non-quantitative trends analysis for tracking temporal
changes in the wetlands, particularly if there are large changes with time.
SITE MAPS
General physical information is needed to create overall descriptions of each
wetland studied, e.g., size, shape, location and surroundings. Detailed physical data
can provide the basis for characterizing attributes of natural wetlands and projects,
and can facilitate comparisons between them. The U.S. Fish and Wildlife’s NWI maps
indicate the locations, types, shapes and sizes of the natural wetlands in the study,
information useful mainly for site selection. The OWS requires detailed physical
information not available at the scale of the NWI maps. Site maps will document the
dimensions and setting of each wetland, and will also create a record of transect
placement and indicate appropriate access points.
For wetland projects, site maps created during this study will document physical
information about projects as-built. As part of the determination of compliance, these
data will be compared against construction plans, blueprints, and Section 404 or
ODSL permit requirements for compliance determinations. The skills and methods
55
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required to make a good site map are discussed below. These skills are
straightforward to learn and personnel can be trained quickly.
The site map will be made by determining the distance and bearing of points
located along the wetland perimeter with the Surveyor’s Transit (hereafter, the transit).
The wetland perimeter will be identified through changes in slope and vegetation.
Locations of objects, landmarks, patches of vegetation, and transect endpoints can be
determined with the transit and included on the map. The distance and direction to all
mapped points is recorded from a single point (the transit location) and later
transferred to graph paper to make the final site map. A rough sketch map is drawn
at the same time the data are collected to check the relative locations of mappable
features during final map construction. Transit-stadia surveying was chosen for this
study because it is sufficiently precise for reconnaissance surveys, rough surveys for
the location of boundaries, and detailed surveys for maps. In addition, it is more rapid
and economical than other survey methods (Davis and Kelley 1969). When calibrated
with a compass, magnetic bearings can be determined with the transit to within 5 feet.
The stadia hairs within the telescope of the transit allow horizontal and vertical
distances to be measured accurately (Klssam 1966).
Measuring distances with the transit and stadia rod is based on the principle
that the intercept, or difference in reading between the two fixed stadia hairs in the
telescope of the transit, is directly proportional to the distance between the target (the
stadia rod) and the telescope. Stadia hairs are two supplementary horizontal cross
hairs equally spaced above and below the center cross hair. The stadia hairs are
fixed so that there is a constant multiplier for converting the stadia interval to distance
(Figure 5-1). The multiplier is usually 100 (Buckner 1983).
Equipment
Brunton Cadet Compass
Surveyor’s Transit and Tripod
Stadia Rod
Forms
Pencils
35-mm Camera
Copy of Form I from visit to the site during site selection (see Figure 2-2)
Walkie Talki& Headphones
The Brunton Cadet Compass
The Brunton Cadet compass (hereafter, the compass) is used to determine
direction and to measure vertical angles and percent of slopes. The principal use of
the compass will be to determine direction via compass bearings and to calibrate the
graduated circle of the Surveyor’s Transit (discussed below) for use in mapping. The
compass circle is divided into 900 quadrants or 360° counterclockwise azimuth. The
azimuth or bearing is read directly off the compass circle with the compass needle as
the pointer. With this method, the compass circle is numbered in reverse. Therefore,
56
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Stadia
Hairs
Horizontal
Cross Hair
Figure 5-1.
A view through the transit telescope showing the Horizontai cross-hair at
1 .20m on the Stadia Rod and a Stadia Interval of O.47m
(1 .44m - O.97m = O.47m). Distance from the transit to the Stadia Rod is 47m
(O.47m x 100 = 47m).
Stadia
Interval
O.47m
57
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East and West are interchanged and the numbers run 00 to 360° counterclockwise.
This allows the needle’s north tip to point directly to the angle on the compass circle
toward the line of sight (Brunton Company 1980). For mapping, the 3600 azimuth is
more useful than the 90° quadrants because there is less chance errors will be made
in calculating directions (Lounsbury and Aldrich 1979).
The compass circle must be set for true north. The compass needle points
torard magnetic north, which changes slightly with time. True north is located
geographically, and maps are based on it because it doesn’t change. The angle
between magnetic north and true north is called magnetic declination. This angle is
the number of degrees the compass needle bears away from true north at that locality.
Declination information for every location in the United States can be obtained from
U.S. Geologic Survey Maps (USGS) (Greenhood 1964). The compass circle can be
adjusted for magnetic declination by manually rotating the compass dial and offsetting
“N” on the compass circle by the appropriate number of degrees for the local
declination. Before using the instrument, always be sure to set the circle at the
declination of the locality. Declination in the Portland, Oregon, area is presently about
20 degrees E of N, so the compass dial must be rotated clockwise so that “N” reads
20° to the right (Figure 5-2).
To take a bearing, i.e., to determine the direction from one object to another,
hold the compass about waist high, open the lid and slant the mirror backward at
about 450 Hold the instrument flat in the left hand with the mirror to the rear. Press
the left forearm against the waist. Steady the instrument with the right hand. Any
tipping of the compass will prevent the needle from swinging freely. Place your eye
so that the line on the mirror (the rear sight) bisects the reflection of the front sight.
Turn your whole body until the reflection of the object to be sighted is aligned with the
sights (i.e., the black center sighting line of the mirror bisects both the reflected front
sight and the objected sighted). The NORTH end (painted) of the needle indicates the
bearing of the object sighted (Brunton Company 1980).
Setting Up the Transit
First, position the transit to enable the operator to see as much of the wetland’s
perimeter and as many sampling points as possible. Generally, a centrally located
position on a slight rise and on firm ground is best. This saves time and effort
because it should allow the operator to collect all mapping and sampling information
without moving the transit (a process called “turning”, Wetland Morphology Section).
Sink the tripod feet into the ground to stabilize the instrument, adjusting the legs to
make a nominally level platform. The legs should have about a 3 1/2-foot spread. If
the tripod has adjustable legs, be sure the wing nuts on the leg clamps are securely
hand tightened.
Place the transit onto the platform, hand tightening the threaded stud of the
tripod to the instrument base securely. While watching the level bubble on the transit,
push individual tripod legs further into the ground until the bubble is somewhat
centered.
58
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I Line of Sight
- .
- -
-
- I - .
• - -•
t__
,P
Dial: 7 ’ .. I l-
- Zj’ - - _ - : - -
• ‘•-.- 7 . ,
- - - - e - -
.• •..... ,..:
p - • -
- C-
- -
L - ‘- “ I ’-
— . - • .
I -
-- A -- s
-.
t -
j
L
I -
_C. C
‘ C
S
1
- -
4- - - -
— 4_ .
- C t -
I
I
;ompasA
a t-
--3 ’
- -
Figure 5—2. Setting the magnetic declination on a compass.
-------
Begin to level the transit using the levelling knobs; while leveling the instrument,
do not touch the tripod. The three leveling screws of the transit are turned one at a
time until the bubble is centered within the black indicator circle. When properly
leveled, the bubble should remain in centered position during a 3600 rotation of the
telescope. The automatic level’s pendulum compensator will maintain this level
alignment even if the tripod or transit is jarred or tilted slightly.
To ensure that the transit remains level during operation, it is important to
periodically check that the bubble is centered. In addition, select a solid object (e.g.,
a large stone, stump, edge of a sidewalk) to use as a benchmark (the elevation
control point). Sightings will be periodically made to the benchmark to ensure that the
transit is level and hasn’t shifted.
Calibrate the graduated circle of the transit with the Brunton compass. Rotate
the transit’s graduated circle so that 00 on the transit corresponds with 00 on the
compass. (Some transits will be equipped with a compass, making this step
unnecessary.)
Using the Transit to Map the Study Site
The Crew Leader will confer with the Botanists to establish the wetland
perimeter based on changes in vegetation, moisture, and elevation. The Crew Leader
will convey this information to the Surveyors and verbally establish the points that will
be used to identify the wetland perimeter. The surveyors record the distance and
direction from the transit to all ucornersD on the wetland perimeter. Corners represent
changes in direction in the wetland boundary. The finished map will depict the
wetland as a polygon.
The distance and direction to all mapped points is recorded from a single point
(the transit location) and later transferred to a map. The transit operator draws a
rough sketch map on Form F-2 (Figure 5-3) while in the field, to check the relative
locations of mapped features during final map construction. The map should include
all points recorded with the transit. Use the following procedure:
1. Assemble a clipboard, compass, transit and stadia rod, several copies of Form
F-2 (Figure 5-3) and map data sheets, Form F-3 (Figure 5-4).
2. Set up the transit at a point where the entire wetland perimeter can be seen. If
the transit must be moved during the mapping procedure, follow the procedures
for turning (See Wetland Morphology section) and record the benchmark data
on the back of Form F-3 (Figure 5-4). Ensure that the transit is level and
calibrated with the compass. On Form F-2 (blank sketch map) indicate
approximately where the transit is located and label this point as Transit
Location 1 . Draw an arrow on the map to indicate North.
3. While the Transit Operator sets up the transit, the Surveyor with the stadia rod
moves along the perimeter of the wetland to the first corner. This will be
corner NAb on the sketch map. To standardize the mapping procedure, the
60
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OREGON WETLANDS STUDY - SUMMER 1993 Page of___
FORM F-2 Sketch Map Date___________
Site Name & Code_________________________________ County___________
Crew__________________________ Personnel____________________________________________
Figure 5-3. Form F-2. Sketch Map.
61
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OREGON WETLANDS STUDY - SUMMER 1993 Page of___
FORM F-3 Map Data Sheet Date___________
Site Name & Code County__________
Crew Personnel ___________
Station
From
Station
To
Bearing
Stadia
Readings
Caiculated
Distance
Comments
U_______________
m________
U______________
n______________
U______________
n_____________
U______________
n_____________
U______________
n_____________
U______________
n_____________
U______________
n_____________
U______________
Tl _________
U
n_____________
U______________
Ti____________
U______________
n___________
U
n______________
Comments:
Figure 5-4. Form F-3. Map Data Sheet for recording bearings and stadia readings of points
on the wetland perimeter. This data will be used In combination with the sketch
map to draw the map for each site. U=upper stadia hair, m=c oss-hair, l=lower
stadia hair.
62
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Form F-3 (cant.)
NO TURN: Benchmark (B.M.) Readings TURN: New Benchmark?
Urstiai Readings YES:
I 2nd Reading
m_____ lr tiaIBM u_____ Stationto.______
I___ m___
Beanng__ ____
Beann
FInaJ Readings u_____
m______ 2 Estab 1sh new Benchmark
Beau 3 1st Reading
ng NewBM. u_____ Stabonto
Error (rn-rn)______ m____
Beanng__ .
4 Difference between new and Initial
Benchmarks u________
TURN: New Benchmark? m_____
NO: I_____
1 2nd Reading
Inltiai B M u_____ Station to______ 5 Relocate Inpod
m______
I______ 6 2nd Reading
NewBM u_____ Stationto._______
Beanng____
m______
2 Relocate Tripod I______
Beanng__
3 3rd Reading
IrWtial B M. u______ Station t0 _______ 7 DIfference between 1st and 2nd ReadIngs
m_____ New Benchmarks u_____
I___ m___
Beann g ° I________
8. A4ustment__________
4 FfnalB.M. (Duff of6&8monly)
Reading u______ Station to
m_____ 9 FinaJReaduig
IritiaIBM u_____ Statlonto______
Beanng_____ m_____
5 Ac ta nent_______ Bear1iin
(Duff 013 &4rnonly)
Figure 5-4 continued.
63
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Surveyor with the stadia rod should move clockwise around the perimeter of the
wetland.
4. The stadia rod is held vertically while the transit operator uses the telescope to
sight the stadia rod. The Transit Operator sketches the approximate location of
the wetland “corner” on the sketch map, labels it, and then records the stadia
readings (upper, middle, and lower cross-hairs) and the compass bearing for
that point on Form F-3. The upper and lower stadia readings indicate the
distance to the corner from the transit location, and the middle stadia reading
indicates the relative elevation of that point. Stadia readings, in meters, are
recorded from the meter scale on the stadia rod (Figure 5-5). The compass
bearing provides the direction to that corner of the wetland from the transit
location and is read directly off the compass rosette on the transit.
5. The Surveyor with the stadia rod continues moving the stadia rod from ucomeru
to “corner” around the perimeter of the wetland while the Transit Operator
recoids the data and makes the rough sketch. The Transit Operator should
also record any anecdotal information which might help construct the final map
in the comments box on Form F-3.
6. In addition to the wetland perimeter, the Transit Operator should map the
locations of all sampling transects by positioning the stadia rod to take
bearings, distance and elevation readings at their beginning and end-points. It
will be necessary to collect this data later during the day, i.e., after sampling
transects have been placed and during collection of wetland morphology data.
Record the information on Form F-3 (the map data sheet) and mark the
positions of the transects on the sketch map.
7. The Transit Operator records the locations of major site features such as open
water, trees, water courses, patches of monotypic vegetation, and man-made
structures.
8. If a corner of the wetland perimeter cannot be reached by the Surveyor carrying
the stadia rod due to deep water, unstable substrate or other obstructions, use
triangulation to determine its location (Lounsbury and Aldrich 1986). First,
using a meter tape, establish two points (endpoints of a baseline) which are a
known distance apart (at least 30m), and record the length and the direction of
the baseline on Form F-3 (Map Data Sheet). Using the transit, take compass
and upper and lower stadia hair readings from both baseline endpoints to a
previously measured point on the wetland perimeter (e.g., a mapped wetland
“corner” or transect endpoint). These readings will be used to locate the
baseline’s position on the sketch map.
Then, from both baseline endpoints, take compass readings through the
transit to the corner not reached by the Surveyor and record the data on Form
F-3. When constructing the final site map, the location of the corner not
64
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-------
reached by the surveyor will be indicated by the intersection of two rays drawn
along these bearings from the baseline endpoints (illustrated in Figure 5-6).
9. After all wetland corners and site features are measured and recorded, examine
the sketch map and document anything that will help complete the final map.
Check that data are recorded for all wetland TM corners’ and that entries on the
data forms are legible.
Drawing the Final Site Map
• Finished maps are drawn from the map data and rough sketch maps in the
office or lab as time permits.
1. Assemble graph paper, pencils, erasers, a ruler with markings in centimeters,
• and a 3600 protractor.
2. Examine the sketch map and map data (Forms F-2 and F-3) to estimate the
appropriate scale so that the map will fit on an 8.5 x 11 inch sheet of paper.
This takes some practice, if the scale is too large, the map won’t fit on the
paper. If too small, the map will not contain the necessary details. A wetland
covering I to 2 ha will typically fit on an 8.5 by 11 inch sheet of paper at a
scale of 1:1000 (one meter in the field equals one millimeter on the map).
3. Establish north 1 and indicate on the map with an arrow.
4. Using the sketch map as a guide, mark on the graph paper the approximate
location of the transit in the wetland.
5. Calculate the distance from the transit to a map point using the data on Form
F-3 (Figure 5-4). To do this, subtract the lower stadia reading from the upper
one and express the result in centimeters. The number of centimeters between
the two stadia lines is equal to the number of meters between the transit and
the mapped point.
6. Align the protractor so that the center mark is positioned on the transit location
and 00 points toward north on the map sheet.
7. Using the bearing information from Form F-3, draw a light line from the transit
location and through the bearing angle for the map point.
8. Using the ruler, measure the distance along the line from the transit position to
the represented mapped point. This distance will depend on the map scale you
have chosen. For instance, if you are drawing the map at a scale of I :1000,
each meter on the ground will equal one millimeter on the map. Label the point
on the map.
66
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/
/
I
/ (a c ) ,# ’ ‘‘%(bc)
A Baseline of known length B
Transit locations
Figure 5-6. Illustration of procedure for triangulation. Triangulation is the process for
determining the intersection of two rays originating from the endpoints of a
baseline, and therefore, the position of the intersection in relation to the
endpoints. A line of sight is made from point A to C (ray ac). A similar
sighting is taken from point B to C (ray bc). The location of C is defined as
the intersection of rays ac and bc (Lounsbury and Aldnch 1986).
67
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9. Repeat this procedure for each point to be mapped. To complete the map,
connect the points with a dark line representing the perimeter of the wetland.
10. Erase unwanted lines and marks, and darken the lines if necessary, to make a
good copy that can be xeroxed. Draw in the site features and label the map
with the site number, location, date sampled, date drawn, and the mapper’s
name. Also indicate the map scale, e.g., Scale: 1 cm = 8 m. See Figure 5-7
for an example of a finished map.
LAND USE AND BUFFERS
Buffer zones between a wetland and a developed upland area can protect the
integrity of the wetland water supply, water quality, and associated wetland-dependent
wildlife (Brown et. al. 1990). A buffer can act to lesson the impacts of development on
adjacent wetlands (Jordan and Shisler 1986). In addition, vegetated buffers provide a
transition between land uses and structural diversity. They create visual and noise
barriers, corridors and linkages to other habitats, and help ensure species diversity.
For this study, the presence of vegetated buffers will be quantitatively
determined along four transects extending out from the perimeter of each wetland.
After positions of the Wetland Morphology Transect and Site Characterization
Transects have been determined, Survey Team members visually determine the
presence or absence of vegetated buffers by viewing the area extending beyond the
wetland edge from beth ends of the Wetland Morphology Transect and the center Site
Characterization Transect (SCT3) (Figure 5-8). If a vegetated buffer exists, the
Surveyors extend a meter tape and record the vegetation strata present (herbs,
shrubs, or trees) at sampling intervals consistent with the sampling interval used within
the wetland on Form F-4 (Figure 5-9) for up to lOOm. When the outside edge of the
vegetated buffer is encountered, the Surveyors record the type of land use that occurs
(Agricultural, Industrial, Commercial, Residential, or Transportation Corridor). If the
buffer width is greater than 10Cm, >lOOm is recorded on Form F-4.
Form 9” (Figure 2-2), used during site selection to collect data on surrounding
land uses and determine wetland types, will be checked, and if necessary, annotated
during flelc sampling to discover if changes have occurred in the year since site
selection, and to verify the site selection data. The Crew Leader uses a colored pencil
to annotate a copy of Form I for the site by: 1) looking for evidence of changes (e.g.,
new construction, felled trees, new culverts); 2) estimating the portions of the
surrounding area that faIl into residential, commercial, industrial, agricultural, or
undeveloped land use categories; and 3) comparing the estimates with those on Form
I. Some differences in estimates of land use will occur due to differences in personnel
making the estimate, but, in general, if wetland surroundings have not changed since
site selection, Form I should be accurate.
68
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: ::
. :
:..;;...; 1 ;::; .j
E
6 ! c r_______
. ;‘ .
i /1
. - . -—
±:i:
:
. ..
±- itI
4: E tI ::
— -- --...-——4...--.
..
Jf ....
I ±
)4
-k
i ii
I±LIi
.: .
— - o qjj iJ 1
- - .. - I tf4f r )
:: :
II
I’
I I I
-h——,(’ . .p ..1 1 ..k.
.... -,-
‘-I. S
__ - i
- -
___ - ____
iT:, :ç
___ I _______
‘\\zi . _: 4 .:.H:..t ±:: .
- - - —— - - -— - -H
. .. .. .z ; . . . ::: .... . ,.... .,. :..j”:
iEL :: ii.T
• cf&o /% h1L:L... :. - jt 4Ej T_ • 4.. ___________
: Z:4 . ;:: . . :t:4b dA’r ... : .: ::.:: . : . : :_. : :
L r A
L(
5caI /c’n -
Figure 5-7. Example of a finished site map.
69
. S. SI
-------
=Basellne
Wetland Morphology Tiansect (WMT)
= Site Characterization Transects (SCT)
I - - - = Transects placed for determination of presence,
type, and widths of buffers.
Figure 5-8. Placement of transects for determination of presence, type and wIdth c i butters. Transects will extend loom ouiwara Trom tue
start and end points of the Wetland Morphology Transect (WM1) and the middle Site Characterization Transect (SCT3).
a
120m
%Weflarid
-------
OREGON WETLANDS STUDY - SUMMER 1993 Page of___
FORM F-4 Butters and Surrounding Land Use Date____________
Site Name & Code County__________
Crew Personnel___________________________________________
Transect# Buffer Width Sampling Interval: I m 3m 6m 9m (circle one)
Record types of vegetation strata at sampling intervals within buffer surrounding wetland (T=trees, S=shrubs,
H=herbaceous). Record O.W. for Open Water and B.G. for Bare Ground. Record vegetation strata up to the
maximum width of the vegetated buffer < lOOm. Record Human Land Use at the point at whith the vegetated buffer
ends (AG=Agricufture, C=Crops, F=FaJlow, G=Grazed, IND=lndustrial; COMM=commercial; TRANSP CORR=
Transportation Corridor RES=Residential, S=Single Family Homes, M=Mutti-family Homes).
Human Land Use outside buffer:
Vegetated
Sample Distance Buffer AG TRANSP RES
Point (Meters) (T,SH) O.W. B G (C,F,G) IND COMM CORR (S.M)
Figure 5-9. Form F-4, used to determine vegetated buffer width and strata, and human land
use outside the vegetated buffer.
71
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PHOTOGRAPHY
A photographic record is used to visually document site characteristics. It can
also be used later to verify data and provides a method for tracking changes in the
wetland over time.
1. To standardize photographs, use a good quality, 35-mm camera equipped with
ASA 100, 35-mm Ektachrome slide film and a 50-mm lens.
2. Label each roll of film by photographing a completed Form F-5 (Figure 5-10) in
the first frame. Photograph a new Form F-5 as the first photo taken with each
new study site. Complete Form F-5 as follows: Using a dark magic marker, fill
in the Date, Site Code, Photographer’s last name and the Film Roll Code. The
Film code contains two parts. The first three characters pertain to the film roll
number. Rolls are numbered consecutively for each camera from the start of
the field season. The fourth and fifth characters are the photographer’s initials.
For example, if Maria Melon is taking photographs on the 14th roll of film
used in that camera, the code would be 01 4MM.
3. Document each photograph by number and topic on the photo log form (Form
F-6, Figure 5-1 1). Make certain to record all photos taken (even accidental
exposures) so that the order of the developed slides matches the order of
exposures recorded in the photo log.
4. Check the camera battery frequently, carry a spare.
5. Never let the camera or film sit in the sun. Extra film should always be carried
and should be stored in a sealed plastic bag in a cooler if the weather is hot.
The primary types of photographs taken at each site are general site photos,
site record photos, and rare or unusual items (i.e., plants, animals, structures). Either
the Crew Leader or the member of the Survey Team not handling either the transit or
the stadia rod for mapping takes the general site and site record photos.
General site photos document the features of the site and the approach to
sampling. Take a panoramic landscape sequence from a central location at the edge
of the wetland. Photograph major wetland features such as open water areas, water
channels, inlets and outlets. Be sure to photograph transect locations along the
direction of the transect line. Photos of transect locations may be used to verify
sampling locations, or possibly, to resample the wetlands at a later date. Interesting
action photos of field crew members sampling will come in handy for future
presentations discussing the research.
Site record photos provide a permanent record of the wetland from a specific
vantage point. Carefully choose a vantage point to see as much of the wetland as
72
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OREGON WETLANDS STUDY - SUMMER 1993
Page of____
FORM F-5
Sfte Name & Code
Crew
Photographic Label
Personnel
Date
County__________
DATE:
SITE CODE:
PHOTOGRAPHER:
Figure 5-10.
Form F-5. Photgraphic Label. The first photograph taken at each site should be
a completed Photographic Label.
FILM ROLLCODE:
73
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OREGON WETLANDS STUDY - SUMMER 1993 Page of___
FORM F-6 Photo Record Date___________
Site Name & Code______________________________ County__________
Crew__________________________ Personnel___________________________________________
Include photographs of: surroundings, overview of wetland, representative
vegetation, evidence of animal activity, disturbance or obstructions, buffers,
evidence of stress, the vii w down the length of each transect (label by number),
and other features of interest and importance. Indicate vantage point and
bearing for Site Record Photos.
Use a new record sheet for every new roll of film and every new sfte.
TYPE OF FILM._________________________________ FILM ID#________________
DEVELOPED
PHOTOGRAPH DESCRIPTION PHOTO FRAME# SLIDE#
Figure 5-11. Form F-6, Photo Record. This form is used to record the order of all
photographs taken at a site and to label the slides developed from them.
74
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possible. Carefully record the location on the map and on Form F-6 so that the
wetland can be re-photographed from the same location in the future and changes in
the wetland can be documented. Also be sure to record the compass bearings of the
photos taken from the vantage point. Be sure to include likely permanent landmarks
like stumps, rock outcrops, fencelines, or roadways.
75
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6. VEGETATION
One of the most striking features of a wetland is the unique array of hydrophytic
plant species. The dominance of plants physiologically adapted to aquatic or
saturated soil conditions distinguishes wetlands from surrounding uplands. Wetland
vegetation is commonly defined within three basic types: forested, shrub, and
emergent. Palustrine freshwater marshes that grade from emergent vegetation to
op n water, are the focus of this study. Such habitats are frequently dominated by
sedges, rushes, grasses, and other colonial plants like cattail, while less abundant
taxa often include diverse forb species. Barring the introduction of invasive exotic
plant taxa, intact wetlands are often partially buffered from the influx of non-native
species because of saturated soil or standing water conditions. Consequently, these
communities are frequently islands of comparatively natural vegetation in areas of
extensive disturbance (e.g., agricultural, urban or industrial lands). Therefore,
wetland ecosystems are valuable resources as refugia for natural plant communities,
uncommon plant species, and as reservoirs of genetic variability.
The condition and composition of wetland vegetation reflects the overall
functional status of a wetland. Although the precise degree of equivalency between
vegetation structure and wetland function is not well understood, the presence of a
structure-function relationship is widely accepted (D’Avanzo 1986). Vegetation reflects
wetland hydrologic and edaphic features in terms of the presence of plant species
adapted to survive in these conditions. Vegetation also influences, or is influenced by,
seven of the ten wetland functions described by Adamus and Stockwell (1983),
including erosion and shoreline anchoring, sediment trapping, nutrient retention and
removal, food chain support, wildlife habitat, active recreation, and passive recreation
(see also Niering and Krauss 1986).
The characterization of vegetation is comparatively easy. It requires minimally
intensive field methods, whereas other wetland variables are often difficult and costly
to assess, e.g., hydrology and many aspects of soils. Based on its importance in
wetland function, its role as an integrative indicator of soils and hydrology, and on
considerations of cost effectiveness, vegetation analysis is a major component of the
OWS. Vegetation variables to be evaluated include species presence/absence,
species abundance, species frequency, community composition, and vegetation
distribution along gradients (Daubenmire 1959, Bannister 1966, Muller-Dombois and
Ellenberg 1974, Gauch 1977, 1982). Data describing these vegetation variables can
provide a broad scope of base-line and decision making information.
Base-line data concerning diversity, similarity, community structure, and
zonation patterns, will be used to characterize and compare vegetation on projects
and natural wetlands. For example:
1. The condition and degree of variability of vegetation in natural wetlands within
specific land use settings can serve as standards for attainable quality in terms
of species diversity, composition, and relative abundance.
2. Differences in vegetation characteristics between project and natural wetlands,
occurring in the same land use sethng might reflect variation in wetland function
associated with project development or limitations in project design.
76
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3. Inferences regarding environmental gradients or conditions controlling
vegetation can be made by comparing the results of indirect ordination
techniques and cluster analyses with site characteristics (Gauch 1982). This
may be particularly useful if correlations of hydrology (water depth) and basin
morphology (shape and elevation change) can be tied to groups of wetland
sites or to a gradient along which the sampled wetlands are distributed.
The results of the characterizations and comparisons between project and
natural wetlands can be used in decision making (Kentula et al. 1 992a) to:
1. Set performance criteria for vegetation on projects in specific land-use settings.
2. Identify problems or successes in vegetation establishment or persistence that
may be related to project construction or development.
3. Generate recommendations for improvements in mitigation strategies, project
design, and implementation procedures with regard to vegetation.
SAMPLING METHODS
Several criteria were used to select sampling methods. The first consideration
was to obtain reliable, high quality data to characterize wetland vegetation and assess
differences between natural and project sites. Second, destructive sampling is not
acceptable on fragile project sites, so avoiding alteration or negative impacts during
sampling is imperative. The third consideration was providing cost-effective
methodologies, that would result in the greatest amount of information for the least
effort and minimum expertise (i.e., proven experience in plant identification).
Procedures using species cover estimation (Daubenmire 1959, Mueller-Dombois and
Ellenberg 1974, Gauch 1977, Cox 1980) will meet data requirements and logistical
considerations.
Species cover estimates are somewhat more labor-intensive than species
presence/absence methods, but are much less time consuming than quantitative
abundance measurements such as density, point-intercept, or biomass measurements.
The extra effort required to gather cover estimates over presence/absence data is
warranted because the resulting data are more informative and suitable for a greater
variety of purposes (Daubenmire 1959, Gauch 1982). Species cover estimation is
also appropriate in terms of accuracy since inherent variability of plant community
samples is usually larger than errors due to estimation (Daubenmire 1959, Orloci
1978, Gauch 1982). The level of accuracy provided by species cover estimation is
more cost-effective than quantitative abundance measurements because quantitative
measurements require so much time to execute that the number of samples collected
declines drastically (Poore 1962, Wikum and Shaholtzer 1978).
The specific method of cover determination used in OWS wetlands will depend
on the vegetation strata under consideration. In cases where density and size of
individual plants or clones are not uniform, use of variable plot sizes or sampling units
increases sampling efficiency (Cox 1980, Gauch 1982). Canopy coverage
77
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(Daubenmire 1959) within quadrat frames will be used for herbaceous vegetation.
Shrubs will be assessed using the line intercept method (Canfield 1941, Cox 1980).
Tree cover will be evaluated in belt transects through measurements of basal area
(Mueller-Dombois and Ellenberg 1974, Homer and Radeke 1989). The merits of each
method are presented in the following discussion.
Canopy coverage is a technique frequently employed to estimate cover for
herbaceous and low statured plants, making it well-suited for sampling emergent
marshes. This method, adapted from Daubenmire (1959) will be used to estimate the
percentage cover of all herbaceous species and other plants < 1 m tall. In most
instances, .this height stratum is dominated by herbs but occasionally will include tree
seedlings and low shrubs.
Cover estimates are made in small plots or quadrats. Plot size can influence
the accuracy of estimation. The plots should be large enough to contain numerous
individuals, but small enough to permit accurate estimations or measurements (Cox
1980). Graminoid taxa dominating meadows and wetlands are frequently low-
statured, clonal, and occur at high density. Keeping plots small reduces errors in
estimation across the plot due to eye movement and memory (Daubenmire 1959).
Also, rare taxa are less likely to be overlooked in small plots where attention can be
focussed on smaller areas. However, errors in cover estimation due to edge effect
can result if plot size is too small (Green 1979). A 1-rn 2 quadrat is suitable for the tall
sedges, rushes, and grasses that dominate wetlands.
Shape of the quadrat can also influence the representativeness of the samples.
Rectangular plots are favored because most plant distributions are clumped, and
rectangular plots will encompass patches of different species, making them more
efficient and more representative of the vegetation (Gauch 1982) than square or
circular plots. Based on size and shape criteria, a 1-rn 2 rectangular quadrat frame will
be used for canopy coverage estimates.
Accuracy in sampling is enhanced by increasing either the size of the plots or
the number of samples (Gauch 1982). A large number of small plots is more accurate
than a few large plots because plants are generally found in clumped distributions
(Brown 1954, Greig-Smith 1964, Daubenmire 1968, Green 1979). For graminoid
dominated herbaceous wetland vegetation, it has been our experience that 40
quadrats is the minimum number required for adequate community or site description
(Homer and Raedeke 1989, Brown 1991, Confer and Niering 1992, Kentula et al.
1992b, unpublished data from 1987 Oregon Pilot Study).
Species canopy cover estimates will be made for all species occurring in each
plot using direct estimation of percent cover. Variability between observers will be
lim Ited by estimating percents in the following intervals: 1% units up to 5%. 5% units
from 5-30%, 10% units from 30-100% (after Gauch 1982). Direct estimation offers
several advantages over cover classes that span a range of cover percentages. It is
often easier and quicker for observers to think in terms of percent cover than to
remember broad intervals on a cover scale (Gauch 1982). Direct estimation also
prevents error due to incorrect cover class assignment caused by observers forgetting
the scale intervals. In addition, percentages can be easily converted to one of the
traditional scales (Gauch 1982), or weighted or transformed as necessary for analysis.
The line-intercept technique (Canfield 1941) is useful where a cover
assessment for large areas is required, particularly for measuring crown cover in
78
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woody plants with a continuous crown outline (Mueller-Dombois and Ellenberg 1974).
This method will be used to measure cover for shrub species and for trees <2 m tall.
The general procedure for gathering data is simple and rapidly executed. A meter
tape is extended on the ground along a transect line and the distances at which the
crowns overlap or intercept the line are recorded by species (Mueller-Dombois and
Ellenberg 1974, Cox 1980). The total intercept length of any one species (e.g., the
total distance along the transect tape occupied by a speciec) out of the total transect
length is expressed as the percent cover for that species (Cox 1980, Mueller-Dombois
and Ellenberg 1974).
Basal area is used as a measure of cover for trees within 2-rn wide belt
transects (Homer and Raedeke 1989). In this case, cover implies the projection of the
basal area of the tree to the ground surface (Mueller-Dombois and Ellenberg 1974),
i.e., the area occupied by the trunk. Basal area, in trees, is obtained by measuring
tree diameter and converting to area via the formula il. Diameter is usually
measured at diameter breast height (dbh) or 1.5 m above the ground. This is an
acceptable measure of basal area for most temperate tree species (Mueller-Dombois
and Ellenberg 1974) and standardizes the location from which measurements are
taken.
FIELD METHODOLOGY
This section describes several aspects of the field methodology: 1) the field
activities and required expertise of each crew member on the Vegetation Teams; 2)
the vegetation sampling protocol outlining the order in which sampling tasks are to be
completed; 3) a list of sampling equipment and supplies; and finally, 4) detailed
sampling procedures for the various cover measurement techniques and other field
activities. The vegetation protocol (Figure 6-1) has been designed to ensure that
quality data are collected and minimal trampling of the vegetation and substrate
occurs. Field procedures consist of standardized methods to facilitate accuracy,
precision, and comparability of the data collected. Thus, it is imperative that sampling
activities be carried out in the order and manner specified.
Sampling procedures are modified from the unpublished methods used in the
1987 Oregon Pilot Study, from Homer and Raedeke (1989), and from field experience
garnered in similar studies (Brown 1991, Confer and Niering 1992). Each activity is
described in detail in the sections below.
Each Vegetation Team consists of two individuals, one Botanist and one
Recorder. Each field crew will have two Vegetation Teams; both work simultaneously
on the same site. The Botanists must have demonstrated skill at wetland plant
identification (See QAPP, in preparation). The Recorders should have at least minimal
botanical training, and at least one Recorder per crew should be capable of
substituting for a Botanist. The sampling activities are divided into several basic task
groups: equipment organization, pre-sampling reconnaissance and plant collection,
vegetation sampling, data form proofing, defining transect endpoints, plant specimen
preservation, and identification of unknowns. The order in which each task and its
component parts are conducted, as well as the team member responsible for task
completion, is illustrated in the vegetation sampling protocol (Figure 6-1). At the site,
79
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Botanists confer with
Crew Leader re:
wetland boundaries and
environmental gradients
-
Recorders organize data sheets
for each clipboard
I
-Recorders flag end-points
of transects
Botanists-During a single pass along
the transect:
(1) Collect vegetation data
in the following order:
-line-Intercepts for shrubs
-canopy coverage for herbs
-basal area for trees
(2) Identify the transect end-point
(3) Proof data for the transect for
completer.ess, legibility, errors
(4) If necessary (rarely) resarnple
parts of transect to obtain/replace
missing or erroneous data
Recorders complete data
sheet headings
1
I
Jr
After sampling ALL transects and
Before leaving the site
Figure 6-1. Vegetation sampling protocol illustrating order of task completion and crew
responsibility.
Botanists conduct presampl ng
reconnaissance and plant
collection. Recorders assist
as time permits.
Each Vegetation Team (one botanist, one recorder) works simultaneously on
separate transects until all transects have been sampled.
Botanists determine position
of the first vegetation
quadrat along the meter tape
they are about to sample.
Recorder: (1) Enters data on the
3ppropriate data sheets. (2) Flags sampling
points for the Survey Crew. (3) Stakes and
flags the transect end-point. (4) Conveys
number of vegetation plots on transect
to Survey Team. (5) Aids Botanist in
data proofing.
Botanists complete collection of
unknown plant species, press all
plant specimens, and if time remains
work on keying non-graminold taxa.
Recorders organize and store
vegetation sampling equipment.
make line-intercept calculations,
and assist Survey Crew, If necessary.
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the two Botanists will conduct a pie-sampling reconnaissance, make canopy cover
estimates, gather line-intercept and belt transect data, collect plant specimens, proof
vegetation data forms, and identify the transect end-point The two Recorders are
responsible for organizing data sheets, flagging and staking the transect start-points
as indicated by the Crew Leader, accurately recording cover values provided by the
Botanists during cover estimation, flagging the end-points of the transect as indicated
by the Botanists, making summary calculations and assisting the Survey Team as
required.
Field Equipment and Supplies
Two 1 -m 2 rectangular quadrats (073m x 1 .40m)
Two diameter tapes
80 flagged wire pins and carrying pouch
Vegetation data forms
Pencils or waterproof pens
Plant presses with blotters, ventilators, and cinch straps
Newsprint for plant pressing
Regional floras (e.g. Hitchcock, C.L. and A Cronquist 1973. Flora of the
Pacific Northwest. University of Washington Press, Seattle, WA.)
Wetland plant species lists
Rare plant lists
Trowel for obtaining plant specimens with intact roots
Hand lenses
6-cm ruler for measuring plant parts during field keying
Gallon size zip-Icc plastic bags
Large plastic bags (e.g. kitchen trash bag)
Letter-sized envelopes
Tags for marking unknowns specimens that are carried as references dunng
sampling
Permanent marking pens
Ice chest
Pro-Sampling Activities
Prior to conducting vegetation sampling activities, the Botanists and Recorders
have specific tasks related to Transect Establishment. These include:
1. Botanists confer with the Crew Leader to aid in identifying wetland boundaries,
as wel! as, the presence and direction of any environmental gradients, and the
location of the Baseline (See Transect Establishment Section). The Botanists
then begin the pie-sampling reconnaissance.
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2. Recorders organize data sheets for all crew members and then, at the
instruction of the Crew Leader, flag the endpoints of the Baseline and the start
points of the transects (See Transect Establishment Section).
Both Botanists conduct a pre-sampling reconnaissance to identify the dominant
species and determine the general nature of the vegetation. This is accomplished by:
Botanists jointly conduct a floristic survey of the area to identify plant species.
Care should be taken to enter and traverse the wetland as little as possible to
avoid trampling damage to the site. Agreement between the Botanists
regarding species names helps to ensure accurate plant identification.
2. Botanists standardize pseudonyms for plants they cannot readily identify in the
field. If the genus name is known, then U pN should be substituted for the
species epithet (e.g., Carex sp.). If there is more than one unknown species of
a genus present, then pseudonyms should include the genus name followed by
numbers, letters, or an identifying characteristic (e.g., Carex 1, Carex 2, Carex -
with 3 stigmas, or Carex - with bidentate perigynia and striped scale). Where
neither the genus nor species names are known the botanists devise a
pseudonym that reflects growth habit, microhabitat, or some distinctive
morphological feature (e.g., bunchgrass # 1, thin-leaved aquatic herb). In
cases where there are numerous unknown taxa, it may be necessary to carry
tagged examples of the plants, in individual bouquets, during sampling to keep
the names straight. This is especially relevant if a single genus has several
unknown representatives on the site.
3. Botanists and Recorders enter, on the Canopy Coverage Form F-7 (Figure 6-2),
the names of species likely to be encountered within the sampling plots.
Species names recorded during field activities are entered in the third column of
the form (the first column will be used during post-field work to record the
validated species name). Use the binary genus/species name if known or enter
the predetermined species code discussed in item 2. If additional taxa are
encountered during sampling record their names or pseudonyms and continue
data collection. Once the transects are completed, both Botanists will reconcile
the names and pseudonyms of these species on their respective data forms.
4. Botanists collect voucher specimens of unknown or interesting plants. DO NOT
COLLECT THREATENED OR ENDANGERED PLANT SPECIES (See
Appendix B for a list of rare wetiand taxa). The Crew Leader will carefully
photograph such taxa and record their precise locations in the field diary. Plant
specimens are placed in plastic bags and then into an ice chest to reduce wilt
prior to pressing. For especially wet specimens, the plants might be placed in a
paper bag or between folds of newspaper before being deposited into a plastic
bag to prevent mold development and wilting. Plastic bags should be marked,
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OREGON WETLANDS STUDY - SUMMER 1993 Page of___
FORM F-7 Herbaceous Vegetationl% Canopy Coverage Date____________
Site Name & Code__________________________________ County___________
Crew__________________________ Personnel____________________________________________
Transect!!_______ Length_______ Bearing ° Sampling Interval: im 3m 6m 9m
QASheet: YIN
checktopbox
If sample nee
tobecollected,
check bottom box
whensamp lehas
been colIecie
PIot#
Distance from Om
—
Bareground
—
Water
—
Standing Dead and Litter
—
Species Name
—
—
—
—
—
—
—
—
—
—
—
—
—
—
— —
Figure 6-2. Form F-7 used for herbaceous vegetatior fcanopy coverago-quadrat data.
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using a permanent marker, with pseudonym information, the site number, date,
and the wetland area or transect number, and the plot number and plot
distance from which the specimen was collected. Examples: Carex 1, Site 61,
7-21-93, Plot 4 (iBm), or Carex 1, Site 61, near the north end of the Baseline
east of the Wetland Morphology Transect.
5. Specimen collection continues throughout the site visit as new species are
found. When a plant sample is collected place a check in the ‘collected” box of
the appropriate vegetation data form (Figures 6-2 or 6-3) . If a specimen is
needed but has not yet been collected, place a check in the “to be collected”
box as a reminder. Collect the required specimens before leaving the site.
Vegetation Sampling
Vegetation sampling is conducted by both Vegetation Teams working
simultaneously on separate transects. One Vegetation Team begins with Site
Characterization Transect I and the other begins with Site Characterization Transect
2. The Teams continue sampling alternate transects until all the Site Characterization
and Vegetation Transects have been sampled. Vegetation sampling involves several
activities: 1) determination of the position of the first vegetation quadrat on each
transect; 2) perparation of the data sheet; 3) placment of the meter tape along the
transect line; 4) collection of line-intercept data for shrubs; 5) collection of canopy
coverage estimates for herbaceous species; and 6) collection of basal area data for
trees. The procedures for each sampling activity are described below, detailing the
steps required to complete a single transect.
The Botanist determines the locations of the first and last vegetation quadrats
on each transect and the Recorder enters the distance information on the Canopy
Coverage Form F-7 (Figure 6-2). The sampling interval (1, 3, 6, or 9m) selected
during transect establishment is used to identify the meter tape distances, at which the
quadrats or sampling points will be placed. Quadrats are placed only at these pre-
defined points.
1. First quadrat location. Transects begin at the basel ne at Om. However, this
position will lie in upland, and vegetation sampling is conducted only in the
wetland. The position of the first quadrat on the meter tape is determined by 1)
identifying the location of the wetland/upland boundary, and 2) proceeding along
the meter tape from the boundary to the first sampling point inside the wetland.
The first quadrat will be located at this point. For example, if a 6-rn sampling
interval is used for the wetland and the wetland boundary occurs at 1 Om from
the Baseline, the nearest sampling point would be at 1 2m (See Figure 6-4, Site
Characterization Transect 3). Thus, in this case, 12m is the location of the first
quadrat on this transect. Subsequent quadrats would be placed at 6-rn
intervals (e.g., iBm, 24m, 30, etc.) until the wetland boundary at the opposite
end of the transect is reached. See Figure 6-4 for more examples of
determining the distance from Om to the first quadrat position. Enter the
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Transect#______
check to collect
Check when collected
Site Name & Code
Crew
OREGON WETLANDS STUDY - SUMMER 1993
FORM F-8 All Shrubs and Trees <2m Tall - LIne-Intercepi Data Form
______________ Personnel________________
Length________ Bearing ° Sampling Interval: I n i 3m 6m 9m (circle one)
Page of____
Date____________
County__________
Record tape position as meters (whole numbers) and centimeters as decimals: e.g.. im I4cm=1.14, 17m 7cm=17 07
QA Sheet: YIN
U i
Species:
\
Species:
pecies:
F—
pecies:
F
pecies:
F—
Tape Postition:
,lflterCePt
i Length
‘ (ml
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rape Postition:
i Intercept
, Length
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rape Postitlon:
ulntercept
i Length
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ape Postition:
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ape Postition:
Intercept
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Figure 6-3. Form F-8 used for all shrubs and for trees c2m tall - line-Intercept data.
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72m
72m
54m
48m
42m
36m
3Cm
24m
18m
12m
60m
54iii
48m
42m
36m
3Cm
24m
1 8m
2m
60m
54m
48m
42m
36m
3Cm
24m
iSm
12m
6m 6m 6m
Om Cm Om Om Cm
SCT5 SCT4 SCT3 SCT2 SCT1
— = Baseline _______________
= She Characterization Transects (SCT) _____
o = Position of the first quadrat
C] = Position of the last auadrat
The position of the first and last quadrats on vegetation sampling transects.
Scale
1cm = 6m
Upland
Emergent
Vegetation
66m
6Cm
0 ’
8rn
Figure 6-4.
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position of the first and subsequent quadrats in the section on data form F-7
marked aist. from 0” (Figure 6-2).
2. Last quadrat location. The final vegetation quadrat on a transect is placed at
the last sampling point where an entire quadrat can be placed inside the far
wetland boundary (i.e., the boundary across the wetland from the Baseline).
The position of the last quadrat on a transect is determined during sampling.
Do not walk the length of the transect prior to sampling because this would
cause unneeded trampling of the vegetation. Examples of last quadrat position
determination are illustrated in Figure 6-4. On Site Characterization Transect 1
the last quadrat occurs at 48m along the meter tape even though the wetland
boundary extends to approximately 60m. A quadrat placed at 54m would cross
the wetland boundary and extend into upland vegetation so it would not be
sampled.
Prior to beginning data collection Recorders complete the headings on all
vegetation data sheets (Figures 6-2, 6-3 and 6-5). It is important to take the time to
do this before beginning to record data. Transect length should be recorded after the
transect has been sampled. Transect length for vegetation sampling will not equal the
transect length for environmental sampling. This is because vegetation sampling does
not occur on the upland ends of the transects. Thus, it is important to record, on the
vegetation forms, the actual length of the transect that has been sampled. This is
particularly critical for the line-intercept data because transect length is used in
calculating cover percentages.
1. Canopy coverage data sheet (Figure 6-2). Record the distances from zero and
the plot numbers for each quadrat along a transect as sampling proceeds. Use
separate data sheets for each transect. If more than one data sheet is required
to complete a transect, repeat the species names in the same order on each
sheet. If the number of species occurring on a transect exceeds the number of
spaces provided for species names, record the additional species on another
data sheet. Make certain to enter the correct quadrat location (distance from
zero and plot number) on the additional data sheets.
2. Line-intercept data sheet (Figure 6-3). Ust all shrub and tree species that occur
on the site in the space provided. Use separate data sheets for each transect.
If more than one data sheet is required to complete a transect because all the
tape position/interval length spaces are filled, repeat the species names in the
same order on each sheet. If more than one data sheet is required because
more than five species occur on the transect, record the additional species on
another data sheet. After sampling the transect be certain to record the precise
transect length in the heading of the form.
3. Diameter at Breast Height (Figure 6-5). Ust all tree species that occur on the
site in the first column of the data form.
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OREGON WETLANDS STUDY - SUMMER 1993 Page of___
FORM F-9 Tree identification and Diameter at Breast Height Date____________
Site Name &Code_________________
Crew__________________________ Personnel
Species
Diameter at Breast Height (dbh) cmfnearest sampling Interval
Figure 6-5.
Form F-9, used for tree identification and diameter at breast height
Transect / i
County
______ Length_______ Bearing ° Sampling Interval: im 3m 6m 9m
QASheet: Y/N
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Placing the meter tape
The Recorder pins or otherwise attaches the meter tape at the flag marking the
transect beginning. The meter tape is NOT stretched the full length of transect prior to
sampling; instead, during sampling, it is stretched along a compass bearing as the
Vegetation Team proceeds toward the end of the transect. The tape is left in place
after the Botanist has finished cover readings so it can be used later by the Survey
Team. These procedures minimize trampling of fragile wetland soils and vegetation.
To avoid trampling of the vegetation that will be sampled in quadrats the Vegetation
Team always travels along the transect on the left side when facing the transect from
the baseline.
Sampling Order for Vegetation Data
Three kinds of data, line-intercept for shrubs, canopy coverage for herbaceous
species, and basal area for trees, will be collected in a single pass along the transect.
Line-intercept intervals for shrub species will be obtained along the meter
tape, percentage cover values for herbaceous species will be estimated within 1 2
quadrats placed adjacent to the meter tape, and basal areas for tree species will be
gathered in a 2-rn wide belt transect centered on the meter tape (Figure 6-6). The
Botanist collects all the types of vegetation data for a given segment of a transect,
then proceeds to the next segment. Sampling is continued in each subsequent
segment until the transect is completed. The length of a transect segment equals the
sampling interval defined during transect establishment (i.e., im, 3m, 6m, or 9m
depending on wetland size). For purposes of vegetation sampling, the first interval
begins at the bottom edge of the first quadrat, that is the edge nearest and parallel to
the baseline, and continues along the meter tape to the bottom edge of the next
quadrat (Figure 6-7).
Data is collected in the following order within each transect interval:
1. Line intercept data is gathered first because vegetation will be matted down due
to kneeling on the transect line while reading the quadrats during estimation of
canopy coverage. Kneeling on and disturbing shrubs would negatively affect
the quality of the line-intercept data.
2. Canopy cover estimates are then obtained for all species occurring in the
qu ad rat.
3. Since both the line transect and the quadrat are contained within the belt
transect, basal area data is gathered last to prevent trampling of the
herbaceous vegetation in the vicinity of trees prior to sampling.
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Determine belt width
by placing a meter
stick perpendicular to
the transect line.
2-rn belt transect
for trees
Une-intercept
transect for shrubs
Figure 6-6. Transects used for sampling herbaceous vegetation, shrubs, and trees.
(Adapted from Homer and Roedeke 1989). Scale: lcm=lm
quadrats
and forbs)
Transect Line
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Belt Transect
I I
• ; Transect Line
I I
I I
I I
quadrat
5mi I
I i I
I I I
I I I
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I I
I I I
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I I
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I I
1. Line-intercept data (shrubs)
2. Canopy coverage data_________ — Transect Segment I
I • I
3. Basal area of trees
I — I
I -first quadrat positioned at
I I
the first sampling Interval
point within the wetland
I I
boundary.
wetland/upland
3m boundary
I I
I I
I I
I I
I I
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Baseline
Figure 6-7. Illustration of transect segments in which vegetation data are collected and the
order of data collection. All data are collected for each segment before
proceeding to the next segment. Scale: lcm=lm
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Une-Intercept data collection (Figure 6-3)
1. Line-intercept data is not gathered from the upland ends of the transect (See
Determining location of the first and last quadrat, above) but only within the
wetland boundaries. Shrubs and small trees are sampled along the transect
length in which vegetation is sampled, e.g., the distance bounded by the
outside edges (those edges parallel to the baseline and nearest the wetland
boundary) of the first and the last quadrat (See Figure 6-4).
2. Definition. Intercept length equals the portion of the transect, i.e.. the distance
along the meter tape, that a plant’s foliage touches, overlies, or underlies.
3. Botanists determine the intercept length for each shrub species and each small
tree (<2m tall) by calling out the species name and the intercept length
beginning and endpoints (e.g., Figure 6-8, Salixpipen, 3.60 to 6.lOm).
4. Recorders enter data on the line-intercept data form (Figure 6-3) by recording
beginning and ending points in the spaces provided under the correct species
name. Meters are recorded as whole numbers and centimeters as decimals
(e.g., continuing the previous example, in the Salix piperi column 3.60 to 6.1Cm)
5. Intercept lengths may be calculated by subtracting the beginning point from the
ending point (e.g., 6.lOm - 3.60m = 2.50m). Calculations should be made by
the Recorders after sampling all transects has been completed.
Canopy cover estimation withIn quadrats
1. Sample plot placement.
a. Sampling begins with the plot nearest the baseline on the transect that
will be sampled (See Determining first plot location above). The Botanist
places the 1-rn 2 quadrat so that its nearest right-hand corner is adjacent
to the appropriate sampling point on the meter tape and its long side is
parallel to the transect (Figure 6-9).
b. The recorder places a flagged wire pin in the nearest right-hand corner
of the quadrat to mark the sampling point location for the Survey Team.
The Survey Team will remove the pins as they sample the transect.
2. Definition. Plant species cover estimates are the percentage of each sampling
plot that is overlain by the undisturbed canopies of each species occurring in
the plot.
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Wetland Boundary
SCT5 SCT4 SCT3 SCT2
Intercept Lengths:
Transect 1 - Salix piper!: 6.lOm-3.60m=2.50m, 8.65m-6.90m=1 .75m
Transect 4- Spirea douglas!!: 3.60m-2.OOm=1.60m
Transect 5 - Spirea douglasli 4.65m-2.70m=1.95m, Rosa pisocarpa: 7.50m-5.20m=2.30m
Figure 6-8. DeterminIng the Intercept intervals for shrubs using the line-intercept method.
SCT1
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1 -rn 2 Quadrat
Location of
flagged wire pin
/ 3,mn
Transect Line_/
Increasing Distance from Zero
Enlarged to show detail. Figure is not to scale.
Figure 6-9. Placement of the 1-rn 2 quadrat along transect line.
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3. Percentages for cover estimation. Use the percentage increments defined for
precision in cover estimates.
For Cover Of: Use Increments Of :
1%to5% 1%
>5% to 30% 5%
>30% 10%
4. Guidelines for cover estimation (Adapted from Daubenmire 1959):
a. Botanists make cover determinations for each species by estimating the
amount of ground space in the plot overlain by the canopies of
individuals or clones of that species (See Figure 6-10). Cover
determinations for microsite characteristics are made by estimating the
ground space occupied by water or bare ground.
b. Do not try to subtract openings created by separated leaves in canopies
of species with open habit (Figure 6-10). The space over which a plant
exerts influence is approximated by the area of its undisturbed canopy
even where such openings exist, since the plant’s root system typically
spreads at least as extensively in the horizontal direction as does the
canopy.
c. The ground space is frequently covered by superimposed layers of
plants due to the vertical stratification of plants within communities.
Thus, the sum of all canopy-coverage estimates often substantially
exceeds 100%.
5. The Recorder reports percentage cover for each of the species names or
microsite characteristics on the Canopy Cover Form F-7 (Figure 6-2) as they
are called out by the Botanist. If a species called out by the Botanist is not
already on the list, the Recorder adds it. The Recorder verbally confirms
names and percent cover with the Botanist for any such information he/she has
difficulty hearing or understanding.
6. Standing water. The Botanist estimates the percentage of area occupied by
standing water, if any is present, within the 1-rn 2 quadrat. Do not include
saturated soil as standing water.
7. Bare ground. Estimate the percentage of the 1-rn 2 quadrat without herbaceous
vegetative cover as bare ground. This includes any area covered by water and
lacking vegetation.
8. Plant species. Using the guidelines in item five, the Botanist estimates the
cover of each plant species occurring in the sample quadrat. If a plant needs
95
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A = 50%
B = 3%
C = 30%
0= 1%
E = 15%
Figure 6-10. Illustration of species cover estimation within a 1-rn 2 Quadrat.
0.73ni
Leaves Open Area
Estimate cover based on solid line
96
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to be collected for taxonomic validation, the recorder makes a check in the to
collect box” in the second column on the Canopy Cover Form F-7 (Figure 6-2).
When a specimen has been collected, check the “collected box” on the form
(see Collection and preservation, later in this section).
Basal area data collection within belt-transects
1. Definition. Basal area is measured by obtaining the diameters at breast height
(dbh = 1 .5m) for all trees > than 2m tall and occurring within a 2-rn wide belt
transect that is centered on the transect line.
2. Determine the outside boundary of the belt transect by placing a meter stick on
the ground perpendicular to the transect line, first on one side of the transect
line, then the other (Figure 6-6). This is done whenever trees are encountered
near the transect line to determine whether or not they occur within the belt
transect. Diameters for all trees occurring within the belt or with at least half of
their bole inside the belt will be measured.
3. The Botanist measures dbh for each tree encountered, by stretching a diameter
tape around the bole (trunk) of the tree at a position 1.5 m from ground level.
Diameters are obtained for each bole of multi-stemmed trees. Botanists call out
the tree species name and its diameter (e.g., Popu!us trichocarpa, 37 cm).
4. The Recorder enters one dbh value/box in the appropriate species row on Form
F-9 (Figure 6-5).
Establishing the Transect Endpoint
After the Vegetation Team has finished data collection for a transect, the
transect end-point must be established so that the Survey Team will know how far to
sample and so that total transect length can be determined.
1. The Botanist determines the location of the transect end-point. This is done by
stretching the meter tape one complete sampling interval beyond the wetland
boundary and into upland vegetation.
2. The Recorder stakes the end-point according to the Botanists instructions. The
stake is marked to identify the transect by attaching pieces of flagging to
correspond with the transect number, e.g., transect 3 would have 3 pieces of
flagging.
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Post-Sampling Activities
The Survey Team will need to know the number of vegetation quadrats that
were sampled along the transect so they can randomly select the locations for soil
sampling.
1. Following completion of a transect, the Recorder calls a Survey Team Member
on a walkie-talkie and gives them the transect type and number and the
number of vegetation plots sampled on the transect.
2. The Survey Team Member confirms the information by repeating the numbers
to the Recorder.
After all the data have been collected for a transect, the Botanists check the
data sheets for completeness and legibility. Botanists check to see whether
specimens have been obtained for all species which need to be collected and that the
appropriate collection box is checked off on the data forms.
Once the vegetation sampling has been completed, the Recorders make line-
intercept calculations, assemble and file data forms, and gather and stow all
vegetation equipment. Recorders then assist the Survey Team as needed or help the
Botanists with plant collection, preservation or identification.
Final Plant Collection and Plant Specimen Preservation
Botanists collect all unknown plant taxa from the site that they have not
previously gathered. All plant specimens are labeled and pressed for subsequent
species validation. Standard procedures for plant collection and preservation are
used. The steps in each procedure are briefly outlined below. More complete
discussions are available in most plant taxonomy texts or lab manuals.
The steps in plant collection are:
1. Plants should, whenever possible, be collected when in flower and/or fruit.
Mature fruit are especially important for Carex (sedge) species.
2. If the plant is dioecious (male plants and female plants) collect specimens from
both sexes whenever possible. Wetland species likely to be dioecious are Sa!&
sp. (willows) and some Carex sp. (sedges).
3. If the specimen is small, collect the entire plant including the roots. Collect at
least enough material to fill a herbarium sheet.
4. If the specimen is large, collect some of the root, part of the stem with leaves,
and part of the inflorescence (flowering stem). If the specimen is a Carex or a
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grass (Poaceae), also place a piece of the inflorescence in a small envelope to
protect it from damage.
5. If the plant is woody, collect twigs with leaves and fruit.
6. Collect enough plant material to ensure adequate material for identification.
7. While in the field, temporarily store specimens in plastic bags labelled with the
species name or pseudonym and the site information described in the pre-
sampling reconnaissance section. If specimens are extremely wet place them
in paper bags or wrap in newspaper before storing in plastic bags.
The steps in pressing specimens are:
1. Standard 30 X 45cm (12 X 18 inch) plant presses will be used.
2. Clean the dirt off the plants before placing them in a press.
3. Place the plants in a sheet of folded newsprint.
4. Lay the plants flat, avoid overlapping plant parts, and spread leaves, flowers,
and fruits so they will be easily seen.
5. Bend long plants sharply so they fit within the frame. Do not curve or twist the
stems.
6. Pad areas around thick stems with layers of newspaper so no air pockets
remain.
7. Write the date, the site number, the area of the wetland or transect number,
and the plot number (if applicable) from which the specimen was collected on
the margin of the newsprint and attach an identifying tag with the same
information to the stem of each plant.
8. Stack the plants in folded newsprint in the press by inserting the newsprint
between blotters and separating the blotter-newsprint sandwiches TM with
corrugated cardboard. The corrugations of the cardboard should run parallel to
the shorter dimension (12 in.) for better air circulation in the press. Use two
adjustable straps to firmly hold the plant press and its contents. It should not
be possible to move the blotters or cardboards from the side in a properly
tightened press.
Botanists and Recorders, if time permits, may wish to key non-graminoid
unknowns while still in the field because it is frequently easier to key fresh specimens
than dried material. Such plants should still be collected and pressed for later
validation. Local floras and hand lenses should be used for field identifications.
99
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LABORATORY ACTIVITIES
The principal lab activities related to vegetation are drying of plant specimens,
identification of unknown plant taxa, checking of plant species name checks. Specific
procedures for these tasks are outlined below.
Equipment
Dissecting microscopes
Hand lenses
Dissecting tools (e.g., single edge razor blades, forceps, dissecting needles)
Regional floras
Plant specimens to be identified
Vegetation data sheets from sites where specimens were collected
Pens, pencils
Plant dryer
Place plant presses in a warm, dry, well-ventilated room or, if available, on a
plant dryer to allow specimens to dry. Once plant specimens are dry, they should be
removed from the presses and stored in labelled boxes until they are identified.
Following identification, specimens will be deposited at the PSU herbarium as
vouchers, and duplicate material will be stored at ERL-C for a minimum of 5 years as
a reference for future wetland studies in the vicinity.
Plant identification is critical to data quality so it is imperative that correct
species names are provided. Precisely following the procedures outlined below will
facilitate accurate identification and verification of species names.
1. Botanists and Recorders work together to key out unknown plant species.
2. Two individuals simultaneously and independently key one unknown. After
each has determined a species name they confer to confirm that both agree on
the name.
3. A Plant Taxonomist assists the Botanists and Recorders as needed and
confirms their identifications. She/he may also wish to personally key
particularly difficult species.
4. The validated species names are written on the appropriate data forms in the
space provided and on the newsprint containing the specimen.
5. The specimen is filed and stored, for future reference, as described above.
100
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6. Plant specimens that cannot be identified with certainty due to missing or
immature parts, difficult key characteristics, or because of poorly defined
taxonomy will be sent to an expert in wetland species.
To avoid confusion during data entry, it is important to check the data forms to
verify that plant species names are spelled correctly and that non-existent
genus/species combinations are not listed.
1. Review the data sheets for correct spellings by comparing the names with the
OWS plant species list, or with the Flora of the Pacific Northwest (Hitchcock
and Cronquist 1973).
2. If an incorrect spelling is observed, record the correct spelling in the space for
validated species name on the data sheet.
3. If a genus/species combination occurs that cannot be found in the Flora of the
Pacific Northwest (Hitchcock and Cronquist 1973) or on the Threatened and
Endangered Species List in Appendix B refer the problem to the Plant
Taxonomist.
4. The Plant Taxonomist will decide how to handle the problem.
101
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7. WETLAND MORPHOLOGY
Morphology and elevational gradients affect wetland functions by influencing
vegetation productivity and composition (Shisler and Charette 1984, D’Avanzo 1986)
and by influencing water flow paths and water retention time within wetlands (van der
Valk et al. 1978, Carter et al. 1984, D’Avanzo 1986). Morphology and
microtopography determine water flow paths through a wetland, and are critical
determinants of vegetation distribution. Vegetation, in turn, can alter the
microtopography (D’Avanzo 1986). For example, in emergent marshes of the Pacific
Northwest, clonal patches or tussocks of wetland species such as sedges facilitate
increased microrelief through detrital build-up and sediment trapping. In addition to
altering microtopography, vegetation may interrupt water flow paths. Plants can
impede surface water flow and also affect the manner in which it moves into the soil
because water runs down stems and roots channelize the soil (D’Avanzo 1986).
Microtopography alone, and in combination with vegetation and soil
permeability, influences water retention time within wetlands. The length of time water
remains in a wetland is important to water quality functions. The greater the retention
time, the greater the amount of nutrient processing (Van der Valk et al. 1978, Cooper
et al. 1986) and fine sediments deposition (Cooper et al. 1986). Differences in
microtopography and morphology between natural wetlands and projects can have
several implications. First, if relative elevations differ greatly, then plant community
composition can also be expected to be quite different between natural wetlands and
projects. Second, if morphology is typified by steeper slopes and more uniform
gradients in wetland projects compared to natural wetlands, one can expect shorter
water retention time and, therefore, less complete processing of nutiients, sediments,
and probably heavy metals. Third, if natural wetlands exhibit a mosaic of
microtopography and vegetation, they can be expected to exhibit greater wildlife
habitat diversity.
Elevation information collected along sampling transects will allow relationships
between wetland vegetation, hydrology and morphology to be analyzed. In addition,
comparisons wi!l be made between the morphology of natural wetlands with that of
projects, and between wetland projects and their design specifications and
construction plans.
FIELD METHODOLOGY
Data on wetland morphology are collected by measuring the relative elevations
of points along transects to provide cross-sectional profiles of each wetland. A transit
and stadia rod will be used to measure relative elevations. The transit establishes a
plane over the ground at eye level, and the stadia rod measures how far the earth is
below that plane. Therefore, as the stadia rod is moved downhill, the numbers read
from it will increase. Because we are concerned with relative elevations, we will use
the lowest reading per site (not per transect) as zero and calculate elevations relative
to that point.
102
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The Survey Team should develop procedures to help assure precise data, e.g.,
hold a pencil on the rod to double-check a reading, use consistent hand signals and
the walkie-talkie radios to indicate if the rod is not vertical or should be moved, etc.
Equipment
Transit & Tripod
Stadia Rod
Data Forms
Pencil
WaikieTaIki& Headphones
Pouch for carrying retrieved plot markers
Getting Started
1. If possible, set up the transit in a location which will allow all transects to be
surveyed from one location. If the transit must be moved during surveying,
carefully follow the instructions for utumingu (below).
2. Set up the tripod and mount the transit. Follow the instructions for setting up
the transit in the section on General Site Data.
3. Establish a ubenchmarku to use as the reference elevation. A solidly anchored
naturai feature, such as a stump, can be used, or one can create a reference
point by driving a stake firmly into the ground. The benchmark must be visible
from all transit locations. Keep this in mind if turns are required. Take a
reading on the benchmark at the beginning and end of each transect, and
before and after each turn. If the difference in benchmark readings at the
beginning and end of a transect is greater than O.Olm (1cm), re-shoot the
elevations for that transect.
4. The Surveyor with the stadia rod must hold the rod verticaJly, and, if the rod is
extended, ensure that the extension set screw is tight and that the extension is
seated properly against the stop. If the stadia rod is vertical, the telescope
cross-hairs will appear exactly parallel to the stadia rod markings. Therefore, it
is the Transit Operator’s responsibility to indicate whether or not the stadia rod
is vertical and correct the positioning through hand signals and the use of the
waikie-talkies.
Collecting Wetland Morphology Data
Relative elevations, water depths, and data on bare ground, open water, or
vegetation at the sampling points will be collected along all sampling transects by the
Survey Team.
103
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The Crew Leader, with input from the Botanists and Surveyors, establishes the
transect locations and directs the Recorders in marking the transect beginning
points with flagged stakes (see Transect Establishment).
2. The Surveyors carrying the stadia rod attach a meter tape to the stake that
marks the starting point of the Wetland Morphology Transect and extend the
meter tape as they advance the stadia rod across the wetland to sample. For
the Site Characterization Transects, the Vegetation Teams will have left the
meter tapes in place after they have sampled the vegetation and inserted
flagged wire pins as plot markers along these transects. The Surveyors with
the stadia rod advance along the meter tape in the same direction as did the
Vegetation Teams along the Site Characterization Transects.
3. Record the first elevation measurement at ‘Om on each transect (at the starting
point). Place the stadia rod directly to the right of the meter tape at the starting
point and hold it vertically until the transit operator signals that the stadia rod
can be moved to the next sampling point. To reduce bias, sampling intervals
along the transects will be determined systematically by the size of the wetland
(see Transect Establishment). The same sampling interval will be used on all
transects at a site. This interval MUST be recorded on all data sheets, and, it
is IMPERATIVE that the same sampling interval be used by all teams so that
data can be correlated during analysis.
4. The Transit Operator measures the elevation at each sample point by sighting
the stadia rod through the transit telescope and recording the stadia reading of
the center cross-hairs on Form F-b (Figure 7-1).
5. The Surveyor holding the stadia rod relays information via the Nwalkie..taikieu
headphones to the Transit Operator. This information includes water depth
measurements, the type of land cover occupying the sampling point (vegetation,
barren ground, or open water), as well as general information such as where
the edges of inundated areas occur, where obvious changes in vegetation
composition occur, locations of landmarks, etc. This additional information is
recoided by the Transit Operator in the appropriate sections of Form F-1O.
6. If the stadia rod is moved out of the sight of the Transit Operator, a Itumu must
be made. Before turning , the Transit Operator must check to see that the
transit is level and record the benchmark elevation. The procedure for tuming
is described in the following section. Document ‘turn information on the back
of Form F-b.
7. After completing all measurements along the Wetland Morphology Transect.
measure elevations along the Site Characterization Transects and along the
Vegetation Transects, if they are used for the site. All data gathered on the
Site Characterization and Vegetation Transects MUST be made within the
104
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OREGON WETLANDS STUDY - SUMMER 1993
FORM F-b Wetland Morphology
Site Name & Code__________________
Crew__________________________ Personnel_
Transect#_______ Length________
Figure 7-1. Form F-i 0, Wetland Morphology.
Page of____
Date___________
County_________
Bearing ° Sampling Interval: 1 m 3m 6m 9m
QASheet Y/N
Sample
Point
Distance
(Meters)
Stadia
Reading
Vertical
Offset
Relative
Elevation
Water
Depth
Open
Water
Vegetated
Bare
Ground
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
105
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Form F-i 0 (cont)
TURN: New Benchmark?
NO:
1 2nd Reading
InttiaiBM._____ Plot#_____
BearIng
2 Relocate Tripod
3 3rd Reading
In itiaJBM____
Beanng °
4 FinaIBM
Reading ______ Plot #______
Beanna °
5. Ai t tment__________
(Duff of3&4)
YES:
1 2nd Reading
IritiaIBM _____ PIot _____
Beanng__
2 Establish new Benchmark
3 1st Readin9
NewBM _____ P 1 0tH
Bearing °
4 Difference between new and Initial
Benchmarks________
S Relocate tripod
8 2nd Reading
NewBM _____ P1 0tH
Beanng
7. DIfference between let and 2nd Readings
New Benchmarks____________
8 ft4t th ont
(Duff of6&8)
9 FinaiReading
lre liaJBM _____ PIot#_____
Bearing °
If transects are interrupted by deep water, distance to the transect start and
endpoints on the far side of the water must be determined. Therefore, record
upper and lower stadia hairs for those points: Start point: u__________
Comments:
Figure 7-1 continued.
End point: U__________
NO TURN: Benchmark (B.M.) Readings
inital Reading__________
Final Reading___________
Error________________
Bearing °
Plot H______
(same as 1)
106
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vegetation plots that were sampled. Therefore, it is extremely important that
the meter tapes are left exactly in place, and that the stadia rod be placed
within the vegetation sampling points. To facilitate this, the Recorders will have
placed flagged wire pins along the transect at the lower right hand corner of
each vegetation sampling plot. Place the stadia rod directly to the right of the
meter tape and wire pin as you are facing toward the end of the transect, so
that it touches the wire pin. After recording elevation data at each sampling
point, retrieve each wire pin and carry them along the transect. You should be
carrying a pouch or pack for this purpose. To avoid trampling vegetation before
the Botanists have sampled, the Surveyors must follow the Vegetation Teams
during sampling.
8. After all measurements have been made on each transect, take a reading of
the benchmark. This reading must not differ from the first benchmark reading
by more than ± 0.01 m. Do this BEFORE dismantling the tripod. Show on the
back of Form F-iC all benchmark readings and calculations. If the error is
greater than ± 0.Olm, reshoot all points measured since the last accurate
benchmark check. To correct data on Form F-l0, put a single line through the
incorrect entry and write the correct entry above it.
9. If transects are interrupted by deep water, distance to the transect start and
endpoints or the far side of the water must be determined. Therefore, upper
and lower stadia readings must be made for these points and recorded on the
back of Form F-b.
10. After all elevation measurements have been made for the entire site, calculate
the relative elevations for all sampling points on the site — NOT PER
TRANSECT.
a: Determine the lowest point on the site. This point corresponds to the
largest stadia rod reading for the site. The stadia rod reading at this
point becomes the “vertical offset” for all calculations.
b. For each measurement, subtract the stadia rod reading from the vertical
offset to determine the relative elevation for each sampling point.
c. Leave all original stadia rod readings on Form F-i0 as a data check, as
well as any notes.
Turning with the Original Benchmark
If the transit operator cannot see all sampling points from the transit location.
the transit must be moved. This procedure is referred to as “making a turn” or
“turning”.
107
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1. BEFORE moving the tripod, take a reading of the original benchmark and
record it on the back of Form F-10 (Figure 7-1).
2. Determine if the original benchmark will be visible from the tripod’s new
position. If so, continue to use the same benchmark, If not, follow the steps in
the next section for Tuming with a new Benchmark .
3. Move the tripod to its new position, set it up and level it.
4. Take a reading of the benchmark from the new position and record it on Form
F-i 0. Then continue to measure the elevations of the sampling points.
Turning with a New Benchmark
If the original benchmark is not visible from the new tripod position, a new
benchmark must be established, It is important to take and record a final reading of
the first benchmark and a reading of the new benchmark BEFORE MOVING THE
TRIPOD. This enables the new TM eye level plane 0 to be correlated with the previous
one, so that elevations read after the tripod is moved will correspond to those read
earlier. The procedure is:
1. Record the elevation of the original benchmark.
2. Determine the new benchmark and record its elevation.
3. Move the tripod to its new position, set it up and level it.
4. Take another reading of the new benchmark and record it. This reading gives
you the new eye level plane.
5.. Continue to record the elevations of the remaining sampling points.
Adjusting the Eye Level Plane
If only one benchmark was required, the elevations calculated from
me surements made after moving the tripod must be correlated with those
measurements made before moving the tripod.
I. Determine the difference between the benchmark readings by subtracting the
smaller reading from the larger. For example, the last reading of the
benchmark before the tripod was moved was 5.15 m. The elevation
measurement of the benchmark after the tripod was moved was 3.74m. This
means the tripod was moved 1.41m downhill (5.15 -3.74 = 1.41.). The new
eye level plane is 1.41m lower than the first (Figure 7-2a).
108
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Rod
Stadia Rod
Figure 7-2. A Adjusting the eye level plane when only one benchmark is required for making
a turn. B. Adjusting the eye level plane when more than one benchmark is
required to make a turn.
A.
of sight
15m
3.74m
Station B (stump)
Station A
B.
Stadia Rod
6.32m
Tripod
Station A
1
(stump)
Benchmark 2
(stump)
Station B
109
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2. Adjust the relative elevations of the sampling points measured after the tripod
was moved by adding 1.41m to each.
If more than one benchmark is required, the procedure for adjusting your eye
level plane is:
1. Calculate the difference between the last reading of the original benchmark and
the reading of the new benchmark taken before moving the tripod . For
example, the last reading of the original benchmark was 5.15m. The reading
for the new benchmark is 4.04m. Therefore, the elevation of the new
benchmark is 1.llm higher than the original benchmark (5.15 -4.04 = 1.11).
2. Calculate the difference between the readings taken of the new benchmark
before and after moving the tripod. For example, the reading of the second
benchmark after moving the tripod is 6.32m. This means that the new eye level
plane is 2.28m higher than the previous plane (6.32 - 4.04 = 2.28) (Figure 7-
2b).
3. When calculating relative elevations for the site, the change in eye level plane
must be considered. Using the example above, 2.28m must be subtracted from
each calculated relative elevation measured after the turn .
110
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S. SOIL AND HYDROLOGIC CHARACTERIZATION
Because soil and hydrologic conditions are central to the occurrence of
wetlands, characterization of soil and hydrologic attributes is essential for
understanding and documenting differences in structure and function of wetland
populations. Hydrology represents the ultimate driving force for the establishment and
maintenance of wetlands (Mitsch and Gosselink 1986) with soils providing the physical
environment in which, and through which, hydrologic and biogeochemical processes
are mediated. Soils both reflect and influence a variety of wetland processes, such as
water and gas exchange, microbial processes, establishment and growth of
vegetation. The presence, at least seasonally, of standing water or saturated soils in
the rooting zone is vital to biogeochemical processes related to wetland development
and to technical determination of wetland occurrence (FICWD 1989). Water impedes
the transfer of gases, including oxygen, between air and the soil; as a result, microbial
respiration depletes soil oxygen, leading to development of anaerobic conditions,
reductions in the soil oxidation-reduction (redox) potential, and generation of
phytotoxic compounds such as hydrogen sulfide and reduced species of manganese
(Mn 2 ). The end result is an environment in which establishment and growth of
vegetation is limited to hydrophytic species that have structural or physiological
adaptations that allow them to tolerate reducing conditions in the rooting zone.
Characterization of soils and hydrology in the OWS is intended primarily to
provide a quantitative description of the nature and variability of these attributes within
the study wetlands. The analyses described in this section will address all of the
major study questions identified in the Study Overview (Table 1-1), except for those
that focus on trends in direct loss of wetlands through permitted destructions and other
conversions. Soil and hydrology data will be used to assess differences among study
wetlands (i.e., natural systems vs. wetland projects, natural wetlands in different land
use settings), to assess the development of wetland projects through time, and to
support development of design guidelines and performance criteria for wetland
projects. The data will also be important for documenting the occurrence of wetland
hydrology and presence of hydric soils, and will be used in efforts to characterize
relationships between wetland soils, hydrology, and other wetland attributes,
particularly vegetation.
In designing soil and hydrologic analyses, and in selecting field and laboratory
methods, it is important to consider 1) how land uses might be affecting specific
structural and functional attributes of wetlands, and 2) how projects are likely to differ
from analogous natural systems. Ideally, characterization and sampling would include
a diverse suite of characteristics to quantify structural and functional attributes of
wetland soils and hydrology, and sites would be visited repeatedly to define temporal
variability of dynamic attributes. Because of logistical and fiscal constraints, most field
sampling in the OWS will be conducted during a single visit to each wetland, and soil
and hydrologic analyses will be limited to a minimum set of attributes required to
address project goals. We will not characterize attributes that are highly time variant,
and will not assess time-integrative functions such as nutrient retention. A
complementary field study will, however, be conducted to intensively monitor hydrology
and quantify sediment accretion in a subset of approximately 40 study wetlands.
111
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Table 1-2 identified the wetland attributes selected for characterization and
sampling in the OWS, along with a rationale for their inclusion and identification of
study questions supported by the characterization of each attribute. Soil and/or
hydrologic data will be particularly important in addressing specific aspects of several
study questions, as described below.
For wetlands located in different land use environments, there are likely to be
significant differences in wetland hydrology due to anthropogenic alteration of runoff
patterns (flood frequency and magnitude, maintenance of base flow) (Leopold 1973,
Dunne and Leopold 1978). Land uses, especially those related to agriculture and
development, are associated with increases in surface runoff and soil erosion, in turn
affecting wetland soils through increased rates of sedimentation (Dunne and Leopold
1978, Martin and Hartman 1987) and associated changes in loadings of nutrients,
pesticides, and toxics (Neely and Baker 1989). We will address these effects through
partial characterization of soils and static measures of hydrology in all study wetlands,
and will measure them directly through monitoring of a subset of sites. We will also
look qualitatively at the relationships between vegetated buffers and soil and
hydrologic attributes.
Differences between soils in natural wetlands and wetland projects have been
widely reported (e.g., Shisler and Charette 1984, D’Avanzo 1991, Zedler and Laigis
1991, Confer and Niering 1992) and were documented in the Oregon Pilot Study
conducted by the WRP in 1987 (Kentula et al. 1992). Substrate conditions are an
important factor in the ecological development of projects, as they influence the
physical, hydrclogic, and nutrient requirements of vegetation (Langis et al. 1991,
Levine and Willard 1991, Zedler and Weller 1991). Characterization of wetland soils
will be important for evaluating quantitative differences between soils of natural
wetlands and wetland projects, and for evaluating the rate of development of attributes
such as organic content, gleying, mottling, etc. in soils of projects characterized during
1987. These data will also be useful in assessing whether there have been changes
in the design or implementation of projects completed since 1987 that have improved
the nature of soils and/or the rate of soil development.
Comparisons of natural wetlands and projects will also include comparisons of
hydrologic attributes such as depth of standing water and percent open water.
Several studies have noted differences in hydrology between natural wetlands and
projects (e.g., Owen 1990, Erwin 1991, Confer and Niering 1992), and hydrology (e.g.,
hydroperiod, water level) has been identified as a key determinant of success in the
establishment and persistence of wetland projects (D’Avanzo 1991, Erwin 1991, Kusler
and Kentula 1991). Hydrologic data will be used to evaluate the continuing
development of old (pre-1987) projects and assess improvements in design and
implementation of post-i 987 projects. Hydrologic and soil data for wetland projects
will also contribute to evaluation of compliance with any permit/design specifications
that involve soils or hydrology.
An additional goal of the OWS is to identify and quantify relationships between
soils, hydrology, and other wetland attributes, especially vegetation. Improving our
understanding of these relationships has been identified as an important need in
improving the design and implementation of future projects (D’Avanzo 1991, Kusler
and Kentula 1991, Levine and Willard 1991, Zedler and Weller 1991). Vegetation,
112
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basin morphology, hydrology, and soils will be sampled in the same plots to facilitate
these kinds of analyses.
In the following section, the strategy and detailed field methods used for field
sampling for soil and hydrologic analyses are presented. Laboratory methods for
analysis of soil organic matter content (loss on ignition) and copies of data forms for
field and laboratory data collection are also included.
FIELD METHODOLOGY
Soils will be sampled and characterized on a randomly located set of plots in
each wetland; plot selection protocols are designed to provide characterization of a
representative sample of soils in each wetland. A total of 15 plots will be described
and sampled in each wetland, three on each of the five Site Characterization
Transects.
Figure 8-1 provides a 110w chart showing the sequence of field sampling
activities to be used. Copies of data forms for field and laboratory data are provided
as Figures 8-2 and 8-3. Based on the presence/absence of standing water and an
evaluation of soil conditions, one of several alternative soil sampling procedures will be
selected. Sampling at each plot will include three types of data collection:
1. Visible soil physical characteristics, such as horizon depths, color, and presence
of anthropogenically-introduced materials will be described. If possible, soil pits
will be excavated to a depth of 0.5m, alternatively soils will be sampled using a
core sampler, bucket auger, or manually;
2. Soils from two depth intervals (0-5 and 15-20cm) will be sampled and returned
to the laboratory for analysis of organic matter content;
3. A limited amount of hydrologic information will be collected. At soil plots with
standing water, the depth will be measured; at plots without standing water,
depth to saturated soils and to the free water surface (if they occur at a depth
of < 50cm) will be determined.
General Considerations In Soil Descriptions and Sampling
1. Sampling and Characterization will be conducted by the Survey Team. Teams
include three members with interchangeable duties. Soil sampling and
characterization will be done concurrently with measurement of basin elevations
and water depths along Site Characterization Transects.
2. Soil sampling — digging of pits, sampling of soils, and characterization -- must
not be done until after the Vegetation Teams have completed all activities on a
plot, to avoid trampling and other disturbance of vegetation.
113
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Flow Chart -- SoivHydrology Field Sampling
Are vegetation analyses complete?
[ Proceed to next plot
ocessary
esence and d
of standing water
Is standing water present?
Yes No
sa m pie u sing corer 50cmdee
Evaluate soil conditions attempt
bucket auger, or manual core tube
5cm diameter
Excavate clean slab
_________ _____________ of soil
If manual corer,
seal and label tube
________ ___________ Measure depth to standing
water, saturated soil, and
i If corer or bucket auger, describe I free water surface; record time
soils as completely as possible I
Describe soil horizons (depth,
color, mottles, gleylng, etc)
Collect soil samples from
0-5, 15-20cm depths
After completing soil sampling,
remeasure depth to standing water
tore sample for return to lab, verify that
____ [ fo s are complete filled o
Figure e-i. Flow chart showing sampling options and the sequence of field sampling
activities for characterization of soil and hydrologic attributes.
114
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OREGON WETLANDS STUDY -SUMMER 1993
FORM F-i 1 Soil/Hydrology Characterization
Site Naine&Code___________________________
Crew_________________________
Page of____
Date__________
Transed #____________________ County____________
Personnel
Samples should be labelled wIth an eleven digit code Including wetland H (characters 14), Transect H (5-6), Plet H (7-8), Depth (9-10). and sample
type (1 for Routlne 2 for QA Duplicate) Also Include a sampling date FEW (<2% Surface). COMMON (2.20%), MANY (>20%)
FINE (<5mm dllameter). MEDIUM (5-15mm), COARSE (>15mm)
U i
-V
•
Hydrology
Soil Description
0
ia
‘
.
.
2
— .
.
4
2
EEEE °1I
c
.
..
C)
Mottles___
-- .
z
.2
!
C
—
2
COrTwnents
(eg.presenceofrodcs.
woody material, burled
m
Figure 8-2.
Form F-i 1, used to record field data for soil and hydrology.
-------
OREGON WETLANDS STUDY - SUMMER 1993 Page of___
FORM L-1 Determination of Soil Moisture Content and Loss on ignition Date____________
Batch #_________ Drying Oven Temperature_________ Date/time in____________ Analyst Initials__________
Date/time out__________ Analyst initials_________
Date Weighed_________ Analyst Initials_________
Muffle Furnace Temperature Date/time in____________ Analyst Initials__________
Date/time out________ Analyst Initials________
Date Weigh ed_ Analyst Initials_________
Sample
Sample
Crucible
TARE_WT
FRESH_WI
DRY_WI
ASHED_WT
Moisture
Loss on
#
Code
#
(g)
(g)
(g)
(g)
%)
Ignition (%)
0
Comments:
Figure 8-3. Form L-1; used to record laboratory data for analysis of soil orgranic content (Loss on Ignition).
-------
3. All measurements will be reported in metric units - centimeters and meters.
rather than inches and feet. All depth measurements are made from the
ground surface, below living vegetation or litter.
Equipment and Supplies
Field data sheets - Form F-i 1 (5 copies per wetland)
Soil sample bags (2 per plot, with labels)
Pencil and waterproof marking pen
Sharpshooter shovel
Bucket auger
Core samplers
Core sampler liners and caps
Knife, with long blade
Munsell color chart with gleyed color page
Two 0.5m rulers (or cut down meter sticks)
Ice chest with ice and rack to hold sample tubes
Squirt bottle for water (filled with clean water)
Paper towels
Handi-wipes (or equivalent) for cleaning hands and equipment
Field Sampling Procedure
Soil sampling will be the final activity conducted by the Survey Teams at each
Sample Point. Notify the Crew Leader if there are questions or problems associated
with any of the soil sampling activities. Soils will be described and sampled at three
locations on each of the five Site Characterization Transects.
1. At the start of each transect, determine the number of plots on the transect.
Identify three of the plots for soil sampling using random numbers provided by
the Crew Leader. Record the three plot numbers on Form F-i 1, and
characterize soils and hydrology on only those plots.
2. Fill out the heading information at the top of Form F-i 1.
3. Upon completion of sampling by the Vegetation Team on the transect, locate
plots for soil sampling during the pass along the transect to measure elevations.
4. Depending on soil and water conditions at the plot, soils may be sampled by
excavating a pit, using a bucket auger, or by using one of two types of coring
devices. The choice of sampling procedures is discussed below. One of four
alternate procedures will be used to sample soils on each plot. For samples
collected from a soil pit (Procedure A) or using a bucket auger (Procedure C),
collect 75-100 grams of soil to insure that there is adequate material for lab
duplicates or reanalysis (if necessary).
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5. Label sample containers -- two bags for each plot if soils will be collected from
a pit or using a bucket auger; a single label for core tubes. Be certain that
labels are written using pencil or waterproof ink, and double check to be certain
that all information on the labels is correct. Sample bags should be labelled as
described below; cores labels will be the same, except that U99U should be
entered on the form for sample depth, and the entire depth interval represented
by the core should be recorded separately. Each sample should be labelled
with the sampling date and an eleven digit code that includes:
• characters 1-4 — wetland number
• characters 5-6 — transect number
• characters 7-8 — plot number for each transect
• characters 9-10 -- depth (lower limit of sampling interval, i.e., 5 or 20 cm)
• character 11 -- sample type (1 for routine, 2 for a field duplicate (QA
sample), 9 for other (note in comment field))
As an example, 2253-05-02-05-1 would be the code for a sample taken from
wetland 2253, transect 05, plot 02, depth 05 cm, for a routine sample (code 1).
Note that transect numbers and depth should be right justified, with a zero in
any extra space.
6. After completing soil sampling on each plot, check to be certain that data forms
have been completely filled out and are legible, and that samples are properly
labelled (see code in step 5). Information on water depths in soil pits will only
be filled in for plots where pits are dug; color and presence/absence of
hydrogen sulfide will not be determined for samples collected using a coring
device. Be sure to note deviations from routine procedures, problems with
equipment or supplies, etc. Notify the Crew Leader if you have questions or if
there are problems with sampling or equipment.
7. After completing soil sampling on each plot, clean all equipment to prevent
contamination of soils on subsequent plots.
8. After completing each transect, replenish supplies as needed, and place
samples in a cooler for return to the laboratory. Core tubes should be handled
as carefully as possible to avoid mixing or other disturbance, and should be
placed in a rack in the cooler. Samples should be frozen as soon as is
practical, and should remain frozen until laboratory analysis.
Upon arrival at each plot, determine whether standing water is present. If water
is not present, follow the instructions for Procedure A. If standing water is present,
enter usuliacen in the space for depth to standing water on Form F-i 1, and select one
of the alternate sampling procedures. For plots with standing water, there are three
alternatives for soil sampling (in order of preference, corer, bucket auger, manually
collected core). The choice among these ultimately is subjective, and depends on the
nature of the substrate, presence and density of roots, etc.
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Evaluate soils on the site -- how dense is the material, how well consolidated, how
much coarse material (stones, woody material, heavy roots or rhizomes, etc.) is
present. The preferred alternative is to use the core sampler (Procedure B). In soils
that are compacted, contain coarse materials (e.g., rock fragments, woody material),
or are heavily ingrown with roots, it may be necessary to sample using a bucket auger
(Procedure C). Finally, in wet, unconsolidated soils, it may be necessary to manually
insert a core tube in the soil and cap both ends before removing it from the soil
(Procedure D). Note the type of sampling device used on Form F-il. For all
sampling procedures, if a rock, log or other impenetrable material, move 6-8 inches to
the left along the transect and make a second attempt to collect a sample.
Procedure A Excavation of soil pit
1. Excavate a pit approximately 25-cm wide and 50-cm deep. Using the knife,
carefully clean the soil on one face of the pit to remove plant tissue, soil
transferred from other depths, etc. Note that in some cases, a rock, log, a
cemented horizon, or similar impenetrable material may be encountered at a
depth of <50cm. In such instances, excavate the pit as deep as possible,
describe and sample soils as the depth of the pit allows, and note the
occurrence and depth to bedrock or the cemented horizon.
2. Using the sharpshooter shovel, excavate and remove an intact slab of soil from
the clean pit face. Lay the shovel and slab carefully on a clean sheet of plastic.
If the presence of water in a pit precludes sampling of a slab of soil to the 50cm
depth, excavate a slab as deep as is practical; if necessary, sample subsoils
using a corer or bucket auger as described in Procedures B and C.
3. If the pit contains standing water, measure the depth to the water surface; note
the depth and time in the space for initial depth to standing water on Form F-
11. If no standing water is present, enter IINPU (not present).
4. If soils at the margins of the pit are saturated with water, record the depth to
the saturated layer. Saturation will be indicated by a sheen or glistening of the
soil. At or below the depth of soil saturation, water may also be oozing from
the soil into the pit. On Form F-i 1, record the depth to saturation and to the
free water surface (where there is flow of water).
5. Carefully examine soils in the pit and in the excavated slab; identify and
describe pertinent features in each horizon on Form F-i 1, including:
• presence of, and upper and lower depth for, each soil horizon. Horizons
will be identified by changes in soil color and texture.
• the size, nature, and abundance of stones, gravel, woody material, etc.
in each horizon;
• presence and abundance, in each horizon, of mottles, gleyed soils, iron
and/or manganese concretions/stai ns;
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• color of the soil matrix and of mottles in each horizon (using the Munsell
color chart);
• presence and abundance of living roots and oxidized root channels;
• presence of hydrogen sulfide. At several depths in each horizon where
there is evidence of reducing conditions (e.g. gleying, mottles), remove a
small piece of soil from the pit (or excavated slab); crush it between
thumb and forefingers and smell it to determine whether hydrogen sulfide
(rotten egg odor) is present. Note depths at which hydrogen sulfide is
present;
• presence and nature of any additional natural or anthropogenic features
in any horizon (or at any discrete depth). Examples might include a
buried horizon or buried organic material, presence of straw or other
introduced organic material.
6. Using a clean knife, remove any foreign material (bits of vegetation, etc.) and
carefully sample soils from the slab at two depths — 0-5 and 15-20cm. Each
sample should be representative of material for its respective depth interval.
Place each sample in a clean, pre-labelled bag. Check labels to verify that the
code for each sample is complete and correct. Wipe the knife clean between
samples.
7. 30 minutes after completing sample collection and description, remeasure the
depth to standing water in the pit; record the depth and time in the space for
final depth/time on Form F-il.
8. Check to be certain that all information has been recorded on data forms; return
the excavated slab to the pit; refill the pit and replace vegetation.
Alternate Procedure B. Core sampler
Detach the corer handle, and place a clean tube in the corer and reattach the
handle. Fill out and verify information on a data label (i.e., the sample
identification including wetland, transect, and plot numbers) prior to sample
collection.
2. Remove litter and live vegetation from the soil surface (cut at ground level so
vegetation will not contaminate sample soils; do not remove roots).
3. Insert the corer into soil as deeply as possible (but not more than 50 cm).
Minimize disturbance to material in the core due to lifting, tipping, or twisting of
the corer during sampling.
4. Withdraw the sampler, remove the handle and attach a cap on the upper end of
the tube, then withdraw the core tube and carefully place an end cap on the
lower end of the tube. Wipe the sides of the tube clean, and examine the tube
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contents. If the tube shows evidence of signilicant disturbance during sampling,
discard the sample and repeat sample collection.
5. If the integrity of the sample in the tube is satisfactory, describe, as completely
as possible, horizon depths, presence of gleying, mottles, etc. in step 5 of
Procedure A Colors determined for materials through the core tube may not
be reliable, so do not spend time trying to determine color for these samples.
Attach the sample label, and record the depth interval for the core on the
sample label arid in the space for comments on Form F-i 1.
Alternate Procedure C. Bucket Auger
1. Remove vegetation from the soil surface (cut at ground level so vegetation will
not contaminate the sample; do not remove roots).
2. Use the auger to collect a sample from the 0-5 cm depth, and place it in a pre-
labelled bag.
3. Auger a second hole to a depth of 20 cm, remove the auger and soil from the
hole, and carefully extrude the soil onto a clean piece of plastic. Separate
material from the 15-20 cm depth interval, and replace material from other
depths in the hole. Recognize that sampling may distort the depth of the
extruded material (by compaction during sampling or crumbling of material
when it is removed from the auger); if this occurs, estimate the depth as well as
possible arid make a note in the comment field on Form F-i 1.
4. Remove stones, roots and other foreign matter, then place a sample in a pro-
labelled bag.
5. Using the auger, dig a third hole in the soil to a depth of .5Ocm; remove the
soil and auger and carefully lay soil on a sheet of clean plastic. Clean the
surface of the sample to remove vegetation and soil from other depths, and
describe the occurrence, depth, and characteristics of soil horizons as
described in step 5 under Procedure A Replace soil in the hole after
completing the description.
Alternate Procedure D. Manual core collection
1. Sample material by manually inserting a core tube into the soil to a depth of 25
cm (or as deep as possible if less than 25 cm).
2. Cap the top of the core, then reach into the soil/sediment and place a second
cap on the lower end of the tube. Insertion and capping should be done in
such a way as to minimize disturbance of the soil column that might cause
disruption and mixing of the soil.
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3. Carefully remove the core from the soil, with a minimum amount of tipping or
twisting of the tube.
4. Prepare a label for the core; record the depth interval for the core on the
sample label and in the space for comments on Form F-i 1.
LABORATORY ANALYSIS - LOSS ON IGNITION
This section describes the laboratory procedure used for determination of soil
organic matter content. The procedure is based on combustion of a soil sample in a
muffle furnace at 4500 C, with organic matter content determined by weight loss of the
sample. The procedure is adapted from USDA (1984) and Blume et al. (1990).
Equipment and Supplies
Balance, weighing to 0.01 g (preferably to 0.001 g)
Drying oven (in operating exhaust hood)
Muffle furnace (in operating exhaust hood)
Desiccator (needed only if samples will not be weighed as soon as removed
from the muffle furnace and allowed to cool to room temperature)
Sieve (#10 mGsh, 2.00 mm opening)
Furnace gloves
Tongs
Forceps
Small crucibles or (preferred) disposable aluminum weigh dishes (Ca 2”
diameter by 0.5” high)
Data Forms L-1 and L-2, log book
Rubber gloves (disposable)
Munsell color chart with gleyed color page
General Considerations for Laboratory Analysis
1. Calibrate the balance according to routine good lab practices. The balance
should be leveled and calibrated using standard weights at the start of
analyses, at least weekly thereafter, and any time the balance has been moved
or disturbed. Record calibration results in a laboratory log book.
2. Place the drying oven and muffle furnace in an operating exhaust hood if
possible, to insure that moisture and objectionable odors (from e.g., H 2 S,
organo-sulfur compounds) are not vented into the lab. Check temperatures for
drying oven and muffle furnaces regularly; ovens should be calibrated or
temperature settings adjusted to insure that samples are dried at the proper
temperature. Record information on calibration of the oven temperatures in the
log book.
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3. If possible, process cores and soils in an exhaust hood or other well-ventilated
area to insure that objectionable odors are not vented into the lab.
4. If part of a sample is spilled, or if material spills into any of the weighing dishes
or crucibles, discard the sample(s), and repeat the entire procedure using a
second aliquot of the sample.
Laboratory Analysis Procedure
Soil samples will be processed in the lab in batches; each batch will include
both routine and QC samples (blanks, audit samples and duplicates). The number of
samples in each batch will depend on the size of the muffle furnace. Number samples
with the batch number, and a sample number for tracking during laboratory and data
analysis. Mark the batch and sample numbers on the soil sample containers, and
record the batch, sample number, and soil identification (wetland and transect number,
etc.) for each sample in a log book. Processing dates for each soil sample will also
be recorded in the log book.
1. Thaw frozen soils; allow materials in bags to thaw completely. For material
frozen in core tubes, thaw the outer layer of the sample (in the tube) by briefly
holding the tube (with end caps still attached) under warm running water, then
slide the core from the tube onto a clean sheet of plastic or a clean tray.
Quickly and carefully slice the 0-5 and 15-20 cm depth segments from the core,
place them in separate, labelled sample bags and allow them to thaw
completely. Discard unused portions of the core. For samples collected using
a corer, record sample identification, presence of hydrogen sulfide, and color on
Form L-2 (Figure 8-4).
2. Carefully remove stones, twigs, live roots, invertebrates (insect larvae, snails,
etc.), and obvious foreign materials (e.g., plastic or metal fragments) from each
sample. Wear clear rubber gloves and use forceps to avoid contamination of
the samples.
3. Sieve soil, using a 10 mesh (2.0mm) sieve, to remove rock fragments, wood
chips, and other materials >2 mm in size. For wet soils, materials will probably
need to be gently pushed through the sieve; this can be done using a spatula
or your fingers (wear rubber gloves). Clean and dry the sieve between
samples.
4. Material passing through the sieve should be mixed thoroughly to homogenize
the sample, and placed in a clean, labelled storage container.
5. Number and pre-weigh crucibles or disposable aluminum weigh boats.
Numbers MUST be applied using a type of marker that will not be obliterated by
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OREGON WETLANDS STUDY - SUMMER 1993
Form L-2 Soil Core Characterization
Analyst Name Date
Sample_Identification
— — Soil_Description — —
2 2
wW
4)
Comments
,
.
.
.
I
.C
Comments:
Figure B-4. Form L-2; used in the laboratory to record supplemental soil data for soils
sampled using a coring device.
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heating or otherwise leave a legible sample code on the container. Record the
container number and tare weight (weight of the empty container) for each
container on Form L-1.
6. Fill containers approximately two-thirds full of fresh soil (10-20 grams). Record
the sample identification and the weight of container plus soil (FRESH_Wi) on
Form L-1. Excess sample matenal will be saved for possible reanalysis. If all
of the soil for a particular sample has been used, make a note in the log book
and discard the container.
7. Place containers in a drying oven and dry overnight (>12 hours) at 105°C. Cool
containers to room temperature and weigh immediately upon cooling. Samples
should be stored in a desiccator if they cannot be immediately weighed.
Record the time samples are placed in, and removed from, the oven on Form
L-1, and record the weight of containers with dried soil under “DRY_Wr on
Form L-1.
8. Carefully place containers in a muffle furnace (at < 100°c). DO NOT attempt to
place samples in a hot furnace; materials with high organic content are likely to
ignite. Set the temperature at 450°C and turn on the oven; samples should be
held at 450°C for at least 2 hours, but can be left longer (e.g., overnight) if
convenient. Record the time samples are placed in the muffle furnace.
9. Turn off the furnace and remove weigh containers and remaining soil. Record
the time samples are removed from the muffle furnace. Place containers in a
desiccator until they have cooled to room temperature. Weigh samples
immediately upon removal from the desiccator, and record weight under
‘ t ASHED_WT’ on Form L-1. Allow the furnace to cool to < 100°C prior to
refilling with a new set of containers.
Calculations
If disposable dishes are used, blanks should be used to check weight changes
in the aluminum dishes. During heating to 450°C, weights sometimes may increase
by 0.01-0.02 g as a small amount of aluminum is oxidized. If such changes are
observed, sample weights should be adjusted accordingly, by subtracting the average
change in the weight of blanks from the HASHED_WTU of each sample.
Moisture content is reported as a percentage of fresh sample weight; loss on ignition
is reported as percentage of oven-dry (105°C) weight. Compute moisture content and
loss on ignition as follows, and record on Form L-1.
Moisture content = ((FRESH_WI - DRY_Wi) * 100%) / (FRESH_WT - TARE_Wi)
Loss on ignition = ((DRY_WI - ASHED_WT) * 100%) / (DRY_WI - TARE_Wi)
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9. EXISTING DATA
Existing data, combined with data collected during the OWS, will be used to
address study questions 1, 2, and 6 (Table 1-1). Study questions 1 and 2 relate to
identifying trends in direct wetland loss, and study question 6 relates to evaluating
compliance with permit specifications and establishing criteria to improve project
design.
TRENDS IN DIRECT WETLAND LOSS
Existing data and data collected during site selection will be used to determine
the cause and rate of direct loss of freshwater palustrine wetlands that range from
sites dominated by open water to those dominated by emergent vegetation. This will
be accomplished by: 1) comparing the most recent inventory based on NWI maps with
a current inventory performed as part of site selection, and 2) documenting the
reasons for wetland conversion identified during the current inventory (i.e., visual
observations made during the 1992 field reconnaissance) (Figure 1.2). The number
and type of wetlands destroyed since the NWI maps were produced will be
documented, as well as the current land use in the location of the previously existing
wetlands. For example, if a natural wetland identified on the NWI map had been
destroyed, and a shopping mall was now in that location, the cause of the wetland
loss would be documented as commercial development.
Existing data were obtained from three sources: 1) U.S. Fish and Wildlife
Service, NWI; 2) Washington , Clackamas, and Multnomah county tax assessors; and
3) METRO. METRO acquired NWI digital data on wetland type, size, and location in
the Portland Metropolitan area from the U.S. Fish and Wildlife Service, and land use
data in the Portland Metropolitan area from Washington, Clackamas, and Multnomah
County tax assessors. The data were transferred to a Geographic Information System
and used to create a color-coded map representing both the NWI and land use data.
This map was used to identify and locate natural wetlands during site selection.
COMPLIANCE OF AS-BUILT CONDITIONS WITH PERMIT SPECIFICATIONS
Study question 6 (Table 1-1) is designed to broaden the information base on
wetland creation and restoration by examining wetland projects of a certain size and
typ e in the context of similar wetlands in the region. Completed projects will be
studied to determine compliance with permit conditions and design specifications,
develop design guidelines, and support the establishment of performance criteria.
Information will be collected from construction plans and permit files and will be
compared with quantitative measurements made during field sampling.
For the wetland projects included in this study, data describing project
specifications will be collected from Section 404 and Oregon Removal-Fill Permit files
maintained by the Oregon Division of State Lands (ODSL) in Salem, Oregon. In
addition, project construction plans, blueprints, and conceptual drawings will be
requested from the contractors responsible for construction of the wetland projects.
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10. DATA MANAGEMENT
The purpose of the Data Management section is to discuss the techniques used
to help ensure data quality. This is a general discussion only, and therefore limited in
technical detail. The EPA is charged with the responsibility of providing environmental
data for use in policy and policy enforcement decisions. To meet this responsibility,
the Agency requires that data quality must be both known and defensible. Data
quality can be improved by the proper use of a computerized dual data entry system.
a process in which two people enter, compare, and reconcile two data sets. By
finding and correcting differences between the data sets, data entry errors are
minimized. Data analysis can be conducted with confidence that the data sets reflect
the actual data collected during field sampling. Dual data entry is fundamental to data
management for the OWS.
TERMS USED
DATA SET is used to describe the collection of databases that represent each
variable measured in the study. For example, for measures of vegetation
characteristics, data from each transect from a site are represented by a database.
All the databases for each variable measured in the study are used to form the data
set.
FILENAME refers to the name that identifies a computer file that is used to
store data.
A DATABASE is a file, or a group of files used to store related information (e.g.
the vegetation data for a transect). The information is stored in records and data
fields.
A RECORD is a row of fields that represent an entity kept as a unit In Figure
10-1, an example of a record from a vegetation database.(RECORD.RGG), has been
highlighted. It is made up of the data fields, Genus I Species Name, Code, Ploti,
Plot2, Plot3, and Plot4.
A DATA FIELD is similar to a column. Each data field represents an individual
data item in a record (Figure 10-2).
A KEY FIELD is a data field(s) used to uniquely identify each record in a
database (Figure 10-2).
USER refers to the people who will enter and operate the dual data entry
program.
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Genus/Species Name - Code Ploti PIot2 PIot3 PIot4
Parentucellia viscosa f-i281 0101 1.0 1.0 0.0 0.0
Potentilla pacifica o/n1450101 2.0 1.0 1.0 0.0
/ /h0530102 25 O “2 ‘ O O
Salix sp. a ‘ 07301 02 1.0 0.0 2.0 0.0
Juncus ensifohus w/n05301 05 1.0 0.0 0.0 0.0
Juncus bufonius w+n0530103 15.0 60.0 10.0 10.0
Peplis portula w1i2360101 1.0 0.0 0.0 0.0
Juncus acuminatus o/n05301 01 1.0 5.0 5.0 0.0
Plantago major f4-i29301 02 0.0 1.0 1.0 0.0
Hypochaeris radicata p/i3040401 0.0 1.0 0.0 0.0
Alopecurus geniculatus w+n0360201 0.0 5.0 0.0 0.0
Juncusfalcatus w-n0530106 0.0 3.0 0.0 0.0
Ranunculus repens wTi l 0901 01 0.0 1.0 0.0 0.0
Eleocharis palustris o/n0370202 0.0 1.0 10.0 1.0
Callitriche stagnalis o/n1680101 0.0 1.0 1.0 0.0
Hypericum anagalloides o/n20701 01 0.0 1.0 0.0 0.0
Lotus cornicu atus f/ il 470201 0.0 1.0 0.0 0.0
Carex sp. a 03701 04 0.0 2.0 1.0 0.0
Glyceria borealis o/n0360501 0.0 0.0 1.0 0.0
Note: The vegetation database above was taken from a previous field study, and
is not intended to represent the layout to be used in the OWS.
Figure 10-1. Example of a record from a vegetation database.
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Genus/Species Name Code Ploti Plot2 Plot3 Plot4
Parentucellia viscosa f-128101 01 1.0 1.0 0.0 0.0
Potentilla pacifica o/n1450 101. 2.0 1.0 1.0 0.0
Juncus articulatus o/ri0530102 25.0 20.0 0.0 3.0
Salix sp. a 0730102 1.0 0.0 2.0 0.0
Juncus ensifolius w/n05301 05 1.0 0.0 0.0 0.0
Juncusbufonius :0530103 15.0 60.0 10.0 10.0
Peplis portula .w/i2360 101 1.0 0.0 0.0 0.0
Juncus acuminatus on0530101 1.0 5.0 5.0 0.0
Plantago major 1 + 12930.1%:.: 0.0 1.0 1.0 0.0
Hypochaeris radicata p1 i3O 4 Q4O 0.0 1.0 0.0 0.0
Alopecurus geniculatus :.w+nO3602O1::.:. 0.0 5.0 0.0 0.0
Juncusfalcatus w-n0530106 0.0 3.0 0.0 0.0
Ranunculus repens wT i l O9O l O l 0.0 1.0 0.0 0.0
Eleocharis palustris o/n0370202. 0.0 1.0 10.0 1.0
Callitriche stagnalis o/n 168010 1. 0.0 1.0 1.0 0.0
Hypericum anagalloides o/n2070101 0.0 1.0 0.0 0.0
Lotus corniculatus iJi147O20 0.0 1.0 0.0 0.0
Carex sp. a : ** O37O1 04 0.0 2.0 1.0 0.0
Glyceria borealis 0.0 0.0 1.0 0.0
Note: The vegetation database above was taken from a previous field study, and
is not intended to represent the layout to be used in the OWS.
Figure 10-2. Example of a key field in a vegetation database.
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DATA ENTRY
A dual data entry program will create two identical data sets that will be used to
reconcile field sheet and data entry errors. The duplicate data sets will be entered by
separate users. Reduction in the number of initial data entry errors will be achieved
by employing three techniques: Lockup tables, Range value checking, and a
Duplicate key field check.
Lockup tables allow the user to select an item from a list. The user enters the
first two characters of the genus name to get a list of possible choices. The user then
selects the appropriate genus/species name from this list, eliminating the need to type
in the name and code. For example, if the user types the letters M TR , the list of
genus/species names, found in Figure 10-3 would appear. If the user selects one of
the names the program will enter the selected name and code in the current file. If a
genus/species name is not found in the master species list file, the user will be
prompted to enter the species name from the form. The program will then add the
name to the master species list and assign a temporary code. At the conclusion of
the data entry process, the master species lists from both data sets will be copied to a
floppy disk. Both lists will be reviewed, compared and reconciled by separate
individuals. After the master species list has been validated, the dual data entry
program will be used to update all the vegetation files in both data sets with the
correct genus/species name and code.
Range value checking is used to set acceptable limits for an entry in a field.
For example, the range of acceptable values for WATER DEPTH is 0 m to 6 m. If a
value outside this range is entered, a warning message is displayed and the user is
prompted to check the entry for a probable error in data entry and to make any
needed corrections.
Another data entry problem is that of duplicate key fields. Key fields must be
unique because they identify each record in a database. This error can occur in one
of two ways:
1. The user tried to enter the same record twice.
2. The key fields that identify each record were entered more than
once on the form.
To eliminate this problem, the dual data entry program will be designed to check the
key fields as they are being entered to make sure that they are unique to the file. If
the user is trying to enter an existing key field the program will display a warning
message so that the cause of the problem can be determined.
RECONCILING THE DATA SETS
The comparison and reconciliation of the data sets will begin once entry of the
duplicate sets has been completed. This is done to identify and correct errors in the
data. The process has two parts: comparison and correction.
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[ Fl] = Help [ F2] = Notes I FILENAME: VO5OT5C
NAME CODE PLOT1 PLOT2 PLOT3
Vicia sativa p\i21 0605 3.5 7.4
Holcus lanatus 1\n602101 4.2 3.0
Rubus discolor u-i201 001 18.3 .5 .4
Geum macrophyllum w-i-n200301 .5 10.3
Stachys coolyeyae o\n590118 . 1.4 4.6 3.8
( FtI Hetp [ Esc1 Ex1t
‘tea e enter the first Iwo
letteI!s ctttia L en js name ITrI rIfollum hybridum
rifohum pratense
rifoliumrepens
Ilumsubterraneum
[ Entor*.HJ=Select
Figure 10-3. Example computer screen showing a lookup table. The user can enter the GENUS/SPECIES name by entering
the first two letters of the GENUS name, then selecting the appropriate name from the lookup table.
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Comparison of the Data Sets
Dual data entry is useful only if both data sets can be reconciled without
inordinate amounts of time and effort. To accomplish this, a three step method for
reconciling two data sets has been developed (Figure 10-4): 1) matching the
filenames; 2) comparing the key fields; and 3) comparing the non-key fields. For each
step in the comparison process, all the files in one data set are compared, record by
record, with the files in the other data set. The program reports any errors found to
the user, so the problems can be corrected. The comparison process is complete
once no errors are identified in any of the three steps.
Filenames in one data set are compared to those in the other data set to
ensure that the files in both are matched, i.e., that each filename in the first data set
has a corresponding filename in the second data set The files for each data set are
stored in separate sub-directories; each with a different file extension. The program
will store the filenames from each set in separate files. These files are then used to
match the filenames from both data sets (Figure 10-5).
Comparing the key fields in one data set with the other ensures that both data
sets are using the same key fields. This is necessary so the records in the data sets
can be compared to identify any differences in the information entered.
Correction of Differences
The three types of differences that can occur between data sets are: 1) non-
matching filenames, 2) invalid or missing key fields, or 3) different field values.
Non-matching filenames occur when the program finds a filename that exists in
only one data set. This problem can occur in one of three ways: 1) the filename in
one of the data sets was misspelled; 2) an inappropriate filename was entered in one
of the data sets; or 3) the file was not entered in one of the data sets.
Invalid or missing key fields occur when the program can not find a matching
key field value in the other data set. There are three possible causes: 1) the key field
was not entered; 2) the wrong key field was entered; or 3) a key field was entered that
does not belong to the file.
There are three possible causes for disparate values or the same field in the
data sets: 1) the value for the field was not entered, 2) the value was not entered in
the correct field, or 3) the wrong value was entered in the field.
When correcting differences the program will automatically position the user on
the proper record and field. A message describing the problem and possible causes
will be displayed. To correct the problem the user will review the appropriate data
sheet and determine if a data entry error occurred. If a data entry error has occurred,
the user can then correct the error (Figure 10-6). After examining the problem, the
user presses the appropriate key to move to the next problem. After all the problems
have been dealt with by both users, the data sets for each user will be transferred to
the other user’s computer, by floppy disks. Once transferred, a new comparison will
be run and the process of correcting the data sets will be repeated until there are no
differences, i.e., the data sets are identical.
132
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1) Compare each filename in set
ONE to the filenames in set TWO.
thefiletes matched’
2) For each file compare every key
field in set ONE to set TWO.
Are all key fields the same? No
Yes
3) For each file use the key fields
to compare the matching fields in
set ONE to set TWO.
Does all the data match?
No
Yes
Have the users reconcile the data
Figure 10-4. Flowchart of the three step comparison and reconciliation process.
Yes
Perform post reconcilation tests:
Date Validation, Percent Completed
Check, Relational Database Check,
and Code check.
133
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Data Set One Files - Data Set Two Files
3352T1 C.ONE 3352T1 C.TWO
3352T2C.ONE 3352T2C.TWO
3T C HE
4379T1 C.ONE 4379T1 C.TWO
4379T2C.ONE 4379T2C.TWO
3487T1 C.ONE 3487T1 C.TWO
3487T2C.ONE 3487T2C.TWO
3487T3C.ONE 3487T3C.TWO
4275T1 C.ONE 4275T1 C.TWO
4275T2C.ONE 4275T2C.TWO
4275T3C.ONE 4275T3C.TWO
4275T4C.ONE 4275T4C.TWO
Figure 10-5. Matching the filenames tQ be compared by the dual data entry program.
134
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Recording Problems
One data entry person will be responsible for entering information into a
notebook. The notebook will be used to record problems and solutions during the
data entry and analysis process. Each section will be organized by site and transect
(Figure 10-7).
TESTS PERFORMED AFTER RECONCILING THE DATA SETS
After the data sets are verified and reconciled, the following tests should be
conducted to determine if there are any problems with the data itself.
Data validation identifies any unusual spellings or values that do not make
sense. This is accomplished by producing a separate file that contains a sorted list of
all unique entries for each field in a data set. If any unusual entries are found they
can be changed by using the program’s global search and replace option.
The percent completed check determines how complete the data are by
calculating the percentage of how often a field was used to store data. This allows
the analyst to consider the amount of information available in the fields before
performing an analysis.
The relational database check determines if all the records in a relational
database system are related properly. A relational database system is a group of files
related by key felds to combine information in one file with information in another file.
If the information is not related properly, then any analysis that is dependent upon the
relation will be erroneous or impossible to perform.
The code check identifies naming conflicts between codes. Codes represent
information in an abbreviated format. For example, in the vegetation database codes
represent the genus/species names of plants. If the same code identifies more than
one genus/species, then a naming conflict has occurred that would produce erroneous
results when the data is analyzed.
Several kinds of vegetation data require summary calculations prior to data
analysis. These calculations principally involve converting individual herbaceous plot
covers, shrub intercept intervals, or tree diameters to summary values for each
transect or site. Formulas are provided in Table 10-1. All calculations will be part of
the data analysis procedures. However, line-intercept intervals will also be calculated
by field personnel and rechecked during data entry for correct arithmetic.
STORAGE OF DATA
The original field sheets will be copied and stored at ERL-C, the copies will be
stored off-site. Data from the field sheets will be stored on three types of computer
media: hard drives, floppy disks and magnetic tape. In addition, data from each data
set will be backed up on floppy disks each time a dual data entry comparison is made.
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Table 10-1. Summary calculations for vegetation data (Homer and Raedeke 1989,
Mueller-Dombois and Ellenberg 1974).
SUMMARY CALCULA11ONS FOR VEGETATION DATA FROM QUADRATS
Percentage Average Canopy Coverage of a Species on a Site =
Sum of cover values for a single species/number of plots examined
Percentage Total Coverage for all Herbaceous Plants =
Sum of the average covers for all species
Percentage Relative Cover for a Species on a Site =
Coverage for species i/sum of coverages for all species on the site
Percentage of Plant Cover for the Site = 100% - % bare ground
SUMMARY CALCULA11ONS FOR LINE-INTERCEPT DATA
Converting Line-Intercept Meter Tape Distances To Intercept Interval Length =
Ending shrub intercept distance - Beginning shrub intercept distance = Interval
length for the occurrence of shrub
Converting Line-Intercept Intervals to Percentage Relative Cover for a Species on
a Site
Percentage Relative Cover = proportion of transect intercepted by each species =
I/L
Where l = the sum of intercept lengths for the species i, and L = the total length of
all transects sampled
SUMMARY CALCULA11ONS FOR BASAL AREA DATA
Converting Diameter (dbh) Measurements to Basal Area
Basal area = 7tr 2 , where r = 1/2 dbh
Basal Area for a Species on a Site = the sum of the basal areas for all individual
trees of the species___________________________________________________
Percentage Relative Cover of Trees on a Site = ba/BA
Where ba = the sum of the basal area of all individuals of species i, and BA = the
sum of the basal areas of all trees sampled on the site.
137
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3352 2
:::::::.:.. :::::: :...::.:.:.:.: .
V3352T1 L9E R 1D Vicia Sativa l.D: PLOT32
Could not determine the number recorded on the
field sheet.
RE$QLUT1QN: No value entered
Figure 10-7. Example notebook entry for identifying problems encountered during the data
reconciliation process and their solutions.
138
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Upon completion of the data entry process, a final copy of each data set will be
archived on two sets of floppy disks. The two sets will be stored on different colored
floppy disks, so they can be easily identified. The floppy disks will be stored in
separate locations along with a copy of the notebook. If any subsequent changes are
made to the data, the following steps will be followed: 1) the changes will be entered
into the notebook; 2) the data sets on the hard drives and both sets of floppy disks will
be updated; and 3) the data analyst(s) will be notified.
139
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11. DATA ANALYSIS
The data analysis section is divided into two parts. The first section lists the
four study objectives and offers a brief discussion of the analyses proposed to address
them. The second section describes, in more detail, the .manner in which the
statistical analyses will be used to facilitate characterization and comparison of the
OWS wetlands.
This is an observational study, therefore, with the exception of Objective 1,
causation cannot be determined. For example, the percent of organic matter in the
soil could be significantly higher in the natural wetlands, however, it is not correct to
say that the higher value was caused by the fact that the wetland was natural. There
could be another confounding variable that was related both to the percent organic
matter in the soil and to the natural status of the wetland.
Objective 1—Determine the number of freshwater wetlands that have been
converted to other land types and Identify causes of this direct loss.
To address this objective, the most recent wetland inventory based on NWI
maps will be compared to a current inventory performed during site selection to
determine the short term trends in wetland loss. Comparisons will be made between
wetland types listed on NWI maps and types of existing wetlands. The wetland type
most frequently destroyed and the locales where the majority of the wetland
destruction has occurred will be documented and summarized. In addition, the land
use in the location of the destroyed wetlands will be documented to determine the
cause (if identifiable) of wetland loss. For example, if a natural wetland identified on a
NWI map has been destroyed, and a shopping mall has been constructed in the
location of that destroyed wetland, the cause o the wetland lo3s is commercial
development. The information on cause of wetland loss will be summarized to detect
trends.
Objective 2—Evaluate the relationshIp between surrounding land uses and the
attainable quality of freshwater wetlands.
Comparisons will be made between wetlands in different land uses for specific
variables of interest (i.e., those variables that are believed to be affected by different
land uses). For example, we might expect the ratio of native to exotic plant species to
be influenced by land uses with intensive human use. Summary statistics (e.g., mean,
mode) will be calculated for the variables of interest, and graphical methods will be
used to display the variables (e.g., box and whisker plots). Analysis of variance will be
used to compare data from wetlands within the different land uses and multiple
comparison tests (e.g., least significant difference) will be used to determine which
group(s) of wetlands are significantly different from the others.
Another mechanism for looking at attaInable quality will be to explore the
structure and function of wetlands with and without vegetated buffers. Summary
statistics will be calculated for variables of interest within wetlands grouped by the
presence or absence of vegetated buffers. The two groups will be compared
140
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graphically and with a two sample test (e.g., Student’s t test, Wilcoxon-Mann-Whitney
rank-sum test).
Objective 3—Evaluate the replacement potential of freshwater wetlands to aid In
the development of performance criteria.
This objective can be divided into a number of questions of interest. How does
the porformance of the pre-1987 projects compare with that of the post-1987 projects?
How do the post-1987 projects compare with similar natural wetlands; if they are
different, are there likely explanations (e.g., age of project, land use setting)?
The performance of the pre- and post-1987 projects will be investigated by
comparing the two groups for certain relevant variables (e.g., the ratio of wetland to
upland taxa). Data for the groups will be compared graphically and statistically. A two
sample test will be used to compare the two groups for a single variable and
Hotelling’s 12 for a group of related variables. In addition, multivariate analyses will be
used to explore the data and determine whether there are distinct differences between
pre- and post-1987 projects. Comparisons of natural wetlands and projects will be
similar to those outlined for the pre- and post-1987 projects. In addition, outliers will
be identified and investigated for both comparisons (i.e., comparisons of pre- and
post-1987 projects and comparisons of project and natural wetlands). Cook’s distance
and other diagnostic tools will be used to determine if there are outliers which have
influence in the statistical sense.
Objective 4—Evaluate how project design and Implementation affect the
replacement potential of freshwater wetlands to aid In the development of
design guidelines.
Existing data compiled from Section 404 and Oregon Removal-Fill Permit files
will be compared with field data to examine the compliance of projects with their
permits and construction plans. In addition, both the design specifications and the as-
built structural features of the projects will be compared to the structural characteristics
of the natural wetlands. Differences and similarities in the structural characteristics of
the two groups of wetlands will be documented and summarized to aid in the
development of design guidelines for future projects.
Permit files and construction plans will be examined for information on the
intended hydrologic regime of each project. Intended water levels, area to be
inundated, and descriptions and locations of water sources, inlets, outlets, and control
structures will be compared to as-built conditions of projects and structural conditions
of natural wetlands identified from field maps and measurements of hydrologic
indicators.
The intended area and shape of each project determined from blueprints and
written permit conditions will be compared to as-built data for each project identified
from field maps. In addition, project shapes (e.g., shoreline sinuosity), will be
compared to the shapes of natural wetlands. Morphology and bank slopes intended
for the projects (e.g., written bank slope specifications and contour lines on blueprints)
will be compared to as-built project morphology and the structural characteristics of
natural wetlands measured during field activities.
141
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Revegetation strategies specified as conditions of permits and lists of species to
be planted will be compared to the plant species identified on the projects during field
sampling. The revegetation information will also be compared to the plant species
identified at the natural wetlands to determine if the species listed for planting occur
naturally on wetlands in the region.
DATA ANALYSIS PROCEDURES
Checking to see that the assumptions of a statistical procedure are met is the
first step in data analysis. The data used for statistical tests must fulfill various
assumptions (e.g., normal distribution, independent observations, equal variances) for
the use of the tests and the results to be valid. However, data can be manipulated
(e.g., transformations) so that assumptions are met. Also, if necessary, alternative
(e.g., non-parametric) analyses can be used.
In addition, to gain the most complete understanding of data, interim results of
the analyses will be discussed with a community ecologist. The ecologist can provide
interpretation or insight that a statistician may lack (e.g., interpretation of an axis
produced by detrended correspondence analysis).
To observe trends, identify outliers, and summarize the data, descriptive
statistics will be calculated (e.g., mean, mode, range) and the data will be graphically
displayed. Displaying data graphically is an effective way to understand relationships
between variables. Such graphics can also be used to compare groups and develop a
preliminary interpretation of results. There are many informative ways to display
univariate data graphically (e.g., histograms, stem and leaf plots, and boxplots).
Multivariate data can be presented as a matrix of scatter plots that is analogous to a
correlation matrix.
Answering the research questions (Table 1-1) for the OWS requires two basic
analysis approaches, characterization and comparison. Comparing natural wetlands to
project wetlands is necessary to evaluate the degree to which projects replicate
natural wetlands and to identify features that suggest improvements to project design.
However, meaningful comparisons cannot be made without detailed descriptions of
wetland attributes and an understanding of existing wetland resources. The first step
of analysis is to characterize the wetlands by employing data that describes wetlands
in terms of their vegetation, soils, hydrology, morphology, and land use (See Table 1-2
for list of variables) to identify groups of wetlands and to document the condition of
wetland resources. The data analysis methods proposed for the characterization and
comparison processes are outlined in Table 11-1. Both a priori groups of wetlands
(e.g., those defined by land use categories, natural vs. project, pre-1987 and post-
1987 projects) and groups of wetlands defined by ecological characteristics will be
evaluated in data analyses.
Characterization and Comparison of the Wetlands
Several data analysis procedures are involved in characterizing the OWS
wetlands. An example illustrating how the data and analysis approaches might be
142
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Table 11-1. Statistical analyses proposed for the Oregon Wetlands Study.
Objective Suggested Analyses
Characterization Graphical Methods--to display variables and identify outliers (e.g., scatter plots, box plots,
Chemoff faces, etc.)
Descriptive Statistics--to summarize variables (e.g., mean, mode, range)
Multivaritate Methods:
Multiple regression--measure relationships between variables
Correlations--measure the relationship between two variables
Cluster analysis--group wetlands based on species abundance or environmental variables
(e.g., CLUSB: non-hierachial, divisive; TWINSPAN: hierachial, dMslve)
Ordinations:
Detrended correspondence analysis--summarize vegetation data and relate to
environmental variables
Principal components analysis--Investigate which variables contribute the major
sources of variability
Binary logtt regresslon/Discriminant function analysis--InvestIgate which variables
most characterize the differences between projects and natural wetlands
Weighted averages—summarize vegetation data based on wetland indicator status
Canonical correspondence analysis—Investigate relationship between two groups of
variables (e.g., vegetation and environmental variables)
Shannon and Simpson’s diversity and dominance measures--to summarize plant
diversity and community structure.
Comparison
A) Natural wetlands within
each land use. Post-i 987 projects
within each land use.
Univanate Methods:
Graphical methods--see above
T-tests/Non parametric two sample tests--compare two groups
ANO VA--compare more than two groups
B)
Post-1987 projects vs. natural
wetlands within each land use.
Muttivariate Methods:
Hotellings T 2 —compare more than one variable for two groups
C)
Pre-1987 projects vs. Post-1987
projects.
-------
used for wetland characterization is provided in Figure 11-1. It is necessary to
describe each wetland (e.g., using site averages), define groups of wetlands that can
be compared (e.g., using Cluster Analysis), and identify the gradients along which the
wetland groups vary or are distributed (e.g., using Ordination Analysis). The next step
is to evaluate the wetlands in greater detail to 1) develop more precise understanding
of wetland characteristics for comparisons, and 2) identify relationships between
variables that can aid in answering some of the study questions or that suggest
hypotheses to be tested in further studies. Techniques useful in this regard are
Diversity Indices and Dominance Measures, Weighted Averaging Ordination,
Correlations, and Multiple Regressions.
Site averages for each variable will be calculated so that each site can be
described in terms of vegetation and environmental measures. The site averages will
be input into several kinds of multivariate analysis programs. First, vegetation data
and environmental data will both be evaluated using Classification techniques
(clustering programs) to 1) describe groups of related wetlands (e.g., projects, natural
wetlands, wetlands in different land uses, wetlands with similar plant communities or
environmental attributes, etc.), and 2) identify outher sites.
Ordinations are also useful in summarizing community data, and can aid in
relating community variation to environmental gradients and understanding community
structure (Gauch 1982). Vegetation and environmental data will be analyzed using
Ordination techniques (e.g. Detrended Correspondence Analysis) to look for gradients
along which the wetland groups are distributed (e.g., hydrology, wetland morphology,
land use, disturbance, project age, buffer presence or absence, etc.). The position,
along the Ordination axes, of the wetland groups identified during Cluster analysis will
be evaluated to see if the groups are aligning along a gradient. The environmental
variables will then be back correlated with the vegetation ordination axes to see if any
of the variables are significantly related to the gradient(s) described by the axes.
Figure 11-2 depicts a hypothetical ordination of wetland species data. Hypothetical
groups resulting from clustering analysis are circled on the diagram to illustrate how
wetland groups are related to the gradients represented by the ordination axes. In this
case, ordination axis 1 represents a hydrologic gradient, and axis 2 represents a
disturbance gradient. Along the first axis, the hypothetical wetlands do not separate
according to whether they are project or natural (except that more projects are ponds),
but are aligned according to inundation duration or water depth. Along the second
axis, wetlands appear to be aligned based on the proportion of native to exotic
species.
Several other approaches for identifying which variables are most explanatory in
d& lning gradients are also available. Canonical Correspondence Analysis can be
used to investigate the relationships between vegetation and environmental variables.
Principal Components Analysis can be used to explain which variables or
combinations of variables account for major sources of variation. Binary logit
regression (for non-normally distributed data) or discriminant function analysis (for
normally distributed data) could be used to identify the variables which best
characterize differences between groups of wetlands (e.g., project and natural).
More information regarding differences between individual or groups of wetlands
will be obtained in several ways. Diversity and Dominance Measures will be used to
1 4
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___________ Muftiple L
Dlversfty Analyses l Regressions
Shannon’s and o.m,. Cotieiat lons -
Simpson’s diversity diversity h
and dominance II ook for relationships between varlablesl
measures .
______ ________ / ,/..‘ /
annonicat Correspondence
Evaluate pOCi S8btJf1d flCe’ An
relationship S S
of diversify Principal Components
‘a” Wnt 4, c Analysis
dandnan
to wetiand Discriminant Function
group. o / I Analysis
to __________ Blnaiy Logit Regression
.nWronm.ntal
Group Look I Look Group
w.f land,, lor 4 f wetlands,
Identify gradients gradients Id.ntify
outn.ra _____ _________ Identify environ- out!!.,,
— Ordination Analysis measures __________ — _____
Cluster Analysis , o.Itio , Weighted Averages Ordination Analysis Cluster Analysis
TW1NSPAN ,,, , DECORRANA (DCA) describing gradients of wetl fld 1WINSPAN
CWSB gruu, . - Iong which wetland. along CLUSB
along messures wmi axes are distributed gradient
Define groi of weliands besed
Statistical comparisons of
wetland groups to answer
research questions.
(See Table 11-1).
Figure 11-1. Example of approaches for characterizing and comparing wetlands. italics = purpose of analyses.
Shading = data sources.
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HYPOTHETICAL CLASS I FICATI ON AND
ORDINATION OF WETLAND SITES
Figure 11-2.
Hypothetical ordination and classification of wetland data. Natural and project
wetlands are distributed along a hydrologic gradient on the first axis and along
a disturbance gradient on the second axis. Cirded groups of wetlands (A-E)
represent hypothetical results of cluster analysis. Notes refer to
characteristics of wetland groups.
Most
Pristine
C
ci
I-
0
0
C
(a,
a
0
a
Most
Disturbed
DCA Axis One (Hydrologic Gradient)
146
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summarize vegetation structure in individual wetlands and to aid in describing
differences between groups of wetlands. For example, such analyses could show
species diversity is greater on young projects than on natural wetlands (Figure 11-3).
This might be due to the influx of weedy colonizers in early succession.
The Weighted Averages Ordination Technique will be used to rank plant
species by their wetland indicator status and produce axes that distribute the wetlands
along a continuum of NWI habitat categories (Wentworth et al. 1988). For example,
Figure 11-4 illustrates the weighted averages score for natural and project wetlands
sampled in the 1987 Oregon Pilot Study. Results could illustrate differences In
wetland type or ‘quality’ that might be related to project vs. natural wetlands, land use,
or presence of buffers, etc. Weighted averages may also be similarly employed using
hydric soil indicator and organic matter data.
Multiple regression can be used to determine the relationship between a
response variable and one or more explanatory variables. For example, regression
could determine if the percent of organic matter found in the soil is related to the
project age and land use.
Correlations are also used to determine the degree of linear relationship
between two variables. Correlation Analyses will be conducted in two ways, using
either site averages or plot values for the variables. Relationships between any of the
variables sampled in the OWS (Table 1-2) can further characterize the study wetlands,
and also permit inferences useful in identifying differences that relate to attainable
quality or replacement potential, and suggest improvements in project design. For
example, if high cover of exotic plant taxa is positively correlated to urban land use,
narrow buffer width, and low soil organic matter, several ideas emerge. The condition
or the attainable quality of a site that occurs in such a situation is likely to be low and
influenced by these particular variables. The potential of replacing a high quality
wetland would likely be low if the compensatory mitigation project was placed in an
urban site that lacked buffers and had limited soil organic matter. Project design
might be enhanced by relocating the project, installing buffers, or adding organic
matter to the site.
Correlations involving plot values for variables could provide detailed
information about relationships between plant species and environmental variables
such as hydric soil indicators, soil organic matter, hydrology, and relative elevation.
Such information could be used to improve pruject designs by providing guidelines for
construction that would generate wetland morphology, hydrology, and soil conditions
conducive to the establishment of desired plant species. Also, planting lists of native
species that are adapted to conditions of marginally successful projects might be
developed.
Following the characterization analyses, data for groups of wetlands will be
statistically (e.g., T-tests, Mann-Whitney rank sum test, Hotelling’s T 2 , ANOVA) and
graphically (e.g., histograms, boxplots, characterization and performance curves)
compared to facilitate answering the research questions. For quantitative comparisons
used to determine if statistical differences in wetland attributes exist between different
wetland groups, the choice of statistical test will depend on the number of groups
being compared and whether data are normally distributed. For comparisons of two
147
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1.0
* *
0.9
**
• * **
a)
4 .
* *
_Cl) 0.8
C
0
U)
-
E
C /)
. ‘ 0.7
Legend
O = mean for 12 natural wetlands
I = +i standard error
* = value for 1 created wetland
0.6 ____________________________
*
0.5 I I I
0 1 2 3 4 5 6 7 8
Age of wetland (years)•
Figure 11-3. Plant diversity data from the 1987 Oregon Pilot Study (Kentula et at. 1 992a).
-------
Figure 11-4. Weighted average scores for the type of vegetation found in individual project (P) and natural (N) wetlands
from the 1987 Oregon Pilot Study (Kentula et al. 1992a).
‘ 0
Extreme wetland
(100% obligate
hydrophytes
Wetland
Extreme upland
(100% obligate
upland species)
Upland
-------
samples, Student’s I test will be used for normally distributed data, and a non-
parametric test such as the Mann-Whitney rank sum test will be used for non-normally
distributed data Similarly, for comparisons of more than three groups (e.g., organic
content of soils for wetlands in the five land use classes), analysis of variance or a
non-parametric equivalent (e.g., Kruskal and Wallis) will be used. Hotelling’s T 2 is a
multivariate extension of a t-test which could be used to summarize a group of related
variables (e.g., vegetation). Graphical depiction of data in characterization or
performance curves will be used to compare projects and natural wetlands, wetlands
in different land use groups, and groups of wetlands defined during the
characterization process. The results of these graphical comparisons will be used to
aid in develop nent of criteria for project evaluation and design (Kentula 1992a). The
utility of characterization and performance curves is discussed in more detail in the
summary section that follows.
SUMMARY
The OWS has been designed to collect, analyze, and report information that will
contribute to sound wetland management using wetland restoration and creation. As
stated in the study overview, information needs related to direct and indirect wetland
loss will be addressed by the study (Figure 1-1). The unique contribution of this study
to wetland science and management is the definition of indirect losses of wetland
function due to land use practices and the design and implementation of wetland
projects. This contribution is best illustrated by the use of characterization curves and
performance curves to represent the results of the study.
Characterization curves are frequency distribution curves in which the vertical
axis represents the number of wetlands (i.e., frequency) and the horizontal axis
represents some measure of function (i.e., the variable of interest). These curves will
be used to summarize data and graphically compare major characteristics of the
wetland groups studied. For example, Figure 11-5 illustrates the results we would
anticipate for the relative function of wetlands in different land use settings based on
results from the 1987 Pilot Study. The shape of the curve indicates whether the group
is homogenous or heterogenous, i.e., includes sites having a similar level of the
function measured (A on Figure 11-5) or includes sites with a wide range of values for
the function (B on Figure 11-5). The position of the curves along the x-axis represents
the relationship between the wetlands in each land use sethng and level of function
measured. Consequently, displaying data in characterization curves allows the
presentation of a large amount of information in a way that portrays the relationship
between land use and specific wetland functions.
Performance curves display the changes in a function in wetland projects over
time as compared to the level of that function in similar natural wetlands. In the 1987
Pilot Study we produced the first portion of these curves for the variables measured at
all wetland projects in existence at that time (Figure 11-6). One goal of the OWS is to
generate the next segment of those curves to determine how pre-1987 projects have
continued to develop and if they are becoming more similar to natural wetlands.
Another goal is to determine if projects constructed since 1987 are developing as we
would expect based on the 1987 study, or if they are developing differently due to
150
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HYPOTHETICAL CHARACTERIZATION CURVES OF WETLANDS
High
C /)
a)
Low
IN DIFFERENT LAND USE SETTINGS
— UNDEVELOPED
• -. INDUSTRIAL
Low High
Figure 11-5.
Level of Function
Hypothetical characterization curves comparing the level of function in groups of wetlands in different land use settings.
The pattern displays the resutts anticipated for the OWS based on the 1987 Pilot Study. A is the characterization curve
of a relatrvely homogeneous group of wetlands; B, of a relatively heterogeneous group of wetlands.
RESIDENTiAL
COMMERCIAL
-— AGRICULTURE
I
I
I
I
S
S
S
S
S
S
S
-------
16
14
12
*
HYPOTHETICAL PERFORMANCE CURVES FOR
ACCUMULATION OF SOIL ORGANIC MATTER
— _ _ — — S — — — S
0 . 5 _•
* *
I I I I I
3
4
Age (years)
5 6 7 8
Figure 11.6. Hypothetical performance curves comparing the anticipated development of the projects contructed prior to 1987 to the development
of projects constructed since 1987 and to similar natural wetlands. The curves present results of the 1987 Pilot Study and suggest
the results that might be expected in the OWS.
Legend
a = mean for natural wetlands in 1993
= mean for natural wetlands in 1987
I = j 1 standard error
* = value for 1 created wetland
— = Pre-1987 Projects in 1987
= Pre-1 987 Projects in 1993
= Post-1987 Projects
*
1 2
-------
changes in design or management. We hope that due to increased knowledge and
experience in wetland restoration and creation that the newer projects are developing
the functions of natural wetlands more rapidly than the projects constructed prior to
1987 (Figure 11-6). Again, the graphic display enables us to summarize and compare
key information simply and rapidly.
in designing the OWS we have responded to the challenge stated in An
Approach to improving Decision Making in Wetland Restoration and Creation
(Kent ’la et al. 1992a) that we continue to build the knowledge base on wetland
restoration and creation through the application, testing, and evaluation of the
concepts presented in Decision Making. The OWS employs one of those concepts
by considering ecological setting in the evaluation of the function of natural wetlands
and projects, and by beginning to address the relationship between land use and
wetland function, it also treats existing projects as experiments in progress, making
monitoring of natural wetlands and projects centrai to the use of restoration and
creation in wetland management, and endorsing the idea that we all must
u...learn by going where we need to go... 1 (Roethke 1961).
153
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LITERATURE CITED
Abbruzzese, B., A.B. JIen, S. Henderson, and M.E. Kentula. 1988. Selecting sites
for comparison with created wetlands, p. 291-297. In C.D.A Rubec and R.P. Overend
(Comp.), Proceedings of Symposium ‘87--Wetlands/Peatlands. Environment Canada,
Ottawa, Ontario, Canada.
Adamus, P.R. and L.T. Stockwell. 1983. A Method for Wetland Functional
Assessment. FHWA-IP-82-83. U.S. Dept. of Transportation, Federal Highway
Administration, Washington, D.C.
Bannister, P. 1966. The use of subjective estimates of cover-abundance as the basis
for ordination. Journal of Ecology 54:665-674.
Blume, L.J., BA Schumacher, P.W. Shaffer, KA. Cappo, M.L Papp, R.D. van
Remortel, D.S. Coffey, M.G. Johnson, and D.J. Chaloud. 1990. Handbook of
Methods for Acid Deposition Studies: Laboratory Analyses for Soil Chemistry.
EPN600/4-90/023. U.S. Environmental Protection Agency, Office of Research and
Development, Washington, D.C.
Brown, M.T. 1991. Evaluating Created Wetlands Through Comparisons with Natural
Wetlands. EPA/600/3-91/058. U.S. Environmental Protection Agency, Environmental
Research Laboratory, Corvallis, OR.
Brown, M.T., J. Schaefer, and K.H. Brandt. 1990. Buffer Zones for Water, Wetlands,
and Wildlife in East Central Florida. Publication Number 89-07 and Florida Agricultural
Experiment Station Journal Series Number T-00061. The Center for Wetlands,
University of Florida, Gainesville, FL
Brown, S.L. 1981. A comparison of the structure, primary productivity, and
transpiration of cypress ecosystems in Florida. Ecological Monographs 51:403-427.
Brunton Company. 1980. The Compass Book. Riverview, NY.
Buckner, R.B. 1983. Surveying Measurements and Their Analysis. 1st Edition. The
Dept. of Geodetic Science and Surveying, Ohio State University, Columbus, OH.
Canfield, R. 1941. Application of the line interception method in sampling range
vegetation. Journal of Forestry 39:338-394.
Carter, V., T. Winter, R. Novitzki, G. Holland, T. Leicher, A. O’Brien, D. Siegel, and 1.
Straw. 1984. Hydrology Panel, p. 17-28. In, J.H. Sather and P.J.R. Stuber (coords.),
Proceedings of the National Wetland Values Assessment Workshop. FWS/OBS-
84/12. U.S. Fish and Wildlife Service, Western Energy and Land Use Team, Fort
Collins, CO.
154
-------
Clarke, S.E., D. White, and A.L Schaedel. 1991. Oregon ecological regions and
subregions for water quality management. Environmental Management 15:847-856.
Confer, S.R. and WA Niering. 1992. Comparison of created and natural freshwater
emergent wetlands in Connecticut (USA). Wetlands Ecology and Management
2:143-1 56.
Conservation Foundation. 1988. Protecting America’s Wetlands: An Action Agenda.
The Final Report of the National Wetlands Policy Forum. Washington D.C.
Cooper, J.R., J.W. Gilliam, and T.C. Jacobs. 1986. Ripanan areas as a control of
nonpoint pollutants, p. 166-192. In D.L Correl (Ed.), Watershed Research
Perspectives. Smithsonian Institution Press, Washington, D.C.
Cooper, J.R ., J.W. Gilliam, R.B. Daniels, and W.P. Robarge. 1987. Riparian areas as
filters for agricultural sediment. Soil Science Society of America Journal 51:416-
420.
Cowardin, LM., V. Carter, F.C. Goulet, and E.T. LaRoe. 1979. Classification of
Wetlands and Deepwater Habitats of the United States. FWS/OBS-79/31. U.S. Fish
and Wildlife Service, Washington, D.C.
Cox, G. 1980. Laboratory Manual of General Ecology. William C. Brook Publishers,
Dubuque, IA.
D’Avanzo, C. 1986. Vegetation in freshwater replacement wetlands in the Northeast,
p. 53-81. In J.S. Larson and C. Neil (Eds.), Mitigating Freshwater Wetland 4Jterations
in the Glaciated Northeastern United States: An Assessment of the Science Base.
PubI. No. 87-1. The Environmental Institute, University of Massachusetts, Amherst,
MA.
D’Avanzo, C. 1991. Long term evaluation of wetland creation projects, p. 75-84. In
J.A Kusler and M.E. Kentula (Eds.), Wetland Creation and Restoration: The Status of
the Science. Island Press, Washington, D.C.
DahI, T.E. i990. Wetland losses in the United States 1780’s to 1980’s. U.S. Fish
and Wildlife Service, Washington, D.C.
Daubenmire, A. 1959. A canopy-coverage method of vegetation analysis.
Northwest Science 33:43-64.
Davis, R.E. and J.W. Kelly. 1969. Elementary Plane Surveying. 4th Edition.
McGraw-Hill, Inc., New York, NY.
Dunne, T. and L.B. Leopold. 1978. Water in Environmental Planning. W.H. Freeman
and Company, San Francisco, CA.
155
-------
Erwin, K.L. 1991. An Evaluation of Wetland Mitigation Within the South Florida Water
Management District, Volume 1. South Florida Water Management District, West
Palm Beach, FL.
Federal Interagency Committee for Wetland Delineation (FICWD). 1989. Federal
Manual for ldenVfying and Delineating Jurisdictional Wetlands. U.S. Army Corps of
Engineers, U.S. Environmental Protection Agency, U.S. Fish and Wildlife Service, and
U.S.D.A. Soil Conservation Service. Cooperative Technical Publication, Washington,
D.C.
Gauch, H.G., 1 4r. 1977. ORDIFLEX - A Flexible Computer Program for Four
Ordination Techniques: Weighted Averages, Polar Ordination, Principal Components
Analysis, and Reciprocal Averaging, Release B. Cornell University, Ithaca, NY.
Gauch, H.G., Jr. 1982. Multivariate Analysis in Community Ecology. Cambridge
University Press, Cambridge, England.
Gilliam, J.W. and R.W. Skaggs. 1988. Natural buffer areas and drainage control to
remove pollutants from agricultural drainage water, p. 145-148. In J.A. Kusler, M.L
Quammen, and G. Brooks (Eds.), Proceedings of the National Wetland Symposium:
Mitigation of Impacts and Losses. Association of State Wetland Managers, Berne,
NY.
Green, RH. 1979. Sampling Design and Statistical Methods for Environmental
Biologists. John Wiley and Sons, Inc., New York, NY.
Greenhood, D. 1964. Mapping. The University of Chicago Press, Chicago, IL.
Greig-Smith, P. 1964. Quantitative Plant Ecology. 2nd Edition. Butterworths,
London, England.
Gwin, S.E. and M.E. Kentula. 1990. Evaluating Design and Verifying Compliance of
Wetlands Created Under Section 404 of the Clean Water Act in Oregon. EPN600/3-
90/061. U.S. Environmental Protection Agency, Environmental Research Laboratory,
Corvallis, OR.
Hitchcock, C.L. and A Cronquist. 1973. Flora of the Pacific Northwest. University of
Washington Press, Seattle, WA.
Holland and Kentula. 1991. The Permit Tracking System (PTS): A User’s Manual.
EPN600/8-91/054. U.S. Environmental Protection Agency, Environmental Research
Laboratory, Corvallis, OR.
Homer, R.R. and K.J. Raedeke. 1989. Guide for Wetland Mitigation Projects
Monitoring. Report Number WA-RD 195.1. Washington State Department of
Transportation, Seattle, WA.
156
-------
Jordan, R.A. and J.K. Shisler. 1988. Research needs for the use of buffer zones for
wetland protection, p. 433-435. In J.A. Kusler, M.L Quammen, and G. Brooks (Eds.),
Proceedings of the National Wetland Symposium: Mitigation of Impacts and Losses.
Association of State Wetland Managers. Berne, NY.
Kentula, M.E., R.P. Brooks, S.E. Gwin, C.C. Holland, A.D. Sherman, and J.C. Sifneos.
1992a. An Approach to Improving Decision Making in Wetland Restoration and
Creation. Edited by A.J. Hairston. EPN600/R-92/150. U.S. Environmental Protection
Agency, Environmental Research Laboratory, Corvallis, OR.
Kentula, M.E.,.J.C. Sifneos, J.W. Good, M. Ryiko, and K. Kunz. 1992b. Trends and
patterns in Section 404 permitting requiring compensatory mitigation in Oregon and
Washington. Environmental Management 16:109-119.
Kershaw, K.A. 1973. Quantitative and Dynamic Ecology. 2nd Edition. Elsevier,
New York, NY.
Kissam, P. 1966. Surveying Practice: The Fundamentals of Surveying. McGraw-Hill
Inc., New York, NY.
Kusler, J.A. and M.E. Kentula. 1991. Executive summary, p. xi-xix. In J.A. Kusler and
M.E. Kentula (Eds.), Wetiand Creation and Restoration: The Status of the Science.
Island Press, Washington, D.C.
Langis, L., M. Zalejko, and J.B. Zedler. 1991. Nitrogen assessments in a constructed
and a natural salt marsh of San Diego Bay. Ecological ApplIcations 1 (1):40-51.
Leibowitz, S.G., E.M. Preston, L.Y. Arnaut, N.E. Detenbeck, C.A. Hagley, M.E.
Kentula, R.K. Olson, W.D. Sanville, and R.R. Sumner. 1992. Wetlands Research
Plan FY92-96: An Integrated Risk-Based Approach. EPNGOOIR-92/060. U.S.
Environmental Protection Agency, Environmental Research Laboratory, Corvallis, OR.
Leopold, L.B. 1973. River channel change with time: An example. Geological
Society of America BulletIn 84:1845-1 860.
Levine, D.A. and D.E. Willard. 1991. Regional analysis of fringe wetlands in the
Midwest: creation and restoration, p. 305-332. In J.A. Kusler and M.E. Kentula (Eds.),
Wetland Creation and Restoration: The Status of the Science. Island Press,
Washington, D.C.
Loucks, O.L. 1991. Restoration of the pulse control function of wetlands and its
relationshipto water quality, p. 55-66. In J.A. Kusler and M.E. Kentula (Eds.),
Wetland Creation and Restoration: The Status of the Science. Island Press,
Washington, D.C.
Lounsbury, J.F. and F.T. Aldrich. 1979. Introduction to Geogrgaphic Field Methods
and Techniques. Charles E. Merrill Publishing Company, Columbus, OH.
157
-------
Lowrance, R., J.K. Sharpe, and J.M. Sheridan. 1986. Long-term sediment deposition
in the riparian zone of a coastal plain watershed. Journal of Soil and Water
ConservatIon 41:266-271.
Magee, T.K, K Dwire, C.C. Holland, AG. Gibson, S.E. Gwin, J.E. Honea, P.W.
Shaffer, J.C. Sifneos, and M.E. Kentula. In Prep. Quality Assurance Project Plan:
Oregon Wetlands Study. EPN)OO(/X-XX/XXX. U.S. Environmental Protection
Agency, Environmental Research Laboratory, Corvallis, OR.
Martin, D.B. and W.A Hartman. 1987. The effect of cultivation on sediment
composition and deposition in prairie pothole wetlands. Water, Air, and Soil
Pollution 34:45-53.
Mitsch, W.J. and J.G. Gosselink. 1986. Wetlands. Van Nostrand Reinhold Company,
Inc., New York, NY.
Mueller-Dombois, D. and H. Ellenberg. 1974. Aims and Methods of Vegetation
Ecology. John Wiley and Sons, Inc., New York, NY.
Neely, R.K. and J.L. Baker. 1979. Nitrogen and phosphorus dynamics and the fate of
agricultural runoff, p. 92-132. In A. van der Valk (Ed.), Northern Prairie Wetlands.
Iowa State University Press, Ames, IA
Niering, WA and M.L. Kraus. 1986. Science base for freshwater wetland mitigation
in the Northeastern United States: Vegetation, p.122-130. In J.S. Larson and C. Neil
(Eds.), Mitigating Freshwater Wetland Alterations in the Glaciated Northeastern United
States: An Assessment of the Science Base. PubI. No. 87-1. The Environmental
Institute, University of Massachusetts, Amherst, MA.
Omernik, J.M. 1987. Ecoregions of the conterminous United States. Annals of the
Association of American Geographers 77(1):118-125. (map scale 1:7,500,000)
Orloci, L. 1978. Multivariate Analysis in Vegetation Research. Junk, The Hague, The
Netherlands.
Owen, C.R. 1990. Effectiveness of Compensatory Wetland Mitigation in Wisconsin.
Technical Report to the Wisconsin Wetlands Association, The Lake Michigan
Federation, The American Clean Water Project. University of Wisconsin, Madison, WI.
Poore, M.E.D. 1962. The method of successive approximation in descriptive ecology.
Advances In Ecological Research 1:35-68.
Roethke, T. 1991. Words for the Wind. Indiana University Press, Bloomington, IN.
Schisler, J.K and D.J. Charette. 1984. Evaluation of Artificial Salt Marshes in New
Jersey. Pub. No. P-40502-01 -84. New Jersey Agricultural Experiment Station.
158
-------
Tiner, R.W., Jr. 1984. Wetlands of the United States: Current Status and Recent
Trends. U.S. Fish and Wildlife Service, National Wetland Inventory, Washington, D.C.
Trimble Navigation Umited. 1991. Operation and Maintenance Guide for the
TransPak II GPS Personal Navigator with I/O. Sunnyvale, CA.
U.S. Department of Agriculture, Soil Conservation Service. 1984. Procedures for
Collecting Soil Samples and Methods of Analysis for Soil Survey. Soil Survey
Investigations Report No. 1. U.S. Government Printing Office, Washington, D.C.
U.S. Fish and Wildlife Service. 1990. Wetlands: Meeting the President’s challenge.
U.S. Fish and Wildlife Service, Washington, DC.
van der Valk, kG., C.B. Davis, J.L. Baker, and C.E. Beer. 1979. Natural freshwater
wetlands as nitrogen and phosphorous traps for land runoff, p. 457-467. In P.E.
Greeson, J.R. Clark, and J.E. Clark (Eds.), Wetland Functions and Values: The State
of Our Understanding. American Water Resources Association, Minneapolis, MN.
Welsch, D.J. 1991. Riparian Forest Buffers: Function and Design for Protection and
Enhancement of Water Resources. Publication NA-PR-07-91. U.S. Dept. of
Agriculture, Forest Service, Radnor, PA.
Wentworth, T.R., G.P. Johnson, and R.L. Kologisiki. 1988. Designation of wetlands
by weighted averages of vegetation data: a preliminary evaluation. Water
Resources Bulletin 24(2) :389-396.
Wikum, D.A. and G.F. Shanholtzer. 1978. Application of the Bran-Blanquet cover-
abundance scale for vegetation analysis in land development studies. Environmental
Management 2:323-329.
Zedler, J.B. and R. Langis. 1991. Comparisons of constructed and natural salt
marshes of San Diego Bay. Restoration and Management Notes 9(1): 21-25.
Zedler, J.B. and M.W. Weller. 1991. Overview and future directions, p. 465-473. In
J.A. Kusler and M.E. Kentula (Eds.), Wetland Creation and Restoration: The Status of
the Science. Island Press, Washington, D.C.
159
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APPENDIX A
LIST OF PLANT SPECIES IDENTIFIED DURING OREGON PILOT STUDY (1987)
Equisetaceae
FAC\n Equisetum arvense
FACW\n Equisetum palustre
FACW\n Equisetum telmateia
Polypodi aceae
FAC\n Athyrium filix-femina
Salviniaceae
OBL\n Azolla fihiculoides
OBL\n Azolla mexicana
Salicaceae
FACW\n Populus trichocarpa
FACW\n Populus balsamifera trichocarpa
Salix sp.
OBL\n Salix fluviatilis
FACW+n Salix lasiandra
FACW\n Salix piperi
OBL\n Salix rigida
FAC\n Salix scouleriana
FACW\n Salix sessilifolia
FACW\n Salix sessilifolia x lasiandra
FACW\n Salix sitchensis
Betu laceae
FAC\n Alnus rubra
UPL\n Corylus comuta
Urticaceae
FAC+i Urtica dioica
Polygonaceae
FACW-i Polygonum aviculare
OBL\n Polygonum coccineum
OBL\n Polygonum amphibium emersum
UPL\n Polygonum douglasii
OBL\n Polygonum hydropiperoides
FACW+i Polygonum lapathifolium
FACWdi Polygonum persicana
160
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OBL\n Polygonum punctatum
ABS\n Polygonum spergulariaeforme
FACLAi Rumex acetoseUa
FACW\i Rumex conglomeratus
FACW I Rumex crispus
FACW\n Rumex salicifolius
UPL\i Rumex sanguineus
Chenopodiaceae
FAC\i Chenopodium album
FAC\i Chenopodium ambrosioides
FACU\i Chenopodium botrys
Aizoaceae
FACdn Mollugo verticillata
Caryophyllaceae
NA\i Cerastium viscosum
FAC-i Spergularia rubra
FACW+n Stellaria calycantha
FAC+n Stellana crispa
UPL\i Stellaria media
Nymphaeaceae
OBL\n Nuphar polysepalum
Ceratophyllaceae
OBL\n Ceratophyllum demersum
Ranunculaceae
OBL\n Ranunculus lobbii
FACW i Ranunculus repens
OBL\n Ranunculus sceleratus
Brassicaceae
FACW+n Barbarea orthoceras
Brassica sp.
UPL\i Brassica nigra
FAC-i Capsella bursa-pastoris
FACW\n Cardamine oligosperma
FACW\n Cardamine pensylvanica
UPL\i Raphanus sativus
FACW+n Rorippa curvisiliqua
OBL\n Rorippa islandica
OBL\n Rorippa palustris
FACW\n Rorippa obtusa
FACW\n Ronppa sphaerocarpa
161
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Crassulaceae
OBL\n TiDaea aquatica
Saxifragaceae
FACU\n Tellima grandiflora
Rosaceae
FAC\n Crataegus douglasii
FACLJ\n Fragaria vesca
FACW+n Geum macrophyllum
FACU\n Oemleria cerasiformis
‘runus sp.
UPL\i Pyrus malus
UPL\i Malus sylvestris
ABS\n Rosa gymnocarpa
FACU\n Rosa pisocarpa
FACU-i Rubus discolor
FACU+i Rubus laciniatus
ABS\n Rubus ursinus
FACW\n Spiraea douglasii
Fabaceae
UPL\i Lathyrus hirsutus
FAC\i Lotus comiculatus
FACU-n Lupinus polyphyllus
UPL\i Trifolium arvense
UPL\i Trifolium dubium
FACU+i Trifolium hybridum
FACU\i Trifolium pratense
FACU+i Trifolium repens
UPL\i Trifolium subterraneum
ABS\n Vicia americana
ABS\i Vicia disperma
UPL\i Vic’ a hirsuta
UPL\i Vicia sativa
UPL\i Vicia tetrasperma
Geraniaceae
UPL\i Geranium dissectum
UPL\i Geranium molle
Oxalidaceae
UPL\n Oxalis suksdorfii
Euphorbiaceae
UPL\i Euphorbia supina
UPL\i Euphorbia maculata
162
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Callitrichaceae
OBL\n Callitriche stagnalis
OBL\n Callitriche verna
Balsaminaceae
FACW\n Impatiens capensis
Malvaceae
ABS\n Sidalcea cusickli
Hypericaceae
OBL\n Hypericum anagalloides
FAC\n Hypericum formosum
UPL\i Hypericum perforatum
Lyth raceae
OBL\i Lythrum hyssopifolia
OBL\i Lythrum salicaria
Onagraceae
FACW-n Boisduvalia densiflora
FACW n Circaea alpina
UPL\n Epilobium minutum
UPL\n Epilobium paniculatum
UPL\n Epilobium brachycarpum
FACW-n Epilobium watsonii
FACW-n Epilobium ciliatum
OBL\n Jussiaea uruguayensis
OBLdn Ludwigia palustris
Haloragaceae
OBL\i Myriophyllum brasiliense
OBL\ri Myriophyllum hippuroides
Araliaceae
UPL\i Hedera helix
Apiaceae
FACLAi Anthriscus scandicina
OBL\n Cicuta douglasii
FAC\i Daucus carota
OBL\n Oenanthe sarmentosa
UPL\n Sanicula crassicaulis
Comaceae
FACW n Comus stolonifera
163
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Primulaceae
FACWVi Ceiitunculus minimus
FACW\i Lysimachia nummularia
Oleaceae
FACW\n Fraxinus latifolia
Gentianaceae
FAC-i Centaurium umbellatum
Convolvulaceae
FAC\i Convolvulus sepium
Polemoniaceae
FAC\n Navarretia minima
UPL\n Navarretia squarrosa
Boraginaceae
FACW\i Myosotis discolor
OBL\n Myosotis laxa
FACW\n Plagiobothrys scouleri
Lamiaceae
FACU+i Glecoma hederacea
UPL\i Lamium amplexicaule
OBL\n Lycopus americanus
FAC\n Mentha arvensis
FACW+i Mentha piperita
FACU+i Prunella vulgaris
FACW+n Scutellaria lateriflora
Stachys sp.
FACW n Stachys cooleyae
FACW\n Stachys emersonii
FAG W+n Stachys palustris
FACW-n Stachys rigida
Solanaceae
FAC\i Solanum dulcamara
FACU\i Solanum nigrum
Scrophulariaceae
FAC\i Antirrhinum orontium
OBLdn Gratiola neglecta
FACU\i Kickxia elatine
OBL\n Limosella aquatica
OBL\n Lindernia anagaflidea
OBL\n Lindernia dubia
164
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FACW\i Mazus japonicus
OBL\n Mirnulus guttatus
FACW+n Mimulus moschatus
FAC-i Parentucellia viscosa
UPL\i Verbascum blattaria
OBL\n Veronica americana
OBLdn Veronica peregrina
UPL\i Veronica persica
OBL i Veronica scutellata
FAC\i Veronica serpyllifolia
Plantaginaceae
FACU+i Plantago lanceolata
FAC+i Plantago major
Rubi aceae
FACU\n Galium aparine
FACW+n Galium trifidum
Caprifoliaceae
FACU\n Sambucus racemosa
FACU\n Symphoricarpos albus
Dipsacaceae
ABS\i Dipsacus sylvestris
Asteraceae
FACU\I Anthemis cotula
FACLJ\i Arctium minus
FACW n Aster subspicatus
FACW+i Bidens cernua
FACW i Bidens tripartita
FACW+n Bidens vulgata
FACW+n Bidens frondosa
UPL\i Centaurea cyanus
FAC\i Chrysanthemum leucanthemum
UPL\i Cichonum intybus
FACU+i Cirsium arvense
FACU\i Cirsium vulgare
FACU\n Conyza canadensis
UPL\i Crepis setosa
FAC+n Gnaphalium palustre
FAC+n Gnaphalium uliginosum
UPL\i Hypochaeris radicata
FAC-i Lactuca serriola
UPL\i Lapsa 1 ia communis
165
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UPL\i Leontodori nudicaulis
UPL\n Madia elegans
UPL\n Madia sativa
FACLJ\n Matricaria matricarloides
FACW+n Psilocarphus brevissimus
UPL\i Senecio jacobaea
FACU\i Senecio vulgaris
FACW\n Solidago occidentalis
FACW n Euthamia occidentalis
FAC-i Sonchus asper
ABS\i Tanacetum vulgare
FACLJ\i Taraxacum officinale
Alismataceae
OBL\n Alisma gramineum
OBL\n Alisma plantago-aquatica
OBL\n Sagittaria latifolia
Hydrocharitaceae
OBL\n Elodea canadensis
OBL\n Elodea densa
Potamogetonaceae
OBL\n Potamogeton ampIifo ius
OBL\n Potamogeton berchtoldii
OBL\n Potamogeton pulsillus tenuissimus
OBL\i Potamogeton crispus
OBL\n Potamogeton epihydrus
OBL\n Potamogeton filiformis
OBL\n Potamogeton foliosus
OBL\n Potamogeton pectinatus
OBL\n Potamogeton zosteriformis
Juncaceae
OBL\n Juncus acuminatus
FACW+n Juncus bufonius
FACW+n Juncus effusus
FACW n Juncus ensifolius
FACW+n Juncus oxymeris
FACW\n Juncus patens
OBL\n Juncus supiniformis
FAC\n Juncus tenuis
FACLI\n Luzula campestris
FACU\n Luzula multiflora
Cyperaceae
Carex sp.
166
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FACW n Carex aperta
FACW+n Carex arcta
FACW\n Carex athrostachya
OBL\n Carex densa
FACW\n Carex feta
FACW\n Carex Iaeviculmis
OBL\n Carex lanuginosa
FACW+n Carex lenticularis
OBL\n Carex obnupta
FAC\n Carex pachystachya
OBL\n Carex rostrata
OBL\n Carex stipata
ABS\n Carex tumulicola
FACW\n Carex unilateralis
OBLdn Cyperus erythrorhizos
FACW\n Cyperus esculentus
OBL\n Eleocharis acicularis
FACW\n Eleocharis bella
OBL\n Eleocharis ovata
OBL\n Eleocharis palustris
OBL\n Scirpus acutus
OBL\n Scirpus fluviatilis
OBL\n Scirpus microcarpus
OBL\n Scirpus validus
Poaceae
FAC-i Agropyron caninum
FACU\i Agropyron repens
FACW\i Agrostis alba
FACW\n Agrostis exarata
FAC\n Agrostis microphylla
UPL\i Agrostis tenuis
UPL\i 4Jra caryophyllea
FACW÷n Aiopecurus geniculatus
FACW\i Aiopecurus pratensis
FACU\i Anthoxanthum odoratum
UPL\i Avenafatua
OBL\n Beckmannia syzigachne
ABS\i Bromus commutatus
FACU\i Bromus moths
FACU\i Bromus secaiinus
FACLJ\i Dactylis glomerata
FACU-n Danthonia californica
FACW\n Deschampsia cespitosa
FACW-n Deschampsia elongata
FACU\i Digitaria ischaemum
FACWdn Echinochloa crusgalli
167
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OBLdn Eragrostis hypnoides
FACdn Eragrostis pectinacea
FACU-i Festuca arundinacea
FAC\n Festuca rubra
OBL\n Glyceria borealis
FACW÷n Glyceria elata
OBL\i Glyceria grandis
OBL\n Glyceria leptostachya
OBL\n Glyceria occidentalis
NAdi Heleochloa alopecuroides
NAdi Crypsis alopecuroides
FAC\n Holcus lanatus
FACW\n Hordeum brachyantherum
OBL\n Leersia oryzoides
FACU\i Lolium multiflorum
FACU\i Lolium perenne
Panicum sp.
FAC\n Panicum capillare
FACdn Paspalum distichum
FACW\n Phalaris arundinacea
FACU\i Phleum pratense
Poasp.
FAC-n Poa annua
FACU\n Poa compressa
FAC\i Poa palustris
FACU+n Poa pratensis
FACW-i Poa trivialis
OBL\n Puccinellia pauciflora
FACU\i Setana viridis
FAC\i Vulpia bromoides/Festuca bromoides
Sparganiaceae
OBL\n Sparganium emersum
OBL\n Sparganium eurycarpum
Typhaceae
OBL\n Typha latifolia
Araceae
OBL\n Lysichitum americanum
Lemnaceae
OBL\n Lemna minor
OBL\n Spirodela polyrhiza
Liliaceae
FACLI\n Brodiaea hyacinthina
168
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FACW-n Camassia Ieichtlinii
FACW\n Camassia quamash
Iridaceae
OBL\i Iris pseudacorus
SYMBOLS KEY:
ABS absent from 1986 WETLAND PLANT LIST; NORThWEST REGION
d associated with drier stages of wetlands; i.e., mudfiats, vernal pools, and
laya lakes
FAC facultative; sometimes found in wetlands (34%-66% frequency)
FACU facultative upland; seldom found in wetlands (1%-33%) and usually
occuring in nonwetlands
FACW facultative wetland; usually found in wetlands (67%-99%)
• troduced species (third column)
u tive species (third column)
NA no agreement on frequency of occurrence on wetlands\no regional
review \not considered due to recent addition to Iist\not occurring in this
region
OBL obligate; always found in wetlands under natural (not planted) conditions
(frequency greater than 99%)
UPL nonwetland; not found in wetlands in this region
no information available
+ indicates a frequency toward the higher end of the facultative categories
above (f.u,w)
- indicates a frequency toward the lower end of the facultative categories
above (f,uw)
\ indicates intermediacy within the facultative categories above OR simply
separates the first and third columns when used with species for which
there was no agreement on frequency of occurrence on wetlands, etc. (n
above)
169
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APPENDIX B
SENSI11VE, THREATENED, AND ENDANGERED SPECIES POTEN11ALLY OCCURRING
IN THE STUDY AREA
Rare plant species are often categorized in one of several ways. Ehdangered species
are any native plant species determined by the state of Oregon Department of Agriculture
(ODA) or the United States Fish and Wildlife Service (USFWS) to be in danger of extinction
throughout all or any significant portion of its range. Threatened species are those taxa that
are determined by the ODA or the USFWS as likely to become endangered within the
foreseeable future throughout all or any significant portion of its range. Sensitive implies a
species may be threatened or endangered but not enough is known about its distribution or
biology to propose it for listing. A list of rare plant species with sensitive, threatened, or
endangered status and that potentially occur within the range and habitats encompassed by
the OWS study area is provided in this appendix.
Organizations which have jurisdictional or tracking responsibilities with regard to rare
plants in Oregon are USFWS, the ODA, and the Oregon Natural Heritage Program (ONHP).
Each of these groups maintains a list defining the status of rare species. Status terminology
and species ranking varies slightly between federal, state, and ONHP lists, so status codes
from each agency are included in the rare plant list below. Many of the rare plant taxa
occurring within the range of the OWS study area are adapted to wetland conditions so FWS
wetland indicator status for each species are also provided. Additionally, superscripted
codes indicating range or habitat limits, or essential background information are provided for
species that may be marginally likely to occur in habitats within the study area. The
definitions for all codes used in the study area list are provided here.
LE = Usted as Endangered by the USFWS under the Endangered Species Act (ESA) or by
the ODA under Oregon Endangered Species Act of 1987 (OESA).
LT = Listed as Threatened by the USFWS or ODA
Cl = Category 1 Candidate Species. Taxa for which the USFWS has sufficient information
to support a purposal for listing as Threatened or Endangered under the ESA.
C2 = Category 2 Candidate Species. USFWS candidates requiring additional information
prior to proposal for listing as Threatened or Endangered under the ESA
3C = Taxa which are more abundant or widespread than previously believed and/or which
have no identifiable threats.
C = ODA Candidate Species. Species designated for study because their numbers are
believed low or declining, or their habitats are threatened or declining, and which may
potentially qualify for listing as threatened or endangered in the foreseeable future.
1 = ONHP List 1 Species. Taxa that are threatened with extinction or presumed to be extinct
throughout their entire range.
170
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2 = ONHP List 2 Species. Taxa that are threatened with extirpation or presumed to be
extirpated from the state of Oregon.
3 = OHNP List 3 Species. Taxa for which more information is required before status can be
determined, but which may be threatened in Oregon or throughout their range.
4 = ONHP Ust 4 Species. Taxa which are of concern due to rarity or declining habitat or
numbers, but which are still too common to be proposed as threatened or endangered.
crg = Taxon typically is found in the Columbia River Gorge but may occasionally be noted in
habitat found in the study area.
fw = Taxon flowers in winter making it difficult to identify during the field season.
h = Taxon typically occurs in a habitat different from study area habitats, but islands of
appropriate habitat may occur in the study area.
n = Taxon generally occurs north of the study area.
pe = Taxon is possibly extinct
peo = Taxon is possibly extinct in Oregon, but is more common elsewhere.
s = Taxon generally occurs south of the study area.
OBL = Obligate hydrophyte - Nearly always occurs in wetlands (>99% of the time).
FACW = Facultative wetland - Usually occurs in wetlands (>66-99% of the time).
FAC = Facultative - Commonly occurs in both wetlands and uplands (>33-66% of the time in
wetlands).
FACU = Facultative upland - Usually occurs in uplands, but may occasionally occur in
wetlands (<33% of the time).
List of Sensitive, Threatened, and Endangered Species that Might Occur in the OWS Study
Area. ________
Species Name
Common Name
Wetland
Status
FWS
Status
ODA
Status
ONHP
List
Agoseris elata
tall agosens
FAC
—-
—-
2
Aster curtis
white-topped
aster
moist
prairie
.C2
C
1
171
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Species Name
Common Name
Wetland
Satus
FWS
Status
ODA
Status
ONHP
List
Carex comosa
bristly sedge
OBL
-
---
3
Carex livida
pale sedge
OBL
---
---
2
Carex macrochaeta
Alaska long-
awned sedge
FACW-
---
---
2
Castilleja levisecta”°
golden
paintbrush
----
Cl
C
1-ex
Cimicifuga elata
tall bugbane
moist
woods
---
C
1
Delphinium
leucophaeum
white rock
larkspur
FACU
C2
C
I
Delphinium nuttallii
Nuttall’s
larkspur
moist
open
areas
---
—-
3
Dulichium
arundinaceum
three-way
sedge
OBL
---
—-
3
Erigeron decumbens
var. decubens 8
Willamette
daisy
—--
Cl
LE
1
Heteranthera dubia
water-star
grass
aquatic
---
—-
4
Howellia aquatilis °
howellia
OBL
Cl
---
1-ex
Lathyrus holochlorus
thin-leaved
peavine
—--
3C
—-
4
Lomatium
bradshawii 8
Bradshaw’s
lomatium
FACW
LE
LE
1
Lupinus suiphereus
var. kincaidii
Kincaid’s lupine
—--
C2
C
1
Meconella oregana
white
meconnella
spring
moisture
—-
C
1
Montia howellii
Howell’s montia
FACW-
C2
C
1
Ronppa columbiae
Columbia cress
OBL
C2
C
1
Sidalcea campestris
meadow
sidalcea
—-
3C
—-
4
172
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Species Name
Common Name
Wetland
Status
FWS
Status
ODA
Status
ONHP
List
Sidalcea nelsoniana
Nelson’s
sidalcea
wet prairie
CI
LT
I
Sullivantia oregana °
Oregon
sullvantia
wet cliffs
and rocks
C2
C
1
Utricutaria minor
lesser
bladderwort
OBL
—-
---
2
Wolfia columbiana
Columbia
water-meal
OBL
—-
—-
2
References and Resources
Eastman, D.C. 1990. Rare and Endangered Plants of Oregon. Beautiful America
Publishing Company. Wilsonville, Oregon.
Hitchcock, CL. and A. Cronquist. 1973. Flora of the Pacific Northwest. University of
Washington Press. Seattle.
Interagency Cooperative Publication. 1989. Federal Manual for Identifying and Delineating
Jurisdictional Wetlands.
Meinke, R.J. 1982. Threatened and Endangered Plants of Oregon: An Illustrated Guide.
United States Fish and Wildlife Service. Portland, Oregon.
Oregon Department of Agriculture. 1989. Oregon Administrative Rules 603, Division 73.
Plants: Endangered, Threatened and Candidate Species. Plant Conservation Biology
Program, Natural Resources Division. Salem, Oregon.
Oregon Department of Agriculture. 1991. Oregon State List of Candidate Plant Species
Under Review for Listing as Threatened or Endangered, Per OAR 603-73-080. Plant
Conservation Biology Program, Natural Resources Division. Salem, Oregon.
Oregon Natural Heritage Program. 1991. Rare, Threatened and Endangered Plants and
Animals of Oregon. Oregon Natural Heritage Program, Portland, Oregon.
Peck, M.E. 1961. A Manual of the Higher Plants of Oregon. 2nd. Edition. Binford and Mort,
Publishers. Portland, Oregon.
Reed, P.B., Jr. 1988. National List of Plant Species that Occur in Wetlands: Region 9 -
Northwest. U.S. Fish and Wildlife Service, Washington, D.C. Biological Report 88(24).
173
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EPA ERL-Corvallis Library
I III II 11111 III 1111111111 III 11111 III 1111 1111
00006 19 1
EPA/600fR-95/24 O
November 1993
USER’S MANUAL:
AVIAN RICHNESS EVALUATION METHOD (AREM)
FOR LOWLAND WETLANDS OF THE COLORADO PLATEAU
by:
Paul R. Adamus
ManTech Environmental Technology, Inc.
USEPA Environmental Research Laboratory
200 SW 35th St.
Corvallis, OR 97333
EPA Project Officer:
Mary E. Kentula
USEPA Environmental Research Laboratory
200 SW 35th St.
Corvallis, OR 97333
-------
DISCLAIMER
This project has been funded by the U.S. Environmental Protection Agency (EPA) and
conducted through contract 68-C8-0006 to ManTech Environmental Technology, Inc.
This document has been subjected to the Agency’s peer and administrative review and
approved for publication. The opinions expressed herein are those of the author and do
not necessarily reflect those of EPA. The official endorsement of the Agency should not
be inferred. Mention of trade names or commercial products does not constitute
endorsement or recommendation for use.
This document should be cited as.
Adamus, P.R. 1993. User’s Manual: Avian Richness Evaluation Method
(AREM) for Lowland Wetlands of the Colorado Plateau. EPAJ600/R-93 O
+ diskette. U.S. Environmental Research Laboratory, Corvallis, Oregon
Additional copies of the manual are available at cost from:
National Technical Information Service (NTIS)
5285 Port Royal Rd.
Springfield, VA 22161
(phone 1-800-553-NTIS)
-------
ACKNOWLEDGMENTS
The project of which this manual and software are a part was conceived by Gene Reetz and
David Ruiter of EPA Region 8. Computer programming of the AREM models was
performed by Rosemary Owen of the Computer Sciences Corporation. Mary E. Kentula of
the Wetlands Research Program, USEPA Environmental Research Laboratory-Corvallis,
provided many useful suggestions and administrative support. Brooke Abbruzzese was the
project manager for ManTech Environmental Technology, Inc. The manual and software
benefitted greatly from the review comments of Kristi DuBois, Ted Ernst, Cindy Holland,
Ronald Lambeth, Gerald Niemi, Raymond J. O’Connor, Jeff Price, Antisa Webb, and
Christopher Welsh.
-------
CONTENTS
1.0 “AREM” AND WHAT IT CAN DO
2.0 NSTRUCT1ONS
2 1 Field Phase
2.2 Program Installation and Analysis Phase
2.3 Summary of the AREM Program Steps
2.4 Interpretation Phase
2.5 Editing Options
2.6 Possible Applications of the Editing Program
2.7 Adapting AREM for a New Region or Ecosystem Type
45
45
45
45
48
49
51
53
54
54
55
56
56
57
4.0 LITERATURE CITED 58
Appendix A. Field Form: Site Documentation
Appendix B. Field Form (Long)
Appendix C. Field Form (Short)
....9
10
26
31
41
42
3.0 LITERATURE DOCUMENTATION FOR AREM
3.1 Documentation of Indicator Thresholds
31.1 Introduction
3.1.2 Area Thresholds
3.1.3 Width Thresholds
3.1.4 Distance Thresholds
3.1.5 Other Thresholds
3.2 Documentation of Weighting Factors
3.2.1 Species Dependency on Wetland/Riparian
3 2 2 Relative Abundance
3.2.3 Taxonomic Uniqueness
3.2.4 Neotropical Migrant Status
3.2.5 Official Conservation Designations . .
3.2.6 Hunted Status
Habitat
-------
LIST OF TABLES
Table 1. Advantages of using AREM 3
Table 2. Limitations and assumptions of AREM 4
Table 3. The context for properly using AREM 5
Table 4. Example showing how AREM scores are calculated 25
Table 5. Use of AREM to select wetland combinations that optimize protection of regional
avian diversity 29
Table 6. Instructions for AREM’s editing program (EDITAREM) 34
Table 7. Meaning of codes used in the species habitat relationships database 36
LIST OF FIGURES
Figure 1. Subregions of the Colorado Plateau addressed by this report 2
Figure 2. AREM’s four introductory screens 12
Figure 3. Part of A.REM’s indicator list 14
Figure 4. AREM’s menu for selecting subregion and seasonal period 15
Figure 5. Example of output in AREM’s score table 16
Figure 6. Menu for specif ’ing the seasonal period upon which species are to be weighted
by abundance 17
Figure 7. Menu for finishing the AREM analysis or changing the weights 18
Figure 8. Menu for changing weights of a species characteristic 19
Figure 9. AREM’s concluding instructions 20
Figure 10. Example of documentation output file from an AREM evaluation 21
Figure 11. Menu for combining bird lists and scores from multiple wetlands 30
Figure 12. Menu for selecting AREM databases to edit 33
Figure 13. Part of AREM’s wildlife habitat relationships database (WI-IRBASE) 35
Figure 14. Part of AREM’s WEIGHTS database 37
Figure 15. Part of AREM’s REGIONS database 38
Figure 16. Part of AREM’s TAX [ NF database 39
Figure 17. Menu for adding indicator conditions 40
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1.0 “AREM” AND WHAT IT CAN DO
This manual describes how to use and interpret the “Avian Richness Evaluation Method”
(AREM), a standardized procedure for estimating the bird species composition and richness
of lowland wetlands of the Colorado Plateau (Figure 1). Instructions for using AREM are
found in Section 2.0, and no additional training courses should be needed. To apply
AREM correctly, you should first read the information in Tables 1-3. If you desire an in-
depth understanding of the concepts and database programming logic of AREM, you may
refer to Section 5.0 of Adamus (1993a). However, it is not essential to review that
information before using AREM. Section 3.0 of the present manual provides
documentation for some of AREM’s individual indicators.
When used correctly, you can expect AREM to do the following:
o Assign a score to each evaluated wetland, which represents the number of bird
species that could occur in the wetland, multiplied by an estimate of the suitability
of the wetland for each species.
o List the species likely to occur in the evaluated wetland. Such a list can be
combined with lists predicted for other wetlands, to identify minimum combinations
of wetlands that will provide habitat for all bird species in an area.
o Tally the number of species likely to occur in the evaluated wetland and which have
particular characteristics, e.g., neotropical migrants, uncommon or game species. If
desired, users can assign scores to these characteristics and use them as “weights”. in
deriving the wetland score.
Some examples of situations where AREM might be used to assist and document resource
decisions are as follows:
Situation 1. Mitigation Calculations. Resource agencies currently spend time “cover-
typing” lands that will be altered in connection with salinity control projects, water
diversions, and other developments where compensatory mitigation has been deemed
necessary. This process involves measuring various categories of habitat before a project is
begun and then estimating any shifts in acreage that will occur among categories as a result
of the project. Acreages in each cover type category that are believed to exist both before
and after the project are multiplied by coefficients, determined through use of HEP’, that
indicate suitability of each category for selected species during both time periods. In this
manner, net change in habitat suitability is predicted, at least for a few selected species.
Where wetland and riparian cover types are the habitats that are expected to change, AREM
might be used in lieu of (or in addition to) HEP to calculate the habitat suitability
coefficients. If non-wetland cover types are also present, AREM could be expanded and
The Habitat Evaluation Procedures (HEP) of the US Fish and Wildlife Service (1980)
I
-------
Figure 1. Subregions of the Colorado Plateau addressed by this report.
SUBLETIE
FREMONT
•
I WYOMING SUBREGION
/ Big Sandy S.C.A.
SWEE1WATER
C.$RBON
Legend
Stat. border
a County border
S.CA - S.Jintty Control
Me.
COLORADO
RIO BLANCO
GARFiELD
UNCOLN
U INIA
UTAH
SAN JUAN
2
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Table 1. Advantages of using AREM.
I Using AREM is relatively simple and rapid Field data collection requires less than 15 minutes per
wetland Data entry and analyses require less than 30 minutes per wetland The models AREM uses
to predict habitat suitability for individual species are mathematically simpler than those used by the
Habitat Evaluation Procedure (HEP, U.S. Fish & Wildlife Service 1980) and thus may be easier to
understand and explain
2. AREM is one of only a few rapid evaluation methods that actually have been validated to some
degree, i e, accuracy during the breeding season was measured through comparison of observed with
predicted conditions (see Adainus 1993b).
3 The scores that result from an AREM evaluation have a high level of accountability. Users can call
up the database for any species to closely examine the habitat model supporting that species Users can
also call up any indicator condition to identify all species predicted by that condition. This feature is
of potential use in predicting a species’ response to wetland change, e g., for impact analysis or planning
of wetland enhancements
4. AREM users, even those with limited computer knowledge, can interactively edit the database and
revise models for any species. This allows users to adapt AREM for other regions and wetland/riparian
types, provided habitat requirements of all bird species in these areas are known, or can be determined
with sufficient accuracy
5. AREM is perhaps the only rapid habitat evaluation method whose major organizing theme and
endpoint is biodiversity Many government agencies are mandated to account for the impacts of their
activities on biodiversity, and public concern over the global and regional loss of biodiversity appears
to be growing.
6. In contrast to 1-IEP, AREM does not require the user to base a wetland’s score on a few presumed
‘indicator species.” Users do not need to assume that habitats which are found to be optimum for a few
species will also be suitable for many species, i.e, be biodiverse
7 Species lists predicted by AREM for various wetlands can be combined in any local area or subregion
to determine which particular combination of wetlands cumulatively supports the greatest number of
species (see p 28) This “optimization process’ can be further focused by applying constraints related
to species characteristics, land ownership, manag ..ment costs, or other factors As such, use of AREM
can provide a complementary, local refinement of the “gap analysis” approach currently being applied
at state and regional levels by the U.S Fish and Wildlife Service (Scott et al 1993)
8 One of AREM’s outputs — the “unweighted richness” score — is the actual number of species predicted
to occur in a wetland. As such, this is an ecological parameter that can be validated empirically.
9. AREM does not require the user to conduct bird surveys or, for that matter, be an expert on birds or
other wildlife
3
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Table 2. Limitations and assumptions of AREM.
1 AREM is a comproi ise between convenience and technical certainty. The technical certainty
of many of the species habitat models that comprise AREM might be increased by formulating them
in a more mathematically complex manner and explaining their details and assumptions at greater
length, but in some cases this would sacrifice speed of application, replicability, and clarity to the
typical user AREM is intended to be intermediate in complexity between the simple, few-indicator
wildlife habitat relationship (WHR) models used in landscape classification and the multi-indicator,
few-species HEP models used for site evaluations AREM shares some of the limitations of WHR’s
as described by Morrison et al. (1992) and limitations of 1-IEP described by Van Home and Wiens
(1991), but avoids others. I
2 Indicator conditions used in AREM’s species models in some cases are related to a species’
presence in a loosely deterministic manner, but in other instances are related only empirically, i.e.,
they correlate with a species’ presence but have not necessarily been shown to control use of
habitats through explicit effects on food, cover, or reproduction.
3. Wetlands are dynamic systems, and scores assigned by any evaluation method can change as a
result of natural vegetative succession, flood or drought, management actions, or other factors
4. AREM pertains only to avian biodiversity. It is not possible to predict the situations in which
wetlands that contain a relatively great variety of bird species also have a relatively great variety
of plants, insects, amphibians, or whatever
5 It cannot be assumed that wetlands that are species-diverse will always be diverse at genetic,
community, or functional levels, although this is often the case
6 It cannot be assumed that wetlands that are species-diverse will contain viable populations of
most species, or greater ecological “integrity,’ ‘health,” or “sustainabilit .” although this is usually
the case
4
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Table 3. The context for properly using AREM.
I AREM is intended for application only to lowland wetlands and nparian areas larger
than 0 1 acre, located within the Colorado Plateau region of western Colorado, eastern
Utah, and southwestern Wyoming (Figure 1, p 2)
2 Users should be capable of recognizing all indicator conditions specified in the field
forms (Appendices B and C). When evaluating a wetland, users should note situations
in which they feel information requested by the field forms required considerable
judgement, and report this with the results
3. As is true of other rapid methods for habitat assessment, AREM’s habitat relationship
models for individual species cannot be used to definitively measure the relative or
absolute abundance or density of these species’ populations Many factors not included
in the species models, e g., weather, determine population size and even presence/absence
in a given wetland In some cases the influence of such factors on species distributions
will exceed the influence of habitat quality, but AREM assumes that for most species,
their influence on species presence/absence will be less.
4 AREM should not be used to compare wetlandlripanan habitats with other habitats.
Within the Colorado Plateau lowlands, species habitat scores from AREM estimate the
suitability of a wetland or npanan habitat relative only to the suitability of other wetland
or ripanan habitats In some circumstances, some species included in AREM might find
nonwetland habitats more suitable.
5 Scores from AREM should not be used in lieu of species occurrence data from actual
surveys of a wetland, provided such data have been collected with sufficient intensity and
using appropriate methods
6 Scores from AREM should be considered as only one of several possible inputs used
in the decision-making process Under most circumstances it is inappropnaze to use
AREM as the only means for deciding whether mitigation should be required A habitat
index, defined as the product of an AREM score and wetland acreage, can be computed
if desired The values from such an index potentially can be used as one input in
mitigation deliberations, monitoring of restorationlenhancement projects, and description
of the future biodiversity consequences of specified impacts to the indicator conditions.
However, the commonly associated practice of using values from such indices to
rationalize a decision to offset the loss of a collectively large acreage of low-quality
wetlands with the creation of a small acreage of high-quality wetlands must be viewed
cautiously As is true of other methods, caution is needed because use of simple
multiplication presumes that species richness is related to habitat acreage (wetland size)
in a direct, linear manner. This is not necessarily valid because (a) the effect of wetland
size on richness can vary by species composition, season, surrounding landscape
charactenstics, wetland shape, and other factors, (b) wetland size is “double-counted,”
first as it is included in individual species models, and second as it is applied as a
multiplier, and (c) “enhanced” habitat quality does not necessarily compensate for lost
h hit t cp we
5
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modified by a knowledgeable ornithologist to include these (see Section 2.7 for guidance in
adapting AREM to other habitats or regions).
Situation 2. Diagnosing Impaired Wetland Quality. Where wetlands are officially
considered by agencies to be “waters of a state” or where they exist within certain public
trust lands (e.g., National Wildlife Refuges), a legal need sometimes arises to determine the
degree to which wetland quality has been impaired. AREM alone cannot determine this.
However, AREM can assist in diagnosing the presence of contamination problems by
defining which species “should” be present in a wetland having a particular habitat
structure, If properly designed surveys then fail to find the predicted species, it might be
because non-physical (e.g., chemical) factors unmeasured by AREM are discouraging
wetland use by birds. Some caution is necessary because species absence could be due to
weather conditions, to demographic factors (e.g., suitable habitats being “undersaturated”
with individuals because of impacts to populations that have migrated from neotropical
wintering areas 2 ), or weaknesses in particular species models that comprise AREM.
Nonetheless, AREM could be useful as an initial screening tool to help decide whether
more effort should be committed to verify that a problem exists.
Situation 3. Selecting Appropriate Indicator Species. By defining which species to
expect in particular types of wetlands, AREM can narrow the list of species to be
considered for potential use as “indicators” in programs to monitor water quality or physical
habitat suitability. Selecting appropriate indicator species is crucial to proper use of HEP,
as well as to the development of wetland biocriteria and the accurate monitoring of wetland
contamination.
Situation 4. Targeting Habitat Enhancements Active management of wetlands will
usually be most effective when it focuses on improving conditions for species with low
species habitat scores, while maintaining conditions suitable for species with high species
habitat scores. In combination with other considerations, AREM can be used in this
manner to suggest habitat features whose enhancement will support the largest variety of
species overall, or of species having a particular attribute.
Situation 5. Wildlife-based Classification of Wetland Habitats. Wetland “types” are
commonly defined by their vegetative communities. Wildlife communities or individual
species also can be a useful primary or secondary feature in classifying wetlands for
scientific or administrative purposes. AREM can assist such classifications by predicting
bird species and richness that are associated not only with vegetation, but also with other
Local absence of a species whose regional populations appear to be Increasing is particularly suggestive of contamination problems in
the local habitat when the habitat has been determined to be otherwise suitable (pets comm, R. 3 O’Connor, Dept of Wildlife, University
of Maine, Orono, Maine)
6
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environmental factors. Statistically-defined, wildlife-based classes of wetlands could be
identified by applying AREM to a probabilistic sample of wetlands in a region.
Situation 6. Optimizing Biodiversity Protection. Resource agencies and conservation
groups sometimes have opportunities to purchase or trade properties to enhance regional
biodiversity. When biological survey data from the subject properties are lacking, AREM
cair be applied (at any season) to predict avian richness of individual properties. The
AREM computer program (p. 28) can then be used to pool the predicted species lists from
multiple wetlands, to determine which combination of wetlands is likely to support the
greatest diversity. This estimate can be focused further by applying constraints related to
land ownership, species characteristics, management costs, or other factors. As such,
AREM can provide a complementary, local refinement of the “gap analysis” approach
currently used for ecosystem management and biodiversity planning at state and regional
levels by the U.S. Fish and Wildlife Service (Scott et a]. 1993).
Intended users of AREM are consultants and employees of government agencies, who have
at least a Bachelor’s degree in one of the environmental disciplines. Users must be able to
recognize a few of the major vegetation types of the Colorado Plateau (e.g., salt cedar,
willow).
7
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2.0 INSTRUCTIONS
The steps associated with a wetland assessment using AREM can be organized into three
phases: Field Phase (Section 2.1), Analysis Phase (Section 2.2), and Interpretation Phase
(Section 2.4).
2.1 Field Phase
Step 1 . Locate the wetland.
AREM can be applied to all or part of any lowland wetland or riparian area in the
Colorado Plateau region (Figure 1). The only requirement is that the part of the
wetlandlriparian area to be evaluated must be at least 0.1 acre in size (about 66 ft to a side,
if squarish). AREM can be used to evaluate riparian and wetland areas, defined broadly as
ecosystems characterized by the presence of soils that are saturated at least periodically and
whose current vegetation is predominantly of species adapted to high soil moisture
conditions. To perform an AREM assessment, you do not need to first delineate wetland
boundaries using a formal procedure.
In some instances it is difficult to distinguish, for purposes of evaluation, where one
wetland should be considered to end and another begin. For example, in river corridors
you may be faced with the need to assign a single rating to a contiguous area that extends
many miles upstream and downstream. If you have time to accurately assess the entire
corridor as one unit, the resulting AREM rating will probably be the truest representation of
the corridor’s actual habitat value. However, it is seldom practical to perform such an
exhaustive assessment with acceptable accuracy. Even if it were, owners of a specific
parcel within the corridor often wish to know, “What is the habitat value of my particular
property?” Or, perhaps you wish to compare the relative values of two habitat patches
within a wetland, each of a different cover type. AREM allows you to do so.
The area you evaluate should be the largest area that you can view accurately while
meeting your particular assessment objectives. What is most crucial is that you
document the boundaries of whatever area you evaluate, e.g., by including on your field
form a sketch of the wetland showing landmarks. Doing so makes it possible for another
person to repeat your evaluation with greater precision, and thus maintains the credibility of
the results.
Step 2 . Answer the AREM Questions.
Make a copy of the field forms (Appendices A, B, and C) and then visit the wetland.
Complete the documentation form (Appendix A) and then answer the questions in the long
8
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form (Appendix B) in sequence, placing marks in the appropriate spaces. The first few
times you use AREM, read through each question and footnote carefully, making sure you
understand it. Recognize that although a few questions are “multiple choice” (one answer
only), for most it is appropriate to check several items. Also, even though AREM is
designed for use by one person, answering questions as a group can improve the credibility
of the results. After you have used AREM several times, you will find it faster to use the
short form (Appendix C), which requests the same information in the same order as the
long form (Appendix B). However, you may still wish to use the long form periodically to
refresh your memory of some of the definitions and special conditions that apply.
It is crucial that you answer the questions in a way that reflects habitat conditions at the
season for which you want information. For example, if you want to base a wetland
decision on the relative value of a wetland to migratory shorebirds, you should not use an
AREM assessment of mud habitat (question 5) made during November because in many
irrigated wetlands the extent of mud habitat in November is much greater than during May,
July, and August when most shorebirds are migrating through the region. If an answer is
needed before a wetland can be visited during all desired seasons, the best approach is to
contact local sources with an historical knowledge of the habitat indicators that are most
likely to change seasonally. Also, you might review any appropriate aerial photographs
taken during these periods. In fact, wherever they are available, detailed aerial photographs
from several time periods are an excellent ancillary source of information that you can use
to cross-check assumptions you might have made in the field.
2.2 Program Installation and Analysis Phase
Step 3 . Load AREM on a Computer and Begin Program.
A disk containing the AREM computer program accompanies this report. The program on
this disk is necessary to convert the information you marked on your field forms into
biodiversity scores and species lists. The program runs on IBM or IBM-clone personal
computers with MS-DOS version 3.1 or later, and requires a hard drive with 580K RAM
and about 2 megabytes of storage available, as well as a floppy disk drive slot capable of
accepting a high-density 3.5-inch disk. No other specialized software is required. The
program runs most rapidly if the files on the disk are first transferred to a computer’s hard
drive 3 . To do this, proceed as follows, pressing the “Enter” key after each step:
After uncomprcssulg, you should find the following 16 files arem bas, arcmc2 cxc, arcmsctexc. chklistms, comb2 cxc. conibarem bat,
editarem bat, ediiarm cxc. habtable dbf, regcom nts, regions dbf, repctexe. taxinfdbI. weights dbf. wghtcom ntx, whibasc dbf You may delete
the aremset cxc file at this point, provided you have maintained a copy on a disk or in another directory
9
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Computer Says: You Type: What This Does
C:\> md arem makes a new directory named “AREM”
C:\> cd\arem puts you in the new AREM directory
Now, insert the AREM source disk into your computer’s disk drive.
C:’>arem copy a:*.* copies the compressed file into the hard drive’s
AREM directory 4
C:\>arem aremset uncompresses the compressed files
C:\>arem arem starts running the program
Be sure to start the program as directed above, by typing “arem,” rather than by typing the
name of the execution file (aremc2.exe). Also, be sure to retain the original disk containing
the program, because when you later edit any of the files (after transferring them to your
hard drive), a backup copy of the original is not automatically saved.
From this point on, the AREM analysis program is menu-driven. That is, instructions will
appear on your computer screen telling you what to do at each step. Basically, you will be
matching information from your completed field forms (Appendices B and C) with similar
information on the screen, and then prompting the computer to analyze it.
2.3 Summary of the AREM Program Steps
The following pages present the computer screens in the order they appear when you use
the AREM programs. Each screen is accompanied by text that clarifies what the user is
expected to do. The analysis sequence is as follows:
AREM Program
Introductory screens, assign a file name (Figure 2)
Mark the indicators from a list (Figure 3)
Mark the subregion and season (Figure 4)
View the wetland scores (Figure 5)
Quit, list scores/species, or change weighting factors (Fig.7)
Change weighting factors (Figure 8)
Instructions for printing (Figure 9)
View the output file (Figure 10)
If this doesn’t work, type b * *
10
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COMBAREM Program (optional)
Combine species lists from different wetlands (Figure 11)
EDITAREM Program (optional)
Select a database to edit (Figure 12)
Computer keys used for editing (Table 6)
Edit the WHRBASE database (Figure 13)
Codes for WI-IRBASE (Table 7)
Edit the WEIGHTS database (Figure 14)
Edit the REGIONS database (Figure 15)
Edit the TAXJ}JF database (Figure 16)
Add an indicator (Figure 17)
11
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Figure 2 AREM’s four introductory screens.
AVIAN RICHNESS EVALUATION METHOD (AlIEN)
Version 1.
Computer program for predicting bird diversity
in lowland wetlands of the Colorado Plateau
Concept, database, and species nodels by:
Paul R. Adamus, ManTech Em I ronmenta I Technology Inc . it
Email: adanuspPk ira .csos .orst .edu
Computer programming b9:
Rosemary Owen, Computer Sciences Corporation”
EPA Project Officer: Nary E. Kentula”
“IJSEPA Environmental Research Laboratory
ZHU SW 35th St.
Corvallis, OR 97333
(503) 754—4666
TO ADVANCE TO NEXT PAGE
INTRODUCTION
The avian richness evaluation method (AREPI) which this software supports
is fully described in the publications:
Adamus, P.R. 1993. Irrigated Wetlands of the Colorado Plateau:
Infornation Synthesis and Habitat Evaluation Method. EPA/6UO”R—93/071.
U . S. Environmental Protection Agency, Environmental Research
Laboratory, Corvallis. Oregon. NTISftPB931B626O
Adarms, P.R. 1993. User’s Manual: Avian Richness Evaluation Method
(AREM) For Lowland Wetlands of the Colorado Plateau. U.S.Eiwironnental
Protection Agency, Environmei tal Research Laboratory, Corvallis, Oregon.
These are available from the National Technical Information Service,
(NTIS), phone 1—8H0—553-684?. Before using ARE1I, be sure you understand
its limitations and the proper context for its use.
PRESS TO ADVANCE TO NEXT PAGE
12
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Figure 2 (continued)
AREPI uas developed durin 1992—93 with the support of US EPA Region 8.
Work uas conducted at the U.S.. Environmental Protection Agency (EPA)
Research Lab through contract fl&8—C8—ø8@6 to ManTech Environmental
Technology Inc. This com uter program has been subjected to the
Agency’s peer and administrative review and approved for general use.
Any opinions represented herein are those of the author and do not
necessarily ref lect thos of EPA. The off ic ia I endorsement of the Agency
should not be inferred.
This program is Furnished by the U.S. Government and is accepted and used
by the recipient Wit)) th express understanding that the U.S. Government
gives no uarranties. expressed or implied, concerning the accuracy,
reliability, usability, or suitability for any particular purpose of the
information contained in this program. The United States shall be under
no I jab iii ty to any person by reason of any use made thereof. Tb is
program belongs to the UJS. Gouernu ent therefore, the recipient further
agrees not to assert any proprietary rights therein, or to represent
this program to anyone as other than a U.S. Government program.
PRESS (ENTER> TO ADVANCE TO NEXT SCREEN
13
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Figure 3 Part of AREM’s indicator list.
1. BICUATER 4
2. ANYWATER 4
3. OPENOTHER 4
4. STILLUATER
4. FISH
4. API’HIRS
4. ENRICHED
4. DRAWDOUN
S. BARE
6. NUDBIG
7. TREEIN 4
7. YREENEAR
8. FORESTDENS
8. FORESTOPEN
8. WOODDENS
This list contains the habitat indicators needed to predict the presence of 165 bird species in the Colorado
Plateau Each abbreviated term corresponds to a question in the field form (Appendices B and C), which is
numbered and named identically Some numbers are repeating because they refer to different conditions of
the same indicator You will notice that when you mark particular indicators, AREM automatically marks
certain others, the program also prohibits you from marking some others These programmed actions are part
of an error.checking routine that helps ensure that the field form has been interpreted consistently and
completely Be sure you do not attempt to assess a wetland by marking directly the abbreviated
indicator conditions shown on the screen Use the field form first. because the meaning of some of the
indicator terms is quite specific and not clearly conveyed by the abbreviated terms
After you have marked all the appropriate indicators and pressed the ESC key, the AREM program extracts
all Colorado Plateau species that use such habitats. The directions you give the computer in the next screen
(Figure 4) will reduce the list of species to just those occurring at a particular season or seasons, in a
subregion you specify. If the program fails to run or takes longer than 10 minutes to process data after you
have pressed “ESC” to initiate data processing, reboot your computer (e g, by turning it off, then on) and
type this at the C \> prompt set clipper ”41E:0
If you later wish to print a list of the indicators you had checked above, at the completion of the AREM run
you should retrieve the file “xxxx hab,” where “xxxx” represents whatever file name you assigned earlier
(Figure 2, fourth screen) This file is in ASCII format, and to pnni it you can either type “copy xxxx.hab
pm” at the C \> prompt, or call up your word processing program and have that program convert it to a
compatible format before you try printing it
Press SPACE—BAR to tag or untag items
marked on the field form
Press U to move cursor up and doun
Press ESC to continue or to exit
14
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Figure 4 AREM’s menu for selecting subregion and seasonal period
Select the periods(s) for which you
uant .a species list an l/or scores.
Select only the period(s) that
would be represented by the field
data you entered.
BREED I NC
NIGRATION
See report For definit:ions
The subregions listed in the top box are major areas of the Colorado Plateau where salinity control projects
are being implemented (see Figure 1, p 2) If you wish to evaluate wetlands in a part of the Colorado
Plateau that is not listed, select the subregion closest to that area Using AREM for areas outside the
Colorado Plateau or for montane wetlands (>7000 ft elevation) will give erroneous results
As noted in the lower box, be sure the conditions you marked for the habitat indicators in an earlier screen
(Figure 3) are appropriate for ll the season(s) you mark in the lower box of this screen Where habitat
conditions change greatly between seasonal periods (as is norniall the case), AREM should be run separately
for each period, if the objective is to estimate year.round avian diversity (as is usually the case) Indicators
that are most likel to change between seasonal periods include the extent of surface water and open water
(#2. 3), bare soil (#5), and intensive grazing (#19) You should use the following calendar dates to define
seasonal periods Breeding June 1 - August 15, Migrating March 1 May 31, and August 16 - November
30 Wintering December 1 - February 28 These dates are appropriate for the majority of Colorado Plateau
wetland species It is recognized that effects of grazing, burning, and mowing can extend over several time
periods For example, burning increases the predominance of salt cedar ( Tamanx rainostssima)(Busch and
Smith 1993), and the effects of this change persist for years in a wetland This would be accounted for by
shrub type (#12) or density of herbaceous vegetation (#14)
After you have marked items in the upper and lower boxes and pressed ESC, the program consults a
supporting database and eliminates from further consideration all species not occurring in that region during
that season Thus, the results are the species that are present during all of the periods marked The next
screen (Figure 5) then appears, showing scores based on this selection of species
Select the subregion
Grand Valley, CO
Lower Gunnison/Uncompahgre, CO
Cortez.’flcEltso Creek, CO
Uinta Basin/Price”San Rafael UT
Big Sandy, WV
Highlight the region the uetiand is in.
Press Enter to select that region.
15
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Figure 5 Example of output in AREM’s score table.
WETLAND SCORES
Cutoff Level for Species Habitat Scores:
>0 >.2 5 >.50 >.75
all Possible nost
spp. conservative
,Unueighted Habitat Score 8.18 0.18 5.81
lUnweighted Richness Score 14.08 14.00 9.88
Habitat Score Weighted By Species
Relative Dependency on Wetlands 18.50 18.58 13.76 1.71
Relative Abundance 10.01 40.01 30.52 0.0 11
Taxonoriic Uniqueness 42.57 42.57 31.08 7.71
Ileotropical Migrant Status 38.08 38.08 31.34 8.57
Official Conservation Designations 23.06 23.86 21.49 886
Hunted Status 8.10 8.18 5.81 0.86
PRESS TO CONTINUE
This is the most important of AREM’s screens It contains the vanous scores that have been calculated from
the input information you provided. Higher scores indicate evaluated areas that are likely to provide habitat
suitable to a greater number of bird species Specifically, the “unweighted richness score’ is the number of
species predicted to occur; the “unweighted habitat score” is the species habitat score (on a scale
representing habitat suitability of 0 to I, for each species) summed across all species, the “weighted habitat
score” (“Habitat Score Weighted by Species’) is the product of each species’ species habitat score and a
weighting coefficient, summed across all species Cutoff levels are thresholds for species habitat scores; their
denvation and meaning is best demonstrated by the example in Table 4.
To interpret these scores for use in resource decisions, see Section 2 4 of this manual To trace the
calculations that led to the scores in a particular instance, you can select the option, “List wetland scores (to
report file for pnntlng)” on a later screen (Figure 7)
16
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Figure 6 Menu for specifying the seasonal period upon which species are to be weighted
b abundance.
This screen might seem redundant because you already specified seasonal information at an earlier menu
prompt (Figure 4) However, at the earlier prompt you could select multiple periods whereas here only one
seasonal period can be selected The reason is that the information in the earlier screen was used to elLmmate
species that are absent during one or more specified periods, whereas this screen is used to weight the
occurring species by their abundance Because abundance of most species changes by seasonal period, the
weighting calculations are feasible only if based on a single period
Pligratiig
Ipi I Mer jig
Meig) ted Habitat! Score b :Relatiue Abundance
For this characteristic. you can specify only one period
for which you want species weighted by their abundance.
Press Enter to se’lect the period you highlighted
.. 1. :
17
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Figure 7. Menu for finishing the AREM analysis or changing the weights.
List Wetland Scores and Species lists
Change weighting Factors
QUIT
r Press Enter to select the highlighted option I
At this point in most applications you will select the option QUIT However, if you select the first option
(‘List wetland scores “) before quitting, the program will save not only the wetland scores (Figure 5), but
also lists of predicted species and their weights, and the list of habitat indicators you selected earlier (Figure
3) These can be viewed by moving the cursor to QUIT and pressing the Enter key again Figure 9 will
appear, follow its instructions to print the scores, predicted species, and habitat indicators
If you select the second option (“Change weighting factors”), the upper screen lets you change the weights
preassigned to different species characteristics For example, currently the AREM program assigns greater
weight to highly dependent species (weight=IO) than to dependent ones (weight=2) If you wish instead to
assign greater importance (weight) to dependent species than to highly dependent species, move the cursor to
the second line and press the Enter key The screen shown on the next page will pop up
18
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Figure 8 Menu for changing weights of a species characteristic
Species’ Relatiue Depei dency on Wetland
Categor9 Current weight New weight (Opt iona I)
Highly Dependent I 10 -
Internediate £
Dependent . 2
II ’ you wish to leawe weights as they are, nowe to last line and press Enter
I I ’ you wish to change wei’ghts, type in new weights, nowe to last Line,
press Enter
I
I
This menu appears if you previously opted (Figure 7) to change the weights of a species charactenstic If
you do not wish to alter the weights for the first charactenstic that appears, move the cursor to the last line
and press Enter The program will then advance to the next characteristic and ask if you want to change its
weights This repeats until you’ve been given a chance to change weights of each of the six characteristics
The program then returns you to Figure 7, where you will probably want to apply the new weights by
selecting the third option (“Create table with new weighting factors”) Then, to recalculate the weighted
habitat scores (Figure 5), move the cursor to the third line (“Create table with new weighting factors”) and
press Enter The program automatically replaces the earlier file (that was based on the previously-assigned
weights) and gives the new “xxxx out” file the same name The new weights you assigned will continue to
be used in all future calculations by AREM Thus, caution is advised because turning the computer off and
on again will not restore the original weights To restore the onginal weights, you must reinstall AREM
from the original disk
19
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Figure 9. AREMs concluding instructions.
This screen tells how to print out the list of species expected to occur in the evaluated wetland, along with
their individual habitat scores Another method for pnnting this information is to begin running your
computer’s word processing software (e g, WordPerfect) Retrieve, view, and print the file xxxx.out,” where
“xxxx” represents whatever file name you assigned earlier (Figure 2, fourth screen) Because the file is in
ASCII format, you will need to first have your word processing program convert it to a compatible format.
Many word processing programs do this automatically
20
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Figure 10. Example of documentation output file from an AREM evaluation.
The following pages contain the contents of a file that was created by running AREM. In this example, the
user input a wintertime descnption of a wetland located in the Lower Gunnison Valley of Colorado.
Lines 1-16 provide a printed copy of the score table you saw earlier on the screen (Figure 5). (In the actual
pnntout, lines are not numbered). See Section 2.4 for guidance in deciding which scores to use for a
particular application
Line 19 specifies the cutoff level for the species habitat score. in this case, the cutoff of >0.00 means that the
lists on the next two pages contain only species whose species habitat score in the evaluated wetland
exceeded 0 00 AREM provides similar lists for the other cutoff levels (>0.25, >0 50, >0.75) but only
information for the >0.00 level is shown in this figure On line 20, the unweighted habitat score is the sum
of the species habitat scores for the listed species (as demonstrated in Table 4) On line 21, the unweighted
richness score is simply the number of species on the list. Again, see Section 2 4 for guidance in deciding
which scores to use for a particular application
Lines 25-30 alphabetically list the 6 species that would occur at that season in that subregion and for which
habitat in the particular wetland was predicted to be at least minimally suitable, i e., the species habitat score
for all listed species is greater than 0 The series of lists that follows provides information and tallies for
each of the weighting characteristics. The weighting characteristics are described in Section 3.2, and include
ordinal values for each species pertaining to the following
Dependency on Wetland/Riparian Habitat
Relative Abundance
Taxonomic Uniqueness
Neotropical Migrant Status
Offical Conservation Designations
Hunted Status
For example, lines 38-40 report that none (0, 0%) of the species predicted to be present is highly dependent
on water as a substrate in lowland wetlands of the Colorado Plateau at this season; 2 (3 3.33%) of the 6
species are of intermediate dependency; and 9 (66 67%) are categorized as dependent. The AREM program
does not assign these dependency categories in a context-specific manner That is, they are not meant to
reflect the dependency of individual birds on a specific individual wetland, but rather the dependency of the
species generally on water as a substrate within the region.
Following this, lines 28-38 contain the same list of species and species habitat scores as in lines 25-30, but
organize the species primarily by dependency category Weights that were used for each category are
reported in the column farthest to the right (“Weight”). These weights were multiplied by the species habitat
scores (“Species Habitat”) to generate the Weighted Score for each species, which when summed for all
species gives dependency score reported on line 34.
Although not essential, additional documentation of the analysis can be viewed If you have the commercial
database program “dBASE,” or another program that allows you to view “.dbf” files, you can load and
examine the file labeled “tmpsort.dbf.” For every species predicted to occur in the last wetland you analyzed,
this lengthy file lists each associated indicator condition that led to its predicted occurrence in this wetland
This file is written over (erased) each time you run AREM.
21
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1 WETLAND SCORE SUMMARY
2
3 Cutoff Level for Species Habitat Scores:
4 ,O .25 >.50 ‘.75
5 alL possible most
6 app, conservative
7
8 unweighted Habitat Score 3.41 3.41 1.99 0.80
9 Unweighted Richness Score 6.00 6.00 3.00 1.00
10 Habitat Score Weighted By Species:
ii Relative Dependency on Wetlands 12.25 12.25 9.41 4.80
12 Relative Abundance 26.40 26.40 18.65 8.00
13 TaxonomiC Uniqueness 20.33 20.33 10.76 7.20
16 Neotropicat Migrant Status 18.48 18.48 11.95 4.80
15 OfficiaL Conservation Designations 15.11 15.11 9.19 8.00
16 Hunted Status 3.41 3.41 1.99 0.80
17
18
19 Cutoff Level for Species Habitat Score: >0.00
20 Unweighted Habitat Score: 3.41
21 unweighted Richness Score: 6.00
22
23 Listing of Species
24 Species Name Species Habitat
25 AMERICAN GOLDFINCH 0.64
26 AMERICAN PIPIT 0.56
27 AMERICAN ROBIN 0.47
28 BALD EAGLE 0.50
29 MARSH WREN 0.80
30 SONG SPARROW 0.45
31
32 Habitat Score weighted By Species
33
34 Weighted Habitat Score by: Relative Dependency on WetLand = 12.25
35
36 Category Current weight Wuiter Percent
37 Species Species
38 HighLy Dependent 10 0 0.00
39 Intermediate 6 2 33.33
40 Dependent 2 4 66.67
41
42 Listing of species
43 Species name Category Weighted Species Weight
44 Scores Habitat
45 AMERICAN PIPIT Intermediate 3.33 0.56 6.00
46 MARSH WREN Intermediate 6.80 0.80 6.00
47 AMERICAN GOLDFINCH Dependent 1.27 0.64 2.00
48 AMERICAN ROBIN Dependent 0.93 0.67 2.00
49 BALD EAGLE Dependent 1.00 0.50 2.00
50 SONG SPARROW Dependent 0.91 0.45 2.00
51
52 Weighted Habitat Score by: Relative Abundance = 26.40
53 Category Current weight Nutter Percent
54 Species Species
55 Unconr lon 10 3 50.00
56 FairLy Carrion 8 1 16.67
57 Carrion 4 1 16.67
58 Abundant 2 1 16.67
59
60 Listing of species
61 Species name Category weighted Species Weight
62 Scores Habitat
63 AMERICAN PIPIT - Lincomon 5.56 0.56 10.00
64 BALD EAGLE Uncorrion 5.00 0.50 10.00
65 MARSH WREN Uncomon 8.00 0.80 10.00
66 AMERICAN GOLDFINCH Fairly Carrion 5.09 0.64 8.00
67 SONG SPARROW Carrion 1.82 0.45 4.00
68 AMERICAN ROBIN Abundant 0.93 0.47 2.00
22
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70
71
72 Weighted Habitat Score by: Texonomic Urnqueness 20.33
73 Category Current weight N irber Percent
74 Species Species
75 Order 9 1 16.67
76 Suborder 8 0 0.00
77 Parvorder 7 0 0.00
78 Suprefamity 6 2 33.33
79 FamiLy 5 3 50.00
80 SubfamiLy 4 0 0.00
81 Tribe 3 0 0.00
82 Genus 2 0 0.00
83 Species 1 0 0.00
84
85 Listing of species
86 Species name Category Weighted Species Weight
87 Scores Habitat
88 BALD EAGLE Order 4.50 0.50 9.00
89 AMERICAN ROBIN Suprafami ly 2.80 0.47 6.00
90 MARSH WREN Suprafami ly 4.80 0.80 6.00
91 AMERICAN GOLDFINCH FamiLy 3.18 0.64 5.00
92 AMERICAN PIPIT FamiLy 2.78 0.56 5.00
93 SONG SPARROW Family 2.27 0.45 5.00
94
95
96 Weighted Habitat Score by: NeotropicaL Migrant 18.48
97 Category Current weight Hurter Percent
98 Species Species
99 TypeA 10 0 0.00
100 TypeS 6 5 83.33
101 Non-neotropicaL species 2 1 16.67
102
103 Listing of species
104 Species name Category Weighted Species Weight
105 Scores Habitat
106 AMERICAN GOLDFINCH Type B 3.82 0.64 6.00
107 AMERICAN PIPIT Type B 3.33 0.56 6.00
108 AMERICAN ROBIN Type B 2.80 0.47 6.00
109 MARSH WREN Type B 4.80 0.80 6.00
110 SONG SPARROW Type B 2.73 0.45 6.00
111 BALD EAGLE Non-neotropicat species 1.00 0.50 2.00
112
113
114 Weighted Habitat Score by: Official Conservation Designations 15.11
115 Category Current weight MuTter Percent
116 Species Species
117 Threatened 10 0 0.00
118 Endangered 10 0 0.00
119 Candidate Endng/Threat. 10 1 16.67
120 03 species 10 0 0.00
121 04 species 10 0 0.00
122 51 species 10 0 0.00
123 S2 species (CO onLy) 10 1 16.67
126 53 species (CO onLy) 10 0 0.00
125 Watch List species (CO) 10 1 16.67
126 -
127 Listing of species
128 Species name Category Weighted Species Weight
129 Score Habitat
130 BALD EAGLE Threatened 5.00 0.50 10
131 BALD EAGLE 03 species 5.00 0.50 10
132 MARSH WREN S3 species (CO onLy) 8.00 0.80 10
133
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134
135
136 Weighted Habitat Score by: Hunted Status = 3.41
137 Category Current weight Nu ter Percent
138 Species Species
139 Hunted 10 0 0.00
140 Not Hunted 1 6 100.00
141
142 Listing of species
143 Species name Category Weighted Species Weight
144 Scores Habitat
145 AMERICAN GOLDFINCH Not Hunted 0.64 0.64 1.00
146 AMERICAN PIPIT Hot Hunted 0.56 0.56 1.00
147 AMERICAN ROBIN Not Hunted 0.47 0.47 1.00
148 BALD EAGLE Not Hunted 0.50 0.50 1.00
149 MARSH WREN Not Hunted 0.80 0.80 1.00
150 SONG SPARROW Not Hunted 0.45 0.45 1.00
151
152
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Table 4. Example showing how AREM scores are calculated.
WETLAND #1.
Species Habitat Conservation Weighted
Species Score (calculated) 5 Prionty Weig t 6 Habitat Score
Downy Woodpecker 0 77 2 1.54
Amencan Crow 063 2 1.26
Black-billed Magpie 0.27 2 0.54
Lewis’ Woodpecker 0 18 2 0.36
Marsh Wren 0.60 6 1.20
Wilson’s Phalarope 031 6 0.62
Pied-billed Grebe 0.84 10 8.40
Bonaparte’s Gull 0.22 10 2.20
Common Goldeneye 0 43 10 4.30
Unweighted Habitat Score. j ( =suni of the species habitat scores)
Unweighted Richness Scores
@ species habitat score cutoff of >075 =
(2 species. downy woodpecker (0 77), pied-billed grebe (0 84))
@ species habitat score cutoff of >0.50 = 4
(above 2 Species, plus American crow (0 63), marsh wren (0.60) = 4 species)
@ species habitat score cutoff of >0 25 = 1
(above 4 species, plus magpie, phalarope, goldeneye = 7 species)
@ species habitat score cutoff of>0 = 2
(all species above, = 9 species)
Weighted Habitat Scores (weighting factor ’= “water dependence”)
@ species habitat score cutoff of >0.75 = 994
(add downy woodpecker (1.54) to pied-billed grebe (8 40))
@ species habitat score cutoff of >0.50 = 12 40
(above, + American crow (1.26) + marsh wren (1.20))
@ species habitat score cutoff of >0.25 = 17.86
(above, + magpie (0 54) + phalarope (0 62) + goldeneye (4 30)
@ species habitat score cutoff of>0 = 20.42
(sum of all weighted habitat scores)
Species having a score of 0 are not incLuded in this exaiipLe. ALso, expect that species Lists
fran most wetLands wiLL be Longer than this exan Le.
in this exairpte, weights in the database that define each species’ reLative dependence on water
are used. Users have the option to seLect other conservation characteristics for which the database
contanis a weight for each species (e.g., reLative regionaL abLaldance, status as a neotropicat
migrant).
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2.4 Interpretation Phase
The AREM program automatically outputs 32 scores (4 cutoffs x 8 score types). AREM
includes such a large number of scores to give potential users maximum flexibility in
tailoring their use of AREM to a particular evaluation objective. But given this large
variety of output, a common question is “Which number should I use?”
There is no universally appropriate answer to this question. Each user should make the
choice based on a thorough understanding of exactly what each type of score represents,
and a knowledge of the objectives for a particular AREM application. Regardless of which
choice is made, if comparisons are going to be made among wetlands, the same type of
score should be calculated and used for all wetlands. The following paragraphs provide
information to facilitate choices concerning which score may be most appropriate.
Unweighted vs Weighted Score . If you prefer to consider all species (not habitats) to be of
equal importance, use the unweighted habitat or richness score. However, there are
sometimes situations where habitats (especially in landscapes undergoing transition because
of recent disturbance) superficially seem important because they are rich in species, but
upon further examination, it is found that the particular species comprising this richness are
(a) “generalists” that could thrive almost anywhere, (b) species that have populations which
are non-sustainable in this habitat type, or (c) are less desirable for other reasons. Thus, in
some instances you may wish to consider some species as more important than others. In
such instances, use the weighted habitat score pertaining to the characteristic you consider
to be most important.
Cutoff Level . The species habitat scores cover the numeric range, 0-1.0, and cutoffs have
been established arbitrarily at the >0, >0.25, >0.50, >0.75 points within this range. These
cutoffs represent habitat suitability, not a finite statistical probability of a species occurring
in a wetland. Likewise, the species habitat score of individual species, which is used to
calculate the unweighted AREM score, describes habitat quality only in relative terms, not
in absolute terms. For example, a species habitat score of 0.78 does not guarantee survival
of minimum viable populations of a species, or mean that a 78% chance exists of finding
the species during any visit to a particular wetland. The score does suggest that the species
is relatively more likely to use the particular wetland than a species whose species habitat
score for the wetland is, say, 0.53. Testing of AREM during the breeding season (Adamus
I 993b) suggested that the 0.75 cutoff predicts actual richness and species composition better
than the other cutoffs. The “best” (most predictive) level for a ctitoff will be influenced by
season, regional population levels of the species, and competitive relationships among
species. Ultimately, the choice of a cutoff level will depend on personal preference of the
user. Users wishing to take a very conservative approach to estimating habitat suitability
will use a cutoff of >.75, whereas those taking a broader approach will use a cutoff of >0.
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Using the broader approach will allow the user to make finer distinctions among wetlands
because more species will be included, but whether or not these distinctions are
commensurate with the true sensitivity of each species’ response to habitat is unknown.
Habitat Score vs. Richness Score . The unweighted habitat score accounts for both the
number of species present and the relative suitability of habitat for each, whereas the
unweighted richness score only quantifies the number of species for which the habitat is at
least minimally suitable. The unweighted habitat score is generally more sensitive than the
unweighted richness score in making fine distinctions among wetlands because it has a
wider range of possible values (e.g., it covers the range between about 0 and 120 with
decimal values as well as whole numbers (integers), whereas the unweighted richness score
covers this range only with integers). The unweighted habitat score includes decimal values
because it is the product of an integer variable (species richness) and an ordinal scaler
(habitat suitability, rated on a 0 to 1.0 scale for each species). However, as stated before, it
is uncertain whether such sensitivity is commensurate with the true ability of species to
discriminate among habitats. In contrast, the unweighted richness score is based on a
quantifiable parameter (species richness) that can be independently measured.
Which Weighting Factor ? The choice of which weighting factor to use is purely one of
values -- personal values, agency values, or values of whomever the wetland evaluation is
being conducted for. The six characteristics that AREM uses to weight individual species
represent a set of values that are generally supported by conservation biologists and/or
natural resource agencies. Users may choose to weight wetlands by using just one of these
weighting factors, or by using several (e.g., by adding or multiplying the scores of each).
Section 3.2 describes the categories defined by each weighting factor.
Multiplying by Habitat Area . Any of the non-zero scores from AREM can be multiplied by
area (acreage) to yield a “habitat index” value. Doing so will further increase the ability of
AREM to show fine differences among wetlands, but again, the point at which these
differences actually reflect meaningful differences in habitat importance to biodiversity is
unknown. Moreover, multiplying an AREM score by area is somewhat redundant, because
AREM has already taken into account the effects of area on species richness 7 . Other
AREM has done so in the following two ways
First, a major reason why nchness increases with habitat area is that as area increases, so typically does habitat complexity (e g. the number
of cover types within a wetland) Greaser habitat complexity generally supports more species AREM accounts for this fact by allowing the
user to note the presence of elements in a wetland that together crease habitat complexity (as con asted with some classification systems that
force the user to assign a single “type’ to a wetland which actually is a mosaic of types)
Second. because species richness in limited circumstances can increase with increasing area independently of changes in habitat complexity,
AREM has directly incorporated habitat patch size into the models for most species However, this independent effect of area was not
considered to be a continuous linear function but, rather, a discrete “stair-step” function that recognizes just two gross patch size thresholds
(see p 46)
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objections described in Table 3 (#6, page 5) further underline the need for caution when
interpreting “habitat index” values.
The Most Important Wetlands Aren’t Always the Highest-Scoring Ones . In most instances,
the greatest importance and the most protective administrative action is accorded to
wetlands for which AREM assigns the highest scores. However, as shown in Table 5, there
are sometimes instances where a wetland has relatively low diversity yet contributes
importantly to regional diversity because the few species it has are absent from most other
wetlands. Thus, if time and resources allow, it is desirable to not only examine AREM
scores from a series of wetlands, but also the species composition predicted for each
wetland. Wetlands predicted to contain species that are present in few if any of the other
wetlands would be accorded high priority, in addition to those that have high AREM
scores.
To screen several wetlands to help identif ’ ones most likely to contribute strongly to
regional avian diversity, review the weighted richness score in which Relative Abundance
was used as the weighting characteristic. Large values for this score often (but not always)
highlight wetlands that contribute exceptionally to avian diversity at a regional level. Using
this cue, you can combine the species lists of two wetlands by typing “combarem” at the
C:\>arem prompt. The screen shown in Figure 11 will then appear. Do not try to start the
program by typing the name of the execution file (comb2.exe). By following the menu
instructions shown in Figure 11, you will be able to generate a cumulative species list for
the two wetlands, as well as producing all the usual types of synthesis scores. By doing
this sequentially among all pairs of wetlands (including “new” wetlands that you have
created by combining existing wetlands using the computer), you can identif ’ the set of
wetlands that collectively will contain the greatest avian diversity. Note that when AR.EM
combines wetlands, it calculates the synthesis scores using the species habitat scores only
from the wetland that had the higher score for a particular species.
Doing a Sensitivity Analysis . Sensitivity analysis is an optional process, and consists of
determining what happens to the output score values if the input values andlor the models
are adjusted. Sensitivity analysis will not tell you which type of score to use, but when
applied to a particular wetland, it will estimate the range of values (certainty interval) that
would result if you had answered questions differently or made different model
assumptions. To conduct a sensitivity analysis using your input data, run the AREM
program several times for the same wetland, each time changing your response to questions
that you were unsure how to answer and that describe an indicator condition. For example,
if you are unsure whether the willow vegetation you see in a wetland should be considered
“dense” or “open” (Appendix B, question #12), try each (and both) to see what happens to
the scores. Then, in your evaluation report you can report the scores for that wetland as a
range of values, rather than a single number. If someone subsequently wishes to use the
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Table 5. Use of AREM to select wetland combinations that optimize protection of
regional avian diversity
This simplified example demonstrates the importance of using AREM (or otheT methods)
to consider wetland functions and values at a cumulative, regional scale as well as
individually 5 If the only basis for a wetland decision was the scores for individual
wetlands, then wetlands A and B below would be selected because they individually have
the most species (I e, highest unweighted richness score) of any of the wetlands.
However, if the objective is to maintain biodiversity at a regional level rather than
exclusively at an individual site level, then wetlands C and D, which individually are the
poorest in species, would be the best choice because together they have a larger species
list (8 species) than the two richer wetlands combined (6 species), or the combination of
either poorer wetland (C or D) with either of the richer wetlands (A or B). Wetlands C
and D also would usually be chosen if the unweighted habitat score were used instead
of the unweighted richness score. These selection principles can be applied to more than
two wetlands at a time, for large sets of wetlands a computer greatly facilitates the
calculations In instances where one or both members of an “optimal pair” (as
determined by this process) cannot be protected because of cost or other reasons, a next-
best pairing of sites can be determined; some authors have even proposed that cost-per-
species-protected be used to optimize conservation strategies, i.e., by calculating and
comparing for all possible wetland combinations both the number of species protected
and the associated land stewardship costs. Of course, sustaining the populations of all
species requires some redundancy of species composition among wetlands.
Occurs in Wetland.
Species A B C D
Mallard x x x
Mourning Dove x x x
Black-billed Magpie x x x
European Starling x x x
Song Sparrow x x x
Kilideer x x
Sora x
Yellow-headed Blackbird x
Total Species
(Unweighted Richness) 6 5 4 4
Collective # of Species, by Combination of Wetlands
Wetlands A ± B = 6 (all species but Killdeer are redundant),
Wetlands A+C 7, Wetlands A+D 7; Wetlands B+C= 6;
Wetlands B + D = 7; Wetlands C + D = 8 (no species are redundant)
Despite a continuing end necessary focus of resource agencies on the indivi&iat
site Level when setting wetland priorities, the cuTs.itetive assessment principles t on
which this exwiple is based are also relevant and have been noted for years by
conservation biologists (e.g., Sameon and Knopf 1982, Usher 1986, Vane-Wright et at.
29
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Figure L Menu for combining bird lists and scores from multiple wetlands.
Press SPACE-BAR to tag or untag files
Press 11 to oue cursor up and down
Press ESC to continue or to exit
30
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scores to differentiate this wetland from others, only the wetlands whose score ranges do
not overlap would be considered different.
To conduct a sensitivity analysis on the models (as opposed to the input data), use the
editing program described in Section 2.4 to vary the habitat models for any or all species.
Then use the modified database to recalculate the scores. Repeat the procedure if you wish,
editing the database and recalculating the scores each time. As described above, in your
evaluation report you can then report each score for that wetland as a range of values,
rather than a single number, so that comparisons among wetlands will be interpreted
meaningfully.
Reporting . Results of some AREM evaluations might ultimately be used in administrative
or legal proceedings, or might be subject to wider public scrutiny. Anticipating this
possibility, it is advisable to document all evaluations with a level of detail appropriate for
the particular application. Some of the key material to retain in a file describing an AREM
evaluation would include the following.
I. AREM Field Form: Documenting Information (Appendix A). This should be
completely filled out and be accompanied by a sketch map showing boundaries of
the area included in the evaluation, as well as its general location.
2. AREM Field Form (Appendix B or C), filled out appropriately.
3. Verification that the original AREM database and program were used to generate
the scores. This can be documented partly by printing out a list of the files in your
AREM directory that shows the dates of those files. If certain files in the listing --
WHRBASE.DBF, WEIGHTS.DBF, REGIONS.DBF, and TAX [ NF.DBF -- are
dated later than 1 l/93 , then it can be assumed they are jj the original files, and
program outputs are suspect. The outputs may still be used if each of the specific
changes that were made to the database are explicitly identified and a rationale is
given for each change.
2.5 Editing Options
A unique feature of AR.EM is that it allows users (regardless of their computer skills) to
edit the main database upon which the species models and ultimately the scores are based.
Keep in mind one crucial point: if you wish to edit any databases, before doing so be
sure you have retained (on at least one separate disk) a backup copy of all files you
wish to save. This is imperative because the AREM program automatically replaces older
Assuming your computer, like most, automatically dates au changes to files
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files with newer ones every time the editing program is used. Once the backups are made,
to begin editing, do the following:
Comi,uter Says: You Tyne: What This Does
C:\>arem editarem starts running the editing program
If the program fails to run when you type “editarem,” type this at the prompt:
set clipper=/IE:O
At this point the screen (Figure 12) asks you to choose a database to edit:
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Figure 12. Menu for selecting AREM databases to edit
This menu allows you to select one of the databases that supports AREM and edit it
Select ‘Edit WI-IRBASE” if you want to change any of the species models, delete or substitute an
indicator, or add or delete a species
Select Edit WEIGHTS” if you want to change any of the numeric weights currently assigned to a
particular species. or substitute a weighting characteristic (Contrast this to the option given in the
main AREM program, which allows you to change a particular weight for all species that have that
weight)
Select “Edit REGIONS” if you want to add or delete a species from a subregion, or change the code
describing its relative abundance in a subregion
Select “Edit TAXI1 ”JF” if you want to edit the taxonomic placement of a species
Select “Add fields to W1-IRBASE” if you want to add a new habitat indicator
The first field (column) in all the databases contains the species names, all databases contain the same 165
species in the same alphabetical order Before attempting to edit these databases, become familiar with keys
needed to move the cursor These are shown in on the next page (Table 6)
Select from the menu
Edit UHRBASE
Edit UEIGIITS
Edit. E IOMS
Add fields to UHRBASE
I UIT.
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Table 6. Instructions for AREM’s editing program (EDITAREM).
Desired Operation Instructions :
Move around in the database use arrow keys and
page up/down keys
Change a code type over the
existing code, then
press Enter
Delete a code Space bar, Enter
Save changes and exit Esc
Delete a species (and all its information) move cursor to
species’ name, press
Del
Undelete a species you deleted this session Del (again)
Move to end of row (last field) Ctrl, End
Move to beginning of row (species name) Ctrl, Home
Move to last species Ctrl, PgDn
Move to first species Ctrl, PgUp
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Figure 13. Part of AREM’s wildlife habitat relationships database (WHRBASE).
If you selected this database to edit, you will be able to change any of the species models, delete or substitute
an indicator, or add or delete a species Be sure, if you add or delete a species, to add or delete it (with its
associated information) from ALL FOUR databases — WI-IRBASE, WEIGHTS, REGIONS, TAXINF
Each of the abbreviated column headings in the above matrix corresponds to a question in the field form
(Appendices B and C) which is named identically The codes within this database (x, f, 1, - 2, etc) are explained
on the next page (Table 7), and if additional clanficationis desired, Adamus (1993a, Table 12, p 46) provides
an example Note that when you edit information on a species in the WHIRBASE database, the computer program
automatically recalculates, if appropriate, the value of PotMax (the potential maximum score for the species,
which is divided into the actual score so as to normalize scores across species) and NumX (the number of
required “X” conditions, as specified for that species) These fields are “locked’ and cannot be edited
35
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Table 7. Meaning of codes used in the species habitat relationships
database.
X Means the indicator condition describes habitat that is minimally
acceptable to the species. In the computation of a species’
habitat score, a base score of 5 points is assigned if the
evaluated wetland contains the indicator condition marked in the
database with an “X”. If the database contains two indicator
conditions marked with an “X,” both must be present.
f Means that condition others that are labeled in the database
with an “f’ are minimally acceptable to the species. If any
condition marked with an “f’ is present in the evaluated
wetland, 5 points are assigned, unless 5 points were assigned
previously due to occurrence of a condition denoted by an “X.”
I (could also be 2, 3, or 4):
Means the condition supports the species in a compensatory
manner. That is, this particular indicator condition could
support the species, but so could other conditions denoted on a
relative scale (4= more important, 1= less important) in the
database, and not preceded by a + or - sign. In calculating the
species habitat score, AREM selects the maximum of the
numbers associated with conditions of the evaluated wetland,
and adds this value to the base score of 5.
+1 (could also be +2 or +3, or could be preceded by a minus sign; a +2
is considered more influential than a + I, and a -2 more influential than
a -1).
Means the condition supports the species in a cumulative
manner. That is, if more than one of such conditions are
present, their individual effects behave approximately in an
additive manner. In calculating the species habitat score,
AREM adds the values of all such conditions that are present in
the evaluated wetland to the previously calculated sum.
(blank)
Means the indicator condition is not sufficiently relevant to
predicting the suitability for the species (i.e., other indicator
conditions are more predictive)
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Figure 14 Part of AREM’s WEIGHTS database.
Record 1/165
COPUIONNAN WETDEPEND NEOTROPIC HUNTED ThREATENED ENDANGERED CAND IDATE
6 2 1 1. 1 1
AMERICAN BITTERN 6 2 1 1 1 1
AMERICAN COOT 18 .1 2 10 1 1 1
AMERICAN CROW 2 - 2 1 1 1 1
AMERICAN GOLDFINCH 2 6 1 1 1 1
AMERICAN KESTREL i 2 6 1 1 1 1
AMERICAN PIPIT •• . 6 6 1 1 1 1
AMERICAN ROBIN . 2 6 1 1 1 1
AMERICAN TREE SPARR . 2 2 1 1 1 1
AMERICAN UIGEON 4. 118 2 10 1 1 1
ASH-THROATED FLYCAT 2 10 1 1 1 1
BALD EAGLE 2 2 1 10 1
BAND—TAILED PIGEON 2 10 1 1 1
BANK SWALLOW 2 18 1 1 1 1
BARN OWL ., I 2 2 1 1 1 1
BARN SIJALLOLI . 2 10 1 1 1 1
BARROW’S GOLDD4EYE . ‘10 2 10 1 1 1
BELTED KINGFISHER 10 6 1 1 1 1
If you selected this database to edit, you will be able to change any of the numeric weigJ ts currently assigned
o a particular species, or substitute a weighting charactenstic Column headings are explained m Section
325
I
37
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Figure 15. Pan of AREM ’s REGIONS database.
If you selected this database to edit, you will be able to add or delete a species from a subregion, or change
the code describing its relative abundance in a subregion The column headings are abbreviated as follows
GVB= Grand VaIle , breeding, GVM= Grand Valley, migration, GVW= Grand Valley, wintering,
CZB= Cortez, breeding, CZM= Cortez., migration, CZW= Cortez, wintering, UTB=Utah, breeding;
UTM= Utah, migration, UTW= Utah, wintering, WYB= Wyoming, breeding, WYM= Wyoming,
migration, WYW= Wyoming, wintering Data were from sources listed in Adarnus (1993a) See
Figure 1 (p. 2 ) for a map showing specific portions of these geographic areas that are covered by
AREM
Codes used in the database are
A (abundant), C (common), F (fairly common), U (uncommon), X (rare), blank (absent or not
regularly-occurring) See Section 3 2 2 for explanation of how these were defined.
38
Record 1/165
COPIIIONP1API CUB CUP, CUU CUR UTR hIM UTU UTR CZB CZPI CZU CZR
:TT.: T •.:: U U
AMERICAN BITTERN - X U U
AMERICAN COOT U C C A U F C
AMERICAN CRO%J U F F C C C
AMERICAN GOLDFINCH U F C C U F C C
AMERICAN KESTREL C C F C C U C C C
AMERICAN PINT U U U C
AMERICAN ROBIN C C A C C C C C
AMERICAN TREE SPARROU U U C
AMERICAN UIGEOM ‘ U F U C C C U
ASH-ThROATED FL’ICATCHER U X F
BALD EAGLE U U C C C
BAND-TAILED PIGEON X F F
DANK SUALLOU U F U Ii
BARHOUL U U U X X
BARN SUALLOLJ A C C U C C
BARROU’ S COLDENEYE X X
BELTED KINGFISHER U U U F F U
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Figure 16 Part of AREM’s TA)UNF database
I Record 1 /165
COPIMONNAN ORDER SUBO PARVO SIJPF FAN SUBF TRB
1 B B B B B B
DOUBLE-CRESTED CORMORANT 2 B B B B B B
ANERJCA IIBITTERN 3, B B .0 1 B H
CREAT I ILUEHERON t ’ I 3. B B B ’ I ’ B B
SNOIJYEGRET 3 B B 0 1 B B
BLACK—CROWNED NIGHT—HERON 3 B B B 1 B B
WHITE—FACED IBIS . 3 B B B 2 B B
MALLARD . 4 B B B B B . B
GREEN-IJINGEDTEAL 4 . B B B B B B
NORTHERNPINTAJL 4. B B B B B B
BLUE-IJINGEDTEAL . 4 B B B B B B
CINNANONTEAL 4 B B B B B B
NORTHERN SHOVELER i 4 B B B B B B
GADIJALL 4. B B B B B B
AMERICANIJIGEON 4 B B B B. B B
WOODDtJCJ( I 4 B B B B B B
CANVASBACK . 4 0 B B B B B
REDHEAD . , 4 0 B B B B 0
If you selected this database, you will be able to edit the taxonomic stanis assigned to species You should
first read Section 3 2 3 The abbreviations used are SUBO= suborder, PARV.O parvorder, SIJPN
superfamily, FAM= family, SIJBF= subfamily, TRB= tribe Numbers are used only as markers to link
members of the same taxonomic unit
39
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Figure 17. Menu for adding indicator conditions.
Add fields to UHRRASE database
Enter new field name: LI,
This nust contain no more than 10 characters.
Enter new indicator number:
If you have chosen to add a new mdicator. this menu prompts you to give it a name and number. The
program uses the number to place it in sequence in the list of indicators (Figure 3)
40
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2.6 Possible Applications of the Editing Program
AREM’s editing program can be used to accomplish the following:
1. Adding a species. Suppose you wish to add some mammals, plants, or additional bird
species to AREM. After loading the EDITAREM program, first select WHPBASE. Go to
the last line (CtrI, PgDn), move the cursor down a line, and type in the new species and its
habitat codes, using a different line for each species added. If you accidentally enter a code
or make a change in the wrong place, just place the cursor on top of the error and press the
space bar to erase the error. Exit the program (Enter, Esc); there will be a delay of perhaps
several minutes as the program automatically saves the information, regardless of whether
you changed the database. Then select each of the other three databases (Figure 12) in turn
and add the new species and their associated information to these databases in a similar
manner.
2. Adding an indicator characteristic. Suppose new evidence suggests that (for example)
soil type is an important indicator of wetland use by a particular species, yet soil type (the
indicator) is not currently one of the indicators used in the species models (WHIRBASE) or
in the field form (Appendix B). As shown in Figure 17, the AREM program allows you to
add soil type, and up to 20 other new indicators, to the databases and computer program.
Load the EDITAREM program and select “Add fields to WHRBASE.” You will be
prompted to name the indicator and specify a number that will define its sequence in the
habitat indicators list (Figure 3) The new indicator is automatically added to WI-IRBASE
arid you are returned to the editing menu. After selecting “Edit WHRBASE,” for each
species whose presence is indicated by soil type, insert an appropriate code (from Table 7)
that describes the nature of its relationship to soil type. Exit the program again. The next
time you use AREM to process some field data, you will be queried for information on the
new indicator That is, the new indicators will have been automatically added to the bottom
of the list of indicators shown in Figure 3.
Updating and refining of data for the currently-used weighting characteristics is strongly
encouraged. Consider, for example, the weighting characteristic, “Relative Abundance.”
Currently, in the Utah subregion nearly all species are categorized as “common” because of
lack of more definitive information. With additional information-gathering, the number of
categories could initially be broadened, and with field surveys, the characteristic (Relative
Abundance) could be reformulated as a continuous (rather than categorical) weighting
variable. For example, for many species the proportion of atlas blocks ’ 0 in which a
‘° “Atlas blocks” in Colorado arc areas approximately 3 miles on a side, defined by I 24,000-scale topographic maps Breeding birds in
these areas are being surveyed by volunteers statewide The project is scheduled for completion in 1994, but sufficient amounts of interim
data may be available for some areas Contact Hugh Kingery as the Denver Museum of Natural History (phone 303.370-6336) Many states
have similar projects
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species occurs could be considered a reasonable surrogate for a species’ abundance (Lacy
and Bock 1986, Bock 1987). To assign more weight (as AREM does) to species that are
less common or more localized, the AREM user could use the number of adequately-
covered atlas blocks in which a species was found (e.g., Adamus 1987), in lieu of the
current practice of using categorical values that describe Relative Abundance only coarsely.
3. Changing weights. Suppose the database currently considers “tree swallow” to be
“Dependent” on wetlands, but new evidence suggests that it is more appropriate to assign
the swallow to the category “Highly Dependent.” After loading the EDITAREM program,
select WEIGHTS. Move the cursor down to the “tree swallow” row, and go to the column
(field) termed “WETDEPEND”. Change the code from a I (dependent) to a 3 (highly
dependent) and press Enter, then save the change by pressing Esc.
2.7 Adapting AREM for a New Region or Ecosystem Type
Suppose you would like to have a procedure similar to AREM for use in rapidly evaluating
the avian diversity of (for example) constructed tidal wetlands in New England or subalpine
forests in Colorado. The following process, which requires assistance from skilled avian
experts, can be used to build the modified AREM.
1. Develop a master list of species regularly occurring in the new region and/or
ecosystem type. “Regularly” means that one or more individuals are present in the
region or ecosystem type at predictable times of the year, at least once annually.
Species lists can be obtained from state Heritage Programs, national wildlife refuges,
national forests, state bird books, and state and local bird clubs.
2. Set up the new REGIONS database. To do so, use the EDITAREM program to
delete all the information in the current REGIONS database, and substitute the new
information from #1. Enter a code describing relative abundance of each species
during each period (season) in each subregion and/or ecosystem type. Choose from
the same codes currently used by AREM. These are: A (abundant), C (common), F
(fairly common), U (uncommon), X (rare), blank (absent or not regularly-occurring).
See Section 3.2.2 for guidance in defining these.
3. Set up the new WEIGHTS database. Again, use the EDITAREM program to
delete all the information in the current WEIGHTS database, and substitute new
weighting information obtained from sources listed in #1 or by contacting other
experts.
4. Construct the species models (first pass). Constructing the species models is
synonymous with setting up the WHRBASE database. Initially, the models should
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be constructed by a wildlife biologist who is (a) experienced using rapid evaluation
methods, arid (b) familiar, both from field experience and from understanding of
current literature, with the gross habitat requirements of all relevant species. The
model builder (i.e., the wildlife biologist) should choose from the codes currently
used by AREM (Table 7) and should construct each species model as a unique
combination of these codes. The codes should then be entered into the W1- [ RBASE
matnx using the program, EDITAREM. It is also inevitable that the new set of
species will be associated with different indicators than are appropriate for Colorado
Plateau lowland wetlands. Because of this, new indicators need to be substituted for
certain old ones, as described on p. 41, #2.
5. Test the adapted AREM and modify further as needed. The simplest way to test
the adapted AREM is as follows:
(I) Visit a series of wetlands (or other ecosystems) and apply the adapted
AREM, using it to generate a species list for each area. Ideally, the number
of areas that are visited and the way they are selected should satisfy an
objective of encompassing as many as possible of the conditions of the
indicators used in the adapted AREM.
(2) Simultaneously, contact a knowledgeable local birder for assistance.
Provide this person with a copy of the regional master list, take them to the
same areas as above, and ask them to check off species they know, or would
anticipate, occur in the specific area. If possible, recruit several birders to
conduct this task independently of one another. Also ask the local birders to
review and comment on the relative abundance data you’ve entered in the
REGIONS database.
(3) Compare the lists of one or more of the local birders with the one that
AREM generated for the area. At each wetland where any discrepancies
exist between the AREM list and the birder lists, have the model builder (the
avian expert) intensively query the birder(s) as to why they would or would
not expect to fmd the discrepant species, i.e., which habitat indicators for
which species are poorly defmed, missing, irrelevant, or over- or under-
emphasized by AREM.
(4) Using EDITAREM, modify the models (second pass) to reflect the local
input.
A somewhat more involved procedure could be used for testing an adapted AREM,
and might come closer to truly validating its accuracy. This procedure would
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progress the same as above, except that in #2, a sufficient number of actual surveys
of birds would be conducted by a skilled birder using appropriate methods, and the
resultant species lists, rather than lists based on a birder’s judgement, would be
compared (in #3) with the lists generated by AREM.
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3.0 LITERATURE DOCUMENTATION FOR AREM
3 1 Documentation of Indicator Thresholds
3.1 .1 Introduction
The following narrative describes the basis for the specific thresholds used for particular
indicators contained in the AREM field form (Appendix B). If desired, readers wishing to
gain a broader, more fundamental understanding of the indicators that AREM uses may
consult Adamus (1993 a).
Whenever numeric thresholds are included in an evaluation method, there is considerable
risk that some users will assume that these values are soundly supported by extensive
research or are appropriate to all situations. This is unfortunately not true. In reality, few
if any of the specific thresholds included in AREM or other rapid evaluation methods are
conclusively supported by research findings. Where they seem to be, there still remains
considerable uncertainty as to whether the supporting research can be validly extrapolated
to all situations where the evaluation method might be used.
Why, then, are specific thresholds used? The reason is that thresholds, by standardizing
important judgements, are essential to improve a method’s replicability (the tendency of
different users to answer questions about the same area in the same manner). When
methods are poorly replicable, their credibility and, in some cases, their legal defensibility
suffers.
Despite the frequent lack of conclusive documentation for particular thresholds, the
numbers used by AREM are not merely speculative. Their general order of magnitude
reflects the author’s inferences from broadly-accepted ecological principles as defined by
current wetlands literature and expert opinion. Users wishing to substitute other
threshold values may do so, provided they (a) explicitly document where they made
substitutions, and (b) cite appropriate data that supports the alternative values. In
particular, use of alternative thresholds may be justified to reflect differing effects of other
seasons, regions, species, and ecosystem types.
3.1.2 Area Thresholds
AREM uses thresholds for habitat area (i.e., size or acreage) in several places (#‘s below
refer to numbered questions on the field form, Appendix B; boldface has been added below
to emphasize area thresholds that are used):
#1. LOCATION. Is the wetland part of... a major ...lake? ( ...lake larger
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than 40 acres).
#2. SURFACE WATER. Is there at least 0.1 acre of surface water...?
#3. OPEN WATER. How much open* water is present...
> 20 acres...
< 1 acre...
____ Other conditions
#4. SPECIFIC AQUATIC CONDITIONS
> 0.1 acre of the surface water is still
#5. BARE SOIL. Is there at least 0.1 acre of mud...
#6. LARGE MUDFLAT. [ Is] the mud habitat...
_____ At least 1 acre in size
#8. TREE COVER.., check the response below that best represents the overall
extent of tree cover:
> 1 acre...
____ 0.1-1 acre...
#11. SHRUBS. Is there at least 0.1 acre of shrubs...
#12. SHRUB SPECIES AND DENSITY... [ by type:]
> 1 acre...
____ 0.1-1 acre...
#13. HERBACEOUS VEGETATION. [ question and threshold similar to #111
#14. HERBACEOUS SPECIES... [ by type:]
[ question and threshold similar to #12]
Rationale for Area Thresholds . As compiled above, the area thresholds that AREM uses
are 0 1 acre, I acre, 20 acres, and 40 acres. AREM assumes that larger wetlands and larger
patches of habitat within wetlands tend to have more species, but that the exact effects
depend primarily on the local pool of species and the type of habitat. The AREM species
models also recognize the role of other factors in influencing the species-area relationship,
such as patch width or shape (Section 3.1.3 below) and proximity to other wetlands or
agricultural lands (for further information see Section 3.1.6, and optionally Section 4.4.1 in
Adamus 1993a).
The larger two thresholds (20, 40 acres) are applied only to open water habitat. Reservoirs
larger than 26 acres are used by the largest numbers of migrant and wintering ducks in arid
western Oklahoma (Copelin 1953), and those larger than 40 acres are preferred by ducks in
north Texas (Hobaugh and Teer 1981) and Quebec (DesGranges and Houde 1989). Geese
most often use wetlands larger than 20 acres (Guthery and Stormer 1984). In the prairie
pothole region a cumulative wetland area of 200-900 acres might be required to support the
full complement of local species (Brown and Dinsmore 1986), and 10 of 25 species did not
use wetlands smaller than about 2 acres. However, data from north-central Minnesota
(Williams 1985) and Maine (Gibbs 1991) demonstrate the elusiveness of simplified
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relationships between avian richness and wetland area
The two smaller thresholds (0.1 and I acre) are applied to both open water and vegetated
wetland habitats. The 0.1 acre threshold approximates the theoretically smallest home
range of about 67% of the 90 species that regularly breed in the Colorado Plateau
region’ 1 , whereas the 1 acre threshold approximates the theoretically smallest home range
size of about 31% of the breeding species. Studies cited in Adamus (1 993a) and Leibowitz
et al. (1992) document regular bird use of wetlands as small as 1 acre, and a simulation
study by Gibbs (1993) highlights the adverse potential consequences of loss of such
wetlands. However, few species use isolated vegetation patches of less than about 1 acre,
because such patches often have maximum dimensions no larger than 100 ft. which
severely exposes their inhabitants to the elements and predators. In some arid regions of
North America, few seasonal wetlands smaller than 0.1 acre and few semipermanent
wetlands smaller than 2 acres persist over time (Stewart and Kantrud 1971), unless
subsidized by irrigation water. Although evidence suggests that one-acre patches of forest
in the eastern U.S. are too small for many breeding birds, many of the species that use
Colorado Plateau lowland wetlands are “edge” species presumably accustomed to using
small patches. In eastern Colorado, one riparian species (tree swallow) nested only in
riparian fragments larger than 37 acres, another (black-capped chickadee) nested in
fragments larger than 17 acres, several nested in fragments larger than about 3 acres
(American kestrel, northern flicker, hairy woodpecker, downy woodpecker), and one (house
wren) nested in fragments as small as 0.3 acre, which was the smallest measured (Gutzwiler
and Anderson 1987).
In a sample of 187 wetlands located within 1000 ft of canals and ditches in the Lower
Gunnison-Uncompahgre subregion, 158 (84%) of the wetlands were smaller than I acre. In
the same general area, a survey of 800 wetlands by Rector et al. (1979) also included
natural bottomland wetlands, and reported the mean wetland size as 27 acres. However,
both of these studies measured the area of an entire wetland, whereas AREM requires
estimation of the area of the individual habitat types within a wetland.
The theoreucal home range size cstunalc was derived using the allomevic equation of Schoener (1968) as demonstrated by Van
Home and Wiens (1991) The equation is
A =986M’”
where A is the predicted home range area (in ha) and M is the body mass (in g) From Dunning (1984, 1993). I obtained average body mass
data for 86 of the 102 species that breed regularly in lowlanl wctland/npanan areas of the region The 26 breeding species categorized as
“highly dependent” or “intermediate” with regard to use of wetlands were projected to have a mean home range of 553 acres (range 004-42
acres), whereas the mean for the 60 species categorized simply as ‘dependent’ was projected as I 03 acres (range 001-14 acres) The
accuracy of the allometric formula is difficult to gauge, but an auempt was made to determine its comparability When I compared (for 40
of the species) the predicted home range areas with areas inferred from Breeding Bird Census (BBC) data (by dividing plot area by number
of pairs, for a small number of plots from wetland habitats nationwide), I found all but 4 of 40 the allometric-based ranges to be smaller than
BBC-based ranges Areas predicted by the allomeuic equation were an order of magnitude smaller than BBC-bascd areas for 17 (43%) of
the 40 species This could mean that a threshold somewhat larger than one acre migJ t be appropriate to represent home range sizes of
Colorado Plateau breeding bird species
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3.1.3 Width Thresholds
AREM uses thresholds for width in the following places:
#1. LOCATION. Is the wetland part of...a major* river...? (t river wider than
100 ft...)
#3. OPEN WATER. How much open* water is present...
____ > 20 acres it is mostly wider than 500 ft
< I acre, , >1 acre but mostly narrower than 3 ft
#6. LARGE MUDFLAT. Does the mud habitat have...
o Maximum dimension greater than 100 ft?
#18. PREDATION POTENTIAL. Wetland...is linear (i.e., no more than 10% of the
wetland is farther than 25 ft from a road, canal, or other artificially linear feature.
Rationale for Width Thresholds . As compiled above, the width thresholds that AREM uses
are 3 ft. 25 ft. 100 ft, and 500 ft. AREM assumes that wider wetlands and wider patches of
habitat within wetlands usually support more species, but that exact effects depend
primarily on the species and the type of habitat. The AREM species models also recognize
the role of other factors that influence bird use of narrow or wide patches, such as patch
area (Section 3.1.2 above), and proximity to other wetlands or agricultural lands (Section
3.1.4 below, and Section 4.4.1 in Adamus 1993a).
The AREM specifications that width of open water patches be greater than 500 ft and
certainly not less than 3 ft (question #3) are based on the assumption that narrower patches
would restrict the ability of some larger waterbirds to take flight. Data from other regions
(Ambrose et al. 1983) suggests that, for taking flight, a few waterbird species require open
water or otherwise flat areas wider than about 500 ft. Shorebirds along inland migratory
routes appear to favor mudflats wider than about 100 ft. and especially wider than 1500 ft,
even though large numbers can occur on lakeshore flats as narrow as 3-6 ft (Taylor and
Trost 1992).
Birds nesting in vegetation patches narrower than 100 ft, and certainly those in areas
narrower than 25 feet, are likely to be frequently disturbed by predators (which follow the
edges of vegetation patches) and human visitors (because such narrow patches offer little
visual buffer). Because specific supporting data were lacking from the Colorado Plateau,
these numerical values were based mostly on the author’s judgement. Studies in other
regions report that zones of emergent vegetation are most likely to develop along ditches
wider than about 30 ft (Linde 1969). Along areas of open water, nesting waterfowl prefer
strips of emergent vegetation that are wider than 25 ft; strips wider than 70 ft are
considerably better (Atlantic Waterfowl Council 1972).
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3.1.4 Distance Thresholds
AREM uses thresholds for distance in the following places:
#1. LOCATION. Is the wetland part of, or is it within 0.5 mile of, a major river or
lake?
#7. TREES. Are there at least 3 trees:
____ within 1000 ft of the wetland (including the wetland itself)?
____ in the wetland or within 300 ft?
#8. TREE COVER. Add the tree acreage within 300 ft of the wetland, to the tree
acreage actually within the wetland...
#9. BIG TREES Are there at least three trees... within the wetland or within 300
ft of its perimeter?
#10. SNAGS. [ question and threshold similar to #9]
#11. SHRUBS. Is there at least 0.1 acre of shrubs*:
____ within 1000 ft of the wetland...?
____ in the wetland or within 300 ft?
#12. SHRUB SPECIES AND DENSITY. For each shrub type...add the acreage of
the same shrub within 300 ft of the wetland to...
#13. HERBACEOUS VEGETATION. [ question and threshold similar to #11]
#14 HERBACEOUS SPECIES. [ question and threshold similar to #12]
#15. SURROUNDING LAND COVER. Within 0.5 mi of the wetland, >60% of the
land cover is...
#16 LOCAL LAND COVER. Within 3 ml of the wetland, >60% of the land c iver
is...
#17. VISUAL SECLUSION
(b) there are no paved roads within 600 ft...
#18. PREDATION POTENTIAL
____ Wetland...is closer than 1000 ft to a normally-occupied building
#20. NESTING LOCATIONS
____ Semi-open structures... suitable for nesting swallows are present within
300 ft
Rationale for Distance Thresholds . As compiled above, the distance thresholds that AREM
uses are 300 ft., 600 ft, 1000 ft, 0.5 mi, and 3 mi. AREM assumes that wetlands with
beneficial habitat features located nearby (especially within these distances) will usually
support more species, and that wetlands with detrimental features located nearby will
support fewer species, other factors being equal.
The 300-ft threshold is intended to approximate a maximum dimension of the theoretical
home range sizes of 16 (19%) of the 86 species that breed in Colorado Plateau wetlands,
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calculated as described in footnote #10 and assuming circular shapes for home ranges. In
other words, vegetation or other habitat outside the wetland but within 300 ft is likely to be
used by several species that mainly use the wetland, and several species outside the wetland
but within 300 ft will regularly use the wetland. The 300-ft threshold is further
documented by the following: (a) from some limited field data, Croonquist and Brooks
(1993) considered widths of 300 ft to be adequate for maintaining avian richness in wooded
str arn corridors in Pennsylvania, (b) in Maryland, a study of riparian birds indicated that
neotropical migrant species breed mostly in corridors wider than about 330 ft (Keller et al.
1993), and (c) in Colorado, the density and type of vegetation is often altered within 295 ft
(90 m) downslope from lined canals, and is sometimes altered up to 590 ft (180 m)
downslope.
The 0.5- and 3-mi thresholds relate to three factors: (a) migratory corridors for shorebirds
and songbirds, (b) foraging distances of larger waterbirds, and (c) dispersal distances of
wetland-dependent songbirds (i.e., the distance that young birds move between wetlands
where they were hatched and, the following year, wetlands where they breed).
Many migratory birds (which comprise about 81% of the region’s wetland avifauna) appear
to concentrate in wetlands in the vicinity of major rivers and lakes, and use these areas as
corridors or “stepping stones” as they migrate long distances Accordingly, AREM assumes
that wetlands located within 0.5 mi of large water bodies would serve this purpose, but this
value and the values that defines “large” were based exclusively on the author’s judgement
because no supporting regional data were available. In the central parts of the United
States, small wetlands seem to support the most nesting waterfowl when located within
about 3 mi of a large water body or a permanently or semipermanently flooded wetland to
which birds can freely travel when foraging (Low 1945, Warren and Bandel 1968, Williams
1985, Dobie 1986, Baldassare and Bolen 1987). Duck broods that are forced to move long
distances due to a low density of wetlands on the landscape have relatively lower survival
rates (Rotella and Ratti 1992). Average dispersal distances of song sparrows (a wetland
species) are 0 6 to 0.9 mi (Nice 1937, Johnston 1956). In arid irrigated areas of Texas,
pheasants use areas within about 0.7 mi of wetlands (Guthery and Stormer 1984), and
pheasants in Michigan, Wisconsin, and North Dakota have an average travel radius of about
0.25 mi (Sather-Blair and Linder 1980).
The 600-ft threshold for visual seclusion also is based on the author’s judgement, but
reflects generally the literature on sensitive species in other regions. Wintering bald eagles
in some areas take flight when approached from as far away as 800-1600 ft (Stalmaster and
Newman 1978, Knight and Knight 1984, McGarigal et al. 1991, Buehler et al. 1991).
Many waterbirds take flight when humans on foot are seen approaching within 75 to 175 ft.
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3.1.5 Other Thresholds
AREM uses several other numeric thresholds, as follows:
#3. OPEN WATER. How much open’ water is present...
(* Water deeper than 2 inches..)
#4. SPECIFIC AQUATIC CONDITIONS
(a) .. .the surface water is still, i.e., usually flows at less than 1 ft/s
(b) Water transparency in the deepest part of the wetland is usually sufficient
to see an object 10 inches below the surface...
(c) Most. ..of the wetland goes dry at least one year in five...
#7. TREES. Are there at least 3 trees...
#8. TREE COVER...
____ >1 acre, dense’
____ >1 acre, open...
* Dense= the tree canopy.. .appears at least 50% closed
#9. BIG TREES. Are there at least three trees of >12 inch diameter...
#10. SNAGS. Are there...trees with dead limbs of diameter >5 inches...
#12. SHRUB SPECIES AND DENSITY... [ question and threshold are similar to #8).
#14. HERBACEOUS SPECIES...
“ Tall= taller than 1 ft
#15. SURROIJND NG LAND COVER. Within 0.5 mi of the wetland, >60% of the
land cover is...
#16. LOCAL LAND COVER. [ question and threshold are similar to #15]
#17. VISUAL SECLUSION
(a) wetland is seldom visited by people on foot or boat (less than once
weekly...
#18. PREDATION POTENTIAL
Wetland adjoins a heavily-traveled road (usual maximum of >1 car/minute),
andlor is in a high-density housing area (>1 house/S acres)...
#20. NESTII’4G LOCATIONS
Vertical, mostly bare dirt banks at least 5 ft high.. .of potential use to nesting
kingfishers, barn owls, and swallows.
Rationales for the Other Thresholds . The first threshold listed above (#3, water >2 inches
deep) describes water that is deep enough for most of the region’s waterfowl species to use,
based on the anatomy and behavior of these species. It is recognized that most waterfowl
prefer greater depths (to at least 12-18 inches depth); AREM accounts for that fact
indirectly by including water body area as an indicator in the waterfowl species models.
The I -ft’s threshold used in question #4(a) describes a velocity beyond which most ducks
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and other birds that use water as a substrate are much less likely to occur. The threshold is
based on the author’s judgement and reflects an assumption that at greater velocities,
waterbirds would spend so much energy maintaining their position that their feeding
success would be lowered.
The 10-inch threshold used in question #4(b) describes a degree of water clarity assumed to
be sufficient to (a) allow at least minimal growth of completely submersed aquatic plants
and associated aquatic insects that are important to many waterfowl species, and (b)permit
waterbirds that feed on subsurface foods to see these foods. This threshold is based on
literature from other regions (as compiled in Kantrud 1990) which suggests that one of the
submersed plants that is most-favored by Colorado Plateau waterfowl -- sago pondweed,
Potamogeton pectinatus -- grows poorly when water column visibility is less than about 10
inches.
The threshold used in question #4(c) -- dry-out occurring at least one year in five --
describes a frequency of water level drawdown that is assumed sufficient to increase the
productivity of open-water wetlands, partly by oxidizing organic matter and associated
nutrients located in wetland sediments, and facilitating seed germination. Abundant
evidence from other regions (Knighton 1985, Fredrickson and Taylor 1982) supports the
assumption that wetlands which otherwise are permanently flooded support greater
secondary production if they periodically dry out or exchange waters with major rivers or
lakes. The specific threshold (one year in five) reflects literature on marsh management
that recommends drawdown frequencies of once every 3-5 years (range, 1-10 years)(Harris
and Marshall 1963, Linde 1969, Payne 1992).
The threshold of three” trees used in question #7 describes a condition assumed to be
minimally acceptable to most riparian species. Birds (particularly perching raptors)
occasionally visit wetlands with only one or two trees, but a threshold of three was set to
allow for minimal resource turnover (i.e., long-term replacement of trees lost from
blowdowns). The threshold is based entirely on the author’s judgement.
The threshold of 50% canopy closure to differentiate dense from open stands of woody
vegetation (#8, 12) also is based entirely on the author’s judgement, because regional data
relating avian richness to canopy closure in lowland riparian areas were not available.
AREM uses a threshold of >12 inches diameter to define large trees (#9) and a threshold of
>5 inches diameter (#10) to define dead trees and limbs useful to cavity-nesting wildlife,
which contribute importantly to avian richness. In northeastern Colorado, cottonwoods
having cavities larger than 1 inch are used (or excavated) by downy woodpecker, black-
capped chickadee, and house wren; those larger than 3-4 inches are used by wood duck,
American kestrel, western screech owl, and northern flicker. Most cavities are found in
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limbs of greater than 6-12 inches diameter (Sedgwick and Knopf 1986).
The threshold of 1 ft for vegetation height, used to differentiate short from tall stands of
herbaceous vegetation (#14), is based on the assumption that many birds which dwell
mostly at ground level (e.g., shorebirds, waterfowl) cannot routinely see above much taller
vegetation. These species often prefer wetlands with vegetation <1 ft so that approaching
predators can be detected and avoided in time. Some other species (e.g., bitterns) seldom
use stands of vegetation shorter than about 20 inches, and especially not shorter than 1 ft.
Studies in Arizona (Ohmart et al. 1985) demonstrated the importance of herbaceous
vegetation height for predicting the birds that use irrigated wetlands.
A threshold of 60% for cover types (#15, 16) within an area of specified size is used to
differentiate landscapes that are functionally (from a bird perspective) dominated by the
specified types of land cover from ones that are not. Recognizing that different species
respond to land cover at different scales, AREM requires that users consider whether this
proportion is attained at distances of 0.5 mi and/or 3 mi from the evaluated wetland. The
proportion (60%) was derived from “percolation theory t ’ by O’Neill et al. (1988) and
reflects a theoretical probability that an unspecified organism will be able to move freely
across a landscape among patches of its favored habitat. The applicability of this
assumption to birds in the Colorado Plateau region is untested.
The thresholds for visual seclusion (#17) and predation potential (#18) are based entirely on
the author’s judgement, because regional data relating avian richness to these types of
disturbances were not available. They are perhaps the most subjective of the thresholds
included in AREM.
The 5-ft threshold for height of banks suitable for bank-nesting birds is based primarily on
the author’s observations and assumes that birds nesting in banks much lower than this
would be more severely harassed by mammalian predators.
3.2 Documentation of Weighting Factors
AREM currently provides users with the option of weighting species according to any of
six characteristics. These are described below Weights are currently assigned on a 1-10
ordinal scale, but there are no empirical data to support particular numerical values, so
users can choose other values and scales.
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3.2.1 Species Dependency on Wetland/Riparian Habitat
The WEIGHTS database of AREM defines the following categories:
Category Preassigned Weight
Highly Dependent 10
Intermediate 6
Dependent 2
“Highly Dependent” means that surface water is the species’ primary substrate: e.g.,
common goldeneye. “Intermediate” means the species occurs only where water/wetland is
present: e.g., spotted sandpiper. “Dependent” means the species also uses uplands, but uses
wetlands frequently: e.g., warbling vireo. AREM users can see which category each
species has been assigned to, and change the designation if they prefer, by loading the
EDITAREM program (see p. 42), selecting the WEIGHTS database, and editing values in
the WETDEPEND column. Current assignments of species to particular categories were
based entirely on the author’s interpretation of literature and experience with the species.
3.2.2 Relative Abundance
The WEIGHTS database of AREM defines the following categories:
Category Code Preassigned Weight
Uncommon U 10
Fairly Common F 6
Common C 4
Abundant A 2
Rare X (not included)
“Uncommon” species are ones that can be found in suitable habitat at the appropriate
season at a rate of about 1-10 per day, whereas “fairly common” species are encountered at
a rate of 10-25 per day, “common” species at a rate of 25-100 per day, and abundant
species at a rate of >100 per day. These definitions are from Dexter and Lavad (1992), and
separate abundance codes have often been assigned for different seasonal periods. Species
that are not likely to be encountered daily, even at an appropriate season and in suitable
habitat, are not included in AREM. However, if there are known instances of a regularly-
present species having such a low detection rate solely because of its characteristic
secretiveness or obscurity, then it should nonetheless be factored into calculations of avian
richness. AREM users can see which category each species has been assigned to, and
change the designation if justified, by loading the EDITAREM program, selecting the
WEIGHTS database, and editing values in the column corresponding to the desired
54
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subregion and season. Current assignments of species to particular categories were based
mainly on literature (cited on p. 70 of Adamus 1993a), but abundance categories of species
breeding in the Grand Valley subregion were modified after data from the author’s field
studies had been analyzed, to reflect insights gained from the data. There is considerable
potential for improving this information, and thus the assignment of appropriate weights,
through collection and analysis of additional field data (see p. 42 for discussion of this).
Inf rmation on relative abundance in the WEIGHTS database is identical to information in
the REGIONS database.
3.2.3 Taxonomic Uniqueness
AREM assigns more weight to wetlands having species that are, relatively speaking,
taxonomically unrelated. For example, a wetland whose (say) five species are each from a
different taxonomic order will be calculated to have greater taxonomic diversity than a
wetland whose five species are from taxonomically different families within a single order.
That is because within the hierarchy of taxonomic classification, orders are considered to be
generally more distinct than families. This is important because animal communities that
are taxonomically diverse are often genetically and functionally diverse, i.e., gene pools
contain considerable variability, species sometimes fill a wide variety of trophic roles, and
food webs can be complex, presumably leading to greater adaptability and sustainability of
populations (Vane-Wright et al 1991)
AREM calculates the taxonomic uniqueness of a wetland in the following manner. After
predicting which species should occur in a wetland, AREM calls up the TAXINF database
and sorts all species present in the evaluated wetland according to the values in the
TAXINF database, proceeding from left (beginning with the “Order” column) to right
(ending with the “Species” column). This sequence reflects decreasing taxonomic
uniqueness. Then, the program assigns the maximum value to each species as follows:
Species Is The Sole Representative
In This Wetland of Its Points
Order 9
Suborder 8
Parvorder 7
Superfamily 6
Family 5
Subfamily 4
Tribe 3
Genus 2
Species I
55
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After assigning weights to all species, AREM sums them to give the final “taxonomic
uniqueness” score for the “weighted habitat.” Information in the TAX [ NF database was
derived from DeSante and Pyle (1986) and Ehrlich et al. (1988).
3.2.4 Neotropical Migrant Status
The WEIGHTS database of AREM defines the following categories:
Category Preassigned Weight
Type A migrants 10
Type B migrants 6
Others 2
“Type A” species breed only in the United States and/or Canada and migrate to the
Neotropics. “Type B” species also breed in the Neotropics. Other regional species
generally do not migrate to Neotropics. AREM users can see which category each species
has been assigned to, and change the designation if they prefer, by loading the EDITAREM
program, selecting the WEIGHTS database, and editing values in the NEOTROPIC column.
Current assignments of species to particular categories were based entirely on information
compiled by Carter and Barker (1993).
3.2.5 Official Conservation Designations
The WEIGHTS database of AREM assigns a weight of “10” to any species that has of
the following official conservation designations:
Endangered (federally listed)
Threatened (federally listed)
Candidate for Threatened or Endangered list
G3 (“rare/uncommon globally but not imperiled”)
G4 (“not rare; apparently secure but cause for longterm concern”)
Si (sensitive due to possibly declining populations and/or rarity statewide)
S2 (sensitive due to possibly declining populations and limited in-state distribution)
S3 (sensitive but fairly common statewide)
“Watch List” (apparently sensitive but information lacking)
Species not officially designated as belonging to any of the above categories are assigned a
weight of “1.” AREM users can see which category each species has been assigned to, and
change the designation if warranted, by loading the EDITAREM program, selecting the
WEIGHTS database, and editing values in the corresponding columns (ENDANGERED,
THREATENED, CANDIDATE, G3, G4, SI, S2, S3, WATCI-ILIST). Species whose
56
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official designations apply only to breeding populations, and which do not breed in the
study region, were not included unless their nonbreeding populations also had been
officially assigned special status. Information on official designations of species came from
the state natural heritage programs in Colorado, Utah, and Wyoming.
3.2.6 Hunted Status
The WEIGHTS database of AREM defines just two categories:
Category Preassigned Weight
Hunted 10
Not Hunted 1
The “Hunted” species category includes all wetland species, whether resident or migratory,
that can be harvested legally in the study region. AREM users can see which category each
species has been assigned to, and change the designation if warranted, by loading the
EDITAREM program, selecting the WEIGHTS database, and editing values in the
corresponding column (HUNTED)
57
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4.0 LITERATURE CITED
Adamus, PR. 1987 Alias of Breeding Birds in Maine, 1978.1983 Maine Dept of Inland Fish & WildI, Augusta, Maine
Adamus, P R I 993 a. Irrigated Wetlands of the Colorado Plateau lnfommnon Synthesis and Habitat Evaluation Method EPA/6001R-
93/07 I US Environmental Protection Agency Environmental Research Laboratory, Corvallis, Oregon
Adarnus, PR. l993b Validation of a habitat evaluation method US Environmental Protection Agency Environmental Research
Laboratory, Corvallis, Oregon
Ambrose, RE, C P.. I-tinkle, and C K. Wenzcl 1983 Practices for Protecting and Enhancing Fish and Wildlife on Coal Surface-mined
Land in the Southcenual United States FWS/OBS-83/1 I U S Fish & Wildi Serv, Washington, DC
Atlantic Waterfowl Council 1972 Techniques Handbook of Waterfowl Habitat Development and Management Atlantic Waterfowl
Council, Bethany Beach. Delaware
Baldassarie, GA and E G Bolen 1987 Management of Waste Corn for Waterfowl Wintering on the Texas High Plains Note 13
Dept. Range & WildI Manage, Texas Tech Univ, Lubbock, Texas
Bock, CE 1987 Diso’ibutjon-abundance relationships of some Arizona landbirds A matter of scale” Ecology 68 124-129
Brown, M and J I Dinsmore 1986 Implications of marsh size and isolation for marsh bird management. 3 Wildl Manage 50(3) 392-
397
Buehler, D A, Ti Mersmann, 3D Fraser, and J KD Seegar 1991 Effects of human activity on bald eagle disttibution on the northern
Chesapeake Bay J WildI Manage 55 282-290
Busch, DE and SD Smith 1993 Effects of fire on water and salinity relations of npanan woody taxa Oecologia 94 186-194
Carter, M F and K Barker 1993 An interactive database for setting conservation priorities for western neoti-opical migrants p 120.
14-4 In D M Finch and P W Stangel (eds) Status and Management of Neoiropical Migratory Birds Gen Tech Rep RM-229 USDA
Forest Serv, Fort Collins, Colorado
Copelin, F F 1953 Waterfowl inventory on small flood prevention reservoirs in western Oklahoma Proc OkIa. Acad Sci 42 260-263
Croonquist, M I and R P Brooks 1993 Effects of habitat disturbance on bird communities in nparian comdors 3 Soil Water
Conserv 48 65-70
DeSante, D and P Pyle 1986 Distributional Checklist of North American Birds Artemesia Press, Lee Vining, California
DesGranges, I L and B Houde 1989 Effects of acidity and other environmental parameters on the distribution of Iacustiinc birds in
Quebec p 7-41 In 3 L DesGrariges (ed) Studies of the Effects of Acidification on Aquatic Habitat in Canada Lacustone Birds and
Their Habitats in Quebec Occasional Pap 67 Canadian WildI Serv, Ottawa
Dexter, C and R Lavad 1992 Bird Check List for the Grand Valley and Surrounding High CounUy of Mesa County, Colorado
Grand Valley Audubon Society, Grand Junction, Colorado
Dobie, B 1986 Private financing for wetland restoration p 14-28 In I L Piehi (ed) Wetland Restoration A Techniques Workshop
Minnesota Chapter, The Wildlife Society, Fergus Falls, Minnesota
Dunning, 3 B, Jr 1984 Body Weights of 686 Species f North American Birds Monograph No I Western Bird Banding Assoc,
Tucson, Arizona
Dunning. I B • Jr 1993 CRC Handbook of Avian Body Masses CRC Press, Boca Raton, Florida.
Elirlich, P K., D S Dobkin, D Wheyc 1988 The Birder’s Handbook A Field Guide to the Natural History of North American Birds
Simon & Schuster Inc. New York
58
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Frednckson, LH and TS Taylor 1982 Management of Seasonally Flooded Impoundments for Wildlife Resour Pub 148 US Fish
& WildI Serv. Washington, DC
Gibbs, J P 1991 Usc of Wetland Habitats by Selected Nongarne Water Birds in Maine Fish and WildI Res Pub 9 U S Fish &
WildI Serv, Washington, DC
Gibbs, J P 1993 Importance of small wetlands for the persistence of locai populations of wetland-associated animals Wetlands 13.25-
31
Guthery, F S and F A Stormer 1984 Playa management. p 177B-182B In FR. Henderson (ed) Guidelines for Increasing Wildlife
on Farms and Ranches Coop Extention Serv • Kansas St. Univ. Manhatten, Kansas
Gutzwiler. K J and S H Anderson 1987 Multiscale associations between cavity-nesting birds and features of Wyoming streaznside
woodlands Condor 89 534-548
Hams, SW and W H Marshall 1963 Ecology of water-level manipulations on a northern marsh Ecology 44331.343
Johnston, RF 1956 Population stiucture in salt marsh song sparrows I Environment and annual cycle Condor 58 24-44
Kantrud, HA 1990 Sago Pondweed A Literature Review Resour PubI 176 US Fish & WildI Serv, Washington, DC
Keller, C M E, CS Robbins, and iS Hatfield 1993 Avian communities in nparian forests of different widths in Maryland and
Delaware Wetlands 13 137-144
Knight, R.L, and S K Knight 1984 Responses of wintenng bald eagles to boating activity I WildI Manage 48 999-1004
Knighton, MD (compiler) 1985 Water Impoundments for Wildlife A Habitat Management Workshop Gen Tech Rep NC-lOO
USDA Forest Serv, St. Paul, Minnesota
Lacy, R.C and C E Bock 1986 The correlation between range size and local abundance of some North Amencan birds Ecology
67 258-260
Leibowi , 5, B Abbruzzese, P R Adamus, L Hughes, and J Irish 1992 A Synoptic Approach to Cumulative Impact Assessment.
EPA/600/R-62i167 U S Environmental Protection Agency Environmental Research Laboratory, Corvallis, Oregon
Linde. A F 1969 Techniques for Wetland Management. Rep No 45 Wisconsin Dept. Nat. Resotir, Madison, Wisconsin
Low, I B 1945 Ecology and management of the redhead in Iowa Ecol Monogr 15 35-69
McGangal, K, RG Anthony, and F B Isaacs 1991 Interactions of humans and bald eagles on the Columbia River estuary Wildi
Monogr 1151-47
Mornson, M L, B G Marcot, and R.W Mannan 1992 Wildlife-habitat relationships Univ Wisconsin Press, Madison, Wisconsin
Nice, MM 1937 Studies in the life history of the song sparrow I A population study of the song sparrow Trans L’innean Soc of
New York 4 1-247
O’Neill, R.V, B T Milne, M G Turner, arid RH Gardner 1988 Resource utilization scales and landscape pattern Landscape Ecol
2 63-69
Ohmart, RD, B W Anderson, and W C Hunter 1985 Influence of agriculture on waterbird, wader, and shorebird use along the lower
Colorado River p 123-127 In RJt Johnson,CD Zicbcll, DR Pant n, PF Ffollioa., and RH Hamrc (tech coords) Ripanan
Ecosystems and Their Management Reconciling Conflicting Uses Gen Tech Rep RM- 120, USDA Forest Serv, Fort Collins,
Colorado
Payne, N F 1992 Techniques of Wildlife Habitat Management of Wetlands McGraw-Hill, Inc,New York. New York
59
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Rector, C D, E W Mustard, and IT Windell 1979 Lower Gunrnson River Basin Wetland Inventory and Evaluation USDA Soil
Conservation Service, Denver, Colorado
Rotella, 1.1 and IT Rant 1992 Mallard brood movements and wctiand selection in southwestern Manitoba. I Wildi Manage 56 508-
S’s
Samson, F B and F L Knopf 1982 In search of a diversity ethic for wildlife management Trans N Amer Wildl Nat. Resour Con!
47 42 1431
Sather-Blair, S and R.L Linder 1980 Pheasant use of South Dakota wetlands during the winter Proc South Dakota Acad Sci
59147-155
Schoener, TW 1968 Sizes of feeding territones among birds Ecology 49 123-131
Scott, J M, F Davis, B Csuti, R. Noss, B Butterfield, C Groves, H Anderson, S Caicco, F D’Erchia, TC Edwards, It, I Ulliman,
and R_G Wnght 1993 Gap analysis a geographic approach to protection of biological diversity WildI Monogr 123 1-41
Sedgwick, I A and F L Knopf 1986 Cavity-nesting birds and the cavity-isee resource in plains cottonwood bottomlands I Wildl
Manage 50 247-252
Stalmaster, MV and JR. Newman 1978 Behavioral responses of winteruig bald eagles to human activity J WiIdl Manage
42 506-513
Stewart, RE and H A Kantrud 1971 Classification of Natural Ponds and Lakes in the Glaciated Prairie Region Res PubI 92 U S
Fish & Wildi Serv, Washington, DC
Taylor, D M and C H Trost 1992 Usc of lakes and reservoirs by migrating shorebirds in Idaho Great Basin Nat. 52 179-184
U S Fish and Wildlife Service (USFWS) 1980 Habitat Evaluation Procedures (HEP) Manual (IO2ESM) US Fish & Wildl Serv,
Washington. DC
Usher, M B (Cd) 1986 Wildlife Conservation Evaluation Chapman and Hall, London, UK
Van Home. B and J A Wiens 1991 Forest Bird Habitat Suitability Models and the Development of General Habitat Models Fish and
Wildlife Research Rep 8 U S Fish & Wildl Serv. Washington, DC
Vane-Wright. RI, C J Humphries, and P H Williams 1991 What to protect’ - systemaucs and the agony of choice Biol Conscrv
55 235-254
Warren, I and D Bandel 1968 Pothole blasting in Maryland wetlands Proc Annu Con! Southeast. Caine Fish Comm 22 58-68
Williams, C L 1985 Classifying wetlands according to relative wildlife value Application to waxer impoundments p 110-119 In
MD Knighton (compiler) Water Impoundments for Wildlife A Habitat Management Workshop (len Tech Rep NC-100 USDA
Forest Serv, St Paul, Minnesota
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Appendix A. AREM Field Form: Documenting Information
(not used in the data analysis)
Name of the Evaluated Area: _____________________________ Date Evaluated: _________
Name of Associated Computer File (assign one, having 8 characters):
Evaluator (s):
Type of Wetland (check one):
On-fann Off-farm
Wetland Water Source (check one or more)’
Subsurface seepage - Mostly Natural
— Subsurface seepage - Mostly Irrigation-related
Overland runoff - Mostly Natural
— Overland runoff - Mostly Irrigation-related
— Channel or lake overflow - Mostly Natural
— Channel or lake overflow - Mostly Irrigation-related
WETLAND SCORES (insert here after completing the data analysis)
Cutoff Level for Species Habitat Scores
>O% >25% >50% >75%
____________________________________ ( all possible spp ) _________ ( most conservative )
Unweighted Habitat Score
Unweighted Richness Score
Habitat Score Weighte& 2 By Species’
Relative Dependency on Wetlands
Relative Abundance
Taxonomic Uniqueness
Neotropical Migrant Status
Official Conservation Designations
Hunted Status
For “Dependency on Wetlands.” largest weights are assigned to species using waler as a substiatc, smallest weights to species
that regularly use upland habitat. For “Relative Abundance,” largest weights are assigned to unrommon species, smallest to abundant species
For “Taxonomic Uniqueness,” largest weights are assigned to species that are the only ones of their genus in the region, smallest to species
having many congeners For Neovopical Migrant Status, largest weights arc assigned to species breeding only in the U S or Canada and
migrating to the Neotropics, smallest weights to nonmigratoTy species For “Official Conservation Designations,” largest weights are assigned
species with stale, federal, or Heritage Program designations, smallest weights to others For “Hunted Status,” largest weights arc assigned
species that arc legally hunted, smallest weights to others
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Appendix B. AREM Long Form
For each numbered item, check only one response unless noted otherwise. Then proceed to
the next question unless noted otherwise. Parenthetical names are the names of fields in the
supporting software database (WHRBASE). If a field name is lacking, the information is
nol used directly.
1. LOCATION. Is the area part of, or is it within 0.5 mile of, a major* river or lake?
* river channel wider than 100 ft. or lake larger than 40 acres
____ Yes (field BigWater) ____ No
2. SURFACE WATER. During this season, does the area contain at least 0.1 acres of
surface water, either obscured by vegetation or not?
* See Figure B-I for guidance in estimating acreage categories
____ Yes (field AnyWater). Go to next question.
____ No. Skip to question #5.
3. OPEN WATER. During this season, how much open* water is present in the area?
• water deeper than 2 inches and mostly lacking vegetation ( cept submerged plants)
____ > 20 acres 4 it is mostly wider than 500 ft (field OpenBig)
____ I acre, , >1 acre but mostly narrower than 3 ft (field OpenSmall)
____ Other conditions (field OpenOther)
4. SPECIFIC AQUATIC CONDITIONS
Check all that apply during this season:
_____ > 0.1 acre of the surface water is still, i.e., usually flows at less than 1 ftls (field
Still Water)
____ The evaluated area can be assumed to contain fish (field Fish)
____ The evaluated area can be assumed to contain frogs, salamanders, andlor crayfish
(field Amphibs)
____ Water transparency in the deepest part of the area is (or would be, if depth is
shallow) sufficient to see an object 10 inches below the surface, the area is not
known to have problems with metal contamination (field Clear)
____ The evaluated area is highly enriched by direct fertilizer applications, water from
nearby feedlots, or other sources (field Enriched)
____ Most of the normally-flooded part of the area goes dry at least one year in five, or,
is subject to flooding from a river at least as often (field Drawdown)
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Figure B-I. Examples of dimensions for various wetland shapes and acreages.
SHAPE
(Not to Scale)
lOfti I
435 ft.
I acre:
(43,500 tñ
208 ft.
lOft. I
10 acres:
(435,000 fi 2 )
20 acres:
(870,000 f t 2)
40 acres:
(1.740.0000 It 2 )
]660ft.
_____ 993ft.
1319 ft.
80 ft.
160 ft.
320 ft.
I
5438 ft.
(—Imi)
5438 ft.
(-1mb
0.1 acre:
(4350 ft5
Sauare
066ft
Linear
4350 ft. (-0.8mi)
1
5438 ft (—Imi)
63
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5 BARE SOIL. Is there at least 0.1 acre of mudt, alkali flat, gravellsand bar, recently
tilled soil, andlor heavily grazed open (grassy, non-shrubby) areas during this season?
* includes soil that is continually saturated up to the suiface, or which was previously covered by water but
has become exposed to the air during this period
____ Yes (field Bare). Go to next question.
____ No. Skip to question #7.
6. LARGE MUDFLAT. Does the area at this season contain mud that has all these
features?:
o At least 1 acre in size
o Maximum dimension is greater than 100 ft
o Salt crust or salt stains are not apparent
o Not recessed within a wash or canal whose depth (relative to surrounding landscape)
is greater than half its width.
Yes (field MudBig) ____ No
7. TREES. Are there at least 3 treest:
* woody plants taller than 20 ft
____ in the evaluation area? (field Treeln).
____ within 1000 ft of the evaluation area? (field TreeNear). Go to #8.
____ neither of the above. Skip to #11.
8. TREE COVER. Check one or more responses below that describe the maximum
cumulative acreage of various conditions of tree cover in the evaluation area. Also include
areas within 300 ft:
____ >1 acre, dense t , and widett (field ForestDens)
____ >1 acre and open; or, dense but narrow (field ForestOpen)
____ 0.1-1 acre, denset (field WoodDens)
____ 0.1-1 acre, open (field WoodOpen)
____ <0.1 acre
* Dense the tree canopy, viewed from the ground during midsummer, appears at least 50% closed, as
averaged across an area that is at least as large as the acreage specified
Wide= the wooded area is wider than 300 ft (average)
9. BIG TREES. Are there at least three trees whose trunk diameter 20 ft above the ground
is >12 inches?
Yes (field TreesBig) ____ No
10. SNAGS. Are there at least three snags, or trees with dead limbs with diameter >5
inches?
Yes (field Snags) No
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11. SHRUBS. Is there at least 0.1 acre of shrubs*:
* woody plants 2-20 ft in height
____ in the evaluation area? (field Shrubln).
____ within 1000 ft of the wetland (including the wetland itself)? (field ShrubNear). Go
to #12.
Neither of the above. Skip to #13.
12. SHRUB SPECIES AND DENSITY. Check one or more responses below that describe
the maximum cumulative extent of various types and conditions of shrub cover in the
evaluation area. Also include areas within 300 ft.
Willow:
____ >1 acre, dense*, and wide** (field WwMuchDens)
____ >1 acre and open; or, dense but narrow (field WwMuchOpen)
____ 0 1-1 acre, dense* (field WwSomeDens)
____ 0.1-1 acre, open (field WwSomeOpen)
____ <0.1 acre; or larger area but height mostly <4 ft and openly spaced
Greasewood or other tall desert shrubs:
____ >1 acre, dense , and wide”’ (field GrMuchDens)
____ >1 acre and open; or, dense but narrow (field GrMuchOpen)
____ 0.1-1 acre, dense (field OrSomeDens)
____ 0.1-1 acre, open (field GrSomeOpen)
<0.1 acre
Russian olive, sumac, buffaloberry, wild rose, or others with fleshy fruit:
____ >1 acre, dense*, and wide”’ (field FrMuchDens)
____ >1 acre, open; or, dense but narrow (field FrMuchOpen)
____ 0.1-1 acre, dense (field FrSomeDens)
____ 0.1-1 acre, open (field FrSomeOpen)
____ <0.1 acre, or larger area but height mostly <4 ft
Tamarisk (salt cedar):
____ >1 acre, dense, and wide”’ (field TmMuchDeris)
____ >1 acre, open; or, dense but narrow (field TmMuchOpen)
____ 0.1-1 acre, dense (field TmSomeDens)
____ 0.1-1 acre, open (field TmSomeOpen)
____ <0.1 acre; or larger area but height mostly <4 ft
* Denser’ the shrub canopy, as viewed from a height of 100 ft during midsummer, oppears to be >50%
closed, as averaged across an area that is at least as large as the acreage specified
W:de= the shrub area is wider than 300 ft (average)
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13. HERBACEOUS VEGETATION. Is there at least 0.1 acre of herbaceous vegetation t :
* Nonwoody plants such as cattail, bulrush, sedges, grasses, and forbs
____ in the evaluation area? (field Herbln).
____ within 1000 ft? (field HerbNear). Go to #14.
____ Neither of the above. Skip to #15.
14. HERBACEOUS SPECIES. Check one or more responses below that describe the
maximum cumulative extent of various types and conditions of shrub cover in the
evaluation area. Also include areas within 300 ft.
Robust emergents (e.g., cattail, phragmites)
____ >1 acre, dense t , and widett (field RbMuchDens)
____ >1 acre, open; or dense but narrow (field RbMuchOpen)
____ 0.1-1 acre, dense (field RbSomeDens)
0.1-1 acre, open (field RbSomeOpen)
Other wettt emergents (e.g., bulrush, sedge)
_____ >1 acre, dense t , widett, and tallttt (field W’EMuchDens)
____ >1 acre, tall, open; or dense but narrow (field WEMuchOpen)
____ >1 acre, dense or open, and short (field WEMuchShrt)
____ 0.1-1 acre, tall, dense (field WESomeDens)
____ 0.1-1 acre, tall, open; or dense but narrow (field WESomeOpen)
____ 0.1-1 acre, dense or open, and short (field WESomeShrt)
Drier emergents (e.g., saltgrass, other grasses)
_____ >1 acre, dense t , widett, and tallttt (field DEMuchDens)
____ >1 acre, tall, open; or dense but narrow (field DEMuchOpen)
____ >1 acre, dense or open, and short (field DEMuchShrt)
____ 0.1-1 acre, tall, dense (field DESomeDens)
____ 0.1-1 acre, tall, open; or dense but narrow (field DESomeOpen)
____ 0.1-1 acre, dense or open, and short (field DESomeShrt)
* Dense ’ plants are o close together that the duff layer or soil beneath the plants is mostly obscured by
foliage, when looking down from just above the plant fops
‘ Wet= water is visible at or above the soil surface during most of the growing season
Wide= the shrub area is wider than 300 ft (average)
* * Talfr taller than Ift
66
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14. HERBACEOUS SPECIES (continued):
Broad-leaved Forbs (e.g., milkweed, thistle, alfalfa)
____ >1 acre (field ForbMuch)
0.1-1 acre (field ForbSome)
Aquatic plants (e.g., watercress, sago pondweed, duckweed)
____ >10 acres (field AqMuch)
0.1-10 acres (field AqSome)
15. SURROUNDTh G LAND COVER. Check one:
Within 0.5 mi of the wetland, > 60% of the land cover is:
____ Pasture, alfalfa, grain crops, row crops, other wetlands, grass lawns, and/or weed
fields (field SurAgwet)
____ Desert shrubs (e.g., sagebrush, shadscale, rabbitbrush)(field SurDesrt)
____ Pinyon-juniper (field SurPJ)
____ Oak scrub (e.g., Gambel oak, serviceberry, skunkbrush)(field SurOak)
Other, or none of the above comprise >60%
16. LOCAL LAND COVER. Check one:
Within 3 mi of the wetland, > 60% of the land cover is
____ Pasture, alfalfa, grain crops, row crops, other wetlands, grass lawns, andlor weed
fields (field LocAgWet)
____ Desert shrubs (e.g., sagebrush, shadscale, rabbitbrush)(field LocDesrt)
____ Pinyon-juniper (field LocPJ)
____ Oak scrub (e.g., Gambel oak, serviceberry, skunkbrush)(field LocOak)
____ Other, or none of the above comprise >60%
17. VISUAL SECLUSION
Check only one:
____ Both of the following:
(a) wetland is seldom visited by people on foot or boat (less than once weekly), (b)
there are no paved roads within 600 ft, or if there are, wetland is not visible from
the roads (field Seclusioni-!).
____ Either (a) or (b) above (field SeclusionM).
Other condition.
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18. PREDATION POTENTIAL
Check only one. The evaluation area:
____ is linear*, adjoins a heavily-traveled road (usual maximum of >1 car/minute), and/or
is in a high-density housing area (>1 house/5 acres)
(field PredHPot)
____ adjoins a less-traveled road, and/or is in an area with sparser housing density but is
closer than 1000 ft to a normally-occupied building (field PredMPot)
____ Other condition.
* at least 90% of the area being evaluated is within 25 ft of a canal, road, railroad tracks, or
other artificially linear feature.
19. GRAZED, BURNED, MOWED. Is the area mowed, burned, or grazed intensively (i.e.,
with clearly visible effects on vegetation) during this season?
____ Yes (field GrazBurnMo)
No
20. NESTING LOCATIONS
Check all that apply:
____ Semi-open structures (bridges, barns) suitable for nesting swallows are present
within 300 ft (field SwaliNest)
____ Platforms suitable for nesting geese are present in the wetland or along its perimeter
(field GooseNest)
____ Vertical, mostly bare dirt banks at least 5 ft high are present within 0.5 mi., of
potential use to nesting kingfishers, barn owls, and swallows (field Banks)
This concludes the initial evaluation. If you intend to infer the value of this wetland at
seasons or years other than the present one, you should go back over all your responses
and, on a new form, change the responses that would be different at that season/year.
Then, proceed to the analysis described by the User’s Manual.
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Appendix C. AREM short form
(A= acre, ft= feet, m= inches, mi miles)
1. Location: river/lake <0.5 mi?
_Big Water
2. Surface Water: >0.1 A?
_Any Water
[ skip to #5 if no]
3. Open Water> 2 inches deep:
_Openflig: >20 A and width mostly >500 ft
_OpenSmall: < I A, or >1 A but width <3 ft
_OpenOther: all other
4. Specific Aquatic Conditions:
StillWater: >0.1 A that flows at <1 ft/s
Fish
Amphibs: crayfish, frogs, salamanders
_Clear: 10 inch visibility and no metals problem
Enriched: feedlots etc.
Drawdown: most of wetland dries out or floods from river 1 year in 5
5. Bare Soil: >0.1 A of exposed mud, alkali flat, recently tilled, heavily grazed, etc. during
this season”
Mud
[ skip to 7 if no]
6. Large Mudflat: >1 A + width>100 ft + no salt + not recessed
_MudBig
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7. Trees: >2 trees...
_Treeln: in wetland
[ skip to 11 if no]
TreeNear: within 1000 ft
8. Tree Cover: tree acres within 300 ft + acres in wetland
_ForestDens: >1 A, closed canopy, and >300 ft wide
ForestOpen: >1 A, open, and >300 ft wide
_WoodDens: 0.1-1.0 A closed, or larger but narrower than 300 ft
WoodOpen: 0.1-1.0 A open, or larger but narrower than 300 ft
9. Big Trees: >2 trees, >12 inch diameter within 300 ft or in?
TreesBig
10.Snags >2 snags (>5 inch diameter), within 300 ft or in wetland?
_Snags
1 l.Shrubs: >0.1 acre of shrubs (2-20 ft height)...
_Shrubln: in wetland _SbrubNear: within 1000 ft
[ skip to 13 if neither]
GrMuchDens:
_GrMuchOpen:
GrSomeDens:
_GrSomeOpen:
FrMuchDens:
_FrMuchOpen:
FrSomeDens:
_FrSomeOpen:
TmMuchDens:
_TmMuchOpen:
TmSomeDens:
_TmSomeOpen:
12.Shrub Species and Density:
_WwMuchDens: willow >1
_WwMuchOpen: willow >1
WwSomeDens. willow 0.1
WwSomeOpen: willow 0.1
shrub acres within 300 ft + in wetland:
A, dense and wide
A, open, or dense but narrow
- 1.0 A, dense
- 1.0 A, open
greasewood etc. >1 A, dense and wide
greasewood etc. >1 A, open, or dense and narrow
greasewood etc. 0.1 - 1.0 A, dense
greasewood etc. >1 A, open
Russian olive etc. >1 A, closed
A, open or clumped
- 1.0 A, closed
- 1.0 A, open or clumped
Russian
Russian
Russian
olive etc. >1
olive etc. 0.1
olive etc. 0.1
tamarisk >1 A, closed
tamarisk >1 A, open or clumped
tamarisk 0.1 - 1.0 A, closed
tamarisk 0.1 - 1.0 A, open or clumped
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13. Herbaceous Vegetation. >0.1 A of herbaceous
Herbln: in wetland HerbNear: within 1000 ft
14. Herbaceous Species and Density: herbaceous acres within 300 ft + in wetland:
_RbMuchDens: robust cattail etc. >1 A, dense and wide
_RbMuchOpen: robust cattail etc. >1 A, open, or dense but narrow
RbSomeDens: robust cattail etc. 0.1 - 1.0 A, dense
_RbSomeOpen: robust cattail etc. 0.1 - 1.0 A, open
_WEMucbDens: wet emergents (sedge, bulrush) >1 A, dense, wide, and >1 ft tall
_WEMuchOpen: wet emergents (sedge, bulrush) >1 A, open tall or dense but narrow
_WEMuchShrt. wet emergents (sedge, bulrush) >1 A, short (<1 ft), dense or open
_WESomeDens: wet emergents (sedge, bulrush) 0.1 - 1.0 A, dense, >1 ft tall
_WESomeOpen: wet emergents (sedge, bulrush) 0.1 - 1.0 A, open tall
_WESomeShrt: wet emergents (sedge, bulrush) 0.1 - 1.0 A, short < in, dense or open
_DEMuchDens: dry emergents (grasses etc.) >1 A, dense, wide, and tail (>1 ft)
DEMuchOpen: dry emergents (grasses etc.) >1 A, open, tall, or dense but narrow
_DEMuchShrt: dry emergents (grasses etc.) >1 A, short (<1 ft), dense or open
_DESomeDens: dry emergents (grasses etc.) 0.1 - 1.0 A, dense, tall (> 1 ft)
_DESomeOpen: dry emergents (grasses etc.) 0.1 - 1.0 A, open, tall, or dense but narrow
_DESomeShrt: dry emergents (grasses etc.) >1 A, short, open or dense
_ForbMuch: alfalfa, milkweed, etc. > I A
ForbSome: alfalfa, milkweed, etc. 0.1 - 1.0 A
_AqMuch. watercress, sago, duckweed etc. > I A
_AqSome watercress, sago, duckweed etc. 0.1 - 1 .0 A
15. Surrounding Land Cover: within 0.5 mi...
_SurAgWet. >60% pasture, alfalfa, grain, row crops, other wetlands, weeds, grass
_SurDesrt. >60% sagebrush, shadscale, rabbitbrush
SurPJ: >60% pinyon-juniper
SurOak: >60% oak, serviceberry, skunkbrush
_Other, or none cf above add to >60%
16. Local Land Cover: within 3.0 mi of wetland...
_LocAgWet: >60% pasture, alfalfa, grain, row crops, other wetlands, weeds, grass
_LocDesrt: >60% sagebrush, shadscale, rabbitbrush
_LocPJ: >60% pinyon-juniper
LocOak: >60% oak, serviceberry, skunkbrush
_Other, or none of above add to >60%
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17. Visual Seclusion: check ONLY ONE:
_Seclusionl-I: no road within 600 ft or not visible if road present, and <1 visit/week on
foot
_SeclusionM: EITHER of above
other
18. Predation Potential: check ONLY ONE:
_PredHPot: major road, urban, or linear
_PredMPot: other road or building within 1000 ft
other
19. Burned, mowed, or intensively grazed during this season?
GrazBurnMo
20. Nesting Locations:
_SwallNest: swallow sites -- barns, bridges within 300 ft
_GooseNest: goose platforms, in wetland or on perimeter
_Banks: within 0.5 mi, height >5 ft. vertical
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