MARINE WETLAND BOUNDARY DEFINITION: EVALUATION OF METHODOLOGY
by
H. Peter Eilers Alan Taylor William Sanville
ENVIRONMENTAL RESEARCH LABORATORY OFFICE OF RESEARCH AND DEVELOPMENT U.S. ENVIRONMENTAL PROTECTION AGENCY CORVALLIS, OREGON 97333
June 1981 MARILYN POTTS MAN LIBRARY RATFIELD M4R1NE SCIENCE CENTER OLLN UATE UNIVERSITY WNW. OREGON 97365 MARINE WETLAND BOUNDARY DEFINITION: EVALUATION OF METHODOLOGY
H. Peter Eilers Alan Taylor William Sanville
CERL - 054 June 1981 ABSTRACT
With legislation to protect wetlands and current pressures to convert them to other uses, it is often necessary to accurately determine a wetland- upland boundary. We investigated 6 methods to establish such a boundary based on vegetation. Each method was applied to a common data set obtained from 295 quadrats along 22 transects between marsh and upland in 13 Oregon and
Washington intertidal wetlands. The multiple occurrence, joint occurrence, and five percent methods required plant species to be classified as wetland, upland, and non-indicator; cluster and similarity methods required no initial classification. Close agreement between wetland-upland boundaries determined by the 6 methods suggests that preclassification of plants and collection of plant cover data may not be necessary to arrive at a defensible boundary determination. Examples of each method and lists of indicator plant species for coastal California, Oregon, and Washington are provided. TABLE OF CONTENTS
Abstract
Figures
Tables
Acknowledgements
Introduction
Methods for Boundary Determination Indicator Species Five Percent Joint Occurrence Multiple Occurrence Cluster Similarity ISJ and ISE
Lists of Indicator Species
Comparison of Methods
Discussion and Recommendations
Literature Cited
Appendices
A. Examples of vegetation methods to determine wetland boundaries. .
B. Salt marsh, non-indicator, and upland plant species of California, Oregon, and Washington
C. Upper limit of marsh and lower limit of transition zone determined by 6 methods applied to 22 transects
D. Sample field data sheet
Computer software available at the U S. Environmental Protection Agency, Corvallis, Oregon FIGURES
Figure 1. Flow diagram to facilitate choice of vegetation method to determine upper limit of wetland
TABLES
Table 1. Lower transition zone limit (LTZ) and upper limit of marsh (ULM) as determined by 6 methods applied to 22 transects from Frenkel et al. (1978). Limits expressed as distance (M) along transect where distance increases from marsh to upland ACKNOWLEDGEMENTS
The refinement of indicator species lists was possible through the effort of numerous scholars: Michael G. Barbour, University of California, Davis;
Lawrence C. Bliss, University of Washington; Kenton L. Chambers, Oregon State
University; Wayne R. Ferren, University of California, Santa Barbara; Keith
Macdonald, Woodward-Clyde Consultants; Robert Ornduff, University of
California, Berkeley; David H. Wagner, University of Oregon; and Joy Zedler,
San Diego State University. We greatly appreciate their time and effort.
We also thank Theodore Boss for comments and criticism, and Jo Oshiro for help with computer graphics. INTRODUCTION
Two decades of intensive research following the suggestions of Odum
(1961) and the work of Teal (1962) have firmly established values attributed to undisturbed coastal salt marshes. These intertidal wetlands were noted for high macrophyte production and for export of energy-rich organic detritus and dissolved organic carbon to estuarine waters. They serve as juvenile fish and wildlife habitat, as buffer to erosion of sediment, and have potential for water purification.
Accompanying the increase in awareness of salt marsh values and poten- tials, however, has been the rapid conversion of coastal marsh to urban, suburban, and agricultural uses through diking, filling, and construction activities (Darnell 1976). Recent federal legislation is designed to retard this rapid conversion and thereby protect what now remains of the nation s wetland resources. Most notable are the Federal Water Pollution Control Act
Amendments of 1972 and 1977 (Water Act) which, in Section 404 provide for a permit review process to regulate dredge and fill projects.
To fully implement Section 404 requires that those involved in the review process be equipped to: (1) identify wetland; and (2) determine boundaries, especially that between the marsh and upland. Yet, while the identification of wetlands may be accomplished by noting the presence of standing water and plants adapted to growth in saturated soil conditions, the determination of the upper limit of wetland is difficult. Instead of exhibiting a sharp break, the characteristics of wetland are more likely to gradually shift to those of upland along a transition. In salt marsh, the influence of the tide gradually
1 diminishes with increasing surface elevation, soils become better drained, and
vegetation gradually changes to that of non-wetland. An ecotone with inter- digitation of marsh and upland plant species occurs between the two systems.
To better understand the nature of the marsh-upland ecotone and to develop methodologies to delineate a defensible intertidal marsh boundary, the
U.S. Environmental Protection Agency in conjunction with the U.S. Army Corps of Engineers began a major research effort in 1976. Following the completion of two pilot projects (Frenkel and Eilers 1976, Jefferson 1976), five groups were funded to investigate transition zones and upper limits. Individually they covered salt marshes along the coasts of California (Harvey et al. 1978);
Oregon and Washington (Frenkel et al. 1978); Alaska (Batten et al. 1978);
Delaware, Maryland, Virginia, and North Carolina (Boon et al. 1978); and freshwater marsh along the shores of the Lake Superior, Lake Michigan, and
Lake Huron (Jefferson 1978). The reports provide an excellent floristic description of marsh-upland ecotones and they identify major approaches to boundary determination based on vegetation.
The purpose of this report is to: (1) evaluate the methods applied by these researchers; (2) present alternative methods; (3) recommend the best approach to wetland boundary delineation based on vegetation; and (4) provide appropriate plant lists and computer software to apply methodology to Pacific
Coast intertidal marshes. We consider the methods presented as applicable to wetland-upland boundary determination in general, not to marine wetlands alone. We acknowledge, however, that vegetation should not be the only criteria considered. The best approach will incorporate vegetation, soils, and hydrology. The methods provided here are a first approximation. As our knowledge of physical factors across the wetland-upland ecotone is increased,
2 methods will be enlarged and refined. At the moment we must rely primarily on
a vegetation approach.
METHODS FOR BOUNDARY DETERMINATION
Methods to determine wetland boundaries presented by these researchers
listed above vary from those with an emphasis on indicator species and little
quantitative data to those requiring classification of all plant species
recorded and intensive quantitative treatment. We will consider the less
quantitative approach favored by Batten et al. (1978) and Jefferson (1978),
then the more quantitative methods of other researchers. To this we will add
other quantitative approaches.
Indicator Species
Batten et al. (1978) investigated Alaskan coastal salt marshes and
collected information on plant species percent cover from quadrats located
along the elevation gradient between marsh and upland. Based on their data
and knowledge of plant species habitat preference, they developed lists of
indicator species that signal the shift from salt marsh to terrestrial upland
or freshwater marsh. The lower limit of the transition zone (LTZ) was estab-
lished at a point where species abundant in upland or freshwater wetland first
become "abundant" in the marsh and the upper limit of marsh (ULM) was reached when all the species characteristic of the vegetation type bordering the marsh
are present in "appropriate amounts." No definition of "abundant" or "appro-
priate amounts" is given and thus the placement of a boundary in the field
following this approach would be highly subjective and ill-suited to cases
involving close legal scrutiny.
3 Jefferson (1978) likewise developed indicator plant species lists from
the study of freshwater marshes along the shores of the Great Lakes. Her
treatment of the marsh-upland ecotone is exhaustive, yet little attention is
given to boundary delineation. She states that "by using the community
descriptions and lists of dominant, prevalent, and differential species,
detection of the ecotone and its limits should be facilitated." As with
Batten et al. (1978), this approach requires much subjective judgment and may
be expected to yield only an approximate boundary determination.
Five Percent
The initial approach of Boon et al. (1978) and Harvey et al. (1978) was
similar to those above but carried further. Following acquisition of plant
cover estimates from transects along the transition from marsh to upland, a
"five percent" method was utilied such that the upper limit of the transition zone was defined as the point "at which the amount of ground coverage by upland plants is at least five percent and is contiguous with the upland proper" (Boon et al. (1978). The lower transition limit is defined similarly with coverage of upland plants less than five percent. Both research groups classified plant species as to marsh, transition, upland (Boon et al. 1978); or marsh, upland, non-indicator (Harvey et al. 1978) and present results graphically. Harvey et al. (1978) applied the following procedures: (1) when a five percent cover value of the appropriate cover type, either marsh or upland, occurred in a quadrat and no trace occurred in the adjacent, more distal quadrat, the quadrat with five percent cover was marked as the transi- tion; (2) if the adjacent quadrat distal to the five percent cover plot had a trace of the vegetation type in question, the adjacent quadrat was marked as the transition limit; (3) if two plots in sequence had a trace of either type
4
vegetation, the more distal quadrat was marked as the limit; (4) if the five
percent cover level fell between two quadrats, the limit was located by inter-
polation; (5) if no overlap of upland and marsh species occurred either due to
bare ground and/or cover by non-indicator species, a point midway between
quadrats in which each type was represented was chosen. Appendices A and C
contain examples of this and other methods described.
Joint Occurrence
After applying the five percent method, Harvey et al. (1978) sought a
"quicker, easier, but equally accurate approach." Their choice was a modifi-
cation of Fager s (1957) measure of joint occurrence which takes the form
I – 2J MU nM + nU
where, for any single quadrat, J is the number of joint occurrences of marsh
and upland species, nM is the number of marsh species, and nU is the number of
upland species. Non-indicator species are disregarded.
Plotting I mu for quadrats along a transect shows a series of zeros for
pure wetland followed by a rise to a peak in the transition and a fall to zero
again in pure upland. In practice, however, Harvey et al. (1978) found it
difficult to interpret such a graph when natural or man-made "patchiness" was
present. This problem was largely eliminated by computing and plotting a
standardized cumulative index (SCI) for each quadrat
MU
SCI. = I and SCI = 1.0 I 1 i=1 I i i=1 where n is the total number of quadrats. After plotting index values, Harvey
et al. (1978) identified the lower and upper limits of the transition as 0.5 m
above the rise of the data line from the abscissa and 0.5 m above SCI = 1.0,
respectively (given 1 m distance between sample quadrats or one-half the
distance between quadrats if greater than 1 m). Close agreement between the
SCI and the five percent method transition boundaries was observed.
Multiple Occurrence
Frenkel et al. (1978) applied an expanded plant classification with four
categories--low marsh, high marsh, non-indicator, and upland--and computed a
score for quadrat data collected along transects between marsh and upland.
The "multiple occurrence method" (MOM) score (M) required the assignment of a
weighting coefficient:
Weighting Species Type Coefficient
Low marsh 2 High marsh 1 Upland -2 Non-Indicator 0
The quadrat score was calculated as
n M = F W.C., i=1 1 1 where W. is the weighting coefficient for species, i, C. is cover value for
species i, and n is total number of species in the quadrat sample. Cover
values were after the classes of Daubenmire (1959): 0-5% = 1, 5-25% = 2,
25-50% = 3, 50-75% = 4, 75-95% = 5, 95-100% = 6. Species present but with
negligible cover were disregarded.
6 Positive M values were interpreted as marsh, the upper limit of marsh was defined as M = 0, and M < 0 denoted upland. However, further interpretation was necessary because M values did not always descend to a single M = 0 and thereafter remain negative. Two additional cases were noted. One contained more than one M = 0 in succession, and the other with M scores alternating above and below zero. In both cases, the portion of the transect between first and last M = 0 were considered as the transition zone and the upper limit of marsh was placed midway through this zone. In our interpretation of this method we have assigned the upper limit of the transition zone as the
ULM, a shift agreed to by Frenkel (personal communication).
Cluster
We reasoned that if marsh and upland are floristically different, cluster analysis (Boesch 1977) of data collected from quadrats along transects between the two systems might be used to identify wetland limits. Such an approach would have the advantage of not requiring preclassification of plant species into "marsh," "upland," "non-indicator," and would provide a more objective instrument. We chose the Bray-Curtis dissimilarity measure (Clifford and
Stephenson, 1975),
n x.. - x. i=1 ij ik Djk – n (x x ) i=1 lji ik • where x is cover value for species i in quadrats i and k, and n is the total number of species. A "flexible" fusion strategy with Beta = -0.25 (Boesch,
1977) was utilized. The end product is a dendrogram showing quadrat clusters
7 which form at decreasing levels of dissimilarity. We identified the upland cluster as that containing the highest numbered quadrats (when quadrats were numbered from wetland to upland). The upper limit of marsh was interpreted as being half the distance (on the transect) between the lowest numbered member of the upland cluster and the next lowest group of quadrats.
Similarity ISJ and ISE
By computing the similarity in species content of adjacent quadrat samples along a transect and graphing these values, we expected to observe a decrease in similarity at the marsh-upland border. In this case, we chose two measures. One was Jaccard s index (Mueller-Dombois and Ellenburg, 1974) which requies binary data (presence-absence):
ISJ — c x 100, a + b + c where c is the number of species common to two quadrats, a is the number of species unique to the first quadrat, and b is the number of species unique to the second quadrat. The other was Ellenberg s (1956 in Mueller-Dombois and
Ellenberg, 1974) modification of Jaccard s index which accepts species quantities:
Mc:2 ISE — x 100 Ma + Mb + Mc:2 •
Here, Mc is the sum of cover values of species common to both quadrats, Ma is the sum of the cover values of the species restricted to the first quadrat, and Mb is the corresponding sum for species restricted to a second quadrat.
Species noted as present but with negligible cover where assigned a value of
0.25.
8 •
LISTS OF INDICATOR SPECIES
Lists of indicator species for California, Oregon, and Washington coastal
marshes are found in Appendix B. They represent a consensus of EPA
researchers and local authorities. We sent tentative plant lists to recog-
nized authorities in botany and wetland ecology for review (see Acknowledge-
ments) and made numerous adjustments. The lists are still evolving, but they
provide a good approximation in present form. In addition, the U.S. Fish and
Wildlife Service is now compiling nationwide lists of wetland plant species
through the National Wetlands Inventory program.
COMPARISON OF METHODS
To compare the results obtained by the quantitative methods presented above (excluding the indicator species method), we applied each to a common data set. We chose 22 transects (12%) at random from the 190 sampled by
Frenkel et al. (1978). The data were collected from 50 x 50 cm quadrats.
Transects were located with the foot well into wetland, the head well into upland, and the orientation parallel to the elevation gradient. Plant species in each quadrat were recorded as to cover class (Daubenmire 1959) except that those with negligible cover were assigned "present" status only. As we calcu- lated LTZ and ULM by each method, we kept careful note of time involved and ease of application. We concentrated our efforts on comparison of ULM identification because of its direct relationship to jurisdictional questions.
We considered the ULM to be synonmous with the upper limit of the transition zone and thus the true limit of wetland.
Table 1 and Appendix C reveal close agreement in LTZ and ULM positions obtained by the six methods. ULM location agreed within 1.0 m on 9 transects
(45%) and within 2.5 m on 13 transects (65%). ULM for two transects (0808 and
9 1606) was not identified by all methods, suggesting that the transects did not extend far enough to include marsh and upland quadrats. The range of ULM estimates was greatest for transect 1703 (25.5 m), but cluster and similarity plots for this transect show discontinuities at positions in agreement with other methods that could be interpreted as ULM. In general, methods with species classification built in (five percent, joint occurrence, and multiple occurrence) exhibit low intragroup variability, as do those without species classification.
All methods, with the exception of cluster, involve simple calculations that can be done by hand. Cluster requires a computer. We found little time difference involved in applying each method given basic field data and plant classifications, so that the choice of method should be attuned to time avail- able for field work and the availability of a valid list of indicator species.
Perhaps the most important result of this comparative treatment is that use of species presence-absence yields ULM positions identical or nearly identical to those requiring species percent cover. Thus, the extended field effort required to obtain plant cover is not necessary and the greatest return for time spent might be expected from utilizing species occurrence only.
DISCUSSION AND RECOMMENDATIONS
The above methods fall into two basic groups. The first comprises five percent, joint occurrence, and multiple occurrence and is characterized by reliance on pre-established lists of wetland and upland indicator species. A consensus of ecological thought as it pertains to plant species is built into these methods. The field researcher must have botanical expertise but, theor- etically, a valid ULM determination could be made without in-depth knowledge
10 of wetland ecology. We caution, however, that results from all methods
reviewed must remain valid under evaluation by wetland specialists.
The second group--cluster, similarity ISJ and similarity ISE--does not
require preclassification of plant species. Instead, it is assumed that
species are distributed along transects in such a way as to form groups char-
acteristic of wetland, transition, and upland, and that these groups can be
identified objectively. We have demonstrated that this is a viable approach
and that results are comparable to those obtained by preclassification
methods. We consider cluster and similarity methods to be very sophisticated
and caution should be given to inexperienced users. Transect 1703 (Table 1,
Appendix C) provides an illustration of this point. A ULM of 31.5 m is
suggested by strict adherence to procedure, but it is likely that a position
closer to 7.0 m as indicated by five percent, joint occurrence, and multiple
occurrence would have been the selected ULM given on-site review by trained
personnel. All six methods should be viewed as tools with strong indicator
value and whether classification of plant species is involved or not, the
final boundary placement should involve the judgment of trained personnel.
We recommend the general vegetation approach to wetland boundary identi-
fication outlined in Figure 1. If classification of plants is available, the
joint occurrence method is the best approach because it reduces field time and yields results close to the five percent and multiple occurrence methods. If
accepted plant classifications are unavailable, as is the present case for
most freshwater wetlands, the cluster method or similarity ISJ applied to
presence-absence data provide defensible boundaries and have the added
advantage of helping to establish a classification. Cluster and similarity
methods are very sensitive to zonal vegetation patterns but, as stated above,
it is the task of trained personnel to interpret results to obtain the ULM.
11 If the requisite information to apply the joint occurrence method is avail- able, it is still advisable to employ either cluster or similarity ISJ or both to support the initial decision.
Even though a vegetation approach to ULM determination is likely to be satisfactory, because plant distributions reflect environmental conditions, our present knowledge of physical factors, such as soils and hydrological regimes, across the transition is very limited. We assume that certain plants indicate physical conditions of wetland, transition, and upland, but we do not know tolerance limits for species so classified. Research underway at the
U.S. Environmental Protection Agency and U.S. Army Corps of Engineers is designed to provide a more holistic treatment of the wetland boundary problem.
Physical factors between wetland and upland are being intensively monitored at numerous wetland sites; greenhouse studies are testing species tolerance to various field conditions, such as inundation and soil saturation, and methods are being devised which incorporate both vegetation and physical factors to identify wetland limits. In the near future, our ability to establish bound- aries will be enhanced beyond the tenuous reliance on vegetation indicators alone.
12 LITERATURE CITED
Batten, A. R., S. Murphy, and D. F. Murray. 1978. Definition of Alaskan
wetlands by floristic criteria. Report to the U.S. Environmental Protec-
tion Agency, Corvallis, Oregon.
Boesch, D. F. 1977. Application of numerical classification in ecological
investigations of water pollution. Special Scientific Report No. 77,
Virginia Institute of Marine Science.
Boon, J. D., D. M. Ware, and G. M. Silberhorn. 1978. Survey of vegetation
and elevational relationships within coastal marsh transition zones in
the central Atlantic coastal region. Report to the U.S. Environmental
Protection Agency, Corvallis, Oregon.
Clifford, H. T. and W. Stephenson. 1975. An introduction to numerical class-
ification. Academic Press, New York.
Darnell, R. M. 1976. Impacts of construction activities in wetlands of the
United States. U.S. EPA, Corvallis, Oregon. Publ. No. EPA-600/3-76-045.
Daubenmire, R. F. 1959. Canopy coverage method of vegetation analysis.
Northwest Sci. 33:43-64.
Fager, E. W. 1957. Determination and analysis of recurrent groups. Ecology
38:586-595.
Frenkel, R. E. and H. P. Eilers. 1976. Tidal datums and characteristics of
the upper limits of coastal marshes in selected Oregon estuaries. Report
to the U.S. Environmental Protection Agency, Corvallis, Oregon.
13 Frenkel, R. E., T. Boss, and S. R. Schuller. 1978. Transition zone vegeta-
tion between intertidal marsh and upland in Oregon and Washington.
Report to the U.S. Environmental Protection Agency, Corvallis, Oregon.
Harvey, H. T., M. J. Kutilek and K. M. DiVittorio. 1978. Determination of
transition zone limits in coastal California wetlands. Report to the
U.S. Environmental Protection Agency, Corvallis, Oregon.
Hitchcock, A. S. 1950. Manual of the grasses of the United States. U.S.
Department of Agriculture Misc. Publ. No. 200.
Hitchcock, C. L. and A. Cronquist. 1973. Flora of the Pacific Northwest.
University of Washington Press, Seattle.
Jefferson, C. A. 1976. Relationship of vegetation and elevation at upper and
lower limits of the transition zone between wetland and upland in
Oregon s estuaries. Report to the U.S. Environmental Protection Agency,
Corvallis, Oregon.
Jefferson, C. A. 1978. Vegetative delineation of the upper limit of coastal
wetlands of the upper Great Lakes. Report to the U.S. Environmental
Protection Agency, Corvallis, Oregon.
Munz, P. A. and D. D. Keck. 1963. A California flora with supplement, 1968.
University of California Press, Berkeley.
Odum, E. P. 1961. The role of tidal marshes in estuarine production. The
Conservationist 15:12-13.
Teal, J. M. 1962. Energy flow in the salt marsh ecosystem of Georgia.
Ecology 43:614-624.
14 Is classification of plant species by wetland, non- indicator, upland available?
Yes No
Does time permit collection Does time permit collection of percent cover? of percent cover?
Yes No Yes No
Use five percent Use joint Is computer Is computer method or occurrence available? available? multiple method occurrence Yes No Yes No method
Use Use cluster cluster method method
Use Use similarity similarity ISE ISJ method method
Figure 1. Flow diagram to facilitate choice of vegetation method to determine upper limit of wetland.
15 •
Table 1. Lower transition zone limit (LIZ) and upper limit of marsh (ULM) as determined by 6 methods applied to 22 transects from Frenkel et al. (1978). Limits expressed as distance (m) along transect where distance increases from marsh to upland.
Joint Multiple Similarity Similarity Five Percent Occurrence Occurrence Cluster ISJ ISE Transect ULM ULM ULM Number Location LTZ ULM LTZ ULM LTZ ULM LTZ ULM LTZ ULM LTZ ULM Mean S.D. Range OREGON
0105 Coquille Estuary 11.0 14.5 9.0 14.5 11.5 13.0 9.0 14.5 11.5 15.5 12.5 14.5 14.4 0.8 2.5 0208 Coos Bay 16.5 19.5 16.5 21.5 21.0 19.5 21.5 --- 21.5 20.8 1.0 2.0 0301 Alsea Bay 9.0 15.5 --- 15.5 10.0 15.0 9.0 15.5 9.0 15.5 9.0 15.5 15.4 0.2 0.5 0310 Alsea Bay 13.0 13.5 10.0 12.0 9.0 13.5 7.0 13.5 9.0 13.5 13.2 0.6 1.5 0402 Yaquina Bay 19.5 19.5 18.5 13.5 19.5 13.5 19.5 ,13.5 19.5 19.3 0.4 1.0 0407 Yaquina Bay . 4.5 19.5 4.5 19.5 7.5 19.5 1.5 19.5 10.5 19.5 10.5 19.5 19.5 0.0 0.0 0704 Nehalem Bay 1.0 11.0 1.0 11.5 8.0 7.0 15.5 --- 9.0 9.0 10.7 2.7 7.5 0706 Nehalem Bay 10.5 13.0 10.5 13.5 10.5 11.1 10.5 15.5 7.0 16.5 12.5 16.5 14.4 2.2 5.4 0710 Nehalem Bay 16.0 --- 15.5 15.0 --- 15.5 15.5 --- 15.5 15.5 0.3 1.0
WASHINGTON
0804 Willapa Bay 14.5 15.5 14.5 16.5 11.0 15.0 9.0 15.5 9.0 15.5 9.0 15.5 15.6 0.5 1.5 0808 Willapa Bay 8.0 5.0 15.5 0809 Willapa Bay 15.0 22.5 22.5 15.0 22.0 19.0 22.5 20.5 22.5 19.0 22.5 22.4 0.2 0.5 0910 Willapa Bay 84.5 87.5 87.5 63.5 87.5 --- 87.5 65.0 87.5 65.0 87.5 87.5 0.0 0.0 1001 Willapa Bay 256.0 265.0 265.0 248.0 259.0 259.0 --- 249.0 --- 249.0 257.7 7.2 16.0 1103 Grays Harbor 105.5 146.0 105.5 147.5 117.5 129.5 117.5 147.5 117.5 147.5 98.0 147.5 144.3 7.3 18.0 1201 Grays Harbor 18.5 19.5 19.5 --- 19.0 17.0 19.5 17.0 19.5 17.0 19.5 19.4 0.2 0.5 1606 Thorndyke Bay ------10.5 10.5 --- 1610 Thorndyke Bay 6.0 3.5 7.5 3.0 10.5 10.5 --- 10.5 8.0 3.1 7.5 1611 Thorndyke Bay 9.0 12.5 12.5 6.0 12.0 10.5 4.5 10.5 4.5 10.5 11.4 1.0 2.0 1612 Thorndyke Bay 21.5 21.5 1.0 20.0 12.0 23.5 12.0 12.0 23.5 20.3 4.3 11.5 1703 Snohomish Estuary 7.5 7.5 6.0 31.5 31.5 --- 31.5 19.3 13.4 25.5 1802 Oak Bay 26.0 25.5 25.5 25.5 10.5 25.5 19.5 25.5 25.6 0.2 0.5 Examples of Vegetation Methods to Determine Wetland Boundaries FIVE PERCENT
Field data collection CALCULATION FOR QUADRAT 5: TRANSECT SUMMARY: Quadrats at regular intervals (i.e., 1 m) along transects between marsh and upland Species %Cover Classification Quadrat %Marsh %Upland Record all plants occurring in quadrats and A SU marsh 1 —100 0 assign percent cover (nearest 5%) to each B 15 non-indicator 2 100 0 species in each quadrat C 20 marsh 3 100 0 D 5 marsh 4 70 5 E 10 non-indicator 5 65 10 F 10 marsh 6 30 35 Classify plants recorded as to G 10 upland 7 20 65 Marsh species 8 5 80 Non-indicator marsh % cover = 65 9 0 95 Upland species upland % cover = 10 10 0 95 11 0 100 12 0 100
Compute total percent cover of marsh species and upland species in each quadrat IN ULPT e
LTZ ■ 4 Plot totals for marsh and upland species against • distance along transect (in bar graph form)
Locate LTZ and ULM « - LTZ is point at which upland species = 5% i ULM is point at which wetland species = 5%
See text for rules. OUADRAT JOINT OCCURRENCE
Field data collection CALCULATION FOR QUADRAT 5: TRANSECT SUMMARY: Quadrats at regular intervals (i.e., 1 m) along transects between marsh and upland Species Classification Quadrat I MU SI SCI Record all plants occurring in quadrats A marsh 1 0 0 0 B non-indicator 2 0 0 0 C marsh 3 0 0 0 marsh 4 .20 .13 .13 Classification of plants recorded as to E non-indicator 5 .40 .27 .40 Marsh species F marsh 6 .20 .13 .53 Non-indicator 0 upland 7 .10 .07 .60 Upland species 8 .60 .40 1.00 9 0 0 1.00 I !mu . 2J . 2 . .40 10 0 0 1.00 nM + nU. 11 0 0 1.00 Compute joint occurrence score for each quadrat 12 0 0 1.00
Compute Standardized Cumulative Index for quadrats
I Plot Standardized Cumulative Index against distance 9.0 along transect 9.1
0.0
Locate LTZ and ULM u LTZ is one half quadrat interval on transect m0.1 above (toward upland) quadrat where SCI initially 0 ULM is one half quadrat interval on transect 9.2 above (toward upland) quadrat where SCI initially = 1.00 6.1 • 118 1 9 4 11 0 7 11191911121S QUADRAT MULTIPLE OCCURRENCE
Field data collection CALCULATION FOR QUADRAT 5: Quadrats at regular intervals (i.e., 1 m) TRANSECT SUMMARY: along transects between marsh and upland Cover Record all plants occurring in quadrats and Species Class Classification Weight Quadrat M assign cover class value to each species in A 3 marsh (low) each quadrat B 2 non-indicator 0 1 30 C 2 marsh (low) 2 2 21 0 1 marsh (low) 2 3 14 E 2 non-indicator 0 4 8 Classify plants recorded as to F 2 marsh (high) 1 5 10 Marsh species 2 upland -2 6 0 Non-indicator 7 -1 Upland species 8 -3 M = WiCi 9 0 I 1=I 10 -8 11 -10 Compute M score for each quadrat = (3x2)+(2x0)+(2x2)+(1x2)+(2x0)+(2x1)+(2x(-2)) 12 -12
= 10
Plot M score against distance along transect
Locate LIZ and ULM LTZ is first M = 0 (if ) 0 1 M = 0) on transect from wetland to upland ULM is last or only M = 0 on transect from wetland to upland
Frenkel et al (1978) used cover class, but we recommend using percent cover rather than class.
We recommend assignment of a weight of 2 to all plants classified as marsh. CLUSTER
Field data collection Quadrats at regular intervals (i.e., 1 m) along transects between marsh and upland Record all plants occurring in quadrats and assign percent cover (nearest 5%) to each species in each quadrat
t
Create computer data file for each transect and rut) program Cluster
Locate LTZ and ULM LTZ is break between marsh and transition clusters A ULM is break between transition and upland WETLAND UPLAND cluster
Collection of cover is optional Available at EPA Corvallis SIMILARITY ISJ
Field data collection CLASSIFICATION FOR QUADRATS 5 AND 6: TRANSECT SUMMARY: Quadrats at regular intervals (i.e., 1 m) along transects between marsh and upland Species Quadrat 5 Quadrat 6 Quadrats ISJ Record all plant species occurring in each A x x —67 quadrat 8 x x 2 3 50 I C x x 3 4 37 D x x 4 5 30 E x x 5 6 63 F Compute similarity coefficient ISJ for all x x 6 7 80 G adjacent quadrat pairs along transect x 7 8 60 H x x 8 9 66 I 1 x 9 10 88 J x 10 11 40 K x Plot similarity values against distance along 11 12 75 transect (values located at mid-point between quadrats) ISJ = c x 100 . 7 x 100 iTETT 34-14-/
. Locate LTZ and ULM Tr x 100 = 63 LTZ is point of low similarity on transect below ULM ULM is point of low similarity on transect NCO closest to upland 00.0
90.•
20.0
ILO
1 2 4 SO 7 00 I II 12 OUADRAT SIMILARITY ISE
Field data collection CALCULATION FOR QUADRATS 5 AND 6: Quadrats at regular intervals (i.e., 1 m) along transects between marsh and upland Species Quadrat 5 Quadrat 6 Record all plant species occurring in quadrats A .25 5.00 ISE = Mc:2 x 100 Ma+Mb+Mc:2 and assign percent cover (nearest 5%) to each B 5.00 5.00 species in each quadrat C 35.00 35.0 _ 191:2 D 5.00 .25 25+.25+191:2 x 100 E 5.00 .25 F 35.00 15.00 95.5 Compute similarity coefficient ISE for all adjacent G 5.00 x 100 = 79 120.75 quadrat pairs along transect H 5.00 15.00 I 15.00 J .25 K 5.00 Plot similarity values against distance along 115.25 75.75 transect (values located at mid-point between quadrats) MA- SCO- Locate I.TZ and ULM TRANSECT SUMMARY: LIZ is point of low similarity on transect Quadrats ISE below ULM MO ULM is point of low similarity on transect T 2 -77 closest to upland 2 8 3 66 3 4 54 4 5 53 ft SC II- 5 6 79 41).9 6 7 88 7 8 70 ULM 8 9 75 NAP- 9 10 94 10 11 33 11 8 12 40 I It s 4 II 7 MCI It OUADMAT APPENDIX B
Salt Marsh, Non-Indicator, and Upland Plant Species
of California, Oregon, and Washington
Plant species contained in this appendix are categorized as follows: intertidal--plants which are adapted to growth in saturated soils and have a high fidelity with intertidal marsh habitat; non-indicator--plants with broad habitat affinities, which can be found in intertidal marshes but are not restricted to them; upland--plants rarely found in intertidal marshes. It should be noted that the upland plant list contains only the most commonly occuring species adjacent to wetlands.
24 California
Intertidal Marsh Plants Plant Species Plant Species
Atriplex patula Orthocarpus castillejoides v. humboldtiensis
Batis maritima Plantago maritima
Carex obnupta Potentilla eqedei
Cordylanthus maritimus Salicornia virginica
Cuscuta salina Scirpus americanus
Distichlis spicata Scirpus californica
Epilobium watsonii Scirpus koilolepis
Frankenia grandifolia Scirpus robustus
Grindelia maritima Spartina foliosa
Grindelia stricta Spartina spartinae2
Jaumea carnosa Spergularia canadensis
Juncus acutus Sperqularia macrotheca
Juncus balticus Suaeda californica
Limonium californicum Triglochin concinnum
Monanthochloe littoralis Triglochin maritima
1 Nomenclature follows Munz and Keck (1963 with supplement 1968). 2 Hitchcock (1950). Also found in areas influenced by brackish and fresh water. Intertidal Marsh Plants North of San Francisco Bay, non-indicator plant San Francisco Bay and South. Variety palustris is a candidate for federal endangered status, spp. maritimus is a listed federal endangered species.
25 Non-Indicator Plants
Plant Species Plant Species
Atriplex watsonii Festuca rubra
Carex barbarae Juncus leseurii
Carex pansa Parapholis incurva
Cressa truxillensis Salicornia subterminalis
Distichlis spicata Vicia sativa
Elymus triticoides
26 California
Upland Plants, Page 1
Plant Species Plant Species
Abronia latifolia Convolvulus cyclostegius
Abronia umbellata Convolvulus soldanella
Achillea millefolium Coreopsis gigantea
Agropyron repens Descurainia pinnata
Ammophila arenaria Elymus mollis
Artemisia californica Elymus vancouverensis
Artemisia douglasiana Erechites prenanthoides
Atriplex lentiformis Eriogonum cinereum
Atriplex semibaccata Eriogonum latifolium
Avena fatua Eriophyllum staechadifolium
Baccharis pilularis Erodium cicutarium
Beta vulgaris Foeniculum vulgare
Brassica campestris Franseria chamissonis
Bromus madrenitensis Geranium dissectum
Bromus maritimus Glehnia leiocarpa
Bromus mollis Gnaphalium chilense
Bromus rigidis Heterotheca grandiflora
Cakile edentula Holcus lanatus
Cakile maritima Hordeum stebbinsii
Cardionema ramosissimum Isomeris arborea v. anqustata
Centaurea melitensis Lolium multiflorum
Cirsium arvense Lolium perenne
Conium maculatum Lotus purshianus
27 California
Upland Plants, Page 2
Plant Species Plant Species
Lotus scoparius Rhus diversiloba
Lupinus rivularis Rhus integrifolia
Lycium californicum Rubus ursinus
Madia subspicata Rumex acetosella
Malva parviflora Silybum maryanum
Melilotus albus Solanum xantii
Melilotus indicus Solidago spathulata
Mesembryanthemum edule Sonchus asper
Montia perfoliata Sonchus oleraceus
Nicotiana glauca Stellaria media
Oenothera cheiranthifolia Tanacetum douglasii
Picris echioides Trifolium wormskioldii
Plantago lanceolata Urtica holosericea
Poa douglasii Vicia tetrasperma
Poa scabrella Yucca whipplei
Polygonum paronychia
28 Oregon, Washington
Intertidal Marsh Plants
Plant Species Plant Species
Aster subspicatus Oenathe sarmentosa
Atriplex patula Orthocarpus castillejoides
Calamagrostis nutkaensis Physocarpus capitatus
Carex obnupta Plantago maritima
Carex lyngbyei Potentilla pacifica
Cordylanthus maritimus Puccinella pumila
Cuscuta salina Rumex occidentalis
Deschampsia cespitosa Salicornia virginica
Distichlis spicata Scirpus americanus
Eleocharis palustris Scirpus cernuus
Epilobium watsonii Scirpus maritimus
Galium triflorum Scirpus microcarpus
Glaux maritima Scirpus validus
Grindelia integrifolia var. macrophylla Sidalcea hendersonii
Hordeum brachyantherum Spartina alterniflora
Jaumea carnosa Stellaria humifusa
Juncus balticus Spergularia canadensis
Juncus effusus Triglochin concinnum
Juncus gerardii Triglochin maritimum
Lilaeopsis occidentalis Zostera nana
1 Nomenclature after Hitchcock and Cronquist (1973). Also occurs in areas influenced by fresh and brackish water. Variety palustris is a candidate for federal endangered status.
29 Oregon, Washington
Upland Species
Plant Species Plant Species
Achillea millefolium Holcus lanatus
Agropyron repens Hypochaeris radicata
Angelica lucida Lathyrus japonicus
Carex pansa Lonicera involucrata
Elymus mollis Maianthemum dilatatum
Erechtites arquta Picea sitchensis
Festuca rubra Plantago lanceolata
Galium aparine Poa pratensis
Galium triflorum Rubus ursinus
Gaultheria shallon Spergularia macrotheca
Heracleum lanatum Vicia gigantea
Oregon, Washington
Non-Indicator Plants
Plant Species Plant Species Agrostis alba Spergularia macrotheca Juncus leseurii Stellaria calycantha Lotus corniculatus Trifolium wormskjoldii
30 APPENDIX C
Upper Limit of Marsh (ULM) and Lower Limit of Transition
Zone (LTZ) Determined by 6 Methods Applied to 22
Transects from Frenkel et al. (1978)
Numbers on the ordinate denote distance (m) along sample transect from wetland to upland. Arrows indicate LTZ and ULM positions listed in Table 1. TRANSECT 0105
FIVE PERCENT 1.• JOINT OCCURRENCE IN
0.• N -
0.• H U
N •.2
N N N II I O. • 2 4 I • NI 12 14 10 111 2 ■ t IS It 14 IS IS MARSH UPLAND MARSH UPLAND MARSH t (UPLAND
• 2 4 i II 1•12 1• IS • MARSH I UPLAND TRANS/TIM HARSH UPLAND TRANSECT 0208
1.9 JOINT OCCURRENCE F IVE PERCENT SIMILARITY ISJ IN
0.0
9.0 Z • - M U 9.4 a -
0.2 is
0 I 12 • 16 10 21 24 27 I 2 0 0 It 16 16 211 24
MULTIPLE OCCURRENCE SIMILARITY ISE CLUSTER 100.0 00.0
00.0
70.0 u6 a w s..•
40.5
90.•
20.0
111.0
r-1 41.11 .... 0 S 0 I a 0 12 16 IS 21 124 HARSH UPLAND TRANSECT laala 1
FIVE PERCENT 110.0 JOINT OCCURRENCE 101 06.6 0.6 55.0 It
0.5 H U
0.4
6.2
N•) li I $4 I 20 -1 11 111111 4 0 IS 12 14 10 1• • IS 111 It If 14 ft 10 17 10
110.0 SIMILARITY ISE CLUSTER 100.0 00.0 00.•
70.0
00.0
g 00.0
MAP
Lit e IS TRANSITION MARSH UPLAND TRANSECT 0310
JOINT OCCURRENCE 1.0 FIVE PERCENT 118.0 180.0 08.0 0.0
0.0
0.4 48.1
90.0 • 02 28.0 10.8 0.11 OA. 4 i i ii 12 14 10 10 1 1 0 0 10 12 14 10 11040010116/M14 4 4
110.0- 12. MULTIPLE OCCURRENCE 2.8 CLUSTER 188.0 • 10.0 Le 08.8 0.0 Le 00.0 • V 0.11 LI 711.0 • 4 0 O • 1.2 • 00.11 O 1.0 M 611.11 •
11.• 8.8 40.11 L12 U O 0.5 38.0
-4.0 9.9 20.0
0.2 16.0
-Ch- o i i ■ ■ Ii 1! 14 II 04 6.90 O 0 10 12 14 10 I I MARSH TRANSITION UPLAND TRANSECT 0402
JOINT OCCURRENCE FIVE PERCENT 1W
s.s -
8.0 H U 41 0.4
9.2 as -
0. • 1110 3 6 i 12 16 II 21 24 6 11 II RI 19 21 It 29
110.0 MULTIPLE OCCURRENCE CLUSTER 100.11 LI- 08.0 00.0
1.2
1.0 • V 60.0 1.1- 48.8 LS- 0 S0.0 0.1- 20.0 0.2 • 10.8
0.00 18 21 £4 A X UPLAND TRANSITION MARSH TRANSECT 0704
JIONT OCCURRENCE MOJI 1.0- FIVE PERCENT SIMILARITY ISJ 100.0• NIP 00.0 N. 00.0• 79.0 H N U 90.0 U 110.0 11.4 411 40.0 30.0
0.5 II 2111.0 tan 10.0- I •.0 • 1 0 2 4 i 0 10 It 14 Is es 11 10 12 14 IS 10 414 411111111111414141411
110.0 CLUSTER MULTIPLE OCCURRENCE 100.0 15.5 00.11
-12.0 0 4 10 It 14 10 III es us so
TRANSITION MARSH UPLAND TRANSECT 0706 JOINT OCCURRENCE 1.0 FIVE PERCENT M8.• SIMILARITY /0J MIL•
11.11 00.• a- OLIO
71.4
14 () 1111.41 vt I W 0.• U Y 40.• s•it $.2 a- 18.•
11.11 • II 12 14 li el 11•90 2 11 2 • IS 1: ii • I 4 • • 1• II It III 14 PI le 17 4• HI t I
CLUSTER SIMILARITY ISE
1.0 a U 0.6
0.4
0.2
4 1i 12 1• Ii It 20
UPLAND MARSH TRANSITION TRANSECT 07- 0
JOINT OCCURRENCE 1.0 FIVE PERCENT
NU- _ OLN 0.•
ss -
•.0 H 0 - SU U 5 •.4 a 0 - a
9.2 0 -
0.e S- . s Melt 14 10 10 I 111 -1 I 1 I 1 1 I 20 • I 4 III • IS n 04 n 44 n a n Is
CLUSTER SIMILARITY ISE
1.5
1.2
g 40.0. 40.0. 40.0■ .5 20.11. 0.2 10.0- ULM O. Os ft 2 • a 010 II 14 ^1i 1i SO TRANSITION MARSH UPLAND TR ANSECT 08-04 JOINT OCCURRENCE 1.0 FIVE PERCENT 11•.0-
20 I"... 0.• N... 0 - 0.0-
0.0 MA. U U It 21 70i: •.4 •- LTR 0.11- 11.2 - 20.0- 111.0. 11141 4.0 • •,1 0.11i .4 11 it 14 II Is 6 I 4 N It 14 II 10 20 11 I 4 IINWHNNUN 1
21.• CLUSTER 110.0 MULTIPLE OCCURRENCE 2.0 SIMILARITY 2SE 100.11- 2.2 0.0 It.. 2.0 1.11 110.0, 1.0 o- z 0.0, w I. 0 0.0. 1.2 V PAP. oo, a um 1.0 LTR OA. 0.0 0.11- 9.0 0.0 0.2 MA O. 111 It 14 4 A 25 IS 2 4 0 11 1i It 14 10 IS ,11 MARSH UPLAND TRANSITION TRANSECT 0808 JOINT OCCURRENCE Le F IVE PERCENT
I
0 .9
0.9 H 1• U
U 0.4 Va 41I
0.2 •
e 4 0 2 14 li 10 ► 1 1 I • IP I 10 11 111 MI 14 /4 III It
1.8 CLUSTER
I.,
1.2
1.0
0.8
0.6
0.0
0.2
1 C i 1.0 12 14 TRANSITION MARSH I UPLAND TRANSECT 0809 JOINT OCCURRENCE 1.0 FIVE PERCENT
NM
0.0
se-
0.
0.♦ U a a -
0.2 0-
. I 1 11 illii "6 ; 4 h 14 ie 16 26 22 24 29 1 : i 4 IP It 12 S4 10 NI • H as NU
CLUSTER SIMILARITY ISE 2.0
1.11
1.1
1.11
1.2
1.0
0.0
0.0
0.I
0.2
n IS 001000011:100.0rctriElrl 4 2 II TRANSITION MARSH UPLAND TRANSECT 0910 JOINT OCCURRENCE 1.• SIMILARITY ISJ
70.5 •.0 H We U 0 20.0 11.4 4111.0 • Lit
0.2 20.11 ML
•••0 1 SO 41 11 to A 00 • •i lo to a a a ei i• M o•
CLUSTER 2.1 2.2 2.0 1.0
1.1 0 21.0 1.2 5 00.0- 1.0
r g cessa g rs leterlISII°2111 MARSH UPLAND TRANSECT 1 001
11111111111r O. eit ui u s mi t4 mi 1 1
MULTIPLE OCCURRENCE CLUSTER 110. 26. • 2.1 110.0 20.11 2.2 16.0 2.0 M. w ISA 1.1
6.0 1.1 MIA • 0.11 L72 1.4
z-6.0. 1.2 N. -10.11• 1.0 411.0 .-16.11• 0.11 ML -20.•• 0.11 mt. -26.0. 0.4 -20.0 0.2
MA, 41 MI its 100 26i 140 a 1111 1211 IM 201 245
TRANSITION UPLAND MARSH TRANSECT 1103
SIMILARITY INJ
Veb
li
11 11 11111111 N 4 4 44 ii1 I4 IN NM 009 fa 909 Fe 916 .0 9119 eV 990 409 991, I 00 PO NO 1
OSA . MULTIPLE OCCURRENCE CLUSTER OSA
OSA 1.11 NA V MA 1.2 SA. OA 1.11 woo 0.11 -ISA. O 11.11 -ISA 0.4 -MIA- -21.0 0.2
SSA 0 1140 41, 011 SO ISO 1211 r.R•:!IIIIIISI311121ttSIG" "111:111111
MARSH TRANSITIONMARSH UPLAND TRANSECT 1 201 JOINT OCCURRENCE 1 .0 FIVE PERCENT
•.0 Z N H U U a •.4 •
•. so
• •.• • 2• 1 • • • t• t• t•
M.• MULTIPLE OCCURRENCE CLUSTER I . 50- SIMILARITY /SE
•.11 LH- 1. 20- •.• V 1.0 -
U •.• •.00- O. /3- -4.11 X 0.5 -
-O. COS- 1•.11-• 0.10- 1111.•■ LT At.• OAS- 10.0 . ULIO •M r 4 If 1• 24 • ■ O It ti 24 I MARSH TRANSITION UPLAND TRANSECT 1 6 06
JOINT OCCURRENCE FIVE PERCENT
101 70.9
69.0- N
60.0 •
H F. U os.e
9.4 U I a • 36.9 L 20.0 N 10.0
0.0 11 10 •.•e 4 • • 16 If 14 16 • • 14
2.9 MULTIPLE OCCURRENCE CLUSTER
1110 t 4 0 6 10 If 1• 10 • 10 If 14 16 TRANSITION MARSH TRANSECT 1610 JOINT OCCURRENCE 1.• FIVE PERCENT SIMILARITY ISJ 7•.
0.9
641.•
H U 40.9 • a •.4 a sc.
0.0 1.2 10.0
•.6 • 4 14 111 I IS I 1 -41 1^11 14 • •
2.• MULT2PLE OCCURRENCE CLUSTER SIMILARITY ISE 1.00- 6.6 111.11 I.90- CT1 -2.41 2.20-
2.05- 8 -4.0 SAW- S 0.7;- I -11.9 11.110- et -6.• 5./15-
11.10- -10.0 11.15- -MO 2 4 • i 5 II 14 1• • • • •4 IS 12 1• TRANSITION UPLAND A
TRANSECT 1 6 1 1 JOINT OCCURRENCE 1.9 FIVE PERCENT N.. SIMILARITY ISJ 09.9
7E9
9.9 • • 0.•
1.2
A 1 1 10 14 10
MULTIPLE OCCURRENCE CLUSTER
4.•
2.11 A o.. 1.71
-4.11
-0.11
CIO 1 TRANSECT 61 2 JOINT OCCURRENCE 1.1 FIVE PERCENT Re
ILO H os U U 0.4 I
0.2
tee • IL 25 • • 11 N 14 17 sea a. a so
CLUSTER
El PI E R N TRANSITION UPLAND MARSH •
TRANSECT 1 703
JOINT OCCURRENCE FIVE PERCENT
NO- - - - -
M ^
0.0 N- 0
0.4 a-
5.2 se -
5 i ID 0 10 111 U a ID II It U IS
15.0 MULTIPLE OCCURRENCE CLUSTER LSO 12.0 LIS 0.0 • 1.20 0.0 3.0 1.05 a 8 0.0 -3.0 O. ?S -OA 0. -0.0 a -12.0 e. -15. • -10.0 0.15
1711 15 10 35 35 N I TRANSECT 1802 JOINT OCCURRENCE 1.0 FIVE PERCENT
0.0
0.0
0 0.4 I • - IM
S. a • I A 11 1 s • it 110 1811 IN 111 VIM
CLUSTER 1.50
1.35
1.20
1.05
0.00
0.75• I 0.110
0.20
0.1, rt.00 10 li el 25 u •• • W 11 MCI TRANSITION UPLAND APPENDIX D
Sample Field Data Sheet
Wetland Name Date
Quadrat (Labeled as distance along transect; 1 wetland) Plant Species 1 2 3 4 5 6 / 8 9 10 11 12 13 14 15 1 2 3 4
6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 APPENDIX E
Computer Software Available at U.S. Environmental
Protection Agency, Corvallis, Oregon
Computer programs are available at the Corvallis Environmental Research
Laboratory, Corvallis, Oregon for the cluster, similarity ISJ and ISE, and joint occurrence methods. We are currently developing an additional program to process data by the multiple occurrence method. Contact Jo Oshiro, U.S.
EPA/CERL, Corvallis, Oregon 97330 for further information.