EPA 910/9-91-037
Puaet Sound Estuary Program
Estuarine Habitat
Assessment Protocol
September 1991
-------
TABLE OF CONTENTS
Page
LIST OF FIGURES .
LIST OFTABLES
INTRODUCTION 1
Statement of Problem 2
Objective 3
Protocol Development 4
Design 6
Classification of Estuarine Habitats 6
Identification of Representative Fish and Wildlife Assemblages 6
Categorization of Habitat Functions 7
Identification of Important Relationships among Assemblage
Species 7
Listing and Ranking Habitat Attributes (Matrix II) 7
Literature Review of Habitat Requirements of Estuarine Habitat
Assemblage Species 9
Attribute Data Questionnaire
Review Workshop 9
Utility and Limitations 10
After the Protocol 11
USING THE PROTOCOL 12
Selection of Attributes and Parameters 12
Sampling Design 13
Selection of Applicable Protocol 13
Esruarine Habitat 13
Assemblage Species 13
Attribute or Attribute Group 13
Reference Material 13
Habitat Descriptions and Examples 15
Emergent Marsh 15
Mudflat 16
Sandflat 16
Gravel-Cobble 16
Eelgrass 16
Nearshore Subtidal Soft Bottom 17
Nearshore Subtidal Hard Substrate 17
Water Column 17
Example Use of Protocol 17
Sampling Considerations Common to All Habitats 19
Sampling Design in Estuarine Habitats 19
Sampling Strategies 20
Replication 24
Sample Dimension 27
Statistical Structure 28
U
-------
Page
LiTERATURE CImD 123
GLOSSARY.... . 135
INDEX 141
APPENDICES 145
APPENDIX A. Habitat-Specific List of Assemblage Species 147
APPENDIX B. Habitat-Specific List of Attributes and Associated
Habitat Functions 156
APPENDIX C. Physiochemical Attributes Identified in Protocol as
Important to Fish and Wildlife Utilization of Estuarine Habitats 192
iv
-------
LIST OF FIGURES
Figure Page
I. Flowchart of the sequence and interrelationships among the various
processes in developing the structure of the Estuarine Habitat
Assessment Protocol 5
2. Decision tree associated with accessing the Esruarine Habitat Assessment
Protocol on the basis of habitat, fish and wildlife assemblage species, or
estuannehabitatatlribute 14
3. Example of Minimum Detectable Effect as a function of sample size for
three levels of power for a two-sample t-test at 5% level of significance 26
4. Example of mean, minimum, and maximum standard error, and detectable
differences and density of organisms as a function of cumulative sample
size 27
LIST OF TABLES
Table Page
1. Hierarchies of functions of estuarine habitats for fish and wildlife used to
structure the Estuarine Habitat Assessment Protocol 8
2. Plant taxa and assemblages of estuarine habitats and that were identified as
being important to fish and wildlife during the protocol development
process 42
V
-------
ACKNOWLEDGMENTS AND CONTRIBUTORS
This Protoccil was prepared by the Wetland Ecosystems Team, Fisheries Research
Institute, University of Washington, under grams from the U.S. Environmental Protection
Agency, Region 10. Kathleen Kunz and Michael Rylko of the U.S. EPA were the project officers.
We extend our appreciation to wetland scientists, resource managers, and consultants who
provided constructive responses and critiques of the Protocol through its various stages of
development. We are hopeful that all contributors to the formulation of the draft protocol prior to
the Protocol Development Workshop (see Introduction), the Workshop participants, and those that
assisted us in the final review iterations are listed in Supplement 8; we apologize if any have been
unintentionally unacknowledged. We would, however, take this opportunity to especially
acknowledge George Blomberg, Port of Seattle, for his continuous motivation through the
Urbanized Estuary Mitigation Working Group (UEMWG) for such a design criteria-oriented
protocol, and Bob Zeigler, Washington Department of Wildlife, for his devotion of unlimited
enthusiasm and energy throughout the history of the Protocol. In addition, Bob Donnelly of the
Fisheries Research Institute was gracious enough to provide his unpublished information on
bottom trawl selectivity. Further appreciation is extended to Leslie Sacha and the Port of Tacoma,
for hosting the many UEMWG meetings during the Protocol’s development. Extensive, useful
review comments on the draft of the Protocol were constructively suggested by Fred Weinmann, 1
Region 10, and Mary Kentula, Environmental Laboratory, U.S. Environmental Protection
Agency. Additional recommendations, no less valuable, were provided by Kurt Fresh and Mary
Lou Mills, Washington Department of Fisheries; Stuart Toshach, Puget Sound Water Quality
Authority; Ken Brunner, U.S. Army Corps of Engineers, Seattle Disthct John Marshall,
Washington Department of Ecology; Tracy McKenzie, Pentel Environmental; George Blomberg,
Port of Seattle; and Mark La Salle, Mississippi Sea Grant Cooperative Extension Service. Finally,
we extend our appreciation especially to Marcus Duke and Alma Johnson, who exerted their
utmost editing skills to make the Protocol understandable and readable.
vi
-------
EXECUTIVE SUMMARY
The Estuarine Habitat Assessment Protocol (hereafter termed “the Protocol”) is the
product of a concept that emerged in the ad hoc Urbanized Estuaiy Mitigation Working Group
( UEMWG ) and was adapted and completed by the Wetland Ecosystem Team (W.E.T.) of the
Fisheries Research Institute, University of Washington, for the U.S. Environmental Protection
Agency’s Office of Puget Sound and Wetland Program.
The Protocol was developed in response to the need for procedures that quantitatively
assess the function of estuarine wetlands and associated nearshore habitats for fish and wildlife.
While all the various functions of estuarine wetlands and nearshore habitats need better
identification and documentation, we felt it imperative to restrict the Protocol to one prominent
function in terms of regulatory emphasis in Pacific Northwest estuaries: use as habitat by fish and
wildlife species. We trust that protocols for assessing other functions and for freshwater wetlands
will be developed in the future, perhaps following the same process.
The functional approach was taken in preference to simply assessing fish and wildlife use
because the latter, usual approach to habitat assessment does not measure habitat quality directly,
nor does it identify the characteristics of the habitat that explicitly promote fish and wildlife
utilization. Thus far, a systematic approach for measuring the function of estuarine wetlands and
nearshore habitats that considers these factors has not been available. Consequently, restoration 1
and creation of estuarine habitats have proceeded haphazardly. Without such procedures, the
scientific knowledge required to link the characteristics of estuarine habitats to their functions in
support of fish and wildlife will not emerge. In the absence of this critical understanding, the
present uncertainty inherent in the emerging technology of habitat restoration and creation will not
be resolved, and we will not progress toward a goal of minimizing future habitat loss. The
approach of the Protocol, and of the procedures and measurements it recommends, is intended to
bridge this gap between estuarine habitat characteristics and the habitat’s function to support fish
and wildlife.
Fish and wildlife utilization of estuarine wetlands and nearshore habitats per se continues to
be extremely difficult and expensive to document. Any reliable assessment methodology must,
therefore, measure characteristics (termed attributes in the Protocol) of estuarine habitats that
promote fish and wildlife utilization and fitness. This Protocol is not intended to supplant
monitoring of the fish and wildlife themselves, which can often be a direct measure of habitat
function. Instead, it should be considered a supportive measure of the pofentici to provide a
specific function which, unlike utilization information, provides design criteria for habitat
restoration.
The goal of the Protocol is to initiate systematic, on-site measurement of estuarine wetland
and nearshore habitat function for fish and wildlife utilization by assessing the attributes of the
habitats idennjled as being functionally iMportant to fish and wildlefe. The Protocol is intended as
a supplement, not a replacement, to more comprehensive but basically qualitative procedures for
assessing overall habitat quality (e.g., Wetland Evaluation Technique [ WE1’], Habitat Evaluation
Procedure [ HEP]). As such, it could be looked upon as a higher resolution extension of the fish
and wildlife function component of those procedures. In addition, it should not be used as a
methodology for assessing other habitat functions (e.g., those that maintain water quality).
Finally, as a strictly scientzfic tool, the Protocol does not promote a procedure for attaching
“values” to wetlands and associated habitats, which we consider to be the purview of policy and
Tenns that are defined in the Glos iy are underlined at their first occurrence.
-------
management disciplines. Probably the single aspect of the Protocol which differentIates it from
these other approaches is that it is designed to accrue information for developing more successful
approaches to habitat restoration.
The Prot col is organized so that it can be accessed to answer a particular question from
three different perspectives: habitat type, fish and wildlife assemblage species, and attribute.
Definitions of habifat types, the fish and wildlife species considered representative of each habitat
type, and the attributes of the habitats that are considered important to these fish and wildlife are
presented and cross-referenced so that the investigator can determine which parameters and
methods are most appropriate to a particular situation. Basic concepts of sampling theory that are
pertinent to estuarine wetland and nearshore habitats are also reviewed to assist the investigator in
deploying sampling in a statistically valid design. Using these considerations, the endpoint of the
Protocol’s use should be an appropriate monitoring plan for assessing estuarine habitat function
from any of these perspectives.
The separately bound supplements (Simenstad et al. 1990) that accompany this document
include the following: (1) the result of the initial surveys (matrices) that guided the Protocol
development; (2) an annotated bibliography assembled from material provided by the survey
respondents and a computerized literature search; (3) individual, detailed descriptions of the
attributes; (4) citations of literature that provide detailed information about the attributes; and (5) a
list of the resource management agency personnel and other scientific experts who contributed to
the development of the Protocol
Under separate programs, the U.S. Environmental Protection Agency is supporting the
preparation of other documents and products that will also contribute to the objective of the
Protocol: (1) a computerized estuarine habitat database in R:Base format and (2) a computer
software version of the Protocol that guides a habitat manager to the appropriate procedure for
assessing their particular habitat
In examining the results of this edition of the Estuarine Habitat Assessment
Protocol, we reinforce the concern that further attention must be given to evaluations of habitat
function and performance not included in the Protocol, which is restricted solely to the assessment
of the fish and wildlife support function of estuarine wetland and nearshore habitats. Similar
assessment protocols need to be developed for other wetland functions (e.g., shoreline
stabilization, water quality) and for non-estuarine (e.g., riparian, palustrine, lacustrine) wetland
habitats. We also strongly recommend the resting and verification of the Protocol in restoration
and mitigation sites as well as in the natural estuarine wetland and nearshore habitats upon which it
was based. For testing at natural sites, “reference” wetland sites need to be established for long-
term monitoring of the mote important, or potentially most inherently variable, estuarine habitat
atthbutes.
Finally, the Protocol is designed as a “living” management tool, in the sense that it was
developed using open-ended matrices and databases that can be expanded and attributes identified
from new studies can be incorporated into future versions. Once the Protocol has been tested and
applied in a variety of situations, the gaps and inadequacies that emerge should be addressed by
ardent revision. This would preferably be done via a workshop similar to the Wetland Restoration
Protocol Development Workshop, which was a critical step in the development of this edition.
Key words: estuarine habitat, wetlands, monitoring protocoLs, fish and wildlife
V I I I
-------
INTRODUCTION
Ecosystem restoration is an activity at which everyone wins: when successful, we
are rewardea by having returned a fragment of the earth’s surface to its former state;
when we fail, we learn an immense amount about how ecosystems work,provided
we are able to determine why the failure occurred
Ewel (1987)
In environmental science, protocols are “formulas defined at the beginning of a preliminary
document.” Two words of this definition are most germane to sampling and analyzing environ-
mental data from Puget Sound: formulas and prelimina,y. In this instance, “formulas” mean
standardized, scientifically based, consistent procedures. As formulas, protocols are critical to any
long-term evaluation of The state of a system, especially one as complex as Puget Sound. Only
through the accumulation of common equivalent data can the results of studies be compared and a
historic time sequence examined for trends that indicate declines or establish improvements in
environmental quality. Protocols must also must be considered “preliminary” because the acqui-
sition of information using protocols should result in revision and refinement of the original
procedures. In sampling theory, a protocol is analogous to the sampling frame , which is a list of
all sampling units (see Sampling Design section) that logically changes with sampling experience.
That the Estuarine Habitat Assessment Protocol (hereafter known as the “Protocol )
is preliminary has two implications. First, it describes procedures that have been evaluated and
generally accepted, typically through expert consensus, prior to a study. Second, the procedures -
are not mandated but advisory, and it is accepted that they will be revised as newer, more effective
tools evolve. Ewel’s quote at the beginning of this introduction, and especially the italicized
segment, summarizes our rationale: Neither the science nor the technology of estuarine habitat
restoration can progress until we treat restoration as rigorous experimentation in which consistent
data are gathered in a inductive format.
The Protocol applies only to the functional assessment of fish and wildlife support in
esnsarine wetlands and certain adjacent habitats of the Puget Sound trough. Although the infor-
mation used to develop the Protocol was derived from natural estuarine habitats, it emphasizes
evaluation of restoration in disturbed estuaries, such as the many urbanized estuaries that surround
Puget Sound. Therefore, the Protocol is designed (1) to assess the function to support fish and
wildlife and (2) to monitor the comparative performance of the site after restoration or of a
mitigation site designed to replace the development site. The information base of the Protocol was
assembled by identifying the attributes of estuarine habitats that promote high use by fish and
wildlife; these attributes form the focus of the Protocol.
The sections immediately following provide a detailed discussion of the impetus and
development, the intended purpose and application, and the structure of the Protocol. This may
not be of direct interest to the reader whose immediate need is to apply the Protocol to a particular
situation; a quick perusal of the rest of the Introduction, however, will better acquaint the reader
with the logic and philosophy behind the Protocol. We recommend that you read the Utility and
Limitations section in order to understand the Protocol’s limitations. Using the Protocol is a road
map to the body of the Protocol. Finally, readers who are interested in the concept of this
approach to assessing estuarine habitat function is directed to the Discussion section, which
addresses several aspects of the implementation, testing, and enhancement of this approach.
In addition to this document, Simenstad et al. (1990) provide eight supplemental materials
that constitute the basis of the Protocol. These include the following: (1) the result of the initial
surveys (matrices) that guided the Protocol development; (2) an annotated bibliography assembled
-------
1$ffRODUCT!ON /2
from material provided by the survey respondents and a computerized literature search; (3) indi-
vidual, detailed descriptions of the biological atthbutes (4) citations of literature with specific
information on the attributes; and (5) a list of resource management agency personnel and other
scientific experts who contributed to the development of the Protocol. These materials are repro-
duced in theiT original form and do not contain caxonomic and other corrections that have been
incorporated subsequently into the Protocol.
STATEMENT OF PROBLEM
The demand for and pace of wetland creatinn/iestoradon appears to be accelerating beyond
oiir abilities to either technically evaluate or effectively manage it (Zedler 1986). In a recent
analysis of 35 projects in Washington receiving wetland development permits requiring mitigation
(<5% of all Clean Water Act Section 404 permits), Kunz et al. (1988) documented that as a best
possible case, on the basis of acreage, only 67% of the natural wetlands that were developed were
replaced by created/restored wetlands, and only 68% of the wetland habitat types lost were
replaced. The Kunz et al. (1988) study did not evaluate the functional status of the
creation/restoration sites, but Kusler et al. (1988) has documented on the national level that, where
the degree of wetland creation/restoration has been measured over the short term, about half have
failed in some respect
However, mitigation is only a policy tool designed to prevent continued loss of wetland
resources. Mitigation does not inherently prescribe the optimum approaches to achieving this end,
nor does it necessarily generate information useful for wetland habitat restoration. Kunz et at.-
(198 8) illustrated that pervasive inadequacies in the negotiation, planning, and enforcement on the
part of agency arlmiriiscradon of Section 404 of the Clean Water Act have resulted in dramatic -
mismatches between the habitats impacted and those generated as their “replacements.”
While the Kunz et aL (1988) and subsequent updates (Rylko and Storm 1991) identified
primarily the administrative and policy faults inhibiting successful mitigation, two technical
problems also lie at the root of the problem: (1) a lack of technical knowledge of the structure of
Pacific Northwest wetlands and how they function; and (2) an inability of regulators and managers
to uniformly assess mitigation projects and their outcome (Cooper 1987; Kunz et al. 1988). These
inadequacies impede both habitat restoration and enhancement and are particularly germane to
estuanne habitats, because most of the considerable development pressure is focused on the
remaining wetland habitats in Puget Sound and other coastal estuaries of Washington and Oregon
(Cooper 1987, Good 1987). Of primary concern is the dependence of many commercially and
recreationally important fish and wildlife resources upon estuarine habitats. The Protocol is a
technical approach to standaixlize techniques for quantitatively assessing estuarine habitat quality
specific to functions enhancing fish and wildlife utilization.
At the core of the mismatch between the pressures to develop estuarine habitats and our
meager track record in habitat restoration/creation is the incomplete understanding of natural
estuarine ecosystems in this region and how they might be created in a manner so as to function
naturally. However, in both cases, an important contributing cause is the lack of uniform
procedures, or protocols, for objectively assessing habitat function. Protocols are critical for the
evaluation of the functional status of estuarine wetland and nearshore habitats proposed for
development, as well as for the subsequent monitoring of compensatory habitats to evaluate stated
project objectives. This lack of standardized, objective protocols has resulted in (1) habitat
assessments that inadequately 1 inaccurately or inappropriately quantify habitat functions; (2) the
slow emergence of design criteria from the results of past mitigation projects; (3) inconclusive
assessments of mitigation results due to inadequate monitoring; and (4) a lack of identifiable
remedial actions to take if a mitigation site does not meet predetermined criteria.
-------
Statement of Problem /3
Habitat restoration should extend beyond the mitigation associated with permit processes,
which are limited in number and scope and constrained by regulatory mandates. This broader
interest in habitat restoration has resulted in the inclusion of a habitat restoration component in the
1991 Puget Sound Water Quality Management Plan (PSWQAMMC 1991) and has instituted a
variety of public, governmental, and private efforts toward estuarine habitat enhancement not
directly related to compensation.
At the time of preparing this Protocol, there was no broadly accepted set of procedures for
monitoring estuarine habitats to evaluate fish and wildlife utilization, nor did any advocate
collecting quantitative data. The quantitative data that were available usually documented
abundance and infrequently biomass. Time series of density and standing stock , and actual
functional variables such as reproduction and feeding, were rare and not measured consistently.
The Urbanized Estuary Mitigation Working Group ( IJEMWG , see Protocol Development section)
identified five principal problems associated with present estuarine habitat monitoring: (1)
monitoring criteria were not applied uniforthly or consistently among projects; (2) data were not
rigorously quantitative, if quantitative at all; (3) tIe foctis on target species ignored tIe more
complex ecological relationships among the other components of the community and the physical
characteristics and processes of the habitat; (4) the interpretation of the results from these diverse
approaches was highly subjective, and (5) critena for design of habitat restoration projects were not
being tested and refined. Therefore, the UEMWG determined that the principal need was to
identify quantitative prncedures to monitor the functional relationship between fish and wildlife and
the other components, biological and physical, of estuarinë wetland and nearshore habitats.
OBJEcTIvE
The objective of the Protocol is to describe and recommend technic ue ’fór quantitatively
measuring attributes of estuarine habitats that characterize the potential ecological function of that
habitat for fish and wildlife.
We direct this objective to estüarine habitat managers, planners, consultants, and applied
scientists who require a community-based procedure to assess estuarine habitat function and
quality relative to restoration and mitigation of fish and wildlife habitat In doing so, we have
assumed that a common approach has definite benefits. Habitat managers would benefit from the
uniform format of habitat assessments they review in their permit evaluations. Planners would
have at hand a rapidly accumulating baseline of the design elements that did or did not create
functioning fish and wildlife habitat. Developers should find the process of permit preparation,
review, and approval more cost efficient and objective. Scientists will benefit considerably from
the acquisition of data that have scientific value in interpreting habitat function and in comparing
both applied and basic research.
The Protocol, however, is not the panacea for all problems faced in estuarine habitat
management. It is not intended to culminate in a single, comprehensive determination of habitat
“value” that would encourage comparison of different habitat types. It does not adcfress flood
desynchronization, groundwater recharge, or any other functions outside those directly applicable
to fish and wildlife habitat and food chain support. It does not account for all attributes of Pacific
Northwest estuarine habitats, nor does it constitute the final or only methodology that might be
used for assessing estuarine habitat function in this region.
Estuarine management demands technically sound decisions regarding the relative
quantities (i.e., habitat balance) that would be desirable in any given estuary. However, the
Protocol is based upon the science of estuarine ecology as we understand it for this region, not on
policy considerations. We have intentionally avoided the strategy of assigning habitat value•
because we find no ecological basis for ranking one habitat higher than another. Each habitat
contributes to the estuarine ecosystem in a unique way, supports discrete fish and wildlife, and
-------
INTRODUCTION /4
varies in its ability to generate, assimilate, or process nutrients, organic matter, and sediments .
Furthermore, estuarine habitats are linked integrally throu gh pathways of materials (the transp
nutrients, detritus) and organisms (the movements of fish, macroinvertebrates, mammals, birds),
they should never be considered as disjunct communities. The natural continuum of habitats
across an estuary must be preserved or restored if we are to maintain and eventually restore
estuarine habitat function for fish and wildlife. For this reason, any decisions relative to habitat
value, if they must be made, belong in the realm of policy and management and outside the
scientific scope of the Protocol.
Physical and biochemical processes (and their associated wetland functions) often regulate
ecological functions. It is probably a truism that most failures of estuarine mitigation projects can
ultimately be attributed to disfunction of physical and biochemical processes upon which biotic
processes are dependent. Unfortunately, we do not have the resources to address the physical and
biochemical functions at the same level as we have addressed the biotic. (We recommend that the
reader pursue more information in these respects by reading Chapters.3 and 4 of Strickland 1986).
Instead, we have sought to distinguish the physical and biochemical conditions that are required by
the biotic attributes of estuarine habitats, arid trust that these are the more important indicators of
abiotic functions.
PROTOCOL DEVELOPMENT
In 1988; Wetland Ecosystem Team (WET; Fisheries Research Instittite, University f
Washington) proposed that the UEMWG objectives be expanded to include the development Of an
estuarine habitat restoration protocol (Fig. 1). The expansion was funded bythè EPA, Region 10
Wetland Protection Program, and EPA ’s Office of Puget Sound. The Port of Seattle also
contributed resources.
The initial goals of the UEMWG were to improve predictability in the mitigation planning
and review process 1 and to increase the success of mitigation projects in urbanized estuaries. Froi.
the beginning, the UEMWG confined its activities to technical aspects of implementing measures
for compensation of fish and wildlife habitat lost due to development activity. As a result, its
discussions did not consider mitigation policy. Any products of the UEMWG, therefore, were
considered tools to be used in a broader management framework for estuarine habitat restoration.
In addition, the development of the fish and wildlife assemblages upon which the final
protocol is based was restricted to regional information and data because the Protocol was designed
to be applied to Puget Sound and its various”sub. estuaries.” In identifying and describing what
we know about the attributes, however, information from estuaries outside Puget Sound was
considered when local data were otherwise unavailable. In this case, the geographic limitation was
northern California to British Columbia, Canada. The data associating the assemblage species with
wetfand and nearshote habitat attributes originated from regional resource scientists and our.
combined knowledge of the applicable scientific literature. We acknowledge that this emphasis on
empirical relationships has the advantage of being based on “hard” scientific evidence. However, a
disadvantage is that it does not encompass subjective associations, which may represent an
important but undocumented relationship.
The simple presence of fish and wildlife in a habitat does not necessarily constitute
utilization per se and does not quantify the causal association between attributes of the habitat and
the function of the habitat to support fish and wildlife. The strategy used to develop the Protocol
was to define frnportanr habitat auributes. This attribute definition involved identifying biological
and physical attributes of estuarine wetlandsand nearshore habitats that determine the extent of fish
and wildlife utilization. In addition, by building the structure of the Protocol around matrices
associating fish and wildlife species (e.g., columns) with the functional attributes of the habitat
(e.g., rows), an attribute could be identified as being important to the biotic community overall,
-------
Protocol Development /5
—
A cmblage
Species l i St
Identified Habitat
Functiotis o( High Importance
To Assemblage Species
MATRIX II:
Identified Specific Attributes
(ic. Prey Species, etc.) Of
High Importance To
Aesemblage Species
‘ ,
QUESI1ONNAJRE
Techniques For Measuring
Habitat Attnbutcs
And Expected Value Ranges
i
DRAFT ASS SM f
PROTOCOL
Figure 1. Flowchart of the sequence and interrelationships among the various processes in
developing the structure of the Estuarine Habitat Assessment Protocol.
MATRIX L
-------
INTRODUCTION /6
rather than just to a single target species. It then followed that incorporating such an attribute in a
habitat restoration and mitigation design would increase the utility of the habitat for the maximum
number of fish and wildlife species.
DESIGN
A detailed process was devised to categorize estuarine habitats, the fish and wildlife
assemblages that typify them, and the attributes of those wetland that are functionally important to
the fish and wildlife fauna (Fig. 1). Each of the following stages of the process is described In
detail in the following section. The first stage of this process involved defining eight estuarine
habitat categories. The next stage involved identifying fish and wildlife species that are considered
representative of these habitats. This was not intended to result in a comprehensive list, but one
which encompassed the fish and wildlife niches evident in each of the eight habitats, thus
representing the overall scope of fish and wildlife use in the respective estuarine habitats. The next
stage in the process of designing the Protocol employed a hierarchical sequence of increasingly
specific matrices in which wetland and nearshore habitat attributes were ultimately ranked
according to their functional importance. Fish and wildlife support functions were defined as (1)
reproduction, (2) feeding and related activities (e.g., “graveling” of waterfowl), and (3) refuge and
physiology (the use of habitats to adapt to physiological changes). These definitions are intended
to include both the “fish and wildlife habitat” and “food web support” (exclusively for fish and
wildlife) functions of estuarine habitats. Two matrices were developed. The first (Matrix I)
ranked habitat functions that were important to specific fish and wildlife assemblages. The second
(Matrix II) ranked the importance of specific attributes that accounted for these functions. The last
task involved using the results of Matrix II to generate a questionnaire for quantitative data and
associated information on the highest-ranked attributes.
CLASSIFICATION OF ESTIJARINE HABITATS
Because of the dynamic nature of estuaries, e.stuarine habitats tend to be complex.
Different habitats are often imbedded within a natural matrix that changes along subtle gradations in
wave exposure, salinity regimes, sediment character, etc. However, habitat restoration and
mitigation are currently practiced at a rather low level of resolution, and so we chose to structure
the protocols around broad habitat categories. We designated eight estuarine habitat categories:
Five of them—emergent marsh. mudflat. sandflat , gravel/cobble, and eelgrass—are acknowledged
intertidal wetlands. The other three categories—water column, subtidal soft bottom , and subudal
hard subslrato—are not wetland habitats, but they are integrally associated with intertidal wetlands
in the estuarine landscape. Because of these broad definitions, the habitat types can be equated to a
habitatclass in any of the several hierarchical wetland and associated habitat classifications
schemes currently being used (e.g., Cowardin et al. 1979 and as modified for this region [ Dethier
19901). See the Habitat Descriptions and Examples section for the specific translation among the
Protocol habitat categories and those of Dethier (1990).
IDENTIFICATION OF REPRESENTATIVE FISH AND WILDLIFE ASSEMBLAGES
The second step was to develop a list of representative fish and wildlife species for each
habitat type. These lists were designed to be representative, rather than inclusive, in order to avoid
creation of unmanageable matrices. Thus, not every fish, bird and mammal which occurs in
estuarine habitats of the Pacific Northwest is included in these lists, but their feeding mode,
‘reproductive habits, behavior, etc., should be represented on the list by at least one sympatric
species. As a consequence, the assemblages are considered to be composed of “functional
species.”
-------
Design /7
The specific assemblage species were also selected (rather than their functional analogies)
because of the extent of information available on their use of estuaries. In effect, we optimized our
ability to complete the matrices with relevant data. The list of assemblage species (see Appendix
A) was generated during UEMWG discussions, then distributed to estuarine habitat and fish and
wildlife experts in rñanagement agencies and other institutions (e.g., universities), and
subsequently revised based upon the review comments.
CATEGORIZATION OF HABITAT FUNCTIONS
Estuarine habitat functions for fish and wildlife are categorized as (1) reproduction, (2)
feeding, and (3) refuge and physiological adaptation (Simenstad 1987). While there are a number
of additional or supplemental functions (e.g., migration corridors), we felt that these three
functions explained the primary mechanisms.
Within each function, we developed a hierarchy of categories or factors which influence the
outcome of the function (Table 1). For instance, fish or wildlife reproduction can occur
exclusively on a particular substrate or over a restricted tidal range, and can be influenced heavily
by ambient sound, light, temperature, etc. Each of these factors constituted a row in the first
evaluation matrix (below).
For the sake of clarity, we have limited the functions that the habitat serves in supporting
fish and wildlife to direct interactions (Table 1), by which we mean those habitat attributes that
influence fish and wildlife survival rates. Of course, certain indirect functions also contribute to
the production of fish and wildlife populations; for example, primary production by wetland plants
is an ultimate energy source for the habitat as well as for the estuarine ecosystem as a whole
(Simenstad and Wissmar 1985). However, we have excluded total production as a direct function
because fish and wildlife do not depend directly upon total production per se. Functions such as
primary production should be addressed, as fish and wildlife support is in this document, as
discrete functions in their own right (see Discussion).
IDENTIFICATION OF IMPORTANT RELATIONSHIPS AMONG ASSEMBLAGE SPECIES
AND HABITAT FUNCTiONS (MATRIX I)
For each habitat type, the association of the assemblage species (columns) and habitat
function categories (rows) formed an “evaluation matrix.” Again, we turned to technical experts in
resource agencies, asking them this time to rank the importance of each habitat function category
for an assemblage species within their expertise. Ranks were to be assigned as 0 (no relationship),
I (low), 2 (medium) or 3 (high), or as 4 (unknown but believed important). The resulting
compilation of ranks was referred to as Matrix I (Supplement 1, Simenstad et al. 1990). Bear in
mind that at this point in the process the data input originated from only six sources (resource
agencies, universities, and developer/consultants), although the number of experts contributing to
each source’s response to the matrix was considerably higher.
LISTING AND RANKING HABITAT ATmIBUrEs (MATRIX U)
The results of Matrix I were refined to identify specific habitat attributes that were indicated
as being of high importance. All matrix cells (i.e., function category/assemblage species associa-
tions) receiving at least one rank 3 were selected to compose a high priority matrix, called Matrix II
(Supplement 2, Simenstad et al. 1990).
-------
INTRODUCTION/S
Table 1. Hierarchies of functions of estuarine habitats for fish and wildlife used to struc e
Estuarine Habitat Assessment Protocol.
I. REPRODUCTION C. Invertebrates
A Genera1 i. nhi
1. light 2. epibenthic
2. salinity 3. neustonie
3. sound 4. pelagic
4. temperature 1). Vertebrates
5. turbidity !.demersal
6. water/sediment quality 2. water column
B. Elevation 3. neustonic
1. intertidai 4. terrestrial
2. subtidal
3. riparian IlL REFUGE AND PHYSIOLOGY
C. Substrate A. General
l.sediment l.light
2. emergent vascular plants 2. salinity
3.macroalgae 3.sound
4. riparian vegetation 4. temperature
5. turbidity
II. FEEDING 6. water/sediment quality
A. General B. Physical complexity
I. carrion 1. bathymetric features
2. detritus 2. horizontal edges
3. graveling 3. vertical relief
4. light 4. water movement
5. salinity C. Biological complexity
6. sound 1. macron
7. temperature 2. emergent vascular plains
8. turbidity 3. submergent vascular plants
9. water/sediment quality
B. Plants
1. rriicroalgae
2. macroalgae
3. emergent vascular
4. submergent vascular
For each matrix celi (habitat function and assemblage species) identified as high priority,
the same UEMWG participants and their colleagues were again asked to list and then, using the
same ranking system, rank the function category/assemblage species relationship, but this time
listing specifically the attributes of the habitat that accounted for the acknowledged high function.
Thus, compilation of the responses to Matrix II resulted in a new list: the attributes of estuarine
habitats that were considered important determinants of fish and wildlife use.
-------
Focus and Directions /9
LITERATURE REVIEW OF HABITAT REQUIREMENTS OF ESTIJARINE HABITAT ASSEMBLAGE
SPECIES
During azid after the period of Matrix 11 evaluation, an independent search was conducted
through the scientific literature for basic habitat requirements of the assemblage species. Particular
attention was giverito those that had received no input or had received ranks that indicated high
importance but with no substantiation. l’his search was conducted primarily through a
computerized query (using the Compact Cambridge retrieval system) of the Aquatic Sciences and
Fisheries Abstracts (ASFA) and Life Sciences Collection (LSC) installed on compact disk and
available in the University of Washington library system. Retrievals were made using the scientific
binomial and common names of the assemblage species.
The literature citations were printed as a bibliography and the titles and abstracts were
scanned to select those citations specific to estuarine habitats. Citations that were relevant were
then examined in tow to extract any information that identified attributes of estuarine habitats as
important determinants of the assemblage species’ use of that habitat. Those selected citations
(Supplement 3, Simenstad et al. 1990) were added to the Matrix II database.
ATrRIBUTE DATA QUESTIONNAIRE
All attributes receiving moderate or high ranks in the Matrix 11 survey were chosen as the
basis of the Wetland Attribute Assessment Questionnaire. Together with the information gathered
from the parallel literature search (above), these attributes formed the criteria upon which the
Protocol was subsequently structured. The questionnaire was sent to more than 200 habitat
specialists; the mailing list was compiled using predominantly the Resource Guide to Wetland
Scientists of the Pacific Northwest (Washington Department of Ecology 1988), and was
augmented by a review of the contemporary literature on estuarine ecology in the Pacific Northwest
and by our own familiarity with the researchers working in the region. It requested docwnented
information about these attributes, and it also solicited information on (1) procedures and sampling
designs the investigators had used to measure the attributes, (2) descriptions and comments on
idealized sampling designs, (3) expected values, (4) data formats, and (5) published sources of
these data.
The survey was conducted from the perspective of natural estuarine habitats common to the
Pacific Northwest, and especially to the sub-estuaries of Puget Sound that were the primary focus
of the UEMWG discussions. Despite the fact that the estuarine habitat mitigation and restoration
being considered by this group was occurring predominantly in disturbed, highly modified habi-
tats, the UEMWG determined that the functional relationships identified in the protocol develop-
ment process should represent the optimum function of estuarine habitats. While it was recognized
that habitat function in an urbanized estuary might be highly contingent upon external factors such
as water quality or fish and wildlife population levels, the UEMWG considered the maximum
potential function of a created or restored habitat to be the primary objective. This was one of the
principal reasons for basing the Protocol on characteristics of the habitat that would enhance fish
and wildlife urili,2tion, rather than on an assessment of fish and wildlife occurrence and abundance
per Se. The results of the questionnaire are included as Supplement 4 in Simenstad et al. (1990).
REvIEw WORKSHOP
With the information received and compiled from the completed Attribute Data
Questionnaires, a rough draft Protocol was prepared for review by a larger body of estuarine
scientists in the region. The review took place at the Estuarine Wetland Restoration Monitoring
Protocol Workshop, which was held at Fort Worden, Port Townsend, Washington, on April 16-
19, 1989. Thirty-eight estuarine scientists, resource managers, consultants, and developers
-------
INTRODUCTION /10
attended. Their task was to critically review both the process that shaped the Protocol “- - me
information that the draft Protocol contained. Most of the workshop sessions involve b’
step review of the forrnulative products of the Protocol’s development, i.e., the estuam ,.
assemblage species, and the results of Matrix I and Matrix if. Information from the AltribULc t
Questionnaire was available in the distributed copies of the draft Protocol, and the attendee” wt
encouraged to correct or augment these data.
The revisions to the Protocol that resulted from the workshop revealed two substax. 4
problems: the lack of input from experts with wetland and manne mammal expertise, and “ l
of an assemblage approach to emergent (marsh) plants. Both of these topics were address i .
later meetings with several of the region’s experts on wetland and marine mammals and orL
estuarine marsh vegetation, and those sections of the Protocol were revised. In the case of
emergent vascular plants (attributes), their association within discrete assemblages and the
distribution of these assemblages according to salinity, tidal elevation, exposure, soil type,
other plants were incorporated into the Protocol structure.
UTILITY AND LIMITATIONS
Although caveats surrounding the application of the Protocol have been mentioned
throughout this introduction, we should reinforce the conditions for which the Protocol is in
and in what cases we consider it inapplicable.
1. Restricted applicanon. The Protocol is explicitly restricted to only fish anä wildlifi
functions and to only estuarine habitats of Puget Sound. It may be more broadly
applicable, with certain reservations, to estuaries outside Puget Sound, but it is not
applicable to tidal fresh water, palustriste, and other freshwater habitats.
2. Based on function. The habitat attributes recommended for measurement are, t
process used to develop the Protocol, indicators of potential fish and wildlife su
The advantage of this approach is that it can be applied across habitats (is not depen
upon particular fish and wildlife species per se) and is probably a measure of overali
community function because of the interactions among fish and wildlife and other
organisms in the community.
3. Augments, rather than supplants, other assessment procedures. The Protocol is intended
to meet the need for additional quantitative information that can be standardized acre
restoration and mitigation efforts. It does not assess the abundance of target fish anc
wildlife populations or their activities in estuarine habitats, nor does it attach a relative
“value” to the habitat. Therefore, the Protocol should be considered as only one tool
available among the many needed to effectively assess the function of estuarme habit
4. Is deficient in terms of physical attributes. Although it was initially designed to include
physical anributes (e.g., sediment structure, salinity range), the Protocol lacks a quar
cation of physical characteristics that are important to fish and wildlife reproduction,
foraging, or refuge/physiology. We found that such information was basically
unavailable, and we entreat natural resource scientists to address this gap.
5. Is not landscape-oriented. The Protocol is based upon attributes exclusively within a
habitat This falls well short of considering the linkages between habitats and across
ecosystems that should be considered to maximize the success of estuarine habitat
restoration and mitigation projects and improve the overall function of estuarine
ecosystems.
-------
Utility and Limitations / 11
Approaches to these deficits in the Protocol are described in more detail in the Discussion
section.
AFFER THE PROTOCOL
The potential for the Protocol to enhance estuarine habitat management will not be realized
without application. We argue in the Discussion that, as with all protocols, its success resides in
the accumulation of consistent, standardized, repeatable, and valid data. This needs to be accom-
plished by two methods: (1) application by resource agencies and environmental consultants in the
process of addressing permit assessment and monitoring requirements; and, (2) explicit testing of
the Protocol assumptions and methods in a purely scientific activity.
In addition, the need for long-term estuarine habitat reference sites is paramount to
continued monitoring of the natural, seasonal, and interannual variability and range in Protocol
parameters. These studies will verify both the concepts and the technical information embodied by
the Protocol. With verification, revisions and additions to the attribute lists will ensure that the
Protocol is biologically comprehensive and, we hope, will expand the technical information on
physicochemical attributes.
-------
USING THE PROTOCOL
The following sections describe recommended procedures for monitoring the function of
estuarine habitats in supporting fish and wildlife in the Puget Sound region. Definitions and lists
of fish and wildlife species and their associated attributes precede the protocol for each habitat such
that the user can “access” it through a variety of topics, e.g., from the perspective of habitat,
assemblage species, or attributes.
The protocols themselves are organized by attribute group, i.e., by those attributes which,
because of location, behavior, etc., can be measured by similarprocedures. Thus, the recom-
mended protocol for monitoring parameters for each attribute group is applied across a number of
habitats, but the list of specific attributes is unique for each habitat. An example of accessing the
Protocol is included at the end of this section to acquaint the user with the process.
SELECTION OF ATTRIBUTES AND PARAMETERS
The process of selecting specific monitoring protocols requires you to answer two
questions: (1) what is appropriate to the habitat(s) of concern? and (2) what is applicable to the
specific habitat restoration/mitigation issue? This Protocol provides monitoring procedures for
estuarine habitats as an assessment of the habitats’ utility to the unique conununiry of fish and
wildlife that would potentially use specific restoration sites. We feel that these attributes are
appropriate for measuring fish and wildlife support at the community level because the habitat
assemblage species were chosen to be broadly representative of fish and wildlife use in each
habitat. In addition, most of the attributes are important to more than one particular fish or wildlife
species. Thus, the optimum approach to using the Protocol is to assess all the attributes relevant to
the habitat(s) of concern if the desire is to gain a complete assessment of the “quality” of the
estuarine habitat as a community.
Many constraints impinge upon your ability to measure the full spectrum of recommended
parameters, even in the best of circumstances. In many cases, funding limits the number of
measurements you can make and samples you can process, and often some parameters are not
particularly relevant to certain sites. Thus, monitoring programs applicable to particular restoration
or mitigation sites normally consist of a subset of the applicable parameters. Selection of which
attributes and parameters to monitor presumably is the decision of the negotiating parties, i.e., the
developer and their consultants, resource agencies, tribes, environmental groups, etc.
This process, the policy of implementing the Protocol, cannot be determined with this
document. We have, however, organized in hierarchical order the parameters of the chosen
attributes that should guide the decision process: (1) minimum, those parameters characterizing an
attribute group that should be monitored under all circumstances; (2) recommended, parameters
that provide an adequate measure of attribute status; and (3) preferred, those parameters that
provide an optimum, irrefutable assessment of the attribute and which should be used whenever an
attribute is to receive special attention in mitigation assessment.
In addition to this hierarchy of monitoring parameters, we recommend sampling units,
periodicity and frequency, methods and statistical considerations (e.g., sample replication) . These
are literally recommendations, because there will always be a need to use alternative methods and
alter sampling designs for untypical sites and situations. Therefore, we have described valid
monitoring procedures for such circumstances (see Considerations Common to all Habitats,
below).
-------
Selection of Attributes and Parameters! 13
In sum, the Protocol is to used first to generate a list of the appropriate attributes to assev
and, second, to set priorities on specific parameters and methods that provide a measure of eaci
attribute.
SAMPLING DESIGN
The first thing you should do before searching for specific protocols is read the Considera-
tions Common to all Habitats section on Sampling Protocols that apply to all habitats (Common to
All Habitats section). This section is consolidated because (sampling) designs for assessing estu-
anne wetland and nearshore habitats are basically the same for all habitats, regardless of specific
attributes. We urge you to become familiar with the principles of applying the Protocol using a
valid sampling design before you proceed to the selection of the specific attributes.
SELECTION OF APPLICABLE PROTOCOL
Figure 2 illustrates the variety of methods by which users can locate the protocols that
pertain to their objectives or situations. if you already know the specific assemblage species or
attribute with which you are concerned, the fastest way to find the appropriate protocol is to use the
Index. If, however, the interest is unspecific, you can access the appropriate protocols through the
following hierarchy:
ESTUARINE HABITAT
From the descriptions of the eight estuarine habitats (see following section), select those
that are applicable to your case or intent. Examine each of these to determine the appropriate
estuanne habitat(s). Next, consult Appendix A—Habitat-Specific List of Assemblage Species—to
determine the fish and wildlife species that constitute the representative assemblage for the habitat
Appendix B—Habitat-Specific List of Attributes and Associated Habitat Functions—lists all the
attributes associated with specific fish and wildlife assemblages. Using these two lists, you can
determine which protocols are applicable to most situations.
ASSEMBLAGE SPECIES
If you are specifically interested in the attributes associated with a particular assemblage
species, use Appendix B to directly determine the attributes that are associated with the specific fish
and wildlife species, and proceed to the appropriate protocoL Note that fish and wildlife species
may occur in more than one habitat If you are unable to find the species of concern in either Ap-
pendix A or Appendix B, check the Index. If it is not listed, consider examining the Assemblage
Species for similar species; they may have been listed as ecologically analogous to the unlisted
species.
ATrRLBUTE OR ATrRIBUTE GROUP
You can also directly locate specific estuarine habitat attributes by using the Index to locate
it within the Attribute Group-Specific Protocols. Unlike the case of the assemblage species, an
attribute occurs only once among the Attribute Groups, e.g., each attribute has only one protocol
description.
REFERENCE MATERIAL
All literature citations used for the body of this report are included in the Literature Cited.
Literature citations which contain the information about the importance of the attributes to the
-------
USING THE PROTOCOL / 14
Figure 2. Decision tree associated with accessing the Estuarine Habitat Assessment
Protocol on the basis of habitat, fish and wildlife assemblage species, or estuarine habitat
attribute.
No
-------
Sampling Design, is
esruarine habitat assemblage species are listed in the Supplemental Bibliography (Supplement 3,
Simenstad et al. 1990). Data and other information on each attribute, generated from the Attribute
Data Questionnaire, are included as Supplement 4. Descriptions of the individual attributes are
included as Supp ment 5, and literature citations used for these descriptions, or recommended for
further information, are cited in Supplement 6.
HABITAT DESCRIPTIONS AND EXAMPLES
For the purposes of the Protocol, we have adopted a comprehensive definition of “estuarine
wetlands and nearshore habitats” and have incorporated three aquatic habitats which are not
wetlands technically but which are integrally associated with wetlands. ProtocoLs were developed
for these associated habitats because fish and wildlife commonly move among habitats, and
therefore it is usually impossible, and undesirable from an ecological standpoint, to ignore
interactions between estuarine wetlands and adjacent habitats. Other associated habitats (e.g.,
riparian, tidal freshwater) that we have not included certainly serve similar functions, but the we
lack adequate information about ecological interactions between these terrestrial habitats and the
estuarine habitats.
In general, we have based our habitat types on the classification of Cowardin et al. (1979),
in part because it includes both vegetated and unvegetated habitats. This recognizes that some
types of habitats lack vascular plant vegetation (e.g., mudflats, sandflats, rocky shores, gravel
beaches, sand bars) (Federal Interagency Committee for Wetland Delineation 1989). Fish and
wildlife typically use unvegetated habitats and the deepwater or unvegetated shallows adjacent to’
wetland habitats. In certain cases, such as defmition of vegetation types, we have adopted some
elements of the Dethier (1990) modification of the Cowardin classification system in terms of
dominant functional groups.
All habitats addressed by the Protocol are estuarine; that is, they are usually semi-enclosed
by land but have open, partially obstructed, or sporadic access to the open ocean, and occur where
sea water is at least occasionally diluted by freshwater runoff from the land (Pritchard 1967). The
upstream/landward limit to this system is normally defined as the point at which the concentration
of ocean-derived salts measures less than 0.50/00 during the period of average annual low flow,
and the seaward limit by an imaginary line closing the mouth of a river, bay, or sound (Cowarclin
et al. 1979). In the Venice System for the classification of brackish waters, these habitats would
usually occur in the oligohaline (5-O.5°/oo), mesohaline (18-5°/ ), and polvhaline (3O-18°/ )
salinity zones, which together encompass the mixohaline (30-0.5°Ioo) zone (McLusky 1981).
Accordingly, these habitats are generally not defined as occurring in either limnetic (<0.5°/o ) or
euhaline (40 3O0/oo) salinity zones.
If the reader has some question as to whether a particular habitat meets the statutory
defmition of wetland, they should consult Cowardin et al. (1979) for more detailed definitions or
the Federal Wetland Delineation Manual (Federal Interagency Committee for Wetland Delineation
1989) for the definitive procedure to make this determination.
EMERGENT MARSH
Emergent marshes occur as intertidal shores of unconsolidated substrate that are colonized
by erect, rooted, herbaceous hydrophvtes , excluding mosses and lichens (Cowardin et al. 1979);
perennial plant vegetation dominates most of the growing season in most years. Sediments vary
from compacted clays and fine, unconsolidated muds to a mixture of coarse sand and gravel.
Where the topography permits and extensive diking and channelization have not occurred,
emergent marshes tend to form conspicuously in the mixing region, where tidal energy generates
flood tide periods with high settling of suspended sediments.
-------
USING THE PROTOCOL /16
Except in the most industrialized estuaries, emergent marshes occur prominently in the
deltas of the major rivers entering Puget Sound and are usually present at the margins (“fringing
marshes”) of other..estuarine habitats in the region. Prominent estuarine emergent marshes can be
found on the deltas of the Skagit, Stilliguarnish, Snohomish, Nisqually, and Skokomish rivers.
MUDFLAT
Mudilats are intertidal shores not vegetated by macrophytes and with unconsolidated
sediment particles smaller than stones, predominantly silt (40 to 8 ; 0.0625 to 0.00391 mm
particle diameter) and clay (80 to 120; 0.00391 to 0.00024mm); the substrate usually has high
organic content, and anaerobic conditions often exist below the surface (Cowardin et a!. l979 .
This habitat occurs over low gradient shorelines, often encompassing broad expanses (>1 kin 2 ).
In Puget Sound, mudflats often occur between the vegetated, emergent marsh habitats and
the MLLW line along channels, and at the delta foreshores of major rivers. Prime examples
include the mudfiats of Skagit Bay and Nisqually Reach.
SANDFLAT
Sandflats are intertidal shores that are not vegetated by macTophytes and have unconsoli-
dated sediment in which particles smaller than stones are predominantly sand (-1 to 40; 2.0 to
0.074 mm). They occur as low gradient flats and bars where the substrate material is exposed to
sorting by wave and cuirent action. In the Pacific Northwest, the sand particles originate primarily
from fluvial, rather than marine, sources.
Sandflats are often found along the more exposed boundaries of mudflats in estuarine river
deltas, particularly adjacent to the river channels, as typified by locations in the outer, foreshore
areas of the Nisqually, Skokomish, and Skagit river estuaries. Moderately exposed embayments
without measurable riverine input, such as Birch Bay in northern Puget Sound, also have extensive
sandflat habitats. Elsewhere, sandflats often form as 50—100 m benches along the moderately
exposed, high bank shores of the Sound, as in the Saratoga Passage area between Whidbey and
Camano islands.
GRAVEL-COBBLE
These habitats are intertidal shores which have substrates composed of a mixture of cobble
(-80 to -70; 256 to 76 mm) and gravel (-70 to -20; 76.2 to 4.76 mm). Owing to wave and current
action, and seldom as flats, the habitat tends to be formed as beaches and bars.
Gravel-cobble beaches tend to be distributed in the more exposed regions of embayments
and along the margins of Puget Sound. Thus, most of the central basin of the sound and the
shores of Hood Canal would be classified as gravel-cobble habitat , and prominent monotypic
locations include headland points such as l’hree Tree Point, Alki Point, West Point, and Point-No-
Point. This habitat also persists in many of the more developed sub-estuaries of Puget Sound,
such as Elliott and CQmmencement bays, because it was the least desirable habitat for dredging and
filling activities.
EELGRASS
This habitat consists of intertidal and shallow subtidal, unconsolidated sand to mud shores
vhich are colonized by rooted vascular angiosperms (seagrasses) of the genus Zostera. Two
1 Units of the phi grade scale; a logarithmic transformation of the Udden grade scale of sediment particle size
categories based on the negative log to the base 2 of the particle diameter in millimeters. For example, between 40
and 80 is silt, and between 80 tO 120 is clay.
-------
Habitat Descriptions and Examples / 17
species are prominent in the Pacific Northwest: Zosrera marina, the endemic eelgrass, and Z.
japonica, an introduced congeneric.
Undoubtedly the largest contiguous expanse (3500 ha) of eelgrass habitat in the Puget
Sound trough occurs in Padilla Bay, within the boundaries of the Padilla Bay National Estuarine
Research R erve. Other prominent intertidal flat eelgrass habitats include many of the pocket
estuaries along Hood Canal, e.g., Duckabush and Dosewailips river deltas. Throughout most of
the rest of Puget Sound, ecigrass (Z. marina) tends to form a 2—10 m band along the lower edge of
the intertidal. Further descriptions of the characteristics of eelgrass habitats can be found in the
excellent synthesis by Phillips (1984).
NEARSHORE SUBTIDAL SOFT BOITOM
The nearshore subtidal soft bottom habitat occurs in the shallow subtidal (<20 m) portion
of estuaries, usually in the channels and the shallower portions of embayments. The bottom is
unconsolidated gravel to silt, with no or minimal relief.
NEARS HORE SUBTIDAL HARD SUBSTRATE
Nearshore subtidal hard substrate habitats are those rare outcrops, erraiics, and other rock
formations that are scattered around the predominantly unconsolidated shoreline of Puget Sound.
Such habitats are usually rare within discrete estuaries, where the heavy sedimentation has often
resulted in complete burial since the last glaciation; they persist, however, where waves and 1
cunents maintain exposure of rocks and rock outcroppings. They are notable as being aniongthe
rare estuanne habitats in which subtidal macroalgae (seaweeds and keips) can colonize and persist.
WATER COLUMN
The water column habitat is that portion of the estuarine subtidal not associated with the
shore or bottom. This does not include the benthic boundary layer, which we include in bottom
habitats, but does include the neustonic layer at the surface.
EXAMPLE USE OF PROTOCOL
An example of accessing the specific protocols illustrates these different approaches.
Consider a situation where an emergent marsh restoration project is to be assessed. The first task
would be to verify that the Protocols definition of an emergent marsh matches the habitat desired
by reviewing the Habitat Descriptions and Examples (pp. 15—17). if the Protocol’s definition of
an emergent marsh is appropriate to the situation, the next step might be to examine the list of
species included in the emergent marsh fish and wildlife assemblage, listed in Appendix A. If the
decision is to assess the restored habitat relative to the entire assemblage, you would select all of
the applicable attribute groups from the sampling protocols section (pp. 40—112). For the
emergent marsh habitat, this would include the following functional groups: rooted vascular
plants, benthic macroalgae, benthic microbiota, surface epifauna, sedentary infauna, epibenthic
plankters, pelagic zooplankton, neustonic drift invertebrates, evasive macroepifauna, sedentary
fish, motile fish, avifauna, and herbivorous mammals.
A second, alternative approach would be to access the Protocol from the standpoint of
selected species from the emergent marsh fish and wildlife assemblage. You would then examine
Appendix B, which lists the attributes associated with each of emergent marsh assemblage species.
For instance, choice of chum salmon and cutthroat trout as species of concern would involve
twelve distinct attributes, three of which are common to both fish species (e.g., Chironomid
funid.J, Eogammarus confer4colus, and Neomysis mercedis). Examination of these attributes in
-------
USING THE PROTOCOL / 18
the Index would reveal that the sampling protocols for assessing all twelve attributes are found
under five functional attribute groups: rooted vascular plants (pp. 40-45), benthic microbiota(pp.
49—5 1), epibenthic plankters (pp. 69—74), neustonic and drift insects (pp. 80—82), and motile fish
(pp. 98—105).
Finally, a user might wish to access attribute-specific sampling protocols directly if they
already know the attributes or functional attribute groups of interest For instance, suppose that the
gammarid amphipods Corophiwn spp. are of interest. Not only are Corophi urn spp. associated
with the emergent marsh habitat, but also the mudflat, sandflat, and eelgrass habitats, and they are
important attributes of at least 12 fish and wildlife species that utilize these four habitats. The
Index will direct the user specifically to the sampling protocols for epibenthic plankters (pp.
69—74).
-------
SAMPLING CONSIDERATIONS COMMON TO ALL HABITATS
A piimazy goal of the Protocol is to promote both scientific stojiciency and adequacy in the
assessment of fish and wildlife support in restored or constructed estuarine habitats. By
sufficiency, we mean that enough information about the habitat must be gathered to adequately
characterize the various support functions. Adequacy addresses the requirement for data of high
quality, which relates to the way it is collected and analyzed.
By identifying the attributes of estuarine habitats, the Protocol is intended to encompass
measurement criteria indicative of ecological function. Scientific adequacy, however, depends
upon the quality of the sampling design, i.e., of the procedures and methods used in making those
measurements. An adequate sampling design always incorporates three principal components of
scientific quality: (1) repeatability in terms of the potential to be exactly repeated, (2) reliability as
the quality to sustain scientific confidence, and (3) validity because it is based on precedence and
evidence (National Academy of Science 1989). In practice, we have adopted as protocols pro-
cedures that represent the current state of good practice as defined by their ability to pass peer
review.
We have addressed sampling in estuarine habitats as methodologies which, although they
often vary in exact design depending upon the habitat type, are determined by a common group of
rules based on accepted concepts of sampling theory and the combined experiences from previous
scientific studies. You will note that, although we generally recommend one or two specific
sampling procedures, the Protocol contains information on alternative methods or procedures. The
diversity of estuarine habitats and attributes will always present situations where prescribed
procedures are insufficient, and the alternatives represent possible solutions to those situations.
We stress that the most important consideration is that sampling conform to rules and precepts that
provide quantitative, precise information which is compatible with the Protocol.
The following section is a review of sampling theory and design, and one that we consider
particularly appropriate to monitoring projects for estuarine habitat restoration. Wetland investi-
gators familiar with biostatistics may consider it obvious and prefer to move to the next section.
We encourage the reader, however experienced, to review this section because it will explain in
part the statistical basis behind many of the Protocol recommendations. If you are not familiar with
statistical concepts or have never applied them to field situations, we strongly advise using the
Protocol as a guide in consultation with a biostatistician before implementing a sampling design.
SAMPLING DESIGN IN ESTUARINE HABITATS
Sampling estuarine habitats is usually necessary, as most habitats are too complex to
monitor in their entirety. Proper sampling design minimizes the effect of inherent variability, or
“noise,” in the monitoring parameters that conceals real differences in the systems under study. It
is a rare habitat that is so small or uncomplicated that every characteristic, or sampling unit , can be
measured in tow, i.e., by statistically measuring (censusing) the total populations . One of the
dominant traits of most estuarine habitats is that the distribution of physical, chemical, and biolo-
gical attributes are complex over space and time. Thus, although sampling estuarine habitats to
provide an accurate picture of their status and quality is a difficult task, it is required if the objective
of estuarine habitat restoration or compensation is to be achieved.
Natural variability is inherent in most attribute parameters in estuarine habitats. In addition,
most sampling techniques used in research produce samplingvariabilitv , which is often unrelated
to, and in addition to, the inherent variability. If extreme, both kinds of variability can obliterate
any distinction of real differences among populations. A rigorous sampling design should ensure
-------
SAMPLING CONSIDERATIONS COMMON TO ALL HABITATS /20
that errors associated with sampling can be reduced to the point that real differences in populati
can be detected with acceptable confidence.
Adoption of a sampling strategy requires attention to what Stuart (1984) terms the
“credentials’ of a sample to appreciate how much our interpretations depend upon them. Essen-
tially, our bility to detect differences in parameters, attributes, and estuarine habitats overall will
depend entir&Iy upon our approach to sampling the habitats. In addition, sampling to determine th
success or failure of estuanne habitat mitigation or restoration includes the cost of misrepresenting
the status or quality of a habitat, an ominous potential for error when your decision could result in
the loss of acres of rapidly disappearing natural habitat or many thousands of dollars if the
mitigation is considered a failure.
As the most important credential, samples must be reliable, precise,free of bias. Secondly
both the sampling design and the samples must be reproducible, i.e., systematic, a specific ob-
jective of the Protocol. In addition, adoption of particular sampling designs, requiring specific
statistical tests, will require that the data meet certain assumptions, such as independent and normal
error distribution, homogeneity of variance, additivity of effects. It is beyond the scope of the
Protocol to discuss the concepts of sampling theory that impose these constraints. We strongly
suggest that readers who are sampling estuaririe habitats read a pertinent technical reference on
sampling design, such as Cochran and Cox (1957), Poole (1974), Green (1979), Scheafer ct al.
(1979), or Clarke (1980). Stuart (1984) provides a particularly lucid explanation of the objectives
of sampling.
Achieving acceptable sampling credentials, however, is not the only constraint on es*qarine
habitat sampling. Proper sampling requires considerable time and effort. Thus, the dilemma: how
do you balance sampling rigor with the resources at hand? How do you distribute the sampling
effort and intensity to minimize the damage that destructive methods will cause to the site? The
following is intended to provide some guidance in the selection of sampling designs within these
constraints.
SAMPLING STRATEGIES
The first question should always be: What is the question? For instance, there is a big
difference in sampling strategy and statistical evaluation if the question is “Can we quantitatively
typify emergent marshes in an estuary?” or it is “Is this particular restored or created emergent
marsh (e.g., one at a development site) functionally equivalent to a natural emergent marsh?” The
former question requires characterizing the spectrum of emergent marshes occurring in the estuary.
Assuming that the “developed” and “mitigated” habitats are located in the same general environ-
mental conditions (e.g., geography, energy level) of the estuary, the second, more specifIc
question is a simpler situation of comparing the two specific habitats. However, placement of the
mitigation habitat at a significant distance from the developed habitat (often called “off-site”
mitigation) violates this assumption and implies the former, more complex and estuary-wide
question.
Random sampling is the most statistically valid approach to characterizing most complex
habitats. On most scales, estuarine habitats tend to be mosaics of different substrates, plants,
animals (sometimes termed microhabitats) that are distributed in a nonrandom (e.g., aggregated,
clustered) manner. Thus, we are typically applying a hierarchy of questions relative to the habitat
complexity: (1) Is this an assessment of a discrete (isolated) habitat or a contiguous array (encom-
passing a variety of types and locations) of habitat types? (2) If it is a discrete habitat, is it a
complex of habitat types? (3) If it is one habitat type, is it structurally or biologically diverse? In
the case of a negative response to the last question, a simple random sampling design could be
applied to the habitat overall. If, however, there is any pattern to the habitat’s heterogeneity, you
-------
Sampling Design in Estuarine Habitats /21
should consider a modification to random sampling that permits stratification or some other
technique to reduce variability and the required level of replication.
Therefore, the first Protocol rule in developing a sampling design is: Know the habitat you
are proposing to sample. This admonishes the investigators, whether they are the ones doing the
field assessment or not, to conduct a site visit and faniiliarize themselves with the habitats to be
monitored. If the site is confined to one habitat type with no obvious pattern in either structural
(e.g., sediment, tidal elevation, topography) or biological character (e.g., vegetation type or
distribution, polychaete tubes, bivalve or shrimp burrows), a purely random sampling design is
justified. If these complexities are at all obvious, however, it will both advantageous and
statistically proper to use stratified random, cluster, or systematic sampling.
Random sampling
Simple random sampling is defined specifically as the procedure in which “a sample of size
n is drawn from a population of N in such a way that every possible sample of size z has the same
chance of being selected” (Scheaffer et a]. 1979). This dependence upon the mechanism of chance
in selecting a sample, in theory, guarantees freedom from selection bias, the essential item in the
credentials of a sample (Stuart 1984). Random samples should be taken (“drawn” in the statistics
sense) from a population by an intentionally random manner by the investigator. Some sampling
approaches, such as haphazard sarr*pling or representative sampling , have been called random but
are, in fact, still vulnerable to the biases of the investigator who makes these haphazard or
representative selections.
Such selection bias can be both explicit and unconscious. Explicit bias results when an
investigator intentionally avoids spots that are di.fficuh to sample or are “unrepresentative” of the
sampling universe, or suspects that the measurements will be unreasonably low or high, or rejects
locations that are too close to previous samples. Unconscious bias results when the investigator is
unaivare of gradients or other factors affecting a nonrandom distribution of the element (attribute),
such as sampling along a steep intertidal gradient, not knowing that the organisms being counted
are highly clustered within narrow tidal elevations.
The avoidance of selection biases leads to the second Protocol rule in developing a
sampling design: Know the sampling response (attribute) you are monitoring. In the case of
biological attributes, this means having some knowledge of the basic ecology, life history, and
expected distribution in the habitat being monitored. To give a simple example, knowledgeable
investigators do not attempt a simple random sampling program for barnacles on a mixed gravel-
boulder beach when they know that barnacles will be found only on the boulders and only in a
restricted tidal elevation. If, however, the sampling universe (habitat) is defined in a restrictive
case as the barnacle habitat, simple random sampling would be appropriate.
I.n the case of physical/chemical attributes, this means understanding something about their
temporal and spatial dynamics in estuarine habitats. One can use measuring salinity as another
obvious example. In most locations in an estuary, salinity as a single measurement in time is
relatively meaningless because tides, and thus water masses with discrete salinities, flux in and out
of the estuary over mixed diurnal cycles, and freshwater flow during winter and spring discharge
periods mediates the tidal effects.
To avoid the selection bias inherent in haphazard and representative sampling, samples
should be selected methodically using a verified random technique such as a random numbers table
or generator. Thus, the third Protocol rule is: Select samples using a consistent, standardized
technique. Random numbers can be applied over both space and time as long as the assumption of
homogeneity of habitat (actually, the attribute’s distribution Within it) holds. Random numbers are
sets of integers generated so that all ten integers (0-9) occur in approximately equal probability,
with no trends in the pattern of their appearance. Most elementary statistics texts or reference
-------
SAMPLING CONSiDERATIONS COMMON TO ALL HABrFATS / 22
books explain how to use random numbers tables, and most hand calculators and computers h
random number generators.
The process of selecting sampling points within the habitat requires that the investigator
establish some decimally graduated reference, either one-dimensional, such as a transect line, or
orthogonal, such as a grid, which encompasses the population to be sampled. Transects would
normally be utilized to sample elongated habitats, such as fringing marshes, while grids should be
used to sample broadly uniform habitats, such as mudflats. Sampling points are selected by using
the random numbers to locate points along the transect or coordinates on the grid. The number of
sampling points is best determined by a preliminary pilot project, or by precedence (see Replication
section). If selecting samolina elements from a transect, the random numbers should be used to
proportion the sampling locations along the whole transect; e.g., use two-digit random numbers to
select percentage points along its total length.
Stratified random sampling
Stratified sampling is adopted when, based upon supplementary information about the
population, there is any indication that the population is separated into nonoverlapping groups or
strata in which the subpopulations are more homogeneous than the population at large. The reason
for stratifying a sampling design is to gain precision through compartmentalizing the variability;
you can never lose precision by stratifying, and you may gain considerable precision (Stuart
1984). The resulting reduction in within-strata variability can also reduce the number of samples
(replicates) required to maintain the level of precision.
This approach is common in estuaries because estuari.ne habitats tend to be stratified across
a variety of gradients. The most obvious estuarine gradient is that of salinity, but tidal elevation,
exposure to wave and current energy, and many other factors are responsible for habitat strata.
Strata are usually obvious or have obvious manifestations in the plants and animals that have
adapted to narrow physiological, morphological, or behavioral regimens. Thus, the factors
associated with tidal exposure in part produce distinct bands of macroalgae and sessile animals
colonizing hard substrates such as boulders on intertidal beaches or prominent emergent plants in
low versus high elevation marshes.
The absence of visually distinct plant, animal, substrate, or other strata should not,
however, be construed as the lack of stratification in an attribute. For instance, tidal elevation on
an outwardly uniform gravel beach will nonetheless affect the occurrence and abundance of certain
animals living within the substrate whose distribution is highly structured by tidal inundation/
exposure. Epibenthic meiofauna , for instance, whose populations are commonly assessed as prey
resources of juvenile salmon, are improperly sampled as a homogeneous population across broad
tidal zones, because different taxa are actually concentrated along narrow tidal elevation zones.
Biodc interactions, such as grazing/predation and competition, also affect the distribution of plants
and animals and should be considered in recognizing and defining strata. These contingencies
reinforce our second rule of estuarine habitat sampling, in that you should be familiar enough with
the attribute you intend to sample to know the space and time over which it should occur as a
homogeneous population in the habitat.
Once you have legitimate reason and evidence to establish sampling strata, a fourth
Protocol rule should be observed: Clearly specifj your strata. Over some sharp gradients, this
means that precise documentation is necessary, such as verifying tidal ranges of the strata through
surveying or correlating with a local, verified NOAA tide gauge. In other instances, the more
important descriptor may be the biological community, as in a mussel or barnacle band, which can
vary in tidal elevation relative to wave energy.
Although increasing the number of strata incurs a direct multiplicative increase in the cost of
your sampling program, remember that it is preferable to designate more strata than fewer. While
-------
Sampling Design in Estuarine Habitats /23
it is possible to pooi samples from strata that show no significant differences in critical parameters,
it is virtually impossible to stratify your samples after the fact. A statistical stranfication principle is
“maximize precision by constructing strata so that their averages are as different as possible and
their variances are as small as possible” (Stuart 1984).
Once strata have been designated, simple random sampling can be conducted within each
stratum according to the principles described earlier. The statistically “safest” method is to allocate
the samples uniformly across all strata where the strata themselves are uniform in size, i.e., as
uniform sampling fractions. The alternative strategy, of sampling some strata more intensively
than others, i.e., using variable sampling fractions, is not necessarily improper as long as you
know the extent to which you are under- or oversampling the respective strata.
In many cases, there is no option but to establish unequal strata, such as in sampling sparse
patches of eelgrass on an otherwise unvegetated littoral flat. A common sampling strategy then is
that of the proportional allocation method, in which the number of sampling units in each stratum is
proportional to the size of the stratum. A less common strategy, the optimal allocation method, can
be applied when preliminaiy information exists on the sample variability in each stratum. This can
be a distinct advantage because limited sampling resources can be focused on the most variable
strata. But, because there is a critical disadvantage to allocating a smaller fraction to the more
variable strata, it is imperative to have some indication of the sample variation within each stratum,
another argument for a pilot study. With pilot study data in hand, you have a high probability of
increasing your precision at the same or lower cost by adjusting the sampling fraction accordingly;
the common rule is to make the sampling fraction proportional to the square root of the variance for
each stratum.
If time and financial resources exist, the more rigorous test of differences between
heterogeneous habitats would be accomplished with optimum allocation among strata based upon a
pilot study. In lieu of such rare opportunities, however, use of equal strata and uniform sampling
fractions is the most prudent approach.
Cluster sampling
In cluster sampling, groups, or clusters, are selected randomly and all elements are sampled
within the selected clusters. Cluster sampling is an economical modification of stratified random
sampling, useful in those cases where obtaining information from an entire sampling frame is too
costly, or becomes so more costly as the distances separating the sampling elements increase
(Scheaffer et al. 1979). Cluster sampling can also be particularly appropriate to estuarine habitat
sampling because habitats are often composed of a mosaic of patches, such as in eelgrass habitats,
which are natural, convenient sampling units. The primary difference from stratified random
sampling is that not all clusters are sampled, but the whole subpopulation in each selected cluster
is. A critical rule for maximizing precision through cluster identification is that “clusters should be
formed so that individuals (elements) within a cluster are as different as possible” (Stuart 1984).
With this in mind, cluster sampling should be applied with care in estuarine habitat sampling
because obvious habitat clusters tend to be contiguous and, thus, many parameters of attributes
within a cluster may be highly correlated, and contrary to the cluster-formation rule.
Cluster sampling can also be staged; i.e., a random selection of elements can be selected
(“subsampled”) from within a cluster. Theoretically, there is no limit to the number of clusters that
can form a (usually) hierarchical sampling strategy. These strategies are typically hierarchical in
the sense that the first population of clusters is the largest or the most diffuse, the second consist of
smaller subunits, and so forth. There are also instances in which cluster sampling can be
combined with stratified sampling to increase precision at one or more stages of cluster selection,
such that clusters can be stratified at any stage in the design and the final elements to be sampled
can also be stratified. Procedures for determining the overall unbiased estimators of the population
-------
SAMPLING CONSIDERATIONS COMMON TO ALL HABITATS /24
average and associated variance of such complex designs are available from most advanced
sampling design references.
Systematic sampling
Random sampling is essential if the objective is to determine the mean and variance of the
population, which will be the case in most monitoring programs applying the Protocol. However,
there are a few instances in which systematic sampling is often more appropriate; probably the
most applicable situation would be when the objective is to determine attribute characteristics in
relation to position in the habitat. In systematic sampling, a random number is determined for the
first sampling unit and the units that follow are selected at fixed intervals. There are two distinct
advantages —the ease of determining the sampling scheme when there is only one random number,
and the fact that the units are distributed evenly across the population—and two disadvantages—
the standard error of the sample mean cannot be reliably determined, and the sample may be very
biased when the interval between units in the sample happens to coincide with a periodic variation
in the population (Elliott 1977).
The first disadvantage can be negated by adopting a variant of systematic sampling,
called repeated systematic sampling, in which more than one systematic sample is collected
randomly (Scheaffer et al. 1979). Using this method, the variance of the mean *11 can be esti-
mated by using the square of the deviations of the multiple sample means about their overall mean:
AA A
V .t = (N-n/N)(Z [ - .t] 2 /fl [ fl 5 - 1]),
where 5 represents the average of the ith systematic sample and ii equals the number of systematic
samples in the populations N.
REPLICATION
At the heart of any sampling design is replication , because sampling error and the “natural”
variability of estuarine habitats ultimately determine our ability to detect and interpret differences
between pre-development or control habitats and “treatment” (restored, created, or otherwise
mitigated) sites. However, the results of a sampling design can have several interpretations
depending upon whether or not both sample and treatment replications were carried out and to what
extent.
Sample replication
Determination of the number of samples ( sample size . n) is not a trivial problem in any
monitoring program. The sensitivity of the sampling design to detect differences in the populations
sampled depends upon adequate sample replication and, thus, should be the first consideration.
On the other hand, economic and effort constraints are valid reasons for revising the complexity of
the sampling design and rethinking the level of response that is acceptable for the question asked.
Oversampling is a waste of time and money, and too many samples are as hard to interpret as too
few. Therefore, a fifth Protocol rule would be: Determine the oprinusm sample size statistically,
given the purposes and resources of the study and considering the potential to damage the site with
excessive destructive sampling.
The sample size required to satisfactorily test for significant differences is a function of at
least the following factors: (1) inherent variability (as measured by the standard deviation or the
coefficient of variation); (2) the size of the effect that it is desired to detect, or the desired length of
a confidence interval in case of estimation; (3) the level of significance of the statistical test or,
-------
Sampling Design in Estuarine Habitats /25
conversely, the level of confidence attached to a particular estimator, and (4) the level of statistical
power, or the probability of being able to detect a change if one has actually occurred. It is pos-
sible, however, to make some general statements about the required range of sample sizes under
certain conditions.. Assuming normal distributions and equal variances, the standardized minimum
detectable effect (MDE) generally gets smaller as the sample size per group in a two-sample t-test
increases (Fig. 3). For sample sizes over 30, the curve flattens out and there is not much drop in
the MDE; similarly, the curve is nearly flat for sample sizes between 20 and 30. Of course, if the
distributions are non-normal, or the variances unequal, the required sample size for a given MDE
value will be larger.
One of the most important considerations in establishing sampling size is the precision
(error on esthnanon, B) of the population mean which is acceptable for accepting or rejecting the
hypothesis ; the precision is defined as the ratio of the standard error to the mean. A relatively
simple method for estimating sample size based upon this error bound is to set two standard
deviations of the sample mean equal to this error level and to solve for n via the equation for
estimating the error around the population mean (Scheaffer et al. 1979):
B = 2 Ia2/n(N -wr -l)
thus, n = Na 2 /(N-l)D÷a 2 ’
where D=B 2 /4.
The critical problem in this procedure is the requirement of the population variance (a 2 ).
Although this is usually unknown, a sample variance (s 2 ) can be used for a close approximation of
n. This implies that some prior data are necessary for estimation of s 2 , another solid case for
conducting a pilot study! Another, somewhat less acceptable method is to use 1/4 of the range of
the parameter as a gross approximation of & if a normal distribution can be generally assumed.
Bros and Cowell (1987) have recently presented an alternative method for determining
sample size when a minimum detectable difference cannot be specified a priori. Their method
considers both resolving power as a primary factor and expended effort as a secondary factor, thus
presenting a mechanism for evaluating the cost of additional samples versus the increased resolving
power. The standard error (SE) of the mean is used as a measure of the resolving power, and the
optimum sample size is determined graphically as the inflection in the rate of change of SE versus
sample size where this relationship originates from a number of random selections over a range of
sample sizes. These repeated selections can be generated using a “bootstrap” method. A graph
superimposing the mean, minimum, and maximum standard error upon the density and detectable
difference as a function of sample size will provide an opportune illustration of the trade-off
between sampling effort and resolving power. For example, Figure 4 indicates that a sample size
of n=6 to n=7 will permit detection of a 100% change in the densities of an organism (in this case,
an epibenthic zooplankter) at a 95% confidence level. However, there will be no measurable
increase in resolving power >n=25. Detailed explanations and examples of this procedure are
available in the source paper.
However, even if the natural variability cannot be measured exactly, the range of the
coefficient of variation (CV = standard deviation/mean) is often sufficient to compute a trial sample
size. In such a case, for the sake of expediency, historic data might be substituted for a pilot
study. For example, if you are considering change with respect to a background or control mean,
then the change, 8, can be expressed as a relative change with respect to the baseline value, pc:
-------
SAMPLING CONSIDERATIONS COMMON TO ALL HABITATS /26
DETERMINING OPTIMUM SAMPLE REPLICATION BASED ON STATISTICAL RESOLVING POWER
Density (no ni—2)
40 :
33 . 33
30
—. — S.C. m i
• 20 • 20 S.C.S . I
D t. 0lf .
0
‘5 -- --
- I±+f-H- I- lt ( (lilt 1(1111 III Ft (II I I III 0
Somple Size
Figure 3. Example of Minimum Detectable Effect (MDE) as a function of sample size for three
levels of power for a two-sample t-test at 5% level of significance (Source: L. Conquest, Center
for Quantitative Science, Univ. Washington, Seattle, WA).
6 a 6
6. . . a. .
where is the re!aave change from baseline, is the coefficient of vanation around the baseline,
6. .
and —is the MDE in standard deviations. One may plot, for example, the lowest required CV
required to detect a 50% difference between two population means as an increasing function of
sample size. Other examples showing power calculations with only a range value as a guess for
the CV may be found in Conquest (1983).
Treatment replication
The variation among plots, habitats, or sites that receive the same “treatments” is evaluated
through treatment replication. Most habitat restoration or mitigation situations will not allow
treatment replication because the projects are seldom large enough to allow separate restoration or
creation of the same habitat within the same site. Restoration and creation of habitats at different
sites could conceivably be considertd replicates, but only if there were convincing evidence that all
other factors were constant among the different sites—probably an impossible condition to meet.
-------
Sampling Design in Estuarine Habitats /27
E
(I )
-S
c’J
E
E
w
I
Number of Samples Per Group
Figure 4. Example of mean, minimum, and maximum standard error, and detectable differences
and density of organisms as a function of cumulative sample size (number of replicates).
Thus, in most situations, monitoring for the purpose of mitigation evaluation is limited to the
comparison of two samples.
It should be remembered, however, that this implies statistically that the question “Does
this mitigation design for restoring/creating this habitat provide values of these parameters equal to
or greater than the development or control site?” cannot be answered because there is no treatment
replication to provide a variance estimate; the assessment of the design applies only to this
particular case. In a rigorous sense, this question can be answered only by multiple application of
the same u eanuient (i.e., restoration/creation design) in more than two estuaries with all other
conditions held equal. Thus, until such broad-scale experiments are conducted for a variety of
habitat restorationjcreation designs, in a statistical sen.se, assessment of the outcome of every
mitigation project must be conducted by monitoring.
SAMPLE DIMENSION
The total number of sampling units in a population depends upon the relationship between
the area of the population (the total sampling area) and the area of the sampling unit (the sample
dimension) (Elliott 1977). The sample dimension basically affects the sampling efficiency, the
relative sampling effort required to give estimates of equal precision over the total sampling area.
In general, most sampling theorists conclude that a small unit is more efficient than a larger one
when the dispersion of a population is contagious because: (1) more small units can be taken for
40
.
0
0 10 20 30 40
-------
SAMPLING CONSIDERATIONS COMMON TO ALL HABITATS /28
the same amount of labor; (2) statistical error can be reduced by a sample of many small units,
which has more degrees of freedom than a sample of a few large units; and (3) a sample of many
small units is more representative of the habitat than a few large units. Noncontagious
populations, however, impose the problem of scaling the sampling unit to the distribution, such as
the dimension of recognizable patches.
In practice, the sample dimension is ultimately determined by the attribute being measured.
Size, abundance, distribution, and motility of the attribute are the primary considerations. Obvi-
ously, a sample dimension must be scaled for the size of the attribute. For example, the dimension
required to sample kelp plants (probably 1 in 2 ) is going to be larger than that required to sample
diatoms (1 cm 2 ). Density, distribution, and motility can be considered in a similar sense.
Attributes that are numerous and immobile, such as barnacles or small plankton, can be sampled
reliably using a much smaller sample dimension (0.25 in 2 ) than those that are less numerous and
more evasive, such as fish or active macroinvertebrates (e.g., 100 in 2 ). In addition, the smaller the
sample dimension, the proportionally greater the sampling error at the edge of the unit. This effect
can be additionally intensified when dealing with evasive animals, which are more likely to avoid a
small sampler than a larger one.
Of course, field investigators always want to sample as many attributes as possible with the
same sample in order to optimize sampling effort. In this case, the larger sample dimension will be
required, but the effort required to measure the more numerous attributes will be intensive. A
compromise design can often be developed by nesting sampling units. For example, large benthic
samples can be obtained from large dimension samples, which are sampled in totality for large or
raze attributes but can be subsampled by a smaller sampling unit for the more evasive, contagious
attributes.
In the section on sampling protocols, we have attempted to recommend sample dimensions
that are most appropriate to the attributes within each of the attribute groups. Where multiple
attributes can be sampled in the same sampling unit, any subsampling strategy that might increase
efficiency is also described. However, if there is any question or there is a lack of precedence in
the scientific literature, we encourage you to test statistically the efficiency of the sample dimension
to ensure independence of your statistical analysis from your sample size. One such method would
be that proposed by Goodall (1961, 1973), which recommends that the minimum area should be
“that of a square with the side equal to the distance at which the variance between samples ceases to
be a function of their spatial separation”; alternatively, a similar rule might be applied to decreasing
the sample dimension until it is much smaller than the scale of spatial pattern (Green 1979).
A final, sixth Protocol rule concerning all aspects of establishing and implementing your
sampling design: Docwnent all procedures completely and maintain active notes of the mod4fica-
nons to any of the original procedures that had to be made in the field at the time of sampling.
STATISTICAL STRUCTURE
Inherent in the application of the Protocol is the intent to compare the resulting parameters
against a benchmark of some kind, presumably a “control,” the habitat proposed for development,
or an established reference site. To perform this “control-treatment” comparison in an exact
manner, statistics are generally used to provide unambiguous interpretation of the results by testing
their significance. The use of biostatistics to evaluate natural biological populations is an elaborate
scientific discipline in itself. Determination of which specific statistical method is appropriate, and
how to apply it, can be obtained by consulting standard biostatistics texts such as Zar (1974),
Sokal and Rohlf (1969), and Snedecor and Cochran (1980). We herein only emphasize several
important basic concepts which should guide the user of the Protocol in designing their monitoring
program for statistical application.
-------
Sampling Design in Estuarine Habitats /29
Field biologists all too often wait until they have collected a suite of data to determine what
statistics they need to use. As a result, their usually astute intuitive understanding about what is
going on in the natural environment is often compromised by their inattention to how to illustrate it
statistically. The application of statistics should depend upon the question, or hypothesis being
asked. In almost every case, a hypothesis must be posed in order for statistical tests to be applied.
The most acceptable form of hypothesis is the a priori null hypothesis (Htj), which can never be
accepted but can be rejected with known risks of error in doing so. This is to say that, while you
can legitimately reject the hypothesis that there is no significant difference between Habitat A and
Habitat B, you cannot say with any known error that they are the same. A cardinal rule is Null
hypotheses must befalsifi able; that is, the results must provide a definitive test of the hypothesis.
Hypotheses should be formulated using Occarn’s Razor, which states that the hypothesis
should be the simplest one possible consistent with the evidence, and with the fewest possible
unknowable explanatory factors. Rejection of HI) implies an alternative hypothesis (HA), the next
most probable explanation in the hierarchy. The relationship between H o and HA lies at the heart
of the Protocol’s design. Ho establishes a format for testing the significance of an attribute
parameter, e.g., that the density of shorebird benthic prey taxa in a restored marsh is not
statistically different from a natural marsh; HA provides the means by which the hypothesized
cause of a significant difference may be tested , e.g., that the substrate structure (which is presumed
to affect the density of these organisms) is significantly different Thus, as many interrelated
attributes as possible should be monitored (f the causal mechanis m or mechanisms behind a
significant difference in a key attribute are to be eluci dazed and this information incorporated into
subsequent, alternative mitigation design criteria.
Once a hypothesis has been formulated, the sampling design will determine the optimum
statistical analysis. In other words, the statistical analysis will only be as good as the structure of
the sampling design; you can always step back to a simpler test if a vital assumption is violated, but
you can seldom step up to a more complex (and usually more precise) analysis if the sampling
design is inappropriate. This argues for a seventh Protocol rule: Develop the hypothesis (or
hypotheses) and the expected methods of analysis before collecting any samples (other than a pilot
study).
The statistical methods available for testing significance are too diverse and complex to
describe here. More important are the constraints upon their application, i.e., the assumptions
about the data which should be met before specific significance tests can be used legitimately.
Green (1979) argues that (1) these assumptions should be understood at the time the statistical
design is chosen; (2) the likelihood and consequences of violation (of these assumptions) should
be assessed (with the aid of data from preliminary sampling); and (3) application of the statistical
test should proceed with awareness of the risks and the possible remedies.
Parametric tests have somewhat obdurate assumptions such as normality and homogeneity
of within-group variation. We say somewhat because, in fact, a test may be quite robust under the
assumptions used to derive it (Harris 1975). Among Harris’s guidelines, at least three are quite
applicable to analyses of habitat data: (1) two-tailed tests with F- and t-statistics will generally be
valid, even on extremely non-normal populations; (2) the ratio of the largest to the smallest sample
variance should not exceed 20, and the ratio of the largest to the smallest sample size should not
exceed 4; and (3) the error degrees of freedom should be 10 or more.
Transforming the data can reduce the violations of assumptions, such as that of nonhomo-
geneity of variance. It is common when dealing with data from estuarine organisms to find the
.variance depending upon the mean. As pointed out by Green (1979), the resulting heterogeneity of
variances associated with differences in means among groups can be removed by transformation,
but differing within-group variances resulting from other, unknown causes cannot. Transforma-
tion, therefore, should not be treated as the all-encompassing answer for resolving assumptions
-------
SAMPLING CONSIDERATIOt ’ S COMMON TO ALL HABrrATS /30
behind parametric tests. You should always test your data for violations of assumptions first, ther
decide whether a transformation of the data is appropriate and, if it is, choose the transformation.
A detailed sequence for making these evaluations and decisions is described in detail in Green
(1979).
When the assumptions of parametric significance tests cannot be met by the data, and the
robustness of the tests is in question, non-parametric or so-called disrribunon.free tests are usually
acceptable alternatives. These tests are particularly applicable to small or unequal samples from
contagious disthbutions, and are usually based on ranking. It is important to remember that many
non-parametric tests axe almost as efficient as their paraniethc equivalents when all the “normal”
assumptions for the paramethc tests are fulfilled (Elliott 1977), which argues for the much simpler
computations required by the non-parametric tests under certain circumstances.
The Mann-Whitney U-test is a common non-parametric tests for comparing two samples.
Other common tests that compare more than two samples are the following: (1) Quenouille’s test
of the difference in mean level; (2) Kruskal-Wallis one-way ana1 sis by ranks; (3) Friedman two-
way analysis by ranks; (4) rank correlation coefficient; and (5) X and contingency tables. The
power-efficiency of these tests can, in fact, be quite high, e.g., between 90% and 96% for normal
data in the case of the Mann-Whitney U-test and 96% for the Kruskal-Wallis. In addition to these
“central value” oriented tests, the Kolmogorov-Smirnov two-sample test is applicable to testing the
overall goodness-of-fit of two samples to see if they come from the same distribution. Deciding
which test to use, relative to the data and the conditions required of it, should be done by consult-
ing with a biostatistician and exploring one or more of the many texts and reference volumes.
Elliott (1977), for instance, provides a good guide to the various methods and examples of their
use, and Siegel (1956) and Wilcoxon and Wilcox (1964) are good general sources.
Several new tests to deal with non-random data have also been developed recently. Use of
such “randomization” or “permutation” tests does not require that the test statistic under the null
hypothesis (and the subsequent calculation of the P-value) depend upon normal distributions; they
also do not require equal variances in many instances. One “simply computes” the values of the
test statistic under all possible arrangements of the data (under the null hypothesis, each distinct
rearrangement of the data values to the various treatment groups is equally likely). The resulting
frequency distribution is known as the randomization distribution or the permutation distribution,
and the P-value attached to the observed test statistic can be directly computed from this
distribution. Box et al. (1978, pp. 94-97) provide a nice illustration of the robustness of the two-
sample t-test under non-normality using a randomization approach.
Of course, it is no simple computing task to compute exact P-values. However, there are a
variety of computer software packages available to perform the calculations. One such package,
“StatXact” 2 developed by C. Mehta at Harvard University, has demonstrated that if sample sizes
are equal (see summary of this section), using ordinary t-tests and F-tests even on non-normal data
gives remarkab1y valid results. As for the case of unequal sample sizes, StatXact will compute
either the exact P-values or an approximate P-value taken from an estimated randomization dis-
tribution. If there are simply too many random rearrangements of the data to compute them all, the
computer will take a very large random sample (e.g., 25,000) from the randomization distribution
and compute the P-values from the approximation to the actual randomization distribution. The P-
values approximated in this manner have been found to be quite reliable.
2 Mention of this trademark product does not constitute an endorsement.
-------
Sample Location / 31
SAMPLE LOCATION
Sampling locations should be repeatable, either from the standpoint of returning to the same
precise location for continued, nondestructive sampling or to avoid sampling a previous sampling
point that had been sampled destructively.
Permanent markers (sometimes called datum markers) are the most reliable method to locate
sampling points, transects of grids. They should be constructed of material that does not deterio-
rate, such as metal rebar or plastic PVC pipe, and implanted in the substrate firmly enough to resist
displacement or loss by wave action. At sites with extreme wave or current exposure, heavier
markers should be used, such as a concrete pier block with a metal pipe driven through it into the
substrate. At the time of installation, all markers should be located relative to a known, pre-
surveyed marker using standard survey techniques. Not only will this serve to locate sampling
locations should markers be lost, but tidal elevations can be surveyed at the same time.
Care should always be taken to make the markers as unobtrusive as possible, both to
minimize visual pollution of the site and to reduce the temptation to remove them without
authorization.
Location of subtidal sampling points requires more elaborate procedures. Sampling for
sedentary and motile fishes and evasive macroepifauna., for example, should employ accurate
navigation, generating data on position, depth, and direction and length of towed samplers. In the
simplest form, sampling points or the beginning and ending points of trawls and other tows can be
established roughly by dropping buoys at the beginning and end of the sample; after sampling, the
positions of the buoys should be determined by thangulation and marked on a fine-scale navigation
chart. Optimally, sampling location should be established precisely using electronic means such as
day-screen radar with built-in variable range markers (VRM), high-resolution lorans with multiple
navigation capabilities, satellite navigation using a global positioning system (GPS), and video
depth sounders and plotters. Puget Sound Estuary Program (1990a) describes in detail the use of
these devices for precision trawl sampling.
SAMPLE PRESERVATION
Standardized procedures are required for preserving samples retained from field
collections, and may vary if the samples are presorted in the field. In addition to preservatives,
relaxants may also be needed to minimize distortion and autotomization of certain organisms (such
as polychaete annelids) and to facilitate retention of organisms during sieving, and staining may be
required for laboratory sorting. The basic rule, however, is to preserve material immediately! If
circumstances prevent immediate preservation, short-term storage of material on ice in a cooler may
be permissible, but identification of soft-bodied organisms (e.g., polychaete annelids) and
organisms from fish stomach contents will not be reliable from iced samples.
Further discussion of standardized procedures for handling biological samples applicable to
Protocol sampling are included in the Puget Sound Protocols for benthic infauna (Puget Sound
Estuary Program 1990b) and soft-bottom demersal fishes (Puget SoundEstuaiy Program 1990a).
More detailed information about fixation and preservation techniques for plankton are available in
Steedman (1976) and Omoii and ilceda (1984) and for benthic infauna in Birkett and McIntyre
(1971).
RELAXANTS
Relaxants are most important for soft-bodied organisms that tend to distort their body shape
or autotoniize, because their identification is often dependent upon certain taxonomic characteristics
-------
SAMPLING CONSIDERATIONS Cor tMoN TO ALL HABITATS /32
that are obvious only in live or re [ axed specimens. Relaxants are most commonly used for benth
(infauna) macminvertebrate samples and seldom used for crustaceans, molluscs, and fish. The
most common general relaxant is probably isotonic magnesium chloride (e.g., 73 grams [ g]
MgCl 6 [ -120 per liter [ l1J of tap water), although propylene phenoxectol, epsom salts (MgSO 4 ),
alcohol, menthol, and tobacco have also been recommended (Birkett and McIntyre 1971; Smith
and Canton 1975).
Relaxants have not been used in most benthic infauna studies in Puget Sound, and the
Subtidal Benthic Macroinvertebrate Protocols (Puget Sound Estuary Program 1990b) do not
recommend their use because of the potential conflict introduced in the level of taxonomic iden-
tification. Because the few soft-bodied infaunal organisms listed as attributes (e.g., Manayunkia
aestuarina, Neanthes lünni cola, Abarenicola pac fica) should not require relaxation prior to
preservation for identification, we also recommend against using relaxants for basic sample
collections.
However, the use of relaxants is encouraged when collecting fish for stomach contents
analysis, because fish introduced directly into preservative often regurgitate. In fact, the ASIH,
AFS, and AIFRB strongly recommend that fish be anesthetized in these instances (ASU-1 1971).
Two of the most common anesthetics used for fish relaxation are Tricaine (MS-222; 3-
Aminobenzoic acid ethyl ester methanesulfonate) and Quinaldine (2-Methyiquinoline). Other fish
anesthetics are sodium pentobarbical, hydrous chiombutanol, and urethane; 3 Cailliet et al. (1986)
described the promise of Etomidate (1-El -Phenylethyll. I H-iniidazole- 5-carboxylic acid ethyl ester)
but cautioned against its field use at that time. An appropriate dosage of MS-222 for fish relaxation
before preservation would be 50-100 ppm.
From a humane standpoint, anesthetics are also required for handling small mammals (e.g.,
Townsend vole) and all other vertebrates collected in the field except those released immediately.
Because the anesthetics and dosages used are very species- and size-specific, we suggest that you
consult an experienced veterinarian or other expert before attempting anesthesis of these animals.
PRESERVATIVES
Formalin (37% by weight solution of formaldehyde gas in water, usually with 10%-l5%
methanol added to prevent polymerization) is the most common biological preservative, at least for
immediate fixing. The normal concentration varies according to the mass of the organisms being
preserved, but it generally ranges from 4% for zooplanklon and benthic infauna to [ 0% for fish.
In all cases, to prevent the preservative from becoming acidic over time, the formalin solution
should be buffered by adding borax (sodium tetraborate), hexamine, or calcium carbonate (e.g.,
marble chips) to excess; in the case of borax, 20 g 11 is recommended. In the case of large
organisms such as fish >3-5 g in weight, incisions should be made in the abdominal cavity to
allow rapid penetration of the preservative to internal organs.
Immediate freezing of samples may be necessary under a few circumstances but is
generally not recommended because most soft tissues usually deteriorate when thawed. Fish and
macroinvertebrates should never be frozen for later gut contents analyses for this reason.
All samples held for long-term storage should be transferred after fixation in the buffered
formalin solution to an alcohol solution, usually 45% isopropanol or 70% ethanol. Fixation in
formalin is usually sufficient after 1 day, but 7 to 10 days are recommended to reduce the risk of
decalcifying molluscs and echinoderms (Puget Sound Estuary Program 1990b).
3 cau on: Urethane is reported to be carcinogenic; use and dispose with care.
-------
Sample Preservation /33
STAINS
Vital stains may be added to samples at the time of preservation to enhance subsequent
sorting because of the selective uptake of the stain by some organisms (most benthic infauna and
meiofauna) and the resulting connast with mineral material in the sample. Conversely, certain
taxonomic features can be obscured in the staining process, and organic detritus also stains and can
confuse the objective of contrasting the fauna. While staining is generally a help in sorting, we
reiterate Puget Sound Estuary Program (1990b) in stating that it is not a substitute for proper
sorting efficiency. A proper quality control program should ensure correct taxonomic identifi-
cations whether or not staining is used.
The most commonly recommended stain is rose bengal ( 4 ,5,6,7-Tetrachloro-3’,6’-
dihydroxy-2’,4’,5’,7’-tetraiodospjro [ jsobenzofjuran- I (3H) ,9’-9 [ H]xanthen] -3-one dipotassium
salt), added to samples either as a powder or in solution. A solution of between 1-4 g l- is
recommended (Birkeit and McIntyre 1971; Eleftheriou and Holme 1984; Puget Sound Estuary
Program 1990b). Rhodainine B has also been used as a stain, with sorting performed under
longwave ultraviolet light (Hamilton 1969).
COLOR PRESERVATIVES
For archival storage, it may be preferable to add an antioxidant or other chemical to retard
color loss for some samples, especially those for which color may be an important taxonomic
character (e.g., some fishes). A 40% emulsifiable concentrate of butylated hydroxytoluene (BHT,
2,6-Bis( 1,1 -dimethyl-ethyl)-4-methylphenol; sold by Shell under the name of lonal CP-40) or
butylated hydroxyamisole (BHA, mixture of 2-tert-butyl-4-methoxyphenol and 3-tert-butyl-4-
methoxyphenol; sold by Universal Oil Products under the name of Sustane I-F) mixed as a 2 ppt
solution in 10% forrnalin or 70% ethanol is recommended for both crustaceans and fish (Omori
and Ikeda 1984). Two other color preservatives recommended for fish are erythorbic acid
(isoascorbic acid D-erythro-Hex-2-enonic acid y-lactone) and lonal CP-40 (butylated
hydroxytoluene; both are normally diluted to 1% in 10% forinalin (Cailliet et al. 1986).
SAMPLE PROCESSING
The same principles of repeatability, reliability, and validity that apply to the samples apply
similarly to how those samples are processed (prepared and measured) in the field and in the
laboratory. In addition, some control and assurance (so-called quality control, QC, and quality
assurance, QA) of processing precision must be guaranteed, and some systematic documentation
must be maintained on the discrete samples so that the data resulting from this processing can be fit
unambiguously to the sampling design. We stress that individual elements of any sample should
be discretely identifiable, and that the procedures for obtaining them should be exactly repeatable.
FIELD
Acquisition of data or sorting of samples on-site is generally encouraged, especially if data
can be obtained undestructively. Even if destructive samples (e.g., benthic grab, bottom trawl) are
collected, we recommend processing them on-site if possible, because most of the organisms can
be returned to the general vicinity alive, and subsamples will usually suffice for more extensive
laboratory analyses. This is especially the case for large organisms, e.g., benthic infauna and fish,
samples of which occupy a large volume and mass and require immediate preservation.
In the case of most benthic samples, organisms must be sorted from mineral and detrital
material, which is usually performed on the deck of a vessel by washing the contents of a sample
(e.g., bottom grab) through a sieve (i.e., 1 mm; Puget Sound Estuary Program 1990b) over a
-------
SAMPLING CONSIDERATIONS COMMON TO ALL HABiTATS /34
sorting table. This procedure, as well as more elaborate sorting mechanisms, ale described in
more detail in Birkett and McIntyre (1971).
Similarly, except in cases of extremely low catches, we recommend subsampling fish
catches immediately after collection and returning the residual catch alive. However, care should
be taken to avoid returning fish to an area that will be immediately sampled again. The preferred
procedure is to hold the earlier catches in containers (such as washtubs or plastic garbage cans)
while subsequent samples are collected and release all residual catches after all sampling has
occurred.
All field samples, subsamples, and any elements separated from the samples at the time of
acquisition should be labeled with a unique sample number or code. At a minirnwn, this label
should contain the following information: (1) date; (2) time; (3) sample location (include distin-
guishing reference number, such as the sample coordinates or transect location); (4) identifying
stratum number, if necessary, e.g., transect number, elevation; (5) replicate number, and (6)
initials of person recording sample data and making out label in the field. In addition, any
comments relative to the potential efficiency of a sample (e.g., “beach seine snagged briefly on
retrieval”) should be noted at this time.
LABORATORY
Having been presorted in the field, most samples can be dealt with directly. In addition,
compared with field-sorting, sorting of samples in the Laboratory can obviously be maintained with
greater precision and accuracy and will obviously be the only option when collecting zooplankton
and meiofauna.
Any processing of samples in the laboratory that involves subsampling should follow the
same precepts of sampling theory that have been described previously in the section on sampling
design. In particular, subsampling should be random and the dimension proportional to the
occurrence of the sampling unit in the populatIon. As in field sampling procedures, these
laboratory subsampling procedures should be well documented.
Sorting and concentrating
Zooplankton, meiofauna, and similar samples should preferably be extracted from the
remainder of the sample while still alive. This is particularly advantageous because the organisms’
behaviors (e.g., rheotaxic, phototaxis) can be used to concentrate them in the sample so that they
can be more easily extracted. Samples may also be concentrated by decanting after repeated
shaking and swirling, or by elutriation with a variety of liquids (e.g., sugar in solution,
magnesium sulfate, sodium chloride, zinc chloride, carbon tetrachioride, detergent). Accepted
methods for doing samples extractions (and source references) are described in more detail in
Birkeit and McIntyre (1971).
Subsampling
Samples with high abundances of organisms should be systematically subsamp led. In
practice, only epibenthic plankters, pelagic zooplankton, and neustonic and drift invertebrates
might require subsampling in the laboratory.
The process of subsampling involves fractioning successive subsamples until the accepted
abundance of the most prominent organisms is efficiently countable but well represented in the
subsample. For most zooplankton studies, 400-500 organisms are considered an acceptable
subsample; however, because the Protocol focuses on specific taxa, a good rule would be that at
least 100 of the attribute organisms should be retained in the subsample to be counted.
-------
Sample Processing / 35
A variety of splitting devices are available, each appropriate for certain types of collections.
The Henson-Stempel pipette, Folsom splitter, and Motoda splitter are the most common devices
used in zooplankton studies, and split (e.g., quartered) Petri dishes ale often used for benthic
insects and neuston. The important principle in selecting a subsampling device is to choose one
that will not introduce bias into the subsampling process. For instance, the Henson-Sternpel
pipette is recommended for epibenthic zooplankters as long as they are the same relative size that
will easily fit through the pipette aperture; large zooplankters such as gammarid amphipods and
mysids should be picked from the sample before using this device. The Folsom and Motoda
splitters, with their considerably larger apertures, are more appropriately designed for large
samples of mixed sizes of organisms. In all devices, the samples should be agitated excessively
prior to splitting in order to suspend all taxa equally.
INSTRUMENTATION
Any instruments used for any data acquisition, whether direct or indirectly associated with
measuring attribute parameters, should be periodically calibrated and their precision documented.
Some instruments, such as salinometers, have internal calibration (e.g., zero setting) or external
calibration (e.g., resistance loops) available for repeated checking and adjustment in the field, but
these should also be periodically checked against a known, documented standard (e.g., USBS
Copenhagen water).
QUALITY CONTROL AND DATA HANDLING
QUALITY ASSURANCE AND QUALrFY CONTROL
Quality assurance/quality control must play a prominent role in any monitoring program
and should extend all the way from the field to the final analytical stage. As pointed out in Fri et
al. (in press), quality assurance/quality control are an essential product of professional competence.
In the field, quality assurance/quality control must guarantee sample integrity. Foremost,
established sampling designs must be adhered to, or, if there are deviations, they must be
documented completely; such deviations are immediately reviewed for consideration before
modifying the sampling design accordingly. Field quality assurance/quality control is actually
implemented before the first sample is taken, by the fact that all sampling equipment should be
tested for proper operation prior to deployment In particular, all instruments must be checked
under field conditions before actually field use. If feasible, back up sampling gear, instruments
and spare parts should be carried into the field during any intensive sampling. When in the field,
sthct attention should be paid to established procedures to ensure that samples are precisely
replicated. Any problematic sample which is suspected of harming the integrity of the sample
should be discarded and that sample repeated. All environmental and sample parameter data must
be recorded according to established format.
In the laboratory, the processing must follow similarly rigorous procedures to provide
propagation of the sample integrity to the point of recording the data. Similarly, data reporting
must adhere to a standardized format. All instruments should be calibrated periodically. Where
sorting and identification of plants and organisms is involved, a complete reference collection
should be maintained and additions to it verified by a relevant specialist for the taxa.
In data analysis, raw data files should be stored separately and all statistical and other
analytical procedures well documented.
-------
SAMPLING CONSIDERATIONS COMMON TO ALL HABITATS /36
DATA FORMA1TING AND ARCHIVING
It is strongly recommended that data collection be organized from the beginning around the
eventual computer entry, manipulation and archiving using some form of relational database. The
optimum method would be to use so-called data loggers, which you can program and use for in
situ entry and storage of data in a magnetic medium (e.g., internal memory or disks) which can be
downloaded to a computer upon return from the field; these are powerful and useful pieces of
equipment, but attention should be made to download frequently or maintain backup records, to
avoid the impact of memory loss in the data logger. Data recording, analysis and archiving is
most effective if it can be recorded in the same format that it is used for analysis and archiving, and
that it conform with a basic data composition format used in similar investigations. It was with this
in mind that the National Oceanographic Data Center (NODC) has generated a suite of data formats
for acquiring data from nationally-funded programs. This format series has been adopted for many
biological and physical studies of Puget Sound and, although it is not archived as a unified Puget
Sound database, these data are available in NODC format from their national office in Washington,
D. c.4 The NODC format is one of the data formats which, in addition to several EPA formats,
which has been incorporated into a recommended standard format and procedure for automated
transfer of data among agencies involved in the Puget Sound Ambient Monitoring Program
(PSAMP) (PSWQA 1991). Given the broad applicability of the PSAMP data format, including
physical (e.g., sediment), chemical (e.g., contaminants) and biological (e.g., fish, shellfish)
parameters and its comparability to the NODC format system, we urge the user of the Protocol to
adopt this .system for recording and archiving their esruarine habitat data.
DATABASES
Even if in a common forma the data resulting from the description and monitoring of
restoration/mitigation projects (and their natural “control” habitats) will not contribute to an
accumulating, standardized base of knowledge about how we measure estuarine habitat function,
and how habitat restoration/mitigation performs relative to fish and wildlife support, if it is not
readily available. Both for your own analyses and for transfer of these data to other investigators
and resource agencies, we advocate that the raw data be entered into, and manipulated from, one of
the common, commercially available computer databases. Such databases can be adapted from
simple “spreadsheet” programs or the more complex, dedicated database programs can be utilized.
Most of these programs directly, or through utilities, have procedures for exporting data in
unstructured (e.g., ASCIi) formats, which enables any other program to access them. The only
recommendation we make is that documentation be generated which describes the structure (e.g.,
field names, lengths, imbedded characters [ e.g., decimals], missing data, etc.) and content of the
original database. In addition, the database should be accompanied be a description of all sampling
sites, including their formal place names, latitude and longitude, a detailed description of each
sampling point or transect or grid, and any other locating characteristics (e.g., Loran coordinates,
MESA station location number).
STATISTICAL ANALYSIS AND INTERPRETATION
As described in the Sampling Design in Estuarine Habitats section, statistical analyses
should be conceptualized at the time of formulating the sampling design, not after all the data has
been collected. If a proper hypothesis structure is employed, the statistical analyses will be direct
4 FOr further information on the NODC data formats used in the Pacific Northwest, and for accessing NODC data
which has been collected in the region, contact the NOAA/NESDIS Northwest Liaison Office in Seattle, aim: Mi.
Sid Stillwaugh.
-------
Quality Control and Data Handling /37
and conclusive. The interpretation of the results should be just as straightforward, but seldom is.
Whereas the rejection of distinctly falsifiable null hypothesis may be conclusive, the alternative
hypotheses which may explain why there was a significant difference must be based on logical
deductions from ancillary data, observations or other studies. Thus, we stress the importance of
discussing your results in the context of any comparable prior data from a similar estuarine habitat,
especially if the new information is contradictory.
GRAPHICAL AND TABULAR ILLUSThATION
While we do not advocate any particular format and style, we do prescribe a number of
standards for presenting any tabular or graphical illustration of data or analytical results with
clarity, precision and efficiency:
1. insert raw or basic stanstical swnmaries of raw data; except in extremely simple sampling
designs with few attributes and parameters, the data will be presented in a reduced form,
but the reader should in most cases have accessible the data from which the summary
tables and graphs were derived; if raw data is extremely voluminous or detailed, include
in the first paragraph of the Results how this data may be obtained from the investigators
in hard copy or magnetic form;
2. include tables of all statistical tests, either in substantiation of the results or, if extremely
numerous, in appendices; any significance tests should explicitly list the significance level
and the test criteria for the test,
3. idennfy the source of all data presented graphically; state in the legend or labelling of the
graph itself whether raw data is presented or, if not, what summary or subset of the data
is graphed;
4. explain and/or reference all complex analytical graphs and tables; complex graphics which
are often the product of computerized statistical analyses (e.g., cluster analysis, principal
components analysis) are not always intuitive and explicit; include in the legend any
clarifying comments and reference the particular segment of the text which describes the
analytical procedure, and clearly label potentially confusing elements of the graph; all
table legends should identify measurement units (in a common dimension such as m 2 ,
cm 2 , 100 knr 2 , etc.) if they are not indicated directly in table;
5. ensure that all graph and labels and patterns are readable; reduction or better-than-perfect
copying of small font size labels often destroys graph readability and, similarly, the
differentiation of fill patterns; use large, high resolution/contrast font sizes and fill
patterns and avoid extensive reduction of graphs;
6. present many numbers in a small space; as long as it is readable and not overtly complex,
the more detail which can be presented, the better the overall picture of the relationship
among the data;
7. encourage direct comparison of dtfferent datasets; overlay, stack or otherwise arrange
data with common axes so that comparisons are easily visualized;
8. show the whole datase: at several levels of detail; use a hierarchical structure, first
showing the data at its broadest level and subsequently in fmer detail; and
9. don’t distort the data to show a result or interpretation that they don’t show, use the
figures to show obvious results.
-------
SAMPLING CONSIDERAflOI S COMMON TO ALL HABITATS /38
We highly recommend consulting Tufte (1983), from whom we adopted many of these
concepts, for his exquisite synopsis of what constitutes effective visual display of quantitative
information.
SUMMARY
In summary, it is important to repeat that care must be exercised in establishing the
sampling design upon which the protocols will be applied. In doing so, we encourage attention to
Green’s (1979) 10 basic principles of sampling design and statistical analysis, most of which are
eminently applicable to the design, analysis, and interpretation of estuarine habitat monitoring
parameters.
1. Be able to state concisely to someone else what question you are asking. Your results
will be as coherent and as comprehensible as your initial conception of the problem.
2. Take replicate samples within each combination of time, location, and any other
controlled variable. Differences among can only be demonstrated by comparison to
differences within.
3. Take an equal number of randomly allocated replicate samples for each combination of
controUed variables. Putting samples in “representative” or “typical” places is not
random sampling.
4. To test whether a condition has an effect, collect samples both where the condition is
present and where the condition is absent but all else the same. An effect can only be
demonstrated by comparison with a control.
5. Carry out some preliminary sampling to provide a basis for evaluation of sampling desir-
and statistical analysis options. Those who skip this step because they do not have
enough time usually end up losing time.
6. Verify that your sampling device or method is sampling the population you think you are
sampling, and with equal and adequate efficiency over the entire range of sampling
conditions to be encountered. Variation in efficiency of sampling from area to area biases
among-area comparisons.
7. If the area to be sampled has a large-scale environmental pattern, break the area up into
relatively homogeneous subareas and allocate samples to each in proportion to the size of
the subarea. If it is an estimate of total abundance over the entire area that is desired,
make the allocation proportional to the number of organisms in the subarea.
8. Verify that your sample unit is appropriate to the sizes, densities and spatial distributions
of the organisms you are sampling. Then estimate the number of replicate samples
required to obtain the precision you want.
9. Test your data to determine whether the error variation is homogeneous, normally
distributed and independent of the mean. If it is not, as will be the case for most field
data, then (a) appropriately transform the data, (b) use a distribution-free (non-
parametric) procedure, (c) use an appropriate sequential sampling design, or (d) test
against simulated H 0 data.
10. Having chosen the best statistical methods to test your hypothesis, stick with the result.
An unexpected or undesired result is not a valid reason for rejecting the method and
hunting for a “better” one.
-------
Summary/39
Finally, when considering allocation of our usually limited sampling effort, we would add
a final caveat. When developing a sampling design and the statistical tests of significance to test
differences in habitat attributes, applicability and realism are of primary importance, while
precision can, within limits, be sacrificed. However, given the critical nature of estuarine habitat
loss, we.suggest that in mitigation and other situations involving “replacement” of natural habitat
function, both realism and precision are mandatory.
-------
SAMPLING PROTOCOLS
ROOTED VASCULAR PLANTS
While the protocol development process resulted in a list of individual vascular plant taxa,
we recognized that these plants generally occur in complexes or assemblages . Thus, in developing
the Protocol, we chose to describe parameters and sampling methodology for these attributes
within the context of their assemblages. Therefore, the assemblages defined below are an
expansion of the individual attributes listed earlier in this document and in Supplements 2-6
(Sirnenstad et al. 1990).
HABiTAT OCCURRENCE
All rooted vascular plants but the seagrasses (Zostera spp., Zostera japonica, and Z.
marina, which occur predominantly in the Eelgrass Habitat) are included by us in the Emergent
Marsh Habitat. They can occur as the basic “matrix” in the habitat or as patches in a matrix of
different habitat type. Eelgrass, in particular, occurs as patches in mudflat or sandflat habitats.
The distributions of habitat patches within habitat matrices must be considered in developing your
sampling design, especially when considered sampling strata.
CHARACTERISTICS
This group of macroscopic plants have below-ground structures (e.g., roots, rhizomes,
etc.) and above-ground structures consisting of stems or shoots. The species vary widely in
morphology from simple upright single shoots to a complex system of branching stems. Trees and
shrubs are considered part of this group. All members of this group grow rooted in sediments.
They are distributed from the upper fringes of tidal influence down to shallow subtidal depths.
Estuarine marsh plants and eelgrass are often epiphytized by smaller plants (usually algae) .
Epiphytes can be important members, in terms of biontass and ptoductivity , of some vascular plant
assemblages.
Estuarine habitat assemblages are distributed along elevational, salinity, substrata and
exposure gradients in Puget Sound. Estuarine habitat assemblages at the lowest elevations,
especially those in polyhaline salinity conditions, are typically dominated by one species (i.e.,
ee lgrass and certain kelp habitats). In contrast, many estuarine marshlands contain several species
in variable quantities which can make these assemblages difficult to characterize. A number of
studies of estuarine marshlands 1 including Disraeli (1977), Burg et al. (1980), Boule’ (1981),
Boule’ and Dybdahl (1981), Bradfield and Porter (1982), Ewing (1982), Hutchinson (1982),
Granger and Burg (1986) and Hutchinson (1989), characterize the assemblages. Although each of
these studies identified one or more marsh assemblages based upon quantitative data on species
cover or abundance, the criteria for delineating an assemblage type were never established. There
is a need for a unified approach to classifying estuarine marsh species into assemblages. To meet
this need, a marine and estuarine habitat classification system has been developed by the
Department of Natural Resources (Dethier 1990). Although quantitative criteria are not given, the
system covers all estuarine habitats in Washington State. The system, therefore represents the
broadest scheme presently available for estuarine plant assemblages of the Puget Sound trough,
and will be used as part of a region-wide nearshore habitat monitoring program. The Dethier
(1990) system was adapted for the Protocol because of its broad coverage and predicted long-term
-------
Rooted Vascular Plants /41
use. At this time, it is the broadest systematically-derived spectrum of assemblage types that one
would encounter in the study region.
Dethier (1990) identified assemblages that consist of single species (i.e., monotypic stands)
or species groups that are diagnostic for each habitat type. In general, a species is diagnostic of a
habitat if it is the most abundant or obvious species at the end of the growing season. Other factors
such as functional importance or fidelity for a habitat may have also been used when identifying a
diagnostic assemblage.
The assemblages (monotypic or multiple species complexes) that are diagnostic of estuarine
habitats in the State are listed in Table 2; these are based upon Dethier (1990) and a survey of
acknowledged estuarine plant experts. Also listed are plant taxa that were identified as important to
fish and wildlife during the protocol development process. Taxa that were identified as being
important to fish and wildlife through the protocol development procedure and are included in
Dethier’s (1990) diagnostic assemblages are identified by an asterisk (*). Taxa designated by a
double asterisk (**) are not among Dethier’s diagnostic species but were listed as important to fish
and wildlife during the protocol development process. Other plant taxa and assemblages are
obviously important for fish and wildlife; however, they were not identified by direct connection
(e.g., food, reproduction or refuge) to fish and wildlife based upon data from previous
investigations. Although not diagnostic by definition, virtually all of these latter ta.xa were listed as
common in at least one estuarine habitat by Dethier (1990).
Several invasive, introduced species (e.g., Phragmites commuras, Zosterajaponica) that
have become well-established in some Pacific Northwest estuaries are included in this list. We
have incorporated these into the region’s wetland plant assemblages not because they necessarily
important to fish and wildlife, but because a better understanding of their role in wetland
communities would be gained by assessing them equivalently with the endemic plant taxa.
MONITORING PARAMETERS
Critical parameters for assessing the structure and function of rooted vascular plant
assemblages are:
Minimum ;
(1) presence/absence of species;
(2) percent cover;
(3) shoot or stem density (not applicable to species with extensive branching);
Recommended :
- (3) above-ground standing stock (live and dead);
(4) shoot or stem length;
(5) density of flowering shoots;
Preferred ;
(6) net aerial primary productivity; and
(7) below-ground standing stock.
Percent cover
Percent cover is the percentage of substrate area covered by a taxon or group of taxa. If
vegetation layers are present (i.e., canopy, understory, surface), separate measures of each layer
axe necessary. The total percent cover in quadrat could exceed 100% in these latter situations.
Percent cover Within a quadrat can be measured using a photogrammetric technique. This involves
taking a photograph of the area enclosed by the quadrat from vertically above the center of the
-------
SAMPLING PROTOCOLS /42
Table 2. Plant taxa and assemblages of estuanne habitats and that were identified as being
important to fish and wildlife during the protocol development process; all but assemblage numbers
1, 14, 23, 25, 26, 50 (all macroalgae), 51 and 52 (seagrasses), and 3, 29,46 and 48 (trees) are
vascular marsh plant taxa. * = taxa considered diagnostic of habitats in Dethier (1990); = taxa
not considered diagnostic of habitats in Dethier (1990). a = non-native invasive; b = estuanne
fringe, freshwater species.
1. Agarum spp. 25. Macrocysas inegrjfolia**
2. Agrostis alba* 26. Nereocysris luetkeana
3. AInu.s rubra**b 27. Phatarisarundinacea a
4. Carex !yngbyei* 28. Phragmites commwzis**a
5. Carex Iyngbyei*/Diszich!is spicara* 29. Picea sirchensis
6. Carex Iynghyei t /Potenfilla pactfica 30. Polygonwn hyd .ropiperoides* *a
7. Deschainpsia caespitosa*/Distichiis 31. Polygonum spp.
spicaw* 32. Populus rrichocarpa**b
8. Deschanzpsia caespitosa*/Distichlis 33. Potenrillapacjfica
spicata /SaIicornia virginica 34. Rwnex spp.
9. Deschampsia caespitosa*/JunczL 35. Ruppia maritima
boiricuslPoteraiIIa pac fica 36. Salicornia virginica*
10. Distichlis spicata* 37. Salicornia virginica*frriglochin
11. Disrichlis spicata*ISalicornia virginica* r,writ J,uiln*
12. Disrichlis spicata*/Salicornia 38. Salix spp.”
virginica*Tl’riglochin maririmwn* 39. Scirpus acurus*
13. Eleocharispaiusrris** 40. Scirpzss wnericanus*
14. Enteromorpha spp. ’ 41. Scirpu.s maritinuss
15. Festuca rubra 42. Scirpu.s validus**
16. Glaux mariwna 43. Siwn suave *
17. Grindelia inzegrjfolia* 44. Spartina spp.**a
18. Jawnea carnosoiSalicornia virginica* 45. Spergularia canadiwn
19. Jawne carnosa/Salicornia 46. Thuja plicara*
virginica*/Triglochin maririznwn* 47. Triglochin mariwnwn*
20. Juncus bojncus*IPore,uilla pac fica 48. Tsuga heteraphylla*
21. Jwicus balticus*/Porerstilla pac fica /forb 49. Typha latzfolia*
22. Juncus gerard.ii 50. Ulva spp.*
23. Laininaria spp. 51. Zosterajaponica*
24. Lilaeopsis occidenwiis 52. Z zera marina*
quadrat. The color (or infrared) slide can then be projected onto a screen containing i ndom dots
(50-100 dots per quadrat are typically used). The plant taxa and number of dots it overlays is
recorded and converted to a percent. Another method involves visually estimating a cover class for
each taxon in the quadrat. For example, a taxon may cover <1%, 1-5%, 6-15%, 16-25%, 26-
50%, 51-75%, 76-95% or 96-100% of the space within the quadrat. The median percent cover is
used when calculating the mean percent cover for a taxon within a habitat. For example, Carex is
estimated to cover 16-25% of the space in the quadrat. The median cover assigned Cater for this
-------
Sampling Protocols /43
quadrat would be 20.5%. Trees and shrub percent cover is generally estimated using this Latter
method. For trees it is useful to record the cover of the crown and the base of the trunk.
Shoot density
Shoot density is the number of shoots per unit area of ground. This parameter is sampled
by counting the number of shoots of each taxon within the quadrat. Standing live shoots (i.e.,
those with green leaves) should be distinguished from standing dead shoots in the counts.
Above-ground species standing stock
Above-ground species standing stock is a measure of the biomass (weight) of plant material
per unit area above the substrate surface (i.e., quadrat area). Above-ground standing stock is
sampled by removing all plant material by cutting the plants at the level of the sediment surface.
Care must be taken to remove only the shoot or stem portion of the plant and not the root or
rhizome. The plants are then separated by species, and by live and dead shoots, and the wet
weight recorded. In most cases, it is advisable to dry the plants at approximately 80°C until a
constant weight it attained, and report the thy weight. Because wet weight varies widely
depending upon the degree of drying that takes place between collection and measurement, wet
weight should only be used in situations where time is extremely limited. The methods (i.e., time
and handling) between harvest and weighing must be consistent for all samples in order to reduce
variability in the net weight measurements. Weights are typically recorded to the nearest 0.1 g.
However, very small plants may require weight to be recorded to the nearest mg.
Shoot length
Shoot length can be recorded by measuring the length of all or a randomly selected group
of shoots within the quadrat using a ruler or tape measure. Shoot lengths can also be measured for
plants removed for the assessment of above-ground standing stock. Shoot length measurements of
highly branched species (e.g., Saiicornia virgiraca) is not recommended.
Flowering
Flowering can be quantified as the number of shoots with flowers, the total number of
flowers per species or simply the presence of flowers in the quadrat.
Net aerial primary productivity
Net aerial primary productivity (NAPP) is defined as the amount of organic matter
produced per unit area and per unit time through photosynthesis after plant respiratory losses are
subtracted. NAPP is a measure of the rate and amount of food produced by plants in a system.
This parameter canj,e assessed by taking samples of above-ground standing stock periodically
during the growing season or once during the period of peak biomass. When sampling occurs
several times over the growing season, the incremental changes in mean standing stock per species
and per assemblage are added to compute a total net annual productivity estimate. In addition,
productivity per week or month (depending upon the sampling interval) can also be calculated.
Species which can lose significant amount of biomass during the growing season (by
sloughing or grazing) will require a modification of the above method. Among the group of taxa
of rooted macrophytes listed in Table 2, Zostera spp. (eelgrass) is the most prone to tissue loss due
to natural sloughing of leaves and its relatively high frequency of submergence. Eelgrass
-------
SAMPLING PROTOCOLS /44
productivity is best measured using a shoot marking technique. In this technique, individual
shoots are tagged and a small hole is poked through the leaves in the region immediately above the
youngest sheath. Upon return to the site in 2-4 weeks, the shoot is removed at its base, and the
biomass in the portion of the leaves relative to the basal hole in the oldest leaf (generally slow or no
growth) is recordecf and used as an estimate of net productivity (Kentula and McLntire 1986).
Values of productivity are given in grams of tissue (dry weight) produced per m 2 per unit
time. A quick method for determining a rough estimate of net annual productivity using standing
stock samples and standard curves of production for selected species, is given in Kibby et al.
(1980).
Below-ground species standing stock
Below-ground standing stock is the weight of plant matter comprising the roots and
rhizome system of a plant per unit area. This is estimated for most species by removing a core
(usually smaller than the above-ground quadrat) of sediment containing plant material from the
center of the quadrat or at a randomly determined point within the quadrat. The plant material is
separated from the sediment and the wet and/or dry weight of the plant material is determined.
Species presencelabsence and percent cover of each (axon within the study area or strata
provide the basic measurement of assemblage structure, and shoot or stem density is a more
precise quantitative measure which can be derived out of the same sampling unit; both involve non-
destructive sampling. Indicators of actual productivity, however, are recommended if emergent
plants are an extensive proportion of the habitat area; the disadvantage, however, is that
measurement of productivity can involve effort-intensive and destructive sampling. These are most
easily measured as above-ground standing stock (also termed “biomass”), shoot or stem length and
density of flowering shoots. Below-ground standing stock is less often measured, but can be a
much more sensitive measure of the success of emergent marsh plant transplants than analogous
above-ground parameters. Monitoring of the Recommended or Preferred parameters should be
conducted under any circumstances where stipulated criteria for a restoration or mitigation activity
involves comparable productivity to a natural habitat.
RECOMMENDED SAMPLING METHODOLOGY
Method : benthic quadrat
Unit : emergent vegetation, 0.25 m 2 ; submergent
vegetation, 0.1 m 2
Measurement of these parameters is most often accomplished through the use of quadrat
samples appropriately stratified, positioned and replicated (see Sampling Design in Estuarine
Habitats section). Other methods do exist (e.g., line-intercept), which are generally quicker to
carry out or better spited for a particular situation. The quadrat method is recommended here
because of its wide-spread application.
Quadrat size is an important consideration. Square quadrats that enclose 1.0 m 2 (i.e., 1.0 x
1.0 m), 0.25 in 2 (0.50 x 0.50 in) and 0.1 in 2 (0.32 x 0.32 m) are used to sample rooted vascular
plants. The chosen quadrat size must allow the measurement of all the target parameters. In
genera1 high replication using smaller quadrats yields a lower variance in most parameters as
compared to larger quadrats using fewer replicates (see Sampling Design in Estuarine Habitats).
The size of the plants will help determine the appropriate quadrat size. For example, stands of
large (i.e., 3-rn shoot length) Typha may be best sampled with a 0.25,0.5, or 1.0 m 2 quadrat.
Whereas, Z .ostera marina may be best sampled using a smaller quadrat (e.g., 0.1 m 2 ) except where
-------
Sampling Protocols /45
plants are sparse, in which case a 0.25 or 0.5 m 2 quadrat dimension is more appropriate.
Sampling larger macrophytes such as large submergent macroalgae (e.g., keips) or wetland tree
and large shrubs may require a much larger “quadrat” size, e.g., 4 m 2 to 100 m 2 ).
Periodicity and Frequency emergent vegetation, once yr 1 late July.early
- September; submergent vegetation, once yr 4
July. Au gust
Statistical Considerauons ( Replication : in lieu of statistical predetermination using pilot study
or historical data; emergent vegetation, n=S; submer-
gent vegetation, n=5; n=1O may be found necessary
for both vegetation types where the communities are
diverse or areal cover/standing stock of plants is
relatively low
While replication depends upon the area of the sampling unit relative to the area of the
habitat, typical replication for quadrat sampling has been five to fifteen. Tooptiznize the potential
and power of statistical analyses, we suggest adopting completely overlapping sampling of
vegetation, e.g., sampling macroalgae within the same quadrats as submergent vegetation and
extracting sediment cores for microalgae from within the same quadrat. Thus, sample replication
(as well as dimension) should adopt the maximum required for any one component.
CASE STUDIES
Studies which assessed all or some of these parameters in Pacific Northwest estuarine
rooted vascular plant assemblages include Burg et a!. (1980), Thom (1981), Eilers (1975) and
Ewing (1982). For assessing the performance of a restored marsh, consult the studies of Mitchell
(1981), Shreffler (1990), Thom et a!. (1988, 1990, 1991) and Frenket and Morlan (1990).
Quantitative studies on eelgrass include Kentula and Mclntire (1986) and Thom (1988, 1989,
1990a). A review of eelgrass meadow mitigation and construction projects can be found in Thorn
(1990b).
-------
BENTHIC MACROALGAE
HABITAT OCCURRENCE
Eelgrass; U/va spp.
epiphytic algae/animals
Emergent Marsh; Enreromorpha spp.
U/va spp.
Gravel-Cobble; La,ninaria spp.
Macro cystis pynfera
U/va spp.
CHARACTERISTICS
Macroalgae, commonly referred to as both seaweeds and keips, (although there is some
vague distinction between these two categories) are generally found attached to rocky substrata.
However, seaweeds do not need to be attached to live and many species in estuaries can be found
free floating in the intertidal zone. Macroalgae are also commonly found as epiphytes on other
algae or rooted vascular plants. Macroaigae do not have below-ground parts (i.e., roots and
rhizomes). Almost all, however, have attachment structures (e.g., holdfasts). Among the
estuarine plant assemblages delineated in Table 2, assemblages 1, 14, 23, 25, 26 and 50 are
macroalgal taxa.
PARAMETERS
Critical parameters for characteriñng the macroalgal assemblage are:
Minimum ;
(1) percent cover
Recommended :
(2) species standing stock; and
Preferred ;
(3) net and gross primary productivity.
Percent coves and species standing stock are the most often used parameters for
characterizing the structure of a benthic macroaigal assemblage, are sampled similar to the methods
described for rooted vascular plants, and should be used in most cases for assessing the
performance of created systems.
Percent cover
Percent cover is the percentage of ground area covered by a taxon or group of taxa. Total
percent cover for a quadrat would be 100%, which may include vegetation, sessile animals and
bare ground. If vegetation layers are present (i.e., canopy, understory), separate measures of each
-------
Ben thic Macroalgae /47
layer are necessary. The total percent cover in the quadrat could exceed 100% in these latter
situations. Percent cover within a quadrat can be measured using a photogramme rj technique.
This involves taking a photograph of the area enclosed by the quadrat from vertically above the
center of the quadrat. The color (or infrared) slide can then be prqjected onto a screen containing
random dots (50-100 dots per quadrat are typically used). The plant taxa and number of dots it
overlays are recorded and converted to a percent. Another method involves visually estimating a
cover class for each taxon in the quadrat. For example, a caxon may cover <1%, 1-5%, 6-15%,
16-25%, 26-50%, 5 1-75%, 76-95% or 96-100% of the space within the quadrat. As with rooted
vascular plants, median percent cover is used when calculating the mean percent cov r for a taxon
within a habitat.
Species standing stoc
Species standing stock is a measure of the biomass (weight) of plant material that occurs
per unit area of substrate. Standing stock is sampled by removing all plant material by total
removal or, for those that have holdfast attachments, cutting the plants’ holdfasts at the level of the
substrata surface. Care must be taken to remove as much of the plant as possible, or to cut the
holdfasts systematically. The plants are then separated by species and the wet weight recorded. In
most cases, it is advisable to dry the plants at approximately 80°C until a constant weight it
attained, and report the dry weight. Because wet weight varies widely depending upon the degree
of drying that takes place between collection and measurement, wet weight should only be used in
situations where time is extremely limited. Weights are typically recorded to the nearest 0.1 g.
However, very small plants may require weight to be recorded to the nearest mg.
Net and gross trimarv productivily
Because seaweeds can loose much of their tissues in a short period of time due to slough-
ing, and because significant amounts of organic matter can leak from the tissues of the plants and
not become incorporated into plant material, net and gross primary productivity assessment is often
done using oxygen flux (photosynthesis and respiration) measurements.
Net primary productivity (NPP) and gross primary productivity (GPP) is measured using
standard light-dark bottle techniques (Littler and Arnold 1985). First, a fresh piece of a species is
placed in a glass bottle (usually a 3 00-ml BOD bottle). The bottle is filled with filtered seawater,
and the initial dissolved oxygen (DO) in the water is measured.. The bottle is sealed and incubated
under ambient day-light and sea temperature conditions for a period of time (i.e., this varies from
0.5-3.0 hrs depending upon how quickly photosynthesis is taking place). The final dissolved
oxygen is then recorded. The bottle can then be darkened to exclude all light, and incubated under
ambient sea temperature for a period of time [ generally much longer than the light treatment
because respiration (R) rates are generally slow in seaweeds]. The final dissolved oxygen
concenhradon is then recorded. The surface area of the piece of plant use is recorded and the dry
weight is determined. NPP and GPP are related as follows:
GPP = NPP + R
Oxygen produced in the light treatment represents net productivity. This change in oxygen should
be divided by either the dry weight of the plant used or by the surface area to give oxygen
produced per mg or cm 2 of tissue. The rate is calculated by dividing the result by the incubation
time. Respiration is the loss of oxygen in the dark bottle, which must be normalized per unit time
(usually 1 hour) and per unit of tissue (mg, cm 2 ). Biomass data from the quadrat sampling can
-------
SAMPLING PROTOCOLS / 48
then be used to calculate the NPP, R or GPP per m 2 (or other suitable unit) in the habitat under
study.
Daily NPP is calculated by multiplying the hourly rate by the number of hours of non-light
limited photosynthesis. This varies from approximately 10 hours around the summer solstice to 4
hours around the winter solstice. Daily R is simply the hourly rate multiplied by 24 hours, since
respiration is assumed to occur all the time. Hence, for a daily GPP, daily NPP and R must be
calculated. Annual rates of productivity are estimated by integration between productivity
experiments. It is strongly recommended that the time between experiments not exceed one month,
and preferably be shorter periods in late-winter through early summer. Seaweeds are most
abundant in Puget Sound estuaries during May through September, and any comprehensive
sampling program should span this period.
RECOMMENDED SAMPLING METHODOLOGY
Method : benthic quadrat
Unit : 0.1 m 2
Periodicity and Frequency : twice yr 1 June-July
Statistical Considerations (Replication) : in lieu of statistical predetermination using pilot study
or historical data; n=5, distributed randomly within
each intertidal elevation strata (transect); at least
three tidal elevations should be sampled, e.g.,
(I) between ÷3 ft and +4 ft MLLW; (2) between 0 ft
and +1 ft MLLW; and, (3) between -4 ft and -3 ft
MLLW.
While replication depends upon the area of the sampling unit relative to the area of the
habitat, typical replication for quadrat sampling has been five to ten. The more effort-intensive
production measurements, however, usually involve only three to five replicates. To optimize the
potential and power of statistical analyses, we suggest adopting completely overlapping sampling
of vegetation, e.g., sampling macroalgae within the same quadrats as subinergent vegetation and
extracting sediment cores for microalgae from Within the same quadrat. Thus, sample replication
(as well as dimension) should adopt the maximum required for any one component
CASE STUDIES
Studies which have documented benthic macroalgal assemblages in Puget Sound include
Thom et al. (1976), Thom (1978, 1980) and Thom and Aibright (in press). Studies of benthic
macroalgae in restored estuarine habitats are not available.
-------
BENTHZC MICROBIOTA
HABITAT OCCURRENCE
Eelgrass; epiphytic algae/animals
Emergent marsh; epiphytic algae/animals
fllamentaus algae
CHARACTERISTrCS
This group of plains consists of microscopic algae (primarily diatoms and blue-greens) that
occur on the surface of sediment grains or attached to larger rocky substrata. It is a diverse group,
consisting potentially of hundreds of species. Although not conspicuous, this group can account
for significant amount of primary productivity in some habitats due to their high productivity rates.
Measurement of microalgal biomass and productivity are advised in situations where benthic
microalgae may be important system components and particularly where benthic infauna and
epibenthic meiofauna are being monitored.
PARAMETERS
Typical parameters for measuring estuarine microalgal assemblages are:
Minimnm
(I) total standing stock; and
Recommendeth
(2) net and gross primary production.
Preferred.
Total standing stock
Total standing stock or biomass is estimated as chlorophyll a concentration per unit area.
In general, chlorophyll a is sampled using 1-cm diameter benthic cores that are 1 cm deep. The
chlorophyll a biomass is commonly used as a direct indicator of total standing stock. Conversion
factors can be used to convert chlorophyll a to carbon equivalents, but this factor can range from
25 to 250 depending upon environmental conditions, nutrient limitation, and growth phase of the
algae (Parsons et al. 1977) and are based predominantly upon phytoplankton taxa Strickland
(1960) recommends a C/chlorophyll a ratio of 30.
Net and gross primary productivity
Productivity (NPP, GPP) measurements follow those of oxygen flux (photosynthesis and
respiration) for macroalgae using standard light-dark bottle techniques (Littler and Arnold 1985).
Sediment cores are extracted from the habitat and these are incubated intact in chambers designed to
hold the cores. For productivity measurements, cores of 5-10 cm in diameter are commonly used.
First, the core is placed in the chamber. The chamber is filled with filtered seawater, and the initial
dissolved oxygen (DO) in the water is measured. The chamber is sealed and incubated under
-------
SAMPLING PROTOCOLS /50
ambient day-light and sea temperature conditions for a period of time (i.e., this varies from 0.5-3.0
hrs depending upon how quickly photosynthesis is taking place). The final dissolved oxygen is
then recorded. The chamber can then be darkened to exclude all light, and incubated under ambient
sea temperature for a period of tune (generally much longer than the light treatment because
respiration (R) rates are generally slow in seaweeds). The final dissolved oxygen concentration is
then recorded. The surface area of the core and the total standing stock (chlorophyll a) are
determined. NPP and GPP axe related as follows:
NPP=GPP-R
Oxygen produced in the light treatment represents net productivity. This change in oxygen should
be divided by either the chlorophyll a concentration or by the surface area of the core to give
oxygen produced per unit of chlorophyll a or cm 2 of sediment surface. The rate is calculated by
dividing the result by the incubation time. Respiration is the loss of oxygen in the dark bottle,
which must be normalized per unit time (usually 1 hour) and per unit of plant matter (chlorophyll
a). Standing stock is estimated by the chlorophyll a determinations is used to calculate the NPP, R
or GPP per cm 2 (or other suitable unit) in the habitat under study. Using GPP = NPP + R, daily
NPP is calculated by multiplying the hourly rate by the number of hours of non-light limited
photosynthesis. This varies from approximately ten hours around the summer solstice to four
hours around the winter solstice. Daily R is simply the hourly rate multiplied by 24 hours, since
respiration is assumed to occur all the time. Hence, for a daily GPP, daily NPP and R must be
calculated. Annual rates of productivity are estimated by integration between productivity
experiments. It is strongly recommended that the time between experiments not exceed one month,
and preferably be shorter periods in late-winter through early summer. Because oxygen may be
lost due to heterotrophic respiration associated with sediments, gross productivity is referred to as
gross community productivity.
RECOMMENDED SAMPLING METHODOLOGY
Method : benthic core
Unit : 0.79 cm 2 (1.0-cm dia.)
Periodicity and Frequency : monthly, March-May
Statistical Consideratidns (Replication’ : in lieu of statistical predetermination using pilot study
or historical data; n=5
When sampled in conjunction with quadrat sampling for other attributes (e.g., benthic
macroalgae, sedentary infauna), one core is usually removed for benthic microalgae, thus
replicating at the same level as the other attributes. Historical studies of sampling just for benthic
microbiota have involved five to fifteen replicates. Similar to the productivity measurements for
benthic macroalgae, normally only three to five replicates are run. To optimize the potential and
power of statistical analyses, we suggest adopting completely overlapping sampling of vegetation,
e.g., sampling macroalgae within the same quadrats as submergent vegetation and extracting
sediment cores for microalgae from within the same quadrat. Thus, sample replication (as well as
dimension) should adopt the maximum required for any one component.
-------
Benthic Microbiota 151
CASE STUDIES
Studies where benthic microalgae have been assessed in Puget Sound include Thom et al.
(1984, 1985), Thom (1988, 1989) and Thom and Aibright (in press). The biornass of microalgae
in estuarine habitat reconstruction monitoring has been measured by Thom et al. (1986, 1987,
1988). Pertinent studies in the Northwest estuaries include Amspoker and Mclntire (1978) and
Mc lntire and Amspoker (1986).
-------
DEMERSAL ADHESIVE FISH EGGS
HABITAT OCCURRENCE
Gravel-Cobble; Clupea harengus pallasi (eggs)
Eelgrass; Clupea harenguspallasi (eggs)
CHARACTERISTICS
The cream-colored eggs of Pacific herring are typically laid in layered masses which adhere
to macroalgae (e.g. keips) or eelgrass in shallow subtidal and low intertidal habitats. For still
indiscernible reasons, hen-ing spawning appears to be extremely site-specific, and we could not
find any information which might provide criteria for optimizing herring spawning on kelp arid
eelgrass. Spawning occurs between March and June, although local herring stocks seem to have
relatively specific spawning ti mes 5 . When intensive, the spawning is visually obvious as an
extensive milky cloud along the shoreline, coincident with considerable fish and seabird activity.
Spawning can occur, however, without such obvious manifestations and measurement of actual
spawn deposition is the more accepted approach.
PARAMETERS
Minimum ;
(1) number of egg layers;
Recommended :
(2) egg density;
Preferred ;
(3) egg survival and viability.
Egg layer (spawning intensity ) -
Counts of the distinct layers of eggs are made from eggs masses on intact vegetation,
discarding any which have been disrupted in sampling, using a grappling rake. Sampling with the
rake is conducted at longshore extremes and distances from shore until no or few egg masses axe
found, providing some quantitative delineation of the area in which spawning occurred.
Egg densitv
This measur ment is the number of eggs per unit of eelgrass or kelp substrate. Samples of
vegetation with eggs intact are removed from within (a minimum of) 0.10- to 0.25-rn 2 quadrats
distributed over a random sampling grid or stratified (where working with a beach gradient) 250-rn
to 500-rn long transects. The eggs are stripped off each eelgrass shoot or kelp frond and counted.
Under extremely high densities, the eggs can be weighed and the total egg counts extrapolated
5Jf monitoring of Pacific herring spawning is considei ed, the investigator should contact the Marine Fish Division
of the Washington Department of Fisheries for more specific information on the timing and location of spawning at
the location under consideration.
-------
Demersal Adhesive Fish Eggs / 53
from the weight of a known subsample of eggs. The vegetation is measured for surface area and
the egg density estimated as a total or as a mean of the individual shoot or frond densities.
Egg suMva and viability
Two methods can be used to evaluate egg survival and viability, one in situ ar d one
laboratory method. On the spawning ground, discrete egg masses can be enclosed in a mesh cage
which permits maximum water movement but limits macroinvertebrate and fish predation. These
cages should be monitored coincident with each spawning ground survey and the number and state
of the eggs recorded relative to the progress of the natural egg masses on the spawning ground.
Eggs removed to a laboratory with flowing seawater of the same temperature and salinity regime as
the spawning ground can be held in conjunction with egg masses from a comparable natural
spawning ground; these eggs should be monitored frequently to assess the number of successful
eggs hatching relative to the controL
The egg layer method is a standard methodology for assessing spawning intensity and has
been used by the Washington Department of Fisheries from the early 1970s (Trumble et al. 1977)
to estimate spawning escapement; this extensive baseline should be considered an important
precedence for sampling Pacific herring eggs in any estuarine habitat in the Puget Sound region.
Although limited to intertidal and shaliow subtidal habitats where sampling units can be deployed,
egg density per unit of spawning substrate is a more precise method which allows variance
estimates and statistical comparison among treatment and control sites. Egg survival and viability
is a more intensive monitoring which should be considered for situations in which the spawning
substrate is not considered to be the sole limiting factor, e.g., water quality or higher bird predatfon
are potential limiting factors.
RECOMMENDED SAMPLING METHODOLOGY
Method : benthic quadrat
Unit : 0.25-rn 2 quadrat
Periodicitv and Frequency : semi-weekly, during documented spawning
period or, if unknown, February-July
Consult the Washington Department of Fisheries for information on spawning periodicity
of local herring stocks.
Statistical Considerations (Replication) : in lieu of statistical predetermination using pilot study
or historical data; n=10 within an identifiable spawn
concentration
ALTERNATIVE PROCEDURES
Using a small skiff, samples of vegetation are collected at 350-500 m intervals along the
spawning grounds using a grappling rake. The herring spawn (egg masses) are sampled directly
from the vegetation. The number of replicate transects will depend upon the shoreline area being
monitored, as the 250-rn to 500-rn sampling segments would constitute replicate samples as long
as tidal elevation and habitat type (strata) does not change.
-------
SAMPLING PROTOCOLS /54
CASE STUDIES
Descriptions of the accustomed spawning ground surveys occur in Trumble et al. (1982).
-------
SURFACE EPIFAUNA
HABrTAT OCCURRENCE
Emergent Marsh; BalatuLs spp.
Chironomidae (larvae)
Corbicula manilensis
Diptera (unid.)
Hemiptera (unid.)
Insecta (unid.)
Litrorina spp.
Mytilus spp.
Saunderia spp.
Gravel-Cobble; Batanus spp.
Corbicula ,nanilensis
Dendrasrer excentricus
Mytilu.s spp.
Nucelia spp.
Mudfla Corbicula manilensis
Corophiwn sa!monis
Corophiwn spp.
Diptera (unid.)
Ostrea lurida
Nearshore Subtidal Soft Bottom; Ampelisca agassizi
Clinocardiurn nutalli
Nearshore Subndal Hard Substrate; Ba/anus crenazus
Balanus glanthila
Sandfiat Clinocardium nutalli
Corophiurn spp.
Oligochaeta (unid.)
CHARACTERISTICS
Surface epifauna are organisms which are attached to (sessile) or relatively closely
associated with the surface of the bottom. As defined, thIs functional group does not include those
organisms that penetrate benthic sediments (infauna) or move off the surface of the substrate into
the benthic boundary layer (epibenthic plankters), although some of the same taxa may appear in
these other groups.
PARAMETERS
Minimun
(1) species occurrence;
(2) percent cover;
-------
SAMPLING PROTOCOLS /56
Recommended :
(3) density and standing stock (wet weight biomass);
Preferred ;
(4) population structure (i.e., length frequency distribution, life history stage,
reproductive status);
(5) age and growth;
(6) standing stock (dry weight or ash free dry weight).
Species occurrence
When sampling is distributed intensively over time and space, or when dealing with non-
motile fauna, the relative occurrence of species (providing species richness and timing) can provide
a minimal indication of the viability of estuarine habitats and associated aquatic habitats, principally
as an assessment of water and/or sediment quality. Species richness should be defined relative to
life history stage, especially because the use of the habitat by reproductive individuals and juveniles
is a more important supportive function than if only adults occur. Species occurrence should be
represented as both (1) mean number of species/life history stages per sample by gear and as (2)
the cumulative number of specie/life history stage by all gears over space or time because different
gears have selection biases and because surface epifauna are often distributed in patches.
Percent cover
For sessile animals that cover sediment surfaces, a minimal measure of their abundance is
the percentage of a standard (quadrat) area which they cover. Total percent cover for a quadrat
would be 100%, which may also include vegetation and bare ground. The total percent cover in
quadrat could exceed 100% in these latter situations. Percent cover within a quadrat can be
measured using a photogrammetric technique. This involves taking a photograph of the area
enclosed by the quadrat from vertically above the center of the quadrat. The color (or infrared)
slide can then be projected onto a screen containing random dots (50-100 dots per quadrat are
typically used). The sessile epifauna taxa and number of dots it overlays is recorded and converted
to a percent. Another method involves visually estimating a cover class for each taxon in the
quadrat. For example, a ta.xon may cover <1%, 1-5%, 6-15%, 16-25%, 26-50%, 5 1-75%, 76-
95% or 96-100% of the space within the quadrat. As with plants, the median percent cover is used
when calculating the mean percent cover for a taxon within a habitat.
Density and standing stock
Density and standing stock are more definitive indicators of subtle differences in habitat
quality because habitat characteristics can effect density-dependent interactions between the surface
epifauna and their habitat which would otherwise not be reflected by species richness. Density and
standing stock are expressed, respectively, as the number and biomass per unit area (e.g. no. rn- 2 ,
g wet rn- 2 ) or volume (e.g., no. m 3 , g wet m 3 ) of the habitat.
Standing stock is normally expressed as wet weight (biomass), which is acceptable as long
as the weighing method is standardized to minimize variability due to different amounts of moisture
content: If feasible, surface epifauna are best weighed fresh (damp) after excess water is toweled
off. If preserved in formalin or alcohol, specimens can also be weighed in this manner but the
standing stock values should expressly state that they are preserved wet weights and the time out of
the preservative should be standardized because drying can be quite rapid under these
circumstances.
-------
Surface Epifauna /57
Due to these sources of variability, which can often introduce considerable bias, the
optimum method to express standing stock is as dry weight or as ashfree dry weight. Dry weight
is defined as the biomass after drying at 100°C until the weight has stabilized (typically >48 hours).
Ashfiee dry weight is the biomass of organic matter combusted at 500-600°C for >24 hr. Both of
these, especially the latter, are extremely labor- and time-intensive measures for epifaunal biomass
estimates and are generally not warranted unless production or some other sensitive bioenergetic
indices are intended.
As in species occurrence, density and standing stock should be expressed relative to
species and life history stage.
Population structure
Population smicture for may epifaunal taxa may an important indication of the function of
an estuarine habitat because critical assessment criteria such as reproduction and recruitment can
only be assessed by data on reproductive state and life history stage, respectively. This is
particularly the case for organisms with intermittent and episodic recruitment. At a minimum, life
history stages should be classified for a subsample of the collections. In the case of most epifauna,
this will take form of three broad life history classes: (1) juvenile, recently settled through all mstar
stages; (2) subadult or non-reproducing; and (3) reproductive individuals.
Size, as measured by dimension and less commonly by weight, frequency distributions can
often be used to differentiate different size classes within these life history stanzas, and can be
important indications of different recruitment events, i.e., short-term age differences. Organism
size can be measured by a variety of standard techniques and several “standards” are used for
different epifaunal taxa: (1) maximum valve length for bivalves such as Mytilus, Ostrea and
Corbicula; (2) total shell length or aperture width for gastropods such as Lirrorina; (3) basal surface
area for barnacles (Balanus); (4) maximum disk diameter for circular or oval organisms such as
Dend raster, and (5) anterior tip of the carapace (including rostrum if present) to tip of telson with
the animal stretched to full length in the case of amphipods. A sample for length measurements
must be completely random and of sufficient size to represent the distribution; typically, a
minimum of 25 to 50, and often 100, are required depending upon the variability.
Age and growth
Although similar to size distributions, age and growth data are some of the most optimal
parameters to assess habitat quality. Not only will this indicate the age at which the population
likely recruited to the habitat, but these data can also indicate the relative productivity of these
organisms. Both bivalves and gastropods can be aged by analysis of thin sections of their shells;
some bi ’alves can actually be aged by external annual striations.
RECOMMENDED SAMPLING METhODOLOGY
Method : emergent marsh, mudflat, sandflat habitats, benthic
core; gravel-cobble, excavation within benthic
quadrat; nearshore subtidal soft- and hard-bottom,
benthic quadrat in combination with airlift
(Venturi) suction sampler; all samples washed
through 1.0 mm mesh sieve
Sediment cores have provided satisfactory samples of estuarine insect larvae and pupae.
Quadrat sampling may be either non-destructive or destructive, depending upon the size of the
-------
SAMPLING PROTOCOLS /58
attributes being sampled and the taxonomic verification required. Airlift or Venturi samplers
commonly used for sampling in unconsolidated sediments (e.g., Brett 1964; Barnet and Hardy
1967; Christie and Allen 1972; Tunberg 1983; Benson 1989) can be used effectively in conjunction
with destructive quadrat sampling. In this context, they are used to suction up all fauna (unless
limited by large sue) which is scraped from within the quadrat and retained a 500-iIm mesh or
smaller sampling bag.
Unit : benthic core, 176.7 cm 2 (15.cm dia.)
excavated to 10 cm depth; benthic quadrat,
0.25 m 2 surface evacuation
Given their size, abundance and distribution, cores with diameters of 10-cm to 20-cm would be
expected to provide adequate samples; LaSalle and Bishop (1987) described samples from 16.5-cm
diameter cores used principally for sampling molluscs, Quadrat size will also vary, depending
upon the size, density and distribution of the attributes being sampled. For instance, assessment of
Balanu.s spp., which can reach high densities, has been assessed using (a minimum of) 0.10- to
0.25-rn 2 quadrats, while Ostrea lurida and other less dense attributes will involve larger quadrat
sizes, e.g. 0.5- or 1.0-rn 2 . Obviously, the size of the quadrat to be used for monitoring many
attributes will be set by the larger or rarer attribute, but staged sampling may be considered in the
case of extremely divergent attributes (see Sampling Design in Estuarine Habitats).
Periodicitv and Frequency : quarterly, e.g., February, May, August,
November, to capture recruitment events
The Puget Sound Protocols (Puget Sound Estuary Program 1990b) suggest that subtidal
benthic macroinvertebrates be sampled in April and May, However, there is other evidence that
this period would encapsulate the primary spawning and recruitment events for many Puget Sound
macroinvertebrate taxa, and thus introduce considerable variance in the estimation of organism
density and standing stock. In a compilation of spawning and reproduction of benthic
macroinvertebrates from Puget Sound compiled by Shimek (1990), it was illustrated that spawning
and reproductive behavior tends to be more concentrated between April to August, and peak
settlement occurred from June through August. The results of this compilation was compared to
selected benthic infauna data for January, June and August. This comparison indicated that,
although differences were not significant, statistical variation tended to be lowest in January for
most taxa. This pattern is presumably due to the early mortality of organisms recruiting to the
benthos in the prior spring or summer, and accompanying stabilization of organism densities.
Only in the case of arthropods was the coefficient of variation greater in January than in one of the
other two months, and the disproportional representation of pagurid crabs (which reproduce in the
winter) may have biased this result.
Given these results, we recommend seasonal (quarterly) sampling in order to capture the
potentially different recruitment events for diverse taxa. This could be abbreviated to twice yr 1 for
specific attribute taxa if sufficient data is available on their life history patterns to identify
representative pre-recruitment and post-recruitment sampling seasons.
Statistical Considerations (Replicationi : in lieu of statistical predetermination using pilot study
or historical data; n=1O, distributed randomly within
each tidal elevation strata (transect); at least three
tidal elevations should be sampled in intertidal
habitats, e.g., (1) between +3 ft and +4 ft MLLW;
-------
Surface Epifauna/ 59
(2) between 0 ft and +1 ft MLLW; and, (3) between
-4 ft and -3 ft MLLW
As in the cases of other core and quadrat studies, replication wiU depend in part upon the
relationship between the quadrat dimension and the areal extent of habitat being monitored.
Typical replication in histonc studies has ranged from five to 25 samples.
CASE SuiDIES
Aibright and Armstrong (1982) describe a sampling program for Corophium spp. in the
mudflat habitats of Grays Harbor based on coring. Hueckel (1980), 1-lueckel and Buckley (1987)
and Benson (1989) have described the use of an air-lift sampler in assessing fish prey organisms
scraped from quadrat samples on a subtidal artificial reef.
-------
SEDENTARY INFAUNA
HABITAT OCCURRENCE
Eelgrass; Capitellidae (unid.)
Cryptomya ca4fornica
Macoma spp.
Mya arenana
Tellina spp.
Emergent Marsh; Manayunkia aestuarina
Neanthes limnicola
Nematod.a (urnd.)
Nereidae (unid.)
Tanais spp.
Transennella tapuilla
Gravel-Cobble; Mya arenaria
Tellina nuculoides
Mudflat Abareni cola pac fica
Macorna spp.
Nematoda (unid.)
Tapes (Ruditapes) phllipinarwn
Nearshore Subtidal Soft Bottom; Transennella tansilla
Sandflat Mya arenaria
CHARACTERISTICS
Sedentary infauna are those which are relatively immobile within the benthic substrate.
These can include not only animals which form burmws (e.g., clams such as Mya arenaria,
Macoma spp., etc.) but free-living nematodes (Nematoth) and polychaetes (Nereidae). Their
general lack of rapid motility means that they can be easily sampled with core and grab devices,
which axe generally inappropriate for the more evasive taxa. In cases where populations densities
and standing stocks are being used as primary assessment criteria, grabs or box corers are
preferred to most coring methods because of their higher reliability in assessing meiofauna
(Elmgren 1973).
PARAMETERS
Minimum ;
(1) species occurrence;
Re ommendeth
(2) density and standing stock (wet weight biomass);
-------
Sedentary Infauna /61
Preferred
(3) population structure (i.e., length frequency distribution, life history stage,
reproductive status);
(4) age and growth;
(5) standing stock (dry weight or ash free dry weight).
Species occurrence
When sampling is distributed intensively over time and space, or when dealing with non-
motile fauna, the relative occurrence of species (providing species richness and timing) can provide
a minimal indication of the viability of estuarine wetland and nearshore habitats, principally as an
assessment of water and/or sediment quality. Species richness should be defined as relative to life
history stage, especially because the use of the habitat by reproductive individuals and juveniles is
indicative of a greater supportive function than if only adults occur. Species occurrence should be
represented as both (1) mean number of species/life history stages per sample by gear and as (2)
the cumulative number of specie/life history stage by all gears over space or rime because different
gears have selection biases and because infauna are often distributed in patches.
Density and standing stock
Density and standing stock are more definitive indicators of subtle differences in habitat
quality because habitat characteristics can effect density-dependent interactions between the infauna
and their habitat which would otherwise not be reflected by species richness. Density and standing
stock are expressed, respectively, as the number and biomass per unit area (e.g. no. rn- 2 , g wet
rn- 2 ) or volume (e.g., no. m 3 , g wet m 3 ) of the habitat.
Standing stock is normally expressed as wet weight (biomass), which is acceptable as long
as the weighing method is standardized to minimize variability due to different amounts of moisture
content. If feasible, infauna are best weighed fresh (damp) after excess water is toweled off. If
preserved in formalin or alcohol, specimens can also be weighed in this manner but the standing
stock values should expressly state that they are preserved wet weights and the time out of the
preservative should be standardized because drying can be quite rapid under these circumstances.
Due to these sources of variability, which can often introduce considerable bias, the
optimum method to express standing stock is as dry weight or as ashfree dry weight. Dry weight
is defined as the biomass after drying at 100°C until the weight has stabilized (typically >48 hours).
Ashfree dry weight is the biomass of organic matter combusted at 500-600°C for >24 hr. Both of
these, especially the latter, are extremely labor- and time-intensive measures for infaunal biornass
estimates and are generally not warranted unless production or some other sensitive bioenergetic
indices are intended.
As in species occurrence, density and standing stock should be expressed relative to
species and life his ry stage.
Population structure
Population structure for may infaunal ta.xa may an important indication of the function of an
estuarine habitat because critical assessment criteria such as reproduction and recruitment can only
be assessed by data on reproductive state and life history stage, respectively. This is particularly
the case for organisms with intermittent and episodic recruitment. At a minimum, life history
stages should be classified for a subsample of the collections. In the case of most infauna, this will
-------
SAMPLING PROTOCOLS /62
take form of three broad life history classes: (1) juvenile, recently settled through all instar stages;
(2) subadult or non-reproducing; and (3) reproductive individuals.
Size, as measured by dimension and less commonly by weight, frequency distributions can
often be used to differentiate different size classes within these life history stanzas, and can be
important indications of different recruitment events, i.e., short-term age differences. Organism
size can be measured by a variety of standard techniques and several “standards” are used for
different infaunal ta.xa: (1) maximum valve length for bivalves; (2) total overall, stretched length for
free-living polychaetes; and (3) anterior tip of the carapace (including rostrum if present) to tip of
telson with the animal stretched to full length in the case of most microcrustacean like tanaicjs and
amphipods. A sample for length measurements must be completely random and of sufficient size
to represent the distribution; typically, a minimum of 25 to 50, and often 100, are required
depending upon the variability.
Age and growth
Although similar to size distributions, age and growth data are some of the most optimal
parameters to assess habitat quality. Not only will this indicate the age at which the population
likely recruited to the habitat, but these data can also indicate the relative productivity of these
organisms. Both bivalves and gastropods can be aged by analysis of thin sections of their shells;
some bivalves can actually be aged by external annual striations.
RECOMMENDED SAMPLING METHODOLOGY
Method : emergent marsh, mudfiat, sandflat and gravel-cobble
habitats, excavation within benthic quadrat;
nearshore subtidal soft- and hard-bottom, benthic
quadrat in combination with airlift (Venturi)
suction sampler; all samples washed through 1.0.
mm mesh sieve
Diver-controlled airlift or Venturi samplers commonly used for sampling in unconsolidated
sediments (e.g., Brett 1964; Barnet and Hardy 1967; Christie and AlIen 1972; Tunberg 1983;
Benson 1989) can be used effectively in conjunction with destructive quadrat sampling. In this
situation, the air-lift sampler is used to excavate the area inside a quadrat (size may vary between
0.25 m 2 and 1.0 m 2 , depending upon the size, density and depth of the infaunal organism being
monitored) to a standard depth (e.g. 12 cm to 25 cm) and the infauna are retained in the collection
bag, which is usually constructed of 0.5-mm to 7.0-mm mesh netting. With extremely large fauna
such as Mya arenaria, they may be removed by hand by the diver during or after the excavation of
the quadrat area.
Unit : 0.25 m 2 excavated to 25 cm depth
As for surface epifauna, the sizes of sampling quadrats used to assess sedentary infauna
vary depending upon the size, density and distribution of the attributes being sampled. The large
sizes of many of the attribute organisms, particularly the bivalves, suggests that the 0.25-rn 2
quadrat size and deep penetration would be necessary to effectively sample their populations.
Obviously, the size of the quadrat to be used for monitoring many attributes will be set by the
larger or rarer attribute, but staged sampling may be considered in the case of extremely divergent
attributes (see Sampling Design in Estuarine Habitats).
-------
Sedentary Infauna /63
Periodicity and Frequency quarterly, e.g., February, May, August,
November, to capture recruitment events
The Puget Sound Protocols (Puget Sound Estuary Program 1990b) suggest that subtidal
benthic macroinvertebrates be sampled in April and May. However, there is other evidence that
this period would encapsulate the primary spawning and recruitment events for many Puget Sound
macroinvertebrate taxa, and thus introduce considerable variance in the estimation of organism
density and standing stock. In a compilation of spawning and reproduction of benthic
macroinvertebrates from Puget Sound compiled by Shimek (1990), it was illustrated that spawning
and reproductive behavior tends to be more concentrated between April to August, and peak
settlement occuned from June through August. The results of this compilation was compared to
selected benthic infauna data for January, June and August. This comparison indicated that,
although differences were not significant, statistical variation tended to be lowest in January for
most taxa. This pattern is presumably due to the early mortality of organisms recruiting to the
benthos in the prior spring or summer, and accompanying stabilization of organism densities.
Only in the case of arthropods was the coefficient of variation greater in January than in one of the
other two months, and the disproportional representation of pagurid crabs (which reproduce in the
winter) may have biased this result.
Given these results, we recommend seasonal (quarterly) sampling in order to capture the
potentially different recruitment events for diverse laxa. This could be abbreviated to twice yr 1 for
specific attribute taxa if sufficient data is available on their life history patterns to identify
representative pre-recruitment and post-recruitment sampling seasons.
Statistical Considerations (Rep1ication) in lieu of statistical predetermination using pilot study
or historical data; n—S , in intertidal habitats
distributed randomly within each tidal elevation strata
(transect); at least three tidal elevations should be
sampled in intertidal habitats, e.g., (1) between +3 ft
and +4 ft MLLW; (2) between 0 ft and + 1 ft MLLW;
and, (3) between -4 ft and -3 ft MLLW
As in the cases of other quadrat studies, replication will depend in part upon the
relationship between the quadrat dimension and the areal extent of habitat being monitored.
Typical quadrat replication ranges from five to 25 samples. Benthic grab samples are often not
replicated (n = I) but many of the historical studies in Puget Sound have involved four to five
samples and this is the recommended sample size established by the Puget Sound Estuary Program
(1990b), and we recommend five for reasonable statistical analyses.
All other sampling considerations should be adopted in accordance with the Puget Sound
Protocols (Puget Sound Estuary Program 1990b).
ALTERNATIVE PROCEDURES
(1) Benthic rabs:
The benthic equivalent to ring nets in sampling zooplankion is the benthic grab for
sampling sedentary infauna in moderate (e.g.. below diving depths of —30 m) to deep depths;
grabs are commonly employed from boats and usually require powered spools. Over the decades
of benthic grab sampling, a plethora of different types and modifications have evolved (see
Eleftheriou and Holme 1984). Word (1977) provided a synopsis and comparison of just seven of
the more common devices used for assessing benthic infauna which are important as prey of
fishes; his evaluation was based on consistency of sampling area, consistency of sampling below
-------
SAMPLING PROTOCOLS /64
the depth where the majority of the species and specimens occur, minimum surface disturbance
caused by pressure waves and minimum disturbance due to leakage. Using these criteria for
evaluation, Word concluded that the chain-rigged 0.1-rn 2 Van Veen and the 0.1-rn 2 Smith-
Mcintyre grabs were preferable, and that the Van Veen was preferred overall because it was
slightly more effective in capturing surface-dwelling microcrustacea and was simpler to use. Most
Van Veen grabs are now modified by a trap door or screen to minimize the pressure wave effect.
Modified Van Veen grabs are available which sample a smaller surface area (e.g., 0.025 m 2 ) but
these should not be used unless the larger, deeper burrowing infauna are not attributes to be
monitored.
(2) Benthic cores:
In intertidal habitats, or sometime also subtidal habitats, benthic cores are easier to utilize
for sampling sedentary infauna. These are simply cylinders which are open-ended and are pushed
or driven to a standard depth into the substrate. When the sediment is extremely unconsolidated, it
may be necessary to excavate around the core and place a shovel blade beneath it before removal; in
muds and more consolidated sediments, the suction is usually sufficient to contain the core sample
within the corer. It is extremely important to avoid disturbance of the sediment surface when
placing the core, especially when deploying under water. The diameter of the core will depend
upon the taxa being monitored. Small cores are almost mandatory when assessing extremely
small, dense taxa such as nematodes but larger cores are required for larger taxa which typically
occur at lower densities, such as most of the bivalves. Word (1977) used 5.4-cm diameter cores to
evaluate the performance of the various grab samplers. In the Seahurst Baseline Studies, Thom et
al. (1984) used two sizes and penetration depths, a 2.74-mm core inserted 10 cm deep and a 14.1
cm core inserted 30 cm deep, to sample small and larger infauna, respectively. In the intertidal and
shallow subtidal benthos studies of Nyblade (1979) and Webber (1980), 500-cm 2 core 15 cm deep
was utilized.
CASE STUDIES
Quadrat excavations, surface scrapes and cores were used in intertidal and shallow subtidal
investigations in Puget Sound by Houghton (1973) and along the Strait of Juan de Fuca by
Nyblade (1979) and Webber (1980). Simenstad et al. (1988b) describes the use of an air-lift
suction pump to quantitatively sample deep-burrowing bivalves within a 0.25-rn 2 quadrat in
shallow subtidal sand and eelgrass habitats in Neah Bay. The modified 0.1-rn 2 Van Veen grab
was used to sample subtidal infauna in the extensive Seahurst Baseline Study in central Puget
Sound (Word ci al. 1984); the smaller 0.025-rn 2 modified Van Veen was used to sample small
infauna in the Simenstad et al. (1988) studies of Neah Bay. Benthic cores of various sizes have
been used to sample intertidal infauna and the most extensive database is probably that of Thom et
al. (1984) from the Seahurst Bight area of central Puget Sound. Thom et al. (1988) have also
utilized a 5.1-cm core inserted 10cm deep to sample benthic infauna in intertidal habitats of the
restored Lincoln A’ enue Wetland in the Puyallup River estuary.
-------
ACTIvE INFAUNA
HABITAT OCCURRENCE
Ee lgrass; Calliancssa cc4fornie,
Mudflat Callianassa ca1 forniensjs
Nearshore Subddal Soft Bottom; Ca!lianassa ca1 forniensjg
Sandflat Callianassjdae (unid)
CHARACTERISTICS
-. Active infauna are exclusively the deep-burrowing, active ghost shrimp. Their deep
burrows and rapid digging capability makes them extremely difficult to sample properly.
PARAMETERS
Minimum :
(I) species occurrence;
Recommended :
(2) density and standing stock (wet weight biomass);
Pteferred
(3) population structure (e.g., size, sex and reproductive state).
Species occurrence
When sampling is distributed intensively over time and space, or when dealing with non-
motile fauna, the relative occurrence of species (providing species richness and timing) can provide
a minimal indication of the viability of estuarine wetland and nearshore habitats, principally as an
assessment of water and/or sediment quality. Species richness should be defined as relative to life
history stage, especially because the use of the habitat by reproductive individuals and juveniles is
indicative of a greater supportive function than if only adults occur. Species occurrence should be
represented as both (1) mean number of species/life history stages per sample by gear and as (2)
the cumulative number of specie/life history stage by all gears over space or time because different
gears have selection biases and because infauna are often distributed in patches.
Density and standing stock
Density and standing stock are more definitive indicators of subtle differences in habitat
quality because habitat characteristics can effect density-dependent interactions between the infauna
and their habitat which would otherwise not be reflected by species richness. Density and standing
stock are expressed, respectively, as the number and biomass per unit area (e.g. no. m 2 , g wet
m 2 ) or volume (e.g., no. rn 3 , g wet nr 3 ) of the habitat.
Standing stock is normally expressed as wet weight (biomass), which is acceptable as long
as the weighing method is standardized to minimize variability due to different amounts of moisture
-------
SAMPLING PROTOCOLS /66
content. If feasible, infauna are best weighed fresh (damp) after excess water is toweled off. If
preserved in formalin or alcohol, specimens can also be weighed in this manner but the standing
stock values should expressly state that they are preserved wet weights and the time out of the
preservative should be standardized because drying can be quite rapid under these Circumstances.
Due to these sources of variability, which can often introduce considerable bias, the
optimum method to express standing stock is as dry weight or as ashfree dry weight. Dry weight
is defined as the biomass after drying at 100°C until the weight has stabilized (typically >48 hours).
Ashfree dry weight is the biomass of organic matter combusted at 500-600°C for >24 hr. Both of
these, especially the latter, are extremely labor- and time-intensive measures for infaunal biomass
estimates and are generally not warranted unless production or some other sensitive bioenergetic
indices are intended. As in species occurrence, density and standing stock should be expressed
relative to species and life history stage.
Some investigators have found the density of borrow openings visually evident at the
sediment surface to be a reliable indicator of subsurface shrimp density. Although this may be
feasible in other situations, it has been found to be unreliable in recent, intensive studies of
Callianassa caljforniensis in Puget Sound (Weitkamp 1991) and is not recommended as an optional
protocol.
Population structure
Population structure for may infaunal taxa may an important indication of the function of an
estuarine habitat because critical assessment criteria such as reproduction and recruitment can only
be assessed by data on reproductive state and life history stage, respectively. This is particularly
the case for organisms with intermittent and episodic recruitment. At a minimum, life history
stages should be classified for a subsample of the collections. In the case of most iñfauna, this will
take form of three broad life history classes: (1) juvenile, recently settled through all instar stages;
(2) subadult or non-reproducing; and (3) reproductive individuals.
Size, as measured by dimension and less commonly by weight, frequency distributions can
often be used to differentiate different size classes within these life history stanzas, and can be
important indications of different recruitment events, i.e., short-term age differences. Organism
size can be measured by a variety of standard techniques and several “standards” are used for
different infaunal taxa: (1) maximum valve length for bivalves; (2) total overall, stretched length for
free-living polychaetes; and (3) anterior tip of the carapace (including rostrum if present) to tip of
telson with the animal stretched to full length in the case of most microcrustacean like tanaids and
amphipods. A sample for length measurements must be completely random and of sufficient size
to represent the distribution; typically, a minimum of 25 to 50, and often 100, are required
depending upon the variability.
RECOMMENDED SAMPLING METHODOLOGY
Method : intertidal habitats, benthic cores; shallow subtidal
habitats, benthic cores evacuated with airlift
(Venturi) samplers; samples washed through
5.0-mm mesh sieve
Studies of burrowing shrimp in other regions have used coring devices on the order of 10-
cm diameter x 50-cm deep in size. Dumbauld et al. (1988), however, consider the small
dimension of the core relative to the usually complex shrimp burrow morphology and the lack of
consistent sediment core retention to be a disadvantage of this method; they recommend either hand
pumps or excavation of a larger core sample. In the latter case, those investigators have used a 40-
-------
Active Infauna /67
cm diameter x 60-cm corer in combination with a Venturi pump system and hand excavating the
sediment core with a small shovel. In shallow subtidal habitat, the diver-controlled airlift or
Venturi samplers commonly used for sampling in unconsolidated sediments (e.g., Brett 1964;
Barnet and Hardy 1967; Christie and Allen 1972; Tudhope and Scoffin 1984; Tunberg 1983;
Benson 1989) could feasibly be used to sample deep-burrowing shrimp in conjunction with
quadrat sampling or if a box is inserted into the sediment to form the sampling volume (as in Brett
1964). In this situation, the air-lift sampler would be used to excavate the area inside a quadrat to a
standard depth (e.g., 1 rn) and the shrimp retained in a collection bag constructed of 0.5-mm mesh
netting. The active digging, swimming shrimp may, however, be too evasive to be effectively
sampled with this method.
Unit : 0.25 m 2 , excavated to 1.0 m
Sampling Periodicity and Frequency : twice yr 1 , in April and September to sample
pre- and post-recruitment population structure and
reproduction
Statistical Considerations (Replication’) : in lieu of statistical predetermination using pilot study
or historical data; n=S, in intertidal habitats
distributed randomly within each tidal elevation strata
(transect); at least two tidal elevations should be
sampled in intertidal habitats, e.g., (1) between +3 ft
and +4 ftMLLW; and (2) betweenOftand +1 ft
? LW
There are few studies upon which to base any recommendation for replication. We suggest
in this instance that a pilot study be conducted to determine the necessaiy replication level for
statistical precision.
ALTERNATIVE PROCEDURES
(1) Hand suction pump:
Many surveyors of ghost/mud shrimp have adopted a hand suction pump which is derived
from sport (bait) shrimp harvesters. Modified from the design of hand bilge-pumps, this device is
usually made of PVC plastic pipe 5-cm to 8-cm in diameter, approximately 1-rn long, and operates
by pulling a plunger attached to a rubber gasket (ball) up through the pipe with the suction end
enclosing a shrimp burrow; pushing the plunger back down expels the shrimp from the sampler if
one has been captured. To our knowledge, no one has conducted a field verification of the
sampling efficiency of the hand suction pump, and it is dubious that it would be effective for more
than documentation of Callianassa presence or absence.
(2) HydraulIc infusion pumps:
The most common method used specifically for sampling Callianassa is the infusion of
water deep (at least 1 in) into the bottom to liquify the sediments and force the shrimp to the surface
in the “boil” of surfacing water. This is duplicated from the common commercial method of
harvesting ghost and mud shrimp and is conducted during low tide exposure of sand and mudflats
where shrimp densities are on the order of >100 rn 2 . A gasoline-powered pumps injects
approximately 50-100 gal min 1 of water drawn from a nearby channel. The shrimp are typically
dipped up with dip nets. No standardization or quantification of surface area being liquified has
been attempted, and estimation of density and standing stock may be a problem. This method,
-------
SAMPLING PROTOCOLS /68
however, does provide a large number of shrimp from which population structure data could be
obtained.
(3) Deep-penetrating box corers:
Although they have not been utilized for these taxa, large (0.5-rn 2 to 1.0-rn 2 ) box corers
may have the ability to sample certain active infauna, but it is questionable that they would be able
to sample much deeper than 0.5 m. Such penetration would be insufficient, for instance, for
sampling Callianassa cal(fornieMis because this species may burrow 0.8 to 1.0 m deep in
sediments. Box corers are also notoriously poor samplers in loose, unconsolidated sediments
(e.g., sand) that tend to drain out of the sampler when hauled to the surface. Box corers could,
however, be used in combination with SCUBA diver controlled airlift (Venturi) samplers to
evacuate the organisms contained within a box corer at the bottom.
CASE STUDIES
To our knowledge, the only published account of data for quantitative sampling of ghost or
mud shrimp in Puget Sound or coastal estuaries are those of Dumbauld et al. (1988) and Weitkamp
(1991). Unpublished data may also be available from the Washington Department of Fisheries,
Point Whitney Shellfish Laboratory (J. Odell, WDF, pers. comm.). Posey (1986) provides some
quantitative data on burrowing shrimp from Oregon estuaries.
-------
EPIBENTHIC PLANKTERS
HABITAT OCCURRENCE
Eelgrass; Caprella laeviuscula
Corophium spp. (males)
Corophium spp.
Cumella vulgarLs
Eogammaru.s co4fervicolus
Eogammarus spp.
Harpacriciis spinulosus
Harpacticus spp.
Harpacticus uniremis
Ischyrocerus spp.
Pontogeneia rostrata
Tisbe spp.
Zaus spp.
Emergent Marsh; Corophium sahnonis
Corophiwn spinicorne
Corophium spp.
Cwnella vulgaris
Eogammarus confervicolus
Eogamntarus spp.
Gnorünosphaeroma oregonese
Gravel-Cobble; Ampithoe spp.
Anisogammarus pugettensis
Corophium spp.
Cuinelta vulgans
Eogaminarus spp.
Ezisiroides spp.
Gnorimosphaeroma oregonese
Mudflat; Atylus spp.
Corophium sabnonis
Corophiwn spp.
Cwnella vulgaris
Eogaininarus confervicolus
Eogammarus spp.
Echaustorius washingtonianus
Ha pacticus uniremis
Megalorchesna pugettensis
Pancolzjs cal forniensis
Tisbe spp.
Nearshore Subtidal Soft Bottom; Orchornene minura
Phons lacia
-------
SAMPLING PROTOCOLS /70
Sandflat Cwnella vulgaris
Eogammaru.s cot jervicolus
Megalorchestia pugenensis
Phoxocephalidae spp.
CHARACTERISTICS
Epibenthic plankters are very small macrofaunal or meiofaunal (e.g., 0.065-mm to 2-mm
long) organisms, predominantly crustaceans, which live at the interface between the bottom
substrate and the water column, either in the very surface layer or in the benthic boundary layer.
These include predominantly harpacticoid copepods, gammarid amphipods, cumpcepns , and
isopods : one tanaid (Pancolus caljforniensis) occurs. In many cases, this is an operational
definition and assemblage which is formed simply by turbulent processes in the boundary layer
and entrainment from organisms sinking out of the water column. However, most of the
organisms identified as attributes in this group are associated with the surface layer of
unconsolidated sediments and benthic epiphytes but which are described to actively (behaviorally)
emerge a short distance into the adjoining water column. Sampling methodologies recommended
are those which cause minimal disruption of and do not penetrate above and below the benthic
boundary layer (thus, air-lift suction samplers are not recommended), sample a known area of the
benthic surface reliably (thus, samplers which contact the bottom intermittently are not
recommended), and which include a long precedence of comparable data in the region.
PARAMETERS
Minimum ;
(I) species occurrence;
(2) settled volume;
Recommended ;
(3) density and standing stock;
Preferred ;
(4) population structure (e.g., naupliar, copepodid stages; ovigerous females); and
(5) diel and tidal stage sampling.
Species occurrence
When produced from an intensive sampling effort over time and space, or in the case of
relatively non-motile organisms, the relative occurrence of species (providing species richness and
timing) can provide-a minimal indication of the viability of estuarine wetland and nearshore
habitats, principally as an assessment of water and/or sediment quality. Species richness should be
defined as relative to life history stage, especially because the use of the habitat or different
rnicrohabitats (e.g., depth strata) by reproductive individuals and different larval stages may a more
important supportive function than if only adults occur. Species occurrence should be represented
as both (1) mean number of species/life history stages per sample by gear and as (2) the cumulative
number of specie/life history stage by all gears over space or time because different gears have
selection biases and because epibenthic plankters occurrence can be exceedingly patchy over space
and time.
-------
Epibenthic Plankters /71
Settled volume
One straightforward, quantitative assessment which can be relatively analogous to total
standing stock is settled volume. This is measured as the volume which the epibenthic plankters
constitute when allQWed to settle in a graduated flask or cylinder and is normally reported in
milliliters (ml).
Density and standing stock
Density and standing stock are preferred monitoring parameters because they are more
definitive indicators of subtle differences in habitat quality. Habitat and microhabitat characteristics
can effect density-dependent interactions between zooplankton and their habitat which would
otherwise not be reflected by species richness. Density and standing stock are expressed,
respectively, as the number and biotnass per unit area (e.g. no. m 2 , g wet m 2 ) or volume (e.g.,
no. m 3 , g wet m 3 ) of the habitat.
Standing stock is normally expressed as wet weight (biomass), which is acceptable as long
as the weighing method is standardized to minimize variability due to different amounts of moisture
content. Wet weights of epibenthic plankters are usually obtained as preserved after excess
preservative is absorbed; the time out of the preservative should be standardized because drying
can be quite rapid under these circumstances, especially if an alcohol is used as the preservative.
Due to these sources of variability, which can often introduce considerable bias, the
optimum method to express standing stock is as dry weight or as ashfree dry weight. Dry weight
is defined as the biornass after drying at 100°C until the weight has stabilized (typically >48 hours
for fish). Ashfree dry weight is the biomass of organic matter combusted at 500-600°C for >24 hr.
Both of these, especially the latter, are somewhat more labor- and time-intensive methods for
epibenthic plankters but are a more precise measure and should be encouraged in production
estimates are intended.
As in species occurrence, density and standing stock should be expressed relative to
species and life history stage.
Population structure
Epibenthic plankters population structure can an important indication of estuarine habitat
function because verification of resident populations can only be determined through verification of
reproduction and contiguous life history stages. At a minimum, life history stages should be
classified for a subsample of the collections. In the case of most epibenthic plankters, this will take
form of five broad life history classes: (1) nauplii; (2) copepodids; (3) nonreproductive females; (4)
males; and (5) ovigerous females. If it is desirable to document these stages in more detail, the
various naupliar and copepodid stages should also be distinguished.
Diel and tidal stage sampling
The occurrence of epibenthic plankters can vary appreciably over diel and tidal cycles due
to actual behavioral migration through the water column. For this reason, monitoring focused on
the identification of viable epibenthic plankter populations should document density, standing stock
and population structure during different diel periods and tidal stages. Minimally, this should
include sampling during (1) diurnal, nocturnal and crepuscular periods and (2) ebb and flood and
slack tide stages.
-------
SAMPLING PROTOCOLS /72
RECOM?IPIENDED SAMPLING METHODOLOGy
Methods : epibenthic suction pump; all samples washed
through O.253.i.im mesh sieve
Efficient, quantitative sampling of epibenthic plankters has been a distinct challenge
because of their small size, their discrete occurrence in the benthic boundary layer and their
avoidance capabilities. Standard benthic samplers (e.g. 1 cores, air-lift suction pumps, benthic
grabs), even when modified to address these organisms, are either ineffective because they disturb
the sediment surface extensively (often prior to actually enclosing a sample), produce a shock wave
which the animals avoid, or make sample processing ambiguous because of the high level of
contamination by infaunal organism of the same general taxa (e.g., interstitial harpacticoid
copepods and gammarid amphipods). The following sampling techniques have been developed in
this region specifically for sampling epibenthic plankters which are the preferred prey of juvenile
salmon foraging in estuarine habitats and, as such, appear to sample these general assemblages
efficiently.
Epibenthic suction pumps have been developed for sampling epibenthic organism in a
variety of habitats, microhabitats, and conditions in Pacific Northwest estuaries. They all have the
same basic design, in which a sampling cylinder with fine-mesh (usually 0.130-mm or 0.252-mm)
screened ports is very slowly lowered to enclose an area of the bottom and segment of the
adjoining benthic boundary layer. The water volume in this sampling cylinder is then evacuated
with a water pump; all water entering the cylinder passes through the screened ports and is thus not
contaminated. Usually three to five times the volume of the cylinder is pumped. The pumped
water and epibenthos is captured and screened to one of several sieve sizes, or nested nets; the
usual geometric mesh series is 0.130-mm, 0.253-mm and 0.500-mm and selection depends upon
the specific taxa and life history stages which are to be monitored.
For large evasive epibenthic plankiers, e.g., mysids and large amphipods, a large,
gasoline-powered (13 L min: ) pump system has been used; that used by Simenstad and
colleagues in the Columbia River estuary and other sites encompasses 0.1 m 2 of the bottom and
(since it is 25 cm high) the sampling cylinder encloses 0.025 m 3 ; this system pumps water into a
sampling apparatus in which the water gravity flows through three nested nets (see above). The
system can be deployed from a small boat to depths of at least 10 m and does not require SCUBA
diver assistance.
Another version of the same design is designed for the smaller, less evasive meiofauna. It
incorporates a battery-powered bilge pump into the sampling cylinder and is thus portable and
small enough to be handled by one person if necessary. This epibenthic pump has been used
effectively in water depths approaching 2.5 m. The sampling cylinder encloses an area of 179 cm 2
of the sediment surface and is equipped with 0.130-mm ports; it is often mounted on a staff for
ease of use and for control of placement of the sampling cylinder in waters >1 m deep.
Most of these sampling methods are employed along constant-elevation intertidal and
shallow subtidal transects during brief (—1 hr.), discrete periods of the tidal cycle.
Unit : meiofauna (e.g., harpacticoids and juvenile
amphipods), 0.018 m 2 ; small macrofauna (e.g.,
amphipods, cumaceans, isopods, 0.10 m 2
Periodicitv and Frequency : biweekly, March-June
Most epibenthic zooplankters have very rapid population turnover rates, especially the
harpacticoid copepods, which may turn over in two weeks. Thus, biweekly sampling is necessary
-------
Epibenthic Plankters /73
to adequate represent densities and standing stock of taxa that are univoltine, e.g., have only one
generation, and appear in only one ephemeral pulse.
Statistical Considerations (Replication) : in lieu of statistical predetermination using pilot study
or historical data; n=1S, in intertidal habitats
disuibuted randomly within uniform microhabitats
along tidal elevation strata (transect); optimum tidal
elevation = 0.0 ft (MLLW), with additional
transects recommended at +2.0 It, -2.0 It,
+4.0 ft and -4.0 ft MLLW tidal elevations in
that relative order of priority
Historical sampling of epibenthic plankters Pacific Northwest estuaries has varied from
essentially no replication to 10 replicates. However, in a recent study of epibenthic crustaceans in
mudflat and sandflat habitats, including many of the attribute taxa, the level of replication found
necessary for statistical testing of treaurient differences was found to be fifteen to twenty-five,
depending upon the natural variability of the taxa (Simenstad et al. 1991). We suggest that fifteen
replicates as a minhinwn number of replicates for monitoring these organisms. We also
recommend that a mesh size for sample retention or sieving be 0.253-mm at the largest, and
smaller mesh if early life history stages are to be monitored.
ALTERNATIVE PROCEDURES
(1) Amphipod traps:
Traps to sample epiphyta.l amphipods such as Anisoganzmaru.s pugettensis have been used
in several estuarine studies: These are usually 0.500-mm mesh bags in which algae such as Fucus
are enclosed and the bags are set at intertidal and shallow subtidal stations over a tidal cycle.
Although they provide species occurrence data, there is no estimate of the area of habitat they
effectively sample.
(2) Epibenthic sleds:
Epibenthic sleds or, in the European vernacular “sledges,” have been used in the Atlantic
for several decades to sample epibenthic crustaceans and, if large enough, can effectively sample
the more evasive taxa such as the mysids Alienacanrhomysis macropsis and Neomysis mercedis.
The more quantitative sleds have opening and closing mechanisms and flow meters (Bossanyi
195 1; Wickstead 1953; Beyer 1958; Frolander and Pratt 1962; Macer 1967; Higley et al. 1977)
when deployed from boats and others are designed to be pushed in the intertidal (Colman and
Segrove 1955) or by SCUBA-equipped divers (Sibert et al. 1977). Of these, the Sibert et al.
(1977) sled is the only one which has been documented for quantitative use in this region. The
larger, modified Higley et al. (1977) variable-height sled used in the Columbia River estuary
(Simenstad 1984; Simenstad and Cordell 1985) to sample evasive macroinvertebrates (see Evasive
Macroinvertebrates section, below) could be used in situations where water depths allow and
where very large samples are desired., but this gear is basically too large and cumbersome for most
shallow estuarine use. Yocum and Tesar (1980) also describe a similar sled which is small enough
to be utilized effectively in shallow water habitats.
(3) Epiphyte sampling:
Recent investigations suggest that many of these organisms may be associated uniquely
with epiphyte communities on eelgrass, kelps and rock (Simenstad et al. 1988a). To sample these
communities, the epiphytes must be removed intact and with as little disturbance as possible (e.g.,
-------
SAMPLING PROTOCOLS /74
slowly and under water). In the case of eelgrass, whole blades or measured segments (if there is a
consideration of difference in epibenthos in different epiphytes) of eelgrass can be slowly enclosed
in a sampling bag or cylinder and preserved whole. In the laboratory, these can be repeatedly
washed over finc-ineshed sieves to remove the epibenthic organism. Parameters are usually related
to the area of the substrate, including both sides of the eelgrass blades, and/or the standing stock of
the epiphyte (normally dry weight).
CASE STUDEES
Epibenthic pump techniques as recommended have been utilized in a large variety of Puget
Sound locations and estuanne habitats such as eelgrass meadows and mud/sandilats in northern
Puget Sound (Simenstad et al. 1988a; Thom et al. 1989); eelgrass, sandflat, and gravel/cobble in
central Puget Sound (Thom et al. 1984; Hiss et al. 1988); and in emergent marsh, mudflat, channel
and gravel/cobble habitats (including restored/created habitats) in the Puyallup River estuary (Thom
et al. 1986, 1989; Shreffler et al. 1990, 1991). These systems have also been used in coastal
estuaries such as Grays Harbor (Simenstad and Eggers 1981; Cordell and Simenstad 1981),
Wilapa Bay (Simenstad and Cordell 1988) and the Columbia River estuary (Sirnenstad 1984;
Simenstad and Cordell 1985), as well as coastal embayments such as Neah Bay (Simenstad et al.
1988b).
-------
PELAGIC ZOOPLANKTON
HABITAT OCCURRENCE
Water Column; Decapoda (larvae)
Cancer spp. (zoea)
Emergent Marsh; Daphnia spp.
Gravel-Cobble; Decapoda (larvae)
Mudflat Caliiana sa caljforniensis (larvae)
Upogebia pugettensis (larvae)
Water Column; Acarna caI forniensis
Acarna clausi
Callianassa caltforniensis (larvae)
Cancer spp. (larvae)
Cancer spp. (megalops)
Corycaeus anglicus
Corycaeus spp.
Daphnia spp.
Decapoda (larvae)
Epilabidocera wnphitrites
Epilabidocera spp.
Euphausia paqfica
Eurytemora affinis
Oikopleura spp.
Oithona similis
Parathemisto pac fica
Pseudo calanus minutiis
Teleostei (larvae)
CHARAcTERIsT ics
Pelagic zooplankton are those organisms which occupy the water column and are passive
or only weakly-swimming. Due to low motility, they are prone to the advection effects of currents
and are often found in aggregations along tidal fronts. However, they can also have the capability
in water columns with no vertical mixing and turbulence for vertical migrations over surprising
depth ranges. Thej can be both permanent members of the plankton (holoplankton) or temporary
members (meroplankton) before they metamorphose and recruit to benthic habitats. Except for
larvaceans (Oikopleura spp.) and fish (Teleostei) larvae, these are exclusively crustaceans,
including predominantly calanoid and c clopoid copepods . as well as several decapods (larvae),
euphausiids, hvperiid amphipods , and cladocerans .
PARAMETERS
Minimum ;
(1) species occurrence;
-------
SAMPLING PRO It)COLS /76
(2) settled volume;
Recommended :
(3) density and standing stoclq
Preferred ;
(4) population structure (e.g., naupliar, copepodid stages; ovigerous females); and
(5) depth-stratified diel sampling.
Species occurrence
When produced from an intensive sampling effort over time and space, or in the case of
comparatively non-motile taxa, the relative occurrence of species (providing species richness and
timing) can provide a minimal indication of the viability of estuarine wetland and nearshore
habitats, principally as an assessment of water and/or sediment quality. Species richness should be
defined as relative to life history stage, especially because the use of the habitat or different
microhabitats (e.g., depth strata) by reproductive individuals and different larval stages may a more
important supportive function than if only adults occur. Species occurrence should be represented
as both (1) mean number of species/life history stages per sample by gear and as (2) the cumulative
number of specie/life history stage by all gears over space or time because different gears have
selection biases and because zooplankton occurrence can be exceedingly patchy over space and
time.
Settled volume
One straightforward, quantitative assessment which can be relatively analogous to total
standing stock is settled volume. This is measured as the volume which the zooplankton constitute
when allowed to settle in a graduated flask or cylinder and is normally reported in milliliters (ml).
Density and standing stock
Density and standing stock are preferred monitoring parameters because they are more
definitive indicators of subtle differences in habitat quality. Habitat and microhabitat characteristics
can effect density-dependent interactions between zooplankton and their habitat which would
otherwise not be reflected by species richness. Density and standing stock are expressed, respect-
ively, as the number and biomass per unit area (e.g. no. m 2 , g wet rn 2 ) or volume (e.g., no. m 3 ,
g wet rn- 3 ) of the habitat.
Standing stock is normally expressed as wet weight (biomass), which is acceptable as long
as the weighing method is standardized to minimize variability due to different amounts of moisture
content Wet weights of zooplankton are usually obtained as preserved after excess preservative is
absorbed; the time out of the preservative should be standardized because drying can be quite rapid
under these circumstances, especially if an alcohol is used as the preservative.
Due to these sources of variability, which can often introduce considerable bias, the
optimum method to express standing stock is as dry weight or as ashfree dry weight. Dry weight
is defined as the biomass after drying at 100°C until the weight has stabilized (typically >48 hours
for fish). Ashfree dry weight is the biomass of organic matter combusted at 500-600°C for >24 hr.
Both of these, especially the latter, are somewhat more labor- and time-intensive methods for
zooplankton but are a more precise measure and should be encouraged in production estimates are
intended.
-------
Pelagic Zooplankton /77
As in species occurrence, density and standing stock should be expressed relative to
species and life history stage.
Population tructure
Zooplankton population structure can be an important indication of habitat function because
verification of resident populations can only be determined through verification of reproduction and
contiguous life history stages. At a minimum, life history stages should be classified for a
subsample of the collections. In the case of most zooplankton, this will take form of five broad life
history classes: (1) nauplii; (2) copepodids; (3) nonreproductive females; (4) males; and (5)
ovigerous females. If it is desirable to document these stages in more detail, the various naupliar
and copepodid stages should also be distinguished.
Depth-stratified did sampling
Despite a planktonic lifestyle, vertical distribution of zooplankton can vary considerably
over diel cycles due to actual behavioral migration through the water column. For this reason,
monitoring of viable zooplankton populations should document density, standing stock and
population structure in different depth strata of the water column over diel periods. At a minimal,
this would entail sampling during representative nocturnal and diurnal times, but would optimally
cover crepuscular periods as well.
RECOMMENDED SAMPLING METHODS
Method : paired (bongo) nets, towed at fixed depths
equipped with 333-jim mesh
Many zooplankton and ichthyoplankton collections have been made in Puget Sound using
paired nets in a “bongo” configuration. The most common bongo net configuration uses a 60-cm
diameter mouth opening equipped with 0.333-mm or 0.500-mm mesh nets, and often with one of
each due to the efficiency of each mesh type for zooplankton versus ichthyoplankton. In estuaries,
which may have strongly-stratified water masses, tows should be conducted over a fixed time (5-
to 10-mm.) at a constant depth (determined by wire angle and length or by time-depth recorder).
Although fixed sampling time will somewhat standardize the volume of water passing through the
nets (as long as vessel speed is constant), one or (preferably) two flow meters should be installed
inside the net openings to provide precise sampling volumes. In some situations, such as strongly
mixed water masses, art oblique haul from depth to the surface, or a combination of the two as a
stepped tow which involves continuous towing at several depths may be appropriate. Sampling
should be conducted in surface layer, as many attribute taxa are found concentrated in this
microhabitat. Sampling “ofiboard” using a davit or boom is also preferred in order to avoid effects
of the vessel’s propwash.
Unit : 60-cm dia, net openings
Collection mesh and sieve mesh sizes can vary by attribute, but 0.333-mm is used often for
zooplankton in the same general size ranges as the identified attributes; 0.500-mm may be used if
only larger taxa are being monitored.
Periodicity and Frequency : monthly, March-August
-------
SAMPLING PROTOCOLS /78
Statistical Considerations (Replication) : in lieu of statistical predetermination using pilot study
or historical data; n=S, standardized or, if
determining vertical migration, stratified by time of
day
Even when using multiple-net sampling methods, it is worthwhile to obtain replicated
pelagic zooplankton samples because of the usual heterogeneous spatial disthbution of these
organisms. Most studies take three to five samples. Optimum sampling times would be associated
with dawn and dusk periods, when vertical migrators are nearest the surface layer. Estuarine
sampling, however, should be stratified more by tidal stage, and encompass at least flood and ebb
slack tides during both neap and spring tidal series.
ALTERNATIVE PROCEDURES
(1) Ring and other single towed nets:
Ring plankton nets have been the archetypical zooplankton sampling gear throughout the
contemporary era of marine science. Their inherent problem, however, is that they are difficult to
use in a quantitative manner and are extremely vulnerable to contamination when used to sample
subsurface depth strata. For this reason, we recommend using the “Puget Sound” net (Miller et al.
1984), which was developed specifically for efficiently sampling large, relatively evasive
zooplankton in this region. This net is a vertically-hauled closing net which has a 1-rn diameter
mouth opening and is messenger operated. While the net’s mesh size can vary according to the
size of the attribute(s) specifically desired, the net equipped with 0.333-mm mesh has been used to
sample most ta.xa and life history stages of concern as attributes which axe preferred prey taxa of
fishes.
Rey et a!. (1988) describe a towed net which is designed to sample zooplankton just
beneath the water surface in very shallow estuarine habitats, such as over tidal flats and in
emergent marshes. The net was 91.4 cm deep X 20.3 cm wide X 167.6cm long and was
constructed of either 0.202-mm or 0.065-mm mesh. In their comparison with a shallow water
pumping apparatus (see below), the authors recommended combining the two gears to obtain
optimum sampling efficiency.
(2) Multiple, opening-closing net systems:
An alternative to using consecutive hauls to sample different depth strata with a single
opening-closing net is a multiple net sampling devise. One such sampler is that described by Be
(1962), as modified by Weikert and John (1981) to carry five nets programmed to open and close
at predetermined depths.
(3) Vertical profiling pumps:
Pumps which suction water from discrete depth strata, often simultaneously, can be
effective in sampling zooplankton, although there is some question of zooplankton detection and
evasion of the velo ity field in small aperture (e.g., 4-mm) suction intakes (Singarajah 1969,
1975). Miller and Judkins (1981) compile a number of advantages of vertical pump systems,
including: (1) reliable measurement of the volume filtered under all conditions of clogging, ship
velocity, and depth of sampling; (2) reliable control of the filtration process with the potential for
sequential use of several mesh sizes; (3) absolute reliability of the “opening-closing” mechanism
when vertically stratified samplers are desired (4) simplicity in control and monitoring of the depth
of sampling; (5) capability for sampling all of the lower trophic levels, all of the physical
• parameters, and all of the nutrient, pollutant, and trace element concentrations in exactly the same
water at exactly the same time; and (6) capability to take long sets of sequential samples of analysis
-------
Pelagic Zooplankton /79
of small-scale distribution. Due to their low filtration rates, relative to towed nets, pumps may
only be useful were plankton densities can be assessed in at most 5 to 10 m 3 of water. Miller and
Judldns (1981) describe several pump systems which have been proven effective in sampling
coastal and estuarine zooplankton; this reference would be most useful in examining the different
options for a pumpsystem to sample zooplankton in particular situations. Although to our
knowledge they have not been used in this region, Coughian and Fleming (1978) and Rey et a!.
(1987) also describe pump sampling apparatii specifically designed for sampling in very shallow
estuarine habitats such as emergent marsh channels; this apparatus should be investigated for these
special situations in which the larger pump systems would not be operable. In their comparison
with a shallow water pumping apparatus (see below), the authors recommended combining the two
gears to obtain optimum sampling efficiency.
(4) Plankton purse seine:
A plankton purse seine which was found under some circumstances to be more effective in
sampling fish larvae was described by Murphy and Clutter (1972). Similar to the purse seines
described for sampling motile fishes (see below), this net is 30-rn long and relatively shallow (6.4
m) and is set and pursed in a circle which was found during tests to enclose 356 in 2 ; the net,
however, is constructed of 0.333-mm mesh plankton netting. This could be an effective sampling
technique for the more evasive components of the zooplankton community, particularly larval
fishes, but its large aspect relative to water flow through it may cause tremendous problems under
even minor current and wind conditions.
CASE STUDIES
Both the “Puget Sound” and Be multiple net zooplankton sampler have been used in Puget
Sound. and particularly in Hood Canal, by Frost (1985, 1988) and his students and coworkers
(Ohman 1985, 1986; Runge 1985). Miller et al. (1977) and Fresh et al. (1979) provide
quantitative data using a bongo net in southern and northern Puget Sound, respectively, and
Chester et al. (1979) provide similar data for the Strait of Juan de Fuca. One of the few
documentations of zooplankton sampling with a vertical profile pumping system is that of Beers et
a!. (1967).
-------
NEUSTONIC AND DRWF IN VERTEBRATES
HABITAT OCCURRENCE
Emergent Marsh; Araneae (unid.)
Chironomidae (unid.)
Diptera (unid.)
Ephydridae (unid.)
Heleidae (unid.)
Water Column; Insecta (unid.)
Insecta (larvae)
Scoloidea (unid.)
CHARACTERISTICS
A distinct assemblage of organism is comprised of adult and larvae insects which are
deposited onto or emerge into the surface layer, and certain other aquatic insects and crustaceans
which spend most of their time in the surface layer of the water column.
PARAMETERS
Minimum ;
(1) species occurrence;
Recommended ;
(2) density and standing stock; and
Preferred ;
(3) diel emergence.
Species occurrence
When produced from an intensive sampling effort over time and space, the relative
occurrence of species (providing species richness and timing) can provide a minimal indication of
the viability of estuarine wetland and nearshore habitats, principally as an assessment of water
and/or sediment quality. Species richness should be defined as relative to life history stage,
especially because the use of the habitat or different microhabitats (e.g., depth strata) by
reproductive individuals and different larval stages may a more important supportive function than
if only adults occur... Species occurrence should be represented as both (1) mean number of
species/life history stages per sample by gear and as (2) the cumulative number of specie/life
history stage by all gears over space or time because different gears have selection biases and
because neustonic invertebrates occurrence can be exceedingly patchy over space and time.
Density and standing stock
Density and standing stock are preferred monitoring parameters because they are more
definitive indicators of subtle differences in habitat quality. Habitat and microhabitat characteristics
can effect density-dependent interactions between zooplankton and their habitat which would
-------
Neusconic and Drift Invertebrates / 81
otherwise not be reflected by species richness. Density and standing stock are expressed,
respectively, as the number and biomass per unit area (e.g. no. nr 2 , g wet m 2 ) or volume (e.g.,
no. m 3 , g wet nr 3 ) of the habitat.
Standing stock is normally expressed as wet weight (biomass), which is acceptable as long
as the weighing method is standardized to minimize variability due to different amounts of moisture
content Wet weights of neustonic invertebrates are usually obtained as preserved after excess
preservative is absorbed; the time out of the preservative should be standardized because drying
can be quite rapid under these circumstances, especially if an alcohol is used as the preservative.
Due to these sources of variability, which can often introduce considerable bias, the
optimum method to express standing stock is as dry weight or as ashfree dry weight. Dry weight
is defined as the biomass after drying at 100°C until the weight has stabilized (typically >48 hours
for fish). Ashfree dry weight is the biomass of organic matter combusted at 500-600°C for >24 hr.
Both of these, especially the latter, are somewhat more labor- and time-intensive methods for
neustonic invertebrates but are a more precise measure and should be encouraged in production
estimates are intended.
As in species occurrence, density and standing stock should be expressed relative to
species and life history stage.
Diel sampling
The occurrence and distribution of neustonie invertebrates can vary appreciably over diel
cycles due to actual behavioral migration through the water column, which often occurs specifically
during crepuscular or nocturnal periods. For this reason, monitoring focused on the identification
of neuston should document density, standing stock and population structure over diel periods. At
a minimum, this would entail sampling during representative nocturnal and diurnal times, but
would optimally cover crepuscular periods as well.
RECO !MENDED SAMPLrNG METHODOLOGY
Methodi neuston net equipped with 253- .tm mesh net
Neuston nets are essentially modified plankton nets which are designed to float on the
surface of the water with their mouth opening sampling just the water surface layer. Usually these
are hand towed, held in an active current, or towed outboard of a small boat. Maintenance of a
constant depth (position at which the net sits in the water) and in situ (within the net) or
simultaneous measurements of current velocities are required in order to determine the sampling
volume. Hodson et al. (1981) describes one example of a surface microlayer/neuston net which is
designed for estuarine habitats. A more elaborate system of two 0.36-rn 2 nets operated in front of
a small boat is described by Miller (1973), and would be highly effective for long-shore and open
water transect sampling.
Unit : 0.025 rn 2 mouth opening
Periodicity and Frequency monthly, during discrete freshwater and
tidal flow phases
Sampling should be conducted during representative periods of tidal inundation (flood tide)
and exposure (ebb) in order to evaluate neuscon import and export, respectively, into/out of the
habitat.
-------
SAMPLING PROTOCOLS /82
Statistical Considerations (Replication) : in lieu of statistical predetermination using pilot study
or historical data; n=S. In the few studies of
estuanne neuston which have taken place in the
Pacific Northwest, the sample size has vaned from
three to five.
ALTERNATIVE PROCEDURES
(1) Emergence traps:
Unlike neuston nets, which are designed to sample what is available in the neuston,
emergence traps sample insects and crustaceans which enter the neuston. They can either entrain
only the surface, in sampling the insects which emerge as adults, or they can encompass the whole
water column in order to sample those organisms which migrate to the water column but don’t
necessarily leave it. Youngbluth (1982) describes three traps to sample migrating demersal
zooplankton which could be modified to encompass the entire water column and surface layer.
However, to ow knowledge, only the emergence trap described by LeSage and Harrison (1979)
has been employed in the Pacific Northwest. These traps cover 0.5 in 2 and are constructed of
0.202-mm mesh netting.
CASE STUDIES
While neustonic organisms are recognized to comprise a unique, important component of
estuarine habitats, the only discrete documentation of this assemblage in this region of which we
are aware is that of the neuston entering the restored Lincoln Avenue Wetland in the Puyallup River
estuary (Schreffler et at. Submitted a & b). Whitehouse et at. (1989) provide data from emergence
trap deployment in both natural and developed estuarine habitats in British Columbia. Recent
studies (Thom et at., in prep.) have utilized both neuston nets and emergence traps in the same
restored wetland system to document fish prey availability and production over a diel period.
-------
EVASIVE MACROEPIFAUNA
HABITAT OCCURRENCE
Eelgrass; Alienacanzhon7ysjs ‘nacropsis
Cancer magister
Crangon spp.
Hemigrapsus nudis
Hippolytidae (unid.)
Emergent Marsh; Cancer produczu
Crangon spp.
Hemigrapsus spp.
Neomysis mercedis
Orchestia traskiana
PacWcastaczjg leniusculus
Gravel-Cobble; Cancer magister
Cancer spp.
Crangon spp.
Hemigrapsus nudis
Hemigrapsus spp.
Hepracarpus spp.
Hippolytidae (unid.)
Neomysis mercedis
Paqflcagtacus leniuscului
Pugettia gracilis
Mudflat Archaeomysjs grebnirzkii
Cancer spp.
Crangon spp.
Hemigrapsus spp.
Nearshore Subtidal Soft Bottom; Crangon spp.
Hemigrapsus spp.
Neomysis mercedis
Nearshore Subtidal Hard Substrate; Eisa/us spp.
Heptacarpus spp.
Lebbeus spp.
Octopus spp.
Pwzdajz s danae
Spirontocarjs spp.
Sandulat Cancer magisrer
Crangon spp.
-------
SAMPLING PROTOCOLS /84
Water Column; Gonatidae (unid.)
Loligo opalescens
CHARACTERISTICS
Evasive macroepifauna include those macroinvertebrates which are associated with the
bottom, either on itor epipelagic in moving up into the water column immediately above it, and
which are highly motile. They therefore have the ability to avoid static and slow-moving sampling
gears.
PARAMETERS
Minirnuni
(1) species occurrence;
Recommended :
(2) density and standing stock (wet weight biomass);
Preferred ;
(3) population structure (e.g., length frequency distribution, life history stage,
reproductive status).
Species occurrence
When produced from an intensive sampling effort over time and space, the relative
occurrence of species (providing species richness and timing) can provide a minimal indication of
the viability of estuarine wetland and nearshore habitats, principally as an assessment of water
and/or sediment quality. Species richness should be defined as relative to life history stage,
especially because the use of the habitat by reproductive individuals and juveniles is a more
important supportive function than if only adults occur. Species occurrence should be represented
as both (1) mean number of species/life history stages per sample by gear and as (2) the cumulative
number of specie/life history stage by all gears over space or time because different gears have
selection biases and because macroinvertebrate occurrence is typically patchy over space and time.
Density and standing stock
Density and standing stock are more definitive indicators of subtle differences in habitat
quality because habitat characteristics can effect density-dependent interactions between the these
macroinvertebrates and their habitat which would otherwise not be reflected by species richness.
Density and standing stock are expressed, respectively, as the number and biomass per unit area
(e.g. no. rn 2 , g wet m 2 ) or volume (e.g., no. rn 3 , g wet m 3 ) of the habitat.
Standing stock is normally expressed as wet weight (biomass), which is acceptable as long
as the weighing method is standardized to minimize variability due to different amounts of moisture
content. Like fish, macroinvertebrates are usually weighed fresh (damp) after excess water is
toweled off. Macroinvertebrates preserved in forrn 1in or alcohol can also be weighed in this
manner but the standing stock values should expressly state that they are preserved wet weights
and the time out of the preservative should be standardized because drying can be quite rapid under
these circumstances.
Due to these sources of variability, which can often introduce considerable bias, the
optimum method to express standing stock is as dry weight or as ashfree dry weight. Dry weight
is defined as the biomass after drying at 100°C until the weight has stabilized (typically >48 hours
-------
Evasive Macroepifauna /85
for fish). Ashfree dry weight is the biomass of organic matter combusted at 500-600°C for >24 hr.
Both of these, especially the latter, are extremely labor- and time-intensive measures for -
macroinvertebrate biomass estimates and are generally not warranted unless production or some
other sensitive bioenergetic indices are intended.
As in species occurrence, density and standing stock should be expressed relative to
species and life history stage.
Population structure
Macroinvertebrate population structure may an important indication of the function of an
estuarine habitat because critical assessment criteria such as reproduction and recr iitment can only
be assessed by data on reproductive state and life history stage, respectively. At a minimum, life
history stages should be classified for a subsample of the collections. In the case of most
macroinvertebrates, this will take form of three broad life history classes: (1) juvenile, recently
settled through all instar stages; (2) subadult or non-reproducing; and (3) ovigerous females; in
addition, mating pairs (for crabs) and recently molted individuals may also be recorded.
Length, and less commonly weight, frequency distributions can often be used to
differentiate different size classes within these life history stanzas, and can be important indications
of different recruitment events, i.e., short-term age differences. Macroinvertebrate length can be
measured by a variety of standard techniques and several “standards” are used for different
macroinvertebrates in this region: (1) maximum carapace width (excluding lateral teeth) is
commonly used for all crabs; (2) tip of rostrum to the tip of the telson for shrimps and mysids; and
(3) anterior tip of the carapace (including rostrum if present) to tip of telson with the animal
stretched to full length in the case of amphipods. A sample for length measurements must be
completely random and of sufficient size to represent the distribution; typically, a mini,num of 25
to 50, and often 100, are required depending upon the variability.
RECOMMENDED SAMPLING METHODOLOGY
Method : emergent marsh and gravel-cobble habitat, SCUBA
transect observations; mudflat and sandflat
habitats, sinking beach seine; eelgrass, and
nearshore subtidal soft-bottom habitats, bottom
(staffbeam) trawl; nearshore subtidal hard
substrate habitat, SCUBA quadrat sampling
with airlift (Venturi) sampler; water column,
mid-water trawl
(1) SCUBA transect observations and sampling:
While there are variants on the general methodology, all SCUBA transect observations
basically involve SCUBA-equipped divers recording observations or taking quadrat samples along
measured underwater “strip” transects on the species, size, activity, etc. of fish and
macroinvertebrates. Transects can be either permanently fixed (e.g., with markers or line), so they
can be consistently revisited, or impermanent and measured before or after the SCUBA
observations. The length of permanent transects are usually established by the length of the line or
by the distances between markers as measured in situ; impermanent transects are usually measured
as between buoys which are typically released at the beginning and the end of the dive and the
distance measured directly or with navigation aids. While the permanent transect, or some similar
modification (e.g., a temporary transect line) establishes the exact transect length, the impermanent
transect should be considered a minimum distance, since dives seldom involve linear paths.
-------
SAMPLING PROTOCOLS /86
In the case of strip transects (i.e., continuous observations), the area swept is estimated as
the transect distance multiplied by a transect path width, which can either be a (minimal) set
distance or estimated as the visibility (at that time) for effective observation of the fishes; given the
variable visibility in Puget Sound estuaries, the latter method is recommended for optimum
standardization of data collection. A common method of establishing effective transect width is to
measure the distance at which a standard target (Secchi disk) disappears and reducing this by a
factor (usually 112) to account for the visibility required to make reliable observations (see Moulton
1979). Examples of permanent, set area transects are those of 23-rn X 6.1-rn and 53-rn X 6.1-rn
used by Hueckel et al. (1983) in their studies of artificial reefs in Puget Sound and Simenstad et
aL’s (1988) continuous transects 1-rn wide to evaluate the demersal fishes in the subtidal portions
of Neah Bay. Strip transects observations can either be made by two divers independently,
covering the entire transect width, or by two divers each making simultaneous observations along
each side of the transect line. The data treatment is, however, is different in these two cases; in the
former case, a mean or consensus must be generated from the two divers’ observations, and in the
latter case the two divers’ observations are additive. In both cases, however, true replicate
sampling of the transect should involve repeated sampling of the transect.
In the case of quadrat sampling, the quadrats are usually placed randomly, sometimes
systematically, along the transect using measured distances along the transect. Counts and samples
are then taken of the fauna within the quadrat. Quadrat size varies according to the size of the
larger, more evasive epifauna, but usually 0.25-rn 2 and 0.50-rn 2 quadrats are used in sampling
shrimps. In order to sample the more evasive shrimps (Hippolytidae, Eualus spp., Heptacarpus
spp., Lebbeus spp., Pandalus danae, Spironticaris spp.) and amphipods (Orchesria waskiana), an
air-lift or Venturi suction sampler is utilized to vacuum up these animals from the turf algae and
other substrate material, sometimes in conjunction with it being scraped (see Surface Epifauna).
These are essentially the same air-lift samplers used for sampling in unconsolidated sediments
(e.g., Brett 1964; Barnet and Hardy 1967; Christie and Allen 1972; Tunberg 1983; Benson 1989).
(2) Sinking beach seine:
The 37- X 2-rn beach seine used to sample evasive macroinvertebrates is the same as that
advocated for sampling sedentary fish (see below) and is designed to sink to the bottom in depths
>2 m. The 18-rn wings composed of 3-cm mesh are joined to a 2-rn H X 2.4-rn W X 2.3-rn D bag
of 6-mm mesh. A detailed description of the net and the protocols associated with its deployment
occurs in Puget Sound Estuary Program (1990a). It is usually deployed 30 m from shore and
parallel to the shoreline from an outboard or row boat. Hauling lines are attached to poles at each
end of the wings and the net is pulled simultaneously and evenly by two shore parties spaced 40-rn
apart. After 20 m of the lines have been hauled in, and the wings are perpendicular to shore, the
shore parties move to Within 10 m of each other and the net is hauled directly to the beach for the
final 10-rn to shore. During all times that the net is sweeping shallow water, effort should be made
to keep the leadline in direct contact with the bottom. Deployed in this manner, the net samples
520 m 2 and 790 m 3 . Some differences in sampling efficiency of beach seines (for fish) have been
documented when the net is deployed over fine (higher efficiency) versus coarse (lower) substrates
(Parsley et al. 1989), although the nets efficiency for macroinvertebrates has not been examined.
Nonetheless, sampling efficiency should be a major consideration when comparing habitats which
differs significantly in substrate size.
(3) Bottom and midwater trawls:
Due to its performance and the ground-rope or “tickler chain” effect in increasing the
capture efficiency of burrowing macroinvertebrates (Kruipers 1975; Creutzberg et al. 1987), a
beam trawl is recommended as the methodology of choice for the demersal taxa among these
attributes, and specifically for Cancer magister, and Crangon spp. In this region, the 3-rn plumb
-------
Evasive Macroepifauna /87
staffbeam trawl has been used almost exclusively in estuarine sampling. This trawl is composed of
similar materials (the codend liner is of 0.4-cm material) but differs in that a solid pipe or beam
keeps the net opening constant, as compared to the trynet in which the net opening can be distorted
in different conditions, even during the same tow. When deployed, the net has an effective width
of 2.3 m (Gunders5n and Ellis 1986). The method of using this specific gear, however, is
otherwise similar to the trynet. (3underson et al. (1985) develop a concise case for bottom trawl
sampling and describe a comprehensive, systematic sampling design appropriate for assessing
Cancer magister density and population dynamics.
Slightly larger (e.g., 5.5-rn and 6-rn) beam trawis have been adopted by investigators and
research institutions in other regions such as the North Sea (Kuipers 1975; Cruetzberg et al. 1987).
Although some trawis vary in the number of ground-ropes or “tickler chains,” this does not appear
to affect gear efficiency for different taxa in muddy habitats. However, different tickler chains
have definitely been found to affect the gears’ selectivity for some taxa which burrow in or cling to
sandy substrates. Thus, if maximally efficiency is required in estimating density and standing crop
of these taxa, consideration should be given to increasing the ground-rope effect strict comparison
of habitats, however, would not per se require such modification.
While most of the taxa in this attribute group are demersal forms, the squids (Gonatidae,
Loligo opalesceM) and shrimp (Pandalus danae) tend to be epipelagic or at least extensively
epibenthic and thus not effectively sampled by bottom trawl gear. When sampling these particular
taxa, a midwater trawl will be required. A 9.2-rn midwater trawl which has been used extensively
for assessment of spawning hernng populations in Puget Sound is appropriate for sampling squid
and shrimp if it can be deployed in near-bottom depths. This net is a four panel trawl with a 9.2-rn
headrope and footrope and 9.2-rn sides designed to open 6.1 rn vertically and horizontally
(Trumble et al. 1982). Mesh sizes taper from 7.6-cm stretch mesh in the wings to 1.3-cm stretch
mesh in the cod end liner. Floats were used on the headrope and chain on the footrope to optimize
the vertical opening. However, we know of no’exact measurement of the net opening and the
variability of this areal dimension under fishing conditions. In the absence of this measurement,
37.2 m 2 will have to be assumed. The net was fished with 31 kg, metal, V-type trawl doors,
which were connected to the side panels by 55-rn dandylines. Standard tow times (e.g., 30-60
mm) must be maintained as a common unit of effort; in addition, it is highly recommended that the
net be equipped with flow meters to provide more precise measurement of the distance sampled by
the trawl; alternatively, exact positions at which the net was deployed and retrieved should be
determined by loran or other high-resolution geographic location system. Trawl depth should be
maintained using a depth sensor mounted on the trawl door, with telemetry sent to the vessel.
variable according to method; SCUBA
transect, seine and trawl should sample at
least 250-1,000 m 2 ; quadrat samples should
be 1 m 2
Periodicitv and Fre4uency : monthly, March-September
Statistical Considerations (Replication) : in lieu of statistical predetermination using pilot study
or historical data; n=5
A minimum of three replicate samples is recommended for trawis, beach seines and
epibenthic sleds, and five to ten samples should be considered for subtidal quadrat sampling with
the airlift sampler.
-------
SAMPLING PROTOCOLS /88
ALTERNATIVE PROCEDURES
(1) Epibenthic sleds:
Epibenthic sleds or, in the European vernacular “sledges,” have been used in the Atlantic
for several decades to sample epibenthic crustaceans and, if large enough, can effectively sample
the more evasive taxa such as the mysids Alienacanthomysis macropsis and Neomysis mercedis.
The more quantitative sleds have opening and closing mechanisms and flow meters (Bossanyi
1951; Wickstead 1953; Beyer 1958; Frolander and Pratt 1962; Macer 1967; HIgley et al. 1977)
when deployed from boats and others are designed to be pushed in the intertidal (Colman and
Segrove 1955) or by SCUBA-equipped divers (Sibert et al. 1977). To our knowledge, the only
sled used specifically to sample evasive macroinvertebrates in this region is the modification of the
Higley et al. (1977) variable-height sled used in the Columbia River estuary (Simenstad 1984;
Simenstad and Cordell 1985). The Columbia River version has a mouth opening of I-rn X 0.25-rn
and could be used with one net or two nets sampling half the mouth area. Net mesh sizes were
vanable, depending upon the epibenthic organisms being targeted in the sampling, but were
generally 0.253-mm or 0.500-mm when sampling mysids (specifically Neomysis mercedis). The
sled can be opened and closed by a cable-mounted triggering device, which should especially be
used when deploying the net in deep channels, when contamination from water column organisms
is particularly desirable. Propeller flowmeters installed at the mouth of the net(s) recorded the
sampling volume.
All subtidal sampling locations should be established precisely using electronic means such
as day-screen radar with built-in variable range markers (VRM), high-resolution lorans with
multiple navigation capabilities, satellite navigation using a global positioning system (GPS), and
video depth sounders and plotters. P11 Environmental Services and the School of Fisheries,
University of Washington (1991) describe in detail the use of these devices for precision trawl
sampling.
CASE STUDIEs
Bottom trawls, particularly the 3-rn staffbeam trawl, have been used recently and in a
diverse array of locations and habitats in Puget Sound to sample quantitatively juvenile Dungeness
crab (Dinnel et al. 1986, 1987; Armstrong et al. 1987). A more extensive database is available for
the same gear and sampling strategy from coastal estuaries of Washington, particularly Grays
Harbor (Stevens and Armstrong 1984, 1985; Gunderson et al. 1985-, 1990; Dumbauld et al. 1986;
Rogers et al. 1989); the Grays Harbor collections are particularly illustrative of sampling for
population dynamics parameters. Both bottom trawls and epibenthic sleds were utilized by
Simenstad (1984) and Simenstad and Cordell (1985) to gather quantitative data on the distribution
and abundance of divergent groups of evasive macroinvertebrates in the Columbia River estuary.
Hueckel and Buckley (1987) and Benson (1989) have conducted quadrat sampling of shrimps and
amphipods from the turf algae habitat which has developed on many of the artificial reefs built in
Puget Sound. Simenstad et al. (1988b) included both bottom trawl and SCUBA transect sampling
of evasive macrofatina in Neah Bay.
-------
SEDENTARY FISH
HABITAT OCCURRENCE
Eelgrass eptocottusarinazus
Lunzpenw sagitra
Plazichthys stellatus
Porichthys notatus
Psettichthys melanosticrzis
Emergent Marsh; Cotrzis spp.
Leprocotrus armatjjs
Platichthys stellatus
Gravel-Cobble; Apodichthysflavidus
PholLs Iaeta
Platichthys stellatus
Mudflat, Lepidogobius lepidus
Leptocottus arinarus
Platichihys stellarus
Pleuronectes vendu,s
Nearshore Subtidal Soft Bottom; Leptocottus annatus
Sandfiat Citharichthys spp.
Cottidae (unid.)
L.eprocorriis arrnarus
Plarichihys srellatus
CHARACTERISTICS
Sedentary fish, which includes those termed “dernersal” fish, are those which are directly
associated with the substrate and are typically slow or relatively passive in their movements along
the bottom. As a result, they can be collected with sampling gears which are would be otherwise
biased by fish with avoidance capabilities (see #13 Motile fish). Thus, in most cases, sampling
efficiencies of the different methods will be more alike for the different taxa than for motile fish.
Sedentary fish can be both transient, such as the fiatfishes (e.g., Cirharichihys, Platichthys and
Pleuronecres) and relatively intransient or even territorial (e.g., Lepidogobi us, PholLc and
Apodichthys).
PARAMETERS
Minimum ;
(1) species occurrence;
Recommended :
(2) density and standing stock (wet weight biomass);
-------
SAMPLING PROTOCOLS /90
Preferred ;
(3) population structure (i.e., length frequency distribution, life history stage,
reproductive status);
(4) spawning activity;
(5) dietcomposition and daily ration;
(6) growth rate; and
(7) standing stock (dry weight or ash free dry weight).
Species occurrence
When produced from an intensive sampling effort over time and space, the relative
occurrence of species (providing species richness and timing) can provide a minimal indication of
the viability of estuarine wetland and nearshore habitats, principally as an assessment of water
and/or sediment quality. Species richness should be defined as relative to life history stage,
especially because the use of the habitat by reproductive individuals and juveniles is a more
important supportive function than if only adults occur. Species occurrence should be represented
as both (I) mean number of species/life history stages per sample by gear and as (2) the cumulative
number of specie/life history stage by all gears over space or time because different gears have
selection biases and because fish occurrence is typically patchy over space and time.
Density and standing stock
Density and standing stock are more defmitive indicators of subtle differences in habitat
quality because habitat characteristics can effect density-dependent interactions between the fish
and their habitat which would otherwise not be reflected by species richness. Density and standing
stock are expressed, respectively, as the number and biomass per unit area (e.g. no. rn- 2 , g wet
m 2 ) or volume (e.g., no. m 3 , g wet m 3 ) of the habitat.
Standing stock is normally expressed as wet weight (biornass), which is acceptable as long
as the weighing method is standardized to minimize variability due to different amounts of moisture
content. Usually fish are weighed fresh (damp) after excess water is toweled off. Fish preserved
in formalin or alcohol can also be weighed in this manner but the standing stock values should
expressly state that they are preserved wet weights and the time out of the preservative should be
standardized because drying can be quite rapid under these circumstances.
Due to these sources of variability, which can often introduce considerable bias, the
optimum method to express standing stock is as dry weight or as ashfree dry weight. Dry weight
is defined as the biomass after drying at 100°C until the weight has stabilized (typically >48 hours
for fish). Ashfree dry weight is the biomass of organic matter combusted at 500-600°C for >24 hr.
Both of these, especially the latter, are extremely labor- and time-intensive measures and are not
warranted unless fish production or some other sensitive bioenergetic index are demanded.
As in species occurrence, density and standing stock should be expressed relative to
species and life history stage.
Population structure
Population structure is an important indication of the function of an estuarine habitat for
fish because critical measures such as reproduction and recruitment can only be assessed by data
on reproductive state and life history stage, respectively. While a few populations may be assumed
relatively homogeneous in some estuarine habitats, e.g. young-of-year recruits of Pleuronecres
vetulus, because the other life history stages utilize predominantly other habitats, basic information
on length, weight, sex, sexual maturation, and age may be required to describe the population
-------
Sedentary Fish/91
structure. At a minimum, life history stages should be classified for a subsample of the
collections. By classifying by life history stage, “relative” classes are ascribed on the basis of
some knowledge of the taxa. Usually, this takes form of classifying life history stage by: (I)
embryo; (2) larva; (3) juvenile; (4) subadult or non-spawning adult; (5) spawning or sexually
mature adult; and ( ) senescent adult; see Balon (1975) for more details about distinguishing these
intervals of fish development. Sexual maturity or spawning state can be made by normal internal
examination of the gonads, although in some instances can be made externally. In addition to
individual fish examination, non-destructive observations can also form important measures of
reproductive activity. For instance, Porichrhys notatus spawns in shallow sublittoral and intertidal
habitats under rocks, and can be observed either by SCUBA-equipped diving or by gently
checking under rocks during low tide periods.
Length, and less commonly weight, frequency distributions can often be used to
distinguish size classes within these life history stanzas, and can be important indications of
different recruitment events, i.e., short-term age differences. Fish length can be measured by a
variety of standard techniques and several “standards” have evolved for different taxa among the
Pacific Northwest fishes: (1) total length (tip of snout to tip of tail) is commonly used for all taxa
with robust snouts and caudal fins, such as sculpins and rockfish; (2) fork length (fork of tail to tip
of Snout) S more commonly used for fishes which have deeply incised caudal fms which can often
erode, e.g., herring, smelts and salmon; and (3) standard length (tip of snout to end of hypural
plate) is not common for any of the sedentary fish included as attributes in the Protocol (see Fig. 4
of Wydoski and Whitney [ 1979] for an illustration of the differences in these measurement
techniques). A sample for length measurements must be completely random and of sufficient size
to represent the distribution; typically, a minimwn of 25 to 50, and often 100, are required
depending upon the variability.
Aging of fish is an effort- and time-intensive process which is seldom required for
monitoring habitat function, especially in transient fish populations. It does, however, have some
value in assessing the potential recruitment chronology of certain fish taxa which are known to be
highly territorial and intransient (e.g., certain species of Sebastes). Aging is conducted normally
by counting distinguishable yearly growth rings (annuli) on the scales or in the otoliths of the fish.
Anderson and Gutreuter (1983) and Cailliet et al. (1986) are valuable references for further
information and detailed descriptions of procedures for length, weight, age, sex, diet and other
standard determinations for fishes.
Spawning activity
• In addition to the basic enumeration of fish species, life history stages and estimates of
sizes, quantitative observations can often be gathered on spawning activity. In particular,
spawning activity by sedentary fishes in shallow subtidal rocky substrate habitats can be assessed
during SCUBA surveys either directly as the occurrence of spawning or of nest guarding or
indirectly as territorial defense by fishes which indicates an egg mass nearby. In gravel-cobble
habitats, spawning of fishes in the low intertidal zone can also be assessed during transect surveys
by examining beneath rocks for nests of pholids, gunnels and Porichthys.
Diet composition and daily ration
In contrast to motile fishes, which we cannot assume have necessarily fed within the habitat
being sampled, most sedentary fishes remain Within their habitats long enough to make their diets
useful indicators of habitat quality. Taxonomic composition of the diet is useful for fish which are
known to be selective feeders but, conversely, is of no real utility for generalistic feeders. Thus,
extensive baseline data is required on the universality of specific prey of these fishes in different
-------
SAMPLING PROTOCOLS /92
estuanne habitats; in general, this is only available for a restricted number of fishes in a few
habitats. Therefore, at this time, the significance of diet differences cannot be interpreted to
necessarily imply habitat differences.
In general, the description of diet must be made at the population level and document both
numerical arid gravimetric (biomass) or volumetric measures of food item “importance.” The
volume of food items should provide a comparable measure as weight, but is not used as often
because it is more difficult to measure in small amounts. Therefore, stomach contents analyses to
gather this information need to be conducted on individual fish rather than for pooled samples in
order to maintain a measure of the population utilization of the item, i.e. as frequency of
occurrence, and of the extent of any feeding selectivity. In addition to counts and weights (wet
damped, dry, or ash-free dry) of the food items in each stomach, some indices of stomach fullness
and digestion rate should also be assessed; these often involve a scale between 1 to 6 and ito 10.
Recording of the total stomach contents weight before separation into identifiable food items will
also provide, by subtraction, a measure of the weight and proportion of unidentifiable (digested)
material. One protocol for fish stomach contents analysis at this level of detail is described by
Terry (1977), and Cailliet et al. (1986) provide a helpful discussion of the important considerations
in fish diet studies.
Fish diet composition using this combination of measures is commonly represented and
illustrated according to an Index of Relative Importance (IRI) which is created for each food item i;
I.R. 1 1 = (%F.O (%N.C. +
where %F.O. = the percent frequency of occurrence, %N.C. = percent numerical composition,
and %G.C. = percent gravimethc/volumethc composition. Because the resulting numerical values
for the I.R.I depend greatly upon sample size, the relative importance is often converted to the
percent of the total I.R.I (%I.R.I.). Graphically, this is illustrated by a two dimensional figure in
which the abscissa is %F.O. and the ordinate is %N.C. above the abscissa and %.G.C. below the
abscissa. The original I.R.I. description occurs in Pinkas et al. (1971), and the approach is
modified and described further in Cailliet (1977) and Cailliet et al. (1986).
Consumption rate, as commonly measured as daily ration, is less ambiguous a measure of
the foraging success than diet composition, and would be an extremely valuable index if coupled
with growth estimates. Daily ration estimates generated from in situ sampling involves periodic
estimates of the mean stomach contents biomass over a diel period.
Non-destructive assessment of diet can also be made by enumerating the number of feeding
attacks on specific groups of prey taxa per unit of observation time during SCUBA transect
surveys. For instance, Hueckel (1980) observed feeding behavior of three species of fishes on
artificial reefs over 5-mm. periods, noting the fish species, its length interval and the type of
substrate in which it fed (all three fish species were of the “turf picker-winnower” feeding type);
this information was then related to quantitative data on the invertebrate organisms found in the
particular substrate type.
Growth rate
A mean growth rate can also be derived for a population of fish from mark and recapture
experiments, but are constrained in open systems due to the lack of information on emigration and
immigration. An alternative is the use of the widths of daily increments laid down on the otoliths,
which has been used to estimate relative growth rate (Volk et al. 1984; Neilson et al. 1985). The
distinct advantage of the otolith-derived growth estimation is that distributions of individual growth
and variance estimates are obtained, rather than a population mean. The lack of verification from in
situ experiments, however, implies that verification of the otolith increment width-ration
-------
Sedentary Fish / 93
relationship should be tested under natural conditions in the field if absolute rates are desired. In
theory, comparison of the relative growth of fishes in a mitigation/restoration habitat as compared
to a natural habitat can be validly derived from otolith microstructure; however, this remains to be
attempted at this time.
RECOMMENDED SAMPLING METHODOLOGY
Method : eelgrass, mudflat and sandflat habitats, 37-rn x 2-rn
sinking beach seine with 6-mm mesh
codend; emergent marsh habitat, channel trap
nets with 6-mm mesh; gravel-cobble habitat,
SCUBA transect observations; nea.rshore
subtidal soft bottom, 3-rn bottom (staffbeam)
trawl with 4-mm codend
-(1) Sinking beach seine:
The 37- X 2-rn beach seine used to sample sedentary fish is the same as that advocated for
sampling motile fish (see below) but does not have flotation along the toprope, such that it sinks to
the bottom when set over depths >2 m. The 18-rn wings composed of 3-cm mesh are joined to a
2-rn H X 2.4-rn W X 2.3-rn D bag of 6-mm mesh. A detailed description of the net and the
protocols associated with its deployment occurs in the Puget Sound Estuary Program (1990a). It
is usually deployed 30 m and parallel to the shoreline from an outboard or row boat. Hauling lines
are attached to poles at each end of the wings and the net is pulled simultaneously and evenly by
two shore parties spaced 40-rn apart. After 20 m of the lines have been hauled in, and the wings
are perpendicular to shore, the shore parties move to within 10 m of each other and the net is
hauled directly to the beach for the final 10-rn to shore. Puget Sound Estuary Program (1990a)
recommend a hauling speed of 10 rn m m 4 . During all times that the net is sweeping shallow
water, effort should be made to keep the leadline in direct contact with the bottom. Fished in this
manner, the net samples 520 m 2 and 790 m 3 . Some differences in sampling efficiency of beach
seines has been documented when the net is deployed over fine (higher efficiency) versus coarse
(lower) substrates (Paisley et al. 1989), which should be a major consideration when comparing
habitats which differ significantly in substrate size.
(2) Channel trap net:
Channel trap nets are designed to capture fishes as they emigrate tidal habitats during an
ebbing tide. Most sedentary fishes will be captured by trap nets except for those that occupy
burrows and depressions during tidal exposure. Although they have been adopted extensively on
the east coast, channel trap nets (e.g., Cain and Dean 1976) and the similar flume nets (Mc lvor and
Odum 1986) have not been utilized extensively in this region. The intertidal trap net utilized by
Levy and Northcote (1982) to sample emergent marshes is one of the few and better examples of
this sampling method. Their net was 2.4-rn deep and constructed of 0.6-cm mesh. It is deployed
at high tide, stretched across a tidal channel , immediately preceding a steep tidal drop, and fastened
to stakes set into the bank along the channel. As the tide ebbs, most of the fish in the marsh
drainage area of the channel above the net, and in the channel proper, are forced into the trap or
into the pools of the channel remaining at low tide. When the channel is as dewatered as will occur
at Low tide, fish are collected from Within the trap and seined from the remaining pools. A most
effective modification, also described by Levy and Northcote, is a removable trap box which acts
as a live collection trap and permits periodic checking of the temporal disthbution and abundance of
fish exiting the channel over the ebb tide.
-------
SAr 1PLING PROTOCOLS /94
(3) SCUBA transect observations:
While there axe variants on the general methodology, all SCUBA transect observations
basically involve SCUBA-equipped divers recording observations or taking quadrat samples along
measured underwater “strip” transects on the species, size, activity, etc. of fish and
macroinvertebrates. Transects can be either permanently fixed (e.g., with markers or line), so they
can be consistently revisited, or impermanent and measured before or after the SCUBA
observations. The length of pemianent transects are usually established by the length of the line or
by the distances between markers as measured £fl situ; impermanent transects are usually measured
as between buoys which are typically released at the beginning and the end of the dive and the
distance measured directly or with navigation aids. While the permanent transect, or some similar
modification (e.g., a temporary transect line) establishes the exact transect length, the impermanent
transect should be considered a minimum distance, since dives seldom involve linear paths.
The area swept is estimated as the transect distance multiplied by a transect path width,
which can either be a (minimal) set distance or estimated as the visibility (at that time) for effective
observation of the fishes; given the variable visibility in Puget Sound estuaries, the latter method is
recommended for optimum standardization of data collection. A common method of establishing
effective transect width is to measure the distance at which a standard target (Secchi disk)
disappears and reducing this by a factor (usually 1/2) to account for the visibility required to make
reliable observations (see Moulton 1979). Examples of permanent, set area transects are those of
23-rn X 6.1-rn and 53-rn X 6.1-rn used by Hueckel et al. (1983) in their studies of artificial reefs in
Puget Sound and Simenstad et aL’s (1988) continuous transects 1-rn wide to evaluate the demersal
fishes in the subtidal portions of Neah Bay.
Transect observations can either be made by two divers independently, covering the entire
transect width, or by two divers each making simultaneous observations along each side of the
transect line. The data treatment, however, is different in these two cases; in the former case, a
mean or consensus must be generated from the two divers’ observations, and in the latter case the
two divers’ observations are additive. In both cases, however, true replicate sampling of the
transect should involve repeated sampling of the transect.
In soft sediment habitats, a modification of the strip transect method developed by Walton
and Bartoo (1976) is recommended in which a 2-rn rod is pushed along the surface of the substrate
to disrupt flatfish (e.g., Plazic/uhys and Pleuronectes) hiding in the surface layer.
(4) Bottom trawl:
Bottom trawls are sock-like nets which are usually towed with one cable behind one boat
with the mouth of the net spread apart by either flat “doors” attached to the bridles of each wing or
by a pole or “beam.” Their use as sampling gear derives from their long history as a commercial
fishing technique, although their application can be limited in situations where there axe
obstructions which will snag the towed net or where the habitat is limited in space (e.g., there is no
room to maneuver the boat and deploy the net effectively). It is, however, one of the few methods
for capturing fishes, especially moderately evasive zaxa, in subtidal habitats.
The trawl net that has been used extensively in sampling esruarine fishes in this region is
the 3-rn plumb staffbeam trawl. This trawl is composed of similar materials (the codend liner is of
0.4-cm material) to the liynet (see Alternative Procedures) but differs in that a solid pipe or beam
keeps the net opening constant, as compared to the trynet in which the net opening can be distorted
in different conditions, even during the same tow. When deployed, the net has an effective width
of 2.3 m (Gunderson and Ellis 1986). The method of using this specific gear, however, is
otherwise similar to the trynet.
It should be acknowledged that the plumb staffbeam trawl and trynet do have some
differences in efficiency due to their selection biases for/against certain taxa or fish intervals.
-------
Sedentary Fish /95
Donnelly (In prep.) has conducted a detailed comparison among the 4.9-rn and 7.6-rn bottom
trawis and 3-rn staffbeam trawis commonly used for research collections in Puget Sound and
coastal estuaries. Although his analyses at this time have not directly compared the 4.9-rn ttynet
with the 3-rn staffbeain trawl, preliminary examination of the data illustrate some notable
differences. For instance, while the 4.9-rn trynet effectively captures Pleuronecres verithis between
120 mm and approximately 250 mm total length, the 3-rn staftheam trawl is biased against fish
>170 mm in length; similarly, the 3-rn staffbeam trawl is less effective in sampling Citharichthys
sordidus >150 mm in length. Efficiency for sampling other taxa, such as Porichthys notarus, were
not significantly different between the two gears. These differences must be taken into
consideration if emphasis is being placed on attribute taxa which are particularly biased against by
one gear or if the population structure characteristics are included in the monitoring parameters.
No matter what the trawl gear chosen, the effort should be standardized. A minimal, and
not overly acceptable standard is the time during which the net is towed, e.g., 5- or 10-mm. The
difficulty using this method is that the areal extent of the sampling is prone to extreme variability
due to current and other effects. A better alternative is either by measuring the distance towed
(through a benthic metering wheel mounted on the net, navigational positioning or measuring the
distance between buoys released at the beginning and end of the trawl) or by the volume filtered
(measured as the water volume passing though the net by a flowmeter).
Location should be established precisely using electronic means such as day-screen radar
with built-in variable range markers (VRM), high-resolution lorans with multiple navigation
capabilities, satellite navigation using a global positioning system (GPS), and video depth
sounders and plotters. P11 Environmental Services and the School of Fisheries, University of
Washington (1991) describe in detail the use of these devices and a standard protocol for precision
trawl sampling.
Unit : beach seine, ‘SOO m 2 ; channel trapnets, dimen-
sions dependent upon channel; SCUBA
transects, SO-rn x 6-rn; staffbeam trawl, ‘4O0O
rn 2
Periodicitv and Frequency : monthly, March-September
Statistical Considerations (Rep1ication : in lieu of statistical predetermination using pilot study
or historical data; n=S
•Kellogg and Shreffler (1985) illustrated that if species richness or diversity are important
monitoring parameters, the necessary sample size for beach seine collections of nearshore fish
ranged between three and six, depending upon habitat. They also compared trynet samples and
found that five to ten sampleS were necessary to establish the representative number of species in a
shallow subtidal soft sediment habitat. These studies would suggest that, in general, sample size
should be set at no-less than five replicates. If monitoring is focused on the density or standing
stock of one or two attributes is the criteria, somewhat fewer replicates may be justified if a pilot
project illustrates lower variability. Given the sedentary nature of these fish, all replicates should
be non-overlapping but in identical habitat conditions.
-------
SAMPLING PROTOCOLS /96
ALTERNATIVE PROCEDURES
(1) Other beach seines:
The Puget sound Estuary Program (1990a) recommends as an alternative to the 37-rn
beach seine a 9-rn seine. Because the catchabiity of this net is likely to be more biased against
larger or more evasive fishes, we do not recommend this net except in unique circumstances. For
instance, if data on small and comparatively slow-moving fish such as young-of-the-year English
sole (Pleuronecres vetuizis) are the primary monitoring objective, this method would be appropri-
ate. This net is 8.8 m in total length, with 3.6-rn long wings. The wings are constructed of 3.9-
mm square, knotless mesh and the bag of 2.4-mm square, knotless mesh. A 6.5 m check line is
installed between the poles to ensure a constant mouth opening. Deployment is different from the
37-rn beach seine; the 9-rn seine is set perpendicular to the beach gradient (waterline) and pulled
manually along (parallel to) the beach at a speed of approximately 15 m min 1 , usually for a
previously-measured distance of 30 m, before being turned into the beach to concentrate ai)d collect
the catch. if the mouth opening is maintained at a constant length (6.5 m), the sampling area effort
will be approximately 195-200 m 2 .
(2) Other lrawls;
A net used often in shallow habitats (e.g.. intertidal mud- and sandflats), where larger
vessels are prohibited from operating, is a 4.9-rn trawl, often referred to as a “trynet.” The body
and codend are normally constructed of 1.9-cm mesh and the codend is, in addition, lined with a
bag of 0.5-cm mesh. The net can be deployed from an outboard powered boat as long as two
requirements are met: (1) the power is enough to move the net across the bottom at 1.0 to 2.0 m
s ; and (2) forward motion of the boat can be maintained when the net is retrieved from the
bottom. In the case of the latter requirement, this often means that the towing cable is stored on a
powered spool or drum which can be driven independently of the boat’s power. If the boat loses
momentum or stops during retrieval, many fish have the capability to swim out of the net. In the
absence of current effects and deployed over an even bottom type and depth range, 5-mm. tows of
this net have been estimated to sample an area and volume of 750 m 2 and 375 m 3 , respectively.
Slightly larger (e.g., 5.5-rn and 6-rn) beam trawis have been adopted by investigators and
research institutions in other regions such as the Ncrth Sea (Kuipers 1975; Cruetzberg et al. 1987).
Although some trawls vary in the number of ground-ropes or “tickler chains,” this does not appear
to affect gear efficiency for different taxa in muddy habitats. However, different tickler chains
have definitely been found to affect the gears’ selectivity for some taxa which burrow in or cling to
sandy substrates. Puget Sound Estuary Program (1990a) advocate a towing speed of 2.6 km hr 1
for the 3-rn staffbeam trawl.
(3) Drop and pop nets:
In vegetated habitats such as eelgrass and emergent marshes, beach seine and trawl
sampling can be both destructive and ineffective samplers of the fish which are associated
specifically with these habitats because they tend to integrate both vegetated and unvegetated
habitats.
Borton (1982) used a drop net to sample shallow subtidal eelgrass and sand habitats in
central Puget Sound (Aild Point) discretely.
Buoyant pop nets have been shown to effectively sample shallow unvegetated habitats and
to be useful in heavily-vegetated freshwater habitats by Dewey et al. (1989), although their size
may limit the assessment of species richness. While there is no precedence of their use in estuarine
habitats in this region, both drop and pop nets should be considered for habitats such as eelgrass.
The pop nets used by Dewey et al. (1989) were 1.8-rn wide X 3.1-rn long X 1.8-rn high when
-------
Sedentary Fish / 97
released and enclosed an area of 5.6 m 2 , the top of the net was attached to a rectangular frame
made buoyant with foam floatation. Different net arrangements had to be used for vegetated and
unvegetated habitats; the net used in unvegetated habitats had a bottom net panel, while the net used
in vegetated habitats had net panels which could be drawn (pursed) over the vegetation once the net
had been deployed .
(3) Intertidal transects:
Several of these sedentary fishes occur commonly in the intertidal zone, most notably
Apodichthysflavidus, Pholis laera, several cottids, and Porichthys notarz s during its spawning
period. Many of these can be enumerated effectively during low tide transect studies. Fishes
occurring within quadrats positioned along the transect should be thoroughly evaluated by
examining under all large rocks and cobble. If tidepools fall within the sampling unit, they should
be drained by bucketing or siphoning the water out; the fish caii also be narcotized by the
application of an ichthyocide such as Quinaldine in low enough concentrations to cause the fish to
leave hiding places but not enough to kill them. Whenever possible, basic data should be gathered
on the live fish and they should then be returned to the pool after it has been restored with fresh
seawater.
(4) Push net:
Another gear designed in many respect to sample the same small, less-evasive fishes as the
9-rn beach seine is a push net, which is especially effective for juvenile flatfishes (Kendall 1966).
One version that has been utilized in this region is the 1.5-rn push net design of Riley and Holford
(1965). This is a rigid-frame net with an opening 1.5-rn wide and 0.3-rn high, equipped with a 2-
mm mesh net. The frame and net are mounted on skis and have a handle. Sampling involves
pushing the net parallel to the depth gradient (e.g., along the 0.0 rn MLLW contour) for a
measured distance (e.g., 100 m).
CASE STUDIES
Pertinent references for techniques and comparable data for sedentary fishes in Puget
Sound are Miller et aL (1977, 1980), Fresh et aL (1979), Donnelly et al. (1984) and Thom et al.
(1989); in addition to the estuarine habitats of Puget Sound, these techniques have been used to
sample motile fishes in coastal estuaries (Simenstad and Eggers 1981; Rogers et al. 1988) and
other coastal habitats (Simenstad et al. 1988b). Miller et al. (1977), Moulton (1979), Hueckel et
al. (1983), Hueckel and Buckley (1987) all provide relatively comparable data on density and
feeding behavior of sedentary fishes observed along SCUBA strip transects in shallow subtidal
hard substrate communities; Walton and Bartoo (1976) and Walton (1982) provide similar data for
soft sediment communities. Weitkamp (1991) also describes the use of, and data on, juvenile
flatfishes using a 1.5-rn push net.
-------
MOTILE FISH
HABITAT OCCURRENCE
Eelgrass; Clupea harenguspoJiasi
Cyrntrogasrer aggregata
Embiotocidae (unid.)
EngraulLs mordax
Oncorhynchzjs spp. (fry)
Thaleichthys pac flcus
Emergent Marsh; Cymatogaster aggregata
Gasterosreus aculeatus
Oncorhynchus gorbuscha (fxy)
Oncorhynchus kera (fry)
Oncorhynchus spp. (fry)
Thaleichrhys pacyicus
Gravel-Cobble; Ammodyres hexaprerus
Clupea harenguspallasi
Cymatogasrer aggregata
Gasterosteus aculeatus
Oncorhynchus spp. (fry)
Sebastes caurinus
Tha!eich:hys pac(flczLs
Mudflat; Engraulis mordax
Gasrerosteus aculeanss
Oncorhynchus spp. (fry)
Nearshore Subtidal Soft Bottom; Ammodyres he.xapzerus
Clupea harenguspallasi
Microgadus proximus
Thaleichrhys pac(ficus
Nearshore Subtidal Hard Substrate; Ammodyres hexaprerus
Clupea harenguspallasi
Phanerodonfurcatus
Sandflat Engraulis mordax
Water Coluizm; Ammodyres hexaprerus
Clupea harenguspallosi
Cymazogaster aggregata
Engraulis mordax
Gadus macrocephalus
Gasterosteus aculeatus
Hypomesus pretiosus
Loinpetra tridentarus
Ma/lotus villosus
Merluccius pro ductus
Microgadus proximus
-------
Motile Fish /99
Oncorhynchu s gorbusc/ja (fry)
Oncorhynchus spp.
Oncorhynchu spp. (fry)
Scorpaenjdae (unid.)
Sebastes spp.
Spirinchus thaleichthys
Tha!eichthys pac ficuj
Theragra choJcogranv,
CHARACTERISTICS
As distinguished from sedentary fish, motile fish are those Species which axe active
swimmers, tend to be epipelagic or water column (also termed “neritic”) and quite often are
schooling species. This offers some particular problems to sampling them quantitatively.
Sampling methods have stressed “active” gears such as seines and trawis instead of “passive”
gears such as gillnets because sampling effort is difficult to impossible to quantify for passive
gears. We also recommend specific methods which either have extensive precedence in sampling
motile fishes (particularly juvenile salrnonids) in Puget Sound estuarine habitats, which have the
least potential for biased catches, and in which the sampling effort can be effectively quantified.
PARAMETERS
Minimu
(1) species occurrence;
Recommende
(2) density and standing stoclq
Preferred :
(3) population structure (e.g., length frequency distribution, life history stage,
reproductive status; and
(4) residence time and growth rate.
Species occurren
When produced from an intensive sampling effort over time and space, the relative
occurrence of species (providing species richness and timing) can provide a minimal indication of
the viability of esruarjne wetland and nearshore habitats, principally as an assessment of water
and/or sediment quality. Species richness should be defined as relative to life history stage,
especially because the use of the habitat by reproductive individuals and juveniles is a more
important supportive function than if only adults occur. Species occurrence should be represented
as both (1) mean number of species/life history stages per sample by gear and as (2) the cumulative
number of species/life history stage by all gears over space or time because different gears have
selection biases and because fish occurrence is typically patchy over space and time.
Density and standing stoc
Density and standing stock are more definitive indicators of subtle differences in habitat.
quality because habitat characteristics can effect density-dependent interactions between the fish
and their habitat which would otherwise not be reflected by species richness. Density and standing
-------
SAMPLING PROTOCOLS /100
stock are expressed, respectively, as the number and biomass per unit area (e.g. no. rn- 2 , g wet
rn 2 ) or volume (e.g., no. m 3 , g wet rn 3 ) of the habitat.
Standing stock is normally expressed as wet weight (biomass), which is acceptable as long
as the weighing method is standardized to minimize variability due to different amounts of moisture
content. Usually fish are weighed fresh (damp) after excess water is toweled off. Fish preserved
in formalin or alcohol can also be weighed in this manner but the standing stock values should
expressly state that they are preserved wet weights and the time out of the preservative should be
standardized because drying can be quite rapid under these circumstances.
Due to these sources of variability, which can often introduce considerable bias, the
optimum method to express standing stock is as dry weight or as ashfree dry weight. Dry weight
is defined as the biomass after drying at 100°C until the weight has stabilized (typically >48 hours
for fish). Ashfree dry weight is the biomass of organic matter combusted at 500-600°C for >24 hr.
Both of these, especially the latter, are extremely labor- and time-intensive measures and are not
warranted unless fish production or some other sensitive bioenergetic index are demanded.
As in species occurrence, density and standing stock should be expressed relative to
species and life history stage.
Population structure
Population structure is an important indication of the function of a habitat for fish because
critical measures such as reproduction and recruitment can only be assessed by data on
reproductive state and life history stage, respectively. While a few populations may be assumed
relatively homogeneous in some estuarine habitats, e.g. young-of-year recruits of Pleisronectes
vetulus, because the other life history stages utilize predominantly other habitats, basic information
on length, weight, sex, sexual maturation, and age may be required to describe the population
structure. At a minimum, life history stages should be classified for a subsample of the
collections. By classifying by life history stage, “relative” classes are ascribed on the basis of
some knowledge of the ta.xa. Usually, this takes form of classifying life history stage by: (1)
embryo; (2) larva; (3) juvenile; (4) subadult or non-spawning adult; (5) spawning or sexually
mature adult; and (6) senescent adult; see Balon (1975) for more details about distinguishing these
intervals of fish development. Sexual maturity or spawning state can be made by normal internal
examination of the gonads, although in some instances can be made externally. In addition to
individual fish examination, non-destructive observations can also form important measures of
reproductive activity. For instance, Porichthys notatus spawns in shallow sublittoral and intertidal
habitats under rocks, and can be observed either by SCUBA-equipped diving or by gently
checking under rocks during low tide periods.
Length, and less commonly weight, frequency distributions can often be used to
differentiate different size classes within these life history stanzas, and can be important indications
of different recruitment events, i.e., short-term age differences. Fish length can be measured by a
variety of standard techniques and several “standards” have evolved for different taxa among the
Pacific Northwest fishes: (1) total length (tip of snout to tip of tail) is commonly used for all taxa
with robust snouts and caudal fins, such as sculpins and rockfish; (2) fork length (fork of tail to tip
of snout) is more commonly used for fishes which have deeply incised caudal fins which can often
erode, e.g., herring, smelts and salmon; and (3) standard length (tip of snout to end of hypural
plate) is not common for any of the sedentary fish included as attributes in the Protocol (see Fig. 4
of Wydoski and Whitney [ 1979] for an illustration of the differences in these measurement
techniques). A sample for length measurements must be completely random and of sufficient size
to represent the distribution; typically, a minimwn of 25 to 50, and often 100, are required
depending upon the variability.
-------
Motile Fish /101
Aging of fish is an effort- and time-intensive process which is seldom required for
monitoring habitat function, especially in transient fish populations. It does, however, have some
value in assessing the potential recruitment chronology of certain fish taxa which are known to be
highly territorial and intransient (e.g., certain species of Sebasres). Aging is conducted normally
by counting distinguishable yearly growth rings (annuli) on the scales or in the otoliths of the fish.
Anderson and Gutreuter (1983) and Cailliet et al. (1986) are valuable references for further
information and detailed descriptions of procedures for length, weight, age, sex, diet and other
standard determinations for fishes.
Aging of fish is an effort- and time-intensive process which is seldom required for
monitoring habitat function, especially in transient fish populations. It does, however, have some
value in assessing the potential recruitment chronology of certain fish taxa which are known to be
highly territorial and intransient (e.g., certain species of Sebasres). Aging is conducted normally
by counting distinguishable yearly growth rings (annuli) on the scales or in the otoliths of the fish.
Anderson and Gutreuter (1983) and Cailliet et al. (1986) are valuable references for further
information and detailed descriptions of procedures for length, weight, age, sex, diet and other
standard determinations for fishes.
Residence time and growth rate
In the case of motile fishes, the period of occupation of a habitat may be an important index
of the habitat’s functional support of the fish. It has been argued (Simenstad and Salo 1982;
Simenstad et al. 1982; Simenstad and Wissmar 1984; Simenstad 1987; Wissmar and Simenstad
1988; Shreffleret al. 1990, 1991) that for some species of juvenile salmon (e.g., fry of pink,
chum and chinook) estuarine residence time is an important survival factor. Thus, the time spent in
specific estuarine habitats and the rate of growth of fish during that occupancy can be a valid
indication of the habitats’ importance relative to natural habitats.
Residence time is most often determined by routine mark-recapture studies, which can be
complicated in open systems sampled sporadically or relatively straightforward in closed systems
(see the design for sampling the Lincoln Avenue Wetland, Thom et al. 1988, Shreffler et al. 1990,
1991). Burnham et al. (1987) effectively present the requirements for release-recapture
experiments.
A mean growth rate can also be derived from mark and recapture experiments, but have the
same constraints in open systems due to the lack of information on emigration and immigration.
An alternative is the use of the widths of daily increments laid down on the otoliths, which has
been used to estimate relative growth rate (Volk et al. 1984; Neilson et al. 1985). The distinct
advantage of the otoith-derived growth estimation is that distributions of individual growth and
variance estimates are obtained, rather than a population mean. The laók of verification from in situ
experiments, however, implies that verification of the otolith increment width-ration relationship
should be tested under natural conditions in the field if absolute rates are desired. In theozy,
comparison of the relative growth of fishes in a mitigation/restoration habitat as compared to a
natural habitat can be validly derived from otolith microstructure; however, this remains to be
attempted at this time.
RECOMMENDED SAMPLING METHODOLOGY
Method : eelgrass, emergent marsh, gravel-cobble, mudflat,
sandflat and water column habitats, 53-rn purse
seine with 6-mm mesh bag; nearshore subtidal
soft bottom habitat, 7.6-rn bottom trawl with
-------
SAMPLING PROTOCOLS / 102
6-mm mesh codend; nearshore subtidal hard
substrate habitat, SCUBA transect observations
Due to the avoidance capabilities of motile fishes, sampling methods employed to catch
them must either enbompass a large area to minimize disturbance from the sampling gear or be
rapid to minimize the avoidance, and preferably both. Purse seines and surface and midwater
trawis are the most common gears used and have selection biases for different groups of fishes and
limitations on the habitat in which they can be deployed. a floating beach seine has been used to
sample these fishes near shore but may be limited in its efficiency.
(1) Purse seine:
A modification of the commercial purse seine technique has been adapted for biological
sampling from smaller boats in the confmed embayments and channels of estuaries. The basic
requirements for this sampling is that the net be long enough to effectively enclose schooling fish,
composed of fine mesh in order to effectively capture small and juvenile estuarine fishes, that it be
deep enough to inhibit avoidance by fish sounding, and that it be deployed and pursed in a rapid
maimer. One seine meeting these criteria has been utilized by the Washington Department of
Fisheries and Fisheries Research Institute (see case studies). This net is 58-rn long and is
composed of 13-mm mesh in the wings and 6-mm mesh in the bunt (the end section of the net
where the fish are concentrated). Ii is deployed rapidly from a 5-rn outboard-powered boat in
“round haul” fashion, which if fished efficiently samples and area and volume of 268 rn 2 and 835
rn 3 , respectively. Setting, pursing and retrieving the net by hand can, with experience, take only
15 to 30 mm.; modification of the boat to deploy, retrieve and store the net on a hydraulic-powered
reel can reduce the sampling time considerably. The round haul technique is an important
requirement, as opposed to the strategy of holding the net open into the prevailing current or
towing it, principally because the sampling area/volume will be known and consistent; in addition,
the “holding open” method requires two boats to work effectively. Although not deployed
extensively, the net employed in Pearce et al.’s (1982) investigations in the Nisqually River
estuary, while slightly larger (61-rn), has the same mesh size and should have performed similar to
the WDF net. Parametrix, Inc. (1980, 1982) has utilized a somewhat smaller (38.1-rn x 4.6-rn)
“research seine” equipped with 9.5-mm mesh in sampling juvenile salmonids in the Duwamish
River estuary; this net, which samples approximately 230 m 2 , should perform similar to the WDF
net but no tests have been conducted to compare gear efficiency. A larger net, 63-rn long by 7-rn
deep, with 25-mm to 6-mm mesh, that samples 300 m 2 and 2000 m 2 has also been used in Puget
Sound and coastal estuaries (see case studies); its size, however, requires a larger (e.g., 7 to 10-rn)
vessel, preferably one equipped with a reel, to be fished effectively and safely.
(2) Bottom trawl:
Motile, demersal fishes are generally less vulnerable to small bottom trawis such as the 4.9-
m trawl and the 3-rn staffbeam trawl. For quantitative monitoring of fishes such as Microgadus
proxi,nzis, Thaleichthys pac ficus, and Theragra chalcogramma, the 7.6-rn “otter” trawl described
in detail by Puget Sound Estuary Program (1990a) is recommended. This trawl has a headrope
and footrope 7.6-rn and 8.1-rn long, respectively. Its body is constructed of 38-mm stretch mesh
and the body is of 32-mm stretch mesh lined with a 6-mm mesh bag. The 7.6-rn otter trawl is
commonly equipped with 23-kg doors and it towed at approximately 4.6 km hr 1 . The scope of
wire cable out to sampling depth varies from about 5:1 in shallower depths to 3:1 at deeper depths
(PT! in press). Pair-wise comparisons of the 7.6-rn trawl with the 4.9-rn trawl by Donnelly (In
prep.) indicate that the larger net is a more effective sampler of Microgadus proxfrnus, Theragra
chaJcogra nma, total flatfish and total fish; in addition, the larger trawl was able to sample much
larger Microgadus than the smaller trawl.
-------
Motile Fish / 103
Unit : purse seine, 268 m 2 ; bottom trawl; SCUBA
transects, 50-rn x 6-rn
Periodicitv and Frequency : monthly, March-September
Statistical Considerations (Replication : in lieu of statistical predetermination using pilot study
or historical data; n=S
Because catches of motile fish tend to be highly variable, we recommend a minimum of
five replicate samples for all methods and as many as ten if the monitoring criteria requires
detecting significant differences in the density or standing stock of attributes which are particularly
patchy (e.g., schooling taxa such as herring, sand lance and small juvenile salmon).
ALTERNATIVE PROCEDURES
(1) Surface trawl:
The Kvichak surface trawl or “townet” has been used extensively for sampling near-surface
(i.e., 3-rn) neritic fishes in Puget Sound since early research on juvenile salmon in Bellingharn Bay
and provided the sampling basis of the Washington Department of Natural Resources (DNR)
Nearshore Fish Survey of neritic fishes in northern Puget Sound and NOAA’s Marine Ecosystem
Analysis (MESA) studies in the Strait of Juan de Fuca in the mid- to late 1970s (see case studies).
In general, this is the “accepted” technique for sampling juvenile salmonids once they have moved
away from shallow shorelines. This net has a mouth opening of 18.3 M (3.0 x 6.1 M) and mesh
size grading from 8.9-cm at the mouth to 0.6-cm at the cod end. Two pipes with large floats at the
top and weights at the bottom were attached to the sides of the net to keep the mouth open
vertically. The net is towed between two boats at an average tow speed of 80 cm s 1 (range 50-100
cm s’), which Bollens and Frost (1989) determined to result in sampling volumes of between
7,300 and 31,700 m 3 .
(2) Midwater trawl:
A midwater trawl used extensively for assessment of spawning herring populations in
Puget Sound is a four panel trawl with a 9.2-rn headrope and footrope and 9.2-rn sides designed to
open 6.1 m vertically and horizontally (Trumble et al. 1982). Mesh sizes taper from 7.6-cm
stretch mesh in the wings to 1.3-cm stretch mesh in the cod end liner. Floats were used on the
headrope and chain on the footrope to optimize the vertical opening. However, we know of no
exact measurement of the net opening, and the variability of this areal dimension, under fishing
conditions; in the absence of this measurement, 37.2 rn 2 will have to be assumed. The net was
fished with 31 kg, metal, V-type trawl doors, which were connected to the side panels by 55-rn
dandylines. Standard tow times (e.g., 30-60 mm) must be maintained as a common unit of effort;
in addition, it is highly recommended that the net be equipped with flow meters to provide more
precise measurement of the distance sampled by the trawl; alternatively, exact positions at which
the net was deployed and retrieved should be determined by loran or other high-resolution
geographic location system. Trawl depth should be maintained using a depth sensor mounted on
the trawl door, with telemetry sent to the vessel.
A similarly-sized trawl has been used for the capture of midwater fishes within 50 m of the
surface of Hood Canal by the University of Washington School of Oceanography (Bollens and
Frost 1989) and should provide comparable catches if deployed similarly. This net has a 81.0 m 2
(9.0 X 9.0 m) mouth area and mesh size ranging from 8.9-cm stretch measure at the mouth of the
net to 1.3-cm mesh in the cod end. The mouth of the net was kept open by 230-kg doors. Tow
-------
SAMPLING PROTOCOLS /104
speed averaged 150 cm s (range 120-180 cm s’), thus the volume filtered by the net ranged
between 115,000 and 449,000 m 3 .
(3) Floating beach seine:
The 37- X 2 m beach seine used to sample sedentazy fish (see above) has been modified by
adding enough large floats (usually the “bullet” floats) to the toprope to keep the net at the surface.
As with the sinking net, the 18-rn wings composed of 3-cm mesh are joined to a 2-rn H X 2.4-rn
W X 2.3-rn D bag of 6-mm mesh. A detailed description of the net and the protocols associated
with its deployment occurs in PT! et al. (in press). It is deployed and retrieved in a similar
manner, i.e. 30-rn and parallel to shore, with the two wings pulled simultaneously toward shore
for the first 20-rn at a distance of 40-rn., and from a distance of 10-rn apart for the final 10-rn to
shore; in this configuration it samples 520 m 2 and 790 m 3 . As utilized by Parametrix (1980, 1982)
and Lipovsky (1985), a smaller (30-rn) beach seine which encompasses an area of 230 m 2 may
sample comparably in shallow water but several variances in the gear and deployment (i.e., 9.5-
mm mesh; setting the net with one end attached to shore) suggest that these two nets may have
significantly different efficiencies, and the associated data should not be directly compared without
conducting paired efficiency tests.
(4) Channel trap net:
Tidal channels in emergent marshes and mud- and sandfiats provide particular problems in
sampling fishes. In many cases, the traditional beach seine techniques are inferior to methods
which sample through an ebb tide cycle because fish which axe utili7ing the flats and emergent
vegetation are comparatively invulnerable.
Channel trap nets are designed to capture fishes as they emigrate tidal habitats during an
ebbing tide. Most motile fishes will be captured by trap nets because few will occupy burrows and
depressions during tidal exposure as will some sedentary fishes. Although they have been adopted
extensively on the east coast, channel trap nets (e.g., Cain and Dean 1976) and the similar flume
nets (Mclvor and Odum 1986) have not been utilized extensively in this region. The intertidal trap
net utilized initially by Levy and Levings (1978) and later by Levy and Northcote (1982) to sample
emergent marshes is one of the few and better examples of this sampling method. Their net was
2.4-rn deep and constructed of 0.6-cm mesh. It is deployed at high tide, stretched across a tidal
channel, immediately preceding a steep tidal drop, and fastened to stakes set into the bank along the
channel. As the tide ebbs, most of the fish in the marsh drainage area of the channel above the net,
and in the channel proper, are forced into the trap or into the pools of the channel remaining at low
tide. When the channel is as dewatered as will occur at low tide, fish are collected from within the
trap and seined from the remaining pools. A most effective modification, also described by Levy
and Northcote, is a removable trap box which acts as a live collection trap and permits periodic
checking of the temporal disthbu non and abundance of fish exiting the channel over the ebb tide.
Shreffler et al. (1988, 1990, 1991) and Thom et al. (1988) describe a modification to a
channel trap net which should be considered when residence time, growth or consumption rate
estimates are requir&1. In this case, the trap net is equipped with two side-by-side “fyke” traps,
one facing up-channel and one down-channel, which are designed to sample fish actively moving
into and out of the channel. The net is set in the lower intertidal portion of the channel such that it
can operate (because it requires some water remaining in the trap area) at low tide, unlike the Levy
and Northcote (1982) net.
(5) Oneida trap:
Another “fyke-net” type of fixed net is the Oneida trap which can be used where currents or
fish movements are predominantly unidirectional. As use by Parametrix, Inc. (1982), the Oneida
trap is constructed of 4.8-mm stretched mesh webbing and is formed of two 12.8-rn wings and a
-------
Motile Fish / 105
40.3-rn center lead which funnel into a 2-rn x 2.1-rn x 2.0-rn “crib” which traps and holds the fish
alive. This is one of the few gears which can be deployed in a habitat with extensive obstructions,
such as under a pier apron. However, unlike the trapnet which samples a comparatively known
area of habitat (i.e., the channel “watershed”), it is difficult if not impossible to quantify the
sampling effort of the Oneida net without several tenuous assumptions, such as uniform
distribution of fish across the total water surface which the net is supposed to be subsarnpling,
equal fishing efficiency during different tidal stages, etc. If the Oneida trap offers the only option
for sampling an estuarine habitat, the effects of these assumptions should be minimized by test
fishing in several locations, sampling during short periods within tidal stages, etc.
For all purse seining and trawling, location should be established precisely using electronic
means such as day-screen radar with built-in variable range markers (VRM), high-resolution lorans
with multiple navigation capabilities, satellite navigation using a global positioning system (GPS),
and video depth sounders and plotters. PT! Environmental Services and the School of Fisheries,
University of Washington (1991) describe in detail the use of these devices and a standard protocol
for precision trawl sampling.
CASE STUDIES
The recommended beach seine, purse seine, and surface trawl fish sampling techniques
have been applied extensively to sampling juvenile salmon and baitfish in estuarine and nearshore
habitats of Puget Sound and the Strait of Georgia in the studies of Tyler (1964), Miller et al.
(1977, 1980), Schreiner et al. (1977), Levy and Levings (1978), Bax et al. (1978), Fresh et al.
(1979), Meyeret al. (1981), Simenstad et al. (1981), Paramethx, Inc. (1982) and Donnelly et al.
(1984); in addition to the estuarine habitats of Puget Sound., these techniques were utilized to
sample juvenile salmonids and other motile fishes in Grays Harbor (Simenstad and Eggers 1981)
and Neah Bay (Simenstad et al. 1988b). Trumble et al. (1982) used midwater trawling to sample
spawning herring in northern Puget Sound during 1976 1979, although they did not report species
other than Pacific herring. Bollens and Frost’s (1989) studies of motile neritic fishes in the surface
waters of Hood Canal provide one of the few highly quantitative datasets of its kind. Levy and
Northcote (1982) provide data from channel trap net collections in an emergent (Carex) marsh in
the Fraser River delta and Shreffler et al. (1988, 1990, 1991) and Thom et al. (1988) provide
analogous data for a restored wetland system in the Puyallup River estuary using the fyke-modified
trap net. The use of an Oneida trap is relatively exclusively reported by Parametrix, Inc. (1982).
-------
GENERAL AVIFAUNA
HABITAT OCCURRENCE
Eelgrass; Ayes (unid.)
Emergent marsh; Ayes (unid.)
Charaduidae (unid.)
Mudflat Ayes (unid.)
CHARACTERISTICS
Birds in general, but especially those associated with estuarine habitats, including most of
the shorebirds and waterfowl occurring in the habitat assemblage groups.
PARAMETERS
Minimum ;
(1) species occurrence;
Recommended ;
(2) density;
Preferred ;
(3) activity patterns; and
(4) diet.
Species occurrence
When produced from an intensive sampling effort over time and space, the relative
occurrence of species (providing species richness over space and time) can provide a minimal
indication of the viability of estuarine wetland and nearshore habitats, principally as an assessment
of gross levels of habitat quality. Species richness should be defined as relative to sex and life
history stage, especially because the use of the habitat by reproductive individuals and juveniles is
a more important supportive function than if only adults occur. Species occurrence should be
represented as both (1) mean number of species/life history stages and sexes by microhabitat and
activity category and as (2) the cumulative number of species/life history stages and sexes, and
times because different methodologies have selection biases and because avifauna movement and
migration patterns can be highly variable.
Density
Density measurements are more definitive indicators of subtle differences in habitat quality
because habitat characteristics can effect density-dependent interactions between the birds and their
habitat which would otherwise not be reflected by species richness. Density is expressed as the
number per unit area (no. k i m 2 ) of the habitat or, if expressed for the total transect or area
surveyed, the transect/plot area should be established and any variances associated with areal
-------
General Avifauna / 107
coverage documented. As in species occurrence, density and standing stock should be expressed
relative to species, life history stage and sex, and relative to microhabitat, tidal cycle and activity
pattern. These effects can also influence estimation precision; for instance, Herman and Bulger
(1981) reported that the best counts were obtained two to three hours on either side of high tide,
i.e., when the tideilne was closest to the observers. While individuals can be counted for most
species, counts of shorebirds and waterfowl must be scaled to tens and hundreds when they occur
in high densities. Particularly when counting dense groups of birds, counts should be made
repeatedly or by different observers and a consensus count agreed upon.
Activity pattern
In conducting either individual or group observations, it is recommended to categorize the
counts as to activity pattern. These can include, but not be limited to: (1) feeding; (2)
roosting/resting; (3) flight, including direction; (4) mating; (5) territoriality/aggression; and (6)
nesting. It may be particularly informative if one behavior can be linked to another (e.g.,
aggression to nesting in mated pairs), or an area/habitat used for one behavior can be linked by
flight patterns to an area/habitat used for another behavior, such as from a feeding area to a
roosting area. In addition to recording the incidence of different behaviors, long-term observation
of individuals or groups should gather data which measures time (inferring energy) budgets,
preferably over the diurnal period of activity.
Food habits of estuarine avifauna in this region are usually extrapolated from the same or
related species in other regions and we generally know little about their feeding dependencies upon
specific plant or animal taxa unique to Pacific Northwest estuanne habitats. Therefore, any
quantitative observations or sampling of avifauna to determine food habits would conthbute
measurably to our understanding of the habitats’ function. At a minimum, any detailed
observations of feeding birds should note their basic feeding strategy. If prey are visible, they
should be categorized if not identified. In the case of nesting birds, food renmants around the
chicks may provide infonnation on the diet during that period. Non-destructive sampling of
stomach contents might involve obtaining regurgitated food items when the adults return to feed
nestlings. Although biased by digestion, analysis of prey hard parts (e.g., bones, shell, otoliths)
in fecal remains may also provide ancillary information. If feeding is a function upon which the
habitat-assessment is dependent, and none of these methods provide conclusive evidence,
destructive sampling of birds utilizing the habitat may have to be considered in order to verify
feeding by detailed stomach contents analyses.
In the case of birds, both the crop (expansion of the esophagus in front of the stomach) and
the proper stomach should be examined for food items. In general, the description of diet must be
made at the population level and document both numerical and gravimetric (biomass) or volumetric
measures of food item “importance.” The volume of food items should provide a comparable
measure as weight, but is not used as often because it is more difficult to measure at low levels.
Thus, stomach contents analyses to gather this information need to be conducted on individ’ual
birds rather than for pooled samples in order to maintain a measure of the population utilization of
the item, i.e. as frequency of occurrence, and of the extent of any feeding selectivity. In addition
to counts and weights (wet damped, dry, or ash-free dry) of the food items in each stomach, some
indices of stomach fullness and digestion rate should also be assessed; these often involve a scale
between 1 to 6 and 1 to 10. Recording of the total stomach contents weight before separation into
identifiable food items will also provide, by subtraction, a measure of the weight and proportion of
unidentifiable (digested) material.
-------
SAMPLING PROTOCOLS / 108
Diet composition can be described using this combination of measures as an Index of
Relative Importance (IRI) which is created for each food item i;
I.R. 1 1 = (%F.O. 1 (%N.C. 1 + %G.C. 1 ))
where %F.O. = the percent frequency of occurrence, %N.C. = percent numerical composition,
and %G.C. = percent gravimetric/volumetric composition. Because the resulting numerical values
for the I.R.I depend greatly upon sample size, the relative importance is often converted to the
percent of the total I.R.I (%I.R.I.). Graphically, this is illustrated by a two dimensional figure in
which the abscissa is %F.O. and the ordinate is %N.C. above the abscissa and %.G.C. below the
abscissa. The original I.R.I. description occurs in Pinkas et al. (1971), and the approach is
modified and described further in Cailliet (1977) and Cailliet et al. (1986).
RECOMMENDED SAMPLING METHODOLOGY
Method : transect/plot observations
(I) Quantitative observations:
Most estuarine avifauna surveys are conducted by systematic observations, either along
transects (Hazel 1984) or from established sites or plots (Herman and Bulger 1981). When
undertaken for broad regions such as large bays, sounds, and inlets, transects are often conducted
from vessels or from aircraft (Maunal et al. 1979; Wahi et al. 1981). Observations are made with
the assistance of binoculars and spotting scopes for standard times and areas and species, relative
sizes, sexes, and activity categories are recorded. It is important that all observations be stratified
or otherwise categorized by tidal stage because many of these birds are feeding, resting, etc.
according to these cycles.
dependent upon areal extent of habitat, 100-
m 2 transects/plots in large habitats
Periodicitv and Frequency : weekly during peak migration periods
(Spring, Fall), monthly during other
periods
Siatistical Considerations (Replication) : in lieu of statistical predetermination using pilot study
or historical data; n=3
Replicate sampling is not always a consideration in avifauna studies, particularly because
the observations are continuous or are designed to assess the whole population(s) in the study area.
It is recommended, however, that some element of replication be incorporated into the sampling
design in order to evaluate sampling error. In particular, repeated sampling of the same population
by different observers should be examined for observer bias and estimation of that source of error
incorporated into the sampling design.
CASE STUDIES
The principal quantitative studies of estuarine avifauna in this region are those conducted
during the MESA program in northern Puget Sound by Manual et al. (1979) and WahI et al. (1981)
and in Grays Harbor by Herman and Bulger (1981) and the Columbia River estuary by Hazel
(1984). Couch (1972) provides one of the few quantitative accounts of avifauna feeding ecology
in this region.
-------
HERBIVOROUS MAMMALS
HABITAT OCCURRENCE
Emergent Marsh; Microtus spp.
Microtus townsendii
Ondatra zibethicus
Peromyscus maniculatug
Sorex bendiril
CHARACTERISTICS
These are small (voles) to moderate-sized (muskrat) mammals which either live entirely in
or venture into emergent marsh habitats; they may also range from adjoining upland habitats to
forage along the intertidal zone. While detailed examination of the habitat can often provide some
information on small mammal use, sampling with traps will usually be required to generate
quantitative information on species, density and standing stock, and population structure.
PARAMETERS
Minimtm ,
(1) species occurrence;
Recommended :
(2) density and standing stock;
(3) birth and rearing sites;
Preferred ;
(4) population structure (e.g., reproductive state); and
(5) diet;
(6) activity patterns.
Species occurrence
When produced from an intensive sampling effort over time and space, the relative
occur ce of species (providing species richness over space and time) can provide a minimal
indication of the viability of estuarine wetland and nearshore habitats, principally as a gross
assessment of habitat quality. Species richness should be defined as relative to life history stage,
especially because the use of the habitat by reproductive individuals and juveniles is a more
important supportive function than if only adults occur. Species occurrence should be represented
as both (1) mean number of species/life history stages and sexes by microhabitat and activity
category and as (2) the cumulative number of specie/life history stages and sexes, and times
because different gears have selection biases and because small mammal movement and migration
patterns can be highly variable.
Density and standing stock
Density measurements are more definitive indicators of subtle differences in habitat quality
because habitat characteristics can effect density-dependent interactions between the birds and their
habitat which would otherwise not be reflected by species richness. Density is expressed as the
-------
SAMPLING PROTOCOLS /110
number per unit area (no. knr 2 ) of the habitat or, if expressed for the total transect or area
surveyed, the transect/plot area should be established and any variances associated with areal
coverage documented. As in species occurrence, density and standing stock should be expressed
relative to species, life history stage and sex, and relative to microhabitat, tidal cycle and activity
pattern. These eff ts can also influence estimation precision; for instance, Herman and Bulger
(1981) reported that the best counts were obtained two to three hours on either side of high tide,
i.e., when the tideline was closest to the observers. While individuals can be counted for most
species, counts of shorebirds and waterfowl must be scaled to tens and hundreds when they occur
in high densities. Particularly when counting dense groups of birds, counts should be made
repeatedly or by different observers and a consensus count agreed upon.
Birth and rearing sites
Birth and rearing sites are usually inferred from the capture of pregnant or lactating
females, as reproductive activities generally occur within the limited home ranges of small
mammals (Howerton 1984).
Population structure
Population structure information is derived principally from trapped individuals. Each
animal is examined for size, sex, age, reproductive status and general condition. Age can be
determined by either sectioning teeth, using the sequence of tooth eruption, using the method of
Hugget and Widths (1951) which is based on fetal weight at birth (estimated by capture of
recently-born young or from literature) and the gestation period (estimated from the literature), or
inferring from growth curve data in the literature (e.g., Dorney and Rusch 1953 for muskrats).
Reproductive status can be determined from examination of females for visible signs of pregnancy
or recent birth (e.g., fetuses, recent placental scars, lactation).
Qi
Food composition of the small mammals can be inferred from the remains of food items left
at documented feeding areas (along transect lines), from analysis of the plant fragments in the
stomach contents and in fecal remains, and from direct observation; trapped individuals can only be
used for stomach analyses if they were trapped without bait or with traps which did not allow the
animal to the bait.
In the case of identification at the feeding site, the presence of tracks, scats and or species-
specific evidence (e.g., cuttings, diggings, etc.) are used to identify the species of mammals
feeding at the site. These data are usually represented as the percent occurrence of mammal species
feeding on a specific plant taxa. Direct observation generates similar data except that the time
energy allocation to feeding on specific plant taxa can provide a more quantitative, comprehensive
measure of feeding..specificity and food item dependency.
Stomach and fecal remains analyses can provide more detailed information because the
weight (biomass) contribution of plant taxa to the diet can be determined and an index of the
variance over the population (percent frequency) for each food item can be estimated. Plant
fragments axe usually measured microscopically, using methods similar to those of Sparks and
Malcheck (1968), Davitt and Nelson (1980) and Korfhage et al. (1980). Data generated are
expressed as frequency of occurrence of identifiable food taxa in the sample and food item weight
over the individuals. In the absence of meaningful measures of food “abundance,” an I.R.I.
approach such as used to assess food item importance to fishes (see Sedentary and Motile Fishes,
above) cannot be used.
-------
Herbivorous Mammals I 111
Activity patterns
Whether generated by real-time observations or radio telemetry of small mammals, the
activity “budget” over diel periods, usually represented as the time or percentage of the daily record
which was spent ma particular activity in different habitats. In the case of the telemetry data, some
observation or supplemental information (e.g., recent feeding evidence) will be necessary to
validate assumptions of unobserved activities.
RECOMMENDED SAMPLING METHODOLOGY
Method : trapping transects/plots
(1) Trapping transects/plots:
Seasonal and permanent transects are typically established along which traps and baits are
used to capture individuals. In the Columbia River estuary (Howerton 1984) these transects
consisted of four trapping stations spaced 25 in apart each trapping station was assumed to have a
diameter of approximately 8 in or a surface area of —50 m 2 . The transects were placed along the
mean high tide elevation, which allowed they traps to function at high tides and still sample
mammals foraging into the intertidal zone. At each trapping station, traps are placed within
microhabitats where the animals are most likely to occur, such as runways, burrows and cavities.
Howerton (1984) operated the trapping transects seasonally for three consecutive nights at each
transect.
Unit : SO m 2
Periodicitv and Frequency : nightly for three nights, bimonthly March-
September
Statistical Considerations (RepIication ’ : in lieu of statistical predetermination using pilot study
or historical data; n=3
Like quadrat sampling, trapping and other sampling of mammals along transects or in plots
should be designed in proportion to the overall habitat area. In the case of standard transect
distances/areas, these are usually conducted in adjoining segments through the center of the habitat.
Sampling plots, such as trapping stations, are often distributed along these transects, and average
four to five in number, within which as many as ten traps are deployed. Howerton (1984), for
instance, used this general design to analyze estuarine mammal population indices based on trap
catch per 100 trap nights. Several historical studies have monitored study sites for five days per
season sampling interval.
ALTERNATIVE PROCEDURES
(1) Radio telemetry:
Activity patterns and disthbution in the habitat and among microhabitats can be obtained for
large mammals (Ondatra) by the mounting of radio transmitters on individuals and locating or
monitoring their locations over periodic periods. Howerton (1984) used surgically-implanted
transmitters for monitoring muskrat and nutria activities and habitat use in the Columbia River
estuary.
-------
SAMPLING PROTOCOLS /112
CASE STUDrES
To our knowledge, the only documented quantitative studies of these small herbivorous
mammals in estuarine habitats are those of Schoen (1972) and Howerton (1984).
-------
PHYSICOCHEMICAL ATTRIBUTES
Although physical and chemical attributes were often identified as important attributes of
estuarine habitats promoting fish and wildlife use, no values per se were identified in the protocol
development process. Such associations between a habitat’s structure and physiochemical
environment, although based only on qualitative observations, should not be discounted.
Physiochemical attributes are particularly important to habitat restoration because many of these
parameters can be directly incorporated into the initial project design, e.g., sites can be selected
within specific salinity ranges and exact bathymetric/topographic features can be created at the
project’s inception. The results of this portion of the Protocol development highlights the
limitations of our understanding of fish and wildlife habitat requirements. Therefore, an important
aspect of the Protocol is to accumulate physiochemical information that will enhance our
quantitative understanding of these factors to fish and wildlife support.
Appendix C and Supplement 7 (Simenstad et al. 1990) lists those attributes which were
identified as potentially being important, even if no specific value, range, etc. could be listed. We
recommend monitoring of as many of these as possible because of their suspected importance to
fish and wildlife species. Based upon these responses and our expert opinions, we have placed the
following priorities on the measurement of physiochemical attributes and our recommendations for
their measurement
RECOMMENDED
(1) Topography/bathymetry: -
If not available or recent, a complete survey should be conducted of the site. The survey
should be linked to established benchmarks and referenced to the closest NOAA tide gauge. The
land portion of the survey should extend as far into the intertidal as feasible, and preferably
conducted during a strong (e.g., minus) spring tide series, if subtidal habitats are involved as
extension of intertidal habitats, a comparable bathymetric survey should be conducted, overlapping
with and tied to the intertidal survey. An elevation datum should be installed permanently in a
protected area of the site, where it would not likely be lost to erosion/accretion processes. All
station positions should be exactly located on this survey. Protocols for station positioning are
found in Puget Sound Estuary Program (l990c). In addition to these surveys, horizontally-
corrected aerial photographs should be acquired of the site annually. These should be flown at the
lowest elevation possible that encompasses the site, preferably 500 ft.
If only subtidal habitats are being considered, a bathymetric survey should be conducted if
none is available, current or of reasonable resolution. This should preferably be conducted with a
digitally recording echosounder linked to a positioning system (e.g., microwave triangulation,
Loran or Global Positioning System).
(2) Water character/quality:
At a mininThm, basic water characteristics should always be monitored during sampling to
describe temporary conditions during sampling. These measurements should include at least: (1)
temperature; (2) salinity; (3) turbidity, and (4) dissolved oxygen. These samples or measurements
should be collected at the immediate location and time of sampling, including at the sampling depth
if submerged.
Given the dynamic nature of estuarine habitats, however, such extremely episodic
measurements will not characterize the habitat; much more extensive, long-term data acquisition is
required. Temperature, salinity, tidal elevation and any constituent of estuarine water should be
gathered over representative tidal cycles and freshwater flow periods. Ideally, a permanent
-------
SAMPLING PROTOCOLS /114
sampling station, such as a tide gauge or a CTD (Conductivity-Temperature-Depth) or STD
(Salinity-Temperature-Depth) instrument package, should be installed over a years period. If only
short-term sampling can be conducted, it should occur over the entire tidal cycle (e.g., at least 26-
30 hr) at least once during each stage of the tidal month (e.g., weak and strong neap and spring
tidal series) and seasonally during the maximal and minimal freshwater flow periods. Optimally,
short-term sampling should occur during all stanzas of the local hydroperiod, including during
storm events. All measurement procedures should follow the Puget Sound Estuary Program’s
recommended protocols for measuring water-column variables (Puget Sound Estuary Program
1990c) or a method of superior precision and validity.
(3) Sediment structure (for all but water column habitat):
Sediment structure should be sampled at least yearly and potentially more frequently in
habitats subject to sporadic erosion/accretion activity, including bioturbation. Although dedicated
samples can be used, sediment may also be retained from samples for benthic infauna, below-
ground vegetation biomass and other soil/sediment attributes. Measurements and analyses should
include at least: (I) mean grain size distribution; (2) statistical characterization of sorting, skewness
and kurtosis; and (3) percentage of organic matter. The recommended procedures for determining
these parameters is contained in Dyer (1979).
SUGGESTED
(1) Water flow levels:
The relationship between the flow (quantity of fluid moved) of fresh water and tidal water
through estuarine habitats and the structure of biotic communities in these habitats is poorly -
understood. These data are important from the standpoint of both the transport of constituents
such as suspended sediments, nutrients and organic matter and of the erosion and deposition of
sediments within the habitat. In habitats where flow can be feasibly estimated, e.g., tidal channels,
it is recommended that recording instrumentation such as current meters be deployed over
representative tidal month periods (e.g., one each during low and high freshwater flow). Due to
the complex nature of water velocities in shallow water, these measurements should optimally be
taken at several points in the water column, and particularly close to the sediment surface.
(2) Sound/light levels:
Due to the lack of information on responses of estuarine organisms to disturbance, you are
encouraged to conduct some sampling of sound and light levels in the vicinity of the sampling site.
These would preferably be monitored continuously for one year or at least during representative
seasonal periods. We know of no published sound/light standards or protocols. The accepted
measurement unit for human health effects is “A-weight” sound levels, and 55dBa is a common
threshold for A-weighted sound averaged over 24 hours. This level may provide an appropriate
benchmark from which to make comparisons with fish and wildlife behavior.
Light levels are even more nebulous, even in human health considerations. Work
standards often us 3-7 foot candles averaged over the work area as a standard, with 0.5-1.5 foot
candles acceptable in perimeter work areas. However, there are many categories of artificial light,
e.g., diffuse, indirect/reflected, and direct glare, and these have yet to be standardized. We
suggest considering all these aspects when monitoring light impacts.
(3) Surface sediment contaminants:
Both prior and recurrent sampling of sediment contamination in development, restoration,
and reference sites is important to understanding the limitations upon biotic communities existing
or anticipated to develop within estuarine habitats. Estuarine habitats have not only been direct
-------
Physicochemical Attributes / 115
depositories of contaminants, but a.lso sinks of contaminants ansported to the site from other
regions of the estuary or outside the estuary entirely. Recurrent sampling, rather than sampling on
one occasion, is also meaningful because the rate of contaminant accumulation may be a pivotal
parameter in determining the biological effects or uptake by biota. Particularly in the case of
habitats in urbanized estuaries, we recommend that sediment contaminant sampling be incorporated
into the initial assessment and later monitoring designs.
At the minimum, a basic screening should conducted for the State of Washington’s
Poliwants of Concern, i.e., organics, heavy metals, PCBs (Tetra Tech, Inc. 1986). If any of these
are found in threshold concentrations (low Apparent Effects Threshold [ AET]), further analysis
will be required using the State of Washington’s sediment management standards. For these
analyses, the reader should consult the State of Washington’s sediment management standards
(Chapter 173-204 WAQ State of Washington Department of Ecology 1991) for (1) contaminant
standards for the quality of surface sediments; (2) biological effects criteria; (3) clean-up standards
for contaminated sediments; and (4) sampling and testing standards.
-------
DISCUSSION
APPLICATION AND TESTING
The potential of the Protocol to foster more effective estuarine habitat restoration and miti-
gation can be realized only if an attempt is made to apply it.. The most likely avenue for application
will be the habitat or aquatic resources permit process (e.g., Shorelines, Clean Water Act Section
404). In addition, the information required for revisions and modifications can only be gained
through application on a broad scale across a variety of habitat types and estuarine situations. It
has been designed essentially as a “toolbox” to be used by all parties involved in habitat restorationj
mitigation activities, from the developer and consultants to the agency representative reviewing the
permit applications and environmental impact assessments. Therefore, it is designed, not to
specify what must be measured and what procedures must be used, but to provide the means to
develop a “template” for procedures to assess both the estuarine resources to be lost to develop-
ment and the mitigation project designed to replace those resources.
Using this strategy, the Protocol should be applied in an adaptive manner. Because every
estuarine site, every development activity, every restoration or mitigation project is unique, we
realize that each situation will require a different subset of tools from those available in our
toolbox. In most cases, the agency representatives and biological consultants are better equipped
to isolate the fish and wildlife issues involved with particular sites, and the site characteristics
which constrain various assessment procedures. These parties should collectively negotiate the
habitat type(s), attributes, parameters and procedures relevant to the particular situation. For
instance, in the case of Clean Water Act-Section 404 Permit and Washington State Hydraulic
Permit Application (HPA) processes, the Protocol would provide the basis for a common template
to be negotiated in the initial pre-scoping meetings intended to guide subsequent impact
assessments and mitigation designs.
In addition to routine application in the permit process, the concept and approach of the
Protocol also need to be verified formally in an explicit test outside the constraints imposed by
mitigation requirements. In such a test, the Protocol would be applied in a research project to
compare natural and restored/created estuarine habitats in Puget Sound with the coastal estuaries of
the region in order to validate the importance of the ecological relationships upon which the
Protocol is based and to generate atleast one comparable dacaset that encompasses as many
attributes and parameters as feasible.
REQUIREMENT FOR REFERENCE SITES
Testing and implementation of the Protocol and its inherent strategy for monitoring may
reduce or eliminate_many of our current problems with estuarine habitat restoration and mitigation.
However, the need still remains to relate Protocol-generated data to “benchmark” or reference
habitats that function in a comparatively natural manner. Any study that looks at the effects of a
real or predicted impact requires some sort of “control” or baseline with which to compare affected
sites. This is a major restriction on the long-term utility of the Protocol because there are no such
programs for consecutive monitoring of any of these attributes in estuarine habitats of Puget
Sound. Even with site- and project-specific control habitats, which will always be required with-
out such reference site monitoring, any interpretation of the function of restoration or mitigation
sites will be inhibited by the absence of any long-term data that indicate the magnitude and trends in
variation of auribute parameters.
-------
Requirement for Reference Sites I 117
Reference site monitoring would enable local coastal resource managers to evaluate more
precisely the result of site-specific monitoring in terms of long-term trends. In addition, such data
would be the only means by which the optimum sampling frequency and duration for
restoration/mitigation monitoring can be derived because permit-required monitoring will unlikely
be of the intensity and resolution to define natural cycles and variation.
The reader is referred to Hughes (1985), Hughes et al. (1986), and Hughes et al. (1990)
for further, more detailed arguments for development and application of reference sites.
REVISION, MODIFICATION, AND EXPANSION OF THE PROTOCOL
As stated in the Introduction, the Protocol is a somewhat basic, untested approach to a
complex scientific and policy situation. It is, however, an approach that shows promise, and one
that can be tested through both regulatory (permit) and scientific (grant and contract) activities over
the next few years. As such, this version should be con.sideredpreliminaiy and certainly subject to
revision or rejection after a reasonable test perioi Just as the Protocol approach was validated
initially at the Estuarine Wetland Restoration Monitoring Protocol Workshop in Port Townsend,
Washington, on 16-19 April 1989 (see section on Review Workshop), the results of the first two
to three years of application and testing of the Protocol would be best critiqued in a workshop with
the original workshop participants and any additional estuanne specialists who have used or dealt
with the Protocol on any level.
At such a “reject or revise” workshop, the participants should examine critically the suc-
cesses and failures of the Protocol in achieving its objectives. If the results have been less than
successful, the participants should evaluate whether or not this arises from the concept of the
Protocol, from its application to actual situations, or because of inappropriate parameters,
attributes, and other driving variables. It would then follow that the workshop would work toward
a consensus to (1) reject the Protocol as being ineffective, (2) recommend changes in the way it is
implemented in the regulatory process, or (3) identify additions and modifications that would
enhance its applicability. The product of the workshop would be either recommendations for
different approaches to monitoring estuarine habitat functions or changes to the existing Protocol.
In particular, further revision of the Protocol must address the lack of identifiable
physical/chemical attributes which promote fish and wildlife support. In the sense that our lack of
understanding of these factors is manifested in the paucity of abiotic parameters in the existing
Protocol, a major objective of the “revision” objective of the workshop will be to compile any new
information and propose studies that might gain information about these attributes.
It must also be remembered that the Protocol is but one approach to monitoring only one
function (fish and wildlife support) in one subset of wetland and aquatic habitat types (estuaries).
If the Protocol is effective, this approach would have to be repeated for other acknowledged
aquatic habitat functions and for other types of aquatic habitats, specifically those in fresh water
(e.g., lacustrine, palustrine). This may or may not be appropriate, and will depend upon the
opinion of hydrologists, sedimentologists, geomorphologists, ecologists and other wetland
scientists as to attributes identifiable with other functions.
A useful example of a different approach to wetland habitat function assessment is that of
Homer and Raedeke (1989) in their Guide for Wetland Mitigation Project Monitoring, in
which they have attempted to address the more important functions of freshwater wetlands and
monitoring. The approach of Homer and Raedeke is more intensively focused on a few select
parameters over a wide range of functions, while this Protocol is comprehensive for only the
primary function of fish and wildlife habitat, and secondarily for food web support. These
different approaches should be compared and evaluated as their use grows, and the best of each
should be integrated into subsequent approaches.
-------
DISCUSSION! 118
BEYOND THE PROTOCOL
The Protocol should be considered only the first step in a sequence of activities designed to
provide more scien f1c rigor to wetland and other aquatic resource policy decisions and restoration,’
mitigation projects. If the objectives for which the Protocol was developed are to be fulfilled,
several other endeavors should follow or, even better, occur simultaneously.
EVOLUTION OF DESIGN CRITERIA
While one of the goals driving the development of the Protocol was to develop a system
that results in successful design criteria for habitat restoration and mitigation, these criteria will not
evolve without gathering information about the relationships between the attributes (and the
specific parameters) and the habitat characteristics that influence them. Some of this information
can be obtained by examining the distribution of attribute parameter values relative to the structure
of the habitat. Thus, it is important when interpreting attribute parameters to consider them in the
context of their location in the habitat, their relationships to microhabitats, morphology, bathy-
metry, surface runoff and seepage, etc. For example, we have identified larval insects (e.g.,
Chironomidae) as important attributes (as prey) of many emergent marsh and mudflat fish and
wildlife. Yet, we have little or no information on the basic habitat requirements of these infaunalj
epibenthic forms of flies. We do not know if they require specific sediment structure and organic
content, whether they are attached to specific emergent plants, and where and when they are
available to foraging fish and wildlife.
In and of itself, attribute correlation does not necessarily imply functional relationships. -
However, conelation among physical and biological attributes, and with other characteristics of the
habitats, can suggest testable hypotheses about the relationships between the habitat structure and
the distribution and abundance of attributes. Such hypotheses could be examined specifically in
dedicated field or laboratory experiments. This coupling between the regulatory process of restora-
tion and mitigation and applied ecological research is one of the few ways in which we will be able
to provide feedback into, and ultimately advance, the “ecotechnology” of habitat restorationj
creation. This feedback cycle is a specifically scientific application of the policy of adaptive
management, which has been advocated as a strategy for optimizing Pacific salmon enhancement
(Larkin 1974; Holing 1978; Lee and Lawrence 1986).
SCALING FACTORS AND OTHER CONSIDERATIONS BEYOND HABITAT TYPE
From its initiation, the protocol development process was based on the concept of a single
uniform habitat, regardless of its size, shape, and relationship to other habitats. This was
necessary, in part, because interactions between fish and wildlife and the habitat were considered
so complex as to limit our initial scope. In fact, the extent of habitat support for many fish and
wildlife species may be limited not so much by the attribute parameters in the habitat as by the
diversity and arrangement of the attributes within the habitat, the habitat’s morphology, the scale
and configuration of the habitat, and its connections to other wetland or upland habitats. Yet, the
Protocol fails to provide criteria for any of these “second order” influences simply because we had
no information upon which to make such judgments. This is to say that we may now have the
building blocks (the attributes) to assess habitat function but we need to know how they fit together
before we are able to provide a working structure (functioning habitat).
One obvious way to address this deficiency in the Protocol is to test how adding and
diversifying attributes affect the number of fish and wildlife species using the habitat; we presume
intuitively that this is a positive relationship but have no empirical knowledge of its form, e.g.,
whether it is linear or exponential, etc. Obviously, selecting attributes that are functionally
-------
Beyond the Protocol / 119
important to many assemblage species in that habitat would be the most direct way to maximize
utilization in terms of the number of fish and wildlife potentially attracted to the habitat. But, if we
wish to incorporate criteria promoting these attributes into designs for restoration or mitigation
projects, we need to understand the tradeoffs incorporating many attributes versus focusing effort
on a few, more “universal” attributes.
Habitat scale, a concept of the emerging science of landscape ecology, logically should be
an important determinant of fish and wildlife support although its influence remains relatively
untested. Obviously, the size of a habitat will determine the level of any space-limited attribute,
such as attached (sessile) epifauna that are limited to hard substrate within a narrow tidal range.
But, the functional thresholds for even these seemingly straightforward relationships are unknown.
For instance, we do not know the minimum dimensions of an eelgrass or marsh vegetation patch
that ensure benefit to fish and wildlife. Similarly, the configuration of the habitat, and its compon-
ent microhabitats, may well produce variable results in terms of fish and wildlife utilization.
Following the same example; is there a difference in the way fish and wildlife respond to many
scattered, dense patches of eelgrass or marsh vegetation as compared with one large but contiguous
sparser patch? Finally, there is the question of how important connectivity (such as corridors) and
transition habitats (buffers zones) are in determining the extent of fish and wildlife use: All the
highest parameter values for a plethora of attributes will not benefit a fish or wildlife species if the
boundaries of the habitat do not have the characteristics that the species requires for access.
Until questions of scale, configuration, complexity, and connectivity are examined directly,
this approach to enhancing the success of estuarine habitat restoration and mitigation through better
design criteria will not achieve its full potential.
COPREHENSIVE, ESTUARY-WIDE PLANNING OF RESTORATION AND MITIGATION
Finally, we suggest that in both policy and practice, restored and created estuarine habitats
will never achieve fidifunction as long as the location and composition of estuarine habitats are not
considered in the context of the estuarine ecosystem. Until we consider the ecosystem of which
we are manipulating but a segment, we face the constant possibility of failure because of factors
outside our sphere of consideration. In this context, it is worth noting Diamond’s (1987)
observation that,
We’re not restoring the natural landscape but tiny pieces of it. The integrity of these
tiny pieces will inevitably depend on the influences from outside their borders.
Hence restored communities tend to be small, and to support small populations
prone to extinction partly because they depend upon resources beyond the boundar-
ies of the community. We are the ones who will have to supply those resources to
small, isolated communities to prevent extinctions and so to preserve the commun-
ity itself. And doing this is a form of restoration—or at least active maintenance.
The roots of the Protocol are based in estuarine scientists’ and managers’ studies and
observations over broad number and spectrum of natural estuarine habitats, but over only a few
restoration/mitigation projects. Thus, the attributes they have identified as being most important in
determining fish and wildlife utilization originate from the wiy the habitats function in the esniarine
system, not as isolated habitats. In contrast, both (1) evaluating the function of the habitat to be
developed and (2) determining an appropriate restoration/mitigation plan presently treat the habitat
in isolation because it is almost exclusively the applicant’s option to choose the habitat and loca-
tion. In most cases, but not necessarily all, the driving constraints are cost: cost of the land, cost
of the restoration/mitigation design, cost of monitoring.
-------
DISCUSSION/ 120
Yet, the success of any particular restoration/mitigation project may depend just as much on
where it is located in the estuary as on how it is designed. Circulation and sedimentation patterns,
salinity distribution, freshwater discharge cycles, water quality, location of critical estuarine
features such as the turbidity maximum (null zone), migration corridors of fish and wildlife: These
factors are impOrtaiit considerations in detennining where and in what form restoredJcrea eJ
habitats should occur.
If resto ration and mitigation projects are to succeed on a large scale, they murt be planned
and implemented on a large scale. At a minimum, this scale must encompass all factors that
determine the occurrence, distribution, and ecological role of habitats in our remaining estuarine
ecosystems.
A primary consideration, for instance, should be the historic habitat composition and
distribution in the estuary before the advent of dredging, filling, and diking. The historic structure
of the estuary’s natural estuarine habitats thus could provide a template both for planning how
restoration/mitigation can best reestablish viable habitats and for determining where chosen projects
have a high probability of succeeding.
It is not our position to advocate a particular restoration/mitigation policy but to argue the
scientific basic for planning on an estuary-wide scale. The policy alternatives in such a planning
effort are being treated elsewhere (Tanner 1990) and are outside the scope and mandate of the
Protocol.
-------
SUMMARY
The Estuarine Habitat Assessment Protocol described in this document is an ad hoc
approach to assessing estuarine habitat function for fish and wildlife using quantitative parameters.
In developing the Protocol, we drew on the accumulated knowledge of estuanne scientists and
managers in the region using a hierarchical series of questionnaires and a workshop to synthesize
their expertise. Although the Protocol may be found inadequate, it will likely be because the
scientific information about fish and wildlife use of habitat in the Pacific Northwest, and estuarine
habitat attributes that account for it, is quite restricted. Of course, the impetus to the Protocol and
its novel structure is, in part, intended to systematically expand this meager base of knowledge.
Our focus from the beginning has also been exceedingly narrow, limited to estuarine
habitats and only their function in support of fish and wildlife. l’his in no way discounts the
importance of other habitats to fish and wildlife, nor the other functions of all habitats; there is just
as much a need for standardized, quantitative monitoring protocols for these as there is for the
habitats and functions we have addressed. We invite similar attempts in these other arenas.
Finally, we repeat our common goal to be effective in reconstructing damaged estuarine
ecosystems and to ensure that no net loss is incurred in the remaining undeveloped estuarine
habitats. The Protocol is one attempt to facilitate this goal, by establishing tools to (1) learn not
only from our successes but also from our mistakes; (2) emphasize restoration/mitigation based on
ecological processes (i.e., function) rather than just structure; (3) provide insights into the dynam-
ics of estuarine communities; and (4) provide “basic” information about the way estuarine corn-
munities develop. A perspective on restoration pointed out by Leopold (1934) long before habitat
restoration/mitigation was a viable concept, muôh less a practice, is that ecologists can take the
same approach as chemists in establishing the elemental composition of a substance by analysis;
but, as in chemistry, the proof of structure lies in synthesizing the compound. Similarly,
restoration of complex habitats can only benefit from its treatment as experimentation into the
processes which determine their “function” to man. We must make this opportunity work to our
advantage.
-------
LITERATURE CITED
Albnght, R., and D. Armstrong. 1982. Corophiwn spp. productivity in Grays Harbor, Washington. Final rep to
U.S. Army Corps Engineers-Seattle Disi. DACW67-80-C-009l. 63 pp.
ASIH (American Society of Ichchyologists and Herpetologists). 1971. Guidelines for use of fishes in field research.
ASIH suppi.
Amspoker, M. C., and C. D. Mc lntire. 1978. Distribution of intertidal diatoms associated with sediments in
Yaquina estuary, Oregon. I. Phycol. 14:387-395.
Anderson, R.. 0., and S. J. Gutreuter. 1983. Length, weight, and associated structural indices. Pp. 282-300 in L.
A. Nielsen and D. L. Johnson (eds.), Fisheries Techniques, Am. Fish. Soc., Bethesda, Md.
Armstrong, D.. J. Armstrong, and P. Dinnel. 1987. Ecology and pop ulanon dynamics of Dungeness crab, Cancer
magister, in Ship Harbor, Anacortes, Washington. Final rep. to Wash. State Dept. Fish., Univ. Wash.. Fish.
Res. Inst., FRI-UW-8701, Seattle. 79 pp.
Balon, E. K. 1975. Terminology of intervals in fish development. I Fish Res. Board Can. 32:1663-1670.
Bameti, P. R. 0., and B. L. S. Hardy. 1967. A diver-operated quantitative suction sampler for sand macrofaunas.
Helgo. wiss. Meereswu. 15:390-398.
Bax, N. .7, E. 0. Salo, B. P. Snyder, C. A. Siznenstad, and W. J. Kinney. 1978. Salmonid outmigration studies in
Hood Canal. Final Report. Phase III. January - July 1977, to U.S. Navy, Wash. Dep. Fish., and Wash. Sea
Grant. Univ. Wash., Fish. Res. Inst., FRI-UW-7819, Seattle. 128 pp.
Be, A. W. H. 1962. Quantitative multiple opening-and-closing plankton samplers. Deep- Sea Re:. 9:144-151.
Beers, I. R., G. L. Stewart 1 and J. D, H. Strickland. 1967. A pumping system for sampling small plankton. I.
Fish Res. Board Can. 24:181 1-1818.
Benson, B. L. 1989. Air-lift sampler applications for sampling hard substrata. Bull. Mar. Sc 44:752-756.
Beyer, F. 1958. A new bottom-living Trachyinedusa from the Oslo Fjord; description of the species, and a general
discussion of the life conditions and fauna of the fjord deeps. Nyu Mag. Zoo!. 6:121-143.
Birkeu, L., and A. D. McIntyre. 1971. Treatment and sorting of samples. Pp. 156-168 in N. A. Holme and A. D.
McIntyre (eds.), Methods for the Study of Marine Benthos, IBP Handbook 16, Internat. Biol. Prog., Blackwell
Sci. Pubi., Oxford. 334 pp.
Bollens, S. M., and B. W. Frost. 1989. Zooplankuvorous fish and variable diel vertical migration in the marine
planktonic copepod Calanus paci icus. Limnol. Oceanogr. 34:1072-1083.
Borenstein, M., and J. Cohen. 1988. Su is:ical Power Analysis: A Computer Program. Lawrence Erlbaum and
Assoc., Hdlsdale, NJ.
Borton, S. F. 1982. A structural comparison of fish assemblages from eelgrass and sand habitats a! Alki Point,
Washington. M.S. thesis, Univ. Wash., School Fish., Seattle. 85 pp.
Bossanyi, J. 1951. An apparatus for the collection of plankton in the immediate neighborhood of the sea-bottom.
I. Mar Biol. Assoc. U.K. 30:265-270.
Boulé, M. E. 1981. 1 dal wetlands of the Puget Sound region, Washington. Wetlands 1:47-60.
Bottle, M. E. and Dybdahl. 1981. Wetlands. In Volume III, Fish and wetlands, Commencement Bay Study,
prepared by Dames and Moore for U.S. Army Corps of Engineers, Seattle District.
Box, G., W. Hunter, and.7. Hunter. 1978. Statistics for Experimenters. John Wiley & Sons, New York, N.Y.
653.pp.
Bradfield, G. E. and G. L. Porter. 1982. Vegetation structure and diversity components of a Fras& estuary tidal
marsh. Canadian I. Botany 60:440-451.
Brett, C. E. 1964. A portable hydraulic diver operated dredge-sieve for sampling subtidal macrofauna. I. Mar. Re:.
22:205-209.
-------
References / 124
Bros, W. E., and B. C. Cowell. 1987. A technique for optimizing sample size (replication). Erp. Mar. Bid. Ecol.
114:63-71.
Burg, M. E., D. R. Tripp, and E. S. Rosenberg. 1980. Plant associations and primary productivity of the
Nisqually salt marsh on southern Puget Sound, Washington. Northwest Science 54:222-236.
Burnham, K. P., D. W. Anderson, G. C. White. C. Brownie, and K. H. Pollock. 1987. Design and analysis
methods for fish survival experiments based on release-recapture. Am. Fish. Soc. Monogr. 5, Bethesda, Md.
437 pp.
Cain, R. L., and J. M. Dean. 1976. The annual occurrence, abundance and diversity of fish in South Carolina
intertidal creeks. J. Mar. Biol. 36:369-379.
Cailliet, G. M. 1977. Several approaches to the feeding ecology of fishes. Pp. 1-13 in C. A. Simenstad and S. J.
Lipovsky (eds.), Proc. Fish Food Habits Studies, 1st Pac. Northwest Tech. Workshop, October 13-15, 1976,
Astoria, Oreg. Wash. Sea Grant Pubi. WSG-WO 77-2, Univ. Wash., Seattle. 193 pp.
Cailliet, G. M., M. S. Love, and A. W. Ebeling. 1986. Fishes; A Field and Laboratory Manual on their
Structure, !denztflcanon, and L (e History. Wadsworth PubI. Co., Belmont, Calif. 194 pp.
Chester, A. J., D. M. Damkaer, D. B. Dey, G. A. Heron, and J. D. Lawrence. 1979. Plankton of the Strait of Juan
de Fuca, 1976-1977. Interagency Energy/Environ., R & D Prog. Doc. EPA-600f7-80-032, U.S. EPA,
Washington, D.C. 64 pp + microfiche.
Christie, N. D., and J. C. Allen. 1972. A self-contained diver-operated quantitative sampler for investigating the
macrofauna of soft substrates. Trans. Roy. Soc. S. Africa 40:299-307.
Clarke, 0. M. 1980. Statistics and Experimental Design. Edward Arnold, London. 188 pp.
Cochran, W. 0., and 0. M. Cox. 1957. Experimental Designs. 2nd ed., Wiley, N.Y.
Cohen, J. 1988. Statistical Power analysis for the Behavioral Sciences. 2nd ed. Lawrence Erlbaum Assoc.,
Hillsdale, N.J.
Colman, J. S., and F. Segrove. 1955. The tidal plankton over Stoupe Beck sands, Robin Hood’s Bay (Yorkshire,
North Riding). I. Aram. Ecol. 24:445-462.
Conquest, L. L. 1983. Assessing the statistical effectiveness of ecological experiments: utility of the coefficient of
variation. Internat. I. Environ. Studies 20: 209-211.
Cooper, J. W. 1987. An overview of estuarine habitat mitigation projects in Washington State. Northwest
Environ. J. 3:113-127.
Cordell, J. R.. and C. A. Simenstad. 1981. Community structure and standing stock of epibenthic zooplankton at
five sites in Grays Harbor, Washington. Final Rep. to Seattle, DiSL, U.S. Army Corps of Engineers. Univ.
Wash., Fish. Res. Inst., FRI-UW-8120, Seattle. 28 pp.
Couch, A. B. 1966. Feeding ecology ofTour species of sandpipers in Western Washington. M.S. thesis, Univ.
Wash., Seattle. 57 pp.
Coughlan, J., and J. M. Fleming. 1978. A versatile pump-sampler for live zooplankton. Estuaries 1:132-135.
Cowardjn, L. M., V. Carter, F. C. Golet, and E. T. LaRoe. 1979. Classification of wetlands and deepwater habitats
of the United States. FWS/OBS-79f31, hal. Serv. Prog., U.S. Fish Wildi. Serv., Washington, D.C. 103 pp.
Creutzberg, F., 0. C. A. Duineveld, and 0. J. van Noort. 1987. The effect of different numbers of tickler chains
on beam-trawl caWhes. I. Cons. mt. Explor Mer 43:159-168.
Cytel Software Corporation. 1989. StaiXac:: Statistical Software for ExaciNonparametric Inference User Manual.
Cambridge, Mass. 219 pp.
Daviti, B. B., and J. R. Nelson. 1980. A method of preparing plant epidermal tissue for use in fecal analysis. Circ.
0628, Coil. Agricult. Res. Center, Wash. State Univ., Pullman.
Dethier, M. N. 1990. A marine and escuarine habitat classification system for Washington State. Wash. Nat.
Heritage Prog., Wash. Dept. Nat. Res., Olympia. 56 pp.
-------
References/ 125
Dewey, M. R.. L. E. Holland-Bartels, and S. J. Zigler. 1989. Comparison of fish catches with buoyant pop nets
and seines in vegetated and nonvegetaled habitats. N. Am. I. Fish. Mgmz. 9:249-253.
Diamond, J. 1987. Reflections on goals and on the relationship between theory and practice. Pp. 329-336 in W.
R. Jordan 111, M. E. Gilpin, and J. D. Abet (eds.), Restoration Ecology: A Synthetic Approach to Ecological
Research. Cambridge Univ. Press, Cambridge. 342 pp.
Dinnel, P., D. Armstrong, and R. McMillan. 1986. Dungeness crab, Cancer magi ter, distribution and
recruitment, growth and habitat use in Lummi Bay, Washington. Final rep. to Lumma Indian Tribe. Univ.
Wash., Fish. Res. Inst., FRI-UW-8612, Seattle. 61 pp.
Dimiel, P., R. McMillan, D. Armstrong, T. Wainwright, A. Whiley. R. Burge, and R. Baumgarner. 1987. Padilla
Bay Dungeness crab, Cancer magister, habitat study. Final rep. to NOAA and U.S. EPA. Univ. Wash., Fish.
Res. Inst., FRI-UW-8704, Seattle. 78 pp.
Disraeli, D.J. 1977. Gradient analysis of the vegetation in a brackish marsh Bellingham Bay, Washington. M.S.
thesis, Western Washington State College, Bellingham.
Donnelly, R. In prep. The comparison of two small research trawis; a 3-rn beam trawl and a 7.6-rn otter trawl.
Unpubi. manuscript, Fish. Res. Inst., Univ. Wash., Seattle. 26 pp.
Donnelly, R. F., B. S. Miller, R. R. Lauth, and J. Shriner. 1984. Fish ecology. Section 7, Vol. V I in K. K.
Chew and Q. J. Stober (Prin. Invest..), Renton Sewage Treatment Plant Project: Seahurst Baseline Study.
Final Rep. to Municip. Metro. Seattle. Univ. Wash., Fish. Res. Inst., FRI-UW-8413, Seattle. 271 pp.
Dorney, R. S., and A. S. Rusch. 1953. Muskrat growth and liner production. Tech. Bull. 8, Wis. Conserv. Dept.
Dumbauld, B., D. Armstrong, and R. Black. 1986. Distribution and abundance of Dungeness crab, Cancer magisrer
in Grays Harbor, Washington, and in adjacent nearshore during falVwinter 1985/86. Final rep. to U.S. Army
Corps Engineers, Seattle Dist. Univ. Wash., Fish. Res. Inst., FRI-UW-8616, Seattle. 83 pp.
Dumbauld, B., D. Armstrong, and D. Doty. 1988. The use of Sevin to control burrowing shrimp in Willapa B y.
Centen. Clean Water Fund Grant, Summary Rep. for Pac. County Conserv. Dist., Wash. State Conserv.
Comm.
Dyer. K. R. (ed.). 1979. Estuarine Hydrography and SedImeraatzon: A Handbook Eswarine and Brackish-water
Sciences Association Handbook, Cambridge Univ. Press, Cambridge. 230 pp.
Ellers, H. P. 1975. Plants, plant communities, net production and tide levels: the ecological biogeography of the
Nehalem salt marshes, Tillamook County, Oregon. Ph.D. dissertation, Oregon State University, Corvallis.
638pp.
Eleftheriou, A.. and N. A. Holme. 1984. Macrofauna techniques. Pp. 140-216 in N. A. Holme and A. D.
McIntyre (eds.), Methods/or the Study of Marine Berahos, Blackwell Sci. PubI., London.
Elliott, 3. M. 1977. Some methods for the s:aasncal analysis of santples of berithic invertebrates. Freshwat. Rio!.
Assoc., Sci. Pub!. 25, 2nd ed., TituiWilson & Son Ltd., KendaL 160 pp.
Elmgren, R. 1973. Methods of sampling sublittoral soft bottom meiofauna. Oikos Suppt 15:112-120.
Ewel, 3. J. 1987. Restoration is the ultimate test of ecological theory. Pp. 32-33 in W. R. Jordan m, M. E.
Gilpin, and I. D. Aber (eds.), Restoration Ecology: A Synthetic Approach to Ecological Research. Cambridge
Univ. Press, Cambridge. 342 pp.
Ewing, K. 1982. Plant response to environmental variation in the Skagit marsh. Ph.D. dissertation, University
of Washington, S àtt1e.
Federal Interagency Committee for Wetland Delineation. 1989. Federal manual for identifying and delineating
jurisdictional wetlands. U.S. Army Corps Engineers, U.S. EPA. U. S. FiSh Wildi. Serv., and U.S.D.A. Soil
Conserv. Serv., Washington, D.C., Coop. Tech. Pubi.
76 pp + appendices.
Fresh, K. L., D. Rabin, C. A. Simenstad, E. 0. Salo, K. Garrison, and L. Matheson. 1979. Fish ecology studies
in the Nisqually Reach area of southern Puget Sound, Washington. Final rep. to Weyerhaeuser Company.
Univ. Washington, Fish. Res. Inst., FRI-UW-7904, Seaule. 229 pp.
Frolander, H. F., and I. Pratt 1962. A bottom skimmer. Limnol. Oceanogr. 7:104-106.
-------
References/ 126
Frost, B. W. 1985. Food limitation of the plankionic marine ccpepods Calamis pacificus and Pseudocalanus sp. in
a temperate fjord. Arch. Hydrobiol. Beih. Ergebn. Limnol. 21:1-13.
Frost, B. W. 1988. Variability and possible adaptive significance of diel vertical migration in Calanus pac flcus, a
planktonic marine copepod. Bull. Mar. Sci. 43:675-694.
Good, J. W. 198g. Mitigating esluarine development impacts in the Pacific Northwest from concept to practice.
Northwest Environ. 1. 3:93-111.
Goodall, D. W. 1961. Objective methods for classification of vegetation. IV. Pattern and minimal area. Aust. I.
Bot. 9: 162-196.
Goodall, D. W. 1973. Numerical methods of classification. Pp. 575-618 in R. I L Wiuttaker (ed.), Qrdination and
Classification of Communities, Part V, Handbook of Vegetation Science. W. Junk, The Hague.
Granger, T., and M. Burg. 1986. Plant communities of a salt marsh in Padilla Bay, Washington. Wetland Section,
Shorelands and Coastal Zone Management Program, Washington State Department of Ecology, Olympia.
Green, R. H. 1979. Sampling Design and Statistical Methods for Environmental Biologists. J. Wiley & Sons,
New York. 257 pp.
Gunderson, D., D. Armstrong, Y. Shi and R. McConnaughey. 1990. Patterns of estuarine use by juvenile English
sole (Parophrys vetulus) and Dungeness crab (Cancer magister). Estuaries 13:59.71.
Gunderson, D., D. Armstrong, and C. Rogers. 1985. Sampling design and methodology for juvenile Dungeness
crab surveys. Pp. 135-144 in Proceedings of the Alaska Sea Grant Dwigeness Crab Symposium, October 1984.
Proc. No. 85-3, AIw k Sea Grant, Fairbanks, AK.
Gunderson, D. R., and I. E. Ellis. 1986. Development of a plumb staff beam trawl for sampling demersal fauna.
Fish. Re:. 4:35-41.
Hailstone, T. S., and W. Stephenson. 1961. The biology of Callianassa (Trypaea) australiensis Dana 1852
(Cruslacea, Thalassinidea). Univ. Queensl. Pap. Dept. Zool. 1:257-286.
Hamilton, A. L. 1969. A method for separating invertebrates from sediments using long- wave ultra-violet light
and fluorescent dyes. /. Fish. Re:. Board Canada 26:1667-1672.
Harris, R. J. 1975. A Primer of Multi variate Statistics. Academic Press, New York.
Hazel. C. R. 1984. Avifauna of the Columbia River estuary. Final rep. to Col. Riv. Estuary Data Dev. Prog.,
Astoria, Oreg. 85 pp + appendices.
Herman, S. G., and J. B. Bulger. 1981. The distribution and abundance of shorebirds during the 1981 spring
migration at Grays Harbor, Washington. Final rep. to U.S. Army Corps Engineers-Seattle Dist Grays Hbr.
and Chehalis Riv. Improv. Nay. Environ. Stud., DACW67-81-0936. 64 pp.
Hess, J. M., J. L Schroeder, and S. Lind. 1988. The effect of beach nourishment on saimonid prey resources of
Lincoln Park beach, Seattle, Washiffgton: pre-project conditions. U.S. Fish Wildi. Serv., Fish. Assist. Off.,
Olympia, Wash. 17 pp.
Higley, 0. L., R. L. Holton, and M. R. Christian. 1977. Design and operation of variable- height plankton sled.
Exposure 5:8-11.
[ -lodson, R. G., C. R. Bennett, and R. J. Monroe. 1981. Ichthyoplankton samplers for simultaneous replicate
samples at surface and bottom. Estuaries 4:176-184.
Holling, C. S. (ed.). 1978. Adap:i Environmental Assessment and Management. Intl. Ser. Appi. Systems Anal.
3, J. Wiley & Sons, Chichester. 377 pp.
Homer, R. R., and K. J. Raedeke. 1989. Guide for wetland mitigation project monitoring. Rep. Res. Proj.
GC8286, Task 6, prepared for Wash. State Transport. Comm. and U.S. Dept. Transport. Wash. State
Transport. Center, Univ. Wash., Seattle.
Houghton, J. P. 1973. Intertidal ecology. Pp. 119-260 in Q. J. Stober and E. 0. Salo (eds.), Ecological studies of
the proposed Kiket Island nuclear power site. Final rep., Univ. Washington, Fish. Res. Inst., FRI-UW-7304,
Seattle.
-------
References,’ 127
Howerton, 1. 1984. Key mammals of the Columbia River estuary. Final rep. to Cal. Riv. Estuary Data Dcv.
Prog., Wash. Dept. Game, Habitat Mgmt. Div., Olympia, Wash. 116 pp + append.
Hueckel, 0. J. 1980. Foraging on an artificial reef by three Puget Sound fish species. Wash. Dept. Fish. Tech.
Rep. 53. 110 pp.
Hueckel, G. J., and RM. Buckley. 1987. The influence of prey communities on fish species assemblages on
artificial reefs in Puget Sound, Washington. Envir. Biol. Fish. 19:195-214.
Hueckel, 0. J., R. M. Buckley, and B. L. Benson. 1983. The biological and fishery development on concrete
habitat enhancement structures off Gedney Island in Puget Sound, Washington. Unpubl. manuscript, Wash.
Dept. Fish., Olympia. Wash.
Huggeit, A. Si. 0., and W. F. Widdas. 1951. The relationship between mammalian foetal weight and conception
age. I. Physiol. 144:306-3 17.
Hughes, R. M. 1985. Use of watershed characteristics to select control streams for estimating effects of metal
mining wastes on extensively disturbed streams. Environ. Mgm. 9:253-262.
Hughes, R. M., D. P. Larsen, and J. M. Omemik. 1986. Regional reference sites: a method for assesing stream
potentials. Environ. Mgnu. 10:629-635.
Hughes, R. M., T. R. Whittier, C. M. Rohm, and D. P. Larsen. 1990. A regional framework for establishing
recovery cnteria. Environ. Mgmz. 14:673-683.
Hutchinson, I. 1982. Vegetation-environment relations in a brackish marsh, Lulu Island, Richmond, B.C. Can J.
Bo:. 60:452-462.
Hutchinson, 1. 1989. Salinity tolerance of plants of estuarine wetlands and associated uplands. Report to
Washington State Shorelands and Coastal Zone Management Program: Wetlands Sections, Washington State
Department of Ecology, Olympia.
Jordan, W. R. III, M. E. Gilpin, and J. D. Aber (eds.). 1987. Restoration Ecology: A Synthetic Approach to
Ecological Research Cambridge Univ. Press, Cambridge. 342 pp.
Kellogg, I., and D. Shreffler. 1985. An analysis of sampling methodology.and nearshore fish assemblages of
northern Puget Sound. Unpubi. student paper, Marine Fish Biology 565a, on file, Friday Harbor Lab., Univ.
Wash., Friday Harbor, Wash. 38 pp.
Kendall, A.W. 1966. Sampling juvenile fishes on some sandy beaches of Puget Sound, Washington. M.S. thesis,
Univ. Wash., Seattle. 77 pp.
Kentula, M. E., and C. D. Mclntu -e. 1986. The autoecology and production dynamics of eelgrass (Zostera marina
L.) in Necarts Bay, Oregon. Estuaries 9: 188-199.
Kibby, H. V., J. L. Gallagher, and W. D. Sanville. 1980. Field guide to evaluate net primary production of
wetlands. EPA-600/8-80-037, Environmental Research Laboratory, U.S. Environmental Protection Agency,
Corvallis, Oreg. 59 pp.
Korfhage, R. C., J. R. Nelson, and J. M. Skovlin. 1980. Summer food habits of Rocky Mountain Elk in
nonheastern Oregon. J. Wildi. Mgmt. 44:176-180.
Kuipers, B. 1975. On the efficiency of a two-metre beam trawl for juvenile plaice (Pleuronectesplazessa). Neth. I
Sea Res. 9:69-85.
Kusler, J. A., M. L. Q ammen, and G. Brooks (eds.). 1988. Proceedings of the National Wetland Symposium:
Mitigation of Impacts and Losses Assoc. State Wetland Managers, Berne, N.Y.
Kunz, K., M. Rylko, and E. Somers. 1988. An assessment of wetland mitigation practices pursuant to Section
404 permitting activities in Washington State. Pp. 5 15-531 in Proc. First Ann. Meet. Puget Sound Res.,
Seattle, Wash., March 18-19, 1988. Puget Sound Wac. Qual. Auth., Seattle. 789 pp.
Larkin, P. A. 1974. Play ii again sam: an essay on salmon enhancement. I. Fish. Res. Board Can. 31:1433-
1456.
LaSalle, M. W., and T. Dale Bishop. 1987. Seasonal abundance of aquatic diptera in two oligohaline tidal marshes
in Mississippi. Estuaries 10:303-315.
-------
References / 128
Lee, K. N., and J. Lawrence. 1986. Adaptive management Learning from the Columbia River Basin Fish and
Wildlife Program. Environ. Law 16:431.460.
Leopold, A. 1934. The Arboretum and the University. Parks Recreat. 18:59-60.
LeSage, L., and A. D. Harrison. 1979. Improved traps and techniques for the study of emerging aquatic insects.
Entomol. News 90:65-73.
Levy, D. A., and C. D. Levings. 1978. A description of the fish community of the Squamish River Estuary,
British Columbia: Relative abundance, seasonal changes and feeding habits of sa.lmonids. Fish. Mar. Serv.
Manuscrpt. Rep. 1475, Dept. Fish. Oceans, Pac. Biol. Sta., Nanaimo, B.C. 63 pp.
Levy, D. A., and T. G. Northcote. 1982. Juvenile salmon residency in a marsh area of the Fraser River Estuary.
Can. I. Fish. Aqua:. Sci. 39:270-276.
Lipovsky, S. 1985. Port of Seattle Terminal 91 habitat mitigation monitoring study. Rep. to Port of Seattle,
Columbia Science. 43 pp + appendices.
Littler, M.M. and K.E. Arnold. 1985. Electrodes and chemicals. Pp. 349-375 in M. M. Littler and D. S. Littler
(eds), Handbook of Phycologicol Methods. Ecological Field Methods: Macroalgae. Carnbndge University
Press, Cambridge. 617 pp.
Macer, T. C. 1967. A new bottom-plankton sampler. J. Corks. in:. Explor. Mer 31:158-163.
Manual, p. A., T. R. Wahi, and S. M. Speich. 1979. The seasonal distribution and abundance of marine bird
populations in the Strait of Juan de Fuca and northern Puget Sound in 1978. NOAA Tech. Mem. ERL MESA-
44, Mar. Ecosyst. Analy. Prog., Boulder, Colorado. 391 pp.
Mc Inure, C. D., and M. C. Amspoker. 1986. Effects of sediment properties on benthic primary production in the
Columbia River estuary. Aqua:. Bo:. 24:249-267.
Mc lvor, C. C., and W. E. Odum. 1986. The flume net A quantitative method for sampling fishes and
macrocrustaceans on tidal marsh surfaces. Estuaries 9:219-224.
McLusky, D. S. 1981. Esnsarine Ecosystem. John Wiley & Sons, New York. 150 pp.
Meyer, J. H., 1. A. Pearce, and S. B. Patlan. 1981. Distribution and food habits of juvenile salmonids in the
Duwamish Estuary, Washington, 1980. U.S. Fish. Wildi. Serv., Fish. Assist. Off., Olympia, Wash.
Miller, B. S., C. A. Simenstad, L. L. Moulton, W. A. Karp, K. L. Fresh, F. C. Funk, and S. F. Borton. 1977.
Puget Sound Baseline Program: Nearshore Fish Survey. Final Report, July 1974 - June 1977. Rep. to Wash.
State Dept. Ecol., FRI-UW-7710, FiSh. Res. Inst., Univ. Wash., Seattle. 219 pp.
Miller, B. S., C. A. Simenstad, 3. N. Cross, and K. L. Fresh. 1980. Nearshore fish and macroinvertebrate
assemblages along the Strait of Juan de Fuca including food habits of the common nearshore fish. Final
Contract Report to NOAA/MESA Puget Sound Project. EPA DOC Research Report EPA-600f7-80-027. (Also
Univ. Wash., Fish. Res. Inst., FRI-UW-8001, Seattle.) 211 pp.
Miller,C. B., and D. C. Judkins. 1981. Design of pumping systems for sampling zooplankion, with descnptions
of two high-capacity samplers for coastal studies. Bwl. Oceanogr. 1:29-56.
Miller, C. B., B. W. Frost, H. P. Batchelder, M. 3. Clemons, and R. E. Conway. 1984. Life histories of large,
grazing copepods in a subarctic ocean gyre: Neocalanusplumchrus, Neocalanus cristazus, and Eucalanus bungis
in the northeast Pacific. Prog. Oceanogr. 13:201-243.
Miller, 3. M. 1973. i .quanutative push-net system for transect studies of larval fish and zooplanklon. Limnol.
Oceanogr. 18:175-178.
Mitchell, D. L. 1981. Salt marsh reestablishment following dike breaching in the Salmon River estuary, Oregon.
Ph.D. Dissertation, Oregon State University, Corvallis. l7lpp.
Moulton, L. 1979. An ecological analysis of fishes inhabiting the rocky nearshore regions of Northern Puget
Sound, Washington. Ph.D. dissertation, University of Washington, Seattle. 181 pp.
Murphy, G. I • and R. I. Clutter. 1972. Sampling anchovy larvae with a plankton purse seine. Fish. Bull. (U.S.)
70:789-79&.
-------
Reference s/ 129
National Academy of Sciences. 1989. The adequacy of environmental infomiation for outer conUnental sheLf oil and
gas decisions: Flonda and California. Nail. Acad. Press, Washington, D.C. 86 pp.
Neilson, J. D., G. H. Geen and D. Bottom. 1985. Estuarine growth of juvenile chinook salinon (Oncorhynchus
tshawy:scha) as inferred from otolith microsiructure. Can. I. Fish. Aqua:. Sci. 42:899-908.
Nyblade, C. F. 1979 The Strait of Juan de Fuca intertidal and shallow subtidal benthos. Interagency
Energy/Environ. R & D Res. Doc. EPA 600-7179-213, U.S. EPA, Washington, D.C.
Ohman, M. D. 1985. Resource-satiated population growth of the copepod Pseudocalanus sp. Arch. Hydrobiol.
Beth. Ergebn Limnol. 21:15-32.
Ohman, M. D. 1986. Predator-limited population growth of the copepod Pseudocala,ws sp. I. Plankton Res
8:673-713.
Omori, M., and I. Tsutomu. 1984. Methods in Marine Zooplankion Ecology. John Wiley & Sons, New York.
332 pp.
Parasnetrix, Inc. 1980. Port of Seattle Terminal 107 fisheries study. Doc. 80-1229-026F to Port of Seattle.
Parametrix, Inc., Bellevue, Wash. 53 pp.
Parametrix, Inc. 1982. 1980 juvenile salmonid study. Doc. 85-0415-012F to Port of Seattle. Parametrix, Inc.,
Bellevue, Wash. 43 pp + appendices.
Parsley, M. J., D. E. Palmer, and R. W. BurkhardL 1989. Variation in capture efficiency of a beach seine for small
fishes. N. Am J. Fish. Mgrnt. 9:239-244.
Parsons, T. R., M. Takahashi, and B. Hargrave. 1977. Biological Oceanographic Processes. 2nd ed., Pergamon
Press, Oxford. 332 pp.
Pearce, T. A., J. H. Meyer, and R. S. Boomer. 1982. Disthbution and food habits of juvenile salmon in the
Nisqually estuary, Washington, 1979-1980. U.S. Fish Wild!. Serv., Fish. Assist. Off., Olympia, Wash. 77
pp.
Phillips, R. C. 1984. The ecology of celgrass meadows in the Pacific Northwest A community profile. U.S.
Fish. WildI. Serv., Biol. Serv. Prog., FWS/OBS-84f24. 85 pp.
Poole, R. W. 1974. An Introduction to Quantitative Ecology. McGraw-Hill, New York.
Posey, M. H. 1986. Predation on burrowing shrimp: distribution and community consequences. I Exp. Mar
Biol. Ecol. 103:143-161.
Pritchard, D. W. 1967. What is an estuary: physical viewpoint. Pp. 3-5 in 0. F. Lauff (ad.), Estuaries. Am.
Assoc. Adv. Sci., PubI. 83, Washington, D.C.
FF1. 1991. Update: Pollutants of concern; matrix and users manual. For Paget Sound Estuary Program, U.S.
EPA, Region 10 (in press).
Paget Sound Estuary Program. 1990a. Recommended guidelines for sampling soft-bottom demersal fishes by beach
seine and trawl in Puget Sound. Prepared by P11 Environmental Services, Teira Tech, Inc., Bellevue, Wash.,
and School of Fisheries, Unversity of Washington, Seattle. In Recommended Protocols and Guidelines for
Measuring Selected Environmental Variables in Puget Sound, U.S. EPA, Region 10. Seattle. 4Opp + append.
Puget Sound Estuary Program. 1990b. Recommended protocols for sampling and analyzing subudal benthic
macroinvertebrate assemblages in Puget Sound. Prepared by Tetra Tech, Inc., Bellevue, Wash. In Recommended
Protocols and Guidelines for Measuring Selected Environmental Variables in Pugel Sound. U.S. EPA, Region
10: Seattle. 31 pp.
Puget Sound Estuary Program. 1990c. Recommended season for sampling subtidai benthic macminvertebraxes
during Puget Sound monitoring. Prepared by Tena Tech, Inc., Bellevue, Wash. In Recommended Protocols and
Guidelines for Measuring Selected Environmentai Variables in Puge: Sound, U.S. EPA, Region 10, Seattle. 22
pp.
Puget Sound Water Quality Authority Monitoring Management Committee. 1991. Puget Sound Ambient
Monitoring Program Data Transfer Formats. Version 2. PSWQA, PSAMP Steering Comm.. Mail Stop PV-
11, Olympia, Wash.
-------
References / 130
Rey, J. R., R. A. Crossman, 1. R. Kain, F. E. Vose, and M. S. Peterson. 1988. Sampling zooplanklon m
shallow marsh and estuarine habitats: gear description and field tests. Estuaries 10:61-67.
Riley, I. D., and B. H. Holford. 1965. A sublittoral survey of Port Erin Bay, particularly as an environment for
yougn plaice. Rep. Mar. Biol. Sta. Pt. Erin. 77:49-53.
Rogers, C. W., D , R.Gunderson, and D. A. Armsuong. 1988. UtiIi7i tion of a Washington estuary by juvenile
English sole, Parophrys vetuius. Fish. Bull. (U.S.) 86:823-831.
Runge, I. A. 1985. Relationship of egg production of Ca/anus pacjficus to seasonal changes in phytoplankion
availability in Puget Sound, Washington. Linznol. Oceanogr. 30:382-396.
Rylko, M., and L. Storm. 1991. How much wetland mitigation are we requiring? Or. is not net loss a reality? Pp.
314-327 in Proceedings of the Second Puget Sound Research Conference, Seattle, Puget Sound Wat. Qual.
Auth., Olympia, Wash. 808 pp.
Scheaffez, R. L., W. Mendenhall, and L. Ott. 1979. Elementary survey sampling. 2nd Ed., Duxbury Press, North
Scituaze, Mass. 278 pp.
Shimek, R. L. 1990. Comparison of variance differences and discussion of larval recruitment effects on benthic
analyses; January, June and August samples. Draft rep., Parametrix, Inc., Bellevue, Wash. 46 pp.
Schoen, J. 1972. Mammals of the San Juan archipelago: distribution and colonization of native land mammals
and insularity in free populations of Perpmyscu.s manicuiatus. M.S. thesis, University of Puget Sound, Seattle.
Schreiner, J. U., E. 0. Salo, B. P. Snyder, and C. A. Simenstad. 1977. Salmomd outmigration studies in Hood
Canal. Final rep., Phase H, to U.S. Navy. Univ. Wash., Fish. Res. Inst., FRI-UW-7715, Seattle. 64 pp.
Shreffler, D. A., R. M. Thom, C. A. Simenstad, J. R. Cordell, and E. 0. Salo. 1988. Habitat utilization of a
restored wetland system by juvenile salmonids. Pp. 504-514 ui Proceedings of the First Annual Meeting on
Puget Sound Research. Puget Sound Wat. Qual. Auth., Seattle. Vol. I and IL 789 pp.
Shreffler, D. A., R. M. Thom, C. A. Simenstad, J. R. Cordell, and E. 0. Salo. 1990. The Lincoln Avenue
wetland system in the Puyallup River estuary, Washington, Phase ill report: Year three monitoring, January-
December 1988. Univ. Wash., Fish. Res. Inst., FRI-UW-8916, Seattle. 54 pp.
Shreffler, D. K., C. A. Simenstad, and R. M Thom. 1990. Temporary residence by juvenile salmon of a restored
estuarine wetland. Can. I. Fish. Aquat. Sci. 47:2079-2084.
Shreffler, D. K., C. A. Simenstad, and R. M. Thom. In press. Juvenile salmon foraging in a restored estuarine
wetland. Estuanes.
Sibert, J., B. A. Kask, and T. J. Brown. 1977. A diver-operated sled for sampling the epibenthos. Fish. Mar.
Serv., Tech. Rep. 738, Fish. Environ. Canada, Pac. Biol. Sin., Nanaimo, B.C. 19 pp.
Siegel, S. 1956. Nonparameiric Statistics for the Behavioral Sciences. McGraw-Hill, N.Y.
Simenstad, C. A. 1984. Epibenthic organisms of the Columbia River Estuary. Final rep. to Col. Riv. Estuary
Data Dcv. Prog. Univ. Wash., Fish. Res. Inst., Seattle.
Simenstad, C. A. 1987. The role of Pacific Northwest estuarine wetlands in supporting fish and motile
macroinvertcbrates: The unseen users. In Dyer, P. (ed.), Northwest Wetlands: What are they for? For Whom?
For What?, Proceedings of the Northwest Wetlands Conference, 1.2 November 1985, Seattle, Wash. Inst.
Environ. Studies, Univ. Wash., Seattle. 253 pp.
Simenstad, C. A., and I. R. Cordeil. 1985. Structural dynamics of epibenthic zooplankion in the Columbia River
Delta. Verh. In:errsai. Verein. Limnol. 22:2173-2182.
Simenstad, C. A., and I. R. Cordell. 1988. Effects of Sevin application on littoral flat meiofauna Preliminary
sampling on Willapa Bay, June-July 1988. Univ. Wash., Fish. Res. Inst., FRI-UW-8804, Seattle.
Simenstad, C. A., J. R. Cordell, R. C. Wissmar, K. L. Fresh, S. Schroder, M. Can, and M. Berg. 1988a.
Assemblages structure, microhabitat distribution, and food web linkages of epibenthic crustaceans in Padilla Bay
National Estuarine Research Reserve, Washington. Uruv. Wash., Fish. Res. Inst., FRI-LJW-8813, Seattle. 60
pp.
-------
Reference s/ 131
Simenstad, C. A., and D. M. Eggers (eds.). 1981. Juvenile salmonid and baitfish distribution, abundance, and prey
resouives in selected areas of Grays Harbor, Washington. Final rep. to Seattle Dist., U.S. Army Corps of
Engineers. Univ. Wash., Fish. Res. Inst., FRI-UW-81 16, Seattle. 205 pp.
Simensiad, C. A., K. L. Fresh, and E. 0. Salo. 1982. The role of Puget Sound and Washington coastal estuaries
in the life hi tory..of Pacific salmon: An unappreciated function. Pp. 343-364 in V. S. Kennedy (ed.),
Estuarine Conzparisons, Academic Press, New York. 709 pp.
Simenstad, C. A., W. J. Kinney, and B. S. Miller. 1979. Epibenthic zooplankton assemblages at selected sites
along the Strait of Juan de Fuca. Final contract rep. for NOAAIMESA Puget Sound Project. Univ. Wash.,
Fish. Res. Inst., Seanie. NOAA Tech. Memo. ERL MESA.46. 73 pp.
Simenstat!, C. A., W. J. Kinney, S. S. Parker, E. 0. Salo, J. R. Cordell,’ and H. Buechner. 1980. Prey community
structures and trophic ecology of outmigrating juvenile churn and pink salmon in Hood Canal, Washington: A
synthesis of three years’ studies, 1977-1979. Final Rep. to Wash. Dept. Fish. Univ. Wash., Fish. Res. Inst.,
JJ’.’/.8026 Seattle. 113 pp.
Simenstad, C. A., R. M. Thom, K. A. Kuzis, I. R. Cordell, and D. K. Shreffler. 1988b. Nearshore community
studies of Neah Bay, Washington. Final rep. to U.S. Army Corps of Engineers, Seattle D1SL Univ. Wash.,
Fish. Res. Inst., FRI-UW-881 1, Seattle. 200 pp.
Simenstad, C. A. and E. 0. Salo. 1982. Foraging success as a determinant of estuarine and nearshore carrying
capacity of juvenile chum salmon (Oncorhynchus keza) in Hood Canal, Washington. Pp. 2 1-37 in B. R.
Mekeff and R. A. Neve (eds.), Proceedings of the North Pacific Aquaculiure Synzposzwn, 18-27 August 1980.
Anchorage, Alaska and Newport, Oregon. Alaska Sea Grant Rep. 82-2. Univ. Alaska, Fairbanks. 372 pp.
Simenstad, C. A., C. D. Tanner, and R. M. Thom. 1990. Estuarine habitat assessment protocol: Supplements.
Univ. Wash., Fish. Res. Inst., FRI-UW-8919, Seattle. 617 pp.
Simenstad, C. A., and R. C. Wissmar. 1984. Variability of estuarine food webs and production may limit our
ability to enhance Pacific salmon (Oncorhynchus spp.). Pp. 273-286 in W. G. Pearcy (ed.), The Influence of
Ocean Conditions on the Production of Salmonids in the North Pacific. Proc. Salrnonid Oceanography
Workshop, 8-10 November 1983. Oregon State Univ., Marine Science Center, Newport, Oreg. OSU Sea Grant
College Prog., ORESU-W-83-001. 327 pp.
Simenstad, C. A., and R. C. Wissmar. 1985. 8 13 C evidence of the origins and fares of organic carbon in estuarine
and nearshore marine food webs. Mar. Ecol. Prog. Ser. 22:141-152.
Srngarajah, K. V. 1969. Escape reactions of zooplankion: the avoidance of a pursuing siphon tube. I. Exp. Mar.
Bsol. Ecol. 3: 171-178.
Singarajah, K. V. 1975. Escape reactions of zooplankton: effects of light and turbulence. I. Mar. Biol. Assoc
U.K. 55:627-639.
Smith, R. I., and I. T. Carlton. 1975. light ’s Manual Intern dal Invertebrates of the Central Cal fornia Coast 3rd
ed., Univ. Calif. Press, Berkeley, Calif. 716 pp.
Snedecor, G. W., and W. G. Cochran. 1980. Statistical Methods. 7th ed., Iowa State Univ. Press, Ames. 507 pp.
Sokal, R. R., and F. J. Rohif. 1990. Biomerry. 2nd ed. W. H. Freeman and Co., N.Y.
859 pp.
Sparks, D. R., and J. C. Malechek. 1968. Esriznanng percentage dry weight in diets using a microscopic
technique. I. Range Mgnu. 21:264-265.
State of Washington Department of Ecology. 1991. Sediment Management Standards, pp. 173-204, Wash. Admin.
Code, Olympia.
Steedman, H. F. (ed.). 1976. Zooplarsfrjon fixation and preservation. The Unesco Press, Paris. 350 pp.
Stevens. B., and D. Armstrong. 1984. Distribution, abundance, and growth of juvenile Dungeness crab (Cancer
magister) in Grays Harbor estuary, Washington USA. Fish. Bull. (U.S.) 82:469-483.
Stevens, B. G., and D. A. Armstrong. 1985. Ecology, growth, and population dynamics of juvenile Dungeness
crab. Cancer rnagister Dana, in Grays Harbor, Washington, 1980-81. Pp. 119-134 in Proceedings of the Alaska
Sea Grant Dungeness Crab Symposium, October 1984. Proc. No. 85-3, Al ck i Sea Grant, Fairbanks, AK.
-------
References / 132
Strickland, I. D. H. 1960. Measuring the production of marine phytoplankton. Bull. Fish. Res. Board Can. 122.
172 pp.
Strickland, R. (ed.). 1986. Wetland Functions, Rehabilitation and Creation in the Pacific Northwest: The state of
our understanding. Proceeding of the Conference, Fort Worden State Park, Pt. Townsend, Wash., April 30-
May 2, 1986., Wash. Dept. Ecol. PubI. 86-14, Olympia. 184 pp.
Stuart, A. 1984. The Ideas of Sampling. Monogr. 4, Oxford Univ. Press, New York. 91 pp.
Tanner, C. D. 1990. Mitigation planning on an estuary-wide scale: An alternative to case.by-case wetland
mitigation policy. MMA thesis, Univ. Wash., Seattle. 109 pp.
Terry, C. 1977. Stomach analysis methodology: still lots of questions. Pp. 87-92 in C. A. Simenstad and S. J.
Lipovsky (eds.), Proceedings of the Fish Food Habiss Studies, 1st Pacific Northwest Technical Workshop,
October 13-15, 1976, Astoria, Oreg. Wash. Sea Grant Pubi. WSG-WO 77-2, Univ. Wash., Seattle. 193 pp.
Thom, R. M. 1978. The composition, growth, seasonal periodicity and habitats of benthic algae on the eastern
shore of central Puget Sound, with special reference to sewage pollution. Ph.D. Dissertation, Univ. Wash.,
Seattle. 237 pp.
Thom. R. M. 1980. Seasonality in low intertidal benthic marine algal communities in central Puget Sound,
Washington, U.S.A. Bozanica Marina 23:7-11.
Thom, R. M. 1981. Primary productivity in Grays Harbor estuary, Washington; Bull. Southern Calif Acad. Sci
83:99-105.
Thom, R. M. 1988. Benthic primary production in the eelgrass meadow at the Pathila Bay National Estuanne
Research Reserve, Washington. Univ. Wash., Fish. Res. Inst., FRI-UW-8808, Seattle. 33 pp.
Thom, R. M. 1989. Plant standing stock and productivity on tidal flats in Padilla Bay, Washington: a temperate
north Pacific estuanne embayment. Univ. Wash., Fish. Res. Inst., FRI-UW-8909, Seattle. 37 pp.
Thom, R. M. 1990a. Spatial and temporal patterns in plant standing stock and primary production in a temperate
seagrass system. Boranica Marina 33:497-510.
Thom, R. M. 1990b. A review of eelgrass (Zostera marina L.) transplanting projects in the Pacific Northwest. The
Northwest Environ. J. 6:121.137.
Thom, R. M., and R. G. Albright. 1990. Dynamics of benthic vegetation standing stock, irradiance, and water
properties in central Puget Sound. Mar. Biol. 104:129-141.
Thom, R.. R. Aibright, C. Simenstad, I. Hampel, I. Cordell, and K. Chew. 1984. Intertidal and shallow subtidal
benthic ecology. Vol. IV in K. K. Chew and Q. J. Stober (eds.), Renton sewage treatment plant study:
Seahurst baseline study. Final Rep. to Municipal. Metro. Seattle. Univ. Wash., Fish. Res. Inst., FRI-UW-
8413, Seattle. 172 pp.
Thom, R. M., I. W. Armstrong, C. P. Staude, K. K. Chew, and R. E. Norris. 1976. A survey of the attached
marine flora at five beaches in the Seattle, Washington, area. Syesis 9:267-275.
Thom, R. M., C. A. Simenstad, I. R. Cordell, and E. 0. Salo. 1986. Early successional development of a
bcnthic-epibenthic community at a newly constructed beach in Slip 1, Commencement Bay, Washington:
initial observations 1985. Univ. Wash., Fish. Res. Inst., FRI-UW-8603, Seattle.
Thom, R. M., C. A. Simenstad, I. R. Cordell, and E. 0. Salo. 1989. Fish and their epibenthic prey in a marina
and adjacent mudflats and eclgrass meadow in a small estuarine bay. Rep. for The Port of Bell ingham. Univ.
Wash., Fish. Res:inst., FRI-UW-8901, Seattle. 27 pp.
Thom, R. M., C. A. Simenstad, and E. 0. Salo. 1987. The Lincoln Avenue wetland system in the Puyallup River
estuary, Washington. Phase I report construction and initial monitoring July 1985-December 1986. Univ.
Wash., Fish. Res. Inst., FRI-UW-8706, Seattle.
Thom, R.M., C.A. Simenstad, D.K. Shreffler, JR. Cordell and E.O. Salo. 1988. The Lincoln Avenue wetland
system in the Puyallup River estuary, Washington, Phase II report year two monitoring, January-December
1987. Univ. Wash., Fish. Res. Inst., FRI-UW-8812, Seattle. 80 pp.
-------
References/ 133
Thom, R.M., C.A. Simenstad, I. R. Cordell, DX. Shreffler, and Laura Hamilton. 1990. The Lincoln Avenue
wetland system in the Puyallup River estuary, Washington. Phase IV report. year four monitoring, January-
December 1989. Univ. Wash.. Fish. Res. Inst., FRI-UW-9004, Seattle. 44 pp.
Thom, R. M., C. A. Simenstad, I. R. Cordell, and L. Hamilton. 1991. The Gog-Li-Hi-Te wetland system in the
Puyallup River e tII ry, Washington. Phrase V report: Year five monitoring, January-December 1990. Univ.
Wash., Fish. Res. Inst., FRI-UW-9108, Seattle. In press.
Trumble, R. J., D. Pentilla, D. Day, P. McAllister, J. Boeuner, R. Adair, and P. Wares. 1977. Results of herring
spawning grounds surveys in Puget Sound: 1975 and 1976. Wash. Prog. Rep. 171, Olympia, Wash. 28 pp.
Trumble, R. J. 1982. Summary of the 1982 sac-me herring fishery in northern Pugec Sound. Wash. Dept. Fish.
Prog. Rep. 171, Olympia, Wash. 32 pp.
Trumble, R. J., R. E. Thorne, and N. A. Lemberg. 1982. The Strait of Georgia herring fishery: A case study of
timely management aided by hydroacoustic surveys. Fish. Bull. (U.S.) 80:38 1-388.
Tudhope, A. W., and T. P. Scoffin. 1984. The effects of Callianassa bioturbation on the preservation of carbonate
grains in Davies Reef Lagoon, Great Barrier Reef, Australia. I. Sed. Petrol. 54:1091-1096.
Tufts, E. R. 1983. The Visual Display of Quantitative Information. Graphics Press, Cheshire, Conn 197 pp.
Tunberg, B. 1983. A simple, diver-operated suction sampler for quantitative sampling in shallow, sandy bottoms.
Opheha 22:185-188.
Tyler, R. W. 1964. Distribution and migration of young salmon in Bellingham Bay, Washington. Circ. 212,
Univ. Wash., Fish. Res. Inst., Seattle. 26 pp.
Volk, E. C., R. C. Wissmar, C. A. Simenstad, and D. M. Eggers. 1984. Relationship between otolith
microstructure and the growth of juvenile chum salmon (Orscorhynchus kaa) under different prey muons Can.
I. Fish. Aquat. Sci. 41:126-133.
Wahl, T. R., S. M. Spiech, D. A. Manwal, K. V. Hirsch, and C. Miller. 1981. Marine bird population of the
Strait of Juan de Fuca, Strait of Georgia, and adjacent waters in 1978 and 1979. NOAA Interagency
Energy/Environ R&D Prog. Rep. EPA-600/7-8l-156, Washington, D.C. 789 pp.
Walton, J. M. 1982. The effects of an artificial reef on resident flatfish populations. Mar. Fish. Rev. 44:45-48.
Walton, J. M., and N. W. Bartoo. 1976. Flatlish densities determined with a diver-operated flounder sampler. I.
Fish Res Board Can. 33:2834-2836.
Washington Department of Ecology. 1988. Resource guide to wetland scientists of the Pacific Northwest. Publ.
#88-2, WDOE Shorelands and Coastal Zone Management Program, Wetland Section, Olympia, Wash.
Webber, H. H. 1980. Whidbey Island intertidal and shallow subtidal benthos. Interagency Energy/Environ. R & D
Prog. Doc. EPA-600/7-80-167, U.S. EPA, Washington, D. C. 91 pp + microfiche.
Weikert, H., and H.-Ch. John. 1981. Experiences with a modified Be multiple opening- closing plankton net. /
Plankton Res 3:167-176.
Weitkamp, L. A. 1991. Disturbance in an intertidal sandllat community: the effects of small- and large-scale
natural and artificial perturbations. M.S. thesis, Univ. Wash., Seattle. 100 pp.
Whitehouse, T. R., B. N. Kamimura, P. A. Poon, S. Dionne, B. A. Raymond, and C. S. Levings. 1989.
Invertebrate sample data from the Campbell and Fraser Rivers estuaries from naturai and developed fish habitats,
1987 and 1988. Can. Data Rep. 763, Fish. Aqua!. Sci., Ottawa.
Wickstead, J. 1953. A new apparatus for the collection of bottom plankton. I. Mar. Biol. Assoc. U.K. 32:347-
355.
Widoski, R. S., and R. R. Whitney. 1979. Inland Fishes of Washington. Univ. Wash. Press, Seattle. 220 pp.
Wilcoxon, R., and R. A. Wilcox. 1964. Some Rapid Approximate Statistical Procedures. Lederle Laboratories,
Pearl River, N.Y.
Wingert, R., and B. Miller. 1979. Distributional analysis of nearshore and demersal fish species groups and
nearshore fish habitat associations in Puget Sound. Final Rep. FRJ-UW-7901, Fish. Res. Inst., Univ. Wash.,
Seattle. 110 pp.
-------
References/ 134
Wissmar. R. C., and C. A. Simenstad. 1988. Energetic constraints of juvenile chum salmon (Oncorhynchus keta)
migrating in estuaries. Can.!. Fish. Aquas. Sd. 45:1555-1560.
Word, J. Q. 1977. An evaluation of benthic invertebrate sampling devices for investigating feeding habits of fish.
Pp. 43-5 5 in C. A. Sunenstad and S. J. Lipovsky (eds.), Proceedings of the First Pac t1c Northwest Technical
Workchop Fish Food Habits Studies, October 13-15, 1976, Astoria, Oreg. Wash. Sea Grant PubL WSG-WO
77-2, Seattle. 193 pp.
Word, J. Q., P. L. Striplin, K. Keeley, I. Ward., P. Sparks-McConkey, L. Bender, S. Huisman, K. Li, and J.
Schrodez. 1984. Subtidal Benthic Ecology. Section 6, Vol. V in K. K. Chew and Q. J. Stober (Pun. Invest),
Renton Sewage Treatment Plant Project: Seahurst Baseline Study, Final Rep. to Municip. Metro. Seattle.
Univ. Wash., Fish. Res. Inst., FRI-UW-84!3, Seattle. 271 pp.
Yocum, W. L., and F. L Tesar. 1980. Sled fox sampling benthic fish larvae. Prog. Fish-Cu!:. 42:118-119.
Youngbluth, M. J. 1982. Sampling demersal zooplankton: a comparison of field collections using three different
emergence traps. I. E p. Mar. Buol. Ecol. 61:111-124.
Zar, J. H. 1974. Biostabsucal Analysis. Prentice-Hall, Inc., Englewood Cliffs, NJ. 620 pp.
Zedler, J. B. 1986. Wetland restoration: trials and errors in ecotechnology? Pp. 11-16 in R. Stnckland (ed.),
Wetland Functions, Rehabilitation and Creation in the Pac4Ic Northwest: The stale of our understanding,
Proceedings of the Conference, April 30—May 2, 1986, Fort Worden State Park, Pt. Townsend, Wash. Wash.
Dept. Ecol. PubI. 86-14, Olympia. 184 pp.
-------
GLOSSARY
algae (p1. of alga ) - simple plant form having no true roots, stems or leaves; ranging in
size from microscopic, single-celled plants (microalgae) to
seaweeds (macroalgae)
amphipod crustaceans in the Order Amphipoda, of Class Malacosiraca
attribute physical and biological characteristic of wetland habitats which
foster fish and wildlife UtIlil2tion by facilitating reproduction,
foraging, refugia (from predation, disturbance) and physiological
adaptation
attribute definition the process by which the e tuarine wetland attributes were
determined; involving (1) the selection of process representative
wetland habitats, (2) fish and wildlife assemblages associated with
them, (3) their primary functions determining fish and wildlife
utilization, and the (4) ranking of these functions and (5) the
attributes of the wetland which are responsible for or indicative of
the wetlands’ functional support
benthic pertaining to the bottom of a body of water
brackish pertaining to water with a salt content ranging between that of sea
water and fresh water, commonly used, however, to refer to
oligohaline waters
calanoid copepods crustaceans in the Order Calanoida, of the Class Copepoda
chlorophyll green pigments essential to the process of photosynthesis, found
primarily in plants; chlorophyll a is a specific type of chlorophyll
pigment often used as an indicator of plant biomass
cladocerans crustaceans in the Order Cladocera, of the Subclass Branchiopoda
copepod crustacean in the Class Copepoda; includes both pelagic
(Calanoida, Cyclopoida) and benthic/epibenthic (Harpacticoida)
orders
c clopoid copepods crustaceans in the Order Cyclopoida, of the Class Copepoda (also
generally includes those in the Order Poeciostomatoida)
creation modification of estuarine shoreline to create a wetland which was
not historically present
cumaceans crustaceans in the Order Cumacean, of the Class Malacostraca
demersal pertaining to an organism, such as a fish, living close to or on the
bottom of a body of water, describing the habitat close to or on the
bottom
density the number of organisms per unit of area or volume ecigrass
thabitat intertidal and shallow subtidal, unconsolidated sand to
mud shores which are colonized by rooted vascular angiosperms
(seagrasses) of the genus Zosrera; two species are prominent in the
-------
Glossary! 136
Pacific Northwest: Zostera marina, the endemic eelgrass, and Z.
japonica, an introduced congeneric
ceigrass (habitat’ ) intertidal and shallow subtidal, unconsolidated sand to mud shores
that are colonized by rooted vascular angiosperms (seagrasses) of
the genus Zostera. Two species predominate in the Pacific
Northwest: Zostera ,narina, the endemic eelgrass, and Z. japonica,
an introduced congeneric
elutriation method of removing organisms from a sediment sample by
continuous flushing with water or another aqueous chemical
emeraent marsh intertidal shores of unconsolidated substrate which are colonized
by erect, rooted, herbaceous hydrophytes, excluding mosses and
lichens
enhancement an effort to improve habitat quantity and quality specifically for fish
and wildlife utilization, and unrelated to mitigation or other
development activity
epibenthic pertaining to the benthic boundary layer habitat at the interface
between the bottom surface and the overlying water column, or to
the organisms living in this habitat
epipelagic pertaining to organisms which, though associated with the bottom,
actively migrate off it into the water column, sometimes to the
surface in shallow depths
estuarine occurring within the boundaries of the estuary, as defined seaward
by the measurable dilution of seawater, usually between headlands
enclosing an embayment, upstream by the limit of tidal influence,
and landward by mean higher high water, but including transition
riparian and upland habitat margins
cub aline waters in the salinity range of 40-30 ppt
euyhpusiids crustaceans in the Order Euphausiacea, of the Class Malacostraca
fish and wildlife assemblages groups of species that are representative of all fish and wildlife
species that commonly utilize specific estuarine habitats; not
inclusive of all species, but each feeding, reproduction, etc., use is
represented; not guilds
gammarid amphipods crustaceans in the Suborder Gammaridea, of the Order Amphipoda
(see amphipod)
gravel-cobble (habj at ) intertidal shores which have substrates composed of a mixture of
cobble (-80 to -70; 256 to 76 mm) and gravel (-70 to -20; 76.2 to
4.76 mm); the habitat tends to be formed as beaches and bars, due
to wave and current action, and seldom flats
habitat sum total of environmental conditions of a specific place that is
occupied by an organism, a population, or a community
haphazard sampling selecting samples using a subjective judgment of randomness
-------
Glossary/ 137
hard substrate (habitat ) outcrops, erratics and other rock formations scattered around the
predominantly unconsolidated shoreline of Puget Sound this
habitat is usually rare within discrete estuaries, where the heavy
sedimentation has often resulted in complete burial since the last
glaciation; they persist, however, where wave and current
exposure maintain exposure of rocks and rock outcroppings
harpacticoid copepods crustaceans in the Order Harpacticoida, of the Class Copepoda
hvdric (soils ) .a soil that is saturated, flooded, or ponded long enough during the
growing season to develop anaerobic conditions in the upper part
hvdrophvtes any macrophyte that grows in water or in a substrate that is at least
periodically deficient in oxygen as a result of excessive water
content; plants typically found in wetlands and other aquatic
habitats
hyperiid amphipods crustaceans in the Suborder Hyperiidea, of the Order Amphipoda
(see amphipod)
hypothesis au idea, usually in the form of a statement of question or theory,
which, without itself having been proved, is taken for granted as a
premise from which to test or discover an assured conclusion;
typically framed in the form of a null hypothesis
infauna those organisms living within the sediments underlying a body of
water
intertidal pertaining to the area exposed at low tides and inundated at high
tides; defmed as the area between Extreme Low Tide and Extreme
High Tide
isopods crustaceans in the Order Isopoda, of the Class Malacostraca
larvae (p1. of larva ) the immature form of a animals which is unlike the adult form and
which requires fundamental changes before reaching the basic adult
form
limnetic waters in the salinity range of 0-0.5 ppt
macrofauna animals with lengths equal to or larger than 0.5 mm (sometimes
1.0 mm) and (usually) less than 5 cm
meiofauna aiiim 1s (usually benthic/epibenthic) between 0.063 and 1 mm long
mesohaline waters in the salinity range of 18-5 ppc
microbiota animals less than 0.063 mm long
mitigation compensation for unavoidable losses of fish and wildlife habitat in
the form of wetland creation or restoration
mixohaline water in the salinity range of 30-0.5 ppt
mudflat intertidal shores not vegetated by macrophytes and with unconsoli-
dated sediment particles smaller than stones, predominantly silt (40
to 8 ; 0.0625 to 0.00391 mm particle diameter) and clay (80 to
120; 0.00391 to 0.00024mm); the substrate usually has high
-------
Glossary / 138
organic content and anaerobic conditions often exist below the
surface
natural variability error associated with estimates of populations which is attributed to
their natural fluctuations, heterogeneous distribution, or dispersal
in the environment -
nearshore subtidal subtidal (depths >ELLW and <20 m) zone adjacent to shoreline or
within estuary
oligohaline waters in the salinity range of 5-0.5 ppt
parameter a measurement or index of an atuibute characteristic; e.g.,
organism density, vegetation height
pelagic pertaining to the water column or to an organism living within the
water column
photosynthesis the process by which plants utilize radiant energy from the sun to
synthesize carbohydrates from carbon dioxide and water
planktonic pertaining to organisms which drift passively or swim weakly in
the water column
polvchaete segmented worms of the phylum Annelida
polyhaline waters with salinity in the range of 30-18 ppt
population all individual of one or more species within a prescribed area or,
statistically, all individuals under investigation
production the amount of organic matter generated by a plant or an animal
oroductivitv the rate at which plants or animals generate organic matter
replication repetition of another independent sample or experiment to obtain
more information for estimating experimental error
representative sampling selecting samples that are considered typical or representative of the
population
restoration modification of developed estuarine shoreline to return it to historic
weUand state
sample a collection of sampling units drawn from a (sampling) frame
sample size the number of sampling units within/upon which measurements are
acquired
sampling the process of collecting a subset of measurements that are
representative of a larger population
sampling element an object or character on which a measurement (parameter) is taken
sampling frame a list of sampling units
sampling units nonoverlapping collections of (parameter) measurements from the
population
sandflat intertidal shores which are not vegetated by i nacrophytes and have
unconsolidated sediment in which particles smaller than stones are
-------
Glossary / 139
predominantly sand (-10 to 4 ; 2.0 to 0.074 mm); they occur as
low gradient flats and bars where the substrate material is exposed
to sorting by wave and current action
sediments the organic and inorganic particulate materials, including gravel,
sand, silt and clay, that cover the bottom of the estuary, including
intertidal areas
soft bottom (habitat’ ) shallow subtidal (i.e., <20 m depth) portion of estuaries, usually in
the channels and shallower portion of embayments in which the
bottom is unconsolidated gravel to silt, with no or minimal relief.
standing stock the weight (biomass) of a group of organisms per unit area or
volume at a given time
subtidal the area below Extreme Lower Low Water (ELLW)
tanaid crustaceans in the Suborder Tanaidacea of the Class Malacostraca
tidal channel a channel through which water drains and fills intertidal areas
UEMWG Urbanized Estuary Mitigation Working Group; an ad hoc technical
group of government agency, tribal, university, and industry repre-
sentatives which has met since 1986 to discuss mitigation in urban-
ized estuaries (a listing of the entities and their representatives of
the UEMWG can be found in Supplement 5 [ Simenstad et al.
1990]) -
variability error associated with estimates of populations which is attributed to
sampling
water column that portion of the estuarine subtidal not associated with the shore
of bottom; this does not include the benthic boundary layer, which
we include in bottom habitats, but does include the neustonic layer
at the surface.
zooplanicton the group of small (primarily microscopic) passively suspended or
weakly swimming animals in the water column
-------
INDEX
A!vremcola pac fica 32, 60 Corophiwn spiiucorne 69
Acarria ca1iforrae i.cis. , 75 Corophiurn spp. 55, 59, 69
Acarria c1au 75 Corycaeus anglicus 75
Active Infauna 65, 68 Corycaeus spp. 75
Agarwn spp. 42 Cottidae (unit) 89
Agrostis alba 42 Couus spp. 89
Aliersacaruhomysis inacropsis 73, 83, 88 Crangon Spp. 83, 86
Alnus rubra 42 Crypzomya ca4forruca 60
Ammodytes hexapterus 98 Cumella vu! garis 69
Ampelzsca agasszzz 55 Cymatogaster aggregaca 98
Ampuhoe spp. 69 Daphnia spp. 75
Arusogammarus pugettensis 69, 73 Decapoda (larvae) 75
Apodicluhysfiavuius 89,97 Demersal Adhesive Fish Eggs 52
Araneae (umd.) 80 dcsnezsal fishes 31, 86, 94, 102
Atylus spp. 69 DendraW&cerarjcu s 55
Ayes (unit) 106 Deschampsia caespisosa 42
avifauna 17 Diptera (unit) 55, 80
Balanuscrenazus 55 Dts:ichiisspicwa 42
Balarsus glandula 55 Eleocharfspaiuszris 42
Balwtus spp. 55 Embiotocidae (unit) 98
benthic grab 33,63 emergence trap 82
Benthic grabs 63, 72 Emergence traps 82
benthic macroalgae 17, 46, 48, 50 Engrazslis mordax 98
benthic microbiota 17, 49, 50 Enteromorpha app. 42, 46
bottom trawl 33, 87, 88, 94, Eogainrizarus corifervicolus 69
95, 101, 102, Eogammaru.sspp. 69
103 Eohaustorzus shingtonianus 69
Callianassa ca4fornienszs 65, 66, 68 Ephydridae (unid.) 80
Cailianassa c ci foriuerssis (larvae) 75 epibenthic pbnkters 17, 34, 55, 69,
Callianassidae (unit) 65 70, 71, 72, 73
Cancer magisier 83, 86, 87 Epilabidocera wnphitri:es 75
Cancer product us 83 Epilabidocera app. 75
Cancer spp. 83 epiphytic algae/animals 46,49
Cancer spp. (larvae) 75 Eualus app. 83,86
Cancer app. (megalops) 75 Euph zu.ciapo4fica 75
Cancer spp. (zoen) 75 Ewyzemora jinis 75
Capitellidae (unid.) 60 Eusiroides app. 69
Caprella Iaevzuscuia 69 evasive macroepifliuna 17, 31, 83, 84
Carex lyngbyei 42 feeding 7
Charadiidae (unit) 106 Fern ica rubra 42
Chironomidae (larvae),. 55 fifth Protocol rule 24
Chironomidae (unit) 80 filainentous algae 49
Citharu hshys spp. 89 first Protocol rule 21
Cisnocardiasra niaalli 55 floating beach seine 102, 104
C1i peo harengu .spa!lasi 98 fourth Protocol rule 22
Clupea harengu.s palia .si (eggs) 52 Gadus rnacrocephalus 98
Cluster sampling 23 Gasrerostes#.s acuieazus 98
connectivity 119 General Avifauna 106
Corbicuic manilensis 55 Glazsx mantima 42
Corophium salmonis 55,69 Gnorimosphaeroma oregonese 69
-------
Index! 142
Gonaridn (unid.) 84 Nereidae (unit) 60
Gravel-Cobble 16, 46, 52, 55, Nereocysii.s luekeana 42
57, 60, 62, 69, neuston net 81, 82
75, 83, 85, 89, neustoriic and drift invertebrates 34, 81)
91, 93, 98, 101 neustonic drift invertebrates 17
Grindelia inzegrifolia 42 Nucella spp. 55
Harpacticus spinulosus 69 Occam’s Raz 29
Harpacticus app. 69 Octopus spp. 83
Harpacucus uniremis 69 Oikopteura spp. 75
Heleidae (unit) 80 Oi:hona similis 75
Hemigrapsusnudis 83 O ligochaeta(unid.) 55
Hemiptera (unit) 55 Oncorhynchus gorbu.scha (fry) 98, 99
Heptacarpus spp. 83,86 Oncorhynchus keca (fry) 98
herbivorous mammals 17, 109, 112 Oncorhynchus spp. 99
Hippolyudae (unid.) 83 Oncorhynchus app. (fry) 98, 99
Hypomesuspretiosus 98 Ondatrazibethicus 109
Insecta (larvae) 80 Orchestia Lraskiana 83, 86
Insecta (unid.) 55,80 Orchomene minuta 69
Ischyrocerus spp. 69 Ostrea lurida 55, 58
Jaunva carno 42 Pac flcas:acj s lersiuscidus 83
Juncus boiticu.s 42 Pancolus cal jforrsiensis 69, 70
Jwicus gerw’dd 42 Pandalusdanae 83, 86, 87
Laminaria spp. 42,46 Paraihemi,uo paqfica 75
Lampetra tridentas’us 98 pelagic zooplankton 17, 34, 75, 78
Lebbeus spp. 83, 86 Peromyscus maniculatus 109
Lepidogobiu.s lepid&s 89 Phatwis arundinacea 42
Leptoconus armazus 89 Perodonfiwcazus 98
L:Iaeopsis occidenwiLs 42 Pholis beta 89. 97
Linorina app. 55 PhoiLs lacia 69
Lohgo opalescen,s 84, 87 Phoxocephalidae app. 70
Lwnpenus saguta 89 Phragmites cominunis 41, 42
Macoina spp. 60 physiological adaptation 7
Macrocystis uuegrifolia 42 Picea sitchensis 42
Macrocysnspyrifera 46 Plarichihys stellazus 89
Mallocus vilbosus 98 Pleuronectes vezuius 89, 90, 95, 96,
Manaywz/da aestuaruia 32, 60 100
Megaborcheszia pugeuertsis 69 Polygonwn hydropiperoides 42
Merluccius prod uclus 98 Polygonum app. 42
Microgadusproxmus 98, 102 Poiuogeneia rostraza 69
Microtus app. 109 pop nets 96
Microtus zownsendü 109 Populus o-ichocarpa 42
midwater trawl 86, 87. 102. 103. Porkhthysrtotazu.s 89, 91, 95, 97,
105 100
motile fish 17, 18. 31, 79, PotentillapacyIca 42
89, 91, 93, 97, Pseuicluhys melanoszictus 89
98, 99, 101, Pseudoc(Jlanusmi,uj zus 75
102, 103, 104, Pugettiagracilis 83
105 purse seine 79. 101, 102,
Myaarenwia 60, 62 103, 105
Myzilus spp. 55 41, 42, 44, 45,
Natural variability 19. 25, 73 46, 47, 48, 50,
Neartzhes linvucola 32, 60 52, 53, 56, 57,
Nematoda (unid.) 60 58, 59, 62, 63,
Neomysis mercedis 17, 73, 83, 88
-------
lndex/ 143
64,67,85,86, Tanaisspp. 60
87, 88, 97, 111 Tapes (Ruduapes) plulipznaruin 60
Random sampling 20, 21, 22, 23, Teleostei (larvae) 75
24, 38, 52 Tellina nuculoides 60
refuge - 7 Tellsna spp. 60
representative sampling 21 Thaleichthys pac ficus 98, 99, 102
reproduction 7 Theragra chalcograrnma 99, 102
Review Workshop 9, 117 third Protocol rule 21
rooted vascular plants 17, 18, 40, 44, Tisbe spp. 69
46,47 Transennejla ta,uilla 60
Rumex spp. 42 Imp nets 93, 104
Ruppia rnanhima 42 treatment replication 24, 26
Salicorrua virginica 42, 43 Triglochin marüirnwn 42
SaILr spp. 42 Tsuga hezeraphylla 42
Sample Processing 33, 72 turbidity maximum 120
sample replication 12, 24, 45, 48, Typha 44
50 Typha Iazifolia 42
sampling frame 1, 23 UEMWG 3, 4, 7, 8
Sampling Strategies 20 Ulva spp. 42, 46
sampling unit 1, 12, 19, 23. 24, Upogebzapugeuens s (larvae) 75
27,28,34,44, Zausspp. 69
45, 48, 53, 97 Zosterajaporaca 40, 41, 42
sampling variability 19 Zosterainarina 17, 42, 44
Sounderza spp. 55 Zosiera spp. 16, 40, 43
scale 27, 28, 92, 101,
107, 116, 118,
119, 120
Scirpu.s acuiu.s 42
Scirpus americanus 42
Scirpus maruimus 42
Scirpu.s validus 42
Scoloidea (urud.) 80
Scorpacnidae (unid) 99
Sebastes caurznus 98
Sebasies spp. 99
second Protocol rule 21
sedentary fish 17, 86, 89. 91.
93, 97, 99,
100, 104
sedentary mfauna 17, 50, 60,62,
63,64
seventh Protocol rule 29
sinking beach seine 85, 86, 93
Slum suave 42
sixth Protocol rule 28
Sorexbendirii 109
Sparuna spp. 42
Sperguiana canathwn 42
Spirinchus :haleichthys 99
Spirontocaris spp. 83
stratified random sampling 23
surface epifauna 17, 55, 56, 62.
86
systematic sampling 21, 24. 87
-------
APPENDICES
APPENDIX A. HABITAT-SPECIFIC LIST OF ASSEMBLAGE SPECIES 147
Emergent Marsh Habitat 147
Mudflat Habitat 149
Snadflat Habitat 150
Gravel-Cobble Habitat 151
Eelgrass Habitat 152
Nearshore Subtidal Soft Bottom Habitat 153
Nearshore Subtidal Hard Substrate Habitat 154
Water Column Habitat 155
APPENDIX B. HABITAT-SPECIFIC UST OF A1TRIBUTES AND
ASSOCIATED HABITAT FUNCI1ONS 156
Emergent Marsh Habitat 156
Mudflat Habitat 166
Snadfiat Habitat 170
Gravel-Cobble Habitat 172
Eelgrass Habitat 177
Nearshore Subtidal Soft Bottom Habitat 182
Nearshore Subtidal Hard Substrate Habitat 184
Water Column Habitat 186
APPENDIX C. PHYSICOCHEMICAL AURJBIJTES DEN1 11-lED IN
PROTOCOL AS IMPORTANT TO FISH AND WILDLIFE UTILIZATION OF
ESTUARINE HABITATS 192
-------
147
APPENDIX A: Habitat-Specific List of Assemblage Species
Emergent Marsh Habitat
Birds
American coot Fulica wnericana
American goldfinch Spinus tristis
American wigeon Antis americana
black brant Braiua bernicla
buffle he ad Bucephala albeola
Canada goose Branta canadensis
common goldeneye Bucephala clangula
common snipe Capella gaulinago
dark-eyed junco Jwzco hyemalis
gadwail Antis strepera
great blue heron Ardea herodias
greater yellowlegs Tringa melanoleuca
green-winged teal Anas crecca
kilideer Charadrius vocifen s
least sandpiper Calidris minutilla
mallard Anas platyrhynchos
merlin Falco columbarius
northern oriole Icerus galbula
osprey Pandion haliaetus
red-tail hawk Buteo jamaicensis
redwing blackbird Agelaius phoeniceus
savannah sparrow Passerculus sand wichens is
short-billed dowitcher Limnodromus g ise1Ls
short-eared owl Asio flammeus
song sparrow Melospiza melodia
spotted sandpiper Actitis macularia
Virginia rail Rallus limicola
western sandpiper Calidris mauri
Fishes
chinook salmon OncorhynchiLs tsha iytscha
chum salmon Oncorhynchus keta
cutthroat trout Oncorhynchus (Salmo) clarki
Pacific staghorn sculpin Leptocottus annatus
prickly sculpin Cottus asper
threespine stickleback Gasterosteus aculeatus
-------
148
Emergent Marsh Habitat - cont.
Mammals
muskrat Ondatra zibethica
Pacific harbor seal Phoca vizulina
raccoon Procyon lotor
river otter Lutra canaden.sis
Townsend vole Microtus townsendii
-------
149
Mudflat Habitat
Birds — -
bufflehead Bucephala albeola
Canada goose Branta canadensis
common goldeneye Bucephaia clangula
common snipe Capella gailinago
dunlin Calidris alpina
great blue heron Ardea herodias
greater yellowlegs Tringa melanoleuca
least sandpiper Calidris minutilla
short-billed dowitcher Limnodro,nus griseus
spotted sandpiper Actitis macularia
western sandpiper Calidris mauri
Fish
bay goby Lepidogobius lepidus
chum salmon Oncorhynchus keta
English sole Pleureonectes (Parophiys) vetulus
green sturgeon Acipenser medirostris
Pacific staghorn sculpin Leptocottus armalus
starry flounder Platichthys stellatu.s
Invertebrates
Dungeness crab Cancer magister
Mammals
Pacific harbor seal Phoca vitulina
raccoon Procyon lotor
-------
150
Sandflat Habitat
Biid
common goldeneye Bucephala clangula
common snipe Capella gallinago
dunlin Calidris alpina
great blue heron Ardea herodias
greater yellowlegs Tringa melanoleuca
horned grebe Podiceps auritu.s
least sandpiper Calidris minufihla
spotted sandpiper Actitis rnacularia
Eish
bay goby Lepidogobius lepidus
chinook salmon Oncorhynchus tshav.ytscha
Pacific sand lance Ammodytes hexapterus
Pacific sanddab Citharichthys sordidus
Pacific staghorn sculpin Leptocottus armatus
sand sole Psettichthys melanostictus
speckled sanddab Citharichthys stiginaeus
Invertebrates
DungenesS crab Cancer magister
Mamrn
Pacific harbor seal Phoca vitulina
Gray whale Eschrichtius robustus
-------
151
Gravel-Cobble Habitat
Birç — -
black brant Branta bernicla
black turnstone Arenaria melanocephala
buftiehead Bucephala oibeola
Common goldeneye Bucephala clangula
double-crested cormorant PhaIacmcora awitus
homed grebe Podiceps awitus
least sandpiper Calidns minutilla
mew gull Larus caluss
spotted sandpiper Actitis macularia
western grebe Aechmophorus occidentai,s
Fi
buffalo sculpin Enophrys bison
coho salmon Oncorhynchus kisutc/j
copper rockflsh Sebastes Caurinus
cutthroat trout Oncorhynchus (Salmo) clarki
dolly varden Salvelinus malma
great sculpin Myoxocephalus polyacant/zocepha1
Pacific herring Clupea harengu.s pallasi
Pacific tomcod Microgadus proximus
padded sculpin Artedius fenestraljs
pile perch Rhacochilus vacca
river lamprey Lainpetra ayresi
rock sole Pleuronectes biineata
starry flounder Platicht/zys stellatus
surf smelt Hypomesus pretiosus
whitespotted greenling Heragrammos stelleri
Invertebrates
red rock crab Cancer productus
Mammpj
raccoon Procyon lotor
river otter Lutra Cano4en.sjs
-------
152
Eelgrass Habitat
Birds
black brant Branta bernicla
bufflehead Bucephala albeola
Canada goose Branta canaden.sis
common snipe Capella gallinago
glaucous-winged gull Larus glaucescens
great blue heron Ardea herodias
greater yellowlegs Tringa melanoleuca
least sandpiper Calidris minutilla
osprey Pandion haliaetus
spotted sandpiper Actitis macularia
Fish
bay pipefish Syngnathus leoptorhynchu.s
chum salmon Oncorhynchus keta
crescent gunnel Pholis laeta
kelp perch Brachyistius frenatus
lingcod Ophiodon elongatus
Pacific herring Clupea harengus pallasi
penpoint gurinel Apodichthys Jkwidus
shiner perch Cymatogoster aggregata
snake prickleback Lumpenus sagitta
striped seaperch Embiotoca lazeralis
tube-snout Aulorhynchus flavidus
Invertebrates
Dungeness crab Cancer magister
Mammals
Pacific harbor seal Phoca vitulina
river otter Lutra canadensis
-------
153
Nearshore Subtidal Soft
Bottom Habitat
Birds
common murre Uria aalge
Fish
C-O sole Pleuronichthys coenosus
Dover sole Microstomus pacificus
hybrid sole Inopsetta ischyra
largescale sucker Catostomus macrocheilus
mountain whitefish Prosopium williwnsoni
northern squawfish Ptychocheilus oregonensis
Pacific cod Gadus macrocephalus
Pacific tomcod Microgadus proximus
ratfish Hydrolagus colliei
rough sculpin Chitonotus pugeten.sLs
sturgeon poacher Agonu..s acipenserinus
walleye pollock Theragra chalcogramma
Invertebrates
Dungeness crab Cancer magister
Mammals
gray whale Eschric/ztius robu.ctus
-------
154
Nearshore Subtidal Hard
Substrate Habitat
Fish
black rockfish Sebasres melanops
brown rockfish Sebastes auriculatzjs
cabezon Scorpaenich:hys marmoratus
copper rockfish Sebastes cawvuss
kelp greenling H&agrwnmos decagrammus
lingcod Ophiodon elongatus
pile perch Rhacochilus vacca
quillback rockfish Sebasres maliger
striped seaperch Embioroca lateralis
-------
155
Water Column Habitat
Birds —
bufflehead Bucep/ ala aibeola
cassin’s aukiet Ptychorwnphus aleuticus
common goldeneye Bucephala clangula
common merganser Me gus mergan.ser
double-crested cormorant Pha!acrocorax auritus
gadwall Anas strepera
mew gull Larus canu.s
osprey Pandion haliaetus
red-breasted merganser Mergus serrator
western grebe Aechmophorus occidentalLs
Fish
chinook salmon Oncorhynclzus tsIza ytscha
chum salmon Oncor/zynchus keta
coho salmon Oncorhynchus kisutch
longfin smelt Spirinclius zhaleichthys
northern anchovy Engraulis mordax
Pacific hake Merluccius productus
Pacific herring Clupea /zarengu.s pallasi
Pacific sand lance Ammodytes hexapterus
pink salmon Oncorhynclius gorbuscha
river lamprey Lam petra ayresi
soft sculpin Gilbertidia sigalutes
steelhead (rainbow) trout Oncorhync/ius mykiss (Salmo gairdneri)
surf smelt Hypomesus pretiosu.s
threespine stickleback Gasterosteus aculeatu..s
western brook lamprey Lam petra richardsoni
Mammals
northern sea lion Eumetopias jubatus
Pacifie harbor seal Phoca vitulina
-------
156
APPENDIX B: Habitat-Specific List of Attributes and Associated Habitat Functions
Emergent Marsh Habitat
Assemblage Attribute Function
Birds
American coot
Scirpus spp. Refuge/Physiology: Biological Complexity,
Emergent Vasc. Plants
Scirpus acutus Feeding: Plants, Emergent Vascular
Typha latifolia Feeding: Plants, Emergent Vascular
American goldfinch
Alnu.s rubra Feeding: Plants, Emergent Vascular
Pha1ari aiundinacea Feeding: Plants, Emergent Vascular
American wigeon
Ba!anus spp. Feeding: Invertebrates, Epibenthic
Enieromorpha spp. Feeding: Plants, Macro Algae
Mytilus edulis Feeding: Invertebrates, Epibenthic
Ruppia maritima Feeding: Plants, Submergent Vascular
Scirpus spp. Refuge/Physiology: Biological Complexity,
Emergent Vasc. Plants
Typha latifolia Refuge/Physiology: Biological Complexity,
Emergent Vasc. Plants
Uh.’a spp. Feeding: Plants, Macro Algae
buffleh ad
Balanus spp. Feeding: Invertebrates, Epibenthic
Insecta (larvae) Feeding: Invertebrates, Epibenthic
Mytilus edulis Feeding: Invertebrates, Epibenthic
-------
157
Emergent Marsh Habitat - cont.
Assemblage Attribute Function
black brant
Carex spp. Feeding: Plants, Emergent Vascular
Enteromorpha spp. Feeding: Plants, Macro Algae
Scirpu..s spp. Refuge/Physiology: Biological Complexity,
Emergent Vasc. Plants
Typha latifolia Refuge/Physiology: Biological Complexity,
Emergent Vasc. Plants
Ulva spp. Feeding: Plants, Macro Algae
Canada goose
Carex lyngbyei Feeding: Plants, Emergent Vascular
Di.sticli!is spicata Feeding: Plants, Emergent Vascular
Scirpu.s americanus Feeding: Plants, Emergent Vascular
Scirpu..s spp. Refuge/Physiology: Biological Complexity,
Emergent Vasc. Plants
Triglochin maritimum Feeding: Plants, Emergent Vascular
Triglochin palustris Feeding: Plants, Emergent Vascular
Typha fatifolia Refuge/Physiology: Biological Complexity,
Emergent Vasc. Plants
common goldeneye
Hemigrapsu c spp. Feeding: Invertebrates, Epibenthic
Littorina spp. Feeding: Invertebrates, Epibenthic
Scirpus spp. Feeding: Plants, Emergent Vascular
common snipe
— . Balanus spp. Feeding: Invertebrates, Epibenthic
Orchestia traskiana Feeding: Invertebrates, Epibenthic
Scirpus spp. Refuge/Physiology: Biological Complexity,
Emergent Vasc. Plants
Transennella tantilla Feeding: Invertebrates, Benthic
Typ/ia latifolia Refuge/Physiology: Biological Complexity,
Emergent Vasc. Plants
-------
158
Emergent Marsh Habitat - cont.
Assemblage Attribute Function
dunlin
Balanus spp. Feeding: Invertebrates, Epibenthic
Transennella tantilla Feeding: Invertebrates, Benthic
great blue heron
Cymazoga.ster aggregata Feeding: Vertebrates, Water Column
Ga.sterosteus aculeatus Feeding: Vertebrates, Water Column
Leptocottus aiinatus Feeding: Vertebrates, Demersal
Microtus spp. Feeding: Vertebrates, Terrestrial
Oncorhynchus spp. (fry) Feeding: Vertebrates, Water Column
Picea sitchensis Reproduction: Substrate, Riparian Vegetation
Platichthys stellatus Feeding: Vertebrates, Demersal
Populus trichocarpa Reproduction: Substrate, Riparian Vegetation
gadwall
Carex spp. Feeding: Plants, Emergent Vascular
Eleocharis palustris Feeding: Plants, Emergent Vascular
Enteromorpha spp. Feeding: Plants, Macro Algae
filamentous algae Feeding: Plants, Micro Algae
Insecta (larvae) Feeding: Invertebrates, Epibenthic
Ruppia mar’itima Feeding: Plants, Submergent Vascular
Scirpus acutis Feeding: Plants, Emergent Vascular
Scirpu.s spp. Refuge/Physiology: Biological Complexity,
Emergent Vasc. Plants
Typha latifolia Refuge/Physiology: Biological Complexity,
Emergent Vase. Plants
Uh’a spp. Feeding: Plants, Macro Algae
greater yellowlegs
Balanus spp. Feeding: Invertebrates, Epibenthic
Transennella tantilla Feeding: Invertebrates, Benthic
-------
159
Emergent Marsh Habitat - cont.
Assemblage Attribute
green-winged teal
Function
Eogamrnarus
con fervicolus
Manayunkia aestua,ina
Polygonurn spp.
Polygon urn
hydropiperoides
Potomogeton spp.
Rumer spp.
Salicornia virginica
Saunderia spp.
Scirpus arnericanus
Scirpus spp.
Scirpus acutus
Triglochin maritimum
Typha latifolia
Insecta (larvae)
Littorina spp.
Cares lyngbyei
Carex spp.
Distichlis spicata
Eleocharis palustris
Eleoc/zaris spp.
Insecta (larvae)
Picea sitchen.sis
Polygonom spp.
Invertebrates, Epibenthic
Invertebrates, Benthic
Plants, Emergent Vascular
Feeding: Plants, Emergent Vascular
Feeding: Plants, Emergent Vascular
Feeding: Plants, Emergent Vascular
Feeding: Plants, Emergent Vascular
Feeding: Invertebrates, Epibenthic
Feeding: Plants, Emergent Vascular
Feeding: Plants, Emergent Vascular
Feeding: Plants, Emergent Vascular
Feeding: Plants, Emergent Vascular
Reproduction: Substrate, Emergent Vasc.
Plants
Feeding: Invertebrates, Epibenthic
Feeding: Invertebrates, Epibe nthic
Feeding: Plants, Emergent Vascular
Feeding: Plants, Emergent Vascular
Feeding: Plants, Emergent Vascular
Feeding: Plants, Emergent Vascular
Feeding: Plants, Emergent Vascular
Feeding: Invertebrates, Epibenthic
Reproduction: Substrate, Riparian Vegetation
Feeding: Plants, Emergent Vascular
• Carex spp.
Distichlis spicata
Eleocharis palu.stris
Eleocharis spp.
Plants, Emergent Vascular
Plants, Emergent Vascular
Plants, Emergent Vascular
Plants, Emergent Vascular
Feeding:
Feeding:
Feeding:
Feeding:
Feeding:
Feeding:
Feeding:
kilideer
mallard
-------
160
Emergent Marsh Habitat - cont.
Assemblage Attribute Function
mallard (cont.)
Polygonum
Fzydropiperoides Feeding: Plants, Emergent Vascular
Populus trichocarpa Reproduction: Substrate, Riparian Vegetation
Potomogeton spp. Feeding: Plants, Emergent Vascular
Rumex spp. Feeding: Plants, Emergent Vascular
Scirpus americanus Feeding: Plants, Emergent Vascular
Scirpu .s spp. Feeding: Plants, Emergent Vascular
Scirpus acutus Feeding: Plants, Emergent Vascular
Triglochin maritimum Feeding: Plants, Emergent Vascular
Typha latifolia Refuge/Physiology: Biological Complexity,
Emergent Vasc. Plants
merlin
Ayes (unid.) Feeding: Vertebrates, Terrestrial
Charadriiformes (unid.) Feeding: Vertebrates, Terrestrial
red-tail hawk
Charadriiformes (unid.) Feeding: Vertebrates, Terrestrial
Microtus townsendii Feeding: Vertebrates, Terrestrial
Ondatra zibethicus Feeding: Vertebrates, Terrestrial
Peromyscus inaniculatus Feeding: Vertebrates, Terrestrial
Sore.x bendirii Feeding: Vertebrates, Terrestrial
redwing blackbird
Typha larifolia Reproduction: Substrate, Emergent
Vasc. Plants
Typha latifolia Feeding: Plants, Emergent Vascular
short-billed dowitcher
Orchestia traskiana Feeding: Invertebrates, Epibenthic
-------
161
Emergent Marsh Habitat - cont.
Assemblage Attribute Function
song sparrow
Grindelia integrifolia Feeding: Plants, Emergent Vascular
Nereidae (unid.) Feeding: Invertebrates, Epibenthic
Scirpus maritimus Feeding: Plants, Emergent Vascular
- - spotted sandpiper
Balanu.s spp. Feeding: Invertebrates, Epibenthic
Transennella tantilla Feeding: Invertebrates, Benthic
western sandpiper
Deschampsia caespitosa Feeding: Plants, Emergent Vascular
Nematoda (unid.) Feeding: Invertebrates, Benthic
Spergularia marina Feeding: Plants, Emergent Vascula
Fishes
chinook salmon
Araneae (unid.) Feeding: Invertebrates, Neustonic
Carex spp. Refuge/Physiology: Biological Complexity,
Emergent Vasc. Plants
Chironornidae (unid.) Feeding: Invertebrates, Neustonic
Chironomidae,
larvae/pupae Feeding: Invertebrates, Epibenthic
Corophium salmonis Feeding: Invertebrates, Epibenthic
Corophium spinicorne Feeding: Invertebrates, Epibenthic
Corophium spp. Feeding: Invertebrates, Epibenthic
Daphnia spp. Feeding: Invertebrates, Pelagic
Diptera (unid.) Feeding: Invertebrates, Epibenthic
Ephydridae (unid.) Feeding: Invertebrates, Neustomc
Heleidae (unid.) Feeding: Invertebrates, Neustonic
Hemiptera (unid.) Feeding: Invertebrates, Epibenthic
Insecta (larvae) Feeding: Invertebrates, Epibenthic
Neomysis mercedis Feeding: Invertebrates, Epibenthic
-------
162
Emergent Marsh Habitat - cont.
Assemblage Attribute Function
chum salmon
Carex spp. Refuge/Physiology: Biological Complexity,
Emergent Vasc. Plants
Chironomidae (unid.) Feeding: Invertebrates, Neustonic
Chironomidae,
larvae/pupae Feeding: Invertebrates, Epibenthic
Corophium spinicome Feeding: Invertebrates, Epibenthic
Corophium spp. Feeding: Invertebrates, Epibenthic
Diptera (unid.) Feeding: Invertebrates, Epibenthic
Eogammarus
con fervicolus Feeding: Invertebrates, Epibenthic
epiphytic algae/animals Feeding: Plants, Micro Algae
Hemiptera (unid.) Feeding: Invertebrates, Epibenthic
Neomysis mercedis Feeding: Invertebrates, Epibenthic
cutthroat trout
Chironomidae (unid.) Feeding: Invertebrates, Neustonic
Eogammarus
confervicolus Feeding: Invertebrates, Epibenthic
Gasterosteus aculeatus Feeding: Vertebrates, Demersal
Neomysis mercedis Feeding: Invertebrates, Epibenthic
Oncorhynchus
gorbuscha (fry) Feeding: Vertebrates, Water Column
Oncorhynchus keta (fry) Feeding: Vertebrates, Water Column
prickly sculpin
Chironomidae,
larvae/pupae Feeding: Invertebrates, Epibenthic
Corophium salmonis Feeding: Invertebrates, Epibenthic
Gnorimosphaeroma
oregonese Feeding: Invertebrates, Epibenthic
Neomysis mercedis Feeding: Invertebrates, Epibenthic
-------
163
Emergent Marsh Habitat - cont.
Assemblage Attribute Function
Pacific staghorn sculpin
Chironomidae,
larvae/pupae Feeding: Invertebrates, Epibenthic
Corophium salmonis Feeding: Invertebrates, Epibenthic
Corophium spp. Feeding: Invertebrates, Epibenthic
Cumella vulgaris Feeding: Invertebrates, Epibenthic
Eogammarus
confervicolus Feeding: Invertebrates, Epibenthic
Gnorimosphaeroma
oregonese Feeding: Invertebrates, Epibenthic
Neanthes limnicola Feeding: Invertebrates, Benthic
Neomysis mercedis Feeding: Invertebrates, Epibenthic
Tanais spp. Feeding: Invertebrates, Benthic
threespine stickleback
Carex spp. Refuge/Physiology: Biological Complexity,
Emergent Vasc. Plants
Chironomidae,
larvae/pupae Feeding: Invertebrates, Epibenthic
Corophium salmonis Feeding: Invertebrates, Epibenthic
Corophium spp. Feeding: Invertebrates, Epibenthic
Eogammarus
confervicolus Feeding: Invertebrates, Epibenthic
Eogainmanis spp. Feeding: Invertebrates, Epibenthic
Insecta (larvae) Feeding: Invertebrates, Epibenthic
Oncorhynchus
gorbuscha (fry) Feeding: Vertebrates, Water Column
Oncorhynclius keta (fry) Feeding: Vertebrates, Water Column
-------
164
Emergent Marsh Habitat - cont.
Assemblage Attribute Function
Mammals
muskrat
Carer lyngbei Feeding: Plants, Emergent Vascular
Carer lyngbei (seeds) Feeding: Plants, Emergent Vascular
PhalarL arundinacea Feeding: Plants, Emergent Vascular
Scirpus americanus Reproduction: Substrate, Emergent Vasc.
Plants
Scirpus maritimus Feeding: Plants, Emergent Vascular
Scirpus validu.s (seeds) Feeding: Plants, Emergent Vascular
Sium suave Feeding: Plants, Emergent Vascular
Typha lazifolia Feeding: Plants, Emergent Vascular
Pacific harbor seal
Cottus spp. Feeding: Vertebrates, Demersal
Crangon spp. Feeding: Invertebrates, Epibenthic
Platichtlzys stellatus Feeding: Vertebrates, Demersal
raccoon
Ayes (unid.) Feeding: Vertebrates, Terrestrial
Cancer productus Feeding: Invertebrates, Epibenthic
Corbicula manilensis Feeding: Invertebrates, Benthic
CottzLs spp. Feeding: Vertebrates, Demersal
Crangon spp. Feeding: Invertebrates, Epibenthic
Engraulis mordar Feeding: Vertebrates, Water Column
Pacificastacus
leniu.sculus Feeding: Invertebrates, Epibenthic
Picea sitchensis Refuge/Physiology: Physical Complexity,
Vertical Relief
Platichthys stellatus Feeding: Vertebrates, Demersal
Salix spp. Refuge/Physiology: Physical Complexity,
Vertical Relief
Thaleic/zt/iys pacificus Feeding: Vertebrates, Water Column
-------
165
Emergent Marsh Habitat - cont.
Assemblage Attribute Function
Townsend vole
bentgrass/a.ster Feeding: Plants, Emergent Vascular
Carex Iyngbei Reproduction: Substrate, Emergent Vasc.
Plants
Carex lyngbei (seeds) Feeding: Plants, Emergent Vascular
Saticornia spp. Feeding: Plants, Emergent Vascular
Scirpu.s americanus Reproduction: Substrate, Emergent Vasc.
Plants
-------
166
Mudflat Habitat
Assemblage Attribute Function
Birds
bufflehead
Diptera (larvae) Feeding: Invertebrates, Epibenthic
Lepidogobius lepidus Feeding: Vertebrates, Demersal
Leptocottus armatus Feeding: Vertebrates, Demersal
Macoma spp. Feeding: Invertebrates, Benthic
Ostrea lurida Feeding: Invertebrates, Epibenthic
Tapes (Ruditapes)
p/zilipinarum Feeding: Invertebrates, Epibenthic
common goldeneye
Hemigrapsus spp. Feeding: Invertebrates, Epibenthic
Leptocottus armatus Feeding: Vertebrates, Demersal
Macoma spp. Feeding: Invertebrates, Benthic
Ostrea lurida Feeding: Invertebrates, Epibenthic
Tapes (Ruditapes)
p/zilipinarum Feeding: Invertebrates, Epibenthic
common snipe
Diptera (larvae) Feeding: Invertebrates, Epibenthic
Megalorcheitia
pugettensis Feeding: Invertebrates, Epibenthic
dunlin
Corop/iium salmonis Feeding: Invertebrates, Benthic
Corophium spp. Feeding: Invertebrates, Benthic
Diptera (larvae) Feeding: Invertebrates, Epibenthic
Eogammarus
confe vico1us Feeding: Invertebrates, Epibenthic
Eogainmarus spp. Feeding: Invertebrates, Epibenthic
Megalorchestia
pugettensis Feeding: Invertebrates, Epibenthic
-------
167
Mudflat Habitat (cont.)
Assemblage Attribute Function
great blue heron
Crangon Spp. Feeding: Invertebrates, Epibenthic
Engrcrulis mordw Feeding: Vertebrates, Water Column
Lepidogobius lepidus Feeding: Vertebrates, Demersal
Leptocottus annatu.s Feeding: Vertebrates, Demersaj
Oncorhynchus spp. (fry) Feeding: Vertebrates, Water Column
Platichthys stellatus Feeding: Vertebrates, Demersal
Pleuronichthys vetulu..s Feeding: Vertebrates, Demersal
least sandpiper
Corop/zium Spp. Feeding: Invertebrates, Benthic
western sandpiper
Diptera (larvae) Feeding: Invertebrates, Epibenthjc
Eogammarus
confervicolus Feeding: Invertebrates, Epibenthjc
Eohaustorj u .g
Was/zin , tonius Feeding: Invertebrates, Epibenthjc
Nematoda (unid.) Feeding: Invertebrates, Benthic
Pancolus californiensis Feeding: Invertebrates, Epibenthjc
Fishe
bay goby
I -f arpacticu.s uniremis Feeding: Invertebrates, Epibenthic
Tisbe Spp. Feeding: Invertebrates, Epibenthic
chum salmon -
Callianassa californjensjs
(larvae) Feeding: Invertebrates, Pelagic
Upogebia pugettensis
(larvae) Feeding: Invertebrates, Pelagic
-------
168
Mudilat Habitat (cont.)
Assemblage Attribute Function
English sole
Abarenicola pacifica Feeding: Invertebrates, Benthic
Archaeomysis grebnitzkii Feeding: Invertebrates, Epibenthic
Corophium salmonis Feeding: Invertebrates, Epibenthic
Corophium spp. Feeding: Invertebrates, Epibenthic
Cumella vulgaris Feeding: Invertebrates, Epibenthic
Eogammarus spp. Feeding: Invertebrates, Epibenthic
Macoma spp. Feeding: Invertebrates, Benthic
Pacific staghorn sculpin
Callianassa
califomien.sis Feeding: Invertebrates, Be nthic
Crangon spp. Feeding: Invertebrates, Epibenthic
Gasterosteus aculeatus Feeding: Vertebrates, Water Column
starry flounder
Atylus spp. Feeding: Invertebrates, Epibenthic
Corophium spp. Feeding: Invertebrates, Epibenthic
Cumella vulgaris Feeding: Invertebrates, Epibenthic
Invertebrates
Dungeness crab
Crangon spp. Feeding: Invertebrates, Epibenthic
Macoma spp. Feeding: Invertebrates, Benthic
Mammals
Pacific harbor seal
Cancer spp. Feeding: Invertebrates, Benthic
Crangon spp. Feeding: Invertebrates, Epibenthic
Platichthys stellatus Feeding: Vertebrates, Demersal
-------
169
Mudilat Habitat (cont.)
Assemblage Attribute Function
raccoon
Ayes (unid.) Feeding: Vertebrates, Terrestrial
Corbicula manilensis Feeding: Invertebrates, Benthic
Hemigrapsus spp. Feeding: Invertebrates, Epibenthic
Platichthys stellatus Feeding: Vertebrates, Demersal
-------
170
Sandflat Habitat
Assemblage Attribute Function
Birds
common goldeneye
Leptocottus annatus Feeding: Vertebrates, Demersal
dunlin
Corophium spp. Feeding: Invertebrates, Benthic
Eogammarus
confe vicolus Feeding: Invertebrates, Epibenthic
Oligochaeta (unid.) Feeding: Invertebrates, Benthic
Megalorchestia
pugettensis Feeding: Invertebrates, Epibenthic
Phoxocephalidae spp. Feeding: Invertebrates, Epibenthic
great blue heron
Citharic/zt/zys spp. Feeding: Vertebrates, Demersal
Cottidae (unid.) Feeding: Vertebrates, Water Column
Crangon spp. Feeding: Invertebrates, Epibenthic
Engraulis mordax Feeding: Vertebrates, Water Column
Leptocottu.s armatus Feeding: Vertebrates, Demersal
Plazic/zthys stellatus Feeding: Vertebrates, Demersal
horned grebe
Leptocottus armatus Feeding: Vertebrates, Demersal
Fishes
Pacific staghorn sculpin
Callianassidae (unid.) Feeding: Invertebrates, Benthic
Cancer magister Feeding: Invertebrates, Epibenthic
Crangon spp. Feeding: Invertebrates, Epibenthic
Cumella vulgaris Feeding: Invertebrates, Epibenthic
Mya arenaria Feeding: Invertebrates, Benthic
-------
171
SandfIat Habitat (cont.)
Assemblage Attribute Function
sand sole
Crangon spp. Feeding: Invertebrates, Epibenthic
Engraulis mordax Feeding: Vertebrates, Water Column
speckled sanddab
Callianassidae (unid.) Feeding: Invertebrates, Benthic
Invertebrates
Dungeness crab
Clinocardium nutalli Feeding: Invertebrates, Benthic
Crangon spp. Feeding: Invertebrates, Epibenthic
Marine Mammals
Gray whale
Callianassa
californiensis Feeding: Invertebrates, Benthic
-------
172
Gravel-Cobble Habitat
Assemblage Attribute Funcifon
Birds
American wigeon
Clupea harengu.s
pallasi (eggs) Feeding: Vertebrates, Demersal
bufflehead
Hemigrapsus Spp. Feeding: Invertebrates, Epibenthjc
black brant
Clupea Izarengus
pallasi (eggs) Feeding: Vertebrates, Demersal
black turnstone
Balanus spp. Feeding: Invertebrates, Epibenthic
Mytilus edulLs Feeding: Invertebrates, Epibenthjc
double-crested cormorant
Ammodytes hexapterus Feeding: Vertebrates, Demersal
Apodichthys flavidus Feeding: Vertebrates, Demersal
Cymatogaster aggregata Feeding: Vertebrates, Water Column
Gasterosteus aculeatus Feeding: Vertebrates, Demersal
Oncorhynchus spp. (fry) Feeding: Vertebrates, Water Column
P1w/is laeta Feeding: Vertebrates, Demersal
Platic/zt/zys stellatus Feeding: Vertebrates, Demersal
Sebastes caurinus Feeding: Vertebrates, Water Column
T/zaleichtlzys pacificus Feeding: Vertebrates, Water Colunm
-------
173
Gravel-Cobble Habitat (cont.)
Assemblage Attribute Function
horned grebe
Apodichthys flavidu.s Feeding: Vertebrates, Demersal
Ga.sterosteus aculeatus Feeding: Vertebrates, Water Column
Oncorhynchus spp. (fry) Feeding: Vertebrates, Water Column
Pholis laeta Feeding: Vertebrates, Demersal
Platichthys stellatus Feeding: Vertebrates, Demersal
Sebastes caurinus Feeding: Vertebrates, Water Column
mew gull
Clupea /zarengus
palla.si (eggs) Feeding: Vertebrates, Demersal
osprey
Gasterosteus aculeatu.s Feeding: Vertebrates, Water Column
Oncorhynclzus spp. (fiy) Feeding: Vertebrates, Water Column
Sebastes caurinu.s Feeding: Vertebrates, Water Column
western grebe
Clupea harE ngus pallasi Feeding: Vertebrates, Water Column
Cymatogaster aggregata Feeding: Vertebrates, Water Column
Platichthys stellatus Feeding: Vertebrates, Demersal
Thaleichthys pacificus Feeding: Vertebrates, Water Column
Fishes
buffalo sculpin
Uha spp. Feeding: Plants, Macro Algae
-------
174
Gravel-Cobble Habitat (cont.)
Assemblage Attribute Function
coho salmon
Ammodytes he,rapteruc Feeding: Vertebrates, Demersal
AnL ogwnmarus
pugettensis Feeding: Invertebrates, Epibenthic
Corophium spp. Feeding: Invertebrates, Epibenthic
Decapoda (larvae) Feeding: Invertebrates, Pelagic
Gnorimosphaeroma
oregonese Feeding: Invertebrates, Epibenthic
Neomysis mercedis Feeding: Invertebrates, Epibenthic
copper rockfish
Macrocystis pyrifera Refuge/Physiology: Biological Complexity,
Submergent Vasc. Plant
cutthroat trout
Ammodytes liexapterus Feeding: Vertebrates, Water Column
Clupea harengus pallasi Feeding: Vertebrates, Water Column
Corophium spp. Feeding: Invertebrates, Epibenthic
Crangon spp. Feeding: Invertebrates, Epibenthic
Cumella vulgaris Feeding: Invertebrates, Epibenthic
Decapoda (larvae) Feeding: Invertebrates, Pelagic
Gasterosteus aculeatus Feeding: Vertebrates, Demersal
Oncorhync/zus spp. (fiy) Feeding: Vertebrates, Water Column
dolly varden
Ammodytes hexapterus Feeding: Vertebrates, Water Column
Clupea harengus pallasi Feeding: Vertebrates, Water Column
Crangon spp. Feeding: Invertebrates, Epibenthic
Gasterosteus aculeatus Feeding: Vertebrates, Demersal
great sculpin
Crangon spp. Feeding: Invertebrates, Epibenthic
-------
175
Gravel-Cobble Habitat (cont.)
Assemblage Attribute Function
pile perch
Laminaria spp. Refuge/Physiology: Biological Complexity,
Macro Algae
Macrocystis pyrifera Refuge/Physiology: Biological Complexity,
Submergent Vasc. Plant
Ulva spp. Refuge/Physiology: Biological Complexity,
Macro Algae
padded sculpin
Hippolytidae (unid.) Feeding: Invertebrates, Epibenthic
Pacific tomcod
Corophium spp. Feeding: Invertebrates, Epibenthic
Crangon spp. Feeding: Invertebrates, Epibenthic
Eogammarus spp. Feeding: Invertebrates, Epibenthic
striped seaperch
Hemigrapsus nudis Feeding: Invertebrates, Epibenthic
starry flounder
Corophium spp. Feeding: Invertebrates, Epibenthic
Crangon spp. Feeding: Invertebrates, Epibenthic
Cumella vulgaris Feeding: Invertebrates, Epibenthic
Dendraster excentricus Feeding: Invertebrates, Benthic
Eogammarus spp. Feeding: Invertebrates, Epibenthic
Mya arenaria Feeding: Invertebrates, Benthic
Teiina nuculoides Feeding: Invertebrates, Benthic
-------
176
Gravel-Cobble Habitat (cont.)
Assemblage Attribute Function
whitespotted greenling
Ampithoe spp. Feeding: Invertebrates, Epibenthic
Cancer spp. Feeding: Invertebrates, Epibenthic
Eusiroides spp. Feeding: Invertebrates, Epibenthic
Heptacarpu. spp. Feeding: Invertebrates, Epibenthic
Hippolytidae (unid.) Feeding: Invertebrates, Epibenthic
Lwninaria spp. Refuge/Physiology: Biological Complexity,
Macro Algae
Pugettia gracilis Feeding: Invertebrates, Epibenthic
Viva spp. Refuge/Physiology: Biological Complexity,
Macro Algae
Invertebrates
Dungeness crab
Hemigrapsus spp. Feeding: Invertebrates, Epibenthic
red rock crab
Balanus spp. Feeding: Invertebrates, Epibenthic
Platic/zt/iys stellatus Feeding: Vertebrates, Demersal
Viva spp. Refuge/Physiology: Biological Complexity,
Macro Algae
Mammals
raccoon
Cancer magister Feeding: Invertebrates, Epibenthic
Corbicula manilensis Feeding: Invertebrates, Benthic
Nucella spp. Feeding: Invertebrates, Benthic
Pacificczstacus
leviusculu.s Feeding: Invertebrates, Epibenthic
-------
177
Eelgrass Habitat
Assemblage Attribute Function
Birds
bufflehead
Zostera japonica Feeding: Plants, Submergent Vascular
Zostera marina Feeding: Plants, Submergent Vascular
black brant
Clupea harengus
pallasi (eggs) Feeding: Vertebrates, Demersal
Spartina spp. Feeding: Plants, Emergent Vascular
Ulva spp. Feeding: Plants, Macro Algae
Zostera japonica Feeding: Plants, Submergent Vascular
Zosiera marina Feeding: Plants, Submergent Vascular
Canada goose
Zostera japonica Feeding: Plants, Submergent Vascular
Zostera marina Feeding: Plants, Submergent Vascular
Zostera spp. Feeding: Plants, Submergent Vascular
great blue heron
Clu pea harengus palkisi Feeding: Vertebrates, Water Column
Cymatogaster aggregata Feeding: Vertebrates, Water Column
Embiotocidae (unid.) Feeding: Vertebrates, Water Column
Leptocottus annatus Feeding: Vertebrates, Demersal
Platichihys stellatus Feeding: Vertebrates, Demersal
glaucous-winged gull
Ayes (unid.) Feeding: Vertebrates, Terrestrial
Clupea harengus pallasi Feeding: Vertebrates, Water Column
Tha!eichthys paciflcu.s Feeding: Vertebrates, Water Column
-------
178
Eelgrass Habitat (cont.)
Assemblage Attribute Function
osprey
Oncorhynchus spp. (fry) Feeding: Vertebrates, Water Column
Thoieichthys pacificus Feeding: Vertebrates, Water Column
western sandpiper
Eogammarus
confervicolus Feeding: Invertebrates, Epibenthic
Fishes
bay pipefish
epiphytic algae/animals Refuge/Physiology: Biological Complexity,
Macro Algae
Zostera spp. Refuge/Physiology: Biological Complexity,
Submergent Vasc. Plant
chum salmon
Corophium spp.
(males) Feeding: Invertebrates, Epibenthic
Cumella vulgaris Feeding: Invertebrates, Epibenthic
Eogammanis spp. Feeding: Invertebrates, Epibenthic
Harpacticus spp. Feeding: Invertebrates, Epibenthic
Harpacticus uniremis Feeding: Invertebrates, Epibenthic
Tisbe spp. Feeding: Invertebrates, Epibenthic
Zaus spp. Feeding: Invertebrates, Epibenthic
Zostera spp. Refuge/Physiology: Biological Complexity,
Submergent Vasc. Plant
crescent gunnel
Caprella laeviu.scula Feeding: Invertebrates, Epibenthic
epiphytic algae/animals Refuge/Physiology: Biological Complexity,
Macro Algae
Ischyrocerus spp. Feeding: Invertebrates, Epibenthic
-------
179
Eelgrass Habitat (corn.)
Assemblage Attribute Function
kelp perch
Cwnella vulgaris Feeding: Invertebrates, Epibenthic
Ulva spp. Refuge/Physiology: Biological Complexity,
Macro Algae
Zostera spp. Refuge/Physiology: Biological Complexity,
Submergent Vasc. Plant
penpoint gunnel
epiphytic algae/animals Refuge/Physiology: Biological Complexity,
Macro Algae
Harpacticus spinulosu.s Feeding: Invertebrates, Epibenthic
lichyrocerus spp. Feeding: Invertebrates, Epibenthic
shiner perch
Capitellidae (unid.) Feeding: Invertebrates, Benthic
Corophium spp. Feeding: Invertebrates, Benthic
Corophium spp.
(males) Feeding: Invertebrates, Epibenthic
Cumella vulgaris Feeding: Invertebrates, Epibenthic
Eogammarus spp. Feeding: Invertebrates, Epibenthic
Harpacticus spp. Feeding: Invertebrates, Epibenthic
Hippolytidae (umd.) Feeding: Invertebrates, Epibenthic
Ischyroceiw spp. Feeding: Invertebrates, Epibenthic
Pontogeneia rostrata Feeding: Invertebrates, Epibenthic
Tisbe spp. Feeding: Invertebrates, Epiberithic
Ulva spp. Refuge/Physiology: Biological Complexity,
Macro Algae
Zostera spp. Refuge/Physiology: Biological Complexity,
Submergent Vasc. Plant
-------
180
Eelgrass Habitat (cont.)
Assemblage Attribute Function
striped seaperch
Crangon spp. Feeding: Invertebrates, Epibenthic
Cumella vulgaris Feeding: Invertebrates, Epibenthic
Decapoda (larvae) Feeding: Invertebrates, Pelagic
Harpacticu.s spp. Feeding: Invertebrates, Epibenthic
Hemigrapsus nudis Feeding: Invertebrates, Epibenthic
Hippolytidae (unid.) Feeding: Invertebrates, Epibenthic
Ischyrocerus spp. Feeding: Invertebrates, Epibenthic
Ulva spp. Refuge/Physiology: Biological Complexity,
Macro Algae
Zosiera spp. Refuge/Physiology: Biological Complexhy,
Submergent Vasc. Plant
tube-snout
Alienacanthomysis
macropsis Feeding: Invertebrates, Epibenthic
Co ycaeus anglicu.s Feeding: Invertebrates, Pelagic
Harpacticus spinulosus Feeding: Invertebrates, Epibenthic
Paracalanus spp. Feeding: Invertebrates, Pelagic
Tisbe spp. Feeding: Invertebrates, Epibenthic
Zostera spp. Refuge/Physiology: Biological Complexity,
Submergent Vasc. Plant
-------
181
Eelgrass Habitat (cont.)
Assemblage Attribute
Invertebrates
Dungeness crab
Function
Callianassa
coiiforniensLs
Cancer mag’ister
Capitellidae (unid.)
Clupea harengus pallasi
Crangon spp.
Cryptomya californica
Embiotocidac (unid.)
Harpacticus spp.
Leptocottus armatu.s
Macoma spp.
Mya arena ia
Psettic/zt/zys
melanoslictus
Tel/ma spp.
Thaleichthys pacificus
Zostera spp.
Feeding: Invertebrates, Benthic
Feeding: Invertebrates, Epibenthic
Feeding: Invertebrates, Benthic
Feeding: Vertebrates, Water Column
Feeding: Invertebrates, Epibenthic
Feeding: Invertebrates, Benthic
Feeding: Vertebrates, Water Column
Feeding: Invertebrates, Epibenthic
Feeding: Vertebrates, Demersal
Feeding: Invertebrates, Benthic
Feeding: Invertebrates, Benthic
Feeding: Vertebrates, Demersal
Feeding: Invertebrates, Benthic
Feeding: Vertebrates, Water Column
Feeding: Plants, Subme rgent Vascular
Mammals
Pacific harbor seal
Cancer magister
Clupea Izarengu.s palla.si
Crangon spp.
Lumpenus sagitta
Poric/ztlzys notatu.s
Thaleichthys pacificus
Feeding: Invertebrates, Epibenthic
Feeding: Vertebrates, Water Column
Feeding: Invertebrates, Epibenthic
Feeding: Vertebrates, Demersal
Feeding: Vertebrates, Demersal
Feeding: Vertebrates, Water Column
-------
182
Nearshore Subtidal Soft Bottom Habitat
Assemblage Attribute Function
Fishes
Pacific cod
Clupea harengus pallasi Feeding: Vertebrates, Water Column
Decapoda (larvae) Feeding: Invertebrates, Pelagic
NeomysLs mercedis Feeding: Invertebrates, Epibenthic
Pacific tomcod
Crangon spp. Feeding: Invertebrates, Epibenthjc
Neomysis mercedis Feeding: Invertebrates, Epibenthjc
ratfish
Hemigrapsus spp. Feeding: Invertebrates, Epibenthic
Yoldia Spp. Feeding: Invertebrates, Benthic
sturgeon poacher
Crangon spp. Feeding: Invertebrates, Epibenthic
walleye pollock
Clupea harengus pallasi Feeding: Vertebrates, Water Column
Decapoda (larvae) Feeding: Invertebrates, Pelagic
-------
183
Nearshore Subtidal Soft Bottom Habitat (cont.)
Assemblage Attribute Function
Invertebrates
Dungeness crab
Ammodytes hexapterus Feeding: Vertebrates, Demersal
Ca1liana ga
californiensis Feeding: Invertebrates, Benthic
Clinocardium nutalli Feeding: Invertebrates, Benthic
Clupea harengus palltzsi Feeding: Vertebrates, Water Column
Crangon spp. Feeding: Invertebrates, Epibenthic
Leptocottus wmatu.s Feeding: Vertebrates, Demersal
Macoma spp. Feeding: Invertebrates, Benthic
Microgadus proximus Feeding: Vertebrates, Demersal
Mya arenaiia Feeding: Invertebrates, Benthic
Tellina spp. Feeding: Invertebrates, Benthic
Thaleichthys pacificus Feeding: Vertebrates, Water Column
Veneropsis japonica Feeding: Invertebrates, Be nthic
Mammals
gray whale
Ampelisca agassizi Feeding: Invertebrates, Benthic
Ampelisca careyi Feeding: Invertebrates, Benthic
Orchomene minuta Feeding: Invertebrates, Benthic
Photi.s lacia Feeding: Invertebrates, Benthic
Protomedeia penates Feeding: Invertebrates, Benthic
-------
184
Nearshore Subtidal Hard Substrate
Assemblage Attribute Function
Fishes
black rockfish
Eua!us spp. Feeding: Invertebrates, Epibenthic
Hep:acarpu.s spp. Feeding: Invertebrates, Epibenthic
Lebbeus spp. Feeding: Invertebrates, Epibenthic
Spirontocaris spp. Feeding: Invertebrates, Epibenthic
brown rocklish
Eua!us spp. Feeding: Invertebrates, Epibenthic
Heptacarpus spp. Feeding: Invertebrates, Epibenthic
Lebbeus spp. Feeding: Invertebrates, Epibenthic
SpirontocarL spp. Feeding: Invertebrates, Epibenthic
copper rockfish
Cancer spp. (zoea) Feeding: Invertebrates, Pelagic
Eualu.s spp. Feeding: Invertebrates, Epibenthic
Heptacarpus spp. Feeding: Invertebrates, Epibenthic
Lebbeus spp. Feeding: Invertebrates, Epibenthic
Pandalus danae Feeding: Invertebrates, Epibenthic
Phanerodon furcatus Feeding: Vertebrates, Water Column
Spirontocaris spp. Feeding: Invertebrates, Epibenthic
kelp greenling
Eualu..s spp. Feeding: Invertebrates, Epibenthic
Heptacarpu.s spp. Feeding: Invertebrates, Epibenthic
Lebbeus spp. Feeding: Invertebrates, Epibenthic
Spirontocaris spp. Feeding: Invertebrates, Epibenthic
lingcod
Ammodytes hexapterus Feeding: Vertebrates, Water Column
Clupea harengus pallasi Feeding: Vertebrates, Water Column
Phanerodon fisrcatus Feeding: Vertebrates, Water Column
-------
185
Nearshore Subtidal Hard Substrate (cont.)
Assemblage Attribute Function
pile perch
Ba/anus crenatus Feeding: Invertebrates, Epibenthic
Ba/anus glandula Feeding: Invertebrates, Epibenthic
Transennella tantilla Feeding: Invertebrates, Benthic
quiliback rockfish
Cancer spp. (zoea) Feeding: Invertebrates, Pelagic
Eualus spp. Feeding: Invertebrates, Epibenthic
Heptacarpu.s spp. Feeding: Invertebrates, Epibenthic
Lebbeus spp. Feeding: Invertebrates, Epibenthic
Panda/us danae Feeding: Invertebrates, Epibenthic
Spirontocaris spp. Feeding: Invertebrates, Epibenthic
striped seaperch
Cancer spp. (zoea) Feeding: Invertebrates, Pelagic
-------
186
Water Column
Assemblage Attribute Function
Birds
common merganser
Clupea harengus pallasi Feeding: Vertebrates, Water Column
Cymazogaster aggregaza Feeding: Vertebrates, Water Column
Gasterosteus aculeatus Feeding: Vertebrates, Water Column
Oncorhynchus spp. (fry) Feeding: Vertebrates, Water Column
Thaleichthys pacificus Feeding: Vertebrates, Water Column
double-crested cormorant
Cymazogaster aggregata Feeding: Vertebrates, Water Column
Thaleichthys pacificus Feeding: Vertebrates, Water Column
mew gull
Cancer spp. (megalops) Feeding: Invertebrates, Pelagic
osprey
Tlzaleichthys pacificus Feeding: Vertebrates, Water Column
red-breasted merganser
Gasterosteus aculeatus Feeding: Vertebrates, Water Column
Oncorhynchus spp. (fry) Feeding: Vertebrates, Water Column
western grebe
Clupea harengus paiiasi Feeding: Vertebrates, Water Column
Cymatogaster aggregata Feeding: Vertebrates, Water Column
-------
187
Water Column (cont.)
Assemblage Attribute Function
Fishes
coho salmon
Ammodytes haapterus Feeding: Vertebrates, Water Column
Ca11iana sa californienszs
(larvae) Feeding: Invertebrates, Pelagic
Cancer spp. (larvae) Feeding: Invertebrates, Neustonic
Clupea harengus pallasi Feeding: Vertebrates, Water Column
Corophium spp. Feeding: Invertebrates, Epibenthic
Engraulis mordax Feeding: Vertebrates, Water Column
Epilabidocera
amphit rites Feeding: Invertebrates, Neustortic
Euphausia pacifica Feeding: Invertebrates, Pelagic
Ewytemora affinis Feeding: Invertebrates, Pelagic
Hypomesus pretiosus Feeding: Vertebrates, Water Column
Insecta (drift) Feeding: Invertebrates, Neustonic
Oncorhynchus
gorbuscha (fry) Feeding: Vertebrates, Water Column
Oncorhynchus keta (fry) Feeding: Vertebrates, Water Column
Teleostei (larvae) Feeding: Vertebrates, Water Column
chinook salmon
Ammodytes hexapteius Feeding: Vertebrates, Water Column
Callianassa califomiensis
(larvae) Feeding: Invertebrates, Pelagic
Clupea harengus pallasi Feeding: Vertebrates, Water Column
Corophium spp. Feeding: Invertebrates, Epibenthic
Daphnia spp. Feeding: Invertebrates, Pelagic
Decapoda (larvae) Feeding: Invertebrates, Pelagic
Euphausia pacifica Feeding: Invertebrates, Pelagic
Oncorhynchus
gorbuscha (fry) Feeding: Vertebrates, Water Column
Oncorhynchu.s keta (fry) Feeding: Vertebrates, Water Column
Teleostei (larvae) Feeding: Vertebrates, Water Column
-------
188
Water Column (cont.)
Assemblage Attribute Function
chum salmon
Acartia clawi Feeding: Invertebrates, Pelagic
Callianassa californiensis
(larvae) Feeding: Invertebrates, Pelagic
Cancer spp. (larvae) Feeding: Invertebrates, Neustonic
Corophiwn spp. Feeding: Invertebrates, Epibenthic
Corycaeu.s anglicus Feeding: Invertebrates, Pelagic
Corycaeus spp. Feeding: Invertebrates, Pelagic
Daphnia spp. Feeding: Invertebrates, Pelagic
Decapoda (larvae) Feeding: Invertebrates, Pelagic
Epilabidocera
amphit rites Feeding: Invertebrates, Neustonic
Epilabidocera spp. Feeding: Invertebrates, Neustonic
Euphausia pacifica Feeding: Invertebrates, Pelagic
Insecta (larvae) Feeding: Invertebrates, Pelagic
Oikopleura spp. Feeding: Invertebrates, Pelagic
Parathemisto pacifica Feeding: Invertebrates, Pelagic
longfin smelt
Acartia clausi Feeding: Invertebrates, Pelagic
Corophium spp. Feeding: Invertebrates, Epibenthic
Eogammarus spp. Feeding: Invertebrates, Epibenthic
northern anchovy
Acarlia californiensis Feeding: Invertebrates, Pelagic
Acartia clausi Feeding: Invertebrates, Pelagic
Corycaeus anglicus Feeding: Invertebrates, Pelagic
Eurvremora affinis Feeding: Invertebrates, Pelagic
Pacific herring
Acania clausi Feeding: Invertebrates, Pelagic
Corycaeus anglicus Feeding: Invertebrates, Pelagic
Daphnia spp. Feeding: Invertebrates, Pelagic
Decapoda (larvae) Feeding: Invertebrates, Pelagic
Inseçta (larvae) Feeding: Invertebrates, Pelagic
-------
189
Water Column (cant.)
Assemblage Attribute Function
pink salmon
Acartia clausi Feeding: Invertebrates, Pelagic
Callianassa californiensis
(larvae) Feeding: Invertebrates, Pelagic
Clupea harengus pallasi Feeding: Vertebrates, Water Column
Euphausia pacifica Feeding: Invertebrates, Pelagic
Insecta (larvae) Feeding: Invertebrates, Pelagic
Oikopleura spp. Feeding: Invertebrates, Pelagic
Oithona simili.s Feeding: Invertebrates, Pelagic
Parathemisto pacifica Feeding: Invertebrates, Pelagic
Pseudoca!anu.s minutus Feeding: Invertebrates, Pelagic
river lamprey
Clupea harengus pallasi Feeding: Vertebrates, Water Column
surf smelt
Acartia californiensis Feeding: Invertebrates, Pelagic
Acartia clausi Feeding: Invertebrates, Pelagic
Daphnia spp. Feeding: Invertebrates, Pelagic
Decapoda (larvae) Feeding: Invertebrates, Pelagic
Ewytemora affinis Feeding: Invertebrates, Pelagic
Insecta (1ar ae) Feeding: Invertebrates, Pelagic
Oikopleura spp. Feeding: Invertebrates, Pelagic
steelhead (rainbow) trout
Ammodytes hexapterus Feeding: Vertebrates, Water Column
Callianassa ca!ifornien.sis
(larvae) Feeding: Invertebrates, Pelagic
Clupea harengus pallasi Feeding: Vertebrates, Water Column
Corophiunz spp. Feeding: Invertebrates, Epibenthic
Decapoda (larvae) Feeding: Invertebrates, Pelagic
Scoloidea (unid.) Feeding; Invertebrates, Neustonic
-------
190
Water Column (cont.)
Assemblage Attribute Function
western brook lamprey
Clupea harengu.s palla.si Feeding: Vertebrates, Water Column
Mammals
Pacific harbor seal
Ammodyzes herapterus Feeding: Vertebrates, Water Column
Cancer magister Feeding: Invertebrates, Epibenthic
Clupea harengus pallasi Feeding: Vertebrates, Water Column
Crangon franciscorum Feeding: Invertebrates, Epibe nihic
Cymatogaster aggregata Feeding: Vertebrates, Water Column
Engraulis mordax Feeding: Vertebrates, Water Column
Gadus macrocephalus Feeding: Vertebrates, Demersal
Lampetra tridentatus Feeding: Vertebrates, Water Column
Leptocottus armatus Feeding: Vertebrates, Demersal
Loligo opalescen.s Feeding: Invertebrates, Pelagic
Lumpenu.s sagitta Feeding: Vertebrates, Demersal
Lycodopsis pacifica Feeding: Vertebrates, Water Column
Merluccius productus Feeding: Vertebrates, Water Column
Microgadus proximus Feeding: Vertebrates, Demersal
P1euronecte (Paroplzrys)
vetulus Feeding: Vertebrates, Water Column
Platichthys stellatus Feeding: Vertebrates, Demersal
Pleuronectidea (unid.) Feeding: Vertebrates, Demersal
Porichthys noratus Feeding: Vertebrates, Demersal
Spirinchus thaleicht/zys Feeding: Vertebrates, Water Column
Thaleichthys pacificus Feeding: Vertebrates, Water Column
Theragra chalcogramma Feeding: Vertebrates, Demersal
-------
191
Water Column (corn.)
Assemblage Attribute Function
northern sea lion
Chspea harengus pallasi Feeding: Vertebrates, Water Column
Cottidae (unid.) Feeding: Vertebrates, Water Column
Gadus macrocephalus Feeding: Vertebrates, Demersal
Gonatidae (unid.) Feeding: Vertebrates, Water Column
MaIlolus villosus Feeding: Vertebrates, Water Column
Merluccius productus Feeding: Vertebrates, Water Column
Octopus spp. Feeding: Invertebrates, Pelagic
Oncorhynchus spp. Feeding: Vertebrates, Water Column
Pleuronectidea (u nid.) Feeding: Vertebrates, De mersal
Scorpaenidae (unid.) Feeding: Vertebrates, Water Column
Seba.stes spp. Feeding: Vertebrates, Water Column
Theragra chalcogrwnma Feeding: Vertebrates, Demersal
-------
192
APPENDIX C: Physicochemical attributes identified in Protocol as important to fish
and wildlife utilization of estuarine habitats.
Parameter Attributes Function Assemblage Species
(1) Bathymetry/ (a) physical complexity, (i) refuge! buffalo sculpin
topography bathymetric features physiology chinook salmon
chum salmon
coho salmon
copper rockflsh
cutthroat trout
Dolly Varden
great sculpin
padded sculpin
rock sole
starry flounder
surf smelt
American coot
bufflehead
black brant
Canada goose
common goldeneye
double-crested
cormorant
great blue heron
greater yellowlegs
Pacific harbor seal
(b) physical complexity- (1) refuge/ chinook salmon
horizontal edges physiology chum salmon
coho salmon
English sole
starry flounder
threespine stickleback
American coot
common snipe
great blue heron
green-winged teal
mallard
Pacific harbor seal
(c) physical complexity- (1) refuge/physiology cutthroat trout
verical relief chum salmon
Dolly varden
English sole
-------
193
shiner perch
starry flounder
threespine stickleback
black brant
bufflehead
Canada goose
common goldeneye
common snipe
double-crested
cormorant
dunlin
gadwal
glaucous-winged gull
great blue heron
greater yellowlegs
green-winged teal
least sandpiper
mallard
mew gull
osprey
Pacific sta Jiom sailpin
red-winged blackbird
rock sole
short-billed dowitcher
song sparrow
spotted sandpiper
western sandpiper
northern sea lion
Pacific harbor seal
Townsend vole
(d) elevation-riparian (i) reproduction American coot
American goldfinch
American wigeon
Canada goose
common snipe
dark-eyed junco
gadwall
great blue heron
green-winged teal
mallard
merlin
northern oriole
osprey
red-tailed hawk
savannah sparrow
song sparrow
-------
194
muskrat
raccoon
(e) elevation-intertidal (i) reproduction Pacific herring
surf smelt
American wigeon
(f) elevation-subtidal (i) reproduction Dungeness crab
copper rockfish
English sole
Pacific cod
Pacific herring
Pacific staghom sailpin
Pacific tomcod
pile perch
starry flounder
threespine stickleback
whitespotted greenling
(2) Water and (a) general (1) feeding red rock crab
sediment
character chinook salmon
and quality chum salmon
coho salmon
C-O sole
cutthroat trout
Dolly Varden
Dover sole
hybrid sole
Pacific cod
Pacific sanddab
Pacific tomcod
pink salmon
raffish
rock sole
rough sculpin
sand sole
speckled sanddab
starry flounder
steelhead (rainbow)
trout
sturgeon poacher
-------
195
surf smelt
threespine stickleback
walleye pollock
American wigeon
black brant
bufflehead
Canada goose
common goldeneye
common mergariser
common snipe
double-crested
cormorant
dunlin
gadwall
glacous-winged gull
great blue heron
greater yellowlegs
green-winged teal
horned grebe
least sandpiper
mallard
mew gull
osprey
short-billed dowitcher
spotted sandpiper
red-breasted merganser
western grebe
western sandpiper
northern sea lion
Pacific harbor seal
(ii) refuge/physiology chinook salmon
chum salmon
coho salmon
C-O sole
cutthroat trout
Dolly Varden
Dover sole
hybrid sole
Pacific cod
Pacific sanddab
Pacific tomcod
pink salmon
raffish
rough sculpin
sand sole
speckled sanddab
-------
196
steelhead (rainbow)
trout
sturgeon poacher
surf smelt
threespine stickleback
walleye pollock
American wigeon
black brant
bufflehead
Canada goose
common goldeneye
common merganser
common snipe
dunlin
gadwall
glaucous-winged gull
greater yellowlegs
green-winged teal
horned grebe
least sandpiper
mallard
mew gull
osprey
red-breasted merganser
short-billed dowitcher
spotted sandpiper
western grebe
western sandpiper
northern sea lion
Pacific harbor seal
(iii) reproduction Dungeness crab
copper rockfish
Pacific herring
prickly sculpin
surf smelt
dunlin
greater lellowlegs
least sandpiper
spotted sandpiper
western sandpiper
(b) sediment size (i) feeding black brant
structure (gravel)
-------
197
(c) sediment organics (i) feeding Dungeness crab
(detritus)
chum salmon
mew gull
(d) salinity (i) feeding Dungeness crab
chinook salmon
chum salmon
C-O sole
coho salmon
copper rockfish
cutthroat trout
Dover sole
English sole
hybrid sole
mountain whitefish
northern squawfish
Pacific cod
ratfish
sand sole
surf smelt
threespine stickieback
walleye pollock
(ii) refuge/physiology chinook salmon
chum salmon
coho salmon
cutthroat trout
kelp perch
northern squawfish
Pacific cod
Pacific herring
Pacific sand lance
Pacific staghom sa 1pin
pink salmon
shiner perch
striped seaperch
surf smelt
(iii) reproduction Dungeness crab
Pacific herring
Pacific tomcod
raffish
starry flounder
surf smelt
walleye pollock
-------
198
(e) temperature (i) feeding chinook salmon
chum salmon
coho salmon
cutthroat trout
Dolly Varden
English sole
pink salmon
steelhead (rainbow)
trout
surf smelt
threespine stickleback
(ii) refuge/physiology chinook salmon
chum salmon
coho salmon
cutthroat trout
pink salmon
steelhead (rainbow)
trout
surf smelt
(iii) reproduction starry flounder
(1) turbidity (1) feeding chinook salmon
chum salmon
coho salmon
cutthroat trout
Dolly Varden
Pacific cod
Pacific sanddab
Pacific tomcod
pink salmon
ratfish
sand sole
speckled sanddab
steelhead (rainbow)
trout
sturgeon poacher
surf smelt
walleye pollock
black brant
bufflehead
common goldeneye
common merganser
double-crested
cormorant
gadwall
great blue heron
-------
199
greater yellowlegs
horned grebe
mew gull
osprey
red-breasted mei anser
western grebe
Pacific harbor seal
raccoon
(ii) refuge/physiology chinook salmon
chum salmon
coho salmon
cutthroat trout
Dolly Varden
Pacific cod
Pacific tomcod
pink salmon
steelhead (rainbow)
trout
surf smelt
threespine stickleback
walleye pollock
great blue heron
greater yellowlegs
(3) Disturbance (a) sound/pressure (i) feeding chinook salmon
chum salmon
cutthroat trout
American goldfinch
American wigeon
black brant
buffle head
Canada goose
common snipe
dark-eyed junco
dunlin
gadwall
great blue heron
greater yellowlegs
gree n-winged teal
least sandpiper
merlin
osprey
red-tailed hawk
savannah sparrow
-------
200
short-billed dowitcher
song sparrow
spotted sandpiper
western sandpiper
muskrat
Pacific harbor seal
raccoon
Townsend vole
(ii) refuge/physiology chinook salmon
chum salmon
coho salmon
cutthroat trout
American wigeon
black brant
Canada goose
common goldeney
common snipe
dunlin
gadwall
great blue heron
greater yellowlegs
least sandpiper
mallard
red-tailed hawk
short-billed dowitcher
spotted sandpiper
western sandpiper
Pacific harbor seal
(iii) reproduction American wigeon
Canada goose
common snipe
gadwall
great blue heron
green-winged teal
mallard
merlin
red-tailed hawk
short-billed dowitcher
Pacific harbor seal
(b) light (1) feeding chinook salmon
chum salmon
cutthroat trout
-------
201
black brant
(4) Water (a) general (1) refuge/physiology river lamprey
movement Western brook lamprey
------- |