Introduction
For several decades, ecologists and scientists alike have been working toward developing
and improving scientifically defensible riparian and wetland assessments (Stevenson 2002).
These assessment tools provide a definitive procedure for evaluating the complex ecological
condition of an ecosystem using a finite set of observable field indicators. They are aimed to be
robust, economical, easily applied, and provide adequate information to guide management and
regulatory decisions. The selection of assessment methods depends upon the objectives,
geographic area, wetland type, desired level of detail, and availability of applicable models.
More importantly, the results of assessments can be translated into restoration activities along
with monitoring protocols (Kleindl et al 2009).
The term restoration is used in different ways; however, it can be defined as,
“reestablishment of the structure, functions and natural diversity of an area that has been altered
from its natural state.” (Pess et al. 2003). In ecological restoration, the structure and function
are considered attributes of the whole ecosystem. Structure refers to the geomorphology,
hydrology, soil , water quality, and vegetation. Functions might refer to detaining flows,
groundwater storage and recharge, filtering pollutants, food web, plant succession, and diversity
of aquatic habitats. Many restoration efforts across the U.S. have experienced shortcomings
because the broader scales necessary to understand the complexity and dynamic nature of
ecosystems and their attributes were not considered (Beechie 2008, Poff).
The dynamics of ecosystems can be observed at a variety of scale and demonstrated by
interactions among individual organisms and transfer of energy. If restoration aims to reestablish
the functions and systems then recapturing the dynamics of the systems maybe dependent on
ensuring that appropriate processes are returned. Methods that assess condition are based on
physical and biological structural attributes with the goal of documenting deviation from the
reference standard condition. (Brinson et al. 1996 ). If an assessment method is used to measure
the connectivity between a stream channel and its floodplain, then the measurement is used to
understand the magnitude and occurrence of hydrologic processes that produce temporary water
storage on the floodplain.
This paper sets out to examine assessment techniques of wetland and riparian systems
and its role in systemically gathering information for achieving improved management decisions
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and effective restoration strategies. Approaches include hydrogeomorphic functional
assessments, quantitative biological methods, as well as semi-quantitative rapid assessment
methods will be discussed (Sutula). An overview of existing rapid assessment methods (RAMs)
and technical considerations that have been developed for use in state and tribal programs will be
provided. Although most of the literature reviewed are specific to wetland ecosystems they are
applicable to floodplain and riparian systems Post-restoration techniques including monitoring
and adaptive management will also be discussed.
Scales of Assessment
Although assessment methods vary in quantitative detail of the data collection, the level
of scale at which assessments are performed has considerable effects on the resolution of the
results. The ability to accurately assess ecological function is complicated by the fact that
wetlands vary in type, in time and in space, which directly influences their functional ability.
Numerous assessment techniques have been implemented on a variety of spatial scales (Sutula et
al. 2006) (Figure 1). Classification is one way of reducing the effect of natural variation on
assessment output so the assessment tool can better discriminate either functional capacity or
condition (Brinson). Classification can be based on a combination of physical, chemical, and/or
biological attributes of a wetland. For example, both riverine wetlands and depressional wetlands
provide habitat support functions; however, the structure of these wetland types and how those
functions are performed, and therefore scaled, differs distinctly.
Current methods vary in intensity and scale, ranging from broad to rapid field methods to
intensive and biological and chemical measures. Assessments conducted on a regional-scale tend
to generate coarser results since it does not develop the assessment models necessary to be
applied rapidly while be sensitive enough to detect changes in function at the appropriate level of
resolution (Kleindl et al. 2009).
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Recognizing the spatial extent of the assessment is important to establish as wetland
ecosystems exhibit distinct characteristics, such as relatively long periods of inundation,
hydrophytic vegetation, and hydric soils. Although wetlands share these characteristics, they also
perform on a wide range of geologic, climate, and physiographic situations (Brinson 1996). This
variability poses a challenge to developing assessment methods that are practical for end users to
conduct in a short period of time and accurate in that the method can detect significant changes
in function.
Referencing condition
Assessment method should incorporate a reference site. The reference site provides a
benchmarks against which assessment scores for specific wetlands can be compared. The
reference site should also include a the range of variation in condition across a gradient of
disturbance from most disturbed to least disturbed (Brinson 1996).
Assessment endpoints
Some methods are developed to assess function. Function is defined as an ecological
process occurring over time or more simply, “the processes that wetlands do.” (Smith et al 1995).
Identifying function requires repeated measures that quantify rates of processes over time. There
is a distinction between methods that assess condition versus those that measure functional
capacity such as the hydrogeomorphic condition. Functional capacity assessment often focus on
the capacity to perform individual functions and provide more specific detailed information,
while the condition-based assessments produces a general evaluation that combines multiple
functions and provides the overall ecological health of a system based on the combined scores.
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The type of approach should be clearly defined and based on management questions being
investigated (Brinson 1996; Stevens et al).
Rapid Assessment Methods
Alarmed by the diminishing water quality of the nation's streams and lakes, as well as the
degradation of wetlands and the valuable benefits they provide, the Federal Water Pollution
Control Act of 1972 was enacted. This legislation later became the Clean Water Act (CWA) and
included requirements to improve water quality and specific limitations on the development of
wetlands. Through this act, wetlands turned out to be the only land type to be regulated on both
private and public lands within the United States (EPA 2004). In 2008, the Environmental
Protection Agency and Army Corp of Engineers released a rule that advocated the use of
condition or functional assessment in mitigation monitoring and performance evaluation. With
that ruling came the need for rapid assessments that would assess wetland function (Cole 2006).
Rapid assessment methods (RAMs) are dynamic tools that can serve many purposes,
including: to assess the ecological condition or integrity of wetlands to document the extent of
degradation; to provide early warning of ecosystem stress or degradation; to determine the
effectiveness of management actions; and track wetland condition for regulatory programs
charged with wetland management, restoration, and mitigation . The National Water Quality
Inventory reported that only 4% of the U.S. wetlands have been monitored which leaves
insufficient data to evaluate the health of wetlands or to quantify the extent to which they are
degraded (EPA 2004).
Increased requirements for project specific monitoring and a growing need to evaluate
the performance of wetland protection programs are compelling state and federal agencies to
develop fairly rapid, cost effective indices commonly known as RAMs. The intent of all RAMs
is to evaluate the complex ecological condition of wetlands using a fixed set of observable field
indicators, such as plant community and structure, hydrology, physical structure, and buffers
(Kleindl et al. 2009). Condition describes the health of a wetland or “the state of a resource,
generally reflecting a combination of physical, chemical, and biological characteristics such as
temperature, water clarity, chemical composition, or the status of biological communities (U.S.
EPA 2004).
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Overview of Select RAMs
There are range of RAM guidebooks and field manuals that have been developed for use
by tribal and state programs. States including California, Maryland, and New Mexico have made
initiatives to develop new assessment methods or modified existing wetland and riparian
assessment methods to suit their specific physiographic area. In spite of their varying
physiographic area, each RAM considered how to define the assessment area when in the field,
how to integrate different wetland types into the application of the method, how scoring is
organized, whether or not certain wetland types or functions should be recognized for their value
or the ecosystem services they provide, regardless of condition; and, the need for verification
with comprehensive ecological data (Brinson 1996). This section provides an overview of
selected rapid assessment methods developed for restoration measures.
Hydrgeomorphic (HGM)
The HGM is one of the most common approaches of functional assessment that was
developed by the Army Corp of Engineers to assess functions of aquatic systems that have been
disturbed by a wide range of land use practices (Stevenson et al. 2002). It was initially designed
to facilitate the Clean Water Act Section 404 permitting program to consider alternatives,
minimize impacts, assess unavoidable project impacts, determine mitigation requirements, and
monitor the success of the mitigation projects. However, a variety of other potential applications
for the HGM approach have been identified, including determining minimal effects under the
Food Security Act, designing mitigation projects, managing wetlands, as well as restoration
prioritization, implementation, and monitoring (Brinson 1996 ).
Though the HGM was developed specifically for riverine wetlands (a class of wetland
that embodies a floodplain or riparian geomorphic regime) the approach is adaptable to many
regions and allows aggregation of wetlands that are functionally similar. (Brinson 1995). The
HGM method assumes rivers and floodplains to be integral components of the riverine wetland
ecosystem as in the Jicarilla Apache Functional Rapid Assessment.
The HGM functional assessments classify wetlands into specific hydrogeomorphic
classes (e.g., depressional wetlands in the northern Great Plains). This classification is followed
by characterization of functions and a compared to the expected function for a least disturbed
wetland of the same class (Brinson 1996). Functions may include nutrient cycling, groundwater
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or surface water storage, and maintaining aquatic food webs. Each function is characterized by
attributes that are can be measured by the degree to which is occurs and responds to
anthropogenic disturbances. Attributes are referenced as “variables” and respond to impact. A
model is developed for each function and calibrated. Wetlands in the calibration dataset are of
the same HGM class, and range from least to most disturbed (Kleindl et al. 2009). …(this section
not complete)
Index of Biological Integrity (IBI)
Since the passage of the 1972 Clean Water Act, the U.S. EPA developed water quality
guidelines to protect its biological integrity. Most of these criteria were based on toxicity tests
with little ground truthing of the success of pollution mitigation strategies. As such, the IBI
approach to bioassessment was developed to meet water quality and biocriteria requirements
specified in Sections 303, 304, 305(b), and 319 of the CWA (Rich 2002).
Karr introduced a usable approach for quantitatively assessing biological integrity
(Stevenson et al 2002). Biotic integrity has been defined as the ability of an area to maintain and
support a balanced, integrated, adaptive community of organisms, diversity and functional
organization comparable to that of natural habitat in that region (Karr and Dudley 1981). The
IBI serves as a tool that promotes assessments based on multiple factors such as sampling fish
and various attributes of sampled fish assemblages in an assessed habitat. Karr’s IBI assessment
identified various attributes (now known as metrics) including total number of species,
proportion of individuals in varying trophic levels, quantity of pollution-sensitive tax, which are
all examples of structural characteristics that vary with the level of anthropogenic impact
(Stevenson 2002) .
Jicarilla Rapid Assessment of Functions (JRAF): A case study
The JRAF was developed for the Jicarilla Apache Nation (New Mexico) to develop
protocols for assessing the functions of riverine floodplains in the Navajo Rive with broader
application to the nearby Rio Grande and Colorado Headwater River systems. The study was
conducted in the framework of the CWA Section 404 program. Additionally, the JRAF was
designed to support the prioritization of riparian areas for restoration, enhancement, preservation,
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and land management efforts; provide baseline data for land management opportunities; and
serve as a tool for the tribe’s long-term monitoring program (Kleindl et al. 2009).
The format of the JRAF employed a simplified model of the HGM approach to functional
assessment of wetlands. It identified wetlands using the following HGM-based criteria that
govern the functions of wetlands: geomorphic setting (the landform and position of wetland in
the landscape), hydrodynamics (energy and direction at which water flows in the wetland), and
water source (primary source of water in the wetlands such as floodwater or groundwater).
There is less emphasis on data collection and analysis and more emphasis on rapid assessments
using the best professional of the end users (Kleindl et al. 2009).
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