Transactions of the American Fisheries Society 136:718–735, 2007
Ó Copyright by the American Fisheries Society 2007
DOI: 10.1577/T06-128.1
[Article]
A Structured Approach for Developing Indices of Biotic Integrity:
Three Examples from Streams and Rivers in the Western USA
THOMAS R. WHITTIER*
AND
ROBERT M. HUGHES
Department of Fisheries and Wildlife, Oregon State University, 200 Southwest 35th Street,
Corvallis, Oregon 97333, USA
JOHN L. STODDARD
U.S. Environmental Protection Agency, National Health and Environmental Effects Research Laboratory,
Western Ecology Division, 200 Southwest 35th Street, Corvallis, Oregon 97333, USA
GREGG A. LOMNICKY
Dynamac Corporation, 200 Southwest 35th Street, Corvallis, Oregon 97333, USA
DAVID V. PECK
U.S. Environmental Protection Agency, National Health and Environmental Effects Research Laboratory,
Western Ecology Division, 200 Southwest 35th Street, Corvallis, Oregon 97333, USA
ALAN T. HERLIHY
Department of Fisheries and Wildlife, Oregon State University, 200 Southwest 35th Street,
Corvallis, Oregon 97333, USA
Abstract.—In the late 1990s the Environmental Monitoring and Assessment Program of the U.S.
Environmental Protection Agency developed a structured set of tests to evaluate and facilitate selection of
metrics for indices of biotic integrity (IBIs). These IBIs were designed to be applicable across multistate
regions as part of a national assessment of all U.S. waters. Here, we present additional steps in, and
refinements to, that IBI development process. We used fish and amphibian assemblage data from 932 stream
and river sites in 12 western U.S. states to develop IBIs for Mountains, Xeric, and Plains ecoregions. We
divided 237 candidate metrics into nine metric classes representing different attributes of assemblage structure
and function. For each ecoregion we sequentially eliminated metrics by testing metric range, signal-to-noise
ratios, responsiveness to disturbance, and redundancy to select the best metric in each class. The IBIs for the
Mountains and Plains each had seven metrics and the Xeric IBI had five. In the Mountains, half of the
estimated stream length that could be assessed had IBI scores greater than 62 (out of 100). In the Xeric and
Plains, half the stream length had scores no greater than 50 and no greater than 37, respectively. An estimated
16% of Xeric stream length had scores greater than 62 (the median for the Mountains), while 5% of Plains
stream length had scores that exceeded 62. This IBI development process is less subjective and more
streamlined and has more clearly defined criteria for metric selection and scoring than those used in the past,
while maintaining a strong ecological foundation.
Twenty-five years ago, when the condition of
streams and rivers was largely assessed by water
quality criteria, Karr (1981) proposed an index of biotic
integrity (IBI). It was designed to quantify characteristics of stream fish assemblages to assess biotic
integrity, which is defined by Frey (1977) and Karr
and Dudley (1981) as the ‘‘capability of supporting and
maintaining a balanced, integrated, adaptive community of organisms having a species composition,
diversity, and functional organization comparable to
* Corresponding author: [email protected]
Received May 29, 2006; accepted January 3, 2007
Published online April 26, 2007
that of the natural habitat of the region.’’ Since that
time, IBIs have become fairly standard tools for
assessment of stream condition, particularly to address
aquatic life uses (Davis and Simon 1995; Simon
1999a). The original IBI, which was developed for fish
assemblages in Midwestern warmwater streams, has
been modified for other regions and continents (Miller
et al. 1988; Hughes and Oberdorff 1999; Karr 2006),
coldwater streams (Lyons et al. 1996; Hughes et al.
2004), plains streams (Bramblett and Fausch 1991;
Shearer and Berry 2002; Bramblett et al. 2005), large
rivers (Hughes and Gammon 1987; Lyons et al. 2001;
Emery et al. 2003; Mebane et al. 2003; Yoder et al.
2005) and lakes (Minns et al. 1994; Drake and Pereira
2003). Others have used IBI concepts to develop multi-
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STRUCTURED APPROACH TO INDICES OF BIOTIC INTEGRITY
metric indices for benthic macroinvertebrates (Kerans
and Karr 1994; Klemm et al. 2003), periphyton (Hill et
al. 2000, 2003; Fore 2003), and riparian birds
(O’Connell et al. 2000; Bryce 2006).
Most of these modifications to the original IBI were
done with as many of Karr’s original metrics (Karr
1981; Karr et al. 1986) as reasonably possible and made
one-for-one substitutions where the original metrics
were judged inappropriate for the region or assemblage
types (e.g., Miller et al. 1988; Simon and Lyons 1995;
Simon 1999a). Collected species were characterized
into trophic, taxonomic, and habitat groups, and
tolerance classes. Metrics were calculated for sampled
sites based on the collection data combined with the
species characterizations. Metrics were scored following the theoretical framework for how the metrics
behave as conditions change from natural to degraded,
as laid out in Karr (1981) and Karr et al. (1986). Scoring
was usually done by plotting metric data values against
a natural gradient such as stream order and lines were
drawn to trisect the data points (across the natural
gradient) to give scores of 5, 3, and 1.
The IBI and this process have not lacked critics.
Throughout this time there have been ongoing spirited
discussions (e.g., Karr and Chu 1999, 2000; Norris and
Hawkins 2000) among researchers and resource
managers about the appropriate use of IBIs and about
methods for developing and evaluating them. Key
issues in this debate are questions such as: When and
how should metrics be modified, replaced or dropped
in an existing IBI? How many metrics are needed in an
IBI? When beginning afresh (i.e., in a region,
ecosystem, or assemblage for which no IBI currently
exists), how should metrics be proposed, evaluated,
and chosen? How can the index development process
be streamlined and made more repeatable (less
subjective)?
To address these questions, scientists and resource
managers working with the U.S. Environmental
Protection Agency’s (EPA) Environmental Monitoring
and Assessment Program (EMAP) developed a set of
tests to evaluate and select metrics, and to evaluate IBIs
at regional scales with multiple stressor variables
(McCormick et al. 2001; Klemm et al. 2003), as part
of its Mid-Atlantic Highlands assessment. In this paper
we present additional steps in that process and some
refinements to the tests used for evaluating and
selecting metrics, and producing IBIs. We illustrate
these changes by presenting three IBIs developed for
perennial streams and rivers in the western USA, using
data from the EMAP Western Survey (hereafter EMAP
West). We then use those IBIs to assess the biotic
condition of the population of western streams and
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rivers as indicated by their aquatic vertebrate (fish and
amphibian) assemblages.
Methods
Study Area and Sample Design
A primary objective of EMAP West (Stoddard et al.
2005a, 2005b) was to estimate the ecological condition
of perennial streams and rivers in 12 states of EPA
regions 8, 9, and 10 (Figure 1). The target population
of perennial streams and rivers was defined as those
present on the digital 1:100,000 scale U.S. Geological
Survey hydrologic maps that were incorporated into
EPA’s River Reach File (Version 3; http://www.fgdl.
org/metadata/fgdc_html/eparr3.fgdc.htm) and that contained water during summer base flow. The lower
portions of the main stems of the Columbia, Missouri,
Snake, and Colorado rivers were excluded. The survey
was explicitly stratified by the 12 states and within
each state we used an unequal probability, spatiallybalanced survey design (Stevens and Olsen 2004;
Stoddard et al. 2005a). Sites were selected by Strahler
stream order to yield approximately equal numbers of
sites for the first-, second-, third-, and fourth-orders and
higher categories and 120 sites for large rivers. Within
that design, the sample size for the basic survey was 50
sites per state for a total of 600 unique sites to be
sampled across the study region. The same design was
used to select additional sites for six intensive study
areas: northern and southern California coastal streams,
Deschutes River and John Day River basins in Oregon,
Wenatchee River basin in Washington, Upper Missouri
River basin streams and rivers, and Colorado plains
streams (Figure 1). A 5% random subset of sites was
selected for up to three repeat visits, usually a second
visit during the initial sample year, and two visits
within a subsequent year. An additional 357 handpicked sites were selected by state agencies and EMAP
as potential reference sites (Whittier et al. 2007b). All
sites were sampled with EMAP protocols.
Because ecological conditions and vertebrate assemblage characteristics vary widely across the western
United States, sites were classified into three largescale ecoregions: the western forested mountains, xeric
lands, and the northern Great Plains (hereafter
Mountains, Xeric, and Plains; Figure 1) and 10
intermediate-scale ecoregions, 4 each in the Mountains
and Xeric, and 2 in the Plains. These were developed
by aggregating Omernik level III ecoregions (Omernik
1987; USEPA 1996) into areas that we judged would
encompass the major types of ecological conditions
and assemblages (Stoddard et al. 2005a, 2005b).
We used the least disturbed sites to define reference
conditions (Hughes 1995; Stoddard et al. 2006; Whittier
et al. 2006) for metric development. We used four sets
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WHITTIER ET AL.
FIGURE 1.—Locations of the 1,367 stream and river sites sampled by the Environmental Monitoring and Assessment Program
–Western Survey during 2000–2004. Sites were selected using a probability design from the population of perennially flowing
waters in the 12 states encompassed. Areas with a concentration of sites, such as northwestern California and the John Day River
basin in Oregon, were given additional sites (i.e., an increased sampling density within the probability design) to support ongoing
U.S. EPA projects. The regions shown are aggregations of Omernik’s (1987) Level III ecoregions.
of criteria to classify sites as least disturbed, most
disturbed, or intermediate. Two sets of filtering criteria
were developed independently by two of us (J.L.S. and
A.T.H.; see also Stoddard et al. 2005a) for each of the
10 intermediate-scale ecoregions following methods in
Herlihy et al. (2006), which required sites to pass a
series of water quality (total phosphorus, total nitrogen,
Cl, SO4, pH, and turbidity) and physical habitat
(riparian disturbance, substrate fines, and riparian
vegetation) criteria to be considered least disturbed. A
variant on this approach was used to identify the least
disturbed sites for each of the three large-scale
ecoregions in which sites were evaluated relative to
their position along natural gradients (e.g., stream size,
site elevation) (Whittier et al. 2006). This natural
gradient approach evaluated catchment disturbance
measures (percent urban land, percent agricultural land,
road density) in addition to most of the water quality
and physical habitat disturbance measures used in the
first two sets of filtering criteria. The fourth evaluation
scored sites based on the numbers, kinds, intensity, and
proximity to the stream of human disturbances visible in
digital (aerial) orthophotographs in their catchments (P.
Lattin, Dynamac, Inc., unpublished data). The reverse
of these tests were used to select the most disturbed
sites, that is, sites that failed any of a series of
ecoregional chemical and physical criteria, or which
had high values of multiple stressors relative to their
positions along natural gradients. We used a roundtable
discussion that included reference to field notes and
data sheets to compare these four evaluations to select a
final list of least disturbed, most disturbed, and
intermediate sites (Stoddard et al. 2005a; Whittier et
al. 2007b). This process was applied to all sampled
sites, combining both probability and handpicked sites.
STRUCTURED APPROACH TO INDICES OF BIOTIC INTEGRITY
Field Methods
Field sampling was conducted during base-flow
periods (generally late spring through late summer)
from 2000 through 2004 with a combination of state
and contract crews. All crews were trained in the
EMAP West sampling protocols (Peck et al. 2006, in
press). Aquatic vertebrates (fish and amphibians) were
sampled via backpack or raft electrofishing, which is an
effective method of collecting instream amphibians
(Connor et al. 1988; Moyle and Marchetti 1999;
Hughes et al. 2004). Backpack electrofishers were used
in small wadeable streams, while rafts were used in
rivers where wading was unsafe or difficult, typically
fourth to fifth order and larger rivers. In wadeable
streams vertebrates were sampled in a reach with length
40 times the average wetted stream width, a reach
length demonstrated to collect 90% of potential fish
species (Reynolds et al. 2003). Raft electrofishing was
employed near shore for a distance equal to 100 times
the average wetted width to collect 95% of the fish
species expected (Hughes et al. 2002). Voucher
specimens were confirmed by, and are cataloged and
archived at, the National Museum of Natural History
(Smithsonian Institution). Field crews also made
detailed instream and riparian physical habitat measurements and collected samples of water, periphyton,
and benthic macroinvertebrates (Peck et al. 2006, in
press) for laboratory analyses.
Species Characteristics
All species collected were classified into habitat,
reproductive, and life history guilds (see appendices)
based on a variety of published sources (e.g., Stebbins
1954; Baxter and Simon 1970; Minckley 1973; Moyle
1976; Wydoski and Whitney 1979; Simpson and
Wallace 1982; Sigler and Sigler 1987, 1996; Simon
1999b; Zaroban et al. 1999). A species’ native or alien
status at each site was based on whether the site was
within its native range as determined from a variety of
published sources (e.g., Bailey and Allum 1962;
Brown 1971; Minckley 1973; Moyle 1976; Wydoski
and Whitney 1979; Lee et al. 1980; Sigler and Sigler
1987, 1996; Page and Burr 1991; Fuller et al. 1999).
We initially assigned species to tolerance classes
(intolerant, intermediate, tolerant, and very tolerant)
using a weighted averaging process (ter Braak and
Barendregt 1986; Birks et al. 1990; Huff et al. 2005) to
evaluate their tolerances to several human disturbance
indicators (e.g., total phosphorus, turbidity, percent fine
substrate, and riparian disturbance). We used species’
relative abundances (as the weight) to estimate each
species’ optimum and upper tolerance for each
disturbance indicator as the weighted average and the
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sum of the weighted average and its standard deviation,
respectively. We then plotted the species optima and
upper tolerances sorted by the upper tolerances. To
identify which species were intolerant or tolerant to
each disturbance indicator, we examined the tails of the
sorted plots looking for break points and identifying
species that occurred at each end of the lists. We
judged species intolerant if they were consistently in
the lower tails of the plots, tolerant if they were in the
upper tails of multiple plots, very tolerant if they were
always in the upper tails, and intermediate otherwise.
This weighted-averages process provided a quantification generally lacking in the traditional method of
assigning species tolerances based primarily on
professional judgment and experience and on similarly
derived classifications in the literature. Despite this
improvement, we found that our decisions about where
to set the tolerance class breaks (e.g., between
intolerant and intermediately tolerant) were a matter
of judgment, given that species upper tolerances (and
optima) were essentially continuous over the range of
disturbances (T.R.W., unpublished data).
As an alternative to tolerance classes, we developed
species tolerance values for tolerance to a generalized
disturbance measure (Whittier et al. 2007a). Our
disturbance measure was the first principal component
(PC1) of a principal components analysis of nine
disturbance indicators (total phosphorus, total nitrogen,
turbidity, percent fines in the substrate, average number
of disturbance types [e.g., pipes, walls, and grazing] in
the stream or riparian zone of the sample reach
[Kaufmann et al. 1999], percent of riparian zone with
shrubs and woody ground cover, percent agricultural
land in catchment, percent urban land in catchment,
and road density). To calculate tolerance scores, for
each species we ran a bootstrap analysis with 500
resamples of the upper tolerance for the PC1 scores as
calculated by weighted averaging. After all tolerance
scores were calculated we rescaled them to a range of 0
to 10 to produce tolerance values (see Whittier et al.
2007a for details).
Following the approach of Chutter (1972) and
Hilsenhoff (1977, 1987), we developed an assemblage
tolerance index (ATI; Whittier et al. 2007a), that is, a
set of site scores that describe the gradient of
disturbance as shown by the composite tolerances in
vertebrate assemblages. For each site, the ATI score
was calculated as the sum of the products of each
species’ tolerance value (TolVal) and its relative
abundance. We included the ATI as a candidate
tolerance metric. For the other candidate tolerance
metrics and tolerance-modified metrics (e.g., percent
sensitive invertivores), we defined four tolerance
classes: intolerant (sensitive; TolVal 2.5), interme-
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WHITTIER ET AL.
diately tolerant (2.5 , TolVal , 7.5), tolerant (7.5 TolVal , 9.0), and very tolerant (TolVal 9.0).
Metric Evaluation and Index Construction
Our objective was to produce three comparable IBIs
for the western USA, one each for the Mountains,
Xeric, and Plains ecoregions (Figure 1). Metrics were
selected and scored separately in the three ecoregions,
by means of the same process throughout for metric
evaluation and scoring, such that the three IBIs could
be combined (over the western USA) in a single
assessment with minimal regional bias.
Overall, 237 candidate metrics (Stoddard et al.
2005a) were calculated from the aquatic vertebrate
data collected for EMAP West. To organize this
number of metrics into a manageable and consistent
evaluation process, we reviewed the ecological rationale used to develop the original IBI metrics (Karr
1981; Karr et al. 1986) and considered whether there
were additional attributes of vertebrate assemblage
integrity that were not included in those. We then
divided the candidate metrics into nine metric classes
(Table 1) each of which was intended to capture a
separate attribute of vertebrate assemblage biotic
integrity (Karr 1981; Karr et al. 1986; Barbour et al.
1999). To develop an IBI we screened this pool of
candidate metrics using a series of tests (Hughes et al.
1998; McCormick et al. 2001; Klemm et al. 2003). In a
key departure from these earlier works we structured
the metric screening process with the goal of finding
the single metric in each metric class with the best
performance (in terms of the tests described below).
The tests were run for each of the three large scale
ecoregions separately, except for the signal-to-noise
test which was run for all sites. Tests were applied
sequentially; metrics that failed a test were not
considered for further evaluation and were not
subjected to subsequent tests.
Range test.—If a metric’s range of values is small, or
if most values are identical, then the metric is unlikely
to differentiate sites. We eliminated richness metrics if
their range was less than four species and eliminated
any metric if more than 75% of the values were
identical.
Signal-to-noise test (S:N).—Signal to noise is the
ratio of variance among sites (signal) to the variance of
repeated visits to the same site (noise, which includes
both natural variance and sampling error) and is a
measure of the repeatability or precision of the metric
values (Kaufmann et al. 1999). A S:N value of 1
indicates that a metric has as much variability within a
site (over time) as it does across different sites and thus
does not distinguish well among sites. We used this test
conservatively by calculating S:N ratios for all samples
TABLE 1.—Metric classes used to develop indices of biotic
integrity in the western USA.
Class
Habitat
Tolerance
Trophic
Reproductive
Composition
Richness
Life history
Aliens
Abundance
Description
Preferred habitat for each vertebrate species (e.g.,
benthic, water column, or hider)
General tolerance to common anthropogenic,
physical, and chemical stressors (sensitive,
intermediate, tolerant, or very tolerant)
Primary source of nutrition for each vertebrate
species as an adult (herbivore, invertivore,
invertivore–piscivore, piscivore, or omnivore)
Reproductive habit for each vertebrate species (e.g.,
lithophil, nest builder, or crevice spawner)
The representation of different taxonomic groups
(e.g., family) in the assemblage
The number of different kinds of taxa
The general life history strategy for each vertebrate
species (e.g., migrating [vagile], long-lived, etc.)
Whether each vertebrate species is native or
introduced in the region where it was collected
The number of individuals of an assemblage,
taxonomic group, or guild collected
west-wide, which produces a higher signal than if done
by ecoregion. Thus, we rejected only very noisy
metrics, that is, those with S:N values less than 3 (i.e.,
where the within-site variability was 1/3 of the
among sites variability).
Correlation with natural gradients.—We evaluated
whether strong relationships between metrics and
natural gradients (e.g., stream size, stream slope, and
elevation) might obscure potential stressor relationships. We wanted to evaluate those relationships
without the often covarying effect of human disturbance. Thus, we regressed the site values from the least
disturbed sites for each metric against these natural
gradients and examined plots of the data points,
regression line, and 95% prediction interval. We
judged there was a strong relationship if the prediction
intervals at the ends of the natural gradients did not
have overlapping values. For metrics that showed a
relationship with a natural gradient we produced a
natural-gradient corrected metric by calculating the
regression equation for least disturbed sites and then
calculating the offset (analogous to the residual) from
that equation for all sites. For our data, correcting for
stream size (estimated by the log10 transformation of
the mean wetted cross sectional area) also corrected for
channel slope and site elevation. The stream-sizecorrected metric then replaced the original metric.
Responsiveness test.—For metrics that passed the
range and S:N tests in the Mid-Atlantic Highlands
assessment, McCormick et al. (2001) and Klemm et al.
(2003) used correlations and scatterplots of multiple
physical habitat, water quality, and watershed measures
to test the responsiveness of metrics to human
disturbance. We generally found weak or poor
STRUCTURED APPROACH TO INDICES OF BIOTIC INTEGRITY
TABLE 2.—Distribution of 932 sites in 12 western states
used to evaluate candidate metrics and develop indices of
biotic integrity, by ecoregion and disturbance class (see text).
Ecoregion
Least
disturbed
Moderately
disturbed
Most
disturbed
Mountains
Xeric
Plains
114
49
47
304
86
155
49
49
79
associations between candidate metrics and individual
stress indicators. This was particularly true in the
Mountains. However, there were numerous clear
differences in metric values between the least disturbed
and most disturbed sites (which integrate multiple
human disturbances). Thus, we evaluated metric
responsiveness with one-way analyses of variance to
test the ability of metrics to distinguish between the
least disturbed and most disturbed sites. Tests were
conducted separately for the three ecoregions, and the
F-statistic was used as the primary basis for evaluating
responsiveness to disturbance.
For each ecoregion, candidate metrics (which had
passed the previous tests) were sorted by F-value and
by F-value within metric classes. The list of metrics
selected for each ecoregion’s IBI was built by first
taking the metric with the highest F-value, then taking
the metric with the next highest F-value from among
all other metric classes, and continuing until all of the
metric classes were represented by one metric,
provided that the selected metrics were not redundant
and had significant F-values. In this process it was
possible that some metric classes lacked appropriate
metrics, in which case the final IBI had fewer than nine
metrics.
Redundancy test.—Only metrics that did not contain
information that was redundant with previously
selected metrics were included in the final IBIs. We
estimated redundancy by creating a correlation matrix
of metric values from least disturbed sites (to avoid
eliminating metrics that are correlated only because
their responses to stressors covary). We considered
metrics redundant if their Spearman correlation coefficients were greater than 0.70. For redundant metric
pairs in different metric classes the metric selected for
inclusion first (i.e., with the higher F-value) was
retained and the redundant metric was replaced with
the next nonredundant metric in its metric class.
Range test for metric scores.—As a final check
before accepting a candidate metric for inclusion in the
IBI, we produced box plots of the metric values for the
least disturbed, intermediate, and most disturbed sites.
If those plots indicated that a majority of sites would
have the same metric score (see next section) regardless
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of disturbance class, we rejected that metric and
returned to the appropriate place in the metric selection
process to pick a replacement.
Metric scoring and evaluation.—We scored each
selected metric on a continuous scale from 0 to 10
(Minns et al. 1994; Hughes et al. 1998; McCormick et
al. 2001; Bramblett et al. 2005). Metrics were scored
separately by ecoregion by means of a process intended
to maximize among-site differences in final IBI scores
(Blocksom 2003); floor and ceiling values for each
metric were defined as the 5th and 95th percentile
values observed in all sites in the region. For positive
metrics, (those that are highest in the least disturbed
sites) values less than the 5th percentile were given a
score of 0, those with values greater than the 95th
percentile were given a score of 10, and metric scores
in between were interpolated linearly. Negative metrics
were scored similarly, with the floor and ceiling values
reversed. Scored metrics were then summed, and the
summed score was scaled to a range of 0–100 by
multiplying each sum by a scalar based on the number
of metrics included in the index.
We evaluated how well the IBIs discriminated
between reference and disturbed sites by calculating
S:N ratios and F-values (between the least disturbed
and most disturbed sites) for each of the three regional
IBIs separately and for all scores combined across the
western USA. Finally, to describe the biotic condition
of aquatic vertebrate assemblages in western streams
and rivers we calculated the cumulative distribution
functions (CDF) of ecoregional IBIs based on estimated stream length (rather than the number of sites) using
the expansion factor (i.e., the inverse of the selection
probability from the site selection design) for each site.
Results
From 2000 to 2004, 1,367 stream and river sites
were sampled, 74 of these receiving 1–3 repeat visits
(within and among years). A total of 196 aquatic
vertebrate species, including 32 amphibian species,
were collected. Vertebrate assemblage sampling was
not done at 195 sites and was judged insufficient at 63
others. Sampling permit restrictions related to threatened or endangered species accounted for a majority of
the unsampled and insufficiently sampled sites. No
vertebrate species were collected at 83 of the
sufficiently sampled sites and an additional 94 sites
had fewer than 10 individuals. We excluded sites with
fewer than 10 individuals from the data set used for
metric evaluation and IBI calibration, leaving 932 sites
(Table 2).
Of the original 237 candidate metrics (Stoddard et al.
2005a), 80 failed the range test in the Mountains, 34
failed in the Xeric, and 109 failed in the Plains. Most
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WHITTIER ET AL.
TABLE 3.—Metrics selected for the Mountains ecoregion, listed in the order selected. The F-values are from a one-way
ANOVA to distinguish between the least disturbed and most disturbed sites. The signal-to-noise ratio (S:N) is the ratio of the
variance among sites to that within sites. Ceiling is the metric value that scored 10 points and floor is the metric value that scored
0 points; for negative metrics, floor values are higher than ceiling values.
Metric
Metric class
F-value
S:N
Ceiling
Floor
Sensitive rheophilic speciesa
Assemblage tolerance index
Sensitive invertivores–piscivoresb
Lithophilic spawnersa
Salmonidaeb
Native sensitive long-lived speciesb
Alien vertebrate speciesb
Habitat
Tolerance
Trophic
Reproductive
Composition
Life history
Aliens
59.2
53.4
43.8
38.6
32.5
14.4
0.03
21.8
38.3
14.8
16.4
17.7
22.9
22.9
1
1.16
1
1
1
1
0
0
5.32
0
0.2
0
0
1
a
b
Proportion of species.
Proportion of individuals.
metrics that failed in all regions were composition or
trophic metrics. Much of the western USA is relatively
species poor, so that most of the composition metrics
based on family membership had inadequate range.
Likewise, there are few herbivorous or piscivorous
species in the western USA; most trophic metrics based
on those characteristics failed the range test. In the
Mountains, other metrics that failed were primarily
based on nest-guarding species, invertivorous cyprinids, large river specialists, and very tolerant species.
In the Plains, other metrics that failed were based on
cool- or coldwater species, rheophilic species, and
metrics that included only sensitive species and to a
lesser extent, nontolerant species.
Of the metrics that passed the ecoregional range
tests, 9 each in the Mountains and Plains, and 11 in the
Xeric had S:N ratios less than 3.0 and were rejected.
Five to seven of these were based on the numbers of
individuals collected (versus proportions of individuals
or taxa). Three metrics were corrected for relationship
to stream size in the Mountains, eight were stream-size
corrected in the Plains, and one was stream-size
corrected in the Xeric. All were species richness
metrics.
We selected seven metrics each for the Mountains
and Plains IBIs and five for the Xeric (Tables 3–5).
There was no apparent pattern in the order in which
metric classes were entered into the ecoregional IBIs
except that an alien species metric was always the last
entered, and the ATI was either the first or second
metric selected. The proportion of lithophilic individuals was selected in two regions, and the proportion of
lithophilic taxa was selected in the other. None of the
IBIs included an abundance metric, because they all
either failed the S:N test or had very low F-values. The
stream-size corrected fish species richness metric
would have been selected as the richness metric for
the Mountains and the Xeric, but was a negative metric
(as were all the other richness metrics). That is, fish
species richness (corrected for stream size) was higher
in the most disturbed sites than in the least disturbed
sites. No life history metrics were selected in either the
Plains or the Xeric, and no species composition metric
was selected in the Xeric. The selected metrics were all
among the higher F-values for their regions, except the
alien species metrics. Overall, alien species occurrence
was unrelated to physical and chemical habitat
alteration.
The high S:N ratios and F-values for IBI scores over
the western USA and by ecoregion (Table 6) indicated
that these IBIs were repeatable over time and had a
strong ability to distinguish between the least disturbed
and most disturbed sites. The IBI scores were
significantly higher for the least disturbed sites than
for the most disturbed sites in all regions and
significantly higher than those for the moderately
disturbed sites in the Xeric and Plains regions (Figure
2). In general IBI scores were higher in the Mountains
TABLE 4.—Metrics selected for the Xeric ecoregion, listed in the order selected. See Table 3 for more details.
Metric
Metric class
F-value
S:N
Ceiling
Floor
Assemblage tolerance index
Lithophilic spawnersa
Omnivoresa
Native sensitive lotic speciesb
Alien vertebrate speciesb
Tolerance
Reproductive
Trophic
Habitat
Aliens
82.6
61.3
31.3
24.7
0.0003
38.3
16.4
13.7
56.6
22.9
0
1
0
1
0
8.45
0
1
0
1
a
b
Proportion of species.
Proportion of individuals.
725
STRUCTURED APPROACH TO INDICES OF BIOTIC INTEGRITY
TABLE 5.—Metrics selected for the Plains ecoregion, listed in the order selected. See Table 3 for more details.
Metric
Metric class
F-value
S:N
Ceiling
Floor
Assemblage tolerance index
Nontolerant vertebrate species richness
Nontolerant native benthic speciesa
Non-tolerant invertivores–piscivoresa
Ictaluridaea
Lithophilic spawnersa
Alien vertebrate speciesa
Tolerance
Richness
Habitat
Trophic
Composition
Reproductive
Aliens
31.1
22.4
13.6
11.2
10.9
5.6
0.07
38.3
8.2
33.0
8.1
4.5
14.6
22.9
2.33
5
0.86
0.909
0
0.948
0
8.97
0
0
0
0.675
0
0.575
a
Proportion of individuals.
and lower in the Plains and scores of moderately
disturbed sites were intermediate between the least
disturbed and most disturbed sites (Figure 2).
Biotic Condition in Western Streams and Rivers
One EMAP West objective was to assess the
ecological condition of the population of streams and
rivers in the 12-state assessment area. Using the EMAP
probability design, Stoddard et al. (2005b) estimated
that there were 420,855 km of perennial flowing waters
in the assessment area. Of those, an estimated 73,967
km were inaccessible due to access denial by
landowners and another 42,344 km were physically
inaccessible. Of the remaining 304,544 km of streams
and rivers, sites representing 64,044 km were not
sampled for aquatic vertebrate assemblages primarily
due to sampling permit issues, and to a lesser extent,
sampling issues such as extremely shallow water.
Another 26,360 km of streams were represented by
adequately sampled sites where no aquatic vertebrate
species were found.
Thus, we assessed the biotic condition of the aquatic
vertebrate assemblages for an estimated 214,140 km of
streams and rivers in this 12-state area. Of this total
stream length, 148,509 km were in the Mountains,
33,992 km in the Xeric, and 31,172 km in the Plains
(Figure 3). In the Mountains, the distribution of IBI
scores was skewed toward relatively high values, half
the estimated stream length having scores greater than
62. In the Xeric and Plains, the distributions of IBI
scores were skewed toward lower scores, half the
stream length having scores of no more than 35 in the
Plains and no more than 50 in the Xeric. An estimated
16% of Xeric stream length had scores greater than 62
(but scores ranged up to 100), while in the Plains only
5% of stream length had IBI scores of at least 62 and
the highest score was 75.
Discussion
The IBIs presented here are the products of a process
that offers advantages over the manner in which
multimetric indices typically have been developed in
the past by being less subjective and more streamlined
and having clearly defined criteria for metric selection
and scoring. A clear lesson that EMAP learned in the
process of developing multimetric indices for the MidAtlantic Highlands and the western USA was the great
diversity of opinions (both within the EMAP program
and among state agency personnel and other researchers) about which metrics are appropriate to consider
and how to evaluate whether a particular metric (or
metric variant) should be included in an index. For
example, the piscivore component of an assemblage
may be quantified as species richness, percent of
individuals, percent of species, and number of
TABLE 6.—Signal-to-noise (S:N) ratios (repeatability over
time) and F-values for differences between the least disturbed
and most disturbed sites of final indices of biotic integrity. All
F-values were significant at P , 0.0001.
Ecoregion
S:N
F-value
Western USA
Mountains
Xeric
Plains
20.5
20.5
28.2
7.2
198.6
58.0
88.0
43.9
FIGURE 2.—Distribution of ecoregional IBI scores for the
least disturbed, moderately disturbed, and most disturbed sites.
Boxes show medians and quartiles, whiskers indicate 10th and
90th percentiles, and circles indicate outliers.
726
WHITTIER ET AL.
FIGURE 3.—Cumulative distribution functions (CDFs) of IBI scores (solid lines) and 95% confidence intervals (dotted lines)
for the population of 148,509 km of perennial streams and rivers in the Mountains, 33,992 km in the Xeric, and 31,172 km in the
Plains ecoregions. Excluded from these CDFs are an estimated 64,044 km of streams represented by sites at which vertebrate
assemblage sampling could not be carried out and 26,360 km of streams at which no vertebrates species were found.
STRUCTURED APPROACH TO INDICES OF BIOTIC INTEGRITY
individuals. These may be further modified by
considering only native species, only nontolerant
species, or a combination of these. Considering these
metric variants has often led to a proliferation of
candidate metrics (Simon and Lyons 1995; Hughes and
Oberdorff 1999).
Previously, the only way to be certain of selecting
the best metrics from among all these potential metrics
was to calculate and compare graphically all proposed
metrics and metric variants, which in our experience
has led to inconsistent decision making as to whether to
accept (for further consideration) or reject candidate
metrics. That is, we repeatedly became aware that a
general pattern seen in a data graph that had been
acceptable earlier in the review was being rejected (or
vice versa) later in the process of viewing graphs for
extended periods of time.
The traditional approach for selecting metrics has
been to use as many of Karr’s original metrics (Karr
1981; Karr et al. 1986) as is reasonably possible and to
make one-for-one substitutions where the original
metrics were judged inappropriate for the region or
assemblage types (e.g., Miller et al. 1988; Simon and
Lyons 1995; Simon 1999a). However, when the
ecosystems and assemblages being evaluated are
ecologically distinct from the low-gradient, warmwater
streams of the humid Midwest where the original IBIs
were created, this metric substitution process becomes
strained. In western systems some of the original
metrics responded to human disturbance in the opposite
direction to that described in Karr (1981) and Karr et
al. (1986). For example, in warmwater streams, native
species richness is expected to be high in natural
situations, decreasing with human disturbance. But in
coldwater streams, native species richness is naturally
low and increases with moderate human disturbances
that enrich and warm the streams, only decreasing as
the disturbance becomes more severe (Mebane et al.
2003; Hughes et al. 2004). In such cases the best
approach might be to retain the IBI concept but to
abandon the original metrics and begin anew.
Regardless of whether one chooses to apply metric
substitution or to create a new IBI, the issue of how to
evaluate and select metrics has a conceptual component
and a procedural component. The conceptual part
addresses the question (Hawkins 2006) of whether the
metrics are selected to encompass the biologically
important features of the assemblage (Karr 1981; Karr
et al. 1986) or primarily to most clearly distinguish
levels of human disturbance (Barbour et al. 1999). If
one chooses the former, then the IBI may have reduced
usefulness as an assessment and management tool. For
example, in some aquatic ecosystems some of the top
carnivores are quite tolerant of disturbed conditions
727
(Whittier and Hughes 1998), so a piscivore metric that
includes all top carnivores would not be as sensitive to
human disturbance as one that excludes individuals of
tolerant species. However, if one chooses only the most
responsive metrics, then the resulting index may not
include some important components of biotic integrity.
How one addresses the balance between including
the major components of biotic integrity and responsiveness to disturbance is key to how one establishes
procedures and criteria for selecting metrics. We chose
not to view this as a dichotomy, rather, we developed
an approach with nine attributes of biotic integrity for
aquatic vertebrate assemblages into which all candidate
metrics were classified (Table 1). We then selected the
single ‘‘best’’ metric from each metric class, with best
defined as being most responsive to disturbance,
having sufficient data range, having an adequate S:N
ratio, and not being redundant with other selected
metrics.
The decision to select only one metric from each
metric class and apply the selection criteria described
above allowed us largely to automate the index
development process, such that we could run the
analyses, evaluate the results of each step, select and
score metrics, and create an IBI in a single day.
Previous EMAP IBI evaluations (e.g., McCormick et
al. 2001; Klemm et al. 2003) strove to increase the
analytical rigor of metric selection by using tests of
metric range, responsiveness, redundancy, and signal
to noise (as described previously) to augment and
support the traditional graphical metric evaluation
methods. However, given that we had hundreds of
candidate metrics, three major ecoregions, and dozens
of stressors to evaluate, the process of viewing and
evaluating thousands of metric scatterplots became
very cumbersome, subject to decision-making fatigue,
and ultimately included considerable qualitative judgment. Limiting metrics to those that were not redundant
and with the highest F-value per metric class
eliminated days of judgment. Although this may seem
like a trivial issue, we believe that the amount of time
previously needed to evaluate metrics and construct
IBIs has been a major impediment to the development
of assemblage-based biological indicators of ecological
condition.
The three ecoregional IBIs developed by the process
presented here show several expected patterns. For
each region, the IBI scores for the least disturbed sites
were significantly higher than those for the most
disturbed sites and significantly higher than those for
the moderately disturbed sites in the Xeric and Plains
regions (Figure 2). For the population of streams and
rivers, IBI scores were highest in the Mountains, lowest
in the Plains, and intermediate in the Xeric (Figures 2,
728
WHITTIER ET AL.
3). This corresponds with our understanding of the
relative intensities of human disturbance in these
regions. Many streams in the Mountains are only
minimally disturbed such that the median IBI score for
moderately disturbed sites was similar to the least
disturbed sites. Hawkins et al. (2000) reported similar
results for macroinvertebrate assemblages, but Hughes
et al. (2004) reported that reference and random sites
differed significantly in the Oregon–Washington Coast
Range. Conversely, nearly all of the Plains has
experienced extensive human use of the land for more
than 100 years, which is reflected in the widespread
disturbed condition of Plains streams (e.g., Bramblett
and Fausch 1991; Bramblett et al. 2005). A number of
other EMAP West analyses of ecological condition
showed that least disturbed Plains streams and rivers
and their watersheds were disturbed as much as the
most disturbed sites in the Mountains (Stoddard et al.
2005a, 2005b; Whittier et al. 2006). This is reflected in
the lower Plains IBI scores; no Plains site scored higher
than 75 despite the fact that individual metrics were
scored based on what was regionally possible in our
data (as were metrics in the other two regions).
Our IBIs incorporated fewer metrics (7 and 5) than
the 12 originally recommended by Karr (1981) because
of substantial faunal differences between western and
Midwestern waters and our screening criteria. Others
have also successfully employed fewer than 12 metrics
in western North America (Bramblett and Fausch 1991
[9]; Lyons et al. 1995 [10]; Moyle and Marchetti 1999
[6]; Karr and Kimberling 2003 [8]; Mebane et al. 2003
[10]; Hughes et al. 2004 [8]; Bramblett et al. 2005 [10])
and in cold or cool waters elsewhere (Leonard and Orth
1986 [7]; Lyons et al. 1996 [5]; Kovacs et al. 2002 [6];
Oberdorff et al. 2002 [7]). Although we evaluated
numerous species richness metrics, none passed our
screens in the Xeric and Mountains regions; Moyle and
Marchetti (1999) and Kovacs et al. (2002) also found
species richness unresponsive in the Sierra Nevada and
Quebec, respectively. We only allowed one composition metric per IBI, unlike the three families (darters,
sunfish, suckers) proposed by Karr (1981), and only
one tolerance metric, unlike the two (intolerant species,
green sunfish Lepomis cyanellus) suggested by Karr
(1981). We also allowed only one habitat metric per
IBI, unlike the 2–3 habitat metrics commonly substituted for Karr’s (1981) three family metrics (Simon and
Lyons 1995; Hughes and Oberdorff 1999). Likewise
we used only one trophic metric per IBI versus Karr’s
(1981) three (omnivores, invertivores, and piscivores).
As indicated previously, our abundance and anomaly
metrics failed the S:N and range tests and were not
included in our IBIs. Others have also found these
metrics problematic (Simon and Lyons 1995; Hughes
and Oberdorff 1999; Pont et al. 2006). An anomalies
metric would contain no information for a very large
majority of sites across the western USA. For
assessments in areas where this is an important (useful)
indicator, one could either use anomalies as a standalone measure or add that metric into the regionally
appropriate IBI and rescale the scoring accordingly.
Unlike Karr (1981) we included metrics to represent
life history, reproduction, and alien components of fish
assemblages as suggested in Hughes and Oberdorff
(1999), Hughes et al. (2004), and Pont et al. (2006).
Thus, although our IBIs include fewer metrics than
proposed by Karr (1981), none of the metrics are
conceptually redundant as are multiple composition,
habitat, tolerance, and trophic metrics.
The IBIs we developed for EMAP West cover a very
large and diverse area and a wide range of stream and
river sizes. This may seem extreme given the tendency
to develop IBIs for single rivers or ecoregions (Simon
and Lyons 1995; Hughes and Oberdorff 1999).
However, McCormick et al. (2001) and Klemm et al.
(2003) each developed single IBIs for a five-state area
of the Appalachians, and Mebane et al. (2003)
developed one IBI for large rivers of Idaho, Oregon,
and Washington. Few or single IBIs are essential for
consistent management and comparisons for agencies
making large-scale state (Yoder and Rankin 1995; Roth
et al. 1998), national (Oberdorff et al. 2002; USEPA
2006), or international (Pont et al. 2006) assessments.
Like ours, their IBIs were possible given the
availability of large consistently collected databases,
reference sites distributed across a wide range of stream
and river types and sizes, calibration for natural
variability, and computerized calculations. Nonetheless, management of smaller areas, such as single rivers
or ecoregions, may benefit from more refined data, but
only if sufficient high-quality data exist (e.g., Hughes
et al. 2004; Bramblett et al. 2005).
Acknowledgments
The field data were collected by agency and contract
crews of the 12 states in the EMAP Western Pilot
assessment area and by Dynamac Corporation crews.
Database management and GIS support were provided
by the Corvallis, Oregon staffs of Computer Sciences
Corporation and Indus Corporation, respectively.
Development of ideas presented here benefited from
discussions with A. Borisenko, F. McCormick, K.
Hermann, D. Huff, B. Marshall, A. Rehn, T. Robinson,
J. VanSickle, and many other participants of the IBI
development workshops. M. Meador, R. Bramblett and
four anonymous reviewers provided useful comments
on earlier versions of this paper. This document has
been prepared at the U.S. EPA National Health and
STRUCTURED APPROACH TO INDICES OF BIOTIC INTEGRITY
Environmental Effects Research Laboratory, Western
Ecology Division, in Corvallis through Cooperative
Agreement CR831682-01 to Oregon State University
and Contracts 68-D01-0005 and EP-D-06-013 to
Dynamac Corporation. This manuscript has been
subjected to the Agency’s peer and administrative
review for publication. Mention of trade names or
commercial products does not constitute endorsement
for use. The EPA reports and data files described or
cited in this article are available from one or more of
the following sources: The U.S. EPA EMAP Website
(http://www.epa.gov/emap/html/pubs/docs/groupdocs/
surfwatr/field/index.html), the EPA Western Ecology
Division Website (http://www.epa.gov/wed/pages/
models.htm) or can be requested from the authors.
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Appendix: Fishes and Amphibians Used for IBI Metrics
TABLE A.1.—Fish species characteristics used to calculate metrics. Species are listed alphabetically by family (not shown) and
then by scientific name. Categories are as follows: Hab (preferred habitat; B ¼ benthic, H ¼ hider, WC ¼ water column); Lotic (X
¼ prefers flowing waters, L ¼ prefers large rivers, R ¼ rheophilic); Drom (migratory; P ¼ potamodromous, A ¼ anadromous, C ¼
catadromous); Troph. (trophic; H ¼ herbivore, I ¼ invertivore, IP ¼ invertivore–piscivore, O ¼ omnivore, P ¼ piscivore); Repr.
(preferred reproductive habitat; A11 ¼ pelagophil, A12 ¼ lithopelogophil, A13 ¼ lithophil, A14 ¼ phytolithophil, A15 ¼
phytophil, A16 ¼ psammophil, A23 ¼ lithophil brood hider, A24 ¼ crevice spawner, B ¼ nest guarder, B27 ¼ speleophil, C2 ¼
egg bearer); Long-lived (.8 years); Tol. value (tolerance value as presented in Whittier et al. 2007a); Air (can breathe air); T&E
(listed as threatened, endangered, or vulnerable).
Species
Green sturgeon Acipenser medirostris
White sturgeon Acipenser transmontanus
River carpsucker Carpiodes carpio
Quillback Carpiodes cyprinus
Utah sucker Catostomus ardens
Longnose sucker Catostomus catostomus
Desert sucker Catostomus clarkii
Bridgelip sucker Catostomus columbianus
White sucker Catostomus commersonii
Bluehead sucker Catostomus discobolus
Sonora sucker Catostomus insignis
Flannelmouth sucker Catostomus latipinnis
Largescale sucker Catostomus macrocheilus
Sacramento sucker Catostomus occidentalis
Mountain sucker Catostomus platyrhynchus
Klamath smallscale sucker Catostomus rimiculus
Santa Ana sucker Catostomus santaanae
Klamath largescale sucker Catostomus snyderii
Tahoe sucker Catostomus tahoensis
Smallmouth buffalo Ictiobus bubalus
Bigmouth buffalo Ictiobus cyprinellus
Black buffalo Ictiobus niger
Silver redhorse Moxostoma anisurum
River redhorse Moxostoma carinatum
Golden redhorse Moxostoma erythrurum
Shorthead redhorse Moxostoma macrolepidotum
Razorback sucker Xyrauchen texanus
Rock bass Ambloplites rupestris
Redbreast sunfish Lepomis auritus
Green sunfish Lepomis cyanellus
Pumpkinseed Lepomis gibbosus
Orangespotted sunfish Lepomis humilis
Hab.
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
WC
B
B
B
B
B
B
WC,
WC,
WC,
WC,
WC,
Lotic
L
L
X
X
X
X
X
X
X
X
X
L
L
X
X
L
X
L
X
X
X
X
X
X
X
X
L, R
H
H
H
H
H
Drom.
P
P
P
P
P
P
P
P
P
P
P
P
P
P
P
Temperature
Trop.
Repr.
Cool
Cool
Warm
Warm
Cool
Cold
Warm
Cool
Cool
Cool
Warm
Warm
Cool
Cool
Cool
Cool
Cool
Cool
Cool
Warm
Warm
Warm
Warm
Warm
Warm
Warm
Cool
Warm
Cool
Warm
Warm
Warm
IP
IP
O
O
O
I
H
H
O
H
I
O
O
O
H
O
H
O
O
O
I
I
I
I
I
I
O
IP
IP
IP
IP
IP
A12
A12
A12
A12
A13
A12
A13
A13
A12
A13
A13
A13
A13
A13
A13
A13
A13
A13
A13
A12
A12
A12
A13
A13
A13
A13
A13
B
B
B
B
B
Longliveda
Tol.
value
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
2.0
2.0
8.7
7.9
6.9
4.6
3.4
2.8
7.6
5.3
2.2
6.0
3.2
2.4
4.4
3.7
3.0
3.0
4.6
9.1
8.9
9.0
8.0
8.0
7.4
8.0
3.0
8.0
8.0
7.2
7.9
9.3
X
X
X
X
X
X
X
X
X
X
Aira
T&Ea
X
733
STRUCTURED APPROACH TO INDICES OF BIOTIC INTEGRITY
TABLE A.1.—Continued.
Species
Hab.
Bluegill Lepomis macrochirus
Longear sunfish Lepomis megalotis
Redear sunfish Lepomis microlophus
Smallmouth bass Micropterus dolomieu
Spotted bass Micropterus punctulatus
Largemouth bass Micropterus salmoides
White crappie Pomoxis annularis
Black crappie Pomoxis nigromaculatus
American shad Alosa sapidissima
Gizzard shad Dorosoma cepedianum
Coastrange sculpin Cottus aleuticus
Prickly sculpin Cottus asper
Mottled sculpin Cottus bairdii
Paiute sculpin Cottus beldingii
Slimy sculpin Cottus cognatus
Shorthead sculpin Cottus confusus
Riffle sculpin Cottus gulosus
Marbled sculpin Cottus klamathensis
Wood River sculpin Cottus leiopomus
Reticulate sculpin Cottus perplexus
Pit sculpin Cottus pitensis
Torrent sculpin Cottus rhotheus
Chiselmouth Acrocheilus alutaceus
Longfin dace Agosia chrysogaster
Central stoneroller Campostoma anomalum
Goldfish Carassius auratus
Lake chub Couesius plumbeus
Grass carp Ctenopharyngodon idella
Satinfin shiner Cyprinella analostana
Red shiner Cyprinella lutrensis
Spotfin shiner Cyprinella spiloptera
Common carp Cyprinus carpio
Alvord chub Gila alvordensis
Utah chub Gila atraria
Tui chub Gila bicolor
Leatherside chub Gila copei
Humpback chub Gila cypha
Bonytail Gila elegans
Gila chub Gila intermedia
Arroyo chub Gila orcuttii
Roundtail chub Gila robusta
California roach Hesperoleucus symmetricus
Western silvery minnow Hybognathus argyritis
Brassy minnow Hybognathus hankinsoni
Plains minnow Hybognathus placitus
Hitch Lavinia exilicauda
Virgin spinedace Lepidomeda mollispinis
Common shiner Luxilus cornutus
Sturgeon chub Macrhybopsis gelida
Sicklefin chub Macrhybopsis meeki
Silver chub Macrhybopsis storeriana
Pearl dace Margariscus margarita
Peamouth Mylocheilus caurinus
Hornyhead chub Nocomis biguttatus
Golden shiner Notemigonus crysoleucas
Emerald shiner Notropis atherinoides
River shiner Notropis blennius
Bigmouth shiner Notropis dorsalis
Blacknose shiner Notropis heterolepis
Spottail shiner Notropis hudsonius
Sand shiner Notropis stramineus
Topeka shiner Notropis topeka
Suckermouth minnow Phenacobius mirabilis
Northern redbelly dace Phoxinus eos
Bluntnose minnow Pimephales notatus
Fathead minnow Pimephales promelas
Flathead chub Platygobio gracilis
Sacramento pikeminnow Ptychocheilus grandis
WC, H
WC, H
WC, H
WC, H
WC, H
WC, H
WC, H
WC, H
WC
WC
B, H
B
B, H
B, H
B, H
B, H
B, H
B, H
B, H
B, H
B, H
B, H
B
B
B
B
WC
WC
WC
WC
WC
B
WC
WC, H
WC
WC
B
B
WC
WC
WC
B
B
B
B
WC
WC, H
WC
B
B
B
WC
B
WC
WC
WC
WC
B
B, H
WC
WC
WC
B
B
WC
WC
B
WC
Lotic
X
Drom.
A
R
R
R
R
R
R
R
R
R
R
R
R
L
X
X
L
X
X
X
X
L, R
L, R
X
X
X
X
L
X
L
P
P
X
X
L, R
L
L
L
X
L
X
L
X
X
X
L
L
P
Temperature
Trop.
Repr.
Warm
Warm
Warm
Cool
Warm
Warm
Warm
Warm
Cool
Warm
Cool
Cool
Cool
Cold
Cold
Cold
Cool
Cool
Cold
Cool
Cool
Cold
Cool
Warm
Warm
Warm
Cool
Warm
Warm
Warm
Warm
Warm
Warm
Warm
Warm
Cool
Warm
Warm
Warm
Warm
Warm
Warm
Warm
Cool
Warm
Warm
Warm
Cool
Warm
Warm
Warm
Cool
Cool
Warm
Warm
Cool
Warm
Warm
Cool
Cool
Warm
Warm
Warm
Cool
Warm
Warm
Cool
Cool
IP
IP
I
P
P
P
IP
IP
I
O
I
IP
I
I
I
I
I
I
I
I
I
IP
H
O
H
O
I
H
O
O
I
O
I
O
O
O
I
O
O
O
O
O
O
O
O
O
O
O
I
I
I
O
I
O
O
I
I
O
I
O
O
I
O
O
O
O
I
IP
B
B
B
B
B
B
B
B
A14
A14
B
B
B
B
B
B
B
B
B
B
B
B
A13
B
A23
A15
A12
A11
A24
B
A24
A14
A14
A14
A14
A14
A13
A13
A15
A14
A13
A14
A11
A15
A11
A13
A14
A23
A11
A11
A12
A12
A13
B
A15
A11
B
B
A15
A12
A14
B
A12
A15
B
B
A11
A13
Longliveda
X
X
X
X
X
X
X
X
X
X
X
X
X
Tol.
value
8.2
8.0
8.0
3.7
9.1
5.9
8.3
8.3
2.8
7.9
0.6
2.6
1.9
2.0
3.0
1.5
3.1
2.0
2.0
3.5
3.0
2.8
4.9
5.0
6.3
9.0
5.5
9.0
8.0
7.6
8.2
9.1
4.0
4.0
4.0
4.0
4.0
4.0
4.0
4.0
4.8
5.0
8.0
9.5
9.0
6.0
4.0
8.2
9.0
9.0
9.0
6.7
3.0
6.0
6.4
6.9
8.0
7.5
8.0
7.7
8.5
8.9
7.0
7.0
7.7
8.3
8.0
3.0
Aira
T&Ea
X
X
X
X
X
X
X
X
X
X
X
734
WHITTIER ET AL.
TABLE A.1.—Continued.
Species
Hab.
Colorado pikeminnow Ptychocheilus lucius
Northern pikeminnow Ptychocheilus oregonensis
Umpqua pikeminnow Ptychocheilus umpquae
Blacknose dace Rhinichthys atratulus
Longnose dace Rhinichthys cataractae
Leopard dace Rhinichthys falcatus
Speckled dace Rhinichthys osculus
Redside shiner Richardsonius balteatus
Lahontan redside Richardsonius egregius
Creek chub Semotilus atromaculatus
Loach minnow Tiaroga cobitis
Tule perch Hysterocarpus traskii
Northern pike Esox lucius
Muskellunge Esox masquinongy
Banded killifish Fundulus diaphanus
Northern plains killifish Fulndulus kansae
Plains topminnow Fundulus sciadicus
Plains killifish Fundulus zebrinus
Burbot Lota lota
Brook stickleback Culaea inconstans
Threespine stickleback Gasterosteus aculeatus
Goldeye Hiodon alosoides
Mooneye Hiodon tergisus
White catfish Ameiurus catus
Black bullhead Ameiurus melas
Yellow bullhead Ameiurus natalis
Brown bullhead Ameiurus nebulosus
Channel catfish Ictalurus punctatus
Stonecat Noturus flavus
Tadpole madtom Noturus gyrinus
Flathead catfish Pylodictis olivaris
Longnose gar Lepisosteus osseus
Shortnose gar Lepisosteus platostomus
White bass Morone chrysops
Striped bass Morone saxatilis
Arkansas darter Etheostoma cragini
Iowa darter Etheostoma exile
Johnny darter Etheostoma nigrum
Orangethroat darter Etheostoma spectabile
Yellow perch Perca flavescens
Blackside darter Percina maculata
Sauger Sander canadensis
Walleye Sander vitreus
Trout-perch Percopsis omiscomaycus
Sand roller Percopsis transmontana
Western brook lamprey Lampetra richardsoni
Klamath river lamprey Lampetra similis
Pacific lamprey Lampetra tridentata
Western mosquitofish Gambusia affinis
Golden trout Oncorhynchus aguabonita
Cutthroat trout Oncorhynchus clarkii
Gila trout Oncorhynchus gilae
Chum salmon Oncorhynchus keta
Coho salmon Oncorhynchus kisutch
Rainbow trout Oncorhynchus mykiss
Sockeye salmon Oncorhynchus nerka
Chinook salmon Oncorhynchus tshawytscha
Mountain whitefish Prosopium williamsoni
Brown trout Salmo trutta
Bull trout Salvelinus confluentus
Brook trout Salvelinus fontinalis
Lake trout Salvelinus namaycush
Freshwater drum Aplodinotus grunniens
Central mudminnow Umbra limi
WC
WC
WC
B
B, H
B, H
B, H
WC
WC
WC
B, H
WC, H
WC, H
WC, H
WC
WC
WC
WC
BH
WC, H
WC, H
WC
WC
B, H
B, H
B, H
B, H
B, H
B, H
B, H
B, H
WC
WC
WC
WC
B, H
B, H
B, H
B, H
WC
B
WC
WC
B, H
B, H
B, H
B, H
B, H
WC
WC, H
WC, H
WC, H
WC
WC
WC, H
WC
WC
B
WC, H
WC, H
WC, H
WC, H
B
BH
a
X indicates that the species meets that criterion.
Lotic
L
L
L
R
R
R
X
X
Drom.
Temperature
Trop.
Repr.
P
P
P
Warm
Cool
Cool
Cool
Cool
Cool
Cool
Cool
Cool
Cool
Cool
Cool
Cool
Cool
Warm
Warm
Warm
Warm
Cold
Cool
Cool
Cool
Cool
Warm
Warm
Warm
Warm
Warm
Warm
Warm
Warm
Warm
Warm
Warm
Cool
Cool
Cool
Warm
Cool
Cool
Cool
Cool
Cool
Cool
Cool
Cool
Cool
Cool
Warm
Cold
Cold
Cold
Cold
Cold
Cold
Cold
Cold
Cold
Cold
Cold
Cold
Cold
Warm
Warm
IP
IP
IP
O
I
I
O
I
I
O
I
IP
P
P
I
I
I
I
IP
I
I
IP
IP
O
IP
IP
IP
IP
IP
IP
P
P
P
P
P
I
I
I
I
IP
I
P
P
I
I
O
O
O
I
IP
IP
IP
I
I
IP
I
I
I
IP
P
IP
IP
IP
I
A13
A13
A13
A12
A12
A12
A12
A12
A12
A23
A12
C2
A15
A15
A15
A15
A15
A15
A13
B24
B24
A12
A12
B27
B27
B27
B27
B27
B27
B27
B27
A15
A15
A14
A14
B
B
B
A23
A14
A23
A12
A12
A13
A13
A23
A23
A23
C2
A23
A23
A23
A23
A23
A23
A23
A23
A13
A23
A23
A23
A23
A11
B
X
R
X
X
P
L
L
L
P
L
X
P
L
P
L
L
X
X
X
X
X
L
L
X
X
X
X
X
R
R
R
R
R
R
R
L, R
R
R
L, R
R
L
A
A
A, P
A
A
A, P
A
A
P
P
P
Longliveda
Tol.
value
X
X
X
3.5
3.5
3.0
7.3
6.2
5.0
4.0
4.6
4.0
7.6
5.0
8.0
7.8
8.0
6.0
6.0
6.1
5.7
2.0
9.4
4.7
9.3
9.0
7.0
9.7
7.0
7.3
8.9
7.1
7.8
9.0
8.0
8.0
10.0
10.0
7.0
7.5
7.8
6.2
7.4
8.0
9.3
8.7
8.4
8.0
1.3
2.0
2.4
8.8
0.0
1.5
2.0
2.0
2.1
2.1
2.0
2.5
2.5
2.7
0.7
1.7
2.0
10.0
8.0
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Aira
T&Ea
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
735
STRUCTURED APPROACH TO INDICES OF BIOTIC INTEGRITY
TABLE A.2.—Amphibian species characteristics used to calculate metrics. Species are listed alphabetically by family (not
shown) and then by scientific name. Characteristics are as follows: Hab (preferred habitat; B ¼ benthic, E ¼ edge, H ¼ hider);
Troph. (trophic; I ¼ invertivore, IP ¼ invertivore–piscivore); Repr. (preferred reproductive habitat; F ¼ floodplain, A11 ¼
pelagophil, A13 ¼ lithophil, A15 ¼ phytophil); Long-lived (.8 years); Tol. value (tolerance value as presented in Whittier et al.
2007a); Air (breathes air); T&E (listed as threatened, endangered, or vulnerable).
Species
Hab.
Longtoed salamander Ambystoma macrodactylum
American toad Bufo americanus
Western toad Bufo boreas
Canadian toad Bufo hemiophrys
Arizona toad Bufo microscaphus
Red-spotted toad Bufo punctatus
Woodhouse’s toad Bufo woodhousii
Idaho giant salamander Dicamptodon aterrimus
California giant salamander Dicamptodon ensatus
Pacific giant salamander Dicamptodon tenebrosus
Canyon tree frog Hyla arenicolor
California tree frog Pseudacris cadaverina
Boreal chorus frog Pseudacris maculata
Pacific tree frog Pseudacris regilla
Tailed frog Ascaphus truei
African clawed frog Xenopus laevis
Red-legged frog Rana aurora
Plains leopard frog Rana blairi
Foothill yellow-legged frog Rana boylii
Cascades frog Rana cascadae
Bullfrog Rana catesbeiana
Green frog Rana clamitans
Columbia spotted frog Rana luteiventris
Mountain yellow-legged frog Rana muscosa
Leopard frog Rana pipiens
Spotted frog Rana pretiosa
Wood frog Rana sylvatica
Lowland leopard frog Rana yavapaiensis
Columbia torrent salamander Rhyacotriton kezeri
Rough-skinned newt Taricha granulosa
California newt Taricha torosa
B
E, H
E, H
E, H
E, H
E, H
E, H
B, H
B, H
B, H
E, H
E, H
E, H
E, H
E, H
B
E, H
E, H
E, H
E, H
E, H
E, H
E, H
E, H
E, H
E, H
E, H
E, H
E, H
E, H
E, H
a
X indicates that the species meets that criterion.
Rheophilica
X
X
X
X
Temperature
Troph.
Repr.
Cool
Cool
Cool
Cool
Cool
Cool
Cool
Cold
Cold
Cold
Cool
Cool
Cool
Cool
Cold
Warm
Cold
Warm
Cold
Cold
Warm
Warm
Cold
Cold
Warm
Warm
Cool
Warm
Cold
Cool
Cool
I
I
I
I
I
I
I
IP
IP
IP
I
I
I
I
I
IP
I
I
I
I
IP
I
I
I
I
I
I
I
IP
I
I
A15
F
F
F
F
F
F
A13
A13
A13
F
F
F
F
A13
A11
A11
A11
A11
A11
A11
A11
A11
A11
A11
A11
A11
A11
A13
A11
A11
Longlived
X
X
X
X
X
X
X
X
X
X
X
X
X
Tol.
value
Aira
1.0
5.0
4.0
5.0
5.0
5.0
5.0
1.0
1.0
1.3
6.0
6.0
6.0
6.0
0.9
10.0
2.1
5.0
0.9
0.0
6.6
5.0
1.0
1.0
7.5
1.0
5.0
5.0
1.0
0.3
0.0
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
T&Ea
X
X
X