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Development of an Index of Biotic Integrity for the MidAtlantic Highlands Region a
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Frank H. McCormick , Robert M. Hughes , Philip R. Kaufmann , David V. Peck , John L. c
Stoddard & Alan T. Herlihy
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U.S. Environmental Protection Agency, National Exposure Research Laboratory , 26 W. M. L. King Drive, Cincinnati, Ohio, 45268, USA b
Dynamac Inc. , 200 SW 35th Street, Corvallis, Oregon, 97333, USA
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U.S. Environmental Protection Agency , 200 SW 35th Street, Corvallis, Oregon, 97333, USA
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Oregon State University, c/o US Environmental Protection Agency , 200 SW 35th Street, Corvallis, Oregon, 97333, USA Published online: 09 Jan 2011.
To cite this article: Frank H. McCormick , Robert M. Hughes , Philip R. Kaufmann , David V. Peck , John L. Stoddard & Alan T. Herlihy (2001) Development of an Index of Biotic Integrity for the Mid-Atlantic Highlands Region, Transactions of the American Fisheries Society, 130:5, 857-877, DOI: 10.1577/1548-8659(2001)1302.0.CO;2 To link to this article: http://dx.doi.org/10.1577/1548-8659(2001)1302.0.CO;2
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Transactions of the American Fisheries Society 130:857–877, 2001 q Copyright by the American Fisheries Society 2001
Development of an Index of Biotic Integrity for the Mid-Atlantic Highlands Region FRANK H. MCCORMICK* U.S. Environmental Protection Agency, National Exposure Research Laboratory, 26 W. M. L. King Drive, Cincinnati, Ohio 45268, USA
ROBERT M. HUGHES Dynamac, Inc., 200 SW 35th Street, Corvallis, Oregon 97333, USA
PHILIP R. KAUFMANN, DAVID V. PECK,
AND
JOHN L. STODDARD
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U.S. Environmental Protection Agency, 200 SW 35th Street, Corvallis, Oregon 97333, USA
ALAN T. HERLIHY Oregon State University, c/o US Environmental Protection Agency, 200 SW 35th Street, Corvallis, Oregon 97333, USA Abstract.—From 1993 to 1996, fish assemblage data were collected from 309 wadeable streams in the U.S. Mid-Atlantic Highlands region as part of the U.S. Environmental Protection Agency’s Environmental Monitoring and Assessment Program. Stream sites were selected with a probabilistic sampling design that allowed regional estimates of stream condition. We examined responses of 58 fish assemblage metrics to physical, chemical, and landscape indicators of disturbance. Univariate and multivariate analyses of relationships among fish metrics, habitat integrity, and anthropogenic disturbance were used to develop a fish index of biotic integrity (IBI) for assessing stream condition in the entire region. Of 58 candidate metrics 9 were selected and scored continuously from 0 to 10; the resulting IBI was scaled so that it ranged from 0 to 100. Regional estimates of stream conditions showed that 27% of the stream length in the Mid-Atlantic Highlands had fish assemblages in good or excellent ecological condition. Of the total wadeable perennial stream length in the region 38% was fair and 14% was poor. There were insufficient data to calculate IBIs for 21% of the wadeable stream length in the Mid-Atlantic Highlands; all of these streams were small (watershed area #2 km2) and lacked sufficient sample size (,10 individuals) to calculate an IBI.
Fish species exhibit diverse morphological, ecological, and behavioral adaptations to their natural habitat and, thus, are particularly effective indicators of the condition of aquatic systems (Karr et al. 1986; Fausch et al. 1990; Simon and Lyons 1995). Human disturbance of streams and landscapes alters key attributes of aquatic ecosystems: water quality, habitat structure, hydrological regime, energy flow, and biological interactions (Karr and Dudley 1981). The index of biological integrity (IBI) was developed to assess the condition of water bodies by direct evaluation of biological attributes (Karr et al. 1986). The IBI is a composite index that integrates structural, ecological, trophic, and reproductive attributes of fish assemblages at multiple levels of organization * Corresponding author:
[email protected] Received April 14, 1999; accepted March 16, 2001
(Fausch et al. 1990). Originally developed for assessment of Midwestern U.S. warmwater streams, it has been modified for use in other regions and waters (Miller et al. 1988; Jordan et al. 1993; Simon and Lyons 1995; Lyons et al. 1996; Hughes and Oberdorff 1999), as well as for other taxa (Lenat 1993; Kerans and Karr 1994; DeShon 1995). Several authors have argued that the IBI must be modified when it is applied in different ecoregions (Fausch et al. 1984; Miller et al. 1988). In the Mid-Atlantic region, researchers have developed IBIs for specific ecoregions (Scott and Hall 1997; Roth et al. 1998; Smogor and Angermeier 1999) or applied it to specific systems (Leonard and Orth 1986). Our objective was to develop a single IBI for assessing the condition of fish assemblages in first-order to third-order streams throughout the upland ecoregions of the mid-Atlantic states.
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There has been a long history of human impact on the landscape, streams, and fish assemblages of the region (Denevan 1992). Streams in the highlands have been subjected to stresses from acid deposition, mining, logging, agriculture, and urban development (Raitz et al. 1984; Whitney 1994; Jones et al. 1997). Agriculture and clear-cutting of highland and valley forests exacerbated soil erosion and sedimentation (USDA 1996). Active and abandoned coal mining resulted in mine drainage that affected approximately 4,000 km of streams (Herlihy et al. 1990; USEPA 1995). Extensive areas of the Ridge, Blue Ridge, and Appalachian Plateau ecoregions have poorly buffered soils and steep slopes, which have also made streams draining these areas susceptible to acid precipitation (Herlihy et al. 1993). Brown trout Salmo trutta, rainbow trout Oncorhynchus mykiss, common carp Cyprinus carpio, and large warmwater species in the genera Micropterus, Lepomis, and Ameiurus were stocked in streams of the Mid-Atlantic Highlands by the U.S. Fish Commission and state agencies (Courtenay et al. 1986; Jenkins and Burkhead 1994). Hatcheries were established in the 1870s to culture trout and warmwater game fishes in response to the loss of native species and public demand for augmented sport fisheries. Other introductions, particularly those of forage fish, occurred to support sport fisheries or as bait bucket transfers (Nico and Fuller 1999). Nonindigenous species constitute as much as 33% of the fish fauna of the Potomac drainage and 48% of the fish species in the upper Kanawha (New) River drainage (Appendix 1; Hocutt et al. 1986; Jenkins and Burkhead 1994). The purpose of this research was to develop an index of biotic integrity for the Mid-Atlantic Highlands region of the United States that could be applied in assessing the condition of small, wadeable streams in the region. Methods Survey design.—During 1993–1996, teams of U.S. Environmental Protection Agency (USEPA), U.S. Fish and Wildlife Service, state, and contract personnel sampled 309 first-order through thirdorder (as defined by Strahler 1957; 1:100,000 map scale) wadeable streams as part of the USEPA’s Environmental Monitoring and Assessment Program (EMAP) project in the Mid-Atlantic Highlands (MAH) (Lazorchak et al. 1998b; Figure 1). The MAH extend northeast from northern North Carolina to the Catskill Mountains of New York and west from the Fall Line to the Western Alle-
gheny Plateau of eastern Ohio. Omernik (1987) subdivided the region into the Blue Ridge, Central Appalachian Plateau, Ridge and Valley, Northern Appalachian Plateau and Uplands, Western Allegheny Plateau, and Piedmont ecoregions. Stream sites were selected using a randomized systematic design with a spatial component (Overton et al. 1991; Herlihy et al. 2000). The sample population of streams in the region was delineated from digitized USGS topographic maps (1:100,000 scale). Sample probabilities were set so that roughly equal numbers of first-, second-, and third-order streams would be selected. Streams were sampled during a 12-week sampling period from April to July, corresponding to spring low flow conditions. Chemistry.—A 4-L cubitainer and four 60-mL syringes were filled in flowing water near the middle of the stream for analysis of major anions, cations, conductivity, and nutrient analyses (Herlihy 1998). Syringes were sealed with a Luer-lock valve to prevent gas exchange. All samples were placed on ice and sent overnight to an analytical laboratory. Syringe samples were analyzed for pH, dissolved inorganic carbon (DIC), and monomeric aluminum, and the cubitainer sample was split into aliquots and preserved within 48–72 h of collection. Major anions (sulfate, nitrate, chloride) were determined by ion chromatography, base cations by atomic absorption, and total N and P by persulfate oxidation and colorimetry. Detailed information on the analytical and preservation procedures for each analyte can be found in USEPA (1987). Physical habitat and riparian disturbance.— Physical habitat data were collected from longitudinal profiles and from 11 cross-sectional transects evenly spaced along the stream reaches sampled. Maximum (thalweg) depth was measured at 100 (150 for streams , 2.5 m wide) evenly-spaced points along the stream reach. The location and amount of woody debris, and habitat unit (e.g., riffle, pool) were recorded while measuring the thalweg. Transect data included channel dimensions (width, depth, bank angles), systematic substrate characterization, channel gradient, bearing (for calculating sinuosity), fish cover, riparian vegetation cover, and structure, and the occurrence and proximity of riparian human disturbances (e.g., roads, buildings, agriculture; Kaufmann and Robison 1998). This method, which required on average 3 h for a crew of two, was used at only 177 sites because of resource limitations and program considerations. A qualitative habitat assessment was performed at all sites using the Rapid
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FIGURE 1.—Sampling locations for the Mid-Atlantic Highlands region used in developing an index of biotic integrity. Sites from the Atlantic Coastal Plain are not shown.
Bioassessment Protocols (Barbour and Stribling 1991; Lazorchak et al. 1998a). Landscape characterization.—Landscape data were gathered from topographic maps and aerial photographic interpretation at the same 177 sites used for habitat structure (Herlihy et al. 1998; Bryce et al. 1999). For all catchments, we used summer Landsat Thematic Mapper (TM) data for
1991, 1992, and 1993. These data sets were referenced to Lambert Azimuthal coordinates. The general procedure was to form a mosaic of multiple summer TM scenes and classify them into 15 land-cover categories by using aerial photographs as reference data (Herlihy et al. 1998). Fish assemblages.—Fish were collected according to time and distance criteria using pulsed-DC
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backpack electrofishing equipment that we supplemented with seining (McCormick and Hughes 1998). The reach length sampled was equivalent to 40 times the mean channel wetted width at the midpoint of the site; the minimum distance was 150 m and maximum was 500 m (Lyons 1992; McCormick 1993, unpublished data). Sampling duration ranged from 45 to 180 min, depending on stream size and complexity. The objective was to collect a representative sample of the fish assemblage by methods designed to collect all except very rare species and provide an unbiased measure of the proportional abundances of species. Sport fish and easily recognized species were identified and released. Voucher specimens (up to 25) of smaller individuals of each species and unidentified specimens were retained for museum verification. Collections were archived at the National Museum of Natural History, Smithsonian Institution. We used regional literature references to classify adult fish into taxonomic and ecological categories for computation of metrics (Appendix 1; Jenkins and Burkhead 1994; Rohde et al. 1994; Simon 1999). We used analysis of variance (ANOVA) to test for ecoregional differences in richness metrics adjusted for catchment area. Finding no such differences, data from several ecoregions were aggregated. We excluded Atlantic Coastal Plain streams from further consideration because of the small sample size (N 5 3). Two data sets were used in the developing the IBI. One set (N 5 177) consisted of sites where quantitative habitat data were used for metric calibration. The resulting metrics and IBI were validated with a data set (N 5 119) that lacked quantitative habitat data. Because there are many ways to define reference conditions and each gives a different reference distribution, we used information from three different reference definitions to determine reference sites for use in setting scoring thresholds. The least restrictive criteria were based on chemical criteria and the mean score of 12 Rapid Bioassessment Protocol habitat measures (N 5 46 good geographic coverage); the moderately restrictive criteria incorporated chemical criteria, watershed land use, road density, and quantitative physical habitat filters (N 5 23 good geographic coverage); the most restrictive criteria included the moderately restrictive criteria described above, plus the watershed condition class (Bryce et al. 1999; N 5 12 restricted geographic coverage). Most of the metrics we selected were proposed by Karr (1981) and Karr et al. (1986) or modifi-
cations thereof (e.g., Barbour et al. 1995; Simon and Lyons 1995). We followed Karr (1981) and Karr et al. (1986) in limiting the classifications of species in an assemblage so that neither sensitive nor tolerant species contributed more than 10% of the regional ichthyofauna. Because too few representatives of darter, sucker, or sunfish species were found in any given stream, we replaced Karr’s ‘‘number of darter species’’ with the ‘‘number of benthic species’’ (including darters [Percidae], sculpins [Cottidae], and madtoms [Ictaluridae]) and replaced Karr’s ‘‘number of sucker species’’ and ‘‘number of sunfish species’’ with the ‘‘number of sensitive cyprinid species.’’ Similarly, given the paucity of green sunfish Lepomis cyanellus in our collections, we replaced Karr’s ‘‘percent of green sunfish’’ metric with the ‘‘proportion of individuals in tolerant taxa.’’ Metric screening.—We evaluated 58 candidate metrics in four categories: taxonomic, trophic, reproductive, and tolerance (variable names and descriptions are presented in Appendix 2). We did not include metrics on individual health (e.g., anomalies; Sanders et al. 1999) because anomalies were rarely encountered. In the evaluation process, which followed Hughes et al. (1998), we examined each metric for its scoring range, variability, responsiveness, and redundancy. Metrics were rejected if they failed a range test (i.e., their raw values ranged between 0 and 2 species) or a signal: noise test (ratio ,3, where signal was the variance among sites and noise was the variance among repeat visits [Kaufmann et al. 1999]). We used Spearman correlations and scatter plots (Hughes et al. 1998) to test the responsiveness of the remaining candidate metrics to physical habitat structure and water quality (pH; sulfate concentration; total nitrogen concentration; total phosphorus concentration; chloride concentration; percent sands and fine substrate; relative bed substrate stability; density of large woody debris; fish cover; indices of riparian and channel disturbance; and indices of channel, riparian, and watershed quality) and to test integrated measures of anthropogenic disturbance (a disturbance classification based on chemical signatures of mine drainage, acid rain, nutrients, etc., and the watershed condition class of Bryce et al. 1999). Proportional variables were arcsin-square root-transformed and tested for univariate normality. The distributions differed significantly from normality; however, Pvalues exceeded 0.01, and the plotted distributions appeared unimodal, with symmetric tails. These findings suggested that the effects of departures
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TABLE 1.—Metrics requiring calibration for watershed area and metrics rejected in evaluation process. See Appendix 2 for metric definitions and metrics rejected for lack of response to disturbance.
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Metrics requiring calibration for watershed area NUMNATSP NUMSPEC NATIVFAM NSBENT NSCOLU NSCATO NSCENT NSDART NSCYPR NREPROS NUMFISH PCARN PBENT PINSE PINVERT PATNG
Failed range test (raw scores 0, 1, or 2) NSANGU NSATHER NSCOTT NSDRUM NSESOX NSFUND NSGAMB NSICTA NSLAMP NSPERCO NSPPER NSSALM NSUMBR
Failed signal : noise test (among-site variance: Repeat sampling variance , 3) NTROPH PNEST
from univariate normality were not severe. To test for redundancy among metrics, we used Pearson’s Product Moment correlation and retained only one metric out of each pair, where r . 0.75. Metrics correlated with watershed area were corrected for the area effect as described below. All statistical analyses were conducted in PC-SAS for Windows, release 6.11 (SAS 1996). Adjustments for watershed area.—For metrics that showed strong correlation with watershed size, we followed the approach described by Urquhart (1982) and normalized them for a watershed size of 100 km2 as follows. We calculated the regression equation of the metrics with watershed area (log10 watershed area in km2) for the 46 least restrictive reference sites. We then applied that reference regression equation to all sites and calculated their residuals. Next, we determined the expected value for reference data at a standardized watershed area of 100 km2 and applied this constant to residuals. This resulted in all variables having nonnegative values. Responsiveness of the index of biotic integrity (IBI).—We evaluated the responsiveness of the IBI to stressors and aggregate measures that represented general disturbance gradients by plotting it against chemical and physical habitat quality variables. We evaluated the ability of the IBI to discriminate known disturbance gradients using reference and nonreference data sets. We assessed fish sampling and temporal variance within the sampling period and across years by comparing IBI scores from sites that were revisited in the same
Failed redundancy test (Pearson correlation coefficient . 0.75) PCOLD PBCLN PTREPRO
Failed calibration test NUMFISH
year with those that were revisited in successive years. Stream condition and IBI.—We used the distribution of IBI scores at reference sites to set thresholds between good, fair, and poor IBI scores. Scores exceeding the mean of the 25th percentiles for reference sites were identified as having ‘‘good’’ biotic integrity, scores between the 10th and 25th percentile for reference sites were identified as being in ‘‘fair’’ condition, and scores below the mean of the10th percentiles for reference sites were in ‘‘poor’’ condition. We used a weighted frequency distribution to produce an estimate of the total length of the streams in the region achieving a particular condition (Herlihy et al. 2000). Results We rejected 13 metrics because they failed to pass the range test, 2 failed the signal to noise test, and 3 failed the redundancy test (Table 1). We rejected 30 metrics with nonsignificant correlations with anthropogenic impacts (P . 0.05; r2 , 0.20; Appendix 2). One metric (NUMFISH) was rejected because it remained correlated with watershed area even after adjusting for area. Presumably, the persistent correlation was because of other natural size-related variables such as stream width, depth, and pool size. Although it did not respond to land-use disturbance, we retained the nonindigenous individuals metric (ALIEN) because it is directly responsive to the disturbance of introduced species. Based on the metric screen-
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TABLE 2.—Spearman rank correlation coefficients (r . 0.15, P , 0.01) between fish assemblage metric variables and chemical and habitat disturbance variables. Metrics were also strongly correlated with abiotic variables naturally associated with stream size (mean width, mean depth, channel slope, residual mean depth, habitat volume indices, and stream power); correlations with these variables are not shown. Derivation of habitat quality and disturbance indices is described in Kaufmann et al. (1999).
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Variables Chemical disturbance pH Acid neutralizing capacity Nitrate Sulfate Manganese Iron Turbidity Ammonium Total nitrogen Total phosphorus Chloride Habitat disturbance and quality Riparian canopy density Riparian disturbance (all types) Riparian disturbance (agricultural) Riparian disturbance index Sand and fines (%) Relative streambed stability Substrate quality index Areal proportion of natural types of fish cover Channel disturbance index Channel 1 riparian disturbance index Channel 1 riparian habitat quality index Watershed forest cover Watershed quality index Watershed 1 riparian quality index Watershed 1 riparian 1 channel habitat quality index
NSCYPR 0.33 0.22 0.15
NSBENT
PCOTTID NSINTOL
PEXOT PPISCINV PMACRO PGRAVEL 0.18 0.15
0.32 0.17
0.27 20.26 20.25 20.27 20.26 20.23 20.23
20.16
20.18
0.20
0.25
0.21
0.20
20.20
20.25
20.20
0.24 0.19 0.25
20.24 20.17 20.20
20.19
0.25 0.15
0.17 0.31 0.24 0.33
0.20 0.18 20.17
20.20 20.23
0.26 20.18
PTOLE
0.20 0.21 20.17
0.16
20.17
20.16
0.15
0.19 0.25
20.15 20.17 20.16
20.20
0.17 0.17 0.27
0.23
20.16
0.23
20.16 20.16 20.15
0.34
0.44
ing process, we selected nine metrics, each significantly correlated (P , 0.001; r . 0.15) to one or more chemical or habitat disturbance variables, from which to calculate an IBI (Table 2). Three of the metrics in the final IBI list (number of native cyprinid species, number of native benthic habitat species, and number of intolerant species) were adjusted for watershed area. Metric Descriptions The final suite of metrics is described below; the variable names (refer to Appendix 2) of the unscored and scored metrics are in parentheses. Number of native cyprinid species (NSCYPR, CYPRINID).—This metric, excluding tolerant taxa
0.19
0.15 20.15
20.27 20.30
20.24
20.26
20.28
20.26
(e.g., blacknose dace Rhinichthys atratulus, creek chub Semotilus atromaculatus) was modified from Karr’s (1981) number of sucker and sunfish species. The number of cyprinid species included in this metric was expected to decline with impairment of watershed condition class. The number of cyprinid species was correlated with the absence of acidification (i.e., high pH and acid neutralizing capacity [ANC] values; Table 2). However, cyprinid species richness was also positively correlated with higher levels of riparian disturbance and negatively correlated with canopy density, the amount of natural fish cover, and indices of watershed and riparian quality. Number of native benthic species (NSBENT,
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BENTHIC).—This metric was modified from Karr’s (1981) Darter Species Richness metric. It measures the habitat quality (substrate) for bottom dwelling species and included darters, sculpins, benthic minnows (excluding blacknose dace), suckers (excluding white suckers Catastomus commersoni), madtoms, and lampreys (Miller et al.1988; Simon and Lyons 1995). The number of benthic species was expected to decline in response to loss or alteration of benthic habitat (e.g., sedimentation or quality of substrate). Like cyprind species richess, benthic species richness was positively correlated with the absence of acidification and negatively correlated with canopy density, the amount of natural fish cover, and indices of watershed and riparian quality (Table 2). Proportion of individuals in family Cottidae (PCOTTID, COTTID).—This metric was modified from Mundahl and Simon (1999) and Maret (1999). The proportion of individuals represented by cottids was expected to decline with degradation of all habitat measures and increases in nutrient loading. Negative correlations were obtained for variables associated with nutrient loading (ammonium, total phosphorus), increased human activity in the watershed (chloride), and turbidity (Table 2). The unscored metric (PCOTTID) was negatively correlated with increasing proportions of fine sediments and positively correlated with indices of substrate quality and indices combining aspects of channel habitat, riparian habitat, and watershed quality. Sensitive species richness (NSINTOL, INTOL).— This metric was modified from Karr’s (1981) intolerant species metric by Hughes et al. (1998). It represented species likely to be the first to disappear following anthropogenic disturbance and the last to recover following restoration. We expected it to be most useful at discriminating among reaches with higher quality assemblages and to decline with impairment of water quality, channel habitat, and watershed condition. Sensitive species richness was negatively correlated with increased nutrients (total phosphorus), turbidity, human activity in the watershed (chloride), and acid mine drainage (sulfate; Table 2). Positive correlations were obtained with indices of substrate quality and indices combining aspects of riparian habitat quality, channel habitat quality, and watershed quality. Proportion of tolerant individuals (PTOLE, TOLRNT).—This metric, modified from Karr’s (1981) percent green sunfish metric, evaluated the tendency of one or more disturbance-tolerant species to predominate the assemblage (Miller et
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al.1988; Simon and Lyons 1995; Hughes and Oberdorff 1999). The proportion of tolerant individuals was expected to increase with degraded water quality, channel habitat, and watershed condition. Positive correlations were obtained with chemical variables associated with increased acid mine drainage (sulfate), increased turbidity, increased nutrients (ammonium, total phosphorus), and general human activity (chloride; Table 2). Negative correlations were obtained with increases fish cover and with various indices of channel, riparian, and watershed quality. Proportion of nonindigenous individuals (PEXOT, ALIEN).—This metric measured the degree to which a site is affected by biological pollution (Miller et al. 1988; Simon and Lyons 1995). Nonindigenous species are themselves a direct disturbance because they may eat, compete with, or hybridize with species that are not adapted to coexist with them. We retained nonindigenous taxa in the calculation of proportional metrics but excluded them from the richness metrics. In this way, they did not artificially inflate the desirable richness (diversity) metrics but still reflected the functional capacity of the respective habitat, reproductive, and trophic categories. Nonindigenous species may have adversely affected the number of native individuals in a particular habitat, reproductive, or trophic guild and potentially excluded other native taxa (Ross 1991; Angermeier and Winston 1998). They include common carp, brown trout, rainbow trout, many sunfishes and black bass species and, increasingly, many baitfish (Litvak and Mandrak 1993; Nico and Fuller 1999). We did not expect responses to specific chemical or habitat variables related to disturbance (or quality), but obtained positive correlations with pH and ANC (suggesting the absence of acidification) and a negative correlation with an index of overall watershed quality (Table 2). Proportion of invertivore–piscivore individuals (PPISCINV, PISCINV).—This metric included species that are piscivores or invertivore–piscivores as adults (black bass, esocids, several sunfishes, American eel Anguilla rostrata) and is a common substitute for Karr’s (1981) percent carnivore metric (Miller et al. 1988; Simon and Lyons 1995). It estimated the ability of the food chain to support fish that prey largely on other fish, vertebrates, or large macrobenthos. The proportion of invertivore–piscivores was expected to decline with increased habitat degradation. The unscored metric variable (PPISCINV) was negatively correlated with increased turbidity, canopy density,
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TABLE 3.—Means (ranges) of fish assemblage variables by aggregated ecoregion (plateaus 5 northern Appalachian 1 central Appalachian 1 western Allegheny plateaus; ridge 5 ridges of Ridge and Valley ecoregion 1 Blue Ridge; valley 5 valleys of Ridge and Valley ecoregion). No significant differences (P . 0.05) were found as determined by a general linear model analysis of variance with a Student–Newman–Keuls’ test for differences among means. Variables are identified in Appendix 2. Variable
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NSBENT NSCYPR NSINTOL PCOTTID PGRAVEL PPISCINV PMACRO PTOLE PEXOT
Plateaus N 5 53
Ridge N 5 78
Valley N 5 145
Piedmont N 5 16
2.13 (0–13) 1.09 (0–7) 0.65 (0–5) 0.11 (0.0–0.69) 0.54 (0.0–1.0) 0.29 (0.0–1.0) 0.04 (0.0–0.43) 0.53 (0.0–1.0) 0.09 (0.0–0.95)
2.86 (0–9) 1.61 (0–7) 1.01 (0–5) 0.12 (0.0–0.66) 0.72 (0.29–1.0) 0.18 (0.0–1.0) 0.06 (0.0–0.88) 0.48 (0.0–1.0) 0.07 (0.0–0.43)
2.52 (0–12) 1.81 (0–8) 0.60 (0–6) 0.13 (0.0–0.88) 0.65 (0.0–1.0) 0.18 (0.0–1.0) 0.07 (0.0–0.55) 0.56 (0.0–1.0) 0.07 (0.0–0.82)
2.88 (0–6) 1.93 (1–6) 0.87 (0–3) 0.01 (0.0–0.1) 0.69 (0.28–0.97) 0.10 (0.0–0.35) 0.03 (0.0–0.18) 0.50 (0.02–0.99) 0.05 (0.0–0.24)
and agricultural disturbance in the riparian zone, and positively correlated with increased fish cover and an index combining aspects of channel and riparian habitat quality (Table 2). Proportion of macro-omnivores (PMACRO, MACRO).—This metric was a measure of the dominance of trophic guilds by individuals that could eat either plant or animal material. Omnivores are trophic generalists; at least 25% of their diet is animal and at least 25% is plant. Ecomorphology (mouth gape, dentition, gut length) were also used to classify a species’ dietary niche. We distinguished macro-omnivores from omnivores on small food items such as microalgae and bacteria. The proportion of macro-omnivores was expected to increase with increased nutrient loading and habitat alterations that might shift the availability of food resources types in the system. Positive correlations were obtained with increased nutrients (nitrate, ammonium, total nitrogen, and total phosphorus), human activity (chloride), sedimentation (percent sand and fines), and relative bed stability (i.e., substrate types such as large boulders or bedrock that are larger than the stream can move, and, thus, could support a permanent periphyton assemblage; Table 2). The proportion of macro-omnivores was negatively correlated with increased substrate quality (Table 2). Proportion of gravel spawning species (PGRAVEL, GRAVEL).—This metric replaced the percent simple lithophils metric of Ohio EPA (1987) and Rabeni and Smale (1995). It consisted of species that are dependent on clean gravel for reproductive success. The proportion of gravel-spawning species was expected to decline with sedimentation, substrate quality, or degraded channel habitat. Positive correlations were obtained with increased bed
stability and with an index of channel disturbance (Table 2). Metric and IBI Scoring The ANOVA revealed no significant differences in unscored metric values across ecoregions for the nine selected metrics (Table 3). Therefore, scoring criteria were based on univariate distributions for the entire MAH region. Metric scoring was based on distributions of reference and nonreference site scores in the calibration data set (Table 4). Positive scoring metrics (which declined with increasing habitat degradation or disturbance) were scored 0–10 points: 0 points for values less than the 5th percentile of nonreference sites and 10 points for values greater than the 50th percentile of high-quality reference sites. Negative scoring metrics (which increased with increasing habitat degradation or disturbance) were scored 0–10 points: 0 points for values greater than the 90th percentile of nonreference sites and 10 points for values less than the 50th percentile of moderately restrictive reference sites. These percentiles were chosen to maximize the discrimination among sites for each metric. Metric scores were linearly interpolated between 0 and 10. We felt continuous scoring over the individual metric ranges of 0–10 led to a more precise index than traditional methods (Hughes et al. 1998). To scale the index from 0 to 100 points, we summed the IBI score of the individual metric scores for each of the nine metrics times 1.11. Sites with Low Fish Abundance To determine if there was a size below which small streams might not be expected to have fish, we plotted the number of fish caught against
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DEVELOPMENT OF AN INDEX OF BIOTIC INTEGRITY
TABLE 4.—Metric percentiles for moderately restrictive reference sites (N 5 23) and nonreference sites (N 5 146) used for metric calibration. The three richness metrics (shown in italics) are adjusted for watershed area. Final index of biotic integrity metric names are in parentheses. Reference sites Metric variable Positive scoring NSINTOL (INTOL) NSCYPR (CYPRINID) NSBENT (BENTHIC) PCOTTID (COTTID) PGRAVEL (GRAVEL) PPISCINV (PISCINV) Negative scoring PMACRO (MACRO) PTOLE (TOLRNT) PEXOT (ALIEN)
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a
Nonreference sites
10th
25th
50th
75th
90th
10th
25th
50th
75th
90th
0.66 4.37 3.21 0.00 0.43 0.00
1.17 5.07 4.59 0.00 0.55 0.00
1.51 6.24 5.35 0.07 0.72 0.09
2.17 7.62 6.71 0.24 0.86 0.18
2.78 8.82 7.21 0.36 0.92 0.52
0.25 3.09 2.57 0.00 0.34 0.00
0.51 4.57 3.76 0.00 0.48 0.00
1.09 6.84 4.82 0.00 0.67 0.03
1.48 8.11 6.02 0.15 0.82 0.12
2.32 9.86 7.54 0.34 0.97 0.27
0.00 0.03 0.00
0.00 0.12 0.00
0.00a 0.28 0.00a
0.03 0.53 0.08
0.07 0.87 0.13
0.00 0.09 0.00
0.00 0.26 0.00
0.02 0.53 0.02
0.09 0.74 0.09
0.16 0.97 0.24
Actual value, 0.002.
QVOLX, an index of stream habitat volume incorporating residual depth, mean width, mean cross-sectional area, and percentage of dry channel length. By plotting the watershed area against the habitat volume, we determined the drainage area and attendant stream volume that would reliably support fish. We found a minimum value for this index of 0.4, below which no streams in the sample had fish present (Figure 2). As a result, we did not calculate an IBI for streams in watersheds less than 2 km2 and in which the number of individuals was less than 10. If the total number of fish caught was less than 10 individuals and the watershed area was 2 km2 or more, then the IBI was set to 0.
FIGURE 2.—Number of individuals versus habitat volume index (top panel) and habitat volume index versus watershed area (bottom panel), showing the relationship between small watershed size, reduced habitat volume, and number of individuals. The plots suggest that fish are not likely to be found in streams with a watershed area of 2 km2or less.
Relationship of IBI to Physical and Chemical Habitat The IBI scores decreased with increasing chloride and increased with increasing forest cover, channel habitat quality, watershed quality, watershed 1 riparian quality, and watershed 1 riparian 1 channel quality (Figure 3) and demonstrated responsiveness to three separate measures of watershed condition (Figure 4). Though small streams tended to have slightly lower IBI scores than larger streams, the correlation with watershed area was not significant (r 5 0.06; P 5 0.98). There were no significant differences in mean IBI scores among ecoregions (one-way ANOVA, F 5 3.56; P . 0.05) or between highland and lowland streams (one-way ANOVA, F 5 3.52; P . 0.05). The IBI was also temporally stable; index scores from 35 site visits within or between years were significantly related (within-year r2 5 0.78, between-year r2 5 0.74; P , 0.05), most of the variation being attributable to differences in sites rather than repeat visits to the same sites (Figure 5).
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FIGURE 3.—Plots of the index of biotic integrity (IBI) versus representative chemical and physical habitat-quality variables. Panels are arranged in increasing order of comprehensiveness of habitat measures. Five sites with an
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Assessment of Condition The IBI scores exceeding the 75th percentile for reference sites (IBI . 82) were classified as having ‘‘excellent’’ biotic integrity and scores between the 75th and 25th percentiles (72 , IBI # 82) were identified as having ‘‘good’’ biotic integrity (Figure 6). Scores between the 5th and 25th percentile for reference sites (IBI 5 56–72) were identified as being in ‘‘fair’’ condition, and scores below the 5th percentile for reference sites (IBI , 56) were defined as in ‘‘poor’’ condition. The 313 stream reaches surveyed represented 184,383 stream kilometers in the Mid-Atlantic Highlands region. Thirty-four sample sites (11,131 km) were dry. Using the above criteria, only 27% of the stream length had excellent (5%) or good (22%), 38% had fair, and 14% had poor fish assemblages (Table 5). The highest proportion of streams in excellent condition were in the Blue Ridge and ridges of the Ridge and Valley ecoregion (1.8%), whereas the plateaus had the highest proportion of streams in fair (13.3%) or poor (6.5%) condition. Of the wadeable stream length in the region, 21% was dry or too small to support fish assemblages. Discussion The similarity in fish assemblage variables across ecoregions was probably a reflection of the size of our watersheds (most were ,500 km2), the fact that these were predominantly upland streams (Bailey 1980; Omernik 1995), and the historical biogeography of the fish fauna (Hocutt et al. 1986). In streams of this size, local physical dimensions may be more powerful determinants of assemblage structure and function than broad physiographic features because the inherent local structure overwhelms ecoregional classifications (Vannote et al. 1980; Newall and Magnuson 1999; Hawkins et al. 2000). Rahel and Hubert (1991) found that the strong longitudinal structure they observed in fish assemblages in high gradient streams was related primarily to temperature, but stream width, depth, discharge, and pool development were important factors. Lyons (1989) found that although Wisconsin fish assemblages showed regional patterns, they were more responsive to channel gradient and temperature than to landscape features associated with ecoregions. Paller (1994) observed similar
FIGURE 4.—Responsiveness of the index of biotic integrity to anthropogenic disturbance, based on categories determined by three tests for reference criteria: (A) water quality and Rapid Bioassessment Protocols habitat, (B) water quality and quantitative physical habitat (Kaufmann et al. 1999), and (C) Bryce et al.’s (1999) measure of watershed condition.
←
IBI score of 0 are not plotted because they were either acidic (pH , 5.0) or had high sulfate levels indicative of mine drainage impacts. One site with an IBI 5 0 was excluded because it was only slightly larger than the cutoff for watershed area (#2 km2) and had lower than predicted habitat volume index values.
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FIGURE 6.—Box plot showing the approach for determining numerical values for narrative descriptions of fish biotic integrity. Scores above the mean of the 75th percentiles were described as ‘‘excellent.’’ Scores between the 75th and 25th percentiles for the reference classifications represented fish assemblages in ‘‘good’’ condition. Scores below the mean of the 5th percentiles for the reference classifications represented fish assemblages in ‘‘poor’’ condition. Intermediate scores represented sites in ‘‘fair’’ condition. The least restrictive criteria (low) were based on chemical and Rapid Bioassessment Protocols habitat filters (N 5 27), the moderately restrictive criteria (Medium) incorporated quantitative habitat filters (N 5 23), and the most restrictive criteria (High) included watershed condition class (Bryce et al. 1999).
FIGURE 5.—Plot of repeat visits within and among years for the index of biotic integrity. Solid diagonal line represents the 1:1 relationship. Dashed line is the result of the linear regression of all data.
variation of richness and trophic structure with width, depth, and volume across stream order in Coastal Plain streams. Osborne et al. (1992) and Osborne and Wiley (1992) suggested that the influence of stream order and stream location in a drainage network on increasing species richness necessitated different metric expectations for the different segments of a drainage network. In our analyses, the strongest correlations between IBI metrics and environmental variables were with those measures that described the physical dimensions or geomorphological features of the streams (e.g., derivatives of
thalweg depth profiles, wetted width, sinuosity, slope, and habitat complexity). Although Angermeier et al. (2000) found ecoregional and basin differences in the Mid-Atlantic Highlands sufficient to create separate multimetric indices for dif-
TABLE 5.—Stream condition in percent of stream kilometers and regional population estimates (in km) in the MidAtlantic Highlands. Estimates are derived from the regional probability sample. The 90% confidence intervals for each estimate are shown in parentheses. Aggregated ecoregions were Plateaus 5 northern Appalachian 1 central Appalachian 1 western Allegheny plateaus, Ridge 5 ridges of Ridge and Valley ecoregion 1 Blue Ridge, Valley 5 valleys of Ridge and Valley ecoregion; IBI 5 index of biotic integrity.
Characteristic IBI score class Excellent Good Fair Poor Not assessed Population length (km) Number of probability sites Total number of sites in study
Piedmont
Plateaus
Ridge
Valley
MidAtlantic Highlands
1.6 (0–4.1) 46 (18–73) 32 (5.6–58) 8.0 (0-17) 13 (0–33)
3.3 (0–7.8) 9.1 (2.8–15) 43 (28–57) 21 (10–31) 25 (10–39)
12 (1.7–23) 9.3 (2.9–16) 41 (25–57) 4.8 (0.8–8.8) 32 (15–50)
8.0 (3.3–13) 16 (10–23) 38 (29–47) 21 (13–28) 17 (9.1–24)
5.0 (2.2–7.7) 22 (12–32) 38 (28–48) 14 (9.0–19) 21 (12–30)
52,300
61,500
26,900
26,400
167,200
15
50
58
109
232
17
58
86
148
309
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ferent ecoregions and basins, McCormick et al. (2000) found no significant differences in fish assemblage structure among ecoregions or basins in the region. Explanations for these different conclusions may reside in the disparities in sampling methods and periods and stream sizes between the two studies. Finding no significant regional or basin differences among fish assemblages in most of the state, the Ohio EPA developed a single IBI for use in Ohio (Yoder and Rankin 1998). The development of a regionally applicable IBI facilitates comparisons of environmental conditions across political (i.e., state) boundaries and integrates biological assessment at the watershed scale. Our IBI was not as strongly correlated with land use as reported by Wang et al. (1997) (r 5 0.69 versus r 5 0.23–0.29 for our data). The residual effects of historical clear-cutting may have affected the hydrological regime, habitat complexity, and woody debris retention in the streams in our study (Poff et al. 1997). These factors may account for the impairment of the fish assemblages in these streams (Horwitz 1978; Pearsons et al. 1992; Grossman et al. 1995). Harding et al. (1998) found that streams in watersheds with a high proportion of forest cover may show the effects of agricultural land use that occurred 40 years earlier. Threshold levels of catchment disturbance (e.g., by agriculture) may have to be exceeded for declines in IBI scores to occur (Wang et al. 1997). Wang et al. (1997) also found that some sites in highly disturbed watersheds still had good IBI and habitat scores because of limited in-stream impacts. We believe that the generally impaired condition of fish assemblages in Mid-Atlantic Highland streams probably reflect the long and pervasive history of human impact in the region and the multiple stressors currently affecting stream biota. Our ability to account for the effect of stream morphology on species richness and fish abundance (and thus reveal responses to disturbance not correlated with increased habitat complexity and size) was hampered by the lack of quantitative physical habitat data from 40% of our sites for which only the Rapid Bioassessment Protocols were used. Imprecision in the individual metrics and the IBI and variance related to the spatial heterogeneity of the region may have further reduced the strength of the correlations with water quality, habitat structure, or landscape variables. Karr and Chu (1999) warned that probability-based sampling may not be suited to development of multimetric indices because the broad range of con-
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ditions encountered in a probability-based sampling program may obscure the response of fish assemblages to different types and intensities of anthropogenic disturbance. We conclude that numerous and wide-ranging disturbance gradients are revealed by probability samples (Table 2), and these data represent an ideal source of data for metric evaluation and IBI development. Schlosser (1990) suggested that the high temporal variability of fish assemblages in upstream areas may limit the usefulness of fish assemblage indices to distinguish among subtle changes in water quality, whether they are due to anthropogenic or natural causes. By using physical habitat, landscape, and water quality data to screen sites to identify gradients of physical and chemical habitat quality in our study, we were able to identify fish assemblage variables that were strongly correlated with measures of anthropogenic disturbance. We found fish assemblage variables that responded to degraded watershed and riparian quality and increased embeddedness and siltation and water quality variables that reflect human impact; our IBI also was strongly correlated with an aggregate (multivariate) measure of habitat quality. Standardized, consistent fish-assemblage sampling methods, coupled with quantitative physical, chemical, and landscape data, allowed us to develop a sensitive and regionally applicable index of fish assemblage integrity. Acknowledgments This research was supported by the U.S. Environmental Protection Agency under the auspices of the Environmental Monitoring and Assessment Program and through cooperative agreement CR821738 with Oregon State University and contract 68-C6-0005 to Dynamac. We thank the many people who conducted the field sampling, as well as those who provided technical expertise and support for verification of species identifications, database management, and statistical support. We are particularly grateful to S. Paulsen for management support, C. Burch-Johnson, S. Bryce, and B. Rosenbaum for geographical expertise, R. Hjort for database management, and M. Schubauer-Berigan for statistical advice. B. Harvey, W. Matthews, P. Angermeier, M. Scott, W. Davis, and an anonymous reviewer provided constructive criticism of an earlier draft. References Angermeier, P. L., and M. Winston. 1998. Local vs. regional influences on local diversity in stream fishes of Virginia. Ecology 79:911–927.
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Angermeier, P. L., R. A. Smogor, and J. L. Stauffer. 2000. Regional frameworks, and candidate metrics for assessing biotic integrity in Mid-Atlantic Highland streams. Transactions of the American Fisheries Society 129:962–981. Bailey, R. G. 1980. Description of the ecoregions of the United States. US Department of Agriculture, Miscellaneous Publication No. 1391, Boise, Idaho. Barbour, M. T., and J. B. Stribling. 1991. Use of habitat assessment in evaluating the biological integrity of stream communities. Pages 25–38 in G. Gibson, editor. Biological criteria: research and regulation, proceedings of a symposium, 12–13 December, 1990, Arlington, Virginia. EPA-440/5–91/005. U.S. Environmental Protection Agency, Office of Water, Washington, D.C. Barbour, M. T., J. B. Stribling, and J. R. Karr. 1995. Multimetric approach for establishing biocriteria and measuring biological condition. Pages 63–77 in W. S. Davis and T. P. Simon, editors. Biological assessment and criteria: Tools for water resource planning and decision making. Lewis Publishers, Boca Raton, Florida. Bryce, S. A., D. P. Larsen, R. M. Hughes, and P. R. Kaufmann. 1999. Assessing the relative risks to aquatic ecosystems in the Mid-Appalachian region of the United States. Journal of the American Water Resources Association 35:23–36. Courtenay, W. R., D. A. Hensley, J. N. Taylor, and J. A. McCann. 1986. Distribution of exotic fishes in North America. Pages 675–698 in C. H. Hocutt and E. O. Wiley, editors. The Zoogeography of North American Freshwater Fishes. John Wiley and Sons, Inc., New York. Denevan, W. M. 1992. The pristine myth: The landscape of the Americas in 1492. Annals of the Association of American Geographers 82:369–385. DeShon, J. E. 1995. Development and application of the invertebrate assemblage index (ICI). Pages 217– 243 in W. S. Davis and T. P. Simon, editors. Biological assessment and criteria: Tools for water resource planning and decision making. Lewis Publishers, Boca Raton, Florida. Fausch, K. D., J. R. Karr, and P. R. Yant. 1984. Regional application of an index of biotic integrity based on stream fish communities. Transactions of the American Fisheries Society 113:39–55. Fausch, K. D., J. Lyons, J. R. Karr, and P. L. Angermeier. 1990. Fish communities as indicators of environmental degradation. Pages 123–144 in S. M. Adams, editor. Biological indicators of stress in fish. American Fisheries Society, Symposium 8, Bethesda, Maryland. Grossman, G. D., J. Hill, and J. T. Petty. 1995. Observations on habitat structure, population regulation, and habitat use with respect to evolutionarily significant units: a landscape perspective for lotic systems. Pages 381–391 in J. L. Nielsen, editor. Evolution and the Aquatic Ecosystem: Defining Unique Units in Population Conservation. American Fisheries Society, Symposium 17, Bethesda, Maryland. Harding, J. S., E. F. Benfield, P. V. Bolstad, G. S. Helf-
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ical Criteria for the Protection of Aquatic Life, volume 2. Users manual for biological field assessment of Ohio surface waters. Division of Water Quality Monitoring and Assessment, Columbus, Ohio. Omernik, J. M. 1987. Ecoregions of the conterminous United States. Annals of the Association of American Geographers 77:118–125. Omernik, J. M. 1995. Ecoregions: A framework for managing ecosystems. The George Wright Forum 12:35–50. Osborne, L. L., and M. J. Wiley. 1992. Influence of tributary spatial position on the structure of warmwater fish communities. Canadian Journal of Fisheries and Aquatic Sciences 49:671–681. Osborne, L. L, S. L. Kohler, P. B. Bayley, D. M. Day, W. A. Bertrand, M. J. Wiley, and R. Sauer. 1992. Influence of stream location in a drainage network on the index of biotic integrity. Transactions of the American Fisheries Society. 121:635–643. Overton, W. S., D. L. Stevens, and D. White. 1991. Design report for EMAP, Environmental Monitoring and Assessment Program. EPA/600/3–91/ 053. U.S. Environmental Protection Agency, Corvallis, Oregon. Paller, M. H. 1994. Relationships between fish assemblage structure and stream order in South Carolina Coastal Plain streams. Transactions of the American Fisheries Society 123:150–161. Pearsons, T. N., H. W. Li, and G. A. Lamberti. 1992. Influence of habitat complexity on resistence to flooding and resilience of stream fish assemblages. Transactions of the American Fisheries Society 121:427–436. Poff, N. L., J. D. Allen, M. B. Bain, J. R. Karr, K. L. Prestegaard, B. D. Richter, R. E. Sparks, and J. C. Stromberg. 1997. The natural flow regime: a paradigm for river conservation and restoration. BioScience 47:769–784. Rabeni, C. F., and M. A. Smale. 1995. Effects of siltation on stream fishes and the potential mitigating role of the buffering riparian vegetation. Hydrobiologia 303:211–219. Rahel, F. J., and W. A. Hubert. 1991. Fish assemblages and habitat gradients in a Rocky Mountain-Great Plains stream: biotic zonation and additive patterns of community change. Transactions of the American Fisheries Society 120:319–332. Raitz, K. B., R. Ulack, and T. R. Leinbach. 1984. Appalachia: a regional geography. Westview Press, Boulder, Colorado. Rohde, F. C., R. G. Arndt, D. G. Lindquist, and J. F. Parnell. 1994. Freshwater fishes of the Carolinas, Virginia, Maryland and Delaware. University of North Carolina Press, Chapel Hill, North Carolina. Ross, S. T. 1991. Mechanisms structuring stream fish assemblages: are there lessons from introduced species? Environmental Biology of Fishes 30:359–368. Roth, N., and eight coauthors. 1998. Maryland Biological Stream Survey: Development of a fish Index of Biotic Integrity. Environmental Monitoring and Assessment 51:89–106. SAS. 1996. SAS/STAT users guide. SAS Institute, Cary, North Carolina. Sanders, R. E., R. J. Miller, C. O. Yoder, and E. T. Rankin. 1999. The use of external deformities, erosion, lesions, and tumors (DELT anomalies) in fish assemblages for characterizing aquatic resources: A
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Appendix 1: Metric Classifications TABLE A1.1.—Metric classifications of fish species collected during the 1993–1994 Environmental Monitoring and Assessment Program streams project in the Mid-Atlantic Highlands region. Species introductions are designated by abbreviations for each drainage: A 5 all Atlantic drainages, J 5 James, P 5 Potomac, R 5 Roanoke, H 5 Rappahannock, S 5 Susquehanna, Y 5 York, G 5 Allegheny, K 5 Kanawha, M 5 Monongahela, N 5 New, T 5 Tennessee, X 5 introduced throughout the region. Green sunfish Lepomis gulosus is introduced to Atlantic drainages in the Ridge and Valley Province. Autecological information is designated for trophic guild classification (IN 5 invertivore, IP 5 invertivore–piscivore, OH 5 omnivore–herbivore), habitat preference (CO 5 water column species, BE 5 benthic species), reproductive guild (AT 5 egg attacher, BS 5 broadcast spawner, CG 5 clean gravel spawner, NA 5 nest association, NG 5 nest guarding, VI 5 viviparous), and tolerance (INT 5 intolerant, TOL 5 tolerant).
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Species American eel Brook silverside River carpsucker White sucker Creek chubsucker Northern hog sucker Roanoke hog sucker Bigeye jumprock Black jumprock Black redhorse Golden redhorse Rustyside sucker Shorthead redhorse Torrent sucker Rock bass Flier Bluespotted sunfish Redbreast sunfish Green sunfish Pumpkinseed Warmouth Bluegill Longear sunfish Redear sunfish Smallmouth bass Spotted bass Largemouth bass White crappie Black crappie Black sculpin Mottled sculpin Banded sculpin Slimy sculpin Potomac sculpin Central stoneroller Goldfish Redside dace Rosyside dace Satinfin shiner Common carp Whitetail shiner Spotfin shiner Steelcolor shiner Blotched chub Tonguetied minnow Cutlips minnow Eastern silvery minnow White shiner Warpaint shiner Crescent shiner Striped shiner Common shiner Rosefin shiner
Anguilla rostrata Labidesthes sicculus Carpiodes carpio Catostomus commersoni Erimyzon oblongus Hypentelium nigricans Hypentelium roanokense Moxostoma ariommum Moxostoma cervinum Moxostoma duquesnei Moxostoma erythrurum Moxostoma hamiltoni Moxostoma macrolepidotum Moxostoma rhothoecum Ambloplites rupestris Centrarchus macropterus Enneacanthus gloriosus Lepomis auritus Lepomis cyanellus Lepomis gibbosus Lepomis gulosus Lepomis macrochirus Lepomis megalotis Lepomis microlophus Micropterus dolomieu Micropterus punctulatus Micropterus salmoides Pomoxis annularis Pomoxis nigromaculatus Cottus baileyi Cottus bairdi Cottus carolinae Cottus cognatus Cottus girardi Campostoma anomalum Carassius auratus Clinostomus elongatus Clinostomus funduloides Cyprinella analostana Cyprinus carpio Cyprinella galactura Cyprinella spiloptera Cyprinella whipplei Erimystax insignis Exoglossum laurae Exoglossum maxillingua Hybognathus regius Luxilus albeolus Luxilus coccogenis Luxilus cerasinus Luxilus chrysocephalus Luxilus cornutus Lythrurus ardens
Trophic
Habitat
IP IN OH OH OH IN IN IN IN IN IN OH IN OH IP IN IN IP IP IN IP IN IN IN IP IP IP IP IP IN IN IN IN IN OH OH IN IN IN OH IN IN IN OH IN IN OH IN IN IN IN IN IN
CO CO BE BE BE BE BE BE BE BE BE BE BE BE CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO BE BE BE BE BE BE CO CO CO CO CO CO CO CO BE CO CO BE CO CO CO CO CO CO
Reproduction
Tolerance
Alien
TOL BS BS BS BS CG CG CG CG BS CG CG BS CG NG NG NG NG NG NG NG NG NG NG NG NG NG NG NG NG NG NG NG NG CG BS NA NA BS BS AT AT AT CG CG CG BS NA NA NA NA NA NA
ANK TOL INT INT INT INT INT NP INT INT AN PH
TOL
TOL INT
NT A NKT ST ANT AN X AN AN AN AN AN
TOL
X
TOL
X K
INT INT N
K J TOL TOL Y
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Appendix 1: Metric Classifications TABLE A1.1.—Continued.
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Species Mountain shiner Pearl dace Bluehead chub River chub Bull chub Golden shiner Bigeye chub Whitemouth shiner Comely shiner Emerald shiner Silverjaw minnow Bridle shiner River shiner Spottail shiner Tennessee shiner Silver shiner Swallowtail shiner Saffron shiner Rosyface shiner New River shiner Mirror shiner Sand shiner Telescope shiner Mimic shiner Kanawha minnow Stargazing minnow Southern redbelly dace Mountain redbelly dace Tennessee dace Bluntnose minnow Fathead minnow Blacknose dace Longnose dace Creek chub Fallfish Redfin (or grass) pickerel Chain pickerel Northern studfish Banded killifish Speckled killifish Yellow bullhead Brown bullhead Channel catfish Yellowfin madtom Stonecat Margined madtom Trout-perch Greenside darter Rainbow darter Fantail darter Swamp darter Stripetail darter Longfin darter Johnny darter Tessellated darter Candy darter Riverweed darter Redline darter Snubnose darter Variegate darter Wounded darter Banded darter Logperch Gilt darter Yellow perch
Lythrurus lirus Margariscus margarita Nocomis leptocephalus Nocomis micropogon Nocomis raneyi Notemigonus crysoleucas Notropis amblops Notropis alborus Notropis amoenus Notropis atherinoides Notropis buccatus Notropis bifrenatus Notropis blennius Notropis hudsonius Notropis leuciodus Notropis photogenis Notropis procne Notropis rubricroceus Notropis rubellus Notropis scabriceps Notropis spectrunculus Notropis stramineus Notropis telescopus Notropis volucellus Phenacobius teretulus Phenacobius uranops Phoxinus erythrogaster Phoxinus oreas Phoxinus tennesseensis Pimephales notatus Pimephales promelas Rhinichthys atratulus Rhinichthys cataractae Semotilus atromaculatus Semotilus corporalis Esox americanus Esox niger Fundulus catenatus Fundulus diaphanus Fundulus rathbuni Ameiurus natalis Ameiurus nebulosus Ictalurus punctatus Noturus flavipinnis Noturus flavus Noturus insignis Percopsis omiscomaycus Etheostoma blennioides Etheostoma caeruleum Etheostoma flabellare Etheostoma fusiforme Etheostoma kennecotti Etheostoma longimanum Etheostoma nigrum Etheostoma olmstedi Etheostoma osburni Etheostoma podostemone Etheostoma rufilineatum Etheostoma simoterum Etheostoma variatum Etheostoma vulneratum Etheostoma zonale Percina caprodes Percina evides Perca flavescens
Trophic
Habitat
IN IN OH IN IN OH IN OH IN OH IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN OH OH OH OH OH OH IN IP IP IP IP IN IN IN OH OH OH IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IN IP
CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO BE BE CO CO CO CO CO BE BE CO CO CO CO CO CO CO BE BE BE BE BE BE BE BE BE BE BE BE BE BE BE BE BE BE BE BE BE BE BE BE CO
Reproduction BS BS CG CG CG BS BS NA BS BS BS BS BS NA BS NA NA NA BS BS BS BS BS BS BS NA NA NA AT AT CG CG NG NG BS BS BS AT BS NG NG NG NG NG NG BS AT CG NG AT NG NG NG NG BS NG CG AT BS AT AT CG CG BS
Tolerance
Alien
H
TOL INT INT
INT N N
INT
INT INT
N N
NKJ
TOL PH TOL TOL TOL
YRHJ ANK
TOL M MK TOL TOL TOL
M
N A
T
TOL
TOL TOL INT
N INT INT
A
INT MNK
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Appendix 1: Metric Classifications TABLE A1.1.—Continued.
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Species Appalachia darter Blackside darter Stripeback darter Shield darter Roanoke logperch Roanoke darter River darter Sauger Chestnut lamprey Mountain brook lamprey Least brook lamprey American brook lamprey Eastern mosquitofish Pirate perch Rainbow trout Brown trout Brook trout Freshwater drum Central mudminnow Eastern mudminnow
Percina gymnocephala Percina maculata Percina notogramma Percina peltata Percina rex Percina roanoka Percina shumardi Stizostedion canadense Ichthyomyzon castaneus Ichthyomyzon greeleyi Lampetra aepyptera Lampetra appendix Gambusia holbrooki Aphredoderus sayanus Oncorhynchus mykiss Salmo trutta Salvelinus fontinalis Aplodinotus grunniens Umbra limi Umbra pygmaea
Trophic
Habitat
Reproduction
IN IN IN IN IN IN IN IP IP OH OH OH IN IN IP IP IP IN IN IN
BE BE BE BE BE BE BE CO BE BE BE BE CO CO CO CO CO BE BE BE
CG CG CG CG CG CG CG BS CG CG CG CG CG VI NG CG CG BS AT NG
Tolerance
Alien
INT NJ
INT
R INT INT TOL TOL
X X
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Appendix 2: Variables and Metrics TABLE A2.1.—Identification of fish assemblage variable and fish metric names. Metric names refer to fish assemblage metrics to which the metric selection process was applied. Italicized metric names indicate fish assemblage variables that failed the responsiveness test (P . 0.05 and r 2 , 0.20; see Methods). Metrics in bold were adopted for use in the index of biotic integrity (see Table A2.2).
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Metric name NUMNATSP NUMSPEC NATIVFAM NSBHAB NSBHAB2 NSCOLU NSINTOL NREPROS NTROPH NUMFISH NSANGU NSATHER NSCATO NSCATO2 NSCENT NSCOTT NYSCYPR NSCYPR2 NSDART NSDRUMX NSESOXX NSFUND NSGAMB NSICTA NSLAMP NSPERCO NSPPER NSSALM NSUMBR PCOTTID PBENTSP PCOLSP PCOLD PCOLD2 PLUNKSP PCYPTL PEXOT PTOLE PBENT PINSE PINVERT PPISC PPISCINV PPISCINV2 PCARN PHERB PMICRO PMICRO2 PMACRO POMNI PNEST PBCST PBCLN PCGBU PATNG PNTGU PTREPRO PGRAVEL
Fish assemblage variable Number of native species Number of species Number of native families Number of benthic species Number of benthic species (excluding tolerant taxa) Number of water-column species Number of sensitive species Number of reproductive guilds Number of trophic guilds Number of fish collected Number of native species, family Anguillidae Number of native species, family Atherinidae Number of native species, family Catostomidae Number of native species, family Catostomidae (excluding tolerant taxa) Number of native species, family Centrarchidae Number of native species, family Cottidae Number of native species, family Cyprinidae Number of native species, family Cyprinidae (excluding tolerant taxa) Number of native species, family Percidae Number of native species, family Sciaenidae Number of native species, family Esocidae Number of native species, family Fundulidae Number of native species, family Poeciliidae Number of native species, family Ictaluridae Number of native species, family Petromyzonidae Number of native species, family Percopsidae Number of native species, family Aphredoderidae Number of native species, family Salmonidae Number of native species, family Umbridae Proportion of individuals, family Cottidae Proportion of individuals in benthic taxa Proportion of individuals in water-column taxa Proportion of individuals of coldwater species Proportion of individuals of coldwater and coolwater species Proportion of large, long-lived individuals Proportion of tolerant cyprinid individuals Proportion of nonindigenous individuals Proportion of tolerant individuals Proportion of benthic invertivores Proportion of water-column invertivores Proportion of invertivores Proportion of piscivores Proportion of invertivore–piscivores Proportion of invertivore–piscivores (excluding S. atromaculatus) Proportion of piscivores 1 invertivore–piscivores Proportion of herbivores Proportion of micro-omnivores Proportion of micro-omnivores (excluding R. atratulus) Proportion of macro-omnivores Proportion of omnivores 1 herbivores Proportion of nest associate spawners Proportion of broadcast spawners Proportion of clean-gravel, broadcast spawners Proportion of clean-gravel egg burying spawners Proportion of egg-attaching spawners Proportion of nest-guarding spawners Proportion of tolerant reproductive strategists Proportion of gravel-spawning individuals
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TABLE A2.2.—The index of biotic integrity (IBI) metric labels are used to distinguish between metric names and the final IBI metrics scaled from 0 to 10. IBI metric label BENTHIC CYPRINID INTOL COTTID ALIEN TOLRNT PISCINV MACRO GRAVEL
IBI metric variable Benthic species richness IBI metric Intolerant cyprinid richness IBI metric Sensitive species richness IBI metric Sculpin individuals IBI metric Nonindigenous individuals IBI metric Tolerant individuals IBI metric Invertivore–piscivore individuals IBI metric Macro-omnivore individuals IBI metric Lithophil individuals IBI metric
TABLE A2.3.—Habitat variable descriptions.
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Habitat variable Channel habitat quality
Watershed quality
Riparian quality
Watershed and riparian quality Watershed, riparian and channel quality
Description An integrated measure of in-channel physical habitat quality that excludes habitat volume indicators but includes measures of five major aspects of channel habitat quality: velocity and stream power, substrate quality, channel alteration, channel spatial complexity, and cover for fish. An integrated index that combines information on the natural land cover, land use, road density, and human population density in the contributing drainage area upstream from each sample stream reach. Each land cover, land-use type is given a separate modeled response shape describing the relative contribution (or degradation) to watershed quality as the percentage of the land-cover or land-use type increases incrementally from 0% to 100%, or the density of roads or human population increase from zero to high values. An integrated measure that combines field site riparian vegetation and human disturbance observations. The measures of riparian vegetation quality include a measure of streambank canopy cover determined in the field with a densiometer and a measure of woody riparian cover complexity and sustainability (Kaufmann et al. 1999). The measure of riparian human disturbances is the proximity-weighted sum of the presence of 11 types of human activities (Kaufmann et al. 1999). An integrated measure that combines field site riparian vegetation and human disturbance observations with the same watershed measures used in calculating the watershed quality index above. An integrated measure that combines an integrated measure of in-channel habitat quality with the watershed and riparian quality measures described above. The in-channel measures exclude habitat volume indicators but include measures of five major aspects of channel habitat quality.