STREAM ASSESSMENTS USING BIOTIC INDICES: RESPONSES TO PHYSICOCHEMICAL VARIABLES

ABSTRACT: Responses of the Wyoming Stream Integrity Index(WSII), a regionally calibrated multimetric index, were investigatedin relation to background elevational changes in water quality andhabitat conditions versus accelerated anthropogenic degradation atthe watershed scale. Assessments were conducted for three riversin southeast Wyoming: the Little Medicine Bow River, the MedicineBow River, and Rock Creek. Pearson correlation coefficients andregression models related “core metrics” and index scores to eleva-tional gradients of physicochemical variables. Velocity, substrate,and weighted habitat values were positively correlated to indexscores, while suspended solids was negatively correlated. The exclu-sive dependence of index scores on physical variables specifies thetype of environmental gradients the WSII is most robust in detect-ing. The individual “core metrics” Plecoptera taxa, Trichopterataxa, percent Trichoptera without Hydropsychidae, and percentnoninsects appeared most sensitive to physical changes and werethus driving associations between index scores and physical vari-ables. Despite strong correlations with physical variables, anoma-lies existed where habitat conditions were good, unknown stressorsexisted, or gradients were naturally occurring despite “Poor” indexscores (i.e., degraded stream conditions). Such findings illustratethe influence of regional variability on biotic indices and the impor-tance of identifying sufficient reference and impaired stream reach-es used to develop and calibrate multimetric indices relying onreference conditions.(KEY TERMS: biotic integrity; environmental indicators; nonpointsource pollution; benthic macroinvertebrates; sediment impacts;and semi-arid regions.)

Miller, Scott W., Quentin D. Skinner, and Katta J. Reddy, 2004. Stream Assess-ments Using Biotic Indices: Responses to Physicochemical Variables. Journalof the American Water Resources Association (JAWRA) 40(5):1173-1188.

INTRODUCTION

Nonpoint source (NPS) pollution is the primarysource of water quality degradation in the UnitedStates, with siltation of aquatic environments identi-fied as the leading NPS pollutant (GPAC, 1992;USEPA, 2000). Miles of unassessed streams anddegraded stream conditions have prompted federal,state, and local monitoring of water quality to estab-lish baseline information from which to judge surfacewater quality and habitat impairments. The ubiqui-tous nature of NPS pollution has changed the focus ofthese monitoring efforts. Traditional emphasis onhuman health related pollutants has been expandedto include parameters for evaluating changes inecosystem health or biological integrity (Karr, 1993).Biological integrity is defined as the ability of a sys-tem to support and sustain a balanced, integrated,adaptive community of organisms, having a composi-tion and diversity comparable with natural habitatsof a given region (Karr et al., 1986; Gibson et al.,1996). The U.S. Environmental Protection Agency(USEPA) has responded to this new focus on biologi-cal integrity by promoting rapid bioassessment proce-dures that can be adapted to the individual needs ofstates and geographic areas. Specifically, bioassess-ments have been identified as the most effectivemeans to evaluate cumulative impacts from NPS pol-lution. Consequently, the USEPA has mandated allstates to implement biomonitoring programs by 2005(USEPA, 2002a).

1Paper No. 03005 of the Journal of the American Water Resources Association (JAWRA) (Copyright © 2004). Discussions are open untilApril 1, 2005.

2Respectively, Graduate Research Assistant, Department of Fisheries and Wildlife, Oregon State University, Nash Hall, Room 104, Corval-lis, Oregon 97331; and Professor and Associate Professor, Department of Renewable Resources, University of Wyoming, P.O. Box 3354,Laramie, Wyoming 82072 (E-Mail/Miller: [email protected]).

JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION 1173 JAWRA

JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATIONOCTOBER AMERICAN WATER RESOURCES ASSOCIATION 2004

STREAM ASSESSMENTS USING BIOTIC INDICES:RESPONSES TO PHYSICOCHEMICAL VARIABLES1

Scott W. Miller, Quentin D. Skinner, and Katta J. Reddy2

Macroinvertebrates have emerged as key biologicalindicators for use in rapid bioassessment proceduresbecause of their numerous advantages over more con-ventional monitoring tools (Lenat et al., 1981; Abel,1989; Barbour et al., 1999). A recent USEPA survey ofU.S. states, tribes, and territories revealed that 56 outof 57 in-place biomonitoring programs use aquaticmacroinvertebrates (USEPA, 2002b). Macroinverte-brates exhibit graded responses to a variety of pollu-tants, are differentially sensitive to pollutants, aresedentary, reflect localized impairments, and providefor a record of impacts over a longer period of timethan do chemical and physical analyses (Metcalfe,1989; Crunkilton and Duchrow, 1991).

Geographically calibrated multimetric indices areone type of bioassessment tool endorsed by theUSEPA for their ability to provide objective andrepeatable methods of assessing community respons-es to environmental stressors (Karr et al., 1986; Gib-son et al., 1996; Barbour et al., 1999). Mulitmetricindices are comprised of individual metrics measuringassemblage structure, function, and pollution sensi-tivity. Individual metrics are selected based on theirability to discriminate between reference and stressedsites, as well as their ecological meaning (B.K. Jessupand J.B. Stribling, 2002, unpublished report, TetraTech., Inc.). Inherent within these indices is thatstress responses differ based on index composition(Yaun and Norton, 2003). Multimetric indices arecommonly developed for the purpose of assessingwater resources over large geographic areas, such asthe state or country level. Consequently, tests of indexefficacy, the validity of reference conditions, and useof stratification layers (e.g., ecoregions) have common-ly been conducted at large spatial scales (e.g., 105 m2).However, widespread acceptance of multimetricindices has expanded their use to the watershed scale,where conditions are assessed along elevational gradi-ents within and among stream systems.

Here a case study is presented to evaluate a multi-metric index developed for the state of Wyoming, asemiarid region. Past studies of the WSII focusedindividually on datasets spanning the entire state ofWyoming or specific bioregions within the state (J.B.Stribling, B.K. Jessup, and J. Gerritsen, 2000, unpub-lished report, Tetra Tech., Inc.; B.K. Jessup and J.B.Stribling, 2002, unpublished report, Tetra Tech., Inc.).The goal of the study is to assess WSII’s ability to dif-ferentiate between background elevational changes inwater quality and habitat conditions versus accelerat-ed anthropogenic changes at the watershed scale.Specific objectives are to (1) identify index score andmetric responses to variability in chemical and physical parameters and (2) assess whether WSIIresponds predictably to environmental gradients andis thus robust in detecting changes in water quality or

habitat conditions. A priori hypotheses predict exclu-sive WSII responses to physical parameters associat-ed with sediment and aquatic habitat, as opposed tovariables of water column chemistry because of dif-fuse land uses and the semiarid nature of the region.Therefore, responses of WSII index scores to variabili-ty in physical parameters were examined to identifyoutliers or site specific anomalies. Site anomalies rep-resent instances where the WSII potentially misclas-sified stream reaches as impaired or cases in which itfailed to detect changes in physical conditions. Bytesting these hypotheses one can assess WSII’s capac-ity to respond to environmental gradients and thusidentify impaired stream reaches or accelerated ratesof degradation. In addition, analysis identifiesresponses of individual core metrics, as well as thetypes of impacts and subsequent degradation WSII ismost capable of detecting. This source relationship iscritical to identifying accurate 303(d) listings requiredby the CWA as well as focusing restoration activitieson the proper causal factor of impairment.

MATERIALS AND METHODS

Study Area

The Medicine Bow River watershed encompasses747,512 ha. Elevation varies from 1,920 to 3,600 mand is included in Omernik’s (1987) Southern Rockiesand Wyoming Basins ecoregions. These correspond tothe Rockies and Wyoming Basins Bioregions used bythe Wyoming Department of Environmental QualityWater Quality Division (WDEQ-WQD). Rock Creek(RC), Little Medicine Bow River (LMB), and theMedicine Bow River (MB) drain the Medicine BowRiver watershed (Figure 1) and are classified as Class2 cold water game fisheries (WDEQ, 1998). RockCreek and the LMB River are tributaries of the MBRiver, which flows into the North Platte River. The cli-mate is cold continental and average annual meantemperature and precipitation at Medicine Bow,Wyoming, are 5.6˚C and 28.4 cm respectively. A snow-pack dominated hydrologic regime produces maxi-mum streamflows from April to June, which arerecorded on each stream by U.S. Geological Survey(USGS) stage recorder gauging stations. Geologic par-ent material in the LMB River drainage is composedof older Mesozoic granitic rock, and the MB River andRC drainage basins are composed of younger Protero-zoic sedimentary geologic material. Major land usesinclude sheep and cattle ranching, oil and gas devel-opment, forestry, and irrigated agriculture for grow-ing grass forage. Production of grass forage is

JAWRA 1174 JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION

MILLER, SKINNER, AND REDDY

dependent upon flood irrigation, which may lowerstream peak flows during spring runoff events (Hill,1976; Brookes, 1992). Mineral exploration and urani-um mining occurred in the LMB drainage from 1955to the early 1980s (McCallum and Birch, 1980).

Sampling Sites

Nine sites were selected – three per river – toquantify responses in WSII index scores to chemical,physical, and biological parameters along each riveraxis (Figure 1). Criteria considered for site selectionincluded elevation, gradient, bioregions, geology, soils,land use, channel morphology, and ability to laterinterpret data in relationship to stream function(Stednick, 1991). Sites LMB-1, MB-1, and RC-1 werelocated in the Montane elevation zone; Sites LMB-2,MB-2, and RC-2 were located in the Foothill elevationzone; and Sites LMB-3, MB-3, and RC-3 were locatedin the Basin elevation zone following Schumm’s(1977) stratification of stream systems by elevation.Montane sites fall within the Rockies (Southern Rock-ies subregion) Bioregion, and Foothill and Basin sitesfall within the Wyoming Basin Bioregion. Streamchannel elevation, sinuosity, slope, and order were

derived from USGS 1:24,000-scale topographic maps(Meador et al., 1993).

Sampling

Twenty-one chemical and physical water qualityparameters were measured from April to October of1999, 2000, and 2001. Samples were collected weeklyduring spring runoff (April through July) andbimonthly during baseflow conditions (Augustthrough October). Water quality parameters includedcalcium, magnesium, sodium, potassium, total dis-solved solids (TDS), total suspended solids (TSS), tur-bidity, carbonate, bicarbonate, fluoride, chloride,nitrate as N, orthophosphate, sulfate, total alkalinityas calcium carbonate, and hardness as calcium car-bonate. A DH-48 sampler was used to collect samplesusing the equal width increment method (Guy andNorman, 1970). Wyoming Analytical Services pro-cessed all samples according to the methods ofUSEPA (1995). Appropriate samples were fixed witheither nitric or sulfuric acid as specified by the stan-dard methods. Electrical conductivity (EC), pH, watertemperature, and dissolved oxygen were measured insitu using a YSI 610 DM multiparameter sonde (YSIInc., 1996). Discharge was calculated by measuringstream velocity with a Marsh McBirney flow meterand water depth and wetted width (Meador et al.,1993).

Channel morphology and habitat attributes at eachsite were assessed using a 200 m section of the streamchannel following Plafkin et al. (1989). Values werecalculated for stream primary factors: channel bottomsubstrate, instream cover for fish, embeddedness, andvelocity/depth ratios. Channel shape, channel alter-ation, pool/riffle ratio, and width/depth ratio wererecorded as secondary variables. Bank vegetation pro-tection, lower bank stability, disruptive pressures,and width of riparian zone were recorded as tertiaryvariables. The USEPA procedure was modified toinclude a quantitative assessment of channel sub-strate using the Wolman (1954) pebble count method.One hundred particles were randomly selected withinthe bankfull width of the stream channel and mea-sured along the intermediate axis while walkingupstream at 45 degree angles from the respectivebank. Weighted habitat scores were calculated fromprimary, secondary, and tertiary habitat variables foreach sampling site and date using the relative impor-tance of each variable for supporting macroinverte-brates and/or fish assemblages.

Macroinvertebrate samples were collected at eachsite during September 1999 and 2001 following theWDEQ-WQD Beneficial Use Reconnaissance Programprotocol (King, 1993). Sampling was confined to riffles


STREAM ASSESSMENTS USING BIOTIC INDICES: RESPONSES TO PHYSICOCHEMICAL VARIABLES

Figure 1. Map of Study Area Illustrating LocationsWhere Chemical, Physical, and Biological

Parameters Were Measured.

or runs representative of the study reach wheredepths were less than 0.61 meters and velocities wereless than 0.914 m/s. A composite of eight randomlyselected samples were collected at each site using a0.093 m2 surber sampler fitted with 500 µm meshnetting and fixed with 70 percent ethanol. Sampleswere analyzed by Aquatic Biology Associates, Corval-lis, Oregon, using a minimum of 400 organisms percomposite sample and identified to genus or speciesfor better known taxa.

Data Analysis

Principle components analysis (PCA) reducedchemical and physical parameters from a set of inter-related variables to simplified sets of uncorrelatedcomponents (Afifi and Clark, 1997). Weighted leastsquares regression techniques were used to derive fac-tor scores for parameters within individual compo-nents. The PCA and regression analyses werefacilitated by use of the Statistical Package for theSocial Sciences (SPSS, 1998) and the Statistical Anal-ysis System (SAS Institute, 1999).

Relationships among chemical, physical, and bio-logical data were analyzed using Pearson correlationcoefficients and simple linear regressions. Pearsoncorrelation analysis identified relationships betweenindividual parameters and biological index scores,while coefficients of determination and slope coeffi-cients quantified observed correlations. Limiteddegrees of freedom restricted the use of multipleregression techniques and multivariate analyses. Theresponse variable of metric scores was tested for inde-pendence on pH, dissolved oxygen, temperature,velocity, mean particle size, embeddedness, habitatscores, dissolved solids, and suspended solids. Valuesfor explanatory variables were transformed using nat-ural logarithms to adjust for nonnormal distributionsof residuals when observed (Mosteller and Tukey,1977).

Macroinvertebrate data were analyzed using aregionally calibrated multimetric biotic index basedon reference conditions for Rockies and WyomingBasin Bioregions (J.B. Stribling, B.K. Jessup, and J. Gerritsen, 2000, unpublished report, Tetra Tech,Inc.). The WDEQ-WQD identifies 10 core metrics forthe Wyoming Basin Bioregion: total taxa,Ephemeroptera taxa, Plecoptera taxa, Trichopterataxa, percent Plecoptera, percent noninsects, percentTrichoptera (no Hydropsychidae), Biotic CommunityIndex/Community Tolerance Quotient (a) or BCICTQa, percent scrapers, and semivoltine taxa. TheWDEQ-WQD identifies nine core metrics for theRockies Bioregion: Ephemeroptera taxa, Plecopterataxa, Trichoptera taxa, percent Ephemeroptera (no

Baetidae), percent Trichoptera (no Hydropsychidae),percent of the five dominant taxa, percent scrapers,Hilsenhoff Biotic Index (HBI), and BCI CTQa). Indi-vidual metrics for respective bioregions were deter-mined to be most effective in discriminating betweenreference and nonreference conditions. Values abovethe 25th percentile of the bioregion reference indexare rated as “Very Good” and “Good,” suggesting thataquatic assemblages compare to Wyoming referenceconditions. Index values below the 25th percentile are“Fair,” “Poor,” or “Very Poor.” A Fair rating suggestspartial support or nonsupport of aquatic life use. Poorand Very Poor ratings imply that macroinvertebrateassemblages do not compare to reference assemblagesand that impaired conditions may exist.

RESULTS

Data Reduction

Principal components analysis produced two signif-icant and interpretable factors from the original 21water quality parameters collected in association withthe WSII (Figure 2). Factor One (dissolved solids)explained 47.24 percent of the variation and consistedof measures of ionic strength and dissolved con-stituents, which included alkalinity, hardness, bicar-bonate, TDS, EC, sulfate, magnesium, calcium,sodium, potassium, chloride, and fluoride. Factor Two(suspended solids) included TSS and turbidity andexplained 15.19 percent of the variation in the data.Concentrations of carbonate, nitrate, and orthophos-phate were less than detection limits (0.1 mg/l) andwere disregarded despite potential impacts onmacroinvertebrate assemblages. The PCA of streamdischarge, pH, temperature, dissolved oxygen, dis-charge, and velocity provided no significant or inter-pretable factors. Consequently, 21 water qualityparameters were reduced to dissolved solids (FactorOne) and suspended solids (Factor Two), in additionto pH, temperature, dissolved oxygen, discharge, andvelocity for evaluating influences of chemical andphysical variables on index scores.

Chemistry

Concentrations of dissolved and suspended solids,inorganic nutrients, and metals were relatively lowfor the Rockies Bioregion sites of each river (Table 1)and aquatic life numeric standards were not violated.However, dissolved and suspended solids increasedfrom Rockies to Wyoming Basin Bioregions within



each river. For example, median dissolved solids con-centrations for RC-3 (Wyoming Rockies Bioregion)were 1,564 mg/l and may be considered highcompared to RC-1 (Wyoming Rockies Bioregion) at 58mg/l, or in comparison to other Basin Bioregion sites.For MB-3, median suspended solid concentration was68 mg/l, while for MB-1, the Rockies Bioregion site,the median concentration was 7.3 mg/l. All WyomingBasin Bioregion sites except RC-3 exceeded thenumeric water quality standards of 25.6˚C, the maxi-mum allowable one-day temperature for cold waterfisheries, during August of each sampling year(WDEQ, 1998).

Physical

Elevation of sample sites was between 1,956 m(MB-3) and approximately 2,500 m (LMB-1). TheLMB River dropped 406 m, the MB River 305 m, andRC 376 m among the Rockies and Wyoming BasinBioregion sites (Table 2). Percent slope declined fromRockies to Wyoming Basin sites for the MB River andRC. However, LMB-1 (0.42 percent) and LMB-3 (0.35percent) were greater than LMB-2 (0.20 percent).Mean particle sizes were greatest (34.7 to 63.7 mm),while embeddedness values were lowest for RockiesBioregion sites (72.4 to 99.2). Mean particle sizesdecreased and embeddedness values increased from

Rockies to Wyoming Basin Bioregion sites. SitesLMB-2 and RC-3 were characterized by mobile sandysubstrates, with little available channel habitat forsediment intolerant species. Natural bank erosion atMB-3 provides a local example where larger substratewas added to an otherwise sandy channel bottomfrom lateral river migration of a meander. Local sub-strate additions were observed throughout the entirewetted width of the stream below two large meandersand seemed to have increased the pool:riffle ratio, ascompared to adjacent stream reaches.

Rockies Bioregion sites supported high weightedhabitat scores (Table 2). Stream reaches were charac-terized by frequent pool riffle sequences, cobble andgravel substrates, low embeddedness, well vegetatedstable stream banks, and abundant cover for fish andother aquatic organisms. Wyoming Basin Bioregionhabitat scores were lower and characterized by sandand silt substrates, higher embeddedness, runs, infre-quent pool riffle sequences, and high degrees of banksloughing. Habitat scores for LMB-2 (64.0) and RC-3(81.0) were below the WDEQ-WQD Basin threshold of84.0, indicating poor habitat conditions (King, 1993).

Biological

No statistical differences were observed for WSIIindex scores between the 1999 and 2001 samplingseasons (T-value = -1.60, p = 0.145); therefore,macroinvertebrate results were analyzed for yearscombined. Overall, 121 unique taxa were collected.Abundant macroinvertebrates in the study area wereChironomidae (Orthocladius Complex, Micropsectrasp., and Rheotanytarus sp.), Trichoptera (Hydropsy-che sp. and Cheumatopsyche sp.), Ephemeroptera(Ephemerella inermis, Tricorythodes minutus, andBaetis tricaudatus), Plecoptera, and Coleoptera. Taxarichness appeared similar for Rockies (mean = 37;range = 33 to 39) and Wyoming Basin Bioregion sites(mean = 32; range = 25 to 40). However, assemblagecompositions and index scores appeared differentamong individual sites.

Sites in the Rockies Bioregion generally had highratios of Ephemeroptera, Plecoptera, and Trichoptera(EPT) taxa per total number of taxa (LMB-1: 0.29;MB-1: 0.62; RC-1: 0.63), as compared with WyomingBasin Bioregion sites (Table 3). Rockies Bioregionsites were also higher in species sensitive to distur-bances. For example, the Order Ephemeroptera sup-ported relatively high ratios of Baetidae to totalnumber of Ephemeroptera taxa (LMB-1: 0.92; MB-1:0.15.0; RC-1: 0.35), while ratios for Basin sites werelower (LMB-3: 0.01; MB-3: 0.0; RC-3: 0.0). The mayflyspecies Tricorythodes minutus was prevalent inWyoming Basin Bioregions, while Baetis tricaudatus



Figure 2. Principle Components Analysis Showing ComponentComposition for the 19 Measured Water Quality Parameters.

Component 1 consists of alkalinity, bicarbonate, calcium,chloride, fluoride, hardness, potassium, magnesium,

sodium, sulfate, conductivity, and TDS. TSS andNTU make up Component 2.



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580.

450.

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30.

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60.

65

was predominant in the Rockies Bioregion. For theOrder Trichoptera, ratios of Hydropsyche sp. to totalnumber of Trichoptera taxa (LMB-1: 0.17; MB-1: 0.0;RC-1: 0.0) appeared lower in the Rockies Bioregion ascompared to Wyoming Basin Bioregion sites (LMB-3:0.91; MB-1: 0.92; RC-3: 0.97). The percentage of toler-ant noninsect taxa was generally greater for WyomingBasin Bioregion sites as compared with RockiesBioregions.

Index scores (LMB-1, MB-1, and RC-1) for theRockies Bioregion were between 26.2 at LMB-1 and73.0 at RC-1 (Table 4). Index values for MB-1 and RC-1 scored Good, and the low value of LMB-1 scoredPoor. Abundant Ephemeroptera taxa, low percentagesfor the five dominant taxa, and low HBI values pro-duced Good index scores for sites MB-1 and RC-1.

The low index score of LMB-1 was caused by lowdiversity macroinvertebrate assemblages, low taxanumbers, and a high BCI CTQa relative to referenceconditions (Table 4). Dominant taxa at LMB-1(Orthocladius complex, Zapada cinctipes, and Capni-idae) accounted for 73.4 percent of total organismsobserved, resulting in a percent of five dominant taxavalue far greater than reference conditions. Dominantmayfly taxa for LMB-1 were Baetis tricaudatus andDiphetor hageni; MB-1 and RC-1 supported a greaterdiversity of mayfly species with a total of eight uniquetaxa as compared to three at LMB-1.

Variation in index scores exists within theWyoming Basin Bioregion as well (Table 5). Indexscores were between 27.6 Poor at LMB-2 and 55.4Fair at MB-2. Sites scoring Poor (LMB-2 and RC-3)



TABLE 2. Physical and Habitat Characteristics Averaged Across 1999 and 2000for the Nine Sampling Sites on the Medicine Bow River Drainage.

Weighted Substrate Size WeightedHabitat Score Mean (SD) Embeddedness*** Elevation Slope

Sample Site* Bioregion (0 to 100)** (mm) (0 to 100) (m) (percent)

LMB-1 Rockies 148.0 34.7 (42.9) 96.5 2,499 0.42LMB-2 WY Basin 064.0 10.2 (12.03) 61.0 2,118 0.20LMB-3 WY Basin 112.0 33.0 (30.9) 67.3 2,093 0.35MB-1 Rockies 146.0 59.8 (39.9) 72.4 2,261 0.83MB-2 WY Basin 108.0 28.6 (20.1) 67.1 2,103 0.60MB-3 WY Basin 105.0 59.8 (43.1) 60.0 1,956 0.30RC-1 Rockies 155.0 63.7 (38.3) 99.2 2,388 0.66RC-2 WY Basin 138.5 23.6 (22.4) 55.6 2,134 0.14RC-3 WY Basin 81.0 09.4 (26.1) 40.2 2,012 0.10

***Little Medicine Bow River (LMB), Medicine Bow River (MB), and Rock Creek (RC).***Value of 0 = poorest habitat, value of 100 = habitat conditions are 100 percent of reference conditions.***Value of 20 = silt covered, 100 = no silt.

TABLE 3. Unique Taxa Numbers, Ratios of Taxonomic Group Abundances, andDiversity Measures Illustrating Differences Among and Within Bioregions.

Hydropsychidae/ Baetidae/Number Number of Total Taxa/ Total Total

Site* Bioregion of Taxa EPT** Taxa EPT** Taxa Trichoptera Ephemeroptera

SLMB-1 Rockies 34 10 0.29 0.17 0.92LMB-2 Basins 25 4 0.16 0 0LMB-3 Basins 37 17 0.46 0.91 0.01MB-1 Rockies 39 24 0.62 0.6 0.15MB-2 Basins 35 16 0.46 0.98 0.04MB-3 Basins 41 15 0.32 0.92 0RC-1 Rockies 40 25 0.63 0 0.35RC-2 Basins 24 13 0.34 0.97 0.51RC-3 Basins 29 9 0.31 0.97 0

**Little Medicine Bow River (LMB), Medicine Bow River (MB), and Rock Creek (RC).**EPT = Ephemeroptera, Plecoptera, and Trichoptera.

were low in taxa numbers for Orders of Ephemerop-tera, Plecoptera, and Trichoptera and high on thenegative core metric, BCI-CTQa. Wyoming BasinBioregion sites supported similar taxa richness; however, taxa abundance was different among sitesscoring Poor, Fair, or Good (Table 5). For example,LMB-2 and RC-3 both scored Poor, with LMB-2

having the lower score of the two. The abundance of Ephemerella inermis, Tricorythodes minutus, Isop-erla sp., Cheumatopsyche sp., and Hydropsyche sp.was 5 to 50 times less at LMB-2 and RC-3 than sitesscoring Fair or Good.



TABLE 5. Wyoming Basin Bioregion: Metric Values, Index Scores, and Ratings for the Medicine Bow River (MB), theLittle Medicine Bow River (LMB), and Rock Creek (RC), in Relation to Reference Conditions Using the WSII.

BasinBioregion LMB-2 LMB-3 MB-2 MB-3 RC-2 RC-3Reference Metric Metric Metric Metric Metric Metric

Core Metric Values Value Score Value Score Value Score Value Score Value Score Value Score

Total Taxa 45.0 25.0 55.6 37.0 82.2 35.0 077.8 41.0 91.1 24.0 53.3 29.0 64.4Ephemeroptera Taxa 09.0 03.0 33.3 08.0 88.9 09.0 100.0 06.0 66.7 07.0 77.8 06.0 66.7Plecoptera Taxa 05.0 01.0 20.0 02.0 40.0 02.0 040.0 03.0 60.0 01.0 20.0 00.0 00.0Trichoptera Taxa 10.0 00.0 00.0 07.0 70.0 05.0 050.0 06.0 60.0 05.0 50.0 03.0 30.0% Plecoptera 16.5 00.3 02.4 05.3 40.5 04.6 035.2 04.9 37.3 05.6 43.0 00.0 00.0% Trichoptera 31.3 00.0 00.0 02.7 08.5 00.9 003.0 04.3 13.6 02.9 09.1 00.2 00.7

(no hydropsychidae)% Noninsects* 00.5 00.6 99.8 02.9 95.7 04.8 092.2 17.8 68.4 04.6 92.4 04.3 93.0BCI CTQa* 62.6 94.9 31.9 86.7 49.2 82.3 058.4 89.2 43.8 77.0 69.5 93.1 35.7% Scrapers 31.8 01.6 04.9 00.8 02.5 08.2 025.6 01.7 05.3 10.6 33.3 00.7 02.1Semivoltine Taxa 07.0 02.0 28.6 03.0 42.9 05.0 071.4 04.0 57.1 02.0 28.6 01.0 14.3

Index Score 27.6 52.0 055.4 50.3 47.7 30.7Rating** Poor Fair Fair Fair Fair Poor

**Metric value where trend increases with increasing stress. Higher values indicate a negative response.**Very Good = > 80.5, Good = 60.9 to 80.4, Fair = 40.6 to 60.8, Poor = 20.3 to 40.5, and Very Poor = < 20.2.

TABLE 4. Rockies Bioregion: Metric Values, Index Scores, and Ratings for the Medicine Bow River (MB), theLittle Medicine Bow River (LMB), and Rock Creek (RC), in Relation to Reference Conditions Using the WSII.

RockiesBioregionReference LMB-1 Metric MB-1 Metric RC-1 Metric

Core Metric Values Value Score Value Score Value Score

Ephemeroptera Taxa 11.0 3.0 27.3 8.0 72.7 8.0 072.7Plecoptera Taxa 8.0 3.0 37.5 6.0 75.0 9.0 100.0Trichoptera Taxa 11.0 4.0 36.4 10.0 90.9 8.0 072.7% Ephemeroptera (no Baetidae) 54.0 0.2 00.3 22.0 40.7 34.6 064.1% Trichoptera (no Hydropsychidae) 46.6 1.7 03.7 17.3 37.2 13.5 028.9% Five Dominant Taxa* 45.7 79.3 31.2 54.7 80.1 54.8 079.9% Scrapers 54.5 0.3 00.6 18.8 34.5 34.1 062.5HBI* 1.4 4.3 66.4 3.2 79.4 2.0 093.6BCI CTQa* 44.1 88.8 32.2

Index Score 26.2 65.0 073.0Rating** Poor Good Good

**Metric value where trend increases with increasing stress. Higher values indicate a negative response.**Very Good = > 78.8, Good = 57.5 to 78.7, Fair = 38.3 to 57.4, Poor = 19.2 to 38.7, Very Poor = < 19.1.

Direct Gradient Analysis: Chemical, Physical, andBiological

Index scores were significantly correlated to meanparticle size, suspended solids (Factor Two), slope,and velocity, while weighted habitat, embeddedness,and temperature approached significance (Table 6).Further analysis of the strongest relationships withsimple linear regression analysis reveals slope coeffi-cients of velocity, mean particle size, slope, and sus-pended solids (Factor Two) as being significantlydifferent from zero. Velocity explained the highestamount of variability in index scores (r2 = 0.81, p =0.001) and had a slope of 25.7 (t = 5.51, p = 0.001).Substrate (r2 = 0.58, p = 0.017) and suspended solids(r2 = 0.44, p = 0.032) also explain a significant amountof variation in index scores, while weighted habitatvalues (r2 = 0.34, p = 0.099) approached significance(Figure 3). No significant relationships were identi-fied between index scores and variables associatedwith water column chemistry (Table 6).

Thirteen overall core metrics are included in theRockies and Wyoming Basin Bioregion WSII (Table7). Plecoptera taxa, Trichoptera taxa, percent Tri-choptera without Hydropsychidae, and percent non-insects appeared to be driving associations betweenindex scores and physical variables. These measureswere most strongly correlated to substrate, weightedhabitat scores, slope, suspended solids, and velocity,as were overall index scores. In contrast, Pearson cor-relation coefficients revealed less than two significantcorrelations among total taxa, Ephemeroptera taxa,percent Plecoptera, percent of five dominant taxa andHBI with the eight physical variables listed in Table7. Individual metrics with low Pearson correlationcoefficients were not responsive to changes in physicalvariables among sites.

DISCUSSION

WSII Responses to Environmental Gradients

Although chemical parameters appeared to changealong elevation gradients, analysis illustrates thatvariation in index scores is better explained by mea-sured physical attributes. Considering the diffuse andsparse population of the MB watershed, measuredchemical parameters appear to represent backgroundconditions for the watershed and therefore do not sig-nificantly impact macroinvertebrate assemblages.Chemical results presented here follow Allan (1995),who found biological responses to chemical variablesinsignificant when conditions are close to average and



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concentrations do not exceed an organism's tolerancethreshold. Temperature (Vannote and Sweeney1980), pH (Ormerod and Edwards, 1987), dissolvedoxygen (Hynes, 1970), dissolved solids (Shieh et al.,1999), and other parameters associated with waterchemistry were not found to be significant explanato-ry variables of macroinvertebrate assemblages in thepresent study as they were in those above. Lower con-stituent concentrations found for the Medicine BowRiver may account for differences among the variousstudies. The one exception was temperature, whichexceeded the maximum allowable one-day tempera-ture for cold water fisheries (25.6°C). Despite elevatedtemperature readings, index scores were only weaklycorrelated with stream temperature. Although theinfluence of water chemistry on macroinvertebrateassemblages is well established, this influenceappears secondary to the primary effects of velocity,substrate, weighted habitat scores, and suspendedsolids for the Medicine Bow River drainage.

Velocity, Substrate, Weighted Habitat Scores, andSuspended Solids

The influence of hydrologic processes on velocity,channel substrate, sediment transport, and riparian/aquatic habitat is well established (Minshall, 1984;

Naiman and Decamps, 1997; Skinner, 2003). Anintrinsic characteristic of these variables is changealong the longitudinal stream profile (Vannote et al.,1980). Consequently and as expected, observedmacroinvertebrate assemblages responded individual-ly to physical variables, showing distinct differencesbetween Rockies and Wyoming Basin Bioregion sites.Relationships among macroinvertebrate assemblagesand velocity, substrate, suspended and deposited sedi-ment, and overall habitat conditions have been exten-sively researched (Allan, 1975, 1995; Winget andMangum, 1991). Therefore, discussion is focused oninterpreting WSII index responses to these variablesand not why responses were observed. The authorsrecognize that variables shown to be significant pre-dictors of WSII index scores (velocity, substrate size,sediment concentrations, and habitat) are not inde-pendent of one another and significant interactionsare known to exist among these variables. As samplesize increases in mountain to basin watersheds, sig-nificant interactions may likely emerge from multipleregression analysis, and all variables would not beincluded in models.

The WSII index scores responded consistently tovariability in stream velocity and mean particle size(Figure 3a and 3b). Stream velocity exerts force onaquatic organisms (Allan, 1995). However, in thisstudy velocity is likely an indirect covariate for its



TABLE 7. Pearson Correlation Coefficients Identifying Individual MetricResponses to Variation in Physical Parameters.

SuspendedSolids

Individual Metric Elevation Substrate Embeddedness Habitat Slope (Factor Two) CFS Velocity

Total Taxa1 -0.679 0.828* 0.516 0.146 0.593 -0.599 0.845 0.636

Ephemeroptera Taxa -0.487 0.196 -0.176 0.129 0.268 -0.094 0.353 0.623

Plecoptera Taxa 0.407 0.939** 0.764* 0.646 0.810** -0.843* 0.239 0.729*

Trichoptera Taxa 0.071 0.807** 0.458 0.700* 0.691* -0.673* 0.325 0.661*

% Plecoptera1 -0.105 0.694 0.77 0.905* 0.466 -0.643 0.477 0.641

% Trichoptera 0.3 0.843** 0.576 0.657 0.757* -0.787* 0.127 0.705*(no Hydropsychidae)

% Noninsects1 0.813* -0.873* -0.299 -0.238 -0.098 0.098 -0.937* -0.25

BCI CTQa 0.195 0.6 0.44 0.677* 0.625 -0.65 -0.013 0.749*

% Scrapers 0.35 0.534 0.53 0.622 0.589 -0.676* -0.167 0.665

Semivoltine Taxa1 -0.166 0.674 0.935** 0.304 0.926** -0.855* 0.671 0.954**

% Ephemeroptera -0.595 0.97 -0.004 0.63 0.699 -0.989 0.449 0.924(no Baetidae)2

% Five Dominant Taxa2 -0.848 0.992 -0.369 0.302 0.912 -0.975 0.745 1.00**

HBI2 -0.443 0.911 0.173 0.757 0.562 -0.947 0.284 0.842

1Pearson correlation coefficients only calculated with six values, metric not present in Rockies Bioregion Index.2Pearson correlation coefficients only calculated with three values, metric not present in Wyoming Basin Bioregion Index.**Correlation significant at the 0.05 alpha level (2-tailed).**Correlation significant at the 0.001 alpha level (2-tailed).

ability to sort and separate substrate particles,deposit and scour sediment from interstitial spaces,and transport and deposit detritus (Rabeni and Min-shall, 1977; Allan, 1995). Slower velocity flows char-acterizing Wyoming Basin Bioregion sites promoteddeposition of suspended solids and increased levels ofembeddedness, which decreased index scores.

Allan (1975), Gore (1978), and ASCE (1992) foundlarger substrate classes to increase channel stabilityresulting in increased species diversity. Higher per-centages of semivoltine taxa at sites possessing largemean particle sizes demonstrates the ability ofinstream habitat stability to support more diversifiedmacroinvertebrate assemblages (e.g., semivoltine per-centages: RC-1, 11.65 percent; RC-2, 5.59 percent;RC-3, 0.33 percent). MB-1 and RC-1 (Rockies Biore-gion sites) produced the largest mean particle sizesand highest stream velocities, which corresponded tothe highest index scores of 65.0 and 73.0, respectively(Table 4). In contrast, RC-3 and LMB-2 (WyomingBasin Bioregion sites) were characterized by highlymobile sand streambeds and low median velocitiesresulting in Poor index scores (30.7 and 27.6). Min-shall (1984) found sand streambeds to have lowerspecies diversity regardless of high taxa numbers,which may help explain low index scores for RC-3 andLMB-2. However, Wyoming Basin Bioregion sites withsandy substrates can be modified by local additions oflarger particle sizes. The high index scores of 50.3 forMB-3 (mean particle size of 59.8) and 52.0 at LMB-3(mean particle size of 33.0) illustrate local influencesof larger substrates on index scores relative toupstream reaches.

Suspended Solids (Factor Two)

Suspended solids (Factor Two) were inversely relat-ed to metric scores (Figure 3c). Increases in suspend-ed solids reduce gravel permeability, habitat space,and available oxygen concentrations when deposited(Moring, 1982; MacDonald et al., 1991). These condi-tions favored sediment tolerant macroinvertebrateassemblages and can thus help explain observed vari-ation in index scores. For example, Rockies Bioregionsites MB-1 and RC-1 had the lowest sediment concen-trations and were dominated by Baetis tricaudatus,which is moderately tolerant of fine sediment concen-trations (Relyea et al., 2000). In contrast, Tricoryth-odes minutus was the predominant mayfly species inBasin Bioregions and is found to prefer fine substratesizes over coarser substrate sizes (Winget andMangum, 1991). The distribution of Trichoptera taxafurther illustrates the effects of fine sediment addi-tion to macroinvertebrate assemblages and indexscores. The ratio of Hydropsychidae to total

Trichoptera taxa approached 100 percent for allWyoming Basin Bioregion sites except LMB-2, whichsupported no taxa from this Order, while the ratio forRockies Bioregion sites was close to zero (Table 3).Species within the Family Hydropsychidae are toler-ant to fine sediment additions (Relyea et al., 2000).The application of life history information unique toindividual species or groups of species demonstratesthe diagnostic capabilities of individual metrics orspecies.

Weighted Habitat Scores

The significant direct relationship between indexscores and weighted habitat scores (Figure 3d) likelyrepresents the cumulative impacts of geomorphology,land use, and riparian conditions surrounding streamreaches. These variables influence velocity, substrate,and suspended solids, which were shown to be signifi-cant explanatory variables of index scores. Low ripari-an impacts, stable and well vegetated stream banks,and wide riparian buffer strips, as indicated by habi-tat assessments, likely caused low sediment concen-trations, larger particle sizes, and low embeddednessfor Rockies Bioregion sites. These conditions favorhealthy, well balanced macroinvertebrate assem-blages as indicated by high index scores whereweighted habitat values were correspondingly high.Conversely, sites such as LMB-2 and RC-3 were char-acterized by incised channels with low density vegeta-tive cover and thus unstable stream banks susceptibleto high rates of erosion. Such conditions favored highsediment concentrations, smaller mean particle sizes,and high embeddedness values, which resulted in lowindex scores.

Of the four types of measures chosen for use inmultimetric indices (measures of richness, composi-tion measures, functional feeding groups, and pollu-tion tolerance), individual core metrics from eachcategory displayed significant correlations with physi-cal variables. The most consistent relationships exist-ed for substrate, habitat, and slope (Table 7). Ingeneral, measures of relative taxa abundance weremost responsive. The failure of certain core metrics(e.g., total taxa, Ephemeroptera taxa, HBI) to respondis expected, given that the types of observed gradientsand the diversity of species within these groupingsoffer only minor diagnostic capabilities.

Interpretation of Poor Index Scores

Velocity, substrate, suspended solids, and habitatprovide proximate explanations for why some sites on



RC and the LMB River received Poor index scores.However, index scores and subsequent Poor ratings,indicating low biological diversity and thus impairedconditions, were not completely robust to natural con-ditions. Site LMB-1 received a Poor index scoredespite high weighted habitat scores and low sus-pended sediment concentrations.

Macroinvertebrate assemblages for LMB-1 werenot comparable to other Rockies Bioregion sites (RC-1and MB-1) or reference conditions. The Poor score ofLMB-1 resulted from low taxa numbers, high percentof five dominant taxa, and functional feeding groupabundances differing from reference conditions. Poormacroinvertebrate assemblages, as scored by theWSII, likely resulted from parent material of theLMB River, representing only one component of habi-tat conditions. Sherman Granite, which characterizesthe headwaters of LMB-1, decomposes to coarse sandsand fine gravels, creating mobile sand substrate withchannel configurations of runs, void of large woodydebris or pool riffle sequencing (Montgomery andBuffington, 1993). These instream conditions domi-nate the LMB watershed except for reaches at LMB-3,where higher slopes, greater stream flow velocities,and larger mean particle sizes are present because oflateral river migration increasing bank erosion ofshale outcrops.

Taxa composition for the LMB River did not changefrom pollution intolerant to pollution tolerant assem-blages between any two sites. In addition, weightedhabitat assessments indicate disruptive pressures tobe relatively low for the entire watershed (Table 2).Index scores responded to the natural physical func-tions of the watershed, which limit the diversity ofmacroinvertebrate assemblages and not anthro-pogenic disturbances. Inclinations to list LMB-1 andLMB-2 as degraded may be artifacts of using a region-ally calibrated multimetric index, where the resolu-tion used to identify reference conditions is notinclusive of all watersheds in Wyoming. Recalibrationof the WSII incorporating sampling efforts from thisand other studies will increase the accuracy of sitedesignations in light of regional variability.

The Rocky Mountains are a diverse geologic forma-tion covering a large geographic area throughout thestate of Wyoming. Currently, the entirety of the RockyMountains is lumped into one bioregion (RockiesBioregion), resulting in the use of homogeneous coremetrics across a diverse physiographic region. Differ-ences exist exclusively for critical reference valuesused to differentiate Good, Fair, Poor, and Very Poorindex ratings for subregions within the Rockies Biore-gion: Middle Rockies West, Central Rockies (high andlow), and Southern Rockies. All sample sites in thisstudy fell into the Southern Rockies portion of theRockies Bioregion. Within the Southern Rockies

region are two flanks, western and eastern, greatlydiffering in their physiographic characteristics. Thewestern flank consists of granite based mountains,while the eastern flank is composed of sand bearingmountains (USEPA, 1999). Such differences werereflected in the substrate composition and particlesize distribution observed among RC, the MB River,and the LMB River (Table 2). Consequently, referenceor minimally impacted conditions are certain to bedifferent between the two. Analysis reveals less thanfive reference and/or test sites located in the easternflank, while more than ten sites exist for the westernflank (B.K. Jessup and J.B. Stribling, 2002, unpub-lished report, Tetra Tech., Inc.). The spatial distribu-tion illustrates that reference and stressed sites arenot evenly distributed within the Southern RockiesBioregion and that a greater number of sites areneeded in the eastern flank to capture regional land-scape heterogeneity. The LMB River was the one riversampled that drained this geographic area. Theauthors understand that in sampling large geographicareas, exceptional streams within bioregions willexhibit different biologic potentials because of chemi-cal and physical discrepancies among streams. How-ever, conditions in the eastern flank do not seemexceptional, but pervasive. Consequently, the authorsbelieve adequate reference and impaired streamreaches have not been identified for this geographicarea, and inaccurate classifications of stream integri-ty are likely to result for streams draining this region.Considering the geologic diversity of Wyoming andothers states in the Rocky Mountain region, the iden-tification of such anomalies highlights the importanceof recalibration procedures incorporating data collect-ed at both the regional and watershed scale.

The misclassification of sites on the LMB River asimpaired is contrasted by sites on RC, which wereproperly classified as impaired or threatened. Thestream reach RC-3 scored Poor, and following theWSII it is degraded because of habitat conditions(e.g., high sediment loads, excessive embeddedness,and insufficient flows). Macroinvertebrate assem-blages shifted from a community dominated by rela-tively pollution intolerant taxa at RC-2 to pollutiontolerant taxa at RC-3. Changes in macroinvertebrateassemblages between RC-2 and RC-3 reflect speciescapable of inhabiting environments of increased finesediment and subsequent sedimentation. Decreases intaxa numbers, increased BCI-CTQa values, andchanges in functional feeding groups support theseconclusions (Table 5).

Historic and present flood irrigation practicesbetween RC-1 and RC-3 have altered the snowmelthydrologic regime by lowering the intensity and dura-tion of flushing flows during spring runoff, as well asaverage annual bankfull conditions. For example,



mean discharge values for RC-1 (61.43 cfs or 1.74cms) were significantly greater than RC-3 (39.34 cfsor 1.11 cms; p = 0.002). Consequently, reductions inaverage annual bankfull flow conditions must favordeposition of sediment, which has been exacerbatedby ongoing drought conditions (Lane, 1955; Heede,1975). Therefore, the low index score of RC-3 can beexplained by three factors: its downstream position inthe watershed, alterations to the average annualbankfull conditions, and prevailing drought conditionsin the semiarid west. All of the preceding favor depo-sition of sediment, which appears to have alteredaquatic habitat conditions and made them unsuitablefor sediment intolerant biota. In contrast to the LMBRiver, taxa composition for RC did change from pollu-tion intolerant to pollution tolerant assemblagesbetween two sites. Therefore, this interpretation ofWSII results – emphasizing changes in velocity, sub-strate, suspended solids, embeddedness, and habitatconditions between RC-2 and RC-3 – demonstratesimpact to aquatic habitat.

CONCLUSION

Analysis of WSII’s response to physicochemicalvariables at the watershed scale followed a prioriexpectations. Velocity, substrate, suspended solids,and weighted habitat scores were significant predic-tors of change along longitudinal gradients frommountains through basin landscapes within a semi-arid region of the western United States. Thesecausal relationships demonstrate the capacity of theWSII to identify impairments or accelerated rates ofchange in physical parameters. Differences inmacroinvertebrate assemblages responded individual-ly to physical variables, showing distinct differencesbetween Rockies and Wyoming Basin Bioregion sitesand thus confirming the importance of this classifica-tion scheme. Results support past research thatstresses the importance of variation in stream struc-ture and function at the reach and watershed scales.

Despite strong relationships with physical vari-ables, anomalies did exist where habitat conditionswere good or gradients were naturally occurringdespite the designation of Poor index scores. Index ofbiological integrity type indices evaluate aquatic habi-tat using a multimetric approach intended to unifyconcepts for describing stream systems that functionalike. Results presented here highlight the need fortesting regionally calibrated multimetric indices atthe watershed scale in addition to the regional scale.Furthermore, sampling efforts among agencies needto be coordinated to allow the incorporation of addi-tional reference and stressed sites to ensure accurate

recalibration and development of multimetric indices.In addition, this study demonstrates the importanceof interpreting individual core metrics, as well as rela-tionships of index values with physical variableswhen using biological indicators to develop state andfederal listings of impaired water bodies.

ACKNOWLEDGMENTS

This research was supported by grants from the Medicine BowConservation District and the Rangeland Ecology and WatershedManagement Department at the University of Wyoming. Theauthors thank Tom Barnes and Steve Holzerland for their hardwork with data collection and logistical support. The authors alsogreatly appreciate the comments of Bob Hall and three anonymousreviewers.

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STREAM ASSESSMENTS USING BIOTIC INDICES: RESPONSES TO PHYSICOCHEMICAL VARIABLES