U.S. Department of the Interior

U.S. Geological Survey

Water-Resources Investigations Report 01–4145

Prepared in cooperation with

Idaho Department of Environmental Quality

Evaluation of Macroinvertebrate Assemblages in

Idaho Rivers Using Multimetric and Multivariate

Techniques, 1996–98
Cover photo: Clockwise from top left: Sampling for benthic macroinvertebrates in the Big Lost River, 

Idaho (photograph by T.R. Maret, U.S. Geological Survey); the caddisfly Wormaldia; the stonefly 

Hesperoperla; the mayfly Ameletus; the mayfly Drunella; the caddisfly Psychoglypha (Photographs of 

invertebrates courtesy of Steven V. Fend and James L. Carter, National Research Program, U.S. 

Geological Survey, Menlo Park, California; and Saelon Renkes, freelance photographer, published with 

permission)
Evaluation of Macroinvertebrate Assemblages in 

Idaho Rivers Using Multimetric and Multivariate 

Techniques, 1996–98

By Terry R. Maret, Dorene E. MacCoy, Kenneth D. Skinner, Susan E. Moore, and

Ivalou O’Dell

Water-Resources Investigations Report 01–4145

Prepared in cooperation with

Idaho Department of Environmental Quality

Boise, Idaho

2001
U.S. DEPARTMENT OF THE INTERIOR

GALE A. NORTON, Secretary

U.S. GEOLOGICAL SURVEY

Charles G. Groat, Director

Any use of trade, product, or firm names in this publication is for descriptive purposes only and does not imply 

endorsement by the U.S. Government.

Additional information can be 

obtained from:

District Chief

U.S. Geological Survey

230 Collins Road

Boise, ID 83702-4520

http://idaho.usgs.gov

Copies of this report can be 

purchased from:

U.S. Geological Survey

Information Services

Box 25286

Federal Center

Denver, CO 80225

e-mail: infoservices@usgs.gov

Copies of this report also are 

available in PDF format, which 

can be viewed using Adobe 

Acrobat Reader, at URL:

http://idaho.usgs.gov/public/

reports.html 
Contents iii

CONTENTS

Contents

Abstract .................................................................................................................................................................................... 1

Introduction .............................................................................................................................................................................. 1

Purpose and scope............................................................................................................................................................. 3

Description of Idaho statewide surface-water quality monitoring program ..................................................................... 3

Description of study area .................................................................................................................................................. 6

Acknowledgments............................................................................................................................................................. 10

Data collection methods ........................................................................................................................................................... 10

Macroinvertebrate collection and processing.................................................................................................................... 10

Macroinvertebrate onsite and laboratory quality assurance.............................................................................................. 11

Environmental variables ................................................................................................................................................... 12

Analytical methods................................................................................................................................................................... 14

General approach .............................................................................................................................................................. 14

Macroinvertebrate assemblages and metrics..................................................................................................................... 15

Multivariate analyses ........................................................................................................................................................ 21

Principal components analysis................................................................................................................................... 22

Detrended correspondence analysis........................................................................................................................... 22

Canonical correspondence analysis ........................................................................................................................... 22

Results of macroinvertebrate taxa and metrics ........................................................................................................................ 23

Comparison of RTH and QMH sample types................................................................................................................... 24

Summary of coldwater taxa .............................................................................................................................................. 24

Evaluation of the invertebrate river index......................................................................................................................... 27

Summary of invertebrate river index scores and metrics.................................................................................................. 30

Relation of macroinvertebrate assemblages to environmental variables ................................................................................. 30

Principal components analysis .......................................................................................................................................... 31

Canonical correspondence analysis................................................................................................................................... 31

Summary and conclusions........................................................................................................................................................ 34

References cited ....................................................................................................................................................................... 36

Supplemental information:

Table A. Macroinvertebrates collected from selected sampling sites in the Idaho statewide surface-water 

quality monitoring program, 1996–98 ....................................................................................................................... 43

Table B. Comparison of macroinvertebrate quality assurance data for selected sites in the Idaho statewide 

surface-water quality monitoring program, 1996–98 ................................................................................................ 67

FIGURES

1. Map showing location of the area comprising the Idaho statewide surface-water quality monitoring program....... 4

2. Map showing major land uses and locations of macroinvertebrate and other sampling sites in the Idaho 

statewide surface-water quality monitoring program................................................................................................. 7

3. Boxplots showing invertebrate river index (IRI) scores in relation to selected metrics for the qualitative 

multiple habitat (QMH) and richest targeted habitat (RTH) samples collected from macroinvertebrate 

sampling sites, Idaho statewide surface-water quality monitoring program, 1996–98.............................................. 25

4. Graph showing percent and number of coldwater taxa collected by site type for richest targeted 

habitat (riffle) samples, Idaho statewide surface-water quality monitoring program, 1996–98 ................................ 26

5. Graph showing detrended correspondence analysis (DCA) ordination plot of macroinvertebrate sampling 

sites, Idaho statewide surface-water quality monitoring program, 1996–98.............................................................. 27

6. Boxplots showing invertebrate river index (IRI) scores in relation to selected metrics for high-quality (12) 

and low-quality (12) sites, Idaho statewide surface-water quality monitoring program, 1996–98............................ 28
iv Evaluation of Macroinvertebrate Assemblages in Idaho Rivers Using Multimetric and Multivariate Techniques, 1996–98

7–11. Graphs showing:

7. Invertebrate river index (IRI) scores in relation to biotic condition categories for macroinvertebrate 

sampling sites, by site type, Idaho statewide surface-water quality monitoring program, 1996–98................. 29

8. Principal components analysis (PCA) ordination plot of macroinvertebrate sampling sites, by site type, 

based on eight metrics, Idaho statewide surface-water quality monitoring program, 1996–98 ........................ 30

9. Principal components analysis (PCA) axis 1 scores in relation to number of Ephemeroptera, Plecoptera, 

and Trichoptera (EPT) taxa for macroinvertebrate sampling sites in the Idaho statewide surface-water 

quality monitoring program, 1996–98............................................................................................................... 31

10. Canonical correspondence analysis (CCA) ordination plot of macroinvertebrate sampling sites in 

relation to selected environmental variables, Idaho statewide surface-water quality monitoring program, 

1996–98 ............................................................................................................................................................. 32

11. Canonical correspondence analysis (CCA) ordination plot of taxa in relation to selected environmental 

variables, Idaho statewide surface-water quality monitoring program, 1996–98 ............................................. 33 

TABLES

1. Basin and site characteristics for all sites in the Idaho statewide surface-water quality monitoring program, 

1996–98 ...................................................................................................................................................................... 8

2. Habitat characteristics for macroinvertebrate sampling sites in the Idaho statewide surface-water quality 

monitoring program, 1996–98.................................................................................................................................... 12

3. Relative total abundances and occurrence of taxa in richest targeted habitat (riffle) samples collected from 

40 macroinvertebrate sampling sites in the Idaho statewide surface-water quality monitoring program, 

1996–98 ...................................................................................................................................................................... 16

4. Macroinvertebrate metrics and invertebrate river index (IRI) scores for selected sampling sites in the Idaho 

statewide surface-water quality monitoring program, 1996–98................................................................................. 20

5. Principal component factor loadings for environmental variables from principal components analysis (PCA) 

for all sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98 .......................... 23

6. Summary of correspondence analysis including canonical coefficients and t-values of canonical coefficients 

for environmental variables, Idaho statewide surface-water quality monitoring program, 1996–98......................... 32
Contents v

CONVERSION FACTORS, VERTICAL DATUM, AND OTHER ABBREVIATED UNITS

Multiply By To obtain

centimeter (cm) 0.3937 inch

cubic meter per second (m3/s) 35.31 cubic foot per second

hectare (ha) 2.471 acre

kilometer (km) 0.6214 mile

liter (L) 0.2642 gallon

meter (m) 3.281 foot

millimeter (mm) 0.03937 inch

square meter (m2) 10.76 square foot

square kilometer (km2) 0.3861 square mile

Temperature in degrees Celsius (°C) can be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8) (°C)+32

Sea level: In this report, “sea level” refers to the National Geodetic Vertical Datum of 1929—a geodetic datum derived from 

a general adjustment of the first-order level nets of the United States and Canada, formerly called Sea Level Datum of 1929. 

Other abbreviated units:

μm micrometer

μS/cm microsiemens per centimeter

mg/L milligram per liter

Outlier

3rd Quartile plus 1.5

 times the IQR

Outlier

1st Quartile minus 1.5

 times the IQR

Median

3rd Quartile

1st Quartile

Explanation for boxplots

shown in figures 3 and 6

Interquartile range

(IQR)
Introduction 1

Evaluation of Macroinvertebrate Assemblages in 

Idaho Rivers Using Multimetric and Multivariate 

Techniques, 1996–98

By Terry R. Maret, Dorene E. MacCoy, Kenneth D. Skinner, Susan E. Moore, and

Ivalou O’Dell

Abstract

Macroinvertebrate assemblages and environmental variables were evaluated as part of the Idaho 

statewide surface-water quality monitoring program 

during 1996–98. Two assessment approaches were 

used to evaluate the macroinvertebrate data collected from Idaho rivers—biological metrics and 

multivariate statistical analyses. A total of 247 macroinvertebrate taxa were identified in semiquantitative riffle habitat (richest targeted habitat; RTH) 

and qualitative multiple habitat (QMH) samples, 

which were collected from 40 sampling sites. Riffles supported most of the taxa collected at all sites. 

One hundred and eighty-four taxa (74 percent of 

total taxa) were identified in the RTH samples. 

Taxa considered abundant in RTH samples included 

Oligochaeta, Baetis tricaudatus, Hydropsyche, 

Simuliidae, Chironomidae pupae, Cricotopus, 

Eukiefferiella, and Orthocladius complex. Comparisons of RTH and QMH sample types indicated 

little difference in various metrics evaluated; either 

sample type could be used to evaluate biological 

condition. Fourteen coldwater taxa were collected 

during this study at 12 sampling sites, representing 

only about 6 percent of all taxa collected and a frequency of occurrence of 30 percent for all sites. An 

evaluation of the Idaho Department of Environmental Quality invertebrate river index (IRI) identified 

statistically significant differences between highand low-quality sites, providing evidence that the index can successfully discriminate impairment. IRI 

scores for all sampling sites identified 25 percent 

of the sites with poor biotic condition and 68 percent with good biotic condition. Maximum temperatures at 62 percent of all sampling sites exceeded Idaho’s instantaneous coldwater temperature criteria of 22°C. No correspondence was evident between ecoregion percentages upstream 

from each site and macroinvertebrate assemblages. 

Multivariate analyses of RTH samples identified 

various environmental variables operating at different spatial scales that affect the macroinvertebrate assemblages in Idaho rivers. Six environmental variables—percent forested land, percent 

agricultural land, urban land, maximum water 

temperature, percent substrate fines, and stream 

gradient—were significant in describing variance 

in the macroinvertebrate assemblages. Two distinct groups of sites and associated taxa were identified: one represented high-gradient, coldwater, 

forested and rangeland sites, and the other represented sites influenced by human disturbance, 

indicated by increased percent substrate fines and 

increased water temperatures typically associated 

with agricultural and (or) urban land uses. 

INTRODUCTION

Introduction

In 1990, the U.S. Geological Survey (USGS), in 

cooperation with the Idaho Department of Environmental Quality (IDEQ), implemented a statewide 

water-quality monitoring program (SWQP) in response 

to Idaho’s antidegradation policy as required by the 

Clean Water Act (Clark, 1990). The program objective 

was to provide water-quality managers with a coordinated, statewide network to detect trends in surfacewater quality. A consistent, integrated assessment of 

water quality will provide water managers, policy makers, and the public with an improved scientific basis for 

evaluating effectiveness of water-quality management 

programs in principal river basins throughout Idaho.

Human activities can alter the physical, chemical, 

or biological processes of surface water. Such alter-
2 Evaluation of Macroinvertebrate Assemblages in Idaho Rivers Using Multimetric and Multivariate Techniques, 1996–98

ations, in turn, can cause changes in the resident 

aquatic biological assemblages. Monitoring the health 

of these assemblages can complement other physical 

and chemical water-quality assessment methods and, 

thus, can provide a more complete evaluation of waterresource conditions (Karr, 1991). According to Allan 

and Flecker (1993), protecting or managing ecosystems and associated biological diversity requires development of ways to monitor ecosystem health. Measuring changes in fish, macroinvertebrate, and algal 

assemblages can provide an index of water quality and 

trends that affect beneficial uses of surface-water 

resources, detect problems that other methods might 

miss or underestimate, and provide a systematic process for measuring progress of pollution abatement 

programs (Intergovernmental Task Force on Monitoring, 1995). 

Macroinvertebrates have been used extensively to 

assess the status and trends of aquatic life in rivers. 

Hardy and others (1995) reported trends in benthic 

invertebrates, along with other physical and chemical 

measures of stream water quality, for a cooperative 

program between the USGS and Chester County, Pennsylvania. Maret (1995) summarized a number of studies that have used macroinvertebrates to assess water 

quality of streams in the upper Snake River Basin. 

Macroinvertebrates inhabit most streams and are a key 

component in processing of organic material and in 

nutrient cycling and are an important food source for 

fish and other aquatic organisms. These organisms are 

easy to collect, relatively sessile, and have specific 

environmental requirements to complete their life 

cycle. Macroinvertebrate assemblages are excellent 

indicators of long-term environmental changes such as 

siltation (Lenat and others, 1981) and point-source pollutants of short duration (Prophet and Edwards, 1973). 

Macroinvertebrates integrate the effects of upstream 

land and water uses in a basin over the long term 

(months to years) because most of their life cycle is 

spent in the water.

Use of biological attributes, or metrics, to describe 

water quality is increasing. Recent State and Federal 

program developments in biological monitoring have 

emphasized more direct measures of biotic integrity to 

assess beneficial use status and trends (Plafkin and others, 1989; Hayslip, 1993). A metric is an enumeration 

representing an assemblage characteristic or combination of characteristics that changes in a predictable way 

with increased human influence (Karr and others, 1986). 

Several macroinvertebrate indices using a variety of 

metrics have been developed in the Northwest as tools 

to help evaluate water quality and biotic integrity. 

Among these are an index identifying urban effects in 

the Puget Sound Lowlands in Washington (Kleindl, 

1995), forestry effects in Oregon (Fore and others, 

1996), and an evaluation of least-disturbed small 

streams in the Cedar River watershed of Washington 

(Black and MacCoy, 2000). The IDEQ recently has 

developed biological monitoring protocols to assess 

beneficial uses of medium and large rivers (Grafe, 

2000) based, in part, on studies by the Idaho State University, Stream Ecology Center (Royer and Minshall, 

1996; Royer and others, 2001). In addition, the USGS, 

through the National Water-Quality Assessment 

(NAWQA) Program, has included comprehensive 

monitoring protocols to assess aquatic life and associated habitat quality (Gurtz, 1994). These studies have 

shown that aquatic biological assemblages are effective 

integrators of stream conditions, including chemical 

and habitat changes that have resulted from human 

activities in river basins. Therefore, evaluation of these 

assemblages can be useful in assessing biotic integrity 

and associated designated beneficial uses such as coldwater biota and salmonid spawning.

The Idaho SWQP, which began with a focus on 

water chemistry, was expanded in 1996 to a more integrated monitoring network that included biological 

information to more effectively assess instream beneficial uses. Major components of this assessment were 

the collection of aquatic macroinvertebrates from a 

variety of stream habitats and measurement of associated environmental variables.

Two assessment approaches were used to evaluate 

the macroinvertebrate data collected from Idaho rivers—biological metrics and multivariate statistical 

analyses. First, biological metrics relate specific measures of assemblage structure, composition, and functional attributes to a minimally disturbed system (Karr 

and others, 1986). The metric approach is dependent on 

regional biological and environmental reference information to score individual metrics (Miller and others, 

1988). A metric score can be used as a single numeric 

index, such as the number of species (or taxa), or combined into a comparative rating of multiple metrics, 

such as U.S. Environmental Protection Agency’s 

(USEPA) rapid bioassessment protocols (Plafkin and 

others, 1989; Barbour and others, 1999). The multimetric approach has been advocated because several metrics, each measuring a different component of the 

assemblage, are believed to provide a more robust 
Introduction 3

assessment of ecological integrity (Fore and others, 

1996). The biological metrics approach also is most 

amenable to nonexperts. In this study, the multimetric 

approach will be evaluated.

Second, ecologists have used multivariate analyses to identify and interpret patterns in macroinvertebrate assemblage structure as they relate to environmental conditions (Gauch, 1982; Richards and others, 

1993; Frenzel, 1996). These multivariate analyses summarize patterns of association within a species-by-sample data matrix for purposes of classification. Multivariate analyses are effective for identifying similarities among sites with respect to various physical, 

chemical, and biological characteristics and for depicting relations between assemblage patterns and environmental gradients. Hypotheses also can be formulated 

from these exploratory analyses about relations 

between macroinvertebrate assemblages and environmental variables. 

Few studies have examined relations between 

macroinvertebrate assemblages and measured environmental variables across the major environmental settings of Idaho. Most macroinvertebrate studies have 

been conducted on small, wadeable streams (fourth 

order or less, after Strahler, 1957); large-river studies 

remain limited. Robinson and Minshall (1998) studied 

wadeable streams across three major ecoregions of 

Idaho. Mebane (2001) studied relations among macroinvertebrate metrics, fine-grained sediment, and metals 

in wadeable streams across four ecoregions of Idaho. 

Royer and Minshall (1996) and Royer and others 

(2001) sampled a number of medium- to large-river 

sites for IDEQ to develop multimetric indices using 

macroinvertebrates. They developed an invertebrate 

river index (IRI) that appears to function well as a bioassessment tool for both medium and large rivers in 

Idaho. However, their index consisted of only 22 sites 

and 6 validation sites from rivers across Idaho. The 

investigation documented in this report offers an independent evaluation of the IRI encompassing a wider 

variety of medium- to large-river sites and environmental conditions by using similar collection methods but 

a different laboratory for taxonomic processing. In 

addition, a number of basin-level variables were determined with a geographic information system (GIS) to 

assess landscape-scale influences, such as basin area 

and land-use variables, on macroinvertebrate assemblages. These quantitative measures of basin and habitat data facilitate evaluation of metric responsiveness to 

multiple measures of impairment, as well as to natural 

influences on macroinvertebrate assemblages.

Purpose and Scope

This report characterizes macroinvertebrate 

assemblages in medium to large rivers (fourth through 

seventh order) and a few spring streams throughout 

Idaho. Macroinvertebrate and environmental data for 

the SWQP were collected during 1996–98. Purposes 

of this report are to (1) compare results of two macroinvertebrate sampling methods—qualitative multiple 

habitat (QMH) samples and semiquantitative riffle 

habitat (richest targeted habitat, RTH); (2) characterize 

macroinvertebrate assemblages by using various metrics that previously have been identified as useful for 

evaluating Idaho rivers; (3) provide an independent 

evaluation of IDEQ’s recently developed IRI; (4) describe relations between macroinvertebrates and measured environmental variables at the landscape and 

stream habitat scale; and (5) suggest changes to improve the SWQP on the basis of evaluation of the data.

Description of Idaho Statewide SurfaceWater Quality Monitoring Program

The SWQP during 1990–95 consisted of chemical 

analyses of water samples collected at 56 sites on the 

Bear, Clearwater, Kootenai, Pend Oreille, Salmon, 

Snake, and Spokane Rivers and their tributaries (fig. 1). 

Water samples were collected bimonthly at sites on a 

rotation of annual, biennial, or triennial schedule. A 

detailed description of the SWQP sampling schedule 

is given in a report by Clark (1990). Onsite and laboratory analyses included discharge, specific conductivity, 

pH, water temperature, dissolved oxygen, bacteria, 

alkalinity, major ions, nutrients, trace elements, turbidity, and suspended sediment (O’Dell and others, 1998). 

To provide continuous discharge records for all sites, 

sampling sites are located at existing USGS surfacewater gaging stations. The USGS actively maintains 

the chemical, physical, and hydrologic data collected 

for this program in the National Water Information 

System data base. Data collected as part of this program also have been published in Idaho’s biennial 

water-quality status reports (Clark, 1998).

In 1996, the Idaho SWQP was redesigned to include collection of macroinvertebrates, fish, fish tissue 
4 Evaluation of Macroinvertebrate Assemblages in Idaho Rivers Using Multimetric and Multivariate Techniques, 1996–98

Priest

River

Pend

River

Oreille

Pend

Oreille

Lake

Kootenai

River

Clark

Fork

Coeur

d'Alene

Lake

Flathead

Lake

Clark

Fork

Blackfoot

River

Bitterroot River

Flathead

River

St

River

Joe

Fork North

South

Fork

Coeur d'Alene

River

Palouse

River

Clearwater

River

Salmon

River

Snake

River

Lapwai

Creek

Spokane

River

116° 115°

114°

113°

117°

46°

47°

48°

118°

49° 49°

48°

47°

46°

Kalispell

Missoula

Sandpoint

Coeur

d'Alene

Figure 1. Location of the area comprising the Idaho statewide surface-water quality monitoring program. 

IDAHO

WASHINGTON

OREGON

NEVADA 

BOUNDARY

BONNER

KOOTENAI

BENEWAH

SHOSHONE

LATAH

CLEARWATER

IDAHO

NEZ

PERCE

LEWIS

SPOKANE

WHITMAN

LINCOLN

ADAMS

PEND

OREILLE LINCOLN

SANDERS

FLATHEAD

MINERAL

LAKE

MISSOULA

POWELL

RAVALLI

GRANITE

DEER

LODGE

SILVER

BOW

LEWIS

AND

CLARK
Introduction 5 Base from U.S. Geological Survey digital data, 1:250,000, 1994; Albers Equal-Area projection Standard parallels 43° 30', 47° 30', and -114° 00', 41° 45' No false easting or false northing 0 25

0 25

50 

River

Weiser

Silver

Creek

American

Falls

Reservoir

River

Snake

River

Payette

River Boise

River

Snake

River

Bruneau

River

Big

River

Little

Wood

Wood

River

Big

Lost

River

Salmon

River

Lemhi

River

Pahsimeroi

Bear

River

River

Portneuf

River

Blackfoot

Snake

Riv

Henrys

Teton

Fork

Creek Johnson

Salmon

Falls

Creek

Rock

Creek

Creek

Marsh

Creek

Willow

Creek

Creek

Camas

Beaver

112° 

112°

113°

114°

115°

116°

117°

42°

43°

44°

45° 45°

118°

Boise

Twin

Falls

Pocatello

Idaho

Falls

CANYON

ADA

GEM

PAYETTE

WASHINGTON

ADAMS

VALLEY

LEMHI

BOISE

CUSTER

CAMAS BLAINE

ELMORE

GOODING

LINCOLN

OWYHEE

JEROME

TWIN

FALLS

BUTTE

CLARK

JEFFERSON

MINIDOKAPOWER

CASSIA

BANNOCK

BEAR

LAK

CARIBOU

ONEIDA

BONNEVILLE

FRANKLIN

FREMONT

TETO

MADISON

BINGHAM

HUMBOLT

ELKO

BOX ELDER

BAKER

MALHEUR

CACHE

RIC
6 Evaluation of Macroinvertebrate Assemblages in Idaho Rivers Using Multimetric and Multivariate Techniques, 1996–98

contaminants, and associated stream habitat parameters 

at 40 of the 56 SWQP sites to more effectively assess 

the status and trends of stream quality in Idaho. Much 

of the biological data collected for this program can be 

accessed on the World Wide Web (idaho.usgs.gov/

public/wq/index.html). In addition, chemical analysis 

sampling frequency was increased to monthly from 

April to September—a period of increased recreational 

use of Idaho rivers. Biological sampling was targeted 

for summer/fall low-flow conditions, when coldwater 

biota (a primary beneficial use) are most limited as a 

result of reduced streamflow, which causes thermal 

stress and habitat loss. SWQP biological monitoring 

sites were divided into three regions—southeastern, 

southwestern, and northern. Biological monitoring sites 

were sampled once over a 3-year rotation in each of the 

three regions. All biological monitoring sites in the 

SWQP were sampled once during 1996–98 for macroinvertebrates (fig. 1). These collections included both 

RTH and QMH samples. Also during this time, 15 of 

these sites were sampled to characterize the fish assemblages and analyze fish tissue for organic and inorganic 

contaminants (not evaluated in this report). Basin and 

site characteristics for all sites in the SWQP are shown 

in table 1.

Description of Study Area

Idaho consists of a vast and varied geography 

throughout 11 ecoregions (Omernik and Gallant, 1986, 

table 1). Ecoregions are areas with similar land use, 

vegetation, soils, and land surface forms and have been 

found to be useful in organizing water-resource information (Hughes and Larsen, 1988; Whittier and others, 

1988). 

The State spans 7 degrees of latitude from 42°N at 

its southern border with Nevada to 49°N at its northern 

border with Canada. Major river basins include the 

Bear, Clearwater, Kootenai, Pend Oreille, Salmon, 

Snake, and Spokane and their tributaries. Most of the 

sampling sites in this study are located in the Snake 

River Basin/High Desert and Central Basin and Range 

ecoregions. 

Rangeland and forested land dominate the landscape and compose almost 80 percent of the State 

(fig. 2). Agriculture composes only 14.5 percent of 

the landscape but is the primary water user. Although 

Idaho has a small population of just over 1 million, it 

has one of the largest amounts of irrigated cropland 

(fifth in the Nation), according to the 1997 Census of 

Agriculture (U.S. Department of Agriculture, Farm and 

Ranch Irrigation Survey, Census of Agriculture, table 

4, accessed April 2000, online). Most of the surface 

water in Idaho is appropriated for urban and agriculture 

uses (Frenzel, 1987). In the central part of the State, 

much of the land is national forest and wilderness, and 

water use is minimal.

 Nonpoint-source pollution and water diversions 

are the predominant influences on surface-water quality in the State (Idaho Department of Health and Welfare, 1998). Pollutants of greatest concern that have 

been associated with habitat degradation of streams 

include nutrients, fine-grained sediment, bacteria, organic waste, and elevated water temperature. Beneficial 

uses of streams most impaired by pollutants include 

coldwater biota, salmonid spawning, and water contact 

recreation (Idaho Department of Health and Welfare, 

1998). Water transfer from one river basin to irrigate 

crops in another is common practice in most of southern Idaho. The ecological consequences of this practice 

include changes in streamflow, introduction of exotic 

species, alteration of habitat, and changes in water 

quality (Meador, 1992).

Elevations range from about 225 m above sea 

level where the Snake River leaves Idaho to 3,859 m at 

Borah Peak in east-central Idaho. Sampling site elevations range from about 300 m to just over 2,000 m. Precipitation varies widely with topography; average rainfall is about 56 cm a year (Frenzel, 1987). The climate 

of Idaho is primarily arid during summer. Precipitation 

is primarily winter snowfall, and peak flows in streams 

result from spring snowmelt.

The southern basins are mainly in semiarid, high 

desert plains and contain the greatest population densities. For example, the population of two counties outside the city of Boise (Ada and Canyon), constitutes 

more than a third of the population in the State. The 

basins toward the north are mainly forested and 

sparsely populated; logging, mining, and grazing are 

the predominant land uses. Because of the diversity 

of the State’s landscape, it is a popular destination for 

sports enthusiasts and tourists. More than 60 percent of 

the land is federally owned and available for recreational activities such as hiking, fishing, hunting, and 

whitewater rafting. 

Most rivers in Idaho are presumed or explicitly 

designated such that their water quality supports coldwater biota (Grafe, 2000). Idaho’s Water Quality Standards have adopted the criteria of a maximum of 22°C 
Introduction 7

100 MILES

100 KILOMETERS

0

0

75

75

25

25

50

50

116° 115°

114°

113°

112° 111°

110°

117°

110°

111°

112°

113°

114°

115°

116°

117°

42°

43°

44°

45°

46°

47°

48°

118°

49° 49°

48°

47°

46°

45°

44°

43°

42°

118°

5

6

7

4

52

50

51

48

47

45

44

46

38

37

41

42

35 33

32

27

28

29

31

56

30

22

21

18

15

16

53

17

14 13

12 8

10

11

25

26

1

2

3

9

19

20 23 24

34

36

39

40 43

49

54

55

EXPLANATION

Agricultural

Forested

Rangeland

Urban

Other

Macroinvertebrate

sampling site and

number

Water-quality sampling

 site and number

LAND USE TYPE

(from Anderson and others, 1976)

33

20

Figure 2. Major land uses and locations of macroinvertebrate and other sampling sites in the Idaho statewide surface-water

quality monitoring program. (Basin and site characteristics shown in table 1)
8 Evaluation of Macroinvertebrate Assemblages in Idaho Rivers Using Multimetric and Multivariate Techniques, 1996–98

Table 1. Basin and site characteristics for all sites in the Idaho statewide surface-water quality monitoring program, 1996–98

[Site locations shown in figure 1; No., number; USGS, U.S. Geological Survey; latitude and longitude in degrees, minutes, and seconds; m, meters; 

km2, square kilometers; R., River; nr, near; N., North; S., South; Cr., Creek; Wash., Washington; Wyo., Wyoming; sites where only water-quality 

data were collected are shaded]

Population

USGS site Elevation density Basin Agricul- ForSite identifi- (m above Stream (people/ area Urban tural Range- ested Other

No. Site name cation Latitude/longitude sea level) order km2) (km2) land land land land land

1 Kootenai R. at Porthill . . . . . . 12322000 48°59'47"/116°30'22" 518 5 2.08 12,409 0.4 3.0 3.0 91.4 2.3

2 Clark Fork R. below

Cabinet Gorge Dam. . . . . . . . 12392000 48°05'30"/116°07'00" 628 6 4.48 55,614 .6 6.4 14.5 72.8 5.7

3 Priest R. nr Priest R. . . . . . . . . 12395000 48°12'31"/116°54'49" 637 5 .61 2,460 .6 .8 1.4 93.1 4.0

4 N. Fork Coeur d’Alene R. 

at Enaville . . . . . . . . . . . . . . . 12413000 47°34'21"/116°15'11" 640 5 .36 2,325 0 .2 1.8 97.6 .3

5 S. Fork Coeur d’Alene R. 

nr Pinehurst . . . . . . . . . . . . . . 12413470 47°33'06"/116°14'13" 667 5 16.11 738 2.6 .1 6.3 88.6 2.5

6 St Joe R. at Calder . . . . . . . . . 12414500 47°16'29"/116°11'17" 662 5 .12 2,679 0 0 7.1 92.6 .2

7 Spokane R. nr Post Falls. . . . . 12419000 47°42'11"/116°58'37" 625 6 .09 10,162 .4 0 9.7 81.5 8.4

8 Snake R. nr Heise . . . . . . . . . . 13037500 43°36'45"/111°39'33" 1,528 6 1.28 14,841 .3 5.9 25.3 60.5 8.0

9 Snake R. at Lorenzo . . . . . . . . 13038500 43°44'06"/111°52'33" 1,478 6 1.42 14,981 .3 6.4 25.2 60.1 8.0

10 Teton R. nr St Anthony . . . . . . 13055000 43°55'38"/111°36'55" 1,515 5 1.78 2,294 .2 39.5 14.9 38.3 7.0

11 Henrys Fork nr Rexburg . . . . . 13056500 43°49'34"/111°54'15" 1,465 6 4.33 8,337 .4 25.9 19.3 49.6 4.8

12 Willow Cr. nr Ririe . . . . . . . . 13058000 43°35'02"/111°44'44" 1,509 6 .46 1,661 0 21.4 50.7 21.7 6.2

13 Blackfoot R. nr Blackfoot. . . . 13068500 43°07'50"/112°28'35" 1,347 6 1.33 2,851 .1 13.7 60.2 20.8 5.1

14 Snake R. nr Blackfoot. . . . . . . 13069500 43°07'31"/112°31'06" 1,341 7 5.47 31,555 .6 19.1 28.7 44.9 6.6

15 Portneuf R. at Topaz . . . . . . . . 13073000 42°37'30"/112°05'20" 1,499 5 1.03 1,520 .2 33.6 53.3 11.5 1.4

16 Marsh Cr. nr McCammon . . . 13075000 42°37'48"/112°13'29" 1,405 5 1.86 885 1.0 52.1 32.3 14.4 .2

17 Portneuf R. at Pocatello . . . . . 13075500 42°52'20"/112°28'05" 1,347 6 8.53 3,292 1.3 36.2 51.2 10.5 .8

18 Snake R. nr Minidoka. . . . . . . 13081500 42°40'23"/113°29'58" 1,259 7 5.26 48,830 .7 23.0 37.8 32.8 5.7

19 Snake R. at Milner . . . . . . . . . 13088000 42°31'41"/114°01'04" 1,238 7 5.10 57,826 .7 22.9 39.2 29.8 7.6

20 Snake R. nr Kimberly . . . . . . . 13090000 42°35'28"/114°21'28" 1,025 7 5.07 59,097 .7 23.4 39.3 29.2 7.3

21 Blue Lakes Spring . . . . . . . . . 13091000 42°36'53"/114°28'06" 1,006 1 0 3 0 0 100 0 0

22 Rock Cr. at Daydream

 Ranch . . . . . . . . . . . . . . . . . . 13092747 42°33'47"/114°29' 42" 1,106 5 11.36 623 1.8 22.8 52.4 22.9 .1

23 Box Canyon Springs . . . . . . . 13095500 42°42' 29"/114°48' 35" 920 1 0 3 0 0 100 0 0

24 Salmon Falls Cr. nr 

Hagerman . . . . . . . . . . . . . . . 13108150 42°41' 47"/114°51' 15" 881 6 .23 5,362 0 5.1 85.1 9.4 .4

25 Camas Cr. at Red Road . . . . . 13108900 44°17'20"/111°53'31" 1,457 4 0 660 0 17.5 40.9 40.5 1.2

26 Beaver Cr. at Spencer . . . . . . . 13113000 44°21'20"/112°10'45" 1,783 4 .03 328 .2 0 68.8 29.7 1.4

27 Big Lost R. nr Chilly . . . . . . . 13120500 43°59'54"/114°01'12" 2,018 5 .40 1,141 0 .2 48.9 31.0 19.8

28 Big Wood R. nr Bellevue . . . . 13141000 43°19'40"/114°20'25" 1,469 5 5.73 2,128 .9 5.1 45.2 41.1 7.8

29 Silver Cr. nr Picabo. . . . . . . . . 13150430 43°19'22"/114°06'29" 1,478 4 1.21 152 .1 35.6 63.6 .7 0

30 Malad R. nr Gooding . . . . . . . 13152500 42°53'12"/114°48'08" 1,019 5 2.52 8,607 .4 14.2 64.7 12.8 7.9

31 Bruneau R. nr Hot Spring. . . . 13168500 42°46'16"/115°43'10" 792 6 .10 6,766 0 .4 90.4 8.9 .3

32 Snake R. nr Murphy . . . . . . . . 13172500 43°17'31"/116°25'12" 692 7 4.29 129,052 .6 19.8 54.2 19.7 5.7

33 Boise R. nr Twin Springs . . . . 13185000 43°39'33"/115°43'34" 992 6 .01 2,148 0 0 7.9 88.0 4.1

34 Boise R. below Diversion 

Dam. . . . . . . . . . . . . . . . . . . . 13203510 43°32'23"/116°05'37" 838 6 .23 6,970 0 .5 27.9 68.7 2.9

35 Boise R. at Glenwood 

Bridge . . . . . . . . . . . . . . . . . . 13206000 43°39'37"/116°16'41" 792 6 8.41 7,463 .7 .7 31.5 64.4 2.7

36 Boise R. nr Parma. . . . . . . . . . 13213000 43°46'54"/116°58'17" 669 6 26.23 10,141 2.5 12.5 34.4 47.9 2.6

37 Snake R. at Nyssa . . . . . . . . . . 13213100 43°52'34"/116°58'53" 661 7 5.02 171,363 .6 16.5 59.4 18.8 4.9

38 S. Fork Payette R. at 

Lowman. . . . . . . . . . . . . . . . . 13235000 44°05'07"/115°37'16" 1,155 5 .16 1,157 .1 0 8.8 83.8 7.3

39 N. Fork Payette R. at 

McCall. . . . . . . . . . . . . . . . . . 13239000 44°54'27"/116°07'04" 1,514 4 4.07 379 1.9 .2 2.5 88.9 6.5

40 N. Fork Payette R. at 

Cascade . . . . . . . . . . . . . . . . . 13245000 44°31'30"/116°02'45" 1,439 6 2.93 1,601 .8 11.9 5.5 71.8 10.0

41 Payette R. nr Payette. . . . . . . . 13251000 44°02'33"/116°55'27" 652 6 3.15 8,536 .5 9.4 25.2 61.7 3.2

42 Weiser R. nr Weiser . . . . . . . . 13266000 44°16'03"/116°46'16" 672 6 .95 3,800 .2 11.8 48.2 39.7 .2

43 Snake R. at Weiser . . . . . . . . . 13269000 44°14'44"/116°58'48" 636 7 4.98 184,995 .6 16.2 57.5 21.1 4.7

44 Pahsimeroi R. at Ellis . . . . . . . 13302005 44°41'34"/114°02'51" 1,413 5 .05 2,151 0 7.5 66.7 14.2 11.5

45 Salmon R. at Salmon . . . . . . . 13302500 45°11'00"/113°53'40" 1,192 6 .61 12,982 .3 4.8 50.3 37.0 7.6

46 Lemhi R. nr Lemhi . . . . . . . . . 13305000 44°56'24"/113°38'16" 1,512 5 .25 2,349 .1 8.6 60.5 24.9 5.9

47 Johnson Cr. at Yellow Pine . . . 13313000 44°57'44"/115°29'58" 1,419 4 0 555 0 0 2.3 97.2 .5

48 Little Salmon R. at Riggins . . 13316500 45°24'47"/116°19'29" 536 5 1.04 1,491 .2 4.8 6.0 88.6 .4

49 Snake R. nr Anatone, Wash. . . 13334300 46°05'50"/116°58'36" 246 8 3.83 258,802 .5 13.8 52.1 29.2 4.4

50 Lapwai Cr. nr Lapwai . . . . . . . 13342450 46°25'36"/116°48'15" 264 5 4.09 682 .4 48.9 14.0 36.5 .2

51 S. Fork Clearwater R. at 

Stites . . . . . . . . . . . . . . . . . . . 13338500 46°05'12"/115°58'32" 400 5 2.19 3,016 .3 19.0 3.9 76.4 .4

52 Palouse R. nr Potlatch. . . . . . . 13345000 46°54'55"/116°57'00" 748 4 3.02 822 .4 23.6 .9 75.0 .1

53 Bear R. at Idaho-Utah State 

Line . . . . . . . . . . . . . . . . . . . 10092700 42°00'47"/111°55'14" 1,845 6 3.59 5,139 .6 29.5 37.1 23.3 9.7

54 Snake R. at King Hill . . . . . . . 13154500 43°00'08"/115°12'06" 760 7 4.31 92,941 .6 20.2 50.2 22.6 6.4

55 Snake R. at Flagg 

Ranch, Wyo. . . . . . . . . . . . . . 13010065 44°05'21"/110°41'38" 2,073 4 .06 1,324 0 0 8.6 82.8 8.6

56 Snake R. nr Buhl. . . . . . . . . . . 13094000 42°39'58"/114°42'41" 900 7 4.67 76,104 .7 21.3 45.8 25.4 6.8

Land use (in percent)
Introduction 9

Table 1. Basin and site characteristics for all sites in the Idaho statewide surface-water quality monitoring program, 1996–98—

Continued

Snake Montana

River Central Valley

Basin/ Basin and Wasatch Northern

Site Columbia Blue High and Northern Foothill Middle Wyoming and Uinta Canadian Basin and

No. Site name Plateau Mountains Desert Range Rockies Prairies Rockies Basin Mountains Rockies Range

1 Kootenai R. at Porthill . . . . . . 0 0 0 0 95.9 0 0 0 0 3.4 0

2 Clark Fork R. below

Cabinet Gorge Dam. . . . . . . . 0 0 0 0 59.0 16.8 0 0 0 24.1 0

3 Priest R. nr Priest R. . . . . . . . . 0 0 0 0 100 0 0 0 0 0 0

4 N. Fork Coeur d’Alene R. 

at Enaville . . . . . . . . . . . . . . . 0 0 0 0 100 0 0 0 0 0 0

5 S. Fork Coeur d’Alene R. 

nr Pinehurst . . . . . . . . . . . . . . 0 0 0 0 100 0 0 0 0 0 0

6 St Joe R. at Calder . . . . . . . . . 0 0 0 0 100 0 0 0 0 0 0

7 Spokane R. nr Post Falls . . . . 0 2.9 32.6 17.6 10.1 .1 12.8 1.9 1.5 0 20.6

8 Snake R. nr Heise . . . . . . . . . . 0 0 .2 .2 0 0 98.8 .8 0 0 0

9 Snake R. at Lorenzo . . . . . . . . 0 0 .8 .2 0 0 98.2 .8 0 0 0

10 Teton R. nr St Anthony . . . . . . 0 0 52.5 0 0 0 47.5 0 0 0 0

11 Henrys Fork nr Rexburg . . . . . 0 0 39.8 0 0 .4 59.8 0 0 0 0

12 Willow Cr. nr Ririe . . . . . . . . 0 0 12.7 65.0 0 0 22.2 0 0 0 0

13 Blackfoot R. nr Blackfoot . . . 0 0 9.3 77.1 0 0 13.6 0 0 0 0

14 Snake R. nr Blackfoot. . . . . . . 0 0 23.9 10.7 0 .1 64.9 .4 0 0 0

15 Portneuf R. at Topaz . . . . . . . . 0 0 0 100 0 0 0 0 0 0 0

16 Marsh Cr. nr McCammon . . . 0 0 0 100 0 0 0 0 0 0 0

17 Portneuf R. at Pocatello . . . . . 0 0 .5 99.5 0 0 0 0 0 0 0

18 Snake R. nr Minidoka . . . . . . 0 0 32.5 25.2 0 .1 41.9 .2 0 0 0

19 Snake R. at Milner . . . . . . . . . 0 0 38.8 25.5 0 .1 35.4 .2 0 0 0

20 Snake R. nr Kimberly . . . . . . . 0 0 40.0 25.0 0 .1 34.6 .2 0 0 .1

21 Blue Lakes Spring . . . . . . . . . 0 0 100 0 0 0 0 0 0 0 0

22 Rock Cr. at Daydream 

Ranch . . . . . . . . . . . . . . . . . . 0 0 42.0 27.0 0 0 0 0 0 0 31.0

23 Box Canyon Springs . . . . . . . 0 0 100 0 0 0 0 0 0 0 0

24 Salmon Falls Cr. nr 

Hagerman . . . . . . . . . . . . . . . 0 0 3.5 31.5 0 0 0 0 0 0 65.0

25 Camas Cr. at Red Road . . . . . 0 0 28.2 0 0 .1 71.7 0 0 0 0

26 Beaver Cr. at Spencer . . . . . . . 0 0 3.3 0 0 29.5 67.1 0 0 0 0

27 Big Lost R. nr Chilly . . . . . . . 0 0 0 0 100 0 0 0 0 0 0

28 Big Wood R. nr Bellevue . . . . 0 0 11.7 0 88.3 0 0 0 0 0 0

29 Silver Cr. nr Picabo. . . . . . . . . 0 0 100 0 0 0 0 0 0 0 0

30 Malad R. nr Gooding . . . . . . . 0 0 64.9 0 35.1 0 0 0 0 0 0

31 Bruneau R. nr Hot Spring. . . . 0 0 6.6 19.5 0 0 0 0 0 0 73.9

32 Snake R. nr Murphy . . . . . . . . 0 0 39.6 22.9 5.7 .1 18.3 2.7 2.1 0 8.4

33 Boise R. nr Twin Springs . . . . 0 0 0 0 100 0 0 0 0 0 0

34 Boise R. below Diversion 

Dam. . . . . . . . . . . . . . . . . . . . 0 0 23.2 0 76.8 0 0 0 0 0 0

35 Boise R. at Glenwood

Bridge . . . . . . . . . . . . . . . . . . 0 0 28.3 0 71.7 0 0 0 0 0 0

36 Boise R. nr Parma . . . . . . . . . 0 0 47.2 0 52.8 0 0 0 0 0 0

37 Snake R. at Nyssa . . . . . . . . . 0 0 33.9 19.0 7.4 .1 13.8 2.1 1.6 0 22.1

38 S. Fork Payette R. at 

Lowman . . . . . . . . . . . . . . . . 0 0 0 0 100 0 0 0 0 0 0

39 N. Fork Payette R. at 

McCall. . . . . . . . . . . . . . . . . . 0 0 0 0 100 0 0 0 0 0 0

40 N. Fork Payette R. at 

Cascade . . . . . . . . . . . . . . . . . 0 8.3 0 0 91.7 0 0 0 0 0 0

41 Payette R. nr Payette. . . . . . . . 0 17.5 13.5 0 69.0 0 0 0 0 0 0

42 Weiser R. nr Weiser . . . . . . . . 0 97.7 2.3 0 0 0 0 0 0 0 0

43 Snake R. at Weiser . . . . . . . . . 0 0 23.4 4.1 0 .1 71.9 .4 0 0 0

44 Pahsimeroi R. at Ellis . . . . . . 0 0 47.0 0 53.0 0 0 0 0 0 0

45 Salmon R. at Salmon . . . . . . . 0 0 27.5 0 69.4 .2 2.9 0 0 0 0

46 Lemhi R. nr Lemhi . . . . . . . . 0 0 41.0 0 41.7 1.4 16.0 0 0 0 0

47 Johnson Cr. at Yellow Pine . . . 0 0 0 0 100 0 0 0 0 0 0

48 Little Salmon R. at Riggins . . 0 58.9 0 0 41.1 0 0 0 0 0 0

49 Snake R. nr Anatone, WA. . . . 2.1 12.3 25.3 12.5 18.6 .1 9.3 1.4 1.1 0 17.3

50 Lapwai Cr. nr Lapwai . . . . . . . 76.8 23.2 0 0 0 0 0 0 0 0 0

51 S. Fork Clearwater R. at 

Stites . . . . . . . . . . . . . . . . . . . 21.2 0 0 0 78.8 0 0 0 0 0 0

52 Palouse R. nr Potlatch . . . . . . 15.6 0 0 0 84.4 0 0 0 0 0 0

53 Bear R. at Idaho-Utah State 

Line . . . . . . . . . . . . . . . . . . . 0 0 0 35.5 0 0 6.7 41.8 16.0 0 0

54 Snake R. at King Hill . . . . . . . 0 0 45.2 17.9 7.9 .2 24.2 .1 0 0 4.5

55 Snake R. at Flagg Ranch. . . . . 0 0 0 0 0 0 100 0 0 0 0

56 Snake R. nr Buhl. . . . . . . . . . . 0 0 43.9 19.6 5.7 .2 29.5 .2 0 0 .9

Ecoregions (in percent)
10 Evaluation of Macroinvertebrate Assemblages in Idaho Rivers Using Multimetric and Multivariate Techniques, 1996–98

instantaneous water temperature and a maximum of 

19°C daily average temperature for the protection of 

coldwater biota beneficial use (Idaho Department of 

Health and Welfare, accessed August 2000, online). 

Waters designated for coldwater biota beneficial use 

have characteristics that support the maintenance and 

propagation of coldwater-adapted fish and other 

aquatic life. According to a presettlement account by 

Gilbert and Evermann (1895), salmon spawned in most 

of the large rivers in southern Idaho, indicating that 

suitable conditions existed to support coldwater aquatic 

life. For several of the large rivers in Idaho, this is no 

longer true (Idaho Department of Health and Welfare, 

1995).

Rivers in forested and rangeland basins are typified by coarse substrate (gravel and cobbles), high-gradient habitats, and sparse macrophyte growth. In general, the spring sites sampled had relatively fine substrate (sand and gravel), low gradients, and abundant 

macrophyte growth. Large rivers (larger than sixth 

order) in agricultural basins typically have fine-grained 

substrate, low gradients, and abundant macrophyte 

growth. 

Acknowledgments

Numerous individuals assisted in collecting and 

processing data during the course of the study, including Jay E. Bateman, Michael A. Beckwith, Joseph T. 

Bunt, Donald G. Cole, Robert W. Erickson, Keith L. 

Hein, William H. Mullins, Michael A. Nolevanko, 

Douglas S. Ott, Tomás Puga, Robert E. Reaves, James 

L. Schaefer, and Terry M. Short, all from the USGS. 

William H. Clark and Christopher A. Mebane, IDEQ, 

contributed to the monitoring network design and facilitated its support. John Keenen provided useful insights 

on multivariate analyses and interpretation. Colleague 

reviews by Robert W. Black, Mark A. Hardy, and 

Patrick M. Lambert, USGS; and William H. Clark, 

Cynthia Grafe, and Christopher A. Mebane, IDEQ, 

improved the quality of the manuscript. This study was 

jointly supported by the USGS and the IDEQ through 

several Joint Funding Agreements. 

DATA COLLECTION METHODS

Data Collection Methods

Forty sites were selected for macroinvertebrate 

sampling from a network of 56 sites. Macroinvertebrate sampling and habitat surveys were conducted 

during base-flow conditions in summer and fall 1996 

through 1998 (fig. 2, table 2). Representative reaches 

for each site were selected on the basis of criteria outlined by Meador and others (1993). Reach lengths varied with stream size (table 2) and usually contained 

repeating geomorphic channel units of riffles, runs, or 

pools.

Macroinvertebrate Collection and 

Processing

QMH and RTH macroinvertebrate samples were 

collected and processed using procedures described in 

a report by Cuffney and others (1993). At each site, 

qualitative samples were collected from all accessible 

instream habitats and composited to form a single QMH 

sample. QMH samples were collected using a D-frame 

kick net equipped with a 210-μm-mesh net. Handpicking and scraping of large substrate such as wood snags, 

macrophytes, and large rocks also supplemented this 

sample type. The effort generally consisted of two people spending about 1 hour of collection time within a 

reach. An effort was made to sample each habitat type 

for an amount of time proportional to the relative abundance of macroinvertebrates in the stream reach. The 

QMH sample provided a comprehensive estimate of 

the variety of taxa present at each site. Five separate 

RTH samples (total area of 1.25 m2) were collected 

from one or more riffles and composited to form a single RTH sample at each of the 40 sites. The RTH samples were collected using a 0.25-m2 Slack rectangular 

kick net (0.5 m wide and 0.25 m high) equipped with 

a 425-μm-mesh net (Cuffney and others, 1993). 

The sampling area was delineated by a metal frame 

attached to the front of the sampler. Large gravel and 

cobbles within each 0.25-m2 area were brushed to dislodge organisms, then this entire area was disturbed by 

kicking for 30 seconds. Samples were collected in upstream order to prevent disturbance of the streambed 

prior to sampling.

Onsite processing consisted of elutriation of each 

sample by repeated washing with a 425-μm-mesh 

sieve. Large substrate and other organic debris such as 

large leaves and twigs were removed. The composited 

samples were placed in labeled, 1-L plastic jars; fixed 

with 10-percent-buffered formalin, and shipped to the 
Data Collection Methods 11

contract laboratory, Aquatic Biology Associates, Inc., 

Corvallis, Oregon, for taxonomic processing. 

 In the laboratory, a minimum of 500 organisms 

were randomly subsampled using a tray marked with a 

series of grids. Organisms were sorted, identified, and 

enumerated by experienced technicians using a dissecting scope at 6X or 12X power. A large-rare search of 

organisms was done after sorting, and these organisms 

were added to the sample total. A sorting efficiency of 

95 percent or better was maintained by a random check 

on at least 10 percent of the samples. Standard bench 

sheets were used to record the counts, and these were 

transferred to electronic files (Aquatic Biology Associates, Inc., accessed April 2000, online). All taxonomic 

data were tabulated and reported for each site by sample type (table A, back of report). Selected taxa were 

retained for voucher specimens and deposited in the 

Orma J. Smith Museum of Natural History, Albertson 

College, Caldwell, Idaho.

Macroinvertebrate Onsite and Laboratory 

Quality Assurance

So that taxonomic consistency among laboratories 

could be compared, composite samples were split onsite at three sites to evaluate intra- and interlaboratory 

precision for QMH and RTH samples (table B, back of 

report). One of each of the sample splits was sent to the 

contract laboratory, and the other was sent to the USGS 

National Water Quality Laboratory in Denver, Colorado, for processing.

Generally, the intralaboratory sample comparisons 

for the contract lab showed an acceptable level of precision. Intralaboratory comparisons were made for two 

RTH samples (sites 21 and 26, table B). Relative differences in total number of taxa for these sites were 12 

and 11 percent, respectively. Relative differences in 

abundance (individuals/m2) were 31 and 23 percent, 

respectively. EPT (Ephemeroptera, Plecoptera, and Trichoptera) taxa differed by only one taxon for both sites, 

4 versus 5 (site 21) and 23 versus 24 (site 26). The final 

IRI scores were identical for both intralaboratory comparisons. 

Interlaboratory duplicate sample comparisons for 

QMH and RTH samples were variable. Relative differences in total number of taxa and EPT taxa for the only 

QMH sample split (site 21) were 6 and 40 percent, 

respectively. The relative differences should be interpreted with caution, especially with low numbers of 

taxa, which can greatly influence this statistic. The 

QMH comparison for site 21 showed differences in the 

level of taxonomic resolution reported by each laboratory. For example, the contract laboratory reported the 

New Zealand mud snail to species level (Potamopyrgus 

antipodarum), whereas the USGS laboratory assigned 

these to the family Hydrobiidae. The contract lab also 

assigned many of the gastropods to a lower level of taxonomy. This is likely due to the contract laboratory 

personnel having more knowledge of local and 

regional species occurrences and taxonomy. 

Interlaboratory sample comparison showed the 

greatest variability for the RTH split sample—relative 

differences in total number of taxa and EPT taxa were 

71 and 91 percent, respectively. Again, the level of taxonomy reported from each laboratory is the primary 

reason for these higher percent differences. The main 

discrepancy between these samples was the absence of 

chironomid taxa in the sample processed by the contractor. The lack of chironomid taxa in this sample was 

probably the result of the unusually high abundance of 

Hydropsyche (more than 34,000/m2) that were counted 

before chironomid larvae were encountered in the subsampling grids. Also, because of the small size of these 

taxa, they would not have been selected as part of the 

large-rare search upon completion of the subsampling 

(Bob Wisseman, Aquatic Biology Associates, Inc., 

Corvallis, Oregon, oral commun., 2000). The relative 

difference in RTH abundance (individuals/m2) between 

laboratories was 50 percent, somewhat larger than the 

intralaboratory comparisons. Even though there were 

large differences in the total number of taxa and EPT 

taxa, the IRI scores for split samples (IRI scores of 11 

and 5) both indicated poor habitat condition (IRI score 

less than or equal to 13). 

The large interlaboratory differences indicate the 

importance of using the same laboratory for consistency in taxonomic determinations and also of standardizing the resolution required for determination of 

metric values used to calculate biotic indices such as 

the IRI. In contrast, intralaboratory variations did not 

significantly affect the IRI scores. These quality assurance samples provide valuable information about the 

performance standards of laboratories and should continue be a vital part of the monitoring program to 

ensure the integrity of the taxonomic data.
12 Evaluation of Macroinvertebrate Assemblages in Idaho Rivers Using Multimetric and Multivariate Techniques, 1996–98

Environmental Variables

Site characterization was based on a tiered design 

that incorporated information at various spatial scales 

(Meador and others, 1993). A variety of environmental 

variables consisting of basin, reach, and instream habitat characteristics were evaluated for each site (tables 1 

and 2). Several sources were used to construct geographic data layers for some characteristics. Basin size, 

ecoregion, land use, and stream order were determined 

using ArcView, a GIS application. Basin boundaries 

were delineated using the hydrography and hydrologic 

unit boundary data layers (U.S. Geological Survey, 

1975). Ecoregions were determined from a report by 

Omernik and Gallant (1986). Land use was modified 

Table 2. Habitat characteristics for macroinvertebrate sampling sites in the Idaho statewide surface-water quality monitoring 

program, 1996–98

[Site locations shown in fig. 2; No., number; m, meters; m3/s, cubic meters per second; m/s, meters per second; μS/cm, microsiemens per centimeter; mg/L, milligrams per liter; °C, degrees Celsius; N., north; R., river; S., south; nr, near; Cr., creek; (H), high-quality site; (L), low-quality 

site; Site type: F, forested; A, agricultural; R, rangeland; LR, large river; S, spring; e, estimated value from discharge measurement]

Reach Stream Stream Stream Specific Percent Percent

Site Sample Site length depth1 width Discharge velocity1 conductance open substrate

No. Site name date type (m) (m) (m) (m3/s) (m/s) (μS/cm) canopy1 fines1

4 N. Fork Coeur d’Alene R. 

at Enaville (H) . . . . . . . . . . 6/16/98 F 479 0.30 61 42.20 0.98 43 68 0

5 S. Fork Coeur d’Alene R. 

nr Pinehurst . . . . . . . . . . . . 6/18/98 F 292 .18 19 14.16 .92 162 16 10

6 St Joe R. at Calder (H) . . . . . . 7/8/98 F 899 .25 80 39.65 .79 54 30 0

7 Spokane R. nr Post 

Falls (L) . . . . . . . . . . . . . . . 8/3/98 F 973 .25 55 31.15 .62 53 29 0

8 Snake R. nr Heise (H) . . . . . . 9/12/96 F 940 .22 110 267.62 .62 311 23 10

10 Teton R. nr St Anthony . . . . . 9/11/96 A 800 .19 e50 21.01 .70 335 26 0

11 Henrys Fork nr Rexburg. . . . . 8/6/96 A 730 .30 74 41.91 .39 196 6 45

12 Willow Cr. nr Ririe . . . . . . . . 8/7/96 R 150 .31 e5 1.22 .44 409 25 15

13 Blackfoot R. nr 

Blackfoot (L) . . . . . . . . . . . 8/7/96 A 200 .28 14 4.19 .81 320 31 10

14 Snake R. nr Blackfoot . . . . . . 9/10/96 LR 885 .31 e90 64.43 .64 321 9 5

15 Portneuf R. at Topaz (L) . . . . 8/14/96 A 351 .21 25 4.19 .74 727 9 25

16 Marsh Cr. nr McCammon . . . 8/13/96 A 160 .22 10 1.30 .17 780 35 30

17 Portneuf R. at Pocatello (L) . . 8/8/96 A 320 .15 12 2.92 .61 632 72 5

18 Snake R. nr Minidoka (L) . . . 7/30/96 LR 515 .48 e119 286.03 .69 333 3 10

21 Blue Lakes Spring . . . . . . . . . 7/31/96 S 187 .26 e22 4.53 .35 653 55 5

22 Rock Cr. at Daydream 

Ranch . . . . . . . . . . . . . . . . . 7/29/96 A 236 .36 e15 4.13 .94 655 59 20

25 Camas Cr. at Red Road . . . . . 7/8/97 R 194 .27 19 2.77 .44 149 13 15

26 Beaver Cr. at Spencer. . . . . . . 7/8/97 R 155 .21 9 .84 .65 426 8 5

27 Big Lost R. nr Chilly (H) . . . . 8/4/96 R 303 .20 17 6.51 .46 194 47 5

28 Big Wood R. nr 

Bellevue (H) . . . . . . . . . . . . 7/23/97 R 321 .24 30 11.33 .91 251 22 5

29 Silver Cr. nr Picabo . . . . . . . . 7/24/97 S 232 .42 16 3.77 .31 369 9 35

30 Malad R. nr Gooding (L) . . . . 7/15/97 A 209 .27 22 7.08 .74 311 20 30

31 Bruneau R. nr Hot Spring . . . 7/10/97 R 246 .32 24 12.40 .83 122 22 20

32 Snake R. nr Murphy (L). . . . . 7/16/97 LR 574 .21 141 225.14 .85 393 48 5

33 Boise R. nr Twin 

Springs (H) . . . . . . . . . . . . . 9/3/97 F 438 .17 38 15.21 .85 80 24 5

35 Boise R. at Glenwood 

Bridge. . . . . . . . . . . . . . . . . 9/11/97 R 314 .22 45 25.77 .74 78 57 15

37 Snake R. at Nyssa (L) . . . . . . 8/6/97 LR 1,120 .25 187 324.55 .64 468 6 5

38 S. Fork Payette R. at 

Lowman (H) . . . . . . . . . . . . 8/31/98 F 465 .15 55 13.03 .60 85 41 0

41 Payette R. nr Payette . . . . . . . 8/7/97 A 728 .22 87 50.13 .99 162 19 5

42 Weiser R. nr Weiser . . . . . . . . 7/14/97 A 250 .21 63 10.76 .54 121 18 5

44 Pahsimeroi R. at Ellis (H) . . . 9/1/98 R 201 .14 21 5.41 .75 383 29 0

45 Salmon R. at Salmon (H). . . . 9/1/98 R 777 .20 100 28.89 1.60 255 30 0

46 Lemhi R. nr Lemhi (H) . . . . . 9/2/98 R 230 .16 14 4.02 .62 513 74 2

47 Johnson Cr. at Yellow 

Pine (H) . . . . . . . . . . . . . . . 9/3/98 F 322 .26 20 2.80 1.78 92 78 0

48 Little Salmon R. at

Riggins (H). . . . . . . . . . . . . 9/17/98 F 310 .23 22 8.35 .52 146 38 4

50 Lapwai Cr. nr Lapwai (L) . . . 9/15/98 A 150 .17 36 .27 .45 311 51 0

51 S. Fork Clearwater R. at 

Stites. . . . . . . . . . . . . . . . . . 9/16/98 F 510 .17 43 5.66 .51 65 34 0

52 Palouse R. nr Potlatch (L) . . . 9/15/98 A 195 .13 11 .20 .55 83 37 0

53 Bear R. at Idaho-Utah State 

Line (L) . . . . . . . . . . . . . . . 8/15/96 A 300 .25 e35 12.04 .31 840 5 20

56 Snake R. nr Buhl (L) . . . . . . . 7/30/97 LR 1,285 .26 127 104.78 .60 549 31 15
Data Collection Methods 13

from 1:250,000-scale digital data (U.S. Geological 

Survey, 1986) consisting of Anderson levels I and II 

land-use classifications at a 16-ha mapping resolution 

(Anderson and others, 1976). Land use consisted of 

agricultural land (including pasture land), rangeland, 

forested land, urban land, and other (water bodies, barren rock, and tundra). Population density for each basin 

was calculated from digital data available on the World 

Wide Web (U.S. Geological Survey, digital map file of 

1990 population and housing data for the United States, 

accessed April 2000, online). Stream elevation, latitude, 

and longitude were determined from 1:24,000-scale 

topographic maps. Basin size and land use for springs 

could not be determined from maps because of the 

Table 2. Habitat characteristics for macroinvertebrate sampling sites in the Idaho statewide surface-water quality monitoring 

program, 1996–98— Continued

Dissolved Maximum Habitat

Percent Dissolved oxygen pH water quality

Site Sample substrate Stream oxygen saturation (standard temperature2 index

No. Site name date embeddedness1 gradient (mg/L) (percent) units) (°C) (percent)3

4 N. Fork Coeur d’Alene R. 

at Enaville (H) . . . . . . . . . . 6/16/98 0 0.02 10.4 116 7.6 21.9 84

5 S. Fork Coeur d’Alene R. 

nr Pinehurst . . . . . . . . . . . . 6/18/98 15 .01 14.0 140 7.3 23.7 68

6 St. Joe R. at Calder (H) . . . . . 7/8/98 15 .06 10.1 113 7.4 23.1 78

7 Spokane R. nr Post 

Falls (L) . . . . . . . . . . . . . . . 8/3/98 15 .18 8.8 115 7.7 27.1 72

8 Snake R. nr Heise (H) . . . . . . 9/12/96 15 .36 8.7 104 8.0 16.9 96

10 Teton R. nr St. Anthony . . . . 9/11/96 12 .19 9.1 106 8.3 21.0 79

11 Henrys Fork nr Rexburg. . . . . 8/6/96 50 .02 8.5 99 8.0 24.4 59

12 Willow Cr. nr Ririe . . . . . . . . 8/7/96 0 .26 10.3 110 8.3 16.0 71

13 Blackfoot R. nr 

Blackfoot (L) . . . . . . . . . . . 8/7/96 37 .34 8.7 103 8.2 25.4 62

14 Snake R. nr Blackfoot . . . . . . 9/10/96 15 .07 10.5 128 8.5 25.1 67

15 Portneuf R. at Topaz (L) . . . . 8/14/96 25 .35 7.0 88 7.8 24.9 32

16 Marsh Cr. nr McCammon . . . 8/13/96 50 .07 8.0 99 8.1 24.4 38

17 Portneuf R. at Pocatello (L) . . 8/8/96 0 .49 8.7 105 8.3 24.8 53

18 Snake R. nr Minidoka (L) . . . 7/30/96 15 .01 8.3 110 8.7 23.6 68

21 Blue Lakes Spring . . . . . . . . . 7/31/96 0 .10 9.4 108 7.7 17.8 92

22 Rock Cr. at Daydream 

Ranch . . . . . . . . . . . . . . . . . 7/29/96 50 .92 10.4 124 8.2 21.6 70

25 Camas Cr. at Red Road . . . . . 7/8/97 25 .17 12.2 175 8.6 22.9 54

26 Beaver Cr. at Spencer. . . . . . . 7/8/97 25 .62 8.8 100 8.4 21.4 79

27 Big Lost R. nr Chilly (H) . . . . 8/4/96 15 .57 12.0 132 8.1 17.3 81

28 Big Wood R. nr 

Bellevue (H) . . . . . . . . . . . . 7/23/97 15 .55 8.3 96 7.8 21.8 61

29 Silver Cr. nr Picabo . . . . . . . . 7/24/97 50 .10 8.4 104 7.8 22.3 85

30 Malad R. nr Gooding (L) . . . . 7/15/97 63 1.64 7.7 101 8.6 28.2 53

31 Bruneau R. nr Hot Spring . . . 7/10/97 15 .65 9.8 117 8.2 28.2 67

32 Snake R. nr Murphy (L). . . . . 7/16/97 25 .04 11.7 147 8.3 26.8 69

33 Boise R. nr Twin 

Springs (H) . . . . . . . . . . . . . 9/3/97 15 .34 10.2 120 7.5 22.9 75

35 Boise R. at Glenwood 

Bridge. . . . . . . . . . . . . . . . . 9/11/97 25 .36 8.7 102 7.4 19.7 67

37 Snake R. at Nyssa (L) . . . . . . 8/6/97 50 .08 10.3 131 8.1 26.9 61

38 S. Fork Payette R. at 

Lowman (H) . . . . . . . . . . . . 8/31/98 15 .83 9.0 102 7.8 19.3 67

41 Payette R. nr Payette . . . . . . . 8/7/97 25 .25 9.7 119 7.9 27.3 52

42 Weiser R. nr Weiser . . . . . . . . 7/14/97 25 .12 9.0 109 8.1 29.0 63

44 Pahsimeroi R. at Ellis (H) . . . 9/1/98 15 .18 9.8 107 8.2 20.1 91

45 Salmon R. at Salmon (H). . . . 9/1/98 15 .57 9.2 113 8.5 22.4 68

46 Lemhi R. nr Lemhi (H) . . . . . 9/2/98 15 .82 8.7 96 8.1 18.0 73

47 Johnson Cr. at Yellow 

Pine (H) . . . . . . . . . . . . . . . 9/3/98 10 1.20 9.1 97 7.8 18.0 82

48 Little Salmon R. at 

Riggins (H). . . . . . . . . . . . . 9/17/98 25 1.90 9.1 101 8.5 20.5 63

50 Lapwai Cr. nr Lapwai (L) . . . 9/15/98 25 .97 8.5 105 8.8 29.1 73

51 S. Fork Clearwater R. at 

Stites. . . . . . . . . . . . . . . . . . 9/16/98 25 .59 9.1 100 7.9 26.9 77

52 Palouse R. nr Potlatch (L) . . . 9/15/98 50 .09 7.2 85 7.7 29.2 59

53 Bear R. at Idaho-Utah State 

Line (L) . . . . . . . . . . . . . . . 8/15/96 35 .04 8.4 111 8.3 25.1 17

56 Snake R. nr Buhl (L) . . . . . . . 7/30/97 50 .07 8.3 101 8.5 22.1 53

1Average measurements taken at each riffle collection site.

2From continuous records, July-September 1996–98.

3Scores calculated using reports by Plafkin and others (1989); Hayslip (1993).
14 Evaluation of Macroinvertebrate Assemblages in Idaho Rivers Using Multimetric and Multivariate Techniques, 1996–98

small size of springs and so were estimated on the basis 

of onsite observation. 

Stream habitat characterization included data on 

reach length, stream depth, wetted stream width, discharge, stream velocity, specific conductance, percent 

open canopy, percent substrate fines, percent substrate 

embeddedness, stream gradient, dissolved oxygen, percent dissolved oxygen saturation, pH, maximum water 

temperature, and habitat quality index (HQI) (table 2). 

Stream width usually was determined at 3 to 5 equally 

spaced points within the reach. In a few cases, this measurement had to be estimated from discharge records. 

Discharge was estimated using information from continuous records collected at USGS gaging stations. 

Onsite parameters were determined following guidelines described by Wilde and Radtke (1998). Upon 

each site visit, instantaneous specific conductance and 

water temperature were measured using a calibrated 

Orion model 122 meter. Stream gradient was determined using 7.5-minute topographic maps. Dissolved 

oxygen and percent dissolved oxygen saturation were 

measured with a calibrated Orion model 260 dissolved 

oxygen meter. A calibrated Orion model 250A pH 

meter was used to measure pH. Maximum summer 

(July–September) water temperatures were determined 

by selecting the highest temperature recorded at a site 

using temperature data loggers manufactured by Onset 

Computer Corporation. Loggers were placed instream 

following procedures reported by Stevens and others 

(1975) and were preset to record continuous hourly 

water temperature. Information on instream and riparian variables was collected and summarized using the 

qualitative HQI developed by USEPA (Plafkin and others, 1989; Hayslip, 1993). HQI values were expressed 

as a percentage of the total maximum score. 

Instream habitat data were collected according to 

methods presented by Meador and others (1993) and 

Platts and others (1983). These data included measurements of percent open canopy, percent substrate fines, 

percent embeddedness of substrate, water depth, and 

water velocity. Measurements were made in association with macroinvertebrate collection at each riffle 

site. Percent open canopy for left and right banks at 

each collection site was estimated using a clinometer. 

Percent substrate fines and percent embeddedness were 

estimated visually to the nearest 10 percent. Percent 

substrate fines were defined as those particles less than 

2 mm in diameter (sand or smaller particles). Water 

depth was measured at each riffle collection site, and 

velocity was estimated at 0.6 of the depth using a 

Marsh-McBirney meter. A mean value was calculated 

to represent those habitat variables that were measured 

multiple times. Photographs were taken of all reaches 

and specific riffle habitats were sampled. 

ANALYTICAL METHODS

Analytical Methods

General Approach

The diverse range of stream types composing 

Idaho’s SWQP and the limited number of sampling 

sites distributed throughout Idaho (40 total) made it 

difficult to focus on questions relating to specific geographic areas. Therefore, the analysis focused on identifying general patterns and relations by using graphic 

displays of various macroinvertebrate metrics and 

exploratory multivariate statistical tools. Multimetric 

analyses incorporate more descriptive ecological information, whereas multivariate analyses are based on statistical algorithms. 

Multivariate analyses of macroinvertebrate assemblage and environmental data consisted of principal 

components analysis (PCA), detrended correspondence 

analysis (DCA), and canonical correspondence analysis (CCA). Each of these exploratory tools provided 

both graphical and correlative statistics to evaluate the 

data. PCA was used to summarize subsets of environmental data by identifying groups of variables that 

were highly correlated. PCA also was used to evaluate 

relations among macroinvertebrate metrics. DCA was 

used to identify major patterns in macroinvertebrate 

assemblages and to determine whether the species data 

generally followed a unimodal pattern for further analysis by CCA (Gauch, 1982). CCA was used to evaluate 

the degree to which environmental variables were associated with macroinvertebrate taxa and abundances. 

This final analysis provided a summary of the most 

important relations among measured environmental 

variables and macroinvertebrate taxa collected for all 

sites. Multimetric and multivariate analyses will be 

explained in more detail in the sections “Macroinvertebrate Assemblages and Metrics” and “Multivariate 

Analyses.”

Preliminary analysis revealed that macroinvertebrate assemblages did not correspond to ecoregions upstream from the sampling sites. This was not surprising 

because most sampling sites are large rivers that drain 

areas representing a mixture of ecoregions (table 1). 

Furthermore, according to Norris (1995), evidence 
Analytical Methods 15

suggests that macroinvertebrate assemblages are controlled more by local, rather than regional, conditions.

To facilitate data analysis, each sampling site was 

categorized into distinct site types on the basis of stream 

size and a priori classification of percentages of agricultural land, forested land, and rangeland upstream 

from each site (table 2). Generally, irrigated agriculture 

and row crop production comprised more than 10 percent of the land use in basins represented by agricultural site types; rangeland comprised more than 40 percent of the land use in basins represented by rangeland 

site types; and forested land comprised more than 60 

percent of the land use in basins represented by forested 

land site types. Maret (1997) found that fish assemblages in the upper Snake River Basin corresponded to 

these environmental variables. Large-river sites (larger 

than sixth order) were combined into a separate largeriver group because aquatic assemblages in large rivers 

are known to differ substantially from those in smaller 

streams (Vannote and others, 1980). In addition, two 

sites were assigned to a spring category because of 

their small size and proximity to spring sources.

RTH and QMH samples collected at each sampling site were compared to evaluate whether sampling 

methods provided different information that may be 

useful in water-quality studies. This type of evaluation 

is important because if only one sampling method is 

required to assess water quality, monitoring costs can 

be reduced. The results of this comparison revealed little difference between sample types. In addition, semiquantitative (RTH) samples targeted riffle areas, which 

effectively normalized this habitat sampled across all 

sites and made site comparison more appropriate. For 

these reasons, RTH samples (summarized in table 3) 

were used in all subsequent metric and multivariate 

analyses.

IRI scores for each site were calculated using the 

metrics percent dominant taxon, total number of taxa, 

EPT taxa, percent Elmidae, and percent predators 

(Grafe, 2000). Comparison of IDEQ’s IRI with the 

1996–98 data sets consisted of selecting a subset of 

least- (high-quality) and most- (low-quality) disturbed 

sites by using various indicators of human disturbance. 

Generally, streams larger than fourth order were selected 

for this comparison to reduce the influence of stream 

size. A few additional metrics—percent coldwater taxa, 

number of coldwater taxa, and abundance—also were 

included in the data analysis to offer additional information useful for evaluating macroinvertebrate data. 

These additional metrics have been found to be useful 

for evaluating fish or macroinvertebrate assemblages in 

Western rivers (Maret, 1997; Mullins, 1999; Zaroban 

and others, 1999). The selected metrics were evaluated 

using boxplots and correlation matrices and by statistically testing medians between least- and most-disturbed 

sites. Metrics also were evaluated using multivariate 

analyses to examine site patterns and relations with 

land use.

Macroinvertebrate Assemblages and 

Metrics

Prior to analysis, ambiguous taxa were removed 

from the data matrix to avoid overestimating taxa richness and diversity as a result of problems associated 

with taxonomic processing. The taxonomic contractor 

assisted with this process. Ambiguous taxa occur when 

the parent (next-highest taxonomic level) of a taxon 

exists in the data set. This happens most frequently 

when members of a genus either are too immature or 

damaged to be identified to species at one or more 

sites. This ambiguity was resolved by combining the 

species with the genus for all sites. In some cases, 

when the genus was reported but the species were very 

abundant, the genus either was dropped or its abundance was distributed among the species. If the ambiguity involved a single genus and species, the genus 

usually was reclassified to the species level. The resulting taxonomic data set provides consistency in the level 

of identification for all sites and increases the validity 

of comparisons among sites.

Macroinvertebrate assemblage data were summarized on the basis of eight metrics (table 4). These metrics consisted of the five metrics used to calculate the 

IRI (percent dominant taxon, total number of taxa, EPT 

taxa, percent Elmidae, and percent predators) and an 

additional three metrics (abundance, percent coldwater 

taxa, and number of coldwater taxa) that were considered to be useful for evaluating the data. Characteristics 

of an effective metric for measuring human disturbance 

include (1) relevance to the assemblage and sites being 

studied, (2) sensitivity to human stressors, (3) low natural variability but large response to human stressors, 

and (4) sampling cost effectiveness (Fore and others, 

1996; Karr and Chu, 1997).

The following definitions of metrics making up 

the IRI and their responses to human disturbance were 

taken primarily from a report by Grafe (2000). Percent 

dominant taxon is the relative abundance of the most 
16 Evaluation of Macroinvertebrate Assemblages in Idaho Rivers Using Multimetric and Multivariate Techniques, 1996–98

Table 3. Relative total abundances and occurrence of taxa in richest targeted habitat (riffle) samples collected from 40 

macroinvertebrate sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98

[Coldwater taxa are shaded; taxa in alphabetical order and grouped by major taxonomic categories; Abundant, greater than 1 percent of total abundance and greater than or equal to 75 percent occurrence; Common, less than 1 percent but greater than or equal to 0.005 percent of total abundance, 

and greater than 5 percent but less than 75 percent occurrence; Rare, less than 0.005 total abundance and less than 5 percent occurrence; No., number] 

No. 

of sites

where

Total Percent taxon was Percent 

Taxon Abundant Common Rare abundance1 abundance collected occurrence

Noninsect

Acari . . . . . . . . . . . . . . . . . . . . . . . . . . . X 2,909 0.759 29 72.5

Ferrissia . . . . . . . . . . . . . . . . . . . . . . . . X 43 .011 2 5.0

Fluminicola. . . . . . . . . . . . . . . . . . . . . . X 4,969 1.297 10 25.0

Gammarus. . . . . . . . . . . . . . . . . . . . . . . X 1,517 .396 2 5.0

Gonidea angulata . . . . . . . . . . . . . . . . . X 2 .001 1 2.5

Gyraulus . . . . . . . . . . . . . . . . . . . . . . . . X 341 .089 2 5.0

Helisoma anceps. . . . . . . . . . . . . . . . . . X 21 .005 1 2.5

Hirudinea. . . . . . . . . . . . . . . . . . . . . . . . X 126 .033 5 12.5

Hyalella azteca . . . . . . . . . . . . . . . . . . . X 31,028 8.101 6 15.0

Nematoda . . . . . . . . . . . . . . . . . . . . . . . X 750 .196 13 32.5

Oligochaeta . . . . . . . . . . . . . . . . . . . . . . X 4,572 1.194 31 77.5

Ostracoda . . . . . . . . . . . . . . . . . . . . . . . X 52 .014 4 10.0

Pacifasticus. . . . . . . . . . . . . . . . . . . . . . X 20 .005 2 5.0

Physella. . . . . . . . . . . . . . . . . . . . . . . . . X 231 .060 7 17.5

Porifera . . . . . . . . . . . . . . . . . . . . . . . . . X 12 .003 1 2.5

Potamopyrgus antipodarum . . . . . . . . . X 26,764 6.987 5 12.5

Pyrgulopsis . . . . . . . . . . . . . . . . . . . . . . X 20 .005 1 2.5

Radix auricularia . . . . . . . . . . . . . . . . . X 66 .017 2 5.0

Sphaeriidae . . . . . . . . . . . . . . . . . . . . . . X 437 .114 6 15.0

Stagnicola . . . . . . . . . . . . . . . . . . . . . . . X 436 .114 5 12.5

Turbellaria. . . . . . . . . . . . . . . . . . . . . . . X 1,371 .358 11 27.5

Valvata humeralis . . . . . . . . . . . . . . . . . X 107 .028 2 5.0

Vorticifex effusa. . . . . . . . . . . . . . . . . . . X 19 .005 1 2.5

Insect

Odonata

Argia . . . . . . . . . . . . . . . . . . . . . . . . . . . X 161 .042 3 7.5

Coenagrionidae . . . . . . . . . . . . . . . . . . . X 2 .001 1 2.5

Ophiogomphus . . . . . . . . . . . . . . . . . . . X 31 .008 2 5.0

Ephemeroptera

Acentrella . . . . . . . . . . . . . . . . . . . . . . . X 5,835 1.523 24 60.0

Ameletus2 . . . . . . . . . . . . . . . . . . . . . . . X 43 .011 4 10.0

Attenella margarita. . . . . . . . . . . . . . . . X 291 .076 5 12.5

Baetidae. . . . . . . . . . . . . . . . . . . . . . . . . X 2,314 .604 8 20.0

Baetis tricaudatus. . . . . . . . . . . . . . . . . X 42,921 11.206 38 95.0

Barbaetis . . . . . . . . . . . . . . . . . . . . . . . X 5 .001 1 2.5

Caenis . . . . . . . . . . . . . . . . . . . . . . . . . . X 360 .094 2 5.0

Caudatella3. . . . . . . . . . . . . . . . . . . . . . X 171 .045 4 10.0

Centroptilum . . . . . . . . . . . . . . . . . . . . . X 9 .002 2 5.0

Choroterpes. . . . . . . . . . . . . . . . . . . . . . X 19 .005 1 2.5

Cinygmula. . . . . . . . . . . . . . . . . . . . . . . X 365 .095 5 12.5

Diphetor hageni . . . . . . . . . . . . . . . . . . X 342 .089 13 32.5

Drunella coloradensis/flavilinea. . . . . . X 124 .032 3 7.5

Drunella doddsi3. . . . . . . . . . . . . . . . . . X 334 .087 9 22.5

Drunella grandis/spinifera . . . . . . . . . . X 320 .084 9 22.5

Epeorus. . . . . . . . . . . . . . . . . . . . . . . . . X 93 .024 4 10.0

Epeorus albertae. . . . . . . . . . . . . . . . . . X 345 .090 6 15.0

Epeorus deceptivus3 . . . . . . . . . . . . . . . X 552 .144 3 7.5

Epeorus grandis3 . . . . . . . . . . . . . . . . . X 65 .017 3 7.5

Epeorus longimanus . . . . . . . . . . . . . . . X 12 .003 1 2.5

Ephemera . . . . . . . . . . . . . . . . . . . . . . . X 2 .001 1 2.5

Ephemerella aurivillii . . . . . . . . . . . . . . X 23 .006 2 5.0

Ephemerella inermis/infrequens . . . . . . X 6,760 1.765 19 47.5

Ephoron. . . . . . . . . . . . . . . . . . . . . . . . . X 38 .010 1 2.5

Heptagenia/Nixe . . . . . . . . . . . . . . . . . . X 638 .167 12 30.0

Paraleptophlebia. . . . . . . . . . . . . . . . . . X 1,288 .336 12 30.0

Paraleptophlebia bicornuta . . . . . . . . . X 8 .002 1 2.5
Analytical Methods 17

Table 3. Relative total abundances and occurrence of taxa in richest targeted habitat (riffle) samples collected from 40 

macroinvertebrate sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued

No. 

of sites

where

Total Percent taxon was Percent 

Taxon Abundant Common Rare abundance1 abundance collected occurrence

Ephemeroptera—Continued

Rhithrogena. . . . . . . . . . . . . . . . . . . . . . X 3,833 1.001 22 55.0

Serratella. . . . . . . . . . . . . . . . . . . . . . . . X 475 .124 6 15.0

Stenonema. . . . . . . . . . . . . . . . . . . . . . . X 672 .175 9 22.5

Tricorythodes . . . . . . . . . . . . . . . . . . . . X 201 .052 2 5.0

Tricorythodes minutus. . . . . . . . . . . . . . X 11,221 2.930 21 52.5

Plecoptera

Calineuria californica. . . . . . . . . . . . . . X 54 .014 5 12.5

Chloroperlidae. . . . . . . . . . . . . . . . . . . . X 264 .069 7 17.5

Claassenia sabulosa . . . . . . . . . . . . . . . X 189 .049 9 22.5

Doroneuria2 . . . . . . . . . . . . . . . . . . . . . X 7 .002 1 2.5

Hesperoperla pacifica . . . . . . . . . . . . . . X 543 .142 11 27.5

Isogenoides . . . . . . . . . . . . . . . . . . . . . . X 44 .011 1 2.5

Isoperla . . . . . . . . . . . . . . . . . . . . . . . . . X 2,672 .698 16 40.0

Perlodidae . . . . . . . . . . . . . . . . . . . . . . . X 153 .040 10 25.0

Pteronarcella. . . . . . . . . . . . . . . . . . . . . X 179 .047 5 12.5

Pteronarcys californica. . . . . . . . . . . . . X 123 .032 6 15.0

Skwala. . . . . . . . . . . . . . . . . . . . . . . . . . X 81 .021 4 10.0

Sweltsa . . . . . . . . . . . . . . . . . . . . . . . . . X 142 .037 3 7.5

Zapada cinctipes. . . . . . . . . . . . . . . . . . X 119 .031 6 15.0

Trichoptera

Amiocentrus aspilus . . . . . . . . . . . . . . . X 78 .020 3 7.5

Apatania2 . . . . . . . . . . . . . . . . . . . . . . . X 10 .003 2 5.0

Arctopsyche grandis . . . . . . . . . . . . . . . X 842 .220 9 22.5

Brachycentrus americanus . . . . . . . . . . X 753 .197 12 30.0

Brachycentrus occidentalis. . . . . . . . . . X 11,077 2.892 22 55.0

Ceraclea . . . . . . . . . . . . . . . . . . . . . . . . X 19 .005 1 2.5

Cheumatopsyche . . . . . . . . . . . . . . . . . . X 6,789 1.772 15 37.5

Chimarra. . . . . . . . . . . . . . . . . . . . . . . . X 12 .003 1 2.5

Culoptila . . . . . . . . . . . . . . . . . . . . . . . . X 29 .008 2 5.0

Dicosmoecus gilvipes . . . . . . . . . . . . . . X 10 .003 2 5.0

Dolophilodes. . . . . . . . . . . . . . . . . . . . . X 79 .021 2 5.0

Glossosoma. . . . . . . . . . . . . . . . . . . . . . X 651 .170 10 25.0

Helicopsyche borealis. . . . . . . . . . . . . . X 564 .147 5 12.5

Hydropsyche . . . . . . . . . . . . . . . . . . . . . X 90,195 23.548 39 97.5

Hydroptila . . . . . . . . . . . . . . . . . . . . . . . X 2,991 .781 13 32.5

Lepidostoma-sand case larvae. . . . . . . . X 1,222 .319 10 25.0

Leucotrichia . . . . . . . . . . . . . . . . . . . . . X 817 .213 6 15.0

Micrasema. . . . . . . . . . . . . . . . . . . . . . . X 14 .004 2 5.0

Nectopsyche . . . . . . . . . . . . . . . . . . . . . X 81 .021 2 5.0

Neophylax rickeri . . . . . . . . . . . . . . . . . X 14 .004 3 7.5

Neotrichia . . . . . . . . . . . . . . . . . . . . . . . X 210 .055 2 5.0

Ochrotrichia . . . . . . . . . . . . . . . . . . . . . X 1,830 .478 9 22.5

Oecetis. . . . . . . . . . . . . . . . . . . . . . . . . . X 2 .001 1 2.5

Onocosmoecus unicolor . . . . . . . . . . . . X 15 .004 1 2.5

Polycentropus . . . . . . . . . . . . . . . . . . . . X 6 .002 1 2.5

Protoptila . . . . . . . . . . . . . . . . . . . . . . . X 508 .133 4 10.0

Psychomyia . . . . . . . . . . . . . . . . . . . . . . X 128 .033 3 7.5

Rhyacophila Angelita Group. . . . . . . . . X 40 .010 3 7.5

Rhyacophila Brunnea Group . . . . . . . . X 24 .006 1 2.5

Rhyacophila Coloradensis Group. . . . . X 107 .028 6 15.0

Tinodes . . . . . . . . . . . . . . . . . . . . . . . . . X 120 .031 1 2.5

Wormaldia. . . . . . . . . . . . . . . . . . . . . . . X 36 .009 2 5.0

Lepidoptera

Petrophila . . . . . . . . . . . . . . . . . . . . . . . X 3,773 .985 19 47.5

Coleoptera

Brychius . . . . . . . . . . . . . . . . . . . . . . . . X 49 .013 2 5.0

Cleptelmis . . . . . . . . . . . . . . . . . . . . . . . X 19 .005 2 5.0

Dubiraphia . . . . . . . . . . . . . . . . . . . . . . X 64 .017 2 5.0

Dytiscidae . . . . . . . . . . . . . . . . . . . . . . . X 17 .004 3 7.5

Eubrianax edwardsi . . . . . . . . . . . . . . . X 7 .002 1 2.5

Gyrinidae. . . . . . . . . . . . . . . . . . . . . . . . X 25 .007 1 2.5

Haliplus. . . . . . . . . . . . . . . . . . . . . . . . . X 2 .001 1 2.5

Heterlimnius . . . . . . . . . . . . . . . . . . . . . X 13 .003 2 5.0
18 Evaluation of Macroinvertebrate Assemblages in Idaho Rivers Using Multimetric and Multivariate Techniques, 1996–98

Table 3. Relative total abundances and occurrence of taxa in richest targeted habitat (riffle) samples collected from 40 

macroinvertebrate sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued

No. 

of sites

where

Total Percent taxon was Percent 

Taxon Abundant Common Rare abundance1 abundance collected occurrence

Coleoptera—Continued

Hydrophilidae . . . . . . . . . . . . . . . . . . . . X 8 0.002 1 2.5

Lara avara. . . . . . . . . . . . . . . . . . . . . . . X 14 .004 1 2.5

Microcylloepus . . . . . . . . . . . . . . . . . . . X 1,774 .463 13 32.5

Narpus. . . . . . . . . . . . . . . . . . . . . . . . . . X 45 .012 3 7.5

Optioservus. . . . . . . . . . . . . . . . . . . . . . X 7,134 1.862 26 65.0

Ordobrevia nubifera . . . . . . . . . . . . . . . X 146 .038 3 7.5

Peltodytes . . . . . . . . . . . . . . . . . . . . . . . X 2 .001 1 2.5

Psephenus . . . . . . . . . . . . . . . . . . . . . . . X 15 .004 3 7.5

Stenelmis. . . . . . . . . . . . . . . . . . . . . . . . X 22 .006 1 2.5

Zaitzevia . . . . . . . . . . . . . . . . . . . . . . . . X 1,510 .394 13 32.5

Diptera

Antocha . . . . . . . . . . . . . . . . . . . . . . . . . X 899 .235 12 30.0

Atherix . . . . . . . . . . . . . . . . . . . . . . . . . X 464 .121 10 25.0

Blephariceridae2 . . . . . . . . . . . . . . . . . . X 162 .042 5 12.5

Brachycera . . . . . . . . . . . . . . . . . . . . . . X 16 .004 1 2.5

Ceratopogoninae . . . . . . . . . . . . . . . . . . X 79 .021 6 15.0

Chelifera . . . . . . . . . . . . . . . . . . . . . . . . X 41 .011 3 7.5

Clinocera. . . . . . . . . . . . . . . . . . . . . . . . X 8 .002 2 5.0

Cryptolabis . . . . . . . . . . . . . . . . . . . . . . X 4 .001 1 2.5

Deuterophlebia2 . . . . . . . . . . . . . . . . . . X 25 .007 2 5.0

Dicranota . . . . . . . . . . . . . . . . . . . . . . . X 46 .012 2 5.0

Empididae . . . . . . . . . . . . . . . . . . . . . . . X 70 .018 5 12.5

Hemerodromia . . . . . . . . . . . . . . . . . . . X 157 .041 11 27.5

Hexatoma . . . . . . . . . . . . . . . . . . . . . . . X 211 .055 11 27.5

Limnophora. . . . . . . . . . . . . . . . . . . . . . X 2 .001 1 2.5

Rhabdomastix2 . . . . . . . . . . . . . . . . . . . X 5 .001 1 2.5

Simuliidae . . . . . . . . . . . . . . . . . . . . . . . X 19,453 5.079 35 87.5

Stratiomyidae . . . . . . . . . . . . . . . . . . . . X 612 .160 2 5.0

Tanyderidae. . . . . . . . . . . . . . . . . . . . . . X 15 .004 2 5.0

Tipula . . . . . . . . . . . . . . . . . . . . . . . . . . X 3 .001 1 2.5

Tipulidae . . . . . . . . . . . . . . . . . . . . . . . . X 4 .001 1 2.5

Chironomidae

Apedilum . . . . . . . . . . . . . . . . . . . . . . . . X 16 .004 1 2.5

Cardiocladius . . . . . . . . . . . . . . . . . . . . X 2,133 .557 19 47.5

Chaetocladius . . . . . . . . . . . . . . . . . . . . X 2 .001 1 2.5

Chironomidae-pupae. . . . . . . . . . . . . . . X 6,612 1.726 37 92.5

Cladotanytarsus . . . . . . . . . . . . . . . . . . X 541 .141 7 17.5

Corynoneura . . . . . . . . . . . . . . . . . . . . . X 14 .004 2 5.0

Cricotopus. . . . . . . . . . . . . . . . . . . . . . . X 21,831 5.699 31 77.5

Cricotopus (Nostococladius) . . . . . . . . X 18 .005 3 7.5

Cryptochironomus. . . . . . . . . . . . . . . . . X 98 .026 5 12.5

Diamesa . . . . . . . . . . . . . . . . . . . . . . . . X 71 .019 5 12.5

Dicrotendipes . . . . . . . . . . . . . . . . . . . . X 200 .052 4 10.0

Eukiefferiella. . . . . . . . . . . . . . . . . . . . . X 5,818 1.519 31 77.5

Hydrobaenus. . . . . . . . . . . . . . . . . . . . . X 27 .007 2 5.0

Limnophyes. . . . . . . . . . . . . . . . . . . . . . X 4 .001 1 2.5

Micropsectra . . . . . . . . . . . . . . . . . . . . . X 307 .080 14 35.0

Microtendipes . . . . . . . . . . . . . . . . . . . . X 457 .119 7 17.5

Nanocladius . . . . . . . . . . . . . . . . . . . . . X 38 .010 4 10.0

Odontomesa . . . . . . . . . . . . . . . . . . . . . X 12 .003 1 2.5

Orthocladiinae. . . . . . . . . . . . . . . . . . . . X 126 .033 2 5.0

Orthocladius Complex . . . . . . . . . . . . . X 16,023 4.183 30 75.0

Pagastia. . . . . . . . . . . . . . . . . . . . . . . . . X 869 .227 9 22.5

Parachironomus . . . . . . . . . . . . . . . . . . X 8 .002 1 2.5

Paracladius . . . . . . . . . . . . . . . . . . . . . . X 2 .001 1 2.5

Parakiefferiella . . . . . . . . . . . . . . . . . . . X 120 .031 1 2.5

Parametriocnemus . . . . . . . . . . . . . . . . X 134 .035 4 10.0

Paraphaenocladius . . . . . . . . . . . . . . . . X 170 .044 3 7.5

Paratanytarsus . . . . . . . . . . . . . . . . . . . X 615 .161 7 17.5

Pentaneura . . . . . . . . . . . . . . . . . . . . . . X 164 .043 3 7.5

Phaenopsectra. . . . . . . . . . . . . . . . . . . . X 46 .012 3 7.5

Polypedilum. . . . . . . . . . . . . . . . . . . . . . X 3,665 .957 24 60.0

Potthastia Gaedii Group . . . . . . . . . . . . X 78 .020 3 7.5
Analytical Methods 19

common taxon in the sample. It is a simple measure of 

assemblage balance. An increase in dominance is considered indicative of a decrease in the health of the 

assemblage and is associated with increased human 

disturbance. The total number of taxa (richness) measures the overall variety of macroinvertebrates in a 

sample. This metric is one of the most commonly used 

in biomonitoring. Increasing richness is thought to indicate increasing health of the assemblage. EPT taxa is 

the number of distinct taxa in the orders Ephemeroptera 

(mayflies), Plecoptera (stoneflies), and Trichoptera 

(caddisflies). These orders generally are considered to 

be intolerant of poor water quality. As with total number of taxa, this metric decreases with human disturbance. Percent Elmidae is the relative abundance of 

riffle beetles. This family of beetles is expected to 

decrease with increased human disturbance. Percent 

predators is the relative abundance of the functional 

feeding group, predators. The abundance of predators 

declines as human disturbance increases, owing to the 

decrease in abundance and diversity of prey. 

IRI scores for each site were calculated using the 

approach outlined by Grafe (2000), whereby each metric was scored a 1, 3, or 5, except percent predators. 

Percent predators were downscaled and scored only a 

1 or 3 because of this metric’s weaker discriminatory 

power. IRI scores 16 or greater indicated a site with 

good biotic condition, scores 13 or less indicated poor 

biotic condition, and scores of 14 and 15 indicated 

intermediate condition. 

The abundance metric is defined as the number of 

individuals per square meter (individuals/m2). This 

metric has been used to evaluate fish food abundance 

and generally is thought to increase with increased 

nutrient enrichment as a result of human disturbance. 

It also may decrease as a result of severe pollution 

effects. Percent coldwater taxa and number of coldwater taxa were evaluated because of their potential to 

help evaluate coldwater habitats, which is one of the 

primary beneficial uses assigned to most waters in 

Idaho. Coldwater taxa designations (table A, back of 

report) were made using a data base compiled by IDEQ 

(M. Edmondson, Idaho Department of Environmental 

Quality, written commun., 2000), which was based on 

the literature and the criteria of a maximum instantaneous water temperature of 22°C and an average daily 

water temperature of 19°C. Regional experts also were 

consulted regarding temperature preferences (Bob Wisseman, Aquatic Biology Associates, Inc., Corvallis, 

Oregon; Gary Lester, EcoAnalyst, Moscow, Idaho, 

written and oral communs., 2000). The number and 

percent coldwater taxa generally are thought to 

decrease with increases in human disturbance.

The IRI was evaluated by first classifying an equal 

number of sites into high- or low-quality groups (12 

sites in each group). To achieve a high degree of certainty in the categorization process, multiple measures 

of resource conditions were examined (table 2), including habitat quality scores, percent agricultural land, 

maximum water temperature, and professional judgment. For example, the HQI for high-quality sites genTable 3. Relative total abundances and occurrence of taxa in richest targeted habitat (riffle) samples collected from 40 

macroinvertebrate sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued

No. 

of sites

where

Total Percent taxon was Percent 

Taxon Abundant Common Rare abundance1 abundance collected occurrence

Chironomidae—Continued

Potthastia Longimana Group . . . . . . . . X 79 0.021 2 5.0

Pseudochironomus . . . . . . . . . . . . . . . . X 188 .049 1 2.5

Rheocricotopus . . . . . . . . . . . . . . . . . . . X 48 .013 3 7.5

Rheotanytarsus . . . . . . . . . . . . . . . . . . . X 3,652 .953 21 52.5

Saetheria . . . . . . . . . . . . . . . . . . . . . . . . X 8 .002 1 2.5

Stempellinella . . . . . . . . . . . . . . . . . . . . X 20 .005 4 10.0

Synorthocladius. . . . . . . . . . . . . . . . . . . X 158 .041 2 5.0

Tanytarsus. . . . . . . . . . . . . . . . . . . . . . . X 58 .015 2 5.0

Thienemanniella . . . . . . . . . . . . . . . . . . X 187 .049 12 30.0

Thienemannimyia Group. . . . . . . . . . . . X 652 .170 16 40.0

Tvetenia. . . . . . . . . . . . . . . . . . . . . . . . . X 1,321 .345 18 45.0

1Individuals per square meter can be derived by dividing the total abundance by number of sites where taxon was collected.

2Coldwater taxa designation (Michael Edmondson, Idaho Department of Environmental Quality, written commun., 2000).

3Coldwater taxa designation (Bob Wisseman, Aquatic Biology Associates, Inc., and Gary Lester, Ecoanalysts, Inc., written and oral communs., 2000).
20 Evaluation of Macroinvertebrate Assemblages in Idaho Rivers Using Multimetric and Multivariate Techniques, 1996–98

Table 4. Macroinvertebrate metrics and invertebrate river index (IRI) scores for selected sampling sites in the Idaho statewide 

surface-water quality monitoring program, 1996–98

[QMH, qualitative multiple habitat; RTH, richest targeted habitat; metrics included in the IRI are shaded; No., number; EPT, Ephemeroptera,

Plecoptera, and Trichoptera]

No. of Percent Percent

cold- cold- Percent Total Elmidae

Site QMH or Total water water dominant No. of EPT (riffle Percent IRI

No. Site name RTH abundance1 taxa taxa taxon taxa taxa beetles) predators score

4 North Fork Coeur d’Alene River . . . . . . . . . . . QMH 3,300 2 4.18 20.36 59 26 3.83 14.08 23

at Enaville RTH 3,005 3 .83 28.59 50 27 3.52 3.2 21

5 South Fork Coeur d’Alene River . . . . . . . . . . . QMH 1,632 3 16.24 19.73 37 17 0 11.69 19

near Pinehurst RTH 1,905 1 28.03 34.17 25 11 .63 3.46 19

6 St. Joe River at Calder . . . . . . . . . . . . . . . . . . . QMH 3,220 1 .47 14.75 56 21 .76 5.78 21

RTH 2,416 2 .66 27.15 50 30 3.04 3.52 23

7 Spokane River near Post Falls . . . . . . . . . . . . . QMH 1,833 0 0 26.35 24 7 0 3.09 13

RTH 9,808 0 0 52.85 15 5 0 1.47 9

8 Snake River near Heise . . . . . . . . . . . . . . . . . . QMH 22,481 0 0 18.68 35 14 .18 4.98 17

RTH 19,243 0 0 24.75 26 11 0 3.88 17

10 Teton River near St. Anthony . . . . . . . . . . . . . . QMH 10,128 0 0 11.06 47 14 6.45 4.89 21

RTH 26,400 0 0 23.30 37 13 7.76 6.44 21

11 Henrys Fork near Rexburg . . . . . . . . . . . . . . . . QMH 3,018 0 0 27.63 38 8 .99 2.79 15

RTH 1,280 0 0 19.06 43 13 2.34 8.74 21

12 Willow Creek near Ririe . . . . . . . . . . . . . . . . . QMH 7,308 0 0 35.14 14 1 0 .49 9

RTH 20,590 0 0 39.52 14 4 0 0 7

13 Blackfoot River near Blackfoot . . . . . . . . . . . . QMH 515 0 0 34.76 36 9 5.04 1.68 17

RTH 13,100 0 0 26.53 33 14 14.51 2.29 19

14 Snake River near Blackfoot . . . . . . . . . . . . . . . QMH 3,006 0 0 21.56 38 11 .2 1.97 17

RTH 9,961 0 0 27.87 35 16 .19 3.2 15

15 Portneuf River at Topaz . . . . . . . . . . . . . . . . . . QMH 7,575 0 0 15.25 43 9 3.96 1.6 19

RTH 6,633 0 0 36.18 32 10 10.54 .94 19

16 Marsh Creek near McCammon . . . . . . . . . . . . QMH 6,684 0 0 28.37 40 6 .7 3.19 15

RTH 5,822 0 0 31.71 33 7 5.15 2.18 17

17 Portneuf River at Pocatello . . . . . . . . . . . . . . . QMH 2,705 0 0 56.01 31 8 1.29 2.57 13

RTH 11,118 0 0 79.61 19 4 3.66 2.31 11

18 Snake River near Minidoka . . . . . . . . . . . . . . . QMH 7,665 0 0 24.27 30 7 0 .99 13

RTH 39,264 0 0 87.96 9 3 0 0 5

21 Blue Lakes Spring . . . . . . . . . . . . . . . . . . . . . . QMH 25,720 0 0 49.92 31 4 0 .22 13

RTH 63,000 0 0 46.67 23 4 0 .19 11

22 Rock Creek at Daydream Ranch . . . . . . . . . . . QMH 20,200 0 0 83.96 18 6 .98 .2 9

RTH 23,400 0 0 75.00 19 8 3.2 0 11

25 Camas Creek at Red Road . . . . . . . . . . . . . . . . QMH 3,544 1 .31 27.91 51 23 4.17 3.04 21

RTH 1,777 0 0 19.41 47 17 6.46 6.65 23

26 Beaver Creek at Spencer . . . . . . . . . . . . . . . . . QMH 14,160 1 .14 19.63 50 21 2.54 5.36 21

RTH 7,450 1 .20 20.03 41 24 3.37 3.58 21

27 Big Lost River near Chilly . . . . . . . . . . . . . . . . QMH 7,920 2 3.79 17.80 45 18 .95 10.44 21

RTH 6,859 5 1.25 55.04 39 23 .36 7.07 19

28 Big Wood River near Bellevue. . . . . . . . . . . . . QMH 8,295 1 .36 38.70 35 17 .18 4.14 21

RTH 1,203 1 .33 31.84 34 16 .18 4.25 19

29 Silver Creek near Picabo . . . . . . . . . . . . . . . . . QMH 4,048 0 0 33.72 34 11 0 1.31 15

RTH 1,231 0 0 20.47 36 10 4.67 3.01 19

30 Malad River near Gooding. . . . . . . . . . . . . . . . QMH 1,499 0 0 29.42 39 12 2.84 .85 19

RTH 1,088 0 0 27.39 33 12 8.03 1.81 19

31 Bruneau River near Hot Spring . . . . . . . . . . . . QMH 2,745 0 0 25.68 34 11 10.2 1.28 19

RTH 1,021 0 0 43.19 27 12 2.44 1.32 19

32 Snake River near Murphy . . . . . . . . . . . . . . . . QMH 1,282 0 0 39.47 37 11 0 1.11 13

RTH 5,763 0 0 50.91 16 7 0 0 7

33 Boise River near Twin Springs. . . . . . . . . . . . . QMH 4,817 3 1.02 11.00 56 25 4.1 4.4 23

RTH 1,780 2 4.83 33.60 29 13 1.08 2.52 17

35 Boise River at Glenwood Bridge . . . . . . . . . . . QMH 39,480 0 0 43.16 30 7 0 .75 11

RTH 4,984 0 0 51.52 25 9 0 2.4 13

37 Snake River at Nyssa . . . . . . . . . . . . . . . . . . . . QMH 3,300 0 0 43.82 25 7 0 .54 11

RTH 2,480 0 0 53.87 22 9 .65 .16 13

38 South Fork Payette River at Lowman . . . . . . . QMH 3,978 3 .75 19.16 56 25 6.43 14.6 23

RTH 4,340 6 5.23 27.81 45 25 2.7 7.43 23

41 Payette River near Payette . . . . . . . . . . . . . . . . QMH 2,112 0 0 25.76 20 4 .19 2.46 11

RTH 3,944 0 0 28.40 24 7 .61 5.06 17
Analytical Methods 21

erally was greater than 65, agricultural land use was 

less than 10 percent, and maximum water temperature 

was less than 22°C. Boxplots were used to evaluate the 

metrics and IRI scores. Median values for each group 

were tested for statistical differences using nonparametric t-tests. These statistical and graphical analyses 

were performed using SYSTAT (Wilkinson, 1998).

Multivariate Analyses

Multivariate analyses are an effective way to examine the distribution patterns of taxa and assemblages in 

relation to environmental variables (Gauch, 1982). 

These analyses were done to generate hypotheses 

about relations between macroinvertebrate assemblages and environmental variables. The use of several 

types of multivariate analyses was essential to reduce 

the number of variables and to assess complex relations 

between macroinvertebrate assemblages and environmental variables measured.

 Normal probability plots and univariate statistics 

for all environmental variables and macroinvertebrate 

metrics were used to evaluate frequency distributions 

and skewness. Log transformations of the environmental variables (percent forested land, basin area, discharge, stream width, and percent agricultural land) 

and the metrics (abundance, coldwater taxa, percent 

coldwater taxa, percent Elmidae, and percent predators) were performed prior to multivariate analyses to 

enhance normality. Because variables were measured 

in different units, those used in the multivariate analyses were standardized by the various statistical analysis 

programs to a mean of 0 and a variance of 1.

Preliminary multivariate analyses were performed on macroinvertebrate taxa presence or absence, 

relative abundance, and log-transformed taxa abundance data. Rare taxa (less than 5 percent frequency of 

occurrence) were excluded from the data set, as recommended by Gauch (1982), or were downweighted. In 

this preliminary analysis, the abundant taxa (table 3) 

also were excluded using steps similar to those used by 

Danehy and others (1999), who found that the exclusion of abundant taxa improved their ability to identify 

relations between environmental gradients and macroinvertebrate assemblages. Rahel (1990) suggested 

examining different levels of numerical resolution and 

censuring taxa data when searching for patterns in biological data. However, none of these approaches for 

Table 4. Summary of macroinvertebrate metrics and invertebrate river index (IRI) scores for selected sampling sites in the Idaho 

statewide surface-water quality monitoring program, 1996–98—Continued

No. of Percent Percent

cold- cold- Percent Total Elmidae

Site QMH or Total water water dominant No. of EPT (riffle Percent IRI

No. Site name RTH abundance1 taxa taxa taxon taxa taxa beetles) predators score

42 Weiser River near Weiser . . . . . . . . . . . . . . . . QMH 3,132 2 0.13 21.71 47 15 2.55 2.05 19

RTH 4,293 1 1.72 32.15 25 12 3.43 2.05 19

44 Pahsimeroi River at Ellis . . . . . . . . . . . . . . . . . QMH 11,490 1 .26 41.78 41 15 11.88 6.27 19

RTH 13,920 0 0 38.97 29 13 11.38 6.54 19

45 Salmon River at Salmon. . . . . . . . . . . . . . . . . . QMH 7,700 0 0 31.17 35 13 .39 1.95 17

RTH 15,936 0 0 33.43 33 15 0 2.55 15

46 Lemhi River near Lemhi . . . . . . . . . . . . . . . . . QMH 13,180 0 0 45.68 40 17 3.19 2.12 19

RTH 15,096 0 0 26.55 31 16 3.5 7.15 21

47 Johnson Creek at Yellow Pine . . . . . . . . . . . . . QMH 687 7 6.11 10.04 57 32 5.24 10.49 23

RTH 2,836 6 8.99 13.54 50 30 5.6 19.34 23

48 Little Salmon River at Riggins. . . . . . . . . . . . . QMH 6,310 2 .32 32.64 39 19 2.37 2.86 21

RTH 4,024 2 .60 34.19 35 21 1 4.58 21

50 Lapwai Creek near Lapwai . . . . . . . . . . . . . . . QMH 7,400 0 0 20.95 45 13 7.03 12.59 21

RTH 5,720 0 0 21.26 34 13 .42 2.1 17

51 South Fork Clearwater River at Stites . . . . . . . QMH 7,890 1 .19 17.30 56 24 6.55 4.88 23

RTH 3,460 2 .81 26.36 45 20 3.61 2.79 21

52 Palouse River near Potlatch . . . . . . . . . . . . . . . QMH 2,810 1 .36 13.88 44 10 4.62 7.49 21

RTH 3,485 0 0 37.79 31 10 10.1 1.84 17

53 Bear River at Idaho-Utah State Line . . . . . . . . QMH 5,100 0 0 18.04 29 9 8.04 .98 19

RTH 9,640 0 0 51.55 26 11 .58 .77 15

56 Snake River near Buhl . . . . . . . . . . . . . . . . . . . QMH 8,640 0 0 38.37 33 7 0 2.59 11

RTH 6,184 0 0 73.61 27 8 1.29 1.81 11

1RTH samples are expressed as individuals per square meter.
22 Evaluation of Macroinvertebrate Assemblages in Idaho Rivers Using Multimetric and Multivariate Techniques, 1996–98

censuring the macroinvertebrate data enhanced the 

ordination analyses.

All multivariate results presented in this report are 

for the RTH macroinvertebrate composition data for 

each site, expressed as percent relative abundance. This 

approach effectively reduced the influence of abnormally large numbers of an individual taxon at a site. 

Using only RTH samples for intersite comparison in 

the multivariate analyses effectively normalized the 

data to riffle habitat across all sites. Rare taxa were 

retained in all analyses and were not downweighted. 

The presence of rare taxa at a particular site often indicates specific habitat conditions (such as coldwater 

habitat) and, therefore, provides critical information 

regarding ecological conditions. 

PRINCIPAL COMPONENTS ANALYSIS

PCA and correlation matrices were used to identify the environmental variables that distinguish each 

type of stream and to reduce the environmental variables in subsequent analyses. PCA was performed 

using SYSTAT (Wilkinson, 1998) to group and summarize environmental variables. This analysis was used 

to shorten an otherwise long list of environmental variables containing redundant information. PCA is appropriate for analyzing data that have an underlying linear 

structure and summarizes the variance-covariance or 

correlation structure of a data set (Gauch, 1982). Relations between the eight macroinvertebrate metrics also 

were evaluated using PCA.

A principal component is a group of related environmental variables that are combined into a surrogate 

variable. For example, basin area, discharge, stream 

order, and stream width are combined to indicate stream 

size. The degree of association between a variable and 

a principal component is expressed by a factor loading. 

If a group of variables have high factor loadings (absolute value greater than 0.50) on a particular principal 

component, then the variables all express similar information about that component. For this study, principal 

components with eigenvalues greater than 1.0 were 

retained and rotated by use of the Varimax procedure 

(Wilkinson, 1998). Eigenvalues equal the maximum 

dispersion of the variable scores on the ordination axis 

and are a measure of importance of the ordination axis 

(Jongman and others, 1995).

DETRENDED CORRESPONDENCE ANALYSIS

Macroinvertebrate taxa were evaluated using 

DCA, a form of indirect gradient analysis, where the 

ordination is not constrained by the environmental variables. DCA was performed using the computer program CANOCO (Ter Braak and Smilauer, 1998). The 

ordination produced by this analysis was examined to 

determine site groups with similar taxa composition 

and spatial patterns. 

This analysis also was used to determine whether 

the taxa data showed a unimodal response, a necessary 

requirement for subsequent direct gradient analysis 

using CCA (Ter Braak and Smilauer, 1998). If gradient 

lengths determined in this analysis approach 4 standard 

deviation units, then the taxa data show a unimodal 

response. 

CANONICAL CORRESPONDENCE ANALYSIS

Macroinvertebrate assemblages were related to 

multiple environmental variables using CCA (Ter 

Braak, 1986). This analytical technique was used to 

perform direct gradient analysis whereby ordination 

axes were chosen on the basis of taxa and environmental data. CCA was designed to detect patterns of variation in taxa data that were explained best by the 

observed environmental variable. CCA was applied 

using the computer program CANOCO (Ter Braak and 

Smilauer, 1998). CANOCO depicts species (or taxa) 

and sites in an ordination diagram by assuming that 

species exhibit Gaussian-type responses to environmental gradients; that is, taxa are depicted at various 

locations along an environmental gradient and exhibit a 

peak in occurrence at an optimum value along that gradient. In the ordination diagram, environmental gradients are displayed as vectors. Vector direction and 

length indicate the relative magnitude and influence of 

a particular variable on the taxa. The main axes are a 

combination of the environmental variables that best 

define the site positions on the CCA diagram. Sites 

with the most taxa in common are clustered in the ordination diagram.

The environmental variables used to represent 

major gradients were derived from PCA and correlation analysis of basin, hydrologic, and habitat characteristics. In a few cases, additional variables were evaluated if they were judged to be potentially important. 

Ten biologically relevant variables out of 24 total were 

selected (table 5) for CCA—percent forested land, 
Results of Macroinvertebrate Taxa and Metrics 23

basin area, percent agricultural land, maximum water 

temperature, dissolved oxygen saturation, stream gradient, elevation, percent substrate fines, percent urban 

land, and percent open canopy. 

Forward selection in CCA was applied on these 10 

variables to determine which had the most influence on 

macroinvertebrate taxa. Forward selection identifies a 

minimum number of environmental variables to help 

explain the taxa composition. A Monte Carlo test of 

199 permutations determined the significance of each 

environmental variable during the forward selection 

process (Ter Braak and Smilauer, 1998). Only variables 

determined to be significant at the 0.05 probability 

level were included in the final CCA. Inflation factors 

for the environmental variables were less than 20, 

which indicates that variables were not highly correlated. The environmental gradient scores were correlated to the axes scores to show the strength of the relation between the environmental gradient and the axes. 

Canonical coefficients, which are analogous to regression coefficients, were examined for significance 

against the first two axes. The statistical significance of 

the relation between the taxa and the whole set of environmental variables also was determined using the global permutation test. Two test statistics were used: one 

based on the first canonical eigenvalue and one based 

on the sum of all canonical eigenvalues. The resulting 

tests determined the significance of the first ordination 

axis and that of all canonical axes together (entire 

model), respectively. Both tests were carried out by a 

Monte Carlo test of 199 permutations. All other parameters in CCA were set at the default settings (Ter Braak 

and Smilauer, 1998).

RESULTS OF MACROINVERTEBRATE 

TAXA AND METRICS

Results of Macroinvertebrate Taxa and Metrics

Two hundred and forty-seven macroinvertebrate 

taxa were identified in RTH and QMH samples collected from the 40 sampling sites (table A, back of 

report). Riffles supported most of the taxa collected at 

all sites. One hundred and eighty-four taxa (74 percent 

of total taxa) were identified in the RTH samples. The 

most abundant taxa (greater than 1 percent of total 

abundance and identified in 75 percent or more of the 

RTH samples) were Oligochaeta, Baetis tricaudatus, 

Hydropsyche, Simuliidae, Chironomidae pupae, Cricotopus, Eukiefferiella, and Orthocladius complex 

(table 3). Thirty rare taxa (composing less than 0.005 

percent total abundance and identified in less than 5 

percent of RTH samples) were collected. Many of the 

taxa identified in the QMH samples that were not identified in the RTH samples consisted of insect taxa in the 

orders Odonata (dragonflies), Hemiptera (bugs), and 

Diptera (flies). Many of these taxa are associated with 

nearshore, backwater, riparian habitats that were not 

sampled as part of the RTH sample collections. 

Total abundance (density expressed as individuals/m2) for RTH samples (table 4) ranged from 1,021 to 

63,000 individuals/m2 at the Bruneau River near Hot 

Spring (site 31) and Blue Lakes Spring (site 21), respectively. The extremely high abundance at site 21 was due 

to the large numbers of Hyalella azteca (scuds) and Potamopyrgus antipodarum (New Zealand mud snail), a 

Table 5. Principal component factor loadings for environmental variables from principal components analysis (PCA) for all 

sampling sites in the Idaho statewide surface-water quality 

monitoring program, 1996–98

[Groups of closely associated variables with high absolute values of 

loadings >0.50 and variables selected for canonical correspondence 

analysis shown in bold; all other loading values shown are >0.30; a 

negative number reflects an opposite relation]

Environmental 

variable 1 2 3 4 5 6 7 8

Percent forested 

land1 . . . . . . . . . . . . -0.89

Percent rangeland . . . .85

Latitude (north) . . . . . -.70 0.43

Specific 

conductance. . . . . . . .65 0.32 -.39 0.33

Basin area1 . . . . . . . . 0.91

Discharge1 . . . . . . . . . .89

Stream order . . . . . . . .84

Stream width1 . . . . . . .84

Percent agricultural land1 . . . . . .79

Habitat quality 

index . . . . . . . . . . . . -.71

Maximum water 

temperature . . . . . . .63 .60

Stream velocity . . . . . .36 -.53

Percent embeddedness . . . . . . . . . . . . . .53 0.52

Dissolved oxygen 

saturation . . . . . . . . 0.94

Dissolved oxygen . . . .90

Stream gradient . . . . 0.82

pH . . . . . . . . . . . . . . . .44 .66

Elevation. . . . . . . . . . -.88

Longitude (west) . . . . .85

Stream depth . . . . . . . .80

Percent substrate 

fines. . . . . . . . . . . . . .34 .74

Population density . . . .86

Percent urban

land . . . . . . . . . . . . . .81

Percent open 

canopy. . . . . . . . . . . -.50 -.49

Percent variance 

explained . . . . . . . . . 21 17 11 9 7 6 5 5

1Variable was log10 (x+1) transformed for analysis.

Principal component
24 Evaluation of Macroinvertebrate Assemblages in Idaho Rivers Using Multimetric and Multivariate Techniques, 1996–98

recently introduced gastropod in the Hagerman Valley 

(along the Snake River in Gooding County, downstream from Twin Falls), thought to be inadvertently 

introduced from commercial movement of aquaculture 

products such as trout eggs and live fish (Zaranko and 

others, 1997). According to Bowler (1991), P. antipodarum was the most dominant species of mollusk in all 

habitats of the middle Snake River (Gooding through 

Minidoka Counties) and some tributaries by 1989. 

Crowding due to immense population densities of P. 

antipodarum (about 6,400 individuals/m2) is suspected 

to cause resource competition with native taxa (T.J. 

Frest, Deixis Consultants, Seattle, Wash., oral commun., 2000). During this study, P. antipodarum abundances were as high as 17,550 individuals/m2 in the 

RTH sample from Rock Creek at Daydream Ranch 

(site 22). Maret (1990) did not report finding this species in macroinvertebrate riffle samples collected from 

six Rock Creek sites between 1981 and 1988. This species also was found at sites 11, 32, 37, 44, and 56, 

which indicates it is spreading from its area of introduction. This species was the dominant taxon at two of 

the sites, where it was identified in RTH samples composing about 14 and 75 percent of all individuals at 

sites 21 and 22, respectively.

The total number of taxa and EPT taxa varied 

greatly among sites for both sample types (fig. 3 and 

table 4). Total number of taxa identified in QMH samples ranged from 14 at Willow Creek near Ririe (site 

12) to 59 at North Fork Coeur d’Alene River at Enaville (site 4). The Willow Creek near Ririe site is immediately downstream from Ririe Lake dam, which may 

be limiting the diversity of taxa at this location. Sampling sites such as this are not representative of the 

basin upstream and could be dropped from the SWQP. 

Total number of taxa identified in RTH samples ranged 

from 9 at the Snake River near Minidoka (site 18) to 50 

at each of three sites: North Fork Coeur d’Alene River 

at Enaville (site 4), St. Joe River at Calder (site 6), and 

Johnson Creek at Yellow Pine (site 47). EPT taxa identified in QMH samples ranged from 1 at Willow Creek 

near Ririe (site 12) to 32 at Johnson Creek at Yellow 

Pine (site 47). EPT taxa identified in RTH samples 

ranged from 3 at Snake River near Minidoka (site 18) 

to 30 at each of two sites: St. Joe River at Calder (site 6) 

and Johnson Creek at Yellow Pine (site 47). The Snake 

River near Minidoka site is located immediately downstream from Lake Walcott dam, which may be limiting 

the diversity of taxa at this location.

Comparison of RTH and QMH Sample 

Types

The macroinvertebrate metrics total abundance, 

number of coldwater taxa, percent coldwater taxa, percent dominant taxon, total number of taxa, EPT taxa, 

percent Elmidae, percent predators, and IRI scores for 

both sample types are summarized in table 4. RTH and 

QMH sample types were compared to evaluate the final 

IRI score and the five metrics composing this index 

developed by IDEQ to evaluate medium to large rivers 

in Idaho (Grafe, 2000). Median values for total number 

of taxa and percent dominant taxon were significantly 

different (p<0.05) between RTH and QMH samples 

(fig. 3). It is not surprising that the total number of taxa 

is significantly larger for QMH samples because these 

samples include taxa collected from additional habitat 

types not sampled by RTH methods. The percent dominant taxon for RTH samples was significantly higher 

than for QMH samples, resulting from the dominance 

of large numbers of riffle-adapted taxa such as Baetis 

tricaudatus and Hydropsyche in the RTH sample type.

There was no statistical difference in median IRI 

scores between sample types. There was only one instance (site 41) where a site was misclassified as having good or poor condition by using the different sample types (see table 4, IRI scores). This statistical similarity indicates that either sample type could be used to 

evaluate biological condition by using the IRI. Targeting riffle areas using the RTH method also provides 

consistency in habitat sampled and can provide estimates of macroinvertebrate densities. Riffles generally 

were common at most SWQP sites and were easily 

accessible by wading from shore. Measures of riffle 

habitat parameters (such as depth, velocity, and embeddedness) at points where RTH samples are collected 

also can provide information that can be used to relate 

macroinvertebrate data to measured environmental 

variables. For these reasons, QMH samples could be 

dropped from the SWQP. In rare cases where riffle habitats may not be available, then QMH samples could be 

collected as a replacement for RTH samples. 

Summary of Coldwater Taxa 

Fourteen coldwater taxa were collected during this 

study (table A, back of report) at 12 sampling sites. This 

represents only about 6 percent (14 of 247) of all taxa 

collected and a frequency of occurrence of 30 percent 
Results of Macroinvertebrate Taxa and Metrics 25

INVERTEBRATE RIVER INDEX SCORE30

20

10

0

p = 0.65

EPHEMEROPTERA, PLECOPTERA,

AND TRICHOPTERA TAXA

40

30

20

10

0

p = 0.99

TO

TAL NUMBER OF TAXA

60

50

40

30

20

10

0

p = 0.002

PERCENT DOMINANT TAXON

80

70

60

50

40

30

20

10

0

p = 0.01

PERCENT ELMIDAE

15

10

5

0

p = 0.72

PERCENT PREDATORS

20

15

10

5

0

p = 0.54

Figure 3. Invertebrate river index (IRI) scores in relation to selected metrics for the qualitative multiple habitat (QMH) and richest

targeted habitat (RTH) samples collected from macroinvertebrate sampling sites, Idaho statewide surface-water quality monitoring program, 1996–98. (p, probability level determined from Wilcoxon signed-rank-paired test)

QUALITATIVE

MULTIPLE

HABITAT

RICHEST

TARGETED

HABITAT

QUALITATIVE

MULTIPLE

HABITAT

RICHEST

TARGETED

HABITAT
26 Evaluation of Macroinvertebrate Assemblages in Idaho Rivers Using Multimetric and Multivariate Techniques, 1996–98

(12 of 40) for all sites. The coldwater taxa were Ameletus, Caudatella, Drunella doddsi, Epeorus deceptivus, 

E. grandis, Capniidae, Doroneuria, Taeniopterygidae, 

Apatania, Blephariceridae, Deuterophlebia, Rhabdomastix, Heleniella, and Stempellina. Ten of these coldwater taxa were identified in RTH samples (table 3) at 

12 sites. Most of these coldwater taxa were collected at 

forested sites (fig. 4); the most abundant taxon was E. 

deceptivus, a mayfly typically associated with highgradient mountain streams. Generally, where coldwater 

taxa were identified in RTH samples, they composed 

a small proportion (less than 10 percent) of the total 

abundance, except at the South Fork Coeur d’Alene 

River near Pinehurst (site 5), where E. deceptivus composed almost 30 percent of the total abundance.

It is not surprising that more coldwater taxa were 

not collected because maximum temperatures at 62 

percent (25 out of 40; table 2) of the sampling sites 

exceeded Idaho’s instantaneous coldwater temperature 

criteria of 22°C during 1996–98. Maximum temperatures exceeded the criteria at 5 of the 12 sites where 

coldwater taxa were identified in RTH samples. The 

most extreme example of occurrence of coldwater taxa 

in reaches where the water temperature exceeded criteria was Weiser River near Weiser (site 42), an agricultural site. Blephariceridae, a coldwater dipteran, was 

collected at this site where the maximum water temperature was 29°C. Two coldwater taxa, Ameletus and D. 

doddsi, also were collected at the South Fork Clearwater River at Stites (site 51), where the maximum temperature was almost 27°C. 

Six coldwater taxa were collected at both the South 

Fork Payette River at Lowman (site 38) and Johnson 

Creek at Yellow Pine (site 47), the largest number for all 

sites (fig. 4). Maximum water temperatures were less 

than 20°C and surface-water gradients were relatively 

high (greater than 0.8 percent) at both of these forested 

sites. Five coldwater macroinvertebrate taxa also were 

collected at the Big Lost River near Chilly (site 27). 

This high-elevation (2,018 m) rangeland site had one of 

the lowest maximum temperatures (17.3 °C) for sites 

where coldwater taxa were collected. 

PERCENT COLDWATER TAXA

30

20

10

0

Figure 4. Percent and number of coldwater taxa collected by site type for richest targeted habitat (riffle) samples, Idaho statewide

surface-water quality monitoring program, 1996–98. (Site types shown in table 2)

10 15 11 22 13 16 30 50 17 41 4 42 52 5 8 53 6 44 7 33 48 38 47 18 51 14 32 25 37 56 27 12 26 35 28 46 31 45 29 21

Agricultural Forested Large

River

Rangeland Spring

SITE NUMBER AND SITE TYPE

1

3 2

1

6 2

6

2 2

1 1

5

Number

of taxa
Results of Macroinvertebrate Taxa and Metrics 27

No coldwater taxa were collected at the five largeriver sites, all of which are located on the main-stem 

Snake River in the southern part of the State. Maximum 

temperatures for these sites ranged from 22.1 to 26.9 °C. 

Coldwater taxa also were not collected at spring sites 

21 and 29, even though maximum temperatures at 

these sites were 22°C or below. These discrepancies 

and the absence of coldwater taxa at spring sites indicate that the taxa currently designated as coldwater 

adapted need to be further evaluated.

Recent work by the IDEQ on 12 southwestern 

Idaho streams demonstrated that the distribution of 

coldwater macroinvertebrate taxa corresponded well to 

measures of low water temperature; coldwater indicators were observed only at sites that did not exceed 

Idaho temperature water-quality criteria (W.H. Clark, 

Idaho Department of Health and Welfare, written commun., 1997). The data collected as part of the SWQP 

show some discrepancies in exceedances of maximum 

water temperature criteria and associated coldwater 

taxa occurrence. Essig (1998) demonstrated similar 

problems with Idaho temperature criteria and fishery 

information, where salmonid spawning and multiple 

age classes are present coincidentally with measured 

temperature criteria exceedances. These findings and 

the results of monitoring at SWQP sites indicate that 

the uniform temperature criteria may not reflect the 

range of stream temperatures in such an ecologically 

diverse State as Idaho. 

Evaluation of the Invertebrate River Index

A subset of 24 sites (noted in table 2) representing 

12 high-quality and 12 low-quality sites were selected 

to validate the IRI. These sites were grouped, independently from IRI rankings, on the basis of multiple measures of human disturbance. A previous discussion, 

“General Approach,” described how these sites were 

grouped. DCA ordination of all sites generally supports 

these site groups with similar taxa composition (fig. 5). 

In this ordination, macroinvertebrate assemblages are 

similar for those sites that plotted nearest one another. 

The high-quality and low-quality sites generally grouped 

together in the lower right and upper center part of the 

plot, respectively. However, the separation between 

these two site groups is not as pronounced as might be 

expected. The tight cluster of low-quality sites 7,17,18, 

32, 37, 50, 52, and 56 in the upper part of the plot typically had a small number of EPT taxa (less than 10) 

and no coldwater taxa. In addition, facultative organisms such as Baetis tricaudatus, Cheumatopsyche, 

Cricotopus, Hydropsyche, Petrophila, Simuliidae, and 

Tricorythodes minutus were the predominant taxa collected at these sites. Sites 21 and 22 are distinctly different from all other sites, primarily because of the 

large number of P. antipodarum collected at these sites. 

The relative magnitude of eigenvalues for each 

DCA axis is an expression of the relative importance of 

each axis. Both axes indicated good separation of taxa 

with eigenvalues of 0.68 and 0.38. It is also noteworthy 

that there are taxa in the data that exhibit unimodal 

response along axis 1 with a gradient of 3.8 standard 

deviation units. A unimodal response approaching 4 

standard deviation units is considered ideal for analysis 

using CCA (Ter Braak and Smilauer, 1998).

Results of the IRI scores in relation to the five 

metrics are shown in figure 6. Between high- and lowquality sites, the IRI median values were significantly 

different, providing evidence that the index can successfully discriminate impairment. However, some values overlapped, as indicated by the boxplots. This is to 

be expected because the high-quality sites were not 

selected specifically as reference sites in this study and, DCA AXIS 2

4

3

2

1

0

Figure 5. Detrended correspondence analysis (DCA) ordination plot

of macroinvertebrate sampling sites, Idaho statewide surface-water

quality monitoring program, 1996–98. (Site names shown in table 1;

locations shown in figure 2. Site quality shown in table 2)

0 34 1 2

DCA AXIS 1

Site and number—blue, high

 quality; open, intermediate

 quality; black, low quality

21

7

32

25

56

18

17

37

52

50

35

13

53

26

16

15

25

30 29

10

42 45

44 8

46 38

14

51

48

31

11

12

47

28 5

6

27

4

41

33

22
28 Evaluation of Macroinvertebrate Assemblages in Idaho Rivers Using Multimetric and Multivariate Techniques, 1996–98 INVERTEBRATE RIVER INDEX SCORE30

20

10

0

p = 0.0033

35

30

25

20

15

10

5

0

p = 0.0002

TO

TAL NUMBER OF TAXA

60

50

40

30

20

10

p = 0.0077

PERCENT DOMINANT TAXON

80

70

60

50

40

30

20

10

p = 0.1782

PERCENT ELMIDAE

15

10

5

0

p = 0.8392

PERCENT PREDATORS

20

15

10

5

0

p = 0.0001

Figure 6. Invertebrate river index (IRI) scores in relation to selected metrics for high-quality (12) and low-quality (12) sites, Idaho

statewide surface-water quality monitoring program, 1996–98. (Specific site information shown in table 2; p, probablility level determined

from Mann-Whitney t-test)

SITE QUALITY

High Low

SITE QUALITY

High Low

EPHEMEROPTERA, PLECOPTERA,

AND TRICHOPTERA TAXA
Results of Macroinvertebrate Taxa and Metrics 29

therefore, would be expected to show some impairment 

and more overlap with the low-quality sites. 

Of the five metrics included in the IRI, median 

values for total number of taxa, EPT taxa, and percent 

predators were significantly different between highand low-quality sites. The EPT taxa and percent predators showed a strong separation between site groups 

(no overlap of interquartile ranges), which indicates 

that these metrics were the most effective at discriminating between high- and low-quality sites. Median 

values for percent dominant taxon and percent Elmidae 

were not significantly different between site groups, 

which indicates that these metrics were relatively ineffective for discriminating between high- and low-quality sites. Contrarily, percent Elmidae was useful in 

other Idaho studies for discriminating reference sites 

from test or adversely affected sites (Robinson and 

Minshall, 1998; Schomberg and others, 1998). Fore 

and others (1996) used percent dominant taxon as a 

metric for evaluating Oregon streams and concluded 

this metric did not distinguish between least- and mostdisturbed sites. Both percent dominant taxon and percent Elmidae metrics displayed a great deal of variability for the low-quality site group, which indicates that 

they are of limited value to the IRI scores. Reexamination of these two metrics would help determine whether 

they are providing useful information to the overall IRI 

score. Some metrics that compose the IRI were redundant. The correlation coefficient between EPT taxa and 

total number of taxa was 0.87 (p<0.05), which indicates that these two metrics are strongly correlated.

Correlation among the eight metrics (total number 

of taxa, EPT taxa, percent predators, percent Elmidae, 

percent dominant taxon, total abundance, number of 

coldwater taxa, and percent coldwater taxa), final IRI 

scores, and the HQI (expressed as percent of total score) 

did not reveal any significant (p<0.05) relations. Stauffer 

and Goldstein (1997) noted similar results in their evaluation of the HQI and fish metrics. They attributed index ineffectiveness to variability as a result of subjectivity in scoring attributes, stream size differences, and 

redundancy in the attributes making up the index. These 

INVERTEBRATE RIVER INDEX SCORE

30

20

10

0

Figure 7. Invertebrate river index (IRI) scores in relation to biotic condition categories for macroinvertebrate sampling sites, by site

type, Idaho statewide surface-water quality monitoring program, 1996–98. (Site types shown in table 2)

10 15 11 22 13 16 30 50 17 41 4 42 52 5 8 53 6 38 7 33 48 47 18 51 14 32 25 37 56 27 12 26 35 28 46 31 45 29 21

Agricultural Forested Large

River

Rangeland Spring

SITE NUMBER AND SITE TYPE

44

Biotic condition

Good

Intermediate

Poor
30 Evaluation of Macroinvertebrate Assemblages in Idaho Rivers Using Multimetric and Multivariate Techniques, 1996–98

findings indicate that the HQI may not be very useful 

for evaluating the condition of Idaho’s larger rivers. 

Summary of Invertebrate River Index 

Scores and Metrics

Results of the final IRI scores for all sites by site 

type are illustrated in figure 7. Biotic condition for 25 

percent of the sites (10 of 40) was categorized as poor 

(IRI score <13). Four of these were large-river sites; 

the remainder of the site types were two agricultural, 

one forested, two rangeland, and one spring. Biotic 

condition for 68 percent of the sites (27 of 40) was categorized as good (IRI score >16); biotic condition for 

only three sites was categorized as intermediate. The 

narrow range separating good from poor biotic condition sites (only 2 score values) is problematic; expansion of this range would improve the discriminatory 

power of the index. 

For example, site 53 appears to be miscategorized 

according to its placement in the PCA ordination with 

other sites with poor condition scores (fig. 8). Expanding the scoring criteria from 0 to 100 points (percentages) may be one simple way to improve separation of 

biotic condition categories. This final scoring criteria 

also would be more familiar to resource managers and 

the public.

The PCA ordination of the eight metrics used to 

summarize macroinvertebrate assemblage data showed 

clear separation of IRI poor and good biotic condition 

(fig. 8). Axes 1 and 2 accounted for 38 and 31 percent 

of the variance among sites, respectively. Metrics with 

high factor loadings on axis 1 (>0.60) included total 

number of taxa, percent Elmidae, percent predators, 

and percent dominant taxon. Number of coldwater 

taxa, percent coldwater taxa, and EPT taxa had high 

factor loadings on axis 2. Total abundance did not have 

a high factor loading on either axis, which indicates 

that this metric was not useful for evaluating biotic 

condition. Sites with good IRI biotic condition scores 

(lower and upper right) typically had a large total number of taxa, percent Elmidae, and percent predators 

(axis 1); and a large number of coldwater taxa, percent 

coldwater taxa, and EPT taxa (axis 2). These metrics 

were typically just the reverse for sites with poor biotic 

condition scores (lower left), and percent dominant 

taxon was higher. 

Many of the sites with increasing values on axis 2 

diverged as a result of the coldwater taxa metrics and 

typically were forested or rangeland site types. These 

results indicate that coldwater metrics may be providing useful information for describing macroinvertebrate assemblages. Further examination of these metrics would help determine whether their inclusion in 

the IRI would improve its discriminatory power. 

RELATION OF MACROINVERTEBRATE 

ASSEMBLAGES TO ENVIRONMENTAL 

VARIABLES

Relation of Macroinvertebrate Assemblages to Environmental Variables

Representative environmental variables consisting 

of basin, site, and habitat characteristics (tables 1 and 

2) were analyzed in relation to the macroinvertebrate 

data by CCA. Because the original list of environmental variables was too large to be interpreted by CCA, a 

subset of these variables was selected using PCA and a 

Monte Carlo forward selection process. This analysis 

helped reduce the redundancy in the environmental 

variables and select a subset of ecologically relevant 

variables for subsequent direct gradient analyses. 

These final CCA ordination plots depict the main pat- PCA AXIS 2

3

2

1

0

-1

-2

-3

Figure 8. Principal components analysis (PCA) ordination plot of

macroinvertebrate sampling sites, by site type, based on eight metrics, Idaho statewide surface-water quality monitoring program,

1996–98. [Metrics shown in table 4, metrics with high factor loadings

(absolute value >0.60) are listed along axes 1 and 2; arrows indicate their

direction of increase. EPT, Ephemeroptera, Plecoptera, and Trichoptera]

-3 -2 2 3 -1 0

PCA AXIS 1

1

38

27

5

33 48

47

4 6

51

26 45

14

8

53 35 7

56

37

32

21 18

12 22 17 31

41 50

16

46

52

44

15 29

13

10

30

11 25

42

28

Site number and site type

Biotic condition Agricultural (13 sites)

Forested (10 sites)

Large river (5 sites)

Rangeland (10 sites)

Spring (2 sites)

25

Good (IRI score >16)

Intermediate

Poor (IRI score <13)

_

_

Total number of taxa

Percent Elmidae

Percent predators

Percent

dominant

taxon

Number of coldwater taxaPercent coldwater taxaNumber of EPT taxa
Relation of Macroinvertebrate Assemblages to Environmental Variables 31

terns of variation in assemblage composition as 

accounted for by the environmental variables.

Principal Components Analysis

PCA of the 24 environmental variables identified 

8 principal components with eigenvalues greater than 1 

(table 5). These 8 principal components explained 81 

percent of the variance in the data set. Loadings with 

an absolute value greater than 0.5 for each principal 

component (shown in bold, table 5) indicated a number 

of groups of closely associated variables. From these 

groups, 10 surrogate variables were selected to represent each group: percent forested land, basin area, percent agricultural land, maximum water temperature, 

dissolved oxygen saturation, stream gradient, elevation, percent substrate fines, percent urban land, and 

percent open canopy. In a few instances, more than one 

variable was selected from the same group because of 

the variable’s ecological relevance. For example, maximum water temperature was selected along with percent agricultural land because of the known influence 

of temperature on macroinvertebrate assemblages 

(Hynes, 1970; Richards and Host, 1994). The HQI and 

stream velocity were inversely related to percent agricultural land, and specific conductance was inversely 

related to percent forested land (table 5).

A scatterplot of PCA axis 1 scores and number of 

EPT taxa (fig. 9) shows a significant inverse relation 

(r=-0.50, p=0.001). PCA axis 1 represents a linear 

combination of percent forested land, latitude, percent 

rangeland, and specific conductance (table 5). The 

number of EPT taxa decreases as the percent of forested land and latitude decrease and percent of rangeland and specific conductance increase. This inversion 

reflects a complex relation of land use and natural factors that influence this important biological metric used 

in water-quality assessments. Corkum (1989) also 

noted a strong association between distributional patterns of benthic invertebrates and landscape variables 

of rivers in northwestern North America. 

Canonical Correspondence Analysis

Percent forested land, percent agricultural land, 

urban land, maximum water temperature, percent substrate fines, and stream gradient were identified in the 

forward selection process by CCA as significant 

(p<0.05) in the ordination of species data. 

Two CCA ordination plots are shown for all sites 

(fig. 10) and taxa scores (fig. 11) in relation to the six 

selected environmental variables. The eigenvalues of 

the first two CCA axes illustrate the strength of the 

relation between taxa and environmental variables 

(table 6). Both axes accounted for about the same 

amount of variance with eigenvalues of 0.35 and 0.34, 

respectively. Correlations among taxa and environmental variables for the first and second axes were 0.84 and 

0.88, respectively, and explained 46 percent of the joint 

variance between the macroinvertebrate taxa and environmental variables. The Monte Carlo test of variables 

along all canonical axes was significant (p=0.005) and 

indicates that the model (ordination diagram) represents a good fit of the macroinvertebrate taxa and environmental data. The environmental variables with long 

vectors are more strongly correlated with the ordination axes than are those with short vectors. In other 

words, long vectors depict greater influence of that 

environmental variable in structuring the macroinverteNUMBER OF EPT TAXA

35

28

21

14

7

0

Figure 9. Principal components analysis (PCA) axis 1 scores in relation to number of Ephemeroptera, Plecoptera, and Trichoptera (EPT)

taxa for macroinvertebrate sampling sites in the Idaho statewide

surface-water quality monitoring program, 1996–98. [Environmental

variables shown in table 5; variables with high factor loadings (absolute

value >0.60) are listed along axis 1; arrows indicate their direction of increase.

Site names shown in table 1; locations shown in figure 2. r, Pearson's correlation coefficient; p, probability level]

-4 -3 4 -2 2 3 -1 0

PCA AXIS 1

1

47

Site and number 25

Percent rangeland

Specific conductance

Percent forested land

Latitude

6

4

38 26

48 27

51

25

28

14

45

11 33 50

13

44

46

29

31 30 53

15 37

42

10

8

35

52

5

7 12

18

56

41 16

22

32

17 21

r = -0.50

p = 0.001
32 Evaluation of Macroinvertebrate Assemblages in Idaho Rivers Using Multimetric and Multivariate Techniques, 1996–98

brate assemblages. These vectors also extend an equivalent length into the opposite quadrant (but are not 

shown on the graph) to represent the effect of low values of the environmental variables. These ordination 

analyses were constrained by the environmental variables shown in figures 10 and 11 and directly relate the 

environmental gradients to the macroinvertebrate 

assemblages. The location of a taxon relative to an axis 

is the taxon’s optimum set of conditions that compose 

the axis (fig. 11). That location is the mode of the unimodal distribution of that taxon’s abundance in the gradient expressed by the axis.

Most of the variability in environmental variables 

was accounted for by forested, urban, and agricultural 

land uses with eigenvalues of 0.32, 0.31, and 0.26, 

respectively (table 6). Land use can be an important, 

large-scale factor affecting the composition and structure of macroinvertebrate assemblages (Richards and 

Host, 1994; Schomberg and others, 1998). Corkum 

(1990) noted that agricultural land overrode the effect 

of natural vegetation patterns on macroinvertebrate 

assemblages. In this study, there was a significant 

inverse relation (r=-0.56, p<0.05), between percent 

agricultural land and the number of coldwater taxa. 

Even though urban land composed a small percentage of most basins (less than 3 percent), it was 

identified as an important environmental gradient in the 

CCA. For example, sites 17 and 22 are at the upper end 

of the urban land-use gradient (fig. 10). Both of these 

sites are within the city limits of Pocatello and Twin 

Falls. Maret (1990) characterized the macroinvertebrates collected from riffle habitats in lower Rock 

Creek (near site 22) as composed primarily of the facultative taxa Hydropsyche, Tricorythodes minutus, and 

Baetis tricaudatus. Jones and Clark (1987) concluded 

that urbanization has a major effect on benthic invertebrate assemblages by reducing diversity and total number of most taxa while increasing the relative abundance of chironomids. Kleindl (1995) found that as 

urbanization increased in Puget Sound basins of Washington, the number of macroinvertebrate taxa, number 

of intolerant taxa, and number of predators declined 

while the relative number and abundance of tolerant 

taxa increased. 

Canonical coefficients for all six environmental 

variables were significant (p<0.05) with axis 1 or 2 

(table 6). Forested land (-0.81) and urban land (0.73) 

were significant (t> +2.1) with axis 1. Urban land 

(0.31), agricultural land (-0.55), percent substrate fines 

(-0.33), maximum water temperature (-0.46), and 

stream gradient (0.23) were significant with axis 2. 

Greater absolute values of canonical coefficients indicated stronger correlation between a variable and the 

Table 6. Summary of correspondence analysis including 

canonical coefficients and t-values of canonical coefficients 

for environmental variables, Idaho statewide surface-water 

quality monitoring program, 1996–98. 

[Significant canonical coefficients with t-values greater than the absolute value of 2.1 (p<0.05) are shown in bold; eigenvalues for axis 1 and 

axis 2 were 0.35 and 0.34, respectively (see figures 10 and 11)]

Canonical

Canonical coefficient

coefficient t-value

Environmental variable Eigenvalue Axis 1 Axis 2 Axis 1 Axis 2

Forested land . . . . . . . . . . . . . . 0.32 -0.81 0.06 -6.24 0.54

Urban land . . . . . . . . . . . . . . . . .31 .73 .31 5.91 2.97

Agricultural land . . . . . . . . . . . .26 -.28 -.55 -2.07 -4.83

Percent substrate fines . . . . . . . .22 -.01 -.33 -.08 -2.98

Maximum water 

temperature . . . . . . . . . . . . . . .21 -.25 -.46 -1.98 -4.41

Stream gradient . . . . . . . . . . . . .17 -.10 .23 -.83 2.35

CCA AXIS 2

1.0

0.5

0

-0.5

-1.0

Figure 10. Canonical correspondence analysis (CCA) ordination plot

of macroinvertebrate sampling sites in relation to selected environmental variables, Idaho statewide surface-water quality monitoring

program, 1996–98. [All environmental variables were significant (p<0.05)

with one or both axes. Site names shown in table 1; locations shown in

figure 2. Coldwater taxa identified in table A, back of report]

-1.0 0.5 1.0 -0.5 0

CCA AXIS 1

8

5

22

47

48

38

27

26

35

28

21

7

45

46

33 6

4

51

12

10

14 41 31

1856 17

29 16

15 53

30 32

37

13 50

52 42

25

11

44

Group 1

Group 2

Percent

forested

land

Stream

gradient

Percent

urban land

Percent

substrate

Percent fines

agricultural

land

Maximum

water

temperature

Site type

Agricultural (13 sites)

Forested (10 sites)

Large river (5 sites)

Rangeland (10 sites)

Spring (2 sites)

25 Site number

Site where coldwater

 taxa were collected

Environmental gradient

EXPLANATION
Relation of Macroinvertebrate Assemblages to Environmental Variables 33

axis tested. Correlations were strongest for variables 

that most influenced taxa composition. Previous studies have demonstrated that the habitat variables stream 

gradient, water temperature, and percent substrate fines 

affect macroinvertebrate assemblages (Hynes, 1970; 

Richards and others, 1993; Tate and Heiny, 1995; Lammert and Allan, 1999). 

Basin size and elevation were not identified as 

important environmental variables in this analysis; 

however, stream gradient could be considered a surrogate for these variables. Because dams and diversions 

affect many Idaho rivers, the use of additional surrogate measures of hydrologic stability, such as the coefficients of variation of annual discharge and stream 

power (basin area x slope), to define the effects of 

hydrologic modifications on macroinvertebrate assemblages could be beneficial for future studies. Both measures have been used to evaluate hydrologic effects on 

aquatic life in streams (Poff and Allan, 1995; Kaufmann and others, 1999).

The CCA ordination (fig. 10) appeared to better 

differentiate between agricultural sites and forested or 

rangeland sites than did the IRI (fig. 7). Two distinct 

groups of sites were identified in the CCA ordination. 

Group 1, primarily above the origin, represented highgradient, coldwater, forested and rangeland sites; group 

2, primarily below the origin, represented sites influenced by human disturbance, increased percent substrate fines, and increased water temperatures that typically are associated with agricultural and (or) urban 

land uses. All five large-river sites on the main-stem 

Snake River grouped together in the ordination plot 

(group 2), which indicates their similarity in taxa and 

environmental conditions. At the 14 forested and rangeland sites (group 1), the mean number of EPT taxa was 

19, and at the 23 agricultural and urban sites (group 2), 

the mean number was 11.

Sites 5, 21, and 22 (fig. 10, upper right quadrant) 

are outliers, not closely associated with either site 

group, primarily as the result of the abundance of the 

introduced species P. antipodarum at sites 21 and 22 

and the abundance of the coldwater species E. deceptivus at site 5 (fig. 11, upper right quadrant). Site 5 on the 

South Fork Coeur d’Alene River is downstream from 

areas of extensive mining activities, and the macroinvertebrate assemblages have been impaired by habitat 

degradation and the toxic effects of trace elements 

(Maret and Dutton, 1999).

Rhyacophila Coloradensis Group

Sweltsa

Zapada cinctipes

Acari

Chaetocladius

Clinocera

Drunella coloradensis/flavilinea

Epeorus deceptivus

Ephemera

Fluminicola

Haliplus

Hirudinea

Hyalella azteca

Parakiefferiella

Pentaneura

Potamopyrgus antipodarum

Rhyacophila Angelita Group

Stratiomyidae

Thienemanniella

Thienemannimyia Group

Tinodes

Tipulidae

Tricorythodes minutus

CCA AXIS 2

1.0

0.5

0

-0.5

-1.0

Figure 11. Canonical correspondence analysis (CCA) ordination plot

of taxa in relation to selected environmental variables, Idaho statewide surface-water quality monitoring program, 1996–98. [All environmental variables were significant (p<0.05) with one or both axes. The 46

taxa most influencing the ordination are shown]

-1.0 0.5 1.0 -0.5 0

CCA AXIS 1

Percent

forested

land

Stream

gradient

Percent

urban land

Percent

substrate

Percent fines

agricultural

land

Maximum

water

temperature

Site where taxa were collected—Letter identifies taxa

 listed below

Site where coldwater taxa were collected—Coldwater

 taxa identified in bold in list below

Environmental gradient

EXPLANATION

Ameletus

Apatania

Arctopsyche grandis

Atherix

Brachycentrus americanus

Calineuria californica

Caudatella

Chloroperlidae

Claassnia sabulosa

Diamesa

Dolophilodes

Drunella doddsi

Drunella grandis/spinifera

Epeorus albertae

Epeorus grandis

Eukiefferiella

Glossosoma

Hesperoperla pacifica

Micrasema

Narpus

Neophylax rickeri

Pteronarcys californica

Rithrogena

A

B

C

D

E

F

G

H

I

J

K

L

M

N

O

P

Q

R

S

T

C

N

D E

S

M

K

R

O

J

G

P

T

Q

A

I

L

H

B

F
34 Evaluation of Macroinvertebrate Assemblages in Idaho Rivers Using Multimetric and Multivariate Techniques, 1996–98

 Forty-six taxa (about 25 percent of the total RTH 

taxa collected) that most influence the ordination analyses are shown in figure 11. A tight cluster of 26 taxa 

that were associated primarily with group 1 in figure 

10 was identified. This group comprised most of the 

coldwater taxa characteristic of group 1 (above origin, 

fig. 11): Ameletus, Apatania, Caudatella, Drunella 

doddsi, and Epeorus grandis. Some of the other closely 

associated taxa in this group may be prime candidates 

for evaluating as possible coldwater or intolerant indicator taxa. According to Wisseman (1996), many of the 

taxa in this group also would be considered intolerant 

to human disturbance.

The lower site group in figure 10 (below origin) 

would be considered more facultative and tolerant to 

human disturbance such as Acari, Thienemanniella, 

Thienemannimyia Group, Hirudinea, Tricorythodes 

minutus, Fluminicola, and Pentaneura (Wisseman, 

1996). Site 50, Lapwai Creek near Lapwai, has been 

characterized (Delong and Brusven, 1998; Waite, 

1994) as having a relatively homogeneous macroinvertebrate assemblage that is tolerant of agricultural nonpoint-source pollution. The position of this site in the 

ordination plot in relation to the environmental variables (fig. 10) supports this characterization. Silver 

Creek near Picabo (site 29, fig. 10) contained only the 

taxa Ephemera, Haliplus, and Chaetocladius (fig. 11). 

This is a relatively small, low-gradient site with an 

abundance of fine substrates.

The CCA has demonstrated that various factors 

operating at different spatial scales are affecting the 

macroinvertebrate assemblages in Idaho rivers. The 

large-scale environmental gradients of basin land use 

were identified as most important; however, more sitespecific habitat measures that relate to land use such as 

maximum water temperature, and substrate characteristics such as percent substrate fines, are also important. Instream measures of these habitat variables 

should be continued and expanded to all SWQP sites. 

The summer continuous temperature monitoring is particularly important for describing temperature extremes 

and duration of exposure for coldwater resources, particularly because elevated water temperature is the second most common cause of surface-water quality 

impairment in Idaho and the Western United States 

(Woodruff, 2000). As more data of this type are collected concurrently with biological assemblage information, more refinements in water-quality criteria and 

use designations can be made. Ultimately, this type of 

information can be used to effectively manage, protect, 

and enhance water resources for human health and 

environmental quality. 

SUMMARY AND CONCLUSIONS

Summary and Conclusions

In 1996, the Idaho statewide surface-water quality 

monitoring program (SWQP) was redesigned to include 

aquatic biological collections of macroinvertebrates, 

fish, fish tissue contaminants, and associated stream 

habitat parameters to more effectively assess the status 

and trends of stream quality in Idaho. Forty sites were 

selected for macroinvertebrate sampling and habitat 

assessment from a network of 56 sampling sites.

Quality assurance samples were collected at three 

sites to evaluate intralaboratory and interlaboratory 

precision for qualitative multiple habitat (QMH) and 

richest targeted habitat (RTH) samples. Interlaboratory 

comparisons indicated the importance of using the same 

laboratory for consistency in taxonomic determinations 

and also in standardizing the resolution required for determination of metric values used in calculating biotic 

indices such as the IRI. In addition, these quality assurance samples provided valuable information about the 

performance standards of laboratories and should continue to be a vital part of the monitoring program to 

ensure the integrity of the taxonomic data.

A variety of environmental variables consisting of 

basin, hydrologic, and habitat characteristics were evaluated for each site. Site characterization was based on a 

tiered design that incorporated information at basin, 

reach, and site levels. Preliminary analysis indicated 

no correspondence between ecoregion percentages 

upstream from each site and macroinvertebrate assemblages. 

Two hundred and forty-seven macroinvertebrate 

taxa were identified in RTH and QMH samples collected from the 40 sampling sites. Riffles (RTH samples) supported 184 taxa (74 percent) of the total taxa 

collected. The most abundant taxa identified in RTH 

samples were Oligochaeta, Baetis tricaudatus, Hydropsyche, Simuliidae, Chironomidae pupae, Cricotopus, 

Eukiefferiella, and Orthocladius complex.

Abundance (density expressed as individuals/m2) 

for RTH samples ranged from 1,021 at Bruneau River 

at Hot Spring (site 31) to 63,000 at Blue Lakes Spring 

(site 21). The extremely high abundance at site 21 was 

due to the large numbers of Hyalella azteca (Amphipod) and Potamopyrgus antipodarum (New Zealand 
Summary and Conclusions 35

mud snail), a recently introduced gastropod in the 

Hagerman Valley, thought to have originated from 

commercial movement of aquaculture products such as 

trout eggs and live fish. This species also was found at 

sites 11, 32, 37, 44, and 56, which indicates that it is 

spreading from its area of introduction.

The total number of taxa and Ephemeroptera, 

Plecoptera, and Trichoptera (EPT) taxa varied greatly 

among sites for both sample types. Total number of 

taxa identified in QMH samples ranged from 14 at 

Willow Creek near Ririe (site 12) to 59 at North Fork 

Coeur d’Alene River at Enaville (site 4). Site 12 is 

immediately downstream from Ririe Lake dam, which 

may be limiting the diversity of taxa at this location. 

Sampling sites such as this are not representative of the 

upstream basin characteristics and could be dropped 

from the SWQP.

RTH and QMH sample types were evaluated 

using final invertebrate river index (IRI) scores and the 

five individual metrics (total number of taxa, EPT taxa, 

percent predators, percent Elmidae, and percent dominant taxon) composing this index. Median values for 

total number of taxa and percent dominant taxon were 

significantly different (p<0.05) between RTH and 

QMH samples. There was no statistical difference in 

median IRI scores between sample types. This statistical similarity indicated that either sample type could be 

used to evaluate biological condition by using the IRI 

and that the QMH sample did not provide additional 

information to help assess water quality by using the 

IRI. These findings indicated that QMH samples could 

be dropped from the SWQP. In rare cases where riffle 

habitat may not be available, then QMH samples could 

be collected as a replacement for RTH samples.

Fourteen coldwater taxa were collected during this 

study at 12 sampling sites. This represented only about 

6 percent (14 of 247) of all taxa identified in both RTH 

and QMH samples; frequency of occurrence was 30 

percent (12 of 40) for all sites. Most of these coldwater 

taxa were collected at forested sites; the most abundant 

taxon was E. deceptivus, a mayfly typically associated 

with high-gradient mountain streams. Generally, where 

coldwater taxa were identified in RTH samples, they 

composed a small proportion (less than 10 percent) of 

the total abundance, except at the South Fork Coeur 

d’Alene River near Pinehurst (site 5), where E. deceptivus composed almost 30 percent of the total abundance.

It is not surprising that more coldwater taxa were 

not collected because maximum water temperature at 

62 percent of the sampling sites exceeded Idaho’s 

instantaneous coldwater temperature criteria of 22 °C. 

Conversely, maximum temperature exceeded 22 °C at 5 

of the 12 sites where RTH samples contained coldwater 

taxa. No coldwater taxa were collected at the five largeriver sites on the main-stem Snake River in the southern part of the State. Maximum temperatures at these 

sites ranged from 22.1 to 26.9 °C. Coldwater taxa also 

were not found at spring sites 21 and 29, even though 

maximum temperatures at these sites were 22 °C or 

below. These discrepancies and the absence of coldwater taxa at spring sites indicated that the uniform temperature criteria may not reflect the range of stream 

temperatures in such an environmentally diverse State 

as Idaho. 

A subset of 24 sites representing 12 high-quality 

and 12 low-quality sites were selected on the basis of 

multiple measures of human disturbance, and the IRI 

scores of these 24 sites were compared to validate the 

index. Detrended correspondence analysis (DCA) of 

all sites supported these site groups with similar taxa 

composition. Between high- and low-quality sites, the 

IRI median values were significantly different, providing evidence that the index can successfully discriminate impairment. Of the five metrics included in the 

IRI, median values for total number of taxa, EPT taxa, 

and percent predators were significantly different 

between high- and low-quality sites. The EPT taxa and 

percent predators showed a strong separation between 

site groups (no overlap of interquartile ranges), which 

indicated that these metrics were the most effective at 

discriminating between high- and low-quality sites. 

Median values for percent dominant taxon and percent 

Elmidae were not significantly different between site 

groups, which indicated that these metrics were relatively ineffective at discriminating between high- and 

low-quality sites. Reexamination of these two metrics 

would help determine whether they are providing useful information to the overall IRI score.

Correlation among the original eight metrics (the 

five metrics used to calculate the final IRI plus total 

abundance, percent coldwater taxa, and number of 

coldwater taxa), final IRI scores, and the habitat quality 

index (HQI), expressed as percent of total score, did 

not reveal any significant (p<0.05) relations. These 

findings indicated that the HQI may not be very useful 

for evaluating the condition of Idaho’s larger rivers.

Biotic condition for 25 percent of the 40 sampling 

sites was categorized as poor (IRI score <13). Four of 

these were large-river sites; the remainder of the site 
36 Evaluation of Macroinvertebrate Assemblages in Idaho Rivers Using Multimetric and Multivariate Techniques, 1996–98

types were two agricultural, one forested, two rangeland, and one spring. Biotic condition for 68 percent of 

the sites (27 of 40) was categorized as good (IRI score 

>16); biotic condition for only three sites was categorized as intermediate. The narrow range separating 

good from poor biotic condition sites (only 2 score values) is problematic; expansion of this range would 

improve the discriminatory power of the index. 

Expanding the scoring criteria from 0 to 100 points 

(percentages) may be one simple way to improve separation of biological condition categories. This final 

scoring criteria also would be more familiar to resource 

managers and the public.

Principal components analysis (PCA) revealed that 

coldwater taxa metrics were associated with forested or 

rangeland site types, which typically had good biotic 

condition scores. These results indicated that coldwater 

metrics may be providing useful information for 

describing macroinvertebrate assemblages. Further 

examination of these metrics would help determine 

whether their inclusion in the IRI would improve its 

discriminatory power.

PCA of the 24 environmental variables identified 

8 principal components with eigenvalues greater than 

1. From groups of closely associated variables, 10 surrogate variables were selected to represent each group: 

percent forested land, basin area, percent agricultural 

land, maximum water temperature, dissolved oxygen 

saturation, stream gradient, elevation, percent substrate 

fines, percent urban land, and percent open canopy. 

A scatterplot of PCA axis 1 scores and number of 

EPT taxa showed a significant inverse relation (r=-0.50, 

p=0.001). The number of EPT taxa decreased as percent forested land and latitude decreased and percent 

rangeland and specific conductance increased. This 

inversion reflected a complex relation of land uses and 

natural factors that influence this important biological 

metric used in water-quality assessments.

Percent forested land, percent agricultural land, 

urban land, maximum water temperature, percent substrate fines, and stream gradient were identified in the 

forward selection process by canonical correspondence 

analysis (CCA) as significant (p<0.05) in the ordination of species data. The first two axes accounted for 46 

percent of the joint variance between the macroinvertebrate taxa and environmental variables. The Monte 

Carlo test of variables along all canonical axes was significant (p=0.005) and indicated that the model (ordination diagram) represented a good fit of the macroinvertebrate taxa and environmental data. Most of the 

variability in environmental variables was accounted 

for by forested, urban, and agricultural land uses with 

eigenvalues of 0.32, 0.31, and 0.26, respectively. 

Canonical coefficients for all six environmental variables were significant (p<0.05) with axis 1 or 2. Forested land (-0.81) and urban land (0.73) were significant with axis 1. Urban land (0.31), agricultural land 

(-0.55), percent substrate fines (-0.33), maximum water 

temperature (-0.46), and stream gradient (0.23) were 

significant with axis 2.

The CCA ordination identified two distinct groups 

of sites—those representing more high-gradient, coldwater, forested and rangeland sites and those representing sites influenced by human disturbance, indicated by 

increased percent substrate fines and increased water 

temperatures that typically are associated with agricultural and urban land uses. At the 14 forested and rangeland sites (group 1), the mean number of EPT taxa was 

19, and at the 23 agricultural and urban sites (group 2), 

the mean number was 11.

The CCA demonstrated that various factors operating at different spatial scales are affecting the macroinvertebrate assemblages in Idaho rivers. The largescale environmental gradients of basin land use were 

identified as most important; however, more site-specific habitat measures that relate to land use such as 

maximum water temperature, and substrate characteristics such as percent substrate fines also are important. 

Instream measures of these habitat variables should be 

continued and expanded to all SWQP sites.

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SUPPLEMENTAL INFORMATION

tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98

; S., South; Cr., Creek; USGS, U.S. Geological Survey; ID, identification; site locations shown in figure 1; QMH, qualitative multiple habitat reported in total 

eted habitat (riffles) reported in abundance (individuals per square meter); No., number; coldwater taxa are shaded]

S. Fork

Coeur Henrys

R. d’Alene R. St. Joe R. Spokane R. Snake R. Teton R. Fork Willow Cr. Blackfoot R. Snake R. Portneuf R. Marsh Cr. Portneuf R. Snake R. 

nr at nr nr nr nr nr nr nr at nr at nr

 Pinehurst Calder Post Falls Heise St. Anthony Rexburg Ririe Blackfoot Blackfoot Topaz McCammon Pocatello Minidoka

1998 1998 1998 1996 1996 1996 1996 1996 1996 1996 1996 1996 1996

0 12413470 12414500 12419000 13037500 13055000 13056500 13058000 13068500 13069500 13073000 13075000 13075500 13081500

5 6 7 8 10 11 12 13 14 15 16 17 18

H QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Noninsect

4 7 40 112 180 500 42 60 1 175 6 94 105 162 12 81 21 15

3

3

6 38 36

580 1,880 66 10 6 19 408 312 1,515 64

312 1,500

570 338

100

6 1 6 12 35 30 15

140 50 294 2 1 195 108 300 1,335 1,238

6 24 12

5

4 12 2 12 15 512 24 30

5 5 4 3 1,720 300 1,120 500 834 82 2,520 750 11 25 210 56 270 432 381 155 279 1,215

40 48 2 30 19 330 432 25 15

12

5 23 860 516 38 1 42 15 96 35 180 113

20

12

2

20

680 50

5 200 150 114 12 42 19 72 81 55 15

900 150 7 25 234 244 12 12 495

0 33 57 144 100 12 36 10

100

19

Insect

25 30

5 6 2 12
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued 

S. Fork 

Coeur Henrys 

R. d’Alene R. St. Joe R. Spokane R. Snake R. Teton R. Fork Willow Cr. Blackfoot R. Snake R. Portneuf R. Marsh Cr. Portneuf R. Snake R. 

nr at nr nr nr nr nr nr nr at nr at nr

 Pinehurst Calder Post Falls Heise St. Anthony Rexburg Ririe Blackfoot Blackfoot Topaz McCammon Pocatello Minidoka

1998 1998 1998 1996 1996 1996 1996 1996 1996 1996 1996 1996 1996

0 12413470 12414500 12419000 13037500 13055000 13056500 13058000 13068500 13069500 13073000 13075000 13075500 13081500

5 6 7 8 10 11 12 13 14 15 16 17 18

H QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Insect—Continued

5

5

1 6

9 8 190 656 37 464 120 300 60 400 25 600 225

25 15

5 85 24 40 2

9 15 4 320 42 179 1,225 405 362

4 188 174 235 224 97 544 4,200 4,388 640 5,100 18 2 12 150 14 550 42 375 1,155 132 196 80 300 465 1,800

6 5

6 35 8 325

140 60 72 36475 4 40 462 5 48

6 19

5 4

4 5 4 140 8

0 44 105 5

0 8

8

4 20 108

0 235 534 8

0 5 30 400 188 80 1,400 1 75 156 2,381 12

3 5 56 80 12 2 5 100 6 56

4 40 120 100 38 25 96 25
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued

S. Fork

Coeur Henrys

R. d’Alene R. St. Joe R. Spokane R. Snake R. Teton R. Fork Willow Cr. Blackfoot R. Snake R. Portneuf R. Marsh Cr. Portneuf R. Snake R. 

nr at nr nr nr nr nr nr nr at nr at nr

 Pinehurst Calder Post Falls Heise St. Anthony Rexburg Ririe Blackfoot Blackfoot Topaz McCammon Pocatello Minidoka

1998 1998 1998 1996 1996 1996 1996 1996 1996 1996 1996 1996 1996

0 12413470 12414500 12419000 13037500 13055000 13056500 13058000 13068500 13069500 13073000 13075000 13075500 13081500

5 6 7 8 10 11 12 13 14 15 16 17 18

H QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Insect—Continued

5 50 276 240 150 120 400 300 12

5 3 6 40 148

109 50

250 56 15 21

20

5 120 48 138 38 84 3,475 210 56 210 450 95 480 788

5 8

8 25 24 20 40 38

0 8 40 38 50 19

16 50

5 4 400 525 100 850 2 1 50 12 281 12

38 19

2 5 9

4 50

50

3

12

125

3 5

4 15

5

4

2 19 9 52
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued 

S. Fork 

Coeur Henrys 

R. d’Alene R. St. Joe R. Spokane R. Snake R. Teton R. Fork Willow Cr. Blackfoot R. Snake R. Portneuf R. Marsh Cr. Portneuf R. Snake R. 

nr at nr nr nr nr nr nr nr at nr at nr

 Pinehurst Calder Post Falls Heise St. Anthony Rexburg Ririe Blackfoot Blackfoot Topaz McCammon Pocatello Minidoka

1998 1998 1998 1996 1996 1996 1996 1996 1996 1996 1996 1996 1996

0 12413470 12414500 12419000 13037500 13055000 13056500 13058000 13068500 13069500 13073000 13075000 13075500 13081500

5 6 7 8 10 11 12 13 14 15 16 17 18

H QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Insect—Continued

180 172 321 825 150 50 6 45 38 648 588 21

3 19

176 1,920 24 12

4 15 25

3 5 3

5 3 4

80 40 15

6 76 126 10 64 483 5,184 1,000 1,763 940 6,150 22 38 20 1,775 90 1,294 1,020 1,025 588 1,846 305 8,851 1,860 34,538

15 1 50 38 45 96 81 30

8 8 150

265

183 736

15

14 4 40

10

25 55

5 4

2 15 25 60

20 50

3 5

50 19

5

6 112

5
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued

S. Fork

Coeur Henrys

R. d’Alene R. St. Joe R. Spokane R. Snake R. Teton R. Fork Willow Cr. Blackfoot R. Snake R. Portneuf R. Marsh Cr. Portneuf R. Snake R. 

nr at nr nr nr nr nr nr nr at nr at nr

 Pinehurst Calder Post Falls Heise St. Anthony Rexburg Ririe Blackfoot Blackfoot Topaz McCammon Pocatello Minidoka

1998 1998 1998 1996 1996 1996 1996 1996 1996 1996 1996 1996 1996

0 12413470 12414500 12419000 13037500 13055000 13056500 13058000 13068500 13069500 13073000 13075000 13075500 13081500

5 6 7 8 10 11 12 13 14 15 16 17 18

H QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Insect—Continued

8 15

40

47 368 80 1,100 1 300 12 300 38 21 15 112

38

24 2 24 58 25

134 3 5 42 1 30

25

15

5 2 500 45 125 12 10 407

4 12 20 40 320 800 6 25 23 1,400 6 19 255 575 24 219

7

6 2

15

4 5 340 1,250 12

5 3 24 32

5 3 3 4 80 200

5 6 2 12 15

5

6
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued 

S. Fork 

Coeur Henrys 

R. d’Alene R. St. Joe R. Spokane R. Snake R. Teton R. Fork Willow Cr. Blackfoot R. Snake R. Portneuf R. Marsh Cr. Portneuf R. Snake R. 

nr at nr nr nr nr nr nr nr at nr at nr

 Pinehurst Calder Post Falls Heise St. Anthony Rexburg Ririe Blackfoot Blackfoot Topaz McCammon Pocatello Minidoka

1998 1998 1998 1996 1996 1996 1996 1996 1996 1996 1996 1996 1996

0 12413470 12414500 12419000 13037500 13055000 13056500 13058000 13068500 13069500 13073000 13075000 13075500 13081500

5 6 7 8 10 11 12 13 14 15 16 17 18

H QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Insect—Continued

10

5 12

5

5 20 50 15 96 21

5 4

2

2 30 9 20 20 7 64 2,720 4,763 180 1,300 48 712 175 19 315 25 1,896 392 35 42 75 281

12

3 12

76 3 6

10 4 6

10

7 16

10

6 53 144 520 112 160 450 193 45

1 38 153 20 88 17 16 640 488 40 450 12 95 204 2,100 6 200 42 319 105 75 24 104 10 75 56

12 102 12 15

4 24 8 25 48 46

10 80 12 8 30

16 170 47 2,920 2,363 248 1,750 24 244 1,032 6,750 38 75 300 2,776 375 50 696 646 30 364 345

10 18 55 1 12 5

5

5 6 8

230 120 40 50 15 648 112 96 23 150
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued

S. Fork

Coeur Henrys

R. d’Alene R. St. Joe R. Spokane R. Snake R. Teton R. Fork Willow Cr. Blackfoot R. Snake R. Portneuf R. Marsh Cr. Portneuf R. Snake R. 

nr at nr nr nr nr nr nr nr at nr at nr

 Pinehurst Calder Post Falls Heise St. Anthony Rexburg Ririe Blackfoot Blackfoot Topaz McCammon Pocatello Minidoka

1998 1998 1998 1996 1996 1996 1996 1996 1996 1996 1996 1996 1996

0 12413470 12414500 12419000 13037500 13055000 13056500 13058000 13068500 13069500 13073000 13075000 13075500 13081500

5 6 7 8 10 11 12 13 14 15 16 17 18

H QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Insect—Continued

9 60 27 10 20 7 16 920 150 40 250 8 132 150 18 38 120 100 12 5 21 15

18

5

10 120 30

12

5 22 6 45 4 13 400 150 30 84 30 12

0 8 200 150 40 150 30 12 12

20 12 8 30 12 48

1 5

25 810 12

8 322 651 55 88 320 96 1,440 1,313 350 82 2,568 8,138 50 169 30

5 10 16 400 375 30 75

18 120 12

200 38 20 60 12

35 66 168 15 50 234 75 48 69 45

11 10 6

10 180 204 104

10 200 15 216 216 30 5 21

8 11 160 136 120 60 30 15 30 800 48 319 225 88 24 12 95 300 15

27 4

132 1

20

600 188

18
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued 

S. Fork 

Coeur Henrys 

R. d’Alene R. St. Joe R. Spokane R. Snake R. Teton R. Fork Willow Cr. Blackfoot R. Snake R. Portneuf R. Marsh Cr. Portneuf R. Snake R. 

nr at nr nr nr nr nr nr nr at nr at nr

 Pinehurst Calder Post Falls Heise St. Anthony Rexburg Ririe Blackfoot Blackfoot Topaz McCammon Pocatello Minidoka

1998 1998 1998 1996 1996 1996 1996 1996 1996 1996 1996 1996 1996

0 12413470 12414500 12419000 13037500 13055000 13056500 13058000 13068500 13069500 13073000 13075000 13075500 13081500

5 6 7 8 10 11 12 13 14 15 16 17 18

H QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Insect—Continued

5 25 36 30 28 9 425 38 60 25 12 15 21

8 30

10

7 120 150 160 8 2

60 50 8 2 18

5 395 520 38 400 30 8 28 50 30 12 96 10

9 11 6 115 120 40 50 48 1 150 36 30 38 60 81 20 43

44 6 4 64 2,000 338 20 50 1 60 62 20 107

25

Rock Cr. Camas Cr. Boise R. Boise R.

at at Beaver Cr. Big Lost R. Big Wood R. Silver Cr. Malad R. Bruneau R. Snake R. nr at Snake R. 

Blue Lakes Daydream Red at nr nr nr nr nr nr Twin Glenwood at 

Spring Ranch Road Spencer Chilly Bellevue Picabo Gooding Hot Spring Murphy Springs Bridge Nyssa

1996 1996 1997 1997 1996 1997 1997 1997 1997 1997 1997 1997 1997

13091000 13092747 13108900 13113000 13120500 13141000 13150430 13152500 13168500 13172500 13185000 13206000 13213100

21 22 25 26 27 28 29 30 31 32 33 35 37

MH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Noninsect 

2,400 720 40 300 230 109 80 105 25 30 2 7 6 25 8 24 21 71 10 120 72 20

60

1,640 2,160 728 252 55 6 22 36

17 2 360

2

80 3 17
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued

Rock Cr. Camas Cr. Boise R. Boise R.

at at Beaver Cr. Big Lost R. Big Wood R. Silver Cr. Malad R. Bruneau R. Snake R. nr at Snake R. 

Blue Lakes Daydream Red at nr nr nr nr nr nr Twin Glenwood at 

Spring Ranch Road Spencer Chilly Bellevue Picabo Gooding Hot Spring Murphy Springs Bridge Nyssa

1996 1996 1997 1997 1996 1997 1997 1997 1997 1997 1997 1997 1997

13091000 13092747 13108900 13113000 13120500 13141000 13150430 13152500 13168500 13172500 13185000 13206000 13213100

21 22 25 26 27 28 29 30 31 32 33 35 37

MH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Noninsect—Continued

3 38 25 2 4

,400 29,400 280 26

80 50 11 40 30 88 4 2 2 5 10 11 42 60 8

960 720 120 114 32 1,020 266 180 25 2 113 44 9 6 45 2 289 8,580 472 6 4

,200 16 20 15 15 8 5 4 60

120 320 30 2

2,840 9,120 16,960 17,550 2 4

80 150 28 35 2 323 4

320 960 40 50 6 3 2 4 10 48 8

7

2

Insect

120 2

40

15 15 90 11 8 2 2 70 6 114 160 99 54 960 232 102 136

23

15 12 7

6 360 236 30 60
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued Rock Cr. Camas Cr. Boise R. Boise R. at at Beaver Cr. Big Lost R. Big Wood R. Silver Cr. Malad R. Bruneau R. Snake R. nr at Snake R. Blue Lakes Daydream Red at nr nr nr nr nr nr Twin Glenwood at 

Spring Ranch Road Spencer Chilly Bellevue Picabo Gooding Hot Spring Murphy Springs Bridge Nyssa

1996 1996 1997 1997 1996 1997 1997 1997 1997 1997 1997 1997 1997

13091000 13092747 13108900 13113000 13120500 13141000 13150430 13152500 13168500 13172500 13185000 13206000 13213100

21 22 25 26 27 28 29 30 31 32 33 35 37

MH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Insect—Continued

160 17 218 54 6 10

840 4,560 1,000 1,800 480 115 1,480 295 885 388 150 32 413 239 400 298 135 69 20 78 83 17,040 1,088 270 88

11

6

15 12 7

40 15 90

12 555 90

6 10 80 15 315 30 22 2 2 7

6 20 45 9

12 30 4 28 38

30 25 56 13

25 2

6 45 9 2

12

8 2

17 16

100 15 285 138 150 49 23 70 11 28 6

2

46 35 120 59 30 4 2 834 32 60 2 23 122

20 75 712 20 15 64 16 420 16 4

300 118 135 51 14

47 8 12 32 60 80

15
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued

Rock Cr. Camas Cr. Boise R. Boise R.

at at Beaver Cr. Big Lost R. Big Wood R. Silver Cr. Malad R. Bruneau R. Snake R. nr at Snake R. 

Blue Lakes Daydream Red at nr nr nr nr nr nr Twin Glenwood at 

Spring Ranch Road Spencer Chilly Bellevue Picabo Gooding Hot Spring Murphy Springs Bridge Nyssa

1996 1996 1997 1997 1996 1997 1997 1997 1997 1997 1997 1997 1997

13091000 13092747 13108900 13113000 13120500 13141000 13150430 13152500 13168500 13172500 13185000 13206000 13213100

21 22 25 26 27 28 29 30 31 32 33 35 37

MH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Insect—Continued

2 26 21 60 18 180

80 250 183 125 15 225 128 441 224 2 24 32 8 168 208

14

20 285

60 88 15 17

12 7

40 30 45 25 15

440 74 90 150 2

22 2 4 42

20 15 30 21

34 15 7

30 38

100 30 15 25 7

46 60 15 26 128 840 12

50

315 25 14 26

120 125 90 81 11 49 6

120 650 51 26 2,780 739 19 54 135 171 289 13

6 10 2 5 148 1,334 7 60 88 48 144

12
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued Rock Cr. Camas Cr. Boise R. Boise R. at at Beaver Cr. Big Lost R. Big Wood R. Silver Cr. Malad R. Bruneau R. Snake R. nr at Snake R. Blue Lakes Daydream Red at nr nr nr nr nr nr Twin Glenwood at 

Spring Ranch Road Spencer Chilly Bellevue Picabo Gooding Hot Spring Murphy Springs Bridge Nyssa

1996 1996 1997 1997 1996 1997 1997 1997 1997 1997 1997 1997 1997

13091000 13092747 13108900 13113000 13120500 13141000 13150430 13152500 13168500 13172500 13185000 13206000 13213100

21 22 25 26 27 28 29 30 31 32 33 35 37

MH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Insect—Continued

11 15 30 10 12 13

450 34 48 44 120 650 17

2,520 40 800 325 272 1,900 1,034 712 8 43 30 102 15 10 506 2,934 409 448 7,380 2,568 756 1,336

320 1,560 40 100 6 13 783 15 2 4 10 8 4 12

3 120 12 30 155 45

40 17 20

2 8

30

15

3 40 20

80 100 6 6 580 1,492 26 2

2

20 15

6

2 5 18 21

77 8

15
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued

Rock Cr. Camas Cr. Boise R. Boise R.

at at Beaver Cr. Big Lost R. Big Wood R. Silver Cr. Malad R. Bruneau R. Snake R. nr at Snake R. 

Blue Lakes Daydream Red at nr nr nr nr nr nr Twin Glenwood at 

Spring Ranch Road Spencer Chilly Bellevue Picabo Gooding Hot Spring Murphy Springs Bridge Nyssa

1996 1996 1997 1997 1996 1997 1997 1997 1997 1997 1997 1997 1997

13091000 13092747 13108900 13113000 13120500 13141000 13150430 13152500 13168500 13172500 13185000 13206000 13213100

21 22 25 26 27 28 29 30 31 32 33 35 37

MH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Insect—Continued

12 14 16

120

57 6 60 30

240 8 48 8 4

20 15 4

29 6 4 5

6 3 80 30 15 11

14

2

5

15

80 450 30 39 66 90 23 16

12

200 300 69 64 300 236 45 12 15 2 52 20 191 13

2

22

51 45 40 2 25 2 7 6

120 15 7 10

25 7

38 7 35

6

40 6 38 60 30 15 8 2 2

120 12
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued Rock Cr. Camas Cr. Boise R. Boise R. at at Beaver Cr. Big Lost R. Big Wood R. Silver Cr. Malad R. Bruneau R. Snake R. nr at Snake R. Blue Lakes Daydream Red at nr nr nr nr nr nr Twin Glenwood at 

Spring Ranch Road Spencer Chilly Bellevue Picabo Gooding Hot Spring Murphy Springs Bridge Nyssa

1996 1996 1997 1997 1996 1997 1997 1997 1997 1997 1997 1997 1997

13091000 13092747 13108900 13113000 13120500 13141000 13150430 13152500 13168500 13172500 13185000 13206000 13213100

21 22 25 26 27 28 29 30 31 32 33 35 37

MH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Insect—Continued

2

4

12 13

20 60 25

15 2 3 32

40

2 6 7 60 16 4

6 29 15 62 45 7

40

200 120 1,080 50 343 64 720 325 780 3,775 1,530 383 1,365 11 21 62 5 2 30 683 21 598 180 64 1,446 52

200 600

2

8

60

6 7

120

49

180

40 29 6 195 15 8 12 35 12 49 120 40 12

2

40 480 51 67 100 148 60 90 96 8 11 15 36 145 73 16 139 113 90 240 48 6 16

10 6

40 6 75 15 2 20 60

6 45 45 8 2

720 3,480 80 50 989 345 100 135 480 11 68 8 57 88 705 441 18 107 353 6 1,200 80 180 100

6 20 30

42 2 6
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued

Rock Cr. Camas Cr. Boise R. Boise R.

at at Beaver Cr. Big Lost R. Big Wood R. Silver Cr. Malad R. Bruneau R. Snake R. nr at Snake R. 

Blue Lakes Daydream Red at nr nr nr nr nr nr Twin Glenwood at 

Spring Ranch Road Spencer Chilly Bellevue Picabo Gooding Hot Spring Murphy Springs Bridge Nyssa

1996 1996 1997 1997 1996 1997 1997 1997 1997 1997 1997 1997 1997

13091000 13092747 13108900 13113000 13120500 13141000 13150430 13152500 13168500 13172500 13185000 13206000 13213100

21 22 25 26 27 28 29 30 31 32 33 35 37

MH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Insect—Continued

23

600400 2,880 150 11 42 800 487 165 88 390 9 2 2 226 42 240 8 6

12

4

40 6 2 4 2 49 3 8

40 2 11

28

11 60 15 4 3

45 28

60 45 45 28

120 6

280 69 41 320 600 12 3,210 229 46 2 11 4 90 100 10 11 233 55 540 48 42

520 236 50

2

2 2

20 78 12

80 120 8 20 60 6

78

6 200 8 2

120 480

200 240 29 6 60

20 68 41

10 402

80 100 40 10 195 11 8 6 18 90 12 11 530 106 54 24
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued Rock Cr. Camas Cr. Boise R. Boise R. at at Beaver Cr. Big Lost R. Big Wood R. Silver Cr. Malad R. Bruneau R. Snake R. nr at Snake R. Blue Lakes Daydream Red at nr nr nr nr nr nr Twin Glenwood at 

Spring Ranch Road Spencer Chilly Bellevue Picabo Gooding Hot Spring Murphy Springs Bridge Nyssa

1996 1996 1997 1997 1996 1997 1997 1997 1997 1997 1997 1997 1997

13091000 13092747 13108900 13113000 13120500 13141000 13150430 13152500 13168500 13172500 13185000 13206000 13213100

21 22 25 26 27 28 29 30 31 32 33 35 37

MH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Insect—Continued

20 74

15

40

15 165 4

320 2,520 40 45 60 19 2 4 20 12 50 245 78 10 12 4

6

11

6 2 10

45

35 2 120

80 45 2 100 99 6

40 40 20 1,410 45 4 13 2 55 254 6

29 10 120 89 45 2 6 4 120 32

6 360 103 555 12 240 2 8 7 28 60 16
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued

Johnson Cr. Little S. Fork

. Payette R. Weiser R. Pahsimeroi R. Salmon R. Lemhi R. at Salmon R. Lapwai Cr. Clearwater R. Palouse R. Bear R. Snake R.

nr nr at at nr Yellow at nr at nr at Idaho-Utah nr

Payette Weiser Ellis Salmon Lemhi Pine Riggins Lapwai Stites Potlatch State Line Buhl

1997 1997 1998 1998 1998 1998 1998 1998 1998 1998 1996 1997

0 13251000 13266000 13302005 13302500 13305000 13313000 13316500 13342450 13348500 13345000 10092700 13094000

41 42 44 45 46 47 48 50 51 52 53 56

H QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Noninsect

21 8 16 28 7 10 24 20 8 14 40 11 70 281 15 24 

4

5

20 375 216 720 24

15 15

300 21

56

15 30 38 30

30

12 16 24 20 24 1 10 5

14 136 8 36 45 24 220 24 300 24 44 24 80 56 120 112 30 48 15 5 262 450 8

8 10 10 60

20 8

15 80 30 5 25 5

60

15 645 88

210 16

20 15 45

40 45 5

24 24 10 260 60 56

Insect

70 20 16

30 1040 125 15

1510
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued 

Johnson Cr. Little S. Fork 

. Payette R. Weiser R. Pahsimeroi R. Salmon R. Lemhi R. at Salmon R. Lapwai Cr. Clearwater R. Palouse R. Bear R. Snake R. 

nr nr at at nr Yellow at nr at nr at Idaho-Utah nr

Payette Weiser Ellis Salmon Lemhi Pine Riggins Lapwai Stites Potlatch State Line Buhl

1997 1997 1998 1998 1998 1998 1998 1998 1998 1998 1996 1997

0 13251000 13266000 13302005 13302500 13305000 13313000 13316500 13342450 13348500 13345000 10092700 13094000

41 42 44 45 46 47 48 50 51 52 53 56

H QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Insect—Continued

7 24 5

34 84 736 156 199 390 336 120 216 20 100 128 10 120 14 27

7 4 10 15 14

8 24

7 30 30 45 10 5 330 638

07 188 384 680 790 4,800 5,424 2,400 5,328 1,700 4,008 59 230 2,060 1,376 1,550 128 1,080 130 25 27 710 525 435 232

15

14 9 130

68

69

254 10

7 7 90 96 20 2 10 5

78 12 62 8 14

27 120 144 3 19 20 40 15 14

10 56 10

14 10 58 10

14 3 43 8

7

75 240 456 100 24 47 72 1,120 1,040 8 1,365 730

38

8 50 264 8 15 5 10

15 20 40 24 2 29 50 340 824 120 53

8 15

98 64 20 30 15 192 110 576 40 48 38 384 110 96 20 64 90 43 15 32

27
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued

Johnson Cr. Little S. Fork

. Payette R. Weiser R. Pahsimeroi R. Salmon R. Lemhi R. at Salmon R. Lapwai Cr. Clearwater R. Palouse R. Bear R. Snake R.

nr nr at at nr Yellow at nr at nr at Idaho-Utah nr

Payette Weiser Ellis Salmon Lemhi Pine Riggins Lapwai Stites Potlatch State Line Buhl

1997 1997 1998 1998 1998 1998 1998 1998 1998 1998 1996 1997

0 13251000 13266000 13302005 13302500 13305000 13313000 13316500 13342450 13348500 13345000 10092700 13094000

41 42 44 45 46 47 48 50 51 52 53 56

H QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Insect—Continued

16 10 59 150

8 48 45 20 240 32 105 29 920 4,969 16

7 24 2 10

30 3

3 19

24 1 14 15 14

7

7 15 24 20 72 60 240 12 34 20 40 15 5

24 44

21 435 312 40 312 60 56 45 16

7 24 24 1 5 8 30

15 60 72

27 20 24 2 10 20 8 15

10 8 10 8

16 101

2 10

34 1 10 10 8

4

5

28 10 120 10 5 75

90 15 10

15 24

7 5

65 165 96 24 20 168 29 326 20 8

82 255 240 24 17 53 10 8

97 324 1,380 10 144 6,020 3,744 470 752 40 24 825 912 19 15 8
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued 

Johnson Cr. Little S. Fork 

. Payette R. Weiser R. Pahsimeroi R. Salmon R. Lemhi R. at Salmon R. Lapwai Cr. Clearwater R. Palouse R. Bear R. Snake R. 

nr nr at at nr Yellow at nr at nr at Idaho-Utah nr

Payette Weiser Ellis Salmon Lemhi Pine Riggins Lapwai Stites Potlatch State Line Buhl

1997 1997 1998 1998 1998 1998 1998 1998 1998 1998 1996 1997

0 13251000 13266000 13302005 13302500 13305000 13313000 13316500 13342450 13348500 13345000 10092700 13094000

41 42 44 45 46 47 48 50 51 52 53 56

H QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Insect—Continued

8 68 288 120 8 470 1,216 120 34 380 997 15 608

15 5 5

21 7 58

09 15 48 80 34 226 10 16 45

16 75 5

21 184 1,120 256 1,151 270 168 330 3,360 160 240 8 72 860 8 1,150 1,136 795 408 390 1,317 290 581 3,315 4,552

20 30 5 110 319 30

72 10 1,660 792 6 5 105 77

28 7 90 40 10 16

7 10

10

4 30 56

1 5

5

310 169 75 8

4 10

1

4 30 120 20 319

8
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued

Johnson Cr. Little S. Fork

. Payette R. Weiser R. Pahsimeroi R. Salmon R. Lemhi R. at Salmon R. Lapwai Cr. Clearwater R. Palouse R. Bear R. Snake R.

nr nr at at nr Yellow at nr at nr at Idaho-Utah nr

Payette Weiser Ellis Salmon Lemhi Pine Riggins Lapwai Stites Potlatch State Line Buhl

1997 1997 1998 1998 1998 1998 1998 1998 1998 1998 1996 1997

0 13251000 13266000 13302005 13302500 13305000 13313000 13316500 13342450 13348500 13345000 10092700 13094000

41 42 44 45 46 47 48 50 51 52 53 56

H QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Insect—Continued

10

24

21 20 24 10 24

32 8 48 180 824 38 5 101 75 75 152

5 11

4

12 15 40

1 15

7

4

1 5 10 8

4 8

1416 4 8 48 44 390 38 80

14 19 3089 16 16 89 1,365 1,584 420 504 33 120 100 32 390 568 105 34 90 336 20 19

50 64 5

5

4 8 15 5

15 30 24 2 14 40 80 24 375 86 16

30 288 10 48 120 264 8 10 20 30 16 15 67

62 4 10 24 120 120 4 5 20 16

7 4 74 2 10 8 10

16

24
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued 

Johnson Cr. Little S. Fork 

. Payette R. Weiser R. Pahsimeroi R. Salmon R. Lemhi R. at Salmon R. Lapwai Cr. Clearwater R. Palouse R. Bear R. Snake R. 

nr nr at at nr Yellow at nr at nr at Idaho-Utah nr

Payette Weiser Ellis Salmon Lemhi Pine Riggins Lapwai Stites Potlatch State Line Buhl

1997 1997 1998 1998 1998 1998 1998 1998 1998 1998 1996 1997

0 13251000 13266000 13302005 13302500 13305000 13313000 13316500 13342450 13348500 13345000 10092700 13094000

41 42 44 45 46 47 48 50 51 52 53 56

H QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Insect—Continued

21

8

10

8 8 16 5 11 16

14 24 10 24 1 14 10 16 10 75 14 5 5

10

5

7 384 512 20 30 945 2,088 1,290 216 240 2,472 3 10 16 250 15 45 11 690 38 150

7

20

20 30

2

52 176 12 7 90 408 90 168 192 40 550 48 105 48 16 210 80

21 52 184 20 15 180 120 90 216 20 240 5 34 40 40 30 40 60 72 10 53 30 112 90 16

240 585 150

12 30 450

40 60

292 384 468 37 780 384 240 600 48 2 5 160 64 380 208 75 106 230 229 50 990 32

7 10 5

8 20 10 19

14 18 38

20 130 120
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued

Johnson Cr. Little S. Fork

. Payette R. Weiser R. Pahsimeroi R. Salmon R. Lemhi R. at Salmon R. Lapwai Cr. Clearwater R. Palouse R. Bear R. Snake R.

nr nr at at nr Yellow at nr at nr at Idaho-Utah nr

Payette Weiser Ellis Salmon Lemhi Pine Riggins Lapwai Stites Potlatch State Line Buhl

1997 1997 1998 1998 1998 1998 1998 1998 1998 1998 1996 1997

0 13251000 13266000 13302005 13302500 13305000 13313000 13316500 13342450 13348500 13345000 10092700 13094000

41 42 44 45 46 47 48 50 51 52 53 56

H QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Insect—Continued

7 40 8 24 360 312 430 384 660 408 15 106 240 40 110 165 10 16 780 8

10

3 19 8

15 60

15

15

45 80 96 10 70 8 135 5 8

12 20 10 16 15

10 20 10 10

15 100

58 52 16 48 315 1,200 610 1,800 460 672 57 38 490 48 160 32 285 149 140 101 390 72

21 15 40 72 5 19

8

1212

30

15 24 96 20 8

7 30

20 19

12 36 45 150 10 40

7 544 200 384 22 15 190 1,008 20 24 40 24 10 190 244 120 16

16 58

5

30

315
tes collected from selected sampling sites in the Idaho statewide surface-water quality monitoring program, 1996–98—Continued 

Johnson Cr. Little S. Fork 

. Payette R. Weiser R. Pahsimeroi R. Salmon R. Lemhi R. at Salmon R. Lapwai Cr. Clearwater R. Palouse R. Bear R. Snake R. 

nr nr at at nr Yellow at nr at nr at Idaho-Utah nr

Payette Weiser Ellis Salmon Lemhi Pine Riggins Lapwai Stites Potlatch State Line Buhl

1997 1997 1998 1998 1998 1998 1998 1998 1998 1998 1996 1997

0 13251000 13266000 13302005 13302500 13305000 13313000 13316500 13342450 13348500 13345000 10092700 13094000

41 42 44 45 46 47 48 50 51 52 53 56

H QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH QMH RTH

Insect—Continued

15 15 29

8 12 96 10 90 48 45 5 20 150 75 30 16

45

7 2 75 5

2

24 45

12 36 60

68 75 70 40 8 10 330 32 60 5 35 5 70 30 16

12 22 15 20 2 130 48 60 10 40

60 24 40 216 20 33 43 135 130 260 131

l Edmondson, Idaho Department of Environmental Quality, written commun., 2000).

sseman, Aquatic Biology Associates, Inc., and Gary Lester, Ecoanalysts, Inc., written and oral communs., 2000).
Table B 67

Table B. Comparison of macroinvertebrate quality assurance data for selected sites in the Idaho statewide surface-water 

quality monitoring program, 1996–98

[Each sample represents a field split; No., number; USGS, U.S. Geological Survey; QMH, qualitative multiple habitat, reported in total abundance 

except for USGS laboratory; RTH, richest targeted habitat (riffles) reported in abundance (individuals per square meter); EPT, Ephemeroptera-Plecoptera-Trichoptera; P, present; NC, not calculated]

Site name and No.

Blue Lakes Spring Beaver Creek Snake River

near Twin Falls at Spencer near Minidoka

21 26 18

USGS Contract Contract Contract Contract Contract USGS Contract

Taxon lab QMH1 lab QMH lab RTH lab RTH lab RTH lab RTH lab RTH lab RTH

Noninsect

Turbellaria. . . . . . . . . . . . . . . . . . . . . . . . . . . P 320 960 1,120

Nematoda . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

Oligochaeta . . . . . . . . . . . . . . . . . . . . . . . . . . P 960 720 160 168 266

Gastropoda . . . . . . . . . . . . . . . . . . . . . . . . . . 50

Fluminicola (Gastropoda). . . . . . . . . . . . . . . P 1,640 2,160 720

Gyraulus (Gastropoda) . . . . . . . . . . . . . . . . . 80 706 338

Hydrobiidae (Gastropoda) . . . . . . . . . . . . . . P

Physella (Gastropoda). . . . . . . . . . . . . . . . . . P 120 8 30 113

Potamopyrgus antipodarum (Gastropoda) . . 12,840 9,120 6,160

Pseudosuccinea (Gastropoda). . . . . . . . . . . . P

Ostracoda . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,200 15

Pacifasticus. . . . . . . . . . . . . . . . . . . . . . . . . . 80

Acari . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,400 720 320 8

Hydrachnidia (Acari) . . . . . . . . . . . . . . . . . . 152

Aeshnidae . . . . . . . . . . . . . . . . . . . . . . . . . . . P

Amphipoda (immature). . . . . . . . . . . . . . . . . 604

Hyalella azteca (Amphipoda). . . . . . . . . . . . P 1,400 29,400 19,920 1,562 1,238

Insect

Odonata

Argia (Agrionidae) . . . . . . . . . . . . . . . . . . . . P 120 320

Coenagrionidae . . . . . . . . . . . . . . . . . . . . . . . 40

Enallagma/Ischnura (Agrionidae) . . . . . . . . 40

Ephemeroptera

Acentrella . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Attenella margarita. . . . . . . . . . . . . . . . . . . . 224 236

Baetidae (immature) . . . . . . . . . . . . . . . . . . . 160 302

Baetis tricaudatus. . . . . . . . . . . . . . . . . . . . . P 840 4,560 2,880 400 295 756 1,800

Callibaetis. . . . . . . . . . . . . . . . . . . . . . . . . . . P

Caudatella. . . . . . . . . . . . . . . . . . . . . . . . . . . 48 15

Diphetor hageni . . . . . . . . . . . . . . . . . . . . . . 80 15

Drunella grandis/spinifera . . . . . . . . . . . . . . 64 30

Ephemerella aurivillii . . . . . . . . . . . . . . . . . . 8

Ephemerella inermis/infrequens. . . . . . . . . . 80 15

Heptagenia/Nixe . . . . . . . . . . . . . . . . . . . . . . 48 59

Rhithrogena. . . . . . . . . . . . . . . . . . . . . . . . . . 8

Serratella . . . . . . . . . . . . . . . . . . . . . . . . . . . 176 118

Tricorythodes sp.. . . . . . . . . . . . . . . . . . . . . . 706

Tricorythodes minutus . . . . . . . . . . . . . . . . . 8 788

Plecoptera

Hesperoperla pacifica. . . . . . . . . . . . . . . . . . 16 30

Isoperla . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 74

Pteronarcella . . . . . . . . . . . . . . . . . . . . . . . . 80 15

Skwala. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 15

Zapada cinctipes. . . . . . . . . . . . . . . . . . . . . . 30

Hemiptera

Corixidae. . . . . . . . . . . . . . . . . . . . . . . . . . . . P

Trichoptera

Amiocentrus aspilus . . . . . . . . . . . . . . . . . . . P

Brachycentrus occidentalis. . . . . . . . . . . . . . 512 739

Glossosoma. . . . . . . . . . . . . . . . . . . . . . . . . . 24 15
68 Evaluation of Macroinvertebrate Assemblages in Idaho Rivers Using Multimetric and Multivariate Techniques, 1996–98

Table B. Comparison of macroinvertebrate quality assurance data for selected sites in the Idaho statewide surface-water 

quality monitoring program, 1996–98—Continued

Site name and No.

Blue Lakes Spring Beaver Creek Snake River

near Twin Falls at Spencer near Minidoka

21 26 18

USGS Contract Contract Contract Contract Contract USGS Contract

Taxon lab QMH1 lab QMH lab RTH lab RTH lab RTH lab RTH lab RTH lab RTH

Insect—Continued

Trichoptera–Continued

Helicopsyche borealis. . . . . . . . . . . . . . . . . . 16 44

Hydropsyche sp. . . . . . . . . . . . . . . . . . . . . . . P 2,520 3,040 656 1,034 8,214 34,538

Hydropsyche californica. . . . . . . . . . . . . . . . 5,646

Hydropsychidae (immature) . . . . . . . . . . . . . 3,578

Hydroptila. . . . . . . . . . . . . . . . . . . . . . . . . . . P 320 1,560 1,120 496 783 50

Lepidostoma-turret case larvae . . . . . . . . . . . P 40

Neotrichia . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 207

Ochrotrichia . . . . . . . . . . . . . . . . . . . . . . . . . 560 1,088 1,492

Onocosmoecus unicolor . . . . . . . . . . . . . . . . 15

Psychomyia sp. . . . . . . . . . . . . . . . . . . . . . . . 50

Rhyacophila Angelita Group. . . . . . . . . . . . . 15

Tinodes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 80

Wormaldia. . . . . . . . . . . . . . . . . . . . . . . . . . . 16 30

Lepidoptera

Petrophila . . . . . . . . . . . . . . . . . . . . . . . . . . . 240 320 112

Coleoptera

Dytiscidae . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Cleptelmis (Elmidae) . . . . . . . . . . . . . . . . . . P 80 24 15

Optioservus (Elmidae) . . . . . . . . . . . . . . . . . 232 236

Zaitzevia (Elmidae). . . . . . . . . . . . . . . . . . . . 24

Hydrophilidae . . . . . . . . . . . . . . . . . . . . . . . . 8

Diptera

Alotanypus . . . . . . . . . . . . . . . . . . . . . . . . . . P

Caloparyphus sp. (Stratiomyidae) . . . . . . . . P

Ceratopogoninae . . . . . . . . . . . . . . . . . . . . . . 40 16 30

Empididae . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 15

Ephydridae . . . . . . . . . . . . . . . . . . . . . . . . . . 40

Simuliidae . . . . . . . . . . . . . . . . . . . . . . . . . . . P 200 120 240 184 325 606 281

Stratiomyidae . . . . . . . . . . . . . . . . . . . . . . . . P 200 600 160

Antocha . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 80 15

Dicranota . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Limonia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . P 40

Chironomidae

Chironomidae-pupae. . . . . . . . . . . . . . . . . . . 40 480 320 72 148 50 56

Cricotopus. . . . . . . . . . . . . . . . . . . . . . . . . . . P 720 3,480 2,480 8 302

Cricotopus (Nostococladius) . . . . . . . . . . . . 32

Dicrotendipes . . . . . . . . . . . . . . . . . . . . . . . . P 600

Eukiefferiella. . . . . . . . . . . . . . . . . . . . . . . . . P 400 2,880 2,320 464 487

Micropsectra. . . . . . . . . . . . . . . . . . . . . . . . . 8

Microtendipes . . . . . . . . . . . . . . . . . . . . . . . . 40

Nanocladius . . . . . . . . . . . . . . . . . . . . . . . . . 16 15

Orthocladiinae. . . . . . . . . . . . . . . . . . . . . . . . P 120 50

Orthocladius Complex . . . . . . . . . . . . . . . . . P 280 160

Pagastia . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168 236

Parachironomus . . . . . . . . . . . . . . . . . . . . . . 50

Parakiefferiella . . . . . . . . . . . . . . . . . . . . . . . 80 120

Parametriocnemus . . . . . . . . . . . . . . . . . . . . 8

Paraphaenocladius. . . . . . . . . . . . . . . . . . . . 120 80

Paratanytarsus . . . . . . . . . . . . . . . . . . . . . . . P 200 240 160 50

Polypedilum . . . . . . . . . . . . . . . . . . . . . . . . . 80

Potthastia Longimana Group . . . . . . . . . . . . 8 74

Pseudochironomus . . . . . . . . . . . . . . . . . . . . 40

Rheocricotopus . . . . . . . . . . . . . . . . . . . . . . . 720 15
Table B 69

Table B. Comparison of macroinvertebrate quality assurance data for selected sites in the Idaho statewide surface-water 

quality monitoring program, 1996–98—Continued

Site name and No.

Blue Lakes Spring Beaver Creek Snake River

near Twin Falls at Spencer near Minidoka

21 26 18

USGS Contract Contract Contract Contract Contract USGS Contract

Taxon lab QMH1 lab QMH lab RTH lab RTH lab RTH lab RTH lab RTH lab RTH

Insect–Continued

Chironomidae–Continued

Rheotanytarsus . . . . . . . . . . . . . . . . . . . . . . . P 320 2,520

Thienemanniella . . . . . . . . . . . . . . . . . . . . . . P 40

Thienemannimyia Group. . . . . . . . . . . . . . . . 72 89

Tvetenia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 103

Total individuals per square meter . . . . . . NC NC 63,000 43,680 5,728 7,450 23,484 39,264

Total number of taxa. . . . . . . . . . . . . . . . . 30 32 23 26 46 41 19 9

EPT taxa . . . . . . . . . . . . . . . . . . . . . . . . . . 6 4 4 5 23 24 8 3

Invertebrate river index score . . . . . . . . . . NC NC 11 11 21 21 11 5 1Presence only.
Maret, T.M., and others / Evaluation of Macroinvertebrate Assemblages in Idaho Rivers 

Using Multimetric and Multivariate Techniques, 1996–98 / WRIR 01– 4145

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