Prepared in cooperation with the Indiana Department of Environmental Management, 

Division of Water, Assessment Branch 

Breakpoint Analysis and Assessment of Selected 

Stressor Variables on Benthic Macroinvertebrate and 

Fish Communities in Indiana Streams: Implications for 

Developing Nutrient Criteria 

U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2010–5026 

Breakpoint Analysis and Assessment of 

Selected Stressor Variables on Benthic 

Macroinvertebrate and Fish Communities in 

Indiana Streams: Implications for Developing 

Nutrient Criteria 

By Brian J. Caskey, Jeffrey W. Frey, and Shivi Selvaratnam 

Prepared in cooperation with the Indiana Department of Environmental 

Management, Division of Water, Assessment Branch 

Scientific Investigations Report 2010–5026 

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2010

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Although this report is in the public domain, permission must be secured from the individual copyright owners to 

reproduce any copyrighted materials contained within this report.

Suggested citation:

Caskey, B.J., Frey, J.W., and Selvaratnam, Shivi, 2010, Breakpoint analysis and assessment of selected stressor 

variables on benthic macroinvertebrate and fish communities in Indiana streams—Implications for developing nutrient criteria: U.S. Geological Survey Scientific Investigations Report 2010–5026, 35 p., plus CD-Rom containing eight 

appendixes. 
iii

Contents

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

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

Purpose and Scope ..............................................................................................................................3

Description of Study Area ...................................................................................................................3

Study Methods ...............................................................................................................................................5

Site Selection and Sampling Strategies ...........................................................................................5

Data Collection and Processing Methods........................................................................................5

Collection of Biological Communities.......................................................................................5

Calculation of Biological-Community Attributes and Metrics..............................................5

Collection of Nutrients and Water-Quality Samples..............................................................6

Collection of Periphyton and Seston Chlorophyll a Samples ...............................................6

Physical Habitat ...........................................................................................................................7

Basin Characteristics..................................................................................................................7

Data Analysis.........................................................................................................................................7

Improvement of the Relations among the Stressor and Response Variables ...................7

Identification of Significant Relations among Variables and Determination of 

Breakpoints .....................................................................................................................8

Assessment of the Stressor Variables and the Biological Communities .............................................9

Influence of Basin Size on the Biological-Community Composition ............................................9

Biological-Community Composition within the Sampled Basins..................................................9

Distribution of the Stressor Variables .............................................................................................10

Relations between the Stressor Variables .....................................................................................10

Comparison of Trophic Classification for the Stressor Variables...............................................12

Biological Breakpoints of the Stressor Variables and Implications for Developing 

Nutrient Criteria..............................................................................................................................15

Summary........................................................................................................................................................21

References Cited..........................................................................................................................................22

Appendix 1. List of invertebrate community attributes and metrics calculated 

for the breakpoint analysis study, 2001–05 ................................................... on CD-Rom

Appendix 2. List of fish community attributes and metrics calculated for the 

breakpoint analysis study, 2001–05................................................................ on CD-Rom

Appendix 3. Species list and percent relative abundance of invertebrates 

collected at 74 sites for the breakpoint analysis study, 2001–05 .............. on CD-Rom

Appendix 4. Invertebrate community attributes and metrics calculated for 

the breakpoint analysis study, 2001–05 ......................................................... on CD-Rom

Appendix 5. Species list and percent relative abundance of fish collected at 

215 sites for the breakpoint analysis study, 2001–05................................... on CD-Rom
iv

Figures

1. Map showing the location of the Indiana Department of Environmental 

Management Watershed Monitoring Program sampling sites used in the 

breakpoint analysis study, 2001–05............................................................................................4

2–6. Graphs showing:

2. Distribution of the mean total nitrogen log transformation of concentrations 

compared to trophic classifications in the three selected datasets used 

in the breakpoint analysis study, 2001–05......................................................................12

3. Distribution of the mean total phosphorus log transformation of 

concentrations compared to trophic classifications in the three selected 

datasets used in the breakpoint analysis study, 2001–05 ...........................................13

4. Distribution of the mean periphyton chlorophyll a log transformation of 

concentrations compared to trophic classifications in the three selected 

datasets used in breakpoint analysis study, 2001–05..................................................13

5. Distribution of the mean seston chlorophyll a log transformation of 

concentrations compared to trophic classifications in the three selected 

datasets used in the breakpoint analysis study, 2001–05 ...........................................14

6. Distribution of the mean turbidity log transformation of concentrations 

compared with turbidity biological impact classifications in the three 

selected datasets used in the breakpoint analysis study, 2001–05...........................14

7–11. Scatter plots showing:

7. Mean total nitrogen concentrations to the percentage of biomass 

composed of white suckers at headwater fish sites for the breakpoint 

analysis study, 2001–05.....................................................................................................16

8. Mean total phosphorus concentrations to the percentage of biomass 

composed of striped shiners at headwater fish sites for the breakpoint 

analysis study, 2001–05.....................................................................................................17

9. Mean periphyton chlorophyll a concentrations to the percentage of 

total richness composed of shredders at invertebrate sites for the 

breakpoint analysis study, 2001–05.................................................................................18

10. Mean seston chlorophyll a concentrations to bluegill biomass at 

headwater fish sites for the breakpoint analysis study, 2001–05 ..............................19

11. Mean turbidity concentrations to the percentage of biomass composed 

of spotted suckers at wadable fish sites for the breakpoint analysis study, 

2001–05 ................................................................................................................................20

Appendix 6. Biomass (grams) of fish collected at 215 sites for the breakpoint 

analysis study, 2001–05 .................................................................................... on CD-Rom

Appendix 7. Fish community details used for calculating fish community 

attributes and metrics in the breakpoint analysis study, 2001–05 ............ on CD-Rom

Appendix 8. Fish community attributes and metrics calculated for the 

breakpoint analysis study, 2001–05................................................................ on CD-Rom
v

Multiply By To obtain

Length

meter (m) 3.281 foot (ft) 

millimeter (mm) 0.03937 inch (in.)

micrometer (μm) 0.001 millimeter (mm)

kilometer (km) 0.6214 mile (mi)

Area

square meter (m2) 10.76 square foot (ft2) 

square kilometer (km2) 247.1 acre

square kilometer (km2) 0.3861 square mile (mi2)

Volume

milliliter (mL) 0.03381 ounce, U.S. liquid (oz)

Mass

gram (g) 0.03527 ounce, avoirdupois (oz)

kilogram (kg) 2.205 pound, avoirdupois (lb)

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

°F=(1.8×°C)+32 

Concentrations of nutrients and seston chlorophyll a in water are given in milligrams per liter 

(mg/L), concentrations of periphyton chlorophyll a are given in milligrams per square meter 

(mg/m2), and concentrations of turbidity are given in Nephelometric turbidity units (NTU). 

Conversion Factors and Abbreviations/Acronyms 

Tables

1. Location of Indiana Department of Environmental Management Watershed 

Monitoring Program sampling sites used in the breakpoint analysis study, 

2001–05 .........................................................................................................................................26

2. Summary statistics for stressor variables used in the breakpoint analysis study, 

2001–05 .........................................................................................................................................11

3. Spearman rho correlations among the stressor variables used in the breakpoint 

analysis study, 2001–05..............................................................................................................11

4. Breakpoint summary for the stressor variables used in the breakpoint analysis 

study, 2001–05..............................................................................................................................15 
vi

Acknowledgments 

The authors could not mention everyone who contributed to this 5-year 

study; however, the authors specifically thank the Indiana Department 

of Environmental Management (IDEM) and the U.S. Geological Survey 

(USGS) scientists for their commitment to collecting and processing 

the data. We also would like to specifically thank Steven A. Newhouse, 

Charles C. Morris, and Kristen M. Arnold of IDEM for their help in 

analytical design and technical review of the report; Robert J. Miltner of the 

Ohio Environmental Protection Agency; David L. Lorenz and Timothy C. 

Willoughby (USGS) for statistical and technical assistance; David C. 

Voelker (USGS) for editorial reviews; and Angela S. Crain and Thomas F. 

Cuffney (USGS) for technical reviews.

Abbreviations and acronyms used in this report

CHIR Chironomidae

CHLa chlorophyll a

CWA Clean Water Act

DELT deformity

EPT Ephemeroptera, Plecoptera, and Trichoptera

GIS Geographic Information System

HBI Hilsenhoff’s Biotic Index

IDEM Indiana Department of Environmental Management

MDS Multiple-dimensional scaling

MIBI Macroinvertebrate Index of Biotic Integrity

N nitrogen

NAWQA National Water-Quality Assessment Program

NTU Nephelometric turbidity units

NWQL National Water Quality Laboratory

P phosphorus

PCT percentage

QHEI Qualitative Habitat Evaluation Index

r2 coefficient of determination

rs Spearman’s rho statistics

TKN Total Kjeldahl nitrogen

TN total nitrogen

TP total phosphorus

USEPA U.S. Environmental Protection Agency

USGS U.S. Geological Survey

WMP Watershed Monitoring Program 
Breakpoint Analysis and Assessment of Selected 

Stressor Variables on Benthic Macroinvertebrate and 

Fish Communities in Indiana Streams: Implications for 

Developing Nutrient Criteria 

By Brian J. Caskey,1 Jeffrey W. Frey,1 and Shivi Selvaratnam2

Abstract

Water chemistry, periphyton and seston chlorophyll a

(CHLa), and biological community data were collected from 

321 sites from 2001 through 2005 to (1) determine statistically 

and ecologically significant relations among the stressor (total 

nitrogen, total phosphorus, periphyton and seston CHLa, and 

turbidity) variables and response (biological community) variables; and, (2) determine the breakpoint of biological community attributes and metrics in response to changes in stressor 

variables. Because of the typically weak relations among the 

stressor and response variables, methods were developed to 

reduce the effects of non-nutrient biological stressors that 

could mask the effect of nutrients. Stressor variable concentrations ranged from 0.30 to 11.0 milligrams per liter (mg/L) for 

total nitrogen, 0.025 to 1.33 mg/L for total phosphorus, 2.9 

to 768 milligrams per square meter (mg/m2)for periphyton 

CHLa, and 0.37 to 42 micrograms per liter (μg/L) for seston CHLa. Turbidity, another stressor variable, ranged from 

0.8 to 65.4 Nephelometric turbidity units (NTUs). When the 

nutrient and CHLa data were compared to Dodds’ trophic 

classifications, 75.0 percent of the values for total nitrogen, 

46.6 percent of the values for total phosphorus, 35.8 percent 

of the values for periphyton CHLa, and 3.5 percent of the 

values for seston CHLa, were eutrophic. The invertebrate 

communities were dominated by families considered highly 

nutrient tolerant, Chironimidae, (41.7 percent relative abundance), Hydropsychidae, (17.3 percent relative abundance), 

and Baetidae, (10.2 percent relative abundance). Fish communities were dominated by algivores and nutrient-tolerant 

species, specifically central stonerollers (13.3 percent relative 

abundance), creek chubs (9.9 percent relative abundance), and 

bluntnose minnows (9.3 percent relative abundance). Although 

not the dominant taxa, white sucker, spotted sucker, green 

sunfish, and bluegill species were correlated (p < 0.05) with 

the stressor variables. The median breakpoints ranged from 

2.4 to 3.3 mg/L for total nitrogen, from 0.042 to 0.129 mg/L 

for total phosphorus, from 54 to 68 mg/m2 for periphyton 

CHLa, from 4.5 to 7.5 μg/L for seston CHLa, and from 14.1 

to 16.1 NTU for turbidity. The breakpoints determined in 

this study, in addition to Dodds’ trophic classifications, were 

used as multiple lines of evidence to show changes in fish and 

invertebrate community and attributes based on annual exposure to nutrients. 

Introduction 

Although nutrients are essential to the development, 

health, and diversity of plants and animals in surface waters, 

excessive inputs of nutrients into streams have potential 

human-health, economic, and ecological consequences. Excess 

amounts of nitrogen (N) and phosphorus (P) have been shown 

to cause eutrophication in aquatic ecosystems, and this sometimes has been linked to fish kills, shifts in species composition, taste and odor in drinking-water, and blooms of harmful 

algae in freshwater and estuaries (Munn and Hamilton, 2003; 

U.S. Environmental Protection Agency, 2000a, b, c). 

The Clean Water Act (CWA), as amended in 1976, 

established a national goal of achieving water quality that 

provides for the protection and propagation of aquatic organisms, wildlife, and recreation in and on the water. In 1996, the 

U.S. Environmental Protection Agency’s (USEPA) National 

Water Quality Inventory identified excess amounts of nutrients as the second leading cause of impairment in rivers and 

streams and as the primary cause of impairments in lakes and 

reservoirs (U.S. Environmental Protection Agency, 1997). The 

excess amounts of nutrients that have been documented in 

many rivers and streams have resulted in streams that do not 

meet the goal of the CWA in Indiana and the Nation.

________________

1

USGS Indiana Water Science Center, Indianapolis, Indiana. 

2

Indiana Department of Environmental Management, Office of Water 

Quality, Assessment Branch. 
2 Analysis and Assessment of Selected Variables on Macroinvertebrate and Fish Communities in Indiana Streams

The USEPA drinking-water criteria (maximum contaminant levels) are 10 mg/L for nitrate as N and 1 mg/L for nitrite 

as N (U.S. Environmental Protection Agency, 2005), to protect 

human health. The nitrate criteria were set mainly to protect 

against methemoglobinemia or “blue baby syndrome.” However, other studies have linked excessive nitrate and nitrite 

levels to adverse reproductive and developmental outcomes in 

animals and humans (Manassaram and others, 2006). In addition, aquatic-life criteria for the protection of aquatic organisms have been developed for ammonia as N. These criteria 

vary with pH, temperature, and life-stage (U.S. Environmental 

Protection Agency, 2005). Current criteria do not address 

the effects of increased nutrients in rivers and streams on the 

biological communities. Typically, nutrient concentrations 

must be extremely high to be toxic to biological communities; 

such concentrations rarely are found in the environment (Ohio 

Environmental Protection Agency, 1999). Exceptions are 

concentrations of ammonia associated with accidental discharges from wastewater-treatment facilities, combined-sewer 

overflows, or concentrated-animal feeding operations (Ohio 

Environmental Protection Agency, 1999). 

Many streams within Indiana, as well as the United 

States, have been placed by the USEPA on the CWA Section 303(d) list of impaired water bodies because of excess 

nutrients (Indiana Department of Environmental Management, 2009). To address these impairments, the USEPA in 

2000 developed nutrient criteria for the causal nutrients total 

nitrogen (TN) and total phosphorus (TP) and for the response 

variables periphyton and seston chlorophyll a (CHLa), and 

turbidity. These criteria are based on USEPA Aggregate Nutrient Ecoregions, which are areas with similar geographic features such as topography, soils, geology, land use, and biogeography (U.S. Environmental Protection Agency, 2000a, b, c). 

The USEPA reviewed selected data and utilized the frequency 

distribution approach to develop criteria for nitrate as N, total 

Kjeldahl nitrogen as N (TKN), TN, TP, CHLa (periphyton 

and seston), and turbidity based on the 25th percentile value 

for all data or the 75th percentile from reference sites for 

each causal variable. However, few of the available data from 

Indiana were included in the criteria development (Dennis 

Clark, Indiana Department of Environmental Management, 

oral commun., 2008; U.S. Environmental Protection Agency, 

2000a, b, c) or, as was the case for CHLa, little or no data 

existed for many of the ecoregions, including those in Indiana 

(U.S. Environmental Protection Agency, 2000a, b, c). Therefore, the proposed nutrient, CHLa, and turbidity criteria may 

not accurately reflect existing local conditions.

In a typical stressor-response relation, a change in a 

stressor (causal) variable (TN and TP, in the case of nutrients) 

results in a corresponding change in a response variable. 

Several studies found significant relations between nutrients 

and periphyton CHLa for temperate streams (Van Nieuwenhuyse and Jones, 1996; Dodds and others, 1997). Robertson and others (2006) found significant relations between 

nutrients (nitrate, TN, dissolved P, and TP) and periphyton 

CHLa in Wisconsin. Biggs (2000) listed several studies that 

found significant relations between nutrients and periphyton 

CHLa, primarily in studies that analyzed a small number of 

streams. When a large number of streams were analyzed using 

a national dataset, Dodds and others (1997) found few and 

very weak significant relations between nutrients and algal 

biomass. In previous studies of nutrient-rich streams in Illinois 

(Figueroa-Nieves and others, 2006; Royer and others, 2008) 

and in Indiana (Frey and others, 2007; Caskey and others, 

2007; Leer and others, 2007; Lowe and others, 2008), there 

were limited weak or no significant relations between nutrients 

and periphyton or seston CHLa variables. Algal biomass can 

be influenced by several natural factors that could account for 

a lack of significant relations with nutrients. Scouring of algal 

growth by increased streamflow can cause algal growth to 

restart in the stream (Biggs and others, 1999), and annual and 

seasonal differences in storm events can allow for “wet” and 

“dry” years with high levels of algal biomass corresponding to 

both high and low concentrations of nutrients, depending upon 

the season or year or both. Biggs (2000) found the strongest 

nutrient and algal biomass relations when a streamflow variable was incorporated into the analysis. Other factors affecting 

algal growth include shading from canopy cover, turbidity 

(Wehr, 2003), and grazing by snails, invertebrates, and fish 

(Lamberti and others, 1987). 

Nutrients at concentrations found typically in streams 

are nontoxic to biological organisms (Miltner and Rankin, 

1998), which indicates that the typical stressor-response relations found in toxicological based approaches would not be 

appropriate. Previous nutrient and algal biomass studies have 

shown mixed results because linear techniques are applied 

to nonlinear data. Instead, nonlinear techniques (that is, 

breakpoint analysis) may be better at discerning the relations 

between nontoxic stressor and response variables and identifying breakpoints (Qian and others, 2003). In small rivers and 

streams in Ohio, Miltner (2010) observed clear associations 

between nutrients, secondary response indicators, and biological communities by utilizing these techniques. Development of 

defensible nutrient criteria for rivers and streams in nutrientrich areas will be complex and require intensive data analysis.

Indiana is part of the nutrient-rich Midwest that leads 

the nation in corn and soybean production. Production of 

these crops requires the use of significant amounts of nutrients—primarily from fertilizer and manure additions—which 

has increased dramatically since the 1940s (Goolsby and 

Battaglin, 2000). Mueller and Spahr (2006) noted that streams 

sampled within the Midwest have some of the highest nutrient 

loading in the United States. A model of the Mississippi River 

Basin found that Indiana, Illinois, and Ohio were leading 

contributors of N and P to the Gulf of Mexico, resulting in 

hypoxia of those waters (Alexander and others, 2008). 

Given that Indiana is in a nutrient-rich area with observed 

weak relations between nutrients and algal biomass, other 

indicators such as biological species, community attributes 

and metrics, could be helpful in developing nutrient criteria 
Introduction 3

for streams and rivers in such regions (Lowe and others, 

2008). Aquatic organisms and related community composition and attributes are frequently used in ecological analysis 

of communities because of the response of these organisms to 

anthropogenic inputs and other variables (Karr, 1981; Wang 

and others, 1997; Brightbill and Bilger, 1998; Carpenter and 

Waite, 2000; Caskey, 2003). For example, several recent studies used biological organisms and attributes to assess nutrients 

in streams by using a causal and response approach (Petersen 

and Femmer, 2002; Heatherly and others, 2007; Mabe, 2007; 

Wang and others, 2007; Weigel and Robertson, 2007). In 

water-quality studies, the covariation of physical and chemical 

variables can conceal the stressor-response relations. Because 

of the multiple and complex interactions between nutrients, 

algal biomass, and biological communities, almost all relations 

tend to be weak. One method that improves the strength of 

these relations is to remove anthropogenic and natural variations that conceal the nutrient, algal biomass, and biological 

community relations. By removing covariable stressors, such 

as basin size or ecoregion, the number and strength of statistically significant stressor-response relations increase (Miltner 

and Rankin, 1998; Frey and Caskey, 2007; Frey and others, 

2007; Caskey and others, 2007; Leer and others, 2007). In this 

study, this resulted in more statistically significant stressorresponse relations, leading to more breakpoint analyses. However, in a study conducted in Indiana and Ohio that accounted 

for variability of stream size, ecoregion, substrate, and canopy 

cover along a nutrient gradient, the biological communities 

reflected eutrophic conditions along the entire nutrient gradient, indicating that parts of the Midwest may be so nutrient 

rich that finding significant relations between nutrients, algal 

biomass, and biological communities may be difficult (Caskey 

and Frey, 2009).

The USEPA mandated that by 2004, states either adopt 

USEPA’s nutrient criteria or develop criteria that are more 

appropriate to waters within each state (U.S. Environmental 

Protection Agency, 2000a, b, c). An extension was given to 

Indiana and other states that adopted plans describing the data 

needs, processes, and the approaches that would be considered 

in developing nutrient water-quality criteria. Beginning in 

2001, the Indiana Department of Environmental Management 

(IDEM) and the U.S. Geological Survey (USGS) collaborated 

on several studies that will provide the technical background 

to assist in the development of nutrient criteria for surface 

waters for the State of Indiana. The results presented in this 

report are representative of similar nutrient-rich ecoregions in 

the Midwest.

Purpose and Scope

This is the final report in a series of six reports that previously presented the occurrence and distribution of, and relations among, total nitrogen as N, total phosphorus as P, periphyton and seston CHLa, turbidity, and biological community 

attributes and metrics in Indiana streams. The study has been 

a cooperative project between the Assessment Branch of the 

Office of Water at the IDEM and the USGS. In this report, 

stressor variables (TN, TP, periphyton and seston CHLa, 

turbidity) are related to biological response variables (benthic 

macroinvertebrate-, and fish-species, and community attributes 

and metrics) to determine statistically significant relations. To 

improve the strength of the relations, sites with water-quality 

standard violations for metals and other select variables were 

removed, leaving 74 sites with invertebrate community data 

and 232 sites with fish community data. Breakpoint analysis 

was used to detect the concentration of the stressor variables 

where there was a significant change in the response variables. 

Results of the breakpoint analysis will provide IDEM with 

relevant information that could be useful in the development 

of nutrient criteria using multiple lines of evidence, such as the 

incorporation of nutrient concentrations that show a specific 

biological response. 

Description of Study Area

With approximately 6.1 million citizens (U.S. Census Bureau, 2000), the State of Indiana is comprised of 

94,617 km2 (Clark, 1980). The climate within Indiana is characterized as humid continental with well defined winter and 

summer seasons. Temperature and precipitation amounts vary 

between northern and southern Indiana. The mean monthly 

temperature in northern Indiana ranges from -5.17oC in winter 

to 22.8oC in summer. In southern Indiana, temperatures ranges 

from -1.29oC in winter to 24.5oC in summer (Purdue Applied 

Meteorology Group, 2008). The mean annual precipitation 

in Indiana ranges from 94.5 cm in the north to 119 cm in the 

south (Purdue Applied Meteorology Group, 2008). Samples 

were collected from all major river basins within Indiana, 

except the Patoka River Basin (fig. 1, table 1 at back of 

report).

Basin characteristics were determined for each of the 

sampling sites in the 5-year study. Typical of Midwestern 

states, the landscape in the study basins is relatively flat; the 

land is used mainly for the production of agricultural row 

crops, primarily corn and soybeans. Many agricultural fields 

use subterranean tiles to improve drainage, and a majority of 

the agriculturally influenced streams in the study area can be 

characterized as having low relief and velocities. All of the 

major river basins in which samples were collected during the 

study were predominantly agricultural; agricultural land use 

comprised 77 percent of all major basins in the study area. 

Within the study area, 16 percent of the land use was classified 

as forest and 4 percent was classified as urban. Other land uses 

including mining and wetlands constituted 3 percent of the 

study area (Lowe and others, 2008).
4 Analysis and Assessment of Selected Variables on Macroinvertebrate and Fish Communities in Indiana Streams

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87°0'0"W 85°30'0"W

40°30'0"N

39°0'0"N

0 25 50 MILES

0 25 50 KILOMETERS

Invertebrate site

Headwater site

Wadable site

Boat site

Site identifier

EXPLANATION

Figure 1. Location of the Indiana Department of Environmental Management Watershed Monitoring 

Program sampling sites used in the breakpoint analysis study, 2001–05. 
Study Methods 5

The percentage of land use by classification varied among 

the major river basins, although agriculture was the dominant 

land use in all basins. The Upper Wabash River Basin had the 

most agricultural land use (92 percent) while the West Fork 

White River Basin, Whitewater River Basin, Kankakee River 

Basin, Lower Wabash River Basin, and Great Lakes Tributaries were heavily agricultural (averaging 82 percent). The East 

Fork White River Basin and the Ohio River Tributaries were 

less agricultural (71 percent and 52 percent, respectively), 

and had a higher percentage of forested areas than the other 

basins. Urbanization was most apparent within the West Fork 

White River Basin, where 8 percent of the land use was urban 

and includes the cities of Indianapolis, Muncie, and Anderson. 

Other land-use influences within the Kankakee River Basin 

and Great Lakes Tributaries were largely attributed to natural 

marshes and wetlands that are typical of the lowland, poorly 

drained areas of northern Indiana (Lowe and others, 2008). 

Study Methods 

This study used field and analytical methods from the 

IDEM and the USGS. The following sections describe the site 

selection and sampling strategies; field and laboratory methods used in collecting and processing biological community, 

nutrient, algal biomass, and basin characteristics; and the 

approaches used in data analysis.

Site Selection and Sampling Strategies

Sampling sites were selected randomly by the USEPA as 

part of the IDEM probabilistic Watershed Monitoring Program 

(WMP) (Indiana Department of Environmental Management, 

1999, 2001). Each selected sampling site represents a specific 

stream order; therefore, statistically valid extrapolations can be 

made from the randomly sampled streams to streams not sampled in a particular basin (Indiana Department of Environmental Management, 1999, 2001). The IDEM WMP works on a 

5-year rotating basin schedule, focusing on one or two selected 

basins each year, with a complete assessment of the state at 

the end of each 5-year cycle. In 2001, the focus was the West 

Fork White River Basin; in 2002, the Whitewater River and 

East Fork White River Basins; 2003, the Upper Wabash River 

Basin; 2004, the Kankakee and Lower Wabash River Basins; 

and in 2005, the Great Lakes and Ohio River Basins. The 

Patoka River Basin was not included in this study because 

the initial proposal in 2001 called for method development in 

the West Fork White River Basin only. Prior to collection of 

field data, IDEM personnel completed a visual assessment of 

selected sampling sites and determined the stream reach. At 

each site, the latitude and longitude provided by USEPA was 

used as the center point of the sampling reach, so that half of 

the reach was upstream and half of the reach was downstream 

of the midpoint. The reach length was determined by measuring the wetted channel width at the center point, and then the 

width was multiplied by 15. 

During periods of stable low flow, a total of 321 sites 

were sampled from May through October 2001–2005 (Lowe 

and others, 2008). Within each major basin, 34 to 45 sites 

were sampled for nutrients and CHLa. The samples were 

collected multiple times in each basin to measure seasonal 

changes in nutrients and CHLa, with the exception of the West 

Fork White River Basin, which was sampled only two times 

during 2001 (rounds 2 and 3). Round 1 samples were collected 

in May and June, round 2 samples were collected in July and 

August, and round 3 samples were collected in September and 

October. At each site, the nutrient and CHLa samples were 

collected on the same day at about the same time. 

Data Collection and Processing Methods

The following sections describe the field and laboratory 

methods used in collecting and processing samples of biological communities, nutrients, water-quality characteristics, and 

algal biomass, and in the determination of habitat and basin 

characteristics. 

Collection of Biological Communities

Invertebrate and fish-community assessments followed 

IDEM methods (Indiana Department of Environmental Management, 1992, 1999). Invertebrates were collected from riffle 

habitats and identified to the family level; whereas, fish were 

collected within the entire reach and identified to the species 

level. Biological communities (invertebrate and fish) were 

assessed one time from midsummer to early fall (June through 

October) as part of the WMP. Approximately 10 percent of 

the sites were sampled a second time during the same year as 

part of the quality-assurance plan. After the assessments were 

completed, IDEM personnel calculated 20 invertebrate and 

43 fish community attributes and metric scores (Simon, 1999; 

Dufour, 2002, Goldstein and Simon, 1999). In addition, USGS 

personnel calculated 89 invertebrate and 651 fish community 

attributes thought to be of interest or previously published 

in the literature. The community attributes and metric scores 

describing the invertebrate- and fish-community data are listed 

in appendixes 1 and 2.

Calculation of Biological-Community Attributes 

and Metrics

Invertebrate community attributes and metrics were calculated using USGS software, the Invertebrate Data Analysis 

System (IDAS) v 4.2.0.10 (Cuffney, 2003). Only 89 attributes 

and metrics could be calculated using the IDAS software 

because the invertebrate samples used in this analysis were 
6 Analysis and Assessment of Selected Variables on Macroinvertebrate and Fish Communities in Indiana Streams

identified to the family level. The standard IDEM invertebrate 

metrics were also included, resulting in a list of 109 invertebrate response variables. The percentage of relative abundance 

was calculated for each invertebrate family that was represented in each sample. The final invertebrate attributes, metrics, counts, and percentage of relative abundance were used 

as response variables in the invertebrate breakpoint analysis.

Attributes found in an extensive literature review were 

used to calculate 651 fish community attributes. These attributes were based on individual counts, percentage of individual counts, species counts, percentage of species counts, 

biomass, and percentage of biomass. In addition, 43 attributes 

and metrics calculated by IDEM were included as response 

variables, resulting in a final list of 694 fish attributes and 

metrics. As with the invertebrate community, the fish community percentage of relative abundance was determined for each 

species that was represented with each sample. 

Collection of Nutrients and Water-Quality 

Samples

Nutrient (TN and TP) and water-chemistry samples were 

collected using a grab method by IDEM and USGS personnel following approved IDEM sample collection (Beckman, 

2000) and quality-assurance methods (Bowren and Ghiasuddin, 1999). After collection, samples analyzed for general 

chemistry were placed directly on wet ice, samples analyzed 

for nutrients were preserved with 2 mL sulfuric acid (H2SO4), 

samples analyzed for metals were preserved with 5 mL of concentrated nitric acid (HNO3

), and samples analyzed for cyanide were preserved with sodium hydroxide (NaOH). Samples 

were then analyzed by independent laboratories (Test America, 

Indianapolis; Heritage Environmental, Indianapolis; or Underwriters Laboratories, South Bend). The independent laboratories used USEPA test method 353.2 for nitrate plus nitrite 

analysis by copper-cadmium reduction; USEPA test methods 

351.2 and 351.4 for Kjeldahl analysis by persulfate digestion 

and colorimetry; and USEPA test methods 365.1, 365.2, and 

SM4500P–E for total phosphorus by persulfate digestion and 

colorimetry. For the analysis in this report, total nitrogen is the 

sum of nitrate plus nitrite as nitrogen and Kjeldahl as nitrogen.

Collection of Periphyton and Seston 

Chlorophyll a Samples 

Samples were collected and processed to estimate algal 

biomass, based on periphyton and seston CHLa concentrations. CHLa is a measure of the pigment found in algal cells 

that are attached to a substrate (periphyton) or floating in the 

water column (seston). The term “seston” is used instead of 

“phytoplankton,” because periphytic algae scoured from substrate can be included in the seston-algal samples. 

Samples were collected and processed using modified 

USGS protocols. The National Water-Quality Assessment 

(NAWQA) Program algal protocols for periphyton (Moulton 

and others, 2002; U.S. Geological Survey, variously dated) 

collect five periphyton subsamples from five different locations within the sampling reach. At each location, the stream 

depth, velocity, shading, and substrate are recorded. The 

samples are composited and marked as a single sample. 

Periphyton samples were collected from the same substrate 

type—epilithic (rocks), epidendric (sticks), or epipsammic 

(sand), at each site during the sampling period, when possible. 

If available, epilithic substrates were the priority substrate 

for periphyton collection in smaller streams with less than 

2,590 km2 drainage area. The primary means of periphyton 

sampling during 2001 through 2003 was the top-rock scrape, 

which consisted of scraping the algae from the rock surface 

and determining the area with a foil template (Moulton and 

others, 2002). During 2004 and 2005, epilithic substrate was 

sampled using a SG-92 modified syringe sampling device or 

by completing an area scrape using the SG-92 to determine the 

sampled area (Moulton and others, 2002). One modification to 

this study from the NAWQA protocols was that 10 periphyton 

subsamples were collected from similar substrate as close to 

the center point of the reach as possible. Then five subsamples 

from rocks or sticks that best visually represented the average algal cover within the reach were collected subsamples, 

and these subsamples were composited into a single sample 

(Charles and others, 2000). The sample volume and total area 

sampled were recorded. A second modification to this study 

from the NAWQA protocols was that stream discharge, the 

point velocities at sample-collection sites, and light availability were not measured. Water-quality field measurements for 

each sample included water temperature, pH, specific conductance, turbidity, and dissolved oxygen.

The preferred method for collecting seston samples was 

the multiple vertical method described by Shelton (1994), in 

which a 3-L bottle with a 0.476-cm nozzle is used. In cases 

where water depths were a limiting factor, a grab method was 

used (Shelton, 1994). The seston samples were collected as 

close as possible to the center of the sampling reach, along a 

line that extended from the left edge of water to the right edge 

of water (transect). Along the transect, the wetted channel 

width and water depths (one-quarter, one-half, and three-quarters points) were recorded. 

Filtered periphyton and seston volumes, needed for the 

CHLa analysis, were determined by examining the color 

density of the filter following USGS National Water Quality 

Laboratory (NWQL) guidelines for particulate carbon sampling and analysis (Patton and others, 2000). Each sample was 

homogenized and filtered onto glass-fiber filters in the field by 

USGS personnel. The filtered volume of each algal-biomass 

sample was recorded. The filters were then placed on dry ice 

and transported to the USGS Indiana Algal Biomass Laboratory for analysis. Filters were processed within 30 days of 

collection. Concentrations of CHLa were determined, following USEPA method 445, with a Turner Designs TD–700 fluorometer outfitted for CHLa analysis (Arar and Collins, 1997). 

There were two exceptions to method 445: filters were ground 

in high-density polyethylene centrifuge tubes rather than 
Study Methods 7

glass to counter the problem of tube breakage, and samples 

were centrifuged at 1,500 to 2,000 revolutions per minute 

(approximately 320 to 569 g) for 15 minutes (Freeman, 1968). 

At the modified centrifuge rate, the filter residue and 90-percent acetone solution usually separated well. If samples did 

not separate well, they were placed in the centrifuge a second 

time. All samples were allowed to steep in 90 percent acetone 

for 2.5 hours at 4oC.

Quality-assurance methods for periphyton and seston 

CHLa samples included collecting triplicate filters from the 

same sample to measure variability and a blank filter from 

each sampling reach to evaluate equipment decontamination 

procedures and possible sample processing contamination 

(Bowren and Ghiasuddin, 1999). In addition, a fifth filter was 

collected at each site and 10 to 15 percent of these filters were 

analyzed for CHLa at the NWQL to measure interlaboratory 

variability. Results from the quality-assurance assessment 

showed no significant bias or contamination, nor was there a 

significant difference between replicate filters analyzed at the 

NWQL (Lowe and others, 2008).

Physical Habitat

Habitat characteristics at each site were assessed from 

June through October following standard IDEM methods 

(Indiana Department of Environmental Management, 1992, 

2002). Habitat assessments were made at the same time fish 

communities were sampled and included in-stream and riparian measurements that are incorporated into the Qualitative 

Habitat Evaluation Index (QHEI). 

Basin Characteristics

Basin characteristics were determined by USGS scientists 

and included drainage area and land use, expressed as the percentage of agriculture, forest, and urban area. Drainage area 

(size) was derived from the basin boundaries by using a Geographic Information System (GIS). Drainage area was used to 

categorize streams as either headwater streams (0 to 51 km2), 

wadable streams (52 to 2,590 km2), or boatable streams (2,591 

to 38,900 km2). Basin boundaries for each site were generated following the method outlined by Ries, III, and others 

(2004). This method combines the National Elevation Dataset, 

Digital Elevation Model data, and the National Hydrography 

Dataset, which is a comprehensive set of digital surface-water 

features. The basin boundaries formed a polygon that was used 

to extract land-use information from the National Land Cover 

Dataset (U.S. Geological Survey, 2000). Each sampling site 

was assessed to determine in which Aggregate Nutrient Ecoregion (U.S. Environmental Protection Agency, 2000a, b, c) and 

Level III Ecoregion (U.S. Environmental Protection Agency, 

1998) it was located.

Data Analysis

Data analysis was steered by two main objectives. The 

first objective was to improve the strength of the relations 

among the stressor (TN, TP, periphyton and seston CHLa, 

and turbidity) and response variables (biological community 

attributes), because typically the relations between nutrients, 

algal biomass, and biological communities have been weak 

(Figueroa-Nieves and others, 2006; Frey and others, 2007; 

Caskey and others, 2007; Leer and others, 2007; Royer and 

others, 2008; Lowe and others, 2008). The first objective was 

accomplished by: (1) removing sites that were biologically 

impaired by other known factors; (2) examining the possible 

covariability of fish and invertebrate communities with nonnutrient variables; and (3) removing sites from the biological 

datasets when a species of interest was not collected because it 

could not be confirmed that the species was missing from the 

site in response to a stressor variable of interest. The second 

objective was to identify the most statistically and ecologically 

significant relations among the stressor and response variables 

and to determine the breakpoints for these significant relations. 

The second objective was accomplished by: (1) reducing the 

number of response variables to a list of candidate response 

variables for three datasets to be used in the breakpoint analysis; (2) selecting the most significant response variables from 

the candidate list; and (3) determining the concentration of 

the stressor variables where the greatest change (breakpoint) 

was seen for each attribute from the final list of significant 

response variables. 

Improvement of the Relations among the 

Stressor and Response Variables 

Sites were initially selected for this analysis if the data 

included the stressor variables (TN, TP, periphyton CHLa, seston CHLa, and turbidity) and response variables (invertebrateand fish-community data). These initial sites included 77 sites 

with sufficient data for the invertebrate-community and 287 

sites for fish-community analyses. 

This study used multiple laboratories across multiple 

years, and thus the resolution of multiple reporting limits was 

required. Stressor variables, specifically TN (nitrate plus nitrite 

plus TKN) and TP, with multiple reporting limits were censored to one-half the highest reporting limit for each variable. 

For TKN there were 5 detection limits (0.1, 0.25, 0.3, 0.5, and 

1 mg/L), and 129 values (about 17.7 percent of the samples) 

had values less than a reporting limit. For TP there were two 

detection limits, 0.03 and 0.05 mg/L, and about 21 percent 

of the samples had values less than those detection limits. 

Variables with a single reporting limit and values less than 

the reporting limit were increased to one-half of the reporting 
8 Analysis and Assessment of Selected Variables on Macroinvertebrate and Fish Communities in Indiana Streams

limit. Variables with values greater than one-half of the highest reporting limits, but less than the highest reporting limit, 

were retained at the reported value. The means for each for the 

five stressor variables were calculated from the two to three 

samples collected at each site between May through October. 

To assess the trophic level of each stream, the mean stressor 

concentrations for TN, TP, periphyton and seston CHLa were 

compared to Dodds’ trophic classification. Dodds and others 

(1998) classified the oligotrophic-mesotrophic boundaries of 

Midwest streams as 0.70 mg/L for TN, 0.025 mg/L for TP, 

20 mg/m2 for periphyton CHLa, and 10 μg/L for seston CHLa

and the mesotrophic-eutrophic boundaries as 1.5 mg/L for 

TN, 0.075 mg/L for TP, 70 mg/m2 for periphyton CHLa, and 

30 μg/L for seston CHLa. The mean turbidity measurements 

were compared to 50 Nephelometric turbidity units (NTU), a 

turbidity biological impact classification (Nelson, 1993).

Sites with nonnutrient water-quality exceedances were 

removed (Indiana Department of Environmental Management, 2000); two sites were removed from the fish dataset, one 

for chloride and one for ammonia impairment. No sites were 

removed from the invertebrate community dataset based on 

water-quality exceedances. Next, sites where the concentrations of nonnutrient water-quality variables were greater than 

two standard deviations of the mean were removed to increase 

the probability that a nutrient was the primary stressor. During 

this step 52 sites from the fish datasets, including 3 sites from 

the invertebrate dataset, were removed, and most of the sites 

were removed based on high temperature, sulfate, arsenic, 

chemical oxygen demand (COD), and dissolved oxygen 

(greater than 16 mg/L) values. Of the 52 sites removed, 36 had 

multiple nonnutrient-related values greater than two standard 

deviations. After the 52 sites were removed, the final list of 

sites (table 1) used in the analysis consisted of 74 sites where 

invertebrate samples were collected from riffle habitats and 

identified to the family level and 232 sites where fish community were collected and identified to species level. 

In lotic ecosystems, multiple habitat and water qualityrelated variables influence biological communities at any 

given time from their headwaters to tailwaters (Vannote and 

others, 1980; Simon, 1999; Goldstein and Meador, 2004). To 

examine the possible covariability associated with nonnutrient variables, the invertebrate and fish community datasets 

were analyzed using Multi-Dimensional Scaling (MDS) in the 

PRIMER software (version 6, Plymouth, United Kingdom). 

An MDS analysis is a similarity or dissimilarity matrix that 

can be used to examine relevant questions within a dataset 

(Clarke and Warwick, 2001). In this study, the MDS analysis 

was used to determine if differences among the invertebrate 

and fish communities were explained by variables such as 

basin size, IDEM’s major river basins, Omernik’s Level III 

ecoregions, and USEPA Nutrient Ecoregions. Of the variables examined, the only variable that strongly explained 

the differences in the fish community was basin size. None 

of the variables examined strongly explained the differences 

in the invertebrate community. The Index of Biotic Integrity 

(IBI) used in Indiana is based on three distinct stream basin 

sizes: headwater sites (drainage basins ≤ 51 km2), wadable 

sites (drainage basins > 51 km2 to < 2,590 km2), and boat 

sites (drainage basins ≥ 2,591 km2). Therefore, the MDS and 

breakpoint analyses were based on the Indiana IBI classification of stream basin size.

In ecological or biocriteria assessments, the lack of an 

organism at a specific site does not necessarily indicate the 

organism was absent. The organism may not naturally occur 

within a certain region or stream, or the organism cannot be 

collected due to sampling methods, habitat, or stream conditions. In dose-response studies, the absence of an organism 

provides important toxicological information and is included 

in further analysis. In this study, sites were removed from this 

analysis if an organism was absent because (1) nutrient values 

found in samples from a site typically are not toxic to organisms, (2) of the uncertainty associated with an absence of an 

organism, and (3) the presence of an organism indicates a 

possible response to nutrients. In almost all cases, the removal 

of sites preserved a stressor gradient. Other variables that are 

covariant may still remain, and removal of sites with waterquality exceedances, nonnutrient-related data outliers, and 

absent organisms should produce a greater number of significant nutrient-biological relations. The most statistically and 

ecologically significant relations were subsequently examined 

for breakpoint response. The number of sites removed because 

a species did not occur varied for each significant response 

variable and ranged from 0 to 52 for the invertebrate dataset, 

42 to 74 for the headwater (fish) dataset, and 2 to 88 for the 

wadable (fish) dataset.

Identification of Significant Relations among 

Variables and Determination of Breakpoints

The identification of the most statistically and ecologically significant relations among the stressor and response 

variables (biological organisms, community attributes, and 

metrics) was aided by the reduction of the large number of 

response variables. First, the stressor variables were related to 

the response variables using Spearman rank order correlation. 

Environmental data typically are not normally distributed and 

when the sample size is greater than 20 for most variables, a 

nonparametric analysis, such as Spearman’s correlations (rs), 

is the preferred method for determining relations between variables (Helsel and Hirsch, 2002). In this study, all potential and 

strong correlations were identified using | rs |.

In this report, for a correlation to be considered statistically significant, the Spearman’s correlation was required to 

have, at most, a 5-percent significance level (α = 0.05) based 

on the sample size. Although an rs with a significance level of 

0.05 is considered significant, there is a possibility of introducing a Type I error in which the relation is declared present 

when the relation is not present (Helsel and Hirsch, 2002). 

Several procedures—such as the Bonferroni correction—are 

available for adjusting the significance level when performing a large number (or “family”) of tests simultaneously 
Assessment of the Stressor Variables and the Biological Communities 9

(Van Sickle, 2003). This adjustment reduces the chances of a 

Type I error at a specific alpha level. Although useful in reducing Type I error, this technique increases the chance of producing a Type II error, in which no relation is declared when a 

relation is present. Because of the low number of significant 

relations between nutrients (TN and TP), periphyton and 

seston CHLa, and turbidity to the biological organisms and 

community attributes and metrics, no Bonferroni corrections 

were applied in this analysis because of concerns of increasing 

a Type II error. Response variables were removed that were 

not statistically correlated (p <0.05) to the stressor variables. 

The remaining response variables were assessed for collinearity; for the response variables that were collinear, only the 

variables with the highest | rs |, or known ecological significance, were kept for further analysis. This analysis produced a 

list of candidate response variables for the three datasets, one 

invertebrate and two fish, used in the breakpoint analysis.

After the list of candidate response variables was completed for the three datasets used in the breakpoint analysis—

one invertebrate and two fish—the mean, standard deviation, 

variance, skewness, and kurtosis were calculated for each 

variable. In addition, a mix of box plots, histograms, NormalProbability (N-P) plots, and Probability-Probability (P-P) plots 

were used to determine the distribution and normality of the 

data. Nonnormal data must be transformed before it can be 

used in a statistical procedure that requires normality, unless 

nonparametric techniques are used. 

The second step in reducing the number of response variables was the use of cluster analysis as a visual censoring tool 

to select the final response variables by partitioning data into 

significant groups (clusters). This technique visually identified covariance among response variables by placing similar 

variables together. The most ecologically significant response 

variable with the highest | rs | from each cluster grouping was 

retained for the breakpoint analysis.

A regression-tree analysis was used in S-Plus (Insightful Corporation, 2001) to determine the concentration where 

the greatest change was seen for each metric or attribute from 

the finalized list of statistically and ecologically significant 

response variables. For each of the stressor variables (TN, TP, 

seston and periphyton CHLa, and turbidity), the median breakpoints for the most significant metrics and attributes from the 

invertebrate and the headwater and wadable fish datasets were 

determined.

Bootstrapping was used to determine the confidence 

intervals at the 90th percentile of the median breakpoints identified in the regression-tree analysis. Bootstrapping simulates 

the results of repeated experiments based on the observed 

data by randomly selecting subsets of the observed data. 

The approach used in the regression tree bootstrap preserved 

sampling along a gradient and allowed for the variables of 

the distribution to change along that gradient. This was done 

by defining groups of data along the environmental gradient 

and forcing the bootstrap to resample within those groups, 

thus preserving the gradient and also the variability of the 

distribution.

Assessment of the Stressor Variables 

and the Biological Communities

The data was evaluated in several ways to aid understanding of the relations among the stressor variables and 

between stressor variables and the biological-community. 

First, the biological community data were examined to determine if natural variability, such as basin size, in invertebrate 

or fish community data made it necessary to subset the data. 

Second, the biological communities were assessed for composition to determine if the species reflected nutrient-enriched 

conditions. Third, the stressor variables were (1) examined for 

distribution, (2) examined for relations among each other, and 

(3) compared to Dodds’ trophic classification levels. Finally, 

the biological communities were assessed to determine where 

the breakpoints in a species or biological community attribute 

or metric occurred in response to a stressor variable of interest. 

Influence of Basin Size on the BiologicalCommunity Composition

The MDS of the invertebrate community data of the 74 

sites visually indicated they were slightly affected by basin 

size; however, the MDS stress level of 0.25 indicates that 

not much reliance should be placed on the relation between 

invertebrate composition and basin size. Consequently, the 

invertebrate community data was not subset based on basin 

size. The MDS of the fish community dataset of the 232 sites 

indicated that they were affected by basin size; the MDS stress 

level of 0.18 statistically supports the influence of basin size 

on the fish community. Therefore, the fish community data 

was subset into three categories based on basin size: headwater (n=98), wadable (n=117), and boatable (n=17). Because the 

number of boatable sites was less than 20, that dataset was not 

analyzed further. 

Biological-Community Composition within the 

Sampled Basins

The invertebrate community consisted of 16,499 individuals, representing 59 families, and ranged from 7 to 18 families per site (appendix 3). Only one family, Chironomidae 

(non-biting midges), was found at all 74 sites. Chironimidae 

accounted for 41.7 percent of the total relative abundance, 

followed by Hydropsychidae – net-spinning caddisflies (collected at 73 sites with a total relative abundance of 17.3 percent), and Baetidae – mayflies (collected at 71 sites with a 

total relative abundance of 10.2 percent). The three dominant 

invertebrate families accounted for 69.2 percent of the total 

relative abundance. Recent studies have shown that invertebrate family-level identification can be as effective as genuslevel identification in relating stressors, such as nutrients, to 

the biological community (Carlisle and others, 2007). Many 
10 Analysis and Assessment of Selected Variables on Macroinvertebrate and Fish Communities in Indiana Streams

genera of the Chironomidae and Hydropsychidae families are 

considered highly nutrient tolerant (Carlisle and others, 2007), 

are an important food source for fish, and are often found in 

enriched freshwater habitats. In addition, as members of the 

order Dipteran, Chironomidae, are often the dominant taxa in 

freshwater habitats with extreme environmental conditions 

(Ward, 1992). Hydropsychidae are often used as indicator 

species in water-quality assessments, because some genera are 

sensitive to pollution (Ward, 1992).

The headwater fish community (n=98) consisted of 

16,896 individuals, representing 71 taxa, and ranged from 1 

to 23 taxa per site (appendix 5). The creek chub (Semotilus 

atromaculatus), central stoneroller (Campostoma anomalum), 

western blacknose dace (Rhinichthys obtusus), bluntnose 

minnow (Pimephales notatus), white sucker (Catostomus

commersonii), orangethroat darter (Etheostoma spectabile),

johnny darter (Etheostoma nigrum), and striped shiner (Luxilus chrysocephalus) accounted for 52.8 percent of the number 

of individuals collected. The most abundant species collected 

were creek chub (collected at 89 sites with a total relative 

abundance of 15.2 percent), central stoneroller (collected 

at 52 sites with a total relative abundance of 10.4 percent), 

and western blacknose dace (collected at 40 sites with a total 

relative abundance of 9.3 percent). In addition, these species 

are moderately tolerant to increases in turbidity (Robison and 

Buchanan, 1984). The central stoneroller populations, tolerant 

to increased turbidity and stream temperatures, can explode in 

warm nutrient-rich systems characterized by abundant algal 

growth (Ohio Department of Natural Resources, 2009). The 

headwater-fish communities were dominated by nutrient-tolerant species (Meador and Carlisle, 2007). 

The wadable fish community (n=117) consisted of 

40,795 individuals, representing 117 taxa, and ranged from 

4 to 40 taxa per site (appendix 5). The central stoneroller, 

bluntnose minnow, longear sunfish (Lepomis megalotis), 

striped shiner, bluegill (Lepomis macrochirus), rainbow darter 

(Etheostoma caeruleum), spotfin shiner (Cyprinella spiloptera), greenside darter (Etheostoma blenniodes), and sand 

shiner (Notropis stramineus) accounted for 50.8 percent of the 

number of individuals collected. The most abundant species 

collected were central stoneroller (collected at 116 sites with 

a total relative abundance of 13.3 percent), bluntnose minnow (collected at 101 sites with a total relative abundance of 

7.9 percent) and longear sunfish (collected at 84 sites with a 

total relative abundance of 7.8 percent). As with the headwater 

fish community dataset, the wadable fish communities were 

dominated by nutrient-tolerant species. Two species, spotfin 

shiner and sand shiner, were highly tolerant of nitrate (Meador 

and Carlisle, 2007) and were dominant in the wadable, but not 

the headwater, sites. Two species, western blacknose dace and 

white sucker, which are highly tolerant of nutrients (Meador 

and Carlisle, 2007), were dominant in the headwater but not 

in the wadable sites. The dominance of the invertebrate- and 

fish-community composition by nutrient-tolerant taxa provides 

evidence that the streams sampled in the study are eutrophic at 

times throughout the year.

Distribution of the Stressor Variables

Mueller and Spahr (2006) found that streams within the 

Midwest, including Indiana, have some of the highest nutrient loadings in the United States. Although streams for this 

study were sampled during periods of stable low flow, which 

typically has lower nutrient levels (Lowe and others, 2008), 

many streams within the state were nutrient enriched, based 

on the trophic classification by Dodds and others (1998). The 

summary statistics show only slight differences between the 

one invertebrate and two fish datasets used in these analyses 

(table 2). Within all three datasets, concentrations of stressor 

variables ranged from 0.30 to 11 mg/L for TN and from 

0.025 to 1.33 mg/L for TP (table 2). For the stressor variables 

periphyton and seston CHLa, concentrations ranged from 2.9 

to 768 mg/m2 and from 0.37 to 42 μg/L, respectively. Turbidity ranged from 0.8 to 65.4 NTU (table 2). 

Relations between the Stressor Variables

The strongest and most frequently significant correlations (rs

) between the stressor variables were between concentrations of TP and turbidity for all three datasets (table 3). 

Turbidity is a measure of the suspended solids within the 

water column and includes clay particles and seston algae. 

The strong correlations between TP and turbidity reflect the 

propensity for phosphorus to bind with clay particles (Hem, 

1989). The concentrations of TP and mean seston CHLa were 

strongly correlated in the invertebrate and fish wadable sites 

datasets, and this was partially a function of the presence of 

both chlorophyll and phosphorus in algae (Van Nieuwenhuyse 

and Jones, 1996; Morgan and others, 2006). Both of these 

factors may explain the significant correlations between seston 

CHLa and turbidity in the fish headwater and wadable sites. 

Turbidity was inversely related to periphyton CHLa in the fish 

headwater dataset, a finding that concurs with previous studies 

(Lowe and others, 2008). Periphyton CHLa was positively 

correlated with TN in the fish headwater and wadable datasets 

and negatively correlated with TP in the invertebrate dataset. 

Concentrations of TN and TP were weakly positively correlated in the fish headwater and wadable site datasets.
Assessment of the Stressor Variables and the Biological Communities 11

Table 2. Summary statistics for stressor variables used in the breakpoint analysis study, 2001–05.

[TN, total nitrogen; mg/L, milligrams per liter; TP, total phosphorus; CHLa, chlorophyll a; mg/m2, milligrams per square 

meter; μg/L, micrograms per liter; NTU, Nephelometric turbidity units; n, number of samples]

Statistic TN1

(mg/L)

TP1

(mg/L)

Periphyton 

CHLa1

(mg/m2)

Seston 

CHLa1

(μg/L)

Turbidity1

(NTU)

Invertebrate sites (n=74)

Minimum 0.79 0.025 7.3 0.50 3.7

25th percentile 3.0 .052 37 2.1 9.9

Median 3.6 .078 62 3.2 14.1

Mean 3.8 .117 76 4.5 17.1

Maximum 8.0 1.13 310 26 65.4

Fish headwater sites (n=98)

Minimum 0.39 0.025 2.9 0.37 0.8

25th percentile .94 .037 20 1.3 7.0

Median 2.7 .065 48 3.3 10.3

Mean 3.4 .105 71 3.7 14.1

Maximum 11 1.33 540 26 52.4

Fish wadable sites (n=117)

Minimum 0.30 0.025 4.7 0.66 2.7

25th percentile 1.7 .050 32 2.2 9.2

Median 3.4 .071 60 3.5 12.5

Mean 3.2 .091 96 5.5 15.1

Maximum 8.2 .417 768 42 65.4

1

 The mean of all the values was used in this analysis. 

Table 3. Spearman rho correlations among the stressor variables used in the breakpoint analysis study, 2001–05.

[TN, total nitrogen; mg/L, milligrams per liter; TP, total phosphorus; CHLa, chlorophyll a; mg/m2, milligrams per square meter; μg/L, 

micrograms per liter; NTU, Nephelometric turbidity units; n, number of samples; bold text, p < 0.05]

Stressor TN1

(mg/L)

TP1

(mg/L)

Periphyton 

CHLa1

(mg/m2)

Seston 

CHLa1 (μg/L)

Turbidity1

(NTU)

Invertebrate sites (n=74)

TN (mg/L) 0.219 0.184 -0.207 -0.071

TP (mg/L) 0.219 -.315 .311 .454

Periphyton CHLa (mg/m2) .184 -.315 .000 -.122

Seston CHLa (mg/L) -.207 .311 .000 .204

Turbidity (NTU) -.071 .454 -.122 .204

Fish headwater sites (n=98)

TN (mg/L) 0.265 0.214 -0.014 0.258

TP (mg/L) 0.265 -.166 .044 .474

Periphyton CHLa (mg/m2) .214 -.166 -.035 -.253

Seston CHLa (mg/L) -.014 .044 -.035 .240

Turbidity (NTU) .258 .474 -.253 .240

Fish wadable sites (n=117)

TN (mg/L) 0.236 0.221 -0.034 0.172

TP (mg/L) 0.236 -.109 .457 .473

Periphyton CHLa (mg/m2) .221 -.109 .004 -.181

Seston CHLa (mg/L) -.034 .457 .004 .310

Turbidity (NTU) .172 .473 -.181 .310

1

 The mean of all the values was used in this analysis.
12 Analysis and Assessment of Selected Variables on Macroinvertebrate and Fish Communities in Indiana Streams

Comparison of Trophic Classification for the 

Stressor Variables

Dodds and others (1998) classified trophic conditions 

as oligotrophic, mesotrophic, and eutrophic on the basis of 

criteria for TN, TP, and CHLa (periphyton and seston) using 

existing data. Based on the Dodds’ criteria, streams in this 

study were most often classified as eutrophic for TN. In 

particular, the streams in the invertebrate dataset were almost 

all considered eutrophic based on Dodds’ classification for 

TN. Based on the Dodds’ criteria for TN, 94.6 percent of the 

invertebrate sites, 67.7 percent of the fish headwater sites, 

and 78.6 percent of the fish wadable sites would be classified as eutrophic (fig. 2). The eutrophic classifications for TP 

were similar among the three datasets: 42.9 percent of the 

invertebrate sites, 39.8 percent of the fish headwater sites, and 

46.2 percent of the fish wadable sites (fig. 3). For periphyton 

CHLa, 43.2 percent of the invertebrate sites, 35.7 percent of 

the fish headwater sites, and 41.0 percent of the fish wadable 

sites would be classified as eutrophic (fig. 4). 

Of all the stressor variables examined based on the 

trophic classification of Dodds and others (1998), the least 

number of streams would be considered eutrophic using 

seston CHLa data. Only about 1 percent of the fish wadable 

site data and none of the invertebrate and headwater fish site 

data would be classified as eutrophic based on seston CHLa

(fig. 5). Part of the reason for the low number of streams 

classified as eutrophic based on seston CHLa in this study is 

that the large river streams were not included in the analysis 

because of the sample size. Typically, seston CHLa concentrations are greater in large rivers than in small rivers (Vannote and others, 1980; Lowe and others, 2008). Turbidity and 

seston CHLa concentrations are closely related (Lowe and 

others, 2008), and as with seston CHLa, few streams in this 

study would be considered impacted based on turbidity. Based 

on a biological impact classification for turbidity as used by 

Nelson (1993), less than 3 percent of the sites were impacted 

adversely by turbidity (fig. 6). Part of the reason for the low 

turbidity values in this study was that samples were only collected during stable low flow conditions to minimize the scour 

effect on algae from elevated streamflow. Of all the stressor 

variables, seston CHLa and turbidity could be the most misleading when assessing the trophic level of streams, because 

headwater and wadable streams generally have lower seston 

CHLa and turbidity. This is especially true for study designs 

that sample only during stable low flow conditions, but the 

alternative design of collecting samples during elevated flow 

would underestimate periphyton CHLa because of scour. 

These findings support the use of multiple lines of evidence 

when assessing the trophic levels in streams. 

x

x

x

x

x

5.0

10.0

74 98 117

30 Number of

values

x

x

TOTAL NITROGEN, IN MILLIGRAMS PER LITER

Dodds mesotrophic-eutrophic

boundary = 1.5 mg/L

Dodds oligotrophic-mesotrophic

boundary = 0.7 mg/L

INVERTEBRATE

SITES

FISH HEADWATER

SITES

FISH WADABLE

SITES

1.0

0.5

0.1

75th percentile

Median

25th percentile

Lower adjacent

Lower outside

EXPLANATION

Schematic boxplot

Upper outside

Upper adjacent

Figure 2. Distribution of the mean total nitrogen log transformation of concentrations compared to Dodd and others (1998) trophic 

classifications in the three selected datasets used in the breakpoint analysis study, 2001–05. 
Assessment of the Stressor Variables and the Biological Communities 13

x

x

x

x

x

x

x x

x

TOTAL PHOSPHORUS, IN MILLIGRAMS PER LITER

Dodds mesotrophic-eutrophic

boundary = 0.075 mg/L

Dodds oligotrophic-mesotrophic

boundary = 0.025 mg/L

30 Number of

values

x

x

75th percentile

Median

25th percentile

Lower adjacent

Lower outside

EXPLANATION

Schematic boxplot

Upper outside

Upper adjacent

1.00

0.50

0.10

0.05

0.01

INVERTEBRATE

SITES

FISH HEADWATER

SITES

FISH WADABLE

SITES

74 98 117

xx

x

x

x

Dodds mesotrophic-eutrophic

boundary = 70 mg/m2

Dodds oligotrophic-mesotrophic

boundary = 20 mg/m2

PERIPHYTON CHLOROPHYLL a,

IN MILLIGRAMS PER SQUARE METER

30 Number of

values

x

x

75th percentile

Median

25th percentile

Lower adjacent

Lower outside

EXPLANATION

Schematic boxplot

Upper outside

Upper adjacent

INVERTEBRATE

SITES

FISH HEADWATER

SITES

FISH WADABLE

SITES

500

100

50

10

5

1

74 98 117

Figure 3. Distribution of the mean total phosphorus log transformation of concentrations compared to Dodds and others (1998) 

trophic classifications in the three selected datasets used in the breakpoint analysis study, 2001–05. 

Figure 4. Distribution of the mean periphyton chlorophyll a log transformation of concentrations compared to Dodds and others (1998) 

trophic classifications in the three selected datasets used in breakpoint analysis study, 2001–05. 
14 Analysis and Assessment of Selected Variables on Macroinvertebrate and Fish Communities in Indiana Streams

x

x

x

xx

x

x

x

x

SESTON CHLOROPHYLL a, IN MICROGRAMS PER LITER

Dodds mesotrophic-eutrophic

boundary = 30 μg/L

Dodds oligotrophic-mesotrophic

boundary = 10 μg/L

30 Number of

values

x

x

75th percentile

Median

25th percentile

Lower adjacent

Lower outside

EXPLANATION

Schematic boxplot

Upper outside

Upper adjacent

INVERTEBRATE

SITES

FISH HEADWATER

SITES

FISH WADABLE

SITES

74 98 117

10.0

50.0

5.0

1.0

0.5

x

x

x

x

x

TURBIDITY, IN NEPHELOMETRIC TURBIDITY UNITS

Turbidity biological impact

classification = 50 NTU

30 Number of

values

x

x

75th percentile

Median

25th percentile

Lower adjacent

Lower outside

EXPLANATION

Schematic boxplot

Upper outside

Upper adjacent

INVERTEBRATE

SITES

FISH HEADWATER

SITES

FISH WADABLE

SITES

10.0

50.0

5.0

1.0

0.5

74 98 117

Figure 5. Distribution of the mean seston chlorophyll a log transformation of concentrations compared to Dodds and others (1998) 

trophic classifications in the three selected datasets used in the breakpoint analysis study, 2001–05. 

Figure 6. Distribution of the mean turbidity log transformation of concentrations compared with turbidity biological impact 

classifications (Nelson, 1993) in the three selected datasets used in the breakpoint analysis study, 2001–05. 
Biological Breakpoints of the Stressor Variables and Implications for Developing Nutrient Criteria 15

Biological Breakpoints of the Stressor 

Variables and Implications for 

Developing Nutrient Criteria

Regression tree analysis was conducted on the most statistically and ecologically significant stress-response relations. 

The strongest and most ecologically significant of these relations and the breakpoints are listed in table 4. The strongest 

correlations | rs | included both invertebrate and fish measures. 

For mean TN, the median breakpoints of the three most 

significant biological response variables ranged from 2.4 to 

3.3 mg/L. The most significant relation was between mean TN 

to percentage of biomass composed of white suckers in the 

fish headwater dataset (table 4 and fig. 7). In this positive relation, mean TN increased as the percentage of biomass composed of white suckers increased with a median breakpoint 

of 2.9 mg/L (fig. 7). White suckers are highly tolerant of 

nutrients, specifically, nitrate and TP (Meador and Carlisle, 

2007), and the relative percentage of white suckers would be 

expected to increase with high nutrients. The TN breakpoints 

presented in this study fall between one-half to one standard 

deviation greater than the statewide mean of 1.9 mg/L for TN, 

which was based on data collected from 1996 to 2005 (Steven 

A. Newhouse, Indiana Department of Environmental Management, oral commun., 2008). The mean TN concentration associated with the biological breakpoints in this study (table 4) 

is high compared with most TN breakpoint values within the 

Midwest. Specifically, the breakpoints for this study are more 

than two times higher than the TN breakpoint of 1.2 mg/L 

to seston CHLa found in a Wisconsin study (Robertson and 

others, 2006). In addition, the median breakpoint for TN of 

2.9 mg/L found in this study is almost two times higher than 

the levels Dodds and others (1998) described as eutrophic. 

Table 4. Breakpoint summary for the stressor variables used in the breakpoint analysis study, 2001–05.

[n, number of sites in analysis; TN, total nitrogen; mg/L, milligrams per liter; TP, total phosphorus; CHLa, chlorophyll a; mg/m2, milligrams per square meter; 

μg/L, micrograms per liter; NTU, Nephelometric turbidity units]

Data site 

type

Biological 

response 

variable

Stressor 

variable to 

biological 

attribute 

Spearman rho

n

Median 

bootstrap 

breakpoint

Bootstrap 

confidence 

interval

TN (mg/L)

Invertebrate Hydroptilidae (percent relative abundance) 0.337 40 3.3 2.3–4.0

Fish headwater White sucker (percentage of biomass) .316 50 2.9 2.8–5.9

Fish wadable Number of pioneer taxa .314 114 2.4 2.0–4.0

TP (mg/L)

Invertebrate Percentage of abundance composed of molluscs 

and crustaceans

0.422 38 0.090 0.057–0.110

Fish headwater Striped shiner (percentage of biomass) -.337 34 .042 .042–.077

Fish wadable Green sunfish (percent relative abundance) .296 88 .129 .099–.176

Periphyton CHLa (mg/m2)

Invertebrate Percentage of total richness composed of shredders -0.519 22 60 50.4–87.8

Fish headwater Number of sensitive taxa .390 56 68 18.1–99.4

Fish wadable Largemouth bass (percent relative abundance) -.266 31 54 19.1–58.6

Seston CHLa (μg/L)

Invertebrate Richness composed of filtering-collectors 0.388 74 4.7 3.0–7.4

Fish headwater Bluegill (g) .367 35 4.5 4.3–4.9

Fish wadable Number of sunfish species .330 115 7.5 5.0–10.3

Turbidity (NTU)

Invertebrate Hydropsychidae (percent relative abundance) 0.335 70 14.1 12.4–22.9

Fish headwater Number of sensitive species -.422 56 16.1 6.7–31.0

Fish wadable Spotted sucker (percentage of biomass) .499 29 14.6 12.2–19.0
16 Analysis and Assessment of Selected Variables on Macroinvertebrate and Fish Communities in Indiana Streams

Of the five stressor variables examined, all the TN median 

breakpoints would be classified as eutrophic using the method 

of Dodds and others (1998). These findings indicate that 

a mean TN concentration target of 2.9 mg/L might be an 

appropriate attribute for showing changes in the fish community from hypereutrophic to eutrophic stream classification, 

but might not be appropriate for showing change to meso- or 

oligotrophic conditions (fig. 7). In the nutrient-saturated Midwest, this may be a possible first target for showing improvements in the hypertrophic headwater streams. This relation is 

another line of evidence that indicates many streams within 

the dataset are eutrophic. 

For mean TP, the median breakpoints of the three most 

significant biological response variables ranged from 0.042 to 

0.129 mg/L. The most significant relation was between mean 

TP to the percentage of biomass composed of striped shiners in the fish headwater dataset (table 4 and fig. 8). In this 

negative relation, as the mean TP increased the percentage of 

biomass composed of striped shiners decreased with a median 

breakpoint of 0.042 mg/L (fig. 8). Striped shiners are intolerant 

of high phosphorus levels (Meador and Carlisle, 2007). Two 

of the median breakpoints for TP found in this study are higher 

than the TP breakpoint of 0.07 mg/L found in a Wisconsin 

study (Robertson and others, 2006), but the striped shiner metric is lower than the value found in Wisconsin. The breakpoint 

in this study falls between one-half and one standard deviation 

below the statewide mean TP of 0.09 mg/L, which was based 

on TP data collected from 1996 to 2005 (Steven A. Newhouse, 

Indiana Department of Environmental Management, oral commun., 2008). These findings indicate that a TP concentration 

target of 0.042 mg/L based upon striped shiner biomass might 

be an appropriate concentration for showing changes from 

eutrophic or mesotrophic stream classification to oligotrophic 

conditions for headwater streams. 

0 2 4 6 8 10 12

0

10

20

30

40

50

60

70

80

PERCENTAGE OF BIOMASS COMPOSED OF WHITE SUCKERS

TOTAL NITROGEN, IN MILLIGRAMS PER LITER

Dodds oligotrophic-mesotrophic

boundary = 0.7 mg/L

Dodds mesotrophic-eutrophic

boundary = 1.5 mg/L

Median bootstrap

breakpoint = 2.9 mg/L

Figure 7. Scatter plot of mean total nitrogen concentrations to the percentage of biomass composed of white 

suckers at headwater fish sites for the breakpoint analysis study, 2001–05. (Trophic classifications from Dodds and 

others, 1998.) 
Biological Breakpoints of the Stressor Variables and Implications for Developing Nutrient Criteria 17

For mean periphyton CHLa, the median breakpoints of 

the three most significant biological response variables ranged 

from 54 to 68 mg/m2 (table 4). The most significant relation 

was between mean periphyton CHLa to percentage of total 

richness composed of shredders in the invertebrate dataset 

(table 4 and fig. 9). In this negative relation, as the mean 

periphyton CHLa increased the percentage of total richness 

composed of shredders decreased with a median breakpoint of 

60 mg/m2 (fig. 9). Although this relation is statistically significant, the ecological significance of this relation is most likely a 

function of habitat and stream size, and not periphyton CHLa

concentrations. As stream size increases more light reaches the 

stream and periphyton CHLa increases (Vannote and others, 

1980). Shredders are widely considered to be of central importance in invertebrate communities because they process coarse 

detritus (Ward, 1992). Headwater streams typically have 

more closed canopy, a source of coarse detritus, than wadable streams (Vannote and others, 1980), and as stream size 

increases the source of detritus decreases; therefore, the role 

of shredders decreases. Although the strongest breakpoint for 

mean periphyton CHLa (table 4) was the invertebrate dataset, 

the fish headwater (number of sensitive taxa) and fish wadable 

(percentage of relative abundance of largemouth bass) datasets 

had similar breakpoints, 60 and 54, respectively. All three of 

these values are close to the mesotrophic/eutrophic boundary 

of 70 mg/m2 found by Dodds and others (1998). Although a 

possible habitat signature influence was observed, these findings indicate that a target of 60 mg/m2

 for periphyton CHLa

or 70 mg/m2 for the Dodds and others (1998) classification for 

eutrophic systems might be appropriate for showing changes 

in the invertebrate community from eutrophic to mesotrophic 

stream classification for headwater and wadable streams. 

0

10

20

30

40

50

60

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45

Median bootstrap

breakpoint = 0.042 mg/L

Dodds oligotrophic-mesotrophic

boundary = 0.025 mg/L

Dodds mesotrophic-eutrophic

boundary = 0.075 mg/L

TOTAL PHOSPHORUS, IN MILLIGRAMS PER LITER, AS PHOSPHORUS

PERCENTAGE OF BIOMASS COMPOSED OF STRIPED SHINER

Figure 8. Scatter plot of mean total phosphorus concentrations to the percentage of biomass composed of striped 

shiners at headwater fish sites for the breakpoint analysis study, 2001–05. (Trophic classifications from Dodds and 

others, 1998.) 
18 Analysis and Assessment of Selected Variables on Macroinvertebrate and Fish Communities in Indiana Streams

For mean seston CHLa, the median breakpoints of the 

three most significant biological response variables ranged 

from 4.5 to 7.5 μg/L. The most significant relation was 

between mean seston CHLa to bluegill biomass in the fish 

headwater dataset (table 4 and fig. 10). In this positive relation, as mean seston CHLa increased the biomass of bluegill 

increased with a median breakpoint of 4.5 μg/L (fig. 10). The 

ecological significance of this relation is not readily discernible. In headwater streams bluegills are primarily juveniles, 

they typically feed on small crustaceans and insects, and they 

are intolerant of continuous high turbidity and siltation (Robison and Buchanan, 1984). Lowe and others (2008) noted that 

as basin size increased, seston CHLa and turbidity increased 

in Indiana streams. In this study, seston CHLa and turbidity 

were significantly related (table 3), and more than 75 percent 

of the seston CHLa samples collected between 2001–05 had 

values less than 6 μg/L (Lowe and others, 2008). It indicates 

that the positive relation might be because the data heavily 

favored low seston CHLa concentrations, and there may have 

been an eventual negative relation if stream size increased or 

a larger seston CHLa gradient was sampled. Lowe and others 

(2008) found that 75 percent of the seston CHLa samples 

had values less than 6 μg/L which is five times lower than 

Dodds and others (1998) eutrophic level. However, Dodds 

and others (1998) based their results on a dataset collected 

during the growing season from Van Nieuwenhuyse and Jones 

(1996) that included many larger streams with drainage areas 

greater than 1,000 km2, and larger streams were not included 

in this study. Seston CHLa values are greater in larger streams 

(Vannote and others, 1980; Lowe and others, 2008), and in 

streams larger than 1,000 km2 the median seston CHLa value 

of 22.1 μg/L was about 10 times greater than the headwater or 

wadable median seston CHLa values (Lowe and others, 2008). 

Consequently, the observed increase in the bluegill biomass 

in this study could be the result of stream size, specifically the 

use of headwater and wadable sites for this analysis, and not a 

direct link to increased seston CHLa. These findings indicate 

that a seston CHLa value between the 4.5 μg/L breakpoint for 

biomass of bluegill metric and the Dodds and others (1998) 

oligotrophic classification of 10 μg/L might be an appropriate 

concentration for showing changes to oligotrophic conditions 

in headwater streams. Based on these findings, multiple lines 

of evidence should be considered in analysis of whether TN, 

TP, periphyton CHLa, or turbidity indicate more eutrophic or 

impacted conditions.

0 20 40 60 80 100 120 140 160 180

0

2

4

6

8

10

12

14

16

18

Dodds oligotrophic-mesotrophic

boundary = 20 mg/m2

Dodds mesotrophic-eutrophic

boundary = 70 mg/m2

Median bootstrap

breakpoint = 60 mg/m2

MEAN PERIPHYTON CHLOROPHYLL a, IN MILLIGRAMS PER SQUARE METER

PERCENTAGE OF TOTAL RICHNESS COMPOSED OF SHREDDERS

Figure 9. Scatter plot of mean periphyton chlorophyll a concentrations to the percentage of total richness 

composed of shredders at invertebrate sites for the breakpoint analysis study, 2001–05. (Trophic classifications from 

Dodds and others, 1998.) 
Biological Breakpoints of the Stressor Variables and Implications for Developing Nutrient Criteria 19

For mean turbidity, the median breakpoints of the three 

most significant biological response variables ranged from 

14.1 to 16.1 NTU. The most significant relation was between 

mean turbidity to percentage of biomass composed of spotted 

suckers in the fish wadable dataset (table 4 and fig. 11). In this 

positive relation, as the mean turbidity increased the percentage of biomass composed of spotted suckers increased with a 

median breakpoint of 14.6 NTU (fig. 11). Increases in turbidity can result in detrimental impacts to fish reproduction and 

larval survival when concentrations are greater than 50 NTU 

(Nelson, 1993). In contrast, the positive relation in this study 

indicates that as turbidity increases there is an increase in spotted suckers. This is unexpected because spotted suckers are 

thought to be particularly intolerant of turbid waters (Trautman, 1981) or slightly turbid waters (Robison and Buchanan, 

1984); but because the turbidity values from this study were 

low, less the 50 NTU, the relation indicates that the percentage of biomass composed of spotted suckers would increase 

until the turbidity reaches 50 NTU, followed by a subsequent 

decrease. This finding is most likely because of the significant 

positive correlation between turbidity and TP; phosphorus can 

bind with clay and provide nutrients essential for algal growth, 

one food source for spotted suckers. In addition, spotted suckers can be found in all sizes of rivers, including the Mississippi 

River (Iowa Department of Natural Resources, 2009). However, since large rivers, which typically have higher turbidity 

(Lowe and others, 2008) were not included in this analysis, 

there may have been a decrease in the percentage biomass of 

spotted suckers if the data from the large river sites had been 

included in this analysis, because large river systems typically 

have turbidity concentrations greater than 50 NTU’s which has 

been shown to impact fish reproduction. Since about 97 percent of the turbidity samples in this analysis reported turbidity 

concentrations less than the 50 NTU and this analysis indicates that a target breakpoint of 16.1 NTU for turbidity, it was 

concluded that the calculated breakpoint of 16.1 NTU would 

lack the sensitivity to show changes in the fish community in 

wadable streams; but use of Nelson’s (1993) turbidity impact 

classification of 50 NTU would protect aquatic biota from 

turbidity impacts. 

SESTON CHLOROPHYLL a, IN MICROGRAMS PER LITER

BLUEGILL BIOMASS, IN GRAMS

0 5 10 15 20 25 30 35

0

50

100

150

200

250

300

350

Dodds oligotrophic-mesotrophic

boundary = 10 μg/L

Dodds mesotrophic-eutrophic

boundary = 30 μg/L

Median bootstrap

breakpoint = 4.5 μg/L

Figure 10. Scatter plot of mean seston chlorophyll a concentrations to bluegill biomass at headwater fish sites for the 

breakpoint analysis study, 2001–05. (Trophic classifications from Dodds and others, 1998.) 
20 Analysis and Assessment of Selected Variables on Macroinvertebrate and Fish Communities in Indiana Streams

Overall, the results from this study indicate some breakpoints between the stressor and the response variables could 

be used to support the development of nutrient criteria. Trophic classifications from Dodds and others (1998) may also be 

appropriate, because even though they were developed based 

on only chemistry data, breakpoints in the biological communities appear to generally follow these trophic classifications. 

It is apparent from the relatively weak correlations between 

the stressor and response variables and lack of a gradient for 

some of the stressor variables in this study (seston CHLa and 

turbidity), that the assessment of the true nutrient condition 

within a stream or the development of nutrient criteria needs 

to rely on multiple lines of evidence that includes measures of 

nutrients (TN and TP), algal biomass (periphyton and seston 

CHLa), turbidity, and biological attributes. Development of a 

nutrient Index of Biotic Integrity that would incorporate fish 

and invertebrate attributes and metrics indicative of oligotrophic, mesotrophic, and eutrophic levels to show changes in 

the biological communities also could aid the assessment of 

stream nutrient conditions. 

0 10 20 30 40 50

4

6

8

10

12

14

16

18

20

2

0

TURBIDITY, IN NEPHELOMETRIC TURBIDITY UNITS

PERCENTAGE OF BIOMASS COMPOSED OF SPOTTED SUCKER

Median bootstrap

breakpoint = 14.6 NTU

Turbidity biological impact

classification = 50 NTU

Figure 11. Scatter plot of mean turbidity concentrations to the percentage of biomass composed of spotted 

suckers at wadable fish sites for the breakpoint analysis study, 2001–05. (Turbidity biological impact classification 

from Nelson, 1993.) 
Summary 21

Summary

Nutrients are essential to the development, health, and 

diversity of plants and animals in surface waters, yet excessive inputs of nutrients into streams have potential humanhealth, economic, and ecological consequences. Indiana is 

part of the nutrient-rich Midwest that leads the nation in corn 

and soybean production, which require the use of significant 

amounts of nutrients—primarily from fertilizer and manure 

for the production of these crops. Streams sampled within the 

Midwest have some of the highest nutrient concentrations and 

loading in the United States. Earlier studies in Indiana found 

weak relations between nutrients and algal biomass and that 

other indicators, such as biological community attributes and 

metrics, could be helpful in developing nutrient criteria for 

streams in such nutrient-rich regions.

Water chemistry and biological community data were 

collected from 321 sites from 2001 through 2005 to determine 

if the changes among biological species and attributes were 

statistically related to changes in stressor (TN, TP, periphyton and seston CHLa, and turbidity) variables. Because of 

the typically weak relations among the stressor and response 

variables, statistical methods were used to eliminate biological 

stressors that could override relations of interest. This included 

removing sites that were biologically impaired by other known 

factors, removing outliers greater that two standard deviations 

of the mean, and removing sites from the biological datasets 

when a species of interest was not collected because it could 

not be confirmed that the species was from the site in response 

to the stressor variable of interest. The invertebrate and fish 

species and attributes were related to stressor variables to 

determine the most statistically and ecologically significant 

stressor-response relations for each community. Breakpoint 

analysis was used for the most statistically significant and 

ecologically relevant relations to find the concentration of the 

stressor variables where the greatest change occurred with the 

biological species and community attributes and metrics.

Within all three datasets, concentrations of stressor 

variables ranged from 0.30 to 11 mg/L for TN and from 0.025 

to 1.33 mg/L for TP. For the stressor variables periphyton and 

seston CHLa, concentrations ranged from 2.9 to 768 mg/m2

and from 0.37 to 42 μg/L, respectively. Turbidity concentrations ranged from 0.8 to 65.4 NTU. Most streams would be 

classified as eutrophic due to TN, and the least number of 

streams would be classified as eutrophic due to seston CHLa. 

Of all the stressor variables, seston CHLa could be the most 

misleading when assessing the trophic level of streams, especially at headwater and wadable sites.

In this study, the relative total abundance of invertebrates 

was dominated by Chironimidae, 41.7 percent, Hydropsychidae, 17.3 percent, and Baetidae, 10.2 percent. Many genera of 

the Chironomidae and Hydropsychidae families are considered 

highly nutrient tolerant. The percentage of richness composed 

of shredders and filtering-collectors were the only invertebrate attributes to be statistically related to periphyton and 

seston CHLa, respectively. Of the three dominant invertebrate 

families, only Hydropsychidae was found to be related to a 

response variable (turbidity). Turbidity and TP were found to 

be correlated, and thus it was expected that a positive relation 

between these two variables would be found because turbidity concentrations were well below a level that would impact 

biological organisms. The two other invertebrate families, 

Hydroptilidae (microcaddisflies or purse-case caddisflies) and 

Tipulidae (crane flies), were found to be statistically related to 

nutrients, TN and TP, respectively.

This study found that the relative total abundance in the 

fish communities were dominated by algivores and nutrienttolerant species, specifically central stonerollers, 13.3 percent,

creek chubs, 9.9 percent, and bluntnose minnow, 9.3 percent. 

Although they are not the dominant taxa, bluegill, spotted 

sucker, white sucker, and striped shiner species were statistically significant with the stressor variables. 

The breakpoint for TN indicates that a target concentration of 2.9 mg/L could be an appropriate attribute to show 

changes in the biomass of white suckers from hypereutrophic 

to eutrophic stream conditions. The breakpoint for TP indicates a target concentration of 0.042 mg/L based upon striped 

shiner biomass might be an appropriate concentration to show 

changes from eutrophic or mesotrophic stream classification to oligotrophic conditions for headwater streams. The 

breakpoint for mean periphyton CHLa indicates that a target 

concentration of around 60 mg/m2, found in this study, to 

70 mg/m2, based on Dodds and others (1998) eutrophic classifications, might be an appropriate attribute to show changes 

in the invertebrate community from eutrophic to mesotrophic 

stream classification for headwater and wadable streams. The 

breakpoint for mean seston CHLa indicates a target concentration between the 4.5 μg/L breakpoint for biomass of bluegill 

metric and 10 μg/L, from Dodds and others (1998) oligotrophic classification, might be an appropriate concentration to 

show changes to oligotrophic conditions in headwater streams. 

Based on these findings, multiple lines of evidence should 

be considered during assessments of whether or not TN, 

TP, periphyton CHLa, or turbidity indicate more eutrophic 

or impacted conditions. The breakpoints for mean turbidity 

lack the sensitivity to show changes in headwater or wadable 

streams, and the Nelson (1993) turbidity biological impact 

classification would provide a starting point to develop turbidity criteria. 
22 Analysis and Assessment of Selected Variables on Macroinvertebrate and Fish Communities in Indiana Streams

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Table 1. Location of Indiana Department of Environmental Management Watershed Monitoring Program sampling sites used in the breakpoint analy2001–05. —Continued [USGS, U.S. Geological Survey; STAID, station identification; IDEM, Indiana Department of Environmental Management; dd.mm.ss, degrees minutes seconds; CK, creek; FT, IN, Indiana; CR, county road; SR, state route; DS, downstream; INDPLS, Indianapolis; NR, Near; E, east; RD, road; FK, fork; N, North; MI, mile; USHWY, US highway; M, mbus, business] Site identifier USGS STAID IDEM site number Latitude (dd.mm.ss) Longitude (dd.mm.ss) USGS station name 

1 400620086050901 INRB01-302 40 06 20 86 05 09 HINKLE CK 1500 FT US EAST 216TH ST AT DEMING, IN 2 393410086085901 INRB01-304 39 34 10 86 08 59 HONEY CR 2300 FT US SR 135 AT STONES CROSSING, IN 

13 392659086181801 INRB01-306 39 26 59 86 18 18 SOUTH PRONG STOTTS CK 1200 FT US SR 44 AT COPE, IN 

4 401606085532301 INRB01-311 40 16 06 85 53 23 POLYWOG CK 3000 FT US CR 300S AT NEW LANCASTER, IN 5 384949087024201 INRB01-313 38 49 49 87 02 42 KANE DITCH 1200 FT DS CR 700E NR EPSOM, IN 6 395256086242601 INRB01-316 39 52 56 86 24 26 BEAMAN DITCH 3800 FT US CR 800N NR BROWNSBURG, IN 

17 394734086133501 INRB01-318 39 47 34 86 13 35 LITTLE EAGLE CREEK 2100 FT US WEST 16TH ST INDPLS 

8 401451086110701 INRB01-319 40 14 51 86 11 07 KIGIN DITCH 300 FT US CR 900W NR EKIN, IN 

19 393046086573501 INRB01-320 39 30 46 86 57 35 BIG WALNUT CK 3700 FT US 1-70 NR PLEASANT GARDENS 

110 385116086565701 INRB01-321 38 51 16 86 56 57 UNNAMED CREEK 3500 FT DS CR 1100E NR FARLEN, IN 

111 393855086245601 INRB01-322 39 38 55 86 24 56 W FK WHITE LICK CK 1500 FT US I-70 NR PLAINFIELD 

112 401449085311801 INRB01-323 40 14 49 85 31 18 JAKES CREEK 600 FT DS CR 700W AT BETHEL, IN 113 395003086410401 INRB01-324 39 50 03 86 41 04 BIG WALNUT CREEK 1600 FT US CR 900E NR BARNARD, IN 114 400046085370901 INRB01-327 40 00 46 85 37 09 FALL CREEK 1300 FT DS CR 300E NR EMPORIA, IN 115 393022086313401 INRB01-330 39 30 22 86 31 34 LAMBS CREEK 1600 FT DS BEREAN RD NR WILBUR, IN 116 394648086432701 INRB01-332 39 46 48 86 43 27 PLUM CREEK 1800 FT US CR 800N AT NEW MAYSVILLE, IN 117 400831084552901 INRB01-335 40 08 31 84 55 29 WHITE RIVER 2800 FT DS CR 200S NR WINCHESTER, IN 118 393713086213101 INRB01-338 39 37 13 86 21 31 E FK WHITE LICK CK 1400FT US OLD 67 MOORESVILLE, IN 

19 401237085510001 INRB01-339 40 12 37 85 51 00 LAMBERSON DITCH 1300 FT US CR 700N NR AROMA, IN 20 392755086444401 INRB01-340 39 27 55 86 44 44 MILL CREEK 3800 FT US CR 1150N AT WALLACE JUNCTION21 384333087082001 INRB01-341 38 43 33 87 08 20 N FK PRARIE CK 3000 FT US CR 100E NR WASHINGTON, IN 

122 395935086163801 INRB01-342 39 59 35 86 16 38 EAGLE CREEK 2600 FT US WEST 146TH ST AT ZIONSVILLE, 

23 392116087052501 INRB01-344 39 21 16 87 05 25 TURKEY CREEK 500 FT US CR 665 NR SALINE CITY, IN 24 393402086384301 INRB01-346 39 34 02 86 38 43 MUD CREEK 5300 FT DS CR 1100W AT LITTLE POINT, IN 
Table 1. Location of Indiana Department of Environmental Management Watershed Monitoring Program sampling sites used in the breakpoint analy2001–05. —Continued[USGS, U.S. Geological Survey; STAID, station identification; IDEM, Indiana Department of Environmental Management; dd.mm.ss, degrees minutes seconds; CK, creek; FT, IN, Indiana; CR, county road; SR, state route; DS, downstream; INDPLS, Indianapolis; NR, Near; E, east; RD, road; FK, fork; N, North; MI, mile; USHWY, US highway; M, mbus, business]

Site 

identifier USGS STAID IDEM site number Latitude (dd.mm.ss) Longitude (dd.mm.ss) USGS station name 

25 401219085344901 INRB01-347 40 12 19 85 34 49 KILLBUCK CREEK 500 FT DS CR 800N NR GILMAN, IN 26 394307086474301 INRB01-348 39 43 07 86 47 43 BLEDSOE BRANCH 500 FT US CR 400N NR FILLMORE, IN 

127 395620085090801 INRB02-401 39 56 20 85 09 08 WHITEWATER R 400 FT DS HOOVER RD NR HAGERSTOWN128 394041084562001 INRB02-402 39 40 41 84 56 20 RICHLAND CK 3800 FT US CR 100W NR CLIFTON, IN 129 393827085001401 INRB02-403 39 38 27 85 00 14 E FK WHITEWATER R 2700 FT US SR 44 NR LIBERTY, IN 130 392010085163801 INRB02-404 39 20 10 85 16 38 SALT CK 1500 FT DS ENOCHSBURG RD AT ENOCHSBURG, I

31 393249085113501 INRB02-407 39 32 49 85 11 35 N BR GARRISON CK 200 FT DS CR 650S AT ALPINE, IN 

132 395649084545201 INRB02-408 39 56 49 84 54 52 FOUNTAIN CK AT WHITEWATER RD AT FOUNTAIN CITY, IN 133 395350085054001 INRB02-409 39 53 50 85 05 40 MORGAN CK 2000 FT DS SR 38 NR GREENS FK, IN 

34 392254084554401 INRB02-410 39 22 54 84 55 44 BIG CEDAR CK 1.8 MI US USHWY52 NR CEDAR GROVE, IN 

135 393609085125801 INRB02-411 39 36 09 85 12 58 FALL CK 1000 FT DS CR 425W NR COLUMBIA, IN 

36 392251085074801 INRB02-412 39 22 51 85 07 48 PIPE CK 900 FT US PUMPHOUSE RD NR OAK FOREST, IN 

137 395148085074801 INRB02-413 39 51 48 85 07 48 MARTINDALE CK 3900 FT US I-70 NR JACKSONBURG, IN 

38 393514084580001 INRB02-415 39 35 14 84 58 00 UNNAMED TRIB 1800 FT DS CR 175W NR ROSEBURG, IN 

139 395158084535701 INRB02-416 39 51 58 84 53 57 W FK E FK WHITEWATER R 2000 FT DS I-70 NR RICHMOND140 394735084561101 INRB02-417 39 47 35 84 56 10 LICK CK 2200 FT US ABINGTON PIKE NR RICHMOND, IN 141 393439085092401 INRB02-419 39 34 39 85 09 24 WHITEWATER R 1200 FT US CR 480S AT NULLTOWN, IN 142 392645085071101 INRB02-420 39 26 45 85 07 11 WHITEWATER R 1.6 MI DS USHWY 52 AT METAMORA, IN 

43 395344085064201 INRB02-421 39 53 44 85 06 42 OSER CK 2700 FT DS SR 38 NR HAGERSTOWN, IN 

144 392616085042301 INRB02-422 39 26 16 85 04 23 WHITEWATER R 4 MI DS USHWY 52 AT YELLOW BANK, IN 

45 393913084491301 INRB02-423 39 39 13 84 49 13 LITTLE FOUR MI CK 2 MI US SR 44 NR FAIRHAVEN, OH 46 394904085002401 INRB02-425 39 49 04 85 00 24 CROWN CK 400 FT DS MCMINN RD AT CENTERVILLE, IN 

147 394318085073301 INRB02-427 39 43 18 85 07 33 WHITEWATER R 1.4 MI US CR 440N AT BEESONS, IN 148 394649085023001 INRB02-429 39 46 49 85 02 30 NOLANDS FK 2600 FT DS MCCONAHA RD NR PINHOOK, IN 
Table 1. Location of Indiana Department of Environmental Management Watershed Monitoring Program sampling sites used in the breakpoint analy2001–05. —Continued [USGS, U.S. Geological Survey; STAID, station identification; IDEM, Indiana Department of Environmental Management; dd.mm.ss, degrees minutes seconds; CK, creek; FT, IN, Indiana; CR, county road; SR, state route; DS, downstream; INDPLS, Indianapolis; NR, Near; E, east; RD, road; FK, fork; N, North; MI, mile; USHWY, US highway; M, mbus, business] Site identifier USGS STAID IDEM site number Latitude (dd.mm.ss) Longitude (dd.mm.ss) USGS station name 

149 392142085152501 INRB02-430 39 21 42 85 15 25 SALT CK 2300 FT US CR 250W NR HAMBURG, IN 

50 393259084502801 INRB02-431 39 32 59 84 50 28 INDIAN CK 900 FT DS SAND RUN RD NR CONTRERAS, OH 

151 395301084511501 INRB02-432 39 53 01 84 51 15 M FK E FK WHITEWATER R 0.5 MI US SR 227 MIDDLEBORO152 394527084541701 INRB02-433 39 45 27 84 54 17 ELKHORN CK 5000 FT US USHWY 27 NR LOCUST GROVE, I

53 394545084540201 INRB02-434 39 45 45 84 54 02 ELKHORN CK 1.3 MI US USHWY 27 NR LOCUST GROVE, IN 

154 393450085061301 INRB02-435 39 34 50 85 06 14 WILSON CK 700 FT DS SR 1 NR EVERTON, IN 

55 392755085181001 INRB02-436 39 27 55 85 18 10 BULL FK 2 MI US STIPPS HILL RD NR BUENA VISTA, IN 

156 394550085073301 INRB02-437 39 45 50 85 07 33 WHITEWATER R 2 MI DS E MILTON RD NR MILTON, IN 157 392638085063101 INRB02-438 39 26 38 85 06 31 WHITEWATER R 2 MI DS USHWY 52 NR METAMORA, IN 158 392809085103601 INRB02-439 39 28 09 85 10 38 WHITEWATER R 2 MI DS LAUREL RD NR LAUREL, IN 159 395822084572701 INRB02-440 39 58 21 84 57 28 MORGAN CK 2600 FT US MEYERS RD NR WILLIAMSBURG, 160 395346085023501 INRB02-441 39 53 48 85 02 37 GREENS FK 1200 FT US SR 38 AT GREENS FK, IN 161 394147085064301 INRB02-443 39 41 47 85 06 43 WHITEWATER R 2900 FT DS CR 440N AT WATERLOO, IN 

62 394540085031701 INRB02-445 39 45 40 85 03 17 CENTERAL RUN 1.3 MI US CHAPEL RD NR PINHOOK, IN 

163 395651085222501 INRB02-501 39 56 51 85 22 26 BIG BLUE R 400 FT DS NRFK-WSTRN RR AT NEW CASTLE, 164 390637085350201 INRB02-502 39 06 36 85 35 02 SAND CK 1.5 RMI US CR 800N NR BREWERSVILLE, IN 165 392348085315501 INRB02-503 39 23 48 85 31 55 CLIFTY CK 840 FT US CR 400N NR ADAMS, IN 

66 384632086094201 INRB02-504 38 46 32 86 09 42 E FK WHITE R 1 RMI US MUSCATATUCK R NR MEDORA, IN 

167 392221085483701 INRB02-505 39 22 21 85 48 37 FLATROCK R 300 FT DS CR 150W NR FLATROCK, IN 

68 385657086275601 INRB02-506 38 56 57 86 27 56 LITTLE SALT CK 400 FT DS CR 650N NR COVEYVILLE, IN 

169 394628085321301 INRB02-509 39 46 28 85 32 13 BIG BLUE R 1 RMI DS CR 450W NR KNIGHTSTOWN, IN 

70 391917085520901 INRB02-510 39 19 17 85 52 09 FLATROCK R 1.5 RMI DS CR 900N AT ST LOUIS CROSSING 

171 385539085431501 INRB02-511 38 55 39 85 43 15 VERNON FK MUSC R 1.2 RMI US CR 500S NR HAYDEN, IN 

72 384810086284601 INRB02-512 38 48 10 86 28 46 E FK WHITE R 3 RMI DS GUTHRIE CK NR YOCKEY, IN 
Table 1. Location of Indiana Department of Environmental Management Watershed Monitoring Program sampling sites used in the breakpoint analy2001–05. —Continued[USGS, U.S. Geological Survey; STAID, station identification; IDEM, Indiana Department of Environmental Management; dd.mm.ss, degrees minutes seconds; CK, creek; FT, IN, Indiana; CR, county road; SR, state route; DS, downstream; INDPLS, Indianapolis; NR, Near; E, east; RD, road; FK, fork; N, North; MI, mile; USHWY, US highway; M, mbus, business]

Site 

identifier USGS STAID IDEM site number Latitude (dd.mm.ss) Longitude (dd.mm.ss) USGS station name 

73 385836086062401 INRB02-515 38 58 36 86 06 24 LITTLE SALT CK 1 RMI DS SR 258 AT FREETOWN, IN 74 383934086463201 INRB02-516 38 39 34 86 46 32 BEAVER CK 3000 FT DS SR 150 AT IRONTON, IN 

175 390659085383801 INRB02-518 39 06 59 85 38 38 WYALOOSING CK 1500 FT DS SR 3 NR SARDINIA, IN 176 390745085273801 INRB02-519 39 07 45 85 27 38 SUGAR CK 4000 FT US N FK MUSC R NR ZENAS, IN 177 392751085291801 INRB02-521 39 27 51 85 29 18 LITTLE FLATROCK R 700 FT US CR 1000S NR MILROY, IN 178 385730086102801 INRB02-522 38 57 30 86 10 28 S FK SALT CK 1 RMI DS SR 58 NR KURTZ, IN 179 384717085320901 INRB02-523 38 47 17 85 32 09 BIG CK 3000 FT US HARVERTS CK AT VOLGA, IN 

80 383107086502501 INRB02-524 38 31 07 86 50 25 E FK WHITE R 800 FT US WOLFE CK NR THALES, IN 

181 392508085545301 INRB02-525 39 25 08 85 54 53 BIG BLUE R 3 RMI US USHWY 65 NR MT AUBURN, IN 

82 384832086340901 INRB02-526 38 48 32 86 34 09 E FK WHITE R 2 RMI US CR 400S NR COXTON, IN 83 384838085383401 INRB02-527 38 48 32 85 38 34 BIG CK 1800 FT US SR 3 NR DEPUTY, IN 

184 382939087060901 INRB02-528 38 48 39 87 06 09 BEAR CK 200 FT DS CR 800N NR OTWELL, IN 

85 384635086041401 INRB02-530 38 46 35 86 04 14 MUSCATATUCK R 3 RMI US SR 135 NR MILLPORT, IN 86 390939086202001 INRB02-531 39 09 39 86 20 20 N FK SALT CK 2250 FT US SR 46 AT BELMONT, IN 87 384433086434501 INRB02-532 38 44 33 86 43 45 E FK WHITE R 2 RMI US DEVILS ELBOW NR HURON, IN 88 393950085544601 INRB02-533 39 39 50 85 54 46 SUGAR CK 1500 FT DS CR 1000N NR PLEASANT VIEW, IN 

189 390028085365701 INRB02-534 39 00 28 85 36 57 VERNON FK MUSC R 1150 FT US WWTF AT N VERNON, IN 190 391848085333801 INRB02-535 39 18 48 85 33 38 UNNAMED TRIB 3000 FT US SR 3 AT EWINGTON, IN 

91 384525086014401 INRB02-536 38 45 25 86 01 44 MUSCATATUCK R 1 RMI US DELANEY CK NR MILLPORT, IN 

192 393249085294401 INRB02-537 39 32 49 85 29 44 FLATROCK R 500 FT DS CR 450S NR MILROY, IN 

93 385607085325901 INRB02-539 38 56 07 85 32 59 GRAHAM CK 1.7 RMI US SR 7 AT WALNUT RIDGE, IN 94 392105085592401 INRB02-542 39 21 06 85 59 24 BIG BLUE R 2500 FT DS SR 31 AT EDINBURGH, IN 95 384858085525501 INRB02-543 38 53 04 85 35 05 VERNON FK MUSC R 2300 FT DS CR 530S NR RETREAT, IN 96 383726086202701 INRB02-544 38 37 26 86 20 26 LOST R 1.5 MI US POTATO RD NR ORLEANS, IN 
Table 1. Location of Indiana Department of Environmental Management Watershed Monitoring Program sampling sites used in the breakpoint analy2001–05. —Continued [USGS, U.S. Geological Survey; STAID, station identification; IDEM, Indiana Department of Environmental Management; dd.mm.ss, degrees minutes seconds; CK, creek; FT, IN, Indiana; CR, county road; SR, state route; DS, downstream; INDPLS, Indianapolis; NR, Near; E, east; RD, road; FK, fork; N, North; MI, mile; USHWY, US highway; M, mbus, business] Site identifier USGS STAID IDEM site number Latitude (dd.mm.ss) Longitude (dd.mm.ss) USGS station name 

97 392544085585801 INRB02-545 39 25 44 85 58 58 SUGAR CK 2600 FT DS USHWY 65 AT AMITY, IN 

198 403857085593501 INRB03-601 40 38 58 85 59 31 PIPE CK 100 FT US PIPE CK AT SANTA FE, IN 

99 401643084521501 INRB03-602 40 16 43 84 52 13 HARSHMAN CK 0.9 MI US MISSISSINEWA R NR SALEM, IN 

1100 404805086333701 INRB03-603 40 48 04 86 33 37 GALBREATH DITCH 0.5 MI DS CR 200N NR LK CICOTT, IN 1101 402554085305901 INRB03-604 40 25 54 85 30 53 MISSISSINEWA R 0.8 MI US SR 26 NR FOWLERTON, IN 

102 405236086495201 INRB03-605 40 52 36 86 49 53 BIG MONON CK 0.5 MI US SR 16 NR MONON, IN 

1103 405243085564701 INRB03-606 40 52 43 85 56 47 PAW PAW CK 0.3 MI US CR 800N NR ROANN, IN 1104 401943086385101 INRB03-607 40 19 43 86 38 50 S FK WILDCAT CK 0.6 MI US CR 800W NR MULBERRY, IN 

105 410301086184501 INRB03-608 41 02 59 86 18 42 MUD CK 0.3 MI US GRUBE DITCH NR PERSHING, IN 106 403712086593901 INRB03-609 40 37 11 86 59 39 MEYERS DITCH 820 FT US I-65 NR BADGER GROVE, IN 

1107 410543085373101 INRB03-610 41 05 42 85 37 27 CLEAR CK 980 FT US SPRING CK AT SOUTH WHITLEY, IN 1108 404156086024501 INRB03-611 40 41 57 86 02 48 LITTLE PIPE CK 900 FT DS CR 150E NR SOUTH PERU, IN 

109 403633085115401 INRB03-612 40 36 34 85 11 53 ROCK CK 770 FT US CR 900S NR PETROLEUM, IN 

1110 403542086305901 INRB03-613 40 35 42 86 30 59 DEER CK 0.7 MI US MERIDIAN LINE RD NR CAMDEN, IN 

1 111 405208085093701 INRB03-614 40 52 09 85 09 37 EIGHTMILE CK 0.4 MI US SR 1 AT OSSIAN, IN 

112 403603086325101 INRB03-615 40 36 03 86 32 51 DEER CK 0.6 MI DS SR 75 AT CAMDEN, IN 113 411707085593601 INRB03-616 41 17 12 85 59 45 EASTERDAY DITCH 0.3 MI DS CR 400N NR ATWOOD, IN 

1114 402612086094301 INRB03-617 40 26 12 86 09 40 E FK LITTLE WILDCAT CK 880 FT US CR200W AT ALTO, IN 1115 404912086080401 INRB03-619 40 49 14 86 08 03 UNNAMED TRIB 1.2 MI US EEL R AT MEXICO, IN 1116 410526085291501 INRB03-622 41 05 27 85 29 19 STONY CK 720 FT US MERIDIAN RD AT PEABODY, IN 1117 402423086423501 INRB03-623 40 24 23 86 42 38 MID FK WILDCAT CK 0.4 MI DS HOG RUN AT PETTIT, IN 

118 411753085493801 INRB03-624 41 17 52 85 49 39 TIPPECANOE R 880 FT DS CR 100E NR ISLAND PARK, IN 119 403639086402301 INRB03-625 40 36 39 86 40 23 WABASH R 1.9 MI US SR 39 NR DELPHI, IN 

120 404739085210101 INRB03-626 40 47 45 85 21 05 ROCK CK 0.4 MI US SR 3 NR MARKLE, IN 
Table 1. Location of Indiana Department of Environmental Management Watershed Monitoring Program sampling sites used in the breakpoint analy2001–05. —Continued[USGS, U.S. Geological Survey; STAID, station identification; IDEM, Indiana Department of Environmental Management; dd.mm.ss, degrees minutes seconds; CK, creek; FT, IN, Indiana; CR, county road; SR, state route; DS, downstream; INDPLS, Indianapolis; NR, Near; E, east; RD, road; FK, fork; N, North; MI, mile; USHWY, US highway; M, mbus, business]

Site 

identifier USGS STAID IDEM site number Latitude (dd.mm.ss) Longitude (dd.mm.ss) USGS station name 

121 402135086211701 INRB03-627 40 21 36 86 21 17 KILMORE CK 500 FT US CR 800E NR FOREST, IN 

1122 410048086350101 INRB03-628 41 00 48 86 35 00 MILL CK 0.6 MI US TIPPECANOE R NR WINAMAC, IN 1123 404248086341901 INRB03-629 40 42 48 86 34 18 UNNAMED TRIB 0.8 MI US BURNETTS CK AT LOCKPORT, IN 1124 404203085274901 INRB03-630 40 42 04 85 27 50 DETAMORE DITCH 700 FT DS I-69 NR WARREN, IN 1125 401517084495201 INRB03-631 40 15 18 84 49 53 LITTLE MISSISSINEWA R 2.8 MI DS SR28 NR COSMOS, OH 1126 402739085413701 INRB03-633 40 27 38 85 41 39 DEER CK 0.25 MI US CR 100W NR WEAVER, IN 1127 401401085413701 INRB03-634 40 13 58 85 09 58 ELKHORN CK 0.25 MI US CR 500N NR FARMLAND, IN 

128 405501086490201 INRB03-635 40 55 04 86 49 01 BIG MONON CK 0.2 MI US BIG MONON DITCH NR MONON, 129 402425084574101 INRB03-636 40 24 25 84 57 42 LITTLE SALAMONIE R 0.4 MI US CR 120S AT LIBER, IN 

1130 410106085191601 INRB03-638 41 01 07 85 19 15 ABOITE CK 0.3 MI US USHWY 24 AT TIMBERCREST, IN 

131 402710086510501 INRB03-639 40 27 10 86 51 04 WILDCAT CK 150 FT US SR 25 AT LAFAYETTE, IN 132 412029086435701 INRB04-701 41 20 29 86 43 57 KANAKEE R 1320 FT US SR39 NR HANNA, IN 133 410737087273101 INRB04-703 41 07 37 87 27 31 LAWLER D 2900 FT DS OF N400W AT LAKE VILLAGE, IN 134 411021087020901 INRB04-705 41 10 21 87 02 09 WOLF CK 60 FT DS E1100N NR WHEATFIELD, IN 135 412400086420601 INRB04-706 41 24 00 86 42 06 KANAKEE R 3.89 MI DS OF W1200S NR HANNA, IN 136 405002087233501 INRB04-708 40 50 02 87 23 35 IROQUOIS R 3430 FT US OF S100W NR BROOK, IN 137 411752087120701 INRB04-709 41 17 52 87 12 07 UNNAMED TRIB 900 FT US OF USHWY231 NR HEBRON, IN 138 412251086110301 INRB04-710 41 22 51 86 11 03 YELLOW R 1700 FT US OF E 8TH ST NR BREMEN, IN 139 403952087271401 INRB04-712 40 39 52 87 27 14 SUGAR CK 8120 FT DS OF N600W NR EARL PARK, IN 140 405728087033201 INRB04-713 40 57 28 87 03 32 RYAN D 4840 FT US OF S250W NR RENSSELAER, IN 141 413841086391401 INRB04-714 41 38 41 86 39 14 COLLINS D 3100 FT US OF SR2 NR LA PORTE, IN 142 412118087182401 INRB04-715 41 21 18 87 18 24 STONY RUN 60 FT US OF IOWA ST NR CROWN POINT, IN 143 404940087182801 INRB04-716 40 49 40 87 18 28 WEISS D 510 FT DS OF SR 55 NR BROOK, IN 144 411619086501501 INRB04-717 41 16 19 86 50 15 KANAKEE R 3890 FT DS OF S650W AT ENGLISH LAKE, IN 
Table 1. Location of Indiana Department of Environmental Management Watershed Monitoring Program sampling sites used in the breakpoint analy2001–05. —Continued [USGS, U.S. Geological Survey; STAID, station identification; IDEM, Indiana Department of Environmental Management; dd.mm.ss, degrees minutes seconds; CK, creek; FT, IN, Indiana; CR, county road; SR, state route; DS, downstream; INDPLS, Indianapolis; NR, Near; E, east; RD, road; FK, fork; N, North; MI, mile; USHWY, US highway; M, mbus, business] Site identifier USGS STAID IDEM site number Latitude (dd.mm.ss) Longitude (dd.mm.ss) USGS station name 

145 411814086334801 INRB04-718 41 18 14 86 33 48 EAGLE CK 150 FT DS OF N700E NR KNOX, IN 146 411056087204401 INRB04-719 41 10 56 87 20 44 KANAKEE R 1370 FT DS OF SR55 AT SHELBY, IN 147 403551087282201 INRB04-720 40 35 51 87 28 22 MINIER LATERAL 960 FT US S800W NR FREELAND PARK, IN 148 412247087081101 INRB04-723 41 22 47 87 08 11 WOLF CK 6320 FT DS OF W300S NR KOUTS, IN 149 405127087211401 INRB04-724 40 51 27 87 21 14 IROQUOIS R 2150 FT US E LK KENOYER RD AT BROOK, IN 150 411541087024601 INRB04-725 41 15 41 87 02 46 KANAKEE R 4320 FT DS OF SR49 NR KOUTS, IN 151 405248087262301 INRB04-727 40 52 48 87 26 23 CLARK D 1770 FT US OF S325W AT ADE, IN 152 404335087232101 INRB04-728 40 43 35 87 23 21 UNNAMED TRIB 4400 FT US OF W1800S NR KENTLAND, IN 153 405552087102801 INRB04-729 40 55 52 87 10 28 IROQUOIS R 5700 FT DS OF USHWY231 AT RENSSELAER, IN 154 405210087043401 INRB04-732 40 52 10 87 04 34 HOWE D 850 FT DS OF SR 16 NR RENSSELAER, IN 155 411556086513401 INRB04-733 41 15 56 86 51 34 KANAKEE R 2 MI DS S650W NR ENGLISH LAKE, IN 156 411635086265901 INRB04-734 41 16 35 86 26 59 YELLOW R 2650 FT US OF S UPAS RD NR CULVER, IN 157 411324087300401 INRB04-735 41 13 24 87 30 04 WEST CK 3750 US OF W223RD AV NR SCHNEIDER, IN 158 413216086262301 INRB04-736 41 32 16 86 26 23 POTATO CK 1830 FT US SMILAX RD AT NORTH LIBERTY, IN 159 412759086453401 INRB04-738 41 27 59 86 45 34 MILL CK 770 FT US OF LONG LANE NR UNION MILLS, IN 160 411514087054501 INRB04-741 41 15 14 87 05 45 HODGE D 2230 FT US N300W NR WHEATFIELD, IN 161 412211086145001 INRB04-742 41 22 11 86 14 50 YELLOW R 3360 FT DS OF N JARRAH RD NR PLYMOUTH, IN 162 394017087302701 INRB04-805 39 40 17 87 30 27 BROUILLETS CK 3760 FT US OF SR163 AT BLANFORD, IN 163 385709087190101 INRB04-808 38 57 09 87 19 01 MARLA CK 500 FT US OF CR 500E NR CARLISLE, IN 164 400204087175301 INRB04-810 40 02 04 87 17 53 PRAIRIE CK 1000 FT US OF S170W NR YEDDO, IN 165 380500087555301 INRB04-812 38 05 00 87 55 53 HAWTHORNE CK 2170 FT DS OLD SAND RD AT NEW HARM166 400753086324501 INRB04-815 40 07 53 86 32 45 SPRING CK 6000 FT DS NORTH RD AT GARDEN PARK, IN 167 395117086531201 INRB04-817 39 51 17 86 53 12 BIG RACCOON CK 2900 FT US USHWY 231 AT RACCOON, IN 168 395506087143101 INRB04-819 39 55 06 87 14 31 W PRONG GREEN CK 1030 FT DS USHWY 41 NR KINGMAN, 
Table 1. Location of Indiana Department of Environmental Management Watershed Monitoring Program sampling sites used in the breakpoint analy2001–05. —Continued[USGS, U.S. Geological Survey; STAID, station identification; IDEM, Indiana Department of Environmental Management; dd.mm.ss, degrees minutes seconds; CK, creek; FT, IN, Indiana; CR, county road; SR, state route; DS, downstream; INDPLS, Indianapolis; NR, Near; E, east; RD, road; FK, fork; N, North; MI, mile; USHWY, US highway; M, mbus, business]

Site 

identifier USGS STAID IDEM site number Latitude (dd.mm.ss) Longitude (dd.mm.ss) USGS station name 

169 375936087434901 INRB04-820 37 59 36 87 43 49 LITTLE CK 1500FT US WILDEMAN RD AT ST PHILLIP, IN 170 394256087260001 INRB04-821 39 42 56 87 26 00 UNNAMED TRIB 600 FT US OF E1150S NR CLINTON, IN 171 403034086504401 INRB04-823 40 30 34 86 50 44 BURNETT CK 160 FT US NORTHEAST RD AT BATTLE GROU172 383357087361701 INRB04-824 38 33 57 87 36 17 SWAN POND D 790 FT DS S6TH ST RD NR ST FRANCISVILLE173 402248087290801 INRB04-826 40 22 48 87 29 08 JORDAN CK 4125 FT DS OF N800W NR TAB, IN 174 401533086201701 INRB04-827 40 15 33 86 20 17 SCOTT WINCOOP D 230 FT DS 900E NR HILLISBURG, IN 175 384046087322101 INRB04-828 38 40 46 87 32 21 WABASH R 1400 FT DS OF USHWY 50 BUS AT VINCENNES, 176 393931087174801 INRB04-829 39 39 31 87 17 48 ROCK RUN 1900 FT DS OF S325W NR ROSEDALE, IN 177 391444087185101 INRB04-830 39 14 44 87 18 51 BUSSERON CK 600 FT US CR 1100N NR FARMERSBURG, IN 178 381003087510301 INRB04-832 38 10 03 87 51 03 UNNAMED TRIB 2900 FT US NEW HARMONY RD STEWART179 402122087190901 INRB04-834 40 21 22 87 19 09 BIG PINE CK 2300 FT DS OF W300N NR CARBONDALE, IN 180 375434088010601 INRB04-836 37 54 34 88 01 06 WABASH R 2.72 MI DS OF SR62 NR MT VERNON, IN 181 394855087025501 INRB04-841 39 48 55 87 02 55 S FK LITTLE RACCOON CK 200 FT DS N1000E NR MILLIGAN182 400252087255101 INRB04-842 40 02 52 87 25 51 WABASH R 830 FT DS OF SR32 AT PERRYSVILLE, IN 183 403351087084501 INRB04-843 40 33 51 87 08 45 LITTLE PINE CK 3000 FT US OF CR 300S NR OXFORD, IN 184 385114087320601 INRB04-844 38 51 14 87 32 06 WABASH R 13.6 MI US OF USHWY50 NR RUSSELLVILLE, IN 185 393948087045101 INRB04-845 39 39 48 87 04 51 ROCKY FORK CK 125 FT DS GREENCASTLE RD NR MANSF186 391647087363201 INRB04-846 39 16 47 87 36 32 WABASH R 21.2 MI DS OF I-70 AT DARWIN, IL 187 411545084562601 INRB05-009 41 15 45 84 56 26 ST JOSEPH RIVER 800 FT US CUBA RD NR GRABILL, IN 188 413836085385001 INRB05-018 41 38 36 85 38 50 LITTLE ELKHART R 200 FT US CR 1150 W NR MIDDLEBURY189 412805085355901 INRB05-023 41 28 05 85 35 59 ELKHART RIVER 3900 FT DS SR 5 AT LIGONIER, IN 190 405814084512701 INRB05-024 40 58 14 84 51 27 FLATROCK CREEK 2100 FT DS CR 101 AT MONROEVILLE, IN 191 413856086032001 INRB05-026 41 38 56 86 03 20 BAUGO CREEK 4100 FT US ASH ROAD AT OSCEOLA, IN 192 414137085182601 INRB05-029 41 41 37 85 18 26 PIGEON RIVER 2400 FT US CR 600 EAST NEAR MONGO, IN 
Table 1. Location of Indiana Department of Environmental Management Watershed Monitoring Program sampling sites used in the breakpoint analy2001–05. —Continued [USGS, U.S. Geological Survey; STAID, station identification; IDEM, Indiana Department of Environmental Management; dd.mm.ss, degrees minutes seconds; CK, creek; FT, IN, Indiana; CR, county road; SR, state route; DS, downstream; INDPLS, Indianapolis; NR, Near; E, east; RD, road; FK, fork; N, North; MI, mile; USHWY, US highway; M, mbus, business] Site identifier USGS STAID IDEM site number Latitude (dd.mm.ss) Longitude (dd.mm.ss) USGS station name 

193 412750087140001 INRB05-030 41 27 50 87 14 00 DEEP RIVER 3600 FT DS RANDOLPH ST AT DEEP RIVER, IN 194 414143085584801 INRB05-042 41 41 43 85 58 48 CHRISTIANA CREEK 1300FT US N MAIN ST AT ELKHART, IN 195 414224086461401 INRB05-047 41 42 24 86 46 14 E BR TRAIL CK 1830 FT US CR400 W AT SPRINGFIELD, IN 196 414046086493201 INRB05-052 41 40 46 86 49 32 UNNAMED TRIB 20FT US I-94 AT ORCHARD HIGHLANDS, I197 412718085502501 INRB05-061 41 27 18 85 50 25 KIEFFER D 20 FT US OLD STATE RD NR MILFORD JUNCTIO198 382108086164601 INRB05-103 38 21 08 86 16 46 BLUE R 230 FT DS OF SR 64 AT MILLTOWN, IN 199 383339085454001 INRB05-104 38 33 39 85 45 40 MILLER FK 1680 FT US HEBRON CHURCH RD AT HENRYVI200 382806085470801 INRB05-106 38 28 06 85 47 08 UNNAMED TRIB 200FT US EBENEZERCHURCH RD NR MEM201 375731086420401 INRB05-109 37 57 31 86 42 04 UNNAMED TRIB 950 FT DS OF ASTER RD NR TELL CITY, IN 202 382151085561201 INRB05-110 38 21 51 85 56 12 INDIAN CK 875 FT DS OF NAVILLETON RD AT GALENA, IN 203 380537086290701 INRB05-111 38 05 37 86 29 07 LITTLE OIL CK 975 FT DS OF PARKS RD NR MAGNET, IN 204 390432085070401 INRB05-112 39 04 32 85 07 04 SOUTH HOGAN CK 6100 FT DS OF SR 101 NR MILAN, IN 205 380309085594301 INRB05-113 38 03 09 85 59 43 MOSQUITO CK 1.2MI DS BUENA VISTA RD NR BUENA VIST206 391155084542401 INRB05-116 39 11 55 84 54 24 BRUSHY FK 1230FT US SAWDON RIDGE RD NR GUILFORD207 381121086184001 INRB05-119 38 11 21 86 18 40 BLUE R 0.6MI DS OLD FOREST RD SW NR LEAVENWORTH, 208 381345086072001 INRB05-121 38 13 45 86 07 20 INDIAN CK 8730 FT US OF SR337 AT CORYDON, IN 209 384615085243501 INRB05-122 38 46 15 85 24 35 DEANS BR 1050 FT US OF SR 1 AT NORTH MADISON, IN 210 390511085032701 INRB05-124 39 05 11 85 03 27 ALLEN BR 4450FT US OF IRELAND RD NR MOORES HILL, I

211 380620087041401 INRB05-125 38 06 20 87 04 14 LITTLE PIGEON CK 0.2MI US PIGEON SWITCH GENTRYVLL

212 383221085352801 INRB05-126 38 32 21 85 35 28 FOURTEENMILE CK 3140FT US ROGERS RUN NR NEW MAR213 380926086344501 INRB05-127 38 09 26 86 34 45 OIL CK 5580 DS OF BRANCHVILLE RD AT BRANCHVILLE, I214 385822085024401 INRB05-128 38 58 22 85 02 44 HAYES BR 1620 FT DS W LAUGHERY CK RD NR MILTON, IN 215 391015084523101 INRB05-132 39 10 15 84 52 31 SALT FK 7380 FT US OF SR 1 NR LAWRENCEBURG, IN 216 390707084521701 INRB05-136 39 07 07 84 52 17 TANNERS CK 6300 FT US SCHENLEY PL AT GREENDALE, IN 
Table 1. Location of Indiana Department of Environmental Management Watershed Monitoring Program sampling sites used in the breakpoint analy2001–05. —Continued[USGS, U.S. Geological Survey; STAID, station identification; IDEM, Indiana Department of Environmental Management; dd.mm.ss, degrees minutes seconds; CK, creek; FT, IN, Indiana; CR, county road; SR, state route; DS, downstream; INDPLS, Indianapolis; NR, Near; E, east; RD, road; FK, fork; N, North; MI, mile; USHWY, US highway; M, mbus, business]

Site 

identifier USGS STAID IDEM site number Latitude (dd.mm.ss) Longitude (dd.mm.ss) USGS station name 

217 380313087075701 INRB05-141 38 03 13 87 07 57 LITTLE PIGEON CK 4550FT US E525 RD NR TENNYSON, IN 218 382349085433601 INRB05-142 38 23 49 85 43 36 SILVER CK 5850FT DS GREENLEAF DR AT SELLERSBURG, I219 382309086145001 INRB05-145 38 23 09 86 14 50 BLUE R 2 MI US OF E TOTTEN FORD RD NR MILLTOWN, IN 220 390550085144001 INRB05-148 39 05 50 85 14 40 LAUGHERY CK 4.3 MI US E PERRY ST NR VERSAILLES, IN 221 382620086032101 INRB05-150 38 26 20 86 03 21 BEAR CK 730FT US E MARTINSBURG FIRE RD MARTINSBU222 381333086164201 INRB05-153 38 13 33 86 16 42 BLUE R 3.64 MI DS OF SR 462 NR LEAVENWORTH, IN 223 382852085421201 INRB05-156 38 28 52 85 42 12 SUGAR RUN 760 FT DS OF SR 160 NR CHARLESTOWN, IN 224 381947086283401 INRB05-157 38 19 47 86 28 34 LITTLE BLUE R 4200FT DS OF SPEARS ST AT ENGLISH, IN 225 385130085152601 INRB05-158 38 51 30 85 15 26 INDIAN KENTUCK CK 8070 FT DS OF SR 62 NR CANAAN, IN 226 380443086464901 INRB05-159 38 04 43 86 46 49 ANDERSON R 1500FT US N AVERY RIDGE RD NR HUFFMAN227 385955084565501 INRB05-162 38 59 55 84 56 55 LAUGHERY CK 4900 FT DS OF COLE LANE AT HARTFORD, 228 383640085324401 INRB05-164 38 36 40 85 32 44 UNNAMED TRIB 2100FT US SR 362 NR NEW WASHINGTON, 229 381044086374601 INRB05-167 38 10 44 86 37 46 WINDING BR 3630 FT US OF CR46 NR APALONA, IN 230 384635085044401 INRB05-172 38 46 35 85 04 44 INDIAN CK 9200 FT US OF KNOX FORD RD NR VEVAY, IN 231 382341086150801 INRB05-179 38 23 41 86 15 08 BLUE R 4.1MI US OF E TOTTEN FORD RD NR MILLTOWN, IN 232 381705086163001 INRB05-185 38 17 05 86 16 30 BLUE R 1.35 MI US OF CR 30 NR MILLTOWN, IN 

1 Invertebrate community sample collected. 
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Caskey and others—Analysis and Assessment of Selected Variables on Macroinvertebrate and Fish Communities in Indiana—Scientific Investigations Report 2010–5026

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