U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2012–5243

Prepared in cooperation with the Indiana Department of Environmental Management, 

Office of Water Quality 

Identifying Nutrient Reference Sites in Nutrient-Enriched 

Regions: Using Algal, Invertebrate, and Fish-Community 

Measures to Identify Stressor-Breakpoint Thresholds in 

Indiana Rivers and Streams, 2005–9 
Cover images: 

Upper left: Indian Creek near Williams, Indiana, June 5, 2007. (Photograph courtesy of Indiana Department of Environmental 

Management (IDEM)).

Upper right: West Fork Busseron Creek near Hymera, Ind., August 10, 2009. (Photograph courtesy of IDEM).

Lower left: Patoka River 1.1 river miles upstream of Dubois Road northeast near Dubois, Ind., September 7, 2006. (Photograph 

courtesy of IDEM).

Lower right: Patoka River 0.1 river miles downstream of Dubois Road northeast near Dubois, Ind., August 22, 2006. 

(Photograph courtesy of IDEM).
Identifying Nutrient Reference Sites 

in Nutrient-Enriched Regions: Using 

Algal, Invertebrate, and Fish-Community 

Measures to Identify Stressor-Breakpoint 

Thresholds in Indiana Rivers and Streams, 

2005–9 

By Brian J. Caskey, Aubrey R. Bunch, Megan E. Shoda, Jeffrey W. Frey, 

Shivi Selvaratnam, and Robert J. Miltner 

Prepared in cooperation with the Indiana Department of Environmental 

Management, Office of Water Quality

Scientific Investigations Report 2012–5243

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: 2013

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Suggested citation:

Caskey, B.J., Bunch, A.R., Shoda, M.E., Frey, J.W., Selvaratnam, Shivi, and Miltner, R.J., 2013, Identifying nutrient 

reference sites in nutrient-enriched regions—Using algal, invertebrate, and fish-community measures to identify 

stressor-breakpoint thresholds in Indiana rivers and streams, 2005–9: U.S. Geological Survey Scientific Investigations 

Report 2012–5243, 28 p., plus CD-ROM containing 11 appendixes. 
iii

Acknowledgments

The authors could not mention everyone who contributed to this multi-year study. However, the 

authors specifically thank the scientists from the Indiana Department of Environmental Management (IDEM) and U.S. Geological Survey (USGS) for their commitment to collecting and processing the data. The authors also would like to specifically thank Kristen Arnold, Todd Davis, Paul 

McMurray, and Stacey Sobat for their assistance in analytical design and technical reviews of 

the report; and Terry R. Maret and Michael R. Meador for their technical reviews.
iv

Contents

Acknowledgments........................................................................................................................................iii

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

Introduction.....................................................................................................................................................2

Purpose and Scope ..............................................................................................................................4

Description of Study Area ...................................................................................................................4

Study Methods ...............................................................................................................................................4

Site Selection and Sampling Strategies ...........................................................................................4

Basin Delineation and Land Use ........................................................................................................6

Data Collection......................................................................................................................................6

Nutrients and Water-Chemistry Samples................................................................................6

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

Invertebrate Samples..................................................................................................................7

Fish-Community Samples ...........................................................................................................7

Calculation of Invertebrate and Fish-Community Index.................................................................8

Data Analysis..................................................................................................................................................8

Data Censoring......................................................................................................................................8

Resolving Multiple Water-Chemistry Reporting Limits for Multiple Laboratories ............8

Influence of Basin Size on the Biological-Community Composition ............................................8

Reducing Variability within the Invertebrate- and Fish-Community Data...................................9

Nutrient and Water-Quality Variables ...............................................................................................9

Invertebrate- and Fish-Community Indexes.....................................................................................9

Nutrient and Biological Breakpoints .................................................................................................9

Additive Quantile Regression Models.............................................................................................10

Differences in Biological Communities Based on Nutrient Groups ...........................................10

Understanding Trophic Condition in Low Nutrient Sites ..............................................................11

Differentiation of Datasets .........................................................................................................................11

Comparison of Nutrient Concentrations by Nutrient Group .................................................................11

Headwater Sites..................................................................................................................................11

Wadable Sites .....................................................................................................................................11

Breakpoint Thresholds................................................................................................................................14

Development of Quantile Regression Models for Nutrient Categories ..............................................16

Comparison of Biological Communities within Nutrient Groups .........................................................16

Differentiation of Oligotrophic and Nutrient Uptake Sites....................................................................16

Low Nutrient Group Invertebrate-Community Analysis ...............................................................19

Low Nutrient Group Fish-Community Analysis ..............................................................................19

Land-Use Differences in the Low Nutrient Group.........................................................................19

Limitations of This Study.............................................................................................................................20

Major Findings and Implications for Developing Nutrient Criteria......................................................21

Conclusions...................................................................................................................................................23

References Cited..........................................................................................................................................23

Appendixes ...................................................................................................................................................28
v

Figures

1. Nutrient-algal biomass conceptual diagram illustrating the relations between 

nutrient concentrations and algal biomass..............................................................................3

2. Map showing location of the 318 Indiana Department of Environmental 

Management Probabilistic Monitoring Program sample sites used in the 

assessment of nutrient-enrichment conditions, 2005–9 ........................................................5

3. Boxplot showing log transformed distribution of mean total nitrogen 

concentrations in three nutrient groups (Low, Medium, and High) based on 

nutrient distribution for the selected datasets in the nutrient-enrichment study, 

2005–9 ...........................................................................................................................................12

4. Boxplot showing log transformed distribution of mean total phosphorus 

concentrations in three nutrient groups (Low, Medium, and High) based on 

nutrient distribution for the selected datasets in the nutrient-enrichment study, 

2005–9 ...........................................................................................................................................12

5. Boxplot showing log transformed distribution of mean periphyton chlorophyll a

concentrations in three nutrient groups (Low, Medium, and High) based on 

nutrient distribution for the selected datasets in the nutrient-enrichment study, 

2005–9 ...........................................................................................................................................13

6. Boxplot showing log transformed distribution of mean turbidity concentrations 

in three nutrient groups (Low, Medium, and High) based on nutrient distribution 

for the selected datasets in the nutrient-enrichment study, 2005–9..................................13

7. Graphs showing Gaussian distribution lines of the total number of invertebrate 

and fish breakpoint threshold concentrations calculated for the headwater 

and wadable site datasets. A, total nitrogen. B, total phosphorus. C, periphyton 

chlorophyll a. D, turbidity...........................................................................................................15

Tables

1. Summary statistics for the stressor variables for headwater and 

wadable sites, 2005–9 ................................................................................................................14

2. Mean breakpoint threshold summary for the stressor variables, 2005–9.........................15

3. Summary of the most similar breakpoint-threshold concentrations and 

quantile-threshold concentrations from the additive quantile regression 

analysis for the headwater and wadable stream types used in the nutrientenrichment study, 2005–9 ..........................................................................................................17

4. Analysis of Similarity (ANOSIM) results for pairwise tests of invertebrate and 

fish communities in Low, Medium, and High total nitrogen and total phosphorus 

groups for headwater and wadable sites, 2005–9 ................................................................17

5. Species list of the 10 most dominant taxa in the 3 nutrient groups (Low, Medium, 

and High) based on nutrient distribution for the nutrient-enrichment study, 2005–9......18

6. Analysis of Similarity (ANOSIM) results for pairwise tests of invertebrate and 

fish communities based on periphyton chlorophyll a categories at low nutrient 

sites, 2005–9.................................................................................................................................19

7. Average dissimilarity and contributing percentage statistics from Similarity 

Percentages (SIMPER) analysis for invertebrate and fish communities based 

on periphyton chlorophyll a categories at low nutrient sites, 2005–9 ...............................20
vi

Conversion Factors and Abbreviations

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

millimeter (mm) 0.03937 inch (in.)

meter (m) 3.281 foot (ft)

micrometer (μm) 0.001 millimeter (mm)

kilometer (km) 0.6214 mile (mi)

Area

square kilometer (km2) 247.1 acre

square kilometer (km2) 0.3861 square mile (mi2) 

Volume

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

liter (L) 0.2642 gallon (gal)

Flow rate

foot per second (ft/s) 0.3048 meter per second (m/s)

Mass

gram (g) 0.03527 ounce, avoirdupois (oz)

pound per square mile (lb/mi2) 0.1751 kilograms per square kilometers 

(kg/km2)

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).
vii

List of abbreviations used in this report:

ANOSIM Analysis of similarity

CHLa chlorophyll a

CPUE catch per unit of effort

CWA Clean Water Act

EMAP Environmental Monitoring Assessment Program

EPA U.S. Environmental Protection Agency

IBI Index of Biotic Integrity

IDAS Invertebrate Data Analysis System 

IDEM Indiana Department of Environmental Management

MDS Multi-Dimensional Scaling N nitrogen

NASS National Agricultural Statistics Service

NAWQA National Water-Quality Assessment program

NWQL National Water Quality Laboratory P phosphorus

PMP Probabilistic Monitoring Program

QA quality assurance

SIMPER Similarity Percentages 

TKN Total Kjeldahl nitrogen

TN total nitrogen

TP total phosphorus

USGS U.S. Geological Survey

Identifying Nutrient Reference Sites in Nutrient-Enriched 

Regions: Using Algal, Invertebrate, and Fish-Community 

Measures to Identify Stressor-Breakpoint Thresholds in 

Indiana Rivers and Streams, 2005–9 

By Brian J. Caskey,1 Aubrey R. Bunch,1 Megan E. Shoda,1 Jeffrey W. Frey,1 Shivi Selvaratnam,2 and 

Robert J. Miltner 3 

____________

1

USGS Indiana Water Science Center, Indianapolis, Ind.

2

Indiana Department of Environmental Management, Office of Water 

Quality, Indianapolis, Ind.

3

Ohio Environmental Protection Agency, Groveport, Ohio.

Abstract

Excess nutrients in aquatic ecosystems can lead to shifts 

in species composition, reduced dissolved oxygen concentrations, fish kills, and toxic algal blooms. In this study, nutrients, 

periphyton chlorophyll a (CHLa), and invertebrate- and fishcommunity data collected during 2005–9 were analyzed from 

318 sites on Indiana rivers and streams. The objective of this 

study was to determine which invertebrate and fish-taxa attributes best reflect the conditions of streams in Indiana along a 

gradient of nutrient concentrations by (1) determining statistically and ecologically significant relations among the stressor 

(total nitrogen, total phosphorus, and periphyton CHLa) and 

response (invertebrate and fish community) variables; and 

(2) determining the levels at which invertebrate- and fish-community measures change in response to nutrients or periphyton 

CHLa. 

For water samples at the headwater sites, total nitrogen 

(TN) concentrations ranged from 0.343 to 21.6 milligrams 

per liter (mg/L) (median 2.12 mg/L), total phosphorus (TP) 

concentrations ranged from 0.050 to 1.44 mg/L (median 

0.093 mg/L), and periphyton CHLa ranged from 0.947 to 

629 mg/L (median 69.7 mg/L). At the wadable sites, TN 

concentrations ranged from 0.340 to 10.0 mg/L (median 

2.31 mg/L), TP concentrations ranged from 0.050 to 

1.24 mg/L (median 0.110 mg/L), and periphyton CHLa

ranged from 0.383 to 719 mg/L (median 44.7 mg/L). 

Recursive partitioning identified statistically significant 

low and high breakpoint thresholds on invertebrate and fish 

measures, which demonstrated the ecological response in 

enriched conditions. The combined community (invertebrate 

and fish) mean low and high TN breakpoint thresholds were 

1.03 and 2.61 mg/L, respectively. The mean low and high 

breakpoint thresholds for TP were 0.083 and 0.144 mg/L, 

respectively. The mean low and high breakpoint thresholds for 

periphyton CHLa were 20.9 and 98.6 milligrams per square 

meter (mg/m2 ), respectively. Additive quantile regression 

analysis found similar thresholds (TN of 0.656 mg/L, mean TP 

of 0.118 mg/L, and periphyton CHLa of 27.2 mg/m2 ) for some 

stressor variables as determined by the breakpoint analysis.

The TN and TP concentrations in this study showed a 

nutrient gradient that spanned three orders of magnitude. Sites 

were divided into Low, Medium, and High nutrient groups 

based on the 10th and 75th percentiles. The invertebrate and 

fish communities were similar along the nutrient gradient, 

using an analysis of similarity, demonstrating there was not a 

species trophic gradient. Within all nutrient groups, invertebrate and fish communities were dominated by nutrient tolerant taxa (algivores, herbivores, and omnivores) that included 

invertebrates, such as Cheumatopsyche sp., Physella sp., and 

fish such as Stonerollers (Campostoma spp.) and Bluntnose 

Minnow (Pimephales notatus). 

To determine if low nutrient concentrations at some sites 

were caused by algal uptake and not oligotrophic conditions, 

sites with low nutrient concentrations (less than 10th percentile for TN or TP) were examined based on the Low (less 

than or equal to the 10th percentile) and High (greater than 

the 75th percentile) periphyton CHLa concentrations. Within 

low nutrient sites, the invertebrate and fish communities 

were statistically different between Low and High periphyton 

CHLa categories. The majority of variance between the Low 

and High periphyton CHLa categories was caused by Cheumatopsyche sp. (caddisfly), Physella sp. (pulmonate snail), 

and Caenis latipennis (a mayfly) in the invertebrate community; and caused by Stonerollers, Western Blacknose Dace 

(Rhinichthys atratulus meleagris), and Creek Chub (Semotilus 

atromaculatus) in the fish community. The dominance of tolerant herbivore and omnivore taxa in the High periphyton CHLa
2 Identifying Nutrient Reference Sites in Nutrient-Enriched Regions: Indiana Rivers and Streams, 2005–9

group indicates that low nutrient concentrations are a result of 

nutrient uptake and increased algal growth. This study highlights the importance of assessing multiple lines of evidence 

when attempting to identify the trophic condition of a site. 

Introduction

Anthropogenic activities have exposed many freshwater 

ecosystems to excessive nutrient inputs. Nutrients are essential to the health and growth of plants and animals; however, 

large amounts can be detrimental to aquatic ecosystems. The 

U.S. Environmental Protection Agency (EPA) listed nutrients as the second leading cause of impairment in rivers and 

streams in the United States (U.S. Environmental Protection 

Agency, 2006). Excess nutrients—primarily nitrogen (N) and 

phosphorus (P)—have been linked to nutrient enrichment of 

aquatic systems. Nutrient enrichment can lead to shifts in species composition, reduced dissolved oxygen concentrations, 

fish kills, and toxic algae blooms; and also results in taste and 

odor problems if the system is used as a drinking water source 

(U.S. Environmental Protection Agency, 2000a, b, c; Munn 

and Hamilton, 2003).

The Clean Water Act (CWA) was enacted to help protect 

aquatic ecosystems in the United States by maintaining and 

restoring the chemical, physical, and biological integrity of 

the Nation’s water. Organic enrichment, oxygen depletion, and 

excessive nutrients are the leading causes that result in many 

freshwater systems being placed on the CWA Section 303(d) 

list of impaired water bodies for failing to meet the goals 

outlined in the CWA (U.S. Environmental Protection Agency, 

2009). Nationwide, 16 percent of streams have been assessed 

(over 908,000 kilometers (km)), and 44 percent of those are 

listed as impaired (U.S. Environmental Protection Agency, 

2009). 

The Midwestern States (Illinois, Indiana, Iowa, Michigan, 

Minnesota, Ohio, and Wisconsin) have some of the highest 

concentrations of nutrients (N and P) in streams in the United 

States. Of these Midwestern States, Illinois, Indiana, and Iowa 

have the highest nutrient-input rates. In Indiana, the annual 

amount of nutrient inputs from farm and nonfarm fertilizer, manure, atmospheric deposition, and sewage have been 

estimated to range from greater than 10,000 to greater than 

40,000 pounds per square mile (lb/mi2) of N, and greater than 

340 to greater than 2,730 lb/mi2 of P (Ruddy and others, 2006; 

Dubrovsky and others, 2010). Excess nutrient inputs have 

resulted in many rivers and streams with nutrient enriched 

ambient concentrations. This enrichment has resulted in many 

biological communities in Indiana and other Midwestern 

streams being dominated by nutrient tolerant taxa (Frey and 

Caskey, 2007; Caskey and others, 2010; Frey and others, 

2011), making it difficult to find acceptable nutrient reference 

sites.

In 2000, the EPA began to develop criteria for total 

nitrogen (TN), total phosphorus (TP), periphyton and seston 

chlorophyll a (CHLa), and turbidity to address nutrient related 

impairments. Stressor-response studies were designed to verify 

the criteria by observing changes in the response variable 

(biological measures) based on exposure to the stressor variable (nutrients). In rivers and streams, correlations between 

nutrient concentrations, CHLa, and biological measures 

are not consistent across studies. Some studies in temperate streams identified a significant relation between nutrients 

and periphyton CHLa (Van Nieuwenhuyse and Jones, 1996; 

Dodds and others, 1997). However, many studies show that in 

nutrient rich streams, like those examined in this study, there 

are limited, weak, or no significant relations between nutrients 

and periphyton or seston CHLa concentrations (FigueroaNieves and others, 2006; Caskey and others, 2007; Frey and 

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

Royer and others, 2008). When the nutrient/periphyton CHLa

relation is examined using larger datasets from streams nationwide, the relation remains weak, possibly because of regional 

variability (Dodds and others, 1997). 

Dynamic interactions among physical, anthropogenic, 

and biological factors can alter nutrient and algal concentrations within freshwater ecosystems (fig. 1). One such interaction is nutrient uptake, the process whereby algae and aquatic 

plants metabolize nutrients (uptake) in the stream, resulting in 

reduced ambient nutrient concentrations (Marcarelli and others, 2009). Failing to take into account factors such as nutrient 

uptake could possibly underestimate the trophic condition of a 

stream (Porter and others, 2008; Munn and others, 2010; Frey 

and others, 2011). One way to address this possible misclassification of trophic condition in streams is to include measures 

of algal productions, such as CHLa, when assessing streams. 

Nutrient uptake by algae and macrophytes is required for 

growth and metabolism (Hein and others, 1995). Increases in 

nutrient inputs in freshwater systems can cause an increase in 

algal biomass, and thus, an increase in nutrient uptake. High 

nutrient uptake by algae can decrease ambient TN and TP 

concentrations, masking the nutrient condition when nutrient 

concentrations are the only measure of water quality. In nutrient enriched areas such as Indiana, it is critical to differentiate oligotrophic or “nutrient reference” sites from sites with 

low nutrient concentrations owing to uptake. In some streams 

with low TN and TP concentrations, Frey and others (2011) 

suggested that the uptake process was a cause of low nutrient concentrations, supported by the dominance of herbivore 

taxa, such as Stonerollers. However, a lack of algal biomass 

data in the study made it difficult to distinguish uptake sites 

from nutrient reference sites. Additionally, the weak relations 

between nutrients and algal biomass documented in previous 

studies might be caused, in part, by the grouping of sites with 

low nutrients and low uptake (oligotrophic) and sites with low 

nutrients owing to high algal biomass (uptake) (Caskey and 

others, 2010; Munn and others, 2010). 
Introduction 3

Nutrient saturation

–physical and biological controls

Nutrients control algae 

–nutrient limitation

Algae control nutrients

–via uptake

Nutrient saturation

–physical and biological controls

Algae limited by physical processes

–streamflow, light,

–potentially some biological controls

threshold

Increasing nutrient concentrations

Increasing chlorophyll 

a

eutrophic

oligotrophic

Figure 1. Nutrient-algal biomass conceptual diagram illustrating the relations between nutrient concentrations and algal 

biomass. 

Physical, chemical, and biological interactions in freshwater ecosystems can make a single measure of trophic condition inaccurate; this highlights the utility of using multiple 

lines of evidence that assess not only nutrient concentration 

and algal biomass, but the overall biological community when 

determining the trophic conditions of a stream. Invertebrate 

and fish communities can differ among streams in the same 

area based on water quality. Many invertebrate and fish taxa 

are sensitive to changes in streams caused by nutrient enrichment, primarily through increased algal growth or wide daily 

dissolved oxygen fluctuations; conversely, some taxa are 

tolerant of enriched nutrient conditions (Meador and Carlisle, 

2007). These differences in tolerance will cause shifts in the 

overall community structure of a stream as it is exposed to 

increased nutrients. By incorporating the assessment of biological communities in streams, a better understanding of the 

trophic condition can be determined. 

Assessing the overall ecosystem response to disturbances, such as excess nutrient inputs, will have significant 

implications for setting regulatory criteria, especially if the 

dynamic interactions within an aquatic system can be taken 

into account (Adams and Greeley, 2000). Determining how 

ecosystem attributes change along a nutrient gradient allows 

for a quantitative description of stressor/response relations; 

however, the relation between ecosystem attributes and 

increasing nutrient concentrations is not always predictable 

along the nutrient gradient. Ecological attributes often will 

remain stable or show small changes until a certain concentration of nutrients, or “threshold concentration” is introduced, 

then a disproportionate change in an ecological attribute 

becomes apparent (Richardson and Qian, 1999; Qian and 

others, 2003). The aquatic system is able to buffer its response 

to a disturbance until the threshold is reached. This threshold 

concentration varies depending on the attribute, and the taxa 

used to calculate that attribute, making it crucial to examine 

multiple attributes in an ecosystem and weigh their ecological 

importance when determining a numerical value for regulatory 

criteria. 
4 Identifying Nutrient Reference Sites in Nutrient-Enriched Regions: Indiana Rivers and Streams, 2005–9

Purpose and Scope

Long-term nutrient enrichment in Indiana rivers and 

streams has made it difficult to find acceptable low nutrient 

reference sites. This report provides information to the Indiana 

Department of Environmental Management (IDEM) for their 

development of nutrient criteria. This study used a variety 

of statistical analyses to determine nutrient response to biota 

in Indiana’s rivers and streams. The manuscript documents 

the mean concentrations of TN, TP, periphyton CHLa, and 

turbidity (stressor variables) of 282 Indiana streams; 126 were 

classified as headwater and 156 were classified as wadable. 

The analysis in this manuscript examined 695 invertebrate 

taxa, 170 invertebrate attributes/metrics, 129 fish species, and 

139 fish attributes/metrics (response variables). The extensive 

datasets used in the analysis can be found in the appendix of 

the manuscript. Examining this extremely robust data will aid 

IDEM in their nutrient criteria development and implications 

process.

Description of Study Area

The State of Indiana comprises 94,617 square kilometers (km2

) with a population of over 6.5 million (U.S. Census 

Bureau, 2010). Agriculture is the dominant land use in Indiana 

with just over 45,000 km2 used in crop production, totaling 

48 percent of the State. The predominant agricultural land 

use is corn (25 percent) and soybean (22 percent) production. 

Other significant land-use types include forest (24 percent), 

grassland (14 percent), and urban (10 percent) for the State 

as a whole. Samples were collected from all the major river 

basins in Indiana: Tributaries to the Great Lakes and Ohio 

River Basins (2005); West Fork White River, Lower White 

River, and Patoka River Basins (2006); East Fork White River 

and Whitewater River Basins (2007); Upper Wabash River 

Basin (2008); and Lower Wabash River and Kankakee River 

Basins (2009). 

Of these major river basins, the Upper Wabash River 

Basin had the highest percentage of agricultural land use: 

92 percent. The West Fork White River Basin, Whitewater 

River Basin, Kankakee River Basin, Lower Wabash River 

Basin, and tributaries to the Great Lakes also were heavily 

agricultural (averaging 82 percent). Basins with the highest 

percentage of forested areas include the East Fork White River 

Basin and the Ohio River tributaries with 71 and 52 percent, 

respectively. The cities of Indianapolis, Muncie, and Anderson 

are within the boundaries of the West Fork White River Basin, 

and 8 percent of land use within the basin is urban (Lowe and 

others, 2008). 

Study Methods

Field and analytical methods developed by IDEM and the 

U.S. Geological Survey (USGS) were used in this study. The 

following section describes site selection and sampling strategies, basin delineation, and field and laboratory methods used 

for the collection and processing of nutrient, algal biomass, 

and invertebrate- and fish-community samples.

Site Selection and Sampling Strategies

Using data from the Environmental Monitoring Assessment Program (EMAP), potential sampling sites used by the 

IDEM Probabilistic Monitoring Program (PMP) are generated 

by the EPA (Indiana Department of Environmental Management, 2011). The EMAP methods are designed to characterize the overall water quality and biota in streams using a 

statistically valid number of randomly selected sites (Indiana 

Department of Environmental Management, 2005, 2006, 2007, 

2008, 2009). The site selection process incorporates a stratified 

probability design in order to select an approximately equal 

number of 1st, 2nd, 3rd, and 4th order streams in the basin 

to allow for statistically valid extrapolations to non-sampled 

streams (Indiana Department of Environmental Management, 

2011). Site reconnaissance activities to finalize the sample 

locations included a review of site maps and aerial photographs to determine potential access route, initial property 

owner searches, and physical site visits to verify access, obtain 

landowner access permission, and determine precise coordinates for each sample location. The IDEM PMP assessed 

streams in the entire State of Indiana on a 5-year rotating basin 

schedule. (In 2011, the schedule changed to a 9-year rotation.) 

Appendix 1 and figure 2 list the sites that were examined for 

this study to assess nutrient conditions in Indiana rivers and 

streams. For this study, the major river basins were sampled 

in the following order: Tributaries of the Great Lakes and 

Ohio River Basins (Indiana Department of Environmental 

Management, 2005), West Fork and Lower White River and 

Patoka River Basins (Indiana Department of Environmental 

Management, 2006), East Fork White River and Whitewater 

River Basins (Indiana Department of Environmental Management, 2007), Upper Wabash River Basin (Indiana Department 

of Environmental Management, 2008), and Lower Wabash 

River Basin and Kankakee River Basin (Indiana Department 

of Environmental Management, 2009). 
Study Methods 5

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87°0'0"W 86°0'0"W 85°0'0"W

41°0'0"N

39°0'0"N

0 25 50 Miles

0 25 50 Kilometers

EXPLANATION

Headwater

Wadable

Boatable

Site type

Figure 2. Location of the 318 Indiana Department of Environmental Management Probabilistic 

Monitoring Program sample sites used in the assessment of nutrient-enrichment conditions, 

2005–9. [Site numbers are associated with appendix 1.] 
6 Identifying Nutrient Reference Sites in Nutrient-Enriched Regions: Indiana Rivers and Streams, 2005–9

Basin Delineation and Land Use

Drainage basin areas were delineated for each site using 

ArcGIS (Environmental Systems Research Institute, 2009) and 

methods generated by Ries and others (2004). To determine 

basin size, basin boundaries were created for each site using 

the National Elevation Dataset, Digital Elevation Model data, 

and National Hydrography Dataset (Ries and others, 2004). 

This delineation then was used to calculate the land use within 

each basin from the Cropland Datalayer (U.S. Department of 

Agriculture, 2010). The Cropland Datalayer is produced by 

the National Agricultural Statistics Service (NASS) and is 

a crop-specific raster with a 56-meter (m) resolution and an 

85 to 95 percent accuracy for crop-specificity, available for 

each year of sampling. Land-use categories were composited 

into general groupings with categories of interest kept unique 

for purposes of analysis. These categories are corn, soybean, 

other agriculture, forest, wetland, grassland, urban, and other. 

Using cropland data specific to the year of sampling allows for 

high reliability of land-use information, especially concerning crops of interest, which is a factor important in Indiana, 

an agriculturally dominated State. The sites sampled in 2005 

were analyzed with the 2006 Cropland Datalayer owing to the 

lack of data for 2005. Additionally, six sites with more than 

4 percent of the total basin area defined by missing data in the 

2006 Cropland Datalayer were analyzed with the 2007 Cropland Datalayer. In all other cases, the sampling year dictated 

the specific Cropland Datalayer used in land-use calculations 

for each basin, and these basins contained less than or equal to 

1 percent of missing data. 

Data Collection 

This section outlines the sampling and processing 

methods for nutrient, periphyton and seston CHLa, and 

invertebrate- and fish-community data collection. Nutrient and 

water-chemistry samples and the periphyton and seston CHLa

samples were collected two to three times from mid-May 

through the end of October, and the invertebrate- and fishcommunity samples were collected from mid-June through the 

end of October. The mean nutrient and CHLa concentrations 

were compared to the biology because the response to the 

biological communities is not instantaneous and because the 

biological communities of interest are more reflective of more 

long-term conditions. 

Nutrients and Water-Chemistry Samples

Nutrient (TN and TP) and water-chemistry samples 

were collected using an approved IDEM grab method (Indiana Department of Environmental Management, 2002) 

and appropriate quality-assurance (QA) protocols (Indiana 

Department of Environmental Management, 2004). Following 

collection, samples analyzed for (1) general chemistry were 

placed directly on wet ice, (2) nutrients were preserved with 

2 milliliters (mL) sulfuric acid, (3) metals were preserved with 

5 mL of concentrated nitric acid, and (4) cyanide samples were 

preserved with sodium hydroxide. The processed samples 

then were sent to independent laboratories for analysis (2005, 

Tributaries to the Great Lakes, Environmental Health Laboratories, South Bend, Ind.; 2005, Ohio River Basin, Heritage 

Environmental, Indianapolis, Ind.; 2006, West Fork and Lower 

White River Basins, Underwriters Laboratories, South Bend, 

Ind.; 2006, Patoka River Basin, Test America, Indianapolis, 

Ind.; 2007, East Fork White River Basins, Test America, 

Indianapolis, Ind.; 2007, Whitewater River Basin, Underwriters Laboratories, South Bend, Ind.; 2008, Upper Wabash River 

Basin, Test America, Dayton, Ohio; 2009, Lower Wabash 

River Basin, Test America, Dayton, Ohio; 2009, Kankakee 

River Basin, Underwriters Laboratory, South Bend, Ind.). 

These independent laboratories used EPA test method 353.2 

for nitrate plus nitrite analysis by copper-cadmium reduction; 

EPA test methods 351.2 and 351.4 for Kjeldahl analysis by 

persulfate digestion and colorimetry; and EPA test methods 

365.1, 365.2, and SM4500P–E for TP by persulfate digestion 

and colorimetry. For the analysis in this report, TN is the sum 

of nitrate plus nitrite as nitrogen and total Kjeldahl as nitrogen, 

which includes organic nitrogen and ammonia. 

Periphyton and Seston Chlorophyll a Samples 

Algal biomass was estimated based on periphyton and 

seston CHLa concentrations at each site. 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. 

As a measure of temporal change, three algal samples 

were usually collected for each site throughout the sample 

year, with the exception of 2006 when only one or two 

samples were collected. Samples were processed using modified National Water-Quality Assessment (NAWQA) program 

algal protocols for periphyton collection (Moulton and others, 2002). Periphyton samples consisted of five composited 

subsamples from the same substrate type—epilithic (rocks), 

epidendric (sticks), or epipsammic (sand). The same substrate type was collected for each of the three visits. Epilithic 

substrates were preferred for periphyton collection. Epilithic 

substrate was sampled using an 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). Areas sampled were recorded and used to standardize 

the CHLa concentrations among samples. One modification 

from the NAWQA protocols was used when sampling epilithic substrates: 10 rocks were collected as close to the center 

point of the reach as possible and 5 rocks—that best visually 

represented the average algal cover within the reach—were 

selected for subsampling (Charles and others, 2000). The 

sample volume, total area sampled, and substrate type was 
Study Methods 7

recorded along with water-quality field measurements: water 

temperature, pH, specific conductance, turbidity, and dissolved 

oxygen.

Seston CHLa collection used the multiple vertical 

method described by Shelton (1994), which calls for collection 

with a 3-liter (L) bottle with a 0.476-centimeter (cm) nozzle 

when flow was greater than 1.5 feet per second (ft/s) and the 

stream could be waded. Grab samples were collected at sites 

where the flow was less than 1.5 ft/s and in cases where water 

depths were a limiting factor for safe sample collection (Shelton, 1994). Seston and water-quality samples were collected 

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

a transect that extended from the left edge of the water to the 

right edge of the water. The wetted channel width and water 

depths (one-quarter, one-half, and three-quarters points) were 

recorded along the transect. 

Each sample was homogenized and filtered in the field 

onto four glass-fiber filters. The sample volume needed for 

periphyton and seston analysis was determined by examining 

the color density of the filter following USGS National Water 

Quality Laboratory (NWQL) (Lakewood, Colo.) guidelines for 

particulate carbon sampling and analysis (Patton and others, 

2000). The filtered volume of each algal-biomass sample was 

recorded. The filters then were placed on dry ice and transported to the USGS Indiana Algal Biomass Laboratory (Indianapolis, Ind.) for analysis. Usually, filters were processed 

within 24 days of collection. Concentrations of CHLa were 

determined following EPA 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 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 grams (g)) for up 

to 15 minutes or until separation was observed. 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. Prior to 

centrifugation, all samples were allowed to steep in 90 percent 

acetone in the dark for 2.5 to 3 hours at 4°C.

The QA methods for periphyton and seston CHLa

samples included processing a total of five filters at each site: 

four sample filters and one blank filter. Of the four sample 

filters, three filters were used to measure variability. For 10 

to 15 percent of all samples, the fourth filter was analyzed at 

the USGS NWQL to measure inter-laboratory variability. The 

blank filter was used to evaluate equipment-decontamination 

procedures and possible sample-processing contamination 

(Indiana Department of Environmental Management, 2011). 

Invertebrate Samples 

Benthic invertebrate samples were collected using a 

slight modification of the multi-habitat EPA Rapid Bioassessment Protocol approach using a D-frame dip net. In the EPA 

multi-habitat methods a total of 20 jabs (kicks) are taken in 

proportion to the percentage that each habitat is represented 

within the sampled stream reach. The IDEM multi-habitat 

approach is composed of a 1-minute kick sample from multiple habitats within the sample reach and a sweep of 50 m of 

shoreline within the reach, typically from riffle habitats. The 

IDEM 50 m sweep of the shoreline is an addition to the methods. When riffles were not present, samples were collected 

from a run habitat. Additionally, emergent vegetation, coarse 

particulate organic matter, depositional zones, and woody 

debris habitats were sampled as they were encountered. If the 

stream was too deep to wade, the 50-m shoreline sample area 

was moved to a location where it could be sampled effectively 

and safely. Sample material was composited into a bucket of 

water, which was elutriated into a 500-micrometer (μm) sieve. 

After taking care to elutriate rocks, gravel, and sand, the sample material was transferred to a white tray where the sample 

collector performed a 15-minute pick of the organisms, on site. 

The picked sample was preserved in 70-percent ethanol and 

returned to the IDEM laboratory for identification to the lowest possible taxonomic level. Replicate samples were collected 

at 10 percent of the sites as part of the IDEM QA plan (Indiana 

Department of Environmental Management, 2011). 

Fish-Community Samples

Fish-community samples were collected using various 

standardized electrofishing equipment and methodologies 

depending on stream size and site accessibility. Samples were 

collected once at each site in a reach 15 times the average 

wetted width of the stream, with a minimum distance of 50 m 

and a maximum of 500 m. To ensure collection of a representative sample, an attempt was made to sample all habitat types 

within the reach. Sampling crews generally consisted of one 

or two operators, depending on equipment, and two primary 

netters using fiberglass dipnets with 3.2 millimeter (mm) bag 

mesh. Fish that were less than 20 mm total length were not 

retained in the sample. Most fish were identified in the field. 

When field identification was not possible, specimens were 

preserved for taxonomic identification in the laboratory. Data 

recorded for fish-community samples included number of individuals; minimum and maximum total length; weight (g); and 

number of individuals with deformities, eroded fins, lesions, 

tumors, and other anomalies. Replicate samples were collected 

at 10 percent of the sites as part of the IDEM QA plan (Indiana 

Department of Environmental Management, 2011). 
8 Identifying Nutrient Reference Sites in Nutrient-Enriched Regions: Indiana Rivers and Streams, 2005–9

Calculation of Invertebrate and Fish-Community 

Index 

After the invertebrate and fish communities were identified and enumerated, IDEM personnel calculated the appropriate Index of Biotic Integrity (IBI) for the invertebrate- and 

fish-community attributes to produce metric scores for assessment of aquatic life for Indiana rivers and streams (Dufour, 

2002; Simon and Dufour 2005; Simon, 2006). In addition, 

USGS personnel calculated 141 invertebrate- and 150 fishcommunity attributes thought to be of ecological interest or 

previously published in the literature. Percent relative abundance and fish biomass also were calculated for each taxon. 

The list of community measures describing the invertebrateand fish-community data are listed in appendixes 2 and 3. 

Data Analysis

This section outlines the statistical procedures used for 

analyzing the nutrient, algal biomass, and biological-community (invertebrate and fish) data. Included in these methods are 

descriptions of how nutrient, algae, and biological conditions 

at each site were determined, and how breakpoint concentrations and quantile regression thresholds were calculated along 

a nutrient gradient for ecologically relevant invertebrate- and 

fish-community attributes. Additionally, the nutrient (TN 

and TP) and periphyton CHLa data were used to identify 

low nutrient, low periphyton CHLa (oligotrophic) and low 

nutrient, and high periphyton CHLa (algal uptake) sites and 

distinguishing taxa associated with each nutrient condition. 

Sites were classified by basin size to account for natural variability in invertebrate and fish communities. All sites that had 

nutrient, algal biomass, and invertebrate and fish data were 

included in the initial analysis.

Data Censoring

The relations between nutrients, algal biomass, and 

biological communities often are weak owing to the complex 

interactions in rivers and streams (Figueroa-Nieves and others, 

2006; Frey and others, 2007; Caskey and others, 2007; Leer 

and others, 2007; Lowe and others, 2008; Royer and others, 

2008). To improve the strength of the relations among stressor 

and response variables, data were censored to remove sites 

that were influenced by non-nutrient variables. The original 

dataset included 322 sites for this study. Two sites (S. Fk. 

Patoka River at CR900S and S. Fk Patoka River at CR875S) 

were removed because they were downstream of a mining 

operation, had several non-nutrient water quality variables 

that were greater than two standard deviations of the mean, 

and had invertebrate and fish IBI scores that indicated the 

biological communities were stressed by non-nutrient factors. Two sites (E. Fk. Whitewater at Fairfield and Killbuck 

Cr at CR600N) were removed because they were classified as 

cold-water streams and the biological communities were outliers when compared to the remaining dataset. The approved 

dataset used for the nutrient enrichment analysis included 318 

sites.

Resolving Multiple Water-Chemistry Reporting 

Limits for Multiple Laboratories 

This study used several laboratories across multiple 

years, and thus, required the resolution of multiple reporting 

limits. Stressor variables, specifically TN—nitrate plus nitrite 

and total Kjeldahl nitrogen (TKN)—and TP, with multiple 

reporting limits were censored to one-half of the reporting 

limit for each laboratory. For variables with a single reporting 

limit, detected values less than one-half of the reporting limit 

were increased to one-half of the reporting limit. Variables 

with detected values greater than one-half of the reporting 

limit, but less than the reporting limit, were retained at the 

reported value. For nitrate plus nitrite there were 4 detection 

limits (0.01, 0.02, 0.1, and 0.2 mg/L), and 69 of the values 

recorded (5.74 percent of the samples) had values less than 

one-half the highest reporting limit. For TKN there were two 

detection limits (0.3 and 0.5 mg/L), and none of the values 

were less than one-half the highest reporting limit. For TP 

there were 5 detection limits (less than 0.05; less than 0.06, 

0.1, and 0.5; and 0.6 mg/L), and about 653 (53.9 percent of 

the samples) had values less than the reporting limit for their 

respective laboratories. In the two instances where the reporting limit was less than a given value, data were censored to 

reflect that value. Frey and others (2011) and Robertson and 

others (2006) found breakpoint thresholds lower than the lowest reporting limits in this study (0.05 mg/L). Since more than 

half of the reported TP values were at or below a reporting 

limit, the censored data could define the outcome of the statistical analysis preformed. Therefore, caution should be taken 

when interpreting the results from the TP analysis. 

Influence of Basin Size on the BiologicalCommunity Composition

In lotic ecosystems, invertebrate- and fish-community 

composition can vary greatly depending on basin size owing 

to differences in habitat and water-quality-related variables 

(Vannote and others, 1980; Goldstein and Simon, 1999; Goldstein and Meador, 2004). Study sites were separated into headwater (basin size less than or equal to 52 km2

), wadable (basin 

size greater than 52 km2 and less than or equal to 2,590 km2), 

and boatable (basin size greater than 2,590 km2) categories 

following IDEM methods (Simon and Dufour, 2005). 

To examine co-variability associated with non-nutrient 

variables, the invertebrate- and fish-community datasets 

were analyzed using Multi-Dimensional Scaling (MDS) with 

PRIMER software (version 6.1.13, Plymouth, United Kingdom). An MDS analysis uses a resemblance matrix to calculate similarities between community composition among sites 
Data Analysis 9

to identify whether a dataset needs to be further subdivided 

to account for natural variability in biological communities 

(Clarke and Warwick, 2001). An MDS stress level of less than 

0.05 indicates an excellent ordination; a stress level between 

0.05 and 0.1 indicates a good ordination; a stress level 

between 0.1 and 0.2 indicates fair ordination; a stress level 

between 0.2 and 0.3 indicates a poor ordination; and a stress 

level greater than 0.3 is very poor. The stress levels are indictors of confidence within the grouping with lower stress levels 

indicating a greater probability that interpretations are correct 

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

of the All dataset was used to determine if differences among 

the invertebrate and fish communities were explained by common variables such as basin size, IDEM’s major river basins, 

Omernik’s Level III ecoregions, and EPA Nutrient Ecoregions. 

Reducing Variability within the Invertebrateand Fish-Community Data 

In dose-response studies, the absence of an organism 

provides important toxicological information. However, in 

ecological or biocriteria assessments, the lack of a specific 

organism at a site does not necessarily indicate the stream is 

without those taxa. In this study, sites were removed from 

the breakpoint and quantile regression analyses if an organism was absent because (1) nutrients typically are not toxic 

to organisms, (2) the absence of an organism may be related 

to sampling or regional differences, and (3) the presence of 

an organism indicates a possible response to nutrients where 

the absence cannot be attributed to nutrients alone. A nutrient 

gradient remained after the removal of sites where taxa were 

not found. A greater number of significant nutrient-biological 

relations are expected to be found after the removal of sites 

with non-nutrient-related data outliers and absent organisms 

even if other covariant variables remain. 

Nutrient and Water-Quality Variables

It has been observed that along a gradient of streamnutrient concentrations and water-quality variables, invertebrate and fish communities will respond differently, resulting 

in changes in the overall community structure (Sprague and 

others, 2006; Meador and others, 2008). To assess these differences in this study, the variables TN, TP, periphyton and 

seston CHLa, and turbidity were used to classify each site into 

nutrient or water-quality categories following methods similar 

to Frey and others (2011). Based upon concentrations of each 

variable, sites were placed into three groups: “Low” groups 

had mean concentrations less than or equal to the 10th percentile; “Medium” groups had concentrations between the 10th 

and 75th percentile; and “High” groups had concentrations 

greater than the 75th percentile. These percentiles were chosen 

as a way to assess the potential differences in conditions at the 

sites owing to nutrients. Initially, the EPA proposed nutrient 

criteria for TN and TP using the 25th percentile within each 

nutrient ecoregion (U.S. Environmental Protection Agency, 

2000d); however, the Low group was set at the 10th percentile 

as a conservative approach to finding low nutrient conditions 

and possible reference sites (Frey and others, 2011). The 

66th percentile was used by Dodds and others (1998) to indicate eutrophic conditions. In this study, the 75th percentile was 

used for the High grouping as a more conservative approach 

to finding high nutrient conditions and possible taxa indicative 

of nutrient enriched sites. The mean concentrations of interest 

(TN, TP, turbidity, and CHLa) for each site are presented in 

appendix 4. 

Invertebrate- and Fish-Community Indexes

The USGS software, Invertebrate Data Analysis System 

(IDAS) ver. 4.2.0.10 (Cuffney, 2003), was used to calculate 

invertebrate-community attributes and indexes. One advantage 

of the IDAS program is that it resolves ambiguous taxa within 

a dataset. Ambiguous taxa occur when all of the individuals within a related group cannot be identified to the same 

taxonomic level of resolution, which results in abundances 

being reported at multiple taxonomic hierarchical levels, 

for example, data including abundances at family and genus 

levels. The IDAS software was used to standardize taxonomic 

resolution among the samples before the community attributes 

and indexes were calculated. There were 131 invertebrate attributes and indexes calculated using the IDAS software and 25 

invertebrate attributes and standard IDEM metrics, resulting in 

a list of 156 invertebrate response variables. Additionally, percent relative abundance was calculated for each invertebrate 

taxon (695), and these values were included in the potential 

response variable list. The total list of invertebrate response 

variables is 851 measures, which includes invertebrate attributes, metrics, indexes, and percentage of relative abundance 

for each taxon (appendixes 5 and 6).

Ninety-six fish-community attributes were calculated 

based on an extensive literature review, and percent relative 

abundance and percent biomass also were calculated for each 

fish taxon (129). Additionally, 43 attributes and metrics were 

calculated by IDEM. The total list of fish response variables is 

526 measures, which include fish attributes, metrics, indexes, 

and percentage of relative abundance of species, functional 

groups, and habitat preference (appendixes 7 and 8).

Nutrient and Biological Breakpoints

Breakpoint analysis was conducted to identify threshold 

concentrations of stressor variables where the most significant 

change in the response variable occurs. The change in the 

response variable can be measured as a shift in response variable mean, variance, or rate of change. In this report, the deviance reduction method was used to determine the threshold 

(Caskey and others, 2010; Frey and others, 2011). This method 

sorts observations along the stressor variable gradient and 

identifies the concentration where the deviance is minimized 
10 Identifying Nutrient Reference Sites in Nutrient-Enriched Regions: Indiana Rivers and Streams, 2005–9

(Qian and others, 2003). The deviance reduction method is an 

iterative process that systematically evaluates the data points 

to minimize the deviance within the dataset by finding the 

points along a distribution where the sum of deviance on either 

side of the point is lowest compared to the overall data deviance (Qian and others, 2003). The method uses a tree-based 

model (Breiman and others, 1984) and selects the first binary 

split as the change point. The method divides the observations into two groups, which are assumed to be relatively 

homogenous (Qian and others, 2003). The deviance reduction 

method will always find a minimum deviance and an associate 

change point regardless of the real ecological change. Breakpoint analysis in this study was completed using S+® (TIBCO, 

2008). 

To reduce the number of invertebrate and fish attributes 

for breakpoint analysis, Spearman rank order correlation was 

used to assess the statistical strength between the stressor 

variables and response variables. The attributes that were 

considered statistically significant (p≤0.05) were examined 

to determine if they were ecologically relevant, based on current literature and best professional judgment. The response 

variables found to be statistically significant and ecologically 

relevant were compiled for both invertebrate and fish. The 

mean, standard deviation, variance, skewness, and kurtosis 

were calculated. In order to reduce the number of response 

variables, cluster analysis was used as a visual censoring tool 

to select the final response variables for breakpoint analysis. 

IDEM and USGS scientists reviewed the potential list of 

response variables. If a variable within a cluster was already 

being used as part of the IDEM PMP, then it was included. 

Additionally, within each cluster, the variables were selected 

that had the best chances to be responsive to nutrients based 

on literature and best professional judgment.

A regression tree analysis was performed in S+® (TIBCO, 

2008) to determine the concentration where the greatest 

change was seen for each response variable from the final list 

of statistically significant and ecologically relevant variables. 

Bootstrapping methods, which simulate the results of repeated 

sampling by randomly selecting subsets of the observed data 

(Qian and others, 2003), were used to determine the 90th percentile confidence interval of the median breakpoints identified in the regression tree. To preserve the range of the stressor 

variables and the local behavior of the response variable, a 

specialized method called random block re-sampling was used 

where groups of data were defined along the environmental 

gradient and bootstrapping was applied to resample within 

those groups.

Once breakpoint threshold concentrations were calculated 

for individual attributes, the mean low and mean high threshold concentrations for each stressor variable were determined. 

This was done by plotting the distribution of invertebrate and 

fish breakpoints together for each stressor variable. Concentrations for which the most breakpoints were calculated (peaks 

in the distribution plot) represent the concentration where the 

most ecological change is occurring, because each individual 

breakpoint represents the concentration where a certain 

biological attribute had the greatest change. In most cases, two 

peaks in the breakpoint plot were observed, allowing for the 

distinction between low and high breakpoints. By using both 

invertebrate and fish breakpoint thresholds for multiple measures, this technique incorporates multiple lines of evidence. 

Breakpoint thresholds determined from this analysis then were 

compared to other studies. 

Additive Quantile Regression Models 

Quantile regression is an advanced procedure that measures the median condition of the response variable, thereby 

estimating multiple rates of change (slope) for each response 

variable (invertebrate or fish measure) along a stressor gradient (nutrient, algal, or turbidity concentrations) (Cade and 

Noon, 2003). The need to find significant ecological relations 

in complex environmental settings has made quantile regression useful in stressor/response studies. In stressor/response 

studies, quantile regression has shown stronger predictive 

relations when more traditional methods, such as regression 

tree or Lowess smooth, are weak. Additive quantile regression models were developed for a subset of data used in the 

breakpoint analysis to compare breakpoint threshold concentrations and quantile threshold concentrations. The procedure 

for additive quantile regression models was conducted using R 

(ver. 2.14.2) (R Development Core Team, 2011) and following 

methods similar to Koenker (2010).

Differences in Biological Communities Based 

on Nutrient Groups 

It is important to establish the strength of relations 

between nutrient concentrations and invertebrate and fish 

communities in order to determine nutrient conditions based 

on biological response. To determine if there were significant 

differences among invertebrate and fish communities based 

on the nutrient groups (Low, Medium, and High), an Analysis of Similarity (ANOSIM) was used. ANOSIM calculates 

a p-value and an R statistic. R statistics range from −1 to 1 

and measure how similar or dissimilar two communities are 

based on pre-defined groups (Seaby and Henderson, 2006). 

For example, when sites are grouped by basin size, an R = 0 

means there are no differences in biological communities 

based on basin size; an R = 1 means there are clear differences in the biological community based on basin size; and 

an R = −1 indicates biological communities are similar, based 

on some other factor besides basin size, such as habitat. An 

R statistic of greater than 0.5 strongly indicates the presence 

of separate groups (Clarke and Gorley, 2006). The invertebrate- and fish-abundance data were fourth-root transformed 

and then MDS analysis was performed using a Bray-Curtis 

similarity resemblance matrix. The three nutrient categories 

(Low, Medium, and High) were tested against each other for 

TN and TP in invertebrate and fish communities at headwater 

and wadable sites. 
Comparison of Nutrient Concentrations by Nutrient Group 11

Understanding Trophic Condition in Low 

Nutrient Sites

To understand the role of nutrient uptake, sites within 

the Low nutrient group for TN or TP were examined (as 

another line of evidence) to quantify whether sites had low 

nutrient concentrations owing to oligotrophic conditions or 

algal uptake. Low nutrient group sites were divided into three 

categories based on periphyton CHLa concentrations: Low—

less than or equal to the 10th percentile, Medium—between 

the 10th and the 75th percentile, and High—greater than the 

75th percentile. To determine if biological communities were 

significantly different based on periphyton CHLa categories, 

data were analyzed with MDS and ANOSIM with pairwise 

tests. Taxa that accounted for the majority of dissimilarity 

between categories were determined by similarity percentages 

(SIMPER). SIMPER is able to determine taxa that discriminate predetermined groups from each other and was used in 

cases where ANOSIM indicated the presence of significantly 

different groups. All multivariate analyses were performed 

in PRIMER (ver. 6.1.13) (Clarke, 1993; Clarke and Gorley, 

2006). A comparison of land use within basins of Low nutrient 

sites with Low CHLa and High CHLa also was performed 

to determine if land use was a possible factor contributing to 

stream trophic conditions in Low nutrient sites.

Differentiation of Datasets

Invertebrate- and fish-community composition in 

freshwater systems differs based on natural landscape factors 

such as stream size (Vannote and others, 1980) and ecoregion 

(Omernik, 1987). Of the examined factors, the only observable 

separation of fish and invertebrate communities was based on 

basin size (MDS stress level of 0.17 and 0.27, respectively). 

Because the fish communities, and to a lesser extend the 

invertebrate communities, were influenced by basin size, both 

communities were subset into three different datasets based on 

basin size: headwater (n=126), wadable (n=156), and boatable 

(n=36). A total of four invertebrate and four fish datasets were 

used (headwater, wadable, boatable, and all) for the breakpoint 

analysis. Initially, breakpoints were determined for the “all 

sites” dataset; however, owing to the variability in communities noted by the MDS according to basin size, additional analysis was not completed on the all sites data set. Additionally, 

boatable sites were excluded from additional analysis owing 

to the low number of sites, which results in a low statistical 

power. Seston CHLa was not used in the analysis owing to its 

lack of influence in headwater and wadable streams (Vannote 

and others, 1980).

Comparison of Nutrient Concentrations 

by Nutrient Group

The ambient concentrations of TN, TP, periphyton CHLa, 

and turbidity (stressor variables) were used to classify sites 

into Low, Medium, and High groups based on percentiles for 

each variable within each dataset, as described in the Nutrient 

and Water-Quality Variables section. The same sites did not 

always fall into the same group for all stressor variables. For 

example, a site could be in the Low TN group but the High 

periphyton CHLa group. Overall, stressor-variable concentrations for Low, Medium, and High groups were similar at headwater and wadable sites (figs. 3–6). The summary statistics 

for the stressor variables for headwater and wadable sites are 

presented in table 1. 

Headwater Sites 

Total nitrogen concentrations in the headwater sites 

(n=126) ranged from 0.343 to 21.6 mg/L. The Low TN group 

had concentrations less than or equal to 0.564 mg/L, and the 

High TN group had concentrations greater than 3.66 mg/L 

(table 1, fig. 3). Total phosphorus concentrations ranged 

from 0.050 to 1.44 mg/L. The Low TP group had concentrations less than or equal to 0.050 mg/L, and the High TP 

group had concentrations greater than 0.140 mg/L (table 1, 

fig. 4). Periphyton CHLa concentrations ranged from 0.947 to 

629 mg/m2. The Low periphyton CHLa group had concentrations less than or equal to 9.18 mg/m2

, and the High periphyton CHLa group had concentrations greater than 143 mg/m2 

(table 1, fig. 5). Turbidity ranged from 1.49 to 243 in nephelometric turbidity units (NTU). The Low turbidity group had 

concentrations less than or equal to 3.74 NTU, and the High 

turbidity group had concentrations greater than 24.1 NTU 

(table 1, fig. 6). 

Wadable Sites

Total nitrogen concentrations in the wadable sites 

(n=156) ranged from 0.340 to 10.0 mg/L. The Low TN group 

had concentrations less than or equal to 0.768 mg/L, and the 

High TN group had concentrations greater than 3.52 mg/L 

(table 1, fig. 3). Total phosphorus concentrations ranged 

from 0.050 to 1.24 mg/L. The Low TP group had concentrations less than or equal to 0.057 mg/L, and the High TP 

group had concentrations greater than 0.157 mg/L (table 1, 

fig. 4). Periphyton CHLa concentrations ranged from 0.383 to 

719 mg/m2. The Low periphyton CHLa group had concentrations less than or equal to 7.29 mg/m2

, and the High periphyton CHLa group had concentrations greater than 115 mg/m2 

(table 1, fig. 5). Turbidity ranged from 1.93 to 186 NTU. The 

Low turbidity group had concentrations less than or equal to 

5.91 NTU, and the High turbidity group had concentrations 

greater than 35.3 NTU (table 1, fig. 6). 
12 Identifying Nutrient Reference Sites in Nutrient-Enriched Regions: Indiana Rivers and Streams, 2005–9

x

x

x

Low

MedHigh

Low

MedHigh

0.5

1.0

5.0

10.0

13 82 31 16 101 39

30 number of 

 values

EXPLANATION 

 schematic boxplot

x

x

upper adjacent

75th percentile

median

25th percentile

lower adjacent

lower outside

upper outside

Headwater Wadable

Total nitrogen, in milligrams per liter

Figure 3. Log transformed distribution of mean total nitrogen concentrations in three nutrient groups (Low, 

Medium, and High) based on nutrient distribution for the selected datasets in the nutrient-enrichment study, 

2005–9. 

x

x

o

Low

MedHigh

Low

Med

High

0.05

0.10

0.50

1.00

28 67 31 18 99 39

30 number of values 

EXPLANATION 

 schematic boxplot

x

x

o

o

upper adjacent

75th percentile

median

25th percentile

lower adjacent

lower outside

lower detached

upper detached

upper outside

Headwater Wadable

Total phosphorus, in milligrams per liter

o

Figure 4. Log transformed distribution of mean total phosphorus concentrations in three nutrient groups (Low, 

Medium, and High) based on nutrient distribution for the selected datasets in the nutrient-enrichment study, 

2005–9. 
Comparison of Nutrient Concentrations by Nutrient Group 13

xx

x

Low

MedHigh

Low

Med

High

1.0

10.0

100.0

1,000.0 14 80 32 16 101 39

30 number of 

 values

EXPLANATION 

 schematic boxplot

x

x

upper adjacent

75th percentile

median

25th percentile

lower adjacent

lower outside

upper outside

Headwater Wadable

Periphyton chlorophyll a, in milligrams per square meter

Figure 5. Log transformed distribution of mean periphyton chlorophyll a concentrations in three nutrient groups 

(Low, Medium, and High) based on nutrient distribution for the selected datasets in the nutrient-enrichment study, 

2005–9. 

x

x

Low

MedHigh

Low

Med

High

5

10

50

100

13 81 32 16 101 39

30 number of 

 values

EXPLANATION 

 schematic boxplot

x

x

upper adjacent

75th percentile

median

25th percentile

lower adjacent

lower outside

upper outside

1

Headwater Wadable

Turbidity, in nephelometric turbidity units

Figure 6. Log transformed distribution of mean turbidity concentrations in three nutrient groups (Low, Medium, 

and High) based on nutrient distribution for the selected datasets in the nutrient-enrichment study, 2005–9. 
14 Identifying Nutrient Reference Sites in Nutrient-Enriched Regions: Indiana Rivers and Streams, 2005–9

Table 1. Summary statistics for the stressor variables for headwater and wadable sites, 

2005–9.

[mg/L, milligrams per liter; CHLa, chlorophyll a; mg/m2, milligrams per square meter; 

NTU, nephelometric turbidity units; ≤, less than or equal to; km2, square kilometer; >, greater than]

Statistic Total nitrogen

(mg/L)

Total phosphorus

(mg/L)

Periphyton CHLa

(mg/m2)

Turbidity 

(NTU)

Headwater sites (≤52 km2) (n=126)

Minimum 0.343 0.050 0.947 1.49

10th percentile .564 .050 9.18 3.74

25th percentile .944 .055 28.1 6.65

Median 2.12 .093 69.7 13.6

75th percentile 3.66 .140 143 24.1

90th percentile 5.92 .292 230 51.7

Maximum 21.6 1.44 629 243

Wadable sites (> 52 km2 ≤2,590 km2) (n=156)

Minimum 0.340 0.050 0.383 1.93

10th percentile .768 .057 7.29 5.91

25th percentile 1.22 .078 19.2 9.77

Median 2.31 .110 44.7 17.4

75th percentile 3.52 .157 115 35.3

90th percentile 4.85 .234 228 64.8

Maximum 10.0 1.24 719 186

Indicates sites with “Low” concentrations less than or equal to the 10th percentile. 

Indicates sites with “High” concentrations greater than the 75th percentile. 

Breakpoint Thresholds

Breakpoint threshold concentrations varied depending 

on which invertebrate or fish attribute was used in analysis 

because nutrients influence certain taxa differently (Frey and 

Caskey, 2007; Caskey and others, 2010; Frey and others, 

2011). Breakpoint threshold concentrations for TN, TP, and 

CHLa were compared to the trophic categories in Dodds and 

others (1998), and turbidity breakpoint threshold concentrations were compared to the biological impact as described in 

Nelson (1993). The complete list of all breakpoints calculated 

for the four stressor variables (TN, TP, periphyton CHLa, and 

turbidity) in this study are listed in appendixes 9 and 10. 

The TN breakpoints ranged from 0.314 to 4.35 mg/L for 

all of the invertebrate and fish measures. The mean low and 

mean high TN breakpoints were 1.03 and 2.61 mg/L, respectively (table 2, fig. 7). The TP breakpoints ranged from 0.050 

to 0.265 mg/L for all of the invertebrate and fish measures. 

The mean low and mean high breakpoints for TP were 0.083 

and 0.144 mg/L, respectively (table 2, fig. 7). The periphyton CHLa breakpoints ranged from 3.49 to 312 for all of the 

invertebrate and fish measures. Mean low and mean high 

breakpoints for periphyton CHLa were 20.9 and 98.6 mg/

m2, respectively (table 2, fig. 7). The turbidity breakpoints 

ranged from 3.48 to 59.1 NTU for all of the invertebrate and 

fish measures. Turbidity mean low and mean high breakpoints 

were 15.4 and 36.3 NTU, respectively (table 2, fig. 7). The 

biological measures used in the calculation of mean low and 

mean high breakpoint threshold concentrations are listed in 

appendix 11. 
Breakpoint Thresholds 15

Table 2. Mean breakpoint threshold summary for the stressor variables, 2005–9.

[TN, total nitrogen; mg/L, milligrams per liter; N/A, not applicable; TP, total phosphorus; Peri, periphyton; CHLa, chlorophyll a; mg/m2, milligrams per 

square meter; NTU, nephelometric turbidity units]

Causal 

variable

Lowest 

breakpoint

Highest 

breakpoint

Mean low 

breakpoint

Mean high 

breakpoint 

Dodd’s 

oligotrophicmesotrophic

Dodd’s 

mesotrophiceutrophic

Biological 

impact

TN (mg/L) 0.314 4.35 1.03 2.61 0.700 1.50 N/A

TP (mg/L) .050 .265 .083 .144 .025 .075 N/A

Peri CHLa (mg/m2) 3.49 312 20.9 98.6 20.0 70.0 N/A

Turbidity (NTU) 3.48 59.1 15.4 36.3 N/A N/A 50.0

Breakpoint threshold concentrations within this range were used to calculate 

 the mean low breakpoint 

Breakpoint threshold concentrations within this range were used to calculate 

 the mean high breakpoint

Distribution of the total number of breakpoints along the concentration gradient 

Total nitrogen, in milligrams per liter Total phosphorous, in milligrams per liter

EXPLANATION

Running average of the number of breakpoints for invertebrate 

and fish communities in headwater and wadable streams

A B

0.05 0.10 0.15 0.20 0.25 0.30

0

2

4

6

8

10

0 1 2 3 4 5

100 150 200 250 300 350

0

2

4

6

8

10

Periphyton chlorophyll a, 

in milligrams per square meter

0 50 0 10 20 30 40 50 60 70

C

Turbidity, in nephelometric turbidity units

0

1

2

3

4

5

D

0

1

2

3

4

Figure 7. Gaussian distribution lines of the total number of invertebrate and fish breakpoint threshold concentrations 

calculated for the headwater and wadable site datasets. A, total nitrogen. B, total phosphorus. C, periphyton 

chlorophyll a. D, turbidity. Peaks represent the concentration where the largest influence to biological communities 

occurred and were used to calculate mean low and mean high breakpoints in the nutrient-enrichment study, 2005–9. 
16 Identifying Nutrient Reference Sites in Nutrient-Enriched Regions: Indiana Rivers and Streams, 2005–9

Development of Quantile Regression 

Models for Nutrient Categories

Additive quantile regression was used as an additional 

line of evidence to verify threshold concentrations determined 

by breakpoint analysis. Of the 29 thresholds calculated using 

quantile regression, six were both ecologically relevant and 

similar to results generated by breakpoint analysis (table 3). 

Quantile regression calculates varying rates of change along 

a stressor gradient, and the lack of agreement between some 

quantile regression and breakpoint analysis might be due to 

the difficulty of calculating a threshold in general, because 

the gradient in TN and TP lacks sufficiently low values. The 

statistical procedures used to calculate thresholds in the two 

methods also differ in the measurement of variation. The 

thresholds that are in agreement from both breakpoint analysis 

and quantile regression are validated by being ecologically 

significant, within the range of previous thresholds calculated 

in the Midwest, and verified by both analysis techniques. 

For the headwater and wadable sites, seven of the eight 

thresholds found using additive quantile regression were 

invertebrate attributes or metrics. Some invertebrate and fish 

metrics indicated similar thresholds (table 3). For example, 

relatively high TP thresholds for tolerant percent of fish taxa 

were found with breakpoint analysis (0.144 mg/L) and quantile regression (0.157 mg/L). 

Comparison of Biological Communities 

within Nutrient Groups 

ANOSIM was conducted to determine if significant differences existed between invertebrate and fish communities 

from headwater and wadable sites based on nutrient group. 

There were no notable differences between any of the 24 

pairwise comparisons of nutrient groups based on TN or TP 

concentrations for headwater or wadable sites (table 4). Only 

four of the pairwise comparisons had significant p-values; 

however, each had an R statistic less than 0.5, indicating no 

statistical differences in invertebrate or fish communities 

based on nutrient groups. 

The relative abundance for invertebrate and fish taxa did 

not differ between TN and TP groups for each site type, and 

many common taxa were dominant across groups and sites. 

Overall, the common invertebrate taxa included Physella sp. 

(pulmonate snail), Cheumatopsyche sp. (net spinning caddisfly), Hyalella azteca (scud), and Dubiraphia minima (riffle 

beetle), which comprised 3.82, 3.57, 3.45, and 2.96 of the total 

percent relative abundance, respectively (appendix 5). The 

invertebrate taxa among the Low, Medium, and High nutrient groups were dominated by similar, tolerant taxa (table 5). 

The Cheumatopsyche sp. and Physella sp. are moderately to 

highly tolerant to nutrients or low dissolved oxygen conditions (Carlisle and others, 2007). For fish, the most common 

taxa included Central Stoneroller (Campostoma anomatum), 

Bluntnose Minnow (Pimephales notatus), Longear Sunfish 

(Lepomis megalotis), and Creek Chub (Semotilus atromaculatus), which comprised 11.6, 8.15, 7.29, and 6.82 of the total 

percent relative abundance, respectively (appendix 7). The fish 

species among the Low, Medium, and High nutrient groups 

were dominated by similar, tolerant taxa (table 5). The most 

common fish species were tolerant to nutrients with the exception of the Central Stoneroller, which is moderately tolerant to 

nutrients (Meador and Carlisle, 2007). The lack of differences 

in invertebrate or fish communities between nutrient groups, 

despite classifying streams conservatively by nutrient groups 

(10th and 75th percentiles), indicates that nutrient concentrations alone may not be the best indicator of impairments of 

streams in Indiana. The presence of many of the same, nutrient 

tolerant taxa in each group is a contributor to these community 

similarities. In nutrient enriched conditions, as in Indiana, 

communities are dominated by nutrient tolerant taxa that 

would not normally thrive in low nutrient conditions. Hence, 

additional analysis was needed to develop an understanding 

of why low nutrient sites were dominated by nutrient tolerant 

taxa.

Differentiation of Oligotrophic and 

Nutrient Uptake Sites

The dominance of eutrophic taxa and the lack of significant differences between invertebrate and fish communities 

among nutrient groups indicate that other factors, such as 

nutrient uptake, may be masking the true nutrient condition of a stream. Periphyton CHLa at sites in Low TN or TP 

groups was used to evaluate if uptake was a potential cause 

for weak relations between nutrients and invertebrate and fish 

communities. A wide range of periphyton CHLa concentrations (2.0 to 428 mg/m2

) was observed at sites with TN or TP 

concentrations that fell at or below the 10th percentile. When 

invertebrate and fish communities were analyzed based on 

periphyton CHLa categories, at these low nutrient sites, statistical differences were found indicating that algal uptake is 

a possible cause of decreased nutrient concentrations at some 

low nutrient sites in this study.
Differentiation of Oligotrophic and Nutrient Uptake Sites 17

Table 3. Summary of the most similar breakpoint-threshold concentrations and quantile-threshold concentrations from the additive 

quantile regression analysis for the headwater and wadable stream types used in the nutrient-enrichment study, 2005–9. 

[Pr(>F), p-value; TN, total nitrogen; mg/L, milligrams per liter; TP, total phosphorus; <, less than; Peri, periphyton; CHLa, chlorophyll a; mg/m2, milligrams per 

square meter; EPT, Ephemeroptera, Plecoptera, and Trichoptera; NTU, nephelometric turbidity units]

Causal 

variable Community Response variable

Number of 

occurrences

Breakpoint 

concentrationp-value

Quantile 

threshold 

concentration

F-value Pr(>F)

Headwater

TN (mg/L) Invertebrate Ablabesmyia mallochi 25 0.656 0.036 0.863 1.77 0.197

TP (mg/L) Invertebrate Percent intolerant species 117 .057 .001 .073 8,950 <.000

Wadable

TP (mg/L) Invertebrate Margalef Index 156 0.153 0.031 0.121 21.9 <0.000

TP (mg/L) Fish Tolerant percent 156 .144 .001 .157 987 <.000

Peri CHLa (mg/m2) Invertebrate EPT 148 27.2 .001 14.0 5.82 .004

Turbidity (NTU) Invertebrate Taxa count 156 34.8 .050 47.1 400 <.000

Table 4. Analysis of Similarity (ANOSIM) results for pairwise tests of invertebrate and 

fish communities in Low, Medium, and High total nitrogen and total phosphorus groups for 

headwater and wadable sites, 2005–9. 

[vs., versus]

Site type Group 

comparisons

Invertebrate Fish

R statistics p-value R statistics p-value

Total nitrogen

Headwater Low vs. Medium − 0.001 0.488 0.070 0.164

Medium vs. High −.056 .936 −.020 .652

Low vs. High .222 .005 .126 .079

Wadable Low vs. Medium .007 .481 −.003 .490

Medium vs. High −.070 .099 .009 .383

Low vs. High .291 .001 .034 .282

Total phosphorus

Headwater Low vs. Medium 0.029 0.237 − 0.027 0.675

Medium vs. High .000 .473 .000 .449

Low vs. High .097 .002 .027 .100

Wadable Low vs. Medium .101 .099 −.069 .838

Medium vs. High .010 .382 .006 .404

Low vs. High .241 .001 .091 .087
18 Identifying Nutrient Reference Sites in Nutrient-Enriched Regions: Indiana Rivers and Streams, 2005–9

Table 5. Species list of the 10 most dominant taxa in the 3 nutrient groups (Low, Medium, and High) based on nutrient distribution for 

the nutrient-enrichment study, 2005–9. 

[sp., species]

Invertebrate Fish

Taxon Number 

of sites

Number 

of 

individuals

Percent 

relative 

abundance

Taxon Number 

of sites

Number 

of 

individuals

Percent 

relative 

abundance

Low nutrient sites (n=68)

Cheumatopsyche sp. 39 715 5.29 Central Stoneroller 40 3,526 18.24

Rheotanytarsus sp. 14 565 4.18 Longear Sunfish 39 1,620 8.38

Physella sp. 42 406 3.00 Bluntnose Minnow 52 1,501 7.76

Caenis sp. 35 381 2.82 Creek Chub 48 1,477 7.64

Baetis intercalaris 22 377 2.79 Striped Shiner 43 985 5.10

Ceratopsyche bronta 13 374 2.77 Bluegill 29 868 4.49

Hyalella azteca 20 263 1.95 Western Blacknose Dace 20 865 4.47

Caenis latipennis 27 261 1.93 Largescale Stoneroller 13 808 4.18

Dubiraphia minima 41 259 1.92 Rainbow Darter 26 644 3.33

Polypedilum flavum 23 258 1.91 Fantail Darter 24 547 2.83

Medium nutrient sites (n=108)

Caenis sp. 46 778 4.16 Central Stoneroller 40 1,965 7.94

Hyalella azteca 47 708 3.79 Longear Sunfish 61 1,667 6.73

Corixidae 39 672 3.60 Bluntnose Minnow 72 1,653 6.68

Cheumatopsyche sp. 57 572 3.06 Creek Chub 61 1,452 5.86

Physella sp. 76 506 2.71 Bluegill 73 1,390 5.61

Dubiraphia minima 63 488 2.61 White Sucker 69 1,162 4.69

Gammarus sp. 16 411 2.20 Spotfin Shiner 51 1,093 4.41

Trichocorixa calva 34 363 1.94 Green Sunfish 74 1,046 4.22

Ceratopsyche bronta 23 345 1.85 Mottled Sculpin 33 1,031 4.16

Tanytarsus sp. 51 329 1.76 Striped Shiner 40 798 3.22

High nutrient sites (n=106)

Physella sp. 82 977 5.63 Central Stoneroller 55 2,615 10.15

Hyalella azteca 37 730 4.21 Bluntnose Minnow 82 2,586 10.03

Dubiraphia minima 73 706 4.07 Creek Chub 61 1,838 7.13

Stictochironomus sp. 39 532 3.07 Longear Sunfish 62 1,782 6.91

Polypedilum illinoense 62 509 2.93 Orangethroat Darter 34 1,104 4.28

Cheumatopsyche sp. 60 488 2.81 White Sucker 66 1,064 4.13

Berosus peregrinus 51 374 2.15 Largescale Stoneroller 5 1,035 4.02

Tricorythodes sp. 36 334 1.92 Spotfin Shiner 48 987 3.83

Corixidae 44 333 1.92 Western Blacknose Dace 22 984 3.82

Peltodytes duodecimpunctata 51 303 1.75 Green Sunfish 76 929 3.60

Indicates taxon present within all three invertebrate or fish groups.
Differentiation of Oligotrophic and Nutrient Uptake Sites 19

Low Nutrient Group Invertebrate-Community 

Analysis

Invertebrate communities in the Low and High periphyton CHLa categories were statistically different (R statistic = 

0.492 and p-value = 0.001) in the Low nutrient group (table 6). 

The average dissimilarity between invertebrate communities in 

the Low and High periphyton CHLa groups was 87.1 percent. 

The top 10 invertebrate taxa contributed to 10.1 percent of this 

average dissimilarity; the relatively low percentage of dissimilarity attributed to these taxa may be due to the large number 

of invertebrate taxa used in the analysis. Cheumatopsyche sp. 

(net spinning Caddisfly) and Physella sp. (pulmonate snail) 

contributed the most to differences between the Low and 

High periphyton CHLa categories (table 7). Cheumatopsyche

sp. and Physella sp. are nutrient tolerant algivores (Carlisle 

and others, 2007) and increase in relative abundance in Low 

nutrient, High periphyton CHLa conditions. Cheumatopsyche

sp. and Physella sp. were both present at 42.9 percent of the 

Low nutrient, Low periphyton CHLa sites and increased to 

76.5 and 88.2 percent of Low nutrient, High periphyton CHLa

sites, respectively. 

Low Nutrient Group Fish-Community Analysis

Fish communities in the Low and High periphyton CHLa

categories were statistically different (R statistic = 0.55 and 

p-value = 0.001) in the Low nutrient group, and results were 

slightly stronger than invertebrate-community results (table 7). 

The average dissimilarity was 76.5 percent. Table 7 shows 

which taxa contributed the most significantly to this total, with 

the first 10 taxa accounting for 30.6 percent of the community 

dissimilarities. An herbivore genus, Stonerollers (Campostoma

spp.) and an insectivore, Western Blacknose Dace (Rhinichthys atratulus meleagris) are both tolerant to high nutrient 

conditions (Meador and Carlisle, 2007) and contributed the 

most to differences between Low and High periphyton CHLa

categories. Stonerollers have been identified as a potential 

indicator of uptake conditions (Justus and others, 2009; Frey 

and others, 2011). Stonerollers were present at 43 percent of 

Low nutrient, Low periphyton CHLa sites and were present 

at 100 percent of Low nutrient, High periphyton sites. Additionally, the Stoneroller mean relative percent increases from 

4.09 to 26.21 between groups. The Western Blacknose Dace 

was present at 29 percent of Low nutrient, Low periphyton 

CHLa sites and at 71 percent of Low nutrient, High periphyton CHLa sites. The Western Blacknose Dace, like some other 

taxa in table 7, did not have a significant change in mean relative percent between nutrient groups. It is important to note 

that SIMPER takes into account the taxa that account for dissimilarity between groups by using the Bray-Curtis similarity 

calculated between all pairs of sites. In this way, discriminating taxa are the ones that are contributing to the differences in 

overall community structure between all pairs of samples and 

sometimes not readily distinguished by comparisons of mean 

relative percent. Creek Chub (omnivore) and a insectivore 

White Sucker (Catostomus commersonii) contributed nearly 

the same amount to the differences between Low nutrient, 

Low periphyton CHLa and Low nutrient, High periphyton 

CHLa sites as did the Western Blacknose Dace. Creek Chub 

and White Suckers also are tolerant of high nutrient conditions 

(Meador and Carlisle, 2007). Some species that are sensitive 

to nutrient conditions also contributed to the differences in the 

periphyton CHLa groups at low nutrient sites. The Longear 

Sunfish increased in relative abundance and was present at a 

higher percentage of sites in the Low periphyton CHLa group. 

The dominance of tolerant taxa and herbivores are typical of 

eutrophic conditions, and their presence in the High periphyton CHLa groups at sites with low nutrients strengthens evidence that nutrient uptake could be the reason for low nutrient 

concentrations. 

Land-Use Differences in the Low Nutrient Group

Forest (mean 45.9 percent) was the most dominant 

land-use type at the oligotrophic sites (Low nutrient and Low 

periphyton CHLa), followed by agriculture (mean 28.1 percent). Conversely, the most dominant land-use type found at 

the nutrient uptake sites (Low nutrient and High periphyton 

CHLa) was agriculture (mean 51.5 percent). For both site 

types, other mean land use accounted for less than 26 percent 

of basin area and included grassland, urban, other, and wetland, with wetland comprising less than one-tenth of 1 percent 

of basin area for all basins. The higher percentage of forested 

area within oligotrophic site basins indicates that the Low 

nutrient, Low periphyton CHLa sites may qualify as acceptable reference sites for the State.

Table 6. Analysis of Similarity (ANOSIM) results for pairwise tests of invertebrate and fish 

communities based on periphyton chlorophyll a categories at low nutrient sites, 2005–9. 

[vs., versus; CHLa, chlorophyll a]

Nutrient group

Invertebrate Fish

R statistic p-value R statistic p-value

Low CHLa vs. High CHLa 0.492 0.001 0.550 0.001

Low CHLa vs. Medium CHLa .248 .017 .218 .039

High CHLa vs. Medium CHLa .045 .207 .011 .387
20 Identifying Nutrient Reference Sites in Nutrient-Enriched Regions: Indiana Rivers and Streams, 2005–9

Table 7. Average dissimilarity and contributing percentage statistics from Similarity Percentages 

(SIMPER) analysis for invertebrate and fish communities based on periphyton chlorophyll a

categories at low nutrient sites, 2005–9. 

[CHLa, chlorophyll a; sp, species]

Taxa Average 

dissimilarity

Contributing 

percentage

Mean relative percent

Low periphyton 

CHLa category

High periphyton 

CHLa category

Invertebrate

Cheumatopsyche sp. 1.39 1.59 4.63 6.59

Physella sp. 1.25 1.44 1.41 6.13

Caenis latipennis 1.16 1.33 .20 3.93

Thienemannimyia sp. .98 1.12 .60 1.75

Caenis sp. .97 1.11 .75 1.99

Sialis sp. .94 1.08 5.48 .81

Dubiraphia minima .88 1.01 3.00 1.57

Tanytarsus sp. .85 .98 .15 .95

Simulium sp. .85 .97 1.72 1.19

Baetis intercalaris .84 .96 .49 3.20

Fish

Stonerollers1 4.77 6.24 4.09 26.21

Western Blacknose Dace 3.67 4.81 10.36 11.63

Creek Chub 3.59 4.69 6.38 13.39

White Sucker 3.25 4.25 .00 3.68

Striped Shiner 2.86 3.74 .91 5.75

Longear Sunfish 2.76 3.62 19.80 1.86

Mottled Sculpin 2.71 3.55 5.95 4.29

Bluntnose Minnow 2.54 3.33 7.01 4.91

Orangethroat Darter 2.29 2.99 2.93 3.03

Silverjaw Minnow 2.18 2.85 .48 2.14

1

Represents pooled populations of Central and Largescale Stonerollers with Central Stonerollers comprising 

80 percent of the group and Largescale Stonerollers as 20 percent. 

Limitations of This Study

Past studies in Indiana found a range of three orders of 

magnitude of nutrient concentrations in rivers and streams 

(Frey and Caskey, 2007; Caskey and others, 2010; Frey and 

others, 2011), indicating some sites have oligotrophic (low 

nutrient concentrations) conditions based on water chemistry 

alone. However, these same studies also found that biological 

communities within Indiana rivers and streams are dominated by nutrient tolerant taxa. Consequently, in the nutrientenriched streams of Illinois, Indiana, and Ohio, the threshold 

breakpoints were three to five times higher when compared to 

less nutrient- enriched streams in surrounding States (Frey and 

others, 2011). This study examined the Low nutrient concentration sites in more detail in an effort to define the trophic 

status of the Low nutrient sites based on the algal biomass and 

dominant biota. Although the sample size in the Low nutrient 

group was small, and it did not have statistically significant 

threshold breakpoints, the analysis showed that many Low 

nutrient sites were dominated by nutrient tolerant taxa.

Although this study used a large dataset, less than 

12 percent of sites were defined as boatable streams, and 

could not be analyzed due to the lack of statistical power. 

Thus, the overall findings are more relevant to headwater and 

wadable streams (less than 2,590 km2 drainage area). Efforts 

were taken to collect samples during stable flow conditions; 

however, streamflow measurements were not included in the 

study design so antecedent conditions of high streamflow, 

which scour benthic algae, and extended stable flow conditions, which encourage algae proliferation, could not be 
Major Findings and Implications for Developing Nutrient Criteria 21

assessed. The lowest reporting levels for TP were 0.05 mg/L, 

and several other studies have found breakpoints (Frey and 

others, 2011) or background conditions (Robertson and others, 

2006) below this value, indicating this dataset might be unable 

to distinguish the lowest TP breakpoints. This study used algal 

biomass as a surrogate for nutrient uptake by algae, which 

causes decreased ambient nutrient concentrations in streams. 

Nutrient concentrations also can be decreased in streams 

through in-stream processing of nutrients, such as denitrification (Duff and others, 2008). Additionally, multiple studies 

have shown that habitat is an important driver of biological 

communities (Cooper, 1993, Munn and others, 2010, Riseng 

and others, 2011) and could account for some of the response 

in the biological communities across the nutrient gradient. 

Major Findings and Implications for 

Developing Nutrient Criteria

Indiana is in a nutrient-enriched region. Row-crop 

agriculture dominates Indiana land use and results in some 

of the largest amounts of nutrient (N and P) inputs to watersheds in the country (Mueller and Spahr, 2006). Consequently, 

Indiana streams have higher nutrient concentrations compared 

to streams in other regions of the Nation (Mueller and Spahr, 

2006; Lorenz and others, 2009). In this study of 282 headwater and wadable rivers and streams, mean TN concentrations 

ranged from 0.340 to 21.58 mg/L, mean TP concentrations 

ranged from 0.050 to 1.44 mg/L, mean periphyton CHLa

concentrations ranged from 0.383 to 719 mg/m2, and mean turbidity ranged from 1.49 to 243 NTU. Even though a nutrient 

gradient is present, overall nutrient concentrations of streams 

in this study are higher than those in less enriched areas to the 

north and south of Indiana.

Despite a nutrient gradient, biological communities 

in streams are similar along a range of nutrient concentrations. Along a nutrient gradient in streams, biological communities will shift from taxa that are sensitive to enriched 

conditions to taxa that are tolerant of enriched conditions; 

however, the streams in this study do not reflect this trend. 

When biological communities were compared based on 

increasing nutrient concentrations, there were no statistical 

differences. Overall, sites within the Low, Medium, and High 

nutrient groups were dominated by the same nutrient tolerant taxa. The common invertebrate taxa included Physella sp. 

(pulmonate snail), Cheumatopsyche sp. (net spinning Caddisfly), and Hyalella azteca (scud) (table 5). Each of these invertebrate taxa is moderately to highly tolerant to nutrients or 

low dissolved oxygen conditions (Carlisle and others, 2007). 

For fish, the most common taxa included Central Stoneroller 

(Campostoma anomatum), Bluntnose Minnow (Pimephales 

notatus), Longear Sunfish (Lepomis megalotis), and Creek 

Chub (Semotilus atromaculatus) (table 5). The Creek Chub 

and Bluntnose Minnow are highly tolerant to nutrient enriched 

conditions, and the Central Stoneroller is moderately tolerant 

(Meador and Carlisle, 2007). The moderately tolerant classification of Stonerollers may be an underestimation because 

Stonerollers and other herbivores may decrease the nutrient 

concentrations in streams with their grazing, especially at 

nutrient uptake sites (Frey and others, 2011). The long-term 

land use and consequent nutrient enrichment in the Midwest 

has led to shifts in species composition toward more nutrient 

tolerant taxa and has resulted in a loss of a biological gradient 

(U.S. Environmental Protection Agency, 2000a, b, c; Munn 

and Hamilton, 2003; Frey and Caskey, 2007; Caskey and others, 2010; Frey and others, 2011), which also indicates a lack 

of acceptable low nutrient (oligotrophic) streams in Indiana.

Determination of breakpoint thresholds using multiple biological-community responses provides a better 

understanding of the ecosystem response. Breakpoint 

thresholds for each stressor variable were calculated using 

multiple measures for both invertebrate and fish communities. 

In past studies, the breakpoint thresholds were determined by 

using either a single breakpoint calculated using one biological 

measure or the mean of all breakpoint thresholds regardless of 

distribution along the nutrient gradient. In this study, in order 

to determine where the largest ecosystem changes occurred, 

the mean low and mean high breakpoint thresholds were determined as the concentration where the most breakpoints for 

both invertebrate and fish measures occurred along the nutrient gradient. This method allows for a better understanding 

of ecosystem response than if only one breakpoint, the mean 

of all the breakpoints, or if just one biological-community 

attribute had been used. Additionally, it allows thresholds for 

more sensitive taxa to be assessed instead of being lost when 

incorporated into an average threshold.

Mean nutrient breakpoint thresholds in this study 

were at least two times greater than in surrounding States 

with less-nutrient-enriched streams. The TN breakpoint 

thresholds for this study ranged from 0.314 to 4.35 mg/L for 

the individual invertebrate and fish measures, and the mean 

low and mean high breakpoint thresholds were 1.03 and 

2.61 mg/L, respectively (table 5). Previous studies in nutrient 

enriched areas, such as Indiana (Caskey and others, 2010), 

southern Minnesota (Heiskary and others, 2010), and the 

Central and Western Plains diatom ecoregion in the Midwest, 

found low and high breakpoints for TN that ranged from 1.7 

to 3.6 mg/L (Caskey and others, 2010). Several studies have 

found low TN thresholds between 0.6 and 0.7 mg/L based on 

modeled background concentrations (Robertson and others, 

2006), the 33rd percentile of stream concentrations (Dodds 

and others, 1998), or breakpoint analysis in Ohio (Miltner and 

Rankin, 1998) and Wisconsin (Robertson and others, 2006; 

Wang and others, 2007; Robertson and others, 2008). The 

mean low and mean high TN breakpoint thresholds calculated 

in this study were similar to those found previously in Indiana 

and other nutrient enriched areas. The mean low TN breakpoint threshold was about two times higher than low breakpoints found in less enriched areas, highlighting the lack of 

low TN breakpoint thresholds in this study.
22 Identifying Nutrient Reference Sites in Nutrient-Enriched Regions: Indiana Rivers and Streams, 2005–9

The TP breakpoint thresholds ranged from 0.050 to 

0.265 mg/L for the individual invertebrate and fish measures, 

and the mean low and mean high breakpoint thresholds were 

0.083 and 0.144 mg/L, respectively (table 5). Previous studies 

in nutrient enriched areas, such as the Central and Western 

Plains diatom ecoregion in the Midwest (Frey and others, 

2011) and Wisconsin (Robertson and others, 2008), found 

low breakpoints for TP in the range of 0.075 to 0.088 mg/L. 

Several studies have identified low TP thresholds ranging 

from 0.025 to 0.040 mg/L based on modeled background 

concentrations (Robertson and others, 2006), the 33rd percentile of stream concentrations (Dodds and others, 1998), 

or breakpoint analysis in Kentucky (Crain and Caskey, 2010) 

and Wisconsin (Robertson and others, 2006). The mean low 

TP breakpoint threshold in this study was higher than those 

previously reported in the area. This could be because the 

minimum reporting limit for TP in this study was relatively 

high (0.05 mg/L) causing 29.3 percent of samples to fall below 

the lowest detection limit. If there was a lower detection limit, 

the breakpoint thresholds may have been pulled closer to what 

was previously found in the area. 

The mean low and high periphyton CHLa breakpoint 

thresholds in this study were similar to previous studies.

The periphyton CHLa breakpoint thresholds ranged from 3.49 

to 312 mg/m2 for the individual invertebrate and fish measures, 

and the periphyton CHLa mean low and mean high breakpoint 

thresholds were 20.9 and 98.6 mg/m2, respectively (table 5). 

Dodds and others (1998) determined an oligotrophic-mesotrophic range of 20 mg/m2

, and a mesotrophic-eutrophic range of 

70 mg/m2, based on the lower- and upper-third percentiles of 

periphyton CHLa. Similarly, Biggs (1996) found 90 percent of 

periphyton CHLa values ranged from 20 to 100 mg/m2 for the 

oligotrophic and eutrophic thresholds in New Zealand. Several 

studies have found 100 mg/m2 to be considered nuisance levels (Welch and others, 1988; Biggs, 1996; Suplee and others 

2009). Caskey and others (2010) determined periphyton CHLa

breakpoints using invertebrate and fish measures ranging from 

54 to 68 mg/m2 in Indiana. The breakpoints found in this study 

were similar to thresholds found in studies both in the same 

area and elsewhere regardless of nutrient enrichment conditions in the study area, providing evidence for low breakpoint 

thresholds of approximately 20 mg/m2 and high breakpoint 

thresholds of approximately 100 mg/m2 for periphyton CHLa

across ecoregions. 

The mean low and high turbidity breakpoint thresholds were lower than expected biological response values, but may be a function of study design. The turbidity 

breakpoint thresholds ranged from 3.48 to 59.1 NTU for the 

invertebrates and fish, and the mean low and high breakpoints 

for turbidity were 15.4 and 36.3 NTU, respectively (table 5). 

Nelson (1993) found detrimental effects to fish communities 

at turbidity above 50 NTU (biological impact). Both the mean 

low and high breakpoints calculated in this study fall below 

this boundary, partly owing to sample collection during stable 

flow periods when turbidity is lowest. The Nelson threshold 

was based on annual averages, which would incorporate high 

turbidity periods. Caskey and others (2010) found turbidity 

breakpoints ranging from 14.1 to 16.1 NTU, which are similar 

to the mean low breakpoint determined in this study. 

The lack of nutrient reference (oligotrophic) sites in 

Indiana diminishes the ability to find low end breakpoint 

thresholds. The overall high nutrient concentrations, lack of 

biological gradient along the nutrient gradient and high nutrient breakpoint thresholds found in this study underscore the 

enriched state of streams in Indiana. This long-term nutrient 

enrichment has created environmental conditions that make 

it difficult to find acceptable low nutrient reference sites that 

would represent undisturbed conditions (Meador and Carlisle, 

2007). Without examples of unimpacted conditions in these 

nutrient rich areas, it is a challenge for stream researchers and 

managers to identify impairments and to assess whether or not 

improvement efforts are effective in enhancing water quality. 

Using nutrient concentrations alone may inaccurately 

assess enrichment in streams by overlooking the stream 

processes that mask relations between nutrients and 

biological response. The periphyton CHLa breakpoints were 

similar to those found in other studies in both low and high 

nutrient areas, indicating that the integration of periphyton 

CHLa data may be crucial when evaluating nutrient conditions 

in streams. Another limitation of using nutrient concentrations 

alone is that a low ambient concentration of TN or TP in a 

stream could be caused by algal uptake and not low nutrient 

inputs. To address this issue, the data from low nutrient sites 

were subset based on periphyton CHLa concentrations. 

Differences in the biological-community composition 

along an algal biomass gradient in the Low nutrient group 

help identify potential oligotrophic and uptake sites. The 

approach used in this study was intended to assess why nutrient tolerant taxa were dominant at some low nutrient sites. 

Consequently, differences between biological communities 

were evaluated at sites with low nutrients (less than 10th percentile for TN or TP) and the low and high (10th and 75th percentiles) ends of the periphyton CHLa gradient. The invertebrate and fish communities in the Low and High periphyton 

CHLa categories in the low nutrient sites were statistically 

different along the periphyton gradient. Cheumatopsyche sp. 

(net spinning Caddisfly) and Physella sp. (pulmonate snail) 

contributed the most to differences between the Low and 

High periphyton CHLa category. Cheumatopsyche sp. and 

Physella sp. are both tolerant algivores and were more present 

at sites with low nutrients and high periphyton CHLa. These 

invertebrate species also increased in relative abundance in 

High periphyton CHLa conditions. For fish, Stonerollers (herbivores), Western Blacknose Dace (insectivore), Creek Chub 

(omnivore), and White Sucker (insectivore) contributed the 

most to differences between Low and High periphyton CHLa

categories. The presence of these fish species increased at high 

periphyton CHLa sites. Stonerollers have been identified as 

a potential indicator of uptake conditions (Justus and others, 

2009; Frey and others, 2011). The high mean relative percentages of nutrient tolerant taxa and algivores are typical of eutrophic conditions, and their presence in the High periphyton 
References Cited 23

CHLa category at sites with low nutrients strengthens evidence that nutrient uptake is causing low nutrient concentrations at certain sites. This highlights the importance of using 

periphyton CHLa data when identifying the trophic condition 

at a site. 

Multiple lines of evidence provide a better understanding of nutrient conditions in streams. The dynamic 

interactions between nutrient input, algal uptake, and biological response makes it difficult to interpret relations related to 

nutrient impairment. The primary focus of this study was to 

evaluate the relations between biological measures (response 

variable) and TN, TP, periphyton CHLa, and turbidity (causal 

variable) in Indiana streams. In complex studies of this type, 

the incorporation of multiple lines of evidence helps to understand the overall ecosystem response. The use of multiple 

biological datasets and analytical techniques in this study 

has created a way to verify results, while taking the overall 

ecosystem response into consideration. The integration of 

nutrient, algal biomass, and invertebrate- and fish-community 

data provided multiple lines of evidence to draw defensible 

conclusions about nutrient conditions and overall ecosystem 

responses. Using nutrient and algal biomass concentrations, 

along with biological-community composition and response 

also minimizes the misclassification of nutrient trophic conditions in streams. The multiple lines of evidence approach used 

in this study could be adapted to provide an in-depth evaluation of thresholds and nutrient conditions in any region, but it 

is of particular importance in nutrient-enriched areas. 

Conclusions

Excessive nutrient input is a leading cause of impairment 

in the Nation’s waterways. Indiana contains many nutrientenriched streams, owing to the high agricultural land use in 

the State, and eutrophic conditions in streams are common. 

Nutrient gradients in Indiana often are so high that relations 

between algal biomass and nutrients are weak, and other datasets are needed to develop a meaningful nutrient threshold. This 

study has approached the development of nutrient thresholds 

from an ecosystem level and built upon previous work in the 

State by considering multiple lines of evidence to verify total 

nitrogen (TN) and total phosphorus (TP) breakpoints and 

establish breakpoints for periphyton chlorophyll a (CHLa) and 

turbidity by using invertebrate- and fish-community measures 

as response variables.

No differences were detected in invertebrate and fish 

communities among sites based on nutrient concentrations. 

Mean low and high breakpoints were calculated for TN, TP, 

periphyton CHLa, and turbidity and were largely in agreement with nutrient thresholds developed for other Midwestern States. The only breakpoints that were consistent with 

those found in other regions were for periphyton CHLa. 

Nutrient uptake sites had significantly different invertebrate 

and fish communities when compared to oligotrophic sites. 

Cheumatopsyche sp., Physella sp., Stonerollers, and Western 

Blacknose Dace were identified as contributing the most to the 

differences in biological communities between oligotrophic 

and uptake sites and should be considered as taxa to investigate for potential to act as indicators of nutrient condition.

This study used invertebrate and fish datasets to describe 

the relation between stream conditions and nutrient input. 

Many of the previous studies that focused on nutrients alone, 

or algal biomass and nutrients, did not provide the strength 

of results needed to make a confident assessment of trophic 

status in Indiana streams. The analyses conducted in this study 

have considered multiple lines of evidence and used biological 

response to guide the development of nutrient thresholds. The 

use of multiple lines of evidence, including nutrient concentrations, algal biomass, and invertebrate and fish communities, 

will be the most effective procedure for the identification of 

the nutrient condition of a stream and will provide defensible 

evidence in support of nutrient criteria and the methodology 

for the development of nutrient criteria.

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28 Identifying Nutrient Reference Sites in Nutrient-Enriched Regions: Indiana Rivers and Streams, 2005–9

Appendixes

The appendixes are contained in a separate Excel document, which is available for downloading at http://pubs.usgs.

gov/sir/2012/5243/. The printed version of this report contains 

a CD-ROM, which includes the appendixes.

Appendix 1. Location of the 318 Indiana Department of 

Environmental Management Watershed Monitoring program 

sampling sites used in the nutrient-enrichment study, 2005–9.

Appendix 2. List of invertebrate-community attributes and 

metrics calculated by the USGS using IDAS (Cuffney, 2003)

and IDEM for the State of Indiana nutrient-enrichment study, 

2005–9.

Appendix 3. List of fish-community attributes and metrics 

calculated for the State of Indiana nutrient-enrichment study, 

2005–9.

Appendix 4. Values for the mean stressor variable concentration at headwater (n=126) and wadable (n=156) sites for the 

nutrient-enrichment study, 2005–9.

Appendix 5. Species list and percent relative abundance 

of invertebrate communities collected at headwater (n=126) 

and wadable (n=156) sites for the nutrient-enrichment study, 

2005–9.

Appendix 6. Values for the invertebrate attributes and metrics 

calculated at headwater (n=126) and wadable (n=156) sites for 

the nutrient-enrichment study, 2005–9.

Appendix 7. Species list and percent relative abundance of 

fish communities collected at headwater (n=126) and wadable 

(n=156) sites for the nutrient-enrichment study, 2005–9.

Appendix 8. Values for the fish attributes and metrics collected at headwater (n=126) and wadable (n=156) sites for the 

nutrient-enrichment study, 2005–9.

Appendix 9. Summary of breakpoint thresholds for the 

stressor variables used in the analysis of invertebrate-community measures (response variables), 2005–9.

Appendix 10. Summary of breakpoint thresholds for the 

stressor variables used in the analysis of fish-community measures (response variables), 2005–9.

Appendix 11. Biological breakpoint thresholds used to calculate mean low and mean high breakpoint concentrations based 

on distribution plots, 2005–9. 

Caskey and others—Identifying Nutrient Reference Sites in Nutrient-Enriched Regions: Indiana Rivers and Streams, 2005–9—Scientific Investigations Report 2012–5243