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

# Professional Paper 1722 In cooperation with the Wisconsin Department of Natural Resources


# Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

# Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

By Dale M. Robertson, David J. Graczyk, Paul J. Garrison, Lizhu Wang, Gina LaLiberte, and Roger Bannerman

In cooperation with the Wisconsin Department of Natural Resources



# Professional Paper 1722

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

# U.S. Department of the Interior P. Lynn Scarlett, Acting Secretary U.S. Geological Survey P. Patrick Leahy, Acting Director

U.S. Geological Survey, Reston, Virginia: 2006

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Library of Congress Cataloging-in-Publication Data Nutrient concentrations and their relations to the biotic integrity of wadeable streams

in Wisconsin / by Dale M. Robertson ... [et al.] ; in cooperation with the Wisconsin Department of Natural Resources. p. cm. -- (Professional paper ; 1722) Includes bibliographical references and index. ISBN 1-4113-0975-8 (alk. paper) 1. Water quality biological assessment--Wisconsin. 2. Nutrient pollution of water--Wisconsin.

I. Robertson, Dale M. II. Series: Professional paper (Geological Survey (U.S.)) ; no. 1722. QH96.8.B5N88 2006 577.6’42709775--dc22

2006006900 ISBN 1-4113-0975-8

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# Contents

Abstract ...................................................................................................................... ............................ 1 Introduction................................................................................................................... ......................... 2 Purpose and Scope ............................................................................................................. ........ 8 Approach ...................................................................................................................... ............... 10 Methods of Data Collection and Analysis ...................................................................................... 1 0 Field Methods ................................................................................................................. ............ 10 Discharge, Water Chemistry, and Suspended Chlorophyll a Concentrations ........ 10 Benthic Chlorophyll a and Diatoms ............................................................................... 12 Physical Habitat and Fish ............................................................................................... 12 Macroinvertebrates ........................................................................................................ 13 Watershed Boundaries and Environmental Characteristics .............................................. 13 Data Summaries ................................................................................................................ ......... 14 Statistical Methods............................................................................................................ ........ 16 Normalization.................................................................................................................. ... 16 Correlations and Regressions ....................................................................................... 16 Simultaneous Partial Residualization ............................................................................ 16 Regression-Tree Analysis ................................................................................................ 17 Redundancy Analysis ....................................................................................................... 17 Statistical Differences among Groups .......................................................................... 18 Water Quality and Its Relations with Environmental Characteristics in the Watershed ........ 19 Relations between Water Quality and Environmental Characteristics in the Watershed .................................................................................................................... 21 Correlations between Individual Characteristics ........................................................ 21 Correlations with Individual Characteristics after Removing Relations with Anthropogenic Characteristics ....................................................... 24 Thresholds in Water-Quality Responses....................................................................... 25 Effects of Multiple Environmental Characteristics on Water Quality ...................... 29 Stepwise Regression ............................................................................................. 29 Redundancy Analysis .............................................................................................. 31 Environmental Characteristics Most Strongly Related to Water Quality ............... 32 Regionalization Schemes for Reference Water Quality and the Response in Water Quality to Changes in Land Use ..................................................................... 34 Reference Water-Quality Conditions ............................................................................. 34 Total Phosphorus .................................................................................................... 38 Total Nitrogen .......................................................................................................... 38 Suspended Chlorophyll a ....................................................................................... 39 Secchi Tube Depth .................................................................................................. 40 Responses of Nutrient Concentrations to Changes in Land Use .............................. 40 Responses of Chlorophyll a Concentrations and Secchi Tube Depth to Changes in Nutrient Concentrations and Land Use ...................................... 45 Physical Habitat .............................................................................................................. .................... 48

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Benthic Chlorophyll a and Periphytic-Diatom Communities and Their Relations with Water-Quality, Environmental, and Physical-Habitat Characteristics ................. 51 Relations with Individual Characteristics ............................................................................. 51 Correlations .................................................................................................................. ..... 51 Responses to Changes in Nutrient Concentrations ................................................... 55 Effects of Multiple Characteristics on Benthic Chlorophyll a Concentrations and Diatom Indices .............................................................................................................. 59 Stepwise Regressions ..................................................................................................... 59 Redundancy Analysis ....................................................................................................... 59 Reference Values for Benthic Chlorophyll a Concentrations and Diatom Indices ......... 60 Macroinvertebrate Communities and Their Relations with Water-Quality, Environmental, and Physical-Habitat Characteristics .................................................... 62 Relations with Individual Characteristics ............................................................................. 62 Correlations .................................................................................................................. ..... 62 Response to Changes in Nutrient Concentrations ..................................................... 66 Effects of Multiple Characteristics on Macroinvertebrate Indices .................................. 69 Stepwise Regressions ..................................................................................................... 69 Redundancy Analysis ....................................................................................................... 70 Reference Values for the Macroinvertebrate Indices ......................................................... 70 Fish Communities and Their Relations with Water-Quality, Environmental, and Physical-Habitat Characteristics ........................................................................................ 72 Relations with Individual Characteristics ............................................................................. 72 Correlations .................................................................................................................. ..... 72 Responses to Changes in Nutrient Concentrations ................................................... 76 Effects of Multiple Characteristics on Fish Indices ............................................................. 76 Stepwise Regressions ..................................................................................................... 76 Redundancy Analysis ....................................................................................................... 80 Reference Values for the Fish Indices ................................................................................... 80 Multiparameter Biotic Indices to Estimate Nutrient Concentrations in Wadeable Streams ....................................................................................................................... ............ 82 Summary and Conclusions ....................................................................................................... ......... 84 Final Regionalization Scheme for Wisconsin Streams ........................................................ 84 Reference Conditions .......................................................................................................... ...... 86 Responses of Water Quality to Changes in Land Use ........................................................ 88 Responses of Biotic Indices to Changes in Nutrient Concentrations ............................... 88 Multiparameter Biotic Indices to Estimate Nutrient Concentrations in Wadeable Streams ....................................................................................................... 89 Nutrient Concentrations Controlling the Biotic Integrity of Streams ................................ 90 Literature Cited .............................................................................................................. ...................... 91 Appendixes .................................................................................................................... ...................... 95

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# Figures

1. National nutrient ecoregions and major land uses in the upper Midwest ................ 4 2. Two regionalization schemes considered for wadeable streams in Wisconsin: A, level III ecoregions with major land-use/land-cover categories and B, environmental phosphorus zones ........................................................................ 5 3. Environmental phosphorus zones in the upper Midwest ............................................. 7 4. Sites on wadeable streams in Wisconsin included in this study .............................. 11 5. Distributions of median monthly total phosphorus, total nitrogen, and suspended chlorophyll a concentrations, and Secchi tube depth ............................ 20 6. Total phosphorus and total nitrogen concentrations as a function of the percentage of total agriculture in the watersheds of the studied wadeable streams in Wisconsin ........................................................................................................ 27 7. Suspended chlorophyll a concentrations and Secchi tube depths as a function of median total phosphorus and total nitrogen concentrations ................. 28 8. Percentages of explained variance in water quality described by anthropogenic/land-use, basin, soil and surficial-deposit characteristics, and interactions among categories ................................................................................ 33 9. Percentages of explained variance in A , Secchi tube depths and B
, suspended chlorophyll a concentrations described by nutrients, environmental characteristics, and interactions among categories ........................ 33 10. Percentiles of A , total agriculture in the watersheds, B , total phosphorus, and C , total nitrogen in streams in the level III ecoregions and environmental phosphorus zones .............................................................................................................. 35 11. A , suspended chlorophyll a concentrations and B , Secchi tube depths in Reference sites, High sites, and sites with only reference total nitrogen or reference total phosphorus concentrations ............................................................ 39 12. Total phosphorus concentrations as a function of the percentage of agricultural land use in A, environmental phosphorus zones and B, level III ecoregions, and response curves for phosphorus concentrations as a function of the percentage of agriculture in the watershed, in C, EPZs, and D, level III ecoregions ............................................................................................... 41 13. Total nitrogen concentrations as a function of the percentage of agricultural land use in A, environmental phosphorus zones and B, level III ecoregions, and response curves for nitrogen concentrations as a function of the percentage of agriculture in the watershed, in C , EPZs, and D, level III ecoregions ............................................................................................... 42 14. Suspended chlorophyll a concentrations as a function of total phosphorus and total nitrogen concentration, by environmental phosphorus zones and by level III ecoregions ............................................................................................... 46 15. Secchi tube depth as a function of total phosphorus and total nitrogen concentration, by environmental phosphorus zones and by level III ecoregions .................................................................................................................... ...... 47

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# Figures—Continued

16. Response curves for A, suspended chlorophyll a concentrations and B, Secchi tube depths in the environmental phosphorus zones as a function of the percentage of agriculture in the watershed ...................................... 48 17. Distributions of benthic chlorophyll a concentrations, Diatom Nutrient Index values, Diatom Siltation Index values, and Diatom Biotic Index values ........ 52 18. Benthic chlorophyll a concentrations, Diatom Nutrient Index values, and Diatom Siltation Index values as a function of total phosphorus and total nitrogen concentration in the environmental phosphorus zones and level III ecoregions .......................................................................................................... .. 56 19. Benthic chlorophyll a concentrations, Diatom Nutrient Index values, and Diatom Siltation Index values as a function of dissolved phosphorus, dissolved nitrite plus nitrate, dissolved ammonia, and total Kjeldahl nitrogen concentrations in the environmental phosphorus zones ............................ 57 20. Benthic chlorophyll a concentrations and Diatom Nutrient Index values for five nutrient categories ............................................................................................... 58 21. Percentage of explained variance in benthic chlorophyll a concentrations and diatom index values described by nutrients, other water-quality characteristics, environmental and physical-habitat characteristics, and interactions among categories ................................................................................ 60 22. Benthic chlorophyll a concentrations, Diatom Nutrient Index, Diatom Siltation Index, and Diatom Biotic Index values in Reference sites, High sites, and sites with only reference total nitrogen or reference total phosphorus concentrations ............................................................................................. 61 23. Distributions of macroinvertebrate Hilsenhoff Biotic Index values, the percentages of individuals that were Ephemeroptera, Plecoptera, or Trichoptera, and the percentages of taxa that were Ephemeroptera, Plecoptera, or Trichoptera ............................................................................................... 63 24. Hilsenhoff Biotic Index values, the percentages of individuals that were Ephemeroptera, Plecoptera, or Trichoptera, and the percentages of taxa that were Ephemeroptera, Plecoptera, or Trichoptera as a function of total phosphorus and total nitrogen concentration in the environmental phosphorus zones and level III ecoregions ........................................ 67 25. Hilsenhoff Biotic Index values, the percentages of individuals that were Ephemeroptera, Plecoptera, or Trichoptera, and the percentages of taxa that were Ephemeroptera, Plecoptera, or Trichoptera as a function of dissolved phosphorus, dissolved nitrite plus nitrate, dissolved ammonia, and total Kjeldahl nitrogen concentrations in the environmental phosphorus zones ................................................................................... 68 26. Percentages of explained variance in six macroinvertebrate index values described by nutrients, other water-quality characteristics, environmental and physical-habitat characteristics, and interactions among categories .............................................................................................................. 70 27. Hilsenhoff Biotic Index values, the percentages of individuals that were Ephemeroptera, Plecoptera, or Trichoptera, and the percentages of taxa that were Ephemeroptera, Plecoptera, or Trichoptera in Reference sites, High sites, and sites with only reference total nitrogen or reference total phosphorus concentrations ............................................................ 71

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28. Distributions of fish Index of Biotic Integrity values, the percentages of the fish that are carnivorous, the percentages of fish considered pollution intolerant, and the number of fish caught ..................................................................... 73 29. Fish Index of Biotic Integrity values, the percentages of fish considered pollution intolerant, and the percentages of the fish that are carnivorous as a function of total phosphorus and total nitrogen concentration in the environmental phosphorus zones and level III ecoregions ........................................ 77 30. Fish Index of Biotic Integrity values, the percentages of fish considered pollution intolerant, and the percentages of the fish that are carnivorous as a function of dissolved phosphorus, dissolved nitrite plus nitrate, dissolved ammonia, and total Kjeldahl nitrogen concentrations in the environmental phosphorus zones ................................................................................... 78 31. Percentages of explained variance in eight fish index values described by nutrients, other water-quality characteristics, environmental and physical-habitat characteristics, and interactions among categories .................... 80 32. Fish Index of Biotic Integrity values, the percentages of the fish that are carnivorous, and the percentages of fish that are considered pollution intolerant in Reference sites, High sites, and sites with only reference total nitrogen or reference total phosphorus concentrations ................................... 81 33. Measured and estimated A, total phosphorus and B, total nitrogen concentrations for the four-parameter regression models, C, measured phosphorus concentrations as a function of Biotic Index of total Phosphorus values, and D, measured nitrogen concentrations as a function of Biotic Index of total Nitrogen values .......................................................... 83 34. Proposed regionalization scheme for defining nutrient criteria for wadeable streams in Wisconsin. .................................................................................... 85

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# Tables

1. Reference concentrations for total phosphorus, total nitrogen, and suspended chlorophyll a , and turbidity in selected national nutrient and level III ecoregions and environmental phosphorus zones ................... 9 2. Summary statistics for median monthly water-quality and environmental characteristics of the watersheds of the sites in the studied wadeable streams in Wisconsin ........................................................................................................ 15 3. Median and average monthly concentrations for total and dissolved phosphorus, suspended chlorophyll a , total nitrogen, nitrite plus nitrate, ammonia, and Kjeldahl nitrogen, and Secchi tube depths ......................................... 21 4. Spearman correlation coefficients between median concentrations of total phosphorus, dissolved phosphorus, total nitrogen, nitrite plus nitrate, ammonia, total Kjeldahl nitrogen, median Secchi tube depths, suspended chlorophyll a concentrations, percentages of urban and agricultural areas, point-source loadings of phosphorus, and specific environmental characteristics ............................................................................................................... .... 22 5. Spearman correlation coefficients between residualized logarithmically transformed median concentrations of total phosphorus, dissolved phosphorus, nitrogen, nitrite plus nitrate, total Kjeldahl nitrogen, ammonia and suspended chlorophyll a , median Secchi tube depths, and specific residualized environmental characteristics .................................................................. 26 6. Results of forward stepwise-regression analyses used to explain the variance in raw and residualized water-quality concentrations ............................... 30 7. Results from redundancy analysis between water-quality and environmental characteristics ............................................................................................................... .... 32 8. Reference conditions for total phosphorus, total nitrogen, and suspended chlorophyll a concentrations, and Secchi tube depths in the environmental phosphorus zones and level III ecoregions .................................................................. 36 9. Responses in total phosphorus total nitrogen, suspended chlorophyll a , and Secchi tube depth to changes in the percentage of agricultural land use in the watershed ......................................................................................................... 4 4 10. Summary statistics for the physical-habitat characteristics and biotic indices ....................................................................................................................... .......... 49 11. Spearman rank correlation coefficients between benthic chlorophyll a concentrations and diatom community indices, and median water-quality, environmental, and physical-habitat characteristics .................................................. 53 12. Thresholds or breakpoints in the responses of benthic chlorophyll a concentrations and diatom indices to changes in nutrient concentrations ............ 55 13. Percentiles of total phosphorus and total nitrogen concentrations for the studied streams having both benthic chlorophyll a and diatom index data ............ 55 14. Results of forward stepwise-regression analysis to explain the variance in benthic chlorophyll a concentrations and the three diatom indices .................... 5915. Spearman rank correlation coefficients between macroinvertebratecommunity indices and median water-quality, environmental, and physical-habitat characteristics ..................................................................................... 64

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16. Thresholds or breakpoints in the responses in macroinvertebrate indices to changes in nutrient concentrations ............................................................. 69 17. Results of forward stepwise-regression analyses to explain variance in macroinvertebrate indices ........................................................................................... 69 18. Spearman rank correlation coefficients (r
s 

### ) between fish-community indices and median water-quality, environmental, and physical-habitat characteristics ............................................................................................................... .... 74 19. Thresholds or breakpoints in the responses in fish indices to changes in nutrient concentrations ................................................................................................ 79 20. Results of forward stepwise-regression analyses to explain variance in fish indices ............................................................................................................... ....... 79 21. Results of forward stepwise-regression analyses to explain variance in total phosphorus and total nitrogen concentrations with biotic indices ....................................................................................................................... .......... 82 22. Reference conditions for water quality, chlorophyll a, diatoms, macroinvertebrates, and fish indices for wadeable streams in Wisconsin ............ 87 23. Summary of thresholds or breakpoints in the responses of suspended chlorophyll a concentrations, Secchi tube depth, and various biotic indices to changes in nutrient concentrations for the studied wadeable streams in Wisconsin ........................................................................................................ 89


# Appendixes

1. Stream identification information, location information, and summary statistics for flow and water-quality data collected for each of the 240 studied wadeable streams in Wisconsin. ...................................................................... 96 2. Physical-habitat characteristics of each of the 240 studied wadeable streams in Wisconsin ...................................................................................................... 110 3. Diatom nutrient-tolerance ranking for individual diatom taxa ................................. 124 4. Biological data for each of the 240 studied wadeable streams in Wisconsin ...... 126

### 



# Conversion Factors

**Multiply By**  **To obtain** Length micrometer (μm) 0.00003927 inch (in.) millimeter (mm) 0.03937 inch (in.) centimeter (cm) 0.3937 inch (in.) meter (m) 3.281 foot (ft) kilometer (km) 0.6214 mile (mi) Area square meter (m 2 ) 0.0002471 acre square centimeter (cm 2 ) 0.001076 square foot (ft 2 ) square meter (m 2 ) 10.76 square foot (ft 2 ) square centimeter (cm 2 ) 0.1550 square inch (in 2 ) square kilometer (km 2 ) 0.3861 square mile (mi 2 ) Volume liter (L) 0.2642 gallon (gal) cubic centimeter (cm 3 ) 0.06102 cubic inch (in 3 ) cubic meter (m 3 ) 35.31 cubic foot (ft 3 ) Flow rate cubic meter per second (m 3 /s) 70.07 acre-foot per day (acre-ft/d) cubic meter per second per

square kilometer [(m 3 /s)/km 2 ] 91.49 cubic foot per second per square mile [(ft 3 /s)/mi 2 ] meter per second (m/s) 3.281 feet per second (ft/s) millimeter per hour (mm/hr) 0.03937 inch per hour (in/hr) millimeter per year (mm/yr) 0.03937 inch per year (in/yr) Mass gram (g) 0.03527 ounce, avoirdupois (oz) kilogram (kg) 2.205 pound, avoirdupois (lb) kilogram per square kilometer

(kg/km 2 ) 5.70992 pound per square mile (lb/mi 2 )
milligram (mg) 0.00003527 ounce, avoirdupois (oz) milligram per square meter

(mg/m 2 ) 0.000003277 ounce, avoirdupois, per square foot (oz/ft 2 ) Hydraulic gradient meter per kilometer (m/km) 5.27983 foot per mile (ft/mi)


### Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows: °F=(1.8×°C)+32 Specific conductance is given in microsiemens per centimeter at 25 degrees Celsius (μS/cm at 25°C). Concentrations of chemical constituents in water are given either in milligrams per liter (mg/L) or micrograms per liter (μg/L).

### xi



# Abbreviations

Ag Agricultural land BCHL Benthic chlorophyll a BIN Biotic Index of total Nitrogen BIP Biotic Index of total Phosphorus CARN% Percentage of fish that are top carnivores DBI Diatom Biotic Index DEM Digital Elevation Model DFA Driftless Area level III ecoregion DNI Diatom Nutrient Index DP Dissolved phosphorus DSI Diatom Siltation Index EPT Ephemeroptera, Plecoptera, or Trichoptera EPTN% Percentage of macroinvertebrate individuals that were EPT EPTTX% Percentage of macroinvertebrate taxa that were EPT EPZ Environmental phosphorus zone EV Explained Variance FISHN Number of fish caught FISHSPEC Number of fish species caught GIS Geographic Information System HBI Hilsenhoff Biotic Index High Sites Sites with nutrient concentration above the upper 95-percent confidence limits for reference nutrient concentrations IBI Fish Index of Biotic Integrity INSECT% Percentage of fish that are insectivores INTOL% Percentage of fish that are pollution intolerant Log Logarithmic transformation to base 10 n number N Nitrogen NCHF North Central Hardwood Forest level III ecoregion NLF Northern Lakes and Forests level III ecoregion NH 4 

### -N Dissolved ammonia NO 3 

### -N Dissolved nitrite plus nitrate NWIS National Water Information System OEPA Ohio Environmental Protection Agency OMNI% Percentage of fish that are omnivorous p Probability P Phosphorus PtS Point-source loadings of phosphorus r Pearson correlation coefficient

r s 

### Spearman correlation coefficient R 2 

### Coefficient of determination Ref Sites Sites with nutrient concentration below median reference concentrations Res Residualized RDA Redundancy analysis SCHL Suspended chlorophyll a

### xii

SCRAP% Percentage of macroinvertebrates that are scrapers SD Secchi tube depth SHRED% Percentage of macroinvertebrates that are shredders SPARTA Spatial regression-tree analysis SWTP Southeastern Wisconsin Till Plains level III ecoregion t tolerance-index value TAXAN Number of macoinvertebrate taxa TKN Total Kjeldahl nitrogen TOL% Percentage of fish that are pollution tolerant Urb Urban land USEPA U.S. Environmental Protection Agency USGS U.S. Geological Survey WDNR Wisconsin Department of Natural Resources

< Less than % Percentage of # Number

### xiii



# Acknowledgments

Technical Reviewers
Michael A. Miller, Water Resources Management Specialist, Wisconsin Department of Natural Resources, Madison, Wis. Mark D. Munn, Stream Ecologist, U.S. Geological Survey, Tacoma, Wash.



## Editorial and Graphics
Mary S. Ashman, Technical Editor, U.S. Geological Survey, Northborough, Mass. Jennifer L. Bruce, Geographer, U.S. Geological Survey, Middleton, Wis. Michelle M. Greenwood, Publications Unit Chief, U.S. Geological Survey, Middleton, Wis. James L. Kennedy, Geographer, U.S. Geological Survey, Middleton, Wis. David A. Saad, Hydrologist, Geographer, U.S. Geological Survey, Middleton, Wis.



## Approving Official
Angel Martin, Jr., Hydrologist, Reports Specialist, Urbana, Ill.

### xiv

# Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Dale M. Robertson 1 

## , David J. Graczyk 1 

## , Paul J. Garrison 2 

## , Lizhu Wang 3 

## , Gina LaLiberte 2 

## , and Roger Bannerman 4


# Abstract

Excessive nutrient (phosphorus and nitrogen) loss from watersheds is frequently associated with degraded water quality in streams. To reduce this loss, agricultural performance standards and regulations for croplands and livestock operations are being proposed by various States. In addition, the U.S. Environmental Protection Agency is establishing regionally based nutrient criteria that can be refined by each State to determine whether actions areneeded to improve a stream’s water quality. More confidence in the environmental benefits of the proposed performance standards and nutrient criteria will be possible with a better understanding of the biotic responses to a range of nutrient concentrations in different environmental settings. The U.S. Geological Survey and the Wisconsin Department of Natural Resources collected data from 240 wadeable streams throughout Wisconsin to: 1) describe how nutrient concentrations and biotic-community structure vary throughout the State; 2) determine which environmental characteristics are most strongly related to the distribution of nutrient concentrations; 3) determine reference water-quality and biotic conditions for differentareas of the State; 4) determine how the biotic community of streams in different areas of the State respond to changes in nutrient concentrations; 5) determine the best regionalization scheme to describe the patterns in reference conditions and the responses in water quality and the bioticcommunity; and 6) develop new indices to estimate nutrient concentrations in streams from a combination of biotic indices. The ultimate goal of this study is to provide the information needed to guide the development of regionally based nutrient criteria for Wisconsin streams. For total nitrogen (N) and suspended chlorophyll(SCHL) concentrations and water clarity, regional variability in reference conditions and in the responses in water quality to changes in land use are best described by subdividing wadeable streams into two categories: streamsin areas with high clay-content soils (Environmental Phosphorus Zone 3, EPZ 3) and streams throughout the rest of the State. The regional variability in the response in total phosphorus (P) concentrations is also best described bysubdividing the streams into these two categories; however, little consistent variability was found in reference P concentrations in streams throughout the State. Reference P concentrations are similar throughout the State (0.03–0.04 mg/L). Reference N concentrations are divided into two categories: 0.6–0.7 mg/L in all streams except those in areas with high clay-content soils, where0.4 mg/L is more appropriate. Reference SCHL concentrations are divided into two categories: 1.2–1.7 μg/L in all streams except those in areas with high clay-content soils, where 1.0 μg/L may be more appropriate. Reference water clarity is divided into two categories: streams in areas with high clay-content soils with a lower reference water clarity (Secchi tube depth, SD, of about 110 cm) and streams throughout the rest of the State (SD greater than or equal to about 115 cm). For each category of the biotic community (SCHL and benthic chlorophyll a concentrations (BCHL), periphytic diatoms, macroinvertebrates, and fish), a few biotic indices were more related to differences in nutrient concentrations than were others. For each of the indices more strongly related to nutrient concentrations, reference conditions were obtained by determining values corresponding to the worst 75th percentile value from a subset of minimally impacted streams (streams having reference nutrient concentrations).By examining the biotic community in streams having either reference P or N concentrations but not both, the relative importance of these two nutrients was determined. For SCHL, P was the more important limiting nutrient; 1 U.S. Geological Survey, Wisconsin Water Science Center, Middleton, Wisconsin

2 Wisconsin Department of Natural Resources, Monona, Wisconsin

3 Michigan Department of Natural Resources, Ann Arbor, Michigan

4 Wisconsin Department of Natural Resources, Madison, Wisconsin

### however, for BCHL and all macroinvertebrate indices, itappears that N was the more important nutrient when concentrations were near reference concentrations. For other diatom indices and all fish indices, small additions of P or N appear to have little effect on these communities when nutrient concentrations are near reference conditions. Concentrations of P and N in streams increase asthe percentage of agricultural land increases. Concentrations of P increase more quickly and concentrations of N increase more slowly in response to increasing percentages of agriculture in areas with high clay-content soils than dostreams in the rest of the State. The response in water clarity is similar in streams throughout the State; however, the streams in areas with high clay-content soils have poorer reference water clarity, and, therefore, as the percentage of agriculture increases, their clarity remains lower than in streams in areas with other soil types.As nutrient concentrations increase, many biotic indices change. This result indicates that these nutrients have direct or indirect effects on the composition of the biotic community. Thresholds were identified at which a small change in nutrient concentrations results in a relatively large change in the biotic communities. The thresholds in the response to changes in P concentrations range from about 0.04 mg/L for BCHL, to 0.06–0.07 mg/L for diatomand fish indices, to about 0.09 mg/L for macroinvertebrate indices. The thresholds in the response to changes in N concentrations range from 0.5 mg/L for the fish indices and one macroinvertebrate index to about 0.9–1.2 mg/L for the diatom and other macroinvertebrate indices. Most of the biotic indices had a wedge-shaped response to increases in nutrient concentrations. At relatively low nutrient concentrations, the biotic indices ranged widely, but at relatively high concentrations, the indices generally were poor. The wedge-shaped distribution indicates that at low nutrient concentrations, factors other than nutrients often limit the health of biotic communities, whereas, athigh nutrient concentrations, nutrients and factors correlated with high nutrient concentrations are the predominant factors. The biotic communities that are present in a stream reflect the overall ecological integrity; therefore, they integrate the effects of many different stressors and thusprovide a broad measure of their aggregate effect. Nutrient concentrations by themselves explained from about 6 to 13 percent of the total variance in the components of the biotic communities or from about 14 to 23 percent of the explained variance. Nutrient concentrations were mostimportant in affecting SCHL concentrations and macroinvertebrate communities, and least important in affecting BCHL, periphytic diatoms, and fish-community structure. For each component of the biotic community, nutrients by themselves only explained a small part of the overall variance; about half of the variance could not be explained by the variables examined in this study and about one-third of the explained variance could not be assigned to single categories of environmental characteristics. By use of a combination of four biotic indices, twonew multiparameter indices (Biotic Index of total Phosphorus, BIP, and Biotic Index of total Nitrogen, BIN) were developed to estimate P and N concentrations in streamsfrom biotic data collected in streams. These multiparameter models estimated high and low nutrient concentrations equally well. The BIP predicted P concentrations better than the BIN predicted N concentrations. The difference in the accuracy of these indices was consistent with biotic indices being more correlated with P concentrations than with N concentrations. This result suggests that P is more important than N in affecting most biotic communities asnutrient concentrations increase above reference concentrations. Although specific mechanisms of how nutrients affect the biota in wadeable streams were not examined in this study, the results indicate that nutrients are important in controlling the biotic health of streams. Although thebiotic-community structure represents the overall ecological integrity of the stream, nutrients alone explained only asmall part of the variance in the biotic community. Therefore, it is difficult to predict the exact result of reducing nutrient concentrations without also modifying the factors typically associated with high nutrient concentrations. Nutrient concentrations in many streams, especially those in agricultural areas, are well above the concentrations where thresholds in the response were found to occur; therefore, small reductions in nutrient concentrations in these streams are not expected to have large effects on the biotic community. Even with these limitations, however, it is expected that reducing nutrient concentrations will improve the biotic community, further the beneficial ecological functioning of most streams, and improve the quality of downstream nutrient-limited receiving waters.



# Introduction

Elevated nutrient concentrations above backgroundconditions are one of the most common stressors (contaminants) affecting streams throughout the United States. 2 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### Problems associated with elevated nutrient concentrations in surface water are not new, but they are among the most persistent. According to the National Water QualityInventory: 1996 Report to Congress by the U.S. Environmental Protection Agency (USEPA), 50 States, Tribes, and other jurisdictions surveyed water-quality conditions in 19 percent of the Nation’s 3.6 million miles of rivers and streams and found overenrichment of nutrients to be the second most common reason for impairment following the combined effects of suspended sediment and siltation (U.S. Environmental Protection Agency, 1996). Excessive nutrients in rivers and streams can result in the overgrowth of benthic algae in shallow areas and in areas with fastcurrent and an overabundance of phytoplankton and macrophytes in deep areas with slow current. High algal and macrophyte biomass can cause severe diurnal fluctuations in dissolved oxygen and pH because of biotic production and respiration, and can generate harmful organic materials when part of the population dies (Welch and others, 1992). These conditions can lead to an increase in the availability of toxic substances, reduction in available aquatic habitat,modifications to the composition of the biotic communities, and a decrease in the overall usefulness of the stream (Miltner and Rankin, 1998; Dodds and Welch, 2000). Excessive transport of nutrients has also been linked to eutrophication of downstream lakes and impoundments, outbreaks of Pfiesteria in bays and estuaries in various Gulf and Mid-Atlantic States, and hypoxia in the Gulf of Mexico (U.S. Environmental Protection Agency, 2000a). Under recommendations of the Clean Water Action Plan released in 1998, the USEPA has developed aNational strategy to develop waterbody-specific nutrient criteria for lakes and reservoirs, rivers and streams, wetlands, and estuaries (U.S. Environmental Protection Agency, 1998); this study is concerned with those for rivers and streams. The intent of this strategy is to get all States and tribes to establish nutrient standards, that, if enforced, will reduce nutrient concentrations and improve the beneficial ecological uses of surface waters. The best way to control nutrient concentrations is to reduce that part contributed by humans, not that part contributed naturally.It has been recognized that various environmental characteristics, such as land use, geology, soils, climate, and hydrology (including human modifications and hydrologic structures) are important in determining water quality (Monteith and Sonzogni, 1981; Clesceri and others, 1986; and Robertson, 1997). Because these characteristics vary greatly across the United States, the establishment of regional nutrient criteria makes scientific sense. Various frameworks have been used to divide large areas into smaller areas of relatively similar environmental characteristics to minimize the natural variation in water quality within the areas and maximize the differences among the areas. One such framework is the ecoregion delineation developed and refined by Omernik (1987; 1995) and Omernik and others (2000). Ecoregions are a mapped-classification system of regions with assumed relative homogeneity in ecological characteristics. Theseregions were said to be defined on the basis of relative differences in a suite of environmental characteristics, suchas land use/land cover, land-surface form, geology, physiography, climate, soils, potential natural vegetation, and other environmental characteristics (Omernik, 1987 and 1995). The USEPA has taken the initial step in developing regional nutrient criteria based on combining Omernik’s 84 level III ecoregions into 14 national nutrient ecoregions for the conterminous United States (U.S. Environmental Protection Agency, 1998; fig. 1). On a subregional basis,such as a specific State, each of these 14 nutrient ecoregions can be further subdivided into the original level III ecoregions. Wisconsin is subdivided into two national nutrient ecoregions (ecoregions 7 and 8; fig. 1), which are further subdivided into four primary level III ecoregions:Northern Lakes and Forests (NLF), North Central Hardwood Forests (NCHF), Southeastern Wisconsin Till Plains (SWTP), and the Driftless Area (DFA)(Omernik and others, 2000; fig. 2A). In addition, there are small pieces of the Western Cornbelt Plains and the Central Cornbelt Plains ecoregions. Because the Cornbelt Plains ecoregions represent only a small part of the State, they will not be discussed in this report. The nutrient ecoregions provide an initial classification scheme for developing nutrient criteria; however, the USEPA expects individual States andtribes to evaluate and possibly develop alternative regionalization schemes (U.S. Environmental Protection Agency, 2000b).The nutrient ecoregions proposed by the U.S. Environmental Protection Agency (1998) may define spatial patterns in water quality; however, this regionalizationscheme has some inherent problems. Although the boundaries between ecoregions are supposed to represent the differences in a suite of related environmental characteristics (Omernik, 1995), specific boundary lines are often based on differences in a single environmental characteristic and that characteristic may not be the primary one affecting a specific water-quality characteristic. Therefore, greatervariations in water quality may occur within an ecoregion than among ecoregions. Second, in defining most Introduction 3668889777111111100250 500 KILOMETERS250125 MILESCroplandCropland and pastureForestWetlandUrbanWaterEXPLANATIONEcoregionCorn Belt and Northern Great PlainsMostly Glaciated Dairy RegionGlaciated Upper Midwest and NortheastSoutheast Temperate Forested PlainsCentral/Eastern Forested UplandsLand use/land cover678911102°84°45°36°Base from USGS digital line graphsFigure 1.National nutrient ecoregions (U.S. Environmental Protection Agency, 1998) and major land uses in the upper Midwest (U.S. Geological Survey, 2000 and 2004). 

### 4 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in WisconsinEnvironmental phosphorus zonesB.A.1Zones2345Mostly croplandLand UseEXPLANATIONEXPLANATIONNorthCentralHardwoodForests(NCHF)Northern Lakes and Forests(NLF)SoutheasternWisconsinTill Plains(SWTP)Driftless Area(DFA)Mixed croplandMixed forestMostly forestUrbanWaterEcoregion boundaryLevel III ecoregions0020 40 60 KILOMETERS20 40 60 MILES43°46°92°88°43°46°92°88°Figure 2.Two regionalization schemes considered for wadeable streams in Wisconsin:A, level III ecoregions (Omernik and others, 2000) with major land-use/land-covercategories (Lillesand and others, 1998) andB, environmental phosphorus zones (Robertson and others, 2006; described on page 6). 

### Introduction 5

### ecoregions, the relative importance of each environmental characteristic is often unknown and can vary from one area of the country to another in an unknown way. Therefore, the differences in water quality among ecoregions can bedifficult to attribute to any specific environmental characteristic. Finally, for many applications, such as establishingreference conditions for nutrient criteria, the environmental characteristics used to delineate regions of similar water quality should be restricted, as much as possible, to characteristics that are intrinsic, or natural, and are not the result of human activities (U.S. Environmental Protection Agency, 2000a). Here, “reference” water quality refers to background concentrations or the potential water quality that could be achieved in the absence of human activities. By comparing the lines delineating the ecoregions with the land-use patterns in figure 1, it is apparent, however, thatland use was the most important characteristic in defining the ecoregions in the upper Midwest. Although the ecoregion delineation is supposed to represent differences in a full suite of environmental characteristics, nutrient ecoregions primarily subdivide the upper Midwest (and Wisconsin) into areas of forest, cropland and pasture, and cropland. To overcome the problems just described with theUSEPA’s nutrient ecoregions, SPARTA (SPAtial Regression-Tree Analysis) was developed to define characteristicspecific zones with similar reference water quality for the upper Midwest (Robertson and Saad, 2003) and refined to remove both the direct and indirect effects of land use (Robertson and others, 2006). There are two steps in the SPARTA process to delineate water-quality zones. The first step is to use regression-tree analysis (Breiman and others, 1984) to describe the relations between a single dependent variable (for example, phosphorus (P) concentrations) and various independent variables (for example, clay content of the soil and basin slope) thought to affect the distribution of the dependent variable. The second step of SPARTA is to use the regression-tree results (specific characteristics and breakpoints) to divide the entire study area into zones representing each of the final branches of the analysis. To refine the SPARTA approach, land-use-adjusted(residualized) water-quality and environmental characteristics were computed and used to remove the direct and indirect effects of land use from the data for each site. Although SPARTA can be applied with only intrinsic or natural characteristics to remove the direct effects of land use as done by Robertson and Saad (2003), these natural characteristics themselves may be strongly correlated with land use. Thus, even if natural characteristics are the only factors included in the analysis, land use can be indirectly incorporated into the results. SPARTA was applied to theland-use-adjusted nutrient data and land-use-adjusted environmental-characteristic data for sites throughout the upper Midwest to develop environmental water-quality zones (Robertson and others, 2006). Because the biota in streams were assumed to be more influenced by P than by total nitrogen (N) concentrations, environmental P zones (EPZs) were examined as an alternative regionalization scheme for the wadeable streams of Wisconsin (fig. 3). The upper Midwest is divided into five EPZs based primarily on the clay content of the soil and secondarily on the slope of the terrain. Wisconsin consists of four major EPZs and one minor EPZ (fig. 2B). Streams in EPZ 1 have basins with the lowest clay content, streams in EPZ 2 have soils with moderate clay content and low-gradient terrain, streams in EPZ 3 have basins with high clay content and low-gradient terrain, and streams in EPZ 4 have basins with moderate clay content and steep terrain. Only a small part of EPZ 5 (basins with high clay content, steep terrain, and high soil erodibility) is in Wisconsin and, therefore, is not examined in detail in this study. Each of these zones contain streams with relatively similar reference P concentrations and with P concentrations that should respond similarly to changes in land use. After relatively homogenous geographic areas arechosen, several approaches have been used to define quantitative nutrient criteria. The approach suggested by the USEPA to define possible criteria is based on the reference or potential water quality of each area. In other words, the criteria should be based on the conditions that are attainable in the geographic location of each stream (U.S. Environmental Protection Agency, 2000a). Reference concentrations for P, N, suspended chlorophyll a (SCHL, also referred to as sestonic chlorophyll), and turbidity havebeen defined from the frequency distribution of all available data (from USEPA’s Storage and Retrieval, STORET, database) for each area. It has been suggested that the lower 25th percentile of all concentration data for an areamay represent this reference condition (U.S. Environmental Protection Agency, 2000b). In other words, 25 percent of all the sites have water quality at least as good as this reference condition. It has also been suggested that theupper (highest or worst) 75th percentile of the concentration data for a subset of streams thought to be minimally impacted for a defined area may represent this reference condition. In other words, 75 percent of the minimally impacted sites have water quality at least as good as this reference condition. The final criterion should be between 6 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### these two concentrations. Another approach to estimate reference concentrations for each relatively homogeneous area is to develop a multiple linear-regression model that relates water quality to various anthropogenic factors or characteristics such as the percentages of agriculture and urban area in the watershed (Dodds and Oakes, 2004). With this approach, the estimated concentration of a constituent occurring in the absence of human activities (in other words, with 0-percent agricultural and 0-percent urban areas) represents the reference concentration. These relations or equations can also be used to place confidence intervals on the reference concentrations. An alternative approach to defining the nutrient criteria is based on thresholds in the response between nutrient concentrations and biotic indices such as algal productivity (chlorophyll a concentration), water clarity, ordiatom or fish biotic indices (U.S. Environmental Protection Agency, 2000a). The biotic community that is present in a stream, however, reflects more than just the nutrient concentrations that are or were present in the stream. Thebiotic community represents the overall ecological integrity of the stream (in other words, physical, chemical, and biological integrity), and thus provides a broad measure of the aggregate effect of all stressors (Barbour and others,1999). Biotic communities are controlled by many physical, chemical, and biological factors, though they may be directly affected by only a subset of variables. Watershed characteristics (such as geomorphology, geochemistry, and land use/land cover) control the physical/chemical habitat of the stream where the biota live (Frissell and others, 1986; Poff, 1997). Nutrients have been shown to directly affect the productivity and species composition of primary producers, such as macrophytes and benthic and suspended algae, and indirectly affect the primaryand secondary consumers in controlled nutrient-enrichment experiments (for example, Mundie and others, 1991; Peterson and others, 1993; Perrin and Richardson, 1997); however, only limited studies have shown observational linkages between nutrients and the health of the bioticcommunities in natural streams. Among the limited studies in natural environments, Miltner and Rankin (1998) reported that macroinvertebrate- and fish-communityindices were negatively correlated with N and P concentrations in wadeable streams in Ohio. Zorn (2003) reported that P was one of the important variables for predicting the presence or absence of specific fish species in Michiganstreams. Heiskary and Markus (2003) also reported significant negative correlations between macroinvertebrate- and fish-community characteristics and P and N concentrations in nonwadeable rivers in Minnesota. If relations between nutrient concentrations and biotic integrity are used to define criteria, the final nutrient 

## Environmental phosphorus zones

Zone
1 2 3 4 5 EXPLANATION

Base from USGS digital line graphs 0 100 200 MILES 0 100 200 KILOMETERS 102° 84°

45°

36°



### Figure 3. Environmental phosphorus zones (EPZs) in the upper Midwest from Robertson and others (2006). 

### Introduction 7

### criteria should be chosen to minimize degradation in the biotic integrity of the streams. In other words, the criteria should be the concentrations that would not result in highalgal concentrations or degradation of other biotic indices. One of the difficulties in defining nutrient criteria is determining the chlorophyll a concentration or other biotic index values for which a stream is considered degraded or impaired. The assumption made with this biotic-responseapproach is that each of the subregions in a regional framework also delineates an area with streams whose bioticindices respond in a similar manner to changes in nutrients. Whichever approach is used, the final criteria must be stringent enough to protect the specific site and cause no adverse effects in downstream waters. Reference nutrient concentrations, the responses in nutrient concentrations to changes in land use, and the biotic responses to changes in nutrients may differ in streams throughout Wisconsin. There would be more confidence in the potential environmental benefits of enforcing nutrient criteria and standards for the State, ifthe criteria and standards were based on the most appropriate regionalization scheme (such as nutrient ecoregions or EPZs), and if the criteria and standards were based on the appropriate regionally defined thresholds to biotic response. Defined nutrient criteria and thresholds forresponsive biotic indices would enable the use of monitoring data to identify streams affected by excessive nutrients and to direct rehabilitation efforts. The two regionalization schemes being considered for the establishment of nutrient criteria for Wisconsin, level III ecoregions and EPZs, are shown in figure 2. The USEPA developed the preliminary criteria based on median concentrations of all the data measured at each site rather than mean concentrations, because a median value represents the concentration most frequently occurring in the stream, and a statistical summary based on median values reduces the effects of outliers and values reported as less than their respective detection limits. The USEPA hasprovided preliminary criteria for P, N, SCHL, and turbidity for the national nutrient ecoregions and most level III ecoregions (table 1). The proposed criteria by the USEPA for P, based on the 25th-percentile approach, are 0.033 mg/L for national nutrient ecoregion 7 and 0.010 mg/L for national nutrient ecoregion 8 (same as the NLF ecoregion).The USEPA has refined the P criteria for level III ecoregions in national nutrient ecoregion 7: 0.029 mg/L for NCHF, 0.070 mg/L for DFA, and 0.080 for SWTP (U.S. Environmental Protection Agency, 2000b and 2001). Robertson and others (2006) estimated median reference P concentrations for the two major national ecoregions and four major EPZs in Wisconsin (fig. 2) by use of the multiple linear-regression approach (previouslydescribed). They found that median reference P concentrations for the two national nutrient ecoregions were similar, approximately 0.015–0.016 mg/L. They also found that the four major EPZs could be combined into two zones based on estimated reference P concentrations of 0.012 mg/L for EPZ 1 and approximately 0.021–0.023 mg/L for EPZ 2, EPZ 3, and EPZ 4, and the four major EPZs could be combined into three zones based on the response of P concentrations to changes in land use: EPZ 1 was least responsive, EPZ 2 and EPZ 4 were moderately responsive, and EPZ 3 was most responsive. Streams in EPZ 3, withthe highest clay content, had high reference P concentrations (similar to EPZs 2 and 4), but were the most responsive to changes in land use. 

## Purpose and Scope

In 2001, the U.S. Geological Survey (USGS) and the Wisconsin Department of Natural Resources (WDNR), began a collaborative study to: 1) describe how the nutrient concentrations and biotic-community structure in streamsdiffer throughout Wisconsin; 2) determine which environmental characteristics of watersheds are most strongly related to the distribution of nutrient concentrations in streams; 3) determine reference water-quality and biotic conditions for different areas of the State; 4) determine how the biotic community of streams in different areas of the State respond to changes in nutrient concentrations; 5) evaluate existing regionalization schemes in terms of describing patterns in reference water-quality conditions and patterns in biotic response to changes in nutrient concentrations; and 6) develop new multiparameter biotic indices to predict nutrient concentrations in streams. The ultimate goal of this study is to provide the informationneeded to guide the development of regionally based nutrient criteria for streams in Wisconsin. Because the biotic response in streams was expected to vary as a function of stream size, and wadeable streams are sampled with different techniques than nonwadeable streams, the study was divided into two parts. The first part involved sampling 240 wadeable streams in 2001–03, andthe second part involved sampling approximately 40 nonwadeable streams in 2003. In this report, the results of thefirst part of this study are presented: nutrient concentrations and their relations to the biotic integrity of wadeable streams in Wisconsin. The second part of the study will be presented in a separate report. 8 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### Table 1. Reference concentrations for total phosphorus, total nitrogen, and suspended chlorophyll a , and turbidity in selected national nutrient and level III ecoregions (U.S. Environmental Protection Agency, 2000b and 2001) and environmental phosphorus zones (EPZs) from Robertson and others (2006).
[USEPA, U.S. Environmental Protection Agency; NCHF, North Central Hardwood Forests; DFA, Driftless Area; SWTP, Southeastern Wis consin Till Plains; --, no data; NTU, nephelometric turbidity units; FTU, formazin turbidity units; mg/L, milligram per liter; μg/L, microg ram per liter]

Region USEPA criteria Reference concentration based on Robertson and others (2006)

Median Standard error Upper 95-percent confidence limit 25th percentile of all sites Total phosphorus (mg/L) Ecoregion 7 0.033 0.016 0.003 0.024 0.040 NCHF-51 a .029 -- -- -- -- DFA-52 a .070 -- -- -- -- SWTP-53 a .080 -- -- -- -- Ecoregion 8 .010 .015 .002 .019 .010

EPZ 1 -- .012 .002 .017 .020 EPZ 2 -- .021 .003 .026 .030 EPZ 3 -- .021 .004 .030 .060 EPZ 4 -- .023 .003 .030 .050 Total nitrogen (mg/L, calculated/reported) Ecoregion 7 0.54/0.54 -- -- -- -- NCHF-51 a .46/.71 -- -- -- -- DFA-52 a 1.88/1.51 -- -- -- -- SWTP-53 a 1.59/1.30 -- -- -- -- Ecoregion 8 .20/.38 -- -- -- -- Turbidity (NTU/FTU) Ecoregion 7 1.7/2.32 -- -- -- -- NCHF-51 a .84/2.14 -- -- -- -- DFA-52 a 3.38/2.4 -- -- -- -- SWTP-53 a --/2.74 -- -- -- -- Ecoregion 8 .81/1.3 -- -- -- -- Chlorophyll a (μg/L, fluorometric/spectrophotometric/trichromatic methods) Ecoregion 7 1.54/3.50/5.8 -- -- -- -- NCHF-51 a 1.03/8.76/-- -- -- -- -- DFA-52 a 1.00/2.32/-- -- -- -- -- SWTP-53 a .55/3.52/-- -- -- -- -- Ecoregion 8 .60/2.60/4.3 -- -- -- --

a USEPA level III ecoregion identification numbers 

### Introduction 9

## Approach

Because simultaneously collected hydrological, water-quality, and biological data were not available to determine how the biotic integrity of Wisconsin streams is related to changes in nutrient concentrations, a network of streams was selected to represent the wadeable and nonwadeable streams in the level III ecoregions and EPZs in the State. Although some level III ecoregions were combined into larger-scale national nutrient ecoregions and some of the EPZs were combined because there were no statistical differences in reference concentrations or in the responses to changes in land use among some zones in the upper Midwest study (Robertson and others, 2006), each of the level III ecoregions and EPZs were examinedseparately in this study. The locations of the 240 wadeable streams are shown in figure 4 and listed in appendix 1. To try to obtain streams that represent the range in environmental conditions in Wisconsin, approximately the same number of sites was chosen in each of the level III ecoregions. To try to obtain streams with a wide range in nutrient concentrations, sites in each ecoregion were chosen to try to represent a full range in the percentageof agricultural land, although this was not always possible. Discharge and water quality of each stream were sampled monthly over a 6-month period (May through October). Benthic (attached) algae and diatoms were sampled once during the period. During 2001, 157 streams with the smallest watersheds were sampled (2.2 to 222 km 2 

### , but generally less than 90 km 2 

### ). During 2002, 78 larger streams were sampled (40 to 1,947 km 2 

### ). In 2003, 42 nonwadeable streams (not discussed in this report) and five additional wadeable streams were sampled (11 to 106 km 2 

### ). Data on macroinvertebrate and fish populations were not collected as part of this study, but were available from past surveys. A prerequisite for site selection was that the macroinvertebrate and fish populations in the stream had been sampled during the past 5 years. For each site, the drainage basin was digitized and a geographic information system (GIS) was used to describe the environmental characteristics of the watershed. Variousmultivariate statistical approaches were then used to determine how the environmental characteristics of the watershed were related to water quality and biotic-communitystructure. The data were used to determine which stratification scheme (level III ecoregions or EPZs) best describes the distributions in reference nutrient concentrations and the responses in nutrient concentrations to changes in land use. Reference concentrations of P, N, and SCHL, andwater clarity were estimated by use of the multiple linearregression approach and the 25th-percentile approach for the best regionalization scheme. Reference values for the biotic indices were estimated by use of the 75th-percentile approach by examining the values of the biotic indices atminimally impacted sites (sites with nutrient concentrations at or below the estimated reference concentrations). Water-quality data were statistically compared with bioticindices describing the suspended and benthic algae, diatoms, macroinvertebrates, and fish to determine how the biotic integrity of streams is related to changes in nutrient concentrations, and whether or not thresholds in P and (or) N concentrations can be defined above which the biology is adversely affected. Two new multiparameter indices were then developed to estimate P and N concentrations in streams on the basis of the biotic-community structure.



# Methods of Data Collection and Analysis

Field Methods

Discharge, Water Chemistry, and Suspended Chlorophyll a Concentrations
Streamflow and water quality in each stream were sampled monthly over a 6-month period (May through October). Each site was sampled near the middle of the month regardless of flow conditions. During each visit, discharge and field parameters (specific conductance, water temperature, dissolved oxygen, and pH) were either measured or estimated and a water-quality sample was collected. Discharge was determined at each site with a current meter (Rantz and others, 1982), with a stage/discharge relation for a continuous-recording gaging station at the site, or estimated from a nearby site. If the site was notwadeable because of high flow and did not have a continuous-recording gage, the discharge was estimated from a nearby streamflow-gaging station by use of relations between previous discharge measurements at the site and at the nearby station. Specific conductance, water temperature, dissolved oxygen, pH, and, at some sites, turbidity were measuredin the field at the time of sampling by use of a multiparameter meter. The meters were calibrated each day before use. Water clarity was measured by use of a 120-cm 10 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### EXPLANATION
Site and identification number Selected city 209

MADISON MILWAUKEE STEVENS

POINT STEVENS

POINT EAU CLAIRE GREEN BAY

Base map from U.S. Geological Survey digital data, 1:2,000,000. 3 1 2

8 9

10

15

28

29
220
52 53 54

55 56

218 217 62 221 58 60 57 59 30 17

19 20 21 18 14

13 12 13 253 255

256

16 219 252 251

249 250

4 6 5 254

7

238

24 27

36 47 48 49 50 223 222

224

301
302 68 69 67
73 229 230

70 303 228 61 225

226

227

72 71

65 63 64
66

74
214 76

77 86 212

110
81
210 209
89
87 88 90 207
208 106

121 104 105 211

103 205
122 204 203

98 201 93 91

206 92 94

97 96 95 202 108
109 107 102 85 79 83 84 78 80 75 215 216 82 213 23

22 45 46 248 39 40
41 42
43 239

240 237 241 32

242 33
34

231 232

304

35 287 277 275 274 136 271 273 138 139 270 272 134 131 129 130

128
157 267 113

116

112 118

258

257 123 124

125 126 156 155

127 114 115 111
117 144 143 145

264 266 147 146

265 148

151 149 150 263 262 152 153 154 158 261 51

99 101

100
260 259 119

120 133 132 140 141 269 142 268 137 135 276 236

305
233 234

235 37 38 31 247 245 244 246
243

25 26 0 0 20 40 60 KILOMETERS

20 40 60 MILES

44° 45°

43° 46° 92° 91°

90°

8 9°

88 °

8 7°



### Figure 4. Sites on wadeable streams in Wisconsin included in this study. Water-quality and biotic data for each site are given by site identification number in the appendixes. 

### Methods of Data Collection and Analysis 11

### Secchi tube (also referred to as a transparency tube, U.S. Environmental Protection Agency, 2004). The Secchi tube was held into the flowing stream and filled. The tube was then held perpendicular to the ground and drained until the Secchi disk at the bottom of the tube became visible. The water level in the tube was read to the nearest centimeter and defined as the Secchi tube depth (SD). If the disk was visible when the tube was full, the value was reported as greater than 120 cm. All water samples were collected by use of the equal-width-increment (EWI) method with a hand-held DH-59 depth-integrating sampler (Edwards and Glysson,1999), except when stream conditions were not appropriate (stream velocity less than approximately 0.45 m/s, maximum depth less than 0.15 m, or the stream was nonwadeable); in this case, a grab sample was collected with an open bottle at the center of the flow. Samples were then split into appropriate bottles for lab analysis. Samples to be analyzed for dissolved constituents were filtered in the field through 0.45-μm membrane filters. Samples to be analyzed for SCHL were obtained by filtering a known volume of water through a 5-μm membrane filter. The filter was then placed in a labeled petri dish and wrapped in aluminum foil. All samples were chilled until they were delivered to the Wisconsin State Laboratory of Hygiene for analysis, except samples to be analyzed for SCHL, which were frozen, kept in the dark, and delivered to the WDNR Research Laboratory. All samples were analyzed for P, dissolved phosphorus (DP), total Kjeldahl nitrogen (TKN), dissolved nitrite plus nitrate nitrogen (NO 3 

### -N), dissolved ammonia nitrogen (NH 4 

### -N), and SCHL

. In July of 2002, samples were also collected for analysis of suspended sediment. All chemical analyses of water samples (except SCHL) were done by the Wisconsin State Laboratory of Hygiene in accordance with standard analytical procedures described in the “Manual of Analytical Methods, Inorganic Chemistry Unit” (Wisconsin State Laboratory of Hygiene, 1993). At the WDNR Research Laboratory, the filters for SCHL analysis were placed in tubes containing 90 percent acetone, stored at least 24 hours, sonicated for 15 minutes,and stored an additional 24 hours in a freezer. The trichromatic chlorophyll a content of the samples was determined by means of a USEPA-approved method (Greenberg and others, 1992). Throughout this report, the water-chemistry, water-clarity, and SCHL data are collectively referred to as “water-quality data.” All water-quality data were input into the USGS National Water Information System (NWIS) (U.S. Geological Survey, 1998). 

## Benthic Chlorophyll a and Diatoms
Samples for benthic chlorophyll a (BCHL) and periphytic-diatom analyses were collected once duringAugust or September. Care was taken to avoid collecting samples within 2 weeks of appreciable rainfall to minimize the potential effect of scouring. Samples were collected by brushing a known area of three to five rocks with a toothbrush. Following collection, the samples were placed on ice and kept in the dark. Within 12 hours of sampling, the sample was diluted to a known volume with distilled water, homogenized in a blender, and a portion was filtered through two 3–5 μm glass-fiber filters. One filter was placed in 90 percent acetone and was analyzed for its acid-corrected chlorophyll a content (BCHL) by means of a USEPA-approved monochromatic method (Greenburg and others, 1992). The other filter was used for the determination of ash-free dry weight. This sample was dried overnight at 105oC and ashed at 550oC for 1 hour. The sample was weighed before and after ashing. Because of either lack of suitable substrate or lack of water at the time of collection, BCHL samples were collected from only 199 sites. The sample for microscopic analysis of the diatomassemblage was obtained from a portion of the homogenized sample used for BCHL analysis; however, if rocks were not available, samples were collected from sticks. The sample was preserved with Lugols solution and cleaned with hydrogen peroxide and potassium dichromate (van der Werff, 1955). A portion of the diatom suspensionwas dried on a cover slip and mounted in Naphrax. Specimen were identified and counted under an oil-immersion objective (1,400 or 1,750X). At least 300 diatoms were counted from two slides in each sample. The keys used to identify the species included Patrick and Reimer (1966, 1975), Camburn and others (1984–86), Dodd (1987), and Krammer and Lange-Bertalot (1986, 1988, 1991a,b). Because of either lack of coarse substrate or lack of water at the time of collection, samples were collected from only 214 sites.


## Physical Habitat and Fish
Physical-habitat and fish data were collected by the WDNR once at each site between 1997 and 2002. The physical habitat was determined for a stream length equal to 35 times the mean stream width, or a minimum of 100 m. This length is generally sufficient to encompass about three meander sequences (Simonson and others, 12 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### 1994; Wang and others, 1996). The physical habitat and fish were quantified between late May and late Augustwhen low flows facilitated effective sampling and largescale seasonal fish movement was unlikely to occur(Lyons and Kanehl, 1993). At each site, 30 physical-habitat characteristics, including channel morphology, bottom substrates, cover, bank conditions, riparian vegetation, and land cover were measured or visually estimated along 12 transects by use of standard procedures (Simonson and others, 1994). The entire length of each site was electrofished with either two backpack units in tandem or a single tow-barge unit with three anodes (Lyons and Kanehl, 1993; Simonson and Lyons, 1995). Efforts were made to collect all of the fish greater than or equal to 25 cm in length. All captured fish were identified to species, counted, and weighed in aggregate by species.



## Macroinvertebrates
Macroinvertebrate samples were collected by the WDNR once at each site between 1999 and 2002. Twotypes of macroinvertebrate samples were collected according to procedures described by Hilsenhoff (1988). Samples were generally collected from each site during low flow in early October by use of a 600-μm mesh D-frame kick net. The first sample was collected from riffles or rockysubstrates. If rocky substrates were not present, then vegetative snags (areas with overhanging grasses, logs, woody debris, and leaf packs) were sampled to ensure that the sample was from the most representative habitat at each site. The second sample was collected only from snags to ensure that these data were comparable between all sites because rocky substrates were not always present.Samples from riffle or rocky substrates were collected by placing the net on the stream bottom and kicking an area immediately upstream of the net to dislodge themacroinvertebrates and wash them into the net. In addition, individual rocks were picked up and the attached macroinvertebrates were removed and added to the sample. This process was repeated in at least three locations within the same riffle or different riffles until at least 200–300 organisms were collected. Samples were collected in snags by placing a net in the water column downstream of the snag, where it would collect most of the dislodged debris. The snags were then disturbed by scraping or shaking them with a net, hands, or feet. At each site, all available snag types at multiple locations were sampled, with first consideration given to larger snags in higher water-velocity habitats. Samples were sorted and identified at the laboratory of Dr. Stanley Szczytko at the University of Wisconsin, Stevens Point. The samples were placed in a glass pan positioned over a 6.5-cm 2 

### grid. All of the organisms from randomly chosen grid squares were selected until a minimum of 125 organisms having tolerance values cited in the literature (such as the values in Hilsenhoff, 1988) were picked, or, until the entire sample was sorted. All of the picked organisms were counted and identified to the species or the lowest taxonomic level possible.



## Watershed Boundaries and Environmental Characteristics

Watershed boundaries for the sampled streams were manually digitized from 1:24,000-scale USGS topographic quadrangle maps. The environmental characteristics thought to affect the water quality and biology in the streams were compiled for each watershed used in this study: land use/land cover (Lillesand and others, 1998); soil characteristics (from the USSOILS digital coverage of the State Soil Geographic, STATSGO, data base; Schwarz and Alexander, 1995); types of surficial deposits (Fullerton and others, 2003); annual air temperature and precipitation (National Climatic Data Center, 2002); mean land-surface slope (based on 30-m DEM data resampled to 100 m; U.S. Geological Survey, 1999); and average annual runoff (Gebert and others, 1987). Point-source loadings of phosphorus upstream of each sampling site (PtS) were estimated from monthly mean P concentrations and monthly mean discharge volumesas reported by the dischargers (for example, wastewatertreatment plants and cheese factories) in their Discharge Monitoring Report with the WDNR (James Baumann,Wisconsin Department of Natural Resources, written commun., 2004). The number of concentrations and discharge volumes reported in a month varied with the size and type of discharger and ranged from one sample per month to daily samples. For sites where P concentrations were not required to be measured and, therefore not reported, the P concentrations were estimated based on the size and type of discharger. All basin characteristics were compiled in digitalform by use of a GIS. A digital coverage of each watershed was used to compute the average or percentage value for each environmental characteristic, including the PtSfor each of the 240 watersheds. A summary of the environMethods of Data Collection and Analysis 13

### mental characteristics (with the specific metric describing each environmental characteristic) for all of the watersheds used in this study is given in table 2.



## Data Summaries

All of the water-quality data collected in this studywere input into the USGS NWIS database (U.S. Geological Survey, 1998) and are summarized in appendix 1. In computing summary statistics, all of the data were usedregardless of whether or not flow could be detected. During some samplings, the water in the streams was found to have dried up, and no water-quality data were collected. All data reported as less than the detection limit were set to one-half of the detection limit, and all SD data greater than 120 cm were set to 120 cm prior to any statistical and graphical analyses. Physical-habitat data were summarized into: mean wetted width, depth, thalweg depth, and stream gradient; the percentage of the stream reach with riffles, runs, or pools; the mean depth of sediment; the percentage of thebottom of the stream reach composed of different substrates, embedded rocky substrate, and covered by algae or macrophytes; the percentage of the stream reach that contains fish cover, is shaded, and that has streambank erosion; and buffer width (Simonson and others, 1994). The physical-habitat data for each site are summarized in appendix 2.Three metrics were used to summarize the diatomcommunity data: the Diatom Nutrient Index (DNI), the Diatom Siltation Index (DSI; Bahls, 1992), and the Diatom Biotic Index (DBI). The DNI computations are based on tolerance values assigned to individual taxa. DNI values range from 1 to 6, with 1 representing species typicallyfound with the lowest nutrient concentrations (oligotrophic, good water quality) and 6 typically representing species found with the highest nutrient concentrations(hypereutrophic, poor water quality). The values for Wisconsin diatoms (appendix 3) were generated largely from Van Dam and others (1994), but values were also assigned based upon experience with the diatom communities in Wisconsin. If no autecological data were known, the taxa were not assigned a value and were not included in the DNI calculation. Because the index is based upon relative abundance, rare species have little effect on the final index value. The formula used to calculate DNI value is

(1), where

n i 

### = number of individuals of species i;

t i 

### = tolerance-index value for species i; j = total number of species in the sample with tolerance-index values; and N = total number of individuals in the sample having tolerance-index values.

The second metric for the diatom community is the Diatom Siltation Index (DSI). This index is based on the sum of all individuals in the Navicula (including Cavinula, Chamaepinnularia, Craticula, Diadesmis, Fallacia , Fistulifera, Geissleria, Hippodonta, Kobayasiella, Luticola, Mayamaia, Placoneis , and Sellaphora ), Nitzschia (including Psammodictyon and Tryblionella ), and Surirella taxa. These taxa were chosen because they have good motility; therefore, this metric reflects the degree of siltation in a reach (Bahls, 1992). The scale for the index is 0–100 withlower values indicating less silt and thus better water quality. To assess stream biotic integrity, a multimetric index called the Diatom Biotic Index (DBI) was created. The DBI is based on both diatom indices, DNI and DSI. For computing the DBI, each metric was standardized to the 95th percentile for a number of reference sites and then the two metrics were averaged. For sites with an individual metric exceeding its 95th percentile, the metric was set to 100. The scale of the DBI is 0 to 100, with higher values indicating better biotic integrity. The DBI is intrinsically designed to be sensitive to nutrient enrichment and theeffects of sedimentation. The reference sites used to standardize the metric were chosen by combining the northern ecoregions (NLF, NCHF) and the southern ecoregions (DFA, SWTP). Reference sites for the southern ecoregions were those where P concentrations for August were less than or equal to 0.050 mg/L. For the southern ecoregions,there were 13 reference sites and 105 sites with P concentrations exceeding 0.050 mg/L. Reference sites for the northern ecoregions were sites with less than or equal to 10-percent agriculture in the watershed. For the northern ecoregions, there were 42 reference sites and 55 sites with more than 10-percent agriculture. Six common measures were used to summarize the macroinvertebrate data: the Hilsenhoff Biotic Index (HBI; Hilsenhoff, 1988) and five other macroinvertebrate indices based on the percentage or total number of individuals of various groups or species that were counted in the samples (for example, Ohio Environmental Protection Agency, 

### DNI =

N n i 

### t i 

# 3

i = 1 j 

### 14 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### Table 2. Summary statistics for median monthly water-quality and environmental (anthropogenic/land-use, basin, soil, and surficial-deposit) characteristics of the watersheds of the sites in the studied wadeable streams in Wisconsin.
[mg/L, milligram per liter; log, logarithm to base 10 transformation; μg/L, microgram per liter; C, Celsius; μS/cm, microSiemen per centimeter; cm, centimeter; (m 3 /s)/km 2 , cubic meter per second per square kilometer; km 2 , square kilometer; mm, millimeter; mm/year, millimeter per year; --, unitless; %, percent; mm/hr, millimeter per hour; kg/km 2 , kilogram per square kilometer; >, greater than; no PtS, only sites with less than 12 kg/km 2 of point-source loading of phosphorus are included in this part of the analysis; summary statistics based on monthly values]

Characteristic Unit Transformation Count Median Mean Standard deviation Minimum Maximum Water-quality characteristics Total phosphorus mg/L log 240 0.085 0.116 0.144 0.012 1.641 Total phosphorus (no PtS) mg/L log 234 .082 .105 .097 .012 .741 Dissolved phosphorus mg/L log 240 .050 .079 .122 .004 1.495 Dissolved phosphorus (no PtS) mg/L log 234 .050 .069 .074 .004 .553 Total nitrogen mg/L log 240 1.695 2.807 2.860 .131 21.260 Dissolved nitrite plus nitrate mg/L log 240 1.048 2.086 2.865 .005 20.550 Dissolved ammonia mg/L log 240 .029 .039 .044 .007 .040 Total Kjeldahl nitrogen mg/L log 240 .563 .675 .414 .070 2.350 Suspended chlorophyll a μg/L log 240 2.27 3.23 4.06 .40 38.01 Water temperature C none 240 15.7 15.5 2.0 9.3 21.6 Specific conductance μS/cm none 240 478 455 284 27 1,405 Secchi tube depth a cm none 240 112.0 97.3 a 28.9 23.5 >120 Flow per unit area (m 3 /s)/km 2 log 240 .007 .009 .011 .001 .122 Anthropogenic/land-use characteristics Urban % none 240 .00 .01 .01 .00 .14 Agriculture (row crops) % none 240 .20 .24 .21 .00 .78 Agriculture (other) % none 240 .20 .19 .15 .00 .57 Total agriculture % none 240 .46 .42 .31 .00 .94 Grassland % none 240 .09 .10 .08 .00 .39 Wetland (open) % none 240 .02 .04 .06 .00 .48 Wetland (forested) % none 240 .03 .07 .10 .00 .85 Barren % none 240 .01 .02 .02 .00 .21 Forest (all) % none 240 .31 .40 .31 .01 .99 Point-source loading of phosphorus kg/km 2 log 240 .00 1.47 6.44 .00 73.62 Basin characteristics Watershed area km 2 log 240 26.4 121.9 261.8 2.2 1947.1 Air temperature C none 240 6.9 6.5 1.4 3.7 9.2 Precipitation mm none 240 837 836 37 743 926 Runoff mm/yr none 240 229 246 50 152 366 Basin slope degrees none 240 5.92 6.85 3.49 1.35 16.04 Soil characteristics Clay content % none 240 18.10 19.07 10.58 3.43 41.80 Erodibility -- none 240 .28 .26 .07 .11 .40 Organic-matter content % none 240 3.83 5.19 5.06 .30 31.02 Permeability mm/hr none 240 58.32 84.57 66.41 16.00 307.71 Soil slope % none 240 6.03 7.49 4.59 1.02 23.03 Surficial-deposit characteristics Nonglacial deposits % none 240 .00 .23 .41 .00 1.00 Clay % none 240 .00 .12 .30 .00 1.00 Loam % none 240 .00 .08 .26 .00 1.00 Peat % none 240 .00 .01 .04 .00 .42 Sand % none 240 .26 .37 .40 .00 1.00 Sand and gravel % none 240 .01 .19 .28 .00 1.00

a All values greater than 120 cm were set to 120 cm for computation of summary statistics, which result in the mean values being biased low. 

### Methods of Data Collection and Analysis 15

### 1988; Kerans and Karr, 1994; Barbour and others, 1999; and Weigel, 2003). The HBI is an abundance-weightedtolerance index based on the tolerance of each macroinvertebrate taxon to organic pollution and dissolved oxygen depletion. HBI values range from 0 to 10, with higher values indicating more degraded water quality. The five other macroinvertebrate indices included the percentage of individuals that were either Ephemeroptera, Plecoptera, or Trichoptera (EPTN%), the percentage of taxa that were Ephemeroptera, Plecoptera, or Trichoptera (EPTTX%), the percentage of individuals that were scrapers (SCRAP%), the percentage of individuals that were shredders (SHRED%), and the total number of taxa (TAXAN). For each site, each of these indices was computed for the riffle and snag samples separately, and then an average value was computed. The macroinvertebrate indices for each site are summarized in appendix 4.Eight community measures were computed to summarize the fish data. Two measures described the quantity of fish caught: total number of fish caught (FISHN) andtotal number of species caught (FISHSPEC). Five indices described feeding and tolerant classifications: the percentages of top carnivores (CARN%), insectivores(INSECT%), and omnivores (OMNI%), and the percentages of pollution-tolerant (TOL%) and pollution-intolerant (INTOL%) fish (based on Lyons, 1992; and Lyons and others, 1996). In addition, the fish Index of Biotic Integrity (IBI) score was computed by use of both the cold-water (Lyons and others, 1996) and warm-water (Lyons, 1992) versions. Because all of the sites were not classified as awarm-water, cool-water, or cold-water fishery and a coolwater version of the IBI is not available for Wisconsin, the higher of the two IBI scores was used as the site’s fish IBI value. The use of different versions of the IBI compensates for different fish assemblages in different thermal regimes.Differences in the other fish indices represent broad feeding and pollution-tolerance classifications; therefore, themetrics in streams with very different species are comparable. The fish metrics for each site are summarized in appendix 4.



## Statistical Methods

The SAS statistical software package (SAS Institute, Inc., 1989) was used for all statistical analyses except for the redundancy analyses, which were done with the CANOCO statistical software package (ter Braak and Smilauer, 2002), and the regression-tree analyses, which were done with the SPLUS statistical software package (Lam, 2001). 

## Normalization
Before statistical analyses, all water-quality data except the SD data were logarithmically transformed (base10) to improve the normality of the data. This transformation improved the normality of the data although not always to the 5-percent-significance level (Shapiro-Wilk normality test). In addition, all chlorophyll a data, pointsource data, and watershed areas were logarithmically transformed prior to statistical analyses.


## Correlations and Regressions
Spearman correlation analyses were used to determine the relation between each water-quality characteristic and biotic index and each environmental characteristic. This nonparametric procedure was chosen to reduce the influence of the assumption of normal-data distributions. Sequential Bonferroni tests were used to determine the statistical significance of the correlations to eliminate the effects of the number of tests on the significant level (Rice, 1989). Pearson correlation analyses were also used todetermine the relation between each water-quality characteristic and each environmental characteristic prior to theuse of multiple regressions and forward stepwise-regression analysis (with p < 0.05 as the critical level for entry). This procedure was used to determine the magnitude of the interaction between environmental characteristics and water-quality characteristics, as well as to determine the best multivariate relation to estimate concentrations at aspecific site as a function of the environmental characteristics in its watershed.



## Simultaneous Partial Residualization
Many studies (such as Robertson and others, 2006, and this study), have shown that land use not only directly affects water quality, but it is often strongly correlated with the environmental characteristics used to define regions ofsimilar water quality (indirect effects of land use). Therefore, in order to determine the relation between water quality and the nonanthropogenic or natural characteristics, a simultaneous partial-residualization approach, related to partial correlation, was used to remove the agricultural and urban effects from the concentrations of P and N and from the measures of each of the environmental characteristics. 16 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### In simple regression, the relation between the dependent variable Y (for example, P) and a predictor variable X 1 

### (for example, the clay content of the soil in the basin) can be measured by the sample correlation r YX1 

### . If the variable X 1 

### is regressed on the variable X 2 

### (for example,the percentage of agricultural area), the estimated regression equation X 1, 2 = β 0 + β 1 X 2 

### would be obtained. To adjust X 1 

### for the effects of X 2 

### , a “residualized X 1 

### ”, X 1 *


### , can be obtained by computing X 1 * 

### = X 1 

### – X 1,2 

### . In a manner similar to simple correlation, the strength of the relation between Y and X 1 

### adjusted for X 2 

### (in this case, land use) can be obtained by the correlation between the residuals for Y on X 2 

### (Y * 

### ) and the residuals for X 1 

### on X 2 

### (X 1 * 

### ). The resulting correlation is the partial correlation of Y and X 1 

### adjusted for X 2 

### ; the strength of the relation between Y and X 1 

### has been adjusted for the effects of X 2 

### . This approach, described by Weisberg (1980), is easily extended to control for more than one variable; X 2 

### can be replaced by an arbitrary set of variables. In this study, the residualization approach was used to remove the effects of the percentages of agriculture and urban areas and PtS (logarithmically transformed point-source loading in the basin) to enable the relations between the dependent variables P, N, SCHL, and SD and all of the nonanthropogenic environmental characteristics to be further examined. This approach wasnot used to examine relations between environmental characteristics and the biotic indices. Spearman correlations and forward stepwise regressions were done with raw dataand with residualized data to determine which environmental characteristics best described the distribution of each water-quality characteristic.


## Regression-Tree Analysis
In traditional linear-regression analysis, a continuous dependent variable is assumed to be a linear function of a set of independent variables. This is often an unrealistic assumption, and departures from linearity can result in underestimating, or completely discounting, importantindependent variables. Although departures from linearity can be addressed to some extent by trial-and-error data transformations, this approach becomes problematic when independent variables interact in multiple dimensions. The method of regression-tree analysis (Breiman and others, 1984) prevents these problems by not incorporating the assumptions about the shapes of the relations between a dependent variable and one or more independent variables. Regression-tree analysis sequentially partitions the values of each independent variable into two groups, computes mean values of the dependent variable for each group, and then computes square errors for each partition. At each step, all of the independent variables are scanned, and the independent variable and its breakpoint that minimize the least-square-error criterion are chosen. In a manner similarto the F-statistic in an analysis of variance, the leastsquare-error criterion is used to identify breakpoints that maximize the variance of the interpartition means relative to the intrapartition variance. This process partitions the independent-variable space into increasingly homogeneousregions (branches on a tree). The end result of this sequential process is a branching diagram. If only one independent variable is used (for example, the concentration of P or N) at each step in the analysis, the best breakpoint for the independent variable is defined as the value which subdivides values of the dependent variable (for example, IBI) into the two groups with the maximum difference in their mean values. This breakpoint represents the threshold in the response of the dependent variable. Regression-tree analyses were done with variousdependent variables (SCHL, SD, and various biotic indices) and the corresponding independent variables (nutrient concentrations) to determine breakpoints or thresholds inthe responses of the dependent variables to changes in specific nutrient concentrations. In the analysis, the minimum number of sites used to define a subgroup was set to 25 toavoid creating small outlier groups. Regression-tree analysis was also used to determine the value (threshold) below which PtS had minimal effect on P concentrations.


## Redundancy Analysis
Redundancy analysis (RDA) is a form of direct-gradient analysis that describes the variation between twomul tivariate data sets (for example, water-quality and environmental characteristics; ter Braak and Prentice, 1988). In RDA, the site scores from a principal-component analysisare regressed on a specified set of environmental characteristics, and the fitted values of the regression become newsite scores for the following iteration; therefore, the principal component analysis is constrained by the environmental variables (Jongman and others, 1987). RDA was usedin this study to quantify the variance in the dependent variables (for example, water-quality characteristics) explained by the independent variables (for example, environmental characteristics) and to determine which environmental characteristics best explained the variance in water quality. Methods of Data Collection and Analysis 17

### In addition, partial RDA (Richards and others, 1996) wasused to determine the fraction of the variance in the waterquality characteristics explained by specified categories of the environmental characteristics (such as land-use, basin, and soil/surficial-deposit characteristics), and to determine the fraction of the variance in populations of specifiedgroups of the biotic community (such as benthic chlorophyll a concentrations and populations of diatoms, macroinvertebrates, and fish) explained by specified categoriesof environmental characteristics (such as nutrient characteristics and environmental characteristics). Monte Carlo permutation tests with 99 iterations, the default number ofiterations in CANOCO, were used to determine the validity of the total and partial RDA results. Monte Carlo testswere done by permutating the assignment of the independent (environmental) data to the dependent (water-quality or biological) data randomly and repeating the ordinations (Richards and others, 1996; Johnson and others, 1997). 

## Statistical Differences among Groups
To determine whether any apparent differences among groupings of data (such as reference sites compared to nonreference sites) were statistically significant, the nonparametric Kruskal-Wallis rank analysis of variance test was used, fol lowed by a Tukey multiple-comparison procedure (SAS Institute, Inc., 1989). For all statistically significant differ ences, the probability of their occurringby chance was less than 5 percent (p < 0.05), unless otherwise specified. 18 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### Median monthly concentrations of total P ranged from 0.012 to 1.641 mg/L (table 2 on page 15). The overall median and mean were 0.085 and 0.116 mg/L, respectively. Highest concentrations were measured in the central part of the State, especially south of Green Bay (fig. 5). High concentrations were also measured in the southwestern part of the State. The lowest P concentrations were measured in the northern one-third of the State. The highest P concentrations were measured in June and July, and the lowest concentrations were measured in October (table 3). Median monthly concentrations of DP ranged from 0.004 mg/L (less than the 0.005 mg/L detection limit) to 1.495 mg/L (table 2). The overall median and mean were 0.050 and 0.079 mg/L, respectively. The distribution and seasonality in DP concentrations were similar to total P concentrations (table 3). DP concentrations were strongly correlated to total P concentrations. Pearson correlation coefficients (r values) between DP and P ranged from 0.90 in June to 0.98 in September. DP represented about 53 to 62 percent of the phosphorus during May through July and about 70 percent during August through October. Median monthly concentrations of N ranged from 0.131 to 21.260 mg/L (table 2). The overall median andmean were 1.695 and 2.807 mg/L, respectively. The highest median N concentrations were measured in the southern quarter of the State and the eastern half of the State (fig. 5). The lowest N concentrations were found in the northern quarter of the State. The highest N concentrations were measured in June, but no consistent seasonal patterns were measured (table 3). Median monthly concentrations of NO 3 

### -N ranged from 0.005 mg/L (less than the 0.010 mg/L detection limit) to 20.550 mg/L (table 2). The overall median and mean were 1.048 and 2.086 mg/L, respectively. Median monthly concentrations of NH 4 

### -N ranged from 0.007 mg/L (less than the 0.013 mg/L detection limit) to 0.040 mg/L. The overall median and mean were 0.029 and 0.039 mg/L, respectively. Median monthly concentrations of TKN ranged from 0.070 mg/L (less the 0.140 mg/L detection limit) to 2.350 mg/L. The overall median and mean were 0.563 and 0.675 mg/L, respectively. Most of the nitrogen was in the form of NO 3 

### -N (ranging from 63 percent in June to 73–79 percent in other months). Highest NO 3 

### -N 

# Water Quality and Its Relations with Environmental Characteristics in the Watershed Water Quality and Its Relations with Environmental Characteristics in the Watershed 19

U.S. Geological Survey personnel collecting streamflow measurements.

### Total phosphorus (P)

0.012 – 0.03 8 Concentrations, in milligrams per liter Concentrations, in milligrams per liter

Depth, in centimeters Concentrations, in micrograms per liter 0.039 – 0.066 0.067 – 0.103 0.104 – 0.162 0.163 – 1.641

0.404 – 1.44 1.45 – 1.99 2.00 – 2.56 2.57 – 3. 8 0 3. 8 1 – 3 8 .01 0.131 – 0.735 0.736 – 1.361 1.362 – 2.245 2.246 – 4.500 4.501 – 21.260

24 – 67 6 8 – 102 103 – 119 r 120 

### Total nitrogen (N)

Suspended chlorophyll a (SCHL) Secchi tube depth (SD)

Figure 5. Distributions (quintiles) of median monthly total phosphorus (P), total nitrogen (N), and suspended chlorophyll a concentrations (SCHL), and Secchi tube depth (SD) for the studied wadeable streams in Wisconsin. (Note: the upper 40 percent of SDs were all greater than or equal to 120 centimeters.) 

### 20 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### and TKN concentrations were measured in June, but no consistent seasonal patterns were measured in any form of nitrogen. Median monthly concentrations of SCHL ranged from 0.40 to 38.01 μg/L (table 2). The overall median and mean were 2.27 and 3.23 μg/L, respectively. Highest SCHL concentrations were measured in the central and eastern parts of the State, especially south of Green Bay and north of Milwaukee (fig. 5). Lowest SCHL concentrations were measured in the northern one-third of the State and in thesouthwestern part of the State. Highest SCHL concentrations were measured in July, and lowest concentrations were measured in September and October (table 3). Median monthly SDs ranged from 23.5 cm to greaterthan 120 cm (table 2). Many sites consistently had clarities greater than the length of the Secchi tube. The overall median and mean were 112 and 97.3 cm, respectively.Highest SDs (the best clarities) were measured in the northern half of the State (fig. 5). Lowest SDs (the worst clarities) were measured in the southwestern and central parts of the State and south of Green Bay. Lowest SDs were measured during May through July, and the highest SDs were measured during August through October (table 3). 

## Relations between Water Quality and Environmental Characteristics in the Watershed
Correlations between Individual Characteristics
Spearman correlation coefficients (r
s 

### values) between median water-quality characteristics are shown in table 4. P and DP were significantly correlated with N, NO 3 

### -N, NH 4 

### -N, and TKN (r
s 

### values ranged from 0.36 to 0.61). Correlations between P and the nitrogen species wereslightly stronger than between DP and the nitrogen species. Concentrations of N were strongly correlated (r
s 

### = 0.91) to NO 3 

### -N because NO 3 

### -N was the major form of nitrogen. Concentrations of NH 4 

### -N and TKN were more strongly correlated to one another (r
s 

### = 0.66) and to P (r
s 

### ~ 0.6) than they were to total N and NO 3 

### -N (r
s 

### ~ 0.1–0.3). NH 4 

### -N is part of TKN; therefore, a correlation between these two forms of nitrogen was expected. Total organic nitrogen was computed by subtracting the NH 4 

### -N concentration from the TKN concentration. Total organic nitrogen and NH 4 

### -N were still strongly correlated with one

Table 3. Median and average monthly concentrations for total and dissolved phosphorus, suspended chlorophyll a , total nitrogen, nitrite plus nitrate, ammonia, and Kjeldahl nitrogen, and Secchi tube depths in the studied wadeable streams in Wisconsin.
[mg/L, milligram per liter; μg/L, microgram per liter; cm, centimeter; >, greater than; all concentrations are in mg/L, except chlorophyll a , which is in μg/L, and Secchi tube depth, which is in cm]

Total phosphorus Dissolved phosphorus Chlorophyll a Secchi tube depth Month Median Average Median Average Median Average Median Average May 0.070 0.115 0.037 0.071 2.890 4.420 105.0 89.8 June .107 .164 .058 .101 2.120 3.120 88.5 79.6 July .092 .143 .052 .089 3.042 7.885 90.0 82.9 August .088 .138 .059 .096 2.168 5.096 > 120 92.9 September .075 .120 .049 .085 1.773 3.336 > 120 101.1 October .049 .101 .035 .070 1.546 2.922 > 120 107.9

Total nitrogen Nitrite plus nitrate Ammonia Kjeldahl nitrogen Month Median Average Median Average Median Average Median Average May 1.589 2.919 0.911 2.120 0.030 0.061 0.700 0.800
June 2.110 3.949 1.120 2.500 .033 .049 .790 .949 July 1.740 2.851 .903 2.083 .032 .067 .560 .768 August 1.573 2.634 .788 1.919 .031 .062 .525 .715 September 1.622 2.750 .987 2.115 .031 .060 .510 .650 October 1.657 2.834 1.080 2.229 .027 .046 .470 .606 

### Water Quality and Its Relations with Environmental Characteristics in the Watershed 21Table 4.Spearman correlation coefficients (rs) between median concentrations of total phosphorus, dissolved phosphorus, total nitrogen, nitrite plus nitrate, ammonia, totalKjeldahl nitrogen, median Secchi tube depths, suspended chlorophyllaconcentrations, percentages of urban and agricultural areas, point-source loadings of phosphorus, andspecific environmental (anthropogenic/land-use, basin, soil and surficial-deposit) characteristics for the studied wadeable streams in Wisconsin.[P, total phosphorus; DP, dissolved phosphorus; N; total nitrogen; NO3-N, nitrite plus nitrate; NH4-N, ammonia; TKN, total Kjeldahl nitrogen; SD, Secchi tube depth; SCHL, suspended chlorophyllaconcentration; % Urb, percentage of urban area; % Ag, percentage of agricultural area; PtS, point-source loading of phosphorusin kilograms per square kilometer; <, less than; no PtS, only sites with less than12 kilograms per square kilometer of point-source loading of phosphorus are included in analysis; all values with an absolute value greater than 0.22 are statistically significant at p < 0.05; all valueswith an absolute value greater than 0.4 are inbold]Characteristic PP(no PtS)DPDP(no PtS)N NO3-N NH4-N TKN SD SCHL % Urb % Ag PtSWater-quality characteristicsTotal phosphorus1.00 1.00 0.95 0.95 0.540.380.61 0.56 -0.57 0.440.140.67.29Dissolved phosphorus0.95 0.95 1.00 1.00 .51.36.55 .52 -.48.35 .11.63.27Total nitrogen.54 .52 .51 .50 1.00 .91.29 .19-.55.31 .28.81.19Dissolved nitriteplus nitrate.38 .37 .36 .35.91 1.00.11 -.12-.42.18 .29.77.18Dissolved ammonia.61 .61 .55 .56.29 .111.00 .66 -.48.35 -.02 .34 -.02Total Kjeldahlnitrogen.56 .55 .52 .52.19 -.12.66 1.00-.38.45.04 .25 .08Suspendedchlorophylla.44 .43.35 .34 .31 .18 .35.45 -.40 1.00.25.45.29Secchi tube depth-.56 -.55 -.48 -.46 -.55 -.42 -.47-.381.00 -.40-.26-.55-.23Anthropogenic/land-use characteristicsUrban .14 .08 .11 .05 .28 .29 -.02 .04 -.26 .251.00.20.49Agriculture(row crops).65 .65 .60 .59 .81 .73.37 .33-.55 .46.23.94.20Agriculture (other).56 .56 .56 .56 .61 .63.22 .04 -.37 .31 .16.80.22Total agriculture.67 .67 .63 .63 .81 .76.34 .25-.55 .45.201.00.21Grassland .02 .03 .03 .04 .17 .25 -.02 -.19 .07 -.07 .21 .00 .08Wetland (open) .07 .06 .03 .02 -.10 -.23 .18.48-.04 .21 .18 -.10 .18Wetland (forested) -.22 -.21 -.21 -.20-.52 -.66.08.47.27 -.04 -.10-.52-.08Barren .34 .32 .29 .27 .37 .33 .14 .22 -.23.40.33.46.17Forest (all)-.64 -.63 -.58 -.58 -.83 -.75-.38 -.30.57 -.47-.27-.94-.21Point-source loadingof phosphorus.29 .22 .27 .19 .19 .18 -.02 .08 -.23 .29.49.211.00 

### 22 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in WisconsinCharacteristic PP(no PtS)DPDP(no PtS)N NO3-N NH4-N TKN SD SCHL % Urb % Ag PtSBasin characteristicsWatershed area -0.07 -0.07 -0.08 -0.09 -0.06 -0.02 -0.23 -0.04 0.03 0.21 0.28 -0.040.51Air temperature.50 .47 .44 .42 .76 .74.29 .09-.55.30 0.250.760.15Precipitation .07 .04 .05 .02 .27 .36 -.07 -.32 -.17 .03 0.20 0.14 0.02Runoff-.48 -.48 -.43 -.43 -.60 -.59-.36 -.19.41-.25 -0.24-0.62-0.16Basin slope .19 .20 .22 .23 .17 .31 .00 -.39 -.14 -.15 -0.05 0.23 0.03Flow per unit area -.21 -.20 -.17 -.16 -.17 -.13 -.13 -.18 .15 -.16 -0.04 -0.25 -0.18Soil characteristicsClay content.52 .53 .52 .52 .58 .58.24 .04-.54.22 0.140.730.15Erodibility.54 .55 .55 .55 .57 .55.21 .15-.47.35 0.110.760.12Organic mattercontent-.34 -.36 -.35 -.36 -.38-.51-.05 .33 .17 .01 0.02 -0.40 -0.05Permeability-.53 -.54 -.54 -.56 -.46 -.44-.21 -.09.48-.21 -0.05-0.63-0.09Soil slope -.31 -.32 -.30 -.30 -.21 .01 -.35-.68.28 -.34 -0.06 -0.30 -0.04Surficial-deposit characteristicsNonglacial deposits .03 .02 .03 .02 .26 .36 -.11-.45-.17 -.01 0.05 0.22 0.09Clay .26 .28 .24 .25 .09 .04 .21 .31 -.29 .20 0.06 0.31 0.16Loam .23 .26 .22 .25 -.04 -.07 .07 .18 .04 -.01 -0.02 0.06 0.15Peat -.06 -.06 -.08 -.07 -.14 -.20 .09 .17 -.08 .07 -0.05 -0.20 0.05Sand -.13 -.14 -.14 -.15 -.16 -.24 -.04 .20 .12 .08 0.05 -0.22 -0.05Sand and gravel-.42 -.44 -.43 -.45-.34 -.33 -.13 .07 .23 -.08 0.13-0.420.05Table 4.Spearman correlation coefficients (rs) between median concentrations of total phosphorus, dissolved phosphorus, total nitrogen, nitrite plus nitrate, ammonia, totalKjeldahl nitrogen, median Secchi tube depths, suspended chlorophyllaconcentrations, percentages of urban and agricultural areas, point-source loadings of phosphorus, andspecific environmental (anthropogenic/land-use, basin, soil and surficial-deposit) characteristics for the studied wadeable streams in Wisconsin—Continued.[P, total phosphorus; DP, dissolved phosphorus; N; total nitrogen; NO3-N, nitrite plus nitrate; NH4-N, ammonia; TKN, total Kjeldahl nitrogen; SD, Secchi tube depth; SCHL, suspended chlorophyllaconcentration; % Urb, percentage of urban area; % Ag, percentage of agricultural area; PtS, point-source loading of phosphorusin kilograms per square kilometer; <, less than; no PtS, only sites with less than12 kilograms per square kilometer of point-source loading of phosphorus are included in analysis; all values with an absolute value greater than 0.22 are statistically significant at p < 0.05; all valueswith an absolute value greater than 0.4 are inbold] 

### Water Quality and Its Relations with Environmental Characteristics in the Watershed 23

### another (r
s 

### = 0.62). Concentrations of P and DP were also significantly correlated with the PtS in the basin (r
s 

### ~ 0.3). The six streams with PtS values higher than 12 kg/km 2 

### had some of the highest measured P (ranging from 0.17 to 1.64 mg/L) and DP concentrations (ranging from 0.098 to 1.49 mg/L). Annual PtS below 12 kg/km 2 

### had little effect on the concentrations of P and DP in the streams (on the basis of results from regression-tree analyses and graphical examination of the data). Omitting the six streams with PtS greater than 12 kg/km 2 

### from the analyses, however, hadlittle effect on the correlations with the other characteristics (table 4). Spearman correlation coefficients between the water-quality characteristics and each environmental characteristic (anthropogenic/land-use, basin, soil, and surficial-deposit characteristics) are also shown in table4. All water-quality characteristics were significantly correlated with many environmental characteristics; however, they were most strongly correlated with characteristics describing land use (presence of agriculture or absence of forest), basin characteristics describing air temperature and runoff from the watershed, and the soil characteristics (clay content, erodibility, and permeability). In general, N (and NO 3 

### -N) and P (and DP) were correlated with thesame environmental characteristics; however, the correlations with N concentrations were generally stronger than with P concentrations. Concentrations of NH 4 

### -N and TKN were less strongly correlated with the nonanthropogenic or natural environmental characteristics than the other water-quality characteristics. Concentrations of NH 4 

### -N were most strongly correlated with runoff and soil slope (r
s 

### ~ -0.35) and concentrations of TKN were most strongly correlated with soil slope (r
s 

### = -0.68). Concentrations of SCHL were significantly correlated with all but one of the nutrient constituents (the exception is NO 3 

### -N with r
s 

### = 0.18). Concentrations of SCHL were most strongly correlated with TKN and P (r
s 

### ~ .45), less strongly correlated with NH 4 

### -N, DP, and N (r
s 

### = 0.31 to

r s 

### = 0.35), and insignificantly correlated with NO 3 

### -N (r
s 

### = 0.18). Concentrations of SCHL were significantlycorrelated with most environmental characteristics; however, they were most strongly correlated with land-use characteristics (positively correlated with the percentage of total agriculture and negatively correlated with the percentage of forest), basin characteristics describing the air temperature and runoff from the watershed, and soil properties in the watershed (erodibility and soil slope). SDs were most strongly correlated with many of the same characteristics as SCHL; however, SDs were more stronglycorrelated with most characteristics, especially more correlated with N, NO 3 

### -N, clay content, and runoff. Similar results were obtained if only sites with SDs less than 120 cm were included in the analysis; however, the correlation coefficients were slightly smaller.



### Correlations with Individual Characteristics after Removing Relations with Anthropogenic Characteristics Many of the environmental characteristics were strongly correlated with the anthropogenic characteristics (characteristics describing the land use and PtS in the basin), primarily the percentage of agriculture in the basin, and less strongly with the percentage of urban area and the PtS in the basin (table 4). Many of the nonanthropogenic or natural characteristics were also strongly correlated with the anthropogenic characteristics. For example, air temperature and runoff were correlated with the percentage of agriculture (r
s 

### values of 0.76 and -0.62, respectively). Therefore, even if the anthropogenic characteristics were not included in further statistical analyses, their effectscould be incorporated into the final results by use of characteristics such as air temperature.To examine the relations between the nonanthropogenic characteristics and the water-quality characteristicsfurther, the relations between the anthropogenic characteristics (percentages of agriculture, Ag %, and urban, Urb %, areas in the basin and the PtS in the basin) and P, N,SCHL, and SD were removed by use of simultaneous partial-residualization. Residualized P, N, and SCHL concentrations and SDs were computed with equations 2–9:

Log P Res 

### = Log P Measured 

### – Log P Predicted 

### , (2) where Log P Predicted 

### = -1.448 + 0.744 Ag % – 1.101 Urb % + 0.267 Log(PtS) (3) R 2 

### = 0.49;

Log N Res 

### = Log N Measured 

### – Log N Predicted 

### , (4) where Log N Predicted 

### = -0.247 + 1.112 Ag % + 3.830 Urb % + 0.045 Log(PtS) (5) R 2 

### = 0.68;

Log SCHL Res 

### = Log SCHL Measured 

### – Log SCHL Predicted 

### , (6) where Log SCHL Predicted 

### = 0.182 + 0.383 Ag % – 0.860 Urb % + 0.260 Log(PtS) (7) R 2 

### = 0.26; 24 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### SD Res 

### = SD Measured 

### – SD Predicted 

### , (8) where SD Predicted 

### = 119.6 – 47.371 Ag % – 227.5 Urb % + 8.039 Log(PtS) (9) R 2 

### = 0.30.

Residual transformations were also applied to all of the other water-quality and environmental characteristics.Spearman correlation coefficients between the residualized values for the water-quality characteristics and the residualized values for the environmental characteristics are shown in table 5. Residualized concentrations and SDs were still significantly correlated with many residualized environmental characteristics; however, they were not as strongly correlated. P Res 

### and DP Res 

### concentrations were most strongly correlated with residualized permeability ofthe soil, residualized soil slope, and residualized sand-andgravel surficial deposits. Basins with more permeable soils had lower P Res 

### concentrations. N Res 

### concentrations were most strongly correlated with various basin characteristics (residualized air temperature, precipitation, and runoff) and residualized clay content of the surficial deposits. Highest N Res 

### concentrations occurred in areas with warmer air temperatures, more precipitation, lower runoff, and lower clay content in the surficial deposits. Highest NO 3 

### -N Res 

### concentrations also occurred in these areas, especially if the areas had steep slopes. Highest TKN Res 

### concentrations occurred where NO 3 

### -N Res 

### concentrations were the lowest. Residualized SCHL concentrations were most strongly correlated with the slopes of the terrain and the soils, organic-matter content, and some surficial-deposit characteristics. Lowest SCHL Res 

### concentrations occurred in areas with steep terrain and high organic-matter content. Residualized SDs were most strongly correlated with the clay content of the soil and surficial deposits; the best water clarity occurred in areas with low clay content.


## Thresholds in Water-Quality Responses
Concentrations of P and N were significantly correlated with the percentage of agriculture in the watershed. To define these relations better, logarithmically transformed P and N concentrations were plotted against the percentage of agriculture in the watershed (fig. 6), and regression-tree analyses were done to determine the percentages of agriculture that were the best breakpoints or thresholds in the responses. Regression-tree results indicate that the best statistically significant (p < 0.001) breakpoints in the responses of P and N to percentages of total agriculture were at 14.1 and 21.3 percent, respectively. In both cases, however, the relations between P and N concentrations and the percentage of agriculture appear linear and the line determined with linear regression better defined the response than a step change in values (on the basis of a mean-square-error criterion). Concentrations of SCHL were significantly correlated with P and N concentrations (tables 4 and 5). To better define these relations, logarithmically transformed SCHLconcentrations were plotted against logarithmically transformed P and N concentrations (fig. 7) and regression-tree analyses were done. Regression-tree results indicate that the best breakpoint in the response of SCHL to changes in P concentration was at 0.070 mg/L (log P = -1.16) and to changes in N concentrations occurred at 1.169 mg/L(log N = 0.07); both breakpoints were statistically significant at p < 0.001. The relations between SCHL and P and N concentrations appear linear and the regression line defines the response better than a step change in median P concentrations; however, the step-change response betterdefines the relation with N (on the basis of a mean-squareerror criterion). A similar response was found between P and SCHL in temperate streams, with the greatest increase in SCHL occurring at P concentrations less than 0.1 mg/L (Van Nieuwenhuyse and Jones, 1996). To define the relations between SDs and P and Nconcentrations better, SDs were plotted against logarithmically transformed P and N concentrations (fig. 7) and regression-tree analyses were done. There was little apparent relation between SDs and P and between SDs and N at lower nutrient concentrations because of the limited length of the Secchi tube; however, with higher nutrient concentrations, SDs gradually decreased. Regression-tree results indicate that the best breakpoint in the response of SDs to changes in P concentrations was at 0.106 mg/L (log P = -0.97) and to changes in N concentrations was at3.305 mg/L (log N = 0.52); both breakpoints were statistically significant at p < 0.001. A regression line defines the response better than a step change for P and N (on the basis of a mean-square-error criterion). The reduction in SDs with increasing nutrient concentrations may have been caused by other factors that are correlated to P and N concentrations, such as the clay content of the soils and surficial deposits (table 4). Water Quality and Its Relations with Environmental Characteristics in the Watershed 25

### Table 5. Spearman correlation coefficients (r
s 

### ) between residualized logarithmically transformed median concentrations of total phosphorus, dissolved phosphorus, nitrogen, nitrite plus nitrate, total Kjeldahl nitrogen, ammonia and suspended chlorophyll a , median Secchi tube depths, and specific residualized environmental (basin, soil, and surficial-deposit) characteristics for the studied wadeable streams in Wisconsin.

[P Res , residualized total phosphorus; DP Res , residualized dissolved phosphorus; N Res residualized nitrogen; NO 3 -N Res , residualized nitrite plus nitrate; NH 4 -N Res . residualized ammonia; TKN Res , residualized total Kjeldahl nitrogen; SD Res , residualized Secchi tube depth; SCHL Res , residualized suspended chlorophyll a concentration; all values with an absolute value greater than 0.18 are statistically significant at p < 0.05; all statisticall y significant values (not including relations between nutrients) are in bold ]

Residualized characteristic P Res DP Res N Res NO 3 -N Res NH 4 -N Res TKN Res SD Res SCHL Res Residualized water-quality characteristics Total phosphorus 1.00 0.91 -0.02 -0.29 0.58 0.55 -0.26 0.22 Dissolved phosphorus .91 1.00 .00 -.22 .50 .48 -.15 .07 Total nitrogen -.02 .00 1.00 .55 .09 .01 -.15 -.11 Dissolved nitrite plus nitrate -.29 -.22 .55 1.00 -.22 -.56 .14 -.30 Dissolved ammonia .58 .50 .09 -.22 1.00 .63 -.31 .28 Total Kjeldahl nitrogen .55 .48 .01 -.56 .63 1.00 -.25 .40 Suspended chlorophyll a .22 .07 -.11 -.30 .28 .40 -.18 1.00 Secchi tube depth -.26 -.15 -.15 .14 -.31 -.25 1.00 -.18 Residualized basin characteristics
Watershed area -.18 -.19 -.06 .03 -.22 -.05 .09 .14 Air temperature -.08 -.09 .24 .43 .00 -.27 -.06 -.10 Precipitation -.07 -.06 .22 .36 -.12 -.37 -.05 -.03 Runoff -.10 -.08 -.18 -.41 -.18 .04 -.07 .03 Basin slope .01 .07 .01 .33 -.09 -.48 .01 -.32 Flow per unit area -.05 -.01 .09 .13 -.06 -.16 .06 -.08 Residualized soil characteristics Clay content .08 .15 -.11 .02 -.04 -.19 -.28 -.13 Erodibility .13 .19 -.09 -.02 -.08 -.12 -.02 .00 Organic-matter content -.11 -.16 -.09 -.44 .08 .41 -.13 .23 Permeability -.28 -.34 .06 .01 -.02 .06 .14 .07 Soil slope -.20 -.19 .06 .39 -.23 -.61 .09 -.24 Residualized surficial-deposit characteristics Nonglacial deposits -.18 -.13 .16 .28 -.19 -.50 -.02 -.19 Clay .12 .12 -.27 -.34 .10 .27 -.22 .06 Loam .12 .11 -.09 -.13 .03 .11 .05 -.06 Peat .06 .03 .07 -.03 .08 .09 -.04 .04 Sand .05 -.01 .03 -.21 .04 .28 .02 .25 Sand and gravel -.31 -.33 -.01 -.02 -.03 .14 .04 .07 

### 26 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsiny = 0.79x - 1.44 R 2 = 0.44

-2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0

0 10 20 14.1 percent

30 40 50 60 70 80 90 100
PERCENTAGE OF TOTAL AGRICULTURAL LAND USE IN BASINLOG (TOTAL PHOSPHORUS, IN MILLIGRAMS PER LITER)LOG (TOTAL NITROGEN, IN MILLIGRAMS PER LITER)

y = 1.13x - 0.23 R 2 = 0.66

-1.0 -0.5 0.0 0.5 1.0 1.5

0 10 20 21.3 percent

30 40 50 60 70 80 90 100 PERCENTAGE OF TOTAL AGRICULTURAL LAND USE IN BASIN



### Figure 6. Total phosphorus and total nitrogen concentrations as a function of the percentage of total agriculture in the watersheds of the studied wadeable streams in Wisconsin. Computed thresholds in the response are identified by vertical lines. Linear-regression lines and coefficients of determination (R 2 

### ) are given on each graph. 

### Water Quality and Its Relations with Environmental Characteristics in the Watershed 27Suspended chlorophyllaconcentrationy = 0.37x + 0.79R2= 0.20-0.50.00.51.01.52.0-2.0 -1.5 -1.0 -0.5 0.0 0.5LOG (MEDIAN TOTAL PHOSPHORUS, IN MILLIGRAMS PER LITER)

LOG (CHLOROPHYLL A , IN MICROGRAMS PER LITER) LOG (CHLOROPHYLL A , IN MICROGRAMS PER LITER)Secchi tube depthy = -41.69x + 51.28R2= 0.28020406080100120-2.0 -1.5 -1.0 -0.5 0.0 0.5LOG (MEDIAN TOTAL PHOSPHORUS, IN MILLIGRAMS PER LITER)

SECCHI TUBE DEPTH, IN CENTIMETERS SECCHI TUBE DEPTH, IN CENTIMETERSSuspended chlorophyllaconcentrationy = 0.23x + 0.32R2= 0.10-0.50.00.51.01.52.0-1.0 -0.5 0.0 0.5 1.0 1.5LOG (MEDIAN TOTAL NITROGEN, IN MILLIGRAMS PER LITER)Secchi tube depthy = -35.48x + 106.14R2= 0.28020406080100120-1.0 -0.5 0.0 0.5 1.0 1.5LOG (MEDIAN TOTAL NITROGEN, IN MILLIGRAMS PER LITER)-1.16 (0.070 mg/L)0.07 (1.169 mg/L)0.52 (3.305 mg/L)-0.97 (0.106 mg/L)Figure 7.Suspended chlorophylla(SCHL) concentrations and Secchi tube depths (SDs) as a function of median total phosphorus and total nitrogen concentrations(logarithmto base 10 transformation) for the studied wadeable streams in Wisconsin. Linear-regression lines and coefficients of determination (R2) are given on each graph. 

### 28 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

## Effects of Multiple Environmental Characteristics on Water Quality Stepwise Regression Forward stepwise regressions were done with all of the environmental characteristics to determine which three environmental characteristics best described the variance in P, N, and SCHL concentrations and SDs, done with only the nonanthropogenic (natural) characteristics to determinewhich of these characteristics best described the variance, and done with residualized characteristics (whose correlations with anthropogenic characteristics had been removed) best described the variance in the water-quality characteristics. Models with more than three variables did not significantly increase the amount of variance explained (accumulative R 2 

### values).The percentage of total agriculture was the first variable incorporated into the model explaining variability in P concentrations; the second and third variables were log PtSand the percentage of loam deposits in the basin, respectively (table 6). Collectively, this model explained 56percent of the variance in P concentrations. If the anthropogenic characteristics were omitted from the analysis, the erodibility of the soil was the first variable incorporated into the model, runoff was second, and the percentage of loam deposits was third. This model explained 44 percent of the variance. After the characteristics were adjusted to remove the anthropogenic effects, residualized loam deposits became the first variable incorporated into the model, residualized sand-and-gravel deposits was second, and residualized nonglacial deposits was third. This model collectively explained 19 percent of the variance in P Res 

### . The difference in the amount of variance explained by the first two regression models was caused by the removal of the effects of the anthropogenic characteristics that were not correlated with other environmental characteristics in the second model. The large difference in the amount of variance explained by the last two regressions was caused by the removal of all of the effects of the anthropogenic characteristics, including the independent (direct) effects and correlated (indirect) effects on the other variables. The percentage of total forest in the basin was thefirst variable incorporated into the model explaining variability in N concentrations, precipitation was the second, and the percentage of row crops in the basin was the third. Collectively, this model explained 72 percent of thevariance in N concentrations. If the anthropogenic characteristics were omitted from the analysis, air temperature was the first variable, soil slope was the second, and theclay content of the soil was the third. After the characteristics were adjusted to remove the anthropogenic effects, residualized clay deposits was the first variable included in the model, residualized air temperature was the second, and residualized peat deposits was the third. This model collectively explained 20 percent of the variance in N concentrations.For both of these constituents, removing the anthropogenic effects greatly reduced the predictability of the regression models. When the direct and indirect effects of the anthropogenic characteristics were included in the models, 56 to 72 percent of the variance could be explained with three variables; however, when all of the anthropogenic effects were removed, the models only explained about 20 percent of the variance. To develop regression models to predict SCHL andSD, all of the water-quality characteristics and environmental characteristics (including the physical-habitat characteristics, such as shading, streambank erosion, and so on) were included. The percentage of total forest in the basin was the first variable incorporated into the model to predict SCHL, TKN was the second, and watershed area was the third.Collectively, this model explained 42 percent of the variance in SCHL concentrations. If the anthropogenic characteristics were simply omitted from the analysis, TKN was the first variable selected, watershed area was the second, and soil erodibility was the third. After the environmental characteristics were adjusted to remove the anthropogenic effects, TKN was the first variable incorporated in the model, watershed area was the second, and P was the third. This model explained 36 percent of the total variance. The percentage of row-crop agriculture in the basin was the first variable incorporated into the model to predict SDs, percentage of clay deposits was the second, and TKN was the third. Collectively, this model explained 43 percentof the variance in SDs. When the anthropogenic characteristics were omitted, total P was the first variable incorporated into the model, the percentage of clay deposits was the second, and DP was the third. After the environmental characteristics were adjusted to remove the anthropogenic effects, total P was the first variable included in the model, total N was the second, and DP was the third. This model explained 42 percent of the total variance.Removing the anthropogenic effects on the environmental characteristics had little effect on the predictability of the SCHL and SD models when nutrients were includedin the models (second and third models). The anthropogenic characteristics were strongly correlated with nutrient concentrations, and therefore, similar predictability wasobtained by including either the anthropogenic characteristics or the nutrient concentrations. The SD models Water Quality and Its Relations with Environmental Characteristics in the Watershed 29

### Table 6. Results of forward stepwise-regression analyses used to explain the variance in raw and residualized water-quality concentrations in the studied wadeable streams in Wisconsin.
[all regressions were on log-transformed concentrations; r, Pearson correlation coefficient; R 2 , coefficient of determination for the one, two, and three variable models; Res, residualized]

Dependent variable First variable Second variable Third variable Total phosphorus (P) All environmental characteristics

P Total agriculture Point-source loading Loam deposits r 0.66 0.34 0.24 Accumulative R 2 .44 .51 .56 No anthropogenic characteristics

P Erodibility Runoff Loam deposits r .54 -.54 .24 Accumulative R 2 .29 .38 .44 Residualized characteristics

P Res Loam Res deposits Sand-and-gravel Res deposits Nonglacial Res deposits r .30 -.29 -.16 Accumulative R 2 .09 .15 .19 Total nitrogen (N) All environmental characteristics

N Total forest Precipitation Agriculture (row) r -.82 .29 .77 Accumulative R 2 .67 .69 .72 No anthropogenic characteristics

N Air temperature Soil slope Clay content of soil r .75 -.19 .51 Accumulative R 2 .56 .59 .61 Residualized characteristics

N Res Clay Res deposits Air temperature Res Peat Res deposits r -.35 .25 .16 Accumulative R 2 .12 .17 .20 Suspended chlorophyll a (SCHL) All environmental characteristics

SCHL Total forest Kjeldahl nitrogen Watershed area r -.47 .46 .28 Accumulative R 2 .22 .33 .42 No anthropogenic characteristics

SCHL Kjeldahl nitrogen Watershed area Erodibility r .46 .28 .33 Accumulative R 2 .21 .30 .41 Residualized characteristics

SCHL Res Kjeldahl nitrogen Watershed area Res Total phosphorus r .46 .28 .44 Accumulative R 2 .21 .30 .36 Secchi tube depth (SD) All environmental characteristics

SD Agriculture (row) Clay deposits Kjeldahl nitrogen r -.55 -.32 -.37 Accumulative R 2 .30 .37 .43 No anthropogenic characteristics

SD Total phosphorus Clay deposits Dissolved phosphorus r -.53 -.32 -.44 Accumulative R 2 .28 .36 .44 Residualized characteristics

SD Res Total phosphorus Total nitrogen Dissolved phosphorus r -.53 -.53 -.44 Accumulative R 2 .28 .36 .42 

### 30 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### that included both P concentration and percentage of clay deposits were significantly better than models that only included P concentrations.


### Redundancy Analysis Each of the four primary water-quality characteristics (P, N, SCHL, and SD) has been shown to be influenced by the anthropogenic characteristics and other characteristics in the watershed upstream from the assessment site. Therelative importance of these factors differs for each characteristic. The relative impor tance of each of the generaltypes of environmental characteristics thought to influence the distribution of overall water quality, as defined by these four water-quality characteristics, was determined by partial RDA. In the partial RDA, the environmental characteristics were divided into three main categories: anthropogenic/land-use characteristics, soil and surficial-deposit characteristics, and basin characteristics (table 2). A two-step process was used to select four characteristics to describe each category. The characteristics initially chosen werethose significantly correlated with the individual waterquality characteristics. The final characteristics within a specific category were chosen to have minimal correlationsamong themselves. For example, the percentage of agriculture and the percentage of forest, although both strongly correlated with water quality, were not both chosen for the anthropogenic/land-use category because they were strongly correlated to one another. The anthropogenic/ land-use category was described by the percentages of total agriculture, urban, and open wetland, and the log PtS in the basin. Soils/surficial deposits were described by theclay content and organic-matter content of the soils, permeability, and erodibility. The basin characteristics were described by log (watershed area), precipitation, runoff,and basin slope. The anthropogenic/land-use characteristics category reflects the extent of human intervention—characteristics that may be altered. The soil and surficialdeposit characteristics and basin characteristics catego riesreflect the geological and topographical effects—characteristics that cannot be altered.The total variance in the four water-quality characteristics was separated into five categories: 1) variance explained by the anthropogenic/land-use characteristics alone, 2) variance explained by soil and surficial-deposit characteristics alone, 3) variance explained by the basinchar acteristics alone, 4) variance explained by the interactions of anthropogenic/land-use, soil and surficial-deposit, and basin character istics (joint variation that could not be assigned to a single category), and 5) variance not explained by these characteristics. Results from the partial RDA indicated that these 12 characteristics collectively explained 43 percent of the variance in water quality (P, N,SCHL, and SD; p < 0.001). Independently, the anthropogenic/land-use characteristics explained 12 percent of the explained variance (5 percent of the total variance;p < 0.001; fig. 8), the soil and surficial-deposit characteristics explained 17 percent of the explained variance (7 percent of the total variance; p < 0.001), and the basincharacteristics explained 4 percent of the explained variance (2 percent of the total variance; p < 0.15). The shared contribution or interactions of all three general categories of environmental characteristics explained about 67 of the explained variance or 30 percent of the total variance. Therefore, much of the variance in water quality could not be explained by a single category of environmental characteristics.RDA was also used to determine which environmental characteristics explained the most variance in overallwater quality (P, N, SCHL, and SD). In RDA, as in principal-component analysis, the explained variance is separated into a series of ordination (canonical) axes. Almost all of the variance in this analysis was explained on the first canonical axis. Therefore, examination of the scores on the first axis (table 7) enables the determination of the importance of individual environmental characteristics and water-quality characteristics that have the most explained variance. Total N and SD had the highest scores (absolute values) on the first canonical axis, which indicates that more of their variance was explained by the environmental characteristics than were the variances in P and SCHL. The most important characteristics explaining the variance in these four water-quality characteristics in descending order of axis score were the percentage of agriculture inthe basin, the clay content of the soil, soil erodibility, runoff, and permeability. The relations between the environmental characteristics and water-quality characteristics can be determined by comparing their respective axis scores.Areas with high percentages of agriculture, high clay-content soils, highly erodible soils, low runoff, and low soilpermeability had the highest nutrient and SCHL concentrations and worst water clarity. These results agree with the findings of the correlation and regression analyses. A multiple-regression approach (similar to partial RDA) was performed to determine how the total variance in SDs and SCHL, independently, could be separated into four categories: 1) variance explained by the 5 nutrients alone (P, DP, N, NO 3 

### -N, and TKN), 2) variance explained by environmental characteristics alone (the same 12 environmental characteristics used in the partial RDA for Water Quality and Its Relations with Environmental Characteristics in the Watershed 31

### water quality), 3) variance explained by the interactions between nutrients and environmental characteristics, and 4) variance not explained by these characteristics. In this approach, three regressions were performed for SD and for SCHL; multiple regressions with all 17 variables, with only the 5 nutrients, and with only the 12 environmental characteristics. The first regression with all 17 variables was used to determine the total variance explained by all of the variables. The other two regressions were used to partition the variance between the three categories. The amount of variance explained by the interaction of the two categories was determined by equation 10:

(10)

where EV is the explained variance by the specified group of variables.

The variance explained by each subset of variables alone was then determined by subtracting the variance explained by the interactions between the variables from the total variance explained by a subset of variables. For example, the variance explained by the nutrients alone is equal to the coefficient of determination for the nutrient regression minus the variance explained by the interactions. Resultsfrom this analysis indicated that these characteristics collectively explained about 55 percent of the variance in both SDs and SCHL concentrations. Nutrients alone explained 22–23 percent of the explained variance in each of these characteristics (fig. 9). The environmental characteristicsalone explained more of the variance in SCHL concentrations than in the SDs, whereas the interactions between the nutrients and environmental characteristics explained more of the variance in SDs than in SCHL concentrations.Again, much of the total variability in these two parameters could not be explained by the nutrients alone.


## Environmental Characteristics Most Strongly Related to Water Quality
Correlations, stepwise regressions, and regressiontree analyses all indicated that the anthropogenic/land-usecharacteristics (primarily the amount of forest and agriculture in the basin) were the characteristics most strongly related to water quality. Simply omitting the anthropogenic characteristics and reanalyzing the data, however, may notprovide a true indication of what factors affect water quality because some of the remaining factors may be correlated with the anthropogenic characteristics of the basins. For example, air temperature and clay content of the soil were both strongly correlated with many water-quality characteristics and with the percentage of agriculture in the basin (table 4). Therefore, it is difficult to determine whether it was these factors or the indirect effects of agriculture that affected water quality. The clay content of the soil has been demonstrated to have a strong effect on the water quality of Midwestern streams (Robertson, 1997; Robertson and others, 2006); however, the effects of air temperature seem questionable and may be indirectly related to the anthropogenic characteristics. Various approaches were used to determine which other environmental characteristics were most strongly related to water quality. The results of partial RDA indicated that soil characteristics were important; however, much of the variance explained by soil characteristics was also explained by the anthropogenic/land-use characteristics. EV Interactions 

### =

, (EV Nutrients 

### + EV Environmental 

### − EV All Variables 

### ) 32 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Table 7. Results from redundancy analysis between waterquality and environmental (anthropogenic/land-use, basin, and soil and surficial-deposit) characteristics for the studied wadeable streams in Wisconsin.
[log, logarithm to base 10 transformation]

First canonical axis score Water-quality characteristics Total phosphorus – log 0.54 Total nitrogen – log .67 Suspended chlorophyll a – log .48 Secchi tube depth -.65 Anthropogenic/land-use characteristics Total agriculture .81 Urban .25 Open wetland .19 Point-source loading of phosphorus – log .31 Basin characteristics Watershed area – log .00 Precipitation .23 Runoff -.61 Basin slope .11 Soil and surficial-deposit characteristics Clay content of the soil .78 Erodibility .63 Organic-matter content -.24 Permeability -.58

### Results of RDA indicated that the most important soilcharacteristics were the clay content of the soils, soil erodibility, and soil permeability. The results also indicated that the amount of runoff was also strongly related to water quality. The results of the residualization analyses indicatedthat the natural (nonanthropogenic) environmental characteristics most strongly related to the distribution of P were soil permeability, the soil slope, and the percentage ofsand-and-gravel deposits. The natural environmental characteristics most strongly related to the distribution of Nwere the percentage of clay deposits and other basin characteristics. A few of the natural characteristics, however, such as clay content of the soil and soil erodibility, were so strongly correlated with the percentage of agriculture in the basin that their relation to water quality may have been removed by the residualization approach. Stepwise regressions with residualized environmental characteristics only explained about 20 percent of the variance in P and N concentrations. In addition to anthropogenic/land-use characteristics, residualization analyses indicated that the distribution ofSCHL concentrations and SDs were related to concentrations of P and various forms of nitrogen. Other important 

### A. Percentages of explained variance in Secchi tube depth



### 22%

22% 56% Nutrients Environmental characteristics Interactions among categories 

### B. Percentage of explained variance in suspended chlorophyll a



### 23%

34% 43% General categories

Figure 9. Percentages of explained variance in A , Secchi tube depths and B , suspended chlorophyll a concentrations described by nutrients, environmental characteristics (anthropogenic/land-use, soil, and surficial-deposit characteristics), and interact ions among categories (variance that can not be explained by a single category) for the studied wadeable streams in Wisconsin. [%, percentage of explained variance] 

### 12% 4%

17% 67% Anthropogenic/land-use characteristics General categories

Basin characteristics Soil and surficial-deposit characteristics Interactions among categories

Figure 8. Percentages of explained variance in water quality (total phosphorus, total nitrogen, and suspended chlorophyll a concentrations and Secchi tube depth) described by anthropogenic/land-use, basin, soil and surficial-deposit characteristics, and interactions among categories (variance that can not be explained by a single category) for the studied wadeable streams in Wisconsin. [%, percentage of explained variance] 

### Water Quality and Its Relations with Environmental Characteristics in the Watershed 33

### natural characteristics related to SCHL concentrationswere the slope of the basin and the soils, the organic-matter content of the soil, and some surficial-deposit characteristics. Other important natural characteristics related to SDs were the clay content of the soil and surficial deposits.


## Regionalization Schemes for Reference Water Quality and the Response in Water Quality to Changes in Land Use

The two primary regionalization schemes considered in choosing the sites for this study and for developingnutrient criteria for Wisconsin were the level III ecoregions of Omernik and others (2000) and the environmental phosphorus zones of Robertson and others (2006) (fig. 2).In addition, a third regionalization scheme was considered after the sites were chosen and sampled. In this third scheme, the EPZs were refined based on the water-quality and environmental characteristics of only the 240 sites inthis study rather than from information from sites throughout the entire upper Midwest. To refine the EPZs in figure 2B, the SPARTA approach (Robertson and others, 2006)was used with land-use-adjusted (residualized) waterquality and environmental characteristics computed for each site to remove the direct and indirect effects of land use (and PtS). P concentrations and many of the natural environmental characteristics related to P (such as the clay content of the soil and soil erodibility) were so strongly correlated with land use (and PtS) that the residualization process almost completely removed their relations with residualized P concentrations. These correlations resultedin a regionalization scheme that explained very little variance in P concentrations and which did not demonstrateclear regional patterns. Therefore, the revised EPZ regionalization scheme based on data from only the 240 sites in this study was discarded. The primary purpose of most regionalization schemes is to minimize the variability in water quality within regions and maximize the variability among regions. This purpose was the reasoning behind the use of Omernik’secoregions as the building block for USEPA’s nutrient ecoregions. The distribution of agriculture differs among the four level III ecoregions in Wisconsin (fig. 10A). Almost 90 percent of the sites in the NLF had less than 8 percent agriculture in their basins; whereas, over 75 percent of the sites in the SWTP had over 50 percent agriculture in their basins. The use of land-use information to delineate specific regions may minimize the variability in water quality within the ecoregions across the upper Midwest and in Wisconsin because land use is the most important factor influencing the geographic distribution of most water-quality characteristics. The USEPA, however, has stated that the environmental characteristics used to delineate regions of similar reference or potential water quality should be restricted, as much as possible, to those that are intrinsic, or natural, and not the result of human activities (U.S. Environmental Protection Agency, 2000a). Therefore, the most appropriate stratification scheme for developing nutrient criteria for Wisconsin should be onethat delineates areas with different reference or potential nutrient concentrations (not necessarily actual water quality), different responses in nutrient concentrations to changes in land use, and different biotic responses to changes in nutrients.


## Reference Water-Quality Conditions
Various approaches have been used to define reference water quality for specific areas. Reference water quality is also referred to as background or potential water quality in other publications. In defining reference conditions for national nutrient criteria, the USEPA has suggested that a value based on the frequency distribution of the data available for a specific area could be used to define a reference condition. The USEPA has suggested that the value indicative of reference conditions be defined as the lower 25th percentile of all the data for that area or the upper (or worst) 75th percentile of the data for a subset of streams thought to be minimally impacted (U.S. Environmental Protection Agency, 2000a). Because it is often difficult to determine which sites are minimally impacted, the lower 25th percentile is the more common approach and the one that has been used by the USEPA to define their proposed water-quality criteria (table 1; U.S. Environmental Protection Agency, 2004). One of the problems with the percentile approach (25th percentile) is that differences in land use within the ecoregions and zones can strongly affect the results for characteristics correlated with land use, such as the water-quality characteristics examined in this study. The reference P and N concentrations based on the percentile approach were directly related to the percentage of thesites within each ecoregion or zone dominated by agriculture. In the ecoregions examined in this study, the percentages of sites dominated by agriculture decrease from the SWTP to DFA to NCHF to NLF (fig. 10A). These differences in land use result in a gradient of conditionsaffecting water quality, and result in P, N, and SCHL concentrations and SDs at the 25th percentile that follow the same gradient (25th percentiles in table 8). For the EPZs, 34 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin0 10 20 30 40 50

0.0 0.1 0.2 0.3 TOTAL PHOSPHORUS CONCENTRATIONS, IN MILLIGRAMS PER LITERPERCENTAGE OF SITES IN ECOREGION

0 10 20 30 40 50

0.0 0.1 0.2 0.3 TOTAL PHOSPHORUS CONCENTRATIONS, IN MILLIGRAMS PER LITERPERCENTAGE OF SITES IN EPZ

0 10 20 30 40 50

01234567 8 TOTAL NITROGEN CONCENTRATIONS, IN MILLIGRAMS PER LITERPERCENTAGE OF SITES IN ECOREGION

0 10 20 30 40 50

01234567 8 TOTAL NITROGEN CONCENTRATIONS, IN MILLIGRAMS PER LITERPERCENTAGE OF SITES IN EPZ 0 10 20 30 40 50

0 20 40 60 8 0 100 PERCENTAGE OF AGRICULTURAL LAND USEPERCENTAGE OF SITES IN ECOREGION

0 10 20 30 40 50

0 20 40 60 8 0 100 PERCENTAGE OF AGRICULTURAL LAND USEPERCENTAGE OF SITES IN EPZ

DFA NCHF NLF SWTP

DFA NCHF NLF SWTP DFA NCHF NLF SWTP

EPZ 1 EPZ 2 EPZ 3 EPZ 4

EPZ 1 EPZ 2 EPZ 3 EPZ 4

EPZ 1 EPZ 2 EPZ 3 EPZ 4 

# A.

B.

C.

Figure 10. Percentiles of A , total agriculture in the watersheds, B , total phosphorus, and C , total nitrogen in streams in the level III ecoregions and environmental phosphorus zones (EPZs) for the studied wadeable streams in Wisconsin. [DFA, Driftless Area; NCHF, North Central Hardwood Forests; NLF, Northern Lakes and Forests; and SWTP, Southeastern Wisconsin Till Plains] 

### Water Quality and Its Relations with Environmental Characteristics in the Watershed 35Table 8.Reference conditions for total phosphorus, total nitrogen, and suspended chlorophyllaconcentrations, and Secchi tube depths in the environmental phosphorus zonesand level III ecoregions for wadeable streams in Wisconsin. Median reference values, standard errors, and upper 95-percent confidence limits were estimated with the multiplelinear-regression approach.[USEPA, U.S. Environmental Protection Agency; EPZ, environmental phosphorus zone; DFA, driftless area; NCHF, North Central Hardwood Forests; NLF, Northern Lakes and Forests; SWTP, SoutheasternWisconsin Till Plains; --, no data; mg/L, milligram per liter; μg/L, microgram per liter; cm, centimeter; >, greater than; --,not available]Zone/ecoregionNumberof sitesMultiple linear-regression approachUSEPAcriteriaPercentilesMedianreferenceStandarderrorUpper 95-percentconfidence limit0 10 25 50 75 90 100Total phosphorus (mg/L)EPZ 1 69 0.032 0.003 0.039 -- 0.012 0.019 0.027 0.041 0.092 0.139 0.527EPZ 2 58 .042 .006 .054 -- .016 .022 .044 .092 .159 .237 .304EPZ 3 25 .029 .006 .043 -- .018 .036 .053 .150 .203 .297 .741EPZ 4 84 .035 .009 .055 -- .027 .043 .061 .095 .128 .210 1.641DFA 58 .040 .008 .057 .070 .027 .040 .053 .087 .121 .183 .611NCHF 48 .041 .009 .060 .029 .019 .027 .054 .106 .176 .258 .527NLF 62 .032 .002 .036 .010 .012 .017 .024 .036 .063 .101 .160SWTP 72 .025 .008 .044 .080 .023 .053 .072 .114 .199 .297 1.641Total nitrogen (mg/L)EPZ 1 69 .557 .057 .676 -- .191 .353 .486 .808 1.690 4.005 8.240EPZ 2 58 .632 .066 .771 -- .298 .492 .793 1.303 2.095 4.710 21.260EPZ 3 25 .367 .103 .601 -- .131 .244 1.318 2.481 3.340 5.095 10.465EPZ 4 84 .690 .161 1.050 -- .780 1.240 1.780 2.920 6.420 8.720 13.205DFA 58 .643 .118 .901 1.880 .882 1.223 1.489 2.563 6.300 8.145 11.385NCHF 48 1.132 .229 1.637 .460 .391 .698 1.188 1.646 2.843 4.870 8.240NLF 62 .509 .038 .587 .200 .131 .298 .403 .548 .793 1.158 1.435SWTP 72 .811 .258 1.409 1.590 .777 1.361 2.020 3.204 5.110 8.720 21.260 

### 36 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### Water Quality and Its Relations with Environmental Characteristics in the Watershed 37Table 8.Reference conditions for total phosphorus, total nitrogen, and suspended chlorophyllaconcentrations, and Secchi tube depths in the environmental phosphorus zonesand level III ecoregions for wadeable streams in Wisconsin—Continued. Median reference values, standard errors, and upper 95-percent confidence limits were estimated withthe multiple linear-regression approach.[USEPA, U.S. Environmental Protection Agency; EPZ, environmental phosphorus zone; DFA, driftless area; NCHF, North Central Hardwood Forests; NLF, Northern Lakes and Forests; SWTP, SoutheasternWisconsin Till Plains; --, no data; mg/L, milligram per liter; μg/L, microgram per liter; cm, centimeter; >, greater than; --,not available]Zone/ecoregionNumberof sitesMultiple linear-regression approachUSEPAcriteriaPercentilesMedianreferenceStandarderrorUpper 95-percentconfidence limit0 10 25 50 75 90 100Suspended chlorophylla(μg/L, trichromatic method)EPZ 1 69 1.56 0.17 1.93 -- 0.40 0.65 1.37 1.95 2.63 3.97 14.64EPZ 2 58 1.71 .24 2.23 -- .45 1.03 1.56 2.34 3.86 5.60 38.01EPZ 3 25 1.03 .24 1.55 -- .77 1.14 1.62 2.48 3.80 7.11 36.63EPZ 4 84 1.17 .25 1.72 -- .94 1.35 1.86 2.44 3.48 5.94 23.51DFA 58 1.48 .25 2.02 -- .94 1.35 1.75 2.16 2.90 4.12 14.64NCHF 48 1.73 .41 2.65 -- .40 .74 1.49 2.43 3.84 5.78 7.46NLF 62 1.49 .12 1.74 -- .41 .77 1.08 1.71 2.34 3.06 4.82SWTP 72 1.44 .54 2.71 -- 1.19 1.62 2.02 3.07 5.22 10.10 38.01Secchi tube depth (cm)EPZ 1 69 115.0 2.5 >120.0 -- 35.5 98.0 >120.0 >120.0 >120.0 >120.0 >120.0EPZ 2 58 117.7 4.9 >120.0 -- 27.0 47.5 88.5 117.5 >120.0 >120.0 >120.0EPZ 3 25 109.5 10.6 >120.0 -- 23.5 42.5 51.5 76.0 102.5 >120.0 >120.0EPZ 4 84 >120.0 10.2 >120.0 -- 25.5 41.5 65.3 95.5 >120.0 >120.0 >120.0DFA 58 118.6 9.2 >120.0 -- 35.5 50.0 67.5 98.0 >120.0 >120.0 >120.0NCHF 48 104.4 6.2 116.9 -- 35.5 81.0 102.3 >120.0 >120.0 >120.0 >120.0NLF 62 116.5 1.7 119.8 -- 66.0 102.0 >120.0 >120.0 >120.0 >120.0 >120.0SWTP 72 >120.0 13.4 >120.0 -- 23.5 33.0 47.8 84.0 108.3 >120.0 >120.0

### the percentages of agriculture in the basins decreased from EPZ 3 to EPZ 4 to EPZ 2 to EPZ 1, and results for the nutrient concentrations and SDs at the 25th percentile followed the same gradient except for EPZ 3 and EPZ 4, which were sometimes reversed (table 8). Therefore, thevalues of the water-quality characteristics at the 25th percentile do not appear to represent the true, or even relative, reference conditions for these different ecoregions and zones. The differences in the values at the 25th percentile represent the differences in the types of land uses among the different ecoregions and zones.Another approach to estimate reference concentrations is a multiple linear-regression model that relates water quality to anthropogenic characteristics (Dodds and Oakes, 2004). After calibrating the model with data from a specific area, an estimate of reference conditions in theabsence of anthropogenic activities can be obtained by setting the variables describing anthropogenic characteristics to 0 (in this study, setting percentage of agricultural area to 0, percentage of urban area to 0, and PtS to 0). These relations can also be used to place confidence intervals on the reference concentrations. Reference conditions were computed for each level III ecoregion and EPZ (fig. 2) based on all of the data available for each area with the general multiple linear-regression model:

Log P Predicted 

### = a + b Ag% + c Urb% + d Log(PtS), (11)

where

a , b , c and d are empirical coefficients determined for each area.

The general form of this model is similar to that used to estimate residualized concentrations in equations 3, 5, 7, and 9 (pages 24 and 25). Because this type of model estimates the logarithm of the reference concentration, themedian reference concentration for each area was estimated as 10 a 

### . For each level III ecoregion and EPZ, themedian reference condition, the standard error of the reference condition, and the upper bound of the 95-percent confidence interval of the reference condition were estimated (table 8). A bias correction is typically applied to resultsfor mean values obtained by logarithmic regression; however, the bias correction was not used here because of the choice of median rather than mean reference conditions. 

### Total Phosphorus Reference concentrations for P ranged from 0.029 mg/L in EPZ 3 to 0.042 mg/L in EPZ 2, with the upper 95-percent confidence intervals ranging from 0.039 mg/L in EPZ 1 to 0.055 mg/L in EPZ 4 (table 8). No statisticaldifferences are present among the reference concentrations for these zones. The regression approach was also used to estimate reference concentrations for each level III ecoregion. Reference concentrations ranged from 0.025 mg/L in the SWTP to 0.041 mg/L in the NCHF. The upper 95-percent confidence intervals ranged from 0.036 mg/L in the NLF to 0.060 mg/L in the NCHF. Again, nostatistical differences are present among these concentrations. The standard errors for the reference concentrations of the EPZs were similar in magnitude to those of the ecoregions (from 0.002 to 0.009 mg/L); therefore, neither regionalization scheme was better in estimating reference P concentrations. Both regionalization schemes indicate that one reference P concentration would be appropriate for wadeable Wisconsin streams: 0.03–0.04 mg/L with an upper 95-percent confidence limit of 0.04–0.06 mg/L.


### Total Nitrogen Reference concentrations for N ranged from 0.367 mg/L in EPZ 3 to 0.690 mg/L in EPZ 4, with the upper 95-percent confidence intervals ranging from 0.601 mg/L in EPZ 3 to 1.050 mg/L in EPZ 4 (table 8). Reference concentrations for EPZ 3 were lower than those for the other EPZs; however, the differences were not significant at p < 0.05. Reference concentrations ranged from 0.509 mg/L in the NLF to 1.132 mg/L in the NCHF. The upper 95-percent confidence intervals ranged from 0.587 mg/L inthe NLF to 1.637 mg/L in the NCHF. Reference concentrations for the NCHF were slightly higher than those for the other ecoregions; however, no statistical differences were present between these concentrations. The standard errors of the reference concentrations of the EPZs ranged from 0.066 to 0.161 mg/L, compared to 0.038 to 0.258 mg/L for the level III ecoregions; the 95-percent confidence limits for the EPZs were generally smaller than those of the ecoregions. Therefore, the EPZs provided more precise estimates of reference N concentrations, although the differences were not significant at p < 0.05. On the basis of the EPZ regionalization scheme, two reference N concentrations may be appropriate for wadeable Wisconsin streams: 0.6–0.7 mg/L in all streams except those in EPZ 3, where 0.4 mg/L may be more appropriate. 38 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### Suspended Chlorophyll a Reference concentrations for SCHL ranged from 1.03 μg/L in EPZ 3 to 1.71 μg/L in EPZ 2, with the upper 95-percent confidence intervals ranging from 1.55 μg/L inEPZ 3 to 2.28 μg/L in EPZ 2 (table 8). Reference concentrations for EPZ 3 were lower than those for the other EPZs; however, the differences were not significant at p < 0.05. Reference concentrations ranged from 1.44 to 1.73 μg/L in the four level III ecoregions, with the upper 95-percent confidence intervals ranging from 1.74 μg/Lin the NLF to 2.71 μg/L in the SWTP. Again, the differences were not significant at p < 0.05. The standard errors for the reference concentrations of the EPZs ranged from about 0.17 to 0.25 μg/L compared to 0.12 to 0.54 μg/L for the ecoregions; the 95-percent confidence limits for the EPZs were generally smaller than those of the ecoregions. Therefore, the EPZs provided more precise estimates of reference SCHL concentrations, although the differences were not significant at p < 0.05. On the basis of the EPZregionalization scheme, two reference SCHL concentrations may be appropriate for wadeable Wisconsin streams: 1.2–1.7 μg/L in all streams except those in EPZ 3, where 1.0 μg/L may be more appropriate. Reference SCHL concentrations and the relative importance of P and N in controlling or limiting SCHL at low nutrient concentrations was also estimated by examining the SCHL concentrations in sites with either or both reference P and reference N concentrations. For this analysis, the 240 sites were divided into five categories: reference sites (Reference, fig. 11)—36 sites with both Pconcentrations at or below the 0.04-mg/L reference concentration and N concentrations at or below the 0.70-mg/L reference concentration; reference P sites (Ref P)—22 siteswith P concentrations at or below the reference concentration, but with N concentrations above the reference concentration; reference N sites (Ref N)—10 sites with N concentrations at or below the reference concentration, but with P concentrations above the reference concentration; high nutrient-concentration sites (High)—135 sites with both P and N concentrations above their respective upper 95-percent confidence limits for reference concentrations Reference High Ref N Ref P -0.5 0.0 0.5 1.0 1.5 2.0LOG (SUSPENDED CHLOROPHYLLA,IN MICROGRAMS PER LITER)

Reference High Ref N Ref P

0 20 40 60 8 0 100 120SECCHI TUBE DEPTH,IN CENTIMETERS EXPLANATION

Outlier

Interquartile

range (IR) 75th percentile + 1.5 * IR

25th percentile – 1.5 * IR 75th percentile

25th percentile Median 

## A.

B.

Figure 11. A , suspended chlorophyll a (SCHL) concentrations and B , Secchi tube depths (SDs) in Reference sites, High (nonreference) sites, and sites with only reference total nitrogen (Ref N sites) or reference total phosphorus (Ref P sites) concentrations in the studied wadeable streams in Wisconsin. 

### Water Quality and Its Relations with Environmental Characteristics in the Watershed 39

### (P concentrations above 0.06 mg/L and N concentrations above 1.0 mg/L); and nonclassified sites—37 sites with P and N concentrations above their respective referenceconcentrations but below their upper 95-percent confidence limits (these sites were not included in this analysis and not included in figure 11). Comparison of the SCHL concentrations for the Reference sites with those of the Ref P and Ref N sites is similar to the comparison of SCHL concentrations for nutrient-addition experiments. SCHLconcentrations for Ref P sites are similar to SCHL concentrations for experiments with N additions, and the SCHL concentrations for the Ref N sites are similar to those for experiments with P additions. The approach described above was used to estimate the reference SCHL concentration for the entire Statebecause nutrient concentrations at or below reference concentrations were primarily measured only in the northern part of the State. The median SCHL concentration of the Reference sites was 1.46 μg/L (log(1.46) = 0.16), with the upper 75th percentile being 2.22 μg/L (log(2.22) = 0.35),which was significantly less than the median concentration of 2.75 μg/L (log(2.75) = 0.44) measured in the High sites (fig. 11A). It has been suggested by the USEPA that the upper 75th percentile of a subset of streams thought to be minimally impacted (Reference sites) may represent the reference condition; therefore, an alternative reference SCHL concentration for the entire State would be 2.22 μg/L. The reference values estimated with both approaches are less than those defined by the USEPA for nutrientecoregions 7 and 8 when the trichromatic method of analysis is used (5.8 and 4.3 μg/L, respectively; table 1).Comparing the median concentration for the Reference sites with the median concentrations for the Ref N and Ref P sites may provide an indication of whether P or N is more important in limiting the concentrations ofSCHL in streams with nutrient concentrations near reference conditions (fig. 11A). The median SCHL concentrations for Ref P and Ref N sites were both higher than that for the Reference sites, although the median concentrations for these categories were not statistically different from one another at p < 0.05. The Ref N sites had a median SCHL concentration most different from that of the Reference sites; therefore, it appears that it may be moreimportant to have low P concentrations than low N concentrations to limit SCHL concentrations (in other words, potential P limitation for sites near reference conditions). 

### Secchi Tube Depth Reference SDs ranged from about 110 cm in EPZ 3to greater than 120 cm in EPZ 4, with all upper 95-percent confidence intervals greater than 120 cm (table 8). These differences were not statistically different from one another at p < 0.05. Reference SDs ranged from 104.4 cm in the NCHF to greater than 120 cm in the SWTP. The upper 95-percent confidence intervals ranged from 116.9 cm in the NCHF to greater than 120 cm in the DFA andthe SWTP. These differences were not statistically different from one another at p < 0.05. The standard errors of the EPZs ranged from 2.5 to 10.6 cm, compared to 1.7 to 13.4 cm for the ecoregions. Therefore, the EPZs provided slightly more precise estimates of reference clarity than the level III ecoregions, although the differences were not statistically different from one another at p < 0.05. On the basis of the EPZ regionalization scheme, two reference SDs may be appropriate for wadeable Wisconsin streams: greater than 115 cm for all streams except those in EPZ 3, where greater than 110 cm may be more appropriate. A reference SD was also determined by examining the sites at which both P and N concentrations were at or below their respective reference concentrations. The median SD measured at the Reference sites was greater than 120 cm, which was significantly greater than the median SD measured in the High sites (90 cm; fig. 11B). The lower 25th percentile of SDs at the Reference sites (equivalent to the worst 75th percentile of the minimally impacted sites) was greater than 120 cm; therefore, an alternative reference SD for the entire State would be greater than 120 cm. The median SDs for Ref P and Ref N sites were similar to that for the Reference sites (fig. 11B); therefore, a 120-cm Secchi tube was not long enough todetermine whether small increases in P or N concentrations were more important in reducing water clarity.


## Responses of Nutrient Concentrations to Changes in Land Use
The responses of specific nutrients to changes in land use or other anthropogenic characteristics, such as PtS, can be estimated for each EPZ and ecoregion by the ways in which concentrations in each area change as a function ofa specific anthropogenic characteristic. Overall, concentrations of P and N increase as the percentage of agricultural land increases (figs. 12A, B and 13A, B); however, variation in these responses may be associated with other 40 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in WisconsinA.Total phosphorus by environmental phosphorus zone-2.0-1.5-1.0-0.50.00.50 20 40 6080 100

LOG (TOTAL PHOSPHORUS, IN MILLIGRAMS PER LITER) LOG (TOTAL PHOSPHORUS, IN MILLIGRAMS PER LITER)B.Total phosphorus by ecoregion-2.0-1.5-1.0-0.50.00.50 20 40 6080 100D.Response as a function of the percentage of total agriculture0.00.10.20.30.40 20 40 6080 100PERCENTAGE OF AGRICULTURAL LAND USE

TOTAL PHOSPHORUS, IN MILLIGRAMS PER LITER

TOTAL PHOSPHORUS, IN MILLIGRAMS PER LITERC.Response as a function of the percentage of total agriculture0.00.10.20.30.40 20 40 6080 100PERCENTAGE OF AGRICULTURAL LAND USEPERCENTAGE OF AGRICULTURAL LAND USEPERCENTAGE OF AGRICULTURAL LAND USEEPZ 1EPZ 2EPZ 3EPZ 4EPZ 5NLFNCHFSWTPDFAEPZ 1EPZ 2EPZ 3EPZ 4All DataNLFNCHFAll DataSWTPDFAFigure 12.Total phosphorus concentrations as a function of the percentage of agricultural land use inA, environmental phosphorus zones (EPZs) andB, level III ecoregions,and response curves for phosphorus concentrations as a function of the percentage of agriculture in the watershed, inC, EPZs, andD, level III ecoregions for wadeable streamsin Wisconsin. [DFA, Driftless Area; NCHF, North Central Hardwood Forests; NLF, Northern Lakes and Forests; and SWTP, Southeastern Wisconsin Till Plains] 

### Water Quality and Its Relations with Environmental Characteristics in the Watershed 41B.Total nitrogen by ecoregion-1.0-0.50.00.51.01.5PERCENTAGE OF AGRICULTURAL LAND USE

LOG (TOTAL NITROGEN, IN MILLIGRAMS PER LITER)A.Total nitrogen by environmental phosphorus zone-2.0-1.5-1.0-0.50.00.51.01.50 20 40 6080 100 0 20 40 6080 100PERCENTAGE OF AGRICULTURAL LAND USE

LOG (TOTAL NITROGEN, IN MILLIGRAMS PER LITER)D.Response as a function of total agriculture by ecoregion02468100 20 40 6080 100PERCENTAGE OF AGRICULTURAL LAND USE

TOTAL NITROGEN, IN MILLIGRAMS PER LITERC.Response as a function of total agriculture by environmental phosphorus zone02468100 20 40 6080 100PERCENTAGE OF AGRICULTURAL LAND USE

TOTAL NITROGEN, IN MILLIGRAMS PER LITEREPZ 5EPZ 1EPZ 3EPZ 4EPZ 2NLFNCHFSWTPDFADFANCHFNLFSWTPAll DataEPZ 1EPZ 2EPZ 3EPZ 4All DataFigure 13.Total nitrogen concentrations as a function of the percentage of agricultural land use inA, environmental phosphorus zones (EPZs) andB, level III ecoregions, andresponse curves for nitrogen concentrations as a function of the percentage of agriculture in the watershed, inC, EPZs, andD, level III ecoregions for wadeable streams inWisconsin. [DFA, Driftless Area; NCHF, North Central Hardwood Forests; NLF, Northern Lakes and Forests; and SWTP, SoutheasternWisconsin Till Plains] 

### 42 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### anthropogenic characteristics such as differences in PtS or the percentage of urban area in the watershed. The four sites in EPZ 5 are plotted in figures 12 and 13 (and in the figures for other water-quality characteristics and biotic indices); however, these sites were not used to obtain regression lines or used in the multiple-regression analyses for P or any of the other water-quality characteristics.A better approach to estimate the response of specific water-quality characteristics to changes in specificanthropogenic characteristics is the use of multiple-regression equations, such as those used to estimate reference concentrations. The response of a specific water-quality characteristic (for example, P) can be estimated for each EPZ and level III ecoregion shown in figure 2 by first determining values for the coefficients a, b, c, and d , in equation 11 on page 38 on the basis of all of the available data for each zone or ecoregion. Concentrations can thenbe predicted as a function of specific anthropogenic characteristics by varying the characteristic of interest while holding the other characteristics constant; in this case, at 0 percent or 0 PtS (figs. 12C, D and 13C, D). This approachremoves the complicating effects of the other characteristics. Because this equation estimates the logarithm of the concentration, the final concentrations were computed as 10 a 

### . A bias correction is typically applied to the results for mean values obtained by logarithmic regression; however, a bias correction was not used here because of the choice of median rather than mean concentrations.Plots of the regression lines show that concentrations of P increase as the percentage of agricultural land increases in all of the EPZs and ecoregions (figs. 12A, B); however, a more detailed evaluation of the responses of P concentrations in the EPZs and ecoregions can be made with multiple-regression analysis. The response of P concentrations to changes in only the percentage of agricultural land was largest in EPZ 1, followed by EPZ3, EPZ 2, and EPZ 4 (fig. 12C). To determine if these responses were statistically significant from one another, the standard errors in the estimates of coefficient b were used to place 95-percent confidence limits on the estimated values (table 9). The responses in P concentrations in EPZ 1 and EPZ 3 were larger than the responses in the other EPZs, although their 95-percent confidence intervals for coefficient b slightly overlapped those of the other EPZs. Because most of the sites in EPZ 1 were in areas with limited agriculture, this difference may not reflect changes that would occur at higher percentages of agriculture. Changes in P concentrations as a function of only the percentage of agricultural land were largest in the NLF ecoregion, followed by NCHF, SWTP, and DFA (fig. 12D).The response in concentrations in the NLF was significantly larger than in any other ecoregion; however, similar to EPZ 1, the ranges in the percentage of agriculture and measured P concentrations were limited, and, therefore, this difference may simply reflect the distribution of theoriginal data. The standard errors in the estimates of coefficient b for the EPZs ranged from 0.12 to 0.15 compared to 0.13 to 0.40 for the ecoregions. Therefore, the EPZs provided better estimates of the response to changes in the amount of agriculture than the level III ecoregions. Based on the EPZ regionalization scheme, subdividing wadeablestreams in Wisconsin into two categories seems appropriate: streams in areas with high clay-content soils (EPZ 3), which respond more dramatically to changes in the amount of agriculture, and streams in the rest of the State.Concentrations of N also increase as the percentage of agricultural land increases in all of the EPZs and ecoregions (fig. 13). The responses in concentrations in EPZ 1 and EPZ 4 were larger than the responses in the other EPZs, and the response in concentrations in EPZ 3 was smaller than those in the other EPZs; however, these differences were not statistically significant at p < 0.05. The changes in N concentrations were largest in the DFA, followed by SWTP, NLF, and NCHF. The response in concentrations in the DFA was significantly larger than in the NCHF, but not significantly larger than in the other ecoregions at p < 0.05. The response in concentrations in EPZ 1 was larger than in any other EPZ and the response in NLF was smaller than in any other ecoregion; however, this difference may simply reflect the distribution of theoriginal data. The standard errors in the estimates of coefficient b for the EPZs ranged from 0.10 to 0.16 compared to 0.12 to 0.40 for the ecoregions (table 9). Therefore, the EPZs provided better estimates of the response to changes in the percentage of agricultural land use than the level III ecoregions. Based on the EPZ regionalization scheme,subdividing wadeable streams in Wisconsin into two categories seems appropriate: streams in areas with clay soils (EPZ 3), which respond less dramatically to changes in the amount of agriculture, and streams in the rest of the State. Water Quality and Its Relations with Environmental Characteristics in the Watershed 43

### Table 9. Responses to changes in the percentage of agricultural land use in the watershed. Estimated values for coefficient b for total phosphorus, total nitrogen, and suspended chlorophyll a concentrations, and Secchi tube depths in environmental phosphorus zones and level III ecoregions for wadeable streams in Wisconsin.

[ b , factor associated with the percentage of agriculture in the watershed (eq. 11 in the text on page 38); mg/L, milligram per l iter; μg/L, microgram per liter; cm, centimeter, EPZ, environmental phosphorus zone; DFA, Driftless Area; NCHF, North Central Hardwood Forests; NLF, Nort hern Lakes and Forests; SWTP, Southeastern Wisconsin Till Plains]

Zone/ecoregion Estimated value for b Standard error for b Upper 95-percent confidence value for b Total phosphorus
EPZ 1 1.03 0.15 1.33 EPZ 2 0.70 .13 0.96 EPZ 3 .99 .12 1.23 EPZ 4 .63 .15 .93

DFA .48 .13 .74 NCHF .95 .19 1.33
NLF 2.28 .40 3.08 SWTP .95 .18 1.31 Total nitrogen
EPZ 1 1.33 .14 1.61
EPZ 2 1.03 .10 1.23 EPZ 3 1.19 .16 1.51
EPZ 4 1.09 .14 1.37

DFA 1.19 .12 1.43 NCHF .49 .18 .85 NLF .96 .40 1.76 SWTP .90 .17 1.24 Suspended chlorophyll a EPZ 1 .22 .16 .55 EPZ 2 .36 .14 .63 EPZ 3 .60 .13 .87 EPZ 4 .54 .13 .80

DFA .35 .35 1.05 NCHF .16 .20 .55
NLF .93 .44 1.80 SWTP .47 .20 .86 Secchi tube depth
EPZ 1 -7.1 8.7 10.3 EPZ 2 -49.8 11.0 -27.8 EPZ 3 -53.0 15.4 -22.1 EPZ 4 -48.5 16.1 -16.2

DFA -42.1 15.2 -11.8 NCHF 8.8 13.7 36.2 NLF -33.8 21.5 9.3 SWTP -89.0 19.2 -50.5 

### 44 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

## Responses of Chlorophyll a Concentrations and Secchi Tube Depth to Changes in Nutrient Concentrations and Land Use

Concentrations of SCHL increased as P and N concentrations increased; however, there was much variation in these relations (fig. 14). For any nutrient concentration, there was about an order of magnitude of variation in SCHL concentrations. Although nutrient concentrations were lower or higher in some areas (especially lower inEPZ 1 and the NLF ecoregion), there was a relatively similar response in SCHL concentrations to changes in nutrient concentrations in all EPZs and level III ecoregions. Five sites, however, had SCHL concentrations that were lowerthan might be expected for the measured P and N concentrations at the site. These sites were in EPZ 1 and the NCHF, and were generally small sites (5.8–55.6 km 2 

### ) with extensive sedimentation and embedded rocky substrate (94–100 percent). The best breakpoints or thresholds in the response of SCHL to changes in P and N concentrations were at 0.070 mg/L (log(P) = -1.16) and 1.169 mg/L (log(N) = 0.07), respectively. This P concentration is expected to occur at approximately 30- to 50-percent agriculture in all areas (fig. 12). This N concentration is expected to occur at approximately 30-percent agriculture in all areas except EPZ 3, where it occurs at about 50-percent agriculture (fig. 13). Water clarity (SDs) decreased as P and N concentrations increased (fig. 15). At low nutrient concentrations,water clarity often exceeded the 120-cm length of the Secchi tube. Then, as nutrient concentrations increased, water clarity decreased; however, there was much variation in this relation. For most nutrient concentrations, other than very low concentrations, SDs ranged from 20 cm to greater than 120 cm. In general, the SD responses were similar inmost EPZs and ecoregions. The best breakpoints or thresholds in the response of SDs to changes in P and N concentrations were at 0.106 mg/L (log(P) = -0.97) and 3.305 mg/L (log(N) = 0.52), respectively. This P concentration is expected to occur at approximately 50- to 70-percent agriculture in all areas (fig. 12). This N concentration isexpected to occur at approximately 55- to 70-percent agriculture in all areas except EPZ 3, where it occurs at about 80-percent agriculture (fig. 13). The multiple-regression approach was again used to estimate changes in SCHL concentrations and SDs in response to changes in the percentage of agricultural land in the watershed. Concentrations of SCHL increased as the percentage of agricultural land increased in all of the EPZs (fig. 16A) and ecoregions (not shown), and the response was similar in all areas except EPZ 1. The response in concentrations in EPZ 1 was less than in any other EPZ; however, this difference may simply reflect the limited distribution of the original data in EPZ 1. The standard errors in the estimates of coefficient b for the EPZs ranged from 0.13 to 0.16 compared to 0.20 to 0.44 for the level III ecoregions (table 9). As are result, the 95-percent confidence intervals for the EPZs were smaller than thosefor the ecoregions. Therefore, the EPZs provided better estimates of the response in SCHL concentrations to changes in the amount of agricultural land in the watershed than the level III ecoregions. Based on the similarity inthe distribution of concentrations (fig. 15) and insignificant differences in values for coefficient b among EPZs, it is not appropriate to subdivide the wadeable streams of Wisconsin based on the response in SCHL concentrations to changes in nutrient concentrations and land use.Water clarity decreased as the percentage of agriculture land increased in all of the EPZs and level III ecoregions, and the response was similar in all areas except EPZ 1 (fig. 16B, shown for EPZs only). The water clarity decreased more slowly in EPZ 1 than in the other zones;however, there were only a few sites in EPZ 1 with extensive agriculture to support this conclusion. The response in water clarity in EPZ 3 was similar to the other areas; the difference in the water clarity in this area was caused by the lower reference clarity. The standard errors in the estimates of coefficient b for the EPZs ranged from 8.7 to 16.1 compared to 13.7 to 21.5 cm for the ecoregions (table 9). Therefore, the EPZs provided better estimates ofthe response in SDs to changes in the amount of agricultural land in the watershed than the level III ecoregions. Based on the results for the EPZ regionalization scheme, subdividing wadeable streams into two categories seems appropriate: streams in areas with high clay-content soils (EPZ 3), which have a lower reference water clarity and clarity that decreases and remains lower than sites in the other areas as the percentage of agricultural land in the watershed increases, and streams in the rest of the State. Water Quality and Its Relations with Environmental Characteristics in the Watershed 45

### 46 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in WisconsinSuspended chlorophyllaby environmental phosphorus zone-0.50.00.51.01.52.0-2.0 -1.5 -1.0 -0.5 0.0 0.5LOG (TOTAL PHOSPHORUS, IN MILLIGRAMS PER LITER) LOG (TOTAL PHOSPHORUS, IN MILLIGRAMS PER LITER)

LOG (CHLOROPHYLL A , IN MICROGRAMS PER LITER) LOG (CHLOROPHYLL A , IN MICROGRAMS PER LITER) LOG (CHLOROPHYLL A , IN MICROGRAMS PER LITER) LOG (CHLOROPHYLL A , IN MICROGRAMS PER LITER)Suspended chlorophyllaby ecoregion-0.50.00.51.01.52.0-2.0 -1.5 -1.0 -0.5 0.0 0.5Suspended chlorophyllaby ecoregion-0.50.00.51.01.52.0-1.0 -0.5 0.0 0.5 1.0 1.5LOG (TOTAL NITROGEN, IN MILLIGRAMS PER LITER)Suspended chlorophyllaby environmental phosphorus zone-0.50.00.51.01.52.0-1.0 -0.5 0.0 0.5 1.0 1.5LOG (TOTAL NITROGEN, IN MILLIGRAMS PER LITER)EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5DFANCHFNLFSWTPDFANCHFNLFSWTP-1.158 (0.070 mg/L)-1.158 (0.070 mg/L)0.068 (1.169 mg/L)0.068 (1.169 mg/L)Figure 14.Suspended chlorophyllaconcentrations as a function of total phosphorus and total nitrogen concentration (logarithm to base 10 transformation), by environmentalphosphorus zones (EPZs) and by level III ecoregions for the studied wadeable streams in Wisconsin. Computed thresholds in the response are identified by vertical lines. [DFA,Driftless Area; NCHF, North Central Hardwood Forests; NLF, Northern Lakes and Forests; and SWTP, Southeastern Wisconsin Till Plains]Secchi tube depth by environmental phosphorus zone020406080100120-2.0 -1.5 -1.0 -0.5 0.0 0.5LOG (TOTAL PHOSPHORUS, IN MILLIGRAMS PER LITER)

SECCHI TUBE DEPTH, IN CENTIMETERS SECCHI TUBE DEPTH, IN CENTIMETERS

SECCHI TUBE DEPTH, IN CENTIMETERS SECCHI TUBE DEPTH, IN CENTIMETERSSecchi tube depth by environmental phosphorus zone020406080100120-1.0 -0.5 0.0 0.5 1.0 1.5LOG (TOTAL NITROGEN, IN MILLIGRAMS PER LITER)Secchi tube depth by ecoregion020406080100120-2.0 -1.5 -1.0 -0.5 0.0 0.5LOG (TOTAL PHOSPHORUS, IN MILLIGRAMS PER LITER)Secchi tube depth by ecoregion020406080100120-1.0 -0.5 0.0 0.5 1.0 1.5LOG (TOTAL NITROGEN, IN MILLIGRAMS PER LITER)EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5DFANCHFNLFSWTPDFANCHFNLFSWTP-0.97 (0.106 mg/L)-0.97 (0.106 mg/L)0.52 (3.305 mg/L)0.52 (3.305 mg/L)Figure 15.Secchi tube depth as a function of total phosphorus and total nitrogen concentration (logarithm to base 10 transformation), byenvironmental phosphorus zones(EPZs) and by level III ecoregions for the studied wadeable streams in Wisconsin. Computed thresholds in the response are identified by vertical lines. [DFA, Driftless Area;NCHF, North Central Hardwood Forests; NLF, Northern Lakes and Forests; and SWTP, Southeastern Wisconsin Till Plains] 

### Physical Habitat 47

# Physical Habitat

The streams examined in this study exhibit considerable variation in their physical habitats, particularly with respect to mean stream widths and depths. Mean widths ranged from 1.1 m to over 55 m, with an overall mean width of 7.6 m (table 10). Mean depths ranged from 0.1 mto 1.0 m, with an overall mean depth of 0.3 m. Mean thalweg depths (deepest part of the cross section) ranged from 0.1 m to 1.3 m, with an overall mean depth of 0.4 m. The gradients of the streams at the sampling sites ranged from nearly flat (0.0 m/km) to quite steep (up to 20.7 m/km) and their sinuosity (not in table 10) ranged from highly meandered to straight channels. About half of the streams contained well-developed runs. On average, 75 percent of the stream’s reach was classified as runs. Most streams had less than 10 percent of the reach classified as pools and riffles. Stream bottoms ranged from being almost completely silt to being dominated by sand or gravel. The percentage of the stream’s reach that was shaded ranged from 0 to 93.7 percent. A. Response in suspended chlorophyll a

0 1 2 3 4 5

0 20 40 60 8 0 100 PERCENTAGE OF AGRICULTURAL LAND USESUSPENDED CHLOROPHYLLA,IN MILLIGRAMS PER LITER



### B. Response in secchi tube depth

0 20 40 60 8 0 100 120

0 20 40 60 8 0 100 PERCENTAGE OF AGRICULTURAL LAND USESECCHI TUBE DEPTH,IN CENTIMETERS EPZ 1 EPZ 2 EPZ 3 EPZ 4 All Data

EPZ 1 EPZ 2 EPZ 3 EPZ 4 All Data



### Figure 16. Response curves for A , suspended chlorophyll

a

concentrations and B , Secchi tube depths in the environmental phosphorus zones (EPZs) as a function of the percentage of agriculture in the watershed for wadeable streams in Wisconsin. 

### 48 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in WisconsinTable 10.Summary statistics for the physical-habitat characteristics and biotic indices for the studied wadeable streams in Wisconsin.[EPT, Ephemeroptera, Plecoptera, and Trichoptera; #, number; m, meter; m/km, meter per kilometer; mg/m2, milligram per square meter; log, logarithm to base 10 transformation; --, values are not indicative ofwater quality]Characteristic/index Abbreviation Units Transformation Count Median MeanBest 25thpercentileof all sitesStandarddeviationMinimum MaximumPhysical-habitat characteristicsStream width WIDTH m none 235 4.5 7.6 -- 8.3 1.1 56.3Stream mean depth DEPTH m none 235 .3 .3 -- .2 .1 1.0Mean thalweg depth THALD m none 235 .4 .4 -- .2 .1 1.3Stream gradient GRAD m/km none 231 2.5 3.2 -- 3.0 .0 20.7Percentage of pools POOL% % none 234 5.0 10.5 -- 13.9 .0 100.0Percentage of riffle RIFF% % none 234 8.5 13.9 -- 17.2 .0 100.0Percentage of run RUN% % none 234 49.7 75.3 -- 22.9 .0 100.0Depth of sediment on stream bottom SEDEP m none 235 .1 .1 -- .1 .0 0.9Percentage of silt in bottom sediments SILT% % none 235 10.6 17.2 -- 18.3 .0 95.6Percentage of sand in bottom sediments SAND% % none 235 27.3 34.3 -- 25.3 .0 99.6Percentage of gravel in bottom sediments GRAV% % none 235 18.8 19.6 -- 14.5 .0 66.2Percentage of rocky-substrate embeddedness EMB% % none 235 64.2 59.8 -- 29.5 6.2 100.0Percentage of stream bottom covered byalgaeALGAE% % none 235 .4 4.8 -- 9.1 .0 53.8Percentage of stream bottom covered bymacrophytesMACR% % none 235 1.3 6.3 -- 10.9 .0 54.8Percentage of stream with fish cover COVER% % none 235 7.2 9.3 -- 9.2 .0 65.5Percentage of stream shaded SHADE% % none 235 28.9 33.9 -- 27.8 .0 93.7Percentage of stream bank with erosion EROSION% % none 235 12.5 17.7 -- 15.9 .0 76.5Buffer width BUFFER m none 235 10.5 12.6 -- 6.5 .0 30.0Benthic chlorophylla/ diatomsBenthic chlorophyllaBCHL mg/m2log 199 1,919 12,879 552 80,884 7 1,068,000Diatom Nutrient Index DNI # none 214 4.1 3.9 3.5 0.8 1.7 5.4Diatom Siltation Index DSI # none 214 38.2 39.9 16.7 24.9 2.6 95.3Diatom Biotic Index DBI # none 214 42.1 46.4 51.3 15.7 22.8 100.0 

### Physical Habitat 49Characteristic/index Abbreviation Units Transformation Count Median MeanBest 25thpercentileof all sitesStandarddeviationMinimum MaximumMacroinvertebratesHilsenhoff Biotic Index HBI # none 227 4.7 4.9 4.0 1.6 0.8 9.4Percentage of EPT individuals EPTN% % none 227 42.3 41.0 61.8 26.1 .0 99.2Percentage of EPT taxa EPTTX% % none 227 35.7 33.9 45.7 16.8 .0 74.3Percentage of scrapers SCRAP% % none 227 14.7 19.0 29.5 18.0 .0 85.4Percentage of shredders SHRED% % none 227 0.0 1.0 -- 3.1 .0 24.7Number of taxa TAXAN # none 232 29 29.2 35.0 10.4 4 67FishFish Index of Biotic Integrity IBI # none 235 40.0 40.2 52.0 20.8 .0 100.0Percentage of carnivores CARN% % none 234 1.6 11.4 9.8 21.3 .0 100.0Percentage of insectivores INSECT% % none 234 48.9 49.8 29.1 24.2 .0 100.0Percentage of omnivores OMNI% % none 234 10.5 15.4 3.8 16.0 .0 81.1Percentage of intolerant species TOL% % none 234 3.3 14.6 15.8 23.3 .0 97.9Percentage of tolerant species INTOL% % none 234 42.8 41.5 19.5 25.6 .0 100.0Number of fish FISHN # log 234 130 199.6 -- 247.8 7 2,147Number of fish species FISHSPEC # none 235 11 11.5 -- 5.4 1 33Table 10.Summary statistics for the physical-habitat characteristics and biotic indices for the studied wadeable streams in Wisconsin—Continued.[EPT, Ephemeroptera, Plecoptera, and Trichoptera; #, number; m, meter; m/km, meter per kilometer; mg/m2, milligram per square meter; log, logarithm to base 10 transformation; --, values are not indicative ofwater quality] 

### 50 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### Four indices were used to describe the benthic chlorophyll a and periphytic-diatom communities foundin the streams in this study (table 10). Benthic chlorophyll a (BCHL) concentrations ranged from 7 mg/m 2 

### to over 1,000,000 mg/m 2 

### (median = 1,919 mg/m 2 

### ), the Diatom Nutrient Index (DNI) values ranged from 1.7 to 5.4 (median = 4.1), the Diatom Siltation Index (DSI) values ranged from 2.6 to 95.3 (median = 38.2), and Diatom Biotic Index (DBI) values ranged from 22.8 to 100 (median = 42.1). In general, streams in the northern part of the State had lower BCHL concentrations and better quality diatom communities, lower DNI and DSI values, and higher DBI values than streams in the rest of the State (fig. 17). 

## Relations with Individual Characteristics
Correlations
Spearman rank correlation coefficients (r
s 

### values) between the four indices describing BCHL and diatom communities and the water-quality, environmental, and physical-habitat characteristics are given in table 11. All four indices were significantly correlated with P and DP concentrations; however, only BCHL, DNI, and DSI were significantly correlated with N and NO 3 

### -N concentrations. Only DNI and DSI were correlated with NH 4 

### -N, and only DNI was significantly correlated with TKN. The relations found for N were primarily the result of variability in NO 3 

### -N concentrations, because N was computed as the sum of NO 3 

### -N and TKN, and TKN was only weakly correlated with most indices. DSI values were more strongly correlated with nutrient concentrations than were the 

# Benthic Chlorophyll a and Periphytic-Diatom Communities and Their Relations with Water-Quality, Environmental, and Physical-Habitat Characteristics Benthic Chlorophyll a and Periphytic-Diatom Communities and Their Relations 51

Wisconsin Department of Natural Resources personnel collecting diatom samples. Microscopic diatom pictures provided by Paul Gar rison (Wisconsin Department of Natural Resources).7 – 446 447 – 1,125 1,126 – 2,996 2,997 – 7,491 7,492 – 1,06 8 ,000 1.7 – 3.1 3.2 – 4.0 4.1 – 4.3 4.4 – 4.6 4.7 – 5.4

2.6 – 14.0 14.1 – 2 8 .1 2 8 .2 – 47.6 47.7 – 66.6 66.7 – 95.3 22. 8 – 35.9 36.0 – 40.4 40.5 – 44.4 44.5 – 57.7 57. 8 – 100.0 Concentrations, in milligrams per square meter Index values

Index values Index values 

### Benthic chlorophyll a (BCHL) Diatom Nutrient Index (DNI)

Diatom Biotic Index (DBI) Diatom Siltation Index (DSI)

Figure 17. Distributions (quintiles) of benthic chlorophyll a (BCHL) concentrations, Diatom Nutrient Index (DNI) values, Diatom Siltation Index (DSI) values, and Diatom Biotic Index (DBI) values for the studied wadeable streams in Wisconsin. 

### 52 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### Table 11. Spearman rank correlation coefficients (r
s 

### ) between benthic chlorophyll a concentrations (BCHL) and diatom community indices, and median water-quality, environmental (anthropogenic/land-use, basin, soil and surficial-deposit), and physical-habitat characteristics for the studied wadeable streams in Wisconsin.

[all bold values were significant at p < 0.05, after being adjusted for the Bonferroni correction (Zar, 1999); see table 10 on page 49 f or definitions of abbreviations and units for each characteristic]

Characteristic Benthic chlorophyll a (BCHL) Diatoms Diatom Nutrient

Index (DNI) Diatom Siltation Index (DSI) Diatom Biotic Index (DBI) Water-quality characteristics Total phosphorus 0.33 0.47 0.60 -0.46 Dissolved phosphorus .33 .47 .59 -.46 Total nitrogen .49 .36 .43 -.10 Dissolved nitrite plus nitrate .53 .31 .40 -.05 Dissolved ammonia .12 .21 .30 -.13 Total Kjeldahl nitrogen -.07 .24 .09 -.17 Suspended chlorophyll a .21 .24 .29 -.17 Secchi tube depth -.22 -.39 -.41 .17 Anthropogenic/land-use characteristics
Urban .25 .26 .10 .03 Agriculture (row crops) .44 .42 .42 -.13 Agriculture (all) .50 .44 .51 -.14 Grassland .10 .12 .20 -.14 Wetland (open) -.12 .18 -.22 -.02 Wetland (forested) -.44 -.18 -.51 .10 Forest (all) -.44 -.45 -.48 .17 Point-source loading of

phosphorus .27 .26 .18 -.17

Basin characteristics
Watershed area .10 .12 -.07 -.07 Air temperature .48 .42 .51 .00 Precipitation .21 .05 .28 .08 Runoff -.42 -.41 -.35 .00 Basin slope .28 .08 .48 -.15 Flow per unit area -.16 -.17 -.18 .15 Soil and surficial-deposit characteristics Clay content .46 .44 .63 -.15 Erodibility .37 .37 .52 -.12 Organic-matter content -.41 -.14 -.55 .17 Permeability -.35 -.36 -.60 .25 Soil slope .06 -.25 .11 .08 Nonglacial deposits .42 -.01 .45 .03 Clay deposits .10 .30 .13 -.17 Loam deposits -.06 .02 .04 -.25 Peat deposits -.09 -.10 -.05 -.02 Sand deposits -.35 .00 -.34 .12 Sand-and-gravel deposits -.26 -.20 -.52 .24 

### Benthic Chlorophyll a and Periphytic-Diatom Communities 53

### DNI values except for TKN, and both indices were more strongly correlated with nutrient concentrations than wereDBI values. BCHL concentrations were more strongly correlated with the different forms of N, whereas the diatom indices were more strongly correlated with the different forms of P. Other studies have found the P-chlorophyll relation to be stronger than the N-chlorophyll relation (for example, Van Nieuwenhuyse and Jones, 1996). BCHL, DNI, and DSI were strongly correlated with SCHL, SD, and many of the anthropogenic/land-usecharacteristics, especially the percentages of total agriculture, row-crop agriculture, and forested areas. In addition, BCHL and the DNI were significantly correlated with the amount of urban land and PtS in the basin. Better index values (lower values for BCHL, DNI, and DSI) generally occurred in streams with lower SCHL and higher clarity, in areas with lower percentages of agriculture, less PtS, and higher percentages of forest. In general, these indices were also strongly correlated with several basin (air temperatureand runoff) and soil (clay content, erodibility, organicmatter content, and permeability) characteristics. Lower BCHL concentrations and better diatom indices generallyoccurred in areas with cooler air temperatures, higher runoff, less erodible soils with lower clay content and higher permeability, and sand-and-gravel surficial deposits. These areas with lower BCHL concentrations and better diatomindices are the mixed and mostly forested areas of Wisconsin (fig. 2A). In general, the BCHL and diatom indices were only weakly correlated with any physical-habitat characteristics except the percentage of the bottom covered in algae andthe amount of sandy sediment. Better benthic diatom communities occurred in streams with lower percentages of algal cover. BCHL and the diatom indices were unrelated to the size or depth of the streams. Characteristic Benthic chlorophyll a (BCHL) Diatoms Diatom Nutrient

Index (DNI) Diatom Siltation Index (DSI) Diatom Biotic Index (DBI) Physical-habitat characteristics
WIDTH -0.03 -0.01 -0.17 -0.04
DEPTH .11 .00 .03 -.03
THALD .07 -.03 .01 -.03 GRAD .02 -.05 .13 .01
POOL% .00 -.04 .13 -.02
RIFF% .13 .13 .11 -.01 RUN% -.07 -.04 -.15 .05 SEDEP -.04 -.10 -.05 .01 SILT% .17 .05 .18 .06
SAND% -.29 -.18 -.22 -.02
GRAV% .00 .22 -.02 -.04 EMB% -.08 -.18 -.06 .04
ALGAE% .28 .21 .24 .02 MACR% .01 -.12 -.06 .12 COVER% -.12 -.10 -.19 .06
SHADE% -.07 .07 -.11 .00
EROSION% .18 .20 .32 -.15
BUFFER -.03 .09 -.07 .04 

### Table 11. Spearman rank correlation coefficients (r
s 

### ) between benthic chlorophyll a concentrations (BCHL) and diatom community indices, and median water-quality, environmental (anthropogenic/land-use, basin, soil and surficial-deposit), and physical-habitat characteristics for the studied wadeable streams in Wisconsin—Continued.

[all bold values were significant at p < 0.05, after being adjusted for the Bonferroni correction (Zar, 1999); see table 10 on page 49 f or definitions of abbreviations and units for each characteristic] 

### 54 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

## Responses to Changes in Nutrient Concentrations
Responses in BCHL, DNI, and DSI to changes in nutrient concentrations are shown in figures 18 and 19 (DBI values, which were computed on the basis of DNI and DSI values, were less strongly correlated with nutrient concentrations and therefore are not shown). Ingeneral, all three indices increased as nutrient concentrations increased, although the responses to changes in N concentrations ranged more widely than changes in P. At low nutrient concentrations, the values of the indices ranged widely; however, at high nutrient concentrations, the values were generally limited to high BCHL and poor diatom indices. High BCHL concentrations and poordiatom indices were measured even at low nutrient concentrations. The lower bounds of the BCHL and DNI plots may provide an indication of the extent to which nutrients are capable of limiting BCHL and the diatom community. The variation above these bounds may indicate the effects caused by factors other than nutrients. Although nutrient concentrations were lower or higher in some EPZs and level III ecoregions (especiallylower in EPZ 1 and the NLF ecoregion), BCHL concentrations and diatom indices responded similarly to changes in nutrient concentrations in all areas (fig. 18). In all EPZs and ecoregions, there was a broad response at low nutrient concentrations and poor (higher) indices at high nutrient concentrations. Differences in the responses among areas could not be distinguished because of the range in the data and because the gradient in nutrient concentrations within many areas was small.Regression-tree analyses were done to define specific thresholds or breakpoints in the responses of BCHL concentrations and the diatom indices (table 12). The best statistical thresholds or breakpoints in the responses to changes in total P concentrations ranged from 0.039 mg/L for BCHL concentrations to 0.057–0.074 mg/L for the diatom indices. Thresholds in the response to changes in DP concentrations ranged from 0.020 mg/L for BCHL to 0.046 mg/L for DSI. Thresholds in the responses to changes in the different forms of N are also listed in table 12; however, the data in figures 18 and 19 do not show any consistent response except the DNI as a function of N. Thresholds in the responses to changes in N concentrations ranged from 0.872 to 1.216 mg/L. In general, sites with concentrations below the defined thresholds had a broad range in index values and sites above the defined threshold had poor index values, although the data do not indicate well-defined thresholds. To examine further the thresholds or breakpoints in the responses of BCHL and the diatom indices to changesin nutrient concentrations, a categorical approach developed by the Ohio Environmental Protection Agency (OEPA; Miltner and Rankin, 1998) was used to examine the BCHL and DNI responses. With this approach, not only was the response to a single nutrient constituent examined but also the interaction of P and N. For this analysis, each of the sites having BCHL and diatom index data was placed into one of five categories based upon their percentile rankings for P and N concentrations (25th, 50th, 75th, and 90th percentiles; table 13). The five categories in increasing nutrient concentrations are: category 1, sites that have both P and N concentrations less than their Table 12. Thresholds or breakpoints in the responses of benthic chlorophyll a (BCHL) concentrations and diatom indices to changes in nutrient concentrations for wadeable streams in Wisconsin.
[all nutrient concentrations are in milligrams per liter; log, logarithm to base 10 transformation]

Biological Indices Total phosphorus Dissolved phosphorus Total nitrogen Dissolved nitrite plus nitrate Dissolved ammonia Total Kjeldahl nitrogen Benthic chlorophyll a (BCHL) - log 0.039 0.020 0.918 0.187 0.040 0.310 Diatom Nutrient Index (DNI) .057 .026 1.216 .381 .021 .745 Diatom Siltation Index (DSI) .074 .046 .872 .089 .022 1.080 Diatom Biotic Index (DBI) .072 .039 1.169 .381 .022 .388



### Table 13. Percentiles of total phosphorus and total nitrogen concentration for the studied wadeable streams in Wisconsin having both benthic chlorophyll a and diatom index data.
[all concentrations in milligrams per liter]

Percentile Total phosphorus Total nitrogen 25th 0.039 0.797 50th .071 1.724 75th .125 3.771 90th .203 7.447 

### Benthic Chlorophyll a and Periphytic-Diatom Communities 55Benthic chlorophyllaBenthic chlorophyllaBenthic chlorophyllaBenthic chlorophylla012345670.0 0.2 0.4 0.6 0.81.0MEDIAN TOTAL PHOSPHORUS,IN MILLIGRAMS PER LITERMEDIAN TOTAL PHOSPHORUS,IN MILLIGRAMS PER LITERMEDIAN TOTAL PHOSPHORUS,IN MILLIGRAMS PER LITER

LOG (BENTHIC CHLOROPHYLL A , IN MILLIGRAMS PER SQUARE METER)Diatom Nutrient Index Diatom Nutrient Index Diatom Nutrient Index Diatom Nutrient Index01234560.0 0.2 0.4 0.6 0.81.0

DIATOM NUTRIENT INDEXDiatom Siltation Index Diatom Siltation Index Diatom Siltation Index Diatom Siltation Index02550751000.0 0.2 0.4 0.6 0.81.0

DIATOM SILTATION INDEXMEDIAN TOTAL NITROGEN,IN MILLIGRAMS PER LITERMEDIAN TOTAL NITROGEN,IN MILLIGRAMS PER LITERMEDIAN TOTAL NITROGEN,IN MILLIGRAMS PER LITER012345670 5 10 1501234560 5 10 1502550751000 5 10 15MEDIAN TOTAL PHOSPHORUS,IN MILLIGRAMS PER LITERMEDIAN TOTAL PHOSPHORUS,IN MILLIGRAMS PER LITERMEDIAN TOTAL PHOSPHORUS,IN MILLIGRAMS PER LITER012345670.0 0.2 0.4 0.6 0.81.001234560.0 0.2 0.4 0.6 0.81.002550751000.0 0.2 0.4 0.6 0.81.00123456701234560255075100MEDIAN TOTAL NITROGEN,IN MILLIGRAMS PER LITERMEDIAN TOTAL NITROGEN,IN MILLIGRAMS PER LITERMEDIAN TOTAL NITROGEN,IN MILLIGRAMS PER LITER0 5 10 15 20 250 5 10 150 5 10 15DFANCHFNLFSWTPDFANCHFNLFSWTPDFANCHFNLFSWTPDFANCHFNLFSWTPDFANCHFNLFSWTPDFANCHFNLFSWTPEPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 50.039 mg/L 1.641 mg/L 1.641 mg/L 1.641 mg/L 1.641 mg/L 1.641 mg/L 1.641 mg/L 21.260 mg/L 21.260 mg/L 21.260 mg/L 21.260 mg/L 21.260 mg/L 21.260 mg/L0.057 mg/L0.074 mg/L 0.074 mg/L0.872 mg/L 0.872 mg/L1.216 mg/L1.216 mg/L0.057 mg/L0.039 mg/L 0.918 mg/L 0.918 mg/LFigure 18.Benthic chlorophyllaconcentrations (logarithm to base 10 transformation), Diatom Nutrient Index values, and Diatom Siltation Index values as a function of totalphosphorus and total nitrogen concentration in the environmental phosphorus zones (EPZs) and level III ecoregions for the studied wadeable streams in Wisconsin. Computedthresholds in the response are identified by vertical lines. [DFA, Driftless Area; NCHF, North Central Hardwood Forests; NLF, Northern Lakes and Forests; and SWTP, SoutheasternWisconsin Till Plains] 

### 56 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin0.040 mg/L0.310 mg/L0.745 mg/L0.021 mg/L0.381 mg/L0.026 mg/L0.046 mg/L0.089 mg/L1.080 mg/L0.022 mg/LBenthic chlorophyllaBenthic chlorophyllaBenthic chlorophyllaBenthic chlorophylla012345670.0 0.2 0.4 0.6 0.81.0MEDIAN DISSOLVED PHOSPHORUS,IN MILLIGRAMS PER LITERMEDIAN DISSOLVED PHOSPHORUS,IN MILLIGRAMS PER LITERMEDIAN DISSOLVED PHOSPHORUS,IN MILLIGRAMS PER LITER

LOG (BENTHIC CHLOROPHYLL A , IN MILLIGRAMS PER SQUARE METER)012345670 5 10 15MEDIAN DISSOLVED NITRITE PLUS NITRATE,IN MILLIGRAMS PER LITER012345670.0 0.1 0.2 0.3 0.4 0.5MEDIAN DISSOLVED AMMONIA,IN MILLIGRAMS PER LITER012345670.0 0.5 1.0 1.5 2.0 2.5MEDIAN TOTAL KJELDAHL NITROGEN,IN MILLIGRAMS PER LITERMEDIAN DISSOLVED NITRITE PLUS NITRATE,IN MILLIGRAMS PER LITERMEDIAN DISSOLVED AMMONIA,IN MILLIGRAMS PER LITERMEDIAN TOTAL KJELDAHL NITROGEN,IN MILLIGRAMS PER LITERMEDIAN DISSOLVED NITRITE PLUS NITRATE,IN MILLIGRAMS PER LITERMEDIAN DISSOLVED AMMONIA,IN MILLIGRAMS PER LITERMEDIAN TOTAL KJELDAHL NITROGEN,IN MILLIGRAMS PER LITERDiatom Nutrient Index Diatom Nutrient Index Diatom Nutrient Index Diatom Nutrient Index01234560.0 0.2 0.4 0.6 0.81.0

DIATOM NUTIENT INDEXDiatom Siltation Index Diatom Siltation Index Diatom Siltation Index Diatom Siltation Index02550751000.0 0.2 0.4 0.6 0.81.0

DIATOM SILTATION INDEX01234560 5 10 1502550751000 5 10 1501234560.0 0.1 0.2 0.3 0.4 0.502550751000.0 0.1 0.2 0.3 0.4 0.501234560.0 0.5 1.0 1.5 2.0 2.502550751000.0 0.5 1.0 1.5 2.0 2.5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4 EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4 EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4 EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 50.020 mg/L 0.187 mg/L

1.460 mg/L 1.460 mg/L 1.460 mg/L 20.550 mg/L 20.550 mg/L 20.550 mg/LFigure 19.Benthic chlorophyllaconcentrations (logarithm to base 10 transformation), Diatom Nutrient Index values, and Diatom Siltation Index values as a function ofdissolved phosphorus, dissolved nitrite plus nitrate, dissolved ammonia, and total Kjeldahl nitrogen concentrations in the environmental phosphorus zones (EPZs) for the studiedwadeable streams in Wisconsin. Computed thresholds in the response are identified by vertical lines. 

### Benthic Chlorophyll a and Periphytic-Diatom Communities 57

### 25th percentiles; category 2, sites that are not in category 1 and have either P or N concentrations less than their 50th percentiles; category 3, sites that are not in categories 1 or 2 and have P concentrations less than its 75th percentileand N concentrations less than its 90th percentile; category 4, sites that are not in categories 1, 2, or 3 and have P concentrations between and including its 75th and 90th percentiles (N concentrations do not matter); and category 5, sites that have both P and N concentrations greater than their 90th percentiles (OEPA also includes a sixth category for sites that have NH 4 

### -N concentrations greater than 1.0 mg/L but there were no such sites in this study.) Sites in category 1 (P concentrations less than 0.039 mg/L and N concentrations less than 0.797 mg/L) had BCHL concentrations significantly less than those in categories 2 through 5 (fig. 20). BCHL concentrations increased slightly from category 2 to category 5; however, the differences were not statistically significant at p < 0.05. Sites in categories 1 and 2 (P concentrations less than 0.071 mg/L and N concentrations less than1.724 mg/L) had significantly lower (better) DNI values than those in categories 3 through 5. Therefore, the threshold in the response of the BCHL concentrations was at P concentrations less than about 0.04 mg/L and N less than about 0.8 mg/L, whereas the threshold in the response 0 1 2 3 4 5 6DIATOM NUTRIENT INDEX 12 3 45 NUTRIENT CATEGORY

12 3 45 NUTRIENT CATEGORY 0 1 2 3 4 5 6LOG (BENTHIC CHLOROPHYLLA,IN MILLIGRAMS PER LITER)

EXPLANATION

Outlier

Interquartile

range (IR) 75th percentile + 1.5 * IR

25th percentile – 1.5 * IR 75th percentile

25th percentile Median



### Figure 20. Benthic chlorophyll a concentrations and Diatom Nutrient Index values for five nutrient categories for the studied wadeable streams in Wisconsin (each nutrient category is defined in the text on pages 55 and 58). 

### 58 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### in DNI values was at higher concentrations of P (less than about 0.07 mg/L) and N (less than about 1.7 mg/L). Thesethresholds are similar to those found from the regressiontree approach, except for the N threshold for the diatom community, which was less (about 1.2 mg/L; table 12) than the value found with this approach. The multimetric diatom index DBI was also tested as a means to define thresholds in the response of the diatom community to changes in nutrient concentrations. The DNI and DSI, however, provided more defined thresholds in the response of the diatom community to changes in nutrient concentrations, and, therefore, the DBI was not examined in further detail for this purpose. 

## Effects of Multiple Characteristics on Benthic Chlorophyll a Concentrations and Diatom Indices Stepwise Regressions
Forward stepwise regressions were done with thewater-quality (median values), environmental, and physical-habitat characteristics to determine which four characteristics best described the variance in BCHL concentrations and the diatom indices (table 14). Models with more than four variables did not significantly increase the amount of variance explained (accumulative R 2 

### values). For BCHL, NO 3 

### -N concentration was the first variable incorporated in the model, whereas DP concentration was the first variable incorporated in the DNI and DBI models.The clay content of the soil was the first variable incorporated in the DSI model, followed by P concentration. The clay content of the soil indicates the potential for siltation and, therefore, was expected to be an important variable in the DSI model. With four variables, the models explained between 31 and 60 percent of the total variance in the indices; therefore, 40 to 70 percent of the variance was not explained by the characteristics examined in this study.


## Redundancy Analysis
Partial RDA was used to determine the relative importance of nutrients, other water-quality characteristics (pH,specific conductance, water clarity, and flow), and environmental and physical-habitat characteristics (tables 2 and 10) in influencing the distribution of BCHL and the three diatom indices. In this analysis, individual monthly (July and August) and median values were included for each nutrient. A forward variable-selection procedure, which correlated the BCHL and the three diatom indices to the other factors, was used to select a subset of variables for each general type of characteristic. This procedure retained 7 nutrient variables, 5 other water-quality characteristics, and 11 environmental and physical-habitat characteristics. These final 23 characteristics explained 54 percent of the variance in BCHL and the diatom indices. Of the explained variance, 13 percent was explained by the nutrients alone, 4 percent by the other water-quality characteristics alone,46 percent by the environmental and physical-habitat characteristics alone, and 37 percent by the interactions amongall the characteristics (fig. 21). Therefore, nutrient concentrations by themselves explained only a small part (about 7 percent) of the total variance in BCHL and the diatom communities. About 46 percent of the total variance could not be explained with the characteristics examined in this study.

Table 14. Results of forward stepwise-regression analysis to explain the variance in benthic chlorophyll a concentrations and the three diatom indices in the studied wadeable streams in Wisconsin.

[R 2 , coefficient of determination for the one-, two-, three-, and four-variable models; all regressions were on log-transformed va lues of the dependant variable]

Dependent variable First variable Second variable Third variable Fourth variable Benthic chlorophyll a (BCHL) Nitrite plus nitrate Nonglacial deposits Loam deposits Runoff Accumulative R 2 0.32 0.37 0.40 0.43 Diatom Nutrient Index (DNI) Dissolved phosphorus Wetland (forested) Percentage of pools Soil slope Accumulative R 2 .25 .31 .33 .34 Diatom Siltation Index (DSI) Clay content of soil Total phosphorus Nonglacial deposits Grassland Accumulative R 2 .42 .49 .59 .60 Diatom Biotic Index (DBI) Dissolved phosphorus Agriculture (row crops) Wetland (forested) Percentage of sand bottom Accumulative R 2 .19 .25 .29 .31 

### Benthic Chlorophyll a and Periphytic-Diatom Communities 59

## Reference Values for Benthic Chlorophyll a Concentrations and Diatom Indices

A reference BCHL concentration and reference values for the three diatom indices were determined by examining the concentrations and index values at only the sites having both P and N concentrations at or below their respective reference concentrations (35 Reference sites). The median BCHL concentration for the Reference sites was 331 mg/m 2 

### (log (331) = 2.52; the 75th percentile was 673 mg/m 2 

### ), which was significantly less than the median concentration measured at the High (nonreference) sites (3,020 mg/m 2 

### ; log (3,020) = 3.48; fig. 22). The median DNI and DSI values for the Reference sites were 3.38 and 11.80, respectively (with 75th percentiles of 4.05 and 22.50, respectively), which were significantly less than the median values measured at the High sites (4.39 and 52.00, respectively). The median DBI value for the Reference sites was 47.5 (with a 25th percentile of 37.4; a lower percentile is given because a larger DBI represents a better diatom community), which was significantly greater than the median value measured at the High sites (39.9). If 75 percent of the minimally impacted sites (the Reference sites) have water-quality conditions or index values at least as good as the reference condition, then the reference concentration for BCHL is 673 mg/m 2 

### , and the reference index values for DNI, DSI, and DBI are 4.05, 22.5, and 37.4, respectively. Comparing the median concentration and index values for the Reference sites with those for the Ref N and Ref P sites may provide an indication of whether P or N is more important in limiting the concentrations of BCHL and the degradation of the diatom community in streams with nutrient concentrations near reference conditions (fig. 22). For BCHL, it appears that N is the more important limiting nutrient because the median value for the Ref P sites was significantly higher than the median value forthe Reference sites, and there was no statistical difference between median values for Reference sites and the Ref N sites. In other words, small additions of N (Ref P) had more of an effect on BCHL concentrations than small additions of P (Ref N). Small additions of N also may have had a small effect on DSI values, although the median values for the categories were not significantly different. Small additions of P and N had little effect on DNI and DBI values in streams with nutrient concentrations near reference conditions. Nutrients Other water-quality characteristics Environmental and physical-habitat characteristics Interactions among categories 

### 13% 4%

37%

46% General categories

Figure 21. Percentage of explained variance in benthic chlorophyll a concentrations and diatom index values described by nutrients, other water-quality characteristics,environmental (anthropogenic/land-use, soil, and surficialdeposit characteristics) and physical-habitat characteristics, and interactions among categories (variance that can not be explained by a single category) for the studied wadeable streams in Wisconsin. [%, percentage of explained variance] 

### 60 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in WisconsinReference High Ref N Ref P 0 20 40 60 8 0 100DIATOM SILTATION INDEX Reference High Ref N Ref P

0 1 2 3 4 5 6 7LOG (BENTHIC CHLOROPHYLLA,IN MILLIGRAMS PER SQUARE METER)

Reference High Ref N Ref P 0 1 2 3 4 5 6DIATOM NUTRIENT INDEX

Reference High Ref N Ref P 0 20 40 60 8 0 100DIATOM BIOTIC INDEX

EXPLANATION

Outlier

Interquartile

range (IR) 75th percentile + 1.5 * IR

25th percentile – 1.5 * IR 75th percentile

25th percentile Median



### Figure 22. Benthic chlorophyll a concentrations, Diatom Nutrient Index, Diatom Siltation Index, and Diatom Biotic Index values in Reference sites, High (nonreference) sites, and sites with only reference total nitrogen (Ref N sites) or reference t otal phosphorus (Ref P sites) concentrations in the studied wadeable streams in Wisconsin. [log, logarithm to base 10 transformation ] 

### Benthic Chlorophyll a and Periphytic-Diatom Communities 61

### Six indices were used to describe the macroinvertebrate communities in the studied wadeable streams in Wisconsin (table 10 on page 50). Hilsenhoff Biotic Index (HBI) values ranged from 0.8 to 9.4 (median = 4.7); the percentage of individuals that were either Ephemeroptera, Plecoptera, or Trichoptera (EPTN%) varied from 0.0 to 99.2 percent (median = 42.3 percent); the percentage of taxa that were Ephemeroptera, Plecoptera, or Trichoptera (EPTTX%) varied from 0.0 to 74.3 percent (median = 35.7percent); the percentage of the individuals that were scrapers (SCRAP%) varied from 0.0 to 85.4 percent (median = 14.7 percent); the percentage of individuals that were shredders (SHRED%) varied from 0.0 to 24.7 percent (median = 0.0 percent), and the total numbers of taxa (TAXAN) varied from 4 to 67 (median = 29). In general,streams in the northern part of the State had macroinvertebrate communities that would normally be considered representative of better water quality, with lower HBI values, higher EPTN% and EPTTX% (fig. 23), and higher TAXAN than the streams in the southeastern part of the State. The SCRAP% and SHRED% did not exhibit strong regional patterns. 

## Relations with Individual Characteristics
Correlations
Spearman rank correlation coefficients (r
s 

### values) between the six macroinvertebrate indices and medianwater-quality, environmental, and physical-habitat characteristics are given in table 15. All six indices were significantly correlated with at least two nutrient constituents. Of the six macroinvertebrate indices, HBI, EPTN%, and EPTTX% were most strongly correlated with the nutrients. HBI and EPTN% were significantly correlated with all of the nutrients except NO 3 

### -N. SCRAP% and TAXAN were negatively correlated with most nutrients, although manyof the correlations were not statistically significant. Concentrations of P and N were positively correlated with HBI values and negatively correlated with EPTN%, EPTTX%, and TAXAN. Better macroinvertebrate indices (lower HBI values, higher EPT indices, and more taxa) occurred with lower nutrient concentrations. The SCRAP%, SHRED%, and TAXAN were less strongly correlated with most nutrient concentrations. Individual monthly nutrient 

# Macroinvertebrate Communities and Their Relations with Water-Quality, Environmental, and Physical-Habitat Characteristics 62 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Wisconsin Department of Natural Resources personnel collecting macroinvertebrate samples. Macroinvertebrate pictures provided b y Stanley Szczytko (University of Wisconsin–Stevens Point).0. 8 – 3.7 3. 8 – 4.4 4.5 – 5.0 5.1 – 6.0 6.1 – 9.4 0 – 11.4 11.5 – 32.6 32.7 – 49.4 49.5 – 6 8 .4 6 8 .5 – 99.2

0 – 17.2 17.3 – 31. 8 31.9 – 3 8 .0 3 8 .1 – 50.0 50.1 – 74.3 Index values Percentages

Percentages 

### Hilsenhoff Biotic Index (HBI) Percentage of EPT indiv iduals (EPTN%)



### Percentage of EPT taxa (EPTTX%)

Figure 23. Distributions (quintiles) of macroinvertebrate Hilsenhoff Biotic Index (HBI) values, the percentages of individuals that were Ephemeroptera, Plecoptera, or Trichoptera (EPTN%), and the percentages of taxa that were Ephemeroptera, Plecoptera, or Trichoptera (EPTTX%) for the studied wadeable streams in Wisconsin. 

### Macroinvertebrate Communities 63

### Table 15. Spearman rank correlation coefficients (r
s 

### ) between macroinvertebrate-community indices and median water-quality, environmental (anthropogenic/land-use, basin, soil and surficial-deposit), and physical-habitat characteristics for the studied wadeable streams in Wisconsin.
[EPT, Ephemeroptera, Plecoptera, and Trichoptera; %, percent; all bold values were significant at p < 0.05, after being adjusted for the Bonferroni correction (Zar, 1999); see table 10 on page 49 for definitions of abbreviations and units for each parameter]

Characteristic Hilsenhoff Biotic Index Percentage of EPT individuals Percentage of EPT taxa Percentage of scrapers Percentage of shredders Number of taxa Water-quality characteristics Total phosphorus 0.55 -0.35 -0.46 -0.21 0.09 -0.19 Dissolved phosphorus .50 -.33 -.43 -.18 .06 -.18 Total nitrogen .37 -.37 -.39 -.10 -.06 -.30 Dissolved nitrite plus nitrate .16 -.24 -.20 .03 -.21 -.28 Dissolved ammonia .53 -.39 -.54 -.21 .12 -.27 Total Kjeldahl nitrogen .54 -.28 -.44 -.28 .30 -.10 Suspended chlorophyll a .42 -.27 -.33 -.04 .18 .04 Secchi tube depth -.41 .29 .34 .17 -.11 .23 Anthropogenic/land-use characteristics
Urban .16 -.10 -.03 .00 .06 -.08 Agriculture (row crops) .45 -.42 -.45 -.07 -.04 -.33 Agriculture (all) .43 -.38 -.42 -.02 -.06 -.31 Grassland -.12 -.02 .08 .18 -.22 -.15 Wetland (open) .17 -.07 -.11 -.08 .22 .04 Wetland (forested) .04 .11 .04 -.14 .25 .16 Forest (all) -.48 .42 .48 .08 .01 .30 Point-source loading of

phosphorus .14 .05 .05 -.05 .11 .03

Basin characteristics Watershed area -.13 .24 .17 .05 .09 .23 Air temperature .36 -.33 -.33 .01 -.13 -.30 Precipitation -.08 -.03 .11 .25 -.21 -.09 Runoff -.32 .27 .26 -.01 .14 .27 Basin Slope -.15 .11 .15 .18 -.26 -.11 Flow per unit area -.30 .22 .27 .17 -.09 .08 Soil and surficial-deposit characteristics Clay content .24 -.26 -.24 .07 -.10 -.31 Erodibility .29 -.24 -.28 .07 -.07 -.21 Organic-matter content .05 .02 -.02 -.21 .31 .13 Permeability -.20 .20 .22 -.05 .06 .21 Soil slope -.39 .28 .42 .23 -.23 .13 Nonglacial deposits -.10 .05 .09 .18 -.18 -.03 Clay deposits .24 -.19 -.22 -.16 .10 -.09 Loam deposits .04 .09 .04 .03 -.03 .00 Peat deposits .09 -.06 -.13 -.19 .24 .01 Sand deposits .02 -.03 -.01 -.08 .17 .09 Sand-and-gravel deposits -.14 .13 .15 -.07 .07 .11 

### 64 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in WisconsinCharacteristic Hilsenhoff Biotic Index Percentage of EPT individuals Percentage of EPT taxa Percentage of scrapers Percentage of shredders Number of taxa Physical-habitat characteristics
WIDTH -0.20 0.35 0.25 0.09 0.11 0.31
DEPTH .00 .13 .04 .00 .12 .10
THALD -.04 .17 .07 .00 .13 .14 GRAD -.16 .01 .11 .19 -.26 -.08 POOL% -.16 .07 .10 .19 -.17 .03
RIFF% -.26 .23 .28 .28 -.28 .01
RUN% .25 -.19 -.25 -.28 .26 -.04
SEDEP .20 -.20 -.26 -.27 .15 -.08
SILT% .41 -.32 -.43 -.15 .09 -.11 SAND% -.18 .06 .16 -.05 -.03 .12
GRAV% -.25 .24 .28 .30 -.22 .04
EMB% .26 -.26 -.30 -.31 .15 -.05
ALGAE% .25 -.15 -.23 .04 -.05 -.13 MACR% .16 -.08 -.15 -.14 .13 .15 COVER% .06 .01 -.07 -.12 .21 .16 SHADE% -.09 .04 .05 .00 -.19 -.15 EROSION% .02 -.03 .00 .06 -.21 -.18 BUFFER .05 -.07 -.05 -.04 .08 -.14 

### Table 15. Spearman rank correlation coefficients (r
s 

### ) between macroinvertebrate-community indices and median water-quality, environmental (anthropogenic/land-use, basin, soil and surficial-deposit), and physical-habitat characteristics for the studied wadeable streams in Wisconsin—Continued.
[EPT, Ephemeroptera, Plecoptera, and Trichoptera; %, percent; all bold values were significant at p < 0.05, after being adjusted for the Bonferroni correction (Zar, 1999); see table 10 on page 49 for definitions of abbreviations and units for each parameter] 

### Macroinvertebrate Communities 65

### concentrations were examined, but in all cases the monthly values explained less variance than the median values. In general, HBI, EPTN%, and EPTTX% were also the indices most strongly correlated with SCHL, SD, and the anthropogenic/land-use characteristics, especiallythe percentages of total agriculture, row-crop agriculture, and forested areas. Better macroinvertebrate indices (lower HBIs and higher EPT indices) generally occurred in streams with lower SCHL and higher clarity, in areaswith lower percentages of agriculture and higher percentages of forest. SCRAP%, SHRED%, and TAXAN were less strongly correlated with the anthropogenic/land-use characteristics. HBI, EPTN%, and EPTTX% were also more strongly correlated with the basin characteristics (air temperature, runoff, and flow per unit area) and the soil and surficial-deposit characteristics (clay content of the soil, erodibility, soil slope, and clay deposits) than were the other three macroinvertebrate indices. In general, better macroinvertebrate communities were found in areas with cooler air temperatures, higher runoff, soils with lower clay content, and higher soil slope. These areas with better macroinvertebrate indices are generally the mixed and mostly forested areas of Wisconsin (fig. 2A). In general, the macroinvertebrate indices were onlymoderately correlated with the physical-habitat characteristics. The physical-habitat characteristics that were most strongly correlated with macroinvertebrate indices were the percentages of rocky-substrate embeddedness, percentagesof riffles and runs, and percentages of silt and gravel sediment. Better macroinvertebrate communities were found inwider streams with lower percentages of runs, rocky-substrate embeddedness, and silt sediment, and higher percentages of riffles and gravel substrate. Many macroinvertebratesamples were collected in areas of the stream with physical-habitat characteristics that were substantially different from the average characteristics for the entire stream reach. Improved correlations between the physical-habitat characteristics and the macroinvertebrate indices would have probably occurred if the habitat characteristics wereestimated for only the area near the macroinvertebrate-sampling location.


## Response to Changes in Nutrient Concentrations
Responses in the three macroinvertebrate community indices most strongly correlated with nutrients (HBI, EPTN%, and EPTTX%) are shown in figures 24 and 25. In general, HBI values increased as nutrient concentrations increased, whereas EPTN% and EPTTX% values decreased or showed no clear trend with increases in nutrient concentrations. At low nutrient concentrations, the values of these macroinvertebrate measures ranged widely; however, at high nutrient concentrations, the values were generally poor (high HBI values and low EPT indices). The best relations were found between HBI values and P, DP, and TKN concentrations, and between both EPT indices and P, DP, and NH 4 

### -N concentrations. The other relations with nutrient concentrations ranged more widely; little relation was found between both EPT indices and N, TKN, and NO 3 

### -N concentrations. The lower bounds ofHBI plots and the upper bounds of the EPT plots may provide an indication of how nutrients are capable of affecting the macroinvertebrate community. The variation below the HBI bounds and above the EPT bounds may indicate the effects caused by factors other than nutrients. Although nutrient concentrations were lower or higher in some EPZs and ecoregions (especially lower in EPZ 1 and the NLF ecoregion), macroinvertebrate indicesresponded similarly to changes in nutrient concentrations in all areas of the State (fig. 24). In all areas, there was a broad response at low nutrient concentrations and poor indices at high nutrient concentrations. Differences in the responses among areas could not be distinguished because of the range of the data and because the gradient in nutrient concentrations within some areas was small. Regression-tree analyses were performed to define specific thresholds or breakpoints in the responses of the three macroinvertebrate community indices most strongly correlated with nutrients (table 16). The thresholds or breakpoints in the responses to changes in most nutrient concentrations were consistent among these three indices, although the data do not indicate well-defined thresholds. The thresholds in the responses to changes in total P concentrations were at about 0.09 mg/L, to changes in DP concentrations were at about 0.06–0.08 mg/L, to changes in total N concentrations were from 0.609 to 1.106 mg/L (the lowest threshold value occurred for HBI), to changes in NH 4 

### -N concentrations were at about 0.03 mg/L, and to changes in TKN concentrations were at about 1.0 mg/L. The range in the thresholds to changes in NO 3 

### -N concentrations was broader (from 1.157 to 3.585 mg/L). In general, the macroinvertebrate indices ranged widely below the thresholds; however, macroinvertebrate indices were poor above the thresholds. 66 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin0.088 mg/L0.088 mg/L

1.641 mg/L 1.641 mg/L 1.641 mg/L 1.641 mg/L 1.641 mg/L 1.641 mg/L 21.260 mg/L 21.260 mg/L 21.260 mg/L 21.260 mg/L 21.260 mg/L 21.260 mg/L0.609 mg/L0.609 mg/L0.907 mg/L0.907 mg/L0.087 mg/L0.087 mg/L0.091 mg/L0.091 mg/L1.106 mg/L1.106 mg/LHilsenhoff Biotic Index012345678910 100.0 0.2 0.4 0.6 0.81.0MEDIAN TOTAL PHOSPHORUS,IN MILLIGRAMS PER LITERMEDIAN TOTAL PHOSPHORUS,IN MILLIGRAMS PER LITERMEDIAN TOTAL NITROGEN,IN MILLIGRAMS PER LITERMEDIAN TOTAL NITROGEN,IN MILLIGRAMS PER LITERMEDIAN TOTAL PHOSPHORUS,IN MILLIGRAMS PER LITERMEDIAN TOTAL PHOSPHORUS,IN MILLIGRAMS PER LITERMEDIAN TOTAL NITROGEN,IN MILLIGRAMS PER LITERMEDIAN TOTAL NITROGEN,IN MILLIGRAMS PER LITERMEDIAN TOTAL PHOSPHORUS,IN MILLIGRAMS PER LITERMEDIAN TOTAL PHOSPHORUS,IN MILLIGRAMS PER LITERMEDIAN TOTAL NITROGEN,IN MILLIGRAMS PER LITERMEDIAN TOTAL NITROGEN,IN MILLIGRAMS PER LITER

HILSENHOFF BIOTIC INDEXPercentage of EPT individuals01020304050607080901000.0 0.2 0.4 0.6 0.81.0

PERCENTAGE OF EPT INDIVIDUALSPercentage of EPT taxa01020304050607080901000.0 0.2 0.4 0.6 0.81.0

PERCENTAGE OF EPT TAXAHilsenhoff Biotic Index0123456789100 5 10 15Percentage of EPT individuals01020304050607080901000 5 10 15Percentage of EPT taxa01020304050607080901000 5 10 15Hilsenhoff Biotic Index01234567890.0 0.2 0.4 0.6 0.81.0Percentage of EPT individuals01020304050607080901000.0 0.2 0.4 0.6 0.81.0Percentage of EPT taxa01020304050607080901000.0 0.2 0.4 0.6 0.81.0Hilsenhoff Biotic Index01234567890 5 10 15Percentage of EPT individuals01020304050607080901000 5 10 15Percentage of EPT taxa01020304050607080901000 5 10 15EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5DFANCHFNLFSWTPDFANCHFNLFSWTPDFANCHFNLFSWTPDFANCHFNLFSWTPDFANCHFNLFSWTPDFANCHFNLFSWTPFigure 24.Hilsenhoff Biotic Index values, the percentages of individuals that were Ephemeroptera, Plecoptera, or Trichoptera, and the percentages of taxa that wereEphemeroptera, Plecoptera, or Trichoptera as a function of total phosphorus and total nitrogen concentration in the environmental phosphorus zones (EPZs) and level IIIecoregions for the studied wadeable streams in Wisconsin. Computed thresholds in the response are identified by vertical lines.[DFA, Driftless Area; NCHF, North CentralHardwood Forests; NLF, Northern Lakes and Forests; and SWTP, Southeastern Wisconsin Till Plains] 

### Macroinvertebrate Communities 670.077 mg/L3.455 mg/L

1.460 mg/L 1.460 mg/L 1.460 mg/L 20.550 mg/L 20.550 mg/L 20.550 mg/L0.029 mg/L0.965 mg/L1.053 mg/L0.029 mg/L0.077 mg/L0.061 mg/L3.585 mg/L0.034 mg/L0.930 mg/L1.157 mg/LHilsenhoff Biotic Index Hilsenhoff Biotic Index Hilsenhoff Biotic Index Hilsenhoff Biotic Index0123456789100.0 0.2 0.4 0.6 0.81.0MEDIAN DISSOLVED PHOSPHORUS,IN MILLIGRAMS PER LITERMEDIAN DISSOLVED NITRITE PLUS NITRATE,IN MILLIGRAMS PER LITERMEDIAN DISSOLVED AMMONIA,IN MILLIGRAMS PER LITERMEDIAN TOTAL KJELDAHL NITROGEN,IN MILLIGRAMS PER LITER

HILSENHOFF BIOTIC INDEX0123456789100 5 10 150123456789100.0 0.1 0.2 0.3 0.4 0.50123456789100.0 0.5 1.0 1.5 2.0 2.5Percentage of EPT individuals Percentage of EPT individuals Percentage of EPT individuals Percentage of EPT individuals0.0 0.2 0.4 0.6 0.81.0MEDIAN DISSOLVED PHOSPHORUS,IN MILLIGRAMS PER LITERMEDIAN DISSOLVED NITRITE PLUS NITRATE,IN MILLIGRAMS PER LITERMEDIAN DISSOLVED AMMONIA,IN MILLIGRAMS PER LITERMEDIAN TOTAL KJELDAHL NITROGEN,IN MILLIGRAMS PER LITER0 5 10 150.0 0.1 0.2 0.3 0.4 0.50.0 0.5 1.0 1.5 2.0 2.50.0 0.2 0.4 0.6 0.81.0MEDIAN DISSOLVED PHOSPHORUS,IN MILLIGRAMS PER LITERMEDIAN DISSOLVED NITRITE PLUS NITRATE,IN MILLIGRAMS PER LITERMEDIAN DISSOLVED AMMONIA,IN MILLIGRAMS PER LITERMEDIAN TOTAL KJELDAHL NITROGEN,IN MILLIGRAMS PER LITER0 5 10 150.0 0.1 0.2 0.3 0.4 0.50.0 0.5 1.0 1.5 2.0 2.50102030405060708090100 PERCENTAGE OF EPT INDIVIDUALSPercentage of EPT taxa Percentage of EPT taxa Percentage of EPT taxa Percentage of EPT taxa0102030405060708090100 PERCENTAGE OF EPT TAXA010203040506070809010001020304050607080901000102030405060708090100010203040506070809010001020304050607080901000102030405060708090100EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5Figure 25.Hilsenhoff Biotic Index values, the percentages of individuals that were Ephemeroptera, Plecoptera, or Trichoptera, and the percentages of taxa that wereEphemeroptera, Plecoptera, or Trichoptera as a function of dissolved phosphorus, dissolved nitrite plus nitrate, dissolved ammonia, and total Kjeldahl nitrogen concentrations inthe environmental phosphorus zones (EPZs) for the studied wadeable streams in Wisconsin. Computed thresholds in the response are identified by vertical lines. 

### 68 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

## Effects of Multiple Characteristics on Macroinvertebrate Indices Stepwise Regressions
Forward stepwise regressions were done with the median water-quality, environmental, and physical-habitat characteristics to determine which four characteristics best described the variance in the macroinvertebrate indices (table 17). Models with more than four variables did not significantly increase the amount of variance explained (accumulative R 2 

### value). For most indices, either a nutrient or the percentage of forest/agriculture was the first variable incorporated in the models, except for the SCRAP% and SHRED% that were found to be weakly correlated with nutrient concentrations. Even with four variables, the models explained only 19 to 47 percent of the variance in the indices. The stepwise regressions explained the most variance in the same three macroinvertebrate indices (HBI, EPTN%, and EPTTX%) that were most related to the nutrients and environmental characteristics. The SHRED% model appears to have better predictability than the percent variance explained indicates because most of the values for SHRED% were 0.

Table 17. Results of forward stepwise-regression analyses to explain variance in macroinvertebrate indices for the studied wadeable streams in Wisconsin.
[EPT, Ephemeroptera, Plecoptera, and Trichoptera; R 2 , coefficient of determination for the one-, two-, three-, and four-variable models]

Dependent variable First variable Second variable Third variable Fourth variable
Hilsenhoff Biotic Index

(HBI) Dissolved ammonia Flow per unit area Percentage of macrophyte cover Total phosphorus

Accumulative R 2 0.31 0.38 0.43 0.47 Percentage of EPT individuals

(EPTN%) Forest (all) Percentage of rockysubstrate embeddedness Stream depth Organic-matter content Accumulative R 2 .19 .28 .32 .35 Percentage of EPT taxa

(EPTTX%) Dissolved ammonia Agriculture (row crops) Percentage of rockysubstrate embeddedness Flow per unit area

Accumulative R 2 .26 .35 .42 .45 Percentage of scrapers

(SCRAP%) Precipitation Sediment depth Total phosphorus Percentage of macrophyte cover Accumulative R 2 .07 .12 .16 .19 Percentage of shredders

(SHRED%) Peat deposits Kjeldahl nitrogen Percentage of streambank with erosion Percentage of silt

Accumulative R 2 .30 .35 .38 .41
Number of taxa

(TAXAN) Total nitrogen Watershed area Clay deposits Buffer width

Accumulative R 2 .14 .17 .20 .22 

### Macroinvertebrate Communities 69

Table 16. Thresholds or breakpoints in the responses in macroinvertebrate indices to changes in nutrient concentrations for wadeable streams in Wisconsin.
[EPT, Ephemeroptera, Plecoptera, and Trichoptera; all concentrations are in milligrams per liter]

Biological indices Total phosphorus Dissolved phosphorus Total nitrogen Dissolved nitrite plus nitrate Dissolved ammonia Total Kjeldahl nitrogen Hilsenhoff Biotic Index (HBI) 0.088 0.077 0.609 3.455 0.029 0.965 Percentage of EPT individuals

(EPTN%) .087 .077 .970 1.157 .029 1.053

Percentage of EPT taxa (EPTTX%) .091 .061 1.106 3.585 .034 .938

## Redundancy Analysis
Partial RDA was used to determine the relative importance of the nutrients, other water-quality characteristics, and environmental and physical-habitat characteristics(tables 2 and 10) in affecting the distribution of the macroinvertebrate communities (the six macroinvertebrate-community indices). In this analysis, individual monthly (July and August) and median values were included for each nutrient. A forward variable-selection procedure, which correlated the macroinvertebrate indices with the other factors, was used to select a subset of variables for each general type of characteristic. This procedure retained 9 nutrient variables, 3 other water-quality characteristics,and 17 environmental and physical-habitat characteristics. These 29 characteristics explained 43 percent of the variance in the six macroinvertebrate-community indices. Of the explained variance, 22 percent was described by the nutrients alone, 5 percent by the other water-quality characteristics alone, 41 percent by the environmental and physical-habitat characteristics alone, and 32 percent by the interactions among all the characteristics (fig. 26). Therefore, nutrient concentrations by themselves explained only a small part (about 10 percent) of the total variance in the macroinvertebrate communities. About 57 percentof the total variance could not be explained by the characteristics examined in this study, and 14 percent of the total variance could not be separated into a single category of characteristics.



## Reference Values for the Macroinvertebrate Indices

Reference values for the three macroinvertebrate indices most related to nutrient concentrations (HBI, EPTN%, and EPTTX%) were determined by examining the index values at only the sites having both P and N concentrations at or below their respective reference concentrations. The median HBI value for the Reference sites was 3.1 (with a 75th-percentile value of 4.4), which was significantly less than the median value at the High (nonreference) sites (5.1; fig. 27). The median reference EPTN% and EPTTX%values were 60 and 50 percent, respectively (with 25thpercentile values of 51 and 38 percent, respectively; lower percentiles are given for these indices because larger values represent better macroinvertebrate communities), which were significantly more than the median valuesmeasured at the High sites (33 and 31 percent, respectively). If 75 percent of the minimally impacted sites (the Reference sites) have index values at least as good as the reference condition, then the reference index values for HBI, EPTN%, and EPTTX% are 4.4, 51 percent, and 38 percent, respectively.Comparing the median index values for the Reference sites with those for the Ref N and Ref P sites may provide an indication of whether P or N is more important in the degradation of the macroinvertebrate community in streams with nutrient concentrations near reference conditions (fig. 27). For all three indices, it appears that N is the more important limiting nutrient because the median values for the Ref P sites were significantly higher (HBI) or lower (EPTN% and EPTTX%) than the median values for the Reference sites. There were no differences between median values for Reference sites and the Ref N sites. Small additions of N (Ref P) had more of an effect on the macroinvertebrate communities than small additions of P(Ref N) for sites with nutrient concentrations near reference conditions.

Nutrients Other water-quality characteristics Environmental and physical-habitat characteristics Interactions among categories 

### 22%

5% 32%

41% General categories

Figure 26. Percentages of explained variance in six macroinvertebrate index values described by nutrients, other water-quality characteristics, environmental (anthropogenic/ land-use, soil, and surficial-deposit characteristics) and physical-habitat characteristics, and interactions among categories (variance that can not be explained by a single category) for the studied wadeable streams in Wisconsin. [%, percentage of explained variance] 

### 70 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### Reference High Ref N Ref P 0 2 4 6 8 10HILSENHOFF BIOTIC INDEX



### Reference High Ref N Ref P

0 20 40 60 8 0 100PERCENTAGE OF EPT INDIVIDUALS



### Reference High Ref N Ref P

0 20 40 60 8 0 100PERCENTAGE OF EPT TAXA EXPLANATION

Outlier

Interquartile

range (IR) 75th percentile + 1.5 * IR

25th percentile – 1.5 * IR 75th percentile

25th percentile Median



### Figure 27. Hilsenhoff Biotic Index values, the percentages of individuals that were Ephemeroptera, Plecoptera, or Trichoptera, and the percentages of taxa that were Ephemeroptera, Plecoptera, or Trichoptera in Reference sites, High (nonreference) sites, and sites with only reference total nitrogen (Ref N sites) or reference total phosphorus (Ref P sites) concentrations in the st udied wadeable streams in Wisconsin. 

### Macroinvertebrate Communities 71

### The streams examined had a wide range in fish communities. Eight indices were used to describe the fish communities (table 10 on page 50). Fish Index of Biotic Integrity (IBI) values ranged from 0.0 to 100.0 (median = 40.0). The percentages of fish considered carnivores (CARN%) and insectivores (INSECT%) ranged from 0.0 to 100.0 percent (median = 1.6 and 48.9 percent, respectively). The percentages of fish considered omnivores (OMNI%) ranged from 0.0 to 81.1 percent (median = 10.5 percent). The percentages of fish considered pollution intolerant (INTOL%) ranged from 0.0 to 97.9 percent (median = 3.3 percent), and the percentage of fish considered pollution tolerant (TOL%) ranged from 0.0 to 100.0 percent (median = 42.8 percent). The number of fish caught (FISHN) ranged from 7 to 2,147 fish (median = 130). The number of species of fish caught (FISHSPEC) ranged from 1 to 33 species (median = 11). Streams in the northern and central parts of the State generally had higher IBI, INTOL%, and CARN% than streams in other parts of the State (fig. 28). The INSECT%, OMNI%, TOL%, FISHN, and FISHSPEC did not exhibit strong regional patterns. 

## Relations with Individual Characteristics
Correlations
Spearman rank correlation coefficients between theeight fish indices and median water-quality, environmental, and physical-habitat characteristics are shown in table 18. All eight indices were significantly correlated with at least one nutrient constituent. IBI, CARN%, and INTOL% values were most strongly correlated with most nutrients.OMNI% and TOL% values were also significantly correlated with some nutrients, but less strongly correlated than these three indices. The other three indices (INSECT%, FISHSPEC, and FISHN) were significantly correlated with only NH 4 

### -N, TKN, or DP. In general, the fish indices indicative of better conditions (higher IBI, CARN%,INTOL% values) occurred with lower nutrient concentrations. Concentrations of NO 3 

### -N were significantly correlated with the smallest number of fish indices. Individual monthly nutrient concentrations were also examined, but in all cases explained less variance than the median values. In general, IBI, CARN%, INTOL%, OMNI%, and FISHAB were the indices most strongly correlated with 

# Fish Communities and Their Relations with Water-Quality, Environmental, and Physical-Habitat Characteristics 72 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Wisconsin Department of Natural Resources personnel collecting fish with electrofishing gear. Fish pictures provided by Michael Miller and John Lyons (Wisconsin Department of Natural Resources).0 – 25 26 – 35 36 – 45 46 – 60 61 – 100

0 0.1 – 2.4 2.5 – 8 .7 8

. 8 – 23.1 23.2 – 97.9 0 0.1 – 1.4 1.5 – 5.2 5.3 – 19.3 19.4 – 100

6 – 45 46 – 93 94 – 170 171 – 2 88 2 8 9 – 2,147 Index values Percentages

Number of fish Percentages 

### Fish Index of Biotic Integrity (IBI) Percentage of carnivorous fish (CARN%)

Number of fish caught

(FISHN) Percentage of intolerant fish

(INTOL%)

Figure 28. Distributions (quintiles) of fish Index of Biotic Integrity (IBI) values, the percentages of the fish that are carnivorous (CARN%), the percentages of fish considered pollution intolerant (INTOL%), and the number of fish caught (FISHN) for the studie d wadeable streams in Wisconsin. 

### Fish Communities 73

### Table 18. Spearman rank correlation coefficients (r
s 

### ) between fish-community indices and median water-quality, environmental (anthropogenic/land-use, basin, soil, and surficial-deposit), and physical-habitat characteristics for the studied wadeable str eams in Wisconsin.

[all bold values were significant at p < 0.05, after being adjusted for the Bonferroni correction (Zar, 1999); see table 10 on page 49 f or definitions of abbreviations and units for each parameter]

Characteristic Fish Index of Biotic Integrity Percentage of carnivores Percentage of insectivores Percentage of omnivores Percentageof intolerant species Percentage of tolerant

species Number of fish species Number of fish
Water-quality characteristics Total phosphorus -0.33 -0.42 0.13 0.23 -0.36 0.24 0.12 0.18 Dissolved phosphorus -.29 -.41 .09 .21 -.36 .22 .12 .23 Total nitrogen -.31 -.29 .09 .26 -.31 .08 -.07 .14 Dissolved nitrate plus

nitrite -.20 -.14 -.04 .27 -.17 -.04 -.10 .12

Dissolved ammonia -.27 -.46 .23 .16 -.39 .29 .04 .16 Total Kjeldahl nitrogen -.25 -.43 .29 .11 -.40 .36 .24 .08 Suspended chlorophyll a -.04 -.28 .18 .26 -.20 .03 .33 .15 Secchi tube depth .32 .36 -.11 -.29 .38 -.17 -.05 .01 Anthropogenic/land-use characteristics
Urban .03 .10 .13 .15 .04 -.05 .12 -.17 Agriculture (row crops) -.25 -.37 .13 .26 -.41 .13 .03 .22 Agriculture (all) -.26 -.36 .09 .29 -.37 .09 .04 .27 Grassland .06 .00 -.02 .07 .09 -.03 -.07 -.01 Wetland (open) .14 -.09 .30 .05 .00 .06 .34 -.08 Wetland (forested) .13 .04 .19 -.22 .05 .12 .16 -.21 Forest (all) .28 .39 -.11 -.31 .40 -.13 -.05 -.24 Point-source loading of

phosphorus .09 .16 .05 .21 .11 -.11 .30 -.23

Basin characteristics
Watershed area .26 .34 .08 .24 .25 -.25 .47 -.20 Air temperature -.32 -.30 .04 .35 -.42 .15 -.05 .25 Precipitation -.15 -.06 -.17 .20 -.12 .02 -.05 .14
Runoff .26 .26 -.11 -.28 .37 -.16 .04 -.17 Basin slope -.12 .05 -.22 .10 -.01 -.04 -.18 .12 Unit area flow .07 .08 -.06 -.09 .20 .03 -.02 .02 

### 74 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in WisconsinCharacteristic Fish Index of Biotic Integrity Percentage of carnivores Percentage of insectivores Percentage of omnivores Percentageof intolerant species Percentage of tolerant

species Number of fish species Number of fish
Soil and surficial-deposit characteristics Clay content -.27 -.25 -.02 .26 -.33 .09 -.05 .23 Erodibility -.28 -.35 -.05 .28 -.35 .10 .07 .38 Organic-matter content .16 .12 .18 -.18 .04 .05 .10 -.25 Permeability .26 .27 .11 -.20 .26 -.10 .01 -.29 Soil slope .05 .30 -.22 -.02 .24 -.16 -.16 -.03 Nonglacial deposits -.13 .04 -.16 .20 .00 -.12 -.07 .13 Clay deposits -.02 .01 .12 .05 -.14 -.02 .09 -.07 Loam deposits .09 .02 .12 -.14 .18 -.07 .13 -.18 Peat deposits .05 .03 .18 .00 .06 -.11 .15 -.12 Sand deposits .12 -.04 .05 -.14 .04 .02 .03 -.02 Sand-and-gravel deposits .21 .19 .09 -.03 .11 -.01 .11 -.26 Physical-habitat characteristics
WIDTH 0.31 0.35 0.02 0.17 0.31 -0.28 0.54 -0.17 DEPTH .04 .15 .12 .32 .13 -.10 .25 -.21
THALD .08 .22 .12 .29 .18 -.15 .26 -.24 GRAD -.11 -.19 -.18 -.10 -.15 .04 -.16 .36 POOL% -.03 -.01 -.20 .03 -.05 .01 .07 .29
RIFF% .14 .00 -.17 -.07 -.01 -.11 .21 .26
RUN% -.03 .03 .24 .01 .07 .08 -.13 -.31
SEDEP -.13 .03 .12 -.01 .01 .07 -.30 -.29
SILT% -.40 -.32 .09 .18 -.39 .25 -.25 .20 SAND% .15 .27 -.05 -.15 .27 -.05 -.11 -.31 GRAV% .15 -.01 -.18 .03 .03 -.03 .39 .23
EMB% -.19 -.01 .11 -.04 -.03 .11 -.40 -.23
ALGAE% -.11 -.25 .00 .18 -.22 .05 .14 .33
MACR% -.07 .02 .08 -.04 -.03 -.02 -.10 .13 COVER% .11 .08 .12 .05 .07 .01 .02 -.10 SHADE% .01 .03 -.13 -.08 .02 .03 -.06 -.10 EROSION% -.11 -.06 -.16 .12 -.04 .03 .10 .01 BUFFER .07 .07 .12 -.08 .03 -.06 .07 -.23 

### Table 18. Spearman rank correlation coefficients (r
s 

### ) between fish-community indices and median water-quality, environmental (anthropogenic/land-use, basin, soil, and surficial-deposit), and physical-habitat characteristics for the studied wadeable str eams in Wisconsin—Continued.

[all bold values were significant at p < 0.05, after being adjusted for the Bonferroni correction (Zar, 1999); see table 10 on page 49 f or definitions of abbreviations and units for each parameter] 

### Fish Communities 75

### SCHL, SD, and the anthropogenic/land-use characteristics than were the other indices. These fish indices were most strongly correlated with the percentage of total agriculture, row-crop agriculture, and forested areas. Better fish indices (high IBI, CARN%, and INTOL% values) occurred with lower percentages of agriculture and higher percentages of forest. INSECT%, TOL%, and FISHSPEC were lessstrongly correlated with most of the anthropogenic/landuse characteristics than were IBI, CARN%, and INTOL%. IBI, CARN%, OMNI%, and INTOL% were more strongly correlated with several basin characteristics (watershed area, air temperature, and runoff) and soil characteristics (clay content, erodibility, permeability, and soil slope) than were INSECT%, TOL%, and FISHSPEC. In general, streams with better fish indices have larger drainage areas, cooler air temperatures, higher runoff, and soils with lower clay content, lower erodibility, and higher permeability. These areas with better fish indices, again, are generally the mixed and mostly forested areas of Wisconsin (fig. 2A). In general, most fish indices were significantly correlated with only a few physical-habitat characteristicsexcept for FISHSPEC and FISHN, which were significantly correlated with many of the characteristics. The physical-habitat characteristics most strongly correlated with fish indices were stream width and the percentage of silt in the bottom sediments. Better fish communities occurred in wider streams with lower percentages of silt in the sediments. More fish and more fish species were caught in streams with higher percentages of pools and riffles, gravel bottoms having less accumulated sediment(shallower sediment depths), lower percentages of rockysubstrate embeddedness, and a higher percentage of algalcover. More fish but fewer fish species were caught in narrower, shallower streams with steeper gradients.


## Responses to Changes in Nutrient Concentrations
Responses of the three fish-community indices most strongly correlated with nutrient concentrations (IBI, CARN%, and INTOL%) are shown in figures 29 and 30. In general, IBI, CARN%, and INTOL% values decrease with increases in P and DP concentrations; however, no consistent pattern is apparent in the relations of these indices to changes in concentrations of the N constituents, except for NH 4 

### -N. At low total P, DP, and NH 4 

### -N concentrations, the values of these fish indices ranged widely; however, at high nutrient concentrations, the values were generally indicative of poor water quality (low values). The upper bounds of the IBI, CARN%, and INTOL% plots may provide an indication of how P, DP, and NH 4 

### -N are capable of affecting the fish community. As was true for the other biotic indices, the variability below these boundsmay be indicative of the effects of factors other than nutrients. Relations between selected fish indices and nutrient concentrations appear to be similar in the various EPZs and ecoregions (fig. 29). In all areas, there was a broad response at low nutrient concentrations and lower indices(generally indicative of poor water quality) at high nutrient (P, DP, and NH 4 

### -N) concentrations. As for the other biotic indices, no significant differences in the responses were found among areas because of the range in the data, and because the gradient in nutrient concentrations within some areas was small. Regression-tree analyses were done to define specific thresholds or breakpoints in the responses of the three fish-community indices that were most strongly correlated with the nutrient concentrations (table 19). The thresholds or breakpoints in the responses to changes in nutrient concentrations were consistent among these three indices.The thresholds in the responses to changes in P concentrations were about 0.06 mg/L, to changes in DP concentrations were from about 0.04 to 0.07 mg/L, and to changes in NH 4 

### -N concentrations thresholds were about 0.02–0.03 mg/L. In general, below these thresholds the fish indices ranged widely, but were consistently poor above these thresholds. The regression-tree analyses defined specific thresholds for N, TKN, and NO 3 

### -N; however, the data in figures 29 and 30 do not indicate any change in the indices with changes in the concentrations of these constituents. 

## Effects of Multiple Characteristics on Fish Indices Stepwise Regressions
Forward stepwise regressions were done with the median water-quality, environmental, and physical-habitat characteristics to determine which four characteristics best described the variance in the fish indices (table 20). Models with more than four variables did not significantly increase the amount of variance explained. For most indices, either P or TKN concentration was the first variable incorporated in these models. If TKN concentrations were not included in these models, then P concentrations became the first variable in the models. Other important variables included the width and depth of the streams and characteristics describing the substrate of the stream bottom. As was 76 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin0.055 mg/L0.055 mg/L0.055 mg/L0.055 mg/L0.539 mg/L0.539 mg/L0.539 mg/L0.067 mg/L

1.641 mg/L 1.641 mg/L 1.641 mg/L 1.641 mg/L 1.641 mg/L 1.641 mg/L 21.260 mg/L 21.260 mg/L 21.260 mg/L 21.260 mg/L 21.260 mg/L 21.260 mg/L0.067 mg/L0.539 mg/L0.539 mg/L0.539 mg/LFish Index of Biotic Integrity Fish Index of Biotic Integrity Fish Index of Biotic Integrity Fish Index of Biotic Integrity01020304050607080901000.0 0.2 0.4 0.6 0.81.0MEDIAN TOTAL PHOSPHORUS,IN MILLIGRAMS PER LITER

FISH INDEX OF BIOTIC INTEGRITYPercentage of carnivorous fish01020304050607080901000.0 0.2 0.4 0.6 0.81.0MEDIAN TOTAL PHOSPHORUS,IN MILLIGRAMS PER LITER

PERCENTAGE OF CARNIVOROUS FISHPercentage of intolerant fish01020304050607080901000.0 0.2 0.4 0.6 0.81.0MEDIAN TOTAL PHOSPHORUS,IN MILLIGRAMS PER LITER

PERCENTAGE OF INTOLERANT FISH01020304050607080901000 5 10 15MEDIAN TOTAL NITROGEN,IN MILLIGRAMS PER LITERPercentage of carnivorous fish01020304050607080901000 5 10 15MEDIAN TOTAL NITROGEN,IN MILLIGRAMS PER LITERPercentage of intolerant fish01020304050607080901000 5 10 15MEDIAN TOTAL NITROGEN,IN MILLIGRAMS PER LITER01020304050607080901000.0 0.2 0.4 0.6 0.81.0MEDIAN TOTAL PHOSPHORUS,IN MILLIGRAMS PER LITERPercentage of carnivorous fish01020304050607080901000.0 0.2 0.4 0.6 0.81.0MEDIAN TOTAL PHOSPHORUS,IN MILLIGRAMS PER LITERPercentage of intolerant fish01020304050607080901000.0 0.2 0.4 0.6 0.81.0MEDIAN TOTAL PHOSPHORUS,IN MILLIGRAMS PER LITER01020304050607080901000 5 10 15MEDIAN TOTAL NITROGEN,IN MILLIGRAMS PER LITERPercentage of carnivorous fish01020304050607080901000 5 10 15MEDIAN TOTAL NITROGEN,IN MILLIGRAMS PER LITERPercentage of intolerant fish01020304050607080901000 5 10 15MEDIAN TOTAL NITROGEN,IN MILLIGRAMS PER LITEREPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5DFANCHFNLFSWTPDFANCHFNLFSWTPDFANCHFNLFSWTPEPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5DFANCHFNLFSWTPDFANCHFNLFSWTPDFANCHFNLFSWTPFigure 29.Fish Index of Biotic Integrity values, the percentages of fish considered pollution intolerant, and the percentages of the fish that are carnivorous as a function of totalphosphorus and total nitrogen concentration in the environmental phosphorus zones (EPZs) and level III ecoregions for the studied wadeable streams in Wisconsin. Computedthresholds in the response are identified by vertical lines. [DFA, Driftless Area; NCHF, North Central Hardwood Forests; NLF, Northern Lakes and Forests; and SWTP, SoutheasternWisconsin Till Plains] 

### Fish Communities 770.068 mg/L3.455 mg/L

1.460 mg/L 1.460 mg/L 1.460 mg/L 20.550 mg/L 20.550 mg/L 20.550 mg/L0.017 mg/L0.408 mg/L0.413 mg/L0.018 mg/L0.095 mg/L0.041 mg/L0.040 mg/L4.693 mg/L0.032 mg/L0.413 mg/LFish Index of Biotic Integrity Fish Index of Biotic IntegrityFish Index of Biotic IntegrityFish Index of Biotic Integrity01020304050607080901000.0 0.2 0.4 0.6 0.81.0MEDIAN DISSOLVED PHOSPHORUS,IN MILLIGRAMS PER LITER

FISH INDEX OF BIOTIC INTEGRITY01020304050607080901000 5 10 15MEDIAN DISSOLVED NITRITE PLUS NITRATE,IN MILLIGRAMS PER LITER01020304050607080900.0 0.1 0.2 0.3 0.4 0.5MEDIAN DISSOLVED AMMONIA,IN MILLIGRAMS PER LITER0102030405060708090010203040506070809010001020304050607080901000102030405060708090100010203040506070809010001020304050607080901000102030405060708090100010203040506070809010001020304050607080901000.0 0.5 1.0 1.5 2.0 2.5MEDIAN TOTAL KJELDAHL NITROGEN,IN MILLIGRAMS PER LITERMEDIAN DISSOLVED PHOSPHORUS,IN MILLIGRAMS PER LITERMEDIAN DISSOLVED NITRITE PLUS NITRATE,IN MILLIGRAMS PER LITERMEDIAN DISSOLVED AMMONIA,IN MILLIGRAMS PER LITERMEDIAN TOTAL KJELDAHL NITROGEN,IN MILLIGRAMS PER LITERMEDIAN DISSOLVED PHOSPHORUS,IN MILLIGRAMS PER LITERMEDIAN DISSOLVED NITRITE PLUS NITRATE,IN MILLIGRAMS PER LITERMEDIAN DISSOLVED AMMONIA,IN MILLIGRAMS PER LITERMEDIAN TOTAL KJELDAHL NITROGEN,IN MILLIGRAMS PER LITERPercentage of carnivorous fish0.0 0.2 0.4 0.6 0.81.0

PERCENTAGE OF CARNIVOROUS FISHPercentage of intolerant fish0.0 0.2 0.4 0.6 0.81.0

PERCENTAGE OF INTOLERANT FISHPercentage of carnivorous fish0 5 10 15Percentage of intolerant fish0 5 10 15Percentage of carnivorous fish0.0 0.1 0.2 0.3 0.4 0.5Percentage of intolerant fish0.0 0.1 0.2 0.3 0.4 0.5Percentage of carnivorous fish0.0 0.5 1.0 1.5 2.0 2.5Percentage of intolerant fish0.0 0.5 1.0 1.5 2.0 2.5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5EPZ 1EPZ 2EPZ 3EPZ 4EPZ 5Figure 30.Fish Index of Biotic Integrity values, the percentages of fish considered pollution intolerant, and the percentages of the fish that are carnivorous as a function ofdissolved phosphorus, dissolved nitrite plus nitrate, dissolved ammonia, and total Kjeldahl nitrogen concentrations in the environmental phosphorus zones (EPZs) for the studiedwadeable streams in Wisconsin. Computed thresholds in the response are identified by vertical lines. 

### 78 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### Table 19. Thresholds or breakpoints in the responses in fish indices to changes in nutrient concentrations for wadeable streams in Wisconsin.
[all concentrations are in milligrams per liter]

Biological Indices Total Phosphorus Dissolved phosphorus Total nitrogen Dissolved nitrite plus nitrate Dissolved ammonia Total Kjeldahl nitrogen
Fish Index of Biotic

Integrity (IBI) 0.055 0.068 0.539 3.455 0.017 0.408

Percentage of carnivorous

fish (CARN%) .055 .041 .539 .095 .018 .413

Percentage of intolerant

fish (INTOL%) .067 .040 .539 4.693 .032 .413



### Table 20. Results of forward stepwise-regression analyses to explain variance in fish indices for the studied wadeable streams in Wisconsin.

[R 2 , coefficient of determination for the one-, two-, three-, and four-variable models; log, logarithm to base 10 transformation]

Dependent variable First variable Second variable Third variable Fourth variable Fish Index of Biotic Integrity

(IBI) Total phosphorus Stream width Percentage of silt Wetland (forested)

Accumulative R 2 0.14 0.21 0.25 0.27 Percentage of carnivorous fish

(CARN%) Kjeldahl nitrogen Nonglacial deposits Buffer width Runoff

Accumulative R 2 .23 .29 .31 .32 Percentage of insectivorous fish

(INSECT%) Kjeldahl nitrogen Percentage of pools Percentage of gravel Stream width

Accumulative R 2 .10 .16 .18 .22 Percentage of omnivorous fish

(OMNI%) Air temperature Stream depth Buffer width Point-source loading of phosphorus Accumulative R 2 .15 .22 .27 .29 Percentage of tolerant fish

(TOL%) Kjeldahl nitrogen Stream width Flow per unit area Soil slope

Accumulative R 2 .15 .21 .23 .24 Percentage of intolerant fish

(INTOL%) Kjeldahl nitrogen Stream width Flow per unit area Soil slope

Accumulative R 2 .15 .26 .27 .29 Number of fish species

(FISHSPEC) Watershed area Percentage of gravel Kjeldahl nitrogen Buffer width

Accumulative R 2 .27 .35 .41 .42 Number of fish caught - log

(FISHN) Erodibility Thalweg depth Percentage of stream shaded Percentage of gravel

Accumulative R 2 .15 .23 .26 .30 

### Fish Communities 79

### true for many other biotic-index models, even with four variables included, the relations only explained a small part of the total variance in these indices (in this case, from 22to 42 percent). The model that explained the most variance was for FISHSPEC, which had watershed area and bottom substrate as the first two variables incorporated in the model.


## Redundancy Analysis
Partial RDA was used to determine the relative importance of the nutrients, other water-quality characteristics, and environmental and physical-habitat characteristics (tables 2 and 10) in affecting the distribution of the fishcommunities (the eight fish indices). In this analysis, individual monthly (July and August) and median values wereincluded for each nutrient constituent. A forward variableselection procedure, which correlated fish indices with the other factors, was used to select a subset of variables for each general type of characteristic. This procedure retained 8 nutrient variables, 3 other water-quality characteristics, and 20 environmental and physical-habitat characteristics.These 31 characteristics explained 44 percent of the variance in the 8 fish-community indices. Of the explained variance, 15 percent was described by the nutrients alone, 3 percent by the other water-quality characteristics alone,46 percent by the environmental and physical-habitat characteristics alone, and 36 percent by the interactions among all characteristics (fig. 31). About 56 percent of the total variance could not be explained with the characteristics examined in this study, and 16 percent of the total variancecould not be separated into a single category of characteristics.



## Reference Values for the Fish Indices

Reference values for the three fish indices that were most related to nutrient concentrations (IBI, CARN%, and INTOL%) were determined by examining the indexvalues at only the sites having both P and N concentrations at or below their respective reference concentrations. The median IBI value for the Reference sites was 50 (with a 25th percentile of 40), the median reference CARN% value was 9.9 percent (with a 25th percentile of 1.5 percent), and the median reference INTOL% value was 14.7 percent (with a 25th percentile of 2.0 percent). Lower percentiles are given because larger values represent better fish communities. These median values were significantly higher than the median values measured at the High sites (35, 0.3 percent, and 2.0 percent respectively; fig. 32). If 75 percent of the minimally impacted sites (the Reference sites) had index values at least as good as the reference condition, then the reference index values for IBI, CARN%, and INTOL% are 40, 9.9 percent, and 2.0 percent, respectively. Comparing the median index values for the Reference sites with those for the Ref N and Ref P sites may provide an indication of whether P or N is more important in thedegradation of the fish communities in streams with nutrient concentrations near reference conditions (fig. 32). For all three indices, there was no difference between median values for Reference sites and median values of the Ref N sites and Ref P sites. Therefore, small additions of P or N appear to have little effect on the fish communities instreams with nutrient concentrations near reference conditions.

Nutrients Other water-quality characteristics Environmental and physical-habitat characteristics Interactions among categories 

### 15% 3%

36%

46% General categories

Figure 31. Percentages of explained variance in eight fish index values described by nutrients, other water-quality characteristics, environmental (anthropogenic/land-use, soil, and surficial-deposit characteristics) and physical-habitat characteristics, and interactions among categories (variance that can not be explained by a single category) for the studied wadeable streams in Wisconsin. [%, percentage of explained variance] 

### 80 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### Reference High Ref N Ref P 0 20 40 60 8 0 100INDEX OF BIOTIC INTEGRITY



### Reference High Ref N Ref P

0 20 40 60 8 0 100PERCENTAGE OF INTOLERANT FISH 

### Reference High Ref N Ref P

0 20 40 60 8 0 100PERCENTAGE OF CARNIVOROUS FISH EXPLANATION

Outlier

Interquartile

range (IR) 75th percentile + 1.5 * IR

25th percentile – 1.5 * IR 75th percentile

25th percentile Median



### Figure 32. Fish Index of Biotic Integrity values, the percentages of the fish that are carnivorous, and the percentages of fish that are considered pollution intolerant in Reference sites, High (nonreference) sites, and sites with only reference total nitrogen (Ref N sites) or reference total phosphorus (Ref P sites) concentrations in the studied wadeable streams in Wisconsin. 

### Fish Communities 81

# Multiparameter Biotic Indices to Estimate Nutrient Concentrations in Wadeable Streams

One goal of this study was to estimate nutrient concentrations in streams from the biotic data. Most of the biotic indices, however, had a wedge-shaped response to increases in nutrient concentrations. In other words, there was a broad response in almost all index values at lownutrient concentrations; however, at high nutrient concentrations, the indices had a narrow range of values normally indicative of poor conditions. This wedge-shaped response of the biotic indices to increases in nutrient concentrations is common in describing relations between biotic indices and human disturbance levels, such as the percentage of urban land use in an area (Wang and others, 2001; 2003). The wedge-shaped response implies that at low nutrientconcentrations, factors other than nutrients are predominant factors limiting the health of biotic communities, whereas at high nutrient concentrations, nutrients may be the predominant factors affecting biotic communities (Cade and others, 1999). Although these relations between nutrient concentrations and biotic indices have rarely been reported for wadeable streams in the literature, relations similar to those found in this study have been reported between P concentrations and percentages of gastropods and predator macroinvertebrates in P-addition experiments in Everglades sloughs (King and Richardson, 2004). The wedge-shaped distribution makes predictions of low nutrient concentrations difficult with any single index. A combination of various biotic indices was used to assess whether this wedge-shaped response could be eliminated or at least reduced. To develop multiparameter indices to estimate P and N concentrations in wadeable streams, each of the indices found to be strongly related to changes in thenutrient concentrations was input into forward stepwiseregression analyses. Eleven biotic indices were included in this analysis: two describing chlorophyll a concentrations in the streams (log SCHL and log BCHL), three describing the periphytic-diatom community (DNI, DPTI, and DSI), three describing the macroinvertebrate community (HBI, EPTN%, and EPTTX%), and three describing the fish community (IBI, INTOL%, and CARN%).The four-parameter model to estimate P concentrations in wadeable streams included indices describing the diatom community (DSI and DNI), suspended chlorophyll

a (SCHL), and the fish community (IBI), and explained 54 percent of the variance in P concentrations (table 21). Models with more than four variables did not significantly increase the amount of variance explained (accumulative R 2 

### value). Measured and estimated log P concentrationsare shown in figure 33A. This multiparameter model estimated high and low P concentrations equally well.The four-parameter model to estimate N concentrations included indices describing benthic chlorophyll a(BCHL), the diatom community (DNI), the macroinvertebrate community (EPTTX%), and the fish community

Table 21. Results of forward stepwise-regression analyses to explain variance in total phosphorus and total nitrogen concentrations with biotic indices in the studied wadeable streams in Wisconsin.
[log, logarithm to base 10 transformation; r
s , Spearman correlation coefficient; R 2 , coefficient of determination for the one-, two-, three-, and four-variable models; SCHL, suspended chlorophyll a concentration; na, not applicable; all regressions were on log-transformed concentrations; see table 10 on page 49 for definitions of abbreviations and units for each parameter]

Statistical parameter Constant First variable Second variable Third variable Fourth variable Total phosphorus (P) Diatom DSI Log (SCHL) Diatom DNI Fish IBI Coefficient in equation -1.797 0.005 0.300 0.140 -0.004

r s na .60 .44 .47 -.33 Accumulative R 2 na .32 .41 .48 .54 Total nitrogen (N) Log (BCHL) EPTTX% Fish IBI Diatom DNI Coefficient in equation -0.373 .200 -.007 -.005 .108

r s na .49 -.39 -.31 .36 Accumulative R 2 na .23 .33 .37 .41 

### 82 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsiny = 0.20x - 0.90R2= 0.41y = 0.25x - 2.25R2= 0.54y = 0.54x - 0.52R2= 0.54y = 0.41x + 0.15R2= 0.41

ESTIMATED LOG (TOTAL NITROGEN, IN MILLIGRAMS PER LITER) MEASURED LOG (TOTAL NITROGEN, IN MILLIGRAMS PER LITER)-1.0-0.50.00.51.0-1.0 -0.5 0.0 0.5 1.0 1.5MEASURED LOG (TOTAL NITROGEN,IN MILLIGRAMS PER LITER)-1.0-0.50.00.51.01.50246810BIOTIC INDEX OF TOTAL NITROGEN (BIN)-2.0-1.5-1.0-0.50.0-2.0 -1.5 -1.0 -0.5 0.0 0.5MEASURED LOG (TOTAL PHOSPHORUS,IN MILLIGRAMS PER LITER)

ESTIMATED LOG ( TOTAL PHOSPHORUS, IN MILLIGRAMS PER LITER) MEASURED LOG (TOTAL PHOSPHORUS, IN MILLIGRAMS PER LITER)-2.5-2.0-1.5-1.0-0.50.00.50246810BIOTIC INDEX OF TOTAL PHOSPHORUS (BIP)C. D.A. B.Figure 33.Measured and estimatedA, total phosphorus andB, total nitrogen concentrations (logarithm to base 10 transformation) for the four-parameter regression models,C, measured phosphorus concentrations as a function of Biotic Index of total Phosphorus (BIP) values, andD, measured nitrogen concentrations as a function of Biotic Index oftotal Nitrogen (BIN) values, with the regression equations and coefficients of determination (R2) for the studied wadeable streams in Wisconsin. 

### Multiparameter Biotic Indices to Estimate Nutrient Concentrations in Wadeable Streams 83

### (IBI). This model explained 41 percent of the variance in N concentrations (table 21). Models with more than fourvariables did not significantly increase the amount of variance explained. Measured and estimated log N concentrations are shown in figure 33B. This multiparameter model estimated high and low N concentrations equally well, but did not estimate N concentrations as well as the P model estimated P concentrations. The regression equations described in table 21 were then used to develop multiparameter biotic indices to estimate P and N concentrations in wadeable streams. The indices were developed to provide values ranging from 1 to 10, with 1 representing the lowest P and N concentrations and 10 representing the highest concentrations.

The Biotic Index of total P (BIP) is computed as:

BIP = 4.0(-1.797 + 0.005DSI + 0.300Log SCHL + 0.140DNI – 0.004IBI) + 9.0 (12)

The Biotic Index of total N (BIN) is computed as:

BIN = 5.0(-0.373 + 0.200LogBCHL – 0.007EPTTX% – 0.005 IBI + 0.108 DNI) + 4.5 (13)

The BIP and BIN values are plotted against their respective measured P and N concentrations in figures 33Cand D. Both BIP and BIN estimate median P and N concentrations equally well over the range of concentrations measured in this study. The BIP predicted P concentrations better than the BIN predicted N concentrations (54 percent of the variance in P concentrations compared to 41 percent of the variance in N concentrations). The difference in the predictability of these indices was consistent with most of the biotic indices being more strongly correlated with P concentrations than with N concentrations. This difference in predictability suggests that P concentrations are more important than N concentrations in affecting the biotic communities over the range in nutrient concentrations measured in this study.


# Summary and Conclusions

Excessive nutrient loss from watersheds is frequently associated with degraded water quality in streams. Toreduce this loss from agricultural areas, performance standards and regulations for croplands and livestock operations are being proposed by various States. In addition, the USEPA is establishing regionally based nutrient criteria that can be refined by each State to determine whether actions are needed to improve a stream’s water quality. More confidence in the environmental benefits of the proposed standards and nutrient criteria are possible with a better understanding of the biotic responses to a range of nutrient concentrations in different environmental settings.To provide the information needed to guide the development of regionally based nutrient criteria for Wisconsinstreams, the USGS and WDNR collected water-quality and biotic data in 240 wadeable streams throughout Wisconsin to: 1) describe how nutrient concentrations and biotic-community structure vary throughout the State; 2) determine which environmental characteristics are moststrongly related to the distribution of nutrient concentrations; 3) determine reference water-quality and biotic conditions for different areas of the State; 4) determine how the biotic community of streams in different areas of the State respond to changes in nutrient concentrations; 5) determine the best regionalization scheme to describe the patterns in reference conditions and the responses in water quality and the biotic community; and 6) develop new indices to estimate nutrient concentrations in streams from a combination of biotic indices.


## Final Regionalization Scheme for Wisconsin Streams

Two regionalization schemes were proposed for defining nutrient criteria for Wisconsin’s wadeablestreams: level III ecoregions and environmental phosphorus zones (EPZs). On the basis of the results of this study, the EPZ regionalization scheme was better than the level III ecoregion scheme at defining differences in reference water quality and differences in the responses in water quality to changes in land use for constituents that variedregionally. For some water-quality characteristics, however, the results indicated that little consistent variability was present and no regionalization was warranted. For total nitrogen (N) concentrations, suspended chlorophyll a(SCHL) and Secchi tube depth (SD), the regional variabilities in reference conditions and in the water-quality responses are best described by subdividing wadeable streams into two categories: streams in areas with high clay-content soils (EPZ 3) and streams throughout the rest of the State (fig. 34). The regional variability in the response in total phosphorus (P) concentrations to changes in land use was also best described by subdividing thestreams into these two categories; however, little consistent variability was found in reference P concentrations in streams throughout the State. 84 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

## Proposed regionalization scheme for wadeable streams in Wisconsin

EXPLANATION Areas without high clay-content soils Areas with high clay-content soils 44° 45°

43° 46° 92° 91°

90°

8 9°

88 °

8 7°

0 0 20 40 60 KILOMETERS

20 40 60 MILES



### Figure 34. Proposed regionalization scheme for defining nutrient criteria for wadeable streams in Wisconsin. 

### Summary and Conclusions 85

### Despite variation in nutrient concentrations amongEPZs and level III ecoregions (especially lower nutrient concentrations in the northern part of the State), theresponses of all of the biotic indices to changes in nutrient concentrations were similar throughout the State. In all areas, there was a broad response in the indices at low nutrient concentrations and a narrower range in values,indicative of poor water quality, at high nutrient concentrations. No regional differences were found in the biotic responses among areas; therefore, there is no reason to subdivide the streams based on the biotic response to changes in nutrient concentrations.



## Reference Conditions

Results of this study indicate that reference P concentrations for wadeable streams are similar throughout the State: 0.03–0.04 mg/L with an upper 95-percent confidence limit of 0.04–0.06 mg/L (table 22). These values are higher than those estimated by Robertson and others (2006), who estimated that reference P concentrations for Wisconsin streams and larger rivers were between 0.012 and 0.023 mg/L. Values from this study are similar to those defined by the USEPA for nutrient ecoregion 7, but higher than those defined for nutrient ecoregion 8. The USEPA definedreference P concentrations for the DFA and SWTP ecoregions at 0.070 and 0.080 mg/L, respectively, which are higher than those estimated in this study. The higher values defined for the DFA and SWTP ecoregions were probably because most of the watersheds of streams in those areas are dominated by agriculture, and more than 25 percent of the streams are affected by anthropogenic factors. Reference N concentrations can be subdivided into two categories: 0.6–0.7 mg/L with the upper 95-percent confidence limit of 0.7–1.0 mg/L in all streams except those in areas with high clay-content soils, where 0.4 mg/L and an upper 95-percent confidence limit of 0.6 mg/L are more appropriate (table 22). These values are also similar to those defined by the USEPA for nutrient ecoregion 7 (0.54 mg/L), but higher than those defined for nutrientecoregion 8 (0.20–0.38 mg/L). The USEPA defined reference N concentrations for the DFA and SWTP ecoregionsto be 1.30–1.88 mg/L, which are higher than those estimated in this study, probably because most of the streams in these areas are dominated by agriculture. Reference SCHL concentrations can be subdividedinto two categories: 1.2–1.7 μg/L with the upper 95-percent confidence limit of 1.7–2.2 μg/L in all streams except those in areas with high clay-content soils, where 1.0 μg/L and upper 95-percent confidence limit of 1.6 μg/L are more appropriate (table 22). These values are less than those defined by the USEPA for nutrient ecoregions 7 and 8 when the trichromatic method of analysis is used (5.8 and 4.3 μg/L, respectively). Reference water clarity can be subdivided into two categories: streams in areas with high clay-content soils (EPZ 3) with poorer reference water clarity (a SD of about 110 cm), and streams throughout the rest of the State with better water clarity (SD greater than 115 cm; table 22). In all areas of the State, the upper 95-percent confidence limit for reference water clarity was better than could be measured with the 120-cm Secchi tube used in this study. It is likely that the poorer clarity in the streams in areas with high clay-content soils is caused by colloidal clay particles, which often remain in suspension. Reference SDs are not directly comparable with values defined by the USEPA for turbidity. For each category of the biotic community (SCHL, BCHL, periphytic diatoms, macroinvertebrates, and fish),the indices most related to changes in nutrient concentrations are listed in table 22. The three diatom indices (Diatom Nutrient Index (DNI), Diatom Siltation Index (DSI), and Diatom Biotic Index (DBI)) displayed the strongest responses to changes in nutrient concentrations. The three macroinvertebrate indices that displayed the strongest responses to changes in nutrient concentrations were theHilsenhoff Biotic Index (HBI), the percentage of individuals that were Ephemeroptera, Plecoptera, or Trichoptera(EPTN%), and the percentage of taxa that were Ephemeroptera, Plecoptera, or Trichoptera (EPTTX%). The three fish indices that displayed the strongest responses to changes in nutrient concentrations were the fish Index of Biotic Integrity (IBI), the percentage of carnivorous fish (CARN%), and the percentage of fish that are considered pollution intolerant (INTOL%). Values of each of these indices ranged widely when nutrient concentrations wereat or below the reference concentrations, but were significantly different from the respective values for streams with nutrient concentrations significantly higher than reference conditions. The median values of the biotic indices at the Reference sites (sites with nutrient concentrations at or below reference concentrations) are given in table 22. It has been suggested that the upper 75th percentile for the concentration data for a subset of streams thought to be minimally impacted for a defined area may represent the reference conditions. This upper 75th percentile assumes that high values are indicative of poor conditions. For some biotic indices, however, lower values are indicative of poor conditions; therefore, the values for each biotic index at the worst 75th percentile of the subset of streams 86 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### Table 22. Reference conditions for water quality, chlorophyll a , diatoms, macroinvertebrates, and fish indices for wadeable streams in Wisconsin.
[EPT, Ephemeroptera, Plecoptera, and Trichoptera; %, percent; mg/L, milligram per liter; μg/L, microgram per liter; cm, centime ter; >, greater than; mg/m 2 , milligram per square meter]

Median reference Upper 95-percent confidence limits

Total phosphorus (P) (mg/L)
Entire State 0.03–0.04 0.04–0.06 Total nitrogen (N) (mg/L) High-clay content areas (EPZ 3) 0.4 0.6 Rest of State 0.6–0.7 0.7–1.0 Suspended chlorophyll a (SCHL)(μg/L) High-clay content areas (EPZ 3) 1.0 1.6 Rest of State 1.2–1.7 1.7–2.2 Secchi tube depth (SD)(cm) High-clay content areas (EPZ 3) 110 > 120 Rest of State >115 > 120

Median reference 1 Worst 75th percentile of sites with reference nutrient concentrations Benthic Chlorophyll a (BCHL)(mg/m 2 ) 331 673 Diatoms Diatom nutrient index (DNI) 3.4 4.1 Diatom siltation index (DSI) 11.8 22.5 Diaton biotic index (DBI) 47.5 37.4 Macroinvertebrates Hilsenhoff Biotic Index (HBI) 3.1 4.4 Percentage of EPT individuals (EPTN%) 59.7 50.7 Percentage of EPT taxa (EPTTX%) 50.0 38.0 Fish Fish Index of Biotic Integrity (IBI) 50.0 40.0 Percentage of carnivorous fish (CARN%) 9.9 1.5 Percentage of intolerant fish (INTOL%) 14.7 2.0

1 Lower values of the indices are not always indicative of better biotic conditions; therefore, the values at the worst (or poore r) 75th percentiles of a subset of minimally impacted streams are given. 

### Summary and Conclusions 87

### thought to be minimally impacted would represent the reference condition. The values of each of the biotic indices at the worst 75th percentile for the minimally impacted streams are given in table 22. 

## Responses of Water Quality to Changes in Land Use

Concentrations of P and N in streams throughout theState increase at different rates as the percentage of agricultural land increases. Concentrations of P increase more quickly and concentrations of N increase more slowly in response to increasing percentages of agriculture in areaswith high clay-content soils than do P and N concentrations in streams in the rest of the State. The response of water clarity to changes in nutrient concentrations is similar in streams throughout the State. The streams in areas with high clay-content soils, however, have a lower reference water clarity, and their clarity remains lower than that in streams from other areas with similar nutrient concentrations as the percentage of agriculture increases. 

## Responses of Biotic Indices to Changes in Nutrient Concentrations

The responses of biotic indices to changes in nutrientconcentrations were examined when nutrient concentrations were at or near reference concentrations and thus hadpotential to limit biotic growth, and as nutrient concentrations increase. Comparison of the median index values for Reference sites with those for sites with P concentrations at or below reference conditions, but with N concentrations above reference conditions and with those of sites with N concentrations at or below the reference conditions, but with P concentrations above reference conditions provided an indication of whether P or N was more important in affecting the biota. For SCHL, P was the more importantlimiting nutrient, whereas for BCHL and all of the macroinvertebrate indices, N was the more important limiting nutrient. For other diatom indices and all fish indices, therewere no differences between the median values for Reference sites and those of the other two categories of sites; therefore, small additions of P or N appear to have littleeffect on these communities in streams with nutrient concentrations near reference conditions. At the start of this study, it was thought that the biota in streams were more affected by P than N concentrations; however, these results suggest that in streams with low nutrient concentrations, N may be at least as important as P in affecting BCHL concentrations and the macroinvertebrate communities.Changes in the biotic indices as nutrient concentrations increase indicate that nutrients have direct or indirect effects on the composition of the biotic community inWisconsin’s wadeable streams. Visual inspection of scatterplots and results of Spearman correlations and multiple linear regressions indicate that as nutrient concentrations increase above reference conditions, changes in the biotic community are more strongly related to changes in P concentrations than to changes in N concentrations. The relations between nutrient concentrations and most biotic indices were found to be nonlinear. The biotic integrity ofwadeable streams was negatively correlated with increasing nutrient concentrations, and the effects on the bioticcommunity were largest at relatively low nutrient concentrations. From the data collected in this study, nutrient-concentration thresholds were identified where a small change in nutrient concentrations corresponds to a relatively large change in the biotic communities. A summary of the nutrient thresholds is given in table 23. The thresholds in the responses to changes in P concentrations ranged from 0.039 mg/L for BCHL, to about 0.06–0.07 mg/L for SCHL, diatom indices, and fish indices, to about 0.09–0.10mg/L for macroinvertebrate indices and SD. The thresholds in the responses to changes in N constituents were more variable than for P concentrations. The thresholds in the responses to changes in N concentrations ranged fromabout 0.5–0.6 mg/L for the fish indices and one macroinvertebrate index, to about 0.9–1.2 for SCHL, the diatom indices, and the other macroinvertebrate indices, to about 3.3 mg/L for SD. The thresholds for most of the bioticresponses were not much above the reference concentrations estimated for P and N throughout the State. Most of the biotic indices had a wedge-shaped response to increases in nutrient concentrations. In other words, there was a broad response in almost all index values at low nutrient concentrations; however, at high nutrient concentrations, the indices had a narrow range ofvalues normally indicative of poor water-quality conditions. This wedge-shaped response of the biotic indices toincreases in nutrient concentrations is common in describing relations between biotic indices and human disturbance levels. The wedge-shaped response implies that at low nutrient concentrations, factors other than nutrients arepredominant factors limiting the health of biotic communities, whereas at high nutrient concentrations, nutrients may be the predominant factors affecting biotic communities. 88 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

### Although there were significant correlations and visual relations between the nutrient concentrations and the characteristics of biotic communities, this may or may not be an indication of cause-and-effect relations. The biotic communities that are present in a stream reflect the overall ecological integrity (in other words, physical, chemical, and biological integrity); therefore, they integrate the effects of many different stressors (such as hydrology,sedimentation, pesticides, and nutrients) over the timespan of days to years and thus provide a broad measure of their aggregate impact. In addition, the geomorphology, geochemistry, land use, and land cover in the watershed control the physical/chemical habitat of the stream where the biota live. The characteristics of biotic communities are controlled by many environmental factors, though they may be directly affected by only a subset of variables. Results of redundancy analyses indicate that nutrients alone explained only a small part of the variance in the biotic indices for wadeable streams, and about a third of the variance could not be resolved into single categories of environmental characteristics. Nutrient concentrations by themselves explained from about 6 to 13 percent of the total variance in the biotic indices or about 13 to 23 percent of the explained variance. Nutrient concentrations were most important in affecting SCHL concentrations and macroinvertebrate communities, and least important in affecting BCHL concentrations, periphytic diatoms, and fish communities.


## Multiparameter Biotic Indices to Estimate Nutrient Concentrations in Wadeable Streams

One goal of this study was to develop an index based on biotic indices to estimate nutrient concentrations in streams. Most of the biotic indices had wedge-shaped responses to increases in nutrient concentrations; thus,estimations of low nutrient concentrations would be difficult with any single index. Through the use of a combination of the biotic indices that were significantly correlated to nutrient concentrations, two new multiparameter indices were developed which eliminated this nonlinear response (Biotic Index of total Phosphorus, BIP, and Biotic Index oftotal Nitrogen, BIN). These multiparameter models estiTable 23. Summary of thresholds or breakpoints in the responses of suspended chlorophyll a concentrations, Secchi tube depth, and various biotic indices to changes in nutrient concentrations for wadeable streams in Wisconsin.
[EPT, Ephemeroptera, Plecoptera, and Trichoptera; all concentrations are in milligrams per liter]

Indices Total phosphorus Dissolved phosphorus Total nitrogen Dissolved nitrite plus nitrate Dissolved ammonia Total Kjeldahl nitrogen Water quality Suspended chlorophyll a (SCHL) 0.070 0.028 1.169 0.095 0.057 0.563 Secchi tube depth (SD) .106 .047 3.305 2.583 .039 .920 Benthic chlorophyll a and diatom indices Benthic chlorophyll a (BCHL) .039 .020 .918 .187 .040 .310 Diatom Nutrient Index (DNI) .057 .026 1.216 .381 .021 .745 Diatom Siltation Index (DSI) .074 .046 .872 .089 .022 1.080 Diatom Biotic Index (DBI) .072 .039 1.169 .381 .022 .388 Macroinvertebrate indices Hilsenhoff Biotic Index (HBI) .088 .077 .609 3.455 .029 .965 Percentage of EPT individuals (EPTN%) .087 .077 .970 1.157 .029 1.053 Percentage of EPT taxa (EPTTX%) .091 .061 1.106 3.585 .034 .938 Fish indices Fish Index of Biotic Integrity (IBI) .055 .068 .539 3.455 .017 .408 Percentage of carnivorous fish (CARN%) .055 .041 .539 .095 .018 .413 Percentage of intolerant fish (INTOL%) .067 .040 .539 4.693 .032 .413 

### Summary and Conclusions 89

### mated high and low nutrient concentrations equally well. The BIP estimated P concentrations better than the BIN estimated N concentrations (54 percent of the variance in P concentrations compared to 41 percent of the variance in N concentrations). The difference in the predictability of these indices was consistent with the biotic indices being more strongly correlated to P concentrations than to Nconcentrations. This difference again suggests that P concentrations are more important than N concentrations in affecting the biotic communities as nutrient concentrations increase above reference conditions.


## Nutrient Concentrations Controlling the Biotic Integrity of Streams

Rather than examining causal relations between nutrients and the biotic community structure, this study focusedon demonstrating that nutrient concentrations are correlated with the health of wadeable streams, that specific responses exist and in some cases differ geographically, and that specific nutrients are more related to changes in stream health than other nutrients. With the results of this study, management activities can be better directed toreduce the controllable nutrient sources. Although the specific mechanisms of how nutrients affect the biota in wadeable streams were not examined, the results of this study indicate that nutrients are important in controlling the biotic health of streams. The biotic-community structure represents the overall ecological integrity of the stream; however, results of this study demonstrated that nutrients alone explained only a small part of the variability in the structure. Therefore, it is difficult to predict the exact resultof reducing nutrient concentrations without also modifying the factors typically associated with high nutrient concentrations. Nutrient concentrations in many streams, especially those in agricultural areas, are well above the response thresholds for the biotic indices; therefore, small reductions in concentrations in these streams are not expected to have large effects on the biotic community. Even with these limitations, however, it is expected that reducing nutrient concentrations will improve the biotic community, further the beneficial ecological uses of moststreams, and improve the quality of downstream nutrientlimited receiving waters. 90 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

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# Appendixes

### 96 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 1. Stream identification (ID) information, location information, and summary statistics for flow and water-quality data collected for each of the 240 studied wadeable streams in Wisconsin.
[Cr, Creek; Trib, Tributary; Br, Brook; ID, identification number; USGS, U.S. Geological Survey; km 2 , square kilometer; m 3 /s/km 2 , cubic meter per second per square kilometer; mg/L, milligram per liter; μg/L, microgram per liter; C; degrees centigrade; μS/cm; microSiemen pe r centimeter; m, meter; --, no data collected at site; all water-quality data are median values unless otherwise noted]

ID (see fig. 4) Stream name USGS site number Ecoregion ID Phosphorus

zone Longitude Latitude Collection year Watershed

area (km 2 ) Flow per unit area (m 3 /s/km 2 )

1 Onion 04026232 NLF-18 3 90.8903 46.7547 2001 15.4 0.0171 2 Thompson 040263165 NLF-15 3 90.9161 46.6686 2001 13.3 .0055
3 Parker 04027788 NLF-12 3 90.4358 46.5608 2001 8.4 .0027
4 Catlin 053315805 NLF-03 1 91.7911 46.3975 2001 5.2 .0111
5 Leo 05331581 NLF-14 1 91.8214 46.3222 2001 15.3 .0078
6 Lower Ox 05331590 NLF-10 1 91.7381 46.3222 2001 221.7 .0026
7 Lord 05331615 NLF-29 1 91.9089 46.2756 2001 26.5 .0068
8 Fivemile 05331811 NLF-01 1 91.2158 46.2042 2001 3.2 .0206 9 Cap 05331813 NLF-33 1 91.2344 46.1975 2001 39.7 .0032 10 Spring Cr 05331814 NLF-22 1 91.2417 46.1986 2001 13.8 .0055 11 Mosquito Br 05331856 NLF-35 1 91.3947 46.0458 2001 24.3 .0032
12 Smith Lake 053318635 NLF-24 1 91.4883 46.0450 2001 19.6 .0033
13 Fiddler 05331872 NLF-02 1 91.5139 45.9936 2001 8.2 .0098 14 Spring Lake 05331873 NLF-23 1 91.4831 45.9911 2001 16.6 .0066
15 Rainbow 05331877 NLF-19 1 91.5192 45.9608 2001 2.9 .0180 16 Dody Brook 05335530 NLF-20 2 92.5036 45.9186 2001 23.9 .0019
17 Swan 05356324 NLF-04 2 91.2369 45.6678 2001 25.1 .0104 18 Becky 05356368 NLF-06 1 91.3108 45.5522 2001 9.5 .0127 19 Hay 053563725 NLF-30 1 91.3178 45.4647 2001 24.8 .0162 20 Soft Maple 05356700 NLF-09 1 91.3507 45.4178 2001 82.7 .0180
21 Mcdermott 05356729 NLF-28 1 91.4408 45.3386 2001 21.0 .0138
22 Meadow Cr 05361730 NLF-41 2 90.6183 45.4500 2001 5.4 .0157
23 Gilbert Cr 05361833 NLF-40 2 90.6583 45.4586 2001 10.3 .0162
24 Trib 1 Shoulder Cr 05362010 NLF-44 2 90.8222 45.3186 2001 7.3 .0057 25 Crazy Horse Cr 05362325 NLF-39 2 90.7192 45.4336 2001 5.8 .0007
26 Alder Cr 05362409 NLF-38 2 90.7197 45.4133 2001 4.5 .0299
27 Sailor Cr 05363619 NLF-43 2 90.5586 45.2725 2001 9.4 .0069
28 Knuteson 05367087 NLF-34 2 91.4814 45.7094 2001 71.4 .0153
29 South Fork Hemlock 05367182 NLF-08 2 91.4756 45.5678 2001 9.0 .0267 30 Little Soft Maple 05376697 NLF-27 1 91.3789 45.4486 2001 21.9 .0161
31 Alvin 04059789 NLF-16 2 88.8739 45.9689 2001 14.4 .0075
32 North Otter 04067725 NLF-07 2 88.8094 45.5889 2001 7.4 .0070
33 North Fork Thunder 04068090 NLF-36 1 88.3550 45.3431 2001 35.2 .0053 34 Waupee 04070175 NLF-25 1 88.3711 45.2242 2001 31.7 .0050
35 Trout 04072167 NCHF-19 2 88.1517 44.5383 2001 35.7 .0055 36 South Fork Popple 053808864 NCHF-17 2 90.3753 44.8000 2001 23.3 .0023

### Appendixes 97

Totalphosphorus (mg/L) Dissolvedphosphorus (mg/L) Total nitrogen (mg/L) Dissolved nitrite plus

nitrate (mg/L) Dissolved ammonia

(mg/L) Total Kjeldahl nitrogen (mg/L) Suspended chlorophyll

a (μg/L) Average temperature (degrees C) Specificconductance (μS/cm) Secchi depth

(m) August pH (standard

units) Average color (standard

units) 0.037 0.028 0.151 0.081 0.010 0.070 0.768 9.3 139.0 >120.0 7.8 10.0

.052 .040 .244 .092 .007 .120 1.138 11.1 246.0 >120.0 8.2 15.0 .018 .013 .486 .018 .013 .450 1.255 15.7 320.5 >120.0 8.0 50.0 .024 .016 .452 .081 .025 .405 .412 15.0 161.5 >120.0 7.6 80.0 .021 .010 .398 .017 .014 .375 .708 16.2 89.0 >120.0 7.2 110.0 .027 .011 .330 .005 .007 .320 2.135 20.1 116.5 >120.0 8.1 40.0 .033 .019 .808 .005 .028 .715 .870 16.8 106.0 106.0 7.4 141.0 .029 .015 .900 .022 .019 .870 .798 15.9 136.5 >120.0 7.1 141.0 .039 .018 .689 .027 .021 .660 2.241 16.0 105.5 >120.0 6.9 141.0 .025 .010 .455 .011 .007 .440 1.340 17.3 135.5 >120.0 7.2 90.0 .021 .011 .403 .018 .017 .360 .580 16.5 129.5 >120.0 7.4 45.0 .092 .069 .759 .012 .039 .725 2.373 19.1 121.5 >120.0 6.8 60.0 .036 .017 .454 .074 .026 .380 2.568 16.3 194.0 >120.0 7.7 50.0 .048 .022 .592 .021 .057 .560 1.811 16.9 144.5 119.0 7.0 80.0 .032 .010 .200 .005 .017 .190 1.585 13.1 200.5 >120.0 7.6 15.0 .038 .020 .422 .032 .021 .390 1.507 14.0 161.0 >120.0 7.2 110.0 .051 .035 .758 .357 .019 .420 1.555 15.7 133.0 >120.0 7.2 80.0 .038 .032 .416 .091 .015 .320 .822 13.9 50.0 >120.0 7.7 90.0 .111 .085 .620 .020 .018 .600 1.951 15.5 89.5 >120.0 6.5 110.0 .114 .066 .735 .181 .027 .595 4.418 15.7 148.0 69.6 7.7 90.0 .139 .084 .626 .025 .038 .595 2.080 15.7 207.5 >120.0 7.4 110.0 .160 .124 1.435 .014 .029 1.430 2.260 15.6 142.0 112.0 7.0 140.0 .103 .064 1.127 .012 .042 1.100 3.060 14.8 120.0 >120.0 7.0 140.0 .101 .065 1.158 .028 .030 1.130 1.560 14.7 117.5 >120.0 6.5 130.0 .102 .065 1.390 .017 .047 1.380 2.705 14.3 65.0 86.0 6.8 141.0 .093 .069 1.230 .016 .040 1.210 2.689 14.3 73.5 85.5 6.8 120.0 .069 .052 .868 .032 .033 .780 1.027 14.7 86.5 >120.0 7.3 140.0 .044 .023 .511 .053 .026 .475 4.460 17.3 113.5 >120.0 7.9 4.3 .074 .060 .536 .041 .021 .465 1.184 14.1 100.5 >120.0 7.5 80.0 .068 .041 .709 .015 .024 .690 1.753 14.2 55.5 >120.0 7.4 100.0 .020 .012 .492 .027 .015 .450 .903 12.9 142.0 >120.0 7.5 141.0 .027 .016 .363 .034 .021 .315 1.875 16.1 247.0 >120.0 7.9 141.0 .014 .008 .326 .075 .007 .245 .504 10.7 238.0 >120.0 8.0 80.0 .017 .008 .625 .025 .026 .600 1.410 17.1 220.0 >120.0 8.0 65.0 .178 .125 3.020 1.885 .058 .955 .797 15.2 802.0 >120.0 8.1 120.0 .172 .125 1.655 0.005 .038 1.650 2.626 16.3 156.5 >120.0 6.8 141.0

### 98 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 1. Stream identification (ID) information, location information, and summary statistics for flow and water-quality data collected for each of the 240 studied wadeable streams in Wisconsin—Continued.
[Cr, Creek; Trib, Tributary; Br, Brook; ID, identification number; USGS, U.S. Geological Survey; km 2 , square kilometer; m 3 /s/km 2 , cubic meter per second per square kilometer; mg/L, milligram per liter; μg/L, microgram per liter; C; degrees centigrade; μS/cm; microSiemen pe r centimeter; m, meter; --, no data collected at site; all water-quality data are median values unless otherwise noted]

ID (see fig. 4) Stream name USGS site number Ecoregion ID Phosphorus

zone Longitude Latitude Collection year Watershed

area (km 2 ) Flow per unit area (m 3 /s/km 2 )
37 Mosquito Cr 05390240 NLF-26 1 89.0758 45.8378 2001 26.7 .0066 38 Hay Meadow 05390248 NLF-17 1 89.0458 45.8683 2001 16.8 .0077 39 Cedar Springs 05391045 NLF-37 1 89.5231 45.7247 2001 2.2 .0548
40 Skunk Cr 05391068 NLF-21 1 89.4589 45.7075 2001 15.0 .0112
41 Jennie 05392002 NLF-05 1 89.5614 45.5631 2001 4.4 .0289
42 Trout 05392006 NLF-11 1 89.5925 45.5497 2001 13.6 .0018 43 Muskellunge – Heafford Junction 05392030 NLF-42 1 89.6972 45.5108 2001 16.3 .0125

45 Johnson 05392109 NLF-31 1 89.7358 45.8997 2001 27.8 .0053
46 Threemile 05392227 NLF-13 1 89.7728 45.8158 2001 13.1 .0005
47 Raeder Cr 05399348 NCHF-13 2 90.2350 44.8511 2001 8.3 .0182
48 Hamann Cr 05399415 NCHF-09 4 90.1119 44.9308 2001 11.9 .0119
49 East Fork Hamann 05399420 NCHF-04 4 90.0786 44.9317 2001 7.9 .0063
50 Hamann Trib 05399434 NCHF-22 4 90.1117 44.9019 2001 6.3 .0061
51 Widow Green 04072670 NCHF-24 2 89.6175 43.7308 2001 8.7 .0055
52 North Fork Willow 05341629 NCHF-11 1 92.2189 45.2344 2001 26.4 .0019
53 Black Brook 05341676 NCHF-02 1 92.3417 45.1833 2001 37.6 .0028
54 South Fork Willow 053416925 NCHF-16 1 92.3531 45.1275 2001 26.1 .0059
55 Hutton Cr 053416927 NCHF-10 1 92.3561 45.1217 2001 51.3 .0021
56 Tenmile Cr 05341732 NCHF-18 1 92.6094 45.0500 2001 47.2 .0091
57 Cr 12–13 05366709 NCHF-06 1 91.6611 45.0067 2001 12.5 .0131 58 Running Valley 05367506 NCHF-14 1 91.6614 45.0267 2001 13.4 .0076
59 Cr 1–8 05367507 NCHF-08 1 91.6686 45.0261 2001 5.8 .0013
60 Cr 1–12 05367508 NCHF-05 1 91.6503 45.0189 2001 6.4 .0066
61 18-mile 05367515 NCHF-07 1 90.1219 44.3022 2001 55.6 .0098 62 Cady 05370509 DFA-08 4 92.1761 44.8414 2001 31.9 .0038 63 Eagle 05378181 DFA-12 4 91.6789 44.2197 2001 17.7 .0077
64 Joos 05378183 DFA-11 4 91.6647 44.2147 2001 15.5 .0074
65 Trout Run 05379430 DFA-13 4 91.5683 44.2136 2001 19.6 .0068
66 Bohris 05379472 DFA-14 4 91.5972 44.1456 2001 24.5 .0061
67 South Branch Oneill Cr 05380984 NCHF-15 2 90.3761 44.6031 2001 15.3 .0110
68 Unnamed Trib 1 East Fork Black 053811665 NCHF-21 2 90.4928 44.4075 2001 13.9 .0064

69 Unnamed Trib 1 Rock Cr 05381168 NCHF-23 2 90.4942 44.4661 2001 9.0 .0069

70 Bloody Run 05400881 NCHF-03 1 89.7853 44.3425 2001 17.7 .0043
71 Beaver Cr 05401764 NCHF-01 2 90.1814 44.5983 2001 11.1 .1215

### Appendixes 99

Totalphosphorus (mg/L) Dissolvedphosphorus (mg/L) Total nitrogen (mg/L) Dissolved nitrite plus

nitrate (mg/L) Dissolved ammonia

(mg/L) Total Kjeldahl nitrogen (mg/L) Suspended chlorophyll

a (μg/L) Average temperature (degrees C) Specificconductance (μS/cm) Secchi depth

(m) August pH (standard

units) Average color (standard

units) 0.030 0.016 0.837 0.019 0.036 0.825 1.545 14.6 53.0 102.0 6.9 141.0

.027 .013 .741 .005 .020 .735 2.775 17.3 67.0 >120.0 7.1 141.0 .032 .022 1.075 .018 .033 1.070 .848 14.6 65.0 >120.0 7.2 -- .040 .019 .950 .009 .036 .930 1.935 16.0 44.0 66.0 6.8 141.0 .039 .019 .467 .036 .047 .375 2.990 15.2 120.0 >120.0 7.0 80.0 .041 .026 .500 .076 .025 .410 1.623 11.5 88.0 >120.0 6.8 141.0 .029 .013 .542 .102 .037 .415 3.216 14.8 112.0 >120.0 7.5 141.0

.019 .004 .486 .031 .026 .450 3.045 18.2 159.0 >120.0 8.5 15.0 .038 .021 .619 .011 .034 .610 3.353 17.7 82.0 >120.0 7.2 100.0 .188 .140 3.010 2.020 .030 .840 3.383 15.2 271.5 85.0 7.0 141.0 .094 .068 2.165 1.056 .020 .740 1.212 14.5 300.0 >120.0 7.0 120.0 .178 .121 .990 .052 .035 .945 3.333 15.8 329.0 >120.0 7.7 110.0 .112 .087 2.675 1.845 .036 .805 3.887 15.2 340.5 >120.0 7.2 110.0 .041 .026 .773 .508 .018 .295 1.536 13.8 385.5 >120.0 8.1 30.0 .132 .071 .831 .046 .024 .785 5.780 18.2 152.5 66.0 7.6 110.0 .134 .077 1.246 .164 .054 .810 1.437 17.5 218.5 >120.0 7.7 140.0 .177 .095 1.644 .819 .035 .545 1.535 15.7 342.5 >120.0 7.7 55.0 .092 .064 4.005 3.400 .030 .540 1.725 14.8 399.5 >120.0 8.0 110.0 .065 .043 4.870 4.355 .025 .515 1.674 14.3 427.0 >120.0 7.9 55.0 .234 .208 3.080 2.550 .023 .410 .594 11.7 129.5 >120.0 6.7 15.0 .203 .129 1.114 .226 .037 .540 .744 13.4 160.0 >120.0 6.7 110.0 .246 .193 5.280 4.610 .049 .440 .404 12.0 176.5 >120.0 6.6 25.0 .527 .385 2.640 1.995 .057 .590 .602 12.6 188.0 106.0 7.0 30.0 .295 .259 2.620 1.975 .023 .455 .816 12.6 138.0 >120.0 7.0 30.0 .032 .025 3.290 3.170 .010 .135 1.811 11.6 483.0 >120.0 7.9 5.0 .056 .047 1.605 1.335 .041 .330 2.097 15.4 540.5 102.0 8.3 10.0 .068 .038 1.458 1.105 .049 .410 2.992 17.0 538.0 89.0 8.3 10.0 .196 .083 1.489 1.005 .061 .510 1.297 13.7 579.0 67.5 8.0 15.0 .141 .072 1.100 .730 .044 .365 2.028 13.7 534.0 67.5 8.1 5.0 .196 .133 1.724 .121 .059 1.400 5.595 17.4 185.0 87.5 8.7 141.0 .023 .011 .698 .013 .021 .685 2.324 16.7 27.0 115.0 7.0 141.0

.132 .069 1.629 .059 .090 1.550 5.520 17.2 63.5 37.5 6.8 141.0

.027 .013 1.690 1.430 .028 .265 .685 13.2 174.0 >120.0 7.4 140.0 .149 .109 1.304 .129 .064 1.100 2.640 15.2 418.0 >120.0 7.4 141.0

### 100 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 1. Stream identification (ID) information, location information, and summary statistics for flow and water-quality data collected for each of the 240 studied wadeable streams in Wisconsin—Continued.
[Cr, Creek; Trib, Tributary; Br, Brook; ID, identification number; USGS, U.S. Geological Survey; km 2 , square kilometer; m 3 /s/km 2 , cubic meter per second per square kilometer; mg/L, milligram per liter; μg/L, microgram per liter; C; degrees centigrade; μS/cm; microSiemen pe r centimeter; m, meter; --, no data collected at site; all water-quality data are median values unless otherwise noted]

ID (see fig. 4) Stream name USGS site number Ecoregion ID Phosphorus

zone Longitude Latitude Collection year Watershed

area (km 2 ) Flow per unit area (m 3 /s/km 2 )

72 Trib To Beaver Cr 054017645 NCHF-20 2 90.1675 44.5981 2001 12.4 0.1017
73 North Fork Hemlock Cr 05402040 NCHF-12 2 90.0281 44.5697 2001 12.5 .0056

74 Mormon 05386295 DFA-46 4 91.0697 43.7531 2001 28.2 .0048
75 Timber Coulee 05386479 DFA-07 4 90.9039 43.7233 2001 31.2 .0083 76 Spring Coulee 05386493 DFA-43 4 90.9700 43.7078 2001 29.4 .0089
77 Rush-02 05388368 DFA-36 4 91.0231 43.4197 2001 34.2 .0049
78 Beaver 054040135 DFA-03 4 90.3594 43.6261 2001 12.6 .0041 79 Dilly 05404112 DFA-05 4 90.3958 43.6531 2001 12.1 .0076
80 Trib West Branch Baraboo 054041125 DFA-01 4 90.4025 43.6603 2001 10.5 .0119

81 Crooked 05407190 DFA-40 4 90.6964 43.0919 2001 28.9 .0110
82 Moore 05407410 DFA-09 4 90.6181 43.8303 2001 47.0 .0056
83 Warner Br 05407740 DFA-02 4 90.4967 43.6147 2001 4.9 .0070
84 Warner 05407775 DFA-04 4 90.4942 43.6433 2001 10.2 .0388 85 Otter Cr – Lafarge 05408149 DFA-38 4 90.6725 43.5853 2001 21.8 .0103
86 Harrison 05409090 DFA-41 4 90.7689 43.4978 2001 18.0 .0085 87 Mccartney Br 05412709 DFA-21 5 90.9161 42.7164 2001 6.2 .0040
88 Hackett Br 05413268 DFA-19 4 90.8822 42.8311 2001 12.4 .0076
89 Kuenster 054134435 DFA-27 5 90.9572 42.7908 2001 23.6 .0130 90 Muskellunge Cr – Beetown 05413447 DFA-25 4 90.9358 42.7939 2001 18.1 .0060

91 Bull 05413885 DFA-28 4 90.5889 42.8467 2001 29.2 .0071
92 Willow 05413959 DFA-10 4 90.5964 42.7942 2001 17.5 .0096
93 Mounds Br 05414129 DFA-18 4 90.3889 42.7914 2001 7.3 .0099 94 Young Br 05414205 DFA-20 4 90.5322 42.7619 2001 6.1 .0019
95 Mcadam Br 05414259 DFA-22 4 90.5189 42.6247 2001 9.5 .0075 96 Indian Cr – Dickeyville 05414278 DFA-16 5 90.6322 42.6183 2001 9.4 .0052
97 Kieler Cr 05414753 DFA-23 5 90.5967 42.5814 2001 8.4 .0031 98 Apple 05418731 DFA-26 4 90.1339 42.5228 2001 24.2 .0187
99 Trib 1 French Spring Cr 040727260 SWTP-09 1 89.3103 43.5917 2001 2.9 .0100

100 Rowan 05405598 SWTP-48 4 89.3861 43.3864 2001 27.4 .0087
101 Hinkson 05405648 SWTP-47 1 89.4111 43.4172 2001 13.0 .0066 102 North Branch Honey 05406210 DFA-44 4 89.9692 43.3514 2001 34.0 .0050
103 Moen 05406370 DFA-29 4 89.7578 43.0347 2001 6.1 .0118
104 Trout Cr – Barneveld 05406573 DFA-06 4 89.9467 43.0478 2001 21.7 .0096 105 Lowery 05406602 DFA-30 4 90.0525 43.1036 2001 10.0 .0045

### Appendixes 101

Totalphosphorus (mg/L) Dissolvedphosphorus (mg/L) Total nitrogen (mg/L) Dissolved nitrite plus

nitrate (mg/L) Dissolved ammonia

(mg/L) Total Kjeldahl nitrogen (mg/L) Suspended chlorophyll

a (μg/L) Average temperature (degrees C) Specificconductance (μS/cm) Secchi depth

(m) August pH (standard

units) Average color (standard

units) 0.179 0.122 1.178 0.163 0.052 1.000 2.560 15.3 241.0 115.0 7.2 120.0

.304 .243 1.505 .038 .055 1.500 3.860 15.9 222.0 100.0 7.3 110.0

.045 .032 1.415 1.255 .014 .175 2.318 12.4 520.5 >120.0 8.4 10.0 .046 .029 2.105 1.890 .012 .255 3.518 13.1 470.5 >120.0 8.5 10.0 .039 .027 1.885 1.770 .016 .210 2.191 12.9 483.0 >120.0 8.4 5.0 .040 .035 2.615 2.435 .011 .195 1.780 13.5 464.0 >120.0 8.2 5.0 .106 .074 1.975 1.440 .027 .480 2.731 14.7 414.0 >120.0 8.1 15.0 .087 .044 1.565 1.150 .032 .380 3.248 13.6 425.0 76.5 8.1 15.0 .052 .029 2.055 1.720 .020 .335 1.451 12.5 516.0 >120.0 8.0 15.0

.044 .033 2.510 2.435 .014 .075 1.605 11.4 559.0 >120.0 7.4 5.0 .093 .056 1.223 .798 .023 .455 2.333 15.6 416.0 115.0 7.8 20.0 .065 .035 1.685 1.175 .035 .410 1.290 14.3 436.0 86.0 8.0 15.0 .072 .051 1.260 .944 .040 .285 1.749 14.1 471.5 98.0 8.1 -- .051 .032 1.555 1.340 .017 .225 4.756 14.1 496.0 >120.0 8.0 10.0 .027 .015 1.265 1.110 .014 .175 1.505 13.7 493.5 >120.0 7.9 5.0 .125 .068 7.385 7.040 .031 .555 1.405 13.6 638.5 59.5 7.7 15.0 .126 .094 7.705 7.265 .051 .430 3.447 14.6 718.0 98.0 8.3 10.0 .169 .124 7.570 6.625 .038 .565 4.118 15.1 735.5 80.0 8.2 30.0 .210 .185 8.145 7.260 .033 .555 2.900 14.6 767.0 94.5 8.0 15.0

.183 .122 6.300 5.475 .056 .655 2.800 14.1 706.5 49.0 8.2 10.0 .115 .091 5.270 4.910 .043 .390 1.834 16.5 659.0 110.0 8.3 10.0 .074 .049 11.040 10.695 .022 .440 2.124 15.5 627.5 84.5 8.2 5.0 .116 .056 7.050 6.670 .090 .675 5.935 17.9 749.5 49.0 8.4 15.0 .084 .060 7.185 6.730 .020 .395 5.185 15.1 798.5 89.0 8.0 40.0 .370 .324 5.235 4.370 .025 .690 3.240 16.8 770.0 62.5 8.5 30.0 .114 .078 4.585 3.815 .045 .455 2.902 16.2 747.5 72.0 8.0 110.0 .095 .066 11.385 10.550 .041 .435 2.746 14.3 661.0 50.5 7.5 55.0 .093 .066 1.361 .590 .055 .805 3.907 15.9 546.5 >120.0 8.1 80.0

.066 .038 3.765 3.405 .032 .370 1.220 12.2 545.5 105.0 7.6 15.0 .100 .031 2.930 2.210 .030 .680 3.720 14.4 486.0 >120.0 7.5 45.0 .115 .063 1.465 1.110 .050 .350 1.503 12.3 356.0 106.0 7.5 10.0 .057 .025 4.675 4.270 .026 .405 1.438 14.4 670.0 70.5 8.0 10.0 .059 .034 2.890 2.515 .021 .305 1.725 13.4 534.0 88.5 7.5 10.0 .031 .020 1.127 .852 .035 .210 .939 15.9 496.5 >120.0 8.1 5.0

### 102 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 1. Stream identification (ID) information, location information, and summary statistics for flow and water-quality data collected for each of the 240 studied wadeable streams in Wisconsin—Continued.
[Cr, Creek; Trib, Tributary; Br, Brook; ID, identification number; USGS, U.S. Geological Survey; km 2 , square kilometer; m 3 /s/km 2 , cubic meter per second per square kilometer; mg/L, milligram per liter; μg/L, microgram per liter; C; degrees centigrade; μS/cm; microSiemen pe r centimeter; m, meter; --, no data collected at site; all water-quality data are median values unless otherwise noted]

ID (see fig. 4) Stream name USGS site number Ecoregion ID Phosphorus

zone Longitude Latitude Collection year Watershed

area (km 2 ) Flow per unit area (m 3 /s/km 2 )

106 Trib Otter Cr 054066478 DFA-39 4 90.2806 43.0767 2001 26.5 0.0046
107 Bear 05406670 DFA-42 4 90.1756 43.3272 2001 43.8 .0101
108 Horse 05406783 DFA-35 4 90.4200 43.3725 2001 19.1 .0103
109 Brush 05406788 DFA-32 4 90.4147 43.3483 2001 14.0 .0107
110 East Mill 05407010 DFA-37 4 90.5258 43.3397 2001 26.3 .0092
111 Trib 1 Dead Cr 05424071 SWTP-10 4 88.7000 43.3428 2001 13.7 .0071
112 Johnson Cr – Farmington 05425534 SWTP-11 2 88.7047 43.1228 2001 8.0 .0061

113 Calamus Cr 05425913 SWTP-13 4 88.9044 43.4347 2001 35.2 .0110
114 Schultz Cr 05425919 SWTP-31 2 88.7894 43.4325 2001 12.9 .0105
115 Pratt Cr 05425928 SWTP-25 4 88.7189 43.4228 2001 9.2 .0126
116 Trib Pratt Cr 05425929 SWTP-12 4 88.7258 43.3939 2001 4.6 .0114 117 Casper Cr 05425935 SWTP-26 4 88.7647 43.3094 2001 10.5 .0025 118 Scuppernong 05426390 SWTP-41 2 88.5061 42.9022 2001 35.7 .0068
119 Door Cr 05429560 SWTP-15 4 89.2392 43.0839 2001 15.7 .0048
120 Little Door Cr 05429590 SWTP-30 4 89.1725 43.0289 2001 6.0 .0050
121 Branch Mineral Point 05432140 DFA-17 4 90.1722 42.9589 2001 8.3 .0077
122 Gill 05436204 SWTP-49 4 89.4678 42.8103 2001 12.3 .0081
123 Baker 05545102 SWTP-20 4 88.5392 42.7061 2001 21.0 .0044 124 Spring Brook 05545118 SWTP-14 4 88.3639 42.7169 2001 12.7 .0099
125 Ore 05545187 SWTP-43 2 88.3994 42.6400 2001 28.4 .0055
126 Bassett Cr 05545955 SWTP-05 2 88.2278 42.5406 2001 11.8 .0090
127 West Branch Nippersink 05548159 SWTP-42 2 88.3636 42.5181 2001 26.2 .0082

128 White Cr 04073462 SWTP-50 2 88.9283 43.8161 2001 9.1 .0198 129 Pumpkinseed Cr 04081480 SWTP-32 3 88.8197 44.0936 2001 5.8 .0034 130 Spring Bk 04081605 SWTP-33 3 88.6958 44.0189 2001 26.4 .0059 131 Daggets Cr 04081775 SWTP-39 3 88.5994 44.1414 2001 10.4 .0030 132 Van Dyne Cr 04082580 SWTP-29 3 88.5194 43.8792 2001 14.3 .0007
133 Trib 1 West Branch Fond Du Lac 04082831 SWTP-28 3 88.7006 43.8800 2001 11.8 .0067

134 Mill Cr 040842515 SWTP-34 3 88.3111 44.0792 2001 8.7 .0035 135 Kankapot Cr 04084479 SWTP-38 4 88.2542 44.2472 2001 11.7 .0007
136 Molash 040852095 SWTP-23 3 87.5342 44.1811 2001 21.2 .0086
137 Grimms 040854193 SWTP-37 3 87.8619 44.1517 2001 13.8 .0022
138 Pine Cr – Newton 0408543802 SWTP-36 3 87.7219 44.0039 2001 16.2 .0035
139 Point Cr 04085439 SWTP-35 3 87.7314 43.9692 2001 45.5 .0028

### Appendixes 103

Totalphosphorus (mg/L) Dissolvedphosphorus (mg/L) Total nitrogen (mg/L) Dissolved nitrite plus

nitrate (mg/L) Dissolved ammonia

(mg/L) Total Kjeldahl nitrogen (mg/L) Suspended chlorophyll

a (μg/L) Average temperature (degrees C) Specificconductance (μS/cm) Secchi depth

(m) August pH (standard

units) Average color (standard

units) 0.064 0.050 2.455 2.240 0.025 0.230 1.148 15.7 533.0 >120.0 8.1 10.0

.086 .034 1.740 1.390 .033 .355 2.535 12.4 488.5 102.5 7.9 10.0 .053 .031 .882 .604 .033 .235 2.015 14.0 393.0 105.0 8.0 40.0 .051 .029 1.034 .724 .037 .285 2.448 14.2 484.5 >120.0 8.1 20.0 .044 .021 .936 .669 .026 .255 2.112 16.1 477.5 >120.0 8.2 35.0 .352 .190 2.407 .013 .404 2.350 9.401 17.9 711.5 75.0 7.1 140.0 .159 .097 3.132 1.115 .238 2.100 1.293 16.4 743.0 90.0 8.1 141.0

.253 .082 1.906 .090 .107 1.700 10.411 17.3 576.0 50.0 7.2 110.0 .071 .027 8.485 8.035 .054 .450 2.923 13.2 826.0 47.5 7.5 20.0 .039 .021 4.015 3.485 .017 .385 2.786 14.4 756.0 >120.0 7.5 25.0 .109 .081 3.265 2.710 .076 .730 2.435 16.7 991.5 96.0 7.7 50.0 .239 .163 5.125 4.260 .056 .950 3.109 16.3 740.5 77.5 7.5 50.0 .028 .014 1.301 .228 .042 1.060 1.626 19.0 579.5 >120.0 8.0 130.0 .127 .066 8.385 7.760 .039 .670 1.640 13.3 819.0 33.0 8.1 10.0 .056 .029 13.205 12.750 .021 .330 1.185 13.2 736.5 49.0 8.0 15.0 .107 .056 8.145 7.690 .050 .495 3.017 16.5 830.5 50.0 8.0 5.0 .093 .066 5.820 5.220 .027 .480 1.879 14.9 597.0 66.0 8.2 40.0 .112 .088 4.082 3.359 .029 .750 3.820 18.2 762.5 105.0 8.0 25.0 .038 .016 9.685 9.215 .018 .485 2.168 16.5 693.0 92.5 8.3 15.0 .123 .085 4.710 4.005 .039 .740 4.152 16.6 718.5 55.0 8.0 15.0 .237 .159 6.240 5.370 .151 .975 1.477 17.4 1405.0 93.5 7.9 25.0 .145 .050 7.780 6.905 .136 1.040 14.605 18.4 743.5 27.5 8.0 25.0

.055 .051 21.260 20.550 .017 .185 1.260 11.4 803.0 86.0 8.0 25.0 .162 .093 2.382 .147 .047 .985 10.096 15.6 797.5 56.0 8.0 25.0 .203 .163 5.095 4.385 .052 .710 2.068 17.5 737.0 42.5 8.2 50.0 .258 .106 6.270 4.075 .039 1.200 6.393 15.9 920.0 47.5 7.2 40.0 .741 .553 3.143 .043 .051 2.000 3.038 21.6 824.0 76.0 9.2 80.0 .189 .104 3.400 1.590 .252 1.500 7.112 18.8 744.0 58.0 8.1 80.0

.088 .038 10.465 9.760 .022 .680 2.028 14.7 815.5 44.5 8.1 15.0 .557 .473 9.382 6.760 .122 2.000 5.048 15.7 1023.5 39.5 7.7 55.0 .150 .126 2.395 .891 .068 1.450 1.615 15.5 529.0 >120.0 7.6 110.0 .349 .297 4.945 3.685 .052 1.100 1.665 15.1 912.0 >120.0 7.7 55.0 .162 .119 2.365 1.265 .043 1.030 3.390 16.9 948.5 59.5 8.1 80.0 .247 .204 2.651 1.651 .072 1.040 3.796 17.0 739.0 76.0 8.3 70.0

### 104 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 1. Stream identification (ID) information, location information, and summary statistics for flow and water-quality data collected for each of the 240 studied wadeable streams in Wisconsin—Continued.
[Cr, Creek; Trib, Tributary; Br, Brook; ID, identification number; USGS, U.S. Geological Survey; km 2 , square kilometer; m 3 /s/km 2 , cubic meter per second per square kilometer; mg/L, milligram per liter; μg/L, microgram per liter; C; degrees centigrade; μS/cm; microSiemen pe r centimeter; m, meter; --, no data collected at site; all water-quality data are median values unless otherwise noted]

ID (see fig. 4) Stream name USGS site number Ecoregion ID Phosphorus

zone Longitude Latitude Collection year Watershed

area (km 2 ) Flow per unit area (m 3 /s/km 2 )
140 Pigeon 040854496 SWTP-22 4 87.8583 43.8917 2001 40.7 0.0037 141 Otter Cr – Plymouth 040857005 SWTP-19 3 87.9222 43.7889 2001 24.7 .0118
142 Weedens 04085995 SWTP-24 3 87.7733 43.7175 2001 19.6 .0146
143 Kettle Moraine 04086096 SWTP-07 2 88.2600 43.6517 2001 39.0 .0110
144 West Branch Milwaukee 04086125 SWTP-21 4 88.3936 43.6161 2001 36.0 .0075

145 Parnell 04086175 SWTP-01 2 88.1600 43.6478 2001 17.1 .0042
146 East Branch Milwaukee 04086177 SWTP-46 1 88.1811 43.6161 2001 93.4 .0051

147 Crooked 04086190 SWTP-03 2 88.1797 43.5978 2001 30.4 .0041
148 Wallace 04086335 SWTP-04 4 88.0864 43.4983 2001 39.3 .0063
149 Hanneman 04086408 SWTP-08 2 87.9589 43.3378 2001 21.7 .0066 150 Mayfield Cr 04086443 SWTP-27 2 88.1814 43.3078 2001 8.8 .0082
151 Friedens 04086465 SWTP-17 2 88.1614 43.3400 2001 10.5 .0052 152 Pigeon Cr – Theinsville 04086696 SWTP-06 3 87.9903 43.2508 2001 23.7 .0050

153 Willow Cr – Germantown 040870195 SWTP-02 3 88.1428 43.2067 2001 16.4 .0089

154 Little Menomonee 04087050 SWTP-44 3 88.0383 43.2067 2001 18.9 .0067
155 Husher 040872347 SWTP-40 3 87.9200 42.8364 2001 27.0 .0068
156 North Branch Pike 04087243 SWTP-18 3 87.8683 42.7194 2001 11.6 .0052 157 Willow Cr – Waupun 05422990 SWTP-16 4 88.6892 43.6836 2001 12.7 .0081 158 Flynn 05424450 SWTP-45 2 88.3375 43.2106 2001 13.4 .0058
201 Galena 05415000 2-DFA-01 4 90.3778 42.5136 2002 322.9 .0094 202 Skinner Cr – Klondyke 05434240 2-DFA-02 4 89.7444 42.6253 2002 90.6 .0068
203 East Branch Pecatonica 05433000 2-DFA-03 4 89.8611 42.7856 2002 571.4 .0062 204 Little Sugar 05436280 2-DFA-04 4 89.6319 42.8172 2002 57.6 .0060
205 West Branch Sugar – #1 05436010 2-DFA-05 4 89.5972 42.9031 2002 84.9 .0084
206 Platte – Rockville 05414000 2-DFA-06 4 90.6403 42.7319 2002 367.2 .0068 207 Pigeon 05413415 2-DFA-07 4 90.8161 42.7864 2002 54.4 .0066
208 Rattlesnake 05413449 2-DFA-08 4 90.9411 42.7817 2002 109.7 .0058
209 Blake 05413245 2-DFA-10 4 90.8583 42.8692 2002 85.8 .0056
210 Fennimore 05407039 2-DFA-11 4 90.5631 43.0278 2002 39.6 .0030
211 Black Earth 1 05406500 2-DFA-12 4 89.7322 43.1342 2002 112.1 .0217 212 Kickapoo 05408000 2-DFA-13 4 90.6431 43.5750 2002 689.7 .0062
213 Moore 05407428 2-DFA-15 4 90.5967 43.7933 2002 94.1 .0047
214 Coon Cr 05386500 2-DFA-16 4 91.0183 43.7047 2002 201.1 .0076
215 Little La Crosse – Sparta 05382500 2-DFA-18 4 90.8403 43.8958 2002 200.2 .0062

### Appendixes 105

Totalphosphorus (mg/L) Dissolvedphosphorus (mg/L) Total nitrogen (mg/L) Dissolved nitrite plus

nitrate (mg/L) Dissolved ammonia

(mg/L) Total Kjeldahl nitrogen (mg/L) Suspended chlorophyll

a (μg/L) Average temperature (degrees C) Specificconductance (μS/cm) Secchi depth

(m) August pH (standard

units) Average color (standard

units) 0.125 0.090 2.950 1.950 0.046 1.090 3.630 16.2 657.5 105.0 7.6 60.0

.104 .066 1.889 1.134 .030 .721 3.700 17.3 672.0 96.5 7.6 40.0 .297 .260 2.859 1.159 .044 1.400 2.475 17.4 789.0 48.0 7.6 110.0 .103 .077 1.593 .297 .049 1.355 2.250 16.9 500.0 >120.0 7.3 120.0 .118 .050 7.160 6.165 .085 1.150 7.276 14.2 832.0 >120.0 7.3 70.0

.087 .077 1.060 .135 .037 .900 2.004 17.2 482.0 103.0 7.9 120.0 .051 .031 .861 .084 .020 .735 2.230 17.3 493.0 >120.0 7.3 110.0

.055 .030 1.144 .209 .038 .885 2.168 16.5 488.5 >120.0 7.8 60.0 .106 .057 2.050 1.125 .028 .755 2.470 15.9 645.0 119.0 7.9 50.0 .068 .043 1.780 .772 .027 .825 2.361 16.4 759.0 >120.0 8.0 55.0 .166 .102 3.790 2.970 .150 .930 1.778 14.8 818.0 29.0 8.2 40.0 .091 .050 3.365 2.750 .011 .725 2.413 14.3 833.0 60.5 8.0 25.0 .053 .035 1.318 .663 .021 .585 1.947 15.8 752.0 102.5 7.8 40.0

.070 .057 1.316 .705 .050 .630 1.927 15.9 935.0 89.0 8.0 60.0

.082 .059 3.320 2.485 .049 .750 2.693 14.6 819.0 67.5 7.5 110.0 .143 .063 4.715 3.085 .036 1.300 5.335 17.2 679.0 23.5 -- 60.0 .053 .021 3.340 2.645 .044 .670 1.400 17.0 895.0 51.5 7.5 30.0 .146 .087 2.025 1.011 .063 1.050 3.579 15.0 756.5 82.0 7.3 110.0 .069 0.034 1.396 .931 .038 .465 1.562 15.0 703.0 88.5 8.0 40.0 .102 .052 7.260 6.940 .014 .325 3.181 17.1 841.2 64.0 8.0 -- .075 .048 4.500 4.200 .024 .300 1.349 15.4 649.0 63.0 7.8 -- .128 .074 4.345 3.775 .037 .375 2.117 16.3 596.3 35.5 7.2 -- .070 .050 3.825 3.425 .024 .285 1.625 13.6 622.0 74.0 7.2 -- .118 .060 6.125 5.680 .032 .460 1.918 12.9 654.0 42.0 7.2 -- .121 .063 5.055 4.735 .017 .330 3.712 15.0 650.3 39.5 7.2 -- .611 .563 6.540 6.110 .007 .425 2.511 16.3 793.7 89.5 7.6 -- .104 .088 8.990 8.680 .007 .325 2.537 16.3 742.3 >120.0 7.7 -- .159 .124 7.925 7.495 .019 .435 1.990 18.1 725.3 80.5 7.8 -- .140 .112 8.690 7.940 .016 .440 2.673 18.5 748.5 66.0 8.1 -- .063 .051 3.350 3.055 .016 .240 1.905 12.4 637.0 >120.0 7.0 -- .122 .069 1.235 .920 .018 .265 1.916 15.9 470.3 64.5 7.8 -- .198 .153 2.125 1.695 .029 .415 2.456 18.3 478.2 >120.0 7.4 -- .043 .028 1.355 1.155 .025 .160 2.071 14.4 301.8 >120.0 7.1 -- .084 .058 1.945 1.750 .017 .215 1.115 15.0 464.7 110.0 7.2 --

### 106 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 1. Stream identification (ID) information, location information, and summary statistics for flow and water-quality data collected for each of the 240 studied wadeable streams in Wisconsin—Continued.
[Cr, Creek; Trib, Tributary; Br, Brook; ID, identification number; USGS, U.S. Geological Survey; km 2 , square kilometer; m 3 /s/km 2 , cubic meter per second per square kilometer; mg/L, milligram per liter; μg/L, microgram per liter; C; degrees centigrade; μS/cm; microSiemen pe r centimeter; m, meter; --, no data collected at site; all water-quality data are median values unless otherwise noted]

ID (see fig. 4) Stream name USGS site number Ecoregion ID Phosphorus

zone Longitude Latitude Collection year Watershed

area (km 2 ) Flow per unit area (m 3 /s/km 2 )

216 Lacrosse 05382325 2-DFA-19 2 90.8106 43.9375 2002 434.1 0.0090
217 Eau Galle 2 05369945 2-DFA-20 4 92.2519 44.8672 2002 124.2 .0100
218 Willow 05341752 2-DFA-21 1 92.7083 45.0117 2002 751.0 .0070
219 Wood 05338955 2-NCHF-01 2 92.6311 45.7853 2002 348.1 .0061
220 Yellow – Barron 053674464 2-NCHF-02 1 91.8300 45.3953 2002 396.1 .0111 221 Hay River 05368000 2-NCHF-03 1 91.9108 45.0478 2002 1083.2 .0111
222 North Fork Eau Claire 05365707 2-NCHF-04 2 90.8492 44.9736 2002 131.8 .0075 223 Big Eau Pleine 05399500 2-NCHF-05 2 90.0794 44.8219 2002 578.6 .0034
224 Black 05381000 2-NCHF-06 2 90.6150 44.5597 2002 1947.1 .0061
225 Yellow – Babcock 05402000 2-NCHF-07 2 90.1219 44.3022 2002 561.3 .0047
226 Little Yellow 05403043 2-NCHF-08 1 90.1764 44.0575 2002 144.5 .0057
227 South Branch Yellow 05403044 2-NCHF-09 1 90.1478 44.0469 2002 144.5 .0025
228 Ten Mile Cr 05401050 2-NCHF-10 1 89.8103 44.2625 2002 173.3 .0108
229 Little Plover 05400650 2-NCHF-11 1 89.5281 44.4736 2002 49.3 .0059
230 Tomorrow 04080798 2-NCHF-12 1 89.3378 44.5244 2002 113.9 .0058
231 Pensaukee – Krakow 04071795 2-NCHF-13 1 88.2764 44.7525 2002 86.7 .0016
232 Pensaukee – Pensaukee 04071858 2-NCHF-14 1 87.9533 44.8189 2002 343.1 .0027

233 Middle Branch Embarrass 0407809265 2-NCHF-15 1 89.1181 44.8253 2002 254.7 .0046

234 Eau Claire – Kelly 05397500 2-NCHF-16 1 89.5500 44.9181 2002 923.8 .0046 235 Eau Claire – Antigo 05397110 2-NCHF-17 1 89.2339 45.1258 2002 471.0 .0069 236 Spring Brook 2 05397180 2-NCHF-18 1 89.1331 45.1547 2002 93.6 .0011
237 Prairie 05394500 2-NCHF-19 1 89.6497 45.2358 2002 477.2 .0092
238 Skinner 05359698 2-NLF-01 2 90.6994 45.5833 2002 74.8 .0086 239 Spirit 05393500 2-NLF-02 2 89.9797 45.4494 2002 211.3 .0120 240 North Fork Copper 05394079 2-NLF-03 2 89.9247 45.2150 2002 70.3 .0084 241 Hunting 04074720 2-NLF-04 1 89.1142 45.3814 2002 67.9 .0084
242 Wolf River 04074950 2-NLF-05 1 88.7333 45.1900 2002 1182.5 .0107
243 North Branch Pike 04066350 2-NLF-06 1 88.1089 45.5675 2002 238.0 .0102 244 Popple 04063700 2-NLF-07 2 88.4631 45.7636 2002 362.4 .0096
245 Woods 04063774 2-NLF-08 2 88.4600 45.8461 2002 59.9 .0096
246 Pine 04064500 2-NLF-09 2 88.2253 45.8378 2002 1377.9 .0094
247 Brule 04060993 2-NLF-10 2 88.3158 45.9608 2002 990.2 .0096
248 Kaubashine 05392233 2-NLF-11 1 89.8008 45.7994 2002 47.7 .0058 249 Namekagon 05331833 2-NLF-12 1 91.3292 46.1714 2002 326.2 .0129

### Appendixes 107

Totalphosphorus (mg/L) Dissolvedphosphorus (mg/L) Total nitrogen (mg/L) Dissolved nitrite plus

nitrate (mg/L) Dissolved ammonia

(mg/L) Total Kjeldahl nitrogen (mg/L) Suspended chlorophyll

a (μg/L) Average temperature (degrees C) Specificconductance (μS/cm) Secchi depth

(m) August pH (standard

units) Average color (standard

units) 0.092 0.047 1.295 1.040 0.034 0.260 2.321 16.7 185.0 >120.0 7.5 --

.037 .033 1.837 1.415 .019 .330 4.480 14.5 356.7 >120.0 7.3 -- .090 .033 2.890 2.335 .044 .615 14.644 17.3 337.7 112.0 7.9 -- .044 .022 .694 .098 .036 .595 2.770 18.1 191.3 >120.0 6.9 -- .099 .050 1.495 .890 .046 .470 7.079 16.7 178.5 102.5 7.0 -- .095 .053 2.245 1.820 .019 .465 2.110 14.6 320.3 107.5 7.4 -- .155 .097 1.051 .145 .025 .895 5.172 16.8 147.3 106.0 6.9 -- .258 .213 1.648 .692 .031 1.020 3.985 18.6 228.8 97.0 7.6 -- .173 .135 1.178 .255 .019 .910 3.814 19.4 137.0 104.5 8.0 -- .271 .136 1.397 .221 .055 1.250 7.457 17.2 142.5 55.5 7.3 -- .056 .026 1.211 .011 .353 1.200 6.347 14.4 115.8 35.5 6.6 -- .053 .019 1.197 .047 .183 1.150 6.683 16.6 71.2 81.0 6.9 -- .051 .019 4.250 3.280 .029 .950 1.956 14.9 372.8 94.5 7.8 -- .031 .023 8.240 7.985 .007 .315 1.702 13.2 497.0 >120.0 8.0 -- .019 .012 3.215 2.775 .007 .385 1.429 10.9 514.8 >120.0 8.0 -- .132 .103 2.155 1.055 .050 1.035 2.496 15.4 716.0 98.0 7.0 -- .086 .067 1.220 .306 .041 .930 2.368 16.5 552.7 102.0 7.7 --

.027 .020 1.616 1.085 .021 .520 2.631 15.0 450.3 >120.0 8.4 --

.049 .032 1.724 .914 .024 .565 3.239 16.1 244.0 >120.0 8.3 -- .085 .048 1.561 .911 .021 .635 3.971 15.4 195.0 >120.0 7.5 -- .055 .038 5.055 4.650 .024 .405 3.399 11.4 376.2 >120.0 7.2 -- .055 .037 0.600 .072 .015 .515 2.270 16.4 141.3 >120.0 8.1 -- .082 .051 1.177 .012 .045 1.150 4.392 17.5 65.5 110.5 6.5 -- .068 .045 .801 .031 .022 .770 4.823 16.7 77.7 >120.0 7.8 -- .063 .043 .793 .019 .025 .760 2.042 13.8 72.5 >120.0 7.1 -- .068 .046 .408 .013 .021 .385 2.204 17.5 184.8 >120.0 8.1 -- .032 .014 .571 .048 .018 .515 2.801 15.8 186.5 >120.0 7.6 -- .012 .006 .344 .043 .007 .300 .653 15.4 233.5 >120.0 8.2 -- .022 .012 .623 .011 .020 .615 1.180 15.6 149.2 >120.0 7.8 -- .019 .015 .554 .149 .011 .430 .452 12.4 231.3 >120.0 7.9 -- .016 .008 .490 .018 .019 .460 .941 16.1 178.2 >120.0 8.2 -- .016 .006 .298 .088 .007 .210 1.881 14.1 274.2 >120.0 7.8 -- .038 .020 .366 .011 .015 .355 1.939 16.9 111.2 >120.0 7.3 -- .017 .011 .363 .033 .007 .315 1.714 14.8 118.8 >120.0 8.0 --

### 108 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 1. Stream identification (ID) information, location information, and summary statistics for flow and water-quality data collected for each of the 240 studied wadeable streams in Wisconsin—Continued.
[Cr, Creek; Trib, Tributary; Br, Brook; ID, identification number; USGS, U.S. Geological Survey; km 2 , square kilometer; m 3 /s/km 2 , cubic meter per second per square kilometer; mg/L, milligram per liter; μg/L, microgram per liter; C; degrees centigrade; μS/cm; microSiemen pe r centimeter; m, meter; --, no data collected at site; all water-quality data are median values unless otherwise noted]

ID (see fig. 4) Stream name USGS site number Ecoregion ID Phosphorus

zone Longitude Latitude Collection year Watershed

area (km 2 ) Flow per unit area (m 3 /s/km 2 )
250 Totagatic 05333067 2-NLF-13 1 91.6947 46.1672 2002 389.6 0.0053
251 Eau Claire 05331597 2-NLF-14 1 91.6550 46.2506 2002 312.6 .0068 252 Upper Ox 05331585 2-NLF-15 1 91.6625 46.3161 2002 180.3 .0017
253 North Fish Cr 040263491 2-NLF-16 3 91.0619 46.5489 2002 99.3 .0258
254 Bois Brule 04025500 2-NLF-17 1 91.5953 46.5378 2002 343.5 .0141
255 Amnicon 04024570 2-NLF-18 3 92.0706 46.4531 2002 67.7 .0141 256 Upper Tamarack 05335574 2-NLF-19 2 92.2839 46.1644 2002 223.1 .0099
257 Turtle Cr 2 05431486 2-SWTP-01 4 88.8292 42.5972 2002 483.9 .0056
258 Whitewater Cr 05426900 2-SWTP-02 2 88.7025 42.8039 2002 53.3 .0081
259 Token Cr 05427800 2-SWTP-03 4 89.3244 43.1811 2002 63.0 .0114
260 Yahara 05427718 2-SWTP-04 4 89.3525 43.2089 2002 192.4 .0025
261 Oconomowoc 05424440 2-SWTP-05 2 88.3006 43.2192 2002 54.0 .0036
262 Milwaukee 04086600 2-SWTP-06 2 87.9428 43.2803 2002 1571.6 .0033
263 Cedar Cr 04086500 2-SWTP-07 2 87.9786 43.3231 2002 290.7 .0031
264 Sauk 04086017 2-SWTP-08 4 87.8692 43.4703 2002 55.2 .0011 265 Stoney 040863313 2-SWTP-09 4 88.0889 43.5275 2002 53.5 .0022
266 North Branch Milwaukee 040863075 2-SWTP-10 4 88.0528 43.5569 2002 132.7 .0055

267 West Branch Rock 05423510 2-SWTP-11 4 88.6856 43.6344 2002 292.2 .0024
268 Onion 04085845 2-SWTP-13 4 87.8200 43.6967 2002 243.5 .0025
269 South Branch Sheboygan 04085480 2-SWTP-14 4 88.2511 43.8092 2002 71.3 .0021

270 Meeme 04085454 2-SWTP-15 4 87.8125 43.9222 2002 49.7 .0024
271 Silver Cr 04085435 2-SWTP-16 3 87.6806 44.0547 2002 54.6 .0031
272 South Branch Manitowoc 04085395 2-SWTP-17 2 88.1181 44.0247 2002 283.1 .0013

273 Manitowoc 04085427 2-SWTP-18 3 87.7142 44.1072 2002 1359.0 .0029
274 East Twin 04085281 2-SWTP-19 2 87.6364 44.2378 2002 285.8 .0043
275 Neshota 04085305 2-SWTP-20 4 87.8142 44.3928 2002 71.8 .0019
276 Kewaunee 04085200 2-SWTP-21 4 87.5564 44.4583 2002 328.6 .0035
277 East 04085109 2-SWTP-22 4 88.0797 44.3867 2002 122.2 .0021
278 Duck Cr 04072150 2-SWTP-23 3 88.1297 44.5358 2002 280.7 .0230
301 Vismal Cr 05381195 3-NCHF-06 2 90.7647 44.3869 2003 10.5 .0061
302 Levis Cr 05381350 3-NCHF-07 1 90.8064 44.3117 2003 106.1 .0051
303 Ditch #6 South Branch Ten Mile Cr 05401035 3-NCHF-11 1 89.6064 44.2783 2003 39.2 .0048

304 South Branch Suamico 040719496 3-NCHF-15 2 88.1867 44.6175 2003 38.8 .0017
305 West Branch Red 04077601 3-NCHF-17 1 88.9882 44.9644 2003 84.0 .0100

### Appendixes 109

Totalphosphorus (mg/L) Dissolvedphosphorus (mg/L) Total nitrogen (mg/L) Dissolved nitrite plus

nitrate (mg/L) Dissolved ammonia

(mg/L) Total Kjeldahl nitrogen (mg/L) Suspended chlorophyll

a (μg/L) Average temperature (degrees C) Specificconductance (μS/cm) Secchi depth

(m) August pH (standard

units) Average color (standard

units) 0.034 0.022 0.586 0.015 0.024 0.560 1.706 16.9 84.2 >120.0 7.2 --

.017 .008 .241 .011 .007 .230 2.197 18.1 130.2 >120.0 7.7 -- .019 .012 .191 .008 .007 .180 1.367 14.2 127.5 >120.0 7.4 -- .026 .018 .131 .030 .007 .070 .857 9.5 331.0 >120.0 7.7 -- .027 .017 .353 .012 .007 .340 2.342 13.1 260.3 >120.0 7.2 -- .036 .022 1.248 .008 .038 1.240 1.142 16.5 115.0 86.0 5.5 -- .041 .027 1.161 .011 .024 1.150 1.081 17.3 118.8 92.5 6.4 -- .073 .028 9.505 9.090 .007 .575 8.421 18.4 768.8 95.0 7.3 -- .023 .014 2.545 2.170 .007 .270 1.717 15.5 661.0 >120.0 7.1 -- .070 .030 9.020 8.620 .020 .435 5.690 14.6 741.3 44.0 7.1 -- .089 .060 8.720 8.190 .018 .510 3.298 16.1 738.3 101.0 6.7 -- .035 .010 2.170 1.305 .036 .860 4.128 19.7 643.7 >120.0 8.2 -- .116 .064 2.095 1.150 .028 .880 7.619 18.1 808.3 107.5 8.6 -- .104 .041 1.677 1.105 .017 .775 10.850 18.6 761.5 110.0 8.3 -- .605 .405 3.476 1.748 .089 1.700 10.075 17.6 883.8 25.5 8.9 -- .069 .050 2.250 1.445 .029 .775 2.286 18.6 647.3 >120.0 8.1 -- .170 .098 3.750 2.615 .069 1.035 7.707 18.3 708.5 41.5 8.1 --

1.641 1.460 7.935 6.995 .075 1.050 10.947 15.9 1205.2 26.5 7.5 --

.196 .120 2.014 .895 .029 .975 23.512 17.4 688.8 51.0 7.8 -- .119 .086 3.265 2.430 .032 .890 2.422 18.2 763.8 109.0 8.0 --

.103 .078 1.825 1.180 .034 .690 5.100 17.7 590.2 92.5 7.4 -- .201 .153 2.955 1.825 .042 1.055 3.378 18.1 709.5 89.0 8.0 -- .242 .081 5.430 3.780 .058 1.750 38.007 19.8 927.7 27.0 8.3 --

.247 .102 2.481 .665 .023 1.950 36.629 19.1 672.5 35.5 8.5 -- .111 .060 3.340 2.400 .057 1.000 3.517 17.8 668.0 45.0 8.0 -- .203 .158 .777 .153 .055 .670 1.926 15.0 695.2 41.5 7.6 -- .076 .051 3.945 3.285 .052 .755 3.243 17.9 691.0 110.0 8.0 -- .412 .311 1.858 .680 .094 1.300 2.054 16.0 816.8 30.5 7.3 -- .160 .130 1.653 .396 .029 1.195 3.996 16.9 775.2 72.0 8.5 -- .021 .015 .391 .194 .014 .215 .917 14.1 62.5 >120.0 7.5 -- .023 .011 .575 .365 .014 .295 1.094 14.9 96.5 >120.0 7.6 -- .058 .046 7.960 7.395 .019 .435 2.285 15.8 430.0 >120.0 8.5 --

.247 .040 1.700 1.285 .026 .460 3.763 17.5 835.0 >120.0 8.0 -- .056 .204 3.755 1.825 .039 1.405 2.340 15.3 394.5 >120.0 8.1 --

### 110 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 2. Physical-habitat characteristics of each of the 240 studied wadeable streams in Wisconsin. All data collected by the Wisconsin Department of Natural Resources.
[CR, Creek; TRIB, Tributary; BR, Brook; ID, identification number; m/km, meter per kilometer; m, meter; --, no data collected a t site]

ID (see fig. 4) Stream name Stream width

(m) Stream
mean depth

(m) Mean thalweg

depth

(m) Stream gradient (m/km) Percent pools Percent riffle Percent
run Depth of sediment on stream bottom (m)
1 Onion 4.35 0.27 0.36 2.03 0.00 0.00 100.00 0.30 2 Thompson 4.29 .22 .35 4.04 11.81 10.42 77.78 .17 3 Parker 4.95 .09 .17 19.70 5.48 67.14 27.38 .00 4 Catlin 2.89 .18 .22 12.40 7.62 35.24 57.14 .02 5 Leo 3.12 .23 .32 3.42 12.96 1.85 85.19 .11 6 Lower Ox 14.18 .27 .37 2.80 1.16 42.82 56.02 .03 7 Lord 4.51 .22 .31 4.35 18.07 28.31 53.61 .01 8 Fivemile 4.38 .12 .16 3.50 19.31 14.48 66.21 .06 9 Cap 5.05 .38 .48 2.50 4.73 .00 95.27 .07 10 Spring Cr 5.52 .17 .24 2.31 2.65 12.39 84.96 .14 11 Mosquito Br 3.67 .17 .25 9.90 14.02 44.86 41.12 .02 12 Smith Lake 3.07 .27 .36 4.85 4.55 .00 95.45 .10 13 Fiddler 4.09 .10 .13 2.10 .00 .00 100.00 .05 14 Spring Lake 8.92 .23 .33 .82 .00 .00 100.00 .12 15 Rainbow 6.96 .16 .23 1.54 .00 .00 100.00 .06 16 Dody Brook 4.80 .40 .54 8.08 73.00 .00 27.00 .14 17 Swan 4.46 .27 .36 2.58 46.62 18.92 34.46 .00 18 Becky 3.00 .20 .27 -- .00 61.86 38.14 .01 19 Hay 5.30 .43 .61 .52 .00 .00 100.00 .20 20 Soft Maple 7.59 .46 .56 .91 19.93 14.59 65.48 .04 21 Mcdermott 4.57 .40 .48 3.30 6.49 .00 93.51 .14 22 Meadow Cr 1.37 .20 .24 2.40 .00 3.26 96.74 .10 23 Gilbert Cr 2.47 .18 .22 6.63 29.00 17.00 54.00 .02 24 Trib 1 Shoulder Cr 4.74 .35 .41 1.82 .00 .00 100.00 .37 25 Crazy Horse Cr 3.20 .39 .48 4.48 13.00 .00 87.00 .12 26 Alder Cr 2.27 .19 .24 2.18 9.00 .00 91.00 .19 27 Sailor Cr 4.27 .19 .27 4.00 12.00 15.00 73.00 .06 28 Knuteson 9.37 .40 .52 3.60 28.37 12.77 58.87 .02 29 South Fork Hemlock 3.57 .11 .18 5.40 4.20 23.08 72.73 .02 30 Little Soft Maple 4.45 .26 .31 4.50 52.00 26.00 22.00 .01 31 Alvin 3.05 .28 .36 2.40 .00 .00 100.00 .09 32 North Otter 4.12 .18 .24 4.10 .00 37.59 62.41 .02 33 North Fork Thunder 4.24 .33 .45 .82 14.38 .00 85.63 .22 34 Waupee 5.13 .36 .52 2.25 19.38 .00 80.63 .36 35 Trout 5.50 .26 .32 2.80 31.20 15.38 53.42 .01 36 South Fork Popple 4.47 .65 .74 .98 .00 .00 100.00 .25 37 Mosquito Cr 4.51 .34 .48 1.16 16.20 .00 83.80 .30 38 Hay Meadow 3.34 .22 .32 2.54 14.55 .00 85.45 .06

### Appendixes 111

Percent

silt Percent sand Percent gravel Percent rockysubstrate embeddedness Percent stream bottom covered by algae Percent
macrophytes Percent
cover Percent stream shaded Percent streambank with erosion Buffer width

(m)

2.40 85.21 5.42 87.29 0.00 0.00 16.53 78.23 18.13 8.90 3.02 71.35 23.02 77.50 .00 .00 7.60 42.71 34.58 9.46

.77 .67 25.29 6.15 .00 .00 .71 56.15 .58 10.00 .00 36.35 24.27 47.92 .00 .00 6.83 86.77 7.29 10.00 5.83 65.10 11.35 83.33 .00 3.13 4.29 60.31 39.58 10.00 7.92 47.19 22.92 39.48 .00 9.69 3.04 .10 .42 10.00 1.48 28.07 28.41 26.70 .00 .00 4.24 61.14 20.23 10.00 41.77 22.81 25.21 68.44 .21 5.73 .00 51.88 6.46 10.00 33.65 41.88 16.46 80.52 .00 .83 14.07 60.21 6.46 10.00 43.85 40.94 3.23 93.33 .00 31.25 .54 22.50 1.46 9.67

.00 42.71 31.88 50.21 .00 .00 9.13 89.48 6.25 10.00 24.69 67.08 5.83 94.06 .00 36.88 18.50 20.52 7.08 .63

1.56 64.06 33.02 67.50 .00 .00 .00 70.00 1.25 10.00 8.96 68.85 6.98 88.96 .00 9.58 1.92 46.98 1.04 10.00 34.69 52.81 .00 100.00 .00 13.75 4.33 17.81 2.50 10.00 32.12 41.25 2.88 94.81 .00 1.54 29.43 58.17 7.12 9.23

.63 33.96 33.02 25.83 20.00 .00 14.21 28.75 9.79 8.58 .63 7.08 10.42 18.13 13.96 .00 7.52 13.65 10.00 .00 22.29 37.60 .21 100.00 .00 20.42 1.34 13.33 6.67 10.00

7.29 26.35 30.52 42.60 .00 .00 11.44 82.40 5.21 10.00 21.88 32.50 26.46 74.38 .00 51.15 38.53 .00 5.21 10.00 29.97 26.69 11.09 76.09 .47 2.84 11.93 27.37 11.15 20.00

6.04 29.09 29.19 32.94 5.29 4.35 11.48 19.64 8.44 20.00 61.20 23.10 .39 99.19 16.67 30.05 16.18 2.50 5.26 12.21 31.46 11.15 2.76 91.25 .00 .60 22.99 57.11 4.06 19.31 30.13 23.65 .83 98.83 .00 4.66 6.19 69.45 5.94 18.74

4.69 40.68 40.42 43.72 .36 2.86 6.22 74.64 13.07 19.48 5.63 33.44 36.04 50.83 .00 .00 7.59 49.79 12.29 7.92 1.04 54.90 25.00 73.85 .00 .00 8.87 86.77 21.67 10.00 1.59 22.84 14.20 29.20 .00 .57 6.91 56.93 22.27 10.00 6.04 63.54 16.67 76.15 .00 11.46 13.34 9.48 13.54 9.92 1.98 34.79 39.48 36.25 .00 2.71 14.70 84.06 5.42 10.00

.00 90.38 1.15 99.04 .00 2.60 26.03 69.33 10.77 10.00 24.62 55.67 .00 100.00 .00 5.10 9.55 33.46 .38 10.00 10.31 35.31 34.27 35.83 9.79 .00 1.32 69.48 72.50 10.00 45.73 8.33 .42 99.11 .10 8.39 45.74 .00 .00 20.00

9.27 87.19 .00 100.00 .00 1.56 15.72 11.15 7.50 10.00 5.83 77.60 9.38 79.58 .00 21.15 16.36 25.10 2.08 10.00

### 112 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 2. Physical-habitat characteristics of each of the 240 studied wadeable streams in Wisconsin—Continued. All data collected by the Wisconsin Department of Natural Resources.
[Cr, Creek; Trib, Tributary; Br, Brook; ID, identification number; m/km, meter per kilometer; m, meter; --, no data collected a t site]

ID (see fig. 4) Stream name Stream width

(m) Stream
mean depth

(m) Mean thalweg

depth

(m) Stream gradient (m/km) Percent pools Percent riffle Percent
run Depth of sediment on stream bottom (m) 39 Cedar Springs 2.42 0.22 0.30 1.97 14.00 0.00 86.00 0.07 40 Skunk Cr 4.02 .48 .61 1.58 .00 3.85 96.15 .12 41 Jennie 5.31 .15 .23 5.44 .00 9.44 90.56 .08 42 Trout 2.62 .13 .19 2.77 .00 .00 100.00 .08 43 Muskellunge – Heafford Junction 6.20 .28 .37 .79 1.38 .00 98.62 .10

45 Johnson 6.77 .20 .34 1.60 .00 .00 100.00 .09 46 Threemile 3.23 .17 .24 1.16 .00 .00 100.00 .10 47 Raeder Cr 3.74 .15 .20 6.49 11.00 35.00 54.00 .01 48 Hamann Cr 4.95 .20 .26 4.22 16.00 14.00 70.00 .01 49 East Fork Hamann 1.78 .21 .25 3.39 11.00 23.00 66.00 .02 50 Hamann Trib 2.07 .17 .21 6.22 6.00 38.00 56.00 .01 51 Widow Green 2.62 .26 .32 1.90 .00 .00 0.00 .16 52 North Fork Willow 6.42 .78 .89 1.76 100.00 .00 0.00 .05 53 Black Brook 4.57 .23 .30 4.47 4.55 2.27 93.18 .04 54 South Fork Willow 3.72 .19 .29 2.41 27.14 .00 72.86 .19 55 Hutton Cr 6.79 .31 .42 2.60 55.00 8.75 36.25 .06 56 Tenmile Cr 6.26 .29 .37 2.80 22.43 2.76 74.81 .02 57 Cr 12–13 1.15 .18 .23 6.57 2.78 .00 97.22 .17 58 Running Valley 4.59 .52 .72 2.24 17.92 4.17 77.92 .11 59 Cr 1–8 1.07 .17 .20 3.33 5.93 .00 94.07 .23 60 Cr 1–12 2.13 .20 .26 2.80 .00 .00 100.00 .75 61 18-mile 1.68 .31 .37 4.40 .00 .00 100.00 .11 62 Cady 4.63 .21 .27 8.24 10.27 31.35 58.38 .00 63 Eagle 2.88 .28 .34 5.10 2.79 12.40 84.80 .17 64 Joos 3.57 .75 .86 5.80 6.61 .00 93.39 .20 65 Trout Run 2.72 .19 .25 4.10 1.94 9.71 88.35 .10 66 Bohris 4.07 .19 .27 4.10 6.11 18.32 75.57 .15 67 South Branch Oneill Cr 3.42 .20 .25 2.67 28.00 7.00 65.00 .03 68 Unnamed Trib 1 East Fork Black 3.50 .22 .28 3.67 31.00 31.00 38.00 .02

69 Unnamed Trib 1 Rock Cr 2.11 .16 .23 2.16 2.06 .00 97.94 .16 70 Bloody Run 3.23 .11 .16 2.30 .00 .00 100.00 .18 71 Beaver Cr 3.27 .26 .31 2.34 29.00 3.00 68.00 .06 72 Tributary To Beaver Cr 3.10 .22 .27 .38 15.00 15.00 70.00 .04 73 North Fork Hemlock Cr 5.17 .17 .22 3.43 28.87 18.56 52.58 .01 74 Mormon 6.58 .22 .34 4.43 7.72 17.83 74.45 .02 75 Timber Coulee 4.32 .27 .37 4.97 18.33 5.00 76.67 .01

### Appendixes 113

Percent

silt Percent sand Percent gravel Percent rockysubstrate embeddedness Percent stream bottom covered by algae Percent
macrophytes Percent
cover Percent stream shaded Percent streambank with erosion Buffer width

(m)

11.02 64.66 1.02 98.30 0.00 22.95 17.09 13.64 1.82 10.00 5.00 65.00 10.96 87.12 .00 5.29 8.82 3.65 .00 9.50 26.67 54.27 17.29 85.73 .00 4.69 2.27 .21 1.46 10.00

.77 76.63 13.17 79.71 3.27 .77 6.80 26.44 15.96 10.00 26.77 64.69 1.67 98.33 .00 .00 1.81 34.90 5.00 10.00

5.21 81.67 9.48 87.19 .00 .00 14.91 71.67 8.13 10.00 15.00 69.90 .00 100.00 1.04 22.92 7.96 31.25 3.75 10.00

.99 20.18 32.08 20.36 2.06 .18 6.15 69.43 15.10 20.00 2.03 14.71 44.40 14.87 20.08 3.07 6.69 70.31 9.43 19.70 10.21 18.02 21.85 33.91 3.49 .23 12.81 58.59 6.77 17.81 4.11 13.13 18.85 18.98 12.40 2.27 10.40 24.14 3.75 15.60 22.50 75.42 .00 100.00 .00 6.56 .56 .00 6.25 .00 31.54 23.46 17.12 64.90 2.21 8.37 21.11 7.12 1.15 10.00 10.58 53.08 27.60 68.46 .00 .00 3.41 63.94 35.00 9.65 26.06 47.02 16.83 84.04 .10 .19 1.42 67.12 56.54 9.23 26.25 31.44 14.23 67.69 2.69 .00 1.59 37.21 70.19 8.62

6.73 38.08 39.52 47.69 .00 .00 3.20 64.04 11.15 9.08 24.81 46.44 .38 99.81 .00 12.40 1.40 30.77 76.54 10.00 14.23 72.50 1.54 94.23 .96 2.02 7.20 16.15 9.81 10.00 34.90 41.04 .00 100.00 .00 3.75 6.48 19.38 63.33 10.00 66.92 .38 .00 100.00 .00 5.00 .00 73.17 67.12 9.92

5.52 89.69 .00 100.00 .00 .00 10.14 .00 8.33 10.00 10.10 2.29 18.33 20.63 6.04 21.46 6.64 29.17 17.29 10.00 31.46 9.90 11.15 79.38 .21 .00 2.33 .00 4.58 8.83 64.13 25.48 .38 98.27 .00 1.73 28.27 9.52 22.69 10.00 10.52 62.08 6.35 76.56 4.17 .83 .00 .00 43.75 .00 15.52 67.60 5.94 87.71 .31 1.04 .00 31.88 23.96 9.38 14.40 21.46 28.13 40.16 13.59 17.50 9.12 5.81 24.27 .21

.76 25.70 29.61 26.54 8.18 3.20 11.55 20.73 21.25 19.86

3.44 89.38 .78 98.31 .00 .00 5.33 76.61 18.49 18.45 13.54 66.98 3.54 97.71 .00 9.17 .64 84.38 28.33 12.38 3.46 25.89 40.29 34.53 3.39 .00 10.73 62.66 20.68 10.78 7.76 33.20 37.19 48.15 2.42 2.84 8.18 52.19 20.47 20.00 3.23 13.07 30.36 16.20 19.35 .31 1.99 90.60 17.34 20.00 26.25 14.90 17.81 51.56 1.04 45.63 .42 33.23 .00 14.88 13.33 11.46 29.17 41.56 14.06 18.44 7.84 51.25 5.83 5.17

### 114 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 2. Physical-habitat characteristics of each of the 240 studied wadeable streams in Wisconsin—Continued. All data collected by the Wisconsin Department of Natural Resources.
[Cr, Creek; Trib, Tributary; Br, Brook; ID, identification number; m/km, meter per kilometer; m, meter; --, no data collected a t site]

ID (see fig. 4) Stream name Stream width

(m) Stream
mean depth

(m) Mean thalweg

depth

(m) Stream gradient (m/km) Percent pools Percent riffle Percent
run Depth of sediment on stream bottom (m) 76 Spring Coulee 7.32 0.27 0.43 4.30 24.80 26.42 48.78 0.07 77 Rush-02 3.53 .19 .24 -- 10.10 63.64 26.26 .01 78 Beaver 2.63 .29 .37 3.40 35.14 24.32 40.54 .01 79 Dilly 2.13 .28 .31 5.51 .00 33.62 66.38 .00 80 Trib West Branch Baraboo 2.96 .26 .31 -- 26.67 14.29 59.05 .04 81 Crooked 4.76 .38 .54 1.42 28.81 .00 71.19 .14 82 Moore 6.43 .33 .41 5.23 6.57 32.86 60.56 .00 83 Warner Br 2.34 .21 .24 5.28 6.09 22.61 71.30 .02 84 Warner 6.99 .41 .57 2.81 12.85 11.17 75.98 .12 85 Otter Cr – Lafarge 4.50 .30 .43 2.31 28.82 32.53 38.65 .04 86 Harrison 2.35 .41 .49 2.46 39.04 3.59 57.37 .08 87 Mccartney Br 2.04 .20 .25 5.23 18.00 30.00 52.00 .04 88 Hackett Br 3.41 .16 .20 10.00 .00 55.00 45.00 .00 89 Kuenster 6.11 .23 .33 5.24 .00 34.07 65.93 .05 90 Muskellunge Cr – Beetown 4.55 .33 .45 4.40 28.74 9.58 61.68 .06 91 Bull 5.32 .32 .41 4.50 29.03 25.35 45.62 .11 92 Willow 4.44 .23 .30 5.00 .00 20.14 79.86 .02 93 Mounds Br 1.93 .22 .28 4.76 4.81 43.27 51.92 .01 94 Young Br 3.09 .22 .28 15.86 19.80 36.63 43.56 .01 95 Mcadam Br 2.45 .22 .28 10.97 14.14 29.29 56.57 .02 96 Indian Cr – Dickeyville 1.36 .07 .10 12.01 .00 85.00 15.00 .00 97 Kieler Cr 1.89 .16 .20 7.35 6.67 28.57 64.76 .01 98 Apple 4.87 .43 .53 4.50 17.81 15.07 67.12 .03 99 Trib 1 French Spring Cr 1.39 .18 .23 3.95 21.43 6.12 72.45 .10 100 Rowan 3.72 .52 .70 2.30 39.23 .00 60.77 .10 101 Hinkson 3.47 .18 .24 1.30 5.13 .00 94.87 .11 102 North Branch Honey 2.61 .32 .38 7.30 .00 .00 100.00 .14 103 Moen 1.87 .16 .22 8.33 13.15 34.74 52.11 .04 104 Trout Cr – Barneveld 4.47 .46 .66 6.02 25.81 16.77 57.42 .12 105 Lowery 2.65 .17 .28 5.39 28.46 8.13 63.41 .17 106 Trib Otter Cr 5.73 .28 .38 4.60 29.93 19.20 50.87 .06 107 Bear 3.49 .37 .53 2.70 23.49 .00 76.51 .07 108 Horse 2.67 .25 .35 2.80 3.57 .00 96.43 .16 109 Brush 2.47 .29 .36 1.70 28.64 17.27 54.09 .08 110 East Mill 3.34 .33 .38 3.36 20.00 27.08 52.92 .01 111 Trib 1 Dead Cr 1.63 .38 .46 .56 .00 .00 100.00 .31 112 Johnson Cr – Farmington 2.32 .26 .33 .74 .00 .00 100.00 .50 113 Calamus Cr 3.43 .35 .39 1.95 .00 .00 100.00 .13

### Appendixes 115

Percent

silt Percent sand Percent gravel Percent rockysubstrate embeddedness Percent stream bottom covered by algae Percent
macrophytes Percent
cover Percent stream shaded Percent streambank with erosion Buffer width

(m)

24.48 44.58 10.00 64.48 0.10 32.29 1.53 69.90 17.50 18.83

5.42 11.46 40.42 21.25 .21 .10 .89 67.19 13.33 16.38 7.19 10.10 46.25 18.54 5.83 .00 7.30 5.73 8.13 20.00 6.98 12.50 27.81 18.75 3.33 .00 5.21 2.29 2.71 .00 9.58 24.17 38.33 36.25 .00 .00 11.00 41.98 12.50 18.92 59.61 25.39 6.41 88.28 .39 47.66 3.91 .00 .47 17.72

3.33 11.88 17.50 17.19 .63 .00 3.43 56.67 19.58 6.71 1.98 34.38 29.79 35.10 10.00 .00 4.33 .00 32.92 .00 5.42 60.94 23.96 68.65 3.75 .00 3.00 53.02 28.33 20.00 10.63 29.61 24.14 42.58 .00 .00 1.32 76.64 29.22 23.44 14.46 28.48 20.54 65.18 .00 15.45 19.88 .00 4.46 .00 32.47 4.92 26.90 46.48 2.84 1.90 11.18 .00 21.41 .00

9.48 3.46 15.36 21.02 45.91 2.21 2.40 1.43 21.46 .00 41.46 3.65 18.75 61.35 22.81 6.25 .00 39.17 22.92 .00 48.46 2.60 15.87 69.52 10.67 28.85 8.13 15.48 26.35 .00 46.25 6.52 17.68 64.55 15.98 17.32 3.21 37.95 38.57 .00 16.46 16.04 15.00 49.38 14.48 19.90 .49 42.71 31.46 .00 15.41 5.79 44.28 29.13 3.99 2.88 8.41 .00 24.13 .00 18.05 1.85 14.95 33.75 19.51 .96 4.39 50.99 28.33 19.78 23.95 5.18 18.88 42.47 19.84 14.87 6.08 5.83 25.83 .00

7.55 6.80 29.92 21.95 6.98 .00 .00 69.51 28.96 17.71 25.28 2.33 15.90 49.75 13.73 1.00 6.46 6.98 9.50 11.03

8.54 9.06 38.75 24.38 14.17 2.81 1.11 .00 38.75 10.00 24.17 50.18 1.61 96.41 .00 .18 20.52 8.98 3.85 16.83 51.44 2.02 10.48 77.60 .00 18.75 9.13 .77 7.50 10.00 13.94 50.87 .48 98.27 .00 .00 1.40 71.73 15.77 10.00 42.40 52.40 2.08 95.42 .10 10.10 4.14 .10 60.63 .00

.54 59.73 20.71 61.52 .54 7.32 7.95 .00 7.86 20.57 15.52 44.79 17.50 68.13 .00 27.29 5.85 .00 33.13 20.00 80.39 4.77 5.39 82.89 .00 54.77 1.12 .00 19.06 .00 39.06 19.90 29.06 67.92 .00 .52 .00 73.33 34.38 .00 22.50 34.23 16.15 76.54 .00 7.40 .79 44.90 28.46 30.00

5.77 88.08 3.17 97.12 .00 .77 1.25 .00 40.00 .00 3.96 40.73 46.56 43.02 .21 .00 11.29 .00 19.79 18.13 3.84 36.52 34.46 32.41 .36 1.70 7.62 .00 8.04 10.00 42.19 .78 1.35 98.88 .00 5.42 30.51 .00 .16 16.61 12.92 81.95 .00 100.00 .00 .00 13.54 6.59 1.25 18.88 60.73 13.26 2.66 96.33 .42 47.71 43.37 .00 1.56 17.85

### 116 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 2. Physical-habitat characteristics of each of the 240 studied wadeable streams in Wisconsin—Continued. All data collected by the Wisconsin Department of Natural Resources.
[Cr, Creek; Trib, Tributary; Br, Brook; ID, identification number; m/km, meter per kilometer; m, meter; --, no data collected a t site]

ID (see fig. 4) Stream name Stream width

(m) Stream
mean depth

(m) Mean thalweg

depth

(m) Stream gradient (m/km) Percent pools Percent riffle Percent
run Depth of sediment on stream bottom (m)
114 Schultz Cr 2.12 0.25 0.32 4.62 0.00 0.00 100.00 0.07 115 Pratt Cr 2.80 .29 .34 1.60 .00 .00 100.00 .22 116 Trib Pratt Cr 1.95 .21 .26 1.33 .00 .00 100.00 .26 117 Casper Cr 1.46 .15 .19 5.04 4.08 12.24 83.67 .07 118 Scuppernong 3.11 .47 .54 .70 .00 .00 100.00 .08 119 Door Cr 2.25 .32 .40 1.37 .00 .00 100.00 .14 120 Little Door Cr 3.10 .17 .22 3.89 .00 13.00 87.00 .08 121 Branch Mineral Point 2.28 .19 .24 4.32 21.00 41.00 38.00 .01 122 Gill 2.56 .22 .26 2.82 .00 .00 100.00 .07 123 Baker 2.60 .18 .24 7.60 18.69 26.17 55.14 .02 124 Spring Brook 4.07 .25 .31 7.20 16.67 26.39 56.94 .02 125 Ore 4.75 .31 .39 2.61 36.80 11.20 52.00 .02 126 Bassett Cr 2.60 .17 .21 3.86 .00 25.00 75.00 .04 127 West Branch Nippersink 5.41 .27 .40 2.23 9.71 .00 90.29 .11 128 White Cr 3.35 .24 .31 4.67 9.03 22.22 68.75 .10 129 Pumpkinseed Cr 2.17 .40 .48 1.71 .00 .00 100.00 .09 130 Spring Bk 2.58 .08 .11 20.73 .00 100.00 0.00 .00 131 Daggets Cr 1.97 .27 .33 1.70 .00 .00 100.00 .20 132 Van Dyne Cr 2.22 .21 .26 8.70 44.00 17.00 39.00 .05 133 Trib 1 West Branch Fond Du Lac 2.43 .26 .32 .87 .00 .00 100.00 .18

134 Mill Cr 2.33 .15 .18 4.32 .00 54.17 45.83 .03 135 Kankapot Cr 2.18 .17 .23 2.57 37.00 17.00 46.00 .04 136 Molash 4.02 .72 .87 .92 .00 .00 100.00 .14 137 Grimms 1.39 .27 .32 2.00 1.94 .00 98.06 .06 138 Pine Cr – Newton 2.90 .33 .40 3.41 4.50 .00 95.50 .07 139 Point Cr 6.24 .30 .36 2.59 8.97 11.03 80.00 .03 140 Pigeon 3.21 .26 .31 1.50 3.73 2.24 94.03 .06 141 Otter Cr – Plymouth 4.80 .20 .25 2.50 .00 6.31 93.69 .01 142 Weedens 3.63 .27 .35 6.80 13.08 16.82 70.09 .01 143 Kettle Moraine 3.58 .26 .29 4.60 18.54 13.25 68.21 .02 144 West Branch Milwaukee 3.17 .48 .63 6.89 .00 .00 100.00 .46 145 Parnell 3.21 .17 .21 5.70 6.03 38.79 55.17 .01 146 East Branch Milwaukee 7.06 .34 .45 .93 13.15 .00 86.85 .11 147 Crooked 5.07 .27 .37 1.09 .00 .00 100.00 .22 148 Wallace 4.22 .39 .47 3.01 29.79 9.93 60.28 .07 149 Hanneman 3.98 .23 .29 3.35 .00 2.88 97.12 .02 150 Mayfield Cr 3.77 .30 .35 6.80 14.29 19.05 66.67 .02 151 Friedens 3.75 .22 .28 9.83 17.14 50.00 32.86 .01

### Appendixes 117

Percent

silt Percent sand Percent gravel Percent rockysubstrate embeddedness Percent stream bottom covered by algae Percent
macrophytes Percent
cover Percent stream shaded Percent streambank with erosion Buffer width

(m)

30.99 4.11 2.63 86.09 4.82 4.35 19.38 62.79 8.59 20.00 61.09 2.58 2.55 99.87 4.64 16.04 19.66 13.85 4.53 10.17 64.79 3.33 .57 97.89 1.30 1.07 16.43 38.67 9.84 9.42 27.86 23.28 13.13 66.56 3.46 .26 5.47 35.16 15.52 12.21 32.08 52.08 .42 100.00 .42 14.38 3.35 .00 27.92 20.00 32.97 32.21 1.69 90.78 .00 3.07 26.95 28.41 3.07 .11 37.42 31.15 8.52 80.49 .00 .00 1.50 78.85 17.34 11.79 12.92 6.95 31.12 25.00 15.03 .03 8.95 17.40 20.89 6.08 7.60 70.00 6.92 82.12 .00 .00 .00 67.02 39.42 6.27 4.58 31.25 48.54 33.75 7.29 7.08 .00 66.77 28.75 17.21 11.67 23.75 17.08 41.98 .00 .00 17.00 93.65 39.79 5.04 11.82 25.80 46.70 36.59 .00 .00 .56 71.48 33.86 20.00 7.45 35.57 34.51 42.58 1.46 .00 1.66 88.91 22.34 6.40 28.44 29.69 25.10 66.56 .63 15.73 6.61 6.04 10.00 20.00 21.98 25.83 13.54 54.38 3.33 1.35 3.13 87.29 11.04 15.79 12.08 .05 .05 99.82 .83 .00 36.82 24.24 2.81 5.84 5.83 5.60 24.74 9.79 3.15 .78 .00 72.76 13.23 17.65 51.49 7.95 1.91 96.67 .00 1.15 4.81 71.53 13.26 15.75 25.97 16.32 18.75 63.65 32.74 1.91 10.05 29.51 17.15 17.96 49.35 7.86 1.85 94.74 11.69 7.06 9.97 39.35 10.78 7.44

8.39 31.41 29.77 34.11 1.09 .00 .42 70.00 26.15 19.55 3.91 23.49 24.24 44.01 6.67 .00 3.20 81.67 45.10 19.32 17.50 58.13 .00 100.00 .00 3.85 14.41 18.96 5.00 20.00 23.13 37.92 10.42 80.21 .42 .00 37.26 22.71 6.04 17.58 42.71 21.98 18.75 70.31 12.71 .00 9.96 8.23 11.04 19.54 20.63 27.29 17.92 62.19 34.38 .00 4.46 22.29 9.58 18.33 51.07 15.63 15.80 76.61 10.98 37.86 19.46 .00 5.00 4.75 17.12 28.85 35.77 43.56 5.38 34.13 1.97 .00 1.92 7.23 6.35 28.13 34.38 28.96 53.75 .00 1.67 32.40 36.25 20.00 13.33 37.29 21.25 50.42 22.50 19.27 7.63 2.92 8.96 19.67 95.63 .21 .00 100.00 30.21 23.75 14.17 .00 4.79 20.00

8.85 18.13 24.17 24.90 16.15 2.50 .00 10.83 41.04 6.56 35.94 34.06 9.90 83.23 .00 .00 2.86 61.35 51.67 10.00 59.09 7.95 9.55 89.09 .00 3.98 1.59 70.91 12.50 19.41 22.81 34.58 18.85 63.65 .83 .00 19.30 66.56 29.58 19.50 17.92 39.38 27.81 51.98 10.00 2.71 1.30 36.35 17.08 17.63 15.00 22.40 26.56 44.38 30.42 .00 9.59 75.00 41.25 19.79

1.77 6.35 27.71 15.10 1.46 .00 6.74 90.52 14.38 9.58

### 118 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 2. Physical-habitat characteristics of each of the 240 studied wadeable streams in Wisconsin—Continued. All data collected by the Wisconsin Department of Natural Resources.
[Cr, Creek; Trib, Tributary; Br, Brook; ID, identification number; m/km, meter per kilometer; m, meter; --, no data collected a t site]

ID (see fig. 4) Stream name Stream width

(m) Stream
mean depth

(m) Mean thalweg

depth

(m) Stream gradient (m/km) Percent pools Percent riffle Percent
run Depth of sediment on stream bottom (m) 152 Pigeon Cr – Theinsville 3.30 0.18 0.23 1.38 19.61 29.41 50.98 0.01 153 Willow Cr – Germantown 2.75 .21 .29 5.09 .00 .00 100.00 .15 154 Little Menomonee 4.12 .32 .40 .51 .00 .00 100.00 .02 155 Husher 4.54 .35 .42 2.51 .00 .00 100.00 .05 156 North Branch Pike 2.96 .45 .51 .82 .00 .00 100.00 .10 157 Willow Cr – Waupun 2.60 .42 .51 .87 .00 .00 100.00 .29 158 Flynn 4.25 .16 .23 6.22 17.69 60.77 21.54 .01 201 Galena 17.76 .43 .54 1.25 .00 31.88 68.13 .00 202 Skinner Cr – Klondyke 7.00 .51 .71 .70 .00 6.49 93.51 .13 203 East Branch Pecatonica 16.30 1.00 1.27 .52 .00 .00 100.00 .33 204 Little Sugar 6.60 .56 .70 1.32 .00 20.35 79.65 .05 205 West Branch Sugar – #1 5.25 .76 .85 .34 .00 .00 100.00 .23 206 Platte – Rockville 16.84 .66 .92 3.30 17.02 25.96 57.02 .03 207 Pigeon 5.95 .42 .58 3.05 14.47 16.23 69.30 .05 208 Rattlesnake 11.81 .41 .49 3.36 1.63 15.12 83.26 .01 209 Blake 7.86 .42 .60 2.20 10.25 8.13 81.63 .06 210 Fennimore 5.23 .44 .54 11.30 16.30 12.77 70.92 .07 211 Black Earth 1 13.02 .60 .69 .95 1.58 4.75 93.67 .07 212 Kickapoo 13.97 .62 .89 .61 .00 .00 100.00 .21 213 Moore 8.00 .29 .42 1.87 3.85 18.38 77.78 .04 214 Coon Cr 12.19 .58 .76 .98 .00 6.46 93.54 .46 215 Little La Crosse – Sparta 8.47 .47 .65 .94 .00 .00 100.00 .15 216 Lacrosse 14.45 .92 1.15 .71 .00 2.79 97.21 .14 217 Eau Galle 2 8.92 .33 .44 2.32 15.10 63.27 21.63 .02 218 Willow 18.51 .70 1.01 2.84 .00 11.08 88.92 .01 219 Wood 11.09 .62 .94 .49 .00 .00 100.00 .74 220 Yellow – Barron 20.74 .52 .66 1.65 9.88 28.50 61.63 .02 221 Hay River 27.03 .67 1.02 .67 .00 .00 100.00 .13 222 North Fork Eau Claire 12.07 .36 .51 1.96 12.42 10.00 77.58 .01 223 Big Eau Pleine 28.08 .70 .86 .96 6.88 9.00 84.13 .02 224 Black 56.27 .62 .78 1.55 1.15 5.13 93.72 .01 225 Yellow – Babcock 18.04 .85 1.21 .19 .00 .00 100.00 .17 226 Little Yellow 9.94 .60 .91 .31 .00 .00 100.00 .89 227 South Branch Yellow 8.68 .24 .37 .31 4.01 .00 95.99 .27 228 Ten Mile Cr 10.44 .61 .97 2.67 .85 .00 99.15 .21 229 Little Plover 5.74 .30 .40 2.55 .00 1.63 98.37 .09 230 Tomorrow 9.08 .54 .69 1.07 .00 5.13 94.87 .07 231 Pensaukee – Krakow 10.56 .35 .43 -- .00 3.13 96.88 .03

### Appendixes 119

Percent

silt Percent sand Percent gravel Percent rockysubstrate embeddedness Percent stream bottom covered by algae Percent
macrophytes Percent
cover Percent stream shaded Percent streambank with erosion Buffer width

(m)

3.65 15.63 49.58 23.54 4.17 0.00 8.42 84.90 13.96 20.00 40.63 23.65 7.60 91.15 .00 .00 4.40 60.21 30.42 18.33 22.40 25.58 19.13 61.06 5.19 3.46 1.59 67.31 15.38 10.00 22.92 23.13 18.75 70.83 .00 .00 6.56 82.08 40.42 20.00 17.89 14.41 17.43 70.00 1.64 1.23 6.86 50.93 22.45 13.55 76.90 .00 .00 100.00 .00 5.36 25.62 .00 2.03 19.13

3.98 12.84 41.93 14.20 5.00 .23 .00 60.80 10.00 20.00 3.63 6.63 30.81 16.31 48.38 .00 2.55 21.44 16.00 10.53 25.52 1.35 14.58 82.50 .63 .00 7.37 61.77 44.58 13.83 19.25 53.25 11.50 80.67 .00 .00 7.23 21.67 36.83 20.00 11.04 15.94 23.33 33.02 9.58 .00 3.98 68.44 23.96 14.21 76.88 11.67 .00 98.54 .00 .00 7.87 29.90 17.71 2.63 19.87 13.62 35.53 35.13 1.18 6.51 5.84 15.26 11.32 15.55 29.42 21.54 13.65 59.81 13.94 21.35 1.87 .58 34.23 .00 23.57 6.34 23.75 38.48 16.88 14.91 2.66 26.43 12.50 .71 28.54 30.21 19.58 69.90 19.38 16.67 .57 .21 38.54 .00 64.50 4.00 21.50 78.17 1.67 4.42 1.15 .00 24.00 .00 17.88 13.56 50.63 37.75 3.88 16.69 21.65 35.56 17.38 10.80

.97 81.16 11.59 84.19 .00 2.72 6.21 23.88 29.63 16.00 1.54 55.87 28.94 61.83 .96 .19 1.76 65.77 65.38 10.27 8.69 68.00 3.13 87.06 .00 .00 4.83 33.69 25.88 12.75

.63 88.23 10.94 77.50 .00 1.25 12.64 .83 17.71 16.63 .13 65.44 19.13 64.94 .00 2.13 14.11 49.88 21.38 11.35 2.08 17.08 33.85 16.88 11.46 4.79 7.23 22.81 8.33 19.00

.00 19.13 28.00 15.81 9.13 1.75 7.65 18.19 11.78 20.00 .31 99.56 .00 100.00 .50 .88 15.25 5.69 13.88 20.00 .38 6.56 32.19 19.00 8.75 14.63 21.73 21.88 11.38 15.63 .00 90.37 8.90 82.65 .44 .00 2.70 14.63 38.97 20.00 .00 25.52 40.52 12.50 .00 .00 3.02 11.46 15.63 .00 .19 18.19 35.06 19.25 .00 .00 13.75 8.00 12.00 19.05 .94 21.88 20.75 34.75 10.50 .00 21.30 4.94 23.50 18.58 .63 83.33 3.96 89.79 .00 .00 25.89 58.33 37.71 20.00 1.88 97.50 .00 100.00 .00 .00 13.32 63.44 65.00 20.00 1.88 92.29 .00 100.00 .00 .00 11.23 47.29 52.29 19.83

.10 93.02 .73 98.96 .00 .00 19.75 38.02 11.04 15.71 .83 85.73 .00 96.04 1.88 6.35 11.88 53.23 .00 20.00 10.19 54.25 12.94 70.31 .31 7.06 24.68 42.69 2.25 19.55 11.98 27.81 42.29 38.23 21.04 1.98 .96 45.63 16.88 17.94

### 120 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 2. Physical-habitat characteristics of each of the 240 studied wadeable streams in Wisconsin—Continued. All data collected by the Wisconsin Department of Natural Resources.
[Cr, Creek; Trib, Tributary; Br, Brook; ID, identification number; m/km, meter per kilometer; m, meter; --, no data collected a t site]

ID (see fig. 4) Stream name Stream width

(m) Stream
mean depth

(m) Mean thalweg

depth

(m) Stream gradient (m/km) Percent pools Percent riffle Percent
run Depth of sediment on stream bottom (m)
232 Pensaukee – Pensaukee 13.40 0.73 0.97 0.97 19.33 0.00 80.67 0.13 233 Middle Branch Embarrass 16.24 .39 .48 .99 .00 14.41 85.59 .04 234 Eau Claire – Kelly 27.24 .60 .88 1.00 24.70 47.12 28.18 .02 235 Eau Claire – Antigo 19.16 .58 .72 .86 .00 11.62 88.38 .03 236 Spring Brook 2 6.07 .19 .26 1.49 13.86 5.94 80.20 .06 237 Prairie 22.86 .41 .54 1.35 .00 .00 100.00 .03 238 Skinner 9.72 .56 .66 2.19 30.25 .00 69.75 .04 239 Spirit 18.06 .51 .63 1.46 .00 10.94 89.06 .03 240 North Fork Copper 9.18 .45 .56 .87 22.50 .00 77.50 .04 241 Hunting 18.80 .27 .42 1.96 .00 27.78 72.22 .03 242 Wolf River 55.12 .61 .82 1.17 .00 11.52 88.48 .02 243 North Branch Pike 11.35 .83 .97 .50 6.77 .00 93.23 .10 244 Popple 22.97 .85 1.01 1.26 22.88 .00 77.13 .04 245 Woods 9.82 .22 .28 3.03 .00 11.27 88.73 .02 246 Pine 35.80 .51 .68 1.05 3.75 6.50 89.75 .01 247 Brule 31.58 .55 .81 1.77 2.75 20.38 76.88 .00 248 Kaubashine 7.71 .17 .23 .44 .00 20.18 79.82 .21 249 Namekagon 27.91 .38 .59 2.52 1.88 31.88 66.25 .02 250 Totagatic 10.89 .32 .54 .92 8.33 3.66 88.01 .20 251 Eau Claire 17.12 .41 .57 1.32 6.60 28.47 64.93 .05 252 Upper Ox 7.70 .35 .59 .89 23.97 .00 76.03 .19 253 North Fish Cr 11.48 .47 .72 .86 4.43 15.44 80.13 .11 254 Bois Brule 19.85 .57 .74 2.67 .00 43.66 56.34 .02 255 Amnicon 8.31 .35 .58 .29 16.27 .00 83.73 .13 256 Upper Tamarack 17.31 .48 .59 1.11 4.76 13.69 81.55 .02 257 Turtle Cr 2 28.63 .38 .52 1.21 .00 17.38 82.63 .03 258 Whitewater Cr 12.49 .43 .49 .98 .00 .00 100.00 .04 259 Token Cr 9.25 .44 .63 .61 .00 .00 100.00 .26 260 Yahara 5.86 .39 .47 1.06 .00 .00 100.00 .06 261 Oconomowoc 10.59 .35 .50 1.30 7.53 .00 92.47 .16 262 Milwaukee 51.87 .42 .60 1.75 .00 40.00 60.00 .01 263 Cedar Cr 21.64 .36 .47 .56 2.72 8.31 88.97 .03 264 Sauk 2.72 .26 .30 .77 -- -- -- .02 265 Stoney 4.64 .28 .35 9.24 5.56 9.44 85.00 .08 266 North Branch Milwaukee 12.01 .39 .51 .18 .00 8.30 91.70 .12 267 West Branch Rock 17.39 .48 .65 .03 16.94 21.67 61.39 .03 268 Onion 16.09 .22 .34 4.45 .00 56.96 43.04 .01 269 South Branch Sheboygan 4.91 .26 .32 5.39 20.41 40.31 39.29 .00

### Appendixes 121

Percent

silt Percent sand Percent gravel Percent rockysubstrate embeddedness Percent stream bottom covered by algae Percent
macrophytes Percent
cover Percent stream shaded Percent streambank with erosion Buffer width

(m)

12.06 56.88 8.06 80.19 0.00 0.00 7.90 39.50 33.25 20.00 2.11 40.39 41.05 45.72 .00 .00 15.35 19.01 3.55 10.26

.00 21.72 30.94 28.44 .63 .00 11.13 24.38 22.34 12.66 .00 28.38 36.56 13.94 4.06 .31 1.63 27.81 9.13 18.25 4.90 52.71 25.10 72.71 .00 1.04 3.99 49.79 2.29 19.71 2.31 25.50 44.56 17.56 .13 10.19 13.00 17.50 12.63 19.63 28.54 16.67 18.75 48.56 .00 .83 16.79 32.02 4.42 10.00

3.88 23.38 29.63 25.06 1.13 15.38 22.58 14.44 8.75 19.78 17.88 32.50 27.88 56.35 .00 1.25 5.67 32.12 28.85 10.00 11.15 20.19 35.58 37.69 .00 3.27 20.73 34.13 2.69 10.00

1.69 22.50 33.31 25.00 .25 6.50 12.77 1.81 7.25 16.50 5.58 73.56 12.98 72.02 .00 1.54 28.23 33.37 4.23 9.62 12.94 45.50 24.75 55.81 .00 .06 11.51 .00 6.00 19.38 4.04 10.77 66.15 11.06 .00 4.71 9.84 30.77 10.38 10.00 2.00 11.63 58.00 7.88 .13 .06 3.86 2.69 11.13 20.00

.00 5.75 37.31 10.44 2.63 .00 15.04 4.19 5.88 19.25 27.19 27.92 16.88 72.92 .00 12.81 2.78 24.38 6.88 10.00

4.81 25.06 25.00 24.25 .75 1.31 6.50 12.44 .75 19.63 3.65 84.42 7.50 87.12 .00 3.37 10.75 32.46 35.38 9.65 5.52 44.90 27.40 53.85 .00 6.35 .55 9.17 .42 8.79 14.20 85.11 .68 97.73 .00 31.70 4.19 .34 .00 10.00

.13 71.00 15.75 64.31 1.00 .00 8.47 11.81 25.00 20.00 1.50 27.19 38.81 33.31 .00 1.19 20.45 23.44 3.88 20.00 35.00 46.63 4.52 87.31 .77 34.33 18.47 2.02 13.27 10.00

2.79 24.71 42.31 22.88 1.54 6.63 16.89 11.63 12.12 9.85 1.81 51.88 26.75 28.91 18.19 8.69 10.54 7.44 23.38 20.00 12.50 55.38 20.63 63.00 21.13 50.63 65.52 10.75 6.63 20.00 33.64 51.48 8.30 85.11 .91 7.61 4.89 39.55 2.73 20.00

2.83 75.00 12.50 64.17 4.50 18.75 13.78 16.58 11.50 1.30 47.19 28.23 5.42 87.19 .10 1.56 1.83 11.98 .63 9.63

.38 11.25 27.69 8.63 2.19 31.44 12.17 4.00 3.00 15.48 6.18 26.91 38.09 31.71 .00 .86 4.34 52.43 20.79 12.82
7.98 31.83 34.90 41.92 19.23 .19 .77 .00 37.31 13.04 13.75 55.42 18.02 62.50 .00 .00 .00 40.94 21.25 20.00 42.13 24.81 18.94 70.50 .00 3.06 9.62 19.88 5.88 20.00 15.92 6.33 19.00 28.42 5.00 .00 16.27 45.33 18.00 9.53 2.50 9.69 19.94 18.25 24.00 .25 10.08 36.88 10.63 11.10

.21 12.40 20.21 11.25 40.83 .00 14.84 13.96 3.75 20.00

### 122 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 2. Physical-habitat characteristics of each of the 240 studied wadeable streams in Wisconsin—Continued. All data collected by the Wisconsin Department of Natural Resources.
[Cr, Creek; Trib, Tributary; Br, Brook; ID, identification number; m/km, meter per kilometer; m, meter; --, no data collected a t site]

ID (see fig. 4) Stream name Stream width

(m) Stream
mean depth

(m) Mean thalweg

depth

(m) Stream gradient (m/km) Percent pools Percent riffle Percent
run Depth of sediment on stream bottom (m)
270 Meeme 4.25 .21 .27 2.80 0.00 37.86 62.14 0.01 271 Silver Cr 4.41 .51 .59 3.08 24.14 .00 75.86 .02 272 South Branch Manitowoc 18.47 .38 .46 .51 .00 7.86 92.14 .02 273 Manitowoc 27.93 .44 .64 1.12 16.42 28.64 54.94 .01 274 East Twin 12.96 .36 .45 1.30 6.74 20.43 72.83 .02 275 Neshota 5.03 .13 .17 1.11 18.30 12.50 69.20 .04 276 Kewaunee 16.44 .36 .47 .86 .00 30.44 69.56 .01 277 East 6.35 .44 .55 .68 53.36 .00 46.64 .16 278 Duck Cr 10.80 .27 .35 2.19 13.51 25.33 61.16 .01 301 Vismal Cr -- -- -- -- -- -- -- -- 302 Levis Cr -- -- -- -- -- -- -- -- 303 Ditch #6 South Branch Ten Mile Cr -- -- -- -- -- -- -- --

304 South Branch Suamico -- -- -- -- -- -- -- -- 305 West Branch Red -- -- -- -- -- -- -- --

### Appendixes 123

Percent

silt Percent sand Percent gravel Percent rockysubstrate embeddedness Percent stream bottom covered by algae Percent
macrophytes Percent
cover Percent stream shaded Percent streambank with erosion Buffer width

(m)

5.94 22.29 53.44 26.04 5.00 1.56 8.57 24.06 12.29 8.92 4.42 22.88 37.50 26.54 37.40 4.04 5.88 .38 1.54 6.92 6.50 16.19 42.06 26.75 .00 .00 14.72 26.88 12.25 13.88 1.00 11.06 35.19 12.06 .38 .00 11.71 8.94 14.13 20.00 7.38 21.56 45.63 24.50 .00 .00 1.85 61.00 7.88 9.85 11.70 26.07 40.98 41.88 1.79 .00 .00 65.18 56.61 10.00 5.31 11.80 27.19 21.72 10.16 .00 5.88 9.06 1.41 14.97 16.50 45.00 5.75 91.00 .00 .00 7.18 77.00 59.50 15.97

.25 12.81 28.88 15.94 .13 .00 8.71 26.50 8.00 16.83

-- -- -- -- -- -- -- -- -- --

-- -- -- -- -- -- -- -- -- --

-- -- -- -- -- -- -- -- -- --

-- -- -- -- -- -- -- -- -- --

-- -- -- -- -- -- -- -- -- --

### 124 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 3. Diatom nutrient-tolerance ranking for individual diatom taxa. Taxa without nutrient-tolerance values are not included in the table.
[nutrient-tolerance ranking: 1, oligotrophic; 2, oligo-mesotrophic; 3, mesotrophic; 4, meso-eutrophic; 5, eutrophic; 6, hypereu trophic; var, variety]

Diatom taxa Nutrient-tolerance ranking Achnanthidium exiguum 2 Achnanthidium hungaricum 6 Achnanthidium minutissimum 2 Amphipleura pellucida 2 Amphora ovalis 5 Amphora ovalis var. affinis 5 Amphora ovalis var. pediculus 5 Amphora perpusilla 5 Amphora veneta 5 Aulacoseira granulata 5
Aulacoseira italica 3 Brachysira brachysira 1 Caloneis bacillum 4 Cocconeis pediculus 5 Cocconeis placentula var. euglypta 5 Cocconeis placentula var. lineata 5 Cocconeis placentula var. placentula 5 Craticula accomoda 1 Craticula buderi 3 Craticula cuspidata 3 Cyclostephanodiscus species 5 Cyclotella atomus 1 Cyclotella radiosa 1 Cymbella affinis 5 Cymbella naviculiformis 2 Cymbella tumida 2 Cymbella tumidula 3 Diatoma vulgare 1 Discotella stelligera 1 Encyonema minutum 5 Encyonema silesiacum 3 Eolimna minima 3 Eolimna subminuscula 5 Epithemia adnata 3 Epithemia sorex 5 Epithemia species 5 Epithemia turgida 5 Eunotia formica 5
Eunotia incisa 5 Diatom taxa Nutrient-tolerance ranking Eunotia naegelii 4 Eunotia pectinalis var. undulata 5
Eunotia sudetica 2 Fallacia pygmaea 5 Fistulifera pelliculosa 2 Fragilaria capucina (several var.) 3 Fragilaria crotonensis 2 Fragilaria vaucheriae 3 Frustulia rhomboides 4 Frustulia saxonica 1 Frustulia vulgaris 4 Geissleria decussis 4 Gomphoneis minutum 1 Gomphoneis olivacea 2 Gomphonema acuminatum 2 Gomphonema acuminatum var. pusilla 2 Gomphonema affine 3 Gomphonema apuncto 1 Gomphonema gracile 1 Gomphonema parvulum 2 Gomphonema truncatum 4 Gyrosigma attenuatum 5 Gyrosigma spencerii 5 Hippodonta capitata 1 Melosira varians 1 Meridion circulare 3 Navicula angusta 2 Navicula antonii 5 Navicula arvensis 4 Navicula capitatoradiata 5 Navicula gottlandica 5 Navicula gregaria 5 Navicula lanceolata 5 Navicula minuscula 4 Navicula radiosa 4 Navicula rostellata 5 Navicula tenelloides 5 Navicula tripunctata 5 Navicula trivialis 5

### Appendixes 125

Diatom taxa Nutrient-tolerance ranking
Navicula veneta 5 Navicula viridula 5 Nitzschia acicularis 5 Nitzschia amphibia 5 Nitzschia capitellata 6 Nitzschia dissipata 4 Nitzschia fonticola 4 Nitzschia frustulum 5 Nitzschia gracilis 3 Nitzschia inconspicua 5 Nitzschia linearis 4 Nitzschia nana 3 Nitzschia palea 6 Nitzschia paleacea 5 Nitzschia pusilla 4 Parlibellus protracta 5 Placoneis exigua var. capitata 4 Planothidium dubium 5
Planothidium lanceolatum 5
Psammothidium subatomoides 2
Reimeria sinuata 3 Rhoicosphenia curvata 5 Rhopalodia gibba 5
Rossithidium linearis 1 Sellaphora pupula 4 Sellaphora rectangularis 4 Sellaphora seminulum 5 Stauroneis anceps 4
Staurosira construens 4
Staurosira construens var. binodis 6
Staurosira construens var. venter 4 Staurosira elliptica 5 Staurosirella leptostauron 4 Staurosirella leptostauron var. dubia 4 Staurosirella pinnata 4 Staurosirella pinnata var. intercedens 5 Stenopterobia delicatissima 1 Stephanocyclus meneghiana 4 Surirella angusta 5 Diatom taxa Nutrient-tolerance ranking
Surirella linearis 2 Synedra delicatissima 3 Synedra filiformis var. exilis 2 Synedra parasitica 4 Synedra rumpens 2 Synedra rumpens var. familiaris 2 Synedra ulna var. amphirhynchus 5 Synedra ulna var. contracta 3 Tabellaria fenestrata 2 Tabellaria flocculosa 3 Tabellaria flocculosa strain IV 3 Tabularia fasciculata 5 Thalassiosira weissflogii 6 

### Appendix 3. Diatom nutrient-tolerance ranking for individual diatom taxa. Taxa without nutrient-tolerance values are not included in the table—Continued.
[nutrient ranking: 1, oligotrophic; 2, oligo-mesotrophic; 3, mesotrophic; 4, meso-eutrophic; 5, eutrophic; 6, hypereutrophic; v ar, variety]

### 126 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 4. Biological data for each of the 240 studied wadeable streams in Wisconsin. All data collected by the Wisconsin Department of Natural Resources.
[CR, Creek; TRIB, Tributary; BR, Brook; ID, identification number EPT, Ephemeroptera, Plecoptera, or Trichoptera; mg/m 2 , milligram per square meter; --, no data collected at site]

ID (see fig. 4) Stream name Benthic chlorophyll a (mg/m 2 ) Diatom Nutrient

Index Diatom Siltation

Index Diatom Biotic Index Hilsenhoff Biotic Index Percent EPT number Percent EPT taxa Percent scrapers

1 Onion -- 4.38 15.10 35.86 2.19 59.69 34.29 1.53 2 Thompson 155 5.16 67.93 22.76 3.46 66.40 37.93 .00 3 Parker 355 3.43 21.80 38.66 3.87 53.85 55.88 23.08 4 Catlin 31 3.98 27.50 32.68 2.07 75.37 55.56 14.18 5 Leo 54 3.47 14.00 43.02 1.84 68.61 38.46 6.73 6 Lower Ox 64 4.10 27.25 32.00 2.47 73.13 74.29 41.85 7 Lord 165 2.14 4.20 92.25 2.07 77.56 57.58 25.64 8 Fivemile 256 2.07 5.25 85.20 4.26 90.00 63.89 5.91 9 Cap -- -- -- -- 4.36 59.20 45.45 16.42 10 Spring Cr 654 3.69 9.20 48.09 4.42 53.79 44.00 35.61 11 Mosquito Br 227 4.34 9.04 44.29 2.18 74.32 56.25 9.29 12 Smith Lake 22 3.76 44.83 31.67 7.15 10.22 12.12 6.57 13 Fiddler 189 3.54 10.10 47.52 4.24 49.37 44.83 34.81 14 Spring Lake -- 2.82 13.40 50.54 5.95 32.61 25.93 1.45 15 Rainbow -- 3.01 18.80 44.15 5.42 50.72 32.20 6.52 16 Dody Brook 16 3.38 15.20 42.74 3.08 77.47 40.00 37.36 17 Swan 2,544 1.75 21.31 58.66 3.63 90.09 72.41 7.76 18 Becky 569 2.38 11.80 59.21 2.36 71.15 66.67 13.46 19 Hay 228 4.47 16.67 34.22 6.22 29.37 16.67 3.97 20 Soft Maple 446 4.29 58.33 27.27 3.57 70.18 52.83 15.54 21 Mcdermott 929 3.36 29.60 37.07 5.22 89.50 45.45 4.50 22 Meadow Cr -- -- -- -- 6.16 6.58 10.00 2.63 23 Gilbert Cr -- -- -- -- 4.64 11.24 24.14 62.13 24 Trib 1 Shoulder Cr -- -- -- -- 7.57 4.27 2.78 5.49 25 Crazy Horse Cr -- -- -- -- 4.93 22.29 10.00 2.29 26 Alder Cr -- -- -- -- 5.67 29.80 13.51 1.32 27 Sailor Cr -- -- -- -- 2.44 70.11 54.55 21.26 28 Knuteson 737 1.84 3.25 100.00 3.28 59.75 48.65 55.08 29 South Fork Hemlock 87 4.78 8.50 43.39 3.32 75.36 61.11 8.70 30 Little Soft Maple 2,197 2.07 20.60 58.96 2.28 71.23 58.00 20.89 31 Alvin 239 3.05 11.05 50.67 2.62 75.91 66.67 27.74 32 North Otter 23,122 4.01 22.50 34.00 2.21 59.24 50.00 32.35 33 North Fork Thunder 80 4.53 2.60 72.84 .84 86.59 66.67 11.59 34 Waupee 318 3.14 7.47 57.72 4.92 53.59 21.43 .00 35 Trout -- -- -- -- 4.42 49.37 29.63 23.63 36 South Fork Popple -- -- -- -- 7.64 6.54 5.26 14.95 37 Mosquito Cr 76 2.43 9.70 61.55 6.55 36.56 30.43 .54 38 Hay Meadow 977 3.14 15.32 45.00 5.46 47.92 36.96 3.65

### Appendixes 127

Percent shredders Number of taxa Fish index of biotic integrity Percent carnivores Percent insectivores Percent omnivores Percent intolerant species Percent tolerant species Number of fish Number of fish species 0.51 35.00 80.00 77.61 22.39 0.00 23.13 0.00 89 9

.00 29.00 90.00 68.35 29.11 .00 86.08 2.53 55 6 1.40 34.00 45.00 40.30 21.39 6.47 12.44 38.81 96 16

.00 27.00 90.00 97.87 2.13 .00 97.87 2.13 45 2 .00 26.00 60.00 11.24 48.31 5.62 12.36 20.22 82 11 .00 35.00 42.00 1.43 67.91 6.24 1.96 30.48 130 15 .00 33.00 20.00 .00 39.87 21.52 .00 51.27 95 9 .91 36.00 15.00 1.67 20.00 1.67 .83 85.00 83 10 .00 44.00 20.00 .00 37.18 7.69 1.28 66.67 53 8 .00 25.00 25.00 1.67 83.33 .00 .00 77.50 106 6 .00 32.00 90.00 89.83 10.17 .00 81.36 .00 55 4 .73 33.00 30.00 20.00 71.43 8.57 .00 80.00 95 4 .00 29.00 50.00 7.89 81.58 2.63 44.74 23.68 34 8 4.35 27.00 30.00 2.88 58.27 17.99 12.95 48.20 93 10 3.14 59.00 80.00 58.04 28.57 2.68 78.57 9.82 75 8

.00 25.00 21.00 .00 46.94 19.97 .58 50.73 457 10 .00 29.00 50.00 30.63 21.35 17.63 35.50 50.81 291 16 .00 36.00 60.00 34.07 24.73 7.14 53.85 32.97 182 9
.79 24.00 30.00 .00 43.00 7.00 2.00 48.00 97 10 .00 53.00 32.00 1.08 31.89 18.38 2.70 65.41 66 12 .00 22.00 25.00 2.31 31.02 10.42 8.33 61.34 281 10 4.61 30.00 35.00 .00 66.19 1.64 .00 48.16 128 8

.00 29.00 40.00 .00 55.01 1.16 4.67 45.31 237 13 18.90 36.00 30.00 .00 80.24 3.12 3.43 52.92 214 13 14.86 30.00 32.00 .00 60.58 3.01 2.15 12.67 233 10

.00 37.00 35.00 .00 46.07 8.86 1.30 30.09 192 13 .00 33.00 17.00 .00 22.65 1.91 .96 70.55 157 13 .00 37.00 55.00 19.32 47.16 18.18 15.34 34.66 62 16 .00 36.00 70.00 73.38 4.32 3.60 58.99 22.30 97 12 .68 50.00 40.00 7.01 10.83 5.73 7.01 76.43 157 11 1.46 33.00 50.00 17.07 18.29 .00 31.71 65.85 78 7

.00 36.00 60.00 64.48 1.64 .00 64.48 33.33 130 5 .00 33.00 90.00 70.00 27.50 .00 67.50 2.50 25 7 .00 42.00 40.00 1.39 75.00 6.94 1.39 37.50 45 9 .00 27.00 32.00 .00 49.17 5.48 4.24 52.38 414 14 4.05 38.00 30.00 .00 56.65 7.98 1.60 42.29 63 12 2.69 46.00 40.00 20.69 75.86 .00 20.69 13.79 20 9 1.56 46.00 40.00 1.59 82.17 3.82 10.83 21.34 285 12

### 128 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 4. Biological data for each of the 240 studied wadeable streams in Wisconsin—Continued. All data collected by the Wisconsin Department of Natural Resources.
[Cr, Creek; Trib, Tributary; Br, Brook; ID, identification number EPT, Ephemeroptera, Plecoptera, or Trichoptera; mg/m 2 , milligram per square meter; --, no data collected at site]

ID (see fig. 4) Stream name Benthic chlorophyll a (mg/m 2 ) Diatom Nutrient

Index Diatom Siltation

Index Diatom Biotic Index Hilsenhoff Biotic Index Percent EPT number Percent EPT taxa Percent scrapers 39 Cedar Springs 3,419 1.94 10.46 67.65 5.98 32.62 37.93 0.53 40 Skunk Cr 505 2.96 10.61 52.41 5.76 65.54 36.00 7.43 41 Jennie 315 2.78 14.02 50.41 3.90 69.73 45.65 24.04 42 Trout 449 3.01 7.71 58.39 4.90 27.03 37.14 17.57 43 Muskellunge – Heafford Junction -- 2.61 27.37 46.45 7.41 7.35 20.83 .74

45 Johnson 347 2.01 12.94 64.27 5.35 28.83 28.26 9.82 46 Threemile 293 2.99 65.46 37.37 7.82 2.63 15.79 .00 47 Raeder Cr 19 4.37 48.21 27.48 4.06 47.26 51.61 23.29 48 Hamann Cr 117 3.13 42.39 37.37 4.45 62.94 34.29 26.40 49 East Fork Hamann -- -- -- -- 4.75 24.83 27.27 46.21 50 Hamann Trib 11 4.31 55.66 27.35 4.61 47.37 40.48 30.70 51 Widow Green 1,629 3.81 49.17 30.93 4.33 25.50 45.83 61.92 52 North Fork Willow 196 4.11 69.21 27.85 6.91 44.33 17.14 .99 53 Black Brook 553 3.63 54.42 31.92 4.88 44.98 33.33 14.83 54 South Fork Willow 470 4.28 64.88 27.04 5.67 11.43 15.63 1.14 55 Hutton Cr 1,222 4.63 33.10 27.94 4.91 40.00 20.83 5.45 56 Tenmile Cr 1,029 4.52 27.89 29.52 3.13 58.27 52.17 33.09 57 Cr 12–13 2,000 3.85 72.33 29.41 4.26 52.17 53.33 2.54 58 Running Valley 16,672 4.09 76.94 27.71 7.53 5.33 8.00 .59 59 Cr 1–8 -- 3.84 51.60 30.52 7.47 7.97 26.09 .00 60 Cr 1–12 -- 4.42 48.90 27.18 4.88 61.19 33.33 .00 61 18-mile 3,915 4.07 18.35 35.50 3.15 51.59 42.55 35.69 62 Cady 5,970 3.01 28.01 63.68 3.67 84.65 58.33 14.11 63 Eagle 8,368 3.82 71.79 42.88 4.34 39.95 34.38 34.80 64 Joos -- -- -- -- 4.28 42.52 41.94 36.92 65 Trout Run -- -- -- -- 2.51 68.63 36.36 .65 66 Bohris 3,924 4.40 60.19 39.54 3.27 47.92 52.94 50.52 67 South Branch Oneill Cr -- -- -- -- 6.87 23.67 15.63 10.06 68 Unnamed Trib 1 East Fork Black 7 2.98 5.54 68.10 3.71 73.19 52.00 30.43

69 Unnamed Trib 1 Rock Cr -- 3.88 47.60 30.56 5.52 61.83 18.52 10.22 70 Bloody Run -- 4.88 3.30 71.19 4.16 24.82 25.93 5.67 71 Beaver Cr -- -- -- -- 5.97 34.78 35.71 27.33 72 Tributary To Beaver Cr -- -- -- -- 4.66 54.55 44.00 42.42 73 North Fork Hemlock Cr -- -- -- -- 7.01 10.30 20.00 1.82 74 Mormon -- 3.97 62.88 42.50 4.35 34.73 38.71 37.25 75 Timber Coulee -- 3.46 28.13 57.65 3.62 34.75 43.75 24.82

### Appendixes 129

Percent shredders Number of taxa Fish index of biotic integrity Percent carnivores Percent insectivores Percent omnivores Percent intolerant species Percent tolerant species Number of fish Number of fish species 2.67 29.00 0.00 7.14 71.43 7.14 0.00 92.86 14 4

.00 25.00 10.00 .00 85.37 4.88 2.44 92.68 26 5 .00 46.00 40.00 1.00 23.38 1.49 15.92 55.22 112 14 .68 35.00 60.00 46.43 14.29 10.71 57.14 42.86 25 5 .00 24.00 .00 9.52 47.62 28.57 9.52 47.62 10 7

1.23 46.00 45.00 2.47 74.38 5.56 4.01 24.07 145 11

.66 19.00 30.00 1.49 24.25 3.73 1.49 64.18 211 8 .00 31.00 30.00 .00 37.37 4.39 10.70 62.02 325 14 .00 35.00 37.00 .00 43.02 9.04 9.72 48.62 332 19 .00 22.00 45.00 .88 47.05 15.61 3.53 69.29 113 13 .44 42.00 42.00 .00 24.61 12.98 5.09 55.73 290 17 .00 24.00 .00 .00 22.22 29.63 .00 51.85 40 4 .00 35.00 25.00 .00 17.77 17.77 .00 18.18 224 7 .00 42.00 32.00 .00 42.17 3.21 1.61 58.63 189 13 .00 32.00 20.00 .00 38.46 5.77 2.88 59.62 87 12 1.21 48.00 40.00 .72 11.69 21.36 2.45 49.78 289 15

.00 23.00 22.00 .00 20.63 17.62 .00 57.23 342 13 .36 30.00 .00 53.33 46.67 .00 53.33 46.67 14 2 .00 25.00 50.00 9.63 52.75 7.80 19.27 37.16 182 10 .00 23.00 70.00 16.67 80.56 2.78 16.67 5.56 33 4 .00 24.00 .00 6.67 93.33 .00 6.67 .00 14 2 .00 47.00 .00 28.57 71.43 .00 28.57 28.57 13 4 .00 24.00 90.00 38.78 58.68 .00 93.03 2.53 426 6 .00 32.00 30.00 .00 52.56 38.46 .00 47.44 174 6 .00 31.00 15.00 .00 7.57 54.98 .00 81.67 234 9 .00 22.00 32.00 .86 57.76 39.66 1.72 45.69 113 9 .00 17.00 52.00 2.59 81.61 9.20 2.87 15.23 266 16 .00 32.00 40.00 .00 43.75 30.21 3.29 58.39 738 19 .00 25.00 30.00 1.96 26.96 28.92 .98 76.47 101 12

.00 27.00 50.00 .00 56.28 4.21 3.16 75.07 96 11 .00 27.00 100.00 66.07 28.57 1.79 87.50 3.57 51 7 .00 14.00 47.00 .00 44.26 19.78 7.65 62.92 333 20 .00 25.00 45.00 .00 46.86 13.51 7.89 64.20 224 17 8.48 30.00 37.00 .00 78.55 4.39 1.46 68.87 208 12

.00 31.00 20.00 1.63 33.70 54.08 .00 62.77 135 9 .00 32.00 60.00 65.23 28.30 6.47 20.49 6.47 206 5

### 130 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 4. Biological data for each of the 240 studied wadeable streams in Wisconsin—Continued. All data collected by the Wisconsin Department of Natural Resources.
[Cr, Creek; Trib, Tributary; Br, Brook; ID, identification number EPT, Ephemeroptera, Plecoptera, or Trichoptera; mg/m 2 , milligram per square meter; --, no data collected at site]

ID (see fig. 4) Stream name Benthic chlorophyll a (mg/m 2 ) Diatom Nutrient

Index Diatom Siltation

Index Diatom Biotic Index Hilsenhoff Biotic Index Percent EPT number Percent EPT taxa Percent scrapers 76 Spring Coulee 19,863 3.42 67.49 47.54 3.62 45.43 37.50 19.29 77 Rush-02 16,047 4.13 43.51 44.80 3.81 52.82 39.29 30.26 78 Beaver 12,290 4.16 77.78 39.45 4.42 47.00 46.43 37.60 79 Dilly -- -- -- -- 4.55 53.91 39.39 32.35 80 Trib West Branch Baraboo 500 4.65 17.21 59.15 2.77 55.83 38.10 38.65 81 Crooked 2,690 3.47 69.41 46.70 3.40 60.89 41.67 9.68 82 Moore 7,423 4.07 77.19 40.22 4.05 49.74 37.93 56.92 83 Warner Br 730 3.97 73.25 41.36 3.78 17.00 37.84 59.65 84 Warner 93 4.35 37.62 45.00 2.42 68.46 52.63 36.91 85 Otter Cr – Lafarge 3,832 4.55 47.25 40.83 3.41 38.43 42.86 56.33 86 Harrison 9,024 3.78 72.64 43.18 4.20 48.57 50.00 36.00 87 Mccartney Br -- -- -- -- 4.76 65.36 32.14 22.88 88 Hackett Br 3,771 4.00 90.03 39.87 4.80 36.47 32.35 24.71 89 Kuenster 1,239 4.44 57.28 39.71 4.90 63.22 35.00 27.59 90 Muskellunge Cr – Beetown 21,785 4.14 79.05 39.43 5.56 22.22 14.29 9.66

91 Bull 10,157 3.46 68.83 46.87 5.97 14.12 13.04 20.00 92 Willow 25,755 4.07 82.41 39.80 4.59 25.39 27.27 26.94 93 Mounds Br -- -- -- -- 5.23 17.19 9.09 5.63 94 Young Br 3,094 3.88 79.57 41.68 5.37 68.51 33.33 18.78 95 Mcadam Br 5,905 4.02 84.19 40.01 5.02 61.79 23.26 12.62 96 Indian Cr – Dickeyville 12,262 4.14 68.52 40.44 7.21 12.43 40.00 .56 97 Kieler Cr 9,107 3.97 60.16 42.91 8.01 .00 .00 .00 98 Apple 3,446 4.93 13.79 64.88 4.34 7.03 27.78 85.41 99 Trib 1 French Spring Cr 3,537 4.28 59.74 40.48 5.01 8.44 16.67 53.90 100 Rowan 264 2.88 10.61 95.68 3.41 32.16 35.29 44.31 101 Hinkson -- -- -- -- 4.42 33.55 28.57 .66 102 North Branch Honey 3,915 3.97 78.58 40.92 5.54 28.88 29.41 1.07 103 Moen 7,491 4.43 47.68 41.58 4.01 35.37 51.85 30.61 104 Trout Cr – Barneveld 7,706 2.99 45.73 56.91 5.12 9.78 36.36 8.00 105 Lowery 11,216 3.16 64.61 51.15 3.81 29.91 35.00 14.53 106 Trib Otter Cr 6,954 4.59 73.90 36.66 4.29 52.60 35.29 30.96 107 Bear 5,507 4.60 74.31 36.59 4.71 41.35 36.11 3.76 108 Horse 1,517 3.80 78.88 42.47 3.87 38.27 55.00 52.35 109 Brush 4,598 3.47 52.79 49.03 4.14 49.45 37.50 39.34 110 East Mill 6,620 4.06 82.35 39.87 4.19 30.34 38.46 17.24 111 Trib 1 Dead Cr -- 5.41 85.67 31.20 9.08 .54 3.57 1.63 112 Johnson Cr – Farmington 1,077 4.15 75.16 39.69 4.41 13.83 13.33 .00 113 Calamus Cr 3,455 4.99 68.88 34.81 7.31 8.56 17.24 1.60

### Appendixes 131

Percent shredders Number of taxa Fish index of biotic integrity Percent carnivores Percent insectivores Percent omnivores Percent intolerant species Percent tolerant species Number of fish Number of fish species 0.00 32.00 60.00 81.20 10.20 7.40 1.40 7.40 203 6

.00 28.00 50.00 43.59 31.41 .00 32.05 25.00 158 6 .00 28.00 30.00 .14 41.64 23.37 .00 41.78 636 12 .00 33.00 45.00 .00 75.58 8.43 8.72 22.97 297 11 .00 21.00 35.00 .57 85.63 2.30 77.01 13.79 166 8 .00 24.00 60.00 100.00 .00 .00 .00 .00 93 2 .00 29.00 40.00 1.26 51.13 24.69 .76 42.82 186 14 .00 37.00 30.00 .00 40.72 1.70 1.14 56.63 459 8 .00 19.00 30.00 .74 52.96 15.19 5.19 44.44 151 12 .00 28.00 30.00 1.07 57.22 13.37 2.14 37.70 163 11 .00 24.00 20.00 5.17 35.63 31.61 1.72 57.47 139 8 .00 28.00 10.00 .00 8.56 60.48 .00 63.12 228 9 .39 34.00 37.00 .00 72.88 .00 .00 13.87 476 9 .00 20.00 15.00 .11 32.17 50.88 .11 51.97 1004 14
.00 42.00 20.00 .32 42.07 42.03 .32 43.12 1483 14

.00 23.00 20.00 .07 26.33 48.94 .20 53.79 693 15 .00 33.00 30.00 .63 53.13 23.44 5.31 30.31 691 15 .00 33.00 40.00 .00 50.94 3.77 .00 32.48 294 11 .00 27.00 20.00 .34 21.13 15.35 .34 26.44 292 13 .33 43.00 45.00 .00 70.71 3.21 .00 4.58 391 13
.00 20.00 .00 -- -- -- -- -- -- 1 .00 8.00 30.00 .00 6.83 29.93 .00 31.51 432 9 .00 18.00 40.00 .00 25.10 14.82 .05 17.21 1336 15 1.30 30.00 65.00 .56 43.33 38.57 9.24 69.92 269 10

.00 17.00 50.00 11.25 83.25 5.50 83.00 5.50 308 4 .00 28.00 70.00 40.64 58.90 .00 84.02 14.61 187 5 .00 34.00 45.00 .40 64.94 6.37 52.59 22.71 246 11 .00 27.00 .00 4.35 78.26 .00 82.61 4.35 22 5 .00 22.00 70.00 25.79 69.68 4.52 70.14 4.52 143 5 .00 20.00 60.00 2.67 81.33 .00 45.33 16.00 60 4 .00 34.00 25.00 .37 36.48 38.21 1.74 58.44 405 13 .00 36.00 25.00 10.43 15.95 26.38 21.47 65.64 98 9 .00 20.00 35.00 .00 31.25 11.72 10.16 72.66 115 10 .00 24.00 80.00 64.75 22.13 8.20 77.05 15.57 111 9 .00 26.00 22.00 .64 11.92 19.65 .00 85.19 518 7 3.80 28.00 20.00 .00 96.83 3.17 .00 100.00 95 3

.00 15.00 40.00 .00 94.38 2.76 .00 89.47 263 8
2.14 29.00 12.00 .00 29.13 70.87 .00 98.70 193 9

### 132 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 4. Biological data for each of the 240 studied wadeable streams in Wisconsin—Continued. All data collected by the Wisconsin Department of Natural Resources.
[Cr, Creek; Trib, Tributary; Br, Brook; ID, identification number EPT, Ephemeroptera, Plecoptera, or Trichoptera; mg/m 2 , milligram per square meter; --, no data collected at site]

ID (see fig. 4) Stream name Benthic chlorophyll a (mg/m 2 ) Diatom Nutrient

Index Diatom Siltation

Index Diatom Biotic Index Hilsenhoff Biotic Index Percent EPT number Percent EPT taxa Percent scrapers
114 Schultz Cr 2,907 4.72 8.50 89.24 4.68 7.60 25.00 43.27 115 Pratt Cr 24,862 3.76 17.43 65.69 6.01 34.36 36.36 18.40 116 Trib Pratt Cr -- -- -- -- 6.13 1.01 7.14 5.05 117 Casper Cr 8,196 4.26 50.33 42.22 5.50 .79 5.56 16.67 118 Scuppernong 252 3.27 9.71 94.51 6.20 36.97 31.82 1.82 119 Door Cr 1,115 4.74 35.42 43.28 4.52 53.88 28.57 19.40 120 Little Door Cr 279 2.86 19.67 73.77 5.66 7.14 31.25 1.95 121 Branch Mineral Point 4,924 4.12 69.95 40.45 4.57 13.38 27.59 61.20 122 Gill 1,909 4.47 51.45 40.51 4.10 13.08 57.14 38.46 123 Baker 855 4.54 28.79 47.86 5.85 27.67 31.82 32.08 124 Spring Brook 212 2.50 18.76 77.32 4.42 56.52 53.85 27.72 125 Ore 615 4.18 72.21 39.75 4.36 33.82 42.31 57.88 126 Bassett Cr 1,954 4.83 15.45 61.42 7.49 11.61 18.75 .65 127 West Branch Nippersink 559 4.55 49.51 40.36 4.87 49.68 29.63 2.55 128 White Cr 8,993 4.68 34.11 44.18 3.99 2.92 10.00 1.46 129 Pumpkinseed Cr -- -- -- -- 7.18 .00 .00 2.96 130 Spring Bk 3,613 4.61 52.81 39.36 5.71 .00 .00 4.14 131 Daggets Cr -- -- -- -- 7.81 4.14 7.14 .00 132 Van Dyne Cr -- -- -- -- 8.01 .00 .00 .00 133 Trib 1 West Branch Fond Du Lac 8,427 3.91 58.18 43.77 7.85 1.04 5.41 1.04

134 Mill Cr 3.97 30.46 51.21 4.28 21.29 40.00 17.42 135 Kankapot Cr 1,680 4.78 70.67 35.84 9.41 .74 12.50 .00 136 Molash 2,850 3.62 76.80 44.39 5.60 63.64 26.09 5.84 137 Grimms -- 4.20 26.07 52.16 7.99 .00 .00 .00 138 Pine Cr – Newton -- -- -- -- 5.81 48.67 37.50 16.67 139 Point Cr -- -- -- -- 5.22 22.11 10.81 47.52 140 Pigeon 1,125 4.65 24.92 49.94 5.24 48.61 20.00 28.70 141 Otter Cr – Plymouth 653 4.75 14.85 63.25 5.22 20.83 36.96 31.25 142 Weedens 5,128 4.51 61.84 38.59 4.98 19.87 13.79 26.94 143 Kettle Moraine 1,518 4.47 44.82 41.95 5.82 39.76 36.36 11.81 144 West Branch Milwaukee 13,871 3.99 19.19 60.92 7.63 .00 .00 .29 145 Parnell 311 4.66 50.94 39.34 4.12 57.59 58.33 27.85 146 East Branch Milwaukee 1,376 4.20 16.67 63.27 4.20 32.24 50.00 68.31 147 Crooked 2,051 2.54 6.49 100.00 4.34 84.81 27.78 12.03 148 Wallace 1,528 4.86 29.70 45.37 4.60 55.49 45.16 29.48 149 Hanneman 2,478 4.89 44.39 39.48 4.84 60.83 40.00 34.10 150 Mayfield Cr 3,377 3.51 32.27 54.73 5.46 7.65 33.33 7.65 151 Friedens 8,416 4.47 51.36 40.53 5.67 17.28 55.00 14.73

### Appendixes 133

Percent shredders Number of taxa Fish index of biotic integrity Percent carnivores Percent insectivores Percent omnivores Percent intolerant species Percent tolerant species Number of fish Number of fish species 0.00 12.00 35.00 0.00 95.00 5.00 0.00 6.11 91 4

.00 11.00 25.00 .00 93.87 6.13 .00 77.02 114 4 .00 28.00 40.00 .00 70.68 26.95 .00 68.11 84 9 .00 18.00 55.00 .00 88.52 7.25 .00 35.65 84 10 .00 22.00 50.00 20.75 64.15 11.32 16.98 56.60 50 10 .00 14.00 35.00 .00 65.84 28.30 .00 56.82 74 8 .00 16.00 40.00 .00 100.00 .00 .00 .00 36 1 .00 29.00 40.00 .00 43.20 1.45 .00 18.77 206 9 .00 14.00 27.00 .00 48.15 11.11 3.70 50.00 52 6 .00 22.00 30.00 .00 25.43 3.47 .00 59.54 162 10 .00 26.00 27.00 6.96 16.16 8.08 .28 72.98 249 18 .00 26.00 25.00 .09 14.89 11.89 .00 53.30 908 13 .00 16.00 25.00 .00 36.45 36.61 .00 87.82 213 9 1.91 27.00 40.00 2.22 48.56 29.93 .22 42.35 258 22

.00 10.00 70.00 46.51 51.16 .00 48.84 2.33 30 4 8.37 16.00 45.00 .00 77.16 11.06 10.42 61.54 104 11 2.76 18.00 55.00 .00 90.47 6.86 .00 26.11 131 13 5.33 14.00 10.00 .00 73.03 20.22 .00 49.44 30 6

.00 4.00 .00 41.67 50.00 8.33 .00 50.00 12 5 11.40 37.00 37.00 .00 73.06 1.46 .00 50.36 206 8

.00 15.00 .00 .00 30.41 6.08 .00 69.59 50 6 .00 8.00 .00 .00 44.64 18.75 .00 63.39 38 5 .00 23.00 25.00 .00 96.91 3.00 .00 94.29 733 6 .38 9.00 25.00 1.92 78.85 9.62 .00 92.31 50 6 .00 16.00 25.00 .00 75.63 14.21 .00 52.28 177 8 .00 37.00 40.00 .29 51.70 5.92 3.30 22.21 711 14 .00 30.00 30.00 1.47 52.11 17.77 .00 46.42 865 11 .42 46.00 32.00 1.14 42.24 22.37 1.14 51.83 395 16 .00 29.00 35.00 1.40 20.30 14.59 .00 80.28 626 17 .00 22.00 35.00 .41 69.67 16.60 .00 83.61 271 14 3.79 17.00 17.00 .00 76.88 19.17 1.98 69.96 469 7

.00 24.00 40.00 .00 39.54 2.29 .00 36.60 222 12 .00 26.00 45.00 1.27 66.76 24.73 1.27 32.06 354 17 .00 18.00 35.00 1.67 55.00 .00 .00 45.00 43 10 .00 31.00 35.00 1.67 43.75 13.33 5.42 56.67 170 14 .00 25.00 30.00 .00 37.27 18.03 2.27 64.09 475 13 .00 9.00 35.00 .00 77.55 15.65 .00 86.39 140 9 .00 20.00 30.00 .00 42.42 13.13 .00 61.62 71 10

### 134 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 4. Biological data for each of the 240 studied wadeable streams in Wisconsin—Continued. All data collected by the Wisconsin Department of Natural Resources.
[Cr, Creek; Trib, Tributary; Br, Brook; ID, identification number EPT, Ephemeroptera, Plecoptera, or Trichoptera; mg/m 2 , milligram per square meter; --, no data collected at site]

ID (see fig. 4) Stream name Benthic chlorophyll a (mg/m 2 ) Diatom Nutrient

Index Diatom Siltation

Index Diatom Biotic Index Hilsenhoff Biotic Index Percent EPT number Percent EPT taxa Percent scrapers 152 Pigeon Cr – Theinsville 800 4.53 46.71 41.10 4.23 48.78 38.46 24.39 153 Willow Cr – Germantown 1,303 4.54 17.78 58.93 5.99 6.90 11.76 6.21 154 Little Menomonee 1,305 4.62 59.87 38.14 4.49 25.81 35.71 40.65 155 Husher 912 4.15 61.37 41.22 5.79 15.38 9.52 10.77 156 North Branch Pike 3,424 3.66 59.48 45.88 6.30 .00 .00 1.19 157 Willow Cr – Waupun 550 4.39 28.13 49.36 7.01 4.71 7.69 .52 158 Flynn 221 4.61 27.84 48.01 4.16 79.20 50.00 28.76 201 Galena 12,363 3.79 63.67 44.08 4.58 83.13 33.33 11.08 202 Skinner Cr – Klondyke 23,008 4.67 83.67 35.37 5.64 70.00 43.75 52.14 203 East Branch Pecatonica 2,162 4.68 67.67 36.72 4.27 46.28 40.00 9.57 204 Little Sugar 30,670 4.51 60.33 38.77 4.75 70.06 40.91 18.64 205 West Branch Sugar – #1 4,137 4.56 52.67 39.70 4.71 84.66 60.71 23.93 206 Platte – Rockville 3,114 4.21 72.67 39.51 4.67 36.76 32.56 18.38 207 Pigeon 9,212 4.55 70.00 37.32 5.14 73.06 46.15 16.06 208 Rattlesnake 1,369 4.01 74.33 40.91 6.41 3.87 4.55 2.21 209 Blake 6,691 4.26 76.67 38.77 5.49 10.65 23.33 2.37 210 Fennimore 6,408 4.11 81.00 39.56 5.41 44.53 33.33 4.86 211 Black Earth 1 3,942 4.51 34.33 45.21 5.02 48.89 40.00 25.93 212 Kickapoo 12,823 3.63 34.00 52.73 4.67 62.58 47.22 11.04 213 Moore 4,259 3.87 54.00 44.76 4.60 36.69 37.50 44.60 214 Coon Cr 40,143 3.88 35.33 49.71 4.08 76.42 51.61 24.12 215 Little La Crosse – Sparta -- 4.40 54.00 40.55 4.32 30.14 47.37 11.42 216 Lacrosse 5,539 3.98 41.00 46.83 5.27 68.42 45.45 23.44 217 Eau Galle 2 5,996 3.86 32.33 51.27 3.71 62.79 35.71 20.93 218 Willow 2,517 4.42 24.00 52.24 -- -- -- -- 219 Wood 84 2.46 18.33 52.07 -- -- -- -- 220 Yellow – Barron 457 3.69 40.00 32.66 -- -- -- -- 221 Hay River 903 4.15 42.00 29.30 -- -- -- -- 222 North Fork Eau Claire 1,303 3.71 66.00 30.66 -- -- -- -- 223 Big Eau Pleine 2,856 4.74 95.33 23.75 -- -- -- -- 224 Black 722 4.16 83.33 27.10 -- -- -- -- 225 Yellow – Babcock 902 4.12 55.00 28.48 5.42 29.33 20.00 2.00 226 Little Yellow 752 2.72 45.33 42.17 8.43 1.49 8.70 .00 227 South Branch Yellow 4,043 2.68 34.67 43.97 6.91 15.45 17.65 2.08 228 Ten Mile Cr 5,562 3.77 34.67 32.80 2.20 63.22 41.38 14.94 229 Little Plover 1,711 2.58 25.67 47.24 3.39 28.68 17.65 .78 230 Tomorrow 1,853 3.07 4.67 73.24 2.74 54.93 51.52 19.01 231 Pensaukee – Krakow 1,621 4.80 39.33 26.23 6.63 78.62 23.08 22.64

### Appendixes 135

Percent shredders Number of taxa Fish index of biotic integrity Percent carnivores Percent insectivores Percent omnivores Percent intolerant species Percent tolerant species Number of fish Number of fish species 0.00 13.00 40.00 9.78 56.00 8.44 0.00 48.44 221 12 1.38 17.00 35.00 .76 51.52 30.30 .00 65.91 132 11

.65 14.00 37.00 .00 85.87 9.78 .00 20.65 60 7 .00 21.00 20.00 .00 65.26 27.37 .00 82.11 68 9 .00 15.00 20.00 2.66 23.32 66.62 .00 87.03 248 15 1.05 39.00 30.00 .00 49.14 23.80 .00 54.33 396 14

.00 26.00 15.00 2.36 23.62 5.51 .00 74.02 98 6 .24 24.00 25.00 11.97 41.88 43.59 24.79 46.15 15 12 .00 16.00 10.00 1.85 14.81 51.85 3.70 72.22 23 12 4.79 25.00 32.00 5.58 28.43 46.19 1.52 50.25 34 24

.00 22.00 38.00 13.87 66.47 19.65 65.90 20.23 77 4 .00 28.00 20.00 2.44 15.85 81.10 12.80 81.71 83 11 .00 43.00 47.00 1.19 68.77 7.11 6.52 7.31 89 17 .00 26.00 30.00 2.08 58.31 28.00 3.67 28.36 359 14 .00 44.00 30.00 2.11 64.43 25.51 2.81 26.13 298 15 .59 30.00 20.00 1.54 37.43 52.99 1.60 53.87 598 13 .81 36.00 20.00 .30 6.53 64.09 3.26 80.42 183 11 .00 30.00 40.00 24.20 10.50 65.30 7.31 66.21 50 8 1.23 36.00 35.00 5.22 26.10 25.70 2.81 65.06 39 24

.00 32.00 40.00 .98 33.66 21.38 2.21 62.90 174 20 .00 31.00 50.00 67.31 7.31 25.38 8.46 26.92 54 7 .46 19.00 30.00 65.04 4.88 22.76 .00 30.08 38 5 .00 33.00 52.00 14.00 56.00 6.00 30.00 6.00 9 12 .00 42.00 47.00 .00 77.78 15.07 57.21 19.47 371 13 -- -- 67.00 6.73 75.78 16.59 16.59 16.59 27 15 -- -- 50.00 5.08 83.62 7.91 11.30 11.30 45 18 -- -- 70.00 1.92 49.27 6.34 14.40 7.73 189 33 -- -- 60.00 2.27 47.73 2.27 43.18 20.45 7 14 -- -- 70.00 .67 66.64 12.16 12.99 16.19 406 23 -- -- 74.00 6.10 68.92 .32 15.02 .80 156 21 -- -- 70.00 32.94 55.29 11.76 51.76 11.76 11 11 2.00 30.00 30.00 .00 82.89 10.53 2.63 13.16 18 15

.00 23.00 20.00 5.32 54.26 39.36 5.32 53.19 35 13 9.55 51.00 45.00 1.55 95.36 1.55 1.86 10.84 100 13

.00 29.00 50.00 18.07 46.99 34.94 34.94 36.14 24 9 .00 17.00 70.00 50.42 32.77 16.81 76.47 18.49 49 5 .00 33.00 70.00 59.06 26.17 13.42 46.31 13.42 48 6 .00 13.00 40.00 .00 66.36 9.81 .00 47.20 74 14

### 136 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 4. Biological data for each of the 240 studied wadeable streams in Wisconsin—Continued. All data collected by the Wisconsin Department of Natural Resources.
[Cr, Creek; Trib, Tributary; Br, Brook; ID, identification number EPT, Ephemeroptera, Plecoptera, or Trichoptera; mg/m 2 , milligram per square meter; --, no data collected at site]

ID (see fig. 4) Stream name Benthic chlorophyll a (mg/m 2 ) Diatom Nutrient

Index Diatom Siltation

Index Diatom Biotic Index Hilsenhoff Biotic Index Percent EPT number Percent EPT taxa Percent scrapers
232 Pensaukee – Pensaukee 2,768 4.12 25.37 32.41 4.44 51.01 54.84 64.93 233 Middle Branch Embarrass 1,015 4.36 11.33 40.05 3.70 39.71 41.18 .74 234 Eau Claire – Kelly 2,661 4.28 3.67 74.18 3.08 25.00 31.82 69.74 235 Eau Claire – Antigo 2,997 3.33 28.33 37.61 4.11 78.74 52.17 6.90 236 Spring Brook 2 4,389 3.55 27.33 35.93 4.00 .49 20.00 .00 237 Prairie 1,010 3.71 16.67 38.95 2.58 34.08 50.00 56.95 238 Skinner 139 2.75 44.00 41.77 4.10 42.33 28.57 .00 239 Spirit 447 4.53 9.67 41.94 4.16 84.72 51.52 4.63 240 North Fork Copper 531 4.41 8.33 45.63 3.58 59.02 31.82 23.77 241 Hunting 1,230 3.67 12.00 43.59 3.15 73.95 50.98 43.14 242 Wolf River 705 2.62 9.33 59.30 2.81 69.68 60.53 25.81 243 North Branch Pike 650 2.29 4.67 84.79 2.58 44.19 54.00 30.23 244 Popple 156 2.66 11.67 54.78 2.55 78.42 60.47 29.50 245 Woods 536 4.40 27.33 30.27 1.86 74.60 59.70 26.70 246 Pine 1,280 1.89 3.00 100.00 4.00 99.17 42.86 .00 247 Brule 627 2.40 7.00 69.50 3.62 47.10 38.00 23.87 248 Kaubashine 1,074 3.86 11.67 42.62 7.92 8.59 19.23 4.91 249 Namekagon 137 2.51 3.67 91.15 2.82 51.35 60.47 41.62 250 Totagatic 281 4.63 94.67 24.29 -- -- -- -- 251 Eau Claire 982 4.18 5.00 61.71 4.05 58.05 52.27 11.49 252 Upper Ox 620 4.05 15.33 37.61 4.72 42.93 33.33 14.13 253 North Fish Cr 694 4.69 53.30 25.54 1.64 77.12 61.54 32.68 254 Bois Brule 20 3.94 23.00 34.28 2.24 78.16 62.50 14.37 255 Amnicon -- 4.72 22.00 30.31 6.44 23.45 18.42 3.54 256 Upper Tamarack 391 4.63 6.33 51.51 3.90 88.46 36.36 1.65 257 Turtle Cr 2 1,628 4.63 44.00 41.15 4.75 53.72 36.96 23.62 258 Whitewater Cr 11,991 4.01 20.67 58.83 5.88 2.58 11.76 5.73 259 Token Cr 625 4.41 30.33 47.86 6.16 7.05 10.53 1.28 260 Yahara 15,612 3.99 21.67 57.86 5.47 25.87 25.00 13.93 261 Oconomowoc 5,280 4.47 29.33 48.03 5.45 24.35 28.13 43.04 262 Milwaukee 1,936 4.82 37.33 42.06 4.76 76.63 37.93 .54 263 Cedar Cr 17,460 4.89 39.67 40.85 5.78 28.25 36.59 27.14 264 Sauk 1,873 4.90 85.00 33.90 7.04 4.07 10.00 .00 265 Stoney 2,082 4.60 34.67 44.49 3.97 58.85 52.17 66.51 266 North Branch Milwaukee 2,132 4.69 38.67 42.35 6.62 4.59 13.33 2.14 267 West Branch Rock 20,485 4.55 52.00 39.88 5.26 80.05 36.36 13.21 268 Onion 2,458 4.91 34.33 42.74 5.15 76.69 34.48 4.21 269 South Branch Sheboygan 6,796 4.61 46.67 40.58 7.40 23.02 22.22 24.40

### Appendixes 137

Percent shredders Number of taxa Fish index of biotic integrity Percent carnivores Percent insectivores Percent omnivores Percent intolerant species Percent tolerant species Number of fish Number of fish species 0.00 31.00 60.00 25.30 48.19 16.87 34.94 16.87 14 14

.00 17.00 55.00 .16 62.30 16.88 1.85 30.87 179 22 .00 22.00 75.00 4.94 86.29 .90 50.79 1.80 67 22 .00 23.00 45.00 1.84 50.41 7.55 3.06 48.16 84 15 .00 5.00 100.00 73.46 25.31 .00 96.60 3.09 154 5 .00 32.00 55.00 34.60 33.68 24.64 54.91 29.10 130 19 24.72 21.00 55.00 .08 66.05 9.80 12.25 32.69 365 20

2.31 33.00 55.00 5.93 71.51 14.24 2.97 25.52 48 17

.00 44.00 40.00 9.16 46.56 27.48 15.27 52.67 55 14 .00 51.00 70.00 9.36 63.69 9.22 12.82 26.96 501 18 .00 38.00 44.00 4.92 84.43 1.64 13.93 11.48 15 13 .58 50.00 50.00 16.30 43.17 6.61 47.14 40.53 59 9 .72 43.00 40.00 .36 77.86 11.79 .36 21.43 35 15 .00 67.00 40.00 5.03 29.54 20.57 10.28 64.77 224 16 .17 7.00 57.00 14.88 82.14 .00 30.95 2.98 21 10 3.87 50.00 52.00 12.27 38.99 10.47 22.74 49.82 35 17

.61 26.00 40.00 .48 24.16 3.68 .80 71.68 287 13 .54 43.00 75.00 12.14 78.60 2.00 15.39 5.63 100 18 -- -- 62.00 5.71 59.93 23.57 20.35 29.53 164 23 .00 44.00 65.00 1.05 81.18 5.26 5.79 13.29 132 17 .54 54.00 40.00 10.26 41.03 11.54 26.50 46.58 80 11 .00 26.00 70.00 74.54 21.47 3.68 21.47 3.68 54 6 .00 40.00 70.00 66.22 19.06 4.68 13.71 14.38 39 15 21.24 38.00 30.00 2.26 65.66 26.79 1.89 59.62 105 13

2.20 22.00 57.00 7.41 74.07 3.13 5.98 23.65 70 18

.97 46.00 52.00 1.78 74.56 9.76 5.03 10.06 42 21 .00 34.00 45.00 .16 87.73 11.70 13.10 12.85 276 12 .64 38.00 20.00 6.45 58.06 35.48 54.84 38.71 15 4 .00 36.00 30.00 6.81 46.81 38.72 14.47 53.19 86 18 .43 32.00 54.00 17.36 60.88 19.32 16.63 25.92 147 21 .00 29.00 69.00 13.51 70.72 10.81 15.77 10.81 28 20 .37 41.00 47.00 13.10 75.95 10.95 12.44 25.79 173 17 3.52 40.00 .00 .00 33.33 4.17 .00 68.75 44 7

.00 23.00 57.00 .67 34.83 19.33 .45 64.94 247 19 .61 45.00 62.00 2.43 80.10 15.05 2.43 19.42 41 21 .54 22.00 .00 .00 27.66 72.34 .00 82.98 13 6 .28 29.00 52.00 7.37 68.84 23.80 7.08 23.80 65 15 1.37 36.00 22.00 1.81 30.02 30.10 .00 65.54 620 15

### 138 Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin

Appendix 4. Biological data for each of the 240 studied wadeable streams in Wisconsin—Continued. All data collected by the Wisconsin Department of Natural Resources.
[Cr, Creek; Trib, Tributary; Br, Brook; ID, identification number EPT, Ephemeroptera, Plecoptera, or Trichoptera; mg/m 2 , milligram per square meter; --, no data collected at site]

ID (see fig. 4) Stream name Benthic chlorophyll a (mg/m 2 ) Diatom Nutrient

Index Diatom Siltation

Index Diatom Biotic Index Hilsenhoff Biotic Index Percent EPT number Percent EPT taxa Percent scrapers
270 Meeme 5,249 4.58 41.67 42.11 7.23 5.91 11.43 0.39 271 Silver Cr 13,180 4.72 52.00 38.80 7.70 5.15 22.22 .74 272 South Branch Manitowoc 6,716 4.77 51.33 38.64 8.40 18.64 15.63 .45 273 Manitowoc 18,736 4.76 59.33 37.35 5.06 42.78 44.74 8.33 274 East Twin 16,379 4.52 63.33 38.29 5.23 39.80 29.41 27.55 275 Neshota 2,077 4.88 15.33 61.42 4.90 25.00 9.52 8.93 276 Kewaunee 4,428 4.67 47.67 39.97 4.72 83.44 45.83 24.50 277 East 8,536 4.29 70.67 39.06 7.85 7.85 17.65 3.66 278 Duck Cr 7,653 4.74 66.67 36.51 4.89 73.04 47.83 16.67 301 Vismal Cr 4,333 2.29 6.33 74.40 -- -- -- -- 302 Levis Cr 75,030 2.87 3.00 97.60 -- -- -- -- 303 Ditch #6 South Branch Ten Mile Cr 337,121 4.56 42.67 27.03 -- -- -- --

304 South Branch Suamico 1,068,000 3.93 40.30 30.89 -- -- -- -- 305 West Branch Red 239,188 2.85 12.00 51.66 -- -- -- --

### Appendixes 139

Percent shredders Number of taxa Fish index of biotic integrity Percent carnivores Percent insectivores Percent omnivores Percent intolerant species Percent tolerant species Number of fish Number of fish species 0.00 35.00 50.00 0.67 62.97 26.01 0.47 37.43 2147 15 7.35 27.00 32.00 1.70 58.52 28.98 .00 39.77 152 11 7.05 32.00 20.00 4.55 23.94 70.91 4.85 74.24 47 22

.83 38.00 69.00 20.51 59.68 12.67 22.58 12.90 54 23 .00 34.00 77.00 7.74 81.98 7.36 11.29 14.59 171 25 .00 21.00 55.00 .61 37.40 14.42 5.53 40.30 663 19 .00 24.00 69.00 7.53 66.97 18.99 20.00 19.55 179 23 .52 34.00 .00 4.55 59.09 31.82 .00 40.91 8 10 .00 23.00 55.00 3.96 69.23 3.30 3.41 28.68 171 14
-- 33.00 -- -- -- -- -- -- -- -- -- 29.00 -- -- -- -- -- -- -- -- -- 50.00 -- -- -- -- -- -- -- --

-- 32.00 -- -- -- -- -- -- -- -- -- 36.00 -- -- -- -- -- -- -- --Robertson, D.M., Graczyk, D.J., Garrison, P.J., Wang, L., LaLiberte, G., and Bannerman, R.—Nutrient Concentrations and Their Relations to the Biotic Integrity of Wadeable Streams in Wisconsin—Professional Paper 1722

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