Report on the Regional Environmental Monitoring 

and Assessment Program Study of Wadeable 

Streams in the Driftless Area Ecoregion in Western 

Wisconsin

R E S E A R C H A N D D E V E L O P M E N T
EPA 600/R-06/165 

November 2006 

www.epa.gov

Report on the Regional Environmental Monitoring and 

Assessment Program Study of Wadeable Streams 

in the Driftless Area Ecoregion in Western Wisconsin

Michael A. Miller1

, Alison C.C. Colby1, and Paul Kanehl2

1

Wisconsin Department of Natural Resources 

Bureau of Fisheries Management and Habitat Protection 

101 South Webster St. 

Madison, Wisconsin 53707 

2

Wisconsin Department of Natural Resources 

Bureau of Integrated Science Services 

2801 Progress Rd. 

Madison, Wisconsin 53716 

Notice: Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official 

Agency policy. Mention of trade names and commercial products does not constitute endorsement or 

recommendation for use. 

U.S. Environmental Protection Agency 

Office of Research and Development 

Washington, DC 20460
Notice 

The United States Environmental Protection Agency (EPA) through its Office of 

Research and Development funded and managed the research described here via a 

grant (#R-829537-01-0). It has been reviewed by the EPA and approved for 

publication. 

Mention of trade names or commercial products does not constitute endorsement 

or recommendation by EPA for use. 

2
Foreword 

The mission of the Ecological Exposure Research Division (EERD) within the National Exposure 

Research Laboratory (NERL) of the U.S. Environmental Protection Agency (EPA) is to improve 

the scientific basis for understanding, measuring, and protecting biological integrity so that EPA 

and other resource agencies can make sound, defensible environmental decisions. Our 

research is primarily focused on the development, evaluation, and implementation of new 

methods to assess ecosystem condition, to evaluate biotic responses to environmental 

stressors, and to predict future vulnerability of natural populations, communities, and 

ecosystems. The scale of our research ranges from molecular to ecosystem levels of biological 

organization and addresses immediate as well as emerging environmental threats. 

EPA's Environmental Monitoring and Assessment Program (EMAP) is a research program to 

develop the tools necessary to monitor and assess the status and trends of national ecological 

resources. EMAP's goal is to develop the scientific understanding for translating environmental 

monitoring data from multiple spatial and temporal scales into assessments of current ecological 

condition and forecasts of future risks to our natural resources. EMAP focuses on surveys 

based on probability (i.e., random) sampling designs to estimate condition with a known level of 

uncertainty. Regional EMAP (REMAP) was initiated to test the applicability of the EMAP 

approach to answer questions about ecological conditions at regional and local scales. REMAP 

proposals are submitted through EPA’s Regional Offices to the Office of Research and 

Development (ORD). ORD carries out scientific review of proposals, and qualified proposals 

are funded as cooperative agreements. 

This report describes the results of a REMAP agreement awarded to the Wisconsin Department 

of Natural Resources (WDNR) to compare random and modified-random sampling designs. 

The EPA Project Officer was Bhagya Subramanian, and Karen Blocksom, a statistician in 

EERD, provided assistance with data analysis. The report was prepared by WDNR and has 

undergone EPA review. EERD is publishing this report to make these findings more widely 

available, given their potential significance for state or tribal agencies that, like WDNR, are 

considering wider adoption of random-sampling approaches in their water quality monitoring 

programs. 

Florence Fulk 

Acting Director 

Ecological Exposure Research Division 

3
Table of Contents 

Notice ..........................................................................................................................................2

Foreword......................................................................................................................................3

Tables ..........................................................................................................................................6

Figures.........................................................................................................................................8

1. Project Summary...........................................................................................................10

1.1 Background and Rationale.....................................................................................10

1.2 Project Objectives and Focus of This Report.......................................................10

1.3 Methods....................................................................................................................11

1.4 Results .....................................................................................................................11

1.5 Importance to the Science of Environmental Monitoring....................................12

1.6 Other Analyses Planned for Wisconsin REMAP Data .........................................13

2. Study Area .....................................................................................................................14

2.1 Watershed Delineation, Land Use Quantification, and Water Quality 

Stressor Gradient Development ...........................................................................14

2.2 Stream Resources in Study Area...........................................................................14

3. Stream Population Sampling Design ..........................................................................17

3.1 Random, Modified-Random, Reference, and Targeted Stream Sites 

Selection ..................................................................................................................17

3.2 Identification of Sampling Sites.............................................................................18

3.3 Temporal Sampling Frame .....................................................................................18

4. Stream Site Sampling Protocols..................................................................................19

4.1 Physical Habitat.......................................................................................................19

4.2 Water Quality and Water Chemistry ......................................................................19

4.3 Periphyton................................................................................................................20

4.4 Benthic Macroinvertebrates ...................................................................................20

4.5 Fish...........................................................................................................................21

5. Data Analytical Methods...............................................................................................22

5.1 Random, Bridge, and Reference Site Comparisons ............................................22

5.2 Probability Estimates and Evaluation of Population Distributions ....................22

5.3 Land Use Evaluation...............................................................................................23

6. Results ...........................................................................................................................24

6.1 Sample Size Summary............................................................................................24

6.2 Watershed Land Use Identification and Quantification - Relationships 

Among Agricultural Land Use and Physical, Chemical, and Biological 

Measures..................................................................................................................25

6.3 Random, Modified-Random, and Reference Site Comparisons .........................30

4
6.4 Comparison of Reference Sites with Random and Modified-Random 

Assessment Sites....................................................................................................38

6.5 Probability Estimates and Evaluation of Population Distributions ....................46

6.6 Targeted vs. Random Stream Assessment ..........................................................58

6.7 Effects of Geographical Distances Between Random and Modified-Random 

Sites..........................................................................................................................59

7. Discussion.....................................................................................................................61

8. Acknowledgements ......................................................................................................66

9. References.....................................................................................................................67

Appendix A. Comparison of Spring and Fall Water Chemistry Parameters.......................70

Appendix B. Relationships of Stream Order with Physical Habitat, Water Quality and 

Water Chemistry, and Biological Measures ...............................................................72

Appendix C. Fish Assemblage Data Analyses......................................................................76

5
Tables 

Table 1. Pearson correlations between watershed land use and in-stream physical 

habitat measures (N = 78)............................................................................................. 25

Table 2. Pearson correlations between watershed land use and water quality and 

water chemistry measures. ........................................................................................... 26

Table 3. Pearson correlations between in-stream physical habitat, watershed land 

use, and biological measures........................................................................................ 28

Table 4. Pearson correlations between water quality and water chemistry 

measures, and biological measures. ........................................................................... 29

Table 5. Weighted paired t-test comparisons of stream physical habitat measures 

from X and B stream assessment sites......................................................................... 31

Table 6. Weighted paired t-test comparisons of water quality and water chemistry 

measures from the X and associated B assessment sites. ........................................... 33

Table 7. Weighted paired t-test comparisons of macroinvertebrate metrics and 

indices collected from X and associated B assessment sites........................................ 35

Table 8. Weighted paired t-test comparisons of fish metrics collected from X and B 

assessment sites........................................................................................................... 37

Table 9. Two sample t-test comparisons for physical habitat measures collected at 

the X and reference sites. . ........................................................................................... 39

Table 10. Two-sample t-test comparisons of water quality and water chemistry 

values between the X and reference stream sites ....................................................... 41

Table 11. Two sample t-test comparisons of the X and reference site 

macroinvertebrate metrics............................................................................................. 43

Table 12. Two-sample t-test comparisons of the X and reference site fish metrics. .... 45

Table 13. Physical habitat reference condition thresholds. .......................................... 46

Table 14. Water chemistry and water quality reference condition thresholds............... 49

Table 15. Macroinvertebrate metric reference condition thresholds............................. 53

Table 16. Fish metric reference condition thresholds................................................... 55

Table A 1. Paired t-test comparisons between spring and fall water quality and 

water chemistry measures collected at the X stream sites............................................ 70

6
Table B 1. ANOVA results of stream order and physical habitat measures 

collected at the X sites. ................................................................................................. 72

Table B 2. Tukey HSD pairwise comparison probabilities for physical habitat 

measures that produced significant ANOVA results...................................................... 72

Table B 3. ANOVA of stream order and water quality and water chemistry 

measures from the X stream sites................................................................................. 73

Table B 4. Tukey HSD pairwise comparison for the percent oxygen saturation............ 73

Table B 5. ANOVA of stream order and macroinvertebrate measures from the X 

stream sites................................................................................................................... 74

Table B 6. ANOVA of stream order and fish assemblage measures from the X 

stream sites (N=42)....................................................................................................... 75

Table B 7. Tukey HSD pairwise comparison probabilities for fish metrics that 

produced significant ANOVA results. ........................................................................... 75

Table C 1. Fish species captured at X stream sites. .................................................... 77

Table C 2. Fish species captured at reference stream sites......................................... 78

7
Figures 

Figure 1. Random and least disturbed reference stream sites in the REMAP 

study area. .................................................................................................................... 16

Figure 2. Bivariate scatterplots comparing physical habitat measurements 

collected at the X and associated B sites...................................................................... 30

Figure 3. Bivariate scatterplots comparing water quality and water chemistry 

measurements collected from the X and associated B sites. ........................................ 32

Figure 4. Bivariate scatterplots comparing macroinvertebrate metrics collected at 

the X and associated B sites. ........................................................................................ 34

Figure 5. Bivariate scatterplots comparing fish metrics collected at the X and 

associated B sites. ........................................................................................................ 36

Figure 6. Bar charts of weighted means and standard deviations (SD) for X and B 

sites and simple random sample mean and SD for reference sites for physical 

habitat measures........................................................................................................... 38

Figure 7. Bar charts of means and standard deviations for water quality and water 

chemistry measures collected at the X, B, and reference stream sites. ........................ 40

Figure 8. Bar charts of mean and standard deviation of macroinvertebrate metrics 

collected at the X, B, and reference stream sites. ......................................................... 42

 Figure 9. Bar charts of mean and standard deviation of fish metrics collected at 

the X, B, and reference stream sites. ........................................................................... 44

Figure 10. Cumulative distribution function curves of physical habitat measures 

collected at the X and B sites. ....................................................................................... 47

Figure 11. The percentages of stream miles not meeting the reference condition 

threshold values for physical habitat measures............................................................. 48

Figure 12. Cumulative distribution function curves of water quality measures 

collected in situ at the X and B sites.............................................................................. 50

Figure 13. Cumulative distribution function curves of laboratory analyzed water 

chemistry measures collected at the X and B sites. ...................................................... 51

Figure 14. The percentages of stream miles not meeting the reference condition 

threshold values for water quality and water chemistry measures. ............................... 52

Figure 15. Cumulative distribution function curves of macroinvertebrate metrics 

collected at the X and B sites. ....................................................................................... 54

8
Figure 16. The percentages of stream miles not meeting the reference condition 

threshold values for macroinvertebrate metrics............................................................. 55

Figure 17. Cumulative distribution function curves for fish metrics collected at the 

X and B sites. ................................................................................................................ 56

Figure 18. The percentages of stream miles not meeting the reference condition 

threshold values for fish metrics.................................................................................... 57

Figure 19. Cumulative distribution function curves of fish IBI scores from 

biologists’ targeted sites and REMAP X sites, compared to the reference 

condition threshold value. Box plots and distribution of the biologist’s targeted 

and REMAP X sites data is shown in figure on right. .................................................... 58

Figure 20. Scatterplots showing relationships between the distance between the 

X and B sites, and the absolute value of the differences in physical, chemical, and 

biological measures collected at these sites. ................................................................ 59

Figure A 1. Box and whisker plots of spring and fall water quality and water 

chemistry measures collected at the X-sites. ................................................................ 71

Figure C 1. Percent frequency of occurrence of fish species at the X, B, and 

reference sites............................................................................................................... 79

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1. Project Summary 

1.1 Background and Rationale 

Hundreds of millions of dollars have been spent in Wisconsin on watershed management and 

restoration activities, yet certain farming, and suburban and urban development practices 

continue to significantly impact a large portion of the state’s waters, and in some areas of the 

state severe stream degradation is readily apparent. Improvements in the assessment of 

Wisconsin stream resources are needed to provide a comprehensive evaluation of the state’s 

waters. Greater understanding of land use factors affecting water resources will help improve 

land and water resource management, and broader dissemination of this information is needed 

to improve the political decision-making processes for these management activities. 

To date, stream monitoring conducted by the WDNR has primarily been targeted sampling to 

provide information for stream-specific management issues. Physical, chemical, and biological 

data are often collected from either highly degraded streams affected by polluted run-off, or from 

high quality streams where game fish management or stream habitat enhancement efforts are 

being evaluated. This resulting data set can be strongly biased if used for making inferences 

about broad-scale conditions of stream resources. Spatial clustering of the WDNR’s current 

sampling effort on a relatively small proportion of the State’s streams and a focus on larger 

streams that support adult game fish also limit the ability to make meaningful statements about 

Wisconsin’s entire stream population. 

Beginning in 2003, the Wisconsin Department of Natural Resources (WDNR), with support from 

the EPA’s Regional Environmental Monitoring and Assessment Program (REMAP), conducted 

an assessment of the physical, chemical, and biological conditions of wadeable streams in the 

Driftless Area ecoregion in western Wisconsin using a probabilistic sampling design. The 

Driftless Area ecoregion encompasses 20 percent of Wisconsin's total land area and contains 

21 percent of the State's perennial stream miles. 

1.2 Project Objectives and Focus of This Report 

The Wisconsin REMAP study was conducted to address the following objectives: 

Objective 1: 

Use a statistically valid probabilistic sampling design to assess the condition of the entire 

wadeable stream population in the Driftless Area ecoregion, and evaluate whether a modifiedrandom sample survey design (sampling randomly selected stream reaches near roadaccessible access points) characterizes individual or populations of streams similarly to a truly 

randomized survey sampling design. 

Objective 2: 

Evaluate whether targeted stream sampling routinely conducted by the WDNR characterizes 

stream fish populations similarly to a probabilistic sampling design. 

Objective 3: 

Investigate whether the effects of agricultural land use can be detected in the quality of instream physical habitat or water chemistry measures, and whether changes in stream physical 

or chemical characteristics influence the biological assemblages in streams. 

10
Objective 4: 

Evaluate whether one biotic assemblage is more discriminating of specific stressors such as 

percent agricultural land within a watershed, in-stream or riparian physical habitat degradation, 

or chemical pollutants, than others, and whether there are significant differences in the 

estimated miles of degraded streams depending upon the biotic assemblage used in the 

estimation. 

Objective 5: 

Compare macroinvertebrate taxonomic data collected using two different field sampling 

protocols, differing laboratory sub-sample sizes, and differing levels of laboratory taxonomic 

resolution, to evaluate whether certain field or lab protocols are more effective at detecting and 

measuring various types of environmental stressors. Additionally, develop a multi-metric 

macroinvertebrate index for the Driftless Area ecoregion and subsequently the entire state, 

using the measured physical and chemical explanatory data, and the more rigorous protocols 

identified. 

This report presents the results of data analyses addressing Objectives 1-4 for 

macroinvertebrate and fish assemblages. Algae were collected and processing of these 

samples is underway. Analyses to address Objective 5 are in progress. 

1.3 Methods 

Watershed land use, riparian and in-stream habitat, field and laboratory-analyzed water 

chemistry, periphyton, macroinvertebrate, and fish data were collected from randomly selected 

stream sites (n = 60), and an associated “modified-random" sampling site on each of these 

streams, that was accessed via a road crossing nearest the randomly selected sampling site. 

These data allowed us to evaluate whether sampling randomly selected stream sites at the 

nearest road crossings would significantly bias the assessment results compared to sampling 

truly random sites. Least disturbed reference sites were sampled to develop stream-quality 

expectations based on objective reference condition criteria (n = 22). Also, WDNR biologists 

provided fish assemblage data from 60 targeted stream sites they had sampled, and which were 

thought to be representative of the range and modal condition of stream resources in the study 

area. We compared fish data from these targeted sites to that from the REMAP random sites to 

evaluate whether targeted sampling characterized the Driftless Area ecoregion stream 

population similarly to the stratified random survey sampling design. 

1.4 Results 

The mean distance between the random (probabilistic) and the associated modified-random 

assessment site on each stream was 701 meters. Study results show no significant differences 

between the random and modified-random assessment sites for all 9 physical habitat measures, 

11 water chemistry measures, 7 macroinvertebrate metrics, or 8 fish metrics. 

We provide evidence that targeted sampling routinely done by WDNR characterized the 

biological condition of stream resources in the Driftless Area ecoregion differently than 

probabilistic sampling. Cumulative distribution plots of fish Index of Biotic Integrity (IBI) scores 

from targeted stream sites sampled by WDNR regional biologists indicate that 65% of the 

stream sites in the study area were not meeting the reference condition threshold value of 60, 

versus the estimate of 80% of the random sample sites not meeting this threshold based on the 

probabilistic sampling design results. 

11
Row cropping is the dominant land use in the study area followed by forest cover. Study results 

indicate there were no significant relationships between the percentage of agricultural land in 

each watershed and the degradation of various in-stream physical habitat features, but water 

column nitrate-nitrite concentrations and conductivity were positively correlated with percent 

watershed agricultural land. Fish assemblages appeared to be insensitive indicators of water 

quality, but sensitive macroinvertebrate taxa declined with increased Kjeldahl nitrogen, 

ammonia, total phosphorus and total dissolved phosphorus concentrations, and were positively 

correlated with dissolved oxygen concentration, percent dissolved oxygen saturation and water 

transparency. 

Physical, chemical, and biological measures from least disturbed reference stream sites were 

used to develop reference conditions. There were significant differences between the random 

sample population (and by inference the entire stream population in the Driftless Area ecoregion 

of Wisconsin) and the reference condition for a number of stream physical, chemical, and 

biological measures. As examples, we documented that 75% of the random sample population 

streams were degraded based on measures of stream bank erosion; 70% of the random sample 

population had higher total dissolved phosphorus concentrations than the reference condition; 

approximately 75% of the streams were degraded based on the percentage of sensitive 

macroinvertebrate taxa present; and 74% of the streams showed impairment based on fish IBI 

scores. 

1.5 Importance to the Science of Environmental Monitoring 

Randomization is an important aspect of sample survey design as it allows objectivity in the 

sample selection process, and in the evaluation of sources of error or sampling variability 

(Larsen 1995, Peterson et al. 1999). Probabilistic sampling designs can reduce sampling bias 

and increase the representativeness of sample data used to make inferences about the target 

population. Previous experience from employing probabilistic sampling designs in Wisconsin 

have shown disadvantages when using this type of sampling design including: 1) Reduced 

accessibility and increased travel times to more remote sites can significantly increase sampling 

effort and cost; 2) Reduced site accessibility can result in having to use more transportable and 

often less effective sampling gear; and 3) Streams highly degraded by poor land management 

are often associated with landowners unwilling to allow access to streams on their property due 

to distrust of government agencies or fear of legal action. With the REMAP project, we 

evaluated whether random, modified-random, and non-random (targeted) sampling designs 

provided similar results. These findings are being used to evaluate fundamental aspects of 

stream sampling designs, which should help improve the monitoring and assessment of stream 

resources in Wisconsin and elsewhere. 

Knowledge of what the physical, chemical, or biological conditions of a stream should be in the 

absence of human disturbances, and understanding of how streams respond to anthropogenic 

stressors, are important to guide assessment and management efforts (Karr and Chu 1999, 

Davies et al. 2000). The Wisconsin REMAP project initiated the collection of physical, chemical, 

and biological data from least disturbed stream sites throughout western Wisconsin to help 

define ecoregional expectations (reference conditions). This methodology will subsequently be 

applied to the entire state. Land use types within the watersheds upstream from each study site 

were quantified to evaluate how land use influence stream habitat and water quality 

characteristics, which in turn can influence the biotic assemblages. 

12
1.6 Other Analyses Planned for Wisconsin REMAP Data 

Numeric biological criteria can provide objective quantifiable measures of ecosystem health. 

Biological indices have been developed for Wisconsin streams using macroinvertebrate and fish 

assemblage data (Hilsenhoff 1987, Lyons 1992a, Lyons et al. 1996). Hilsenhoff’s Biotic Index 

(HBI) uses macroinvertebrate taxa data from samples collected from riffles to assess organic 

pollution that manifests itself as reduced dissolved oxygen concentrations (Hilsenhoff 1987). 

Alternative or refined macroinvertebrate field or lab protocols may result in the collection of data 

that are more discriminating of specific types of stream impairment other than organic pollution. 

Refined macroinvertebrate indices would also add additional measures of stream condition to 

corroborate physical, chemical, and biotic measures such as fish or diatom indices, and can be 

applied to streams where these other biological indices are insensitive. Two commonly used 

macroinvertebrate field sample collection protocols (single (riffle) habitat and proportional multihabitat sampling), differing laboratory sub-sampling levels (100, 300, 500 fixed-count), and 

differing levels of taxonomic identification (family and genus levels, versus lowest practical level) 

are also being evaluated as part of the Wisconsin REMAP project. These results will be used to 

characterize the method performance (rigor) of various aspects of the WDNR’s 

macroinvertebrate field and lab protocols. These data will also be used to develop a multimetric macroinvertebrate index for western Wisconsin streams, and this process will 

subsequently be applied to develop multi-metric macroinvertebrate indices for the entire state. 

13
2. Study Area 

The geographic extent of the REMAP study area is 7,418,000 acres (20.6% of Wisconsin’s total 

land area), and encompasses the Western Coulee and Ridges and the Southwest Savanna 

ecoregions in western Wisconsin (Figure 1), which are based on the United States Department of 

Agriculture – Forest Service’s National Hierarchical Framework of Ecological Units (Keys et al. 

1995). These ecological units closely approximate Omernik’s Level III Driftless Area Ecoregion 

(Omernik 1987) and are collectively referred to as the Driftless Area in this report. The Driftless 

Area extends into the states of Minnesota, Iowa, and Illinois, and remained unglaciated during the 

most recent glacial period, whereas the rest of Wisconsin and most of the upper Midwest was 

covered with ice. As a result, the Driftless Area has a “mature” drainage system characterized by 

deeply incised valleys and few natural lakes or wetlands relative to the rest of Wisconsin. The 

relatively steep topography creates a significant water flow gradient and valley bottoms are close 

to the water table, resulting in streams with high baseflow that are dominated by coldwater fish 

assemblages. The soils of the Driftless Area are well-drained silty loess over dolomite, limestone, 

or sandstone. Land use patterns closely follow spatial differences in slope, with field corn, 

soybean, alfalfa, and pastureland situated on the ridge tops and in the valley bottoms, and 

hardwood forests dominate the steeply sloped valley sides. The Driftless Area was selected for 

the REMAP study area because the amount of topographic relief in this area provides clearly 

delineated watersheds, and land use (and presumably stream quality) varies significantly among 

watersheds, relative to other areas of the state (Keys et al. 1995). 

2.1 Watershed Delineation, Land Use Quantification, and Water Quality Stressor 

Gradient Development 

We used Geographic Information System (GIS) technology and a digital elevation model to 

delineate the watershed area upstream of each random and least disturbed reference stream site. 

Wisconsin Initiative for Statewide Cooperation on Landscape Analysis and Data (WISCLAND) 

GIS land cover data were used to quantify land use within the study area watersheds. The 

WISCLAND data were derived from LANDSAT Thematic Mapper satellite imagery acquired from 

fly-overs beginning in August 1991 and ending in May 1993. The on-the-ground resolution of 

each WISCLAND digital pixel is 30 square meters. We quantified land use data to develop a land 

use disturbance gradient based on the total proportion of agricultural (row crop) acreage found 

within each watershed upstream of each stream assessment site. Higher proportions of row crop 

acreage within each watershed were equated with greater potential in-stream impacts. 

Agricultural land use is the major land “disturbance” and cause of degradation to Wisconsin 

streams (Robertson et al. 2006). In particular, row crops such as field corn and soybeans are the 

major contributors of sediment, and chemical fertilizers and livestock manure are the major 

sources of nitrogen and phosphorus for the study area streams. It is recognized that riparian land 

use, buffer width, plant species composition and linear extent, cropland slope, crop rotations, and 

numerous geological and meteorological factors strongly influence pollutant delivery to streams, 

but the level of effort needed to adequately characterize and quantify these factors were beyond 

the scope of this study. 

2.2 Stream Resources in Study Area 

The REMAP study area has an estimated 3,560 individual (19.5 % of statewide total number) and 

8,840 miles (21.1% of Wisconsin’s total stream mileage) of perennial streams. Perennial streams 

14
in the study area were identified and numbers and miles quantified from a 1:24,000-scale GIS 

statewide hydrography layer developed by the WDNR from digitized 7.5 minute U. S. Geological 

Survey (USGS) quadrangle maps. The numbers of perennial stream miles by Strahler (1957) 

stream order for the REMAP stream population are as follows: order 1 (1,031 mi.), order 2 (2,448 

mi.), order 3 (2,282 mi.), and order 4 (1,548 mi.). The REMAP target population of first through 

fourth order streams comprise 3,540 individual (19.3% of Wisconsin’s total number) and 7,310 

miles (17.4% of Wisconsin’s total mileage of perennial streams) of streams. In western 

Wisconsin, fifth order streams typically transition from wadeable to non-wadeable; therefore, only 

first through fourth order streams were included in the target and sample populations. 

15
Figure 1. Random and least disturbed reference stream sites in the REMAP study area. 

16
3. Stream Population Sampling Design 

3.1 Random, Modified-Random, Reference, and Targeted Stream Sites Selection 

The EPA’s Environmental Monitoring and Assessment Program (EMAP) probabilistic sampling 

design was used to randomly select stream sites from the target population (Stevens and Olsen 

1999, 2004). The sampling design was weighted so that equal numbers of first through fourth 

order streams were included in the sample population. The EPA Office of Research and 

Development (ORD) staff in Corvallis, Oregon used an unequal probability random tessellation 

stratified (RTS) sampling design described by Stevens and Olsen (1999) and Stevens (1997), and 

the WDNR 1:24000 - scale hydrography layer to identify 100 potential sample sites. From these 

sample sites, 15 perennial stream sites in each of stream orders one through four (n = 60) were 

randomly selected throughout the Driftless Area ecoregion. EPA - ORD also identified an 

additional 100 over-sample sites to use as replacements if original sites were rejected. The 

sample population for each stream order was weighted to account for the number of stream miles 

these populations represented in the target population. These initial weights were calculated 

assuming that only the first 100 sites would be evaluated. Because many of the original sites 

were rejected and replaced with over-sample sites, weights were adjusted by multiplying the total 

stream length calculated for the study area by the original weight, and dividing this number by the 

sum of the weights of the final sample population. The WDNR hydrography layer was also used to 

generate summary statistics on numbers and miles of streams statewide and in the study area. 

Reference Site Selection 

Selection of reference stream sites was based on evaluation of watershed land ownership (i.e., 

county, state, or federal lands tended to have less agricultural or urban land) and land use, using 

the WISCLAND database. This a priori method used to select candidate watersheds and 

reference stream sites was based on guidance developed by EPA and others (Hughes et al. 

1986, Gibson et al. 1996). Reconnaissance of each candidate reference site was conducted to 

verify that there were no apparent watershed or riparian land use factors significantly degrading 

the site, and to do a cursory evaluation of in-stream physical habitat conditions prior to 

designating it as a reference site. To develop reference conditions we collected physical, 

chemical, and biological data from 22 least disturbed reference stream sites located throughout 

the study area (Figure. 1). We sampled a total of four first-order, four second-order, ten thirdorder, and four fourth-order least disturbed reference sites during the 2003 field season for the 

same parameters as the random and modified-random sites. 

Regional Targeted Sampling Sites 

Regional WDNR biologists that assess and manage stream resources in the REMAP study area 

were asked to select a total of 60 stream sites that were recently sampled and thought to be 

representative of the range and modal condition of stream resources in the study area. Fish data 

were collected by the biologists from these non-random sites using the same sampling protocols 

used in the REMAP study, and these data were then compared to the fish data collected at the 

REMAP random sites. 

17
3.2 Identification of Sampling Sites 

EPA-ORD provided the latitude and longitude coordinates to identify the mid-point of each 

randomly selected stream sampling site. Each corresponding modified-random sampling site was 

located either upstream or downstream of the randomly selected site, at the nearest “easy” 

access point (typically accessed from a roadway or driveway bridge that crossed each stream). 

We dropped candidate streams from the sample population if there were intervening tributaries 

between the random and modified-random sites that resulted in a Strahler stream order difference 

of more than one order between the random and modified-random sites. In this report, random 

sites are subsequently referred to as “X” sites and the modified-random sites are referred to as 

“B” (Bridge) sites. The B sites were located sufficient distances (typically 10 x the mean stream 

wetted width (MSW)) away from road crossings or driveways to avoid hydraulic influences of 

bridge abutments, culverts, or other manmade structures on stream physical habitat 

characteristics, or that created artificial fish habitat. 

3.3 Temporal Sampling Frame 

We followed the sampling index periods of the WDNR’s standard operating procedures (SOPs) 

when collecting stream physical habitat and fish assemblage data, and macroinvertebrate and 

water chemistry samples. We collected stream physical habitat data and water chemistry 

samples during stream baseflow conditions following spring snowmelt and rain event high-flow 

conditions. Fish sampling was done from mid-June through mid-September. The fish sampling 

index period avoids spring migratory movements of spawning catostomids, and high numbers of 

young-of-the-year salmonids and centrarchids that exceed typical stream carrying capacities, as 

well as fall upstream spawning migrations of salmonids and downstream overwintering migrations 

of ictalurids and centrarchids. We collected macroinvertebrate samples in the fall of 2003. The 

fall index period for benthic macroinvertebrate sampling allows for a greater portion of aquatic 

invertebrates to be identified since most taxa are of sufficient size and development for 

identification. In-situ water chemistry (instantaneous readings from an electronic water quality 

meter) and laboratory-processed grab samples were collected in the spring (June) and again in 

the fall (August – September) during baseflow conditions at each X, B, and reference stream site 

during the 2003 field season (Appendix A). 

18
4. Stream Site Sampling Protocols 

4.1 Physical Habitat 

In-stream and riparian physical habitat characteristics were measured or visually estimated at 12 

transects within each X, B, and reference stream assessment reach. We used WDNR SOPs for 

assessing stream physical habitat at all of the study sites. Stream assessment reach lengths for 

physical habitat and fish assemblage sampling were based on 35 x MSW. An assessment length 

of 35 X MSW generally encompasses three run-riffle-pool sequences, and typically most fish 

species found within stream reaches in Wisconsin will be encountered within this length of stream 

surveyed (Lyons 1992b). For streams with a MSW less than 2.9m, the minimum assessment 

reach was 100m long. At some sites, the reach lengths were slightly lengthened if it resulted in 

starting and/or ending the assessment reach at a riffle, which enabled more efficient fish collection 

since blocknets were not used. At each habitat assessment transect, measures of water and 

sediment depth, bankfull water depth, overhead canopy; and visual estimates of percent substrate 

composition were collected at four points equally spaced along the transect line. Bank erosion 

was measured and riparian land use and land cover characteristics were visually estimated along 

each of the transect lines extending laterally 10 meters into the upland riparian zones. The 

distance between bends was measured and divided by the mean stream width. Throughout the 

report this ratio is referred to as ‘distance between bends’ to abbreviate. 

4.2 Water Quality and Water Chemistry 

We collected 6 in situ (metered) water quality measures at all X, B, and reference stream sites in 

the spring and fall during baseflow conditions. A Yellow Springs Instruments Company Model 85 

electronic water quality meter was used to collect instantaneous measures of water temperature, 

dissolved oxygen concentration, dissolved oxygen percent saturation, and conductivity. An Orion 

QuikchekTM pen was used to measure pH. Both meters were calibrated following the 

manufacturer’s instructions prior to the start of each field day using air calibration for dissolved 

oxygen, and chemical standards for conductivity and pH. To measure water column transparency 

we used a transparency tube. This device consists of a 125 cm long x 4.5 cm diameter Plexiglas 

cylinder sealed at the bottom with a 4.5 cm diameter Secchi disk. The transparency tube was 

filled with stream water while at each assessment site, and the water was drained from the tube 

(reducing the water column height) until the Secchi disk became visible when looking down into 

the tube through the water column. The height of the water column was measured by reading a 

height scale on the side of the tube. For some assessment sites (particularly reference sites), the 

transparency of the water was often high enough that the Secchi disk could be seen when the 

tube was completely filled with water (122 cm), so that an exact transparency value could not be 

measured, since the true value was “off-scale”. In these instances, a value of 122 cm was 

assigned. 

Five water chemistry parameters were measured. We collected one laboratory-analyzed water 

chemistry grab sample during baseflow in the spring and fall at each X, B, and reference site. 

The parameters analyzed included: total phosphorus, total dissolved phosphorus, total Kjeldahl 

nitrogen, ammonia, and nitrate - nitrite nitrogen. Samples were preserved (acidified) and placed 

on ice in the field, refrigerated upon return from the field, and submitted to the Wisconsin State 

Laboratory of Hygiene within specified holding times for analysis, following the lab SOPs. 

19
4.3 Periphyton 

To assess diatom assemblages we collected periphyton samples at all X, B, and reference sites. 

Samples were collected in August and September of 2003 from cobble or smaller rocks, or in the 

absence of mineral substrates, soft sediment samples were collected. At sites with rock 

substrate, nine rocks (5cm – 25cm in diameter) were taken from riffle areas. An area 4 cm square 

was measured on the upper surface of each of the rocks with a ruler and delineated with a 

scalpel. The scalpel was then used to scrape the delineated area on each rock, and the material 

adhering to the scalpel and loosened on the rock was washed with de-ionized water into a clean 

pan. The same delineated areas were then scrubbed with a clean nylon brush and both the brush 

head and brushed area of the rocks were again rinsed into the sample collection pan. The 

composite sample was poured from the pan into a 1L bottle and diluted to the smallest volume 

possible, either 250mL, 500mL, 750mL, or 1000mL, and the dilution volume was recorded. The 

capped 1L bottle was vigorously shaken to suspend and homogenize the sample. A clean turkey 

baster was then used to remove a 40mL aliquot from the 1L bottle and transfer it into a 60mL 

bottle. The 40mL aliquot was preserved with 1.6mL of a 50% glutaraldehyde solution. The 

preserved samples were placed on ice in the field and refrigerated upon arrival to the lab. At sites 

lacking coarse substrate, a glass Petri dish (49mm inside diameter) was inverted and placed on 

streambed fine sediment (sand, clay, silt), and a stainless steel spatula without openings in the 

blade was used to trap the fine sediment within the Petri dish. The fine sediment was then 

deposited into a clean sample pan. A total of nine fine-sediment samples were collected and 

composited in the sample pan. The fine sediment periphyton samples were homogenized, subsampled, and preserved using the sample methods applied to the coarse substrate periphyton 

samples. 

Although the collection and analysis of periphyton samples from the X, B, and reference sites 

were not part of the original study proposal, these samples were collected and are currently being 

processed. Upon completion of the analytical results, a manuscript will be submitted to a 

scientific journal. 

4.4 Benthic Macroinvertebrates 

We collected macroinvertebrate samples at all X, B, and reference stream sites in the fall of 2003 

using a D-framed net with 500 micron mesh, following WDNR SOPs. One kick sample was 

collected from a single riffle (course gravel or cobble substrate) located within the habitat and fish 

sampling reach where water velocities created erosional habitat. The net frame was placed at 

arm's-length downstream of the sample collector, who using the toe or heel of their boot disturbed 

the substrate to a depth of approximately 5 cm. Sampling continued for approximately 3 minutes, 

typically at which time there was a fist-sized wad of debris in the net and it was evident that over 

100 organisms had been collected. In the absence of coarse substrate, overhanging riparian 

vegetation, or grass and leaf "snags" were sampled. The D-frame net was used to sweep and jab 

the overhanging vegetation for approximately 5 minutes, or the net was placed downstream of 

snags, and the tree branches holding the snags were disturbed until the organic debris was 

dislodged and washed into the net. In addition, a 20-jab proportional-habitat sample was 

collected along a 100m-long reach within the habitat and fish assessment reach at each X, B, 

and reference stream site following protocols described by Barbour et al. (1999). A rangefinder 

was used to estimate each 100m-long sampling reach. For both the single riffle and proportional 

habitat samples, rocks, twigs, and other coarse debris were removed from the net while making 

certain to rinse or remove by hand organisms clinging to the debris and placing them back into the 

20
sample. Samples were placed in containers identified with internal and external labels, preserved 

with an 80% ethanol solution, and transported to the lab for processing. 

 

We used a 125+ organism fixed-count random sub-sampling method in the lab to process all of 

the macroinvertebrate samples, following WDNR SOPs. In the lab, each field sample was evenly 

distributed in a gridded pan, and a random number was used to select a grid square. All 

organisms within the chosen grid-square were removed, enumerated, and stored for later 

taxonomic identification. If fewer than 125 organisms were removed from the initial grid square, 

subsequent randomly selected grid squares were picked in their entirety until the target number of 

125+ organisms was reached. Guidelines provided by Hilsenhoff (1987) were followed for 

determining which taxonomic groups were identified and the level of taxonomic resolution that 

was applied to the taxa in the sub-samples. Lifestages and groups of organisms not included in 

the enumeration and identification included: adult insects, empty or sealed Trichoptera cases, 

Hemiptera, Coleoptera (non-dryopids), Collembola, Mollusca, Annelida, Decapoda, Nematoda, 

Nematomorpha, Hydracarina, and Turbellaria. 

The taxonomic analyses are still being conducted on the 20-jab samples and only the results of 

the riffle samples are included in this report. The single-riffle and 20-jab sample data will be part 

of a detailed Performance-Based System study (Miller et al.: in prep.) that follows guidelines 

developed by Diamond et al. (1996). The study will evaluate the rigor of macroinvertebrate field 

and lab methods to help refine WDNR biological assessment protocols and macroinvertebrate 

indices for streams. 

4.5 Fish 

We used WDNR SOPs to assess fish assemblages by electrofishing each of the X, B, and 

reference sites. The majority of the stream sites were sampled by a three-person crew that used 

two handheld electrodes powered by a DC generator mounted in a small tow barge, pulled 

upstream by one crew member. Each crewmember used a hand-held net to capture fish. In 

streams too narrow or shallow to be negotiated by the tow barge, a two-person crew, each with a 

hand-held net, used one battery-powered backpack electrofishing unit with one anode to stun fish. 

All stream habitats were thoroughly sampled, and an effort was made to capture all fish greater 

than 25mm total length. The fish were placed in the tow barge live well or in buckets, and 

subsequently identified to species, measured, enumerated, and released. If field identification of 

fish specimens were uncertain, specimens were preserved for laboratory identification. 

21
5. Data Analytical Methods 

5.1 Random, Bridge, and Reference Site Comparisons 

A total of 9 physical habitat, 11 water quality and water chemistry, 7 macroinvertebrate, and 8 fish 

metrics were analyzed and are presented in this report. Prior to analyses, variables were 

“weighted” using an assigned weight that accounted for the total number of stream miles 

represented by that site in the target population. Weighted means and Horvitz-Thompson 

estimates of standard deviation (Diaz-Ramos et al. 1996) were calculated for X and B sites using 

the PSURVEY.ANALYSIS package (v. 2.7) developed by EPA’s EMAP program (available at 

http://www.epa.gov/nheerl/arm/analysispages/software.htm) for the free software R (R: A 

Language and Environment for Statistical Computing, Vienna, Austria; http://www.r-project.org/). 

An alpha level of 0.05 was applied to determine the significance of all tests reported. 

Bivariate scatterplots were created for each metric to visually compare the X and B site data, and 

Pearson correlation coefficients were calculated to identify any significant correlations. Paired ttests incorporating the weighted means and standard deviations were used with a Bonferroni 

adjustment to determine if significant differences existed for any of the variables collected, 

between the X and B sites. 

The weighted means and standard deviations were plotted alongside the simple random sample 

mean and variance estimates calculated from reference sites for each variable. Two-sample ttests assuming unequal variances were performed using the weighted mean and variance values 

for the X sites and the simple random sample mean and variance for reference sites. A 

Bonferroni adjustment was applied to each group of variables (i.e., habitat, chemistry, 

macroinvertebrates, fish) to determine significance of differences at an overall Type I error rate of 

0.05. 

5.2 Probability Estimates and Evaluation of Population Distributions 

Empirical cumulative distribution functions (CDFs) of X and B site data were generated to 

estimate the percentage of the X and B stream populations that met reference condition 

thresholds for various physical habitat, chemical, and biological metrics. The 25th percentile (for 

those metrics where lower values indicated lower environmental quality) or the 75th percentile (for 

those metrics where higher values indicated lower environmental quality) of physical habitat, 

chemical, and biological measures calculated from the reference sites were used to develop the 

reference condition thresholds. The CDFs and percentage estimates were calculated using the 

PSURVEY.ANALYSIS package in R. A cumulative distribution function summarizes the overall 

distribution of some variable (x-axis) measured at many random sites. The probability that any 

variable within the population will be less than or greater than some specified value can be 

estimated from the CDF curve (Sokal and Rohlf, 1981). If X and B CDFs provide equivalent data, 

then their population estimates should be similar and their confidence intervals should overlap. 

Kolmogorov-Smirnov two-sample tests were used to determine whether the X and B probability 

distributions differed statistically (Sokal and Rohlf, 1981). CDF plots were also used to compare 

the WDNR regional biologist’s targeted fish sample data with the REMAP X sites fish sample 

data. 

22
5.3 Land Use Evaluation 

A digital elevation model was used to delineate watershed areas upstream of each X, B, and 

reference site. WISCLAND land cover data were used to estimate percent land use types within 

each of these watersheds. Pearson correlation coefficients were calculated to evaluate 

relationships between stream reach physical habitat, water chemistry, and biological assemblage 

attributes, and the percent row crop agriculture, grassland, and forest cover within each 

watershed. Stepdown Bonferroni adjustments were applied to determine p-value significance 

(Legendre and Legendre, 1998). 

23
6. Results 

6.1 Sample Size Summary 

Of the 100 random sites and 100 additional over-sample sites provided by EPA-ORD, we rejected 

a total of 71 candidate sites during their initial reconnaissance. Reasons for dropping sites 

included: stream channel was dry at assessment site (38 sites), with the majority of these in 

Strahler first order (68%) and second order (24%) streams; Strahler stream order changes 

between the random and modified-random assessment sites were greater than 1 stream order 

(10 sites); assessment site was in a wetland without a well-defined stream channel (6 sites); 

greater than 50% of the assessment site fell within an artificial impoundment or area dammed by 

beaver (Castor canadensis) making these sites too deep to wade (5 sites); assessment site was 

actually part of Mississippi River backwater channels (5 sites); access to private property was 

denied (4 sites); no stream channel was located at the random site coordinates (2 sites); a 3 

meter-tall barrier fence prevented access to the assessment site (1 site). Two of the 60 streams 

accepted after reconnaissance were subsequently dropped because they dried-up prior to 

collecting all of the fish, habitat, or macroinvertebrate data. The final study population consisted 

of 58 stream sites. In all analyses, the term “percentage of stream miles” refers specifically to 

stream miles that were accessible, had water present, and were wadeable. 

Physical habitat data were collected at 57 of the 58 X-B paired sites. One of the 58 sites could 

not be sampled at the X site due to the presence of dangerous livestock. Four streams had their 

X and B sites combined for habitat sampling, because upon delineating the assessment site it 

was found that the X and B sampling sites overlapped. 

Water chemistry data were collected at the X and B sites from 56 of the 58 streams. Two of the 

58 streams had their X and B sites combined when collecting water chemistry data. Some 

sampling sites did not have water quality or chemistry data collected from either the spring or fall 

sampling period. Reasons included: suspect meter readings (significantly outside the range of 

values routinely encountered, or a meter was not meeting the calibration standard while in the 

field); grab samples were not collected because recent rainfall resulted in non-baseflow conditions 

at the site; or as with conductivity, no spring data were collected due to a meter malfunction. Only 

spring water quality and chemistry data were used for analyses, with the exception of conductivity 

measures, since the spring sample size was greater. 

Macroinvertebrates were sampled from 57 of the 58 random sites, and fish were surveyed at 55 of 

the 58 sites. Fish were not sampled at two sites with dangerous livestock, and inclement weather 

prevented sampling at another site. Four streams had their X and B sites combined for fish 

assessments, because upon delineating the assessment sites it was found that the X and B 

assessment reaches overlapped. Only those stream sites where a minimum of 25 individual fish 

were captured were used in computing fish IBI scores. 

24
6.2 Watershed Land Use Identification and Quantification - Relationships 

Among Agricultural Land Use and Physical, Chemical, and Biological 

Measures 

The primary land use in the study area, determined from the 1991 – 1993 WISCLAND 

(LANDSAT) data, was agriculture (40%) followed by forest cover (37%), grassland (13%), wetland 

(5%), open water (2%), urban land (1%), and miscellaneous other (2%). Watershed area 

upstream from the X sites ranged from 102 acres to 81,881 acres, with an average size of 7,268 

acres. For the reference sites, watershed sizes ranged from 123 acres to 34,450 acres, with an 

average watershed size of 5,532 acres. 

The total percentage of land area identified as row cropland within the X site watersheds ranged 

from zero to 82%, with an average of 19%. The total land area identified as row cropland in the 

reference site watersheds ranged from zero to 41%, with an average of 14.5%. Forest cover in 

the X site watersheds ranged from zero to 86% with an average of 43%, and in the reference site 

watersheds forest cover ranged from 15% to 99%, with an average of 41%. Pearson correlations 

were calculated to evaluate whether percent agricultural land, percent grassland, or percent forest 

cover within watersheds had detectable relationships with various riparian and in-stream physical 

habitat measures. Data collected at both the random X sites and the minimally disturbed 

reference sites were used in these analyses. No significant correlations were observed among 

the in-stream physical habitat measures and the surrounding watershed land use (Table 1). 

Stepdown Bonferroni adjusted p-values equal 1.00 for all correlations in Table 1. 

Table 1. Pearson correlations between watershed land use and in-stream physical 

habitat measures (N = 78). 

Habitat Measures % Agriculture % Grassland % Forest 

% Sand, silt, and rs = -0.163 0.138 0.125

clay sediments p-value = 0.153 0.230 0.276

Bank rs = -0.069 0.114 0.041

erosion p-value = 0.550 0.318 0.721

Depth of rs = -0.001 0.087 -0.068

fine substrate p-value = 0.993 0.446 0.552

Sinuosity rs = 0.049 0.093 -0.052

 p-value = 0.667 0.420 0.649

Distance rs = 0.132 0.063 -0.178

between bends p-value = 0.250 0.581 0.120

Riffle rs = -0.042 0.058 0.049

length p-value = 0.716 0.615 0.670

Pool rs = 0.020 -0.022 -0.001

length p-value = 0.866 0.851 0.993

Riparian rs = -0.185 0.062 0.178

buffer p-value = 0.106 0.590 0.120

Width:Depth rs = -0.139 -0.080 0.173

ratio p-value = 0.224 0.486 0.129

25
Pearson correlations and associated p-values were calculated to evaluate relationships between 

watershed land use and stream water quality and water chemistry measures, and these original pvalues are presented in Table 2. In addition, Stepdown Bonferroni adjustments were applied and 

the resulting adjusted p-values are provided in parentheses. Nitrate-nitrite and conductivity were 

found to be significantly correlated with percent agriculture and forest cover. 

Table 2. Pearson correlations between watershed land use and water quality and water 

chemistry measures. P values in bold are significant when a Stepdown Bonferroni 

adjustment is applied. 

Water Quality and Chemistry % Agriculture % Grassland % Forest 

N-Kjeldahl rs = 0.109 -0.058 -0.152

 p-value = 0.332 (1.00) 0.610 (1.00) 0.177 (1.00)

 N = 80 80 80

NH3 rs = 0.118 -0.015 -0.171

 p-value = 0.298 (1.00) 0.892 (1.00) 0.130 (1.00)

 N = 80 80 80

NO3NO2 rs = 0.606 -0.149 -0.586

 p-value = <.001 (0.003) 0.188 (1.00) <.001 (0.003)

 N = 80 80 80

Total rs = 0.113 -0.143 -0.169

Dissolved p-value = 0.317 (1.00) 0.207 (1.00) 0.135 (1.00)

Phosphorus N = 80 80 80

Total rs = -0.017 -0.0417 -0.037

Phosphorus p-value = 0.878 (1.00) 0.714 (1.00) 0.742 (1.00)

 N = 80 80 80

Dissolved rs = -0.064 0.228 0.047

O2 p-value = 0.572 (1.00) 0.042 (1.000) 0.678 (1.00)

 N = 80 80 80

% O2 rs = 0.099 0.113 -0.101

Saturation p-value = 0.380 (1.00) 0.319 (1.00) 0.373 (1.00)

 N = 80 80 80

Temperature rs = 0.235 -0.170 -0.207

 p-value = 0.036 (0.999) 0.132 (1.00) 0.066 (1.00)

 N = 80 80 80

Transparency rs = -0.069 0.194 0.031

 p-value = 0.544 (1.00) 0.085 (1.00) 0.788 (1.00)

 N = 80 80 80

pH rs = 0.272 -0.051 -0.217

 p-value = 0.018 (0.513) 0.661 (1.00) 0.060 (1.00)

 N = 76 76 76

Conductivity rs = 0.544 -0.093 -0.543

 p-value = <.001 (0.003) 0.429 (1.00) <.001 (0.003)

 N = 75 75 75

Stepdown Bonferroni adjusted p-values are in parentheses. 

26
Pearson correlations were also calculated to evaluate the sensitivity of the macroinvertebrate and 

fish assemblage metrics to specific environmental stress factors such as high percentages of 

cropland in the watersheds, in-stream or riparian physical habitat degradation, or chemical 

pollutants. The percentage of EPT macroinvertebrate genera present, HBI score, percentage of 

‘tolerant’ fish individuals present, and fish IBI score were compared with 9 in-stream habitat 

measures, 3 watershed-scale land use measures, and 11 water quality and water chemistry 

measures (Tables 3, 4). Macroinvertebrate measures showed stronger correlations with physical 

habitat data than the fish measures, based on the Pearson correlations presented in Table 3, and 

statistically significant correlations were observed between macroinvertebrate measures and 7 of 

the 11 water quality and water chemistry measures when Stepdown Bonferroni adjustments were 

applied (Table 4). 

27
Table 3. Pearson correlations between in-stream physical habitat, watershed land use, 

and biological measures. 

Habitat Parameters % EPT 

Genera HBI Score % Tolerant Fish 

Individuals IBI Score 

% Sand, silt, rs = -0.247 0.177 0.055 -0.062

and clay p-value* = 0.030 (1.00) 0.127 (1.00) 0.676 (1.00) 0.640 (1.00)

sediments N = 77 76 61 60

Bank rs = -0.360 0.261 0.372 -0.198

erosion p-value = 0.001 (0.062) 0.023 (0.866) 0.003 (0.150) 0.130 (1.00)

 N = 77 76 61 60

Depth of rs = -0.126 0.281 0.036 -0.104

fine p-value = 0.275 (1.00) 0.014 (0.592) 0.768 (1.00) 0.430 (1.00)

substrate N = 77 76 61 60

Sinuosity rs = -0.227 0.112 0.281 -0.256

 p-value = 0.048 (1.00) 0.336 (1.00) 0.028 (1.00) 0.049 (1.00)

 N = 77 76 61 60

Distance rs = -0.284 0.144 0.130 -0.119

between p-value = 0.012 (0.533) 0.214 (1.00) 0.319 (1.00) 0.365 (1.00)

bends N = 77 76 61 60

Riffle rs = 0.232 -0.332 -0.181 0.204

length p-value = 0.043 (1.00) 0.003 (0.150) 0.163 (1.00) 0.117 (1.00)

 N = 76 76 61 60

Pool rs = 0.052 0.012 0.007 0.016

length p-value = 0.656 (1.00) 0.915 (1.00) 0.958 (1.00) 0.902 (1.00)

 N = 77 76 61 60

Riparian rs = 0.271 -0.168 -0.273 0.328

buffer p-value = 0.017 (0.688) 0.146 (1.00) 0.033 (1.00) 0.011 (0.477)

 N = 77 76 61 60

Width:Depth rs = 0.191 -0.249 -0.241 0.120

ratio p-value = 0.096 (1.00) 0.030 (1.00) 0.061 (1.00) 0.362 (1.00)

 N = 77 76 61 60

% rs = -0.259 0.283 0.071 -0.265

Agriculture p-value = 0.020 (0.796) 0.012 (0.533) 0.589 (1.00) 0.041 (1.00)

 N = 80 79 61 60

% 

Grassland rs = 0.209 -0.274 0.012 0.198

 p-value = 0.063 (1.00) 0.015 (0.599) 0.928 (1.00) 0.129 (1.00)

 N = 80 79 61 60

% Forest rs = 0.232 -0.254 -0.062 0.205

 p-value = 0.038 (1.00) 0.024 (0.881) 0.635 (1.00) 0.116 (1.00)

 N = 80 79 61 60

*Stepdown Bonferroni adjusted p-values are in parentheses. 

28
Table 4. Pearson correlations between water quality and water chemistry measures, and 

biological measures. P-values in bold are significant when a Stepdown Bonferroni 

adjustment is applied. 

Water Quality and 

Chemistry 

% EPT 

Genera HBI Score 

% Tolerant 

Fish 

Individuals 

IBI Score 

N-Kjeldahl rs = -0.491 0.564 0.263 -0.374

 p-value* = <.001 (0.004) <.001 (0.004) 0.041 (0.851) 0.003 (0.099)

 N = 79 78 61 60

NH3 rs = -0.429 0.537 0.232 -0.348

 p-value = <.001 (0.004) <.001 (0.004) 0.073 (1.00) 0.007 (0.176)

 N = 79 78 61 60

NO3NO2 rs = -0.011 0.101 -0.259 -0.001

 p-value = 0.921 (1.00) 0.377 (1.00) 0.044 (0.874) 0.996 (1.00)

 N = 79 78 61 60

Total rs = -0.346 0.418 -0.059 -0.241

Dissolved P p-value = 0.002 (0.058) <.001 (0.004) 0.651 (1.00) 0.064 (1.00)

N = 79 78 61 60

Total P rs = -0.361 0.388 0.055 -0.318

 p-value = <.001 (0.004) 0.005 (0.143) 0.674 (1.00) 0.013 (0.335)

 N = 78 78 61 60

Dissolved rs = 0.312 -0.487 -0.357 0.332

O2 p-value = 0.005 (0.143) <.001 (0.004) 0.005 (0.143) 0.010 (0.250)

 N = 79 78 61 60

% O2 rs = 0.150 -0.397 -0.216 0.172

Saturation p-value = 0.187 (1.00) 0.003 (0.099) 0.094 (1.00) 0.190 (1.00)

 N = 79 78 61 60

Temperature rs = -0.350 0.215 0.280 -0.316

 p-value = 0.002 (0.007) 0.058 (1.00) 0.030 (0.669) 0.014 (0.335)

 N = 79 78 61 60

Transparency rs = 0.435 -0.413 -0.267 0.373

 p-value = <.001 (0.004) 0.002 (0.007) 0.038 (0.834) 0.003 (0.099)

 N = 79 78 61 60

pH rs = -0.218 -0.036 0.091 -1.071

 p-value = 0.060 (1.00) 0.763 (1.00) 0.491 (1.00) 0.594 (1.00)

 N = 75 74 60 59

Conductivity rs = -0.138 -0.018 0.157 -0.159

 p-value = 0.243 (1.00) 0.882 (1.00) 0.235 (1.00) 0.232 (1.00)

 N = 74 73 59 58

 *Stepdown Bonferroni adjusted p-values are in parentheses. 

29
6.3 Random, Modified-Random, and Reference Site Comparisons 

Stream Physical Habitat Measures 

Each of the 9 physical habitat measures collected at the X sites was compared with its associated 

B site value using Pearson correlations and bivariate scatterplots (Figure 2). Large correlation 

coefficients (r) and significant p-values were observed for 8 of the 9 habitat variables. The only 

physical habitat variable that did not show a significant correlation between the X and B sites was 

mean total sum of pool habitat length. 

0

2

4

6

8

10

0 2 4 6 8 10

X-site riparian buffer width (m)

B-site riparian buffer width (m)

r = 0.429

p = 0.001

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

X-site bank erosion (m)

B-site bank erosion (m)

r = 0.617

p < 0.001

0

25

50

75

100

125

150

0 25 50 75 100 125 150

X-site distance between bends (m)

B-site distance between bends (m)

r = 0.307

p = 0.020

0

20

40

60

80

100

0 20 40 60 80 100

X-site pool length (m)

B-site pool length (m)

r = 0.054

p = 0.689

0

10

20

30

40

0 10 20 30 40

X-site width : depth ratio

B-site width : depth ratio

r = 0.587

p < 0.001

0

0.3

0.6

0.9

0 0.3 0.6 0.9

X-site fine sediment depth (m)

B-site fine sediment depth (m)

r = 0.329

p = 0.012

0

0.5

1

1.5

2

2.5

0 0.5 1 1.5 2 2.5

X-site sinuosity

B-site sinuosity

r = 0.869

p < 0.001

0

10

20

30

40

0 10 20 30 40

X-site riffle length (m)

B-site riffle length (m)

r = 0.896

p < 0.001

0

20

40

60

80

100

0 20 40 60 80 100

X-site % sand/silt/clay

B-site % sand/silt/clay

r = 0.646

p < 0.001

Figure 2. Bivariate scatterplots comparing physical habitat measurements collected at 

the X and associated B sites. 

30
Weighted paired t-tests were used to determine if significant differences existed in physical habitat 

data between the X and B sites. The weighted paired t-tests did not produce statistically 

significant p-values for any of the 9 physical habitat measures, indicating that there were no 

significant differences between the X and B sites for these variables (Table 5). 

Table 5. Weighted paired t-test comparisons of stream physical habitat measures from X 

and B stream assessment sites. 

X vs B Site Physical Habitat Measures 

(n = 57) 

t-value* p-value 

Mean Riparian Buffer Width (m) 1.68 0.0981 

Mean Length of Pools (m) -1.61 0.1125 

Sinuosity 1.84 0.0712 

Mean Width of Bank Erosion (m) 0.36 0.7218 

Width : Depth Ratio -1.64 0.1060 

Mean Length of Riffles (m) 1.74 0.0878 

Mean Distance Between Bends (m) 1.85 0.0697 

Mean Depth of Fines (m) -0.52 0.6081 

Percent Sand, Silt, and/or Clay Sediments -0.05 0.9609 

*Degrees of freedom = 56. 

31
Water Chemistry and Water Quality Measures 

Each of the 11 water quality and water chemistry measures collected at the X sites was compared 

with its associated B site value using Pearson correlations and bivariate scatterplots (Figure 3). 

 

0

0.1

0.2

0.3

0 0.1 0.2 0.3

X-site NH3 (mg/L)

B-site NH3 (mg/L)

r = 0.436

p = 0.001

0

5

10

15

20

25

0 5 10 15 20 25

X-site NO3-NO2 (mg/L)

B-site NO3-NO2 (mg/L)

r = 0.929

p < 0.001

0

0.1

0.2

0.3

0.4

0 0.1 0.2 0.3 0.4

X-site total dissolved P (mg/L)

B-site total dissolved P (mg/L)

r = 0.848

p < 0.001

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

X-site total P (mg/L)

B-site total P (mg/L)

r = 0.860

p < 0.001

0

2

4

6

8

10

12

14

0 2 4 6 8 10 12 14

X-site dissolved O2 (mg/L)

B-site dissolved O2 (mg/L)

r = 0.804

p < 0.001

0

26

52

78

104

130

0 26 52 78 104 130

X-site % O2 saturation

B-site % O2 saturation

r = 0.812

p < 0.001

0

500

1000

1500

2000

0 500 1000 1500 2000

X-site conductivity (uS)

B-site conductivity (uS)

r = 0.950

p < 0.001

6

6.5

7

7.5

8

8.5

9

6 6.5 7 7.5 8 8.5 9

X-site pH

B-site pH

r = 0.889

p < 0.001

0

25

50

75

100

125

0 25 50 75 100 125

X-site transparency (cm)

B-site transparency (cm)

r = 0.881

p < 0.001

0

5

10

15

20

25

30

0 5 10 15 20 25 30

X-site water temperature (C)

B-site water temperature (C)

r = 0.901

p < 0.001

0

0.4

0.8

1.2

1.6

0 0.4 0.8 1.2 1.6

X-site N-Kjeldahl (mg/L)

B-site N-Kjeldahl (mg/L)

r = 0.735

p < 0.001

Figure 3. Bivariate scatterplots comparing water quality and water chemistry 

measurements collected from the X and associated B sites. 

32
Large correlation coefficients (r) with significant p-values were observed for all 11 water quality 

and chemistry variables (Figure 3), showing a strong linear relationship between X site and B site 

data. The results of weighted paired t-tests evaluating water quality and water chemistry 

measures show no significant differences between the X and B site data for all 11 variables 

(Table 6). 

Table 6. Weighted paired t-test comparisons of water quality and water chemistry 

measures from the X and associated B assessment sites. 

X vs B Site Water Chemistry Measures 

(n = 57) 

t-value* p-value 

Total Phosphorus (mg/L) 1.69 0.0965 

Total Dissolved Phosphorus (mg/L) 2.88 0.0056 (0.0617)† 

NH3 (mg/L) -0.08 0.9344 

NO3-NO2 (mg/L) -2.28 0.0264 (0.2904) 

N-Kjeldahl (mg/L) 1.09 0.2809 

Dissolved Oxygen (mg/L) 1.04 0.3010 

Percent Dissolved Oxygen Saturation 1.06 0.2946 

pH (df=55) -1.89 0.0644 

Conductivity (uS/cm) (df=52) -1.26 0.2140 

Water Temperature (C) 0.21 0.8377 

Transparency (cm) -1.53 0.1319 

*Degrees of freedom = 56, unless otherwise noted. 

†Value in parentheses is the Bonferroni-adjusted p-value.

33
Macroinvertebrate Metrics 

Figure 4 shows the relationships between the 7 macroinvertebrate metrics collected at each X 

and associated B site. Pearson correlation coefficients and bivariate scatterplots show significant 

p-values and correlations (r) between X and B site data for all 7 macroinvertebrate metrics, 

indicating strong linear relationships between the X and B sites. 

0

10

20

30

40

0 10 20 30 40

X-site species richness

B-site species richness

r = 0.733

p < 0.001

0

2

4

6

8

10

0 2 4 6 8 10

X-site HBI score

B-site HBI score

r = 0.805

p < 0.001

0

20

40

60

80

100

0 20 40 60 80 100

X-site % EPT individuals

B-site % EPT individuals

r = 0.616

p < 0.001

0

2

4

6

8

10

12

0 2 4 6 8 10 12

X-site % EPT genera

B-site % EPT genera

r = 0.755

p < 0.001

0

10

20

30

40

50

0 10 20 30 40 50

X-site % 'shredders'

B-site % 'shredders'

r = 0.667

p < 0.001

0

1

2

3

4

5

012345

X-site Shannons Diversity Index

B-site Shannons Diversity Index

r = 0.782

p < 0.001

0

10

20

30

40

50

60

70

0 10 20 30 40 50 60 70

X-site % 'scrapers'

B-site % 'scrapers'

r = 0.681

p < 0.001

Figure 4. Bivariate scatterplots comparing macroinvertebrate metrics collected at the X 

and associated B sites. 

34
Weighted paired t-tests were used to compare macroinvertebrate samples collected at the X and 

associated B sites. The results show no significant differences between these paired sites for any 

of the 7 metrics (Table 7). 

Table 7. Weighted paired t-test comparisons of macroinvertebrate metrics and indices 

collected from X and associated B assessment sites. 

X vs B Site Macroinvertebrate Metrics 

(n = 56)

t-value* p-value 

Species richness 0.42 0.6739 

Percent EPT genera present 0.02 0.9865 

Shannon's Diversity Index score -0.46 0.6473 

Hilsenhoff’s Biotic Index score -0.69 0.4962 

Percent Shredders -1.23 0.2244 

Percent Scrapers 0.33 0.7406 

Percent EPT individuals present 0.12 0.9056 

*Degrees of freedom = 55. 

35
Fish Assemblage Metrics 

Bivariate scatterplots and Pearson correlation coefficients show that significant correlations exist 

between X and B site data for all 8 fish metrics analyzed (Figure 5). 

0

5

10

15

20

0 5 10 15 20

X-site species richness

B-site species richness

r = 0.901

p < 0.001

0

500

1000

1500

2000

0 500 1000 1500 2000

X-site # fish captured

B-site # fish captured

r = 0.924

p < 0.001

0

20

40

60

80

100

0 20 40 60 80 100

X-site % 'tolerant' individuals

B-site % 'tolerant' individuals

r = 0.659

p < 0.001

0

1

2

3

4

5

6

0123456

X-site # 'intolerant' species

B-site # 'intolerant' species

r = 0.841

p < 0.001

0

20

40

60

80

100

0 20 40 60 80 100

X-site % top carnivores

B-site % top carnivores

r = 0.854

p < 0.001

0

20

40

60

80

100

0 20 40 60 80 100

X-site % stenotherms

B-site % stenotherms

r = 0.765

p < 0.001

0

20

40

60

80

100

0 20 40 60 80 100

X-site % brook trout

B-site % brook trout

r = 0.918

p < 0.001

0

20

40

60

80

100

0 20 40 60 80 100

X-site IBI score

B-site IBI score

r = 0.866

p < 0.001

Figure 5. Bivariate scatterplots comparing fish metrics collected at the X and associated 

B sites. 

36
Weighted paired t-tests were used to determine if significant differences existed between the X 

and B sites. Of the 58 streams sampled, 42 streams had sufficient numbers of fish at both the X 

and associated B sites with which to make paired-site t-test comparisons. The results of the 

weighted paired t-tests show no significant differences between X and B sites (Table 8). 

Table 8. Weighted paired t-test comparisons of fish metrics collected from X and B 

assessment sites. 

X vs B Site Fish Community Metrics 

(n = 42) 

t-value* p-value 

Species Richness -2.17 0.0358 

(0.2509)† 

Number of Intolerant Species 0.06 0.9553 

Percent of Salmonid Individuals that are Brook Trout 1.08 0.2883 

Percent of Individual that are Top Carnivore Species -1.58 0.1219 

Coldwater IBI Score -0.77 0.4471 

Percent of Individuals that are ‘Tolerant’ Species -0.34 0.7368 

Percent of Individuals that are Stenothermal Cool / Coldwater Species 0.20 0.8406 

*Degrees of freedom = 41.

†Value in parentheses is the Bonferroni-adjusted p-value. 

37
6.4 Comparison of Reference Sites with Random and Modified-Random 

Assessment Sites 

Stream Physical Habitat Measures 

Bar charts were used to visually compare data for 9 physical habitat measures collected at the X, 

B, and reference sites (Figure 6). 

Ref Bridge X-Site

0.00

0.05

0.10

0.15

0.20

0.25

Mean Depth of Fines m( )

Ref Bridge X-Site

0

20

40

60

80

100

Distance be wt een Bends m( )

Ref Bridge X-Site

0

5

10

15

Mean Buffer Width m( )

Ref Bridge X-Site

0

20

40

60

80

100

%

Sand S/ ilt C/ lay

Ref Bridge X-Site

0

10

20

30

40

Mean Riffle Length m( )

Ref Bridge X-Site

0.0

0.2

0.4

0.6

0.8

1.0

Mean bank erosion m( )

Ref Bridge X-Site

0.0

0.5

1.0

1.5

2.0

2.5

Sinuosity

Ref Bridge X-Site

0

10

20

30

Mean Pool Length m( )

Ref Bridge X-Site

0

20

40

60

80

100

Width D: epth Ratio

Figure 6. Bar charts of weighted means and standard deviations (SD) for X and B sites 

and simple random sample mean and SD for reference sites for physical habitat 

measures. 

38
Two-sample t-tests were used to compare the 9 physical habitat measures collected at the X sites 

with data collected at the least disturbed reference sites. The mean width of stream bank erosion 

and the mean width of riparian buffer were the only measures that showed a significant difference 

between the X sites and the reference sites (Table 9). 

Table 9. Two sample t-test comparisons for physical habitat measures collected at the X 

and reference sites. Tests are based on the difference (X site mean - reference mean) 

and use weighted values for X sites. 

X vs Reference Site Habitat Measures t-value p-value* 

Mean Depth of Fines (m) 0.631 0.5300 

Mean Distance Between Bends (m) 0.287 0.7746 

Mean Riparian Buffer Width (m) -4.869 <0.0001 

Percent Sand, Silt, and/or Clay Sediments 1.855 0.0675 

Mean Length of Riffles (m) (df=75) -0.504 0.6159 

Mean Width of Bank Erosion (m) 3.570 0.0006 

Sinuosity 0.742 0.4605 

Mean Length of Pools (m) (df=75) -1.913 0.0596 

Width:Depth Ratio -1.575 0.1195 

*P-values in bold are significant (p < 0.006) when a Bonferroni correction is applied for an overall Type I error rate of 

0.05. Degrees of freedom = 76, unless otherwise noted. 

39
Water Quality and Water Chemistry Measures 

Bar charts were used to visually compare data for 11 water chemistry and water quality measures 

among the X, B, and reference sites (Figure 7). 

Ref Bridge X-Site

0.0

0.2

0.4

0.6

0.8

1.0

Kjeldahl N- m( g/L)

Ref Bridge X-Site

0.0

0.1

0.2

0.3

0.4

0.5

Total P m( g/L)

Ref Bridge X-Site

0

50

100

150

Transparency (cm)

Ref Bridge X-Site

0.00

0.03

0.06

0.09

0.12

0.15

NH3 m( g/L)

Ref Bridge X-Site

0

4

8

12

Dissolved O2 m( g/L)

Ref Bridge X-Site

0

2

4

6

8

10

pH

Ref Bridge X-Site

0

2

4

6

8

10

NO3 N- O2 m( g/L)

Ref Bridge X-Site

0

20

40

60

80

100

%

O2 Saturation

Ref Bridge X-Site

0

200

400

600

800

1000

Conductivity (uS/cm)

Ref Bridge X-Site

0.00

0.06

0.12

0.18

0.24

0.30

Total Dissolved P m( g/L)

Ref Bridge X-Site

0

5

10

15

20

25

Water Temperature C( )

Figure 7. Bar charts of means and standard deviations for water quality and water 

chemistry measures collected at the X, B, and reference stream sites. Values for X and B 

sites are weighted. 

40
Two-sample t-tests were used to compare the 6 in-situ water quality and 5 lab-analyzed grabsample water chemistry measures collected at the X and reference sites. Eight of these 11 

measures were found to be significantly different at the X sites versus the reference sites (Table 

10). 

Table 10. Two-sample t-test comparisons of water quality and water chemistry values 

between the X and reference stream sites. Tests are based on the difference (X site 

mean - reference mean) and use weighted values for X sites. 

X vs Reference Site Water Chemistry Measures t-value p-value* 

Kjeldahl-N (mg/L) 5.410 <0.0001 

Total Phosphorus (mg/L) 4.376 <0.0001

Transparency (cm) -5.243 <0.0001

NH3 (mg/L) 5.137 <0.0001

Dissolved Oxygen (mg/L) -4.850 <0.0001

pH (df = 74) 0.953 0.3436 

NO3-NO2 (mg/L) 1.100 0.2748 

Percent Dissolved Oxygen Saturation -2.910 0.0047 

Conductivity (uS/cm) (df = 73) 0.122 0.9035 

Total Dissolved Phosphorus (mg/L) 4.470 <0.0001 

Water Temperature (C) 3.745 0.0003 

*P-values in bold are significant (p < 0.005) when a Bonferroni correction is applied for an overall Type I error rate of 

0.05. Degrees of freedom = 78, unless otherwise noted. 

41
Macroinvertebrate Metrics 

Bar charts were used to visually compare data among X, B, and reference sites for 

macroinvertebrate metrics (Figure 8). 

 

Ref Bridge X-Site

0

10

20

30

40

Species Richness

Ref Bridge X-Site

0

10

20

30

% Scrapers

Ref Bridge X-Site

0

1

2

3

4

5

Shannon Diversity Index

Ref Bridge X-Site

0

2

4

6

8

HBI Score

Ref Bridge X-Site

0

5

10

15

20

% Shredders

Ref Bridge X-Site

0

20

40

60

80

100

% EPT Individuals

Ref Bridge X-Site

0

10

20

30

40

50

60

70

% EPT Genera

Figure 8. Bar charts of mean and standard deviation of macroinvertebrate metrics 

collected at the X, B, and reference stream sites. Values for X and B sites are weighted. 

Two sample t-tests comparing 7 macroinvertebrate metrics for data collected at the X and 

reference sites show significant differences in HBI scores, and the percentage of genera and 

individuals in the sample that are Ephemeroptera, Plecoptera and Trichoptera (EPT) taxa. The 

lower HBI scores and the higher percentages of EPT genera or EPT individuals found at the 

reference sites relative to the X sites indicate that the reference streams have greater biological 

quality and a greater percentage of environmentally sensitive taxa than the X stream sites. No 

significant differences were detected between the X and reference stream populations for species 

richness, Shannon’s Diversity Index, the percent ‘shredders’, and the percent ‘scrapers’ present 

(Table 11). 

42
Table 11. Two sample t-test comparisons of the X and reference site macroinvertebrate 

metrics. Tests are based on the difference (X site mean - reference mean) and use 

weighted values for X sites. 

 X vs Reference Site Macroinvertebrate Metrics t-value p-value* 

Species Richness 1.900 0.0611 

Percent Scrapers 0.091 0.9279 

Shannon's Diversity Index Score 0.691 0.4915 

Hilsenhoff’s Biotic Index Score (HBI) 5.307 <0.0001 

Percent Shredders -1.689 0.0953

Percent EPT Individuals -5.439 <0.0001 

Percent EPT Genera -14.772 <0.0001 

*P-values in bold are significant (p < 0.007) when a Bonferroni correction is applied for an overall Type I error rate of 

0.05. Degrees of freedom = 77. 

43
Fish Metrics 

Bar charts were used to visually compare distributions of fish metrics among X, B, and reference 

sites (Figure 9). 

 

Ref Bridge X-Site

0

1

2

3

4

5

# Intolerant Species

Ref Bridge X-Site

0

50

100

150

%

Stenothe mr s

Ref Bridge X-Site

0

20

40

60

80

100

Coldwater IBI Score

Ref Bridge X-Site

0

20

40

60

80

100

%

Tolerant Individuals

Ref Bridge X-Site

0

25

50

75

100

125

% Brook Trout

Ref Bridge X-Site

0

5

10

15

Species Richness

Ref Bridge X-Site

0

20

40

60

80

100

%

Top Carnivores

Figure 9. Bar charts of mean and standard deviation of fish metrics collected at the X, B, 

and reference stream sites. Values for X and B sites are weighted. 

44
Fish IBI scores were significantly different between the X and reference sites, when compared 

using two-sample t-tests. The mean IBI score for the X sites population was 34 (narrative rating 

of “Fair”), versus 70 (narrative rating of “Good”) for the reference condition. In addition, there 

were significant differences found in species richness, percentage of individuals captured that are 

considered “tolerant”, percentage of individuals captured that are top carnivores, and the 

percentage of individuals that are cool/coldwater stenotherms (as defined by Lyons 1996). There 

were no significant differences observed between the X stream population and the reference 

condition for the number of intolerant species present or the percentage of salmonids captured 

that were brook trout. (Table 12) 

Table 12. Two-sample t-test comparisons of the X and reference site fish metrics. Test is 

based on the difference (X site mean - reference mean). 

X vs Reference Site Fish Metrics t-value p-value* 

Number of Intolerant Species (df=59) -2.319 0.0239 

Percent of Individuals that are Stenothermal Cool or Coldwater 

Species -7.427 <0.0001 

Coldwater IBI score -7.021 <0.0001

Percent of Individuals that are Tolerant Species 6.165 <0.0001

Percent of Salmonid Individuals that are Brook Trout (df=59) -2.087 0.0412 

Species Richness (df=59) 3.183 0.0023 

Percent of Individuals that are Top Carnivore Species -4.632 <0.0001 

*P-values in bold are significant (p < 0.007) when a Bonferroni correction is applied for an overall Type I error rate of 

0.05. Degrees of freedom = 58, unless otherwise noted. 

45
6.5 Probability Estimates and Evaluation of Population Distributions 

Physical Habitat Cumulative Distributions 

Empirical CDFs were plotted to further compare differences between the X and B site data, and 

to estimate the percentage of the X and B sample populations that met reference condition 

threshold values. For each physical habitat measure, either the 25th or 75th percentile calculated 

from the least disturbed reference sites population was used as a reference condition threshold 

(Table 13). The upper 75th percentiles calculated from least disturbed reference sites were 

used as the thresholds for the percentage of sand, silt, and clay substrates, the mean depth of 

fine sediments, the width:depth ratio, the mean distance between bends, and the mean erosion 

width. The 25th percentile was used as the threshold for mean riparian buffer width. 

The X and B site cumulative distribution functions and their confidence intervals overlap for all of 

the physical habitat measures analyzed (Figure 10), indicating the population estimates of these 

measures are not significantly different between the random and modified-random sites. The 

results of Kolmogorov-Smirnov tests (Dmax values) also found no significant differences (all Dmax 

p-values > 0.05). 

Table 13. Physical habitat reference condition thresholds. 

Habitat Measures 

Reference 

Condition 

Threshold 

Impairment Criteria 

% sand, silt, and clay sediments 66.8% > 66.8% sand, silt and clay 

mean depth of fine sediment (m) 0.122 > 0.122m mean depth of fines 

width : depth ratio 18.4 > 18.4 width : depth ratio 

mean distance between bends (m) 42 > 42m distance between bends 

mean riparian buffer width (m) 9.5 < 9.5m mean buffer width 

mean bank erosion width ( m) 0.104 > 0.104m mean bank erosion 

46
0

20

40

60

80

100

0 20 40 60 80 100

% Sand, Silt, and Clay Sediment

Population Estimate (%)

Dmax = 0.178

0

20

40

60

80

100

0 20 40 60 80 100 120 140

Mean Distance Between Bends (m)

Population Estimate (%)

Dmax = 0.201

0

20

40

60

80

100

0 5 10 15 20 25 30

Width:Depth Ratio

Population Estimate (%)

Dmax = 0.096

0

20

40

60

80

100

0 1 2 3 4 5 6 7 8 9 10

Mean Riparian Buffer Width(m)

Population Estimate (%)

Dmax = 0.157

0

20

40

60

80

100

0.0 0.2 0.4 0.6 0.8 1.0

Mean Depth of Fines (m)

Population Estimate (%)

Dmax = 0.116

0

20

40

60

80

100

0.0 0.2 0.4 0.6 0.8 1.0

Mean Bank Erosion Width (m)

Population Estimate (%)

Dmax = 0.161

 X site CDF X site 95% C.I. B site CDF B site 95% C.I.

Figure 10. Cumulative distribution function curves of physical habitat measures 

collected at the X and B sites. The stippled lines represent 95% confidence intervals 

around the distribution plots. The vertical lines represent the reference condition 

threshold values. 

47
Reference condition threshold values were applied to the CDF data to approximate the percent of 

the stream population (miles) that did not meet these criteria and therefore received a ‘poor’ rating 

(Figure 11). Overlapping error bars show no significant differences between the X site population 

and the B site population for all physical habitat measures presented in Figure 11. 

0

10

20

30

40

50

60

70

80

90

100

% sand,

silt, clay

depth of

fines (m)

distance

between

bends (m)

erosion

width (m)

riparian

buffer (m)

width :

depth ratio

% stream miles rated 'poor'

B sites

X sites

Figure 11. The percentages of stream miles not meeting the reference condition 

threshold values for physical habitat measures. The error bars equal 1 standard error. 

48
Water Quality and Water Chemistry Cumulative Distributions 

Cumulative distribution functions were plotted for 10 water quality and water chemistry measures. 

Either the 25th or 75th percentile of each water quality and water chemistry measure calculated 

from the least disturbed reference sites were used to set reference condition thresholds (Table 

14). The 75th percentile calculated from the reference sites was used as the threshold for 

Kjeldahl-N, NH3, NO3-NO2, total dissolved P, and total P. The 25th percentile was used as the 

threshold for the percentage dissolved oxygen saturation, dissolved oxygen concentration, and 

water clarity. 

Table 14. Water chemistry and water quality reference condition thresholds. 

Water Chemistry & Quality 

Measures 

Reference Condition 

Threshold 

Impairment Criteria 

% Oxygen Saturation 73.3% < 73.3% dissolved oxygen 

saturation 

Transparency (cm) 122 < 122cm water transparency 

Dissolved Oxygen (mg/L) 7.6 < 7.6 mg/L dissolved oxygen 

conc. 

Kjeldahl-N (mg/L) 0.15 > 0.15 mg/L concentration 

NH3 (mg/L) 0.028 > 0.028 mg/L concentration 

NO3-NO2 (mg/L) 2.63 > 2.63 mg/L concentration 

Total Dissolved P (mg/L) 0.04 > 0.04 mg/L concentration 

Total P (mg/L) 0.07 > 0.07 mg/L concentration 

49
0

20

40

60

80

100

30 50 70 90 110 130

% Oxygen Saturation

Dmax

Population Estimate (%)

 = 0.102

0

20

40

60

80

100

2 4 6 8 10 12 14

Dissolved O2 (mg/L)

Dmax = 0.158

Population Estimate (%)

0

20

40

60

80

100

0 20 40 60 80 100 120

Transparency (cm)

Dmax

Population Estimate (%)

 = 0.137

 X site CDF X site 95% C.I. B site CDF B site 95% C.I. 

Figure 12. Cumulative distribution function curves of water quality measures collected in 

situ at the X and B sites. The stippled lines represent 95% confidence intervals around 

the distribution functions. The vertical lines represent the reference condition threshold 

values. 

50
0

20

40

60

80

100

0.0 0.2 0.4 0.6 0.8 1.0

Total P (mg/L)

Dmax = 0.102

Population Estimate (%)

0

20

40

60

80

100

0 0.1 0.2 0.3 0.4

Total Dissolved P (mg/L)

Dmax

Population Estimate (%)

 = 0.153

0

20

40

60

80

100

0 2 4 6 8 10 12 14 16 18 20

NO3-NO2 (mg/L)

Dmax = 0.158

Population Estimate (%)

0

20

40

60

80

100

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6

Kjeldahl-N (mg/L)

Dmax = 0.128

Population Estimate (%)

0

20

40

60

80

100

0.00 0.05 0.10 0.15 0.20 0.25 0.30

NH3 (mg/L)

Dmax

Population Estimate (%)

 = 0.168

 X site CDF X site 95% C.I. B site CDF B site 95% C.I. 

Figure 13. Cumulative distribution function curves of laboratory analyzed water 

chemistry measures collected at the X and B sites. The stippled lines represent 95% 

confidence intervals around the distribution plots. The vertical lines represent the 

reference condition threshold values. 

51
All 10 water quality and water chemistry measurements have overlapping X and B site cumulative 

distribution function curves (Figures 12, 13), showing no significant differences between the X and 

B sampling sites. The results of Kolmogorov-Smirnov tests (Dmax values) also found no significant 

differences (all Dmax p-values > 0.05). Reference condition threshold values were applied to the 

CDF data and estimates of the percent of stream miles not meeting these criteria were 

determined (Figure 14). The overlapping error bars show similarities between the X site 

population and the B site population for the 8 water quality and water chemistry measures 

analyzed in Figure 14. 

0

10

20

30

40

50

60

70

80

90

100

Estimated % stream miles 'Poor'

B site

X site

% O2 

Saturation

Clarity 

(cm)

Diss. O2 

(mg/L)

Kjeldahl-N 

(mg/L)

NH3 

(mg/L)

NO3-NO2 

(mg/L)

Total Diss. 

P (mg/L)

Total P 

(mg/L)

Figure 14. The percentages of stream miles not meeting the reference condition 

threshold values for water quality and water chemistry measures. The error bars equal 1 

standard error. 

52
Macroinvertebrate CDFs 

Cumulative distribution function curves were created for 4 macroinvertebrate measures. The 

75th percentile of reference site measurements was used as the threshold for the HBI scores. 

The 25th percentile was used as the threshold for species richness, the percentage of EPT 

genera and EPT individuals present. (Table 15) 

Table 15. Macroinvertebrate metric reference condition thresholds. 

Macroinvertebrate 

Metrics 

Reference Condition 

Threshold 

Impairment Criteria 

HBI 3.92 HBI score > 3.92 

Species Richness 16 < 16 species 

% EPT Genera 35% < 35% of genera are EPT taxa 

% EPT Individuals 31% < 31% of individuals are EPT taxa 

53
0

20

40

60

80

100

5 10 15 20 25 30 35 40

Species Richness

Population Estimate (%)

Dmax = 0.139

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10

HBI Score

Population Estimate (%)

Dmax = 0.119

0

20

40

60

80

100

0 20 40 60 80 100

% EPT Individuals

Population Estimate (%)

Dmax = 0.130

0

20

40

60

80

100

0 10 20 30 40

% EPT Genera

Population Estimate (%)

Dmax = 0.088

 X site CDF X site 95% C.I. B site CDF B site 95% C.I.

Figure 15. Cumulative distribution function curves of macroinvertebrate metrics 

collected at the X and B sites. The stippled lines represent the 95% confidence intervals 

around the cumulative distribution estimates. The vertical lines represent the reference 

condition threshold values. 

The X site and B site data produced overlapping CDFs and confidence intervals for species 

richness, HBI score, the percentage of EPT genera and the percentage of EPT individuals 

(Figure 15). The results of Kolmogorov-Smirnov tests (Dmax values) also found no significant 

differences (all Dmax p-values > 0.05). Reference condition threshold values were applied to the 

CDF data and estimates of the percent of stream miles not meeting these criteria were 

determined (Figure 16). The overlapping error bars show no statistical differences between the 

X site population and the B site population for all macroinvertebrate metrics in Figure 16. The 

reference condition threshold value for the percentage of EPT genera present in a sample was 

35 percent, and no sites in the sample populations met this criteria. 

54
0

10

20

30

40

50

60

70

80

90

100

HBI Species

Richness

% EPT

Genera

% EPT

Individuals

% Stream Miles 'Poor'

B site

X site

Figure 16. The percentages of stream miles not meeting the reference condition 

threshold values for macroinvertebrate metrics. The error bars equal 1 standard error. 

Fish Cumulative Distributions 

Cumulative distribution functions were plotted for the 4 fish metrics (Figure. 17). The 75th 

percentile calculated from the reference site measurements was used as the threshold for the 

percentage of ‘tolerant’ individuals. The 25th percentile was used as the threshold for the 

percentage of stenothermal individuals present, the percentage of top carnivore individuals 

present, and the fish IBI score. (Table 16) 

Table 16. Fish metric reference condition thresholds. 

Fish Metrics Reference Condition 

Threshold 

Impairment Criteria 

% Top Carnivore Individuals 24.4% 

Any site where < 24.4% of 

individuals were not top 

predators 

% Stenothermal Individuals 83.5% 

Any site where < 83.5% of 

individuals were not 

stenotherms 

% ‘Tolerant’ Individuals 3.40% Any site where > 3.40% of 

individuals are tolerant species

IBI Score 60 Any site where fish IBI score is 

< 60 

55
 The CDF results show significant overlap between the X site and B site data, indicating that X 

and B site data provide equivalent population estimates for fish metrics. The results of 

Kolmogorov-Smirnov tests (Dmax values) also found no significant differences (all Dmax p-values > 

0.05). 

0

20

40

60

80

100

0 20 40 60 80 100

% Stenothermal Individuals

Population Estimate (%)

Dmax = 0.173

0

20

40

60

80

100

0 20 40 60 80 100

% Tolerant Individuals

Population Estimate (%)

Dmax = 0.212

0

20

40

60

80

100

0 20 40 60 80 100

% Top Carnivore Individuals

Population Estimate (%)

Dmax = 0.131

0

20

40

60

80

100

0 20 40 60 80 100

IBI Score

Population Estimate (%)

Dmax = 0.082

 X site CDF X site 95% C.I. B site CDF B site 95% C.I. 

Figure 17. Cumulative distribution function curves for fish metrics collected at the X and 

B sites. The stippled lines represent 95% confidence intervals around the distribution 

plots. The vertical lines represent the reference condition values. 

56
Fish metric reference condition threshold values were applied to the CDF data and estimates of 

the percent of stream miles not meeting these criteria were determined (Figure 18). The 

overlapping error bars show no statistical differences between the X site population and the B site 

population for all fish metrics. 

0

10

20

30

40

50

60

70

80

90

100

% Top

Carnivore

%

Stenothermal

% Tolerant IBI score

% Stream Miles 'Poor'

B site

X site

Figure 18. The percentages of stream miles not meeting the reference condition 

threshold values for fish metrics. The error bars equal 1 standard error. 

57
6.6 Targeted vs. Random Stream Assessment 

Fish Index of Biotic Integrity Cumulative Distribution Function Plots of Random and 

Regional Biologist’s Targeted Sampling Sites 

Cumulative distribution function curves and box plots show differing distributions of fish IBI scores 

between the REMAP X and WDNR regional biologist’s targeted sampling sites (Figure. 19). The 

cumulative distribution functions show that 80 percent of the REMAP random sample population 

(using weighted data) and 65 percent of the WDNR targeted stream population received an IBI 

score of 60 or less, thereby not meeting the reference condition threshold for fish IBI score. 

0

20

40

60

80

100

 Fish IBI Score

10 0 Random 

Sample

0 10 Targeted

Sample

0%

20%

40%

60%

80%

100%

0 20 40 60 80 100

Coldwater Fish IBI Score

Frequency

Figure 19. Cumulative distribution function curves of fish IBI scores from biologists’ 

targeted sites (solid bold line) and REMAP X sites (stippled bold line), compared to the 

reference condition threshold value (stippled vertical line). Box plots and distribution of 

the biologist’s targeted and REMAP X sites data is shown in figure on right. 

58
6.7 Effects of Geographical Distances Between Random and Modified-Random 

Sites 

Excluding 3 sites where the X and B reaches overlapped, the average distance from the X sites to 

the B sites was 701 meters, with a minimum distance of 106 meters and a maximum distance of 

2,283 meters. We investigated the relationships between the distance from X to B sampling sites 

for the following measures: width:depth ratio, percentage of fine substrate, percentage of EPT 

genera present, HBI score, number of fish captured, IBI score, fish species richness, dissolved 

total phosphorus, and NH3. 

0 500 1000 1500 2000 2500

Distance (m)

0

5

10

15

20

Difference in Width : Depth

0 500 1000 1500 2000 2500

Distance (m)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Differences in % Fine Substrate

0 500 1000 1500 2000 2500

Distance (m)

0

1

2

3

4

Difference in HBI Score

0 500 1000 1500 2000 2500

Distance (m)

0

1

2

3

4

5

6

Difference in % EPT Genera

0 500 1000 1500 2000 2500

Distance (m)

0

10

20

30

40

50

Difference in IBI Score

0 500 1000 1500 2000 2500

Distance (m)

0

1

2

3

4

5

6

Difference in Fish Species Richness

0 500 1000 1500 2000 2500

Distance (m)

0

100

200

300

400

500

600

Difference in # Fish Caught

0 500 1000 1500 2000 2500

Distance (m)

0.0

0.1

0.2

0.3

0.4

Total Dissolved P Differences (mg/L)

0 500 1000 1500 2000 2500

Distance (m)

0.0

0.1

0.2

0.3

NH3 Difference (mg/L)

rs = 0.112

rs = 0.033

rs = 0.077

rs = -0.138 rs = 0.084

rs = 0.250

rs = 0.209

rs = -0.208

rs = 0.195

Figure 20. Scatterplots showing relationships between the distance between the X and B 

sites, and the absolute value of the differences in physical, chemical, and biological 

measures collected at these sites. 

59
Spearman correlation coefficients (rs) indicate no significant relationships between the distance 

between the X and associated B assessment sites and any of the physical, chemical, or biological 

measures reported (Figure 20). From these coefficients, we determined that the distance 

between a random sampling site and the closest bridge sampling site did not appear to influence 

the strength of the correlations between the X and B sites data. 

60
7. Discussion 

Characterization of Stream Resources in the Driftless Area 

A primary objective of this study was to characterize the physical, chemical, and biological 

conditions of stream resources in the Driftless Area ecoregion using the EMAP probabilistic 

sampling design. Previous sampling efforts in the Driftless Area and entire state have primarily 

been targeted sampling to gather data to address stream specific data needs. These targeted 

sampling efforts may have induced intentional or unintentional biases, and have produced data 

for which confidence values cannot be estimated. This REMAP study is the first broad-scale 

assessment of stream resources by the WDNR that has produced data of known quality and 

applied objective numeric criteria to judge whether individual or populations of streams are 

physically, chemically, or biologically degraded. The 25th or 75th percentile values for various 

physical, chemical, and biological measures from the reference stream sites were used to set 

reference condition values (management expectations). Study results indicate that the 

percentages of the sample population (and by inference the entire Driftless Area stream 

population) not meeting their potential ranged from 77 to 100 percent depending upon the 

physical, chemical, or biological criteria used. While setting management goals at the 25th or 

75th percentiles is a scientifically defensible approach, setting resource management goals 

should perhaps be viewed as a societal decision. Stream assessment findings and the 

methods used to set reference conditions will stimulate further discussion within WDNR on 

which individual or combinations of measures should be used to assess stream quality, and 

what numeric criteria thresholds for these various parameters should be applied to judge stream 

quality. 

 

Differences Between Random and Modified-Random Sample Sites 

Another primary objective of this study was to evaluate whether sampling randomly selected 

stream segments at sites accessed from road crossings would provide results comparable to a 

truly randomized sampling design. None of the 35 physical, chemical, or biological, parameters 

evaluated were significantly different between the random (X) and modified-random (B) sampling 

sites. 

Given the relative homogeneity of water chemistry parameters due to mixing in lotic systems, 

intuitively, few differences would be expected to exist for these measures between the X and B 

sites. However, it is possible that tributaries intervening between the X and B sampling sites can 

change the concentration of chemical parameters, water temperature, or dissolved oxygen 

concentrations, if the tributaries have differing water chemistry concentrations, temperature, or 

dissolved oxygen concentrations than the receiving stream. Intervening groundwater or pointsource inputs could also have similar affects. 

None of the seven macroinvertebrate metrics analyzed were significantly different between and X 

and B sites. Most macroinvertebrate taxa are relatively sessile organisms and have been shown 

to be more strongly influenced by local habitat or reach-scale environmental factors than fish, 

which show a stronger response to watershed-scale influences (Barbour et al. 1999, Lammert and 

Allan 1999). Given that macroinvertebrates are thought to respond more strongly to site-specific 

or reach-scale influences, the lack of X and B site differences in the macroinvertebrate measures 

61
may be a more sensitive test of bias being induced by the modified-random sampling design than 

the fish assemblage data. 

Probabilistic Sampling Design Issues 

Fundamental principles of probabilistic sampling are that every population element in the target 

population has a known (and non-zero) probability of being sampled, and it is critically important 

to rigorously define both the target population and the elements it’s comprised of (Cochran 1977). 

A major objective of the Wisconsin REMAP study was to estimate the number of stream miles in 

the study area that were meeting physical, chemical, and biological, reference condition criteria. 

Therefore, a continuous sampling design was applied, where assessment measurements were 

taken at or in the vicinity of randomly selected points (Larsen 1997). For population elements that 

are spatially-static such as stream physical habitat (and perhaps less influenced by dynamic 

elements such as flowing water), sampling at the modified-random sites violates key principles of 

probabilistic sampling (in essence, the target population becomes the lengths of all streams that 

are within some distance of road crossings that field crews are willing to travel to reach an 

assessment site). For spatially-dynamic population elements (water chemistry parameters, fish, 

or macroinvertebrates that are strongly influenced by upstream land use and the ambient 

conditions of flowing water) is it less clear (at least to the authors) what the spatial boundaries of 

these population elements are. It is hoped that this REMAP report will generate further research 

and discussion on the validity of using road accessible stream sampling sites to characterize 

stream target populations.

The mean distance between the random and modified-random assessment sites in this study was 

approximately 701 meters (0.44 mi.). For other ecoregions in Wisconsin or areas outside the 

state with lower road density, greater land cover or land use heterogeneity, higher potential for 

intervening point sources of pollution, or greater topographic relief than the REMAP study area, 

there may be a greater potential for differences between random and modified-random 

assessment reaches. For example, in a significant proportion of northern Wisconsin road density 

is about 30 percent less than that of the REMAP study area. This increases the potential distance 

between random and road-accessible sites, and may result in greater observed differences 

between these sites. However, this portion of northern Wisconsin is also characterized by more 

homogeneous land cover and land use, and human population densities are less than in the 

REMAP study area, which may result in fewer observed differences between sites. 

It will be interesting to evaluate these types of interactions in Wisconsin’s other ecoregions. 

Sample Population Site Selection 

The finding that 71 of the randomly selected stream sites were rejected during the field 

reconnaissance effort to reach a sample population of 60 streams (nearly 120% of the original 

sample population) is of significance for stream assessment studies and programs that use 

probabilistic sampling designs. Sample designs must include sufficient over-sample populations 

to maintain target sample sizes, given that significant numbers of random sites are likely to be 

rejected. Also, project planning must incorporate a sufficient amount of time for map work to 

identify site locations, and for field time for reconnaissance of assessment sites and subsequent 

replacement of rejected sites. The fact that over half of sites were dropped due to dry stream 

channels indicates a significant amount of error in the WDNR’s perennial stream hydrography 

database for the Driftless Area Ecoregion. Only 5% of the random sites were dropped due to 

landowner access denial, which is significantly less than what the investigators had expected prior 

to the start of the study. 

62
Selection of Reference Sites and Application of Reference Condition Data 

While macroinvertebrate and fish assemblage indices are increasingly used to objectively assess 

stream resources in Wisconsin, development of reference conditions for stream physical habitat 

and water chemistry measures provides additional objective numeric criteria with which to 

evaluate the condition of individual and populations of streams. In addition, the macroinvertebrate 

and fish assemblage data collected at reference sites allowed calibration of statewide biological 

indices specifically for the study area streams, thereby increasing the accuracy of the stream 

assessments. 

 

The selection of least disturbed reference sites for this study was the first time WDNR has applied 

an a priori site selection of reference sites based on GIS data of percentages of watershed land 

use types and stream physical habitat characteristics (Hughes et al. 1986). Streams in 

watersheds with high proportions of county, state, or federal land ownership, and low proportions 

of agricultural land were evaluated as potential least disturbed reference sites. Study results 

show that on average the size of the least disturbed watersheds were smaller than the mean size 

for the random sample population watersheds. As watershed area increases there is a greater 

likelihood that agricultural and other land uses that negatively affect stream quality will occur 

within a watershed, increasing the potential cumulative negative impacts in higher order streams. 

Since stream size (Strahler order, or flow volume) is strongly influenced by watershed size, there 

presumably are fewer least disturbed large streams relative to small streams in Wisconsin. The 

influence of stream order on physical, chemical, and biological parameters is further evaluated in 

Appendix B. Stream order may have implications for setting management goals for larger 

streams. If reference conditions are developed based on data from lower order (smaller) streams, 

applying these criteria to higher order streams may result in unrealistic management goals for 

larger wadeable streams. 

A total of 60% (n = 21) of the 35 parameter comparisons between the random and reference 

stream populations were significantly different. The remaining 14 parameters that were not 

significantly different may vary little among streams in the study population, and may be 

indiscriminate measures of stream condition in the study area. Thus, the lack of differences 

between the random and associated modified-random sample pairs for these same parameters 

may be more a function of insensitive ecological measures than a lack of differences between 

random and modified-random sampling sites. 

Response of Stream Physical Habitat and Water Chemistry to Watershed Land Use 

No significant relationships were detected between watershed percent cropland, percent 

grassland, or percent forest cover, and riparian or in-stream physical habitat characteristics (e.g., 

sediment depth). With increasing agricultural land, particularly row cropping, the potential for 

sediment delivery to streams increases. While the proportion of cropland in individual watersheds 

can influence sediment delivery, proximity of cropland to streams, cropland slope, riparian land 

use, width and linear extent, and plant species composition of riparian buffers, and a number of 

other factors can influence nutrient and sediment delivery to streams. An earlier study conducted 

by the USGS in Wisconsin showed that streams in the Driftless Region had twice the sediment 

and nutrient loading rate compared to the statewide average (Corsi et al. 1997). Based on 

Natural Resource Conservation Service cropland erosion rate data and the USGS study findings, 

it is evident that significant amounts of sediment are being delivered to the study area streams, 

but given the relatively steep topography and resulting stream gradient, the majority of the 

sediment flows through these stream systems and is not deposited on the streambeds. In 

63
addition, the WISCLAND land use data used to quantify percent watershed agricultural land was 

based on 10-12 year old LANDSAT data. So while the general land use patterns have changed 

little in these watersheds over recent time, the dated land use data could have weakened the 

relationships between land use and measurable in-stream physical habitat degradation. The fact 

that some of the reference stream watersheds had significant amounts of agricultural land 

suggests that with sufficient riparian protection and proper agricultural land management, 

agricultural productivity and high quality streams can co-exist. 

Response of Biotic Indices to Percent Watershed Agriculture, Stream Sediment and 

Water Chemistry Variables 

The results of the Pearson correlation analyses indicate stronger responses of 

macroinvertebrates than fish to increasing watershed disturbance. Based on adjusted p-values, 

neither the macroinvertebrate nor the fish metrics were strongly related to habitat or land use 

variables. However, the two macroinvertebrate metrics examined were significantly correlated to 

several water chemistry and water quality measures. The fish IBI score was only weakly 

correlated with Kjeldahl nitrogen and water clarity. These results are surprising, as various 

studies have provided evidence that the structure and function of stream fish communities are 

altered with increasing proportions of agricultural land within watersheds (Fausch et al., 1990, 

Meador and Goldstein, 2003). The EPT metric indicated reductions in the quality of the benthic 

community in response to increasing total dissolved phosphorus concentration and, more weakly, 

streambed sedimentation. Various studies have shown that as nutrient concentrations increase in 

streams there is an increase in filamentous algae growth which displaces the periphytic (diatom) 

community that is an important food source for many macroinvertebrate taxa (Lillie et al. 2003). 

Similarly, with increasing sedimentation there is a corresponding loss of available coarse 

substrate (rubble, cobble, and gravel) and the associated interstitial spaces that are critical habitat 

for many macroinvertebrate taxa (Lillie et al. 2003). The lack of strong relationships between 

metrics and measures of habitat and land use may be a function of the metrics selected, as some 

metrics may show responses only to specific types of disturbance. Other factors related to the 

land cover data also could affect the relationships observed, including the age of the LANDSAT 

data, the distribution of agricultural land within individual watersheds, and the quality of the 

riparian corridor along individual streams. 

Comparison of Random Sample Population with WDNR Biologist’s Targeted Sample 

Population 

The WDNR has primarily relied on targeted sampling to provide data on stream conditions for 

site-specific, regional and statewide resource assessments. While it is critically important to 

continue to collect data for stream-specific assessments and management decisions, the REMAP 

study results indicate that using targeted data to make broad spatial inferences about the quality 

of stream populations can lead to erroneous estimations of stream quality. In general, the 

emphasis of stream monitoring in western Wisconsin has been to target high quality streams to 

assess the condition of trout fisheries or to determine the potential for these streams to support 

brown trout or the more environmentally-sensitive native brook trout. A key finding of this study 

was that the bias of targeted sampling resulted in an overestimation of stream quality when 

extrapolated to the population-level, findings similar to that of Hughes et al. (2000). Bias induced 

from targeted sampling can of course also underestimate the quality of regional stream 

populations if the focus of the targeted sampling is directed toward streams impaired by industrial 

or municipal waste discharges, or polluted urban or agricultural run-off, as is typically the focus of 

Total Maximum Daily Load watershed assessments. 

64
Implications for WDNR’s Wadeable Stream Monitoring Program 

The REMAP study results provide valuable insights for improving the rigor of the WDNR’s 

wadeable stream monitoring program. This study is the first time the WDNR has conducted a 

probabilistic survey on a broad geographic scale. Results also indicate macroinvertebrate and 

fish assemblages differ in their power to detect physical habitat degradation and chemical 

pollution. In addition, this study provides evidence that the targeted sampling design routinely 

used overestimates the quality of stream resources in western Wisconsin. The preliminary 

findings that a modified-random sampling design appears to induce little bias in the assessment of 

stream quality may allow a more efficient and cost-effective stream sampling effort in Wisconsin, 

but additional study is needed to more rigorously evaluate the utility of applying a road-accessible 

sampling design. Finally, the process of using numeric criteria to objectively determine whether 

individual or populations of streams are meeting their potential will be applied statewide which will 

help reduce WDNR resource managers’ reliance on subjective, qualitative, resource evaluations. 

65
8. Acknowledgements 

 A number of WDNR staff contributed to this study. Among those, we thank Sue Acre, Bob 

Busch, Bill Ceelen, Walt Jaeger, and Joanne Tooley. In addition, a number of EPA staff were 

key contributors to this project and the authors are very thankful for their support. Dr. Florence 

Fulk – NERL, and Sarah Lehmann and Edward Hammer of Region 5 helped secure funding and 

initiate the project. Dr. Tony Olsen, NHEERL-WED provided the sample population - draw and 

statistical guidance; Drs. Robert Hughes, Tony Olsen, Steve Paulsen, and Paul Ringold of 

NHEERL provided review comments; and Karen Blocksom of NERL provided statistical 

guidance, and technical reviews of earlier report drafts. 

66
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Environmetrics 8:167-95. 

Stevens, D.L., Jr., and A.R. Olsen. 1999. Spatially restricted surveys over time for aquatic 

resources. Journal of Agricultural, Biological, and Environmental Statistics 4: 415-428. 

Stevens, D.L., Jr., and A.R. Olsen. 2004. Spatially-balanced sampling of natural resources. 

Journal of the American Statistical Association 99:262-278. 

Strahler, A.N. 1957. Quantitative analysis of watershed geomorphology. Transactions of the 

American Geophysical Union 38:913-920. 

69
Appendix A. Comparison of Spring and Fall Water Chemistry 

Parameters 

Evaluation of Seasonal Effects 

Water quality and water chemistry data collected in the spring and fall of 2003 were compared 

using Bonferroni-adjusted paired t-tests to determine if seasonal differences existed. In the spring 

and fall of 2003 we measured instantaneous values of dissolved oxygen concentration, dissolved 

oxygen percent saturation, pH, and water temperature in situ with electronic meters, and water 

transparency with a transparency tube at the X, B and reference stream sites. Total phosphorus, 

total dissolved phosphorus, NH3 (ammonia), NO3-NO2 (nitrate-nitrite), and total Kjeldahl nitrogen 

concentrations were also measured using laboratory-analyzed grab samples. Paired t-tests (with 

Bonferroni adjustments) were used to compare within-site spring and fall differences for these 10 

parameters. Water transparency, dissolved oxygen concentration and dissolved oxygen percent 

saturation showed statistically significant differences between the spring and fall sampling periods 

(Table A1, Figure A1). Dissolved oxygen concentration, the percent dissolved oxygen saturation, 

and water column transparency had higher values during the fall sampling period than the spring. 

Total dissolved phosphorus, NH3, and Kjeldahl nitrogen also displayed statistically significant 

concentration differences between the spring and fall samples. Total dissolved phosphorus 

values were significantly higher in the fall. In contrast, both NH3 and Kjeldahl nitrogen were 

significantly higher in the spring samples. Because of these seasonal differences in various water 

chemistry measures, and because the spring dataset had a greater number of sites sampled, only 

water chemistry samples collected in spring were used for analyses in this study. 

Table A 1. Paired t-test comparisons between spring and fall water quality and water 

chemistry measures collected at the X stream sites. 

Spring Vs Fall Water Chemistry Measures No. of 

samples 

Degrees of 

Freedom p-value

Total Phosphorus (mg/L)* 47 46 0.240 

Total Dissolved Phosphorus (mg/L)* 49 48 0.001 

NH3 (mg/L)* 49 48 0.001 

NO3-NO2 (mg/L)* 49 48 0.670 

N-Kjeldahl (mg/L)* 49 48 0.043 

Dissolved Oxygen (mg/L) 49 48 0.000 

Transparency (cm) 43 42 0.034 

% Oxygen Saturation 43 42 0.000 

pH 38 37 0.798 

Water Temperature (C) 49 48 0.294 

*Data were Log10 transformed prior to conducting the paired t-tests. P-values in bold are significant.

70
spring fall

0

1

2

3Kjeldahl-N (mg/L)

spring fall

0.0

0.1

0.2

0.3

0.4

NH3 (mg/L)

spring fall

0

5

10

15

20

NO3-NO2 (mg/L) 

spring fall

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Total Dissolved P (mg/L)

spring fall

0.0

0.2

0.4

0.6

0.8

1.0

Total P (mg/L)

spring fall

0

5

10

15

Dissolved O2 (mg/L)

spring fall

0

50

100

150

 % O2 Saturation (mg/L)

spring fall

10

15

20

25

30

spring fall

6

7

8

9 pH

spring fall

0

50

100

 +122 Transparency (cm)

n=49 

p=0.043

n=47 

p=0.240 

n=49 

p=0.294 

n=49 

p=0.001

n=49 

p=0.000

n=38 

p=0.798 

n=49 

p=0.670 

n=43 

p=0.000 

n=43 

p=0.034 

n=49 

p=0.001 

Water Temperature (C)

Figure A 1. Box and whisker plots of spring and fall water quality and water chemistry 

measures collected at the X-sites. P-values represent paired t-test results. 

71
Appendix B. Relationships of Stream Order with Physical Habitat, 

Water Quality and Water Chemistry, and Biological Measures 

Habitat Measures and Stream Order 

To evaluate relationships between stream order and physical habitat measures, an ANOVA was 

applied to each habitat measure collected at the X sites. Significant relationships were detected 

between stream order and sinuosity, mean distance between bends, and mean length of bank 

erosion (Tables B1, B2). Sinuosity differed between first and second order sites compared to 

third and fourth order streams. Width of bank erosion and distance between bends both differed 

significantly between second and fourth order streams only. 

Table B 1. ANOVA results of stream order and physical habitat measures collected at the 

X sites. 

X Site Habitat Measures Vs Stream Order # of Samples F-ratio p-value 

Sinuosity* 53 12.551 <0.001 

Width : Depth Ratio 56 0.869 0.463 

Mean Depth of Fines* 53 1.493 0.228 

Percent Sand, Silt, and/or Clay Sediments 53 2.144 0.107 

Mean Distance Between Bends (m)* 53 3.367 0.026 

Mean Length of Riffles (m)* 53 0.366 0.778 

Mean Length of Pools (m)* 53 1.552 0.213 

Mean Width of Bank Erosion (m)* 53 6.795 0.001 

* Data were Log10(x+1) transformed prior to conducting ANOVA. The percent sand, silt, and clay values were arcsine 

square root transformed prior to conducting ANOVA. P values in bold are significant. 

Table B 2. Tukey HSD pairwise comparison probabilities for physical habitat measures 

that produced significant ANOVA results. P-values in bold indicate significantly different 

parameter values between the corresponding stream orders. 

Parameter Stream Order 1 2 3 

2 0.992 

3 0.006 0.002 

Sinuosity 

4 0.000 0.000 0.589 

2 0.987 

3 0.895 0.696 

Mean Distance 

Between Bends 

4 0.069 0.027 0.167 

2 0.100 

3 0.936 0.211 

Mean Width of 

Bank Erosion 

4 0.317 0.000 0.061 

72
Water Quality and Water Chemistry Measures and Stream Order 

Similar to the ANOVA conducted with the habitat data, we evaluated water quality and water 

chemistry data collected from the X sites to determine if these measures varied by stream order. 

Only dissolved oxygen percent saturation showed statistical differences among stream orders 

(Tables B3, B4). 

Table B 3. ANOVA of stream order and water quality and water chemistry measures from 

the X stream sites. 

X Site Water Chemistry Vs Stream Order # of Samples F-ratio p-value 

Total Phosphorus (mg/L)* 56 0.506 0.680 

Total Dissolved Phosphorus (mg/L)* 56 0.528 0.665 

NH3 (mg/L)* 56 0.647 0.588 

NO3-NO2 (mg/L)* 56 2.709 0.054 

N-Kjeldahl (mg/L)* 56 0.767 0.518 

Dissolved Oxygen (mg/L) 57 2.522 0.068 

Percent Oxygen Saturation 57 3.662 0.018 

Transparency (cm) 57 0.536 0.660 

pH 57 2.769 0.051 

Conductivity (uS)* 47 0.439 0.726 

Water Temperature (C) 57 0.398 0.755 

*Data were Log10 transformed prior to conducting the ANOVA analysis. P values in bold are significant. 

Table B 4. Tukey HSD pairwise comparison for the percent oxygen saturation. The pvalue in bold indicates significantly oxygen saturation values between second and third 

order streams. 

Stream Order 1 2 3 

2 1.000 

3 0.060 0.049 

4 0.247 0.224 0.900 

73
Macroinvertebrate Measures and Stream Order 

ANOVA results comparing macroinvertebrate data and stream order indicated no significant 

relationships between stream order and any of the 7 macroinvertebrate metrics or indices. (Table 

B5) 

Table B 5. ANOVA of stream order and macroinvertebrate measures from the X stream 

sites. 

X Site Macroinvertebrate Measures* Vs Stream Order F-ratio p-value 

Species Richness 0.765 0.520 

HBI Score 1.288 0.290 

Percent EPT Genera 2.075 0.117 

Percent EPT Individuals 0.867 0.465 

Shannon's Diversity Index Score 0.713 0.549 

Percent Shredders 0.224 0.879 

Percent Scrapers 1.303 0.285 

*Percent values were arc-sine square root transformed prior to conducting ANOVAS. n = 49

74
Fish Assemblage Measures and Stream Order 

In contrast to the macroinvertebrate data presented above, ANOVA results showed some 

significant differences among stream orders and fish assemblage measures. Specifically, species 

richness and the number of “intolerant” species present are significantly related to stream order. 

(Tables B6, B7) 

Table B 6. ANOVA of stream order and fish assemblage measures from the X stream 

sites (N=42). 

X Site Fish Assemblage Measures Vs Stream Order F-ratio p-value 

Species Richness 4.672 0.007 

Number of Intolerant Species* 4.601 0.008 

Percent of Tolerant Individuals 0.558 0.646 

Percent Top Carnivores 1.887 0.148 

Percent Stenothermal Cool/Coldwater 0.879 0.461 

Percent of Salmonids that are Brook Trout 1.228 0.313 

 IBI Score* 0.993 0.406 

* Data were Log10(X+1) transformed prior to conducting ANOVAS. **Data were Log10(X) transformed prior to 

conducting ANOVAs. Percent values were arc-sine square root transformed prior to conducting ANOVA. P-values in 

bold indicate significant tests. 

 

Table B 7. Tukey HSD pairwise comparison probabilities for fish metrics that produced 

significant ANOVA results. P-values in bold indicate significantly different parameter 

values between the corresponding stream orders. 

Parameter Stream Order 1 2 3 

2 0.770 

3 0.712 1.000 

Species 

Richness 

4 0.018 0.056 0.043 

2 0.200 

3 0.143 0.999 

Number of 

Intolerant 

Species 4 0.005 0.250 0.247 

75
Appendix C. Fish Assemblage Data Analyses 

We captured a total of 54 species and 19,999 individual fish at the X, B, and reference stream 

sites. Forty different species of fish were captured at the X sites, and eighteen different species of 

fish were captured at the reference sites (Tables C1, C2). No fish were captured at 11 of the 

individual X or B stream sites and at 2 of the reference sites. Numbers of individual fish caught 

per X, B, or reference site ranged from 0 to 1,755. On average, 179 fish were captured at the X 

and B sites and 101 fish at the reference sites. The number of fish species caught at individual X 

and B sites ranged from 1 to 18, with an average of 6 species captured per site. The number of 

fish species captured at each reference site ranged from 1 to 8, with an average of 3 species 

captured per site. 

Brook Trout (Salvelinus fontinalis) was the most common species (650 individuals) captured at 

the reference stream sites, and Central Stoneroller (Campostoma anomalum) was the most 

common species captured at the X sites (1,190 individuals). Two-thirds of the fish species 

captured at the X sites were not found at the reference sites; conversely, Burbot (Lota lota), 

Rainbow trout (Oncorhynchus mykiss), and Slimy Sculpin (Cottus cognatus) were captured at the 

reference sites but at none of the X sites. Species with the greatest dissimilarity in frequency of 

occurrence between the X and reference sites were Creek Chub (Semotilus atromaculatus) 

occurring in 57% of the X sites and only 5% of the reference sites, White Sucker (Catostomus 

commersoni) occurring in 55% of the X sites and only 14% of the reference sites, and Johnny 

Darter (Etheostoma nigrum) occurring in 45% of the X sites and only 10% of the reference sites. 

Brook Trout occurred in 57% of the reference sites and only 30% of the X sites, Mottled Sculpin 

(Cottus bairdi) occurred at 38% of the reference sites and only 24% of the X sites, and Brown 

trout (Salmo trutta) occurred at 48% of the reference sites and only 24% of the X sites (Fig. C1). 

76
Table C 1. Fish species captured at X stream sites. 

Species Scientific Name Total No. of 

Fish Caught

No. of X-Sites 

with Species 

Present 

Frequency of 

species at Xsites 

American Brook Lamprey Lampetra appendix 17 5 9.8% 

Bigmouth Shiner Notropis dorsalis 49 4 7.8% 

Blacknose Dace Rhicnichthys atratulus 284 17 33.3% 

Blacknose Shiner Notropis heterlepis 26 4 7.8% 

Blackside Darter Percina maculata 4 3 5.9% 

Bluegill Lepomis macrochirus 16 3 5.9% 

Bluntnose Minnow Pimephales notatus 542 9 17.7% 

Brassy Minnow Hybognathus hankinsoni 2 1 2.0% 

Brook Stickleback Culaea inconstans 180 20 39.2% 

Brook Trout Salvelinus fontinalis 511 15 29.4% 

Brown Trout Salmo trutta 208 12 23.5% 

Central Mudminnow Umbra limi 4 3 5.9% 

Central Stoneroller Campostoma anomalum 1,190 7 13.7% 

Channel Catfish Ictalurus punctatus 1 1 2.0% 

Common Carp Cyprinus carpio 4 1 2.0% 

Common Shiner Notropis cornutus 1,154 9 17.6% 

Creek Chub Semotilus atromaculatus 945 29 56.9% 

Fantail Darter Etheostoma flabellare 156 14 27.5% 

Fathead Minnow Pimephales promelas 106 6 11.8% 

Green Sunfish Lepomis cyanellus 22 4 7.8% 

Hornyhead Chub Nocomis biguttatus 745 7 13.7% 

Johnny Darter Etheostoma nigrum 345 23 45.1% 

Longnose Dace Rhinichthys cataractae 95 8 15.7% 

Mottled Sculpin Cottus bairdi 260 12 23.5% 

Northern Brook Lamprey Ichthyomyzon fossor 3 2 4.0% 

Northern Hog Sucker Hypentelium nigricans 2 1 2.0% 

Pearl Dace Semotilus margarita 238 3 5.9% 

Pumpkinseed Lepomis gibbosus 1 1 2.0% 

Quillback Carpiodes cyprinus 4 1 2.0% 

Rosyface Shiner Notropis rubellus 34 5 9.8% 

Sand Shiner Notropis stramineus 3 1 2.0% 

Shorthead Redhorse Moxostoma 

macrolepidotum 

3 3 5.9% 

Smallmouth Bass Micropterus dolomieu 25 3 5.9% 

Southern Redbelly Dace Phoxinus erythrogaster 227 8 15.7% 

Spotfin Shiner Notropis spilopterus 29 3 5.9% 

Stonecat Noturus flavus 42 3 5.9% 

Suckermouth Minnow Phenacobius mirabilis 32 2 3.9% 

Tiger Trout Salvelinus fontinalis X 

Salmo trutta 

1 1 2.0% 

Walleye Sander vitreus 2 1 2.0% 

White Sucker Catostomus commersoni 762 28 54.9% 

Total Number of Fish 8,275 

77
 Table C 2. Fish species captured at reference stream sites. 

Species Scientific Name 

Total No. 

of Fish 

Caught 

No. of Reference 

Sites with 

Species Present 

Frequency of 

species at 

Reference Sites 

American Brook Lamprey Lampetra appendix 55 5 23.8% 

Blacknose Dace Rhicnichthys atratulus 35 4 19.1% 

Blacknose Shiner Notropis heterolepis 2 1 4.8% 

Bluntnose Minnow Pimephales notatus 6 1 4.8% 

Brook Stickleback Culaea inconstans 63 6 28.6% 

Brook Trout Salvelinus fontinalis 650 12 57.1% 

Brown Trout Salmo trutta 625 10 47.6% 

Burbot Lota lota 43 2 9.5% 

Central Mudminnow Umbra limi 1 1 4.8% 

Central Stoneroller Camostoma anomalum 5 1 4.8% 

Creek Chub Semotilus 

atromaculatus 

8 1 4.8% 

Fantail Darter Etheostoma flabellare 35 2 9.5% 

Johnny Darter Etheostoma nigrum 35 2 9.5% 

Longnose Dace Rhinichthys cataractae 76 3 14.3% 

Mottled Sculpin Cottus bairdi 547 8 38.1% 

Rainbow Trout Oncorhynchus mykiss 3 3 14.3% 

Slimy Sculpin Cottus cognatus 118 1 4.8% 

White Sucker Catostomus 

commersoni 

90 3 14.3% 

Total Number of Fish 2,397 

78
0 10 20 30 40 50 60

Figure C 1. Percent frequency of occurrence of fish species at the X, B, and reference 

sites. 

79
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