c/EPA
United States
Environmental Protection
Agency
Region 5
230 South Dearborn Street
Chicago, Illinois 60604
EPA 905/9-90-005
October 1990
Proceedings of the 1990
Midwest Pollution Control
Biologists Meeting
Chicago, Illinois
April 10-13,1990
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PROCEEDINGS OF THE 1990 MIDWEST
POLLUTION CONTROL BIOLOGISTS MEETING
held in
CHICAGO, ILLINOIS
April 10-13, 1990
Edited by:
Wayne S. Davis
U.S. Environmental Protection Agency, Region V
Environmental Sciences Division
Sponsored by:
U.S. Environmental Protection Agency
Assessment and Watershed Protection Division
Washington, D.C. 20460
U.S. Environmental Protection Agency, Region V
Environmental Sciences Division
Instream Biocriteria and Ecological Assessment Committee
Chicago, IL 60604
-ency
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The 1990 MPCB Meeting was dedicated to
James L. Plafkin
(1990)
The 1990 MPCB Proceedings is dedicated to
Michael J. Glorioso
(1980)
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NOTICE - DISCLAIMER
This document and it's contents do not necessarily reflect the
position or opinions of the U.S. Environmental Protection Agency.
This document has not been subjected to the EPA peer-review
process and is intended to facilitate information exchange
between professional pollution control biologists in the midwest/
and nationally. Mention of trade names or commercial products
does not constitute endorsement or recommendation for use.
When citing individual papers within this document:
Berg, M.B. and Hellenthal, R.A. 1990. Data variability and the
use of chironomids in environmental studies: the standard error
of the midge, pp.1-8. In; W.S. Davis (editor). Proceedings of
the 1990 Midwest Pollution Control Biologists Meeting. U.S.
Environmental Protection Agency Region V, Environmental Sciences
Division, Chicago, IL. EPA-905-9-90/005.
When citing this document:
Davis, W.S. (editor). 1990. Proceedings of the 1990 Midwest
Pollution Control Biologists Meeting. U.S. Environmental
Protection Agency Region V, Environmental Sciences Division,
Chicago, IL. EPA-905-9-90/005.
•
To request copies of this document, please write to:
U.S. Environmental Protection Agency
Publication Distribution Center, ODD
11027 Kenwood Road, Bldg. 5 - Dock 63
Cincinnati, OH 45242
Cover: Cover design and illustration by Elaine D. Snyder of EA
Engineering, Science, and Technology, Inc. Depicted is a fathead
minnow, a bluegill, a gammarid amphipod, and an emphemerellid
mayfly superimposed on a drop of water. This design was
developed for USEPA's Rapid Bioassessment Program, Assessment and
Watershed Protection Division, Office of Water, Washington, D.C.
Special Thanks: The staff and management of ICF Kaiser should be
recognized for their outstanding efforts in assisting USEPA in
advertising and coordinating this meeting, as well a preparing
the written materials used during the meeting. Thank you to
Helen Taylor, Danielle Gordon, and Bill Ward.
Acknowledgement: Thank you to the Region V Instream Biocriteria
and Ecological Assessment Committee and Region V management for
supporting this meeting.
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FORWARD
A Historical Perspective on Regulatory Biology
After several years of debate, the United States Environmental
Protection Agency (USEPA) has thoroughly recognized the benefit of
using biological survey data to assist with the Agency's regulatory
decisions for surface waters. The myriad of uses that biological
survey data can provide were discussed in the recent "Biocriteria
Program Guidance Document" (USEPA 1990a), and examples were
presented in the "Biocriteria Development by States" (USEPA I990b).
The use of biological survey data to assess the health of our rivers
and streams was prompted by some early work conducted by the
Illinois State Natural History Survey almost a century ago. This
paper specifically reviews the circumstances regarding that first
biological survey, and the evolution of more rigorous and objective
assessment end-points. Washington (1984) provided a comprehensive
review of the history and application of biotic indices, and the
information presented here is intended to complement Washington's
work.
"Dilution is the Solution"
In 1848, the Illinois and Michigan Cana] (I&MC) was opened crossing
the continental divide between the Great Lakes drainage system and
the Mississippi River drainage. The I&MC connected the South Fork
of the South Branch of the Chicago River near the tanneries and
packinghouses of the famous Chicago Stockyards with the Upper
Illinois River at LaSalle (Figure 1; U.S. Engineers Office 1924).
Initially intended for navigation, the I&MC soon became an obvious
outlet for the sewage created by a growing population and industrial
base, and, beginning in 1869, an average of 167 cfs (maximum 400
cfs) of water was pumped from the Chicago River into the sluggish
I&MC, reversing the normal flow of the South Branch into the
Illinois River. More direct gravity flow from the Chicago River was
provided in 1871 by deepening the summit of the canal, and, in 1884,
an additional 1000 cfs was pumped into the river to facilitate the
flow. The growth of Chicago's north side also required additional
pumping to increase the southward flow of the water and 400 cfs was
pumped from Lake Michigan to the Chicago River mainstem. The
inadequacy of the I&MC to solve the city's sewage needs, and to keep
the city's water intake supply in Lake Michigan from additional
contamination, became apparent.
The Sanitary District of Chicago was created by the State of
Illinois in 1889 to plan for the city's additional sewerage
requirements. In 1892, construction of the 28-mile long Chicago
Drainage Canal began adjacent to the much smaller I&MC, connecting
the South Branch of the Chicago River (near the West Fork) with the
Des Plaines River at Lockport. The Canal, opened in January 1900,
was designed to divert up to 14,000 cfs of water from Lake Michigan,
resulting in a reversal of the flow of the Chicago River and sewage
flowing away from the drinking water supply.
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Forward - Historical Perspectives
LAKL COUNTY
COOK
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Forward - Historical Perspectives
The population and industrial growth of the city required several
pumping stations to be added to adequately "flush" the raw sewage
downstream, construction of the North Shore Channel from 1908-1910
which connected Lake Michigan with the Chicago River north of the
city added about 1000 cfs. Sewers were soon built along the
lakeshore communities eventually diverting all sewage in the
Sanitary District from Lake Michigan into the Des Plaines River
basin. The expansion of the far south side district resulted in the
construction of the Calumet-Sag Channel, which was completed in
1922. The channel connected the Little Calumet River with the
Chicago Drainage Canal 22 miles downstream, diverting an additional
500 cfs from Lake Michigan.
"Poisoning the Mississippi?"
As one can imagine, this diversion of raw sewage from the Chicago
River system into the Des Plaines River did not please the
downstream communities, although Chicago's drinking water supply was
no longer contaminated. Before the Chicago Drainage Canal was
officially opened, the State of Missouri brought suit against the
State of Illinois and the Chicago Sanitary District on January 17,
1900 seeking an injunction from opening the Canal (Leighton 1907).
The suit charged that the drainage of the "sewage matter from nearly
the whole City of Chicago and a portion of Cook County" would
"poison the waters of the Mississippi and render them unfit for
domestic uses". The defendants claimed, however, that the
Mississippi River water would actually be cleaner due to the
dilution water from Lake Michigan (approximately 9:1).
Due to the interstate nature of this dispute which affected State
sovereignty, the United States Supreme Court became involved. After
years of gathering facts and assembling the nation's expert water
quality scientists, engineers, and sanitarians, the testimony
provided by these experts was deemed to be overwhelmingly in support
of the State and Sanitary District's position. On February 19,
1906, the United States Supreme Court concluded that not only did
the State of Missouri not prove it's case, but that the Chicago
Drainage Canal (i.e. Sanitary and Ship Canal) substantially improved
the quality of the nearby Illinois River (Leighton 1907).
"Bureaucracy in the 1800's"
Today's bureaucracy is painted with pictures of government required
permits, licenses, and unnecessary delays, but such was the case
even in the 1800's. In fact, a crucial permit was not obtained
related to the building of the Chicago Drainage Canal because it was
not thought to be necessary (U.S Engineer Office 1924).
A primary concern in the late 1800's was the defense of this
country/ under the authority of the War Department (now Department
of Defense). One of the main mechanisms for defense mobilization
was through navigable waterways, and their maintenance to serve in
that capacity was of great iirportance. Maintenance of all navigable
waterways in this country was the primary impetus for the Rivers and
iii
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Forward - Historical Perspectives
Harbors Appropriation Act of 1899 (30 Stat. 1151 1899). Before any
major alterations of a waterway were to be conducted, a Federal
permit was required, but the Chicago Sanitary District did not apply
for the permit until 1896, four years after construction was begun.
The Federal government conceded the permit later that year, but
stated that "the authority shall not be interpreted as approval of
the plans of the Sanitary District of Chicago to introduce a current
into the Chicago River." The Federal government also issued a
temporary and revocable permit to open the canal in 1899 and
eventually modified the permit in 1903 restricting the flow through
the South Branch of the Chicago River to a maximum of 5833 cfs in
winter when navigation is closed, and a maximum of 4167 cfs the rest
of the year.
"Dilution was NOT the Solution"
Beginning in 1907, the Sanitary District made several permit
applications for increasing the allowable flow in the river system
through the diversion of water from Lake Michigan. Each application
was denied by the War Department which stated in 1907 that diversion
greater than the values permitted in 1903 would not be allowed.
Despite the denial of Federal permits and even a Federal Court suit
seeking to enjoin the District from constructing the Calumet-Sag
Channel which would divert even more water, the construction of the
North Shore and Calumet-Sag Channels continued, and was soon
completed (U.S. Engineer Office 1924).
Arguments for both sides in this law suit were heard in Federal
Court beginning in 1915, and in 1920, the United States District
Court gave an oral opinion that the United States government was
entitled to an injunction. After a motion of reconsideration was
filed by the Sanitary District, the District Court issued a formal
decree in 1923 supporting the injunction sought by the United States
government. After an appeal to the Supreme Court, the decision made
by the District Court was upheld on January 5, 1925.
The Supreme Court decision affected not only the illegal diversion
of waters from Lake Michigan, but also the mitigation of adverse
effects and actual damage caused by the diversion on the ecology of
the Illinois River. To comply with both the need to dispose of
sewage without additional diversion of water from Lake Michigan and
to improve the poor ecological conditions of the Illinois River
resulting from the now illegal diversion, the Sanitary District of
Chicago committed over $125 million to construct/improve the sewer
system and build the first wastewater treatment plants in the area.
It was demonstrated that dilution alone no longer provided adequate
protection of the streams and rivers and the era of physical and
biological wastewater treatment arrived (Sanitary District of
Chicago 1925).
"Early Biological Surveys"
It is likely that the immediate outcome of the law suits filed
against the Sanitary District would not have adequately addressed
iv
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Forward - Historical Perspectives
the impacts on the Illinois River if it had not been for the work of
Stephen Forbes, the Director of the Illinois State laboratory of
Natural History. In fact, the District Engineer from the U.S.
Engineer Office documented the damage to the Illinois River based
upon the work conducted and initiated by Forbes, and included that
information in a 1924 report submitted to the War Department
supporting the Federal government's case before the Supreme Court
(U.S. Engineer Office 1924).
Forbes opened a permanent field biology station on the Illinois
River in 1894 to document the effects on the stream biology as a
result of the opening of the» Chicago Drainage Canal in 1900. The
planning for that station included investigating not only the
effects due to periodic flooding of the river due to the increased
flow, but also the direct effects from the pollution added from the
Canal (Forbes 1928).
Between 1894 and 1899, Kofoid (1908) studied the river's plankton
populations, life histories and how they were affected by
environmental factors including sewage. This baseline study was
later used by Forbes and Richardson (1913) and Purdy (1930) to
document the river's assimilative capacity and decline of the
plankton populations due to the opening of the Chicago Drainage
Canal
After increasing the number of monitoring stations on the river,
Stephen Forbes and Robert Richardson (1913) published their first
report on the conditions of the Illinois River. They defined the
degradation via pollutional zones (septic, polluted, contaminate,
and clean water), similar to that of Kolkwitz and Marsson's (1908)
Saprobic Index. However, the Saprobic Index was based upon bacteria
and protozoa while Forbes and Richardson's zones were based on water
chemistry, plankton, benthic macroinvertebrate and fish populations.
Their surveys conducted between 1909 and 1911 documented 107 miles
of water below the mouth of the Chicago Drainage Canal to be
polluted before recovery fully occurred.
"Development of the First 'Biotic Index'"
In 1921 (a), Richardson found 146 miles of the river to be polluted
based on their work conducted between 1913 and 1915 and in 1920
concluded that 226 miles of the Illinois River was now polluted with
146 miles of near anoxic conditions (1921b). Based on their data
collected over seven years, they reported between 8 and 16
additional river miles per year were classified as polluted.
Richardson began to rely heavily on defining pollution zones based
on pollution tolerances for the biota, focusing heavily on the
benthic macroinvertebrate community due to their role in the food
chain.
The last report on the pollution biology of the Illinois River
conducted by Richardson was published in 1928, and proved to be the
predecessor to the more recent biotic indices. The study added data
collected between 1924 and 1925 and also marked the change of
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Forward - Historical Perspectives
responsibility for the river surveys to the State Water Survey. In
this classic report, he detected shifts in water quality based on
observing the benthos alone, although he preferred to also use
chemical data to better define the pollutional zones. He further
refined the pollutional zones (called septic, pollutional,
subpollutional, and clean water; Richardson 1925) based on "index
values" of the benthos which used specific taxa as indicators.
"Development of Biological Assessment Methods"
Based on the work conducted by Forbes and Richardson, the use of
benthic macroinvertebrates as indicator organisms was founded and
the concept of biotic indices introduced. Although the work was
similar in concept to the "Saprobic Index" developed by Kolkwitz and
Marsson (1908), Forbes and Richardson used organisms at higher
trophic levels. The work conducted by Forbes and Richardson forms
the basis for some of our current regulatory biology programs
supported by USEPA.
Richardson (1925,1928) decided that numerical abundances of each
index group was not as significant as their relative abundances and
overall occurrences. For instance, he reported the number of
pollution tolerant Tubificid worms in the river to range from under
1000 to over 350,000 per square yard in pollutional zones, and
Chironomids to range from zero to over 1,000 per square yard.
Richardson also reported seasonal and habitat changes as responsible
for much of the numeric variability at a given site, supporting the
use of the occurrence of a species as the better index measure.
Wright and Tidd"(1933) actually applied the numerical abundance of
oligochaetes to assess the degree of pollution. They reported
values of less than 1000 m"2 as indicating negligible pollution,
between 1000-5000 m"2 as mild pollution, and over 5000 m"2 was severe
pollution (Washington 1984). Washington felt this work was the
"original index", apparently unaware of Richardson's earlier work
with "index values" for benthos. Ruth Patrick (1950) developed a
"histogram" based upon seven taxonomic groups and assigned stream
classes of healthy, semi-healthy, polluted, very polluted, and
atypical based upon the comparison of predominance of three of the
taxonomic groups with the other four.
"Biotic and Diversity Indices"
It took several more years for an improved assessment end-point to
be introduced. In 1955, Beck published a biotic index which
produced a numerical end-point that could more easily be interpreted
by biologists, as well as the engineering and management dominated
discipline. Beck's index was based upon two classes of benthos:
intolerant and facultative, assigned a weight value of 2 and 1,
respectively. Therefore, the higher the index value, the healthier
the stream is assumed to be. In the next two decades Washington
reported several biotic indices, but Chutter's (1972) biotic index
ushered in a new era for these indices.
vi
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Forward - Historical Perspectives
Chutter studied South African streams and assigned specific
tolerance values ranging from 0 to 10 for various taxa which
accounted for both the number of individuals and the number of taxa.
The results were also presented in a 0 to 10 fashion with an average
biotic index value of 0-2 regarded as clean-water, 2-4 slightly
enriched, 4-7 enriched, and 7-10 polluted. This index was the
predecessor to the widely used Hilsenhoff Biotic Index (1977) in the
midwestern United States which was initially based on a 0-5 scale
which included many more taxa than Chutter's.
Hilsenhoff's index was based on taxa from Wisconsin using
genus/species classifications of the aquatic insects. Hilsenhoff
updated his index in 1982 and 1987 to revise the index values and
include new taxa, and in 1988 he developed a very popular family-
level biotic index.
The development and use of diversity indices for water pollution
assessment was thoroughly reviewed by Washington (1984).
Essentially, the use of diversity as an optimal measure of stream
community response has been widely used since the 1960's, but the
theoretical diversity which is based on calculating the evenness of
the number of individuals among the assembled taxa was not
developed, nor intended, for the application to natural systems.
One of the first diversity indices based on information was
published by Shannon (1949) as H1. Washington (1984) stated that it
was eventually termed the Shannon-Weiner Index because Weiner (1948)
independently published a similar measure. Washington further
explains that the confusion with erroneously calling the index the
Shannon-Weaver index began when Shannon published his work in a book
coauthored by Weaver.
Possibly the first use of diversity indices for assessing water
quality, particularly the Shannon-Wiener Index, was by Wilhm and
Dorris (1966) and further explained by Wilhm (1967) who described
the ranges of H' associated with clean, moderately polluted, and
substantially polluted streams.
"New Assessment End-Points"
The major asset of both diversity and biotic indices is that they
both reduced the relatively complex interactions and pollution
responses of an aquatic community into a single number for water
quality management purposes. However, neither of these indices were
successful in describing the overall "health" of the aquatic
communities under a variety of conditions. Little information is
available on whether both of these indices were widely used
together, or if an attempt was made to develop a single end-point
based on assigning a score to each index. However, it was clear
that a better tool was need to more consistently and accurately
characterize the aquatic communities.
In 1981, James Karr published the Index of Biotic Integrity (IBI),
based on supporting the 1972 Clean Water Act's objective to restore
vii
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Forward - Historical Perspectives
and maintain the physical, chemical, and biological integrity of the
nation's waters. The IBI was based on 12 individual indices, or
metrics, based on fish species composition, trophic composition, and
abundance and condition. Each metric was given a score (index
value) based upon specific ecological expectations,and the twelve
scores were added to provide a single site assessment end-point.
The scores resulted in "integrity classes" for streams of excellent,
good, fair, poor, very poor, or no fish (Karr et al. 1986).
The IBI can be termed a "composite index" because it combines
several community attributes into a single index value. This
overall concept, and the IBI in particular, has been demonstrated to
be very successful for water quality, or water "resource"
evaluations and is widely used by a number of regulatory agencies
(Dodd et al. 1990; Cunningham and Whitaker 1989). It did not take
long before this concept was successfully applied to benthic
inaCTx»invertebrates as well. Jeff DeShon at the Ohio Environmental
Protection Agency (OEPA) developed the Invertebrate Community Index
(ICI) in 1986 which is based on ten structural and functional
metrics the OEPA biologists had subjectively used for a number of
years (Ohio EPA 1987a-c).
Based on the enormous success of the IBI as an assessment end-point,
USEPA independently began the development of an IBI-type index for
benthos. In 1989, USEPA published another set of composite indices
called Rapid Bioassessment Protocols (RBPs) for benthic
macroinvertebrate and fish communities (Plafkin et al. 1989). The
benthic community metrics were based on very general structural and
trophic relationships that could be applied nationally, and the
primary fish assessment method was the IBI. The RBPs are best used
with regionally-defined (ecoregions) reference sites which can be
validated for specific States by modifying the RBP metrics, as done
by Bruce Shakelford (1988) in Arkansas.
Currently, the USEPA water quality standards program is requiring
each State to adopt narrative biological criteria within the next
three years, and eventually numerical biocriteria. Development and
implementation of biocriteria would not be successful without these
composite indices. These new assessment end-points have truly
changed the way regulatory agencies can, and. will, utilize
biological survey data.
Wayne S. Davis
1990 MPCB Meeting Coordinator
Literature Cited and Bibliography
Beck, W.M. 1955. Suggested method for reporting biotic data. Sewage
and Industrial Wastes, 27:1193-1197.
Chutter, P.M. 1972. An empirical biotic index of the quality of
water in South African streams and rivers. Water Research, 6:19-30.
Vlll
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Forward - Historical Perspectives
Cunningham, P.A. and Whitaker, C.O. 1989. A survey of the status of
biomonitoring in state NPDES and nonpoint source monitoring
programs. Prepared by Research Triangle Institute (KTI/7839/02-03F)
for USEPA Office of Policy, Planning and Evaluation, Washington,
D.C.
Dodd, R., McCarthy, M., Little, K., Cunningham, P., Duff in, J.,
Praskins, W., and Armstrong, A. 1990. Background paper: Use support
assessment methods. Prepared by Research Triangle Institute for
USEPA Assessment and Watershed Protection Division, Washington, D.C.
Forbes, S.A. 1928. The biological survey of a river system - its
objects, methods and results. Bulletin Illinois Natural History
Survey, 17:277-284.
Forbes, S.A. and Richardson, R.E. 1913. Studies on the biology of
the upper Illinois River. Bulletin Illinois Natural History Survey,
9:1-48.
Forbes, S.A. and Richardson, R.E. 1919. Some recent changes in
Illinois River biology. Bulletin Illinois Natural History Survey,
13:139-156.
Hilsenhoff, W.L. 1988. Rapid field assessment of organic pollution
with a family-level biotic index. Journal North American
Benthological Society 7(1):65-68.
Hilsenhoff, W.L. 1987. An improved biotic index of organic stream
pollution. Great Tnkf»s Entomologist 20(1): 31-39.
Hilsenhoff, W.L. 1982. Using a biotic index to evaluate water
quality in streams. Technical Bulletin No. 132, Wisconsin
Department of Natural Resources, Madison, WI, 23 p.
Hilsenhoff, W.L. 1977. Use of arthropods to evaluate water quality
of streams. Technical Bulletin No. 100, Wisconsin Department of
Natural Resources, Madison, WI, 15 p.
Karr, J. R. 1981. Assessment of biotic integrity using fish
communities. Fisheries 6(6):21-27.
Karr, J.R., Fausch, K.D., Angermeier, P.L., Yant, P.R. and
Schlosser, I.J. 1986. Assessing biological integrity in running
waters: a method and its rationale. Illinois Natural History
Survey, Special Publication 5, Springfield, IL. 28 p.
Kofoid, C.A. 1908. The plankton of the Illinois River, 1894-1899,
with introductory notes upon the hydrography of the Illinois River
and its basin. Part II. Constituent organisms and their seasonal
distribution. Bulletin Illinois Natural History Survey, 8:1-360.
Kofoid, C.A. 1903. The plankton of the Illinois River, 1894-1899,
with introductory notes upon the hydrography of the Illinois River
and its basin. Part I. Quantitative investigations and general
results. Bulletin Illinois Natural History Survey, 6:1-535.
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Forward - Historical Perspectives
Kblkwitz, R. and Marsson, W.A. 1908. Ecology of plant saprobia
(Ger.)- Ver. dt. Ges., 26:505-519.
Leighton, M.O. 1907. Pollution of Illinois and Mississippi Rivers by
Chicago sewage: A digest of the testimony taken in case of the State
of Missouri v the State of Illinois of the Sanitary District of
Chicago. U.S. Geological Survey, Water Supply and Irrigation Paper
No, 194, Series L, Quality of Water, 20. Government Printing Office,
Washington, D.C. 369 pp.
Ohio Environmental Protection Agency. 1987a. Biological criteria
for the protection of aquatic life: Volume I. The role of
biological data in water quality assessment. Division of Water
Quality Monitoring and Assessment, Surface Water Section, Columbus,
Ohio, 44 p.
Ohio Environmental Protection Agency. 1987b. Biological criteria
for the protection of aquatic life: Volume II. Users manual for
biological field assessment of Ohio surface waters. Division of
Water Quality Monitoring and Assessment, Surface Water Section,
Columbus, Ohio.
Ohio Environmental Protection Agency. 1987c. Biological criteria
for the protection of aquatic life: Volume III. Standardized
biological field sampling and laboratory methods for assessing fish
and macroinvertebrate communities. Division of Water Quality
Monitoring and Assessment, Surface Water Section, Columbus, Ohio.
Patrick, R. 1950. Biological measure of stream conditions. Sewage
and Industrial Wastes, 22(7):926-938.
Plafkin, J.L., Barbour, M.T., Porter, K.D. and Gross, S.K., and
Hughs, R.M. 1989. Rapid Bioassessment Protocols for Use in Streams
and Rivers: Benthic Macroinvertebrates and Fish. EPA/444/4-89/001,
Office of Water Regulations and Standards, Washington, D.C.
Purdy, W.C. 1930. A study of the pollution and natural purification
of the Illinois River. U.S. Public Health Service, Public Health
Bulletin No. 198, Government Printing Office, Washington, D.C.
Richardson, R.E. 1921a. Changes in the bottom and shore fauna of the
middle and lower Illinois River and its connecting lakes since 1913-
1915 as a result of the increase southward of sewage pollution.
Bulletin Illinois Natural History Survey, 14:33-75.
Richardson, R.E. 1921b. The small bottom and shore fauna of the
middle and lower Illinois River and its connecting lakes,
Chillicothe to Grafton: its valuation; its sources of food; and its
relation to the fishery. Bulletin Illinois Natural History Survey,
13:363-524.
Richardson, R.E. 1925. Changes in the small bottom fauna of Peoria
lake, 1920 to 1922. Bulletin Illinois Natural History Survey,
15:327-388.
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Forward - Historical Perspectives
Richardson, R.E. 1928. The bottom fauna of the Middle Illinois
River, 1913-1925: its distribution, abundance, valuation, and index
value in the study of stream pollution. Bulletin Illinois Natural
History Survey, 17:387-472.
Sanitary District of Chicago. 1925. Report of the Engineering Board
of Review of the Sanitary District of Chicago on the lake lowering
controversy and a program of remedial measures. Part II. The
technical bases for the recommendations of the board of review.
Sanitary District of Chicago, Chicago, IL.
Shakelford, B. 1988. Rapid bioassessment of lotic macroinvertebrate
communities: biocriteria development. State of Arkansas, Department
of Pollution Control and Ecology, Little Rock, AK
Shannon, C.E. and Weaver, W. 1949. The mathematical theory of
communication, pp. 19-27, 82-83, 104-107. The University of Illinois
Press, Urbana, IL.
US Engineer Office. 1924. Diversion of water from Lake Michigan:
Report on the Sanitary District of Chicago, with recommendations for
action on the part of the War Department with reference to diversion
of water from Lake Michigan. 97p. United States War Department,
Office of the Chief of Engineers, Government Printing Office,
Washington, D.C.
USEPA. 1990a. Biological criteria: national program guidance for
surface waters. Office of Water, EPA-440/5-90-004, Washington, D.C.
USEPA. 1990b. Development of biological criteria by the States.
DRAFT, Office of Water, Washington D.C.
USEPA. 1988a. Report of the national workshop on instream biological
monitoring and criteria. USEPA Region V Instream Biological
Criteria Committee, USEPA Office of Water, Washington, D.C., 34 p.
USEPA. 1988b. Proceedings of the first national workshop on
biological criteria - Lincolnwood, Illinois, December 2-4, 1987.
EPA-905/9-89/003, USEPA Region Instream Biocriteria and Ecological
Assessment Committee, Chicago, IL, 129 p.
US Supreme Court. 1925. Supreme Court Reporter, October Term 1924,
405-432, 266 U.S.
Washington, H.G. 1984. Diversity, biotic and similarity indices:
a review with special relevance to aquatic ecosystems. Water Res.
18(6):653-694.
Weiner, N. 1948. Cybernetics, or control and communication in the
animal and the machine, pp. 10-11, 60-65. The Massachusetts
Institute of Technology Press, Cambridge, MA.
Wilhm, J. L. and Dorris, T.C. 1966. Species diversity of benthic
macroinvertebrates in a stream receiving domestic and oil refinery
effluents. American Midland Naturalist, 76:427-449.
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Wilhm, J. L. 1967. Comparison of sane diversity indices applied to
populations of benthic macroinvertebrates in a stream receiving
organic wastes. Journal Water Pollution Control Federation, 39:1673-
1683.
Wright, S. and Tidd, W.M. 1930. Summary of liinnolcgical
investigations in western Lake Erie in 1929 and 1930. Transactions
American Fisheries Society/ p. 271-285.
XII
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TABLE OF CONTENTS
Author
Title
Page
Davis
Berg and Hellenthal
Rankin and Yoder
Lenat
Steven and Szczytko
Hilsenhoff
Reash
Troelstrup and Perry
Tazik
Kennedy
Gammon
Ray
Simon
Forward - A Historical Perspective on i
Regulatory Biology
Data Variability and the Use of Chironomids in 1
Environmental Studies: The Standard Error
of the Midge
The Nature of Sampling Variability in the 9
Index of Biotic Integrity (IBI) in Ohio Streams
\
Reducing Variability in Freshwater 19
Macroinvertebrate Data
The Use and Variability of the Biotic Index to 33
Monitoring Changes in an Effluent Stream
Following Treatment Plant Upgrades
. Data Variability in Arthropod Samples Used 47
for the Biotic Index
Results of Ohio River Biological Monitoring 53
During the 1988 Drought
Interpretation of Scale Dependent Inferences 64
from Water Quality Data
Aquatic Vegetation and Habitat Quality in the 86
Lower Des Plaines River: 1985-1987
Use of Acute and Chronic Bioassays to Assess 100
the Applicability of Selected Advanced
Wastewater Treatment Technologies for the
Green Bay Metropolitan Sewerage District
Land Use Influence on Fish Cammunities in 111
Central Indiana Streams
Indiana's NPS Program 121
Instream Water Quality Evaluation of the 124
Upper Illinois River Basin Using the
Index of Biotic Integrity
-------
Data Variability and the Use of Chironomids In Environmental Studies:
The Standard Error of the Midge
Martin B. Berg and Ronald A. Hellenthal
Department of Biological Sciences
University of Notre Dame
Notre Dame, Indiana 46556
Abstract
Many aquatic insect taxa have been used as indicators of environmental quality.
However, none has been used as extensively as chironomids (Diptera:
Chironomidae). The successful use of midges in environmental studies relies on
the integrity and reliability of chironomid databases with species-specific
environmental requirements. Errors or inconsistencies within these databases may
lead to inconclusive or erroneous results. Much of this can be attributed to
methodological errors associated with using midges in environmental assessment.
These include: 1) failure to identify to species, 2) inaccurate identifications,
3) inappropriate sampling designs, and 4) inadequate sampling, sorting and sample
preparation techniques. These errors can have substantial impacts on estimates
of species richness and diversity, on the detection of environmental impact and
change, and on determinations of secondary production rates and energy flow in
aquatic ecosystems. We refer to the common tendency to ignore or misuse
chironomids in environmental assessment as "The Standard Error of the Midge."
Key Words: midges, sampling, taxonomy, data variability, environmental
assessment
Introduction
Aquatic insects long have been used as
indicators of water quality
(Hellenthal 1982). Fundamental to
assessing environmental quality in
aquatic habitats is the recognition of
reliable indicator species or, prefer-
ably, indicator associations or assem-
blages. Historically, one of the most
widely used groups of indicator organ-
isms in both lotic and lentic ecosys-
tems has been larvae of the dipteran
family Chironomidae, or midges.
In lentic ecosystems, Thienemann
(1922) used genera of chironomids,
primarily Qrhionnmus and Tanvtarsus.
as the basis for his lake typology
system. In lotic systems, some of the
earliest pollution studies recognized
the usefulness of chironomids as
indicators of impacted areas (Gaufin
and Tarzwell 1952, Richardson 1921).
The reasons that chironomids have been
used extensively in assessing water
quality are sound. The family
Chironomidae is a species-rich group
with about 15,000 species worldwide
and 1000-2000 species in North America
(Ooffman and Ferrington 1984). Midges
are ubiquitous and frequently the
numerically dominant insects in
aquatic habitats, attaining densities
in excess of 50,000 m"2 (Ooffman and
Ferrington 1984). Finally, the
environmental requirements of many
chironomid species are environmentally
specific and well documented (Beck
1977, Dawson and Hellenthal 1986).
Unfortunately, these characteristics,
which give chironomids such great
potential in environmental assessment,
also contribute to serious diffi-
culties for environmental biologists.
Because of their small size (mature
larvae range from 2-30 mm) and because
of their high densities, the collect-
ing and sorting of larval chironomids
is a tedious and time-consuming pro-
cess. In addition, accurate species-
level identifications of larval
chironomids may be difficult for the
untrained biologist. It is these
species identifications, however, that
are essential for effective use of
chironomids to assess environmental
quality. When combined, errors associ-
ated with the sampling and identifi-
-------
Berg and Hellenthal
cation of chironomids result in highly
variable and unreliable data.
Study Site
The data used to illustrate the caramon
errors associated with using chirono-
mids were collected from Juday Creek,
a third-order stream in northern
Indiana (41°43'N, 86°16'W, elevation =
206 m). Juday Creek is a tributary of
the St. Joseph River that flows north
into Lake Michigan. Mean annual
discharge in Juday Creek is 0.26 ii^s"1
with a range of 0.09 m3s"1 in August
to 0.56 m's"1 in April (Schwenneker
1985). The study site was located 0.35
km upstream from the confluence in a
natural woodland maintained by the
Izaak Walton League of America. This
section of stream has a moderate
gradient of 1.3% and is primarily
riffle habitat with occasional small
pools and a pool:riffle ratio (Platts
et al. 1983) of 0.1:1.
Results and Discussion
Sampling
One of the greatest sources of varia-
bility in using chironomids, particu-
larly in stream studies, is the design
of a sampling regime. Sampling must
consider both spatial and temporal
population characteristics. As with
most stream insects, the distribution
of chironpmid larvae within a stream
reach typically is heterogeneous. This
heterogeneity must be considered in
the design of sampling programs that
attempt to detect changes in community
structure or population densities. To
minimize variability, researchers may
have to choose between collecting many
samples from a wide range of micro-
habitats or collecting fewer samples
that are restricted to a particular
microhabitat.
The distribution of chironomids, even
within a single riffle area, is highly
variable (Figure 1). Thus, studies
that restrict sampling to a particular
area of the stream, such as the
center, still can result in highly
variable density estimates. This
variability, however, can be minimized
Figure 1. Three-dimensional response
surface showing the distribution of
the chironomid Pagastia (Oliver)
(Diamesinae) during the winter within
a single riffle area of Judav Creek.
by conducting a preliminary study to
determine species-specific micro-
distributional patterns (Schwenneker
and Hellenthal 1984). Results from
this preliminary study then can be
used to develop a more efficient
sampling strategy designed to address
the specific question being con-
sidered. For example, prior to
conducting a study in Juday Creek,
preliminary sampling was used in an
attempt to minimize variability of
chironomid density estimates. Based on
results from this preliminary study, a
sampling program was designed that
resulted in density estimates with
standard errors within 5% of the mean.
In addition to considering spatial
variability in designing adequate
sampling programs, temporal varia-
bility components also must be
addressed. Since the Chironomidae is a
diverse taxonomic family, often with
more than 100 species found in a given
habitat (Boerger 1981), a wide variety
of life cycles commonly are repre-
sented. These can range from uni-
voltine to asynchronous. Species with
overlapping cohorts may make determin-
ation of life cycles difficult.
Chironomid life cycles of three, four
-------
Standard Error of the Midge
or more generations per year are
cannon. As a result of these diverse
life cycles, densities of chironomids
can vary dramatically throughout the
year (Figure 2). Densities of
chironomids in Juday Creek range from
7500 m"2 in October to 90,000 m"2 in
early May. Variations such as these
must be taken into account in the
design of adequate sampling programs.
In Juday Creek, 50 samples would be
required to detect a 100% change in
total chironomid numbers during the
summer while only 15 samples would be
necessary during the winter. It is
clear that a knowledge of species life
histories is essential to design the
most cost-effective and efficient
sampling program. Knowledge of life
histories also is essential to ensure
that failure to collect a particular
species is not misinterpreted as an
effect of an environmental impact.
Instar-specific distributional
patterns also may be an important
source of data variability. The summer
and winter distributions of
Parametriocnemus lundbecki (Johannsen)
(Orthocladiinae), in addition to
showing substantial spatial
heterogeneity within each season, also
100,000-,
5
cc
i
z
80,000-
60,000-
40,000-
20,000-
JAS O N D J FMA M J
MONTH
Figure 2. Annual variability in total
larval chironomid density (mean
density m'2 ± 95% CI) in Judav Creek.
demonstrate large interseasonal
distribution differences (Figure 3).
These differences are primarily the
result of early instar larvae predom-
inating along stream margins in the
summer and moving toward the center of
the stream as they mature during
winter. The summer sample was
collected early in the season at a
time when most of the organisms were
second instars. The winter sample, on
the other hand, had a mixed assemblage
of second, third and fourth instars.
The high degree of intra-annual
variability due to instar-specif ic and
species-specific distributional
patterns may limit the ability to
detect significant changes in
chironomid densities and species
composition during the course of a
year. This variability can be
minimized by restricting sampling to a
particular time of year. This decision
should be based on the specific
question being addressed. For example,
in studies that attempt to detect
changes in chironomid densities,
sampling should be conducted at times
when densities are most stable. Such
an approach will result in a greater
likelihood of detecting an environ-
mental impact in addition to saving
substantial time, manpower and money.
. Thus, failure to consider both spatial
and temporal aspects of chironomid
sampling can result in the inability
to detect environmental change or an
erroneous conclusion that an
environmental change has occurred.
A second major source of variability
is choice of sampling method. Hess and
Surber samplers, which are among the
most commonly used benthic samplers,
typically have too coarse mesh sizes
to retain most larval chironomids. The
use of one of these samplers or a
similar type of net, such as a kick-
net, leads inevitably to the loss of
many chironomids and, therefore, to a
gross underestimation of chironomid
densities. In addition, methods such
as these also bias sampling in favor
of larger taxa and may lead to serious
underestimates of species richness and
-------
Berg and Hellenthal
SUMMER
\
Figure 3. TJiree-dimensional response
surface illustrating interseasonal
variability in mica^odistributional
patterns of the chironomid
Parametriocnemus lundbecki (Johannsen)
(Orthocladiinae) in Judav Creek.
diversity. Similar errors occur when
sampling involves scrubbing rocks,
tiles or other substrates with
brushes. Passing benthic samples
through one or more sieves to facili-
tate sample processing and sorting
also may cause the loss of substantial
numbers of chironomids. In Juday
Creek, even the use of a 250/zm mesh
sieve often resulted in the loss of as
much as 80% of the larval chironomids.
Samples with high densities should be
subsampled repeatedly until a manage-
PERCENT WEIGHT LOSS
40 r
30
20
10
y - 6.76 * 14.96 log x
(n - 27. r 2- 0.90)
*
0.1 1 10 100
PRESERVATION TIME (MONTHS)
Figure 4. Replicated linear regression
of percent weight loss of chironomid
larvae versus length of time in an 80%
ethanol preservative.
able density is attained. Analyses
should then be conducted on the entire
subsample.
Sampling errors also occur in attempts
to measure standing stock biomass of
chironomids, such as those in second-
ary production studies. Conflicting
views can be found in the literature
as to the effects of preservatives on
biomass estimates. Some researchers
have reported little or no weight loss
upon preservation in formalin or
ethanol (Wiederholm and Eriksson 1977)
while others claim substantial losses
in weight (Howmiller 1972). In a four-
year study of the effects of an 80%
ethanol preservative on dry mass of
larval chironomids, we found that
chironomid biomass decreased by 5%
after the first month, 22% after 1
year (i.e. an additional 17% from
month 1 to month 12) and 31% after 3
years (or an additional 9% from month
12 to month 48) (Figure 4). Percent
weight loss was described by the
linear regression:
y = 5.76 + 14.961og x (n=27, 1^=0.90),
where x = months in preservative.
Weight loss using other types of
preservatives also may occur. Thus,
-------
Standard Error of the Midge
the length of time in preservative can
result in substantial differences in
chironomid standing stocks observed
between different studies as well as
within a study. Understanding the
relationship between duration in
preservative and changes in biomass is
essential in any study that relies on
estimates of standing stocks or
secondary production. Ihe duration of
these studies should correspond to the
maximum length of time any one sample
remains in preservative prior to
biomass determination.
It is now clear that different methods
can yield substantially different, and
potentially conflicting, results.
Thus, the high level of variability
observed among studies using chirono-
mids is not surprising given that
results from studies using different
methods often are compared.
Identification
Another major source of error in
environmental studies using chirono-
mids concerns larval identifications.
Taxonomic keys for larval chironomids
are based largely on conspicuous, or
not so conspicuous, headcapsule char-
acteristics of mature fourth instar
larvae. To see these characters, it is
necessary to sever the headcapsule and
mount both headcapsule and body on a
microscope slide. Thus, the
identification of even a few larvae is
an extremely time-intensive ordeal. It
is not difficult to understand why
many researchers have tried to find
short cuts to avoid this whole
procedure. The roost common short cut
is to group all chironomids at the
family level and to deal with the
midges as a single taxonomic entity.
This approach invariably will result
in the loss or obscuring of important
information such as species diversity
and species richness that could be
used in assessing environmental
quality. This is probably why the use
of chironomids as environmental
indicators has had varying success. If
expertise in the identification of
larval chironomids is lacking, it is
essential to seek additional
assistance so that the sensitivity of
the results can be maximized.
Ideally, the identification of
chironomids to the species level would
be of greatest value since published
environmental requirements are
described for individual species.
However in the case of some larval
chironomids, the inability to make
species-level identifications without
rearing the larvae, combined with the
high number of species collected in a
given habitat, result in studies
identifying chironomids to a taxonomic
level higher than species, such as
species group or subfamily. This
approach obscures important ecological
information since a high level of
diversity exists within these groups
with respect to species-specific
environmental requirements. The
different taxonomic levels to which
midges are identified in different
studies must be kept in mind. Failing
to do so can result in the inability
to assess the usefulness of chirono-
mids in environmental evaluation.
An obvious source of error when using
chironomids is the accuracy of the
identification. Chironomid taxonomy
has gone through major changes in the
past decade and continues to change at
a rapid pace. Relying on outdated
handbooks that provide keys to midges
can result in costly misinterpreta-
tions of community composition. These
misinterpretations are perpetuated in
the literature and inevitably result
in erroneous or conflicting conclu-
sions that cast doubt on the useful-
ness of midges in environmental
research. The value of accurate and
complete chironomid identifications
can not be overstated. Confirmation of
species identifications by qualified
researchers and the maintenance of
voucher collections are important
steps to ensure the integrity of
chironomid databases.
Given all of the variability associ-
ated with using chironomids and the
-------
Berg and Hellenthal
Table 1. Assumptions of the size-frequency method and effects on secondary
production estimates if assumptions are violated.
Effect on Production Estimate
All species have similar life cycles
All species attain same maximum size
Assumption
Underestimate
Overestimate
Same length of time is spent in each size class Overestimate or Underestimate
difficulty in working with them, the
question that often arises is why do
they even have to be considered? One
way of assessing the importance of
chironomids would be to examine their
role in energy transfer and their
contribution to overall stream insect
secondary production. Previous studies
that have attempted to examine
chironomid secondary production have
committed many of the same errors
discussed above.
One of the most commonly used methods
to calculate chironomid secondary
production is the size-frequency
method (Hynes and Ooleman 1968). Since
this method does not necessitate
cohort separation, chironomids usually
are pooled at the family level and
production is calculated on the family
as a whole. However, a series of
assumptions associated with this
method is invariably violated when
chironomids are grouped into a single
taxonomic group. Ihese assumptions
are: 1) all species have similar life
cycles, 2) all species attain the same
maximum size, and 3) the same length
of time is spent in each size class.
Violating these assumptions can either
underestimate or overestimate
secondary production or can have
unpredictable effects on secondary
production estimates (Table 1).
In a study conducted in Juday Creek,
we estimated chironomid secondary
production by following 48 species for
one year and calculating secondary
production on a species-specific and,
usually, a cohort-specific basis
without grouping midges at some higher
taxonomic level. We found that the 15
numerically dominant chironomid
species accounted for over 80% of the
total stream insect secondary produc-
tion (Figure 5). Thus, chironomids are
an important energetic component in
streams and must be considered in any
rapid bioassessment or other
environmental assessment program.
Conclusions
The effects of common methodological
and taxonomic errors in chironomid
studies have strong implications in
many areas of aquatic ecology such as
designing adequate sampling programs,
the examinations of secondary produc-
tion and seasonal patterns of energy
flow, and the evaluation of stream
diversity, as well as the ability to
conduct successful environmental
monitoring. If chironomids are to be
used successfully in future environ-
mental studies, reducing the level of
non-impact related variability is
crucial. This can be achieved best by
reducing what we have called the
"standard error of the midge."
Literature Cited
Beck, W.M. 1977. Environmental
requirements and pollution tolerance
of common freshwater Chironomidae.
Report No. EPA-600/4-77-024. U.S.
Environmental Protection Agency,
Cincinnati, Ohio.
Boerger, H. 1981. Species composition,
abundance and emergence phenology of
midges (Diptera: Qiironomidae) in a
brown-water stream of West-Central
Alberta, Canada. Hydrobiologia 80:7-
30.
Coffman, W.P. and L.C. Ferrington, Jr.
1984. Chironomidae. Pages 551-652 in
R.W. Merritt and K.W. Cummins (eds.).
-------
Standard Error of the Midge
DIPTERA (EX. CHIR.)
1.3
OTHER ORDERS
0.5
TRICHOPTERA
3.4
CHIRONOMIDAE
29.7
Figure 5.Comparison of chironomid and non-chironoitdd secondary production rates
fa drv mass m'2 vr'M in Juday Creek.
An introduction to the aquatic insects
of North America. Kendall/Hunt,
Dubuque, Iowa.
Dawson, C.L. and R.A. Hellenthal.
1986. A computerized system for the
evaluation of aquatic habitats based
on environmental requirements and
pollution tolerance associations of
resident organisms. Report No. EPA-
600/53-86/019. U.S. Environmental
Protection Agency, Cincinnati, Ohio.
Gaufin, A.R. and C.M. Tarzwell. 1952.
Aquatic invertebrates as indicators of
stream pollution. Public Health Report
67:57-64.
Hellenthal, R.A. 1982. Using aquatic
insects for the evaluation of
freshwater canmunities. Pages 347-354
in N.B. Armantrout (editor).
Acquisition and utilization of aquatic
habitat inventory information. Western
Division of the American Fisheries
Society.
Howmiller, R.P. 1972. Effects of
preservatives on weights of some
common macrobenthic invertebrates.
Transactions of the American Fisheries
Society 101:743-746.
Hynes, H.B.N. and M.J. Coleman. 1968.
A simple method of assessing the
annual production of stream benthos.
Limnology and Oceanography 13:569-573.
Platts, W.S., W.F. Megahan and G.W.
Minshall. 1983. Methods for evaluating
stream, riparian,
and biotic
conditions. "u.S. Forest Service,
General Technical Report INT-138.
Richardson, R.E. 1921. The small
bottom and shore fauna of the Middle
and Lower Illinois River and its
connecting lakes, Chillicothe to
Grafton; its valuation; its sources of
food supply and its relation to the
fishery. Illinois Natural History
Survey Bulletin 13:363-522.
Schwenneker, B.W. 1985. The
contribution of allochthonous and
autochthonous organic material to
aquatic insect secondary production
rates in a north temperate stream.
Ph.D. Dissertation, University of
-------
Berg and Hellenthal
Notre Dame, Notre Dame, Indiana.
363pp.
Schwenneker, B.W. and R.A. Hellenthal.
1984. Sampling considerations in vising
stream insects for monitoring water
quality. Environmental Entomology
13:741-750.
Thienemann, A. 1922. Die beiden
Chiroronusarten der Tiefenfauna der
norddeutschen Seen. Ein
hydrobiologisches Problem. Archiv fur
Hydrobiologie 13:609-646.
Wiederholm, T. and L. Eriksson. 1977.
Benthos of an acid late. Oikos 29:261-
267.
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The Kature of Sampling Variability in the Index on Biotic
Integrity (IBI) in Ohio Streams
Edward T. Rankin and Chris O. Yoder
Ecological Assessment Section
Division of Water Quality Planning and Assessment
Ohio EPA
1030 King Avenue
Columbus, OH 43212
Abstract
Hie Index of Biotic Integrity (IBI) was examined from a number of Ohio streams
to determine the amount of variation that can be expected among replicate samples
within years and among rivers with various degrees of cultural impact. Biosurvey
data have been collected with standardized, pulsed-DC electrofishing techniques
by the Ohio EPA over the past 12 years as part of its surface water monitoring
program. The variation among samples, as measured by the coefficient of variation
(CV) is lowest in streams and rivers that are least impacted by pollution (CV
values < 10-12%) and increases in streams as cultural pollution increases (CV
values up to 30-40%) until impacts are so toxic that there are only minimal fish
communities (IBI scores 12-15). Indeed, high variability among samples in a year
was a characteristic of impacted waterbodies. Variability among sampling passes
also increased with decreasing habitat quality as measured by the Qualitative
Habitat Evaluation Index (QHEI). Precision in the IBI compared favorably to
precision in toxicological studies and analytical chemistry results. Among these
approaches, as a direct measure of aquatic life, the IBI will be the most
accurate arbiter of aquatic life use attainment in most situations.
Introduction
With increasing use of biosurvey data
in state water resource monitoring
programs it is important to under-
stand, define and control the sources
of variation common to biosurvey data.
The Ohio EPA has been collecting fish
community data, in a standardized
manner, in streams and rivers since
1979 and has amassed data on over 3600
sites. This data provides an
opportunity to examine patterns of
data variability in response to
temporal, geographical, and
anthropogenic factors.
Five important sources of variability
in biosurvey data are: (1) temporal
variability (e.g., seasonal, daily,
and diurnal changes in community
composition), (2) sampling varia-
bility (e.g., related to gear, train-
ing, and effort), (3) spatial varia-
bility (e.g., related to stream size,
fauna! changes), (4) analytical
variability (e.g., related to choice
of the appropriate analytic tool), and
(5) anthropogenic variability (e.g.,
degradation of water quality, habitat,
toxic impacts to aquatic communities).
It is critical to minimize or
partition temporal, sampling, and
analytical variation in biosurvey data
to maximize the ability to distinguish
anthropogenic impacts and variation.
The goal of this paper is to define
the "background" variation in the
Index of Biotic Integrity (IBI) in
minimally impacted streams (to define
temporal and sampling variability) for
comparison with variability in streams
impacted by anthropogenic activities
(i.e., those with aquatic life use
impairment).
Background and Methods
The Ohio EPA uses pulsed-DC electro-
fishing methods (Ohio EPA 1989a) to
capture a representative sample of the
resident fish community in Ohio
streams and rivers. Temporal varia-
bility in fish communities composition
is minimized by sampling during
daylight hours during the summer-early
fall months (June 15 - October 15). In
most situations we collect three
sampling passes on different days
during this period to detect within
-------
Rankin and Yoder
season (temporal) changes in the fish
community. Recent work, however, in
the largest Ohio rivers (Ohio River,
lower Muskingum River) suggests that
night sampling may provide more
reliable results in these waterbodies
(Sanders 1990) and we have excluded
these rivers from this analysis.
Sampling variability is minimized
through an extensive training program
supported by a a detailed quality
assurance manual (Ohio EPA 1989a) and
the retention of experienced super-
visory and field personnel (average
experience > 10 years). Sampling
equipment (longline, towboat, or boat
mounted electrofishers) and methods
and sampling effort are chosen to
match the stream size and habitat
(Figure 1). Effort is standardized on
linear sampling distance which
increases with stream size (Figure 1);
minimum sampling times are defined for
boat methods to ensure a minimum level
of effort in large river habitats.
Macroinvertebrate community data and
water column chemistry data are
generally collected during the same
time period as fish community data
(June 15 - October 15). Field crews
also perform habitat assessments with
the Qualitative Habitat Evaluation
Index (QHEI: Rankin 1989, Ohio EPA
1989a) within fish sampling zones.
Water chemistry data, habitat data,
knowledge of pollution sources, and
biological response "signatures"
(e.g., community response to differ-
ent types of impacts) are used to
determine the causes, sources, and
magnitudes of impacts to aquatic life
(Ohio EPA 1990). The Index of Biotic
Integrity (IBI) is an analytical index
used to assess fish community
integrity; its applicability and
derivation have been discussed else-
where (Karr 1981, Fausch et al. 1984,
Karr et al. 1986, Ohio EPA 1987a,b).
As a measure of variation we
calculated the percent coefficient of
variation (SD/Mean * 100) for the IBI
at sites with three sampling passes
200J00400500600 100 800900 1000
Drainage Area (sq mi)
Figure 1. Range of stream sizes
sampled by the Ohio EPA with boat,
towboat, and longline pulsed-DC
electrofishing methods. Sampling zone
length for each method is included on
each graph.
between Junel5 - October 15. The IBI,
the Index of well-being (Iwb) for fish
(Gammon et al. 1981) and the Inverte-
brate Community Index (Id) for
macroinvertebrates (Ohio EPA 1987b)
comprise Ohio's biocriteria (Ohio
Administrative Code 3745-1) and are
the arbiter of aquatic life use
impairment for Ohio's streams and
rivers.
Although it is beyond the scope of
this paper, one critical source of
variation in water resource monitor-
ing with biosurvey data is the appro-
priate choice of analytical tool. The
advantages of broad-based, multi-
metric indices that have an ecological
basis with both structural and
functional components have been dis-
10
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Sampling Variability in the IBI
cussed by others (Karr 1981, Fausch et
al. 1984, Karr et al. 1986, Karr
1990).
Results and Discussion
The median percent coefficient of
variation (CV) at 1335 sites (1979-
1989) with three sampling passes shows
a distinct increase with decreasing
IBI score except at the very lowest
IBI range of 12-15 (Figure 2). Figure
2 is divided into IBI ranges that
roughly correspond to Ohio's
Exceptional Wantiwater Habitat (EWH)
aquatic life use IBI criteria, Wanti-
water Habitat (WWH) aquatic life use
IBI criteria, and IBI scores that
reflect impaired aquatic life uses.
The median CV is generally less than
10% in EWH streams and 15% in WWH
streams that achieve their respective
IBI biccriteria. The distribution and
range of CV values broadened signifi-
cantly in streams with impaired
aquatic life uses except at the very
lowest IBI scores (12-15). By them-
selves increases in the variation of
biosurvey data are an indication of
impact to a stream. Cairns (1986)
suggests that "...differences in
variability rather than differences in
averages or means might be the best
measure of stress in natural systems".
Increases in variation are observed
among streams affected by most types
of impact (Figure 3). Ohio has no
pristine, unimpacted streams. The
"least impacted" streams in Ohio,
however, such as the West Fork of
Little Beaver Creek, Captina Creek,
Pocky Fork of the Licking River, and
the Kokosing River, have CV values of
less than 5-10% and stable fish
communities (as measured by the IBI).
For example, the West Fork of Little
Beaver Creek achieves an IBI of 50 or
more (Ohio's EWH IBI criteria) in 25
of 27 sampling passes (Figure 4). This
data spans five years and the two
exceptions to this trend are due to a
problem of recent origin.
Streams with inpacted fish communities
(IBI scores generally less than 40)
had 75th percentile CV values of >
10-15% and as high as 30-40% (Figure
3). For example, the CV was negatively
correlated with the QHEI (Qualitative
Habitat Evaluation Index: Rarikin 1989,
Ohio EPA 1989), a measure of habitat
quality (Figure 4). Low QHEI scores
reflect low habitat quality that
supports fewer habitat sensitive
species and more tolerant individuals
resulting in higher variability in
catches and CKJE. Other impacts also
resulted in increased variation in the
IBI with toxic impacts among those
associated with the highest IBI
variation (Figure 3). Low species
richness or low abundance of certain
species, due to any impact type,
increases the likelihood of IBI
metrics being near scoring thresholds
(1 vs 3 or 3 vs 5 points) and
increases the variability in the IBI.
Similarly, water quality impacts can
reduce species numbers or affect
trophic group composition through
avoidance or mortality, and increase
the variability of the IBI.
In contrast, extremely toxic impacts
(IBI scores 12-15) were often
characterized by little or no
variation. In these situations few
fish survive and metrics nearly always
score a one. Exceptions are the
downstream "edge" of a toxic effect
(or episodic water quality impacts)
which may shift the location of an
impact over time, especially where
there is migration from a nearby
"refugia" with a healthy fish
community. This situation was
illustrated in Hurford Run near Canton
Ohio (Figure 5). Upstream sections of
Hurford Run had fish communities that
were consistently very poor, but the
fish community near the mouth
fluctuated as tolerant, colonizing
fish species (young-of-year green
sunf ish [Lepomis cyanellus], bluntnose
minnow [Pimephales notatus], creek
chub [Semotilus atromaculatus])
migrated from a roainstem "refugia".
The CV showed no regional pattern
other than that which can be explained
11
-------
Rankin and Yoder
o
L\As
90
80
70
Coefficient
of *°
Variation so
40
30
20
10
n
Aquatic Life Use Impaired
o
o
o
0 0 0
0
.° •
* 0 0
8
• T * -
0 °
T
T
i
w
o
0 °
o
1 *I *
M9^¥y$
Warmwater
Habitat
e
e
o
e
4 i
Exceptional
Warmwater
Habitat
•>
^2^9Sw ^^^^^^^
12-15
16-20 21-25 26-30 31-35 36-40 41-45 46-50 51-55
56-60
IBI Range
Figure 2. Median percent coefficient of variation (CV), 25th and 75th CV
peroentiles, CV range, and CV outliers (> 2 interquartile ranges from median) for
the Index of Biotic Integrity (IBI) versus IBI range. CV values were calculated
for sites with three sampling passes collected between June 15 - Oct 15. N = 1335
sites.
QHEI and CV by River
/u
60
50
% Coefficient
Of 40
Variation
30
20
10
0
4 n
.
-
-
-
1
1 1
"1 Wrt
i "1
-10 '
90
i • • * •
i
ii
1
n
i
H
7
i
t
vi i
Predominant Imoact Tvoea:-
1
1 1
i
O Umnallmpta J
| TOXK Impta '_
| Conv«ntion««mp«cl '
0 HmbUmt lmp*ct ~
^ ^toqpoOTf hnpaci \
-
i :
-
"„ ? ^
T :
i
I" :
i
i :
80 70 60 50 40
Mean QHEI
Figure 3. Median percent coefficient of variation (CV), and 10th and 90th CV
percentiles for the Index of Biotic Integrity (IBI) versus QHEI (Qualitative
Habitat Evaluation Index) for twenty Ohio streams and rivers. Shading of median
in these stireams.
12
-------
Sampling Variability in the IBI
IBI
60
50
40
30
20
10
1989
West Fork Little Beaver Creek
14
12
10
River Mile
Figure 4. The Index of Biotic Integrity (IBI) versus river mile (upstream to
downstream) for the West Fork of Little Beaver Creek (Oolumbiana Oo., Ohio) for
1985 (11=3 passes). 1987 (N = 1 pass). and 1989 fN = 1
60
IBI
50
40
30
20
10
Hurford Run
1 — O-IBI - 1985
-•e-IBI - 1986
-•-IBI - 1987
WWHBac
'
— »~CV | * .
« I
rttna
I -
I
Recovery/Edge Effect I
i . . , , i
/* "
s
I
25
20
15
10
5
0
cv
2.5
1.5 1
River Mile
0.5
Figure 5. Ihe Index of Biotic Integrity (IBI) and median percent coefficient of
variation (CV) versus river mile (upstream to downstream) for the Hurford Run
(Stark Oo., CXiio) for 1985 (N=3 passes), 1986 (N = l pass), and 1988 (N = 1
13
-------
Rankin and Yoder
by overall impacts within the eco-
regions of Ohio (Figure 6). There was
a slight trend in the upper threshold
of variation in the IKE with stream
size (Figure 7). Figure 7 represents
the CV for streams in Ohio with IBI
scores greater than 48 (i.e., the CV
at these sites represents background
variation due to inherent sampling
variation and normal fluctuations in
fish communities over time). The
increase in the CV with stream size
(Figure 7) roost likely reflected the
smaller proportion of the total
community that was sampled in large
versus small streams. Even in larger
rivers, however, the CV was under
the majority of situatit
60
55
50
45
IBI40
35
30
25
20
15
10-
HELP
IP
EOLP
WAP
ECBP
HELP
IP EOLP WAP ECBP
Ecoregion
Figure 6. Boxplot of the median, 25th
and 75th percentiles, range, and
outliers (> 2 interquartile ranges
from median) for the IBI (top panel)
and percent coefficient of variation
(CV, bottom panel) for sites in Ohio's
five ecoregions. HELP: Huron Erie Lake
Plain, IP: Interior Plateau, EOLP:
Erie Ontario Lake Plain, WAP: Western
Allegheny Plateau, ECBP: Eastern Corn
Belt Plains.
Development of Ohio EPA "Significant
Difference" in the IBI
Because we expected some background
variation or "noise" in our samples we
derived guidelines for detecting
significant differences between IBI
values from our intensive surveys and
the regional reference sites used to
derive our ecoregion-based
biocriteria. We examined histograms of
deviations in sample IBI values from
mean IBI values at all locations where
we had three sampling passes (Figure
8). We chose the 75th percentile value
of this deviation from the mean as the
limit of tolerable variation. This
resulted in a guideline that the
difference between a sample IBI and
the ecoregion IBI biocriteria must be
greater than 4 units to be classified
as a significant, departure. Because we
used a mix of impacted and relatively
unimpacted sites deviations of greater
than 4 units probably reflects
variation of anthropogenic origin.
This is a protective criteria,
however, because all available and
applicable criteria for two organism
groups (i.e., the modified iwb for
fish in addition to the IBI and ICI
for macroinvertebrates) must be met to
fully attain an aquatic life use (Ohio
EPA 1987b).
Detecting impacts and their underlying
causes is more complex than simply
determining significant departures
from ecoregion biocriteria. For sites
not attaining their aquatic life use
the structural and functional
characteristics of fish and
macroinvertebrate communities provide
information or "biological response
signatures" about the type of impact
that is affecting the aquatic life
(Ohio EPA 1990a). Two sites that have
similar IBI scores that indicate
impaired communities may have very
different community responses. The
difference in the composition,
function, and structure of the
communities, in concert with chemical,
toxicological, and physical data,
provide clues to the cause or causes
of impairment. Similarly, contrasts
14
-------
Sampling Variability in the IBI
25
22.5
20
17.5
15'
CV 12.5
10
7.5
5
2.5
O Towboit or Longline Methods
• Boat Methods
95% Line
1
10 100
Drainage Area (sq mi)
1000
Figure 7. Median percent coefficient of variation (CV) versus drainage area for
streams in Ohio with IKE scores > 48. The line on the graph represents an "upper
threshold" and was drawn by eve through the upper 5% of the points.
350
300
250
Number
of 20°
Sites
150
50th Percentile = 3
75th Percentile = 4
90th Percentile = 6
95th Percentile = 8
IBI Deviation from Mean
Figure 8. Frequency of the deviations of individual IBI passes from mean IBI
values at stream sites with three sampling passes for all sites (solid bars) and
reference sites (cross—hatched bars).
15
-------
Rankin and Yoder
between the fish and macroinvertebrate
community response are advantageous
for detecting the type of impact. Work
on formally classifying the responses
of the biota to different types of
impacts is in a developmental stage.
New techniques, such as artificial
intelligence (e.g., machine learning
algorithms) may prove useful in this
endeavor (David Davis, BEN Inc.,
personal communication).
Comparison of the CV values from
biosurveys with other types of
environmental monitoring data (e.g.,
water column chemistry, toxicity
testing) provides additional perspec-
tive on the precision of the IBI.
Mount (unpublished) compiled coeffi-
cient of variation values from a
number of efforts to compare inter-
laboratory variability in toxicity
testing and analytical water chemistry
data. For organic and inorganic
analyses most CV values were greater
than 30% for the lower detection range
of these parameters (e.g., mean of
inorganic analyses = 125%). CV values,
however, generally decrease when
higher concentrations of compounds are
analyzed (Turle 1990). The mean CV
value (inter-laboratory variability)
for toxicity tests (mostly LC50
values) was 30% (range: 0 - 66%; N =
16 CV values). Although replicate
variability in the IBI was examined in
this paper, the levels of
interlaboratory variability associated
with analytical chemistry data and
toxicity testing are somewhat higher
than the replicate biosurvey data.
Though this interlaboratory
variability is not strictly comparable
to biosurvey replicate variability it
does suggest that variability in
biosurvey data is within or below the
range of other, widely accepted
environmental measurements.
CV values for replicate macroinverte-
brate samples in a Wisconsin stream
ranged from 6.2% to 43.6% (Szczykto
1989) depending on the index used in
the analysis (all index scores were
generated from the same data). Davis
and lubin (1989) calculated a CV of
20% for the Invertebrate Community
Index (ICI) for all of the sites in
Ohio EPA's regional reference site
database. "Background" levels of
precision are likely lower than 20%
for replicate ICI scores for any given
site because the reference sites are
not homogeneous and represent a
gradient of aquatic life performance.
Nineteen replicate Id scores at a
relatively unimpacted test site in Big
Darby Creek had a CV of 10.8%, which
was lower than 8 of 9 of the index's
underlying components. This CV value
is similar to those found for the IBI
in relatively uniinpacted sites (see
Figure 3).
Based on the data presented here the
IBI scores collected by the Ohio EPA
reflect low enough levels of sampling
and natural variation to detect
meaningful changes in biological
integrity in streams. The precision of
the IBI compares favorably with
precision in analytical water
chemistry methods and toxicity
testing. However, this is not an
effort to establish the "superiority"
of one environmental measure over the
other. Beyond considerations of
precision, biosurvey data, water
chemistry data and toxicity tests have
specific applications where they are
most appropriate and accurate. Our
experience in Ohio has shown us that
biosurvey, water chemistry, and
toxicity testing are all necessary to
completely and accurately define an
impact to a stream in a complex
situation, but that each is not
necessarily independent of the other
in all situations. There will be
instances where one measure will carry
more influence or weight than another.
Unfortunately, this is not completely
predictable at this point.
In the assessment of water resource
impacts it is important to differ-
entiate between accuracy and pre-
cision and to choose the appropriate
"tool". Given an acceptable level of
precision, emphasis should be put on
16
-------
Sampling Variability in the IBI
environmental measures that accurately
reflect water resource management
goals (e.g., protection of aquatic
life). For example, biological
community data is free from
assumptions and safety factors
associated with laboratory derived
data and accurately and directly
reflects attainment of aquatic life
uses (i.e., a high level of reality).
Rankin and Yoder (1990) have shown
that a reliance on water chemistry
data and criteria alone under-
estimated the impacts on aquatic life
uses in Ohio in 49% of stream segments
that were assessed. In contrast, only
a small percentage of stream segments
(< 3%) had biological communities that
attained aquatic life uses, but
violated chemical water quality
criteria.
The IBI, when data collection methods
are standardized, increases the
accuracy of water resource assess-
ments. Further work needs to: (1)
identify biological response "signa-
tures" for different types of impact,
(2) identify situations where bio-
survey data from multiple organism
groups decreases the "variability" or
increases the sensitivity of an
assessment, (3) identify inter-
laboratory variability in biosurvey
data collection, and (4) compare
variation between quantitative,
standardized sampling methods (Ohio
EPA approach described here) and more
qualitative methods (e.g., Rapid
Bioassessment Protocols, volunteer
monitoring).
Acknowledgements
The work summarized here could not
have been accomplished with the help
of the staff biologists at the Ohio
EPA: Marc Smith, Jeff DeShon, Chuck
McKhight, Randy Sanders, Jack Freda,
Roger Thoma, and Mike Bolton.
References
Fausch, K. D., J. R. Karr, and P. R.
Yant. 1984. Regional application of an
index of biotic integrity based on
stream fish communities. Transactions
of the American Fishery Society
113:39-55.
Karr, J. R., K. D. Fausch, P. L.
Angermeier, P. R. Yant, and I. J.
Schlosser. 1986. Assessing biological
integrity in running waters: A method
and its rationale. Illinois Natural
History Survey Special Publication No.
5, 28 pp. Champaign, Illinois
Karr, J. R. 1989. Monitoring of
biological integrity: An evolving
approach to assessment and
classification of water resources.
Proceedings of the Midwest Pollution
Control Biologists Meeting. U.S. EPA,
Chicago, IL. EPA-905/9-89-007.
Mount, D. I. 1987 (unpublished).
Comparison of test precision of
effluent toxicity tests with chemical
analyses. U. S. EPA, Environmental
Research Laboratory, Duluth,
Minnesota.
Ohio Environmental Protection Agency.
1987a. Biological criteria for the
protection of aquatic life: Volume I.
The role of biological data in water
quality assessment. Division of Water
Quality Planning and Assessment,
Ecological Assessment Section,
Columbus, Ohio.
Ohio Environmental Protection Agency.
1987b. Biological criteria for the
protection of aquatic life: Volume II.
Users manual for biological field
assessment of Ohio surface waters.
Division of Water Quality Planning and
Assessment, Ecological Assessment
Section, Columbus, Ohio.
Ohio Environmental Protection Agency.
1989a. Biological criteria for the
protection of aquatic life: Volume
III. Standardized biological field
sampling and laboratory methods for
assessing fish and macroinvertebrate
communities. Division of Water
Quality Planning and Assessment,
Ecological Assessment Section,
Columbus, Ohio.
17
-------
Rankin and Yoder
Ohio Environmental Protection Agency.
1990a. Water Resource Inventory -
Executive Summary: Volume I 1990
305(b) report. Edward T. Rankin, Chris
Yoder, and Dennis Mishne. Division of
Water Quality Planning and Assessment..
Rankin, E.T. and C.O. Yoder. 1990. A
Comparison of Aquatic Life Use
Iirpairment Detection and its Causes
between an Integrated, Biosurvey-Based
Environmental Assessment and its Water
Column Chemistry Subcomponent.
Appendix I In: Ohio Environmental
Protection Agency. 1990. Water
Resource Inventory - Executive
Summary: Volume I 1990 305 (b) report.
Edward T. Rankin, Chris Yoder, and
Dennis Mishne, editors. Division of
Water Quality Planning and Assessment,
Ecological Assessment Section,
Columbus, Ohio.
Sanders, R. 1990. A 1989 night
electrofishing survey of the Ohio
River mainstem (EM 280.8 - 442.5).
Ohio EPA, Division of Water Quality
Planning and Assessment, Ecological
Assessment Section, Columbus, Ohio
Szczytko, S. W. 1989. Variability of
commonly used macroinvertebrate
community metrics for assessing
biomonitoring data and water quality
in Wisconsin streams. Proceedings of
the Midwest Pollution Control
Biologists Meeting. U.S. EPA, Chicago,
IL. EPA-905/9-89-007.
Turle, 1990. In-house reference
materials as a means to QA: The CMS
experience. Third Ecological Quality
Assurance Workshop, Canada Centre for
Inland Waters, Burlington, Ontario,
Canada.
18
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Reducing Variability in Freshwater Macroinvertebrate Data
David R. Lenat
NC Division of Environmental Management
Water Quality Section
Archdale Building
PO Box 27687
Raleigh NC 27611
Abstract
The benthic macroinvertebrate cxatimunity is often used to evaluate stream water
quality, but this efficiency of this process may be complicated by high data
variability. This variability can be reduced by proper selection of sampling
sites, collection methods, identification levels, and analysis metrics.
Corrections also can be made to compensate* for predictable changes associated
with ecoregion, stream size and seasonality. Some evaluation should be made for
the effects of antecedent flow, especially after droughts and high rainfall
periods.
Key words: North Carolina, benthos, data variability, methods, identification.
Introduction
Environmental monitoring groups often
use characteristics of freshwater
macroinvertebrate communities to
assess stream water quality. In cases
of severe pollution, any kind of
collection technique and/or any kind
of data analysis can be used to
demonstrate a water quality problem.
In cases of "less than catastrophic"
pollution, however, high data
variability may obscure the effects of
changes in water quality (Howmiller
1975). There are many different
sources of variation for benthic
macroinvertebrate data, including
differences in collection efficiency,
habitat, season of the year, and flow.
The problems of data variability can
be greatly reduced by making correc-
tions for any changes in habitat and
season of the year, as well as through
wise choices of identification levels,
collection methods, and data analysis
techniques. Erman (1981) has shown the
frustrations in trying to compare
studies with different collection
techniques and identification levels.
This paper will focus on North
Carolina's experience with making
these choices, and the ways we are
developing seasonal and habitat-
associated adjustments to our
biocriteria. Some overlap with Lenat
(1988) is inevitable, as both papers
discuss the subject of taxa richness
variability, but a large amount of new
material has been included.
The North Carolina program was
originally set up to deal with
relatively simple between-station and
between-date comparisons; the emphasis
was on showing large changes in water
quality or habitat quality. As the
water quality program expanded, we
began to look at more subtle water
quality problems. Monitoring was
required for all stream sizes (from
temporary streams to large rivers) and
we were asked to make collections
during all months of the year and
under a variety of flow conditions. To
deal with these complicating factors,
we are examining "normal" changes in
the benthic macroinvertebrate
community associated with differences
in habitat, stream size, and
seasonality.
North Carolina originally used
quantitative collections (kick-net
samples) to evaluate the benthic
macroinvertebrate community. All
samples were laboriously sorted in the
lab. As our monitoring requirements
expanded, we developed several new
collection methods to collect reliable
information in a more cost-efficient
manner, including a new "rapid
bioassessment" technique.
19
-------
Lenat
Much of the data presented in this
paper is still in a preliminary stage
of analysis, as North Carolina has
just completed a four month effort to
put all information (1983-present)
into a large computerized data base.
We have been using this data set to
look at the spatial, temporal prefer-
ences of each taxa, as well as
generating pollution tolerance data.
We would like to use this paper as a
means of soliciting opinions and
advice concerning these analysis
methods from other biomonitoring
groups.
Results »cnA Discussion
Collection and Identification Choices
The first step in reducing variability
is to apply common-sense during sample
collection. Stations should be chosen
to be similar in habitat
characteristics, and collections
should not be made if high flow will
interfere with collection efficiency.
The collection method also should be
suitable for the habitat being
sampled. For example, dredge samples
are rarely appropriate for shallow,
fast-flowing streams.
There is considerable disagreement
about the appropriate identification
level and/or what groups should be
identified (see Lenat 1988). North
Carolina has chosen to use species or
genus level identifications (where
possible), including the infamous
Chironomidae. It is clear that species
level identifications increase the
efficiency of site classifications
(Resh and Unzicker 1975, Furse et al.
1981, Furse et al. 1984, Hilsenhoff
1982, Rosenberg et al. 1986), but with
a cost of added identification time. I
agree with Hilsenhoff (1982) that the
added time required for species
identifications is trivial compared to
collection and sorting time. Many
investigators elect to identify the
Chironomidae to family (or subfamily)
level, even if other groups are
classified at a genus/species level.
While the taxonomy of this group can
be difficult, the information added by
good chironomid data can be valuable
in determining the nature of water
quality problems.
Collection methods should be chosen
which yield reliable data in the most
cost-efficient manner. This choice
will vary depending on the objectives
of the study, especially on the need
for precise estHtnat-iae; of species
abundance. Abundance measurements will
be required for life cycle studies and
production studies, but are
notoriously difficult to obtain. Our
experience in water quality assessment
is that we need a quantitative
estimate of taxa richness and a
qualitative estimate of abundance
values (Rare, Common, Abundant).
These requirements lead to the deri-
vation of our standardized qualita-
tive collection method (Lenat 1988).
All North Carolina collection methods
utilize large composite, multiple-
habitat, samples. The Standard quali-
tative method utilizes 10 samples,
taken with 6 different collection
methods. We have also developed an
Abbreviated ("rapid bioassessment")
collection method, which has become an
important part of North Carolina's
biomonitoring program. The latter
method uses only 4 composite samples
(kick-net, sweep-net, leaf-pack, and
"visuals"), with collection and
identification limited to the EFT
groups. Note that the Abbreviated
collection method produces a sub-
sample of the Standard collection. We
have recently compared Standard and
Abbreviated samples collected inde-
pendently at 30 sites (Larry Eaton,
unpublished data). The 4-sample
collections naturally collect fewer
species than the 10-sample collec-
tions, but results from these two
methods are highly correlated (Figure
1, 1^=0.96), allowing criteria to be
developed for each. High variability
is associated with a smaller sample
size, but this is offset by the larger
number of sites that may be sampled. A
more detailed description of the
Abbreviated method is in preparation.
20
-------
Variability of Macroinvertebrate Data
Standard
Collections
70
60.
50.
30.
20.
10.
0
y = 1.175X - .319, R-squared: .959
Standard Error = 3.6
10 15 20 25 30
Abbreviated Collections
35
40
45
50
Figure 1. EFT taxa richness for standard (10-sairple) collections vs. abbreviated
(4—sample) collections.
Analysis Metrics
The choice of analysis metrics have a
significant effect on the variability
of your data or the reliability of
site ratings. The ideal metric will be
insensitive to normal habitat changes,
but sensitive to changes in water
quality. Many monitoring groups are
trying to increase the confidence in
their water quality evaluations by
using several (relatively independent)
ways of examining the benthic
roacroinvertebrate community. This
latter technique has been borrowed
from the Index of Biotic Integrity
(Karr 1981) used by fisheries
scientists.
Taxa Richness. The North Carolina
methods tend to focus on taxa
richness, especially taxa richness for
the intolerant (EFT = Ephemeroptera +
Plecoptera +• Trichoptera) groups. Many
investigators have shown that taxa
richness (and related parameters) are
more stable than abundance values
(Godfrey 1978, Minshall 1981). Taxa
richness values have been frequently
associated with environmental stress
(especially water quality), but this
parameter is fairly stable in clean
water habitats, even given some
changes in habitat characteristics
and/or flow (Patrick 1975, Bradt and
Wieland 1981, Minshall 1981, Wagner
1984).
Biotic Indices. Another way to reduce
variability is to use metrics which
are (theoretically) independent of
sample size. Diversity indices were
derived with this in mind, but have
proved to be unreliable in many types
of pollution assessment (Godfrey 1978,
Hughes 1978). Biotic indices have
greater promise for water quality
assessment (Hilsenhoff 1982), but
their use in the Southeast has been
hampered by the lack of a good data
base on the environmental tolerances
of benthic macroinvertebrates.
Tolerance values have invariably been
21
-------
Lenat
Table 1. Preliminary information for deriving a North Carolina biotic index from
existing bioclassifications. Mean abundance values vary from 0-10 and
bioclassifications are coded 1-5. Percentile calculations are based on cumulative
abundance values, starting from the Excellent bioclassification.
Bioclassification:
Bioclass #:
Percentile
Intolerant Species
Drunella vrayah
Khithrogenia spp.
Chimarra spp.
Micrasema wataga
Goera spp.
Brachycentrus chelatus
Pteronarcys dorsata
Acroneuria abnormis
0.1
0.2
Facultative Species
Stenonema modestum
Ephemerella catawba gr.
Eurylophella temporalis
Cheumatopsyche spp.
Hydropsyche venularis
Perlesta spp.
Ancyronyx variegata
Polypedilum convictum
Tolerant Species
Cricotopus bicinctus
C. tremulus gr
(C/0 sp. 5)
Ghironouius spp.
Polypedilum illinoense
Physella spp.
Argia spp.
Linmodrilus
hoffmeisteri
Asellus spp.
3.6
1.7
Mean Abundance Values
Poor Fair
1.0 2.0
Good- Good
Fair
3.0 4.0
0.3
0.1
0.1
0.6
2.2
1.3
0.1
1.2
0.8
0.3
2.3
0.
0.
2.
0.
0,
0,
0,
0.8
0.8
0.6
0.5
Excellent
5.0
Bioclass #
Mean Percentiles Converted1
75th 90th 75th
0.3
0.8
3.8
1.0
0.6
0.1
0.7
5.4 8.0
1.5
0.7
0.1
3.0
0.7
0.1
0.9
0.5
7.0
0.7
0.4
7.3
1.9
1.0
2.1
1.6
8.4
0.9
0.9
7.7
3.4
1.4
2.2
2.8
7.8
1.7
1.3
7.0
2.5
1.6
1.5
2.0
8.3
3.0
1.3
7.4
2.7
1.4
0.9
1.8
3.6 3.3 3.2 2.0 1.1
1.4
3.8
4.3
3.4
3.1
1.2
2.2
3.4
2.7
3.4
1.1
1.5
3.3
2.3
2.7
0.7
0.9
2.3
1.8
1.9
0.4
0.5
1.7
1.1
1.8
0.6
0.3
4.5
4.5
4.2
3.9
4.5
4.5
4.0
4.2
4.6
5.0
4.2
3.7
4.8
4.5
4.1
4.2
4.3
4.0
3.0
3.2
4.3
4.2
3.3
3.0
0.6
0.0
1.1
1.9
0.3
0.7
1.3
1.1
Means: 4.3 4.4 3.7 0.6
3.5
3.9
3.8
3.4
3.5
3.6
3.1
3.4
3.0
3.4
3.5
2.7
3.1
3.2
2.5
3.0
2.2
2.0
2.7
2.0
1.9
2.4
1.8
2.0
2.9
2.3
2.1
3.3
3.0
3.1
3.6
2.9
Means: 3.5 3.1 2.2 2.9
2.8 1.9 1.4 4.4
2.7
2.4
2.9
2.8
2.9
2.3
2.5
1.8
1.6
1.9
1.8
2.0
1.5
1.7
1.2
1.2
1.3
1.3
1.4
1.2
1.2
4.6
4.9
4.4
4.6
4.3
5.0
4.7
Means: 2.6 1.8 1.3 4.6
1 Numbers "flipped" so that a higher value reflects greater pollution tolerance: x = 6-y,
range expanded (with regression equation) to a 0-5 scale: tolerance value = 1.43x - 1.43.
Converted numbers are comparable to a Hilsenhoff-type index.
22
-------
Variability of Macroinvertebrate Data
assigned based on best professional
judgement, as was the case for North
Carolina's existing biotic index.
North Carolina has initiated a program
to more systematically derive inverte-
brate tolerance values, using our
existing computerized data base. This
data base currently has 130CH- indivi-
dual collections, including samples
from a broad range of water quality
classifications, ecoregions, stream
sizes and seasons. Table 1 presents
some very preliminary data from our
efforts to derive tolerance values. I
present this information here in an
effort to solicit comments and sugges-
tions from readers, the final form of
our biotic index may vary substantial-
ly from the concept presented here.
The initial step was to combine
information on bioclassifications
(based on EPT taxa richness), with
abundance (0=Absent, l=Rare, 3=Common,
10=Abundant) and frequency data. The
first set of numbers in Table 1 are
average abundance values (0-10) for
each water quality class. The summary
values are based on the water quality
class (1-5), with a mean, 75th
percentile and 90th percentile.
Percentiles are based on the
cumulative frequency distribution,
starting from Excellent water quality
(Class #5). Ideally, the tolerance
values should show a large separation
of tolerant and intolerant taxa, while
still producing intermediate values
for facultative taxa (near the median
bioclass # of 3.0). The 75th
percentile number was chosen as the
summary statistic closest to these
ideal characteristics, and was
converted to a Hilsenhoff-type biotic
index. The numbers were "flipped" so
that a higher number reflects greater
pollution tolerance. This produced a
range of values similar to a
Hilsenhoff index, but with a range of
only 1.0 to 4.5. A simple regression
equation was used to expand this range
to 0-5, with the resulting numbers
directly comparable to Hilsenhof f-type
indices. If there is insufficient data
to derive a tolerance value for some
species, the original value (based on
best professional judgement) can be
retained. This approach to deriving a
biotic index seems to show great
promise as an alternate method of
bioassessment. The next step would be
to derive index criteria for both
Standard and Abbreviated samples.
Collector Effects
Several investigators have examined
the effect of the collector on the
variability of benthic invertebrate
data (Chutter and Noble 1966, Pollard
1981, Furse et al. 1981, Lenat 1988).
While some differences can be found,
most studies agree with Egglishaw
(1964) that collector effects are "not
large". The type of differences noted
by Furse et al. (1981) argue strongly
for standardization of collection
methods.
Habitat Effects
Between-site and between-sample dif-
ferences in habitat often contribute
to data variability. If these differ-
ences are large, it may negate any
attempt to look for changes in water
quality. In many cases, the investi-
gator can limit habitat differences,
but these problems may be unavoidable
for basin^wide surveys. Habitat dif-
ferences can be considered for three
distinct size scales: ecoregion,
stream reach, and microhabitat.
Ecoreaion. Ecoregion is rapidly
becoming one of the roost significant
buzz-words of the 1990's. No govern-
ment document can be released without
at least one reference to the need for
ecoregion reference sites. The
ecoregion concept suggests that
streams within a relatively uniform
geographic areas will have similar
faunas, or at least similar community
structure (Hughes and Larsen 1988).
This concept has been most fully
developed for fish communities, but
has also been shown to be applicable
to stream invertebrates (State of
Arkansas 1987, Lenat 1988). North
Carolina has utilized three broad eco-
23
-------
Lenat
48.
46.
44.
42
40
38
36
34
32
30
2 4 6 8 10 12
Width
A. EPT Taxa richness vs. Width
14
16 18 20 22
48.
46.
44.
42.
40.
38
36
34
32
30.
.5 1 1.5 2 2.5
Ln Width
B. EPT taxa richness vs. the natural logarithm of width
3.5
Figure 2. EFT taxa richness (abbreviated samples) vs stream width (m)
Cataloochee Creek catchment. January 1990.
regions to develop bioclassif ication
procedures, but there may be up to 12
different ecoregions in our state.
Preliminary work indicates that at
least 7 ecoregions will be needed to
establish reliable site classifica-
tions, requiring up to 7 different
sets of biocriteria. Seine important
factors in determining ecoregion
include elevation/slope, soil type and
permeability, geology, vegetation, and
land use.
Stream Reach. At the next size scale,
one must consider variability between
stream reaches, especially in regard
to stream size. Several studies have
looked at the changes in the inverte-
brate community in relation to stream
size, usually indicating an increase
in taxa richness from first to fifth
order streams, with a decline in
higher order streams. Such studies
usually look at average values per
sample, rather than looking at changes
in the entire stream community
(Minshall et al. 1985 and Naiman et
al. 1987). It is possible that a part
of the decline in higher order streams
is related to the smaller proportion
of the stream that single (usually
midstream) collections will sample in
larger rivers. Gaschignard et al.
(1983) found that the river fauna
could be separated into two units: a
mid-channel community, and a
community found within 10 meters of
the bank. In small streams, midchan-
nel samples will include both assemb-
lages. As stream size increases,
however, there is a decreased
probability that the bank assemblage
24
-------
Variability of Macroinvertebrate Data
will be included in single-habitat
samples. Multiple-habitat samples may
eventually produce a slightly
different picture of stream size
versus taxa richness.
All investigators agree that lower
taxa richness is expected in small
stream. This point is illustrated in
Figure 2, showing a sharp drop in taxa
richness in comparing a site 1.5
meters in width with a site 4.5 meters
in width, Tfexa richness vs. the
natural logarithm of width (in this
example) showed an almost linear
relationship. Most biological criteria
are derived from larger streams and
rivers; a logical refinement would be
to make some adjustment for different
size classes.
The problem of classifying streams
with taxa richness values is greatest
for very small streams. These streams
will have more limited habitat
complexity, but the most important
cause of reduced taxa richness in
these systems is the periodic stress
caused by drought/low flow conditions.
Droughts may cause drastic reductions
in current speed, often with an
accompanying reduction in dissolved
oxygen; some streams may dry up
entirely.
What constitutes a "small stream" in
North Carolina will vary with soil
permeability. In well-drained soils
(Sandhills ecoregion), permanent flow
occurs in some streams less than one
meter wide. In poorly drained soils,
however, (Slate Belt Ecoregion)
streams up to 15 meters wide may
become temporary during extended
droughts. In evaluating very small
streams, it is important to evaluate
prior flow/rainfall records.
Small pristine mountain streams also
have been found to have reduced taxa
richness and North Carolina is in the
process of deriving special criteria
for these areas. Preliminary analysis
indicated that these criteria should
be applied only to mountain streams
with the following physical
characteristics:
1. First or second order stream
2. Average width <4 meters
3. Largely closed canopy (70-100%)
4. No abundant Aufwuchs growths
Given these characteristics, we would
define areas with an Excellent
bioclassification based on EFT taxa
richness (>27 for Abbreviated samples,
>30 for Standard samples), ratio of
EFT S/Total S (>0.5), Few Odonata,
Coleqptera and Mollusca (<10% of total
taxa richness), a biotic index value
(still being derived) and the presence
of species characteristic of small
streams. A list of "small stream" taxa
also is currently being developed from
our data base. All of the above
classification criteria are in review,
and some minor changes are expected.
Microhabitat. Examination of
individual samples has often indicated
species with a "clumped" spatial
distribution. This problem can be
overcame by the use of larger samples,
especially composite samples. This is
the strategy implicit in "traveling
kicks", many types of D-frame or pond-
net collections, and North Carolina's
composite collections. Our multiple-
habitat semi-quantitative sampling
should help to reduce microhabitat
variations.
Jenkins et al. (1984) recommended
sampling at least three habitats to
adequately inventory the aquatic
fauna, especially in relation to the
"conservation" value of streams.
Brooker (1984) also showed that the
effects of habitat change (channeli-
zation, etc.) were not properly
assessed by riffle-only collections.
Cuff and Coleman (1979) showed that
overall precision was increased by
taking single samples from many
stations, rather than by taking many
replicates at a single site. This
25
-------
Lenat
analysis would seem to support a
multi-habitat sampling design.
Changes with Time
Seasonal Changes. Individual
macrobenthic species are well known to
exhibit marked seasonal changes in
abundance (Hynes 1972). Overall
seasonal changes in community
structure are more difficult to form
generalizations about, but we should
expect considerable between-ecoregion
and between-year differences, largely
due to differences in seasonal
temperature regimes. Spring and/or
fall peaks in taxa richness have been
observed at many of our North Carolina
sites, with the spring peaks being the
most pronounced. Seasonality changes
are not predictable using a "standard"
correction factor for each month.
Different years may have quite
different seasonal patterns,
especially with regard to the onset of
spring generations. We have also found
that greatest seasonal variation
occurs at sites with highest water
quality, i.e., seasonal variation is
reduced at severely polluted sites.
Some .of the "seasonal" change in
slightly impacted streams may reflect
a real change in water quality, not a
change caused by temperature-related
hatching or emergence. The latter is
especially true in agricultural areas,
where there may be a seasonal input of
sediment, nutrients and/or pesticides.
The first step in making seasonal
corrections in taxa richness is some
knowledge of the life cycles of the
invertebrates in each ecoregion (Table
2). Year-round species, or multi-
voltine species with no resting stage,
have little influence on seasonal
changes in taxa richness. However,
many species will be absent for a
portion of the year, sometimes up to 9
months. Often spring peaks in EFT taxa
richness are caused by the addition of
many Plecoptera species. This pattern
is illustrated in Table 3, comparing
EFT taxa richness of single spring
collections with average summer data.
It is apparent from these examples
that a large part of the spring taxa
richness increase was caused by the
appearance of many plecopteran taxa.
In some cases, some adjustment also
must be made for increases in
Ephemeroptera. Simple subtraction of
these species, rather than making the
same proportional adjustment for all
sites, appears to be the most reason-
able means of seasonal adjustment. In
all cases, the seasonal adjustment
must be validated by comparison with
summer data. We have not yet been able
to come up with an adjustment scheme
that does not require such test sites.
The importance of control sites,
especially ecoregion reference sites,
cannot be overemphasized in making
water quality assessments outside of
the usual summer collection periods.
Flow. Some "seasonal" changes do not
reflect normal shifts in populations,
but irregular changes in water quality
or habitat quality, often related to
flow. Given adequate flow information,
it may be possible to predict at least
the direction of changes associated
with floods and/or droughts. Note that
high quality (daily/hourly) flow
information is usually available from
the United States Geological Survey's
monitoring network.
Extreme variation in flow has been
shown to have a catastrophic effect on
the macroinvertebrate fauna of some
streams (Gray 1981). Given some refuge
from scouring, however, the
invertebrate community can withstand
more moderate changes in flow. Data
from both King (1983) and Poole and
Stewart (1976) indicate that the
hyporheic zone may act as a partial
refuge from the effects of elevated
flow. The invertebrate community,
however, seems; to have much of its
variability caused by changes in flow
(Leland et al. 1986, McElravy et al.
1989); some seasonal minima may be
more related to floods than to
emergence (Chutter 1970).
The effects of drought and flood are
often very site-specific, but can be
26
-------
Variability of Macroinvertebrate Data
Table 2. Examples of variations in normal seasonal patterns.1 Numbers are frequency of
collection (0-1) x average abundance value when present (0-10), final values vary from
0-10. Underlining indicates periods of maximum abundance, bold-faced type used to show
minima.
A. Year-round taxa: Multiple species/Univoltine or irultivoltine with no resting stage
123456 7 8 9 10 11 12
Stenonema modestum 6.5 6.6 6.3 5.0 6.8 6.7 8.1 8.2 6.7 8.2 5.0 7.6
Acroneuria abnormis 3.2 2.4 3.3 2.7 2.1 2.0 3.5 4.8 3.6 4.5 2.4 2.4
Stenacrdn
interpunctatum 0.4 0.8 1.5 2.0 3.7 1.2 3.0 3.4 2.0 2.0 1.4 1.3
Isonychia spp. 3.4 1.9 2.7 2.0 3.0 4.3 5.3 6.4 3.3 4.1 2.4 2.3
Hydropsyche sparna 1.9 1.3 3.1 1.2 1.4 1.6 2.3 1/7 1.1 2.0 1.3 1.3
Cheumatopsyche spp. 4.7 4.0 6.0 3.7 7.4 5.7 7.4 8.0 5.5 6.3 4.5 9.8
B. Almost Year-round species, with periods of distinct absence or minima.
123456 7 8 9 10 11 12
Baetisca Carolina 1.1 0.4 0.3 0.6 0.1 0.4 + + 0.3 0.2 0.7 0.8
Caenis spp. + 0.7 0.7 1.6 1.9 2.9 3.5 2.2 1.8 0.6 1.1 0.2
Serratella deficiens 0.3 0.7 0.3 1.2 2.5 0.9 1.6 2.3 0.1 0.3 0.2 0.4
Heptagenia marginalis 0.2 0.1 0.3 + 0.4 0.5 1.6 2.5 1.2 0.6 0.3 +
Eurylcphella temporalis 1.2 1.8 3.4 1.5 3.2 1.0 0.1 0.1 0.2 0.5 0.6 1.5
Neoperla spp. 0.6 0.4 + + 0.8 0.3 0.5 0.1 0.5 1.8 0.3 0.3
Perlesta spp. 0.2 0.8 1.0 3.0 5.4 3.1 1.1 0.4 + 0.1 0.2 0.6
Trianenodes tarda 0.2 0.2 + 0.7 0.4 1.0 1.4 1.0 0.6 1.2 0.1 0.7
Hydroptila spp. 0.2 0.2 0.3 0.6 0.3 0.9 1.1 1.5 0.3 0.2 .0.3 0.6
Hydropsyche roorosa 0.2 + 0.2 0.4 - 0.2 1.0 1.9 0.2 0.3 + 0.4
Fast (Short Life Cycle) Taxa: Univoltine with resting stage.
1
Danella simplex
Drunella allegheniensis -
Serratella serrata
Baetis pluto 0.2
Cinygmula subaequalis -
Drunella walkeri
Aoapetus spp. 0.4
Isoperla namata 1.0
Clioperla clio 1.2
Leptophlebia spp. 2.3
Apatania spp. 4.0
Strophopteryx spp. 5.1
2
+
0.1
1.0
1.7
2.4
0.7
3.7
3
+
0.7
0.9
0.3
3.9
0.3
1.0
0.2
0.9
4
0.8
1.9
1.0
0.4
1.2
0.1
+
5
0.2
1.8
0.1
0.3
0.6
+
0.1
6
•f
+
0.2
1.5
0.3
0.5
0.4
0.1
+
7
0.3
0.3
0.1
1.0
+
+
8
0.9
0.9
0.4
2.0
+
+
0.1
+
9
+
1.8
+
0.2
10
3.5
0.6
1.1
0.3
11
0.7
1.2
2.4
1.5
0.9
12
0.1
0.5
1.5
3.7
2.0
2.6
1Nurabers are derived from North Carolina's computer data base (1983-present, 1300+
collectians), representing a wide range of water quality conditions, ecoregions, seasons,
and stream sizes.
27
-------
Lenat
Table 3. Evaluation of EFT taxa richness, comparing simmer vs.spring collections
in three eooregions of North Carolina.
A. Mountain
French Broad River at Bosnian
Summer Value
Mean (Range)
Spring Value
Ephemeroptera 20.3 (19-23)
Plecoptera 7.0 (6-8)
Trichoptera 17.0 (12-20)
# Uhivoltine Taxa with
(<6 month) Life Cycles
Summer Spring
22 (No change)
14 (+7)
19 (No change)
Total
44.3
B. Upper Piedmont
Mavo River at Price
Ephemeroptera 18.0
Plecoptera 4.5
Trichoptera 16.0
(3-6)
55 (+11)
23 (+5)
13 (+8)
18 (No change?)
Total 38.5
C. Coastal Plain
Plecoptera
Trichoptera
Total
6.5 (5-8)
6.5 (6-7)
16.5 (15-19)
54 (+15)
11 (+4)
12 (+5)
17 (No change)
29.5
40 (+10)
8
0
4
9
0
6
2
0
1
8
11
3
11
8
3
3
7
2
broken down into a series of common
sense questions:
1. Was there a substantial decline in
current velocity that might eliminate
high current species? (especially in
small streams)
2. Was there a change in scour?
(especially for extremely sandy
streams with little or no refuge) Was
there a refuge from scour and was this
refuge included in the samples
collected? Refuges include inter-
stitial habitat (especially clean
rubble/boulder substrate), snags above
the bottom, river weed, etc.
3. Was there a change in dilution of a
point source discharger, especially if
organic loading was a problem? If
there was a significant point source
impact, was there a change in length
of recovery zone? Note that recovery
zones are often shorter under low flow
conditions, but with more acute
effects close to discharge point.
4. Was there a change in the amount of
nonpoint runoff, especially if the
catchment contains land-disturbing
activities?
5. Was there a change in macrophyte
growths or the Aufwuchs population
caused by a change in transparency,
scour, and/or nutrient concentration?
Separating out the possible effects of
changes in flow regimes from real
changes in water quality is the task
of most trend monitoring networks.
28
-------
Variability of Macroinvertebrate Data
o_
LU
o
U-
w
24
23
22
21
20
19
18
17
16
15
14
.83
089
50 60 70 80 9001_1PQ. 110 120 130 140 150
S Fork Flow
A. South Fork Catawba River, 1983-1989
Q_
HI
•D
m
I
a
u.
32
30
28
26
24
22-
20-
18
16
14
20
88
83o
84
40 60
80 100
French Brd Flow
120
140
160
B. French Broad River, 1983-1988
Q.
LU
tr
Q)
26
24
22
20
18
16
14
12'
10
8
6
84
50
100
150
L Little R Flow
200
250
300
C. Lower Little River, 1982-1987
3. Examples of flow (as % of normal) vs. EFT T&xa Richness: South Fork
CatawbaRiverMacAdenville, French Broad River at Marshall and
jv 1 X/JQT* 9 ~
North Carolina has had such a network
in place since 1983, and sanples have
been taken after both draught and
flood conditions. A few exanples have
been drawn from this data base
toillustrate possible carpi icat ions
caused by between-years changes in
flow.
Figure 3 shows flow (as percent of
average flow) for three sites. Two of
these sites (Figure 3A and 3B)
illustrate results from catchments
affected by nonpoint runoff. For both
the French Broad River at Marshall and
the South Fork Catawba River at
McAdenville, there was an inverse
29
-------
Lenat
relationship between flow and EFT taxa
richness. Low flows, especially during
the summers of 1987-1988, were
associated with an increase in EFT
taxa richness, but it is unlikely that
this changes represent a true
long-term change in water quality.
The third site is the lower Little
River at Manchester. There is a
municipal wastewater treatment plant
above this station, with a permitted
flow of 8.0 MGD. During high flow<
years, (1982, 1984) relatively high
EPT taxa richness values were
recorded. low flow years, however,
provided little dilution for the
wastewater discharge, and EPT taxa
richness declined sharply. Changes in
flow probably contribute to the
decline in taxa richness at the Lower
Little River site, although this
information does not preclude the
possibility of an actual decline in
water quality as well.
Sunnary
Many factors affect the variability of
benthic macroinvertebrate data. Much
of this variability can be reduced by
appropriate choices of sample sites,
collection method, identification
level, and analysis techniques.
Variability can also be reduced by
making corrections for predictable
changes associated with habitat
characteristics (ecoregion, stream
size) or the time of the year. In the
absence of specific corrections
methods, analyses should be supported
by a comparison with ecoregion
reference sites. The effects of
changes in flow are less predictable
that habitat associated changes, but
the general trend can be evaluated
based on land use, ecoregion, stream
size and the presence of point source
dischargers.
North Carolina is in the process using
a computerized data base to correct
biocriteria for predictable variation
in taxa richness based on ecoregion,
stream size and seasonal changes.
Collections in very small streams or
during spring months can be expected
require some adjustment before
applying biocriteria. Our data base is
also being used to derive tolerance
values for a Hilsenhoff-type biotic
index.
Acknowledgements
The information, collection methods,
and analysis techniques presented in
this paper are a joint development of
the Bioassessment Group, North
Carolina Division of Environmental
Management. Individuals working on
benthic macroinvertebrate studies
include Dave Penrose, Larry Eaton,
Feme Winborne and Trish MacPherson.
These individuals, however, take no
responsibility for stupid opinions
incautiously advanced by the author.
Literature Cited
Arkansas Department of Pollution
Control and Ecology. 1987. Physical,
chemical and biological characteris-
tics of least-disturbed reference
streams in Arkansas' ecoregions.
Bradt, P.T. and G.E. Wieland. 1981. A
comparison of the benthic
macroinvertebrate communities in a
trout stream: winter and spring 1973
and 1977. Hydrobiologia 77: 31-35.
Brooker, M.P. 1984. Biological
surveillance in Welsh rivers for water
quality and conservation assessment.
pages 25-33 in D. Pascoe and R.W.
Edwards (editors). Freshwater
Biological Monitoring. Permagon Press,
Oxford, England.
Chutter, F.M. 1970. Hydrobiological
studies in the catchment of the Vaal
Dam, South Africa. Part I. River
zonation and the benthic fauna.
Internat Revue ges. Hydrobiol. 55:
445-494.
Chutter, F.M. and R. G. Noble 1966.
The reliability of a method of
sampling stream invertebrates. Archiv
fur Hydrobiologie 62: 95-103.
Cuff, W. and N. Coleman. 1979. Optimal
survey design: lessons from a
30
-------
Variability of Macroinvertebrate Data
stratified random sample of
macrobenthos. Journal Fisheries
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32
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The Use and Variability of the Biotic Tnft*x to Monitor Changes
in an Effluent Stream Following Wasteuater Treatment Plant Upgrades
Jeffrey C. Steven
Madison Metropolitan Sewerage District
1610 Moorland Road
Madison, WI 53713
Stanley W. Szczytko
College of Natural Resources
University of Wisconsin
Stevens Point, WI 54481
Abstract
In 1982 the Madison Metropolitan Sewerage District began an intensive study of
the Nine Springs wastewater treatment plant effluent stream Badfish Creek. The
purpose of this study was to provide baseline data to monitor changes in the
aquatic communities that may have occurred as a result of upgrades in the
wastewater treatment plant that were completed in 1986.
The biotic index was determined for replicates of Kick net (6) and artificial
substrate (3) samples at 4 sites along Badfish Creek at ca. 5 mile intervals from
the headwaters progressing downstream. There was a definite improvement in water
quality ratings at all stations from spring 1983 - spring 1988. Generally all
sampling stations improved at least one water quality rating during this period
and these improvements were probably due to upgrades in the wastewater treatment
plant. There were some differences in spring and fall BI values, however these
differences were not substantial. Artificial substrate samples generally had
lower BI values and water quality ratings than the kick net samples taken at the
same station and time. Approximately 39% of the comparisons of mean BI values of
kick net and artificial substrate samples had different water quality ratings.
Kick net samples were overall slightly more variable (CV = 4.5%) than artificial
substrate samples (CV = 2.7%). The standard deviation of the kick net samples was
0.31 which is comparable to other studies and the standard deviation of the
artificial substrate samples was 0.19.
Introduction
The Madison Metropolitan Sewerage
District (MMSD) began a detailed
aquatic macroinvertebrate study in
1982 on Badfish Creek which is a
receiving stream for the Nine Springs
wastewater treatment plant (Fig. 1).
The purpose of this study was to
provide baseline data to monitor
changes in the aquatic communities
that may have occurred as the result
of upgrades in wastewater treatment,
that were completed in 1986. The
District also anticipated that these
biosurvey data might be an important
tool in future years when examining
necessary permit limits.
The MMSD treats wastewater from the
City of Madison and surrounding com-
munities, comprising ca. a 149 square
mile service area, at the Nine Springs
wastewater treatment plant. The plant
is an activated sludge, advanced
secondary treatment facility. The
plant was upgraded in 1986 to gain
advanced secondary treatment status
which included: in-plant nitrifica-
tion, larger plant size allowing
longer retention time which lowered
suspended solids and biological oxygen
demand in the effluent, a switch from
chlorination to ultraviolet
disinfection, and bank stabilization
(riprap) of three key sections of
Badfish Creek.
Changes in effluent water quality due
to the treatment plant improvements
discussed above have been significant
33
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Steven and Szczytko
NINE SPRINGS WASTEWATER
TREATMENT PLANT
EFFLUENT AND STREAM
MONITORING STATIONS
MONTH
VJ
Figure 1. Biotic index sampling stations on Badf ish Creek, Dane Co., Wisconsin.
and include a decrease in free ammonia
fron 9-15 ppm prior to 1985 to less
than 0.2 ppm after April 1986. Total
suspended solids also decreased
substantially from 10-15 ppn prior to
1986 to ca. 5 ppm after April 1986.
Biological oxygen demand decreased
from 15-20 ppm prior to 1986 to 2-6
ppm after April 1986.
Treated wastewater from the Nine
Springs facility has been discharged
to the headwaters of Badfish Creek
since December 1958. The effluent
travels through an underground
pipeline for ca. 5 miles to where it
surfaces at the headwaters of Badfish
Creek. The plant currently discharges
37 million gallons per day to the
creek, which constitutes about 80% of
the flow in the upper reaches. Inflows
from 4 tributaries (Oregon Branch,
Rutland, Spring and Frog Pond Creeks)
and other surface runoff increases the
flow to ca. 67 million gallons 20
miles downstream near the Yahara
34
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Biotic Index Variability to Monitoring Effluent Upgrades
River. The effluent constitutes ca.
50% of the flow prior to entering the
Yahara River.
Materials and Methods
Four macroinvertebrate sampling sites
were established on Badfish Creek
which were positioned at ca. 5 mile
intervals from the headwaters progres-
sing downstream (Fig. 1). Biotic index
(BI) samples (Hilsenhoff 1982, 1987)
were taken in the spring (April) and
fall (October) from spring 1983-
spring 1988 (1988 fall samples were
not included).
Aquatic macroinvertebrates were
collected with a standard D-f rame kick
net which had a 12 in diameter opening
and a 1 mm mesh bag. Samples were
collected by kicking and disturbing
the substrate upstream from the net
for ca. one minute (Hilsenhoff 1982,
1987). Six kick samples were taken at
each of the 4 sites using stratified
random sampling procedures. One sample
each was taken at the center and to
the right and left of the center of
the creek, 2 samples were taken near
one bank and one sample was taken
along the other bank for a total of 6
replicate kick net samples. After kick
samples were taken they were vigorous-
ly washed in the net to remove fine
sediments. The remaining debris and
organisms were placed in labeled pint
jars and preserved in 95% ethanol.
Artificial substrate samplers, similar
to those described by Beak et al.
(1973) were also used to collect BI
samples. These samplers consisted of a
16 in dia., 1 in deep aluminum pizza
pan with two expanded metal mesh
inserts placed inside the tray one on
top of the other, which served as the
colonization substrates. The tray and
inserts were attached to a cement
anchor block that was placed on the
stream bottom. These trays worked well
because the problems of vandalism and
organic debris build-up were minimized
by their low profile. Three trays were
placed across the creek at each
sampling site. One tray each was
placed at the center and near each
bank at each sampling site 6 weeks
prior to the fall and spring sampling
dates to allow sufficient time for
colonization to occur. A special
retrieval top was used to retrieve the
trays after the 6 week colonization
period. This method ensured minimal
loss of organisms during the retrieval
process. The inserts and trays were
rinsed into a 1 mm mesh soil sieve to
remove fine sediments and retain the
macroinvertebrates. The organisms and
retained debris were then placed in
labeled pint jars and preserved with
95% ethanol.
Aquatic macroinvertebrates were
removed from debris in the laboratory
and the contents of each sample were
placed in a screen and rinsed to
remove the alcohol and remaining fine
sediments. The samples were then
placed in a 10 in X 16 in white enamel
pan and evenly spread over the pan
bottom in water. A plexiglass grid
(1.5 in high) was placed in the pan
which partitioned the sample into 32
squares.
Squares were randomly selected for the
kick net samples and all organisms
were removed from each square until a
total of 150 organisms were removed.
If 150 organisms were removed before a
square was completed the remaining
organisms in the square were also
included. Artificial substrate samples
were also sorted in the enamel pan and
4 squares (ca. 1/8 of the sample) were
randomly selected and all organisms in
each square were picked. The grid
insert was removed after the 4 squares
were picked and the rest of the sample
was sorted. The dominant organisms
(over 30 count in the 4 squares) were
not picked in the remaining sample but
those picked from the 4 squares were
multiplied by 8 to approximate the
total numbers in the sample. All
remaining non-dominant organisms were
picked and counted.
Aquatic macroinvertebrates were
identified to the lowest possible
35
-------
Steven and Szczytko
taxonomic unit. Qiironomidae (Diptera)
were slide mounted with Hoyers
mounting media and allowed to clear to
facilitate identification.
The BI was determined for each sample
(Hilsenhoff 1982, 1987) and a mean BI
was determined for each 6 replicate
set of kick samples and 3 replicate
set of artificial substrate samples.
The BI was originally designed to
'detect problems with low dissolved
oxygen caused by organic loading of
putrescible wastes and it appears to
work well for that purpose (Hilsenhoff
1977, 1982, 1987). It has been widely
used by many state agencies and is the
standard rapid bioassessment measure
used by the WI Dept. of Natural
Resources for water quality
assessments. This index provides water
quality ratings based on a numerical
system of 0-10 with 0 indicating very
good water quality and no organic
pollution and 10 indicating very poor
water quality and severe organic
pollution (Table 1). The coefficient
of variability (CV) and the standard
deviation (STD) of the means were used
to estimate data variability. The CV
and STD were determined for each
replicate set of kick net and
artificial substrate samples for each
sampling period.
Results and Discussion
Generally, BI values decreased and
water quality ratings improved at all
sampling stations from 1984 to 1988
and BI values increased at all
stations from 1983 to 1984 (Table 2;
Figs. 2-5). The roost substantial
improvements in water quality ratings
occurred in the spring of 1985 and
improvements continued through the
spring of 1986 after which ratings for
all stations appeared to stabilize
(Table 3).
Station IB had consistently the
poorest water quality ratings of all
stations (Table 3). This is not
surprising since it has the greatest
percentage of effluent of all stations
and is closest to the MMSD wastewater
treatment plant. Water quality at
station IB improved from very poor in
1983-1984 to fairly poor in the spring
of 1988. Water quality at station 4B
improved from a poor or very poor
rating in 1984 to a fair rating from
fall 1985 to spring 1988. Stations 6B
and 8B improved from a general rating
of fair - fairly poor in 1983-1984 to
a fair - good rating in spring of
1988. Stations 48, 6B and 8B generally
had similar water quality ratings
after spring of 1985 (Table 3). These
improvements in water quality from
1983-1988 are most likely due to the
improvements and upgrades in the MMSD
treatment plant including decreases in
free ammonia, total suspended solids,
and biological oxygen demand, and the
change from chlorination to
ultraviolet light for disinfection.
Fall samples generally had slightly
lower mean BI values (determined from
the replicate sets) than spring
samples. Fifty five percent of the
kick net samples and 65% of the
artificial substrate samples had lower
BI values in the fall than spring
(Table 2; Figs. 6-9), however only 16%
and 18% respectively of the kick net
and artificial substrate sample
comparisons of spring and fall data
had different water quality ratings
(Table 3). The absolute mean differ-
ence between spring and fall kick net
samples was 0.47 ± 0.43 and 0.75 ±
0.77 for artificial substrate samples.
Hilsenhoff (1988) recommended that BI
samples be taken 60 days after the 440
degree day accumulation in warm-water
streams and 45 days after the 1050
degree day accumulation in cold-water
streams. Badfish Creek is classified
as a warm-water stream and the fall
samples were taken at least 45 days
after the 440 degree day accumulation.
Approximately 39% (17) of the 44
comparisons of mean BI values from
replicate sets of artificial substrate
(3 replicates) and kick samples (6
replicates) taken at the same time and
stations had different water quality
classifications. Artificial substrate
36
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Biotic Index Variability to Monitoring Effluent Upgrades
Table l. Water quality classifications for the biotic index (from Hilsenhoff
1987).
BIOTIC INDEX VALUES
WATER QUALITY DEGREE OF ORGANIC
CLASSIFICATION POLLUTION
0.00-3.50
3.51-4.50
4.51-5.50
5.51-6.50
6.51-7.50
7.51-8.50
8.51-10.00
Excellent
Very Good
Good
Fair
Fairly Poor
Poor
Very Poor
No apparent organic pollution
Possible slight organic pollution
Some organic pollution
Fairly significant organic pollution
Significant organic pollution
Very significant organic pollution
Severe organic pollution
10
STATION 1B
9 -
LJJ
CO
7 -
19B3
KICK SAMPLES
ARTIFICIAL SUBSTRATES
1984
1965
1986
1987
1988
Figure 2. Mean BI values of the replicate set of kick net and artificial
substrate samples (spring and fall data combined) from spring 1983 - spring 1988
for sampling station IB from Badfish Creek. Dane Co.. Wisconsin.
37
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Steven and Szczytko
Table 2. Seasonal BI values by year and station (values are means and standard
deviations of the replicate sample sets - 6 samples for kick net and 3 samples
for artificial substrates).
Year/Season
Type of sample
1983/Spring
KS3
AS2
1983/Fall
KS
AS
1984/Spring
KS
AS
1984/Fall
KS
AS
1985/Spring
KS
AS
1985/Fall
KS'
AS
1986/Spring
KS
AS
1986/Fall
KS
AS
1987/Spring
KS
AS
1987/FaIl
KS
AS
1988/Spring
KS
AS
IB
923 ± 032
92S ± 030
8.92 ± 024
9.12 ± 0.12
9.51 ± 022
9.57 ± 032
9.81 ± 0.05
9.82 ± 0.03
8.40 ± 0.90
9.05 ± 021
6.71 ± 0.10
6.62 ± 0.09
7.70 ± 0.62
6.79 ± 030
7.12 ± 0.40
6.52 ± 028
6.61 ± 0.09
622 ± 0.19
6.64 ± 0.14
7.69 ± 025
6.89 ± 0.46
6.91 ± 027
Sampling
46
7.12 ± 0.44
637 ± 031
7.10 ± 0.19
8.03 ± 0.42
7.82 ± 0.83
7.09 ± 037
9.19 ± 0.12
9.73 ± 0.07
6.74 ± 037
632 ± 0.09
6.47 ± 0.02
623 ± 0.10
635 ± 020
5.97 ± 0.09
633 ± 0.14
5.83 ± 020
6301024
6.10 ± 0.02
6.12 ± 032
5.55 ± 0.24
620 ± 032
5.94 ± 0.18
Stations
6B
6.93 + 0.16
6.80 + 0.02
6.84 ±022
7.00 ± 0.10
7.43 ± 022
6.91 ± 0.09
8.42 ± 039
831 ± 0.83
6.69 ± 0.15
6.51 ± 0.41
627 ± 027
637 ± 0.18
6.09 ± 032
6.09 ± 0.13
554 ±023
5.70 ± 0.60
6.40 ± 030
627 ± O.B
5.64 ± 0.18
5.13 ± 0.05
5.79 ± 0.18
5.41 ± 0.11
8B
6.57 + 022
6.47 ± 0.11
6.73 ± 039
6.09 ± 0.07
6^5 ±030
635 ± 0.13
7.15 ± 027
6.46 ± 022
625 ± 0.12
6.10 ± 0.06
6^8 ± 0.60
553 ± 0.12
638 ± 051
5.97 ± 0.16
6.17 ± 0.42
5.44 + 0.17
6.16 ± 0.09
6.11 ± 0.07
5.72 + 036
5.16 + 0.06
5.98 ± 038
5.89 ± 022
1 Kick net samples
2 Artificial substrate samples
38
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Biotic Index Variability to Monitoring Effluent Upgrades
Table 3. Seasonal water quality ratings by year and station (water quality
ratings from Hilsenhoff 1987) .
Year/Season
Type of sample
1983/Spring
KS1
AS2
1983/Fall
KS
AS
1984/Spring
KS
AS
1984/FaIl
KS
AS
1985/Spring
KS
AS
1985/Fall
KS
AS
1986/Spring
KS
AS
1986/Fall
KS
AS
1987/Spring
KS
AS
1987/Fall
KS
AS
1988/Spring
KS
AS
IB
Very Poor
Very Poor
Very Poor
Very Poor
Very Poor
Very Poor
Very Poor
Very Poor
Poor*
Very Poor
Fairly Poor
Fairly Poor**
Poor
Fairly Poor
Fairly Poor
Fairly Poor**
Fairly Poor**
Fair
Fairly Poor**
Poor**
Fairly Poor
Fairly Poor
Sampling
4B
Fairly Poor
Fair*
Fairly Poor
Poor
Poor
Fairly Poor
Very Poor
Very Poor
Fairly Poor
Fair*
Fair*
Fair
Fair*
Fair
Fair*
Fair
Fair*
Fair
Fair
Fair**
Fair
Fair
Stations
6B
Fairly Poor
Fairly Poor
*
Fairly Poor
Fairly Poor
Fairly Poor*
Fairly Poor
Poor*
Poor*
Fairly Poor**
Fairly Poor*
Fair
Fair**
Fair
Fair
Fair**
Fair**
Fair*
Fair
Fair**
Good
Fair
Good*
SB
Fairly Poor**
Fair*
Fairly Poor
Fair
Fairly Poor**
Fair*
Fairly Poor
Fair*
Fair
Fair
Fairly Poor**
Fair
Fair
Fair
Fair*
Good*
Fair
Fair
Fair
Good
Fair
Fair
Kick net samples
7 Artificial substrate samples
* Ratings which missed the next poorer water quality rating by 0.20 BI units
** Ratings which missed the next better water quality rating by 0.20 BI units
39
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Steven and Szczytko
STATION 4B
8 -
LU
ID
I7
CD
6 -
KICK SAMPLES
ARTIFICIAL SUBSTRATES
1983
1964
1985
1986
1967
1988
Figure 3. Mean BI values of the replicate sets of kick and artificial substrate
sanples (spring and fall data combined) from spring 1983 - spring 1988 for
sampling station 4B from Badfish Creek. Dane Co.. Wisconsin.
STATION 6B
7.5 -
7 -
LU
< 6.5 -
m
6 -
5.5 -
KICK SAMPLES
ARTIFICIAL SUBSTRATES
1983
1984
1985
1986
1987
1988
Figure 4. Mean BI values of the replicate sets of kick and artificial substrate
samples (spring and fall data combined) from spring 1983 - spring 1988 for
sampling station 6B from Badfish Creek. Dane Co.. Wisconsin.
40
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Biotic Index Variability to Monitoring Effluent Upgrades
6.5 -
LU
m
5.5 -
STATION 8B
1983
1984
1985
1986
1987
1988
Figure 5. Mean BI values of the replicate sets of kick and artificial substrate
samples (spring and fall data combined) from spring 1983 - spring 1988 for
sampling station 8B from Badfish Creek. Dane Oo.. Wisconsin.
10
UJ
m
9 -
8H
7 -
STATION 1B
SPRING
ARTIFICIAL SUBSTRATE
FALL
ARTIFICIAL SUBSTRATE
1983
1984
1985
1986
1987
Figure 6. Mean BI values of the replicate sets of kick and artificial substrate
samples for spring and fall from spring 1983 - spring 1988 for sampling station
IB from Badfish Creek. Dane Oo.. Wisconsin.
41
-------
Steven and Szczytko
STATION 4B
10
9 -
LU 8 -
D
CP 7 -
6 -
SPRING
KICK SAMPLES
FALL
KICK SAMPLES
SPRING
ARTIFICIAL SUBSTRATE
FALL
ARTIFICIAL SUBSTRATE
1983
1984
1865
1986
1987
Figure 7. Mean HI values of the replicate sets of kick and artificial substrate
sanples for spring and fall from spring 1983 - spring 1988 for sampling station
4B from Badfish Creek, tene Oo., Wisconsin^
STATION 6B
LU
CD
6 -
SPRING
KICK SAMPLES
FALL
KICK SAMPLES
SPRING
ARTIFICIAL SUBSTRATE
FALL
ARTIFICIAL SUBSTRATE
1983
1984
1985
1988
1987
Figure 8. Mean El values of the replicate sets of kick and artificial substrate
sanples for spring and fall from spring 1983 - spring 1988 for sampling station
6B from Badfish Creek. Dane Oo.. Wisconsin.
42
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Biotic Index Variability to Monitoring Effluent Upgrades
STATION 8B
LJJ
CO
7.5 -
7 -
6.5 -
5.5 -
1983
FALL
KICK SAMPLES
SPRING
ARTIFICIAL SUBSTRATE
FALL
ARTIFICIAL SUBSTRATE
1984
1985
1986
1987
Figure 9. Mean EL values of the replicate sets of kick and artificial substrate
sanples for spring and fall from spring 1983 - spring 1988 for sampling station
8B from Badfish Creek. Dane Oo.. Wisconsin.
>4
O
<3
UJ
KICK
ARTIF.
1
I
I
1
1983
1984
1985
1986
1987
1988
Figure 10. Annual mean coefficient of variation (C7) of the replication sets of
kick net and artificial substrate samples (spring and fall and all station data
combined) from spring 1983 - spring 1988 from Badfish Creek. Dane Co.. Wisconsin.
43
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Steven and Szczytko
8
2 -
1 -
SPRING
FALL
i
y,
/\
1983
1984
1985
1986
1987
1988
Figure 11. Seasonal mean ooefficient of variation (CV) of kick net samples from
spring 1983 - spring 1988 from Badfish Creek. Dane Co.. Wisnpnsin.
O
I3
0 SPRING £vjj FALL
x -.'•'tan
j
1
i
I
1983
1984
1985
1986
1987
1988
Figure 12. Seasonal mean coefficient of variation (CV) of artificial substrate
samples from sprmg 1983 - spring 1988 from Badfish Creek. Dane Co.. Wisconsin.
44
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Biotic Index Variability to Monitoring Effluent Upgrades
5 -
s3
KICK SAMPLES [53 ART1RCIAL SUBSTRATE
1B
4B 6B
SAMPLING STATIONS
8B
Figure 13. Mean coefficient of variation (CV) of the replicate sets of kick net
and artificial substrate samples for each station (annual and seasonal data
combined) from Badfish Creek. Dane Co.. Wisconsin. .—
samples had a one range cleaner water
quality classification than the kick
samples in 15 of the 17 conparisons
that were different. Only 2 of artifi-
cial substrate samples provide a
poorer (one range) water quality
rating than the kick samples (Table 3 ;
Figs. 2-9). The absolute mean
difference between the means of the BI
determined from the replicate sample
sets for kick net and artificial
substrate samples taken at the same
times and stations was 0.37 ± 0.29.
The overall variability of the kick
samples (mean CV = 4.5%) was greater
than the artificial substrate samples
(mean CV = 2.7%) based on comparisons
of the means of 6 and 3 replicate sets
for kick and artificial substrate
samples respectively from spring 1983-
spring 1988 (Fig. 10). This slight
difference in variability may have
been due to the different number of
replicates taken for artificial
substrate and kick net samples, or to
differences inherent in the types of
samplers. The overall standard
deviation of 6 replicate sets of kick
samples was 0.31 which is comparable
to values of 0.24 and 0.28 reported by
Hilsenhoff (1988) and Szczytko (1988)
respectively for biotic index samples.
The overall standard deviation of the
artificial substrate samples was 0.19.
The variability of biotic index values
of replicate sample sets combined fron
1983-1988 was slightly lower in the
fall (CV = 4.10%) than spring (CV =
4.83%) for kick samples and greater in
the fall (CV = 3.17%) than spring (CV
= 2.62%) for artificial substrate
samples (Figs. 11 & 12). These differ-
ences are small and were probably
related to sampling and sorting tech-
niques or to the heterogeneous distri-
bution of the macroinvertebrates.
The CV among replicate sample sets was
variable from 1983-1988 for both kick
net and artificial substrate sanples
and no annual trends were apparent
(Fig. 10). The CV ranged from 3.84-
5.41% for kick samples and fron 2.06-
3.97% for artificial substrate samples
during the course of this study.
Sampling station 8 had the lowest
45
-------
Steven and Szczytko
combined (all years and seasonal data
combined) variability (CV = 2.1%) for
artificial substrate samples and
station 6 had the lowest variability
(CV = 3.7%) for kick samples (Fig.
13). There were no obvious trends in
variability related to the sampling
stations in this study.
Conclusions
There was a definite improvement in
water quality ratings determined > from
BI values in Bq^flgh Creek from spring
1983- spring 1988. Basically all sam-
pling stations improved at least one
water quality rating better during the
course of this study. These improve-
ments were most likely related to
upgrades in the wastewater treatment
plant discussed above and the water
quality ratings observed in the spring
of 1988 are probably the water quality
ratings which will continue in the
future. Station IB had the lowest
water quality ratings of all stations
and station 4B, 6B and 8B had similar
ratings by the end of this study.
Generally there were some differences
in fall and spring BI values, however
we do not view these differences as
substantial since part of the varia-
bility can be explained by the stand-
ard deviation of the means. Also only
16% of the kick net and 23% of the
artificial substrate sample ocnpari-
sons between spring and fall had
different water quality ratings and
many of the water quality ratings that
were different missed the water qual-
ity rating of the other season by only
0.20 BI units or less (Table 3).
Artificial substrate samples generally
had lower BI values and water quality
ratings than the kick net samples
taken at the same time and sampling
station. These differences were
probably related to the different
types of samplers and sorting
techniques used. In many cases water
quality ratings from kick or
artificial substrate samplers missed
the water quality rating of the other
type of sampler by only 0.20 BI units
or less (Table 3).
Kick net samples were slightly more
variable than artificial substrate
samples (mean CV determined from the
sets of replicate samples). These
differences invariability (1.8%) were
small and were probably related to
sampling and sorting techniques. The
overall standard deviation of the kick
net samples were comparable to other
studies. The variability of BI samples
is lower than most other benthic
community metrics currently used for
water quality assessment (Szczytko
1988).
Literature Cited
Beak, T. W., Griff ing, T. C. and A. G.
Appleby. 1973. Use of artificial
substrate samplers to assess water
pollution. In Biological Methods for
the Assessment of Water Quality. ASTM
STP 528, American Society for Testing
and Materials, pp. 227-241.
Hilsenhoff, W. L. 1977. Use of
arthropods to evaluate water quality
of streams. Tech. Bull. WI. Dept. Nat.
Resour. No. 100 15pp.
Hilsenhoff, W. L. 1982. Using a biotic
index to evaluate water quality in
streams. Tech. Bull. WI. Dept. Nat.
Resour. No. 132 22pp.
Hilsenhoff, W. L. 1987. An improved
biotic index of organic stream pol-
lution. Great Lakes Entomol. 20:31-39.
Hilsenhoff, W. L. 1988. Seasonal
correction factors for the biotic
index. Great lakes Entorool. 21:9-13.
Szczytko, S. W. 1989. Variability of
commonly used macroinvertebrate
community metrics for assessing
biomonitoring data and water quality
in Wisconsin streams. In W.S. Davis
and T.P. Simon (eds). Proceedings of
the 1989 Midwest Pollution Control
Biologists Meeting, Chicago, IL. USEPA
Region V, Instream Biocriteria and
Ecological Assessment Committee,
Chicago, IL. EPA 905/9-89/007.
46
-------
Data Variability in Arthropod Samples
Used for the Biotic Index1
William L. Hilserihoff
Department of Entomology
University of Wisconsin
Madison, WI 53706
Abstract
Factors that influence the reliability of the biotic index (BI) for evaluating
the water quality of streams include sample size, substrate sampled, current,
method of processing samples, water temperature, time of the year, and level of
arthropod identification. Comparison of standard deviations of sample sizes of
50, 100, 150, and 200 indicated that a sample of 100 was adequate for most
evaluations. By sampling only riffles*, differences in substrate and current were
minimized, and differences between riffles in the same stream were not
substantial enough (SD=0.25) to alter evaluations made with the BI. Biases were
found in samples picked in the laboratory as well as in those picked in the
field, but these biases had little effect on the BI. By processing samples in the
laboratory more valuable field time is made available. The greatest variability
in BI evaluations resulted from seasonal differences in the fauna, with index
values being abnormally high in late spring or summer. Much time can be saved by
evaluating streams with a family-level biotic index, but precision is lost and
the ability to discriminate between various levels of pollution is deminished.
Key Words: Biotic index, Water quality, Pollution, Arthropods, Insects, Data
variability, Sampling, Sample bias, Streams
Introduction
In 1977 I recommended using a biotic
index (BI) of the arthropod fauna to
evaluate the water quality of streams.
This index was based on a sample of
100 or more arthropods that were
collected with a net from the riffle
area of a stream (Hilsenhoff 1977).
Species (or genera when species could
not be identified) of stream arthro-
pods were assigned tolerance values of
0 to 5, depending on their tolerance
to organic pollution, with the most
tolerant organisms having a value of
five. The BI is the average of toler-
ance values for all species of arthro-
pods in a sample. After five years
tolerance values were revised and
several studies relating to sampling
procedure and data variability were
completed (Hilsenhoff 1982). More
recently data from more than 2,000
stream sites were used to further
revise tolerance values and a 0 to 10
scale was introduced to increase
precision (Hilsenhoff 1987). since
tolerance values of 0 to 10 are as-
signed to each species there are only
11 categories of arthropods that are
use to calculate a BI. This results in
less data variability than when
several dozen different species are
available for collection. A discussion
of important factors that introduce
variability into the BI follows.
Sample Size
Kaesler and Herricks (1976) found that
a sample size of 100 was adequate for
evaluation of stream samples with a
diversity index. Two sets of six
samples of 50 arthropods from Arm-
strong Creek, Wisconsin were combined
in all possible ways to produce three
replicated samples of 50, 100, 150,
and 200 arthropods (Hilsenhoff 1982).
As sample size was increased, standard
deviations decreased (Table 1), but
when evaluating streams with the BI
the gain in precision from a sample of
more than one-hundred probably does
not justify the extra time needed to
Research supported by the College of Agricultural and life
Sciences, University of Wisconsin-Madison, and by Hatch Research
Project 2785
-------
Hilsenhoff
Table l. Standard deviations of biotic
index values in relation to sample
size from two sets of six samples of
50 arthropods, combined in all pos-
sible ways to produce samples of 100,
150 and 200. Samples were collected
from the same riffle in Armstrong
Creek; one set was one picked in the
field and the other was picked in the
laboratory.
*
Sample Standard Deviation
Size Number Field—Picked tab—picked
50 6 0.213 0.347
100 15 0.124 0.205
150 20 0.085 0.146
200 15 0.062 0.103
collect and process a larger sample.
If greater precision is desired,
replicated samples are recommended.
Sampling Site Differences
Three different riffles in each of six
streams were sampled at two-^week
intervals from April through November
in 1984 and 1985 (Hilsenhoff 1988a).
Ihe standard deviation of 32 sets of 3
samples from each stream was 0.25 and
the 95% confidence limits were +0.48
(Table 2).
Table 2. Standard deviations (SD) and
confidence limits of biotic index (BI)
values of samples collected from three
different riffles in each of 6 streams
on 32 dates over a two-year period.
Confidence Limit"?1
Stream
Otter Creek
Trout Creek
Sugar River
Pecatonica R.
Narrows Creek
Badf ish Creek
Average
BI
2
2
4
5
6
6
4
•
•
•
•
•
•
•
24
29
91
48
08
46
58
SD
0.
0.
0.
0.
0.
0.
0.
,26
,33
,26
,25
,20
,14
.25
95%
+0
+0
+0
+0
+0
+0
+0
•
•
•
•
•
•
•
50
65
50
49
38
28
48
99%
+0.67
+0.85
+0.67
+0.64
+0.52
+0.36
+0.63
Differences in substrate and current
are most likely to affect the fauna;
areas with slow currents, especially,
tend to be inhabited by insects that
are more tolerant of low dissolved
oxygen levels and organic pollution.
When the BI of three riffles in each
of six streams was compared
(Hilsenhoff 1988a), significant
differences were found in four of the
streams (Table 3), but these differ-
ences were not great enough to sub-
stantially alter the evaluation of any
stream. Differences did not appear to
be related to current since the riffle
with the slowest current had the high-
est BI value in two of the streams and
the lowest in the other two. Most
riffles have currents in excess of O.5
m/sec, which is sufficiently fast so
that arthropods will not be stressed
in well-oxygenated water. Variability
of substrate was most likely responsi-
ble for significant differences in the
BI of samples from some streams.
Bias in Sample Picking
When arthropods are picked from a
sample there is always a distinct bias
that favors certain species. In a set
of 12 samples from the same riffle in
Armstrong Creek that were alternately
picked in the field or preserved and
picked in the laboratory (Hilsenhoff
1982) distinct biases in picking were
obvious (Table 4); at the time the
samples were picked I believed that
almost every arthropod had been
removed from each sample. Active
arthropods tend to be preferentially
picked in field samples, and if
cryptically colored they are difficult
to find among the debris in preserved
samples. Inactive, cryptically-colored
arthropods are. difficult to see in
field samples, but many change color
when preserved in alcohol and are easy
to find in the laboratory. larvae of
Optioservus (Elmidae) are an excellent
example. When preserved in alcohol
they often become distended, exposing
white intersegmental membranes that
are easily seen. Fortunately these
biases usually do not have much effect
the BI. In a study of five streams in
which alternate samples from the same
riffle were picked in the field or in
the laboratory (Hilsenhoff 1982) only
48
-------
Biotic Index Variability
Table 3. Analysis of variance of biotic index values of arthropod samples from
three riffles with varying currents at low flow in six Wisconsin streams.
Samples were collected at 2-week intervals from 18 September to 13 November 1985.
(Reproduced with permission from the Great Lakes Entomologist.)
Stream
Otter Creek
Trout Creek
Sugar River
Pecatonica River
Badf ish Creek
Narrows Creek
Current m/sec
123
0.42
0.87
0.47
0.68
0.48
0.81
0.53
0.81
0.38
0.61
0.64
0.81
0.75
0.59
0.56
0.65
0.66
0.71
Mean
1
2.
3.
5.
5.
7.
7.
08
83
27
41
11
85
Biotic
2
1.
3.
5.
5.
6.
7.
83
33
62
92
87
41
Index
3
2.06
2.73
5.19
5.82
7.08
7.13
SD
0.27
0.46
0.24
0.16
0.17
0.32
F
1.
7.
4.
14
3.
6.
37
23*
49*
.68**
12
36*
* P = 0.05 ** P = 0.01
Table 4. The amount of bias in laboratory- and field-picked samples.
Number of ArthroDods
Family or Order
Perlidae
Baetidae
Ephemerellidae
Heptageniidae
Other Ephemeroptera
Odonata
Brachyoentridae
Glossosomatidae
Hydropsychidae
(Tnrvrta 1 i tia*»
^-^-'^j n • •fcnrin '^
Elmidae adults
Elmidae larvae
Athericidae
Chironomidae
Simuliidae
Tipulidae
Gammaridae
Asellidae
Tah8
96
173
65
40
38
12
31
54
245
38
38
264
37
93
46
51
54
200
Field
142
176
65
57
38
14
94
12
358
35
84
36
48
73
54
28
61
202
Differenceb
+46
+3
0
+17
0
+2
+63
-42
"+113
-3
+46
-228
+11
-20
+8
-23
+7
+2
Bias6
Ratio
+1.48
+1.02
1.00
+1.43
1.00
+1.17
+3.03
-4.50
+1.46
-1.09
+2.21
-7.33
+1.30
-1.27
+1.17
-1.82
+1.13
+1.01
Bias
Rank
6(+)
.«
3(+)
l(-)
10(-)
5(~)
a Adjusted so that laboratory-picked totals equal field-picked totals.
b Laboratory-picked sample subtracted from field-picked sample.
c Bias ratio is a ratio of the largest number to the smallest.
in the Mecan River was there a most numerous in field-picked samples.
significant difference in the BI The BI varies most in very clean
(Table 5). Here Optioservus larvae streams (Tables 2, 6), but since all
(tolerance value of 4) predominated in values below 3.5 are considered to
laboratory-picked samples, while the represent "excellent" water quality
active but cryptically colored (Hilsenhoff 1987), these variations in
Brachycentrus americanus. B. the BI of clean streams are not
occidentalis. and Ceratopsyche sparna important. Preserving samples and
(all with a tolerance value of 1) were processing them in laboratory is
49
-------
Hilsenhoff
Table 5. Comparison of differences (t-test) between means of biotic index values
of replicated field-picked and laboratory-picked samples from five streams. SD
= standard deviation from the mean.
Mean Biotic Index
Stream
Field
Lab.
df
SD
Armstrong Creek
Radfiah Creek
Mecan River
Milancthon Creek
Poplar River
2.22
7.16
2.01
3.71
5.01
2.08
7.22
3.15
3.80
5.08
10
4
4
4
4
0.84
0.15
14.51**
0.28
1.76
0.29
0.50
0.09
0.40
0.15
** P = 0.01
Table 6. Comparison of differences (t-test) between means of the biotic index
(BI) and the family-level biotic index (FBI) of three replicate samples from six
streams in mid-April, late-June, early-September and mid-November in 1984 and
1985. SD = standard deviation from the mean. (Reproduced with permission from the
Journal of the North American Benthological Society.)
Stream
Otter Creek
Trout Creek
Sugar River
Pecatonica River
Narrows Creek
Badf ish Creek
All samples
* P = 0.05 **
Year
1984
1985
1984
1985
1984
1985
1984
1985
1984
1985
1984
1985
P = 0.01
BI
2.43
2.62
2.23
2.61
5.49
5.44
6.31
5.81
6.68
6.36
7.05
6.77
Mean
FBI
2.77
3.27
2.52
3.18
5.13
4.83
6.31
5.76
6.15
5.83
6.71
6.24
SD
t
4.65**
4.90**
4.41**
4.84**
7.28**
8.73**
0.06
0.34
6.67**
10.76**
2.20*
6.08**
BI
0.22
0.27
0.45
0.35
0.28
0.23
0.19
0.20
0.20
0.18
0.17
0.15
0..24
FBI
0.30
0.37
0.54
0.39
0.33
0.28
0.21
0.23
0.34
0.20
0.30
0.36
0.32
recommended because much valuable
field time is saved.
Seasonal Variability
A recent study (Hilsenhoff 1988a)
showed that the greatest variability
in BI evaluations resulted from
seasonal differences in the fauna
(Fig. 1). BI values were highest in
summer when water temperatures were
warmest, currents were slowest, and
species that were collected were those
that are most tolerant of low
dissolved oxygen. In warm-water
streams a substantial rise (usually
greater than 1.5) in the BI occurred
in late May or June and lasted for
about two months. In cold water
streams this rise occurred in the
summer and was of a lesser magnitude
(about 1.0). The timing and magnitude
of the late spring or summer elevation
of the BI depends on spring
temperatures and can be predicted by
accumulation of degree days from a
50
-------
Biotic Index Variability
7.0
6.0
BIOTIC
s.o
INDEX
4.0
3.0
2.0
Bl WARM-WATER STREAMS
Bl COLD-WATER STREAMS
1000
900
800
700
600
DEGREE
500
DAYS C
400
300
200
100
16 30 14 28 11 25 9 23 6 20 3 17 1 15 29 12 26
APR. MAY JUNE JULY AUG. SEP. OCT. NOV.
Figure l. Mean biotic index values of four warm-water streams and two cold-water
streams in 1984 (solid lines) and 1985 (dashed lines), with 95% confidence limits
(dotted lines) for the mean of the lowest 75% of biotic index values. Comparison
of degree day accumulations of mean air temperature above 4.5° C in 1984 (solid
line) and 1985 (dashed line) with 1951-1980 average (dot-dash line). (Reproduced
with permission from the Great Lakes Entomologist.)
base of 4.5° C (Hilsenhoff 1988a).
Using the Bl to evaluate streams
during the summer months is not
recommended.
Family-level Biotic Index
Evaluation of streams with a family-
level biotic index (FBI) takes about
one-fourth the time required for a Bl
evaluation that uses species and
genera (Hilsenhoff 1988b). This saving
of time, however, results in greatly
reduced precision and there is a
greater chance of making an erroneous
evaluation. In organically polluted
streams the FBI was substantially
lower than the Bl and in unpolluted
streams it was higher (Table 6) ;
standard deviations were always
greater when using the FBI. However,
if FBI samples are preserved, a Bl
evaluation can always be completed at
a later date.
Sunmary
If samples of 100 or more arthropods
are collected from rock or gravel
riffles at the proper time of the
year, sample variability will be held
to a minimum and the Bl can be used to
accurately evaluate the degree of
organic or nutrient pollution that has
occurred in the stream. Use of the FBI
will save considerable time, but the
evaluation will be much less accurate.
Literature Cited
Hilsenhoff, W.L. 1977. Use of
arthropods to evaluate water quality
of streams. Technical Bulletin No. 100
51
-------
Hilsenhoff
Wisconsin Department of Natural
Resources. 15pp.
Hilsenhoff, W.L. 1982. Using a biotic
index to evaluate water quality in
streams. Technical Bulletin No. 132
Wisconsin Department of Natural
Resources. 22pp.
Hilsenhoff, W.L. 1987. An improved
biotic index of organic stream pol-
lution. Great Lakes Entomologist
20:31-39.
Hilsenhoff, W.L. 1988a. Seasonal cor-
rection factors for the biotic index.
Great Lakes Entomologist 21:9-13.
Hilsenhoff, W.L. 1988b. Rapid field
assessment of organic pollution with a
family-level biotic index. Journal of
the North American Benthological
Society 7:65-68.
Kaesler, R.L., and E.E. Herricks.
1976. Analysis of data from biological
surveys of streams; diversity and
sample size. Water Resources Bulletin
12:125-135.
52
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Results of Ohio River Biological Monitoring
During the 1988 Drought1
Rob J. Reash2
Environmental Engineering Group
American Electric Power Service Corporation
1 Riverside Plaza
Columbus, Ohio 43215
Abstract
The Ohio River Ecological Research Program is a long-term monitoring study
sponsored by several electric utilities owning coal-fired power plants on the
Ohio River (American Electric Power, Cincinnati Gas & Electric Company, Ohio
Edison Company, Ohio Valley Electric Corporation, Tennessee Valley Authority).
The 1988 drought created anomalous physicochemical conditions in the Ohio River;
extremely low flows and elevated ambient water temperatures were observed at
plant sites between RM 54-946. Despite potential limiting conditions, monitoring
studies indicated diverse and healthy communities. Macroinvertebrate data
indicated no consistent differences between upstream/downstream assemblages;
substrate quality appeared to be more limiting than water quality at all plant
sites. Record high densities of larval fish were observed at most sites in 1988,
and total larval species richness was second highest of recent years. A record
total 84 species of adult/juvenile fishes were collected throughout the river.
Record number of species were collected at five of six plant sites; likewise
total abundance of fishes was relatively high at all sites. Spatial differences
in fish abundance/biomass were not consistent between upstream/downstream sites
at individual plant sites. Drought conditions likely caused displacement of some
fish species from inland waters into the Ohio River.
Key Words: Ohio River, Drought, Larval fish, Adult fish, Macroinvertebrates,
Thermal effects.
Introduction
The Ohio River Ecological Research
Program is a long-term study of
aquatic life near once-through cooled
power plants on the Ohio River. The
purpose of the Program is to: (1)
assess potential effects of wastewater
discharges (principally once-through
cooling water) on nearby aquatic
communities; (2) define factors
influencing spatial and temporal
patterns of biological parameters; and
(3) provide inferences on the status
of Ohio River water quality based on
biological parameters. As a
continuation of the Program,
biological and water quality data were
collected at six coal-fired generating
stations on the Ohio River during
1988: Ohio Edison Company's W. H. Sam-
mis Plant (River Mile 54), Ohio Power
Company's Cardinal Plant (RM 76.7),
Ohio Valley Electric Corporation's
Kyger Creek Plant (RM 260), Cincinnati
Gas & Electric Company's W. C. Beck-
jord Plant (RM 453), Indiana Michigan
Power Company's Tanners Creek Plant
(RM 494), and Tennessee Valley Author-
ity's Shawnee Plant (RM 946). Macroin-
vertebrates were collected near three
plant sites (Cardinal, Kyger Creek,
Tanners Creek Plant) whereas ichthyo-
plankton and juvenile/adult fishes
were collected at all plant sites.
1 A publication of the Ohio River Ecological Research Program,
sponsored by American Electric Power, Cincinnati Gas & Electric Company, Ohio
Edison Company, Ohio Valley Electric Corporation, and Tennessee Valley
Authority
2 Chairman, Sponsor Group, Ohio River Ecological Research Program
53
-------
Reash
7) W.H. 8AMMIS PLANT
CARDINAL PLANT
T) KYGER CREEK PLANT
W.C. BECKJORD PLANT
TANNERS CREEK PLANT
-------
Ohio River Biological Monitoring
mental Science and Engineering, Inc. A
longitudinal distance of 1,435 km (892
miles) separated the uppermost plant
site (Sammis Plant; RM 54) and the
furthest downstream site (TVA's Shaw-
nee Plant; RM 946) (Fig. 1). The six
plant sites encompass three distinct
ecoregions within the Ohio River basin
(Western Allegheny Plateau, Interior
Plateau, and Interior River Lowland).
The boundaries of these ecoregions
approximate the traditional geographic
delineation of upper, middle, and
lower segments of the Ohio River
(Pearson and Krumholz 1984, Omernik
1987) A brief description of methods
and material for all sampling is given
below. Detailed descriptions are given
in ESE (1989).
Physioochemical and Flow Measurements
Two or more routine water quality
variables (dissolved oxygen, water
temperature, conductivity, Secchi disk
depth) were measured during all
sampling dates at all stations. During
weekly ichthyoplankton collections
dissolved oxygen and water temperature
were measured at stations upstream of
power plants (i.e., ambient measure-
ments) . All other variables were
measured during ichthyoplankton beach
seine sampling (semi-monthly) and
adult fish sampling (once during May,
July, and September).
River flow data were obtained from
U.S. Army Corps of Engineers measure-
ments at the following locations: New
Cumberland lock and Dam (Sammis
Plant), Pike Island lock and Dam
(Cardinal Plant), Gallipolis lock and
Dam (Kyger Creek Plant), Meldahl lock
and Dam (Beckjord Plant), Markland
Lock and Dam (Tanners Creek Plant),
and Smithland Dam (Shawnee Plant).
River stage data were also obtained,
but river stage varied only slightly
during summer and fall 1988.
Macroinvertebrates
Macroinvertebrates were sampled at
three plant sites (Cardinal Plant,
Kyger Creek Plant, and Tanners Creek
Plant) during two seasonal surveys.
Organisms were collected at two
stations using Hester-Dandy artificial
substrate samplers and ponar grabs.
Sampling stations were located just
upstream of the power plant and
between 250-1,000 meters downstream of
the once-through cooling water
discharge. At each station, five
replicate Hester-Dendy's were set.
Three replicate ponar grabs were taken
at the time of Hester-Dandy retrieval.
Two seasonal (temporal) collections of
macroinvertebrates were taken at each
station. The first colonization period
was during mid-May through mid-June
and the second period was during
mid-July to mid-August.
Ichthyoplankton
Ichthyoplankton (larval fish and eggs)
were sampled at all plant sites from
April 19 through August 25 using
plankton nets and a bag seine.
Nightime ichthyoplankton tows (using
500 u mesh nets having a 1-meter
diameter mouth) were taken weekly at
two transects upstream of all power
plants. Duplicate surface tows and
replicate bottom tows were taken at
each transect, with a ininimum of 50 n?
water sampled for each tow. A total of
864 ichthyoplankton tow samples were
collected in 1988. Bag seine samples
were taken weekly from mid-April
through July and once in August at all
plant sites. A 560 u bag seine was
used to sample larval fishes in shal-
low littoral areas at three stations
along the plant shore. A total of 162
beach seine samples were collected.
Adult and Juvenile Fish
Adult and juvenile fishes were sampled
using electrofishing, seining, trawl-
ing, hoop netting, and gill netting
gear. Fishes were sampled during three
seasonal surveys (May, July and
September) at six stations per plant
site. Three stations were located
upstream of the plants and three were
located downstream of the once-through
cooling discharge. Details on field
and laboratory processing for all
methods are given in ESE (1989).
55
-------
Reash
25
-(•0)
-
20
2-
c
10
raaa
-(SO)
APRIL
JUNE
MEASUREMENT DATE
AUOU8T
Figure 2. Ambient water temperature measurements taken upstream of Kyger Creek
Plant during 1988, 1986 and 1985. Measurements were taken during
weekly ichthvoplankton tows.
.Results
In 1988, ambient water temperatures in
the Ohio River approached historical
mean values during the months of May
and June. Ambient temperatures near
19 "C have typically been associated
with high densities of dominant larval
fishes (gizzard shad, freshwater drum,
carp, and carpsucker/buffalo) during
previous years.
During 1988 temperatures near 19 "C
occurred during the week of May 16 in
the upper Ohio River and during the
week of May 9 in the middle and lower
Ohio River, a trend observed in
several previous years. Ambient water
temperatures during July and August
(the months following spawning for
several species), however, were higher
than historical means at all plant
sites. As a site-specific example,
July and August water temperatures up-
stream of Kyger Creek Plant were con-
siderably higher than recent previous
years, and temperatures exceeded 30'C
during all measurements in August
(Fig. 2).
During August at all plant sites,
ambient temperatures exceeded maximum
allowable stream temperatures as
established by ORSANCO (ORSANCO 1987).
At Shawnee Plant, ambient temperatures
exceeded maximum ORSANCO criteria
during several months. These observa-
tions indicate that ORSANCO tempera-
ture criteria were not derived to
reflect anomalous meterolcgical and
hydrological conditions, and that
generic temperature criteria for the
upper, middle, and lower Ohio River
may not be appropriate due to dif-
fering ambient temperature regimes in
the lower and upper sections.
Dissolved oxygen (DO) concentrations
were near saturation during all
sampling occasions at all sites. The
lowest DO concentration recorded
during 1988 was 6.0 mg/L downstream of
56
-------
Ohio River Biological Monitoring
,1888 FLOW
HISTORICAL MEAN
RM66
250 r
1888 FLOW
HISTORICAL MEAN
RM632
50
APR MAY
JUN JUL AUQ
FLOW MONTH
SEP
APR
MAY JUN JUL AUQ
FLOW MONTH
SEP
Figure 3. Flow rate measured at New Cumberland Lock and Dam (EM 55) (left) and
Markland Lack and Dam (RM 532) (right), April through September,
1988. Historical mean flows indicated by horizontal line for each
month.
Kyger Creek Plant in July. Upstream
concentrations were just slightly
higher on this date, however, averag-
ing 6.4 mg/L. In general, concentra-
tions in the Ohio River were not
limiting during 1988 and downstream
sites influenced by cooling water
discharges at all plants had similar
or only slightly lower DO levels.
Flow rates measured at proximal lock
and dam locations indicated markedly
lower flows in 1988 compared to
historical means. Throughout the
river, flow rate was highest in spring
(April and May), lowest in late June
and August, and somewhat higher in
September compared to August. The
magnitude of deviation of 1988 flows
from historical means was related to
longitude, and tended to increase
downstream. Flow rates near Sammis
Plant (FM 54) were below historical
means during June through September
whereas flow rates near Shawnee Plant
(KM 946) were well below historical
means for all months studied (April
through September); deviation of flow
rates from historical means near
Tanners Creek Plant (KM 495) was
intermediate compared to previously
mentioned plant sites (Figs. 3, 4).
Benthic Macroinvertebrates
Combined Hester-Dendy and ponar grab
collections (for both surveys) showed
total macroinvertebrate densities of
1,459/m2 at CrmUnal Plant and
1,381/m2 at Tanners Creek. In con-
trast, combined ponar and Hester-Dendy
samples from Kyger Crek Plant had a
mean total density of 892/m2. Although
a lower mean density was observed at
Kyger Creek, the total number of taxa
collected was similar at all plant
sites (Table 1). The benthic (Community
near Cardinal Plant was dominated by
an oligochaete-amphipod complex. An
57
-------
Reash
600 r ^HISTORICAL MEAN
400
„ 300
200
100
RM618
-1888 FLOW
APR
MAY JUN JUL AUG.
FLOW MONTH
SEP
Figure 4. Flow rate measured at
Smithland lock and Dam (RM 918), April
through September, 1988. Historical
mean flow indicated by horizontal line
for each month.
oligochaete-mollusk complex dominated
at Kyger Creek plant whereas an oligo-
chaete-amphipod-chironomid assemblage
was numerically dominant near Tanners
Creek Plant (Table 1).
Temporal variation in macroinverte-
brate parameters between upstream and
downstream stations was observed at
all three plant sites. At Cardinal
Plant, marcoinvertebrate parameters
during the May-June Hester-Dendy
survey suggested a more limited
community at the downstream station.
Upstream and downstream values (in
parentheses) for number of taxa, total
density (#/m2) and biotic index were
24(18), 1,199(569) and 4.19(4.18),
repsectively. During the late summer
survey, however, the upstream station
showed a more limited community.
Upstream and downstream values (in
parentheses) for number of taxa, total
density, and biotic index for the
July-August survey were 17(20),
312(1,281), and 5.77(7.24).
A similar trend was observed at Kyger
Creek Plant. During the first Hester-
Dendy survey upstream and downstream
values (in parentheses) for number of
taxa, total density, and biotic index
were 33(30), 665(460), and 4.36(6.18) ,
respectively. For the July-August
survey upstream and downstream values
(in parentheses) for number of taxa,
total density/ and biotic index were
24(33), 618(801), and 7.07(6.66),
respectivley. These data not only
confirm the expected temporal varia-
bility of macroinvertebrate parameters
in the Ohio River, but indicate that
downstream benthic communities were
not consistently less diverse and
abundant than upstream communities.
At all plant sites, Hester-Dendy
samples had consistently greater
number of taxa compared to Ponar grab
samples. This trend ws observed for
both seasonal surveys. These results
suggest that substrate characteristics
were more limiting than potential
water quality effects at all sites
studied.
The collection of one macroinverte-
brate species in 1988 deserves special
mention. Medusae of the freshwater
jellyfish (Craspedacusta sowerbyi)
were collected in ichthyoplankton tows
at all six plant sites. The presence
of this species indicates low flow
conditions in -the Ohio River as this
invertebrate is usually restricted to
lentic systems (Pennak, 1978).
Ichthyoplankton
For combined tow and beach seine
samples at all sites, a total of
492,365 larvae and eggs were collected
during 1988. Seventy taxa (including
52 species) representing 13 taxonomic
families were identified. This was the
second highest total taxa since larval
fishes were first collected in 1976.
Taxa richness was highest from Shawnee
Plant collections, where 47 taxa (34
species) were collected in 1988. Taxa
richness was lowest at Tanners Creek
Plant (32 taxa, 24 species) and Kyger
Creek Plant (33 taxa, 25 species).
58
-------
Ohio River Biological Monitoring
Table 1. Benthic macroinvertebrate sampling results at three Ohio River plant
locations, May-August, 1988. Values given are for combined upstream and
downstream stations and combined May-June and July-August surveys.
Macroinvertebrate
Parameter
Cardinal
EM 77
Kyger Creek
PM 260
Tanner Creek
RM 495
Mean density 840
(Hester-Dendy)8
Mean density 2,077
(ponar)8
Mean density 1,459
(combined methods)8
Most abundant taxa
(combined methods)15
636
1,148
892
2,769
954
1381
Imm. tubificids Imm.tubificids
Limnodrilus sp. Gammarus sp.
Corbicula sp. Glyptotendipes sp.
Limnodrilus sp. Gamtnarus sp. Cricotopus sp.
Dugesia sp. Glyptotendipes sp.Cyrnellus sp.
Imm. tubificids
Gammarus sp.
Aulodrilus sp.
Total taxa 54
Shannon-Wiener 2.49
diversity
Biotic index 6.18
63
3.14
6.49
62
3.24
7.40
a Densities given as
b Most abundant taxa
#/m2.
listed in descending order of relative abundance.
Taxa that were abundant at all plant
sites included gizzard shad, carp,
emerald shiner, carpsucker/buffalo,
Morone sp./white bass, Lepomis sp.,
and freshwater drum. Spotfin shiner,
sand shiner, mimic shiner, bluntnose
minnow, channel catfish, logperch, and
walleye were collected at all plant
sites but in fewer numbers. These
ubiquitous species have extensive geo-
graphic ranges and many can tolerate a
wide range of water quality/habitat
conditions.
Several taxa were restricted to
specific regions of the Ohio River.
Larval fishes collected exclusively in
the upper ecoregion (Western Allegheny
Plateau) were northern hog sucker,
shorthead redhorse, rock bass, banded
darter, and yellow perch. Larval
species restricted to the middle and
lower ecoregions included paddlefish,
goldeye, speckled chub, bullhead
minnow, striped bass, threadfin shad,
blue sucker, blue catfish, and
brindled roadtom.
During 1988 larvae of four species
were collected for the first time:
pumpkinseed (RM 76), silver lamprey
(PM 260), gravel chub (RM 453), and
striped bass (three lower plant
sites). The collection of a larval
lamprey at Kyger Creek Plant was
unexpected as ammocoetes of most
lamprey species are typically confined
to inland streams or rivers. The
collection of this specimen may
represent actual spawning in the Ohio
River or displacement from streams
having insufficient flow due to
drought conditions.
59
-------
Reash
OZ2AB08HAD
tea
Figure 5. Weekly densities of ichthyo-
plankton sampled just upstream of W.H.
Sammis Plant (EM 54). 1986-1988.
Record high densities of ichthyo-
plahkton were observed at five of six
plant sites in 1988. Peak densities
were highest at W. H. Sammis Plant
(635 larvae/10 m3 on June 26) (Fig.
5). This peak density was the highest
ichthyoplankton density observed in
the history of the Program, and was
comprised predominantly by gizzard
shad larvae (612 larvae/10 m3).
Gizzard shad or combined herring taxa
dominated the peak densities at all
other plant sites. Gizzard shad
comprised 98% of all larvae during
peak densities at Tanners Creek Plant
(Fig. 6), and herrings comprised 90%
of all larvae during the peak density
at Shawnee Plant (Fig. 7). Other taxa
collected in considerably greater
numbers during 1988 were carp, Morone
sp., white bass, Lepomis sp., and
Stizostedion sp.
In previous years, total mean density
of ichthyoplankton was -typically
highest at middle or lower Ohio River
plant sites. In 1988, however, total
mean density was highest at W.H.
Sammis Plant (upper river) and lowest
• 160
60
GIZZARD SHAD
(271/10 m')
Figure 6. Weekly densities of ichthyo-
plankton sampled just upstream of Tan-
ners Creek Plant (PM 495) . 1986-1988.
at Beckjord Plant (middle river). The
chance collection of numerous gizzard
shad shortly after a major hatch near
Sammis Plant is likely responsible for
this observation.
Densities of ichthyoplankton in near-
shore areas (beach seine collections)
were highest at the two lower plant
sites. Beach seine densities were
highest at Shawnee Plant (mean density
= 255/10 m3) and Tanners Creek Plant
(mean density = 118/10 m3). Mean
densities at other plant sites ranged
between 23 - 70/10 m3.
Adult and Juvenile Fish
In 1988, a total of 90,710 individuals
representing 94 taxa (84 species) were
collected during adult and juvenile
fish sampling. The 84 species col-
lected in 1988 represents the highest
species richness during the history of
the Program. Forage species were
numerically dominant throughout the
river, as in previous years. Gizzard
shad and emerald shiner accounted for
46% (41,638 individuals) and 27%
(24,7470 individuals) of the total
species catch, respectively. Channel
60
-------
Ohio River Biological Monitoring
180
20
1867
APRS.
r « ii i3
SAMPLE WEEK
18
SEPT
Figure 7. Weekly densities of ichthyo-
plankton sampled just upstream of
Shawnee Plant CRM 946). 1987-1988.
catfish, white bass, bluegill, and
freshwater drum were also abundant at
all plant sites.
Species collected at plant sites
located in the upper ecoregion only
included brown trout, river chub,
striped shiner, sand shiner, black
redhorse, white sucker, rock bass, and
several darter species. Paddlefish,
shortnose gar, bowfin, threadfin shad,
red shiner, and blue catfish were
collected exclusively near the Shawnee
Plant in 1988. Many of these
region-specific collections have been
documented in previous years. No
longitudinal trends in species
richness were evident during 1988, as
in previous years. Species richness
was highest at Sammis Plant (53
species) and Shawnee Plant (51
species). Species richness at other
plant sites ranged from 39 to 47
species collected.
For all sites combined, seining was
the most productive sampling gear with
51,400 individuals captured by seines
in 1988. Electrofishing sampling
resulted in the collection of 23,443
fishes, whereas gill netting and
trawling each collected about 7,000
specimens. Hoop netting was the least
productive sampling method (841
individuals). The relatively high
catches in beach seines was due to
utilization of near-shore littoral
areas by several species, especially
these using littoral zones for nursery
areas.
Statistical analyses of total
abundance and biomass data using ANOVA
indicated significant temporal (i.e.,
seasonal) effects at all plant sites
for two or more sampling methods. For
example, gill netting and electro-
fishing in September produced higher
catch rates than May and July samples
at several plant sites. Seine col-
lections produced higher catch rates
in July at five of six plant sites.
In contrast, spatial (i.e., upstream
versus downstream) effects were
generally not observed during 1988. At
Shawnee Plant, catch rates for gill
netting and trawling were higher at
upstream sites, whereas biomass of
fishes was higher in electrofishing
samples downstream of Kyger Creek
Plant. Adult and juvenile fish
sampling in 1988 indicated no trend of
decreased catch rates at downstream
sites. These results indicate that the
abundance and biomass of fishes was
similar upstream and downstream of the
cooling water discharges, and poten-
tial thermal effects (expected to be
exacerbated by low flow conditions)
were not observed.
Discussion
IXie to prolonged drought conditions,
anomalous hydrological and physico-
chemical conditions were observed in
the Ohio River during 1988. Elevated
ambient temperatures and below normal
flow rates appeared to profoundly
influence the biological productivity
of the entire river. The timing of
elevated ambient temperatures appeared
to be a crucial factor in promoting
biological productivity, especially
fish spawning success and larval
survival. Water temperatures in June,
61
-------
Reash
July and August were wanner than
historical means at all plant sites.
These are the months following
spawning of many Ohio River fishes.
Sustained high temperatures likely
enhanced the early spawning of some
species, promoted larval growth rates
due to the increased abundance of
phytoplarikton or zooplankton, and
favored the increased duration of
spawning for some species. Increased
larval survival resulted in higher
than normal ichthyoplahkton densities,
as was observed with gizzard shad.
Because the flushing rate of the Ohio
River was reduced considerably in
1988, larvae of pelagic spawning
fishes (e.g., gizzard shad, freshwater
drum, skipjack herring) were very
abundant and appeared to have high
survival.
Comparison of 1988 benthic macro-
invertebrate data with previous years
(1981 and 1984; Gep-Marine 1982,
Geo-Marine 1986) indicates that no
major changes in species composition
have occurred at upper and middle
river plant sites. An increase in the
number of taxa present in 1988 was
observed at Kyger Creek and Tanners
Creek Plants; taxa richness at
Cardinal Plant was similar to the
number of taxa collected in 1984.
Increases in taxa richness, however,
may be attributable to increased
ability to identify some taxa.
Total densities of macroinvertebrates
were generally higher in 1988 compared
to previous years. In addition, biotic
index scores have generally decreased
since 1981 at caTrjjna] and Kyger Creek
Plants, suggesting improved water
quality at these sites due to the
presence of less intolerant communi-
ties. In contrast, biotic index scores
at Tanners Creek Plant have not
changed markedly since 1981. In
summary, benthic macroinverterbrate
data collected during the Ohio River
Ecological Research Program suggest
improved water quality, especially at
sites in the upper river. Reinvasion
or extensions of numerous fish species
in the upper- section have been
recently noted (Pearson and Pearson
1989). These trends are consistent
with temporal patterns of chemical-
specific parameters in the upper river
that indicate improvements in water
quality (Cavanaugh and Mitsch 1989).
Adult and juvenile fish sampling in
1988 indicated that the longitudinal
distribution of Ohio River fishes is
related to factors associated with
zoogeography, flow regime, and
environmental tolerance. These and
other factors have been discussed
previously (Reash and Van Hassel 1988;
Van Hassel et al. 1988). At plant-
specific locations the abundance,
biomass, and species richness of
adult/juvenile fishes was not
adversely affected by power plant
discharges in 1988. Rather, the
combination of habitat, water quality,
and flow effects appear to be more
important influences as significant
temporal dif ferences in fish community
parameters were common, whereas
upstream/downstream differences were
rarely observed.
«
Acknowledgments
All field sampling and data analysis
were conducted by the project consul-
tant, Environmental Science and Engi-
neering, Inc., St. Louis, Missouri.
S. L. Foster typed the manuscript.
Literature Cited
Cavanaugh, T.M. and W.J. Mitsch. 1989.
Water quality trends of the upper Ohio
River from 1977 to 1987. Ohio Journal
of Science 89:153-163.
ESE (Environmental Science and
Engineering, Inc.). 1989. 1988 Ohio
River Ecological Research Program.
Final Report. Environmental Science
and Engineering, Inc., St. Louis,
Missouri.
Geo-Marine, Inc. 1982. 1981 Ohio River
Ecological Research Program. Adult and
juvenile fish, ichthyoplankton and
benthic macroinvertebrate studies.
Geo-^torine, Inc., Piano, Texas.
62
-------
Ohio River Biological Monitoring
Geo-Marine, Inc. 1986. 1984 Ohio River
Ecological Research Program. Adult and
juvenile fish, ichthyoplankton, and
macroinvertebrate studies. Geo-Marine,
Inc., Piano, Texas.
Omernik, J.M. 1987. Ecoregions of the
aanterminous United States. Annals of
the Association of American
Geographers 77:118-125.
Pearson, W.D. and L.A. Krumholz. 1984.
Distribution and status of Ohio River
fishes. Oak Ridge National Laboratory
Publication No. ORNVSub/79-7831/1.
Oak Ridge, Tennessee.
Pearson, W.D. and B.J. Pearson. 1989.
Fishes of the Ohio River. Ohio Journal
of Science 89:181-187.
Pennak, R.W. 1978. Fresh-water
invertebrates of the United States.
2nd Edition. John Wiley & Sons, Inc.,
New York.
ORSANCO (Ohio River Valley Water
Sanitation Commission). 1987.
Pollution control standards, 1987
revision. Ohio River Valley Sanitation
Commission, Cincinnati, Ohio.
Reash, R.J. and J.H. Van Has.se!. 1988.
Distribution of upper and middle Ohio
River fishes, 1973-1985: II. Influence
of zoogeographic and physicochemical
tolerance factors. Journal of
Freshwater Ecology 4:459-476.
Van Hassel, J.H., R.J. Reash, H.W.
Brown, J.L. Thomas and R.C. Mathews,
Jr. 1988. Distribution of upper and
middle Ohio River fishes, 1973-1985:
I. Associations with water quality and
ecological variables. Journal of
Freshwater Ecology 4:441-458.
63
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Interpretation of Scale Dependent Inferences
from Water Quality Data
Nels H. Troelstrup, Jr. and James A. Perry
Department of Forest Resources
University of Minnesota
110 Green Hall, 1530 N. Cleveland Avenue
St. Paul, MN 55108
Abstract
A survey of 15 trout streams was conducted to evaluate spatial patterns of water
quality and their relationship to biophysical processes on different scales with-
in the driftless area of southeastern Minnesota. Results suggest that subsurface
geology, surface landform and land-lose patterns change significantly across this
physiographic region. The Hilsenhoff Biotic Index, (%) EPT, EPT:Chironomidae,
nitrate-N and specific conductance were all highly correlated with these regional
biophysical characteristics. Stream discharge variance, pH, and (%) sediment on
riffle sites varied signficantly with differences in watershed-level land use and
morphology while alkalinity, (%) leaf substrate, (%) wood substrate, (%)
shredders and the scraper :collector-filterer ratio varied with reach-level
channel morphology and riparian management. Scale corrected classes of monitoring
variables displayed different patterns of water quality. These results support
theoretical claims that aquatic ecosystems are hierarchically structured and
controlled by processes operating on multiple spatial and temporal scales. Water
quality monitoring networks should be designed on a scale(s) defined by
management objectives and the scale (s) upon which monitoring variables respond.
Key words: scale, water quality patterns, trout streams, driftless area,
biomonitoring.
Introduction
Ecological phenomena are known to
respond to processes which show hier-
archical order (Kbestler 1967, Allen
and Starr 1982; O'Neill et al. 1986,
Kblasa 1989, Wiens 1989, May 1990).
Biophysical processes operating within
the landscape provide a hierarchical
set of constraints which define the
observed characteristics and dynamics
of our natural resources. Thus,
processes operating at levels above
those of interest constrain or limit
processes at lower levels within the
system (Allen and Starr 1982, O'Neill
et al. 1986). These factors acting
within their own holon (sensu Kbestler
1967) or interacting between holons
comprise the dynamic processes which
define hydrologic regimes, soils and
vegetation and influence physiological
processes, life history character-
istics and community composition and
function of biota within aquatic
ecosystems (Frissell et al. 1986,
Cummins 1988, Delcourt and Delcourt
1988, Rash and Rosenburg 1989).
Factors controlling landscape dynamics
and the structure and function of
stream communities may manifest
themselves at multiple spatial and
temporal scales (Minshall 1988,
Townsend 1989, Rash and Roseriburg
1989, Ward 1989). Geologic and
climatic events exert control over
landscape and watershed level
characteristics on a spatial scale of
100's to 1000's of square kilometers
and a temporal scale of 100,000 to
1,000,000 years. Vegetation dynamics
and land management practices exert
controls over processes operating over
landscapes and watersheds on spatial
scales of 10's to 100's of square
kilometers and temporal scales of
100's to 1000's of years, while
management and natural processes
operating along the stream corridor
determine inputs of organic matter,
light energy and temperature regimes
over spatial scales of 1 to 100 square
meters and temporal scales of weeks to
months (Frissell et al. 1986, Delcourt
and Delcourt 1988, Minshall 1988).
64
-------
Interpretation of Scale Dependent Inferences
Until recently, most efforts to define
factors controlling benthic
communities in streams have focused on
watershed, reach and roicrohabitat
level processes operating over
temporal scales of days to months
(Resh and Rosenburg 1989). In
addition, these studies have focused
on biological responses to processes
operating on one spatial and/or
temporal scale (e.g., Fisher 1987,
Peckarsky 1986,1987). Despite
excellent attempts to introduce
hierarchy theory and the importance of
scale to stream ecology (Frissell et
al. 1986, Cummins 1988, Minshall 1988,
Townsend 1989, Ward 1989), few
attempts have been made to examine
benthic data or controls over water
quality monitoring variables across a
number of spatial and temporal scales
(except see Resh and Rosenburg 1989).
Scale phenomena also influence the
design and inferences drawn from water
quality investigations (Jeffers 1988).
However, unlike the basic sciences,
applied sciences like water quality
are necessarily tied to the human
perspective. This perspective (scale
of human activities and influences)
also operates hierarchically on
multiple social and political scales
and must be integrated with natural
biophysical phenomenon to allow for
proper monitoring and management of
natural resources. In fact, it is
preoccupation with the human
perspective by the applied sciences
which often limits the utility of
monitoring data (Perry et al. 1984).
Matching the scale of a natural
phenomenon with the scale of a
management objective is necessary to
improve the efficiency and accuracy of
our monitoring efforts (Schumm 1988).
The objectives of the work presented
in this paper were to (1) define
spatial patterns of water quality
within a heterogeneous region, (2)
determine the relationships between
water quality monitoring variables and
biophysical processes across multiple
scales, and (3) compare patterns of
water quality generated by variables
operating on different spatial scales.
We hypothesized that there would be
discernible regional patterns in
physical, chemical and biomonitoring
variables throughout the "driftless
area" (Winchell and Upham 1884).
Furthermore, we hypothesized that
different monitoring variables would
respond at different scales of
resolution (regional, watershed,
reach, and riparian levels) within the
driftless area, since processes
controlling their dynamic behavior
operate at different levels.
Study Area
Samples were collected from riffle
sites on 15 randomly selected trout
stream tributaries of the Root River
Basin in southeastern Minnesota
(longitude 91°-93° W, Latitude 43°-44°
N) (Fig. 1). This area of Minnesota
was considered part of the "driftless
area" by J.D. Winchell during his
geological survey of the state
(Winchell and Upham 1884) and falls
within the "driftless area aquatic
ecoregion" defined by Omernik and
Gallant (1988). The climate of the
study area is mid-continental with
72cm of precipitation per year, 66%
occurring during the growing season
(May-September). Mean air temperatures
range from -10° C during the winter
months to 22° C in the summer with
extremes of -36°C in the winter and
36°C in the summer (Kuehnast 1972).
The Root River flows across the study
area, downcutting into bedrock strata
along its course to the Mississippi
River (Fig. 1). Topography is largely
determined by surface erosion into
bedrock due to the lack of glacial
till throughout much of the study
area. Valley slopes exceed 35% near
the Mississippi River, becoming more
level along the western portion of the
study area. Well drained, silty loam
soils, derived from loess deposits,
predominate throughout much of the
study area (University of Minnesota
1973).
65
-------
Troelstrup and Perry
Natural vegetation within the region
consists of maple-basswood forest in
the eastern portion of the study area
grading to open oak savannah in the
west (Kratz and Jensen 1977). Dominant
woody vegetation along stream
corridors consists of willow (Salix
spp.), elm (UlJnus americana L.),
cottonwood (Populus deltoides Marsh)
and birch (Betula spp.). Agriculture
is a prominent feature of the
landscape with production of -corn,
soybeans, alfalfa, swine and dairy
cattle common in the uplands and along
stream corridors (United States
Department of Agriculture and
Minnesota Department of Agriculture
1988).
Methods
Regional Variable
The mean elevation of spring sources
above each site (ELEV) was determined
from USGS topographic maps (scale
1:24000) for use as an independent
variable in our analyses. ELEV served
as a geology variable because changes
in this characteristic imply different
sources of water (i.e., geological
strata). Five aquifers serve as the
main sources of water for springs in
the region. Streams draining the
western portion of the study area
originate from the karst limestone and
dolomite aquifers of the
Maquoketa/Dubuque and Galena
formations, streams in the central
portion of the study area drain from
the sandstone and dolomite St. Peter
and Prairie du Chien formations and
streams in the eastern portion of the
study area originate from sandstone
aquifers of the Jordan and Franoonia
formations (Fig. 1). Springs were
identified directly on each map or
were inferred from the origin(s) of
perennial stream flow on each map.
ELEV data were standardized to the top
of the Jordan aquifer using the
information provided by Broussard et
al. (1975) to correct for a westerly
dip in the geological strata across
the study area (Fig. 1).
Land-Use Data
land-use information at three
different spatial scales (watershed,
reach, riparian) for each site was
obtained from published sources and
interpretation of low altitude,
standard color aerial photographs.
Watershed level land-use data was
obtained from the Land Management
Information Center (IMIC) of the
Minnesota State Planning Agency
(1971). The spatial resolution of this
data is 40 acres (16.2 ha). Data
obtained consisted of the percentage
of 40 acre parcels within each section
of a township which were dominated by
cultivated (WGUL), pasture (WPAS) and
forested (WFOR) land-use types. Aerial
photographs taken during the 1987
growing season over 3 of the study
watersheds were interpreted using IMIC
procedures and revealed that 1969 data
were satisfactory for watershed-level
analyses.
Low altitude, standard color aerial
photographs (1987 growing season) were
obtained from county Agricultural
Stabilization and Conservation Service
offices to evaluate land-use at the
reach and riparian levels using a
modified version of the IMIC method. A
twenty-five cell grid (total grid size
40 acres (16.2 ha), cell size 1.6
acres (0.65 ha)) was projected onto a
color print of the section containing
each site (Fig. 1). The entire grid
was placed over a study site
perpendicular to stream flow with the
back edge of the middle cell
corresponding with the location of the
site. Dominant land-use in each cell
was noted as was land use of the cells
through which the stream flowed.
Reach-level land use was estimated by
calculating the percentage of cells
dominated by cultivated (RECU),
pasture (REPA) and forested (REFO)
land-use types over the entire grid.
Riparian-level land-use (RICU,RIPA,
RIFO) was evaluated by calculating
similar percentages for cells through
which the stream flowed (Fig. 1).
66
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Interpretation of Scale Dependent Inferences
RIPARIAN
B
LEGEND_
Limestone ana Dolomite Formations i
Upper Sandstone Formations '
Lower Sandstone Formations
Aquitard
V/7& Forested Land Use
•• Agriculture Land Use
Figure 1. Diagram of study area in southeastern Minnesota showing locations of
study sites, regional patterns in subsurface geology (cores) and land-use (pie-
diagrams), and differences in biophysical perspective at regional, watershed,
reach and riparian scales along the Root River Basin.
67
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Troelstrup and Perry
Table 1. Methods used in collection and analysis of water quality samples.
Variable1
NTTR
AIKA
PH
COND
TEMP
TOPB
FI£V
Substrate
HBIN
PEPT
EPTC
SHRD
SCCO
Method
Spectrophototnetric
Titrimetric
Electrometric
YSI Model 33 S-C-T Meter
YSI Model 33 S-C-T Meter
Hach Turbidimeter
Sixth-Tenths-Depth Method
% Occurrence along Transects
Duplicate, 1 min. Kicknet
Duplicate, 1 min. Kicknet
Duplicate, 1 min. Kicknet
Duplicate, 1 min. Kicknet
Duplicate, 1 min. Kicknet
Source
APHA2 (1985)
APHA (1985)
APHA (1985)
APHA (1985)
APHA (1985)
APHA (1985)
Platts, et al. (1983)
IN TEXT
Hilsenhoff (1988)
Plafkinetal. (1989)
Plafkinetal. (1989)
Plafkinetal. (1989)
Plafkinetal. (1989)
1 Abbreviations as defined under Methods.
2American Public Health Association.
Accuracy of interpretations was
calculated to be 95% based on quality
control procedures.
Catchment and Channel Parameters
Watershed area (AREA) and channel
gradient (GRAD) from headwaters to
site were determined from USGS
topographic maps (scale 1:24005).
Watershed gradient was estimated by
calculating the absolute gradient from
headwaters to site (change in
elevation over channel length) using
information derived from the
topographic maps. Mean channel width
(WIDT), depth (DEPT) and current
velocity (CURR) were determined from
measurements taken in the field.
Monitoring Variables
Physical and chemical water quality
characteristics were evaluated on 5
randomly chosen dates in the spring
and fall of 1988 (i.e., 10 repeated
measures at each site). Parameters
evaluated included nitrate-N (NITR),
specific conductance (OOND), stream
temperature (TEMP), turbidity (TORE)
and coefficient of variation of flow
measurements (FLCV). Methods used in
the determination of these parameters
are shown in Table 1.
The percent occurrence of five
substrate categories were determined
on each riffle on the first and last
sampling dates in the spring and fall
(i.e., 4 repeated measures at each
site). A 10 meter chain was fitted
with colored flags (10cm spacing) and
laid across the stream at ten equally
spaced longitudinal positions along
the channel. Substrate observations
were made at ten locations on the
chain (O.lOx channel width spacing)
along each of the ten transects for a
total of 100 determinations per
riffle. The data translated directly
to percent occurrence of rock (ROCK)
(diameter > 4mm), wood (WOOD), leaf
(IEAF), sediment (SEDI) (diameter <
4mm) and macrophyte (MACR) on each
riffle.
Invertebrates were sampled at each
site on the first and last sampling
dates in the fall of 1988. Biomonitor-
ing metrics evaluated from these
samples included the Hilsenhoff Biotic
Index (HBIN), percent of Ephemerop-
tera, Plecoptera and Trichoptera
(PEPT) invertebrates in each sample,
the ratio of EFT to Qiironomidae
(EPTC), percentage of shredder
invertebrates (SHRD), and ratio of
68
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Interpretation of Scale Dependent Inferences
scrapers to collector-f ilterers (SCOO)
(Plafkin, et al. 1989). Averages of
duplicate samples collected on each
date were used in further analyses
(i.e., 2 repeated measures at each
site). In addition, the dominant taxon
in kicknet samples from each site was
identified and relative abundance of
these taxa were compared between
sites.
Data Analysis
Abiotic gradients and biophysical
relationships across the study area
were identified using graphical,
multiple regression and principal
components analysis techniques (NH
Analytical Software, 1988). Date by
date Spearman Rank Correlations were
calculated from repeated measures of
each monitoring variable versus
biophysical characteristics of each
site (n=15 sites). Seasonal (n=30; 15
sites x 2 seasons) and overall means
(n=15 sites) for monitoring variables
were used in regression analyses to
define relationships between biophysi-
cal characteristics of each site and
monitoring variables at different
spatial scales. If season did ..not
contribute significantly to a regres-
sion model (t-statistic, p>0.05),
overall site means were used in
regression analyses (n=15). Model
selection was based on maximizing the
coefficient of determination (R2),
minimizing the residual mean square
and collinearity among predictors and
achieving a null residual plot through
transformation of the raw data
(Weisberg 1985). Results of correla-
tion and regression analyses were used
to define scale corrected groups
(classes) of monitoring variables. An
agglomerative cluster analysis
technique was used to identify site
groupings based on scale corrected
classes of monitoring variables. Site
means of each monitoring variable were
standardized for unit differences by
calculating z-scores and clustered
based on squared euclidean distances
between centroids of each cluster with
the software package SPSS (Norusis
1988).
RESORTS
Biophysical Characteristics of Sites
ELEV above each site varied signifi-
cantly (Fig. 2a) with distance from
the Mississippi River. These data
confirm changes in aquifer sources to
trout streams distributed across the
study area (Fig. 1). In addition, GRAD
(Fig. 2b) and WFOR (Fig. 2c) displayed
significant regional patterns across
the driftless area. Lower GRAD were
observed in the western portion of the
study area, reflecting regional
changes in topography. WFOR also
decreased logarithmically with
distance from the Mississippi River.
These data show the increase in
intensity of agricultural land-use
practices on a regional scale with
distance from the Mississippi River
and are consistent with Minnesota
state records of agricultural land-use
(United States Department of Agricul-
ture and Minnesota Department of Agri-
culture 1987). AREA (Fig. 2d) did not
vary significantly with distance from
the Mississippi River as did the other
regional biophysical variables. Thus,
the observed regional trends in GRAD
were not merely artifacts of sampling
site location within study watersheds.
Regional trends exhibited by ELEV,
GRAD and WFOR clearly show hetero-
geneity in biophysical characteristics
across the driftless area.
Additional information on the
biophysical characteristics of these
sites is provided by the results of
principal components analysis (PGA).
PCA created a new set of biophysical
variables through linear combinations
of the original 15 variables.
Eigenvector loadings of monitoring
variables on each principal component
(PC) indicated that there were sets of
biophysical characteristics operating
together on different scales (Table
2). Highest loadings on PCI were
mainly from biophysical character-
istics known to vary on a regional
scale (ELEV, WCUL, WFOR, GRAD). Thus,
PCI explained 31.3% of the variability
in the data set and seemed to repre-
sent large scale biophysical processes.
69
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Troelstrup and Perry
300
ELE V=3.2« 1DIST-81.80e
UJ
-100
2.0
E
•* 1.5
« 1.0
to
k.
o
o>
o
0.5
0.0
log 0 H AD=-0.008DIS T-M .2 8 8
nnl 6 F = 10.05 F2 = 0.3
~ 2.4
a
a.
(0
e
1.8
1 .2
o 0.6
a
o
0.0
I o g( WF 0 R + 1 )=-0.0 1 3DIS T + l .035
n = 1 S F=11.43 R2=0.43
c.
2.5
cT1 2.0
E
JL
(D
« 1.5
h.
<
01
^ 1.0
30
60
90 -
Distanceik
log A BEA=0.004DIST + 1 .3OO
n = 1 8 F=1.78 B2«0.06
d.
m)
90
Figure 2. Kegional patterns in biophysical characteristic
the driftless area of southeastern Minnesota, (a) Rel;
spring elevation (ELJEV) above each sampling site and aei
that sampling site from the Mississippi River; (b) Relatia
gradient (GRAB) and distannpi from the Mississippi River; (c
the number of 40 acre parcels dominated by forested land-
(WFQR) and distance from the Mississippi River; (d)
watershed ^Tea (AREA) and distance from the Mississippi R
Highest loadings on PC2 were
associated with reach and riparian
management practices and channel
morphology (RIFO, REFO, REPA, WIDT).
PC2 explained an additional 26.8% of
the variability in the data set and
represented local scale processes.
Loadings on PC3 were highest on reach
and riparian management practices
(RIOJ, KEOJ, REFO). Watershed level
land-use (WPAS) and morphology (GRAB)
were also highly correlated with this
principal component. PC3 explained
15.9% of the variability in the
biophysical data set. loadings on PC4
were only significantly correlated
with channel morphology (DEFT, WIDT)
at the reach level. Ihis principal
component explained 8.7% of the
variability in the data set. Strong
collinearity was observed among land-
uses on different scales, especially
70
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Interpretation of Scale Dependent Inferences
Table 2. Eigenvalues, eigenvectors and
variance (% Var) explained from
principal components analysis of trout
stream biophysical characteristics
(n=15 sites) and scales represented by
each principal component.
PC Eigenvalue % Var
1 4.689
2 4.014
3 2.382
4 1.305
VARIABLE1
ELEV
WCUL
WFOR
DEFT
CURR
AREA
GRAD
REPA
RIPA
REPA
RIPA
REPO
RIPO
DEPT
31.3
26.8
15.9
8.7
EIGENVECTOR
PCI
-0.39
-0.32
0.32
-0.29
0.32
-0.27
0.31
-0.30
-0.28
PC2
0.34
-0.31
0.37
-0.39
0.23
Cumulative %
31.3
58.0
73.9
82.6
SCALE
REGIONAL/
WATERSHED
REACH/
RIPARIAN
WIDT
WPAS
RECU
REPO
RICU
CURR
GRAD
DEPT
WIDT
-0.35
-0.28
-0.54
0.37
-0.54
-0.29
0.24
PC4
0.42
0.48
WATERSHED/
REACH
REACH
Abbreviations defined under Methods
reach and riparian. High collinearity
among predictors within a nested
hierarchy would be expected since
characteristics at one scale are part
of the next higher scale.
Stream Wat1 AT Quality Characteristics
Most of the monitoring variables
displayed large ranges in values,
typical of disturbed catchments over
dissolution aquifers (Table 3). NTTR
and TURB values occasionally exceeded
water quality standards for trout
waters within the state (Minnesota
Pollution Control Agency 1990) and
flow variance was highest in streams
of the karst area within the region
(Table 3).
Most of the monitoring variables were
significantly correlated with biophys-
ical characteristics at multiple
scales (Table 4). NTTR and COND data
displayed the expected trend of low
values at sites draining diffuse
sandstone aquifers of the Jordan and
Franconia formations and high values
from the Maquoketa-Dubuque and Galena
formations. TURB values showed consid-
erable variance due to the effects of
a thunderstorm which influenced sam-
ples of sites 5, 14 and 15 on one date
in the spring of 1988 and men working
with farm equipment in the stream at
site 3 on one date during fall
sampling. Thus, COND seemed to respond
on a regional scale with changes in
subsurface geology and regional land-
use. NITR and PH seemed to be
influenced by watershed-level land-use
characteristics while ALKA, TURB and
TEMP were highly correlated with reach
and/or riparian level management
practices (Table 4). FLCV was not
significantly correlated with any of
the biophysical characteristics.
All five substrate types on riffles
displayed large ranges in values
(Table 3). ROCK was the dominant
substrate at riffle sites across the
study area followed by MACR (Table 3).
WOOD was the least common substrate
type and was highly correlated with
the amount of reach and riparian
forest above and adjacent to a site
(Table 4). Similar observations were
made of LEAF material as a substrate,
except the occurrence of LEAF material
was strongly seasonal (see below).
SEDI was prevalent as a substrate type
71
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Troelstrup and Perry
Table 3. Overall summary statistics for monitoring variables evaluated in
Southeast Minnesota Streams (n-number of repeated measures x 15 sites).
Variable1
NTTR (mg L"1)
AIKA (mg L''
-1'
CCND (us can'1)
TEMP (°C)
TORE (NTU)
FI£V (%)
ROCK (%)
WOOD (%)
IEAF (%)
SEDI (%)
MACR (%)
n
150
150
150
150
150
150
30
60
60
60
60
60
Mean
Median
Physical/Chemical
3.9 3.4
266 262
8.01 8.02
397 386
11.7 11.0
5.12 1.80
19.2 15.3
Substrate
51.8 56.0
2.5 1.0
8.2 1.0
8.4 4.0
28.8 22.0
s.e.
0.2
2
0.03
5
0.4
1.37
2.5
3.2
0.5
1.5
1.5
3.5
Range
0.5-10.9
226-333
7.05-8.74
275-660
4.2-25.0
0.30-146.00
2.6-66.3
0.0-89.0
0.0-13.0
0.0-48.0
0.0-56.0
0.0-94.0
Invertebrates
HBIN
PEPT (%)
EPIC
SHRD (%)
SOCO
30
30
30
30
30
3.7
55.2
9.1
12.1
0.8
3.3
57.3
5.8
7.2
0.3
0.2
4.5
2.2
2.8
0.2
1.8-6.3
1.5-93.9
0.02-63.7
0.0-67.3
0.0-4.6
1 Abbreviations as defined under Methods.
at many of the agricultural sites and
was most highly correlated with
riparian land management (Table 4).
ROCK and MACR were most highly corre-
lated with watershed and reach-level
management practices. ROCK was more
abundant at agricultural sites with
high current velocities while MACR
tended to be more abundant at forested
sites with lower current velocity.
Ranunculus agnatilis (Chaix), Veronica
connata var. qlaberriroa (Pennell) and
Nasturtium officinale (R. Br.) were
the macrophyte species occurring most
frequently at all sites across the
study area.
HBIN values ranged from "fair" (6.25)
to "excellent" (1.77) indicating that
some of these trout streams were
influenced by significant organic
loading. The PEPT in kicknet samples
ranged from 1.5 to 93.9% and EPTC in
kicknet samples ranged from 0.02 to
63.67. These three metrics suggested
differences in invertebrate community
structure between sites and all three
were highly correlated with regional
changes in subsurface geology and
watershed morphology (Table 4).
Regional changes in benthic community
structure were confirmed by examining
the dominant invertebrate taxa at each
site. Two western sites (1,5) were
dominated by the chironomids Tanytar-
sus sp. (35%) and Rheotanytarsus sp.
(54%), site 3 was dominated by the
mayfly Baetis tricaudatus vaoans
(McDunnough) (42%), and site 4 was
dominated by the caddisfly Cheuroato-
psvche spp. (17%). Empirically derived
tolerance values to organic pollution
for these taxa were 6, 6, 2 and 5 on a
scale of 0-10 (Hilsenhoff 1987). The
invertebrate communities of three
centrally located sites (6, 8, 10) and
one western site (2) were dominated by
Optioservus fastiditus (LeConte). This
72
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Interpretation of Scale Dependent Inferences
Table 4. Highest Spearman Rank correlation1 between each monitoring variable and
the most frequently correlated predictor at each scale based on date by
date correlations of monitoring variables with biophysical characteristics.
Variable^
Regional^ Watershed^ Reaclr
Ripariarr
NITR
pH
TURB
ALKAL
COND
TEMP
FLCV
ROCK
WOOD
LEAF
SEDI
MACR
HBIN
PEPT
EPTC
SHRD
SCCO
ELEV(0.79) WFOR(-0.91) OJRR(0.77)
ELEV(-0.56) WPAS(0.83) REPAS(-0.46)
ELEV(0.50) WPAS(0.58) RECUL(0.74)
ELEV(0.55) GRAD(0.50) RECUL(-0.69)
EIEV(0.81) WFOR(-0.73) REPAS(0.68)
ELEV(-0.67) GRAD(0.58> REFOR(-0.68)
NO SIGNIFICANT CORRELATIONS WITH SITE V2
WPAS(0.71) OJRR(0.48)
WFOR(0.52) REPAS(-0.53)
ELEV(0.52) GRAD(-0.49) REPAS(-0.76)
ELEV(-0.38) AREA(-0.60) REFOR(-0.54)
WPAS(-0.63) RECUL(-0.69)
ELEV(0.62) GRAD(-0.69) CHNWD(0.55)
ELEV(-0.64) GRAD(0.53) CHNWD(-0.55)
ELEV(-0.56) AREA(-0.68) OJRR(0.58)
ELEV(0.50) WFOR(-0.38) REOJL(-0.74)
AREA(0.42) REFOR(0.57)
RIFOR(-0.64)
RIFOR(0.39)
RIPAS(0.62)
RICUL(-0.66)
RIPAS(0.67)
RICUL(0.56)
^RIABLES
RICUL(0.60)
RIFOR(0.52)
RIFOR(0.41)
RIFOR(0.62)
RICUL(-0.64)
-
-
-
RICUL(-0.42)
RICUL(-0.61)
1 Correlations presented in table statistically significant (p<0.10) based
on quantiles for the Spearman's Test Statistic (Conover 1980).
2Abbreviations as defined under Methods.
elmid beetle contributed 19-27% of the
cumulative number of invertebrates
sampled at each of the sites and has a
tolerance value of 4 on a scale of 0-
10. Site 7 kicknet samples were
dominated by the caddisf ly Micrasema
kluane (Ross and Iforse) (50%) and the
invertebrate communities of the
eastern sites within the study area
(sites 11-15) were all dominated by
Brachycentrus occidentalis (Banks).
This caddisf ly contributed 21-55% of
the cumulative abundance of all taxa
collected on both dates at each of the
eastern sites. Both of these
brachycentrid caddisflies have
tolerance values of 1 on a scale of 0-
10. Thus, invertebrate communities in
the western portion of the study area
were dominated by taxa which were
moderately tolerant to organic
enrichment (except sites 2,3) while
communities of eastern sites were
dominated by taxa which exhibited low
tolerance to high organic loadings.
While conmunity structure seemed to be
influenced primarily at the regional
and watershed levels, invertebrate
community function was more highly
correlated with local reach/riparian
level processes (Table 4). SHRD and
SCCO were positively correlated with
the extent of forest development at
the reach and riparian-levels and
negatively correlated with agricul-
tural land-uses on these same scales.
Regression Relationships
Statistically significant relation-
ships were observed for all monitoring
variables with one or two biophysical
characteristics (Table 5). However,
the variance explained by these models
was quite variable (range of R2= 0.17
to 0.92). Six of the 17 monitoring
variables displayed significant
seasonal differences (i.e., PH, TORE,
COND, TEMP, FLCV and LEAF). Of these
six monitoring variables, only LEAF
displayed higher values in fall
samples. The remaining monitoring
73
-------
Troelstrup and Perry
variables had significant amounts of
variability explained by a combination
of watershed, reach and riparian level
biophysical site characteristics
(Table 5). More than half of the
regression equations explained 40% or
more of the variance in the monitoring
data.
Our monitoring variables can be
divided into groups based on the
predictors in each model (Watershed,
Watershed/Reach, Reach/Riparian).
Thus, 7 of the monitoring variables
had significant amounts of their
variance explained by biophysical
characteristics on the watershed level
(NTTR, FH, FI£V, SEDI, KEEN, PEPT,
EPTC), 2 monitoring variables by a
combination of characteristics on the
watershed and reach levels (OOND,
TEMP) and 8 variables by character-
istics on the reach and riparian
levels (TURB, AIKA, ROCK, WOOD, IEAF,
MACR, SHRD, SOOO). Combining the
results of correlation and regression
analyses, we delineated scale
corrected classes of monitoring
variables (Table 6). Four classes
(regional, watershed, reach, riparian)
were defined.
Patterns at Different Scales
Scale corrected classes of monitoring
variables (Table 6) were used to
generate site groupings. Cluster
dendograms were generated using
monitoring variables which had the
greatest amount of their variance
explained by regional, watershed,
reach and riparian-level biophysical
characteristics. Dendograms produced
by these analyses (Fig. 3) were
compared to identify and interpret
differences in spatial patterns of
water quality within the study area.
Each dendogram portrays a different
pattern of site groupings based on the
relationship between monitoring
variables used to generate the
dendogram and biophysical character-
istics of each site. Regional patterns
(Fig. 3a) generated from NTTR, COND,
HBIN, PEPT and EPTC monitoring data
show 5 distinct site groupings. An
examination of site characteristics
with respect to those monitoring
variables allowed interpretation of
the observed pattern. Cluster 1 (sites
8, 11, 12, 13) had low NTTR and COND
compared to the regional median.
Cluster 2 (sites 2, 6, 15) had high
NTTR and COND values. Cluster 3 (sites
1, 4, 9, 10) had high HBIN, low PEPT
and EPTC values compared to regional
medians. In contrast, the cluster
formed from the combination of
clusters 1 and 2 (above) had low HBIN,
PEPT and high EPTC values. The cluster
formed from the agglomeration of sites
3 and 5 differed from the other
monitoring sites due to low PEPT
values. These two sites were located
in the karst portion of the study area
below heavily developed watersheds.
The watershed-level dendogram (Fig.
3b) delineates two major groups of
sites; group 1 (Sites 2,4,6,8,9,
10,11,13,15) and group 2 (Sites 1,3,5,
7,12,14). These two groups can be
distinguished by differences in SEDI
and MACR substrate at riffle sites.
Group 1 sites had lower SEDI and^
higher MACR than group 2 sites when
compared to regional median values.
Reach and riparian-level analyses
produced very similar site patterns
(Fig. 3c,d). Two groups of sites are
easily delineated from the dendograms
produced by these analyses. All sites
except 3,5,7 at the reach-level and 5,
7 at the riparian level belong to one
large group of relatively similar
sites. These outlier sites displayed
poor water quality characteristics
(i.e., higher NTTR, COND, ALKA and
SHRD and lower WOOD) as compared to
regional median values for each
monitoring variable.
Thus, cluster analysis on scale
corrected monitoring data provided
distinctly different site groupings
which could be interpreted from
monitoring variables operating on
different scales.
74
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Interpretation of Scale Dependent Inferences
Table 5. Regression models for monitoring variables and biophysical factors in
Southeast Minnesota streams (n-nuniber of observations; R*-coefficient of
determination; F(p)- F-statistic and probability value for regression; RMS-
residual mean square for regression; Season- t-statistic and significance for
season effect in regression (*-p<0.05, NS-p>0.05)).
Variable1 • * Predictor1 • *
NTTR -log(WFORKL)
pH -WOJL
-GRAD
log TURB RECCJ
RIPA
log AIKA -REOJ
log GOND -WFOR
REPA
log TEMP log(WPAS+l)
-log(REFCH-l)
log FLCV WCUL
AREA
log Rock CURR
arcs WDOD REOJ
RIFO
log(LEAF+l) log(RIFCH-l)
log(SEDI+l) -log AREA
arcs MACR -RECU
log HBIN -log GRAD
arcs PEPT GRAD
log(EPTCH-l) -AREA
log(SHRDfl) -RECU
log(SCOOfl) REFO
rf & F(p)
15 0.84 76.2
(<0.001)
30 0.42 7.9
(<0.001)
15 0.37 5.0
(<0.016)
15 0.17 3.9
(0.047)
30 0.70 23.0
(<0.001)
30 0.81 41.7
(<0.001)
30 0.37 6.6
(<0.001)
15 0.25 5.7
(0.017)
15 0.52 8.7
(0.002)
29 0.92 172.9
(<0.001)
15 0.21 4.7
(0.029)
15 0.32 7.5
(0.007)
15 0.42 11.2
(0.002)
15 0.28 6.5
(0.011)
14 0.53 15.4
(<0.001)
15 0.38 9.55
(0.003)
15 0.28 6.4
(0.012)
1 Monitoring and biophysical variable abbreviations
RMS Season
1.039 0.62,NS
0.042 -3.21,*
0.037 -1.52,NS
0.001 0.29,NS
0.001 -5.27,*
0.003 -10.43,*
0.051 -3.90,*
0.044 -0.76,NS
0.004 -1.58,NS
0.026 18.27,*
0.164 -0.60,NS
0.063 -1.20,NS
0.011
0.054
0.065
0.086
0.034
as defined under Methods.
2Data transformations included arcs=(sin"1)1/2 and log=ooinmon logarithm.
3Seasonal means used in
regression (n=30) or overall
means (n=15) .
Discussion
Data presented in this paper suggest
that commonly used water quality
monitoring variables respond to
processes operating on several spatial
scales within the driftless area.
Regional patterns in NITR, COND, and
invertebrate community structure were
highly correlated with regional trends
in subsurface geology and land-nose
patterns. Streams in the western
portion of the study area drain karst
limestone and dolomite aquifers
(Winchell and Upham 1884, Broussard et
75
-------
Troelstrup and Perry
Table 6. Scale corrected classes1 of monitoring variables based on
correlation and regression analyses.
Variable"
LEAF
WOOD
TORE
SHRD
SCCO
ALKA
MACR
ROCK
TEMP
COND
NITR
PH
FDCV
EPTC
SEDI
HBIN
PEPT
REGIONAL
WATERSHED
REACH
RIPARIAN
1 Class Membership Based on Regression Results-
Class Membership Based on Significant Correlations-
2Abbreviations as defined under Methods.
al. 1975, Ojakangas and Matsch 1982,
Singer et aL. 1983). The combination
of intensive agricultural land-use
within these watersheds and karst
subsurface geology promotes water
quality problems (LsGrand 1973, Singer
et al. 1982, St. Ores et al. 1982,
Hallberg et al. 1985, Wall et al.
1989) which simplify the structure of
invertebrate communities by reducing
or eliminating intolerant taxa ( Perry
et al. 1988, Troelstrup and Perry
1989, Bartodziej and Perry MS, Wilton
and Perry unpubl. data). In contrast,
streams in the eastern portion of the
study area originate from sandstone
aquifers and drain watersheds with
more woody vegetation. Despite steeper
gradients, these streams have the
lowest NITR, COND and HBIN values and
the highest PEPT and EPTC values.
These regional biophysical character-
istics serve as a template over which
finer grain reach and riparian
processes operate (Frissell et al.
1986, Minshall 1988, Townsend 1989,
Ward 1989). Local responses of NTTR,
COND and PH were probably related to
subsurface dynamics within the
riparian zone. Agricultural land use
adjacent to a stream is known to
reduce denitrification and plant
uptake of nitrogen and promote
nitrification and nutrient export to
the stream channel (Vitousek and
Melillo 1979, Peterjohn and Cornell
1984, Pinay and Decamps 1988). Higher
NITR, COND and PH values would be
expected adjacent to agricultural
conditions where redox potentials and
movement of soluble ions are high
(Green and Kauffman 1989).
TURB, ALKA and TEMP were also observed
to vary with reach and riparian
management in this study. These
parameters are influenced directly by
loss of riparian vegetation and sub-
sequent bed and bank erosion in and
adjacent to the stream channel. TURB
levels increase dramatically in
response to livestock grazing and
cultivation adjacent to the stream
76
-------
Interpretation of Scale Dependent Inferences
a.
Regional
6
15
2
4
9
8-
11-
10-
13-
7-
1-
12-
14-
3-
5-
Watershed
c.
Reach
d.
Riparian
Figure 3. Results of clustering sites on scale corrected classes (see Table 6)
of monitoring variables, (a) dendogram generated from regional class, (b)
dendogram generated from watershed class, (c) dendogram generated from reach
class, (d) dendogram generated from riparian class (Numbers adjacent to each
dendocrram refer to site locations as defined in Ficpi'ne 1).
bank (Woodall and Wallace 1972, Karr
and Schlosser 1978, Bratton et al.
1980, Manzel et al. 1984). These
activities in close proximity to the
stream may also increase channel width
and reduce channel depth due to
sedimentation of sloughed material
from the stream bank (Clifton 1989).
Numerous studies have noted increases
in mean temperature and greater ranges
in temperature regimes adjacent to
agricultural areas (Karr and Schlosser
1978, Bratton et al. 1980, Dance and
Hynes 1980, Menzel et al. 1984, Smart
et al. 1985).
Substrate characteristics in driftless
area streams are probably controlled
by a combination of hydrologic
processes operating on the watershed
level and light and mesoscale hydro-
dynamics on the reach and riparian
77
-------
Troelstrup and Perry
levels. POCK and MACR substrate types
were negatively correlated with one
another and highly correlated with
current regimes and reach and riparian
management. Occurence of SEDI was
negatively correlated with watershed
area and positively correlated with
reach and riparian management. The
flashy nature of karst streams
(LeGrand 1973, Hallberg et al. 1985)
and prevalence of sedimentation in
^agricultural reaches (Karr and
Schlosser 1978, Dance and Hynes 1980,
Lenat 1984) would seem to explain
observed patterns of these substrate
types throughout the study area. WOOD
material in the channel and LEAF
material on the stream bottom were
negatively correlated with reach
pasture land and positively correlated
with riparian forested land. Seasonal
patterns in IEAF abundance associated
with autumn abscission were also
observed, suggesting that spatial and
temporal patterns of availability
govern the dynamics of these substrate
types. Agricultural streams flowing
through open riparian canopies have
been shown to harbor extensive algal
communities (Menzel et al. 1984, Smart
et al. 1985, Bachmann et al. 1988).
Thus, management of the riparian zone
may directly influence functional
characteristics of a stream by
altering detrital inputs and primary
production on a local scale within a
watershed (Hynes 1975, Swanson et al.
1982).
Biomonitoring has been promoted as a
useful tool in evaluating support of
designated uses in water quality
investigations (Lenat et al. 1980,
Hilsenhoff 1982, Lenat 1988, Plafkin
et al. 1989). Oorkum and Ciborowski
(1988) and Oorkum (1989) were success-
ful in delineating broad scale invert-
ebrate community patterns associated
with biophysical characteristics in
northwestern North America. Inverte-
brate community structure proved
sensitive to regional patterns in
geology, surface land form and land-
use in the driftless area. We observed
low PEPT and EPIC and high HBIN values
from streams draining dissolution
aquifers through agricultural water-
sheds. Others have observed similar
large scale patterns in community
structure using these metrics (Welch
et al. 1977, Bratton et al. 1980,
Dance and Hynes 1980, Hilsenhoff 1982,
Lenat 1984, Menzel et al. 1984, Kite
and Bertrand 1989).
We observed shifts in the relative
abundance of different feeding guilds
within the invertebrate communities at
our sites. Higher SHRD and SCOO values
were observed adjacent to forested
riparian zones. If food were a
limiting resource to these insects,
SHRD abundances would be expected to
track the availability of LEAF
material (Hynes 1975, Swanson et al.
1982, Cummins et al. 1989) while SCCO
abundances would track the availa-
bility of benthic algae in the stream
(Dance and Hynes 1980, Karr and Dudley
1981, Menzel et al. 1984). Ross (1963)
provided evidence of regional patterns
in the distribution of caddisflies
(Trichoptera) related to the predomi-
nant terrestrial vegetation. Within
his large scale framework, our data
suggest that functional" character-
istics of invertebrate communities may
be tightly tied to local biophysical
characteristics which influence inputs
and types of organic material to the
stream (Hynes 1975, Swanson et al.
1982, Cummins et al. 1989).
Ihe results of this study provide
evidence of significant variability in
biophysical characteristics across the
driftless area in southeastern
Minnesota. Subsurface geology, land
surface form and land-use all vary
significantly with distance from the
Mississippi River. Ihese trends in
biophysical characteristics explain a
significant amount of the variability
in physical (OQND), chemical (NTIR)
and biological (BIND, PEPT, EPIC)
water quality monitoring variables.
Regional patterns, together with local
variance in reach and riparian
characteristics, provide a mosaic of
biophysical factors which vary at
78
-------
Interpretation of Scale Dependent Inferences
multiple spatial and temporal scales.
This presents a tremendous challenge
to the "aquatic ecoregion" concept
which has been tested widely (Hawkes
et al. 1986, Rohm et al. 1987, Hughes
et al. 1987, Larsen et al. 1988,
Whittier et al. 1988, Lyons et al.
1989) and implemented by state water
quality agencies (e.g., Hieskary et
al. 1987).
Aquatic ecoregions were originally
defined to address national and large
scale regional water quality issues
(Omernik 1987). However, several
investigators have noted problems in
implementing this approach to water
quality monitoring and management.
Omernik and Griffith (1986) observed
differences in alkalinity between
seepage and drainage lakes within the
same ecoregion. Hawkes (1986) found
that fish ecoregions in Kansas showed
little similarity to the aquatic
ecoregions of Hughes and Qmernik
(1981). Lyons (1989) found that local
habitat characteristics associated
with reach and riparian management
were better predictors of fish
community characteristics than
membership within an aquatic ecoregion
in Wisconsin. Whittier et al. (1988)
found poor separation of ecoregions in
Oregon using periphyton and inverte-
brate data from streams across the
state. In particular, large within-
region variability occurred when
valley and mountain streams occupied
the same ecoregion. This challenge has
been met by generalizing the "aquatic
ecoregion" concept to a "regionaliza-
tion" concept (Gallant et al. 1989).
Under this approach, regions may be
defined at any scale. Thus, hetero-
geneous regions may be broken up into
smaller more homogeneous units. This
approach has great promise if state
water quality agencies can secure
funding to increase the number of
monitoring stations necessary for such
stratification.
Properly designed water quality
monitoring programs operate from well
defined objectives, utilize monitoring
variables which relate directly to
those objectives, provide spatial and
temporal information necessary to
address those objectives and optimize
resources to account for natural
variability in measured parameters
(Schaeffer et al. 1985, Perry et al.
1985). Consideration of which
variables to measure is an important
step in the planning process of these
efforts. Many state and federal water
quality agencies evaluate a list of
variables at monitoring sites
distributed over a sociopolitical area
(state or county) and sample on a
regular temporal frequency (e.g., 1
month) (Perry et al., 1984). Our data
suggest that different monitoring
variables are controlled by processes
operating on different scales
(regional, watershed, reach, riparian)
and that different sets of variables
may be more effective for detecting
water quality problems at different
scales. The variable/scale
associations identified in this study
may not be appropriate for other
physiographic regions. In addition,
this study focused on spatial patterns
of water quality. Temporal dynamics in
biophysical characteristics are
equally important when designing a
monitoring program (Wiens 1989).
However, the methods used to derive
scale relationships in this study
could be used in other regions. Thus,
scale corrected groups of monitoring
variables could be identified which
would (1) provide more sensitivity to
a problem on a particular scale and
(2) provide greater security against
conflicting results due to scale
incompatibility with management
objectives.
Current ecological theory suggests
that natural systems are hier-
archically structured. The character-
istics of any level of a natural
system are thought to be controlled by
rate processes operating on higher
spatial and temporal scales (Koestler
1967, Allen and Starr 1982, O'Niell et
al. 1986, O'Neill 1988). Examples of
controlling processes operating within
79
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Troelstrup and Perry
the landscape include faulting,
volcanism, climatic changes, pedo-
genesis, weathering and erosion. These
processes result in the development of
controlling factors in the landscape
which influence the characteristics of
water resources and the biota
inhabiting aquatic ecosystems. Clear-
ly, interpretation of structural and
functional patterns in nature is scale
dependent and our ability to monitor
and manage those resources depends on
our understanding of that hierarchical
structure and its dynamics.
Acknowledgements
The authors wish to thank Mr. Brian
Shelley and Mrs. Cindy Troelstrup for
their valuable assistance in the
field, Dr. Ralph Holzenthal
(University of Minnesota, Department
of Entomology) for confirming aquatic
insect identifications, Susanne Maeder
(Minnesota State Planning Agency) for
providing land-use information, Mr.
Mel Haugstad (Minnesota Department of
Natural Resources) for providing data
and management information about
southeastern Minnesota trout streams,
and members of the Forest Water
Quality Group at the University of
Minnesota for critical review of this
manu-script. This work was supported
by the College of Natural Resources
and the University of Minnesota
Agricultural Experiment Station under
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85
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Aquatic Vegetation and Habitat Quality
in the Lower Des Plaines River: 1985-1987
Pamela P. TazUc
Illinois Natural History Survey
607 E. Peabody Drive
Champaign, Illinois 61820
Abstract
In the early 1980's, locally abundant populations of aquatic vegetation were
observed in the lower Des Plaines River after being virtually absent for nearly
20 years. This study was conducted in 1985-1987 to characterize the aquatic
vegetation community in a 13-mile reach (river miles 273-286) of the Des Plaines
River and to assess aspects of habitat quality. Twenty species of aquatic
macrophytes were identified; vegetation cover, estimated from ground-truth
surveys and low-altitude color aerial photographs, reached 60 ha in August 1987.
The most heavily vegetated areas were river miles 285.5, 279.5, 277, and 273.5.
Sediments at these locations contained high levels of As, Od, Cr, Cu, Fe, Hg, Pb,
and Zn and aquatic macrophytes had high levels of Al, Ba, Cr, Co, Sn, V, Zn, and
PCBs. At senescence, these accumulated substances can remain in macrophyte
tissues or be released into the water or sediments, affecting overall habitat
quality. Therefore, interactions between rooted vascular plants and toxic
substances, particularly those in sediments, should be considered when assessing
habitat quality.
Key words: aquatic macrophytes, Des Plaines River, Illinois, vegetation cover,
aerial photography, heavy metals, PCB's
Introduction
The Illinois River and its bottomland
lakes have been virtually devoid of
submersed and floating-leaved
vegetation since the early 1960's
(Bellrose et al. 1983, Havera et al.
1980). This decline has been linked to
the release of wastewater, industrial
effluents, and runoff. In the early
1980's, locally abundant populations
of aquatic vegetation were observed in
the lower Des Plaines River. Because
macrophytes modify and diversify
habitat and fuel secondary production
by producing oxygen, cycling
nutrients, and providing cover for
fishes and substrate for fish food
organisms (Barko et al. 1986, Bennett
1971, Engel 1985, Raschke 1978, Wright
et al. 1981), recent increases in
aquatic vegetation should improve
water and habitat quality (e.g.,
reduced turbidity, increased oxygen
levels, larger and more diverse
invertebrate populations, and an
improved fishery).
Macrophytes also modify sediment and
water chemistry (Dawson et al. 1978,
Hutchinson 1975, Sculthorpe 1967,
Westlake 1973), often by substance
uptake and release (Hill 1979, Jaynes
and Carpenter 1986, Smith and Adams
1986*). Accumulated substances, both
mineral nutrients and toxic
substances, may remain in roots and
rhizomes or be translocated to other
plant parts (i.e., acrcpetal translo-
cation). During plant senescence,
these substances may associate with
decomposing particulate matter or
leach into the water column. Thus,
substances concentrated from deeper
sediments can be moved into the water
column and top sediments (Campbell et
al. 1985, Everard and Denny 1985,
Gabrielson et al. 1984, Howard-
Williams and Lenton 1975, Kraus et al.
1986, Mclntosh et al. 1978, Smith and
Adams 1986, Welsh and Denny 1976).
Sediments of the lower Des Plaines
River are characterized by the
presence of 'toxic substances, and
rooted aquatic macrophytes are capable
of mobilizing these sediment-bound
substances. The purpose of this study
was to assess habitat quality in the
86
-------
Lower Des Plaines River
Truu Ulud
Des Plaines River
Miles
1 2
Aquatic vegetation
Figure 1. Location and extent of aquatic vegetation beds in the lower Des Plaines
River (river miles 273-286) in Auqust 1987.
lower Des Plaines River by (1) doc-
umenting the extent and species
composition of the aquatic macrophyte
community, (2) chemically analyzing
water, sediments, and macrophyte
tissues for heavy metals, PCBs, and
organic pesticides, and (3) examining
toxic substance interactions between
sediments and macrophytes.
Study Site
The study site, in Will and Grundy
counties, Illinois, includes a reach
of the Des Plaines River from Brandon
Road Lock and Dam (RM 286) to the
confluence of the Des Plaines and
Kankakee rivers (RM 273) (Fig. 1). The
tributary Grant Creek enters the Des
Plaines River near RM 274; Mobil Oil,
AMOCO, Olin Matheson, Commonwealth
Edison, and Rexall Chemical are
located along this reach. Treated
effluents released into the Sanitary
and Ship Canal by the Metropolitan
Sanitary District of Greater Chicago
enter the Des Plaines River 4 miles
upstream of the study reach. Toxic
sediments have been identified in the
North Branch of the Chicago River and
the Des Plaines River (Blodgett et al.
1984, Illinois Environmental
Protection Agency 1984).
The study reach was divided into eight
segments of approximately equal size
(Fig. 1). Segment boundaries were
delimited without separating heavily
vegetated areas.
Materials and Methods
Low-altitude, natural-color aerial
photography and ground-truth surveys
(Motorola Mini-Ranger III System,
transect methods, and hand mapping)
were used to document location,
extent, and species composition of
87
-------
Tazik
Table 1. Macrophytes collected in the Des Plaines River for chemical analyses
in 1986 and 1987. Water and sediments were collected at all locations. FM =
river mile.
location
Segment 1
(FM 285.5)
Segment 4
(FM 279.5)
Segment 5a
(FM 277.5)
Macrophytes
Eleccharis acicularis
Myriophyllum sp.
Potamogeton cripsus
Fotamogeton nodosus
Potamogeton pectinatus
Sagittaria latifolia
Typha sp.
Myriophyllum sp.
Potamogeton cripsus
Potamogeton nodosus
Potamogeton pectinatus
Vallisneria amsricana
1986
X
X
X
X
X
X
X
X
1987
X
X
X
X
X
X
X
X
Segment 5b
(FM 276.8)
Segment 8
(FM 273.5)
Myriophyllum sp.
Potamogeton nodosus
Potamogeton pectinatus
Potamogeton pectinatus
Vallisneria americana
x
x
X
X
X
aquatic nacrophytes in June or July,
1985-1987. Voucher specimens were
collected, identified (Beal 1977,
Cornell and Oorrell 1972, Fassett
1967), and archived in the Illinois
Natural History Survey Herbarium
(HIS). Data were recorded on base
maps, digitized, and entered into a
Geographic Information System
(ARC/INFO) (Sparks et al. 1986, Tazik
and Sparks 1987, Tazik 1988).
Eight macrophyte species (two emersed
and six submersed) were collected and
chemically analyzed in 1986 (Table 1).
In 1987, macrophytes, water, and
sediments samples were collected from
five locations for chemical analysis.
Prior to chemical analysis, macro-
phytes were divided into above-ground
(shoots) and below-ground (roots)
parts. Each sample analyzed was a
composite or homogenate of several
subsamples to assure thorough repre-
sentation of the water, sediments, and
plant species at each location.
Samples were chemically analyzed for
total cations using standard methods
(Tazik 1988). Substances measured at
or below detection limits for all
sample sites or macrophyte species are
not reported here.
Correlation analyses were used to
examine the association between
substance levels in sediments and
plant tissues. Average linkage cluster
analyses were used to identify
similarities in sediments from the
five locations, similarities in
macrophyte species, and similarities
between sediments and macrophyte
tissues. (Pielou 1984, Sokal and Rohlf
1969, Wilkinson 1987). Variances were
equalized prior to cluster analysis to
prevent swamping of uncommon elements
or those in lower concentrations by
abundant elements (i.e., having higher
means and variances) (Pielou 1984).
For details of chemical analyses,
mineral nutrient concentrations,
macroinvertebrate communities, and
88
-------
Lower Des Plaines River
Table 2. Aquatic macrcphytes collected in the Des Plaines River, 1985-1987.
Growth forms are rooted (R), submersed (S), emersed (E), aquatic (A), terrestrial
(T), floating (F), and floating-leaved (FL).
Scientific name
Caramon name
Growth form
Calamagrostis
Ceratophyllum demersum L.
Dianthera americana L.
Eleocharis acicularis (L.) R. & S.
Elodea canadensis (Michx.) Planchon.
\
Gramineae
Lemna spp.
Lythrum salicaria L.a
Myriophyllum sp.
Nelumbo lutea (Willd.) Pers.
Nymphaea tuberosa Painea
Phragmites communis Trin.
Polygonum sp.
Potamogeton crispus L.
Potamogeton pectinatus L.
Potamogeton zosteriformis Fernald.
Potamogeton nodosus Poirb
Sagittaria latifolia L.
Scirpus fluviatilis (Torr.) Gray
Scirpus validus Vahl.
Typha angustifolia L.
Typha latifolia L.
Vallisneria americana (Michx.)
a New taxa in 1986
b New taxa in 1987
Reed bentgrass
Coontail
Water willow
Needle rush
American elodea,
waterweed
Grass family
Duckweed
Purple loosestrife
Water milfoil
American lotus
White water lily
Reed grass
Smartweed
Curlyleaf pondweed
Sago pondweed
Flatstem pondweed
American pondweed
Common arrowhead
River bulrush
Soft-stem bulrush
Narrowleaf cattail
Common cattail
Eelgrass
R T
F A
R E A
R E A
R S A
R T
F
R E A
R S A
R FL A
R FL A
R E A
R T
R S A
R S A
R S A
R FL A
R E A
R E A
R E A
R E A
R E A
R S A
macrophyte standing crops, see Sparks
et al. (1986), Tazik and Sparks
(1987), and Tazik (1988).
Results
Species Composition and Cover
Twenty macrophyte species were
collected from the study reach from
1985 to 1987 (Table 2). The total
vegetated area (46 ha) was nearly
identical in 1985 and 1986 (Table 3).
There were slight differences in the
amount of cover of individual species
and within segments, but overall there
was little change between the 2 years.
Total vegetative cover increased to 60
ha in 1987, primarily due to an
increase in submersed macrophytes in
Segment 5 (Table 3). The areas most
heavily vegetated in all years were
Segments 1 (FM 285.5), 4 (EM 279.5), 5
(RM 277), and 8 (RM 273.5) (Table 3,
Figs. 2-5). Potamogeton spp.,
Myriophyllum sp., and Vallisneria
americana accounted for approximately
70% of the total vegetated area in all
years, with the most extensive cover
in Segments 1, 5, and 8. Emersed
vegetation, primarily Sagittaria
latifolia, covered over 10 ha of the
study reach, primarily in Segments 2,
3, and 4 (RM 279-284).
Chemical Analyses
Water samples from all sites contained
low levels of nearly every element
measured. Concentrations of 16 of 26
elements measured were at or below
detection limits; all remaining
elements were within quality criteria
established for aquatic life (US
Environmental Protection Agency 1976).
89
-------
Tazik
Table 3 . Coverage (ha) of macrophyte species in study segments in 1986 and 1987 .
Segment
Macrophyte
Ceratophyllum demersum
Myriophyllum sp.
Potamogeton pectinatus
Potamogeton crispus
0.
0.
1
-
82
—
19
2
-
0.02
0.02
-
3
-
—
—
—
4
1986
-
—
—
—
5
-
—
—
—
Potamogeton zosteriformis - - - - -
Potamogeton nodosus
Potamogeton spp. mix
Submersed species mix
Nymphacea tuberosa
Lythrum salicaria
Phragmites communis
Sagittaria latifolia
Typha spp.
Emersed species mix
Total
Ceratophyllum demersum
Myriophyllum sp.
Potamogeton pectinatus
Potamogeton crispus
0.
0.
8.
0.
17
34
77
-
-
-
32
-
-
10.61
0.
-
29
-
-
-
-
—
-
-
-
0.78
-
-
0.82
-
-
-
-
—
* —
—
—
—
0.05
1.80
0.10
-
1.95
-
-
-
-
—
—
—
—
—
0.06
6.91
1.48
-
8.45
1987
-
—
-
-
—
—
14.62
—
—
—
0.07
0.18
—
14.87
-
—
-
—
6
-
0.02
0.02
—
0.03
—
—
0.09
—
—
—
0.07
—
—
0.23
-
—
—
—
0.
0.
0.
0.
0.
0.
0.
0.
0.
7
01
—
—
02
—
—
—
09
12
02
—
04
26
04
60
-
—
—
—
8
-
—
—
—
—
—
—
8.55
—
—
—
0.06
0.11
—
8.72
-
—
—
—
Total
0.01
0.86
0.04
0.21
0.03
0.17
0.34
32.12
0.12
0.02
0.11
10.05
2.13
0.04
46.25
-
0.29
—
—
Potamogeton zosteriformis ---------
Potamogeton nodosus
Potamogeton spp. mix
Submersed species mix
Nymphacea tuberosa
Lythrum salicaria
Phragmites communis
Sagittaria latifolia
Typha spp.
Emersed species mix
Total
0.
9.
09
-
00
-
-
-
-
-
-
-
-
-
—
-
24.57
—
-
0..47
—
—
0.32
—
—
8.06
------ 0.13
0.
-
-
48
-
-
-
3.07
-
-
-
3.67
-
-
0.03
7.05
1.64
-
-
0.07
0.14
—
-
0.10
—
-
—
0.12
------ 0.20
9.
86
3.07
3.67
8.72
24.78
0.57
0.77
—
—
0.09
0.18
0.06
8.39
0.09
—
42.42
0.13
—
0.03
14.53
2.08
0.26
59.83
Sediments samples in 1987 (Table 4)
contained As, Cd, Cr, Cu, Fe, Hg, Pb,
and Zn at highly elevated or extreme
levels, the two highest categories of
the Illinois Stream Classification
System (Illinois Environmental
Protection Agency 1984, Kelly and Kite
1984). Dieldrin and heptachlor epoxide
were not detected and PCBs in the
sediments were generally <1 ppm. All
but a few substances were found in
higher concentrations in sediments
than in plant tissues (Table 5).
Substance concentrations in macrophyte
tissues were generally comparable with
those measured in other studies, al-
though Zn levels were often higher in
our plants (Campbell et al. 1985,
Cowgill 1974, DiGiulio and Scanlan
1985). PCBs, Co, and Mn were consist-
ently accumulated in greater amounts
in macrophyte tissues than in sedi-
ments, while Zn and Ni were frequently
present in amounts comparable to those
in the sediments (Tables 4 and 5).
Levels of Co, Cr, Se, Sn, and V were
generally higher in plant roots than
in shoots. Conversely, shoots had
higher levels of PCBs, Zn, and Mn
levels than did roots. Eleocharis
acicularis, Myriophyllum sp., and
90
-------
Lower Des Plaines River
-5 .
vegetation
^ Submersed vegetation
X Chemistry samples
Figure 2. location and extent of aquatic vegetation beds, Segment 1, lower Des
Plaines River. August 1987.
MILES
0 •» .5
^ Emersed vegetation
£2 Submersed vegetation
X Chemistry samples
Figure 3. Location and extent of aquatic vegetation beds, Segment 4, lower Des
Plaines River. August 1987.
91
-------
Tazik
0 -JS .5
Emersed vegetation
^ Submersed vegetation
[v] Algae/Duckweed
X Chemistry samples
Figure 4. location and extent of aquatic vegetation beds, Segment 5, lower Des
Plaines River. August 1987.
p^l Emersed vegetation
£3 Submersed vegetation
X Chemistry samples
Kankakee
River
Figure 5. location and extent of aquatic vegetation beds, Segment 8, lower Des
Plaines River. August 1987.
92
-------
Lower Des Plaines River
Table 4. Concentration of minerals, roetals, and PCB's in sediments collected from
the Des Plaines River (RM 273-286), 1987. All concentrations are reported in ppm
except Hg (ppb). Detection limits are in parentheses, concentrations less than
detection limits are noted as
-------
Tazik
Table 5. Concentration of minerals, metals, PCBs, dieldrin, and heptachlor
epoxide in macrophytes collected from the Des Plaines River (PM 273-286), 1986
and 1987. Samples designated by plant part were collected in 1987; other samples
were collected in 1986. All concentrations are reported in ppm except Hg (ppb).
Detection limits are in parentheses; concentrations less than detection limits
are denoted
-------
Lower Des Plaines River
Table 5 (concluded) .
Pb Se Sn
Macrophyte (1.16) (2.42) (2.72)
Eleocharis acicularis
roots
shoots
18.8
-------
Tazik
o.ooo
Distances
5.000
Myriophyllum
P. pecUnatus
P. nodosus
Sagittaria
P. pectlnatus
P. pectinatus —i
P. nodosus —' I
P. cfispus '
Myriophyllum
Vallisnerla 1
£. acicularls '
Vallisneria
Fig. 6. Dendogram of cluster analysis of cadmium, chromium, mercury and zinc
concentrations in macrophyte roots. The average linkage method is used, distance
is measured in Euclidean distance (SYSTAT™).
and (4) differential uptake of
substances (Campbell et al. 1985,
Kraus et al. 1986, Kraus 1988, Miller
et al. 1983). These data, are not
sufficient to establish a statisti-
cally significant relationship between
substance concentrations in sediments
and in plants; 65% of 105 cases
examined by Campbell et al. (1985)
showed no relation between these
parameters. Nor do these data define
individual macrophyte uptake and
translocation processes. Nonetheless,
substantial quantities of toxic
substances were identified in sedi-
ments and macrophyte tissues. Once
substances are concentrated by macro-
phytes, they may be stored in macro-
phyte tissues or released into the
environment. For Co, PCBs, and Hg,
which were concentrated by macrophytes
to levels that exceeded those in
sediments, release into the environ-
ment could pose a serious threat to
other biota. Conversely, harvesting
contaminated plants could be used as
part of a rehabilitation plan. Cd, Co,
Cr, V, Sn, and Se which are concen-
trated primarily in roots and rhizomes
could also be removed from the system
by harvesting macrophytes; moreover,
this removal would not be complicated
by seasonal senescence of shoots.
In conclusion, there is now locally
abundant aquatic vegetation in the
Lower Des Plaines River (RM 273-286).
As roacrqphyte populations increase,
water and habitat quality should
improve (e.g., reduced turbidity,
increased oxygen levels, larger and
more diverse invertebrate populations,
and an improved fishery). Toxic
substances are clearly a part of this
aquatic system, and interactions of
aquatic plants and toxic substances,
particularly those in sediments, can
affect habitat quality. Rooted macro-
phytes can move toxic substances from
deeper sediments to the water column
and top sediments via uptake and
acropetal translocation.
Conversely, substances that are
concentrated and remain in below-
ground plant parts are unavailable to
other biota, at least until those
parts senesce. Removal of macrophytes
96
-------
Lower Des Plaines River
that have accumulated toxic substances
may provide a mechanism for rehabili-
tating polluted aquatic systems.
Acknowledgments
The project was conducted in con-
junction with R.E. Sparks, Illinois
Natural History Survey. I thank K.D.
Blodgett and C. Mayer for assistance
during field collections, S.Sobaski
and D. Glosser for CIS and digitizing
work, S. Wood and J. Sandberger for
completing chemical analyses, and D.
Austen for assistance with data
analyses. L.L. Osborne's critical
review of this manuscript is greatly
appreciated, as is J. Waite's
editorial assistance. This research
was supported by the Commonwealth
Edison Company, Chicago, Illinois.
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succession in relation to river
vegetation and management.
Internationale Verhandlungen Vereingun
fur Theoretische und Angewandte
Limnologie 20:1429-1434.
DiGiulio, R.T. and P.F. Scanlon. 1985.
Heavy metals in aquatic plants, clams,
sediments from the Chesapeake Bay,
U.S.A.: Implications for waterfowl.
The Science of the Total Environment
41:259-274.
Donnermeyer, G.N. and M.M. Smart.
1985. The biomass and nutritive poten-
tial of Vallisneria americana in Navi-
gation Pool 9 of the Upper Mississippi
River. Aquatic Botany 22: 33-44.
Engel, S. 1985. Aquatic cxmmunity
interactions of submerged macrophytes.
Wisconsin Department of Natural
Resources Technical Bulletin No. 156,
Madison.
97
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Tazik
Everard, M. and P. Denny. 1985. Flux
of lead in submerged plants and its
relevance to a freshwater system.
Aquatic Botany 21:185-193.
Fassett, N.C. 1967. A manual of
aquatic plants. 2nd edition. MoGraw
Hill Book Co., Madison, WI.
Gabrielson, J.O., M.A. Perkins, and
E.B. Welsh. 1984. The uptake,
translocation and release of
phosphorus by Elodea densa.
Hydrobiologia 111:43-48.
Havera, S.P., F.C. Bellrose, H.K.
Archer, F.L. Paveglio, Jr., D.W.
Steffeck, K.S. Lubinski, R.E. Sparks,
W.U. Brigham, L.C. Coutant, S.W.
Waite, and D. McCormick. 1980.
Projected effects of increased
diversion of lake Michigan water on
the environment of the Illinois River
valley. Final report to U.S. Array
Corps of Engineers, Chicago District.
Illinois Natural History Survey,
Champaign.
Hill, B.H. 1979. Uptake and release of
nutrients by aquatic macrophytes.
Aquatic Botany 7:87-93.
Howard-Williams, C. and G.M. Lenton.
1975. The role of the littoral zone in
the functioning of a shallow tropical
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5:445-459.
Hutchinson, G.E. 1975. A treatise on
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report, 1982-1983. IEPA/WPC/84-024.
Jaynes, M.L. and S.R. Carpenter. 1986.
Effects of vascular and nonvascular
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Kraus, M.L., P. Weis, and J.H. Crow.
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Mclntosh, A.W., B.K. Shephard, R.A.
Mayes, G.J. Atchison, and D.W. Nelson.
1978. Some aspects of sediment
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heavy metals in a contaminated lake.
Journal of Environmental Quality
7:301-305.
Miller, G.E., I. Wile, and G.G.
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accumulation of selected metals in
members of the soft-water macrophyte
flora of Central Ontario lakes.
Aquatic Botany 15:53-64.
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39-50 in W.T. Mason (editor). Methods
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Workshop Proceedings, US Fish and
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aquatic vascular plants. Edward Arnold
Publishers Ltd., London.
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Phosphorus transfer from sediments by
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Sparks, R.E. 1984. Ecological river macrophytes. Freshwater Biology
structure and function of major rivers 11:369-380.
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1984(8). Illinois Natural History
Survey, Champaign.
Sparks, R.E., P.P. Tazik, K.D.
Blodgett, G.L. Warren, and M.J.
Wetzel. 1986. Des Plaines River
long-term monitoring program, Phase I.
Aquatic Biology Technical Report
1986(6). Illinois Natural History
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program, Phase II. Aquatic Biology
Technical Report 1987(4). Illinois
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Tazik P.P. 1988. Des Plaines River
long-term monitoring program, Phase
III. Aquatic Biology Technical Report
1988(5). Illinois Natural History
Survey, Champaign.
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Partitioning of trace metals in
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149:43-52.
U. S. Environmental Protection Agency.
1976. Quality criteria for water.
EPA-440/9-76-023. Washington, DC.
Welsh, P. and P. Denny. 1976.
Waterplants and the recycling of heavy
metals in an English lake.
Proceedings, Trace Substances and
Environmental Health 10:217-223.
Westlake, D.F. 1973. Aquatic
macrophytes in rivers. A review.
Polskie Archiwum Hydrobiologii
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three mapping procedures developed for
99
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Use of Acute and Chronic Bioassays to Assess the Applicability
of Selected Advanced Wastewater Treatment Technologies
for the Green Bay Metropolitan Sewerage District
John Kennedy
Green Bay Metropolitan Sewerage District
P.O. Box 19015
Green Bay, WI 54307-9015
Abastract
Several state-of-the-art advanced wastewater treatment technologies were
evaluated during pilot studies. All treatment endpoints received extensive
chemical analysis as well as whole effluent bioassays. Results indicated that
effluent from the existing carbonaceous treatment is toxic most of the time,
whereas nitrified effluent streams showed no acute or chronic bioassay failures.
Subtle effects on Ceriodaphnia were, however, observed. Tertiary treatment
typically reduced these effects, though one treatment system introduced another
source of toxicity inherent to the chemical process. Interpretation of bioassay
results were further complicated by inconsistencies within the chronic test
statistics procedure. These observations support the need to review all data
generated during bioassays, such as mean growth rates or reproduction, rather
than chronic "pass/fail" endpoints alone.
Introduction
The Green Bay Metropolitan Sewerage
District (GBMSD) provides wastewater
treatment for nine communities and two
large pulp and paper industries. The
existing facilities were placed into
operation in 1975 and were designed to
meet the community's needs through the
year 1990.
The District's operation has consis-
tently maintained compliance with EPA
categorical effluent limits of 30 mg/1
BOD and TSS, and a 1.0 mg/1 total
phosphorus limit as established by an
International Joint Commission (IJC)
Agreement between the U.S. and Canada.
The treatment plant effluent dis-
charges to the Fox River at the mouth
of Green Bay, Lake Michigan. Histor-
ical water quality problems of the Fox
River and lower Green Bay have been
well documented (Bertrand et al. 1976;
Day 1978; Howmiller and Beeton 1971;
Patterson et al. 1975; Peterman et al.
1980; Smith et al. 1988; Sullivan, and
Delfino 1982). The lower Fox River/
Green Bay area has been designated as
one of the 42 "Areas of Concern" by
the IJC.
In 1987 the Wisconsin Department of
Natural Resources (WDNR) issued notice
of its intent to reissue a Wisconsin
Pollutant Discharge Elimination System
(WPDES) discharge permit to the GBMSD.
The permit was to contain new and more
stringent limits for CBOD, chlorine
residual, fecal coliform and whole
effluent toxicity, along with recom-
mendations pertaining to future moni-
toring and effluent limits for certain
toxic compounds, including ammonia,
heavy metals and residual organics.
The Wisconsin DNR has recently
developed new administrative codes
NR105 and 106 for the control of
toxics from point sources. These codes
address over 100 toxic compounds, and
also enable the WDNR to place a
bioassay effluent limit or monitoring
requirement in a WPDES permit.
Existing effluent data indicated the
possibility of noncompliance with
future permit conditions. Whole
effluent bioassays performed in 1987
showed both acute and chronic failure
to fathead minnows and Ceriodaphnia
(Buttke and Rades 1987a,b).
GBMSD therefore commissioned a facili-
ty plan to address these and other
issues. A major component of the plan
included extensive pilot studies using
state-of-the-art Advanced Wastewater
100
-------
Wastewater Treatment Plants
Treatment (AWT) technologies. The
pilot studies were designed to evalu-
ate alternative AWT processes likely
to ensure compliance with the proposed
and potential future permit
requirements.
Methodology
Pilot studies were conducted in 1987
and 1988, with the majority of work
occurring between November, 1987 and
March, 1988. Processes investigated
include:
• Single-stage nitrification (identi-
fied as B12)
• Powdered Activated Carbon (PACT™)
nitrification
• Alum/sulfide treatment
• High-lime treatment
• Filtration
• Carbon adsorption
Four pilot study tests evaluated
single-stage nitrification followed by
the AWT systems. Four more tests
evaluated the PACT™ process followed
by the AWT systems.
Each location within the pilot system
identified as a possible treatment
endpoint was sampled intensively for
chemical parameters and whole effluent
bioassays, including: activated sludge
nitrified effluent (B12); B12 after
chlorination/dechlorination; PACT™
secondary effluent; PACT™ filter
effluent; alum/sodium sulfide filter
effluent; alum/sodium sulfide carbon
column effluent; high lime recarbona-
tion clarifier effluent; high lime
filter effluent; high lime carbon
column effluent; and existing carbona-
ceous effluent (B15). A total of eight
7-day bioassays were performed on
eight effluents and a Green Bay dilu-
tion water control. All tests were
conducted in strict accordance with
EPA protocol (Horning and Weber 1985).
The acute bioassay measures percent
survival in 100% effluent. The chronic
bioassay determines any sublethal
effects, measured as reduction in
growth for fathead minnows, or a
decrease in Ceriodaphnia reproduction.
The chronic "pass/fail" endpoint is
based on observed sublethal effects at
a particular effluent concentration,
termed the "Instream Waste
Concentration" (IWC). This
concentration is defined as the
percentage composition of the effluent
in the receiving water stream assuming
a stream flow of 25% of the historical
minimum 7-day flow expected once in
ten years (7-day Q10). The chronic test
statistics calculate a "No Observed
Effect Concentration", or N.O.E.C. The
GBMSD IWC was calculated to be 34%.
Therefore, the N.O.E.C. calculated
from a given test must be at least 34%
to pass the chronic criterion.
Results and Discussion
A total of eight 7-day test periods
were utilized for bioassay analysis.
Four of these included full-scale
nitrification as the effluent source
to the tertiary systems, while four
runs reflect use of the PACT™ pilot
plant effluent to drive the tertiary
systems. Each 7-day run is identified
by the "mode" of nitrification, e.g.
"B12" or "PACT™", followed by the
chronological run number.
Table 1 presents an overall summary of
the 63 total acute and chronic
bioassays performed. A total of six
acute failures were noted; five in the
existing carbonaceous effluent
(B14/15), and one in the alum filter
effluent. The B14/15 mortalities were
presumably due to high ammonia levels,
while residual sulfide was believed to
be responsible for the alum mortality.
Referring to Table l, a total of 12
chronic failures were noted during the
entire study. Six of these
corresponded to the B14/15 effluent.
Of the remaining six failures, three
were in the alum filter, two in the
lime filter effluent, and one in the
101
-------
Kennedy
Table 1. Number of acute and chronic bioassay failures observed during the GEMSD
Pilot Study.
Acute Bios
is say
Results
Chronic Bio*^sav Results
Fathead
Minnow CeriodaDhnia
Effluent
Full Scale Nitrification
B12
B12 Tchlor/dechlor)
Alum Filter Eff.
Alum CC Eff.
Lime Recarb Eff.
Lime Filter Eff.
Lime CC Eff.
N
4
2
4
4
4
4
4
Failures
0
0
0
0
0
0
0
NF
4
2
4
4
4
4
4
ailures
0
0
1
0
0
0
0
N
3
2
3
3
3
3
3
Fathead
Minnow
Failures
0
0
0
0
0
1
0
Oeriodaphnia
N
4
2
4
4
5
3
4
Failures
0
1
0
0
0
1
0
PACT™ Nitrification
PACT™ Secondary Eff.
PACT™ Filter Eff.
Alum Filter Eff.
Alum CC Eff.
Lime Recarb Eff.
Lime Filter Eff.
Lime CC Eff.
Carbonaceous
B14/15
4
4
0
0
4
4
4
4
4
4
4
0
0
0
0
0
4
4
4
4
4
0
0
4
4
0
0
0
0
0
0
0
4
4
4
4
4
0
0
0
0
0
4
4
4
4
6
2
4
0
0
3
0
0
0
0
B12-1 (chlorination/dechlorination)
effluent. Figure 1 presents a
graphical depiction of chronic
bioassay results for run B12-3.
Results are displayed for both fathead
minnow and Oeriodaphnia. All graphs
contain results from the 100% effluent
analyses only. Each summary graph for
fathead minnow data includes percent
survival (bar graphs represent actual
percent survival) and mean final
weights including 95% confidence
interval. N.O.E.C. values, as
calculated by WCNR computer programs,
are listed in parentheses above each
bar or mean weight interval. Results
for Ceriodaphnia include percent
survival (again shown by bar graphs)
and mean number of offspring per
Individual including 95% confidence
interval. N.O.E.C. values are also
listed above each bar or mean number
interval. The following paragraphs
(tipr^isp bioassay results in more
detail, grouped by treatment system.
Carbonaceous Effluent (B14/15)
Significant detrimental effects were
noted on all B14/15 bioassays. For
fathead minnows, five of seven chronic
tests yielded failures. One out of
eight f^rifx^phnia Ivggts failed. As
previously noted, ammonia is thought
to be the main source of toxicity.
Fathead minnows are known to be highly
102
-------
Wastewater Treatment Plants
55
Survive!
PILOT STUDY CHRONIC BIOASSY RESULTS
CERIODAPHNIA
Run 812-3 (N.O.E.C. Values Printed in Parentheses)
Percent Survival - 10055 Effluent
MOOT) (100X1
(100X1
B12 >12
CWor/
(100X1(1001) (100X)
I
=
(
OOX
i
I
1
Mm Mun _Un» ukn u™
Eif EB. at tn. en
SAMPLING LOCATION
(100X1
%
Survival
PILOT STUDY CHRONIC BIOASSY RESULTS
FATHEAD MINNOW
Run B12-3 (N.O.E.C. Values Printed in Parentheses)
Percent Survival - 100% Eflluent
SxS
XSS
SxS
vxs
(100
X) (1»
J]
a*}
wr
I
oox
1 (I
OCX)
I
I
00X1
!
(341)
EH CH Cfl
SAMPLING LOCATION
Mean Number of Offspring with
95% Confidence Interval —
100% Effluent
til
CW«r/
Ml* Ab«l Urn. Um
FIW CC IbMk nMv
CR. DL Dl Dl
SAMPLING LOCATION •
Mean Final Weights (mg)
With 95% Confidence Interval -
100% Effluent
30
Mean u
Number M
of
Offspring ift.
10
t
o<
T O«X)
(MX) 1
!
(MX)
f
(MX)
!
(IOOX)
1
(MX)
1
(IOOX)
I
0.7
Mean "•'
Final "
Weights 0.«
OJ
0.1
(IOOX)
(MX) <*« (M
n
(101
W (M
(
-------
Kennedy
Samples from run B12-3 showed
identical Ceriodaphnia results to
urtchlorinated B12 effluent.
PACT™ Nitrification
Bioassays were performed on two
effluents from the Zimpro PACT™ pilot
plant: secondary effluent; and, filter
effluent. No chronic failures were
noted throughout the four PACT™ runs.
Fathead minnow results were very
similar to the control. Ceriodaphnia
reproduction was slightly effected
during runs PACT™-3 and PACT™-4.
Alum AWT
Bioassays were performed on two
effluents from the alum AWT system:
alum filter effluent; and, alum carbon
column effluent.
Fathead minnow results showed no
significant difference from the con-
trol on all eight runs except for run
B12-3, when the filter effluent showed
a slight effect (N.O.E.C. of 34%).
Ceriodaphnia results, however, showed
significant toxicity-related effects.
Recall that run B12-1 showed an acute
toxicity failure for Ceriodaphnia in
alum filter effluent. This problem was
believed to be related to residual
sulfide from the alum/sodium sulfide
treatment, in conjunction with the
short detention time of the pilot
system. A secondary aeration/holding
tank was incorporated into the system
hoping to drive off any residual
sulfide, and no more acute failures
were observed. However, chronic
effects were noted throughout the
remaining bioassays. Ihree of the
eight alum filter effluent Cerio-
daphnia bioassays failed the repro-
duction test. However, even the five
tests which passed showed obvious
detrimental effects. It was further
noted that during four out of the
eight runs, the carbon column treat-
ment step improved conditions to the
point that the bioassay results were
not significantly different from the
control. The remaining four runs
showed improvement, but to a lesser
degree.
It was thought, at first, that the
added aeration step had alleviated the
sulfide problem, as the next few
bioassays yielded no failures. It
later became apparent that a toxicity
problem in the alum system was still
present. In order to verify the
effectiveness of the aeration tank,
five grab samples of filter effluent
were collected during run PACT™-4.
Results showed a range of 41 to 74
/ig/1 (ppb) residual sulfide. One
sample was split prior to analysis,
with one aliquot receiving an extra
hour of vigorous aeration in the
laboratory prior to analysis. This
extra aeration step reduced the resi-
dual sulfide level from 41 to 35 jjg/1.
Residual sulfide levels at these
concentrations could be the source of
toxicity in the alum system. The EPA
"Gold" book criterion for undissoci-
ated HjS for fish and aquatic life (in
fresh and marine water) is 2.0 /^g/1.
Residual sulfide levels found in the
alum system, however, are not identi-
cal in form to undissociated HjS.
Sulfide exists in three forms in
water; HjS, hydrosulfide (HS-) ions or
sulfide (S=) ions. The proportion of
each is controlled primarily by pH. As
pH drops below 9.0, the proportion of
undissociated H^S (and therefore the
toxicity) increases. The aeration step
which was added to the alum pilot
system increased the alum filter pH
from approximately 7.1 to 8.0. This
aeration-induced pH increase may have
served to reduce the sulfide toxicity,
rather than reducing the sulfide
concentration.
To further investigate the sulfide
toxicity problem, the pilot system was
operated again in May, 1988. Cerio-
daphnia bioassays were performed on
alum filter effluent, both before and
after a chlorination/dechlorination
procedure. The chlorination process
was suggested as a possible means of
oxidizing any residual sulfide. The
chlorination/dechlorination procedure
104
-------
Wastewater Treatment Plants
was identical to that which was used
on earlier bioassays, using sodium
thiosulfate to dechlorinate.
Results of sulf ide analyses indicated
that the chlorination process did
remove approximately half of the
residual sulfide, though daily
variability was considerable. Sulfide
levels after chlorination ranged from
<2 /ig/1 to 78 jug/1. Bioassay results
were very similar to the previous
eight tests, showing significant
effect on Ceriodaphnia reproduction.
The chlorination/dechlorination
process reduced the level of toxicity,
but to only a minor degree.
High
AVTT
Bioassays were performed on three
effluents from the high lime AWT
system: recarb clarifier effluent;
lime filter effluent; and, carbon
column effluent.
Fathead minnow results showed no
significant difference from the
control on five of the eight (total)
runs. Run B12-2 showed a significant
effect for all three effluents,
presumably caused by very low
(approximately 20 mg/1) alkalinity
concentrations observed in the lime
system during this run. Lime system
alkalinity values measured during the
other pilot runs were all above 30
mg/1. It is thought that the lower
than average operating load from one
of the two paper mill influent streams
is the reason for the low aUcalinities
seen during run B12-2. Alkalinity
values close to 20 mg/1 have the
effect of increasing the toxicity of
heavy metals and other compounds. It
is believed that the B12-2 run results
reflect this phenomenon.
In order to prove that the observed
toxicity was alkalinity related, a
duplicate series of lime system
effluents with added NaHCQj were
tested during the next bioassay.
However, alkalinities in the lime
system returned to the 30-40 mg/1
range, and no toxicity was observed in
either sample series.
The high lime system consumes
alkalinity during the chemical
reactions involved during treatment.
Even though the other seven bioassays
showed no repeat of this occurrence,
it should be considered a potential
problem for future full-scale
application.
The lime filter effluent sample failed
the fathead minnow growth test on run
B12-3 (shown on Figure 1 as <34%).
However, it appears that this failure
is more related to a statistical error
than to toxicity. The confidence
interval around the mean weight value
is extremely small, normally an
indication of high data reliability.
This narrow range of variability,
however, allows the WENR statistics
program to detect very small
differences when compared to the
control. In effect, if the replicate
weight variations had been greater,
the N.O.E.C. would have been much
higher, even if the mean value
remained the same. Realistically,
therefore, this test should not be
considered a "fail".
An unusual event occurred with the
fathead minnow bioassays during run
PACT™^. Relatively high mortalities
were observed in the lime system
samples for one day of the test,
corresponding to effluent collected on
February 18, 1988. The number of
mortalities decreased as treatment
advanced (i.e. most mortalities in
recarb clarifier effluent, least in
carbon column effluent). No further
mortalities were observed. Currently,
there are no obvious explanations for
this occurrence. Review of chemical
data shows no obvious problems, and no
operational difficulties were noted.
Even so, no acute or chronic test
failures were observed for the run.
Ceriodaphnia results from high lime
system bioassays indicate a subtle
recurring effect on reproduction,
particularly in the lime filter
105
-------
Kennedy
Table 2. Ammonia concentrations measured in bioassay samples during the GEMSD
Pilot Study. (Weekly average value followad by daily range.)
Run
B12-1
B12-2
B12-3
B12-4
PACT™-1
PACT™-2
PACT™-3
PACT™-4
Ammonia-Nitrogen (ma/1)
B14/15
17
13
22
14
B14/15
16
13
18
14
B12
2.3 (
-------
Wastewater Treatment Plants
during run PACT™-2, at 12.1 rog/1. The
weekly average for this run was 3.0
mg/1. Bioassay results from PACT™-2
and B12-3 indicate a slight effect
noted for fathead minnow growth,
though no test failures occurred.
Weekly average ammonia values for
existing carbonaceous effluent
(B14/15) are also included in Table 2.
It is interesting to note that for an
average ammonia concentration of
approximately 16 mg/1 (entire study),
failure rates for acute and chronic
bioassays were 63% and 71%,
respectively.
Bioassav Procedure Concerns
The 7-day chronic bioassay test
procedures, as conducted during the
GEMSD pilot study, have been developed
primarily by the EPA. Several changes
in techniques and procedures have been
made during recent years, and even
today, the methods appear to be in a
state of continuing evolution.
The GEMSD experience with the test
methods, themselves, was mostly
positive. Overall, the tests appear to
be credible and repeatable. It is
interesting to note that the two
organisms seem to respond quite
differently to differing toxic agents,
thus supporting their selection as
complementary test animals.
Bioassay results have identified
possible toxicity problems affiliated
with some of the treatment systems
tested, even when results of chemical
analysis do not clearly show such
evidence. However, during review of
multiple data sets, several
inconsistencies were noted relating to
the statistical program which
calculates final N.O.E.C. values.
For example, Green Bay dilution water
used during the first three runs of
the pilot study caused significant
mortality to fathead minnows, both in
the control samples themselves and in
the 34% effluent samples. The problem
appeared to be excessive numbers of
bacteria or fungi in the bay water.
Fish that died were observed to have
fungus-like growths in their gut, and
a mat-like layer developed on the
bottom of the 34% effluent beakers
each day. (This problem was eliminated
by changing the water collection site
from the east shore to the west
shore.) The statistics program
responded to this condition by
lowering the "standards" of the test,
in one case assigning a N.O.E.C. value
of 100% to an effluent that achieved
only 57% survival in 100% effluent. A
later test, with 100% control sur-
vival, calculated a N.O.E.C. value of
34% for an effluent that achieved 87%
survival in 100% effluent. Therefore,
it appears that it is to the discharg-
ers advantage to conduct effluent
bioassays using dilution water that is
mildly toxic. Clearly, improvements in
the statistical analysis program would
seem appropriate.
Another inconsistency involves the
previously discussed situation where
replicate variability is very low,
allowing the statistics to detect very
small differences between mean values
of the control and the effluent. This
means that the statistics seem to
expect variability between replicates,
and that a high degree of confidence
regarding the actual test data may
actually result in a lowered N.O.E.C.
value. It would seem prudent, there-
fore, to review all bioassay results,
such as that included in Figure 1,
rather than to judge the test based
strictly on N.O.E.C. values.
The GEMSD experience regarding
EPA/WDNR bioassay test procedures was
acceptable, though some inconsis-
tencies with the statistics program
were noted. Our experience tends to
support the need to review bioassay
results from a biological as well as a
mathematical perspective. Bioassay
data generated were useful in the
final selection process within the
GEMSD Facilities Plan. Figure 2 con-
tains a comparison of bioassay results
between existing carbonaceous effluent
107
-------
Kennedy
CHRONIC BIOASSAY RESULTS
100
90
60
TO
60
50
40
30
20
10
FATHEAD MINNOW
(100%)
RUN
RUN «2
RUN «3
(34%)
RUN «4
ESS Control ESS Nitrified S CefbonaceoiM
HtVjent BTluent
CHRONIC BIOASSAY RESULTS
CERIODAPHNIA
OOOV (100%)
(100%)
(WOW
RUN #1
RUN «2
RUN «3
RUN #4
53 Control E3Mllrined B Corbonoccou*
BTluent ETIVicnt
CHRONIC BIOASSAY RESULTS
FATHEAD MINNOW
1.0
o.e
0.8
0.7
S OJ6
I
I
I
0.3
O.2
0.1
OX)
RUN #1
(04%)
RUN «2
RUN #3
(100%)
RUN *4
K3 Control O3 Nitrified CD CarbonaoMw
BTYj»nt
CHRONIC BIOASSAY RESULTS
CERIODAPHNIA
1100%)
(X>OK)
(34%)
(34%)
(34%)
RUN #1
RUN #2
RUN *3
RUN *4
C^MItrtfled CD Carbonaceous
BlkMft BHuent
Figure 2. Comparison of bioassay results between GEMSD carbonaceous effluent,
nitrified effluent, and Green Bay control water.
and full scale nitrification. Results
from bioassays performed on nitrified
effluent show a significant improve-
ment over carbonaceous effluent. In
fact, nitrified effluent results show
only minimal variation from the
receiving water controls.
Summary
A total of eight 7-day chronic
bioassays were performed on eight
effluents during the GEMSD pilot
study. Excluding existing carbonaceous
effluent (B14/15), only one acute and
six chronic failures were observed
throughout the entire test period.
Effluent from the full scale
nitrification quadrant (B12) passed
all acute and chronic bioassays.
Fathead minnow results from all runs
showed no significant difference from
the control. A slight effect was noted
in Oeriodaphnia reproduction, though
not to the level of test failure.
Results from the PACT™ pilot plant
effluent were very similar to B12
effluent with no apparent effect noted
on fathead minnows, but a slight
108
-------
Wastewater Treatment Plants
effect noted
reproduction.
in
Results of the bioassay program show
concern regarding residual sulfide
levels in the alum/sodium sulfide
treatment system. Significant
reductions in Ceriodaphnia
reproduction were noted, including one
acute and three chronic failures.
Subsequent testing indicated that
residual sulfide is a definite problem
with this form of treatment, though it
is not known how the pilot scale
results would apply to a full-scale
operation.
Three separate effluents of the high
lime system were analyzed. The
effluent from this treatment system is
characteristically low in alkalinity.
Bioassay results have shown that the
effluent alkalinity must be maintained
at 30 mg/1 or more in order to
minimize increased toxicity from
various compounds. A slight reduction
in Ceriodaphnia reproduction was noted
in the lime system effluents and may
be related to the system itself.
Bioassays on effluent using 00^ gas
for pH adjustment, instead of sulfuric
acid, showed no apparent improvement.
High lime system results are difficult
to assess completely, as the nitrified
effluent which fed the lime system was
already relatively nontoxic. However,
if bioassay results from the
influentto the lime system showed
subtle effects as compared to the
controls, the lime treatment typically
improved the results. As with the alum
system, the carbon column polishing
step significantly improved the
C^riodaphnia bioassay test results if
the influent stream showed depressed
reproduction.
Several inconsistencies were noted
relating to the statistical program
which calculates final N.O.E.C.
values. Results obtained during the
GBMSD pilot study support the need to
review all bioassay results, such as
graphical plots of actual data, rather
than to judge the test based strictly
on N.O.E.C. values.
Aetocwledrjanents
The Institute of Paper Chemistry,
Appleton, Wisconsin, was contracted to
conduct the bioassay analyses. George
Buttke served as Project Officer,
while Dave Rades served as Project
Administrator. The pilot study was a
joint effort involving all divisions
with the GEMSD. CHJ1 Hill was the
Facilities Plan consultant. This paper
was accepted for presentation at the
62nd Annual WPCF Conference in San
Francisco, but was cancelled due to
the earthquake of October 17, 1989.
Author
John Kennedy is the Laboratory
Services Manager for the GEMSD, P.O.
Box 19015, Green Bay, Wisconsin,
54307-9015.
References
Bertrand, G., J. Lang and J. Ross.
1976. The Green Bay Watershed: Past/
Present/Future. University of
Wisconsin Sea Grant. Technical Report
#229. 300 p.
Buttke, G. and D. Rades. 1987a.
Effluent Bioassays for Green Bay
Metropolitan Sewerage District." The
Institute of Paper Chemistry.
Report No. 3625-07.
Buttke, G. and D. Rades. 1987b.
Effluent Bioassays for Green Bay
Metropolitan Sewerage District. The
Institute of Paper Chemistry. Report
No. 3625-01.
Day, H.J. 1978. Water Use Implications
for the Bay. In: Research needs for
Green Bay, H.J. Harris and V. Garsow
Eds. University of Wisconsin Sea
Grant. WIS-SG-78-234. pp. 103-112.
Horning, W.B. and C.I. Weber (eds).
1985. Short-term Methods for
Estimating the Chronic Toxicity of
Effluents and Receiving Waters to
Freshwater Organisms. EPA/600/4-85-
109
-------
Kennedy
014. U.S. EPA, Cincinnati, OH.
Howmiller, R.P. and A.M. Beeton. 1971.
Biological Evaluation of Environmental
Quality, Green Bay, lake Michigan." J.
Water Pollution Control Federation
43(1): 123-133.
Patterson, D., E. Epstein and J.
McEvoy. 1975. Water Pollution
Investigation: Lower Green Bay and
Icwer Fox River. Wisconsin Department
of Natural Resources, Rpt. No. EPA-
905/9-74-017 (1975).
Peterman, P.H., J.J. Delfino, D.J.
Dube, T.A. 1980. Gibson and F.J.
Priznar. "Chloro-organic Coropounds in
the lower Fox River, Wisconsin." In;
Hydrocarbons and halogenated
hydrocarbons in the aquatic
environment. B.K. Afghan and D. Mackay
Eds. Plenum Publishing Publishing
Corp. pp. 145-160.
Smith, P.L., R.A. Ragotzkie, A.W.
Andren and H.J. Harris. 1988. Estuary
Rehabilitation: The Green Bay Story.
Oceanus, 31(3): 12-20 (1988).
Sullivan, J.R. and J.J. Delfino. 1982.
A Select Inventory of Chemicals Used
in Wisconsin's Lcwer Fox River Basin."
University of Wisconsin Sea Grant.
WIS-SG-82-238. 176 p.
110
-------
Land Use influence on Fish Ocamunities
in Central Tnri-ia'na streams
James R. Gammon, Clifford W. Gammon, and Mary K. Schmid
Department of Biological Sciences, DePauw University
Greencastle, Indiana 46135
Abstract
In recent years a number of large rivers including the Ohio and Wabash Rivers
have experienced better environmental conditions and fish communities principally
because of improvements in point-source discharges. Further progress is not
likely to occur until NPS sources are reduced. The trends in smaller streams in
agricultural landscapes are less encouraging. The fish communities in several
stream systems in the Wabash River drainage have undergone sharp changes in
character during the past decade or two. The sequence of change is a sudden loss
of darters, followed by the disappearance of centrarchids, and then smallmouth
bass. In extreme cases this is followed by a loss of Moxostoma species and a
variety of minnows as more and more of the watershed is converted to tilled
fields. Sporadic spills of fertilizer and feed lot wastes no doubt accelerate and
confound the overall trends. The changes are not gradual and linear. The presence
of "good" refugial tributaries permits a natural "residing" during benevolent
years. The trends observed suggest that streams which have only recently lost
their smallmouth bass populations may be rehabilitated with relatively modest
effort and expense.
Introduction
The influence of agricultural on
Indiana streams can be roughly
categorized into (a) point source
influences such as animal feed lots
and fertilizer spills and (b) non-
point source (NPS) influences
including tilled fields and pastures.
Agriculture occupies 70% of Indiana
lands and 78% of this land is devoted
to rowcrop agriculture (55% of
Indiana), mostly corn and soybeans. Of
the estimated 108 million tons of soil
annually eroded from Indiana land,
nearly four-fifths (79%) originates
from tilled fields that occupy slight-
ly more than half of Indiana. Perhaps
the Illinois rule-of-thumb estimate
states the problem most succinctly:
for every bushel of corn harvested,
two bushels of soil are lost.
It is difficult to convince most
people, including farmers, politi-
cians, and engineers, that soil is a
pollutant although they might readily
agree that pesticides, herbicides, and
fertilizers do pollute water. It is
also extremely difficult to document
the chronic effects of NPS pollution
apart from the sporadic fish kills
caused by specific agricultural
activities.
In recent years, a number of large
rivers including the Ohio and Wabash
Rivers have experienced better
environmental conditions and improved
fish communities principally because
of refinements in waste treatment of
point-source discharges. Further
progress is unlikely until NPS
contributions are reduced. In the
Wabash River the number of catchable
game fish is more than 10 times as
great as it was in the 1970's and the
non-game species have similarly
increased. Furthermore, the size of
fish is bigger. About the only species
which have declined are carp and
gizzard shad. For the first time in
over 20 years, predator fishes in the
Wabash River are numerous enough to
control gizzard shad.
Why this rather sudden improvement? It
is partly because of improved waste
treatment of towns and industries
within the basin. Decomposable organic
matter (BOD) today is only 2.5 to 3.0
mg/1 today compared to 4.5 to 5.0 mg/1
15 years ago (Gammon 1989). That
translates into better oxygen condi-
111
-------
Gammon
Standing Crop - kg/ha
100
10
0 10 20 30 40 50 60 70 60 90 100
% Plsclvores & Insectlvores
Figure 1: Changes in the fish
communities of central Indiana streams
under agricultural development.
tions through reduced dissolved oxygen
deficits. An additional contributing
factor might well be the 1983 PIK
program, a year during which 25% less
corn and soybeans were grown with
concomitant "reductions in applications
of herbicides and pesticides.
In order to further improve river
ecosystems nutrient delivery to the
river must be reduced. Half of the
carbonaceous BOD entering the middle
Wabash is estimated to come from
agriculture (HydroQual 1984).
Phytoplankton, mostly diatoms, colors
the Wabash River brown during the
summer with as much as 100,000 algal
cells per ml and chlorophyll-a
concentrations exceeding 150 ug/1.
High densities of algae produce two
undesirable ecological effects: (a)
the dissolved oxygen level is
depressed at night and (b) the
turbidity interferes with the ability
of predator fish such as bass and
walleye to locate food. In one segment
of the Wabash it has also caused
fishkills on at least two occasions
(Parke 1985, Parke and Gammon 1986).
There is also an undesirable recrea-
tional effect. Few people care to
swim, canoe, or fish in turbid rivers
which are perceived as being "dirty".
The trends of fish communities in
smaller
streams
in Indiana's
agricultural landscapes are quite
different and not nearly as
encouraging. Some are known to have
undergone sharp changes in character
during the past decade or two. It is
likely that others are going to follow
suit or, perhaps, have already done so
without our knowledge.
The pattern of change was demonstrated
during a Model Implementation Project
study of three central Indiana stream
systems (Gammon et. al. 1983).
Moderate agricultural development of a
watershed may only result in an
increase in fish standing crop with no
measureable change in the darter,
sunfish, and bass components of the
community (Figure 1). Further
agricultural expansion, however,
ultimately results in a sudden loss of
darters, centrarchids, and possibly
catostomids with expansions of
omnivores and detritivores. Further
changes occur through the loss of
Moxostoma species (redhorse) and a
variety of minnows as more and more of
the watershed is converted to tilled
fields. The changes occur first in
smaller streams and then progress
downstream.
Methods and Materials
The streams discussed in this paper
are located in rural areas of Indiana
and are not influenced strongly by
industry, mining, or municipalities
(Figure 2). The fish communities of
most of the included streams have been
intensely examined at multiple
stations over several years during the
past 12 years. Stream segments
measurably influenced by towns or
industries have been excluded from the
analyses.
Methods of collecting fish vary with
size of stream. A seine and backpack
electrofisher were used in most small
112
-------
Nonpoint Source Impacts on Fish
second and third order streams. larger
streams were electrofished with an
electric seine, a backpack electro-
fisher carried in a boat, and/or a
seine in shallows areas.
Data on agricultural landuse was
obtained variously from (a) estimates
by Soil Conservation Service per~
sonnel, (b) detailed computer analysis
of LandSat imagery (Hyde, Goldblatt,
and Stolz 1982), and (c) conventional
analysis of enlarged LandSat infrared
photographs taken during early summer,
as described below.
Using topographic maps of the stream
or tributary of concern, the drainage
area perimeter was determined and
drawn onto rescaled drainage maps
(Hoggatt 1975). An infrared LandSat
photograph taken on June 10, 1978
provided good contrast of permanent
vegetation as grass or trees (red)
from tilled field (tan and black).
After establishing the best darkness
Figure 2: Location of Study Streams.
setting the watershed of interest was
xeroxed to produce an acceptable dark
copy of the red portions in contrast
to the lighter portions.
This xerox copy was superimposed over
the scaled drainage maps on a light
table, the drainage basin boundary was
traced onto the xerox copy, and
enlarged to 150%. This copy was placed
over a fine transparent grid on a
light table. If single grids contained
more than 50% vegetation a mark was
made. The total number of grids marked
in relation to the total number of
grids provided an estimate of the
percentage of the drainage basin area
in rowcrop agriculture.
Results
Data on the IBI of fish communities
and the percent of watershed devoted
to rowcrop agriculture are summarized
in Table l. A majority of streams
flowed through watersheds with more
than 65% of the area in row crop
agriculture.
Discussion
The IKE should function well in
assessing the degree to which stream
fish communities are influenced by
non-point source pollution because 5
of the 12 metrics include species
sensitive to sediment pollution. The
data from Table 1 was divided into two
parts: (1) smaller streams (Orders I
and II), and (2) larger streams
(Orders III and IV). IBI values for
the larger streams generally exceeded
those for smaller streams, but there
was considerable overlap. Studies in
Ohio and Illinois indicate a direct
relationship between stream order and
IBI values (Ohio E.P.A. 1988, Kite and
Bertrand 1989).
The IBI of the fish community and the
percent of the watershed in rowcrop
agriculture is summarized in Figure 3.
The few watersheds having 50% or less
of their areas in rowcrops contained
fish communities with IBIs of 50 or
greater. There was a statistically
significant correlation (Spearman) at
the 0.05 level between percent rowcrop
113
-------
Gammon
Table 1: Drainage basin
communities of
Stream
area, agricultural land-use, and
central Indiana streams.
Drainage
Basin Area %
Stream Order km2 (mi2) Rowcroo
Mainstem
Above Darlington III
Darl. to C-ville IV
C-ville to mouth IV
Tributaries
Rush
Sugar Mill
Indian
Rattlesnake/
Offield
Black
Walnut Fork
Little Sugar
Lye
Wolf
Prairie
I
II
II
III
II
II
II/III
II/III
III
II
III
fish
Number
of Species
IBI Par. Sun. Bass
Sugar Creek System
829
1318
2100
42
197
65
81
90
117
117
203
65
127
.2
.4
.5
.3
.4
.3
.6
.8
.8
.9
Big
Mainstem
Montogomery Co.
Ramp Crk. to
Putnam line
Tributaries
Cornstalk
Haw
Ramp
III
III
II
II
III
251
365
52
72
85
.0
.2
.6
.5
.7
Big
Mainstem
Above US 36
IV
US 36 to G-castle IV
357
575
.6
.0
(320)
(509)
(811)
(16.3)
(76.2)
(25.3)
(31.4)
(34.9)
(45.3)
(45.4)
(78.7)
(25.4)
(49.4)
Raccoon
(96.9)
(141)
(20.3)
(28.0)
(33.1)
Walnut
(138)
(222)
75
60
64
69
70
59
59
66
71
69
82
74
70
Creek
80
71
72
73
62
Creek
81
67
47.1"
49. T6
48.0°
44
42
38
52
42
40
42
47
36.5
52
28
System
42"
43. le
41
42
52
System
50. 2f
48.5s
2.0
3.0
2.7
2
1
1
2
2
3
3
3
3
4
3
1
1.42
2
1
5
3.0
1.7
0.9
1.2
1.2
0
0
3
3
1
2
3
3
2
5
1
3
1.62
2
3
1
1.9
2.2
0.5
1.0
1.3
0
2
1
2
1
1
2
1
2
1
1
1
0.82
*
1
1
1
1.2
1.5
Eagle Creek System
Mainstem - upper
Tributaries
School Branch
Fishback
Little Eagle
Finley
Mount's Run
in
I
II
II
I
II
74
22
53
75
25
41
.1
.7
.8
.9
.2
.2
(28.6)
( 8.7)
(20.8)
(29.3)
( 9-8)
(15.9)
74.4
73.6
65.3
72.4
72.1
59.7
48
46
42
46
48
48
4
4
5
4
4
4
5
3
3
3
2
5
2
1
1
1
0
2
Stotts Creek System
Mainstem
North Fork
lower
upper
IV
III
II
155
56
.6
.7
(60.1)
(21.9)
58.4
55.0
48
54
43
3
5
5
3
3
3
2
2
2
114
-------
Nonpoint Source Impacts on Fish
Table 1 concluded.
South Pork
lower
upper
III 87.3 (33.7)
II
Streams
Rattlesnake Creek III 65.2 (25.2)
Stinking Fork III 70.7 (27.3)
53.4
15?
40?
50
44
53h
501'
5
2
5
3.3
2
2
4.5
3
0
0
1.5
1.3
8 Mean
b Mean
c Mean
d Mean
e Mean
f Mean
9 Mean
h Mean
j Mean
of 7 stations above Darlington.
of 4 stations between Darlington and Crawfordsville.
of 12 stations between Crawfordsville and the mouth.
of 3 stations.
of 8 stations over 8 years from 1981 through 1989.
of 8 stations from 1979 through 1984.
of 8 stations from 1979 through 1987.
of 2 stations.
of 4 stations
IBI
60
50
40
30
20
III&IV
10 20 30 40 50 60 70 80 90 100
% Rowcrop
Order III & IV
Order I & II
Figure 3: IKE values of fish communities as a function of rowcrop agriculture
of the watersheds. ______„
115
-------
Gammon
in the watershed of third and fourth
order streams and the IBI. The IBI
values decline steadily as the per-
centage of rowcrops increases, al-
though there is much scatter among the
data points. The general trends for
smaller and larger streams, indicated
by arrows, suggest that smaller
streams are more strongly affected by
progressively greater agricultural
development. They also may be
negatively influenced at lower rates
of development, although watersheds in
the 40% to 50% range are lacking.
Four of the stream systems originate
in the Tipton Till Plain of Boone
County, Indiana and flow in a gener-
ally south or southwesterly direction.
Within 20 or so miles Sugar, Big
Raccoon, and Big Walnut Creeks cut
deeply into the plain creating a
highly dissected landscape for varying
distances. These portions of the
watersheds are covered by a mature
deciduous forest and are poorly suited
for agriculture. The riparian
protection thus afforded may be
responsible in part for the continued
maintenance of reasonably good fish
'communities in Sugar Creek.
All of the above streams, together
with Eagle Creek, once supported
healthy populations of smallmouth
bass, sunfish, and darters. Sugar
Creek still harbors them today (Gammon
and Riggs 1983, Gammon et. al. 1990),
but Big Walnut Creek and Eagle Creek
contain only marginal populations
(Benda and Gammon 1965, Fisher and
Gammon 1981, 1982).
Big Raccoon Creek and some of its
tributaries supported good populations
25 years ago (Gammon 1965), but
darters, sunfish, and bass were lost
sometime prior to 1981. From 1981
through 1989 three electrofishing
collections each at eight stations
were made for purposes of biologically
monitoring a landfill (Gammon 1990).
The landfill has had no measurable
effect on the fish community, but
agriculture has certainly impacted it.
This data set is interesting because
it demonstrates community changes in
agricultural watersheds as affected by
natural weather and flow patterns.
Table 2 summarizes IBI values for each
station and year of study. Mean IBI
values for the most downstream station
are lower, perhaps because of
occasional spring inundation by
Mansfield Reservoir downstream. The
other stations are remarkably similar
to each other, but variability over
time is quite striking with mean IBIs
lowest in 1981 (IBI = 36.5) and
highest in 1988 (IBI = 50.5).
The low IBI values from 1981 through
1984 probably resulted from poor
reproduction and survival during
unusually high water in the summers of
1979, 1981, and 1982. Darters,
sunfish, and bass were virtually
absent during those years (Figure 4)
and a special seining effort in 1984
aimed at collecting darters also
indicated very low population densi-
ties. The very high IBI values found
in 1988 were associated with extremely
low flows and a prolonged drought.
Fish were undoubtedly concentrated and
more vulnerable to capture.
Over the period of study the IBI
values steadily increased, and so did
the mean frequency of darters,
sunfish, and bass. Figure 5 shows that
while the mean IBI increased from less
than 35 to more than 50 the mean
number of darter, sunfish, and bass
species captured per station increased
from near zero to more than 2 in a
linear fashion.
The weather and regime of stream flow
are obviously influential. A succes-
sion of years with poor reproduction
may decimate species populations which
are merely marginal during good years.
Conversely, a run of years favoring
good reproduction may lead to the
appearance of recovery. Generaliza-
tions concerning the "health" of a
fish population based on investiga-
tions conducted during a single year
116
-------
Nonpoint Source Impacts on Fish
Table 2: IBI values based on three series of electrof ishing collections at 8
stations from Big Raccoon Creek from 1981 to 1989.
Year
1981
1982
1984
1985
1986
1987
1988
1989
Mean
FI
36
40
48
46
40
44
52
42
43.5
F2
38
44
44
50
40
46
48
48
44.8
F3
38
42
42
48
40
50
50
46
44.5
F4
36
40
46
53
38
40
52
44
43.6
F5
38
40
44
50
42
43
50
44
43.9
F6
34
40
40
50
38
44
50
50
43.5
F7
36
38
40
48
40
40
52
42
42.0
F8
36
34
40
44
36
34
52
40
39.0
Mean
36.5
39.8
43.0
48.6
39.3
42.6
50.5
44.5
43.1
Total Number
250
200
150
100
50
-
-
--
, .
-
• fcj
—
|
1981 1982 1983 1984 1985
- -
- -
"Jij
1986 1987
§• Log Perch E^ Other Darters OOH Baas
--
I
J
No/km
-
n=
I
I
-
|i
:
-
-
_
\
\\j\j
10
1988 1989
03 Sunflsh
Fi'mino A* TVi+^al mnnHo'ne rvF 1 mrttn^ri > Aar+frvv- t-nrr\fits^ -»«v4 w-***-. ~«-i i ~-^-~j -i^
Big Raccoon Creek from 1981 through 1989.
117
-------
Gammon
60
so
40
30
20
10
IBI
IBI • 31.8 • 7.33X
rxr • 0.703
0.5 1 L5 2 2.5
Mean Species D. SF. & B
Figure 5: Relationship of catches of
darters, sunfish, and bass to IBI
values: Big Raccoon Creek 1981
throucfo 1989.
would be unwise and tenuous. Unlike
point-source influences which are more
sustained and constant, agricultural
nonpoint-source pollution is much more
sporadic.
Rowcrop intensity has been used as a
general measure of agricultural
influence. The actual overall pattern
of changes in fish communities is
obscured and/or influenced by many
factors other than agricultural land-
use. Sporadic spills of fertilizer and
feed lot wastes accelerate the
process. Towns and industries may
likewise reinforce the process through
point-source contributions of wastes.
The pattern of fields relative to
streams is no doubt of considerable
importance. Streams which are well-
protected by riparian vegetation are
probably less susceptible to change
than streams with tilled fields which
extend to the stream banks and heavy
lateral erosion. Lower Sugar Creek is
strongly degraded by the effects of
lateral erosion (Gammon and Riggs
1983), but not during all years
(Gammon et. al. 1989).
Other environmental attributes
unrelated to agriculture modify and/or
influence the overall process in whole
stream systems. The drainage pattern
of the stream system is probably
influential. Systems which are
strongly linear with mostly small,
low-order tributaries are likely to be
more susceptible than more dendritic
systems in which one or more less
disturbed tributaries may serve as
refugia which periodically replenish
or restock a degraded mainstem during
favorable periods.
Some of the agriculturally degraded
tributaries of Sugar Creek appeared to
contain better fish communities than
they should have, probably because of
the presence of good populations of
fish in the mainstem and their
migration during favorable periods.
Upper Big Walnut Creek also contains a
fairly good fish community despite
being heavily rowcropped. All areas
need to be examined for the pattern of
permanent "vegetation. Extensive
agriculture may not be incompatible
with good fish communities if adequate
protection is afforded by a riparian
buffer system.
Agriculture as an influence on streams
has not received sufficient attention.
Inere is a great need for programs to
assess landuse activities throughout
the state by CIS or comparable
methodologies. Many of Indiana's
streams have already been degraded by
agriculture and even the better
streams are in danger. We need to
eliminate the pasturing of farm
animals directly in streams. We need
to develop programs for the
enhancement of riparian buffers and
stabilization of eroding banks.
Acknowledgements
The research has received diverse
support in the past. Grants from Eli
Lilly and Company, Public Service
118
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Nonpoint Source Impacts on Fish
Indiana, and Heritage Environmental
Services made long-term studies
possible. The Environmental Protection
Agency supported the MIP studies.
Other support has come from the
Indiana Department of Natural
Resources and the Dana Foundation.
Dedication
The oral presentation of this research
followed by six hours the birth of
Robert Wayne Gammon-Pittman. May he
and his entire generation enjoy clean
rivers in the future.
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Angermeier, P. L. and J. R. Karr.
1986. Applying an Index of Biotic
Integrity based on stream-fish
communities: considerations in
sampling and interpretation. No. Am.
Jour. Fish. Management 6:418-429.
Benda, R. S. and J. R. Gammon. 1968.
The fish populations of Big Walnut
Creek. Proc. Indiana Acad. Sci.
77:193-205.
Braun, E. R. and R. Robertson. 1982.
Eel River watershed investigation
1982. Fisheries Section, Indiana
Department of Natural Resources,
Division of Fish and Wildlife, 607
State Office Building, Indianapolis,
Indiana 46204. 60 pp. mimeo.
Fisher, W. L. and J. R. Gammon. 1981.
The implications of rotenone
eradication on the fish community of
Eagle Creek in Central Indiana. Proc.
Indiana Acad. Sci. 90:208-215.
Fisher, W. L. and J. R. Gammon. 1982.
The fish populations of Eagle, Stotts,
and Rattlesnake Creeks. Proc. Indiana
Acad. Sci. 91:171-182.
Gammon, J. R. 1965. The distribution
of fishes in Putnam County, Indiana,
and vicinity. Proc. Ind. Acad. Sci.
74:353-359.
Gammon, J. R. 1989. Wabash River Fish
Communities 1974 - 1988. A report for
Public Service Indiana, Plainfield,
Indiana and Eli Lilly and Company,
Indianapolis, Indiana.
Gammon, J. R. 1989. The fish
communities of Big Raccoon Creek 1981
- 1989. A Report for Heritage Environ-
mental Services, One Environmental
Plaza, 7901 West Morris St.,
Indianapolis, Indiana 46231. 120 pp.
Gammon, J.R., M.C. Johnson, C.E. Mays,
D.A. 'Schiappa, W.L. Fisher, and B.L.
Pearman. 1983. Effects of agriculture
on steam fauna in central Indiana.
Tech. Report, EPA 600/3-83-020. 88 pp.
Gammon, J. R., C. W. Gammon, and C. E.
Tucker. 1989. The fish communities of
Sugar Creek. Ind. Acad. Sci. 98; in
press
Kite, R. L. and B. A. Bertrand. 1989.
Biological stream characterization
(BSC): a biological assessment of
Illinois stream quality. Special
Report No. 13 of the Illinois State
water plan task force. 42 pp.
Hoggatt, R. E. 1975. Drainage areas of
Indiana streams. U.S. Department of
the Interior, Geological Survey, Water
Resources Division. 231 pp.
Hyde, R. F., I. A. Goldblatt, and B.
J. Stolz. 1982. The Holcomb Research
Institute and the Indiana Heartland
Model Implementation Project pp 4-1 to
4-44 in Insights into Water Quality.
Final Report by A. Preston.
Karr, J.R. 1981. Assessment of biotic
integrity using fish communities.
Fisheries (Bethesda) 6(6):21-27.
Karr, J.R. 1987. Biological monitoring
and environmental assesssment: a
conceptual framework. Env. Mgt.
11:249-256.
Karr, J.R., K.D. Fausch, P.L.
Angermeier, P.R. Yant, and I.J.
Schlosser. 1986. Assessing biological
integrity in running waters: a method
and its rationale. 111. Nat. Hist.
Surv. Spec. Publ. 5, Urbana.
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Gammon
Karr, J.R., P.R. Yant, K.D. Fausch,
and I.J. Schlosser. 1987. Spatial and
temporal variability of the index of
biotic integrity in three midwestern
streams. Trans. Am. Fish. Soc. 116:1-
11.
ludwig, J.A. and J.F. Reynolds. 1988.
Statistical Ecology. J.Wiley and Sons,
N.Y. 337 pp.
Miller, D.L., P.M. Leonard, R.M.
Hughes, J.R. Karr, P.B. Moyle, L.H.
Schrader, B.A. Thompson, R.A. Daniels,
K.D. Fausch, G.A. Fitzhugh, J.R.
Gammon, D.B. Halliwell, P.L.
Angermeier, and D.J. Qrth. 1988.
Regional applications of an index of
biotic integrity for use in water
resource management. Fisheries
13 (5):12-20.
Olio Environmental Protection Agency.
1988a. Biological criteria for the
protection of aquatic life: Volume I.
The role of biological data in water
quality assessment. Division of Water
Quality Monitoring and Assessment,
Surface Water Section, 1030 King Ave.,
Columbus, Olio 43212. 44 pp.
Olio Environmental Protection Agency.
1988b. Biological criteria for the
protection of aquatic life: Volume II.
Users manual f orbiological field
assessment of Olio surface waters.
Division of Water Quality Monitoring
and Assessment, Surface Water Section,
1030 King Ave., Columbus, Olio 43212.
Parke, N. J. 1985. An investigation on
phytoplankton sedimentation in the
middle Wabash River. M. A. Thesis,
DePauw University, Greencastle,
Indiana. 71 pp.
Parke, N. J. and J. R. Gammon. 1986.
An investigation on phyto-plankton
sedimentation in the middle Wabash
River. Proc. Indiana Acad. Sci.
95:279-288.
120
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Indiana's NPS Program
James K. Ray
Indiana Department of Environmental Management
5500 W. Bradbury
Indianapolis, Indiana 46241
Abstract
Although a variety of existing programs have helped curb non-point source (NPS)
water pollution in Indiana, the effects have often been only coincidental to
their primary goals. State conformance with Section 319 of the Clean Water Act
has recently resulted in development of an integrated, multi-disciplinary NPS
control plan that refocuses many programs on the issue of water quality, and has
established a number of new initiatives. This effort has been significantly
enhanced by national attention on the topic, with shifts toward a water quality
emphasis by federal agencies such as the Department of Agriculture. Indiana is
now able to address NPS water pollution in a much more unified fashion, guided
by a comprehensive plan. Indiana's new late Enhancement Program is a part of "T
by 2000," a statewide strategy for dealing with soil erosion and sedimentation
problems. The goal for late enhancement is to control the flow of sediment and
associated nutrients into public lakes. Toward that goal, Indiana Department of
Natural Resources' (IDNR) Division of Soil Conservation is providing technical
and financial assistance for late enhancement needs in accordance with guidelines
set by the State Soil Conservation Board, the policy-making body for the
division. The late Enhancement Program's policies and procedures will be reviewed
and specific examples of how the program operates will be discussed.
Key words: Indiana, nonpoint sources, water quality, pollution
Our environment looks and is cleaner
than it was twenty years ago when the
first Earth Day was celebrated. That's
not to say that there isn't a great
deal more to be done but progress
has been made, and that progress has
been the result of the cooperative
efforts of many federal and state
agencies, local governments, and
concerned citizens who value our water
resources.
Up until now, the majority of our work
in protecting water quality has been
in cleaning up point source discharges
by setting water quality standards,
enforcing NPDES permit limitations,
and promoting construction and
upgrading of wastewater treatment
facilities. Indiana is committed to
continuing that work on point sources
so that all communities and industries
discharging to state waters will be in
compliance with the Clean Water Act.
Review of surface water quality data
for Indiana shows that pollution
coming from point sources has declined
significantly in twenty years. How-
ever, analysis has also shown that
nonpoint source pollution continues to
degrade water quality and that use
impairments are often caused by NPS
pollution, either by itself, or in
combination with point sources.
Studies of Indiana's public lakes
reveal that they are particularly
vulnerable to certain types of NPS
pollution, which currently threaten
the designated uses of many of them.
Traditionally, in many respects, NPS
water pollution control has been
secondary to regulation of point
sources in Indiana as well as at the
national level. This can be attributed
largely to the difficulty and expense
involved in identifying and monitoring
many of the nonpoint pollutant
sources.. .but it can also be attri-
buted to the pervasive nature of the
problems, and tacit acceptance arising
from the belief that resolution of the
problems was not economically feas-
121
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Ray
ible. However, it's become obvious
that state water quality goals will
never be attained without reduction of
NFS pollution.
Indiana state government has sponsored
some long-standing programs that have
partially addressed certain categories
of NFS pollution, such as disposal of
waste from confined animal production
facilities and control of agricultural
erosion, for example, but none of the
efforts have been adequate to fully
address the problems. In addition,
there have been some areas which have
received only minimal attention, such
as evaluating the effects that storm
sewers and atmospheric deposition have
on water quality. So, there have been
obvious voids, then, in Indiana's
overall ability to gauge and control
the various NFS pollution, problems
that exist in the state.
Section 319 of the Clean Water Act
provided the impetus for the state to
develop a comprehensive plan which
would integrate all aspects of NFS
control. In response to requirements
of Section 319, a multiagency Task
Force was formed which provided a
strategy development forum for the
state's resource professionals. By
bringing a variety of program
directors together as a group, a
climate of increased cooperation was
created in which NFS pollution control
could be more thoroughly addressed.
The Task Force included
representatives of nine different
organizations and was responsible for
two major aocomplishments:
production of NFS "Assessment
Report" which summarized available
information regarding NFS-impacted
water bodies and the causes of the
problems, and;
• development of a NFS "Management
Program" describing categorical NFS
problems and their proposed solutions.
I should say a few words about the
Assessment Report, since during its
preparation one of the things we
discovered was just how little actual
scientific information was available
regarding NFS impacts to public
waters, and how difficult it was going
to be to obtain the information in the
future. So, although the rationale for
preparing the report was to somehow
quantify the extent of NFS pollution
in the state, we were only able to
assemble the data that were then
available, which describe merely a
fraction of the state's waters. This
has left us in the position of needing
to acquire an enormous amount of
additional information if we're to be
able to truly assess statewide NFS
effects, in order to prioritize
problem areas for treatment.
We are proceeding slowly in that
direction, having begun to develop a
variety of biological monitoring
programs, since those appear to be the
most cost effective and practical
methods of evaluating impacts to
aquatic systems, but our resources for
pursuing such an initiative are
limited.
The Management Program itself is based
on five premises which must be
supported in order for the program to
be successful:
(1) financial assistance must be made
available to fund recommended
activities;
(2) activities involving different
organizations must be well
coordinated;
(3) research and monitoring must be
continued which will provide
information on water quality trends
that will guide future program needs;
(4) information and education efforts
must be an integral component of the
overall program; and,
(5) in addition to financial and
technical assistance, regulatory
alternatives must also be considered
122
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Indiana's Nonpoint Source Program
for the resolution of some types of
problems.
It will take a great deal of money to
implement all of the Management
Program's recxsnmendations, and Indiana
has recently received assistance in
this regard through EPA's granting of
Section 319 funds to the state. Let me
briefly highlight some of the work
that we will be doing with the money.
Portions of the money will be used to
finance projects demonstrating the
elimination of acid runoff from
abandoned mine land and reduction of
erosion from a commercial timber
harvesting operation.
Part of the money will be used to fund
a NPS evaluation and prioritization
project in an industrialized urban
watershed.
A state university will use some of
the grant to develop computer software
that can be distributed to local
health departments, enabling them to
evaluate the adequacy of proposals for
on-site disposal systems.
Another university will be paid to
evaluate the effects of BMP
implementation on particular lake
watersheds.
And there will be a number of other
uses for the money, with the most
interesting being a survey of the Bel
River to determine how NPS pollution
is affecting the aquatic biota.
The continued support and involvement
of federal, state, and local
governments in the control of NPS
pollution is essential. We're hopeful
that current efforts, in combination
with our Manage-ment Program's actions
and federal assistance through Section
319, will eventually allow our streams
and lakes to regain their former
vitality.
123
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Instream Water Quality Evaluation of the Upper Illinois River Basin
Using the Index of Biotic Integrity
Thomas P. Simon
U.S. Environmental Protection Agency, Region V
Environmental Sciences Division
Central Regional Laboratory
536 S. Clark Street
Chicago, IL 60605
Abstract
The twelve stations sampled within the Upper Illinois River drainage revealed
that the best water quality as indicated by the Index of Biotic Integrity (IBI)
was found in the Kankakee, Fox, DuPage, Des Plaines and Chicago River sub-basins,
respectively. These areas were -correlated with degree of dominant land use, e.g.
agriculture and sparse residential areas in the Kankakee and Fox drainages and
heavy urban and industrial in the Des Plaines, Chicago, and DuPage drainages.
Principal concerns within each of these basins indicate that bank erosion from
the lack of a stable riparian zone, combined sewer overflow and street runoff and
point sources of pollution contribute greatly to the lower water quality
observed.
The stations sampled in each drainage varied in number, however, the overall
objective was to provide a quantitative approach to categorizing the biological
integrity of the sub-basins on a long-term basis. The IBI was able to rapidly
estimate water quality and provide interpretation of water quality without the
long-term exercise of measuring water chemistry on a weekly or monthly basis. Yet
the amount of similarity based on the two data sets are comparative since the
biological fauna assimilates all past and present conditions.
Keywords: IBI, fish, Kankakee River, Des Plaines River, Upper Illinois River
Basin, Chicago River and Canals, Fox River
Introduction
The Upper Illinois River has a rich
history of biological information
dating back to the late 1800»s (Mills
et al. 1966; Steffeck and Striegl
1988). Information regarding fish
distribution and documenting impacts
incurred from once through cooling of
industries and municipalities has
added greatly to the body of data from
this region with over 200 published
papers and reports. The greatest
handicap one has in interpreting this
body of information lies in its
relevance to the Upper Illinois River
as it exists today. Collections on the
River have been conducted for a
variety of reasons, including but not
limited to: species-specific
population estimation, general
distribution, length-weight ponderal
indioe«, and fisheries management
strategy development. The evaluation
of water quality within the River has
been one of immense concern, however,
the implications of such varied
collection techniques and study
objectives has practically made the
historic data base uninterpretable.
As part of the National Water Quality
Assessments (NAWQA) Pilot Survey the
Environmental Science Division's
Central Regional Laboratory (CRL) of
the Environmental Protection Agency
(USEPA), Region V surveyed twelve
stations in the basin to evaluate
instream biological quality of the
Upper Illinois River. Karr's index of
biotic integrity (1986) was used to
evaluate water quality based on fish
communities.
Fish sampling was conducted at twelve
stations within the Upper Illinois
River basin which has the mainstem
initiate at the junction of the Des
Plaines and Kankakee Rivers, Will
124
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Upper Illinois River Water Quality
County, Illinois and for this study
terminated just below the junction
with the Fox River at Ottawa,
Illinois.
Sampling in the Upper Illinois River
basin began during late July 1989 and
was completed by late August. Water
conditions were stable and close to
normal conditions following drought
conditions observed during summer
1988.
Study Area
The Upper Illinois River is considered
a seventh order tributary in the
vicinity of Ottawa, Illinois (IEPA
1988). The River is comprised of five
sub-basins comprising the Kankakee,
Chicago, Des Plaines, DuPage, and Fox
Rivers. The general flow of the River
is from northeast to southwest, with
the most northerly sub-basin
originating in Waukesha County,
Wisconsin (Fox River) and the most
easterly sub-basin in St. Joseph
County, Indiana (Kankakee River). The
River is primarily contained within
the Central Cornbelt Plains ecoregion
with a minor portion of its headwaters
occurring in the Southeastern
Wisconsin Till Plains ecoregion
(Omernik 1987). The dominant land use
in both ecoregions is cropland,
however, soil constituents and the
urban area of Chicago are the major
differences. Low to moderate flows
occur within the Rivers.
The study area borders the shores of
Lake Michigan and is a primary drain-
age of the upper Mississippi River.
The River has a series of navigation
impoundments on the mainstem which has
made the River more homogeneous,
turning it into a series of pools.
Each of the sub-basins has a series of
low-head dams or flood control dams.
The Kankakee River has a single dam on
its entire length, and the entire
stretch within Indiana has been
ditched. The Chicago River, which
previously was considered a Lake
Michigan drainage tributary, was
included in the current study because
of its connection with the Upper
Illinois River through the Sanitary
and Ship Canal.
Station Locations
A total of twelve stations were
sampled from July 26 to August 24,
1989 (Fig. 1). All stations occur in
the State of Illinois unless otherwise
noted. The furthest station downstream
in the Upper Illinois River basin was
the Illinois River at Marsailles
(station 1), LaSalle Co., downstream
of the dam from Central Illinois Power
(R.M. 246.4) to Delbridge Creek (R.M.
245.5), T 33N R 4E S 15/16.
The first sub-basin was the Fox River
which included three stations, one
mainstem and two tributaries. Station
2, was the Fox River near the Rt. 62
bridge, Algonquin, Algonquin Township,
downstream of the dam influence at a
crossover walk bridge but upstream of
the Algonquin STP (T 43N R 8E S 30).
Station 3 was at Indian Creek, LaSalle
Co, 11 mi N Ottawa, Freedom Township,
at E 1553 and E 16th Street bridge
intersection (T 35N R 3E S 1/2).
Station 4 was at Honey Creek, Walworth
Co., WI, Himelbaugh Road bridge, 7 mi
N Burlington (T 4N R 18E S 25).
The second sub-basin was the DuPage
River which included two stations.
Station 5 was the DuPage River, Will
Co., 1 mi N Shorewood, downstream of
Black Road bridge at Hammel Woods
DuPage River access (T 35N R 9E S 10).
Station 6, was the East Branch of the
DuPage River, Will Co., off Royce
Road, 2-1/2 mi NW Bolingbrook, 1/2 mi
E of Naperville Road intersection, (T
37N R IDE S 5/8).
Sub-basin 3 was the Des Plaines River
which included two mainstem stations
and a tributary station. Station 7,
Des Plaines River at Brandon Road Lock
and Dam, Will Co., was 3 mi S Joliet
and sampled in a backwater area on the
east side of the Navigation channel,
(T 5N R 10E S 20). Station 8, Des
Plaines River at Riverside, Cook Co.,
was accessed at a Cook County Forest
125
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Simon
EXPi ANATION
I NAVK..X ItONAl OAM
ANU I OCK
• MYDnoELECtRIC POWCB
PLANT AND LOCK
BASIN BOUNDARY
Chicago HarDor
Chicago Sanitai
ana She Canal
alumei Sag ,.
Channel i ^__
•l Hitboi^s ^.-\~ \ "•.
Fig. 1. Station locations for fish collected in the Upper Illinois River basin
during 1989.
Preserve off 40th Street (T 39N R 12E
S 36). Station 8 was downstream of the
confluence of Salt Creek. Station 9,
Salt Creek, Cook Co., at Beamis Woods
footpath 1/2 mi N Western Springs off
Wolf Road and Ogden Road (Rt. 34) (T
39N R 11E S 31).
Sub-basin 4 included the Chicago River
basin and the canal system. A single
station was sampled in this basin.
Station 10, North Branch Chicago
River, Cook Co., at Touhy Avenue
bridge, 1.5 mi S Niles (T 42N R 12E S
15).
Sub-basin 5 was the Kankakee River
basin which included two mainstem
locations. Station 11, was the Kanka-
kee River at Momence, Kankakee Co.,
off E 1050N, 1 mi from Rt. 114 bridge,
T 31N R 13E, S 22/23. Station 12,
Kankakee River, Newton Co., Indiana,
In Rt. 55 bridge, 1 mi S Shelby, Eagle
Creek Township, T 32N R 8W S 33/34.
Materials and Methods
Fish Sampling
The sampling protocols for fish
follows that documented in the USEPA,
Environmental Science Division's,
Central Regional laboratories Standard
Operating Procedure for Rapid Assess-
ment using fish (1988).
The following collection techniques
were applied to obtain a representa-
tive sample from each of twelve
stations within the Upper Illinois
River basin. All habitats that were
present were sampled including riffle,
pool, and run. No samples were taken
in the vicinity of bridges, or in the
mouths of tributaries entering large
rivers, lakes or reservoirs since they
tend to be more similar to larger-
126
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Upper Illinois River Water Quality
order habitats than the one under
consideration (Fausch et al. 1984).
Seines were considered by Karr et al.
(1986) the best collection tool for
obtaining an unbiased sample in small
streams. As stream complexity in-
creased a 50 ft. bag seine with 1/8 in
mesh was utilized for collection and a
boat mounted pulsed DC electroshocker
was selectively included at appropri-
ate sites. The seine was able to get
an excellent representation of the
species present, since low water
levels allowed easy access for most
portions of the Rivers. Likewise,
adult species which only use the
stream in a transitory manner would be
excluded from this analysis (e.g.
adult salmonids, eels). Young-of-the-
year species less than 20 mm total
length were excluded following the
recommendations of Angermeier and Karr
(1986). Distances between 100 to 500 m
were sampled at each site and included
similar levels of effort (usually 1 hr
of intensive sampling per 100 m)
within all available habitats.
Each sampling period consisted of a
single site visit under normal to
moderate flow conditions. During field
collection, all larger specimens were
identified to species, smaller speci-
mens of minnows and darters were pre-
served in 10% formalin, and returned
to the laboratory. At the completion
of the study, voucher specimens were
deposited into the fish collection
repository at the Field Museum of
Natural History.
The ambient environmental data was
evaluated using the Index of Biotic
Integrity (IBI; Karr et al. 1986).
The IBI relies on multiparameters
based on coromunity concepts, to evalu-
ate a complex system. It incorporates
professional judgement in a systematic
and sound manner, but sets quantita-
tive criteria that enables determina-
tion of what is poor and excellent
based on species richness and composi-
tion, trophic constituents, and fish
abundance and condition. The twelve
IBI metrics reflect insights from sev-
eral perspectives and cumulatively are
responsive to changes of relatively
small magnitude, as well as broad
ranges of environmental degradation
(Table 1).
Since the metrics are differentially
sensitive to various perturbations
(e.g. siltation or toxic chemicals),
as well as to various levels within
the range of integrity, conditions at
a site can be determined with
considerable accuracy. The inter-
pretation of IBI numerical scoring is
provided in six narrative categories
that have been tested in Region V
(Karr 1981; Table 2).
Several of the metrics are drainage
size dependent and require selection
of numerical scores. The ecoregion
approach developed by USEPA-Corvallis,
OR was utilized to compare least
impacted zones within the region
(Omernik 1986). Extensive work within
the Central Corn Belt Plain ecoregion
by Illinois EPA (1988) and documenta-
tion in Karr et al. (1986), were used
to determine "excellent" or control
conditions for scoring the metrics
based on stream sizes equivalent to
the various sub-basins in the Upper
Illinois River basin (Table 3).
Habitat Evaluation
A habitat quality evaluation assess-
ment was completed in conjunction with
fish collection. The QJHEI, quality
habitat evaluation index, developed by
Ohio EPA (1986) provides numerical
assignments for six criteria to assess
riffles and pools. The criteria were
modified to include only five of
Ohio's criteria and were adjusted to
reflect the same equivalent total
score. Scoring was based on 100 total
points and incorporates substrate
quality, instream cover, channel
morphology, riparian zone and bank
erosion, and pool and riffle quality
based on drainage area.
For station comparisons of the fish
samples to be considered valid, the
127
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Simon
TABIE 1. Scoring criteria for 12 IKE metrics for low to moderate gradient
streams within the Northeastern Region of Illinois for the Upper
Illinois River basin (Karr et al. 1986).
Metrics
Scores
1. Number of total species
2. Number of darter species
\
3. Number of sucker species
4. Number of sunfish species
(excluding Micropterus)
5. Number of intolerant species
6. Proportion of individuals as
Green Sunfish
7. Proportion of individuals as
omnivores
8. Proportion of individuals as
insectivorous minnows and darters
9. Proportion of individuals as
piscivores
10. Catch rate (number/100 m)
11. Proportion of individuals with poor
condition or disease
12. Proportion of individuals as hybrids >5%
Stream size dependent
Stream size dependent
Stream size dependent
Stream size dependent
Stream size dependent
>20%
>45%
<20%
5-20%
20-45%
20-45%
1-5%
Varies with gear and
stream size
>2-5%
1-5%
< 5%
<20%
>45%
stations must be capable of supporting
the same type of communities. A stream
section habitat evaluation was vised to
determine if all sample sites had
similar habitat types for comparisons.
In order for a station to be
comparable habitat scores from the
QHEE had to be within 90% to be
comparable and at least 75% to be
supportive (Plafkin et al. 1989).
Results
Quality Habitat Evaluation Index
Flow, bank erosion, and warmer water
temperatures varied the habitat within
the Upper Illinois River basin between
the various sub-basins (Table 4).
Habitat criteria was developed for
each site based on the quality of the
site for promoting biological
diversity. The highest QHEE score
during the current study was 89.3.
Comparing all other scores to this
value resulted in seven stations being
equal in available habitat, two
stations being cctnparable, and three
stations not meeting the 75% criteria.
The station with the best overall
habitat score was Honey Creek (Fox
River sub-basin) station 4. The Upper
Illinois River at Marsailles
128
-------
Upper Illinois River Water Quality
Table 2. Biotic integrity classes used in assessing fish comnunities along
with general descriptions of their attributes (Karr et al. 1986).
Class
Attributes
IEE fenge
Excellent Ccrrparable to the best situations without influence 58-60
of man; all regionally expected species for the
habitat and stream size, including the most intolerant
forms, are present with full array of age and sex
classes; balanced trophic structures.
Good Species richness somewhat below expectation, especially 48-52
due to loss of most intolerant forms; some species with
less than optimal abundances or size distribution;
trophic structure shows some sign of stress.
Fair Signs of additional deterioration include fewer 39-44
intolerant forms, more skewed trophic structure
(e.g., increasing frequency of omnivores); older age
classes of top predators may be rare.
Poor Dominated by omnivores, pollution-tolerant forms, and 28-35
habitat generalists; few top omnivores; growth rates
and condition factors commonly depressed; hybrids and
diseased fish often present.
Very Poor Few fish present, mostly introduced or tolerant forms; 12-22
hybrids common; disease, parasites, fin damage,
and other anomalies regular.
No Fish Repetitive sampling fails to turn up any fish.
Table 3.
Metric scores for Illinois Northeast region surface waters of
various stream orders for calculating the Index of Biotic Integrity
(criteria shown is for the score of 3, values greater than that
listed receive a 5 and lower a 1; IEPA 1988) .
Metric
1.
2.
3.
4.
5.
2
Total number of species 6-10
Number
Number
Number
Number
of
of
of
of
Darter species
Sunf ish species
Sucker species
Intolerant species
2
1
2
2-3
St
3
7-12
2-3
2
2-3
2-3
ream Or
4
8-14
2-3
2-3
2-3
3-4
der
5
9-16
3-4
2-3
3-4
3-5
6
10-18
3-5
3-4
3-5
3-5
7
11-20
3-5
3-4
3-5
4-6
129
-------
Simon
(station 1), Fox River at Algonquin
(station 2), DuPage River at Shorewood
(station 5), East Branch DuPage River
near Bolingbrook (station 6), the Des
Plaines River at Brandon Road (station
7), and Des Plaines River at Riverside
(station 8) were habitat equal, while
Indian Creek (station 3), and Kankakee
River at Mornenoe (station 11) were
habitat compatible. Habitat limited
were Salt Creek at Beamis Woods
(station 9), North Branch Chicago
River (station 10), and Kankakee River
at Shelby, IN (station 12). The
primary causes of habitat degradation
was channelization, siltation and
embeddedness.
Fish - Index of Biotic Integrity
Illinois River-Mainstem : River
conditions at Marsailles indicated
"fair to poor" conditions from the
upstream headwater drainage (Table 5).
Sampling techniques used at this sta-
tion consisted of 50 ft bag-seining,
and electrofishing for 500 m of river
reach. Habitat sampled included 70%
riffle, 20% run and 10% pool.
Poor metric scores contributing to
reduced station scoring included
number of darter, sunfish, and sucker
species, number of intolerant species,
and number of individuals in the
sample. Excellent scores were achieved
for proportion of green sunfish, pro-
portion of omnivores and carnivores,
number of hybrids, and disease factor.
Dominant taxa within the site included
emerald shiner (77.96%), gizzard shad
(9.82%), and freshwater drum (3.61%).
Intolerant taxa included three taxa. A
stable level of carnivores were found
in the drainage including smallmouth
bass, flathead catfish, channel cat-
fish, and white bass. Bullhead minnow,
flathead catfish and white bass were
collected exclusively at this station.
larval specimens of emerald shiner and
gizzard shad were abundant along the
margins of the River.
Fox River Basin; The Fox River basin
obtained the highest IBI score among
all Upper Illinois River sampling with
a score of 52 at Indian Creek. A
rating of "good" at Indian Creek was
similar to the high score in the
Kankakee basin. The Fox River at
Algonquin rated "fair" and Honey Creek
a "poor". Sample distances collected
at the Fox River at Algonquin, Indian
Creek and Honey Creek were 250 m, 100
m, and 150 m, respectively. Habitat
sampled in the Fox River consisted of
70% run, and 15% each of pool and
riffle. The primary collection
technique was a 50 ft bag seine and a
10 ft common minnow seine. Indian
Creek sampling consisted of common
minnow seining within habitat composed
of 30% each of pool and riffle, and
40% run. Honey Creek was likewise
seined using a 10 ft common minnow
seine within habitat composed of 15%
pool, 40% riffle and 45% run.
The mainstem Fox River was classified
"fair" due to low scores for number of
darter, sucker, and intolerant
species; and proportion of carnivores
(Table 6). Sampling downstream of the
walk bridge but upstream of the
Algonquin STP resulted in high scores
for total number of taxa, number of
sunfish species, proportion of green
sunfish, proportion of omnivores and
insectivores, number of individuals in
the sample, lack of hybrids, and
disease. Indian Creek scored very high
in most categories except number of
sunfish species, while Honey Creek
scored poorly in number of darter and
sunfish taxa, proportion of carni-
vores, number of individuals and
diseased individuals. A high propor-
tion of individuals had black spot
indicating environmental stress at
Honey Creek.
Taxa unique to the Fox River basin
included yellow bass at Fox River at
Algonquin, and rainbow and fantail
darters at Indian Creek. The down-
stream pool and riffle habitat had
several intolerant taxa including two
taxa at the Fox River proper, eight
taxa at Indian Creek, and two taxa at
Honey Creek. The most dominant taxa at
130
-------
Upper Illinois River Water Quality
Table 4. Quality Habitat Evaluation Index scones for twelve stations sampled
in the Upper Illinois River basin, during 1989.
Character
predominate
substrate
Silt covered.
Illinois Fox
River River
boulder/ sand/
sand cobble
Indian
Creek
sand/
gravel
Honey DuPage
Creek River
sand/ sand
cobble/
gravel
E. Branch
DuPage River
sand/
gravel
Area affected
none
none
none
none
none
Instream Cover
Relative % extensive sparse sparse
Channel Morphology
sinuosity none moderate high
development good fair fair
channelization recovered none none
stability moderate high low
Riparian Zone
sparse- sparse
moderate
high
good
none
high
moderate
fair
none
moderate
none
sparse
moderate
fair
none
moderate
Zone width
Quality
Bank erosion
OHEI score
moderate
forest
little
83.1 89
narrow
residen-
tial
little
very
narrow
open
pasture
moderate
.0 74.3 89
wide
forest
little
.3
wide-
extensive
park/
forest
moderate
88.1 87
extensive-
narrow
forest/
park
little
.0
Table 4. (continued)
Des Plaines Des Plaines
Character Brandon Riverside
Salt N. Branch Kankakee Kankakee
Creek Chicago R. Maraence Shelby
predominate
substrate
Silt covered
Area affected
Instream Cover
Relative %
muck/
bedrock
pools
sand/
bedrock
none
sand
none
sand
none
sand/
gravel
none
sand
none
moderate moderate
Channel Morphology
sinuosity low
development good
channelization none
stability low
Riparian Zone
Zone width
Quality
Bank erosion
narrow
moderate
good
recovered
low
wide
forest/ forest
old field
moderate heavy
sparse sparse- moderate sparse
moderate
low none low low
fair good fair fair
recovered recovered none recovered
moderate moderate high moderate
moderate moderate/ very narrow
narrow narrow
forest forest residen- residen-
tial tial
little little none moderate
QHEE score
81.5
83.7
59.2
57.6
74,
61.7
131
-------
Simon
Table 5. Fish collected, length range,
number and relative percent composi-
tion from the Illinois River mainstem
collected during July and August, 1989.
Illinois River
at Marsailles
Species
N %
Range mm
Gizzard shad
Quillback
Carp
Emerald shiner
Spottail shiner
Sand shiner
Spotf in shiner
Golden shiner
Bluntnose minnow
Bullhead minnow
Flathead catfish
Channel catfish
White bass
Bluegill
Smallmouth bass
Freshwater drum
49
1
2
389
I
2
10
1
4
1
1
4
5
6
5
18
9.8
0.2
0.4
77.9
0.2
0.4
2.0
0.2
0.8
0.2
0.2
0.8
1.0
1.2
1.0
3.6
100-128
300
345-688
59-110
100
52-54
36-51
100
45-52
38
650
350-475
200-300
68-250
300-385
375-500
IBI score
36
Algonquin were spotfin shiner (63.1%),
brook silverside (23.94%), and
orangespotted sunfish (4.87%). Taxa
dominant at Indian Creek included
spotfin shiner (34.14%), sand shiner
(21.72%), and common shiner (10.0%),
while at Honey Creek dominant taxa
included sand shiner (39.13%), spotfin
shiner (31.3%), and golden shiner
(18.26%). Unique taxa collected in the
Fox River included yellow bass.
Larval fish collected or observed on
the Fox River at Algonquin downstream
of the walk bridge along run habitat
included cyprinids and centrarchids.
Downstream along the pool margins
green sunfish and brook silverside
were collected. Few larval fish were
collected from Indian Creek with those
collected being sand shiners. No
larval fishes were collected from
Honey Creek.
DoPage River Basin; Two stations were
sampled in the DuPage River basin. The
furthest downstream station, DuPage
River proper at Shorewood (station 5),
was seined for 200 m of stream reach
and included 45% run, 45% riffle and
10% pool habitat. The East Branch of
the DuPage River (station 6), was
seined using a 10 ft common minnow
seine for 100 m. The habitat sampled
included 40% each of run and riffle,
and 20% pool. A disjunct collection
was obtained at this location with the
majority of sampling being conducted
in the run and riffle habitat along
the margins of the park. Additional
sampling was conducted upstream of the
primary site, in the tree line around
the bend in the River.
The mainstem DuPage River scored an
IBI rating of "fair to good", while
the East Branch station rated "poor"
(Table 7). Contributions to reduced
metric scores at Shorewood were low
numbers of darter species (metric 2)
and catch per unit effort (metric 10).
High scores were observed for total
number of species, proportion of green
sunfish, proportion of omnivores,
insectivores, and carnivores, lack of
hybrids and diseased individuals. The
East Branch of the DuPage River had
reduced scores because of the lack of
benthic and intolerant taxa (metrics
2, 4, and 5), reduced catch per unit
effort (metric 10), and high
proportion of diseased individuals
(mostly black spot). High scores were
observed for proportion of green
sunfish, proportion of insectivorous
cyprinids, and no hybrids.
Salt Creek. At Brandon Road, 60%
riffle, 25% pool, and 15% run habitat
was sampled for 300 m of stream reach.
Riverside sampling consisted of 55%
riffle, 25% run and 20% pool habitat
being sampled for 400 m. This location
consisted of a disjunct collection
with 300 m sampled in the primary
location (the long run and riffle) and
100 m sampled upstream in the River
bend. Salt Creek was sampled for 100 m
with 100% of the habitat consisting of
run habitat.
132
-------
Upper Illinois River Water Quality
Table 6. Fish collected, length range (range measured in mm), number and
relative percent composition from the Fox River sub-basin of the
Upper Illinois River collected during July and August, 1989.
location
Fox River
at- Alqonqiiin
Species
Northern pike
Carp
Cannon stoneroller
Emerald shiner
Rosyf ace shiner
River shiner
Bigmouth shiner
Sand shiner
Mimic shiner
Spottail shiner
Spotf in shiner
Cannon shiner
Golden shiner
Bluntnose minnow
Fathead minnow
Suckermouth minnow
Hornyhead chub
Creek chub
White sucker
Quillback
Smallroouth buffalo
Northern hogsucker
Silver redhorse
Brook silverside
Yellow bass
Black bullhead
Largemouth bass
Smal Ijnnnth t^55?5
Bluegill
Green sunf ish
Pumpkinseed
Grangespotted sunf ish
White crappie
Black crappie
Johnny darter
Rainbow darter
Fantail darter
Banded darter
N
1
2
1
1
1
1310
32
1
12
10
9
497
7
5
1
71
3
1
101
6
4
%
0.1
0.1
0.1
0.1
0.1
63.1
1.5
0.1
0.6
0.5
0.4
23.9
0.3
0.3
0.1
3.4
0.1
0.1
4.9
0.3
0.2
Range
875
300-575
69
30
38
30-84
48-144
32
28-60
59-95
69-114
21-77
64-275
200-275
44
20-83
22-27
100
22-82
50-72
51-70
Indian Creek Honev Creek
N
2
10
1
63
21
99
29
10
2
2
1
2
4
3
26
7
1
2
1
4
%
0.7
3.5
0.3
21.7
7.3
34.1
10.0
3.5
0.7
0.7
0.3
0.7
1.4
1.0
9.0
2.4
0.3
0.7
0.3
1.4
Range N
49-92
40-67
91
21
30-70 45
52-65
28-80 36
94-104
1
35-70 8
49-55
40-100
66
1
60-66
55-65
1
44-49
45-180
30-114
49 2
35-43
25
47-56
% Range
18.3 32-71
39.1 30-66
31.3 45-74
0.9 65
7.0 24-65
0.9 61
0.9 54
1.7 44-61
IBI score
44
52
32
133
-------
Simon
Table 7. Fish collected, length range (range measured in mm), number and
relative percent composition from the DuPage River sub-basin of
the Upper Illinois River collected during July and August, 1989.
location
DuPage River
at Shorewood
Species
Gizzard shad
Carp
Common stoneroller
Bigmouth shiner
Sand shiner
Spotfin shiner
Common shiner
Golden shiner
Bluntnose minnow
Creek chub
Quillback
Smallmouth buffalo
Blackstripe topminnow
Largemouth bass
Smallmouth bass
Bluegill
Green sunf ish
longear sunf ish
Qrangespotted sunf ish
IBI score
*
N
3
1
1
12
184
2
1
19
2
1
3
3
12
1
12
3
46
%
1.1
0.4
0.4
4.5
68.7
0.8
0.4
7.1
0.8
0.4
1.1
1.1
4.5
0.4
4.5
1.1
Range
69-95
350
50
25-69
40-58
46-55
55
25-69
250-325
195
30-67
55-138
45-325
95
64-89
38-66
East Branch
DuPacre River
N
19
4
6
6
29
1
3
1
1
4
1
32
%
25.3
5.3
8.0
8.0
38.7
1.3
4.0
1.3
1.3
5.3
1.3
Range
47-85
51-119 <
58-64
57-66
49-94
102
56-73
134
82
53-81
127
Dominant taxa at the DuPage River at
Shorewood included spotfin shiner
(68.66%), bluntnose minnow (7.09%),
and equal dominance of sand shiner,
smallmouth bass, and longear sunfish
(4.48%). Dominant taxa on the East
Branch included spotfin shiner
(38.67%), Gizzard shad (25.33%), and
equal numbers of sand and bigmouth
shiners (8.0%). Four intolerant taxa
were collected at Shorewood and one on
the East Branch.
Few larval taxa were observed in the
DuPage basin. Spotfin shiner larvae
were the only taxa observed and only
at the DuPage River at Shorewood.
Des Plaines River Basin; Three
stations were sampled in the Des
Plaines River basin, including the Des
Plaines River at Brandon Road (station
7), Des Plaines River at Riverside
(station 8), and Salt Creek (station
9). Seining and electrofishing
techniques were used at Brandon Road,
while only seining was conducted at
Des Plaines River at Riverside and
IBI scores at Brandon Road and
Riverside rated "poor" with equivalent
scores of 34 (Table 8). At Salt Creek
a score of 30 rated the site "poor"
(Table 8). Reduced metric scores at
Brandon Road were observed for five
metrics with low scores for number of
darter and sucker species, number of
intolerant taxa, proportion of
omnivores, and reduced catch per unit
effort. Dew scores at Riverside were
likewise a result of five metrics,
including numbers of darters, suckers
and intolerant species, proportion of
carnivores, and reduced catch per unit
effort. Six metrics scored poorly for
Salt Creek with low scores for total
number of species, number of darter,
134
-------
Upper Illinois River Water Quality
sucker, and intolerant taxa,
proportion of carnivores, and catch
per unit effort.
Dominant taxa at Brandon Road include
bluntnose minnow (39.74%), emerald
shiner (25.64%), and carp (10.26%). At
Riverside dominant taxa included sand
shiners (44.16%), bluntnose minnow
(19.05%) and spotfin shiner (14.72%).
Salt Creek was dominated by spotfin
shiner (50.0%), bluntnose minnow
(28.57%), and green sunfish (10.71%).
Intolerant taxa included two taxa at
Brandon Road, and a single taxa at
Riverside and Salt Creek. Unique taxa
collected in the Des Plaines River
included mosguitofish at Riverside.
Many of the fish collected during the
collections in the Des Plaines River
were young of the year specimens. An
abundance of tolerant taxa, i.e. green
sunfish, bluntnose minnow, and fathead
minnow, indicated degraded conditions
for most of this basin from the urban
and industrial areas of Chicago.
Chicago River and Canal Sub-Basin;
A single station was sampled in the
Chicago River basin. The North Branch
of the Chicago River at Tbuhy Avenue
(station 10) was sampled for 100 m and
consisted of entirely run habitat.
This station, although rigorously
sampled, did not produce any fish.
Several crayfish and a large snapping
turtle were collected and released.
This station scored the poorest of all
1989 Upper Illinois River stations
with a score of zero (no fish).
Kankakee River Basin; Two stations
were sampled in the Kanakakee River
basin, including the Kankakee River at
Momenoe (station 11) and Kankakee
River at Shelby, Indiana (station
12). Sampling at Momence consisted
entirely of seining for 300 m and
included 50% each of run and riffle
habitat. At Shelby, channelization of
the Kankakee River resulted in both
seining and electrofishing methods
needing to be conducted. Over 500 m of
reach was sampled by electrof ishing
and 50 m was sampled seining. The
habitat within this reach consisted of
65% run and 35% pool.
The Kankakee River basin consistently
scored the highest of all sub-basins
collected during 1989. A rating of
"good" was observed at Momence with a
score of 52, and a rating of "fair" at
Shelby with a score of 44 (Table 9).
The only low score at Momence was for
catch per unit effort, while at Shelby
low scores were given for number of
darter species, proportion of
carnivores, and catch per unit effort.
Dominant taxa at Momence included
spotfin shiner (41.04%), sand shiner
(18.66%), and orangespotted sunfish
(13.43%). At Shelijy dominant taxa
included spotfin shiner (87.45%), sand
shiner (4.73%), and carp (2.47%). The
number of intolerant taxa at Momenoe
was seven taxa and five taxa at
Shelby. At Momence unique taxa
collected included spotted sucker,
blackside darter, and mimic shiner.
Discussion
Water quality characterization of
twelve stations within the Upper
Illinois River basin provided expected
results based on known water
chemistry, areas of dominant land use,
habitat and known point source
dischargers (Fig. 2).
Increased biological integrity, as it
relates to water quality, was observed
from an upstream to downstream
direction for the all of the various
sub-basins. Reasons for these trends
in index of biotic integrity rating
depended on a variety of factors. In
the Fox River sub-basin, at two
similar sized streams, water quality
was considered "good" at Indian Creek
and "poor" at Honey Creek. Habitat
quality was the reverse, with Honey
Creek consisting of superior riparian
zone and habitat cycles, while Indian
Creek was in the center of a cow
pasture. The Fox River proper was
sampled only at a single site and was
135
-------
Simon
Table 8. Fish collected, length range (range measured in mm), number and
relative percent composition from the Des Plaines River sub-basin
Upper Illinois River collected during July and August, 1989.
T neat ion
Des Plaines River
Brandon Road
Species
Northern pike
Grass pickerel
Gizzard shad
Carp
Goldfish
Emerald shiner
Spottail shiner
Bigmouth shiner
Sand shiner
Spotf in shiner
Bluntnose minnow
Fathead minnow
Smallmouth buffalo
Blackstripe topminnow
Mosquitofish
Tadpole madtom
largemouth bass
Bluegill
Green sunf ish
White crappie
Black crappie
N
1
1
8
1
20
1
31
1
5
1
6
1
1
%
1.
1.
10.
1.
25.
1.
39.
1.
6.
1.
7.
1.
1.
3
3
3
3
6
3
7
3
4
3
7
3
3
Range
250
134
300-500
35
53-76
42
23-38
300
65-72
34
35-61
115
75
N
22
3
4
3
102
34
44
12
3
3
1
Des Plaines River
Riverside
% Range
9.5 59-105
1.3 372-750
1.7 41-60
1.3 39-46
44.2 22-65
14.7 22-65
19.1 21-60
5.2 22-32
1.3 26-37
1.3 22-66
0.4 84
N
1
14
8
1
1
3
•
Salt
Creek
% Range
3.
50.
28.
3.
3.
10.
6
0
6
6
6
7
33
35-58
25-43
24
22
65-125
IBI score
34
34
30
intermediate in quality between the
upper and lower tributary segments. A
rating of "fair" was scored because
of a lack of benthic species (e.g.
darters and suckers), however, a
number of catfish were collected
including various bullheads. Reasons
for a decline at Algonquin were due to
the uniformity of habitat (e.g. mostly
run), and the lack of riparian buffer
zone along the mostly residential
shoreline. Input of nutrients from
septic systems and runoff of
fertilizers have probably contributed
to degradation along this stretch of
the River. Upstream of the site was a
dam and downstream was the Algonquin
STP. Both of these may act as barriers
to recolonization of fish species from
upstream and downstream refugia. The
lack of darters was surprising since
suitable riffle habitat was present at
this site.
The DuPage River sub-basin, indicated
that the East Branch of the River was
"poor" and probably a result of
upstream perturbations. The East
Branch has undergone a series of
building projects in many of the towns
which line the River upstream. The
lack of a substantial fish population
at this station is indicative of areas
with organic enrichment. The
preponderance of green sunf ish and the
increase of black spot disease
affecting individuals of the
insectivorous trophic guild (e.g.
136
-------
Upper Illinois River Water Quality
Table 9. Fish oollected, length range (range measured in mm), number and
relative peroent composition from the Kankakee River sub-basin of
the Upper Illinois River collected during July and August, 1989.
Location
Kankakee River
at Momence
Species
Grass pickerel
Carp
Common stoneroller
Rosyf ace shiner
Sand shiner
Mimic ghifygr
Bigmouth shiner
Spotf in shiner
Common shiner
Bluntnose minnow
Creek chub
Hornyhead chub
Northern hogsucker
Shorthead redhorse
Spotted sucker
Brook silverside
Blackstripe topminnow
Rock bass
Largemouth bass
Bluegill
Green sunf ish
Longear sunf ish
Orangespotted sunf ish
Black crappie
Johnny darter
Banded darter
Blackside darter
IBI score
N %
2
50
4
110
20
2
1
1
1
5
7
3
12
3
5
36
1
1
3
1
52
0
18
1
41
7
0
0
0
0
1
2
1
4
1
1
13
0
0
1
0
.8
.7
.5
.0
.5
.8
.4
.4
.4
.9
.6
.1
.5
.1
.9
.4
.4
.4
.1
.4
Range
119-192
37-68
52-76
36-70
94-176
54-63
82
212
143
130-167
33-49
55-59
70-93
80-131
78-101
46-78
115
39
45-50
86
Kankakee River
at Shelbv
N
12
1
1
23
4
425
3
2
4
3
3
1
2
1
1
44
%
2.
0.
0.
4.
0.
87.
0.
0.
0.
0.
0.
0.
0.
0.
0
i
5
2
2
7
8
5
6
4
8
6
6
2
4
2
.2
Range
432-628
51
68
40-65
36-65
35-85
40-52
42-44
125-250
152-314
32-37
151
115-135
91
t
103
spotfin shiner) are usually a result
of fertilizer runoff and muck or soft
substrates. The lack of a riparian
zone probably has contributed greatly
to this problem. The downstream
location at Shorewood, on the mainstem
DuPage River had an IBI rating of
"fair to good". This particular
station had a high proportion of
smallmouth bass and insectivorous
cyprinids which usually indicate
increased water quality. A variety of
sunf ishes and other species typical of
good pool habitat were present, as
well as, specimens of herbivores and
other trophic guilds. This particular
station has potential for increased
water quality scores in future
sampling events.
The Des Plaines River sub-basin was
rated the second poorest of the Upper
Illinois River sub-basins. The River
typically scored "poor" with
downstream areas scoring higher than
upstream locations. Brandon Road lock
and Dam was a surprise since the
majority of the backwater habitat
possessed an abundance of aquatic
macrophytes and soft muck sediments. A
137
-------
Simon
high proportion of intolerant taxa
were present including a number of
game species, e.g. black and white
crappie, northern pike, and bluegill.
Tadpole madtom and smallmouth buffalo,
both benthic species indicated that
conditions were improving over
historic conditions at this location.
A nice firm riffle over a bedrock
substrate may provide adequate habitat
for Moxostoma species and other larger
river species. Although redhorses were
not collected during the present
collection, further sampling will
probably indicate their presence. The
site at Riverside was equally
impressive with a nice riffle/run
along the margin of the Cook County
Forest Preserve. A high amount of
erosion does affect this site, since
it too possessed few benthic species.
The presence of both bigmouth and sand
shiners, and a high proportion of
insectivorous cyprinids indicates that
it has potential to improve in water
quality. Salt Creek the furthest
upstream location sampled in the Des
Plaines sub-basin had limited habitat
diversity. Species collected at the
station were expected for the site,
due to the lack of true pool and the
limited, basically non-existent,
riffle habitat. Species using these
types of habitats would be excluded
from the site. Darters, suckers and
madtoms were not present since they
require clear clean riffles, and
centrarchids and black basses were
absent because there was no pool
habitat. Further downstream pool
habitat was present but was
considerably disjunct from the
location sampled. The major
contributor of poor conditions has to
be traced to the high degree of
urbanization surrounding the basin.
Sewer overflows, point source
dischargers, flow fluctuations, and
salt runoff from street cleaning
contribute greatly to the inability of
this basin to achieve its potential.
Habitat within the basin is adequate
to support more species than what
currently occurs.
The Chicago River and its supporting
canal system have been modified so
that their flow is away from lake
Michigan and into the Upper Illinois
River. This was done to protect the
City of Chicago's water supply from
contamination and send waste products
down the Illinois River. Better
treatment processes and increased
water quality regulation have reduced
the amount of waste going to the
system, thereby, having a dramatic
effect on the Upper Illinois River
mainstem. However, the station at
Touhy Avenue on the North Branch
Chicago River indicates that other
urban affects have reduced the
biological integrity of the water.
Straightening of the River channel by
channelization, runoff of road salts
used for winter, and severe bank
erosion have all but eliminated use of
the River for aquatic life. Although
the presence of luxuriant aquatic
macrophyte beds, debris piles, and
firm substrates should attract fish
species, no fish were collected after
extensive sampling at Touhy Avenue.
Overall, the Kankakee River sub-basin
possessed the best water quality among
Upper Illinois River sub-basins.
Channelization of the River within
Indiana has improved flow rates and
increased flushing rates into
Illinois. Water quality at Momence was
observed to possess a "good" rating
with an abundance of intolerant
species, including: three species of
darters, rock bass, various redhorse
and sucker species, and cyprinids. The
River at Momence has a shallow wide
topography with some islands and
vegetation along the stream margins. A
nice selection of habitat diversity
occurs within the area, however, no
pool habitat was located during
collection. Additional predators, such
as northern pike, smallmouth and
largemouth bass would have been
located if these pools existed further
improving the location score. At
Shelby, the Kankakee River although
still of good water quality had a
reduction in IBI rating because of the
138
-------
Upper Illinois River Water Quality
effect of channelization. The lack of
shallow shore margins,
the
preponderance of sand substrate, and
lack of heterogenous habitat has
precluded many fish species from using
the area. The lack of darter species
and catfish were probably the most
noticeable absent species.
Overall scoring indicated that the
Kankakee River, followed by the Fox
River, were the two best sub-basins in
the Upper Illinois River System, while
the DuPage, Des Plaines, and Chicago
Rivers were respectively the next
best. This presents an interesting
comparison since the primary land use
within the Kanakakee and Fox River
sub-basins include agricultural and
less-concentrated residential uses,
while the DuPage, Des Plaines, and
Chicago River sub-basins are heavily
populated urban and industrial areas.
A distinct difference between the non-
continuous non-point source of diffuse
pollution compared to constant
discrete point source input suggests
that the water quality in these five
sub-basins suffer from upstream inputs
from the City of Chicago and
industrial suburbs. The riparian
buffer zone and amount of
allochthonous input shows that a
increase in degradation is apparent as
one gets closer to the metropolitan
areas of Chicago. Increases in bank
stabilization, improvement in combined
sewer overflow and road runoff, and
other non-Tpoint source influences will
greatly improve the resiliency of
these Rivers.
Similar results were observed between
streams of equal size, third order
streams, e.g. Honey Creek, East Branch
DuPage River, and Salt Creek, were all
considered "poor" by IBI standards.
However, Indian Creek and the North
Branch Chicago River were outliers
representing the best and worst case
scenarios for the same order streams.
Acknowledgments
This report was prepared under
contract with the U.S. Geological
Survey, Raleigh, North Carolina
district. The sampling techniques
described were those conducted by the
U.S. Environmental Protection Agency,
Region V, Central Regional Laboratory.
Special thanks to Donald Krichiver,
Charles S. Steiner, Max A. Anderson,
and Pete Howe, U.S. Environmental
Protection Agency, Region V, Chicago,
Illinois, and Pete Ruhl, U.S.
Geological Survey, Urbana, Illinois
for their sampling assistance.
Literature Cited
Angermeier, P.L. and J.R. Karr. 1986.
Applying an index of biotic integrity
based on stream fish communities:
considerations in sampling and
interpretation. North American Journal
of Fisheries Management 6. In press
Fausch, K.D., J.R. Karr, and P.R.
Yant. 1984. Regional application of an
index of biotic integrity based on
stream-fish communities. Transactions
of the American Fisheries Society
113:39-55.
Illinois Environmental Protection
Agency (IEPA). 1988. Users guide to
IBI-AIBI - version 2.01 (A Basic
program for computing the Index of
Biotic Integrity within the IBM-PC).
State of Illinois Environmental
Protection Agency, Division of Water
Pollution and Planning Section,
Marion, IL. IEPA/WPC/89-007.
Karr, J.R. 1981. Assessment of biotic
integrity using fish communities.
Fisheries 6:21-27.
Karr, J.R., P.R. Yant, and K.D.
Fausch. 1987. Spatial and temporal
variability of the index of biotic
integrity in three midwestern streams.
Transactions of the American Fisheries
Society 116(1):1-11.
Karr, J.R., K.D. Fausch, P.L.
Angermeier, P.R. Yant, and I.J.
Schlosser. 1986. Assessing biological
integrity in running waters a method
and its rationale. Illinois Natural
History Survey Special Publ. 5, 28 pp.
139
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Simon
Mills, H.B., W.C. Starrett, and F.C.
Bellrose. 1966. Man's effect on the
fish and wildlife of the Illinois
River. Illinois Natural History Survey
Biological Notes No. 57.
Ohio Environmental Protection Agency.
1987. Water quality implementation
manual. QA Manual (3rd update) Fish.
Ohio Environmental Protection Agency.
Columbus, Ohio.
Omernik, J.M. 1987. Ecoregions of the
conterminous United States. Annuals
Association of American Geography, in
press.
Plafkin, J.L., M.T. Harbour, K.D.
Porter, S.K. Gross, and R. Hughs.
1989. Rapid bioassessment protocols
for use in streams and rivers: benthic
macroinvertebrates. US Environmental
Protection Agency, Monitoring and Data
Support Division, Washington, D.C.
Steffeck, D. and R. Striegel. 1988.
Macrobiological investigations that
relate to stream water quality in the
Upper Illinois River Basin.
Unpublished report. U.S. Fish and
Wildlife Service, Bloomington, IN.
U.S. Environmental Protection Agency.
1988. Standard Operating Procedure for
conducting rapid assessment of ambient
water quality conditions using fish.
USEPA, Region V, Central Regional
Laboratory, Chicago, IL.
U.S. Environmental Protection Agency.
1973. Biological Field and laboratory
Methods for Measuring the Quality of
Surface Water and Effluents.
Environmental Monitoring and Support
laboratory- Cincinnati, OH. EPA
670/4-73-001.
140
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Upper Illinois River Water Quality
Appendix A. Fish metrics used to score specimens collected from the
Sub-basins of the Upper Illinois River during July and
August, 1989.
Feeding
Species Native Endangered Tolerance Guild
Gizzard shad
Alewife
Skipjack herring
Northern pike
Grass pickerel
Carp
Goldfish
Common stoneroller
Rosyf ace shiner
Emerald shiner
River shiner
Mimic shiner
Sand shiner
Bigmouth shiner
Spottail shiner
Spotf in shiner
Cannon shiner
Golden shiner
Bluntnose minnow
Fathead minnow
Bullhead minnow
Suckermouth minnow
Creek chub
Hornyhead chub
White sucker
Shorthead redhorse
Silver redhorse
Quillback
Smallmcuth buffalo
Spotted sucker
Northern hogsucker
Brook silverside
Blackstripe topminnow
Flathead catfish
Channel catfish
Yellow bullhead
Black bullhead
Tadpole madtom
Stonecat
White bass
Yellow bass
Rock bass
Largemouth bass
Smallmcuth bass
Bluegill
Green sunf ish
N
I
N
N
N
I
I
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
Tolerant
Tolerant
Intolerant
Intolerant
Intolerant
Intolerant
«
Intolerant
Intolerant
Intolerant
Intolerant
Intolerant
Intolerant
Tolerant
Omni
Cam
Cam
Cam
Omni
Omni
Herb
Insect
Insect
Insect
Omni
Insect
Omni
Insect
Insect
Insect
Omni
Omni
Omni
Omni
Insect
Insect
Insect
Omni
Cam
Cam
Cam
Cam
Cam
Cam
Cam
> * 1 1 A 1
Habitat
Preference
SCR
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
x
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
x
X
X
X
X
X
X
X
X
141
-------
Simon
Appendix A (continued)
longear sunfish
Pumpkinseed
Orangespotted sunfish
White crappie
Black crappie
Yellow perch
Johnny darter
Rainbow darter
Fantail darter
Banded darter
Blackside darter
Logperch
Slerderhead darter
Freshwater drum
Mottled sculpin
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
Intolerant
Cam
Cam
Cam
Intolerant
Intolerant
Intolerant
Intolerant
Intolerant
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
S - Streams and smaller rivers
C - Creeks and brooks
R - larger rivers
Omni - Omnivore
Insect - Insectivorous
Cam - Carnivore
142
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