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
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Forward  - Historical  Perspectives
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                               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

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     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-

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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

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 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

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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

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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

-------
 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
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90


80

70
Coefficient
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Variation so

40
30
20
10
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Aquatic Life Use Impaired

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              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

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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





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s
I
25
20
15
10

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                                            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

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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

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 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

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  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

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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.

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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

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 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

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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

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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

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                     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

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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

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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

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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

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 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

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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

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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

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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

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 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

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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

-------
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

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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

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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

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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

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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

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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
Project  MN-42-25  of  the  Mclntire-
Stennis Cooperative Forestry Research
Program and the USDA.  Publication No.
18369 of the Scientific Journal Series
of    the   Minnesota    Agricultural
Experiment Station.
T .1 l-orati TTTP
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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

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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

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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

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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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Lower Des  Plaines River
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Wetzel.   1986.   Des  Plaines   River
long-term monitoring program, Phase I.
Aquatic   Biology  Technical   Report
1986(6).  Illinois  Natural   History
Survey, Champaign.

Tazik, P.P. and Sparks, R.E. 1987. Des
Plaines  River  long-term  monitoring
program,  Phase  II.  Aquatic  Biology
Technical  Report  1987(4).  Illinois
Natural History Survey, Champaign.

Tazik  P.P.   1988.  Des Plaines  River
long-term monitoring program,  Phase
III. Aquatic Biology Technical Report
1988(5).  Illinois  Natural   History
Survey, Champaign.

Tessier, A. and P.G.C. Campbell. 1987.
Partitioning   of  trace   metals  in
sediments:    relationships    and
bioavailability.    Hydrobiologia
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
20:31-40.

Wilkinson, L. 1987.  SYSTAT: the  system
for    statistics.   SYSTAT,    Inc.,
Evanston, IL.

Wright,  J.F., P.O. Hiley,  S.F. Ham,
and A.D.  Berrie. 1981. Comparison of
three mapping procedures developed for

                                      99

-------
        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

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                    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

-------
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.

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.  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.
                                     119

-------
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

-------
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

-------
 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

-------
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

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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

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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

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 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

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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

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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

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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

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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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