United States
             Environmental Protection
             Agency
             Environmental Monitoring
             and Support Laboratory
             PO Box 15027
             Las Vegas NV89114
x-/EPA
Distribution of
Phytoplankton in
Nebraska Lakes
Working
Paper 699

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DISTRIBUTION OF PHYTOPLANKTON IN NEBRASKA LAKES

                        by

 F.  A.  Morris*, M.  K.  Morris*, W. D.  Taylor,
L. R.  Williams, S.  C.  Hern, and V.  W.  Lambou

            Water and  Land Quality Branch
           Monitoring  Operations Division
   Environmental  Monitoring and Support Laboratory
              Las Vegas, Nevada  89114
         *Department of Biological  Sciences
           University of Nevada, Las Vegas
              Las Vegas, Nevada  89154
               WORKING PAPER NO.  699
         NATIONAL EUTROPHICATION SURVEY
       OFFICE OF RESEARCH AND DEVELOPMENT
      U.S.  ENVIRONMENTAL PROTECTION AGENCY
                 November 1978

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DISCLAIMER
This report has been reviewed by the Environmental Monitoring and
Support Laboratory-Las Vegas, U.S. Environmental Protection Agency, and
approved for publication. Mention of trade names or commercial products does
not constitute endorsement or recommendation for use.
11

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FOREWORD
The National Eutrophication Survey was initiated in 1972 in response to
an Administration commitment to investigate the nationwide threat of
accelerated eutrophication to freshwater lakes and reservoirs. The Survey
was designed to develop, in conjunction with State environmental agencies,
information on nutrient sources, concentrations, and impact on selected
freshwater lakes as a basis for formulating comprehensive and coordinated
national , regional , and State management practices relating to point source
discharge reduction and nonpoint source pollution abatement in lake
watershed.
The Survey collected physical, chemical, and biological data from 815
lakes and reservoirs throughout the contiguous United States. To date, the
Survey has yielded more than two million data points. In-depth analyses are
being made to advance the rationale and data base for refinement of nutrient
water quality criteria for the Nation’s freshwater lakes.
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Foreword
Introduction
Materials and Methods
Lake and Site Selection
Sample Preparation
Examination
Quality Control
Results
Nygaard’s Trophic State Indices .
Palmer’s Organic Pollution Indices
Species Diversity and Abundance Indices
Species Occurrence and Abundance .
Literature Cited
Appendix A. Phytoplankton Species list for the State
of Nebraska
Appendix B. Summary of Phytoplankton Data
CONTENTS
Page
111
1
2
2
2
3
4
5
5
5
7
9
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INTRODUCTION
The collection and analysis of phytoplankton data were included in the
National Eutrophication Survey in an effort to determine relationships between
algal characteristics and trophic status of individual lakes.
During spring, summer, and fall of 1974, the Survey sampled 179 lakes in
10 States. Over 700 algal species and varieties were identified and
enumerated from the 573 water samples examined.
This report presents the species and abundance of phytoplankton in the
9 lakes sampled in the State of Nebraska (Table 1). The Nygaard’s Trophic
State (Nygaard 1949), Palmer’s Organic Pollution (Palmer 1969), and species
diversity and abundance indices are also included.
TABLE 1 . LAKES SAMPLED IN THE STATE OF NEBRASKA
STORET No. Lake Name County
3101 Branched Oak Lancaster
3102 Harlan County Reservoir Harlan
3103 Harry 0. Strunk Frontier
(Medicine Creek)
3104 Hugh Butler (Red Willow) Frontier, Red Willow
3105 Johnson Reservoir Dawson, Gosper
3106 Lake McConaughy Keith
3107 Pawnee Lake Lancaster
3108 Sherman County Reservoir Sherman
3110 Swanson Reservoir Hitchcock
1

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MATERIALS AND METHODS
LAKE AND SITE SELECTION
Lakes and reservoirs included in the Survey were selected through
discussions with State water pollution agency personnel and U.S. Environmental
Protection Agency Regional Offices (U.S. Environmental Protection Agency
1975). Screening and selection strongly emphasized lakes with actual or
potential accelerated eutrophication problems. As a result, the selection was
limited to lakes:
(1) impacted by one or more municipal sewage treatment plant outfalis
either directly into the lake or by discharge to an inlet tributary
within approximately 40 kilometers of the lake;
(2) 40 hectares or larger in size; and
(3) with a mean hydraulic retention time of at least 30 days.
Specific selection criteria were waived for some lakes of particular State
interest.
Sampling sites for a lake were selected based on available information on
lake morphometry, potential major sources of nutrient input, and on-site
judgment of the field limnologist (U.S. Environmental Protection Agency 1975).
Primary sampling sites were chosen to reflect the deepest portion of each
major basin in a test lake. Where many basins were present, selection was
guided by nutrient source information on hand. At each sampling site, a
depth—integrated phytoplankton sample was taken. Depth—integrated samples
were uniform mixtures of water from the surface to a depth of 15 feet
(4.6 meters) or from the surface to the lower limit of the photic zone
representing 1 percent of the incident light, whichever was greater. If the
depth at the sampling site was less than 15 feet (4.6 meters), the sample was
taken from just off the bottom to the surface. Normally, a lake was sampled
three times in 1 year, providing information on spring, summer, and fall
conditions.
SAIIPLE PREPARATION
To preserve the sample 4 milliliters (ml) of Acid-Lugol’s solution
(Prescott 1970) were added to each 130-mi sample from each site at the time of
collection. The samples were shipped to the Environmental Monitoring and
Support Laboratory, Las Vegas, Nevada, where equal volumes from each site
2

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were mixed to form two 130—mi composite samples for a given lake. One
composite sample was put into storage and the other was used for the
exami nation.
Prior to examination, the composite samples were concentrated by the
settling method. Solids were allowed to settle for at least 24 hours prior to
siphoning off the supernate. The volume of the removed supernate and the
volume of-the remaining concentrate were measured and concentrations
determined. A small (8—mi) library subsample of the concentrate was then
taken. The remaining concentrate was gently agitated to resuspend the
plankton and poured into a capped, graduated test tube. If a preliminary
examination of a sample indicated the need for a more concentrated sample, the
contents of the test tube were further concentrated by repeating the settling
method. Final concentrations varied from 15 to 40 times the original.
Permanent slides were prepared from concentrated samples after analysis
was complete. A ring of clear Karo® corn syrup with phenol (a few crystals of
phenol were added to each 100 ml of syrup) was placed on a glass slide. A
drop of superconcentrate from the bottom of the test tube was placed in the
ring. This solution was thoroughly mixed and topped with a covergiass. After
the syrup at the edges of the covergiass had hardened, the excess was scraped
away and the mount was sealed with clear fingernail polish. Permanent diatom
slides were prepared by drying sample material on a covergiass, heating in a
muffle furnace at 4QQ0 C for 45 minutes, and mounting in Hyrax®. Finally, the
mounts were sealed with clear fingernail polish.
Backup samples, library samples, permanent sample slides, and
Hyrax mounted diatom slides are being stored and maintained at the
Environmental Monitoring and Support Laboratory-Las Vegas.
EXAMINATION
The phytoplankton samples were examined with the aid of binocular
compound microscopes. A preliminary examination was performed to precisely
identify and list all forms encountered. The length of this examination
varied depending on the complexity of the sample. An attempt was made to find
and identify all of the forms present in each sample. Often forms were
observed which could not be identified to species or to genus. Abbreviated
descriptions were used to keep a record of these forms (e.g., lunate cell,
blue—green filament, Navicula #1). Diatom slides were examined using a
standard light microscope. If greater resolution was essentia1 to accurately
identify the diatoms, a phase-contrast microscope was used.
After the species list was compiled, phytoplankton were enumer ated using
a Neubauer Counting Chamber with a 40X objective lens and a lox ocular lens.
All forms within each field were counted. The count was continued until a
minimum of 100 fields had been viewed, or until the dominant form had been
observed a minimum of 100 times.
Regi stered trademark
3

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QUALITY CONTROL
Project phycologists performed internal quality control intercomparisons
regularly on 7 percent of the species identification and counts. Although an
individual had primary responsibility for analyzing a sample, taxonomic
problems were discussed among the phycologists.
Additional quality control checks were performed on the Survey samples by
Dr. G. W. Prescott of the University of Montana at the rate of 5 percent.
Quality control checks were made on 75 percent of these samples to verify
species identifications while checks were made on the remaining 25 percent of
the samples to verify genus counts. Presently, the agreement between quality
control checks for species identification. and genus enumerations is
sati sfactory.
4.

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RESULTS
A phytoplankton species list for the State is presented in Appendix A.
Appendix B sunimarizes all of the phytoplankton data collected from the State
by the Survey. The latter is organized by lake, and includes an alphabetical
phytoplankton species list with concentrations for individual species given by
sampling date. Results from the application of several indices are presented
(Nygaard’s Trophic State, Palmer’s Organic Pollution, and species diversity
and abundance). Each lake has been assigned a four—digit STORET number.
(STORET (STOrage and RETrieval) is the U.S. Environmental Protection Agency’s
computer system which processes and maintains water quality data.) The first
two digits of the STORET number identify the State; the last two digits
identify the lake.
NYGAARD’S TROPHIC STATE INDICES
Five indices devised by Nygaard (1949) were proposed under the assumption
that certain algal groups are indicative of levels of nutrient enrichment.
These indices were calculated in order to aid in determining the surveyed
lakes’ trophic status. As a general rule, Cyanophyta, Euglenophyta, centric
diatoms, and members of the Chlorococcales are found in waters that are
eutrophic (rich in nutrients), while desmids and many pennate diatoms
generally cannot tolerate high nutrient levels and so are found in
oligotrophic waters (poor in nutrients).
In applying the indices to the Survey data, the number of taxa in each
major group was determined from the species list for each sample. The ratios
of these groups give numerical values which can be used as a biological index
of water richness. The five indices and the ranges of values established for
Danish lakes by Nygaard for each trophic state are presented in Table 2. The
appropriate symbol, (E) eutrophic and (0) oligotrophic, follows each
calculated value in the tables in Appendix B. A question mark (?) following a
calculated value in these tables was entered when that value was within the
range of both classifications.
PALMER’S ORGANIC POLLUTION INDICES
Palmer (1969) analyzed reports from 165 authors and developed algal
pollution indices for use in rating water samples with high organic pollution.
Two lists of organic—pollution—tolerant forms were prepared, one containing
20 genera, the other, 20 species (Tables 3 and 4). Each form was assigned a
pollution index number ranging from 1 for moderately tolerant forms to 6 for
5

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TABLE 2. NYGAARD’S TROPHIC STATE INDICES ADAPTED FROM HUTCHINSON (1967)
Index
Calculation
Oligotrophic
Eutrophic
Myxophycean
Myxophyceae
0.0-0.4
0.1-3.0
Desmi deae
Chiorophycean
Chiorococcales
0.0—0.7
0.2—9.0
Desmideae
Diatom
Centric Diatoms
0.0-0.3
0.0—1.75
Pennate Diatoms
Euglenophyte
Euglenophyta
0.0-0.2
0.0—1.0
Myxophyceae + Chiorococcales
Compound
Myxophyceae ÷ Chiorococcales +
Centric Diatoms + Euglenophyta
0.0—1.0
1.2—25
Desrnideae
TABLE 3. ALGAL GENUS POLLUTION INDEX
TABLE 4. ALGAL
SPECIES
POLLUTION
(Palmer 1969)
INDEX
(Palmer
1969)
Genus
Pollution
Index
Anacystis
1
Ankistrodesmus
2
4
3
Chiarnydornonas
ChioreIla
Closterium
1
Cyclotella
1
Euglena
5
Gomphonema
1
Lepocinclis
1
1
Melosira
Micractinium
1
3
Navicula
Nitzschia
3
Oscillatoria
5
1
Pandorina
Phacus
2
Phormidium
1
Scenedesmus
4
2
2
Stigeoclonium
Synedra
Species
Pollution
Index
Ankistrodesmus falcatus
3
2
2
Arthrospira jenneri
Chiorella vulgaris
Cyclotella meneghiniana
2
1
Euglena gracilis
Euglena viridis
6
Gomphonema parvulum
1
Melosira varians
2
Navicula cryptocephala
1
1
Nitzschia acicularis
Nitzschia palea
5
Oscillatoria chiorina
2
4
1
1
4
3
4
3
3
Oscillatoria limosa
Oscillatoria princeps
Osciulatoria putrida
Oscillatoria tenuis
Pandorina morum
Scenedesmus guadricauda
Stigeoclonium tenue
Synedra ulna
6

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extremely tolerant forms. Palmer based the index numbers on occurrence
records and/or where emphasized by the authors as being especially tolerant of
organic pollution.
In analyzing a water sample, any of the 20 genera or species of algae
present in concentrations of 50 per milliliter or more are recorded. The
pollution index numbers of the algae present are totaled, providing a genus
score and a species score. Palmer determined that a score of 20 or more for
either index can be taken as evidence of high organic pollution, while a score
of 15 to 19 is taken as probable evidence of high organic pollution. Lower
figures suggest that the organic pollution of the sample is not high, that the
sample is not representative, or that some substance or factor interfering
with algal persistence is present and active.
SPECIES DIVERSITY AND ABUNDANCE INDICES
“Information content” of biological samples is being used commonly by
biologists as a measure of diversity. Diversity in this connection means the
degree of uncertainty attached to the specific identity of any randomly
selected individual. The greater the number of taxa and the more equal their
proportions, the greater the uncertainty, and hence, the diversity (Pielou
1966). There are several methods of measuring diversity, e.g., the fomulas
given by Brillouin (1962) and Shannon and Weaver (1963). The method which is
appropriate depends on the type of biological sample on hand.
Pielou (1966) classifies the types of biological samples and gives the
measure of diversity appropriate for each type. The Survey phytoplankton
samples are what she classifies as larger samples (collections in Pielou’s
terminology) from which random subsamples can be drawn. According to Pielou,
the average diversity per individual (H) for these types of samples can be
estimated from the Shannon-Wiener formula (Shannon and Weaver 1963):
S
H = - P logy P 1
1=1
where P is the proportion of the ith taxon in the sample, which is calculated
from nj/N; flj is the number of individuals per milliliter of the ith
taxon; N is the total number of individuals per ml; and S is the total number
of taxa. However, Basharin (1959) and Pielou (1966) have pointed out that H
calculated from the subsample is a biased estimator of the sample H, and if
this bias is to be accounted for, we must know the total number of taxa
present in the sample since the magnitude of this bias depends on it.
Pielou (1966) suggests that if the number of taxa in the subsample falls
only slightly short of the number in the larger sample, no appreciable error
will result in considering S , estimated from the subsample, as being equal to
the sample value. Even though considerable effort was made to find and
identify all taxa, the Survey samples undoubtedly contain a fair number of
rare phytoplankton taxa which were not encountered.
7

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In the Shannon-Wiener formula, an increase in the number of taxa and/or
an increase in the evenness of the distribution of individuals among taxa will
increase the average diversity per individual from its minimal value of zero.
Sager and Hasler (1969) found that the richness of taxa was of minor
importance in determination of average diversity per individual for
phytoplankton and they concluded that phytoplankton taxa in excess of the 10
to 15 most abundant ones have little effect on H. This was verified by our
own calculations. Our counts are in number per milliliter and since
logarithms to the base 2 were used in our calculations, H is expressed in
units of bits per individual. When individuals of a taxon were so rare that
they re not counted, a value of 1/130 per milliliter or 0.008 per milliliter
was used in the calculations since at least one individual of the taxon must
have been present in the collection.
A Survey sample for a given lake represents a composite of all
phytoplankton collected at different sampling sites on the lake during a given
sampling period. Since the number of samples (M) making up a composite is a
function of both the complexity of the lake sampled and its size, it should
affect the richness—of—taxa component of the diversity of our phytoplankton
collections. The maximum diversity (MaxH) (i.e., when the individuals are
distributed among the taxa as evenly as possible) was estimated from loge S
(Pielou 1966), while the minimum diversity (MinU), was estimated from the
formula:
MinH = - ji iog 2 - [ N N ] log 2 [ N N ]
given by Zand (1976). The total diversity (D) was calculated from HN (Pielou
1966). Also given in Appendix B are L (the mean number of individuals per
taxa per milliliter) and K (the number of individuals per milliliter of the
most abundant taxon in the sample).
The evenness component of diversity (J) was estimated from H/MaxH
(Pielou 1966). Relative evenness (RJ) was calculated from the formula:
RJ = H—MinH
MaxH-Mi nH
given by Zand (1976). Zand suggests that RJ be used as a substitute for both
J and the redundancy expression given by Wilhm and Dorris (1968). As pointed
out by Zand, the redundancy expression given by Wilhni and Dorris does not
properly express what it is intended to show, i.e., the position of H in the
range between MaxH and MinH. RJ may range from 0 to 1; being 1 for the most
even samples and 0 for the least even samples.
Zand (1976) suggests that diversity indices be expressed in units of
“sits”, i.e., in logarithms to base S (where S is the total number of taxa in
the sample) instead of in “bits”, i.e., in logarithms to base 2. Zand points
out that the diversity index in sits per individual is a normalized number
ranging from 1 for the most evenly distributed samples to 0 for the least
evenly distributed samples. Also, it can be used to compare different
samples, independent of the number of taxa in each. The diversity in bits per
8

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individual should not be used in direct c iiparisons involving various samples
which have different numbers of taxa. Since MaxH equals log S, the expression
in sits is equal to logs S , or 1. Therefore diversity in sits per
individual is numerically equivalent to J, the evenness component for the
Shannon-Wiener formula.
SPECIES OCCURRENCE AND ABUNDANCE
The alphabetic phytoplankton species list for each lake, presented in
Appendix B, gives the concentrations of individual species by sampling date.
Concentrations are in cells, colonies, or filaments (CEL, COL, FIL) per
milliliter. An “X” after a species name indicates that the species identified
in the preliminary examination was in such a low concentration that it did not
appear in the count. A blank space indicates that the organism was not found
in the sample collected on that date. Column S is used to designate the
examiner’s subjective opinion of the five dcminant taxa in a sample, based
upon relative size and concentration of the organism. The percent column (%C)
presents, by abundance, the percentage ccniposition of each taxon.
9

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LITERATURE CITED
Basharin, G. P. 1959. On a statistical estimate for the entropy of a
sequence of independent random variables, pp. 333—336. In: Theory of
Probability and Its Applications (translation of “Teoriya Veroyatnosei i
ee Premeneniya”). N. Artin (ed). 4. Society for Industrial and
Applied Mathematics, Philadelphia.
Brillouin, 1. 1962. Science and Information Theory (2nd ed.). Academic
Press, New York. 351 pp.
Hutchinson, G. E. 1967. A Treatise on Lininology. II. Introduction to Lake
Biology and the Limnoplankton. John Wiley and Sons, Inc., New York.
1,115 pp.
Nygaard, G. 1949. Flydrobiological studies of some Danish ponds and lakes.
II. (K danske Vidensk. Selsk.) Biol. Sci. 7:293.
Palmer, C. M. 1969. A composite rating of algae tolerating organic
pollution. J. Phycol. 5:78-82.
Pielou, E. C. 1966. The measurement of diversity in different types of
biological collections. J. Theor. Biol. 13:131-144.
Prescott, G. W. 1970. How to Know the Freshwater Algae. William C. Brown
Company, Dubuque. 348 pp.
Sager, P. E., and A. 0. Hasler. 1969. Species diversity in lacustrine
phytoplankton. I. The components of the index of diversity
from Shannon’s formula. Amer. Natur. 103(929):51-59.
Shannon, C. E., and W. Weaver. 1963. The Mathematical Theory of Commu-
nication. University of Illinois Press, Urbana. 117 pp.
U.S. Environmental Protection Agency. 1975. National Eutrophication Survey
Methods 1973—1976. Working Paper No. 175. Environmental Monitoring and
Support Laboratory, Las Vegas, Nevada, and Corvallis Environmental
Research Laboratory, Corva1lis, Oregon. 91 pp.
Wilhm, V. L., and T. C. Dorris. 1968. Biological parameters for water
quality criteria. Bio—Science. 18:477.
Zand, S. M. 1976. Indexes associated with information theory in water
quality. J. Water Pollut. Contr. Fed. 48(8):2026—2031.
10

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APPENDIX A
PHYTOPLANKTON SPECIES FOR THE STATE OF NEBRASKA
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Achncmthes sp. D nobr’,’on divergens
Actinastrum hantzschii Dinohyron sociaZ.e
v. fiuviatile v. cvnericanum
Anahaena sp. Elakotothrix sp.
Ankistrodesmus fa catus Epithemia sp.
Ankis trodesmus fa 7 catus Errere 174 bornherniensis
v. a ularie Eudorina elegons
Ankistrodesraus fal catus Euglena sp.
v. mirabi lvs Fra.gi 1 ar - ia capucina
Aphanizoinenon floe-aquas FragiZari.a conatruene ?
As t sri one 174 formosa Fragi lana crotonensis
Caloneje lewie Fragilari.a inter,nedia ?
Carteria klebeii F’z’agiiaria lepto8taUron
Ceratium hirundinelia Fan ia sp.
Ceratiwn hirundinelia Gienodiniuzn gymnodiniwn
f. furcoides Glenodiniwn gymnodiniwn
Ceratiwn h -irundinella v. biscutelliforms
f. ecotticwn Glenodiniwn oculatum
Chl nydomonas sp. Gioeocyetis conpia ?
C l i lore goniwn sp. Gomphonema o livaceum
Closter’ium SP. Gyranodinium a ibuiwn
Cocconeis pla Gymnodiniuin ordinatwn
Coelastrwn CcJflb2 l .CWfl Gyrosigrna sp.
Coslastrwn cambricwn Hantzschia wnphiocys
v. intermediwn f. capitata
Coelastrwn reticulaturn Kirchnerielia sp.
Coelosphaeriwn naegelianwn Lagerheimia quadniseta
Cosrnariwn sp. LepocincliB sp.
Crucigenia apicul.ata Lyngbya sp.
Crucigenia rectangularis ? llzllomonae caudata
Crucigenia tetrapedia Melosira distans
Cryptomonas erosa Melosira granulata
Cryptornonas erosa Melosirci granulata
v. reflexa v. angustissima
CDyptoTnonas marssonii Melosira ital -ica
Cryptomonas ovata Melosira vari s
Cryptomonas refleza Merismopedia minima
Cyc lots 1 la meneghiniana Merismopedia tenuissima
Cyclotella stelligera Mesostigma viridie
Cymatop leura e 1 lip tica Micractiniwn pusi liwn
f. spiralis rncrocysti. -e aenuginosa
Cymatopleura so lea 1 crocystis incerta
C’ymbelia affinis Mougeotia sp.
C ymbelZa twnida Navicula latens ?
Cymbella turgida Navicula radiosa
Dactylococcopsis irregulani..s Neidiwn ? sp.
Denticula P. Nitzechia filiforinis
Diatoma elongatum Nitzschia pa lea
Diatoma vu igare Ni tzschia sigmoidea
Dictyosphasnium puichellum Qocystis sp.
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Ophiocytium capitatwn
Oscillatoria limnetica
Oscil.latoria tenuis
Pandorina inorurn
Pandorina pro tuberans
Pediastrwn boryanurn
Pediastrum duplex
Pediastrwn duplex
v. ciathratun
Pediastrwn duplex
v. reticulatum
Pediastrwn duplex
v. rotundatum
Pediastrwn simplex
v. duodenc2’iu n
Pediastruin tetras
Pediastrwn tetras
v. tetraodon
Peridiniuin inconspicuwn
Thacus acuininatus
Phacus longicauda
Phacus megalopsis
Pinnulczria sp.
Raphidiopsis curvata
Rhoicosphenia sp.
Rhopalodia gibba
Scenedesrnus abundans
Scenedesmus acuininatus
Scenedesmus arcuatus
Scenedesmus balatonicus ?
Scenedesmus bicaudatus
Scenedesmus bijuga
Scenedesmus bijuga
v. flexuosus
Scenedesmus dimorphus
Scenedesmus interinedius
Scenedesmus oh liquus
Scenedesmus opo liensis
Scenedesmus pro tuberans
Scenedesmus quadricauda
Scenedesmus raciborskii
f. granulatas
Schroederia setigera
Sphaerocy8tis schroeteri
Staurastrun chaetocerus
Stephanodiscus astraea
Stephanodiecus niagarae
Surirella angustata
Surirella ovata
Synedra acus
Synedra rump ens
Synedra ulna
Te traedron cauda turn
Tetraedron caudaturn
v. longecornuturn
Tetraedron hastaturn
Tetraethion mjnj nwn
Te traedron muticurn
2 ’s traedron trigonum
v. gracile
Tetrczstrwn ? glabrwn
Tetrastrwn S legans
Tetraetru n heteracanthurn
2’s trastrwn s taurogeniasforine
Trachelomonas abrupta ?
Trache lornonas ensifercz
Trache lomonas fluviati us
Trache lomonas intermedia
Trache lomonas p Zanctonica
Trachelornonas schauins Zandii
Trache lomonas verrucosa
Trache lomonas vo ivocina
Wislouchiella sp.
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APPENDIX B. SUMMARY OF PHYTOPLANKTON DATA
This appendix was generated by computer. Because it was only possible to
use upper case letters in the printout, all scientific names are printed in
upper case and are not italicized.
The alphabetic phytoplankton lists include taxa without species names
(e.g., EUNOTIA, EUNOTIA #1, FLAGELLATE, FLAGELLATES, MICROCYSTIS INCERTA ?,
CHLOROPFIYTAN COCCOID CELLED COLONY). When species determinations were not
possible, symbols or descriptive phrases were used to separate taxa for
enumeration purposes. Each name on a list, however, represents a unique
species different from any other name on the same list, unless otherwise
noted, for counting purposes.
Numbers were used to separate unidentified species of the same genus. A
generic name listed alone is also a unique species. A question mark ( ) is
placed immediately after the portion of a name which was assigned with
uncertainty. Numbered, questioned, or otherwise designated taxa were
established on a lake-by-lake basis; therefore NAVICULA #2 from lake A cannot
be compared to NAVICULA #2 from lake B. Pluralized categories (e.g.,
FLAGELLATES, CENTRIC DIATOMS, SPP.) were used for counting purposes when taxa
could not be properly differentiated on the counting chamber.
14

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LAKE AflE: BRANCHED OAK
STORII NUMBER: ‘ 1 1
NY(,AARD TROPHIC SlATE IHOICES
0411 0’, 17 7 ’ 07 02 7’, i9 26 74
MUOPHYCEAN 0310 £ u 1 ,l0 E ‘.. jC E
CIIICROPHYCIAM 0710 E 12/0 € u.O0 E
EUGLENOPIIYTE 0.10 7 0.12 1 0/12 ?
DIATOM 0.17 ? u.bl E I. 0 E
COMPOUND 12/0 E 20/0 E 5.0 E
PALMER’S OKOANIC POLLUTION INDICES
DATE 04 ii 74 07 02 7’, v 9 26 74
GENUS 02 03 10
SPECiES 03 3
SPECIES DlVE SITY AND AaUNOA .CE INDICES
DATE 04 17 74 07 02 7’. 09 26 74
AVERAGE OtVERS1TY H 1.3’, 2.93 2.85
Of TAXA S 23.Cu 3C.C0 11.00
NUMBER Of SAMPLES COhPO IrED N 3.00 3.00 3.00
NAXIMuM DIVERSITY S AXH ‘ ,.52 ‘,.S1
PIINUPIU,l DiVERSITY NINH 0.02 0.1 0.04
TOTAL DIVERSITY D Z7333.32 11bC .13 22942.50
TOTAL NUM6ER OF INUIV IDUALS#ML N 2O398.3 39o1.00 8050.00
£VCP ESS COMPONENT J 0.30 . 0 0.oS
RELATIVE EVENISS RJ
MEAN NUMBER UF IMO IVIOLJALSIIAXA I 88o.87 132.u3 3b3.33
NUMeER/ME Of QST A UNCANT TAXON K 15728.00 15 1. 0 2b41.00
15

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v. 51586)115 CR I I I I I 2.2) 58 I I I
£PhAMIZOMCN FtOS—AOIJA1 III. I I I III .oI 220 I II 6.4) 11)
aSh) l3M1LLA 008I,bSA (IL 11177.11 15728 I I I I I I
CALWIIIS 7 CLI. I I I I I I I I I I
CAITL I IA CCL I I I 11138.91 1541 I I I
CNLA TDDMON8S P (I I * I I I I I I I 1.01 129
COCCO NI IS CU I I I I I I I I I I
COCL*.5 1 3 U1 ’ CAMBRICUP. CDL I I S I I I I I I I I
COILASIS.J5 RR1 )CULATUM CDL I I I I I I I I I I
COILCiSPMRE*lUM NAIGELIAI4L.I’ CDL I I I I I I I I I 3.21
(fl5P.8 lU$ CII. $ I I I I I I I 3.81 04
CRUCIGINIR ICTRAPICIA CDL I $ I I I I I I 0.8* 04
C RTPTC1O IAS (IL I I I I2IIO.,* 390 I I I
Ck!PT0 5JNA . 55058 CCI Ill 2.81 112 I I I 141 7.21 580 $
CT. bII .IA CII. I I I 1 I I I I I I
C S1 CLI I I I 131 7.11 3C8 I I I
O ACIYLOCOCCGPSIS (IL I I I X I I I I I I
CDL I I I I I 2.21 88 I I I
DICTYOSPHAFRIUM PUICIIILL. .$ CDL I I $ I I I I I 2.41 1 3 U
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V. ASEIIICANUII CII. 141 b.SI 1334 I I I I $ I
LLAI*1QIH SIX CII. I I I I I I J I I U
FLAIELLAIE .1 CIt $31 0.51 )334 I I U X $ I 4.01 322
FLAGILLAII 52 C LI. Ill 4.21 65* I U I I I
IL*GIILAI(S CII I I I I 114.41 572 I I I
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CIINODIM IUM DCULAIIJM CII. I I I 141 3.3) 132 I I I $
CTIIP.OGIM IUS 0RO1M*IUN ( IL I I I I I I I I I I
LACIRHIIMIA ;UADRISL1I CII. I I 0.51 95 I I I I I I
LIPOCINCLIS CII. I I I 1 I I I I I I I
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SICOO(’IS!IS ALRU 2NUS8 CDL I I I i I I 4.41 176 131 2. I 193
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PIOLASTNUS DUPLIX I I I I I I I I I
V. CLaIHRATU CCL I I I * I I I * I I I
510. 1 .6 15 UIAJOM CII. I I I I I 4.4U 170 I I I
PI’*CUS CII. I I I I I I I I I
puQICC PHINII CIL I I I I I I I U I $
SCCNLC.(S$U5 LIJUI.A CDL I I I I I I I I 1.01 129
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V. ILLIUDSUS CGL I I I I I I I I I I
SCINIOU ISUS UA0R ICAL.LIL C CL I I I 1 I I I I I U
¶CIN(D% 35105 5 5(180 ) 5* 1 1 I I I I I I I I I
I. GIAPIULATAS CU ). I I I I U I I I I I
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TITRAIE.RQN HAS TATUS (IL I I S I I I I I I I
rilpaSTlupI !TAUKUI.LMIA* 13 8 5 1 ( CL I I 7.21 45 I I I I I I
3961
16

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LAKE NA (: HARLAN
SIDRET MUM ER: 31(i2
NYC ,AARO TROPHIC STATE IMOICIS
DATE U’. 16 74 06 2b 7 u9 3C 74
MYXUPHYCEAN 0110 E 0413 £ 03/0 L
CHLUROPHTC(AN O1I( E 1210 E 13/0 £
EUGLENOPHYTE 0.50 E 0.31 £ .i .12 ?
(IIA1(Th 0.21 ? 0.67 E 0.57 E
CONPOUND 0610 L. 2510 E 22/0
PaLMIR’ ORGANIC POLLUTTOM INDICES
DAlE 04 16 74 06 28 74 09 30 74
GENUS 03 C9 11
SPECIES CO 00 07
SPECIES DIVERSIIY AMO A6UN0A CE INDICES
DATE U4 16 7’, 06 2b 74 9 30 74
AVERAGE DiVERSiTY H 1.64 3.37 2.23
NLJN8LR OF TAXA S 25.00 37.00 33.00
NUMBER ( F SAMPLES C0 iP0SITLD H 3.00 3.J3 3.03
? AXIP1UM DIVERSITY MAXH 4.64 5.21 5.04
IHUMUM UIVERSITY M1NH 0.01 0.09 0.06
IQIAL UAVERSITY 0 43199.2 ’ 1918d.7a 159uC.18
TOTAL NUMBER LW 1NUIV IDUALS/M1 N 26341.0V 5b94. ’0 71bb. )0
LVEFIE5S CUmPOP ,(IIT J 3.35 0.65
RELATiVE EVIP .ESS RJ 0.36 0.65 0.4’,
jEAN NUMBER OF INDIV1OUALS/TAXA I. 13 ’3.b4 153.J9 217.15
NUMBERIML UF MOST A6UNDANI TAXON K 17479.00 I4bb.i)0 3555.00
17

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122$ 4A I: .*2$A$i CC I MI IMU $(a
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. lb 14 39 30 74
I AL(.AL I ALGAL I ALGAL I
UMI2S I u .IT I UMI1S I
102$ IS 2G PLI ML IS C ELI III IS CC PER ML I
£CEIMISIWUP .i*IiILSCHII I I I I I I I I I $
V. ELUg IACILI CIL I I I I I I 1 I I $ I
ANABSIMA IlL I I I $ $ I I I $ $ $
*M2ISIL.JDISMUS F&LCA$US ( II I I I I I C I I 0.31 54 I
6PII*NIZJD1LHCJ ELUS—.GUAI P IL I I I 121 14.71 131 I I I
ASII2LCN(LLA EORMUSA CCL 12110.01 42 11 I I I I $ $ $ I $
CA E ILPIA C I I. I I I I I I I I I * I
CAR TEE CA *LEBS1C CCL $ I $ 13115.41 £79 I $ I $
CCR*IIU$ HIRUNDIMILLI CCL I I $ I $ I I $ I I $
C0&LASTR$JM CAM%6ICUII CCL I I I I I I I I I I I
COILASI2 $.M CAMIRICUM P C C I I I I $ I I $ I I I
CPTP!TJMUIIAS LEOSA C(I 151 3.51 392 $ I 4.41 251 I I I
Ck,PELMCI IAS PIELLIA CL I I I I I $ I I I I I I
1yPTua.2NAS Pp. CCL I I I I I I 151 1.51 IC3 $
CTCL PEL1A CCL I1IIo. $ 17S79 $ $ 2.91 1a7 $2122.01 $016 I
CY IECPL(UIA 501(2 CII. $ I I I I I I I I I I
CYPLELLA EEL S I I $ $ I I I I I I
DACITLUCCCCLPSCS ICI L RI3 CCL $ C 3.71 979 I I I 1 I $ 2.3$ 102 I
C IA IOPI VUL(.AIL CII $ I I I I I I I I * I
UICTICSPSAEPIUI$ P,JLCNILLU M CCL $ I I I $ $ I I I I I
LIkIRILLA CG$’NI,LnLL .SLS CCL I $ $ I $ I I $ I I I
IuGUI.L ((I I I $ I I I 3.71 42 I I $ 1 I
UAr CLLaIi .1 CI I $31 8. ,I 21G5 I I 2.91 107 i i I
rL..6LtLAIC $3 (IL I I I I I I $3114.71 $050 I
$AG$LARIA (CL 1$ I I 1$ I II I I
II*C$La A CRLTUPsII .SIS CLI $ I $ I I $ 1.41 419 I I I
GYrNGLINLUM ALB I,IUA CII. $ I .ZI 9 I I 0.7$ 42 I I I I
CCL I I I I I I 2 $ I I
LI,4A1 1 CCII CFL $ I 3.2$ I I I I I I $
CII I $ I 1 I I $ $ I S I
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V. 6,4bU)IISSIMA CII $ I $ PSI 5.11 293 $ I I 2 I
$$2 ISMUMLO IA MI$$MA CCI , I I I $ $ I I $ 1.51 103 I
IMI5O3II MA VIPIDI . CI I $ $ $ $ I $ I I 0.31 54 I
M ICRACI IrII IJM PiJSILLUM C DI. $ $ I $ $ I * $ I I I
M$CkCCT .II5 .I$#UC ’II.JSA CCL $ I I I I 1.5$ e I I I I
MICROCTSIIS INCLI IA C DL I I $ I I I $ I 1.1$ R I I
MDV$Ct.LA CLI. I $ $ $ I I I I I I I
NAVLCIJLA .1 CCL $ I 3.25 4Q I $ $ $ I I $
NaV$CLLA 12 CII I $ $ Z $ $ I $ I I
MEIO$$JM I CCL $ I $ I I I I $ I I $
NIIZSCMIA 2$ CIL I S I I I I S $ S I
ITZSC$iLA .2 CII I I $ 2 I $ $ I $ I $
M$1ZSC,HI* 23 (CI I I I I I S I $ I I 2 $
N$TzS(HL2 24 CCL S I I I I I I I $ I I
MIIZS(N.A IS CCL I $ $ I $ I $ I 1.1$ 31 I
N ITZSC$.$a 26 ( IL I I I I I 3.71 42 $ $ $ I
OOCT3IIS CII I I I $ $ I 1 I I I I I
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PH2CUS LQMG$CAIJO& CCL I I I I I I I $ I I I
PHACUS ILGALCiPSIS CII. $ I I I $ I I I $ I I P
SCI,iCICSMUS ALUMOI1IS CCL I I $ I I $ I I 3.11 54 $
SCLII(.I IUS j ,CI, IIAI.JS (CI I $ I I P 1.51 2 $ $ $ I
SCIMIUS PtJS OS,IGkPHUS ((.1 I I I I I S $ I $ I I
SCCNL.$S US IMT(RMCOLUS CCL I I I $ I I $ $ $ I I
SCINCUISMUS 0.. a0k$CaU0A CDL I I 0.21 49 I I v.?I 42 1.$ 1.51 105 I
5CPINuIOENla 51212112 (IL I $ $ I I 2.71 ZOV $ I .4$ 27 $
SPUALPUC TS 115 SCHICiI Ill I (CL I I I I $ I £ I $ I
SI(PKAI’ O OISCUS CCL III 3.21 332 14$ 1.3$ 502 $1I49.I I 35 $
SU$ ’ 111112 ((1 I I $ 2 $ I I I $ I I
SUIIR*LLA ANGU TAIA CII $ $ I a I I I $ $ I
SU&LR(ILA OVA IA CII I I I I I $ I $ I I $
11 Cf I $ 3.05 147 I I 1.5$ $4 S $ $
STM UI ULkA CEL I I I 2 $ $ I $ $ I
TI $RALC.UI MUIICUN CLI I I $ I $ $ $ I I I
IC ICi I It. R 14 ILRACAI.t. (_$ (01 I $ I I I 1. I $4 I I I
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TRACHILOMOPI&S SCH*ULNSLAMGI I CLL I I $ $ I $ I I I I
v I SLOIiC$$ILLA (EL $ I I I $ I I $ S I
Total 2639 1 5094 7 566
18

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LAI E NA . E: HM ’RY 0. STRWu
StORFI NUMBER: 31C3
NYGAA U IkGPHIC SiAn r ICE!
DAlE 34 lb 74 . 7 l 74 .9 27 7 ’ .
SI7AUPHYCEAN 0.50 E 03/0 E I3 0
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LUGLENOPNTTE 0/02 2 3! ..5 2 0.22 L
OIAION 0.57 E 0.75 E 3.71
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PALMER’S UkGANIC POLL a1I3N 1NOICES
t) TE C’. lb 74 07 31 74 .)9 27 7’.
G IUS CO 2 07
SPECILS 33
SPECIES OIV RSIT AND ABUNDANCE INO1CES
OATE 04 lb 7’. 31 7 J 27 74
AvERAGE UIvEflTY N .88 2.38
NUP% ER JF IAXA S 19.30 lb.’..t)
NUMB(k OF SAMPLES COMPUS]1EO N 2.3) 2.3 2.U3
MAXIMUM DIVE $I1T MAXH 4. 4.C3 4.58
MIP .UNuM DivE ISITY ? ‘IP1H (.00 0. .5 (‘.05
TOTAL. DIVERSITY 0 b’311.28 8b32.Zb 15 ’ 72.2 .
TOTAL MU EetR CF iN01VlDUAL iML N 73081.00 3 27.C s b42C.3’ )
VENtSS CUIPCP EN1 J 3.21 3.6’)
RELAIIVE EVLP .ESS RJ i..z l 0.59 0.53
MEAN Nu thU OF INOIVIL,UALS IT / lA I 3846.37 226.69 Zb7.53
NUM6ERIML OF MUST AÔIJNC .ANT TAXON V. 62062.30 1596.00 3 ’ b8.00
19

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tAKE MAul: HUGH BUTLER
SIGRET NUM2ER: 3104
r’uTGAAkU T C PH1C SlATE I CICES
LAIE 34 It 74 07 Cl 7 ° 27 7 ’u
MTXOPHrC(AN 0110 E 03/0 1 I. .C E
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DIATOM 0.43 1 0.b7 F 0.42 £
CDNPCUND 1310 1 18/0 1 7.50 F
PALMER’S ORGAnIC POLLUTIOn INDICES
DATE 04 lb 74 07 01 74 .9 27 7’,
GENUS 05 15 35
SPECIES 33 C7 00
SPECIES DIVERSITY AND AJ .0aN(E II D iCES
DaTE 04 10 74 U? 01 7’, 9 27 74
AVLFAt,E U1VEM ITY H 2. Ob 3.5 2.75
P’UMbLR OF IAXA S 25.00 28.00 24.33
MUIIGER OF SAMPLES CO ’1PO5ITED M 2.00 3.00 3.3 0
P AX1MUM DIVERSITY IIAXH 4.0’, 4.81 5.09
M1NUM jM UIVE. SITY HINH 0.01 ).C b .15
TIJIAL DIVERSITY 0 03004.30 lb 42 .42 7004.75
TOTAL NUMBER OF IND IV1DuALS/rL N 30905.00 4b73.. C 275c.00
EVENESS COMPOPIENT J 0.44 3.74 C.5.
RELATIVE EVEI .ESS RJ $ (.45 . 4.7 ’, 0.53
nEAN NUMbER UP IMOIV1OUALS/lAXA L 1230.20 ioo.b’1
NUMBER/MI OF MUST A6UP OAU( TAXON K 1c84 .CO 8j5., 3 LIBC.36
21

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GENUS 17 11
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23

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LAKE MANE: MCCONAUGHY
?,TOWET t4UMBEk: 3106
MYGAARD IROPMIC SlATE It 0ICES
CATE 0’, 7’, 7 01 7’, ;9 27 74
‘ YX( PHYCEAN 0110 E 03/0 E 2.Co E
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DATE C 4 15 74 07 01 7’, 09 27 74
GENUS C l ii )
SPECIES 00
SPECIES DIVERSiTY AND AIUNOANCE INDICES
DATE 04 15 74 07 03 74 39 27 7’.
AVCRAGE DIVERSITY H 2.23 3.17 3.37
NIjlib1 Uf 1 /&XA S 23.00 2 1.C0 48.00
NUMBER OF SAMPLE IWIPOSITED N 3.Jt) 3.u O 3.00
PAXIMLI1 L IVERSITT I A2H “.52 4.39 .52
MINUMUM DIVERSITY MINH 0.03 0.08 C.t3
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TOTAL NUP.81R CF INLi1ViDUALS/ ’L P4 12239.0t 3311.00 4933.0w
EVEP.E SS C ).IPUNENT o .. ‘ .c 0.72 C.61
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MEAN NUMBER OF Ir .DIVIDUALS/IAXA L 532.13 )57.(,7 1 ’7.2s
NUMBER /N t 01 MU 1 ABUNIJANI TAXCN K 5173.33 602.00 1023.JU
25

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LA cE NA 1E: PAWNEE LAKE
S1OR 1 NUMBER; 3107
4VGAAI 0 TI CPH]C si r ir cic
,ATE C ’ 17 74 ‘37 32 7’, , Q Ze 74
MYX0PHYL AN 1. O E 1.b7 E ‘ 30 E
CHLOROPMTC(AH 0/uI 0 3.U0 8 9.00 E
LUCLENOPHYTE l.( 0 8 3.14 ? 0.C8 ?
DIATOM 0.80 8 3.00 8 5.00 8
CCHPOUPIO 6.00 8 b.33 8 89.0 8
PALMER’S ORGANIC POLLUTiON INDiCES
DATE 04 17 74 07 ( .2 74 9 Zb i ’ ,
GENUS 01 02 32
SPECIES 0(1 JO
SPECIES DIVEPSITY AND ABUNDANCE INOICES
GAlE C4 17 74 J7 02 74 9 28 74
AVERAGL DIVERSITY H 2.13 3.52 2.71
N(,Mbf OF T A S 21.C0 33.’i O 27.03
NUMBER OF SAMPLES COMPOSITED H 2. 3 2. Ou 2. 30
IAX1HU OIVERSI1Y $AXH 4q39 5• 4 4.75
MINUIfl.i DIVERSiTY tiINH (1.14 0.15 C.1t
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TOTAL NuMBER OF INDIVIDUALSIML N i698. . . i 2789.30 4057.30
IVENESS COjiP(ltsENT J 3•’,9 3 .7 C.57
RELATIVE VENE S RJ .47 0.89 0.58
MEAN P’UMBLR CF IND1VI1 ’UALSITA 4 L O.8u 84.52 78.89
NUM8ERIML OF HOST ABUNDANT TAXON K 049.03 834.0. ) 785.00
27

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LA) E bA1IE: SHERMAN C0uNT RIS.
ST0 ET UMeER: 31u8
NYGAA . TROPHIC STAlE INC ICtS
DAlE 4 17 74 31 01 7 Z7 74
MYXOPHYCEAN 03/0 £ 02/U L 2.00 C
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DATE C4 17 74 07 01 74 9 27 74
GENUS 04
SPECIES Co
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DATE C” 17 74 07 01 7’s 09 27 74
AVERAIE 0IVE S1TY H 2.83 2.35 1.69
NUMd R OF 1*1* S 14.00 12.00 Z5. 0
NUMBER OF SAMPLES C0 POS1TEO N 2.30 2.C0 2. 0
MAXIMUM DIVERSITY NAXH 3.81 3.58
M1MUMUM DIVERSITY MIHH 0.1C 0.09
TOTAl. DIvERSITY 0 4525.17 3614.30 5213.65
TOTAL NUtIUER OF I DIvI0UALS/P L N ]599.OC 1538.00 30b 5.0C
(VEMESS CU,jPC, EMT j 0.74 0.bb 0.36
RELAIIVI EVENESS P . 1 0.7’, 0.6! u.36
MLAN NUIIBEb OF INOIVIDUALSITAXA L 114.21 128.17 113. ’3
NUMBER/MI OF MUST AiIUNOANT TAlON K 503.00 461.00 2198.00
29

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LAKE A1E S ANSCN
STC.RET NUMBER: 3110
NTGAAIC IROPHIC STATE INDiCES
DATE C4 1 74 30 28 7 . 9 27 7’.
MTXCJPHYCEAU 0!CZ 0 3.00 E 1.50 E
CHLOIJOPHYCEAN 1.00 E ‘ ,.OO E “.50 1
EUGLLNOPIITTE 01C2 0.14 7 0.42 1
DIAIOM 0.12 7 0.50 1 .33 I
COMPOUND 1.5 E 9.00 1 9.50 1
PALMER’S ORGANIC POLLuTIOM IMOICES
DATE 04 15 74 06 28 74 ,j9 27 74
GEM$ S 01 00 11
SPECIES 02 00 03
SPECIES D1VERSIIY AND ASUNDANCE INDICES
DATE 0’ , 15 74 Ob 28 74 C9 27 74
AVERAGE DIVERSITY H c.3? 2.9’ 3.30
NOPibIR OF TAXA S lt.0O 18.03 32.’J3
NUMBER OF SAMPLES CQr P0SITED N 2.uO 2.00 2.00
MAXIMUM DiVERSITY MAXH 4.30 4.17 5.00
PtINUMUN DIVERSITY MLMH 0.01 3.11 C.L’ .
TOTAL DiVERSITY 0 5968.47 5779.70 b2Sb.)3
TOTAL NUMBER CF i 4b1VIDUALSIML N 16131.03 19 ’ 3.O0 2752.00
EVIi’ESS COMPONENT J o.)’ 0.70 C_bc
R(LA1IVE EVI1IE5S RJ 0.13 0.69 C.59
MOAN NUMBER OF INDIVIDUALS 1IAXA L 1008.19 110.72 86.00
MUMBE IIML UF nOST A8UNDAMT TAXOY4 F. 15214.00 413.30 912.30
31

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