United Suites
           Environmental Proln linn
           Agency
             Environmental Monitoring
             Systems Laboratory
             PO Box 15027
             Las Vegas NV 89114
              i-h ;md Development
EPA
Distribution of
Phytoplankton in
Missouri Lakes
Working
Paper 698

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DISTRIBUTION OF PHYTOPLANKTON IN MISSOURI LAKES

                      by

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

          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. 698
       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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CONTENTS
Page
Foreword iii
Introduction . . 1
Materials and Methods . 2
Lake and Site Selection . 2
Sample Preparation . 2
Examination 3
Quality Control 4
Results . 5
Nygaard’s Trophic State Indices . 5
Palmer’s Organic Pollution Indices . 5
Species Diversity and Abundance Indices . 7
Species Occurrence and Abundance . 9
Literature Cited . 10
Appendix A. Phytoplankton Species list for the State
of Missouri 11
Appendix B. Summary of Phytoplankton Data 14
V

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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
6 lakes sampled in the State of Missouri (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 MISSOURI
STORET No.
Lake Name
County
2901
Clearwater Lake
Reynolds
2902
Pomme de Terre Reservoir
Polk, Hickory
2903
Stockton Reservoir
Dade, Polk, Cedar
2904
Lake Taneycomo
Taney
2905
Thomas Hill Reservoir
Macon, Randolph
2906
Wappepello Reservoir
Wayne, Butler
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 outfalls
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 morphornetry, 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.
SAMPLE 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
examination.
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-’.ml) 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 Karoe 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 coverglass. After
the syrup at the edges of the coverglass 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 coverglass, heating in a
muffle furnace at 400° 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.
EXAMINAT ION
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 essential 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 intercoinparisons
regularly on 7 percent of the species identifications 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 forihe State is presented in Appendix A.
Appendix B summarizes 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 Chiorococcales 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 pol1ution_to1erant 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
Desmideae
Chiorophycean
Chiorococcales
0.0-0.7
0.2-9.0
De smideae
Diatom
Centric Diatoms
0.0—0.3
0.0—1.75
Pennate Diatoms
Euglenophyte
Euglenophyta
0.0-0.2
0.0—1.0
Myxophyceae + Chlorococcales
Compound
Myxophyceae + Chiorococcales +
Centric Diatoms + Euglenophyta
0.0-1.0
1.2-25
Desmideae
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
Chiamydomonas
Chiorella
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
Stigeoclonium
4
2
2
Synedra
Species
Pollution
Index
Ankistrodesmus falcatus
3
2
2
Arthrospira ,jenneri
Chlorella vulgaris
Cyclotella meneghiniana
2
1
Euglena gracilis
Euglena viridis
6
Gomphonema parvulum
1
Melosira varians
2
Navicula cryptocephala
1
1
5
Nitzschia acicularis
Nitzschia palea
Oscillatoria chlorina
Oscillatoria limosa
Oscillatoria princeps
U?Eillatoria putrida
Oscillatoria tenuis
Pandorina morum
2
4
1
1
4
3
Scenedesmus guadricauda
4
3
3
Stigeoclonium tenue
Synedraulna
6

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extremely tolerant foms. 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 formulas
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. log,
i=1
where P is the proportion of the ith taxon in the sample, which is calculated
from ni/N; ni 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 1092 S
(Pielou 1966), while the minimum diversity (M1nH , was estimated from the
formula:
= - • ! log . - [ N N ] log 2 [ N N ]
given by Land (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
Max H-Mi nH
given by Zand (1976). Land 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 Wilhm 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 comparisons 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 fomula.
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 dominant taxa in a sample, based
upon relative size and concentration of the organism. The percent column (SC)
presents, by abundance, the percentage composition 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, L. 1962. Science and Information Theory (2nd ed.). Academic
Press, New York. 351 pp.
Hutchinson, G. E. 1967. A Treatise on Limnology. II. Introduction to Lake
Biology and the Limnoplankton. John Wiley and Sons, Inc., New York.
1,115 pp.
Nygaard, G. 1949. Hydrobiological studies of some Danish ponds and lakes.
II. (K danske Vidensk. Seisk.) 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. D. Hasler. 1969. Species diversity in lacustrine
phytoplankton. I. The components of the index of diversity
from Shannon’s formula. Pmer. Natur. 103(929):5]—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, Corvallis, 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 MISSOURI
11

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Achnanthes microcephala Euastrwn denticulatwn
Actinaetrwfl gracililfllAlfl uglena acue
Anahasna SP. Euglena ehrenbergii
Ankistrode8mus falcatus Eugl.ena g-rczci lie
AnksitrodesmU8 falcatue Euglena O yurV8
v. aciculai’i-s v. minor
AnkistrodeeflTu8 falcatus Eug Lena subehrenbergii
v. r,rLrabilis Euglena triptez e
Aphanizorne non floe-aquas Rragi Lana crotonensia
Aphanothece sp. Franceia sp.
AstenionelZ42 formosa Glenodiniuin a culifeDWfl
Aaterzonella formosa Glenodinium gymnodiniurn
v. gracillima GZ.enodiniwn gymnodiniuzn
Cartenia sp. v. biscutel.liforme
Ceratiwn hirundinella GlenodiniziJn ocuZa n
f. brachyceras Glenodiniwn penardiforme
Ceratiwn hirundineUa Gornphonema olivacewn
f. furcoidee Gomphosphasnia
C zloJnydcn7ona8 Sp. Gymnodiniu)fl albuiwn
Chiorogonvuin SP. Gyrosigma sp.
Chroon7Onas acuta Han tzschia csnphioxys
Ciosteriwn sp. Kirchner iella lunaris
Cocconeis SP. Eagerheimia chodati ?
Coelastrum c ’nbricwn Lagerheimia quadniseta ?
Coelastrum microporwfl Lepocinolis sp.
Coelastrwn reticuiatwn Lynghya sp.
Coelastrum reticulatwn Malloinonas sp.
v. polychordon Meloaira dietans
Coelaatrwn sphaer .cwn Melosira granulata
CoeLosphaerw n pallidwn Melosira granulata
Cosmaniwl? clepsydra v. an etiesima
v. nwzwn Melosira vai’ms
Crucigenia apiculata Meridion circuiare
cruciqenia quadrata Merismopedia glauca
crucigenia tetrapedia Meriamopedia minima
Cryptomoflas eroca Merismopedia punctata
CryptoinoflaS erosa Menamopedia tenuissima
v. refle. a Meso8tvgma viridia
Crijptomofla s refiexa Mi cractini urn ? sp.
Cyclotelia meneghini via Microcy8tie aerugiflOsa
Cyc lote 1 La ate 1 ligera Microcyatis incerta
Cyn7atopleura so lea Mougeoti.a sp.
Cymbella cymbiformia zVavicula saZ.inarum
Cymbella turgigula Nitzschia acicuZaria
Dacty L.ococcopeie sp. Ni tzachia fi liformis
Diatorna vulgare Nitzechia tryblionella
Dictyo8phaervwfl pulchellw77 v. debilis
Dinobryon bavaricum Qocystis sp.
Dinobryon divergene Oscillatoria liznnetica
Dinobryon sociale Pandonna mcrwn
12

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Pediastrwn biradiatwn
Pedias trwn biradiaturn
v. longecornutwfl
Pediastrwn duplex
v. reticule ttwn
Pedia.strum simplex
Pediastrwn simplex
v. duoden ’iwn
Pediastrwfl tetrczs
v. tetraodon
Peridiniwn aciculiferwn ?
Peridini urn inconspicuun
Peridiniwn quadridens
Phacus acwninatus
Thacus caudatus
Phacus curvicauda
Phacue longicauda
Phacue megalopsis
Raphidiopais cur vata
Scenedesnnss abundans
Scenedesmus aCWlTflatUB
Scenedesinus arcuatus
Scenedesmus bicaudatus
Scenede8rnue bijuga
Scenedesraus denDicu Zatus
Scenedesmus denticu latus
v. lineci’is
Scenedewnue dirnorphus
Scenedesmus intermedius
Scenedeslnu8 intez’,nedius
v. bicaudatas
ScenedesflTuB quadi’icazi’
Scenedesmus quadricaud.a
v. quadrspna
Schroederia setigera
Ske letonerna pota’nos
Sphaerocystis schroeteri
Staurastrwn sp.
Ste phanodiscua astraea
V. fl?iflUtZa 2
Ste phonodiscus niagarae
Surirella cznguata
Syne4ra acus
S ,’nedra capitata
Synedra de licatis8ufla
Synedra delicati8sima
v. angustiesma
Synedra ulna
Te traedron cons trictw’n
Te traedron graci le
Te traedron limneticum
Tetraedron mininnan
Tetraedron nth2irnwn
v. scrobicuiatwn
Tetraedron rnuticwn
Tetraedron trigonwn
v. grac’ile
Tetraedron trigonwn
v. papilliferwn
Tetrastrwn staurogeniaefoz ne
T’rache 7,ornonaa fiuviati lie
2”rachelornonas hispida
Trache lonionas interrnedia
Trache lomonas jacuiata
Trache lomonas ye ivocina
Treubaria setigerwn
Treu.baria triappendicUlat4
13

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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 ‘,
CHLOROPHYTAN 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 N IIE CLEAR A1ER LAKE
STORE1 tw BEk; 2901
NVGAARO IROPHIC STAlE inDICES
DATE C q 1 ’. 06 18 74 10 C8 74
YXLPHYCEAN 2.30 E 2.60 E 3JtJJ Q
CHL0ROPHYCEA S 2. 0 E 7.00 1 ‘..C0 E
EUGLENQPHYIE £ 3.56 1 1.75 1
DIATUII 0. 0 E 0.44 E 0.25 ?
C0MPOU’ 0 9. 0 E 1b.0 I 12. L
PALNER’S ORGANIC POLLUTION INDICES
DATE 64 9 74 06 18 74 10 08 74
(,EPiUS 05 C2 31
SPECIES 00 60 00
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LAKE NAME: WAPPEP(LLO RU.
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DATE 04 (j9 74 Oo 18 7’. } J Q 74
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CT’L II I II I i II I I
CII II I II I I II I I
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PIL II I II I 1* I A I
CCt S I I S I I. I 21 I I I I
C CL IS I II 2 II S I
LOS. S I S S S C.4I 22 I I I S
CCL II I a II .4I Z $1 1.35 20 5
I 5 1.25 S I j.dt ) I I I
CIL I I I 54$ 9.21 S6 I I I I
CII IS I II I I I I 1 5
CU S I 2.21 S I S S I I I
CIL I I S I I 1.01 90 S S I I
( IL II S Ii I II I I I
CII II S X II I u I
II I IS I I I I
CII I I I I I I I I 2.51 119 5
II S I I II S I
CIL II I I I Z SI S I
CII II I II I II I I
(IL I S I I I I S 131 5.1 I 239 5
CII I S I I I 0.45 22 I I I I
29
4044

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