United States
Environmental Protection
Agency
Environmental Monitoring
and Support Laboratory
P.O. Box 15027
Las Vegas NV 89114
oEPA
Distribution of
Phytoplankton in
Kansas Lakes
Working
Paper 697
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DISTRIBUTION OF PHYTOPLANKTON IN KANSAS LAKES
by
L. R. Williams, S. C. Hern, V. W. Lambou,
F. A. Morris*, M. K. Morris*, and W. D. Taylor
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. 697
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.
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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.
iii
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CONTENTS
Foreword iii
Introduction 1
Materials and Methods 3
Lake and Site Selection 3
Sample Preparation 3
Examination 4
Quality Control 5
Results •. 6
Nygaard's Trophic State Indices 6
Palmer's Organic Pollution Indices 6
Species Diversity and Abundance Indices 8
Species Occurrence and Abundance 10
Literature Cited 11
Appendix A. Phytoplankton Species list for the State
of Kansas 12
Appendix B. Summary of Phytoplankton Data 15
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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
15 lakes sampled in the State of Kansas (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 KANSAS
STORET No.
Lake Name
County
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
Cedar Bluff Reservoir
Council Grove
Elk City
Fall River Reservoir
John Redmond Reservoir
Kanopolis Reservoir
Marion Reservoir
Melvern Reservoir
Mil ford Reservoir
Norton Reservoir
Perry Reservoir
Trego
Morri s
Montgomery
Greenwood
Coffey
Ellsworth
Marion
Osage
Clay, Geary, Riley
Norton
Jefferson
(Continued)
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TABLE 1. LAKES SAMPLED IN THE STATE OF KANSAS (Continued)
STORET No. Lake Name County
2012 Pomona Reservoir Osage
2013 Toronto Reservoir Greenwood, Woodson
2014 Tuttle Creek Reservoir Marshall, Riley, Pottawatomie
2015 Wilson Reservoir Russell, Lincoln
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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
1imited 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 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.
SAMPLE PREPARATION
To preserve the sample 4 milliliters (ml) of Acid-LugoTs solution
(Prescott 1970) were added to each 130-ml 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
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were mixed to form two 130-ml 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 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 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.
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 essential to accurately
identify the diatoms, a phase-contrast microscope was used.
After the species list was compiled, phytoplankton were enumerated using
a Neubauer Counting Chamber with a 40X objective lens and a 10X 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.
®Registered trademark
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QUALITY CONTROL
Project phycologists performed internal quality control intercomparisons
regularly on 7 percent of the species identification and counts. Although ctn
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
satisfactory.
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RESULTS
A phytoplankton species list for the 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 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
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TABLE 2. NYGAARD'S TROPHIC STATE INDICES ADAPTED FROM HUTCHINSON (1967)
Index
Calculation
Oligotropnic Eutropnic
Myxophycean
Chlorophycean
Diatom
Euglenophyte
Compound
Myxophyceae
Desmideae
Chlorococcales
Desmideae
Centric Diatoms
Pennate Diatoms
Euglenophyta
ytc
ilot
Myxophyceae + Chlorococcales
Myxophyceae + Chlorococcales +
Centric Diatoms + Euglenophyta
Desmideae
0.0-0.4
0.0-0.7
0.0-0.3
0.0-0.2
0.0-1.0
0.1-3.0
0.2-9.0
0.0-1.75
0.0-1.0
1.2-25
TABLE 3. ALGAL GENUS POLLUTION INDEX
(Palmer 1969)
TABLE 4. ALGAL SPECIES POLLUTION
INDEX (Palmer 1969)
Genus
Anacystis
Ankistrodesmus
Chlamydomonas
Chi orel la
Closterium
Cyclotella
Euglena
Gomphonema
Lepocinclis
Melosira
Micractinium
Navicula
Nitzschia
Oscillatoria
Pandorina
Phacus
Phormidium
Scenedesmus
Stigeoclonium
Synedra
Pollution
Index
1
2
4
3
1
1
5
1
1
1
1
3
3
5
1
2
1
4
2
2
Species
Ankistrodesmus falcatus
Arthrospira jenneri
Chlorella vulgaris
Cyclotella meneghiniana
Euglena gracilis
Euglena viridis
Gomphonema parvulum
Melosira varians
Navicula cryptoce^hala
Nitzschia acicularis
Nitzschia palea
Oscillatoria chlorina
Oscillatoria limosa
Oscillatoria princeps
Oscillatoria putrida
Oscillatoria tenuis
Pandorina morum
Scenedesmus quadricauda
Stigeoclonium tenue
Synedra ulna
Pollution
Index
3
2
2
2
1
6
1
2
1
1
5
2
4
1
1
4
3
4
3
3
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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.
s
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):
PI logx P.
1-1
where P is the proportion of the ith taxon in the sample, which is calculated
from n-j/N; n-j 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 sl-ightly 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.
8
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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 were 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 Iog2 S
(Pielou 1966), while the minimum diversity (MinH), was estimated from the
formula:
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 a H-MinH
MaxH-MinH
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 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
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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 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 dominant taxa in a sample, based
upon relative size and concentration of the organism. The percent column (%C)
presents, by abundance, the percentage composition of each taxon.
10
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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. 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. D. 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, 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.
11
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APPENDIX A
PHYTOPLANKTON SPECIES FOR THE STATE OF KANSAS
12
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Actinastrum gracilimum
Andbaena sp.
Andbaenopsis sp.
Ankistrodesmus falcatus
Ankistrodesmus falcatus
v. acicularis
Ankistrodesmus falcatus
v. mirabilis
Aphanizomenon flos-aquae
Asterionella formosa
Asterionella formosa
v. gracillima
Botryococcus sudeticus
Carteria klebsii
Ceratium hirundinella
f. brachyceras
Ceratium hirundinella
f. fi&Qoides
Cerat-^um h-irundinella
f. scott-icwn
Characium limneticwn
Charaoium naegelii ?
Chlamydomonas globosa
Chlorogonium sp.
Ckroomonas aouta
Closteriopsis sp.
Closterium sp.
Cooooneis pedieulus ?
Coelastrum cambriaim
v. intevmedum
Coelastnan microponon
Coelastrwn reticulation
Coelastrum reticulatum
v..polychordon
Coelosphaeriwn naegelianum
Cosma^-uan granatwn
Cvucigenia apiculata
Crucigenia fenestrata
Crucigenia quadrata
Crucigenia tetrapedia
Cryptomonas evosa.
Cryptomonas evosa
v. reflexa
Cryptomonas marssonii
Cryptomonas reflexa
Cyclotella meneghiniana
Cyclotella michiganiana ?
Cyclotella stelligera
Cymatopleura solea
Cymbella affinis
Dactylococcopsis aciculavis
Dactylococcopsis irregularis
Diatoma vulgare
Dictyosphaerium pulchellum
Dinobryon divergens
Dinobryon sertularia
Dinobryon sociale
Diploneis smithii
v. pumila
Diplopsalis acuta
Elakatothrix gelatinosa
Entomone-is alata
Euastrum sp.
Eudorina sp.
Euglena acus
Euglena efoeribergii
Euglena gracilis
Euglena oxyuris
Euglena oayuris
v. minor
Euglena tripteris
Fragilaria crotonensis
Fragilaria intermedia
Glenodinium edax
Glenodinium oculatum
Gloeocystis sp.
Golenkinia sp.
Gomphonema gracile
Gomphonema olivaceum
Gymnodinium albulum
Gymnodinium ordinatum
Gyrosigma sp.
Hantzschia amphioxys
Kirchneriella contorta
Lagerheimia sp.
Lepocinclis sp.
Lyngbya sp.
Mzllomonas sp.
Melosira distans
Melosira granulata
Melosira granulata
v. angustissima
Melosira granulata
v. angustissima f. spiralis
Melosira italica
Melosira italica
v. tenuissima
Melosira varians
Merismopedia minima
Merismopedia punctata
Merismopedia tenuissima
Mesostigma viridis
13
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Mioraotinium pusillum
Miarooystis aeruginosa
Miarooystis inoerta
Naviaula aryptooephala ?
Navioula cuspidata
Navioula heufieri
Navioula salinarium
v. intermedia
Nephroaytium sp.
Nitzsahia aoioularis
Nitzsohia apiculata ?
Nitzsahia dissipata
Nitzsahia holsatioa
Nitzsohia hungarioa
Nitzsohia longissima
v. reversa
Nitzsahia sigmoidea
Nitzsohia tryblionella
Nitzsohia tryblionella
v. debilis ?
Nitzsahia vermicularis
Oooystis sp.
Osaillatoria agardhii
Oscillatoria lirmetica
Pandofina morum
Pediastrwn bovyanum
Pediastman duplex
v. alathratim
Pediastrum duplex
v. retiaulatum
Pediastrum simplex
v. duodenarium
Pediastrum tetras
Pediastrim tetras
v. tetvaodon
Pevidinium quadpidens
Phaaus acuminatus
Phaous oaudatus
Phaaus helikoides
Phaaus longioauda
Phaous megalopsis
Phaous orbicularis
Phaaus pseudonordstedtii
Phormidium sp.
Pinnularia sp.
Pteromonas angulosa
Scenedesmus abundans
Saenedesmus aauminatus
Soenedesmus arouatus
Soenedesmus balatonious
Soenedesmus bijuga
Soenedesmus dentioulatus
Soenedesmus dimorphus
Soenedesmus intevmedius
Saenedesmus intermedius
v. bioaudatus
Soenedesmus opoliensis
Soenedesmus quadrioauda
Soenedesmus quadriaauda
v. longispina
Schvoederia setigera
Skeletonema potamos
Sphaerocystis schroeteri
Staurastrum tetracerum
Stephanodisous astraea
v. minutula
Stephanodisous hantzsohia
Stephanodisous invistatus
Stephanodiscus tenuis
Surirella angusta
Surirella linearis
v. helvetica ?
Surivella ovata
•Synedra aous
Synedra minusoula
Synedra vumpens
Synedva ulna
Tetraedron minium
Tetraedron minium
v. sorobioulatum
Tetraedron mutioum
Tetrastrum elegans
Tetrastrum glabrum
Tetrastmm staurogeniaeforme
Traohelomonas australiaa
Traohelomonas bulla
Trachelomonas fluviatilis
Trachelomonas gibbevosa
Tvachelomonas girardiana
Trachelomonas hispida
Traohelomonas -intermedia
Traahelomonas oblonga
Traohelomonas soabra
Traohelomonas schauinslandii
Traahelomonas verruoosa
Traohelomonas volvooina
14
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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.
15
-------
LAKE NAME! CEDAR BLUFF RES.
STGRET NUrtBEfi: 2001
NYGAAKO TROPHIC STATE INDICES
&AH 04 14 74 06 26 74 lo 01 74
MYXCiPHYCE AN
CHLOfcOPHYCtAN
EUGlENOPHYTE
DIATOM
COMPOUND
0/03 0
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C/06 ?
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1.00 E
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C.33 £
0.75 E
11.0 I
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0.67 t
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PAlflEK'S ORGANIC POLLUTION iNLICtS
DATE 0* 1*. Tt 06 26 74 10 01 7^
GENUS
SPECIES
03
00
00
00
05
JC
SPECIES 01VEHS1TY AND ABUNDANCE INDICES
AVERAGE DIVERSITY
NUMBER UF TAXA
NUMBER OF SAMPLES COMPUSITED
MAXIMUM DIVERSITY
HlNCflUH DIVERSITY
TOTAL DIVERSITY
. TOTAL NUKBER CF 1NOIV10UALS/M
EVENESS COMPONENT
RELAI1VE EVENESS
MEAN NUMBER iif INC1V1C.UALS/IAXA
NUMBER/ML OF MOST AbUNOANT TAXON
DATE
H
S
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D
N
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-------
LAKE NAfll: COUNCIL GROVE
STOkEI NUMBER:
NYGAARC TROPHIC STATE INI/ICES
DATE 04 11 74 06 25 74 10 C2 74
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18
-------
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LAKE NArtl : ftlVE'Rh RES.
STORE! NUMBER: 2006
DATE
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LAKE NAflt : Pt»RY f.
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-------
lAKfc NAME: POMONA RES.
STORET NUMBER: 2012
NYGAARO TROPHIC STATE INDICES
DATE 04 H 7* 06 25 74 10 01 74
MYXOPHYCEAN
CHLOROPHYCEAN
EUGLENOPHYTE
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DATE 04 11 74 06 25 74 10 01 74
GENUS
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03
03
06
CO
01
JO
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DATE
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NUMBER OF TAXA s
NUMBER OF SAMPLES COMPOSITED M
MAXIMUM DIVERSITY MAXH
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TOTAL DIVERSITY D
TOTAL NUMBER CF IN01VIDUALS/Ml N
EVENESS COMPONENT J
RELATIVE EVENESS RJ
MEAN NUMBER OF INOIVIDUALS/TAXA L
NUMBEK/RL 3F MOST ABUNDANT TAXON K
04 11 74 06 25 74 10 01 74
1.95
U.OO
3.00
3.56
0.05
5912.40
3032.00
0.54
C.54
252.67
1663.CO
1.72
15.00
3.00
3.91
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6640.92
3861.00
0.44
0.44
257.40
2119.00
1.84
17.00
3. 00
4.09
0.39
761.76
414.00
0.45
0.40
24.35
184.00
38
-------
IAM *
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39
-------
LAKE NAME: TORONTO KES,
STORET NUMBER: 2013
NYGAARO TROPHIC STATE INDICES
DATE 0* 10 74 06 24 74 10 C2 74
MYXOPHYCEAN
CHLGROPHYCEAN
tUGLENOPHYTE
DIATOM
COMPOUND
0/0 0
02/0 E
1.00 E
0.50 E
07/0 E
1.00 E
I.JO E
2.00 E
1.00 E
9.00 E
3.00 E
3.00 E
0.50 E
1.25 E
14.0 E
PALHER«S ORGANIC POLLUTION INDICES
DATE 04 10 74 06 24 74 10 02 74
GENUS
SPECIES
03
03
01
00
01
00
SPECIES DIVERSITY AND ABUNDANCE INDICES
DATE
AVERAGE DIVERSITY
NUMBER OF TAXA
NUMBER OF SAMPLES COMPOSITED
MAXIMUM DIVERSITY HAXH
HlNUHliM DIVERSITY HINH
TOTAL DIVERSITY
TOTAL NUMBER OF INDIVIOUAlS/ML
EVENESS COMPONENT
RELATIVE EVENESS
MEAN NUMBER OF INOIV1DUALS/TAXA
NUMBER/ML OF MOST ABUNDANT TAXON
04 10 74 06 24 74 10 02 74
H
S
M
XH
NH
D
N
J
RJ
L
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1.73
17.00
2.00
4.09
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6402.73
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0.42
0.42
217.71
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1.76
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4.09
0.26
1195. 04
679.00
0.43
3.40
39.94
255.00
3.01
23.00
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4.52
0.45
1547.14
514.00
0.67
0.63
22.35
103.00
40
-------
I ant runt : TOBUNTU RtS.
SJOKfl nunetR: 2013
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LAKE NAME: TUTHE CREEK RES.
STORET NUMBER: 2U14
NYGAARO TROPHIC STATE INDICES
DATE C4 11 74 06 25 74 10 C2 74
MYXOPHYCEAN
CHLCfcOPHYCEAN
EUGtENQPHYTE
DIATOM
COMPOUND
Cl/0 E
04/0 E
0.40 E
0.29 ?
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1.00 E
02/0 E
06/0 E
02/0 E
09/0 E
0.09 ?
1.17 E
19/0 E
PALMER'S ORGANIC POLLUTION INDICES
DATE 0* 11 7* 06 25 74 10 02 74
GENUS
SPECIES
09
03
01
cc
03
00
SPECIES DIVERSITY AND ABUNDANCE INDICES
DATE
AVERAGE DIVERSITY
NUMBER OF TAXA
NUMBER OF SAMPLES COMPOSITED
MAXIMUM DIVERSITY MAXH
MINUMUH DIVERSITY MINH
TOTAL DIVERSITY
TOTAL NUMBER OF INOIV 10UALS/ML
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RELATIVE EVENESS
MEAN NUMBER OF 1ND1VIDUALS/TAXA
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04 11 7* 06 25 74 10 02 74
H
s
M
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NH
D
N
J
RJ
L
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0.95
22.00
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4.46
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1304C.65
13727.00
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623.95
10947.00
0.95
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3.17
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1935.15
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0.30
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226.33
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4.91
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3820.00
0.44
0.43
127.33
1641.00
42
-------
IAKE N1HE: IUITIE CREt*
201*
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-------
LAKE NAME: WILSON RES.
STORET NUMBER: 2015
NY6AARO TROPHIC STATE INDICES
DATE 04 12 74 06 26 74 10 01 74
NYXOPHYCEAN 3.00 t 0/0 0 1.00 E
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PALMER'S ORGANIC POLLUTION INDICES
DATE 04 12 74 06 26 74 10 01 74
GENUS
SPECIES
09
03
CO
CO
07
00
SPECIES DIVERSITY AND ABUNDANCE INDICES
DATE 04 12 74 06 26 74 10 01 74
AVERAGE DIVERSITY
NUMBER OF TAXA
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MINUMUM DIVERSITY M1NH
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H
S
K
XH
NH
D
N
J
RJ
L
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2.75
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3.00
4.81
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0.57
3i7.93
3438.00
1.32
12.00
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3.58
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1103.52
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0.37
0.35
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3.00
4.81
0.08
11476.08
4554.00
0.52
0.52
162.64
1847.00
44
-------
IAKE NAME! .JISOM DCS.
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